PK=UbG+]NONOrefs.MYD|?:Rankinen, K. Gao, G. Granlund, K. Gronroos, J. Vesikko, L.2015}Comparison of impacts of human activities and climate change on water quantity and quality in Finnish agricultural catchments415-428Landscape Ecology303Mar~We studied the influence of human activities and climate change on water quantity and quality. Human activities included methods of agricultural policy, i.e. land use and management practices. Finland started to follow EU's agricultural policy in 1995. In this study our main objective was to find out whether the original targets of the Finnish Agri-Environmental Programme (FAEP) were achieved. We analyzed trends in discharge, water quality and climate parameters in 37 years long time-series in two catchments. We focused on the suspended sediment and phosphorus concentrations and loads, the main interests to FAEP. We found an increasing trend in mean annual temperature, especially in spring and late summer-early autumn. There was no statistical significant change in annual runoff. Increasing winter runoff in the other catchment could be explained by the increased number of days when temperature was above zero degrees making snowmelt possible. In this area high potential sediment delivery occurred in early winter. FAEP succeeded in decreasing the suspended sediment load by reduced tillage and wintertime vegetation cover. In controlling the phosphorus loads FAEP succeeded only in the catchment with erosion sensitive soils. In the catchment where soils were less sensitive for erosion increase in the dissolved reactive phosphorus load exceeded the benefits of the reduced particulate phosphorus load. Climate change may increase the suspended sediment load by increasing winter runoff. Even then, instead of decreasing the suspended sediment loads FAEP should rather focus on dissolved nutrients as they cause eutrophication in receiving waters.!://WOS:000350227000004Times Cited: 1 0921-2973WOS:00035022700000410.1007/s10980-014-0149-1|?mLu, Nan Akujarvi, Anu Wu, Xing Liski, Jari Wen, Zhongming Holmberg, Maria Feng, Xiaoming Zeng, Yuan Fu, Bojie2015Changes in soil carbon stock predicted by a process-based soil carbon model (Yasso07) in the Yanhe watershed of the Loess Plateau399-413Landscape Ecology303MariSoil carbon sequestration is an ecosystem process that can provide important ecosystem services such as climate regulation and mitigation of global warming. Spatiotemporal variation in the soil organic carbon (SOC) stock is the basic information needed for landscape management and determination of regional carbon budgets. The objective of this study was to evaluate the effect of ecological restoration on SOC stocks and determine the influences of multiple factors in the Yanhe watershed of the Loess Plateau. We coupled the Yasso07 soil carbon model with remote sensing indices as model input. The model performance was evaluated by uncertainty and sensitivity analyses as well as validation against field measurement. The modeling captured the spatial pattern of SOC variability across the landscape generally well. Net primary productivity (NPP) was the foremost factor that affecting the spatiotemporal variation of SOC density. Converting cropland to grassland was the most efficient restoration type in soil carbon sequestration in the study period. Land use change influenced the spatial correlation between NPP and SOC density by altering both litter quantity and quality. The changes in land use area tended to have higher contributions to the changes in SOC stock than did the changes in SOC density for different land use types. The overall effect of ecological restoration on soil carbon sequestration was dependent on the main vegetation restoration type and the time of recovery. Human-derived land use changes could have more substantial effects on soil carbon budgets compared to natural factors in a short period of time.!://WOS:000350227000003Times Cited: 1 0921-2973WOS:00035022700000310.1007/s10980-014-0132-x8|?Fu, Bojie Forsius, Martin20155Ecosystem services modeling in contrasting landscapes375-379Landscape Ecology303Mar/Landscape ecology can make a large contribution to ecosystem service (ES) studies since most ESs are place-based, and thus best evaluated, maintained, enhanced, and restored using integrative techniques at the landscape scale. Integration of field observation, modeling, and remote sensing are increasingly used to quantify and assess ES at different scales. In this special issue, several comprehensive methodologies and tools are described in the thirteen papers included. The papers are grouped into four categories: modelling and evaluation of carbon and water services of ecosystems, comprehensive analysis and assessment of multiple ESs, integrated ES methodologies for conservation, and development of integrated modeling environments for ESs. We believe that these papers provide both useful methods and tools to simulate and evaluate ESs at different spatial and temporal scales, as well as interesting results from case studies. We also hope that they can provide information for policy makers and managers regarding wiser landscape management and conservation.!://WOS:000350227000001Times Cited: 0 0921-2973WOS:00035022700000110.1007/s10980-015-0176-6}|?pWu, Xing Akujarvi, Anu Lu, Nan Liski, Jari Liu, Guohua Wang, Yafeng Holmberg, Maria Li, Fei Zeng, Yuan Fu, Bojie2015Dynamics of soil organic carbon stock in a typical catchment of the Loess Plateau: comparison of model simulations with measurements381-397Landscape Ecology303MarLand use changes are known to significantly affect the soil C balance by altering both C inputs and losses. Since the late 1990s, a large area of the Loess Plateau has undergone intensive land use changes during several ecological restoration projects to control soil erosion and combat land degradation, especially in the Grain for Green project. By using remote sensing techniques and the Yasso07 model, we simulated the dynamics of soil organic carbon (SOC) stocks in the Yangjuangou catchment of the Loess Plateau. The performance of the model was evaluated by comparing the simulated results with the intensive field measurements in 2006 and 2011 throughout the catchment. SOC stocks and NPP values of all land use types had generally increased during our study period. The average SOC sequestration rate in the upper 30 cm soil from 2006 to 2011 in the Yangjuangou catchment was approximately 44 g C m(-2) yr(-1), which was comparable to other studies in the Loess Plateau. Forest and grassland showed a more effective accumulation of SOC than the other land use types in our study area. The Yasso07 model performed reasonably well in predicting the overall dynamics of SOC stock for different land use change types at both the site and catchment scales. The assessment of the model performance indicated that the combination of Yasso07 model and remote sensing data could be used for simulating the effect of land use changes on SOC stock at catchment scale in the Loess Plateau.!://WOS:000350227000002Times Cited: 2 0921-2973WOS:00035022700000210.1007/s10980-014-0110-3c|??Shanahan, D. F. Lin, B. B. Gaston, K. J. Bush, R. Fuller, R. A.2015lWhat is the role of trees and remnant vegetation in attracting people to urban parks? (vol 30, pg 153, 2015)761-762Landscape Ecology304Apr!://WOS:000350360100014Times Cited: 0 0921-2973WOS:00035036010001410.1007/s10980-015-0162-z|?Byrd, Kristin B. Flint, Lorraine E. Alvarez, Pelayo Casey, Clyde F. Sleeter, Benjamin M. Soulard, Christopher E. Flint, Alan L. Sohl, Terry L.2015Integrated climate and land use change scenarios for California rangeland ecosystem services: wildlife habitat, soil carbon, and water supply (vol 30, pg 729, 2015)751-751Landscape Ecology304Apr!://WOS:000350360100013Times Cited: 0 0921-2973WOS:00035036010001310.1007/s10980-015-0180-x |?Byrd, Kristin B. Flint, Lorraine E. Alvarez, Pelayo Casey, Clyde F. Sleeter, Benjamin M. Soulard, Christopher E. Flint, Alan L. Sohl, Terry L.2015Integrated climate and land use change scenarios for California rangeland ecosystem services: wildlife habitat, soil carbon, and water supply729-750Landscape Ecology304AprContext In addition to biodiversity conservation, California rangelands generate multiple ecosystem services including livestock production, drinking and irrigation water, and carbon sequestration. California rangeland ecosystems have experienced substantial conversion to residential land use and more intensive agriculture. Objectives To understand the potential impacts to rangeland ecosystem services, we developed six spatially explicit (250 m) climate/land use change scenarios for the Central Valley of California and surrounding foothills consistent with three Intergovernmental Panel on Climate Change emission scenario narratives. Methods We quantified baseline and projected change in wildlife habitat, soil organic carbon (SOC), and water supply (recharge and runoff). For six case study watersheds we quantified the interactions of future development and changing climate on recharge, runoff and streamflow, and precipitation thresholds where dominant watershed hydrological processes shift through analysis of covariance. Results The scenarios show that across the region, habitat loss is expected to occur predominantly in grasslands, primarily due to future development (up to a 37 % decline by 2100), however habitat loss in priority conservation errors will likely be due to cropland and hay/pasture expansion (up to 40 % by 2100). Grasslands in the region contain approximately 100 teragrams SOC in the top 20 cm, and up to 39% of this SOC is subject to conversion by 2100. In dryer periods recharge processes typically dominate runoff. Future development lowers the precipitation value at which recharge processes dominate runoff, and combined with periods of drought, reduces the opportunity for recharge, especially on deep soils. Conclusion Results support the need for climate-smart land use planning that takes recharge areas into account, which will provide opportunities for water storage in dry years. Given projections for agriculture, more modeling is needed on feedbacks between agricultural expansion on rangelands and water supply.!://WOS:000350360100012Times Cited: 1 0921-2973WOS:00035036010001210.1007/s10980-015-0159-7|?@Bruton, Melissa J. Maron, Martine Levin, Noam McAlpine, Clive A.2015Testing the relevance of binary, mosaic and continuous landscape conceptualisations to reptiles in regenerating dryland landscapes715-728Landscape Ecology304AprContext Fauna distributions are assessed using discrete (binary and mosaic) or continuous conceptualisations of the landscape. The value of the information derived from these analyses depends on the relevance of the landscape representation (or model) used to the landscape and fauna of interest. Discrete representations dominate analyses of landscape context in disturbed and regenerating landscapes; however within-patch variation suggests that continuous representations may help explain the distribution of fauna in such landscapes. Objectives Wetested the relevance of binary, mosaic, and continuous conceptualisations of landscape context to reptiles in regenerating dryland landscapes. Methods For each of thirteen reptile groups, we compared the fit of models consisting of one landscape composition and one landscape heterogeneity variable for each of six landscape representations (29 binary, 29 mosaic, and 29 continuous), at three buffer distances. We used Akaike weights to assess the relative support for each model. Maps were created from Landsat satellite images. Results Reptiles varied in their response to landscape context; however, the binary landscape representation with classes 'intact/disturbed' was best supported overall. Species richness was best described by a binary landscape representation with classes 'wooded/clear', whereas reptile abundance was best described by a mosaic landscape representation with classes defined by vegetation type. Five out of ten reptile species responded strongly to a single landscape representation, with the most relevant representation and conceptualisation varying among species. Conclusions Our findings support the use of multiple landscape conceptualisations and representations during analyses of landscape context for fauna in regenerating landscapes.!://WOS:000350360100011Times Cited: 0 0921-2973WOS:00035036010001110.1007/s10980-015-0157-9 |?6Lechner, Alex Mark Brown, Greg Raymond, Christopher M.2015Modeling the impact of future development and public conservation orientation on landscape connectivity for conservation planning699-713Landscape Ecology304AprContext Recent papers on the spatial assessment of conservation opportunity have focused on how social values for conservation may change modeled conservation outcomes. Accounting for social factors is important for regional wildlife corridor initiatives as they often emphasize the collaborative aspects of conservation planning. Objectives We present an approach for characterizing the potential effects of public conservation orientation and projected future development land use scenarios on landscape connectivity. Methods Using public participation GIS techniques (mail-based surveys linked to a mapping component), we classified spatially explicit conservation values and preferences into a conservation orientation index consisting of positive, negative, or neutral scores. Connectivity was then modeled using a least-cost path and graph-network approach for a range of conservation orientation and development scenarios in the Lower Hunter region, Australia. Scenarios were modelled through either adding vegetation (positive orientation) or removing vegetation (negative orientation, development). Results Scenarios that included positive conservation orientation link the isolated eastern and western reaches of the Lower Hunter, even when negative conservation scores were included in the model. This outcome is consistent with proposed connectivity corridors identified in regional strategies. The development scenario showed connectivity patterns similar to only modelling negative conservation orientation scores, with greater fragmentation across the region. Conclusions The modeled outcomes showed consistency between the public's conservation orientation and the ecological rationale for increasing connectivity within the region. If conservation orientation can be translated into conservation initiatives, the result will be enhanced regional landscape connectivity that is both ecologically beneficial, as well as socially acceptable.!://WOS:000350360100010Times Cited: 0 0921-2973WOS:00035036010001010.1007/s10980-015-0153-0'|?(Baltensperger, Andrew P. Huettmann, Falk2015Predictive spatial niche and biodiversity hotspot models for small mammal communities in Alaska: applying machine-learning to conservation planning681-697Landscape Ecology304AprContext Changing global environmental conditions, especially at northern latitudes, are threatening to shift species distributions and alter wildlife communities. Objective We aimed to establish current distributions and community arrangements of small mammals to provide important baselines for monitoring and conserving biodiversity into the future. Methods We used 4,408 archived museum and open-access records and the machine learning algorithm, RandomForests, to create high-resolution spatial niche models for 17 species of rodents and shrews in Alaska. Models were validated using independent trapping results from 20 locations stratified along statewide mega-transects, and an average species richness curve was calculated for field samples. Community cluster analyses (varclus) identified geographic patterns of sympatry among species. Species models were summed to create the first small-mammal species richness map for Alaska. Results Species richness increased logarithmically to a mean of 3.3 species per location over 1,500 trapnights. Distribution models yielded mean accuracies of 71 % (45-90 %), and maps correctly predicted a mean of 75 % (60-95 %) of occurrences correctly in the field. Top predictors included Soil Type, Eco-region, Landfire Land-cover, December Sea Ice, and July Temperature at the geographic scale. Cluster analysis delineated five community groups (3-4 species/group), and species richness was highest (11-13 species) over the Yukon-Tanana Uplands. Conclusions Models presented here provide spatial predictions of current small mammal biodiversity in Alaska and an initial framework for mapping and monitoring wildlife distributions across broad landscapes into the future.!://WOS:000350360100009Times Cited: 0 0921-2973WOS:00035036010000910.1007/s10980-014-0150-8a|?SCampbell, Rebecca E. Winterbourn, Michael J. Cochrane, Thomas A. McIntosh, Angus R.2015YFlow-related disturbance creates a gradient of metacommunity types within stream networks667-680Landscape Ecology304AprContext Metacommunities are sets of local communities linked by dispersal. Their characteristics are defined by both large-scale spatial processes such as dispersal, and local environmental processes, although which factors are likely to predominate in a given situation is poorly understood. Objectives We investigated whether flow regime at the network-scale helped explain the relative importance of spatial and local-environmental processes in structuring stream metacommunities. Methods Spatial sampling of stream macroinvertebrates was carried out in stream networks in New Zealand. Local environmental variables were also measured throughout the stream networks, while hydrographs were modelled and calibrated with field measurements. Results Significant associations with both spatial and local-environmental predictor variables were found, consistent with several metacommunity types. In particular, two measures of flow regime were associated with different metacommunity types. Thus, stream networks characterised by a period of stability just before sampling, and networks sampled after a long period of instability, had more significant spatial structuring of metacommunities than those of intermediate flow stability. The importance of spatial processes in structuring the network metacommunities also increased with time since the last community-resetting flow. Our results therefore suggested that metacommunity type depended on the flow regime. Dispersal traits and network topology also helped explain some of the variation among the metacommunities. Conclusions Overall, our findings conform to theoretical predictions related to dispersal limitation and topology, and indicate that metacommunity models need to be dynamic to capture processes in both space and time.!://WOS:000350360100008Times Cited: 0 0921-2973WOS:00035036010000810.1007/s10980-015-0164-x |?Baker, William L.2015iHistorical Northern spotted owl habitat and old-growth dry forests maintained by mixed-severity wildfires655-666Landscape Ecology304AprContext Reconstructing historical habitat could help reverse declining animal populations, but detailed, spatially comprehensive data are rare. For example, habitat for the federally threatened Northern spotted owl (NSO; Strix occidentalis caurina) was thought historically rare because low-severity fires kept forests open and habitat restricted to fire refugia, but spatial historical data are lacking. Objectives Here I use public land-surveys to spatially reconstruct NSO habitat and old-growth forests in dry forests in Oregon's Eastern Cascades in the late-1800s. I used reconstructions of forest structure across about 280,000 ha, including 9,605 tree records and 2,180 section-line descriptions. I was able to reconstruct likely NSO nest trees, nest stands, and foraging and roosting habitat, based on modern NSO habitat studies. Results Historical nest stands, including sufficient nest trees, were predicted across 22-39 % and foraging and roosting habitat across 11-68 % of the study area, thus neither were rare. More habitat than expected occurred in forests with preceding mixed-severity fires. Early post-fire succession produced foraging and roosting habitat. Mid-to late-succession produced nesting habitat. Late-succession after high-severity fires can also provide NSO habitat. Old-growth forests, covering 76 % of study-area forests, also likely link to preceding mixed-severity fires. Conclusions Mixed-and high-severity fires strongly shaped historical dry forests and produced important components of historical NSO habitat. Focus on short-term loss of nest sites and territories to these fires is mis-directed. Fuel treatments to reduce these natural fires, if successful, would reduce future habitat of the NSO in dry forests.!://WOS:000350360100007Times Cited: 0 0921-2973WOS:00035036010000710.1007/s10980-014-0144-6|?,Clarke, Lorraine Weller Jenerette, G. Darrel2015`Biodiversity and direct ecosystem service regulation in the community gardens of Los Angeles, CA637-653Landscape Ecology304Apr>Context Urban community gardens are globally prevalent urban agricultural areas and have the potential to fulfill human needs in impoverished neighborhoods, such as food security and access to open space. Despite these benefits, little research has been conducted evaluating environmental and socioeconomic factors influencing community garden plant biodiversity and ecosystem services (ES). Objective Our study investigated the drivers of managed plant richness, abundance, and ES production in community gardens across Los Angeles County, CA from 2010 to 2012 at regional, garden, and plot scales. Methods Fourteen community gardens were visited in the summers of 2010-2012 for comprehensive species surveys across regional, garden, and plot scales. We compared biodiversity to household income, plot size, and gardener ethnicity. Results In total, 707 managed plant species were recorded in summer surveys over a 3-year period. Ornamental plant richness increased with neighborhood income, while edible and medicinal richness increased with size of garden plots. Gardener ethnicity also influenced the composition of managed species, especially edible species. Conclusions We explain these patterns through a hierarchy of needs framework; gardeners preferentially plant species progressively less connected to human need. Ornamental plant increases in high-income regions may be explained by their requirement for financial investment and maintenance time. Cultural and provisioning ES are important for immigrant populations, resulting in ethnically distinct crop assemblages. Finally, distinct species-area relationships imply high demand for food abundance and biodiversity. Our quantitative results indicate that community gardens contribute to a biologically diverse urban ecosystem and provide valued ecosystem services in food insecure regions.!://WOS:000350360100006Times Cited: 0 0921-2973WOS:00035036010000610.1007/s10980-014-0143-7|?iLoos, Jacqueline Kuussaari, Mikko Ekroos, Johan Hanspach, Jan Fust, Pascal Jackson, Laurie Fischer, Joern2015bChanges in butterfly movements along a gradient of land use in farmlands of Transylvania (Romania)625-635Landscape Ecology304Apr Context Agricultural transformation and increased land use intensity often lead to simplified landscapes and biodiversity loss. For animals, one possible mechanism underpinning biodiversity loss in agricultural landscapes is the disruption of movements. The disruption of movements may explain, for example, why butterfly communities in agricultural landscapes are often dominated by generalist species with high mobility. Objectives Here, we investigated how the movement patterns of butterflies characterised by different levels of mobility changed along a gradient of agricultural land use intensity. Methods To this end, we studied 15 landscapes in low-intensity farmland in Central Romania, measuring 10 ha each and covering a gradient of landscape heterogeneity and woody vegetation cover. In these landscapes, we tracked movements of 563 individuals of nine butterfly species. Results Our findings showed that overall movement activities differed significantly between species, corresponding well with expert-derived estimates of species-specific mobility. Interestingly, species of low and high mobility responded in opposite ways to increasing levels of landscape heterogeneity. In relatively simple landscapes, the movement patterns of low and high mobility species were similar. By contrast, in complex landscapes, the flight paths of low-mobility species became shorter and more erratic, whereas the flight paths of high-mobility species became longer and straighter. An analysis of the land covers traversed showed that most species avoided arable land but favoured the more heterogeneous parts of a given landscape. Conclusions In combination, our results suggest that non-arable patches in agricultural landscapes are important for butterfly movements, especially for low-mobility species.!://WOS:000350360100005Times Cited: 0 0921-2973WOS:00035036010000510.1007/s10980-014-0141-9#|?nMullins, Jacinta Ascensao, Fernando Simoes, Luciana Andrade, Leonardo Santos-Reis, Margarida Fernandes, Carlos2015Evaluating connectivity between Natura 2000 sites within the montado agroforestry system: a case study using landscape genetics of the wood mouse (Apodemus sylvaticus)609-623Landscape Ecology304AprSContext The Natura 2000 network is the centerpiece of European nature conservation policy but its effectiveness is challenged by ongoing landscape change. Objective Our objective was to assess landscape connectivity between Natura 2000 sites in the biodiversity-rich western Mediterranean region. Methods We used the wood mouse as a focal species with short-range dispersal and obtained genetic data for 393 individuals uniformly distributed between two Natura 2000 sites in SW Portugal. We created a map of connectivity between the two sites that was based on a stack of analyses including reciprocal causal modeling and least-cost path modeling coupled with resistant kernel analysis. Results Wood mice in the study area were genetically diverse and connected by gene flow over a large area. We did not find evidence of major population subdivision in the study area. Gene flow was limited by geographic distance, with significant genetic similarity between individuals within 3 km of each other. Vegetation cover and land use explained more of the variation in genetic distance than geographic distance alone. In particular, agroforestry areas and transitional woodland were associated with higher costs to movement than forest or arable land uses. This result may have been influenced by the difficulty in classifying land use in the open montado. Conclusions The Natura 2000 sites we studied are well connected by multiple corridors for dispersal. Our analysis also highlighted the importance of the Serra de Grandola, part of the European Long Term Ecological Research Network but not yet included in Natura 2000.!://WOS:000350360100004Times Cited: 0 0921-2973WOS:00035036010000410.1007/s10980-014-0130-z|?#Pryke, James S. Samways, Michael J.2015WConserving natural heterogeneity is crucial for designing effective ecological networks595-607Landscape Ecology304AprLarge-scale ecological networks (ENs) are an important mitigation measure in agriculturally transformed landscapes. However, understanding the multitude of pressures influencing the presence/absence of species, and subsequent degree of species spatial heterogeneity, is important when planning effective ENs. We aim here to measure these pressures and determine species heterogeneity in ENs against natural reference sites. We use arthropods, as they are effective bioindicators for measuring these pressures and heterogeneity, as many are habitat sensitive. Here we use many arthropod taxa to determine how a suite of variables influences the spatially sensitive grassland interior species of both EN corridors and protected areas (PAs). At each of 48 selected sites, nine stations were sampled for arthropods, with six stations in plantation block (i.e. transformed grassland) or natural indigenous forest, as well as associated edge zone and three stations in EN corridor or PA interior. Eleven variables were measured and classed into environmental, design, and current and historical management variables. Data were split into: overall data, recording all species found in interior zones, and datasets containing only species that had >50 or >75 % of their abundance sampled in the interior zone. These datasets were split into total species and singleton-removed datasets. Overall, the richness of non-singleton species, i.e. those frequently sampled in grassland interiors, were most responsive to natural background environmental variables, while design and management variables were most important for datasets with singletons retained. This means that when planning ENs, we first need to conserve the natural range of environmental heterogeneity to conserve a range of interior specialists. This natural spatial heterogeneity then needs to be incorporated into design and management planning to conserve the full range of biodiversity in ENs, as if in PAs.!://WOS:000350360100003Times Cited: 0 0921-2973WOS:00035036010000310.1007/s10980-014-0096-x|?]Betts, Matthew G. Gutzwiller, Kevin J. Smith, Matthew J. Robinson, W. Douglas Hadley, Adam S.2015XImproving inferences about functional connectivity from animal translocation experiments585-593Landscape Ecology304Apr)Context Functional connectivity reflects the ease with which an organism can access different locations within its environment. Because functional connectivity can significantly influence dispersal, habitat selection, and ultimately the viability of populations, it is central to understanding and predicting biological responses to anthropogenic disturbance. Currently, no consensus exists on how to measure functional connectivity. Objectives and methods Species-centered approaches such as translocation experiments have recently been advocated because they enable strong inferences about functional connectivity. The use of these types of experiments is increasing rapidly, but to date there has been no synthesis of the wide range of methods available to minimize possible study design problems. Here, we review the recent literature on translocation experiments and highlight potential confounds that may lead to inappropriate conclusions from translocation studies. Results We report several approaches that can limit the degree to which these confounds affect inferences. We briefly describe paired and repeated-measures designs that use mixed models to address lack of spatial and temporal independence as means for coping with confounds. Conclusions Such approaches to the design and analyses of translocation experiments should facilitate high-quality measurements of landscape functional connectivity. We encourage investigators to continue functional connectivity research that capitalizes on the advantages of translocations while applying rigorous study designs.!://WOS:000350360100002Times Cited: 0 0921-2973WOS:00035036010000210.1007/s10980-015-0156-xJ|?kIverson, Louis R. Collins, Scott Dangermond, Jack Forman, Richard Nassauer, Joan I. Wiens, John Wolfe, Erin2015'In memoriam: Paul G. Risser (1939-2014)579-583Landscape Ecology304Apr!://WOS:000350360100001Times Cited: 0 0921-2973WOS:00035036010000110.1007/s10980-015-0174-8|?lVan Teeffelen, Astrid J. A. Vos, Claire C. Jochem, Rene Baveco, Johannes M. Meeuwsen, Henk Hilbers, Jelle P.2015Is green infrastructure an effective climate adaptation strategy for conserving biodiversity? A case study with the great crested newt937-954Landscape Ecology305MayIncreasing the amount of green infrastructure, defined as small-scale natural landscape elements, has been named as a climate adaptation measure for biodiversity. While green infrastructure strengthened ecological networks in some studies, it is not known whether this effect also holds under climate change, and how it compares to other landscape adaptation options. We assessed landscape adaptation options under scenarios of climate change for a dispersal-limited and climate-sensitive species: great crested newt, Triturus cristatus. A spatially-explicit modelling framework was used to simulate newt metapopulation dynamics in a case study area in the Netherlands, under alternative spatial configurations of 500 ha to-be-restored habitat. The framework incorporated weather-related effects on newt recruitment, following current and changing climate conditions. Mild climate change resulted in slightly higher metapopulation viability, while more severe climate change (i.e. more frequent mild winters and summer droughts) had detrimental effects on metapopulation viability. The modelling framework revealed interactions between climate and landscape configuration on newt viability. Restoration of ponds and terrestrial habitat may reduce the negative effects of climate change, but only when certain spatial requirements (habitat density, connectivity) as well as abiotic requirements (high ground water level) are met. Landscape scenarios where habitat was added in the form of green infrastructure were not able to meet these multiple conditions, as was the case for a scenario that enlarged core areas. The approach allowed a deduction of landscape design rules that incorporated both spatial and abiotic requirements resulting in more effective climate adaptation options.!://WOS:000352691300012Times Cited: 0 0921-2973WOS:00035269130001210.1007/s10980-015-0187-3|?BMelles, Stephanie J. Chu, Cindy Alofs, Karen M. Jackson, Donald A.2015Potential spread of Great Lakes fishes given climate change and proposed dams: an approach using circuit theory to evaluate invasion risk919-935Landscape Ecology305MayThe Great Lakes currently harbour a number of non-native fishes that are thermally limited to the comparatively warm waters of Lake Erie and Lake Ontario. Climate change could facilitate the inland spread of many non-native species as the Great Lakes and their tributaries warm, putting thousands of inland lakes and streams at risk. We investigated how watershed network configurations, climate change and proposed hydro-power development could influence invasion risk in the Great Lakes Basin. Electric circuit theory was used to model hydrologic accessibility of aquatic ecological networks (i.e., lake, river, and impoundment chains) within tertiary watersheds. Risk of invasion was measured as the product of probability of non-native species spread (hydrologic accessibility) and amount of suitable thermal habitat under an ensemble of air temperature projections. Proposed hydro-power dam sites and their upstream catchments were used to evaluate changes in total risk of invasion given passable, semi-passable, and impassable dams. We show that projected climate change will lead to more coolwater stream and warmwater lake habitat. Overall invasion risk of cool- and warmwater species was highest in southern Ontario and surprisingly in northern watersheds draining into Lake Superior. This risk could be partially mediated by proposed dams if dams reduce connectivity and access to potentially suitable habitat. Our evaluation of mean invasion risk provides a broad-scale comparative tool for management of invasive species control options.!://WOS:000352691300011Times Cited: 0 0921-2973WOS:00035269130001110.1007/s10980-014-0114-z|?7Cowley, Daniel J. Johnson, Oliver Pocock, Michael J. O.2015Using electric network theory to model the spread of oak processionary moth, Thaumetopoea processionea, in urban woodland patches905-918Landscape Ecology305MayCHabitat fragmentation is increasing as a result of anthropogenic activities, especially in urban areas. Dispersal through fragmented habitats is key for species to spread, persist in metapopulations and shift range in response to climate change. However, high habitat connectivity may also hasten the spread of invasive species. To develop a model of spread in fragmented landscapes and apply it to the spread of an invasive insect in urban woodland. We applied a patch-based model, based on electric network theory, to model the current and predicted future spread of oak processionary moth (OPM: Thaumetopoea processionea) from its source in west London. We compared the pattern of 'effective distance' from the source (i.e. the patch 'voltage' in the model) with the observed spread of the moth from 2006 to 2012. We showed that 'effective distance' fitted current spread of OPM. Patches varied considerably in their 'current' and 'power' (metrics from the model), which is an indication of their importance in the future spread of OPM. Patches identified as 'important' are potential 'pinch points' and regions of high 'flow', where resources for detection and management will be most cost-effectively deployed. However, data on OPM dispersal and the distribution of oak trees limited the strength of our conclusions, so should be priorities for further data collection. This application of electric network theory can be used to inform landscape-scale conservation initiatives both to reduce the spread of invasives and to facilitate large-scale species' range shifts in response to climate change.!://WOS:000352691300010Times Cited: 0 0921-2973WOS:00035269130001010.1007/s10980-015-0168-6|?Leito, Aivar Bunce, Robert Gerald Henry Kuelvik, Mart Ojaste, Ivar Raet, Janar Villoslada, Miguel Leivits, Meelis Kull, Anne Kuusemets, Valdo Kull, Tiiu Metzger, Marc Joris Sepp, Kalev2015yThe potential impacts of changes in ecological networks, land use and climate on the Eurasian crane population in Estonia887-904Landscape Ecology305MayThe Eurasian crane (Grus grus) is an iconic and sensitive species. It is therefore necessary to understand its landscape ecology in order to determine threats. (1) To map the distribution of cranes and then model their habitat requirements in Estonia, linked to the current level of protection. (2) To determine the environmental characteristics of, and the habitats present in, sites utilized by the birds, and their sensitivity to change. (1) The distribution of cranes was recorded by observation and by tracking individuals. A model of potential breeding sites was compared with the occurrence of the bird in Estonia and then linked to protected sites. (2) The seasonal distribution of the bird was overlaid with a European environmental classification and the CORINE land cover map. A model of climate change was also utilized. (1) A new map of European migration routes, wintering and stopover sites is presented. (2) The bird requires a habitat network, with wetlands being essential for nesting and roosting. The composition of habitats used for feeding varies according to geographical location. (3) In Estonia not all potential breeding sites are occupied and many existing sites are not protected. (4) Climate change could threaten populations in the south but could be beneficial in Estonia. (1) The existing ecological network in Estonia is adequate to maintain a viable breeding population of the Eurasian crane. (2) Climate change could support the breeding of cranes but complicate their migration and wintering.!://WOS:000352691300009Times Cited: 0 0921-2973WOS:00035269130000910.1007/s10980-015-0161-0|?PKros, J. Bakker, M. M. Reidsma, P. Kanellopoulos, A. Alam, S. Jamal de Vries, W.2015yImpacts of agricultural changes in response to climate and socioeconomic change on nitrogen deposition in nature reserves871-885Landscape Ecology305MayVThis paper describes the environmental consequences of agricultural adaptation on eutrophication of the nearby ecological network for a study area in the Netherlands. More specifically, we explored (i) likely responses of farmers to changes in climate, technology, policy, and markets; (ii) subsequent changes in nitrogen (N) emissions in responses to farmer adaptations; and (iii) to what extent the emitted N was deposited in nearby nature reserves, in view of the potential impacts on plant species diversity and desired nature targets. For this purpose, a spatially-explicit study at landscape level was performed by integrating the environmental model INITIATOR, the farm model FSSIM, and the land-use model RULEX. We evaluated two alternative scenarios of change in climate, technology, policy, and markets for 2050: one in line with a 'global economy' (GE) storyline and the other in line with a 'regional communities' (RC) storyline. Results show that the GE storyline resulted in a relatively strong increase in agricultural production compared to the RC storyline. Despite the projected conversions of agricultural land to nature (as part of the implementation of the National Ecological Network), we project an increase in N losses and N deposition due to N emissions in the study area of about 20 %. Even in the RC storyline, with a relatively modest increase in agricultural production and a larger expansion of the nature reserve, the N losses and deposition remain at the current level, whereas a reduction is required. We conclude that more ambitious green policies are needed in view of nature protection.!://WOS:000352691300008Times Cited: 1 0921-2973WOS:00035269130000810.1007/s10980-014-0131-y|?van der Knaap, Yasmijn A. M. de Graaf, Myrjam van Ek, Remco Witte, Jan-Philip M. Aerts, Rien Bierkens, Marc F. P. van Bodegom, Peter M.2015pPotential impacts of groundwater conservation measures on catchment-wide vegetation patterns in a future climate855-869Landscape Ecology305MayIn temperate Europe, warming, summer droughts, and increased winter precipitation are predicted to have profound effects on vegetation performance and composition. Especially groundwater dependent vegetation will be affected. These impacts within the landscape may negatively affect the connectivity within ecological networks. With an integrated surface- and groundwater model and a climate robust traits-based vegetation model, we simulated the implementation of water conservation measures in a stream valley catchment in the Netherlands. We assessed the impacts of conservation measures on groundwater levels, seepage flux, and vegetation composition for the current climate and two climate scenarios, with a global temperature increase of 2 A degrees C and an increase (+6 %) or decrease (-2 %) in annual precipitation. Our model showed that water conservation measures on average increased groundwater levels, although there were large spatial differences. At the same time, water conservation decreased the seepage flux in the stream valley, thereby decreasing the supply of nutrient-poor groundwater. These negative impacts on seepage flux will be amplified in a future climate. Semi-terrestrial vegetation along the streams will benefit from water conservation measures and increasingly so in a future climate. Other vegetation types showed a wide array of responses depending on spatially-differentiated changes in groundwater level and seepage fluxes. Our results highlight the importance of integrating spatially-explicit hydrology-vegetation interactions into models that evaluate climate adaptation measures. Customized water conservation measures can contribute to minimize negative effects of climate change on groundwater dependent vegetation and ensure the robustness of ecological networks.!://WOS:000352691300007Times Cited: 0 0921-2973WOS:00035269130000710.1007/s10980-014-0142-8I|?Witte, Jan-Philip M. Bartholomeus, Ruud P. van Bodegom, Peter M. Cirkel, D. Gijsbert van Ek, Remco Fujita, Yuki Janssen, Gijs M. C. M. Spek, Teun J. Runhaar, Han2015yA probabilistic eco-hydrological model to predict the effects of climate change on natural vegetation at a regional scale835-854Landscape Ecology305MaytClimate change may hamper the preservation of nature targets, but may create new potential hotspots of biodiversity as well. To timely design adequate measures, information is needed about the feasibility of nature targets under a future climate. Habitat distribution models may provide this, but current models have certain drawbacks: they apply indirect empirical relationships between habitat and vegetation, they often disregard spatially explicit information about groundwater, and they are designed for too coarse spatial scales. We introduce a model that explicitly takes into account spatial effects through groundwater and that can easily be adapted to new scientific approaches and the needs of end-users. It combines (spatially explicit) data sources, transfer functions derived from mechanistic models, and robust relationships between habitat factors and plant characteristics. Outputs are maps showing the occurrence probabilities of vegetation types and their associated conservation values, both on a spatial scale that fits the needs of nature managers and spatial planners. The model was applied to a catchment of 270 km(2) to forecast, on a 25 m resolution, the effects of a national climate scenario (related to IPCC A2 and A1B). Computation time was a couple of minutes on a standard PC. Severe loss was predicted for wet and mesotrophic species-rich grasslands, while vegetation of dry and acidic soils appeared to profit. The results were not univocal though, and could probably not have been foreseen on the basis of expert judgement and logic alone, especially because of edaphic factors and spatial hydrological relationships.!://WOS:000352691300006Times Cited: 2 0921-2973WOS:00035269130000610.1007/s10980-014-0086-z|?Piquer-Rodriguez, Maria Torella, Sebastian Gavier-Pizarro, Gregorio Volante, Jose Somma, Daniel Ginzburg, Ruben Kuemmerle, Tobias2015YEffects of past and future land conversions on forest connectivity in the Argentine Chaco817-833Landscape Ecology305MayLand-use change is the main driver of habitat loss and fragmentation worldwide. The rate of dry forest loss in the South American Chaco is among the highest in the world, mainly due to the expansion of soybean production and cattle ranching. Argentina recently implemented a national zoning plan (i.e., the Forest Law) to reduce further forest loss. However, it is unclear how the effects of past deforestation and the implementation of the Forest Law will affect forest connectivity in the Chaco. Our main goal was to evaluate the potential effect of the Forest Law on forest fragmentation and connectivity in the Argentine Chaco. We studied changes in the extent, fragmentation, and connectivity of forests between 1977 and 2010, by combining agricultural expansion and forest cover maps, and for the future in a scenario analysis. Past agricultural expansion translated into an overall loss of 22.5 % of the Argentine Chaco's forests, with deforestation rates in 2000-2010 up to three times higher than in the 1980s. Forest fragmentation and connectivity loss were highest in 1977-1992, when road construction fragmented large forest patches. Our future scenario analysis showed that if the Forest Law will be implemented as planned, forest area and connectivity in the region will decline drastically. Land-use planning designed to protect stepping stones could substantially mitigate connectivity loss due to deforestation, with the co-benefit of preserving the greatest amount of biodiversity priority areas across all evaluated scenarios. Including scenario analyses that assess forest fragmentation and connectivity at the ecoregion scale is thus important in upcoming revisions of the Argentine Forest Law, and, more generally, in debates about sustainable resource use.!://WOS:000352691300005Times Cited: 0 0921-2973WOS:00035269130000510.1007/s10980-014-0147-3R|?van Dijk, Jerry van der Vliet, Roland E. de Jong, Harm van Emmichoven, Maarten J. Zeylmans van Hardeveld, Henk A. Dekker, Stefan C. Wassen, Martin J.2015Modeling direct and indirect climate change impacts on ecological networks: a case study on breeding habitat of Dutch meadow birds805-816Landscape Ecology305MayClimate change can directly affect habitats within ecological networks, but may also have indirect effects on network quality by inducing land use change. The relative impact of indirect effects of climate change on the quality of ecological networks currently remains largely unknown. The objective of this study was to determine the relative impact of direct and indirect effects of climate change on a network of breeding habitat of four meadow bird species (Black-tailed godwit, Common redshank, Eurasian oystercatcher and Northern lapwing) in the Netherlands. Habitat models were developed that link meadow bird breeding densities to three habitat characteristics that are sensitive to environmental change (landscape openness, land use and groundwater level). These models were used to assess the impact of scenarios of landscape change with and without climate change on meadow bird breeding habitat quality for a case study area in the peat meadow district of the Netherlands. All scenarios led to significantly reduced habitat quality for all species, mainly as a result of conversion of grassland to bioenergy crops, which reduces landscape openness. Direct effects of climate change on habitat quality were largely absent, indicating that especially human adaptation to climate change rather than direct effects of climate change was decisive for the degradation of ecological network quality for breeding meadow birds. We conclude that scenario studies exploring impacts of climate change on ecological networks should incorporate both land use change resulting from human responses to climate change and direct effects of climate change on landscapes.!://WOS:000352691300004Times Cited: 1 0921-2973WOS:00035269130000410.1007/s10980-014-0140-x|?_Bakker, Martha Alam, Shah Jamal van Dijk, Jerry Rounsevell, Mark Spek, Teun van den Brink, Adri2015jThe feasibility of implementing an ecological network in The Netherlands under conditions of global change791-804Landscape Ecology305May[Both global change and policy reform will affect the implementation of the National Ecological Network (NEN) in the Netherlands. Global change refers to a combination of changing groundwater tables arising from climate change and improved economic prospects for farming. Policy reform refers to the abolition of an intermediary organization that organizes land trades with the support of a national land bank. In this paper we evaluate the effects of these factors on future land acquisition for the NEN. We applied an agent-based model of the land market based on sales and purchases between farmers and nature-conservation organizations (establishing the NEN) within a case study area. Our results demonstrate that future land acquisitions for the NEN are constrained by strong competition for land from farmers due to improved economic prospects for farming. Effects of climate change are that fewer parcels will be sold from farmers to nature-conservation organizations in a dry scenario as compared to a wet scenario. An important constraint for land acquisitions is the low willingness to pay (WTP) for land by nature-conservation organizations. We demonstrate that higher WTP increases land purchases considerably. However, the spatial pattern of land acquisition is fragmented, which may undermine its effectiveness from a restoration perspective. The combination of these processes leads to land acquisitions for the NEN that do not meet the initially-stated policy objectives by far. In addition, the abolition of a land-trade organization supported by a land bank leads to more fragmented pattern of nature reserves.!://WOS:000352691300003Times Cited: 3 0921-2973WOS:00035269130000310.1007/s10980-014-0145-5|?DGimona, Alessandro Poggio, Laura Polhill, J. Gary Castellazzi, Marie2015Habitat networks and food security: promoting species range shift under climate change depends on life history and the dynamics of land use choices771-789Landscape Ecology305MayHHabitat networks are often advocated as an effective measure for adaptation to climate change, while intensification of land use is a possible response to threats to food security. We examined the question of whether woodland networks are likely to help promote species range shift, and tried to disentangle the influence of land use change, as mediated by land managers' choices, climate change and dispersal ability. Using Scotland as the study area, we considered species types with different dispersal abilities and, with the help of an Agent-Based Model, constructed four stylised scenarios in with different levels of woodland planting and different land managers' choices. We then modelled range expansion of broadleaved woodland species having increasing dispersal abilities. Woodland networks could help range shift for species with dispersal distance (DD) of more than 2 km, but would be no panacea if rapid range shift were needed to preserve population viability. In particular, land use choices influenced most the movements of species with DD between 2 and 5 km. Therefore for such species potential disequilibrium between climate and distribution can be mitigated by increasing stepping stones thus improving landscape permeability to movement. Species that had DD a parts per thousand currency sign2 km moved very slowly in our simulations, and this is consistent with paleo-ecological estimates. For populations of species with short DD that might need to shift their distribution to remain viable, translocation could be a more effective conservation option than creating woodland networks.!://WOS:000352691300002Times Cited: 0 0921-2973WOS:00035269130000210.1007/s10980-015-0158-8|?JBakker, Martha M. Opdam, Paul F. M. Jongman, Rob H. G. Van den Brink, Adri2015VModel explorations of ecological network performance under conditions of global change763-770Landscape Ecology305May+Ecological networks facilitate the mobility and vitality of species populations by providing a network of habitat patches that are embedded in a traversable landscape matrix. Climate change and land-use change pose threats to biodiversity, which can potentially be overcome by ecological networks. Yet, systematic assessments of ecological network performance under conditions of climate change and land-use change are rare. In this special issue we explore and evaluate approaches to assess the functionality of ecological networks under scenarios of global change. Hereby we distinguish three research fields: dynamics in the spatial configuration of networks; changes in the abiotic conditions within networks; and population viability and mobility of species within the networks. We present novel approaches for each of these themes, as well as approaches that aim to combine them within one modelling framework. Whilst the contributions featured all show promising developments towards the goal of ecological network performance under conditions of global change, we also see challenges for future research: the need to achieve (i) better integration between the three research fields; (ii) better empirical grounding of theoretical models; and (iii) better design of scientific models in order to assist policymaking.!://WOS:000352691300001Times Cited: 0 0921-2973WOS:00035269130000110.1007/s10980-015-0181-9|?*Arvola, Lauri Einola, Eeva Jarvinen, Marko2015kLandscape properties and precipitation as determinants for high summer nitrogen load from boreal catchments429-442Landscape Ecology303Mar`Hydrological conditions are among the most important factors influencing nutrient concentrations in rivers and their fluxes out of the catchments. In the boreal area extreme hydrological conditions are typical with intense floods during the snow-melt period in spring and the base-flow conditions during winter and summer. In this study we compared nitrate-nitrogen (NO3-N), ammonium-nitrogen (NH4-N) and dissolved organic nitrogen (DON) concentrations and fluxes among summer seasons (June-August) with contrasting hydrology in four small boreal rivers with differing land-use in southern Finland. For the analysis we selected 3 years of the lowest summer discharge (1999, 2010, 2011) and 3 years of the highest summer discharge (1996, 1998, 2004). During high discharge summers NH4-N and DON concentrations were on average 187 and 240 % higher than during low discharge summers. Because of large differences in discharge between the summers the flux values of the different N fractions were at maximum 10-20 times higher during high discharge summers. The effect of heavy rains on N loading was clearly demonstrated in summer 2004 when two consecutive floods transported 42 % of the annual NO3-N flux, 44 % of the NH4-N flux and 57 % of the DON flux out of the catchment. Available nitrogen storages in the studied catchment areas were probably in excess especially during the wet summers when the plant uptake was presumably lower compared to dryer and warmer summers. When the hydrological conditions were suitable for surface and subsurface runoff, the concentrations and fluxes of NO3-N, NH4-N and DON increased substantially.!://WOS:000350227000005Times Cited: 1 0921-2973WOS:00035022700000510.1007/s10980-015-0166-8|?EDunford, Robert W. Smith, Alison C. Harrison, Paula A. Hanganu, Diana2015wEcosystem service provision in a changing Europe: adapting to the impacts of combined climate and socio-economic change443-461Landscape Ecology303MarUFuture patterns of European ecosystem services provision are likely to vary significantly as a result of climatic and socio-economic change and the implementation of adaptation strategies. However, there is little research in mapping future ecosystem services and no integrated assessment approach to map the combined impacts of these drivers. Map changing patterns in ecosystem services for different European futures and (a) identify the role of driving forces; (b) explore the potential influence of different adaptation options. The CLIMSAVE integrated assessment platform is used to map spatial patterns in services (food, water and timber provision, atmospheric regulation, biodiversity existence/bequest, landscape experience and land use diversity) for a number of combined climatic and socio-economic scenarios. Eight adaptation strategies are explored within each scenario. Future service provision (particularly water provision) will be significantly impacted by climate change. Socio-economic changes shift patterns of service provision: more dystopian societies focus on food provision at the expense of other services. Adaptation options offer significant opportunities, but may necessitate trade-offs between services, particularly between agriculture- and forestry-related services. Unavoidable trade-offs between regions (particularly South-North) are also identified in some scenarios. Coordinating adaptation across regions and sectors will be essential to ensure that all needs are met: a factor that will become increasingly pressing under dystopian futures where inter-regional cooperation breaks down. Integrated assessment enables exploration of interactions and trade-offs between ecosystem services, highlighting the importance of taking account of complex cross-sectoral interactions under different future scenarios of planning adaptation responses.!://WOS:000350227000006Times Cited: 1 0921-2973WOS:00035022700000610.1007/s10980-014-0148-2|?kLu, Yihe Sun, Feixiang Wang, Jianglei Zeng, Yuan Holmberg, Maria Bottcher, Kristin Vanhala, Pekka Fu, Bojie2015Managing landscape heterogeneity in different socio-ecological contexts: contrasting cases from central Loess Plateau of China and southern Finland463-475Landscape Ecology303MarLandscape transition drives environmental change across the globe. However, landscape and its change are complex with high spatial heterogeneity, which challenges strategic decision-making. This paper aims to derive management meaningful units based on landscape status and change analysis and the generalization of landscape spatial heterogeneity. Based on contrasting cases from Finland (Vanajavesi) and China (Baota District), this paper analyzed the landscape attributes and change since 2000. A k-means clustering approach was used to generalize the landscape types based on indicators of landscape composition and its change, spatial pattern, population, and income. Most significant change in land covers was the expansion of artificial surfaces, and the bi-directional transitions between agricultural areas and forests and semi-natural areas in Vanajavesi, while the expansion of artificial land and shrinkage of cropland were most significant in Baota District. Larger changes in landscape metrics were also observed in Baota District. Finally, three landscape clusters were generalized in both of the case areas. For each cluster, the landscapes and their change characteristics were interpreted as pertinent to the average land cover pattern and its change and socioeconomic conditions. Brief landscape management recommendations were also given for the resulting clusters. This paper contributes to enriching the understanding of the analysis and management of landscape spatial heterogeneity based on the information from both landscape status and change. The contrasting case analyses from an international perspective indicate the usefulness of clustering approach in accommodating spatial heterogeneity, which imply a regionalized need for landscape monitoring, assessment, and management.!://WOS:000350227000007Times Cited: 1 0921-2973WOS:00035022700000710.1007/s10980-014-0129-5 [|?%Liu, Miao Liu, Guohua Zheng, Xiaoxuan2015Spatial pattern changes of biomass, litterfall and coverage with environmental factors across temperate grassland subjected to various management practices477-486Landscape Ecology303Mar Understanding the influences of different utilization patterns in different grassland types on grassland traits is essential for grassland conservation and improvement of grassland management. Grazing, mowing, and fencing have the potential to substantially affect vegetation characteristics. The general pattern and mechanisms for relationships between vegetation characteristics and abiotic factors are fundamental issues in ecology .The effect of the key factors on vegetation traits under different management practices has been rarely comprehensively elucidated in previous studies,especially across the temperate grasslands in the Hulunbuir region. Therefore, the principal purposes of this study were: (1) to analyze the effects of different management practices on vegetation characteristics using data investigated from 23 sites across the temperate grasslands; (2) to explore the relationship of environmental factors with vegetation dynamics, and to identify the main factors using correlation analysis; and (3) to predict the evolution of vegetation dynamics with the major factors using the generalized additive modelat the landscape scale. The study area is situated at the western part of Mt. Daxing'anling, Hulunbuir, Inner Mongolia, China. Samples were collected in the grasslands utilized for grazing (always from 10 sampled sites), mowing (since 2003, from 6 sampled sites), and fencing (since 2003, from 7 samples sites). In each site, we investigated above ground biomass, below ground, litter, coverage and soil properties in five plots (1 m x 1 m) at a 10 m interval along a transect. Data pertaining to the environmental factors and vegetation characteristics in different utilization types were compared using ANOVA. The relationship of the main elements with vegetation traits was analyzed using CA in these utilization types. GAM analysis was conducted to explore the evolutionary trend of vegetation dynamics with respect to the critical factors at the landscape scale. Fencing and mowing practices, which can improve vegetation traits, and increase grassland carbon sink, should be continued to promote the Hulunbuir grasslands, rather than grazing management. Thus, appropriate reforms concerning the proper utilize the grassland (e.g. mowing and fencing) is necessary to ensure sustainability of the grassland ecological system, and what is more, the effects of the ecological project in the sustainable development of the temperate grasslands in the Hulunbuir region should be gradually explored.!://WOS:000350227000008Times Cited: 1 0921-2973WOS:00035022700000810.1007/s10980-014-0120-1|?5Posch, Maximilian Duan, Lei Reinds, Gert Jan Zhao, Yu2015dCritical loads of nitrogen and sulphur to avert acidification and eutrophication in Europe and China487-499Landscape Ecology303MarFForests and other (semi-)natural ecosystems provide a range of ecosystem services, such as purifying water, stabilizing soils and nutrient cycles, and providing habitats for plants and wildlife. Critical loads are a well-established effects-based approach that has been used for assessing the environmental consequences of air pollution on large regional or national scales. Typically critical loads of sulphur (S) and nitrogen (N) have been derived separately for characterizing the vulnerability of ecosystems to acidification (by S and N) and eutrophication (by N). In this paper we combine the two approaches and use multiple criteria, such as critical pH and N concentrations in soil solution, to define a single critical load function of N and S. The methodology is used to compute and map critical loads of N and S in two regions of comparable size, Europe and China. We also assess the exceedance of those critical loads under globally modelled present and selected future N and S depositions. We also present an analysis, in which the sensitivity of the critical loads and their exceedances to the choice of the chemical criteria is investigated. As pH and N concentration in soil solution are abiotic variables also linked to plant species occurrence, this approach has the potential for deriving critical loads for plant species diversity.!://WOS:000350227000009Times Cited: 1 0921-2973WOS:00035022700000910.1007/s10980-014-0123-yI|?Vihervaara, Petteri Mononen, Laura Auvinen, Ari-Pekka Virkkala, Raimo Lu, Yihe Pippuri, Inka Packalen, Petteri Valbuena, Ruben Valkama, Jari2015cHow to integrate remotely sensed data and biodiversity for ecosystem assessments at landscape scale501-516Landscape Ecology303MarBiodiversity and ecosystem functioning underpins the delivery of all ecosystem services and should be accounted for in all decision-making related to the use of natural resources and areas. However, biodiversity and ecosystem services are often inadequately accounted for in land use management decisions. We studied a boreal forest ecosystem by linking citizen-science bird data with detailed information on forest characteristics from airborne laser scanning (ALS). In this paper, we describe this method, and evaluate how similar kinds of biological data sets combined with remote sensing can be used for ecosystem assessments at landscape scale. We analysed data for 41 boreal forest bird species and for 14 structural ALS-based forest parameters. The results support the use of the selected method as a basis for quantifying spatially-explicit biodiversity indicators for ecosystem assessments, while suggestions for improvements are also reported. Finally, we evaluate the capacity of those indicators to describe biodiversity-ecosystem service relationships, for example with carbon trade-offs. The results showed clear distinctions between the different species as measured, for example, by above-ground forest biomass at the observation sites. We also assess how the available data sources can be developed to be compatible with the concept of essential biodiversity variables (EBV), which has been put forward as a solution to cover the most important aspects of biodiversity and ecosystem functioning. We suggest that EBVs should be integrated into environmental monitoring programmes in the future, and citizen science and remote sensing methods need to be an important part of them.!://WOS:000350227000010Times Cited: 1 0921-2973WOS:00035022700001010.1007/s10980-014-0137-5 |?Maes, Joachim Barbosa, Ana Baranzelli, Claudia Zulian, Grazia Batista e Silva, Filipe Vandecasteele, Ine Hiederer, Roland Liquete, Camino Paracchini, Maria Luisa Mubareka, Sarah Jacobs-Crisioni, Chris Castillo, Carolina Perpina Lavalle, Carlo2015vMore green infrastructure is required to maintain ecosystem services under current trends in land-use change in Europe517-534Landscape Ecology303MarGreen infrastructure (GI), a network of nature, semi-natural areas and green space, delivers essential ecosystem services which underpin human well-being and quality of life. Maintaining ecosystem services through the development of GI is therefore increasingly recognized by policies as a strategy to cope with potentially changing conditions in the future. This paper assessed how current trends of land-use change have an impact on the aggregated provision of eight ecosystem services at the regional scale of the European Union, measured by the Total Ecosystem Services Index (TESI8). Moreover, the paper reports how further implementation of GI across Europe can help maintain ecosystem services at baseline levels. Current demographic, economic and agricultural trends, which affect land use, were derived from the so called Reference Scenario. This scenario is established by the European Commission to assess the impact of energy and climate policy up to 2050. Under the Reference Scenario, economic growth, coupled with the total population, stimulates increasing urban and industrial expansion. TESI8 is expected to decrease across Europe between 0 and 5 % by 2020 and between 10 and 15 % by 2050 relative to the base year 2010. Based on regression analysis, we estimated that every additional percent increase of the proportion of artificial land needs to be compensated with an increase of 2.2 % of land that qualifies as green infrastructure in order to maintain ecosystem services at 2010 levels.!://WOS:000350227000011Times Cited: 2 0921-2973WOS:00035022700001110.1007/s10980-014-0083-2t|?*Zhang, Liwei Fu, Bojie Lu, Yihe Zeng, Yuan2015FBalancing multiple ecosystem services in conservation priority setting535-546Landscape Ecology303MarIConservation priority setting is the critical process of allocating the limited resources available for nature conservation and; safeguarding the sustainability of biodiversity and ecosystem services (ESs). It is difficult, however, to achieve the goal of simultaneously conserving both biodiversity and ESs, not only because of the potential trade-offs between biodiversity and ESs, but also because of the trade-offs between multiple ESs. Thus far, research has focused on the trade-offs between ESs caused by spatial competition resulting from land use change or by the destruction of biophysical interaction between multiple ESs. Few studies, however, have paid attention to the trade-offs induced during the decision-making process. Approaches for measuring the trade-offs between multiple ESs in decision-making processes would thus prove to be extremely helpful. In this paper, we map the water supply, soil conservation, and net primary production as ESs in the Jiangxi province of China in the year 2010, and use risk, tradeoff, and spatial efficiency indices to measure the conservation efficiency of seven established ordered weighted averaging (OWA) scenarios under two conservation levels (conserving the top ESs at 10 or 20 % of the area of the Jiangxi province). The main results are as follows: (1) conserving one ES may result in inefficient conservation of other ESs; and (2) conserving multiple ESs and the use of GIS-based OWA methods can balance conflicts among multiple ESs and can significantly enhance the spatial efficiency of the identified priority areas. Decision-makers may combine the spatial efficiency, risk and tradeoff levels of each OWA scenario with other specific conservation demands of their own specific cases in order to achieve the optimal identification of priority areas for the simultaneous conservation of multiple ESs.!://WOS:000350227000012Times Cited: 2 0921-2973WOS:00035022700001210.1007/s10980-014-0106-z|?-Hu, Haitang Fu, Bojie Lu, Yihe Zheng, Zhenmin2015]SAORES: a spatially explicit assessment and optimization tool for regional ecosystem services547-560Landscape Ecology303MarThe concept of ecosystem services (ES) has become mainstreamed in environmental planning and management recently, and with that various tools for quantifying ecosystem services have emerged. However, designing the tools for integrated assessment and optimization of multiple ES has become a challenging task. In order to promote the efficiency of ecosystem planning and management, we develop a spatial decision support tool named SAORES, which provides a platform for exploratory scenario analysis and optimal planning design, rather than ES assessment. SAORES is formed with four modules: the scenario development module, the integrated ecosystem service model base, the ecosystem service trade-off analysis module, and the multi-objective spatial optimization module based on NSGA-II. Using SAORES, we make a case study on the Yangou catchment of the Loess Plateau, China. Based on impact assessment of the Grain to green program (GTGP), we optimize the farmland retiring planning, involving multiple objectives which include the eco-compensation and the key ES. The integrated assessment shows that, the aim of the GTGP, the water and soil retention are prominent improved. Optimization for GTGP provides a series of optimal solutions, which are better than other single optimized solutions, and are twice the cost-effectiveness of the actual situation. SAORES, as a decision support tool, can improve the scenario analysis and multi-objective optimal planning design for ecosystem management and planning. The case study demonstrates the potential and effectiveness of SAORES and spatial multi-objective optimization model for ecosystem service management, especially in the Loess Plateau.!://WOS:000350227000013Times Cited: 2 0921-2973WOS:00035022700001310.1007/s10980-014-0126-8|?#Holmberg, Maria Akujarvi, Anu Anttila, Saku Arvola, Lauri Bergstrom, Irina Bottcher, Kristin Feng, Xiaoming Forsius, Martin Huttunen, Inese Huttunen, Markus Laine, Yki Lehtonen, Heikki Liski, Jari Mononen, Laura Rankinen, Katri Repo, Anna Piirainen, Vanamo Vanhala, Pekka Vihervaara, Petteri2015ESLab application to a boreal watershed in southern Finland: preparing for a virtual research environment of ecosystem services561-577Landscape Ecology303MariWe report on preparatory work to develop a virtual laboratory for ecosystem services, ESLab, and demonstrate its pilot application in southern Finland. The themes included in the pilot are related to biodiversity conservation, climate mitigation and eutrophication mitigation. ESLab is a research environment for ecosystem services (ES), which considers ES indicators at different landscape scales: habitats, catchments and municipalities and shares the results by a service that utilizes machine readable interfaces. The study area of the pilot application is situated in the boreal region of southern Finland and covers 14 municipalities and ten catchments including forested, agricultural and nature conservation areas. We present case studies including: present carbon budgets of natural ecosystems; future carbon budgets with and without the removal of harvest residues for bioenergy production; and total phosphorus and nitrogen future loads under climate and agricultural yield and price scenarios. The ESLab allows researchers to present and share the results as visual maps, statistics and graphs. Our further aim is to provide a toolbox of easily accessible virtual services for ES researchers, to illustrate the comprehensive societal consequences of multiple decisions (e.g. concerning land use, fertilisation or harvesting) in a changing environment (climate, deposition).!://WOS:000350227000014Times Cited: 2 0921-2973WOS:00035022700001410.1007/s10980-014-0122-zv|?Schippers, Peter van der Heide, C. Martijn Koelewijn, Hans Peter Schouten, Marleen A. H. Smulders, Rene M. J. M. Cobben, Marleen M. P. Sterk, Marjolein Vos, Claire C. Verboom, Jana2015gLandscape diversity enhances the resilience of populations, ecosystems and local economy in rural areas193-202Landscape Ecology302FebIn today's world, rapid environmental and economic developments and changes pose major threats to ecosystems and economic systems. In this context we explore if resilience can be increased by the spatial configuration of the rural landscape in an integrated ecological-genetic-economic way. We study the concept of landscape diversity from genetic, ecological and economic perspectives. We show that small-scale landscapes are potentially more resilient than large-scale landscapes, provided that ecosystem patch sizes are sufficiently large to support genetic diversity and ecosystem and economic functions. The basic premise underlying this finding is that more variation in a landscape generally leads to greater genetic and species diversity. This, in turn, stabilizes populations and strengthens the different ecosystem elements in the landscape. Greater variation in ecosystem elements provides for more varied ecosystem services, which may enhance the resilience of the local economy. We conclude that a resilient landscape is shaped within the context of economic and ecological possibilities and constraints, and is determined by landscape diversity and spatial organisation.!://WOS:000348131500001Times Cited: 0 0921-2973WOS:00034813150000110.1007/s10980-014-0136-6|?&Tomscha, Stephanie A. Gergel, Sarah E.2015lHistoric land surveys present opportunities for reconstructing frontier settlement patterns in North America203-213Landscape Ecology302Feb{Historical frontier expansion in North America has played a foundational role in shaping contemporary landscapes, yet early-settlement patterns are poorly quantified. Historic datasets such as land surveys have been underutilized in this context as they have been primarily used for historical ecological research on vegetation patterns. We use information from GLO surveys (late 1800s) to map a variety of linear disturbances (e.g., roads, trails) and examine their spatial patterns of concordance. Using a watershed in eastern Washington State, we asked: (1) Historically, which anthropogenic disturbances co-occur? and (2) Did historical disturbances vary with landscape position? With the exception of trails, we found most disturbance types co-occurred with at least one other disturbance. Disturbances were concentrated in riparian zones and terraces with approximately 45 % of disturbances occurring in less than 16 % of the landscape reflecting the disproportionate importance of floodplains for frontier settlers. Our results have implications for interpretation of GLO-derived vegetation maps and for fragmentation of modern floodplains.!://WOS:000348131500002Times Cited: 0 0921-2973WOS:00034813150000210.1007/s10980-014-0124-x|? Eddy, Ian M. S. Gergel, Sarah E.2015RWhy landscape ecologists should contribute to life cycle sustainability approaches215-228Landscape Ecology302FebUnderstanding the consequences of changes in land use and land cover is among the greatest challenges in sustainability science, yet key themes related to land cover change are often left out of sustainability assessment tools. Because sustainability teaching is expanding at a rapid rate, incorporation of interdisciplinary, rigorous, quantitative tools to distinguish sustainable and unsustainable landscape change are needed. As a heuristic exercise, we contrast and synthesize two approaches to quantifying sustainability using a case study of palm oil and tropical deforestation in Borneo, Indonesia. First, we use Markovian land cover change analysis (from 2000 to 2010) to estimate changes in forest cover, project these rates of change into the near future, and estimate changes in carbon stocks due to palm oil conversion. Second, we estimate greenhouse gas emissions from a typical Indonesian palm oil biodiesel plantation using a life cycle assessment approach (LCA). These two approaches show conflicting assessments for the carbon footprint of palm biodiesel: a sustainable endeavor when short-term global warming potential is evaluated yet highly unsustainable when rates of forest loss are measured. Furthermore, accounting for carbon that incorporated prior land cover dramatically altered sustainability assessments. Thus, integration of these two approaches reveals the importance of including both historic and future land cover changes into sustainability assessments. This synthesis demonstrates the importance of using a plurality of approaches from different disciplines when teaching sustainability, and highlights the unique role that landscape ecological approaches can play in sustainability assessments such as LCA.!://WOS:000348131500003Times Cited: 0 0921-2973WOS:00034813150000310.1007/s10980-014-0135-7|?\Villasenor, Nelida R. Blanchard, Wade Driscoll, Don A. Gibbons, Philip Lindenmayer, David B.2015`Strong influence of local habitat structure on mammals reveals mismatch with edge effects models229-245Landscape Ecology302FeboWhat determines mammal occurrence across wildland-urban edges? A better understanding of the variables involved will help update edge effects theory and improve our ability to conserve biota in urbanizing landscapes. For the first time, we tested whether the occurrence of mammals across urban-forest edges and forest interiors was best predicted by: (1) edge variables (i.e. edge type and distance to an urban boundary), (2) local habitat structure (e.g. proportion of understory cover), or (3) edge variables after accounting for local habitat structure. Using 77 camera stations in South-Eastern Australia, we quantified the factors influencing the occurrence of five native mammals (brown antechinus, bush rat, common brushtail possum, black wallaby and long-nosed bandicoot) and three non-native mammals (red fox, cat, and dog). The occurrence of most native and non-native mammals was best predicted by local habitat structure rather than by edge variables. Although edge variables had effects on most species occurrences, local habitat structure outweighed the impacts of edge effects. Our findings are important for management and urban planning as they suggest that local-scale management of habitat and habitat retention at urban edges will mitigate urban impacts on fauna. Our work reveals a critical mismatch in the spatial scale of predictive variables commonly used in edge effects models (edge types and distance to a boundary) compared with the smaller scale of local habitat variables, which underlie most species occurrence. We emphasize the need to consider heterogeneity within patches in predictive frameworks of edge effects.!://WOS:000348131500004Times Cited: 0 0921-2973WOS:00034813150000410.1007/s10980-014-0117-9D|?De Keersmaeker, Luc Onkelinx, Thierry De Vos, Bruno Rogiers, Nele Vandekerkhove, Kris Thomaes, Arno De Schrijver, An Hermy, Martin Verheyen, Kris2015The analysis of spatio-temporal forest changes (1775-2000) in Flanders (northern Belgium) indicates habitat-specific levels of fragmentation and area loss247-259Landscape Ecology302Feb^Spatio-temporal forest changes can have a progressive negative impact on the habitat of species that need forest continuity, i.e. the continuous presence of forest. Long-term species data that demonstrate such an impact are often not available. Instead we applied a spatial analysis on maps of the historical and present-day forests, by calculating landscape indices that explain forest plant species diversity. We digitized for this purpose, forests in Flanders (northern Belgium, similar to 13,500 km2) at four time slices (1775, 1850, 1904-1931, 2000) and created a map of forest continuity in 2000. The ecological relevance of the analysis was further enhanced by a site classification, using a map of potential forest habitat types based on soil-vegetation relationships. Our results indicated that, between 1775 and 2000, forests occupied 9.7-12.2 % of the total study area. If continuity was not taken into consideration, forest fragmentation slightly increased since 1775. However, only 16 % of the forest area in 2000 remained continuously present at least since 1775 and is therefore called ancient forest (AF). Moreover, connectivity of forest that originated after 1775, called recent forest, was low and only 14 % was in physical contact with AF. The results were habitat-specific as forest on sites that are potentially suitable for a high number of slow-colonizing species, e.g. ancient forest plants, were affected most. We discuss that a GIS analysis of this kind is essential to provide statistics for forest biodiversity conservation and restoration, in landscapes with a dynamic and heterogeneous forest cover.!://WOS:000348131500005Times Cited: 0 0921-2973WOS:00034813150000510.1007/s10980-014-0119-7T|?Wray, Julie C. Elle, Elizabeth2015nFlowering phenology and nesting resources influence pollinator community composition in a fragmented ecosystem261-272Landscape Ecology302Feb Habitat loss is the leading cause of extinctions on the planet. However, negative effects of habitat loss and fragmentation on biodiversity can be reduced if resources in urban or semi-natural areas in the surrounding matrix can be used by wildlife. We investigated the influence of floral and nesting resources in urban- and forest-associated oak-savannah fragments, surrounding urban and forest matrix, and urban areas spatially independent from oak-savannah habitat on pollinator community composition in a fragmented oak-savannah ecosystem. Both independent urban and urban matrix sites supported high abundance and richness of plants and pollinators relative to other fragment categories, especially towards the end of the season when plants and pollinators in oak-savannah fragments were scarce. A species of particular conservation concern in our region, Bombus occidentalis, was supported by late-flowering resources in our urban sites. Forest-associated oak-savannah fragments were missing late-season species while urban-associated fragments supported high abundance and richness of mid- to late-season pollinators, likely due to supplemental use of floral resources in the urban matrix. Female cavity-nesting and ground-nesting bees were not restricted by the availability of natural nesting resources we expected them to require (e.g. small cavities, bare soil). These results provide important information on native pollinators in a highly fragmented habitat, and suggest that we should consider matrix quality in conservation planning.!://WOS:000348131500006Times Cited: 0 0921-2973WOS:00034813150000610.1007/s10980-014-0121-0Z|?IBakker, Martha M. Alam, Shah Jamal van Dijk, Jerry Rounsevell, Mark D. A.2015QLand-use change arising from rural land exchange: an agent-based simulation model273-286Landscape Ecology302FebLand exchange can be a major factor driving land-use change in regions with high pressure on land, but is generally not incorporated in land-use change models. Here we present an agent-based model to simulate land-use change arising from land exchange between multiple agent types representing farmers, nature organizations, and estate owners. The RULEX model (Rural Land EXchange) was calibrated and applied to a 300 km(2) case study area in the east of the Netherlands. Decision rules about which actor will sell and buy land, as well as which specific land to buy or sell are based on historical observations, interviews, and choice experiments. A reconstruction of land-use change for the period 2001-2009 demonstrates that RULEX reproduces most observed land-use trends and patterns. Given that RULEX simulates only one mechanism of land-use change, i.e. land exchange, it is conservative in simulating change. With this model, we demonstrate the potential of incorporating land market processes in an agent-based, land-use change model. This supports understanding of land-use change that is brought about by ownership change, which is an important process in areas where pressure on land is high. The soundness of the process representation was corroborated by stakeholders within the study area. Land exchange models can be used to assess the impact of changes in climate, markets, and policy on land use change, and help to increase effectiveness of alternative land purchasing strategies by stakeholders or spatial planning policy.!://WOS:000348131500007Times Cited: 1 0921-2973WOS:00034813150000710.1007/s10980-014-0116-x Q|?%Galitsky, Christina Lawler, Joshua J.2015jRelative influence of local and landscape factors on bird communities vary by species and functional group287-299Landscape Ecology302Feb Both fine scale patterns of vegetation and coarser scale landscape patterns affect bird community composition, but the relative importance of these two sets of patterns tends to be context dependent, varying by location and taxonomic group. Here, we explore the relative roles of landscape pattern and stand structure and composition in defining bird communities in 44 remnant oak stands in the Willamette Valley, Oregon. We focused on: (1) whether bird communities are influenced more by landscape (matrix and patch) patterns or stand composition and structure, and (2) in what contexts each of these spatial scales are more important. Specifically, we focused on how different groups of bird species (functional groups, synanthropic and non-synanthropic species, and individual species) were differentially influenced by landscape and more local patterns. We conducted point counts to determine avian abundance, richness and evenness and categorized birds into functional groups based on diet and foraging tactics. We then used canonical correspondence analysis and generalized linear models to analyze overall community patterns, functional group diversity, synanthropic and non synanthropic species diversity and individual species' abundances. Both local and landscape factors significantly influenced each group of avian species for every measure of diversity we tested, but their relative importance varied markedly. Local factors explained four times more variance than landscape factors for overall species diversity, whereas for functional groups, landscape factors explained one quarter to ten times the variance of local factors, depending on the group. For example, landscape factors were five times more important for the corvidae omnivores and ten times more important for the flycatchers than were local factors. By contrast, local factors were twice as important for seed eaters, frugivores and ground foragers, and bark foragers than were landscape patterns. We found the same high variability for individual species. We conclude that the relative contribution of factors at different scales to the structuring of bird communities (as with the effects of so many other ecological processes and patterns) strongly depends on context-in this case, the specific group of species being considered.!://WOS:000348131500008Times Cited: 0 0921-2973WOS:00034813150000810.1007/s10980-014-0138-4|?]Goodsman, Devin W. Goodsman, Jeric S. McKenney, Daniel W. Lieffers, Victor J. Erbilgin, Nadir2015Too much of a good thing: landscape-scale facilitation eventually turns into competition between a lepidopteran defoliator and a bark beetle301-312Landscape Ecology302FebSpecies distributions are influenced by how individuals interact with conspecifics, how they interact with other species, and by abiotic environmental factors. Resolving the nature of interspecific interactions using the relative spatial distributions of multiple species can therefore be considered an inverse problem. We wished to determine whether defoliation by a lepidopteran (Choristoneura biennis [Freeman]) facilitates subsequent spruce beetle (Dendroctonus rufipennis [Kirby]) attack using spatiotemporal infestation patterns. We used convergent cross mapping to probe time series of historical outbreaks of C. biennis and D. rufipennis in British Columbia, Canada, for evidence of interspecific interactions. We then fitted mixed model logistic regressions to spatial outbreak data to determine whether the probability of D. rufipennis infestation is impacted by prior defoliation by C. biennis. Convergent cross-mapping suggested that prior defoliation by C. biennis impacts D. rufipennis populations but this method cannot give information on the nature of the interaction. Our logistic regressions, however, provided insight into the nature of interactions by showing that the odds of moderate D. rufipennis infestation increased after moderate C. biennis infestation but decreased after severe C. biennis outbreaks. Thus, interactions between C. biennis and D. rufipennis are facilitative at moderate severities of C. biennis defoliation, but increasingly competitive as C. biennis outbreak severity increases. Interactions between our study insects shifted from facilitative to competitive depending on outbreak severity-a proxy for population density. Density-dependent shifts from facilitation to competition are likely common in the animal kingdom.!://WOS:000348131500009Times Cited: 0 0921-2973WOS:00034813150000910.1007/s10980-014-0139-3|?VStueve, Kirk M. Hollenhorst, Tom P. Kelly, John R. Johnson, Lucinda B. Host, George E.2015bHigh-resolution maps of forest-urban watersheds present an opportunity for ecologists and managers313-323Landscape Ecology302FebGreen infrastructure may improve water quality and mitigate flooding in forest-urban watersheds, but reliably quantifying all benefits is challenging because most land cover maps depend on moderate- to low-resolution data. Complex and spatially heterogeneous landscapes that typify forest-urban watersheds are not fully represented with these types of data. Hence important questions concerning how green infrastructure influences water quality and quantity at different spatial scales remain unanswered. Demonstrate the feasibility of creating novel high-resolution land cover maps across entire watersheds and highlight deficiencies of standard land cover products. We used object-based image analysis (OBIA) to create high-resolution (0.5 m) land cover maps and detect tree canopy overlapping impervious surfaces for a representative forest-urban watershed in Duluth, MN, USA. Unbiased estimates of accuracy and area were calculated and compared with similar metrics for the 30-m National Land Cover Database (NLCD). Mapping accuracies for the high-resolution land cover and canopy overlap maps were similar to 90 %. Error-adjusted estimates of area indicated that impervious surfaces comprised similar to 21 % of the watershed, tree canopy overlapped similar to 10 % of impervious surfaces, and that three high-resolution land cover classes differed significantly from similar NLCD classes. OBIA can efficiently generate high-resolution land cover products of entire watersheds that are appropriate for research and inclusion in the decision-making process of managers. Metrics derived from these products will likely differ from standard land cover maps and may produce new insights, especially when considering the unprecedented opportunity to evaluate fine-scale spatial heterogeneity across watersheds.!://WOS:000348131500010Times Cited: 0 0921-2973WOS:00034813150001010.1007/s10980-014-0127-7k|?Sandercock, Brett K. Alfaro-Barrios, Matilde Casey, Ashley E. Johnson, Tracey N. Mong, Tony W. Odom, Karan J. Strum, Khara M. Winder, Virginia L.2015Effects of grazing and prescribed fire on resource selection and nest survival of upland sandpipers in an experimental landscape325-337Landscape Ecology302FebConservation of grassland vertebrates requires a mechanistic understanding of the effects of landscape heterogeneity on habitat selection and demographic performance. Our goal was to investigate the effects of rangeland management on resource selection and nest survival of upland sandpipers (Bartramia longicauda). We conducted our project at Konza Prairie, a Long-Term Ecological Research site. The station has 60 experimental units with replicated grazing and fire treatments that create a heterogeneous landscape of different habitat patches. We radio-tracked sandpipers for two breeding seasons (2003-2004, n = 37 birds) and monitored sandpiper nests for eight seasons (2001-2008, n = 246 nests). We used resource utilization functions to examine resource selection with respect to five landscape features. Home ranges of sandpipers were large in contiguous prairie () and explain area-sensitive occurrence in fragmented prairie. Upland sandpipers selected grazed and burned sites with short vegetation within their home range. In contrast, nest site selection was influenced by fire frequency and birds selected infrequently burned sites with greater vegetative structure. Settlement decisions affected fitness because nest survival was low in burned and grazed sites (0.068), but higher in unburned and ungrazed sites (0.201-0.247). Our results raise concerns for conservation because private rangelands managed for livestock production are often homogeneous landscapes with heavy grazing and frequent fires. Rotational grazing and fire could be used to restore heterogeneity to grasslands but the duration of rotation, patch size, and optimal configuration require further investigation.!://WOS:000348131500011Times Cited: 0 0921-2973WOS:00034813150001110.1007/s10980-014-0133-9|?KBecker, Douglas A. Wood, Petra B. Strager, Michael P. Mazzarella, Christine2015Impacts of mountaintop mining on terrestrial ecosystem integrity: identifying landscape thresholds for avian species in the central Appalachians, United States339-356Landscape Ecology302Feb+Mountaintop removal/valley fill (MTR/VF) mining in the central Appalachians is a major driver of landscape change within terrestrial ecosystems. We quantified avian community and individual taxa thresholds in response to changing landscapes from MTR/VF using a Threshold Indicator Taxa Analysis approach. We conducted 50-m fixed radius avian surveys (n = 707) within forest adjacent to mine lands in 2012-2013 and obtained data for additional surveys (n = 905) sampled using comparable methods during 2008-2013. We quantified positive and negative community, habitat guild, and species thresholds in abundance and occurrence for each of five landscape metrics within a 1-km radius of each survey point. Reclaimed mine-dominated landscapes (less forest and more grassland/shrubland cover) elicited more negative (57 %) than positive (39 %) species responses. Negative thresholds for each landscape metric generally occurred at lower values than positive thresholds, thus negatively responding species were detrimentally affected before positively responding species benefitted. Forest interior birds generally responded negatively to landscape metric thresholds, interior edge species responses were mixed, and early successional birds responded positively. The forest interior guild declined most at 4 % forest loss, while the shrubland guild increased greatest after 52 % loss. Based on random forest importance ranks, total amount of landscape grassland/shrubland had the most influence, although this varied by guild. Because of little overlap in habitat requirements, managing landscapes simultaneously to maximally benefit both guilds may not be possible. Our avian thresholds identify single community management targets accounting for scarce species. Guild or individual species thresholds allow for species-specific management.!://WOS:000348131500012Times Cited: 0 0921-2973WOS:00034813150001210.1007/s10980-014-0134-8U|?xKuang, Wenhui Liu, Yue Dou, Yinyin Chi, Wenfeng Chen, Guangsheng Gao, Chengfeng Yang, Tianrong Liu, Jiyuan Zhang, Renhua2015What are hot and what are not in an urban landscape: quantifying and explaining the land surface temperature pattern in Beijing, China357-373Landscape Ecology302FebUnderstanding how landscape components affect the urban heat islands is crucial for urban ecological planning and sustainable development. The purpose of this study was to quantify the spatial pattern of land surface temperatures (LSTs) and associated heat fluxes in relation to land-cover types in Beijing, China, using portable infrared thermometers, thermal infrared imagers, and the moderate resolution imaging spectroradiometer. The spatial differences and the relationships between LSTs and the hierarchical landscape structure were analyzed with in situ observations of surface radiation and heat fluxes. Large LST differences were found among various land-use/land-cover types, urban structures, and building materials. Within the urban area, the mean LST of urban impervious surfaces was about 6-12 A degrees C higher than that of the urban green space. LSTs of built-up areas were on average 3-6 A degrees C higher than LSTs of rural areas. The observations for surface radiation and heat fluxes indicated that the differences were caused by different fractions of sensible heat or latent heat flux in net radiation. LSTs decreased with increasing elevation and normalized difference vegetation index. Variations in building materials and urban structure significantly influenced the spatial pattern of LSTs in urban areas. By contrast, elevation and vegetation cover are the major determinants of the LST pattern in rural areas. To alleviate urban heat island intensity, urban planners and policy makers should pay special attention to the selection of appropriate building materials, the reasonable arrangement of urban structures, and the rational design of landscape components.!://WOS:000348131500013Times Cited: 0 0921-2973WOS:00034813150001310.1007/s10980-014-0128-6|?Jelinski, Dennis E.2015GOn a landscape ecology of a harlequin environment: the marine landscape1-6Landscape Ecology301Jan!://WOS:000347284600001Times Cited: 0 0921-2973WOS:00034728460000110.1007/s10980-014-0109-97|?Cushman, Samuel A.2015pThermodynamics in landscape ecology: the importance of integrating measurement and modeling of landscape entropy7-10Landscape Ecology301Jan!://WOS:000347284600002Times Cited: 0 0921-2973WOS:00034728460000210.1007/s10980-014-0108-x |?>Buergi, Matthias Silbernagel, Janet Wu, Jianguo Kienast, Felix20151Linking ecosystem services with landscape history11-20Landscape Ecology301JanThe concept of ecosystem services (ES) has become widely used because it bridges ecology and economics and links nature to society. ES may evolve over time in dynamic landscapes driven by myriad processes. However, the consequences of changes in key ES has not been considered adequately in current ES research. Here we propose a framework for linking ES with landscape history, which can help us better understand the evolution of ES over time. We illustrate the framework by a case study from Switzerland. Both the capacity of landscapes to supply ES and the realization and recognition of key ES are likely to change over time. This insight should have important implications for landscape sustainability and related scenario studies.!://WOS:000347284600003Times Cited: 0 0921-2973WOS:00034728460000310.1007/s10980-014-0102-3|?tHumphrey, Jonathan W. Watts, Kevin Fuentes-Montemayor, Elisa Macgregor, Nicholas A. Peace, Andrew J. Park, Kirsty J.2015|What can studies of woodland fragmentation and creation tell us about ecological networks? A literature review and synthesis21-50Landscape Ecology301JanMThe development of ecological networks could help reverse the effects of habitat fragmentation on woodland biodiversity in temperate agricultural landscapes. However, efforts to create networks need to be underpinned by clear evidence of the relative efficacy of local (e.g. improving or expanding existing habitat patches) versus landscape-scale actions (e.g. creating new habitat or corridors in the landscape matrix). Using cluster analyses we synthesised the findings of 104 studies, published between 1990 and 2013 focusing on the responses of woodland vascular plant, vertebrate, cryptogam and invertebrate species to local and landscape variables. Species responses (richness, diversity, occurrence) were strongly influenced by patch area, patch characteristics (e.g. stand structure) and isolation (e.g. distance between habitat patches). Patch characteristics were of overriding importance for all species groups, especially cryptogams. Many studies recording significant species responses to patch characteristics did not record significant responses to patch area and vice versa, suggesting that patch area may sometimes act as a surrogate for patch characteristics (i.e. larger patches being of 'better quality'). Ecological continuity was important for vascular plants, but assessed in only a few vertebrate and invertebrate studies. Matrix structure (e.g. presence of corridors) was important for vertebrates, but rarely assessed for other species groups. Actions to develop ecological networks should focus on enhancing the quality and/or size of existing habitat patches and reducing isolation between patches. However, given that very few studies have assessed all local and landscape variables together, further information on the relative impacts of different attributes of ecological networks in temperate agricultural landscapes is urgently needed.!://WOS:000347284600004Times Cited: 0 0921-2973WOS:00034728460000410.1007/s10980-014-0107-yB|?NVranken, Isabelle Baudry, Jacques Aubinet, Marc Visser, Marjolein Bogaert, Jan2015A review on the use of entropy in landscape ecology: heterogeneity, unpredictability, scale dependence and their links with thermodynamics51-65Landscape Ecology301JanThe identification of a universal law that can predict the spatiotemporal structure of any entity at any scale has long been pursued. Thermodynamics have targeted this goal, and the concept of entropy has been widely applied for various disciplines and purposes, including landscape ecology. Within this discipline, however, the uses of the entropy concept and its underlying assumptions are various and are seldom described explicitly. In addition, the link between this concept and thermodynamics is unclear. The aim of this paper is to review the various interpretations and applications of entropy in landscape ecology and to sort them into clearly defined categories. First, a retrospective study of the concept genesis from thermodynamics to landscape ecology was conducted. Then, 50 landscape ecology papers that use or discuss entropy were surveyed and classified by keywords, variables and metrics identified as related to entropy. In particular, the thermodynamic component of entropy in landscape ecology and its various interpretations related to landscape structure and dynamics were considered. From the survey results, three major definitions (i.e., spatial heterogeneity, the unpredictability of pattern dynamics and pattern scale dependence) associated with the entropy concept in landscape ecology were identified. The thermodynamic interpretations of these definitions are based on different theories. The thermodynamic interpretation of spatial heterogeneity is not considered relevant. The thermodynamic interpretation related to scale dependence is also questioned by complexity theory. Only unpredictability can be thermodynamically relevant if appropriate measurements are used to test it.!://WOS:000347284600005Times Cited: 0 0921-2973WOS:00034728460000510.1007/s10980-014-0105-0|?-Mammides, Christos Kadis, Costas Coulson, Tim2015vThe effects of road networks and habitat heterogeneity on the species richness of birds in Natura 2000 sites in Cyprus67-75Landscape Ecology301JanBThe large European supra-national network of protected areas, known as Natura 2000, is considered to be the cornerstone of the European Union's efforts to conserve its biodiversity. The effective management of these areas requires a good understanding of how human-induced ecosystem change, evident in these sites, affects habitats and species of interest. In this study, we examine the factors that influence the presence of birds in thirty-eight Natura 2000 sites in Cyprus. Using structural equation modeling (SEM), we test the direct and indirect effects of human population density, road networks and hunting on the overall species richness of birds and the species richness of four additional bird categories: (1) forest and shrubland species, (2) farmland species, (3) wetland species and (4) species listed in the Annex I of the Birds Directive (2009/147/EC). Other potentially important factors such as size of the area, habitat diversity, percentage of the area covered by migratory corridors and mean altitude, are also incorporated into the analyses. Our results show that road networks have negative effects on four of the five bird categories tested while area and habitat diversity positively influence all categories. These findings have significant conservation implications for the management of the Natura 2000 sites in the EU.!://WOS:000347284600006Times Cited: 0 0921-2973WOS:00034728460000610.1007/s10980-014-0100-5|?PPerez-Hernandez, Christian G. Vergara, Pablo M. Saura, Santiago Hernandez, Jaime2015vDo corridors promote connectivity for bird-dispersed trees? The case of Persea lingue in Chilean fragmented landscapes77-90Landscape Ecology301JanDisentangling the contribution of corridors to landscape connectivity is crucial for adopting efficient measures in conservation, but their actual role in heterogeneous landscapes is not yet fully understood. We assessed the hypothesis that corridors, consisting of hedgerows and riparian vegetation strips, are important landscape elements promoting functional connectivity for the lingue (Persea lingue), a tree endemic to southern Chile and Argentina whose seeds are mainly dispersed by the habitat generalist austral thrush (Turdus falcklandii). For this purpose, we used empirical estimates of seed production, fruit consumption and bird movement patterns, in combination with a seed dispersal model and a graph-theoretical approach for network connectivity analysis. We found that for this plant-animal interaction, the hypothesis mentioned above is not supported. Functional connectivity decreased as the structural connectivity provided by corridors increased, and stepping stones were much more effective connectivity providers than corridors. Our findings are not generalizable to other situations because thrushes contribute to the dispersal of seeds along narrow and sinuous corridors, which provide unsuitable conditions for the establishment of lingues. We conclude that (a) the effectiveness of corridors for promoting connectivity and successful dispersal is landscape- and species-specific; and that (b) effective conservation of Chilean forest biodiversity involves a tradeoff between enhancing the availability of stepping stones and providing corridors of sufficient width and appropriate shape to meet the needs and dispersal modalities of different species.!://WOS:000347284600007Times Cited: 0 0921-2973WOS:00034728460000710.1007/s10980-014-0111-2|?KMiddleton, Nick Rueff, Henri Sternberg, Troy Batbuyan, Batjav Thomas, David2015KExplaining spatial variations in climate hazard impacts in western Mongolia91-107Landscape Ecology301JanThe winter of 2009/2010 induced a mass loss of livestock known as dzud in Mongolia. We examine spatial heterogeneity in this livestock loss in a western Mongolian province using a semi-structured questionnaire, key informant interviews, meteorological station data, and two datasets derived from satellite imagery. We identify marked local variability in the impact of winter 2009/2010 demonstrated by a striking difference in livestock mortality between three Altai mountain districts and three Gobi desert districts. We explain this pattern with reference to site-specific circumstances. We ascertain a counter-intuitive pattern of milder winters with less snow in Mountain districts when compared to Desert districts, a contrast that was particularly acute in the winter of 2009/2010 which was uncommonly long and hard, with particularly deep and widespread snow cover in the Desert, but unusually mild in the Mountains. Examination of possible drivers of dzud vulnerability at the household and community levels-wealth and herder experience-found virtually no influence on livestock losses, although a large majority of herder households were characterised by a general lack of alternative income opportunities. The severity of conditions undermined many Desert herders' coping and adaptive strategies, including communal pooling, although those who managed to move their herds in response to the 2009/2010 dzud suffered markedly smaller livestock losses. Limited government capacity, partly influenced by remoteness, further increased vulnerability in the Desert districts where the deep snow restricted access to dzud relief assistance. Implications for hazard management and governance are discussed, as are recent policy initiatives.!://WOS:000347284600008Times Cited: 0 0921-2973WOS:00034728460000810.1007/s10980-014-0091-2|?TXie, Yingying Ahmed, Kazi F. Allen, Jenica M. Wilson, Adam M. Silander, John A., Jr.2015zGreen-up of deciduous forest communities of northeastern North America in response to climate variation and climate change109-123Landscape Ecology301JanHTemporal shifts in phenology are important biotic indicators of climate change. Satellite-derived Land Surface Phenology (LSP) offers data for the study of vegetation phenology at landscape to global spatial scales. However, the mechanisms of plant phenological responses to temperature are rarely considered at broad spatial scales, despite the potential improvements to spatiotemporal predictions. Geographical gradients in community species composition may also affect LSP spatially and temporally. Using a modified survival analysis, we reveal how weather and climate relate to physiological chilling and heating requirements and affect deciduous forest green-up in New England, USA over 9 years (2001-2009). While warm daily temperatures lead to earlier green-up of deciduous forests, chilling temperatures had a larger influence on green-up. We also found that the effects of community composition across the landscape were as important as the effects of weather. Greater oak dominance led to later green-up, while sites with more birch tended to have earlier green-up dates. Projection into the future (2046-2065) with statistically downscaled, bias corrected climate model output suggested advanced green-up (8-48 days) driven by higher heating and chilling accumulations, but green-up in coastal areas may be delayed due to reduced chilling accumulation. This study provides an innovative statistical method combining plant physiological mechanisms, topographic spatial heterogeneity, and species composition to predict how LSP responds to climate and weather variation and makes future projections.!://WOS:000347284600009Times Cited: 0 0921-2973WOS:00034728460000910.1007/s10980-014-0099-7]|??Puech, Camille Poggi, Sylvain Baudry, Jacques Aviron, Stephanie2015CDo farming practices affect natural enemies at the landscape scale?125-140Landscape Ecology301Jan Farming practices are rarely considered in the description of agricultural landscapes. However, the variety of cropping systems creates a particular kind of heterogeneity which can strongly affect the diversity of species living in agro-ecosystems, and consequently the ecosystem services they provide. In this study, we investigate the effects of landscape composition and configuration of organic and conventional farming practices on three groups of aphids' natural enemies, compared to field habitat quality and land cover heterogeneity. A field survey was carried out in 2012 and 2013 in western France (Brittany). Ladybirds, carabid beetles and parasitoids were sampled in 40 pairs of organic and conventional winter wheat fields, distributed along a landscape gradient of organic farming areas. The relationships between farming practices and natural enemies were investigated with a PLS-path modeling approach, hardly ever used in ecology but presenting numerous advantages to analyze multivariate systems. Results showed that abundance and species richness of natural enemies were mainly affected by local farming practices, with a higher diversity in organic fields. To a lesser extent, landscapes also affected natural enemies, but only in relation to the length and configuration of hedgerows. Our results open up avenues for the design of agricultural landscapes since our results suggest that natural enemy diversity can be enhanced without a specific organization of organic fields. We discuss methodological issues regarding the description and the analysis of farming practices at the landscape scale. We argue that such investigations require high quality maps covering large spatial extents, and the use of statistical tools providing a good handling of complex relationships occurring in agro-ecosystems.!://WOS:000347284600010Times Cited: 0 0921-2973WOS:00034728460001010.1007/s10980-014-0103-2$|?@Gould, Susan F. Hugh, Sonia Porfirio, Luciana L. Mackey, Brendan2015(Ecosystem greenspots pass the first test141-151Landscape Ecology301JanGiven climate change projections, the ability to identify locations that provide refuge under drought conditions is an urgent conservation priority. Previously, it has been proposed that the ecosystem greenspot index could be used to identify locations that currently function as habitat refuges from drought and fire. If this is true, these locations may have the potential to function as climate-change micro-refuges. In this study we aimed to: (1) test whether ecosystem greenspot indices are related to vegetation specific gradients of habitat resources; and (2) identify environmental correlates of the ecosystem greenspots. Ecosystem greenspot indices were calculated for two vegetation types: a woodland and a grassland, and compared with in situ data on vegetation structure. There were inaccuracies in the identification of the grassland greenspot index due to fine scale spatial heterogeneity and misclassification. However, the woodland greenspot index accurately identified vegetation specific gradients in the biomass of the relevant framework species. The spatial distribution of woodland greenspots was related to interacting rainfall, soil and landscape variables. The ability to provide information about variation in resources, and hence habitat quality, within specific vegetation types has immediate applications for conservation planning. This is the first step toward validating whether the ecosystem greenspot index of Mackey et al. (Ecol Appl 22:1852-1864, 2012) can identify potential drought micro-refuges. More work is needed to (1) address sources of error in identifying specific vegetation types; (2) refine the analysis and field validation methods for grasslands; and (3) to test whether species persistence during drought is supported by identified greenspots.!://WOS:000347284600011Times Cited: 0 0921-2973WOS:00034728460001110.1007/s10980-014-0112-1|??Shanahan, D. F. Lin, B. B. Gaston, K. J. Bush, R. Fuller, R. A.2015UWhat is the role of trees and remnant vegetation in attracting people to urban parks?153-165Landscape Ecology301JanzPublic parks commonly contain important habitat for urban biodiversity, and they also provide recreation opportunities for urban residents. However, the extent to which dual outcomes for recreation and conservation can be achieved in the same spaces remains unclear. We examine whether greater levels of (i) tree cover (i.e. park 'greenness') and (ii) native remnant vegetation cover (i.e. vegetation with high ecological value) attract or deter park visitors. This study is based on the park visitation behaviour of 670 survey respondents in Brisbane, Australia, detailing 1,090 individual visits to 324 urban parks. We first examined the presence of any clear revealed preferences for visiting parks with higher or lower levels of tree cover or remnant vegetation cover. We then examined the differences between each park visited by respondents and the park closest to their home, and used linear mixed models to identify socio-demographic groups who are more likely to travel further to visit parks with greater tree cover or remnant vegetation cover. Park visitation rates reflected the availability of parks, suggesting that people do not preferentially visit parks with greater vegetation cover despite the potential for improved nature-based experiences and greater wellbeing benefits. However, we discovered that people with a greater orientation towards nature (measured using the nature relatedness scale) tend to travel further for more vegetated parks. Our results suggest that to enhance recreational benefits from ecologically valuable spaces a range of social or educational interventions are required to enhance people's connection to nature.!://WOS:000347284600012Times Cited: 1 0921-2973WOS:00034728460001210.1007/s10980-014-0113-0|?7Lemessa, Debissa Hamback, Peter A. Hylander, Kristoffer2015yThe effect of local and landscape level land-use composition on predatory arthropods in a tropical agricultural landscape167-180Landscape Ecology301Jan~It has been suggested that the composition of different non-crop land-use types along with tree density regulate local biodiversity in agricultural landscapes. However, specific data is limited, not least from tropical regions. We examined how different land-use types and forest cover at different scales influenced the abundance and species composition of predatory arthropods in 40 homegardens of southwest Ethiopia. We collected specimens using pitfall traps during two separate months and related sample composition to land-use in the vicinity (1 ha plot, local scale, field data) and tree cover within 200 and 500 m radius zones (landscape scale, satellite data). Spiders, beetles and ants were most common. A high abundance of ants was found in tree-rich homegardens while the variation in abundance of spiders was best explained by the interaction between tree cover at the local and landscape scales. The highest spider abundances were found when either the homegarden or the surroundings had high tree-cover and was lower in both the most tree-rich and tree-poor landscape-garden combinations. In addition, open non-crop cover (mostly grasslands) and ensete (a banana-like perennial crop) favored spiders. This pattern demonstrates that different land-use types at different scales can interact to create variations in biodiversity across an agricultural landscape. To enhance numbers of predatory arthropods in homegardens, which may be beneficial for natural pest control, our results suggest that different strategies are needed depending on the target group or species. Grasslands, ensete fields and tree-rich habitats seem to play important roles.!://WOS:000347284600013Times Cited: 0 0921-2973WOS:00034728460001310.1007/s10980-014-0115-y|?Du Preez, Cherisse2015lA new arc-chord ratio (ACR) rugosity index for quantifying three-dimensional landscape structural complexity181-192Landscape Ecology301JanRugosity is an index of surface roughness that is widely used as a measure of landscape structural complexity in studies investigating spatially explicit ecological patterns and processes. This paper identifies and demonstrates significant issues with how we presently measure rugosity and, by building on recent advances, proposes a novel rugosity index that overcomes these issues. The new arc-chord ratio (ACR) rugosity index is defined as the contoured area of the surface divided by the area of the surface orthogonally projected onto a plane of best fit (POBF), where the POBF is a function (interpolation) of the boundary data only. The ACR method is described in general, so that it may be applied to a range of rugosity analyses, and its application is detailed for three common analyses: (a) measuring the rugosity of a two-dimensional profile, (b) generating a rugosity raster from an elevation raster (a three-dimensional analysis), and (c) measuring the rugosity of a three-dimensional surface. Two case studies are used to compare the ACR rugosity index with the rugosity index most commonly used (i.e. surface ratio rugosity), demonstrating the advantages of the ACR index. The ACR method for quantifying rugosity is simple, accurate, extremely versatile, and consistent in its principles independent of data dimensionality (2-D or 3-D), scale and analysis software used. It overcomes significant issues presented by traditional rugosity indices (e.g. decouples rugosity from slope) and is a promising new landscape metric. To further increase ease of use I provide multiple ArcGIS(A (R)) resources in the electronic supplementary materials (e.g. Online Appendix 1: a downloadable ArcToolbox containing two ACR rugosity geoprocessing model tools).!://WOS:000347284600014Times Cited: 0 0921-2973WOS:00034728460001410.1007/s10980-014-0118-80۽7c0Gutzwiller, KevinJ Dibble, EricD Franklin, Janet2015,In memoriam: Samuel K. Riffell (1970–2014)959-962Landscape Ecology306Springer Netherlands 2015/07/01+http://dx.doi.org/10.1007/s10980-015-0202-8 0921-2973Landscape Ecol10.1007/s10980-015-0202-8Englishڽ7dCumming, GraemeS Abolnik, Celia Caron, Alexandre Gaidet, Nicolas Grewar, John Hellard, Eléonore Henry, DominicA W. Reynolds, Chevonne2015bA social–ecological approach to landscape epidemiology: geographic variation and avian influenza963-985Landscape Ecology306Springer Netherlands3Disease Zoonosis Pathogen Scale Anatidae Complexity 2015/07/01+http://dx.doi.org/10.1007/s10980-015-0182-8 0921-2973Landscape Ecol10.1007/s10980-015-0182-8English۽7eCumming, GraemeS Abolnik, Celia Caron, Alexandre Gaidet, Nicolas Grewar, John Hellard, Eléonore Henry, DominicA W. Reynolds, Chevonne2015nErratum to: A social–ecological approach to landscape epidemiology: geographic variation and avian influenza987-987Landscape Ecology306Springer Netherlands 2015/07/01+http://dx.doi.org/10.1007/s10980-015-0204-6 0921-2973Landscape Ecol10.1007/s10980-015-0204-6English1ڽ7fzRees, E. E. St-Hilaire, S. Jones, S. R. M. Krkošek, M. DeDominicis, S. Foreman, M. G. G. Patanasatienkul, T. Revie, C. W.2015VSpatial patterns of sea lice infection among wild and captive salmon in western Canada989-1004Landscape Ecology306Springer NetherlandsAtlantic salmon aquaculture British Columbia Caligus clemensi Lepeophtheirus salmonis Pacific salmon Sea lice Spatial–temporal modeling 2015/07/01+http://dx.doi.org/10.1007/s10980-015-0188-2 0921-2973Landscape Ecol10.1007/s10980-015-0188-2Englishڽ7gRoach, JenniferK Griffith, Brad2015YClimate-induced lake drying causes heterogeneous reductions in waterfowl species richness 1005-1022Landscape Ecology306Springer NetherlandsNAlaska Biodiversity Climate warming Lake change Lake size Species–area curve 2015/07/01+http://dx.doi.org/10.1007/s10980-015-0207-3 0921-2973Landscape Ecol10.1007/s10980-015-0207-3Englishڽ7hAlbano, ChristineM2015Identification of geophysically diverse locations that may facilitate species’ persistence and adaptation to climate change in the southwestern United States 1023-1037Landscape Ecology306Springer NetherlandsPClimate adaptation Climate change Geophysical diversity Gap analysis Land facets 2015/07/01+http://dx.doi.org/10.1007/s10980-015-0167-7 0921-2973Landscape Ecol10.1007/s10980-015-0167-7Englishڽ7iHSerra-Diaz, JosepM Scheller, RobertM Syphard, AlexandraD Franklin, Janet2015TDisturbance and climate microrefugia mediate tree range shifts during climate change 1039-1053Landscape Ecology306Springer Netherlands@Climate change Forest dynamics LANDIS-II Range change Succession 2015/07/01+http://dx.doi.org/10.1007/s10980-015-0173-9 0921-2973Landscape Ecol10.1007/s10980-015-0173-9Englishڽ7j_Yang, Jian Weisberg, PeterJ Shinneman, DouglasJ Dilts, ThomasE Earnst, SusanL Scheller, RobertM2015Fire modulates climate change response of simulated aspen distribution across topoclimatic gradients in a semi-arid montane landscape 1055-1073Landscape Ecology306Springer Netherlands]Quaking aspen Fire disturbance Gradient analysis Great Basin LANDIS-II Climatic water deficit 2015/07/01+http://dx.doi.org/10.1007/s10980-015-0160-1 0921-2973Landscape Ecol10.1007/s10980-015-0160-1Englishڽ7k<Weed, AaronS Bentz, BarbaraJ Ayres, MatthewP Holmes, ThomasP2015jGeographically variable response of Dendroctonus ponderosae to winter warming in the western United States 1075-1093Landscape Ecology306Springer NetherlandsdClimate change Demography Mountain pine beetle Process-based model Bark beetles Pinus Cold tolerance 2015/07/01+http://dx.doi.org/10.1007/s10980-015-0170-z 0921-2973Landscape Ecol10.1007/s10980-015-0170-zEnglishڽ7lBateman, BrookeL Pidgeon, AnnaM Radeloff, VolkerC Allstadt, AndrewJ Resit Akçakaya, H. Thogmartin, WayneE Vavrus, StephenJ Heglund, PatriciaJ2015TThe importance of range edges for an irruptive species during extreme weather events 1095-1110Landscape Ecology306Springer NetherlandsEDrought Extreme weather Grassland birds Range edge Range core Refuges 2015/07/01+http://dx.doi.org/10.1007/s10980-015-0212-6 0921-2973Landscape Ecol10.1007/s10980-015-0212-6Englishڽ7m>Van Den Hoek, Jamon Burnicki, AmyC Ozdogan, Mutlu Zhu, A. Xing2015oUsing a pattern metric-based analysis to examine the success of forest policy implementation in Southwest China 1111-1127Landscape Ecology306Springer Netherlands]Pattern analysis Forest policy NFPP SLCP Forest cover change Temporal resolution Yunnan China 2015/07/01+http://dx.doi.org/10.1007/s10980-015-0171-y 0921-2973Landscape Ecol10.1007/s10980-015-0171-yEnglishڽ7nQMartin, SherryL Jasinski, BrianaL Kendall, AnthonyD Dahl, TravisA Hyndman, DavidW2015zQuantifying beaver dam dynamics and sediment retention using aerial imagery, habitat characteristics, and economic drivers 1129-1144Landscape Ecology306Springer NetherlandsVAerial imagery Spatial GIS analysis Beaver population dynamics Hydrology Sedimentation 2015/07/01+http://dx.doi.org/10.1007/s10980-015-0165-9 0921-2973Landscape Ecol10.1007/s10980-015-0165-9Englishڽ7o6Bastian, Olaf Grunewald, Karsten Khoroshev, AlexanderV2015The significance of geosystem and landscape concepts for the assessment of ecosystem services: exemplified in a case study in Russia 1145-1164Landscape Ecology307Springer NetherlandsmLandscape genesis Landscape units River basins Catena Natural potentials Spatial scales Forestry Water runoff 2015/08/01+http://dx.doi.org/10.1007/s10980-015-0200-x 0921-2973Landscape Ecol10.1007/s10980-015-0200-xEnglishڽ7p8Qian, Yuguo Zhou, Weiqi Yu, Wenjuan Pickett, StewardT A.2015^Quantifying spatiotemporal pattern of urban greenspace: new insights from high resolution data 1165-1173Landscape Ecology307Springer NetherlandsZWithin-city dynamics Beijing Urban sustainability Ecosystem services Scale Urban landscape 2015/08/01+http://dx.doi.org/10.1007/s10980-015-0195-3 0921-2973Landscape Ecol10.1007/s10980-015-0195-3Englishڽ7q!Huang, Lu Wu, Jianguo Yan, Lijiao2015CDefining and measuring urban sustainability: a review of indicators 1175-1193Landscape Ecology307Springer NetherlandsmUrbanization Urban sustainability indicators Indicator frameworks Sustainable cities Landscape sustainability 2015/08/01+http://dx.doi.org/10.1007/s10980-015-0208-2 0921-2973Landscape Ecol10.1007/s10980-015-0208-2Englishڽ7r3Baur, AlbertH Förster, Michael Kleinschmit, Birgit2015The spatial dimension of urban greenhouse gas emissions: analyzing the influence of spatial structures and LULC patterns in European cities 1195-1205Landscape Ecology307Springer Netherlands^Climate change mitigation Urban design Landscape metrics Urban form Urban shape Urban planning 2015/08/01+http://dx.doi.org/10.1007/s10980-015-0169-5 0921-2973Landscape Ecol10.1007/s10980-015-0169-5Englishڽ7sJim, C. Y. Zhang, Hao2015HEffect of habitat traits on tree structure and growth in private gardens 1207-1223Landscape Ecology307Springer NetherlandssSpecies composition Tree habitat Tree structural damage Tree health condition Domestic garden Urban tree management 2015/08/01+http://dx.doi.org/10.1007/s10980-015-0179-3 0921-2973Landscape Ecol10.1007/s10980-015-0179-3Englishbڽ7tcEhlers Smith, YvetteC Ehlers Smith, DavidA Seymour, ColleenL Thébault, Elisa van Veen, F. J. Frank2015wResponse of avian diversity to habitat modification can be predicted from life-history traits and ecological attributes 1225-1239Landscape Ecology307Springer NetherlandsAgroecosystem Anthropogenic habitats Ecological attributes Functional diversity Functional traits Habitat heterogeneity Life history traits Habitat transformation RLQ analysis 2015/08/01+http://dx.doi.org/10.1007/s10980-015-0172-x 0921-2973Landscape Ecol10.1007/s10980-015-0172-xEnglishڽ7u)MacLean, MeghanGraham Congalton, RussellG2015A comparison of landscape fragmentation analysis programs for identifying possible invasive plant species locations in forest edge 1241-1256Landscape Ecology307Springer NetherlandsuAccuracy assessment Edge Fragmentation FRAGSTATS Invasive plants Landscape metrics New England PolyFrag Raster Vector 2015/08/01+http://dx.doi.org/10.1007/s10980-015-0175-7 0921-2973Landscape Ecol10.1007/s10980-015-0175-7Englishڽ7v5Halsey, ShilohM Zielinski, WilliamJ Scheller, RobertM2015<Modeling predator habitat to enhance reintroduction planning 1257-1271Landscape Ecology307Springer NetherlandskFisher (Pekania pennanti) Bobcat (Lynx rufus) Reintroduction Predation Habitat modeling Classification tree 2015/08/01+http://dx.doi.org/10.1007/s10980-015-0177-5 0921-2973Landscape Ecol10.1007/s10980-015-0177-5Englishڽ7w;Richmond, Sonya Jenkins, Eva Couturier, Andrew Cadman, Mike2015`Thresholds in forest bird richness in response to three types of forest cover in Ontario, Canada 1273-1290Landscape Ecology307Springer NetherlandsYForest-breeding birds Habitat amount Habitat loss Species richness Threshold Forest cover 2015/08/01+http://dx.doi.org/10.1007/s10980-015-0183-7 0921-2973Landscape Ecol10.1007/s10980-015-0183-7Englishڽ7xCMeyer, SpencerR Beard, Kate Cronan, ChristopherS Lilieholm, RobertJ2015jAn analysis of spatio-temporal landscape patterns for protected areas in northern New England: 1900–2010 1291-1305Landscape Ecology307Springer NetherlandskLarge landscape conservation Pattern analysis Spatial autocorrelation Conservation easements Reserve design 2015/08/01+http://dx.doi.org/10.1007/s10980-015-0184-6 0921-2973Landscape Ecol10.1007/s10980-015-0184-6Englishڽ7y.Cooney, ScottA Schauber, EricM Hellgren, EricC2015XComparing permeability of matrix cover types for the marsh rice rat (Oryzomys palustris) 1307-1320Landscape Ecology307Springer Netherlands?Agriculture Connectivity Edge Movement Perceptual range Wetland 2015/08/01+http://dx.doi.org/10.1007/s10980-015-0185-5 0921-2973Landscape Ecol10.1007/s10980-015-0185-5Englishڽ7z,Bürgi, Matthias Salzmann, Daniel Gimmi, Urs2015c264 years of change and persistence in an agrarian landscape: a case study from the Swiss lowlands 1321-1333Landscape Ecology307Springer NetherlandsaLandscape history Rates of change Driving forces Historical maps Agricultural history Switzerland 2015/08/01+http://dx.doi.org/10.1007/s10980-015-0189-1 0921-2973Landscape Ecol10.1007/s10980-015-0189-1Englishڽ7{HGrilli, MarianoP Pedemonte, MaríaLaura Bruno, Marina Fachinetti, Romina2015cThe effect of landscape structure on two species of different trophic levels in an arid environment 1335-1349Landscape Ecology307Springer NetherlandsZSiphoninus phillyreae Clitostethus arcuatus Olive patches Dry land Landscape configuration 2015/08/01+http://dx.doi.org/10.1007/s10980-015-0190-8 0921-2973Landscape Ecol10.1007/s10980-015-0190-8Englishڽ7|With, KimberlyA2015\How fast do migratory songbirds have to adapt to keep pace with rapidly changing landscapes? 1351-1361Landscape Ecology307Springer NetherlandsAdaptive response Edge effects Habitat loss Habitat fragmentation Landscape dynamics Phenotypic plasticity Spatially-structured population model 2015/08/01+http://dx.doi.org/10.1007/s10980-015-0191-7 0921-2973Landscape Ecol10.1007/s10980-015-0191-7Englishsڽ7}Collier, MarcusJ20151Novel ecosystems and social-ecological resilience 1363-1369Landscape Ecology308Springer NetherlandsYNovel ecosystems Resilience Social-ecological systems Transitioning Transitory landscapes 2015/10/01+http://dx.doi.org/10.1007/s10980-015-0243-z 0921-2973Landscape Ecol10.1007/s10980-015-0243-zEnglish ڽ7~-Hicks, JosephP Hails, RosemaryS Sait, StevenM2015hScale-dependent, contrasting effects of habitat fragmentation on host-natural enemy trophic interactions 1371-1385Landscape Ecology308Springer NetherlandsBiotic interactions Habitat connectivity Habitat loss Host-parasite Host-parasitoid Host-pathogen Landscape epidemiology Natural enemies Species interactions 2015/10/01+http://dx.doi.org/10.1007/s10980-015-0192-6 0921-2973Landscape Ecol10.1007/s10980-015-0192-6English(ڽ7uIkin, Karen Mortelliti, Alessio Stein, John Michael, Damian Crane, Mason Okada, Sachiko Wood, Jeff Lindenmayer, David2015dWoodland habitat structures are affected by both agricultural land management and abiotic conditions 1387-1403Landscape Ecology308Springer NetherlandsvAgricultural intensification Conservation Habitat loss and fragmentation Patch quality Ecosystem restoration Australia 2015/10/01+http://dx.doi.org/10.1007/s10980-015-0193-5 0921-2973Landscape Ecol10.1007/s10980-015-0193-5English7ڽ7hMateo-Sánchez, MaríaC Balkenhol, Niko Cushman, Samuel Pérez, Trinidad Domínguez, Ana Saura, Santiago2015A comparative framework to infer landscape effects on population genetic structure: are habitat suitability models effective in explaining gene flow? 1405-1420Landscape Ecology308Springer NetherlandsaGene flow Habitat suitability Landscape resistance Species movement Landscape genetics Brown bear 2015/10/01+http://dx.doi.org/10.1007/s10980-015-0194-4 0921-2973Landscape Ecol10.1007/s10980-015-0194-4Englishڽ7-Fernandes, Izaias Penha, Jerry Zuanon, Jansen2015tSize-dependent response of tropical wetland fish communities to changes in vegetation cover and habitat connectivity 1421-1434Landscape Ecology308Springer NetherlandswTemporary habitat Effective distance Landscape connectivity Exotic species Water depth Cattle ranching impacts Pantanal 2015/10/01+http://dx.doi.org/10.1007/s10980-015-0196-2 0921-2973Landscape Ecol10.1007/s10980-015-0196-2English3ڽ7Toma, Yuichi Imanishi, Junichi Yokogawa, Masashi Hashimoto, Hiroshi Imanishi, Ayumi Morimoto, Yukihiro Hatanaka, Yuki Isagi, Yuji Shibata, Shozo2015Factors affecting the genetic diversity of a perennial herb Viola grypoceras A. Gray var. grypoceras in urban fragmented forests 1435-1447Landscape Ecology308Springer NetherlandsJHabitat fragmentation Urbanization Genetic variation Spatial variables SSR 2015/10/01+http://dx.doi.org/10.1007/s10980-015-0197-1 0921-2973Landscape Ecol10.1007/s10980-015-0197-1Englishڽ7Watling, JamesI Braga, Lorenzo2015aDesiccation resistance explains amphibian distributions in a fragmented tropical forest landscape 1449-1459Landscape Ecology308Springer NetherlandsKConnectivity Conservation physiology Movement Permeability Trait Water loss 2015/10/01+http://dx.doi.org/10.1007/s10980-015-0198-0 0921-2973Landscape Ecol10.1007/s10980-015-0198-0Englishڽ7qEglington, SarahM Brereton, TomM Tayleur, CatherineM Noble, David Risely, Kate Roy, DavidB Pearce-Higgins, JamesW2015LPatterns and causes of covariation in bird and butterfly community structure 1461-1472Landscape Ecology308Springer NetherlandsaCitizen science Community specialisation Diversity Evenness Species richness Surrogacy approaches 2015/10/01+http://dx.doi.org/10.1007/s10980-015-0199-z 0921-2973Landscape Ecol10.1007/s10980-015-0199-zEnglishtڽ7Hanberry, BriceB He, HongS2015LEffects of historical and current disturbance on forest biomass in Minnesota 1473-1482Landscape Ecology308Springer Netherlands5Carbon Densification Fire Harvest Land use Management 2015/10/01+http://dx.doi.org/10.1007/s10980-015-0201-9 0921-2973Landscape Ecol10.1007/s10980-015-0201-9Englishڽ7yDorresteijn, Ine Teixeira, Lucas von Wehrden, Henrik Loos, Jacqueline Hanspach, Jan Stein, JohnAntonRobert Fischer, Joern2015XImpact of land cover homogenization on the Corncrake (Crex crex) in traditional farmland 1483-1495Landscape Ecology308Springer NetherlandsuDistribution modelling Eastern Europe Grassland birds Land cover change Landscape composition Landscape heterogeneity 2015/10/01+http://dx.doi.org/10.1007/s10980-015-0203-7 0921-2973Landscape Ecol10.1007/s10980-015-0203-7Englishڽ7UDarby, PhilipC DeAngelis, DonaldL Romañach, StephanieS Suir, Kevin Bridevaux, Joshua2015DModeling apple snail population dynamics on the Everglades landscape 1497-1510Landscape Ecology308Springer Netherlands|Pomacea paludosa Population matrix model Distribution Abundance Florida Wetlands Hydrology Management Restoration Snail kite 2015/10/01+http://dx.doi.org/10.1007/s10980-015-0205-5 0921-2973Landscape Ecol10.1007/s10980-015-0205-5Englishڽ7Martins da Silva, Pedro Berg, MattyP da Silva, AntónioAlves Dias, Susana Leitão, PedroJ Chamberlain, Dan Niemelä, Jari Serrano, ArturR M. Sousa, JoséPaulo2015Soil fauna through the landscape window: factors shaping surface-and soil-dwelling communities across spatial scales in cork-oak mosaics 1511-1526Landscape Ecology308Springer NetherlandsCarabidae Collembola Community structure Dispersal ability Environmental factors Landscape metrics Mediterranean region Multiscale analysis Spatial modelling Variance partitioning 2015/10/01+http://dx.doi.org/10.1007/s10980-015-0206-4 0921-2973Landscape Ecol10.1007/s10980-015-0206-4Englishڽ7USkarin, Anna Nellemann, Christian Rönnegård, Lars Sandström, Per Lundqvist, Henrik2015HWind farm construction impacts reindeer migration and movement corridors 1527-1540Landscape Ecology308Springer NetherlandsYRangifer Disturbance Anthropogenic development Step length GPS collars Cumulative effects 2015/10/01+http://dx.doi.org/10.1007/s10980-015-0210-8 0921-2973Landscape Ecol10.1007/s10980-015-0210-8English ڽ7lZhao, Shuqing Zhou, Decheng Zhu, Chao Qu, Wenyuan Zhao, Jiajia Sun, Yan Huang, Dian Wu, Wenjia Liu, Shuguang2015^Rates and patterns of urban expansion in China’s 32 major cities over the past three decades 1541-1559Landscape Ecology308Springer NetherlandshUrbanization Spatiotemporal dynamics Remote sensing Urban growth modes Patch structure Self-organization 2015/10/01+http://dx.doi.org/10.1007/s10980-015-0211-7 0921-2973Landscape Ecol10.1007/s10980-015-0211-7Englishڽ7.Rodríguez-San Pedro, Annia Simonetti, JavierA2015nThe relative influence of forest loss and fragmentation on insectivorous bats: does the type of matrix matter? 1561-1572Landscape Ecology308Springer Netherlands`Habitat fragmentation Habitat loss Landscape matrix Insectivorous bats Scale-dependent responses 2015/10/01+http://dx.doi.org/10.1007/s10980-015-0213-5 0921-2973Landscape Ecol10.1007/s10980-015-0213-5Englishڽ71Hessburg, PaulF Churchill, DerekJ Larson, AndrewJ Haugo, RyanD Miller, Carol Spies, ThomasA North, MalcolmP Povak, NicholasA Belote, R. Travis Singleton, PeterH Gaines, WilliamL Keane, RobertE Aplet, GregoryH Stephens, ScottL Morgan, Penelope Bisson, PeterA Rieman, BruceE Salter, R. Brion Reeves, GordonH2015ERestoring fire-prone Inland Pacific landscapes: seven core principles 1805-1835Landscape Ecology3010Springer NetherlandsForest and rangeland restoration Hierarchical organization Large fires Patch size distributions Successional patches Topographic controls 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0218-0 0921-2973Landscape Ecol10.1007/s10980-015-0218-0Englishڽ7AShirk, AndrewJ Schroeder, MichaelA Robb, LeslieA Cushman, SamuelA2015vEmpirical validation of landscape resistance models: insights from the Greater Sage-Grouse (Centrocercus urophasianus) 1837-1850Landscape Ecology3010Springer NetherlandsZCentrocercus urophasianus Greater Sage-Grouse Landscape genetics Lek Resistance Validation 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0214-4 0921-2973Landscape Ecol10.1007/s10980-015-0214-4Englishڽ7jRüdisser, Johannes Walde, Janette Tasser, Erich Frühauf, Johannes Teufelbauer, Norbert Tappeiner, Ulrike2015XBiodiversity in cultural landscapes: influence of land use intensity on bird assemblages 1851-1863Landscape Ecology3010Springer NetherlandsjBiodiversity indicator Naturalness Random effects hurdle model Scale Landscape metrics European Bird Index 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0215-3 0921-2973Landscape Ecol10.1007/s10980-015-0215-3Englisheڽ7`Moriarty, KatieM Epps, ClintonW Betts, MatthewG Hance, DaltonJ Bailey, J. D. Zielinski, WilliamJ2015Experimental evidence that simplified forest structure interacts with snow cover to influence functional connectivity for Pacific martens 1865-1877Landscape Ecology3010Springer NetherlandsConnectivity Forest management Fuel reduction Functional connectivity Landscape fragmentation Martes americana Martes caurina Marten Movement Titration experiment 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0216-2 0921-2973Landscape Ecol10.1007/s10980-015-0216-2English8ڽ7USchneiderman, JeffreyE He, HongS Thompson, FrankR, III Dijak, WilliamD Fraser, JacobS2015Comparison of a species distribution model and a process model from a hierarchical perspective to quantify effects of projected climate change on tree species 1879-1892Landscape Ecology3010Springer NetherlandskClimate change LINKAGES 2.2 Climate Change Tree Atlas Hierarchical Process model Species distribution model 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0217-1 0921-2973Landscape Ecol10.1007/s10980-015-0217-1Englishڽ7\Yuan, Jing Cohen, MatthewJ Kaplan, DavidA Acharya, Subodh Larsen, LaurelG Nungesser, MarthaK2015OLinking metrics of landscape pattern to hydrological process in a lotic wetland 1893-1912Landscape Ecology3010Springer NetherlandsVSpatial metrics Connectivity Hydrology Hydroperiod Ridge and slough Wetland Everglades 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0219-z 0921-2973Landscape Ecol10.1007/s10980-015-0219-zEnglishڽ7Boucher, Dominique De Grandpré, Louis Kneeshaw, Daniel St-Onge, Benoît Ruel, Jean-Claude Waldron, Kaysandra Lussier, Jean-Martin2015rEffects of 80 years of forest management on landscape structure and pattern in the eastern Canadian boreal forest 1913-1929Landscape Ecology3010Springer NetherlandsMLogging Fires Multi-scale Heterogeneity Forest composition Old-growth forests 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0220-6 0921-2973Landscape Ecol10.1007/s10980-015-0220-6Englishڽ7DRanius, Thomas Johansson, Victor Schroeder, Martin Caruso, Alexandro2015uRelative importance of habitat characteristics at multiple spatial scales for wood-dependent beetles in boreal forest 1931-1942Landscape Ecology3010Springer NetherlandsConnectivity Dead wood Hierarchical Bayesian regression Island effect Occurrence patterns Sampling effect Saproxylic beetles Threshold 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0221-5 0921-2973Landscape Ecol10.1007/s10980-015-0221-5Englishڽ7JLiu, Zhihua Wimberly, MichaelC Lamsal, Aashis Sohl, TerryL Hawbaker, ToddJ2015Climate change and wildfire risk in an expanding wildland–urban interface: a case study from the Colorado Front Range Corridor 1943-1957Landscape Ecology3010Springer NetherlandssDisturbance Coupled human and natural systems Western United States Land use Land cover Social–ecological systems 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0222-4 0921-2973Landscape Ecol10.1007/s10980-015-0222-4Englishڽ71Garden, JenniG O’Donnell, Tim Catterall, CarlaP2015aChanging habitat areas and static reserves: challenges to species protection under climate change 1959-1973Landscape Ecology3010Springer Netherlands@Conservation planning Fauna Global change Habitat refugia Forest 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0223-3 0921-2973Landscape Ecol10.1007/s10980-015-0223-3Englishڽ76Beduschi, Tatiane Tscharntke, Teja Scherber, Christoph2015rUsing multi-level generalized path analysis to understand herbivore and parasitoid dynamics in changing landscapes 1975-1986Landscape Ecology3010Springer NetherlandsCrop rotation Multitrophic interactions Grid-based landscape analysis Biological control Structural equation model Regular (systematic) sampling 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0224-2 0921-2973Landscape Ecol10.1007/s10980-015-0224-2Englishڽ7BBehrman, KathrineD Juenger, ThomasE Kiniry, JamesR Keitt, TimothyH2015USpatial land use trade-offs for maintenance of biodiversity, biofuel, and agriculture 1987-1999Landscape Ecology3010Springer NetherlandsfSpecies richness Ecosystem services Switchgrass Spatial optimization ALMANAC model Panicum virgatum L. 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0225-1 0921-2973Landscape Ecol10.1007/s10980-015-0225-1Englishڽ7UHiron, Matthew Berg, Åke Eggers, Sönke Berggren, Åsa Josefsson, Jonas Pärt, Tomas2015`The relationship of bird diversity to crop and non-crop heterogeneity in agricultural landscapes 2001-2013Landscape Ecology3010Springer NetherlandssBiodiversity Landscape complementation Conservation Composition Landscape ecology Intensification Land use patterns 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0226-0 0921-2973Landscape Ecol10.1007/s10980-015-0226-0Englishڽ7SPauli, BenjaminP Badin, HollyA Haulton, G. Scott Zollner, PatrickA Carter, TimothyC2015dLandscape features associated with the roosting habitat of Indiana bats and northern long-eared bats 2015-2029Landscape Ecology3010Springer NetherlandscHabitat Landscape MaxLike Myotis septentrionalis Myotis sodalis Occupancy Presence-only model Roost 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0228-y 0921-2973Landscape Ecol10.1007/s10980-015-0228-yEnglishڽ7VBennett, JoanneM Clarke, RohanH Horrocks, GregoryF B. Thomson, JamesR Mac Nally, Ralph2015_Climate drying amplifies the effects of land-use change and interspecific interactions on birds 2031-2043Landscape Ecology3010Springer NetherlandsGDespotic species Drought Fragmentation Habitat degradation Habitat loss 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0229-x 0921-2973Landscape Ecol10.1007/s10980-015-0229-xEnglishHڽ72Bishop-Taylor, Robbi Tulbure, MirelaG Broich, Mark2015Surface water network structure, landscape resistance to movement and flooding vital for maintaining ecological connectivity across Australia’s largest river basin 2045-2065Landscape Ecology3010Springer NetherlandsEcological connectivity Ecological networks Graph theory Circuit theory Least-cost Dispersal Amphibians Protected areas Flooding Murray–Darling Basin 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0230-4 0921-2973Landscape Ecol10.1007/s10980-015-0230-4Englishڽ7pFerreira, PatríciaA Boscolo, Danilo Carvalheiro, LuísaG Biesmeijer, JacobusC Rocha, PedroL B. Viana, BlandinaF2015[Responses of bees to habitat loss in fragmented landscapes of Brazilian Atlantic Rainforest 2067-2078Landscape Ecology3010Springer NetherlandsZPollinators Forest understory Tropical Landscape changes Multiscalar approach Bahia Brazil 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0231-3 0921-2973Landscape Ecol10.1007/s10980-015-0231-3Englishڽ70Hayward, MattW Ortmann, Sylvia Kowalczyk, Rafał2015[Risk perception by endangered European bison Bison bonasus is context (condition) dependent 2079-2093Landscape Ecology3010Springer NetherlandsGiving-up density Forage quality Landscape of fear Marginal value theorem Optimal foraging theory Resource selection Predation risk 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0232-2 0921-2973Landscape Ecol10.1007/s10980-015-0232-2Englishڽ74Gutzwiller, KevinJ Riffell, SamuelK Flather, CurtisH2015hAvian abundance thresholds, human-altered landscapes, and the challenge of assemblage-level conservation 2095-2110Landscape Ecology3010Springer NetherlandsAbrupt spatial changes Bird–landscape thresholds Geographic ranges Internal structure Landscape planning and management Threshold pervasiveness and diversity 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0233-1 0921-2973Landscape Ecol10.1007/s10980-015-0233-1Englishڽ74Severns, PaulM Sackett, KathrynE Mundt, ChristopherC2015qOutbreak propagule pressure influences the landscape spread of a wind-dispersed, epidemic-causing, plant pathogen 2111-2119Landscape Ecology3010Springer NetherlandsdBiological invasion Disease spread Epidemic Landscape epidemiology Long-distance dispersal Power-law 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0234-0 0921-2973Landscape Ecol10.1007/s10980-015-0234-0English`ڽ7Krosby, Meade Breckheimer, Ian John Pierce, D. Singleton, PeterH Hall, SoniaA Halupka, KarlC Gaines, WilliamL Long, RobertA McRae, BradH Cosentino, BrianL Schuett-Hames, JoanneP2015Focal species and landscape “naturalness” corridor models offer complementary approaches for connectivity conservation planning 2121-2132Landscape Ecology3010Springer NetherlandsRCoarse-filter Connectivity Corridors Fine-filter Focal-species Landscape integrity 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0235-z 0921-2973Landscape Ecol10.1007/s10980-015-0235-zEnglishڽ7}Araujo Calçada, Emmanuelle Lenoir, Jonathan Plue, Jan Broeckx, LauraS Closset-Kopp, Déborah Hermy, Martin Decocq, Guillaume2015vSpatial patterns of water-deposited seeds control plant species richness and composition in riparian forest landscapes 2133-2146Landscape Ecology3010Springer NetherlandsBiodiversity maintenance Disturbance Environmental gradients Flooding Hydrochory Recruitment limitation Seed dispersal Soil seed bank Temperate floodplain forest Vascular plant diversity 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0236-y 0921-2973Landscape Ecol10.1007/s10980-015-0236-yEnglishWڽ7Ducci, Laura Agnelli, Paolo Di Febbraro, Mirko Frate, Ludovico Russo, Danilo Loy, Anna Carranza, MariaLaura Santini, Giacomo Roscioni, Federica2015Different bat guilds perceive their habitat in different ways: a multiscale landscape approach for variable selection in species distribution modelling 2147-2159Landscape Ecology3010Springer NetherlandsWChiroptera Foraging Landscape pattern Multiscale approach Moving windows, Spatial scale 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0237-x 0921-2973Landscape Ecol10.1007/s10980-015-0237-xEnglish8ڽ7fJoseph, GrantS Makumbe, Milton Seymour, ColleenL Cumming, GraemeS Mahlangu, Zacheus Cumming, DavidH M.2015xTermite mounds mitigate against 50 years of herbivore-induced reduction of functional diversity of savanna woody plants 2161-2174Landscape Ecology3010Springer NetherlandsBottom-up versus top-down effects Functional divergence Functional evenness Functional richness Spatial heterogeneity Termitaria 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0238-9 0921-2973Landscape Ecol10.1007/s10980-015-0238-9English5۽7 Yocom, Ken2015TR.I. McDonald: Conservation for cities: how to plan and build natural infrastructure 2175-2177Landscape Ecology3010Springer Netherlands 2015/12/01+http://dx.doi.org/10.1007/s10980-015-0274-5 0921-2973Landscape Ecol10.1007/s10980-015-0274-5Englisha۽7&Fang, Jingyun Bai, Yongfei Wu, Jianguo2015eTowards a better understanding of landscape patterns and ecosystem processes of the Mongolian Plateau 1573-1578Landscape Ecology309Springer Netherlands 2015/11/01+http://dx.doi.org/10.1007/s10980-015-0277-2 0921-2973Landscape Ecol10.1007/s10980-015-0277-2Englishڽ7-Wu, Jianguo Zhang, Qing Li, Ang Liang, Cunzhu2015OHistorical landscape dynamics of Inner Mongolia: patterns, drivers, and impacts 1579-1598Landscape Ecology309Springer NetherlandsMongolian Plateau Inner Mongolia Landscape history Land use and land cover change Socioeconomic drivers Grasslands Rangeland degradation and sustainability 2015/11/01+http://dx.doi.org/10.1007/s10980-015-0209-1 0921-2973Landscape Ecol10.1007/s10980-015-0209-1English ڽ7ZZhao, Xia Hu, Huifeng Shen, Haihua Zhou, Daojing Zhou, Liming Myneni, RangaB Fang, Jingyun2015[Satellite-indicated long-term vegetation changes and their drivers on the Mongolian Plateau 1599-1611Landscape Ecology309Springer Netherlands{Climate change Human activity Normalized difference vegetation index (NDVI) Phenology Vegetation activity Mongolian Plateau 2015/11/01+http://dx.doi.org/10.1007/s10980-014-0095-y 0921-2973Landscape Ecol10.1007/s10980-014-0095-yEnglishڽ7>Zhou, Daojing Zhao, Xia Hu, Huifeng Shen, Haihua Fang, Jingyun2015RLong-term vegetation changes in the four mega-sandy lands in Inner Mongolia, China 1613-1626Landscape Ecology309Springer NetherlandsOClimate change Human activity Desertification Sandy land Vegetation change NDVI 2015/11/01+http://dx.doi.org/10.1007/s10980-015-0151-2 0921-2973Landscape Ecol10.1007/s10980-015-0151-2EnglishSڽ7uChen, Leiyi Li, He Zhang, Pujin Zhao, Xia Zhou, Luhong Liu, Taoyu Hu, Huifeng Bai, Yongfei Shen, Haihua Fang, Jingyun2015Climate and native grassland vegetation as drivers of the community structures of shrub-encroached grasslands in Inner Mongolia, China 1627-1641Landscape Ecology309Springer NetherlandsArid and semi-arid area Climate Community structure Geographic pattern Grassland Shrub encroachment Shrubby grassland Shrubland 2015/11/01+http://dx.doi.org/10.1007/s10980-014-0044-9 0921-2973Landscape Ecol10.1007/s10980-014-0044-9Englishڽ7FJiang, Guangshun Liu, Jun Xu, Lei Yan, Chuan He, Honglin Zhang, Zhibin2015Intra- and interspecific interactions and environmental factors determine spatial–temporal species assemblages of rodents in arid grasslands 1643-1655Landscape Ecology309Springer NetherlandsoSpecies competition and coexistence Density dependence Environmental filter Species assemblage Rodent community 2015/11/01+http://dx.doi.org/10.1007/s10980-014-0039-6 0921-2973Landscape Ecol10.1007/s10980-014-0039-6Englishڽ73Hao, Shuguang Wang, Shiping Cease, Arianne Kang, Le2015Landscape level patterns of grasshopper communities in Inner Mongolia: interactive effects of livestock grazing and a precipitation gradient 1657-1668Landscape Ecology309Springer NetherlandsJGrasshopper Plant community Grazing intensity Precipitation Inner Mongolia 2015/11/01+http://dx.doi.org/10.1007/s10980-015-0247-8 0921-2973Landscape Ecol10.1007/s10980-015-0247-8Englishڽ7`Chen, Dima Mi, Jia Chu, Pengfei Cheng, Junhui Zhang, Lixia Pan, Qingmin Xie, Yichun Bai, Yongfei2015jPatterns and drivers of soil microbial communities along a precipitation gradient on the Mongolian Plateau 1669-1682Landscape Ecology309Springer NetherlandszThe Inner Mongolia grassland transect Precipitation gradient PLFA Soil microbial community Plant community Soil properties 2015/11/01+http://dx.doi.org/10.1007/s10980-014-9996-z 0921-2973Landscape Ecol10.1007/s10980-014-9996-zEnglish1ڽ77Mi, Jia Li, Jianjun Chen, Dima Xie, Yichun Bai, Yongfei2015Predominant control of moisture on soil organic carbon mineralization across a broad range of arid and semiarid ecosystems on the Mongolia plateau 1683-1699Landscape Ecology309Springer NetherlandsSOC mineralization Precipitation gradient Water filled pore space (WFPS) Temperature sensitivity of SOC mineralization Microbial biomass carbon 2015/11/01+http://dx.doi.org/10.1007/s10980-014-0040-0 0921-2973Landscape Ecol10.1007/s10980-014-0040-0Englishڽ7JLi, Zhiyong Ma, Wenhong Liang, Cunzhu Liu, Zhongling Wang, Wei Wang, Lixin2015}Long-term vegetation dynamics driven by climatic variations in the Inner Mongolia grassland: findings from 30-year monitoring 1701-1711Landscape Ecology309Springer Netherlands`Climate change Community composition Functional group Inner Mongolia grassland Long-term dynamic 2015/11/01+http://dx.doi.org/10.1007/s10980-014-0068-1 0921-2973Landscape Ecol10.1007/s10980-014-0068-1English/ڽ7AWang, Ling Liu, Chen Alves, DiogoGomes Frank, DouglasA Wang, Deli2015sPlant diversity is associated with the amount and spatial structure of soil heterogeneity in meadow steppe of China 1713-1721Landscape Ecology309Springer NetherlandsBiodiversity conservation Soil spatial heterogeneity Spatial structure Spatial variability Heterogeneity–diversity relationship Plant diversity Species richness 2015/11/01+http://dx.doi.org/10.1007/s10980-013-9955-0 0921-2973Landscape Ecol10.1007/s10980-013-9955-0Englishhڽ7Wu, Jianguo Naeem, Shahid Elser, James Bai, Yongfei Huang, Jianhui Kang, Le Pan, Qingmin Wang, Qibing Hao, Shuguang Han, Xingguo2015yTesting biodiversity-ecosystem functioning relationship in the world’s largest grassland: overview of the IMGRE project 1723-1736Landscape Ecology309Springer NetherlandsBiodiversity and ecosystem functioning relationship BEF removal experiments Ecological stoichiometry Plant functional types Inner Mongolian grasslands 2015/11/01+http://dx.doi.org/10.1007/s10980-015-0155-y 0921-2973Landscape Ecol10.1007/s10980-015-0155-yEnglishWڽ7RYuan, Fei Wu, Jianguo Li, Ang Rowe, Helen Bai, Yongfei Huang, Jianhui Han, Xingguo2015Spatial patterns of soil nutrients, plant diversity, and aboveground biomass in the Inner Mongolia grassland: before and after a biodiversity removal experiment 1737-1750Landscape Ecology309Springer NetherlandsBiodiversity and Ecosystem Functioning (BEF) Removal experiments Spatial heterogeneity Pattern analysis Disturbance Inner Mongolia grassland 2015/11/01+http://dx.doi.org/10.1007/s10980-015-0154-z 0921-2973Landscape Ecol10.1007/s10980-015-0154-zEnglish/ڽ7=Li, Wenhuai Zhan, Shuxia Lan, Zhichun Ben Wu, X. Bai, Yongfei2015Scale-dependent patterns and mechanisms of grazing-induced biodiversity loss: evidence from a field manipulation experiment in semiarid steppe 1751-1765Landscape Ecology309Springer NetherlandsSpatial scale Scaling effect Species richness Species-area relationship (SAR) SAR decomposition Rare species Species abundance distribution 2015/11/01+http://dx.doi.org/10.1007/s10980-014-0146-4 0921-2973Landscape Ecol10.1007/s10980-014-0146-4Englishtڽ7lWan, Hongwei Bai, Yongfei Hooper, DavidU Schönbach, Philipp Gierus, Martin Schiborra, Anne Taube, Friedhelm2015xSelective grazing and seasonal precipitation play key roles in shaping plant community structure of semi-arid grasslands 1767-1782Landscape Ecology309Springer NetherlandsSpecies richness Spatial heterogeneity Precipitation seasonality Diversity-grazing intensity relationship Intermediate disturbance hypothesis Dynamic equilibrium model C3/C4 abundance 2015/11/01+http://dx.doi.org/10.1007/s10980-015-0252-y 0921-2973Landscape Ecol10.1007/s10980-015-0252-yEnglishڽ7JPeng, Jiangtao Liang, Cunzhu Niu, Yongmei Jiang, Wei Wang, Wei Wang, Lixin2015ZModerate grazing promotes genetic diversity of Stipa species in the Inner Mongolian steppe 1783-1794Landscape Ecology309Springer NetherlandsHGrazing disturbance Small-scale Genetic diversity Genetic structure ISSR 2015/11/01+http://dx.doi.org/10.1007/s10980-015-0227-z 0921-2973Landscape Ecol10.1007/s10980-015-0227-zEnglishڽ7QBaoyin, Taogetao Li, FrankYonghong Minggagud, Hugjiltu Bao, Qinghai Zhong, Yankai2015Mowing succession of species composition is determined by plant growth forms, not photosynthetic pathways in Leymus chinensis grassland of Inner Mongolia 1795-1803Landscape Ecology309Springer NetherlandsWGrassland succession Plant growth-forms Photosynthetic pathways Long-term mowing Steppe 2015/11/01+http://dx.doi.org/10.1007/s10980-015-0249-6 0921-2973Landscape Ecol10.1007/s10980-015-0249-6English8? Aaviksoo,K.1993vChanges of plant cover and land use types (1950's to 1980's) in three mire reserves and their neighbourhood in Estonia287-301Landscape Ecology84vaerial photograph, classification, mire landscape, typological mapping (repeated), transition matrix, dynamics, forest|7 Aaviksoo, K.1993oChanges of Plant Cover and Land-Use Types (1950s to 1980s) in 3 Mire Reserves and Their Neighborhood in Estonia287-301Landscape Ecology84raerial photograph classification mire landscape typological mapping (repeated) transition matrix dynamics forecastDecThe dynamics of plant cover and land use types in three study areas - Keava (1192.05 ha), Meenikonna (1513.35 ha) and Natsi-Volla (888.61 ha) mire landscapes, each divided into natural (N) and anthropogenous (A) subareas, was investigated by repeated aerial photo (black-and-white panchromatic, 1: 10,000) interpretation. Nineteen plant cover and land use (PC&LU) types were differentiated and three contour maps were drawn for each study area (corresponding to 1950's, 1960's and 1980's). The dynamics of mire landscapes were modelled by transition matrices P = [p(ij)], which contain the transition probabilities between i-th and j-th PC&LU types during the time interval between the aerial photographs. A total of 12 transition matrices were constructed. In A-subareas peat milling was started in the middle of the 60's whereas N-subareas acquired mire reserve status in 1981, which is manifested in a different development. 93% of N-subarea and 69% of the A-subarea remained unchanged from the 50's to the 80's. The increase of anthropogenous land use types in A-subareas of Keava, Meenikonna and Natsi-Volla were respectively 0.84%, 0.32% and 1.17% per year. Two different matrices (I and II period) were used to predict the future state of the study areas. The applicability of the transition matrix model has been discussed by comparing matrices of different base periods. Errors arising from photointerpretation, contour input, (transition) area measurement, matrix reduction etc. are evaluated.://A1993MN73600005-Mn736 Times Cited:18 Cited References Count:0 0921-2973ISI:A1993MN73600005IAaviksoo, K Tartu Univ,Dept Phys Geog & Landscape Ecol,Tartu 2400,EstoniaEnglishڽ7-Abdel Moniem, HossamEldienM Holland, JeffreyD2013AHabitat connectivity for pollinator beetles using surface metrics 1251-1267Landscape Ecology287Springer NetherlandsCerambycidae Fragmentation Geographical information system Lepturinae Spatial modeling Landscape gradient model Surface metrology 2013/08/01+http://dx.doi.org/10.1007/s10980-013-9886-9 0921-2973Landscape Ecol10.1007/s10980-013-9886-9English|?^ nAcevedo, Pelayo Angel Farfan, Miguel Luz Marquez, Ana Delibes-Mateos, Miguel Real, Raimundo Mario Vargas, Juan2011MPast, present and future of wild ungulates in relation to changes in land use19-31Landscape Ecology261JanEIn recent decades, Mediterranean landscapes have been experiencing more rapid changes in land use than usual, which have affected the ecology of the species inhabiting this biodiversity hotspot. Some studies have assessed the effect of such changes on biodiversity, but most of these were diachronic studies of population dynamics, or synchronic studies of species habitat selection, whereas few studies have simultaneously taken into account temporal changes in habitat composition and changes in species distribution. This study analysed the effects of land-use changes on the distribution of wild ungulates (Capreolus capreolus, Capra pyrenaica, Cervus elaphus and Sus scrofa). Using favourability function and Markov chain analysis combined with cellular automata, we addressed the following objectives: (i) to examine the environmental determinants of ungulate distribution in the past (1960s) and present (1990s), (ii) to model land use for 2040 to forecast future species distributions and (iii) to assess the biogeographical differences between the above-mentioned study periods (past-present and present-future). Species favourability was predicted to be more widely distributed in the present than in the past, but this increase varied across species. Areas predicted to be favourable in the present should remain stable in the future, but in addition there will be more new favourable areas not previously occupied by these species. The results are discussed from the perspective of the socio-economic relevance of wild ungulates in relation to some unfavourable areas of Mediterranean regions.!://WOS:000286004400003Times Cited: 0 0921-2973WOS:00028600440000310.1007/s10980-010-9538-2 |?Adamo, Maria Tarantino, Cristina Tomaselli, Valeria Kosmidou, Vasiliki Petrou, Zisis Manakos, Ioannis Lucas, Richard M. Mucher, Caspar A. Veronico, Giuseppe Marangi, Carmela De Pasquale, Vito Blonda, Palma2014XExpert knowledge for translating land cover/use maps to General Habitat Categories (GHC) 1045-1067Landscape Ecology296JulMonitoring biodiversity at the level of habitats and landscape is becoming widespread in Europe and elsewhere as countries establish international and national habitat conservation policies and monitoring systems. Earth Observation (EO) data offers a potential solution to long-term biodiversity monitoring through direct mapping of habitats or by integrating Land Cover/Use (LC/LU) maps with contextual spatial information and in situ data. Therefore, it appears necessary to develop an automatic/semi-automatic translation framework of LC/LU classes to habitat classes, but also challenging due to discrepancies in domain definitions. In the context of the FP7 BIO_SOS (www.biosos.eu) project, the authors demonstrated the feasibility of the Food and Agricultural Organization Land Cover Classification System (LCCS) taxonomy to habitat class translation. They also developed a framework to automatically translate LCCS classes into the recently proposed General Habitat Categories classification system, able to provide an exhaustive typology of habitat types, ranging from natural ecosystems to urban areas around the globe. However discrepancies in terminology, plant height criteria and basic principles between the two mapping domains inducing a number of one-to-many and many-to-many relations were identified, revealing the need of additional ecological expert knowledge to resolve the ambiguities. This paper illustrates how class phenology, class topological arrangement in the landscape, class spectral signature from multi-temporal Very High spatial Resolution (VHR) satellite imagery and plant height measurements can be used to resolve such ambiguities. Concerning plant height, this paper also compares the mapping results obtained by using accurate values extracted from LIght Detection And Ranging (LIDAR) data and by exploiting EO data texture features (i.e. entropy) as a proxy of plant height information, when LIDAR data are not available. An application for two Natura 2000 coastal sites in Southern Italy is discussed.!://WOS:000338331600010Times Cited: 6 0921-2973WOS:00033833160001010.1007/s10980-014-0028-9<<7Adler, P. B. Hall, S. A.2005_The development of forage production and utilization gradients around livestock watering points319-333Landscape Ecology203consumption; foraging behavior; grazing; piosphere; simulation model; spatial hetereogeneity; utilization; Eastern Washington; USA MIXED-GRASS PRAIRIE; TALLGRASS PRAIRIE; NONEQUILIBRIUM RANGELANDS; SPATIAL HETEROGENEITY; VEGETATION; BISON; PATTERNS; MODEL; COMMUNITIES; ENERGETICSArticleAprLarge herbivores can impose spatial patterns on otherwise homogeneous vegetation, but how these patterns change through time is poorly understood. Domestic livestock pastures are model systems for studying how foraging behavior influences the development of coupled grazing and vegetation patterns. We sampled forage production and utilization by cattle along distance-from-water gradients to provide a snapshot of grazing and vegetation patterns, and then evaluated the ability of simulation models to qualitatively reproduce these patterns. In the field, forage production increased with distance from water, as expected, but utilization peaked at intermediate distances from water in two of three study areas. Likewise, simulations based on a variety of foraging strategies produced gradients in forage production and, after forage availability near water declined sufficiently, peaks in utilization at intermediate distances. Distance-from-water gradients thus represent cumulative but not necessarily present day gradients in grazing intensity. The model with a foraging strategy based on time minimization produced slightly more realistic patterns in forage abundance than a model based on energy maximization, although results were sensitive to the value of the threshold for rejecting sites of low forage biomass. However, all models produced implausible thresholds in grazing and forage distribution, suggesting that factors besides resource distribution influence herbivore distributions. Moreover, different foraging rules produced similar vegetation gradients, especially on point water source landscapes, illustrating the difficulty of inferring foraging processes from vegetation patterns.://000231824400007 ISI Document Delivery No.: 963RU Times Cited: 0 Cited Reference Count: 58 Cited References: *R DEV COR TEAM, 2003, R LANG ENV STAT COMP ADLER PB, 2001, OECOLOGIA, V128, P465 ADLER PB, 2003, THESIS COLORADO STAT ADLER PB, 2004, IN PRESS ECOLOGICAL ANDREW MH, 1988, TREES-STRUCT FUNCT, V3, P7 ARMSTRONG HM, 2000, CAN J ZOOL, V78, P1604 BEECHAM JA, 1998, ECOL MODEL, V113, P141 BERGMAN CM, 2001, J ANIM ECOL, V70, P289 BIONDINI ME, 1999, J RANGE MANAGE, V52, P454 BLAISDELL JP, 1949, ECOLOGY, V30, P298 BOCK CE, 1984, J RANGE MANAGE, V37, P239 CHARNOV EL, 1976, THEORETICAL POPULATI, V9, P129 COLLINS SL, 1998, SCIENCE, V280, P745 COPPEDGE BR, 1998, J RANGE MANAGE, V51, P258 COPPOCK DL, 1983, OECOLOGIA, V56, P10 DAUBENMIRE R, 1970, TECHNICAL B WASHINGT, V62 DENNIS P, 1998, ECOL ENTOMOL, V23, P253 FARNSWORTH KD, 1999, AM NAT, V153, P509 FARNSWORTH KD, 2001, OIKOS, V95, P15 FORTIN D, 2003, OECOLOGIA, V134, P219 FUHLENDORF SD, 2001, BIOSCIENCE, V51, P625 GANSKOPP D, 1988, J RANGE MANAGE, V41, P472 GOLLUSCIO RA, 1998, GRASS FORAGE SCI, V53, P47 GRAETZ RD, 1978, AUSTR RANGELAND J, V1, P126 GRANT WE, 1982, J MAMMAL, V63, P248 HOBBS NT, 1988, AM NAT, V131, P760 HOBBS NT, 1991, ECOLOGY, V72, P1374 HUNTLY N, 1991, ANNU REV ECOL SYST, V22, P477 HUTCHINGS NJ, 2001, ECOL MODEL, V136, P209 JANO AP, 1998, J ECOL, V86, P93 JOHNSON CJ, 2001, OECOLOGIA, V127, P590 KELLNER K, 1992, J ARID ENVIRON, V22, P99 LUDWIG JA, 1999, RANGELAND J, V21, P135 MATLACK RS, 2001, AM MIDL NAT, V146, P361 MCNAUGHTON SJ, 1984, AM NAT, V124, P863 MOEN R, 1997, ECOLOGY, V78, P505 MOEN R, 1998, ECOSYSTEMS, V1, P52 MORRISON FB, 1961, FEEDS FEEDING ABRIDG MYSTERUD A, 1999, CAN J ZOOL, V77, P776 NASH MS, 1999, ECOL APPL, V9, P814 PARUELO JM, 1992, UNPUB IMPACTO DESERT PASTOR J, 1997, J MAMMAL, V78, P1040 PASTOR J, 1999, ECOSYSTEMS, V2, P439 PEARSON SM, 1995, ECOL APPL, V5, P744 PICKUP G, 1988, INT J REMOTE SENS, V9, P1469 PICKUP G, 1994, ECOL APPL, V4, P497 PICKUP G, 1998, J APPL ECOL, V35, P365 POSSE G, 2000, J VEG SCI, V11, P43 SENFT RL, 1987, BIOSCIENCE, V37, P789 SMITH CC, 1940, ECOLOGY, V21, P381 STERN SJ, 1998, ECOLOGICAL SCALE THE, P289 THRASH I, 2000, J ARID ENVIRON, V44, P61 TURNER MD, 1998, J BIOGEOGR, V25, P669 TURNER MD, 2002, LANDSCAPE ECOL, V17, P367 VANDEKOPPEL J, 2002, AM NAT, V159, P209 WALLISDEVRIES MF, 1994, OECOLOGIA, V100, P98 WEBER GE, 1998, J APPL ECOL, V35, P687 WILMSHURST JF, 1995, BEHAV ECOL, V6, P209 0921-2973 Landsc. Ecol.ISI:000231824400007Colorado State Univ, Grad Degree Program, Ft Collins, CO 80523 USA. Adler, PB, Univ Calif Santa Barbara, Dept Ecol Evolut & Marine Biol, Santa Barbara, CA 93106 USA. adler@lifesci.ucsb.eduEnglish<7X Agee, J. K.2003LHistorical range of variability in eastern Cascades forests, Washington, USA725-740Landscape Ecology188Abies grandis Abies lasiocarpa cascade range fire ecology fire history historical range of variability landscape ecology Pinus contorta Pinus ponderosa Pseudotsuga menziesii FIRE HISTORY NATIONAL-PARK PINE FORESTS CRATER LAKE OREGON MANAGEMENT ECOSYSTEM MONTANA MOUNTAINS PATTERNSArticle'The historical range of variability (HRV) has been suggested as a coarse filter approach to maintain ecosystem sustainability and resiliency. The historical range of variability in forest age structure for the central eastern Cascade Range in Washington State, USA was developed from historical fire return intervals and the manner in which fire acted as both cyclic and stochastic processes. The proportions of seven forest structural stages calculated through these processes were applied to the area of each forest series within the central eastern Cascades landscape. Early successional forest stages were more common in high elevation forest than low elevation forest. The historical proportion of old growth and late successional forest varied from 38 to 63 percent of the forested landscape. These process-based estimates are consistent with those developed from forest structural information. HRV is a valuable planning tool for ecosystem conservation purposes, but must be applied to real landscapes with consideration of both temporal and spatial scale.://000188716100001 ISI Document Delivery No.: 770HA Times Cited: 8 Cited Reference Count: 71 Cited References: AGEE JK, 1984, ECOLOGY, V65, P810 AGEE JK, 1986, P NAT WILD RES C CUR AGEE JK, 1990, CAN J FOREST RES, V20, P350 AGEE JK, 1993, FIRE ECOLOGY PACIFIC AGEE JK, 1994, PNWGTR320 USDA FOR S AGEE JK, 1998, NW SCI, V72, P24 AGEE JK, 1999, ECOLOGY CONSERVATION AGEE JK, 2002, CONSERVATION BIOL PR, V3, P18 AGEE JK, 2003, NAT AREA J, V23, P114 ALT DD, 1984, ROADSIDE GEOLOGY WAS ANDERSON L, 1987, FOREST ECOL MANAG, V22, P251 ANTOS JA, 1981, NW SCI, V55, P26 ARNO SF, 1976, INT187 USDA FOR SERV ARNO SF, 1980, J FOREST, V78, P460 BAKER WL, 1989, CAN J FOREST RES, V19, P700 BARRETT SW, 1991, CAN J FOREST RES, V21, P1711 BONNICKSEN TM, 1981, FOREST ECOL MANAG, V3, P307 BORK J, 1985, THESIS OREGON STATE CAMP A, 1997, FOREST ECOL MANAG, V95, P63 CISSEL JH, 1999, ECOL APPL, V9, P1217 CLEMENTS FE, 1935, ECOLOGY, V16, P342 COBB DF, 1988, THESIS U WASHINGTON COWLIN RA, 1942, FOREST RESOURCES PON DAUBENMIRE R, 1968, PLANT COMMUNITIES EVERETT RL, 2000, FOREST ECOL MANAG, V129, P207 EVERS L, 1997, FIRE ECOLOGY MIDCOLU FAHNESTOCK GR, 1976, TALL TIMB FIR EC C P, V15, P33 FINCH RB, 1984, FIRE HIST SELECTED S FRANKLIN JF, 1973, PNW8 USDA FOR SERV G FRELICH LE, 1991, J ECOL, V79, P223 FRELICH LE, 2002, FOREST DYNAMICS DIST GANNETT H, 2002, 5 USDI GEOL SURV H GARDNER RH, 1999, PREDICTING FOREST FI HALL FC, 1976, TALL TIMB FIR EC C, V15, P155 HANN WJ, 1994, PNWGTR318 USDA FOR S HARROD RJ, 1999, FOREST ECOL MANAG, V114, P433 HAUFLER JB, 1996, WILDLIFE SOC B, V24, P200 HESSBURG PF, 1994, PNWGTR327 USDA FOR S HESSBURG PF, 1999, PNWRP514 USDA FOR SE HESSBURG PF, 2000, APPL VEG SCI, V3, P163 HESSBURG PF, 2000, FOREST ECOL MANAG, V136, P53 HOLLING CS, 1996, CONSERV BIOL, V10, P328 JOHNSON EA, 1985, CAN J FOREST RES, V15, P214 JOHNSON EA, 1992, FIRE VEGETATION DYNA JOHNSON EA, 1994, ADV ECOL RES, V25, P329 LANDRES PB, 1999, ECOL APPL, V9, P1179 LERTZMAN K, 1998, ECOLOGICAL SCALE THE LESICA P, 1996, BIOL CONSERV, V77, P33 LILLYBRIDGE TR, 1995, PNWGTR359 USDA FOR S LITTLE R, 1992, THESIS U WASHINGTON MEYER WH, 1938, USDA TECHNICAL B, V630 ODUM EP, 1969, SCIENCE, V164, P262 OLSON DL, 1999, THESIS U WASHINGTON PICKETT STA, 1978, BIOL CONSERV, V13, P27 ROMME WH, 1982, ECOL MONOGR, V52, P199 ROMME WH, 1991, CONSERV BIOL, V5, P373 SCHUMACHER FX, 1930, CALIFORNIA AGR EXPT, V491 SHUGART HH, 1984, THEORY FOREST DYNAMI SOERIAATMADJA RE, 1966, THESIS OREGON STATE STEPHENSON NL, 1999, ECOL APPL, V9, P1253 THOMAS TL, 1986, CAN J FOREST RES, V16, P1082 VALE TR, 2002, FIRE NATIVE PEOPLES WALTERS C, 1986, ADAPTIVE MANAGEMENT WEAVER H, 1959, J FOREST, V57, P15 WEAVER H, 1961, ECOLOGY, V42, P416 WIENS JA, 1989, FUNCTIONAL ECOLOGY, V3, P383 WIENS JA, 2002, INTEGRATING LANDSCAP WILLIAMS CK, 1990, FORESTED PLANT ASS C WIMBERLY MC, 2000, CONSERV BIOL, V14, P167 WISCHNOFSKE MG, 1983, NATURAL ROLE FIRE WE WRIGHT CS, 1996, THESIS U WASHINGTON 0921-2973 Landsc. Ecol.ISI:000188716100001Univ Washington, Coll Forest Resources, Seattle, WA 98195 USA. Agee, JK, Univ Washington, Coll Forest Resources, Box 352100, Seattle, WA 98195 USA. jagee@u.washington.eduEnglish <7Ahas, R. Aasa, A.2001^Impact of landscape features on spring phenological phases of maple and bird cherry in Estonia437-451Landscape Ecology165@Estonia landscape factors phenological maps phenology GREEN-WAVEArticleJulWe analysed the spatial distribution of the pollination of maple (Acer platanoides L.) and bird cherry (Prunus padus L.) in Estonia on the basis of phenological data from the time series for 1948-1995, in 27 observation points, and from the special field observation programme 1996-1999, in 46 observation points. Phenological maps show that these springtime phenophases spread in the landscape at a rate of 3-6 days per 100 km, with different rates in early and late springs. The maple has a steeper gradient on northeastern islands and the bird cherry on the western islands; the values of standard deviation have a similar spatial pattern. The distribution of phenological phases in Estonia is influenced by differences between the temperature regimes of the Baltic Sea and inland areas, different climatic conditions in north-eastern Estonia, local altitude-impact of uplands with an absolute height of 150-300 m asl, and the effects of bigger lakes and wetland areas. On the basis of spring phenology, three seasonally different landscape types can be determined in Estonia: (1) Relatively continental South-East Estonian Plain and uplands - have the earliest spring with the smallest deviations and stable intervals between phases, (2) Central, western and northern Estonian plains - with temperate influence of the temperature regime of the Baltic Sea, and big variations from year to year. Large variability is caused by the presence and duration of ice cover on the sea in cold springs, and direct access by warm air masses in early springs. (3) North-east Estonia - has the most boreal climate with longer snow cover and very late spring, influenced by arctic air masses, local influence of the Baltic Sea, uplands, and large wetlands.://000170952100005 VISI Document Delivery No.: 471WR Times Cited: 2 Cited Reference Count: 22 Cited References: *GEOGR SOC USSR, 1965, NAT CAL N W USSR AHAS R, 1999, INT J BIOMETEOROL, V42, P119 AHAS R, 2000, INT J BIOMETEOROL, V44, P159 BERUCHASHVILI NL, 1994, RUSSIAN ACAD, V6, P24 DEFILA C, 1992, PZLANZENPHANOLOGISCH HOPKINS AD, 1918, MONTHLY WEATHER RE S, V9, P5 JAAGUS J, 1997, CLIMATIC CHANGE, V36, P65 JAAGUS J, 2000, CLIMATE RES, V15, P207 KARING P, 1992, AIR TEMPERATURE ESTO KOCH E, 2000, PROGR PHENOLOGY MONI LAPPALAINEN H, 1994, MEM SOC FAUNA FLORA, V70, P105 LIETH H, 1974, ECOL STUD, V8, P3 MALYSHEVA TC, 1968, METHODOLOGICAL MANUA MENZEL A, 1999, NATURE, V397, P659 MYNENI RB, 1997, NATURE, V386, P698 SCHNELLE F, 1955, PFLANZENPHANOLOGIE P SCHNELLE F, 1970, 4 MITT GES 3 VET BER, P6 SCHULTZ GE, 1982, WETTER LEBEN, V34, P160 SCHWARTZ MD, 1994, INT J BIOMETEOROL, V38, P18 SCHWARTZ MD, 1997, PHENOLOGY SEASONAL C, P23 SCHWARTZ MD, 1998, NATURE, V394, P839 WHITE MA, 1997, GLOBAL BIOGEOCHEM CY, V11, P217 0921-2973 Landsc. Ecol.ISI:000170952100005vUniv Tartu, Inst Geog, EE-51014 Tartu, Estonia. Ahas, R, Univ Tartu, Inst Geog, Vanemuise 46, EE-51014 Tartu, Estonia.Englishڽ7  Ahern, Jack2013Urban landscape sustainability and resilience: the promise and challenges of integrating ecology with urban planning and design 1203-1212Landscape Ecology286Springer NetherlandsKUrban sustainability Urban resilience Strategic planning Urban biodiversity 2013/07/01+http://dx.doi.org/10.1007/s10980-012-9799-z 0921-2973Landscape Ecol10.1007/s10980-012-9799-zEnglish&|?5 Ahlqvist, O. Shortridge, A.2010:Spatial and semantic dimensions of landscape heterogeneity573-590Landscape Ecology254This paper addresses the challenge of measuring spatial heterogeneity in categorical map data. Spatial heterogeneity is a complex notion that involves both spatial variability and attribute variability, and metrics to capture this are a product of their developers' simplifying assumptions about both spatial and attribute dimensions. We argue that the predominantly binary treatment of categorical data is frequently an unnecessary oversimplification that can be replaced by ordered measures based on semantic similarity evaluations. We develop a typology of autocorrelation metrics for categorical data that identifies a critical gap: existing measures are limited in their ability to capture variability of both spatial and attribute dimensions simultaneously. We demonstrate an approach to formally characterize the semantic similarity between pairs of categorical data classes as a continuous numeric variable. A series of experiments on synthetic and actual land cover data contrasts the information content provided by metrics representative of all portions of the typology: the recently proposed semantic variogram, the indicator variogram, the contagion index, and the edge contrast index. Experimental results suggest that the typology captures essential qualities of metric information richness. Among our findings is that the commonly used contagion index is directly correlated with Moran's I for 2-class maps but it fails to distinguish between negatively and positively autocorrelated patterns. We identify the semantic variogram as the only metric that can simultaneously detect both spatial and semantic attribute aspects of categorical autocorrelation. The semantic variogram is also relatively robust to attribute scale changes and therefore less sensitive to class aggregation than the other metrics.!://WOS:000275444100007Times Cited: 0 0921-2973WOS:00027544410000710.1007/s10980-009-9435-8<7GAlados, C. L. Pueyo, Y. Barrantes, O. Escos, J. Giner, L. Robles, A. B.2004qVariations in landscape patterns and vegetation cover between 1957 and 1994 in a semiarid Mediterranean ecosystem543-559Landscape Ecology195]fragmentation; land-use; Mediterranean; semi-arid ecosystem; vegetation cover transition; Cabo de Gata-Nijar Natural Park; Spain ACUTE MYOCARDIAL-INFARCTION; LEFT-VENTRICULAR FUNCTION; LONG-RANGE CORRELATIONS; DIGITAL TERRAIN DATA; EXTINCTION THRESHOLDS; HABITAT FRAGMENTATION; FRACTAL LANDSCAPES; SPATIAL-PATTERNS; NATURAL RAINFALL; PLANT COMMUNITYArticleThe aim of this study was to analyze the main processes that determine changes in landscape patterns and vegetation cover from 1957-1994 to develop a model for land cover dynamics. Land cover and landscape patterns were assessed and compared using aerial photographs taken in 1957, 1985, and 1994. Over this period, tall grass steppe and arid garrigues increased by 6% and 4%, respectively, while crop fields decreased by 15% and tall arid brush remained the same. Over the same period, tall grass steppes and arid garrigues became less fragmented. Changes in land use were triggered by socioeconomic forces, which were constrained by the underlying structure of the physical landscape. The best preserved vegetation (tall arid brushes) was concentrated at higher elevations, with a pronounced slope, not oriented towards the sea, and in volcanic substrate. Communities tended to be better preserved further away from towns and at lower house densities. Tall grass steppe was present on more gradual sea-oriented slope and in calcareous substrate, and increased at higher elevations, although not far from the town but away from high anthropogenic influence. Previous studies have revealed that traditional land uses of this landscape, particularly grazing, favoured the transition from tall arid brush to tall grass steppe. In this study, we analyzed to what extent the underlying structure of the physical landscape imposes limitations to the vulnerability to human activity of the main vegetation types. According to the data on the probability of vegetation transition over the 37-year period, the shift from tall arid brush to tall grass steppe appeared to be favoured by gradual slopes. Tall arid brush recovered from either arid garrigues or tall grass steppes at steeper slopes. Thus, steep terrain had a favourable effect on the formation of brushwood and more gradual terrain favoured tall grass steppe. The prevalent trends were confirmed by a projection of a transition matrix over 100 years.://000222941500007 \ISI Document Delivery No.: 841OY Times Cited: 7 Cited Reference Count: 89 Cited References: *CORINE, 1991, COR BIOT MAN *PORN, 1996, PLAN ORD REC NAT PLA ADLER PB, 2001, OECOLOGIA, V128, P465 AIDOUD A, 1998, ECOLOGICAL BASIS LIV, P133 ALADOS CL, 1999, ENVIRON TOXICOL CHEM, V18, P2392 ALADOS CL, 2003, ECOL MODEL, V163, P1 ALADOS CL, 2003, IN PRESS ECOLOGICAL ARIANOUTSOUFARA.M, 1985, J ARID ENVIRON, V9, P237 BARBERA GG, 1997, ACCION HUMANA DESERT, P9 BENET AS, 1997, CATENA, V31, P23 BERAEL C, 1995, DESERTIFICATION EURO, P371 BOLSTAD PV, 1998, LANDSCAPE ECOL, V13, P271 BURROWS CJ, 1990, PROCESSES VEGETATION CAMMERAAT LH, 2002, GEODERMA, V105, P1 CARDILLE JA, 2001, ECOL APPL, V11, P111 CASTRO H, 1993, MONOGRAFIES DIPUTACI, V23 CERDA A, 1997, J ARID ENVIRON, V36, P37 CERDA A, 1998, CAN J SOIL SCI, V78, P321 CERDA A, 2001, EUR J SOIL SCI, V52, P59 CHAPMAN RW, 1978, J ARID ENVIRON, V1, P261 CONGALTON RG, 1991, REMOTE SENS ENVIRON, V37, P35 CONNELL JH, 1977, AM NAT, V111, P1119 DAVIS FW, 1990, LANDSCAPE ECOL, V4, P69 DICASTRI G, 1981, ECOSYSTEMS WORLD, V11 EDWARDS PJ, 1994, LARGE SCALE ECOLOGY FUHLENDORF SD, 2001, APPL VEG SCI, V4, P177 GROOM MJ, 1993, BIOTIC INTERACTIONS, P24 GUERREROCAMPO J, 1999, J ARID ENVIRON, V41, P401 GUIRADO J, 2000, DESERTIFICACION ALME, P101 GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HADAR L, 1999, J VEG SCI, V10, P673 HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HAUSDORFF JM, 1995, J APPL PHYSIOL, V78, P349 HAUSDORFF JM, 1997, J APPL PHYSIOL, V82, P262 HESSEN I, 1999, FEDD REPERT, V110, P265 HODGSON J, 1994, GEOMORFOLOGIA ESPANA, V2, P239 HUEBNER CD, 1999, PLANT ECOL, V144, P83 HUIKURI HV, 2000, CIRCULATION, V101, P47 ISPIKOUDIS I, 1993, LANDSCAPE URBAN PLAN, V24, P259 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 JOHNSON CR, 2002, TRENDS ECOL EVOL, V17, P83 KAREIVA P, 1993, BIOTIC INTERACTIONS KOLASA J, 1991, ECOLOGICAL HETEROGEN, P1 KRUMMEL JR, 1987, OIKOS, V48, P321 LANDE R, 1987, AM NAT, V130, P624 LEHOUEROU HN, 2001, J ARID ENVIRON, V48, P103 LEVIN SA, 1974, P NATL ACAD SCI USA, V71, P2744 LYRINTZIS GA, 1996, ENVIRON CONSERV, V23, P140 MA ZK, 1995, PHOTOGRAMM ENG REM S, V61, P435 MAKIKALLIO TH, 1999, AM J CARDIOL, V83, P836 MARTINEZMENA M, 2000, CATENA, V38, P175 MARTINEZMENA M, 2001, HYDROL PROCESS, V15, P557 MOTA JF, 1996, BIODIVERS CONSERV, V5, P1597 MOTA JF, 1997, DATOS VEGETACION SUR NAEEM S, 1997, NATURE, V390, P507 ONEILL RV, 1989, PERSPECTIVES ECOLOGI, P140 PAN DY, 1999, LANDSCAPE ECOL, V14, P35 PAPANASTASIS VP, 1998, ECOL STUD, V136, P141 PASSERA CB, 1999, PROPUESTAS METODOLOG PEARSON SM, 1996, BIODIVERSITY MANAGED, P77 PEINADO M, 1992, VEGETATION SE SPAIN, V10 PENG CK, 1992, NATURE, V356, P168 PENG CK, 1994, PHYS REV E, V49, P1685 PETERSON GD, 2002, ECOSYSTEMS, V5, P329 PICKETT STA, 1987, VEGETATIO, V69, P109 RIETKERK M, 2002, AM NAT, V160, P524 ROBLES AB, 1997, ACTAS ETNOBOTANICA, V92, P333 RODRIGUEZ JE, 2000, DESERTIFICACION ALME, P35 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SOULE M, 1986, CONSERVATION BIOL STEVENSON AC, 1992, P PREHIST SOC, V58, P227 SWANSON FJ, 1988, BIOSCIENCE, V38, P92 SWENSON JJ, 2000, LANDSCAPE ECOL, V15, P713 TAQQU MS, 1995, FRACTALS, V3, P785 TAYLOR PD, 1993, OIKOS, V68, P571 TILMAN D, 1996, NATURE, V379, P718 TILMAN D, 2001, SCIENCE, V294, P843 TOMASELLI R, 1981, ECOSYSTEMS WORLD, V11, P95 TURNER BL, 1990, EARTH TRANSFORMED HU TURNER MG, 1993, LANDSCAPE ECOL, V8, P213 TURNER MG, 1996, ECOL APPL, V6, P1150 TURNER MG, 2001, LANDSCAPE ECOLOGY TH VALEROGARCES BL, 2000, AMBIO, V29, P344 WICKHAM JD, 2000, LANDSCAPE ECOL, V15, P171 WITH KA, 1997, OIKOS, V78, P151 WITH KA, 1999, CONSERV BIOL, V13, P314 WITH KA, 1999, LANDSCAPE ECOL, V14, P73 0921-2973 Landsc. Ecol.ISI:000222941500007$Pyrenean Inst Ecol, Zaragoza 50080, Spain. Univ Zaragoza, Dept Agr & Econ Agr, E-50013 Zaragoza, Spain. Infraestructura & Ecol, Madrid 28034, Spain. Estac Expt Zaidin, Granada 18008, Spain. Alados, CL, Pyrenean Inst Ecol, Avda Montanana 1005,Apd 202, Zaragoza 50080, Spain. alados@ipe.csic.esEnglish R<76 JAlagador, D. Trivino, M. Cerdeira, J. O. Bras, R. Cabeza, M. Araujo, M. B.2012XLinking like with like: optimising connectivity between environmentally-similar habitats291-301Landscape Ecology272connectivity environmental surrogates graph theory iberian peninsula minimum steiner tree problem protected areas spatial conservation planning reserve-network minimal fragmentation programming approach species-diversity area selection conservation climate assemblage corridors designFebHabitat fragmentation is one of the greatest threats to biodiversity. To minimise the effect of fragmentation on biodiversity, connectivity between otherwise isolated habitats should be promoted. However, the identification of linkages favouring connectivity is not trivial. Firstly, they compete with other land uses, so they need to be cost-efficient. Secondly, linkages for one species might be barriers for others, so they should effectively account for distinct mobility requirements. Thirdly, detailed information on the auto-ecology of most of the species is lacking, so linkages need being defined based on surrogates. In order to address these challenges we develop a framework that (a) identifies environmentally-similar habitats; (b) identifies environmental barriers (i.e., regions with a very distinct environment from the areas to be linked), and; (c) determines cost-efficient linkages between environmentally-similar habitats, free from environmental barriers. The assumption is that species with similar ecological requirements occupy the same environments, so environmental similarity provides a rationale for the identification of the areas that need to be linked. A variant of the classical minimum Steiner tree problem in graphs is used to address c). We present a heuristic for this problem that is capable of handling large datasets. To illustrate the framework we identify linkages between environmentally-similar protected areas in the Iberian Peninsula. The Natura 2000 network is used as a positive 'attractor' of links while the human footprint is used as 'repellent' of links. We compare the outcomes of our approach with cost-efficient networks linking protected areas that disregard the effect of environmental barriers. As expected, the latter achieved a smaller area covered with linkages, but with barriers that can significantly reduce the permeability of the landscape for the dispersal of some species.://0003000887000129Sp. Iss. SI 889QQ Times Cited:0 Cited References Count:57 0921-2973Landscape EcolISI:000300088700012Alagador, D CSIC, Museo Nacl Ciencias Nat, Dept Biodivers & Evolutionary Biol, C Jose Gutierrez Abascal 2, E-28006 Madrid, Spain CSIC, Museo Nacl Ciencias Nat, Dept Biodivers & Evolutionary Biol, C Jose Gutierrez Abascal 2, E-28006 Madrid, Spain CSIC, Museo Nacl Ciencias Nat, Dept Biodivers & Evolutionary Biol, E-28006 Madrid, Spain Univ Tecn Lisboa, Forest Res Ctr, Inst Super Agron, P-1349017 Lisbon, Portugal Univ Tecn Lisboa, Grp Math, Dept Biosyst Sci & Engn, Inst Super Agron, P-1349017 Lisbon, Portugal Univ Tecn Lisboa, CEMAPRE Ctr Appl Math & Econ, Inst Super Econ & Gestao, P-1200781 Lisbon, Portugal Univ Helsinki, Dept Biol & Environm Sci, Bioctr 3, FIN-00014 Helsinki, Finland Univ Evora, Rui Nabeiro Biodivers Chair, CIBIO, P-7000 Evora, PortugalDOI 10.1007/s10980-012-9704-9English<7} Alain, B. Gilles, P. Yannick, D.2006lFactors driving small rodents assemblages from field boundaries in agricultural landscapes of western France449-461Landscape Ecology2136agricultural landscape; diversity; linear habitats; multivariate analysis; small rodent community MOUSE APODEMUS-SYLVATICUS; SMALL-MAMMAL COMMUNITIES; VOLE MICROTUS-ARVALIS; LAND-USE PATTERNS; WOOD MOUSE; CLETHRIONOMYS-GLAREOLUS; BANK VOLES; STATISTICAL INEVITABILITY; POPULATION REGULATION; REGIONAL PROCESSESArticleAprhIn this study, we investigated the factors driving diversity and abundance of small rodent species inhabiting permanent linear habitat patches within high-intensified agricultural landscapes of western France. Multivariate (co-inertia) analysis was used to analyse relationships of habitat and landscape descriptive variables with rodent records. Two main ecological gradients were recognized according to statistical analysis. Relationships of species occurrence with environmental factors were interpreted according to their main life traits. The first ecological gradient clearly differentiated communities from hedges to those of grass-dominated linear banks. This first gradient was associated with the prevalence of forest versus grassland rodent species. This partitioning seems to reflect rather ecological requirements of species than competitive interactions. Small rodents diversity and abundance were inversely evolving along this gradient. The second factor influencing species assemblages was associated to landscape heterogeneity surrounding the permanent habitats. According to this second gradient, species seemed to be selected in relation to their ability to disperse and to use cultivated fields. Maximum diversity was generally observed in heterogeneous permanent habitats with mixed vegetation structure but hedges are important to produce biomass for predators.://000236968500011 ISI Document Delivery No.: 034ZD Times Cited: 0 Cited Reference Count: 70 Cited References: BOWMAN J, 2000, ECOGRAPHY, V23, P328 BOWMAN J, 2001, FOREST ECOL MANAG, V140, P249 BRYJA J, 2000, FOLIA ZOOL, V49, P191 BUREL F, 1990, LANDSCAPE ECOL, V4, P197 BUREL F, 1998, ACTA OECOL, V19, P47 BUTET A, 1993, ACTA OECOL, V14, P857 BUTET A, 2001, BIOL CONSERV, V100, P289 CANOVA L, 1991, ACTA THERIOL, V36, P73 CHURCHFIELD S, 1997, J ZOOL 3, V242, P519 CORNELL HV, 1992, J ANIM ECOL, V61, P1 DELAPENA NM, 2003, LANDSCAPE ECOL, V18, P265 DELATTRE P, 1992, AGR ECOSYST ENVIRON, V39, P153 DOAK DF, 1998, AM NAT, V151, P264 DOLEDEC S, 1994, FRESHWATER BIOL, V31, P277 DOLEDEC S, 1997, TOPICS DOCUMENTATION, V4 DOUGLASS RJ, 1992, ACTA THERIOL, V37, P359 FABER J, 1986, ACTA THERIOL, V31, P479 FASOLA M, 2000, ACTA THERIOL, V45, P353 FITZGIBBON CD, 1997, J APPL ECOL, V34, P530 FLOWERDEW JR, 1977, HDB BRIT MAMMALS, P206 FLOWERDEW JR, 1985, ECOLOGY WOODLAND ROD, P418 GEUSE P, 1985, ACTA ZOOL FENN, V173, P61 GEUSE P, 1985, ANN SOC ROY ZOOL BEL, V115, P211 GLIWICZ J, 2002, ACTA THERIOL S1, V47, P185 GURNELL J, 1985, S ZOOLOGICAL SOC LON, V55, P377 HANSSON L, 1967, OIKOS, V18, P261 HANSSON L, 1971, OIKOS, V22, P183 HANSSON L, 1985, ANN ZOOL FENN, V22, P315 HARRIS S, 1990, DISPERSAL MAMMALS AG, P159 HEALING TD, 1980, J ZOOLOGY LONDON, V191, P406 HEROLDOVA M, 1992, FOLIA ZOOL, V41, P11 HOLISOVA V, 1965, ZOOL LISTY, V14, P15 INNES DGL, 1994, MAMMAL REV, V24, P179 INNES DGL, 1994, SPECIAL PUBLICATION, V18, P111 KIKKAWA J, 1964, J ANIM ECOL, V33, P259 KORPIMAKI E, 1991, ECOLOGY, V72, P814 KOZAKIEWICZ M, 1993, ACTA THERIOL, V38, P1 KROHNE DT, 1990, OECOLOGIA, V82, P97 LAMBIN X, 1989, ACTA THERIOL, V34, P385 LOMAN J, 1991, EKOLOGIA POLSKA, V39, P221 LOMAN J, 1991, MAMMALIA, V55, P91 MAGURRAN AE, 1988, ECOLOGICAL DIVERSITY, P215 MASER C, 1978, ECOLOGY, V59, P799 MAZEROLLE MJ, 1999, ECOSCIENCE, V6, P117 MEEUS JHA, 1990, LANDSCAPE URBAN PLAN, V18, P289 MERRIAM G, 1988, CONNECTIVITY LANDSCA, P29 MIDDLETON J, 1981, J APPL ECOL, V18, P703 MILLYMAKI A, 1977, EPPO B, V7, P177 MONTGOMERY WI, 1993, J APPL ECOL, V30, P783 OUIN A, 2000, AGR ECOSYST ENVIRON, V78, P159 PAILLAT G, 2000, THESIS U RENNES PERAULT DR, 2000, ECOL MONOGR, V70, P401 PETRUSEWICZ K, 1983, ACTA THERIOL S1, V28, P1 PIANKA ER, 1974, P NATL ACAD SCI USA, V71, P2141 POLLARD E, 1970, J APPL ECOL, V7, P549 RAOUL F, 2001, REV ECOL-TERRE VIE, V56, P339 RICKLEFS RE, 1987, SCIENCE, V235, P167 ROBINSON RA, 2002, J APPL ECOL, V39, P157 SALAMOLARD M, 2000, ECOLOGY, V81, P2428 SANTINI L, 1977, EPPO B, V7, P243 SHANNON CE, 1962, MATH THEORY COMMUNIC SOLBRIG OT, 1991, GENES ECOSYSTEMS RES SULLIVAN TP, 2003, WILDLIFE SOC B, V31, P464 SZACKI J, 1991, LANDSCAPE ECOL, V5, P219 THIOULOUSE J, 1997, STAT COMPUT, V7, P75 TILMAN D, 1998, AM NAT, V151, P277 VANAPELDOORN RC, 1992, OIKOS, V65, P265 WILSON WL, 1993, MAMMAL REV, V23, P73 YAHNER RH, 1992, AM MIDL NAT, V127, P381 ZHANG Z, 1991, ACTA THERIOL, V36, P239 0921-2973 Landsc. Ecol.ISI:000236968500011Univ Rennes 1, CAREN, UMR CNRS 6553, F-35042 Rennes, France. Alain, B, Univ Rennes 1, CAREN, UMR CNRS 6553, Av Gen Leclerc, F-35042 Rennes, France. alain.butet@univ-rennes1.frEnglish? ,Albanese, Gene Davis, Craig Compton, Bradley2012oSpatiotemporal scaling of North American continental interior wetlands: implications for shorebird conservation 1465-1479Landscape Ecology2710Springer NetherlandsBiomedical and Life SciencesWithin interior North America, erratic weather patterns and heterogeneous wetland complexes cause wide spatio-temporal variation in the resources available to migrating shorebirds. Identifying the pattern-generating components of landscape-level resources and the scales at which shorebirds respond to these patterns will better facilitate conservation efforts for these species. We constructed descriptive models that identified weather variables associated with creating the spatio-temporal patterns of shorebird habitat in ten landscapes in north-central Oklahoma. We developed a metric capable of measuring the dynamic composition and configuration of shorebird habitat in the region and used field data to empirically estimate the spatial scale at which shorebirds respond to the amount and configuration of habitat. Precipitation, temperature, solar radiation and wind speed best explained the incidence of wetland habitat, but relationships varied among wetland types. Shorebird occurrence patterns were best explained by habitat density estimates at a 1.5 km scale. This model correctly classified 86 % of shorebird observations. At this scale, when habitat density was low, shorebirds occurred in 5 % of surveyed habitat patches but occurrence reached 60 % when habitat density was high. Our results suggest scale dependence in the habitat-use patterns of migratory shorebirds. We discuss potential implications of our results and how integrating this information into conservation efforts may improve conservation strategies and management practices.+http://dx.doi.org/10.1007/s10980-012-9803-7 0921-297310.1007/s10980-012-9803-7k|? DAlbeke, Shannon E. Nibbelink, Nathan P. Mu, Lan Ellsworth, Daniel J.2010Measuring boundary convexity at multiple spatial scales using a linear "moving window" analysis: an application to coastal river otter habitat selection 1575-1587Landscape Ecology2510DecLandscape metrics have been used to quantify ecological patterns and to evaluate relationships between animal presence/abundance and habitat at multiple spatial scales. However, many ecological flows occur in linear systems such as streams, or across patch/landscape boundaries (ecotones). Some organisms and flows may depend on the boundary shape, but metrics for defining linear boundary characteristics are scarce. While sinuosity and fractal dimension address some elements of shape, they fail to specify the dominate shape direction (convexity/concavity). We propose a method for measuring boundary convexity and assess its utility, along with sinuosity and fractal dimension, for predicting site selection by coastal river otters. First, we evaluate the characteristics of boundary convexity using a hypothetical boundary. Second, to compare convexity with other linear metrics boundary convexity, sinuosity and fractal dimension were calculated for the coastline of a set of islands in Prince William Sound, AK. Finally, we use logistic regression in an information-theoretic framework to assess site selection of river otters as a function of these linear metrics. Boundary convexity, fractal dimension and sinuosity are relatively uncorrelated at all scales. Otter latrine sites occurred at significantly more convex locations on the coastline than random sites. Using logistic regression and convexity values at the 100 m window-size, 69.5% of the latrine sites were correctly classified. Coastal terrestrial convexity appears to be a promising landscape-scale metric for predicting otter latrine sites. We suggest that boundary convexity may be an important landscape metric for describing species use or ecological flows at ecotones.!://WOS:000283371000009Times Cited: 0 0921-2973WOS:00028337100000910.1007/s10980-010-9528-4|?>Albert, Christian Aronson, James Fuerst, Christine Opdam, Paul2014[Integrating ecosystem services in landscape planning: requirements, approaches, and impacts 1277-1285Landscape Ecology298Oct}Despite growing knowledge of ecosystem services (ES), and heightened awareness of their political and socio-economic relevance, mainstreaming and implementing ES in landscape planning and decision-making are still in their infancy. The objective of this special issue, therefore, is to explore requirements for, approaches to, and potential impacts of, integrating ES in landscape planning and management. The issue includes three key research themes: (i) Requirements and interests of planners and decision-makers for integrating ES in different application contexts, (ii) Approaches to applying ES in (participatory) planning, and (iii) Potential impacts of integrating ES in policy and decision-making. These themes are addressed by 12 papers that refer to case studies in Africa, Australia, and Europe. Four lessons are highlighted: (i) Information on ES is considered useful by many practitioners, but the type, production and communication of ES information need to be adapted to the specific context of a planning case; (ii) A broad range of approaches are available for integrating the ES concept in (participatory) planning with different and complementary contributions to decision-support; (iii) Effectively integrating ES in planning requires careful scoping of the context, objectives and capacities; (iv) Integrating ES in planning can effectively support the co-production of relevant knowledge and the collaboration of diverse actors. A new research field of 'Planning-for-ES Science' is emerging which focuses on, among other issues, the critical evaluation of real-world case studies of applying the ES concept in different fields of practice.!://WOS:000342078600001Times Cited: 0 0921-2973WOS:00034207860000110.1007/s10980-014-0085-0|?BAlbert, Christian Hauck, Jennifer Buhr, Nina von Haaren, Christina2014What ecosystem services information do users want? Investigating interests and requirements among landscape and regional planners in Germany 1301-1313Landscape Ecology298Oct7While political and scientific interests in ecosystem services (ES) information increases, actual implementation in planning still remains limited. We investigated how landscape and regional planners in Germany already use environmental information, and explored their perceptions concerning an integration of additional information on ES in their work. Four themes are addressed: (1) existing decision-making contexts, (2) current use of environmental information, (3) perceived options for integrating ES information, and (4) useful ES information formats. The research method consists of semi-structured interviews and a web-based survey with German landscape and regional planners. Results are disaggregated between landscape and regional planners, as well as planners with and without prior knowledge of the ES concept. Our results illustrate that a broad range of environmental information is already used that could be associated with ES, but the two most frequently consulted data, species and habitats, relate more to biodiversity. Stronger integrating ES information in planning was generally perceived as useful. However, implementation would often require a mandate from higher-ranking policy levels and the provision of appropriate resources. Project-oriented planning, public information and regional development were seen as promising application contexts. Contrary to our expectations, planners with prior knowledge of the ES concept did not evaluate the usefulness of ES information significantly more optimistic. No single optimal ES information format (ordinal, cardinal, economic valuation) emerged, but context-specific combinations were proposed. The results present valuable guidance for studies and assessments that aim at addressing the ES information needs and requirements of decision makers, and planners in particular.!://WOS:000342078600003Times Cited: 3 0921-2973WOS:00034207860000310.1007/s10980-014-9990-53<7OAlderman, J. McCollin, D. Hinsley, S. A. Bellamy, P. E. Picton, P. Crockett, R.2005}Modelling the effects of dispersal and landscape configuration on population distribution and viability in fragmented habitat857-870Landscape Ecology207?bird dispersal; habitat fragmentation; isolation; metapopulation; PatchMapper; perceptual range; woodland; Sitta europaea; habitat threshold NUTHATCH SITTA-EUROPAEA; LEVEL PERCEPTUAL ABILITIES; CONSERVATION BIOLOGY; REPRODUCTIVE SUCCESS; EURASIAN NUTHATCH; NATURAL CAVITIES; SPATIAL MODELS; FOREST; ECOLOGY; BUTTERFLIESArticleNovLandscape configuration and dispersal characteristics are major determinants of population distribution and persistence in fragmented habitat. An individual-based spatially explicit population model was developed to investigate these factors using the distribution of nuthatches in an area of eastern England as an example. The effects of immigration and increasing the area of breeding quality habitat were explored. Predictions were compared with observed population sizes in the study area. Our model combined a nuthatch population simulator based on individual behaviour with a grid-based representation of the landscape; nuthatch life cycle and immigration parameters were user selectable. A novel aspect of the model is user-selection of habitat perceptual range. Using a realistic set of parameters, the number of breeding pairs predicted by the model matched observed numbers. According to model simulations, the main cause of nuthatch scarcity in the study area was the inability of patches to support viable populations without immigration from elsewhere. Modelled habitat management, which increased breeding quality habitat in existing woods, lowered the threshold above which the study area population became self-sustaining. The existence of a large core habitat area was critical in producing a self-sustaining population in this landscape, the same area in dispersed small woods failed to sustain populations.://000233036300007  ISI Document Delivery No.: 980RQ Times Cited: 1 Cited Reference Count: 67 Cited References: ADLER FR, 1994, THEOR POPUL BIOL, V45, P41 ALDERMAN J, 2004, LANDSCAPE ECOLOGY TR, P76 ANDREN H, 1994, OIKOS, V71, P355 BELLAMY PE, 1998, OECOLOGIA, V115, P127 BIEDERMANN R, 2004, J BIOGEOGR, V31, P1179 BIRCHAM PMM, 1994, ATLAS BREEDING BIRDS CAIN ML, 1985, ECOLOGY, V66, P876 CLARK JS, 1996, BIRDS HUNTINGDON PET COWLEY MJR, 2000, J APPL ECOL S1, V37, P60 CURRIE D, 1998, BELG J ZOOL, V128, P49 DUNNING JB, 1995, ECOL APPL, V5, P3 ENOKSSON B, 1995, LANDSCAPE ECOL, V10, P267 FAHRIG L, 1988, APPL MATH COMPUT, V27, P53 FORMAN R, 1995, LAND MOSAICS ECOLOGY GIBBONS DW, 1993, NEW ATLAS BREEDING B HALSTEAD AJ, 2004, BR J ENTOMOL NAT HIS, V17, P131 HANSKI I, 1998, NATURE, V396, P41 HENEIN K, 1998, OIKOS, V81, P168 HINSLEY SA, 1995, J AVIAN BIOL, V26, P94 HINSLEY SA, 1996, P ROY SOC LOND B BIO, V263, P307 JONES RA, 2004, BR J ENTOMOL NAT HIS, V17, P137 LANDE R, 1999, AM NAT, V154, P271 LAURANCE WF, 1991, CONSERV BIOL, V5, P79 LENNON JJ, 2002, GLOBAL ECOL BIOGEOGR, V11, P103 LIMA SL, 1996, TRENDS ECOL EVOL, V11, P131 LIU JG, 1995, CONSERV BIOL, V9, P62 LURZ PWW, 2001, LANDSCAPE ECOL, V16, P407 MATTHYSEN E, 1986, ARDEA, V74, P117 MATTHYSEN E, 1989, AUK, V106, P560 MATTHYSEN E, 1989, ORNIS SCAND, V20, P278 MATTHYSEN E, 1990, AUK, V107, P86 MATTHYSEN E, 1995, OIKOS, V72, P375 MATTHYSEN E, 1998, AUK, V115, P955 MATTHYSEN E, 1998, NUTHATCHES NEWTON I, 1986, SPARROWHAWK NILSSON SG, 1976, ORNIS SCAND, V7, P179 NILSSON SG, 1987, J ANIM ECOL, V56, P921 OOSTERMEIJER JGB, 2002, BIOL CONSERV, V104, P339 OPDAM P, 1985, BIOL CONSERV, V34, P333 ORMEROD SJ, 2000, J APP ECOL S1, V37, P1 PRAVOSUDOV VV, 1993, ORNIS SCAND, V24, P290 PRAVOSUDOV VV, 1993, WILSON BULL, V105, P475 PULLIAM HR, 1992, ECOL APPL, V2, P165 RICKETTS TH, 2001, AM NAT, V158, P87 RUCKELSHAUS M, 1997, CONSERV BIOL, V11, P1298 SAMWAYS MJ, 1989, ENVIRON CONSERV, V16, P217 SAUNDERS DA, 1991, BIOL CONSERV, V1, P18 SCHIPPERS P, 1996, ECOGRAPHY, V19, P97 SCHOOLEY RL, 2003, OIKOS, V102, P559 SIMBERLOFF D, 1995, IBIS S, V137, P105 SMITH S, 2002, NATL INVENTORY WOODL STEFFANDEWENTER I, 2000, ECOL LETT, V3, P449 SUTCLIFFE OL, 1996, CONSERV BIOL, V10, P1359 TRAVIS JMJ, 2000, ECOL LETT, V3, P163 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 VILLARD MA, 1999, CONSERV BIOL, V13, P774 WALSH AL, 1996, J APPL ECOL, V33, P519 WANG RJ, 2004, ECOL ENTOMOL, V29, P367 WENNERGREN U, 1995, OIKOS, V74, P349 WESOLOWSKI T, 1991, ORNIS SCAND, V22, P143 WIENS JA, 1994, IBIS, V137, P97 WIENS JA, 1997, OIKOS, V78, P257 WITH KA, 1997, CONSERV BIOL, V11, P1069 WITH KA, 1999, CONSERV BIOL, V13, P314 ZOLLNER PA, 1997, OIKOS, V80, P51 ZOLLNER PA, 1999, ECOLOGY, V80, P1019 ZOLLNER PA, 2000, LANDSCAPE ECOL, V15, P523 0921-2973 Landsc. Ecol.ISI:000233036300007Univ Coll Northampton, Sch Appl Sci, Northampton NN2 7AL, England. Ctr Ecol & Hydrol, Huntingdon PE28 2LS, Cambs, England. Alderman, J, 2 Friars Ave, Northampton, England. jolyon.alderman@btinternet.comEnglish<7j-Ales, R. F. Martin, A. Ortega, F. Ales, E. E.1992gRecent changes in landscape structure and function in a mediterranean region of SW Spain (1950–1984) 3-18Landscape Ecology71eAGROECOLOGY; DONANA-NATIONAL-PARK; BIOLOGICAL CONSERVATION; GUADALQUIVIR VALLEY; SIERRA-MORENA; SPAINArticleApriRecent economic development has altered landscape structure and function of a mediterranean region in Southwestern Spain. Intensive agricultural systems have concentrated in the more fertile areas, while marginal ones have been abandoned. As a result, landscape structure has changed. Consequences of this structural change on landscape processes are discussed.://A1992HX80900001 IISI Document Delivery No.: HX809 Times Cited: 23 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1992HX80900001PALES, RF, UNIV SEVILLA,DEPT BIOL VEGETAL & ECOL,APDO 1095,E-41080 SEVILLE,SPAIN.Englishn|7 -Ales, R. F. Martin, A. Ortega, F. Ales, E. E.1992dRecent Changes in Landscape Structure and Function in a Mediterranean Region of Sw Spain (1950-1984)3-18Landscape Ecology71`agroecology donana-national-park biological conservation guadalquivir valley sierra-morena spainApriRecent economic development has altered landscape structure and function of a mediterranean region in Southwestern Spain. Intensive agricultural systems have concentrated in the more fertile areas, while marginal ones have been abandoned. As a result, landscape structure has changed. Consequences of this structural change on landscape processes are discussed.://A1992HX80900001-Hx809 Times Cited:27 Cited References Count:0 0921-2973ISI:A1992HX80900001NAles, Rf Univ Sevilla,Dept Biol Vegetal & Ecol,Apdo 1095,E-41080 Seville,SpainEnglish$o?%Alessandro, Gimona Richard, V. Birnie2002Spatio-temporal modelling of broad scale heterogeneity in soil moisture content: a basis for an ecologically meaningful classification of soil landscapes27-41Landscape Ecology171iBroad scale - Grasslands - Heather - Heterogeneity - Model - Soil landscapes - Soil moisture - VegetationWe describe the classification of landscapes characterised bymineral soil using a model that calculates soil moisture availability on amonthly basis. Scotland is used as a case study area. The model uses potentialsoil moisture deficit, estimated using broad scale (40 × 40 km)climate patterns, in conjunction with meteorological station measurements toobtain finer scale values of climatic soil moisture deficit. Point estimates ofsoil available water are obtained for soil characteristics using appropriatepedotransfer functions, and geostatistical techniques are used to upscale theresults and interpolate to a 1-km grid. Known heterogeneityin soil physical characteristics is used to provide local corrections to thepotential soil moisture deficit, estimated using the climatic variables above.Temporal profiles of monthly water content are modelled for each1-km location and classified into six classes usingunsupervised cluster analysis. The spatial distribution of these classesreflects regional variations in the availability of moisture and energy, onwhich finer-grained topographic patterns are superimposed. In the case study,the broad scale spatial heterogeneity of heathlands and grasslands on mineralsoils in Scotland is shown to be strongly related to the soil moistureclassification. The results can be used in studies investigating the patternsofdistribution of communities at the landscape and regional scale.*http://dx.doi.org/10.1023/A:1015236110766 10.1023/A:1015236110766 References Armstrong H.M., Gordon I.J., Grant S.A., Hutchings N.J., Milne J.A. and Sibbald A.R. 1997. 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Effects of climate change on soil fauna; Responses of enchytraeids, Diptera larvae and tardigrades in a transplant experiment. Applied Soil Ecology 6: 117-134. Chertov O.G. and Komarov A.S. 1997. A model of soil organic matter dynamics. Ecological Modelling 94: 177-189. Deutsch C.V. and Journel A.G. 1992. GSLIB Geostatistical software Library and User Guide. OUP, New York, USA. Edwards C.A. and Bohlen P.J. 1996. Biology and Ecology of Earthworms. 3rd edn. Chapman and Hall, London, UK. Field M. 1983. The Meteorological Office Rainfall and Evaporation Calculation System. Agricultural Water Management 6: 297-306. Goovaerts P. 1997. Geostatistics for Natural Resources Evaluation. OUP, New York, New York, USA. Haxeltine A., Prentice I.C. and Creswell D.I. 1996. A coupled carbon and water flux model to predict vegetation structure. Journal of Vegetation Science 7: 651-666. Heuvelink G.B.M. and Pebesma E.J. 1999. Spatial aggregation and soil process modelling. Geoderma 89: 47-65. Hodkinson I.D., Webb N.R., Bale J.S. and Block W. 1999. Hydrology, water availability and tundra ecosystem function in a changing climate: the need for a closer integration of ideas? Global Change Biology 5: 359-369. Isaaks E.H. and Srivastava R.M. 1989. An Introduction to Applied Geostatistics. Oxford University Press, London, UK. Iverson L.R., Dale M.E., Scott C.T. and Prasad A. 1997. GIS-derived integrated moisture index to predict forest composition and productivity of Ohio forests USA. Landscape Ecology 12: 331-348. Jarvis R.A., Bendelow V.C., Bradley R.I., Carroll D.M., Furness R.R., Kilgour I.N.L. et al. 1984. Soils and their use in northern England. Lawes Agricultural Trust. Rothamsted Experimental station, Harpenden, UK, Soil survey of England and Wales Bulletin no 10. Kabat P., Hutjes R.W.A. and Feddes R.A. 1997. The scaling characteristics of soil parameters: from plot scale heterogeneity to subgrid parametrisation. Journal of Hydrology 190: 363-396. Lance A.N. 1987. Estimating acceptable stocking levels for heather moorland. In: Bell M. and Bunce R.G.H. (eds), Agriculture and Conservation of the Hills and Uplands. ITE, Merlewood, UK. Leiros M.C., Trasar-Cepeda C., Sean S. and Gil-Sotres F. 1999. Dependence of mineralisation of soil organic matter on temperature and moisture. Soil Biology and Biochemistry 31: 227-335. Li J. and Islam S. 1999. On the estimation of soil moisture profile and surface fluxes partitioning from sequential assimilation of surface layer soil moisture. Journal of Hydrology 220: 86-103. Lilly A. and Matthews K. 1994. A soil wetness class map of Scotland: new assessments of soil and climate data for land evaluation. Geoforum 25: 371-379. Matthews K.B., MacDonald A., Aspinall R.J., Hudson G., Law A.N.R. and Paterson E. 1994. Climatic soil moisture deficit-climate and soil data integration in a GIS. Climatic Change 28: 273-287. MacDonald A., Matthews K.B., Paterson E. and Aspinall R.J. 1994. 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A meteorological system for estimating evaporation, soil moisture deficit and hydrologically effective rainfall. Meteorological Office, Interim report. Yoke K.A. and Rennie J.C. 1996. Landscape ecosystem classification in the Cherokee National Forest, east Tennessee, USA. Environmental Monitoring and Assessment 39: 323-338. iLand Use Change Programme, The Macaulay Land Use Research Institute (MLURI), Craigiebuckler, AB15 8QH, UK<7<Allen, C. R. Pearlstine, L. G. Wojcik, D. P. Kitchens, W. M.2001The spatial distribution of diversity between disparate taxa: Spatial correspondence between mammals and ants across South Florida, USA453-464Landscape Ecology165ants biodiversity Florida Gap Analysis mammals scale spatial analysis spatial correspondence species richness SPECIES RICHNESS ENVIRONMENTAL-IMPACT BIOLOGICAL DIVERSITY GUILD CONCEPT THIEF ANTS HYMENOPTERA FORMICIDAE CONSERVATION MANAGEMENTArticleJulDGap Analysis takes a proactive landscape-level approach to conserving native species by identifying nodes of high biological diversity. It uses vertebrate species richness as an index of overall biological diversity. However, it remains unknown whether or not the spatial distribution of vertebrate diversity corresponds with the diversity of other taxa. We tested whether landscape-level diversity patterns corresponded between a vertebrate and an invertebrate taxon, mammals and ants, across the southern half of the Florida peninsula, USA. Composite digital maps with a 30-m spatial resolution were produced for each taxon. Spatial correspondence between the taxa was determined by normalizing and then subtracting the composite maps. There were large areas of spatial correspondence - indicating that richness between mammals and ants was similar over much of southern Florida. However, spatial correspondence occurred where the richness of both taxa was low or moderate, and areas with the highest species richness (highest 20%) for each taxon, the explicit focus of Gap Analyses, corresponded over only 8752 ha. Gap Analysis provides a much needed assessment of landscape-level diversity patterns and proactive reserve design, but it must be explicit that the results are applicable for vertebrate diversity, which does not necessarily correspond with diversity patterns of other taxa. The two taxa investigated differ by orders of magnitude in the scale that they perceive their environment, and it is likely that diversity hotspots vary as the scale of investigation - and the taxa mapped - vary.://000170952100006 ISI Document Delivery No.: 471WR Times Cited: 4 Cited Reference Count: 78 Cited References: *NAT CONS, 1997, INT CLASS EC COMM TE ALLEN CR, 1998, GAP ANAL B, V7, P10 ALLEN CR, 2001, BIOL CONSERV, V99, P135 BLAIR FW, 1935, AM MIDL NAT, V16, P801 BLAIR FW, 1935, J MAMMAL, V16, P271 BUREN WF, 1977, P INT SOC CITRICULT, V2, P496 CARROLL JF, 1975, THESIS U FLORIDA GAI CHAPMAN JA, 1982, WILD MAMMALS N AM COLE BJ, 1982, PSYCHE, V89, P351 COX J, 1994, CLOSING GAPS FLORIDA CREIGHTON WS, 1950, B MUS COMP ZOOL HARV, V104, P1 CRIST EP, 1984, PHOTOGRAMM ENG REM S, V50, P343 DEYRUP M, 1986, FLA ENTOMOL, V69, P206 DEYRUP M, 1989, FLA ENTOMOL, V72, P91 DEYRUP MA, 1988, FLORIDA ENTOMOLOGIST, V71, P163 DEYRUP MA, 1991, P 4 S NAT HIST BAH S, P15 EISNER T, 1995, SCIENCE, V268, P1231 GASTON KJ, 1991, CONSERV BIOL, V5, P283 GUNDERSON LH, 1982, T655 S FLOR RES CTR GUNDERSON LH, 1982, T664 S FLOR RES CTR GUNDERSON LH, 1982, T665 S FLOR RES CTR GUNDERSON LH, 1982, T666 S FLOR RES CTR GUNDERSON LH, 1986, SFRC8603 HAMILTON WJ, 1941, AM MIDL NAT, V25, P686 HANDEL SN, 1981, B TORREY BOT CLUB, V108, P430 HUMPHREY SR, 1992, RARE ENDANGERED BIOT, V1 HURRO RL, 1987, ENDANGERED SPECIES U, V4, P1 HYOLLDOBLER B, 1990, ANTS IVEY RD, 1959, J MAMMAL, V40, P585 JOHNSON C, 1986, INSECTA MUNDI, V1, P243 KERR JT, 1997, CONSERV BIOL, V11, P1094 KLOTZ JH, 1995, FLA ENTOMOL, V78, P109 KREMEN C, 1993, CONSERV BIOL, V7, P796 KUSHLAN JA, 1979, BIOL CONSERV, V15, P281 LANDRES PB, 1983, ENVIRON MANAGE, V7, P393 LANDRES PB, 1988, CONSERV BIOL, V2, P316 LAYNE J, 1984, ENV S FLORIDA PAST P, V2, P269 MACKAY WP, 1993, SOCIOBIOLOGY, V22, P1 MASER C, 1984, PNW172 USDA FOR SERV MILLER RI, 1994, MAPPING DIVERSITY NA MOORE JC, 1946, J MAMMAL, V27, P49 NOSS RF, 1994, SAVING NATURES LEGAC NOSS RF, 1995, ENDANGERED ECOSYSTEM OLMSTED I, 1980, T547 S FLOR RES CTR OLMSTED I, 1980, T586 S FLOR RES CTR OLMSTED I, 1980, T604 S FLOR RES CTR OLMSTED I, 1981, T620 S FLOR RES CTR OLMSTED I, 1983, SFRC8305 PEARSON PG, 1954, AM MIDL NAT, V51, P468 POURNELLE GH, 1950, J MAMMAL, V31, P310 PRENDERGAST JR, 1993, NATURE, V365, P335 PRENDERGAST JR, 1997, ECOGRAPHY, V20, P210 RISCH SJ, 1982, ECOLOGY, V63, P1979 SCHNEIRLA TC, 1944, AM MUS NOVIT, V1261, P1 SCOTT JM, 1987, BIOSCIENCE, V37, P782 SCOTT JM, 1993, WILDLIFE MONOGRAPH, V123 SEVERINGHAUS WD, 1981, ENVIRON MANAGE, V5, P187 SHAFER CL, 1990, NATURE RESERVES ISLA SHERMAN HB, 1952, Q J FLORIDA ACAD SCI, V15, P100 SMITH DR, 1979, CATALOG HYMENOPTERA, V2, P1323 SMITH MR, 1930, FLORIDA ENTOMOL, V14, P1 SMITH MR, 1933, FLORIDA ENTOMOL, V17, P21 SMITH MR, 1944, FLA ENTOMOL, V27, P14 STARNER BA, 1956, Q J FLORIDA ACAD SCI, V19, P153 THOMPSON CR, 1989, FLA ENTOMOL, V72, P268 THOMPSON CR, 1989, FLA ENTOMOL, V72, P697 VANPELT AF, 1947, THESIS U FLORIDA GAI VANPELT AF, 1950, THESIS U FLORIDA GAI VANPELT AF, 1956, AM MIDL NAT, V56, P358 VANPELT AF, 1958, AM MIDL NAT, V59, P1 VANPELT AF, 1966, J E MITCHELL SCI SOC, V82, P35 VERNER J, 1984, ENVIRON MANAGE, V8, P1 WATKINS JF, 1985, J KANSAS ENTOMOLOGIC, V58, P479 WHEELER WM, 1932, J NY ENTOMOL SOC, V40, P1 WILSON EO, 1964, BREVIORA, V210, P1 WILSON EO, 1985, BIOSCIENCE, V35, P700 WILSON EO, 1988, BIODIVERSITY WILSON EO, 1992, DIVERSITY LIFE 0921-2973 Landsc. Ecol.ISI:000170952100006Univ Florida, Florida Cooperat Fish & Wildlife Res Unit, Gainesville, FL 32611 USA. Allen, CR, Clemson Univ, S Carolina Cooperat Fish & Wildlife Res Unit, USGS, Biol Resource Div, Clemson, SC 29634 USA.English1ڽ7/fAllen, JenicaM Leininger, ThomasJ Hurd, JamesD, Jr. Civco, DanielL Gelfand, AlanE Silander, JohnA, Jr.2013cSocioeconomics drive woody invasive plant richness in New England, USA through forest fragmentation 1671-1686Landscape Ecology289Springer NetherlandsNortheastern United States Invasive Plant Atlas of New England IPANE Alien invasive species Exotic plants Social-ecological Land use/land cover 2013/11/01+http://dx.doi.org/10.1007/s10980-013-9916-7 0921-2973Landscape Ecol10.1007/s10980-013-9916-7English[?5Michael F. Allen Lawrence E. Hipps Gene L. Wooldridge1989hWind dispersal and subsequent establishment of VA mycorrhizal fungi across a successional arid landscape165-171Landscape Ecology23omycorrhizal fungi, wind dispersal, landscape, establishment, mesoscale wind patterns, landscape ecology, desert Wind is an important vector in the dispersal of microorganisms to new habitats. However, wind dispersal is generally assumed to be random or logarithmically related to distance. We assessed the wind dispersal and subsequent establishment of an important group of plant symbionts, VA mycorrhizal fungi, across a 74 Ha recontoured surface mine. Winds were predominantly westerly aloft, but due to complex north-south ridges, up-valley, thermally-driven air flows developed. Patterns of spore dispersal were tested by a combination of released spore mimics from the potential source areas and by assessing the composition of species deposited across the site and in the putative source areas. Survival of the fungi was assessed two years after the dispersal patterns were monitored. The spore mimics moved in predictable but complex patterns across the site depending on the interactions of surface and upper winds. Mimics from the valley sources moved up the valleys in the lower flows and occasionally over the ridges in the upper winds. Those from the ridge approximately 2 km distant were entrained in the upper air flows and deposited all across the site. The VA mycorrhizal fungal species compositions from the soils correlated with the deposition patterns measured with the mimics. Fungal survival showed a pattern similar to dispersal; the fungi often survived in habitats not resembling the habitat of origin although some selection in both more favorable and less favorable sites occurred. These data suggest that microbial dispersal even by wind is predictable if the wind characteristics are known, that the VA mycorrhizal fungi from the site can survive in habitats different from their habitats of origin, but that some selection among species may occur after deposition.q|?X2Almeida-Gomes, Mauricio Rocha, Carlos Frederico D.2014dLandscape connectivity may explain anuran species distribution in an Atlantic forest fragmented area29-40Landscape Ecology291Jan"In this work we evaluated anuran species distribution in an Atlantic forest fragmented landscape, in the state of Rio de Janeiro, Brazil. Sampling was carried out in three continuous forest sites, 12 forest fragments, and five pasture areas (matrix). We recorded, by visual encounter surveys, 2,495 individuals from 50 amphibian species for all sampled areas. Considering the pooled data, higher richness occurs in continuous forest area. Additionally, more than a third of species that occurred in continuous forest area did not occur in fragments or in matrix. Both ordination analyses showed that continuous forest sites clustered together and matrix areas seemed to be separated from other areas. This ordination resulted from the existence of species occurring only in continuous forest, suggesting that these species may be sensitive to habitat fragmentation. Besides, matrix appears separated from other areas due to occurrence of frog species typical from disturbed environments, which are not recorded in continuous forest sites or in sampled fragments. By analyzing the effect of landscape metrics, we found that there was a tendency for fragments with lower isolation to have higher species richness and proportion of species which did not occur in matrix areas and amphibian local communities seems to be affected in a more local scale by habitat changes. Because local matrix is apparently hostile to typically forest-associated amphibian species, many of them may be unable to reach most isolated fragments by dispersal, which may explain observed results.!://WOS:000330827600003Times Cited: 5 0921-2973WOS:00033082760000310.1007/s10980-013-9898-5^?=Anantha, Prasad2003WBook review, Lessons from Amazonia, The Ecology and Conservation of a Fragmented Forest214-215Landscape Ecology182*http://dx.doi.org/10.1023/A:1024476024119 10.1023/A:1024476024119 This revised version was published online in August 2006 with corrections to the Cover Date. Anantha Prasad Email: aprasad@fs.fed.us REFERENCES van Apeldoorn R.C., Celada C. and Nieuwenhuizen W. 1994. Dis-tribution and dynamics of the red squirrel (Sciurus vulgaris L.) in a landscape with fragmented habitat. Landscape Ecology 9: 227–235. Arnold G.W., Weeldenburg J.R. and Ng V.M. 1995. 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Metapopula-tion persistence of an endangered butterfly in a fragmented landscape. Oikos 72: 21–28. Hill J.K., Thomas C.D. and Lewis O.T. 1996. Effects of habitat patch size and isolation on dispersal by Hesperia comma but-terflies: implications for metapopulation structure. Journal of Animal Ecology 65: 725–735. Hokit D.G., Stith B.M. and Branch L.C. 1999. Effects of landscape structure in Florida scrub: a population perspective. Ecological Applications 9: 124–134. Hokit D.G., Stith B.M. and Branch L.C. 2001. Comparison of two types of metapopulation models in real and artificial landscapes. Conservation Biology 15: 1102–1113. Hosmer D.W. and Lemeshow S. 1989. Applied Logistic Regression. John Wiley and Sons, New York, New York, USA. Jiménez J.E. 1995. Conservation of the last wild chinchilla (Chin-chilla lanigera) archipelago: a metapopulation approach. Vida Silvestre Neotropical 4: 89–97. Jonsen I.D., Bourchier R.S. and Roland J. 2001. The influence of matrix habitat on Aphthona flea beetle immigration to leafy spurge patches. Oecologia 127: 287–294. Keyghobadi N., Roland J. and Strobeck C. 1999. Influence of landscape on the population genetic structure of the alpine butterfly Parnassus smintheus (Papilionidae). Molecular Ecology 8: 1481–1495. Kindvall O. 1996. Habitat heterogeneity and survival in a bush-cricket metapopulation. Ecology 77: 207–214. King P.S. 1987. Macro-and microgeographic structure of a spa-tially subdivided beetle species in nature. Evolution 41: 401–416. León R.J.C., Bran D., Collantes M., Paruelo J.M. and Soriano A. 1998. Grandes unidades de vegetación de la Patagonia extra andina. Ecología Austral 8: 125–144. Mazerolle M.J. and Villard M.-A. 1999. Patch characteristics and landscape context as predictors of species presence and abun-dance: a review. Ecoscience 6: 117–124. Micol T., Doncaster C.P. and Mackinlay L.A. 1994. 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SPSS Base 10.0 Applications Guide. SPSS Inc., Chicago, Illinois, USA. Stith B.S., Fitzpatrick J.W., Woolfenden G.E. and Pranty B. 1996. Classification and conservation of metapopulations: a case study of the Florida scrub jay. In: McCullough D.R. (ed.), Me-tapopulations and Wildlife Conservation. Island Press, Wash-ington, DC, USA, pp. 187–216. Vos C.C., Antonisse-de Jong A.G., Goedhart P.W. and Smulders M.J.M. 2001. Genetic similarity as a measure for connectivity between fragmented populations of the moor frog (Rana arva-lis). Heredity 86: 598–608. Walker R.S. 2001. Effects of Landscape Structure on the Distribu-tion of Mountain vizcacha (Lagidium viscacia) in the Patago-nian Steppe. PhD Thesis, University of Florida, Gainesville, Florida, USA, 100 pp. Walker R.S., Ackermann G., Schachter-Broide J., Pancotto V. and Novaro A.J. 2000. Habitat use by mountain vizcachas (Lagid-ium viscacia Molina, 1782) in the Patagonian steppe. Zeitschrift für Säugetierkunde 65: 293–300. Wiens J.A. 1997. Metapopulation dynamics and landscape ecology. In: Hanski I. and Gilpin M.E. (eds), Metapopulation Biology: Ecology, Genetics and Evolution. Academic Press, San Diego, California, USA, pp. 43–68. Wilcox B.A. 1980. Insular ecology and conservation. In: Soule M.E. and Wilcox B.A. (eds), Conservation Biology: An Evolu-tionary-Ecological Perspective. Sinauer Assoc., Inc., Sunderland, Massachusetts, USA, pp. 95–117. cAnantha Prasad1 (1) Northeastern Research Station, USDA Forest Service, Delaware, OH 43015, USA ~?nAndersen, B. J.20084Research in the journal Landscape Ecology, 1987-2005129-134Landscape Ecology23This paper examined the types of research papers published in the journal Landscape Ecology. Based on the original six criteria developed by John Wiens in his 1992 study of the first five volumes, changes over time through Volume 20 were investigated. From this brief study, there was found some progress in diversifying landscape ecology. There was a modest increase in papers addressing sociological subjects, a more spread out distribution of study scales, more use of descriptive, methodological and GIS approaches, and more employment of mathematical and statistical approaches. The lack of experimental studies continued through Volume 20. A suggestion for further work is advanced."://WOS:000252636100002 Times Cited: 1WOS:000252636100002(10.1007/s10980-007-9187-2|ISSN 0921-2973<7Andersen, M. D. Baker, W. L.2006kReconstructing landscape-scale tree invasion using survey notes in the Medicine Bow Mountains, Wyoming, USA243-258Landscape Ecology212forest-grassland ecotone; GLO surveys; logistic regression; Southern Rocky Mountains; vegetation dynamics; woody encroachment ASPEN POPULUS-TREMULOIDES; LAND SURVEY RECORDS; SUB-ALPINE MEADOWS; NATIONAL-PARK; CINNABAR PARK; FOREST; COLORADO; GRASSLANDS; RANGE; ENCROACHMENTArticleFeb We assessed landscape-scale invasions of openings in mountain forests by native tree species since EuroAmerican settlement (ca. 1870-1899). We reconstructed historical openings across a 250,240 ha area in the Medicine Bow Mountains, Wyoming, using notes from the original General Land Office (GLO) surveys, and compared historical openings to modern openings interpreted from digital aerial photography. We constructed logistic regression models to describe and predict tree invasion, based on a set of environmental and land use predictors. Openings have decreased by about 7.3% in the last ca. 110 years. Invasion was more likely to occur on moister sites, indicated by high values for steady-state wetness, low values for evaporative demand, proximity to streams, and topographic settings in basins or channels. More invasion also occurred on unprotected public land, in openings surrounded by lodgepole pine and aspen, and on mesic soils. The relatively slow rates of invasion in the study area may be driven by climate and land use.://000235866400008 ISI Document Delivery No.: 019WC Times Cited: 1 Cited Reference Count: 69 Cited References: *ESRI, 1996, US ARCVIEW GIS *SAS I INC, SAS *US GEOL SURV, 1994, BEDR GEOL WYOM *US GEOL SURV, 1999, 30 MET NAT EL DAT TI *USDA, 1999, SOIL TAX BAS SYST SO AKAIKE H, 1983, B INT STAT I, V50, P277 ARNO SF, 1986, J RANGE MANAGE, V39, P272 BEERS TW, 1966, J FOREST, V64, P691 BEHAN MJ, 1958, THESIS U WYOMING LAR BOURDO EA, 1956, ECOLOGY, V37, P754 BRAGG TB, 1976, J RANGE MANAGE, V29, P19 BUECHLING A, 2004, CAN J FOREST RES, V34, P1273 BUFFINGTON LC, 1965, ECOL MONOGR, V35, P139 BUOL SW, 1989, SOIL GENESIS CLASSIF, P527 CANHAM CD, 1984, ECOLOGY, V65, P803 COOK ER, 2004, IGBP DATA CONTRIBUTI COPPEDGE BR, 2001, ECOL APPL, V11, P47 DALY C, 2002, CLIMATE RES, V22, P99 DOERING WR, 1992, ARCTIC ALPINE RES, V24, P27 DUNHAM KM, 2003, BIOL CONSERV, V113, P111 DUNWIDDIE PW, 1977, ARCTIC ALPINE RES, V9, P393 ELLIOTT GP, 2004, J BIOGEOGR, V31, P733 FIELDS JR, 1982, ACSM ASP CONV FALLS, P115 GALATOWITSCH SM, 1990, GREAT BASIN NAT, V50, P181 GALLANT JC, 1996, COMPUT GEOSCI, V22, P713 GESSLER PE, 1995, INT J GEOGR INF SYST, V9, P421 GROVE JM, 1988, LITTLE ICE AGE HANSEN K, 1995, FOREST CONSERV HIST, V39, P66 HESSL AE, 1997, ARCTIC ALPINE RES, V29, P173 HOSMER DW, 1989, APPL LOGISTIC REGRES HOWE E, 2003, ANN ASSOC AM GEOGR, V93, P797 JAKUBOS B, 1993, ARCTIC ALPINE RES, V25, P382 JENNESS JS, 2004, WILDLIFE SOC B, V32, P829 JESSUP KE, 2003, J VEG SCI, V14, P841 JOBBAGY EG, 2004, GLOBAL CHANGE BIOL, V10, P1299 JOHNSON WM, 1962, B U WYOMING, V387 KAUL RB, 1983, P 7 N AM PRAIR C SW, P95 KAY CE, 1997, J FOREST, V95, P4 KING JE, 2003, EDUC PSYCHOL MEAS, V63, P392 KIPFMUELLER KF, 2000, J BIOGEOGR, V27, P71 KNIGHT DH, 1994, MOUNTAINS PLAINS ECO KNIGHT SH, 1990, WYOMING GEOLOGICAL S, V4 KULAKOWSKI D, 2004, ECOL APPL, V14, P1603 LIVERMORE M, 1991, ERA FICTITIOUS SURVE MANIES KL, 2000, LANDSCAPE ECOL, V15, P741 MAST JN, 1997, FOREST ECOL MANAG, V93, P181 MENARD S, 2002, APPL LOGISTIC REGRES MERRILL EH, 1996, WYOMING GAP ANAL PRO, P250 MILLER EA, 1998, J VEG SCI, V9, P265 PATTEN DT, 1963, ECOL MONOGR, V33, P375 PATTEN DT, 1969, AM MIDL NAT, V82, P229 PIEPER RD, 1990, J RANGE MANAGE, V43, P413 ROCHEFORT RM, 1996, ARCTIC ALPINE RES, V28, P52 SCHULTE LA, 2001, J FOREST, V99, P5 SCHWARZ G, 1978, ANN STAT, V6, P461 SHTATLAND ES, 2001, 22226 SAS I INC SKINNER CN, 1995, LANDSCAPE ECOL, V10, P219 STARR CR, 1974, THESIS U WYOMING LAR STEWART LO, 1935, PUBLIC LAND SURVEYS THOMPSON B, 1995, EDUC PSYCHOL MEAS, V55, P525 THYBONY S, 1985, MED BOWS WYOMINGS MO URBAN DL, 2000, LANDSCAPE ECOL, V15, P603 VALE TR, 1978, AM MIDL NAT, V100, P277 VALE TR, 1987, ANN ASSOC AM GEOGR, V77, P1 WAKELYN LA, 1987, J WILDLIFE MANAGE, V51, P904 WEARNE LJ, 2001, ARCT ANTARCT ALP RES, V33, P369 WIRSIG JM, 1973, THESIS U WYOMING LAR WOOD JD, 1996, THESIS U LEICESTER L ZIER JL, IN PRESS FOREST ECOL 0921-2973 Landsc. Ecol.ISI:000235866400008Univ Wyoming, Dept Geog, Dept 3371, Laramie, WY 82071 USA. Baker, WL, Univ Wyoming, Dept Geog, Dept 3371, 1000 E Univ Ave, Laramie, WY 82071 USA. bakerwl@uwyo.eduEnglishe<7Anderson, D. P.2005TSpecial issue on reciprocal interactions between herbivores and landscapes - Preface255-256Landscape Ecology203Editorial MaterialApr://000231824400001 HISI Document Delivery No.: 963RU Times Cited: 0 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:000231824400001English<7lAnderson, D. P. Forester, J. D. Turner, M. G. Frair, J. L. Merrill, E. H. Fortin, D. Mao, J. S. Boyce, M. S.2005`Factors influencing female home range sizes in elk (Cervus elaphus) in North American landscapes257-271Landscape Ecology203cross validation; forage; heterogeneity; home range kernel; scale; snow-water equivalent WHITE-TAILED DEER; MULE DEER; HABITAT USE; SIMULATION-MODEL; PREDATION RISK; SIERRA-NEVADA; PATCH CHOICE; RED DEER; ROE DEER; PATTERNSArticleAprXHome range size is a result of individual movements and the spatial distribution of a population. While body size, sex, and age are known to influence the area over which an animal ranges, it remains uncertain how landscape heterogeneity influences home range size. We examined elk (Cervus elaphus) seasonal home range sizes in relation to the quantity and spatial heterogeneity of forage biomass, forest cover, topography, snow-water equivalents, and landscape structure in three study landscapes: Yellowstone National Park, Wyoming, USA; eastern slopes of the Canadian Rockies, Alberta; and northern Wisconsin, USA. We used a 95% fixed kernel estimator to measure the home range size and location of all elk. To identify the scales at which important factors influenced home range sizes, we quantified environmental variables within the estimated home range polygon and within concentric circles with radii of 1000, 2000, 3000, 4000, and 5000 in from the home range center. Results indicate that there was an inverse relationship between forage biomass and summer and winter home range sizes in Alberta and Wisconsin, however the relationship was positive in Yellowstone. The size of summer and winter home ranges was positively related to percent forest cover; however this relationship was significant only when forest cover was quantified within the home range polygon or radii that were greater than or equal to 3000 in. Winter home ranges also had a positive relationship with snow-water equivalents. The predictive strength of summer home range models was greatest when landscape variables were quantified within the concentric circles with a radius of 3000 in or more, whereas the predictive strength of the winter models was greatest within the estimated home range polygon. Results suggest that elk ranging patterns reflected complex trade-offs that affect foraging, group dynamics, movement energetics, predation avoidance and thermal regulation. The multi-scale analysis indicates that elk based home ranging decisions on an area equal to their home range, but areas outside of the estimated home range were also important.://000231824400002 CISI Document Delivery No.: 963RU Times Cited: 3 Cited Reference Count: 82 Cited References: *ENV CAN, 2004, CAN CLIM NORM AV 197 *ESRI, 2001, ARCGIS VERS 8 1 *SAS I INC, 1999, SAS ONLINEDOC VERS 8 *STAT, 2001, STAT REF MAN REL 7 *USDA, 1986, FIN ENV IMP STAT CHE *USDA, 2001, CDS DAT DICT *WIDNR, 1998, WISCLAND LAND COV WL ALBON SD, 1992, OIKOS, V65, P502 ALTENDORF KB, 2001, J MAMMAL, V82, P430 ANDERSON DP, IN PRESS J WILDLIFE AYCRIGG JL, 1997, J MAMMAL, V78, P468 BEYER HL, 2004, HAWTHS ANAL TOOLS AR BOWYER RT, 1981, J MAMMAL, V62, P574 BOWYER RT, 1998, J MAMMAL, V79, P415 BURNHAM KP, 2002, MODEL SELECTION INFE CAIN ML, 1985, ECOLOGY, V66, P876 CARR AP, 1998, HRE HOME RANGE EXTEN CLAYTON MK, 1995, J AM STAT ASSOC, V90, P753 COOK JG, 1998, WILDLIFE MONOGR, V141, P1 COOK RC, 2004, J MAMMAL, V85, P714 CRAWFORD HS, 1984, WHITE TAILED DEER EC, P629 DEMARCHI MW, 1993, CAN J FOREST RES, V23, P2419 DESPAIN DG, 1990, YELLOWSTONE VEGETATI DIRKS RA, 1982, 6 US DEP INT NAT PAR DIXON GD, 1997, CUMULATIVE EFFECTS M FORD RG, 1983, AM ZOOL, V23, P315 FORTIN D, IN PRESS ECOLOGY FRAIR JL, 2005, LANDSCAPE ECOLOGY FRYXELL JM, 1997, INDIVIDUAL BEHAV COM GOODISON BE, 1981, HDB SNOW PRINCIPLES, P191 GRACE J, 1979, J APPL ECOL, V16, P37 HOBBS NT, 1989, WILDLIFE MONOGR, V101, P1 HOOGE PN, 2002, ANIMAL MOVEMENT PROG HUOT J, 1974, CAN FIELD NAT, V88, P293 JONES PF, 2002, CAN FIELD NAT, V116, P183 KALUNZNY SP, 1998, S SPATIAL STATS USER KAREIVA P, 1983, VARIABLE PLANTS HERB KAREIVA P, 1995, NATURE, V373, P299 KIE JG, 1999, J MAMMAL, V80, P1114 KIE JG, 2002, ECOLOGY, V83, P530 KIE JG, 2005, LANDSCAPE ECOLOGY LANGVATN R, 1993, OECOLOGIA, V95, P164 LARSON TJ, 1978, J WILDLIFE MANAGE, V42, P113 LESAGE L, 2000, CAN J ZOOL, V78, P1930 LOFT ER, 1993, CALIF FISH GAME, V79, P145 LOOMIS JB, 1991, J RANGE MANAGE, V44, P395 MAO JS, 2003, THESIS U ALBERTA EDM MCGARIGAL K, 1995, PNWGRT351 USDA FOR S MCNAB BK, 1963, AM NAT, V97, P133 MERRILL EH, 1991, GREATER YELLOWSTONE, P263 MOE SR, 1994, CAN J ZOOL, V72, P1735 MYSTERUD A, 1999, J ZOOL 4, V247, P479 MYSTERUD A, 2001, OECOLOGIA, V127, P30 NAMS VO, 2000, LOCATE 2 USERS GUIDE NICHOLSON MC, 1997, J MAMMAL, V78, P483 OEHLER MW, 2003, MAMMALIA, V67, P385 ONEILL RV, 1988, LANDSCAPE ECOL, V2, P63 PARKER KL, 1984, J WILDLIFE MANAGE, V42, P113 PARKER KL, 1990, J RANGE MANAGE, V43, P73 PAULEY GR, 1993, J WILDLIFE MANAGE, V57, P904 PORTER WP, 2000, AM ZOOL, V40, P597 PORTER WP, 2002, INTEGR COMP BIOL, V42, P431 RELYEA RA, 2000, J WILDLIFE MANAG, V64 SEAMAN DE, 1999, J WILDLIFE MANAGE, V63, P739 SENFT RL, 1987, BIOSCIENCE, V37, P789 SKOVLIN JM, 2002, N AM ELK ECOLOGY MAN, P531 SMITH DW, 2003, BIOSCIENCE, V53, P330 STEWART KM, 2002, J MAMMAL, V83, P229 SWEENEY JM, 1984, J MAMMAL, V65, P524 TAYLOR CR, 1972, SCIENCE, V178, P1096 TUFTO J, 1996, J ANIM ECOL, V65, P715 TURCHIN P, 2003, COMPLEX POPULATION D TURNER MG, 1993, ECOL MODEL, V69, P163 TURNER MG, 1994, ECOL APPL, V4 TURNER MG, 2004, ECOSYSTEMS, V7, P751 WHITE CA, 2003, FOREST ECOL MANAG, V181, P77 WHITE GC, 1992, ANAL WILDLIFE RADIOT WICKSTROM ML, 1984, J WILDLIFE MANAGE, V48, P1285 WILMSHURST JF, 1995, BEHAV ECOL, V6, P209 WITH KA, 1995, ECOLOGY, V76, P2446 WOCKNER G, 2002, SNOW MODEL YELLOWSTO WOLFF JO, 2003, CAN J ZOOL, V81, P266 0921-2973 Landsc. Ecol.ISI:000231824400002Univ Wisconsin, Dept Zool, Madison, WI 53706 USA. Univ Alberta, Dept Biol Sci, Edmonton, AB T6G 2E9, Canada. Univ Laval, Dept Biol, Ste Foy, PQ G1K 7P4, Canada. Anderson, DP, Univ Wisconsin, Dept Zool, 430 Lincoln Dr, Madison, WI 53706 USA. danders3@wisc.eduEnglish p<76 Anderson, G. S. Danielson, B. J.1997bThe effects of landscape composition and physiognomy on metapopulation size: the role of corridors261-271Landscape Ecology125connectivity; corridor; landscape; model; metapopulation; dispersal PEROMYSCUS-LEUCOPUS; POPULATION SURVIVAL; COMPLEX LANDSCAPES; DYNAMICS; DISPERSAL; CONNECTIVITY; ELEMENTS; MODEL; QUALITY; MOUSEArticleOct~We develop and analyze a model that examines the effects of corridor quality, quantity, and arrangement on metapopulation sizes. These ideas were formerly investigated by Lefkovitch and Fahrig (1985) and Henein and Merriam (1990). Our simulations provide results similar to the Henein and Merriam model, indicating that the quality of corridors in a landscape and their arrangement will influence the size of a metapopulation. We then go one step further, describing how corridor arrangement alters the metapopulation, and provide a method for predicting which corridor arrangements should support larger metapopulations. In contrast to the Henein and Merriam model, we find that the number of corridor connections has no influence on the size of a metapopulation in a landscape unless there is an accompanying change in the uniformity of the distribution of corridor connections among patches.://000077684100001 |ISI Document Delivery No.: 150UN Times Cited: 34 Cited Reference Count: 24 Cited References: ADLER GH, 1987, ECOLOGY, V68, P1785 BARNUM SA, 1992, J MAMMAL, V73, P797 BENNETT AF, 1994, BIOL CONSERV, V68, P155 DUNNING JB, 1992, OIKOS, V65, P169 FAHRIG L, 1985, ECOLOGY, V66, P1762 FORMAN RTT, 1986, LANDSCAPE ECOLOGY GAINES MS, 1980, ANNU REV ECOL SYST, V11, P163 GOLDWASSER L, 1994, ECOLOGY, V75, P40 GOTELLI NJ, 1993, OIKOS, V68, P36 GYLLENBERG M, 1993, MATH BIOSCI, V118, P25 HANSKI I, 1994, J ANIM ECOL, V63, P151 HENEIN K, 1990, LANDSCAPE ECOL, V4, P157 KOZAKIEWICZ M, 1993, ACTA THERIOL, V38, P1 KREBS CJ, 1992, ANIMAL DISPERSAL, P161 KROHNE DT, 1984, AM MIDL NAT, V112, P146 LEFKOVITCH LP, 1985, ECOL MODEL, V30, P297 LORENZ GC, 1990, AM MIDL NAT, V123, P348 PULLIAM HR, 1992, ECOL APPL, V2, P165 SZACKI J, 1993, ACTA THERIOL, V38, P113 TAYLOR AD, 1990, ECOLOGY, V71, P429 TAYLOR PD, 1993, OIKOS, V68, P571 TERMAN CR, 1993, J MAMMAL, V74, P678 WEGNER J, 1990, BIOL CONSERV, V54, P263 ZHANG Z, 1991, ACTA THERIOL, V36, P239 0921-2973 Landsc. Ecol.ISI:000077684100001xIowa State Univ, Dept Anim Ecol, Ames, IA 50011 USA. Danielson, BJ, Iowa State Univ, Dept Anim Ecol, Ames, IA 50011 USA.English|?. %Anderson, K. Bennie, J. Wetherelt, A.2010ZLaser scanning of fine scale pattern along a hydrological gradient in a peatland ecosystem477-492Landscape Ecology253Lowland ombrotrophic (rain-fed) peatlands are a declining ecological resource in Europe. Peatlands display characteristic patterns in vegetation and surface topography, linked to ecological function, hydrology, biodiversity and carbon sequestration. Laser scanning provides a means of precisely measuring vegetation pattern in peatlands, and thus holds promise as a tool for monitoring peatland condition. Terrestrial laser scanning (TLS) was used for measurement of vegetation pattern along an eco-hydrological gradient at a UK peatland (Wedholme Flow, Cumbria) at fine grain sizes (< 1 cm spatial resolution over 10 m spatial extent). Seven sites were investigated-each showed varying water table and ecological characteristics. TLS data were analysed using semi-variogram analysis which enabled the scale of spatial dependence in vegetation structures to be measured. In addition ecological, hydrological and positional surveys were conducted to elucidate interpretation of spatial patterns. Results show that TLS was able to rapidly measure vegetation patterns associated with eco-hydrological condition classes. Intact sites with hummock-hollow topography showed an isotropic pattern with a grain size or length-scale of 1 m or less (indicated by semi-variogram range). Degraded sites with high shrub cover showed increased sill variance values at larger range distances-typically around 3-4 m. The work presented shows the advantages of TLS methodologies for rapid measurement of 3-D vegetation canopy structure and surface microtopography, at fine spatial scales, in short vegetation. The paper considers how these approaches may be extended to monitoring peatland structure over larger spatial extents from airborne LiDAR systems.!://WOS:000275122600012Times Cited: 0 0921-2973WOS:00027512260001210.1007/s10980-009-9408-y|?Anderson, L. Burgin, S.2008tPatterns of bird predation on reptiles in small woodland remnant edges in peri-urban north-western Sydney, Australia 1039-1047Landscape Ecology239The predator-prey relationship plays an integral role in community structure. In the presence of habitat fragmentation, the dynamic interaction among co-existing species may be disrupted. In this paper we investigated the interaction between small skinks resident in open woodland remnants and the predatory birds that cross-forage between the remnants and the surrounding peri-urban matrix. Skinks were found in significantly fewer numbers in the edge of remnants compared to their core. In contrast, predatory birds were in largest numbers at the edge compared to the core of remnants. We found that there was a strong negative correlation between skink numbers and predatory birds (individually and combined) consistent with higher predation pressure in the edge compared to the core of remnants. Strike rates on decoys that mimicked skinks were also higher in the edge compared to core habitats, consistent with higher predation rates in this edge habitat.!://WOS:000260283100004Times Cited: 0 0921-2973WOS:00026028310000410.1007/s10980-008-9252-5{?3Lotta Anderson Ake Sivertun1991iA GIS-supported method for detecting the hydrological mosaic and the role of man as a hydrological factor107-124Landscape Ecology52NGIs, soil-wetness, hydrological response, water-partitioning, human activitiesdA Geographical Information System (GIs)-supported method was developed for predicting the spatial distribution of soil wetness as an indicator to determine the probability of an area to act as a groundwater recharge or discharge area. The method was based on overlays of maps with the distribution of hydrological responsedetermining factors. An application was made for the Svarti river basin (south-central Sweden). Changes in the soil-wetness mosaic due to human activities were also analyzed. Since the 1870s drainage and forestry had, according to the analysis, decreased by 5% the parts of the basin that act as discharge areas during wet spells. In the agriculturally dominated sub-basins, the alterations were larger. Forty percent of the open land had been artificially drained. The main shift of soil wetness index classes was caused by an alteration of areas that earlier fluctuated between groundwater discharge and recharge into typical recharge areas. For the plains, the shift from discharge areas to recharge areas was also significant. A conceptual water partitioning model was used to assess the spatial distribution of water flows (evaporation and recharge), as a response to climatic inputs, for areas with different physiographic and vegetative characteristics. The present water flow pattern was compared with the response mosaic of the 1870s. The increased maximum daily recharge peaks during autumn constitute the only significant change in the hydrological response for the studied area as a whole. The consequences that the desiccation of the landscape have on chemical and biological processes were discussed.V|? >Andersson, Erik Ahrne, Karin Pyykonen, Markku Elmqvist, Thomas2009MPatterns and scale relations among urbanization measures in Stockholm, Sweden 1331-1339Landscape Ecology2410 In this study we measure urbanization based on a diverse set of 21 variables ranging from landscape indices to demographic factors such as income and land ownership using data from Stockholm, Sweden. The primary aims were to test how the variables behaved in relation to each other and if these patterns were consistent across scales. The variables were mostly identified from the literature and limited to the kind of data that was readily accessible. We used GIS to sample the variables and then principal component analyses to search for patterns among them, repeating the sampling and analysis at four different scales (250 x 250, 750 x 750, 1,250 x 1,250 and 1,750 x 1,750, all in meters). At the smallest scale most variables seemed to be roughly structured along two axes, one with landscape indices and one mainly with demographic factors but also impervious surface and coniferous forest. The other land-cover types did not align very well with these two axes. When increasing the scale this pattern was not as obvious, instead the variables separated into several smaller bundles of highly correlated variables. Some pairs or bundles of variables were correlated on all scales and thus interchangeable while other associations changed with scale. This is important to keep in mind when one chooses measures of urbanization, especially if the measures are indices based on several variables. Comparing our results with the findings from other cities, we argue that universal gradients will be difficult to find since city shape and size, as well as available information, differ greatly. We also believe that a multivariate gradient is needed if you wish not only to compare cities but also ask questions about how urbanization influences the ecological character in different parts of a city.%://BIOSIS:PREV201000014108Times Cited: 0 0921-2973BIOSIS:PREV201000014108:10.1007/s10980-009-9385-1?2Andow, D.A. P.M. Kareiva S.A. Levin A. Okubo1990Spread of invading organisms177-188Landscape Ecology42/3#species invasions, diffusion models?Andrew, Lister2003?Book review Review of Ecoregion-Based Design for Sustainability807-807Landscape Ecology1885http://dx.doi.org/10.1023/B:LAND.0000014624.68397.04 10.1023/B:LAND.0000014624.68397.04 Andrew Lister Email: alister@fs.fed.us This revised version was published online in July 2006 with corrections to the Cover Date.gAndrew Lister1 (1) USDA Forest Dervice, Northeastern Research Station Newtown Square, PA 19073, USA q|?HAnteau, Michael J. Shaffer, Terry L. Wiltermuth, Mark T. Sherfy, Mark H.2014`Landscape selection by piping plovers has implications for measuring habitat and population size 1033-1044Landscape Ecology296Jul How breeding birds distribute in relation to landscape-scale habitat features has important implications for conservation because those features may constrain habitat suitability. Furthermore, knowledge of these associations can help build models to improve area-wide demographic estimates or to develop a sampling stratification for research and monitoring. This is particularly important for rare species that have uneven distributions across vast areas, such as the federally listed piping plover (Charadrius melodus; hereafter plover). We examined how remotely-sensed landscape features influenced the distribution of breeding plover pairs among 2-km shoreline segments during 2006-2009 at Lake Sakakawea in North Dakota, USA. We found strong associations between remotely-sensed landscape features and plover abundance and distribution (R-2 = 0.65). Plovers were nearly absent from segments with bluffs (> 25 m elevation increase within 250 m of shoreline). Relative plover density (pairs/ha) was markedly greater on islands (4.84 +/- A 1.22 SE) than on mainlands (0.85 +/- A 0.17 SE). Pair numbers increased with abundance of nesting habitat (unvegetated-flat areas ). On islands, pair numbers also increased with the relative proportion of the total area that was habitat (). Our model could be adapted to estimate the breeding population of plovers or to make predictions that provide a basis for stratification and design of future surveys. Knowledge of landscape features, such as bluffs, that exclude use by birds refines habitat suitability and facilitates more accurate estimates of habitat and population abundance, by decreasing the size of the sampling universe. Furthermore, techniques demonstrated here are applicable to other vast areas where birds breed in sparse or uneven densities.!://WOS:000338331600009Times Cited: 0 0921-2973WOS:00033833160000910.1007/s10980-014-0041-z<7a)Antolin, M. F. Savage, L. T. Eisen, R. J.2006bLandscape features influence genetic structure of black-tailed prairie dogs (Cynomys ludovicianus)867-875Landscape Ecology216disease; dispersal; metapopulation; plague; population genetics; sciuridae SYLVATIC PLAGUE; MULTILOCUS GENOTYPES; POPULATIONS; VARIABILITY; DIVERSITY; METAPOPULATIONS; PHILOPATRY; DISPERSAL; PATTERNS; ECOLOGYArticleAugvBlack-tailed prairie dogs (Cynomys ludovicianus) currently live in metapopulations in the parts of their range where plague, caused by the bacterium Yesinia pestis, has invaded. Prairie dogs are highly susceptible to the pathogen, with most animals within towns dying during Y. pestis outbreaks. A review of population genetic studies of prairie dogs demonstrates considerable differentiation between prairie dog towns. Despite declines and fluctuations in size of prairie dog populations, they continue to harbor considerable genetic variation. This results from continual dispersal and gene flow, likely along low-lying drainages that connect towns. When combined with estimates of population size, the landscape genetic approach described here will provide precise estimates of dispersal and gene flow, in addition to evaluation of long-term stability of prairie dog metapopulations.://000239484200007 %ISI Document Delivery No.: 069YA Times Cited: 3 Cited Reference Count: 43 Cited References: ADDICOTT JF, 1987, OIKOS, V49, P340 ANISIMOV AP, 2004, CLIN MICROBIOL REV, V17, P434 ANTOLIN MF, 2002, T N AM WILDL NAT RES, V67, P104 BARNES AM, 1993, US FISH WILDLIFE SER, V13, P28 BARTON NH, 1997, METAPOPULATION BIOL, P183 CHESSER RK, 1983, EVOLUTION, V37, P320 CHESSER RK, 1991, GENETICS, V127, P437 CINCOTTA RP, 1987, GREAT BASIN NAT, V47, P339 CORNUET JM, 1999, GENETICS, V153, P1989 CULLY JF, 2000, J WILDLIFE DIS, V36, P389 CULLY JF, 2001, J MAMMAL, V82, P894 DALEY JG, 1992, J WILDLIFE MANAGE, V56, P212 DOBSON FS, 1998, J MAMMAL, V79, P671 ECKE DH, 1952, PUBLIC HLTH MONOGRAP, V6 ESKEY CR, 1940, US PHS B, V254 FOLTZ DW, 1983, EVOLUTION, V37, P273 GAGE KL, 2005, ANNU REV ENTOMOL, V50, P505 GAGGIOTTI OE, 2004, MOL ECOL, V13, P811 GARRETT MG, 1982, AM MIDL NAT, V108, P51 GARRETT MG, 1988, J MAMMAL, V69, P236 HALPIN ZT, 1987, MAMMALIAN DISPERSAL, P104 HANSKI I, 2004, ECOLOGY GENETICS EVO, P3 HEDRICK PW, 2004, GENETICS POPULATIONS HOLLISTER N, 1916, N AM FAUNA, V40 HOOGLAND JL, 1995, BLACK TAILED PRAIRIE JOHNSON WC, 2004, BIOL CONSERV, V115, P487 JONES RT, 2005, MOL ECOL NOTES, V5, P71 KNOWLES CJ, 1985, PRAIRIE NAT, V17, P33 KNOWLES CJ, 1986, J RANGE MANAGE, V39, P249 KOENIG WD, 1996, TRENDS ECOL EVOL, V11, P514 KOFORD CB, 1958, WILDLIFE MONOGRAPHS, V3 KOTLIAR NB, 1999, ENVIRON MANAGE, V24, P177 LOMOLINO MV, 2003, BIOL CONSERV, V115, P111 LUCE RJ, 2003, MULTISTATE CONSERVAT MANEL S, 2003, TRENDS ECOL EVOL, V18, P189 MENCHER JS, 2004, INFECT IMMUN, V72, P5502 PANNELL JR, 2000, PHILOS T ROY SOC B, V355, P1851 ROACH JL, 2001, J MAMMAL, V82, P946 SLATKIN M, 1993, EVOLUTION, V47, P264 STAPP P, 2004, FRONT ECOL ENVIRON, V2, P235 TRUDEAU KM, 2004, J WILDLIFE DIS, V40, P205 WHITLOCK MC, 2004, ECOLOGY GENETICS EVO, P153 WILSON GA, 2003, GENETICS, V163, P1177 0921-2973 Landsc. Ecol.ISI:000239484200007Colorado State Univ, Dept Biol, Ft Collins, CO 80523 USA. Colorado State Univ, Short Grass Steppe Long Term Ecol Res Program, Ft Collins, CO 80523 USA. Antolin, MF, Colorado State Univ, Dept Biol, Ft Collins, CO 80523 USA. michael.antolin@colostate.eduEnglish<7) Antrop, M.2000@Changing patterns in the urbanized countryside of Western Europe257-270Landscape Ecology153countryside planning rural landscape urbanization Western Europe FARMING LANDSCAPES CITY FRINGE AREAS TRANSFORMATION CONSERVATION FRAMEWORK REGIONS GERMANY TREESArticleApr5Urbanization refers to the complex interaction of different processes which transform landscapes formed by rural life styles into urban like ones. Urbanization causes profound changes in the ecological functioning of the landscape and gradually results in a changing spatial structure, i.e. forms new landscape patterns. The existing cities and urban network form the framework for this change, which is affecting increasingly larger areas in the countryside. Urbanization is mainly studied from social and economical viewpoints. Urban planners think about optimization of the land use and about aesthetics when reshaping the environment. Landscape ecology is lacking in urban planning because of different goals and concepts, but mostly because of missing significant information about these highly dynamical landscapes.://000085293300007 7ISI Document Delivery No.: 283UB Times Cited: 18 Cited Reference Count: 85 Cited References: 1990, LONGMAN DICT CONT EN *UN CTR HUM SETTL, 1996, URB WORLD GLOB REP H *UNESCO, 1973, MAB REP SER, V13 AGER P, 1984, IALE P 1 INT SEM MET, P61 ALBRECHTS L, 1998, STARTNOTA PROVINC 1A ANTROP M, 1988, CONNECTIVITY LANDSCA, P57 ANTROP M, 1990, AERIAL PHOTOGRAPHY G, V2, P13 ANTROP M, 1993, LANDSCAPE URBAN PLAN, V24, P3 ANTROP M, 1994, ACTA GEOGRAPHIA LOVA, V34, P501 ANTROP M, 1996, IMPACT URBANIZATION ANTROP M, 1997, LANDSCAPE URBAN PLAN, V38, P105 BERRY JL, 1958, ECON GEOGR, V34, P145 BRADSHAW AD, 1984, LANDSCAPE PLAN, V11, P35 BRANDT J, 1998, KEY CONCEPTS LANDSCA, P421 BRYANT C, 1982, CITYS COUNTRYSIDE LA BRYANT CR, 1984, LANDSCAPE PLAN, V11, P307 BRYANT CR, 1986, LANDSCAPE URBAN PLAN, V13, P251 BUNCE RGH, 1984, P 1 INT SEM METH LAN, P45 BUURSINK J, 1992, LANDSCAPE URBAN PLAN, V22, P243 CARTER H, 1995, STUDY URBAN GEOGRAPH CHISHOLM M, 1962, RURAL SETTLEMENT LAN CHOVANEV A, 1994, LANDSCAPE URBAN PLAN, V29, P43 CHRISTALLER W, 1933, ZENTRALER ORTE SUDDE COETERIER JF, 1994, LANDSCAPE URBAN PLAN, V29, P55 DANIELS RE, 1988, LANDSCAPE URBAN PLAN, V15, P291 DESSYLAS MD, 1990, LANDSCAPE URBAN PLAN, V18, P197 DRAMSTAD WE, 1998, KEY CONCEPTS LANDSCA, P63 FARINA A, 1998, PRINCIPLES METHODS L FORMAN R, 1968, LANDSCAPE ECOLOGY FREEMAN C, 1999, LANDSCAPE URBAN PLAN, V44, P1 FRY GLA, 1998, KEY CONCEPTS LANDSCA, P81 GATRELL A, 1983, DISTANCE SPACE GEOGR GOLLEY FB, 1991, LANDSCAPE URBAN PLAN, V21, P3 GREEN BH, 1987, LANDSCAPE URBAN PLAN, V14, P153 HAGGETT P, 1975, GEOGRAPHY MODERN SYN HARMS WB, 1998, KEY CONCEPTS LANDSCA, P355 HERBERT DT, 1982, URBAN GEOGRAPHY 1 AP HERMY M, 1997, PUNTEN LIJNEN LANDSC HOHENBERG P, 1990, WORDING EUROPA ONTWI HOLDEN R, 1997, LANDSCAPE URBAN PLAN, V36, P315 HUNSAKER CT, 1994, LANDSCAPE ECOL, V9, P207 ILBERY B, 1998, GEOGRAPHY RURAL CHAN JIM CY, 1993, LANDSCAPE URBAN PLAN, V23, P119 JORDAN T, 1973, EUROPEAN CULTURE ARE KONTULY T, 1992, LANDSCAPE URBAN PLAN, V22, P219 LEBEAU R, 1969, GRANDS TYPES STRUCTU LEWIS GJ, 1976, GEOGRAFISKA ANN B, V58, P17 LEWIS GJ, 1979, RURAL COMMUNITIES LOSCH A, 1954, EC LOCATION LUCY WH, 1997, LANDSCAPE URBAN PLAN, V36, P259 MCDONALD GT, 1984, LANDSCAPE PLAN, V11, P125 MEEUS JHA, 1990, LANDSCAPE URBAN PLAN, V18, P289 MONHEIM R, 1992, LANDSCAPE URBAN PLAN, V22, P121 NAVEH Z, 1994, LANDSCAPE ECOLOGY TH NAVEH Z, 1995, LANDSCAPE URBAN PLAN, V32, P43 NEWMAN PK, 1992, HOUSING TRANSPORT UR NORTHAM RM, 1975, URBAN GEOGRAPHY PACIONE M, 1984, RURAL GEOGRAPHY PRIGOGINE I, 1987, ORDE UIT CHAOS REFREW C, 1991, ARCHAEOLOGY THEORIES RICHTER H, 1984, P 1 INT SEM METH LAN, V5, P29 ROBERTS B, 1987, MAKING ENGLISH VILLA ROGERS GF, 1988, LAND URBAN PLANN, V15, P59 SAEY P, 1973, TIJDSCHRIFT EC SOCIA, V64, P181 SCHREIBER KF, 1988, CONNECTIVITY LANDSCA SCHROEDER HW, 1988, LANDSCAPE URBAN PLAN, V15, P119 SMARDON RC, 1988, LANDSCAPE URBAN PLAN, V15, P85 STANNERS D, 1995, EUROPES ENV DOBELE A STERN MA, 1997, LANDSCAPE URBAN PLAN, V36, P243 SUKOPP H, 1988, LANDSCAPE URBAN PLAN, V15, P39 SUKOPP H, 1993, STADTOKOLOGIE SULLIVAN WC, 1994, LANDSCAPE URBAN PLAN, V29, P85 TIMAR J, 1992, LANDSCAPE URBAN PLAN, V22, P177 TURNER T, 1908, LANDSCAPE URBAN PLAN, V15, P301 VANDERHAEGEN H, 1982, ACTA GEOGRAPHICA LOV, V22, P251 VANHECKE E, 1994, LEREN KEREN MILIEU N, P45 VERHOEVE A, 1992, TIJDSCHRIFT BELG VER, V61, P1 VINK APA, 1980, LANDSCHAPSECOLOGIE L VINK APA, 1982, PERSPECTIVES LANDSCA, P87 WEHRWEIN G, 1942, ECON GEOGR, V18, P217 WELCH JM, 1994, LANDSCAPE URBAN PLAN, V29, P131 WESTMACOTT R, 1991, LANDSCAPE URBAN PLAN, V21, P21 WRBKA T, 1998, KEY CONCEPTS LANDSCA, P177 YOKOHARI M, 1994, LANDSCAPE URBAN PLAN, V29, P103 ZMYSLONY J, 1998, LANDSCAPE URBAN PLAN, V40, P295 0921-2973 Landsc. Ecol.ISI:000085293300007State Univ Ghent, Dept Geog, B-9000 Ghent, Belgium. Antrop, M, State Univ Ghent, Dept Geog, Krijgslaan 281, B-9000 Ghent, Belgium.English<7 Antrop, M.2007-Reflecting upon 25 years of landscape ecology 1441-1443Landscape Ecology2210Editorial MaterialDec://000250632100003UISI Document Delivery No.: 227BL Times Cited: 0 Cited Reference Count: 7 Antrop, Marc 0921-2973 Landsc. Ecol.ISI:000250632100003Univ Ghent, Dept Geog, Ghent, Belgium. Antrop, M, Univ Ghent, Dept Geog, Krijgslaan 281 S8, Ghent, Belgium. marc.antrop@ugent.beEnglishjڽ70Antrop, Marc Brandt, Jesper Loupa-Ramos, Isabel Padoa-Schioppa, Emilio Porter, Jonathan Van Eetvelde, Veerle Pinto-Correia, Teresa2013How landscape ecology can promote the development of sustainable landscapes in Europe: the role of the European Association for Landscape Ecology (IALE-Europe) in the twenty-first century 1641-1647Landscape Ecology289Springer NetherlandsTEurope’s landscapes and identity European Landscape Convention Transdisciplinarity 2013/11/01+http://dx.doi.org/10.1007/s10980-013-9914-9 0921-2973Landscape Ecol10.1007/s10980-013-9914-9English|?*VAnyomi, Kenneth A. Raulier, Frederic Bergeron, Yves Mailly, Daniel Girardin, Martin P.2014Spatial and temporal heterogeneity of forest site productivity drivers: a case study within the eastern boreal forests of Canada905-918Landscape Ecology295May5Forest productivity is driven by a suite of direct climatic and non-climatic factors that are transient or permanent. The kind of productivity driver and the nature of their effects vary by species, and scale dependencies potentially complicate these relationships. This study explored productivity-driver relations in eastern Boreal Canada and determined spatial effects in productivity control when expressed with stand dominant height at a reference age (site index). Data from 4,217 temporary sample plots obtained from boreal mixedwood and conifer bioclimatic domains, and with varied species composition, were used in this study. A single-level global model that assumes equal sensitivities across spatial scales was calibrated and compared with three alternative models reflecting different hypotheses on possible spatial heterogeneities. Alternative models were calibrated by plot-level soil deposit types (microscale), landscape dominant deposits (mesoscale) and bioclimatic domains (macroscale). A marked difference between the global and alternative models was observed, suggesting that a single global model does not sufficiently reflect existing heterogeneity in productivity-driver relationships. A combination of macro- and microscale models provided the best explanation of site index. Results further showed that site index is mainly driven by species composition (complementarity effects of aspen and jack pine compositions) and stand diameter structural diversity effects. It is concluded that successional changes, more than direct climatic effects, drive productivity.!://WOS:000334689900012Times Cited: 1 0921-2973WOS:00033468990001210.1007/s10980-014-0026-y|? CAragon, Roxana Oesterheld, Martin Irisarri, Gonzalo Texeira, Marcos2011UStability of ecosystem functioning and diversity of grasslands at the landscape scale 1011-1022Landscape Ecology267AugnDiversity often increases ecosystem functioning and enhances stability, but this relationship has been evaluated at the community scale and considering, for the most part, only species richness. Here, we explored the relationship between landscape diversity and either the coefficient of variation or the interannual standard deviation of greenness in Pampean grasslands and Patagonian meadows, and tried to elucidate the mechanisms responsible for the resulting patterns. The coefficient of variation decreased with increasing landscape richness in Pampas but remained constant in Patagonia, while the interannual standard deviation of greenness decreased in both regions. The diversity-variability relationship in Pampean grasslands was largely accounted for by the mechanism of statistical averaging, while in Patagonian meadows, it was accounted for by a combination of statistical averaging, mean-variance rescaling and positive covariation of landscape units. There were no cases of negative covariance among landscape units. This is the first demonstration that landscape diversity increases stability of ecosystem functioning.!://WOS:000292705900009Times Cited: 0 0921-2973WOS:00029270590000910.1007/s10980-011-9625-zR~?LArce-Nazario, J. A.2007nHuman landscapes have complex trajectories: reconstructing Peruvian Amazon landscape history from 1948 to 200589-101Landscape Ecology22,Long-term landscape history studies can probe the complexity of landscape dynamics that appear linear or determined by a single driver on shorter time scales, and may span variations of both human-initiated and naturally occurring drivers. With a variety of historical sources this study traces the history of landscape change in Amazonian communities that have existed since the early 1900's, in a region comprising both upland and riverine ecosystems. Aerial photography from 1948, 1965 and 1977 and satellite images from 1993 to 2005 are analyzed to reconstruct spatial transformations of the study region. The reconstructed landscape history is analyzed as a result of shifts in economy, policy, local markets and river dynamics. In 1948, the upland region was used for agriculture and farms appeared to be encroaching into primary forest. However by 1965, 49% of the upland farm area had become secondary forest, as farmers left upland farms fallow and moved into the floodplain to farm crops promoted through agricultural credit programs. Between 1965 and 1977 river channel migration affected the riverine landscape, dramatic floods occurred throughout the Amazon River and many farmers migrated to the city. During the 1980's the credit given to small farmers greatly increased, resulting in the highest density of farms in the landscape by 1993. The disappearance of these credits is reflected in reduced farming activity and increased charcoal production. The results show that agricultural activity and deforestation do not always have a simple trajectory of increment."://WOS:000251543600007 Times Cited: 0WOS:00025154360000710.1007/s10980-007-9123-5 ~?Y.Arellano, L. Leon-Cortes, J. L. Ovaskainen, O.2008Patterns of abundance and movement in relation to landscape structure: a study of a common scarab (Canthon cyanellus cyanellus) in Southern Mexico69-78Landscape Ecology231Few relevant data are available to analyze how landscape features affect the abundance and movement patterns of tropical insects. We used mark-release-recapture techniques to study the effects of landscape structure and composition on habitat preferences and movements of Canthon cyanellus cyanellus individuals, within a complex tropical deciduous forest landscape in South Mexico during 2004 and 2005. In total, 2,460 individuals of C. c. cyanellus were captured, including 1,225 females and 1,235 males, out of which 124 individuals (65 females and 59 males) were recaptured once, and 9 individuals (seven females and two males) were recaptured twice. The abundance of individuals was equally high in large forest fragments, small forest fragments and hedgerows, but the abundance in pastures was less than half of the abundance in the other habitat types. To disentangle the movement behaviour of the species from the spatially and temporally varying sampling effort, we applied a Bayesian state-space modelling framework with a diffusion based movement model. Males showed generally faster movement rate than females, and they moved faster within forests and hedgerows than within pastures. Contrary to the assumption of the diffusion model, individuals did not move in a continuous fashion, indicated by the large fraction of individuals that were recaptured in the site of release. However, the posterior predictive data did not deviate substantially from the real data in terms of the mean and maximum movement distances recorded, and in terms of the dependence of movement distance on time between captures. Our results suggest that an important component of the biota in Mexican agro-pasture landscapes can utilize contemporary landscape elements such as hedgerows or small forest fragments in addition to large fragments of remnant habitat. These habitats are still locally common in semi-natural ecosystems and require less intensive conservation management."://WOS:000251796100008 Times Cited: 0WOS:00025179610000810.1007/s10980-007-9165-8<7]Arens, P. van der Sluis, T. van't Westende, W. P. C. Vosman, B. Vos, C. C. Smulders, M. J. M.2007|Genetic population differentiation and connectivity among fragmented Moor frog (Rana arvalis) populations in The Netherlands 1489-1500Landscape Ecology2210SSRs molecular markers habitat fragmentation genetic diversity landscape history amphibians time delay landscape scale LANDSCAPE GENETICS FLOW MICROSATELLITE CONSERVATION DIVERSITY DISTANCE MARKERS TOADArticleDecWe studied the effects of landscape structure, habitat loss and fragmentation on genetic differentiation of Moor frog populations in two landscapes in The Netherlands (Drenthe and Noord-Brabant). Microsatellite data of eight loci showed small to moderate genetic differentiation among populations in both landscapes (F (ST) values 0.022 and 0.060, respectively). Both heterozygosity and population differentiation indicate a lower level of gene flow among populations in Noord-Brabant, where populations were further apart and have experienced a higher degree of fragmentation for a longer period of time as compared to populations in Drenthe. A significant isolation-by-distance pattern was found in Drenthe, indicating a limitation in dispersal among populations due to geographic distance. In Noord-Brabant a similar positive correlation was obtained only after the exclusion of a single long-time isolated population. After randomised exclusion of populations a significant additional negative effect of roads was found but not of other landscape elements. These results are discussed in view of improving methodology of assessing the effects of landscape elements on connectivity.://000250632100008ISI Document Delivery No.: 227BL Times Cited: 0 Cited Reference Count: 46 Arens, Paul van der Sluis, Theo van't Westende, Wendy P. C. Vosman, Ben Vos, Claire C. Smulders, Marinus J. M. 0921-2973 Landsc. Ecol.ISI:000250632100008IUniv Wageningen & Res Ctr, Plant Res Int, Dept Biodivers & Breeding, NL-6700 AA Wageningen, Netherlands. Univ Wageningen & Res Ctr, Dept Landscape Ecol, NL-6700 AA Wageningen, Netherlands. Arens, P, Univ Wageningen & Res Ctr, Plant Res Int, Dept Biodivers & Breeding, POB 16, NL-6700 AA Wageningen, Netherlands. paul.arens@wur.nlEnglish<7$Ares, J. Bertiller, M. del Valle, H.2001Functional and structural landscape indicators of intensification, resilience and resistance in agroecosystems in southern Argentina based on remotely sensed data221-234Landscape Ecology163xagriculture environmental impact habitat fragmentation landscape indicators global vegetation indices remote sensing GISArticleApr.There is increasing interest in developing criteria to evaluate the environmental implications of intensive agricultural land use. This implies discriminating between nature and man-made effects upon structural and functional attributes of agroecosystems. Adequate indicators of these combined effects should be cost efficient yet compatible with the core of ecological theory on biodiversity, spatial organization and ecosystem stability. We developed resistance-resilience metrics of plant growth to evaluate the intensity of agricultural use in a temperate irrigated basin in southern Argentina. The metrics are based on an analysis of the components of a temporal series of vegetation indices computed at a low resolution from available globally remote sensed reflectance imagery. We related the developed metrics to the properties of the soils and plant canopies observed at field scale and high-resolution imagery of the basin. Soil depth, soil erosion status and land fragmentation account for large fractions of the variance of the distribution of functional groups of the plant canopies and are also correlated with smaller scale attributes of land vegetation cover. Resistance-resilience indicators constitute a cost-efficient and adequate approach to evaluate the degree of intensification of land agricultural use.://000168194400003 ISI Document Delivery No.: 423TT Times Cited: 4 Cited Reference Count: 38 Cited References: *IGM, 1967, CART TOP REP ARG *OECD, 1994, COMAGRCAENVEPOC9498 *US EPA, 1995, 39R95012 US EPA ARES JO, 1998, ENVIRON MODEL ASSESS, V3, P95 BALDOCK D, 1990, 3 CAP BASTIAN O, 1998, LANDSCAPE URBAN PLAN, V41, P171 BLOOMFIELD R, 1976, TIME SERIES ANAL BROUWER F, 1999, ENV INDICATORS AGR P, P57 CABRERA A, 1953, MANUAL FLORA ALREDED CABRERA A, 1980, BIOGEOGRAFIA AM LATI CAPPANNINI DA, 1967, COLECCION SUELOS, V1 CORREA MN, 1969, COLECCION CIENTIFICA CRIST A, 1994, PHOTOGRAM ENG REMOTE, V50, P343 EASTMAN R, 1997, IDRISIS WINDOWS USER EIDENSHINK JC, 1994, INT J REMOTE SENS, V15, P3443 GIRARDIN P, 1997, OCL-OL CORPS GRAS LI, V4, P418 GULINK H, 1997, REV EEA REPORT EUROP KAUTH RJ, 1976, P S MACH PROC REM SE KIRBY MJ, 1999, PROCESS MODELING LAN, P189 MAGURRAN AE, 1988, ECOLOGICAL DIVERSITY MCNAUGHTON SJ, 1994, BIODIVERSITY ECOSYST, P361 MEYER O, 1994, BIODIVERSITY ECOSYST, P67 NORUSIS M, 1995, SPSS STAT PACKAGE GU PAIN DJ, 1997, FARMING BIRDS EUROPE PARRIS K, 1999, ENV INDICATORS AGR P, P25 PICKUP G, 1993, REMOTE SENS ENVIRON, V43, P243 ROMSTAD E, 1997, D011997 AGR U NORW D ROMSTAD E, 1999, ENV INDICATORS AGR P, P15 RUNDELL G, 1990, PEAKFIT NONLINEAR CU RUTHENBERG H, 1980, FARMING SYSTEMS TROP SWIFT MJ, 1994, BIODIVERSITY ECOSYST, P15 TAPPEINER U, 1998, ECOL MODEL, V113, P225 TUCKER G, 1999, ENV INDICATORS AGR P, P89 TUCKER GM, 1994, BIRDLIFE CONSERVATIO, V3 VANWAMBEKE A, 1976, RIA SERIES, V3 VITOUSEK PM, 1994, BIODIVERSITY ECOSYST, P3 WALTER H, 1983, VEGETATION EARTH ECO WRIGHT RG, 1998, NAT AREA J, V18, P38 0921-2973 Landsc. Ecol.ISI:000168194400003CONICET, Ctr Nacl Patagonico, RA-9120 Puerto Madryn, Argentina. Ares, J, CONICET, Ctr Nacl Patagonico, RA-9120 Puerto Madryn, Argentina.English0<7)Ares, J. O. Bertiller, M. B. Bisigato, A.2003Estimates of dryland degradation in Argentina with Fourier signatures from low-altitude monochromatic images with high spatial resolution51-63Landscape Ecology181cimage signatures land degradation patch structure change NORTHERN PATAGONIA SOIL COMMUNITIES STEPPEArticleJanMost world drylands are used as graziny lands and undergo degradation of their vegetation cover. The plant cover is typically structured in patchy arrangements, inducing fertility islands critical to maintenance of ecosystem properties. The characteristics of patch structure (size of patches, connectivity-continuity of patch units, etc.) are indicators of the degree of dryland deterioration. We characterized changes in patch structure induced by sheep grazing at a landscape scale using monochromatic low-altitude imagery digitized to a spatial resolution of about 1 m with standard techniques of harmonic analysis applied to develop Fourier signatures. The signatures developed on image line transects were tested with ground samples and mathematical models of plant cover in several dryland fields where spatial deterioration gradients existed. The sensitivity and errors associated to long-wave noise introduced by the geometry of the camera-field-sun spatial arrangement and to high frequency noise introduced by the digitizing process were evaluated by applying suitable filters in the frequency domain. Fourier signatures developed on monochromatic low-altitude imagery proved to be indicative of changes in the patching arrangements of plant cover. We concluded that adequately filtered, high spatial resolution monochromatic images can be used to evaluate the degree of deterioration of dryland landscapes through the computation of selected Fourier signatures in their frequency domain. At comparable cost, aerial photography allows inspecting the landscape at higher spatial resolutions than those attainable with satellite imagery. Also, aerial photos of many areas are available for earlier dates than images from remote sensors, which would allow better inspection of long-term ecosystem changes.://000181767500004 ISI Document Delivery No.: 659FW Times Cited: 3 Cited Reference Count: 44 Cited References: *ERDAS INC, 1994, ERDAS IM FIELD GUID, P195 AKCAKAYA HR, 1997, APPL POPULATION ECOL, P35 ARES JO, 1990, MANAGED GRASSLANDS R, P268 BERTILLER MB, 1998, ECOLOGIA AUSTR, V8, P191 BERTILLER MB, 2001, BIODIVERS CONSERV, V11, P69 BERTILLER MB, 2001, P 4 REUN GRUP REG PA BISIGATO AJ, 1997, J ARID ENVIRON, V36, P639 BLOOMFIELD P, 1976, FOURIER ANAL TIME SE, P28 BORCARD D, 1992, ECOLOGY, V73, P1045 BRAIN P, 1996, ASPECTS APPL BIOL, V46, P173 CALLAWAY RM, 1997, ECOLOGY, V78, P1958 CZARAN T, 1998, SPATIOTEMPORAL MODEL, P15 DALE MRT, 1999, SPATIAL PATTERN ANAL, P91 DEFOSSE GE, 1992, P INT RANG DEV S SOC, P12 DHERBES JM, 2001, BANDED VEGETATION PA, P1 EASTMAN R, 1997, IDRISI WINDOWS USERS, P124 EASTMAN R, 1999, IDRISI32 GUIDE GIS I, P61 GARNER W, 1989, J ARID ENVIRON, V16, P257 GONZALEZ RC, 1992, DIGITAL IMAGE PROCES, P45 JENSEN JR, 1996, INTRO DIGITAL IMAGE, P67 KEELING M, 1999, ADV ECOLOGICAL THEOR, CH3 LEGENDRE P, 1989, VEGETATIO, V80, P107 LEON RJC, 1998, ECOLOGIA AUSTRAL, V8, P125 LEPS J, 1990, SPATIAL PROCESSES PL, P1 LEPS J, 1990, SPATIAL PROCESSES PL, P71 LEWIS M, 1997, SPATIAL ECOLOGY, CH3 MARSHALL EJP, 1999, J APPL ECOL, V36, P443 MAZZARINO MJ, 1996, ARID SOIL RES REHAB, V10, P295 MAZZARINO MJ, 1998, PLANT SOIL, V202, P125 MERRIT FS, 1970, APPL MATH ENG PRACTI, P129 MONTANA C, 2001, BANDED VEGETATION PA, P132 NORUSIS MJ, 1986, SPSS PC PLUS IBM PC, P435 NOYMEIR I, 1973, ANNU REV ECOL SYST, V4, P25 PALMER MW, 1993, ECOLOGY, V74, P2215 ROSSI RE, 1992, ECOL MONOGR, V62, P277 ROSTAGNO CM, 1988, CATENA, V15, P347 SEGHIERI J, 2001, BANDED VEGETATION PA, P32 STUTH JW, 1991, GRAZING MANAGEMENT E, CH5 TONGWAY DJ, 2001, BANDED VEGETATION PA, P20 VINTON MA, 1995, ECOLOGY, V76, P1116 WATT AS, 1947, J ECOL, V59, P615 WHITTAKER RH, 1977, THEORETICAL POPULATI, V12, P117 WILSON SD, 1998, POPULATION BIOL GRAS, P231 WITHERS MA, 1999, LANDSCAPE ECOLOGICAL, CH11 0921-2973 Landsc. Ecol.ISI:000181767500004Consejo Nacl Invest Cient & Tecn, Natl Patagon Ctr, RA-9120 Puerto Madryn, Argentina. Ares, JO, Consejo Nacl Invest Cient & Tecn, Natl Patagon Ctr, RA-9120 Puerto Madryn, Argentina. joares@arnet.com.arEnglish0<7(Ares, J. O. Dignani, J. Bertiller, M. B.2007~Cost analysis of remotely sensed foraging paths in patchy landscapes with plant anti-herbivore defenses (Patagonia, Argentina) 1291-1301Landscape Ecology229cost model; foraging; large herbivores; patagonian Monte; remote sensing; spatial analysis; surface cost theory GPS COLLAR; RED DEER; SHEEP; VEGETATION; PATTERNS; BEHAVIOR; CHOICE; MODEL; ENVIRONMENT; STRATEGIESArticleNovcWe developed metrics at a landscape scale to evaluate the costs and rewards experienced by large herbivores while foraging in natural vegetation with patchy anti-herbivore plant structures. We show an application of these metrics to the analysis of 16,000 records of positions at successive 1 min intervals of free-ranging ewes (Ovis aries) harnessed with Global-Positioning-System (GPS) loggers, in a large paddock of the Patagonian Monte shrublands (Argentina). Dominant shrubs in the area display numerous anti-herbivore defenses (spiny-resinous leaves, thorny stems, etc.) protecting them from grazing and herbivore trampling. Preferred grasses and forbs constitute a minor part of aboveground plant biomass and grow in relatively open areas among or around shrub patches. We mapped the movement speed of ewes onto high-resolution aerial photographs of the grazed paddocks and estimated costs and rewards along their paths based on algorithms of surface cost theory. Ewes explored areas of sparse vegetation at low speeds compatible with predominant grazing, and increased their speed when crossing denser shrubby patches. The cost algorithm was applied to evaluate daily searching costs as well as grazing rewards in relation to the length of daily searching paths. The observed path lengths and search speeds were consistent with those that compensate costs and rewards of the grazing activities as estimated by the surface cost analysis. We conclude that the technique presented here constitutes a valuable tool to quantify the effect of landscape characteristics on behavioral traits of grazing animals in similar environments.://000250207500003 Cited Reference Count: 58 Cited References: ANDERSON DJ, 1983, THEOR POPUL BIOL, V24, P145 ARES J, 2003, ENVIRON MODEL ASSESS, V8, P1 ARES J, 2003, GLOBAL CHANGE BIOL, V9, P1643 ARES JO, 1990, MANAGED GRASSLANDS R, P268 ARES JO, 2003, LANDSCAPE ECOL, V18, P51 BALDI R, 2004, J WILDLIFE MANAGE, V68, P924 BASU A, 2004, J REGIONAL SCI, V44, P743 BAZELY DR, 1988, THESIS U OXFORD OXFO BEECHAM JA, 2001, BIOSYSTEMS, V61, P55 BISIGATO A, 2002, PHYTOCOENOLOGIA, V32, P581 BISIGATO A, 2005, ECOGRAPHY, V28, P1 BISIGATO AJ, 1997, J ARID ENVIRON, V36, P639 CALENGE C, 2005, ECOL MODEL, V186, P143 CHARNOV EL, 1976, AM NAT, V110, P141 CLARKE JL, 1995, J APPL ECOL, V32, P166 CRAMER AE, 1997, NATURE, V387, P464 CUTHIL IC, 1999, BEHAV ECOLOGY EVOLUT, P97 DEFOSSE GE, 1992, P INT RANG DEV S SOC, P12 DHERBES JM, 2001, BANDED VEGETATION PA, P1 DOUGLAS DH, 1994, CARTOGRAPHICA, V31, P37 EASTMAN JR, 1989, P AUTOCARTO, V9, P288 EASTMAN JR, 2001, ANISOTROPIC COST ANA FANTINO E, 1985, BEHAV BRAIN SCI, V8, P315 FARNSWORTH KD, 1999, AM NAT, V153, P509 GALLISTEL CR, 1999, J COGNITIVE NEUROSCI, V11, P126 GANSKOPP D, 2000, APPL ANIM BEHAV SCI, V68, P179 GODARD V, 2006, P 9 INT S COMP ASS C, V9, P288 GOLDSHMIDT JN, 2000, PSY SCI, V11, P229 GROSS JE, 1995, LANDSCAPE ECOL, V10, P209 HESTER AJ, 1999, J APPL ECOL, V36, P133 HOBBS NT, 1991, ECOLOGY, V72, P1374 HULBERT IAR, 1998, APPL ANIM BEHAV SCI, V60, P359 JUDSON OP, 1994, TRENDS ECOL EVOL, V9, P9 KIE JG, 2005, LANDSCAPE ECOL, V20, P289 KOHLER F, 2006, LANDSCAPE ECOL, V21, P281 LACA EA, 1992, THESIS U CALIFORNIA LEA SEG, 1979, ANIM BEHAV, V27, P875 LEON RJC, 1998, ECOLOGIA AUSTRAL, V8, P125 LEWISON RL, 2004, ECOL MODEL, V171, P127 LIMA SL, 1996, TRENDS ECOL EVOL, V11, P131 LONDON DM, 1999, THESIS TEXAS TECH U MACARTHUR RH, 1966, AM NAT, V100, P603 MCNAIR JN, 1982, AM NAT, V119, P511 NOYMEIR I, 1973, ANNU REV ECOL SYST, V4, P25 OOM SP, 2002, OIKOS, V98, P65 OOM SP, 2005, ECOL COMPLEX, V1, P299 ORDUNA V, 2004, BEHAV PROCESS, V67, P147 PASTOR J, 1992, AM NAT, V139, P690 PRAIR JL, 2005, LAND ECOL, V20, P273 ROPERTCOUDERT Y, 2004, BEHAV ECOL, V15, P824 RUTTER SM, 1997, COMPUT ELECTRON AGR, V17, P177 STEPHENS DW, 1986, FORAGING THEORY STILLMAN RA, 2000, BEHAV ECOL, V11, P597 TONGWAY DJ, 1990, AUST J ECOL, V15, P23 TURNER MG, 1993, ECOL MODEL, V69, P163 UNGAR ED, 2005, RANGELAND ECOL MANAG, V58, P256 VISWANATHAN GM, 1999, NATURE, V401, P911 ZOLLNER PA, 1999, ECOLOGY, V80, P1019 0921-2973 Landsc. Ecol.ISI:000250207500003Consejo Nacl Invest Cient & Tecn, CENPAT, Natl Patagon Ctr, RA-9120 Puerto Madryn, Argentina. Ares, JO, Consejo Nacl Invest Cient & Tecn, CENPAT, Natl Patagon Ctr, Blvd Brown S-N, RA-9120 Puerto Madryn, Argentina. joares@cenpat.edu.ar joares@arnet.com.arEnglish <7, Arler, F.2000&Aspects of landscape or nature quality291-302Landscape Ecology153catmosphere biodiversity connoisseur ethics landscape quality narrativity nature quality picturesqueArticleApr!Landscape or nature quality has become a key concept in relation to nature policy and landscape planning. In the first part of the article it is argued, that these qualities should not be conceived as mere expressions of private or subjective preferences. Even though there may not be any `objective' or `scientific' method dealing with them, they are still values which can be shared, reflected on, and discussed in a reasonable way. The connoisseurs are introduced as experienced persons, who are particularly capable of identifying different kinds of qualities, bridge builders between cognition and evaluation. The second part of the article deals with four central sets of landscape or nature qualities: qualities related to species diversity, qualities related to the `atmospheres' and characters of places, pictorial qualities, and qualities related to narrativity. It is argued that experience of these and similar qualities are an important part of human flourishing, and that they should therefore all have a prominent place in landscape planning.://000085293300010 ISI Document Delivery No.: 283UB Times Cited: 9 Cited Reference Count: 50 Cited References: ARBER A, 1986, HERBALS THEIR ORIGIN ARLER F, 1997, NATUR NATURKVALITET ARLER F, 1998, CROSS CULTURAL PROTE BATESON G, 1979, MIND NATURE NECESSAR BOHME G, 1989, OKOLOGISCHE NATURAST BOHME G, 1992, NATURLICH NATUR BOHME G, 1995, ATMOSPHARE DARWIN C, 1909, SELVBIOGRAFI DREYFUS H, 1986, MIND MACH EHRLICH A, 1981, EXTINCTION CAUSES CO ELLIOT R, 1995, ENV ETHICS EMERSON RW, EMERSONS ESSAYS FORMAN RTT, 1990, CHANGING LANDSCAPES FUCHS L, 1542, HIST STIRPIUM GOLLEY FB, 1996, LANDSCAPE ECOL, V11, P321 HARGROVE E, 1994, BIODIVERSITY LANDSCA JONES M, 1991, NORSK GEOGRAFISK TID, V45, P229 KANT I, 1974, KRITIK URTEILSKRAFT KELLERT S, 1996, VALUE LIFE KIESTER AR, 1996, HUMAN ECOLOGY REV, V3, P151 KNIGHR RP, 1805, ANAL INQUIRY PRINCIP MACINTYRE A, 1981, VIRTUE MAY RM, 1995, BIODIVERSITY MEASURE MAYR E, 1982, GROWTH BIOL THOUGHT MINELLI A, 1993, BIOL SYSTEMATICS STA MUIR J, 1998, YOSEMITE NATIONS JD, 1988, BIODIVERSITY NAVEH Z, 1984, METHODOLOGY LANDSCAP, V1 NORTON B, 1987, WHY PRESERVE NATURAL NORTON B, 1998, COMMUNITY BASED APPR NORTON B, 1998, ECOL ECON, V24, P193 ONEILL J, 1988, GOOD LIFE BELOW SNOW ONEILL J, 1993, ECOLOGY POLICY POLIT PAHUUS M, 1988, PHILOSOPHIA ARHUS PECK AL, 1961, PARTS ANIMAL ROLSTON H, 1994, CONSERVING NATURAL V ROSS D, 1961, NICOMACHEAN ETHICS SAGOFF M, 1988, PHILOS LAW ENV SAGOFF M, 1992, J ENERGY NATURAL RES, V12, P351 SCHAMA S, 1995, LANDSCAPE MEMORY SEEL M, 1991, ASTHETIK NATUR SEEL M, 1996, ETHISCH ASTHETISCHE THOMSENK, 1997, ALLE TIERS URSKOV TUAN YF, 1977, SPACE PLACE PERSPECT VONLINNE C, 1958, DIAETA NATURALIS 173 VONLINNE C, 1978, JAMVIKTEN NATUREN WILSON A, 1992, CULTURE NATURE WILSON EO, 1984, BIOPHILIA ZAGZEBSKI LT, 1996, VIRTUES MIND ZONNEVELD IS, 1990, CHANGING LANDSCAPES 0921-2973 Landsc. Ecol.ISI:000085293300010`Aarhus Univ, Dept Philosophy, DK-8000 Aarhus, Denmark. Arler, F, Univ Aalborg, Aalborg, Denmark.English<7 Arnaud, J. F.2003}Metapopulation genetic structure and migration pathways in the land snail Helix aspersa: influence of landscape heterogeneity333-346Landscape Ecology183(allozyme genetic structure habitat configuration landscape connectivity land snail metapopulation microsatellite spatial autocorrelation DIRECTIONAL SPATIAL AUTOCORRELATION MICROSATELLITE LOCI POPULATION-STRUCTURE ARIANTA-ARBUSTORUM PATTERNS DIFFERENTIATION GASTROPODA HELICIDAE DISTANCE DYNAMICSArticleApr:The spatial genetic structuring of the land snail Helix aspersa was investigated for 32 colonies within an intensive agricultural area, the polders of the Bay of Mont-Saint-Michel ( France). Given the habitat patchiness and environmental instability, the setting of H. aspersa colonies meets the broader view of a metapopulation structure. The identification of extrinsic barriers to migration and their impact on the genetic distribution was addressed through the genotyping of 580 individuals using a combined set of enzyme and microsatellite loci. To evaluate the distance as well as the direction over which the spatial genetic arrangement occurs, two-dimensional spatial autocorrelation analyses, Mantel tests of association and multivariate Mantel correlograms were used. Different connectivity networks and geographical distances based on landscape features were constructed to evaluate the effect of environmental heterogeneity and to test the adequacy of an isolation by distance model on the distribution of the genetic variability. Genetic divergence was assessed using either classical IAM-based statistics, or SMM-based genetic distances specifically designed to accommodate the mutational processes thought to fit microsatellite evolution (IAM: Infinite Allele Model; SMM: Stepwise Mutation Model). Genetic distances based only on genetic drift yielded the most plausible biologically meaningful interpretation of the observed spatial structure. Applying a landscape-based geographical distance which postulates that migration arises along roadside verges, hedges or irrigation canal embankments gave a better fit to an isolation by distance model than did a simple Euclidean distance. The progressive decline of genetic similarity with physical distance appeared to be environmentally induced, leading to functional migration pathways.://000183770600010 ISI Document Delivery No.: 694JD Times Cited: 16 Cited Reference Count: 59 Cited References: ARNAUD JF, 1999, HEREDITY 2, V83, P110 ARNAUD JF, 1999, J MOLLUS STUD 2, V65, P267 ARNAUD JF, 2000, THESIS U RENNES 1 FR ARNAUD JF, 2001, MOL ECOL, V10, P1563 ARTER HE, 1990, EVOLUTION, V44, P966 BAHL A, 1996, SPECIES SURVIVAL FRA, P329 BARBUJANI G, 1987, GENETICS, V117, P777 BAUR A, 1992, GLOBAL ECOL BIOGEOGR, V2, P52 BAUR A, 1993, MALACOLOGIA, V35, P89 BAUR B, 1993, ANN NATURHISTORISC B, V94, P307 BOHONAK AJ, 1999, Q REV BIOL, V74, P21 CASTRIC V, 2001, EVOLUTION, V55, P1016 CAVALLISFORZA LL, 1967, AM J HUM GENET, V19, P233 DAVISON A, 2000, P ROY SOC LOND B BIO, V267, P1399 ESTOUP A, 1999, MICROSATELLITES EVOL, P49 GABRIEL KR, 1969, SYST ZOOL, V18, P259 GOODMAN SJ, 1997, MOL ECOL, V6, P881 GOUDET J, 1995, J HERED, V86, P485 GUILLER A, 1994, J MOLLUS STUD, V60, P205 GUILLER A, 2000, MOL ECOL, V9, P1191 HANSKI I, 1999, METAPOPULATION ECOLO HARRISON S, 1997, METAPOPULATION BIOL, P27 HUTCHISON DW, 1999, EVOLUTION, V53, P1898 INGVARSSON PK, 1997, EVOLUTION, V51, P187 KEYGHOBADI N, 1999, MOL ECOL, V8, P1481 LUGONMOULIN N, 1999, MOL ECOL, V8, P419 MADEC L, 1996, CR ACAD SCI III-VIE, V319, P225 MADEC L, 2000, BIOL J LINN SOC, V69, P25 MCCAULEY DE, 1995, MOSAIC LANDSCAPES EC, P178 MICHELS E, 2001, MOL ECOL, V10, P1929 ODEN NL, 1984, GEOGR ANAL, V16, P1 ODEN NL, 1986, SYST ZOOL, V35, P608 PAILLAT G, 1996, ACTA OECOL, V17, P553 PANNELL JR, 2000, PHILOS T ROY SOC B, V355, P1851 ROGERS JS, 1972, PUBLICATION U TEXAS, V7213, P145 ROSENBERG MS, 1999, EUR J EPIDEMIOL, V15, P15 ROSENBERG MS, 2000, GEOGR ANAL, V32, P267 ROSENBERG MS, 2001, PASSAGE PATTERN ANAL ROUSSET F, 2001, DISPERSAL, P18 ROWE G, 2000, OIKOS, V88, P641 SCHLOTTERER C, 2000, CHROMOSOMA, V109, P365 SHRIVER MD, 1995, MOL BIOL EVOL, V12, P914 SLATKIN M, 1994, ECOLOGICAL GENETICS, P3 SLATKIN M, 1995, GENETICS, V139, P457 SMOUSE PE, 1986, SYST ZOOL, V35, P627 SOKAL RR, 1978, BIOL J LINN SOC, V10, P199 SOKAL RR, 1979, SYST ZOOL, V28, P227 SOKAL RR, 1986, GENETICS, V114, P259 SOKAL RR, 1987, AM NAT, V129, P122 SOKAL RR, 1998, HUM BIOL, V70, P1 SORK VL, 1999, TRENDS ECOL EVOL, V14, P219 TAKEZAKI N, 1996, GENETICS, V144, P389 VENDRAMIN GG, 1999, MOL ECOL, V8, P1117 VIARD F, 1997, GENETICS, V146, P973 VOS CC, 2001, HEREDITY 5, V86, P598 WEIR BS, 1984, EVOLUTION, V38, P1358 WIENS JA, 2001, DISPERSAL, P96 WRIGHT S, 1943, GENETICS, V28, P114 ZHIVOTOVSKY LA, 1999, MOL BIOL EVOL, V16, P467 0921-2973 Landsc. Ecol.ISI:0001837706000108Univ Lille 1, CNRS, UMR 8016, Lab Genet & Evolut Populat Vegetales, F-59655 Villeneuve Dascq, France. Univ Rennes 1, Equipe Evolut Populat & Especes, CNRS, UMR 6553, F-35042 Rennes, France. Arnaud, JF, Univ Lille 1, CNRS, UMR 8016, Lab Genet & Evolut Populat Vegetales, Bat SN2, F-59655 Villeneuve Dascq, France.English?'Arnold, G.W. Weeldenburg, J.R. Ng, V.M.1995oFactors affecting the distribution and abundance of Western grey kangarooos and euros in a gragmented landscape65-74Landscape Ecology102#gragmentation, landscape, kangaroos \|7^ *Arnold, G. W. Weeldenburg, J. R. Ng, V. M.1995Factors Affecting the Distribution and Abundance of Western Grey Kangaroos (Macropus-Fuliginosus) and Euros (M-Robustus) in a Fragmented Landscape65-74Landscape Ecology102!fragmentation landscape kangaroosAprhAll the remnants of native vegetation in a 1680 km(2) area of the central wheatbelt of Western Australia were assessed for use by two species of kangaroo (Western grey kangaroo Macropus fuliginosus and euro M. robustus). Use was determined from faecal pellet density. Densities over large areas (100 km(2)) varied with the amount of residual native vegetation in the area. The less the vegetation the lower was the faecal density, indicating that increased separation between remnants has led, over the 50-70 years since fragmentation, to lower kangaroo densities. The densities of kangaroos in 152 individual remnants of > 2 ha were examined in relation to their physical attributes (e.g. area, edge length, distance to nearest remnant, presence of linkages and the vegetation types present), and to an index of isolation from human disturbance. Few remnants < 2 ha were used by kangaroos. Canonical discriminant analysis showed that separation of remnants without kangaroos from those with kangaroos was associated with many of the attributes. Of these, the numbers of vegetation types and their proportions and the degree of isolation from human disturbance were of greatest importance. Regression analyses were done to obtain predictors of densities within remnants grouped according to the kangaroo species using the remnants. These showed that the importance of attributes differed for different groupings. Isolation from human disturbance was the most important factor for remnants that had either species, but not for the larger ones that had both species. For euros, density increased with the rank of the linkage to other remnants and decreased with the percentage of the remnant in open woodland. For Western grey kangaroos, rank for distance to nearest remnant was significant. Since the study area is representative of a much larger area, the findings should have wide applicability.://A1995QX34400001-Qx344 Times Cited:11 Cited References Count:0 0921-2973ISI:A1995QX34400001OArnold, Gw Csiro,Div Wildlife & Ecol,Lmb 4,Po Midland,Midland,Wa 6056,AustraliaEnglish<71Arnot, C. Fisher, P. F. Wadsworth, R. Wellens, J.2004:Landscape metrics with ecotones: pattern under uncertainty181-195Landscape Ecology192ecotones; intergrades; landscape metrics; fuzzy classification; remote sensing REMOTELY-SENSED DATA; LAND-COVER; MULTISCALE ANALYSIS; FUZZY-LOGIC; BOUNDARIES; ECOLOGY; CLASSIFICATION; PHYTOSOCIOLOGY; REPRESENTATION; SCALEArticleLandscape metrics are in widespread use, but previous research has highlighted problems over scale and error in the reliability of the metric values. This paper explores the variation of metric values when it is hard to distinguish exactly where one land cover type changes into another; when the ecotone is not an abrupt transition, but has a spatial extent in its own right. The values of metrics are explored in a landscape classified, using satellite imagery and the fuzzy c-means classifier, into fuzzy sets so that every location has a degree of belonging to all classes. The result is that any ecotone can be characterised by a variety of metric values depending on the degree to which a location is in any particular land cover class. The values recorded show some similarities, however, to those for an interpretation of the same landscape with abrupt changes, but the nature of that similarity varies unpredictably between metrics and classes. This analysis provides a limited degree of reassurance for those using metric analysis where the boundaries may have spatial extent, but much further work is required to establish an improved description of metrics under this condition.://000220452500006 ISI Document Delivery No.: 806SB Times Cited: 5 Cited Reference Count: 47 Cited References: BAKER WL, 1992, LANDSCAPE ECOL, V7, P291 BASTIN L, 1997, INT J REMOTE SENS, V18, P3629 BEZDEK JC, 1984, COMPUT GEOSCI, V10, P191 BISSONETTE JA, 1997, WILDLIFE LANDSCAPE E BURROUGH PA, 1996, SPATIAL CONCEPTUAL M BURROUGH PA, 1996, SPATIAL CONCEPTUAL M, P3 CAIN DH, 1997, LANDSCAPE ECOL, V12, P199 FISHER P, 1997, INT J REMOTE SENS, V18, P679 FISHER P, 2000, FUZZY SET SYST, V113, P7 FISHER PF, 1990, REMOTE SENS ENVIRON, V34, P121 FISHER PF, 1998, CARTOGR J, V35, P5 FISHER PF, 2000, GEOCOMPUTATION, P161 FONTE CC, IN PRESS INT J GEOGR FOODY GM, 1992, PHOTOGRAMM ENG REM S, V58, P221 FOODY GM, 1996, INT J REMOTE SENS, V17, P1317 FORMAN TT, 1986, LANDSCAPE ECOLOGY FORTIN MJ, 1994, ECOLOGY, V75, P956 FORTIN MJ, 1995, OIKOS, V72, P323 FORTIN MJ, 2000, LANDSCAPE ECOL, V15, P453 FORTIN MJ, 2001, SPATIAL UNCERTAINTY, P158 HESS G, 1994, LANDSCAPE ECOL, V9, P3 HESS GR, 1997, LANDSCAPE ECOL, V12, P309 HUNSAKER CT, 2001, SPATIAL UNCERTAINTY LEGRENDRE P, 1998, NUMERICAL ECOLOGY LEVIN SA, 1992, ECOLOGY, V73, P1943 LOEHLE C, 1996, LANDSCAPE ECOL, V11, P225 MCGARIGAL K, 1995, PNW351 USDA FOR SERV MILLINGTON AC, 1996, MAPA COMUNIDADES VEG MLADENOFF DJ, APACK LANDSCAPE ANAL MORACZEWSKI IR, 1993, VEGETATIO, V106, P1 MORACZEWSKI IR, 1993, VEGETATIO, V106, P13 ONEILL RV, 1986, HIERARCHICAL CONCEPT RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 ROBERTS DW, 1989, VEGETATIO, V83, P71 ROBINSON VB, 1986, GEOGRAPHIC INFORMATI ROBINSON VB, 2003, T GIS, V7, P3 SHAO G, 2001, CANADIAN J REMOTE SE, V27, P33 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1991, QUANTITATIVE METHODS WANG FJ, 1996, INT J GEOGR INF SYST, V10, P573 WELLENS J, 1999, P C INT INV MAN RES WELLENS J, 2000, VEGETATION MAPPING P WICKHAM JD, 1995, INT J REMOTE SENS, V16, P3585 WIENS JA, 1997, METAPOPULATION BIOL, P43 WU JG, 2002, LANDSCAPE ECOL, V17, P761 ZHANG J, 1998, INT J REMOTE SENS, V19, P2721 ZHU AZ, 2001, SPATIAL UNCERTAINTY, P330 0921-2973 Landsc. Ecol.ISI:000220452500006Univ Leicester, Dept Geog, Leicester LE1 7RH, Leics, England. Fisher, PF, Univ Leicester, Dept Geog, Leicester LE1 7RH, Leics, England. pete.fisher@le.ac.ukEnglish|?: Aronson, James2011RSustainability science demands that we define our terms across diverse disciplines457-460Landscape Ecology264Apr!://WOS:000288807300001Times Cited: 1 0921-2973WOS:00028880730000110.1007/s10980-011-9586-2)ڽ71gArroyo-Rodríguez, Víctor González-Perez, IraidaM Garmendia, Adriana Solà, Mireia Estrada, Alejandro2013The relative impact of forest patch and landscape attributes on black howler monkey populations in the fragmented Lacandona rainforest, Mexico 1717-1727Landscape Ecology289Springer Netherlands[Alouatta pigra Habitat fragmentation Habitat loss Matrix quality Population status Primates 2013/11/01+http://dx.doi.org/10.1007/s10980-013-9929-2 0921-2973Landscape Ecol10.1007/s10980-013-9929-2English ?)Francisco J . Artigas Ralph E. J. Boerner1989qAdvance regeneration and seed banking of woody plants in Ohio pine plantations: Implications for landscape change139-150Landscape Ecology23Olandscape ecology, pine, succession, seeds, regeneration, Ohio, hardwood forestSilviculturally-managed pine plantations within southern Ohio are chronically disturbed patches of introduced vegetation distinct from the surrounding matrix of hardwood forest. To determine the successional pathways by which such pine stands might blend back into the hardwood forest matrix under different types of silvicultural management, we determined the current status of hardwood regeneration under 24 pine stands. Stands of Pinus virginiana (Virginia pine) had the highest density of hardwood seedlings and saplings (20,560 stems ha-1) whereas P. strobus (white pine) stands averaged only 7090 hardwood stems ha-1; P. resinosa (red pine) stands were intermediate. The most abundant hardwood seedling and sapling species under pine canopies were Acer rubrum and Cornus florida. DCA ordination of the seedling + sapling assemblages clustered most of the P. resinosa and P. strobus stands in the center of the ordination along with a group of species which are common in second-growth forests of the area. P. virginiana stands, in contrast, were scattered throughout the ordination space. Most of the woody species common in second-growth forests of the region were also common in the pine understory. Multiple regression indicated that large plantations with deeper litter, higher soil pH and lower total hardwood density had the greatest abundance of mesic-site species in the understory. This relationship did not hold for P. resinosa stands, however, due to more frequent and intense silvicultural intervention. The seed bank was not an important source of woody seedlings to the understory assemblage under intact pine plantations. The vegetation of 1-4 yr old clear-cut sites was dominated by wind and bird dispersed species which were generally absent from the understory of intact plantations. We conclude these chronically disturbed planted patches will revert to matrix vegetation faster if the disturbance is allowed to end in a gradual manner through stand senescence than if it is abruptly ended by clear-cutting ."~?j-Ashcroft, M. B. Chisholm, L. A. French, K. O.2008cThe effect of exposure on landscape scale soil surface temperatures and species distribution models211-225Landscape Ecology23Species distribution models (SDMs) often use elevation as a surrogate for temperature or utilise elevation sensitive interpolations from weather stations. These methods may be unsuitable at the landscape scale, especially where there are sparse weather stations, dramatic variations in exposure or low elevational ranges. The goal of this study was to determine whether radiation, moisture or a novel estimate of exposure could improve temperature estimates and SDMs for vegetation on the Illawarra Escarpment, near Sydney, Australia. Forty temperature sensors were placed on the soil surface of an approximately 12,000 ha study site between November 2004 and August 2006. Linear regression was used to determine the relationship with environmental factors. Elevation was correlated more with moderate temperatures (winter maximums, summer minimums, spring and autumn averages) than extreme temperatures (summer maximums, winter minimums). The correlation (r(2)) between temperature and environmental factors was improved by up to 0.38 by incorporating exposure, moisture and radiation in the regressions. Summer maximums and winter minimums were predominately determined by exposure to the NW and coastal influences respectively, while exposure to the NE and SW was important during other seasons. These directions correspond with the winds that are most influential in the study area. The improved temperature estimates were used in Generalised Additive Models for 37 plant species. The deviance explained by most models was increased relative to elevation, especially for moist rainforest species. It was concluded that improving the accuracy of seasonal temperature estimates could improve our ability to explain the patchy distribution of many species."://WOS:000252636100009 Times Cited: 0WOS:000252636100009(10.1007/s10980-007-9181-8|ISSN 0921-2973<7$Asselin, H. Belleau, A. Bergeron, Y.2006gFactors responsible for the co-occurrence of forested and unforested rock outcrops in the boreal forest271-280Landscape Ecology212alternative stable states; boreal forest; diverging types; fire; primary succession; secondary succession PRIMARY SUCCESSION; PLANT SUCCESSION; FIRE FREQUENCY; POSTGLACIAL VEGETATION; TREE REGENERATION; GRANITE OUTCROPS; LICHEN WOODLANDS; NORTHERN QUEBEC; COMMUNITIES; CANADAArticleFeb'Rock outcrops in the boreal forest of Quebec can show either of two different states: a forested state with > 25% tree cover, and an unforested state (< 25% tree cover). We tested three different hypotheses that might explain the co-occurrence of forested and unforested rock outcrops: (1) differences in bedrock geology, with unforested outcrops associated to bedrock types inimical to tree growth; (2) unforested outcrops as recently disturbed sites undergoing secondary succession towards a forested state; (3) unforested outcrops as an alternative stable state to forested outcrops, induced by post-fire regeneration failure. Digitized forest inventory maps were used along with bedrock geology maps and time-since-fire maps to compare forested and unforested outcrops for bedrock geology type and date of the last fire. Field surveys were conducted on 28 outcrops (14 forested, 14 unforested) to gather information regarding tree species composition and site characteristics (thickness of the organic matter layer, percent cover of lichens, mosses and ericaceous shrubs). None of the three hypotheses explain the co-occurrence of forested and unforested rock outcrops in the boreal forest of Quebec. Both outcrop types occur on the same bedrock geology types. Unforested outcrops are not recently disturbed sites in early-successional states, as no clear distinction could be made in tree species composition and date of the last fire between the two outcrop types. Forested and unforested outcrops are not alternative stable states, as unforested outcrops are unstable and cannot maintain themselves through time in the prolonged absence of fire. Hence, unforested rock outcrops could be viewed as degraded, diverging post-fire types maintained by the late Holocene disturbance regime, characterized by high fire frequencies.://000235866400010 ISI Document Delivery No.: 019WC Times Cited: 0 Cited Reference Count: 77 Cited References: *ENV CAN, 2005, CANC CLIM NORM AV 19 *SPSS, 2001, SPSS 11 0 1 WIND ARSENEAULT D, 1992, ECOLOGY, V73, P1067 ASSELIN H, 2001, FOREST ECOL MANAG, V140, P29 ASSELIN H, 2005, GLOBAL ECOL BIOGEOGR, V14, P307 ASSELIN M, 1995, COLLECTION REGIONS Q, V7, P21 BARBOUR MG, 1987, TERRESTRIAL PLANT EC BERGERON Y, 1982, GEROGR PHYS QUATERN, V36, P291 BERGERON Y, 1989, VEGETATIO, V79, P51 BERGERON Y, 1993, HOLOCENE, V3, P255 BERGERON Y, 1998, CONS ECOL, V2 BERGERON Y, 1998, GEOGR PHYS QUATERN, V52, P1 BERGERON Y, 2001, CAN J FOREST RES, V31, P384 BERGERON Y, 2004, AMBIO, V33, P356 BERGERON Y, 2004, ECOLOGY, V85, P1916 BROWN RT, 1974, ACTA FOR FENN, V141, P1 BURBANCK MP, 1964, ECOLOGY, V45, P292 BURBANCK MP, 1983, AM MIDL NAT, V109, P94 CARCAILLET C, 2001, J ECOL, V89, P930 CATELLINO PJ, 1979, ENVIRON MANAGE, V3, P41 CHAPIN FS, 2004, AMBIO, V33, P361 CLAYDEN S, 1983, CAN J BOT, V61, P850 CLEMENTS FE, 1916, PLANT SUCCESSION ANA CLEMENTS FE, 1936, J ECOL, V24, P252 CONNELL JH, 1983, AM NAT, V121, P789 COWLES S, 1982, NAT CAN, V109, P573 FASTIE CL, 1995, ECOLOGY, V76, P1899 FRELICH LE, 1998, CONSERV ECOL, V2, P7 GAJEWSKI K, 1993, J ECOL, V81, P433 GAUDREAU L, 1979, ETUDES ECOLOGIQUES, V1 GREEN DG, 1982, J BIOGEOGR, V9, P29 GRONDIN P, 1996, MANUEL FORESTERIE, P148 HEINSELMAN ML, 1981, FOREST SUCCESSION CO, P374 HOBBS RJ, 1994, ECOSCIENCE, V1, P346 HOCQ M, 1994, GEOLOGIE QUEBEC MINI, P21 HOULE G, 1989, ECOLOGY, V70, P1307 HOULE G, 2003, ECOSCIENCE, V10, P80 JASINSKI JPP, 2004, FRONT ECOL ENVIRON, V2, P10 JASINSKI JPP, 2005, IN PRESS ECOL MONOGR KEEVER C, 1951, B TORREY BOT CLUB, V78, P401 KERSHAW KA, 1977, CAN J BOT, V55, P393 KRUCKEBERG AR, 2002, GEOLOGY PLANT LIFE E LAROCQUE I, 2003, ECOSCIENCE, V10, P515 LILIENFEIN J, 2003, GEODERMA, V116, P249 LYNCH EA, 1998, ECOLOGY, V79, P1320 MALLIK AU, 2003, CRIT REV PLANT SCI, V22, P341 MANN DH, 1999, ECOSCIENCE, V6, P272 MCVAUGH R, 1943, ECOL MONOGR, V13, P119 MUELLERDOMBOIS D, 1974, AIMS METHODS VEGETAT MULLER SD, 2001, J BIOGEOGR, V28, P1169 OOSTING HJ, 1937, ECOLOGY, V18, P280 OOSTING HJ, 1939, BOT GAZ, V100, P750 PAINE RT, 1998, ECOSYSTEMS, V1, P535 PAYETTE S, 1985, NATURE, V313, P570 PAYETTE S, 1992, SYSTEMS ANAL GLOBAL, P144 PAYETTE S, 2000, CAN J FOREST RES, V30, P288 PHILLIPS DL, 1981, AM MIDL NAT, V106, P313 PHILLIPS DL, 1982, AM MIDL NAT, V107, P206 ROWE JS, 1973, QUATERNARY RES, V3, P444 SAUCIER JP, 1998, AUBELLE S, V124, P1 SEDIA EG, 2003, OIKOS, V100, P447 SHURE DJ, 1977, ECOLOGY, V58, P993 SIMARD MJ, 2003, CAN J FOREST RES, V33, P672 SIROIS L, 1991, ECOLOGY, V72, P619 SIROIS L, 1993, J VEG SCI, V4, P795 SKUTCH AF, 1929, ECOLOGY, V10, P177 SOUSA WP, 1985, AM NAT, V125, P612 STRAHLER AH, 1978, J BIOGEOGR, V5, P403 TERBRAAK CJF, 2002, CANOCO REFERENCE MAN UNO GE, 1987, B TORREY BOT CLUB, V114, P387 VEILLETTE JJ, 1994, QUATERNARY SCI REV, V13, P945 VINCENT JS, 1977, GEROGR PHYS QUATERN, V31, P357 WHITEHOUSE E, 1933, ECOLOGY, V14, P391 WHITLOCK C, 1993, ECOL MONOGR, V63, P173 WINTERRINGER GS, 1956, ECOL MONOGR, V26, P105 WISER SK, 1996, J VEG SCI, V7, P703 ZAR JH, 1996, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000235866400010Univ Quebec, NSERC, UQAT, UQAM, Rouyn Noranda, PQ J9X 5E4, Canada. Asselin, H, Univ Quebec, NSERC, UQAT, UQAM, 445 Blvd Univ, Rouyn Noranda, PQ J9X 5E4, Canada. hugo.asselin@uqat.caEnglish<7Atauri, J. A. de Lucio, J. V.2001The role of landscape structure in species richness distribution of birds, amphibians, reptiles and lepidopterans in Mediterranean landscapes147-159Landscape Ecology162diversity distribution landscape ecology landscape heterogeneity species richness distribution PLANT DIVERSITY FOREST FRAGMENTATION CENTRAL SPAIN HABITAT ECOLOGY ABUNDANCE PATTERNS HETEROGENEITY DETERMINANTS BIODIVERSITYArticleFeb[The parameters referring to landscape structure are essential in any evaluation for conservation because of the relationship that exists between the landscape structure and the ecological processes. This paper presents a study of the relationships between landscape structure and species diversity distribution (estimated in terms of richness of birds, amphibians, reptiles and butterflies) in the region of Madrid, Spain. The results show that the response of species richness to landscape heterogeneity varies depending on the group of species considered. For birds and lepidopterans, the most important factor affecting the distribution of richness of species is landscape heterogeneity, while other factors, such as the specific composition of land use, play a secondary role at this scale. On the other hand, richness of amphibians and reptiles is more closely related to the abundance of certain land-use types. The study highlights the importance of heterogeneity in Mediterranean landscapes as a criterion for landscape planning and for definition of management directives in order to maintain biodiversity.://000167936500006 S ISI Document Delivery No.: 419EN Times Cited: 36 Cited Reference Count: 62 Cited References: *SEO, 1994, ATL AV NID MADR *STATS INC, 1992, CSS STAT ANDREN H, 1994, OIKOS, V71, P355 ANDREWARTHA HG, 1961, INTRO STUDY ANIMAL P ANTROP M, 1997, LANDSCAPE URBAN PLAN, V38, P105 BAKER WL, 1992, LANDSCAPE ECOL, V7, P291 BAZ A, 1995, J BIOGEOGR, V22, P129 BERG A, 1997, BIRD STUDY 3, V44, P355 BERNALDEZ FG, 1991, DIVERSIDAD BIOL BIOL, P23 BOHNINGGAESE K, 1997, J BIOGEOGR, V24, P49 BUREL F, 1995, AGR ECOSYST ENVIRON, V55, P193 CARCERDO FJA, 1988, ATLAS GEOCIENTIFICO COWLING RM, 1996, TRENDS ECOL EVOL, V11, P362 DEAGAR PM, 1995, ENVIRON MANAGE, V19, P345 DEAIZPURUA CG, 1997, MARIPOSAS DIURNAS MA DELEON A, 1989, CARACTERIZACION AGRO DEPABLO CL, 1988, LANDSCAPE ECOLOGY, V1, P203 EDENIUS L, 1997, ECOGRAPHY, V20, P425 ESTRADA A, 1997, BIODIVERS CONSERV, V6, P19 FARINA A, 1997, LANDSCAPE ECOL, V12, P365 FORMAN RTT, 1995, LAND MOSAICS FORMAN RTT, 1995, LANDSCAPE ECOL, V10, P133 FRANKLIN JF, 1993, ECOL APPL, V3, P202 GARCIAPARIS M, 1989, REV ESPANOLA HERPETO, V3, P237 GONZALEZ BM, 1992, AM J CLIN ONCOL-CANC, V15, P23 GROSSI JL, 1995, LANDSCAPE URBAN PLAN, V31, P291 HARRISON S, 1995, MOSAIC LANDSCAPES EC HAWKSWORTH DL, 1995, GLOBAL BIODIVERSITY HULSHOFF RM, 1995, LANDSCAPE ECOL, V10, P101 HUSTON MA, 1994, BIOL DIVERSITY COEXI JONGMAN RHG, 1996, ECNC PUBLICATION SER, V2 KEITT TH, 1997, CONSERV ECOL, V1 KERR JT, 1997, NATURE, V385, P252 LEGENDRE L, 1982, NUMERICAL ECOLOGY DE, V3 LEVIN SA, 1992, ECOLOGY, V73, P1943 LUBCHENCO J, 1991, ECOLOGY, V72, P371 MARRUGAN AE, 1989, DIVERSIDAD ECOLOGICA MAZEROLLE MJ, 1999, ECOSCIENCE, V6, P117 MEENTEMEYER V, 1987, LANDSCAPE HETEROGENE, P15 MILLER JN, 1997, LANDSCAPE ECOL, V12, P137 NAVEH Z, 1994, RESTORATION ECOLOGY, V2, P180 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 ORIVE L, 1985, MAPA FORMACIONES VEG PARISH T, 1995, J APPL ECOL, V32, P362 PINEDA FD, 1992, ETHN C 92 CORD SPAIN RESCIA AJ, 1994, J VEG SCI, V5, P505 RITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 RUIZ JP, 1990, LANDSCAPE URBAN PLAN, V18, P211 SANTOS T, 1997, ARDEOLA, V44, P113 SCHEINER SM, 1994, EVOL ECOL, V8, P331 SHMIDA A, 1985, J BIOGEOGR, V12, P1 TELLERIA JL, 1987, ARDEOLA, V34, P145 TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P245 TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 TURNER MG, 1991, QUANTITATIVE METHODS URBAN DL, 1987, BIOSCIENCE, V37, P119 WIENS JA, 1989, LANDSCAPE ECOLOGY, V3, P87 WIENS JA, 1993, OIKOS, V66, P369 WRIGHT DA, 1983, OIKOS, V41, P456 ZAR JH, 1984, BIOSTATISTICAL ANAL ZONNEVELD IS, 1990, CHANGING LANDSCAPES 0921-2973 Landsc. Ecol.ISI:000167936500006Univ Alcala de Henares, Fac Sci, Dept Ecol, Madrid, Spain. Atauri, JA, Univ Alcala de Henares, Fac Ciencias, Dept Ecol, Alcala De Henares 28871, Spain.English|? ,Atwell, R. C. Schulte, L. A. Westphal, L. M.2009pLandscape, community, countryside: linking biophysical and social scales in US Corn Belt agricultural landscapes791-806Landscape Ecology246JuliUnderstanding the interplay between ecological and social factors across multiple scales is integral to landscape change initiatives in productive agricultural regions such as the rural US Corn Belt. We investigated the cultural context surrounding the use of perennial cover types-such as stream buffers, wetlands, cellulosic bioenergy stocks, and diverse cropping rotations-to restore water quality, biodiversity, and ecosystem function within a Corn Belt agricultural mosaic in Iowa, USA. Through ethnographic techniques and 33 in-depth interviews, we examined what was most important to rural stakeholders about their countryside. We then used photo elicitation to probe how interviewees' assessments of farm practices involving perennial cover types were related to their sense of place. Our interviewees perceived their rural "countryside" as a linked social and biophysical entity, identifying strongly with the farming lifestyle and with networks of people across the landscape. While most interviewees approved of perennial farm practices on marginal agricultural land, implementation of these practices was neither a priority nor strongly assimilated into rural experience and ethics. We identified three scale boundaries in our interviewees' perception of place which present key challenges and opportunities for landscape change: landscape-community, individual-community, and community-institution. In all cases, community social norms and networks-exhibited at landscape spatial scales-may be instrumental in bridging these boundaries and enabling networks of perennial cover types that span privately owned and operated farms.://0002682481000073Atwell, Ryan C. Schulte, Lisa A. Westphal, Lynne M. 0921-2973ISI:00026824810000710.1007/s10980-009-9358-40|? Augustine, David J.2010JSpatial versus temporal variation in precipitation in a semiarid ecosystem913-925Landscape Ecology256JulSpatial and temporal variations in precipitation are central features of semiarid ecosystems, influencing patterns of plant productivity and the distribution of native fauna. Although temporal variation in precipitation has been studied extensively, far less is known about the spatial scale and pattern of precipitation variability in semiarid regions. I used long-term precipitation records to examine spatial variation across the 63 km(2) Central Plains Experimental Range in northeastern Colorado, and across the 117,000 km(2) region of shortgrass steppe in eastern Colorado. Relative to temporal variation, spatial variation was low at scales < 10 km, increased linearly across scales of 40-120 km, and was nearly equal in magnitude to temporal variation across distances of 120-160 km. Although I hypothesized that most spatial variation would be generated by early-summer convective thunderstorms in June, I found that the magnitude and spatial pattern of variation was similar for precipitation received in June compared to cumulative precipitation received during the full growing season. The degree of spatial autocorrelation in precipitation across all distances that I evaluated was similar for drought, dry, above-average and wet years. Across distances of 10-120 km, spatial variation within a single growing season was approximately two times greater than spatial variation in long-term mean growing-season precipitation, indicating spatial shifting in the locations of patches of high and low precipitation over multiple years. Overall, these findings suggest spatial variation at scales of 10-160 km may have been an important factor influencing vegetation patterns and migratory fauna of the shortgrass steppe, and have implications for livestock producers and future assessments of climate change.!://WOS:000278526000008Times Cited: 1 0921-2973WOS:00027852600000810.1007/s10980-010-9469-yH|?IAugustine, D. J. Dinsmore, S. J. Wunder, M. B. Dreitz, V. J. Knopf, F. L.2008[Response of mountain plovers to plague-driven dynamics of black-tailed prairie dog colonies689-697Landscape Ecology236Sylvatic plague is a major factor influencing the dynamics of black-tailed prairie dog (Cynomys ludovicianus) colonies in the western Great Plains. We studied the nesting response of the mountain plover (Charadrius montanus), a grassland bird that nests on prairie dog colonies, to plague-driven dynamics of prairie dog colonies at three sites in the western Great Plains. First, we examined plover nest distribution on colonies that were previously affected by plague, but that had been recovering (expanding) for at least 6 years. Plovers consistently nested in both young (colonized in the past 1-2 years) and old (colonized for 6 or more years) portions of prairie dog colonies in proportion to their availability. Second, we examined changes in plover nest frequency at two sites following plague epizootics, and found that mountain plover nest numbers declined relatively rapidly (<= 2 years) on plague-affected colonies. Taken together, our findings indicate that available plover nesting habitat associated with prairie dog colonies closely tracks the area actively occupied by prairie dogs each year. Given the presence of plague throughout most of the mountain plover's breeding range in the western Great Plains, important factors affecting plover populations likely include landscape features that determine the scale of plague outbreaks, the distance that plovers move in response to changing breeding habitat conditions, and the availability and quality of alternate breeding habitat within the landscape.!://WOS:000257210900005Times Cited: 0 0921-2973WOS:00025721090000510.1007/s10980-008-9230-y ~?xWAugustine, D. J. Matchett, M. R. Toombs, T. P. Cully, J. F. Johnson, T. L. Sidle, J. G.2008OSpatiotemporal dynamics of black-tailed prairie dog colonies affected by plague255-267Landscape Ecology233fBlack-tailed prairie dogs (Cynomys ludovicianus) are a key component of the disturbance regime in semi-arid grasslands of central North America. Many studies have compared community and ecosystem characteristics on prairie dog colonies to grasslands without prairie dogs, but little is known about landscape-scale patterns of disturbance that prairie dog colony complexes may impose on grasslands over long time periods. We examined spatiotemporal dynamics in two prairie dog colony complexes in southeastern Colorado (Comanche) and northcentral Montana (Phillips County) that have been strongly influenced by plague, and compared them to a complex unaffected by plague in northwestern Nebraska (Oglala). Both plague-affected complexes exhibited substantial spatiotemporal variability in the area occupied during a decade, in contrast to the stability of colonies in the Oglala complex. However, the plague-affected complexes differed in spatial patterns of colony movement. Colonies in the Comanche complex in shortgrass steppe shifted locations over a decade. Only 10% of the area occupied in 1995 was still occupied by prairie dogs in 2006. In 2005 and 2006 respectively, 74 and 83% of the total area of the Comanche complex occurred in locations that were not occupied in 1995, and only 1% of the complex was occupied continuously over a decade. In contrast, prairie dogs in the Phillips County complex in mixed-grass prairie and sagebrush steppe primarily recolonized previously occupied areas after plague-induced colony declines. In Phillips County, 62% of the area occupied in 1993 was also occupied by prairie dogs in 2004, and 12% of the complex was occupied continuously over a decade. Our results indicate that plague accelerates spatiotemporal movement of prairie dog colonies, and have significant implications for landscape-scale effects of prairie dog disturbance on grassland composition and productivity. These findings highlight the need to combine landscape-scale measures of habitat suitability with long-term measures of colony locations to understand the role of plague-affected prairie dogs as a grassland disturbance process."://WOS:000254112100002 Times Cited: 0WOS:000254112100002(10.1007/s10980-007-9175-6|ISSN 0921-2973 X<77 $Awade, M. Boscolo, D. Metzger, J. P.2012Using binary and probabilistic habitat availability indices derived from graph theory to model bird occurrence in fragmented forests185-198Landscape Ecology272habitat connectivity equivalent connected area (eca) playback technique pyriglena leucoptera atlantic forest brazil atlantic-rain-forest gap-crossing decisions landscape connectivity functional connectivity insectivorous birds southeastern brazil patch size conservation movements scaleFeb"Loss of connectivity is one of the main causes of decreases in habitat availability and, thus, in species abundance and occurrence in fragmented landscapes. It is therefore important to measure habitat connectivity for conservation purposes, but there are several difficulties in quantifying connectivity, including the need for species movement behavioral data and the existence of few consistent indices to describe such data. In the present study, we used a graph theoretical framework to measure habitat availability, and we evaluate whether this variable is adequate to explain the occurrence pattern of an Atlantic rainforest bird (Pyriglena leucoptera, Thamnophilidae). The playback technique was used to parameterize the connectivity component of habitat availability indices and to determine the presence or absence of the study species in forest patches. Patch-and landscape-level habitat availability indices were considered as explanatory variables. Two of these were landscape-level indices, which varied in terms of how inter-patch connections are defined, using either a binary or probabilistic approach. This study produced four striking results. First, even short open gaps may disrupt habitat continuity for P. leucoptera. Second, the occurrence of P. leucoptera was positively affected by habitat availability. Third, proper measures of this explanatory variable should account for the landscape context around the focal patch, emphasizing the importance of habitat connectivity. Finally, habitat availability indices should consider probabilistic and not binary inter-patch connections when intending to explain the occurrence of bird species in fragmented landscapes. We discuss some conservation implications of our results, stressing the advantages of an ecologically scaled graph theoretical framework.://0003000887000049Sp. Iss. SI 889QQ Times Cited:0 Cited References Count:68 0921-2973Landscape EcolISI:000300088700004iAwade, M Univ Sao Paulo USP, Dept Ecol, Inst Biosci, Rua Matao,Trav 14,321Cid Univ, BR-05508900 Sao Paulo, Brazil Univ Sao Paulo USP, Dept Ecol, Inst Biosci, Rua Matao,Trav 14,321Cid Univ, BR-05508900 Sao Paulo, Brazil Univ Sao Paulo USP, Dept Ecol, Inst Biosci, BR-05508900 Sao Paulo, Brazil Fed Univ Sao Paulo UNIFESP, BR-09972270 Jd Eldorado, Diadema, BrazilDOI 10.1007/s10980-011-9667-2English}<7(Axelsson, A. L. Ostlund, L. Hellberg, E.2002kChanges in mixed deciduous forests of boreal Sweden 1866-1999 based on interpretation of historical records403-418Landscape Ecology175boreal deciduous trees fire forest history forest management land-use history logging regeneration restoration succession SWEDISH FORESTS LANDSCAPE FIRES TRANSFORMATION BIODIVERSITY SETTLEMENT BEETLES ASPEN RAREArticleOctQCurrent knowledge of patterns and abundance of deciduous trees in the pre-industrial landscape of boreal Sweden is limited. This is due to a dramatic transformation of the forest landscape during the last 100 years and the lack of representative forest reserves. We used historical records to study change in five mixed deciduous forests between 1866 and 1999. The results show that large changes occurred due to complex interactions between fire disturbance, fire suppression, logging and silviculture. Before fire suppression, the presence of deciduous trees was mainly determined by earlier fire influence. Later selective logging disturbed natural succession and favoured regeneration of deciduous trees. During the 20(th) century deciduous trees were removed by girdling, thinning and herbicide spraying. Much of the mixed deciduous stands changed to coniferous stands between 1906-15 and 1969-70, and then deciduous trees were totally removed from these stands between late 1960s and 1999. Today mixed deciduous forest occurs mainly in young stands and on other sites than previously. Our results also show that large coniferous trees and multi-aged forest occurred in all sites in the early 1900s. Most sites were dominated by coniferous species and forest dominated by deciduous trees occurred only in smaller areas. These results are not consistent with the current view that deciduous-dominated forest occupied substantial areas in boreal Sweden before fire suppression. Appropriate changes in forest management are discussed, as is the value of historical data in interpreting changes in forest landscapes.://000179388800003 ISI Document Delivery No.: 617YP Times Cited: 9 Cited Reference Count: 53 Cited References: 1932, UPPSKATTNING SVERIGE, V26 1990, STAT MEDDELANDEN J 1997, SWEDISH FSC STANDARD 2000, STAT YB FORESTRY ANGELSTAM PK, 1998, J VEG SCI, V9, P593 AS S, 1993, ECOGRAPHY, V16, P219 AXELSSON AL, 2001, FOREST ECOL MANAG, V147, P109 AXELSSON AL, 2001, THESIS SWEDISH U AGR BERG A, 1994, CONSERV BIOL, V8, P718 BERG A, 1995, CONSERV BIOL, V9, P1629 BERG S, 1996, LOVTRAD SVERIGE TILL BERGMAN F, 1991, BJORK ASP SKOGSFAKTA, P4 BUNTE R, 1982, VINDELN NORRLANDSK K BURGI M, 1999, LANDSCAPE ECOL, V14, P567 ENGELMARK O, 1999, ECOSYSTEMS DISTURBED, P161 ERICSSON O, 1992, THESIS SWEDISH U AGR ESSEEN PA, 1997, BOREAL ECOSYSTEMS LA, P16 HAZELL P, 1999, BIOL CONSERV, V90, P133 HEINSELMAN M, 1996, BOUNDARY WATERS WILD JANSSON G, 1999, LANDSCAPE ECOL, V14, P283 JOHANSSON O, 1998, HANDLEDNING EKOLOGIS JONSELL M, 1998, BIODIVERS CONSERV, V7, P749 LAMAS T, 1995, WATER AIR SOIL POLL, V82, P57 LANGSTON N, 1995, FOREST DREAMS FOREST LINDER P, 1998, BIOL CONSERV, V85, P9 LINDER P, 1998, THESIS SWEDISH U AGR MARTIKAINEN P, 1998, CONSERV BIOL, V12, P293 MIKUSINSKI G, 1999, NATURE CULTURE LANDS, P220 NIKLASSON M, 1998, THESIS SWEDISH U AGR NIKLASSON M, 2000, ECOLOGY, V81, P1484 OSTLUND L, 1993, THESIS SWEDISH U AGR OSTLUND L, 1995, SCAND J FOR RES, V10, P56 OSTLUND L, 1997, CAN J FOREST RES, V27, P1198 RADELOFF VC, 1999, CAN J FOREST RES, V29, P1649 ROMME WH, 1995, ECOLOGY, V76, P2097 ROMME WH, 1997, NAT AREA J, V17, P17 SACHS DL, 1998, CAN J FOREST RES, V28, P23 SIITONEN J, 1994, SCAND J FOR RES, V9, P185 SLOTTE H, 1997, SVENSK BOT TIDSKRIFT, V91, P1 STENER LG, 1998, LANSVISA UPPGIFTER A, V4 STENMAN L, 1983, THESIS UPPSALA U UPP STOKES MA, 1968, INTRO TREE RING DATI THORELL KE, 1931, J FOREST, V4, P585 TIREN L, 1937, MEDDELANDEN STATENS, V30, P67 TROLLE JP, 1947, LYCKSELE STAD LAPPMA WEIR JMH, 1998, CAN J FOREST RES, V28, P459 WHITE PS, 1997, RESTOR ECOL, V5, P338 WHITNEY GG, 1987, J ECOL, V75, P667 WHITNEY GG, 1994, COASTAL WILDERNESS F WIKARS LO, 1999, SKOG FORSKNING, V2, P53 ZACKRISSON O, 1977, OIKOS, V29, P22 ZACKRISSON O, 1985, BROADLEAVES BOREAL S, P17 ZACKRISSON O, 1991, SKOG FORSKNING, V4, P13 0921-2973 Landsc. Ecol.ISI:000179388800003mNatl Board Forestry, S-55183 Jonkoping, Sweden. Axelsson, AL, Natl Board Forestry, S-55183 Jonkoping, Sweden.Englishm<7#Bachelet, D. Herstrom, A. Brown, D.1993mRice production and climate-change - Design and development of a GIS database to complement simulation models77-91Landscape Ecology82&RICE; GIS; CLIMATE CHANGE; MODEL; ASIAArticleJunVA cooperative project between the International Rice Research Institute in Los Banos, Philippines, and the U.S. EPA Environmental Research Laboratory in Corvallis, Oregon, was initiated to estimate how rice yield in Asia might be affected by future climate change and enhanced UV-B irradiance following stratospheric ozone depletion. A radiative transfer model was used to estimate daily UV-B irradiance levels using remotely sensed ozone and cloud cover data for 1274 meteorological stations. A rice yield model using daily climatic data and cultivar-specific coefficients was used to predict changes in yield under given climate change scenarios. This paper gives an overview of the data required to run these two models and describes how a geographical information system (GIS) was used as a data pre- or postprocessor. Problems in finding reliable datasets such as cloud cover data needed for the UV-B radiation model and radiation data needed for the rice yield model are discussed. Issues of spatial and temporal scales are also addressed. Using simulation models at large spatial scales helped identify weaknesses of GIS data overlay and interpolation capabilities. Even though we focussed our efforts on paddy rice, the database is not intended to be system specific and could also be used to analyze the response of other natural systems to climatic change.://A1993LM22200001 HISI Document Delivery No.: LM222 Times Cited: 3 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1993LM22200001dBACHELET, D, MANTECH ENVIRONM TECHNOL INC,US EPA,ENVIRONM RES LAB,200 SW 35TH ST,CORVALLIS,OR 97333.English0|7 #Bachelet, D. Herstrom, A. Brown, D.1993mRice Production and Climate-Change - Design and Development of a Gis Database to Complement Simulation-Models77-91Landscape Ecology82"rice gis climate change model asiaJunVA cooperative project between the International Rice Research Institute in Los Banos, Philippines, and the U.S. EPA Environmental Research Laboratory in Corvallis, Oregon, was initiated to estimate how rice yield in Asia might be affected by future climate change and enhanced UV-B irradiance following stratospheric ozone depletion. A radiative transfer model was used to estimate daily UV-B irradiance levels using remotely sensed ozone and cloud cover data for 1274 meteorological stations. A rice yield model using daily climatic data and cultivar-specific coefficients was used to predict changes in yield under given climate change scenarios. This paper gives an overview of the data required to run these two models and describes how a geographical information system (GIS) was used as a data pre- or postprocessor. Problems in finding reliable datasets such as cloud cover data needed for the UV-B radiation model and radiation data needed for the rice yield model are discussed. Issues of spatial and temporal scales are also addressed. Using simulation models at large spatial scales helped identify weaknesses of GIS data overlay and interpolation capabilities. Even though we focussed our efforts on paddy rice, the database is not intended to be system specific and could also be used to analyze the response of other natural systems to climatic change.://A1993LM22200001,Lm222 Times Cited:3 Cited References Count:0 0921-2973ISI:A1993LM22200001bBachelet, D Mantech Environm Technol Inc,Us Epa,Environm Res Lab,200 Sw 35th St,Corvallis,or 97333English[? )Baeta, Renaud Bélisle, Marc Garant, Dany2012_Agricultural intensification exacerbates female-biased primary brood sex-ratio in tree swallows 1395-1405Landscape Ecology2710Springer NetherlandsBiomedical and Life SciencesImpacts of agriculture practices are documented at every ecosystem level from landscape structure to biodiversity. Birds are especially affected by agricultural modifications as shown by the decline of farmland species in Europe and North America. Few studies have assessed the effects of such modifications on individual characteristics directly influencing population dynamics. Several bird studies showed that sex-ratio may be adaptive and that mother condition affects the production of sons and daughters. However, little is known about the connections between environmental and individual characteristics on sex allocation. Here we quantified the variation in primary sex-ratio in tree swallows ( Tachycineta bicolor ) nesting in contrasted environments associated with agricultural intensification in southern Québec, Canada. We found that intensive agricultural practices affected female sex-ratio allocation in this area, resulting in more biased sex-ratio towards daughters throughout most of the hatching period. Yet, this bias towards daughters was reduced as the season progressed in the most intensively cultivated areas, suggesting that tree swallows have problems foreseeing the difficult growth and postfledging conditions that their nestlings will experience in such environments. Our results thereby support the hypothesis that intensive agricultural areas act as an ecological trap in our study system. We also found that effects of agricultural intensification on sex allocation differed among years and affected the relationships between sex-ratio allocation and hatching date. Our results suggest that agricultural intensification modifies female sex allocation in tree swallows, but the importance of the effects might vary among years and depend on timing of breeding.+http://dx.doi.org/10.1007/s10980-012-9785-5 0921-297310.1007/s10980-012-9785-5|?_ RBaggio, Jacopo A. Salau, Kehinde Janssen, Marco A. Schoon, Michael L. Bodin, Orjan2011<Landscape connectivity and predator-prey population dynamics33-45Landscape Ecology261JanLandscapes are increasingly fragmented, and conservation programs have started to look at network approaches for maintaining populations at a larger scale. We present an agent-based model of predator-prey dynamics where the agents (i.e. the individuals of either the predator or prey population) are able to move between different patches in a landscaped network. We then analyze population level and coexistence probability given node-centrality measures that characterize specific patches. We show that both predator and prey species benefit from living in globally well-connected patches (i.e. with high closeness centrality). However, the maximum number of prey species is reached, on average, at lower closeness centrality levels than for predator species. Hence, prey species benefit from constraints imposed on species movement in fragmented landscapes since they can reproduce with a lesser risk of predation, and their need for using anti-predatory strategies decreases.!://WOS:000286004400004Times Cited: 0 0921-2973WOS:00028600440000410.1007/s10980-010-9493-y}?Baguette, M. Van Dyck, H.2007_Landscape connectivity and animal behavior: functional grain as a key determinant for dispersal 1117-1129Landscape Ecology228Oct://000248941900001 0921-2973ISI:000248941900001L}?;Bailey, D. Billeter, R. Aviron, S. Schweiger, O. Herzog, F.2007oThe influence of thematic resolution on metric selection for biodiversity monitoring in agricultural landscapes461-473Landscape Ecology223SPECIES RICHNESS; BEETLE COMMUNITIES; SPATIAL-PATTERN; CHANGING SCALE; RURAL-AREAS; HETEROGENEITY; DIVERSITY; ECOLOGY; INDEXES; INTENSIFICATION MarThe objective of this paper is to investigate the relationship between landscape pattern metrics and agricultural biodiversity at the Temperate European scale, exploring the role of thematic resolution and a suite of biological and functional groups. Factor analyses to select landscape-level metrics were undertaken on 25 landscapes classified at four levels of thematic resolution. The landscapes were located within seven countries. The different resolutions were considered appropriate to taxonomic and functional group diversity. As class-level metrics are often better correlated to ecological response, the landscape-level metric subsets gained through exploratory analysis were additionally used to guide the selection of class-level metric subsets. Linear mixed models were then used to detect correlations between landscape- and class-level metrics and species richness values. Taxonomic groups with differing requirements (plants, birds, different arthropod groups) and also functional arthropod groups were examined. At the coarse scale of thematic resolution grain metrics (patch density, largest patch index) emerged as rough indicators for the different biological groups whilst at the fine scale a diversity metric (e.g. Simpson's diversity index) was appropriate. The intermediate thematic resolution offered most promise for biodiversity monitoring. Metrics included largest patch index, edge density, nearest neighbour, the proximity index, circle and Simpson's diversity index. We suggest two possible applications of these metrics in the context of biodiversity monitoring and the identification of biodiversity hot spots in European agricultural ://000244455200010 0921-2973ISI:000244455200010<7Bain, D. J. Brush, G. S.2004aPlacing the pieces: Reconstructing the original property mosaic in a warrant and patent watershed843-856Landscape Ecology198yBaltimore; Maryland; USA; land use history; landscape heterogeneity; property mosaics; urban ecology NEW-ENGLAND; HISTORYArticleRecent research shows that land use history is an important determinant of current ecosystem function. In the United States, characterization of land use change following European settlement requires reconstruction of the original property mosaic. However, this task is difficult in unsystematically surveyed areas east of the Appalachian Mountains. The Gwynns Falls watershed (Baltimore, MD) was originally surveyed in the 1600-1700s under a system of warrants and patents (commonly known as 'metes and bounds'). A method for the reconstruction and mapping of warrant and patent properties is presented and used to map the original property mosaic in the Gwynns Falls watershed. Using the mapped mosaic, the persistence of properties and property lines in the current Gwynns Falls landscape is considered. The results of this research indicate that as in agricultural areas, the original property lines in the Gwynns Falls watershed are persistent. At the same time, the results suggest that the property mosaic in heavily urbanized/suburbanized areas is generally 'reset.' Further, trends in surveying technique, parcel size, and settlement patterns cause property line density and property shape complexity to increase in the less urbanized upper watershed. The persistence of original patterns may be damping expression of heterogeneity gradients in this urban landscape. This spatial pattern of complexity in the original mosaic is directly opposite of hypothesized patterns of landscape heterogeneity arising from urbanization. The technique reported here and the resulting observations are important for landscape pattern studies in areas settled under unsystematic survey systems, especially the heavily urbanized areas of the eastern United States.://000226268600003 ISI Document Delivery No.: 886YI Times Cited: 1 Cited Reference Count: 38 Cited References: *BALT EC STUD, 1999, OCT 5 LEAF ON 2 FOOT *INT LTD, 1996, GEOM WIN95 *MAR OFF PLANN, 1999, MAR PROP VIEW BOURDO EA, 1956, ECOLOGY, V37, P754 BROOKS NA, 1979, HIST BALTIMORE COUNT COMBER AJ, 2003, GLOBAL ECOL BIOGEOGR, V12, P207 CURTIS JT, 1956, MANS ROLE CHANGING F DONNELLY RH, 1980, SURV MAPP, V40, P51 EARLE CV, 1975, EVOLUTION TIDEWATER FINLEY RW, 1976, ORIGINAL VEGETATION FOSTER DR, 1992, J ECOL, V80, P753 GORDON RB, 1966, NATURAL VEGETATION O HARDING JS, 1998, P NATL ACAD SCI USA, V95, P14843 HARLEY RB, 1948, THESIS U IOWA IOWA C HORVATH GJ, 1978, EARLY OWNERS NEAR WA HORVATH GJ, 1985, ELKRIDGE ELLICOTTS U JOHNSON HB, 1957, GEOGR REV, V47, P330 JOHNSON HB, 1976, ORDER LAND US RECTAN KILTY J, 1808, LAND HOLDERS ASSISTA KIMBALL D, 2001, NWF DEM DATA EDITING MAGILL AH, 1997, ECOL APPL, V7, P402 MARSCHNER FJ, 1974, ORIGINAL VEGETATION MCDONNELL MJ, 1990, ECOLOGY, V71, P1232 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MCGRAIN JW, 1985, PIG IRON COTTON DUCK MOTZKIN G, 1996, ECOL MONOGR, V66, P345 NIEMI RG, 1990, J POLIT, V52, P1155 OLSON SH, 1997, BALTIMORE BUILDING A PICKETT STA, 2001, ANNU REV ECOL SYST, V32, P127 PRICE ET, 1995, DIVIDING LAND EARLY RICHTER DD, 2001, UNDERSTANDING SOIL C ROLAND J, 1993, OECOLOGIA, V93, P25 RUSSELL EWB, 1997, PEOPLE LAND TIME RYON RN, 1993, W BALTIMORE NEIGHBOR RYON RN, 2000, NW BALTIMORE ITS NEI STEFFEN CG, 1993, GENTLEMEN TOWNSEMEN THROWER NJW, 1966, ORIGINAL SURVEY LAND WHITNEY GG, 1994, COASTAL WILDERNESS F 0921-2973 Landsc. Ecol.ISI:000226268600003Johns Hopkins Univ, Dept Geog & Environm Engn, Baltimore, MD 21210 USA. Bain, DJ, US Geol Survey, 345 Middlefield Rd,MS 420, Menlo Pk, CA 94025 USA. djbain@usgs.govEnglish~?PBaird, A. H. Kerr, A. M.2008SLandscape analysis and tsunami damage in Aceh: comment on Iverson and Prasad (2007)3-5Landscape Ecology231Data presented in Iverson and Prasad (2007), Using landscape analysis to assess and model tsunami damage in Aceh province, Sumatra. Landscape Ecology 22: 323-331 do not justify their conclusion that tree belts provided an effective defence against the Indian Ocean tsunami in Aceh, Indonesia. The mitigation hypothesis is not explicitly tested, and their modelling approach to predict areas susceptible to tsunami damage ignores many variables known to be important in the area studied."://WOS:000251796100002 Times Cited: 0WOS:00025179610000210.1007/s10980-007-9152-0~?lBajocco, S. Ricotta, C.2008`Evidence of selective burning in Sardinia (Italy): which land-cover classes do wildfires prefer?241-248Landscape Ecology23The objective of this paper is to identify land-cover types where fire incidence is higher (preferred) or lower (avoided) than expected from a random null model. Fire selectivity may be characterized by the number of fires expected in a given land-cover class and by the mean surface area each fire will burn. These two components of fire pattern are usually independent of each other. For instance, fire number is usually connected with socioeconomic causes whereas fire size is largely controlled by fuel continuity. Therefore, on the basis of available fire history data for Sardinia (Italy) for the period 2000-2004 we analyzed fire selectivity of given land-cover classes keeping both variables separate from each other. The results obtained from analysis of 13,377 fires show that for most land-cover classes fire behaves selectively, with marked preference (or avoidance) in terms of both fire number and fire size. Fire number is higher than expected by chance alone in urban and agricultural areas. In contrast, in forests, grasslands, and shrublands, fire number is lower than expected. In grasslands and shrublands mean fire size is significantly larger than expected from a random null model whereas in urban areas, permanent crops, and heterogeneous agricultural areas there is significant resistance to fire spread. Finally, as concerns mean fire size, in our study area forests and arable land burn in proportion to their availability without any significant tendency toward fire preference or avoidance. The results obtained in this study contribute to fire risk assessment on the landscape scale, indicating that risk of wildfire is closely related to land cover."://WOS:000252636100011 Times Cited: 0WOS:000252636100011(10.1007/s10980-007-9176-5|ISSN 0921-2973<70(Baker, M. E. Weller, D. E. Jordan, T. E.2006TImproved methods for quantifying potential nutrient interception by riparian buffers 1327-1345Landscape Ecology218riparian buffers; landscape metrics; land cover; nutrient filters; topographic analysis COASTAL-PLAIN WATERSHEDS; CHESAPEAKE BAY; LAND-COVER; NITRATE REMOVAL; LANDSCAPE INDICATORS; SURFACE-WATER; GROUND-WATER; QUALITY; FOREST; ZONESArticleNovNEfforts to quantify the effects of riparian buffers on watershed nutrient discharges have been confounded by a commonly used analysis, which estimates buffer potential as the percentage of forest or wetland within a fixed distance of streams. Effective landscape metrics must instead be developed based on a clear conceptual model and quantified at the appropriate spatial scale. We develop new metrics for riparian buffers in two stages of increasing functional specificity to ask: (1) Which riparian metrics are more distinct from measures of whole watershed land cover? (2) Do functional riparian metrics provide different information than fixed-distance metrics? (3) How do these patterns vary within and among different physiographic settings? Using publicly available geographic data, we studied 503 watersheds in four different physiographic provinces of the Chesapeake Bay Drainage. In addition to traditional fixed-distance measures, we calculated mean buffer width, gap frequency, and measures of variation in buffer width using both "unconstrained" metrics and "flow-path" metrics constrained by surface topography. There were distinct patterns of relationship between watershed and near-stream land cover in each physiographic province and strong correlations with watershed land cover confounded fixed-distance metrics. Flow-path metrics were more independent of watershed land cover than either fixed-distance or unconstrained measures, but both functional metrics provided greater detail, interpretability, and flexibility than the fixed-distance approach. Potential applications of the new metrics include exploring the potential for land cover patterns to influence water quality, accounting for buffers in statistical nutrient models, quantifying spatial patterns for process-based modeling, and targeting management actions such as buffer restoration.://000242089300012 d ISI Document Delivery No.: 106GP Times Cited: 0 Cited Reference Count: 58 Cited References: *US EPA, 2000, MULT RES LAND CHAR C ALTMAN SJ, 1995, J ENVIRON QUAL, V24, P707 BAKER ME, IN PRESS LANDSCAPE E BAKER ME, 2001, J AM WATER RESOUR AS, V37, P1615 BAKER ME, 2003, ENVIRON MANAGE, V32, P706 BAKER ME, 2006, PHOTOGRAMM ENG REM S, V72, P159 COOPER AB, 1990, HYDROBIOLOGIA, V202, P13 CORRELL DL, 1997, GROUNDWATER SURFACE, P162 CULLINAN VI, 1992, LANDSCAPE ECOL, V7, P211 GERGEL SE, 2002, AQUAT SCI, V64, P118 GERGEL SE, 2005, LANDSCAPE ECOL, V20, P177 GILLIAM JW, 1994, J ENVIRON QUAL, V23, P896 GOLD AJ, 2001, J AM WATER RESOUR AS, V37, P1457 GREGORY SV, 1991, BIOSCIENCE, V41, P540 GRIFFITH JA, 2002, WATER AIR SOIL POLL, V138, P181 GROFFMAN PM, 1992, J ENVIRON QUAL, V21, P666 HELLWEGER FL, 1997, AGREE DEM SURFACE RE HILL AR, 1996, J ENVIRON QUAL, V25, P743 HOLLENHORST TP, 2006, IN PRESS SCALING UNC, CH15 HUNSAKER CT, 1992, ECOLOGICAL INDICATOR, V2, P997 HUNSAKER CT, 1995, BIOSCIENCE, V45, P193 JACOBS TC, 1985, J ENVIRON QUAL, V14, P467 JENSON SK, 1988, PHOTOGRAMM ENG REMOT, V54, P1593 JOHNSON LB, 1997, FRESHWATER BIOL, V37, P193 JONES KB, 2001, LANDSCAPE ECOL, V16, P301 JORDAN TE, 1993, J ENVIRON QUAL, V22, P467 JORDAN TE, 1997, J AM WATER RESOUR AS, V33, P631 JORDAN TE, 1997, J ENVIRON QUAL, V26, P836 JORDAN TE, 2003, ESTUARIES, V26, P226 KING RS, 2005, ECOL APPL, V51, P137 LANGLAND MJ, 1995, 954233 US GEOL SURV LI HB, 2004, LANDSCAPE ECOL, V19, P389 LIU ZJ, 2000, J AM WATER RESOUR AS, V36, P1349 LOWRANCE R, 1985, J SOIL WATER CONSERV, V40, P87 LOWRANCE R, 1997, ENVIRON MANAGE, V21, P687 MARCEAU DJ, 1994, REMOTE SENS ENVIRON, V49, P105 MCGARIGAL K, 1995, PNWGTR351 PAC NW RES NAIMAN RJ, 1997, ANNU REV ECOL SYST, V28, P621 NORTON MM, 2000, ECOL ENG, V14, P337 OMERNIK JM, 1981, J SOIL WATER CONSERV, V36, P227 OSBORNE LL, 1988, J ENVIRON MANAGE, V26, P9 OSBORNE LL, 1993, FRESHWATER BIOL, V29, P243 PETERJOHN WT, 1984, ECOLOGY, V65, P1466 PHILLIPS PJ, 1993, WETLANDS, V13, P75 RICHARDS C, 1996, CAN J FISH AQUAT S1, V53, P295 ROSENBLATT AE, 2001, J ENVIRON QUAL, V30, P1596 ROTH NE, 1996, LANDSCAPE ECOL, V11, P141 RUSSELL GD, 1997, RESTOR ECOL S, V5, P56 SHUFT MJ, 1999, PHOTOGRAMMETRIC ENG, V65, P1157 TARBOTON DG, 1997, WATER RESOUR RES, V33, P309 TISCHENDORF L, 2001, LANDSCAPE ECOL, V16, P235 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P245 TURNER MG, 2001, LANDSCAPE ECOLOGY TH VIDON PGF, 2004, WATER RESOUR RES, V40 VOGELMANN JE, 1998, ENVIRON MONIT ASSESS, V51, P415 VOGELMANN JE, 1998, PHOTOGRAMM ENG REM S, V64, P45 WELLER CM, 1996, ENVIRON MANAGE, V20, P731 WELLER DE, 1998, ECOL APPL, V8, P1156 0921-2973 Landsc. Ecol.ISI:000242089300012Utah State Univ, Dept Aquat Watershed & Earth Resources, Logan, UT 84322 USA. Smithsonian Environm Res Ctr, Edgewater, MD 21037 USA. Baker, ME, Utah State Univ, Dept Aquat Watershed & Earth Resources, Logan, UT 84322 USA. matt.baker@usu.eduEnglish}?(Baker, M. E. Weller, D. E. Jordan, T. E.2007mEffects of stream map resolution on measures of riparian buffer distribution and nutrient retention potential973-992Landscape Ecology227Aug://000248381900002 0921-2973ISI:000248381900002? Baker, W.L.1989&A Review of Models of Landscape Change111-133Landscape Ecology22 Models, Landscape change, reviewKModels of landscape change may serve a variety of purposes, from exploring the interaction of natural processes to evaluating proposed management treatments. These models can be categorized as either whole landseape models, distributional landscape models, or spatial landscape models, depending on the amount of detail included in the models. Distributional models, while widely used, exclude spatial detail important for most landscape ecological research. Spatial models require substantial data, now more readily available, via remote sensing, and more easily manipulated, in geographical information systems. In spite of these technical advances, spatial modelling is poorly developed, largely because landscape change itself is poorly understood. To facilitate further development of landscape models I suggest (1) empirical multivariate studies of landscape change, (2) modelling of individual landscape processes, (3) explicit study of the effect of model scale on model behavior, and (4) ‘scaling-up’ results of studies, on smaller land areas, that have landscape relevance.?7 Baker, W.L.1992[The landscape ecology of large disturbances in the design and management of nature reserves181-194Landscape Ecology73]disturbances, nature reserves, landscape management, conservation biology, landscape modelingLarge disturbances such as fires and floods are landscape processes that may alter the structure of landscapes in nature reserves. Landscape structure may in turn influence the viability of species and the functioning of ecosystems. Past reserve design and management strategies have been focussed on species and ecosystems rather than on landscape-scale processes, such as disturbance. An essential feature of a natural disturbance regime is the variation in disturbance attributes (e.g., size, timing, intensity, spatial location). Although some past reserve management policies have included natural disturbances, perpetuating disturbance variation has not been the explicit goal of either reserve design or management. To design a reserve to perpetuate the natural disturbance process requires consideration of: (1) the size of the reserve in relation to maximum expected disturbance size, (2) the location of the reserve in relation to favored disturbance initiation and export zones and in relation to spatial variation in the disturbance regime, and (3) the feasibility of disturbance control at reserve boundaries, or in reserve buffers. Disturbance management possibilities are constrained by the design of the reserve and the reserve goals. Where a natural disturbance regime is not feasible, then it is important that the managed disturbance regime mimic historical variation in disturbance sizes and other attributes as well as possible. Manipulating structure on the landscape scale to restore landscapes thought to have been altered by historical disturbance control is premature given our understanding of spatial disturbance processes in landscapes.%|7 Baker, W. L.1992[The Landscape Ecology of Large Disturbances in the Design and Management of Nature-Reserves181-194Landscape Ecology739disturbances nature reserves landscape ecology managementSepLarge disturbances such as fires and floods are landscape processes that may alter the structure of landscapes in nature reserves. Landscape structure may in turn influence the viability of species and the functioning of ecosystems. Past reserve design and management strategies have been focussed on species and ecosystems rather than on landscape-scale processes, such as disturbance. An essential feature of a natural disturbance regime is the variation in disturbance attributes (e.g., size, timing, intensity, spatial location). Although some past reserve management policies have included natural disturbances, perpetuating disturbance variation has not been the explicit goal of either reserve design or management. To design a reserve to perpetuate the natural disturbance process requires consideration of: (1) the size of the reserve in relation to maximum expected disturbance size, (2) the location of the reserve in relation to favored disturbance initiation and export zones and in relation to spatial variation in the disturbance regime, and (3) the feasibility of disturbance control at reserve boundaries, or in reserve buffers. Disturbance management possibilities are constrained by the design of the reserve and the reserve goals. Where a natural disturbance regime is not feasible, then it is important that the managed disturbance regime mimic historical variation in disturbance sizes and other attributes as well as possible. Manipulating structure on the landscape scale to restore landscapes thought to have been altered by historical disturbance control is premature given our understanding of spatial disturbance processes in landscapes.://A1992JW40100004-Jw401 Times Cited:87 Cited References Count:0 0921-2973ISI:A1992JW40100004;Baker, Wl Univ Wyoming,Dept Geog & Recreat,Laramie,Wy 82071English$?7 Baker, W. L.1995SLongterm response of disturbance landscapes to human intervention and global change143-159Landscape Ecology103Ilandscape change, natural disturbance, landscape structure, GIS, DISPATCHf|7[ Baker, W. L.1995TLong-Term Response of Disturbance Landscapes to Human Intervention and Global Change143-159Landscape Ecology103<landscape change natural disturbance landscape structure gisJunThe structure of landscapes subject to patch-forming catastrophic disturbances, or ''disturbance landscapes'', is controlled by the characteristics of the disturbance regime, including the distribution of disturbance sizes and intervals, and the rotation time. The primary landscape structure in disturbance landscapes is the structure of the mosaic of disturbance patches, which can be described by indices such as patch size and shape. The purpose of this research was to use a geographical information system-based spatial model (DISPATCH) to simulate the effects of the initial density of patches on the rate of response to alteration of a disturbance regime, the effects of global warming and cooling, and the effects of fragmentation and restoration, on the structure of a generalized temperate-zone forested disturbance landscape over a period of 400 yr. The simulations suggest that landscapes require 1/2 to 2 rotations of a new disturbance regime to adjust to that regime regardless of the size and interval distributions. Thus alterations that shorten rotations, as would be the case if global warming increases fire sizes and decreases fire intervals, produce a more rapid response than do alterations that lengthen rotations, such as cooling and fire suppression. Landscape with long rotations may be in perpetual disequilibrium with their disturbance regimes due to a mismatch between their adjustment rate and the rate of climatic change. Landscapes with similar rotation times may have different structures, because size and interval distributions independently affect landscape structure. The response of disturbance landscapes to changing disturbance regimes is governed by both the number and size of patch births.://A1995RF27500003-Rf275 Times Cited:70 Cited References Count:0 0921-2973ISI:A1995RF27500003;Baker, Wl Univ Wyoming,Dept Geog & Recreat,Laramie,Wy 82071English?7Baker, W.L. Y. Cai1992pThe r.le programs for multiscale analysis of landscape structure using the GRASS geographical information system291-302Landscape Ecology744Landscape structure, GIS, landscape pattern indiciesGeographical information systems (CIS) are well suited to the spatial analysis of landscape data, but generally lack programs for calculating traditional measures of landscape structure (e.g., fractal dimension). Standalone programs for calculating landscape structure measures do exist, but these programs do not enable the user to take advantage of GIS facilities for manipulating and analyzing landscape data. Moreover, these programs lack capabilities for analysis with sampling areas of different size (multiscale analysis) and also lack some needed measures of landscape structure (e.g., texture). We have developed the r.le programs for analyzing landscape structure using the CRASS CIS. The programs can be used to calculate over sixty measures of landscape structure (e.g., distance, size, shape, fractal dimension, perimeters, diversity, texture, juxtaposition, edges) within sampling areas of several sizes simultaneously. Also possible are moving window analyses, which enable the production of new maps of the landscape structure within windows of a particular size. These new maps can then be used in other analyses with the CIS.;|7 Baker, W. L. Cai, Y. M.1992pThe R Le-Programs for Multiscale Analysis of Landscape Structure Using the Grass Geographical Information-System291-302Landscape Ecology74Alandscape structure software geographical information systems gisDecxGeographical information systems (GIS) are well suited to the spatial analysis of landscape data, but generally lack programs for calculating traditional measures of landscape structure (e.g., fractal dimension). Stand-alone programs for calculating landscape structure measures do exist, but these programs do not enable the user to take advantage of GIS facilities for manipulating and analyzing landscape data. Moreover, these programs lack capabilities for analysis with sampling areas of different size (multiscale analysis) and also lack some needed measures of landscape structure (e.g., texture). We have developed the r.le programs for analyzing landscape structure using the GRASS GIS. The programs can be used to calculate over sixty measures of landscape structure (e.g., distance, size, shape, fractal dimension, perimeters, diversity, texture, juxtaposition, edges) within sampling areas of several sizes simultaneously. Also possible are moving window analyses, which enable the production of new maps of the landscape structure within windows of a particular size. These new maps can then be used in other analyses with the GIS.://A1992KD83100005.Kd831 Times Cited:117 Cited References Count:0 0921-2973ISI:A1992KD831000051Baker, Wl Univ Wyoming,Dept Geog,Laramie,Wy 82071English<7=Baldwin, D. J. B. Weaver, K. Schnekenburger, F. Perera, A. H.2004Sensitivity of landscape pattern indices to input data characteristics on real landscapes: implications for their use in natural disturbance emulation255-271Landscape Ecology193classification; disturbance emulation; extent; index; landscape; pattern; sensitivity; resolution QUANTIFY SPATIAL-PATTERNS; BOREAL FOREST; MULTISCALE ANALYSIS; FIRE REGIMES; METRICS; SIMULATION; DYNAMICS; ONTARIO; SCALESArticle' Resource management strategies have begun to adopt natural landscape disturbance emulation as a means of minimizing risk to ecosystem integrity. Detailed understanding of the disturbance regime and the associated spatial landscape patterns are required to provide a "natural" baseline for comparison with the results of emulation strategies. Landscape pattern indices provide a useful tool to quantify spatial pattern for developing these strategies and evaluating their success. Despite an abundance of indices and tools to calculate these, practical knowledge of interpretation is rare. Quantifying changes in landscape pattern indices and the meaning of these changes is confounded by index sensitivity to input data characteristics such as spatial extent, spatial resolution, and thematic resolution. Sensitivity has been examined for simulated landscapes but rarely using real data for large areas as real landscapes are more difficult to manipulate systematically than simulated data. While simulated data offer a control, they do not provide an accurate portrayal of reality for practical applications. Our goal was to test the sensitivity of a suite of landscape pattern indices useful for disturbance emulation strategy development and evaluation to spatial extent, spatial resolution, and thematic resolution using current land cover data for a case study of the managed forest of Ontario, Canada. We also examined how sensitivity varies spatially across the study area. We used Landsat TM-based land cover data (> 45.5 million ha), controlling spatial extent (2,500 to 2,560,000 ha), spatial resolution (1 to 16 ha), and thematic resolution (2 to 26 classes). For each index we tested a hypothesis of insensitivity to changes in each input data characteristic using a combination of ANOVA and regression and compared our results with previous studies. Of the 18 indices studied, significant (p < 0.01) effects were found for 17 indices with changes in spatial extent, 13 indices with changes in spatial resolution and 18 indices with changes in thematic resolution. A significant (p < 0.01) linear trend accounted for the majority of the variance for all of the significant relationships identified. Most of the mean index responses were consistent with those interpreted from previous studies of simulated and real landscapes; however, sensitivity varied greatly among indices and over space. We suggest that variation in sensitivity to input data characteristics among indices and over space must be explicitly incorporated in the design of future natural disturbance emulation efforts.://000221878900003 \ ISI Document Delivery No.: 827DL Times Cited: 5 Cited Reference Count: 67 Cited References: *ESRI, 1997, ARC INF ARC GRID VER *ESRI, 1998, ARCVIEW WIND VERS 3 *OMNR, 1996, FOR MAN PLANN MAN ON *OMNR, 1996, FOR RES INV DAT MAN *OMNR, 2001, FOR MAN GUID NAT DIS *OMNR, 2002, NAT WAY GUID NAT DIS *SAS I, 1993, SAS PROC GUID VERS 6 *SPECTR INC, 1997, UNPUB US MAN ONT PRO BAKER WL, 1992, LANDSCAPE ECOL, V7, P291 BALDWIN DJB, 2000, ECOLOGY MANAGED TERR, P12 BARTEL A, 2000, ECOL MODEL, V130, P87 BENSON BJ, 1995, LANDSCAPE ECOL, V10, P113 BERGERON Y, 1999, FOREST CHRON, V75, P49 BERGERON Y, 2001, CAN J FOREST RES, V31, P384 CAIN DH, 1997, LANDSCAPE ECOL, V12, P199 CANDAU JN, 1998, CAN J FOREST RES, V28, P1733 CHEW V, 1976, HORTSCIENCE, V11, P348 CISSEL JH, 1999, ECOL APPL, V9, P1217 DRAPER NR, 1981, APPL REGRESSION ANAL ELKIE PC, 2001, FOREST ECOL MANAG, V147, P253 FINNEY MA, 1999, SPATIAL MODELING FOR, P186 FORMAN RT, 1986, LANDSCAPE ECOLOGY FRANKLIN SE, 2000, FOREST CHRON, V76, P877 GLUCK MJ, 1996, ENVIRON MONIT ASSESS, V39, P435 GRIFFITH JA, 2000, LANDSCAPE URBAN PLAN, V52, P45 GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HAINESYOUNG R, 1996, PROG PHYS GEOG, V20, P418 HARGIS CD, 1997, WILDLIFE LANDSCAPE E, P231 HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HAY GJ, 2001, LANDSCAPE ECOL, V16, P471 HE HS, 2000, LANDSCAPE ECOL, V15, P591 HEINSELMAN ML, 1973, QUATERNARY RES, V3, P329 HESSBURG PF, 1999, ECOL APPL, V9, P1232 HUNTER ML, 1993, BIOL CONSERV, V65, P115 KEANE RE, 1999, LANDSCAPE ECOL, V14, P311 KEANE RE, 2002, ECOL MODEL, V151, P29 KITZBERGER T, 1999, LANDSCAPE ECOL, V14, P1 LAVOREL S, 1993, OIKOS, V67, P521 LEITAO AB, 2002, LANDSCAPE URBAN PLAN, V59, P65 LI HB, 1993, LANDSCAPE ECOL, V8, P155 LI HB, 1994, ECOLOGY, V75, P2446 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MCGARIGAL K, 2001, LANDSCAPE ECOL, V16, P327 MORGAN P, 1994, J SUSTAINABLE FOREST, V2, P87 NAGENDRA H, 2002, APPL GEOGR, V22, P175 ONEILL RV, 1992, LANDSCAPE ECOL, V7, P55 ONEILL RV, 1999, ECOSYST HEALTH, V5, P225 PERERA AH, IN PRESS EMULATING N, R20 PERERA AH, 1997, LEAP 2 LANDSCAPE ECO PERERA AH, 1998, 147 ONT MIN NAT RES PERERA AH, 1998, 152 ONT MIN NAT RES PERERA AH, 2000, ECOLOGY MANAGED TERR, P74 PERERA AH, 2003, FOREST CHRON, V79, R20 PETERSON GD, 2002, ECOSYSTEMS, V5, P329 REMMEL TK, 2001, FOREST ECOL MANAG, V152, P119 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 ROWE JS, 1972, CANADIAN FOREST SERV, V1300 SAURA S, 2000, LANDSCAPE ECOL, V15, P661 SCHROEDER D, 2002, FOREST ECOL MANAG, V159, P217 SOKAL RR, 1981, BIOMETRY THOMPSON WA, 2000, FOREST ECOL MANAG, V134, P163 TISCHENDORF L, 2001, LANDSCAPE ECOL, V16, P235 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P245 TURNER MG, 1989, OIKOS, V55, P1532 TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 0921-2973 Landsc. Ecol.ISI:000221878900003Ontario Forest Res Inst, Sault Ste Marie, ON P6E 2E5, Canada. Sault Coll Appl Arts & Technol, Sault Ste Marie, ON P6A 5L3, Canada. Baldwin, DJB, Ontario Forest Res Inst, 1235 Queen St E, Sault Ste Marie, ON P6E 2E5, Canada. baldwin@spatialworks.comEnglish &?L Gerard Balent Bernard Courtiade1992cModelling bird communities and scape patterns relationships in a rural area of South-Western France195-211Landscape Ecology63birds, community, landscape attribute, modelling, correspondence analysis, niche breadth, ecological diversity, gradient, rural area, South-Western FranceThe new trends in agricultural policy in Western Europe conduct to new management problems in maintaining and utilizing biological resources. In the South-Western France, the evolution of agricultural practices occurs in two opposite ways. On one hand, the intensification of agriculture leads to simplify the landscape by hedgerows removal, grasslands ploughing and drainage for corn cultivation. On the other hand, the decreasing numbers of cattle and sheep conduct the less fertile parts of the territory to evolve into fallow. These two processes are closely linked on a same territory and important interactions exist between intensive agricultural areas and semi-natural communities. To understand the importance of these interactions and their role in ecological stability of landscapes, we use passerine bird communities as an ecological indicator. We modelized the relationships between birds and landscape structure from 256 relevCs. Each relevC includes a bird count point of 20 mn and a description of the landscape feature on the surrounding 6.25 ha. An ordination of the releves along the main ecological gradients was realized using Correspondence Analysis. Then, these ordinations where related to the landscape structure with Stepwise and Multiple Regression Analysis. The rate of woody area, the hedgerow network complexity and the rate of fallow land are the main ecological gradients. We have used this model to measure the importance of the changes induced on landscape by a range of management practices differing in intensity. To achieve this aim we compare the displacement of 116 relevis along the ecological gradients between 1983 and 1988. The changes occurring both in bird composition and landscape structure reveal the ecological impacts of the different management practices (hedgerow removal, drainage, ploughing, decreasing grazing pressure). We examine the behaviour of ecological diversity of landscape units differing in structure and use.|7mBalkenhol, N. Gugerli, F. Cushman, S. A. Waits, L. P. Coulon, A. Arntzen, J. W. Holderegger, R. Wagner, H. H.2009LIdentifying future research needs in landscape genetics: where to from here?455-463Landscape Ecology244'landscape resistance adaptive genetic variation gene flow single nucleotide polymorphisms spatial heterogeneity spatio temporal scale population-structure habitat fragmentation environmental-factors sympatric speciation spatial-analysis circuit-theory diversity ecology connectivity conservationApr,Landscape genetics is an emerging interdisciplinary field that combines methods and concepts from population genetics, landscape ecology, and spatial statistics. The interest in landscape genetics is steadily increasing, and the field is evolving rapidly. We here outline four major challenges for future landscape genetic research that were identified during an international landscape genetics workshop. These challenges include (1) the identification of appropriate spatial and temporal scales; (2) current analytical limitations; (3) the expansion of the current focus in landscape genetics; and (4) interdisciplinary communication and education. Addressing these research challenges will greatly improve landscape genetic applications, and positively contribute to the future growth of this promising field.://000263898100001-414XI Times Cited:0 Cited References Count:57 0921-2973ISI:000263898100001Balkenhol, N Univ Idaho, Dept Fish & Wildlife Resources, Moscow, ID 83844 USA Univ Idaho, Dept Fish & Wildlife Resources, Moscow, ID 83844 USA WSL Eidgenoss Forsch Sanstalt, CH-8903 Birmensdorf, Switzerland Rocky Mt Res Stn, Missoula, MT 59801 USA Cornell Lab Ornithol, Ithaca, NY 14850 USA Natl Museum Nat Hist, Res Dept, NL-2300 RA Leiden, Netherlands Univ Toronto, Dept Ecol & Evolutionary Biol, Mississauga, ON L5L 1C6, CanadaDoi 10.1007/S10980-009-9334-ZEnglish~?}5Bar Massada, A. Gabay, O. Perevolotsky, A. Carmel, Y.2008aQuantifying the effect of grazing and shrub-clearing on small scale spatial pattern of vegetation327-339Landscape Ecology233Disturbances such as grazing, invading species, and clear-cutting, often act at small spatial scales, and means for quantifying their impact on fine scale vegetation patterns are generally lacking. Here we adopt a set of landscape metrics, commonly used for quantifying coarse scale fragmentation, to quantify fine scale fragmentation, namely the fine scale vegetation structure. At this scale, patches often consist of individual plants smaller than 1 m(2), requiring the grain of the analysis to be much smaller. We used balloon aerial photographs to map fine details of Mediterranean vegetation (pixel size < 0.04 m) in experimental plots subjected to grazing and clear-cutting and in undisturbed plots. Landscape metrics are sensitive to scale. Therefore, we aggregated the vegetation map into four coarser scales, up to a resolution of 1 m, and analyzed the effect of scale on the metrics and their ability to distinguish between different disturbances. At the finest scale, six of the seven landscape metrics we evaluated revealed significant differences between treated and undisturbed plots. Four metrics revealed differences between grazed and control plots, and six metrics revealed differences between cleared and control plots. The majority of metrics exhibited scaling relations. Aggregation had mixed effects on the differences between metric values for different disturbances. The control plots were the most sensitive to scale, followed by grazing and clearing. We conclude that landscape metrics are useful for quantifying the very fine scale impact of disturbance on woody vegetation, assuming that the analysis is based on sufficiently high spatial resolution data."://WOS:000254112100007 Times Cited: 0WOS:000254112100007(10.1007/s10980-007-9189-0|ISSN 0921-2973|?? Bar Massada, A. Radeloff, V. C.2010ATwo multi-scale contextual approaches for mapping spatial pattern711-725Landscape Ecology255The majority of landscape pattern studies are based on the patch-mosaic paradigm, in which habitat patches are the basic unit of the analysis. While many patch-based landscape indices successfully relate spatial patterns to ecological processes, it is also desirable to use finer grained analyses for understanding species presence, abundance, and movement patterns across the landscape and to describe spatial context by measuring habitat change across scales. Here, we introduce two multi-scale pixel-based approaches for spatial pattern analysis, which quantify the spatial context of each pixel in the landscape. Both approaches summarize the proportion of habitat at increasing window sizes around each pixel in a scalogram. In the first regression-based approach, a third-order polynomial is fitted to the scalogram of each pixel, and the four polynomial coefficients are used as descriptors of spatial context of each pixel within the landscape mosaic. In the second shape-based approach, the scalogram mean and standard deviation, and the mean slope between forest cover at the smallest window size and each of the larger window sizes are calculated. The values emerging from these two approaches are assigned to each focal pixel and can be used as predictive variables, for example, in species presence and abundance studies. We tested the performance of these approaches on 18 random landscapes and nine actual landscapes with varying forest habitat cover. Results show that both methods were able to differentiate between several spatial contexts. We thus suggest that these approaches could serve as a complement or an alternative to existing methods for landscape pattern analysis and possibly add further insight into pattern-species relations.!://WOS:000276609800005Times Cited: 0 0921-2973WOS:00027660980000510.1007/s10980-010-9452-7? BBarbaro, Luc Brockerhoff, Eckehard Giffard, Brice van Halder, Inge2012WEdge and area effects on avian assemblages and insectivory in fragmented native forests 1451-1463Landscape Ecology2710Springer NetherlandsBiomedical and Life SciencessDisentangling the confounded effects of edge and area in fragmented landscapes is a recurrent challenge for landscape ecologists, requiring the use of appropriate study designs. Here, we examined the effects of forest fragment area and plot location at forest edges versus interiors on native and exotic bird assemblages on Banks Peninsula (South Island, New Zealand). We also experimentally measured with plasticine models how forest fragment area and edge versus interior location influenced the intensity of avian insectivory. Bird assemblages were sampled by conducting 15 min point-counts at paired edge and interior plots in 13 forest fragments of increasing size (0.5–141 ha). Avian insectivory was measured as the rate of insectivorous bird attacks on plasticine models mimicking larvae of a native polyphagous moth. We found significant effects of edge, but not of forest patch area, on species richness, abundance and composition of bird assemblages. Exotic birds were more abundant at forest edges, while neither edge nor area effects were noticeable for native bird richness and abundance. Model predation rates increased with forest fragmentation, both because of higher insectivory in smaller forest patches and at forest edges. Avian predation significantly increased with insectivorous bird richness and foraging bird abundance. We suggest that the coexistence of native and exotic birds in New Zealand mosaic landscapes enhances functional diversity and trait complementation within predatory bird assemblages. This coexistence results in increased avian insectivory in small forest fragments through additive edge and area effects.+http://dx.doi.org/10.1007/s10980-012-9800-x 0921-297310.1007/s10980-012-9800-x? xBarber, Jesse Burdett, Chris Reed, Sarah Warner, Katy Formichella, Charlotte Crooks, Kevin Theobald, Dave Fristrup, Kurt2011hAnthropogenic noise exposure in protected natural areas: estimating the scale of ecological consequences 1281-1295Landscape Ecology269Springer NetherlandsEarth and Environmental ScienceThe extensive literature documenting the ecological effects of roads has repeatedly implicated noise as one of the causal factors. Recent studies of wildlife responses to noise have decisively identified changes in animal behaviors and spatial distributions that are caused by noise. Collectively, this research suggests that spatial extent and intensity of potential noise impacts to wildlife can be studied by mapping noise sources and modeling the propagation of noise across landscapes. Here we present models of energy extraction, aircraft overflight and roadway noise as examples of spatially extensive sources and to present tools available for landscape scale investigations. We focus these efforts in US National Parks (Mesa Verde, Grand Teton and Glacier) to highlight that ecological noise pollution is not a threat restricted to developed areas and that many protected natural areas experience significant noise loads. As a heuristic tool for understanding past and future noise pollution we forecast community noise utilizing a spatially-explicit land-use change model that depicts the intensity of human development at sub-county resolution. For road noise, we transform effect distances from two studies into sound levels to begin a discussion of noise thresholds for wildlife. The spatial scale of noise exposure is far larger than any protected area, and no site in the continental US is free form noise. The design of observational and experimental studies of noise effects should be informed by knowledge of regional noise exposure patterns.+http://dx.doi.org/10.1007/s10980-011-9646-7 0921-297310.1007/s10980-011-9646-7.|? DBarbier, Nicolas Couteron, Pierre Planchon, Olivier Diouf, Abdoulaye2010Multiscale comparison of spatial patterns using two-dimensional cross-spectral analysis: application to a semi-arid (gapped) landscape889-902Landscape Ecology256JulSpectral analysis allows the characterization of temporal (1D) or spatial (2D) patterns in terms of their scale (frequency) distribution. Cross-spectral analysis can also be used to conduct independent correlation analyses at different scales between two variables, even in the presence of a complex superposition of structures, such as structures that are shifted, have different scales or have different levels of anisotropy. These well-grounded approaches have rarely been applied to two-dimensional ecological datasets. In this contribution, we illustrate the potential of the method. We start by providing a basic methodological introduction, and we clarify some technical points concerning the computation of two-dimensional coherency and phase spectra and associated confidence intervals. First, we illustrate the method using a simple theoretical model. Next, we present a real world application: the case of patterned (gapped) vegetation in SW Niger. In this example, we investigate the functional relationships between topography and the spatial distribution of two shrub species, Combretum micranthum G. Don. and Guiera senegalensis J.F. Gmel. We show that both the global vegetation pattern and the distribution of C. micranthum are independent at all analyzable scales (i.e., from 10 to 50 m) from possible relief-induced determinisms. Additionally, the two dominant shrub species form distinct patches, thus suggesting separate niches.!://WOS:000278526000006Times Cited: 1 0921-2973WOS:00027852600000610.1007/s10980-010-9466-1<7+Barkhadle, A. M. I. Ongaro, L. Pignatti, S.1994JPastoralism and plant cover in the lower Shabelle region, southern Somalia79-88Landscape Ecology92SOMALIA; RANGELAND; VEGETATIONArticleJunA vegetation and rangeland survey has been carried out in the lower Shabelle region, Southern Somalia, with the aim of evaluating the natural vegetation as a source of forage for grazing animals. In this framework, four different vegetation types have been recognized and mapped using remote sensing techniques; general vegetation characteristics, mainly floristic and physiognomic aspects, are described. Dynamic relationships between these vegetation types are also outlined.://A1994NU09400001 HISI Document Delivery No.: NU094 Times Cited: 1 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1994NU09400001JBARKHADLE, AMI, IST AGRON OLTREMARE,VIA A COCCHI 4,I-50131 FLORENCE,ITALY.English<7Barnett, D. T. Stohlgren, T. J.2001eAspen persistence near the National Elk Refuge and Gros Ventre Valley elk feedgrounds of Wyoming, USA569-580Landscape Ecology166aspen regeneration Cervus elaphus elk herbivory landscape-scale surveys Populus tremuloides PLANT DIVERSITY PARK REGENERATION RANGE SIZE FIREArticleAugWe investigated aspen (Populus tremuloides) regeneration in the Gros Ventre River Valley, the National Elk Refuge and a small part of Grand Teton National Park, Wyoming. USA to see if elk (Cervus elaphus) browsing was as damaging as previously thought. We conducted a landscape-scale survey to assess aspen regeneration across gradients of wintering elk concentrations using 68 randomly selected aspen stands in the 1090 km(2) study area. Forty-four percent of the stands sampled supported some newer regeneration that had reached the canopy. There were no significant differences of regeneration across elk winter range classification (p = 0.25) or distance from feed-rounds p = 0.96). However, a multiple linear regression found that the concentration of elk was one of several important predictors of successful aspen regeneration (p = 0.005, R-2 = 0.36). Our results suggest that stand-replacing regeneration occurs across the landscape at a variety of elk densities despite some trends of reduced regeneration under greater elk concentrations. We propose that high spatial and temporal variation and scattered patches of successful aspen regeneration characterize aspen persistence between periods of episodic regeneration and recruitment.://000172548800007 ISI Document Delivery No.: 499AW Times Cited: 6 Cited Reference Count: 43 Cited References: *ENV SYST RES I IN, 1999, TOP ARC VERS 7 2 1 P *SPSS INC, 1996, SYST 6 0 WIND STAT *VEMAP MEMB, 1995, GLOBAL BIOGEOCHEMICA, V40, P407 BAKER FS, 1925, B USDA, V1291 BAKER WL, 1997, ECOGRAPHY, V20, P155 BARTOS DL, 1991, INT448 USDA FOR SERV BEETLE AA, 1968, WYOMING AGR EXP STAT, V26 DEBYLE NV, 1978, W WILDLANDS, V5, P18 DEBYLE NV, 1985, ASPEN ECOLOGY MANAGE, P35 DESPAIN DG, 1990, YELLOWSTONE VEGETATI DONALSON DD, 1999, ECOLOGY, V80, P2492 FAGAN WF, 1999, ECOL APPL, V9, P1430 GRUELL GE, 1974, RELATIONSHIPS ASPEN HESS K, 1993, ROCKY TIMES ROCKY MO HESSL AE, 2000, THESIS U ARIZONA TUC HSIAO TC, 1973, ANNU REV PLANT PHYS, V24, P519 JOHNSON CW, 1985, ASPEN ECOLOGY MANAGE, P185 JONES JR, 1985, ASPEN ECOLOGY MANAGE, P71 KAY CE, 1990, THESIS UTAH STATE U KAY CE, 1993, NORTHWEST SCI, V67, P94 KAY CE, 1997, J FOREST, V95, P4 KAYE M, 1998, UNPUB KILPATRICK S, 1998, COMMUNICATION KREBILL RG, 1972, INT129 USDA FOR SERV LOOPE LL, 1973, QUATERNARY RES, V3, P425 OLMSTEAD CE, 1997, 20 YEARS CHANGE ROCK OLMSTED CE, 1979, N AM ELK ECOLOGY BEH, P89 RIPPLE WJ, 2000, BIOL CONSERV, V95, P361 ROMME WH, 1995, ECOLOGY, V76, P2097 SCHIER GA, 1975, INT170 USDA FOR SERV SCHIER GA, 1978, FOREST SCI, V24, P303 SCHIER GA, 1985, ASPEN ECOLOGY MANAGE, P71 SIMONSON S, 1998, THESIS COLORADO STAT SMITH B, 1998, COMMUNICATION SMITH BL, 1994, MIGRATIONS MANAGEMEN STOHLGREN TJ, 1997, ECOL APPL, V7, P1064 STOHLGREN TJ, 1999, ECOL APPL, V9, P45 STOHLGREN TJ, 1999, IN PRESS BIOSCIENCE STOHLGREN TJ, 2000, BIODIVERS CONSERV, V9, P65 STRICKLAND D, 1985, STANDARDIZED DEFINIT SUZUKI K, 1999, LANDSCAPE ECOL, V14, P231 WEINSTEIN J, 1979, N AM ELK ECOLOGY BEH, P79 WHITE CA, 1998, WILDLIFE SOC B, V26, P449 0921-2973 Landsc. Ecol.ISI:000172548800007Colorado State Univ, Nat Resource Ecol Lab, Ft Collins, CO 80523 USA. Barnett, DT, Colorado State Univ, Nat Resource Ecol Lab, Ft Collins, CO 80523 USA.Englishڽ7KBarrell, Jeffrey Grant, Jon2013bDetecting hot and cold spots in a seagrass landscape using local indicators of spatial association 2005-2018Landscape Ecology2810Springer NetherlandsaZostera marina Seagrass Seascape Getis-Ord G i * Spatial scale Geostatistics Hot spots Cold spots 2013/12/01+http://dx.doi.org/10.1007/s10980-013-9937-2 0921-2973Landscape Ecol10.1007/s10980-013-9937-2English|7(Barrett, T. L. Farina, A. Barrett, G. W.2009*Positioning aesthetic landscape as economy299-307Landscape Ecology243aesthetics economy of survival levels of organization noosphere set point transcending processes virtualsphere ecosystem services ecology managementMarmFlexibility is required in modern times to comprehend vast and fluctuating levelscapes of information. The ability to observe, simulate, and assimilate situations and circumstances from different points of reference and view is paramount for survival. This ability as preamble to consequence in landscape is valid, and provides an impetus for expanding landscape ecology from its traditional realm of definitive terrafirma to an assimilation of terraform (i.e. the process that alters an environment capable of supporting life forms). The traditional human-nature duplexity, regarding landscape ecology, is simulated with real and virtual fields in a noospheric configuration. The involvement of culture (i.e. by consensus of value) and history (i.e. by sequencing relevancy) is a contributing determinant of "real" (landscape(r)) and "virtual" (landscape(v)) fields of existence and extinction. Within this noospheric network unique observations of landscape ecology are possible (e.g. eco-field). Suggested in the noospheric network, aesthetics is an efficiency relevant to life-support systems exemplified by value that precludes aestheticism (i.e. typically limited to a dichotomy of beautiful and ugly). Aesthetics viewed as a transcending process through levels of ecological organization and as a transcending property of transcending processes becomes understood as economy (energetic efficiency) capable of supporting nonmarket and market units of valuation. The consequence of these units of valuation articulates as subjects or objects of criticism within an aesthetic set point model, which measures individual or societal tolerance.://000263419500001-408EY Times Cited:0 Cited References Count:65 0921-2973ISI:000263419500001Barrett, GW Univ Georgia, Eugene P Odum Sch Ecol, Athens, GA 30602 USA Univ Georgia, Eugene P Odum Sch Ecol, Athens, GA 30602 USA Univ Urbino, Inst Biomath, I-61029 Urbino, ItalyDoi 10.1007/S10980-009-9326-ZEnglish07 (Barrett, T. L. Farina, A. Barrett, G. W.2009CAesthetic landscapes: an emergent component in sustaining societies 1029-1035Landscape Ecology248SpringereUniv Georgia, Eugene P. Odum Sch Ecol Athens G. A. U. S. A. Univ Urbino, Inst Biomath I. Urbino ItalyAesthetic landscapes Culture-sustained vitality Ecological and cultural succession Landscape sustainability Market and nonmarket capitalOctA revival in the concept of sustainability is appreciated as Earth's human population continues to increase and its related global concerns in disease ecology, energy resource management, environmental literacy, food production, genetic diversity, and landscape vitality continue to magnify. Sustain is defined within this paper as to keep in existence or to supply with resources or necessities to prevent from falling below a given threshold of health or vitality. Barrett et al. (Bioscience 47:531-535, 1997) illustrated how seven (7) processes (behaviour, development, diversity, energetics, evolution, integration, regulation) transcend eleven (11) levels of ecological organization, ranging from the ecosphere to the cellular. Comprehension of how these processes transcend all levels of ecological organization allow programs and initiatives (e.g. preserving biotic diversity) to be defined by informed incentive, rather than regulatory mandate, within societal systems. We describe how the integration of an eighth transcending process-aesthetics-is essential in the approach to and managing of market and nonmarket capital necessary in sustaining societies.://000269913600004yISI Document Delivery No.: 495RV Times Cited: 1 Cited Reference Count: 50 Barrett, Terry L. Farina, Almo Barrett, Gary W. 0921-2973 DORDRECHT2009 Landsc. Ecol.ISI:000269913600004Landscape ecologyYBarrett, GW, Univ Georgia, Eugene P Odum Sch Ecol, Athens, GA 30602 USA. gbarrett@uga.edu10.1007/s10980-009-9354-8English~?sWBartholomew, A. Bohnsack, J. A. Smith, S. G. Ault, J. S. Harper, D. E. McClellan, D. B.2008Influence of marine reserve size and boundary length on the initial response of exploited reef fishes in the Florida Keys National Marine Sanctuary, USA55-65Landscape Ecology23!We examine the influence of reserve size and boundary length on the relative rate of fish density change in reserves versus fished reference reefs for three exploitable-sized reef fish categories: (1) combined fish (34 species of Haemulidae, Lutjanidae, Serranidae, and hogfish Lachnolaimus maximus); (2) Haemulidae (13 species); and (3) Lutjanidae (9 species). If reef habitat boundaries are highly permeable to fish movements then fish recovery within a reserve would be inversely proportional to: reserve perimeter (RP)/total reserve area (RA) (RP/RA). If, however, reef habitat boundaries are relatively impermeable barriers to fish movements, recovery within the reserve would be inversely proportional to: reserve boundary that intersects reef habitat (HI)/reef habitat area within the reserve (HA) (HI/HA). From 1994 to 2001 we monitored reef fishes within and outside of no-take marine reserves established in 1997 in the Florida Keys, USA. A significant majority of reserves had greater rates of density change than reference reefs for Lutjanidae and combined fish (22 of 24 reserves for both categories). Significantly higher rates of density change were found in ten reserves for Lutjanidae, two reserves for combined fish, and one reserve for Haemulidae. Reserves appeared to promote an increased density of exploitable fishes. A significant, negative, but weakly correlated relationship was found between the relative rate of density change (RDC) for combined fish and the HI/HA ratio. Reserve size and placement appeared to have a minimal effect upon RDC."://WOS:000252922800005 Times Cited: 0WOS:000252922800005(10.1007/s10980-007-9136-0|ISSN 0921-2973<7*Barton, A. M. Swetnam, T. W. Baisan, C. H.2001Arizona pine (Pinus arizonica) stand dynamics: local and regional factors in a fire-prone madrean gallery forest of Southeast Arizona, USA351-369Landscape Ecology164age structure Arizona pine dendrochronology drought severity El Nino fire radial growth stand dynamics SOUTHWESTERN UNITED-STATES COLORADO FRONT RANGE PONDEROSA PINE NORTHERN PATAGONIA CLIMATIC VARIABILITY AMERICAN SOUTHWEST SPATIAL PATTERNS AGE STRUCTURES TREE-GROWTH DROUGHTArticleMayKIn southwestern North America, large-scale climate patterns appear to exert control on moisture availability, fire occurrence, and tree demography, raising the compelling possibility of regional synchronization of forest dynamics. Such regional signals may be obscured, however, by local, site-specific factors, such as disturbance history and land use. Contiguous sites with similar physical environments, lower and middle Rhyolite Canyon, Arizona, USA, shared nearly the same fire history from 1660-1801, but then diverged. For the next 50 years, fires continued to occur frequently in lower Rhyolite, but, probably as result of flood-induced debris deposition, largely ceased in middle Rhyolite. We related stand dynamics of Arizona pine (Pinus arizonica) to fire history and drought severity and compared the dynamics in the two sites before and after the divergence in fire frequency. Fires occurred during unusually dry years, and possibly following unusually moist years. Arizona pine exhibited three age structure peaks: two (1810-1830 and 1870-1900) shared by the two sites and one (1610-1640) only in middle Rhyolite. The latter two peaks occurred during periods of unusually low fire frequency, suggesting that fire-induced mortality shapes age structure. Evidence was mixed for the role of favorable moisture availability in age structure. As expected, moisture availability had a prominent positive effect on radial growth, but the effect of fire was largely neutral. The two sites differed only moderately in stand dynamics during the period of divergence, exhibiting subtle age structure contrasts and, in middle Rhyolite only, reduced growth during a 50-year fire hiatus followed by fire-induced release. These results suggest that, despite local differences in disturbance history, forest responses to regional fire and climate processes can persist.://000169516300005 ISI Document Delivery No.: 446MD Times Cited: 3 Cited Reference Count: 97 Cited References: ABBOTT I, 1983, FOREST ECOL MANAG, V6, P139 ALLEN CD, 1998, P NATL ACAD SCI USA, V95, P14839 BAHRE CJ, 1991, LEGACY CHANGE HIST H BAHRE CJ, 1995, DESERT PLANTS, V11, P41 BAILEY DK, 1983, PHYTOLOGIA, V53, P226 BAISAN CH, 1990, CAN J FOREST RES, V20, P1559 BARTON AM, IN PRESS INTENSE WIL BARTON AM, 1993, AM J BOT, V80, P15 BARTON AM, 1993, ECOL MONOGR, V63, P367 BARTON AM, 1994, B TORREY BOT CLUB, V121, P251 BARTON AM, 1995, FIRE WILDERNESS PARK, P159 BARTON AM, 1999, FOREST ECOL MANAG, V120, P143 BETANCOURT JL, 1993, MANAGING PINON JUNIP, P42 BROWN L, 1992, SOUTHERLY, V52, P1 BROWN PM, 1999, LANDSCAPE ECOL, V14, P513 CARTER JL, 1997, TREES SHRUBS NEW MEX CONDIT R, 1995, ECOL MONOGR, V65, P419 COOK ER, 1996, TREE RINGS ENV HUMAN, P155 COOK ER, 1999, J CLIMATE, V12, P1145 COOPER CF, 1960, ECOL MONOGR, V30, P129 COVINGTON WW, 1984, FOREST SCI, V30, P83 COVINGTON WW, 1986, SOIL SCI SOC AM J, V50, P452 COVINGTON WW, 1994, J FOREST, V92, P39 COVINGTON WW, 1994, J SUSTAINABLE FOREST, V2, P153 DEBANO LF, 1995, P S TUCS AZ SEPT 19 FRITTS HC, 1976, TREE RINGS CLIMATE FRITTS HC, 1989, ADV ECOL RES, V19, P111 FRITTS HC, 1991, RECONSTRUCTING LARGE FULE PZ, 1994, RESTORATION ECOLOGY, V2, P261 FULE PZ, 1996, J FOREST, V94, P33 FULE PZ, 1997, ECOL APPL, V7, P895 FULE PZ, 1998, PLANT ECOL, V134, P197 GLOCK WS, 1955, BOT REV, V21, P73 GRISSINOMAYER HD, 1996, TREE RINGS ENV HUMAN, P191 GRISSINOMAYER HD, 2000, HOLOCENE, V10, P213 HARGROVE WW, 1992, LANDSCAPE ECOL, V6, P251 HEYERDAHL EK, 2001, ECOLOGY, V82, P660 HUSTON MA, 1999, OIKOS, V86, P393 JOHNSON EA, 1993, CAN J FOREST RES, V23, P1213 JOHNSON EA, 1994, J ECOL, V82, P923 KAIB H, 1998, THESIS U ARIZONA TUC KAYE MW, 1999, PHYS GEOGR, V20, P305 KITZBERGER T, 1995, CAN J FOREST RES, V25, P1684 KITZBERGER T, 1997, J BIOGEOGR, V24, P35 LEHY JH, 1978, CATALOGUE FLORA ARIZ LOUGH JM, 1987, CLIMATIC CHANGE, V10, P219 LYNCH DW, 1959, PNW412 USDA FOR SERV MARSHALL JT, 1962, J ARIZONA ACAD SCI, V2, P75 MAST JN, 1998, J BIOGEOGR, V25, P743 MAST JN, 1999, ECOL APPL, V9, P228 MEKO D, 1993, J CLIMATE, V6, P1773 MOORE MM, 1999, ECOL APPL, V9, P1266 MORINO KA, 1996, RECONSTRUCTION INTER MORRIS WG, 1958, J FOREST, V56, P203 MUTCH L, 1995, FIRE WILDERNESS PARK, P241 MUTCH LS, 1994, THESIS U ARIZONA TUC NEILSON RP, 1986, SCIENCE, V232, P27 NIERING WA, 1984, VEGETATIO, V58, P3 PEARSON GA, 1923, USDA FOREST SERVICE, V1105 PEET RK, 1981, VEGETATIO, V45, P3 PERRY JP, 1991, PINES MEXICO CENTRAL PETERSON DL, 1986, ENVIRON MANAGE, V10, P797 PLATT WJ, 1997, SAVANNA BARREN ROCK, P23 REINHARDT ED, 1988, INT387 USDA FOR SERV RYAN KC, 1988, CAN J FOREST RES, V18, P1291 SAKCETT SS, 1996, ADAPTIVE ECOSYSTEM R, P53 SAVAGE M, 1990, ECOLOGY, V71, P2374 SAVAGE M, 1996, ECOSCIENCE, V3, P310 SEKLECKI M, 1996, EFFECTS FIRE MADREAN, P238 SELLERS WD, 1985, ARIZONA CLIMATE STOKES MA, 1968, INTRO TREE RING DATI SUTHERLAND EK, 1991, FOREST ECOL MANAG, V44, P161 SWETNAM TW, 1985, USDA FOREST SERVICE, V639 SWETNAM TW, 1989, 32 U AR COOP PARK SE SWETNAM TW, 1990, SCIENCE, V249, P1017 SWETNAM TW, 1991, FIRE FLOOD CANYON WO SWETNAM TW, 1992, ECOLOGY MANAGEMENT O, P165 SWETNAM TW, 1992, OLD GROWTH FORESTS S, P24 SWETNAM TW, 1993, SCIENCE, V262, P885 SWETNAM TW, 1996, P 2 LA MES FIR S 29, P11 SWETNAM TW, 1998, J CLIMATE, V11, P3128 SWETNAM TW, 1999, ECOL APPL, V9, P1189 SWETNAM TW, 2001, CHANGING PLANT LIFE, P95 SZEICZ JM, 1995, J ECOL, V83, P873 TURNER MG, 1993, LANDSCAPE ECOL, V8, P213 VEBLEN TT, 1999, ECOL MONOGR, V69, P47 VILLALBA R, 1997, CAN J FOREST RES, V27, P580 VILLALBA R, 1997, ECOSCIENCE, V4, P534 VILLALBA R, 1997, J ECOL, V85, P113 VILLALBA R, 1998, ECOLOGY, V79, P2624 VILLANUEVADIAZ J, 1995, BIODIVERSITY MANAGEM, P416 VILLANUEVADIAZ J, 1996, EFFECTS FIRE MADREAN, P85 WHITE AS, 1985, ECOLOGY, V66, P589 WHITTAKER RH, 1965, ECOLOGY, V46, P429 WILSON JP, 1995, ISLANDS DESERT HIST WOOLDRIDGE DD, 1965, J FOREST, V63, P92 WRIGHT SJ, 1999, ECOLOGY, V80, P1632 0921-2973 Landsc. Ecol.ISI:000169516300005sUniv Maine, Dept Nat Sci, Farmington, ME 04938 USA. Barton, AM, Univ Maine, Dept Nat Sci, Farmington, ME 04938 USA.English |?7\Barton, Philip S. Ikin, Karen Smith, Annabel L. MacGregor, Christopher Lindenmayer, David B.2014bVegetation structure moderates the effect of fire on bird assemblages in a heterogeneous landscape703-714Landscape Ecology294AprEcological theory predicting the impact of fire on ecological communities is typically focused on post-disturbance recovery processes or on disturbance-diversity dynamics. Yet the established relationship between vegetation structure and animal diversity could provide a foundation to predict the short-term effects of fire on biodiversity, but has rarely been explored. We tested the hypothesis that fire effects on bird assemblages would be moderated by increasing vegetation structure. We examined bird assemblages in burnt and unburnt sites at 1 and 6 years after a wildfire, and compared richness and composition responses among and within three structurally distinct vegetation types in the same landscape: heath, woodland and forest. We found that short-term changes in bird assemblage composition were largest in simple heath vegetation and smallest in complex forest vegetation. The short-term change in species richness was larger in forest than in heath. We also found that among-site assemblage variability was greater shortly after fire in heath and woodland vegetation compared with forest vegetation. Our results indicate that complexity in vegetation structure, particularly overstorey cover, can act as an important moderator of fire effects on bird assemblages. Mechanisms for this response include a greater loss of structure in vegetation characterised by a single low stratum, and a proportionally greater change in bird species composition despite a smaller absolute change in species richness. We discuss our results in the context of a new conceptual model that predicts contrasting richness and composition responses of bird assemblages following disturbance along a gradient of increasing vegetation structure. This model brings a different perspective to current theories of disturbance, and has implications for understanding and managing the effects of fire on biodiversity in heterogeneous landscapes.!://WOS:000333533800012Times Cited: 3 0921-2973WOS:00033353380001210.1007/s10980-014-0017-z ?Bas, Pedroli Bert, Harms2002 Introduction1-3Landscape Ecology170*http://dx.doi.org/10.1023/A:1015255124407 10.1023/A:1015255124407 References Amoros C., Rostan J.C., Pautou G. and Bravard J.P. 1987. The reversible process concept applied to the environmental management of large river systems. Environ. Manag. 11: 607-617. Bayley P.B. 1991. The flood pulse advantage and the restoration of river-floodplain systems. Regul. Riv. Res. Manag. 6: 75-86. Billen G., Décamps, H. Garnier J., Boët P., Meybeck M. and Servais P. 1995. Atlantic river systems of Europe. In: C.E. Cushing, K.W. Cummins and G.A. Minshall (eds), River and Stream Ecosystems. Ecosystems of the world 22, Elsevier, Amsterdam, The Netherlands, pp. 389-418. De Waal L.C., Large A.R.G., Gippel C.J. and Wade P.M. 1995. River and floodplain rehabilitation in Western Europe: opportunities and constraints. Arch. Hydrobiol. Suppl. 101, 3/4: 679-693. Dister E., Gomer D., Obrdlik P., Petermann P. and Schneider E. 1990. Water management and ecological perspectives of the Upper Rhine's floodplains. Regul. Riv. Res. Manag. 5: 1-15. Hansen H.O. 1996. River restoration-Danish experience and examples. Ministry of Environment and Energy, National Environmental Research Institute, Silkeborg, Denmark. IRC 1987. Rhine Action Programm. Technisch-wissenschaftliches Sekretariat, International Rhine Commission, Koblenz, Germany. Large A.R.G. and Petts G.E. 1994. Rehabilitation of river margins. In: P. Calow and G.E. Petts (eds), The Rivers Handbook. Hydrological and Ecological Principles. Volume 2, Blackwell, Oxford, UK, pp. 401-418. Middelkoop H. 1997. Embanked floodplains in the Netherlands. Thesis, University Utrecht. Netherlands Geographical Studies 124. Milner A.M. 1994. System recovery. In: P. Calow and G.E. Petts (eds), 1994. The Rivers Handbook. Hydrological and Ecological principles. Vol. 2, Blackwell, Oxford, UK, pp. 76-97. Postma R., Kerkhofs M.J.J., Pedroli G.B.M. and Rademakers J.G.M. 1995. Een stroom natuur, Natuurstreefbeelden voor Rijn en Maas. Ministerie van Verkeer en Water-staat, project Watersysteemverkenningen, RIZA nota 95.060, ISBN 9036945267, Arnhem, The Netherlands (in Dutch with summary in English). Ramade F. 1995. Qualitative and quantitative criteria defining a 'healthy' ecosystem. In: D.J. Rapport, C.L. Gaudet and P. Calow (eds), Evaluating and monitoring the health of large scale ecosystems. NATO Advanced Science Institutes Series 1: Global Environmental Change 28. Springer Verlag, Berlin, Germany. Theiling C.H. 1995. Habitat rehabilitation on upper Mississippi river. Reg. Riv. Res. Manag. 11: 227-238. Van Dijk G.M., Marteijn E.C.L., Schulte-Wülwer-Leidig A. 1995. Ecological Rehabilitation of the River Rhine: Plans, progress and perspectives. Reg. Riv. Res. Manag. 11: 377-388. Van der Kraats J.A. (ed.), 1994. Rehabilitation of the River Rhine. Water Science & Technology, Special Issue: Proceedings of the International Conference on Rehabilitation of the River Rhine 15-19 March 1993, Arnhem, The Netherlands. Bas Pedroli1 and Bert Harms1 (1) Alterra Green World Research, Wageningen University and Research Centre, PO Box 47, 6700 AA Wageningen, The Netherlands $?=Bas, Pedroli Geert de, Blust Kris van, Looy Sabine van, Rooij20023Setting targets in strategies for river restoration5-18Landscape Ecology170VHabitat network - Meuse - Population persistence - River restoration - Setting targetsSince about 90% of the natural floodplain area of rivers in Europe has been reclaimed and now lacks river dynamics, nature rehabilitation along rivers is of crucial importance for the restoration of their natural function. Flood protection, self-purification of surface water, groundwater recharge, species protection and migration are all involved in this process. It is now generally recognised that rivers form natural arteries in Europe but are also of economic importance and are recognisable cultural landscape. Many examples are already available of successful small river restoration projects. Several species thought to be extinct have now reappeared and characteristic species have also expanded in recent years. This paper concentrates on the concept of setting targets for river restoration as exemplified by the Meuse River. A modelling exercise shows the restraints of current habitat configuration and the potential for habitat restoration along the river. A policy analysis, using a strategic approach, illustrates the influence of the decision making process on the targets for natural river development. River dynamics play a key factor in determining the potential for persistent populations of target animal species along the river, with the help of an expert system (LARCH, Landscape ecological Analysis and Rules for the Configuration of Habitat). The potentials for the increase of dispersion and biodiversity and the maximisation of ecological benefits at different scales, are also considered. *http://dx.doi.org/10.1023/A:1015221425315 10.1023/A:101522142531 Bas Pedroli Email: b.pedroli@alterra.wag-ur.nl References Amoros C. and Petts G.E. (eds) 1993. Hydrosystèmes Fluviaux. Macon, Paris. Anonymous 1994. Natur 2000 in Nordrhein-Westfalen. Leitlinien und Leitbilder für Natur und Landschaft. Ministerium für Umwelt, Raumordnung und Landwirtschaft des Landes Nordrhein-Westfalen, Dortmund, Germany. Arbeitsgemeinschaft Renaturierung Hochrhein 1996. Hochrhein Fachtagung 'Lebendiger Hochrhein'. Beiträge zur Umsetzung des Aktionsprogramms 'Rhein 2000'. Arbeitsgemeinschaft Renaturierung des Hochrheins, Basel, Switzerland. Bayley P.B. 1991. The flood pulse advantage and the restoration of river-floodplain systems. Regul. Rivers Res. Man. 6: 75-86. Billen G., Décamps H., Garnier J., Boët P., Meybeck M., and Servais P. 1995. Atlantic river systems of Europe. In: C.E. Cushing, K.W. Cummins and G.W. Minshall (eds), River and Stream Ecosystems. Ecosystems of the world 22, Elsevier, Amsterdam, The Netherlands, pp. 389-418. Boon P.J. 1992. Essential Elements in the Case for River Conservation. In: P.J. Boon, P. Calow and G.E. Petts (eds), River Conservation and Management, Wiley, Chichester, UK, pp. 11-33. Cals M.J.R., Postma R., Buijse A.D., and Marteijn E.C.L. 1998. Habitat restoration along the River Rhine in The Netherlands: Putting ideas into practice. Aquat. Conserv. Mar. Freshw. Ecosyst. 8: 61-70. Chardon J.P., Foppen R.P.B., and Geilen N. 2000. LARCH-RIVER, a method to assess the functioning of rivers as ecological networks. Europ. Water Manag. 3(6): 35-43. Dahm C.N., Cummins K.W., Valett H.M., and Coleman R.L. 1995. An ecosystem View of the Restoration of the Kissimmee River. Restor. Ecol. 3: 225-238. De Blust G., Froment A., Kuijken E., Nef L., and Verheyen R. 1985. 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Smits, P.H. Nienhuis and R.S.E.W. Leuven (eds), New Approaches to River Management, Backhuys Publishers, Leiden, The Netherlands, pp. 15-32. Junk W.J., Bayley P.B. and Sparks, R.E. 1989. The flood-pulse concept in river-floodplain systems. Spec. Publ. Can. J. Fish. Aquat. Sci. 106: 110-127. Kern K. 1992. Rehabilitation of Streams in South-west Germany. In: P.J. Boon, P. Calow and G.E. Petts (eds), River Conservation and Management, Wiley, Chichester, UK, pp. 321-335. Lenders H.J.R., Aarts B.G.W., Strijbosch H., and Van der Velde G. 1998. The role of reference and target images in ecological recovery of river systems: Lines of thought in The Netherlands. In: P.H. Nienhuis, R.S.E.W. Leuven and A.M.J. Ragas (eds), New Concepts for Sustainable Management of River Basins, Backhuys Publishers, Leiden, The Netherlands, pp. 35-52. Lorenz C.M., Van Dijk G.M., Van Hattum A.G.M., and W.P. Cofino 1997. Concepts in river ecology: Implications for indicator development. Regul. Rivers Res. Man. 13: 501-516. Pedroli B. 1999. The Nature of Lowland Rivers: A Search for River Identity. In: J.A. Wiens and M.R. Moss (eds), Issues in Landscape Ecology, International Association for Landscape Ecology/University Guelph. Guelph, Canada, pp. 103-111. Pedroli G.B.M. and Postma R. 1998: Nature rehabilitation in European river ecosystems. Three cases. In: P.H. Nienhuis, R.S.E.W. Leuven and A.M.J. Rages (eds), New Concepts for Sustainable Management of River Basins, Backhuys Publishers, Leiden, The Netherlands, pp. 67-84. Pedroli B., Postma R., Rademakers J., and Kerkhofs S. 1996. Welke natuur hoort er bij de rivier? Naar een natuurstreefbeeld afgeleid van karakteristieke fenomenen van het rivierlandschap. Landschap 13: 97-113. Petts G. 1990. Water, engineering and landscape: development, protection and restoration. In: D. Cosgrove and G. Petts (eds), Water, Engineering and Landscape. 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Freshwater Biol. 16: 127-139. Vanacker S., Van Looy K., and De Blust G. 1998. Typologie en habitatmodellering van de oevers van de Grensmaas. Rapport Instituut voor Natuurbehoud 98.4, Brussel, Belgium. Van der Kraats J.A. (ed.) 1994. Rehabilitation of the River Rhine. Water Science & Technology, Special Issue: Proceedings of the International Conference on Rehabilitation of the River Rhine 15-19 March 1993, Arnhem, The Netherlands. ] Van de Ven G.P. (ed.) 1993. Man-made Lowlands. History of water management and land reclamation in the Netherlands. Matrijs, Utrecht. Van Looy K. and De Blust G. 1995. De Maas natuurlijk?! Aanzet tot een grootschalig natuurontwikkelingsproject in de Grensmaasvallei. Wetenschappelijke Mededelingen van het Instituut voor Natuurbehoud 1995 (2), Brussels, Belgium. Van Looy K. and Kurstjens G. 1997. Kerkeweerd: doorkijk naar de natuurontwikkeling langs de Grensmaas. Natuurhistorisch Maandblad 86: 155-159. Vannote R.L., Minshall G.W., Cummins K.W., Sedell J.R., and Cushing C.E. 1980. The River Continuum Concept. Can. J. Fish. Aquat. Sci. 37: 130-137. Verboom J., Foppen R., Chardon P., Opdam P., and Luttikhuizen P. 2001. Introducing the key patch approach for habitat networks with persistent populations: An example for marshland birds. Biol. Conserv. 100: 89-101. Vos C.C., Verboom J., Opdam P.F.M., and Ter Braak C.J.F. 2001. Toward ecologically scaled landscape indices. Am. Naturalist 157: 24-41. Ward J.V. 1989. The four-dimensional nature of lotic ecosystems. J. North Am. Benthol. Soc. 8: 2-8. Bas Pedroli1 , Geert de Blust2, Kris van Looy2 and Sabine van Rooij1 (1) Landscape Ecology Deptartment, Alterra Green World Research, Wageningen, The Netherlands (2) Institute for Nature Conservation of the Flemish Community, Brussels, Belgium  %<7ZBascompte, J. Vila, C.1997$Fractals and search paths in mammals213-221Landscape Ecology124fractal dimension; wolves; tracking; patterns of movement CORRELATED RANDOM-WALK; CANIS-LUPUS; ECOLOGY; GROWTH; MOVEMENTS; DIMENSION; PATTERNSArticleAugDThe fractal index by Katz and George (1985) for the characterization of planar curves is applied to wolf search paths recorded by radio-telemetry. All the sets of paths studied show spatial patterns whose complexity is between a straight line and a true random walk. Females' fractal dimensions show significant changes throughout the year, depending on the state of their life cycle (normal, breeding and wandering). There are also differences between males and females, but not between adults and non-adults. The results are discussed with regard to wolf food-search strategies.://A1997XV63300002 2ISI Document Delivery No.: XV633 Times Cited: 23 Cited Reference Count: 33 Cited References: BASCOMPTE J, 1995, TRENDS ECOL EVOL, V10, P361 BATSCHELET E, 1981, CIRCULAR STATISTICS BOVET P, 1988, J THEOR BIOL, V131, P419 BRADBURY RH, 1984, MAR ECOL-PROG SER, V14, P295 BURLANDO B, 1990, J THEOR BIOL, V146, P99 BURLANDO B, 1993, J THEOR BIOL, V163, P161 CODY ML, 1971, THEOR POPULATION BIO, V2, P142 CUESTA L, 1991, MAMMALIA, V55, P239 FUJIKAWA H, 1989, J PHYS SOC JPN, V58, P3875 GAUTESTAD AO, OIKOS, V69, P154 GOLDBERGER AL, 1985, BIOPHYS J, V48, P525 JOSLIN PWB, 1967, AM ZOOL, V7, P279 KAREIVA PM, 1983, OECOLOGIA, V56, P234 KATZ MJ, 1985, B MATH BIOL, V47, P273 KRUMMEL JR, 1987, OIKOS, V48, P321 LEWIS MA, 1993, NATURE, V366, P738 LOEHLE C, 1990, LANDSCAPE ECOL, V5, P39 MACH J, 1994, EUROPHYS LETT, V25, P271 MANDELBROT BB, 1977, FRACTALS FORM CHANCE MANDELBROT BB, 1983, FRACTAL GEOMETRY NAT MANDELBROT BB, 1984, J STAT PHYS, V34, P895 MATSUSHITA M, 1990, PHYSICA A, V168, P498 MECH LD, 1983, HDB ANIMAL RADIO TRA PYKE GH, 1978, THEOR POPUL BIOL, V13, P72 PYKE GH, 1981, ANIM BEHAV, V29, P882 PYKE GH, 1983, ECOLOGY ANIMAL MOVEM SALVADOR A, 1987, MAMMALIA, V51, P45 SHLESINGER MF, 1991, PHYS REV LETT, V67, P2106 SUGIHARA G, 1990, TRENDS ECOL EVOL, V5, P79 VANBALLENBERGHE V, 1983, J MAMMAL, V64, P168 VILA C, 1993, THESIS U BARCELONA WHITE GC, 1990, ANAL WILDLIFE RADIO WIENS JA, 1989, LANDSCAPE ECOLOGY, V3, P87 0921-2973 Landsc. Ecol.ISI:A1997XV63300002/UNIV BARCELONA,DEPT ECOL,BARCELONA 08028,SPAIN.EnglishP<7tBaskent, E. Z.1999_Controlling spatial structure of forested landscapes: a case study towards landscape management83-97Landscape Ecology141landscape management spatial structure landscape indicators landscape dynamics forest management decision making landscape fragmentation simulation modeling OLD-GROWTH PATTERNArticleFebThis paper presents an overview of the landscape management design process and focuses on changes in forest landscape dynamics as a result of different harvesting patterns and initial landscape structure. A case study involved two different forest landscapes, one quite fragmented and the other little fragmented, with both covering the same total area and having similar forest age class distributions. The effects of four different harvesting patterns (:scatter, negative edge distribution, edge progressive and nuclei progressive) and two different initial forest landscape structures on landscape fragmentation were explored using a GIS-based landscape management model (LANDMAN). The model suggested that future landscape patterns vary greatly according to initial landscape structure as well as to the four harvesting patterns. The scatter harvesting pattern created fragmented landscapes, while the nuclei progressive pattern significantly reduced fragmentation, regardless of initial spatial structure. Likewise, the negative edge distribution and edge progressive harvesting patterns tended;also to reduce fragmentation. The model indicated that for a given harvesting pattern, fragmentation was generally reduced in the initially fragmented forest, whereas the clustered forest became fragmented initially, but later recovered. In conclusion, the case study demonstrated that geographically prescribed harvesting patterns, in combination with indicators of forest performance and landscape fragmentation, provide an opportunity to design management fr the creation of alternative forest landscapes of significantly different spatial structure. The prerequisites for on-the-ground forest landscape management are a quantitative description of the forest landscape, a computer model, geographically-prescribed harvest interventions, an understanding of spatial forest dynamics, and a GIS-based management design process.://000079005100007 vISI Document Delivery No.: 173XM Times Cited: 9 Cited Reference Count: 40 Cited References: BAKER WL, 1992, LANDSCAPE ECOL, V7, P291 BASKENT EZ, 1991, FOREST CHRON, V67, P610 BASKENT EZ, 1994, UNPUB DATA FILE DESI BASKENT EZ, 1995, CAN J FOREST RES, V25, P1830 BASKERVILLE GL, 1991, FOREST CHRON, V67, P117 BURGESS RL, 1981, FOREST ISLAND DYNAMI CHEN JQ, 1992, ECOL APPL, V2, P387 CHOU YH, 1990, PHOTOGRAMM ENG REM S, V56, P1507 CLARK PJ, 1954, ECOLOGY, V35, P445 CLIFF AD, 1973, SPATIAL AUTOCORRELAT COSTANZA R, 1989, ECOL ECON, V1, P1 DEJONG P, 1984, GEOGR ANAL, V16, P17 FOREST B, 1995, ENVIRON PLANN D, V13, P133 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 FRANKLIN JF, 1993, ECOL APPL, V3, P202 GILLIS AM, 1990, BIOSCIENCE, V40, P558 HALL TH, 1978, TR78 NB DEP NAT RES HARRIS LD, 1984, FRAGMENTED FOREST IS HILDITCH J, 1968, MACH INTELL, V3, P325 HUNTER ML, 1990, WILDLIFE FORESTS FOR LAURANCE WF, 1991, BIOL CONSERV, V55, P77 LI H, 1993, LANDSCAPE ECOL, V8, P63 MCGARIGAL K, 1994, UNPUB FRAGSTATS SPAT METHVEN IR, 1992, CPPA ANN M WOODL SEC, E55 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 MOORE TGE, 1991, PIX98 PNFI FOR CAN MORAN PAP, 1948, J ROY STAT SOC B MET, V37, P243 NOSS FR, 1989, CONSERV BIOL, V4, P355 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 RISSER PG, 1984, SPECIAL PUBLICATION, V2 SALWASSER H, 1990, J FOREST, V88, P32 SEYMOUR RR, 1992, MISCELLANEOUS PUBLIC, V716 SIMBERLOFF D, 1993, P SUST EC SYST IMPL, P85 SPIES TA, 1994, ECOL APPL, V4, P555 SWANSON FJ, 1992, ECOL APPL, V2, P262 TEMPLE AS, 1985, WILDLIFE 2000 MODELL, P301 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 WALLIN DO, 1994, ECOL APPL, V4, P569 WILCOVE DS, 1986, CONSERVATION BIOL SC, P237 0921-2973 Landsc. Ecol.ISI:000079005100007Karadeniz Tech Univ, Orman Fak, TR-61080 Trabzon, Turkey. Baskent, EZ, Karadeniz Tech Univ, Orman Fak, TR-61080 Trabzon, Turkey.English<7 Bastian, O.20011Landscape ecology - towards a unified discipline?757-766Landscape Ecology168complementarity geographical and biological roots holistic perspective landscape evaluation landscape visions transdisciplinarityArticleContemporary landscape ecology is not unified at all. There are historical, geographical and biological reasons for the lack of unification, as well as differences between science and application. The search for a unified theory of landscape ecology should consider previous concepts such as 'landscape diagnosis' and 'landscape functions' which were elaborated in Central Europe. Because of the various aspects in a landscape (components, processes, relations), landscape ecology should be regarded as a multidisciplinary, better a transdisciplinary, science where different views and approaches are involved in a holistic manner. The principle of complementarity is helpful to understand and describe the landscape. As a crucial step, the transformation of natural science categories to categories of the human society is brought out. This is realized by land(scape) evaluation and by the elaboration of goals (visions) of landscape development.://000175490900007  ISI Document Delivery No.: 550EP Times Cited: 14 Cited Reference Count: 60 Cited References: AHERN JF, 1999, 5 IALE WORLD C SNOWM ANTROP M, 1999, 5 IALE WORLD C SNOWM BASTIAN O, 1998, EKOL BRATISLAVA, V17, P49 BASTIAN O, 1998, EKOLOGIA BRATISLAV S, V17, P19 BASTIAN O, 1998, LANDSCAPE URBAN PLAN, V41, P171 BASTIAN O, 1999, ANAL OKOLOGISCHE BEW BAUME O, 1994, PETERMANNS GEOGRAPH, V138, P235 BUCHHEIM W, 1983, ABHANDL SACHS AKA MN, V55 CERVANTES JF, 1999, 5 IALE WORLD C SNOWM DRDOS J, 1996, EKOL BRATISLAVA, V15, P369 FAIRBANKS DHK, 1999, 5 IALE WORLD C SNOWM FARINA A, 1998, PRINCIPLES METHODS L FINKE L, 1994, LANDSCHAFTSOKOLOGIE FORMAN RTT, 1981, P INT C NETH SOC LAN, P35 FORMAN RTT, 1986, LANDSCAPE ECOLOGY HAASE G, 1978, GEOGRAPH MITT, V112, P113 HAASE G, 1990, EKOLOGIA BRATISLAVA, V9, P11 HABER W, 1979, VERH GES OKOL, V7, P19 HAINESYOUNG R, 1999, ISSUES LANDSCAPE ECO, P33 HARD G, 1970, C GEOGR 11 BONN GERM JAEGER J, 1998, GAIA, V7, P10 JONGMAN RGH, 1999, ISSUES LANGSCAPE ECO, P112 KING AW, 1999, ISSUES LANDSCAPE ECO, P6 LEHMANN E, 1986, ABHANDL AKAD WIS MNT, V2, P15 LESER H, 1997, LANDSCHAFTSOKOLOGIE LI BL, 1999, 5 IALE WORLD C SNOWM LINGNER E, 1955, FORSCHUNGSARBEIT LAN, P211 MANNSFELD K, 1979, PETERMANNS GEOGR MIT, V123, P2 MIKLOS L, 1996, EKOL BRATISLAVA, V15, P377 MOSS M, 1999, ISSUES LANDSCAPE ECO, P138 NASSAUER JI, 1999, ISSUES LANDSCAPE ECO, P129 NAVEH Z, 1984, LANDSCAPE ECOOGY THE NAVEH Z, 1987, LANDSCAPE ECOL, V1, P75 NAVEH Z, 1995, LANDSCAPE URBAN PLAN, V32, P43 NAVEH Z, 1999, 5 IALE WORLD C SNOWM NEEF E, 1966, FORSCH FORTSCHRITTE, V40, P65 NEEF E, 1967, THEORETISCHEN GRUNDL NEEF E, 1969, GEOGR RUNDSCH, V21, P453 NEEF E, 1983, GEOL MIJNBOUW, V62, P531 NEEF E, 1984, APPL GEOGR DEV, V24, P38 NEEF E, 1985, PETERMANNS GEOGR MIT, V129, P141 OTAHEL J, 1999, ISSUES LANDSCAPE ECO, P134 PIETRZAK M, 1998, SYNTEZY KRAJOBRAZOWE RICHLING A, 1994, LANDSCAPE RES ITS AP, P15 RUZICKA M, 1982, EKOLOGIA, V1, P297 SCHMITHUSEN J, 1942, Z GES ERDKUNDE, P113 SMUTS J, 1926, HOLISM EVOLUTION SOCWA WB, 1974, GEOGRAPH MITT, V118, P161 SOLON J, 1999, ISSUES LANDSCAPE ECO, P22 SUKACHEV V, 1964, FUNDAMENTALS FOREST SWOUDENSVOBODOV.H, 1991, P EUR SEM PRACT LAND, V4, P1 TRESS B, 2000, PLEN LECT IALE DEUTS, P14 TROLL C, 1939, Z GESELLSCHAFT ERDKU, P241 TROLL C, 1950, STUDIUM GEN, V3 TROLL C, 1968, INT S VER VEG STOLZ, P1 WIDACKI W, 1994, LANDSCAPE RES ITS AP, P109 WIENS JA, 1999, ISSUES LANDSCAPE ECO WIENS JA, 1999, ISSUES LANDSCAPE ECO, P148 WIENS JA, 1999, PERSPECTIVES ECOLOGY, P13 ZONNEVELD IS, 1995, LAND ECOLOGY 0921-2973 Landsc. Ecol.ISI:000175490900007~Saxon Acad Sci, D-01097 Dresden, Germany. Bastian, O, Saxon Acad Sci, Neustadter Markt 19 Blockhaus, D-01097 Dresden, Germany.English*<7Bastian, O. Bernhardt, A.1993OAnthropogenic landscape changes in central Europe and the role of bioindication139-151Landscape Ecology82PBIOINDICATION; BIOTIC DIVERSITY; LANDSCAPE PROGNOSIS; STAGES OF LANDSCAPE CHANGEArticleJunAnthropogenic landscape changes in Central Europe occurred in several stages. Characteristic features include an acceleration in the sequence of changes, a continual increase in the scope and complexity of ecologic problems, growing destabilization of the natural household and a rising proportion of irreversible changes. Various bioindication techniques are excellently suited for detecting and evaluating landscape changes, as reflected in a large number of case studies. Of these, a number are classified by the authors according to the following criteria: landscape features/components, structure of the test area, and time framework for the studies. Thorough changes must be brought about in man's relation with nature to remedy the aggrevated environmental situation, with these priorities: making human thinking and action compatible with the environment, transforming material production along ecological lines, and applying ecological principles to landscape management, for example in the form of landscape planning.://A1993LM22200006 HISI Document Delivery No.: LM222 Times Cited: 9 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1993LM22200006pBASTIAN, O, LEIPZIG AG NATURHAUSHALT GEBIETSCHARAKTER,SACHS AKAD WISSENSCH,AUGUSTUSSTR 2,W-8010 DRESDEN,GERMANY.English|7 Bastian, O. Bernhardt, A.1993OAnthropogenic Landscape Changes in Central-Europe and the Role of Bioindication139-151Landscape Ecology82Mbioindication biotic diversity landscape prognosis stages of landscape changeJunAnthropogenic landscape changes in Central Europe occurred in several stages. Characteristic features include an acceleration in the sequence of changes, a continual increase in the scope and complexity of ecologic problems, growing destabilization of the natural household and a rising proportion of irreversible changes. Various bioindication techniques are excellently suited for detecting and evaluating landscape changes, as reflected in a large number of case studies. Of these, a number are classified by the authors according to the following criteria: landscape features/components, structure of the test area, and time framework for the studies. Thorough changes must be brought about in man's relation with nature to remedy the aggrevated environmental situation, with these priorities: making human thinking and action compatible with the environment, transforming material production along ecological lines, and applying ecological principles to landscape management, for example in the form of landscape planning.://A1993LM22200006-Lm222 Times Cited:15 Cited References Count:0 0921-2973ISI:A1993LM22200006nBastian, O Leipzig Ag Naturhaushalt Gebietscharakter,Sachs Akad Wissensch,Augustusstr 2,W-8010 Dresden,GermanyEnglish1|?MBastian, Olaf Grunewald, Karsten Syrbe, Ralf-Uwe Walz, Ulrich Wende, Wolfgang2014;Landscape services: the concept and its practical relevance 1463-1479Landscape Ecology299NovRecently, in addition to the popular concept of "ecosystem services" (ES), the term "landscape services" (LS) has come into use. We are examining the question of whether a stronger focus on LS would be useful, particularly with regard to case studies carried out in Germany. Important reasons for introducing the term LS include the prominent role of spatial aspects, the reference to landscape elements and the landscape character, and the relevance of LS for landscape planning. We found no strong arguments for replacing the concept of ES by LS; however, we do prefer a situation-related use of both concepts. We propose the following definition: Landscape services are the contributions of landscapes and landscape elements to human well-being.!://WOS:000343648700001Times Cited: 1 0921-2973WOS:00034364870000110.1007/s10980-014-0064-5<7w"Bastian, O. Kronert, R. Lipsky, Z.2006[Landscape diagnosis on different space and time scales - a challenge for landscape planning359-374Landscape Ecology213evaluation; landscape assessment; landscape character; landscape functions; rare and endangered landscapes; spatial reference units ECOLOGYArticleApr4Landscape diagnosis provides a bridge between scientific knowledge and socio-economic issues that is needed to meet the demands of sophisticated landscape planning and management. The diagnostic assessment of landscape functions (capacities, goods and services supported by the landscape) at different spatio-temporal scales is a valuable tool that can solve the transformation problem. A variety of landscape classification systems - including biophysical and landscape units - can be applied as a spatial reference system. Examples are described from the multitude of approaches to assess landscape functions that can be employed in landscape diagnosis. The theoretical and methodological aspects of the approach are illustrated using examples both from Germany and the Czech Republic. The examples focus on landscape functions such as groundwater recharge, regulation of water balance, and resistance to wind erosion. In addition, the rarity of and threats to landscape types, landscape aesthetic values, and the landscape character and landscape persistence are discussed.://000236968500005 ISI Document Delivery No.: 034ZD Times Cited: 0 Cited Reference Count: 57 Cited References: *FAO, 1976, FAO SOILS B, V32 *FAO, 1993, FAO DEV SER, V1 AUGENSTEIN I, 2002, THESIS U ROSTOCK GER, V3 BACHFISCHER R, 1980, HDB PLANUNG GESTALTU, V3, P524 BASTIAN O, 1991, THESIS M LUTHER U HA BASTIAN O, 1998, EKOLOGIA BRATISLAV S, V17, P19 BASTIAN O, 1999, MAB SERIES UNESCO, V24, P43 BASTIAN O, 1999, NATURSCHUTZ LANDSCHA, V31, P293 BASTIAN O, 2000, LANDSCAPE URBAN PLAN, V50, P145 BASTIAN O, 2001, LANDSCAPE ECOL, V16, P757 BASTIAN O, 2002, DEV PERSPECTIVES LAN BASTIAN O, 2004, MULTIFUNCTIONAL LAND, V1, P75 BUKACEK R, 1998, LANDSCAPE CHARACTER, P32 CULEK M, 1998, OCHRANA PRIRODY, V53, P5 DEGROOT RS, 1992, FUNCTIONS NATURE DOLLINGER F, 1988, SALZBURGER I RAUMFOR, V3, P45 DOMS M, 1995, LANDSCHAP, V95, P39 DURWEN KJ, 1995, NURTINGER HOCHSCHULS, V13, P45 FORMAN RTT, 1986, LANDSCAPE ECOLOGY GLUGLA G, 1997, DOKUMENTATION ANWEND HAASE D, 2002, DEV PERSPECTIVES LAN, P113 HAASE G, 1978, PETERMANNS GEOGRAPHI, V112, P113 HAASE G, 1979, PETERMANNS GEOGRAPHI, V123, P7 HAASE G, 1990, EKOLOGIA BRATISLAVA, V9, P11 HAASE G, 1991, BEITRAGE GEOGRAPHIE, V34, P26 HAASE G, 2002, FORSCHUNGEN DTSCH LA, V250 LESER H, 1997, LANDSCHAFTSOKOLOGIE LINGNER E, 1955, FORSCHUNGSARBEIT LAN, P211 LIPSKY Z, 1995, LANDSCAPE URBAN PLAN, V31, P39 LOFFLER J, 2002, DEV PERSPECTIVES LAN, P49 LOW J, 1997, METHODS LANDSCAPE CH MANN S, 1997, PERSONAL TECHNOLOGIE, V1, P21 MANNSFELD K, 1979, PETERMANNS GEOGR MIT, V123, P2 MARKS R, 1992, FORSCHUNGEN DTSCH LA, P229 MEYER BC, 2000, ADV ECOL SCI, V5, P119 MEYNEN E, 1953, HDB NATURRAUMLICHEN MICHAL I, 1997, OCHRANA PRIRODY, V52, P35 MICHAL I, 1997, OCHRANA PRIRODY, V52, P4 MICHAL I, 1997, OCHRANA PRIRODY, V52, P67 MICHAL I, 1997, OCHRANA PRIRODY, V52, P99 MIMRA M, 1996, OCHRANA PRIRODY, V51, P268 MJANNSFELD K, 1985, SITZUNGSBERICHTE MN, V117, P57 NAVEH Z, 1995, INT J ECOL ENV SCI, V21, P1 NEEF E, 1966, FORSCH FORTSCHRITTE, V40, P65 NEEF E, 1969, GEOGR RUNDSCH, V21, P453 NIEMANN E, 1977, ARCH NATURSCHUTZ LAN, V17, P119 PAFFEN KH, 1953, FORSCHUNGEN DTSCH LA, V68 PEDROLI B, 2000, LANDSCAPE OUR HOME E PETRY D, 2001, LANDSCAPE BALANCE LA, P251 PETRY D, 2001, THESIS U HALLE S PREOBRAZENSKIJ VS, 1980, INVESTIGATION LANDSC RODER M, 1999, ERDE, V130, P297 SCHLUTER H, 1992, NATURSCHUTZ LANDSCHA, V24, P173 STEINHARDT U, 1999, REGIONALISIERUNG LAN VANDERMAAREL E, 1978, GLOBAL ECOLOGICAL MO, V9 VOREL I, 1997, OCHRANA PRIRODY, V52, P11 WASCHER DM, 2005, EUROPEAN LANDSCAPE C 0921-2973 Landsc. Ecol.ISI:000236968500005-Saxon Acad Sci, D-01097 Dresden, Germany. UFZ, Environm Res Ctr, Dept Appl Landscape Ecol, Leipzig, Germany. Charles Univ, Fac Sci, Dept Phys Geog & Geoecol, Prague, Czech Republic. Bastian, O, Saxon Acad Sci, Neustadter Markt 19,Blockhaus, D-01097 Dresden, Germany. Olaf.Bastian@mailbox.tu-dresden.deEnglish<7CBastin, L. Thomas, C. D.1999?The distribution of plant species in urban vegetation fragments493-507Landscape Ecology145area colonisation conservation extinction isolation metapopulation METAPOPULATION DYNAMICS ISLAND SIZE POPULATION CONSERVATION PATCH COMPETITION LANDSCAPES EXTINCTION SELECTION DIVERSITYArticleOct(1) The presence and absence of 22 plant species of various growth forms and habitat associations were analysed in 423 habitat fragments totalling 10.4 km(2) in a 268 km(2) urban and suburban region, in Birmingham, UK. (2) Multivariate logistic regressions were used to assess the effects of patch geometry and quality on the species distributions. Measures of geometry were area, shape (S-factor), distance from open countryside and various measures of isolation from other patches. Potential habitat for each species was determined quantitatively, and the distribution of each species was considered within a subset of patches containing potentially suitable habitat types. There was found to be a significant positive correlation between the density of patches available to a species and the proportion of these patches which were occupied. (3) Logistic analyses and incidence functions revealed that, for many of the species, occupancy increased with site age, area, habitat number and similarity of adjacent habitats, while increasing distance to the nearest recorded population of the same species decreased the likelihood that a species would be found in a patch. (4) Patterns of occupancy are consistent with increased extinction from small sites, and colonisation of nearby habitats, coupled with an important role for site history. We conclude that spatial dynamics at the scale of the landscape are of importance to the long-term persistence of many plant species in fragmented landscapes, and must be seriously considered in conservation planning and management. These results have direct implications for the siting and connectivity of urban habitat reserves.://000082510000007 ISI Document Delivery No.: 234XQ Times Cited: 40 Cited Reference Count: 43 Cited References: BOECKLEN WJ, 1984, BIOL CONSERV, V29, P63 BOORMAN SA, 1973, THEORETICAL POPULATI, V4, P85 BRIGHT PW, 1994, J APPL ECOL, V31, P329 DIAMOND JM, 1972, P NAT ACAD SCI, V69, P3199 DIAMOND JM, 1975, ECOLOGICAL STRUCTURE GILPIN M, 1991, METAPOPULATION DYNAM, P3 GRUBB PJ, 1982, PLANT COMMUNITY WORK, P79 GULVE PS, 1996, METAPOPULATIONS WILD HANSKI I, 1985, ECOLOGY, V66, P335 HANSKI I, 1991, METAPOPULATION DYNAM, P17 HANSKI I, 1993, AM NAT, V142, P17 HANSKI I, 1994, BIOL CONSERV, V68, P167 HANSKI I, 1994, J ANIM ECOL, V63, P151 HANSKI I, 1994, TRENDS ECOL EVOL, V9, P131 HANSKI IA, 1997, METAPOPULATION BIOL HARRISON S, 1991, METAPOPULATION DYNAM, P57 HASTINGS A, 1989, ECOLOGY, V70, P1261 HASTINGS A, 1991, METAPOPULATION DYNAM, P57 HELLIWELL DR, 1975, BIOL CONSERV, V7, P61 HOPKINS PJ, 1984, J APPL ECOL, V21, P935 JARVINEN O, 1982, OIKOS, V38, P301 KINDLMANN P, 1983, OECOLOGIA, V59, P141 KOHN DD, 1994, J ECOL, V82, P367 LEVINS R, 1969, B ENTOMOL SOC AM, V15, P237 LEVINS R, 1970, LECT MATH LIFE SCI, V2, P77 MARTIN JL, 1989, J BIOGEOGR, V16, P159 MCCOLLIN D, 1993, GLOBAL ECOL BIOGEOGR, V3, P48 MCEACHERN AK, 1994, RESTORATION ENDANGER, P194 OUBORG NJ, 1993, OIKOS, V66, P298 PETERKEN GF, 1974, BIOL CONSERV, V6, P239 PETERKEN GF, 1981, J ECOL, V69, P781 POLLARD E, 1973, HEDGES PULLIAM HR, 1988, AM NAT, V132, P652 REES M, 1996, AM NAT, V147, P1 SLATKIN M, 1974, ECOLOGY, V55, P128 SOULE ME, 1992, OIKOS, V63, P39 TAYLOR B, 1991, METAPOPULATION DYNAM, P177 THOMAS CD, 1992, OECOLOGIA, V92, P563 THOMAS CD, 1994, CONSERV BIOL, V8, P373 THOMAS CD, 1994, INDIVIDUALS POPULATI, P319 WATKINSON AR, 1989, J ECOL, V77, P162 WATKINSON AR, 1995, J ANIM ECOL, V64, P126 WEBB NR, 1984, J APPL ECOL, V21, P921 0921-2973 Landsc. Ecol.ISI:000082510000007Univ Leicester, Dept Geog, FLIERS, Leicester LE1 7RH, Leics, England. Bastin, L, Univ Leicester, Dept Geog, FLIERS, Leicester LE1 7RH, Leics, England.English<7HBaudry, J. Burel, F. Aviron, S. Martin, M. Ouin, A. Pain, G. Thenail, C.2003\Temporal variability of connectivity in agricultural landscapes: do farming activities help?303-314Landscape Ecology183connectivity farming system landscape structure simulations temporal variability HEDGEROW NETWORK LANDSCAPE FRAGMENTED POPULATIONS ABAX-PARALLELEPIPEDUS FRANCE MODEL MANAGEMENT COLEOPTERA CARABIDAE DYNAMICS BRITTANYArticleAprqIn landscapes where natural habitats have been severely fragmented by intensive farming, survival of many species depends on connectivity among habitat patches. Spatio-temporal structure of agricultural landscapes depends on interactions between the physical environment and farming systems, within a socio-economic and historical background. The question is how incentives in agricultural policies may influence connectivity? May they be used to manage the land for biodiversity conservation? We used simulations based on property field maps to compare connectivity on the same landscape during seven years of crop succession for two dairy farming systems, one being representative of conventional systems of western France, the second one representative of systems undergoing intensification of production. Connectivity is a measure of landscape structure and species characteristics based on individual area requirements and dispersal distance. Models used are based on weighed distances, considering differential viscosity for different land uses. The results show that, for a given farming system, physical and field patterns constraints are such that landscape connectivity remains the same over years, while it is significantly different between the two farming systems. This is consistent with the recent input of policies to promote environmentally friendly farming systems, and confirms that policies must encounter the landscape level. The analysis also demonstrates that the localisation of forest patches, resulting from long term land cover changes, plays a central role in connectivity and overrides changes in agricultural land uses.://000183770600008 BISI Document Delivery No.: 694JD Times Cited: 12 Cited Reference Count: 45 Cited References: AGGER P, 1988, LANDSCAPE ECOL, V1, P227 ALES RF, 1992, LANDSCAPE ECOL, V7, P3 ALTIERI MA, 1980, ENVIRON MANAGE, V4, P467 BAKER WL, 1989, LANDSCAPE ECOL, V2, P111 BARR C, 2001, HEDGEROWS WORLD THEI BARR CJ, 2000, J ENVIRON MANAGE, V60, P23 BAUDRY J, 2000, J ENVIRON MANAGE, V60, P7 BAUDRY J, 2000, LANDSCAPE URBAN PLAN, V50, P119 BAUDRY J, 2001, PROGR PROSPECTS, P243 BUREL F, 1996, CRIT REV PLANT SCI, V15, P169 CHARRIER S, 1997, AGR ECOSYST ENVIRON, V61, P133 DELAPENA NM, 2003, AGR ECOSYST ENVIRON, V94, P59 DUBY G, 1975, HIST FRANCE RURALE, V1 DUNNING JB, 1992, OIKOS, V65, P169 FAHRIG L, 1994, CONSERV BIOL, V8, P50 FLAMM RO, 1994, LANDSCAPE ECOL, V9, P37 GILPIN M, 1991, METAPOPULATION DYNAM GREEN BH, 1989, J APPL ECOL, V26, P793 HANSKI I, 1997, METAPOPULATION BIOL, P512 KNAAPEN JP, 1992, LANDSCAPE URBAN PLAN, V23, P1 LECOEUR D, 2002, AGR ECOSYSTEMS ENV LEONARD PL, 1977, LANDSCAPE PLANNING, V4, P205 LEVINS R, 1970, EXTINCTIONS SOME MAT, P77 MARTIN M, 2001, COMPTES RENDU ACAD S, V324, P1 MEDLEY KE, 1995, LANDSCAPE ECOL, V10, P161 MEEUS JHA, 1990, MILIEU, V6, P225 MIEYNIER A, 1966, NOROIS, P595 MOILANEN A, 1998, ECOLOGY, V79, P2503 MOILANEN A, 2001, OIKOS, V95, P147 OUIN A, 2000, AGR ECOSYST ENVIRON, V78, P159 PAIN G, 2000, GEOMATIQUE, V10, P89 PAPY F, 2001, MODELISATION AGROECO, P51 PETIT S, 1998, CR ACAD SCI III-VIE, V321, P55 PITHER J, 1998, OIKOS, V83, P166 RAKCHAM O, 1986, HIST COUNTRYSIDE, P445 RICKETTS TH, 2001, AM NAT, V158, P87 SCHIPPERS P, 1996, ECOGRAPHY, V19, P97 SIMPSON JW, 1994, LANDSCAPE ECOL, V9, P261 TAYLOR PD, 1993, OIKOS, V68, P571 THENAIL C, 2002, AGR SYST, V71, P207 TISCHENDORF L, 2001, OIKOS, V95, P152 TURNER BL, 1994, CHANGES LAND USE LAN, P2 VOS CC, 2001, AM NAT, V157, P24 WIENS JA, 1993, OIKOS, V66, P369 YU KJ, 1996, LANDSCAPE URBAN PLAN, V36, P1 0921-2973 Landsc. Ecol.ISI:000183770600008INRA, SAD Armor, F-35042 Rennes, France. Univ Rennes 1, CNRS, UMR 6553, Ecobio, F-35042 Rennes, France. INP, ENSAT, F-31326 Castanet Tolosan, France. Ecole Super Agr, F-49007 Angers 01, France. Baudry, J, INRA, SAD Armor, CS 84215,65 Rue Saint Brieuc, F-35042 Rennes, France.English<7;Bayne, E. M. Van Wilgenburg, S. L. Boutin, S. Hobson, K. A.2005Modeling and field-testing of Ovenbird (Seiurus aurocapillus) responses to boreal forest dissection by energy sector development at multiple spatial scales203-216Landscape Ecology202fragmentation; passive displacement; seismic line; spatial model; threshold HABITAT FRAGMENTATION; PAIRING SUCCESS; LANDSCAPE; BEHAVIOR; BIRDS; WESTERN; ROADS; SIZEArticleFebAlthough the area disturbed by linear features in forested systems is small relative to many other human disturbances, linear features create significantly more amounts of edge per unit area. In the boreal plains of Alberta, Canada, energy sector exploration has resulted in extensive dissection of the landscape through 8 m wide seismic lines. A spatially explicit model was developed to test how bird abundance might change in response to increasing seismic line density if individuals use seismic lines as territory boundaries or actively avoid these edges. Assuming birds had fixed territory shape and size, increasing seismic line density from 0 to 8 km/km(2) resulted in a 38% decline and an 82% decline in bird abundance when individuals used lines as territory boundaries or avoided edges by 50 m, respectively. We tested the assumptions of our model using the Ovenbird ( Seiurus aurocapillus). Based on radio-telemetry ( n = 12), all Ovenbirds crossed seismic lines at some point during the breeding season. However, male Ovenbirds showed a distinct use of one side of the seismic line, suggesting lines acted as territory boundaries. In 12.25 ha plots ( n = 24) spot-mapping detected no change in Ovenbird density as linear feature density increased from 0 to 8.6 km/km(2). In 4 km(2) landscapes ( n = 62) sampled using a grid of nine point-counts, we also detected no changes in Ovenbird numbers across the same range of seismic line densities. Ovenbirds declined with seismic line density at the level of the individual point-count station ( 12 ha scale), but only when a threshold seismic line density of 8.5 km/km(2) was reached. Above the threshold, Ovenbirds declined 19% for each 1 km/km(2) increase in seismic line density. While relatively few places in Alberta's boreal forest have local seismic line densities of 8.5 km/km(2), forest dissection could increasingly become an issue if current energy exploration practices continue.://000230299600007 nISI Document Delivery No.: 942RN Times Cited: 3 Cited Reference Count: 36 Cited References: *PETR COMM FDN, 2000, CAN OIL SANDS HEAV O AEBISCHER NJ, 1993, ECOLOGY, V74, P1313 BAYNE EM, 2001, AUK, V118, P380 BAYNE EM, 2001, CONDOR, V103, P343 BEISSINGER SR, 1997, BEHAV APPROACHES CON, P23 BIBBY CJ, 2000, BIRD CENSUS TECHNIQU BURNHAM KP, 1998, MODEL SELECTION INFE DEBINSKI MD, 2000, CONSERV BIOL, V2, P342 DONOVAN TM, 1997, ECOLOGY, V78, P2064 FAHRIG L, 2003, ANNU REV ECOL EVOL S, V34, P487 FORMAN RTT, 1998, ANNU REV ECOL SYST, V29, P207 HANNON SJ, IN PRESS MANAGEMENT HARDIN J, 2001, GEN LINEAR MODELS EX HINSLEY SA, 1996, OECOLOGIA, V105, P100 HOOGE PN, 1997, ANIMAL MOVEMENT EXTE HUXLEY JS, 1934, BRIT BIRDS, V27, P270 KINNAIRD MF, 2003, CONSERV BIOL, V17, P245 KIRK DA, 1996, CAN J ZOOL, V74, P1749 LAMBERT JD, 2000, AUK, V117, P687 LAURANCE WF, 2000, ORYX, V34, P39 MARRA PP, 1997, ECOLOGY, V78, P947 MAXEROLLE DF, 2001, THESIS U SASKATCHEWA NEWTON I, 1992, BIOL REV, V67, P129 ORTEGA YK, 1999, AUK, V116, P937 PIMM SL, 1995, P NATL ACAD SCI USA, V92, P9343 RAIL JF, 1997, CONDOR, V99, P976 REVEL RD, 1984, FOREST GROWTH REGENE RICH AC, 1994, CONSERV BIOL, V8, P1109 ROBBINS CS, 1989, P NATL ACAD SCI USA, V86, P7658 ROITBERG BD, 1997, OIKOS, V80, P234 SCHMIEGELOW FKA, 2002, ECOL APPL, V12, P375 SCHNEIDER RR, 2003, CONSERV ECOL, V7 SMITH TM, 1987, ECOLOGY, V68, P695 SOKHAL RR, 1981, BIOMETRY VANHORN MA, 1994, BIRDS N AM ZAR JH, 1999, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000230299600007PUniv Alberta, Dept Biol Sci, Integrated Landscape Management Grp, Edmonton, AB T6G 2E9, Canada. Canadian Wildlife Serv, Saskatoon, SK S7N 0X4, Canada. Univ Saskatchewan, Dept Biol, Saskatoon, SK S7N 0W0, Canada. Bayne, EM, Univ Alberta, Dept Biol Sci, Integrated Landscape Management Grp, Edmonton, AB T6G 2E9, Canada. bayne@ualberta.caEnglishT|?H 'Bazelet, Corinna S. Samways, Michael J.2011bRelative importance of management vs. design for implementation of large-scale ecological networks341-353Landscape Ecology263MarEcological networks (ENs) are used to mitigate landscape-scale habitat loss, and are managed and designed to conserve regional biodiversity. In our study region in southern Africa, ENs of isolated grassland remnants are specifically set aside and managed for conservation, and are complemented by corridor-like power line servitudes which are maintained by regular mowing. Using grasshoppers, a sensitive and reliable bioindicator taxon, we determine whether ENs effectively conserve biodiversity. We used cluster analysis and variation partitioning to select the best subset of environmental variables which explained the patterns of species composition. We then compared the relative importance of environmental variables grouped by the scale of their influence: local-scale variables affected by management practices vs. landscape-scale variables affected by design of ENs. Management was consistently and significantly 2-5 times more influential than design in determining grasshopper assemblages within ENs and servitudes. Servitudes had a higher proportion of bare ground, lower proportion of tall grasses and higher abundance of grasshoppers relative to ENs. Three grasshopper species were strongly associated with servitudes and exhibited traits consistent with early colonizers. As management actions are primarily responsible for vegetation succession, the use of ENs for conservation efforts should first focus on appropriate management strategies, such as fire regime and grass height management before altering the landscape structure (e. g. increasing connectivity or enlarging patches). The conservation implications of these results are that, if ENs are managed and designed for heterogeneity and to simulate multiple successional stages, they may be beneficial for biodiversity conservation.!://WOS:000288808100004Times Cited: 0 0921-2973WOS:00028880810000410.1007/s10980-010-9557-z|?! `Beasley, James C. Olson, Zachary H. Dharmarajan, Guha Eagan, Timothy S., II Rhodes, Olin E., Jr.2011TSpatio-temporal variation in the demographic attributes of a generalist mesopredator937-950Landscape Ecology267Aug5Human land-use practices have dramatically altered the composition and configuration of native habitats throughout many ecosystems. Within heterogeneous landscapes generalist predators often thrive, causing cascading effects on local biological communities, yet there are few data to suggest how attributes of fragmentation influence local population dynamics of these species. We monitored 25 raccoon (Procyon lotor) populations from 2004 to 2009 in a fragmented agricultural landscape to evaluate the influence of local and landscape habitat attributes on spatial and temporal variation in demography. Our results indicate that agricultural ecosystems support increased densities of raccoons relative to many other rural landscapes, but that spatial and temporal variation in demography exists that is driven by non-agricultural habitat attributes rather than the availability of crops. At the landscape scale, both density and population stability were positively associated with the size and contiguity of forest patches, while at the local scale density was positively correlated with plant diversity and the density of tree cavities. In addition, populations occupying forest patches with greater levels of plant diversity and stable water resources exhibited less temporal variability than populations with limited plant species complexity or water availability. The proportion of populations comprised of females was most strongly influenced by the availability of tree cavities and soft mast. Despite the abundance of mesopredators in heterogeneous landscapes, our results indicate that all patches do not contribute equally to the regional abundance and persistence of these species. Thus, a clear understanding of how landscape attributes contribute to variation in demography is critical to the optimization of management strategies.!://WOS:000292705900004Times Cited: 1 0921-2973WOS:00029270590000410.1007/s10980-011-9619-x|?jBeatty, William S. Webb, Elisabeth B. Kesler, Dylan C. Raedeke, Andrew H. Naylor, Luke W. Humburg, Dale D.2014hLandscape effects on mallard habitat selection at multiple spatial scales during the non-breeding period989-1000Landscape Ecology296Jul Previous studies that evaluated effects of landscape-scale habitat heterogeneity on migratory waterbird distributions were spatially limited and temporally restricted to one major life-history phase. However, effects of landscape-scale habitat heterogeneity on long-distance migratory waterbirds can be studied across the annual cycle using new technologies, including global positioning system satellite transmitters. We used Bayesian discrete choice models to examine the influence of local habitats and landscape composition on habitat selection by a generalist dabbling duck, the mallard (Anas platyrhynchos), in the midcontinent of North America during the non-breeding period. Using a previously published empirical movement metric, we separated the non-breeding period into three seasons, including autumn migration, winter, and spring migration. We defined spatial scales based on movement patterns such that movements > 0.25 and < 30.00 km were classified as local scale and movements > 30.00 km were classified as relocation scale. Habitat selection at the local scale was generally influenced by local and landscape-level variables across all seasons. Variables in top models at the local scale included proximities to cropland, emergent wetland, open water, and woody wetland. Similarly, variables associated with area of cropland, emergent wetland, open water, and woody wetland were also included at the local scale. At the relocation scale, mallards selected resource units based on more generalized variables, including proximity to wetlands and total wetland area. Our results emphasize the role of landscape composition in waterbird habitat selection and provide further support for local wetland landscapes to be considered functional units of waterbird conservation and management.!://WOS:000338331600006Times Cited: 1 0921-2973WOS:00033833160000610.1007/s10980-014-0035-x <78 8Beier, C. M. Signell, S. A. Luttman, A. DeGaetano, A. T.2012OHigh-resolution climate change mapping with gridded historical climate products327-342Landscape Ecology273temperature trends climate maps parameter regression independent slopes model (prism) north american regional reanalysis (narr) downscaling climate adaptation united-states temperature precipitation model interpolation variables surfaces terrain maximum trendsMar The detection of climate-driven changes in coupled human-natural systems has become a focus of climate research and adaptation efforts around the world. High-resolution gridded historical climate (GHC) products enable analysis of recent climatic changes at the local/regional scales most relevant for research and decision-making, but these fine-scale climate datasets have several caveats. We analyzed two 4 km GHC products to produce high-resolution temperature trend maps for the US Northeast from 1980 to 2009, and compared outputs between products and with an independent climate record. The two products had similar spatial climatologies for mean temperatures, agreed on temporal variability in regionally averaged trends, and agreed that warming has been greater for minimum versus maximum temperatures. Trend maps were highly heterogeneous, i.e., a patchy landscape of warming, cooling and stability that varied by month, but with local-scale anomalies persistent across months (e.g., cooling 'pockets' within warming zones). In comparing trend maps between GHC products, we found large local-scale disparities at high elevations and along coastlines; and where weather stations were sparse, a single-station disparity in input data resulted in a large zone of trend map disagreement between products. Preliminary cross-validation with an independent climate record indicated substantial and complex errors for both products. Our analysis provided novel landscape-scale insights on climate change in the US Northeast, but raised questions about scale and sources of uncertainty in high-resolution GHC products and differences among the many products available. Given rapid growth in their use, we recommend exercising caution in the analysis and interpretation of high-resolution climate maps.://000300087500002-889QE Times Cited:0 Cited References Count:35 0921-2973Landscape EcolISI:000300087500002{Beier, CM SUNY Syracuse, Dept Forest & Nat Resources Management, Coll Environm Sci & Forestry, Adirondack Ecol Ctr, 1 Forestry Dr, Syracuse, NY 13210 USA SUNY Syracuse, Dept Forest & Nat Resources Management, Coll Environm Sci & Forestry, Adirondack Ecol Ctr, 1 Forestry Dr, Syracuse, NY 13210 USA SUNY Syracuse, Dept Forest & Nat Resources Management, Coll Environm Sci & Forestry, Adirondack Ecol Ctr, Syracuse, NY 13210 USA SUNY, Coll Environm Sci & Forestry, Adirondack Ecol Ctr, Newcomb, NY USA Clarkson Univ, Dept Math & Comp Sci, Potsdam, NY USA Cornell Univ, Dept Earth & Atmospher Sci, NOAA, NE Reg Climate Ctr, Ithaca, NY USADOI 10.1007/s10980-011-9698-8EnglishV<7Belanger, L. Grenier, M.2002_Agriculture intensification and forest fragmentation in the St. Lawrence valley, Quebec, Canada495-507Landscape Ecology176human population satelite imagery HAUT-SAINT-LAURENT HABITAT FRAGMENTATION NEW-ENGLAND LANDSCAPE BIRDS DYNAMICS DEFORESTATION PERCEPTIONS ASSEMBLAGES VEGETATIONArticleOctQuantifying remaining forest cover and understanding how the fragmentation process operates with respect to the various land- use practices are important steps when working to preserve the biodiversity associated with woodlots in agricultural landscapes. We used LANDSAT satellite imagery, soil types, and boundaries of regional county municipalities (RCM) as the sampling unit of a 6 million- ha territory located in southern Quebec (Canada), to provide a picture of the forest situation in the St. Lawrence Valley. We assessed the effect of human population densities and various types of agricultural production on the fragmentation process. On average, 45% of the total land area of RCMs is forested. However, in 8 of the 59 RCMs studied 20% or less of the total area is still forest habitat. As agricultural use of land increased, the density of woodlots also increased but their average size decreased. An overall fragmentation effect seems to occur where less than 50% of the territory is forested, as it is the case for 31 of the 59 studied RCMs. Fragmentation increased along a gradient from traditional dairy agriculture to more intensive cash crop agriculture. Finally, we found that the forest discontinuity index, mean woodlot area, and woodlot density were the best indicators of the ongoing forest fragmentation process, but overall human population density is the most useful predictive variable.://000179774900001  ISI Document Delivery No.: 624RN Times Cited: 6 Cited Reference Count: 50 Cited References: *MAM, 1994, REP MUN QUEB *MRN, 1996, FICH PHYL VERS 1993 ANDREN H, 1994, OIKOS, V71, P355 BELANGER L, 1999, HABITAT STATUS LAND BERGERON Y, 1988, NATL CANCER I MONOGR, V115, P19 BOUCHARD A, 1978, NAT CAN, V105, P383 BURGESS RL, 1981, FOREST ISLAND DYNAMI BURKE DM, 1998, NAT AREA J, V18, P45 CUNNINGHAM SA, 2000, CONSERV BIOL, V14, P758 DEON RG, 2000, FOREST CHRON, V76, P475 DIAZ JA, 2000, ANIM CONSERV 3, V3, P235 DOMON G, 1986, CAN J BOT, V64, P1027 DOMON G, 1993, LANDSCAPE URBAN PLAN, V25, P53 FAHRIG L, 1997, J WILDLIFE MANAGE, V61, P603 FAUTH PT, 2000, LANDSCAPE ECOL, V15, P621 FOSTER DR, 1992, J ECOL, V80, P753 FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 FREEMARK K, 1991, TECHNICAL REPORT SER, V114 FREEMARK KE, 1986, BIOL CONSERV, V36, P115 GATES JE, 1978, ECOLOGY, V59, P871 GRANTNER MM, 1966, VEGETATION FORESTIER HARRIS LD, 1984, FRAGMENTED FOREST IS IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 JOBIN B, 1996, CAN J BOT, V74, P323 KOMONEN A, 2000, OIKOS, V90, P119 LYNCH JF, 1978, CLASSIFICATION INVEN, P461 MALINGREAU JP, 1988, AMBIO, V17, P49 MCGARIGAL K, 2000, MULTIVARIATE STAT WI MEDLEY KE, 1995, LANDSCAPE ECOL, V10, P161 MEILLEUR A, 1992, VEGETATIO, V102, P13 MERCER E, 2000, ENVIRON MONIT ASSESS, V63, P43 NUPP TE, 2000, J MAMMAL, V81, P512 PURICMLADENOVIC D, 2000, FOREST CHRON, V76, P247 ROBBINS CS, 1989, P NATL ACAD SCI USA, V86, P7658 ROBINSON SK, 1995, SCIENCE, V267, P1987 ROSENFIELD RN, 1992, NPSNRUWNRTR9208 US D SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SKOLE D, 1993, SCIENCE, V260, P1905 SOULE J, 1990, AGROECOLOGY, P165 SOULE ME, 1986, CONSERVATION BIOL SC TRZCINSKI MK, 1999, ECOL APPL, V9, P586 VALLAN D, 2000, BIOL CONSERV, V96, P31 VILLARD MA, 1999, CONSERV BIOL, V13, P774 VOGELMANN JE, 1995, CONSERV BIOL, V9, P439 WHITCOMB RF, 1981, FOREST ISLAND DYNAMI, P125 WICKHAM JD, 2000, LANDSCAPE ECOL, V15, P171 WIENS JA, 1994, IBIS, V137, P97 WILCOVE DS, 1985, ECOLOGY, V66, P1211 WILCOX BA, 1985, AM NAT, V125, P879 ZAR JH, 1974, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000179774900001Environm Canada, Environm Conservat Branch, Canadian Wildlife Serv, St Foy, PQ G1V 4H5, Canada. Belanger, L, Environm Canada, Environm Conservat Branch, Canadian Wildlife Serv, 1141 Route Eglise,POB 10100, St Foy, PQ G1V 4H5, Canada.English<7Belisle, M. Desrochers, A.2002yGap-crossing decisions by forest birds: an empirical basis for parameterizing spatially-explicit, individual-based models219-231Landscape Ecology173Hconnectivity corridor dispersal forest birds fragmentation habitat loss movement playback experiment spatially-explicit models BLACK-CAPPED CHICKADEES SPARROWHAWKS ACCIPITER-NISUS LANDSCAPE STRUCTURE POPULATION-MODELS HABITAT CONNECTIVITY HETEROGENEOUS LANDSCAPES FIELD EXPERIMENTS MIGRATORY BIRDS PASSERINE BIRDS PREY SELECTIONArticle}Spatially-explicit, individual-based models are increasingly used to evaluate the effects of habitat loss and fragmentation on habitat use and population persistence. Yet, they are criticized on the basis that they rely on little empirical data, especially regarding decision rules of moving individuals. Here we report the results of an experiment measuring the gap-crossing decisions of forest birds attracted to a recording of chickadee (Poecile atricapillus) mobbing calls, and provided with options to travel to the speaker by either crossing an open area (short cut) or taking a longer route under forest cover (detour). We performed the experiment in winter and late summer near Quebec City, Quebec, Canada. We recorded 1078 travel paths from 6 resident and 12 migratory species in 249 experimental sites. In both seasons, birds preferred to travel under forest cover rather than cross open areas, even when the forested detour conveyed a substantially longer route than the short cut in the open. Only when the detour under forest cover. This was considerably longer than the short-cut in the open, in both relative and absolute terms, were birds more likely to take short cuts, indicating that gap-crossing decisions are scale dependent. However, birds rarely ventured > 25 m from forest edges despite having the opportunity to do so. Except for Hairy Woodpeckers (Picoides villosus) which ventured further into the open, all species showed similar gap-crossing decisions. Residents remained marginally closer to forest edges in late summer as compared to in winter. Conspecific group size had no influence on gap-crossing decisions. This experiment supports the hypothesis that forest bird movements are constrained in fragmented landscapes, and provides opportunities to calibrate spatially-explicit, individual-based models addressing the influence of landscape composition and configuration on dispersal.://000178082200002 $ISI Document Delivery No.: 594ZK Times Cited: 21 Cited Reference Count: 86 Cited References: *SPSS INC, 1997, SPSS 8 0 WIND ANDERS AD, 1998, AUK, V115, P349 BAILLIE SR, 2000, J APPL ECOL S1, V37, P88 BART J, 1995, ECOL APPL, V5, P411 BEAUCHAMP G, 1997, J ANIM ECOL, V66, P671 BEIER P, 1998, CONSERV BIOL, V12, P1241 BELANGER L, 1998, SERIE RAPPORT TECHNI, V327 BELISLE M, 2001, CONSERV ECOL, V5 BELISLE M, 2001, ECOLOGY, V82, P1893 BERNSTEIN C, 1991, J ANIM ECOL, V60, P205 BROOKER L, 1999, CONSERV ECOL, V3 COHEN J, 1988, STAT POWER ANAL BEHA CONROY MJ, 1995, ECOL APPL, V5, P17 CRESSWELL W, 1995, ARDEA, V83, P381 CURIO E, 1978, Z TIERPSYCHOL, V48, P175 CURIO E, 1985, Z TIERPSYCHOL, V69, P3 DANIELSON BJ, 1992, EVOL ECOL, V6, P399 DAVIES KF, 2000, ECOLOGY, V81, P1450 DESROCHERS A, 1988, AUK, V105, P727 DESROCHERS A, 1997, CONSERV BIOL, V11, P1204 DESROCHERS A, 1999, ACT 22 C INT ORN U N, P2447 DESROCHERS A, 2000, OIKOS, V91, P376 DIFFENDORFER JE, 1998, OIKOS, V81, P417 DOLBY AS, 1999, CONDOR, V101, P408 DONOVAN TM, 1995, CONSERV BIOL, V9, P1380 DONOVAN TM, 1995, CONSERV BIOL, V9, P1396 DROLET B, 1999, CONDOR, V101, P699 DUNNING JB, 1984, MONOGRAPH W BIRD BAN, V1 DUNNING JB, 1995, ECOL APPL, V5, P3 FAHRIG L, 1994, CONSERV BIOL, V8, P50 FALL A, 2001, ECOLOGICAL MODELLING, V137, P1 GOTMARK F, 1994, AUK, V111, P251 GOTMARK F, 1996, PHILOS T ROY SOC B, V351, P1559 GRUBB TC, 1999, AUK, V116, P618 GUNN JS, 2000, J FIELD ORNITHOL, V71, P472 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 HANSKI I, 1999, METAPOPULATION ECOLO HARRIS RJ, 2001, AUK, V118, P544 HINSLEY SA, 2000, LANDSCAPE ECOL, V15, P765 HURD CR, 1996, BEHAV ECOL SOCIOBIOL, V38, P287 IMS RA, 1995, MOSAIC LANDSCAPES EC, P85 IMS RA, 1997, METAPOPULATION BIOL, P247 JONSEN I, 2000, CONSERV ECOL, V4 JONSEN ID, 2000, OIKOS, V88, P553 KEITT TH, 1997, CONSERV ECOL, V1 KLEINBAUM DG, 1988, APPL REGRESSION ANAL KOTLIAR NB, 1990, OIKOS, V59, P253 LAMBERSON RH, 1994, CONSERV BIOL, V8, P185 LETCHER BH, 1998, BIOL CONSERV, V86, P1 LIMA SL, 1990, CAN J ZOOL, V68, P619 LIMA SL, 1996, TRENDS ECOL EVOL, V11, P131 MATTHYSEN E, 1995, OIKOS, V72, P375 MCNAMARA JM, 1990, ACTA BIOTHEOR, V38, P37 MOOIJ WM, 1999, CONSERV BIOL, V13, P930 PETERS RH, 1991, CRITIQUE ECOLOGY PORNELUZI PA, 1999, CONSERV BIOL, V13, P1151 PRAVOSUDOV VV, 1997, CURR ORNITHOL, V14, P189 RAIL JF, 1997, CONDOR, V99, P976 ROBINSON SK, 1995, SCIENCE, V267, P1987 ROLAND J, 1997, NATURE, V386, P710 ROMEY WL, 1996, ECOL MODEL, V92, P65 RUCKELSHAUS M, 1997, CONSERV BIOL, V11, P1298 RUCKELSHAUS M, 1999, CONSERV BIOL, V13, P1223 RYTKONEN S, 1998, ORNIS FENNICA, V75, P77 SCHIPPERS P, 1996, ECOGRAPHY, V19, P97 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SCHUMAKER NH, 1998, EPA600R98135 US EPA SIEVING KE, 1996, AUK, V113, P944 SOUTH A, 1999, CONSERV BIOL, V13, P1039 STCLAIR CC, 1998, CONSERV ECOL, V2, P13 TAYLOR PD, 1993, OIKOS, V68, P571 TISCHENDORF L, 1997, ECOL MODEL, V103, P33 TODD IA, 1990, ANIM BEHAV, V40, P112 TRAVIS JMJ, 2000, ECOL LETT, V3, P163 TREXLER JC, 1993, ECOLOGY, V74, P1629 TURCHIN P, 1998, QUANTITATIVE ANAL MO URBAN D, 2001, ECOLOGY, V82, P1205 VANLANGEVELDE F, 2000, ECOGRAPHY, V23, P614 VANLANGEVELDE F, 2000, LANDSCAPE ECOL, V15, P243 VEGARIVERA JH, 1998, CONDOR, V100, P69 VILLARD MA, 1999, CONSERV BIOL, V13, P774 WEINBERG HJ, 1998, AUK, V115, P879 WIEGAND T, 1999, AM NAT, V154, P605 WITH KA, 1997, OIKOS, V78, P151 ZOLLNER PA, 1999, ECOLOGY, V80, P1019 ZOLLNER PA, 2000, LANDSCAPE ECOL, V15, P523 0921-2973 Landsc. Ecol.ISI:000178082200002Univ Laval, Ctr Rech Biol Forestiere, St Foy, PQ G1K 7P4, Canada. Belisle, M, Univ Laval, Ctr Rech Biol Forestiere, St Foy, PQ G1K 7P4, Canada.EnglishI~?t+Bell, S. S. Fonseca, M. S. Kenworthy, W. J.2008]Dynamics of a subtropical seagrass landscape: links between disturbance and mobile seed banks67-74Landscape Ecology23Disturbance is a well known modifier of landscapes. In marine systems hurricanes may not only remove or bury subtidal seagrasses but they may also impact the seed banks of these taxa. We ask whether seagrass landscape pattern and seed dispersal are influenced by physical disturbance in a subtropical deep water setting. We examined the spatial dynamics of an offshore landscape composed of the seagrass, Halophila decipiens in summer 1999 and again in 2000 after the passage of a hurricane. A towed video camera was used to collect data within a 1 km(2) area and construct benthic maps of seagrass, macroalgae, hard bottom outcrops, and sediments from over 20,000 video frames. The appearance of sand and seagrass at a portion of the site in summer 2000 that was previously hard substrate verified sediment and seed movement. Although seeds released by this seagrass are deposited into sediments near parent plants, movement en masse of the seagrass seed reservoir appears to be an important component of dispersal. The generation of new landscape patches when disturbance is large and intense suggests that large-scale disturbance, resulting in the local redistribution of sediment and the seed bank, appears to mold the spatial signature of the resulting seagrass landscape in a MidShelf area. This impact of physical disturbance differs from that previously reported for factors influencing spatial arrangements of seagrass in shallow waters but has some features similar to those of large infrequent disturbances studied in terrestrial settings."://WOS:000252922800006 Times Cited: 0WOS:000252922800006(10.1007/s10980-007-9137-z|ISSN 0921-2973<7Bellehumeur, C. Legendre, P.1998rMultiscale sources of variation in ecological variables: modeling spatial dispersion, elaborating sampling designs15-25Landscape Ecology131spatial pattern variogram correlogram fractal sampling design analysis of variance TROPICAL RAIN-FOREST PATTERN HETEROGENEITY VARIANCE SCALE AUTOCORRELATION ZOOPLANKTON LANDSCAPES BIOLOGY SIZEArticleFebDetection of structured spatial variation and identification of spatial scales are important aspects of ecological studies. Spatial structures can correspond to physical features of the environment or to intrinsic characteristics of ecological processes and phenomena. Spatial variability has been approached through several techniques such as classical analysis of variance, or the calculation of fractal dimensions, correlograms or variograms. Under certain assumptions, these techniques are all closely related to one another and represent equivalent tools to characterize spatial structures. Our perception of ecological variables and processes depends on the scale at which variables are measured. We propose simple nested sampling designs enabling the detection of a wide range of spatial structures that show the relationships among nested spatial scales. When it is known that the phenomenon under study is structured as a nested series of spatial scales, this provides useful information to estimate suitable sampling intervals, which are essential to establish the relationships between spatial patterns and ecological phenomena. The use of nested sampling designs helps in choosing the most suitable solutions to reduce the amount of random variation resulting from a survey. These designs are obtained by increasing the sampling intensity to detect a wider spectrum of frequencies, or by revisiting the sampling technique to select more representative sampling units.://000077256700002 1ISI Document Delivery No.: 143LG Times Cited: 28 Cited Reference Count: 45 Cited References: BELLEHUMEUR C, 1997, PLANT ECOL, V130, P89 BOLVIKEN B, 1992, J GEOCHEM EXPLOR, V43, P91 BORCARD D, 1994, ENVIRON ECOL STAT, V1, P37 BURROUGH PA, 1981, NATURE, V294, P240 BURROUGH PA, 1987, DATA ANAL COMMUNITY, P213 CARR JR, 1991, MATH GEOL, V23, P945 CLIFF AD, 1981, SPATINAL PROCESSES M CRESSIE NAC, 1991, STAT SPATIAL DATA DAVID M, 1977, GEOSTATISTICAL ORE R DUTILLEUL P, 1993, ECOLOGY, V74, P1646 DUTILLEUL P, 1993, OIKOS, V66, P152 FORTIN MJ, 1989, VEGETATIO, V83, P209 GARDNER RH, 1997, ECOLOGICAL SCALE THE GARRETT RG, 1983, HDB EXPLORATION GEOC, V2, P83 GEARY RC, 1954, INCORPORATED STATIST, V5, P115 GOWER JC, 1962, BIOMETRICS, V18, P537 GREIGSMITH P, 1952, ANN BOT, V16, P293 HE F, 1994, ENV ECOLOGICAL STAT, V1, P265 HE FL, 1996, J BIOGEOGR, V23, P57 HE FL, 1997, J VEG SCI, V8, P105 HEWITT JE, 1997, IN PRESS J EXP MAR B JOURNEL AG, 1978, MINING GEOSTATISTICS KOCHUMMEN KM, 1991, J TROP FOR SCI, V3, P1 LEGENDRE P, 1989, VEGETATIO, V80, P107 LEVIN SA, 1992, ECOLOGY, V73, P1943 LEWIS WM, 1978, ECOLOGY, V59, P666 LUDWIG JA, 1978, VEGETATIO, V38, P49 MANDELBROT BB, 1983, FRACTAL GEOMETRY NAT MATHERON G, 1965, VARIABLES REGIONALIS MIESCH AT, 1975, GEOLOGICAL SOC AM ME, V142, P333 MILNE BT, 1991, ECOLOGICAL HETEROGEN, P69 MORAN PAP, 1950, BIOMETRIKA, V37, P17 NORTCLIFF S, 1978, J SOIL SCI, V29, P403 OLIVER MA, 1986, GEOGR ANAL, V18, P227 PALMER MW, 1988, VEGETATIO, V75, P91 PINELALLOUL B, 1988, ECOLOGY, V69, P1393 PLATT T, 1973, LIMNOL OCEANOGR, V18, P743 RENSHAW E, 1984, VEGETATIO, V56, P75 ROSSI RE, 1992, ECOL MONOGR, V62, P277 SHAW RG, 1993, ECOLOGY, V74, P1638 SOKAL R, 1995, BIOMETRY SOKAL RR, 1978, BIOL J LINN SOC, V10, P199 SOKAL RR, 1978, BIOL J LINN SOC, V10, P229 TROUSSELLIER M, 1989, MICROOGRANISMES ECOS, P27 VERHOEF JM, 1993, J VEG SCI, V4, P441 0921-2973 Landsc. Ecol.ISI:000077256700002Univ Montreal, Dept Sci Biol, Montreal, PQ H3C 3J7, Canada. Bellehumeur, C, Univ Montreal, Dept Sci Biol, CP 6128,Succursale Ctr Ville, Montreal, PQ H3C 3J7, Canada.Englishz|?D ,Belmaker, Jonathan Ziv, Yaron Shashar, Nadav2011OThe influence of connectivity on richness and temporal variation of reef fishes587-597Landscape Ecology264AprDTo test the effects of connectivity on fish diversity in isolated reef patches we deployed pairs of artificial reefs (AR) at constant distances (12 and 25 m) from a large continuous reef and added series of small ARs to half of them. These small reefs served as stepping-stones to increase fish movement between the large ARs and the continuous reef. Species gain and loss curves were compared to obtain deeper understanding of the underlying mechanisms in relation to the theory of island biogeography. We found that AR without stepping-stones maintained up to 57-fold more individuals than ARs with stepping-stones during mass recruitment events that were dominated by the family Apogonidae. However, in-between these mass recruitment events the overall impact of the stepping-stones on richness and abundance was small. By contrast, increasing distance from the continuous reef from 12 to 25 m increased fish richness, although this was confounded with time since AR deployment. Increase in richness with distance was predominantly caused by elevated species gain. Our results suggest that fish assemblages respond in distinct ways to two types of isolation: (1) Increased richness with distance from a continuous reef, and (2) increased fluctuation in abundance with decreased connectivity. The latter may be the outcome of accumulation and then abrupt emigrations of fishes from isolated reefs. This study confirms that the spatial setting of reef patches in relation to larger or continuous reefs alters fish assemblages, which may be important for planning AR deployments that maximizes diversity.!://WOS:000288807300011Times Cited: 0 0921-2973WOS:00028880730001110.1007/s10980-011-9588-0<7Ben Wu, X. Archer, S. R.2005Scale-dependent influence of topography-based hydrologic features on patterns of woody plant encroachment in savanna landscapes733-742Landscape Ecology206/Prosopis glandulosa; ecohydrology; tree-grass interactions; parkland; vegetation change; wetness index; scale multiplicity; woody plant encroachment; southwestern USA PROSOPIS-GLANDULOSA; SEMIARID WOODLAND; SHRUB INVASION; SOIL-MOISTURE; TIGER BUSH; VEGETATION; ECOSYSTEM; MECHANISMS; AUSTRALIA; CLIMATEArticleSepWRainfall in drylands is erratic. Topographic features of landscapes can dampen or amplify temporal variability by spatially influencing patterns of water loss and accumulation. The extent to which portions of a landscape may differentially capture or retain scarce water and nutrient resources is an important determinant of vegetation patterns, particularly with respect to the distribution of woody plants. We therefore hypothesized that historic changes in woody cover on landscapes experiencing similar climate and disturbance regimes would vary with catena-to-catena (hillslope-to-hillslope) variation in topography-based hydrologic features. We tested this hypothesis by comparing topographic wetness index (TWI) values on replicate landscapes where woody plant abundance has increased over the past 100 yr. These landscapes are characterized by savanna parklands on coarse-textured upland portions of catenas that grade (1-3% slopes) into closed-canopy woodlands on fine-textured (lowland) portions of catenas. TWI values for woody and herbaceous communities were comparable within uplands, suggesting factors unrelated to surface/subsurface hydrology determine patterns of woody cover in these catena locations. TWI values for upland savanna parklands were significantly lower than those of closed-canopy woodlands occupying catena footslopes. Furthermore, uplands adjoining historically static woodland boundaries had lower TWI values than those where woodland boundaries had moved upslope 2.1 in yr(-1) from 1976 to 1995. Results suggest runoff-runon relationships influence patterns of woody plant cover and change at the catena scale and may override constraints imposed by soil texture. As a result, changes in woody cover potentially accompanying changes in disturbance regimes, climate or atmospheric chemistry are likely to be constrained by topoedaphic settings. Models of vegetation dynamics may therefore need to explicitly account for rainfall-topography soil texture relationships and associated scale-dependent mechanisms to accurately predict rates and patterns of change in woody and herbaceous plant abundance.://000233600700008 ISI Document Delivery No.: 988KS Times Cited: 0 Cited Reference Count: 66 Cited References: *ERDAS INC, 1998, US ARCVIEW IM AN *ESRI INC, 1994, ARC INFO VERS 7 ARC *ESRI INC, 1998, WORK ARCVIEW SPAT AN *MATHSOFT INC, 1998, S PLUS US GUID ANDERSON VJ, 1997, AUST J BOT, V45, P331 ARCHER S, 1988, ECOL MONOGR, V58, P111 ARCHER S, 1995, CLIMATIC CHANGE, V29, P91 ARCHER S, 1995, ECOSCIENCE, V2, P83 ARCHER S, 1995, TROP GRASSLANDS, V29, P218 ARCHER S, 1996, ECOLOGY MANAGEMENT G, P101 ARCHER S, 2001, GLOBAL BIOGEOCHEMICA, P115 BERGKAMP G, 1998, CATENA, V33, P201 BEVEN KJ, 1979, HYDROL SCI B, V24, P43 BOUTTON TW, 1998, GEODERMA, V82, P5 BRESHEARS DD, 1999, LANDSCAPE ECOL, V14, P465 BROWN JR, 1987, VEGETATIO, V73, P73 BROWN JR, 1999, ECOLOGY, V80, P2385 DELBARRIO G, 1997, LANDSCAPE ECOL, V12, P95 DICE LR, 1943, BIOTIC PROVINCES N A FRANCOPIZANA J, 1995, J VEG SCI, V6, P73 FUENTES ER, 1984, OECOLOGIA, V62, P405 GALLE S, 1999, CATENA, V37, P197 HAASE P, 1996, J VEG SCI, V7, P527 HOUSE JI, 2003, J BIOGEOGR, V30, P1 IRVIN BJ, 1997, GEODERMA, V77, P137 JELTSCH F, 2000, PLANT ECOL, V150, P161 JOHNSON RW, 1985, ECOLOGY MANAGEMENT W, P1 KENTULA ME, 1997, RESTOR ECOL S, V5, P69 KNOOP WT, 1985, J ECOL, V73, P235 KOCHY M, 2001, J ECOL, V89, P807 LEHOUEROU HN, 1988, ARID LANDS TODAY TOM, P417 LI HB, 2004, LANDSCAPE ECOL, V19, P389 LUDWIG J, 1997, LANDSCAPE ECOLOGY FU LUDWIG JA, 1999, CATENA, V37, P257 LUDWIG JA, 2002, LANDSCAPE ECOL, V17, P157 MCAULIFFE JR, 1994, ECOL MONOGR, V64, P111 MCMAHAN CA, 1984, VEGETATION TYPES TEX MCPHERSON GR, 1988, AM MIDL NAT, V120, P391 MILLER D, 2001, J ARID ENVIRON, V48, P23 MONTANA C, 1992, J ECOL, V80, P315 NOYMEIR I, 1973, ANNU REV ECOL SYST, V4, P25 NUTTLE WK, 2002, EOS, V83, P205 OLOUGHLIN EM, 1981, J HYDROL, V53, P229 OLOUGHLIN EM, 1990, AGR FOREST METEOROL, V50, P23 ONEILL MP, 1997, RESTOR ECOL S, V5, P85 RODRIGUEZITURBE I, 1999, WATER RESOUR RES, V35, P3709 RODRIGUEZITURBE I, 2000, WATER RESOUR RES, V36, P3 SCHOLES RJ, 1997, ANNU REV ECOL SYST, V28, P517 SCIFRES CJ, 1987, B MP, V1626 SEGHIERI J, 1999, ACTA OECOL, V20, P209 SHACHAK M, 1998, ECOSYSTEMS, V1, P475 STOKES CJ, 1999, THESIS TEXAS A M U C STROH JC, 1995, THESIS TEXAS A M U C TODD SW, 1998, INT J REMOTE SENS, V19, P427 TONGWAY DJ, 2001, BANDED VEGETATION PA VANAUKEN OW, 2000, ANNU REV ECOL SYST, V31, P197 VITOUSEK PM, 1989, ECOL MONOGR, V59, P247 WALKER BH, 1987, DETERMINANTS TROPICA WALKER BH, 1997, J BIOGEOGR, V24, P813 WELTZ MA, 1995, J RANGE MANAGE, V48, P45 WHITTAKER RH, 1979, VEGETATIO, V39, P65 WIENS JA, 1989, FUNCT ECOL, V3, P385 WILCOX BP, 2003, ECOL MONOGR, V73, P223 WILLIAMS RJ, 1996, J BIOGEOGR, V23, P747 WU JG, 2004, LANDSCAPE ECOL, V19, P125 WU XB, 2000, J ECOL, V88, P790 0921-2973 Landsc. Ecol.ISI:000233600700008Texas A&M Univ, Dept Rangeland Ecol & Management, College Stn, TX 77843 USA. Univ Arizona, Sch Nat Resources, Tucson, AZ 85721 USA. Ben Wu, X, Texas A&M Univ, Dept Rangeland Ecol & Management, College Stn, TX 77843 USA. xbw@tamu.eduEnglish*<7(Bender, D. J. Tischendorf, L. Fahrig, L.2003MUsing patch isolation metrics to predict animal movement in binary landscapes17-39Landscape Ecology181dispersal fragstats island biogeography metapopulation nearest neighbor patch isolation proximity HABITAT FRAGMENTATION AGRICULTURAL LANDSCAPE BANK VOLE METAPOPULATION DYNAMICS CLETHRIONOMYS-GLAREOLUS SCIURUS-VULGARIS SPATIAL PATTERN SMALL MAMMALS RED SQUIRREL POPULATIONArticleJan]Habitat isolation can affect the distribution and abundance of wildlife, but it is an ambiguous attribute to measure. Presumably, isolation is a characteristic of a habitat patch that reflects how spatially inaccessible it is to dispersing organisms. We identified four isolation metrics (nearest-neighbor distance, Voronoi polygons, proximity index, and habitat buffers) that were representative of the different families of metrics that are commonly used in the literature to measure patch isolation. Using simulated data, we evaluated the ability of each isolation metric to predict animal dispersal. We examined the simulated movement of organisms in two types of landscapes: an artificially-generated point-pattern landscapes where patch size and shape were consistent and only the arrangement of patches varied, and realistic landscapes derived from a geographic information system (GIS) of forest-vegetation maps where patch size, shape, and isolation were variable. We tested the performance of the four isolation metrics by examining the strength of the correlation between observed immigration rate in the simulations and each patch isolation metric. We also evaluated whether each isolation metric would perform consistently under varying conditions of patch size/shape, total amount of habitat in the landscape, and proximity of the patch to the landscape edge. The results indicate that a commonly-used distance-based metric, nearest-neighbor distance, did not adequately predict immigration rate when patch size and shape were variable. Area-informed isolation metrics, such as the amount of available habitat within a given radius of a patch, were most successful at predicting immigration. Overall, the use of area-informed metrics is advocated despite the limitation that these metrics require parameterization to reflect the movement capacity of the organism studied.://000181767500002 ISI Document Delivery No.: 659FW Times Cited: 19 Cited Reference Count: 60 Cited References: ANDREN H, 1994, OIKOS, V71, P355 BENDER DJ, 2000, THESIS CARLETON U OT BOLGER DT, 1997, ECOL APPL, V7, P552 BOWMAN J, IN PRESS ECOLOGY BRENNAN JM, 2002, IN PRESS INTEGRATING CAPPUCCINO N, 1997, OECOLOGIA, V110, P69 DELIN AE, 1999, LANDSCAPE ECOL, V14, P67 DEVRIES HH, 1996, OECOLOGIA, V107, P332 DIAMOND JM, 1975, BIOL CONSERV, V7, P129 DIGGLE PJ, 1983, STAT ANAL SPATIAL PO DOAK DF, 1994, ECOLOGY, V75, P615 DUNNING JB, 1995, CONSERV BIOL, V9, P542 ELKIE PC, 1999, PATCH ANAL USERS MAN FITZGIBBON CD, 1993, J APPL ECOL, V30, P736 FITZGIBBON CD, 1997, J APPL ECOL, V34, P530 GRASHOFBOKDAM C, 1997, J VEG SCI, V8, P21 GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 GUSTAFSON EJ, 1994, LANDSCAPE URBAN PLAN, V29, P117 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HANSKI I, 1991, BIOL J LINN SOC, V42, P3 HANSKI I, 1998, NATURE, V396, P41 HANSKI I, 2000, NATURE, V404, P755 HANSSON L, 1998, OIKOS, V81, P55 HARGIS C, 1998, LANDSCAPE ECOLOGY, V13 HARRISON RL, 1992, CONSERV BIOL, V6, P293 HILL JK, 1996, J ANIM ECOL, V65, P725 HJERMANN DO, 1996, J ANIM ECOL, V65, P768 HOKIT DG, 1999, ECOL APPL, V9, P124 JOHANNESEN E, 2000, OIKOS, V89, P37 KAREIVA P, 1990, PHILOS T ROY SOC B, V330, P175 KINNUNEN H, 1996, ANN ZOOL FENN, V33, P165 KOZAKIEWICZ M, 1985, ACTA THERIOL, V30, P193 KREBS CJ, 1989, ECOLOGICAL METHODOLO LAAN R, 1990, BIOL CONSERV, V54, P251 LEVINS R, 1970, SOME MATH PROBLEMS B, P77 LUISELLI L, 1997, BIODIVERS CONSERV, V6, P1339 MACARTHUR RH, 1967, THEORY ISLAND BIOGEO MARSH DM, 1999, J ANIM ECOL, V68, P804 MATTER SF, 1996, OECOLOGIA, V105, P447 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MLADENOFF DJ, 2000, APACK 2 14 ANAL SOFT OKUBO A, 1980, DIFFUSION ECOLOGICAL OPDAM P, 1985, BIOL CONSERV, V34, P333 OPDAM P, 1991, LANDSCAPE ECOL, V5, P93 PAILLAT G, 1996, ACTA OECOL, V17, P553 PATTON DR, 1975, WILDLIFE SOC B, V3, P171 PERERA AH, 1997, 146 ONT FOR RES I ON STEEL RDG, 1980, PRINCIPLES PROCEDURE SUTHERLAND GD, 2000, CONSERV ECOL, V4 SZACKI J, 1993, ACTA THERIOL, V38, P113 TISCHENDORF L, 2000, LANDSCAPE ECOL, V15, P633 TISCHENDORF L, 2001, LANDSCAPE ECOL, V16, P235 TRZCINSKI MK, 1999, ECOL APPL, V9, P586 TURCHIN P, 1998, QUANTITATIVE ANAL MO VANAPELDOORN RC, 1992, OIKOS, V65, P265 VANDORP D, 1987, LANDSCAPE ECOLOGY, V1, P59 VERBOOM B, 1990, LANDSCAPE ECOL, V4, P171 VOS CC, 1995, LANDSCAPE ECOLOGY, V11, P203 VOS CC, 1998, J APPL ECOL, V35, P44 WITH KA, 1999, CONSERV BIOL, V13, P314 0921-2973 Landsc. Ecol.ISI:000181767500002Carleton Univ, Ottawa Carleton Inst Biol, Ottawa, ON K1S 5B6, Canada. Fahrig, L, Carleton Univ, Ottawa Carleton Inst Biol, Ottawa, ON K1S 5B6, Canada. lfahrig@ccs.carleton.caEnglishm<74Bender, O. Boehmer, H. J. Jens, D. Schumacher, K. P.2005tAnalysis of land-use change in a sector of Upper Franconia (Bavaria, Germany) since 1850 using land register records149-163Landscape Ecology202Cadastral maps; Cultural landscape; Disturbance regime; Germany; Grazing; human disturbance; Landscape history; multitemporal GIS LANDSCAPE CHANGE; COVER CHANGE; BIODIVERSITY; PATTERNS; CONSERVATION; HISTORY; MAPSArticleFebThis study analyses changes in the landscape of a sector of Upper Franconia (Bavaria, Germany) by comparing land use changes over four time periods (1850, 1900, 1960, 2000). Geodetic and other data derived from the Bavarian real estate tax and land register were entered into various temporal layers of a land register-based vector GIS. This multitemporal GIS permits a precise analysis of the historical structure and development of landscapes on the basis of land plots. In 1850, the study area was almost exclusively agricultural in structure. Woodlands made up only 18% of the total surface. Rough pastures and wastelands, which covered about 9% of the total surface, were used for grazing. During the first half of the 20th century, the proportion of wooded areas increased considerably. The rough pastures that had formerly been a typical feature of the region nearly disappeared during this period. Agricultural use declined to less than 50% of the total area. In the course of the period between 1960 and 2000, the livestock industry has become an almost exclusively indoor activity. Village development has started spilling over into the adjacent fields. The causes and background of these changes are discussed in detail. From an ecological standpoint, the land use categories surveyed in this analysis of landscape change can be regarded as vegetation types, thereby constituting habitats for specialized biota. The intensity and frequency of any type of land use creates a certain disturbance regime, which disrupts and controls the succession in a certain way. The concept of categories of change incorporated into the GIS helps to evaluate these habitat types and the rate of change more accurately, e.g. for nature conservation purposes.://000230299600003  ISI Document Delivery No.: 942RN Times Cited: 0 Cited Reference Count: 59 Cited References: *BA LAND BETR AGR, 1986, AGR REG OB *BFN, 2000, SCHRIFTENREIHE VEGET, V35 *BUND NAT, 1988, SCHRIFTENREIHE LANDS, V55 *CEC, 1991, CORINE BIOT MAN ANAND M, 1994, COENOSES, V9, P81 BENDER O, 2005, LANDSCAPE URBAN PLAN, V70, P111 BENTON TG, 2003, TRENDS ECOL EVOL, V18, P182 BOEHMER HJ, 1994, MITTEILUNGEN FRANKIS, V41, P323 BOEHMER HJ, 1997, NATUR LANDSCHAFT, V72, P333 BONN S, 1988, AUSBREITUNGSBIOLOGIE CHRISTENSEN NL, 1997, ECOLOGICAL BASIS CON, P167 COUSINS SAO, 2001, LANDSCAPE ECOL, V16, P41 COUSINS SAO, 2002, LANDSCAPE URBAN PLAN, V61, P1 ELLENBERG H, 1996, VEGETATION MITTELEUR FAHRIG L, 1994, CONSERV BIOL, V8, P50 FORMAN RTT, 1986, LANDSCAPE ECOLOGY GAUCKLER K, 1938, 23 BAYER BOT GES GORDON DR, 1995, ECOLOGICAL BASIS CON, P262 GUTZWILLER KJ, 2002, APPL LANDSCAPE ECOLO, P357 HANSKI I, 1999, METAPOPULATION ECOLO HEIDER J, 1954, BAYERISCHE KATASTER HENKEL G, 1995, LANDLICHE RAUM HOFFMEISTER S, 1966, THESIS U ERLANGEN ER HOHENESTER A, 1989, SCHRIFTEN ZENTRALINI, P77 HORNBERGER T, 1959, REMAGEN FORSCHUNGEN, V109 HOUGHTON RA, 1994, BIOSCIENCE, V44, P305 HUMMER P, 1976, MITTEILUNGEN FRANISC, V21, P527 HUMMER P, 1986, FRANKEN PLANUNG BESS, P285 JACOBEIT W, 1961, VEROFFENTLICHUNGN I, V25 JAEGER J, 2002, LANDSCHAFTSZERSCHNEI JEDICKE E, 1998, NATURSCHUTZ LANDSCHA, V30, P229 KLEYER M, 1996, SPECIES SURVIVAL FRA, P138 LAMARCHE H, 1982, NATUR LANDSCHAFT, V57, P458 LAMBECK RJ, 2002, APPL LANDSCAPE ECOLO, P360 MCLURE JT, 2002, T GIS, V6, P69 MESSNER R, 1967, 150 HAHRE OSTERREICH MUELLERDOMBOIS D, 2002, AIMS METHODS VEGETAT OLDFIELD F, 2000, PAGES NEWSLETTER, V8, P21 OLSSON EGA, 2000, LANDSCAPE ECOL, V15, P155 PARTEL M, 1999, LANDSCAPE ECOL, V14, P187 PETIT CC, 2002, LANDSCAPE ECOL, V17, P117 PICKETT STA, 1985, ECOLOGY NATURAL DIST POIANI KA, 2000, BIOSCIENCE, V50, P133 POUDEVIGNE I, 2003, LANDSCAPE ECOL, V18, P223 REID RS, 2000, LANDSCAPE ECOL, V15, P339 RIEBSAME WE, 1994, BIOSCIENCE, V44, P350 ROWECK H, 1995, LOBF MITTEILUNGEN, V20, P25 RUSCH GM, 2003, J VEG SCI, V14, P307 SPORRONG U, 1998, LINKING SOCIAL ECOLO, P67 TURNER MG, 2001, LANDSCAPE ECOLOGY TH URBAN DL, 1987, BIOSCIENCE, V37, P119 VERHEYEN K, 1999, J BIOGEOGR, V26, P1115 VONHAAREN C, 2002, LANDSCAPE URBAN PLAN, V60, P73 WAGNER H, 1950, ENTWICKLUNG KATASTER WALDHARDT R, 2003, NOVA ACTA LEOPOLDINA, V328, P237 WALENTOWSKI H, 1991, BERICHTE BAYERISCHEN, V62 WEISEL H, 1971, ERLANGER GEOGRAPHISC, V28 WIENS JA, 2002, APPL LANDSCAPE ECOLO, P3 WITH KA, 1995, ECOLOGY, V76, P2446 0921-2973 Landsc. Ecol.ISI:000230299600003CTech Univ Munich, Dept Ecol, D-85350 Freising Weihenstephan, Germany. Austrian Acad Sci, Inst Urban & Reg Res, A-1010 Vienna, Austria. Univ Freiburg, Dept Human Geog, D-79085 Freiburg, Germany. Bender, O, Tech Univ Munich, Dept Ecol, Landscape Ecol LOEK,Hochanger 6, D-85350 Freising Weihenstephan, Germany. neobiota@web.deEnglishS<7#Benjamin, K. Domon, G. Bouchard, A.2005rVegetation composition and succession of abandoned farmland: effects of ecological, historical and spatial factors627-647Landscape Ecology206>abandoned fields; Canada; ecological groups; land management; old fields; Quebec; scrublands; shrublands; successional vectors; variation partitioning SAINT-LAURENT QUEBEC; OLD-FIELD SUCCESSION; RIGHTS-OF-WAY; PLANT SUCCESSION; SOUTHERN QUEBEC; NEW-YORK; SEEDLING EMERGENCE; TREE ESTABLISHMENT; TOMPKINS COUNTY; FORESTArticleSepxIn North America, as well as in Europe, the mechanization and the modernization of the agricultural activities had strongly modified the agricultural landscapes. Originating from these transformations of the agricultural environment, abandoned farmlands remain poorly known environments. A holistic approach, including the analysis of ecological, historical and spatial factors, is used in order to understand the dynamics of these environments created by agricultural abandonment in southwestern Quebec (Canada). The analysis of 36 abandoned farmlands in the study area reveals the existence of two ecological groups. The first ecological group is composed by abandoned farmlands originating from pasture and at the moment dominated by a spiny shrub vegetation. The second ecological group includes past cultivated field at the moment dominated by either hydric herbaceous and shrub vegetation. Abiotic ecological variables such as slope, surface stoniness, canopy opening and soil pH, as well as land-use history, and age of the abandoned farmlands, are major factors explaining the current state of abandoned farmlands. Succession vector analysis reveals a strong differentiation among abandoned farmlands as to their tree species regeneration. Possible management alternatives, such as reforestation, are proposed in order to integrate those new environments to the modern agricultural landscape.://000233600700001 ISI Document Delivery No.: 988KS Times Cited: 0 Cited Reference Count: 66 Cited References: *CHAMBR AGR, 1991, PAYS FRICH ACHERAR M, 1984, ACTA OECOL-OEC PLANT, V5, P179 ANDRE MF, 1995, NOROIS, V42, P629 ARMESTO JJ, 1986, VEGETATIO, V66, P85 BAKKER ES, 2004, J APPL ECOL, V41, P571 BARBOUR MG, 1999, TERRESTRIAL PLANT EC BEAUDET M, 1998, CAN J FOREST RES, V28, P1007 BORCARD D, 1992, ECOLOGY, V73, P1045 BOUCHARD A, 1983, SYLLOGEUS BOUCHARD A, 1996, MANUEL FORESTERIE, P160 BOUCHARD A, 1997, LANDSCAPE URBAN PLAN, V37, P99 BOUYOUCOS GJ, 1962, AGRON J, V54, P464 BRISSON J, 1988, CAN J BOT, V66, P1192 BRISSON J, 1997, 6 INT C ENV CONC RIG, P25 BRISSON J, 2003, ECOSCIENCE, V10, P236 BURTON PJ, 1991, AM J BOT, V78, P131 BUTTOUD G, 1991, E C C WORKSH AFF AGR CASGRAIN P, 2001, R PACKAGE MULTIVARIA COGLIASTRO A, 1997, FOREST ECOL MANAG, V96, P49 COGLIASTRO A, 2003, FOREST ECOL MANAG, V177, P347 DANSEREAU P, 1946, CANADIAN J RES C, V24, P235 DEBLOIS S, 1995, J VEG SCI, V6, P531 DEBLOIS S, 2001, LANDSCAPE ECOL, V16, P421 DELAGE M, THESIS U MONTREAL DERIOZ P, 1994, THESIS U AVIGNON AVI DESTEVEN D, 1991, ECOLOGY, V72, P1066 DESTEVEN D, 1991, ECOLOGY, V72, P1076 DOMON G, 1993, LANDSCAPE URBAN PLAN, V25, P53 DREYER GD, 1986, ENVIRON MANAGE, V10, P113 FOSTER DR, 2002, J BIOGEOGR, V29, P1381 FRAZER GW, 2000, B ECOL SOC AM, V81, P191 GARDESCU S, 2004, J TORREY BOT SOC, V131, P53 GILL DS, 1991, ECOL MONOGR, V61, P183 GIRARD M, 1990, MEMOIRE RECHERCHE GLOBENSKY Y, 1987, 8502 MM MIN RESS QUE GOFF FG, 1972, AM MIDL NAT, V87, P397 HILL JD, 1995, ECOL APPL, V5, P459 HOUEROU HNL, 1993, AGROFOREST SYST, V21, P43 LABRECQUE J, 2002, PLANTES VASCULAIRES LEGENDRE P, 1998, NUMERICAL ECOLOGY LEGENDRE P, 2001, OECOLOGIA, V129, P271 MAILLOUX A, 1954, B TECHNIQUE, V4 MARIEVICTORIN F, 1995, FLORE LAURENTIENNE MCGARIGAL K, 2002, FRAGSTATS SPATIAL PA MEILLEUR A, 1994, ENVIRON MANAGE, V18, P907 MERCIER C, 2001, ENVIRON MANAGE, V28, P777 MESSIER C, 1998, J VEG SCI, V9, P511 MOTZKIN G, 1999, J VEG SCI, V10, P903 MOTZKIN G, 2002, J BIOGEOGR, V29, P1439 MYSTER RW, 1994, ECOLOGY, V75, P387 NIERING WA, 1955, ECOLOGY, V36, P356 OLSSON EG, 1987, ACTA OECOL-OEC GEN, V8, P379 ORWIG DA, 1994, CAN J FOREST RES, V24, P1216 PAN DY, 1999, LANDSCAPE ECOL, V14, P35 PARENT S, 1996, CAN J FOREST RES, V26, P151 PEARCY RW, 1989, PLANT PHYSL ECOLOGY PELISSIE D, 1992, REV FOR FR, V44, P479 PUTZ FE, 1992, FOREST ECOL MANAG, V49, P267 SIMARD H, 1996, CAN J FOREST RES, V26, P1670 SMIT R, 1996, COLONIZATION WOODY S SMITH BE, 1993, B TORREY BOT CLUB, V120, P229 STAALAND H, 1998, AMBIO, V27, P456 STOVER ME, 1998, J TORREY BOT SOC, V125, P150 TATONI T, 1994, J VEG SCI, V5, P295 TERBRAAK CJF, 2002, CANOCO REFERENCE MAN UHL C, 1988, J ECOL, V76, P663 0921-2973 Landsc. Ecol.ISI:000233600700001`Univ Montreal, Inst Rech Biol Vegetale, Dept Sci Biol, Montreal, PQ H1X 2B2, Canada. Univ Montreal, Fac Environm Design, Montreal, PQ H3C 3J7, Canada. Univ Quebec, GREFi, Montreal, PQ H3C 3P8, Canada. Benjamin, K, Univ Montreal, Inst Rech Biol Vegetale, Dept Sci Biol, 4101 Est Rue Sherbrooke, Montreal, PQ H1X 2B2, Canada. karyne.benjamin@umontreal.caEnglish#۽7Bennett, AndrewF2013=The challenge of integrating science for landscape management 1427-1428Landscape Ecology287Springer Netherlands 2013/08/01+http://dx.doi.org/10.1007/s10980-013-9889-6 0921-2973Landscape Ecol10.1007/s10980-013-9889-6Englishy?&Andrew F. Bennett1990ZHabitat corridors and the conservation of small mammals in a fragmented forest environment109-122Landscape Ecology42/3dsmall mammals, habitat corridors, forest fragmentation, agricultural landscape, roadsides, AustraliadAt Naringal in south-western Victoria, Australia, clearing of the original forest environment has created an agricultural landscape dominated by grazed pastures of introduced grasses. Remnant forest vegetation is restricted to small patches of less than 100 ha in size, that are loosely linked by narrow forested strips along road reserves and creeks. Six native and two introduced species of small terrestrial mammal (< 2 kg) occur within this environment. The native mammals, being dependent upon forest vegetation, were less tolerant to forest fragmentation than were the introduced species that also persist% farmland and farm buildings. The native mammals displayed an increasing frequency of occurrence in successively larger size-classes of forest patches. Those species with the greatest body-weight were the most vulnerable to habitat loss. All species of small mammal occurred in narrow habitat corridors of forest vegetation on roadsides. The resident status, seasonal variation in relative abundance, patterns of reproduction, and movements of each species were monitored in two habitat corridors during a 25-month trapping study. The corridors were found to facilitate continuity between otherwise-isolated populations of small mammals in this locality in two ways: firstly, by providing a pathway for the dispersal of single animals between patches; and secondly, by enabling gene flow through populations resident within the corridors. The small size of forest remnants at Naringal, and the vulnerability of species with low population sizes, emphasize the importance of preserving a mosaic of numerous habitat patches that together will support regional populations of sufficient size for longer-term persistence. The continuity between remnant habitats that is provided by a network of habitat corridors is an essential, and critical, component of this conservation strategy.|<7.Bennett, E. M. Carpenter, S. R. Clayton, M. K.2005USoil phosphorus variability: scale-dependence in an urbanizing agricultural landscape389-400Landscape Ecology204agriculture; nonpoint source pollution; phosphorus; scale; soil; urban; variability SPATIAL VARIABILITY; LAND-USE; PATTERN; MANAGEMENT; ECOLOGY; RESOURCES; RUNOFF; MODEL; USAArticleMay=We examine the hypothesis that human activity changes patterns of variance in soil P (Bray-1) concentrations across several spatial scales. We measured sod P concentrations and variability for each of four different land uses at three distinct levels of analysis. Land uses were remnant prairie, lawns, corn fields of cash grain farms, and corn fields of dairies in Dane County, Wisconsin (USA). For each land use type, levels of analysis were sites (an agricultural field, residential lawn or prairie, ranging in size from 100 m(2) to approximately 20 ha), 10-m plots within a site, and points within the 10-m diameter plot. The rank of mean soil P concentrations was cash grain > dairy > lawn > prairie. For all land use types, most of the variance was accounted for by site-to-site variation. Among-site variance was higher for human-dominated sites (0.55, 0.15, 0.14 [log (mg/kg)](2) for cash grain, dairy, and lawn sites, respectively) than it was for prairies (0.07 [log (mg/kg)](2)). However, prairies had the highest among-plot variation (0.04 [log (mg/kg)](2)) compared to other sites (0.01, 0.002, and 0.01 [log (mg/kg)](2) for cash grain, dairy, and lawn sites, respectively). The results indicate that in this watershed, human activity has increased the mean soil P and variance of soil P, and shifted the scale of variance to larger spatial extents. Human impacts on landscape pattern extend to soil properties that affect nutrient flow and eutrophication of surface waters. Because soil P turns over slowly, the legacy of altered soil P patterns may affect freshwaters for centuries.://000233035100003 ISI Document Delivery No.: 980RE Times Cited: 0 Cited Reference Count: 46 Cited References: *DAN COUNT REG PLA, 1992, REG TRENDS DAN COUNT *R DEV COR TEAM, 2002, R VERS 1 5 1 *USDA SCS, 1978, SOIL SURV DAN COUNT BENNETT EM, 1999, ECOSYSTEMS, V2, P69 BENNETT EM, 2003, ENVIRON MANAGE, V32, P476 BIRRELL SJ, 1996, P 3 INT C PREC AGR, P207 BOX GEP, 1978, STAT EXPT INTRO DESI BURROUGH PA, 1983, J SOIL SCI, V34, P599 CURTIS JT, 1959, VEGETATION WISCONSIN FOSTER D, 2003, BIOSCIENCE, V53, P77 FRATERRIGO J, IN PRESS ECOLOGY GBUREK WJ, 1996, ADV HILLSLOPE PROCES, P263 GBUREK WJ, 2000, J ENVIRON QUAL, V29, P130 HEATHWAITE L, 1999, WATER SCI TECHNOL, V39, P149 HEATHWAITE L, 2000, J ENVIRON QUAL, V29, P158 HECKRATH G, 1995, J ENVIRON QUAL, V24, P904 JENNY H, 1980, SOIL RESOURCE KELLING KA, 1991, A2809 U WISC EXT LATHROP RC, 1992, FOOD WEB MANAGEMENT, P69 LATTY EF, 2004, ECOSYSTEMS, V7, P193 LEVIN SA, 1992, ECOLOGY, V73, P1943 LUCK M, 2002, LANDSCAPE ECOL, V17, P327 MALLARINO AP, 1996, SOIL SCI SOC AM J, V60, P1473 MCCOLLUM RE, 1991, AGRON J, V83, P77 MILNE BT, 1992, THEOR POPUL BIOL, V41, P337 NEEDELMAN BA, 2001, SOIL SCI SOC AM J, V65, P1516 NOWAK P, 1996, 1 ENV RES CTR ONEILL RV, 1986, HIERARCHICAL CONCEPT PAZGONZALEZ A, 2000, COMMUN SOIL SCI PLAN, V31, P2135 PAZGONZALEZ A, 2000, GEODERMA, V97, P273 PIONKE HB, 1997, PHOSPHORUS LOSS SOIL ROBERTSON GP, 1993, OECOLOGIA, V96, P451 ROBERTSON GP, 1997, ECOL APPL, V7, P158 SCHLESINGER WH, 1996, ECOLOGY, V77, P364 SHARPLEY A, 1995, J ENVIRON QUAL, V24, P947 SHARPLEY AN, 1985, SOIL SCI SOC AM J, V49, P1010 SHARPLEY AN, 1993, J PROD AGRIC, V6, P492 SHARPLEY AN, 2001, J ENVIRON QUAL, V30, P2026 SMITH VH, 1998, SUCCESSES LIMITATION SNEDECOR GW, 1980, STAT METHODS SOLIE JB, 1999, SOIL SCI SOC AM J, V63, P1724 SORANNO PA, 1996, ECOL APPL, V6, P865 TURNER MG, 1997, ECOL MONOGR, V67, P411 TURNER MG, 2001, LANDSCAPE ECOLOGY TH URBAN DL, 1987, BIOSCIENCE, V37, P119 VITOUSEK PM, 1991, BIOGEOCHEMISTRY, V13, P87 0921-2973 Landsc. Ecol.ISI:000233035100003Univ Wisconsin, Ctr Limnol, Madison, WI 53706 USA. Univ Wisconsin, Dept Stat, Madison, WI 53706 USA. Bennett, EM, Univ Wisconsin, Ctr Limnol, 680 N Pk St, Madison, WI 53706 USA. embennett@wisc.eduEnglishڽ7 2Bennett, VictoriaJ Sparks, DaleW Zollner, PatrickA2013QModeling the indirect effects of road networks on the foraging activities of bats979-991Landscape Ecology285Springer NetherlandsAccessible habitat Anthropogenic disturbance Disturbance-related behavior Foraging success Individual-based model Myotis sodalis Threshold 2013/05/01+http://dx.doi.org/10.1007/s10980-013-9874-0 0921-2973Landscape Ecol10.1007/s10980-013-9874-0English!<7Benning, T. L. Seastedt, T. R.1995fLandscape-level interactions between topoedaphic features and nitrogen limitation in tallgrass prairie337-348Landscape Ecology106Bfire; nitrogen; NDVI; transect; watershed FIRE; DYNAMICS; DETRITUSArticleDecTransects across watersheds with varying fire histories and remotely-sensed data were used to study vegetation-resource interactions in a tallgrass prairie in Kansas. Paired plots (fertilized, control) were established along these transects and sampled for grass and forb biomass during the 1989 and 1990 growing seasons. Fertilization resulted in significant production responses in grass and total biomass on the west slopes of the annually burned (1D) and infrequently burned (N4) watersheds for both years (p = 0.05). In 1989, fertilization also produced a significant increase in grass biomass on the west slope of the unburned transect (p = 0.05), however, total production was not significantly increased. East slopes were insensitive to nitrogen additions. Differences in production response along these transects were assessed by testing the interaction between fertilization response and slope position. Significant interactions occurred on both 1D and N4, but only in 1990. Production data for both years were also compared to Normalized Difference Vegetation Index (NDVI) values derived from thematic mapper (TM) images for 1989 and 1990. When differences among transects or watersheds were statistically different, a positive relationship between NDVI and biomass was observed. NDVI values accurately reflected the spatial patterns of production along these transects for both years although not necessarily the magnitude.://A1995TN14300002 ISI Document Delivery No.: TN143 Times Cited: 8 Cited Reference Count: 37 Cited References: ABER JD, 1978, CAN J FOREST RES, V8, P306 ABRAMS MD, 1986, AM J BOT, V73, P1509 BARK D, 1987, CLIMATES LONG TERM E, P45 BENNING TL, IN PRESS OECOLOGIA BENNING TL, 1993, THESIS U COLORADO BO BIEDERBECK VO, 1980, SOIL SCI SOC AM J, V44, P103 BROWN MJ, 1971, TECHNICAL B, V547 CHAPIN FS, 1986, AM NAT, V127, P48 DAUBENMIRE R, 1968, ADV ECOL RES, V5, P209 HULBERT LC, 1969, ECOLOGY, V50, P874 HULBERT LC, 1988, ECOLOGY, V69, P46 JANTZ DR, 1975, SOIL SURVEY RILEY CO KNAPP AK, 1984, AM J BOT, V71, P220 KNAPP AK, 1985, ECOLOGY, V66, P1309 KNAPP AK, 1986, BIOSCIENCE, V36, P662 KNAPP AK, 1993, ECOLOGY, V74, P549 LILLESAND TM, 1987, REMOTE SENSING IMAGE, P615 LUCERA CL, 1981, FIRE REGIMES ECOSYST OJIMA DS, 1987, THESIS COLO STATE, P57 OJIMA DS, 1990, FIRE N AM TALLGRASS, P99 OLD SM, 1969, ECOL MONOGR, V39, P355 PARTON WJ, 1987, SOIL SCI SOC AM J, V51, P1173 PASTOR J, 1986, BIOGEOCHEMISTRY, V2, P3 RAISON RJ, 1979, PL SOIL, V51, P73 RISSER PG, 1981, TRUE PRAIRIE ECOSYST, P1 RISSER PG, 1982, ECOLOGY, V63, P1342 SALA OE, 1988, ECOLOGY, V69, P40 SCHIMEL DS, 1991, ECOLOGY, V72, P672 SCHOTT JR, 1988, REMOTE SENS ENVIRON, V26, P1 SEASTEDT TR, 1988, ECOLOGY, V69, P59 SEASTEDT TR, 1990, FIRE N AM TALLGRASS, P81 SEASTEDT TR, 1991, OECOLOGIA, V87, P72 SEASTEDT TR, 1993, AM NAT, V141, P621 TOWNE G, 1984, J RANGE MANAGE, V37, P392 TURNER CL, 1992, J GEOPHYS RES, V97, P855 TURNER CL, 1992, J GEOPHYS RES, V97, P866 VITOUSEK PM, 1991, BIOGEOCHEMISTRY, V13, P87 0921-2973 Landsc. Ecol.ISI:A1995TN14300002EUNIV COLORADO,DEPT ENVIRONM ORGANISM & POPULAT BIOL,BOULDER,CO 80309.English2?1Benninger-Truax, M. J.L. Vankat R.L. Schaefer1992tTrail corridors as habitat and conduits for movement of plant species in Rochy Mountain National Park, Colorado, USA269-278Landscape Ecology64-disturbance, edge, exotic species, vegetationGround-layer vegetation was sampled along selected trail corridors to determine whether corridors provide habitat for certain species and act as conduits for species movement. Patterns of plant species composition were analyzed in relation to distance from trail edge, level of trail use, and distance from trailheads, junctions, and campgrounds. Species composition was significantly affected by distance from trail edge and level of trail use, as species were favored or inhibited by the corridor, depending upon their growth habits. Species composition was also affected by distance from trailheads. These findings, along with the presence of exotic species, indicate that trail corridors in Rocky Mountain National Park function as habitat and conduits for movement of plant species.? Benoît, Marc Rizzo, Davide Marraccini, Elisa Moonen, Anna Galli, Mariassunta Lardon, Sylvie Rapey, Hélène Thenail, Claudine Bonari, Enrico2012NLandscape agronomy: a new field for addressing agricultural landscape dynamics 1385-1394Landscape Ecology2710Springer NetherlandsBiomedical and Life Sciences+Landscape dynamics increasingly challenge agronomists to explain how and why agricultural landscapes are designed and managed by farmers. Nevertheless, agronomy is rarely included in the wide range of disciplines involved in landscape research. In this paper, we describe how landscape agronomy can help explain the relationship between farming systems and agricultural landscape dynamics. For this, we propose a conceptual model of agricultural landscape dynamics that illustrates the specific contribution of agronomy to landscape research. This model describes the relationship between three elements: farming practices, landscape patterns and natural resources. It can stimulate agronomists to deal with research issues in agricultural landscape dynamics and enhance the interdisciplinary integration of farming systems in wider landscape research. On these premises, we discuss the main research issues that will benefit from an active involvement of agronomy, to understand, but also to assess landscape dynamics and to design relevant decision support systems.+http://dx.doi.org/10.1007/s10980-012-9802-8 0921-297310.1007/s10980-012-9802-8?%Benson, Barbara J. Mackenzie, Mark D.1995FEffects of sensor spatial resoltuion on landscape structure parameters113-120Landscape Ecology102Fscale effect, remote sensing, grain, landscape pattern, texture, scale |7b Benson, B. J. Mackenzie, M. D.1995FEffects of Sensor Spatial-Resolution on Landscape Structure Parameters113-120Landscape Ecology1024remote sensing grain landscape pattern texture scaleAprWe examined the effects of increasing grain size from 20 m to 1100 m on landscape parameters characterizing spatial structure in the northern Wisconsin lake district. We examined whether structural parameters remain relatively constant over this range and whether aggregation algorithms permit extrapolation within this range. Images from three different satellite sensors were employed in this study: (1) the SPOT multispectral high resolution visible(HRV), (2) the Landsat Thematic Mapper (TM), and (3) the NOAA Advanced Very High Resolution Radiometer (AVHRR). Each scene was classified as patches of water in a matrix of land. Spatial structure was quantified using several landscape parameters: percent water, number of lakes (patches), average lake area and perimeter, fractal dimension, and three measures of texture (homogeneity, contrast, and entropy). Results indicate that most measures were sensitive to changes in grain size. As grain size increased from 20 m using HRV image data to 1100 m (AVHRR), the percent water and the number of lakes decreased while the average lake area, perimeter, the fractal dimension, and contrast increased. The other two texture measures were relatively invariant with grain size. Although examination of texture at various angles of adjacency was performed to investigate features which vary systematically with angle, the angle did not have an important effect on the texture parameter values. An aggregation algorithm was used to simulate additional grain sizes. Grain was increased successively by a factor of two from 20 m (the HRV image) to 1280 m. We then calculated landscape parameter values at each grain size. Extrapolated values closely approximated the actual sensor values. Because the grain size has an important effect on most landscape parameters, the choice of satellite sensor must be appropriate for the research question asked. Interpolation between the grain sizes of different satellite sensors is possible with an approach involving aggregation of pixels.://A1995QX34400005-Qx344 Times Cited:46 Cited References Count:0 0921-2973ISI:A1995QX34400005ABenson, Bj Univ Wisconsin,Ctr Limnol,680 N Pk St,Madison,Wi 53706Englishx<7Bergen, K. M. Dronova, I.2007\Observing succession on aspen-dominated landscapes using a remote sensing-ecosystem approach 1395-1410Landscape Ecology2296aspens; ecosystem classification; land-cover classification; Landsat ETM; Michigan; remote sensing; secondary succession; Upper Great Lakes; University of Michigan Biological Station (UMBS) NORTHERN LOWER MICHIGAN; FOREST CLASSIFICATION; SATELLITE IMAGERY; AMERICAN ASPENS; USA; MINNESOTA; INDEXES; SITES; PINEArticleNov In the North American upper Great Lakes region, forests dominated by the aspens (Populus grandidentata Michx. - bigtooth aspen, and P. tremuloides Michx. - trembling aspen), which established after late 19th and early 20th century logging, are maturing and succession will create a new forest composition at landscape to regional scales. This study analyzed the capabilities of Landsat ETM+ remote sensing data combined with existing ecological land unit classifications to discriminate and quantify patterns of succession at the landscape scale over the 4200 ha University of Michigan Biological Station (UMBS) in northern Lower Michigan. In a hierarchical approach first multi-temporal Landsat ETM+ was used with a landscape ecosystem classification to map upland forest cover types (overall accuracy 91.7%). Next the aspen cover type was subset and successional pathways were mapped within that type (overall accuracy 89.8%). Results demonstrated that Landsat ETM+ may be useful for these purposes; stratification of upland from wetland types using an ecological land unit classification eliminated confounding issues; multi-temporal methods discriminated evergreen conifer versus deciduous understories. The Landsat ETM+ classifications were then used to quantify succession and its relationship to landform-level ecological land units. Forests on moraine and ice contact landforms are succeeding distinctly to northern hardwoods (95% and 88% respectively); those on outwash and other landforms show greater diversity of successional pathways.://000250207500011 =Cited Reference Count: 34 Cited References: *LEIC GOES, 2005, ERDAS IMAGINE 9 0 *NASA LAND PROJ SC, 2006, LANDS 7 SCI DAT US H ALBERT DA, 1995, REGIONAL LANDSCAPE E BAILEY RG, 1996, ECCOSYSTEMS GEOGRAPH BARNES BV, 1966, ECOLOGY, V47, P439 BARNES BV, 1969, SILVAE GENET, V18, P130 BARNES BV, 1982, J FOREST, V80, P493 BARNES BV, 2004, MICHIGAN TREES GUIDE DRONOVA I, 2004, THESIS U MICHIGAN DYMOND CC, 2002, REMOTE SENS ENVIRON, V80, P460 FINEGAN B, 1984, NATURE, V312, P109 FRIEDMAN SK, 2005, ECOL APPL, V15, P726 GATES FC, 1930, BOT GAZ, V90, P233 GLENNLEWIN DC, 1992, PLANT SUCCESSION THE GRAHAM SA, 1963, ASPENS PHOENIX TREES HALL FG, 1991, ECOLOGY, V72, P628 HALL RJ, 2000, FOREST CHRON, V76, P887 HARTMAN JR, 2005, FOREST ECOL MANAG, V216, P77 HE HS, 1998, ECOL APPL, V8, P1072 KEMPERMAN JA, 1976, CAN J BOT, V54, P2603 KILBURN PD, 1960, B TORREY BOT CLUB, V87, P402 MICKELSON JG, 1998, PHOTOGRAMM ENG REM S, V64, P891 MLADENOFF DJ, 1994, REMOTE SENSING GIS E, P218 PEARSALL DR, 1995, LANDSCAPE ECOSYSTEMS PERALA DA, 1990, SILVICS N AM, V2, P555 PRICE JC, 1987, REMOTE SENS ENVIRON, V21, P15 ROBERTS MR, 1985, CAN J BOT, V63, P1641 SAKAI AK, 1985, AM MIDL NAT, V113, P271 SHARIK TL, 1989, AM MIDL NAT, V122, P133 TOU JT, 1974, PATTERN RECOGNITION WOLTER PT, 1995, PHOTOGRAMM ENG REM S, V61, P1129 WOLTER PT, 2002, LANDSCAPE ECOL, V17, P133 ZIMMERMAN EA, 2003, THESIS U MICHIGAN ZOGG GP, 1995, CAN J FOREST RES, V25, P1865 0921-2973 Landsc. Ecol.ISI:000250207500011Univ Michigan, Sch Nat Resources & Environm, Ann Arbor, MI 48109 USA. Bergen, KM, Univ Michigan, Sch Nat Resources & Environm, 440 Church St, Ann Arbor, MI 48109 USA. kbergen@umich.edu idronova@umich.eduEnglishs|?d EBergerot, Benjamin Fontaine, Benoit Julliard, Romain Baguette, Michel2011pLandscape variables impact the structure and composition of butterfly assemblages along an urbanization gradient83-94Landscape Ecology261JanHow urbanization affects the distribution patterns of butterflies is still poorly known. Here we investigated the structure and composition of butterfly assemblages along an urbanization gradient within the most urbanized and densely populated region in France (AZle-de-France). Using a method issued from artificial neural networks, i.e. self-organizing maps (SOMs), we showed the existence of four typical assemblages ranging from urban-tolerant species to urban-avoider species. We identified indicator species of these assemblages: the peacock butterfly (Inachis io) in urbanized areas, the swallowtail (Papilio machaon) in sites with intermediate human pressure, or the meadow brown (Maniola jurtina), the small heath (Coenonympha pamphilus) and the gatekeeper (Pyronia tithonus) in meadows around Paris. A discriminant analysis showed that the four assemblages were mainly segregated by landscape elements, both by structural variables (habitat type, proportion of rural areas and artificial urban areas, patch surface) and functional variables (distance to the nearest wood, artificial area and park). Artificial neural networks and SOMs coupled stepwise discriminant analysis proved to be promising tools that should be added to the toolbox of community and spatial ecologists.!://WOS:000286004400008Times Cited: 0 0921-2973WOS:00028600440000810.1007/s10980-010-9537-3ڽ7 UBergès, Laurent Pellissier, Vincent Avon, Catherine Verheyen, Kris Dupouey, Jean-Luc2013EUnexpected long-range edge-to-forest interior environmental gradients439-453Landscape Ecology283Springer NetherlandsLandscape patterns Mean plant indicator value Depth-of-edge influence Patch size Land-use history Edge displacement Eutrophication 2013/03/01+http://dx.doi.org/10.1007/s10980-012-9841-1 0921-2973Landscape Ecol10.1007/s10980-012-9841-1English|? Berggren, A.2009uEffect of landscape and population variables on immune response in experimentally introduced bush-cricket populations749-757Landscape Ecology246JulDespite the growing interest in relationships between ecological variables and individual immune function, few empirical data have been available from wild populations. In this study, I assayed the immune response from 370 wild-caught bush-crickets, Metrioptera roeseli, from 20 experimentally introduced populations, by measuring individual encapsulation responses to a surgically implanted nylon monofilament. Bush-crickets descended from populations introduced into larger habitat patches showed a greater immune response when compared to individuals from smaller habitat-area introductions. Also, there was a significant positive correlation between immune response and the amount of linear elements at the introduction site. However, there was a lack of effect of population variables (i.e., propagule size and rate of population growth) on immune response. These results suggest that large-scale environmental parameters, such as patch size and connectivity, can be important for an individual's physiological health and its ability to defend against disease-causing agents. Such effects are likely to compound the negative impacts associated with isolation of sub-populations and habitat fragmentation.://000268248100004 Berggren, Asa 0921-2973ISI:00026824810000410.1007/s10980-009-9348-6k<728Bergin, T. M. Best, L. B. Freemark, K. E. Koehler, K. J.2000rEffects of landscape structure on nest predation in roadsides of a midwestern agroecosystem: a multiscale analysis131-143Landscape Ecology152(agricultural landscapes artificial nests landscape structure multiscale analysis nest predation roadsides spatial scale ARTIFICIAL GROUND NESTS IOWA ROWCROP FIELDS FOREST FRAGMENTATION HABITAT FRAGMENTATION BIRD ABUNDANCE MIGRATORY SONGBIRDS CENTRAL ILLINOIS BREEDING BIRDS AMERICAN CROWS SUCCESSArticleFebNest predation is an important cause of mortality for many bird species, especially in grassland ecosystems where generalist predators have responded positively to human disturbance and landscape fragmentation. Our study evaluated the influence of the composition and configuration of the surrounding landscape on nest predation. Transects consisting of 10 artificial ground nests each were set up in 136 roadsides in six watersheds in south-central Iowa. Nest predation on individual roadside transects ranged from 0 to 100% and averaged 23%. The relationship of landscape structure within spatially-nested landscapes surrounding each roadside transect (within 200, 400, 800, 1200, and 1600 m of the transect line) to nest predation was evaluated by using multiple regression and canonical correlation analyses. The results of this multiscale landscape analysis demonstrated that predation on ground nests was affected by the surrounding landscape mosaic and that nest predators with different-sized home ranges and habitat affinities responded to landscapes in different ways. In general, wooded habitats were associated with greater nest predation, whereas herbaceous habitats (except alfalfa/pasture) either were associated with less nest predation or were not important. Different landscape variables were important at different spatial scales. Whereas some block-cover habitats such as woodland were important at all scales, others such as rowcrops and alfalfa/pasture were important at large scales. Some strip-cover habitats such as gravel roads and paved roads were important at small scales, but others such as wooded roadsides were important at all all scales. Most landscape metrics (e.g., mean patch size and edge density) were important at large scales. Our study demonstrated that the relationships between landscape structure and predator assemblages are complex, thus making efforts to enhance avian productivity in agricultural landscapes a difficult management goal.://000084522700005 ISI Document Delivery No.: 270EP Times Cited: 27 Cited Reference Count: 86 Cited References: *IA DEP AGR LAND S, 1994, IOW CLIM REV, V8 *SAS I INC, 1994, SAS STAT US GUID REL ALLEN RA, 1968, P IOWA ACAD SCI, V75, P147 ANDERSON TW, 1984, INTRO MULTIVARIATE S ANDREN H, 1992, ECOLOGY, V73, P794 ANDREN H, 1994, OIKOS, V71, P355 ARANGOVELEZ N, 1997, BIOL CONSERV, V81, P137 ASKINS RA, 1995, SCIENCE, V267, P1956 BASORE NS, 1986, J WILDLIFE MANAGE, V50, P19 BERGIN TM, 1997, WILSON BULL, V109, P437 BEST LB, 1980, CONDOR, V82, P149 BEST LB, 1986, WILDLIFE SOC B, V14, P308 BEST LB, 1995, AM MIDL NAT, V134, P1 BEST LB, 1997, WILDLIFE SOC B, V25, P864 BOLLINGER EK, 1990, WILDLIFE SOC B, V18, P142 BRYAN GG, 1994, WILDLIFE SOC B, V22, P583 BURGER LD, 1994, J WILDLIFE MANAGE, V58, P249 CAMP M, 1993, WILDLIFE SOC B, V21, P315 CAMP M, 1994, AM MIDL NAT, V131, P347 DARROW R, 1938, T N AM WILDL C, V3, P834 DEMERS MN, 1995, CONSERV BIOL, V9, P1159 DRAPER N, 1981, APPL REGRESSION EINARSEN AS, 1956, OREGON STATE MONOGR, V10 FENSKECRAWFORD TJ, 1997, CONDOR, V99, P14 FORMAN RT, 1986, LANDSCAPE ECOLOGY FRAWLEY BJ, 1989, THESIS IOWA STATE U FRAWLEY BJ, 1991, WILDLIFE SOC B, V19, P135 FREEMARK K, 1995, LANDSCAPE URBAN PLAN, V31, P99 FREEMARK KE, 1995, ECOLOGY MANAGEMENT N, P381 FRITZELL EK, 1978, J WILDLIFE MANAGE, V42, P118 GATES JE, 1978, ECOLOGY, V59, P871 GLUECK TF, 1988, WILDLIFE SOC B, V16, P6 HERKERT JR, 1994, ECOL APPL, V4, P461 HERKERT JR, 1996, MANAGEMENT MIDWESTER, P89 HUNTER JE, 1995, CONDOR, V97, P684 JOHNSON RA, 1982, APPL MULTIVARIATE ST JOHNSON RG, 1990, J WILDLIFE MANAGE, V54, P106 JONGMAN RH, 1987, DATA ANAL COMMUNITY KOFORD RR, 1996, MANAGEMENT MIDWESTER, P68 LITVAITIS JA, 1980, J WILDLIFE MANAGE, V44, P62 MAJOR RE, 1990, IBIS, V132, P608 MANKIN PC, 1992, AM MIDL NAT, V128, P281 MARINI MA, 1995, BIOL CONSERV, V74, P203 MARTIN TE, 1988, EVOL ECOL, V2, P11 MOELLER AP, 1989, OKIOS, V56, P240 NOUR N, 1993, ECOGRAPHY, V16, P111 PEARSON SM, 1993, LANDSCAPE ECOL, V8, P3 PRIOR JC, 1991, LANDFORMS IOWA PROBST JR, 1996, MANAGEMENT MIDWESTER, P22 PULLIAM HR, 1991, AM NAT S, V137, P50 REARDEN JD, 1951, J WILDLIFE MANAGE, V15, P386 REIJNEN R, 1996, BIOL CONSERV, V75, P255 RICKLEFS RE, 1969, SMITHSON CONTRIB ZOO, V9, P1 ROBBINS CS, 1986, RES PUBL US FISH WIL, V157 ROBINSON SK, 1995, SCIENCE, V267, P1987 ROBINSON SK, 1996, MANAGEMENT MIDWESTER, P1 RODENHOUSE NL, 1995, ECOLOGY MANAGEMENT N, P269 SANDS JK, 1995, IOWA AGR STAT SEITZ LC, 1993, CONDOR, V95, P297 SHALAWAY SD, 1979, THESIS MICHIGAN STAT SHIRER HW, 1970, J MAMMAL, V51, P491 SMALL MF, 1988, OECOLOGIA, V76, P62 SMITH GJ, 1981, WILDLIFE SOC B, V9, P88 SMITH KG, 1981, USE MULTIVARIATE STA, P80 SNYDER WD, 1974, 36 COL DIV WILDL SOOTER CA, 1946, J WILDLIFE MANAGE, V10, P33 STORM GL, 1965, J WILDLIFE MANAGE, V29, P1 STUEWER FW, 1943, ECOL MONGR, V13, P203 SULLIVAN BD, 1990, J WILDLIFE MANAGE, V54, P433 SULLIVAN BD, 1992, CAN FIELD NAT, V106, P181 TREVOR JT, 1991, PRAIRIE NAT, V23, P93 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 VICKERY PD, 1992, OIKOS, V63, P281 WARNER RE, 1986, J WILDLIFE MANAGE, V50, P525 WARNER RE, 1987, WILDLIFE SOC B, V15, P221 WARNER RE, 1992, BIOL CONSERV, V59, P1 WARNER RE, 1994, CONSERV BIOL, V8, P147 WIENS JA, 1993, OIKOS, V66, P369 WILCOVE DS, 1985, ECOLOGY, V66, P1211 YAHNER RH, 1988, CONSERV BIOL, V2, P333 YAHNER RH, 1988, J WILDLIFE MANAGE, V52, P158 YAHNER RH, 1989, J WILDLIFE MANAGE, V53, P1135 YAHNER RH, 1992, WILSON BULL, V104, P162 YAHNER RH, 1996, CONSERV BIOL, V10, P285 ZAR J, 1984, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000084522700005uIowa State Univ, Dept Anim Ecol, Ames, IA 50011 USA. Bergin, TM, Iowa State Univ, Dept Anim Ecol, Ames, IA 50011 USA.English)|?`Berland, Adam Elliott, Grant P.2014kUnexpected connections between residential urban forest diversity and vulnerability to two invasive beetles141-152Landscape Ecology291JanInvasive pests pose a threat to the key environmental and social benefits provided by urban forests, and diverse tree planting is a primary management strategy for reducing pest vulnerability. For example, past urban forest losses to Dutch elm disease (DED) prompted municipal foresters to emphasize diversification, but it is unclear whether residential properties developed after the peak DED outbreak are actually more diverse than older properties. To address this issue, we inventoried all public and private trees on 150 residential properties in the Twin Cities Metropolitan Area, Minnesota, USA, and compared genus diversity on pre- and post-Dutch elm properties. We then quantified vulnerability to two current invasive pest threats, emerald ash borer (EAB) (Agrilus planipennis) and Asian longhorned beetle (ALB) (Anoplophora glabripennis), to evaluate whether higher diversity corresponds with lower pest vulnerability. We assessed vulnerability based on two fundamental urban forest metrics-frequency and size of vulnerable trees. Surprisingly, properties developed after the peak DED outbreak were less diverse than older properties. At the same time, less diverse post-Dutch elm properties exhibited low ALB vulnerability and modest EAB vulnerability, while more diverse older sites were highly susceptible to ALB. The importance of pest host specificity in characterizing urban forest vulnerability was underscored by low EAB vulnerability and high ALB vulnerability on our oldest study sites. This research highlights an apparent disconnect between the theoretical notion that higher diversity should reduce invasive pest vulnerability, and our empirical data indicating that genus diversity does not necessarily correspond with pest vulnerability.!://WOS:000330827600011Times Cited: 0 0921-2973WOS:00033082760001110.1007/s10980-013-9953-2 ڽ7dBernadou, Abel Céréghino, Régis Barcet, Hugues Combe, Maud Espadaler, Xavier Fourcassié, Vincent2013sPhysical and land-cover variables influence ant functional groups and species diversity along elevational gradients 1387-1400Landscape Ecology287Springer NetherlandsZAnts Community ecology Elevation gradient Landscape heterogeneity Neural networks Pyrenees 2013/08/01+http://dx.doi.org/10.1007/s10980-013-9892-y 0921-2973Landscape Ecol10.1007/s10980-013-9892-yEnglish=?4F.G. Bernaldez J.M. Rey Benayas C. Levassor B. Peco1989;Landscape ecology of uncultivated lowlands in central Spain3-18Landscape Ecology31Aquifer discharge habitats, Central Spain, halophilous vegetation, wetland ecology, wetland conservation, grassland ecology, wildlife conservation, saline soilsThe relationship between groundwater and landscape in representative areas of the Spanish plateaux is discussed, with special attention given to the Douro River basin. The study focusses on the transference of water and matter that is conditioned by groundwater flow systems, and also on water bodies, wet meadows, marshes, saline soils under their influence. These factors are of great importance in semiarid areas. Using photointerpretation, interviews, vegetation plots, water samples from wells and springs and soil samples, and the results of data processing (principal component analysis, shared information) we find that hydrological processes are the main controlling factor in the ecological function and variation of uncultivated lowlands. These processes include the alternation of recharge and discharge areas, the geochemical evolution of groundwater and the independent flows of the regional system. The landscapes in recharge and discharge areas are compared, as well as the influence of the evolutionary stage of the groundwater in the latter areas (glycophyte or halophyte vegetation). After observing the ecological importance of these aquifer discharges systems, the causes of their accelerated transformation are analyzed.!|?4Berry, N. J. Phillips, O. L. Ong, R. C. Hamer, K. C.2008mImpacts of selective logging on tree diversity across a rainforest landscape: the importance of spatial scale915-929Landscape Ecology238Selective logging of tropical forests imposes spatial pattern on the landscape by creating a mosaic of patches affected by different intensities of disturbance. To understand the ecological impacts of selective logging it is therefore necessary to explore how patterns of tree species composition are affected by this patchy disturbance. This study examines the impacts of selective logging on species composition and spatial patterns of vegetation structure and tree diversity in Sabah, Borneo. We compare tree diversity between logged and unlogged forest at three scales: species richness within plots, species turnover among plots, and total species richness and composition of plots combined. Logging had no effect on tree diversity measured at the smallest scale. Logged forest had a greater rate of species turnover with distance, so at a large spatial scale it supported more tree species than the relatively homogeneous unlogged area. Tree species composition also differed significantly between the two types of forest, with more small dipterocarps and large pioneers in logged forest, and more large dipterocarps in unlogged forest. Our results emphasize the importance of sampling at a sufficiently large scale to represent patterns of biodiversity within tropical forest landscapes. Large areas of production forest in SE Asia are threatened with conversion to commercial crops; our findings show that selectively logged forest can retain considerable conservation value.!://WOS:000259481900004Times Cited: 0 0921-2973WOS:00025948190000410.1007/s10980-008-9248-1A|?R CBiamonte, Estaban Sandoval, Luis Chacon, Eduardo Barrantes, Gilbert2011FEffect of urbanization on the avifauna in a tropical metropolitan area183-194Landscape Ecology262FebThe rapid and unplanned expansion of urban areas is a common pattern in neotropical developing countries. Urbanization has eliminated or drastically altered large areas of natural habitats used by the rich neotropical avifauna. In our study area, in Costa Rica's Central Valley, urbanization increased 72% in 33 years with the consequent destruction, fragmentation, and isolation of forest tracts, shade plantations, and other semi-natural habitats used by a rich avifauna. We show that over the last 16 years 32 resident species of birds have disappeared from this area. Species with specialized habitat requirements or particular life history traits (e.g., altitudinal migrants) are disproportionately represented among those birds that have disappeared from the region. Another 34 latitudinal migrants have gone undetected as nearly all habitats these species used as a stopover site during the autumn migration have disappeared; many of these migrants were very abundant 16 years earlier. Relative abundance has also decreased for most resident and migratory species that remained or visited the area. If uncontrolled urban expansion continues, we predict that the rate of extinction of the avifauna that originally inhabited this region would continue possibly increasing.!://WOS:000286474900003Times Cited: 0 0921-2973WOS:00028647490000310.1007/s10980-010-9564-0 7<7(Bianchi, Fjja Honek, A. van der Werf, W.2007Changes in agricultural land use can explain population decline in a ladybeetle species in the Czech Republic: evidence from a process-based spatially explicit model 1541-1554Landscape Ecology2210coccinella septempunctata aphid modelling landscape composition trophic interactions spatial scale SEPM COCCINELLA-SEPTEMPUNCTATA COLEOPTERA METOPOLOPHIUM-DIRHODUM LINYPHIID SPIDERS NATURAL ENEMIES LANDSCAPE APHIDS BIODIVERSITY ABUNDANCE MOVEMENT DYNAMICSArticleDecChanges in land use affect species interactions and population dynamics by modifying the spatial template of trophic interaction and the availability of resources in time and space. We developed a process-based spatially explicit model for evaluating the effects of land use on species viability by modelling foraging performance and energy sequestration in a stage structured, three-trophic population model. The model is parameterized with realistic parameters for a ladybeetle-aphid-host plant interaction, and is run in four realistic landscapes in the Czech Republic. We analysed whether changes in crop selection and fertilizer input could explain the dramatic and unexplained decline in abundance of the ladybeetle Coccinella septempunctata in the Czech Republic from 1978 to 2005. The results indicate that a major reduction in fertilizer input after the transition to a market economy, resulting in lower aphid population densities in cereal crops and negatively affecting energy sequestration, survival and reproduction of ladybeetles, provides a sufficient explanation for the observed population decline. Simulations further indicated that the population viability of C. septempunctata is highly dependent on availability of aphid prey in crops, in particular cereal, which serves as their major reproduction habitat. The results demonstrate how the abundance of naturally occurring predators, which are instrumental for biological pest control, depends upon the spatial resource template that are provided at the landscape scale.://000250632100012ISI Document Delivery No.: 227BL Times Cited: 0 Cited Reference Count: 41 Bianchi, Felix J. J. A. Honek, Alois van der Werf, Wopke 0921-2973 Landsc. Ecol.ISI:000250632100012)CSIRO Entomol, Indooroopilly, Qld 4068, Australia. Wageningen Univ, Dept Plant Sci Grp Crop & Weed Ecol, NL-6700 AK Wageningen, Netherlands. Res Inst Crop Prod, CR-16106 Prague, Czech Republic. Bianchi, FJJA, CSIRO Entomol, Meiers Rd 120, Indooroopilly, Qld 4068, Australia. felix.bianchi@csiro.auEnglish|7?2Bianchi, F. J. J. A. Goedhart, P. W. Baveco, J. M.2008EEnhanced pest control in cabbage crops near forest in The Netherlands595-602Landscape Ecology235Xnon-crop habitat biological control landscape composition natural enemies agro-ecosystems ecosystem service parasitism parasitoid spatial scale eriborus-terebrans hymenoptera different spatial scales landscape structure agricultural landscapes pseudaletia-unipuncta habitat management biological-control natural enemies host density parasitoidsMayLandscapes are composed of a multitude of habitat types which, potentially, can influence natural enemy populations. The contribution of specific habitat types to sustaining natural enemy populations in agricultural landscapes and the associated ecosystem service of pest control is not well understood. We investigated how landscape composition affected parasitism rates in 22 organic Brussels sprout fields in The Netherlands. Second and third instar larvae of Plutella xylostella were placed on experimental Brussels sprout plants in Brussels sprout fields and were recovered after two days in the field. Parasitism rates ranged between 4 and 94% and were related to landscape variables at a scale of 0.3, 1, 2 and 10 km. Univariate analysis using a generalized linear mixed model indicated that parasitism rates were positively related with area of forests at a scale of 1, 2 and 10 km, forest edges at a scale of 1 and 2 km and road verges at a scale of 1 km. Forest and road verges are likely to provide food and alternative hosts for parasitoids and are less disturbed habitats than agricultural fields. These results suggest that forests and road verges may play an important role in sustaining effective densities of parasitoids of P. xylostella in agricultural landscapes.://000254964600009-288CU Times Cited:0 Cited References Count:37 0921-2973ISI:000254964600009Bianchi, FJJA CSIRO Entomol, Meiers Rd 120, Indooroopilly, Qld 4068, Australia CSIRO Entomol, Indooroopilly, Qld 4068, Australia Alterra Green World Res, NL-6700 AA Wageningen, Netherlands Univ Wageningen & Res Ctr, NL-6700 AC Wageningen, NetherlandsDoi 10.1007/S10980-008-9219-6English|?+ Bigelow, S. W. Parks, S. A.2010TPredicting altered connectivity of patchy forests under group selection silviculture435-447Landscape Ecology253Group selection silviculture creates canopy openings that can alter connectivity in patchy forests, thereby affecting wildlife movement and fire behavior. We examined effects of group selection silviculture on percolation (presence of continuously forested routes across a landscape) in Sierra Nevada East-side pine forest in northern California, USA. Four similar to 250 ha project areas were analyzed at three map resolutions in three ways: analyzing forest cover maps for percolation before and after group-selection treatment, placing simulated group openings in forest cover maps until fragmentation occurred, and comparing project areas to neutral maps that varied in forest cover and self-adjacency. Two project areas were fragmented (i.e., did not percolate) prior to treatment, one resisted fragmentation, and the other became fragmented by treatment when analyzed at 30 m cell resolution. Median simulated openings required to create fragmentation agreed well with the actual number. There was a well-defined transition between percolating and non-percolating neutral maps; increased aggregation of forest lowered the critical value at which forests percolated. A logistic model based on these maps predicted percolation behavior of the project areas effectively, but alternative generating algorithms gave slightly different predictions. A graph of this model provides a straightforward way to visualize how close a landscape is to fragmentation based on its forest cover and aggregation. In East-side Sierran landscape, fragmentation from group-selection openings may make the landscape less hospitable to the American marten but more resistant to crown fire.!://WOS:000275122600009Times Cited: 0 0921-2973WOS:00027512260000910.1007/s10980-009-9421-1~?Billings, S. A. Gaydess, E. A.2008ZSoil nitrogen and carbon dynamics in a fragmented landscape experiencing forest succession581-593Landscape Ecology235Forest fragmentation is an increasingly common feature across the globe, but few studies examine its influence on biogeochemical fluxes. We assessed the influence of differences in successional trajectory and stem density with forest patch size on biomass quantity and quality and N transformations in the soil at an experimentally fragmented landscape in Kansas, USA. We measured N-related fluxes in the laboratory, not the field, to separate effects of microclimate and fragment edges from the effects of inherent biomass differences with patch size. We measured net N mineralization and N2O fluxes in soil incubations, gross rates of ammonification and nitrification, and microbial biomass in soils. We also measured root and litterfall biomass, C:N ratios, and delta C-13 and delta N-15 signatures; litterfall [cellulose] and [lignin]; and [C], [N], and delta C-13 and delta N-15 of soil organic matter. Rates of net N mineralization and N2O fluxes were greater (by 113% and 156%, respectively) in small patches than in large, as were gross rates of nitrification. These differences were associated with greater quantities of root biomass in small patch soil profiles (664.2 +/- 233.3 vs 192.4 +/- 66.2 g m(-2) for the top 15 cm). These roots had greater N concentration than in large patches, likely generating greater root derived organic N pools in small patches. These data suggest greater rates of N cycling in small forested patches compared to large patches, and that gaseous N loss from the ecosystem may be related to forest patch size. The study indicates that the differences in successional trajectory with forest patch size can impart significant influence on soil N transformations in fragmented, aggrading woodlands."://WOS:000254964600008 Times Cited: 0WOS:000254964600008(10.1007/s10980-008-9218-7|ISSN 0921-2973ڽ7 dBilly, Claire Birgand, François Ansart, Patrick Peschard, Julien Sebilo, Mathieu Tournebize, Julien2013nFactors controlling nitrate concentrations in surface waters of an artificially drained agricultural watershed665-684Landscape Ecology284Springer NetherlandsNNitrate Land use Isotopic nitrogen Retention Subsurface drainage Forested area 2013/04/01+http://dx.doi.org/10.1007/s10980-013-9872-2 0921-2973Landscape Ecol10.1007/s10980-013-9872-2Englishڽ7 cBiró, Marianna Czúcz, Bálint Horváth, Ferenc Révész, András Csatári, Bálint Molnár, Zsolt2013[Drivers of grassland loss in Hungary during the post-socialist transformation (1987–1999)789-803Landscape Ecology285Springer Netherlands[East-Central Europe Land-cover change Logistic GLMs Proximate and underlying driving forces 2013/05/01+http://dx.doi.org/10.1007/s10980-012-9818-0 0921-2973Landscape Ecol10.1007/s10980-012-9818-0English <79 Biswas, S. R. Wagner, H. H.2012RLandscape contrast: a solution to hidden assumptions in the metacommunity concept?621-631Landscape Ecology275<connectivity dispersal ecological theory environmental filtering landscape heterogeneity landscape model matrix metacommunity models species interaction heterogeneous metacommunities population-distributions metapopulation dynamics community ecology dispersal colonization coexistence butterflies movements frameworkMayThe metacommunity concept provides a spatial perspective on community dynamics, and the landscape provides the physical template for a metacommunity. Several aspects of landscape heterogeneity, such as landscape diversity and composition, and characteristics of the matrix between habitat patches such as habitat connectivity, and geometry of habitat patches, may moderate metacommunity processes. These aspects of landscape heterogeneity are rarely considered explicitly in the metacommunity discussion, however. We propose landscape contrast (i.e., the average dissimilarity in habitat quality between neighboring patches) as a key dimension of landscape heterogeneity. The concept of landscape contrast unifies discrete and continuous landscape representations (homogeneous, gradient, mosaic and binary) and offers a means to integrate landscape heterogeneity in the metacommunity concept. Landscape contrast as perceived by the organisms affects several fundamental metacommunity processes and may thus constrain which metacommunity models may be observed. In a review of empirical metacommunity studies (n = 123), only 22 % of studies were explicit about their underlying landscape model assumptions, with striking differences among taxonomic groups. The assumed landscape model constrained, but did not determine, metacommunity models. Integration and explicit investigation of landscape contrast effects in metacommunity studies are likely to advance ecological theory and facilitate its application to real-world conservation problems.://000303056100001-929JC Times Cited:0 Cited References Count:71 0921-2973Landscape EcolISI:000303056100001Biswas, SR Univ Toronto, Dept Ecol & Evolutionary Biol, 3359 Mississauga Rd N, Mississauga, ON L5L 1C6, Canada Univ Toronto, Dept Ecol & Evolutionary Biol, 3359 Mississauga Rd N, Mississauga, ON L5L 1C6, Canada Univ Toronto, Dept Ecol & Evolutionary Biol, Mississauga, ON L5L 1C6, CanadaDOI 10.1007/s10980-012-9732-5EnglishR<7 Blab, J. Riecken, U. Ssymank, A.1995FProposal on a criteria system for a national red data book of biotopes41-50Landscape Ecology101LRED DATA BOOK; STATUS OF BIOTOPES; REGENERATION ABILITY; NATURE CONSERVATIONArticleFeb/The proposed criteria system should be able to describe the status of biotopes and biotope complexes as exactly as possible and it should provide useful guidelines for nature conservation. The given proposal includes two criteria to estimate the threat of biotopes: 1. threat by destruction (loss of area); 2. threat by qualitative changes (creeping degradation/destruction of certain variants); supplemented by a third criterion: 3. assessment of regeneration ability. The categories and their definitions use basically the criteria system developed for the National Red Data Book of Species (Blab et al. 1984) but adjusted to the special needs of biotope evaluation. The first steps to realise a National Red Data Book of Biotopes are described and the limitations in the use in nature conservation are discussed.://A1995QL68700004 HISI Document Delivery No.: QL687 Times Cited: 4 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1995QL68700004sBLAB, J, BUNDESAMT NATURSCHUTZ,FED AUTHOR NAT CONSERVAT,DEPT HABITAT PROTECT & LANDSCAPE ECOL,D-53177 BONN,GERMANY.Englishu|?Blair, R. B. Johnson, E. M.2008wSuburban habitats and their role for birds in the urban-rural habitat network: points of local invasion and extinction? 1157-1169Landscape Ecology2310+Suburban habitats in naturally forested areas present a conundrum in the urban-rural habitat network. Typically, these habitats contain less than half of the native woodland bird species that would exist at these sites if they were not developed. They also contain more total bird species than if these sites were left in a natural state. This apparent contradiction raises the question of "How do suburban habitats function in the urban-rural habitat network?" In this study, we analyze bird distributions on three rural-to-urban gradients in different ecoregions of the United States: Oxford, Ohio; Saint Paul, Minnesota; and Palo Alto, California. All three gradients exhibit similar patterns of extinction of native species followed by invasion of common species and subsequent biotic homogenization with urbanization. This patterning suggests that suburban land uses, those represented by the intermediate levels of development on the gradients, are a point of extirpation for woodland birds as well as an entry point for invasive species into urban systems. Furthermore, there are consistent patterns in the functional characteristics of the bird communities that also shift with intensifying urbanization, providing insight on the possible mechanisms of homogenization and community structure in urban ecosystems including an increase in the number of broods per year, a shift in nesting strategies, a decrease in insectivorous individuals, an increase in granivorous individuals, and a decrease in territoriality. Consequently, it appears that there are specific traits that drive the shift in community composition in response to urban and suburban land use. These results have significant implications for improving understanding of the mechanisms of suburban community ecology and conserving birds in urban habitat networks.!://WOS:000261790600003Times Cited: 0 0921-2973WOS:00026179060000310.1007/s10980-008-9267-y<7XBlancomontero, C. A. Bennett, T. B. Neville, P. Crawford, C. S. Milne, B. T. Ward, C. R.1995ZPotential environmental and economic-impacts of turfgrass in Albuquerque, New Mexico (USA)121-128Landscape Ecology1022TURFGRASS; SATELLITE IMAGERY; ENVIRONMENTAL IMPACTArticleAprWe estimated the ecological and economic impact of urban turfgrass production in a large city. A satellite image was used to evaluate the turfgrass area of Albuquerque, New Mexico, U.S.A. Turfgrass, the major vegetation component of the city, covers 7,650 ha and represents approximately 30.0% of the metropolitan area. Of the total grass area, 85.0% exists as home lawns, 8.3% occurs in parks, and 6.7% is on golf courses. We estimated that turfgrass uses an average of 475,000 m(3) of water every day, yielding more than 4,575,000 kg of grass clippings going to the landfill in approximately 250,000 garbage bags each year. The approximate yearly cost of maintenance comes to more than $30 million which includes the potential purchase of 322,065 kg of nitrogen fertilizer, 286,110 kg of phosphorus fertilizer, 237,915 kg of potassium fertilizer, and 37,408 kg of active ingredients of insecticides. Our evaluation of the cumulative effects of domestic and municipal turfgrass production can guide the application of economically sound Integrated Pest Management strategies and enable planning for sustained use of potentially limiting resources, such as water, in semiarid environments.://A1995QX34400006 HISI Document Delivery No.: QX344 Times Cited: 3 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1995QX34400006BBLANCOMONTERO, CA, UNIV NEW MEXICO,DEPT BIOL,ALBUQUERQUE,NM 87131.English|7c XBlancomontero, C. A. Bennett, T. B. Neville, P. Crawford, C. S. Milne, B. T. Ward, C. R.1995ZPotential Environmental and Economic-Impacts of Turfgrass in Albuquerque, New-Mexico (USA)121-128Landscape Ecology1020turfgrass satellite imagery environmental impactAprWe estimated the ecological and economic impact of urban turfgrass production in a large city. A satellite image was used to evaluate the turfgrass area of Albuquerque, New Mexico, U.S.A. Turfgrass, the major vegetation component of the city, covers 7,650 ha and represents approximately 30.0% of the metropolitan area. Of the total grass area, 85.0% exists as home lawns, 8.3% occurs in parks, and 6.7% is on golf courses. We estimated that turfgrass uses an average of 475,000 m(3) of water every day, yielding more than 4,575,000 kg of grass clippings going to the landfill in approximately 250,000 garbage bags each year. The approximate yearly cost of maintenance comes to more than $30 million which includes the potential purchase of 322,065 kg of nitrogen fertilizer, 286,110 kg of phosphorus fertilizer, 237,915 kg of potassium fertilizer, and 37,408 kg of active ingredients of insecticides. Our evaluation of the cumulative effects of domestic and municipal turfgrass production can guide the application of economically sound Integrated Pest Management strategies and enable planning for sustained use of potentially limiting resources, such as water, in semiarid environments.://A1995QX34400006,Qx344 Times Cited:3 Cited References Count:0 0921-2973ISI:A1995QX34400006@Blancomontero, Ca Univ New Mexico,Dept Biol,Albuquerque,Nm 87131English `<7 %Blevins, E. Wisely, S. M. With, K. A.2011Historical processes and landscape context influence genetic structure in peripheral populations of the collared lizard (Crotaphytus collaris) 1125-1136Landscape Ecology268microsatellites flint hills tallgrass prairie collared lizard maximum-likelihood-estimation habitat fragmentation genotyping errors relative influences 2 tests abundance dispersal expansion flow microsatellitesOct^Populations at the periphery of a species' range often show reduced genetic variability within populations and increased genetic divergence among populations compared to those at the core, but the mechanisms that give rise to this core-periphery pattern in genetic structure can be multifaceted. Peripheral population characteristics may be a product of historical processes, such as founder effects or population expansion, or due to the contemporary influence of landscape context on gene flow. We sampled collared lizards (Crotaphytus collaris) at four locations within the northern Flint Hills of Kansas, which is at the northern periphery of their range, to determine the genetic variability and extent of genetic divergence among populations for ten microsatellite loci (n = 229). We found low genetic variability (average allelic richness = 3.37 +/- 0.23 SE; average heterozygosity = 0.54 +/- 0.05 SE) and moderate population divergence (average FST = 0.08 +/- 0.01 SE) among our sample sites relative to estimates reported in the literature at the core of the species' range in Texas. We also identified differences in dispersal rates among sampling locations. Gene flow within the Flint Hills was thus greater than for other peripheral populations of collared lizards, such as the Missouri glade system where most of the mesic grasslands have been converted to forest since the last glacial retreat, which appears to have greatly impeded gene flow among populations. Our findings signify the importance of considering landscape context when evaluating core-peripheral trends in genetic diversity and population structure.://000297145000006-849SI Times Cited:0 Cited References Count:70 0921-2973Landscape EcolISI:000297145000006Blevins, E Kansas State Univ, Div Biol, Lab Landscape & Conservat Ecol, 116 Ackert Hall, Manhattan, KS 66506 USA Kansas State Univ, Div Biol, Lab Landscape & Conservat Ecol, 116 Ackert Hall, Manhattan, KS 66506 USA Kansas State Univ, Div Biol, Lab Landscape & Conservat Ecol, Manhattan, KS 66506 USA Kansas State Univ, Div Biol, Conservat Genet & Mol Ecol Lab, Manhattan, KS 66506 USADOI 10.1007/s10980-011-9631-1English [|?+ !Blevins, Emilie With, Kimberly A.2011Landscape context matters: local habitat and landscape effects on the abundance and patch occupancy of collared lizards in managed grasslands837-850Landscape Ecology266JulThe distribution and abundance of a species may be simultaneously influenced by both local-scale habitat features and the broader patch and landscape contexts in which these populations occur. Different factors may influence patch occupancy (presence-absence) versus local abundance (number of individuals within patches), and at different scales, and thus ideally both occupancy and abundance should be investigated, especially in studies that seek to understand the consequences of land management on species persistence. Our study evaluated the relative influences of variables associated with the local habitat patch, hillside (patch context), and landscape context on patch occupancy and abundance of the collared lizard (Crotaphytus collaris) within tallgrass prairie managed under different fire and grazing regimes in the northern Flint Hills of Kansas, USA. Using a multi-model information-theoretic approach that accounted for detection bias, we found that collared lizard abundance and occupancy was influenced by factors measured at both the local habitat and landscape scales. At a local scale, collared lizard abundance was greatest on large rock ledges that had lots of crevices, high vegetation complexity, and were located higher up on the hillslope. At the landscape scale, collared lizard abundance and occupancy were both higher in watersheds that were burned frequently (1-2 year intervals). Interestingly, grazing only had a significant effect on occupancy and abundance within less frequently burned (4-year burn interval) watersheds. Our results suggest that, in addition to the obvious habitat needs of this species (availability of suitable rock habitat), land-management practices have the potential to influence collared lizard presence and abundance in the grasslands of the Flint Hills. Thus, mapping the availability of suitable habitat is unlikely to be sufficient for evaluating species distributions and persistence in such cases without consideration of landscape management and disturbance history.!://WOS:000291485400006Times Cited: 0 0921-2973WOS:00029148540000610.1007/s10980-011-9612-4?MBJacques Blondel Philippe Perret Marie Maistre Paula Cristina Dias1992cDo harlequin mediterranean environments function as source sink for Blue Tits (Parus caeruleus L.)?213-219Landscape Ecology63Parus caeruleus, source-sink, food resources, nestboxes, Quercus pubescens, Q. ilex, clutch size, laying date, caterpillars, habitat quality, geneticsxWe investigate whether a mosaic of habitats of different quality functions as a source-sink system for the Blue Tit Parus caeruleus L. Breeding parameters, especially laying date, clutch size and breeding success have been studied in relation to the food supply in three habitats: two habitats, one rich and one poor, next to each other on the mainland (southern France) and one poor habitat on the island of Corsica. Food resources are more abundant and are available earlier in the season in the rich habitat than in both the mainland and the island poor habitats. The timing of breeding is nicely timed on the food peak of abundance in the rich mainland habitat and in the poor insular one but tits are mistimed in the poor mainland habitat because they start to breed too early in relation to food availability. Such patterns strongly suggest that the rich mainland habitat where birds produce many fledglings functions as a source from which birds emigrate in the poor habitat which functions as a sink. These birds which are genetically programmed to breed in the source habitat become mistimed in the sink. Tits on Corsica which are isolated from any mainland population have adjusted their breeding traits on the local patterns of food availability and abundance. This hypothesis is supported by the existence of a strong genetic component of laying date which has been experimentally proved.P<7Bodin, O. Norberg, J.2007YA network approach for analyzing spatially structured populations in fragmented landscape31-44Landscape Ecology221landscape fragmentation; compartments; graphs; network analysis; Madagascar; Lemur catta; spatial resilience; natural reserves HABITAT FRAGMENTATION; LEMUR-CATTA; CONNECTIVITY; METRICS; RESILIENCE; MADAGASCAR; DISPERSAL; PERSPECTIVE; THRESHOLDS; MAMMALSArticleJanWe extend the recently proposed graph-theoretical landscape perspective by applying some network-centric methods mainly developed in the social sciences. The methods we propose are suitable to (1) identify individual habitat patches that are disproportionally high in importance in preserving the ability of organisms to traverse the fragmented landscape, and (2) find internally well-connected compartments of habitat patches that contribute to a spatial compartmentalization of species populations. We demonstrate the utility of these methods using an agricultural landscape with scattered dry-forest patches in southern Madagascar, inhabited by the ring-tailed lemur, Lemur catta. We suggest that these methods are particularly suitable in landscapes where species' traversability is not fully inhibited by fragmentation, but merely limited. These methods are potentially highly relevant in studying spatial aspects of resilience and in the design of natural reserves.://000243619800005 ISI Document Delivery No.: 127XO Times Cited: 0 Cited Reference Count: 48 Cited References: BENDER DJ, 2003, LANDSCAPE ECOL, V18, P17 BENGTSSON J, 2003, AMBIO, V32, P389 BODIN O, 2006, ECOL APPL, V16, P440 BOGAERT J, 2003, CONSERV ECOL, V7 BORGATTI SP, 1990, SOC NETWORKS, V12, P337 BORGATTI SP, 2002, UCINET WINDOWS SOFTW BROOKS CP, 2003, OIKOS, V102, P433 BRUINDERINK GG, 2003, CONSERV BIOL, V17, P549 BUNN AG, 2000, J ENVIRON MANAGE, V59, P265 CALABRESE JM, 2004, FRONT ECOL ENVIRON, V2, P529 DEGENNE A, 1999, INTRO SOCIAL NETWORK ELMQVIST T, 2003, FRONT ECOL ENVIRON, V1, P488 ELMQVIST T, 2004, PLANT TALK, P29 FREEMAN LC, 1979, SOC NETWORKS, V1, P215 FREEMAN LC, 2004, DEV SOCIAL NETWORK A GARANT D, 2005, NATURE, V433, P60 GILPIN ME, 1991, METAPOPULATION DYNAM GIRVAN M, 2002, P NATL ACAD SCI USA, V99, P7821 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HANSKI I, 1994, J ANIM ECOL, V63, P151 HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 JOLLY A, 1999, INT J PRIMATOL, V20, P359 KEITT TH, 1997, CONSERV ECOL, V1, P1 KRAUSE AE, 2003, NATURE, V426, P282 LEE JT, 2005, LANDSCAPE URBAN PLAN, V71, P17 LEIBOLD MA, 2004, LIMNOL OCEANOGR 2, V49, P1278 LEVIN SA, 2000, FRAGILE DOMINION COM LI HB, 2004, LANDSCAPE ECOL, V19, P389 LILLESAND TM, 1994, REMOTE SENSING IMAGE LOREAU M, 2003, ECOL LETT, V6, P673 LUCZKOVICH JJ, 2003, J THEOR BIOL, V220, P303 MEFFE GK, 2002, ECOSYSTEM MANAGEMENT MELIAN CJ, 2004, ECOLOGY, V85, P352 NEWMAN MEJ, 2004, PHYS REV E, V69 NYSTROM M, 2001, ECOSYSTEMS, V4, P406 POSTMA E, 2005, NATURE, V433, P65 RICKETTS TH, 2001, AM NAT, V158, P87 ROBINSON GR, 1992, SCIENCE, V257, P524 ROSHIER DA, 2001, LANDSCAPE ECOL, V16, P547 SEIDMAN S, 1983, SOC NETWORKS, V5, P92 SUSSMAN RW, 1991, AM J PHYS ANTHROPOL, V84, P43 SUTHERLAND GD, 2000, CONSERV ECOL, V4 TENGO M, 2004, THESIS STOCKHOLM U S TISCHENDORF L, 2001, LANDSCAPE ECOL, V16, P235 URBAN D, 2001, ECOLOGY, V82, P1205 VERBEYLEN G, 2003, LANDSCAPE ECOL, V18, P791 WASSERMAN S, 1994, SOCIAL NETWORK ANAL WITH KA, 1999, LANDSCAPE ECOL, V14, P73 0921-2973 Landsc. Ecol.ISI:000243619800005Stockholm Univ, Dept Syst Ecol, S-10691 Stockholm, Sweden. Bodin, O, Stockholm Univ, Dept Syst Ecol, S-10691 Stockholm, Sweden. orjan@system.ecology.su.seEnglishH|?FBoer, M. M. Sadler, R. J. Bradstock, R. A. Gill, A. M. Grierson, P. F.2008ySpatial scale invariance of southern Australian forest fires mirrors the scaling behaviour of fire-driving weather events899-913Landscape Ecology238Power law frequency-size distributions of forest fires have been observed in a range of environments. The scaling behaviour of fires, and more generally of landscape patterns related to recurring disturbance and recovery, have previously been explained in the frameworks of self-organized criticality (SOC) and highly optimized tolerance (HOT). In these frameworks the scaling behaviour of the fires is the global structure that either emerges spontaneously from locally operating processes (SOC) or is the product of a tuning process aimed at optimizing the trade-offs between system yield and tolerance to risks (HOT). Here, we argue that the dominant role of self-organized or optimised fuel patterns in constraining unplanned-fire sizes, implicit in the SOC and HOT frameworks, fails to recognise the strong exogenous controls of fire spread (i.e. by weather, terrain, and suppression) observed in many fire-prone landscapes. Using data from southern Australia we demonstrate that forest fire areas and the magnitudes of corresponding weather events have distributions with closely matching scaling exponents. We conclude that the spatial scale invariance of forest fires may also be a mapping of the meteorological forcing pattern.!://WOS:000259481900003Times Cited: 0 0921-2973WOS:00025948190000310.1007/s10980-008-9260-5?: Boerner, Ralph2012%People, Forests, and Human Perception 1235-1236Landscape Ecology278Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9749-9 0921-297310.1007/s10980-012-9749-9e?Ralph E. J. Boerner2007vRed State Ecology: Arvid Nelson, Cold War Ecology: Forests, Farms, & People in the East German Landscape, 1945–1989 793-795Landscape Ecology225 Book Review?"Ralph E.J. Boerner James G. Kooser1989ULeaf litter redistribution among forest patches within an Allegheny Plateau watershed81-92Landscape Ecology22VOhio, Allegheny Plateau, leaf litter, decomposition, landscape ecology, Neotoma valleyThis study quantified the redistribution of leaf litter in and among distinct patches within Neotoma Valley, a 73 ha watershed in the unglaciated Allegheny Plateau of Ohio. Total vertical litterfall and Quercus litterfall were greater on the Quercus dominated east slope and valley bottom than on the west slope or on the ridgetops. To measure net downslope movement of leaf litter following deposition, sets of littertraps with upslope or downslope sides open were placed at seven sites within this watershed. Net downslope litter movement was as large as vertical litterfall at all sites except the valley bottom. Quercus litter was 1.3-1.5 x as likely to be redistributed as non-Quercus litter, depending on slope. Most redistribution occurred during the January-April leafless season. On the drier, Quercus-dominated ridgetops and east slope, 14-24% of the litter falling within 20 m upslope of a trap subsequently was redistributed down into that trap. In the more mesic patches, only 1-8% of vertical litterfall was redistributed. On an area basis, the west ridgetop and the upper east slope lost the most litter to redistribution (60-80 g m-2 yr-1 dry mass); the lower east and west slope positions and the valley bottom received the greatest litter subsidies from redistribution. Donor sites lost 4.5-5.7 kg ha-1 yr-1 of N and 0.3-0.5 kg ha-1 yr-1 of P through redistributed litter; sink areas received subsidies of 2.2-6.1 kg ha-1 yr-1 N and 0.2-0.4 kg ha-1 yr-1 of P. Litter redistribution helps maintain and even accentuate the gradient of soil fertility among patches in this watershed by accelerating the normal loss of nutrients during soil development in some patches while retarding it in others.D<7CBoerner, R. E. J. Morris, S. J. Sutherland, E. K. Hutchinson, T. F.2000`Spatial variability in soil nitrogen dynamics after prescribed burning in Ohio mixed-oak forests425-439Landscape Ecology155fire landscape N mineralization oak-hickory forest restoration SOUTHERN OHIO FIRE LANDSCAPE VEGETATION PATTERNS MINERALIZATION AVAILABILITY ECOSYSTEMS RESPONSES STANDSArticleJulThis study describes the results of the application of a single dormant season prescribed fire to two southern Ohio forest sites for the purposes of restoring the ecosystem functional properties that existed in these sites prior to major human intervention (clearcutting, fire suppression, and atmospheric deposition). Each forest site was composed of three contiguous watershed units, two of which were burned in April of 1996. The forest sites differed in soil pH and available litter mass prior to the fires, and in both sites pH and available inorganic N varied among landscape positions such that inorganic C increased with increasing longterm soil moisture potential (measured as the GIS-derived Integrated Moisture Index [IMI] developed for this region). The fire temperatures at 10 cm above the litter surface were generally 150-300 degrees C, and 29-80% of the litter was consumed, depending on site and landscape position. Soil solution total inorganic N (TIN) present one month after the fires did not differ significantly from that present prior to the fires in either burned or unburned watersheds, but was consistently greater in mesic landscape positions than in more xeric ones. N mineralization potential and organic C content varied both among fires and landscape positions. At the site which burned at higher intensity, soil N mineralization and TIN were both decreased by fire. At the less intensely burned site, fire resulted in increased TIN in the soils from the more xeric landscape position, and greater soil organic C in soils from the intermediate soil moisture areas. Path analysis produced models for fire-induced changes in C and N dynamics capable of explaining 26-69% of the observed variation using combinations of landscape and fire behavior. Losses of N to volatilization from these single fires were generally < 1 kg N/ha, and thus could not be expected to ameliorate the effects of atmospheric N deposition in these sites.://000088036700003 ISI Document Delivery No.: 331UH Times Cited: 13 Cited Reference Count: 52 Cited References: *SAS I, 1995, STAT AN SYST US GUID ALLISON LE, 1965, METHODS SOIL ANAL 2, P1367 ARBUCKLE JL, 1995, AMOS USERS GUIDE BARNES TA, 1998, SOUTH J APPL FOR, V22, P138 BARRETT SW, 1997, INTGTR370 USDA FOR S BENNING TL, 1995, LANDSCAPE ECOL, V10, P337 BOERNER REJ, 1982, BIOSCIENCE, V32, P187 BOERNER REJ, 1983, OECOLOGIA, V59, P129 BOERNER REJ, 1984, CAN J FOREST RES, V14, P794 BOERNER REJ, 1988, AM MIDL NAT, V120, P108 BOERNER REJ, 2000, RESTORING MIXED OAK BROSE PH, 1998, CAN J FOREST RES, V28, P331 BURNS PY, 1952, YALE FORESTRY B, V50 COLE KL, 1992, NAT AREA J, V12, P177 DAY GM, 1953, ECOLOGY, V34, P329 DEBANO LF, 1979, SOIL SCI SOC AM J, V43, P504 DECKER KLM, 1999, CAN J FOREST RES, V29, P232 DESELM HR, 1991, P 6 BIENN SO SILV RE, P409 DOLAN RW, 1994, P INDIANA ACAD SCI, V103, P25 DUDLEY JL, 1993, AM MIDL NAT, V130, P286 FONTEYN PJ, 1984, AM MIDL NAT, V112, P246 FOWELLS HA, 1934, SOIL SCI, V34, P175 FRANKLIN SB, 1997, J APPL ECOL, V34, P613 GRABNER K, 1997, 11 CENTR HARDW FOR C, P202 GRIFFITH AL, 1946, INDIAN FORESTRY B, V130 HARDY CC, 1996, INTGTR341 USDA FOR S HAYWARD F, 1938, J FOREST, V36, P478 HENDERSHOT WH, 1993, METHODS SOIL ANAL 2, P141 HUTCHINS RB, 1976, SOIL SCI, V121, P234 IVERSON LR, 1997, LANDSCAPE ECOL, V12, P331 IVERSON LR, 2000, RESTORING MIXED OAK JORGENSEN JR, 1971, SOIL SCI SOC AM P, V35, P806 KNOEPP JD, 1993, CAN J FOREST RES, V23, P2263 MORRIS SJ, 1998, FOREST ECOL MANAG, V103, P129 MORRIS SJ, 1998, LANDSCAPE ECOL, V13, P215 PHILLIPS MJ, 1985, SOIL SCI SOC AM J, V49, P1563 PIETIKAINEN J, 1993, CAN J FOREST RES, V23, P1275 RAISON RJ, 1979, PL SOIL, V51, P73 RIEBOLD RJ, 1971, PRESCR BURN S P ASH, P11 SCHIMEL D, 1985, ECOLOGY, V66, P276 STOUT W, 1933, OHIO STATE ARCH HIST, V42, P72 SUTHERLAND EK, 1997, P 11 CENTR HARDW FOR, P172 SUTHERLAND EK, 2000, IN PRESS RESTORING M TURNER MG, 1994, LANDSCAPE ECOL, V9, P59 VANCE ED, 1984, SOIL SCI SOC AM J, V48, P184 VOGT KA, 1991, AGR ECOSYST ENVIRON, V35, P171 WAGLE RF, 1972, ECOLOGY, V53, P118 WEBB BG, 1991, P 6 BIENN SO SILV RE, P418 WELLS CG, 1971, PRESCRIBED BURNING S, P86 WHITNEY GG, 1994, COASTAL WILDERNESS F WILLIAMS M, 1989, AM THEIR FOREST WOLFE JN, 1949, OHIO BIOL SURV B, V41, P1 0921-2973 Landsc. Ecol.ISI:000088036700003Ohio State Univ, Dept Ecol Evolut & Organismal Biol, Columbus, OH 43210 USA. Boerner, REJ, Ohio State Univ, Dept Ecol Evolut & Organismal Biol, 1735 Neil Ave, Columbus, OH 43210 USA.English/۽7 Boerner, RalphE J.2013IE. J. Blakely and A. Carbonell (eds.): Coastal regions and climate change993-994Landscape Ecology285Springer Netherlands 2013/05/01+http://dx.doi.org/10.1007/s10980-013-9876-y 0921-2973Landscape Ecol10.1007/s10980-013-9876-yEnglish|?/-Boeye, Jeroen Kubisch, Alexander Bonte, Dries2014HHabitat structure mediates spatial segregation and therefore coexistence593-604Landscape Ecology294AprvUnderstanding the mechanisms driving diversity in nature is an important and ongoing challenge in our changing world. To efficiently protect ecosystem diversity it is crucial to explain why and how species coexist. Over the last decades models explaining species coexistence have increased in complexity but usually don't incorporate a detailed spatial context. However, spatial structure has been shown to affect species coexistence and habitat deterioration is one of the biggest threats to biodiversity. We therefore explore a spatially explicit two-species model and assess the effects of habitat structure on species coexistence using a wide diversity of fractal landscapes. Each species is specialized in a particular habitat type. We find that landscape structure has a major influence on the stability and constitution of a two species system and may be sufficient to explain the coexistence of two species. Well connected and highly structured habitat configurations allow spatial segregation of both species and this decreases local interspecific competition; in our model this is the most important process stabilizing coexistence.!://WOS:000333533800004Times Cited: 1 0921-2973WOS:00033353380000410.1007/s10980-014-0010-6|<7(Bogaert, J. Myneni, R. B. Knyazikhin, Y.2001TA mathematical comment on the formulae for the aggregation index and the shape index87-90Landscape Ecology171aggregation index index redundancy landscape metric perimeter pixel edge pixel geometry shape index spatial pattern COMPACTNESS PERIMETER PATTERNSArticleIn a recent paper [Landscape Ecol. 15: 591-601 (2000)] He et al. described an aggregation index AI(i), to measure pixel aggregation within a single class i. We show that the commonly used shape index SIi is related to the proposed aggregation metric as SIi = Phi(A(i)) + AI(i)(1 - Phi(A(i))), with Phi(A(i)) dependent on class area A(i) only. Moreover, it is shown that the normalized shape index, SIi*, equals (1 - AI(i)). We conclude that AI(i) does not provide any information not provided by SIi, or SIi*.://000176014400007 ISI Document Delivery No.: 559FF Times Cited: 5 Cited Reference Count: 9 Cited References: BOGAERT J, 2000, APPL MATH COMPUT, V111, P71 BRIBIESCA E, 1997, COMPUT MATH APPL, V33, P1 HE HS, 2000, LANDSCAPE ECOL, V15, P591 JOHNSSON K, 1995, INT J GEOGR INF SYST, V9, P211 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MILLER JN, 1997, LANDSCAPE ECOL, V12, P137 MILNE BT, 1991, QUANTITATIVE METHODS, P199 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PEARSON SM, 1999, LANDSCAPE ECOLOGICAL, P335 0921-2973 Landsc. Ecol.ISI:000176014400007Boston Univ, Dept Geog, Climate & Vegetat Res Grp, Boston, MA 02215 USA. Bogaert, J, Boston Univ, Dept Geog, Climate & Vegetat Res Grp, Boston, MA 02215 USA. jan.bogaert@ua.ac.beEnglish C? Bohnet, Iris Roebeling, Peter Williams, Kristen Holzworth, Dean van Grieken, Martijn Pert, Petina Kroon, Frederieke Westcott, David Brodie, Jon2011Landscapes Toolkit: an integrated modelling framework to assist stakeholders in exploring options for sustainable landscape development 1179-1198Landscape Ecology268Springer NetherlandsEarth and Environmental ScienceZAt present, stakeholders wishing to develop land use and management change scenarios at the landscape scale and to assess their corresponding impacts on water quality, biodiversity and economic performance, must examine the output of a suite of separate models. The process is not simple and presents a considerable deterrent to making such comparisons and impedes the development of more sustainable, multifunctional landscapes. To remedy this problem, we developed the Landscapes Toolkit, an integrated modelling framework that assists natural resource managers, policy-makers, planners and local communities explore options for sustainable landscape development. The Landscapes Toolkit links spatially-explicit disciplinary models, to enable integrated assessment of the water quality, biodiversity and economic outcomes of stakeholder-defined land use and management change scenarios. We use the Tully–Murray catchment in the Great Barrier Reef region of Australia as a case study to illustrate the development and application of the Landscapes Toolkit. Results show that the Landscapes Toolkit strikes a satisfactory balance between the inclusion of component models that sufficiently capture the richness of some key aspects of social-ecological system processes and the need for stakeholders to understand and compare the results of the different models. The latter is a prerequisite to making more informed decisions about sustainable landscape development. The flexibility of being able to add additional models and to update existing models is a particular strength of the Landscapes Toolkit design. Hence, the Landscapes Toolkit offers a promising modelling framework for supporting social learning and adaptive management through participatory scenario development and evaluation as well as being a tool to guide planning and policy discussions at the landscape scale.+http://dx.doi.org/10.1007/s10980-011-9640-0 0921-297310.1007/s10980-011-9640-0|? Bohnet, Iris C.2010Integrating social and ecological knowledge for planning sustainable land- and sea-scapes: experiences from the Great Barrier Reef region, Australia 1201-1218Landscape Ecology258OctpThe integration of social and ecological knowledge has been identified as one of the key issues and research priorities in landscape ecology. However, research into the tools and processes that support knowledge integration for planning sustainable land- and sea-scapes is largely lacking. To fill this gap, Bohnet and Smith (Landsc Urban Plan 80:137-152, 2007) developed a social-ecological planning framework based on a holistic landscape concept which I applied in the Tully-Murray basin to test the framework's transferability and effectiveness for knowledge integration in a water quality improvement planning context in the Great Barrier Reef (GBR) region, Australia. In this paper I present the context in which the Tully Water Quality Improvement Plan (WQIP) was developed, the tools and processes applied during the three planning stages to achieve knowledge integration, and the results from this exercise. I then discuss the transferability and effectiveness of the framework using criteria identified to assess collaborative planning processes, outputs and outcomes, such as collaborative science and social and political capital. While many social outcomes such as the creation of partnerships between multiple-stakeholders, including Traditional Owners, local farmers, industry, government, community groups, schools, and the wider public, have been achieved, the research also highlights some of the challenges related to multiple-stakeholder relations. Further research into the roles and responsibilities of multiple-stakeholders for knowledge integration in developing and managing sustainable land- and sea-scapes is recommended.!://WOS:000281725700006YTimes Cited: 2 10th International Congress of Ecology Aug 16-21, 2009 Brisbane, AUSTRALIA 0921-2973WOS:00028172570000610.1007/s10980-010-9504-z?<Janine Bolliger Felix Kienast Reto Soliva Gillian Rutherford2007^Spatial sensitivity of species habitat patterns to scenarios of land use change (Switzerland) 773-789Landscape Ecology225Agricultural decline - Habitat suitability maps - Species habitat distribution modelling - Scenarios of land use change - Switzerland yLong-term societal trends which include decreasing population in structurally poorer regions and changes in agricultural policies have been leading to land abandonment in various regions of Europe. One of the consequences of this development includes spontaneous forest regeneration of formerly open-land habitats with likely significant effects on plant and animal diversity. We assess potential effects of agricultural decline in Switzerland (41,000 km2) and potential impacts on the spatial distribution of seven open-land species (insects, reptile, birds) under land-use change scenarios: (1) a business-as-usual scenario that extrapolates trends observed during the last 15 years into the future, (2) a liberalisation scenario with limited regulation, and (3) a lowered agricultural production scenario fostering conservation. All scenarios were developed in collaboration with socio-economists. Results show that spontaneous reforestation is potentially minor in the lowlands since combinations of socio-economic (better accessibility), topographic (less steep slopes), and climatic factors (longer growing seasons) favour agricultural use and make land abandonment less likely. Land abandonment, spontaneous reforestation, and subsequent loss of open-land, however, are potentially pronounced in mountainous areas except where tourism is a major source of income. Here, socio-economic and natural conditions for cultivation are more difficult, leading to higher abandonment and thus reforestation likelihood. Evaluations for open-land species core habitats indicate pronounced spatial segregation of expected landscape change. Habitat losses (up to 59%) are observed throughout the country, particularly at high elevation sites in the Northern Alps. Habitat gains under the lowered agricultural production scenario range between 12 and 41% and are primarily observed for the Plateau and the Northern Alps. g|?;.Bolliger, Janine Lander, Tonya Balkenhol, Niko2014GLandscape genetics since 2003: status, challenges and future directions361-366Landscape Ecology293Mar7A scientific symposium on landscape genetics, held at the 2013 IALE Europe Conference in Manchester UK (September 2-8, 2013), highlighted status, challenges and future avenues in the field. Key topics included analytical aspects in landscape genetics, conceptual progress and application of landscape genetics for conservation management. First, analytical aspects referred to statistical relationships between genetic and landscape data. It was suggested that linear mixed models or Bayesian approaches are particularly promising due to more appropriate and powerful ways for analyzing landscape effects on genetic variation. Second, supplementing neutral genetic variation with adaptive genetic variation is very promising. However, research needs to go beyond the identification of genomic regions under selection and provide information on the ecological function of adaptive genetic regions. Conceptually, endogenous processes (e. g., life-history attributes such as dispersal) require consideration as supplementary factors in shaping the genetic variation in addition to landscapes. Also, the temporal dimension in landscapes for both the past and the future should be given increased attention as the genetic responses to landscape change may be non-simultaneous, resulting in time lags. As for applied conservation management, landscape genetics can provide important baseline information such as basic data on species movement in a spatial context, assessments of the spatial need for management efforts, or evaluations of the effectiveness of already existing management measures.!://WOS:000331935500001Times Cited: 2 0921-2973WOS:00033193550000110.1007/s10980-013-9982-x<7u!Bolstad, P. V. Swank, W. Vose, J.1998NPredicting Southern Appalachian overstory vegetation with digital terrain data271-283Landscape Ecology135Ndeciduous forests community composition prediction landscape DEM terrain shapeArticleOct Vegetation in mountainous regions responds to small-scale variation in terrain, largely due to effects on both temperature and soil moisture. However there are few studies of quantitative, terrain-based methods for predicting vegetation composition. This study investigated relationships between forest composition, elevation, and a derived index of terrain shape, and evaluates methods for predicting forest composition. Trees were measured on 406 permanent plots within the boundaries of the Coweeta Hydrologic Lab, located in the Southern Appalachian Mountains of western North Carolina, USA. All plots were in control watersheds, without human or major natural disturbance since 1923. Plots were 0.08 ha and arrayed on transects, with approximately 380 meters between parallel transects. Breast-height diameters were measured on all trees. Elevation and terrain shape (cove, ridge, sideslope) were estimated for each plot. Density (trees/ha) and basal area were summarized by species and by forest type (cove, xeric oak-pine, northern hardwoods, and mixed deciduous). Plot data were combined with a digital elevation data (DEM), and a derived index of terrain shape at two sampling resolutions: 30 m (US Geological Survey), and 80 m (Defense Mapping Agency) sources. Vegetation maps were produced using each of four different methods: 1) linear regression with and without log transformations against elevation and terrain variables combined with cartographic overlay, 2) kriging, 3) co-kriging, and 4) a mosaic diagram. Predicted vegetation was compared to known vegetation at each of 77 independent, withheld data points, and an error matrix was determined for each mapping method. We observed strong relationships between some species and elevation and/or terrain shape. Cove and xeric oak/pine species basal areas were positively and negatively related to concave landscape locations, respectively, while species typically found in the mixed deciduous and northern hardwood types were not. Most northern hardwood species occurred more frequently and at higher basal areas as elevation increased, while most other species did not respond to elevation. The regression and mosaic diagram mapping approaches had significantly higher mapping accuracies than kriging and co-kriging. There were significant effects of DEM resolution on map accuracy, with maps based on 30 m DEM data significantly more accurate than those based on 80 m data. Taken together, these results indicate that both the mapping method and terrain data resolution significantly affect the resultant vegetation maps, even when using relatively high resolution data. Landscape or regional models based on 100 m or lower resolution terrain data may significantly under-represent terrain-related variation in vegetation composition.://000165537200001 ISI Document Delivery No.: V2651 Times Cited: 24 Cited Reference Count: 38 Cited References: *USGS, 1990, DIG EL MOD DAT US GU, V5 ABER JD, 1993, ECOL MODEL, V67, P37 AGREN GI, 1991, ECOL APPL, V1, P118 BAILEY RG, 1980, USDA FOR SERV MISC P, V1391 BAILEY RG, 1996, ECOSYSTEM GEOGRAPHY BARBOUR M, 1988, N AM TERRESTRIAL VEG BARNES BV, 1991, TEMPERATE DECIDUOUS BIERI R, 1965, CASTANEA, V30, P205 BLASZCZYNSKI JS, 1997, PHOTOGRAMM ENG REM S, V63, P183 BRAUN EL, 1950, DECIDUOUS FOREST E N BURROUGH PA, 1986, PRINCIPLES GEOGRAPHI CAIN SA, 1931, BOT GAZ, V91, P22 CRESSIE N, 1991, STAT SPATIAL DATA DAVIS FW, 1990, LANDSCAPE ECOL, V4, P69 DAY FP, 1974, ECOLOGY, V34, P329 DAY FP, 1988, FOREST HYDROLOGY ECO DOUGLASS JE, 1988, FOREST HYDROLOGY ECO ELLIOT KJ, 1997, UNPUB CANADIAN J FOR EYRE FH, 1980, FOREST COVER TYPES U GARREN KH, 1943, BOT REV, V9, P617 GOLDEN MS, 1981, AM MIDLAND NATURALIS, V10 HARSHBERGER JW, 1903, BOT GAZ, V36, P241 HATCHER RD, 1988, FOREST HYDROLOGY ECO LORIMER CG, 1980, ECOLOGY, V61, P1169 MCNAB WH, 1989, FOREST SCI, V35, P91 MEINERS TM, 1984, PLANT SOIL, V80, P171 NELSON TC, 1955, ECOLOGY, V36, P352 NICHOLS GE, 1935, ECOLOGY, V16, P403 OOSTING HJ, 1955, BOT GAZ, V116, P340 PEET R, 1988, N AM TERRESTRIAL VEG PHILLIPS DL, 1985, FOREST SCI, V31, P226 RUNKLE JR, 1982, ECOLOGY, V63, P1533 SKIDMORE AK, 1989, INT J GEOGR INF SYST, V3, P323 STEPHENSON SL, 1974, CASTANEA, V39, P278 SWANK WT, 1988, FOREST HYDROLOGY ECO SWIFT LW, 1988, FOREST HYDROLOGY ECO WHITTAKER RH, 1956, ECOL MONOGR, V26, P1 WOODS FW, 1959, ECOLOGY, V40, P349 0921-2973 Landsc. Ecol.ISI:000165537200001Univ Minnesota, Dept Forest Resources, St Paul, MN 55108 USA. USFS, SFES, Coweeta Hydrol Lab, Otto, NC 28763 USA. Bolstad, PV, Univ Minnesota, Dept Forest Resources, St Paul, MN 55108 USA.English? Gordon B. Bonan1989`Environmental factors and ecological processes controlling vegetation patterns in boreal forests111-130Landscape Ecology32)boreal forest, gap model, forest dynamicsAn individual tree model of forest dynamics was used to examine the environmental and ecological factors controlling forest vegetation patterns in upland boreal forests of North America. Basic life history traits that characterized the regeneration, growth, and death of individual trees were combined with species-specific responses to important environmental factors. This model simulated forest structure and vegetation patterns in conifer, hardwood, and mixed conifer-hardwood forests and woodlands in several bioclimatic sub-regions of the North American boreal forest zone. Model testing identified the processes and parameters required to understand the ecology of upland boreal forests and weaknesses in our current understanding of these processes. These factors included climate, solar radiation, soil moisture, soil temperature and permafrost, the forest floor organic layer, nutrient availability, forest fires, and insect outbreaks. Model testing also identified which of these factors were important in each bioclimatic sub-region.<7ABond, G. Burnside, N. G. Metcalfe, D. J. Scott, D. M. Blamire, J.2005pThe effects of land-use and landscape structure on barn owl (Tyto alba) breeding success in southern England, UK555-566Landscape Ecology205barn owl; cluster analysis; GIS; habitat mosaic; landscape structure; nest box; pellet analysis SET-ASIDE; HABITAT; INTENSIFICATION; DIET; FOODArticleJulTo aid effective conservation and management there is a need to understand the effect of landscape on species ecology. The aim of this research was to assess the effect of landscape parameters on breeding success of barn owls throughout the Rother and Arun River catchments, Sussex, UK. We used a Geographic Information System to describe the habitat mosaic and landscape structure within an estimated home range area of 3 km(2) around 85 artificial nest box sites. Results showed that land cover was less heterogeneous at successful sites, with home ranges dominated by a few habitat types of regular patch shapes. Unsuccessful nesting sites had significantly more improved grassland, suburban land and wetlands than successful sites. Cluster analysis and Principle Components Analysis was used to assess the similarity of the habitat mosaic within these areas and pellet analysis was undertaken to assess barn owl diet and prey availability. Ten prey species were recovered from pellets, field vole (Microtus agrestis), common shrews (Sorex araneus) and house mice (Mus musculus) making up nearly 90% of recoveries. However box sites varied in relative proportions of small mammal, and hence prey availability. Results indicated that land use and landscape structure can affect breeding success in barn owls. Higher levels of poor quality small mammal habitat were associated with unsuccessful sites. However, at a landscape scale, the habitat mosaic across the study area lacked variation, limiting analysis and clear correlations between habitat type and positive breeding success, suggesting that a finer scale was needed in future studies utilising this approach.://000232205600005 HISI Document Delivery No.: 969AK Times Cited: 0 Cited Reference Count: 41 Cited References: *ITE, 2000, LAND COV 2000 DAT *RAMS CONV WETL, 1999, AR VALL *RAMS CONV WETL, 2003, RAMS PROF UK AR VALL *ROYAL SOC PROT BI, 2003, BARN OWLS ANDRIES AM, 1994, ECOGRAPHY, V17, P278 BARR CJ, 1993, COUNTRYSIDE SURVEY 1 BLAMIRE J, 2001, REV ARUN ROTHER BARN BUNN DS, 1982, BARN OWL EVERITT BS, 2001, CLUSTER ANAL FARINA A, 1998, PRINCIPLES METHODS L FIRBANK LG, 1993, ITE RES PUBLICATION, V7 FORMAN R, 1995, LAND MOSAICS ECOLOGY FOWLER J, 1999, PRACTICAL STAT FIELD GLUE DE, 1974, BIRD STUDY, V21, P200 GREEN BH, 1990, GRASS FORAGE SCI, V45, P365 HARRIS S, 1990, SPECIES DISPERSAL AG, P159 JACOB J, 2003, MAMM BIOL, V68, P102 JEANNERET P, 1999, HETEROGENEITY LANDSC KENT M, 1992, VEGETATION DESCRIPTI LAPENA N, 2003, LANDSCAPE ECOL, V18, P265 LOVE R, 2000, MAMMAL REV, V30, P107 MARTI CD, 1999, J RAPTOR RES, V33, P118 MARTINEZ JA, 1999, J ORNITHOL, V140, P93 MEEK WR, 2003, BIOL CONSERV, V109, P271 PERCIVAL SM, 1990, 57 BTO SALVATI L, 2002, J RAPTOR RES, V36, P224 SHAWYER CR, 1987, BARN OWL BRIT ISLES SHAWYER CR, 1994, BARN OWL HAMLYN SPEC SHAWYER CR, 1995, INVESTIGATION BARN O STOATE C, 2001, J ENVIRON MANAGE, V63, P337 TATTERSALL FH, 1997, ACTA THERIOL, V42, P329 TATTERSALL FH, 2000, BIOL CONSERV, V96, P123 TAYLOR IR, 1994, BARN OWLS PREDATOR P TEW TE, 1994, HEDGEROW MANAGEMENT, P80 TOME R, 2001, ORNIS FENNICA, V78, P109 TOMS MP, 2001, BIRD STUDY 1, V48, P23 VALKAMA J, 1995, ORNIS FENNICA, V72, P49 WAITE S, 2000, STAT ECOLOGY PRACTIC WEBSTER JA, 1973, SEASONAL VARIATION M, V32, P122 WIDEN P, 1994, J AVIAN BIOL, V25, P219 YALDEN DW, 1990, ANAL OWL PELLETS 0921-2973 Landsc. Ecol.ISI:000232205600005OUniv Brighton, Div Biol, BERG, Brighton BN2 4GJ, E Sussex, England. Univ Brighton, Sch Environm, BERG, Brighton BN2 4GJ, E Sussex, England. Sussex Downs Conservat Board, Rother Valley Project, Midhurst GU29 9QX, W Sussex, England. Scott, DM, Univ Brighton, Div Biol, BERG, Brighton BN2 4GJ, E Sussex, England. dawn.scott@brighton.ac.ukEnglish<7 Boone, R. B.2007SEffects of fragmentation on cattle in African savannas under variable precipitation 1355-1369Landscape Ecology229subdivision; precipitation; ecosystem modeling; coefficient of variation; cattle; Savanna; Shrub expansion; Kenya; Tanzania; South Africa NGORONGORO-CONSERVATION-AREA; HABITAT FRAGMENTATION; SOUTH-AFRICA; EAST-AFRICA; RAINFALL; SYSTEMS; BIODIVERSITY; SUBDIVISION; VARIABILITY; HERBIVORESArticleNovCattle move to access patches that vary in forage quantity and quality. Fragmentation can prevent animals from reaching patches. I used an integrative ecosystem model applied to three African landscapes to explore the sensitivity of cattle populations to fragmentation (here, changes in populations as parcel areas decreased) under different precipitation patterns. I hypothesized that low and high precipitation would yield populations relatively insensitive to fragmentation, intermediate precipitation would yield more sensitive populations, and more variable inter-annual precipitation would reduce sensitivity to fragmentation. Precipitation data were altered to yield averages of 100-1,000 mm year(-1) and inter-annual coefficients of variation of 0-60%. A 1,000 km(2) landscape in each area was divided into progressively smaller parcels and simulations conducted for each parcel. Rainfall at 100 mm year(-1) supported low populations that were insensitive to fragmentation. Populations peaked at rainfall levels similar to those observed, and declined under higher precipitation, due in-part to shrub expansion. Fragmenting landscapes caused up to a 62% decline in cattle. High inter-annual variation in precipitation reduced sensitivity to fragmentation when precipitation was above that observed. The pattern was opposite when precipitation was below what was observed. Cattle on the landscape with fine-scale heterogeneity were relatively insensitive to fragmentation, and those on the heterogeneous but coarse-grained landscape were extremely sensitive. Fragmentation in landscapes where populations are sensitive will require more intensive inputs to offset losses, and changes in the frequency of extreme weather associated with climate change will alter the sensitivity of some populations to fragmentation.://000250207500008 Cited Reference Count: 48 Cited References: *FAO, 2001, PAST NEW MILL ANDREN H, 1994, OIKOS, V71, P355 ASH A, 2004, AFRICAN J RANGE FORA, V21, P137 ASH AJ, 1996, RANGELAND J, V18, P216 BEKURE S, 1991, MAASAI HERDING ANAL BOON RB, IN PRESS RESOURCE EC BOONE RB, 2000, INTEGRATED MANAGEMEN BOONE RB, 2002, AFR J ECOL, V40, P138 BOONE RB, 2004, AFR J RANGE FORAGE S, V21, P79 BOONE RB, 2004, CLIMATIC CHANGE, V64, P317 BOONE RB, 2005, CONSERVATION SOC, V3, P150 BOONE RB, 2005, RANGELAND ECOL MANAG, V58, P523 BOONE RB, 2006, HUM ECOL, V34, P809 BOONE RB, 2007, J ARID ENVIRON, V70, P495 COE MJ, 1976, OECOLOGIA, V22, P341 CONRAD V, 1941, MON WEATHER REV, V69, P5 COUGHENOUR MB, 1985, ANN MO BOT GARD, V72, P852 COUGHENOUR MB, 1992, ECOLOGICAL INDICATOR, V1, P787 CUSHMAN SA, 2006, BIOL CONSERV, V128, P231 DAVIS SA, 2002, PHILOS T ROY SOC B, V357, P1249 DONCASTER CP, 2001, J ANIM ECOL, V70, P91 EAST R, 1984, AFR J ECOL, V22, P245 EASTERLING DR, 2000, B AM METEOROL SOC, V81, P417 EASTMAN JL, 2001, GLOBAL CHANGE BIOL, V7, P797 ELLIS J, 1994, BIOSCIENCE, V44, P340 ELLIS JE, 1988, J RANGE MANAGE, V41, P450 ELLIS JE, 1993, RANGE ECOLOGY DISEQU ELLIS JE, 1998, DRYLANDS SUSTAINABLE, P97 EWERS RM, 2005, BIOL REV, V81, P147 FAHRIG L, 2003, ANNU REV ECOL EVOL S, V34, P487 FORMAN RTT, 1995, LAND MOSAICS GALVIN KA, 2004, AFRICAN J RANGE FORA, V21, P183 GALVIN KA, 2006, HUM ECOL, V34, P155 JAMES CD, 1999, J ARID ENVIRON, V41, P87 LANGE RT, 1985, T ROYAL SOC S AUSTR, V109, P167 LEWONTIN RC, 1969, P NATIONAL ACADEMY S, V62, P1056 LUDWIG JA, 2001, ENVIRON INT, V27, P167 MASON SJ, 1999, CLIMATIC CHANGE, V41, P249 MCCABE JT, 1995, UNPUB NATL GEOGRAPHI MDUMA SAR, 1999, J ANIM ECOL, V68, P1101 NIAMIRFULLER M, 1999, MANAGING MOBILITY AF NICHOLSON SE, 1980, MON WEA REV, V108, P473 PHILLIPSON J, 1975, E AFR WILDL J, V13, P171 RITCHIE ME, 1999, NATURE, V400, P557 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 THORNTON PK, 2003, AGR SYST, V76, P601 THORNTON PK, 2004, CLIMATE RES, V26, P33 THORNTON PK, 2006, AGR SYST, V87, P331 0921-2973 Landsc. Ecol.ISI:000250207500008Colorado State Univ, Nat Resource Ecol Lab, Ft Collins, CO 80523 USA. Boone, RB, Colorado State Univ, Nat Resource Ecol Lab, 1499 Campus Delivery,B234 NESB, Ft Collins, CO 80523 USA. rboone@nrel.colostate.eduEnglish&<7Boone, R. B. Hunter, M. L.1996kUsing diffusion models to simulate the effects of land use on grizzly bear dispersal in the Rocky Mountains51-64Landscape Ecology111DRESOURCE-EXTRACTION INDUSTRIES; FOOD-HABITS; MOVEMENTS; CONSERVATIONArticleFebN Timber harvests proposed for Trail Creek Watershed, in southwestern Montana, U.S.A., have been opposed because grizzly bear (Ursus arctos horribilis) dispersal from northern Montana wildernesses into the Greater Yellowstone Ecosystem may be less likely. We used an individual-based model to simulate grizzly bear responses to: 1) region-level management practices represented by ownership patterns, and 2) watershed-level changes in habitat availability due to proposed harvests and road building. We assigned permeabilities (i.e., values that represent how easily a bear can move through a patch) to ownership blocks (region-level) and habitat patches (watershed-level) based upon a literature review, and used a correlated random-walk diffusion model to simulate movements. Simulated bears were placed into rasterized landscapes in a stratified random manner. At the regional level, bears moved less than or equal to 1500 times (i.e., approximate to 1530 km), and their destinations were tallied. At the watershed level, the number of moves required for bears to leave the watershed were tallied. Sensitivity analyses were used to determine the variability of the results with respect to changes in some parameters of interest (i.e,, permeabilities of private lands, harvest permeabilities, and disturbance indices). With the permeability of private land set at 50 (range: 0 to 99), simulated grizzlies did not disperse from the Scapegoat and Bob Marshall Wildernesses into Yellowstone National Park (0 of 10000 simulated individuals), Under the assumptions of this model, a linkage between the wildernesses in northern Montana and Yellowstone does not appear to exist. However, a significant number of simulated grizzlies (41%) dispersed from Anaconda Pintler Wilderness, which is near Trail Creek Watershed, into the wilderness ES in eastern Idaho. A linkage may exist between these sites. At the watershed-level, removal of forest habitat under proposed Harvest I (1.77% of the watershed cut) led to simulated grizzlies using slightly more moves (i.e., less than or equal to 5.6%, P = 0.042) to exit the watershed than under existing conditions. Harvests of 3.5% of the watershed (planned Harvest Il) did not alter the number of moves required to exit the watershed (P = 0.068). When disturbances associated with roads and harvests were also examined, large increases in number of movements required to exit the watershed occurred (less than or equal to 151%, P = 0.002). These analyses suggest that grizzly bears would be disturbed while timber harvests were ongoing, but that long-term changes in movement would not occur if roads were closed following harvests. The analyses demonstrate the utility of applying individual-based diffusion models to landscape-level movements of animals, and identifies the need for telemetry studies to determine movement rates through specific habitats.://A1996UN74400005 ISI Document Delivery No.: UN744 Times Cited: 24 Cited Reference Count: 42 Cited References: 1975, FED FEG, V40, P31736 *US DEP AGR, 1990, TRAIL CREEK FIN ENV *US DEP AGR, 1991, TRAIL CREEK SUPPL IN *US DEP INT FISH W, 1982, GRIZZL BEAR REC PLAN AGEE JK, 1989, PHOTOGRAMM ENG REM S, V55, P1637 ALMACK JA, 1986, P GRAZZL BEAR HAB S, P150 AUNE K, 1983, ROCKY MOUNTAIN FRONT BEAN MJ, 1983, EVOLUTION NATIONAL W BLANCHARD BM, 1991, BIOL CONSERV, V58, P41 BRATKOVICH AA, 1986, P GRIZZL BEAR HAB S, P180 BUECHNER M, 1987, BIOL CONSERV, V41, P57 BUTTERFIELD BR, 1986, P GRIZZL BEAR HAB S, P58 CRAIGHEAD JJ, 1980, MONOGR, V1 CRAIGHEAD JJ, 1982, WILDLIFE WILDLANDS I, V1 DAVIS DL, 1986, P GRIZZL BEAR HAB S, P158 DESPAIN DG, 1986, P GRIZZL BEAR HAB S, P230 ELGMORK K, 1978, BIOL CONSERV, V13, P81 FORMAN RTT, 1986, LANDSCAPE ECOLOGY HILLIS M, 1986, P GRIZZL BEAR HAB S, P176 HUSTON M, 1988, BIOSCIENCE, V38, P682 JOHNSON AR, 1992, LANDSCAPE ECOL, V7, P63 KNIGHT RR, 1980, BEARS THEIR BIOL MAN, P1 KNIGHT RR, 1987, YELLOW STONE GRIZZLY KNIGHT RR, 1988, WILDLIFE SOC B, V16, P121 MACCRACKEN JG, 1986, 12 U ID ID FOR WILDL MANGEL M, 1988, DYNAMIC MODELING BEH MATTSON DJ, 1986, P GRIZZL BEAR HAB S, P135 MATTSON DJ, 1991, CAN J ZOOL, V69, P1619 MATTSON DJ, 1991, CONSERV BIOL, V5, P364 MCLELLAN BN, 1986, P GRIZZL BEAR HAB S, P163 MCLELLAN BN, 1988, J APPL ECOL, V25, P451 MCLELLAN BN, 1989, J APPL ECOL, V26, P371 MCLELLAN BN, 1989, WILDLIFE SOC B, V17, P269 MILLER SD, 1982, J WILDLIFE MANAGE, V46, P869 PICTON HD, 1986, INT C BEAR RES MANAG, V6, P7 SERVHEEN C, 1983, J WILDLIFE MANAGE, V47, P1026 SERVHEEN C, 1993, ENDANGERED SPECIES T, V18, P10 SERVHEEN C, 1995, BIOL CONSERV, V71, P261 STAMPS JA, 1987, AM NAT, V129, P533 TURCHIN P, 1991, ECOLOGY, V72, P1253 YOUNG DL, 1986, P GRIZZLY BEAR HABIT, P217 ZAGER PE, 1980, THESIS U MONTANA MIS 0921-2973 Landsc. Ecol.ISI:A1996UN74400005_Boone, RB, UNIV MAINE,MAINE COOPERAT FISH & WILDLIFE RES UNIT,5755 NUTTING HALL,ORONO,ME 04469.Englishk<7;Boone, R. B. Krohn, W. B.2000FPredicting broad-scale occurrences of vertebrates in patchy landscapes63-74Landscape Ecology151fragmentation heterogeneous landscapes patch occupancy predicted distributions ranges species model assessment species richness species/habitat associations sprawl BIOLOGICAL DIVERSITY SPECIES RICHNESS HABITAT MODELS OAK WOODLANDS UNITED-STATES DISTRIBUTIONS MARTEN FORESTArticleJan"Spatially explicit landscape-scale models that predict species distributions, where patches of habitat are shown as having potential to be occupied or unoccupied, are increasingly common. To successfully use such data, one should understand how these predicted distributions are created and how their relative accuracies are assessed. Geographic ranges, defined upon observations (e.g., atlases), literature review, and expert review, are a primary data layer. A map of land cover is created, often from interpretation of satellite imagery or other remotely-sensed data. Species/habitat associations are defined based upon a literature review and expert review, describing associations for habitats derived from the cover map. Included as ancillary associations are how species relate to physical features, where appropriate, such as elevation and hydrography. The three layers of information (range, land cover, and associations) are merged, often using raster-based algebraic statements that exclude unused habitats or patches outside the range of a species. The accuracy of predictions for a suite of species is typically assessed with surveys by comparing the species predicted to occur in an area to the species observed. Omission (i.e., present in species lists but not predicted) and commission (i.e., predicted but not present in lists) errors are reported. Errors may be due to many sources. For example, ranges of species change, cover types may be misidentified, species/habitat associations may be incorrect or change, or species may be rare and unlikely to be seen in surveys and judged in-error even though the species may be present. An example is given of an appropriate use of broad-scale species predicted distributions, in which patterns and threats to Maine terrestrial vertebrate diversity are summarized.://000083830400006 ISI Document Delivery No.: 258GN Times Cited: 11 Cited Reference Count: 63 Cited References: *GAP AN PROGR, 1998, GAP AN PROGR PROGR D *LAND ACQ PRIOR AD, 1997, FIN REP REC LAND ACQ *MAIN AUD SOC, 1996, SOL FUT MAIN WOODS W *MAIN FOR SERV, 1990, FOR REG CLEARC STAND, CH20 *NO FOR LANDS COUN, 1994, FIND COMM GROUND CON *RESTORE, 1994, MAIN WOODS PROP NAT AVERY ML, 1990, CALIF FISH GAME, V76, P103 BLOCK WM, 1994, WILDLIFE SOC B, V22, P549 BOONE RB, 1996, THESIS U MAINE ORONO BOONE RB, 1998, MAINE GAP ANAL VER 1 BOONE RB, 1998, MAINE GAP ANAL VER 2 BOONE RB, 1999, ECOL APPL, V9, P835 BOONE RB, 1999, GAP ANAL B, V7, P41 BROWN JH, 1995, MACROECOLOGY BUTTERFIELD BR, 1994, MAPPING DIVERSITY NA, P53 CHAPIN TG, 1998, CONSERV BIOL, V12, P1327 CONGALTON RG, 1999, ASSESSING ACCURACY R CONROY MJ, 1996, ECOL APPL, V6, P763 COUTURE R, 1993, USDI FISH WILDLIFE S, V16, P49 CSUTI B, 1996, GAP ANAL LANDSCAPE A, P135 DEGRAAF RM, 1986, NE108 NE FOR EXPT ST DOBSON AP, 1997, SCIENCE, V275, P550 DUBEC LJ, 1990, J WILDLIFE MANAGE, V54, P594 EDWARDS TC, 1996, CONSERV BIOL, V10, P263 EDWARDS TC, 1998, REMOTE SENS ENVIRON, V63, P73 ELLIOT CA, 1987, THESIS U MAINE ORONO FINLEY RW, 1976, ORIGINAL VEGETATION GAWLER SC, 1996, BIOL DIVERSITY MAINE HALL LS, 1997, WILDLIFE SOC B, V25, P173 HENGEVELD R, 1992, DYNAMIC BIOGEOGRAPHY JENNINGS MD, 1993, USDI FISH WILDLIFE S, V2 KELLETT MJ, 1989, NEW MAINE WOODS RESE KROHN WB, 1992, WILDLIFE SOC B, V20, P441 KROHN WB, 1996, GAP ANAL LANDSCAPE A, P147 KROHN WB, 1997, CONSERVATION PUBLIC KROHN WB, 1998, MAINE GAP ANAL FINAL LITVAITIS JA, 1993, CONSERV BIOL, V7, P866 LIU JG, 1995, CONSERV BIOL, V9, P62 LIVINGSTON SA, 1990, J WILDLIFE MANAGE, V54, P644 MARSCHNER FJ, 1974, ORIGINAL VEGETATION MASTER L, 1996, GAP ANAL LANDSCAPE A, P171 MASTER LL, 1993, GAP ANAL B, V3, P6 MAURER BA, 1994, GEOGRAPHIC POPULATIO MCMAHON JS, 1990, ATLAS NATIVE WOODY P MERRILL EH, 1996, WYOMING GAP ANAL GEO MILLER RI, 1994, MAPPING DIVERSITY NA MLADENOFF DJ, 1998, J WILDLIFE MANAGE, V62, P1 MORRISON ML, 1992, WILDLIFE HABITAT REL OHARA F, 1997, COST SPRAWL ROBBINS CS, 1986, USDI FISH WILDLIFE S, V157 ROOT T, 1988, ECOLOGY, V69, P330 SCHAMBERGER M, 1982, FWSOBS8210 USDI FISH SCHAMBERGER M, 1982, T N AM WILDL NAT RES, V47, P154 SCHULZ TT, 1992, WILDLIFE SOC B, V20, P74 SCOTT JM, 1987, BIOSCIENCE, V37, P782 SCOTT JM, 1993, WILDLIFE MONOGR, P1 SCOTT JM, 1996, GAP ANAL LANDSCAPE A SMITH KG, 1996, GAP ANAL LANDSCAPE A, P163 STRAW JA, 1994, INT ASS FISH WILDLIF, P96 THOMAS JW, 1979, USDA FOREST SERVICE, V553 VANHORNE B, 1991, FISH WILDLIFE RES, V8 VICKERMAN S, 1996, GAP ANAL LANDSCAPE A, P195 WHITE D, 1992, CARTOGR GEOGR INFORM, V19, P5 0921-2973 Landsc. Ecol.ISI:000083830400006Univ Maine, Dept Wildlife Ecol, Orono, ME 04469 USA. Boone, RB, Univ Maine, Dept Wildlife Ecol, 5755 Nutting Hall, Orono, ME 04469 USA.EnglishI|?W MBorda-de-Agua, Luis Navarro, Laetitia Gavinhos, Catarina Pereira, Henrique M.2011eSpatio-temporal impacts of roads on the persistence of populations: analytic and numerical approaches253-265Landscape Ecology262FebRoads can have drastic impacts on wildlife populations. Although there is wide recognition of the negative impacts caused by roads and a wealth of practical studies, there is a lack of theoretical work that can be used to predict the impact of road networks or to implement mitigation measures. Here, using Skellam's diffusion model, we develop analytic and numerical approaches to analyze the impact of road networks on the survival of populations. Our models show that the viability of a population is determined not only by road density but also by the size and shape of patches. Accordingly, we studied the minimum size of a patch to sustain a population with given diffusion and growth parameters. We provide simple formulas to estimate the minimum patch size, and illustrate the importance of shape with square and rectangular patches. Our models also allow the estimation of time to extinction after road construction for a population in a patch smaller than that of the minimum size. Finally, using numerical computations we illustrate how the spatial arrangement of fences strongly affects both the equilibrium density and the spatial distribution of populations, and that not all fence layouts are equally effective. We anticipate that our methods provide a tool to assess the impact of geometrical features of road networks on wildlife and that they can be used to design mitigation measures to prevent the decline and extinction of populations in an anthropogenically disturbed landscape.!://WOS:000286474900008Times Cited: 0 0921-2973WOS:00028647490000810.1007/s10980-010-9546-2ڽ7 5Bormpoudakis, Dimitrios Sueur, Jérôme Pantis, JohnD2013jSpatial heterogeneity of ambient sound at the habitat type level: ecological implications and applications495-506Landscape Ecology283Springer NetherlandsxAmbient sound Habitat acoustics Habitat type Soundscape Heterogeneity Lake Kerkini Habitat choice Ecological informatics 2013/03/01+http://dx.doi.org/10.1007/s10980-013-9849-1 0921-2973Landscape Ecol10.1007/s10980-013-9849-1English?  R. Bornkamm1987Allochthonous ecosystems119-122Landscape Ecology12/ecosystems, allochthonous, desert, hemerobiosisIn extreme deserts with precipitation of less than 10-20 mm/yr, biocoenoses occur which are void of producers but show ecosystem functions such as food chains and energy flow. Since they are fed by the importation of allochthonous organic material the term ‘allochthonous ecosystems’ is proposed to designate these systems. The application of this term to other incomplete ecosystems without producers is discussed.|? Boscolo, D. Metzger, J. P.2009cIs bird incidence in Atlantic forest fragments influenced by landscape patterns at multiple scales?907-918Landscape Ecology247AugThe degree to which habitat fragmentation affects bird incidence is species specific and may depend on varying spatial scales. Selecting the correct scale of measurement is essential to appropriately assess the effects of habitat fragmentation on bird occurrence. Our objective was to determine which spatial scale of landscape measurement best describes the incidence of three bird species (Pyriglena leucoptera, Xiphorhynchus fuscus and Chiroxiphia caudata) in the fragmented Brazilian Atlantic forest and test if multi-scalar models perform better than single-scalar ones. Bird incidence was assessed in 80 forest fragments. The surrounding landscape structure was described with four indices measured at four spatial scales (400-, 600-, 800- and 1,000-m buffers around the sample points). The explanatory power of each scale in predicting bird incidence was assessed using logistic regression, bootstrapped with 1,000 repetitions. The best results varied between species (1,000-m radius for P. leucoptera; 800-m for X. fuscus and 600-m for C. caudata), probably due to their distinct feeding habits and foraging strategies. Multi-scale models always resulted in better predictions than single-scale models, suggesting that different aspects of the landscape structure are related to different ecological processes influencing bird incidence. In particular, our results suggest that local extinction and (re)colonisation processes might simultaneously act at different scales. Thus, single-scale models may not be good enough to properly describe complex pattern-process relationships. Selecting variables at multiple ecologically relevant scales is a reasonable procedure to optimise the accuracy of species incidence models.://000268430900005 Boscolo, Danilo Metzger, Jean P. 0921-2973ISI:00026843090000510.1007/s10980-009-9370-8<7Bosschieter, L. Goedhart, P. W.2005\Gap crossing decisions by reed warblers (Acrocephalus scirpaceus) in agricultural landscapes455-468Landscape Ecology204barriers; birds; connectivity; corridors; fragmentation; movement; radio telemetry; translocation experiment BREEDING DISPERSAL; HABITAT CORRIDORS; SMALL MAMMALS; FOREST BIRDS; MOVEMENTS; CONNECTIVITY; ARUNDINACEUS; BUTTERFLIES; PATTERNS; PATCHESArticleMayTo meet the need for research on the requirements for corridors for marshland birds, this study set out to quantify gap crossing decisions made by reed warblers moving through the landscape. In three experiments, reed warblers were released into landscape situations with different gap sizes and their movement towards reed patches fringing a watercourse were monitored. In all experiments, most birds flew over the smallest gap towards the nearest reed patch. In the experiment with two gap sizes, the probability of crossing a gap was a function of the ratio between distances to the reed patches. In the experiment with increasing gap sizes, most birds crossed the smaller gaps frequently. Near the bigger gaps, birds did not cross the gaps; instead, they only crossed the watercourse repeatedly. In the third experiment with more realistic landscape configurations.. the birds preferred nearby non-reed landscape elements to more distant reed patches. It is concluded that reed warblers were reluctant to cross gaps wider than 50 m. The results suggest that the presence and size of gaps in reed patches affect reed warblers' local gap-crossing decisions: when given a choice, the birds prefer to cross the smallest gap. Furthermore, reed warblers may be directed towards suitable marshlands by creating corridors of reed vegetation with gaps no wider than 50 m. The surrounding agricultural landscape and the presence of trees and ditches could decrease the reluctance to cross gaps in corridors.://000233035100007 ISI Document Delivery No.: 980RE Times Cited: 2 Cited Reference Count: 53 Cited References: *NPP, 1990, NAT CONS FISH *NPP, 2000, NAT POL PLAN NAT PEO ANDREASSEN HP, 1996, J APPL ECOL, V33, P555 BEIER P, 1995, J WILDLIFE MANAGE, V59, P228 BEIER P, 1998, CONSERV BIOL, V12, P1241 BELISLE M, 2001, CONSERV ECOL, V5 BELISLE M, 2001, ECOLOGY, V82, P1893 BENNETT AF, 1999, LINKAGES LANDSCAPE R BENSCH S, 1991, J ANIM ECOL, V60, P857 BOROWIEC M, 1992, ACTA ZOOL CRACOV, V35, P315 BOWNE DR, 1999, LANDSCAPE ECOL, V14, P53 CONRADT L, 2000, P ROY SOC LOND B BIO, V267, P1505 DENBOER T, 2000, 47 DIR NAT DESROCHERS A, 1997, CONSERV BIOL, V11, P1204 FISCHER S, 1994, VOGELWARTE, V37, P183 FOPPEN RPB, 2000, CONSERV BIOL, V14, P1881 GOBEIL JF, 2002, OIKOS, V98, P447 GRAVELAND J, 1998, ARDEA, V86, P187 GREENWOOD PJ, 1982, ANNU REV ECOL SYST, V13, P1 HAAS CA, 1995, CONSERV BIOL, V9, P845 HADDAD N, 2000, CONSERV BIOL, V14, P738 HADDAD NM, 1999, ECOL APPL, V9, P612 HANSKI I, 1994, J ANIM ECOL, V63, P151 HARRISON S, 1997, METAPOPULATION BIOL INGLIS G, 1992, CONSERV BIOL, V6, P581 LEERDAM A, 1992, NATUUR UIT MOERAS NA LEVINS R, 1970, LECT MATH LIFE SCI, V2, P77 LIMA SL, 1996, TRENDS ECOL EVOL, V11, P131 MACDONALD DW, 2001, DISPERSAL, P358 MACHTANS CS, 1996, CONSERV BIOL, V10, P1366 MANSERGH IM, 1989, J WILDLIFE MANAGE, V53, P701 MAURITZEN M, 1999, J APPL ECOL, V36, P215 MCCULLAGH P, 1989, GEN LINEAR MODELS MERRIAM G, 1990, LANDSCAPE ECOL, V4, P123 MORTON ML, 1991, ORNIS SCAND, V22, P98 NOORDWIJK AJV, 1995, J APPL STAT, V22, P683 OPDAM P, 1990, SPECIES DISPERSAL AG OPDAM P, 1991, LANDSCAPE ECOL, V5, P93 OPDAM P, 2002, LANDSCAPE ECOLOGY, V16, P767 OSIECK ER, 1994, 12 VOG NED PARADIS E, 1998, J ANIM ECOL, V67, P518 PITHER J, 1998, OIKOS, V83, P166 RUCKELSHAUS M, 1997, CONSERV BIOL, V11, P1298 RUFENACHT B, 1995, BIOL CONSERV, V71, P269 SAUNDERS DA, 1991, NATURE CONSERVATION, V2 SUTCLIFFE OL, 1996, CONSERV BIOL, V10, P1359 VOS CC, 2001, AM NAT, V157, P24 VOS CC, 2002, APPL LANDSCAPE ECOLO, P84 VOS, 1999, THESIS WAGENINGEN U WAUTERS L, 1994, OIKOS, V69, P140 WEGNER JF, 1979, J APPL ECOL, V16, P349 WHITE GC, 1990, ANAL WILDLIFE RADIOT WIENS JA, 2001, DISPERSAL, P96 0921-2973 Landsc. Ecol.ISI:000233035100007=Alterra Green World Res, NL-6700 AA Wageningen, Netherlands. Univ Wageningen & Res Ctr, Dept Plant Ecol & Nat Conservat, NL-6700 HB Wageningen, Netherlands. Wageningen UR, NL-6700 AC Wageningen, Netherlands. Bosschieter, L, Alterra Green World Res, POB 47, NL-6700 AA Wageningen, Netherlands. laura.bosschieter@wur.nlEnglish<7-Bossenbroek, J. M. Wagner, H. H. Wiens, J. A.2005^Taxon-dependent scaling: beetles, birds, and vegetation at four North American grassland sites675-688Landscape Ecology206canonical correspondence analysis; Colorado; hierarchical-variance partitioning; Kansas; species-environment relationships; Prairie CANONICAL CORRESPONDENCE-ANALYSIS; GRADIENT ANALYSIS; GROUND BEETLES; SOIL TEXTURE; COLEOPTERA; PATTERNS; TENEBRIONIDAE; LANDSCAPE; DIVERSITY; PRAIRIEArticleSepBecause organisms respond to the environment at different scales, it is important to develop ways of determining the appropriate scales for a specific ecological process and organism. We consider whether the relative importance of different scales is associated with organism mobility, and whether this relationship is independent of landscape characteristics. We observed abundances of particular species for vascular plants, ground-dwelling beetles and breeding birds along eight 2-km transects of 40 sampling stations each, distributed over four sites along the regional gradient from shortgrass steppe in central Colorado to tallgrass prairie in central Kansas. For each transect and taxonomic group, the relative importance of factors measured at the trap scale (I in; soil texture and hardness, vegetation height, bare ground), at the local scale (10 m; density of shrubs and cacti) and at the landscape scale (30 m; Landsat 7 TM spectral bands, slope and elevation) was assessed using hierarchical canonical variance partitioning with forward selection of explanatory variables. Plant, beetle and bird community composition was explained by environmental factors measured at all three scales. Factor influence was more consistent between transects and between plants and beetles for the more homogeneous landscapes of the shortgrass steppe than for the more heterogeneous landscapes of the tallgrass prairie. We conclude that, independent of the mobility of a taxonomic group, factors at several scales are important in explaining community composition. The importance of different scales shifts along a regional gradient, and the variability between sites is high even for nearby sites.://000233600700004 &ISI Document Delivery No.: 988KS Times Cited: 0 Cited Reference Count: 34 Cited References: *ESRI, 2002, ARCGIS VERS 7 1 *NAT CONS, 2001, CONS DES *US FISH WILDL SER, 1999, CONS NAT AM *USGS, 1998, US GEOL SURV DEM 7 5 ADDICOTT JF, 1987, OIKOS, V49, P340 ALLEN TFH, 1982, HIERARCHY PERSPECTIV BORCARD D, 1992, ECOLOGY, V73, P1045 BROWN JH, 1984, AM NAT, V124, P255 BROWN JH, 1998, BIOGEOGRAPHY BUCKLAND ST, 1993, DISTANCE SAMPLING ES COTTAM G, 1956, ECOLOGY, V37, P451 CUSHMAN SA, 2002, LANDSCAPE ECOL, V17, P637 DODD MB, 2002, PLANT ECOL, V158, P127 DUFRENE M, 1997, ECOL MONOGR, V67, P345 HANSEN AJ, 1992, LANDSCAPE ECOL, V7, P163 KINRAIDE TB, 1984, SW NATURALIST, V29, P277 KOIVULA M, 2003, ENTOMOL FENNICA, V14, P1 LARSEN KI, 2003, PEDOBIOLOGIA, V47, P288 LEGENDRE P, 1998, NUMERICAL ECOLOGY MCCULLEY RL, 2004, SOIL SCI SOC AM J, V68, P106 MCCUNE B, 1997, ECOLOGY, V78, P2617 MCINTYRE NE, 1997, AM MIDL NAT, V138, P230 OHMANN JL, 1998, ECOL MONOGR, V68, P151 PALMER MW, 1993, ECOLOGY, V74, P2215 PANZER R, 1998, CONSERV BIOL, V12, P693 RICKLEFS RE, 1987, SCIENCE, V235, P167 RYKKEN JJ, 1997, CONSERV BIOL, V11, P522 SCHNEIDER DC, 1994, QUANTITATIVE ECOLOGY STAPP P, 1997, AM MIDL NAT, V137, P298 STOHLGREN TJ, 1995, VEGETATIO, V117, P113 TERBRAAK CJF, 1986, ECOLOGY, V67, P1167 WEEKS RD, 1997, ENTOMOL EXP APPL, V82, P267 WHITTAKER RH, 1975, COMMUNITIES ECOSYSTE WIENS JA, 1989, FUNCT ECOL, V3, P385 0921-2973 Landsc. Ecol.ISI:000233600700004Colorado State Univ, Dept Biol, Ft Collins, CO 80523 USA. Colorado State Univ, Grad Degree Program Ecol, Ft Collins, CO 80523 USA. Bossenbroek, JM, Univ Notre Dame, Dept Biol Sci, Notre Dame, IN 46556 USA. Bossenbroek.1@nd.eduEnglish <7'Bossuyt, B. Honnay, O.2006Interactions between plant life span, seed dispersal capacity and fecundity determine metapopulation viability in a dynamic landscape 1195-1205Landscape Ecology218clonality; extinction risk; population growth rate; RAMAS/Metapop; seed dispersal; stage structured model SCALE SPATIAL DYNAMICS; SUCCESSIONAL LANDSCAPES; EXTINCTION; PERSISTENCE; POPULATIONS; MODEL; ECOSYSTEMS; EVOLUTION; REMNANTArticleNovgClassical metapopulation models do not account for temporal changes in the suitability of habitat patches. In reality, however, the carrying capacity of most habitat types is not constant in time due to natural succession processes. In this study, we modeled plant metapopulation persistence in a successional landscape with disappearing and emerging habitat patches, based on a realistic dune slack landscape at the Belgian-French coast. We focused on the effects of the variation of different plant traits on metapopulation persistence in this changing landscape. Therefore, we used a stage based stochastic metapopulation model implemented in RAMAS/Metapop, simulating a large variation in plant traits but keeping landscape characteristics such as patch turnover rate and patch life span constant. The results confirm the conclusions of earlier modeling work that seed dispersal distance and seed emigration rate both have an important effect on metapopulation persistence. We also found that high population growth rate or high recruitment considerably decreased the extinction risk of the metapopulation. Additionally, a long plant life span had a strong positive effect on metapopulation persistence, irrespective of the plant's dispersal capacity and population growth rate. Plant species that invest in life span require less investment in offspring and dispersal capacity to avoid extinction, even in dynamic landscapes with deterministic changes in habitat quality. Moreover, metapopulations of long-lived plant species were found to be much less sensitive to high levels of environmental stochasticity than short-lived species.://000242089300003 tISI Document Delivery No.: 106GP Times Cited: 0 Cited Reference Count: 36 Cited References: AKCAKAYA HR, 2002, RAMAS METAPOP VIABIL AKCAKAYA HR, 2004, CONSERV BIOL, V18, P526 AMARASEKARE P, 2001, J THEOR BIOL, V209, P333 BAGUETTE M, 2004, BASIC APPL ECOL, V5, P213 BOSSUYT B, 2003, J VEG SCI, V14, P781 BOUGHTON D, 2002, CONSERV ECOL, V6 BRACHET S, 1999, J THEOR BIOL, V198, P479 BROWN JH, 1977, ECOLOGY, V58, P445 DRAKE JM, 2004, ECOL LETT, V7, P26 DURRETT R, 1994, THEOR POPUL BIOL, V46, P363 EHRLEN J, 1998, APPL VEG SCI, V1, P29 EHRLEN J, 2002, OIKOS, V98, P308 EHRLEN J, 2003, J ECOL, V91, P316 ELLNER SP, 2003, ECOLOGY, V84, P882 ERIKSSON O, 1994, ECOL RES, V9, P257 ERIKSSON O, 1996, OIKOS, V77, P248 ERIKSSON O, 2000, GLOBAL ECOL BIOGEOGR, V9, P443 ERIKSSON O, 2001, INTEGRATING ECOLOGY, P157 FRECKLETON RP, 2002, J ECOL, V90, P419 FRECKLETON RP, 2003, J ECOL, V91, P321 HANSKI I, 1994, J ANIM ECOL, V63, P151 HASTINGS A, 2003, SCIENCE, V301, P1525 HONNAY O, 2005, OIKOS, V108, P427 HUSBAND BC, 1996, J ECOL, V84, P461 JOHNSON MP, 2000, OIKOS, V88, P67 JOHST K, 2002, OIKOS, V98, P263 KEYMER JE, 2000, AM NAT, V156, P478 KNEITEL JM, 2004, ECOL LETT, V7, P69 LEVINS R, 1969, B ENTOMOL SOC AM, V15, P237 LINDBORG R, 2004, ECOLOGY, V85, P1840 MATLACK GR, 2004, J ECOL, V92, P1025 OLIVIERI I, 1995, AM NAT, V146, P202 OUBORG NJ, 2004, ECOLOGY GENETICS EVO, P447 PERRY JN, 1993, J ECOL, V81, P453 RONCE O, 1997, AM NAT, V150, P220 VERHEYEN K, 2004, ECOLOGY, V85, P3302 0921-2973 Landsc. Ecol.ISI:000242089300003 Univ Ghent, Dept Biol, Terr Ecol Unit, B-9000 Ghent, Belgium. Katholieke Univ Leuven, Dept Biol, Div Plant Systemat & Ecol, B-3001 Heverlee, Belgium. Bossuyt, B, Univ Ghent, Dept Biol, Terr Ecol Unit, Ledeganckstr 35, B-9000 Ghent, Belgium. beatrijs.bossuyt@Ugent.beEnglish|?^!Bouchard, Mathieu Auger, Isabelle2014}Influence of environmental factors and spatio-temporal covariates during the initial development of a spruce budworm outbreak111-126Landscape Ecology291JanyRecurrent and synchronous spruce budworm (SBW) outbreaks have important impacts in boreal and sub-boreal forest ecosystems of North America. This study examines the early phase of an outbreak that was developing across a 268,000 km(2) area over a period of 9 years (2003-2011). The territory was subdivided in 225 km(2) cells, and the relative influence of forest composition, elevation, forest age, average degree-days and soil drainage were examined during three development phases of the outbreak: initial epicenter location, relatively long-distance spread (cell-to-cell expansion), and expansion inside individual cells (within-cell expansion). The results indicate that elevation is the most determinant variable for initial epicenter location. Other variables that were identified as important for outbreak development by previous studies, such as forest composition and average degree-days, were not so important during this phase. However, forest composition and average degree-days were important factors during the cell-to-cell and within-cell expansion phases. Separating outbreak development in distinct phases also allowed to integrate phase-specific spatial and temporal covariates that were highly significant in the models, such as distance from previous year defoliations during the cell-to-cell expansion phase, and the proportion of defoliated stands during the preceding year for the within-cell expansion phase. Overall, this study provides limited evidence that patterns of SBW outbreak expansion could be altered by reducing host tree species abundance in the forest [mainly balsam fir (Abies balsamea) in this region]. More generally, this study suggests that the influence of environmental variables on SBW outbreak development is clearly phase-dependent, and that this landscape-level, process-based approach could be useful to forecast insect outbreak development in forest ecosystems.!://WOS:000330827600009Times Cited: 0 0921-2973WOS:00033082760000910.1007/s10980-013-9966-x D|7/Boucher, Y. Arseneault, D. Sirois, L. Blais, L.2009{Logging pattern and landscape changes over the last century at the boreal and deciduous forest transition in Eastern Canada171-184Landscape Ecology2420balsam fir ecosystem-based management historical forestry maps land cover change logging constraint preindustrial forest physical environment timber floating reference conditions balsam fir new-brunswick land-use european settlement natural variability pre-settlement old-growth quebec disturbance standsFeb$Forestry practices associated with the industrial era (since similar to 900) have altered the natural disturbance regimes and greatly impacted the world's forests. We quantified twentieth century logging patterns and regional scale consequences in three sub-boreal forest landscapes of Eastern Canada (117,000, 49,400 and 92,300 ha), comparing forestry maps depicting age and forest cover types for early industrial (1930) and present-day (2000) conditions. Results were similar for the three landscapes, indicating large-scale forest change during the twentieth century. In 1930, previous logging activities had been concentrated in the lowlands and along the main hydrographical network, as compared to a more even distribution over the landscapes in 2000, reflecting a decreasing influence of the environmental constraints on forest harvesting. In 1930, old-aged forests (> 100 years) accounted for more than 75% of the unlogged areas of the three landscapes, as compared to less than 15% for the present-day conditions. Logging practices have thus inverted the stand age distribution of the landscapes that are currently dominated by young and regenerating stands. The 1930 forest cover types showed a clear relationship with elevation, with conifers located in the lowlands and mixed and deciduous stands restricted to the upper slopes. Between 1930 and 2000, 58-64% of the conifer areas transformed to mixed and deciduous forests, such that no clear altitudinal relationships remained in 2000. We conclude that twentieth century logging practices have strongly altered the preindustrial vegetation patterns in our study area, to the point that ecosystem-based management strategies should be developed to restore conifer dominance, altitudinal gradients, as well as the irregular structure inspired from old forest stands.://000262828900003-399WB Times Cited:0 Cited References Count:70 0921-2973ISI:000262828900003\Boucher, Y Minist Ressources Nat & Faune, Direct Rech Forestiere, 2700 Einstein, Quebec City, PQ G1P 3W8, Canada Minist Ressources Nat & Faune, Direct Rech Forestiere, Quebec City, PQ G1P 3W8, Canada Univ Quebec, Dept Biol Chim & Geog, Chaire Rech Foret Habitee, Rimouski, PQ G5L 3A1, Canada Univ Quebec, Ctr Etud Nord, Rimouski, PQ G5L 3A1, CanadaDoi 10.1007/S10980-008-9294-8English|?A,Boucher, Yan Grondin, Pierre Auger, Isabelle2014XLand use history (1840-2005) and physiography as determinants of southern boreal forests437-450Landscape Ecology293MarLand use history has altered natural disturbance dynamics, causing widespread modifications of the earth's forests. The aim of this study is to reconstruct a regional, spatially-explicit, fire and logging history for a large southern boreal forest landscape (6,050 km(2)) of eastern Canada. We then examined the long-term influence of land use history, fires, and physiographical gradients on the area's disturbances regimes, present-day age structure and tree species composition. Spatially-explicit fire (1820-2005) and logging (1900-2005) histories were reconstructed from forestry maps, terrestrial forest inventories and historical records (local newspapers, travel notes, regional historical reviews). Logistic regression was used to model the occurrence of major boreal tree species at the regional scale, in relation to their disturbance history and physiographical variables. The interplay of elevation and fire history was found to explain a large part of the present-day distribution of the four species studied. We conclude that human-induced fires following the colonization activities of the nineteenth and twentieth centuries have increased fire frequency and the dominance of fire-adapted species at lower elevations. At higher elevations, the low historical fire frequency has fostered the dominance of fire-sensitive species. Twentieth-century forestry practices and escaped settlement fires have generated a forest landscape dominated by younger forest habitats than in presettlement times. The expected increase of wildfire activity in North America's eastern boreal forest, in conjunction with continued forest management, could have significant consequences on the resilience of boreal forests.!://WOS:000331935500007Times Cited: 0 0921-2973WOS:00033193550000710.1007/s10980-013-9974-xm?$ Roel M.J. Boumans Fred H. Sklar1990CA polygon-based spatial (PBS) model for simulating landscape change83-97Landscape Ecology42/3Slandscape ecology, wetland, swamp, marsh, succession, Lake Pontchartrain, LouisianasA spatial model of long term habitat succession at a degrading Louisiana wetland was constructed based upon simulating exchanges across irregularly shaped polygons. Polygons represented the natural morphology which is indicative of the natural landscape. The PBS model was partially successful in simulating spatial habitat changes over a 28-year period when more than 1000 ha of wetland loss occurred (r2 = .56). General landscape trends did, however, emerge from the model development. Areas of high annual water level fluctuations, and high primary productivity were less likely to change from wetlands to open water and were most likely to recover if altered. We discuss the potential for predictive improvement and for integration with polygon-based geographic information systems, and conclude that a PBS model demonstrates the need for spatially explicit landscape management.H<7pBoutet, J. C. Weishampel, J. F.2003bSpatial pattern analysis of pre- and post-hurricane forest canopy structure in North Carolina, USA553-559Landscape Ecology186autocorrelation canopy topography disturbance Fractal dimension hurricane laser altimetry remote sensing duke forest forest landscape ecosystem organisation CATASTROPHIC WIND RAIN-FOREST PUERTO-RICO BASAL AREA GAP MODEL LANDSCAPE LIGHT TEMPERATE BIOMASS LIDARArticleExisting spatial patterns of a forest are in part a product of its disturbance history. Using laser altimetry and field measures of canopy top height to represent pre- and post-hurricane canopy topography, respectively, we measured changes in spatial patterns of stand structure of a United States southern mixed coniferous-deciduous forest. Autocorrelative and fractal properties were measured in this opportunistic study to quantify changes in canopy architecture along twelve, 190-250 m transects that were subjected to moderate to high levels of wind disturbance. Prior to the hurricane, canopy heights were autocorrelated at scales < 40 m with an average fractal dimension of 1.71. After the disturbance, autocorrelation disappeared; the average fractal dimension rose to 1.94. This shift towards spatial randomness illustrates part of the cyclical nature of ecosystem development. It shows how a catastrophic collapse of biomass accumulation corresponds to a decrease in ecosystem organization across a landscape.://000185827300001 p ISI Document Delivery No.: 730JH Times Cited: 3 Cited Reference Count: 50 Cited References: BELLINGHAM PJ, 1996, J TROP ECOL 5, V12, P699 BLAIR JB, 1994, P IGARSS 94, V2, P939 BOOSE ER, 1994, ECOL MONOGR, V64, P369 BRADSHAW GA, 1992, J ECOL, V80, P205 BROKAW NVL, 1991, BIOTROPICA, V23, P386 CLARK DB, 1996, CAN J FOREST RES, V26, P747 CONNER WH, 1998, COASTALLY RESTRICTED, P271 DRAKE JB, 2000, FOREST ECOL MANAG, V128, P121 EVERHAM EM, 1995, WIND TREES, P340 EVERHAM EM, 1996, BOT REV, V62, P113 FERNANDEZ DS, 1991, BIOTROPICA, V23, P393 FORD ED, 1976, AGR METEOROL, V17, P9 FOSTER DR, 1988, J ECOL, V76, P135 FOSTER DR, 1992, J ECOL, V80, P79 FOSTER DR, 1997, BIOSCIENCE, V47, P437 FOSTER DR, 1998, ECOSYSTEMS, V1, P497 GARDNER LR, 1992, NETH J SEA RES, V30, P249 HARRELL PA, 1997, REMOTE SENS ENVIRON, V59, P223 HINSLEY SA, 2002, FUNCT ECOL, V16, P851 HOFTON MA, 2000, INT J REMOTE SENS, V21, P2413 HOLLING CS, 1995, BARRIERS BRIDGES REN, P3 KEITT TH, 2000, LANDSCAPE ECOL, V15, P479 KOVACS JM, 2001, ENVIRON MANAGE, V27, P763 LEFSKY MA, 1999, REMOTE SENS ENVIRON, V67, P83 LEFSKY MA, 2002, BIOSCIENCE, V52, P19 LEGENDRE P, 1989, VEGETATIO, V80, P107 LODGE DJ, 1991, BIOTROPICA, V23, P373 MACFARLANE DW, 2003, FOREST ECOL MANAG, V173, P145 MAYFIELD M, 1996, US NATL HURRICANE CT MEANS JE, 1999, REMOTE SENS ENVIRON, V67, P298 MENENTI M, 1994, WATER RESOUR RES, V30, P1329 MORAN PAP, 1948, J ROY STAT SOC B MET, V37, P243 NELSON R, 1988, J FOREST, V86, P247 NELSON R, 1997, REMOTE SENS ENVIRON, V60, P311 PACHEPSKY YA, 1997, REMOTE SENS ENVIRON, V61, P150 PALMER MW, 1988, VEGETATIO, V75, P91 PALMER MW, 2002, LEARNING LANDSCAPE E, P129 PARKER GG, 1993, SELBYANA, V14, P5 PARKER GG, 1995, FOREST CANOPIES, P73 PIELKE RA, 1990, LANDSCAPE ECOL, V4, P133 PIELKE RA, 1998, GLOB CHANGE BIOL, V4, P461 PLATT WJ, 2000, PLANT ECOL, V146, P43 PUTZ FE, 1983, CAN J FOREST RES, V13, P1011 SHUGART HH, 2000, FOREST SCI, V46, P478 TERBORGH J, 1985, AM NAT, V126, P760 VEDYUSHKIN MA, 1994, VEGETATIO, V113, P65 WEISHAMPEL JF, 1992, J VEG SCI, V3, P521 WEISHAMPEL JF, 1996, ECOL MODEL, V86, P101 WEISHAMPEL JF, 2000, SELBYANA, V21, P79 WEISSMAN L, 1996, INTERNET WORLD, V7, P14 0921-2973 Landsc. Ecol.ISI:000185827300001Univ Cent Florida, Dept Biol, Orlando, FL 32816 USA. Sci Applicat Int Corp, Orlando, FL 32826 USA. Weishampel, JF, Univ Cent Florida, Dept Biol, Orlando, FL 32816 USA.English<7OBowers, M. A. Dooley, J. L.1999rA controlled, hierarchical study of habitat fragmentation: responses at the individual, patch, and landscape scale381-389Landscape Ecology144ecological model system ecological scaling edge habitat experimentation fragment habitat fragmentation landscape Microtus MICROTUS-PENNSYLVANICUS SMALL MAMMALS MEADOW VOLES POPULATION-DYNAMICS HOME-RANGE SPACE USE ECOLOGY MICROHABITAT FOREST SIZEArticleAug)We compared the performance of individuals and whole populations of meadow voles, Microtus pennsylvanicus, within and between experimentally created habitat fragments of three sizes (1.0, 0.25, and 0.0625 ha) and between a 20-ha fragmented and a 20-ha continuous habitat landscape. We recorded 10,020 captures of 3946 individuals over 17 censuses between June 1993 and October 1994. Five demographic parameters showed significantly different population responses between the two landscapes but no difference in tests comparing fragment size: i.e., mean and peak population densities (the latter, in each of the two growing seasons) averaged 149 to 172% higher, population growth rate averaged 219% higher, and adult recruitment 170% higher in fragmented than in the continuous control landscape. Observations at the individual level (body sizes, rates of reproduction, residence times) suggested that these landscape differences involved enhanced performance of adult females associated with edge habitats rather than differential immigration or emigration. If this turns out to be a common response to fragmentation, the detection of such responses will be greater when comparing fragmented and unfragmented landscapes with qualitatively different structure than for fragments of varied size with differing proportions of edge. That responses to habitat fragmentation may be more evident at the very small (individual) and very large (landscape) scales, but may be obscured at the intermediate spatial scale of fragments, is a proposition that clearly requires more attention.://000081305700006 ISI Document Delivery No.: 214AP Times Cited: 23 Cited Reference Count: 54 Cited References: BELSKY AJ, 1986, AM NAT, V127, P870 BIRNEY EC, 1976, ECOLOGY, V57, P1043 BOWERS MA, 1993, OECOLOGIA, V94, P247 BOWERS MA, 1996, OECOLOGIA, V105, P107 BOWERS MA, 1996, OECOLOGIA, V108, P182 BOWERS MA, 1997, J MAMMAL, V78, P999 BOWERS MA, 1998, ECOLOGY SMALL MAMMAL BURGESS RL, 1981, FOREST ISLAND DYNAMI COCKBURN A, 1983, OECOLOGIA, V59, P167 COLLINS RJ, 1997, LANDSCAPE ECOL, V12, P63 DIFFENDORFER JE, 1995, ECOLOGY, V76, P827 DOOLEY JL, 1996, OIKOS, V75, P453 DOOLEY JL, 1998, ECOLOGY, V79, P969 FOSTER J, 1991, ECOLOGY, V72, P1358 GETZ LL, 1985, SPECIAL PUBLICATION, V8, P286 GROOM MJ, 1993, BIOTIC INTERACTIONS, P24 HARGROVE WW, 1992, LANDSCAPE ECOL, V6, P251 HARPER SJ, 1993, J MAMMAL, V74, P1045 HARRIS LD, 1984, FRAGMENTED FOREST IS HOPKINS AJM, 1987, NATURE CONSERVATION, P15 IMS RA, 1993, BIOL CONSERV, V63, P261 JONES EN, 1990, J MAMMAL, V71, P382 KAREIVA P, 1989, PERSPECTIVES ECOLOGI, P68 KAREIVA PM, 1987, NATURE, V321, P388 KOTLIAR NB, 1990, OIKOS, V59, P253 LEVIN SA, 1992, ECOLOGY, V73, P1943 LIDICKER WZ, 1995, LANDSCAPE APPROACHES LIDICKER WZ, 1996, METAPOPULATIONS WILD, P85 LIDICKER WZ, 1998, IN PRESS LANDSCAPE E LOVEJOY TE, 1986, CONSERVATION BIOL SC, P257 LYNCH JF, 1984, BIOL CONSERV, V28, P287 MENKENS GE, 1988, ECOLOGY, V69, P1952 ONEILL RV, 1989, PERSPECTIVES ECOLOGI, P140 OSTFELD RS, 1988, J ANIM ECOL, V57, P385 OTIS DL, 1978, WILDLIFE MONOGR, V62, P5 QUINN JF, 1987, CONSERV BIOL, V1, P198 ROBINSON GR, 1992, SCIENCE, V257, P524 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SIMBERLOFF D, 1988, ANNU REV ECOL SYST, V19, P473 SKALSKI JR, 1992, TECHNIQUES WILDLIFE SMITH AT, 1979, J MAMMAL, V60, P778 SOULE ME, 1986, CONSERVATION BIOL SC STAMPS JA, 1987, AM ZOOL, V27, P307 STENSETH NC, 1985, TRENDS ECOLOGICAL RE, P239 STEWARTOATEN A, 1995, AM NAT, V146, P519 TEMPLE SA, 1986, MODELING HABITAT REL, P261 USHER MB, 1987, NATURE CONSERVATION, P103 VANDORP D, 1987, LANDSCAPE ECOLOGY, V1, P59 VANHORNE B, 1982, ECOLOGY, V63, P992 VERBOOM J, 1991, OIKOS, V61, P149 WHITCOMB RF, 1981, FOREST ISLAND DYNAMI, P125 WIENS JA, 1985, OIKOS, V45, P421 WILCOX BA, 1980, CONSERVATION BIOL EV, P95 YAHNER RH, 1988, CONSERV BIOL, V2, P242 0921-2973 Landsc. Ecol.ISI:000081305700006Univ Virginia, Dept Environm Sci, Boyce, VA 22620 USA. Bowers, MA, Univ Virginia, Dept Environm Sci, Route 2,Box 210, Boyce, VA 22620 USA.English|? 9Bowman, David M. J. S. Murphy, Brett P. Banfai, Daniel S.2010gHas global environmental change caused monsoon rainforests to expand in the Australian monsoon tropics? 1247-1260Landscape Ecology258Oct0A large research program in the Australian monsoon tropics has concluded that monsoon rainforests have expanded within the savanna matrix, a trend that has been emulated throughout the tropics worldwide. The driver of the northern Australian trend was not resolved, but it was suggested to be linked to a long-term trend towards wetter climates, atmospheric CO(2) enrichment, and changed fire regimes. We review these findings with particular consideration of its analytical and evidentiary basis and plausibility of the global change hypothesis. Field validation has largely demonstrated that the aerial photographic technique that underpinned the previous research is reliable enough to detect rainforest expansion. Statistical modelling demonstrated that the expansion is related to sites with regionally low fire activity, although models are of low explanatory power reflecting the sketchy historical records of fire and feral animal impacts. Field studies show that current fire regimes adjacent to expanding rainforest patches are causing populations of the native conifer Callitris intratropica, an obligate seeder, to crash. Therefore, it is unlikely that changes in fire regimes, which have been deleterious to other fire-sensitive taxa and plant communities in the region, are responsible for the rainforest expansion. We conclude that the expansion of monsoon rainforests is most plausibly linked to the current wetting trend or elevated CO(2) concentration. Increases in either water availability or CO(2) concentration can potentially overwhelm the negative feedback between fire and rainforest cover that is responsible for the meta-stability of monsoon rainforest boundaries. However, further research at the continental scale, using aerial photography, tree rings and other proxies, is required to evaluate this hypothesis.!://WOS:000281725700009YTimes Cited: 1 10th International Congress of Ecology Aug 16-21, 2009 Brisbane, AUSTRALIA 0921-2973WOS:00028172570000910.1007/s10980-010-9496-8<7Bowne, D. R. Bowers, M. A.2004MInterpatch movements in spatially structured populations: a literature review1-20Landscape Ecology191 dispersal; habitat patch; metapopulation; spatial scale BUFO-CALAMITA METAPOPULATION; VOLE MICROTUS-OECONOMUS; SMALL MAMMALS; HABITAT FRAGMENTATION; LANDSCAPE ECOLOGY; PATCH SIZE; TETRAOPES-TETRAOPHTHALMUS; AGRICULTURAL LANDSCAPE; SIGMODON-HISPIDUS; GENETIC-STRUCTUREReview4We used published data of individuals moving among habitat patches to answer questions pertaining to frequency of interpatch movements and subsequent effects on population dynamics. A review of 415 published articles produced data for 89 species-system combinations where movements were recorded in sufficient detail to include in our analysis. The percentage of individuals in a population that moved among habitat patches ranged from 0.00 to 93.00%, with a mean of 16.84%. Scaling this statistic by generation time yielded a mean movement rate of 15.45 +/- 3.27% per generation. The relatively low movement rates suggest that subpopulations, except those of invertebrates, should not be highly integrated. Less than half of the empirical studies reported on the population effects of interpatch movement. Of these, thirty-three studies yielded population effects on 34 individual species in 45 species-systems. They reported movement having a positive effect 28 times, a negative effect twice and a neutral effect 14 times. Despite its importance, relatively few studies document rates of interpatch movement and far fewer determine population level consequences of these movements. This deficiency limits our ability to understand the dynamics of spatially structured populations and apply that knowledge to conservation efforts.://000189394100001 ISI Document Delivery No.: 780RA Times Cited: 20 Cited Reference Count: 108 Cited References: AARS J, 1999, ECOLOGY, V80, P1648 ADDICOTT JF, 1987, OIKOS, V49, P340 ANDREASSEN HP, 1998, ECOLOGY, V79, P1223 ANDREASSEN HP, 1998, J ANIM ECOL, V67, P941 BEACHAM TD, 1980, J ANIM ECOL, V49, P867 BENNETT AF, 1990, LANDSCAPE ECOL, V4, P109 BERVEN KA, 1990, EVOLUTION, V44, P2047 BJOERNSTAD ON, 2000, P ROY SOC LONDON, V267, P1787 BOWERS MA, 1991, OIKOS, V60, P180 BOWERS MA, 1993, OECOLOGIA, V94, P247 BOWERS MA, 1996, OECOLOGIA, V105, P107 BOWERS MA, 1996, OECOLOGIA, V108, P182 BOWERS MA, 1997, J MAMMAL, V78, P999 BREDEN F, 1987, COPEIA, P386 BROWN JH, 1977, ECOLOGY, V58, P445 BROWNIE C, 1993, BIOMETRICS, V49, P1173 COLE FR, 1978, AM MIDL NAT, V100, P480 DEMPSTER JP, 1995, OECOLOGIA, V104, P354 DICKMAN CR, 1989, J ANIM ECOL, V58, P119 DIFFENDORFER JE, 1995, ECOLOGY, V76, P827 DOOLEY JL, 1996, OIKOS, V75, P543 ELPHICK C, 2001, SIBLEY GUIDE BIRD LI EVANS FC, 1943, J MAMMAL, V24, P231 FAHRIG L, 1985, ECOLOGY, V66, P1762 GARRETT MG, 1988, J MAMMAL, V69, P236 GIBBONS JW, 1990, LIFE HIST ECOLOGY SL, P210 GILL DE, 1978, EVOLUTION, V32, P839 GROSHOLZ ED, 1993, OECOLOGIA, V96, P347 HAAS CA, 1995, CONSERV BIOL, V9, P845 HADDAD NM, 1999, ECOL APPL, V9, P612 HADDAD NM, 2003, ECOLOGY, V84, P609 HANSKI I, 1991, BIOL J LINN SOC, V42, P3 HANSKI I, 1994, ECOLOGY, V75, P747 HANSKI I, 1995, OIKOS, V72, P21 HANSKI I, 1997, METAPOPOULATION BIOL HANSKI I, 2000, ECOLOGY, V81, P239 HARRISON S, 1988, AM NAT, V132, P360 HARRISON S, 1991, BIOL J LINN SOC, V42, P73 HARRISON S, 1995, LARGE SCALE ECOLOGY, P111 HARRISON S, 1997, METAPOPULATION BIOL, P27 HASTINGS A, 1991, ECOLOGY, V72, P896 HENDERSON MT, 1985, BIOL CONSERV, V31, P95 HILL JK, 1996, J ANIM ECOL, V65, P725 IMS RA, 1997, METAPOPULATION BIOL, P247 JOULE J, 1975, J MAMMAL, V56, P378 KAREIVA P, 1995, NATURE, V373, P299 KINDVALL O, 1992, CONSERV BIOL, V6, P520 KOTLIAR NB, 1990, OIKOS, V59, P253 KOZAKIEWICZ M, 1993, LANDSCAPE ECOL, V8, P19 KOZEL RM, 1979, SW NATURALIST, V24, P239 KROHNE DT, 1984, AM MIDL NAT, V112, P146 LEVIN SA, 1992, ECOLOGY, V73, P1943 LEVINS R, 1970, FSOME MATH PROBLEMS, P77 LIDICKER WZ, 1995, LANDSCAPE APPROACHES LINDBERG MS, 1998, ECOLOGY, V79, P1893 LOISON A, 1999, J MAMMAL, V80, P620 LORENZ GC, 1990, AM MIDL NAT, V123, P348 MADER HJ, 1984, BIOL CONSERV, V29, P81 MARSH DM, 1999, J ANIM ECOL, V68, P804 MATTER SF, 1996, OECOLOGIA, V105, P447 MCCAULEY DE, 1981, OECOLOGIA, V51, P145 MITCHELL JC, 1994, REPTILES VIRGINIA MORREALE SJ, 1984, CAN J ZOOL, V62, P1038 NEVE G, 1996, ACTA OECOL, V17, P621 NIEMINEN M, 1996, OECOLOGIA, V108, P643 NOSS RF, 1991, LANDSCAPE LINKAGES B, P27 OXLEY DJ, 1974, J APPL ECOL, V11, P51 PEACOCK MM, 1997, OECOLOGIA, V112, P524 PICKETT STA, 1995, SCIENCE, V269, P331 RANTA E, 1998, OIKOS, V83, P376 RASMUSSEN IR, 1992, OECOLOGIA, V89, P277 READING CJ, 1991, J ZOOL, V225, P201 ROWE G, 2003, EVOLUTION, V57, P177 SCOTT JA, 1986, BUTTERFLIES N AM NAT SEXTON OJ, 1959, ECOL MONOGR, V29, P113 SHERMAN PW, 1984, ECOLOGY, V65, P1617 SINSCH U, 1992, OECOLOGIA, V90, P489 SINSCH U, 1995, AUST J ECOL, V20, P351 SINSCH U, 1997, OECOLOGIA, V112, P42 SMITH AT, 1979, J MAMMAL, V60, P778 SOLBRECK C, 1990, OIKOS, V58, P199 SPENDELOW JA, 1995, ECOLOGY, V76, P2415 STACEY PB, 1997, METAPOPULATION BIOL, P267 STEEN H, 1996, ECOLOGY, V77, P2365 STENSETH NC, 1992, ANIMAL DISPERSAL SMA, P5 SUCKLING GC, 1984, AUST WILDLIFE RES, V11, P49 SUTCLIFFE OL, 1997, OECOLOGIA, V109, P229 SVENSSON BW, 1998, OIKOS, V82, P111 SWANN LA, 1972, COMMON INSECTS N AM SWIHART RK, 1984, J MAMMAL, V65, P357 SZACKI J, 1987, ACTA THERIOL, V32, P31 SZACKI J, 1991, LANDSCAPE ECOL, V5, P219 SZACKI J, 1999, LANDSCAPE ECOL, V14, P369 THOMAS CD, 1999, J ANIM ECOL, V68, P647 THOMAS CFG, 1998, OECOLOGIA, V116, P103 TILMAN D, 1994, NATURE, V371, P65 VANHORNE B, 1982, ECOLOGY, V63, P992 VERHULST S, 1997, ECOLOGY, V78, P864 VERNER L, 1985, J MAMMAL, V66, P338 WEDDELL BJ, 1991, J BIOGEOGR, V18, P385 WIENS JA, 1976, ANNU REV ECOL SYST, V7, P81 WIENS JA, 1993, OIKOS, V66, P369 WIENS JA, 1994, IBIS, V137, P97 WIGGETT DR, 1989, CAN J ZOOL, V67, P42 WILKINS KT, 1982, SW NATL, V27, P459 WILLIAMS DW, 2000, ECOLOGY, V81, P2753 WILSON DE, 1979, SMITHSONIAN BOOK N A ZHANG Z, 1991, ACTA THERIOL, V36, P239 0921-2973 Landsc. Ecol.ISI:000189394100001Univ Virginia, Dept Environm Sci, Boyce, VA 22620 USA. Univ Virginia, Blandy Expt Farm, Boyce, VA 22620 USA. Bowne, DR, Univ Richmond, Dept Biol, Richmond, VA 23173 USA. dbowne@richmond.eduEnglishm<7q(Bowne, D. R. Peles, J. D. Barrett, G. W.1999hEffects of landscape spatial structure on movement patterns of the hispid cotton rat (Sigmodon hispidus)53-65Landscape Ecology141corridor matrix cotton rat Sigmodon hispidus movement patterns micro-habitat selection spatial structure MICROTUS-PENNSYLVANICUS SMALL MAMMALS PEROMYSCUS-MANICULATUS CORRIDOR QUALITY HABITAT DISPERSAL POPULATIONS CONNECTIVITY OCHROGASTER HETEROGENEITYArticleFebA large-scale experimental landscape study was conducted to examine the use of corridors and the forest matrix habitat by the hispid cotton rat (Sigmodon hispidus). The role of micro-habitat selection by S. hispidus in influencing routes of movement was also investigated. The experimental landscape consisted of ten 1.64-ha patches (each 128 x 128 m) established in a loblolly (Pinus teada) forest. Four of the patches were isolated while the other six were connected in pairs by a 32-m wide corridor. Cotton rats (N = 96) were simultaneously released into both an isolated and connected patch, and monitored by radiotelemetry for 10 days. We found that the forest matrix was not a barrier to movements of cotton rats. Fifty percent of the cotton rats moved through the matrix. Corridors had no significant effect on the number of animals leaving connected patches (60%) compared to isolated patches (50%). However, corridors were the preferred route to leave a connected patch. Colonization success for cotton rats leaving connected and isolated patches did not significantly differ. Cotton rats exhibited micro-habitat preferences and these preferences differed within patch/corridor and matrix habitats. In patch/corridor habitats, cotton rats selected sites with tall (>1 m) shrubs and high percent cover. In the forest matrix, cotton rats selected sires with abundant cover by vines and low tree canopy cover. Movement patterns of Sigmodon hispidus are not strongly influenced by large-scale landscape spatial structures. Micra-habitat selection, however, does influence movement patterns. These findings have important implications regarding habitat connectivity for small mammals.://000079005100004  ISI Document Delivery No.: 173XM Times Cited: 36 Cited Reference Count: 62 Cited References: *SAS I, 1990, SAS STAT US GUID VER AMBROSE HW, 1972, J MAMMAL, V53, P909 BEACHAM TD, 1980, J ANIM ECOL, V49, P867 BENNETT AF, 1990, LANDSCAPE ECOL, V4, P109 BENNETT AF, 1994, BIOL CONSERV, V68, P155 BRIESE LA, 1974, J MAMMAL, V55, P615 BUECHNER M, 1989, LANDSCAPE ECOLOGY, V2, P191 CAMERON GN, 1979, SW NAT, V24, P63 CAMERON GN, 1981, MAMM SPECIES, V158, P1 CLARK BK, 1988, AM MIDL NAT, V120, P276 CRAWLEY MC, 1969, OIKOS, V20, P310 DEBUSK J, 1975, AM MIDL NAT, V93, P149 DUSENBERY DB, 1989, J THEOR BIOL, V136, P309 ESHER RJ, 1978, J MAMMAL, V59, P551 FAHRIG L, 1988, ECOLOGY, V69, P468 FAHRIG L, 1994, CONSERV BIOL, V8, P50 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FURRER RK, 1973, J MAMMAL, V54, P466 GEORTZ JW, 1964, ECOL MONOGR, V34, P359 GOLLEY FB, 1965, J MAMMAL, V46, P1 GREENWOOD PJ, 1980, ANIM BEHAV, V28, P1140 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 HADDAD NM, 1997, THESIS U GA ATHENS HANSSON L, 1991, BIOL J LINN SOC, V42, P89 HARRISON S, 1991, BIOL J LINN SOC, V42, P73 HENEIN K, 1990, LANDSCAPE ECOL, V4, P157 JONES WT, 1989, J MAMMAL, V70, P27 KENT M, 1992, VEGETATION DESCRIPTI KINCAID WB, 1983, ECOLOGY, V64, P1471 KINCAID WB, 1985, ECOLOGY, V66, P1769 KOZAKIEWICZ M, 1993, ACTA THERIOL, V38, P1 KOZAKIEWICZ M, 1993, LANDSCAPE ECOL, V8, P19 LAMBIN X, 1994, ECOLOGY, V75, P224 LAPOLLA VN, 1993, LANDSCAPE ECOL, V8, P25 LAYNE JN, 1974, AM MUS NOVIT, V2544, P1 LEVINS R, 1970, SOME MATH PROBLEMS B, P77 LIDICKER WZ, 1992, LANDSCAPE ECOL, V6, P259 LIDICKER WZ, 1996, METAPOPULATIONS WILD, P85 LIMA SL, 1996, TRENDS ECOL EVOL, V11, P131 LORENZ GC, 1990, AM MIDL NAT, V123, P348 MERRIAM G, 1990, LANDSCAPE ECOL, V4, P123 MERRIAM G, 1995, LANDSCAPE APPROACHES, P64 METSGAR LH, 1967, J MAMMAL, V48, P387 NOSS RF, 1987, CONSERV BIOL, V1, P159 PORTER JH, 1993, ECOLOGY, V74, P2436 ROFF DA, 1974, OECOLOGIA, V15, P245 ROSENBERG DK, 1997, BIOSCIENCE, V47, P677 RUEFENACHT B, 1995, BIOL CONSERV, V71, P269 SMITH MH, 1965, AM MIDL NAT, V75, P457 SPENCER SR, 1983, BEHAV ECOL SOCIOBIOL, V13, P27 STAMPS JA, 1987, AM NAT, V129, P533 STOKES MK, 1995, J MAMMAL, V76, P83 SWIHART RK, 1984, J MAMMAL, V65, P357 SWIHART RK, 1985, ECOLOGY, V66, P1176 SZACKI J, 1991, LANDSCAPE ECOL, V5, P219 SZACKI J, 1993, ACTA THERIOL, V38, P113 VERNER L, 1985, J MAMMAL, V66, P338 WHITE GC, 1990, ANAL WILDLIFE RADIOT WIENS JA, 1993, OIKOS, V66, P369 WITH KA, 1997, OIKOS, V78, P151 WOLFF JO, 1993, OIKOS, V68, P173 ZAR JH, 1984, BIOSTATICAL ANAL 0921-2973 Landsc. Ecol.ISI:000079005100004Univ Georgia, Inst Ecol, Athens, GA 30602 USA. Bowne, DR, Univ Virginia, Dept Environm Sci, Clark Hall, Charlottesville, VA 22903 USA.English&|?7 5Bradstock, R. A. Hammill, K. A. Collins, L. Price, O.2010vEffects of weather, fuel and terrain on fire severity in topographically diverse landscapes of south-eastern Australia607-619Landscape Ecology254The effects of weather, terrain, fuels on fire severity were compared using remote sensing of the severity of two large fires in south-eastern Australian forests. The probability of contrasting levels of fire severity (fire confined to the understorey vs. tree canopies consumed) was analysed using logistic regression. These severities equate to extremes of fire intensity (< 1,500 vs. > 10,000 kW m(-1)), consequent suppression potential (high vs. nil) and potential adverse ecological impacts on vertebrate fauna and soils (low vs. high). Weather was the major influence on fire severity. Crown fire was absent under non-extreme weather and but more likely under extreme weather, particularly on ridges in vegetation unburnt for > 10 years. Crown fire probability was very low in recently burnt vegetation (1-5 years) and increased at higher fuel ages. In all cases, fire severity was lower in valleys, probably due to effects of wind protection and higher fuel moisture in moderating fire behaviour. Under non-extreme weather, fires are likely to be suppressible and burn heterogeneously, due to the influence of topographic position, slope and fuel load. Under extreme weather, fires are influenced only by fuel and topographic position, and probability of suppression on accessible ridges will be low except in recently burnt (i.e. 1-5 year old) fuels. Topographically imposed variation may mitigate adverse ecological effects on arboreal fauna and soil erosion potential.!://WOS:000275444100009Times Cited: 0 0921-2973WOS:00027544410000910.1007/s10980-009-9443-8? CBrady, Mark Sahrbacher, Christoph Kellermann, Konrad Happe, Kathrin2012sAn agent-based approach to modeling impacts of agricultural policy on land use, biodiversity and ecosystem services 1363-1381Landscape Ecology279Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9787-3 0921-297310.1007/s10980-012-9787-3|? JBrady, M. J. McAlpine, C. A. Miller, C. J. Possingham, H. P. Baxter, G. S.2009sHabitat attributes of landscape mosaics along a gradient of matrix development intensity: matrix management matters879-891Landscape Ecology247AugThe matrix is an important element of landscape mosaics that influences wildlife indirectly through its influence on habitat, and directly, if they live in or move through it. Therefore, to quantify and manage habitat quality for wildlife in modified landscapes, it is necessary to consider the characteristics of both patch and matrix elements of the whole landscape mosaic. To isolate matrix effects from the often simultaneous and confounding influence of patch and landscape characteristics, we identified nineteen 500 m radius landscapes in southeast Queensland, Australia with similar remnant forest patch attributes, habitat loss, and fragmentation, but exhibiting a marked gradient from rural through high-density suburban development of the matrix, quantified by a weighted road-length metric. We measured habitat disturbance, structure, and floristics in patch core, patch edge and matrix landscape elements to characterise how landscape habitat quality changes for small mammals. Correlation analyses identified that with increased matrix development intensity, human disturbance of core sites increased, predators and exotic plant species richness in matrix sites increased, and structural complexity (e.g. logs and stumps) in the matrix decreased. Ordination analyses showed landscape elements were most similar in habitat structure and floristics at low to moderate levels of matrix development, suggesting enhanced landscape habitat quality. Matrix development intensity was not, however, the greatest source of overall variation of habitat throughout landscapes. Many variables, such as landholder behaviour, complicate the relationship. For enhanced conservation outcomes the matrix needs to be managed to control disturbances and strategically plan for matrix habitat retention and restoration.://000268430900003WBrady, Megan J. McAlpine, Clive A. Miller, Craig J. Possingham, Hugh P. Baxter, Greg S. 0921-2973ISI:00026843090000310.1007/s10980-009-9372-6g|?0 WBrady, Megan J. McAlpine, Clive A. Possingham, Hugh P. Miller, Craig J. Baxter, Greg S.2011YMatrix is important for mammals in landscapes with small amounts of native forest habitat617-628Landscape Ecology265MayAcknowledgment that the matrix matters in conserving wildlife in human-modified landscapes is increasing. However, the complex interactions of habitat loss, habitat fragmentation, habitat condition and land use have confounded attempts to disentangle the relative importance of properties of the landscape mosaic, including the matrix. To this end, we controlled for the amount of remnant forest habitat and the level of fragmentation to examine mammal species richness in human-modified landscapes of varying levels of matrix development intensity and patch attributes. We postulated seven alternative models of various patch habitat, landscape and matrix influences on mammal species richness and then tested these models using generalized linear mixed-effects models within an information theoretic framework. Matrix attributes were the most important determinants of terrestrial mammal species richness; matrix development intensity had a strong negative effect and vegetation structural complexity of the matrix had a strong positive effect. Distance to the nearest remnant forest habitat was relatively unimportant. Matrix habitat attributes are potentially a more important indicator of isolation of remnant forest patches than measures of distance to the nearest patch. We conclude that a structurally complex matrix within a human-modified landscape can provide supplementary habitat resources and increase the probability of movement across the landscape, thereby increasing mammal species richness in modified landscapes.!://WOS:000291485100002Times Cited: 0 0921-2973WOS:00029148510000210.1007/s10980-011-9602-64<7# Brandt, J.2000%The landscape of landscape ecologists181-185Landscape Ecology153Editorial MaterialApr://000085293300001 KISI Document Delivery No.: 283UB Times Cited: 5 Cited Reference Count: 7 Cited References: DECAMPS H, 1998, IALE B, V16 DUNING X, 1998, IALE B, V16 MERRIAM G, 1998, IALE B, V16 NAVEH Z, 1998, IALE B, V16 RUZICKA M, 1999, IALE B, V17 VERNADSKY WI, 1945, AM SCI, V33 ZONNEVELD I, 1998, IALE B, V16 0921-2973 Landsc. Ecol.ISI:000085293300001English#ڽ7OBrandt, Jesper Christensen, AndreasAagaard Svenningsen, StigRoar Holmes, Esbern2013@Landscape practise and key concepts for landscape sustainability 1125-1137Landscape Ecology286Springer NetherlandsProtected areas Nature parks Natura 2000 Visitor carrying capacity Sustainable landscapes European Landscape Convention Sustainable regional development Case study Landscape accessibility 2013/07/01+http://dx.doi.org/10.1007/s10980-012-9777-5 0921-2973Landscape Ecol10.1007/s10980-012-9777-5Englishy<7rBrandt, J. S. Townsend, P. A.2006cLand use - land cover conversion, regeneration and degradation in the high elevation Bolivian Andes607-623Landscape Ecology214classification; desertification; remote sensing; South America; spectral mixture analysis (SMA) MULTIPLE SPATIAL SCALES; LANDSCAPE INFLUENCES; BIOTIC INTEGRITY; PUNA ECOSYSTEMS; VEGETATION; CLASSIFICATION; ALTIPLANO; STREAMS; ACCURACY; AMAZONIAArticleMayRegional land-cover change affects biodiversity, hydrology, and biogeochemical cycles at local, watershed, and landscape scales. Developing countries are experiencing rapid land cover change, but assessment is often restricted by limited financial resources, accessibility, and historical data. The assessment of regional land cover patterns is often the first step in developing conservation and management plans. This study used remotely sensed land cover and topographic data (Landsat and Shuttle Radar Topography Mission), supervised classification techniques, and spectral mixture analysis to characterize current landscape patterns and quantify land cover change from 1985 to 2003 in the Altiplano (2535-4671 m) and Intermediate Valley (Mountain) (1491-4623 m) physiographic zones in the Southeastern Bolivian Andes. Current land cover was mapped into six classes with an overall accuracy of 88% using traditional classification techniques and limited field data. The land cover change analysis showed that extensive deforestation, desertification, and agricultural expansion at a regional scale occurred in the last 20 years (17.3% of the Mountain Zone and 7.2% of the Altiplano). Spectral mixture analysis (SMA) indicated that communal rangeland degradation has also occurred, with increases in soil and non-photosynthetic vegetation fractions in most cover classes. SMA also identified local areas with intensive management activities that are changing differently from the overall region (e.g., localized areas of increased green vegetation). This indicates that actions of local communities, governments, and environmental managers can moderate the potentially severe future changes implied by the results of this study.://000237487700012 [ISI Document Delivery No.: 041WR Times Cited: 0 Cited Reference Count: 44 Cited References: *RSI, 2000, ENVI US GUID *UNEP, 1992, WORLD ATL DES ADAMS JB, 1995, REMOTE SENS ENVIRON, V52, P137 ALLAN JD, 1997, FRESHWATER BIOL, V37, P149 BAATZ M, 2003, ECOGNITION BAIED CA, 1993, MT RES DEV, V13, P145 BALLESTER MVR, 2003, REMOTE SENS ENVIRON, V87, P429 BARRY RG, 2000, AMBIO, V29 BLUSKE RA, 1998, AREAS PROTEGIDAS DEP BRUSH SB, 1982, MOUNTAIN RES DEV, V2, P19 CARPIO J, 2002, VALOCACION HIDROLOGI CINGOLANI AM, 2004, REMOTE SENS ENVIRON, V92, P84 COLLINS JB, 1996, REMOTE SENS ENVIRON, V56, P66 ELLENBERG H, 1979, J ECOL, V67, P401 ELMORE AJ, 2000, REMOTE SENS ENVIRON, V73, P87 FLECKER AS, 1994, FRESHWATER BIOL, V31, P131 FOODY GM, 2002, REMOTE SENS ENVIRON, V80, P185 HALL CAS, 1995, J BIOGEOGR, V22, P753 HAMILTON LS, 1983, TROPICAL FORESTED WA HAMITON LS, 1997, MOUNTAINS WORLD GLOB, P103 HOSTERT P, 2003, INT J REMOTE SENS, V24, P4019 JANZEN DH, 1973, BIOTROPICA, V5, P117 JENSEN JR, 1996, INTRO DIGITAL IMAGE JOHNSON LB, 1997, FRESHWATER BIOL, V37, P193 JUSTICE C, 1981, ANAL REMOTE SENSING, P38 KOK K, 1995, BIODIVERS CONSERV, P527 LILLESAND T, 1994, REMOTE SENSING IMAGE LU DS, 2003, REMOTE SENS ENVIRON, V87, P456 MESSERLI B, 1997, MT RES DEV, V17, P229 MONAGHAN KA, 2000, ARCH HYDROBIOL, V149, P421 NUMATA I, 2003, REMOTE SENS ENVIRON, V87, P446 OKIN GS, 2001, REMOTE SENS ENVIRON, V77, P212 ROBERTS DA, 1998, REMOTE SENSING CHANG, P137 ROBERTS DA, 2003, REMOTE SENS ENVIRON, V87, P377 ROTH NE, 1996, LANDSCAPE ECOL, V11, P141 RUNDEL PW, 2000, MT RES DEV, V20, P262 SEIBERT P, 1983, MANS IMPACT VEGETATI, P74 SMALL C, 2004, REMOTE SENS ENVIRON, V93, P1 SOUZA C, 2003, REMOTE SENS ENVIRON, V87, P494 TOWNSEND PA, 2004, ECOL APPL, V14, P504 VERBURG PH, 2002, ENVIRON MANAGE, V30, P391 WANG LZ, 1997, FISHERIES, V22, P6 WANG XH, 1997, ENVIRON INT, V23, P103 WASHINGTONALLEN RA, 1998, INT J REMOTE SENS, V19, P1319 0921-2973 Landsc. Ecol.ISI:000237487700012/Univ Autonomo Juan Misael Saracho, Inst Interuniv Boliviano Recursos Hidricos, Tarija, Bolivia. Univ Maryland, Appalachian Lab, Ctr Environm Sci, Frostburg, MD 21532 USA. Townsend, PA, Univ Wisconsin, Dept Forest Ecol & Management, Russell Labs, 1630 Linden Dr, Madison, WI 53706 USA. ptownsend@wisc.eduEnglishڽ7 UBraun, Matthew Bai, Yuguang McConkey, Brian Farrell, Richard Romo, J. T. Pennock, Dan2013TGreenhouse gas flux in a temperate grassland as affected by landform and disturbance709-723Landscape Ecology284Springer Netherlands=Northern Mixedgrass Prairie GHGs CO2 N2O CH4 Mowing Landscape 2013/04/01+http://dx.doi.org/10.1007/s10980-013-9878-9 0921-2973Landscape Ecol10.1007/s10980-013-9878-9English ? ;Brearley, Grant McAlpine, Clive Bell, Sarah Bradley, Adrian2012}Influence of urban edges on stress in an arboreal mammal: a case study of squirrel gliders in southeast Queensland, Australia 1407-1419Landscape Ecology2710Springer NetherlandsBiomedical and Life SciencesThere is growing recognition that ecological research must expand its focus beyond inference based on pattern-process relationships to the direct measurement of ecological and physiological processes. Physiological assessment is important because vertebrates cope with unpredictable and noxious stimuli by initiating a stress response. However, an over-activation of the acute stress response by numerous novel and potentially stressful anthropogenic pressures, including those associated with urban edges, has the potential to generate chronic stress and a greater susceptibility to disease, reduce fecundity and survivorship. An individual’s physiological response to edge habitats with varying degrees of contrast to the adjacent disturbed urban matrix (e.g. major vs. minor roads), may provide insight into their survival likelihood in fragmented urban landscapes. Although demographic changes in wildlife resulting from urbanization have been documented, only recently have physiological consequences been examined. We addressed this problem using a case study of the squirrel glider ( Petaurus norfolcensis ) in the fragmented urban landscape of southeast Queensland, Australia. Hair samples were used to enable a comparison of hair cortisol levels in individual squirrel gliders, providing an indication of potential stress. We applied a linear mixed-effect modeling approach clustered by patch to quantify the influence of site-level habitat factors and relative abundance comparative to edge contrast on hair cortisol levels. We found that edge type had a strong positive effect on hair cortisol levels; but this depended on the availability of abundant nest hollows at a site. We conclude that individual hair cortisol concentration, providing an index of stress, was lowest in interior habitats and highest in edge habitats adjacent to major roads. Furthermore, gliders occupying low edge contrast habitats adjacent to residential areas and minor roads, and containing abundant tree nest hollows, had low-moderate hair cortisol levels. This highlights the potential importance of these habitats for the conservation of arboreal mammals such as the squirrel glider in urban landscapes.+http://dx.doi.org/10.1007/s10980-012-9790-8 0921-297310.1007/s10980-012-9790-8(<7]Bresee, M. K. Le Moine, J. Mather, S. Brosofske, K. D. Chen, J. Q. Crow, T. R. Rademacher, J.2004gDisturbance and landscape dynamics in the Chequamegon National Forest Wisconsin, USA, from 1972 to 2001291-309Landscape Ecology193$disturbance; forest management; fragmentation; GIS; landscape dynamics; landscape structure; landsat MSS; roads; TM and ETM; Wisconsin VEGETATION RESPONSES; BUDWORM DEFOLIATION; NORTHERN WISCONSIN; MANAGED LANDSCAPE; WESTERN OREGON; COVER CHANGES; LAND-USE; ECOSYSTEM; PATTERNS; FRAGMENTATIONArticle Land uses, especially harvesting and road building, are considered to be the primary cause of forest fragmentation in many parts of the world. To test this perception, we (1) quantified changes and rates of change in vegetative composition and structure within the Washburn Ranger District in northern Wisconsin using Landsat images, (2) examined changes in landscape structure, (3) assessed changes within the area of road influence (ARI), and (4) investigated changes in landscape composition and structure within the context of forest management activities. Our landscape classifications included six dominant cover types: mixed hardwood (MH), jack pine (JP), red pine (RP), mixed hardwood/conifer (MHC), non-forested bare ground (NFBG), and regenerating forest or shrub (RFS). Increases in NFBG and RFS, by 196% and 28% respectively, reflect expansion of the pine-barrens. Windthrow in the mature hardwoods during the late 1970s and jack pine budworm outbreaks during the mid-1990s correlated with decreases in those classes over the corresponding intervals. A 69% decrease in mean patch size and a 60% increase in edge density reflect increased fragmentation. An inverse relationship existed between the compositional trends of forested (excluding JP) cover types and RFS and NFBG cover types. ARI covered 8% of the landscape affecting species composition within the MH, RFS, and NFBG. Results from this study are key in assessing the links between management activities and ecological consequences and thereby facilitate adaptive management.://000221878900005 1ISI Document Delivery No.: 827DL Times Cited: 6 Cited Reference Count: 42 Cited References: *USDA FOR SERV, 1986, CHEQ FOR PLAN *USDA FOR SERV, 1993, LANDSC LEV AN DES FU ADAMS JB, 1995, REMOTE SENSING ENG, V52, P13 AGEE JK, 1993, FIRE ECOLOGY PACIFIC ALBERT DA, 1995, NC178 USDA FS GEN BAILEY RG, 1995, MISC PUBL USDA FORES, V1391 BROSOFSKE KD, 1999, PLANT ECOL, V143, P203 BROSOFSKE KD, 2001, FOREST ECOL MANAG, V146, P75 CHEN JQ, 1992, ECOL APPL, V2, P387 CHEN JQ, 1999, BIOSCIENCE, V49, P288 COHEN WB, 1995, INT J REMOTE SENS, V16, P721 COHEN WB, 2002, ECOSYSTEMS, V5, P122 CROW TR, 1999, LANDSCAPE ECOL, V14, P449 CURTIS JT, 1959, VEGETATION WISCONSIN CUSHMAN SA, 2000, LANDSCAPE ECOL, V15, P643 DUDA RO, 1973, PATTERN CLASSIFICATI, P100 EUSKIRCHEN ES, 2001, FOREST ECOL MANAG, V148, P93 FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 HEINSELMAN ML, 1981, FIRE REGIMES ECOSYST, P7 JAKUBAUSKAS ME, 1996, REMOTE SENS ENVIRON, V56, P118 MAS JF, 1999, INT J REMOTE SENS, V20, P139 MCGARIGAL K, 2002, FRAGSTATS SPATIAL PA MCNAB WH, 1994, WOWSA5 USDA FOR SERV OVERBAY JC, 1992, P NAT WORKSH TAK EC, P3 PAN D, 2001, LANDSCAPE ECOL, V16, P99 RADELOFF VC, 1999, REMOTE SENS ENVIRON, V69, P156 RADELOFF VC, 2000, ECOL APPL, V10, P233 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SAUNDERS SC, 1998, LANDSCAPE ECOL, V13, P381 SAUNDERS SC, 1999, FOREST ECOL MANAG, V117, P17 SAUNDERS SC, 2002, BIOL CONSERV, V103, P209 SCHOWENGERDT RA, 1983, TECHNIQUES IMAGE PRO SMITH BE, 1993, B TORREY BOT CLUB, V120, P229 VANWAGNER CE, 1978, CANADIAN J FOREST RE, V8, P220 VOGELMANN JE, 1995, CONSERV BIOL, V9, P439 VORA RS, 1993, RESTORATION MANAGEME, V11, P39 WALLIN DO, 1994, ECOL APPL, V4, P569 WALSH SJ, 1998, GEOMORPHOLOGY, V21, P183 WATKINS RZ, 2003, CONSERV BIOL, V17, P411 WOLTER PT, 2002, LANDSCAPE ECOL, V17, P133 ZHENG D, 2001, ECOLOGICAL MODELING, V132, P175 ZHENG DL, 1997, LANDSCAPE ECOL, V12, P241 0921-2973 Landsc. Ecol.ISI:000221878900005RUniv Toledo, Dept Earth Ecol & Environm Sci, Toledo, OH 43606 USA. Michigan Technol Univ, Sch Forest Resources & Environm Sci, Houghton, MI 49931 USA. US Forest Serv, Forestry Sci Lab, USDA, Grand Rapids, MN 55744 USA. Bresee, MK, Univ Toledo, Dept Earth Ecol & Environm Sci, 2801 W Bancroft St, Toledo, OH 43606 USA. bres9575@hotmail.comEnglish|?&Breuste, J. Niemela, J. Snep, R. P. H.2008>Applying landscape ecological principles in urban environments 1139-1142Landscape Ecology2310!://WOS:000261790600001Times Cited: 0 0921-2973WOS:00026179060000110.1007/s10980-008-9273-0|?GBridgham, Scott D. Moore, Tim R. Richardson, Curtis J. Roulet, Nigel T.2014~Errors in greenhouse forcing and soil carbon sequestration estimates in freshwater wetlands: a comment on Mitsch et al. (2013) 1481-1485Landscape Ecology299Nov`Radiative forcing feedbacks from wetlands have been an important component of past climate change and will likely be so in the future, so accurately assessing the carbon (C) and radiative balances of wetlands remains an important research priority. This commentary shows that the paper by Mitsch et al. (Landscape Ecol 28: 583-597, 2013) seriously underestimated the radiative forcing effect of methane (CH4) emissions and overestimated soil C sequestration in freshwater wetlands. The model that they used is flawed in double counting the atmospheric decay of CH4 and incorporating a single 100 year CH4 global warming potential. They also used a small number of sites and short-term soil dating that resulted in unrealistically high soil C sequestration rates, ignoring decay of the entire soil C pool and allochthonous inputs of C. They calculated the radiative balance instead of the radiative forcing of natural wetlands, making their calculations irrelevant to anthropogenic climate change. Irrespective of the radiative forcing of wetlands, they provide essential ecosystem services that are important to protect.!://WOS:000343648700002Times Cited: 0 0921-2973WOS:00034364870000210.1007/s10980-014-0067-2 <7; QBridgman, L. J. Benitez, V. V. Grilli, M. G. Mufato, N. Acosta, D. Guichon, M. L.2012Short perceptual range and yet successful invasion of a fragmented landscape: the case of the red-bellied tree squirrel (Callosciurus erythraeus) in Argentina633-640Landscape Ecology275dispersal invasive rodents landscape connectivity orientation translocation experiment white-footed mice body-mass ecology connectivity habitat forest marsupials dispersal abilities dynamicsMay9Dispersal is a key element of the invasion process for introduced species, and is influenced by landscape connectivity. The red-bellied squirrel (Callosciurus erythraeus) was introduced to Argentina in 1970. Suitable forest habitat for this arboreal species is highly fragmented in a rural-urban matrix, but despite this, the squirrel population has spread. Squirrels disperse into new habitat patches using connective features such as forest corridors. They may also cross gaps but up to what extent is not known. Gap crossing success is influenced by perceptual range, which is the distance from which animals can perceive suitable habitat. Perceptual range has been previously estimated for vulnerable species, but not for introduced species. We used a model relating perceptual range to body mass to predict the perceptual range of the red-bellied tree squirrel in Argentina. We then tested our prediction of 202-221 m by releasing squirrels in an unfamiliar arable field at different distances (300, 200, 100 and 20 m) from woodland habitat. We assumed that if woodland could be perceived, squirrels would orientate toward it. We estimated perceptual range to be between 20 and 100 m, considerably lower than predicted. Our results indicate that squirrels can potentially cross small habitat gaps, but dispersal over greater distances lacking connectivity is less likely. Incorporating this information when modelling the spread of exotic squirrels in the Pampas Region can yield more accurate prediction of the invasion process and guide management practices to minimise their expansion.://000303056100002-929JC Times Cited:0 Cited References Count:42 0921-2973Landscape EcolISI:000303056100002Univ Nacl Lujan, Dept Ciencias Basicas, Rutas 5 & 7, RA-6700 Buenos Aires, DF, Argentina Univ Nacl Lujan, Dept Ciencias Basicas, Rutas 5 & 7, RA-6700 Buenos Aires, DF, Argentina Univ Nacl Lujan, Dept Ciencias Basicas, RA-6700 Buenos Aires, DF, ArgentinaDOI 10.1007/s10980-012-9727-2English 9<7< Broadbent, E. N. Zambrano, A. M. A. Dirzo, R. Durham, W. H. Driscoll, L. Gallagher, P. Salters, R. Schultz, J. Colmenares, A. Randolph, S. G.2012{The effect of land use change and ecotourism on biodiversity: a case study of Manuel Antonio, Costa Rica, from 1985 to 2008731-744Landscape Ecology275biological corridor secondary forests land use and land cover change sustainable development remote sensing oil palm plantations protected areas population-growth human-needs conservation forest deforestation corridors mammals parksMay9Development in biodiversity rich areas is of global concern. While development may lead to socioeconomic benefits, this often comes concomitant with biodiversity loss and deforestation. Biodiversity rich areas present the opportunity for both improvements in socioeconomic conditions and conservation; however numerous challenges exist. Costa Rica's Manuel Antonio National Park presents an ideal case study to investigate the balance between alternative forms of development which have contrasting environmental impacts. The Manuel Antonio region is a highly dynamic landscape experiencing deforestation, from agriculture, cattle ranching and oil palm plantations; and also reforestation from abandonment of land holdings and nature oriented tourism. Landscape dynamics are closely intertwined with the livelihoods and perspectives on biodiversity conservation of local communities, determining ecological sustainability. We use an analysis combining multi-temporal remote sensing of land cover dynamics from 1985 to 2008 with questionnaire data from local families on their socioeconomic status, perspectives on conservation, and perceived changes in local wildlife populations. Our results show that, while regeneration occurred and forest fragmentation in the area decreased from 1985 to 2008, Manuel Antonio National Park is rapidly becoming isolated. Decreasing ecological connectivity is related to the rapid expansion of oil palm plantations adjacent to the park and throughout the lowland areas. Perceived decreases in wildlife abundance and compositional change are evident throughout the area, with local communities attributing this primarily to illegal hunting activities. Nature based tourism in the area presents an effective strategy for conservation, including reductions in hunting, through increased valuation of biodiversity and protected areas, and socioeconomic advantages. However, without urgent efforts to limit deforestation and preserve the remaining forested corridor connecting the park to core primary forest, the ability to maintain biodiversity in the park will be reduced.://000303056100009-929JC Times Cited:0 Cited References Count:66 0921-2973Landscape EcolISI:000303056100009Broadbent, EN Stanford Univ, Dept Global Ecol, Carnegie Inst Sci, 260 Panama St, Stanford, CA 94305 USA Stanford Univ, Dept Global Ecol, Carnegie Inst Sci, 260 Panama St, Stanford, CA 94305 USA Stanford Univ, Dept Global Ecol, Carnegie Inst Sci, Stanford, CA 94305 USA Stanford Univ, Dept Biol, Stanford, CA 94305 USA Stanford Univ, Dept Anthropol, Stanford, CA 94305 USA Stanford Univ, Ctr Responsible Travel, Stanford, CA 94305 USA Univ Arizona, Dept Anthropol, Flagstaff, AZ 86011 USA Univ Turismo Costa Rica, San Jose, Costa RicaDOI 10.1007/s10980-012-9722-7English`<7+Brook, B. W. Bowman, Dmjs2006Postcards from the past: charting the landscape-scale conversion of tropical Australian savanna to closed forest during the 20th century 1253-1266Landscape Ecology218^aerial photography; historical ecology; indigenous fire-use; generalised linear modelling; geographic information systems; landscape ecology; vegetation dynamics MONSOON RAIN-FOREST; ASSESSING VEGETATION CHANGE; NORTHERN AUSTRALIA; HABITAT FRAGMENTATION; LOGISTIC-REGRESSION; AERIAL-PHOTOGRAPHY; STRONG INFERENCE; FIRE REGIMES; HUMAN IMPACT; DYNAMICSArticleNov/Repeated sequences of digitised and geo-referenced historical aerial photography provide a powerful means of understanding landscape change. We use this method to demonstrate a landscape wide expansion of closed forest (42% increase in total coverage) in the Australian monsoon tropics over the past five decades. Retrospective habitat suitability models (HSI) of closed forest derived using four landscape measures (drainage distance, slope angle, aspect and elevation) for imagery taken in 1947 correctly forecast the subsequent spatial distribution of the expansion, with topographic fire protection primarily determining the closed-forest distribution. The dynamics of the closed forest-savanna boundary were predicted accurately by generalised linear models, with closed-forest expansion in fire-protected sites along forest edges and regression in the more fire-prone areas. Two factors may plausibly explain the expansion of closed forests. First, eco-ethnographic records stress the skilful use of fire by Aboriginal people in protecting isolated and locally resource-rich closed-forest patches. Second, the recent global increase in atmospheric CO2 may be changing the competitive balance between savanna and forest by enabling C-3 trees to (grow fast enough to escape the fire trap presented by flammable C-4 grasses.://000242089300007 ISI Document Delivery No.: 106GP Times Cited: 0 Cited Reference Count: 51 Cited References: ANDERSON DR, 2001, WILDLIFE SOC B, V29, P311 ARCHER M, 1989, AUSTR ZOOLOGIST, V25, P29 AUGUSTIN NH, 2001, J APPL ECOL, V38, P991 BALZTER H, 1998, ECOL MODEL, V107, P113 BANFAI DS, 2005, AUST J BOT, V53, P185 BOND WJ, 2003, GLOBAL CHANGE BIOL, V9, P973 BOND WJ, 2005, NEW PHYTOL, V165, P525 BOWMAN D, 2005, NEW PHYTOL, V165, P341 BOWMAN DMJ, 1994, PACIFIC CONSERVATION, V1, P98 BOWMAN DMJ, 2000, AUSTR RAINFORESTS IS BOWMAN DMJ, 2006, IN PRESS PACIFIC CON BOWMAN DMJS, 1993, J BIOGEOGR, V20, P373 BOWMAN DMJS, 1998, NEW PHYTOL, V140, P385 BOWMAN DMJS, 2001, GLOBAL ECOL BIOGEOGR, V10, P535 BOWMAN DMJS, 2004, AUSTRAL ECOL, V29, P605 BROOK BW, 2002, J ENVIRON MANAGE, V65, P355 BURNHAM KP, 2001, WILDLIFE RES, V28, P111 BURNHAM KP, 2002, MODEL SELECTION MULT CONROY SDS, 2003, POPUL ECOL, V45, P105 CRANSTON PS, 1998, AUST J ENTOMOL 2, V37, P107 EDWARDS A, 2001, INT J WILDLAND FIRE, V10, P79 FAHRIG L, 2002, ECOL APPL, V12, P346 FELICISIMO AM, 2002, PHOTOGRAMM ENG REM S, V68, P455 FENSHAM RJ, 2002, AUST J BOT, V50, P415 FIELDING AH, 1997, ENVIRON CONSERV, V24, P38 FRANKLIN J, 1995, PROG PHYS GEOG, V19, P474 HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HILBORN R, 1997, ECOLOGICAL DETECTIVE IHAKA R, 1996, J COMPUTATIONAL GRAP, V5, P299 KADMON R, 1999, REMOTE SENS ENVIRON, V68, P164 KEELING CD, 2004, TRENDS COMPENDIUM DA LEGENDRE P, 2002, ECOGRAPHY, V25, P601 MALHI Y, 2000, TRENDS ECOL EVOL, V15, P332 MCCULLAGH P, 1989, GEN LINEAR MODELS MILLER G, 2005, GEOLOGY, V33, P65 MILLER GH, 1999, SCIENCE, V283, P205 MILLER JR, 2004, BIOSCIENCE, V54, P310 ODORICO DM, 1998, EMERG INFECT DIS, V4, P641 PEARCE J, 2000, ECOL MODEL, V133, P225 PICKARD J, 2002, AUST J BOT, V50, P409 PLATT JR, 1964, SCIENCE, V146, P347 PRICE OF, 2004, AUSTRAL ECOL, V29, P137 PRIOR LD, 2003, FUNCT ECOL, V17, P504 RUSSELLSMITH J, 1992, BIOL CONSERV, V59, P51 RUSSELLSMITH J, 1992, BIOTROPICA, V24, P471 RUSSELLSMITH J, 2004, J BIOGEOGR, V31, P1305 SHARP BR, 2003, J BIOGEOGR, V30, P783 SHULMEISTER J, 1992, HOLOCENE, V2, P107 SMITH I, 2004, AUST METEOROL MAG, V53, P163 VANGROENENDAEL JM, 1996, J VEG SCI, V7, P211 YIBARBUK D, 2001, J BIOGEOGR, V28, P325 0921-2973 Landsc. Ecol.ISI:000242089300007Charles Darwin Unic, Sch Environm Res, Inst Adv Studies, Darwin, NT 0909, Australia. Brook, BW, Charles Darwin Unic, Sch Environm Res, Inst Adv Studies, Darwin, NT 0909, Australia. barry.brook@cdu.edu.auEnglish|?+Brooker, R. W. Osler, G. H. R. Gollisch, J.2008jAssociation of vegetation and soil mite assemblages with isolated Scots pine trees on a Scottish wet heath861-871Landscape Ecology237MIsolated trees may significantly enhance biodiversity at the landscape level. However, our understanding of their impacts is still poor, particularly in environments with high soil moisture where research on this topic has been comparatively limited. We examined understorey vegetation and soil oribatid mite assemblages under live and dead Scots pine trees and in open treeless areas, all within the same Scottish upland wet heath system, to determine whether isolated live trees affected the understorey and mite components of the ecosystem, and whether these effects occurred in parallel. We also explored whether these responses might result from tree-driven reductions in soil moisture content. Live trees reduced soil moisture (relative to wet heath and beneath dead trees) and appeared to change vegetation from wet heath to dry heath type communities. These effects were strongly related to tree trunk diameter (tree size). No major effects of dead trees on understorey vegetation or soil moisture were apparent. Higher mite species abundance and richness were found under live trees than in treeless open heath. Although mite abundances were lower under dead trees than live trees, richness remained similar, thus different factors seem to be regulating mite abundance and community composition. These findings indicate that landscape-level biodiversity responses to environmental change such as habitat fragmentation cannot be predicted from vegetation patterns alone, and that even in heavily fragmented landscapes comparatively small patches such as isolated individual trees can enhance biodiversity.!://WOS:000258540300008Times Cited: 0 0921-2973WOS:00025854030000810.1007/s10980-008-9242-77<7b6Broquet, T. Ray, N. Petit, E. Fryxell, J. M. Burel, F.2006bGenetic isolation by distance and landscape connectivity in the American marten (Martes americana)877-889Landscape Ecology216American marten; boreal forest; connectivity; dispersal; effective distance; genetic structure; isolation by distance; landscape genetics CONTINUOUS POPULATION; FOREST; FLOW; DISPERSAL; DIFFERENTIATION; METAPOPULATION; INDIVIDUALS; ECOLOGY; HABITAT; MARKERSArticleAugEmpirical studies of landscape connectivity are limited by the difficulty of directly measuring animal movement. 'Indirect' approaches involving genetic analyses provide a complementary tool to 'direct' methods such as capture-recapture or radio-tracking. Here the effect of landscape on dispersal was investigated in a forest-dwelling species, the American marten (Martes americana) using the genetic model of isolation by distance (IBD). This model assumes isotropic dispersal in a homogeneous environment and is characterized by increasing genetic differentiation among individuals separated by increasing geographic distances. The effect of landscape features on this genetic pattern was used to test for a departure from spatially homogeneous dispersal. This study was conducted on two populations in homogeneous vs. heterogeneous habitat in a harvested boreal forest in Ontario (Canada). A pattern of IBD was evidenced in the homogeneous landscape whereas no such pattern was found in the near-by harvested forest. To test whether landscape structure may be accountable for this difference, we used effective distances that take into account the effect of landscape features on marten movement instead of Euclidean distances in the model of isolation by distance. Effective distances computed using least-cost modeling were better correlated to genetic distances in both landscapes, thereby showing that the interaction between landscape features and dispersal in Martes americana may be detected through individual-based analyses of spatial genetic structure. However, the simplifying assumptions of genetic models and the low proportions in genetic differentiation explained by these models may limit their utility in quantifying the effect of landscape structure.://000239484200008 ISI Document Delivery No.: 069YA Times Cited: 1 Cited Reference Count: 53 Cited References: *R DEV COR TEAM, 2005, R LANG ENV STAT COMP ADRIAENSEN F, 2003, LANDSCAPE URBAN PLAN, V64, P233 ARNAUD JF, 2003, LANDSCAPE ECOL, V18, P333 AVISE JC, 2004, MOL MARKERS NATURAL BROQUET T, IN PRESS MOL ECOL BROQUET T, 2004, THESIS U RENNES 1 RE BUSKIRK SW, 1989, J WILDLIFE MANAGE, V53, P191 BUSKIRK SW, 1994, MARTENS SABLES FISHE, P283 CASTRIC V, 2001, EVOLUTION, V55, P1016 CHARDON JP, 2003, LANDSCAPE ECOL, V18, P561 CLEVELAND WS, 1992, STAT MODELS S, P309 COULON A, 2004, MOL ECOL, V13, P2841 DANCHIN E, 2001, DISPERSAL, P243 DAVIS CS, 1998, MOL ECOL, V7, P1776 DAVIS JM, 2004, TRENDS ECOL EVOL, V18, P411 DEON R, 2002, CONSERV ECOL, V6 EPPERSON BK, 2003, GEOGRAPHICAL GENETIC FECSKE DM, 2002, CAN FIELD NAT, V116, P309 FENSTER CB, 2003, EVOLUTION, V57, P995 GARDNER RH, 2004, ECOL MODEL, V171, P339 GOODWIN BJ, 2002, OIKOS, V99, P552 GOODWIN BJ, 2003, LANDSCAPE ECOL, V18, P687 GOUDET J, 1995, J HERED, V86, P485 GOUDET J, 2001, FSTAT PROGRAM ESTIMA HALE ML, 2001, SCIENCE, V293, P2246 HANSKI I, 1999, METAPOPULATION ECOLO HARDY OJ, 1999, HEREDITY 2, V83, P145 HARDY OJ, 2002, MOL ECOL NOTES, V2, P618 HARDY OJ, 2003, MOL ECOL, V12, P1577 LEBLOIS R, 2004, GENETICS, V166, P1081 MICHELS E, 2001, MOL ECOL, V10, P1929 MOILANEN A, 2001, OIKOS, V95, P147 NEIGEL JE, 1997, ANNU REV ECOL SYST, V28, P105 PAYER DC, 2003, FOREST ECOL MANAG, V179, P145 POOLE KG, 2004, CAN J ZOOL, V82, P423 RAY N, 2004, MOL ECOL NOTES, V5, P177 ROUSSET F, 1997, GENETICS, V145, P1219 ROUSSET F, 2000, J EVOLUTION BIOL, V13, P58 ROUSSET F, 2001, DISPERSAL, P18 ROUSSET F, 2001, HDB STAT GENETICS, P681 ROUSSET F, 2004, GENETIC STRUCTURE SE SELONEN V, 2004, BEHAV ECOL, V15, P564 SOUTIERE EC, 1979, J WILDLIFE MANAGE, V43, P850 STEVENTON JD, 1982, J WILDLIFE MANAGE, V46, P175 SUMNER J, 2001, MOL ECOL, V10, P1917 TAYLOR PD, 1993, OIKOS, V68, P571 TISCHENDORF L, 2000, LANDSCAPE ECOL, V15, P633 TISCHENDORF L, 2001, OIKOS, V95, P152 VERBEYLEN G, 2003, LANDSCAPE ECOL, V18, P791 VOS CC, 2001, HEREDITY 5, V86, P598 WATT WR, 1996, FOREST MANAGEMENT GU WIENS JA, 2001, DISPERSAL, P96 WRIGHT S, 1943, GENETICS, V28, P114 0921-2973 Landsc. Ecol.ISI:000239484200008iUniv Rennes 1, UMR CNRS 6553 Ecobio, F-35042 Rennes, France. Univ Melbourne, Sch Bot, Environm Sci Grp, Parkville, Vic 3010, Australia. Univ Rennes 1, UMR CNRS 6552 Ethol, F-35380 Paimpont, France. Univ Guelph, Dept Zool, Guelph, ON N1G 2W1, Canada. Broquet, T, Univ Rennes 1, UMR CNRS 6553 Ecobio, Av Gen Leclerc, F-35042 Rennes, France. thomas.broquet@unil.chEnglish<7&Brotons, L. Herrando, S. Martin, J. L.2004WBird assemblages in forest fragments within Mediterranean mosaics created by wild fires663-675Landscape Ecology196Catalonia; forest avifauna; fragmentation; habitat mosaics; Mediterranean; resource supplementation and complementation; Spain HABITAT FRAGMENTATION; LANDSCAPE CHANGES; BOREAL FOREST; BREEDING AVIFAUNA; PINE PLANTATIONS; CONSERVATION; MANAGEMENT; SPAIN; EDGE; CONSEQUENCESArticleAugThe role of habitat heterogeneity as a key factor in determining species pools in habitat mosaics has been acknowledged, but we still know little on the relative importance of the different ecological processes acting within such complex landscapes. We compared species richness and distribution in forest fragments imbedded in shrub-lands to those in continuous forests or in continuous shrublands. We examined the consistency of our data with the predictions of two hypotheses: 1) the Habitat fragmentation hypothesis which states that fragmentation has negative effects on the species from the original continuous habitat; 2) the Habitat supplementation /complementation hypothesis which stipulates that the presence of a matrix habitat around the fragments will mitigate negative effects on the species from the original habitat (supplementation) or allow the presence of species that depend on the presence of both the fragment and matrix habitats (complementation). We show that: 1) species richness in forest fragments did not differ from species richness in segments of continuous forests of equal area; 2) the bird community of forest fragments got impoverished in some forest species but a higher proportion of species common in continuous forests were not affected by fragmentation; 3) fragment communities had a significant proportion of common species that were scarce in, or absent from both continuous forests and shrublands. While, a few forest species supported predictions from the fragmentation hypothesis, occurrence patterns observed in several other species were consistent with either the supplementation or the complementation hypotheses. Our results suggest that there is no single hypothesis that properly captures the consequences of a shift from continuous forests to a mosaic of forest fragments and shrublands and that different ecological mechanisms act in conjunction to determine species pools in habitat mosaics. Habitat heterogeneity at a local scale appears a key factor in maintaining bird diversity in fire driven Mediterranean landscapes.://000224100600008 ISI Document Delivery No.: 857FC Times Cited: 1 Cited Reference Count: 61 Cited References: ANDREN H, 1994, OIKOS, V71, P355 BIBBY CJ, 1992, BIRD CENSUS TECHIQUE BISSONETTE JA, 2002, CONSERV ECOL, V6 BLONDEL J, 1999, BIOL WINDLIFE MEDITE BROTONS L, 2001, ACTA OECOL, V22, P21 BROTONS L, 2003, AM NAT, V162, P343 COVAS R, 1998, IBIS, V140, P395 CRAWLEY MJ, 1993, GLIM ECOLOGISTS DEBINSKI DM, 2000, CONSERV BIOL, V14, P342 DEBUSSCHE M, 1999, GLOBAL ECOL BIOGEOGR, V8, P3 DIAZ M, 1998, J APPL ECOL, V35, P562 DRAPEAU P, 1999, J AVIAN BIOL, V30, P367 DUNNING JB, 1992, OIKOS, V65, P169 FAHRIG L, 2003, ANNU REV ECOL EVOL S, V34, P487 FISCHER J, 2002, BIOL CONSERV, V106, P129 FOLCH R, 1986, VEGET PAISOS CATALAN FORMAN RTT, 1995, LAND MOSAICS ECOL GREENACRE MJ, 1984, THEORY APPLICATIONS HAILA Y, 2002, ECOL APPL, V12, P321 HANSKI I, 1991, BIOL J LINN SOC, V42, P3 HARDY CC, 1996, USE FIRE FOREST REST HERRANDO S, 2002, ECOGRAPHY, V25, P161 HERRANDO S, 2003, IBIS, V145, P307 IZHAKI I, 1997, INT J WILDLAND FIRE, V7, P335 LAW BS, 1998, BIODIVERS CONSERV, V7, P323 LEGENDRE P, 1998, NUMERICAL ECOL LLORET F, 2002, LANDSCAPE ECOL, V17, P745 LOPEZ G, 1997, J APPL ECOL, V34, P1257 MACARTHUR RH, 1967, THEORY ISLAND BIOGEO MARTIN JL, 1992, J BIOGEOGR, V19, P375 MAZEROLLE DF, 2002, OECOLOGIA, V130, P356 MCCOLLIN D, 1998, ECOGRAPHY, V21, P247 MCGARIGAL K, 2002, ECOL APPL, V12, P335 MONKKONEN M, 1999, OIKOS, V84, P302 MOREIRA F, 2001, LANDSCAPE ECOL, V16, P175 MURCIA C, 1995, TRENDS ECOL EVOL, V10, P58 NORTON MR, 2000, ECOGRAPHY, V23, P209 PATON PWC, 1994, CONSERV BIOL, V8, P17 PAUSAS JG, 1998, MODELING FIRE PRONE, P327 PERRINS CM, 1998, COMPLETE BIRDS WEST PINO J, 2000, LANDSCAPE URBAN PLAN, V49, P35 PINOL J, 1998, CLIMATIC CHANGE, V38, P345 PONS P, 1998, BIRD SITE TENACITY, P261 PONS P, 2003, BIODIVERS CONSERV, V12, P1843 PREISS E, 1997, LANDSCAPE ECOL, V12, P51 PRODON R, 1981, OIKOS, V37, P21 PULIDO JP, 1992, ARDEOLA, V39, P63 RETANA J, 2002, ECOSCIENCE, V9, P89 ROBINSON SK, 1984, AUK, V101, P672 ROCAMORA G, 1997, MEDITERRANEAN FOREST, P239 SANTOS T, 1992, BIOL CONSERV, V60, P1 SANTOS T, 2002, BIOL CONSERV, V105, P113 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SCHAEFER T, 2000, J ORNITHOL, V141, P335 SCHMIEGELOW FKA, 2002, ECOL APPL, V12, P375 SHOCHAT E, 2001, J APPL ECOL, V38, P1135 SISK TD, 1997, ECOL APPL, V7, P1170 TELLERIA JL, 1995, BIOL CONSERV, V71, P61 TRABAUD L, 1981, ECOSYSTEMS WORLD, V11, P523 TYE A, 1992, IBIS, V134, P273 WIENS JA, 1994, IBIS, V137, P97 0921-2973 Landsc. Ecol.ISI:000224100600008GCNRS, Functional & Evolutionary Ecol Ctr, F-34293 Montpellier, France. Forest Technol Ctr Catalonia, Biodiversity Section, E-25280 Solsona, Spain. Catalan Ornithological Inst, E-08037 Barcelona, Spain. Brotons, L, CNRS, Functional & Evolutionary Ecol Ctr, 1919 Route De Mende, F-34293 Montpellier, France. lluis.brotons@ctfc.esEnglish<7e=Brotons, L. Monkkonen, M. Huhta, E. Nikula, A. Rajasarkka, A.2003pEffects of landscape structure and forest reserve location on old-growth forest bird species in Northern Finland377-393Landscape Ecology184boreal forest birds habitat isolation landscape mosaics reserve network BOREAL FORESTS PROTECTED AREAS HABITAT FRAGMENTATION POPULATION TRENDS SOUTHERN FINLAND BREEDING BIRDS LAND BIRDS SCALE COMMUNITIES MANAGEMENTArticleOld-growth forest birds in Fennoscandia have sharply declined in numbers during the last decades apparently due to commercial forest harvesting and fragmentation of old-growth forests. Conservation measures have led to the establishment of a forest reserve network to assure the persistence of forest birds at a regional scale. However, little is known about the effects of landscape structure within and around the reserves on the distribution of old-growth forest birds. We used a hierarchical approach to address the questions of how landscape structure and composition within forest reserves, landscape composition of surrounding areas and reserve location affect the abundance of resident, old-growth forest birds in the Northern Finnish forest reserve network. The positive role of particular landscape features on bird distribution indicates that both the proportion of old-growth forests and the structure of boreal landscape mosaic has an important role in determining the distribution of these birds. The landscape composition surrounding the reserves proved to be only a weak predictor in species distribution models, which argues against the primary role of the surrounding matrix in determining species distribution within forest reserves. Reserves located near the Russian border showed a higher abundance of old-growth birds than more western ones. Once east-west gradients in overall landscape composition had been accounted for, however, reserves did not differ significantly in the number of species present. These results suggest that landscape gradients, rather than ecological processes such as the presence of source areas located along the border with Russia, are the main determinant of the distribution of old-growth forest birds in the Finnish reserve network. We propose that to enhance regional persistence of old-growth forest birds, conservation efforts should be primarily directed towards the protection and enhancement of forest habitat quality and natural heterogeneity of landscapes within targeted areas.://000185919200003 ISI Document Delivery No.: 732AT Times Cited: 9 Cited Reference Count: 53 Cited References: AHTI T, 1968, ANN BOT FENN, V5, P169 ANDREN H, 1994, OIKOS, V71, P355 ANGELSTAM P, 1992, ECOLOGICAL PRINCIPLE, P9 BENDER DJ, 1998, ECOLOGY, V79, P517 BUCKLAND ST, 1993, J APPL ECOL, V30, P478 CHAMBERS JM, 1997, STAT MODELS S CRAWLEY MJ, 1993, GLIM ECOLOGISTS CUMMING SG, 1996, ECOGRAPHY, V19, P162 DESROCHERS A, 1999, P 22 INT ORN C U NAT DRAPEAU P, 2000, ECOL MONOGR, V70, P423 EDENIUS L, 1996, LANDSCAPE ECOL, V11, P325 ESSEEN PA, 1992, ECOLOGICAL PRINCIPLE, P252 ESSEEN PA, 1997, ECOLOGICAL B, V46, P16 FAYT P, 1999, ORNIS FENNICA, V76, P135 HAILA Y, 1990, BIOGEOGRAPHY ECOLOGY, P61 HAILA Y, 1994, ANN ZOOL FENN, V31, P203 HARRISON S, 1999, ECOGRAPHY, V22, P225 HELLE P, 1986, ANN ZOOL FENN, V23, P269 HELLE P, 1986, OIKOS, V46, P107 HERRERA CM, 1978, AUK, V95, P496 IMBEAU L, 2001, CONSERV BIOL, V15, P1151 JARVINEN O, 1975, OIKOS, V26, P316 JARVINEN O, 1977, OIKOS, V29, P225 JARVINEN O, 1977, SILVA FENNICA, V11, P282 JOKIMAKI J, 1996, ORNIS FENNICA, V73, P97 KOUKI J, 2000, ORNIS FENNICA, V77, P145 LAHTI K, 1998, ECOLOGY, V79, P2904 LEGENDRE P, 1998, NUMERICAL ECOLOGY LINDEN H, 2000, WILDLIFE BIOL, V6, P179 MCGARIGAL K, 1995, PNWGTR351 US FOR SER MONKKONEN M, 1994, ANN ZOOL FENN, V31, P61 MONKKONEN M, 1999, BIODIVERS CONSERV, V8, P85 MONKKONEN M, 1999, OIKOS, V84, P302 NILSSON C, 1992, CONSERV BIOL, V6, P232 RAIVIO S, 1990, ORNIS FENNICA, V67, P73 REUNANEN P, 2002, IN PRESS WILDLIFE BI ROLDSTAD J, 1989, FINNISH GAME RES, V46, P43 SAAB V, 1999, ECOL APPL, V9, P135 SCHMIEGELOW FKA, 1997, ECOLOGY, V78, P1914 SCHMIEGELOW FKA, 2002, ECOL APPL, V12, P375 SIITONEN J, 2001, ECOLOGICAL B, V49, P11 SJOBERG K, 1997, ECOL B, V46, P48 SNOW DW, 1998, BIRDS W PALEARCTIC STORAAS T, 1987, J WILDLIFE MANAGE, V51, P167 SYRJANEN K, 1994, ANN ZOOL FENN, V31, P19 TOMPPO E, 1993, P ILV S NAT FOR INV, P52 UIMANIEMI L, 2000, ECOGRAPHY, V23, P668 VAISANEN RA, 1986, ORNIS SCAND, V17, P282 VAISANEN RA, 1998, DISTRIBUTION NUMBERS VILLARD MA, 1999, CONSERV BIOL, V13, P774 VIRKKALA R, 1987, ANN ZOOL FENN, V24, P281 VIRKKALA R, 1991, BIOL CONSERV, V56, P223 VIRKKALA R, 1994, CONSERV BIOL, V8, P532 0921-2973 Landsc. Ecol.ISI:000185919200003Univ Turku, Dept Biol, Sect Ecol, FIN-20014 Turku, Finland. Finnish Forest Res Inst, FIN-96301 Rovaniemi, Finland. Nat Heritage Serv, FIN-90101 Oulu, Finland. Univ Oulu, Dept Biol, FIN-90014 Oulu, Finland. Brotons, L, CNRS, CEFE, 1919 Route Mende, F-34293 Montpellier, France.Englishڽ7 LBrouwers, Niels Matusick, George Ruthrof, Katinka Lyons, Thomas Hardy, Giles2013Landscape-scale assessment of tree crown dieback following extreme drought and heat in a Mediterranean eucalypt forest ecosystem69-80Landscape Ecology281Springer Netherlands|Climate change Drought effects Heat effects Warming Die-off Dieback Tree mortality Forest mortality Soils Topography Geology 2013/01/01+http://dx.doi.org/10.1007/s10980-012-9815-3 0921-2973Landscape Ecol10.1007/s10980-012-9815-3English|7Brouwers, N. C. Newton, A. C.2009The influence of habitat availability and landscape structure on the distribution of wood cricket (Nemobius sylvestris) on the Isle of Wight, UK199-212Landscape Ecology242woodland forest habitat availability fragmentation landscape scale invertebrate insect wood cricket nemobius sylvestris isle of wight fragmented forest landscape metapopulation dynamics patch characteristics tree hollows connectivity conservation beetle diversity bird sizeFeb>Little information is available regarding the landscape ecology of woodland invertebrate species with limited dispersal ability. An investigation was therefore conducted within woodland fragments in an agricultural landscape for the flightless wood cricket (Nemobius sylvestris) on the Isle of Wight, UK. The current pattern of distribution of the species, established during a field survey, was related to measures of habitat availability and habitat isolation/fragmentation. Results revealed that wood cricket populations were patchily distributed and mainly found in relatively large mature woodland fragments situated closely (< 50 m) to another occupied site. Although the occurrence of wood cricket was related to fragment area, isolation, habitat availability and woodland age, a logistic regression model revealed that presence of the species was most accurately predicted by fragment isolation and area alone. These results highlight the vulnerability of relatively immobile woodland invertebrate species, such as wood cricket, to the impacts of habitat loss and fragmentation.://000262828900005-399WB Times Cited:0 Cited References Count:53 0921-2973ISI:000262828900005Brouwers, NC Bournemouth Univ, Sch Conservat Sci, Talbot Campus, Poole BH12 5BB, Dorset, England Bournemouth Univ, Sch Conservat Sci, Poole BH12 5BB, Dorset, EnglandDoi 10.1007/S10980-008-9298-4EnglishL<7[ Brown, D. G.2003SLand use and forest cover on private parcels in the Upper Midwest USA, 1970 to 1990777-790Landscape Ecology188agricultural abandonment forest regrowth land use recreational development remote sensing LANDSCAPE CHANGE USE HISTORY VEGETATION DYNAMICS PATTERNS STATES REGIONArticleuThis paper analyzes the interactions between land use and forest cover in the Upper Midwest, USA from 1970 to 1990. New data are presented and interpreted to evaluate the effects of land-use changes, especially abandonment of agriculture and dispersed development, on forest cover throughout the region. Forest-cover data were collected from Landsat satellite imagery and land use was interpreted from aerial photographs for land parcels, based on archival maps of land ownership. In general, forest cover increased throughout the region and throughout the period. Simultaneously, the area used for agriculture declined, much of it being converted to natural uses, and the area of land in low density residential development increased. Forest cover increased most rapidly on low density residential lands and in counties in which a large percentage of homes were for seasonal use (i.e., vacation homes). The data suggest that the transformation of the region from an extractive (i.e., forestry and agriculture) to a recreation-based service economy has played a significant role in the increasing forest cover observed throughout the region.://000188716100004 |ISI Document Delivery No.: 770HA Times Cited: 3 Cited Reference Count: 41 Cited References: *US BUR CENS, US CENS POP *USDA, 1987, US CENS AGR ALLEN THF, 1982, HIERARCHY PERSPECTIV BAILEY RG, 1996, ECOSYSTEM GEOGRAPHY BROWN DG, 1996, P GIS LIS 96 C DENV, P1199 BROWN DG, 2000, J ENVIRON MANAGE, V59, P247 BROWN DG, 2000, REMOTE SENS ENVIRON, V71, P106 BURGESS RL, 1981, FOREST ISLAND DYNAMI CASPERSEN JP, 2000, SCIENCE, V290, P1148 DELCOURT HR, 1987, TRENDS ECOL EVOL, V2, P39 DRZYZGA SA, 2002, LINKING PEOPLE PLACE, P155 FAN S, 1998, SCIENCE, V282, P442 FOSTER DR, 1992, J ECOL, V80, P753 GRUBLER A, 1994, CHANGES LAND USE LAN, P287 HART JF, 1984, GEOGR REV, V74, P192 HUSTON M, 1993, SCIENCE, V262, P1676 JENERETTE GD, 2001, LANDSCAPE ECOL, V16, P611 JOHNSON KM, 1998, WILSON Q, V22, P16 KNIGHT RL, 1995, WILDLIFE RECREATIONI LANT C, 2001, ENVIRON MANAGE, V28, P325 LEATHERBERRY EC, 1993, RESOURCE B USDA LEVIN SA, 1974, P NATL ACAD SCI USA, V71, P2744 LUNETTA RS, 1998, PHOTOGRAMM ENG REM S, V64, P821 MEDLEY KE, 1995, LANDSCAPE ECOL, V10, P161 MEYER WB, 1995, CONSEQUENCES SPR, P25 MILES PD, 1995, RESOURCE B USDA NAGASHIMA K, 2002, FOREST ECOL MANAG, V163, P245 OKUBO A, 1975, ECOLOGY DIFFUSION OMERNIK JM, 1987, ANN ASSOC AM GEOGR, V77, P118 PASTOR J, 1993, ECOLOGY, V74, P467 PICKETT STA, 1982, VEGETATIO, V49, P45 RAILE GK, 1983, RESOURCE B USDA SCHMIDT T, 1996, RESOURCE B USDA SHELLITO BA, 2001, SE DIV ASS AM GEOGR STEWART SI, 1994, THESIS MICHIGAN STAT STYNES DJ, 1997, USDA N CENT, V189, P139 SWANSON FJ, 1988, BIOSCIENCE, V38, P92 TURNER BL, 1995, 35 ROYAL SWED AC SCI WAISANEN PJ, 1997, GLOBAL BIOGEOCHEMICA, V16, P1137 WHITE PS, 1985, ECOLOGY NATURAL DIST, P3 WILLIAMS M, 1989, AM THEIR FORESTS 0921-2973 Landsc. Ecol.ISI:000188716100004Univ Michigan, Sch Nat Recources & Environm, Ann Arbor, MI 48109 USA. Brown, DG, Univ Michigan, Sch Nat Recources & Environm, Ann Arbor, MI 48109 USA. danbrown@umich.eduEnglish <7{Brown, J. R. Carter, J.1998ZSpatial and temporal patterns of exotic shrub invasion in an Australian tropical grassland93-102Landscape Ecology132landscape resistance plant dispersal weed invasion livestock grazing Acacia nilotica AFRICAN SAVANNA RANGE CONDITION PROSOPIS THRESHOLDS MANAGEMENT VEGETATION LANDSCAPE VIEWPOINT DYNAMICS PRAIRIEArticleAprWe used aerial photography from 1960, 1974 and 1994 to quantify meso-scale spatial and temporal invasion patterns of an exotic, leguminous shrub, Acacia nilotica, in a northern Australia grassland. The invasion was episodic, the population remained relatively stable from 1960 to 1974, then exhibited a large increase from 1974 to 1994. This episodic increase did not appear to be regulated by climate or changes in landscape attributes, but rather, paralleled a shift to cattle (a more effective dispersal vector) as the dominant domestic livestock species, implicating more effective dispersal as the proximate cause. We also measured much greater A. nilotica densities adjacent to water courses than in upland areas, suggesting either better quality habitat or greater numbers of seeds deposited there by cattle. We infer that habitat quality rather than seed availability regulates shrub density as density remained constant from 1974 to 1994 in areas that were occupied in the 1960 to 1974 period. There was a significant effect of landscape position on population dynamics of the invasion. A. nilotica increased in both extent and density in riparian areas but remained static in upland areas during 1960-1974. There were significant increases in extent and density in both riparian and upland areas in 1974-1994. Thus, it is likely that landscapes with fewer or smaller riparian areas would be less susceptable to the invasion of A. nilotica. However, the ability of domestic stock to transport seeds across distances that exceed the distance between riparian areas renders this argument less relevant. The transition from open grassland to shrubland may be irreversible in a practical sense, so control programs should emphasize containment of the invasion to existing levels as well as restoration of invaded areas. This will require strategies, tactics and operations to 1) control cattle movement, 2) exclude cattle from seed producing A. nilotica populations, 3) detect new populations early in the life cycle and implement broadscale, low-cost control techniques and 3) prioritize eradication efforts on populations that act as a seed source to uninfested areas.://000077256800003 ISI Document Delivery No.: 143LH Times Cited: 37 Cited Reference Count: 47 Cited References: *AUSTR BUR MET, 1988, CLIM AV *AUSTR BUR STAT, 1994, QUEENSL YB ANDREW MH, 1988, TRENDS ECOL EVOL, V3, P336 ARCHER S, 1994, ECOLOGICAL IMPLICATI, P13 ARCHER S, 1995, ECOSCIENCE, V2, P83 BROWN JR, 1987, VEGETATIO, V73, P73 BROWN JR, 1989, OECOLOGIA, V80, P19 BROWN JR, 1993, P 10 AUSTR WEEDS C W, P471 BURROWS WH, 1987, WOODY WEEDS NATIVE P CARTER JO, 1993, PESTS PASTURES WEED, P128 CHRISTENSEN PE, 1986, ECOLOGY BIOL INVASIO, P97 COLLINS SL, 1987, ECOLOGY, V68, P1243 EVERIST SL, 1975, NATL SYSTEMS ECOLOGI, P39 FORMAN RTT, 1995, LANDSCAPE ECOL, V10, P133 FRIEDEL MH, 1991, J RANGE MANAGE, V44, P422 FRITH HJ, 1970, AUSTR GRASSLANDS, P74 GEORGE MR, 1992, J RANGE MANAGE, V45, P436 GLENDENING GE, 1952, ECOLOGY, V33, P319 GRIME JP, 1979, PLANT STRATEGIES VEG HABER W, 1990, CHANGING LANDSCAPES, P217 HARRINGTON GN, 1991, ECOLOGY, V72, P1138 HARVEY GJ, 1981, P 6 AUSTR WEEDS C GO, V1, P197 HENNESSY JT, 1983, J RANGE MANAGE, V36, P370 HODDER RM, 1978, AUSTR RANGELAND J, V1, P95 HOLLING CS, 1973, ANNUAL REV ECOLOGY S, V4, P1 HUBBLE GD, 1957, 656 CSIRO DIV SOILS KNIGHT CL, 1994, LANDSCAPE ECOL, V9, P117 KNOOP WT, 1985, J ECOL, V73, P235 LAYCOCK WA, 1991, J RANGE MANAGE, V44, P427 MACKEY AP, 1996, PRICKLY ACACIA ACACI MCPHERSON GR, 1990, AM MIDL NAT, V123, P144 MILLER MF, 1996, J TROP ECOL 3, V12, P345 ONEILL RV, 1988, LANDSCAPE ECOL, V2, P63 ORR DM, 1975, TROP GRASSLANDS, V9, P21 ORR DM, 1984, MANAGEMENT AUSTR RAN, P241 PARSONS WT, 1992, NOXIOUS WEEDS AUSTR PEINETTI R, 1993, J RANGE MANAGE, V46, P483 PERRY RA, 1970, AUSTR GRASSLANDS, P246 POLLEY HW, 1994, ECOLOGY, V75, P976 SCHLESINGER WH, 1990, SCIENCE, V247, P1043 SIMPSON JW, 1994, LANDSCAPE ECOL, V9, P261 SKARPE C, 1990, J APPL ECOL, V27, P873 STUARTHILL GC, 1989, J APPL ECOL, V26, P285 SWEET RJ, 1985, ECOLOGY MANAGEMENT W, P229 WADDINGTON CH, 1977, TOOLS THOUGHT WESTOBY M, 1989, J RANGE MANAGE, V42, P266 ZEEMAN EC, 1976, SCI AM, V234, P65 0921-2973 Landsc. Ecol.ISI:000077256800003CSIRO, Davies Lab, Aitkenvale, Qld 4814, Australia. James Cook Univ N Queensland, Dept Environm Studies & Geog, Aitkenvale, Qld 4814, Australia. Brown, JR, CSIRO, Davies Lab, PMB,PO Aitkenvale, Aitkenvale, Qld 4814, Australia.EnglishF<7f5Brown, K. Hansen, A. J. Keane, R. E. Graumlich, L. J.2006PComplex interactions shaping aspen dynamics in the Greater Yellowstone Ecosystem933-951Landscape Ecology216aspen; biophysical; gradient analysis; land cover change; Populus tremuloides NATIONAL-PARK; POPULUS-TREMULOIDES; FIRE; COLORADO; ELK; PERSISTENCE; VEGETATION; HERBIVORY; PATTERNS; TERRAINArticleAugDLoss of aspen (Populus tremuloides) has generated concern for aspen persistence across much of the western United States. However, most studies of aspen change have been at local scales and our understanding of aspen dynamics at broader scales is limited. At local scales, aspen loss has been attributed to fire exclusion, ungulate herbivory, and climate change. Understanding the links between biophysical setting and aspen presence, growth, and dynamics is necessary to develop a large-scale perspective on aspen dynamics. Specific objectives of this research were to (1) map aspen distribution and abundance across the Greater Yellowstone Ecosystem (GYE), (2) measure aspen change in the GYE over the past 50 years (3) determine if aspen loss occurs in particular biophysical settings and (4) investigate the links between biophysical setting and aspen presence, growth, and change in canopy cover. We found that aspen is rare in the GYE, occupying 1.4% of the region. We found an average of 10% aspen loss overall, much lower than that suggested by smaller-scale studies. Aspen loss corresponded with biophysical settings with the lowest aspen growth rates, where aspen was most abundant. The highest aspen growth rates were at the margins of its current distribution, so most aspen occur in biophysical settings less favorable to their growth.://000239484200012 ISI Document Delivery No.: 069YA Times Cited: 0 Cited Reference Count: 48 Cited References: *NAT RES CONS SERV, 1994, STAT SOIL GEOGR STAT *SAS I INC, 2001, SAS SYST WIND AUSTIN MP, 1990, ECOL MONOGR, V60, P161 BARNETT DT, 2001, LANDSCAPE ECOL, V16, P569 BARRETT SW, 1994, INT J WILDLAND FIRE, V4, P65 BARTOS DL, 1994, J RANGELAND MANAGE, V47, P25 BOWERMAN TS, 1997, TARGHEE NATL FOREST BOYCE MS, 1989, JACKSON ELK HERD INT BREIMAN L, 1984, CLASSIFICATION REGRE BROWN K, 2003, THESIS MONTANA STATE BRYANT JP, 1983, OIKOS, V40, P357 BURNHAM KP, 1998, MODEL SELECTION INFE DESPAIN D, 1990, YELLOWSTONE VEGETATI FISCHER WC, 1983, INT141 USDA GTR FOR GALLANT AL, 2003, ECOL APPL, V13, P385 HANSEN AJ, 2000, LANDSCAPE ECOL, V15, P505 HANSEN AJ, 2002, BIOSCIENCE, V52, P151 HESSL AE, 2002, J BIOGEOGR, V29, P889 IHAKA R, 1996, J COMPUTATIONAL GRAP, V5, P299 JENSEN JR, 1996, INTRO DIGITAL IMAGE, P247 JONES JR, 1985, ASPEN ECOLOGY MANAGE, P77 JONES JR, 1985, ASPEN ECOLOGY MANAGE, P9 KAY CE, 1993, NORTHWEST SCI, V67, P94 KAY CE, 1997, J FOREST, V95, P4 KAYE MW, 2003, LANDSCAPE ECOL, V18, P591 KEANE RE, 2006, RMRSGTR168DVD USDA F KULAKOWSKI D, 2004, ECOL APPL, V14, P1603 LARSEN EJ, 2001, THESIS OREGON STATE LITTELL JS, 2002, THESIS MONTANA STATE LOOPE LL, 1973, QUATERNARY RES, V3, P425 MANIER DJ, 2002, FOREST ECOL MANAG, V167, P263 MARSTON RA, 1991, CONSERV BIOL, V5, P338 MEANS JE, 1994, PNWGTR340 USDA FOR S NEILSON RP, 1992, LANDSCAPE ECOL, V7, P27 NETER J, 1996, APPL LINEAR STAT MOD PARMENTER AW, 2003, ECOL APPL, V13, P687 PEET RK, 1978, J BIOGEOGR, V5, P275 POWELL SL, 2004, THESIS MONTANA STATE RENKIN R, 1996, ECOLOGICAL IMPLICATI, P95 RIPPLE WJ, 2001, BIOL CONSERV, V102, P227 ROMME WH, 1982, ECOL MONOGR, V52, P199 ROMME WH, 1995, ECOLOGY, V76, P2097 SUZUKI K, 1999, LANDSCAPE ECOL, V14, P231 THORNTON PE, 1997, J HYDROL, V190, P214 TOMAN TL, 1997, BRUCELLOSIS BISON EL, P56 WHITE CA, 1998, WILDLIFE SOC B, V26, P449 WHITLOCK C, 1993, QUATERNARY RES, V39, P231 WIRTH T, 1996, MONITORING ASPEN DEC 0921-2973 Landsc. Ecol.ISI:000239484200012AUSDA, Forest Serv, Missoula Fire Sci Lab, Rocky Mt Res Stn, Missoula, MT 59807 USA. Montana State Univ, Dept Ecol, Bozeman, MT 59717 USA. Montana State Univ, Big SKY Inst, Bozeman, MT 59717 USA. Keane, RE, USDA, Forest Serv, Missoula Fire Sci Lab, Rocky Mt Res Stn, 5775 W Hwy 10, Missoula, MT 59807 USA. rkeane@fs.fed.usEnglish<7D,Brown, P. M. Kaufmann, M. R. Shepperd, W. D.1999hLong-term, landscape patterns of past fire events in a montane ponderosa pine forest of central Colorado513-532Landscape Ecology146crossdating dendrochronology fire chronology fire extent fire frequency fire scars fire regimes fire seasonality fire severity SOUTHWESTERN UNITED-STATES FRONT RANGE HISTORY DISTURBANCE MANAGEMENT MODELS COMMUNITIES EQUILIBRIUM ECOLOGY CLIMATEArticleDecParameters of fire regimes, including fire frequency, spatial extent of burned areas, fire severity, and season of fire occurrence, influence vegetation patterns over multiple scales. In this study, centuries-long patterns of fire events in a montane ponderosa pine - Douglas-fir forest landscape surrounding Cheesman Lake in central Colorado were reconstructed from fire-scarred trees and inferences from forest stand ages. We crossdated 153 fire-scarred trees from an approximately 4000 ha study area that recorded 77 total fire years from 1197 to the present. Spatial extent of burned areas during fire years varied from the scale of single trees or small clusters of trees to fires that burned across the entire landscape. Intervals between fire years varied from 1 to 29 years across the entire landscape to 3 to 58 years in one stand, to over 100 years in other stands. Large portions of the landscape did not record any fire for a 128 year-long period from 1723 to 1851. Fire severity varied from low-intensity surface fires to large-scale, stand-destroying fires, especially during the 1851 fire year but also possibly during other years. Fires occurred throughout tree growing seasons and both before and after growing seasons. These results suggest that the fire regime has varied considerably across the study area during the past several centuries. Since fires influence plant establishment and mortality on the landscape, these results further suggest that vegetation patterns changed at multiple scales during this period. The fire history from Cheesman Lake documents a greater range in fire behavior in ponderosa pine forests than generally has been found in previous studies.://000082563500001  ISI Document Delivery No.: 235VP Times Cited: 49 Cited Reference Count: 63 Cited References: ARNO SF, 1977, INT42 USDA FOR SERV ARNO SF, 1995, RESTORATION MANAGEME, V13, P32 BAISAN CH, 1990, CAN J FOREST RES, V20, P1559 BAKER WL, 1992, LANDSCAPE ECOL, V7, P181 BARRETT SW, 1997, INTGTR370 USDA FOR S BESSIE WC, 1995, ECOLOGY, V76, P747 BORMANN FH, 1979, PATTERN PROCESS FORE BROWN PM, IN PRESS ECOSCIENCE BROWN PM, 1996, INT J WILDLAND FIRE, V6, P97 COOPER CF, 1960, ECOL MONOGR, V30, P129 COVINGTON WW, 1992, OLD GROWTH FORESTS S, P81 COVINGTON WW, 1994, J FOREST, V92, P39 COVINGTON WW, 1994, J SUSTAINABLE FOREST, V2, P13 COVINGTON WW, 1997, J FOREST, V95, P23 DEANGELIS DL, 1987, ECOL MONOGR, V57, P1 DIETERICH JH, 1980, P FIR HIST WORKSH, P8 DIETERICH JH, 1984, FOREST SCI, V30, P238 FINNEY MA, 1995, INT J WILDLAND FIRE, V5, P197 FRITTS HC, 1976, TREE RINGS CLIMATE FULE PZ, 1997, ECOL APPL, V7, P895 GOLDBLUM D, 1992, PHYSICAL GEOGR, V13, P133 GRISSINOMAYER HD, 1995, THESIS U ARIZONA TUC HEINSELMAN ML, 1981, FIRE REGIMES ECOSYST, P7 HOLLING CS, 1996, CONSERV BIOL, V10, P328 JOHNSON EA, 1994, ADV ECOL RES, V25, P239 KAUFMANN MR, UNPUB CAN J FOR RES KAUFMANN MR, 1994, RM246 USDA FOR SERV KAUFMANN MR, 1997, B ECOL SOC AM PROGR, V78, P120 KAUFMANN MR, 1998, RMRSGTR19 USDA FOR S LORIMER CG, 1985, CAN J FOREST RES, V15, P200 MAST JN, 1993, THESIS U COLORADO BO MORGAN P, 1994, J SUSTAINABLE FOREST, V2, P87 MUTCH RW, 1970, ECOLOGY, V51, P1046 MUTCH RW, 1993, PNW310 USDA FOR SERV NETER J, 1989, APPL LINEAR REGRESSI ORTLOFF W, 1996, TREE RINGS ENV HUMAN, P89 PEARSON GA, 1933, ECOLOGY, V17, P270 PEET RK, 1981, VEGETATIO, V45, P3 PICKETT STA, 1985, ECOLOGY NATURAL DIST PYNE SJ, 1984, INTRO WILDLAND FIRE RIECE SR, 1994, AM SCI, V82, P424 ROMME WH, 1982, ECOL MONOGR, V52, P199 ROMME WR, 1980, P FIR HIST WORKSH OC, P8 SAVAGE M, 1996, ECOSCIENCE, V3, P310 SMITH TM, 1988, VEGETATIO, V74, P143 SOUSA WP, 1984, ANNU REV ECOL SYST, V15, P353 STOKES MA, 1968, INTRO TREE RING DATI SWETNAM TW, 1990, EFFECTS FIRE MANAGEM, P6 SWETNAM TW, 1990, SCIENCE, V249, P1017 SWETNAM TW, 1992, OLD GROWTH FORESTS S, P24 SWETNAM TW, 1993, SCIENCE, V262, P885 SWETNAM TW, 1996, FIRE EFFECTS SW FORE, P11 SWETNAM TW, 1996, P S EFF FIR MADR PRO, P15 SWETNAM TW, 1998, J CLIMATE, V11, P3128 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1993, LANDSCAPE ECOL, V8, P213 URBAN DL, 1994, SUSTAINABLE ECOLOGIC, P127 VEBLEN TT, 1986, PHYSICAL GEOGR, V7, P1 VEBLEN TT, 1996, UNPUB FIRE ECOLOGY W VEBLEN TT, 1999, FIRE HIST NO PATAGON WATT AS, 1947, J ECOL, V35, P1 WHITE AS, 1985, ECOLOGY, V66, P589 ZARICKSSON O, 1977, OIKOS, V29, P22 0921-2973 Landsc. Ecol.ISI:000082563500001Rocky Mt Tree Ring Res Inc, Ft Collins, CO 80526 USA. Brown, PM, Rocky Mt Tree Ring Res Inc, 2901 Moore Ln, Ft Collins, CO 80526 USA.English|? 3Bruggeman, D. J. Jones, M. L. Scribner, K. Lupi, F.2009\Relating tradable credits for biodiversity to sustainability criteria in a dynamic landscape775-790Landscape Ecology246Jul Tradable biodiversity credit systems provide flexible means to resolve conflicts between development and conservation land-use options for habitats occupied by threatened or endangered species. We describe an approach to incorporate the influence of habitat fragmentation into the conservation value of tradable credits. Habitat fragmentation decreases gene flow, increases rates of genetic drift and inbreeding, and increases probabilities of patch extinction. Importantly, tradable credit systems will change the level of fragmentation over time for small and/or declining populations. We apply landscape equivalency analysis (LEA), a generalizable, landscape-scale accounting system that assigns conservation value to habitat patches based on patch contributions to abundance and genetic variance at landscape scales. By evaluating habitat trades using two models that vary the relationship between dispersal behaviors and landscape patterns, we show that LEA provides a novel method for limiting access to habitat at the landscape-scale, recognizing that the appropriate amount of migration needed to supplement patch recruitment and to offset drift and inbreeding will vary as landscape pattern changes over time. We also found that decisions based on probabilities of persistence alone would ignore changes in migration, genetic drift, and patch extinction that result from habitat trades. The general principle of LEA is that habitat patches traded should make at least equivalent contributions to rates of recruitment and migration estimated at a landscape scale. Traditional approaches for assessing the "take" and "jeopardy" standards under the Endangered Species Act based on changes in abundance and probability of persistence may be inadequate to prevent trades that increase fragmentation.://000268248100006ABruggeman, Douglas J. Jones, Michael L. Scribner, Kim Lupi, Frank 0921-2973ISI:00026824810000610.1007/s10980-009-9351-y_|?2VBruggeman, Douglas J. Wiegand, Thorsten Walters, Jeffrey R. Gonzalez Taboada, Fernando2014Contrasting the ability of data to make inferences regarding dispersal: case study of the Red-cockaded woodpecker (Picoides borealis)639-653Landscape Ecology294AprDispersal is a critical biological process that contributes to the persistence of species in complex and dynamic landscapes. However, little is known about the ability of different types of data to reveal how species interact with landscape patterns during dispersal. Further, application of process-based, landscape-scale models able to capture the influence of land use and climate change are limited by this lack of dispersal knowledge. Here we highlight a method for building such models when dispersal parameters are unknown, but information on the mating system and survival are available. We applied a common statistical framework, rooted in information theory, to contrast the ability of abundance, movement, and genetic data to estimate dispersal parameters for endangered Red-cockaded woodpecker (RCW), using an individual-based, spatially-explicit population model. Dispersal was modeled as a multifaceted process in which foray distance, long-distance dispersal, competition for mates, and landscape permeability were treated as uncertain. We found that movement data are three-times more powerful than abundance data collected at the same spatial and temporal scales. However, habitat occupancy data collected over much a shorter time scale but at regional spatial scales were very effective for estimating dispersal. We also found that one-year of abundance data provided a similar reduction in uncertainty as genetic differences among breeding groups estimated using a 24-year pedigree. Substituting population genetic data for movement and abundance data often led to the same parameter values, but not always. Our study highlights important differences in the information content of data commonly collected in the field.!://WOS:000333533800007Times Cited: 1 0921-2973WOS:00033353380000710.1007/s10980-014-0011-5-<7WBrunet, R. C. Astin, K. B.1997GSpatio-temporal variations in sediment nutrient levels: the River Adour171-184Landscape Ecology123riparian vegetation; sediment retention; nitrogen and carbon transport AGRICULTURAL WATERSHEDS; RIPARIAN ZONE; RETENTION; NITROGEN; DYNAMICS; FOREST; SOIL; PERSPECTIVE; DEPOSITION; ECOSYSTEMSArticleJunThe retention capacity of the flood zone of the River Adour (SW France) has been estimated. This zone consists of ca, 1 km(2) Of riparian vegetative strips (rvs) and ca. 16 km(2) of floodplain (Barthes), A novel method of sediment collection has been used in both sectors to determine the quantities of sediment together with concentrations of organic nitrogen and carbon. The study indicates that the vegetative strips accumulate large quantities of sediment with total nitrogen and total carbon concentrations of ca, 4 mg/g dry matter and ca. 30 mg/g dry matter respectively. These concentrations were found to vary as a function of topography and vegetation. The floodplain receives less sediment but the observed concentrations of nitrogen and carbon are more variable and found in the range of 1-9 mg/g dry matter and 10-82 mg/g dry matter respectively. The highest levels of C and N are generally found in wooded areas of the floodplain.://A1997XV63400005 r ISI Document Delivery No.: XV634 Times Cited: 9 Cited Reference Count: 61 Cited References: *CONS GEN LAND, 1991, SCHEM ORG BARTH AD *TECHN, 1976, TECHN INSTR SYST TEC ALLEN JRL, 1965, SEDIMENTOLOGY, V5, P81 AUBERTIN GM, 1974, J ENVIRON QUAL, V3, P243 BESCHTA RL, 1986, WATER RES B, V22, P370 BORMANN FH, 1967, SCIENCE, V155, P424 BORMANN FH, 1969, BIOSCIENCE, V19, P600 BORMANN FH, 1974, ECOL MONOGR, V44, P255 BRADY NC, 1990, NATURE PROPERTIES SO, P279 BRINSON MM, 1983, DYNAMICS LOTIC ECOSY, P199 BRINSON MM, 1984, J APPL ECOL, V21, P1041 BRUNET RC, 1994, RES MANAGE, V8, P55 BRUNET RC, 1994, THESIS U P SABATIER, V93 BRUNET RC, 1995, ACTA OECOL, V16, P331 BRUNET RC, 1995, IN PRESS HYDROBI JUN BURESH RJ, 1980, ADV AGRON, V33, P149 BURKE IC, 1989, ECOLOGY, V70, P1115 CLAUSEN JC, 1990, J ENVIRON QUAL, V19, P83 COOPER AB, 1990, HYDROBIOLOGIA, V202, P13 COOPER JR, 1987, SOIL SCI SOC AM J, V51, P416 COUNILH F, 1985, THESIS U BORDEAUX COUNILH P, 1982, J FRANCAIS HYDROLOGI, V37, P35 DILLAHA TA, 1988, J WATER POLLUT CONTR, V60, P1231 DOYLE RC, 1977, ASAE, P77 FOSTER GR, 1982, ASAE MONOGRAPH, V5 GAZELLE F, 1983, 82 DDE, P10 GREGORY SV, 1991, BIOSCIENCE, V41, P540 GRUBAUGH JW, 1989, HYDROBIOLOGIA, V174, P235 HAUPT HF, 1965, J FOREST, V63, P664 HOPMANS P, 1987, FOREST ECOL MANAG, V20, P209 HOROWITZ AJ, 1985, 2277 US GEOL SURV WA HOWARDWILLIAMS C, 1985, FRESHWATER BIOL, V15, P391 HYNES HBN, 1975, VERH INT VEREIN LIMN, V19, P1 JOHNSTON CA, 1984, J ENVIRON QUAL, V13, P282 KARR JR, 1977, 600377097 US EPA LAMBERT CP, 1987, GEOGR ANN A, V69, P393 LEE G, 1975, EFFECTS MARSHES WATE, P105 LIKENS GE, 1974, BIOSCIENCE, V24, P447 LOWRANCE R, 1984, BIOSCIENCE, V34, P374 LOWRANCE R, 1985, J SOIL WATER CONSERV, V40, P87 LOWRANCE R, 1986, J SOIL WATER CONSERV, V41, P266 LOWRANCE R, 1988, J ENVIRON QUAL, V17, P734 LOWRANCE RR, 1984, J ENVIRON QUAL, V13, P27 MORING JR, 1982, HYDROBIOLOGIA, V88, P295 NICHOLS JD, 1984, SOIL SCI SOC AM J, V48, P1382 PETERJOHN WT, 1984, ECOLOGY, V65, P1466 PETERSON DL, 1985, FOREST ECOL MANAG, V12, P73 PINAY G, 1988, REGUL RIVER, V2, P507 PINAY G, 1990, ECOLOGY MANAGEMENT A, P141 PLANTYTABACCHI AM, 1987, MEMOIRE DEA DES PONNAMPERUMA FN, 1972, ADV AGRON, V24, P25 SCHLOSSER IJ, 1981, ENVIRON MANAGE, V5, P233 SCHWER CB, 1989, J ENVIRON QUAL, V18, P446 SPEAKER RW, 1984, VERH INT VER LIMNOL, V22, P1835 STRAHLER AN, 1957, T AM GEOPHYSICAL UNI, V38, P913 SWANSON FJ, 1982, ANAL CONIFEROUS FORE, P267 TOLLNER EW, 1977, 762056 AM SOC AGR EN TRISKA FJ, 1984, VERH INT VER LIMNOL, V22, P1876 VITOUSEK PM, 1975, BIOSCIENCE, V25, P376 WILSON LG, 1967, T ASAE, P35 WONG SL, 1981, DESIGN VEGETATIVE BU 0921-2973 Landsc. Ecol.ISI:A1997XV634000054CNRS,CTR ECOL SYST FLUVIAUX,F-31055 TOULOUSE,FRANCE.English <7#Brunzel, S. Elligsen, H. Frankl, R.2004Distribution of the Cinnabar moth Tyria jacobaeae L. at landscape scale: use of linear landscape structures in egg laying on larval hostplant exposures21-27Landscape Ecology191dispersal; hostplant exposures; landscape scale distribution; linear structures; Tyria jacobaeae METAPOPULATION DYNAMICS; POPULATION-DYNAMICS; DEPENDENT MIGRATION; BUTTERFLIES; DISPERSAL; CONNECTIVITY; CONSERVATION; EXTINCTION; CORRIDORS; SURVIVALArticleoThe distribution of the xerothermophilous Cinnabar moth Tyria jacobaeae was studied in a low mountain region in western Germany between 1989 and 2001. T. jacobaeae started its immigration into the study area in 1989 and first established populations in climatically favoured habitats like abandoned quarries and train stations where the larval host plant, ragwort (Senecio jacobaea), occurs. Analysis of landscape features (altitude, morphology) reveals that T. jacobaeae then dispersed along valleys with roads to higher altitudes of the study area. Elevations of occupied sites increased between 1989 and 2001. In order to investigate whether dispersal is affected by linear structures like valleys or roads with gravelled verges, hostplant exposures were placed at a distance of 600 m to the next population of T. jacobaeae. The experiments suggest that egglaying predominantly took place on exposures in valleys with roads and sparsely plant-covered verges but can also occur along valleys lacking roads and suitable habitats. However, larvae were never recorded on Senecio exposures which were placed aside from valleys and roads.://000189394100002 ISI Document Delivery No.: 780RA Times Cited: 2 Cited Reference Count: 30 Cited References: ANDERSON GS, 1997, LANDSCAPE ECOL, V12, P261 BAGUETTE M, 1998, ACTA OECOL, V19, P17 BROWNE DR, 1999, LANDSCAPE ECOLOGY, V14, P53 BRUNZEL S, 1996, Z OKOL NATURSCHUTZ, V5, P37 BRUNZEL S, 1999, CONTRIBUTIONS ENTOMO, V49, P447 BRUNZEL S, 2002, CONTRIBUTIONS ENTOMO, V52, P241 CROWLEY MJR, 2001, J ANIM ECOL, V70, P410 CROWLEY MJR, 2001, J ANIM ECOL, V70, P426 DEMPSTER JP, 1971, OECOLOGIA BERL, V7, P26 DEMPSTER JP, 1997, OECOLOGIA, V111, P549 EBERT G, 1997, SCHMETTERLINGE BADEN, V5 FAHRIG L, 1985, ECOLOGY, V66, P1762 HANSKI I, 1991, BIOL J LINN SOC, V42, P3 HANSKI I, 1994, BIOL CONSERV, V68, P167 HANSKI I, 1994, ECOLOGY, V75, P747 HANSSON L, 1991, BIOL J LINN SOC, V42, P89 KINDVALL O, 1999, J ANIM ECOL, V68, P172 LEDERHOUSE RC, 1982, BEHAV ECOL SOCIOBIOL, V10, P109 MOUSSON L, 1999, BIOL CONSERV, V87, P285 MUNGUIRA ML, 1992, J APPL ECOL, V29, P316 PETIT S, 2001, OIKOS, V92, P491 ROY DB, 2001, J ANIM ECOL, V70, P201 SUTCLIFFE OL, 1996, CONSERV BIOL, V10, P1359 SUTCLIFFE OL, 1997, OECOLOGIA, V109, P229 THOMAS CD, 2001, NATURE, V411, P577 VANDERMEIJDEN E, 1976, NETH J ZOOL, V26, P136 VANDERMEIJDEN E, 1979, OECOLOGIA, V42, P307 VANDERMEIJDEN E, 1991, NETH J ZOOL, V41, P158 WARREN MS, 2001, NATURE, V414, P65 WITH KA, 1997, OIKOS, V78, P151 0921-2973 Landsc. Ecol.ISI:000189394100002Univ Marburg, Res Ctr Environm & Soc, D-35032 Marburg, Germany. Univ Marburg, Fac Biol, Dept Environm Protect 2, D-35032 Marburg, Germany. Brunzel, S, Univ Marburg, Res Ctr Environm & Soc, Karl Frisch Str 8A, D-35032 Marburg, Germany. Brunzel@mailer.uni-marburg.deEnglishA?Marybeth Buechner1989gAre small-scale landscape features important factors for field studies of small mammal dispersal sinks?191-199Landscape Ecology23Nlandscape ecology, dispersal, patch, emigration, small mammals, dispersal sink7Interest in the influence of landscape features on animal movement has been widespread; however, few field studies of the emigration of small mammals from patches of habitat directly consider the effects of the smallscale landscape features. The simulation models of Stamps et al. (1987a, b) and Buechner (1987a, b) suggest that the size of a dispersal sink relative to the size of the source patch, the average distance traveled by dispersers in the sink, the ease with which dispersers cross the edge between the sink and a source patch, and source patch perimeter:area ratio may all be important influences on emigration rates. A review of field studies of small mammal dispersal into sinks suggests that in a substantial fraction of such studies the values of these factors fall within the ranges that the simulation models indicate have the greatest potential effect on emigration rates. New field studies of dispersal sinks that include a consideration of these factors are necessary in order to evaluate the magnitude of the impact of these factors on natural populations.L<7x&Buijs, A. E. Pedroli, B. Luginbuhl, Y.2006uFrom hiking through farmland to farming in a leisure landscape: changing social perceptions of the European landscape375-389Landscape Ecology213culture; Europe; France; landscape; nature landscape preference; perception; spatial planning; the Netherlands; views of nature DISCOURSESArticleApr_The idea that landscape has been created by human activities on a biophysical basis allows for clear cause-effect reasoning. However, landscape planning and management practice learns that it is impossible to neglect the social perception of landscape, i.e. the ways people think about nature and landscape. It is the result of social research and human sciences of the last decade that a differentiation in views of nature and landscape can be identified in the different groups of social actors in the landscape. Case studies from France and the Netherlands show a marked change in values attributed to nature and landscape in the end of the last century. Social demand for landscape is growing and a shift from a functional image of nature and landscape to a more hedonistic image like the Arcadian and wilderness images has taken place. Comparing the Netherlands with France and rural with urban inhabitants, the influence of urbanisation is evident in this process. It is further shown that images of nature vary considerably between for example farmers, urban residents, hunters and conservationists. The way people perceive landscape seems determined by their functional ties with the landscape and the social praxis in which they encounter the landscape. It is concluded that the concept of landscape is nearer to the lifeworld of people than the abstract notions of nature and biodiversity. This implies a big challenge both for national and international landscape policies and for local landscape management initiatives to be developed, taking into due consideration both the material and immaterial nature of landscape.://000236968500006 % ISI Document Delivery No.: 034ZD Times Cited: 0 Cited Reference Count: 62 Cited References: *COUNC EUR, 2000, EUR LANDSC CONV EUR, V176 *IFEN, 2000, SENS EC FRANC TRAV O, P190 *INED, 1992, ENQ NAT PAYS AARTS MNC, 1998, THESIS WAGENINGEN U BASTIAN O, 2002, DEV PERSPECTIVES LAN BUCHECKER M, 2003, LANDSCAPE URBAN PLAN, V64, P29 BUIJS AE, CONSUMENT BURGER BUIJS AE, 1997, 546 STAR CENTR BUIJS AE, 1998, 623 STAR CENTR BUIJS AE, 2000, LANDSCHAP, V17, P97 CADIOU N, 1995, PAYSAGE PLURIEL APPR, P19 COETERIER JF, 1996, LANDSCAPE URBAN PLAN, V34, P27 CONAN M, 1994, CINQ PROPOSITIONS PO, P33 DEGROOT WT, 1992, ENV SCI THEORY CONCE DEGROOT WT, 2002, LANDSC URBAN PLAN, V63, P127 EDER K, 1996, SOCIAL CONSTRUCTION FILIUS P, 2000, 104 ALT GREEN WORLD FROUWS J, 1998, SOCIOL RURALIS, V38, P54 HERVIEU B, 1996, BONHEUR CAMPAGNES PR, P155 JACOBS MH, 2002, WATERBEELDEN STUDIE JOLLIVET M, 1996, EUROPE SES CAMPAGNES JONES O, 1995, J RURAL STUD, V11, P35 JONGMAN R, 2004, NEW DIMENSIONS EUROP KEULARTZ J, 2004, ENVIRON VALUE, V13, P81 KLIJN J, 2000, P EUR C LANDSC EC TH, P163 KOLKMAN G, 2003, WIE IS ER BANG STAD, P124 LOCKWOOD M, 1999, ENVIRON VALUE, V8, P381 LOFGREN O, 1994, TOPOS, V6, P6 LUGINBUHL Y, 1995, SENSIBILITES PAYSAGE LUGINBUHL Y, 2001, ENV QUESTION SOCIALE, P49 LUGINBUHL Y, 2001, RAPPORT SEANCE INAUG, P7 LUGINBUHL Y, 2002, TRADITION INNOVATION, P82 LUGINBUHL Y, 2003, HAIE BOCAGES ORGANIS MACNAGHTEN P, 1998, CONTESTED NATURES MINGAY GF, 1989, RURAL IDYLL PALANG H, 2003, LANDSCAPE INTERFACES, P414 PEDROLI B, 2000, LANDSCAPE OUR HOME L, P222 PEDROLI B, 2005, ISSUES PERSPECTIVES, P259 PINE JB, 1999, EXPERIENCY EC WORK I POTSCHIN M, 2002, DEV PERSPECTIVES LAN, P38 RINK D, 2004, NATURVERSTANDNISSE N SCHAMA S, 1995, LANDSCAPE MEMORY SEAMON D, 1987, ADV ENV BEHAV DESIGN, P344 STEG L, 2004, PSYCHOL DUURZAME ONT TERRASSON D, 2000, LANDSCAPE OUR HOME L, P173 THIEBAUT L, 2002, NATURE SCI SOC, V10, P54 THOMPSON M, 1990, CULTURAL THEORY TOOGOOD M, 2001, EUR NAT, P13 TRESS B, 2001, LANDSCAPE URBAN PLAN, V57, P137 TURNHOUT E, 2004, ENVIRON VALUE, V13, P187 ULRICH SR, 1993, BIOPHILIA HYPOTHESIS URRY J, 1990, TOURIST GAZE LEISURE VANDENBERG AE, 1999, INDIVIDUAL DIFFERENC VANDENBERG AE, 2001, VAN BUITEN WORDT JE VANDENBORN RJG, 2001, ENVIRON CONSERV, V28, P65 VANDERPLOEG JD, 2002, LIVING COUNTRYSIDES VANKOPPEN, 2002, THESIS WAGENINGEN U VANMANSVELT JD, 2003, LANDSCAPE INTERFACES, P375 VOISENAT C, 1995, PAYSAGE PLURIEL APPR VOLK M, 2002, DEV PERSPECTIVES LAN, P1 WASCHER DM, 2000, FACE EUROPE POLICY P, V4 WILSON A, 1992, CULTURE NATURE 0921-2973 Landsc. Ecol.ISI:000236968500006Alterra Green World Res, Landscape Ctr, NL-6700 AA Wageningen, Netherlands. Univ Paris 01, LADYSS, F-75005 Paris, France. Buijs, AE, Alterra Green World Res, Landscape Ctr, POB 47, NL-6700 AA Wageningen, Netherlands. arjen.buijs@wur.nlEnglish~?RBunce, R. G. H. Metzger, M. J. Jongman, R. H. G. Brandt, J. De Blust, G. Elena-Rossello, R. Groom, G. B. Halada, L. Hofer, G. Howard, D. C. Kovar, P. Mucher, C. A. Padoa-Schioppa, E. Paelinx, D. Palo, A. Perez-Soba, M. Ramos, I. L. Roche, P. Skanes, H. Wrbka, T.2008hA standardized procedure for surveillance and monitoring European habitats and provision of spatial data11-25Landscape Ecology231Both science and policy require a practical, transmissible, and reproducible procedure for surveillance and monitoring of European habitats, which can produce statistics integrated at the landscape level. Over the last 30 years, landscape ecology has developed rapidly, and many studies now require spatial data on habitats. Without rigorous rules, changes from baseline records cannot be separated reliably from background noise. A procedure is described that satisfies these requirements and can provide consistent data for Europe, to support a range of policy initiatives and scientific projects. The methodology is based on classical plant life forms, used in biogeography since the nineteenth century, and on their statistical correlation with the primary environmental gradient. Further categories can therefore be identified for other continents to assist large scale comparisons and modelling. The model has been validated statistically and the recording procedure tested in the field throughout Europe. A total of 130 General Habitat Categories (GHCs) is defined. These are enhanced by recording environmental, site and management qualifiers to enable flexible database interrogation. The same categories are applied to areal, linear and point features to assist recording and subsequent interpretation at the landscape level. The distribution and change of landscape ecological parameters, such as connectivity and fragmentation, can then be derived and their significance interpreted."://WOS:000251796100004 Times Cited: 0WOS:00025179610000410.1007/s10980-007-9173-8\? Burel ,F.1989QLandscape Structure Effects on Carabid Beetles Spatial Patterns in Western France215-226Landscape Ecology24NCarabids, Hedgerow, Landscape, Spatial distribution, Landscape ecology, FrancegAnalysis of carabids spatial distribution in a hedgerow network landscape in western France, pinpoints the role of the landscape among other levels of ecological organization. Dispersion of forest species differs among core forest species, peninsula forest species and corridor forest species. Abundance 04 forest carabid species in a particular hedgerow is related to the positive effect of a dense herbaceous layer and the presence of a tree layer which is enhanced by the presence of two parallel hedgerows, especially along lanes. At the landscape level distance from the largest forest determines abundance of forest species within the first kilometer out of it. Beyond that, abundance is independent of distance from the source forest and the discriminant ecological factors are: hedgerow structure, presence of lanes bordered by two hedgerows.?IFrancoise Burel1992TEffect of landscape structure and dynamics on species diversity in hedgerow networks161-174Landscape Ecology63ilandscape ecology, landscape structure, dynamics, hedgerow network, carabid beetles, spatial distributionStructure and dynamics of a hedgerow network landscape over the last thirty years are compared to the current spatial distribution of carabid beetles in hedgerows. Spatial and temporal scales are chosen according to the observed phenomena, and a multiscale approach used. None of the descriptors of landscape at any given period of time is related to carabid assemblages except heterogeneity in 1985. This measure of landscape structure in Brittany integrates part of the recent changes. Carabid assemblages are also related to overall landscape trajectories through time. Relationship between landscape and carabid spatial patterns may be modeled at the stand and landscape levels.?)Francoise Burel Jacques Baudry1990EStructural dynamic of a hedgerow network landscape in Brittany France197-210Landscape Ecology44Xlandscape ecology, hedgerow networks, spatial dynamic, scale, agricultue, rural planningChanges in agricultural systems since the 50’s led to considerable changes in rural hedgerow network landscapes. In these landscapes, ecological processes depend on the spatial structure of the network (length of hedgerows, connectedness, grain size). This paper reports on a study of the dynamics of such a landscape at four periods of time (1952, 1961, 1972, 1985) done on 26 contiguous 16 ha quadrats. A correspondence analysis of the data matrix yields a gradient of change from dense highly connected networks to heterogeneous landscapes with few hedgerows. The study of individual trajectories of the quadrats allowed them to be regrouped in various types of changes. It is possible for a quadrat to go through several pathways. Rates of change varied through time, the 1961- 1972 period had most changes. The use of supplementary elements in correspondence analysis proves to be a useful way to approach spatial hierarchy and allows a better understanding of the differentiation of landscape units.<7Burger, A. E. Page, R. E.2007aThe need for biological realism in habitat modeling: a reinterpretation of Zharikov et al. (2006) 1273-1281Landscape Ecology229ecological modeling; biological realism; habitat use; nest site selection; marbled murrelet; Brachyramphus marmoratus; British Columbia MARBLED MURRELETS; MICROCLIMATIC GRADIENTS; BREEDING SUCCESS; CLEAR-CUT; FOREST; LANDSCAPE; SELECTION; INTERIOR; AREASArticleNovfZharikov et al. (2006: Landscape Ecology 21:107-120) modeled the nest-site habitat use of marbled murrelets (Brachyramphus marmoratus) in Desolation Sound (DS) and Clayoquot Sound (CS), British Columbia. They compared known nest sites, located with radio-telemetry, with randomly-located points within the same areas. Their conclusions suggest that murrelets tended to nest in disproportionately smaller fragments within the more disturbed DS landscape; streams, steeper slopes, and lower elevations were selected in both landscapes; murrelets nested closer to recent clearcuts than would be expected in the DS landscape; and survivorship of nestlings was greater in areas with recent clearcuts and was positively correlated with recent habitat fragmentation. These conclusions are contrary to current management guidelines in British Columbia, and therefore require close scrutiny. Our detailed examination reveals flaws in their use of data, application of modeling, and most seriously, interpretation of the results. Problems include: conceptual errors in the interpretation of models; inappropriate spatial resolution; confusing use and interpretation of fragmentation and patch size data; overemphasis of statistically significant but biologically trivial results; and ignoring some contradictory studies. We conclude that it would be risky to apply the results from Zharikov et al. in the selection of murrelet nesting habitat for management purposes in British Columbia. Our review identifies issues that may arise in other ecological modeling studies and stresses the need for biological realism in addition to statistical rigour.://000250207500001 YCited Reference Count: 40 Cited References: *CAN MARBL MURR RE, 2003, MARBL MURR CONS ASS *PROV BRIT COL, 2004, MARBL MURR BRACH MAR BAHN V, 2002, MULTISCALE STUDIES P, P101 BEISSINGER SR, 2006, ORNITHOLOGICAL MONOG, V59, P1 BRADLEY RW, 2001, NW NATURALIST, V82, P52 BRADLEY RW, 2002, BREEDING ECOLOGY RAD BRADLEY RW, 2004, J WILDLIFE MANAGE, V68, P318 BROSOFSKE KD, 1997, ECOL APPL, V7, P1188 BURGER AE, 2000, CONDOR, V102, P915 BURGER AE, 2001, J WILDLIFE MANAGE, V65, P696 BURGER AE, 2002, 387 TECH REP SER HAB BURNHAM KP, 2002, MODEL SELECTION MULT CAUGHLEY G, 1994, J ANIM ECOL, V63, P215 CHEN JQ, 1993, AGR FOREST METEOROL, V63, P219 CHEN JQ, 1995, ECOL APPL, V5, P74 CHEN JQ, 1999, BIOSCIENCE, V49, P288 DONALDSON A, 2004, STAND METHODS IDENTI HULL CL, 2001, AUK, V118, P1036 HUNSAKER CT, 2001, SPATIAL UNCERTAINTY HUSTON MA, 2002, PREDICTING SPECIES O, P7 KREMSATER L, 1999, FOREST FRAGMENTATION, P117 MANLEY IA, 1999, PACIFIC SEABIRDS, V26, P40 MANLY B, 2002, RESOURCE SELECTION A MARZLUFF JM, 1999, FOREST FRAGMENTATION, P155 MASSELINK MNM, 2001, THESIS U VICTORIA VI MCSHANE C, 2004, EVALUATION REPORT 5 MEYER CB, 2002, CONSERV BIOL, V16, P755 MEYER CB, 2002, LANDSCAPE ECOL, V17, P95 MIZUNO K, 1998, ARCTIC ALPINE RES, V30, P340 NELSON SK, 1995, USDA PAC SW, V152, P89 OCONNOR RJ, 2002, PREDICTING SPECIES O, P25 PARISH R, 2004, OECOLOGIA, V141, P562 RAPHAEL MG, 2002, STUDIES AVIAN BIOL, V25, P221 RIPPLE WJ, 2003, NW NATURALIST, V84, P80 RODWAY MS, 2002, MULTISCALE STUDIES P, P57 RRALPH CJ, 1995, PSWGTR152 TRIPP T, 2001, SYNOPSIS MARBLED MUR VISSCHER DR, 2006, ECOGRAPHY, V29, P458 WHITWORTH DL, 2000, CONDOR, V102, P452 ZHARIKOV Y, 2006, LANDSCAPE ECOL, V21, P107 0921-2973 Landsc. Ecol.ISI:000250207500001Univ Victoria, Dept Radiol, Victoria, BC V8W 3N5, Canada. Burger, AE, Univ Victoria, Dept Radiol, Victoria, BC V8W 3N5, Canada. aburger@uvic.caEnglish <7H Burgi, M.19993A case study of forest change in the Swiss lowlands567-575Landscape Ecology146Sdriving forces forest history forest management human impact landscape history LANDArticleDecThis paper presents a regional case study of forest development and the history of forest use and management in the north-eastern lowlands of Switzerland during the 19th and 20th centuries. The analysis draws on historical documents related to forestry to consider the following aspects of forest change: forest types, growing stock, trees species composition and non-timber forest uses. Based on the data presented, three overlapping periods of forest use and management can be discerned. The 'period of traditional multiple use' lasted until the second half of the 19th century. From the mid 19th to the mid 20th century, a 'period of primacy of timber production' occurred. During the 20th century, the 'period of modern multi-impact management' has developed. For these three periods, groups of main actors, their needs and interests, and how they were causing the changes in the aspects under study were defined. This procedure of defining periods and the respective groups of main actors is a critical link between landscape ecology and history, as changes in demands of the society can be directly linked with changes in land-use and land-cover.://000082563500005 ISI Document Delivery No.: 235VP Times Cited: 8 Cited Reference Count: 25 Cited References: AUCLAIR AN, 1976, ECOLOGY, V57, P431 BURGI M, IN PRESS ENV HIST BURGI M, 1997, BEITR FORSTWIRTSCHAF, V31, P145 BURGI M, 1998, ECOLOGICAL HIST EURO, P203 BURGI M, 1998, SCHWEIZERISCHEZ FO S, P84 ELLENBERG H, 1972, MITT SCHWEIZ ANST FO, V48, P589 FOSTER DR, 1992, J ECOL, V80, P773 FRITZSCHE B, 1994, GESCH KANTONS ZURICH, V20 FRITZSCHE B, 1994, GESCH KANTONS ZURICH, V3 FRITZSCHE B, 1995, GESCH KANTONS ZURICH, V19 HARINGTON CR, 1992, YEAR SUMMER WORLD CL HOBBS R, 1997, LANDSCAPE URBAN PLAN, V37, P1 KWASNIAK AJ, 1996, LANDSCAPE J, V15, P154 LANDOLT E, 1872, WALD SEINE VERJUNGUN MAGNUSON JJ, 1995, ECOLOGICAL TIME SERI, P448 MAREK D, 1994, UMWELTGESCHICHTE UMW MAYER H, 1992, WALDBAU SOZIOLOGISCH PFISTER C, 1990, EARTH TRANSFORMED HU RUSSELL EWB, 1995, PEOPLE LAND TIME LIN SCHENK W, 1996, UOMO FORESTA 2, P201 SCHULER A, 1985, SCHWEIZERISCHE Z FOR, V136, P470 SCHULER A, 1998, EFI P, V18, P353 SCHULMAN KA, 1992, MED DECIS MAKING, V12, P109 TURNER BL, 1995, 35HDP IGBP TURNER MG, 1996, ECOL APPL, V6, P1150 0921-2973 Landsc. Ecol.ISI:000082563500005Harvard Univ, Harvard Forest, Petersham, MA 01366 USA. Burgi, M, Swiss Fed Inst Forest Snow & Landscape Res, CH-8903 Birmensdorf, Switzerland.English~?KBurgi, M. Gimmi, U.2007aThree objectives of historical ecology: the case of litter collecting in Central European forests77-87Landscape Ecology22Most ecosystems and landscapes worldwide are dominated or influenced by human impacts. Consequently, studies of pattern and processes of and within anthropogenic ecosystems and cultural landscapes have to consider human impacts and their historical development adequately. Three major objectives of historical ecology, i.e., the study of human impacts on ecosystems and landscapes over time, can be distinguished: (a) preserving cultural heritage in ecosystems and landscapes, (b) understanding historical trajectories of pattern and processes in ecosystems and landscapes, and (c) informing ecosystem and landscape management. In this paper, the application of these three major objectives of historical ecology is illustrated with a case study on litter collecting-a largely forgotten traditional forest use in Central Europe. Historical analyses do not allow-and should not be misused- to directly deduct management goals, as goals need to be set based on present needs and demands. Still, information on reference condition is relevant in the process of defining goals. Once specific goals are set, historical ecology may advise on how to best achieve and maintain desirable pattern and processes in ecosystems or landscape."://WOS:000251543600006 Times Cited: 0WOS:00025154360000610.1007/s10980-007-9128-0h<7,Burgi, M. Hersperger, A. M. Schneeberger, N.2004?Driving forces of landscape change - current and new directions857-868Landscape Ecology198land-use planning; land-use and land-cover change; landscape history; persistence; precursors of change; standard procedure LAND-USE CHANGE; ECOLOGY; GUIDELINES; MANAGEMENT; DYNAMICS; PATTERNS; HISTORY; CULTURE; COVER; MODELArticletThe concept of driving forces is gaining increasing attention in landscape-change research. We summarize the state of the art of this field and present new conceptual and methodological directions for the study of driving forces of landscape changes. These new directions address four major challenges faced by landscape-change studies, i.e., studying processes and not merely spatial patterns, extrapolating results in space and time, linking data of different qualities, and considering culture as a driver of landscape change. The proposed research directions include: studying landscape change across borders and transects, focusing on persistence as well as change, investigating rates of change, considering attractors of landscape change, targeting correlation and causality, and searching for precursors of landscape change. Based on established knowledge and the new approaches we outline a standard procedure to study driving forces of landscape change. We anticipate that our analytical and systematic approach increases the relevance of studies of landscape change for science as well as for the solution of real world problems.://000226268600004 ; ISI Document Delivery No.: 886YI Times Cited: 12 Cited Reference Count: 61 Cited References: ADAMS WM, 1990, GREEN DEV AGARWAL C, 2002, NE297 USDA FOR SERV ALLEN TFH, 1982, HIERARCHY PERSPECTIV ANTROP M, 1998, LANDSCAPE URBAN PLAN, V41, P155 ANTROP M, 2000, LANDSCAPE ECOL, V15, P257 BAKER WL, 1989, LANDSCAPE ECOL, V2, P111 BAUR B, 2002, EFI P, V42 BERGER J, 1987, LANDSCAPE URBAN PLAN, V14, P295 BICIK I, 2001, LAND USE POLICY, V18, P65 BLAIKIE P, 1985, POLITICAL EC SOIL ER BLAIKIE P, 1987, LAND DEGRADATION SOC BRANDT J, 1999, LAND USE CHANGES THE, P81 BURGI M, 1999, LANDSCAPE ECOL, V14, P567 BURGI M, 2001, LAND USE POLICY, V18, P9 BURGI M, 2002, ECOSYSTEMS, V5, P184 BURGI M, 2003, FOREST ECOL MANAG, V176, P173 CHRISTENSEN NL, 1989, J FOREST HIST, V33, P116 CRONON W, 2000, ECOL APPL, V10, P673 DALE VH, 1993, PHOTOGRAMM ENG REM S, V59, P997 DALE VH, 2000, ECOL APPL, V10, P639 EGAN D, 2001, HIST ECOLOGY HDB FORMAN RTT, 1986, LANDSCAPE ECOLOGY FOSTER DR, 1998, ECOSYSTEMS, V1, P96 FROHLICH P, 2002, DEV CAR BASED ACCESS HERSPERGER AM, 1994, J PLANNING LITT, V9, P15 HERSPERGER AM, 1995, DISP OKT, P10 HOBBS R, 1997, LANDSCAPE URBAN PLAN, V37, P1 IRWIN EG, 2001, AGR ECOSYST ENVIRON, V85, P7 KATES RW, 1990, EARTH TRANSFORMED HU, P1 KIENAST F, IN PRESS BELGEO LAMBIN EF, 2001, GLOBAL ENVIRON CHANG, V11, P261 LESER H, 1991, LANDSCHAFTSOKOLOGIE MAGNUSON JJ, 1990, BIOSCIENCE, V40, P495 MARCUCCI DJ, 2000, LANDSCAPE URBAN PLAN, V49, P67 MCDONNELL MJ, 1993, HUMANS COMPONENTS EC MEYER WB, 1994, CHANGES LAND USE LAN NASSAUER JI, 1995, LANDSCAPE ECOL, V10, P229 NASSAUER JI, 1997, PLACING NATURE CULTU NAVEH Z, 1994, LANDSCAPE ECOLOGY TH NAVEH Z, 2001, LANDSCAPE URBAN PLAN, V57, P269 PROCTOR JD, 1998, GLOBAL ENVIRON CHANG, V8, P227 ROCKWELL RC, 1994, CHANGES LAND USE LAN, P357 RUSSELL EWB, 1994, BIOL CONSERV, V68, P263 RUSSELL EWB, 1997, PEOPLE LAND TIME LIN SERGEANT A, 2002, HUMAN ECOLOGICAL RIS, P369 SERNEELS S, 2001, AGR ECOSYST ENVIRON, V85, P65 SILBERNAGEL J, 1997, LANDSCAPE ECOL, V12, P223 STEINITZ C, 1996, BIODIVERSITY LANDSCA STEINITZ C, 2003, ALTERNATIVE FUTURES TRESS B, 2001, LANDSCAPE URBAN PLAN, V57, P137 TURNER BL, 1990, EARTH TRANSFORMED HU URBAN DL, 1987, BIOSCIENCE, V37, P119 VELDKAMP A, 2001, AGR ECOSYST ENVIRON, V85, P1 VERBURG PH, 2002, ENVIRON MANAGE, V30, P391 VOGT KA, 2002, INTEGRATING LANDSCAP, P143 WHITNEY GG, 1994, COASTAL WILDERNESS F WIENS JA, 1995, MOSAIC LANDSCAPES EC, P1 WILSON JB, 1995, LANDSCAPE ECOL, V10, P191 WIRTH E, 1969, ERDE, V2, P155 WOOD R, 2001, LANDSCAPE RES, V26, P45 WU JG, 2002, LANDSCAPE ECOL, V17, P355 0921-2973 Landsc. Ecol.ISI:000226268600004Swiss Fed Inst Forest Snow & Landscape Res, CH-8903 Birmensdorf, Switzerland. Burgi, M, Swiss Fed Inst Forest Snow & Landscape Res, CH-8903 Birmensdorf, Switzerland. matthias.buergi@wsl.chEnglish1|? +Burgi, M. Straub, A. Gimmi, U. Salzmann, D.2010The recent landscape history of Limpach valley, Switzerland: considering three empirical hypotheses on driving forces of landscape change287-297Landscape Ecology252Understanding global landscape dynamics is a core challenge for the newly emerged field of land change science. Such an understanding requires insights into general pattern of landscape changes and the related driving forces. Many case studies of landscape change exist, but only few attempts have been made, to synthesize the results and to search for general pattern. We suggest that applying hypotheses on driving forces of landscape change derived from one case study in another region as a promising way to advance towards a more integrative view on landscape dynamics. Based on the conclusions drawn in a case study conducted in Godmanchester (Quebec, Canada; Domon and Bouchard 2007), we formulated three hypotheses and discussed them in a case study on landscape change in the Limpach valley, Switzerland. We confirm the importance of geomorphological characteristics for landscape development (hypothesis 1) and our analysis also supports the second hypothesis, which states that changes in demand for certain resources result in landscape change. However, we suggest replacing the term resources by the more encompassing concept of goods and services. The third hypothesis, which states that technological transformations stand at the beginning of landscape change, also was confirmed. Technologies have to be affordable, socially accepted, and corresponding to a demand, to be implemented on a large scale. This will cause a technological transformation, which then-depending on the specifics of the technology applied-becomes relevant for landscape development. We conclude with three reworded hypotheses on driving forces of landscape change and we hope that they will be tested and further developed in other case studies.!://WOS:000274437100009Times Cited: 0 0921-2973WOS:00027443710000910.1007/s10980-009-9412-2? mOBurke, I. Schimel, D. Yonker, C. M. Parton, W. J. Joyce, L. A. Lauenroth, W. K.19908Regional modeling of grassland biogeochemistry using GIS45-54Landscape Ecology41Cspatial modeling, grassland, biogeochemistry, scale dependent errorIWe used an ecosystem model coupled to a Geographic Information System (GIS) to simulate spatial variability in storage and fluxes of C and N within grassland ecosystems. The GIS contained information on driving variables required to run the model. These were soil texture, monthly precipitation and monthly minimum and maximum temperatures. We overlayed polygon maps of the above variables to produce a driving variable map of our study region. The final map had 768 polygons’in 160 unique classes. The ecosystem model was run to a steady state for each class and NPP, soil organic matter (SOM), net N mineralization and trace gas emission were mapped back into the GIS for display. Variation in all of the above propertiees occurred within the region. NPP was primarily controlled by climate and patterns followed spatial variation in precipitation closely. Soil organic matter, in contrast, was controlled largely by soil texture within this climatic range. Error associated with aggregation within the study area showed that spatial averages over the study area could be used to drive simulations of NPP, which is linearly related to rainfall. More spatial detail had to be preserved for accurate simulation of SOM, which is nonlinearly related to texture. Mechanistic regional models form a valuable link between process studies and global models.V<76 Burke, V. J.2000*Landscape ecology and species conservation1-3Landscape Ecology151HALFWAYArticleJan://000083830400001 ISI Document Delivery No.: 258GN Times Cited: 15 Cited Reference Count: 14 Cited References: BURKE VJ, 1995, CONS BIOL, V9, P1363 BURLEY FW, 1988, BIODIVERSITY, P227 ESTES JE, 1996, GAP ANAL LANDSCAPE A, P71 FRAZER NB, 1992, CONSERV BIOL, V6, P179 HANSSON L, 1991, LANDSCAPE ECOL, V5, P191 HOLLING CS, 1996, CONSERV BIOL, V10, P328 JENNINGS MD, 1996, GAP ANAL LANDSCAPE A, P71 LEOPOLD A, 1949, SAND COUNTY ALMANAC MEFFE GK, 1992, CONSERV BIOL, V6, P350 PRESSEY RL, 1993, TRENDS ECOL EVOL, V8, P124 RISSER PG, 1984, ILLINOIS NATURAL HIS, V2 SCOTT JM, 1987, BIOSCIENCE, V37, P782 SCOTT JM, 1996, GAP ANAL LANDSCAPE A WHITELAW S, 1996, HEALTH EDUC RES, V11, P349 0921-2973 Landsc. Ecol.ISI:000083830400001Univ Missouri, Sch Nat Sci, Columbia, MO 65211 USA. Burke, VJ, Smithsonian Inst Press, 470 Lenfant Plaza,Suite 7100, Washington, DC 20560 USA.English<7= Burnicki, A. C.2012QImpact of error on landscape pattern analyses performed on land-cover change maps713-729Landscape Ecology275landscape metrics error land-cover change simulation landscape pattern analysis spatial-pattern habitat fragmentation metrics misclassification propagation sensitivity ecology indexesMayResearchers have emphasized the value of linking observed patterns of land-cover change to the processes driving changes in land-use to explain the dynamics of a land change system. The association of pattern and process requires an accurate quantification of the spatial characteristics of land-cover change. The objective of this research is to assess the impact of error on the accuracy of landscape pattern analyses performed on maps of change. Simulation was used to develop of a series of error-free and error-perturbed change maps, which varied with respect to the pattern of change occurring between the time-1 and time-2 land-cover maps and the patterns of error associated with the time-1 and time-2 land-cover maps. A variety of change and error patterns were examined. The error-free and error-perturbed change maps were compared by calculating landscape pattern metrics, which revealed the degree to which error altered the pattern of change. The introduction of error notably changed the structure of the persistent and transitioning classes, with metrics indicating a more fragmented and variable landscape under error. Agreement between the error-free and error-perturbed maps improved when a greater amount of change occurred within the time-series, change was concentrated at the boundaries of land-cover classes and when time-2 errors were increasingly correlated to their time-1 counterparts. These results have several implications for change pattern analyses given the fundamental nature of land-cover change.://000303056100008-929JC Times Cited:0 Cited References Count:43 0921-2973Landscape EcolISI:000303056100008Burnicki, AC Univ Wisconsin, Dept Geog, 550 N Pk St, Madison, WI 53706 USA Univ Wisconsin, Dept Geog, 550 N Pk St, Madison, WI 53706 USA Univ Wisconsin, Dept Geog, Madison, WI 53706 USADOI 10.1007/s10980-012-9719-2English|?Burns, C. E. Grear, J. S.2008Effects of habitat loss on populations of white-footed mice: testing matrix model predictions with landscape-scale perturbation experiments817-831Landscape Ecology237Habitat loss is the leading cause of decline in wildlife diversity and abundance throughout the world, but its effects on wildlife are not always predictable. Matrix population modeling is an increasingly common tool used to predict the effects of habitat loss. In spite of the growing number of studies using this approach, and its wide use in conservation practice, the predictions generated by matrix population models are rarely explicitly tested in the field. We compared the ability of a suite of spatially explicit demographic matrix models to predict the response of white-footed mice to loss of high quality habitat at mosaic sites in northeast Connecticut, USA. We tested short-term model predictions with landscape scale habitat perturbation experiments, including clear-cut logging or prescribed burning of high quality habitat at two study sites. Comparison of each model's predictions with the observed responses at both sites qualitatively supported predictions that perturbation of high quality habitat would have negative effects extending into the surrounding landscape. The best-supported model assumed that evicted residents of the perturbed habitat would successfully resettle in nearby intact habitats, and allowed for gradual population recovery in the perturbed habitat. Similarly, long-term simulations (20 years) revealed how loss of a single habitat could trigger population declines throughout a mosaic site. This study shows that careful consideration of model assumptions such as those pertaining to resettlement behavior is crucial if predictions are to be reliable, and highlights the role of experiments for comparing alternative model predictions.!://WOS:000258540300005Times Cited: 0 0921-2973WOS:00025854030000510.1007/s10980-008-9239-29<7?Burrough, P. A. Wilson, J. P. van Gaans, P. F. M. Hansen, A. J.2001sFuzzy k-means classification of topo-climatic data as an aid to forest mapping in the Greater Yellowstone Area, USA523-546Landscape Ecology166mdigital elevation models Fuzzy k-means GIS landscape classification topo-climatic analysis vegetation mappingArticleAug"Previous attempts to quantify topographic controls on vegetation have often been frustrated by issues concerning the number of variables of interest and the tendency of classification methods to create discrete classes though species have overlapping property sets (niches). Methods of fuzzy k-means classification have been used to address class overlap in ecological and geographical data but previously their usefulness has been limited when data sets are large or include artefacts that may occur through the derivation of topo-climatic attributes from gridded digital elevation models. This paper presents ways to overcome these limitations using GIS, spatial sampling methods, fuzzy k-means classification, and statistical modelling of the derived stream topology. Using data from a ca. 3600 km(2) forested site in the Greater Yellowstone Area, we demonstrate the creation of meaningful, spatially coherent topo-climatic classes through a fuzzy k-means classification of topo-climatic data derived from 100 m gridded digital elevation models (DEMs); these classes were successfully extrapolated to adjacent areas covering a total of ca. 10 000 km(2). Independently derived land cover data and middle infrared corrected Landsat TM derived estimates of Normalised Difference Vegetation Index (M-NDVI) at 575 independently sampled sites were used to evaluate the topo-climatic classes and test their extrapolation to the larger area. Relations between topo-climatic classes and land cover were tested by chi (2) analysis which demonstrated strong associations between topo-climatic class and 11 of the 15 cover classes. Relations between M_NDVI and topo-climatic classes proved to be stronger than relations between M_NDVI and the independent cover classes. We conclude that the fuzzy k-means procedure yields sensible and stable topo-climatic classes that can be used for the rapid mapping of large areas. The value of these methods for quantifying topographic controls on biodiversity and the strength of their relations with computed NDVI values warrant further investigation.://000172548800004 _ISI Document Delivery No.: 499AW Times Cited: 15 Cited Reference Count: 39 Cited References: ALBRECHT KF, 1992, ECOL MODEL, V63, P45 AUSTIN MP, 1984, VEGETATIO, V55, P11 BEZDEK JC, 1984, COMPUT GEOSCI, V10, P191 BURROUGH PA, 1997, GEODERMA, V77, P115 BURROUGH PA, 1998, PRINCIPLES GEOGRAPHI BURROUGH PA, 2000, FUZZY SET SYST, V113, P37 CHRISTENSEN NL, 1989, BIOSCIENCE, V39, P678 DAVIS TJ, 1997, INT J GEOGR INF SCI, V11, P409 DESPAIN D, 1990, YELLOWSTONE VEGETATI ELLENBERG H, 1992, SCRIPTA GEOBOTANICA, V18, P1 FITZGERALD RW, 1996, COMPUT GEOSCI, V22, P981 FRANKLIN J, 1995, PROG PHYS GEOG, V19, P474 FRANKLIN J, 2000, TERRAIN ANAL PRINCIP, P331 GERRARD RA, 1997, T GIS, V2, P45 HANSEN AJ, 1998, MANAGING FORESTS BIO HOSMER DW, 1989, APPL LOGISTIC REGRES HUTCHINSON MF, 1989, J HYDROL, V106, P211 JONGMAN RHG, 1995, DATA ANAL COMMUNITY KOESTLER A, 1967, GHOST MACHINE LAGACHERIE P, 1997, GEODERMA, V77, P197 MACKEY BG, 1988, ENVIRON MANAGE, V12, P501 MACKEY BG, 1996, P 3 INT C INT GIS EN MACKEY BG, 2000, TERRAIN ANAL PRINCIP, P391 MOORE ID, 1991, HYDROL PROCESS, V5, P3 MOORE ID, 1992, J SOIL WATER CONSERV, V47, P423 MOORE ID, 1993, ENV MODELLING GIS, P197 MOORE ID, 1994, J SOIL WATER CONSERV, V49, P174 NEMANI R, 1993, INT J REMOTE SENS, V14, P2519 ROMME WH, 1982, ECOL MONOGR, V52, P199 ROSSI RE, 1992, ECOL MONOGR, V62, P277 TILMAN D, 1994, ECOLOGY, V75, P2 VANGAANS PFM, 1995, FUZNLMEX COMPUTER PR VRIEND SP, 1988, APPL GEOCHEM, V3, P213 WALSH SJ, 1994, MOUNTAIN ENV GEOGRAP WEBSTER R, 1972, J SOIL SCI, V23, P210 WESSELING CG, 1996, T GIS, V1, P40 WHEATLEY JM, 2000, TERRAIN ANAL PRINCIP, P355 WILSON JP, 1998, LANDFORM MONITORING, P219 WILSON JP, 2000, TERRAIN ANAL PRINCIP, P133 0921-2973 Landsc. Ecol.ISI:000172548800004Univ Utrecht, Fac Geog Sci, Utrecht Ctr Environm & Landscape Dynam, NL-3508 TC Utrecht, Netherlands. Burrough, PA, Univ Utrecht, Fac Geog Sci, Utrecht Ctr Environm & Landscape Dynam, PB 80115, NL-3508 TC Utrecht, Netherlands.English <7Busing, R. T. White, P. S.1993dEffects of area on old-growth forest attributes - implications for the equilibrium landscape concept119-126Landscape Ecology82EQUILIBRIUM LANDSCAPE; FOREST STRUCTURE; GRAIN SIZE; SPATIAL HETEROGENEITY; SPATIAL SCALE; SPECIES COMPOSITION; TEMPERATURE FORESTArticleJunTo investigate applicability of the equilibrium landscape concept to various attributes of vegetation, the effects of sampling area (or grain size) on structural and compositional stand parameters were determined in an old-growth hemlock-hardwood forest. Three 1-ha plots, each gridded into 1 00 0.01-ha subplots, were established on the Roaring Fork watershed in Great Smoky Mountains National Park, Tennessee, USA. Estimates for 10 different stand descriptors were calculated for a variety of grain sizes (subplot aggregation levels) ranging from 0.01 to 1 ha. The stand descriptors included measures of physical structure (basal area and biomass) as well as measures of species composition (relative basal area). All stand descriptors exhibited high deviation from the corresponding 3-ha mean at grain sizes approximating observed canopy gap area (< 0.02 ha). Deviations for total tree density, basal area and biomass diminished sharply with increasing grain size, while deviations for relative basal area of four important species remained relatively high even at grain sizes > 0.5 ha. The relationship between sample variance and grain size was inverse and approximately log-log linear for all descriptors. Biomass, basal area, and large canopy tree density had relatively steep slopes. These variables of physical structure presumably were related to canopy gap size and distribution. The remaining measures of density and relative basal area had gentler slopes, indicating a milder decrease in variation with increasing grain size. Coefficients of variation for each parameter also showed this response to grain size, with compositional parameters having relatively high variation at scales > 0.5 ha. In general, the nature of physical structure patches (e.g. total basal area and biomass) differed from that of composition patches (eg. relative basal area of individual species). This contrast should be considered in equilibrium landscape concepts and vegetation sampling design.://A1993LM22200004 IISI Document Delivery No.: LM222 Times Cited: 14 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1993LM22200004CBUSING, RT, FORESTRY SCI LAB,3200 JEFFERSON WAY,CORVALLIS,OR 97331.English Z<7Buyantuyev, A. Wu, J. G.2007<Effects of thematic resolution on landscape pattern analysis7-13Landscape Ecology221landscape characterization; image classification; thematic resolution; landscape metrics; landscape pattern analysis SCALING RELATIONS; CHANGING SCALE; METRICS; INDEXES; FRAGMENTATION; AGGREGATION; SENSITIVITY; BEHAVIOR; AREAArticleJanThe thematic resolution of mapped data determines the amount of detail of geospatial information, and influences various aspects of landscape classification and the relevance of derived pattern attributes to particular ecological questions. Here we show that changing thematic resolution may significantly affect landscape metrics and in turn their ability to detect landscape changes. The effects of thematic resolution on many landscape metrics tend to show consistent general patterns, but the details of these patterns are likely to be dependent on specific landscape patterns and classification criteria. Thus, the effects of thematic resolution, like those with regard to grain and extent, must be considered in landscape pattern analysis.://000243619800003 ISI Document Delivery No.: 127XO Times Cited: 0 Cited Reference Count: 24 Cited References: *FED GEOGR DAT COM, 1997, VEG CLASS STAND ANDERSON JR, 1976, LAND USE LAND COVER BALDWIN DJB, 2004, LANDSCAPE ECOL, V19, P255 BUYANTUYEV A, 2006, P 8 ANN S CENTR AR P, P11 HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 LI HB, 1993, LANDSCAPE ECOL, V8, P155 LI HB, 2004, LANDSCAPE ECOL, V19, P389 MCGARIGAL K, 1995, FRAGSTATS SPATIAL PA NEEL MC, 2004, LANDSCAPE ECOL, V19, P435 OPPENSHAW S, 1984, MODIFIABLE AREAL UNI RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 SAURA S, 2004, LANDSCAPE ECOL, V19, P197 SCOTT JM, 1998, ANN MO BOT GARD, V85, P34 SHEN WJ, 2004, ECOGRAPHY, V27, P459 STEFANOV WL, 2000, 1985 1990 1993 1998 STEFANOV WL, 2001, REMOTE SENS ENVIRON, V77, P173 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 WICKHAM JD, 1995, INT J REMOTE SENS, V16, P3585 WU J, IN PRESS KEY TOPICS WU J, 1995, LECT MODERN ECOLOGY, P1 WU J, 2000, GEOGRAPHICAL INFORMA, V6, P6 WU JG, 2002, LANDSCAPE ECOL, V17, P761 WU JG, 2004, LANDSCAPE ECOL, V19, P125 0921-2973 Landsc. Ecol.ISI:000243619800003Arizona State Univ, Sch Life Sci, Tempe, AZ 85287 USA. Arizona State Univ, Global Inst Sustainabil, Tempe, AZ 85287 USA. Buyantuyev, A, Arizona State Univ, Sch Life Sci, Tempe, AZ 85287 USA. Alexander.Buyantuyev@asu.eduEnglish)|? Buyantuyev, A. Wu, J. G.2010Urban heat islands and landscape heterogeneity: linking spatiotemporal variations in surface temperatures to land-cover and socioeconomic patterns17-33Landscape Ecology251The urban heat island (UHI) phenomenon is a common environmental problem in urban landscapes which affects both climatic and ecological processes. Here we examined the diurnal and seasonal characteristics of the Surface UHI in relation to land-cover properties in the Phoenix metropolitan region, located in the northern Sonoran desert, Arizona, USA. Surface temperature patterns derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer for two day-night pairs of imagery from the summer (June) and the autumn (October) seasons were analyzed. Although the urban core was generally warmer than the rest of the area (especially at night), no consistent trends were found along the urbanization gradient. October daytime data showed that most of the urbanized area acted as a heat sink. Temperature patterns also revealed intra-urban temperature differences that were as large as, or even larger than, urban-rural differences. Regression analyses confirmed the important role of vegetation (daytime) and pavements (nighttime) in explaining spatio-temporal variation of surface temperatures. While these variables appear to be the main drivers of surface temperatures, their effects on surface temperatures are mediated considerably by humans as suggested by the high correlation between daytime temperatures and median family income. At night, however, the neighborhood socio-economic status was a much less controlling factor of surface temperatures. Finally, this study utilized geographically weighted regression which accounts for spatially varying relationships, and as such it is a more appropriate analytical framework for conducting research involving multiple spatial data layers with autocorrelated structures.!://WOS:000273479100003Times Cited: 1 0921-2973WOS:00027347910000310.1007/s10980-009-9402-4 <7Y"Cain, D. H. Riitters, K. Orvis, K.1997.A multi-scale analysis of landscape statistics199-212Landscape Ecology124?assessment; ecology; remote sensing; satellite PATTERN; ECOLOGYArticleAugIt is now feasible to monitor some aspects of landscape ecological condition nationwide using remotely-sensed imagery and indicators of land cover pattern. Previous research showed redundancies among many reported pattern indicators and identified six unique dimensions of land cover pattern. This study tested the stability of those dimensions and representative pattern indicators across different types of land cover maps. The maps were derived from Landsat Thematic Mapper images of the Tennessee River and Chesapeake Bay watersheds, and they differed in resolution, number of attributes, and method of delineating landscape unit boundaries, A multivariate analysis of pattern metrics was conducted separately for each map, and the results were then compared among types of maps, Measures of land cover diversity, texture, and fractal dimension were more consistent than measures of average patch shape or compaction among the land cover maps.://A1997XV63300001 ISI Document Delivery No.: XV633 Times Cited: 48 Cited Reference Count: 26 Cited References: *ESRI, 1991, ARC INF US GUID *SAS I, 1982, SAS US GUID *USEPA, 1994, 620R94009 US EPA OFF *USEPA, 1994, 620R94020 USEPA OFF BAKER WL, 1992, LANDSCAPE ECOL, V7, P291 BROWN JH, 1990, ADV ECOLOGICAL RES EVERETT R, 1994, PNWGTR317 USDA FOR S, V1 FEGAEAS RG, 1983, 895E US GEOL SURV FORMANN RTT, 1986, LANDSCAPE ECOLOGY FOTHERINGHAM AS, 1991, ENVIRON PLANN A, V23, P102 FRANKLIN JF, 1993, ECOL APPL, V3, P202 GONZALEZ RC, 1992, DIGITAL IMAGE PROCES HOLLING CS, 1978, ADAPTIVE ENV ASSESSM HUNSAKER CT, 1994, LANDSCAPE ECOL, V9, P207 JOHNSON RA, 1982, APPLIED MULTIVARIATE JOHNSTON RJ, 1980, MULTIVARIATE STATIST LAM NSN, 1993, FRACTALS GEOGRAPHY MCDONALD RP, 1985, FACTOR ANAL RELATED MCGARIGAL K, 1994, FRAGSTATS SPATIAL PA RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 SEABER PR, 1987, 2294 USGS SUTER GW, 1990, ENVIRON MANAGE, V14, P19 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 TURNER MG, 1991, QUANTITATIVE METHODS WIENS JA, 1989, FUNCT ECOL, V3, P385 0921-2973 Landsc. Ecol.ISI:A1997XV63300001,UNIV TENNESSEE,DEPT GEOG,KNOXVILLE,TN 37919.English~?iCairns, D. M. Lafon, C. W. Waldron, J. D. Tchakerian, M. Coulson, R. N. Klepzig, K. D. Birt, A. G. Xi, W.2008sSimulating the reciprocal interaction of forest landscape structure and southern pine beetle herbivory using LANDIS403-415Landscape Ecology234RThe reciprocal interaction of landscape structure and ecological processes is a cornerstone of modern landscape ecology. We use a simulation model to show how landscape structure and herbivory interact to influence outbreaks of southern pine beetle (Dendroctonus frontalis Zimmermann) in a landscape representative of the southern Appalachian Mountains, USA. We use LANDIS and its biological disturbance agent module to simulate the effects of landscape composition (proportion of landscape in host area) and host aggregation on the size and severity of insect outbreaks and the persistence of the host species, Table Mountain Pine (Pinus pungens Lamb.). We find that landscape composition is less important in the modeled landscapes than host aggregation in structuring the severity of insect outbreaks. Also, simulated southern pine beetle outbreaks over time tend to decrease the aggregation of host species on the landscape by fragmenting large patches into smaller ones, thereby reducing the severity of future outbreaks. Persistence of Table Mountain pine decreases throughout all simulations regardless of landscape structure. The results of this study indicate that when considering alternative restoration strategies for insect-affected landscapes, it is necessary to consider the patterns of hosts on the landscape as well as the landscape composition."://WOS:000254250400004 Times Cited: 0WOS:000254250400004(10.1007/s10980-008-9198-7|ISSN 0921-2973ڽ7FCaldwell, IainR Gergel, SarahE2013wThresholds in seascape connectivity: influence of mobility, habitat distribution, and current strength on fish movement 1937-1948Landscape Ecology2810Springer NetherlandsUHabitat abundance Habitat loss Fragmentation Conservation Marine Landscape Damselfish 2013/12/01+http://dx.doi.org/10.1007/s10980-013-9930-9 0921-2973Landscape Ecol10.1007/s10980-013-9930-9English?-Caldwell, L. K1990KLandscape, law and public policy: conditions for an ecological perspective.3-8Landscape Ecology51$<73Calvete, C. Estrada, R. Angulo, E. Cabezas-Ruiz, S.2004PHabitat factors related to wild rabbit conservation in an agricultural landscape531-542Landscape Ecology195agricultural landscape; conservation; habitat; Oryctolagus cuniculus; Spain; wild rabbit ORYCTOLAGUS-CUNICULUS L; DONANA-NATIONAL-PARK; MEDITERRANEAN HABITATS; EUROPEAN RABBITS; SW SPAIN; LAND-USE; POPULATION; MANAGEMENT; ABUNDANCE; ENGLANDArticlePopulations of European wild rabbit (Oryctolagus cuniculus) have been decreasing since the 1950s. Changes in agricultural practices have been suggested as reasons for their decline in Mediterranean landscapes. We evaluated the environmental variables affecting rabbit distribution in a semiarid agricultural landscape of Northeastern Spain. Sampling was performed in 147 sites randomly distributed across Zaragoza province. At each site, data were recorded in five 100 m segments along a 1 km transect, following ecotones between crops and natural-vegetation areas. A rabbit abundance index was estimated from latrine count, pellet density and number of plots with pellets. In addition to environmental variables that have been shown to be related to rabbit abundance in other habitats, as climate, soil hardness and topography of the site, we measured landscape components related to agricultural use, such as structure of natural vegetation in remaining areas non-devoted to agricultural use and distances to different types of crops and to ecotone between crop and natural vegetation. Our results showed that rabbit abundance was positively correlated to yearly mean temperature, February and May mean rainfall, and negatively correlated to September and November mean rainfall, hardness of soil, and site topography. In relation to agricultural use, rabbit abundance was positively correlated to the scrub structure of natural-vegetation areas and negatively correlated to distance to edge between cultivated unirrigated cereal crops (wheat or barley) and yearly resting cereal crops. Rabbit abundance increased only when the edge between alternate cereal crops was less than 50 m from the ecotone between crops and natural vegetation.://000222941500006 y ISI Document Delivery No.: 841OY Times Cited: 5 Cited Reference Count: 51 Cited References: *SAS I INC, 1997, SAS STAT SOFTW CHANG ANGULO E, 2003, THESIS COMPLUTENSE U ARGUELLO JL, 1988, MED VET, V5, P645 BELL DJ, 1991, J ZOOL, V224, P639 BOAG B, 1987, CROP PROT, V6, P347 CALVETE C, 1997, J ZOOL 2, V241, P271 CALVETE C, 2002, VET REC, V150, P776 CARRETE M, 2002, BIODIVERS CONSERV, V11, P975 CHAMBERLAIN DE, 2000, AGR ECOSYST ENVIRON, V78, P1 CHAPUIS JL, 1995, GIBIER FAUNE SAUVAGE, V12, P213 DELIBES M, 1979, DONANA ACTA VERTEBRA, V6, P91 DELIBES M, 1981, P WORLD LAG C U GUEL, P614 EISERMANN K, 1993, PHYSIOL BEHAV, V54, P973 FA JE, 1999, J ZOOL 1, V249, P83 FORYS E, 1999, LANDSCAPE ECOL, V14, P177 GIBB JA, 1993, J ZOOL, V229, P581 HOMOLKA M, 1988, FOLIA ZOOL, V37, P121 HONES P, 1996, WILDERU REV, P94 IBORRA O, 1997, MAMMALIA, V61, P205 LANDE R, 1994, NATURE, V372, P88 LOCHMILLER RL, 1995, J RANGE MANAGE, V48, P232 MCCULLAGH P, 1997, GEN LINEAR MODELS, P33 MORENO S, 1995, BIOL CONSERV, V73, P81 MORENO S, 1996, CAN J ZOOL, V74, P1656 MORRISON ML, 1992, WILDLIFE HABITAT REL, P1 MUNOZGOYANES G, 1960, ANVERSO REVERSO MIXO, P58 MYERS K, 1965, CSIRO WILDLIFE RES, V10, P1 MYERS N, 2000, NATURE, V403, P853 NADAL J, 1996, REV ECOL-TERRE VIE, V51, P243 PALMA L, 1999, J APPL ECOL, V36, P812 PALOMARES F, 2001, WILDLIFE SOC B, V29, P578 PAPILLON Y, 1997, GAME WILDL, V14, P303 PARER I, 1985, AUST WILDLIFE RES, V12, P387 PEITZ DG, 1997, J RANGE MANAGE, V50, P450 RANDS MRW, 1986, J APPL ECOL, V23, P479 RATCLIFFE FN, 1952, NATURE, V170, P1 RICHARDSON BJ, 1982, AUST WILDLIFE RES, V9, P443 RODEL HG, 2000, LIFE COLD, P511 ROGERS PM, 1979, J APPL ECOL, V16, P691 ROGERS PM, 1981, J APPL ECOL, V18, P355 SMITH HG, 2002, AGR ECOSYST ENVIRON, V92, P107 SUAREZ F, 1997, FARMING BIRDS EUROPE, P297 TAYLOR RH, 1956, NZ J SCI TECH B, V38, P236 TELLA JL, 1998, CONSERV BIOL, V12, P593 TROUT RC, 1995, J ZOOL, V237, P411 TROUT RC, 2000, J ZOOL 2, V252, P227 VILLAFUERTE R, 1997, ACTA THERIOL, V42, P225 VILLAFUERTE R, 1997, REV ECOL-TERRE VIE, V52, P345 VIRGOS E, 2003, ACTA THERIOL, V48, P113 WILCOVE DS, 1986, CONSERVATION BIOL SC, P237 WOOD DH, 1980, J ANIM ECOL, V49, P55 0921-2973 Landsc. Ecol.ISI:000222941500006CSIC UCLM, Natl Res Inst Game Biol, Ciudad Real, Spain. CSIC, Donana Biol Stn, Seville, Spain. Calvete, C, CSIC UCLM, Natl Res Inst Game Biol, Ciudad Real, Spain. vetecal2003@jazzfree.comEnglish!?4WKees J. Canters Cees P. den Herder Aart A. de Veer Paul W.M. Veelenturf Rein W. de Waal1991/Landscape-ecological mapping of the Netherlands145-162Landscape Ecology53geographical database, GIS, grid map, landscape ecology, land classification, nature conservation, susceptibility, significance, vulnerabilityThe Landscape-ecological Mapping of the Netherlands project (LMN project) started in 1983 with the aim of establishing a landscape-ecological database for use in developing and evaluating national land-use plans. The project, working with grid cells of 1 km2, has four working objectives: a) development of mapping potential for basic landscape-ecological data, b) assessment of susceptibility to interventions, c) evaluation of significance for nature conservation and d) production of vulnerability maps, as a combination of susceptibility and significance. In addition to information on soil, groundwater, ecotopes, flora and fauna, the database also incorporates information on physiographical features and entire landscapes. The resulting database is a geographic information system (GIs). This article describes the second phase of the project (1985-1989), covering the ‘Randstad’ area, and focusses on the methods and the applications potential of the database.? )Cantwell, Margot D. Forman, Richard T. T.1993mLandscape graphs: Ecological modeling with graph theory to detect configurations common to diverse landscapes239-255Landscape Ecology84 |7 Cantwell, M. D. Forman, R. T. T.1993nLandscape Graphs - Ecological Modeling with Graph-Theory to Detect Configurations Common to Diverse Landscapes239-255Landscape Ecology84DecIn view of the bewildering diversity of landscapes and possible patterns therein, our objectives were to see if a useful modeling method for directly comparing land mosaics could be developed based on graph theory, and whether basic spatial patterns could be identified that are common to diverse landscapes. The models developed were based on the spatial configuration of and interactions between landscape elements (ecosystems, land uses or ecotopes). Nodes represented landscape elements and linkages represented common boundaries between elements. Corridors, corridor intersections, and the matrix were successfully incorporated in the models. Twenty-five landscape graphs were constructed from aerial photographs chosen solely to represent a breadth of climates, land uses and human population densities. Seven distinctive clusters of nodes and linkages were identified and common, three of which, in the forms of a 'spider', 'necklace' and 'graph cell,' were in > 90% of the graphs. These represented respectively the following 'configurations' of patches, corridors and matrix: (1) a matrix area surrounding or adjoining many patches; (2) a corridor bisecting a heterogeneous area; and (3) a unit in a network of intersecting corridors. The models also indicated that the connectivity or number of linkages for several common elements, such as fields and house clearings, was relatively constant across diverse landscapes, and that linear shaped elements such as roads and rivers were the most connected. Several additional uses of this graph modeling, including compatibility with systems dynamics models, are pinpointed. Thus the method is useful in allowing simple direct comparisons of any scale and any landscape to help identify patterns and principles. A focus on the common and uncommon configurations should enhance our understanding of fluxes across landscapes, and consequently the quality of land planning and management.://A1993MN73600002-Mn736 Times Cited:31 Cited References Count:0 0921-2973ISI:A1993MN73600002/Harvard Univ,Grad Sch Design,Cambridge,Ma 02138English?Carmela Canzonieri2007YM.E. Benedict and E.T. McMahon, Green Infrastructure: Linking Landscapes and Communities 797-798Landscape Ecology225 Book Review <7QCaplat, P. Lepart, J. Marty, P.2006Landscape patterns and agriculture: modelling the long-term effects of human practices on Pinus sylvestris spatial dynamics (Causse Mejean, France)657-670Landscape Ecology215agriculture; bioscene; French Mediterranean; grazing; land-use; landscape history; multiagent systems; rangeland; Scots Pine; shifting cultivation; time-lag SCOTS PINE; VEGETATION PATTERNS; SOUTHERN FRANCE; NEW-ENGLAND; LAND-USE; FOREST; CONSEQUENCES; ENVIRONMENT; MANAGEMENT; HISTORYArticleJul}This paper focuses on understanding human impact on landscape. Both ecological and human practices are analysed as interacting processes. An agent-based model integrating biological and historical knowledge is used to analyse the pattern of Scots Pine encroachment in a French Mediterranean upland. In the STIPA model, pine trees are autonomous agents and a cellular automaton simulates land-use. We test the effects of shifting cultivation on tree establishment at the landscape scale. This allows us to understand how agro-pastoral practices patterned this area from the 17th to 19th century: simulations show the importance of shifting cultivation in limiting woodland progression. Fallow duration linked to environmental heterogeneity is a significant factor for explaining pine dynamics and landscape patterning at the scale of the study region. We put this result in perspective with current rangeland management policies that often consider grazing as the most relevant tool for open landscape maintenance. Our results also show the importance of taking into account time-scale effects when linking landscape patterns to agricultural systems.://000240500100003 ] ISI Document Delivery No.: 083ZE Times Cited: 1 Cited Reference Count: 68 Cited References: *INV FOR NAT, 1989, INV FOR LOZ *PNC, 1999, PLAN GEST ANT CAUSS BALANDIER P, 2002, CAHIERS AGR, V11, P103 BARTOLOME J, 2000, AGR ECOSYST ENVIRON, V77, P267 BECU N, 2003, ECOL MODEL, V170, P319 BENGTSSONLINDSJ.S, 1991, ECOL B, V41, P388 BIRKS HH, 1988, CULTURAL LANDSCAPE P BOTKIN DB, 1972, J ECOL, V60, P849 BOUSQUET F, 1998, LECT NOTES ARTIF INT, V1416, P826 BOUSQUET F, 2004, ECOL MODEL, V176, P313 BRUN A, 1978, CAUSSE MEJEAN CRISE BUGMANN H, 2001, CLIMATIC CHANGE, V51, P259 BULLOCK JM, 2000, OECOLOGIA, V124, P506 CARLISLE A, 1968, J ECOL, V56, P269 CARRERE P, 1999, P INT OCC S EUR GRAS CASTRO J, 1999, PLANT ECOL, V145, P115 CASTRO J, 2002, J VEG SCI, V13, P725 CASTRO J, 2004, J ECOL, V92, P266 CAZALIS F, 1856, B SOC AGR IND SCI AR, P440 CHASSANY JP, 1978, CAUSSE MEJEAN ELEMEN CHILDE VG, 1971, PREHISTORIC AGR NATU, P15 COHEN GD, 1997, AM J GERIAT PSYCHIAT, V5, P1 COHEN M, 1995, GRANDS CAUSSES NOUVE, P113 DAUBREE M, 1992, STAT ATLAS FORETS FR DEBAIN S, 2003, J VEG SCI, V14, P509 DEBAIN S, 2003, THESIS ENSAM MONTPEL DEBUSSCHE M, 1999, GLOBAL ECOL BIOGEOGR, V8, P3 DIAMOND J, 2002, NATURE, V418, P700 ETIENNE M, 2001, J MEDITERRANEAN ECOL, V2, P221 FLAHAULT C, 1931, B SOC LANGUEDOCIENNE, P89 FOSTER DR, 2003, FOREST ECOL MANAG, V185, P127 FOWLER P, 1999, ANTIQUITY, V73, P411 GORHAM E, 1997, PLACING NATURE CULTU, P15 GRIMM V, 1999, ECOL MODEL, V115, P275 GROVE AT, 2001, NATURE MEDITERRANEAN GUITTET J, 1974, OECOLOG PLANTAR, V9, P111 HASTINGS A, 2005, ECOL LETT, V8, P91 HESTER AJ, 1992, BIOL CONSERV, V60, P25 HIGGINS SI, 1998, PLANT ECOL, V135, P79 LAUR F, 1929, PLATEAU LARZAC CONTR LEBRUN P, 1957, B SOC BOT FRANCE, V104, P339 LEHOUEROU HN, 1981, MEDITERRANEAN TYPE S, V11, P479 LEPART J, 1992, LANDSCAPE BOUNDARIES, P76 LEPART J, 2001, FORET MEDITERRANEENN, V22, P23 LIOU TN, 1929, ARCH BOT, V3 MARRES P, 1935, ARRAULT CIE MARTONNE ED, 1926, GRANDES REGIONS FRAN MARTY P, 2003, ENV DYNAMICS HIST ME, P179 MATHEVET R, 2003, ECOL MODEL, V165, P107 MCVEAN DN, 1963, NAT CONSERVANCY, P671 MEDAIL F, 2001, FORET MEDITERRANEENN, V22, P5 MOORE PD, 1975, NATURE, V256, P267 MOTZKIN G, 1996, ECOL MONOGR, V66, P345 MOTZKIN G, 1999, J VEG SCI, V10, P903 OSTY PL, 1978, CAUSSE MEJAN ELEVAGE PEREVOLOTSKY A, 1998, BIOSCIENCE, V48, P1007 PETIT F, 1978, CAUSSE MEJEAN EXODE PREVOSTO B, 2003, PLANT ECOL, V168, P123 QUETIER F, 2005, AGR SYST, V84, P171 QUILES D, 2002, C R PALEVOL, V1, P59 ROUSSET O, 2002, PLANT ECOL, V165, P197 SEGERSTROM U, 2002, VEG HIST ARCHAEOBOT, V11, P181 THIAULT M, 1968, RECONNAISSANCE PHYTO, V37 THIRGOOD JV, 1981, MAN MEDITERRANEAN FO TOUPAL RS, 2003, CONSERV ECOL, V7 VERNET JL, 1972, B SOC BOT FRANCE, V119, P169 VONDROSTE B, 1995, CULTURAL LANDSCAPES ZAMORA R, 2001, FOREST ECOL MANAG, V144, P33 0921-2973 Landsc. Ecol.ISI:000240500100003CNRS, Ctr Ecol Fonct & Evolut, UMR 5175, F-34293 Montpellier 5, France. Caplat, P, CNRS, Ctr Ecol Fonct & Evolut, UMR 5175, 1919 Route Mende, F-34293 Montpellier 5, France. caplat@cefe.cnrs.frEnglish 1|7!Caprio, E. Ellena, I. Rolando, A.2009Native oak retention as a key factor for the conservation of winter bird diversity in managed deciduous forests in northern Italy65-76Landscape Ecology241bird community forest cover landscape pattern oak black locust forest fragmentation class and landscape-predictors italy avian nest success habitat selection landscape ecology pine forests fragmentation communities biodiversity restoration populations passerinesJanBirds can serve as useful model organisms to investigate community level consequences of forestry practices. In this study we investigated the relationships between wintering bird communities and habitat and landscape characteristics of lowland managed forests in Northern Italy. This area is characterized by the spread of the black locust, an alien species that has been favored by forestry practices at the expense of natural oak forests. Birds were censused in winter by point counts in randomly selected plots of 50 m radius. We first addressed bird community-habitat relationships by means of habitat structure measurements, then we investigated bird community-landscape relationships by using GIS techniques. We used generalized linear models (GLM) to test for the effects of habitat and landscape variables on bird community parameters (namely bird species richness, diversity and abundance). Bird community parameters were influenced by oak biomass and tree age, and by oak area and core area, while the other forest habitat types showed less influence. In forest management terms, the main conclusion is that the retention of native oaks is the keyfactor for the conservation of winter bird diversity in local deciduous woods. At the habitat level black locust harvesting may be tolerated, provided that old, large, native oaks are retained in all local woodlots to preserve landscape connectivity and foraging resources. At the landscape meso-scale, large native oak patches, should be preserved or, where necessary, restored.://000262506000006-395EI Times Cited:0 Cited References Count:76 0921-2973ISI:000262506000006Caprio, E Univ Turin, Dipartimento Biol Anim & Uomo, Via Acad Albertina 13, I-10123 Turin, Italy Univ Turin, Dipartimento Biol Anim & Uomo, I-10123 Turin, ItalyDoi 10.1007/S10980-008-9280-1English<7>,Cardillo, M. Macdonald, D. W. Rushton, S. P.1999tPredicting mammal species richness and distributions: testing the effectiveness of satellite-derived land cover data423-435Landscape Ecology145bassociative models biodiversity mapping distributions land cover mammals species richness PATTERNSArticleOctPMapping species richness and distributions is an important aspect of conservation and land use planning, but the time and cost of producing maps from field surveys is prohibitive. It is useful, therefore, if mappable environmental variables, from a readily accessible source, can be used as surrogates for species attributes. We evaluated the power of satellite-derived land cover information, from the Land Cover Map of Great Britain, to predict species richness and occurrences of terrestrial mammals in one hundred 10 x 10 km quadrats, from four regions of Britain. The predictive power of the land cover data was relatively poor - with a few exceptions, land cover explained less than half of the variation in mammal species richness and occurrence in regression models. Predictive power was considerably stronger when regions were analyzed separately than when analyzed together, and best fitting models varied between regions and between mammal taxa. Predictive power was also affected (positively or negatively depending on taxon) when PCA-ordinated land cover variables were used as predictors. The predictive strength of the land cover data was probably limited mostly by the high proportion of British mammal species with geographic distributions changing rapidly and independently of land cover (and hence the non-saturation of preferred habitats), and to a lesser extent by shortcomings in the mammal and land cover data, and the influence of landscape factors other than land cover on mammal distributions. The results suggest that regional stratification is essential when attempting to predict species richness and distributions, even across relatively limited areas such as Great Britain. We conclude that caution is necessary in using results from environmental information systems such as this as a basis for conservation and land use planning decisions.://000082510000002 PISI Document Delivery No.: 234XQ Times Cited: 12 Cited Reference Count: 22 Cited References: ADAMS JM, 1996, GLOBAL ECOL BIOGEOGR, V5, P3 ARNOLD H, 1993, ATLAS BRIT MAMMALS BIAN L, 1997, SCALE REMOTE SENSING, P13 BOHNINGGAESE K, 1997, J BIOGEOGR, V24, P49 BRIGHT PW, 1994, J APPL ECOL, V31, P329 BUTTERFIELD BR, 1994, MAPPING DIVERSITY NA, P53 CLARKE R, 1986, HDB ECOLOGICAL MONIT CORBET GB, 1991, HDB BRIT MAMMALS DANELL K, 1996, ECOGRAPHY, V19, P404 FULLER RM, 1994, PHOTOGRAMM ENG REM S, V60, P553 GURNELL J, 1993, MAMMAL REV, V23, P127 HARRIS S, 1995, REV BRIT MAMMALS POP MACDONALD DW, 1996, J BIOGEOGR, V23, P649 MACDONALD DW, 1998, PROPOSALS FUTURE MON MILLER RI, 1994, MAPPING DIVERSITY NA SHORT HZ, 1996, CONSERVATION FAUNAL, P569 SPELLERBERG IF, 1991, MONITORING ECOLOGICA THORNTON PS, 1988, MAMMAL REV, V18, P11 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 TURPIE JK, 1994, S AFR J ZOOL, V29, P19 VEITCH N, 1995, ADV ENV REMOTE SENSI, P157 WRIGHT DH, 1993, SPECIES DIVERSITY EC, P66 0921-2973 Landsc. Ecol.ISI:000082510000002Univ Oxford, Dept Zool, Wildlife Conservat Res Unit, Oxford OX1 3PS, England. Cardillo, M, Univ Oxford, Dept Zool, Wildlife Conservat Res Unit, S Parks Rd, Oxford OX1 3PS, England.English? ICarlile, D. W. J.R. Skalski J.E. Batker J.M. Thomas V.I. Cullinan1989!Determination of ecological scale203-213Landscape Ecology24~spatial correlation, ecological scale, line-intercept transects, spatial pattern, segment length, dispersal, landscape patternXWe suggest that ecological processes and physical characteristics possess an inherent scale at which the processes or characteristics occur over the landscape. We propose a conceptual spatial response model that describes the nature of this ecological scale. Based on the proposed spatial model, we suggest methods for estimating the size of study plots or transects and the distance between replicate plots needed to approach statistical independence. Using data on percent cover for Agropyron spicatum, a common arid-land bunchgrass, we demonstrated four relationships that should hold if the spatial response model is appropriate. These relationships are sample variance increases as functions of (1) transect segment length and (2) intersegment length (transect segment dispersal), and correlation decreases as functions of (3) intersegment length and (4) j transect segment length. Based on evaluation of these four relationships, cover for A. spicatum is correlated over the landscape on a scale of 400 to 700 m, and a segment length of 64 to 128 m is most appropriate for measuring cover for this species.<7Carmel, Y. Flather, C. H.2004Comparing landscape scale vegetation dynamics following recent disturbance in climatically similar sites in California and the Mediterranean basin573-590Landscape Ecology196California; convergent evolution; disturbance history; Israel; landscape dynamics; Mediterranean-type ecosystems; vegetation change OAK REGENERATION; CONVERGENCE; ECOSYSTEMS; GRASSLAND; MODEL; CLASSIFICATION; WOODLAND; ISRAEL; FIREArticleAug7A long line of inquiry on the notion of ecological convergence has compared ecosystem structure and function between areas that are evolutionarily unrelated but under the same climate regime. Much of this literature has focused on quantifying the degree to which animal morphology or plant physiognomy is alike between disjunct areas. An important property of ecosystems is their behavior following disturbance. Yet, this aspect of ecosystems has not been investigated in a comparative study of convergence. If different ecosystems are under similar environmental controls, then one would predict that the rates and patterns of response to disturbance would also be similar. The objective of this study is to compare landscape dynamics following disturbance using spatiotemporal models to quantify vegetation change in Mediterranean ecosystems found in California and Israel. We model the process of tree and shrub regeneration at the landscape scale in two similar study sites in Israel (Mount Meron) and California (Hasting Nature Reserve). During the periods studied (1964-1992 for Israel and 1971-1995 for California), average annual change in tree cover was 5 times larger in Israel than in California. Based on multiple regression models, differences were found in the relative importance of specific variables predicting vegetation change. In Hastings (California), initial tree cover accounted for most of the explained variability in 1995 tree cover (partial R-2 = 0.71), while in Meron (Israel) grazing type and intensity, topography indices, and initial vegetation each accounted for about a third of the explained variability. These findings support the notion that traits such as regeneration pattern and rate, both at the individual level and at the landscape level, were largely affected by the human land use history of the region.://000224100600001 3 ISI Document Delivery No.: 857FC Times Cited: 1 Cited Reference Count: 67 Cited References: ARMESTO JJ, 1995, ECOLOGY BIOGEOGRAPHY, P418 AXELROD DI, 1977, TERRESTRIAL VEGETATI, P139 BARBOUR MG, 1990, ISRAEL J BOT, V39, P453 BROOKS CN, 2001, RESTOR ECOL, V9, P1 CADLE JE, 1993, SPECIES DIVERSITY EC, P281 CALLAWAY RM, 1993, ECOLOGY, V74, P1567 CARMEL Y, 1998, J VEG SCI, V9, P445 CARMEL Y, 1999, PLANT ECOL, V145, P239 CARMEL Y, 2001, ECOL APPL, V11, P268 CARMEL Y, 2001, PHOTOGRAMM ENG REM S, V67, P865 CODY ML, 1973, MEDITERRANEAN TYPE E, P306 CODY ML, 1978, ANNU REV ECOL SYST, V9, P265 COWLING RM, 1996, TRENDS ECOL EVOL, V11, P362 DALY C, 1994, J APPL METEOROL, V33, P140 DAVIS FW, 1998, CALIFORNIA GAP ANAL DAVIS J, 1967, AM MIDL NAT, V77, P234 DICASTRI F, 1973, MEDITERRANEAN TYPE E FRELICH LE, 1998, J ECOL, V86, P149 GLENNLEWIN DC, 1992, PLANT SUCCESSION THE, P11 GRIFFIN JR, 1971, ECOLOGY, V52, P862 GRIFFIN JR, 1988, 1 U CAL HAST NAT HIS HOBBS RJ, 1995, MEDITERRANEAN TYPE E, P1 JANSEN HC, 1997, P S OAK WOODL EC, P313 KADMON R, 1999, J VEG SCI, V10, P383 KARR JR, 1975, ECOLOGY EVOLUTION CO, P258 KUMMEROW J, 1973, MEDITERRANEAN TYPE E, P157 LAWTON JH, 1999, OIKOS, V84, P177 LEGENDRE P, 1998, NUMERICAL ECOLOGY LIKENS GE, 1992, ECOSYSTEM APPROACH I, V3 LINDSDALE JM, 1943, UNPUB HUMAN RELATION LOSOS JB, 1998, SCIENCE, V279, P2115 MARKUS M, 1994, MERON MOUNTAIN LANDS MARTINEZ E, 1993, ECOL APPL, V3, P417 MCCLARAN MP, 1987, P S MULT US MAN CAL, P358 MCCREARY DD, 1989, CALIF AGR, V43, P358 MENSING SA, 1992, MADRONO, V39, P36 MENSING SA, 1998, MADRONO, V45, P1 MILES SR, 1997, PUBLICATION USDA FOR MOMEN B, 1994, INT J PLANT SCI, V155, P744 MUICK PC, 1991, P S OAK WOODLANDS HA, P21 NAVEH Z, 1967, ECOLOGY, V48, P445 NAVEH Z, 1973, MEDITERRANEAN TYPE E, P273 NAVEH Z, 1979, VEGETATIO, V41, P171 NAVEH Z, 1986, EARTH TRANSITION PAT, P259 NAVEH Z, 1994, ROLE FIRE MEDITERRAN, P163 NOYMEIR I, 1989, J ECOL, V77, P290 PARASKEVOPOULOS SP, 1994, VEGETATIO, V115, P109 PARUELO JM, 1998, ECOL APPL, V8, P194 PAVLIK B, 1992, OAKS CALIFORNIA PHILLIPS RL, 1996, CALIF AGR, V50, P17 PIANKA ER, 1975, SCIENCE, V188, P847 PIANKA ER, 1986, ECOLOGY NATURAL HIST PREISS E, 1997, LANDSCAPE ECOL, V12, P51 PRENTICE KC, 1990, J GEOPHYS RES-ATMOS, V95, P11811 RABINOVITCHVIN A, 1983, MEDITERRANEAN TYPE E, P74 SAMOCHA Y, 1980, LAYAARAN, V30, P6 SCHEIDLINGER CR, 1979, P S EC MAN UT CAL OA, P81 SCHLUTER D, 1986, ECOLOGY, V67, P1073 SELIGMAN NG, 1994, PLANT ANIMAL INTERAC, P93 SHMIDA A, 1981, ISRAEL J BOT, V30, P105 STANDIFORD R, 1997, MADRONO, V44, P170 SUDWORTH GB, 1908, FOREST TREES PACIF S SWEITZER RA, 2002, P 5 S OAK WOODL OAKS, P219 TILMAN D, 1989, PERSPECTIVES ECOLOGI, P89 WHITE KL, 1966, ECOLOGY, V47, P229 WIENS JA, 1991, ECOLOGY, V72, P479 ZINKE PJ, 1973, MEDITERRANEAN TYPE E, P61 0921-2973 Landsc. Ecol.ISI:000224100600001Technion Israel Inst Technol, Fac Civil & Environm Engn, IL-32000 Haifa, Israel. US Forest Serv, USDA, Rocky Mt Res Stn, Ft Collins, CO USA. Carmel, Y, Technion Israel Inst Technol, Fac Civil & Environm Engn, IL-32000 Haifa, Israel. yohay@tx.technion.ac.ilEnglish ? Carpenter, S.R.1989OTemporal variance in lake communities: Blue-green algae and the trophic cascade175-184Landscape Ecology33/4@blue-green algae, fish, lake, scale, trophic cascade, time scaleTwo examples, blue-green algal blooms and the fish-driven trophic cascade, illustrate important consequences of time scale dependency in lakes. Blue-green algae and fish populations are notably variable components of lake communities. The timing of colonization of the water column by blue-green algae, relative to population oscillations of grazers and other algal groups, determines the magnitude of subsequent blooms. Variability in colonization acts jointly with dynamic variability in herbivory to produce large fluctuations in blue-green algal concentration at time scales of weeks to years. Fishes exhibit high interannual variance in recruitment. Episodes of high recruitment cascade through lake food webs, inducing fluctuations in lower trophic levels at time scales of years to decades. Fishes, through their effects on herbivores, contribute to variability in blue-green algal blooms. Blue-green algae and fishes are foci of lake management, so analyses of their variable and scale-dependent interactions are important for applied limnology. Theories and models that address nonequilibrial dynamics, analyses of effects of time scale on correlations and experiments, and improved paleolimnological capabilities will yield valuable progress on temporal scale issues in limnology and ecology. xeroxed copy <7> 2Carranza, M. L. D'Alessandro, E. Saura, S. Loy, A.2012^Connectivity providers for semi-aquatic vertebrates: the case of the endangered otter in Italy281-290Landscape Ecology272&functional connectivity graph theory habitat suitability models dendritic networks least-cost modeling probability of connectivity matrix permeability riverscapes lutra-lutra population habitat patches landscape connectivity availability conservation suitability networks ecology indexes modelsFebNModeling habitat connectivity for conservation of semi-aquatic vertebrates is a particularly challenging task, due to the fine-scale and linear distribution of riverine habitats and to the capacity of species to move both on freshwater and terrestrial realms. We showed how the integrated analytical framework provided by the habitat availability (reachability) metrics and their fractions can be used to effectively evaluate the distinctive roles and contributions of both habitat patches (aquatic and riparian) and linkage areas (permeable land matrix) to the connectivity and functioning of a complex system composed of multiple river catchments. Analysis focused on the Eurasian otter (Lutra lutra L.), one of the most endangered mammals in Italy. We developed a network connectivity model based on suitable otter habitats and multiple least-cost paths between catchments. A graph analytical approach was used to identify critical nodes and links for the potential expansion and long-term viability of the species in the region. Our results showed that few basins concentrate most of the importance for sustaining the overall habitat connectivity, due to the extension of suitable habitats they contain, their strong connections with other basins, and their importance as stepping stones that uphold ecological fluxes between otherwise weakly connected habitats. The potential contribution of each basin to enhance the dispersal and expansion of otters in the area strongly depended on the key functional paths (sequences of links and nodes) among the catchments. We identified vacant basins that could be colonized by otters in the near future, and connecting areas in the intermediate matrix that might be preferentially used to conduct and promote dispersal movements and gene flow in the area. The novel approach here adopted could be easily extended to other semiaquatic species and catchment systems, offering a management strategy to preserve the hydrographic network as an integrated system, as well as a joint evaluation of the role of both the river courses and the matrix in between in a single landscape model.://0003000887000119Sp. Iss. SI 889QQ Times Cited:0 Cited References Count:44 0921-2973Landscape EcolISI:000300088700011Carranza, ML Univ Molise, Environmetr Lab, Dept Stat, I-86170 Pesche, IS, Italy Univ Molise, Environmetr Lab, Dept Stat, I-86170 Pesche, IS, Italy Univ Molise, Environmetr Lab, Dept Stat, I-86170 Pesche, IS, Italy Univ Politecn Madrid, ETSI Montes, E-28040 Madrid, SpainDOI 10.1007/s10980-011-9682-3Englishڽ7!Carroll, JohnM Peterson, BradleyJ2013eEcological trade-offs in seascape ecology: bay scallop survival and growth across a seagrass seascape 1401-1413Landscape Ecology287Springer Netherlands}Bay scallops Seagrass Artificial seagrass unit Ecological trade-off Mortality to foraging ratio Edge effects Seascape ecology 2013/08/01+http://dx.doi.org/10.1007/s10980-013-9893-x 0921-2973Landscape Ecol10.1007/s10980-013-9893-xEnglish?=m R.W.G. Carter19918Near-future sea level impacts on coastal dune landscapes29-39Landscape Ecology61/2]coastal dunes, sea level rise, global warming, C02-enhancement, beach stages, sediment budgetHVery little attention has been paid to the impact of global warming, especially sea level rise, on coastal dunescapes, despite the fact that these provide natural protection along many of the world’s shorelines. This paper reviews likely responses given the IPCC climate change predictions to 2030AD, which include sea level rise in the order of 0.09 to 0.29m. It is envisaged that coastal dunes will react in a variety of ways dependent both on regional and local factors. Rising water levels will increase susceptibility to erosion, but the fate of released sediment, particularly the onshore/offshore partitioning, must depend on morphodynamic antecedence, and the propensity for periodic domain shifts. The release of material at the shoreline may allow construction of coastal dunes, to the point of progradation in some zones. The response of dune vegetation to a warmer, wetter climate is uncertain. Most of the main temperate dune species are C3 plants which given favourable conditions would respond positively to C02 enhancement. However local factors may offset such potential gains.T<7Cary, G. J. Keane, R. E. Gardner, R. H. Lavorel, S. Flannigan, M. D. Davies, I. D. Li, C. Lenihan, J. M. Rupp, T. S. Mouillot, F.2006|Comparison of the sensitivity of landscape-fire-succession models to variation in terrain, fuel pattern, climate and weather121-137Landscape Ecology211EMBYR; FIRESCAPE; LAMOS; LANDSUM; model comparison; SEM-LAND; simulation modelling YELLOWSTONE-NATIONAL-PARK; HETEROGENEOUS LANDSCAPES; SOLAR-RADIATION; BOREAL FOREST; VEGETATION; DISTURBANCE; SIMULATION; DYNAMICS; BEHAVIOR; TEMPERATUREArticleJanThe purpose of this study was to compare the sensitivity of modelled area burned to environmental factors across a range of independently-developed landscape-fire-succession models. The sensitivity of area burned to variation in four factors, namely terrain (flat, undulating and mountainous), fuel pattern (finely and coarsely clumped), climate (observed, warmer & wetter, and warmer & drier) and weather (year-to-year variability) was determined for four existing landscape-fire-succession models (EMBYR, FIRESCAPE, LANDSUM and SEM-LAND) and a new model implemented in the LAMOS modelling shell (LAMOS(DS)). Sensitivity was measured as the variance in area burned explained by each of the four factors, and all of the interactions amongst them, in a standard generalised linear modelling analysis. Modelled area burned was most sensitive to climate and variation in weather, with four models sensitive to each of these factors and three models sensitive to their interaction. Models generally exhibited a trend of increasing area burned from observed, through warmer and wetter, to warmer and drier climates with a 23-fold increase in area burned, on average, from the observed to the warmer, drier climate. Area burned was sensitive to terrain for FIRESCAPE and fuel pattern for EMBYR. These results demonstrate that the models are generally more sensitive to variation in climate and weather as compared with terrain complexity and fuel pattern, although the sensitivity to these latter factors in a small number of models demonstrates the importance of representing key processes. The models that represented fire ignition and spread in a relatively complex fashion were more sensitive to changes in all four factors because they explicitly simulate the processes that link these factors to area burned.://000235887300010 ISI Document Delivery No.: 020DD Times Cited: 1 Cited Reference Count: 87 Cited References: *CSIRO, 1996, CLIM CHANG SCEN AUST *FOR CAN FIR DANG, 1992, STX3 FOR CAN FIR DAN, P63 *IPCC, 2001, CLIM CHANG 2001 SCI *SAS I INC, 2000, ONLINEDOC VERS 8 *VEMAP, 1996, VEG EC MOD AN PROJ V AGEE JK, 1993, FIRE ECOLOGY PACIFIC ANDERSON DH, 1982, J AUST MATH SOC B, V23, P451 ANTONOVSKI MY, 1992, SYSTEMS ANAL GLOBAL, P373 BAKER WL, 1989, LANDSCAPE ECOL, V2, P111 BAKER WL, 1992, LANDSCAPE ECOL, V7, P181 BAKER WL, 1999, SPATIAL MODELING FOR, P277 BARROWS JS, 1977, LIGHTNING FIRES NO R BESSIE WC, 1995, ECOLOGY, V76, P747 BOTKIN DB, 1993, FOREST DYNAMICS ECOL, P309 BRISTOW KL, 1984, AGR FOREST METEOROL, V31, P159 BUGMANN HKM, 1996, CLIMATIC CHANGE, V34, P289 BYRAM GM, 1959, FOREST FIRE CONTROL, P61 CARY GJ, 1909, ADV GLOBAL CHANGE RE, P233 CARY GJ, 1997, P BIENN AUSTR BUSHF CARY GJ, 1998, THESIS AUSTR NATL U, P284 CARY GJ, 2002, FLAMMABLE AUSTR FIRE, P26 CLARK JS, 1989, OIKOS, V56, P17 CLARK JS, 1990, ECOL MONOGR, V60, P135 CLARK JS, 1993, GEOLOGICAL SOC AM SP, V276, P295 CRAMER W, 1999, GLOB CHANGE BIOL S1, V5, P1 CRUTZEN PJ, 1993, FIRE ENV ECOLOGICAL DALE VH, 1985, ECOL MODEL, V29, P145 DAVIS FW, 1993, PATCH DYNAMICS, P247 DEANGELIS DL, 1998, ECOSYSTEMS, V1, P64 FLANNIGAN MD, 1988, J APPL METEOROL, V27, P441 FLANNIGAN MD, 1991, CAN J FOREST RES, V21, P66 FLANNIGAN MD, 2001, FOREST FIRES BEHAV E, P335 FOX BJ, 1979, AUST J BOT, V27, P157 FUQUAY DM, 1980, P 6 C FIR FOR MET SO GARDNER RH, 1980, ECOLOGY, V61, P323 GARDNER RH, 1982, ECOLOGY, V63, P1771 GARDNER RH, 1996, GLOBAL CHANGE TERRES, P149 GILL AM, 1975, AUST FORESTRY, V38, P4 HARGROVE WW, 2000, ECOL MODEL, V135, P243 HELY C, 2001, CAN J FOREST RES, V31, P430 HIRSCH KG, 1996, 7 CAN FOR SERV NO FO JACKSON WD, 1968, P ECOL SOC AUST, V3, P9 KEANE RE, 1996, INTRP484 USDA FOR SE KEANE RE, 2002, ECOL MODEL, V151, P29 KEANE RE, 2003, FIRE CLIMATIC CHANGE, P32 KEANE RE, 2003, INT J WILDLAND FIRE, V12, P309 KEANE RE, 2004, ECOL MODEL, V179, P3 KNIGHT DH, 1987, LANDSCAPE HETEROGENE, P59 LAVOREL S, 2000, LANDSCAPE FIRE MODEL, P25 LERTZMAN K, 1998, NW SCI, V72, P4 LI C, 2000, CAN J FOREST RES, V30, P1905 LI C, 2000, ECOL MODEL, V134, P129 LI C, 2001, NATURAL RESOURCE MOD, V14, P495 LI C, 2002, ECOL MODEL, V154, P103 LI C, 2002, ROLE BOREAL FORESTS, P107 LI C, 2003, P 4 INT C INT GIS EN LI C, 2004, EMULATING NATURAL FO MATALAS NC, 1967, WATER RESOUR RES, V3, P937 MCARTHUR AG, 1967, 107 COMM AUSTR FOR T MCCARTHY MA, 2002, FLAMMABLE AUSTR FIRE, P76 MORENO JM, 1994, ROLE FIRE MEDITERRAN NOBLE IR, 1980, AUSTR J ECOL, V5, P201 OLSON JS, 1963, ECOLOGY, V44, P322 PAN YD, 1998, OECOLOGIA, V114, P389 RAISON RJ, 1983, AUST FORESTRY, V46, P294 RICHARDSON CW, 1981, WATER RESOUR RES, V17, P182 RODERICK ML, 1999, AGR FOREST METEOROL, V95, P169 RODERICK ML, 2002, SCIENCE, V298, P1410 ROMME WH, 1982, ECOL MONOGR, V52, P199 ROMME WH, 1991, CONSERV BIOL, V5, P373 ROSE KA, 1991, WATER RESOUR RES, V27, P2577 ROTHERMEL RC, 1972, INT115 USDA FOR SERV RUPP TS, 2000, LANDSCAPE ECOL, V15, P383 SCHMIDT KM, 2002, RMRSGTRCD000 USDA FO SHUGART HH, 2001, ENCY GLOBAL ENV CHAN, V2 STARFIELD AM, 1996, ECOL APPL, V6, P842 STOCKS BJ, 1998, CLIMATIC CHANGE, V38, P1 SUFFLING R, 1988, ENVIRON MANAGE, V12, P73 SWANSON FJ, 1997, CHANGING LANDSCAPES, P191 SWETNAM TW, 1993, SCIENCE, V262, P885 TURNER MG, 1989, ECOLOGICAL MODELLING, V47, P1 TURNER MG, 1989, OIKOS, V55, P121 TURNER MG, 1997, ECOL MONOGR, V67, P411 VANWAGNER CE, 1969, FOREST CHRON, V45, P3 VANWAGNER CE, 1987, 35 CAN FOR SERV WALKER J, 1981, FIRE AUSTR BIOTA, P101 WOTTON BM, 1993, FOREST CHRON, V69, P187 0921-2973 Landsc. Ecol.ISI:000235887300010Australian Natl Univ, Sch Resources Environm & Soc, Canberra, ACT 0200, Australia. US Forest Serv, USDA, Rocky Mt Res Stn, Missoula, MT USA. Univ Maryland, Ctr Environm Sci, Appalachian Lab, Frostburg, MD USA. CNRS, Lab Ecol Alpine, Grenoble, France. Canadian Forest Serv, Sault Ste Marie, ON, Canada. Australian Natl Univ, Res Sch Biol Sci, Canberra, ACT 2601, Australia. Canadian Forest Serv, Edmonton, AB, Canada. US Forest Serv, USDA, Pacific NW Res Stn, Corvallis, OR USA. Univ Alaska Fairbanks, Dept Forest Sci, Fairbanks, AK USA. CNRS, CEFE, IRD, UR060, Montpellier, France. Cary, GJ, Australian Natl Univ, Sch Resources Environm & Soc, Bldg 48 Linnaeus Way, Canberra, ACT 0200, Australia. geoffrey.cary@anu.edu.auEnglish|?PCaryl, F. M. Hahs, A. K. Lumsden, L. F. Van der Ree, R. Wilson, C. Wintle, B. A.2014Continuous predictors of species distributions support categorically stronger inference than ordinal and nominal classes: an example with urban bats 1237-1248Landscape Ecology297Aug<Understanding of how species distributions are driven by landscape-level processes has been obscured by null or inconsistent findings from poorly designed studies. We explore how differences in the way potential drivers of species distributions are defined can influence their perceived effects. Specifically, we evaluate how much statistical power is lost when continuous variables are discretised, and how the use of qualitatively defined nominal variables impacts biological interpretation of results. We fitted generalized linear models to dependent variables relating to bat distribution (species richness, diversity, relative abundance of functional groups and individual species) obtained from 36 sites across Melbourne, Australia, and independent variables that were continuous (percentage tree cover, dwelling density), ordinal (dichotomised continuous variables) or nominal (land-use, urban context). We found that models fitted with continuous predictors had better fit and explanatory power than those fitted with ordinal predictors for all response variables. Ordinal models failed to detect statistically significant effects for 4 of the 11 response variables that were successfully modelled with continuous data, suggesting Type II errors had occurred. Models fitted with nominal data explained a comparable amount of variation in some dependent variables as continuous models. However, interpretation of the mechanisms behind responses to nominal categorical levels was obscured because environmental conditions within them were confounded and not homogenous. To gain better understanding from nominal predictors would therefore require further investigation. Our findings show that careful consideration must be given to the choice of environmental variables used for species distribution modelling and how those variables are defined.!://WOS:000339831300012Times Cited: 0 0921-2973WOS:00033983130001210.1007/s10980-014-0062-7|?ICasado-Arzuaga, Izaskun Onaindia, Miren Madariaga, Iosu Verburg, Peter H.2014Mapping recreation and aesthetic value of ecosystems in the Bilbao Metropolitan Greenbelt (northern Spain) to support landscape planning 1393-1405Landscape Ecology298Oct&This paper presents a method to quantify cultural ecosystem services (ES) and their spatial distribution in the landscape based on ecological structure and social evaluation approaches. The method aims to provide quantified assessments of ES to support land use planning decisions. A GIS-based approach was used to estimate and map the provision of recreation and aesthetic services supplied by ecosystems in a peri-urban area located in the Basque Country, northern Spain. Data of two different public participation processes (frequency of visits to 25 different sites within the study area and aesthetic value of different landscape units) were used to validate the maps. Three maps were obtained as results: a map showing the provision of recreation services, an aesthetic value map and a map of the correspondences and differences between both services. The data obtained in the participation processes were found useful for the validation of the maps. A weak spatial correlation was found between aesthetic quality and recreation provision services, with an overlap of the highest values for both services only in 7.2 % of the area. A consultation with decision-makers indicated that the results were considered useful to identify areas that can be targeted for improvement of landscape and recreation management.!://WOS:000342078600010Times Cited: 3 0921-2973WOS:00034207860001010.1007/s10980-013-9945-2]<7 Cascorbi, U.2007zIntegration of invasion ecology theories into the analysis of designed plant communities: a case study in Southern Germany 1371-1381Landscape Ecology229establishment; horticultural meadows; invasiveness; invasibility; aster spp; urban landscapes GAP SIZE; HERBACEOUS PERENNIALS; EUROPEAN LANDSCAPE; TALLGRASS PRAIRIE; INVASIBILITY; GRASSLAND; DIVERSITY; ESTABLISHMENT; VEGETATION; DOMINANCEArticleNovTheories regarding the establishment and persistence of self-naturalising alien species can help in interpreting these processes in designed plant communities with their combination of exotic species and native plant communities. Thus, they may provide a theoretical basis for this kind of landscape design. A case study investigated the influence of plant community conditions (invasibility), species-specific traits (invasiveness), and gap diameter size on the establishment of selected North American prairie forbs in Central European horticultural meadows. Experimental sites were located in Freising, Bavaria. Introduced forbs included Aster laevis, Aster novae-angliae, Aster x salignus, and Aster x versicolor. Establishment success was measured as survival rate and total aboveground dry biomass. Invasibility of the investigated horticultural meadows was strongly related to resource availability, as most influences of plant community traits could ultimately be attributed to this factor. Leaf area and specific leaf area above canopy height of the resident meadow species appear to be the traits that best explained differences in establishment success of the Asters. Gap size influenced species performance mainly on the less productive site, again due to higher availability of resources in the larger gaps. These results are consistent with findings of studies on self-naturalising alien species. By applying this interdisciplinary approach, valuable insights in the functioning of designed plant communities could be gained. Horticultural meadows can be one important tool in designing the highly dynamic urban landscape. In choosing suitable sites, resource availability should be strongly considered.://000250207500009 Cited Reference Count: 53 Cited References: ADOLPHI K, 1990, FLORISTISCHE RUNDBRI, V24, P35 ALMUFTI MM, 1977, J ECOL, V65, P759 ANTROP M, 2000, LANDSCAPE ECOL, V15, P257 BARUCH Z, 1999, OECOLOGIA, V121, P183 BENKERT D, 1996, VERBREITUNGSATLAS FA BUIJS AE, 2006, LANDSCAPE ECOL, V21, P375 BURKE MJW, 1996, ECOLOGY, V77, P776 CLEMENT EJ, 1994, ALIEN PLANTS BRIT IS DAVIDSON MN, 1999, RES NEGOT O, V7, P3 DAVIS MA, 2000, J ECOL, V88, P528 DAVIS MA, 2001, ECOL LETT, V4, P421 DUKES JS, 2002, ECOL APPL, V12, P602 DUNNETT N, 2004, DYNAMIC LANDSCAPE DE, P97 ELLENBERG H, 1986, VEGETATION MITTEUROP FARGIONE J, 2003, P NATL ACAD SCI USA, V100, P8916 FOSTER BL, 2002, OIKOS, V99, P300 GOLDBERG DE, 1983, OECOLOGIA, V60, P149 GRIME JP, 1989, COMP PLANT ECOLOGY GRIME JP, 2001, PLANT STRATEGIES VEG HAEUPLER H, 2000, BILDATLAS FARN BLUTE HANLEY ME, 1996, OECOLOGIA, V106, P240 HEGER T, 2003, BIOL INVASIONS, V5, P313 HITCHMOUGH J, 1999, LANDSCAPE URBAN PLAN, V45, P107 HITCHMOUGH JD, 2000, LANDSCAPE URBAN PLAN, V51, P37 HITCHMOUGH JD, 2003, J HORTIC SCI BIOTECH, V78, P89 HITCHMOUGH JD, 2003, RESTOR ECOL, V11, P20 KING SE, 2000, AM J BOT, V87, P1279 KNICK ST, 1997, LANDSCAPE ECOL, V12, P287 LEVINE JM, 1999, OIKOS, V87, P15 LOHMEYER W, 2001, BRAUNSCHWEIGER GEOBO, V8, P179 LONDSDALE WM, 1999, ECOLOGY, V80, P1522 MAGDA D, 2001, LANDSCAPE ECOL, V16, P491 MEINERS SJ, 2004, ECOL LETT, V7, P121 MORGAN JW, 1997, J APPL ECOL, V34, P566 MULLERDOMBOIS D, 2002, AIMS METHODS VEGETAT OPDAM P, 2002, LANDSCAPE ECOLOGY, V16, P767 PEDROLI B, 2006, LANDSCAPE ECOL, V21, P421 PRIEURRICHARD AH, 2000, AUSTRAL ECOL, V25, P1 PRIEURRICHARD AH, 2000, ECOL LETT, V3, P412 REJMANEK M, 2000, AUSTRAL ECOL, V25, P497 RENOFALT BM, 2005, LANDSCAPE ECOL, V20, P165 SHEA K, 2002, TRENDS ECOL EVOL, V17, P170 SMITH B, 1996, OIKOS, V76, P70 SMITH MD, 1999, OECOLOGIA, V120, P605 SMITH MD, 2001, INT J PLANT SCI, V162, P785 SMITH MD, 2004, OIKOS, V106, P253 THOMPSON K, 2001, J ECOL, V89, P1054 TRESS G, 2004, LANDSCAPE ECOL, V20, P479 VONHOLLE B, 2004, OIKOS, V105, P551 WARDLE DA, 2001, OIKOS, V95, P161 WEAVER JE, 1968, PRAIRIE PLANTS THEIR WEIHER E, 1999, J VEG SCI, V10, P609 WU JG, 2002, LANDSCAPE ECOL, V17, P355 0921-2973 Landsc. Ecol.ISI:000250207500009Tech Univ Munich, Dept Ecol, Subject Grp Ecotoxicol, D-85350 Freising Weihenstephan, Germany. Cascorbi, U, Tech Univ Munich, Dept Ecol, Subject Grp Ecotoxicol, Hochanger 6, D-85350 Freising Weihenstephan, Germany. cascorbi@wzw.tum.deEnglish?|?SCastella, Jean-Christophe Bourgoin, Jeremy Lestrelin, Guillaume Bouahom, Bounthanom2014fA model of the science-practice-policy interface in participatory land-use planning: lessons from Laos 1095-1107Landscape Ecology296JulAn essential task of participatory action-research is to help close the policy implementation gap that leads to large discrepancies between policy frameworks and local practices. Too often, official regulations, laws and decrees fail to translate into concrete action on the ground. Loose institutional linkages between research, extension and local communities are often blamed as the main culprits for this gap. In turn, many stakeholders call for enhanced participation as a way to bring together scientists, development practitioners and local communities in negotiating competing claims for natural resources and designing realistic pathways towards sustainable development. Despite such general consensus about the value of participation, the latter cannot be decreed nor imposed. Participation is an emerging quality of collective-action and social-learning processes. In this paper, the experience of participatory land-use planning conducted in Laos serves to illustrate a model of the science-practice-policy interface that was developed to facilitate the interactions between three groups of stakeholders, i.e. scientists, planners and villagers, in designing future landscapes. Emphasis was put on developing an approach that is generic and adaptive enough to be applied nationally while engaging local communities in context-sensitive negotiations. The set of tools and methods developed through action-research contributed to enhanced communication and participation from initial consultation and cooperation stages towards collective decision-making and action. Both the activity of landscape design and the resulting patterns can be improved by incorporating landscape science in strategic multi-stakeholder negotiations.!://WOS:000338331600013Times Cited: 0 0921-2973WOS:00033833160001310.1007/s10980-014-0043-xd|7,Castilla, G. Larkin, K. Linke, J. Hay, G. J.2009QThe impact of thematic resolution on the patch-mosaic model of natural landscapes15-23Landscape Ecology241geocover landscape metrics maup patch-mosaic model scale thematic resolution minimum mapping unit pattern-analysis changing scale metrics sensitivity ecology indexes sizeJanWe argue that thematic resolution, i.e., the level of categorical detail of a thematic map expressed by the number of classes included in the map legend, is an inherent component of the scale at which a landscape is analyzed. Changing the number of classes can change the configuration of the patch mosaic as much as changing the grain does. We address recent calls in this and other journals to deepen research in this topic. In particular, we report how thematic resolution affects the patchiness of mosaics representing natural landscapes, which have seldom been studied in this respect. We selected seven 50 x 50 km landscapes within national parks, each representative of a world biome. We applied an object-based unsupervised classification to Landsat TM imagery of these landscapes using increasing numbers of classes, between 2 and 50, and derived curves of mean patch size and patch density for each site. Our results are consistent with previous findings in that the patchiness of output mosaics increases monotonically with increasing thematic resolution, with a higher rate of increase up to eight classes that declines until it becomes roughly constant for more than 16 classes. However, this constant rate of increase is still considerable, meaning that, at least for natural landscapes, there is no threshold beyond which the patch-mosaic model is independent of the conceptual filter applied. This dependence on human fiat calls for re-thinking the patch-mosaic paradigm.://000262506000002-395EI Times Cited:0 Cited References Count:31 0921-2973ISI:000262506000002Castilla, G Univ Calgary, Dept Geog, 2500 Univ Dr NW, Calgary, AB T2N 1N4, Canada Univ Calgary, Dept Geog, Calgary, AB T2N 1N4, CanadaDoi 10.1007/S10980-008-9310-ZEnglishڽ75Cattarino, Lorenzo McAlpine, CliveA Rhodes, JonathanR2013vThe consequences of interactions between dispersal distance and resolution of habitat clustering for dispersal success 1321-1334Landscape Ecology287Springer Netherlands~Landscape change Intensity of habitat removal Scale of fragmentation Scale of management Scale mismatch Individual-based model 2013/08/01+http://dx.doi.org/10.1007/s10980-013-9881-1 0921-2973Landscape Ecol10.1007/s10980-013-9881-1English۽75Cattarino, Lorenzo McAlpine, CliveA Rhodes, JonathanR2013Erratum to: The consequences of interactions between dispersal distance and resolution of habitat clustering for dispersal success 1335-1335Landscape Ecology287Springer Netherlands 2013/08/01+http://dx.doi.org/10.1007/s10980-013-9895-8 0921-2973Landscape Ecol10.1007/s10980-013-9895-8English<7Caylor, K. K. Shugart, H. H.2004xSimulated productivity of heterogeneous patches in Southern African savanna landscapes using a canopy productivity model401-415Landscape Ecology194vegetation structure; vegetation productivity; Africa; Botswana; Kalahari; spatial heterogeneity LIGHT-USE EFFICIENCY; SEMIARID SAVANNAS; GLOBAL CHANGE; KALAHARI; RAINFALL; SOIL; PHOTOSYNTHESIS; COMPETITION; COEXISTENCE; VEGETATIONArticle$A daily model of terrestrial productivity is used to simulate the annual productivity of heterogeneous vegetation structure at three savanna/woodland sites along a large moisture gradient in southern Africa. The horizontal distributions of vegetation structural parameters are derived from the three-dimensional canopy structure generated from detailed field observations of the vegetation at each site. Rainfall and daily climatic data are used to drive the model, resulting in a spatially explicit estimate of vegetation productivity in 100 m(2) patches over an area 810,000 m(2) (8,100 patches per site). Production is resolved into tree and grass components for each subplot. The model simulates the relative contribution of trees and grasses to net primary productivity (NPP) along the rainfall gradient. These simulated production estimates agree with previously published estimates of productivity in southern African savannas. Water-use efficiency of each site is directly related to the structural composition of the site and the differing water-use efficiencies for tree and grass functional types. To assess the role of spatial scale in governing estimates of vegetation productivity in heterogeneous landscapes, spatial aggregation is performed on the canopy mosaic at the northern-most (wettest) site for 625 m(2), 2500 m(2) and 5625 m(2) resolutions. These simulations result in similar overall patterns of average NPP for both trees and grasses, but drastically reduced distributions of productivity due to reduced structural heterogeneity. In particular, the aggregation of the detailed spatial mosaic to coarser resolutions is seen to eliminate information regarding demographic processes such as regeneration and mortality, and the dependence of grass productivity on over-story density. These results indicate that models of system productivity in savanna/woodland ecosystems must retain high spatial resolution to adequately characterize multi-year structural responses and to accurately represent the contribution of grass biomass to overall ecosystem production.://000221879000005 LISI Document Delivery No.: 827DM Times Cited: 2 Cited Reference Count: 46 Cited References: ASNER GP, 1998, J GEOPHYS RES, V103, P28 BALL JT, 1987, PROGR PHOTOSYNTHESIS, V4 BELSKY AJ, 1993, J APPL ECOL, V30, P143 BELSKY AJ, 1994, ECOLOGY, V75, P922 CAMPBELL GS, 1998, INTRO ENV BIOPHYSICS CAYLOR KK, IN PRESS GLOBAL CHAN CAYLOR KK, 2003, J ARID ENVIRON, V54, P281 COOK GD, 2002, J VEG SCI, V13, P413 DOWTY P, 2000, SUSTAINABLE NATURAL DOWTY PR, 1999, MODELING BIOPHYSICAL DYE PJ, 1982, ZIMBABWE J AGR RES, V20, P103 FARQUHAR GD, 1980, PLANTA, V149, P78 GHOLZ HL, 1997, USE REMOTE SENSING M GOLLUSCIO RA, 1998, OECOLOGIA, V115, P17 GOODMAN PS, 1990, SOIL VEGETATION LARG HARLEY PC, 1992, PLANT CELL ENVIRON, V15, P271 HAXELTINE A, 1996, FUNCT ECOL, V10, P551 HELY C, IN PRESS J ECOLOGICA JELTSCH F, 1996, J ECOL, V84, P583 JELTSCH F, 1998, J ECOL, V86, P780 JONES HG, 1992, PLANTS MICROCLIMATE KOCH GW, 1995, VEGETATIO, V121, P53 LARCHER W, 1995, PHYSL PLANT ECOLOGY MEDLYN BE, 1998, TREE PHYSIOL, V18, P167 PEARCY RW, 1984, PLANT CELL ENVIRON, V7, P1 PORPORATO A, IN PRESS J GEOPHYSIC PRINCE SD, 1991, INT J REMOTE SENS, V12, P313 PRIVETTE JL, IN PRESS GLOBAL CHAN PRIVETTE JL, 2002, REMOTE SENS ENVIRON, V83, P232 RODRIGUEZITURBE I, 1999, WATER RESOUR RES, V35, P3709 SCANLON TM, IN PRESS GLOBAL CHAN SCHOLES RJ, 1993, AFRICAN SAVANNA SYNT SCHOLES RJ, 1996, GLOBAL CHANGE EFFECT, P69 SCHOLES RJ, 1997, ANNU REV ECOL SYST, V28, P517 SCHOLES RJ, 1997, GEODERMA, V79, P9 SCHOLES RJ, 2002, J VEG SCI, V13, P419 SELLERS PJ, 1996, J CLIMATE, V9, P676 SHUGART HH, 1984, THEORY FOREST DYNAMI SHUGART HH, 1998, TERRESTRIAL ECOSYSTE SKARPE C, 1991, J VEG SCI, V2, P565 SMIT GN, 2000, J ARID ENVIRON, V44, P41 SMITH TM, 1986, J ECOL, V74, P1031 THOMAS DSG, 1991, KALAHARI ENV WALKER BH, 1987, DETERMINANTS TROPICA WOODWARD FI, 1994, ADV BOT RES, V20, P1 WOODWARD FI, 1995, GLOBAL BIOGEOCHEM CY, V9, P471 0921-2973 Landsc. Ecol.ISI:000221879000005Princeton Univ, Dept Civil & Environm Engn, Princeton, NJ 08544 USA. Univ Virginia, Dept Environm Sci, Charlottesville, VA 22904 USA. Caylor, KK, Princeton Univ, Dept Civil & Environm Engn, Princeton, NJ 08544 USA. kcaylor@princeton.eduEnglish ڽ7JdChang, Yu Zhu, Zhiliang Bu, Rencang Chen, Hongwei Feng, Yuting Li, Yuehui Hu, Yuanman Wang, Zhicheng2013\Predicting fire occurrence patterns with logistic regression in Heilongjiang Province, China 1989-2004Landscape Ecology2810Springer NetherlandssLogistic regression Forest fire Fire occurrence Receiver operating characteristic curve Heilongjiang province China 2013/12/01+http://dx.doi.org/10.1007/s10980-013-9935-4 0921-2973Landscape Ecol10.1007/s10980-013-9935-4EnglishO<7l Chapa-Vargas, L. Robinson, S. K.2006Nesting success of a songbird in a complex floodplain forest landscape in Illinois, USA: local fragmentation vs. vegetation structure525-537Landscape Ecology214Acadian flycatcher; Empidonax virescens; habitat fragmentation; Illinois; Kaskaskia River bottoms; landscape composition; multiple scale edge effects BOTTOMLAND HARDWOOD FOREST; REPRODUCTIVE SUCCESS; NEOTROPICAL MIGRANT; PREDATION; HABITAT; BIRDS; EDGE; COWBIRDS; ECOLOGY; DISTURBANCEArticleMayMeasuring edge effects in complex landscapes is often confounded by the presence of different kinds of natural and anthropogenic edges, each of which may act differently on organisms inhabiting habitat patches. In such landscapes, proportions of different habitats surrounding nests within patches often vary and may affect nesting success independently of distance to edges. We developed methods to measure and study the effects of multiple edges and varying habitat composition around nests on the breeding success of the Acadian flycatcher (Empidonax virescens), an understory, open-cup nesting songbird. The Kaskaskia River in Southwestern Illinois was our study area and consists of wide (> 1000-m) floodplain corridors embedded in an agricultural matrix with a variety of natural (wide rivers, backwater swamps, and oxbow lakes) and anthropogenic (internal openings, and agricultural) habitats. We also measured vegetation structure around each nest. Nest survival increased with increasing nest concealment, and probabilities of brood parasitism increased with increasing distances from anthropogenic and natural water-related openings surrounding nests. The magnitude of these effects was small, probably because the landscape is saturated with nest predators and brood parasites. These results illustrate the importance of considering both larger landscape context and details of natural and anthropogenic disturbances when studying the effects of habitat fragmentation on wildlife.://000237487700006 ISI Document Delivery No.: 041WR Times Cited: 0 Cited Reference Count: 58 Cited References: *ENV SYST RES I IN, 2002, ARV VIEW VERS 3 3 ANDREN H, 1995, MOSAIC LANDSCAPES EC, P225 ANGELSTAM P, 1986, OIKOS, V47, P365 BEST LB, 1978, AUK, V95, P9 BIDER JR, 1968, ECOL MONOGR, V38, P269 BOWMAN GB, 1980, J WILDLIFE MANAGE, V44, P806 BRAWN JD, 2001, ANNU REV ECOL SYST, V32, P251 BRITTINGHAM MC, 1983, BIOSCIENCE, V33, P31 BURHANS DE, 2002, J WILDLIFE MANAGE, V66, P240 BURNHAM KP, 2002, MODEL SELECTION INFE CHALFOUN AD, 2002, ECOL APPL, V12, P858 CHAPA L, 2001, THESIS U ILLINOIS UR CHAPA L, 2005, UNPUB AUK 0126 COKER DR, 1995, J WILDLIFE MANAGE, V59, P631 DONNOVAN TM, 2001, ECOL APPL, V11, P871 DONOVAN TM, 1997, ECOLOGY, V78, P2064 DURNER GM, 1993, J WILDLIFE MANAGE, V57, P812 FITZGERALD JA, 2000, PARTNERS FLIGHT BIRD GATES JE, 1991, WILSON BULL, V103, P204 GATES JE, 1998, ECOL APPL, V8, P27 GUSTAFSON EJ, 2002, ECOL APPL, V12, P412 HAHN DC, 1995, CONSERV BIOL, V9, P1415 HOLMES RT, 1996, J ANIM ECOL, V65, P183 HOOVER JP, 1992, THESIS PENNSYLVANIS HOSMER DW, 2000, APPL LOGISTIC REGRES HUHTA E, 2001, ECOGRAPHY, V24, P431 JAMES FC, 1970, AUDUBON FIELD NOTES, V24, P727 JENNESS J, 2004, NEAREST FEATURES VER MANOLIS JC, 2000, AUK, V117, P615 MARTIN TE, 1992, ECOLOGY CONSERVATION, P455 MARTIN TE, 1993, BIOSCIENCE, V43, P523 MARTIN TE, 1993, J FIELD ORNITHOL, V64, P507 MOORMAN CE, 2002, CONDOR, V104, P366 MORSE SF, 1999, CONSERV BIOL, V13, P327 NOLAN V, 1963, ECOLOGY, V44, P305 NORMAN RF, 1975, AUK, V92, P610 OCONNER RJ, 1992, T MISSOURI ACAD SCI, V26, P1 PARKER JW, 1972, BIRD BANDING, V43, P216 PATON PWC, 1994, CONSERV BIOL, V8, P17 PEAK RG, 2004, AUK, V121, P726 RATTI JT, 1988, J WILDLIFE MANAGE, V52, P484 ROBINSON SK, 1994, BIRD CONSERV INT, V4, P233 ROBINSON SK, 1995, SCIENCE, V267, P1987 ROSEBERRY JL, 1970, WILSON B, V82, P243 ROTELLA JJ, 2004, ANIMAL BIODIVERSITY, V27, P187 SARACCO JF, 1999, WILSON BULL, V111, P541 SHAFFER TL, 2004, AUK, V121, P526 SMALL MF, 1988, OECOLOGIA, V76, P62 SUAREZ AV, 1997, CONSERV BIOL, V11, P928 THOMPSON FR, 1995, ECOLOGY MANAGEMENT N, P201 THOMPSON FR, 2000, ECOLOGY MANAGEMENT C, P271 UYEHARA JC, 1996, THESIS U CALIFORNIA UYEHARA JC, 2000, ECOLOGY MANAGEMENT C, P204 VICKERY PD, 1992, AUK, V109, P706 WHITEHEAD DR, 2002, BIRDS N AM, V614, P1 WILSON RR, 1998, WILSON BULL, V110, P226 WILSOVE DS, 1986, CONSERVATION BIOL SC, P237 ZIMMERMAN JL, 1984, CONDOR, V86, P68 0921-2973 Landsc. Ecol.ISI:000237487700006mPotosine Inst Sci & Technol Res, Div Environm Engn & Nat Resources Management, San Luis Potosi 78231, Mexico. Univ Florida, Florida Museum Nat Hist, Gainesville, FL 32611 USA. Chapa-Vargas, L, Potosine Inst Sci & Technol Res, Div Environm Engn & Nat Resources Management, Camino Presa San Jose 2055,Lomas 4a Sect, San Luis Potosi 78231, Mexico. lchapa@ipicyt.edu.mxEnglish۽7Chappell, M. Jahi2013The Localization Reader 1631-1633Landscape Ecology288Springer Netherlands 2013/10/01+http://dx.doi.org/10.1007/s10980-013-9890-0 0921-2973Landscape Ecol10.1007/s10980-013-9890-0Englishp<7q+Chardon, J. P. Adriaensen, F. Matthysen, E.2003Incorporating landscape elements into a connectivity measure: a case study for the Speckled wood butterfly (Pararge aegeria L.)561-573Landscape Ecology186Belgium butterfly connectivity cost-distance effective distance GIS landuse type resistance value spatial configuration HABITAT FRAGMENTATION METAPOPULATION DYNAMICS AGRICULTURAL LANDSCAPE DISPERSAL BEHAVIOR PATCH CONNECTIVITY CORRIDOR USE MODEL SIMULATION RESPONSES QUALITYArticleIn spatial studies of populations, Euclidean distance is commonly used to measure the structural connectivity between habitat patches. The role of the matrix on patch connectivity is thereby ignored. However, the importance of the matrix for (dispersal) movement is increasingly being acknowledged. Our study compared the cost-distance measure with the Euclidean distance. The cost-distance is a simple GIS-calculated connectivity measure that incorporates the resistance of the landscape matrix to movement behaviour. We used presence-absence data from a field study on the Speckled wood butterfly in two Belgian landscapes. Logistic regression revealed that the cost-distance measure had a significantly better predictive power than the Euclidean distance. This result was consistent for all the six sets of different matrix resistance values. In our study the cost-distance proves to be a better connectivity measure than the Euclidean distance.://000185827300002 J ISI Document Delivery No.: 730JH Times Cited: 18 Cited Reference Count: 64 Cited References: *ESRI, 1994, PC ARC INFO *ESRI, 1996, ARCV *GENST 5 COMM, 1993, GENST 5 REL 3 REF MA ADRIAENSEN F, 2003, LANDSCAPE URBAN PLAN, V64, P233 BENNETT AF, 1994, BIOL CONSERV, V68, P155 BOWNE DR, 1999, LANDSCAPE ECOL, V14, P53 BROOKS JD, 1999, MOL UROL, V3, P1 BUNN AG, 2000, J ENVIRON MANAGE, V59, P265 CHRISTOFIDES N, 1975, GRAPH THEORY ALGORIT CONRADT L, 2000, P ROY SOC LOND B BIO, V267, P1505 CONRADT L, 2001, OIKOS, V95, P416 DANIELSON BJ, 2000, LANDSCAPE ECOL, V15, P323 DAVIES NB, 1978, ANIM BEHAV, V26, P138 DAWSON D, 1994, 94 ENGL NAT DEBINSKI DM, 2000, CONSERV BIOL, V14, P342 DOVER JW, 2001, ENTOMOL EXP APPL, V100, P221 EASTMAN JR, 1992, IDRISI USERS GUIDE FAHRIG L, 1985, ECOLOGY, V66, P1762 FERRERAS P, 2001, BIOL CONSERV, V100, P125 FOPPEN RPB, 2000, CONSERV BIOL, V14, P1881 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 HADDAD NM, 1999, AM NAT, V153, P215 HANSKI I, 1994, J ANIM ECOL, V63, P151 HANSKI I, 1999, METAPOPULATION ECOLO HANSKI I, 1999, OIKOS, V87, P209 HILL JK, 2001, ECOL LETT, V4, P313 JONGMAN RHG, 1995, DATA ANAL COMMUNITY JONSEN ID, 2000, OIKOS, V88, P553 KNAAPEN JP, 1992, LANDSCAPE URBAN PLAN, V23, P1 MAES D, 1999, DAGVLINDERS VLAANDER MCCULLAGH P, 1989, GEN LINEAR MODELS MOILANEN A, 1998, ECOLOGY, V79, P2503 MOILANEN A, 2001, OIKOS, V95, P147 MOILANEN A, 2002, ECOLOGY, V84, P1131 OPDAM P, 2002, LANDSCAPE ECOLOGY, V16, P767 PETIT S, 1998, AGR ECOSYST ENVIRON, V69, P243 PITHER J, 1998, OIKOS, V83, P166 POLLARD E, 1993, MONITORING BUTTERFLI RICKETTS TH, 2001, AM NAT, V158, P87 RIES L, 2001, J ANIM ECOL, V70, P840 ROLAND J, 2000, ECOLOGY, V81, P1642 SCHIPPERS P, 1996, ECOGRAPHY, V19, P97 SCHULTZ CB, 2001, ECOLOGY, V82, P1879 SHREEVE TG, 1985, THESIS OXFORD POLYTE STCLAIR CC, 1998, CONSERV ECOL, V2, P13 SUTCLIFFE OL, 1996, CONSERV BIOL, V10, P1359 TISCHENDORF L, 1998, ECOL MODEL, V106, P107 TISCHENDORF L, 2000, OIKOS, V90, P7 TISCHENDORF L, 2001, OIKOS, V95, P152 VANAPELDOORN RC, 1992, OIKOS, V65, P265 VANDYCK H, 1997, ANIM BEHAV 1, V53, P39 VERBEYLEN G, IN PRESS DOES MATRIX VERBOOM B, 1990, LANDSCAPE ECOL, V4, P171 VERBOOM J, 2001, BIOL CONSERV, V100, P89 VERMEULEN HJW, 1995, THESIS WAGENINGEN AG VOS CC, UNPUB MODELLING MOVE VOS CC, 1998, J APPL ECOL, V35, P44 VOS CC, 2001, AM NAT, V157, P24 WALKER R, 1997, P ESRI EUR US C COP WARREN MS, 1992, ECOLOGY BUTTERFLIES, P73 WHITCOMB RF, 1981, FOREST ISLAND DYNAMI, P125 WICKMAN PO, 1983, ANIM BEHAV, V31, P1206 WITH KA, 1999, ECOLOGY, V80, P1340 ZOLLNER PA, 2000, LANDSCAPE ECOL, V15, P523 0921-2973 Landsc. Ecol.ISI:000185827300002Univ Wageningen & Res Ctr, Dept Landscape Ecol, ALTERRA, NL-6700 AA Wageningen, Netherlands. Univ Antwerp, Lab Anim Ecol, B-2610 Antwerp, Belgium. Chardon, JP, Univ Wageningen & Res Ctr, Dept Landscape Ecol, ALTERRA, POB 47, NL-6700 AA Wageningen, Netherlands.English? Chatterjee, A. Jenerette, G.2011MSpatial variability of soil metabolic rate along a dryland elevation gradient 1111-1123Landscape Ecology268Springer NetherlandsEarth and Environmental ScienceXA general framework of ecosystem hotspots suggests variation in soil metabolic activity can be understood through the relative distribution and intensity of patches of disproportionately high ecosystem process rates. To better understand the causes of soil metabolic spatial variability and the variation in ecosystem hotspots we quantified soil respiration (R) spatial heterogeneity across a network of seven sites spanning a 2,489 m elevation gradient in the Santa Rosa Mountains of Southern California. At each site, soil samples were collected from 0–5 and 5–15 cm soil depths at 2 m intervals along three 100 m transects. Each soil sample was analyzed for organic matter content (SOM) and was incubated at 40% water holding capacity for 20 days. R was measured at days 5 and 20. Strong contrasts were observed between the relationships of soil physical variables and R at scales of individual landscapes and the whole region. Notably, the relationship between SOM and R was positive within individual landscapes and negative across the entire region. Plant canopy microenvironments were associated with elevated SOM and R relative to the interspaces. This microenvironment effect on R was reduced by elevation, incubation interval, and soil depth. Geostatistical analyses conducted individually for each site identified an increasing range of autocorrelation from 2 to 10 m and a decreasing proportion of variation that was included in this range with elevation. These results suggest hotspots increase in size but decrease in intensity with elevation thereby creating a maximum hotspot effect at middle elevations.+http://dx.doi.org/10.1007/s10980-011-9632-0 0921-297310.1007/s10980-011-9632-0R<7 Cheddadi, R. Guiot, J. Jolly, D.2001DThe Mediterranean vegetation: what if the atmospheric CO2 increased?667-675Landscape Ecology167abiomes CO2 Mediterranean pollen POLLEN DATA CLIMATE CHANGE MODEL EQUILIBRIUM EUROPE RECORD BIOMESArticleOctThe atmospheric CO2 content is expected to continue to increase and probably induce warming at the global scale during the next century. The impact of such an increase will affect the composition and distribution of ecosystems on the same scale. To predict the integrated whole-ecosystem response to the CO2 increase in the Mediterranean region we used a vegetation biogeochemical model. This model (BIOME3) integrates monthly temperature and precipitation, some soil characteristics, cloudiness and CO2 concentration as inputs to simulate the vegetation in terms of biomes. First we demonstrate the ability of the model to simulate past vegetation when tested versus pollen data. Second we use the vegetation model for different climate scenarios and report results of future changes in the Mediterranean vegetation. These simulations indicate that an increase of the atmospheric CO2 to 500 ppmv, jointly with an increase of about 2 degreesC of the mean annual temperature, as simulated by several atmospheric general circulation models, should be accompanied by a severe reduction (more than 30%) of the present annual precipitation to change significantly the present vegetation surrounding the Mediterranean. When precipitation is maintained at its present-day level, an evergreen forest spreads in the eastern Mediterranean and a conifer forest in Turkey. In NW Africa, a woody xerophytic vegetation occupies a more extensive territory than today and replaces part of the present steppe area.://000172809400007 ISI Document Delivery No.: 503QG Times Cited: 9 Cited Reference Count: 37 Cited References: *IPCC, 1995, SCI CLIMATE CHANGE C BEERLING DJ, 1997, GLOBAL ECOL BIOGEOGR, V6, P439 BROCCOLI AJ, 1987, CLIM DYNAM, V1, P87 BROCCOLI AJ, 1994, NATO ASI SERIES I, V22, P551 CEULEMANS R, 1994, NEW PHYTOL, V127, P425 CHEDDADI R, 1997, CLIM DYNAM, V13, P1 CUELEMANS R, 1998, P EUR SCH CLIM NAT H, P159 GUIOT J, 1996, PALAEOCLIMATES, V1, P311 HAXELTINE A, 1996, GLOBAL BIOGEOCHEM CY, V10, P693 HENNESSY KJ, 1997, CLIM DYNAM, V13, P667 HUNTLEY B, 1989, J BIOGEOGR, V16, P5 HUNTLEY B, 1991, ANN BOT-LONDON, V67, P15 JOLLY D, 1997, SCIENCE, V276, P786 KALLEL N, 1997, OCEANOL ACTA, V20, P697 KALLEL N, 1997, PALAEOGEOGR PALAEOCL, V135, P97 LARCHER W, 1981, COMPONENTS PRODUCTIV, P259 LEEMANS R, 1991, RR9118 INT I APPL SY LEHOUEROU HN, 1979, ARID LAND ECOSYSTEMS, P83 MASSON V, 1999, CLIM DYNAM, V15, P163 MELILLO JM, 1993, NATURE, V363, P234 MITCHELL JFB, 1987, NATURE, V330, P238 PAGANI M, 1999, PALEOCEANOGRAPHY, V14, P273 PENG C, 1997, ECOENVIRON RES SUSTA, P1 PENNINGTON W, 1986, LAGS ADJUSTMENT VEGE PONS A, 1988, PALAEOGEOGR PALAEOCL, V66, P243 PRENTICE IC, 1992, J BIOGEOGR, V19, P117 PRENTICE IC, 1996, CLIM DYNAM, V12, P185 RAYNAUD D, 1993, SCIENCE, V259, P926 RITCHIE JC, 1986, VEGETATIO, V67, P65 SAUGIER B, 1998, P EUR SCH CLIM NAT H, P101 TARASOV PE, 1998, J QUATERNARY SCI, V13, P335 VANDEGEIJN SC, 1998, P EUR SCH CLIM NAT H, P137 WALTER H, 1970, AREALKUNDE FLORISTIS WEBB T, 1986, VEGETATIO, V67, P75 WIJMSTRA TA, 1969, ACTA BOT NEERL, V18, P511 WILSON CA, 1987, CLIMATIC CHANGE, V10, P11 WOODWARD FI, 1987, CLIMATE PLANT DISTRI 0921-2973 Landsc. Ecol.ISI:000172809400007Fac Sci & Tech St Jerome, Inst Mediterraneen Ecol & Paleoecol, CNRS, UMR 6116, F-13397 Marseille 20, France. Cheddadi, R, Fac Sci & Tech St Jerome, Inst Mediterraneen Ecol & Paleoecol, CNRS, UMR 6116, F-13397 Marseille 20, France.English|?/Chen, Huapeng Ott, Peter Wang, James Ebata, Tim2014|A positive response of mountain pine beetle to pine forest-clearcut edges at the landscape scale in British Columbia, Canada 1625-1639Landscape Ecology299Nov$In British Columbia, large-scale salvage harvesting has been underway to recover timber value from forest stands infested by mountain pine beetle during the current outbreak. Understanding the response of beetles to clearcut edges particularly at the landscape scale is crucial to understanding the impacts of increased habitat fragmentation due to salvage harvesting on the spread of the beetle infestations. A novel proximity analysis approach based on null models of complete spatial randomness with three different spatial extents was developed to examine the spatial patterns of infestations in relation to cutblocks. Inhomogeneous Poisson point process models were fitted to predict how intensities of infestations varied with distances to the nearest cutblocks. Marked Poisson point process models were also fitted to evaluate the effects of the variables associated with the nearest cutblocks and adjacent infested pine stands on the edge response of beetles. The results clearly illustrated a significant positive edge response of beetles at the landscape scale. The intensities of infestations decreased non-linearly with distances to the nearest cutblocks. The results also suggested that the quality and distribution of key habitat resources could not fully explain the fundamental mechanisms underlying the edge response. The behavioural change of beetle dispersal at edges may also be an important factor contributing to a positive edge response. The results from this study may be useful in improving the efficacy of mountain pine beetle management efforts.!://WOS:000343648700013Times Cited: 0 0921-2973WOS:00034364870001310.1007/s10980-014-0090-3n|? &Chen, Hao Pontius, Robert Gilmore, Jr.2010iDiagnostic tools to evaluate a spatial land change projection along a gradient of an explanatory variable 1319-1331Landscape Ecology259Nov"This paper proposes a method to quantify the goodness-of-fit of a land change projection along a gradient of an explanatory variable, by classifying pixels as one of four types: null successes, false alarms, hits, and misses. The method shows: (1) how the correctness and error of a land change projection are distributed along the gradient of an explanatory variable, (2) how the gradient of the explanatory variable relates to the stationarity of the land transition processes, and (3) how to use the insights from the previous two points to search for additional explanatory variables. The paper illustrates the method through a case study that applies the model Geomod in Central Massachusetts, USA. Results reveal that the model predicts more than the observed amount of change on flat slopes and less than the observed amount of change on steep slopes. One reason for these types of errors is that the land change process during the calibration interval is different than the process during the prediction interval with respect to slope. The method allows modelers to use the validation step as a diagnostic tool to search for potentially influential missing variables and to gain insight into land transition processes. The technique is designed to be applicable to a variety of types of land change models.!://WOS:000281981000002Times Cited: 1 0921-2973WOS:00028198100000210.1007/s10980-010-9519-5|?Chen, Jiquan Liu, Yongqiang2014BCoupled natural and human systems: a landscape ecology perspective 1641-1644Landscape Ecology2910Dec!://WOS:000346920900001Times Cited: 0 0921-2973WOS:00034692090000110.1007/s10980-014-0125-9+<7fChen, S. S. Jim, C. Y.2003HQuantitative assessment of the treescape and cityscape of Nanjing, China395-412Landscape Ecology184cityscape Nanjing species diversity treescape urban forest urban landscape urban tree URBAN FOREST STRUCTURE HONG-KONG LANDSCAPE FLORAArticlexThe urban landscape is by nature the result of many cultural and natural factors and processes. Cityscape associated with land attributes and human activities expresses a city's social and economic functions. Treescape in the form of species composition, tree dimension and tree performance echoes ecological and environmental functions. The cityscape can be denoted by urban factors, such as tree growing-space condition, tree management regime, human activities and planting history. The hypothesis that the cityscape plays a key role in molding the treescape is tested. Nanjing, an east China city notable for its high tree coverage, is chosen as the study area. A quantitative method has been developed to assess the relationship between cityscape and treescape. Based on statistical analyses on the surveyed results of 6527 trees and related cityscape attributes, this paper explores the pertinent patterns and underlying factors of treescape variations. Species composition has the strongest association with cityscape. Roadside and factories have lower species diversity. Residential and industrial land uses show smaller tree dimension. Trees in residential, commercial, heavy industrial land-uses perform below par. A three-way classification has been developed to examine the effects of urban factors on treescape at different cityscape scales. At the small scale, a well-vegetated groundcover will ensure better tree performance and a lower management burden. The medium-scale cityscape (land-use and habitat) is preferred in the study of treescape attributes and their spatial variations, and is suitable for urban tree planning and management.://000185919200004 <ISI Document Delivery No.: 732AT Times Cited: 0 Cited Reference Count: 38 Cited References: ANDERSON CJ, 1989, SOIL USE MANAGE, V5, P62 BRADSHAW AD, 1995, TREES URBAN LANDSCAP BREUSTE J, 1998, URBAN ECOLOGY CHEN S, 1998, SCI GEOGRAPHICA SINI, V18, P425 FORMAN RTT, 1986, LANDSCAPE ECOLOGY GILBERT OL, 1989, ECOLOGY URBAN HABITA GODEFROID S, 2001, LANDSCAPE URBAN PLAN, V52, P203 IHSE M, 1995, LANDSCAPE URBAN PLAN, V31, P21 IVERSON LR, 2000, URBAN ECOSYSTEMS, V4, P105 JAENSON R, 1992, J ARBORICULT, V18, P171 JIM CY, 1989, GEOFORUM, V20, P57 JIM CY, 1993, LANDSCAPE URBAN PLAN, V23, P119 JIM CY, 1997, ARBORICULTURAL J, V21, P73 JIM CY, 1997, ARBORICULTURAL J, V21, P89 JIM CY, 1998, LANDSCAPE URBAN PLAN, V40, P235 JIM CY, 2001, FOREST ECOL MANAG, V146, P99 LI BL, 2000, LANDSCAPE URBAN PLAN, V50, P27 MANDER U, 1998, LANDSCAPE URBAN PLAN, V41, P149 MCDONNELL MJ, 1990, ECOLOGY, V71, P1231 MEDLEY KE, 1995, PROF GEOGR, V47, P159 MILLER PR, 1984, URBAN ECOL, V8, P29 NADEL IB, 1977, TREES CITY PORACSKY J, 1999, J ARBORICULT, V25, P9 ROWNTREE RA, 1983, GEOGRAPHICAL PERSPEC, V51, P49 SANDERS RA, 1980, URBAN ECOL, V5, P33 SANDERS RA, 1984, URBAN ECOL, V8, P13 SCHMID JA, 1975, 161 U CHIC DEP GEOGR SIMPSON EH, 1949, NATURE, V163, P688 SKANES HM, 1997, LANDSCAPE URBAN PLAN, V38, P61 SUDHA P, 2000, LANDSCAPE URBAN PLAN, V47, P47 SUKOPP H, 1990, URBAN ECOLOGY PLANTS TALARCHEK GM, 1987, J ARBORICULT, V13, P217 TALARCHEK GM, 1990, URBAN GEOGR, V11, P65 WALKER TD, 1990, PLANTS LANDSCAPE, P152 WELCH JM, 1994, LANDSCAPE URBAN PLAN, V29, P131 WHITNEY GG, 1985, URBAN ECOL, V9, P143 WICKOP E, 1998, URBAN ECOL, P49 ZMYSLONY J, 1998, LANDSCAPE URBAN PLAN, V40, P295 0921-2973 Landsc. Ecol.ISI:000185919200004Univ Hong Kong, Dept Geog, Hong Kong, Hong Kong, Peoples R China. Chinese Acad Sci, Nanjing Inst Geog & Limnol, Nanjing, Peoples R China. Jim, CY, Univ Hong Kong, Dept Geog, Pokfulam Rd, Hong Kong, Hong Kong, Peoples R China.English |? Chen, Xiangqiao Wu, Jianguo2009sSustainable landscape architecture: implications of the Chinese philosophy of "unity of man with nature" and beyond 1015-1026Landscape Ecology248>As the world population continues to grow and as global urbanization continues to unfold, our ecosystems and landscapes will be increasingly domesticated and designed. Developing and maintaining sustainable landscapes have become one of the most challenging and imperative tasks for scientists and stakeholders of all sorts. To accomplish this task, landscape ecology and landscape architecture can and must play a critical role. Landscape architects intentionally modify and create landscapes, and their imprints and influences are pervasive and profound, far beyond the physical limits of the designed landscapes. As an interdisciplinary and transdisciplinary enterprise that integrates the science and art of studying and influencing the relationship between spatial pattern and ecological processes, the theory, methods, and applications of landscape ecology are directly relevant to sustainability. However, neither landscape ecology nor landscape architecture is likely to achieve its expected goal if they are not truly integrated to produce a sustainable landscape architecture. In this paper, we argue that the ancient Chinese philosophy of "unity of man with nature" and its associated design principles can provide useful guidelines for this integration as well as for the development of a sustainable landscape architecture. We discuss several principles and models of Chinese landscape architecture, including "unity of man with nature" philosophy, "peach blossom spring" ideal, "world-in-a-pot" model, and Feng-Shui theory, and their implications for developing a sustainable landscape architecture. Although differences in the philosophical roots and design traditions between Eastern and Western landscape architecture will continue to exist, interactions and integration between the two will continue to increase under the theme of sustainability. To promote the translation of scientific knowledge into practice, we urge landscape ecologists to work proactively with landscape architects to integrate pattern-process-scale and holistic perspectives into the design and planning of landscapes.%://BIOSIS:PREV200900587089Times Cited: 0 0921-2973BIOSIS:PREV200900587089:10.1007/s10980-009-9350-z <7&$Chen, X. W. Barrows, C. W. Li, B. L.2006SPhase coupling and spatial synchrony of subpopulations of an endangered dune lizard 1185-1193Landscape Ecology218Coachella Valley fringe-toed lizard; density; reproductive effort; spatial synchrony; phase coupling POPULATION-DYNAMICS; MOTH; OUTBREAKS; PATTERNSArticleNovExamining demographic phase coupling and spatial synchrony is important for understanding complicated spatiotemporal population dynamics. It is also necessary for protecting rare and endangered species; populations whose dynamics are controlled by resource flux will face increased extinction risk if environmental conditions that drive those resources become spatially synchronized. In this study, we studied the spatial synchrony of subpopulations of the threatened Coachella Valley fringe-toed lizard (Uma inonzata), on its remaining sand dune habitat in the Coachella Valley of California. Our results indicated that there is a high level of spatial synchrony between lizard density and their mean reproductive effort for two subpopulations separated by a relatively short distance. High levels of spatial synchrony also exist between the mean lizards' reproductive effort and annual precipitation. We measured spatial synchrony using four separate methods; using different methods allows understanding of complicated ecological interactions.://000242089300002 ISI Document Delivery No.: 106GP Times Cited: 0 Cited Reference Count: 23 Cited References: BARROWS CW, 1996, CONSERV BIOL, V10, P888 BARROWS CW, 1997, SOUTHWEST NAT, V42, P218 BJORNSTAD ON, 1999, TRENDS ECOL EVOL, V14, P427 BUONACCORSI JP, 2001, ECOLOGY, V82, P1668 GRENFELL BT, 1998, NATURE, V394, P674 HANSKI I, 1993, J ANIM ECOL, V62, P656 HAYDON DT, 2000, THEOR POPUL BIOL, V58, P239 HAYDON DT, 2001, P NATL ACAD SCI USA, V98, P13149 HEINO M, 1997, P ROY SOC LOND B BIO, V264, P481 HUDSON PJ, 1999, TRENDS ECOL EVOL, V14, P1 IMS RA, 1990, OIKOS, V57, P381 KOENIG WD, 1998, CONSERV BIOL, V12, P612 KROHNE DT, 1988, CAN J ZOOL, V66, P2170 LAMBIN X, 1998, P ROY SOC LOND B BIO, V265, P1491 MASON RR, 1978, ENVIRON ENTOMOL, V7, P672 NORRIS KS, 1958, B AM MUS NAT HIST, V114, P251 PALMQVIST E, 1998, OIKOS, V83, P359 PELTONEN M, 2002, ECOLOGY, V83, P3120 POLLARD E, 1991, OIKOS, V60, P7 POST E, 2004, P NATL ACAD SCI USA, V101, P9286 RANTA E, 1995, P ROY SOC LOND B BIO, V262, P113 STEBBINS RC, 1944, ECOL MONOGR, V14, P311 WILLIAMS DW, 1995, ENVIRON ENTOMOL, V24, P987 0921-2973 Landsc. Ecol.ISI:000242089300002fAlabama A&M Univ, Ctr Forestry & Ecol, Normal, AL 35762 USA. Univ Calif Riverside, Dept Bot & Plant Sci, Riverside, CA 92521 USA. Univ Calif Riverside, Ctr Conservat Biol, Riverside, CA 92521 USA. Ctr Nat Lands Management, La Quinta, CA 92253 USA. Chen, XW, Alabama A&M Univ, Ctr Forestry & Ecol, POB 1927, Normal, AL 35762 USA. xiongwen.chen@e-mail.aamu.eduEnglish?Cherrill, Andrew McClean,Colin1995mAn investigation of uncertainty in field habitat mapping and the implications for detecting land cover change5-21Landscape Ecology101Ofield survery, vegetation, land cover type, mapping, uncertainty, error, changed|7e Cherrill, A. Mcclean, C.1995mAn Investigation of Uncertainty in-Field Habitat Mapping and the Implications for Detecting Land-Cover Change5-21Landscape Ecology101Hfield survey vegetation land cover type mapping uncertainty error changeFebELand cover data for landscape ecological studies are frequently obtained by field survey. In the United Kingdom, temporally separated field surveys have been used to identify the locations and magnitudes of recent changes in land cover. However, such map data contain errors which may seriously hinder the identification of land cover change and the extent and locations of rare landscape features. This paper investigates the extent of the differences between two sets of maps derived from field surveys within the Northumberland National Park in 1991 and 1992. The method used in each survey was the 'Phase 1' approach of the Nature Conservancy Council of Great Britain. Differences between maps were greatest for the land cover types with the smallest areas. Overall spatial correspondence between maps was found to be only 44.4%. A maximum of 14.4% of the total area surveyed was found to have undergone genuine land cover change. The remaining discrepancies, equivalent to 41.2% of the total survey area, were attributed primarily to differences of land cover interpretation between surveyors (classification error). Differences in boundary locations (positional error) were also noted, but were found to be a relatively minor source of error. The implications for the detection of land cover change and habitat mapping are discussed.://A1995QL68700002-Ql687 Times Cited:19 Cited References Count:0 0921-2973ISI:A1995QL68700002Cherrill, A Univ Newcastle Upon Tyne,Ctr Land Use & Water Resources Res,Porter Bldg,St Thomas St,Newcastle Tyne Ne1 7ru,Tyne & Wear,EnglandEnglish <7]Cherrill, A. McClean, C.1997MThe impact of landscape and adjacent land cover upon linear boundary features255-260Landscape Ecology124Elinear habitats; drystone walls; land cover; boundaries; edge effectsArticleAugThe condition of over 200 km of traditional drystone walls was surveyed within 115 km(2) in lowland, marginal upland and upland landscapes in northern England. The land covers adjacent to walls were also recorded. Of the total length of walls surveyed, 12.6% were in disrepair. The condition of the walls differed between landscapes and was also related to the type of vegetation in the adjacent enclosure. Walls enclosing conifer plantations and unimproved rough grazing were in poor condition reflecting historical and recent changes in their roles as livestock barriers and markers of ownership. The effect of other land covers on the condition of walls was not consistent between landscapes. Using drystone walls as a simple model system suggests that the condition of linear features in general may often be determined by both the adjacent land cover and the landscape in which the features occur.://A1997XV63300005 ?ISI Document Delivery No.: XV633 Times Cited: 1 Cited Reference Count: 22 Cited References: *NAT CONS COUNC, 1990, HDB PHAS 1 HAB SURV BARR CJ, 1986, LANDSCAPE CHANGES BR BARR CJ, 1993, COUNTRYSIDE SURVEY 1 BOATMAN ND, 1994, BCPC MONOGRAPH, V58, P209 BOATMAN ND, 1994, BRIT CROP PROTECTION, V58 BUNCE RGH, 1993, LANDSCAPE ECOLOGY AG, P11 BUNCE RGH, 1994, BCPC MONOGRAPH, V58, P13 BUNCE RGH, 1994, BCPC MONOGRAPH, V58, P43 CHERRILL A, 1995, APPL GEOGR, V15, P69 CHERRILL AJ, 1996, LANDSCAPE RES, V21, P109 DARLINGTON A, 1981, ECOLOGY WALLS DENNIS P, 1994, J APPL ECOL, V31, P361 HEGARTY CA, 1994, BRIT CROP PROTECTION, V58, P227 LACK PC, 1992, BIRDS LOWLAND FARMLA MOUNTFORD JO, 1994, BRIT CROP PROTECTION, V58, P105 POLLARD E, 1974, HEDGES RACKHAM O, 1986, HIST COUNTRYSIDE RAISTRICK A, 1946, PENNINE WALLS SINCLAIR G, 1983, UPLAND LANDSCAPES ST SOTHERTON NW, 1987, BRIT CROP PROTECTION, V35, P67 WATSON A, 1989, LANDSCAPE RES, V14, P18 YAHNER RH, 1988, CONSERV BIOL, V2, P333 0921-2973 Landsc. Ecol.ISI:A1997XV63300005gUNIV NEWCASTLE UPON TYNE,CTR LAND USE & WATER RESOURCES RES,NEWCASTLE TYNE NE1 7RU,TYNE & WEAR,ENGLAND.English?KCherrill, A.J. McClean, C. Watson, P. Tucker,K. Rushton, S.P. Sanderson, R.1995`Predicting the districutions of plant species at the regional scale: a hierarchical matrix model197-207Landscape Ecology104Landscape classification, land cover, National Vegetation Classification, spatial scale, geographical inforamtion systems, environmental impact assessment|7T NCherrill, A. J. Mcclean, C. Watson, P. Tucker, K. Rushton, S. P. Sanderson, R.1995aPredicting the Distributions of Plant-Species at the Regional-Scale - a Hierarchical Matrix Model197-207Landscape Ecology104landscape classification land cover national vegetation classification spatial scale geographical information systems environmental impact assessmentAugThis paper describes a model which links four levels in an ecological hierarchy using a series of matrices. The four levels are landscape, land cover type, community and species. Each matrix quantifies the probabilistic associations between entities in two adjacent levels in the hierarchy. A landscape classification (1 km resolution) provides a spatial element to the model enabling the distributions of species to be predicted and presented as maps within a geographical information system (GIS). Implementation of the model in Northern England is described. The distributions of 579 species of plants were predicted and compared with data from independent field surveys. The predicted distributions were found to be accurate for 59% of species. The distributions of rare and non-native (introduced) species of plant were relatively poorly predicted. The potential of this approach to model plant species distributions is discussed.://A1995RP98800002-Rp988 Times Cited:22 Cited References Count:0 0921-2973ISI:A1995RP98800002GCherrill, Aj Univ Sunderland,Ctr Ecol,Sunderland Sr1 3sd,Durham,EnglandEnglishB|?! Child, M. F. Milton, S. J. Dean, R. W. J. Lipsey, M. K. Puttick, J. Hempson, T. N. Mann, G. K. Babiker, H. Chaudrey, J. Humphrey, G. Joseph, G. Okes, N. C. Potts, R. Wistebaar, T.2010ETree-grass coexistence in a flood-disturbed, semi-arid savanna system315-326Landscape Ecology252The coexistence of trees and grasses in savanna ecosystems is a contentious phenomenon. Fire and herbivory disturbances are often cited as major structuring forces that create a sustainable tree grass relationship. However, periodic flooding of savanna patches may also enable coexistence. The aim of this study was to investigate the effects of flood-disturbance on the recruitment patterns of Acacia karroo trees in a semi-arid savanna system in South Africa. We analysed the spatial coincidence of A. karroo seedlings with tussocks of the tall spiny grass Stipagrostis namaquensis in the riverbed and related herbivory intensity to spatial position. The data showed that A. karroo seedlings were significantly positively associated with S. namaquensis (Chi-square test, chi(2)(1) = 45.20, n = 118, P < 0.001); A. karroo seedlings growing inside of tussocks experienced less browsing pressure than those growing in the floodplain (Kruskal-Wallis test, H = 11.90, n = 118, P < 0.01); and recruitment success of A. karroo trees was spatially discrete (K-S test, D = 0.78, n = 196, P < 0.01). We suggest that floods create an enemy-free zone, which S. namaquensis colonises and then facilitates successful A. karroo establishment. High levels of A. karroo recruitment in the riverbed may replenish the woodlands fringing the river, which appear to be sink areas for A. karroo seedlings. Thus, the interaction between disturbances at different spatial and temporal scales (flooding versus herbivory) seems to maintain the inherently unstable coexistence of tree and grass species in this ecosystem. These findings also suggested that flood disturbances alter the tree-grass relationship.!://WOS:000274437100011Times Cited: 0 0921-2973WOS:00027443710001110.1007/s10980-009-9409-x<7.Childers, D. L. Sklar, F. H. Hutchinson, S. E.1994oStatistical treatment and comparative analysis of scale-dependent aquatic transect data in estuarine landscapes127-141Landscape Ecology92~ESTUARIES; COASTAL LANDSCAPES; AQUATIC TRANSECT DATA; COMPARATIVE STATISTICS; ANCOVA; FLOATING WINDOW; VARIABLE SCALE ANALYSISArticleJun Estuarine ecosystem dynamics have evolved around and respond to landscape-level influences that are dynamic in space and time. The estuarine water column is effectively the physical and biologial integrator of these landscape inputs. In this paper, we present a floating window Analysis of Covariance (ANCOVA) technique to statistically compare and contrast aquatic transect data that were taken at different times and under different tidal conditions, yet were geographically parallel and spatially articulate. The floating window ANCOVA compared two transects by testing whether the means of the dependent variable were significantly different while also testing whether the slopes of patterns in the dependent variable were significantly different. By varying the size of the floating window where the ANCOVA was run, we were able to examine how scale affected the magnitude and spatial pattern of that variable. The percentages of total models run, at a given window size, that generated significantly different magnitudes (means) and patterns (slopes) in the dependent variable were referred to as the ''degree of dissimilarity''. Plots of window size versus degree of dissimilarity elucidated temporal and spatial variability in water column parameters at a range of scales. The advantages of this new statistical method in relation to traditional spatial statistics are discussed. We demonstrated the efficacy of the floating window ANCOVA method by comparing chlorophyll and salinity transect data taken at the North Inlet, SC estuary during flooding and ebbing tides in Winter, Spring, and Summer 1991. Chlorophyll concentrations represented the biological characteristics of the estuarine water column and salinity represented the physical processes affecting that water column. We found total dissimilarity in the magnitude of salinity data from one season to the next at all scales, but inter-seasonal similarity in spatial patterns over both short (hourly) and long (monthly) time scales. We also found a large seasonal dissimilarity in the magnitude of chlorophyll levels, as expected. Spatial patterns in phytoplankton biomass (as chlorophyll concentrations) appeared to be largely controlled by the physical processes represented with the salinity data. Often, we observed greater dissimilarity in biological and physical parameters from one tide to the next [on a given day] than from one season to the next. In these cases, the greatest flood-ebb differences were associated with landscape-level influences - from rivers and the coastal ocean - that varied greatly with direction of tidal flow. We are currently using spatially articulate aquatic transect data and the floating window ANCOVA technique to validate spatial simulation models at different scales. By using this variable-scale statistical technique to determine coherence between the actual transect data and model output from simulations run at different scales, we will test hypotheses about the scale-dependent relationships between data resolution and model predictability in landscape analysis.://A1994NU09400005 HISI Document Delivery No.: NU094 Times Cited: 7 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1994NU09400005hCHILDERS, DL, NATL MARINE FISHERIES SERV,SE FISHERY SCI CTR,GALVESTON LAB,4700 AVE U,GALVESTON,TX 77551.EnglishK|7x .Childers, D. L. Sklar, F. H. Hutchinson, S. E.1994oStatistical Treatment and Comparative-Analysis of Scale-Dependent Aquatic Transect Data in Estuarine Landscapes127-141Landscape Ecology92xestuaries coastal landscapes aquatic transect data comparative statistics ancova floating window variable scale analysisJun Estuarine ecosystem dynamics have evolved around and respond to landscape-level influences that are dynamic in space and time. The estuarine water column is effectively the physical and biologial integrator of these landscape inputs. In this paper, we present a floating window Analysis of Covariance (ANCOVA) technique to statistically compare and contrast aquatic transect data that were taken at different times and under different tidal conditions, yet were geographically parallel and spatially articulate. The floating window ANCOVA compared two transects by testing whether the means of the dependent variable were significantly different while also testing whether the slopes of patterns in the dependent variable were significantly different. By varying the size of the floating window where the ANCOVA was run, we were able to examine how scale affected the magnitude and spatial pattern of that variable. The percentages of total models run, at a given window size, that generated significantly different magnitudes (means) and patterns (slopes) in the dependent variable were referred to as the ''degree of dissimilarity''. Plots of window size versus degree of dissimilarity elucidated temporal and spatial variability in water column parameters at a range of scales. The advantages of this new statistical method in relation to traditional spatial statistics are discussed. We demonstrated the efficacy of the floating window ANCOVA method by comparing chlorophyll and salinity transect data taken at the North Inlet, SC estuary during flooding and ebbing tides in Winter, Spring, and Summer 1991. Chlorophyll concentrations represented the biological characteristics of the estuarine water column and salinity represented the physical processes affecting that water column. We found total dissimilarity in the magnitude of salinity data from one season to the next at all scales, but inter-seasonal similarity in spatial patterns over both short (hourly) and long (monthly) time scales. We also found a large seasonal dissimilarity in the magnitude of chlorophyll levels, as expected. Spatial patterns in phytoplankton biomass (as chlorophyll concentrations) appeared to be largely controlled by the physical processes represented with the salinity data. Often, we observed greater dissimilarity in biological and physical parameters from one tide to the next [on a given day] than from one season to the next. In these cases, the greatest flood-ebb differences were associated with landscape-level influences - from rivers and the coastal ocean - that varied greatly with direction of tidal flow. We are currently using spatially articulate aquatic transect data and the floating window ANCOVA technique to validate spatial simulation models at different scales. By using this variable-scale statistical technique to determine coherence between the actual transect data and model output from simulations run at different scales, we will test hypotheses about the scale-dependent relationships between data resolution and model predictability in landscape analysis.://A1994NU09400005,Nu094 Times Cited:7 Cited References Count:0 0921-2973ISI:A1994NU09400005fChilders, Dl Natl Marine Fisheries Serv,Se Fishery Sci Ctr,Galveston Lab,4700 Ave U,Galveston,Tx 77551English <7p?Childress, W. M. Rykiel, E. J. Forsythe, W. Li, B. L. Wu, H. I.19968Transition rule complexity in grid-based automata models257-266Landscape Ecology115Tgrid-based models; cellular automata; spatial automata; succession DYNAMICS; PATTERNArticleOct'Grid-based automata models have been widely applied in simulating ecological process and spatial patterns at all spatial scales, In this paper, we present methods for calculating the effects of number of states, size of the neighborhood, means of tallying neighborhood states, and choice of deterministic or stochastic rules on the complexity and tractability of spatial automata models, We use as examples Conway's Game of Life and models for successional dynamics in a mesquite savanna landscape in south Texas, The number of possible neighborhood state configurations largely determines the complexity of automata models. The number of different configurations in Life, a two-state, deterministic, voting-rule model with an eight-cell Moore neighborhood is 18. A similar model for the seven-state savanna system would have 21,021 different neighborhood configurations. For stochastic models, the number of possible state transitions is the number of neighborhood configurations times the number of possible cell states, A stochastic, unique neighbor model for the savanna system with a Moore neighborhood and seven possible states would have 282,475,249 possible neighborhood-based state transitions. Stochastic models with an eight-cell Moore neighborhood are probably most appropriate for ecological applications. The best options for minimizing the complexity of ecological models are using voting rather than unique neighbor transition rules, reducing the number of possible states, and implementing ecologically-based heuristics to simplify the transition rule table.://A1996VR02500003 ISI Document Delivery No.: VR025 Times Cited: 5 Cited Reference Count: 13 Cited References: BARKHAM JP, 1982, J ECOL, V70, P323 GARDNER M, 1970, SCI AM, V223, P120 HANSKI I, 1991, BIOL J LINN SOC, V42, P3 HOGEWEG P, 1988, APPL MATH COMPUT, V27, P81 MOLOFSKY J, 1994, ECOLOGY, V75, P30 PRATT WK, 1991, DIGITAL IMAGE PROCES SCANLAN JC, 1991, J VEG SCI, V2, P625 SILVERTOWN J, 1992, J ECOL, V80, P527 SMITH AR, 1976, AUTOMATA LANGUAGES D, P405 TURNER MG, 1993, LANDSCAPE ECOL, V8, P213 VONTONGEREN O, 1986, VEGETATIO, V65, P163 WISSEL C, 1991, MOSAIC CYCLE CONCEPT, P22 ZHOU GF, 1995, LANDSCAPE ECOL, V10, P177 0921-2973 Landsc. Ecol.ISI:A1996VR02500003HTEXAS A&M UNIV,DEPT IND ENGN,CTR BIOSYST MODELLING,COLLEGE STN,TX 77843.Englishڽ7 mCho, MosesAzong Ramoelo, Abel Debba, Pravesh Mutanga, Onisimo Mathieu, Renaud Deventer, Heidi Ndlovu, Nomzamo2013qAssessing the effects of subtropical forest fragmentation on leaf nitrogen distribution using remote sensing data 1479-1491Landscape Ecology288Springer Netherlands=Subtropical forest fragmentation Leaf nitrogen Remote sensing 2013/10/01+http://dx.doi.org/10.1007/s10980-013-9908-7 0921-2973Landscape Ecol10.1007/s10980-013-9908-7English<7Christensen, P. Hornfeldt, B.2006?Habitat preferences of Clethrionomys rufocanus in boreal sweden185-194Landscape Ecology212habitat patches; habitat quality; immatures; landscape design; local habitat; reproductive females; reproductive males DELAYED DENSITY-DEPENDENCE; LONG-TERM DECLINE; NORTHERN SWEDEN; POPULATION FLUCTUATIONS; VOLES; DYNAMICS; CYCLES; PEAK; ORGANIZATION; LANDSCAPESArticleFebBA long-term decline of vole populations in boreal Sweden, especially of the grey-sided vole (Clethrionomys rufocanus Sund.), has been revealed by snap-trapping in 1971-2004. We identified important habitats for the grey-sided vole by mapping the distribution of cumulated number of reproductive females in 1971-1978, prior to the major decline in the 1980s. Mean abundance of C. rufocanus was higher in the western (inland) than eastern (coastland) part of the study area. As the inland appeared to represent the most, as far as we know, pristine, abundant part of the population, we based identification of high quality habitats on inland data only. Four habitats were more important than others and yielded nearly 86% of the reproductive females in spring: (1) forests of dry, (2) moist and (3) wet/hydric dwarf-shrub type, in addition to (4) forest/swamp complexes rich in dwarf-shrubs. The latter three habitats were used more frequently than expected from their occurrence in the landscape. Still, the variation in density of reproductive females within patches of the same habitat was frequently high. This suggested that habitat composition in the surrounding landscape, perhaps may have affected local vole density at the patch scale. Clear-cut sampling plots appeared to be low-frequently used by reproductive females, but also by males and immatures. In conclusion, our study indicated the importance of also studying habitat at a larger scale than that of the patch to get a deeper understanding on how habitat influences local and regional densities and population dynamics of C. rufocanus.://000235866400003 ISI Document Delivery No.: 019WC Times Cited: 0 Cited Reference Count: 42 Cited References: *MIN INC, 1998, MINITAB REL 12 WIND AHTI T, 1968, ANN BOT FENN, V5, P169 ANDREN H, 1994, OIKOS, V71, P355 ARNBORG T, 1990, VEGETATIO, V90, P1 CHRISTENSEN P, 2003, J MAMMAL, V84, P1292 ECKE F, 2001, ECOLOGICAL B, V49, P165 ECKE F, 2002, J APPL ECOL, V39, P781 ECKE F, 2003, THESIS LULEA U TECHN ENGELMARK O, 1999, SWEDISH PLANT GEOGRA, P55 HAMBACK PA, 1998, J ANIM ECOL, V67, P544 HANSEN TF, 1999, P NATL ACAD SCI USA, V96, P986 HANSKI I, 1993, NATURE, V364, P232 HANSKI I, 1996, J ANIM ECOL, V65, P220 HANSSON L, 1977, LANDSCAPE PLANNING, V4, P85 HANSSON L, 1999, OIKOS, V86, P159 HENTTONEN H, 1992, ANN ZOOL FENN, V29, P1 HENTTONEN H, 2000, POLISH J ECOLOGY S, V48, P87 HORNFELDT B, 1978, OECOLOGIA BERL, V32, P141 HORNFELDT B, 1991, THESIS U UMEA UMEA, P24 HORNFELDT B, 1994, ECOLOGY, V75, P791 HORNFELDT B, 1995, REPORT WORLD WILDLIF, V3, P21 HORNFELDT B, 1998, FAUNA FLORA, V93, P137 HORNFELDT B, 2004, OIKOS, V107, P376 HORNFELDT B, 2005, MILJOOVERVAKNING SMA IMS RA, 1987, OIKOS, V50, P103 IMS RA, 1989, ECOLOGY, V70, P607 JOHANNESEN E, 1999, ANN ZOOL FENN, V36, P215 KANEKO Y, 1998, RES POPUL ECOL, V40, P21 LIDICKER WZ, 1985, ACTA ZOOL FENN, V173, P23 LIDICKER WZ, 1988, J MAMMAL, V69, P225 LIDICKER WZ, 2000, OIKOS, V91, P435 LOFGREN O, 1995, OIKOS, V72, P29 LUNDMARK JE, 1986, SKOGSMARKENS EKOLOGI OKSANEN T, 1999, OIKOS, V86, P463 OKSANEN T, 2001, OIKOS, V94, P101 PULLIAM HR, 1988, AM NAT, V132, P652 SAITOH T, 1997, MAMMAL STUDY, V22, P27 SIIVONEN L, 1968, NORDEUROPAS DAGGDJUR SVENSSON SA, 1980, 30 SWED U AGR SCI DE VANHORNE B, 1983, J WILDLIFE MANAGE, V47, P893 VIITALA J, 1977, ANN ZOOL FENN, V14, P53 WIELGOLASKI FE, 1971, IBP NORDEN 0921-2973 Landsc. Ecol.ISI:000235866400003Umea Univ, Dept Ecol & Environm Sci, SE-90187 Umea, Sweden. Christensen, P, Umea Univ, Dept Ecol & Environm Sci, SE-90187 Umea, Sweden. pernilla.christensen@eg.umu.seEnglishڽ7 GChristianson, David Klaver, RobertW Middleton, Arthur Kauffman, Matthew2013GConfounded winter and spring phenoclimatology on large herbivore ranges427-437Landscape Ecology283Springer NetherlandsXClimate Elk Green-up Normalized difference vegetation index Phenology Snow Spring Winter 2013/03/01+http://dx.doi.org/10.1007/s10980-012-9840-2 0921-2973Landscape Ecol10.1007/s10980-012-9840-2English<7.Chust, G. Pretus, J. L. Ducrot, D. Ventura, D.2004GScale dependency of insect assemblages in response to landscape pattern41-57Landscape Ecology191diptera; fragmentation; homoptera; landscape pattern; remote sensing; scale; spatial indices; species richness SPECIES RICHNESS; SATELLITE IMAGES; SPATIAL SCALES; BIODIVERSITY; FRAGMENTATION; CONSERVATION; DIVERSITY; COMMUNITIES; PERSPECTIVE; GRASSLANDSArticlePatches and their boundaries are sensitive to the scale at which they are viewed. The response of species to patchiness may depend on the resolution and on the extent by which the spatial pattern is perceived. The goal of this paper is to identify the scale at which forest spatial pattern causes changes in species richness and abundances of Dipteran and Homopteran species as a whole, and further on their distinctive ecological functional groups. Using remotely-sensed optical imagery, we described the landscape structure surrounding sampling sites. We used two approaches to deal with the problem of the scale of observation: 1) variation of extent using a multiscale analysis, and 2) comparison of two satellite sensors with different spatial resolutions (SPOT: 20 x 20 m, and Landsat TM: 30 x 30 m). The relationship between entomological data and landscape descriptors at different spatial scales was tested with the Mantel test, redundancy analysis and stepwise multiple linear regression. Relative abundances of Homopteran species were affected by landscape patterns at finer scales than in Diptera. The strength of response to landscape was different for each Dipteran functional group. The multiscale analysis also enabled the optimal scale (6.25 ha) of landscape pattern, accounting for 62% of the variation in Homopteran richness, to be identified. As a practical application, Homopteran richness was mapped by extrapolation of the regression function to the pixels of the image. Multiscale analysis provides an alternative view of fragmentation effects, which are traditionally studied through the patch-based approach, and highlights the importance of scale in ecological processes. The detection of optimal scales and the use of satellite images enable maps of important biotic indicators to be drawn up.://000189394100004 ISI Document Delivery No.: 780RA Times Cited: 4 Cited Reference Count: 52 Cited References: BAWA K, 2002, CONSERV ECOL, V6 BERGIN TM, 2000, LANDSCAPE ECOL, V15, P131 CARDILLO M, 1999, LANDSCAPE ECOL, V14, P423 CASGRAIN P, 2000, R PACKAGE MULTIVARIA CASUCCI F, 1998, P SOC PHOTO-OPT INS, V3499, P332 CHUST G, 2000, BELGIAN J ENTOMOLOGY, V2, P99 CHUST G, 2002, THESIS U P SABATIER CHUST G, 2003, ECOGRAPHY, V26, P257 COLLINGE SK, 2002, LANDSCAPE ECOL, V17, P647 CORNELL HV, 1992, J ANIM ECOL, V61, P1 CUMMING GS, 2000, J BIOGEOGR, V27, P425 DAVIES KF, 2001, ECOLOGY, V82, P1830 DEBOLOS O, 1970, ACTA GEOBOTANICA BAR, V5, P1 DIDHAM RK, 1996, TRENDS ECOL EVOL, V11, P255 ELLIOTT NC, 1998, LANDSCAPE ECOL, V14, P239 FERRAR P, 1987, ENTOMONOGRAPH, V8, P1 GERING JC, 2003, CONSERV BIOL, V17, P488 GULINCK H, 2000, INT J REMOTE SENS, V21, P2541 HARALICK RM, 1973, IEEE T SMC, V3, P610 JENNINGS MD, 2000, LANDSCAPE ECOL, V15, P5 JONSEN ID, 1997, LANDSCAPE ECOL, V12, P185 JORGENSEN AF, 1996, INT J REMOTE SENS, V17, P91 KOLASA J, 1998, ECOLOGICAL SCALE THE LAUGA J, 1992, LANDSCAPE ECOL, V6, P183 LAURANCE WF, 2002, CONSERV BIOL, V16, P605 LEGENDRE P, 1998, NUMERICAL ECOLOGY LILLESAND TM, 2000, REMOTE SENSING IMAGE LUOTO M, 2002, LANDSCAPE ECOL, V17, P195 MAGURA T, 2001, J BIOGEOGR, V28, P129 MEDAIL F, 1997, ANN MO BOT GARD, V84, P112 MYERS N, 2000, NATURE, V403, P853 ORMSBY JP, 1987, PHOTOGRAMM ENG REM S, V53, P1081 OZANNE CMP, 1997, CANOPY ARTHROPODS, P534 PAPP L, 1997, CONTRIBUTION MANUAL, V2 PAPP L, 1998, CONTRIBUTION MANUAL, V3 PAPP L, 2000, CONTRIBUTION MANUAL PEARMAN PB, 2002, ECOL MONOGR, V72, P19 PEREIRA JMC, 1991, PHOTOGRAMM ENG REM S, V57, P1475 ROLAND J, 1997, NATURE, V386, P710 RUSEK J, 1992, LANDSCAPE BOUNDARIES SAVERAID EH, 2001, LANDSCAPE ECOL, V16, P71 STEFFANDEWENTER I, 2002, BIOL CONSERV, V104, P275 STOMS DM, 1993, INT J REMOTE SENS, V14, P1839 STOMS DM, 2000, LANDSCAPE ECOL, V15, P21 TERBRAAK CJF, 1998, CANOCO REFERENCE MAN TURNER W, 2001, CONSERV BIOL, V15, P832 WHITTAKER RJ, 2001, J BIOGEOGR, V28, P453 WIENS JA, 1989, FUNCT ECOL, V3, P385 WIENS JA, 1989, LANDSCAPE ECOLOGY, V3, P87 WIENS JA, 1992, ECOLOGICAL STUDIES ZAR JH, 1996, BIOSTATISTICAL ANAL ZSCHOKKE S, 2000, OECOLOGIA, V125, P559 0921-2973 Landsc. Ecol.ISI:000189394100004.Univ Barcelona, Fac Biol, Dept Ecol, E-08028 Barcelona, Spain. CNRS, IRD,UPS, CNES, Ctr Space Studies Biosphere, F-31055 Toulouse, France. Univ Barcelona, Fac Biol, Dept Zool, E-08028 Barcelona, Spain. Chust, G, Univ Barcelona, Fac Biol, Dept Ecol, Diagonal 645, E-08028 Barcelona, Spain. chust@cict.frEnglish7?? Chytrý, Milan2012^N. Jürgens, U. Schmiedel and M. T. Hoffman (eds): Biodiversity in Southern Africa, Vols 1–3465-466Landscape Ecology273Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-011-9678-z 0921-297310.1007/s10980-011-9678-z|?1Cilliers, S. S. Williams, N. S. G. Barnard, F. J.2008]Patterns of exotic plant invasions in fragmented urban and rural grasslands across continents 1243-1256Landscape Ecology2310Linear native grassland remnants in fragmented landscapes are usually at a great risk of exotic species invasion from their edges. Changes in species distribution near habitat edges are extensively studied in ecology as knowledge about edge responses is important to understand the development of patterns and processes in landscapes. However, elucidating robust general principles for edge effects has been difficult as species responses to habitat edges are highly variable and dependent on a large number of attributes which affect the function and structure of edges and therefore the distance that edge effects penetrate into fragmented natural vegetation. The objective of this study was to investigate the generality of exotic species invasion patterns from edges in native grassland patches surrounded by urban and rural landscapes. This was done by comparing the results of research from Victoria, Australia with a similar study from North-West Province, South Africa. Despite their occurrence on different continents, the grasslands are floristically and structurally similar and are dominated by the same grass species. Invasion patterns were quantified using two spatial statistics methods; block kriging and spatially constrained clustering. Two distinct patterns of exotic species invasion were identified in native grassland remnants in South Africa and Australia, namely exotic species invasion from the edge where the cover of exotic species increased with increasing proximity to the edge and a pattern that suggests that gap phase vegetation dynamics may also drive exotic species invasion at urban grasslands. Although urbanization and weed invasions are complex processes similar patterns of exotic species invasion in urban grasslands were found in two different continents suggesting that general patterns may occur. Implications of this for the conservation of native grasslands in contrasting landscapes are discussed.!://WOS:000261790600009Times Cited: 0 0921-2973WOS:00026179060000910.1007/s10980-008-9295-7<78Claessens, L. Verburg, P. H. Schoorl, J. M. Veldkamp, A.2006Contribution of topographically based landslide hazard modelling to the analysis of the spatial distribution and ecology of kauri (Agathis australis)63-76Landscape Ecology211"vegetation pattern; DEM; shallow landslides; logistic regression; stand replacement model; Agathis australis (kauri); Waitakere Ranges; New Zealand DIGITAL ELEVATION MODELS; NEW-ZEALAND; LOGISTIC-REGRESSION; LAND-USE; SOLAR-RADIATION; PUERTO-RICO; VEGETATION; FOREST; DISTURBANCE; LANDSCAPEArticleJanIn this paper the use of topographical attributes for the analysis of the spatial distribution and ecological cycle of kauri (Agathis australis), a canopy emergent conifer tree from northern New Zealand, is studied. Several primary and secondary topographical attributes are derived from a Digital Elevation Model (DEM) for a study area in the Waitakere Ranges. The contribution of these variables in explaining presence or absence of mature kauri is assessed with logistic regression and Receiver Operating Characteristic (ROC) plots. A topographically based landslide hazard index, calculated by combining a steady state hydrologic model with the infinite slope stability equation, appears to be very useful in explaining the occurrence and ecological dynamics of kauri. It is shown that the combination of topographical, soil physical and hydrological parameters in the calculation of this single landslide hazard index, performs better in explaining presence of mature kauri than using topographical attributes calculated from the DEM alone. Moreover, this study demonstrates the possibilities of using terrain attributes for representing geomorphological processes and disturbance mechanisms, often indispensable in explaining a species' ecological cycle. The results of this analysis support the 'temporal stand replacement model', involving disturbance as a dominant ecological process in forest regeneration, as an interpretation of the community dynamics of kauri. Furthermore a threshold maturity stage, in which trees become able to stabilize landslide prone sites and postpone a possible disturbance, together with great longevity are seen as major factors making kauri a 'landscape engineer'.://000235887300006 ISI Document Delivery No.: 020DD Times Cited: 0 Cited Reference Count: 75 Cited References: *AUCKL REG COUNC, 2002, 171 TP ARC *ESRI, 1999, ARCVIEW GIS VERS 3 2 *FAO, 2001, 94 FAO AGRESTI A, 2002, CATEGORICAL DATA ANA AHMED M, 1987, NEW ZEAL J BOT, V25, P217 ANSELIN W, 1988, SPATIAL ECONOMETRICS ASPINALL RJ, 2002, ECOL MODEL, V157, P301 AUSTIN MP, 1985, ANNU REV ECOL SYST, V16, P39 BELL KP, 2000, REV ECON STAT, V82, P72 BOCKSTAEL NE, 1996, AM J AGR ECON, V78, P1168 BONAN GB, 1989, ANNU REV ECOL SYST, V20, P1 BROWN DG, 1994, J VEG SCI, V5, P641 BURNS BR, 1996, NEW ZEAL J BOT, V34, P79 BURROWS C, 1990, PROCESSES VEGETATION BUTLER DR, 1994, PHYSICAL GEOGR, V15, P181 CLAESSENS L, 2005, IN PRESS GEOMORPHOLO CLARK JS, 1991, ECOLOGY, V72, P1102 DAVIS FW, 1990, LANDSCAPE ECOL, V4, P69 DELBARRIO G, 1997, LANDSCAPE ECOL, V12, P95 DENYER K, 1993, WAITAKERE ECOLOGICAL DUAN J, 2000, ANAL PRINCIPLES APPL, P311 DUBAYAH R, 1995, INT J GEOGR INF SYST, V9, P405 ECROYD CE, 1982, NEW ZEAL J BOT, V20, P17 ENRIGHT NJ, 1995, ECOLOGY SO CONIFERS, P271 ENRIGHT NJ, 1999, J VEG SCI, V10, P793 ENRIGHT NJ, 2001, AUSTRAL ECOL, V26, P618 FIELDING AH, 1997, ENVIRON CONSERV, V24, P38 FLORINSKY IV, 1996, CATENA, V27, P123 FLORINSKY IV, 1998, INT J GEOGR INF SCI, V12, P47 FRANKLIN J, 1998, J VEG SCI, V9, P733 GARDNER RO, 1981, TANE, V27, P196 GUARIGUATA MR, 1990, J ECOL, V78, P814 GUISAN A, 2000, ECOL MODEL, V135, P147 HAYWARD BW, 1976, NZ J GEOLOGY GEOPHYS, V19, P871 HORSCH B, 2003, ECOL MODEL, V168, P267 JESSOP R, 1992, THESIS U AUCKLAND NZ KIRKPATRICK JB, 1980, J BIOGEOGR, V7, P197 KRAMER MG, 2001, ECOLOGY, V82, P2749 KULAKOWSKI D, 2002, J ECOL, V90, P806 KUMAR L, 1997, INT J GEOGR INF SCI, V11, P475 MACKEY BG, 2000, ANAL PRINCIPLES APPL, P391 MANEL S, 1999, ECOL MODEL, V120, P337 MANEL S, 2001, J APPL ECOL, V38, P921 MENARD S, 2001, SAGE U PAPERS SERIES METZ CE, 1978, SEMIN NUCL MED, V8, P283 MONTGOMERY DR, 1994, WATER RESOUR RES, V30, P1153 MOORE ID, 1991, HYDROL PROCESS, V5, P3 MOORE ID, 1993, ENV MODELING GIS, P196 MOORE ID, 1993, J HYDROL, V150, P717 MYSTER RW, 1997, LANDSCAPE ECOL, V12, P299 NETER J, 1996, APPL LINEAR STAT MOD OCALLAGHAN JF, 1984, COMPUT VISION GRAPH, V28, P323 OGDEN J, 1985, NEW ZEAL J BOT, V23, P751 OGDEN J, 1995, ECOLOGY SO CONIFERS, P81 OVERMARS KP, 2003, ECOL MODEL, V164, P257 PACK RT, 2001, 15 ANN GIS C GIS 200 PEARCE J, 2000, ECOL MODEL, V133, P225 PFEFFER K, 2003, LANDSCAPE ECOL, V18, P759 PINDER JE, 1997, PLANT ECOL, V131, P17 PONTIUS RG, 2001, AGR ECOSYST ENVIRON, V85, P239 QUINN P, 1991, HYDROL PROCESS, V5, P59 RESTREPO C, 2003, PLANT ECOL, V166, P131 SCHOORL JM, 2000, EARTH SURF PROC LAND, V25, P1025 SEGAL M, 1985, AGR FOREST METEOROL, V36, P19 STAAL SJ, 2002, AGR ECON, V27, P295 SWANSON FJ, 1988, BIOSCIENCE, V38, P92 SWETS JA, 1988, SCIENCE, V240, P1285 TANG SM, 1997, LANDSCAPE ECOL, V12, P349 TAPPEINER U, 1998, ECOL MODEL, V113, P225 TURNER MG, 1990, LANDSCAPE ECOLOGY, P323 VERBURG PH, 2004, ENVIRON PLANN B, V31, P125 WALKER LR, 1996, BIOTROPICA A, V28, P566 WARDLE P, 1991, VEGETATION NZ WHITE PS, 1985, ECOLOGY NATURAL DIST, P3 WILSON JP, 2000, TERRAIN ANAL PRINCIP 0921-2973 Landsc. Ecol.ISI:000235887300006Univ Wageningen & Res Ctr, Lab Soil Sci & Geol, NL-6700 AA Wageningen, Netherlands. Claessens, L, Univ Wageningen & Res Ctr, Lab Soil Sci & Geol, POB 37, NL-6700 AA Wageningen, Netherlands. l.claessens@cgiar.orgEnglish m<7<Clark, F. S. Slusher, R. B.2000xUsing spatial analysis to drive reserve design: a case study of a national wildlife refuge in Indiana and Illinois (USA)75-84Landscape Ecology151C-Plan conservation biology gap analysis geographic information system landscape ecology national wildlife refuge reserve design DIVERSITYArticleJanOur refuge design strategy involves a landscape approach formulated to complement existing management efforts and employ restoration in the heavily degraded Kankakee River watershed in northeastern Indiana and northwestern Illinois. The watershed historically contained an approximately 400,000 ha wetland (Grand Marsh), a diverse riverine system, oak savanna, and prairie. Today only fragments of these habitats remain. The U.S. Fish and Wildlife Service developed a preliminary project proposal (PPP) during the summer of 1996 to protect and restore habitat within the watershed by establishing the Grand Kankakee Marsh National Wildlife Refuge. The Indiana and Illinois Gap Analysis projects provided the resources to move beyond the expert workshop approach to a data-driven method for initial reserve design. Using visual analysis of various Gap Analysis data layers, we established 'Focus Areas' that formed the basis for the Environmental Assessment and the Economic Impact Study required under the National Environmental Policy Act (NEPA). We have initiated Phase II of the reserve design analysis using preliminary results of the Indiana Gap Analysis project and C-Plan software in conjunction with the New South Wales National Parks and Wildlife Service.://000083830400007 ISI Document Delivery No.: 258GN Times Cited: 7 Cited Reference Count: 21 Cited References: *IND DEP NAT RES D, 1990, WAT RES AV KANK RIV *TNC, 1997, UNPUB FAIR OAKS FARM *US FISH WILDL SER, 1998, DIV REALT GUID LAND BETZ RF, 1978, P 5 MIDW PRAIR C IOW, P25 CLARK FS, 1998, DRAFT ENV ASSESSMENT CSUTI B, 1997, BIOL CONSERV, V80, P83 DAHL TE, 1990, WETLANDS LOSSES US 1 JOHNSON DA, 1995, INTERNET RES, V5, P46 LEACH MK, 1995, MIDW OAK SAV WOODL E MAUSEL PW, 1998, UNPUB IDENTIFICATION MEYER A, 1936, ARTS LETT, V21 NOSS RF, 1983, BIOSCIENCE, V33, P700 NOSS RF, 1986, ENVIRON MANAGE, V10, P299 NUZZO VA, 1986, NAT AREA J, V6, P6 PACKARD S, 1997, TALLGRASS RESTORATIO PRESSEY RL, IN PRESS PRIORITY CO PRESSEY RL, 1994, BIODIVERS CONSERV, V3, P242 PRESSEY RL, 1995, NATURE CONSERVATION, V4, P23 PRESSEY RL, 1998, ECOLOGY EVERYONE COM, P73 SHIVELY G, 1998, DRAFT ENV ASSESSMENT SOULE ME, 1986, BIOL CONSERV, V35, P19 0921-2973 Landsc. Ecol.ISI:000083830400007US Fish & Wildlife Serv, Bloomington Field Off, Bloomington, IN 47403 USA. Clark, FS, US Fish & Wildlife Serv, Bloomington Field Off, 620 S Walker St, Bloomington, IN 47403 USA.Englishڽ72 Clark, KyleH Nicholas, KimberlyA2013tIntroducing urban food forestry: a multifunctional approach to increase food security and provide ecosystem services 1649-1669Landscape Ecology289Springer NetherlandscUrban agriculture Urban forestry Sustainability science Edible landscaping Agroforestry Agroecology 2013/11/01+http://dx.doi.org/10.1007/s10980-013-9903-z 0921-2973Landscape Ecol10.1007/s10980-013-9903-zEnglish<7]Cleary, D. F. R. Genner, M. J. Boyle, T. J. B. Setyawati, T. Angraeti, C. D. Menken, S. B. J.2005~Associations of bird species richness and community composition with local and landscape-scale environmental factors in Borneo989-1001Landscape Ecology208Akaike's information criterion (AIC); community similarity; habitat heterogeneity; habitat structure; Indonesia; Kalimantan; logging; topography SPATIAL SCALE; RAIN-FOREST; DIVERSITY; PATTERNS; AREAS; ECOLOGY; DISTURBANCE; RESPONSESArticleDecA comprehensive understanding of variables associated with spatial differences in community composition is essential to explain and predict biodiversity over landscape scales. In this study, spatial patterns of bird diversity in Central Kalimantan, Indonesia, were examined and associated with local-scale (habitat structure and heterogeneity) and landscape-scale (logging, slope position and elevation) environmental variables. Within the study area (c. 196 km(2)) local habitat structure and heterogeneity varied considerably, largely due to logging. In total 9747 individuals of 177 bird species were recorded. Akaike's information criterion (AIC) revealed that the best explanatory models of bird community similarity and species richness included both local- and landscape-scale environmental variables. Important local-scale variables included liana abundance, fern cover, sapling density, tree density, dead wood abundance and tree architecture, while important landscape-scale variables were elevation, logging and slope position. Geographic distance between sampling sites was not significantly associated with spatial variation in either species richness or similarity. These results indicate that deterministic environmental processes, as opposed to dispersal-driven stochastic processes, primarily structure bird assemblages within the spatial scale of this study and confirm that highly variable local habitat measures can be effective means of predicting landscape-scale community patterns.://000233036400007 ISI Document Delivery No.: 980RR Times Cited: 2 Cited Reference Count: 41 Cited References: ANGGRAINI K, 2000, BIRD CONSERV INT, V10, P189 ASDAK C, 1998, J HYDROL, V206, P237 BECK J, 2002, J TROP ECOL 1, V18, P33 BORCARD D, 1992, ECOLOGY, V73, P1045 BRAY JR, 1957, ECOL MONOGR, V27, P325 BURNHAM KP, 2002, MODEL SELECTION MULT CANNON CH, 1998, SCIENCE, V281, P1366 CHAPPELL NA, 2001, PLANT ECOL, V153, P215 CLARKE KR, 2001, PRIMER V5 USER MANUA CLERGEAU P, 2001, J APPL ECOL, V38, P1122 COLLAR NJ, 2001, THREATENED BIRDS ASI CONDIT R, 2000, SCIENCE, V288, P1414 CURRAN LM, 2004, SCIENCE, V303, P1000 DINIZ JAF, 2003, GLOBAL ECOL BIOGEOGR, V12, P53 DRAPEAU P, 2000, ECOL MONOGR, V70, P423 DUFRENE M, 1997, ECOL MONOGR, V67, P345 DUFRENE M, 1998, INDVAL 2 0 PROGRAMME GOTELLI NJ, 2001, ECOSIM NULL MODELS S HARMS KE, 2001, J ECOL, V89, P947 HERRANDO S, 2002, ECOGRAPHY, V25, P161 JOHNS AD, 1992, PHILOS T ROY SOC B, V335, P437 JOHNSON DDP, 1998, P ROY SOC LOND B BIO, V265, P951 LIU AZ, 2001, ACTA BOT SIN, V43, P319 MACFADEN SW, 2002, FOREST SCI, V48, P243 MALCOLM JR, 2000, CONSERV BIOL, V14, P1623 MCCULLAGH P, 1989, GEN LINEAR MODELS MUELLERDOMBOIS D, 1974, AIMS METHODS VEGETAT PEARMAN PB, 2002, ECOL MONOGR, V72, P19 PERES C, 1999, TRENDS ECOL EVOL, V14, P217 POTTS MD, 2002, ECOLOGY, V83, P2782 ROBINSON WD, 2000, ECOL MONOGR, V70, P209 SCHMIEGELOW FKA, 1997, ECOLOGY, V78, P1914 SCHNITZER SA, 2002, TRENDS ECOL EVOL, V17, P223 SEOANE J, 2004, ECOL MODEL, V171, P209 SVENNING JC, 1999, J ECOL, V87, P55 TERBORGH J, 1990, ECOL MONOGR, V60, P213 THIOLLAY JM, 2002, J TROP ECOL 4, V18, P471 TUOMISTO H, 2003, SCIENCE, V299, P241 VANCLAY JK, 1997, FOREST ECOL MANAG, V94, P149 WARDELLJOHNSON G, 2000, FOREST ECOL MANAG, V131, P1 WILLIAMS SE, 2002, ECOLOGY, V83, P1317 0921-2973 Landsc. Ecol.ISI:000233036400007Univ Amsterdam, Inst Biodivers & Ecosyst Dynam, NL-1090 GT Amsterdam, Netherlands. Natl Museum Nat Hist, NL-2300 RA Leiden, Netherlands. Univ Hull, Dept Biol Sci, Kingston Upon Hull HU6 7RX, N Humberside, England. UN, Dev Program, GEF Unit, New York, NY 10017 USA. Univ Melbourne, Inst Land & Food Resources, Parkville, Vic 3010, Australia. Conservat Int Indonesia, Jakarta 12540, Indonesia. Cleary, DFR, Univ Amsterdam, Inst Biodivers & Ecosyst Dynam, POB 94766, NL-1090 GT Amsterdam, Netherlands. cleary@science.uva.nlEnglish<7Cleland, D. T. Crow, T. R. Saunders, S. C. Dickmann, D. I. Maclean, A. L. Jordan, J. K. Watson, R. L. Sloan, A. M. Brosofske, K. D.2004cCharacterizing historical and modern fire regimes in Michigan (USA): A landscape ecosystem approach311-325Landscape Ecology193fire regimes; fire risk; natural disturbance; landscape ecosystems; ecological units SOUTHERN BOREAL FOREST; NORTHWESTERN MINNESOTA; HETEROGENEOUS LANDSCAPES; CATASTROPHIC DISTURBANCE; PRESETTLEMENT FORESTS; NORTHERN HARDWOOD; UPPER-PENINSULA; CLIMATE CHANGE; SPRUCE FOREST; VEGETATIONArticleWe studied the relationships of landscape ecosystems to historical and contemporary fire regimes across 4.3 million hectares in northern lower Michigan (USA). Changes in fire regimes were documented by comparing historical fire rotations in different landscape ecosystems to those occurring between 1985 and 2000. Previously published data and a synthesis of the literature were used to identify six forest-replacement fire regime categories with fire rotations ranging from very short (< 100 years) to very long (> 1,000 years). We derived spatially-explicit estimates of the susceptibility of landscape ecosystems to fire disturbance using Landtype Association maps as initial units of investigation. Each Landtype Association polygon was assigned to a fire regime category based on associations of ecological factors known to influence fire regimes. Spatial statistics were used to interpolate fire points recorded by the General Land Office. Historical fire rotations were determined by calculating the area burned for each category of fire regime and dividing this area by fifteen (years) to estimate area burned per annum. Modern fire rotations were estimated using data on fire location and size obtained from federal and state agencies. Landtype Associations networked into fire regime categories exhibited differences in both historical and modern fire rotations. Historical rotations varied by 23-fold across all fire rotation categories, and modern forest fire rotations by 13-fold. Modern fire rotations were an order of magnitude longer than historical rotations. The magnitude of these changes has important implications for forest health and understanding of ecological processes in most of the fire rotation categories that we identified.://000221878900006 ISI Document Delivery No.: 827DL Times Cited: 6 Cited Reference Count: 69 Cited References: AGEE JK, 1993, FIRE ECOLOGY PACIFIC ALBERT DA, 1996, UNPUB LANDTYPE ASS N ARNO SF, 1977, INT42 USDA FOR SERV ARNO SF, 1983, INT301 USDA FOR SERV ATTIWILL PM, 1994, FOREST ECOL MANAG, V63, P247 BAKER WL, 1989, CAN J FOREST RES, V19, P700 BERGERON Y, 1991, ECOLOGY, V72, P1980 BERGERON Y, 1993, J VEG SCI, V4, P827 BERGERON Y, 1999, FOREST CHRON, V75, P49 BORMANN FH, 1979, AM SCI, V67, P660 BROWN PM, 2001, ECOSCIENCE, V8, P115 BRUBAKER LB, 1975, QUATERNARY RES, V5, P499 CANHAM CD, 1984, ECOLOGY, V65, P803 CARDILLE JA, 2001, ECOL APPL, V11, P111 CHANDLER C, 1983, FIRE FORESTRY, V1 CHRISTENSEN NL, 1993, FIRE ENV ECOLOGICAL, P234 CISSEL JH, 1999, ECOL APPL, V9, P1217 CLARK JS, 1988, NATURE, V334, P233 CLARK JS, 1988, QUATERNARY RES, V30, P81 CLARK JS, 1990, CAN J FOREST RES, V20, P219 CLELAND DT, 1997, ECOSYSTEM MANAGEMENT, P181 CLEMENTS FE, 1910, US FOREST SERVICE B, V79 COMER PJ, 1995, MICHIGANS NATIVE LAN CORNER RA, 1999, 199902 NO LOW MICH E CWYNAR LC, 1978, CAN J BOT, V56, P10 DANSEREAU PR, 1993, CAN J FOREST RES, V23, P25 DAVIS MB, 1993, LARGE SCALE ECOLOGY, P19 ENGSTROM RT, 1999, ECOLOGICAL STEWARDSH, V2, P313 FRELICH LE, 1991, ECOL MONOGR, V61, P159 FRISSELL SS, 1973, QUATERNARY RES, V3, P397 GOSZ JR, 1992, ECOL APPL, V2, P248 GRIMM EC, 1984, ECOL MONOGR, V54, P291 HEINSELMAN ML, 1973, QUATERNARY RES, V3, P329 HEINSELMAN ML, 1981, FIRE REGIMES ECOSYST HENRY JD, 1974, ECOLOGY, V55, P772 HOST GE, 1987, FOREST SCI, V33, P445 HUNTER ML, 1993, BIOL CONSERV, V65, P115 JOHNSON EA, 1994, ADV ECOL RES, V25, P239 JORDAN JK, 2002, P LAND TYP ASS C DEV KIMBALL AJ, 1995, B TORREY BOT CLUB, V122, P115 LANDRES PB, 1999, ECOL APPL, V9, P1179 LARSEN CPS, 1998, ECOLOGY, V79, P106 LARSEN CPS, 1998, J ECOL, V86, P815 LOOPE WL, 1991, CAN FIELD NAT, V105, P18 MACLEAN AL, 2003, FIRE FUEL TREATMENTS, P289 MANIES KL, 2001, CANADIAN J FOREST RE, V17 MITCHELL JA, 1929, FOREST FIRES MICHIGA MITCHELL JA, 1952, FOREST FIRES FOREST MOTZKIN G, 1999, J VEG SCI, V10, P903 NOWACKI GJ, 1998, PNWGTR421 USDA FOR S PLUMMER FG, 1912, GOVT PRINT OFF B, V117 ROWE JS, 1980, FOREST CHRON, V56, P19 ROWE JS, 1984, FOREST LAND CLASSIFI, P132 ROWE JS, 1992, FOREST CHRON, V68, P222 SCHMIDT KM, 2002, RMRS87 USDA FOR SERV SIMARD AJ, 1982, FIRE HIST MICHIGAN J, P59 SOUSA WP, 1984, ANNU REV ECOL SYST, V15, P353 SPIES TA, 1985, CAN J FOREST RES, V15, P949 SPURR SH, 1954, ECOLOGY, V35, P21 STEARNS FW, 1949, ECOLOGY, V30, P350 SWAIN AM, 1973, QUATERNARY RES, V3, P383 SWAIN AM, 1978, QUATERNARY RES, V10, P55 SWAIN AM, 1980, ECOLOGY, V61, P747 SWETNAM TW, 1999, ECOL APPL, V9, P1189 TURNER MG, 1989, OIKOS, V55, P121 TURNER MG, 1994, LANDSCAPE ECOL, V9, P59 VANWAGNER CE, 1978, CANADIAN J FOREST RE, V8, P220 WHITNEY GG, 1986, ECOLOGY, V67, P1548 ZHANG QF, 1999, CAN J FOREST RES, V29, P106 0921-2973 Landsc. Ecol.ISI:000221878900006US Forest Serv, USDA, Eastern Reg Off, Rhinelander, WI 54501 USA. US Forest Serv, USDA, So Res Stn, Rhinelander, WI 54501 USA. US Forest Serv, USDA, N Cent Res Stn, Grand Rapids, MN 55744 USA. Michigan Technol Univ, Sch Forest Resources & Environm Sci, Houghton, MI 49931 USA. Michigan State Univ, Dept Forestry, E Lansing, MI 48824 USA. Exosol Consultants, Tustin, MI 49688 USA. Cleland, DT, US Forest Serv, USDA, Eastern Reg Off, Rhinelander, WI 54501 USA. dcleland@fs.fed.usEnglish <7@ ZCobben, M. M. P. Verboom, J. Opdam, P. F. M. Hoekstra, R. F. Jochem, R. Smulders, M. J. M.2012Landscape prerequisites for the survival of a modelled metapopulation and its neutral genetic diversity are affected by climate change227-237Landscape Ecology272climate change metapopulation neutral genetic diversity landscape structure simulation model frog rana-arvalis population biodiversity differentiation implementation connectivity adaptation divergence migration responsesFeb(In response to climate change a species may move, adapt, or go extinct. For the adaptability of a population its genetic diversity is essential, but climate change-induced range shifts can cause a loss of genetic diversity. We investigated how landscape structure affects the level and distribution of genetic diversity in metapopulations subject to climate change-induced range shifts. For this we used the spatially explicit, individual-based model METAPHOR which simulates metapopulation demography and genetics under different temperature increase scenarios. The results indicated that increasing total habitat area may enhance the maintenance of the genetic diversity in metapopulations while they are shifting their range under climate change. However, the results also showed that a high level of total habitat area did not prevent the populations in the newly colonised habitat area of being depleted of much of the original genetic diversity. We therefore conclude that enhancing landscape connectivity may lead to a delayed loss of genetic diversity in metapopulations under climate change, but that additional measures would be necessary to ensure its long-term conservation. Importantly, our simulations also show that a landscape which could be regarded as well-structured under stable climatic conditions, may be inferior for the conservation of genetic diversity during a range shift. This is important information for landscape management when developing strategies for the in situ conservation of genetic variation in natural populations under climate change.://0003000887000079Sp. Iss. SI 889QQ Times Cited:1 Cited References Count:38 0921-2973Landscape EcolISI:000300088700007Cobben, MMP Wageningen UR, Plant Res Int, POB 16, NL-6700 AA Wageningen, Netherlands Wageningen UR, Plant Res Int, POB 16, NL-6700 AA Wageningen, Netherlands Wageningen UR, Plant Res Int, NL-6700 AA Wageningen, Netherlands Wageningen UR, Alterra, NL-6700 AA Wageningen, Netherlands Wageningen UR, Land Use Planning Grp, NL-6700 AA Wageningen, Netherlands Wageningen UR, Genet Lab, NL-6700 AH Wageningen, NetherlandsDOI 10.1007/s10980-011-9676-1English?Coffin, D.P. W.K. Lauenroth1989QDisturbances and gap dynamics in a semiarid grassland: A landscape-level approach19-27Landscape Ecology31Hgap dynamics, grassland, disturbance, succession, blue grama, simulationWe developed a spatially-explicit gap dynamics simulation model to evaluate the effects of disturbances at the scale of a landscape for a semiarid grassland in northcentral Colorado, USA. The model simulates the establishment, growth, and death of individual plants on a small plot through time at an annual time step. Long-term successional dynamics on individual plots (single gaps) and on a landscape composed of a grid of plots were evaluated. Landscapes were simulated as either a collection of independent plots or as a collection of interacting plots where processes on one plot were influenced by processes on adjacent plots. Because we were interested in the recovery of the dominant plant species, the perennial grass blue grama (Bouteloua gracilis (H.B.K.) Lag. ex Griffiths) after disturbances, we focused on scale-dependent processes, such as seed dispersal, that are important to the recruitment of individuals of B. gracilis. The type of simulated landscape was important to the recovery time of B. gracilis after a disturbance. Landscapes composed of independent plots recovered more rapidly following a disturbance than landscapes composed of interacting plots in which the recoyery time was dependent on the spatial scale of the disturbance.|?BColgan, Charles Hunter, Malcolm L. McGill, Brian Weiskittel, Aaron2014ZManaging the middle ground: forests in the transition zone between cities and remote areas 1133-1143Landscape Ecology297AugRIn many parts of the world there are extensive landscapes where forests and people strongly intermingle, notably in the suburbs and exurbs of cities. This landscape of transitional forest generally receives limited attention from policy makers and researchers who tend to be rooted in traditions centered on either urban planning or management of natural resources in rural areas. The transitional forest is on the periphery of both perspectives, but it is a large area that provides numerous important values (biodiversity, ecosystem function, forest products, and amenities) to the people that live in them and their neighboring cities. Here we argue for increased attention to transitional forests, identify major challenges, and suggest changes to planning and management practices needed to ensure that the values of these forests are sustained.!://WOS:000339831300004Times Cited: 0 0921-2973WOS:00033983130000410.1007/s10980-014-0054-7<7Collinge, S. K. Johnson, W. C. Ray, C. Matchett, R. Grensten, J. Cully, J. F. Gage, K. L. Kosoy, M. Y. Loye, J. E. Martin, A. P.2005gLandscape structure and plague occurrence in black-tailed prairie dogs on grasslands of the western USA941-955Landscape Ecology208Colorado; disease; grasslands; habitat fragmentation; landscape context; Montana; plague; prairie dogs; rodents; urbanization BUTTERFLY DIVERSITY; SYLVATIC PLAGUE; CONSERVATION; FRAGMENTATION; BIODIVERSITY; HABITAT; LUDOVICIANUS; PATTERNS; COLONIES; WILDLIFEArticleDecXLandscape structure influences the abundance and distribution of many species, including pathogens that cause infectious diseases. Black-tailed prairie dogs in the western USA have declined precipitously over the past 100 years, most recently due to grassland conversion and their susceptibility to sylvatic plague. We assembled and analyzed two long-term data sets on plague occurrence in black-tailed prairie dogs to explore the hypotheses that plague occurrence is associated with colony characteristics and landscape context. Our two study areas (Boulder County, Colorado, and Phillips County, Montana) differed markedly in degree of urbanization and other landscape characteristics. In both study areas, we found associations between plague occurrence and landscape and colony characteristics such as the amount of roads, streams and lakes surrounding a prairie dog colony, the area covered by the colony and its neighbors, and the distance to the nearest plague-positive colony. Logistic regression models were similar between the two study areas, with the best models predicting positive effects of proximity to plague-positive colonies and negative effects of road, stream and lake cover on plague occurrence. Taken together, these results suggest that roads, streams and lakes may serve as barriers to plague in black-tailed prairie dog colonies by affecting movement of or habitat quality for plague hosts or for fleas that serve as vectors for the pathogen. The similarity in plague correlates between urban and rural study areas suggests that the correlates of plague are not altered by uniquely urban stressors.://000233036400004 OISI Document Delivery No.: 980RR Times Cited: 1 Cited Reference Count: 45 Cited References: *CIT BOULD OP SPAC, 1996, BLACK TAIL PRAIR DOG *ENV SYST RES I, 2002, ARCINFO VERS 8 3 *SAS I INC, 2001, SAS VERS 8 2 *US BUR CENS, 2000, STAT ABSTR US ALLAN BF, 2003, CONSERV BIOL, V17, P267 ANDERSON DR, 2001, WILDLIFE SOC B, V29, P311 ANDERSON DR, 2002, J WILDLIFE MANAGE, V66, P912 ANDERSON SH, 1997, J WILDLIFE DIS, V33, P720 ANTOLIN MF, 2002, T N AM WILDL NAT RES, P104 BARNES AM, 1982, ANIMAL DIS RELATION, P237 BENNETT AF, 1994, BIOL CONSERV, V68, P155 BENNETT BC, 1997, THESIS U COLORADO BO BLAIR RB, 1997, BIOL CONSERV, V80, P113 BOCK CE, 2002, CONSERV BIOL, V16, P1653 BURNHAM KP, 2002, MODEL SELECTION INFE CHAPIN FS, 2000, NATURE, V405, P234 COLLINGE SK, 2000, ECOLOGY, V81, P2211 COLLINGE SK, 2001, BIOL CONSERV, V100, P1 COLLINGE SK, 2003, CONSERV BIOL, V17, P178 CULLY JF, 1997, J MAMMAL, V78, P146 CULLY JF, 2001, J MAMMAL, V82, P894 GAGE KL, 1995, J MAMMAL, V76, P695 GOBER P, 2000, FED REGISTER, V65, P5476 HARRISON S, 1999, ECOGRAPHY, V22, P225 HOOGLAND JL, 1995, BLACK TAILED PRAIRIE HUBBARD CE, 1947, FLEAS W N AM JOHNSON WC, 2004, BIOL CONSERV, V115, P487 KNOWLES CJ, 1985, PRAIRIE NAT, V17, P33 KNOWLES CJ, 2002, GREAT PLAINS RES, V12, P219 LANGLOIS JP, 2001, LANDSCAPE ECOL, V16, P255 LAPOLLA VN, 1993, LANDSCAPE ECOL, V8, P25 LIDICKER WZ, 1996, METAPOPULATIONS WILD, P85 LOMOLINO MV, 2001, J MAMMAL, V82, P937 MILLER SD, 2001, J MAMMAL, V82, P889 OSTFELD RS, 2003, ECOLOGY, V84, P1421 PERROW C, 1997, ORG ENV, V10, P66 READING RP, 1997, J WILDLIFE MANAGE, V61, P664 RIEBSAME WE, 1997, ATLAS NEW W ROACH JL, 2001, J MAMMAL, V82, P946 SAMSON FB, 1996, PRAIRIE CONSERVATION SCHMID KA, 2001, ECOLOGY, V82, P609 STAFFORD JD, 2003, B ECOL SOC AM, V84, P68 STAUBACH C, 2001, AM J TROP MED HYG, V65, P943 THEOBALD DM, 1997, LANDSCAPE URBAN PLAN, V39, P25 WILSON ME, 1994, DIS EVOLUTION GLOBAL 0921-2973 Landsc. Ecol.ISI:000233036400004Univ Colorado, Dept Ecol & Evolutionary Biol, Boulder, CO 80309 USA. Univ Colorado, Environm Studies Program, Boulder, CO 80309 USA. Bur Land Management, Malta Field Off, Malta, MT 59538 USA. US Fish & Wildlife Serv, Charles M Russell Natl Wildlife Refuge, Lewistown, MT 59457 USA. Kansas State Univ, US Geol Survey, Kansas Cooperat Fish & Wildlife Res Unit, Manhattan, KS 66506 USA. Ctr Dis Control, Bacterial Zoonoses Branch, Div Vector Borne Infect Dis, Ft Collins, CO 80522 USA. Univ Calif Davis, Dept Entomol, Davis, CA 95616 USA. Collinge, SK, Univ Colorado, Dept Ecol & Evolutionary Biol, 334 UCB,RAmaley N122, Boulder, CO 80309 USA. sharon.collinge@colorado.eduEnglish<7Collinge, S. K. Palmer, T. M.2002pThe influences of patch shape and boundary contrast on insect response to fragmentation in California grasslands647-656Landscape Ecology177beetles boundaries connectivity edge effects fragmentation grasslands landscape structure patch shape permeability HABITAT FRAGMENTATION LANDSCAPE STRUCTURE COMMUNITY STRUCTURE MOVEMENT PATTERNS DARKLING BEETLES CONSERVATION ECOLOGY SIZE DYNAMICS CONNECTIVITYArticleNovLandscape ecologists typically identify boundaries to demarcate habitat patches. The boundary between two habitat types may be abrupt, such as the transition between a grassland and a parking lot, or more gradual, such as the shift between successional forest stages. Two key aspects of landscape boundaries, their shape and contrast, are predicted to influence movement of materials, plants, and animals. Ecological theory suggests that a patch's perimeter-to-area ratio should strongly influence animal emigration when patch boundaries are relatively permeable, but not when boundaries are more severe. We investigated the interactive effects of patch shape and boundary contrast on movement of ground-dwelling beetles (Carabidae and Tenebrionidae) in native grassland habitat at Jepson Prairie, Solano County, California, USA. We conducted a field experiment with two patch shape treatments, square and rectangle, that held patch area constant, and two boundary contrast treatments created by mowing grass surrounding each plot at two different heights. We monitored the number of beetles leaving each patch over a three-week period following treatment establishment. We observed a significant effect of boundary contrast on net movement of beetles, with low contrast boundaries exhibiting net immigration and high contrast boundaries experiencing net emigration. Moreover, the importance of patch shape appeared to be greater for low contrast versus high contrast boundaries, consistent with theoretical expectations. Our combined observations indicate that these ground-dwelling beetles were more likely to move into patches that were rectangular and surrounded by a low contrast matrix than patches that were square or surrounded by a high contrast matrix. We conclude that net movement of beetles across patch boundaries is strongly influenced by boundary contrast and may be affected by patch shape when boundary contrast is low.://000179746400005 e ISI Document Delivery No.: 624EB Times Cited: 14 Cited Reference Count: 52 Cited References: *SAS I, 1990, SAS VERS 6 *SAS I, 1997, JMP VERS 3 2 BUREL F, 1989, LANDSCAPE ECOLOGY, V2, P214 COLLINGE SK, 1996, LANDSCAPE URBAN PLAN, V36, P59 COLLINGE SK, 1998, LANDSCAPE URBAN PLAN, V42, P157 COLLINGE SK, 1998, OIKOS, V82, P66 COLLINGE SK, 2000, ECOLOGY, V81, P2211 COLLINGE SK, 2001, BIOL CONSERV, V100, P1 CRIST TO, 1995, J ANIM ECOL, V64, P733 DUELLI P, 1990, BIOL CONSERV, V54, P193 FERRERAS P, 2001, BIOL CONSERV, V100, P125 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY GAME M, 1980, NATURE, V287, P630 GREZ AA, 2000, ENVIRON ENTOMOL, V29, P1244 GUTZWILLER KJ, 1992, LANDSCAPE ECOL, V6, P293 HADDAD NM, 1999, AM NAT, V153, P215 HALFFTER G, 1992, FOLIA ENTOMOLOGICA M, V84, P131 HAMAZAKI T, 1996, LANDSCAPE ECOL, V11, P299 HANSEN AJ, 1992, LANDSCAPE BOUNDARIES HARPER SJ, 1993, J MAMMAL, V74, P1045 HARRISON S, 1999, ECOGRAPHY, V22, P225 HAWROT RY, 1996, AUK, V113, P586 HELZER CJ, 1999, ECOL APPL, V9, P1448 HERKERT JR, 1994, ECOL APPL, V4, P461 HOLMQUIST JG, 1998, OIKOS, V81, P558 IMS RA, 1995, MOSAIC LANDSCAPES EC, P85 JOHNSON AR, 1992, ECOLOGY, V73, P1968 KAREIVA P, 1985, ECOLOGY, V66, P1809 KEPPEL G, 1982, DESIGN ANAL RES HDB KUNIN WE, 1997, BIOL CONSERV, V82, P369 LAURANCE WF, 2001, TRENDS ECOL EVOL, V16, P70 LIMA SL, 1996, TRENDS ECOL EVOL, V11, P131 MAZEROLLE MJ, 1999, ECOSCIENCE, V6, P117 MCINTYRE NE, 1999, ECOLOGY, V80, P2261 MCINTYRE NE, 1999, LANDSCAPE ECOL, V14, P437 NEWMAN JA, 1997, ECOLOGY, V78, P1312 OKUBO A, 1980, DIFFUSION ECOLOGICAL POLLAK O, 1998, ECOLOGY CONSERVATION, P241 SIEGFRIED WR, 1998, BIOL CONSERV, V84, P131 SOKAL RR, 1995, BIOMETRY STAMPS JA, 1987, AM NAT, V129, P533 THIOLLAY JM, 1993, ECOGRAPHY, V16, P97 TISCHENDORF L, 2000, LANDSCAPE ECOL, V15, P633 TISCHENDORF L, 2001, LANDSCAPE ECOL, V16, P235 TURCHIN P, 1998, QUANTITATIVE ANAL MO USHER MB, 1998, BIODIVERS CONSERV, V7, P725 VERMEULEN R, 1994, CARABID BEETLES ECOL, P387 VIROLAINEN KM, 1998, J APPL ECOL, V35, P700 WHITE RE, 1983, FIELD GUIDE BEETLES WIENS JA, 1985, OIKOS, V45, P421 WIENS JA, 1993, OIKOS, V66, P369 WIENS JA, 1997, OIKOS, V78, P257 0921-2973 Landsc. Ecol.ISI:000179746400005Univ Calif Davis, Dept Environm Design, Davis, CA 95616 USA. Univ Calif Davis, Grad Grp Ecol, Davis, CA 95616 USA. Collinge, SK, Univ Colorado, Dept EPO Biol, 334 UCB, Boulder, CO 80309 USA.Englishڽ73Collins, BrandonM Roller, GaryB2013dEarly forest dynamics in stand-replacing fire patches in the northern Sierra Nevada, California, USA 1801-1813Landscape Ecology289Springer Netherlands:Fire ecology High severity Tree regeneration Mixed-conifer 2013/11/01+http://dx.doi.org/10.1007/s10980-013-9923-8 0921-2973Landscape Ecol10.1007/s10980-013-9923-8English |7>Collins, B. M. Kelly, M. van Wagtendonk, J. W. Stephens, S. L.2007ISpatial patterns of large natural fires in Sierra Nevada wilderness areas545-557Landscape Ecology224fire ecology normalized burn ratio dnbr prescribed natural fire regression tree wildland fire use yellowstone-national-park mixed-conifer forests jeffrey pine regression trees grand-canyon landscape regimes USA california severityApr~The effects of fire on vegetation vary based on the properties and amount of existing biomass (or fuel) in a forest stand, weather conditions, and topography. Identifying controls over the spatial patterning of fire-induced vegetation change, or fire severity, is critical in understanding fire as a landscape scale process. We use gridded estimates of fire severity, derived from Landsat ETM+ imagery, to identify the biotic and abiotic factors contributing to the observed spatial patterns of fire severity in two large natural fires. Regression tree analysis indicates the importance of weather, topography, and vegetation variables in explaining fire severity patterns between the two fires. Relative humidity explained the highest proportion of total sum of squares throughout the Hoover fire (Yosemite National Park, 2001). The lowest fire severity corresponded with increased relative humidity. For the Williams fire (Sequoia/Kings Canyon National Parks, 2003) dominant vegetation type explains the highest proportion of sum of squares. Dominant vegetation was also important in determining fire severity throughout the Hoover fire. In both fires, forest stands that were dominated by lodgepole pine (Pinus contorta) burned at highest severity, while red fir (Abies magnifica) stands corresponded with the lowest fire severities. There was evidence in both fires that lower wind speed corresponded with higher fire severity, although the highest fire severity in the Williams fire occurred during increased wind speed. Additionally, in the vegetation types that were associated with lower severity, burn severity was lowest when the time since last fire was fewer than 11 and 17 years for the Williams and Hoover fires, respectively. Based on the factors and patterns identified, managers can anticipate the effects of management ignited and naturally ignited fires at the forest stand and the landscape levels.://000245296600006-151NF Times Cited:7 Cited References Count:43 0921-2973ISI:000245296600006/Collins, BM Univ Calif Berkeley, Dept Environm Sci Policy & Management, Ecosyst Sci Dept, 137 Mulford Hall, Berkeley, CA 94720 USA Univ Calif Berkeley, Dept Environm Sci Policy & Management, Ecosyst Sci Dept, Berkeley, CA 94720 USA Western Ecol Res Ctr, United State Geol Survey, El Portal, CA 95318 USADoi 10.1007/S10980-006-9047-5English|? &Collins, Brandon M. Stephens, Scott L.2010Stand-replacing patches within a 'mixed severity' fire regime: quantitative characterization using recent fires in a long-established natural fire area927-939Landscape Ecology256JulgThe complexity inherent in variable, or mixed-severity fire regimes makes quantitative characterization of important fire regime attributes (e.g., proportion of landscape burned at different severities, size and distribution of stand-replacing patches) difficult. As a result, there is ambiguity associated with the term 'mixed-severity'. We address this ambiguity through spatial analysis of two recent wildland fires in upper elevation mixed-conifer forests that occurred in an area with over 30 years of relatively freely-burning natural fires. We take advantage of robust estimates of fire severity and detailed spatial datasets to investigate patterns and controls on stand-replacing patches within these fires. Stand-replacing patches made up 15% of the total burned area between the two fires, which consisted of many small patches (< 4 ha) and few large patches (> 60 ha). Smaller stand-replacing patches were generally associated with shrub-dominated (Arctostaphylos spp. and Ceanothus spp.) and pine-dominated vegetation types, while larger stand-replacing patches tended to occur in more shade-tolerant, fir-dominated types. Additionally, in shrub-dominated types stand-replacing patches were often constrained to the underlying patch of vegetation, which for the shrub type were smaller across the two fire areas than vegetation patches for all other dominant vegetation types. For white and red fir forest types we found little evidence of vegetation patch constraint on the extent of stand-replacing patches. The patch dynamics we identified can be used to inform management strategies for landscapes in similar forest types.!://WOS:000278526000009Times Cited: 1 0921-2973WOS:00027852600000910.1007/s10980-010-9470-5H<7^Collins, R. J. Barrett, G. W.1997}Effects of habitat fragmentation on meadow vole (Microtus pennsylvanicus) population dynamics in experiment landscape patches63-76Landscape Ecology122habitat fragmentation; landscape patches; meadow vole; Microtus pennsylvanicus; radio-telemetry SPACE USE; REPRODUCTIVE SUCCESS; SUPPLEMENTAL FOOD; TERRITORIAL; RELATEDNESS; DEMOGRAPHY; PREDATION; ECOLOGY; RODENTS; FORAGEArticleAprThis study examined the effects of habitat fragmentation on meadow vole (Microtus pennsylvanicus) population dynamics in experimental landscape patches. The study was conducted from May-November 1993 at the Miami University Ecology Research Center. Fight 0.1-ha small mammal enclosures were used. Four enclosures contained a 160 m(2) nonfragmented patch and four enclosures contained four 40 m(2) fragmented patches. Thus, each treatment was replicated 4 times in a systematic research design. The patches in both treatments contained high-quality habitat surrounded by low-quality matrix. Six pairs of adult meadow voles were released in each enclosure on 27 May 1993. Populations were monitored by live-trapping and radio-telemetry methods. Significantly greater densities of female voles were found during October in the fragmented treatment compared to the nonfragmented treatment. Also, significantly more females than males were found in the fragmented treatment compared to the nonfragmented treatment for the total study period. Significantly more subadult and juvenile males were found in the matrix versus the patch of the nonfragmented treatment compared to the fragmented treatment. Males in the fragmented treatment had significantly greater mean home range size than males or females in the nonfragmented treatment. There appears to exist a relationship between patch fragmentation and the social structure of meadow vole populations; this relationship appears to function as a population regulatory mechanism.://A1997XQ45000001 ISI Document Delivery No.: XQ450 Times Cited: 32 Cited Reference Count: 50 Cited References: ADLER GH, 1989, CAN J ZOOL, V67, P772 BARRETT GW, 1988, J MAMMAL, V69, P170 BARRETT GW, 1995, LANDSCAPE APPROACHES, P157 BARRETT GW, 1995, LANDSCAPE URBAN PLAN BATZLI GO, 1979, J MAMMAL, V60, P740 BERGERON JM, 1987, OECOLOGIA, V71, P510 BIRNEY EC, 1976, ECOLOGY, V57, P1043 BOONSTRA R, 1983, J ANIM ECOL, V52, P757 BREWER SR, 1993, AM MIDL NAT, V130, P393 BROWN JS, 1988, BEHAV ECOL SOCIOBIOL, V22, P37 BROWN JS, 1992, J MAMMAL, V73, P821 DESY EA, 1983, J ANIM ECOL, V52, P127 DESY EA, 1989, ECOLOGY, V70, P411 DOONAN TJ, 1995, ECOLOGY, V76, P814 FORMAN RTT, 1981, BIOSCIENCE, V31, P733 FOSTER J, 1991, ECOLOGY, V72, P1358 GAULIN SJC, 1988, J MAMMAL, V69, P311 HARPER SJ, 1993, J MAMMAL, V74, P1045 HURLBERT SH, 1984, ECOL MONOGR, V54, P187 IMS RA, 1993, BIOL CONSERV, V63, P261 KIE JG, 1994, CALHOME HOME RANGE A LABOV JB, 1981, AM NAT, V118, P361 LAMBIN X, 1991, OIKOS, V61, P126 LAPOLLA VN, 1993, LANDSCAPE ECOL, V8, P25 LINDROTH RL, 1984, J MAMMAL, V65, P600 MADISON DM, 1980, BEHAV ECOL SOCIOBIOL, V7, P65 MADISON DM, 1984, BEHAV ECOL SOCIOBIOL, V15, P8 MARQUIS RJ, 1989, J MAMMAL, V70, P503 MCGRAVY KW, 1992, J MAMMAL, V73, P151 MOHR CO, 1947, AM MIDL NAT, V37, P223 ODUM EP, 1960, ECOLOGY, V41, P34 OSTFELD RS, 1988, J ANIM ECOL, V57, P385 OSTFELD RS, 1990, TRENDS ECOL EVOL, V5, P411 OSTFELD RS, 1992, EFFECTS RESOURCE DIS, P43 PETRUSEWICZ K, 1962, EKOL POL A, V10, P85 PORNELUZI P, 1993, CONSERV BIOL, V7, P618 ROBINSON GR, 1992, SCIENCE, V257, P524 SERA WE, 1994, ECOLOGY, V75, P1560 SHERIDAN M, 1988, BEHAV ECOL SOCIOBIOL, V22, P85 SPENCER SR, 1980, AM MIDL NAT, V103, P32 STAMPS JA, 1987, AM ZOOL, V27, P307 STUECK KL, 1978, ECOLOGY, V59, P539 SZACKI J, 1993, ACTA THERIOL, V38, P113 THOMAS JW, 1990, CONSERVATION STRATEG THOMPSON DQ, 1965, AM MIDL NAT, V74, P76 TUDOR GD, 1982, J AGR SCI, V98, P395 TURNER BN, 1973, ECOLOGY, V54, P967 WEBSTER BA, 1981, J MAMMAL, V62, P738 WOLFF JO, 1993, OIKOS, V68, P364 WTSON A, 1970, ANIMAL POPULATIONS R, P167 0921-2973 Landsc. Ecol.ISI:A1997XQ45000001'UNIV GEORGIA,INST ECOL,ATHENS,GA 30602.EnglishA<7uZComeleo, R. L. Paul, J. F. August, P. V. Copeland, J. Baker, C. Hale, S. S. Latimer, R. W.1996`Relationships between watershed stressors and sediment contamination in Chesapeake Bay estuaries307-319Landscape Ecology115environmental monitoring; estuary; watershed; land use; point source pollution; nonpoint source pollution; pollutant loading; sediment contamination; Chesapeake Bay QUALITY; STATISTICS; WETLANDSArticleOctThree methods for assessing the relationships between estuarine sediment contaminant levels and watershed stressors for 25 Chesapeake Bay sub-estuaries were compared. A geographic information system (GIS) was used to delineate watersheds for each sub-estuary and analyze land use pattern (area and location of developed, herbaceous and forested land) and point source pollution (annual outflow and contaminant loading) using three landscape analysis methods: (1) a watershed approach using the watershed of the estuary containing the sampling station, (2) a 'partial watershed' approach using the area of the watershed within a 10 km radius of the sampling station and (3) a 'weighted partial watershed' approach where stressors within the partial watershed were weighted by the inverse of their linear distance from the sampling station. Nine sediment metals, 16 sediment organics and seven metals loading variables were each reduced to one principal component for statistical analyses. Relationships between the first principal components for sediment metals and organics concentrations and watershed stressor variables were analyzed using rank correlation and stepwise multiple regression techniques. For both metals and organics, the watershed method yielded R(2) values considerably lower than the partial and weighted partial watershed analysis methods. Regression models using stressor data generated by the weighted partial watershed landscape analysis method explained 76% and 47% of the variation in the first principal component for sediment metals and organics concentrations, respectively. Results suggest that the area of developed land located in the watershed within 10 km of the sediment sampling station is a major contributing factor in the sediment concentrations of both metals and organics.://A1996VR02500008 ISI Document Delivery No.: VR025 Times Cited: 10 Cited Reference Count: 36 Cited References: *CHES BAY PROGR, 1994, 10294 CBPTRS *NAT RES COUNC, 1990, MAN TROUBL WAT ROL M *SAS I, 1990, SAS STAT US GUID *US EPA, 1988, SABEC88040 US EPA SC *US EPA, 1994, 10294 CPBTRS *US EPA, 1994, EPA620R94020 BASTIAN RK, 1988, ECOLOGY MANAGEMENT W, V1, P87 CONOVER WJ, 1981, AM STAT, V35, P124 CORRELL DL, 1992, ESTUARIES, V15, P431 DETENBECK NE, 1993, LANDSCAPE ECOL, V8, P39 FEGAS RG, 1983, 895E US GEOL SURV CA HOLLAND AF, 1990, 600490033 EPA OFF RE JOHNSTON CA, 1990, BIOGEOCHEMISTRY, V10, P105 KADLEC RH, 1979, WETLAND FUNCTIONS VA, P436 KARR JR, 1978, SCIENCE, V201, P229 KIM K, 1993, PHOTOGRAMM ENG REM S, V59, P1539 LONG ER, 1995, ENVIRON MANAGE, V19, P81 MAIDMENT DR, 1993, ENV MODELING GIS, P147 MEENTEMEYER V, 1987, LANDSCAPE HETEROGENE, P15 MORRISON ML, 1992, WILDLIFE HABITAT REL NEFF NA, 1980, SURVEY MULTIVARIATE NETER J, 1985, APPL LINEAR STAT MOD OSBORNE LL, 1988, J ENVIRON MANAGE, V26, P9 PACHECO PA, 1993, POINT SOURCE METHODS PETERJOHN WT, 1984, ECOLOGY, V65, P1466 PHILIPPI TE, 1993, DESIGN ANAL ECOLOGIC, P183 POTVIN C, 1993, ECOLOGY, V74, P1617 RITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 SCHIMMEL SC, 1994, EPA620R94005 OFF RES STROBEL CJ, 1992, EPA620R94019 OFF RES TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 VALIELA I, 1992, ESTUARIES, V15, P443 WEHDE M, 1982, PHOTOGRAMMETRIC ENG, V48, P1289 WEISBERG SB, 1993, 600R93006 ENV RES LA WHIGHAM DF, 1988, ENVIRON MANAGE, V12, P663 ZAR JH, 1984, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:A1996VR02500008PComeleo, RL, UNIV RHODE ISL,ROW SCI INC,ATLANTIC ECOL DIV,NARRAGANSETT,RI 02882.English4}?Compin, A. Cereghino, R.2007Spatial patterns of macroinvertebrate functional feeding groups in streams in relation to physical variables and land-cover in Southwestern France 1215-1225Landscape Ecology228Oct://000248941900008 0921-2973ISI:000248941900008F~?d)Concepcion, E. D. Diaz, M. Baquero, R. A.2008[Effects of landscape complexity on the ecological effectiveness of agri-environment schemes135-148Landscape Ecology23 Agricultural intensification is a major cause for biodiversity loss. It occurs at field scales through increased inputs and outputs, and at landscape scales through landscape simplification. Agri-environment schemes (AES) of the European Common Agricultural Policy (CAP) aim at reducing biodiversity loss by promoting extensification of agricultural practises mostly at field scales. We present a conceptual model for the relationship between landscape complexity and ecological effectiveness of AES based on (a) non-linear relationships between landscape complexity and abundance and diversity at field scales and (b) four possible interactive scenarios between landscape- and field scale effects on abundance and diversity. We then evaluated whether and how effectiveness of AES interacted with landscape-scale effects of intensification along a landscape complexity gradient established in central Spain. Pairs of cereal fields with and without AES but with the same landscape context were selected in three regions differing in landscape complexity. Effectiveness of AES was measured as differences between paired fields in species richness and abundance of five target groups (birds, grasshoppers and crickets, spiders, bees and plants). Landscape metrics were measured in 500-m radius circular plots around field centres. Positive, negative and no effects of landscape complexity on effectiveness of AES were found, suggesting that effects of complexity on effectiveness of AES changes from positive to negative along gradients of landscape complexity. Effectiveness of AES for improving biodiversity was then constrained by landscape. Compulsory measures aimed at enhancing or maintaining landscape complexity would enhance the effectiveness of AES for preserving biodiversity in farmed landscapes."://WOS:000252636100003 Times Cited: 0WOS:000252636100003(10.1007/s10980-007-9150-2|ISSN 0921-2973ڽ7 =Connors, JohnPatrick Galletti, ChristopherS Chow, WinstonT L.2013Landscape configuration and urban heat island effects: assessing the relationship between landscape characteristics and land surface temperature in Phoenix, Arizona271-283Landscape Ecology282Springer Netherlands9ASTER Quickbird Remote sensing CAP-LTER Urban temperature 2013/02/01+http://dx.doi.org/10.1007/s10980-012-9833-1 0921-2973Landscape Ecol10.1007/s10980-012-9833-1English<7"Cook, G. D. Dawes-Gromadzki, T. Z.2005bStable isotope signatures and landscape functioning in banded vegetation in arid-central Australia649-660Landscape Ecology206Acacia aneura; banded vegetation; landscape function; mulga; stable isotope ratios; trophic position N-15 NATURAL-ABUNDANCE; EASTERN AUSTRALIA; CARBON ISOTOPES; FOOD-HABITS; NITROGEN; MULGA; DELTA-N-15; TERMITES; DELTA-C-13; ISOPTERAArticleSepWe examined how the measurement of stable carbon and nitrogen isotopes in soils, vegetation and invertebrates can contribute to understanding landscape processes in mulga Acacia aneura ecosystems characterised by alternating wooded groves and intergroves. Our analyses showed that greater leakiness of water from intergroves at the landscape scale tended to promote more conserving physiology at the plant scale. Thus isolated mulga trees in intergroves probably have higher water use efficiency than those in groves. Both trees and grasses in the intergroves have a greater reliance on recycled nitrogen than plants in the groves for which recently fixed N was a substantial source. Grasses in the intergroves had higher N concentrations than those in the groves despite the soil having lower N concentrations. A lack of variation in the isotopic signature of surface soil N suggested that the lower N concentrations in soils of intergroves than groves is due to lower rates of input and not shorter residence times. Stable isotopic signatures of invertebrates showed a diversity of feeding strategies amongst termite species and indicated symbiotic N fixation in two species. There was no relationship between the dependence on N fixation and the habitat preference or diet of termites. Our results suggest that with cautious interpretation, stable isotope signatures could contribute to understanding other ecosystems where patch-interpatch functioning is an important landscape process.://000233600700002 ISI Document Delivery No.: 988KS Times Cited: 1 Cited Reference Count: 55 Cited References: ABBADIE L, 1992, ECOLOGY, V73, P608 ANDERSON VJ, 1997, AUST J BOT, V45, P331 ASH AJ, 1995, RANGELAND J, V17, P86 AUSTIN AT, 1999, AUST J PLANT PHYSIOL, V26, P293 BASTIN GN, 2002, ECOL INDIC, V1, P247 BOUTTON TW, 1983, OECOLOGIA, V59, P1 BOWMAN DMJS, 2002, AUSTRAL ECOL, V27, P94 CLEWETT JF, 2003, Q103040 DEP PRIM IND COLLINS NM, 1983, NITROGEN ECOLOGICAL, P381 COOK GD, 2001, AUSTRAL ECOL, V26, P630 COVENTRY RJ, 1988, AUST J SOIL RES, V26, P375 CURTIS AD, 1997, PHYSIOL ENTOMOL, V22, P303 DAWSON TE, 2002, ANNU REV ECOL SYST, V33, P507 DENIRO MJ, 1978, GEOCHIM COSMOCHIM AC, V42, P495 DENIRO MJ, 1981, GEOCHIMICA COSMOCHIM, V45, P341 DUNKERLEY DL, 2002, J ARID ENVIRON, V51, P199 ELDRIDGE DJ, 2001, BANDED VEGETATION PA, P105 FARQUHAR GD, 1982, AUST J PL PHYSL, V9, P121 FARQUHAR GD, 1984, AUST J PLANT PHYSIOL, V11, P539 FARQUHAR GD, 1989, ANNU REV PLANT PHYS, V40, P503 GALLE S, 2001, BANDED VEGETATION PA, P77 GREENE RSB, 1992, AUST J SOIL RES, V30, P55 GREENE RSB, 2001, BANDED VEGETATION PA, P52 HANDLEY LL, 1999, AUST J PLANT PHYSIOL, V26, P185 HILL GF, 1942, TERMITES ISOPTERA AU HOGBERG P, 1997, NEW PHYTOL, V137, P179 LENDON C, 1978, PHYSICAL BIOL FEATUR, P66 LEPAGE M, 1993, J TROP ECOL, V9, P303 LOW WA, 1978, PHYS BIOL FEATURES K LUDWIG JA, IN PRESS ECOL LUDWIG JA, 1995, LANDSCAPE ECOL, V10, P51 LUDWIG JA, 1999, LANDSCAPE ECOL, V14, P557 LUDWIG JA, 2002, LANDSCAPE ECOL, V17, P157 MINAGAWA M, 1984, GEOCHIM COSMOCHIM AC, V48, P1135 MOORE CWE, 1970, SEARCH, V1, P43 NOYMEIR I, 1981, ARID LAND ECOSYSTEMS, P411 NOYMEIR I, 1985, HOT DESERTS ARID SHR, P93 OELBERMANN K, 2002, OECOLOGIA, V130, P337 PATE JS, 1998, PLANT CELL ENVIRON, V21, P1231 PETERSON BJ, 1987, ANNU REV ECOL SYST, V18, P293 ROBINSON D, 2001, TRENDS ECOL EVOL, V16, P153 SLAYTOR M, 1994, COMP BIOCHEM PHYS B, V107, P1 SPAIN AV, 1996, SOIL BIOL BIOCHEM, V28, P1585 TAYASU I, 1998, ECOL RES, V13, P377 TAYASU I, 2002, SOIL BIOL BIOCHEM, V34, P297 TONGWAY DJ, 1989, AUST J ECOL, V14, P263 TONGWAY DJ, 1990, AUST J ECOL, V15, P23 TONGWAY DJ, 1996, RESTOR ECOL, V4, P388 TONGWAY DJ, 1997, LANDSCAPE ECOLOGY FU, P13 TONGWAY DJ, 1997, LANDSCAPE ECOLOGY FU, P49 TONGWAY DJ, 2001, BANDED VEGETATION PA WADA E, 1991, CRIT REV FOOD SCI, V30, P361 WATSON JAL, 1973, TROP GRASSLANDS, V7, P121 WATSON JAL, 1978, PHYSICAL BIOL FEATUR, P101 WATSON JAL, 1981, AUST J ZOOL S, V78, P1 0921-2973 Landsc. Ecol.ISI:000233600700002CSIRO, Trop Ecosyst Res Ctr, Cooperat Res Ctr Sustainable Management Trop Sava, Winnellie, NT 0822, Australia. Cook, GD, CSIRO, Trop Ecosyst Res Ctr, Cooperat Res Ctr Sustainable Management Trop Sava, PMB 44, Winnellie, NT 0822, Australia. garry.cook@csiro.auEnglishF|?DCook-Patton, Susan C. Weller, Daniel Rick, Torben C. Parker, John D.2014_Ancient experiments: forest biodiversity and soil nutrients enhanced by Native American middens979-987Landscape Ecology296JulThe legacy of ancient human practices can affect the diversity and structure of modern ecosystems. Here, we examined how prehistoric refuse dumps ("middens") impacted soil chemistry and plant community composition in forests along the Chesapeake Bay by collecting vegetational and soil nutrient data. The centuries- to millennia-old shell middens had elevated soil nutrients compared to adjacent sites, greater vegetative cover, especially of herb and grass species, and higher species richness. Not only are middens important archaeological resources, they also offer a remarkable opportunity to test ecological hypotheses about nutrient addition over very long time scales. We found no evidence, for example, that elevated nutrients enhanced invasion by non-native species as predicted by the fluctuating resource hypothesis. However, we did find that elevated nutrients shifted community structure from woody species to herbaceous species, as predicted by the structural carbon-nutrient hypothesis. These results highlight the long-lasting effects that humans can have on abiotic and biotic properties of the natural environment, and suggest the potential for modern patterns of species' distributions and abundances to reflect ancient human activities.!://WOS:000338331600005Times Cited: 1 0921-2973WOS:00033833160000510.1007/s10980-014-0033-zڽ7!5Coops, NicholasC Schaepman, MichaelE Mücher, CasparA2013What multiscale environmental drivers can best be discriminated from a habitat index derived from a remotely sensed vegetation time series? 1529-1543Landscape Ecology288Springer NetherlandsZEnvironmental classification Remote sensing Dynamic habitat index Habitat SPOT NDVI Europe 2013/10/01+http://dx.doi.org/10.1007/s10980-013-9900-2 0921-2973Landscape Ecol10.1007/s10980-013-9900-2English6<7Coops, N. C. Catling, P. C.2002Prediction of the spatial distribution and relative abundance of ground-dwelling mammals using remote sensing imagery and simulation models173-188Landscape Ecology172Hairborne videography generalised linear modelling long-nosed potoroo Macropus rufogriseus Nadgee nature reserve Potorous tridactylus red-necked wallaby swamp wallaby Wallabia bicolor NEW-SOUTH-WALES BLACK BEAR HABITAT EUCALYPT FORESTS AIRBORNE VIDEOGRAPHY WILDLIFE MANAGEMENT ARBOREAL MARSUPIALS VEGETATION COMPLEXITY SYSTEM GISArticlebWe present an approach that allows current, retrospective and future relative abundances of mammal species to be predicted across landscapes. A spatial generalized regression model of species relative abundance based on habitat quality and time since disturbance was combined with coverages of the spatial distribution of habitat quality derived from a simulation model which predicts the historical and future spatial arrangement of forest habitat. The strength of this approach is that the input habitat data can be derived as part of a standard forest inventory mapping program with the addition of high spatial resolution remote sensing imagery. Furthermore, it operates at the scale used for wildlife management in Australia, which makes it widely applicable. To demonstrate the approach we use data collected over 20 years on the long-nosed potoroo (Potorous tridactylus) and the large wallabies (red-necked wallaby, Macropus rufogriseus, and swamp wallaby, Wallabia bicolor) and their habitats following wildfire. Results indicate the relative abundance of the potoroo has increased, from initially sparse numbers of less than 0.5 % of plot-night occurrences to close to 3% approximately twenty years after a major fire event. The large wallabies by contrast decreased in relative abundance from about 20% since the major fire event. Presently the relative abundance of large wallabies was modelled at 2% of plot-nights with tracks which was very low. Predictions of future relative abundance without additional disturbance were low, with the region likely to be unsuitable for the species in the next 5 years. These models offer tools for investigating the current and historical abundances of key species which can provide data to forest managers for wildlife management thereby translating current scientific understanding into tools suitable for every-day use by forest managers.://000177049100005 ISI Document Delivery No.: 577ET Times Cited: 6 Cited Reference Count: 60 Cited References: *NSW NAT PARKS WIL, 1979, NADG NAT RES PROV FI *STATS INC, 1995, STATISTICA WIND COMP AIROLA TM, 1989, P 12 BIENN WORKSH CO, P94 ASPINALL R, 1993, PHOTOGRAMM ENG REM S, V59, P537 BENNETT AF, 1993, WILDLIFE RES, V20, P267 BIDEAU E, 1993, J MAMMAL, V74, P745 BRAITHWAITE RW, 1997, AUST J ECOL, V22, P57 BROWN S, 1994, J ENVIRON MANAGE, V42, P349 BYRON AMH, 1981, NOTES MAMM SOC, V42, P271 CALABY JH, 1995, MAMMALS AUSTR, P350 CATLING PC, 1982, P S DYN MAN MED TYP, P199 CATLING PC, 1991, CONSERVATION AUSTR F, P353 CATLING PC, 1994, WILDLIFE RES, V21, P219 CATLING PC, 1995, WILDLIFE RES, V22, P271 CATLING PC, 1998, WILDLIFE RES, V25, P449 CATLING PC, 2000, WILDLIFE RES, V27, P639 CATLING PC, 2001, IN PRESS WILDLIFE RE CLARK JD, 1993, J WILDLIFE MANAGE, V57, P519 COOPS NC, 1997, INT J REMOTE SENS, V18, P2677 COOPS NC, 1997, WILDLIFE RES, V24, P691 COOPS NC, 1998, AUSTR FORESTRY, V61, P244 COOPS NC, 2000, AUSTRAL ECOL, V25, P344 COOPS NC, 2001, COMPUT GEOSCI-UK, V27, P795 CORK SJ, 1996, FOREST ECOL MANAG, V85, P163 CRAWLEY MJ, 1993, GLIM ECOLOGISTS EVERITT JH, 1986, PHOTOGRAMM ENG REM S, V52, P1655 FRELICH LE, 1998, J ECOL, V86, P149 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GARDNER RH, 1991, QUANTITATIVE METHODS, P289 GAUSMAN HW, 1983, REMOTE SENS ENVIRON, V13, P363 GILL AM, 1989, FIRE MANAGEMENT NATU, P137 GILMORE P, 1983, SURVEY VEGETATION NA HOLT RD, 1995, ECOL APPL, V5, P20 INCOLL RD, 1995, LANDSCAPE ECOLOGY GL KING DJ, 1991, PHOTOGRAMMETRIC ENG, V57, P12671 KING DJ, 1995, CAN J REMOTE SENS, V21, P245 KOLMOGOROFF A, 1941, ANN MATH STAT, V12, P461 LAMBERSON RH, 1994, CONSERV BIOL, V8, P185 LAPERRIERE AJ, 1980, J WILDLIFE MANAGE, V44, P881 LINDENMAYER DB, 1991, BIOL CONSERV, V56, P295 LINDENMAYER DB, 1995, RISK EXTINCTION RANK, P204 LINDENMAYER DB, 1995, WILDLIFE RES, V22, P445 MAUSEL PW, 1992, PHOTOGRAMM ENG REM S, V58, P1189 MENKHORST PW, 1995, MAMMALS VICTORIA DIS, P360 MERCHANT JC, 1995, MAMMALS AUSTR, P404 MORRISON RGB, 1981, FIELD GUIDE TRACKS T NEWSOME AE, 1979, ECOSYSTEMS WORLD A, V9, P301 PEREIRA JMC, 1991, PHOTOGRAMM ENG REM S, V57, P1475 PICKUP G, 1995, INT J REMOTE SENS, V16, P1647 READING RP, 1996, WILDLIFE RES, V23, P221 RICHARDSON AJ, 1992, P 13 BIENN WORKSH CO RUDIS VA, 1995, J WILDLIFE MANAGE, V59, P170 SCHAMBERGER ML, 1986, WILDLIFE 2000 MODELI, P5 SEEBECK JH, 1981, WILDLIFE RES, V8, P285 SKIDMORE AK, 1996, INT J GEOGR INF SYST, V10, P441 THOMAS JW, 1990, CONSERVATION STRATEG THOR G, 1990, T 19 IUGB C 1998 NOR, P49 TRIGGS B, 1984, MAMMALS TRACKS SIGNS TRIGGS B, 1996, TRACKS SCATS OTHER T WU ST, 1988, P 1 WORKSH VID AM SO, P128 0921-2973 Landsc. Ecol.ISI:000177049100005CSIRO, Forestry & Forest Prod, Clayton, Vic 3169, Australia. Coops, NC, CSIRO, Forestry & Forest Prod, Private Bag 10, Clayton, Vic 3169, Australia.EnglishM<7.Coppedge, B. R. Engle, D. M. Fuhlendorf, S. D.2007PMarkov models of land cover dynamics in a southern Great Plains grassland region 1383-1393Landscape Ecology229conservation Reserve Program; Grassland; fragmentation; Juniper; landscape; Oklahoma; transition matrix CROPLAND RETIREMENT; LANDSCAPE CHANGE; JUNIPERUS-VIRGINIANA; USA; CONSEQUENCES; SIMULATION; CONVERSION; PATTERNS; PRAIRIE; SYSTEMArticleNovGrassland regions of the southern Great Plains are fragmented by agricultural activity and many habitat remnants have experienced encroachment by juniper (Juniperus virginiana L.). Recently, many cropland areas have been converted to monoculture grassland (pastures) and enrolled into the Conservation Reserve Program (CRP). Our objectives were to develop spatial and temporal Markov models to characterize land cover dynamics relative to juniper expansion and CRP using aerial photography from 1965, 1981, and 1995. We used landscapes surrounding three Breeding Bird Survey routes with varying levels of juniper encroachment in Oklahoma as study areas. As expected, land cover changes from 1965 to 1995 included increases in juniper woodland, mixed juniper-deciduous woodland, and pastures from CRP activity. Markov models revealed that juniper had a low likelihood of self-replacement in early stages of encroachment. In all areas, relatively little native grassland was lost to juniper encroachment, but other native habitat types such as deciduous woodland were heavily impacted. Transition probabilities for land cover dynamics varied significantly both spatially and temporally. Projections of these raw transition matrices produced widely varying models of future land cover conditions. By modifying the matrices to account for recent and potential socio-political and ecological changes occurring in this region, a number of more plausible land cover scenarios were produced than those resulting from simple projections of raw transition matrices.://000250207500010 Cited Reference Count: 44 Cited References: ANTROP M, 1998, LANDSCAPE URBAN PLAN, V41, P155 ARCHER S, 1994, ECOLOGICAL IMPLICATI, P13 BAKER WL, 1989, LANDSCAPE ECOL, V2, P111 BOERNER REJ, 1996, GEOGR ANAL, V28, P56 BRIGGS JM, 2002, ECOSYSTEMS, V5, P578 BRIGGS JM, 2005, BIOSCIENCE, V55, P243 BROWN JR, 1998, LANDSCAPE ECOL, V13, P93 BURGI M, 2004, LANDSCAPE ECOL, V19, P857 CHAPIN FS, 2001, GLOBAL BIODIVERSITY COPPEDGE BR, 2001, AVIAN ECOLOGY CONSER, P225 COPPEDGE BR, 2001, ECOL APPL, V11, P47 COPPEDGE BR, 2001, LANDSCAPE ECOL, V16, P677 COPPEDGE BR, 2004, BIOL CONSERV, V115, P431 DUNN CP, 1993, CONSERV BIOL, V7, P132 DUSSART E, 1998, J RANGE MANAGE, V51, P685 ENGLE DM, 1992, J RANGE MANAGE, V45, P301 ENGLE DM, 1995, E947 OKL COOP EXT SE ENGLE DM, 1996, AI APPLICATIONS, V10, P1 FUHLENDORF SD, 1996, ECOL MODEL, V90, P245 GLANTZ MH, 1994, DROUGHT FOLLOWS PLOW, P9 HARRIS BL, 1991, CONSERVATION RESERVE, P24 HOLTHUIJZEN AMA, 1985, CAN J BOT, V63, P1508 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 JOYCE LA, 1988, IMPACTS CONSERVATION, P115 LAYCOCK W, 1991, CONSERVATION RESERVE, P1 LAYCOCK WA, 1988, IMPACTS CONSERVATION, P3 LEATHERS N, 2000, PROF GEOGR, V52, P83 LIPPE E, 1985, J ECOL, V73, P775 MITCHELL JE, 2000, RMRSGTR68 MOLEELE NM, 1998, J ARID ENVIRON, V40, P245 MULLER MR, 1994, LANDSCAPE ECOL, V9, P151 PAN DY, 1999, LANDSCAPE ECOL, V14, P35 RIDDEL M, 1997, J PROD AGRIC, V10, P106 ROBERTS RS, 1987, PROF GEOGR, V39, P275 SCHIMEL DS, 1994, GLOBAL BIOGEOCHEM CY, V8, P279 SKOLD MD, 1989, J PROD AGRIC, V2, P197 TURNER MG, 1987, LANDSCAPE ECOL, V1, P29 TURNER MG, 1988, APPL MATH COMPUT, V27, P39 TYRL RJ, 2002, FIELD GUIDE OKALHOMA URBAN DL, 2002, LEARNING LANDSCAPE E, P35 USHER MB, 1992, PLANT SUCCESSION THE, P215 VANAUKEN OW, 2000, ANNU REV ECOL SYST, V31, P197 WORSTER D, 1979, DUST BOWL SO PLAINS YODER J, 2003, REV AGRIC ECON, V25, P218 0921-2973 Landsc. Ecol.ISI:000250207500010Oklahoma State Univ, Dept Nat Resource Ecol & Management, Tulsa, OK 74107 USA. TCC W, Div Sci & Math, Tulsa, OK 74107 USA. Coppedge, BR, Oklahoma State Univ, Dept Nat Resource Ecol & Management, 008C Ag Hall, Tulsa, OK 74107 USA. bcoppedg@tulsacc.eduEnglishK<7LCoppedge, B. R. Engle, D. M. Fuhlendorf, S. D. Masters, R. E. Gregory, M. S.2001]Landscape cover type and pattern dynamics in fragmented southern Great Plains grasslands, USA677-690Landscape Ecology168Conservation Reserve Program encroachment fragmentation grassland conversion juniper landscape pattern Oklahoma CONSERVATION-RESERVE-PROGRAM WOODY PLANT INVASION HABITAT FRAGMENTATION SPATIAL PATTERN NORTH-AMERICA BIRDS JUNIPER INDEXES COMMUNITIES PROSOPISArticledWe documented land cover and landscape pattern changes in an area of northwestern Oklahoma, USA using aerial photography from 1965, 1981, and 1995. This region of the southern Great Plains is fragmented by agricultural activity, and in recent years many remnant native grasslands have experienced extensive invasion by woody juniper (Juniperus virginiana L.). Concurrently, many cropland areas are being planted into perennial forage grasses and converted to intensively managed introduced grasslands as part of the U.S. Conservation Reserve Program (CRP). Our objectives were to document land cover and landscape pattern changes in the region relative to the expansion of juniper and CRP activity. We then examined how local landscape dominance by either anthropogenic or woody vegetation patches affected landscape pattern indices. Land cover changes from 1965 to 1995 included substantial increases in juniper woodlands and mixed woodlands that resulted from juniper encroachment into deciduous woodlands. Introduced grasslands also increased in many areas as a result of CRP implementation. Changes in landscape pattern generally reflected the influx of juniper into many areas. Landscapes dominated by woody vegetation had significantly more patches, smaller patches and patch core areas, more total edge, and higher patch diversity than landscapes dominated by anthropogenic cover types. Results indicate that expanding juniper is exacerbating the fragmentation process initiated by previous human activity, and represents a serious threat to the continued integrity and conservation of remaining southern Great Plains grasslands.://000175490900001 ISI Document Delivery No.: 550EP Times Cited: 10 Cited Reference Count: 59 Cited References: *SOIL WAT CONS SOC, 1994, WHEN CONS RES PROGR *US BUR CENS, 1945, US CENS AGR, V1 ANDREN H, 1994, OIKOS, V71, P355 ARCHER S, 1994, ECOLOGICAL IMPLICATI, P13 AREND JL, 1950, J FOREST, V48, P129 ASKINS RA, 1993, CURR ORNITHOL, V11, P1 AXELROD DI, 1985, BOT REV, V51, P163 BENDER DJ, 1998, ECOLOGY, V79, P517 BEST LB, 1997, WILDLIFE SOC B, V25, P864 BOWDEN MJ, 1981, CLIMATE HIST STUDIES, P479 BRAGG TB, 1976, J RANGE MANAGE, V29, P19 BROWN JR, 1989, OECOLOGIA, V80, P19 BROWN JR, 1998, LANDSCAPE ECOL, V13, P93 BYSTRAK D, 1981, STUD AVIAN BIOL, V6, P34 COPPEDGE BR, 2001, AVIAN ECOLOGY CONSER, P225 COPPEDGE BR, 2001, ECOL APPL, V11, P47 CULLINAN VI, 1992, LANDSCAPE ECOL, V7, P211 DAVIDSON C, 1998, WILDLIFE SOC B, V26, P32 DRISCOLL RS, 1984, USDA FOR SERV MISC P, V1439 DROEGE S, 1990, SURVEY DESIGNS STAT, P1 ENGEL DM, 1995, E947 OKL COOP EXT SE ENGLE DM, 1987, J RANGE MANAGE, V40, P237 ENGLE DM, 1996, AI APPLICATIONS, V10, P1 FUHLENDORF SD, 1996, ECOL MODEL, V90, P245 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GERARD PW, 1995, 4 US DEP INT GFIBSON AM, 1981, OKLAHOMA HIST 5 CENT GLANTZ MH, 1994, DROUGHT FOLLOWS PLOW, P9 GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HELZER CJ, 1999, ECOL APPL, V9, P1448 HERKERT JR, 1994, ECOL APPL, V4, P461 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 JOERN A, 1995, CHANGING PRAIRIE N A JOHNSON DH, 1993, CONSERV BIOL, V7, P934 KNOPF FL, 1994, STUDIES AVIAN BIOL, V15, P247 KRUMMEL JR, 1987, OIKOS, V48, P321 KURZEJESKI EW, 1992, WILDLIFE SOC B, V20, P253 LAYCOCK WA, 1988, IMPACTS CONSERVATION, P3 LOEHLE C, 1996, LANDSCAPE ECOL, V11, P225 MCCOY TD, 2001, AM MIDL NAT, V145, P1 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MILLER JN, 1997, LANDSCAPE ECOL, V12, P137 MILNE BT, 1996, ECOLOGY, V77, P805 MORTENSEN TL, 1989, J SOIL WATER CONSERV, V44, P494 NEWMAN JB, 1988, IMPACTS CONSERVATION ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 POLLEY HW, 1994, ECOLOGY, V75, P976 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 RISSER PG, 1981, TRUE PRAIRIE ECOSYST SAMPSON F, 1994, BIOSCIENCE, V44, P418 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SIMPSON JW, 1994, LANDSCAPE ECOL, V9, P261 THUROW TL, 1997, 1997 JUN S TEX AGR E TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 WOLDA H, 1981, OECOLOGIA, V50, P296 YOUNG CE, 1990, J SOIL WATER CONSERV, V45, P370 0921-2973 Landsc. Ecol.ISI:000175490900001Oklahoma State Univ, Div Agr Sci & Nat Resources, Stillwater, OK 74078 USA. Coppedge, BR, Oklahoma State Univ, Div Agr Sci & Nat Resources, Stillwater, OK 74078 USA.Englisht<7Coppolillo, P. B.2001jCentral-place analysis and modeling of landscape-scale resource use in an East African agropastoral system205-219Landscape Ecology163 pastoralism herding grazing human resource use savanna Sukuma Tanzania NOMADIC PASTORAL ECOSYSTEM SPATIALLY-EXPLICIT MODEL SAHELIAN WEST-AFRICA DAILY GRAZING ORBITS NATIONAL-PARK NUTRIENT AVAILABILITY NORTHERN TANZANIA SHORTGRASS STEPPE FAUNAL COLLAPSE GAME RESERVESReviewAprrMost spatial models of grazing assume a global search; that is, the entire paddock or landscape is available to grazers. These 'unconstrained' models characterize landscape patches based on absolute properties (i.e., without regard for how individual grazers are situated within them). In most of East Africa cattle are herded and must start and end each day's grazing at their enclosure. Thus, global search is not a realistic assumption. This implies that the relative location of a patch may be more important than its absolute properties because its quality depends not only on the properties of the patch itself, but also on its location relative to home and to water. Using data from 73 full-day herd follows among a group of agropastoralists in western Tanzania, I build and test an unconstrained model and compare its analytical utility and predictive power to a 'central-place' model that defines the landscape relative to herders' homes (the central place) and dry season water. The central-place model provides analytical insights into the grazing system that are not apparent when using an unconstrained model, and it explains more of the variance in grazing intensity. Because many types of resources are collected around a focal point, central-place models should have wide applicability for analyzing and modeling many kinds of resource use, particularly in the developing world.://000168194400002 ISI Document Delivery No.: 423TT Times Cited: 1 Cited Reference Count: 106 Cited References: *TWCM, 1992, KAT RUKW CENS NOV 19 ABRAHAMS RG, 1967, PEOPLES GREATER UNYA ANDERSEN DC, 1996, ECOL MODEL, V89, P99 ARHEM K, 1985, PASTORAL MAN GARDEN BAILEY DW, 1996, J RANGE MANAGE, V49, P386 BAKER WL, 1995, LANDSCAPE ECOL, V10, P143 BETTINGER RL, 1997, J ARCHAEOL SCI, V24, P887 BIGNAL EM, 1998, J APPL ECOL, V35, P949 BIRD DW, 1997, J ARCHAEOL SCI, V24, P39 BORNER M, 1985, ORYX, V19, P91 BRANDON K, 1998, PARKS PERIL PEOPLE P, P415 BRANDSTROM P, 1985, AGROPASTORAL DILEMMA BROTEN M, 1995, SERENGETI, V2, P169 BROWN LH, 1971, BIOL CONSERV, V3, P93 BURKEY TV, 1995, BIOL CONSERV, V71, P107 CAMPBELL K, 1995, SERENGETI, V2, P534 CARO TM, 1999, AFR J ECOL, V37, P305 CARO TM, 1999, J APPL ECOL, V36, P205 CASIMIR MJ, 1998, HUM ECOL, V26, P113 CLAYTON L, 1997, ECOL APPL, V7, P642 CONANT FP, 1982, DESERTIFICATION DEV COPPOCK DL, 1986, J APPL ECOL, V23, P573 COPPOLILLO PB, 2000, HUM ECOL, V28, P527 COUGHENOUR MB, 1985, SCIENCE, V230, P619 COUGHENOUR MB, 1991, J RANGE MANAGE, V44, P530 COVICH AP, 1976, ANNU REV ECOL SYST, V7, P235 CUTHILL I, 1990, ANIM BEHAV, V40, P1087 DAHL G, 1976, HAVING HERDS PASTORA DEANGELIS DL, 1985, ECOL MODEL, V29, P399 DODD JL, 1994, BIOSCIENCE, V44, P28 DUTOIT JT, 1999, BIODIVERS CONSERV, V8, P1643 EAST R, 1981, BIOL CONSERV, V21, P111 ELDRIDGE JD, 1991, PROF GEOGR, V43, P500 ELLIS JE, 1988, J RANGE MANAGE, V41, P450 ELLIS JE, 1996, INT WORKSH SUST US R ELTRINGHAM SK, 1998, MKOMAZI ECOLOGY BIOD, P485 ENGHOFF M, 1990, NOMADIC PEOPLES, V25, P93 ESTES RD, 1991, BEHAV GUIDE AFRICAN FERNANDEZGIMENEZ ME, 1999, HUM ECOL, V27, P1 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FORMAN RTT, 1997, LANDSCAPE URBAN PLAN, V37, P129 FOX J, 1996, CONSERV BIOL, V10, P562 GALATY JG, 1988, PRODUCTION AUTONOMY, P163 GALATY JG, 1990, WORLD PASTORALISM HE HACKEL JD, 1999, CONSERV BIOL, V13, P726 HAGGETT P, 1977, LOCATIONAL ANAL HUMA HAYNES KE, 1984, GRAVITY SPATIAL INTE HILL DH, 1995, OUTLOOK AGR, V24, P155 HOMEWOOD KM, 1984, HUM ECOL, V12, P431 HOMEWOOD KM, 1991, MAASAILAND ECOLOGY P KACELNIK A, 1984, J ANIM ECOL, V53, P283 KAHURANANGA J, 1997, AFR J ECOL, V35, P179 KEPE T, 1999, HUM ECOL, V27, P29 KREMEN C, 1994, CONSERV BIOL, V8, P388 KREMEN C, 1998, CONSERV BIOL, V12, P549 LAMPREY HF, 1964, E AFR WILDL J, V1, P1 LAWRENCE D, 1998, LANDSCAPE ECOL, V13, P135 LEWIS DM, 1995, ECOL APPL, V5, P861 LINDSAY WK, 1989, CONSERVATION AFRICA, P149 LITTLE PD, 1996, AFRICA, V66, P37 MCCABE JT, 1990, HUM ECOL, V18, P81 MCCABE JT, 1992, HUM ORGAN, V51, P353 MCINTYRE S, 1999, CONSERV BIOL, V13, P1282 MEIR A, 1996, HUM ECOL, V24, P39 METCALFE D, 1992, AM ANTHROPOL, V94, P340 MILLER RI, 1977, BIOL CONSERV, V12, P311 MISHRA C, 1997, ENVIRON CONSERV, V24, P338 MOEN R, 1997, ECOLOGY, V78, P505 MWALYOSI RBB, 1992, J APPL ECOL, V29, P581 NEWMARK WD, 1996, CONSERV BIOL, V10, P1549 NYERGES AE, 1980, BROWSE AFRICA CURREN, P465 OBOT EA, 1989, ENVIRON CONSERV, V16, P165 ORIANS GH, 1979, ANAL ECOLOGICAL SYST PEDEN DG, 1987, J RANGE MANAGE, V40, P67 PERCIVAL SM, 1996, J APPL ECOL, V33, P979 PICKUP G, 1994, J APPL ECOL, V31, P231 PICKUP G, 1997, J APPL ECOL, V34, P657 PRATT DJ, 1966, J APPL ECOL, V3, P369 PRESTON RE, 1992, PROGR HUMAN GEOGRAPH, V16, P523 PRINS HHT, 1992, ENVIRON CONSERV, V19, P117 RUNYORO VA, 1995, SERENGETI, V2, P146 SABERWAL VK, 1996, CONSERV BIOL, V10, P741 SCHOENER TW, 1983, AM NAT, V121, P608 SENFT RL, 1983, J RANGE MANAGE, V36, P553 SENFT RL, 1985, J RANGE MANAGE, V38, P295 SENFT RL, 1985, J RANGE MANAGE, V38, P82 SHAFFER R, 1989, COMMUNITY EC EC STRU SHUGART HH, 1998, TERRESTRIAL ECOSYSTE SINCLAIR ARE, 1985, CAN J ZOOL, V63, P987 SMITH MS, 1988, MODELING 3 APPROACHE SOULE ME, 1979, BIOL CONSERV, V15, P259 SPENCER P, 1973, NOMADS ALLIANCE SYMB STEVENS S, 1997, CONSERVATION CULTURA TERMAN MR, 1997, LANDSCAPE URBAN PLAN, V38, P183 TURNER MD, 1998, J BIOGEOGR, V25, P669 TURNER MD, 1998, J BIOGEOGR, V25, P683 TURNER MG, 1993, ECOL MODEL, V69, P163 WARD D, 1998, J ARID ENVIRON, V40, P357 WEBER GE, 1998, J APPL ECOL, V35, P687 WESTERN D, 1975, E AFR WILDL J, V13, P265 WESTERN D, 1979, HUM ECOL, V7, P75 WESTERN D, 1981, AFR J ECOL, V19, P7 WESTERN D, 1994, NATURAL CONNECTIONS WESTERN D, 1994, NATURAL CONNECTIONS, P15 WETTERER JK, 1989, THEOR POPUL BIOL, V36, P267 ZAVALA MA, 1997, LANDSCAPE URBAN PLAN, V38, P213 0921-2973 Landsc. Ecol.ISI:000168194400002Univ Calif Davis, Dept Anthropol, Ecol Grad Grp, Davis, CA 95616 USA. Coppolillo, PB, Wildlife Conservat Soc, Living Landscapes Program Int Conservat, So Blvd, Bronx, NY 10460 USA.English |7/Corace, R. G. Flaspohler, D. J. Shartell, L. M.2009Geographical patterns in openland cover and hayfield mowing in the Upper Great Lakes region: implications for grassland bird conservation309-323Landscape Ecology243bobolink conservation planning grassland birds hayfields midwest michigan minnesota wisconsin reserve program field agricultural landscapes habitat quality united-states crp fields land-use abundance density north associationsMarPopulations of many grassland bird species such as Grasshopper Sparrow (Ammodramus savannarum), Henslow's Sparrow (A. henslowii), and Bobolink (Dolichonyx oryzivorus) have experienced considerable declines over the last century. To foster multi-species grassland bird conservation in the Upper Great Lakes (UGL) states of Michigan, Minnesota, and Wisconsin, we quantified geographic patterns within three sub-regional zones (e.g., North, Central, and South) of the UGL. Patterns of interest included the distribution and abundance of openland cover type (including managed pasture-hayland), the distribution, phenology, habitat affinity, and long-term population trends of ten grassland bird species, and (in particular) the geographic patterns in hayfield mowing and the temporal changes in hayfield cover. Approximately 10, 38, and 53% of the UGL openland was proportioned in the North, Central, and South zones, respectively. The distribution of hayland also varied by zone: North, 17%; Central, 46%; and South, 37%. In the central portion of the UGL where the greatest area is devoted to hay production, alfalfa-more intensively managed than mixed-grass hay-predominates. Although we found significance differences (P < 0.05) in hayfield mowing intensity between zones (with the majority of land under relatively low-intensity mowing found in the North Zone, particularly the Upper Peninsula of Michigan) no strong relationships were found between hayfield mowing patterns, other land cover-land use variables, and bird population trends at finer scales of study. Nonetheless, we suggest that the geographic patterns illustrated here provide useful information for grassland bird conservation planning across the UGL.://000263419500002-408EY Times Cited:0 Cited References Count:54 0921-2973ISI:000263419500002Corace, RG US Fish & Wildlife Serv, 1674 Refuge Entrance Rd, Seney, MI 49883 USA US Fish & Wildlife Serv, Seney, MI 49883 USA Michigan Technol Univ, Sch Forest Resources & Environm Sci, Houghton, MI 49931 USADoi 10.1007/S10980-008-9306-8English ^|7Coreau, A. Martin, J. L.2007rMulti-scale study of bird species distribution and of their response to vegetation change: a Mediterranean example747-764Landscape Ecology225scale land-use change landscape terrestrial bird community variance decomposition vegetation composition and structure island environment relationships land abandonment landscape ecology habitat community consequences abundance dynamics forestsMay~Land use changes operate at different scales. They trigger a cascade of effects that simultaneously modify the composition or structure of the landscape and of the local vegetation. Mobil animals, and birds in particular, can respond quickly to such multi-scalar changes. We took advantage of a long term study on the response of songbirds to land-use changes on four Mediterranean islands in Corsica and Sardinia to explore the benefits of a multi-scale analysis of the relationships between songbird distribution, vegetation structure and landscape dynamics. Field data and aerial photographs were used to describe the vegetation at three different scales. Birds were censused by point counts. We used statistical variance decomposition to study how bird distribution and vegetation at various scales were linked. We analysed multi-scale vegetation changes (floristic composition, plot vegetation type, and landscape structure) and their consequences on bird distribution with multivariate and non-parametrical tests. The distribution of most species was linked to at least two spatial scales. The weight of a given scale was consistent with life-history traits for species whose biology was well-known. In the examples studied, vegetation composition, vegetation type and landscape changes that resulted from land abandonment negatively affected birds depending on open or heterogeneous areas. Our results emphasize that multi-scale analyses can greatly enhance our understanding of bird distribution and of their changes. Management of these populations should take into account measures at various spatial scales depending on the sensitivity of the species.://000246111800009-162TG Times Cited:2 Cited References Count:49 0921-2973ISI:000246111800009xMartin, JL Cefe, Umr 5175, 1919 Route Mende, F-34293 Montpellier 5, France Cefe, Umr 5175, F-34293 Montpellier 5, FranceDoi 10.1007/S10980-006-9074-2English#|? Cornell, K. L. Donovan, T. M.2010rEffects of spatial habitat heterogeneity on habitat selection and annual fecundity for a migratory forest songbird109-122Landscape Ecology251Understanding how spatial habitat patterns influence abundance and dynamics of animal populations is a primary goal in landscape ecology. We used an information-theoretic approach to investigate the association between habitat patterns at multiple spatial scales and demographic patterns for black-throated blue warblers (Dendroica caerulescens) at 20 study sites in west-central Vermont, USA from 2002 to 2005. Sites were characterized by: (1) territory-scale shrub density, (2) patch-scale shrub density occurring within 25 ha of territories, and (3) landscape-scale habitat patterns occurring within 5 km radius extents of territories. We considered multiple population parameters including abundance, age ratios, and annual fecundity. Territory-scale shrub density was most important for determining abundance and age ratios, but landscape-scale habitat structure strongly influenced reproductive output. Sites with higher territory-scale shrub density had higher abundance, and were more likely to be occupied by older, more experienced individuals compared to sites with lower shrub density. However, annual fecundity was higher on sites located in contiguously forested landscapes where shrub density was lower than the fragmented sites. Further, effects of habitat pattern at one spatial scale depended on habitat conditions at different scales. For example, abundance increased with increasing territory-scale shrub density, but this effect was much stronger in fragmented landscapes than in contiguously forested landscapes. These results suggest that habitat pattern at different spatial scales affect demographic parameters in different ways, and that effects of habitat patterns at one spatial scale depends on habitat conditions at other scales.!://WOS:000273479100009Times Cited: 0 0921-2973WOS:00027347910000910.1007/s10980-009-9405-1/?AJean-Jacques Corre1991uThe sand dunes and their vegetation along the Mediterranean coast of France. Their likely response to climatic change65-75Landscape Ecology61/2OClimate change, sand dunes, wash-over, vegetation, Mediterranean, Golfe du LionThe Golfe du Lion is mainly bordered by low and narrow sand dunes. Since about four decades, 1/3 of its shoreline has been receding, while 1/3 has been prograding and another 1/3 is stable. Several types of dunes may be described mainly depending on storms, high wind frequencies and sand grain size. Vegetation on dune system is distributed along a primary gradient according to sand stability and soil development, and a secondary gradient along slope of dune according to a seasonal cycle of fresh and salt phreatic water level. Global changes in climate may influence these geomorphological and biological structures mainly through: - Winter minimum temperatures changing the distribution of several plant species, especially in the middle - Frequent high storms which cause damages to the front of the dune systems and disrupt the shore. Changes in dune ecosystems will be cyclic so these tendencies will be obvious only upon a long term period. <7 Corry, R. C.2005hCharacterizing fine-scale patterns of alternative agricultural landscapes with landscape pattern indices591-608Landscape Ecology205Corn Belt; data resolution; FRAGSTATS; Iowa; landscape design; landscape metrics; planning; small mammals FOREST LANDSCAPE; HABITAT; METRICS; ECOLOGY; USA; FRAGMENTATION; CONNECTIVITY; OREGONArticleJul&Landscape pattern indices are common tools of landscape ecologists, affording comparisons of different study areas, or the same study area at different times. Since the advent of popular index-calculating software, more landscapes can be analyzed in short amounts of time, yet the behaviour of landscape pattern indices can vary for different contexts or data characteristics, complicating interpretation. I applied a selected set of landscape pattern indices to fine-resolution (3 m) data representing a highly fragmented landscape - Corn Belt Iowa agriculture - to investigate the performance of landscape pattern indices. Indices measured pattern attributes that affect the viability of small mammal populations, namely habitat proportion and connectivity and landscape grain size and heterogeneity. Results showed that the performance of indices for fine-resolution data can be highly variable, depending upon data and contextual issues like the presence of linear elements and the amount of habitat. For these Corn Belt landscapes good habitat proportions and patch sizes were small (commonly less than 10% and less than 1 ha, respectively), and connectivity was variable depending on the measure. Aggregation and mean nearest neighbour indices performed better than other connectivity indices. Fine-resolution data representing highly fragmented landscapes can raise difficulties for indices of landscape configuration. Landscape pattern indices require improvement to perform better for increasingly available fine-resolution data representing common landscape types.://000232205600008 JISI Document Delivery No.: 969AK Times Cited: 0 Cited Reference Count: 44 Cited References: BUREL F, 1998, ACTA OECOL, V19, P47 CARDILLE JA, 2001, LEARNING LANDSCAPE E, P85 COOK EA, 2002, LANDSCAPE URBAN PLAN, V58, P269 CORRY RC, IN PRESS LANDSCAPE U CORRY RC, 1998, P 4 INT C PREC AGR A, P547 CORRY RC, 2002, INTEGRATING LANDSCAP, P92 CORRY RC, 2004, LANDSCAPE REV, V9, P86 CRESSIE NAC, 1993, STAT SPATIAL DATA FAUTH PT, 2000, LANDSCAPE ECOL, V15, P621 FORMAN RTT, 1995, LAND MOSAICS FOSTER J, 1991, ECOLOGY, V72, P1358 FROHN RC, 1998, REMOTE SENSING LANDS GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HE HS, 2000, LANDSCAPE ECOL, V15, P591 JAEGER JAG, 2000, LANDSCAPE ECOL, V15, P115 LAWLER JJ, 2002, LANDSCAPE ECOL, V17, P223 LEITAO AB, 2002, LANDSCAPE URBAN PLAN, V59, P65 LI HB, 2004, LANDSCAPE ECOL, V19, P389 LUDWIG JA, 1999, ISSUES LANDSCAPE ECO, P59 MCGARIGAL K, 1995, FRAGSTATS SPATIAL PA MOSER D, 2002, LANDSCAPE ECOL, V17, P657 NASSAUER JI, 2002, J SOIL WATER CONSERV, V57, A44 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 ONEILL RV, 1996, LANDSCAPE ECOL, V11, P169 PELES JD, 1999, LANDSCAPE ECOLOGY SM, P41 RIPPLE WJ, 1991, BIOL CONSERV, V57, P73 RISSER PG, 1984, LANDSCAPE ECOLOGY DI SANTELMANN MV, 2004, LANDSCAPE ECOL, V19, P357 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SCHWARTZ MW, 1997, CONSERVATION HIGHLY, P379 SCHWEIGER EW, 1999, LANDSCAPE ECOLOGY SM, P175 SPIES TA, 1994, ECOL APPL, V4, P555 TAYLOR PD, 1993, OIKOS, V68, P571 THOMPSON CM, 2002, LANDSCAPE ECOL, V17, P569 TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 TURNER MG, 2001, LANDSCAPE ECOLOGY TH WAIDE JB, 1995, PRELIMINARY MASTER A WICKHAM JD, 1997, PHOTOGRAMM ENG REM S, V63, P397 WIENS JA, 1989, FUNCT ECOL, V3, P385 WU JG, 2002, LANDSCAPE ECOL, V17, P355 WU JG, 2004, LANDSCAPE ECOL, V19, P125 0921-2973 Landsc. Ecol.ISI:000232205600008Univ Guelph, Sch Environm Design & Rural Dev, Guelph, ON N1G 2W1, Canada. Corry, RC, Univ Guelph, Sch Environm Design & Rural Dev, Guelph, ON N1G 2W1, Canada. rcorry@uoguelph.caEnglishW|?4dCosentino, Bradley J. Schooley, Robert L. Bestelmeyer, Brandon T. Kelly, Jeffrey F. Coffman, John M.2014pConstraints and time lags for recovery of a keystone species (Dipodomys spectabilis) after landscape restoration665-675Landscape Ecology294AprHabitat restoration is typically focused on reestablishing suitable conditions at a local scale, but landscape constraints may be important for keystone species with limited dispersal. We tested for time lags and examined the relative importance of local and landscape constraints on the response of the banner-tailed kangaroo rat (Dipodomys spectabilis) to restoration of Chihuahuan Desert grasslands in New Mexico, USA. Dipodomys spectabilis is a keystone species that creates habitat heterogeneity and modifies the structure of plant and animal communities. We selected 21 sites and compared density of D. spectabilis between areas treated with herbicide to control shrubs (treated areas) and paired untreated areas. We evaluated whether density of D. spectabilis depended on treatment age, local habitat quality (vegetation and soil structure), and landscape factors (treatment area and spatial connectivity). Density was greater at treated areas than at untreated areas due to a direct effect of reduced shrub cover. However, the response of D. spectabilis to restoration was lagged by a decade or more. Structural equation modeling indicated the time lag reflected a dispersal constraint as opposed to a temporal change in habitat quality. This inference was corroborated by a positive relationship between density at treated areas and connectivity to source populations. Our results indicate that density of D. spectabilis depended strongly on the spatial configuration of treated areas, which supports a landscape mosaic approach to restoration. If keystone species commonly exhibit limited dispersal ability, landscape constraints may be broadly important for shaping ecosystem structure and function after habitat restoration.!://WOS:000333533800009Times Cited: 1 0921-2973WOS:00033353380000910.1007/s10980-014-0003-5V|? BCosentino, Bradley J. Schooley, Robert L. Phillips, Christopher A.2010vWetland hydrology, area, and isolation influence occupancy and spatial turnover of the painted turtle, Chrysemys picta 1589-1600Landscape Ecology2510DecHabitat area and isolation have been useful predictors of species occupancy and turnover in highly fragmented systems. However, habitat quality also can influence occupancy dynamics, especially in patchy systems where habitat selection can be as important as stochastic demographic processes. We studied the spatial population dynamics of Chrysemys picta (painted turtle) in a network of 90 wetlands in Illinois, USA from 2007 to 2009. We first evaluated the relative influence of metapopulation factors (area, isolation) and habitat quality of focal patches on occupancy and turnover. Next, we tested the effect of habitat quality of source patches on occupancy and turnover at focal patches. Turnover was common with colonizations (n = 16) outnumbering extinctions (n = 10) between the first 2 years, and extinctions (n = 16) outnumbering colonizations (n = 3) between the second 2 years. Both metapopulation and habitat quality factors influenced C. picta occupancy dynamics. Colonization probability was related positively to spatial connectivity, wetland area, and habitat quality (wetland inundation, emergent vegetation cover). Extinction probability was related negatively to wetland area and emergent vegetation cover. Habitat quality of source patches strongly influenced initial occupancy but not turnover patterns. Because habitat quality for freshwater turtles is related to wetland hydrology, a change from drought to wet conditions during our study likely influenced distributional shifts. Thus, effects of habitat quality of source and focal patches on occupancy can vary in space and time. Both metapopulation and habitat quality factors may be needed to understand occupancy dynamics, even for species exhibiting patchy population structures.!://WOS:000283371000010Times Cited: 0 0921-2973WOS:00028337100001010.1007/s10980-010-9529-3|?J BCosentino, Bradley J. Schooley, Robert L. Phillips, Christopher A.2011DConnectivity of agroecosystems: dispersal costs can vary among crops371-379Landscape Ecology263MarKnowledge of how habitat heterogeneity affects dispersal is critical for conserving connectivity in current and changing landscapes. However, we generally lack an understanding of how dispersal costs and animal movements vary among crops characteristic of agroecosystems. We hypothesized that a physiological constraint, desiccation risk, influences movement behavior among crops and other matrix habitats (corn, soybean, forest, prairie) in Ambystoma tigrinum (tiger salamander) in Illinois, USA. In a desiccation experiment, salamanders were added to enclosures in four replicate plots of each matrix habitat, and water loss was measured every 12 h for 48 h. Changes in water loss were examined using a linear mixed model. Water loss varied among treatments, over time, and there was a significant treatment-time interaction. Water loss was greater in corn and prairie than in forest and soybean. To assess whether salamanders move through matrix habitats that minimize desiccation, we tracked movements of individuals released on edges between habitats for two treatment combinations: soybean-corn, and soybean-prairie. As predicted based on our desiccation experiment, movements were oriented towards soybean in both cases. Thus, variation in desiccation risk among matrix habitats likely influenced movement decisions by salamanders, although other factors such as predation risk could have contributed to habitat choice. We argue that conceptualizing dispersal cost as uniformly high in all crop types is too simplistic. Estimating crop-specific dispersal costs and movement patterns may be necessary for constructing effective measures of landscape connectivity in agroecosystems.!://WOS:000288808100006Times Cited: 1 0921-2973WOS:00028880810000610.1007/s10980-010-9563-1|?, 2Costanza, Jennifer K. Moody, Aaron Peet, Robert K.2011PMulti-scale environmental heterogeneity as a predictor of plant species richness851-864Landscape Ecology266JuluEcological theory predicts a positive influence of local-, landscape-, and regional-scale spatial environmental heterogeneity on local species richness. Therefore, knowing how heterogeneity measured at a variety of scales relates to local species richness has important implications for conservation of biological diversity. We took a statistical modeling approach to determine which metrics of heterogeneity measured at which scales were useful predictors of local species richness, and whether the heterogeneity-local richness relationship was always positive. Local plant species richness data came from 400-m(2) vegetation plots in North and South Carolina, USA. At each of four scales from within plots to across regions, we used either GIS or field data to calculate measures of heterogeneity from abiotic environmental variables, vegetation productivity data, and land cover classifications. Among all predictors at all scales, we found that no measure of heterogeneity was a better predictor of local richness than mean pH within plots. However, at scales larger than within plots, measures of heterogeneity were correlated most strongly with local richness, and each of the three classes of variables we used had a distinct scale at which it performed better than the others. These results highlight the fact that ecological processes occurring across multiple scales influence local species richness differently. In addition, relationships between heterogeneity and richness were usually, though not always, positive, underscoring the importance of processes that occur at a variety of scales to local biodiversity conservation and management.!://WOS:000291485400007Times Cited: 0 0921-2973WOS:00029148540000710.1007/s10980-011-9613-3R?hCostanza, R. T. Maxwell1994AResolution and predictability: An approach to the scaling problem47-57Landscape Ecology91Nspatial scaling, predictability, resolution, GIS, fractals, landscape modeling |7 Costanza, R. Maxwell, T.1994BResolution and Predictability - an Approach to the Scaling Problem47-57Landscape Ecology91Ascaling predictability resolution gis fractals landscape modelingMarVWe analyzed the relationship between resolution and predictability and found that while increasing resolution provides more descriptive information about the patterns in data, it also increases the difficulty of accurately modeling those patterns. There are limits to the predictability of natural phenomenon at particular resolutions, and ''fractal-like'' rules determine how both ''data'' and ''model'' predictability change with resolution. We analyzed land use data by resampling map data sets at several different spatial resolutions and measuring predictability at each. Spatial auto-predictability (P(a)) is the reduction in uncertainty about the state of a pixel in a scene given knowledge of the state of adjacent pixels in that scene, and spatial cross-predictability (P(c)) is the reduction in uncertainty about the state of a pixel in a scene given knowledge of the state of corresponding pixels in other scenes. P(a) is a measure of the internal pattern in the data while P(c) is a measure of the ability of some other ''model'' to represent that pattern. We found a strong linear relationship between the log of P(a) and the log of resolution (measured as the number of pixels per square kilometer). This fractal-like characteristic of ''self-similarity'' with decreasing resolution implies that predictability may be best described using a unitless dimension that summarizes how it changes with resolution. While P(a) generally increases with increasing resolution (because more information is being included), P(c) generally falls or remains stable (because it is easier to model aggregate results than fine grain ones). Thus one can define an ''optimal'' resolution for a particular modeling problem that balances the benefit in terms of increasing data predictability (P(a)) as one increases resolution, with the cost of decreasing model predictability (P(c)).://A1994NC71800005-Nc718 Times Cited:43 Cited References Count:0 0921-2973ISI:A1994NC71800005hCostanza, R Univ Maryland,Maryland Int Inst Ecol Econ,Ctr Environm & Estuarine Studies,Solomons,Md 20688English |70Cote, D. Kehler, D. G. Bourne, C. Wiersma, Y. F.2009>A new measure of longitudinal connectivity for stream networks101-113Landscape Ecology241 aquatic connectivity barriers connectivity indices dendritic ecological networks fish passage fragmentation river networks watersheds landscape connectivity swimming performances extinction risk fishes habitat fragmentation conservation barriers ecology restorationJanHabitat connectivity is a central factor in shaping aquatic biological communities, but few tools exist to describe and quantify this attribute at a network scale in riverine systems. Here, we develop a new index to quantify longitudinal connectivity of river networks based on the expected probability of an organism being able to move freely between two random points of the network. We apply this index to two fish life histories and evaluate the effects of the number, passability, and placement of barriers on river network connectivity through the use of simulated dendritic ecological networks. We then extend the index to a real world dendritic river system in Newfoundland, Canada. Our results indicate that connectivity in river systems, as represented by our index, is most impacted by the first few barriers added to the system. This is in contrast to terrestrial systems, which are more resilient to low levels of connectivity. The results show a curvilinear relationship between barrier passability and structural connectivity. This suggests that an incremental improvement in passability would result in a greater improvement to river network connectivity for more permeable barriers than for less permeable barriers. Our analysis of the index in simulated and real river networks also showed that barrier placement played an important role in connectivity. Not surprisingly, barriers located near the river mouth have the greatest impact on fish with diadromous life histories while those located near the center of the river network have the most impact on fish with potadromous life histories. The proposed index is conceptually simple and sufficiently flexible to deal with variations in river structure and biological communities. The index will enable researchers to account for connectivity in habitat studies and will also allow resource managers to characterize watersheds, assess cumulative impacts of multiple barriers and determine priorities for restoration.://000262506000009-395EI Times Cited:0 Cited References Count:58 0921-2973ISI:000262506000009Cote, D Terra Nova Natl Pk, Gen Delivery, Glovertown, NF A0G 2L0, Canada Atlantic Serv Ctr, Halifax, NS B3J 1S9, Canada Mem Univ, Dept Biol, St John, NF A1B 3X9, CanadaDoi 10.1007/S10980-008-9283-YEnglishq<7TCoughlan, J. C. Running, S. W.1997oRegional ecosystem simulation: A general model for simulating snow accumulation and melt in mountainous terrain119-136Landscape Ecology123snow; model; regional simulation; forest; remote sensing ENERGY EXCHANGE; WATERSHED SCALE; ALPINE REGION; SIERRA-NEVADA; FOREST; BALANCE; SURFACE; CLIMATE; TEMPERATUREArticleJun& A general snow accumulation and melt model was developed to (1) determine how accurately snow accumulation and ablation can be modeled over heterogeneous landscapes with routinely available climatologic, topographic. and vegetation data, and (2) improve estimates of annual forest snow hydrology for point and regional calculations of annual forest productivity. The snow model was designed to operate within the Regional Hydroecological Simulation System (RHESSys), a GIS based modeling system to manage spatial data for distributed computer simulations on watershed scales. One feature of the RHESSys Snow Model (RSM) is it can use satellite derived forest leaf area index (LAI) to represent catchment forest cover; difficult to obtain in adequate cover and resolution by any other means. The model was tested over 3 water years (October to September) with data recorded by 10 snow telemetry stations (SNOTEL) in 5 slates ranging in meso-climate and elevations from a coastal Oregon site (1067 m) to a continental Colorado site (3261 m). Predictions for the 10 sites were made with identical parameter values and only site climate varied for all sites, The average difference between observed and predicted snow depletion dates for all sites and water years was 6.2 days and 8 of the 30 simulations were within +/-2 days (R-2 = 0.91). Radiation melt was the dominate snow ablation component at the Colorado site where sublimation was 10% (LAI = 0) to 20% (LAI = 6) of snow loss while air temperature was the dominate component at the Oregon site with sublimation reduced to 1% (LAI = 0) to 6% (LAI = 6) of snow loss. LAI had a greater effect determining snow depletion than site aspect, Aspect increased in importance if the snow depletion occurred during early spring when solar insolation differences between hillslopes is greater than in the late spring. An accurate prediction of daily snowpack water equivalent (SWE) was not a strong determinant for making an accurate prediction of snowpack depletion date. Predicted snowpack depletion dates were more sensitive to timing when the snowpack reached an isothermal condition. Daily estimates of SWE were most sensitive to correctly estimating snowfall from SNOTEL data. This means that for purposes of determining the snow depletion dates which are useful for forest ecosystem modeling, tracking SWE is less important then triggering snowmelt. Comparisons of simulations to published snow depletion dates show that RSM predicted the relative ranking and magnitude of depletion for different combinations of forest cover, elevation, and aspect.://A1997XV63400002 ISI Document Delivery No.: XV634 Times Cited: 16 Cited Reference Count: 49 Cited References: *SOIL CONS SERV, 1985, SNOTEL SYST COOP US *US ARM CORP ENG, 1956, SNOW HYDR SUMM REP S AGUADO E, 1985, WATER RESOUR RES, V21, P1049 ANDERSON EA, 1968, WATER RESOUR RES, V4, P19 ANDERSON EA, 1973, NOAA PUBLICATION BAKER DG, 1990, J APPL METEOROL, V29, P179 BAKER FS, 1944, ECOL MONOGR, V14, P223 BAND LE, 1991, ECOL MODEL, V56, P171 BERRIS SN, 1987, WATER RESOUR RES, V23, P135 BLACK TA, 1981, MODELING WATER BALAN BRISTOW KL, 1984, AGR FOREST METEOROL, V31, P159 BUFFO J, 1972, PNW142 USFS COUGHLAN JC, 1996, USE REMOTE SENSING M, P135 FRIEND AD, 1993, ECOLOGY, V74, P792 GARY HL, 1967, RM93 USFS GARY HL, 1982, RM17 USFS GILES DG, 1985, CAN J FOREST RES, V15, P107 GOLDING DL, 1978, CAN J FOREST RES, V8, P380 GOLDING DL, 1986, WATER RESOUR RES, V22, P1931 GRAY DM, 1987, CAN J EARTH SCI, V24, P1760 HARDY JP, 1990, 58 ANN M W SNOW C, P23 HUNGERFORD RD, 1990, INT414 USFS HUNT ER, 1991, TREE PHYSIOL, V9, P161 KAUFMANN MR, 1982, RM238 USFS KNIGHT DH, ECOL MONOGR, V55, P29 LEAF CA, 1973, RM107 USFS LEAF CA, 1973, RM99 USFS MALE DH, 1981, WATER RESOUR RES, V17, P609 MARKS D, 1992, WATER RESOUR RES, V28, P3029 MARKS D, 1992, WATER RESOUR RES, V28, P3043 MCLEOD SD, 1988, CAN J FOREST RES, V18, P346 MCMURTRIE R, 1992, FOREST ECOL MANAG, V5, P243 MOTOYAMA H, 1990, J APPL METEOROL, V29, P1104 NEMANI R, 1993, INT J REMOTE SENS, V14, P2519 NEMANI RR, 1993, ENV MODELING GIS, P296 PANICONI C, 1993, WATER RESOUR RES, V29, P1601 PREVOST M, 1991, CAN J FOREST RES, V21, P1 PRICE AG, 1988, J HYDROL, V101, P145 RUNNING SW, 1984, AGR FOREST METEOROL, V23, P267 RUNNING SW, 1987, CAN J FOREST RES, V17, P472 RUNNING SW, 1988, ECOL MODEL, V42, P125 RUNNING SW, 1991, CLIMATIC CHANGE, V19, P349 RUNNING SW, 1991, TREE PHYSIOL, V9, P149 RYAN MG, IN PRESS EFFECTS CLI SOLOMON RM, 1976, RM174 USFS TROENDLE CA, 1980, APPROACH WATER RES E TROENDLE CA, 1985, WATER RESOUR RES, V21, P1915 WARING RH, 1979, SCIENCE, V204, P1380 WARING RH, 1985, FOREST ECOSYSTEM CON 0921-2973 Landsc. Ecol.ISI:A1997XV63400002mCoughlan, JC, NASA,AMES RES CTR,JOHNSON CONTROLS WORLD SERV,NASA AMES OPERAT,MS 242-4,MOFFETT FIELD,CA 94035.English]~?VCoulon, A. Morellet, N. Goulard, M. Cargnelutti, B. Angibault, J. M. Hewison, A. J. M.2008xInferring the effects of landscape structure on roe deer (Capreolus capreolus) movements using a step selection function603-614Landscape Ecology235In this study, we sought to understand how landscape structure affects roe deer movements within their home-range in a heterogeneous and fragmented agricultural system of south-western France. We analysed the movements of 20 roe deer fitted with GPS collars which recorded their locations every 2-6 h over several months (mean = 9 months). Based on empirical observations and previous studies of roe deer habitat use, we hypothesised that roe deer should avoid buildings and roads, move preferentially along valley bottoms and through the more wooded areas of the landscape. To test these hypotheses we paired each observed movement step with 10 random ones. Using conditional logistic regression, we modelled a step selection function, which represents the probability of selecting a given step as a function of these landscape variables. The selected model indicated that movements were influenced by all the tested landscape features, but not always in the predicted direction: our results suggested that roe deer tend to avoid buildings, roads, valley bottoms and possibly the more wooded areas (although the latter result should be interpreted with caution, as it may be influenced by a bias in the rate of GPS fix acquisition in woods). The distances to buildings and to roads were the most influential variables in the model, suggesting that the avoidance of potential sources of disturbance may be a key factor in determining ranging behaviour of roe deer in human dominated landscapes."://WOS:000254964600010 Times Cited: 0WOS:000254964600010(10.1007/s10980-008-9220-0|ISSN 0921-2973Y|? ECourbin, Nicolas Fortin, Daniel Dussault, Christian Courtois, Rehaume2009pLandscape management for woodland caribou: the protection of forest blocks influences wolf-caribou co-occurrence 1375-1388Landscape Ecology2410Various management plans have been developed to mitigate the effects of human activities on threatened woodland caribou (Rangifer tarandus caribou) populations. Most plans do not account for the behavior of wolves (Canis lupus), their main predator. The success of caribou recovery plans may nonetheless depend on how landscape management shapes wolf-caribou interactions. We evaluated the species-specific responses of caribou and wolves to a management plan in Qu,bec, and assessed its impact on the probability of wolf-caribou co-occurrence. Landscape management consisted of the protection of large forest blocks, and the spatial aggregation of cutblocks. Based on telemetry data, we modeled animal-habitat spatial relationships with resource selection functions, and then estimate the relative probability of wolf-caribou co-occurrence. We found that caribou selected mature conifer forests with lichen. Wolves selected mixed and deciduous stands. Caribou avoided roads and cutblocks, while wolves selected them, which resulted in a relatively low probability of co-occurrence in harvested areas. Concurrent habitat selection by the two species was such that the highest probability of wolf-caribou co-occurrence took place in protected forest blocks (PB) from December to May. For efficient mitigation measures, the location of PBs should be selected while accounting for differences in habitat selection between wolf and caribou. The blocks should include mature conifer forests with lichen, minimize the abundance of mixed and deciduous stands, and be far from roads and cutblocks. Consideration of predator behavior can improve suitability of landscape management plans for the long-term persistence of threatened prey populations under top-down control.%://BIOSIS:PREV201000014112Times Cited: 0 0921-2973BIOSIS:PREV201000014112:10.1007/s10980-009-9389-x<7Cousins, S. A. O.2001gAnalysis of land-cover transitions based on 17th and 18th century cadastral maps and aerial photographs41-54Landscape Ecology161bedrock continuity grassland land use change rectification soil species richness transition matrices SEMINATURAL PASTURES LANDSCAPE DYNAMICS PLANTS FRAGMENTATION GRASSLANDS STABILITY PATTERNS ESTONIA HISTORYArticleJanmThis paper explores the possibility of using non-geometric cadastral maps from the 17th and 18th century together with aerial photographs from 1945 and 1981 to analyse land-cover change in south-east Sweden. Habitats rich in plant species in the European rural landscape seem to be correlated with a long continuity of management. Accurate spatial data from historical data sources are fundamental to understand patterns of vegetation and biodiversity in the present-day landscape. However, traditional methods for rectification of non-geometric maps using corresponding points from orthophotos or modern maps are not satisfying, as internal inaccuracies will remain in the maps. This study presents a method to rectify the maps by local warping, thereby eliminating geometrical irregularities. Further, the land-cover changes were calculated and presented as transition matrices. The extent of arable fields and grasslands were analysed in relation to soil characteristics and continuity of management. The results show a dynamic relation between grassland and arable field, albeit the overall proportions remained almost the same between 17th and 18th centuries: 60% grassland to 32% arable field. The most substantial changes in land-cover were prior to 1945. Today there is 18% grasslands left in the study area, while 56% of the land-cover is arable field. Approximately 8% of present-day land-cover is semi-natural grassland 300 years of age or more. Compared to 300 years ago there is only 1% grassland left on peat and 2% on clay. In contrast, grassland covers associated with bare bedrock have been fairly stable in size. All semi-natural grasslands with a long continuity of management were situated on shallow soils, less than 50 cm depth. The major conclusions from this study are that (i) correctly rectified, old maps are very useful to address questions of land-cover changes in historical time, (ii) general trends in land use over 300 years in this hemi-boreal landscape seem to underestimate the full dynamics of land use change, and (iii) only a small proportion of the semi-natural grassland area had a 300 year continuity of management.://000167389900004 ISI Document Delivery No.: 409NN Times Cited: 28 Cited Reference Count: 36 Cited References: AAVIKSOO K, 1993, LANDSCAPE ECOL, V8, P287 AMBROSIANI B, 1964, THESIS UPPSALA U SWE AUSTRHEIM G, 1999, BIOL CONSERV, V87, P369 BERNES C, 1994, BIOL DIVERSITY SWEDE COUSINS SAO, UNPUB DISTRIBUTION P COUSINS SAO, 1998, LANDSCAPE URBAN PLAN, V41, P183 CRAWLEY MJ, 1990, PHILOS T ROY SOC B, V330, P125 EASTMAN JR, 1997, IDRISI WINDOWS USERS ERIKSSON A, 1995, ECOGRAPHY, V18, P310 ERIKSSON A, 1997, NORD J BOT, V17, P469 ERIKSSON A, 1998, ECOGRAPHY, V21, P35 ERIKSSON A, 1999, THESIS STOCKHOLM U S ERIKSSON O, 1996, OIKOS, V77, P248 FAHRIG L, 1998, ECOL MODEL, V105, P273 FRY G, 1991, BRIT ECOLOGICAL S, V3, P415 GILPIN M, 1994, THEOR POPUL BIOL, V46, P121 HARRISON S, 1999, ECOGRAPHY, V22, P225 HERBEN T, 1993, J VEG SCI, V4, P163 IHSE M, 1995, LANDSCAPE URBAN PLAN, V31, P21 KAIN RJP, 1992, CADASTRAL MAP SERVIC KULL K, 1991, J VEG SCI, V2, P711 LI BL, 1995, ECOL MODEL, V82, P247 LIDMARBERGSTROM K, 1995, GEOMORPHOLOGY, V12, P45 PARTEL M, 1999, LANDSCAPE ECOL, V14, P187 POSCHLOD P, 1998, ACTA BOT NEERL, V47, P27 RUDBERG S, 1961, GEOGRAPHY NORDEN, P27 SILVERTOWN J, 1993, J ECOL, V81, P465 SKOANES H, THESIS STOCKHOLM U S SPORRONG U, 1990, NATL ATLAS SWEDEN MA, P136 STEINBERG EK, 1998, SPATIAL ECOLOGY ROLE, P318 TOLLIN C, 1991, ATTEBACKAR ODEGARDEN USHER MB, 1981, VEGETATIO, V46, P11 VALVERDE T, 1997, J ECOL, V85, P193 WHITE MA, 1994, LANDSCAPE ECOL, V9, P191 WIDGREN M, 1983, STOCKHOLM STUDIES HU WIENS JA, 1995, MOSAIC LANDSCAPES EC, P1 0921-2973 Landsc. Ecol.ISI:000167389900004Stockholm Univ, Dept Phys Geog, SE-10691 Stockholm, Sweden. Cousins, SAO, Stockholm Univ, Dept Phys Geog, SE-10691 Stockholm, Sweden.English<7Cousins, S. A. O. Eriksson, O.2002qThe influence of management history and habitat on plant species richness in a rural hemiboreal landscape, Sweden517-529Landscape Ecology176alpha diversity beta diversity habitat history land use physical properties plant species richness SEMINATURAL PASTURES ABUNDANCE PATTERNS AERIAL PHOTOGRAPHS GRASSLANDS DIVERSITY BIOTOPE REMNANT SOIL SIZE AGEArticleOct?We explored patterns of plant species richness at different spatial scales in 14 habitats in a Swedish rural landscape. Effects of physical conditions, and relationships between species richness and management history reaching back to the 17 (th) century were examined, using old cadastral maps and aerial photographs. The most species-rich habitats were dry open semi- natural grasslands, midfield islets and road verges. Alpha diversity (species richness within sites) was highest in habitats on dry substrates (excluding bedrock with sparse pines) and beta diversity (species richness among sites) was highest in moist to wet habitats. Alpha and beta components of species richness tended to be inversely related among habitats with similar species richness. Management history influenced diversity patterns. Areas managed as grasslands in the 17 th and 18 th century harboured more species than areas outside the villages. We also found significant relationships between species richness and soil type. Silt proved to be the most species- rich topsoil (10- 20 cm) in addition to thin soils top of on green- or limestone bedrock. The variation in species richness due to local relief or form of the site also showed significant relationships, where flat surfaces had the highest number of species. In contrast, no significant relationship was found between species richness and aspect. Our study suggests that present- day diversity patterns are much influenced by management history, and that small habitat, e. g., road verges and midfield islets, are important for maintaining species richness.://000179774900003 ISI Document Delivery No.: 624RN Times Cited: 21 Cited Reference Count: 49 Cited References: 1992, ANGS HAGMARKER SODER *SURV DIV STAFF SO, 1993, USDA HDB, V18 AKERLUND A, 1996, THESIS STOCKHOLM U S ARONSSON M, 1995, SWEDISH RED DATA BOO AUSTRHEIM G, 1999, BIOL CONSERV, V87, P369 BAKKER JP, 1989, NATURE MANAGEMENT GR BERGLUND BE, 1991, ECOLOGICAL B, V41, P73 BERGLUND BE, 1996, PALAEOECOLOGICAL EVE BIRKELAND PW, 1999, SOILS GEOMORPHOLOGY BRUNNBERG L, 1995, QUATERNARIA A, V2 COLLINS SL, 1990, AM NAT, V135, P633 COUSINS SAO, IN PRESS LANDSCAPE U COUSINS SAO, 1998, LANDSCAPE URBAN PLAN, V41, P183 COUSINS SAO, 2001, ECOGRAPHY, V24, P461 COUSINS SAO, 2001, LANDSCAPE ECOL, V16, P41 DUCHAUFOUR P, 1982, PEDOLOGY ERIKSSON A, 1995, ECOGRAPHY, V18, P310 ERIKSSON A, 1997, NORD J BOT, V17, P469 ERIKSSON A, 1998, ECOGRAPHY, V21, P35 ERIKSSON O, 1996, OIKOS, V77, P248 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FRIES M, 1965, 84 GEOL SOC AM INC GOLDBERG DE, 1991, J ECOL, V79, P1013 GRACE JB, 1999, PERSPECT PLANT ECOL, V2, P1 HUSTON MA, 1994, BIOL DIVERSITY COEXI HUSTON MA, 1999, OIKOS, V86, P393 IHSE M, 1995, LANDSCAPE URBAN PLAN, V31, P21 KAIN RJP, 1992, CADASTRAL MAP SERVIC KIENAST F, 1993, LANDSCAPE ECOL, V8, P103 KOHN DD, 1994, J ECOL, V82, P367 KULL K, 1991, J VEG SCI, V2, P711 LENNARTSSON T, 1996, SYMB BOT UPSAL, V31, P169 LIDMARBERGSTROM K, 1995, GEOMORPHOLOGY, V12, P45 LINCOLN R, 1998, DICT ECOLOGY EVOLUTI MCLEAN EO, 1982, AGRONOMY, V9 NILSSON SG, 1992, ECOLOGICAL PRINCIPLE NORDERHAUG A, 2000, LANDSCAPE ECOL, V15, P201 OLSSON G, 1995, STUDIES HONOUR U MIL, P219 OLSSON M, 1999, EUR18991 SOIL RESOUR PARTEL M, 1999, ECOGRAPHY, V22, P153 PARTEL M, 1999, LANDSCAPE ECOL, V14, P187 POSCHLOD P, 1998, ACTA BOT NEERL, V47, P27 SCHLUTER D, 1993, SPECIES DIVERSITY EC TYLER G, 1996, VEGETATIO, V127, P215 WELINDER S, 1998, SVENSKA JORDBRUKETS WHITTAKER RH, 1975, COMMUNITIES ECOSYSTE WIKLANDER L, 1976, MARKLARA WILSON EO, 1994, NATURALIST ZOBEL M, 1992, OIKOS, V65, P314 0921-2973 Landsc. Ecol.ISI:000179774900003Stockholm Univ, Dept Phys Geog & Quaternary Geol, S-10691 Stockholm, Sweden. Stockholm Univ, Dept Bot, SE-10691 Stockholm, Sweden. Cousins, SAO, Stockholm Univ, Dept Phys Geog & Quaternary Geol, S-10691 Stockholm, Sweden.English<7(Cousins, S. A. O. Lavorel, S. Davies, I.2003Modelling the effects of landscape pattern and grazing regimes on the persistence of plant species with high conservation value in grasslands in south-eastern Sweden315-332Landscape Ecology183&disturbance LAMOS landscape history land use modelling Plant Functional Groups semi-natural grassland RURAL HEMIBOREAL LANDSCAPE EXTINCTION THRESHOLDS SEMINATURAL PASTURES SEEDLING RECRUITMENT VEGETATION RESPONSE POPULATION-DYNAMICS FRACTAL LANDSCAPES FUNCTIONAL TYPES SITE OCCUPANCY MANAGEMENTArticleAprMSemi-natural grasslands in Sweden are threatened by land-use change and lack of management with attendant risk to their biodiversity. We present a model to explore the effects of grazing frequency and intensity on plant species persistence, and the relative effects of grassland size and pattern. We used a landscape modelling platform, LAMOS (LAndscape MOdelling Shell), to design a landscape model of vegetation dynamics incorporating the effects of local succession, dispersal and grazing disturbance. Five plant functional groups (PFG), representing various combinations of persistence and dispersal character, light requirements and disturbance responses, were defined to model species dynamics. Based on old cadastral maps three different landscapes were designed representing specific time-layers, i.e., a historical (17th to 18th century), a pre-modern (1940s) and a present-day landscape. Simulations showed that a threshold was crossed when grasslands decreased in area to about 10 - 30% of the modelled area, and as a consequence the biomass of grassland-specific PFGs was strongly reduced. These competition sensitive groups did not persist in the model even with intense grazing in the present-day landscape, where grasslands occupy 11% of the total area. However, all grassland species would have been able to persist in the historical landscape, where grasslands occupied 59% of the total area, even without grazing. Our results suggest that continuous but low-intensity grazing is more positive for grassland PFGs than discontinuous but highly intensive grazing. This effect was particularly strong when the frequency and/or intensity of grazing dropped below a threshold of 20%. Simulations using three landscape maps designed to explore effects of further fragmentation and habitat loss showed that the spatial pattern of remaining grasslands is important for the persistence of grassland-specific PFG. The model presented here is an advance towards more realistic grazing models to explore the effects of prescribed grazing and landscape fragmentation on the persistence species or plant functional groups.://000183770600009 RISI Document Delivery No.: 694JD Times Cited: 17 Cited Reference Count: 92 Cited References: ANDREASSIAN B, 1997, ANN CARDIOL ANGEIOL, V46, P171 AUSTIN MP, 1999, ECOGRAPHY, V22, P465 AUSTRHEIM G, 1999, BIOL CONSERV, V87, P369 BAZZAZ FA, 1996, PLANTS CHANGING ENV BRUUN HH, 2000, ECOGRAPHY, V23, P641 BULLOCK JM, 2001, J APPL ECOL, V38, P253 CAMEL Y, 1999, PLANT ECOL, V145, P239 COLASANTI RL, 1993, FUNCT ECOL, V7, P169 COLLINS SL, 1998, SCIENCE, V280, P745 COUSINS SAO, 2001, ECOGRAPHY, V24, P461 COUSINS SAO, 2001, LANDSCAPE ECOL, V16, P41 COUSINS SAO, 2002, LANDSCAPE ECOL, V17, P517 DIAZ S, 2001, J APPL ECOL, V38, P497 DIAZ S, 2002, IN PRESS PROGR PROSP EHRLEN J, 2000, ECOLOGY, V81, P1667 EKSTAM U, 1988, ANGAR LT FORLAG EKSTAM U, 1997, GRASSLAND MANAGEMENT ERIKSSON A, 1995, ECOGRAPHY, V18, P310 ERIKSSON A, 1997, NORD J BOT, V17, P469 ERIKSSON A, 2000, J VEG SCI, V11, P245 ERIKSSON O, 1996, OIKOS, V77, P248 ERIKSSON O, 1999, BIOL CONSERV, V87, P319 ERIKSSON O, 2000, FOLIA GEOBOT, V35, P115 GITAY H, 1997, PLANT FUNCTIONAL TYP, P3 GRACE JB, 1999, PERSPECT PLANT ECOL, V2, P1 GRIME JP, 1979, PLANT STRATEGIES VEG GRIME JP, 2001, PLANT STRATEGIES VEG GRUBB PJ, 1977, BIOL REV, V52, P107 HANSKI I, 1999, OXFORD SERIES ECOLOG HANSSON M, 2000, J VEG SCI, V11, P31 HARPER JL, 1977, POPULATION BIOL PLAN HARRISON S, 1999, ECOGRAPHY, V22, P225 HOLLING CS, 1986, SUSTAINABLE DEV BIOS HULME PD, 1999, J APPL ECOL, V36, P886 HULME PE, 1996, J ECOL, V84, P609 HUNT LP, 2001, J APPL ECOL, V38, P238 HUSTON M, 1987, AM NAT, V130, P168 HUSTON MA, 1994, BIOL DIVERSITY COEXI JELTSCH F, 1997, J APPL ECOL, V34, P1497 JELTSCH F, 1997, J VEG SCI, V8, P177 KIVINIEMI K, 1999, OIKOS, V86, P241 KIVINIEMI K, 1999, THESIS STOCKHOLM U KULL K, 1991, J VEG SCI, V2, P711 LANDSBERG J, 1999, NUTR ECOLOGY HERBIVO, P752 LAVOREL S, 1997, TRENDS ECOL EVOL, V12, P474 LAVOREL S, 2000, P LANDSC FIR MOD WOR, P25 LENNARTSSON T, 1996, SYMB BOT UPSAL, V31, P170 LINDBORG R, 2002, CONSERV BIOL, V16, P683 LINDENMAYER DB, 2002, CONSERV BIOL, V16, P338 MCINTYRE S, 1999, CONSERV BIOL, V13, P1282 MCINTYRE S, 2000, MANAGEMENT SUSTAINAB, P92 MCINTYRE S, 2001, J ECOL, V89, P209 MEDAIL F, 1998, ACTA OECOL, V19, P263 MILNE BT, 1992, THEOR POPUL BIOL, V41, P337 MOLONEY KA, 1996, ECOLOGY, V77, P375 MONTALVO J, 1993, J VEG SCI, V4, P213 MOORE AD, 1990, J ENVIRON MANAGE, V31, P61 NOBLE IR, 1980, VEGETATIO, V43, P5 NOBLE IR, 1999, INTEGRATING HYDROLOG, P298 OPDAM P, 2002, LANDSCAPE ECOLOGY, V16, P767 PALMER MW, 1992, AM NAT, V139, P375 PARTEL M, 1999, LANDSCAPE ECOL, V14, P187 PAUSAS JG, 1999, J VEG SCI, V10, P717 PEART DR, 1989, J ECOL, V77, P236 PETTIT NE, 2001, AUSTRAL ECOL, V26, P22 PICKUP G, 1994, J APPL ECOL, V31, P231 PLOTNICK RE, 2002, ECOL MODEL, V147, P171 POSCHLOD P, 1998, ACTA BOT NEERL, V47, P27 PRACH K, 1997, OIKOS, V79, P201 REES M, 2001, J APPL ECOL, V38, P364 REYNOLDS JF, 1997, PLANT FUNCTIONAL TYP, P195 RUCKELSHAUS M, 1997, CONSERV BIOL, V11, P1298 RYSER P, 1995, FOLIA GEOBOT PHYTOTX, V30, P157 SCHIPPERS P, 2001, OIKOS, V95, P198 STERNBERG M, 2000, J APPL ECOL, V37, P224 STRYKSTRA RJ, 1998, ACTA BOT NEERL, V47, P57 SUDING KN, 2001, ECOLOGY, V82, P2133 TILMAN D, 1988, PLANT STRATEGIES DYN TILMAN D, 1994, NATURE, V371, P65 TURNBULL LA, 2000, OIKOS, V88, P225 VANDERMAAREL E, 1989, OIKOS, V56, P364 VANDORP D, 1997, LANDSCAPE ECOL, V12, P39 VESK PA, 2001, J APPL ECOL, V38, P897 WAHREN CHA, 1994, AUST J BOT, V42, P607 WEBER GE, 1998, J APPL ECOL, V35, P687 WEIBULL AC, 2002, THESIS SWEDISH U AGR WEIGAND T, 1996, VEGETATIO, V125, P169 WEINS JA, 1997, METAPOPULATION BIOL, P43 WITH KA, 1997, CONSERV BIOL, V11, P1069 WITH KA, 1997, OIKOS, V79, P219 WITH KA, 1999, CONSERV BIOL, V13, P314 ZOBEL M, 1992, OIKOS, V65, P314 0921-2973 Landsc. Ecol.ISI:000183770600009QStockholm Univ, Dept Bot, Dept Phys Geog & Quaternary Geol, S-10691 Stockholm, Sweden. CNRS, Ctr Ecol Fonct & Evolut, F-34033 Montpellier, France. Australian Natl Univ, Res Sch Biol Sci, Ecosyst Dynam Grp, Canberra, ACT 2601, Australia. Cousins, SAO, Stockholm Univ, Dept Bot, Dept Phys Geog & Quaternary Geol, S-10691 Stockholm, Sweden.English?-Sara A. O. Cousins Helena Ohlson Ove Eriksson2007Effects of historical and present fragmentation on plant species diversity in semi-natural grasslands in Swedish rural landscapes 723-730Landscape Ecology225Area-effects - Biological diversity - Extinction - Historical ecology - Landscape change - Management - Old maps - Remnants - Resilience - Thresholds Habitat loss and fragmentation of natural and semi-natural habitats are considered as major threats to plant species richness. Recently several studies have pinpointed the need to analyse past landscape patterns to understand effects of fragmentation, as the response to landscape change may be slow in many organisms, plants in particular. We compared species richness in continuously grazed and abandoned grasslands in different commonplace rural landscapes in Sweden, and analysed effects of isolation and area in three time-steps (100 and 50 years ago and today). Old cadastral maps and aerial photographs were used to analyse past and present landscape patterns in 25 sites. Two plant diversity measures were investigated; total species richness and species density. During the last 100 years grassland area and connectivity have been reduced by about 90%. Present-day habitat area was positively related to total species richness in both habitats. There was also a relationship to habitat area 50 years ago for continuously grazed grasslands. Only present management was related to species density: continuously grazed grasslands had the highest species density. There were no relationships between grassland connectivity, present or past, and any diversity measure. We conclude that landscape history is not directly important for present-day plant diversity patterns in ordinary landscapes, although past grassland management is a prerequisite for the grassland habitats that can be found there today. It is important that studies are conducted, not only in very diverse landscapes, but also in managed landscapes in order to assess the effects of fragmentation on species. <7n$Couteron, P. Barbier, N. Gautier, D.2006oTextural ordination based on fourier spectral decomposition: A method to analyze and compare landscape patterns555-567Landscape Ecology214Cameroon; Central Africa; Fourier transform; multi-scale analysis; remote sensing; sahel; spectral analysis; texture feature extraction; tropical savannas AERIAL PHOTOGRAPHS; SEMIARID VEGETATION; CLASSIFICATION; STATISTICS; RESOLUTION; TRANSFORM; IMAGESArticleMayWe propose an approach to texture characterization and comparison that directly uses the information of digital images of the earth surface without requesting a prior distinction of structural 'patches'. Digital images are partitioned into square 'windows' that define the scale of the analysis and which are submitted to the two-dimensional Fourier transform for extraction of a simplified textural characterization (in terms of coarseness) via the computation of a 'radial' power spectrum. Spectra computed from many images of the same size are systematically compared by means of a principal component analysis (PCA), which provides an ordination along a limited number of coarseness vs. fineness gradients. As an illustration, we applied this approach to digitized panchromatic air photos depicting various types of land cover in a semiarid landscape of northern Cameroon. We performed 'textural ordinations' at several scales by using square windows with sides ranging from 120 m to 1 km. At all scales, we found two coarseness gradients (PCA axes) based on the relative importance in the spectrum of large (> 50 km(-1)), intermediate (30-50 km(-1)), small (10-25 km(-1)) and very small (< 10 km(-1)) spatial frequencies. Textural ordination based on Fourier spectra provides a powerful and consistent framework to identifying prominent scales of landscape patterns and to compare scaling properties across landscapes.://000237487700008 ISI Document Delivery No.: 041WR Times Cited: 0 Cited Reference Count: 30 Cited References: ARES JO, 2003, LANDSCAPE ECOL, V18, P51 BRABANT P, 1985, SOLS RESSOURCES TERR CAIN DH, 1997, LANDSCAPE ECOL, V12, P199 COUTERON P, 2001, J ECOL, V89, P616 COUTERON P, 2002, INT J REMOTE SENS, V23, P3407 COUTERON P, 2005, J APPL ECOL, V42, P1121 DIGGLE PJ, 1990, TIME SERIES BIOSTATI DYMOND JR, 1992, REMOTE SENS ENVIRON, V39, P95 FORMAN RTT, 1981, BIOSCIENCE, V31, P733 HARALICK RM, 1979, P IEEE, V67, P786 HUTCHINSON J, 1973, FLORA TROPICAL W AFR KADMON R, 1999, REMOTE SENS ENVIRON, V68, P164 KEITT TH, 2000, LANDSCAPE ECOL, V15, P479 KUMARESAN R, 1993, HDB DIGITAL SIGNAL P, P1143 LHOTE Y, 2000, ATLAS PROVINCE EXTRE, P17 LI H, 1995, OIKOS, V73, P280 LUDWIG JA, 2002, LANDSCAPE ECOL, V17, P157 MANLYU BFJ, 1994, MULTIVARIATE STAT ME MUGGLESTONE MA, 1998, COMPUT GEOSCI, V24, P771 MUSICK HB, 1991, QUANTITATIVE METHODS, P77 PUECH C, 1994, INT J REMOTE SENS, V15, P2421 RIPLEY BD, 1981, SPATIAL STAT SEIGNOBOS C, 2000, ATLAS PROVINCE EXTRE, P61 SOKAL RR, 1995, BIOMETRY PRINCIPLES TANG XO, 2000, COMPUT VIS IMAGE UND, V79, P25 TONGWAY DJ, 2001, BANDED VEGETATION PA TURNER MG, 2001, LANDSCAPE ECOLOGY TH TURNER SJ, 1991, QUANTITATIVE METHODS, P17 VERHOEF JM, 1993, J VEG SCI, V4, P441 WHITE F, 1983, VEGETATION AFRICA DE 0921-2973 Landsc. Ecol.ISI:000237487700008IFP, Pondicherry 605001, India. AMAP, Joint Res Unit, UMR, F-34398 Montpellier 05, France. Free Univ Brussels, Serv Bot Systemat & Phytosociol, B-1050 Brussels, Belgium. CIRAD, Bamako, Mali. Couteron, P, IFP, 11 St Louis St, Pondicherry 605001, India. pierre.couteron@ifpindia.orgEnglish?1George W. Cox Jodee Hunt1990:Nature and origin of stone stripes on the Columbia Plateau53-64Landscape Ecology51obasalt weathering, Columbia Plateau, erosion, fossorial rodents, Mima mounds, stone stripes, Thomomys talpoidesBeds of size-sorted stones forming stripes perpendicular to the contour are conspicuous on hillsides of the Columbia Plateau. Stripes occur on terrain ranging from 0" to about 30" in steepness, often beginning among Mima-type mounds on mesa tops and extending downward onto steep, unmounded slopes. Four mechanisms of their origin have been hypothesized: 1) water erosion, 2) solifluction and soil creep, 3) weathering of rock outcrops, and 4) tunneling by pocket gophers. We measured characteristics of five stripes on slopes of differing exposure and steepness. These stripes were 58-124 m long, and widths showed a maximum range of 0.55-3.70 m. Data on physical and biotic characteristics of the stripes suggest that pocket gopher tunneling is a basic mechanism of stripe formation on gentle slopes, and that this mechanism is augmented by outcrop weathering and colluvial dynamics on steeper slopes, with erosion playing a secondary role.<7A &Cox, W. A. Thompson, F. R. Faaborg, J.2012XLandscape forest cover and edge effects on songbird nest predation vary by nest predator659-669Landscape Ecology275cause-specific mortality forest birds nest survival passerines mice peromyscus-leucopus fragmented forests artificial nest bird community habitat success snakes metaanalysis hypothesis selectionMay Rates of nest predation for birds vary between and within species across multiple spatial scales, but we have a poor understanding of which predators drive such patterns. We video-monitored nests and identified predators at 120 nests of the Acadian Flycatcher (Empidonax virescens) and the Indigo Bunting (Passerina cyanea) at eight study sites in Missouri and Illinois, USA, during 2007-2010. We used an information-theoretic approach to evaluate hypotheses concerning factors affecting predator-specific and overall rates of predation at landscape, edge, and nest-site scales. We found support for effects of landscape forest cover and distance to habitat edge. Predation by Brown-headed Cowbirds (Molothrus ater) increased, and predation by rodents decreased as landscape forest cover decreased. Predation by raptors, rodents, and snakes increased as the distance to forest edges decreased, but the effect was modest and conditional upon the top-ranked model. Despite the predator-specific patterns we detected, there was no support for these effects on overall rates of predation. The interactions between breeding birds, nest predators, and the landscapes in which they reside are scale-dependent and context-specific, and may be resistant to broad conceptual management recommendations.://000303056100004-929JC Times Cited:0 Cited References Count:62 0921-2973Landscape EcolISI:000303056100004cCox, WA Univ Missouri, Dept Fisheries & Wildlife Sci, 302 ABNR, Columbia, MO 65211 USA Univ Missouri, Dept Fisheries & Wildlife Sci, 302 ABNR, Columbia, MO 65211 USA Univ Missouri, Dept Fisheries & Wildlife Sci, Columbia, MO 65211 USA Univ Missouri, USDA, Forest Serv, No Res Stn, Columbia, MO 65211 USA Univ Missouri, Div Biol Sci, Columbia, MO 65211 USADOI 10.1007/s10980-012-9711-xEnglish B~?y"Cozzi, G. Muller, C. B. Krauss, J.2008How do local habitat management and landscape structure at different spatial scales affect fritillary butterfly distribution on fragmented wetlands?269-283Landscape Ecology233Habitat fragmentation, patch quality and landscape structure are important predictors for species richness. However, conservation strategies targeting single species mainly focus on habitat patches and neglect possible effects of the surrounding landscape. This project assesses the impact of management, habitat fragmentation and landscape structure at different spatial scales on the distribution of three endangered butterfly species, Boloria selene, Boloria titania and Brenthis ino. We selected 36 study sites in the Swiss Alps differing in (1) the proportion of suitable habitat (i.e., wetlands); (2) the proportion of potential dispersal barriers (forest) in the surrounding landscape; (3) altitude; (4) habitat area and (5) management (mowing versus grazing). Three surveys per study site were conducted during the adult flight period to estimate occurrence and density of each species. For the best disperser B. selene the probability of occurrence was positively related to increasing proportion of wetland on a large spatial scale (radius: 4,000 m), for the medium disperser B. ino on an intermediate spatial scale (2,000 m) and for the poorest disperser B. titania on a small spatial scale (1,000 m). Nearby forest did not negatively affect butterfly species distribution but instead enhanced the probability of occurrence and the population density of B. titania. The fen-specialist B. selene had a higher probability of occurrence and higher population densities on grazed compared to mown fens. The altitude of the habitat patches affected the occurrence of the three species and increasing habitat area enhanced the probability of occurrence of B. selene and B. ino. We conclude that, the surrounding landscape is of relevance for species distribution, but management and habitat fragmentation are often more important. We suggest that butterfly conservation should not focus only on a patch scale, but also on a landscape scale, taking into account species-specific dispersal abilities."://WOS:000254112100003 Times Cited: 0WOS:000254112100003(10.1007/s10980-007-9178-3|ISSN 0921-2973? )Craig, Michael Orrock, John Brudvig, Lars2011\Edge-mediated patterns of seed removal in experimentally connected and fragmented landscapes 1373-1381Landscape Ecology2610Springer NetherlandsEarth and Environmental Science/While biological reserves remain central to biodiversity conservation, the amount of area available for terrestrial reserves may be inadequate for many taxa. Biodiversity spillover—the promotion of diversity in matrix areas surrounding reserves—might help address this shortfall in reserve area. However, the mechanistic underpinning of spillover remains uninvestigated. Two fundamental processes—seed dispersal and establishment—might generate plant biodiversity spillover. Here, we investigate the role of establishment in promoting spillover by assessing post-dispersal seed predation, a key component of establishment, in the matrix of a replicated, large-scale habitat fragmentation experiment, where spillover is elevated around patches connected by landscape corridors. Our results show that matrix seed predation may constrain the distance of this spillover effect by reducing establishment: seed removal was least at the matrix edge and increased further into the matrix. We found some support for matrix seed predation underpinning previously reported landscape-level variation in spillover. Of the three species we investigated, two showed evidence for elevated seed predation in the matrix surrounding the unconnected patches around which the lowest levels of spillover occur. However, seed predation did not explain connectivity-enhanced spillover, suggesting that seed dispersal likely drives this pattern. Management activities that increase seed deposition in the matrix may have beneficial effects via spillover. Our work also illustrates that matrix-mediated gradients in seed predation may be widespread, but likely vary depending upon matrix composition and the ecological system under consideration. In fragmented landscapes, this gradient could impact the distribution, abundance, and spread of plant species.+http://dx.doi.org/10.1007/s10980-011-9650-y 0921-297310.1007/s10980-011-9650-yn<78-Crawford, T. W. Commito, J. A. Borowik, A. M.2006jFractal characterization of Mytilus edulis L. spatial structure in intertidal landscapes using GIS methods 1033-1044Landscape Ecology217benthic structure; blue mussel; fractal dimension; image processing; multi-scale; mussel bed; quadrat; soft-bottom; spatial pattern BODY-SIZE DISTRIBUTION; MUSSEL BEDS; ECOSYSTEM ENGINEERS; METAZOAN COMMUNITY; LOCAL INTERACTIONS; CHANGING SCALE; SOFT-BOTTOM; PATTERN; ECOLOGY; COMPLEXITYArticleOctThe blue mussel, Mytilus edulis L., forms dense and variable patch mosaics composed of aggregates of mussel individuals. Knowledge of mussel bed spatial pattern at multiple scales is important for understanding the form and function of intertidal systems where mussels are prominent features. This study extends prior work demonstrating fractal patterns of mussel boundaries in soft-bottom systems at the quadrat-scale by investigating fractal structure using GIS methods at both the quadrat- and bed-scales. The study pursues three goals for mussel beds in eastern Maine: (1) to compare quadrat-scale fractal dimensions obtained using manual methods with those obtained using digital imagery and techniques, (2) to determine if fractal patterns identified at the quadrat-scale are also present at the bed-scale, (3) and to evaluate the effectiveness of aerial photography and image analysis techniques. Photographs of randomly located quadrats (2500 cm(2) each) were scan digitized and classified into mussel presence/absence classes. Fractal dimensions of mussel/non-mussel boundaries were calculated using the box-counting method and compared with results obtained using analog photographs and methods. Digital aerial photographs at low tide were acquired for beds at two sites and classified using image processing techniques, and bed-scale fractal dimensions were calculated. At the quadrat-scale, fractal dimensions and their relationship with percent cover differed consistently in absolute value from results using manual methods but agreed in demonstrating fractal patterns for all quadrats and a parabolic trend with percent cover very similar to the one revealed manually. At the bed-scale, both sites were shown to be fractal, with higher dimension value for the bed that subjectively appeared more fragmented and highly dissected. Because mussels are important soft-bottom ecosystem engineers, i.e., foundation species that regulate species composition and abundances, the fractal spatial distribution identified in this study suggests that the species affected by them also exhibit fractal patterns. These results indicate the effectiveness of archive imagery and GIS methods for characterizing intertidal systems and point to the feasibility of future image acquisition.://000241010900006 : ISI Document Delivery No.: 091FA Times Cited: 0 Cited Reference Count: 59 Cited References: *TRUS INT INC, 2004, BEN 1 3 FRACT AN SYS BAK P, 1996, NATURE WORKS BENGUIGUI L, 2000, ENV PLAN B, V27, P597 COMMITO JA, 2000, J EXP MAR BIOL ECOL, V255, P133 COMMITO JA, 2001, ECOLOGICAL COMP SEDI, V51, P39 COMMITO JA, 2004, REGULATION HIERARCHI CRACKNELL AP, 1999, INT J REMOTE SENS, V19, P485 CRAWFORD TW, 2004, ANN M ASS GEOGR SE D CROOKS JA, 2002, OIKOS, V97, P153 CULLINAN VI, 1992, LANDSCAPE ECOL, V7, P211 ERLANDSSON J, 2004, MAR ECOL-PROG SER, V267, P173 FINKBEINER M, 2001, NOAACSC20117PUB FORMAN RTT, 1986, LANDSCAPE ECOLOGY GARRABOU J, 1998, LANDSCAPE ECOL, V13, P225 GEE JM, 1994, J EXP MAR BIOL ECOL, V178, P247 GEE JM, 1994, MAR ECOL-PROG SER, V103, P141 GUICHARD F, 2000, LIMNOL OCEANOGR, V45, P328 GUICHARD F, 2003, AM NAT, V161, P889 GUNNARSSON B, 1992, FUNCT ECOL, V6, P636 GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 GUTIERREZ JL, 2003, OIKOS, V101, P79 HALLEY JM, 2004, ECOL LETT, V7, P254 HASTINGS HM, 1993, FRACTALS USERS GUIDE HUNTER EL, 2002, INT J REMOTE SENS, V23, P2989 JENSEN JR, 1996, INTRO DIGITAL IMAGE KOSTYLEV V, 2001, MAR BIOL, V139, P497 LAWRIE SM, 2001, J EXP MAR BIOL ECOL, V257, P135 LEDUC A, 1994, LANDSCAPE ECOL, V9, P279 LIU AJ, 2001, LANDSCAPE ECOL, V16, P581 MILNE BT, 1992, AM NAT, V139, P32 PAINE RT, 1981, ECOL MONOGR, V51, P145 PEAKE AJ, 1993, ECOGRAPHY, V16, P269 PECH D, 2004, J EXP MAR BIOL ECOL, V299, P185 PETRAITIS PS, 1999, ECOLOGY, V80, P429 PETRAITIS PS, 2003, J EXP MAR BIOL ECOL, V293, P217 PICKETT STA, 1995, SCIENCE, V269, P331 RAGNARSSON SA, 1999, J EXP MAR BIOL ECOL, V241, P31 REMILLARD MM, 1992, LANDSCAPE ECOL, V7, P151 REUSCH TBH, 1997, ECOL MONOGR, V67, P65 SAURA S, 2001, PHOTOGRAMM ENG REM S, V67, P1027 SCHNEIDER DC, 1994, QUANTITATIVE ECOLOGY SNOVER ML, 1998, J EXP MAR BIOL ECOL, V223, P53 SUGIHARA G, 1990, TRENDS ECOL EVOL, V5, P79 THIEL M, 2002, HELGOLAND MAR RES, V56, P21 THOMSON AG, 1998, INT J REMOTE SENS, V19, P1189 THOMSON AG, 1998, MAR POLLUT BULL, V37, P164 THOMSON AG, 2003, INT J REMOTE SENS, V24, P2717 TILMAN D, 1997, PRINCETON MONOGRAPHS, V30 TUCKER CJ, 1979, REMOTE SENS ENVIRON, V8, P127 TURCOTTE DL, 1997, FRACTALS CHAOS GEOLO TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 TURNER MG, 2001, LANDSCAPE ECOLOGY TH URBAN DL, 1987, BIOSCIENCE, V37, P119 VANDEKOPPEL J, 2005, AM NAT, V165, E66 VANHEES WWS, 1994, LANDSCAPE ECOL, V9, P271 WOOTTON JT, 2001, NATURE, V413, P841 WU JG, 2002, LANDSCAPE ECOL, V17, P761 WU JG, 2004, LANDSCAPE ECOL, V19, P125 0921-2973 Landsc. Ecol.ISI:000241010900006E Carolina Univ, Dept Geog, Greenville, NC 27858 USA. Gettysburg Coll, Dept Environm Studies, Gettysburg, PA USA. Crawford, TW, E Carolina Univ, Dept Geog, Brewster A-234, Greenville, NC 27858 USA. crawfordt@ecu.eduEnglishz|?0DCreech, Tyler G. Epps, Clinton W. Monello, Ryan J. Wehausen, John D.2014VUsing network theory to prioritize management in a desert bighorn sheep metapopulation605-619Landscape Ecology294Apr%Connectivity models using empirically-derived landscape resistance maps can predict potential linkages among fragmented animal and plant populations. However, such models have rarely been used to guide systematic decision-making, such as identifying the most important habitat patches and dispersal corridors to protect or restore in order to maximize regional connectivity. Combining resistance models with network theory offers one means of prioritizing management for connectivity, and we applied this approach to a metapopulation of desert bighorn sheep (Ovis canadensis nelsoni) in the Mojave Desert of the southwestern United States. We used a genetic-based landscape resistance model to construct network models of genetic connectivity (potential for gene flow) and demographic connectivity (potential for colonization of empty habitat patches), which may differ because of sex-biased dispersal in bighorn sheep. We identified high-priority habitat patches and corridors and found that the type of connectivity and the network metric used to quantify connectivity had substantial effects on prioritization results, although some features ranked highly across all combinations. Rankings were also sensitive to our empirically-derived estimates of maximum effective dispersal distance, highlighting the importance of this often-ignored parameter. Patch-based analogs of our network metrics predicted both neutral and mitochondrial genetic diversity of 25 populations within the study area. This study demonstrates that network theory can enhance the utility of landscape resistance models as tools for conservation, but it is critical to consider the implications of sex-biased dispersal, the biological relevance of network metrics, and the uncertainty associated with dispersal range and behavior when using this approach.!://WOS:000333533800005Times Cited: 0 0921-2973WOS:00033353380000510.1007/s10980-014-0016-0? TCrespo-Pérez, Verónica Rebaudo, François Silvain, Jean-François Dangles, Olivier2011ZModeling invasive species spread in complex landscapes: the case of potato moth in Ecuador 1447-1461Landscape Ecology2610Springer NetherlandsEarth and Environmental SciencejTropical mountains have a long history of human occupation, and although vulnerable to biological invasions, have received minimal attention in the literature. Understanding invasive pest dynamics in socio-ecological, agricultural landscapes, like the tropical Andes, is a challenging but timely issue for ecologists as it may provide developing countries with new tools to face increasing threats posed by these organisms. In this work, road rehabilitation into a remote valley of the Ecuadorian Andes constituted a natural experiment to study the spatial propagation of an invasive potato tuber moth into a previously non-infested agricultural landscape. We used a cellular automaton to model moth spatio-temporal dynamics. Integrating real-world variables in the model allowed us to examine the relative influence of environmental versus social landscape heterogeneity on moth propagation. We focused on two types of anthropogenic activities: (1) the presence and spatial distribution of traditional crop storage structures that modify local microclimate, and (2) long-distance dispersal (LDD) of moths by human-induced transportation. Data from participatory monitoring of pest invasion into the valley and from a larger-scale field survey on the Ecuadorian Andes allowed us to validate our model against actual presence/absence records. Our simulations revealed that high density and a clumped distribution of storage structures had a positive effect on moth invasion by modifying the temperature of the landscape, and that passive, LDD enhanced moth invasion. Model validation showed that including human influence produced more precise and realistic simulations. We provide a powerful and widely applicable methodological framework that stresses the crucial importance of integrating the social landscape to develop accurate invasion models of pest dynamics in complex, agricultural systems.+http://dx.doi.org/10.1007/s10980-011-9649-4 0921-297310.1007/s10980-011-9649-4w<7:&Crist, P. J. Kohley, T. W. Oakleaf, J.2000GAssessing land-use impacts on biodiversity using an expert systems tool47-62Landscape Ecology151animal behavior biodiversity conservation decision support environmental planning expert systems gap analysis GIS land-use planning CONSERVATION BIOLOGY LANDSCAPE ECOLOGY LOCAL-GOVERNMENT MANAGEMENT CALIFORNIA PROTECTION RAREArticleJanqHabitat alteration, in the form of land-use development, is a leading cause of biodiversity loss in the U.S. and elsewhere. Although statutes in the U.S. may require consideration of biodiversity in local land-use planning and regulation, local governments lack the data, resources, and expertise to routinely consider biotic impacts that result from permitted land uses. We hypothesized that decision support systems could aid solution of this problem. We developed a pilot biodiversity expert systems tool (BEST) to test that hypothesis and learn what additional scientific and technological advancements are required for broad implementation of such a system. BEST uses data from the U.S. Geological Survey's Gap Analysis Program (GAP) and other data in a desktop GIS environment. The system provides predictions of conflict between proposed land uses and biotic elements and is intended for use at the start of the development review process. Key challenges were the development of categorization systems that relate named land-use types to ecological impacts, and relate sensitivities of biota to ecological impact levels. Although the advent of GAP and sophisticated desktop GIS make such a system feasible for broad implementation, considerable ongoing research is required to make the results of such a system scientifically sound, informative, and reliable for the regulatory process. We define a role for local government involvement in biodiversity impact assessment, the need for a biodiversity decision support system, the development of a prototype system, and scientific needs for broad implementation of a robust and reliable system.://000083830400005 ISI Document Delivery No.: 258GN Times Cited: 12 Cited Reference Count: 76 Cited References: *ENV PROT AG, 1995, EPA833K94002 *ESRI, 1998, ARCV PROD *TET COUNT, 1994, LAND DEV REG *US DEP COMM, 1996, STAT ABSTR US *USGS GAP AN PROGR, 1998, HDB GAP AN ADAMS LW, 1989, WILDLIFE RESERVES CO ALLEN TFH, 1982, HIERARCHY PERSPECTIV ANDERSON SH, 1994, RES MANAGEMENT TECHN, P592 ARCESE P, 1997, BEHAV APPROACHES CON, P48 ARNOLD CL, 1996, J AM PLANN ASSOC, V62, P243 BEATLEY T, 1994, HABITAT CONSERVATION BEISSINGER SR, 1997, BEHAV APPROACHES CON, P23 BENNET J, 1995, INDIANAS BIOL DIVERS BERRIS CR, 1987, LANDSCAPE J, V6, P31 BLAIR RB, 1996, ECOL APPL, V6, P506 CLEMMONS JR, 1997, BEHAV APPROACHES CON, P3 COLE DN, 1995, WILDLIFE RECREATIONI, P183 COLEMAN JS, 1993, WILDLIFE SOC B, V21, P381 COLEMAN WG, 1996, CONSERV BIOL, V10, P1494 CRIST PJ, 1994, FILLING GAP PLANNING, P1 DIAMOND HL, 1996, LAND USE AM DOBSON AP, 1997, SCIENCE, V275, P550 EMLEN JT, 1974, CONDOR, V76, P184 FELLEMAN J, 1992, DEEP INFORMATION EME FLATHER CH, 1997, ECOL APPL, V7, P531 GRANT J, 1996, J AM PLANN ASSOC, V62, P331 GUTHRIE DA, 1974, AM MIDL NAT, V92, P461 HALLOCK D, 1986, WILDLIFE CONSERVATIO, P151 HARTMAN RL, 1997, GAP ANAL PROGRAM B, V6 HECNAR SJ, 1997, CONSERV BIOL, V11, P670 JENNINGS MD, 1991, ENVIRON CONSERV, V18, P211 JENSEN DB, 1993, IN OUR OWN HANDS JOHNSON K, 1993, ART AM, V81, P134 KNIGHT RL, 1995, WILDLIFE RECREATIONI KNIGHT RL, 1995, WILDLIFE RECREATIONI, P51 KREBS CJ, 1994, ECOLOGY EXPT ANAL DI KREBS JR, 1993, INTRO BEHAV ECOLOGY LARSON RA, 1995, WILDLIFE RECREATIONI, P257 LAZELL J, 1989, NATL PARKS, V63, P18 LYNCH K, 1962, SITE PLANNING MASCHINSKI J, 1997, CONSERV BIOL, V11, P990 MCGARIGAL K, 1991, WILDL MONOG, V115, P47 MCHARG I, 1969, DESIGN NATURE MERRILL EH, 1996, WYOMING GAP ANAL PRO MOULTON CA, 1991, NIUW S SER, V2, P67 NOSS RF, 1994, SAVING NATURES LEGAC NOSS RF, 1995, 28 USDI NAT BIOL SER OLSHANSKY RB, 1996, J AM PLANN ASSOC, V62, P313 ONEILL RV, 1986, MONOGRAPHS POPULATIO, V23 PALMER A, 1981, EDEN PEEK JM, 1986, REV WILDLIFE MANAGEM PRESS D, 1996, CONSERV BIOL, V10, P1538 REILLY J, 1997, AM PLANN ASS NAT C S ROGERS EM, 1995, DIFFUSION INNOVATION RUGGIERO, 1994, RM254 USDA FOR SERV SAMPSON R, 1996, WILDFIRE NEWS NOTES, V10, P1 SCARLETT L, 1997, AM PLANN ASS ANN M S SCHEMSKE DW, 1994, ECOLOGY, V75, P584 SCOTT JM, 1993, WILDLIFE MONOGR, V123, P41 SHORT HL, 1983, RES MANAGEMENT TECHN, P615 SIMMENS H, 1996, OFFICE STATE PLANNIN, V2 SOULE ME, 1991, J AM PLANN ASSOC, V57, P313 STEINER F, 1991, LIVING LANDSCAPE ECO TARLOCK AD, 1993, U CHICAGO LAW REV, V60, P555 THAXTON JE, 1996, FLORIDA FIELD NATURA, V24, P25 THERRES GD, 1993, T 38 N AM WILDL NAT, P62 THILLMAN JH, 1976, T 41 N AM WILDL NAT, P548 THOMAS JW, 1976, T 41 N AM WILDL NAT, P452 TRUETT JC, 1994, RES MANAGEMENT TECHN, P607 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 URBAN DL, 1987, BIOSCIENCE, V37, P119 WESTMAN WE, 1985, ECOLOGY IMPACT ASSES WIENS JA, 1989, FUNCT ECOL, V3, P385 WITH KA, 1997, CONSERV BIOL, V11, P1069 YAFEE SL, 1997, CONS BIOL, V11, P328 ZHU XA, 1998, ENVIRON MANAGE, V22, P35 0921-2973 Landsc. Ecol.ISI:000083830400005}USGS Gap Anal Program, Moscow, ID 83843 USA. Crist, PJ, USGS Gap Anal Program, 530 S Asbury St,Suite 1, Moscow, ID 83843 USA.English|?9Croci, S. Butet, A. Georges, A. Aguejdad, R. Clergeau, P.2008SSmall urban woodlands as biodiversity conservation hot-spot: a multi-taxon approach 1171-1186Landscape Ecology2310To evaluate the importance of urban woodlands to serve as potential sites for biodiversity conservation, we analysed bird, carabid beetle and small mammal community responses to urbanisation at different spatial scales. We analysed the relationships between the variations of the structure (species richness S, diversity H' and dominance D) of animal communities of woodlands distributed along a rural-urban gradient, and the variations along this same gradient of (1) the vegetation within woodlands, (2) the landscape at 100 m and (3) 600 m around the woodlands. We identified the spatial scales whose variations along the gradient most affected each animal community structure, and characterised community responses to these variations. Our results showed that urbanisation affected taxa differently according to their dispersal ability. Carabid beetles, less mobile, seem to be sensitive to increasing fragmentation and built surfaces from periurban to town centre which could make their movement within the urban landscape difficult. Birds, mobile species, seem to be more sensitive to variations of the vegetation structure within woodlands from periurban to town centre that could affect their capacity to maintain in habitat patches. Although our study did not allow relating the small mammal community structure to urbanisation, it suggests that this taxa is sensitive to urban local disturbances. A relevant management scale of woodlands can be specified for each taxa conservation. Urban woodlands accommodate over 50% of the species present in periurban woodlands, and effective management could enhance this number. Woodlands seem to be a good choice for promoting biodiversity conservation in towns.!://WOS:000261790600004Times Cited: 0 0921-2973WOS:00026179060000410.1007/s10980-008-9257-0 ڽ7 -Cross, PaulC Caillaud, Damien Heisey, DennisM2013Underestimating the effects of spatial heterogeneity due to individual movement and spatial scale: infectious disease as an example247-257Landscape Ecology282Springer NetherlandsSource-sink metapopulation Epidemiological model Observational bias Disease transmission Host density Modifiable areal unit problem 2013/02/01+http://dx.doi.org/10.1007/s10980-012-9830-4 0921-2973Landscape Ecol10.1007/s10980-012-9830-4EnglishG|?DCrouzeilles, Renato Prevedello, Jayme Augusto Lima Figueiredo, Marcos de Souza Lorini, Maria Lucia Viveiros Grelle, Carlos Eduardo2014The effects of the number, size and isolation of patches along a gradient of native vegetation cover: how can we increment habitat availability?479-489Landscape Ecology293MarzHabitat availability-or how much habitat species can reach at the landscape scale-depends primarily on the percentage of native cover. However, attributes of landscape configuration such as the number, size and isolation of habitat patches may have complementary effects on habitat availability, with implications for the management of landscapes. Here, we determined whether, and at which percentages of native cover, the number, size and isolation of patches contribute for habitat availability. We quantified habitat availability in 325 landscapes spread across the state of Rio de Janeiro, in the Atlantic Forest hotspot, with either high (>50 %), intermediate (50-30 %), low (30-10 %) or very low (<10 %) percentage of native cover, and for six hypothetical species differing in inter-patch dispersal ability. Above 50 % of native cover, the percentage of cover per se was the only determinant of habitat availability, but below 50 % the attributes of landscape configuration also contributed for habitat availability. The number of patches had a negative effect on habitat availability in landscapes with 50-10 % of native cover, whereas patch size had a positive effect in landscapes with <10 % of native cover. The different species generally responded to the same set of landscape attributes, although to different extents, potentially facilitating decision making for conservation. In landscapes with >50 % of native cover, conservation actions are probably sufficient to guarantee habitat availability, whereas in the remaining landscapes additional restoration efforts are needed, especially to reconnect and/or enlarge remaining habitat patches.!://WOS:000331935500010Times Cited: 1 0921-2973WOS:00033193550001010.1007/s10980-013-9978-6Z<7@(Crow, T. R. Host, G. E. Mladenoff, D. J.1999cOwnership and ecosystem as sources of spatial heterogeneity in a forested landscape, Wisconsin, USA449-463Landscape Ecology145forest management land cover land use landscape ecology spatial pattern OLD-GROWTH PATTERNS ENVIRONMENTS DISTURBANCE DYNAMICS HISTORY HABITAT ECOLOGY SCALEArticleOct The interaction between physical environment and land ownership in creating spatial heterogeneity was studied in largely forested landscapes of northern Wisconsin, USA. A stratified random approach was used in which 2500-ha plots representing two ownerships (National Forest and private non-industrial) were located within two regional ecosystems (extremely well-drained outwash sands and moderately well-drained moraines). Sixteen plots were established, four within each combination of ownership and ecosystem, and the land cover on the plots was classified from aerial photographs using a modified form of the Anderson (U.S. Geological Survey) land use and land cover classification system. Upland deciduous forests dominated by northern hardwoods were common on the moraines for both ownerships. On the outwash, the National Forest was dominated by pine plantations, upland deciduous forests, and upland regenerating forests (as defined by < 50% canopy coverage). In contrast, a more even distribution among the classes of upland forest existed on private land/outwash. A strong interaction between ecosystem and ownership was evident for most comparisons of landscape structure. On the moraine, the National Forest ownership had a finer grain pattern with more complex patch shapes compared to private land. On the outwash, in contrast, the National Forest had a coarser grain pattern with less complex patch shapes compared to private land. When patch size and shape were compared between ecosystems within an ownership, statistically significant differences in landscape structure existed on public land but not on private land. On public land, different management practices on the moraine and outwash, primarily related to timber harvesting and road building, created very different landscape patterns. Landscape structure on different ecosystems on private land tended to be similar because ownership was fragmented in both ecosystems and because ownership boundaries often corresponded to patch boundaries on private land. A complex relationship exits between ownership, and related differences in land use, and the physical environment that ultimately constrains land use. Studies that do not consider these interactions may misinterpret the importance of either variable in explaining variation in landscape patterns.://000082510000004 ISI Document Delivery No.: 234XQ Times Cited: 21 Cited Reference Count: 43 Cited References: *SAS I INC, 1988, SAS STAT US GUID ALBERT DA, 1986, REGIONAL LANDSCAPE E ALBERT DA, 1995, NC178 USDA FOR SERV ANDERSEN O, 1996, LANDSCAPE URBAN PLAN, V35, P247 ANDERSON JR, 1976, 964 GEOL SURV BARNES BV, 1998, FOREST ECOLOGY BROUWER FM, 1989, J ENVIRON MANAGE, V29, P1 CLAYTON L, 1984, 46 U WISC GEOL NAT H CRIST TO, 1992, FUNCT ECOL, V6, P536 CURTIS JT, 1959, VEGETATION WISCONSIN DEROOS AM, 1995, OIKOS, V74, P347 FLADER SL, 1983, GREAT LAKES FOREST E FOLSE LJ, 1989, ECOL MODEL, V46, P57 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FORMAN RTT, 1995, LANDSCAPE ECOL, V10, P133 FRELICH LE, 1994, CAN J FOREST RES, V24, P1939 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 HASSELL MP, 1980, OIKOS, V35, P150 HEINSELMAN ML, 1973, QUATERNARY RES, V3, P329 HOST GE, 1996, ECOL APPL, V6, P608 KEYS JE, 1995, ECOLOGICAL UNITS E U KOTLIAR NB, 1990, OIKOS, V59, P253 KRUMMEL JR, 1987, OIKOS, V48, P321 LEVIN SA, 1976, ANNU REV ECOL SYST, V7, P287 LEVIN SA, 1992, ECOLOGY, V73, P1943 LI HB, 1994, ECOLOGY, V75, P2446 MCGARIGAL K, 1995, GTR351 USDA FOR SERV MEYER WB, 1994, CHANGES LAND USE LAN MILNE BT, 1991, ECOLOGICAL HETEROGEN, P69 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 MORRISON G, 1987, OECOLOGIA, V73, P609 NASSAUER JI, 1995, LANDSCAPE ECOL, V10, P229 NASSAUER JI, 1997, PLACING NATURE CULTU NAVEH Z, 1995, LANDSCAPE URBAN PLAN, V32, P43 PARKER L, 1997, CREATING FORESTRY 21, P218 RUNKLE JR, 1982, ECOLOGY, V63, P1533 RUSSELL EWB, 1997, PEOPLE LAND TIME LIN TURNER MG, 1996, ECOL APPL, V6, P1150 WATT AS, 1947, J ECOL, V35, P1 WEAR DN, 1993, NATURAL RESOURCE MOD, V7, P379 WEAR DN, 1996, ECOL APPL, V6, P1173 WHITNEY GG, 1986, ECOLOGY, V67, P1548 WIENS JA, 1976, ANNU REV ECOL SYST, V7, P81 0921-2973 Landsc. Ecol.ISI:000082510000004Univ Michigan, Sch Nat Resources & Environm, Ann Arbor, MI 48109 USA. Crow, TR, Univ Michigan, Sch Nat Resources & Environm, 430 E Univ, Ann Arbor, MI 48109 USA.English'<7Crow, T. R. Perera, A. H.2004NEmulating natural landscape disturbance in forest management - an introduction231-233Landscape Ecology193 ECOSYSTEMEditorial Material://000221878900001 "ISI Document Delivery No.: 827DL Times Cited: 2 Cited Reference Count: 10 Cited References: BAKER WI, 1994, CONSERV BIOL, V8, P763 CROW TR, 1999, LANDSCAPE ECOL, V14, P449 CROW TR, 2002, FOREST SCI, V48, P129 HAILA Y, 1994, ANN ZOOL FENN, V31, P203 HARVEY BD, 2002, FOREST ECOL MANAG, V155, P369 MCRAE DJ, 2001, ENV REV, V9, P223 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 PALIK BJ, 2002, FOREST ECOL MANAG, V155, P347 PERERA AH, IN PRESS EMULATING N SEYMOUR RS, 2002, FOREST ECOL MANAG, V155, P357 0921-2973 Landsc. Ecol.ISI:000221878900001US Forest Serv, USDA, N Cent Res Stn, Grand Rapids, MN 55744 USA. Ontario Forest Res Inst, Sault Ste Marie, ON P6A 2E5, Canada. Crow, TR, US Forest Serv, USDA, N Cent Res Stn, 1831 Hwy 169 E, Grand Rapids, MN 55744 USA.English4<7o Csorba, P.1996$Professor K.-F. Schreiber is seventyU2-U2Landscape Ecology115Item About an IndividualOct://A1996VR02500002 HISI Document Delivery No.: VR025 Times Cited: 0 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1996VR02500002English<7LCubizolle, H. Tourman, A. Argant, J. Porteret, J. Oberlin, C. Serieyssol, K.2003Origins of European biodiversity: palaeo-geographic signification of peat inception during the Holocene in the granitic eastern Massif Central (France)227-238Landscape Ecology183biodiversity climatic change human impact mire palaeo environment peat inception radiocarbon dating sampling method ARCHAEOLOGYArticleAprMires are rare, unique environments that greatly contribute to biodiversity and occupy key functions in the hydrological cycle, but today many of these ecosystems are menaced, making conservation measures necessary. The efficiency of these measures is partly related to our knowledge of their origins and their development, a question rarely addressed. In this paper we examine the development of mires during the 10.000 last years (Holocene) in the eastern Massif Central, France, focusing on the contributions of climate change and human activities. Radiocarbon dates of the basal layers of 63 sites show that many mires formed around 7500 BP. During the Holocene, many mires were formed in the Atlantic period, characterised by warmer and wetter climatic conditions. At shorter time scales of 10(3) - 10(2) years, several other factors are related to peat inception, including topography, geomorphology and superficial geology, vegetation successions and human-induced changes. There is evidence that the building of small dams in headwater streams during the Iron age induced local water logging which then lead to the initiation and growth of mires. The influence of Bronze age communities is further demonstrated by new pollen analysis results. Forest clearing and grazing also favoured soil water logging, enabling peat inception. We consider human societies to be responsible for the formation of some mires. Human activities can be considered to having taken part in the development of the European biodiversity at least during the last 5 millennium.://000183770600002  ISI Document Delivery No.: 694JD Times Cited: 1 Cited Reference Count: 49 Cited References: *EEA DMEER, 2000, 4 EIONET SEM NAT CON, P30 ALLEE P, 1997, 17 RENC INT ARCH HIS, P365 BARBER KE, 1984, QUATERNARY NEWSLETTE, V44, P28 BEAULIEU JL, 1988, CAHIERS MICROPALEONT, V3, P5 CAMPY M, 1987, TRAVAUX FRANCAIS PAL, P165 CASELDINE C, 1993, CLIMATE CHANGE HUMAN, P119 CHAMBERS FM, 1988, ARCHAEOLOGY FLORA BR, P107 CONWAY VM, 1947, J ECOL, V34, P149 CONWAY VM, 1954, J ECOL, V42, P117 COX CB, 1973, BIOGEOGRAPHY ECOLOGI CUBIZOLLE H, UNPUB HOLOCENE VEGET CUBIZOLLE H, 2001, QUATERNAIRE, V12, P15 CUBIZOLLE H, 2001, QUATERNAIRE, V12, P53 CUBIZOLLE H, 2002, IN PRESS ACT C PEVS DIMBLEBY GW, 1963, GRANA PALYNOL, V4, P140 DUCHAUFOUR P, 1983, PEDOLOGIE PEDOGENESE ETLICHER B, 1986, THESIS U LYON 2 FRANCEZ AJ, 1990, 86242EGP SRETIE CERE GOBAT JM, 1998, SOL VIVANT PRESSES P, P14 GODWIN H, 1981, ARCH PEAT BOGS GOWDIN H, 1975, HIST BRIT FLORA GRANIERO PA, 1999, CATENA, V36, P233 HOFFMANN RC, 1996, AM HIST REV, V101, P631 JANSSEN CR, 1982, CR HEBD ACAD SCI, V294, P155 JANSSEN CR, 1990, MONTS FOREZ MILIEU H, P65 JULVE P, 1994, BAGF, V3, P287 JULVE P, 1996, CAH SCI TEC RES TOUR, V1, P2 LEMEE G, 1941, REV SCI NATURELLES A, P41 LUTGERINK RHP, 1989, POLLEN SPORES, V31, P45 MAGNY M, 1995, HIST CLIMAT DERNIERS MCGLADE J, 1995, ANTIQUITY, V69, P113 MOORE PD, 1984, EUROPEAN MIRES, P203 MOORE PD, 1988, MONOGRAPH OXFORD U C, V14, P116 MOORE PD, 1993, CLIMATE CHANGE HUMAN, P217 OZENDA P, 1983, NATURE ENV SERIES, V29 PERSAT H, 1997, B FR PECHE PISCIC, P15 RANKINE WF, 1960, P PREHIST SOC, V26, P246 REILLE M, 1985, POLLEN SPORES, V27, P209 REILLE M, 1989, B SOC BOT FR-LETT, V136, P61 ROBICHAUD PR, 2000, J HYDROL, V231, P220 SIMMONS IG, 1985, BIOGEOGRAPHICAL MONO, V2, P7 SMITH AG, 1970, STUDIES VEGETATIONAL, P81 SMITH AG, 1975, EFFECT MAN LANDSCAPE, P64 STUIVER M, 1998, RADIOCARBON, V40, P1041 SUCHEL JB, 1990, MONTS FOREZ MILIEU H, P81 THEBAUD DG, 1988, THESIS U CLERMONT TOURMAN A, 2000, MISE PLACE TOURBIERE VANDERLEEUW S, 1995, HOMME DEGRADATION EN, P487 WOODELL SRJ, 1985, ENGLISH LANDSCAPE PA 0921-2973 Landsc. Ecol.ISI:000183770600002rUniv St Etienne, CNRS, ZAL BRGM,CRENAM, UMR 5600, F-42023 St Etienne 2, France. Univ Lyon 1, Inst Dolomieu, ESEP, UMR 6636, F-38031 Grenoble, France. Univ Lyon 1, Ctr Datat Radiocarbone, F-69622 Villeurbanne, France. Amer Univ Paris, F-75007 Paris, France. Cubizolle, H, Univ St Etienne, CNRS, ZAL BRGM,CRENAM, UMR 5600, 6 Rue Basses Rives, F-42023 St Etienne 2, France.English C<77,Cullinan, V. I. Simmons, M. A. Thomas, J. M.1997mA Bayesian test of hierarchy theory: scaling up variability in plant cover from field to remotely sensed data273-285Landscape Ecology125>hierarchy theory; Bayesian analysis; scales of pattern PATTERNArticleOctHierarchy theory predicts that a hierarchy of process rates should be reflected in a hierarchy of spatial and temporal scales observable on the landscape. We will show that multiple scales of pattern for total plant cover measured in the field at 1-m resolution are correlated with scales of vegetative pattern obtained from remotely sensed data with resolutions of 25 m(2) and 30 m(2). Second, using four models based on postulates of hierarchy theory, we will combine the scales of pattern of each individual species within a community to estimate the remotely sensed community scales of pattern. Finally, we will compare the four models using a Bayesian analysis to determine which model best portrays how vegetative patterns of individual species combine to produce remotely observed community patterns. The results of the model comparisons provide an example of how postulates of hierarchy theory can be tested and how individual species patterns can be scaled-up to estimate remotely observed scales of pattern.://000077684100002 TISI Document Delivery No.: 150UN Times Cited: 8 Cited Reference Count: 17 Cited References: ALLEN TFH, 1982, HIERARCHY PERSPECTIV CARLILE DW, 1989, LANDSCAPE ECOLOGY, V2, P203 CARPENTER SR, 1990, ECOLOGY, V71, P2038 CULLINAN VI, 1992, LANDSCAPE ECOL, V7, P211 EFRON B, 1983, AM STAT, V37, P36 GREIGSMITH P, 1983, QUANTITATIVE PLANT E HILL MO, 1973, J ECOL, V61, P225 ONEILL RV, 1986, HIERARCHICAL CONCEPT ONEILL RV, 1988, SCALES GLOBAL CHANGE, P29 ONEILL RV, 1989, PERSPECTIVES ECOLOGI, P140 ONEILL RV, 1991, LANDSCAPE ECOL, V5, P137 RECKHOW KH, 1990, ECOLOGY, V71, P2053 SIMMONS MA, 1992, LANDSCAPE ECOL, V7, P77 STEEL RGD, 1980, PRINCIPLES PROCEDURE TRANGMAR BB, 1985, ADV AGRON, V38, P44 TURNER MG, 1991, ECOLOGICAL STUDIES S WALTERS CJ, 1990, ECOLOGY, V71, P2060 0921-2973 Landsc. Ecol.ISI:000077684100002gPacific NW Natl Lab, Richland, WA 99352 USA. Cullinan, VI, Pacific NW Natl Lab, Richland, WA 99352 USA.English<7Cullinan, V. I. Thomas, J. M.1992NA comparison of quantitative methods for examining landscape pattern and scale211-227Landscape Ecology73[SPATIAL HETEROGENEITY; ECOLOGICAL PATTERNING; ECOLOGICAL SCALE; QUANTITATIVE METHODS; PATCHArticleSepEcologists have long recognized the importance of spatial and temporal patterns that characterize heterogeneity in landscapes. However, despite the realization that inferences about ecological phenomena are scale dependent, little attention has been paid to determining appropriate scales of measurement (e.g., plot or grain size) in studies of landscape dynamics or ecosystem change. This paper compares the results from three data sets using several quantitative methods available for characterizing landscape heterogeneity and/or for determining scale of measurement. Methods evaluated include tests of non-randomness, estimation of patch size, spectral analysis, fractals, variance ratio analysis, and correlation analysis. The results showed that no one method provides consistently good estimates of scale. Thus, sampling strategies for landscape studies should be derived from estimates of patch size and/or scale of pattern obtained from more than one of these methods.://A1992JW40100006 IISI Document Delivery No.: JW401 Times Cited: 54 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1992JW40100006SCULLINAN, VI, BATTELLE MEM INST,MARINE SCI LAB,439 W SEQUIM BAY RD,SEQUIM,WA 98382.English|? Culman, Steven W. Young-Mathews, Anna Hollander, Allan D. Ferris, Howard Sanchez-Moreno, Sara O'Geen, Anthony T. Jackson, Louise E.2010Biodiversity is associated with indicators of soil ecosystem functions over a landscape gradient of agricultural intensification 1333-1348Landscape Ecology259NovAgricultural intensification has led to dramatic losses in biodiversity over the past several decades. Many studies have shown the effects of intensification on vegetation or soil communities at field or local scales. However, the functional significance of biodiversity may only appear at larger spatial and temporal scales, due to exchanges among local ecosystems throughout a landscape. To examine how patterns of biodiversity loss are reflected at larger spatial scales, plant and soil biodiversity and associated indicators of ecosystem functions were assessed in riparian areas over a 150 km(2) agricultural landscape in the Sacramento Valley of California. Publicly-available GIS data were first used to classify and select sites over the range of soils, topography and plant community types. Representative sites from the landscape were sampled for soil physiochemical properties, as well as microbial, nematode, and plant communities. Higher agricultural intensification, based on field and landscape indices, was negatively correlated with richness and diversity of plant and soil taxa, and was related to indicators of ecosystem functions, such as increased soil nitrate and phosphorus loading, decreased riparian health ratings, and lower soil carbon, soil microbial biomass and soil food web structure. Both field- and landscape-scale factors played important roles in the measured losses. The study area was composed of a wide array of soils, vegetation, and land management, indicating that the observed trends transcended site-specific conditions.!://WOS:000281981000003Times Cited: 0 0921-2973WOS:00028198100000310.1007/s10980-010-9511-0ڽ7>Cumming, GraemeS Olsson, Per Chapin, F. S., III Holling, C. S.2013QResilience, experimentation, and scale mismatches in social-ecological landscapes 1139-1150Landscape Ecology286Springer NetherlandsVResilience Landscape planning Management Social learning Adaptation Ecosystem services 2013/07/01+http://dx.doi.org/10.1007/s10980-012-9725-4 0921-2973Landscape Ecol10.1007/s10980-012-9725-4English]?Graeme S. Cumming20074Global biodiversity scenarios and landscape ecology 671-685Landscape Ecology225Diversity - Scenario planning - Species richness - Ticks - Ixodidae - Climate change - Millennium Assessment - Policy - Management - Scale - Species–area relationship The composition of ecological communities is both cause and consequence of landscape pattern. Predicting biodiversity change involves understanding not only ecology and evolution, but also complex changes in human societies and economies. Scenarios offer a less rigid approach to thinking about biodiversity change in a policy and management context. They shift the focus of research and management from making singular predictions and developing single ‘best’ strategies to exploring uncertainties and assessing the outcomes of alternative policies. The four Millennium Ecosystem Assessment (MA) biodiversity scenarios illustrate current approaches to biodiversity estimation in global scenarios. The MA biodiversity scenarios are built around the species–area relationship and the magnitudes of a few area-dependent processes such as nitrogen deposition and climate change. Some of the most obvious landscape-related omissions from the MA scenarios are pattern-process feedbacks, scale dependencies, and the role of landscape configuration. While the MA has set a new standard for biodiversity scenarios, future exercises would benefit from a more multi-scale and more mechanistic framework. I use examples from research on the landscape ecology and biogeography of African ticks to illustrate how a hypothesis-based approach can be used to analyse the multi-scale, multi-level drivers of change in patterns of species occurrences. Two of the most important challenges for the future development of both landscape ecology and biodiversity scenarios are to become more mechanistic (less pattern-based) and more general (applicable across different landscapes). S|? Cumming, Graeme S.2011QSpatial resilience: integrating landscape ecology, resilience, and sustainability899-909Landscape Ecology267Aug5Landscape ecology has a high potential to contribute to sustainability in the interactions of people and nature. Landscape ecologists have already made considerable progress towards a more general understanding of the relevance of spatial variation for ecosystems. Incorporating the complexities of societies and economies into landscape ecology analyses will, however, require a broader framework for thinking about spatial elements of complexity. An exciting recent development is to explicitly try to integrate landscape ecology and ideas about resilience in social-ecological systems through the concept of spatial resilience. Spatial resilience focuses on the importance of location, connectivity, and context for resilience, based on the idea that spatial variation in patterns and processes at different scales both impacts and is impacted by local system resilience. I first introduce and define the concepts of resilience and spatial resilience and then discuss some of their potential contributions to the further interdisciplinary integration of landscape ecology, complexity theory, and sustainability science. Complexity theorists have argued that many complex phenomena, such as symmetry-breaking and selection, share common underlying mechanisms regardless of system type (physical, social, ecological, or economic). Similarities in the consequences of social exclusion and habitat fragmentation provide an informative example. There are many strong parallels between pattern-process interactions in social and ecological systems, respectively, and a number of general spatial principles and mechanisms are emerging that have relevance across many different kinds of system. Landscape ecologists, with their background in spatially explicit pattern-process analysis, are well placed to contribute to this emerging research agenda.!://WOS:000292705900001Times Cited: 0 0921-2973WOS:00029270590000110.1007/s10980-011-9623-1|? Cumming, G. S. George, A.2009Historical influences dominate the composition of regenerating plant communities in abandoned citrus groves in north-central Florida957-970Landscape Ecology247AugThe question of what determines plant community composition is fundamental to the study of plant community ecology. We examined the relative roles of historical land use, landscape context, and the biophysical environment as determinants of plant community composition in regenerating citrus groves in north-central Florida. Results were interpreted in light of plant functional traits. Herbaceous and woody plants responded differently to broad-scale variables; herbs correlated most strongly with surrounding land cover at a scale of 8 km, while the only significant determinant of woody species distributions was local land use history. There were significant correlations between herbaceous species and spatial context, habitat isolation, environmental variables, and historical variables. Partial Mantel tests indicated that each variable provided a unique contribution in explaining some of the variation in the herbaceous dataset. The correlation between woody plants and local historical variables remained significant even with other effects corrected for. In the herbaceous community, species composition was linked to functional traits much as expected from classical theory. While spatial influences in our study system are important for both woody and herbaceous plants, the primary determinant of plant community composition in regenerating citrus groves is historical land use. Our results suggest that the fine-scale mechanisms of local competition, tolerance and facilitation invoked by many classical studies may ultimately be less important than land use history in understanding current plant community composition in regenerating agricultural areas.://000268430900009Cumming, Graeme S. George, Ann 0921-2973ISI:00026843090000910.1007/s10980-009-9368-2<7Cumming, S. Vernier, P.2002oStatistical models of landscape pattern metrics, with applications to regional scale dynamic forest simulations433-444Landscape Ecology175boreal mixedwood forest Alberta Canada canonical correlation analysis forest configuration forest fragmentation forest inventory data fragstats landscape models landscape pattern metrics principal components analysis BOREAL MIXEDWOOD FRAGMENTATION ALBERTA BIRDSArticleOctForest managers in Canada need to model landscape pattern or spatial configuration over large (100,000 km(2)) regions. This presents a scaling problem, as landscape configuration is measured at a high spatial resolution, but a low spatial resolution is indicated for regional simulation. We present a statistical solution to this scaling problem by showing how a wide range of landscape pattern metrics can be modelled from low resolution data. Our study area comprises about 75,000 km(2) of boreal mixedwood forest in northeast Alberta, Canada. Within this area we gridded a sample of 84 digital forest cover maps, each about 9500 ha in size, to a resolution of 1 ha and used FRAGSTATS to compute a suite of landscape pattern metrics for each map. We then used multivariate dimension reduction techniques and canonical correlation analysis to model the relationship between landscape pattern metrics and simpler stand table metrics that are easily obtained from non-spatial forest inventories. These analyses were performed on four habitat types common in boreal mixedwood forests: young deciduous, old deciduous, white spruce, and mixedwood types. Using only three landscape variables obtained directly from stand attribute tables ( total habitat area, and the mean and standard deviation of habitat patch size), our statistical models explained more than 73% of the joint variation in five landscape pattern metrics ( representing patch shape, forest interior habitat, and patch isolation). By PCA, these five indices captured much of the total variability in the rich set of landscape pattern metrics that FRAGSTATS can generate. The predictor variables and strengths of association were highly consistent across habitat classes. We illustrate the potential use of such statistical relationships by simulating the regional, cumulative effects of wildfire and forest management on the spatial arrangement of forest patches, using non-spatial stand attribute tables.://000179388800005 ISI Document Delivery No.: 617YP Times Cited: 4 Cited Reference Count: 38 Cited References: 2000, CRITERIA INDICATORS *CAN COUNC FOR MIN, 2000, CRIT IND SUST FOR MA *ESRI, 1998, ARCV GIS VERS 3 1 *GLOB FOR WATCH CA, 2000, CAN FOR CROSSR ASS Y *STAT CORP, 1997, STAT STAT SOFTW REL BAKER WL, 1999, SPATIAL MODELLING FO BOULINIER T, 2001, ECOLOGY, V82, P1159 CUMMING SG, 1996, ECOGRAPHY, V19, P162 CUMMING SG, 1997, THESIS U BRIT COLUMB CUMMING SG, 2000, 200011 U ALB SUST FO CUMMING SG, 2000, P SOC CONS BIOL 14 A CUMMING SG, 2001, 20011 U ALB SUST FOR CUMMING SG, 2001, CAN J FOREST RES, V31, P1297 CUMMING SG, 2001, ECOL APPL, V11, P97 CUMMING SG, 2001, FOREST CHRON, V77, P501 DIX RL, 1971, CAN J BOT, V49, P657 ELKIE PC, 2001, FOREST ECOL MANAG, V147, P253 GILLIS MD, 1993, PIX114 PET NAT FOR I HAIR JF, 1995, MULTIVARIATE DATA AN KABZEMS A, 1986, TECHNICAL B SASKATCH, V8 KING AW, 1991, QUANTITATIVE METHODS KREMSATER LL, 1999, FOREST FRAGMENTATION KURZ WA, 2000, COMPUT ELECTRON AGR, V27, P227 LEHMKUHL JF, 1993, J WILDLIFE MANAGE, V57, P302 MAURER BA, 1999, UNTANGLING ECOLOGICA MCGARIGAL K, 1995, ECOL MONOGR, V65, P235 MCGARIGAL K, 1995, PNWGTR351 US FOR SER MLADENOFF DJ, 1999, SPATIAL MODELING FOR MOSS EH, 1932, J ECOL, V20, P380 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 ROWE JS, 1972, PUBLICATION CANADIAN, V1300 RYKIEL EJ, 1996, ECOL MODEL, V90, P229 SCHMIEGELOW FKA, 1997, THESIS U BRIT COLUMB SEMENCHUK GP, 1992, ATLAS BREEDING BIRDS STRONG WL, 1992, T244 ENR ALB FOR LAN VILLARD MA, 1999, CONSERV BIOL, V13, P774 WALTERS C, 1992, ECOL APPL, V2, P189 WITH KA, 2001, BIOL CONSERV, V100, P75 0921-2973 Landsc. Ecol.ISI:000179388800005Boreal Ecosyst Res Ltd, Edmonton, AB T6H 2W1, Canada. Vernier, P, Univ British Columbia, Dept Forest Sci, Ctr Appl Conservat Biol, 3004-2424 Main Mall, Vancouver, BC V6T 1Z4, Canada.English? LCushman, S. Raphael, M. Ruggiero, L. Shirk, A. Wasserman, T. O’Doherty, E.2011WLimiting factors and landscape connectivity: the American marten in the Rocky Mountains 1137-1149Landscape Ecology268Springer NetherlandsEarth and Environmental ScienceIn mobile animals, movement behavior can maximize fitness by optimizing access to critical resources and minimizing risk of predation. We sought to evaluate several hypotheses regarding the effects of landscape structure on American marten foraging path selection in a landscape experiencing forest perforation by patchcut logging. We hypothesized that in the uncut pre-treatment landscape marten would choose foraging paths to maximize access to cover types that support the highest density of prey. In contrast, in the post-treatment landscapes we hypothesized marten would choose paths primarily to avoid crossing openings, and that this would limit their ability to optimally select paths to maximize foraging success. Our limiting factor analysis shows that different resistant models may be supported under changing landscape conditions due to threshold effects, even when a species’ response to landscape variables is constant. Our results support previous work showing forest harvest strongly affects marten movement behavior. The most important result of our study, however, is that the influence of these features changes dramatically depending on the degree to which timber harvest limits available movement paths. Marten choose foraging paths in uncut landscapes to maximize time spent in cover types providing the highest density of prey species. In contrast, following landscape perforation by patchcuts, marten strongly select paths to avoid crossing unforested areas. This strong response to patch cutting reduces their ability to optimize foraging paths to vegetation type. Marten likely avoid non-forested areas in fragmented landscapes to reduce risk of predation and to benefit thermoregulation in winter, but in doing so they may suffer a secondary cost of decreased foraging efficiency.+http://dx.doi.org/10.1007/s10980-011-9645-8 0921-297310.1007/s10980-011-9645-8|? $Cushman, Samuel A. Landguth, Erin L.2010/Scale dependent inference in landscape genetics967-979Landscape Ecology256JulEcological relationships between patterns and processes are highly scale dependent. This paper reports the first formal exploration of how changing scale of research away from the scale of the processes governing gene flow affects the results of landscape genetic analysis. We used an individual-based, spatially explicit simulation model to generate patterns of genetic similarity among organisms across a complex landscape that would result given a stipulated landscape resistance model. We then evaluated how changes to the grain, extent, and thematic resolution of that landscape model affect the nature and strength of observed landscape genetic pattern-process relationships. We evaluated three attributes of scale including thematic resolution, pixel size, and focal window size. We observed large effects of changing thematic resolution of analysis from the stipulated continuously scaled resistance process to a number of categorical reclassifications. Grain and window size have smaller but statistically significant effects on landscape genetic analyses. Importantly, power in landscape genetics increases as grain of analysis becomes finer. The analysis failed to identify the operative grain governing the process, with the general pattern of stronger apparent relationship with finer grain, even at grains finer than the governing process. The results suggest that correct specification of the thematic resolution of landscape resistance models dominates effects of grain and extent. This emphasizes the importance of evaluating a range of biologically realistic resistance hypotheses in studies to associate landscape patterns to gene flow processes.!://WOS:000278526000012Times Cited: 4 0921-2973WOS:00027852600001210.1007/s10980-010-9467-0n|? "Cushman, Samuel A. Lewis, Jesse S.2010JMovement behavior explains genetic differentiation in American black bears 1613-1625Landscape Ecology2510DecDIndividual-based landscape genetic analyses provide empirically based models of gene flow. It would be valuable to verify the predictions of these models using independent data of a different type. Analyses using different data sources that produce consistent results provide strong support for the generality of the findings. Mating and dispersal movements are the mechanisms through which gene flow operates in animal populations. The best means to verify landscape genetic predictions would be to use movement data to independently predict landscape resistance. We used path-level, conditional logistic regression to predict landscape resistance for American black bear (Ursus americanus) in a landscape in which previous work predicted population connectivity using individual-based landscape genetics. We found consistent landscape factors influence genetic differentiation and movement path selection, with strong similarities between the predicted landscape resistance surfaces. Genetic differentiation in American black bear is driven by spring movement (mating and dispersal) in relation to residential development, roads, elevation and forest cover. Given the limited periods of the year when gene flow events primarily occur, models of landscape connectivity should carefully consider temporal changes in functional landscape resistance.!://WOS:000283371000012Times Cited: 3 0921-2973WOS:00028337100001210.1007/s10980-010-9534-6 <7Cushman, S. A. McGarigal, K.2002LHierarchical, multi-scale decomposition of species-environment relationships637-646Landscape Ecology177canonical correspondence analysis hierarchy partial canonical ordination species-environment relationships variance decomposition GRADIENT ANALYSIS MODELArticleNovWe present an adaptation of existing variance partitioning methods to decompose species-environment relationships in hierarchically-structured, multi-scaled data sets. The approach translates a hierarchical, multi-scale conceptual model into a statistical decomposition of variance. It uses a series of partial canonical ordinations to divide the explained variance in species-environment relationships into its independent and confounded components, facilitating tests of the relative importance of factors at different organizational levels in driving system behavior. We discuss the method in the context of an empirical example based on forest bird community responses to multiple habitat scales in the Oregon Coast Range, USA. The example presents a two-tiered decomposition of the variation in the bird community that is explainable by a series of habitat factors nested within three spatial scales (plot, patch, and landscape). This method is particularly suited for the problems of hierarchically structured landscape data. The explicit multi-scale approach is a major step forward from conducting separate analyses at different scale levels, as it allows comprehensive analysis of the interaction of factors across scales and facilitates ecological interpretation in theoretical terms.://000179746400004 }ISI Document Delivery No.: 624EB Times Cited: 30 Cited Reference Count: 23 Cited References: ALLEN TFH, 1982, HIERARCHY PERSPECTIV ANDERSON MJ, 1998, AUST J ECOL, V23, P158 ANDERSON MJ, 1999, J STAT COMPUT SIM, V62, P271 BORCARD D, 1992, ECOLOGY, V73, P1045 BORCARD D, 1994, ENVIRON ECOL STAT, V1, P37 KOTLIAR NB, 1990, OIKOS, V59, P253 LEGENDRE P, 1994, ENV ECOLOGICAL STAT, V1, P57 LEGENDRE P, 1998, NUMERICAL ECOLOGY LIU QH, 1995, WATER AIR SOIL POLL, V1, P61 MCGARIGAL K, 1995, ECOL MONOGR, V65, P235 MCGARIGAL K, 1995, PNWGTR351 MCGARIGAL K, 2000, MULTIVARIATE STAT WI MCGARIGAL K, 2002, ECOLOGICAL APPL ONEILL RV, 1986, HIERARCHICAL CONCEPT SCHNEIDER DC, 1994, QUANTITATIVE ECOLOGY TERBRAAK CJF, 1986, ECOLOGY, V67, P1167 TERBRAAK CJF, 1988, ADV ECOL RES, V18, P271 TERBRAAK CJF, 1988, CLASSIFICATION RELAT, P551 TERBRAAK CJF, 1988, VEGETATIO, V75, P159 TERBRAAK CJF, 1992, BOOTSTRAPPING RELATE, P79 TERBRAAK CJF, 1998, CANOCO REFERENCE MAN WHITTAKER J, 1984, APPL STAT-J ROY ST C, V33, P52 WIENS JA, 1989, FUNCT ECOL, V3, P385 0921-2973 Landsc. Ecol.ISI:000179746400004Univ Massachusetts, Dept Nat Resources Conservat, Amherst, MA 01003 USA. Cushman, SA, Univ Massachusetts, Dept Nat Resources Conservat, Amherst, MA 01003 USA.English #<7B (Cushman, S. A. Shirk, A. Landguth, E. L.2012|Separating the effects of habitat area, fragmentation and matrix resistance on genetic differentiation in complex landscapes369-380Landscape Ecology273landscape genetics area configuration fragmentation limiting factors cdpop simulation thresholds species-environment relationships oregon coast range extinction thresholds population-dynamics fractal landscapes breeding birds forest models connectivity arrangementMar"Little is known about how variation in landscape mosaics affects genetic differentiation. The goal of this paper is to quantify the relative importance of habitat area and configuration, as well as the contrast in resistance between habitat and non-habitat, on genetic differentiation. We hypothesized that habitat configuration would be more influential than habitat area in influencing genetic differentiation. Population size is positively related to habitat area, and therefore habitat area should affect genetic drift, but not gene flow. In contrast, differential rates and patterns of gene flow across a landscape should be related to habitat configuration. Using spatially explicit, individual-based simulation modeling, we found that habitat configuration had stronger relationships with genetic differentiation than did habitat area, but there was a high degree of confounding between the effects of habitat area and configuration. We evaluated the predictive ability of six widely used landscape metrics and found that patch cohesion and correlation length of habitat are among the strongest individual predictors of genetic differentiation. Correlation length, patch density and clumpy are the most parsimonious set of variables to predict the magnitude of genetic differentiation in complex landscapes.://000300087500005-889QE Times Cited:1 Cited References Count:59 0921-2973Landscape EcolISI:000300087500005ZCushman, SA US Forest Serv, Rocky Mt Res Stn, 2500 S Pine Knoll Dr, Flagstaff, AZ 86001 USA US Forest Serv, Rocky Mt Res Stn, 2500 S Pine Knoll Dr, Flagstaff, AZ 86001 USA US Forest Serv, Rocky Mt Res Stn, Flagstaff, AZ 86001 USA Univ Washington, JISAO Climate Impacts Grp, Seattle, WA 98195 USA Univ Montana, Div Biol Sci, Missoula, MT 59812 USADOI 10.1007/s10980-011-9693-0English"<7 Cushman, S. A. Wallin, D. O.2000^Rates and patterns of landscape change in the Central Sikhote-alin Mountains, Russian Far East643-659Landscape Ecology157change detection FRAGSTATS landscape pattern remote sensing Russian Far East spatial analysis FOREST LANDSCAPE HABITAT FRAGMENTATION PACIFIC-NORTHWEST SATELLITE DATA RAIN-FORESTS DEFORESTATION BIODIVERSITY DYNAMICS IMAGERY OREGONArticleOctWe used Landsat imagery and GIS to quantify the rates and patterns of landscape change between 1972 and 1992 for a 734,126 ha forested study area in the central Sikhote-alin Mountains of the Russian Far East. The study area includes a portion of the Sikhote-alinskiy Biosphere Reserve which is a part of the United Nations international Man and the Biosphere (MAB) reserve network. Wildfire is a major disturbance agent throughout the area and timber harvesting outside the reserve is also important. Maximum likelihood classification of the satellite imagery identified four broad cover types (hardwood, conifer, mixed and non-forest) in 1992 and changes among them between 1972 and 1992. We used multi-temporal principal components analysis to describe the magnitude and direction of landscape change for six watersheds that represent a range of ecological histories and disturbance regimes. Overall, forest cover declined from 90.4% in 1972 to 77.2% in 1992. The disturbance rate was more than twice as high in conifer than in hardwood forests. The rate of disturbance outside the reserve was three times that inside. While the rates of disturbance are not markedly higher than those recorded from other temperate forests, there has recently been a large alteration in the disturbance regime which will lead to a general transformation of forest composition and structure in the study area if the trend continues.://000089421500005 ISI Document Delivery No.: 356AV Times Cited: 15 Cited Reference Count: 64 Cited References: *ESRI, 1994, UND GIS ARC INFO MET *PCI STAFF, 1995, US PCI SOFTW, V1 *PCI STAFF, 1995, US PCI SOFTW, V2 ANDREN H, 1994, OIKOS, V71, P355 BJORNDALEN JE, 1992, AGR ECOSYST ENVIRON, V40, P313 CISSEL JH, 1994, J FOREST, V92, P30 CISSEL JH, 1994, J FOREST, V98, P46 COHEN WB, 1995, INT J REMOTE SENS, V16, P721 COHEN WB, 1995, REMOTE SENSING CHANG COHEN WB, 1998, PHOTOGRAMM ENG REM S, V64, P293 CRIST EP, 1986, ESA PUBL DIVISION, P1465 CUSHMAN SA, 1997, THSIS W WASHINGTON U DOBRYNIN A, 1996, FRIENDS EARTH FAHRIG L, 1988, THEOR POPUL BIOL, V34, P194 FEARNSIDE PM, 1990, DEFORESTATION RATE B FIORELLA M, 1993, PHOTOGRAMM ENG REM S, V59, P239 FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 FRANKLIN JF, 1993, ECOL APPL, V3, P202 GREEN GM, 1990, SCIENCE, V248, P212 HALL FG, 1991, ECOLOGY, V72, P628 HANSEN AJ, 1991, BIOSCIENCE, V41, P382 HARGIS C, 1999, LANDSCAPE ECOL, V13, P167 HARGIS CD, 1999, J APPL ECOL, V36, P157 IVERSON LR, 1987, ADV SPACE RES, V7, P183 JENKINS MD, 1987, MADAGASCAR ENV PROFI KAMIBAYASHI N, 1994, JAPANESE J REMOTE SE, P213 KAREIVA P, 1990, PHILOS T ROY SOC B, V330, P175 KAREIVA P, 1995, NATURE, V373, P299 KAUTH RJ, 1976, P S MACHINE PROCES B, V4, P41 KHARKEVICH SS, 1988, VASCULAR PLANTS SOVI LAMBERSON RH, 1992, CONSERV BIOL, V6, P505 LILLESAND TM, 1994, REMOTE SENSING IMAGE LUQUE SS, 1994, LANDSCAPE ECOL, V9, P287 MARSHALL S, 1997, J FISH BIOL, V51, P526 MCCUNE B, 1995, PCORD MULTIVARIATE A MCGARIGAL K, 1995, 351 PNW US FOR SERV MCGARIGAL K, 1995, ECOL MONOGR, V65, P235 MIQUELLE DG, 1995, A HABITAT PROTECTION MIQUELLE DG, 1996, J WILDLIFE RES, V1, P138 MIQUELLE DG, 1999, RIDING TIGER TIGER C MORRISON PH, 1991, ANCIENT FORESTS PACI MYERS N, 1980, CONVERSION TROPICAL NELSON R, 1987, INT J REMOTE SENS, V8, P1767 NEWELL J, 1996, RUSSIAN FAR E FRIEND PRYDE PR, 1991, ENV MANAGEMENT SOVIE RIPPLE WJ, 1991, BIOL CONSERV, V57, P73 RITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 SACHS DL, 1998, CAN J FOREST RES, V28, P23 SADER SA, 1987, P IGARSS 87 S ANN AR, P209 SADER SA, 1988, BIOTROPICA, V20, P11 SAUNDERS DA, 1991, CONSERV BIOL, V5, P1 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SHAO GF, 1996, CAN J FOREST RES, V26, P206 SHIVLIKOV A, 1995, UNPUB CLASSIFICATION SKOLE D, 1993, SCIENCE, V260, P1905 SMIRNOV EN, 1999, RIDING TIGER TIGER C SPIES TA, 1994, ECOL APPL, V4, P555 TIAN H, 1995, WATER AIR SOIL POLL, V82, P465 TUCKER CJ, 1984, REMOTE SENS ENVIRON, V15, P255 TURNER MG, 1996, ECOL APPL, V6, P1150 WALKER K, 1988, PHOTOGRAMMETRIC ENG, V54, P373 WALLIN DO, 1994, ECOL APPL, V4, P569 WALLIN DO, 1996, FOREST ECOL MANAG, V85, P291 ZHENG DL, 1997, LANDSCAPE ECOL, V12, P241 0921-2973 Landsc. Ecol.ISI:000089421500005Western Washington Univ, Huxley Coll Environm Studies, Ctr Environm Sci, Bellingham, WA 98225 USA. Cushman, SA, Univ Massachusetts, Dept Forestry & Wildlife Management, Amherst, MA 01003 USA.EnglishI<7!Cyr, D. Gauthier, S. Bergeron, Y.2007oScale-dependent determinants of heterogeneity in fire frequency in a coniferous boreal forest of eastern Canada 1325-1339Landscape Ecology229GIS; DEM; top-down; bottom-up; picea mariana; abies balsamea; cote-Nord; cox regression; partial likelihood NORTHERN DISTRIBUTION; TEMPORAL VARIATIONS; SPATIAL-PATTERNS; CLIMATE-CHANGE; JACK PINE; QUEBEC; MANAGEMENT; LANDSCAPES; DYNAMICS; DISTURBANCEArticleNov\Despite the recognized importance of fire in North American boreal forests, the relative importance of stochastic and determinist portions of intra-regional spatial variability in fire frequency is still poorly understood. The first objective of this study is to identify sources of spatial variability in fire frequency in a landscape of eastern Quebec's coniferous boreal forest. Broad-scale environmental factors considered included latitude, longitude, human activities and belonging to a given bioclimatic domain, whereas fine-scale factors included slope, position on the slope, aspect, elevation, surficial deposit and drainage. The average distance to waterbodies was also considered as a potential intermediate-scale source of variability in fire frequency. In order to assess these environmental factors' potential influence, they were incorporated into a proportional hazard model, a semi-parametric form of survival analysis. We also used a digital elevation model in order to evaluate the dominant aspect within neighborhoods of varying sizes and successively incorporated these covariates into the proportional hazard model. We found that longitude significantly affects fire frequency, suggesting a maritime influence on fire frequency in this coastal landscape. We also found that position on the slope was related to fire frequency since hilltops and upperslopes were subject to a lower fire frequency. Dominant aspect was also related to fire frequency, but only when characterized within a neighborhood delimited by 4,000 to 10,000-m radii (5,027-31,416 ha). A 2-6-fold variation in fire frequency can be induced by geographic and topographic contexts, suggesting a substantial intra-regional heterogeneity in disturbance regime with potential consequences on forest dynamics and biodiversity patterns. Implications for forest management are also briefly discussed.://000250207500006 #Cited Reference Count: 78 Cited References: 1996, CANADIAN CLIMATE NOR *ESRI, 2000, ARCVIEW GIS 3 2A *SAS I INC, 2001, 8 02 SAS ALLISON PD, 1995, SURVIVAL ANAL USING ANDISON DW, 2003, TACTICAL FOREST PLAN ANGELSTAM P, 1997, ECOL B, V46, P140 ARNO SF, 1977, INT42 USDA FOR SERV ASSELIN H, 2003, J BIOGEOGR, V30, P1709 ATTIWILL PM, 1994, FOREST ECOL MANAG, V63, P247 BAKER WL, 1992, LANDSCAPE ECOL, V3, P191 BEATY RM, 2001, J BIOGEOGR, V28, P955 BERGERON Y, 1998, J VEG SCI, V9, P493 BERGERON Y, 2001, CAN J FOREST RES, V31, P381 BERGERON Y, 2004, ECOLOGY, V85, P1916 BERGERON Y, 2006, CAN J FOREST RES, V36, P2737 BESSIE WC, 1995, ECOLOGY, V76, P747 BONAZOUNTAS M, 2005, HUM ECOL RISK ASSESS, V11, P617 BRONCANO MJ, 2004, INT J WILDLAND FIRE, V13, P209 CLARK JS, 1990, ECOL MONOGR, V60, P135 COX DR, 1972, J ROY STAT SOC B MET, V34, P187 CYR D, 2005, CAN J FOREST RES, V35, P65 DELONG SC, 2000, FOREST ECOL MANAG, V131, P93 DEON RG, 2004, FOREST CHRON, V80, P341 DESPONTS M, 1992, CAN J BOT, V70, P1157 DISSING D, 2003, CAN J FOREST RES, V33, P770 DORNER B, 2002, LANDSCAPE ECOL, V17, P729 ENGELMARK O, 1987, ANN BOT FENN, V24, P317 FLANNIGAN MD, 1988, J APPL METEOROL, V27, P441 FLANNIGAN MD, 1993, INT J WILDLAND FIRE, V3, P241 FLANNIGAN MD, 1998, J VEG SCI, V9, P477 FRANKLIN JF, 1993, ECOL APPL, V3, P202 FRELICH LE, 1995, ECOL MONOGR, V65, P325 GAUTHIER S, 1996, ENVIRON MONIT ASSESS, V39, P417 GAUTHIER S, 2001, NAT CAN, V125, P10 GAVIN DG, 2003, ECOLOGY, V84, P186 GRENIER DJ, 2005, CAN J FOREST RES, V35, P656 GRONDIN P, 1996, MANUEL FORESTERIE PR HEINSELMAN ML, 1973, QUATERNARY RES, V3, P329 HELLBERG E, 2004, CAN J FOREST RES, V34, P332 HEYERDAHL EK, 2001, ECOLOGY, V82, P660 HIRSCH K, 2001, FOREST CHRON, V77, P357 HUNTER ML, 1988, CONSERV BIOL, V2, P375 HUNTER ML, 1990, WILDLIFE FORESTS FOR JOHNSON EA, 1991, ECOLOGY, V72, P194 JOHNSON EA, 1992, FIRE VEGETATION DYNA JOHNSON EA, 1994, ADV ECOL RES, V25, P239 KAFKA V, 2001, INT J WILDLAND FIRE, V10, P119 KASISCHKE ES, 2002, INT J WILDLAND FIRE, V11, P131 KEANE RE, 2004, EMULATING NATURAL DI KNOWLES JB, 1993, THESIS COLORADO STAT KRAWCHUK MA, 2006, ECOLOGY, V87, P458 KUSHLA JD, 1998, INT J REMOTE SENS, V19, P2493 LARSEN CPS, 1997, J BIOGEOGR, V24, P663 LEFORT P, 2003, FOREST SCI, V49, P509 LEGOFF H, 2004, CAN J FOREST RES, V34, P2399 LEGOFF S, 2005, FOREST CHRON, V81, P582 LERTZMAN K, 1998, ECOLOGICAL SCALE THE LERTZMAN K, 1998, NW SCI, V72, P4 LESIEUR D, 2002, CAN J FOREST RES, V32, P1996 MASTERS AM, 1990, CAN J BOT, V68, P1763 MERMOZ M, 2005, ECOLOGY, V86, P2705 MORITZ MA, 2004, FRONT ECOL ENVIRON, V2, P67 NOSS RF, 1987, BIOL CONSERV, V41, P11 PARISIEN MA, 2003, CAN J FOREST RES, V33, P243 PAYETTE S, 1992, SYSTEM ANAL GLOBAL B PENG CH, 2000, J ENVIRON SCI, V12, P257 REED WJ, 1998, FOREST SCI, V44, P465 ROBITAILLE A, 1998, PAYSAGES REGIONAUX Q SAUCIER JP, 1994, POINT OBSERVATION EC SCHIMMEL J, 1996, ECOLOGY, V77, P1436 SCHULTE LA, 2005, ECOSYSTEMS, V8, P73 SEYMOUR RS, 1999, MAINTAINING BIODIVER STOCKS BJ, 2002, J GEOPHYS RES-ATMOS, V108 THOMPSON ID, 1998, ENVIRON MONIT ASSESS, V49, P213 VAZQUEZ A, 2001, FOREST ECOL MANAG, V147, P55 WEBER MG, 1997, ENV REV, V5, P145 WEIN RW, 1983, ROLE FIRE N CIRCUMPO WEISBERG PJ, 2004, FOREST SCI, V50, P245 0921-2973 Landsc. Ecol.ISI:000250207500006Univ Quebec, Ctr Etude Foret, Montreal, PQ H3P 3P8, Canada. Nat Resources Canada, Laurentian Forestry Ctr, Quebec City, PQ G1V 4C7, Canada. Univ Quebec, Ind Chair Sustainable Forest Management, NSERC UQAT UQAM, Quebec City, PQ J9X 5E4, Canada. Cyr, D, Univ Quebec, Ctr Etude Foret, CP 8888, Montreal, PQ H3P 3P8, Canada. cyr.dominic@gmail.com sgauthier@cfl.forestry.ca yves.bergeron@uqat.caEnglish<7D'Eon, R. G. Glenn, S. M.2005The influence of forest harvesting on landscape spatial patterns and old-growth-forest fragmentation in southeast British Columbia19-33Landscape Ecology201Canada; managed forests; landscape indices; landscape metrics; patches HABITAT FRAGMENTATION; BREEDING BIRDS; PATCH SHAPE; CONNECTIVITY; EXTINCTION; INDEXES; OREGON; PSEUDOREPLICATION; ORGANISMS; DYNAMICSArticleJanHabitat fragmentation is considered one of the major conservation issues of recent decades. We tested predictions of landscape patterns in a 352,253-ha managed forest area in southeast British Columbia. We did this by focussing on forest fragmentation concerns among old-growth, harvest, and wildfire patches in 44 delineated landscapes using patch indices as measures of landscape pattern. We found no significant association between amount of harvesting and 15 old-growth patch indices. Comparisons among patch types revealed that amounts and spatial patterns of harvest patches diered little from amounts and spatial patterns of old-growth patches in control landscapes. Variability indices revealed similar variability between harvest patches and old-growth patches, and more variability between harvest patches and wildfire patches. Little of the evidence gathered in this study supported predictions of fragmentation of old-growth spatial patterns, or predicted dierences between harvest spatial patterns and more naturally occurring spatial patterns. We suggest these results could be due to the relatively small amounts of harvesting and old-growth forest in these landscapes, and therefore habitat amount may be a more important factor than spatial configuration of patches in these landscapes.://000231223900002  ISI Document Delivery No.: 955KD Times Cited: 0 Cited Reference Count: 55 Cited References: *BC MIN FOR BC MIN, 1995, FOR PRACT COD BIOD G *SPSS INC, 1998, SYSTAT 8 0 WIND ANDREN H, 1994, OIKOS, V71, P355 BAKER WL, 1993, OIKOS, V66, P66 BRAUMANDL TF, 1992, FIELD GUIDE SITE IDE CLARK PJ, 1954, ECOLOGY, V35, P445 DAVIDSON C, 1998, WILDLIFE SOC B, V26, P32 DEBINSKI DM, 2000, CONSERV BIOL, V14, P342 DEON R, 2002, CONSERV ECOL, V6 DEON RG, 2000, FOREST CHRON, V76, P475 DEON RG, 2002, FOREST CHRON, V78, P686 DEON RG, 2002, THESIS U BRIT COLUMB FAHRIG L, 1997, J WILDLIFE MANAGE, V61, P603 FORMAN RT, 1997, LAND MOSIACS ECOLOGY FOWLER J, 1998, PRACTICAL STAT FIELD FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 GARRABOU J, 1998, LANDSCAPE ECOL, V13, P225 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 GUTZWILLER KJ, 1992, LANDSCAPE ECOL, V6, P293 HAGAR HA, 1998, BIODIVERS CONSERV, V7, P1069 HAILA Y, 2002, ECOL APPL, V12, P321 HAMAZAKI T, 1996, LANDSCAPE ECOL, V11, P299 HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HARGROVE WW, 1992, LANDSCAPE ECOL, V6, P251 HARRIS LD, 1984, FRAGMENTED FOREST HULSHOFF RM, 1995, LANDSCAPE ECOL, V10, P101 HURLBERT SH, 1984, ECOL MONOGR, V54, P187 HURLBERT SH, 1990, OIKOS, V58, P257 KOZAK A, 1995, FOREST CHRON, V71, P326 KREMSATER L, 1999, FOREST FRAGMENTATION, P1178 KRUMMEL JR, 1987, OIKOS, V48, P321 MACARTHUR RH, 1967, THEORY ISLAND BIOGEO MCGARIGAL K, 1995, ECOL MONOGR, V65, P235 MCGARIGAL K, 2002, ECOL APPL, V12, P335 MEYER JS, 1998, WILDLIFE MONOGR, V139, P1 MILLER R, 1985, ENCY STAT SCI, V5, P670 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 ONEILL RV, 1988, LANDSCAPE ECOL, V2, P63 PATON DR, 1975, WILDLIFE SOC B, V3, P171 PIMM SL, 1988, AM NAT, V132, P757 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 RIPPLE WJ, 1991, BIOL CONSERV, V57, P73 ROWE JS, 1972, CANADIAN FOREST SERV, V1300 SACHS DL, 1998, CAN J FOREST RES, V28, P23 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SPIES TA, 1994, ECOL APPL, V4, P555 STAUFFER D, 1985, INTRO PERCOLATION TH TISCHENDORF L, 2000, LANDSCAPE ECOL, V15, P633 TRZCINSKI MK, 1999, ECOL APPL, V9, P586 TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 VILLARD MA, 1999, CONSERV BIOL, V13, P774 WADE TG, 2003, CONSERV ECOL, V7 WALLIN DO, 1996, FOREST ECOL MANAG, V85, P291 WILCOX BA, 1985, AM NAT, V125, P879 0921-2973 Landsc. Ecol.ISI:000231223900002Univ British Columbia, Ctr Appl Conservat Res, Dept Forest Sci, Vancouver, BC V6T 1Z4, Canada. D'eon, RG, 414 Observ St, Nelson, BC V1L 4Y6, Canada. rdeon@interchange.ubc.caEnglish8?$Dagmar, Söndgerath Boris, Schröder2002oPopulation dynamics and habitat connectivity affecting the spatial spread of populations – a simulation study57-70Landscape Ecology171Cellular automaton - Dispersal - Habitatsuitability - Habitat connectivity - Leslie matrix - Population dynamics - Spatially explicitmodeling - Stepping stonehabitatsIn this paper we show how the spatialconfiguration of habitat quality affects the spatial spread of apopulation in a heterogeneous environment. Our main result is thatfor species with limited dispersal ability and a landscape withisolated habitats, stepping stone patches of habitat greatlyincrease the ability of species to disperse. Our results showthat increasing reproductive rate first enables and thenaccelerates spatial spread, whereas increasing the connectivity has aremarkable effect only in case of low reproductive rates. Theimportance of landscape structure varied according to thedemographic characteristics of the population. To show this wepresent a spatially explicit habitat model taking into accountpopulation dynamics and habitat connectivity. The population dynamicsare based on a matrix projection model and are calculated on eachcell of a regular lattice. The parameters of the Leslie matrix dependon habitat suitability as well as density. Dispersal between adjacentcells takes place either unrestricted or with higher probability inthe direction of a higher habitat quality (restricted dispersal).Connectivity is maintained by corridors and stepping stones ofoptimal habitat quality in our fragmented model landscape containinga mosaic of different habitat suitabilities. The cellular automatonmodel serves as a basis for investigating different combinations ofparameter values and spatial arrangements of cells with high and lowquality*http://dx.doi.org/10.1023/A:1015237002145 /10.1023/A:1015237002145 Dagmar Söndgerath Email: d.soendgerath@tu-bs.de Boris Schröder Email: boris.schroeder@uni-oldenburg.de References Adler G.H. and Wilson M.L. 1985. Small mammals on Massachusetts islands: the use of probability functions in clarifying biogeographic relationships. Oecologia 66: 178-186. Akçakaya H.R. and Atwood J.L. 1997. A habitat-based metapopulation model of the california gnatcatcher. Conserv. Biol. 11: 422-434. Akçakaya H.R., McCarthy M.A. and Pearce J.L. 1995. Linking landscape data with population viability analysis: management options for the helmeted honeyeater Lichenostomus melanops cassidix. Biol. Conserv. 73: 169-176. Amarasekare P. 1998. Interactions between local dynamics and dispersal: insights from single species models. Theor. Popul. 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With K.A. and Crist T.O. 1995. Critical thresholds in species responses to landscape structure. Ecology 76: 2446-2459. With K.A., Gardner R.H. and Turner M.G. 1997. Landscape connectivity and population distributions in heterogeneous environments. Oikos 78: 151-169. With K.A. and King A.W. 1999. Extinction thresholds for species in fractal landscapes. Conserv. Biol. 13: 314-326. Tischendorf and Fahrig 2000a. On the usage and measurement of landscape connectivity. OIKOS 90: 7-19. Tischendorf and Fahrig 2000b. How should we measure landscape connectivity? Landscape Ecol. 15: 633-641. +Dagmar Söndgerath1 and Boris Schröder2 (1) Institute of Geoecology, Technical University of Braunschweig, Langer Kamp 19c, D-38106 Braunschweig, Germany (2) Department of Biology, Earth and Environmental Sciences, University of Oldenburg, Landscape Ecology Group, D-26111 Oldenburg, Germany |?7Dahlin, Kyla M. Asner, Gregory P. Field, Christopher B.2014qLinking vegetation patterns to environmental gradients and human impacts in a mediterranean-type island ecosystem 1571-1585Landscape Ecology299NovVegetation patterns at the landscape scale are shaped by myriad processes and historical events, and understanding the relative importance of these processes aids in predicting current and future plant distributions. To quantify the influence of different environmental and anthropogenic patterns on observed vegetation patterns, we used simultaneous autoregressive modeling to analyze data collected by the Carnegie Airborne Observatory over Santa Cruz Island (SCI; California, USA). SCI is a large continental island, and its limited suite of species and well documented land use history allowed us to consider many potential determinants of vegetation patterns, such as topography, substrate, and historical grazing intensity. As a metric of vegetation heterogeneity, we used the normalized difference vegetation index (NDVI) stratified into three vegetation height classes using LiDAR (short, medium, and tall). In the SAR models topography and substrate type were important controls, together explaining 8-15 % of the total variation in NDVI, but historical grazing and spatial autocorrelation were also key components of the models, together explaining 17-21 % of the variation in NDVI. Optimal spatial autocorrelation distances in the short and medium height vegetation models (600-700 m) were similar to the home range sizes of two crucial seed dispersers on the island-the island fox (Urocyon littoralis santacruzae) and the island scrub-jay (Aphelocoma insularis)-suggesting that these animals may be important drivers of the island's vegetation patterns. This study highlights the importance of dynamic processes like dispersal limitation and disturbance history in determining present-day vegetation patterns.!://WOS:000343648700009Times Cited: 0 0921-2973WOS:00034364870000910.1007/s10980-014-0076-1 <7C Dainese, M. Poldini, L.2012lPlant and animal diversity in a region of the Southern Alps: the role of environmental and spatial processes417-431Landscape Ecology273climate elevation habitat heterogeneity human impact land use pcnm variation partitioning species-richness patterns agricultural intensification land-cover elevational gradients landscape structure neighbor matrices ecological data european alps water-energy biodiversityMarDifferent organisms respond to landscape configuration and spatial structure in different terms and across different spatial scales. Here, regression models with variation partitioning were applied to determine relative influence of the three groups of variables (climate, land use and environmental heterogeneity) and spatial structure variables on plant, bird, orthopteran and butterfly species richness in a region of the Southern Alps, ranging in elevation from the sea level to 2,780 m. Grassland and forest cover were positively correlated with species richness in both taxonomic groups, whilst species richness decreased with increasing urban elements and arable land. The variation was mainly explained by the shared component between the three groups in plants and between landscape and environmental heterogeneity in birds. The variation was related to independent land use effect in insects. The distribution in species richness was spatially structured for plants, birds and orthopterans, whilst in butterflies, no spatial structure was detected. Plant richness was associated with linear trend variation and broad-scale spatial structure in the northern part of the region, whilst bird richness with broad-scale variation which occurs on the external Alpine ridge. Orthopteran diversity was strongly related to fine-scale spatial structure, generated by dynamic processes or by unmeasured spatially structured abiotic factors. Although the study was carried out in relatively small area, the four taxonomic groups seem to respond to biodiversity drivers in a surprisingly different way. This has considerable implications for conservation planning as it restricts the usefulness of simple indicators in prioritizing areas for conservation purposes.://000300087500009-889QE Times Cited:0 Cited References Count:70 0921-2973Landscape EcolISI:0003000875000094Dainese, M Univ Padua, Dept Land & Agroforest Environm, Viale Univ 16, I-35020 Legnaro, PD, Italy Univ Padua, Dept Land & Agroforest Environm, Viale Univ 16, I-35020 Legnaro, PD, Italy Univ Padua, Dept Land & Agroforest Environm, I-35020 Legnaro, PD, Italy Univ Trieste, Dept Life Sci, I-34127 Trieste, ItalyDOI 10.1007/s10980-011-9687-yEnglish b<7Dale, M. R. T.20004Lacunarity analysis of spatial pattern: A comparison467-478Landscape Ecology1557scale patch pattern analysis transect PLANT COMMUNITIESArticleJulVLacunarity analysis has been proposed as a general method for the analysis of spatial pattern, in particular for patterns of the dispersion of points. The method is clearly an improvement over the variance:mean ratio approach based on quadrat counts, because it examines dispersion at a range of spatial scales. This paper examines the properties of lacunarity analysis and compares it with other methods of pattern analysis. Lacunarity analysis gives different results for complementary patterns, which may be an advantage depending on circumstances. The method, however, is not precise in determining the scale or the patch size in pattern with known properties. A modification that improves the interpretability of the results of the analysis is introduced but a weakness of this approach is that it does provide clear indications of the characteristics of cases that exhibit more than one scale of pattern. Because different methods react to different features in data, it is recommended that data be analysed by more than one method and the results compared for greater insight into their characteristics.://000088036700006 [ISI Document Delivery No.: 331UH Times Cited: 14 Cited Reference Count: 24 Cited References: ALLAIN C, 1991, PHYS REV A, V44, P552 BRADSHAW GA, 1992, J ECOL, V80, P205 CARLILE DW, 1989, LANDSCAPE ECOLOGY, V2, P203 DALE MRT, 1989, J ECOL, V77, P78 DALE MRT, 1990, J VEG SCI, V1, P153 DALE MRT, 1998, J VEG SCI, V9, P805 DALE MRT, 1999, SPATIAL PATTERN ANAL DIGGLE PJ, 1983, STAT ANAL SPATIAL PO GREIGSMITH P, 1983, QUANTITATIVE PLANT E HILL MO, 1973, J ECOL, V61, P225 HURLBERT SH, 1990, OIKOS, V58, P257 KENKEL NC, 1993, ABSTR BOT, V17, P53 LEPS J, 1990, SPATIAL PROCESSES PL, P71 MANDELBROT BB, 1982, FRACTAL GEOMETRY NAT MANLY BFJ, 1997, RANDOMIZATION BOOTST PIELOU EC, 1977, MATH ECOLOGY PLOTNICK RE, 1993, LANDSCAPE ECOL, V8, P201 PLOTNICK RE, 1996, PHYS REV E B, V53, P5461 RIPLEY BD, 1978, J ECOL, V66, P965 SOKAL RR, 1981, BIOMETRY TURNER SJ, 1991, QUANTITATIVE METHODS, P17 UPTON GJG, 1985, SPATIAL DATA ANAL EX, V1 VERHOEF JM, 1993, J VEG SCI, V4, P441 WU YG, 1997, ECOL APPL, V7, P268 0921-2973 Landsc. Ecol.ISI:000088036700006Univ Alberta, Dept Biol Sci, Edmonton, AB T6G 2E9, Canada. Dale, MRT, Univ Alberta, Dept Biol Sci, Edmonton, AB T6G 2E9, Canada.Englishڼ7BDale, VirginiaH Kline, KeithL Kaffka, StephenR Langeveld, J. W. A.2013AA landscape perspective on sustainability of agricultural systems 1111-1123Landscape Ecology286Springer NetherlandsFContext Farm Incentives Indicators Scale Spatial heterogeneity Systems 2013/07/01+http://dx.doi.org/10.1007/s10980-012-9814-4(Hans) 0921-2973Landscape Ecol10.1007/s10980-012-9814-4English|?& 7Dale, Virginia H. Efroymson, Rebecca A. Kline, Keith L.2011(The land use-climate change-energy nexus755-773Landscape Ecology266JulrLandscape ecology focuses on the spatial patterns and processes of ecological and human interactions. These patterns and processes are being altered by both changing resource-management practices of humans and changing climate conditions associated, in part, with increases in atmospheric concentrations of greenhouse gases. Dominant resource-extraction and land-management activities involve energy, and the use of fossil energy is one of the key drivers behind increasing greenhouse gas emissions as well as land-use changes. Alternative energy sources (such as wind, solar, nuclear, and bioenergy) are being explored to reduce greenhouse gas emission rates. Yet, energy production, including alternative-energy options, can have a wide range of effects on land productivity, surface cover, albedo, and other factors that affect carbon, water, and energy fluxes and, in turn, climate. Meanwhile, climate influences the potential output, relative efficiencies, and sustainability of alternative energy sources. Thus, land use, climate change, and energy choices are linked, and any comprehensive analysis in landscape ecology that considers one of these factors should be cognizant of these interactions. This analysis explores the implications of linkages between land use, climate hange, and energy and points out ecological patterns and processes that may be affected by their interactions.!://WOS:000291485400001Times Cited: 0 0921-2973WOS:00029148540000110.1007/s10980-011-9606-2x?'Dale, V.H. R.H. Gardner M.G. Turner1989LPredicting across scales: Comments of the guest editors of landscape ecology147-151Landscape Ecology33/4scaling, lansdscape ecology ?*;V.H. Dale L.K. Mann R.J. Olson D.W. Johnson K.C. Dearstone1990DThe long-term influence of past land use on the Walker Branch forest211-224Landscape Ecology44Hcalcium, forest, insects, land use, landscape ecology, soils, successionForest structure and composition influence patterns of insect outbreaks and can be explained on the Walker Branch watershed by past land use (timber harvest and agriculture), soils, aspect, and slope. In particular, pine bark beetles caased large losses of pine on sites that had been used for agriculture, on Fullerton silt loam soils, and on north-to-northeast and east-to-southeast exposures. Hickory bark beetles had a high impact on hickory biomass on Bodine soil areas that were forested in 1935 and sloped greater than 11 To. Thus, prior land use can have an indirect effect on future disturbances. Because forest disturbances can affect nutrient distribution, land use can also indirectly affect nutrient availability. For example, locations of hickory bark beetle outbreaks experience a large flux of calcium from dead wood to soil because hickory accumulates large amounts of calcium in woody tissue. The research demonstrates a link between past land use, insect outbreaks, and calcium cycling.ڽ7H/Dalkvist, Trine Sibly, RichardM Topping, ChrisJ2013PLandscape structure mediates the effects of a stressor on field vole populations 1961-1974Landscape Ecology2810Springer NetherlandsgEpigenetics Population-level risk assessment Ecotoxicology Microtus agrestis Modelling Spatial dynamics 2013/12/01+http://dx.doi.org/10.1007/s10980-013-9932-7 0921-2973Landscape Ecol10.1007/s10980-013-9932-7English<7Danielson, B. J. Hubbard, M. W.2000rThe influence of corridors on the movement behavior of individual Peromyscus polionotus in experimental landscapes323-331Landscape Ecology154clearcut corridor dispersal experimental landscape movement behavior old-field mice patch Peromyscus polionotus SMALL MAMMALS POPULATION SURVIVAL COMPLEX LANDSCAPES HABITAT CONNECTIVITY DISPERSAL DYNAMICS MODELS TERRITORIALITY CONSERVATIONArticleMayuTo assess corridor effects on movement in Peromyscus polionotus (old-field mice), we used a set of three experimental landscapes that contained multiple patches (1.64 ha) of usable, open habitat embedded in a loblolly pine (Pinus taeda) forest matrix. Some patches were connected by corridors and others were isolated (unconnected). We introduced mice to nest boxes in experimental patches and followed them through the landscapes via trapping. We found weak evidence that the presence of corridors decreased the probability that P. polionotus (particularly females) would disperse or disappear from a patch. In the process of live trapping the patches, we also encountered 'feral' P. polionotus, Sigmodon hispidus (cotton rats), and Peromyscus gossypinus (cotton mice). The average number of feral animals did not differ between isolated and connected patches. This suggests that corridors do not act as drift fences that 'sieve' individuals out of the matrix and into the patches. However, more male than female P. polionotus and S. hispidus were trapped in isolated patches. This intersexual difference did not exist in connected patches.://000086006700002 ISI Document Delivery No.: 296DA Times Cited: 25 Cited Reference Count: 43 Cited References: AKCAKAYA HR, 1990, RAMAS SPACE SPATIALL ANDERSON GS, 1995, THESIS IOWA STATE U ANDERSON GS, 1997, LANDSCAPE ECOL, V12, P261 ANDREASSEN HP, 1998, ECOLOGY, V79, P1223 BENNETT AF, 1990, HABITAT CORRIDORS TH BENNETT AF, 1990, LANDSCAPE ECOL, V4, P109 BENNETT AF, 1994, BIOL CONSERV, V68, P155 BOWNE DR, 1999, LANDSCAPE ECOL, V14, P53 BUNCE RGH, 1992, SPECIES DISPERSAL AG CONROY MJ, 1995, ECOL APPL, V5, P17 DANIELSON BJ, 1987, ECOLOGY, V68, P1778 DANIELSON BJ, 1987, J MAMMAL, V68, P160 DANIELSON BJ, 1999, ECOLOGY SMALL MAMMAL, P89 DAVENPORT LB, 1964, J MAMMAL, V45, P95 DRAMSTAD WE, 1996, LANDSCAPE ECOLOGY PR DUNNING JB, 1992, OIKOS, V65, P169 DUNNING JB, 1995, ECOL APPL, V5, P3 FAHRIG L, 1985, ECOLOGY, V66, P1762 FAHRIG L, 1994, CONSERV BIOL, V8, P50 FORMAN RTT, 1995, LAND MOSAICS GOLLEY FB, 1965, J MAMMAL, V46, P1 HADDAD NM, 1999, ECOL APPL, V9, P623 HALAMA KJ, 1994, OIKOS, V69, P107 HANSSON L, 1987, HOLARCTIC ECOL, V10, P154 HENEIN K, 1990, LANDSCAPE ECOL, V4, P157 IMS RA, 1995, MOSAIC LANDSCAPES EC, P85 JOHNSON ML, 1990, ANNU REV ECOL SYST, V21, P449 KING JA, 1983, CAN J ZOOL, V61, P2740 LAPOLLA VN, 1993, LANDSCAPE ECOL, V8, P25 LEFKOVITCH LP, 1985, ECOL MODEL, V30, P297 MERRIAM G, 1990, LANDSCAPE ECOL, V4, P123 OPDAM P, 1988, MUNSTERSCHE GEOGRAPH, V29, P75 PULLIAM HR, 1992, ECOL APPL, V2, P165 STAMPS JA, 1987, AM NAT, V129, P533 STENSETH NC, 1992, ANIMAL DISPERSAL SMA STICKEL LF, 1968, AM SOC MAMM SPEC PUB, V2, P373 SZZCKI J, 1987, ACTA THERIOL, V32, P31 TAYLOR PD, 1993, OIKOS, V68, P571 WEGNER JF, 1979, CONS BIOL, V2, P349 WIENS JA, 1993, OIKOS, V66, P369 WOLFF JO, 1983, BEHAV ECOL SOCIOBIOL, V12, P237 WOLFF JO, 1993, OIKOS, V68, P364 WOLFF JO, 1998, ETHOL ECOL EVOL, V10, P227 0921-2973 Landsc. Ecol.ISI:000086006700002Iowa State Univ, Dept Anim Ecol, Ames, IA 50011 USA. Danielson, BJ, Iowa State Univ, Dept Anim Ecol, 124 Sci Hall 2, Ames, IA 50011 USA.English<7Darcy, M. C. Eggleston, D. B.2005VDo habitat corridors influence animal dispersal and colonization in estuarine systems?841-855Landscape Ecology2077bay scallops; colonization; corridor; dispersal; estuarine macrofauna; grass shrimp; interpatch distance; recruitment ARGOPECTEN-IRRADIANS LAMARCK; CALLINECTES-SAPIDUS RATHBUN; BAY SCALLOPS; FRAGMENTED LANDSCAPES; DECAPOD CRUSTACEANS; ARTIFICIAL SEAGRASS; MARINE LANDSCAPES; PATCH SIZE; FIELD-TEST; CONNECTIVITYArticleNov6Studies investigating animal response to habitat in marine systems have mainly focused on habitat preference and complexity. This study is one of the first to investigate the affect of benthic habitat corridors and their characteristics on dispersal and colonization by estuarine macrofuana. In this study, mark-recapture field experiments using artificial seagrass units (ASUs) assessed the effects of seagrass corridors, interpatch distance (5 m vs. 10 m), and the ratio of corridor width to patch width (0.5 m:1 m vs. 0.25 m:1 m) on dispersal of two benthic organisms: the highly mobile grass shrimp, Palaemonetes sp., and the less mobile bay scallop, Argopecten irradians, in two estuarine systems in southeastern North Carolina (NC). The presence of a seagrass corridor, interpatch distance, and corridor width to patch width ratios did not significantly affect shrimp or scallop dispersal to receiver patches. Bay scallop dispersal to receiver patches was significantly higher at one site (Drum Shoals) with relatively high flow, compared to a second site (Middle Marsh) with lower flow. We then examined colonization of estuarine macrofauna to seagrass patches with and without corridors to determine which, if any, taxonomic groups respond positively to corridors at scales of 10 m and over 1 month. Colonization of estuarine macrofauna to seagrass patches was enhanced in the presence of corridors at a relatively large interpatch distance (10 m), which was statistically significant for relatively slow moving polychaete worms. Thus, although benthic habitat corridors may facilitate dispersal of relatively slow moving estuarine animals between otherwise isolated seagrass patches, several common seagrass fauna such as grass shrimp and bay scallops apparently use water currents to rapidly disperse across the seagrass/sand landscape.://000233036300006 ] ISI Document Delivery No.: 980RQ Times Cited: 1 Cited Reference Count: 53 Cited References: ANDREASSEN HP, 1996, J APPL ECOL, V33, P63 BEIER P, 1998, CONSERV BIOL, V12, P1241 BELL SS, 1991, MAR ECOL-PROG SER, V73, P61 BERNTSSON KM, 2000, J EXP MAR BIOL ECOL, V251, P59 BLACKMON DC, 2001, J EXP MAR BIOL ECOL, V257, P183 BOXSHALL AJ, 2000, J EXP MAR BIOL ECOL, V254, P143 BROOKS RA, 2001, J EXP MAR BIOL ECOL, V264, P67 CASELLE JE, 1996, ECOLOGY, V77, P2488 COFFMAN CJ, 2001, OIKOS, V93, P3 COWEN RK, 2000, SCIENCE, V287, P857 DUNNING JB, 1995, CONSERV BIOL, V9, P542 EGGLESTON DB, 1989, J SHELLFISH RES, V8, P475 EGGLESTON DB, 1998, J EXP MAR BIOL ECOL, V223, P111 EGGLESTON DB, 1999, J EXP MAR BIOL ECOL, V236, P107 ELIS WE, 1998, THESIS N CAROLINA ST, P102 ETHERINGTON LL, 2003, CAN J FISH AQUAT SCI, V60, P873 FAHRIG L, 1985, ECOLOGY, V66, P1762 FAHRIG L, 1988, ECOLOGY, V69, P468 FERGUSON SH, 2000, CAN J ZOOL, V78, P713 GILLANDERS BM, 2003, MAR ECOL-PROG SER, V247, P281 GOODSELL PJ, 2002, MAR ECOL-PROG SER, V239, P37 HADDAD NM, 1999, AM NAT, V153, P215 HADDAD NM, 1999, ECOL APPL, V9, P612 HADDAD NM, 1999, ECOL APPL, V9, P623 HAMILTON PV, 1996, J EXP MAR BIOL ECOL, V199, P79 HARRISON RL, 1992, CONSERV BIOL, V6, P293 HENEIN K, 1990, LANDSCAPE ECOL, V4, P157 HOWARD RK, 1985, MAR ECOL-PROG SER, V22, P163 IMS RA, 1995, MOSAIC LANDSCAPES EC, P85 INGLIS G, 1992, CONSERV BIOL, V6, P581 IRLANDI EA, 1995, OIKOS, V72, P307 IRLANDI EA, 1997, OECOLOGIA, V110, P222 IRLANDI EA, 1997, OIKOS, V78, P511 IRLANDI EA, 1999, J EXP MAR BIOL ECOL, V235, P21 JORDAN F, 2000, J CRUSTACEAN BIOL, V20, P769 KOTLIAR NB, 1990, OIKOS, V59, P253 MERRIAM G, 1990, LANDSCAPE ECOL, V4, P123 MICHELI F, 1999, CONSERV BIOL, V13, P869 NOSS RF, 1987, CONSERV BIOL, V1, P159 PALMER MA, 1996, TRENDS ECOL EVOL, V11, P322 PERKINSVISSER E, 1996, J EXP MAR BIOL ECOL, V198, P155 PETERSON CH, 1982, B MAR SCI, V32, P939 POWERS SP, 2000, LIMNOL OCEANOGR, V45, P727 QIAN PY, 1999, HYDROBIOLOGIA, V402, P239 REYNS NB, 2004, IN PRESS OECOLOGIA ROBBINS BD, 1994, TRENDS ECOL EVOL, V9, P301 ROBERTS CM, 1997, SCIENCE, V278, P1454 SOGARD SM, 1989, J EXP MAR BIOL ECOL, V133, P15 TEWKSBURY JJ, 2002, P NATL ACAD SCI USA, V99, P12923 TOLIMIERI N, 2004, CORAL REEFS, V23, P184 UNDERWOOD AJ, 1981, OCEANOGR MAR BIOL AN, V19, P513 VIRNSTEIN RW, 1986, MAR ECOL-PROG SER, V29, P279 WINTER MA, 1985, J EXP MAR BIOL ECOL, V88, P227 0921-2973 Landsc. Ecol.ISI:000233036300006N Carolina State Univ, Dept Marine Earth & Atmospher Sci, Raleigh, NC 27695 USA. Darcy, MC, Mote Marine Lab, Ctr Fisheries Enhancement, 1600 Ken Thompson Pkwy, Sarasota, FL 34236 USA. mdarcy@-mote.orgEnglish 8|? ,Dauer, J. T. Luschei, E. C. Mortensen, D. A.2009IEffects of landscape composition on spread of an herbicide-resistant weed735-747Landscape Ecology246JulWidespread adoption of genetically modified glyphosate-resistant (GR) crops in the US has dramatically changed the agricultural landscape to one that selects for establishment and spread of weedy species resistant to glyphosate, a commonly applied herbicide. Weed species that possess the means to readily spread across the landscape will be contained by weed management strategies that limit weed establishment and prevent seed set. An empirically-derived simulation model was developed to explore GR Conyza canadensis spread in relation to characteristics of the agricultural landscape. C. canadensis seeds are carried in the wind and move among fields and therefore, access high quality habitat (GR crops) at long distances. The baseline scenario was the current GR adoption levels in many US agricultural landscapes with corn and soybean rotated annually. Alternate scenarios examined the interacting effects of management uniformity (GR crop adoption) and increased landscape richness (three crops: corn, soybean, alfalfa, instead of two), over a 10 year simulation period. When landscape uniformity increased (increased GR corn adoption), 3x more fields would be infested with the resistant biotype and a specific field would have up to 24% greater likelihood of being infested compared to the current GR crop adoption levels. Increased landscape richness (adding alfalfa as a third crop) slightly decreased GR C. canadensis abundance. Reduced GR management uniformity by way of reducing GR soybeans to half their current adoption levels had the greatest impact on spread and prevented GR C. canadensis from reaching high abundance. Large-scale reliance on glyphosate for weed management has increased high-fitness habitat and will result in rapid spread of glyphosate-resistant weeds. Without significant reductions of glyphosate use and without spatial coordination of weed and crop management practices, GR weeds will continue to spread rapidly and impact agricultural practices in areas reliant on glyphosate.://0002682481000037Dauer, Joseph T. Luschei, Edward C. Mortensen, David A. 0921-2973ISI:00026824810000310.1007/s10980-009-9345-9{?[!David, K. Oline Michael, C. Grant2002FScaling patterns of biomass and soil properties: an empirical analysis13-26Landscape Ecology171wColorado Front Range - Environmental gradients - Geostatistics - Multiple scales - Rocky mts - Scaling patterns - SoilsxWe argue that studies at multiple scales must necessarilychange the extent of measurements, not just the spacing, in order toeffectivelycapture information regarding processes at multiple scales. We have implementeda multi-scale sampling scheme using transects of 10 cm, 1m, 10 m, 100 m, and 1 km ateach of four sites along an elevational gradient from dry foothills forest toalpine tundra in the Front Range of Colorado; these four sites form anadditional transect of 22 km. Along each of these transects wetookten equally spaced soil cores and measured variables important in determiningboth microbial and plant community structure: soil water content, organicmattercontent, pH, and total soil biomass. With this sampling scheme we are able totreat scale as an independent variable in our analyses, and our data show thatboth particular sites and particular variables can determine whether estimatesof mean values are scale-dependent or not. A geostatistical analysis using allof our data shows common relationships between scales across ecologicallydiverse sites; biomass shows the most complex pattern of distribution acrossscales, as measured by fractal dimension. Our analyses also reveal theinadequacy of several standard geostatistical models when applied to data frommultiple scales of measurement – we recommend the use of the boundedpowerlaw model in such cases. We hypothesize that because biological communitiesmustrespond simultaneously to multiple variables with differing patterns of spatialvariation, the spatial variation of biological communities will be at least ascomplex as the most complex environmental variable at any given site.*http://dx.doi.org/10.1023/A:1015276723949 10.1023/A:1015276723949 References Amarasekare P. 1994. Spatial population structure in the bannertailed kangaroo rat, Dipodomys spectabilis. Oecologia 100: 166-174. Bartlett R.J. and Ross D.S. 1988. Colorimetric determination of oxidizable carbon in acid soil solutions. Soil Sci. Soc. Am. J. 52: 1191-1192. Berntson G.M. and Stoll P. 1997. Correcting for finite spatial scales of self-similarity when calculating the fractal dimensions of real-world structures. Proc. R. Soc. London, Ser. B 264: 1531-1537. Bian L. and Walsh S.J. 1993. Scale dependencies of vegetation and topography in a mountainous environment of Montana. Prof. Geog. 45: 1-11. Brosofske K.D., Chen J., Crow T.R. and Saunders S.C. 1999. Vegetation responses to landscape structure at multiple scales across a northern Wisconsin, USA, pine barrens landscape. Plant Ecol. 143: 203-218. Burrough P.A. 1981. Fractal dimensions of landscapes and other environmental data. Nature 294: 240-242. Burrough P.A. 1983a. Multiscale sources of spatial variation in soil. I. The application of fractal concepts to nested levels of soil variation. J. Soil Sci. 34: 577-597. Burrough P.A. 1983b. Multiscale sources of spatial variation in soil. II. A non-Brownian fractal model and its application in soil survey. J. Soil Sci. 34: 599-620. Cairns D.M. 1999. Multi-scale analysis of soil nutrients at alpine treeline in Glacier National Park, Montana. Phys. Geog. 20: 256-271. Chilés, Jean-Pau1 and Pierre Delfiner 1999. Geostatistics: Modeling Spatial Uncertainty. John Wiley & Sons Inc., New York, New York, USA. Cressie, Noel, Douglas M. and Hawkins 1980. Robust estimation of the semivariogram: I. Math. Geol. 12: 115-125. Cullinan V.I., Simmons M.A. and Thomas J.M. 1997. A Bayesian test of hierarchy theory: scaling up variability in plant cover from field to remotely sensed data. Lands. Ecol. 12: 273-285. Decker K.L.M., Boerner R.E.J. and Morris S.J. 1999. Scale-dependent patterns of soil enzyme activity in a forested landscape. Can. J. For. Res. 29: 232-241. Greenland D. 1989. The climate of Niwot Ridge, Front Range, Colorado, U.S.A. Arct. Alp. Res. 21: 380-381. Jackson R.B. and Caldwell M.M. 1993. Geostatistical patterns of soil heterogeneity around individual perennial plants. J. of Ecol. 81: 683-692. Kotilar N.B. 1996. Scale dependency and the expression of hierarchical structure in Delphinium patches. Vegetatio 127: 117-128. Lipson D.A., Schmidt S.K. and Monson R.K. 1999. Links between microbial population dynamics and nitrogen availability in an alpine ecosystem. Ecology 80: 1623-1631. Loehle C. and Li B. 1996. Statistical properties of ecological and geological fractals. Ecol. Modell. 85: 271-284. Mark D.M. and Aronson P.B. 1984. Scale-dependent fractal dimensions of topographic surfaces: an empirical investigation, with applications in geomorphology and computer mapping. Math. Geol. 16: 671-683. Marr J.W. 1961. Ecosystems of the East Slope of the Front Range in Colorado. University of Colorado Studies Series in Biology. Vol. 8. University of Colorado Press, Boulder, Colorado, USA. Milne B.T. 1988. Measuring the fractal geometry of landscapes. Appl. Math. Comp. 27: 67-79. Morris S.J. 1999. Spatial distribution of fungal and bacterial biomass in souther Ohio hardwood forest soils: fine scale variability and microscale patterns. Soil Biol. Biochem. 31: 1375-1386. Rodriquez-Iturbe I., Vogel G.K. and Rigon R. 1995. On the spatial organization of soil moisture fields. Geophys. Res. Lett. 22: 2757-2760. Rogers D.L., Millar C.I. and Westfall R.D. 1999. Fine-scale genetic strcture of whitebark pine (Pinus albicaulis): associations with watershed and growth form. Evolution 53: 74-90. Walker D.A., Halfpenny J.C., Walker M.D. and Wessman C.A. 1993. Long term studies of snow-vegetation interactions. Bioscience 43: 287-301. Western A.W. and Blöschl G. 1999. On the spatial scaling of soil moisture. J. Hydrol. 217: 203-224. Yang J., Hammer R.D. and Blanchar R.W. 1995. Microscale pH spatial distribution in the Ap horizon of Mexico silt loam. Soil Sci. 160: 371-375. Yost R.S., Uehara G. and Fox R.L. 1982. Geostatistical analysis of soil chemical properties of large land areas. 1. Semi-semivariograms. Soil Sci. Soc. Am. J. 46: 1028-1032. lDepartment of Environmental, Organismic, and Population Biology, University of Colorado, Boulder, 80309, USA9ڽ7"0Davidson, Achiad Carmel, Yohay Bar-David, Shirli2013Characterizing wild ass pathways using a non-invasive approach: applying least-cost path modelling to guide field surveys and a model selection analysis 1465-1478Landscape Ecology288Springer NetherlandsAkaike’s information criterion (AIC) Conservation Equus hemionus Faeces GIS Landscape barriers Landscape connectivity Least-cost models Reintroduction 2013/10/01+http://dx.doi.org/10.1007/s10980-013-9915-8 0921-2973Landscape Ecol10.1007/s10980-013-9915-8EnglishQ?Davidson, Eric A.1995`Spatial covariation of soil organic carbon, clay content, and drainage class at a resional scale349-362Landscape Ecology106climate change, FAO, geographic information system, global carbon cycle, Kansas, Montana, soil maps, soil organic matter, soil taxonomy, soil texture, STATSGO f|7L Davidson, E. A.1995`Spatial covariation of soil organic carbon, clay content, and drainage class at a regional scale349-362Landscape Ecology106climate change fag geographic information system global carbon cycle kansas montana soil maps soil organic matter soil taxonomy soil texture statsgo great plains climate balance worldDec:Several factors affecting stocks of soil organic-C have been identified, including climate, soil texture, and drainage, but how these factors and their influence vary spatially is not well documented. The State Soil Geographic Data Base (STATSGO) was used to estimate soil organic-C stocks of Montana and Kansas and to map spatial variation of soil properties. Regressions across map units of area-weighted estimates of soil organic-C, clay content, and drainage class show that clay content is positively correlated with organic-C in Kansas, bur that drainage class is a better indicator of soil with high and low organic-C stocks in Montana. About 85% of Kansas is covered by Mollisols. These grasslands of the North American Great Plains are where the paradigm relating clay content to stabilization of soil organic-C was developed. In contrast, clay content does not covary with soil organic-C across Montana. Only 30% of Montana is covered by Mollisols; the remainder includes rangeland, covered primarily by Aridisols and Entisols, and forests, covered by Inceptisols, Spodosols, and Histosols. Although other unidentified factors contribute to spatial variation in soil organic-C stocks in Montana, drainage class distinguishes the C-rich and the C-poor soils. When taken with similar results correlating soil C stocks with drainage class in a separate study of Maine, soil wetness emerges as an important controller of soil organic-C in northern states of the USA. Another objective was to compare STATSGO estimates (1:250,000 scale) of area covered by soil orders with estimates from the FAO/UNESCO Soils Map of the World (1:5,000,000). Agreement was excellent in Kansas and reasonably good in Montana. When used with regionally specific estimates for soil-C, the FAO map holds promise for regional and global extrapolation of soil C stocks.://A1995TN14300003.Tn143 Times Cited:17 Cited References Count:23 0921-2973ISI:A1995TN14300003;Davidson, EA Woods Hole Res Ctr,Pob 296,Woods Hole,Ma 02543English}?Davies, Z. G. Pullin, A. S.2007cAre hedgerows effective corridors between fragments of woodland habitat? An evidence-based approach333-351Landscape Ecology223Xclimate change; connectivity; conservation; habitat fragmentation; habitat loss; landscape-scale; movement; population; systematic review; woodland fauna CLIMATE-CHANGE; AGRICULTURAL LANDSCAPES; ABAX-PARALLELEPIPEDUS; POPULATION-DYNAMICS; BEETLE COMMUNITIES; NETWORK LANDSCAPE; BIRD COMMUNITIES; HESPERIA-COMMA; FARM WOODLANDS; SMALL MAMMALS Mar<Anthropogenic modification of the countryside has resulted in much of the landscape consisting of fragments of once continuous habitat. Increasing habitat connectivity at the landscape-scale has a vital role to play in the conservation of species restricted to such remnant patches, especially as species may attempt to track zones of habitat that satisfy their niche requirements as the climate changes. Conservation policies and management strategies frequently advocate corridor creation as one approach to restore connectivity and to facilitate species movements through the landscape. Here we examine the utility of hedgerows as corridors between woodland habitat patches using rigorous systematic review methodology. Systematic searching yielded 26 studies which satisfied the review inclusion criteria. The empirical evidence currently available is insufficient to evaluate the effectiveness of hedgerow corridors as a conservation tool to promote the population viability of woodland fauna. However, the studies did provide anecdotal evidence of positive local population effects and indicated that some species use hedgerows as movement conduits. More replicated and controlled field investigations or longterm monitoring are required in order to allow practitioners and policy makers to make better informed decisions about hedgerow corridor creation and preservation. The benefits of such corridors in regard to increasing habitat connectivity remain equivocal, and the role of corridors in mitigating the effects of climate change at the landscape-scale is even less well understood. ://000244455200002 0921-2973ISI:000244455200002?Davis, F.W. S. Goetz19906Modeling vegetation pattern using digital terrain data69-80Landscape Ecology41KCalifornia, GIS, Oak forest, Patch size, Predictive mapping, Remote sensing Using a geographic information system (GIS), digital maps of environmental variables including geology, topography and calculated clear-sky solar radiation, were weighted and overlaid to,predict the distribution of coast live oak (Quercus agrifolia) forest in a 72 km2 region near Lompoc, California. The predicted distribution of oak forest was overlaid on a map of actual oak forest distribution produced from remotely sensed data, and residuals were analyzed to distinguish prediction errors dueto alteration of the vegetation cover from those due to defects of the statistical predictive model and due to cartographic errors. Vegetation pattern in the study area was associated most strongly with geologic substrate. Vegetation pattern was also significantly associated with slope, exposure and calculated monthly solar radiation. The proportion of observed oak forest occurring on predicted oak forest sites was 40% overall, but varied substantially between substrates and also depended strongly on forest patch size, with a much higher rate of success for larger forest patches. Only 21% of predicted oak forest sites supported oak forest, and proportions of observed vegetation on predicted oak forest sites varied significantly between substrates. The non-random patterns of disagreement between maps of predicted and observed forest indicated additional variables that could be included to improve the predictive model, as well as the possible magnitude of forest loss due to disturbances in different parts of the landscape.m<7-Davis, J. D. Debinski, D. M. Danielson, B. J.2007aLocal and landscape effects on the butterfly community in fragmented Midwest USA prairie habitats 1341-1354Landscape Ecology229&butterflies; conservation; floral resources; habitat fragmentation; partial least squares regression; spatial extent; variance partitioning CANONICAL CORRESPONDENCE-ANALYSIS; AGRICULTURAL LANDSCAPES; ARABLE FARMLAND; LEVEL FACTORS; DISPERSAL; ABUNDANCE; CONSERVATION; DIVERSITY; MOVEMENT; SCALEArticleNovThe fragmented landscape of the Midwest USA includes prairie remnants embedded in an agricultural matrix, potentially impermeable to dispersing individuals. We examined butterfly responses to local (environmental variables measured within the prairie fragment itself such as vegetative characteristics) and landscape (environmental variables measured up to 2 km surrounding the fragment, but not the fragment itself) factors at 20 prairie remnants in Iowa. Our objectives were to: 1) document how the composition and configuration of the landscape affects butterfly community within the fragment, 2) determine whether explanatory power is gained by including both landscape and local variables rather than only local variables, and 3) analyze differences in butterfly community composition between linear and block shaped fragments. Results from partial least squares regression suggest there are significant effects of the landscape on butterfly community composition at all spatial extents investigated. The local variable that was most highly correlated with butterfly community response was percentage litter, while percentage of roads was the most important variable at all landscape spatial extents. Ordination diagrams clearly separate linear from block sites based on butterfly community composition. Variance partitioning using partial canonical correspondence analysis indicated that landscape variables at all spatial extents add additional explanatory power beyond local variables with little overlap in percentage of variation explained. Our results suggest that butterflies are making decisions based both on the local and landscape environmental factors, thus land surrounding prairie remnants should be included in management decisions.://000250207500007 y Cited Reference Count: 68 Cited References: *ENV SYST RES I, 2004, ARCGIS REL 8 3 *R DEV COR TEAM, 2004, R LANG ENV STAT COMP AUCKLAND JN, 2004, ECOL ENTOMOL, V29, P139 BAGUETTE M, 2003, CR BIOL S1, V326, S200 BERGIN TM, 2000, LANDSCAPE ECOL, V15, P131 BERGMAN KO, 2004, ECOGRAPHY, V27, P619 BORCARD D, 1992, ECOLOGY, V73, P1045 CANT ET, 2005, P ROY SOC B-BIOL SCI, V272, P785 CHUST G, 2003, CONSERV BIOL, V17, P1721 CLAUSEN HD, 2001, BIOL CONSERV, V98, P167 COLLINGE SK, 2003, CONSERV BIOL, V17, P178 CONRADT L, 2000, P ROY SOC LOND B BIO, V267, P1505 DEBINSKI DM, 2001, BIOL CONSERV, V98, P179 DEBINSKI DM, 2006, J BIOGEOGR, V33, P1791 DEJONG S, 1993, CHEMOMETR INTELL LAB, V18, P251 DENNIS RLH, 2003, OIKOS, V102, P417 DOVER JW, 1996, J APPL ECOL, V33, P723 DOVER JW, 1997, J INSECT CONSERV, V1, P89 DOVER JW, 2001, ENTOMOL EXP APPL, V100, P221 FAHRIG L, 1994, CONSERV BIOL, V8, P50 GRAHAM CH, 2001, ECOL APPL, V11, P1709 HADDAD NM, 1999, AM NAT, V153, P215 HADDAD NM, 1999, ECOL APPL, V9, P612 HADDAD NM, 1999, ECOL APPL, V9, P623 HARRISON S, 1989, ECOLOGY, V70, P1236 HENDRIX SD, 2000, CONSERV BIOL, V14, P304 HINES HM, 2005, ENVIRON ENTOMOL, V34, P1477 JEANNERET P, 2003, LANDSCAPE ECOL, V18, P253 JOHANSSON ME, 2002, J APPL ECOL, V39, P971 JONES RE, 1980, J ANIM ECOL, V49, P629 KINDLMANN P, 2004, ECOL ENTOMOL, V29, P447 KOPPER B, 2000, J INSECT BEHAV, V13, P561 KRAUSS J, 2003, J BIOGEOGR, V30, P889 KUUSSAARI M, 1996, J ANIM ECOL, V65, P791 LIMA SL, 1996, TRENDS ECOL EVOL, V11, P131 LORD JM, 1990, CONSERV BIOL, V4, P197 LUOTO M, 2001, ECOGRAPHY, V24, P601 MATTER SF, 2002, ECOL ENTOMOL, V27, P308 MAZEROLLE MJ, 1999, ECOSCIENCE, V6, P117 MERCKX T, 2003, P ROY SOC LOND B BIO, V270, P1815 MEVIK BH, 2006, R NEWS, V6, P12 MILLER JR, 2004, ECOL APPL, V14, P1394 OPLER PA, 1984, BUTTERFLIES E GREAT OUIN A, 2004, AGR ECOSYST ENVIRON, V103, P473 PEARSON SM, 1993, LANDSCAPE ECOL, V8, P3 PYWELL RF, 2004, BIOL CONSERV, V118, P313 REEDER KF, 2005, AGR ECOSYST ENVIRON, V109, P40 RIBIC CA, 2001, AM MIDL NAT, V146, P105 RICKETTS TH, 2001, AM NAT, V158, P87 RIES L, 2001, CONSERV BIOL, V15, P401 RIES L, 2001, J ANIM ECOL, V70, P840 SAMSON F, 1994, BIOSCIENCE, V44, P418 SAUNDERS DA, 1991, CONSERV BIOL, V5, P19 SAWCHIK J, 2003, ACTA OECOL, V24, P25 SCHNEIDER C, 2001, J INSECT CONSERVATIO, V5, P163 SCHNEIDER C, 2003, ECOL ENTOMOL, V28, P252 SCHULTZ CB, 2001, ECOLOGY, V82, P1879 SHEPHERD S, 2005, BIOL CONSERV, V126, P51 SPARKS TH, 1995, BIOL CONSERV, V73, P221 STEFFANDEWENTER I, 1997, OECOLOGIA, V109, P294 STEFFANDEWENTER I, 2000, ECOL LETT, V3, P449 SUTCLIFFE OL, 2003, LANDSCAPE URBAN PLAN, V63, P15 TERBRAAK CJF, 1995, AQUAT SCI, V57, P255 THOMAS JA, 1983, BIOL CONSERV, V27, P195 TITEUX N, 2004, J BIOGEOGR, V31, P1841 TSCHARNTKE T, 2002, ECOL APPL, V12, P354 WAHLBERG N, 2002, OECOLOGIA, V130, P33 WILLIAMS PA, 2004, J BIOGEOGR, V31, P1355 0921-2973 Landsc. Ecol.ISI:000250207500007Iowa State Univ, Program Evolut Biol & Ecol, Ames, IA 50011 USA. Davis, JD, Iowa State Univ, Program Evolut Biol & Ecol, 1126L Agron Hall, Ames, IA 50011 USA. jdd@iastate.eduEnglish<70%Davis, J. H. Howe, R. W. Davis, G. J.20004A multi-scale spatial analysis method for point data99-114Landscape Ecology152bird distributions Monte Carlo nearest neighbor point patterns randomization spatial pattern spatial statistics test of randomness MIGRATORY BIRDS REPRODUCTIVE SUCCESS POPULATIONS PATTERNS FOREST ABUNDANCE VARIOGRAM DYNAMICS SINKSArticleFebZThis paper presents a nearest neighbor method for the spatial analysis of data collected from discrete field sampling sites. The method was applied to point counts of birds at permanent survey sites in the Nicolet National Forest of northeastern Wisconsin. The spatial analysis method we developed uses a Monte Carlo randomization approach to test for non-randomness not only of the mean nearest neighbor distance between n points but also the mean second nearest, third nearest,..., to (n-1)th nearest distances to reveal spatial information at multiple scales. Because the bird survey sites are not randomly distributed throughout the forest, the survey sites at which a given species was recorded were compared with random samples drawn from the total survey sites rather than from all possible points within the forest. More refined analyses restricted the randomization by (a) habitat type, in order to separate the effects of non-randomly distributed habitat types on species' distributions; and (b) north-south regions of the forest, in order to account for regional gradients in distribution which were evident for some species. Spatial patterns among the sites at which the birds were detected reveal information about the scale at which the birds are distributed in their environment and provide a more complete picture of multi-scale bird population dynamics.://000084522700003 ISI Document Delivery No.: 270EP Times Cited: 8 Cited Reference Count: 55 Cited References: BLAKE JG, 1994, CONDOR, V96, P381 BOLLINGER EK, 1994, WILSON BULL, V106, P46 BRAWN JD, 1996, ECOLOGY, V77, P3 BROWN JH, 1995, ECOLOGY, V76, P2028 CONWELL PM, 1997, WATER RESOUR RES, V33, P2489 CURTIS JT, 1959, VEGETATION WISCONSIN DAVIS JD, 1996, HABITAT SPATIAL ANAL DESMOND MJ, 1995, CAN J ZOOL, V73, P1375 DIGGLE PJ, 1983, STAT ANAL SPATIAL PO DONNELLY K, 1978, SIMULATION METHODS A DONOVAN TM, 1995, CONSERV BIOL, V9, P1380 EDGINGTON ES, 1980, RANDOMIZATION TESTS FINLEY RW, 1976, ORIGINAL VEGETATION FLATHER CH, 1996, ECOLOGY, V77, P28 FREEMARK KE, 1995, ECOLOGY MANAGEMENT N GHENT AW, 1990, AM MIDL NAT, V124, P184 GILPIN M, 1991, BIOL J LINN SOC, V42, P1 GREIGSMITH P, 1983, QUANTITATIVE PLANT E HOLMES RT, 1992, ECOLOGY CONSERVATION HOLT RD, 1993, SPECIES DIVERSITY EC HOWE RW, 1991, BIOL CONSERV, V57, P239 HOWE RW, 1995, POINT COUNT METHODS HOWE RW, 1996, HEMLOCK ECOLOGY MANA, P125 HOWE RW, 1996, MANAGING MIDWESTERN HOWE RW, 1997, PASSENGER PIGEON, V59, P183 LANDE R, 1991, BIRD POPULATION STUD LEGENDRE P, 1993, ECOLOGY, V74, P1659 LITWIN TS, 1992, ECOLOGY CONSERVATION LUDWIG JA, 1988, STAT ECOLOGY PRIMER MANLY BFJ, 1991, RANDOMIZATION MONTE MANLY BFJ, 1997, RANDOMIZATION BOOTST PETERJOHN PG, 1994, WILDLIFE SOC B, V22, P155 PIELOU EC, 1969, INTRO MATH ECOLOGY PRICE J, 1995, SUMMER ATLAS N AM BI PULLIAM HR, 1988, AM NAT, V132, P652 RALPH CJ, 1981, STUDIES AVIAN BIOL, V6 RALPH CJ, 1995, MONITORING BIRD POPU REYNOLDS RT, 1980, CONDOR, V82, P309 RIPLEY BD, 1981, SPATIAL STAT ROBBINS CS, 1986, US FISH WILDLIFE SER, V157 ROBBINS CS, 1989, P NATL ACAD SCI USA, V86, P7658 ROBINSON SK, 1992, ECOLOGY CONSERVATION ROBINSON SK, 1995, SCIENCE, V267, P1987 ROMESBURG HC, 1989, COMPUT GEOSCI, V15, P1011 SCHNEIDER DC, 1994, QUANTITATIVE ECOLOGY SHERRY TW, 1995, ECOLOGY MANAGEMENT N SHERRY TW, 1996, ECOLOGY, V77, P36 SINCLAIR DF, 1985, ECOLOGY, V66, P1084 SOLOW AR, 1989, ECOLOGY, V70, P379 THOMPSON HR, 1956, ECOLOGY, V37, P391 TURNER MG, 1991, QUANTITATIVE METHODS TURNER SJ, 1991, QUANTITATIVE METHODS VILLARD MA, 1995, ECOLOGY, V76, P27 WARRICK AW, 1987, WATER RESOUR RES, V23, P496 WEBSTER R, 1992, J SOIL SCI, V43, P177 0921-2973 Landsc. Ecol.ISI:000084522700003Univ Wisconsin, Wisconsin Breeding Bird Atlas, Green Bay, WI 54311 USA. Davis, JH, Univ Wisconsin, Wisconsin Breeding Bird Atlas, Green Bay, WI 54311 USA.English? 3De Angelis, Antonella Bajocco, Sofia Ricotta, Carlo2012IPhenological variability drives the distribution of wildfires in Sardinia 1535-1545Landscape Ecology2710Springer NetherlandsBiomedical and Life SciencesFuel characteristics play an important role in driving fire ignition and propagation; at the landscape scale fuel availability and flammability are closely related to vegetation phenology. In this view, the NDVI profiles obtained from high temporal resolution satellites, like MODIS, are an effective tool for monitoring the coarse-scale vegetation seasonal timing. The aim of this paper is twofold: our first objective consists in classifying by means of multitemporal NDVI profiles the coarse-scale vegetation of Sardinia into ‘phenological clusters’ in which fire incidence is higher (preferred) or lower (avoided) than expected from a random null model. If fires would burn unselectively, then fires would occur randomly across the landscape such that the number of fires in a given phenological cluster would be nearly proportional to the relative area of that land cover type in the analyzed landscape. Actually, certain vegetation types are more fire-prone than others. That is, they are burnt more frequently than others. In this framework, our second objective consists in investigating the temporal parameters of the remotely sensed NDVI profiles that best characterize the observed phenology–fire selectivity relationship. The results obtained show a good association between the NDVI temporal profiles and the spatio-temporal wildfire distribution in Sardinia, emphasizing the role of bioclimatic timing in driving fire regime characteristics.+http://dx.doi.org/10.1007/s10980-012-9808-2 0921-297310.1007/s10980-012-9808-2<7#de Blois, S. Domon, G. Bouchard, A.2001cEnvironmental, historical, and contextual determinants of vegetation cover: a landscape perspective421-436Landscape Ecology1656agricultural landscape agroforested landscape human disturbance landscape model land use history Mantel test path analysis Quebec spatial context vegetation model HAUT-SAINT-LAURENT CENTRAL NEW-ENGLAND FOREST LANDSCAPE AGRICULTURAL LANDSCAPE SOUTHERN QUEBEC NOTARY DEEDS DYNAMICS CANADA 19TH-CENTURY MANAGEMENTArticleJullWe formulated and tested models of relationships among determinants of vegetation cover in two agroforested landscapes of eastern North America (Haut Saint-Laurent, Quebec, Canada) that differed by the spatial arrangement of their geomorphic features and intensity of agricultural activities. Our landscape model compared the woody plots of each landscape in terms of the relative influence of environmental attributes, land use history (1958 - 1997), and spatial context (i.e., proximity of similar or contrasting land cover). Our vegetation model evaluated the relative contribution of the same sets of variables to the distributions of herbs, trees, and shrubs. Relationships were assessed using partial Mantel tests and path analyses. Significant environmental and contextual differences were found between the vegetation plots of the two landscapes, but disturbance history was similar. Our vegetation model confirms the dominant effect of historical factors on vegetation patterns. Whereas land-use history overrides environmental and contextual control for trees, herbaceous and shrub species are more sensitive to environmental conditions. Context is determinant only for understory species in older, less-disturbed plots. Results are discussed in relevance to vegetation dynamics in a landscape perspective that integrates interactions between environmental and human influences.://000170952100004 ISI Document Delivery No.: 471WR Times Cited: 14 Cited Reference Count: 72 Cited References: *ENV CAN, 1982, NORM CLIM CAN 1951 1 *INTERA TYDAC, 1991, SPANS SPAT AN SYST R *SAS I, 1988, SAS US GUID ABRAMS MD, 1995, CAN J FOREST RES, V25, P659 AUSTIN MP, 1988, DIVERSITY PATTERN PL, P95 AUSTIN MP, 1989, VEGETATIO, V83, P35 BARITEAU L, 1988, THESIS U MONTREAL MO BARTON AM, 1993, ECOL MONOGR, V63, P367 BERGERON Y, 1997, J VEG SCI, V8, P37 BERGERON Y, 1998, J VEG SCI, V9, P493 BOUCHARD A, IN PRESS TOURBIERES BOUCHARD A, 1989, CAN J FOREST RES, V19, P1146 BOUCHARD A, 1997, LANDSCAPE URBAN PLAN, V37, P99 BOUTIN C, 1998, ECOL APPL, V8, P544 BRISSON J, 1988, CAN J BOT, V66, P1192 BRISSON J, 1992, NAT AREA J, V12, P3 BRISSON J, 1994, ECOSCIENCE, V1, P40 BROSOFSKE KD, 1999, PLANT ECOL, V143, P203 CASGRAIN P, 1999, PROGICIEL R V 4 0 AN CROW TR, 1999, LANDSCAPE ECOL, V14, P449 DEBLOIS S, 1995, J VEG SCI, V6, P531 DIETZ EJ, 1983, SYST ZOOL, V32, P21 DOMON G, 1993, LANDSCAPE URBAN PLAN, V25, P53 DZWONKO Z, 1992, J BIOGEOGR, V19, P195 DZWONKO Z, 1993, J VEG SCI, V4, P693 EASTABROOK GF, 1966, BIOSCIENCE, V16, P789 FLANNIGAN MD, 1998, J VEG SCI, V9, P469 FOSTER DR, 1992, J ECOL, V80, P753 FOSTER DR, 1998, ECOSYSTEMS, V1, P96 FULLER TL, 1998, ECOSYSTEMS, V1, P76 GOWER JC, 1971, BIOMETRICS, V27, P857 GRASHOFBOKDAM C, 1997, J VEG SCI, V8, P21 GRASHOFBOKDAM CJ, 1998, J BIOGEOGR, V25, P837 HARRISON S, 1999, ECOLOGY, V80, P70 HOBBS R, 1997, LANDSCAPE URBAN PLAN, V37, P1 HOBBS RJ, 1993, BIOL CONSERV, V64, P231 HOBBS RJ, 1993, CONSERVATION BIOL AU, P77 HOLM S, 1979, SCAND J STAT, V6, P65 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 JACKSON DA, 1989, CAN J ZOOL, V67, P766 JEAN M, 1987, CAN J BOT, V65, P1969 JULES ES, 1999, CONSERV BIOL, V13, P784 KLEIJN D, 1997, J APPL ECOL, V34, P1413 KLINE J, 1998, ECOL ECON, V26, P211 LEDUC A, 1992, J VEG SCI, V3, P69 LEGENDRE P, 1989, VEGETATIO, V80, P107 LEGENDRE P, 1998, DEV ENV MODELLING, V20 LIU JG, 1999, ECOL APPL, V9, P186 MANTEL N, 1967, CANCER RES, V27, P209 MARIEVICTORIN F, 1964, FLORE LAURENTIENNE MATLACK GR, 1993, BIOL CONSERV, V66, P185 MATLACK GR, 1994, ECOLOGY, V75, P1491 MATLACK GR, 1994, J ECOL, V82, P113 MEILLEUR A, 1992, VEGETATIO, V12, P13 MEILLEUR A, 1994, VEGETATIO, V111, P173 MEINERS SJ, 1999, ECOGRAPHY, V22, P261 MURCIA C, 1995, TRENDS ECOL EVOL, V10, P58 NOLET P, 1995, FOREST ECOL MANAG, V78, P85 PALIK BJ, 1992, AM MIDL NAT, V127, P327 PAN DY, 1999, LANDSCAPE ECOL, V14, P35 PAQUETTE S, 1997, LANDSCAPE URBAN PLAN, V37, P197 RESCIA AJ, 1994, J VEG SCI, V5, P505 ROCHE P, 1998, J VEG SCI, V9, P221 ROWE JS, 1972, ENV CANADA PUBL F, V1300 SIMARD H, 1996, CAN J FOREST RES, V26, P1670 SIMPSON JW, 1994, LANDSCAPE ECOL, V9, P261 SMOUSE PE, 1986, SYST ZOOL, V35, P627 SOKAL RR, 1995, BIOMETRY PRINCIPLES SOMERS KM, 1993, CAN J ZOOL, V71, P1136 TURNER MG, 1996, ECOL APPL, V6, P1150 WHITE MA, 1994, LANDSCAPE ECOL, V9, P191 WIENS JA, 1999, ISSUES LANDSCAPE ECO, P148 0921-2973 Landsc. Ecol.ISI:000170952100004Univ Montreal, Inst Rech Biol Vegetale, Montreal, PQ H1X 2B2, Canada. de Blois, S, McGill Univ, Dept Plant Sci, Macdonald Campus 21,111 Lakeshore Rd, St Anne De Bellevue, PQ H9X 3V9, Canada.English <7 De Jager, N. R. Pastor, J.2009wDeclines in moose population density at Isle Royle National Park, MI, USA and accompanied changes in landscape patterns 1389-1403Landscape Ecology2410Herbivory Landscape patterns Moose Plant-animal interactions Population dynamics Semivariance free-ranging moose boreal forests spatially explicit urine deposition large herbivores balsam fir scots pine vegetation royale ecosystemsArticleDec<Ungulate herbivores create patterns of forage availability, plant species composition, and soil fertility as they range across large landscapes and consume large quantities of plant material. Over time, herbivore populations fluctuate, producing great potential for spatio-temporal landscape dynamics. In this study, we extend the spatial and temporal extent of a long-term investigation of the relationship of landscape patterns to moose foraging behavior at Isle Royale National Park, MI. We examined how patterns of browse availability and consumption, plant basal area, and soil fertility changed during a recent decline in the moose population. We used geostatistics to examine changes in the nature of spatial patterns in two valleys over 18 years and across short-range and long-range distance scales. Landscape patterns of available and consumed browse changed from either repeated patches or randomly distributed patches in 1988-1992 to random point distributions by 2007 after a recent record high peak followed by a rapid decline in the moose population. Patterns of available and consumed browse became decoupled during the moose population low, which is in contrast to coupled patterns during the earlier high moose population. Distributions of plant basal area and soil nitrogen availability also switched from repeated patches to randomly distributed patches in one valley and to random point distributions in the other valley. Rapid declines in moose population density may release vegetation and soil fertility from browsing pressure and in turn create random landscape patterns.://000271809800010&ISI Document Delivery No.: 519ZP Times Cited: 0 Cited Reference Count: 87 De Jager, Nathan R. Pastor, John National Science Foundation We thank John Briggs, Knut Kielland and an anonymous reviewer for their thoughtful comments which helped us improve the paper. The staff of Isle Royale National Park provided valuable logistic support. Bradley Dewey analyzed the resin bag samples and assisted with field work during the 18 years spanning this research. This research and the earlier research of Pastor et al. (1998) were funded by the National Science Foundation's Long-term Research in Environmental Biology Program. Without the continuous support of this program, this research would not have been possible, and we thank the officers, staff and review panels of NSF for making it so. Springer Dordrecht 0921-2973 Landsc. Ecol.ISI:000271809800010^[De Jager, Nathan R.] US Geol Survey, Upper Midwest Environm Sci Ctr, La Crosse, WI 54603 USA. [De Jager, Nathan R.] Univ Minnesota, Dept Ecol Evolut & Behav, St Paul, MN 55108 USA. [Pastor, John] Univ Minnesota, Dept Biol, Duluth, MN 55812 USA. De Jager, NR, US Geol Survey, Upper Midwest Environm Sci Ctr, La Crosse, WI 54603 USA. ndejager@usgs.gov10.1007/s10980-009-9390-4English D|?6 &De Jager, Nathan R. Rohweder, Jason J.2011nSpatial scaling of core and dominant forest cover in the Upper Mississippi and Illinois River floodplains, USA697-708Landscape Ecology265MayDifferent organisms respond to spatial structure in different terms and across different spatial scales. As a consequence, efforts to reverse habitat loss and fragmentation through strategic habitat restoration ought to account for the different habitat density and scale requirements of various taxonomic groups. Here, we estimated the local density of floodplain forest surrounding each of similar to 20 million 10-m forested pixels of the Upper Mississippi and Illinois River floodplains by using moving windows of multiple sizes (1-100 ha). We further identified forest pixels that met two local density thresholds: 'core' forest pixels were nested in a 100% (unfragmented) forested window and 'dominant' forest pixels were those nested in a > 60% forested window. Finally, we fit two scaling functions to declines in the proportion of forest cover meeting these criteria with increasing window length for 107 management-relevant focal areas: a power function (i.e. self-similar, fractal-like scaling) and an exponential decay function (fractal dimension depends on scale). The exponential decay function consistently explained more variation in changes to the proportion of forest meeting both the 'core' and 'dominant' criteria with increasing window length than did the power function, suggesting that elevation, soil type, hydrology, and human land use constrain these forest types to a limited range of scales. To examine these scales, we transformed the decay constants to measures of the distance at which the probability of forest meeting the 'core' and 'dominant' criteria was cut in half (S(1/2), m). S(1/2) for core forest was typically between similar to 55 and similar to 95 m depending on location along the river, indicating that core forest cover is restricted to extremely fine scales. In contrast, half of all dominant forest cover was lost at scales that were typically between similar to 525 and 750 m, but S(1/2) was as long as 1,800 m. S(1/2) is a simple measure that (1) condenses information derived from multi-scale analyses, (2) allows for comparisons of the amount of forest habitat available to species with different habitat density and scale requirements, and (3) can be used as an index of the spatial continuity of habitat types that do not scale fractally.!://WOS:000291485100008Times Cited: 0 0921-2973WOS:00029148510000810.1007/s10980-011-9594-2 ? Dde la Giroday, Honey-Marie Carroll, Allan Lindgren, B. Aukema, Brian2011Incoming! Association of landscape features with dispersing mountain pine beetle populations during a range expansion event in western Canada 1097-1110Landscape Ecology268Springer NetherlandsEarth and Environmental ScienceeMountain pine beetle, Dendroctonus ponderosae Hopkins (Coleoptera: Curculionidae, Scolytinae), is a forest insect that undergoes intermittent population eruptions, causing landscape-level mortality to mature pines. Currently, an outbreak covers over 16.3 million ha of British Columbia and Alberta in western Canada. Recent incursion into the jack pine ( Pinus banksiana Lamb.) of northwestern Alberta threatens further range expansion through the boreal forest to central and eastern Canada. The spread from British Columbia into northwestern Alberta has been facilitated by above-canopy dispersal of the insect by meso-scale atmospheric currents. At these scales, dispersing D. ponderosae may behave like inert particles, causing terrain-induced tropospheric convective and advective currents to influence population dispersal and establishment. We use spatial point process regression models to examine the association of meso-scale variables, including landscape features and their orientations, habitat suitability, elevation and treatment efforts, with occurrence of D. ponderosae infestations in 2004, 2005, and 2006. Infestations of D. ponderosae primarily established in canyons and valleys, before moving into more open-sloped areas. Southwestern slopes of midslope ridges and small hills, southwest facing open slopes, and valleys that run in a northeast–southwest cardinal direction were positively associated with higher intensities of infestation. This study provides insight into the influences of complex terrain on landscape disturbance by a forest insect, and can be used to prioritize areas for potential management.+http://dx.doi.org/10.1007/s10980-011-9628-9 0921-297310.1007/s10980-011-9628-92<7Sde la Pena, N. M. Butet, A. Delettre, Y. Paillat, G. Morant, P. Le Du, L. Burel, F.2003[Response of the small mammal community to changes in western French agricultural landscapes265-278Landscape Ecology1831agricultural intensification Barn Owl biodiversity farming landscapes small mammal community multivariate statistical analysis VOLE MICROTUS-ARVALIS MOUSE APODEMUS-SYLVATICUS BANK VOLE BARN OWL CLETHRIONOMYS-GLAREOLUS SPECIES-DIVERSITY WOOD MOUSE HABITAT FRAGMENTATION POPULATION-DYNAMICS SPATIAL DYNAMICSArticleAprZWe studied the response of the small mammal community ( rodents and shrews) to recent changes in agricultural systems of western French landscapes. Work was conducted on twelve sites representative of the diversity of farming systems in this region. The characteristics of small mammal assemblages in each site were assessed using Barn Owl (Tyto alba) pellet analysis. Relationships between small mammal data and landscape descriptors were performed through co-inertia analysis. Richness and specific composition of the small mammal community were not affected by the degree of cultivation but variations in species frequency could be observed. The prevalence of some species allowed us to distinguish threemain assemblages which were characteristic of low, medium, and high intensified landscapes. Status and life traits of these species showed that intensification of agriculture has negative effects on density of rare and habitat-specialist species while it favours habitat-generalist species, some of them being known to exhibit fluctuating density. The two main ways of agricultural intensification ( maize vs. other crops) did not show any significant relationships with species assemblages. Our results gave us the opportunity to suggest recommendations on agronomical and conservation problems that may arise from these changes of agriculture in western France.://000183770600005 }ISI Document Delivery No.: 694JD Times Cited: 8 Cited Reference Count: 85 Cited References: AARS J, 1998, MOL ECOL, V7, P1383 ANDREN H, 1994, OIKOS, V71, P355 BAUDRY J, 1982, ACTA OECOL OEOL APPL, V3, P177 BAUDRY J, 1995, CHLOE ROUTINE ANAL S BENNETT AF, 1990, LANDSCAPE ECOL, V4, P109 BLEM CR, 1993, AM MIDL NAT, V129, P281 BOHME W, 1978, HDB SAUGETIERE EUROP, V1, P290 BOWMAN J, 2001, FOREST ECOL MANAG, V140, P249 BRYJA J, 2000, FOLIA ZOOL, V49, P191 BUNN DS, 1982, BARN OWL BUREL F, 1990, LANDSCAPE ECOL, V4, P197 BUREL F, 1998, ACTA OECOL, V19, P47 BUTET A, 1993, ACTA OECOL, V14, P857 BUTET A, 2001, BIOL CONSERV, V100, P289 CANOVA L, 1991, ACTA THERIOL, V36, P73 CHALINE J, 1974, PROIES RAPACES PETIT CHURCHFIELD S, 1997, J ZOOL 3, V242, P519 COOKE D, 1996, BIOL ENVIRON B, V96, P97 DELATTRE P, 1992, AGR ECOSYST ENVIRON, V39, P153 DELATTRE P, 1996, LANDSCAPE ECOL, V11, P279 DOLEDEC S, 1994, FRESHWATER BIOL, V31, P277 DOLEDEC S, 1997, TOPICS DOCUMENTATION, V4 EASTMAN JR, 1995, IDRISI WINDOWS USERS FIERS V, 1997, COL PATRIMOINES NATU, V24 FURNESS RW, 1993, BIRDS MONITORS ENV C GENOUD M, 1990, HDB SAUGETIERE EUROP, V3, P429 GIRAUDOUX P, 1990, ALAUDA, V58, P17 GIRAUDOUX P, 1994, ACTA OECOL, V15, P385 GLUE DE, 1967, BIRD STUDY, V14, P169 GLUE DE, 1971, MAMMAL REV, V21, P200 GOUNOT M, 1969, METHODES ETUDE QUANT GURNELL J, 1985, S ZOOLOGICAL SOC LON, V55, P377 HALLE S, 1993, OECOLOGIA, V94, P120 HANNEY P, 1962, ANN MAG NAT HIST, V6, P705 HANSSON L, 1989, HOLARCTIC ECOL, V12, P345 HARPER SJ, 1993, J MAMMAL, V74, P1045 HUTTERER R, 1990, HDB SAUGETIERE EUROP, V3, P183 KORPIMAKI E, 1991, ECOLOGY, V72, P814 KOZAKIEWICZ M, 1991, ACTA THERIOL, V36, P363 KOZAKIEWICZ M, 1993, LANDSCAPE ECOL, V8, P19 KRATOCHVIL J, 1959, COMMON VOLE MICROTUS LANDE R, 1996, OIKOS, V76, P5 LEDU L, 2000, UNITES PAYSAGE TELED, P109 LIBOIS RM, 1983, REV ECOL, V37, P187 LOMAN J, 1991, MAMMALIA, V55, P91 LOVARI S, 1976, B ZOOL, V43, P173 LUKYANOVA LE, 1994, RUSSIAN J ECOLOGY EN, V25, P203 MACARTHUR RH, 1964, AM NAT, V98, P387 MAGURRAN AE, 1988, ECOLOGICAL DIVERSITY MCLAUGHLIN A, 1995, AGR ECOSYST ENVIRON, V55, P201 MEEUS JHA, 1990, LANDSCAPE URBAN PLAN, V18, P289 MEEUS JHA, 1990, MILIEU, V6, P225 MERRIAM G, 1988, MUNSTERSCHE GEOGRAPH, V29 MIDDLETON J, 1981, J APPL ECOL, V18, P703 MIKKOLA M, 1983, OWLS EUROPE MILLYMAKI A, 1977, EPPO B, V7, P177 MITCHELLJONES AJ, 1999, ATLAS EUROPEAN MAMMA MONTGOMERY WI, 1991, J ANIM ECOL, V60, P179 MORANT P, 1999, MAPPEMONDE, V18, P61 OUIN A, 2000, AGR ECOSYST ENVIRON, V78, P159 PAILLAT G, 1996, ACTA OECOL, V17, P553 PAILLAT G, 2000, BIODIVERSITE PAYSAGE PERAULT DR, 2000, ECOL MONOGR, V70, P401 PERRIN MR, 1982, S AFRICAN J WILDLIFE, V12, P14 RAOUL F, 2001, REV ECOL-TERRE VIE, V56, P339 RUEFENACHT B, 1995, BIOL CONSERV, V71, P269 SALAMOLARD M, 2000, ECOLOGY, V81, P2428 SANTINI L, 1977, EPPO B, V7, P243 SHVARTS EA, 1997, ECOSCIENCE, V4, P158 SOLBRIG OT, 1991, GENES ECOSYSTEMS RES SPITZENBERGER F, 1990, HDB SAUGETIERE EUROP, V3, P334 SQUIRES VR, 1982, J RANGE MANAGE, V35, P116 SZACKI J, 1987, ACTA THERIOL, V32, P31 SZACKI J, 1991, LANDSCAPE ECOL, V5, P219 TABERLET P, 1986, REV ECOL-TERRE VIE, V41, P193 TAYLOR I, 1994, BARN OWLS PREDATOR P THIOULOUSE J, 1997, STAT COMPUT, V7, P75 TURNER BL, 1994, CHANGES LAND USE LAN, P3 VANAPELDOORN RC, 1992, OIKOS, V65, P265 YAHNER RH, 1992, AM MIDL NAT, V127, P381 YLONEN H, 1991, ANN ZOOL FENN, V28, P7 YOMTOV Y, 1991, OIKOS, V60, P173 YOMTOV Y, 1997, CONDOR, V99, P972 ZELENCA G, 1964, REV ECOLOGIE TERRE V, V111, P178 ZHANG Z, 1991, ACTA THERIOL, V36, P239 0921-2973 Landsc. Ecol.ISI:000183770600005Univ Rennes 1, ECOBIO, UMR 6553, F-35042 Rennes, France. Univ Rennes 2, COSTEL, UMR 6554, F-35043 Rennes, France. Butet, A, Univ Rennes 1, ECOBIO, UMR 6553, Av Gen Leclerc, F-35042 Rennes, France.EnglishS<7:#de Oiveira, F. J. B. Metzger, J. P.2006aThresholds in landscape structure for three common deforestation patterns in the Brazilian Amazon 1061-1073Landscape Ecology217-Brazilian Amazon; connectivity; deforestation patterns; fragmentation; landscape dynamics; structural threshold; tropical forests HABITAT FRAGMENTATION; FRACTAL LANDSCAPES; EXTINCTION THRESHOLDS; CONSERVATION BIOLOGY; PERCOLATION THEORY; DISPERSAL SUCCESS; SPATIAL-PATTERN; FOREST; RESPONSES; DYNAMICSArticleOctRAlthough abrupt changes (i.e. thresholds) have been precisely defined in simulated landscapes, such changes in the structure of real landscapes are not well understood. We tested for threshold occurrence in three common deforestation patterns in the Brazilian Amazon: small properties regularly distributed along roads (fishbone), irregularly distributed small properties (independent settlements), and large properties. We analyzed differences between real deforestation patterns, and tested the capacity of simulated landscape with different aggregation degrees to predict threshold occurrence. Three 8 x 8 km sites (replicates) with more than 90% of forest in 1984 and less than 30% in 1998 were selected/simulated for each deforestation pattern. Thresholds were observed for fishbone and large property patterns, especially when considering the connectivity index, although threshold incidences were more frequently observed in simulated landscapes. The capacity of simulated landscapes to predict the exact threshold point in real landscapes was limited, even when considering highly aggregate simulations. However, the general trend in landscape structural changes was similar in real and simulated landscapes. Thresholds occurred at the beginning of the deforestation for mean patch size and at an intermediate stage, corresponding to the percolation threshold, for connectivity, isolation and fragmentation. Threshold behavior for connectivity index might suggest that the survival of strictly forest species will sharply decrease when the proportion of forest reach values < 0.60, indicating that conservation efforts should be done to maintain forest cover above this limit. Significant differences observed among the real deforestation patterns, especially in patch isolation and number of fragments, can have significant consequences for conservation. The independent settlement pattern is, without a doubt, the least favorable of them, resulting in a higher level of fragmentation, whereas the large property and fishbone patterns may be less detrimental if connectivity among the remnant forest patches is preserved.://000241010900008 ISI Document Delivery No.: 091FA Times Cited: 0 Cited Reference Count: 59 Cited References: *INPE, 2004, LEV AR DESFL AM LEG *RADAMBRASIL, 1983, FOLHA SC 21JUR LEV R, V20 ALVES DS, 2002, INT J REMOTE SENS, V23, P2903 ANDREN H, 1994, OIKOS, V71, P355 ANDREN H, 1996, OIKOS, V76, P235 BASCOMPTE J, 1996, J ANIM ECOL, V65, P465 BASKENT EZ, 1999, LANDSCAPE ECOL, V14, P83 BATISTELLA M, 2003, PHOTOGRAMM ENG REM S, V69, P805 BOSWELL GP, 1998, P ROY SOC LOND B BIO, V265, P1921 BURKEY TV, 1989, OIKOS, V55, P75 COLLINGE SK, 1998, OIKOS, V82, P66 DALE VH, 1993, PHOTOGRAMM ENG REM S, V59, P997 FAHRIG L, 1997, J WILDLIFE MANAGE, V61, P603 FAHRIG L, 1998, ECOL MODEL, V105, P273 FLATHER CH, 2002, AM NAT, V159, P40 FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GARDNER RH, 1991, ECOTONES ROLE LANDSC, P76 GARDNER RH, 1991, LANDSCAPE ECOLOGY, P289 GARDNER RH, 1999, LANDSCAPE ECOLOGICAL, P280 GEIST HJ, 2001, LUCC REPORT SERIES, V4 GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 GUSTAFSON EJ, 1994, J FOREST, V92, P28 HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 KING AW, 2002, ECOL MODEL, V147, P23 LAURANCE WF, 1997, SCIENCE, V278, P1117 LAURANCE WF, 2000, ENVIRON MONIT ASSESS, V61, P113 LAURANCE WF, 2001, SCIENCE, V291, P438 LI H, 1993, LANDSCAPE ECOL, V8, P63 MAHAR D, 1988, GOVT POLICIES DEFORE MCINTYRE NE, 1999, OIKOS, V86, P129 METZGER JP, 1997, ACTA OECOL, V18, P1 METZGER JP, 2001, BIOTA NEOTROPICA, V1, P1 METZGER JP, 2002, LANDSCAPE ECOL, V17, P419 MYKRA S, 2000, ANN ZOOL FENN, V37, P79 NAUGLE DE, 1999, LANDSCAPE ECOL, V14, P267 NEEL MC, 2004, LANDSCAPE ECOL, V19, P435 NEPSTAD DC, 1997, CIENCIA CULTURA, V49, P73 ONEILL RV, 1988, LANDSCAPE ECOL, V2, P63 RIPPLE WJ, 1991, BIOL CONSERV, V57, P73 ROMME WH, 1982, ECOL MONOGR, V52, P199 SERRA J, 1982, IMAGE ANAL MATH MORP SKOLE D, 1993, SCIENCE, V260, P1905 SKOLE DL, 1994, BIOSCIENCE, V44, P314 SOARES B, 2004, GLOBAL CHANGE BIOL, V10, P745 SOARES BS, 2002, ECOL MODEL, V154, P217 STAUFFER D, 1985, INTRO PERCOLATION TH TRANI MK, 1999, FOREST ECOL MANAG, V114, P459 TURNER MG, 1989, OIKOS, V55, P121 WALKER RT, 1997, REV EC SOCIOLOGIA RU, V35, P115 WITH KA, 1995, ECOLOGY, V76, P2446 WITH KA, 1997, CONSERV BIOL, V11, P1069 WITH KA, 1997, OIKOS, V78, P151 WITH KA, 1999, CONSERV BIOL, V13, P314 WITH KA, 1999, ECOLOGY, V80, P1340 WITH KA, 1999, LANDSCAPE ECOL, V14, P73 WITH KA, 2002, ECOL APPL, V12, P52 ZAR JH, 1996, BIOSTATISTICAL ANAL ZIPPERER WC, 1993, LANDSCAPE ECOL, V8, P177 0921-2973 Landsc. Ecol.ISI:000241010900008Univ Sao Paulo, Dept Ecol, Biosci Inst, BR-05508900 Sao Paulo, Brazil. Metzger, JP, Univ Sao Paulo, Dept Ecol, Biosci Inst, Rua Matao,321,Travessa 14, BR-05508900 Sao Paulo, Brazil. jpm@ib.usp.brEnglish??de Pablo,C.L. de Agar, P. Martin A. Gomez Sal and F.D. Pineda1988\Descriptive capacity and indicative value of territorial variables in ecological cartography203-211Landscape Ecology14ldiversity spectra, ecological cartography, ecological indicators, mutual information, environmental planningA method is described for selecting different sets of indicator variables from sectors of an ecological hierarchical map. The indicator selection is obtained by analyzing the spatial scale on which each variable attains its maximum indicator capacity. This capacity for prediction is examined by preparing mutual information spectra of each variable using different scales of detail, that can also be viewed as hierarchical levels in a classification.'ڽ7 de Paula, FelipeRossetti Gerhard, Pedro Wenger, SethJ Ferreira, Anderson Vettorazzi, CarlosAlberto Barros Ferraz, SilvioFrosini2013}Influence of forest cover on in-stream large wood in an agricultural landscape of southeastern Brazil: a multi-scale analysis13-27Landscape Ecology281Springer NetherlandsVLandscape ecology Fragmented landscapes Large wood Stream conservation Atlantic forest 2013/01/01+http://dx.doi.org/10.1007/s10980-012-9809-1 0921-2973Landscape Ecol10.1007/s10980-012-9809-1EnglishF?71de Vasconcelos, M.J. B.P. Zeigler L.A. Graham1993[Modeling multi-scale spatial ecological processes under the discrete event systems paradigm273-286Landscape Ecology84?hierarchical modeling, modular modeling, Discrete Event Systems?/Valerie J. Debuse Judith King Alan P. N. House2007Effect of fragmentation, habitat loss and within-patch habitat characteristics on ant assemblages in semi-arid woodlands of eastern Australia 731-745Landscape Ecology2256Landscape - Functional groups - Variance partitioning The reliability of ants as bioindicators of ecosystem condition is dependent on the consistency of their response to localised habitat characteristics, which may be modified by larger-scale effects of habitat fragmentation and loss. We assessed the relative contribution of habitat fragmentation, habitat loss and within-patch habitat characteristics in determining ant assemblages in semi-arid woodland in Queensland, Australia. Species and functional group abundance were recorded using pitfall traps across 20 woodland patches in landscapes that exhibited a range of fragmentation states. Of fragmentation measures, changes in patch area and patch edge contrast exerted the greatest influence on species assemblages, after accounting for differences in habitat loss. However, 35% of fragmentation effects on species were confounded by the effects of habitat characteristics and habitat loss. Within-patch habitat characteristics explained more than twice the amount of species variation attributable to fragmentation and four times the variation explained by habitat loss. The study indicates that within-patch habitat characteristics are the predominant drivers of ant composition. We suggest that caution should be exercised in interpreting the independent effects of habitat fragmentation and loss on ant assemblages without jointly considering localised habitat attributes and associated joint effects. {?HMax Debussche Jacques Lepart1992XEstablishment of woody plants in mediterranean old fields: opportunity in space and time133-145Landscape Ecology63age structure, Buxus sempervirens, dispersal, fleshy-fruited plants, Fraxinus angustijolia, Mediterranean, old field, seedling, seed shadow, succession*The establishment of woody plants following agricultural abandonment in the Mediterranean region is a very widespread process which underlines the extent of the rural exodus. The installation windows in space and time were studied in the French Mediterranean region for two common woody plants, Buxus sempervirens and Fraxinus angustifofia and for a group of common woody fleshy-fruited species. These plants differ in their principal modes of dispersal which are respectively, barochory, anemochory and ornithochory. Their installation was analyzed in relation to the seed shadows, the spatial patterns and the age structures of the seedlings. The majority of the seeds were dispersed over short distances, although some animal vectors may promote a limited amount of long distance dispersal. Hence, whatever the mode of dispersal, a few seeds are often dispersed far from the maternal plant. The combination of several dispersal types in one plant species is a frequently observed feature, one being dominant at a small scale, and related to successional processes, the other being dominant at a larger scale and related to invasive processes. In the old fields the spatial pattern of seedlings closely follow the observed seed shadows. However, competition with the maternal plants may lead to, in some cases, a recruitment deficit close to the seed-bearers. Age structures show that woody plants often install very early after the abandonment of cultivation and that the installation window in time is shortened by the development of a dense herbaceous cover. It is concluded that the installation of woody plants in Mediterranean old fields cannot be reduced to a general rule. The rate and extent of installation depends mainly on the spatial distribution of the seed-bearers, therefore of the spatial patterns of the landscape.Y?i?Henri Decamps Madeleine Fortune Franqois Gazelle and Guy Pautou1988KHistorical influence of man on the riparian dynamics of a fluvial landscape163-173Landscape Ecology13Mriparian dynamics, ecotone, historical environment, fluvial landscape, riversMan’s influence, over the last three centuries, has gradually influenced the dynamics of forest cover along the valley of the Garonne, a seventh order river in Southern France. The vegetation cover of the floodplain depends on topographical levels which govern the frequency and duration of submergence during flooding. Along the valley, forest patches vary from a continuous ribbon of riparian wood along the river to a mosaic of groves towards the upland terraces. In the floodplain, the forest dynamics are influenced by floods, appear to be reversible, and are subject to dominant allogenic processes. On the contrary, forest dynamics on the terraces, which are not influenced by floods, are irreversible and subjected to dominant autogenic processes. Since the end of the 17th century, the structure of riparian woods has been modified by navigation and agriculture leading to a fragmentation of forest cover in the floodplain. Modern agriculture and urbanization have accentuated these tendencies by modifying the hydrologic regime of the river. These historical changes result in a fragmentation of forest cover and a substitution of species in the riparian zone, the forest dynamics being still reversible in the floodplain.?FDecamps, H. J. C. Lefeuvre1992*A spatial approach to ecological processes117-119Landscape Ecology63 +<7D (Decout, S. Manel, S. Miaud, C. Luque, S.2012Integrative approach for landscape-based graph connectivity analysis: a case study with the common frog (Rana temporaria) in human-dominated landscapes267-279Landscape Ecology272common frog habitat suitability structural connectivity landscape permeability maximum entropy modelling graph theory pond-breeding amphibians habitat fragmentation species distributions genetic-structure suitable habitat conservation models patches capercaillie methodology populationsFebTGraph-based analysis is a promising approach for analyzing the functional and structural connectivity of landscapes. In human-shaped landscapes, species have become vulnerable to land degradation and connectivity loss between habitat patches. Movement across the landscape is a key process for species survival that needs to be further investigated for heterogeneous human-dominated landscapes. The common frog (Rana temporaria) was used as a case study to explore and provide a graph connectivity analysis framework that integrates habitat suitability and dispersal responses to landscape permeability. The main habitat patches influencing habitat availability and connectivity were highlighted by using the software Conefor Sensinode 2.2. One of the main advantages of the presented graph-theoretical approach is its ability to provide a large choice of variables to be used based on the study's assumptions and knowledge about target species. Based on dispersal simulation modelling in potential suitable habitat corridors, three distinct patterns of nodes connections of differing importance were revealed. These patterns are locally influenced by anthropogenic barriers, landscape permeability, and habitat suitability. And they are affected by different suitability and availability gradients to maximize the best possible settlement by the common frog within a terrestrial habitat continuum. The study determined the key role of landscape-based approaches for identifying the "availability-suitability-connectivity" patterns from a local to regional approach to provide an operational tool for landscape planning.://0003000887000109Sp. Iss. SI 889QQ Times Cited:0 Cited References Count:56 0921-2973Landscape EcolISI:000300088700010Luque, S Irstea, Inst Agr & Environm Engn Res, Mt Ecosyst Res Unit, 2 Rue Papeterie, F-38402 St Martin Dheres, France Irstea, Inst Agr & Environm Engn Res, Mt Ecosyst Res Unit, 2 Rue Papeterie, F-38402 St Martin Dheres, France Irstea, Inst Agr & Environm Engn Res, Mt Ecosyst Res Unit, F-38402 St Martin Dheres, France Univ Aix Marseille 1, Lab Populat Environm Dev, Equipe Ville Environm Dev, F-13331 Marseille, France Equipe Genome Populat & Biodiversite, Lab Ecol Alpine, F-38041 Grenoble, FranceDOI 10.1007/s10980-011-9694-zEnglish<7QFDelattre, P. De Sousa, B. Fichet-Calvet, E. Quere, J. P. Giraudoux, P.1999YVole outbreaks in a landscape context: evidence from a six year study of Microtus arvalis401-412Landscape Ecology144edge effects habitat landscape structure multiannual fluctuation predation HABITAT FRAGMENTATION RODENT POPULATIONS LAND-USE PREDATION PERSPECTIVE MAMMALS ECOLOGY SCALES CYCLEArticleAugAnalysis of population variations in space and time suggests that landscape may act as a substrate for several kinds of interactions: neighborhood effects, edge effects, prey-predator and parasite-host relationships, etc. Here we discuss how landscape structure and physiognomy affect vole population dynamics. We present the results of a six-year survey of vole populations in the Jura mountains of eastern France (700-900 m elev.) which was conducted to determine whether patch array (i.e. spatial arrangement of different habitat patches) and vole demography are interconnected? The population kinetics of M. arvalis has been monitored in different habitats characterized by extensive homogenous and heterogeneous landscapes. We compare results from different parts of these landscapes to test the neighborhood effects of hedgerow networks, wood mosaics, forests, and villages. Analysis suggests that (1) refuge habitats for specialist predators act as destabilizing factors increasing both the amplitude of fluctuations and the duration of the high density phase, (2) refuge habitats for generalist predators act as regulating factors, dampening vole population kinetics and shortening the phase of peak numbers, (3) sink effects occur at forest edges and in the vicinity of villages, and (4) barrier effects are detected in grassland surrounded by forest. Such descriptive studies have implications for pest control strategies and provide a framework for further demographic field studies and natural experiments.://000081305700008 pISI Document Delivery No.: 214AP Times Cited: 16 Cited Reference Count: 39 Cited References: ANDERSSON M, 1977, OIKOS, V29, P591 ANDREN H, 1994, OIKOS, V71, P355 BARRETT GW, 1994, LANDSCAPE URBAN PLAN, V28, P99 BATZLI GO, 1994, POLISH ECOL STUDIES, V20, P85 BOWERS AM, 1998, IN PRESS LANDSCAPE E BUTET A, 1994, POL ECOL STUD, V20, P137 CHAMBERS LK, 1996, WILDLIFE RES, V23, P23 DELATTRE P, 1990, REV ECOL-TERRE VIE, V45, P375 DELATTRE P, 1992, AGR ECOSYST ENVIRON, V39, P153 DELATTRE P, 1992, REV FRANCAISE FOREST, V44, P91 DELATTRE P, 1996, LANDSCAPE ECOL, V11, P279 ERLINGE S, 1983, OIKOS, V40, P36 FAHRIG L, 1992, THEOR POPUL BIOL, V41, P300 FITZGERALD BM, 1977, J ANIM ECOL, V46, P367 GAINES MS, 1994, POLISH ECOL STUDIES, V20, P163 GIRAUDOUX P, 1997, AGR ECOSYST ENVIRON, V66, P47 HANSKI I, 1987, TRENDS ECOL EVOL, V2, P55 HANSKI I, 1991, J ANIM ECOL, V60, P353 HANSSON L, 1988, MAMMALIA, V52, P159 HANSSON L, 1989, OIKOS, V54, P117 HANSSON L, 1990, OECOLOGIA BERL, V85, P213 HANSSON L, 1994, LANDSCAPE ECOL, V9, P105 HANSSON L, 1995, LANDSCAPE APPROACHES, P20 HENTTONEN H, 1986, THESIS U HELSINKI HENTTONEN H, 1987, OIKOS, V50, P353 HESKE EJ, 1998, IN PRESS LANDSCAPE E LIDICKER WZ, 1988, J MAMMAL, V69, P225 LIDICKER WZ, 1991, J MAMMAL, V72, P631 LIDICKER WZ, 1994, POLISH ECOL STUDIES, V20, P215 LIDICKER WZ, 1995, LANDSCAPE APPROACHES, P3 LIRO A, 1994, POLISH ECOL STUDIES, V20, P227 LOMAN J, 1991, LANDSCAPE ECOL, V5, P183 OSTFELD RS, 1992, WILDLIFE 2001 POPULA, P851 PULLIAM HR, 1988, AM NAT, V132, P652 READHEAD TD, 1988, EPPO B, V18, P237 SZACKI J, 1993, ACTA THERIOL, V38, P113 TEIVAINEN T, 1979, FOLIA FORESTALIA, V387, P1 TURNER MG, 1991, QUANTITATIVE METHODS WIENS JA, 1993, OIKOS, V66, P369 0921-2973 Landsc. Ecol.ISI:000081305700008Univ Montpellier 2, INRA, F-34095 Montpellier 05, France. Delattre, P, Univ Montpellier 2, INRA, CC64, F-34095 Montpellier 05, France.English <7r=Delattre, P. Giraudoux, P. Baudry, J. Quere, J. P. Fichet, E.1996rEffect of landscape structure on Common Vole (Microtus arvalis) distribution and abundance at several space scales279-288Landscape Ecology115landscape structure; fluctuation; population dynamics; Microtus arvalis RODENT POPULATIONS; HETEROGENEOUS LANDSCAPES; PREDATION; MOVEMENTS; KINETICS; DYNAMICS; ISLANDS; MICEArticleOctThis paper aims to answer the following question: are the fluctuations of abundance of Common Vole (Microtus arvalis) specific to different types of landscapes? The research was carried out in landscapes where grass land was dominant. The sampling method was based upon a partition in both landscape types and landscape units. Tracking of vole indices was used to evaluate their relative abundance. Six landscape transects were sampled during two successive years. Results show that population variation and diffusion of demographic states are closely related to landscape types. The possible causes of this are discussed. The landscape units can be used as global variables to assess outbreak risk and landscape design can be used to prevent them.://A1996VR02500005 ISI Document Delivery No.: VR025 Times Cited: 29 Cited Reference Count: 35 Cited References: ANDERSSON M, 1977, OIKOS, V29, P591 APELDOORN RC, 1992, OIKOS, V65, P265 BARRY RE, 1990, CAN FIELD NAT, V104, P387 BAUDRY J, 1989, AGR ECOSYST ENVIRON, V27, P119 DELATTRE P, 1990, REV ECOL-TERRE VIE, V45, P375 DELATTRE P, 1992, AGR ECOSYST ENVIRON, V39, P153 DOUGLASS RJ, 1992, ACTA THERIOL, V37, P359 EDWARDS WR, 1988, T 53 NA WILDL NAT RE, V2, P115 ERLINGE S, 1983, OIKOS, V40, P36 FAHRIG L, 1985, ECOLOGY, V66, P1762 FINERTY JP, 1980, POPULATION ECOLOGY C FORMAN RTT, 1986, LANDSCAPE ECOLOGY GAINES MS, 1992, T 57 NA WILDL NAT RE, P252 GEUSE P, 1985, ANN SOC ROY ZOOL BEL, V115, P211 GIRAUDOUX P, 1990, ALAUDA, V58, P17 GIRAUDOUX P, 1991, THESIS DIJON GIRAUDOUX P, 1994, ACTA OECOL, V15, P385 HANSKI I, 1987, TRENDS ECOL EVOL, V2, P55 HANSKI I, 1991, J ANIM ECOL, V60, P353 HANSSON L, 1988, MAMMALIA, V52, P159 HANSSON L, 1989, OIKOS, V54, P117 HEIKKILA J, 1994, OIKOS, V70, P245 HENTTONEN H, 1987, OIKOS, V50, P353 JOHNSON AR, 1992, LANDSCAPE ECOL, V7, P63 KOZAKIEWICZ M, 1993, ACTA THERIOL, V38, P1 KREBS CJ, 1974, ADV ECOL RES, V8, P267 LIDICKER WZ, 1985, ACTA ZOOL FENN, V173, P23 LIDICKER WZ, 1988, J MAMMAL, V69, P225 LIDICKER WZ, 1992, LANDSCAPE ECOL, V6, P259 LOMAN J, 1991, LANDSCAPE ECOL, V5, P183 MERRIAM G, 1990, CHANGING LANDSCAPES, P121 ROSE RK, 1985, SPECIAL PUBLICATION, V8, P310 SZACKI J, 1993, ACTA THERIOL, V38, P113 TEIVAINEN T, 1979, FOLIA FORESTALIA, V387 THIOULOUSE J, 1989, COMPUT APPL BIOSCI, V5, P287 0921-2973 Landsc. Ecol.ISI:A1996VR02500005BDelattre, P, UNIV MONTPELLIER 2,CC64,F-34095 MONTPELLIER 5,FRANCE.English#|7 4delBarrio, G. Alvera, B. Puigdefabregas, J. Diez, C.1997NResponse of high mountain landscape to topographic variables: Central Pyrenees95-115Landscape Ecology122omontane landscapes gis model landscape classification catchment geomorphology ecology models prediction patternAprAn objective method for inductively modelling the distribution of mountain land units using GIS managed topographic variables is presented. The landscape of a small high mountain catchment in the Spanish Pyrenees, covered with grassland, was classified in tan land units by hierarchical agglomerative clustering, using a sample of 194 random plots, in which classes of vegetation, soils and landforms were defined. Additionally, seven layers of topographic variables (altitude, slope angle, aspect, solar radiation, topographic wetness index, specific catchment area, and regolith thickness) were created from a Digital Elevation Model. The affinity of each land unit to the topographic variables was calculated using Binary Discriminant Analysis (BDA), after dichotomising the latter around their mean values. Then, the distribution of each land unit was predicted by boolean operations combining step by step distributions for the seven topographic variables ordered, for each unit, after the absolute values of the Haberman's residuals in BDA. The predicted distributions were tested (chi(2)) against that of the observed sampling plots. From the original ten land units, the distributions of eight of them were successfully predicted (four are related to the slept sequence, two reflect the water accumulation in the soil, and two respond to geomorphic processes) while the remaining two had to be rejected. Part of the catchment (39%) was not assigned to any land unit, probably because more distributed variables accounting for snow distribution are necessary.://A1997XQ45000003.Xq450 Times Cited:25 Cited References Count:62 0921-2973ISI:A1997XQ45000003JdelBarrio, G Csic,Estac Expt Zonas Aridas,Gen Segura 1,Almeria 04001,SpainEnglish D?!Delcourt, H. R. Delcourt, P. A.1988?Quaternary landscape ecology: Relevant scales in space and time23-44Landscape Ecology21karchaeology, hierarchy, long-term data sets, paleoecology, Southeastern US, scale, spatial-temporal domainsmTwo primary goals of landscape ecologists are to (1) evaluate changes in ecological pattern and process on natural landscapes through time and (2) determine the ecological consequences of transforming natural landscapes to cultural ones. Paleoecological techniques can be used to reconstruct past landscapes and their changes through time; use of paleoecological methods of investigation in combination with geomorphic and paleoethnobiological data, historical records, and shorter-term ecological data sets makes it possible to integrate long-term ecological pattern and process on a nested series of temporal and spatial scales. ‘Natural experiments’ of the past can be used to test alternative hypotheses about the relative influences of environmental change, biological interactions, and human activities in structuring biotic communities within landscape mosaics. On the absolute time scale of the Quaternary Period, spanning the past 1.8 million years, current distributional ranges of the biota have taken shape and modern biotic communities have assembled. Quaternary environmental changes have influenced the development of natural landscapes over time scales of centuries to hundreds of thousands of years; human cultural evolution has resulted in the transformation of much of the biosphere from natural to cultural landscapes over the past 5,000 years. The Quaternary extends to and includes the present and the immediate future. Knowledge of landscape changes on a Quaternary time scale is essential to landscape ecologists who wish to have a context for predicting future trends on local, regional, and global scales.V<7mDelcourt, H. R. Delcourt, P. A.1996kPresettlement landscape heterogeneity: Evaluating grain of resolution using General Land Office Survey data363-381Landscape Ecology116.General Land Office Surveys; Great Lakes forests; landscape ecology; mixed conifer northern hardwoods forest; restoration ecology HEMLOCK-HARDWOOD FORESTS; SYLVANIA RECREATION AREA; OLD-GROWTH; CONIFER ECOSYSTEMS; NORTHERN HARDWOOD; SPATIAL PATTERN; UPPER-PENINSULA; BEECH CLIMAX; MICHIGAN; DISTURBANCEArticleDecGeneral Land Office Survey (GLOS) records from the A.D. 1840s provide data for quantitative characterization of presettlement vegetation across western Mackinac County, Michigan, located within the mixed conifer-northern hardwoods forest region. We analyzed data from land survey plat maps and 1958 bearing, witness, and line trees from 162 surveyed section and quarter-section corners in order to map vegetation cover types at a level of spatial resolution appropriate for characterizing landscape heterogeneity using standard landscape ecological metrics. As also demonstrated by a number of both classic and contemporary plant-ecological studies, the distribution of landforms, soils properties, hydrology, and location of fire breaks all contribute to the heterogeneity in vegetation observed at a landscape scale in the region. Through a series of spa tial landscape analyses with differing grain of resolution, in this study we determine that a grid cell size of 65 ha (0.5 mix0.5 mi or 0.25 mi(2) to 259 ha (1 mi(2)) gives a conservative characterization of landscape heterogeneity using standard metrics and is therefore appropriate for use of GLOS data to study historical landscape changes.://A1996VY82900006 ISI Document Delivery No.: VY829 Times Cited: 23 Cited Reference Count: 87 Cited References: ALBERT DA, 1986, REGIONAL LANDSCAPE E ANDERSON RC, 1970, T ILLINOIS STATE ACA, V63, P214 BARNES BV, 1981, MICHIGAN TREES GUIDE BARNES BV, 1989, NAT AREA J, V9, P45 BERNABO JC, 1981, QUATERNARY RES, V15, P143 BOURDO EA, 1956, ECOLOGY, V37, P754 BOURDO EA, 1983, GREAT LAKES FOREST E, P3 BRAUN EL, 1974, DECIDUOUS FORESTS E BROWN RT, 1952, ECOL MONOGR, V22, P217 BURNS RM, 1990, USDA FOREST SERV 654, V1 BURNS RM, 1990, USDA FOREST SERV 654, V2 BURT WA, 1850, US GOVT SERIES, V551, P876 BURT WA, 1881, KEY SOLAR COMPASS SU CANHAM CD, 1984, ECOLOGY, V65, P803 CLAMPITT C, 1985, BIOSCIENCE, V35, P738 CRANKSHAW WB, 1965, ECOLOGY, V46, P688 CURTIS JT, 1959, VEGETATION WISCONSIN DELCOURT HR, 1974, ECOLOGY, V55, P638 DELCOURT HR, 1977, ECOLOGY, V58, P1085 DELCOURT PA, 1992, LANDSCAPE BOUNDARIES, V92, P19 DELCOURT PA, 1996, IN PRESS QUARTERNARY FARRAND WR, 1985, QUATERNARY EVOLUTION, P17 FINLEY RW, 1951, THESIS U WISCONSIN M FLADER SL, 1983, GREAT LAKES FOREST E FRANZMEIER DP, 1963, MICH STATE U AGR EXP, V46, P37 FRASER GS, 1990, GEOLOGICAL SOC AM SP, V251, P75 FRELICH LE, 1991, ECOL MONOGR, V61, P145 FRELICH LE, 1993, ECOLOGY, V74, P513 FUTYMA RP, 1982, THESIS U MICHIGAN AN GAUCH HG, 1982, MULTIVARIATE ANAL CO GLEASON HA, 1963, MANUAL VASCULAR PLAN GORDON RB, 1966, NATURAL VEGETATION M GORDON RB, 1969, B OHIO BIOL SURVEY, V3, P1 GRAHAM SA, 1941, ECOLOGY, V22, P355 GRIMM EC, 1984, ECOL MONOGR, V54, P291 HALLIDAY WED, 1937, FOREST SERVICE B, V89 HARSBERGER JW, 1911, SAMMLUNG PFLANZENGEO, V12 IVERSON LR, 1987, ADV SPACE RES, V7, P183 IVERSON LR, 1989, ILLINOIS NATURAL HIS, V11, P1 KANOYER LA, 1942, PAPERS MICHIGAN ACAD, V28, P47 KENOYER LA, 1934, PAPERS MICHIGAN ACAD, V19, P107 KENOYER LA, 1940, PAPERS MICHIGAN ACAD, V25, P75 LAMBERT JL, 1971, SOIL SCI SOC AM J, V35, P785 LARSEN CE, 1987, US GEOLOGICAL SURVEY, V1801, P1 LEITNER LA, 1991, LANDSCAPE ECOL, V5, P203 LINDSEY AA, 1965, BOT GAZ, V126, P155 LINDSEY AA, 1973, P INDIANA ACAD SCI, V82, P181 LORIMER CG, 1977, ECOLOGY, V58, P139 MADSEN BJ, 1987, THESIS U MICHIGAN AN MARSCHNER FJ, ORIGIANL FORESTS MIC MARSCHNER FJ, 1957, USDA AGR HDB, V153 MARTIN JB, 1986, CALL N COUNTRY STORY MCINTOSH RP, 1962, AM MIDL NAT, V68, P409 MEDLEY KE, 1987, MICH BOT, V26, P78 MLADENOFF DJ, 1980, T WISC ACAD SCI, V68, P74 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 NICHOLS GE, 1935, ECOLOGY, V16, P403 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PASTOR J, 1990, LANDSCAPE ECOL, V4, P55 PETTY WH, 1994, THESIS U TENNESSEE K PETTY WH, 1996, J PALEOLIMNOL, V15, P147 PREGITZER KS, 1984, CAN J FOREST RES, V14, P362 ROWE JS, 1972, CAN FOR SERV PUBL, V1300, P1 ROWE RR, 1977, OUR 1 50 YEARS 1927 SCHWARTZ MW, 1994, ECOLOGY, V75, P687 SIMPSON TB, 1990, 4 HUR MOUNT WILDL FD SPIES TA, 1985, CAN J FOREST RES, V15, P949 SPIES TA, 1985, CAN J FOREST RES, V15, P961 STEARNS FW, 1949, ECOLOGY, V30, P350 STEARNS FW, 1951, ECOLOGY, V32, P345 STEARNS FW, 1974, HDB VEGETATION SCI 8, P75 STEARNS FW, 1987, CONS FDN LAK STAT GO, P24 STEWART LO, 1935, PUBLIC LAND SURVEYS TRANSEAU EN, 1905, AM NAT, V39, P875 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1990, QUANTITATIVE METHODS TURNER MG, 1993, LANDSCAPE ECOL, V8, P213 VEATCH JO, 1953, SOIL MAP MICHIGAN WHITE CA, 1983, HIST RECTANGULAR SUR WHITE MA, 1994, LANDSCAPE ECOL, V9, P191 WHITFORD HN, 1901, BOT GAZ, V31, P289 WHITNEY G, 1995, SOIL SURVEY MACKINAC WHITNEY GG, 1986, ECOLOGY, V67, P1548 WHITNEY GG, 1987, J ECOL, V75, P667 WHITNEY GG, 1990, J ECOL, V78, P443 WHITNEY GG, 1995, COASTAL WILDERNESS F WILLIAMS M, 1989, AM THEIR FORETS HIST 0921-2973 Landsc. Ecol.ISI:A1996VY82900006NDelcourt, HR, UNIV TENNESSEE,DEPT ECOL & EVOLUTIONARY BIOL,KNOXVILLE,TN 37996.English?J/Yannick Delettre Paul TrChen Patrick Grootaert1992QSpace heterogeneity, space use and short-range dispersal in Diptera: A case study175-181Landscape Ecology63landscape ecology, habitat heterogeneity, patchiness, community structure, tactics, population dynamics, behaviour, dispersal, flight, Diptera, Empididae, ChironomidaeThis study investigates the impact of landscape heterogeneity on community structure and population dynamics in two families of Diptera (Empididae and Chironomidae). Adult emergence is compared with aerial flow by means of emergence traps and yellow traps on a transect across four habitats (pond banks, woodland, grassland and heathland) in close proximity to each other. Empids use different space units according to their larval development, sexual behaviour and food requirements. This creates an intermingling of species and individuals originating from different habitats in the lowest part of the transect. Adult chironomids of aquatic species exhibit a preferential use of open habitats while adults with terrestrial larvae disperse largely above the four sites. Habitat fragmentation and heterogeneity lead to opposite patterns in chironomid distribution: some species disperse over the whole set of macrohabitats but others are confined to a single patch, resulting in population isolation. The impact of spatial and temporal landscape patterning is discussed with a view to community structure, life-history tactics and population dynamics. <7rDelin, A. E. Andren, H.1999bEffects of habitat fragmentation on Eurasian red squirrel (Sciurus vulgaris) in a forest landscape67-72Landscape Ecology141red squirrel habitat fragmentation forest landscape fragment size isolation the random sample hypothesis matrix SELECTION ECOLOGY BIRDSArticleFeb We studied the effects of habitat fragmentation, measured as forest stand size and isolation, on the distribution of Eurasian red squirrels (Sciurus vulgaris). Squirrel density was surveyed during four years in 46 forest stands (0.1-500 ha) in a forest landscape in south-central Sweden. The only factor that significantly influenced a density index was the proportion of spruce within a habitat fragment. Neither fragment size nor degree of isolation were significant. Furthermore, none of the interactions with year were significant, suggesting the same pattern in all four years. Thus, the effect of habitat fragmentation in this study seems to be only pure habitat loss, i.e. halving the proportion of preferred habitat in the landscape should result in a halving of the red squirrel population. Therefore, the landscape can be viewed as functionally continuous for the squirrels, although the preferred habitat was divided into fragments. The most likely explanation for the difference between this study and other studies on squirrels that found effects due to habitat fragmentation is a combination of shorter distances and less hostile surroundings in our study area. To identify landscape effects requires multiple studies because single studies usually consider only one landscape.://000079005100005 $ISI Document Delivery No.: 173XM Times Cited: 19 Cited Reference Count: 28 Cited References: *SWED NAT BOARD FO, 1988, BAS FOR ABERG J, 1995, OECOLOGIA, V103, P265 AHTI T, 1968, ANN BOT FENN, V5, P169 ANDREASSIAN B, 1997, ANN CARDIOL ANGEIOL, V46, P171 ANDREN H, 1992, ECOGRAPHY, V15, P303 ANDREN H, 1994, OIKOS, V70, P43 ANDREN H, 1994, OIKOS, V71, P355 ANDREN H, 1996, OIKOS, V76, P235 ANDREN H, 1997, OIKOS, V80, P193 ARNQVIST G, 1995, TRENDS ECOL EVOL, V10, P236 BRIGHT PW, 1994, J APPL ECOL, V31, P329 CELADA C, 1994, BIOL CONSERV, V69, P177 COHEN J, 1988, STAT POWER BEHAV SCI CONNOR EF, 1979, AM NAT, V113, P791 ESSEEN PA, 1997, ECOLOGICAL B, V46, P16 HAILA Y, 1983, OIKOS, V41, P334 HANSSON L, 1979, J APPL ECOL, V16, P339 HAYNE DW, 1965, T 30 N AM WILDL C, P393 HURLBERT SH, 1984, ECOL MONOGR, V54, P187 HURRELL E, 1984, MAMMAL REV, V14, P1 LANDE R, 1987, AM NAT, V130, P624 SOUTHWOOD TRE, 1977, J ANIM ECOL, V4, P171 TAYLOR PD, 1993, OIKOS, V68, P571 VANAPELDOORN RC, 1994, LANDSCAPE ECOL, V9, P227 VERBOOM B, 1990, LANDSCAPE ECOL, V46, P337 WAUTERS L, 1994, OIKOS, V69, P140 WAUTERS LA, 1994, P ROY SOC LOND B BIO, V255, P107 WRIGHT DH, 1991, J BIOGEOGR, V18, P463 0921-2973 Landsc. Ecol.ISI:000079005100005Swedish Univ Agr Sci, Dept Conservat Biol, Grimso Wildlife Res Stn, S-73091 Riddarhyttan, Sweden. Andren, H, Swedish Univ Agr Sci, Dept Conservat Biol, Grimso Wildlife Res Stn, S-73091 Riddarhyttan, Sweden.English<7 Demers, M. N.1993rRoadside ditches as corridors for range expansion of the western harvester ant (Pogonomyrmex occidentalis Cresson)93-102Landscape Ecology82vCORRIDORS; ANTS; RANGE EXPANSION; POGONOMYRMEX-OCCIDENTALIS; LANDSCAPE QUEUES; WESTERN HARVESTER ANT; ROADSIDE DITCHESArticleJunThe northeasternmost range extent of the western harvester ant (Pogonomyrmex occidentalis Cresson) occurs just east of the Missouri River in North Dakota. The earliest known records (1882) of this species place it in the same general position as existed at the time of the first exhaustive survey in 1966. A 1990 survey reveals substantial eastward and northward range expansion beyond locations known to be stable between 1966 and 1978. This suggests that this species' range has not yet stabilized with post quaternary climatic changes. Field observations show that, near the expanding edge of its range, a strong relationship exists between anthropogenic modification of the landscape and locational propensity. Specifically, land uses which periodically disrupt the soil, such as row cropping, show a nearly absolute lack of occupancy, while the well-drained, sheltered roadside ditches are heavily populated by P. occidentalis. The roads themselves closely resemble bare-soil, post-nuptial landing sites known to encourage P. occidentalis ant colonization. This strongly suggests that the roadside ditches act as corridors for range expansion of the species. The similarity between road network density within and beyond the species range, combined with severe drought conditions during 1988 and 1989 indicate that climate, as a regional scale variable, is the stimulus for range expansion, while landscape level queues provided by the roadside ditches, are the mechanism by which it is accomplished. Of the site level factors examined, only roadside ditch azimuths and soil texture showed statistical significance as possible locational factors, but no causal mechanism can be assumed.://A1993LM22200002 IISI Document Delivery No.: LM222 Times Cited: 17 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1993LM22200002TDEMERS, MN, OHIO STATE UNIV,DEPT GEOG,103 BRICKER,190 N OVAL MALL,COLUMBUS,OH 43210.English|7 Demers, M. N.1993rRoadside Ditches as Corridors for Range Expansion of the Western Harvester Ant (Pogonomyrmex-Occidentalis Cresson)93-102Landscape Ecology82pcorridors ants range expansion pogonomyrmex-occidentalis landscape queues western harvester ant roadside ditchesJunThe northeasternmost range extent of the western harvester ant (Pogonomyrmex occidentalis Cresson) occurs just east of the Missouri River in North Dakota. The earliest known records (1882) of this species place it in the same general position as existed at the time of the first exhaustive survey in 1966. A 1990 survey reveals substantial eastward and northward range expansion beyond locations known to be stable between 1966 and 1978. This suggests that this species' range has not yet stabilized with post quaternary climatic changes. Field observations show that, near the expanding edge of its range, a strong relationship exists between anthropogenic modification of the landscape and locational propensity. Specifically, land uses which periodically disrupt the soil, such as row cropping, show a nearly absolute lack of occupancy, while the well-drained, sheltered roadside ditches are heavily populated by P. occidentalis. The roads themselves closely resemble bare-soil, post-nuptial landing sites known to encourage P. occidentalis ant colonization. This strongly suggests that the roadside ditches act as corridors for range expansion of the species. The similarity between road network density within and beyond the species range, combined with severe drought conditions during 1988 and 1989 indicate that climate, as a regional scale variable, is the stimulus for range expansion, while landscape level queues provided by the roadside ditches, are the mechanism by which it is accomplished. Of the site level factors examined, only roadside ditch azimuths and soil texture showed statistical significance as possible locational factors, but no causal mechanism can be assumed.://A1993LM22200002-Lm222 Times Cited:17 Cited References Count:0 0921-2973ISI:A1993LM22200002RDemers, Mn Ohio State Univ,Dept Geog,103 Bricker,190 N Oval Mall,Columbus,Oh 43210English |?` 8Desrochers, A. Belisle, M. Morand-Ferron, J. Bourque, J.2011DIntegrating GIS and homing experiments to study avian movement costs47-58Landscape Ecology261JanForest cover reduction may affect movements of forest animals, but resistance to animal movements in and out of forests remains unknown despite its importance for modelling. We tested whether ovenbird (Seiurus aurocapilla), a forest-interior songbird, responds similarly to the amount of forest cover while moving locally (similar to 2 km) and over entire landscapes (similar to 25 km). We compared spatially-explicit simulations to field data to address the issue of resistance to movement in open areas. We caught, banded and translocated 143 territorial males 0.8-27 km away from their territory early in the breeding season. Seventy-eight percent and 50% of translocated males returned (homed) within 10 days following "local" and "landscape" translocations respectively. Independent of translocation distance, homing times increased with decreasing forest in the landscape. With a Geographic Information System (GIS), we simulated "least-cost" paths that homing ovenbirds would ideally take, when resistance to movement in open areas ranged 1-1000 times the resistance to movement in forest. The length, the cumulative cost, and variability of simulated least-cost movement paths increased with increasing resistance in open areas. With landscape translocations, least-cost path length explained homing time better than Euclidean distance, and based on an information-theoretic approach, resistance to movement was estimated to be 27 times greater in open areas than in forests (95% confidence interval: 16-45). However, least-cost path length did not perform better than Euclidean distance with local translocations, and the cumulative cost of least-cost paths was not associated to homing time in either translocation scale. We conclude that resistance to animal movements in open areas can be addressed by a combination of GIS modelling and translocation experiments, and is between one and two orders of magnitude greater than resistance to movements in forests, in the case of ovenbirds.!://WOS:000286004400005Times Cited: 1 0921-2973WOS:00028600440000510.1007/s10980-010-9532-86<7o(Desrochers, A. Hanski, I. K. Selonen, V.2003ISiberian flying squirrel responses to high- and low-contrast forest edges543-552Landscape Ecology185boundary edge effect flying squirrel forest fragmentation Pteromys volans radio tracking spatial scale Finland PTEROMYS-VOLANS CLEAR-CUT ACCIPITER-GENTILIS POPULATION DECLINE HABITAT EDGES RANGE SIZE PATCH SIZE LANDSCAPE INTERIOR BOUNDARIESArticleNWe examined responses of Siberian flying squirrels (Pteromys volans) to edges between nesting habitat (mature spruce forests), movement habitat (other forests, pine bogs), and open areas within their home ranges in southern Finland in 1996-2000. Radio-tracked squirrels (n = 146) were generally associated to edges when they were active at night. Compared to distances expected from the habitat pattern of their home range, squirrels occurred closer to high-contrast edges (of open areas) and low-contrast edges (nesting or movement forest types). Association with edges of open areas was more pronounced when squirrels were in movement habitat than in nesting habitat, possibly because of stronger channeling of movements in the former habitat. When in nesting habitat, squirrels responded more strongly to field edges than to recent clearcut edges, probably as a result of the presence of more deciduous trees on field edges, unlike clearcut edges. Responses to open areas were independent of spatial scale. However, responses to movement habitat from nesting habitat, and vice versa, were more pronounced over hundreds than tens of meters. Nesting cavities and dreys were generally located at random with respect to edges. We conclude that squirrel responses to edges of landscape attributes are diverse and depend both on spatial scale and edge contrast.://000185827200007 ISI Document Delivery No.: 730JG Times Cited: 6 Cited Reference Count: 54 Cited References: *ESRI, 1999, ARCV 3 2 GIS *SAS I INC, 1989, SAS STAT US GUID VER, V1 BENDER DJ, 1998, ECOLOGY, V79, P517 BIDER JR, 1968, ECOL MONOGR, V38, P269 CHAPIN TG, 1998, CONSERV BIOL, V12, P1327 CHEN JQ, 1993, AGR FOREST METEOROL, V63, P219 DESROCHERS A, 2000, OIKOS, V91, P376 DIDHAM RK, 1996, TRENDS ECOL EVOL, V11, P255 DIJAK WD, 2000, J WILDLIFE MANAGE, V64, P209 DONOVAN TM, 1997, ECOLOGY, V78, P2064 FRAVER S, 1994, CONSERV BIOL, V8, P822 GIBBS JP, 1998, J WILDLIFE MANAGE, V62, P584 GRINDAL SD, 1999, ECOSCIENCE, V6, P25 HADDAD NM, 1999, AM NAT, V153, P215 HANSKI IK, 1998, WILDLIFE BIOL, V4, P33 HANSKI IK, 2000, BIOL GLIDING MAMMALS, P67 HANSKI IK, 2000, J MAMMAL, V81, P798 HANSSON L, 1994, LANDSCAPE ECOL, V9, P105 HESKE EJ, 1995, J MAMMAL, V76, P562 HOKKANEN H, 1982, BIOL CONSERV, V23, P273 HOLMQUIST JG, 1998, OIKOS, V81, P558 HOOGE PN, 1997, ANIMAL MOVEMENT EXTE JOKIMAKI J, 1998, CAN J FOREST RES, V28, P1068 KENWARD RE, 1982, J ANIM ECOL, V51, P69 KING DI, 1998, FOREST ECOL MANAG, V104, P151 KREBS CJ, 1989, ECOLOGICAL METHODOLO KREMSATER L, 1999, FOREST FRAGMENTATION, P117 KURKI S, 1998, J ANIM ECOL, V67, P874 LAHTI DC, 2001, BIOL CONSERV, V99, P365 LANDE R, 1987, AM NAT, V130, P624 LIDICKER WZ, 1992, ANIMAL DISPERSAL SMA, P21 LIDICKER WZ, 1992, LANDSCAPE ECOL, V6, P259 LIDICKER WZ, 1996, METAPOPULATIONS WILD, P85 LIDICKER WZ, 1999, LANDSCAPE ECOL, V14, P333 LIDICKER WZ, 1999, LANDSCAPE ECOLOGY SM, P211 MILLS LS, 1995, CONSERV BIOL, V9, P395 MILLS LS, 1996, NATL PARKS PROTECTED, P199 MONKKONEN M, 1997, ECOGRAPHY, V20, P623 PALOMARES F, 2000, CONSERV BIOL, V14, P809 PATON PWC, 1994, CONSERV BIOL, V8, P17 PITKANEN A, 1999, HOLOCENE, V9, P311 RASSI P, 2000, SUOMEN LAJIEN UHANAL REDPATH SM, 1995, J ANIM ECOL, V64, P652 REUNANEN P, 2000, CONSERV BIOL, V14, P218 RIES L, 2001, J ANIM ECOL, V70, P840 SCHULTZ CB, 2001, ECOLOGY, V82, P1879 SELONEN V, 2001, ECOGRAPHY, V24, P588 SISK TD, 1993, NATURE CONSERVATION, V3, P57 TORNBERG R, 2001, IBIS, V143, P41 VANWILGENBURG SL, 2001, ECOSCIENCE, V8, P454 VILLARD MA, 1998, AUK, V115, P801 WIDEN P, 1989, IBIS, V131, P205 WITH KA, 2001, BIOL CONSERV, V100, P75 WOLFF JO, 1980, CAN J ZOOL, V58, P1800 0921-2973 Landsc. Ecol.ISI:000185827200007Univ Laval, Fac Forestry & Geomat, Forest Biol Ctr, Quebec City, PQ G1K 7P4, Canada. Univ Helsinki, Dept Systemat & Ecol, FIN-00014 Helsinki, Finland. Desrochers, A, Univ Laval, Fac Forestry & Geomat, Forest Biol Ctr, Quebec City, PQ G1K 7P4, Canada.English<7-Detenbeck, N. E. Johnston, C. A. Niemi, G. J.1993SWetland effects on lake water-quality in the Minneapolis-St. Paul metropolitan area39-61Landscape Ecology81QWETLANDS; LAKE WATER-QUALITY; MINNESOTA; LANDSCAPE; PRINCIPAL COMPONENTS ANALYSISArticleMarA method developed to evaluate the cumulative effect of wetland mosaics on water quality was applied to 33 lake watersheds in the seven-county region surrounding Minneapolis-St. Paul, Minnesota. A geographic information system (GIS) was used to record and measure landscape variables derived from aerial photos. Twenty-seven watershed land-use and land-cover variables were reduced to eight principal components which described 85% of the variance among watersheds. Relationships between lake water quality variables and the first six principal components plus an index of lake mixis were analyzed through stepwise multiple regression analysis. A combination of three landscape components (wetland/watershed area, agriculture/wetlands, and forest/soils components) explained 49% of the variance in a trophic state index, even though most of the lakes examined were already highly eutrophic, and thus were influenced by internal loading. The regression equations explained a range of 14 to 76% of the variation in individual water quality variables. Forested land-use was associated with lower lake trophic state, chloride, and lead. High lake trophic state was associated with agricultural land-use and with wetland distance from the lake of interest. The extent of wetlands was associated with low total lead and high color in lakes downstream. Wet meadows or herbaceous, seasonally-flooded wetlands contributed more to lake water color than did cattail marshes.://A1993KW95800004 IISI Document Delivery No.: KW958 Times Cited: 28 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1993KW95800004IDETENBECK, NE, US EPA,ENVIRONM RES LAB,6201 CONGDON BLVD,DULUTH,MN 55804.English|7 -Detenbeck, N. E. Johnston, C. A. Niemi, G. J.1993RWetland Effects on Lake Water-Quality in the Minneapolis St-Paul Metropolitan-Area39-61Landscape Ecology81Mwetlands lake water-quality minnesota landscape principal components analysisMarA method developed to evaluate the cumulative effect of wetland mosaics on water quality was applied to 33 lake watersheds in the seven-county region surrounding Minneapolis-St. Paul, Minnesota. A geographic information system (GIS) was used to record and measure landscape variables derived from aerial photos. Twenty-seven watershed land-use and land-cover variables were reduced to eight principal components which described 85% of the variance among watersheds. Relationships between lake water quality variables and the first six principal components plus an index of lake mixis were analyzed through stepwise multiple regression analysis. A combination of three landscape components (wetland/watershed area, agriculture/wetlands, and forest/soils components) explained 49% of the variance in a trophic state index, even though most of the lakes examined were already highly eutrophic, and thus were influenced by internal loading. The regression equations explained a range of 14 to 76% of the variation in individual water quality variables. Forested land-use was associated with lower lake trophic state, chloride, and lead. High lake trophic state was associated with agricultural land-use and with wetland distance from the lake of interest. The extent of wetlands was associated with low total lead and high color in lakes downstream. Wet meadows or herbaceous, seasonally-flooded wetlands contributed more to lake water color than did cattail marshes.://A1993KW95800004-Kw958 Times Cited:33 Cited References Count:0 0921-2973ISI:A1993KW95800004GDetenbeck, Ne Us Epa,Environm Res Lab,6201 Congdon Blvd,Duluth,Mn 55804English<74Devasconcelos, M. J. P. Zeigler, B. P. Graham, L. A.1993ZModeling multiscale spatial ecological processes under the discrete-event systems paradigm273-286Landscape Ecology84ArticleDecA multi-scale spatial ecological model of a wet sclerophyllous forest subject to recurrent fires is presented. The model is specified in a Discrete Event Systems framework (DEVS) (Zeigler, 1990) interfaced with a Geographic Information System (GIS), and includes the ability to simulate landscape dynamics at several levels of resolution simultaneously. This is achieved by encoding a modular hierarchical representation of the forest landscape components into a set of nested, interconnected, and spatially referenced dynamic models. The results of the landscape dynamics simulations are displayed as sequences of maps through time, illustrating the potential of this modeling methodology for dealing with complex hierarchical structures that operate at several spatial and temporal resolutions.://A1993MN73600004 HISI Document Delivery No.: MN736 Times Cited: 1 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1993MN73600004XDEVASCONCELOS, MJP, CTR NACL INFORMACAO GEOG,RUA BRAANCAMP 82 1D,P-1200 LISBON,PORTUGAL.English)<7$Diaz-Delgado, R. Lloret, F. Pons, X.2004;Spatial patterns of fire occurrence in Catalonia, NE, Spain731-745Landscape Ecology197%fire occurrence; fire recurrence; fire size distribution; fractal dimension; land cover; Lorenz curves; spots; residual vegetation islands SELF-ORGANIZED CRITICALITY; SOUTHERN CALIFORNIA; LANDSCAPE PATTERNS; FOREST-FIRES; WILDLAND FIRE; NEW-ZEALAND; WILDFIRES; INEQUALITY; SUCCESSION; BEHAVIORArticleIn this paper, we analyse spatial patterns of fire occurrence in Catalonia (NE Spain) during 1975-98. Fire scar maps, discriminated by means of 30-60 m resolution remote sensing imagery, have been used as a source of fire occurrence. We employ several visual or analytical approaches to interpret fire occurrence in this region, such as those of Minnich and Chou (1997), Ricotta et al. (2001) or Krummel et al. (1987). Crucial spatial patterns such as fire size distribution, fire frequency distribution, spots and residual vegetation islands are documented. In addition, several geographical layers were overlaid with burned area maps in order to determine interactions between fire occurrence and environmental parameters such as altitude, slope, solar radiation, and burned land cover. Assuming that fire occurrence is well determined by such a posteriori empirical factors we detect areas most prone to fire in this region and aim to enhance the local forest management and conservation plans.://000226384000003 Q ISI Document Delivery No.: 888OL Times Cited: 6 Cited Reference Count: 62 Cited References: *DARP, 1999, FOCV PROGR GEST RISC, P231 *ICCDARP, 1993, MOD DIG EL CAT *MAPA, 1979, CON PRIM INV FOR NAC, P174 *MAPA, 1980, FROND PRIM INV FOR N, P235 AGEE JK, 1993, FIRE ECOLOGY PACIFIC ALBINI FA, 1976, INTO0 USDA FOR SERV ARNO SF, 1977, INT42 USDA FOR SERV BENDEL RB, 1989, OECOLOGIA, V78, P394 DATE C, 1995, INTRO DATABASE SYSTE, P839 DIAZDELGADO R, 2002, ECOLOGY, V83, P2293 DIAZDELGADO R, 2003, INT J REMOTE SENS, V24, P1751 DIAZDELGADO R, 2004, INT J WILDLAND FIRE DONNEGAN JA, 1999, ECOLOGY, V80, P1370 EBERHART KE, 1987, CAN J FOREST RES, V17, P1207 FINNEY MA, 1999, SPATIAL MODELING FOR, P186 FOLCH R, 1986, VEGETACIO PAISOS CAT FOLCH R, 1996, ECOLOGIA FOC, P255 FOSTER DR, 1983, CAN J BOT, V61, P2459 GASAWAY WC, 1985, CAN FIELD NAT, V99, P135 GRACIA C, 1997, P 11 WORLD FOR C ANT, P43 HANES TL, 1971, ECOL MONOGR, V41, P27 HEINSELMAN ML, 1973, QUATERNARY RES, V3, P329 JOHNSTON C, 1990, LANDSCAPE ECOL, V4, P3 KEELEY JE, 1999, SCIENCE, V284, P1829 KEELEY JE, 2001, CONSERV BIOL, V15, P1536 KILGORE BM, 1979, ECOLOGY, V60, P129 KRUMMEL JR, 1987, OIKOS, V48, P321 LEE CK, 1998, TOURISM MANAGE, V19, P341 LIEFFERS VJ, 1989, CAN J BOT, V67, P2900 LLORET F, 2002, LANDSCAPE ECOL, V17, P745 LLORET F, 2003, PLANT ECOL, V167, P223 LORENZ MO, 1905, J AM STAT ASSOC, V9, P209 LOVEJOY S, 1982, SCIENCE, V216, P185 MAFFINI G, 1987, PHOTOGRAMMETRIC ENG, V53, P1397 MALAMUD BD, 1998, SCIENCE, V281, P1840 MANDELBROT BB, 1977, FRACTALS FORM CHANCE, P213 MILLER C, 1999, CAN J FOREST RES, V29, P202 MINNICH RA, 1997, INT J WILDLAND FIRE, V7, P221 MORENO JM, 1998, LARGE FOREST FIRES, P159 NIKORA VI, 1999, LANDSCAPE ECOL, V14, P17 PERRY GLW, 1999, J APPL ECOL, V36, P502 PINOL J, 1998, CLIMATIC CHANGE, V38, P345 PONS X, 1996, MODELOS SISTEMAS INF, P87 QUIRK WA, 1971, FIRE NO ENV, P179 REED WJ, 2002, ECOL MODEL, V150, P239 RICOTTA C, 1999, ECOL MODEL, V119, P73 RICOTTA C, 2001, ECOL MODEL, V141, P307 ROTHERMEL RC, 1972, INT115 USDA FOR SERV ROTHERMEL RC, 1983, INT143 USDA FOR SERV ROUSSEAU R, 1999, ENVIRON ECOL STAT, V6, P211 ROWE JS, 1973, QUATERNARY RES, V3, P444 SALVADOR R, 2000, INT J REMOTE SENS, V21, P655 STRAUSS D, 1989, FOREST SCI, V35, P319 TERRADAS J, 1996, ECOLOGIA FOC, P63 TRABAUD L, 1992, FEUX FORET, P278 TRABAUD L, 1994, ROLE FIRE MEDITERRAN, P1 VANWAGNER CE, 1983, ROLE FIRE NO CIRCUMP, P65 WEINER J, 1986, OIKOS, V47, P211 WELLS ML, 1990, P GIS 90 S GIS 90 LO, P87 WHELAN RJ, 1995, ECOLOGY FIRE ZASADA J, 1971, FIR NO ENV S PAC NW, P231 ZEDLER PH, 1983, ECOLOGY, V64, P809 0921-2973 Landsc. Ecol.ISI:000226384000003Autonomous Univ Barcelona, CREAF, E-08193 Barcelona, Spain. Dept Geog, Barcelona 08193, Spain. Diaz-Delgado, R, Autonomous Univ Barcelona, CREAF, E-08193 Barcelona, Spain. rdiaz@ebd.csic.esEnglish<7b diCastri, F.1997AEditorial: Landscape ecology in a changing globalized environment3-5Landscape Ecology121Editorial MaterialFeb://A1997XQ44800001 HISI Document Delivery No.: XQ448 Times Cited: 5 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1997XQ44800001OdiCastri, F, CNRS,CTR ECOL FONCT & EVOLUT,BP 5051,F-34033 MONTPELLIER 1,FRANCE.English<7XPDickson, B. G. Prather, J. W. Xu, Y. G. Hampton, H. M. Aumack, E. N. Sisk, T. D.2006IMapping the probability of large fire occurrence in northern Arizona, USA747-761Landscape Ecology215fire risk; lightning; ponderosa pine; topographic roughness; weights of evidence; wildland fire UNITED-STATES; LANDSCAPE STRUCTURE; AMERICAN SOUTHWEST; FOREST ECOSYSTEMS; WILDFIRE; MANAGEMENT; MOUNTAINS; REGIMES; ROADS; RESTORATIONArticleJulIn the southwestern U.S., wildland fire frequency and area burned have steadily increased in recent decades, a pattern attributable to multiple ignition sources. To examine contributing landscape factors and patterns related to the occurrence of large (>= 20 ha in extent) fires in the forested region of northern Arizona, we assembled a database of lightning- and human-caused fires for the period 1 April to 30 September, 1986-2000. At the landscape scale, we used a weights-of-evidence approach to model and map the probability of occurrence based on all fire types (n = 203), and lightning-caused fires alone (n = 136). In total, large fires burned 101,571 ha on our study area. Fires due to lightning were more frequent and extensive than those caused by humans, although human-caused fires burned large areas during the period of our analysis. For all fires, probability of occurrence was greatest in areas of high topographic roughness and lower road density. Ponderosa pine (Pinus ponderosa)-dominated forest vegetation and mean annual precipitation were less important predictors. Our modeling results indicate that seasonal large fire events are a consequence of non-random patterns of occurrence, and that patterns generated by these events may affect the regional fire regime more extensively than previously thought. Identifying the factors that influence large fires will improve our ability to target resource protection efforts and manage fire risk at the landscape scale.://000240500100010 p ISI Document Delivery No.: 083ZE Times Cited: 0 Cited Reference Count: 61 Cited References: *USDA, 1999, NAT FIR OCC DAT 1986 *USDA, 2000, NAT FIR PLAN MAN IMP AGEE JK, 1998, NW SCI, V72, P24 AGTERBERG FP, 1989, SCIENCE, V245, P76 AGTERBERG FP, 2002, NAT RESOUR RES, V11, P249 ALLEN CD, 2002, ECOL APPL, V12, P1418 ALLEN CD, 2002, FIRE NATIVE PEOPLES, P143 ATTIWILL PM, 1994, FOREST ECOL MANAG, V63, P247 BAILEY TC, 1995, INTERACTIVE SPATIAL BONHAMCARTER GF, 1989, STAT APPL EARTH SCI, P171 BROWN RT, 2004, CONSERV BIOL, V18, P903 BRUNSON MW, 2004, SOC NATUR RESOUR, V17, P661 CARDILLE JA, 2001, ECOL APPL, V11, P111 CASE P, 2000, MAPPING WILDFIRE HAZ, P159 CHOU YH, 1993, ENVIRON MANAGE, V17, P129 CLARK PJ, 1954, ECOLOGY, V35, P445 COVINGTON WW, 1994, J FOREST, V92, P39 COVINGTON WW, 1997, J FOREST, V95, P23 COVINGTON WW, 2000, NATURE, V408, P135 DAHMS CW, 1997, RMGTR295 DALE VH, 2001, BIOSCIENCE, V51, P723 DAVIS JB, 1990, J FOREST, V88, P26 DEBANO LF, 1998, FIRES EFFECTS ECOSYS DELLASALA DA, 2001, FIRE MANAGEMENT TODA, V61, P12 DEVASCONCELOS MJP, 2001, PHOTOGRAMM ENG REM S, V67, P73 DIAZAVALOS C, 2001, CAN J FOREST RES, V31, P1579 DOMBECK MP, 2004, CONSERV BIOL, V18, P883 FORMAN RTT, 2000, CONSERV BIOL, V14, P31 FULE PZ, 2003, INT J WILDLAND FIRE, V12, P129 GELBARD JL, 2003, CONSERV BIOL, V17, P420 GOSZ JR, 1995, ECOL APPL, V5, P1141 GRAHAM RT, 2004, RMRSGTR120 USDA FOR GRIGAL DF, 2000, FOREST ECOL MANAG, V138, P167 GRISSINOMAYER HD, 2000, HOLOCENE, V10, P213 GUYETTE RP, 2000, P WORKSH FIR PEOPL C, P28 HEYERDAHL EK, 2001, ECOLOGY, V82, P660 KEELEY JE, 2001, CONSERV BIOL, V15, P1536 KEMP LD, 2001, ARC SDM ARCVIEEW EXT LYFORD ME, 2003, ECOL MONOGR, V73, P567 MALAMUD BD, 2005, P NATL ACAD SCI USA, V102, P4694 MCGARIGAL K, 2001, LANDSCAPE ECOL, V16, P327 MCKENZIE D, 2004, CONSERV BIOL, V18, P890 MENSING SA, 2000, WEST N AM NATURALIST, V60, P111 NEUENSCHWANDER LF, 2000, MAPPING WILDFIRE HAZ, P35 PODUR J, 2003, ECOL MODEL, V164, P1 PREISLER HK, 2004, INT J WILDLAND FIRE, V13, P133 PRESTEMON JP, 2002, FOREST SCI, V48, P685 RAINES GL, 2002, NAT RESOUR RES, V11, P241 REED RA, 1996, CONSERV BIOL, V10, P1098 SACKETT SS, 1996, USDA ROCKY, V289, P187 SISK TD, IN PRESS LANDSCAPE U SPIEGELHALTER DJ, 1986, STAT MED, V5, P421 SWETNAM TW, 1990, P S EFF FIR MAN SW N SWETNAM TW, 1990, SCIENCE, V249, P1017 SWETNAM TW, 1994, FIRE EFFECTS SW FORE, P11 SWETNAM TW, 1998, J CLIMATE, V11, P3128 THORNTON PE, 1997, J HYDROL, V190, P214 VANKAT JL, 1985, P S WORKSH WILD FIR, P408 VANWAGTENDONK JW, 1991, P 11 C FIR FOR MET A, P605 WEATHERSPOON CP, 1996, SIERRA NEVADA ECOSYS, V2, P1167 WHELAN RJ, 1995, ECOLOGY FIRE 0921-2973 Landsc. Ecol.ISI:000240500100010iColorado State Univ, Dept Fishery & Wildlife Biol, Ft Collins, CO 80523 USA. USDA, US Forest Serv, Rocky Mt Res Stn, Flagstaff, AZ 86001 USA. No Arizona Univ, Ctr Environm Sci & Educ, Lab Landscape Ecol & Conservat Biol, Flagstaff, AZ 86011 USA. Dickson, BG, Colorado State Univ, Dept Fishery & Wildlife Biol, Ft Collins, CO 80523 USA. dickson@cnr.colostate.eduEnglish S|?"Dickson, Brett G. Sisk, Thomas D. Sesnie, Steven E. Reynolds, Richard T. Rosenstock, Steven S. Vojta, Christina D. Ingraldi, Michael F. Rundall, Jill M.2014Integrating single-species management and landscape conservation using regional habitat occurrence models: the northern goshawk in the Southwest, USA803-815Landscape Ecology295MaykConservation planners and land managers are often confronted with scale-associated challenges when assessing the relationship between land management objectives and species conservation. Conservation of individual species typically involves site-level analyses of habitat, whereas land management focuses on larger spatial extents. New models are needed to more explicitly integrate species-specific conservation with landscape or regional scales. We address this challenge with an example using the northern goshawk (Accipiter gentilis), a forest raptor with circumpolar distribution that is the focus of intense debate regarding forest management on public lands in the southwestern USA. To address goshawk-specific habitat conservation across a management area of 22,800-km(2) in northern Arizona, we focused on the territory scale rather than individual nest sites. We compiled a 17-year database of 895 nest sites to estimate territory locations. We then estimated the likelihood of territory occurrence for the entire management area using multiple logistic regression within an expert-driven, spatially balanced, and information-theoretic framework. Our occurrence model incorporated forest structure variables that were derived from USFS Forest Inventory and Analysis plots and high-resolution satellite imagery. Results indicated that high canopy-bulk density, intermediate canopy-base heights, and low variation in tree density were strong predictors of territory occurrence. We used model-averaged parameter estimates for these variables to map and explore patterns of territory distribution across multiple land jurisdictions and ecological subregions. Our iterative modeling approach complements previous demographic studies in the region. It also provides a robust framework for integrating species conservation and landscape management in ongoing and future regional planning efforts.!://WOS:000334689900004Times Cited: 0 0921-2973WOS:00033468990000410.1007/s10980-014-0013-3 <7E RDiefenderfer, H. L. Johnson, G. E. Skalski, J. R. Breithaupt, S. A. Coleman, A. M.2012^Application of the diminishing returns concept in the hydroecologic restoration of riverscapes671-682Landscape Ecology275Tcumulative effects dike breach law of the diminishing increment law of diminishing returns fish hydrodynamics nonlinear dynamics planning restoration juvenile salmon spatial scale restored estuarine wetland juvenile chinook salmon columbia river-basin forested wetlands conservation floodplains ecosystems biodiversity landscapes principlesMay Increasing our knowledge of unplanned anthropogenic synergies, which have affected ecosystems since prehistory, may facilitate ecological restoration. Predictive relationships between spatial pattern and ecosystem processes and functions in riverscapes have the potential to inform applied ecosystem restoration planning and design, where principles are needed for large-scale river reconnections. Although synergistic, additive, and antagonistic interactions affect ecosystems, the role of such interactions in restoration rarely has been evaluated. Using hydrodynamic modeling, we experimentally examine the aggregate effects of reestablishing hydrologic connections in a tidal freshwater tributary on the floodplain of the Columbia River, USA, which is currently undergoing dike breaching to restore juvenile salmon habitat. Sets of dike breaches yielded average wetted floodplain areas conforming to a two-parameter hyperbola (r (2) = 0.93). These findings demonstrate that the yield of inundated floodplain habitat area from dike breaching can conform to the well-established "law of the diminishing increment," developed in the study of agriculture and economics. Furthermore, the influence of spatial configuration on yield was strong, with midstream breaches yielding 63% and upstream breaches 2% of the wetted area produced by downstream breaches, although conditions of extreme high river flow were not studied. Opening the dike at 26% of the historically present channel outlets provided the maximum return on investment for the study riverscape. Verification of this relationship elsewhere in tidal areas of the Columbia River and on other large river floodplains would contribute to cost-benefit analyses in ecological restoration program planning and have implications for effects on biota.://000303056100005-929JC Times Cited:0 Cited References Count:62 0921-2973Landscape EcolISI:000303056100005Diefenderfer, HL Pacific NW Natl Lab, Marine Sci Lab, 1529 W Sequim Bay Rd, Sequim, WA 98382 USA Pacific NW Natl Lab, Marine Sci Lab, 1529 W Sequim Bay Rd, Sequim, WA 98382 USA Pacific NW Natl Lab, Marine Sci Lab, Sequim, WA 98382 USA Pacific NW Natl Lab, Portland, OR 97204 USA Univ Washington, Sch Aquat & Fisheries Sci, Columbia Basin Res, Seattle, WA 98101 USA Pacific NW Natl Lab, Seattle, WA 98109 USA Pacific NW Natl Lab, Richland, WA 99354 USADOI 10.1007/s10980-012-9713-8Englisht|?, Diekotter, T. Baveco, H. Arens, P. Rothenbuhler, C. Billeter, R. Csencsics, D. De Filippi, R. Hendrickx, F. Speelmans, M. Opdam, P. Smulders, M. J. M.2010Patterns of habitat occupancy, genetic variation and predicted movement of a flightless bush cricket, Pholidoptera griseoaptera, in an agricultural mosaic landscape449-461Landscape Ecology253Habitat fragmentation has been generally regarded detrimental to the persistence of many species, especially those with limited dispersal abilities. Yet, when exactly habitat elements become functionally disconnected very much depends on the dispersal ability of a species in combination with the landscape's composition in which it occurs. Surprisingly, for many small and ground-walking generalists knowledge at what spatial scale and to what extent landscape structure affects dispersal is very scarce. Because it is flightless, the bush cricket Pholidoptera griseoaptera may be regarded susceptible to fragmentation. We applied habitat occupancy surveys, population genetic analyses and movement modelling to investigate the performance of P. griseoaptera in an agricultural mosaic landscape with suitable habitat patches of varying size and isolation. Despite its presumed dispersal limitation we could show that P. griseoaptera occupied the majority of suitable habitats, including small and isolated patches, showed a very low and non-significant genetic differentiation (F (ST) = 0.0072) and, in the model, managed to colonize around 73% of all suitable habitat patches within one generation under weak and strong landscape-effect scenarios. We conclude that P. griseoaptera possesses the behavioural attributes (frequent inter-patch dispersal) necessary to persist in this landscape characterized by a patchy distribution of habitat elements. Yet, sound recommendations to landscape planning and conservation require more research to determine whether this represents a general behaviour of the species or a behavioural adaptation to this particular landscape.!://WOS:000275122600010Times Cited: 0 0921-2973WOS:00027512260001010.1007/s10980-009-9428-7?%%Krzysztof Dmowski Michal Kozakiewicz1990UInfluence of a shrub corridor on movements of passerine birds to a lake littoral zone99-108Landscape Ecology42/3]habitat mosaic, ecological corridor, landscape configuration, connectivity, landscape ecologyA pine forest was separated from a lake littoral zone by a meadow on one area (discontinuous) while these habitats were separated by a shrub strip in another area (continuous). This shrub strip acted as an ecological corridor enhancing the movements of birds between the forest and the littoral reed zone. The number of individuals of non-littoral species that visited the reed zone was higher (p < .001) on the area with the connecting shrub strip in autumn but the number of species visiting the littoral zone was not significantly higher. Significantly more (p < .001) autumn movements by birds in the continuous area were oriented along paths between the forest and the littoral zone whereas movements in the discontinuous area paralleled the littoral and forest zones (p < .001). Movements of birds were concentrated along the edge of the shrub strip. The spatial configuration of the landscape facilitated access by some forest birds to the littoral habitat.*}?Domon, G. Bouchard, A.2007The landscape history of Godmanchester (Quebec, Canada): two centuries of shifting relationships between anthropic and biophysical factors 1201-1214Landscape Ecology228Oct://000248941900007 0921-2973ISI:000248941900007~?(Donner, D. M. Probst, J. R. Ribic, C. A.2008kInfluence of habitat amount, arrangement, and use on population trend estimates of male Kirtland's warblers467-480Landscape Ecology234Kirtland's warblers (Dendroica kirtlandii) persist in a naturally patchy environment of young, regenerating jack pine forests (i.e., 5-23 years old) created after wildfires and human logging activities. We examined how changing landscape structure from 26 years of forest management and wildfire disturbances influenced population size and spatial dispersion of male Kirtland's warblers within their restricted breeding range in northern Lower Michigan, USA. The male Kirtland's warbler population was six times larger in 2004 (1,322) compared to 1979 (205); the change was nonlinear with 1987 and 1994 identified as significant points of change. In 1987, the population trend began increasing after a slowly declining trend prior to 1987, and the rate of increase appeared to slow after 1994. Total amount of suitable habitat and the relative area of wildfire-regenerated habitat were the most important factors explaining population trend. Suitable habitat increased 149% primarily due to increasing plantations from forest management. The relative amount and location of wildfire-regenerated habitat modified the distribution of males among various habitat types, and the spatial variation in their abundance across the primary breeding range. These findings indicate that the Kirtland's warbler male population shifted its use of habitat types temporally and spatially as the population increased and as the relative availability of habitats changed through time. We demonstrate that researchers and managers need to consider not only habitat quality, but the temporal and the spatial context of habitat availability and population levels when making habitat restoration decisions."://WOS:000254250400009 Times Cited: 0WOS:000254250400009(10.1007/s10980-008-9208-9|ISSN 0921-2973|?OlDonoso, Pablo J. Frene, Cristian Flores, Marco Moorman, Michelle C. Oyarzun, Carlos E. Zavaleta, Jennifer C.2014Balancing water supply and old-growth forest conservation in the lowlands of south-central Chile through adaptive co-management245-260Landscape Ecology292FebEcosystem management is a conservation strategy, but there is not a standard protocol for implementation. In theory, ecosystem management will utilize the best available science to sustain social-ecological systems in the landscape by maximizing multiple ecosystem services expected from the stake-holders' of those systems. Llancahue is a watershed (1,270 ha) that provides fresh water to the city of Valdivia (130,000 inhabitants) and protects[ 700 ha of old-growth forest within a severely disturbed landscape in the lowlands of south-central Chile. The native vegetation of this landscape is the threatened Valdivian Temperate Rainforests. Management of the watershed by the Universidad Austral de Chile needs to both provide timber and work to the neighboring campesinos (small poor rural land owners) who were illegally logging the forest and improve the conservation of the old-growth forests and the quantity and quality of water provided by the watershed. This paper demonstrates how adaptive management has utilized a multi-step process to improve management of the watershed. This process has included (1) understanding stakeholders' views towards the project, (2) developing an ecosystem management plan for the watershed that balanced multiple societal demands and ecosystem functions from the watershed, and (3) monitoring the Llancahue forest and streams to ensure activities provided desired results. This paper reports results after 4 years of implementation and provides perspectives on the ecosystem management approach.!://WOS:000331935100006Times Cited: 1 0921-2973WOS:00033193510000610.1007/s10980-013-9969-7<7 Dorner, B. Lertzman, K. Fall, J.2002[Landscape pattern in topographically complex landscapes: issues and techniques for analysis729-743Landscape Ecology178GIS landscape management landscape metrics raster analysis spatial statistics topography GLACIER-NATIONAL-PARK PACIFIC-NORTHWEST SPATIAL PATTERNS ALPINE TREELINE DISTURBANCE MANAGEMENT FORESTS LANDFORMS DYNAMICS MONTANAArticleDecEcological research provides ample evidence that topography can exert a significant influence on the processes shaping broad-scale landscape vegetation patterns. Studies that ignore this influence run the risk of misinterpreting observations and making inappropriate recommendations to the management community. Unfortunately, the standard methods for landscape pattern analysis are not designed to include topography as a pattern-shaping factor. In this paper, we present a set of techniques designed to incorporate the topographic mosaic into analyses of landscape pattern and dynamics. This toolbox includes adjustments to 'classic' landscape indices that account for non-uniform landscape topography, indices that capture associations and directionality in vegetation pattern due to topographic structure, and the application of statistical models to describe relationships between topographic characteristics and vegetation pattern. To illustrate these methods, we draw on examples from our own analysis of landscape pattern dynamics in logged and unlogged forest landscapes in southwestern British Columbia. These examples also serve to illustrate the importance of considering topography in both research and management applications.://000181767400005 D ISI Document Delivery No.: 659FV Times Cited: 12 Cited Reference Count: 60 Cited References: *FOR EC MAN ASS TE, 1993, FOR EC MAN EC EC SOC *STAT SCI INC, 1993, SPLUS WIND US MAN VE ALLEN TR, 1996, PHOTOGRAMM ENG REM S, V62, P1261 ATTIWILL PM, 1994, FOREST ECOL MANAG, V63, P247 BAKER WI, 1994, CONSERV BIOL, V8, P763 BAKER WL, 1992, LANDSCAPE ECOL, V7, P291 BUTLER DR, 1994, PJHYS GEOGR, V15, P166 CISSEL JH, 1994, J FOREST, V92, P30 CISSEL JH, 1994, J FOREST, V92, P46 CISSEL JH, 1999, ECOL APPL, V9, P1217 COSTELLO JD, 1995, BIOSCIENCE, V45, P16 CRIST EP, 1984, PHOTOGRAMM ENG REM S, V50, P343 DORNER B, 2002, THESIS S FRASER U BU FLORINSKY IV, 1998, PROG PHYS GEOG, V22, P33 GARDNER RH, 1991, QUANTITATIVE METHODS, P289 HADLEY KS, 1994, B TORREY BOT CLUB, V121, P47 HESSBURG PF, 1999, ECOL APPL, V9, P1232 JENKINS SH, 1979, OECOLOGIA BERL, V44, P112 JENSEN ME, 1993, EASTSIDE FOREST ECOS KEDDY PA, 1991, ECOLOGICAL HETEROGEN, P181 KNIGHT DH, 1987, LANDSCAPE HETEROGENE, P59 KOLASA J, 1991, ECOLOGICAL HETEROGEN, P1 KRAMER MG, 2001, ECOLOGY, V82, P2749 LANDRES PB, 1998, WILDERNESS NATURAL A, P41 LANDRES PB, 1999, ECOL APPL, V9, P1179 LEDUC A, 1992, J VEG SCI, V3, P69 LEGENDRE P, 1989, VEGETATIO, V80, P107 LEHMKUHL JF, 1991, PNWGTR285 USDA FOR S LEHMKUHL JF, 1994, PNWGTR328 USDA FOR S LERTZMAN KP, 1997, RAINFORESTS HOME PRO, P361 MCGARIGAL K, 1994, FRAGSTATS SPATIAL PA MCNAB WH, 1989, FOREST SCI, V35, P91 MLADENOFF DJ, 1994, CONSERV BIOL, V8, P752 MONTGOMERY DR, 1999, J WATER RESOURCES AS, V35, P1 MOORE ID, 1993, J HYDROL, V150, P717 MORGAN P, 1994, J SUSTAINABLE FOREST, V2, P87 OHMANN JL, 1998, ECOL MONOGR, V68, P151 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PASTOR J, 1990, LANDSCAPE ECOL, V4, P55 PIKE RJ, 2000, PROG PHYS GEOG, V24, P1 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 RIPPLE WJ, 1994, J FOREST, V92, P45 ROMME WH, 1981, ECOLOGY, V62, P319 ROSSI RE, 1992, ECOL MONOGR, V62, P277 SWANSON FJ, 1988, BIOSCIENCE, V38, P92 SWANSON FJ, 1992, LANDSCAPE BOUNDARIES, P304 SWANSON FJ, 1993, PNWGTR318 USDA FOR S TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1991, QUANTITATIVE METHODS, P324 TURNER SJ, 1991, QUANTITATIVE METHODS, P536 URBAN DL, 1987, BIOSCIENCE, V37, P119 VEBLEN TT, 1996, HIGH LATITUDE RAINFO, P173 VOLLER J, 1998, CONSERVATION BIOL PR WALLIN DO, 1996, FOREST ECOL MANAG, V85, P291 WALSH SJ, 1990, PHOTOGRAMM ENG REM S, V56, P615 WALSH SJ, 1994, J VEG SCI, V5, P657 WESTERVELT J, 1991, N8722 USACERL ADP WIENS JA, 1985, ECOLOGY NATURAL DIST, P169 WONDZELL SM, 1996, LANDSCAPE ECOL, V11, P351 ZHANG QF, 1999, CAN J FOREST RES, V29, P106 0921-2973 Landsc. Ecol.ISI:000181767400005Simon Fraser Univ, Sch Resource & Environm Management, Burnaby, BC V5A 1S6, Canada. Dorner, B, Simon Fraser Univ, Sch Resource & Environm Management, Burnaby, BC V5A 1S6, Canada. bdorner@sfu.caEnglishs?BD. van Dorp P.F.M. Opdam1987REffects of patch size, isolation and regional abundance on forest bird communities59-73Landscape Ecology11Abirds, patch, rural landscape, forest fragmentation, connectivity@The aim of this study was to assess the impact of isolation on forest bird communities in agricultural landscapes in The Netherlands. We studied the avifauna of 235 small (0.1-39 ha) woodlots composed of mature deciduous trees in 1984- 1985. These woodlots were selected in the eastern and central/southern part of the country within 22 regions showing great differences in landscape structure, i.e., degree of isolation. Multiple regression analysis indicated that woodlot size was the best single predictor of species number and probability of occurrence of most species. It turned out that the isolation variables, area of wood, number of woods, interpatch distance, and proximity and density of connecting elements, explained small but significant parts of the residual variances in species number. No single species was significantly affected by the density of connecting elements. Biogeographical differences between two groups of regions were emphasized. Evidence of four woodland- species suggested that regional abundance affected the probability of occurrence in small isolates.L|?|Dorresteijn, Ine Hanspach, Jan Kecskes, Attila Latkova, Hana Mezey, Zsofia Sugar, Szilard von Wehrden, Henrik Fischer, Joern2014<Human-carnivore coexistence in a traditional rural landscape 1145-1155Landscape Ecology297AugFacilitating human-carnivore coexistence is a major conservation concern in human-dominated landscapes worldwide. Useful insights could be gained by studying and understanding the dynamics of human-carnivore coexistence in landscapes in which carnivores and humans have coexisted for a long time. We used a two-pronged approach combining ecological and social data to study coexistence of the brown bear (Ursus arctos) and humans in Transylvania, Romania. First, we surveyed 554 km of walking transects to estimate activity via a bear sign index, namely the proportion of anthills disturbed by bears, and used spatially explicit predictive models to test which biophysical and anthropogenic variables influenced bear activity. Second, we interviewed 86 shepherds and 359 villagers and community representatives to assess conflicts with bears and attitudes of shepherds towards bears. Our interdisciplinary study showed that bears and humans coexisted relatively peacefully despite occasional conflicts. Coexistence appeared to be facilitated by: (1) the availability of large forest blocks that are connected to the source population of bears in the Carpathian Mountains; (2) the use of traditional livestock management to minimize damage from bears; and (3) some tolerance among shepherds to occasional conflict with bears. In contrast, bear activity was unrelated to human settlements, and compensation for livestock losses did not influence people's attitudes toward bears. Our study shows that coexistence of humans and carnivores is possible, even without direct economic incentives. A key challenge for settings with a discontinuous history of human-carnivore coexistence is to reinstate both practices and attitudes that facilitate coexistence.!://WOS:000339831300005Times Cited: 1 0921-2973WOS:00033983130000510.1007/s10980-014-0048-5?Douglas, M. Johnston20035Book review, Landscape Erosion and Evolution Modeling210-211Landscape Ecology182 book review\This revised version was published online in August 2006 with corrections to the Cover Date.*http://dx.doi.org/10.1023/A:1024419906372 F10.1023/A:1024419906372 Douglas M. Johnston Email: dmjohnst@uiuc.edu Douglas M. Johnston1 (1) Department of Landscape Architecture, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA ڽ7 #Dramstad, WencheE Fjellstad, WendyJ2013VTwenty-five years into “our common future”: are we heading in the right direction? 1039-1045Landscape Ecology286Springer NetherlandsESustainable development Landscape services Adaptive management Norway 2013/07/01+http://dx.doi.org/10.1007/s10980-012-9740-5 0921-2973Landscape Ecol10.1007/s10980-012-9740-5English<7eDrew, C. A. Eggleston, D. B.2006`Currents, landscape structure, and recruitment success along a passive-active dispersal gradient917-931Landscape Ecology216cellular model; dispersal strategy; habitat shifts; hydrodynamic currents; recruitment success ONTOGENIC HABITAT SHIFTS; REEF FISH; PATCHY LANDSCAPE; MARINE RESERVES; CONNECTIVITY; CONSERVATION; POPULATIONS; ESTUARINE; MOVEMENT; BEHAVIORArticleAugThere exists a gradient in dispersal behavior from passive to active, which reflects organisms' dependence upon currents vs. self-propelled movement. We asked: Do currents modify organism-landscape interactions to influence recruitment success along this dispersal gradient? Using a spatially-explicit cellular model, we simulated the recruitment success of three generalized dispersal strategies (walkers, swimmers, and drifters) through hierarchically structured benthic landscapes. We evaluated the relative recruitment success (recruited population size, overall area occupied, time to recruit) of the three dispersal strategies in similar landscapes, as well as the consequences of varying the total proportion of habitat suitable for recruitment, and the scale and pattern of habitat patchiness on recruitment success. In the presence of currents, swimmers and drifters generally recruited over larger areas and in less time than walkers. Differences among the dispersal strategies' recruitment success were most pronounced when an intermediate number of good habitat cells (16-48% of landscape) were broadly dispersed across the landscape. Although recruitment success always increased with increasing proportion of good habitat, drifters were more sensitive, and swimmers less sensitive, to these landscape changes than walkers. We also found that organisms dispersing within currents typically responded non-linearly (logarithmically or exponentially) to increasing proportion of total good habitat, whereas walkers more often responded linearly.://000239484200011 ISI Document Delivery No.: 069YA Times Cited: 0 Cited Reference Count: 59 Cited References: ACOSTA CA, 1999, CONSERV BIOL, V13, P603 AKAIKE H, 1973, P 2 INT S INF THEOR, P267 ARMSWORTH PR, 2001, AM NAT, V157, P434 BECK MW, 2001, BIOSCIENCE, V51, P633 BOTSFORD LW, 2001, ECOL LETT, V4, P144 CABEZA M, 2003, CONSERV BIOL, V17, P1402 CARR MH, 2003, ECOL APPL S, V13, S90 COWEN RK, 2000, SCIENCE, V287, P857 DAHLGREN CP, 2000, ECOLOGY, V81, P2227 DARCY MC, 2005, LANDSCAPE ECOL, V20, P841 EGGLESTON DB, 1995, MAR ECOL-PROG SER, V124, P9 ELLIOTT JM, 2003, FRESHWATER BIOL, V48, P1652 FAHRIG L, 1985, ECOLOGY, V66, P1762 FAHRIG L, 1988, APPL MATH COMPUT, V27, P53 FAHRIG L, 1988, ECOLOGY, V69, P468 FIRLE S, 1998, ECOLOGY, V79, P2113 FORWARD RB, 2001, OCEANOGR MAR BIOL, V39, P305 FROESE R, 2003, FISHBASE GLOBAL INFO GAINES SD, 2003, ECOL APPL, V13, P32 GARDNER RH, 1999, LANDSCAPE ECOLOGICAL, P280 GIBSON RN, 2003, HYDROBIOLOGIA, V503, P153 GILLANDERS BM, 2003, MAR ECOL-PROG SER, V247, P281 GOODWIN BJ, 2002, OIKOS, V99, P552 HIEBELER D, 2004, THEOR POPUL BIOL, V66, P205 IRLANDI EA, 1997, OECOLOGIA, V110, P222 IVERSON LR, 2004, LANDSCAPE ECOL, V19, P787 JOHNSON AR, 1992, ECOLOGY, V73, P1968 JONSEN ID, 2001, OECOLOGIA, V127, P287 KING AW, 2002, ECOL MODEL, V147, P23 KINLAN BP, 2003, ECOLOGY, V84, P2007 KOTLIAR NB, 1990, OIKOS, V59, P253 KRAWCHUK MA, 2003, OIKOS, V103, P153 LAMBECK RJ, 1997, CONSERV BIOL, V11, P849 LAVOREL S, 1993, OIKOS, V67, P521 LESLIE H, 2003, ECOL APPL S, V13, S185 LIMA SL, 1996, TRENDS ECOL EVOL, V11, P131 MCCORMICK MI, 1998, AUST J ECOL, V23, P258 MYUNG IJ, 1997, PSYCHON B REV, V4, P79 NATHAN R, 2005, DIVERS DISTRIB, V11, P131 NILSSON C, 2002, ECOLOGY, V83, P2878 OVANKAINEN O, 2002, J THEOR BIOL, V215, P95 ROBERTS CM, 1997, SCIENCE, V278, P1454 RUCKELSHAUS M, 1997, CONSERV BIOL, V11, P1298 RUSSELL RE, 2003, OIKOS, V103, P142 SCHMITT RJ, 2002, MAR FRESHWATER RES, V53, P329 SCHOOLEY RL, 2003, OIKOS, V102, P559 STEIDL RJ, 2001, DESIGN ANAL ECOLOGIC, P14 SUTHERLAND GD, 2000, CONSERV ECOL, V4 TEWKSBURY JJ, 2002, P NATL ACAD SCI USA, V99, P12923 TEWS J, 2004, J BIOGEOGR, V31, P79 THOMAS CFG, 2003, J APPL ECOL, V40, P912 THOMPSON WM, 1977, INVEST RADIOL, V12, P146 TUOMISTO H, 2003, SCIENCE, V299, P241 WITH KA, 1995, ECOLOGY, V76, P2446 WITH KA, 2002, CONSERV BIOL, V16, P1192 WOLANSKI E, 1997, NATURWISSENSCHAFTEN, V84, P262 ZOLLNER PA, 1997, OIKOS, V80, P51 ZOLLNER PA, 1999, ECOLOGY, V80, P1019 ZOLLNER PA, 2005, OIKOS, V108, P219 0921-2973 Landsc. Ecol.ISI:000239484200011N Carolina State Univ, Dept Marine Earth & Atmospher Sci, Raleigh, NC 27695 USA. Drew, CA, N Carolina State Univ, Dept Marine Earth & Atmospher Sci, 2800 Faucette Dr,Rm 1125 Jordan Hall,Campus Box 8, Raleigh, NC 27695 USA. cadrew@unity.ncsu.eduEnglish <7F ,Driscoll, D. A. Whitehead, C. A. Lazzari, J.2012dSpatial dynamics of the knob-tailed gecko Nephrurus stellatus in a fragmented agricultural landscape829-841Landscape Ecology276metacommunity reptile patch-matrix model invasive weeds land clearing incidence function model habitat fragmentation metapopulation dynamics restoration ecology replicated counts patchy population mixture-models climate-change united-states small mammalsJulIn fragmented landscapes, a species' dispersal ability and response to habitat condition are key determinants of persistence. To understand the relative importance of dispersal and condition for survival of Nephrurus stellatus (Gekkonidae) in southern Australia, we surveyed 92 woodland remnants three times. This gecko favours early post-fire succession conditions so may be at risk of extinction in the long-unburnt agricultural landscape. Using N-mixture models, we compared the influence of four measures of isolation, patch area and two habitat variables on the abundance and occurrence of N. stellatus, while taking into account detection probability. Patch occupancy was high, despite the long-term absence of fire from most remnants. Distance to the nearest occupied site was the most informative measure of patch isolation, exhibiting a negative relationship with occupancy. Distance to a nearby conservation park had little influence, suggesting that mainland-island metapopulation dynamics are not important. Abundance and occurrence were positively related to %-cover of spinifex (Triodia), indicating that niche-related factors may also contribute to spatial dynamics. Patterns of patch occupancy imply that N. stellatus has a sequence of spatial dynamics across an isolation gradient, with patchy populations and source-sink dynamics when patches are within 300 m, metapopulations at intermediate isolation, and declining populations when patches are separated by > 1-2 km. Considering the conservation needs of the community, habitat condition and connectivity may need to be improved before fire can be reintroduced to the landscape. We speculate that fire may interact with habitat degradation and isolation, increasing the risk of local extinctions.://000305218000004-958DZ Times Cited:0 Cited References Count:78 0921-2973Landscape EcolISI:000305218000004UDriscoll, DA Australian Natl Univ, Fenner Sch Environm & Soc, GPO Box 4, Canberra, ACT 0200, Australia Australian Natl Univ, Fenner Sch Environm & Soc, GPO Box 4, Canberra, ACT 0200, Australia Australian Natl Univ, Fenner Sch Environm & Soc, Canberra, ACT 0200, Australia Flinders Univ S Australia, Sch Biol Sci, Adelaide, SA 5001, AustraliaDOI 10.1007/s10980-012-9734-3EnglishF|?P $du Toit, Marie J. Cilliers, Sarel S.2011kAspects influencing the selection of representative urbanization measures to quantify urban-rural gradients169-181Landscape Ecology262FebThe quantification of urban-rural gradients using urbanization measures has become standard practice in many urban ecological studies. Nonetheless, the choice of urbanization measures for a specific urban gradient still remains problematic. Increasing numbers of papers stress the importance of comparative urban ecological research, in an attempt to contribute to an understanding of the ecology 'of' cities. This implies that research in diverse urban areas globally should be comparable. This study follows an approach to quantify the urban-rural gradient in Klerksdorp previously followed in Melbourne, Australia with the goal to help elucidate the viability of creating a standard set of urbanization measures that is useful across continents. Satellite imagery and spatial analysis were used to calculate the values of 12 urbanization measures across a 900 km(2) landscape grid. Principal components analysis is commonly used to identify smaller subsets of measures to quantify urban-rural gradients. The results of this study indicate that factor analysis is more suitable than principal components analysis and ideal in identifying these independent measures of urbanization. The factor analysis revealed that landscape structure and demographic attributes are both essential characteristics of a city that needs to be accounted for in the choice of urbanization measures. Additionally, we identified seven aspects influencing the direct comparison of cities, namely: scale of analysis, spatial resolution, classification typology, accuracy of input data, specific measure equations, the type of statistical analysis and the habitat context. These aspects must be taken into consideration and resolved before effective comparative gradient research between cities can be achieved.!://WOS:000286474900002Times Cited: 0 0921-2973WOS:00028647490000210.1007/s10980-010-9560-4|?Duchamp, J. E. Swihart, R. K.2008dShifts in bat community structure related to evolved traits and features of human-altered landscapes849-860Landscape Ecology237Population declines for many bat species are associated with rapid, human-induced ecosystem changes. In this context, the available species pool is determined in part by historical adaptation to the native ecosystem, but the resulting community structure may be determined principally by the ability of evolved traits to function in the novel context of a human-dominated ecosystem. To investigate the role of human disturbance as a determinant of bat communities, we surveyed assemblages and species occurrence rates in 27 agriculturally dominated landscapes exhibiting a gradient of human-induced forest fragmentation in Indiana, USA. We used multiple linear regression to explore the relationship of landscape environmental variables to species diversity. We then examined the relationship between community structure, evolved species traits and fragmentation conditions across a landscape using RLQ analysis. Overall, species diversity was positively related to the amount of forest and negatively correlated with amount of urban development in a landscape. We also observed a significant relationship between evolved species traits and landscape-level variables that is consistent with globally anticipated trends for bat species extinction risk. Our findings suggest that responses of bat species to human modification of ecosystems on the scale of a few kilometers could drive distributional dynamics at larger spatial and longer temporal scales.!://WOS:000258540300007Times Cited: 0 0921-2973WOS:00025854030000710.1007/s10980-008-9241-8 =07 kDuff, G. Garnett, D. Jacklyn, P. Landsberg, J. Ludwig, J. Morrison, J. Novelly, P. Walker, D. Whitehead, P.2009A collaborative design to adaptively manage for landscape sustainability in north Australia: lessons from a decade of cooperative research 1135-1143Landscape Ecology24SpringerJCsiro, Atherton Qld Australia Charles Darwin Univ, Tscrc Darwin N. T. Australia Queensland Dept Primary, Ind Fisheries, Mareeba Qld Australia Charles Darwin Univ, N. Australia Indigenous Land Sea Management Alli, Darwin N. T. Australia Western Australia Dept, Agr Food, Kununurra W. A. Australia Csiro, Canberra A. C. T. AustraliaJCollaboration Communication Integration Natural resources Savannas TropicsOctApproaches to manage for the sustainable use of natural and cultural resources in a landscape can have many different designs. One design is adaptive collaborative landscape management (ACLM) where research providers and users work closely together on projects to develop resources while adaptively managing to sustain or maintain landscapes in the long term. We propose that collaborative projects are more useful for achieving outcomes than integrative projects where participants merely join their separate contributions. To foster collaborative research projects to adaptively manage landscapes in northern Australia, a Tropical Savannas Cooperative Research Centre (TSCRC) was established in 1995. The TSCRC is a joint venture of major organizations involved in research and land management. This paper is our perspective on the four most important 'lessons learned' after using a ACLM-type approach for over 10 y. We learnt that collaboration (working in combination) not necessarily integration (combining parts into a whole) achieved sustainable outcomes. We found that integration across culturally diverse perspectives seldom achieved sustainable solutions because it devalued the position of the less empowered participants. In addition, positive outcomes were achieved when participants developed trust and respect for each other by embracing and respecting their differences and by sharing unifying concepts such as savanna health. Another lesson learned was that a collaborative organization must act as an honest broker by resisting advocacy of one view point over another. Finally, we recognized the importance of strongly investing in communication and networking so that people could adaptively learn from one another's experiences, understand each other's challenges and respect each other's choices. Our experience confirms the usefulness of the ACLM approach and highlights its role in the process of sustaining healthy landscapes.://000269913600011ISI Document Delivery No.: 495RV Times Cited: 1 Cited Reference Count: 32 Duff, Gordon Garnett, David Jacklyn, Peter Landsberg, Jill Ludwig, John Morrison, Joe Novelly, Paul Walker, Dan Whitehead, Peter 0921-2973 DORDRECHT2009 Landsc. Ecol.ISI:000269913600011Landscape ecologyNLudwig, J, CSIRO, POB 780, Atherton, Qld 4883, Australia. john.ludwig@csiro.au10.1007/s10980-008-9236-5English'? /Duggan, Jennifer Schooley, Robert Heske, Edward2011Modeling occupancy dynamics of a rare species, Franklin’s ground squirrel, with limited data: are simple connectivity metrics adequate? 1477-1490Landscape Ecology2610Springer NetherlandsEarth and Environmental ScienceConservation of populations in fragmented habitats is often based on spatially realistic metapopulation theory, which predicts negative relationships between patch extinction and area and patch colonization and isolation. Cost-distance metrics have been developed to integrate habitat quality into measures of connectivity, and thus may improve predictive power of the area-isolation paradigm. Few studies use empirical data to compare predictive performance of complex cost-distance metrics to simple metrics relying on Euclidean distances. We used 3 years of presence–absence data to examine relative influence of habitat quality, habitat area, and connectivity on occupancy and extinction rates for Poliocitellus franklinii (Franklin’s ground squirrel), a rare grassland species of conservation concern. We calculated connectivity using nearest-neighbor (NN) and incidence function model (IFM) metrics based on Euclidean and cost-distances. Habitat quality, area, and connectivity were all positive predictors for occupancy, but only isolation was a positive predictor of extinction. P. franklinii does not appear to be a tallgrass prairie obligate, but the species distribution is limited by isolation of suitable grassland habitat. A simple NN metric measuring Euclidean distance between a target area and nearest occupied source outperformed IFM (Euclidean and cost-distance) in predicting occupancy and extinction for P. franklinii. Although NN metrics are criticized for considering only the contribution of the source nearest to a target, this simplicity may be acceptable when measuring connectivity for rare species with few occupied habitat patches within dispersal distance.+http://dx.doi.org/10.1007/s10980-011-9652-9 0921-297310.1007/s10980-011-9652-9 ?Z0Stéphanie Duguay Felix Eigenbrod Lenore Fahrig 2007PEffects of surrounding urbanization on non-native flora in small forest patches 589-599Landscape Ecology224Forest plants - Forest flora - Forest vegetation - Introduced species - Non-native species - Landscape context - Urbanization - Species richness - Forest patch - Forest fragmentation 4The purpose of our study was to compare the number, proportion, and species composition of introduced plant species in forest patches situated within predominantly forested, agricultural, and urban landscapes. A previous study suggested that agricultural landscape context does not have a large effect on the proportion of introduced species in forest patches. Therefore, our main goal was to test the hypothesis that forest patches in an urban landscape context contain larger numbers and proportions of non-native plant species. We surveyed the vegetation in 44 small remnant forest fragments (3–7.5 ha) in the Ottawa region; 15 were situated within forested landscapes, 18 within agricultural landscapes, and 11 within urban landscapes. Forest fragments in urban landscapes had about 40% more introduced plant species and a 50% greater proportion of introduced plant species than fragments found in the other two types of landscape. There was no significant difference in the number or proportion of introduced species in forest fragments within forested vs. agricultural landscapes. However, the species composition of introduced species differed among the forest patches in the three landscape types. Our results support the hypothesis that urban and suburban areas are important foci for spread of introduced plant species.  :<7/3Duhamel, R. Quere, J. P. Delattre, P. Giraudoux, P.2000rLandscape effects on the population dynamics of the fossorial form of the water vole (Arvicola terrestris sherman)89-98Landscape Ecology152Rmanagement pluriannual fluctuation rodent source-sink space use LAND-USE ABUNDANCEArticleFebThe dynamics of microtine rodents show large variations among species and even among populations of a single species. Several studies have shown that landscape structure and predation play a role in these variations. We studied the influence of landscape structure on the spatial distribution and the population dynamics of the fossorial form of the water vole (Arvicola terrestris sherman). The sampling was based on a preliminary five-year survey of a rodent cycle on a regional scale, as well as a method of abundance estimation using surface indices. This survey led to distinguishing epicentres where outbreaks started, and diffusion sections where outbreaks occurred later. Results showed differences in dynamics of spatial distribution of the vole colonies between these two types of sections. This distribution pattern is related to landscape composition and structure. Epicentres are characterized by a higher ratio of open landscape, a lower ratio of forest, and less fragmentation when compared to the diffusion sections. Therefore landscape analysis has the potential of providing a valuable framework for the designing of programs for the early control of A. terrestris populations.://000084522700002 KISI Document Delivery No.: 270EP Times Cited: 4 Cited Reference Count: 22 Cited References: *AB CONC INC, 1988, STATV SE PLUS GRAPH AIROLDI JP, 1985, DTSCH PFLANZENSCHUTZ, V67, P123 ANDERSSON M, 1977, OIKOS, V29, P591 DELATTRE P, 1986, C NAT CNRS BIOL POP, P537 DELATTRE P, 1988, EPPO B, V18, P415 DELATTRE P, 1992, AGR ECOSYST ENVIRON, V39, P153 DELATTRE P, 1996, LANDSCAPE ECOL, V11, P279 GIRAUDOUX P, 1990, ALAUDA, V58, P17 GIRAUDOUX P, 1995, ACTA THERIOL, V40, P77 GIRAUDOUX P, 1997, AGR ECOSYST ENVIRON, V66, P47 HABERT M, 1987, DEFENSE VEGETAUX, V248, P9 HABERT M, 1988, EPPO B, V3, P423 HANSSON L, 1977, OIKOS, V29, P593 HANSSON L, 1985, OECOLOGIA, V67, P394 KREBS CJ, 1974, ADV ECOL RES, V8, P267 LIDICKER WZ, 1988, J MAMMAL, V69, P225 LIDICKER WZ, 1995, LANDSCAPE APPROACHES MOREL J, 1970, REV SUISSE ZOOL, V77, P705 SCHERRER B, 1984, BIOSTATISTIQUE SIEGEL S, 1988, NONPARAMETRIC STAT B TAITT MJ, 1985, BIOL NEW WORLD MICRO, P567 WEISCHER B, 1985, DTSCH PFLANZENSCHUTZ, V37, P122 0921-2973 Landsc. Ecol.ISI:000084522700002Univ Franche Comte, Lab Biol & Ecophysiol, F-25030 Besancon, France. Giraudoux, P, Univ Franche Comte, Lab Biol & Ecophysiol, F-25030 Besancon, France.English? Dumyahn, Sarah Pijanowski, Bryan2011FBeyond noise mitigation: managing soundscapes as common-pool resources 1311-1326Landscape Ecology269Springer NetherlandsEarth and Environmental ScienceThe extent of noise and its impacts continues to grow globally indicating a different approach from regulating individual noise sources is needed. We pose the argument that soundscapes, or the acoustic environment, should be managed as a common-pool resource (CPR). Using CPR theory, we argue that soundscapes possess key features of CPRs: (1) multiple soundscape users, (2) difficulty of exclusion, and (3) subtractability and degradation. Using Ostrom’s Social-Ecological Systems (SES) framework, we describe the main elements of soundscapes to consider for their sustainable management. In order to assess noise issues and challenges in managing national park soundscapes, we conducted interviews with U.S. National Park Service managers at parks identified as having air tour overflight impacts. While most managers indicated that aircraft overflights posed the most serious impacts to park resources and visitor experiences, the park units also experienced several other types of noise impacts including traffic on park roads, park maintenance operations, and different types of motorized recreational vehicles. Addressing single sources of noise is necessary, as is the case with air tour overflights, but we argue that a more comprehensive approach is needed to protect park soundscapes. From this study several SES framework variables emerged that need to be addressed for sustainable management, such as the lack of clear soundscape boundaries, availability of acoustic monitoring and data, and the number and types of soundscape users. Based on CPR theory and using the SES framework, the challenges and a potential new approach for sustainable management are discussed.+http://dx.doi.org/10.1007/s10980-011-9637-8 0921-297310.1007/s10980-011-9637-8? Dumyahn, Sarah Pijanowski, Bryan2011Soundscape conservation 1327-1344Landscape Ecology269Springer NetherlandsEarth and Environmental ScienceWe argue that soundscapes possess both ecological and social value and that they should be considered natural resources worthy of management and conservation. In this paper we bring together diverse bodies of literature that identify the human and ecological benefits provided by soundscapes. Sense of place, cultural significance, interactions with landscape perceptions, and wildlife wellbeing are a few of the values ascribed to soundscapes. The values and benefits of soundscapes are motivation to advance soundscape conservation and management. Given that soundscape conservation is new, we present a summary of conservation principles that need to be considered in soundscape conservation planning. These include the need to set goals, identify targets, assess condition, identify and manage threats, and conduct monitoring of the soundscape. We also argue that soundscape conservation needs to consider the soundscape within the larger mosaic of the landscape that is occupied by humans—a perspective provided by landscape ecology. We describe several different kinds of soundscapes that need to be conserved, such as natural quiet, sensitive, threatened, and unique soundscapes, and the ways that conservation planning can protect these for the future.+http://dx.doi.org/10.1007/s10980-011-9635-x 0921-297310.1007/s10980-011-9635-x~<7X:Duncan, B. W. Boyle, S. Breininger, D. R. Schmalzer, P. A.1999hCoupling past management practice and historic landscape change on John F. Kennedy Space Center, Florida291-309Landscape Ecology143historic landcover fire suppression landscape management disturbance scrub flatwoods Florida remote sensing GIS GPS LAKE WALES RIDGE VEGETATION FIRE PATTERNS SANDHILL GEORGIAArticleJunHistoric landcover dynamics in a scrubby flatwoods (Tel-4) and scrub landscape (Happy Creek) on John F. Kennedy Space Center were measured using aerial images from 1943, 1951, 1958, 1969, 1979, and 1989. Landcover categories were mapped, digitized, geometrically registered, and overlaid in ARC/INFO. Both study sites have been influenced by various land use histories, including periods of range management, fire suppression, and fire management. Several analyses were performed to help understand the effects of past land management on the amount and spatial distribution of landcover within the study sites. A chi-squared analysis showed a significant difference between the frequency of landcover occurrence and management period. Markov chain models were used to project observed changes over a 100-year period; these showed current management practices being effective at Tel-4 (restoring historic landscape structure) and much less effective at Happy Creek. Documenting impacts of past management regimes on landcover has provided important insight into current landscape composition and will provide the basis for improving land management on Kennedy Space Center and elsewhere.://000081041200007  ISI Document Delivery No.: 209HB Times Cited: 16 Cited Reference Count: 48 Cited References: *ENV SYST RES I IN, 1991, ARC INFO COMM REF US *ENV SYST RES I IN, 1994, INTR ARCV ARCV GEOGR *SPSS INC, 1993, SPSS WIND BAS SYST U *TRIMBL NAV LTD, 1994, PRO XL SYST OP MAN ABRAHAMSON WG, 1984, AM J BOT, V71, P35 ABRAHAMSON WG, 1984, AM J BOT, V71, P9 ABRAHAMSON WG, 1990, ECOSYSTEMS FLORIDA, P103 ADRIAN FW, 1983, UPLAND MANAGEMENT PL AUBREVILLE A, 1938, ANN ACADEMIE SCI COL, V9, P1 BENSON BJ, 1995, LANDSCAPE ECOL, V10, P113 BERGEN S, 1994, THESIS FLORIDA I TEC BOYLE SR, 1996, THESIS FLORIDA I TEC BRATTON SP, 1994, B TORREY BOT CLUB, V121, P1 BREININGER DR, 1990, AM MIDL NAT, V123, P64 BREININGER DR, 1995, CONSERV BIOL, V9, P1442 BREININGER DR, 1996, 111676 NASA JF KENN CALLAWAY RM, 1993, ECOLOGY, V74, P1567 CLEMENTS FE, 1916, CARNEGIE I PUBLICATI, V242 DAUBENMIRE RF, 1968, PLANT COMMUNITIES TX DAVISON KL, 1986, 22 CPSU U GEORG I EC DUNCAN BW, 1995, PHOTOGRAMM ENG REM S, V61, P1361 FERNALD RT, 1989, 6 FLOR GAM FRESHW FI FORMAN RT, 1986, LANDSCAPE ECOLOGY FRELICH LE, 1995, ECOL MONOGR, V65, P325 FROST CC, 1993, P 19 TALL TIMB FIR E, P39 GALLAGHER R, 1997, SCIENCE, V277, P485 GLEASON HA, 1926, B TORREY BOT CLUB, V53, P439 KIENAST F, 1993, LANDSCAPE ECOL, V8, P103 KIRKMAN LK, 1993, P 19 TALL TIMB FIR E, P10 KUSHLAN JA, 1990, ECOSYSTEMS FLORIDA, P324 LARSON RW, 1952, 6 USDA FOR SERV LEE RC, 1981, FIRE MANAGEMENT PLAN MOTZKIN G, 1996, ECOL MONOGR, V66, P345 MYERS RL, 1985, B TORREY BOT CLUB, V112, P241 MYERS RL, 1987, B TORREY BOT CLUB, V114, P21 MYERS RL, 1990, ECOSYSTEMS FLORIDA, P150 NAVEH Z, 1994, LANDSCAPE ECOLOGY TH PERONI PA, 1986, FLORIDA SCI, V49, P176 ROBBINS LE, 1989, SEASONAL EFFECTS PRE SCHMALZER PA, 1992, CASTANEA, V57, P158 SCHMALZER PA, 1992, CASTANEA, V57, P220 SCHMALZER PA, 1994, 109202 NASA JF KENN STITH BM, 1996, METAPOPULATIONS WILD, P187 SWAIN HM, 1995, SCRUB CONSERVATION D TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 TURNER MG, 1990, PHOTOGRAMM ENG REM S, V56, P379 WHITTAKER RH, 1953, ECOL MONOGR, V23, P41 WOOLFENDEN GE, 1984, FLORIDA SCRUB JAY DE 0921-2973 Landsc. Ecol.ISI:000081041200007NASA, Biomed Operat Off, Dynam Corp, Kennedy Space Ctr, FL 32899 USA. Duncan, BW, NASA, Biomed Operat Off, Dynam Corp, Mail Code DYN-2 Kennedy Space Ctr, Kennedy Space Ctr, FL 32899 USA.English-<7 Duncan, B. W. Schmalzer, P. A.2004ZAnthropogenic influences on potential fire spread in a pyrogenic ecosystem of Florida, USA153-165Landscape Ecology192fire modeling; fuel fragmentation; FARSIDE; historic; pyrogenic; Southeast US LAKE WALES RIDGE; VEGETATION; SUPPRESSION; REGIMES; FUELSArticle!Fire has historically been an important ecological factor maintaining southeastern U. S. vegetation. Humans have altered natural fire regimes by fragmenting fuels, introducing exotic species, and suppressing fires. Little is known about how these alterations specifically affect spatial fire extent and pattern. We applied historic (1920 and 1943) and current (1990) GIS fuels maps and the FARSITE fire spread model to quantify the differences between historic and current fire spread distributions. We held all fire modeling variables (wind speed and direction, cloud cover, precipitation, humidity, air temperature, fuel moistures, ignition source and location) constant with exception of the fuel models representing different time periods. Model simulations suggest that fires during the early 1900's burned freely across the landscape, while current fires are much smaller, restricted by anthropogenic influences. Fire extent declined linearly with patch density, and there was a quadratic relationship between fire extent and percent landscape covered by anthropogenic features. We found that as little as 10 percent anthropogenic landcover caused a 50 percent decline in fire extent. Most landscapes (conservation or non-conservation areas) are now influenced by anthropogenic features which disrupt spatial fire behavior disproportionately to their actual size. These results suggest that land managers using fire to restore or maintain natural ecosystem function in pyrogenic systems will have to compensate for anthropogenic influences in their burn planning.://000220452500004 ISI Document Delivery No.: 806SB Times Cited: 6 Cited Reference Count: 36 Cited References: *ENV SYST RES I IN, 1997, ARC INFO COMM REF US ABRAHAMSON WG, 1984, AM J BOT, V71, P35 ABRAHAMSON WG, 1984, AM J BOT, V71, P9 ADRIAN FW, 1995, FIRE MANAGEMENT PLAN AGEE J, 1993, FIRE ECOLOGY PACIFIC ANDERSON HE, 1982, INT122 USDA FOR SERV BAKER WL, 1992, ECOLOGY, V73, P1879 BAKER WL, 1999, SPATIAL MODELING FOR, P277 CHRISTENSEN NL, 1985, ECOLOGY NATURAL DIST, P85 DAVIS FW, 1994, ROLE FIRE MEDITERRAN, P117 DAVISON KL, 1986, 22 CPSU U GEORG I EC DUNCAN BW, 1999, LANDSCAPE ECOL, V14, P291 DUNCAN BW, 2000, NAT AREA J, V20, P308 DUNCAN BW, 2003, UNPUB NATURAL AREAS FERNANDES PAM, 2001, FOREST ECOL MANAG, V144, P67 FINNEY MA, 1998, RMRSRP4 USDA FOR SER FINNEY MA, 1999, SPATIAL MODELING FOR, P189 GALLAGHER R, 1997, SCIENCE, V277, P485 KEELEY JE, 1999, SCIENCE, V284, P1829 LARSON RW, 1952, 6 USDA FOR SERV LUNT ID, 1998, AUST J BOT, V46, P629 MCGARIGAL K, 1995, PNWGTR351 USDA AGR F MILLER C, 2000, LANDSCAPE ECOL, V15, P145 MINNICH RA, 1983, SCIENCE, V219, P1287 MLADENOFF DJ, 1999, SPATIAL MODELING FOR MYERS RL, 1987, B TORREY BOT CLUB, V114, P21 MYERS RL, 1990, ECOSYSTEMS FLORIDA, P150 RAMOSNETO MB, 2000, ENVIRON MANAGE, V26, P675 ROBBINS LE, 1989, SEASONAL EFFECTS PRE ROTHERMEL RC, 1972, INT115 USDA FOR SERV SCHMALZER PA, 1992, CASTANEA, V57, P158 SCHMALZER PA, 1992, CASTANEA, V57, P220 SCHMALZER PA, 1994, 109202 NASA JF KENN SCHMALZER PA, 1999, FLORIDA SCI, V62, P13 SCHMALZER PA, 2001, P FLOR SCRUB S 2001, P17 TURNER MG, 1989, OIKOS, V55, P121 0921-2973 Landsc. Ecol.ISI:000220452500004Dynamac Corp, Kennedy Space Ctr, FL 32899 USA. Duncan, BW, Dynamac Corp, Mail Code DYN-2, Kennedy Space Ctr, FL 32899 USA. duncabw@kscems.ksc.nasa.govEnglish~?X/Duncan, D. H. Dorrough, J. White, M. Moxham, C.2008ZBlowing in the wind? Nutrient enrichment of remnant woodlands in an agricultural landscape107-119Landscape Ecology231Increasing fertiliser use in agricultural landscapes is likely to threaten the viability of remnant native vegetation in many parts of the world. Australia's prime grain production landscapes have nutrient poor soils, which formerly supported semi-arid woodland. The ecological function and capacity for regeneration of these remnants may be particularly susceptible to nutrient enrichment. The key sources of nutrients are wind and water deposition from crop fertilisation, and manure and feed from sheep. We hypothesised that these sources would result in unequal deposition of nutrients within and among remnant vegetation patches. We surveyed soil nutrients (Total N, Available P and K, C:N ratio, and soil pH) in the edges and interiors of 60 remnant woodland patches of various sizes, and in adjacent cultivated paddocks. Nutrient load was negatively correlated with remnant size and patterns were particularly strong for available P. Small remnant patches (< 3 ha) were accumulation zones for nutrients, with levels comparable or higher than within crop lands. The patterns are consistent with the hypothesis that small remnants are strongly enriched as a result of being used for livestock shelter. In larger remnants, the primary cause of enrichment is consistent with edge accumulation of nutrients due to wind and water movement. In large patches, remnant edges, particularly the windward edge, were elevated compared to interiors of large patches. In these semi-arid crop lands, current trends in intensification of cropping and a shift away from livestock may reduce the input of nutrients to small patches but increase the nutrient threat to larger remnants."://WOS:000251796100011 Times Cited: 0WOS:00025179610001110.1007/s10980-007-9160-0<7Dunford, W. Freemark, K.2005TMatrix matters: Effects of surrounding land uses on forest birds near Ottawa, Canada497-511Landscape Ecology205agricultural intensity; forest birds; land use; matrix; multi-scale; urbanization SPECIES RICHNESS; COMMUNITY COMPOSITION; ARTIFICIAL NESTS; LANDSCAPE-SCALE; HABITAT; ABUNDANCE; FRAGMENTATION; PREDATION; SONGBIRDS; PATTERNSArticleJul!Matrix quality affects probability of persistence in habitat patches in landscape simulation models while empirical studies show that both urban and agricultural land uses affect forest birds. However, due to the fact that forest bird abundance and species richness can be strongly influenced by local habitat factors, it is difficult to analyze matrix effects without confounding effects from such factors. Given this, our objectives were to (1) relate human-dominated land uses to forest bird abundance and species richness without confounding effects from other factors; (2) determine the scale at which forest birds respond to the matrix; and (3) identify whether certain bird migratory strategies or habitat associations vary in richness or abundance as a function of urban and agriculture land uses. Birds were surveyed at a single point count site 100 m from the edge of 23 deciduous forest patches near Ottawa, Ontario. Land uses surrounding each patch were measured within increasingly large circles from 200 to 5000 m radius around the bird survey site. Regression results suggest that effects of urban and agricultural land uses on forest birds (1) are not uniformly positive or negative, (2) can occur at different spatial scales, and (3) differentially affect certain groups of species. In general, agriculture appeared to affect species at a broad spatial scale (within 5 km), while urban land use had an impact at both a narrower spatial scale (within 1.8 km) and at the broad scale. Neotropical and short distance migrant birds seemed to be the most sensitive to land use intensification within the matrix. Limiting urban land use within approximately 200-1800 m of forest patches would be beneficial for Neotropical migrant birds, which are species of growing conservation concern in temperate North America.://000232205600001 ISI Document Delivery No.: 969AK Times Cited: 3 Cited Reference Count: 54 Cited References: *SAS I INC, 1990, SAS STAT US GUID VER ABERG J, 1995, OECOLOGIA, V103, P265 BAYNE EM, 1997, CONSERV BIOL, V11, P1418 BOLGER DT, 1997, CONSERV BIOL, V11, P406 BOULINIER T, 1998, ECOLOGY, V79, P1018 BOUTIN C, 1998, ECOL APPL, V8, P544 BURKE DM, 1998, AUK, V115, P96 DEGRAAF RM, 1998, FOREST ECOL MANAG, V103, P217 DRAPEAU P, 2000, ECOL MONOGR, V70, P423 DUNFORD W, 2001, THESIS CARLETON U OT ENGLES TM, 1994, CONSERV BIOL, V8, P286 FAHRIG L, 2001, BIOL CONSERV, V100, P65 FAUTH PT, 2000, LANDSCAPE ECOL, V15, P621 FLATHER CH, 1996, ECOLOGY, V77, P28 FREEMARK K, 1992, ECOLOGY CONSERVATION, P443 FREEMARK K, 2002, APPL LANDSCAPE ECOLO, P58 FREEMARK KE, 1989, IS FOREST FRAGMENTAT, P7 FREEMARK KE, 1995, ECOLOGY MANAGEMENT N, P381 FRIESEN L, 1998, FOREST CHRON, V74, P855 FRIESEN LE, 1995, CONSERV BIOL, V9, P1408 GASCON C, 1999, BIOL CONSERV, V91, P223 HAGAN JM, 1992, ECOLOGY CONSERVATION HERSPERGER AM, 2003, OIKOS, V101, P279 HINSLEY SA, 1995, J AVIAN BIOL, V26, P94 HOWELL CA, 2000, LANDSCAPE ECOL, V15, P547 JACKSON DA, 1993, ECOLOGY, V74, P2204 KENDEIGH SC, 1982, POPULATIONS E CENTRA KERR JT, 2004, ECOL APPL, V14, P743 KIRK DA, 2001, ECOSCIENCE, V8, P173 KLUZA DA, 2000, ANIM CONSERV 1, V3, P15 LEE M, 2002, OIKOS, V96, P110 MARTIN TE, 1995, ECOLOGY MANAGEMENT N MATESSI G, 1999, BIRD STUDY 2, V46, P184 MATSON PA, 1997, SCIENCE, V277, P504 MAZEROLLE MJ, 1999, ECOSCIENCE, V6, P117 NEAVE P, 2000, ENV SUSTAINABILITY C, P145 NICHOLS JD, 1998, CONSERV BIOL, V12, P1390 PARODY JM, 2001, GLOBAL ECOL BIOGEOGR, V10, P305 RENJIFO LM, 2001, ECOL APPL, V11, P14 RICKETTS TH, 2001, AM NAT, V158, P87 RODEWALD AD, 2000, WILSON BULL, V112, P238 SAAB V, 1999, ECOL APPL, V9, P135 SAUER JR, 2000, N AM BREEDING BIRD S SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SISK TD, 1997, ECOL APPL, V7, P1170 STINSON ER, 1994, WILDLIFE SOC B, V22, P566 TILMAN D, 1999, P NATL ACAD SCI USA, V96, P5995 TRAZINSKI MK, 1999, ECOL APPL, V9, P586 VILLARD MA, 1994, OECOLOGIA, V98, P393 VILLARD MA, 1998, AUK, V115, P801 WELSH DA, 1995, MONITORING BIRD POPU, P93 WHITCOMB RF, 1981, FOREST ISLAND DYNAMI, P125 WILCOVE DS, 1985, ECOLOGY, V66, P1211 ZAR JH, 1996, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000232205600001Carleton Univ, Ottawa Carleton Inst Biol, Geomat & Landscape Ecol Res Lab, Ottawa, ON K1S 5B6, Canada. Environm Canada, Natl Wildlife Res Ctr, Ottawa, ON K1A 0H3, Canada. Environm Canada, Knowledge Integrat Directorate, Natl Indicators Reporting Off, Gatineau, PQ K1A OH, Canada. Dunford, W, Canadian Wildlife Serv, Species Risk Branch, 351 St Joseph Blvd, Gatineau, PQ K1A 0H3, Canada. wendy.dunford@ec.gc.ca kathryn.lindsay@ec.gc.caEnglish|?$ BDunn, William C. Milne, Bruce T. Mantilla, Ricardo Gupta, Vijay K.2011kScaling relations between riparian vegetation and stream order in the Whitewater River network, Kansas, USA983-997Landscape Ecology267AugRiparian communities have been well-studied along individual streams, but not within the context of networks of which streams are a part. To study networks, hydrologists use Horton-Strahler ordering to assign streams to discrete categories in which increasing numerical value (omega) reflects increasing size of the stream and complexity of the network. A key use of this classification method has been to demonstrate scaling relations between hydrogeomorphic variables and order. These relations now provide a foundation to determine how ecological processes are associated with the geometry and topology of river networks. We used geographic information systems (GIS) to map and measure the stream network and riparian vegetation of the Whitewater River basin of eastern Kansas, USA. With the resulting data, we tested if (1) riparian vegetation scaled with order, and (2) riparian vegetation at confluences of two streams differed from that found along constituent streams. Most characteristics of riparian vegetation scaled with order. In confluence zones, density and diversity of riparian vegetation generally were equivalent to that of the largest constituent stream. Scaling relations between riparian vegetation and order provide a framework to quantify the role of riparian vegetation in the water balance of stream networks and a tool to predict area and distribution of riparian vegetation from network topology.!://WOS:000292705900007Times Cited: 0 0921-2973WOS:00029270590000710.1007/s10980-011-9622-2E|? Duvall, C. S.2008AHuman settlement ecology and chimpanzee habitat selection in Mali699-716Landscape Ecology236BCustomary land-use practices create distinctive cultural landscapes, including landscapes where abandoned settlements host vegetation that attracts wild animals. Understanding how landscape patterns relate to land-use history can help clarify the ecological effects of particular land uses. This study examines relationships between chimpanzee habitat selection and Maninka settlement practice, to determine how settlement history has affected chimpanzee habitat in Mali's Bafing Biosphere Reserve, where conservation practitioners assume that the characteristic settlement pattern reflects a process of settlement expansion into undisturbed habitat. Three types of data are reported: (1) ethnographic interviews on settlement history and practice; (2) systematic sampling of chimpanzee habitat use; and (3) ground-based mapping of settlement sites, surface water, and fruit-tree patches. These data show that the Maninka have a shifting settlement system, meaning that most sites are occupied for only relatively brief periods; and that some abandoned settlement sites host fruit-tree patches that are seasonally important chimpanzee habitat. Two main conclusions are: (1) settlement expansion has not occurred; instead, historic settlement has created habitat that is both attractive and available to chimpanzees. Anthropogenic habitat does not appear to be vital for chimpanzee survival, but it spatially and temporally supplements natural habitats. (2) Conservation policies meant to reduce the presumed threat of settlement expansion may have initiated an unintended, long-term threat of habitat loss for chimpanzees. While settlement practices may be a component of short-term threats to chimpanzees, such as hunting, when addressing these threats conservation practitioners should consider long-term settlement processes to avoid creating new threats.!://WOS:000257210900006Times Cited: 0 0921-2973WOS:00025721090000610.1007/s10980-008-9231-x |7 Dyer, J. M.2009XAssessing topographic patterns in moisture use and stress using a water balance approach391-403Landscape Ecology243Pwater budget evapotranspiration soil moisture solar radiation species-environment relationships climate change topography deciduous forests coweeta ohio southeastern united-states soil-moisture vegetation distribution root distributions incident radiation migration capacity gradient analysis climate-change heat load evapotranspirationMarThrough its control on soil moisture patterns, topography's role in influencing forest composition is widely recognized. This study addresses shortcomings in traditional moisture indices by employing a water balance approach, incorporating topographic and edaphic variability to assess fine-scale moisture demand and moisture availability. Using GIS and readily available data, evapotranspiration and moisture stress are modeled at a fine spatial scale at two study areas in the US (Ohio and North Carolina). Model results are compared to field-based soil moisture measurements throughout the growing season. A strong topographic pattern of moisture utilization and demand is uncovered, with highest rates of evapotranspiration found on south-facing slopes, followed by ridges, valleys, and north-facing slopes. South-facing slopes and ridges also experience highest moisture deficit. Overall higher rates of evapotranspiration are observed at the Ohio site, though deficit is slightly lower. Based on a comparison between modeled and measured soil moisture, utilization and recharge trends were captured well in terms of both magnitude and timing. Topographically controlled drainage patterns appear to have little influence on soil moisture patterns during the growing season. In addition to its ability to accurately capture patterns of soil moisture in both high-relief and moderate-relief environments, a water balance approach offers numerous advantages over traditional moisture indices. It assesses moisture availability and utilization in absolute terms, using readily available data and widely used GIS software. Results are directly comparable across sites, and although output is created at a fine-scale, the method is applicable for larger geographic areas. Since it incorporates topography, available water capacity, and climatic variables, the model is able to directly assess the potential response of vegetation to climate change.://000263419500008-408EY Times Cited:0 Cited References Count:70 0921-2973ISI:000263419500008^Dyer, Jm Ohio Univ, Dept Geog, Athens, OH 45701 USA Ohio Univ, Dept Geog, Athens, OH 45701 USADoi 10.1007/S10980-008-9316-6English <7G 7Dyer, R. J. Chan, D. M. Gardiakos, V. A. Meadows, C. A.2012Pollination graphs: quantifying pollen pool covariance networks and the influence of intervening landscape on genetic connectivity in the North American understory tree, Cornus florida L.239-251Landscape Ecology272pollination graph connectivity conditional genetic distance gene flow cornus florida long-distance dispersal seed dispersal 2-generation analysis bumble bees natural-populations flowering dogwood mating patterns quercus-lobata flow movementFeb&The manner by which pollinators move across a landscape and their resulting preferences and/or avoidances of travel through particular habitat types can have a significant impact on plant population genetic structure and population-level connectivity. We examined the spatial genetic structure of the understory tree Cornus florida (Cornaceae) adults (N-Adults = 452) and offspring (N-Offspring = 736) across two mating events to determine the extent to which pollen pool genetic covariance is influenced by intervening forest architecture. Resident adults showed no spatial partitioning but genotypes were positively autocorrelated up to a distance of 35 m suggesting a pattern of restricted seed dispersal. In the offspring, selfing rates were small (s(m) = 0.035) whereas both biparental inbreeding (s(b;open) (canopy) = 0.16, s(b;closed canopy) = 0.11) and correlated paternity (r(p;open canopy) = 0.21, r(p;closed canopy) = 0.07) were significantly influenced by primary canopy opening above individual mothers. The spatial distribution of genetic covariance in pollen pool composition was quantified for each reproductive event using Pollination Graphs, a network method based upon multivariate conditional genetic covariance. The georeferenced graph topology revealed a significant positive relationship between genetic covariance and pollinator movement through C. florida canopies, a negative relationship with open primary canopy (e. g., roads under open canopies and fields with no primary canopy), and no relationship with either conifer or mixed hardwood canopy species cover. These results suggest that both resident genetic structure within stands and genetic connectivity between sites in C. florida populations are influenced by spatial heterogeneity of mating individuals and quality of intervening canopy cover.://0003000887000089Sp. Iss. SI 889QQ Times Cited:0 Cited References Count:75 0921-2973Landscape EcolISI:000300088700008Dyer, RJ Virginia Commonwealth Univ, Dept Biol, Richmond, VA 23284 USA Virginia Commonwealth Univ, Dept Biol, Richmond, VA 23284 USA Virginia Commonwealth Univ, Dept Biol, Richmond, VA 23284 USA Virginia Commonwealth Univ, Dept Math, Richmond, VA 23284 USADOI 10.1007/s10980-011-9696-xEnglishڽ7Dzialak, MatthewR Houchen, DeanJ Harju, SethM Mudd, JamesP Wondzell, JohnJ Webb, StephenL Gould, NicholasP Hess, JenniferE Winstead, JeffreyB2013qEcosystem-level dynamics of soil-vegetation features, with implications for conserving a narrowly endemic reptile 1371-1385Landscape Ecology287Springer NetherlandsDune-dwelling species Dunes sagebrush lizard Landscape context Narrow endemics Object-based image classification Sand shinnery oak Soil-vegetation dynamics Sustainable landscape management 2013/08/01+http://dx.doi.org/10.1007/s10980-013-9888-7 0921-2973Landscape Ecol10.1007/s10980-013-9888-7English y|?' Dzialak, Matthew R. Webb, Stephen L. Harju, Seth M. Winstead, Jeffrey B. Wondzell, John J. Mudd, James P. Hayden-Wing, Larry D.2011nThe spatial pattern of demographic performance as a component of sustainable landscape management and planning775-790Landscape Ecology266JulPrioritizing habitat for animal conservation in heterogeneous landscapes requires an understanding of where animal occurrence coincides with human influences on demographic performance. We related broad-scale patterns of occurrence with risk of mortality among female Rocky Mountain elk (Cervus elaphus) in a human-modified landscape to develop a spatially-explicit framework for animal conservation at the landscape level. Variability in the spatial pattern of elk occurrence was driven by preference for specific habitat types as well as responses to human activity. In contrast, risk of mortality was a function of human modification of the landscape with little variation explained by habitat. Proximity to industrial development was associated with increased risk of mortality whereas proximity to residences and agricultural structures was associated with decreased risk. Individual-level results revealed added complexity, whereby risk of mortality was associated with a consistent pattern of occurrence relative to industrial development, yet the association between risk and occurrence relative to structures was highly variable and likely a function of disparate land-use priorities. Approaches to managing human-mediated risk at the landscape level are most effective when they decompose human activity into constituent parts influencing risk, and when individual variation relative to the population response is investigated. Conservation interventions need to target factors that have a consistent influence across the population rather than risk uncertainty that would arise from targeting factors that influence individuals in variable or situation-specific ways. The spatial tools developed herein provide guidance for sustainable landscape planning in the study area, while the concept of linking occurrence and demographic performance within a hierarchical modeling framework has general application for animal conservation in landscapes subject to change, human-caused or otherwise.!://WOS:000291485400002Times Cited: 1 0921-2973WOS:00029148540000210.1007/s10980-011-9607-1|?3 JEcke, F. Christensen, P. Rentz, R. Nilsson, M. Sandstrom, P. Hornfeldt, B.2010XLandscape structure and the long-term decline of cyclic grey-sided voles in Fennoscandia551-560Landscape Ecology2540Changes in forest landscape structure have been suggested as a likely contributing factor behind the long-term decline in the numbers of cyclic grey-sided voles (Clethrionomys rufocanus) in northern Fennoscandian lowland regions in contrast to mountain regions due to the absence of forest management in the mountains. This study, for the first time, formally explored landscape structure in 29 lowland (LF) and 14 mountain forest (MF) landscapes (each 2.5 x 2.5 km) in northern Sweden, and related the results to the cumulated spring trapping index of the grey-sided vole in 2002-2006. The grey-sided vole showed striking contrasts in dynamics close in space and time. The MF landscapes were characterized by larger patches and less fragmentation of preferred forest types. The grey-sided vole was trapped in all of 14 analyzed MF landscapes but only in three out of 29 of the LF landscapes. MF and LF landscapes with grey-sided vole occurrence were characterized by similar focal forest patch size (mean 357 ha, minimum 82 ha and mean 360 ha, minimum 79 ha, respectively). In contrast, these MF compared to the LF landscapes were characterized by larger patches of preferred forest types and less fragmented preferred forest types and by a lower proportion of clear-cut areas. The present results suggest that landscape structure is important for the abundance of grey-sided voles in both regions. However, in the mountains the change from more or less seasonal dynamics to high-amplitude cycles between the mid 1990s and 2000s cannot be explained by changes in landscape structure.!://WOS:000275444100005Times Cited: 0 0921-2973WOS:00027544410000510.1007/s10980-009-9441-x><7i4Ecke, F. Christensen, P. Sandstrom, P. Hornfeldt, B.2006eIdentification of landscape elements related to local declines of a boreal grey-sided vole population485-497Landscape Ecology2141-ha sampling plot; clear cuts; Fennoscandia; fragmentation; GIS; landscape design; landscape structure; long-term decline; old-growth pine forest; remotely sensed data DELAYED DENSITY-DEPENDENCE; RANDOM SAMPLE HYPOTHESIS; LONG-TERM DECLINE; HABITAT FRAGMENTATION; AGRICULTURAL LANDSCAPE; SMALL MAMMALS; CLETHRIONOMYS-RUFOCANUS; CLASSIFICATION TREES; FOREST INVENTORY; NORTHERN SWEDENArticleMaySeveral studies indicate a long-term decline in numbers of different species of voles in northern Fennoscandia. In boreal Sweden, the long-term decline is most pronounced in the grey-sided vole (Clethrionomys rufocanus). Altered forest landscape structure has been suggested as a possible cause of the decline. However, habitat responses of grey-sided voles at the landscape scale have never been studied. We analyzed such responses of this species in lowland forests in Vasterbotten, northern Sweden. Cumulated spring densities representing 22 local time series from 1980-1999 were obtained by a landscape sampling design and were related to the surrounding landscape structure of 2.5x2.5 km plots centred on each of the 22 1-ha trapping plots. In accordance with general knowledge on local habitat preferences of grey-sided voles, our study supported the importance of habitat variables such as boulder fields and old-growth pine forest at the landscape scale. Densities were negatively related to clear cuts. Habitat associations were primarily those of landscape structure related to habitat fragmentation, distance between habitat patches and patch interspersion rather than habitat patch type quantity. Local densities of the grey-sided vole were positively and exponentially correlated with spatial contiguity (measured with the fragmentation index) of old-growth pine forest, indicating critical forest fragmentation thresholds. Our results indicate that altered land use might be involved in the long-term decline of the grey-sided vole in managed forest areas of Fennoscandia. We propose two further approaches to reveal and test responses of this species to changes in landscape structure.://000237487700003 J ISI Document Delivery No.: 041WR Times Cited: 0 Cited Reference Count: 57 Cited References: *ENV SYST RES I, 2002, ARCGIS, V82 *STAT INC, 2002, STATISTICA DAT AN SO AARS J, 2002, ECOLOGY, V83, P3449 ANDREN H, 1992, ECOLOGY, V73, P794 ANDREN H, 1994, OIKOS, V71, P355 ANDREN H, 1996, OIKOS, V76, P235 ANDREN H, 1999, OIKOS, V84, P306 BAYNE EM, 1998, CAN J ZOOL, V76, P62 BENNETT AF, 1990, LANDSCAPE ECOL, V4, P109 BJARVALL A, 1995, DAGGDJUR ALLA EUROPA BOWERS MA, 1996, OECOLOGIA, V108, P182 CHRISTENSEN P, 2003, J MAMMAL, V84, P1292 COLLINS RJ, 1997, LANDSCAPE ECOL, V12, P63 DEBELJAK M, 2001, ECOL MODEL, V138, P321 FAHRIG L, 1998, ECOSYSTEMS, V1, P197 FORMAN RT, 1997, LAND MOSAICS ECOLOGY FRANCOLOPEZ H, 2001, REMOTE SENS ENVIRON, V77, P251 GAINES MS, 1992, WILDLIFE 2001 POPULA, P875 HANSEN TF, 1999, P NATL ACAD SCI USA, V96, P986 HANSKI I, 1996, J ANIM ECOL, V65, P220 HANSKI I, 1999, METAPOPULATION ECOLO HANSSON L, 1974, FAUNA FLORA, V69, P91 HANSSON L, 1977, LANDSCAPE PLANNING, V4, P85 HANSSON L, 1999, OIKOS, V86, P159 HENTTONEN H, 1992, ANN ZOOL FENN, V29, P1 HENTTONEN H, 2000, POLISH J ECOLOGY S, V48, P87 HORNFELDT B, 1978, OECOLOGIA BERL, V32, P141 HORNFELDT B, 1991, THESIS UMEA U SWEDEN HORNFELDT B, 1994, ECOLOGY, V75, P791 HORNFELDT B, 1995, REPORT WORLD WILDLIF, V3, P21 HORNFELDT B, 1998, FAUNA FLORA, V93, P137 HORNFELDT B, 2004, OIKOS, V107, P376 JOHANNESEN E, 1996, ECOLOGY, V77, P1196 JONGMAN RHG, 1995, DATA ANAL COMMUNITY KALELA O, 1957, ANN ACAD SCI FENN, V334, P1 KANEKO Y, 1998, RES POPUL ECOL, V40, P21 LEVIN SA, 1992, ECOLOGY, V73, P1943 LOFGREN O, 1995, OIKOS, V72, P29 LOMAN J, 1991, LANDSCAPE ECOL, V5, P183 LUOTO M, 2002, J BIOGEOGR, V29, P1027 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S, P122 MILLER J, 2002, ECOL MODEL, V157, P227 ONEILL RV, 1986, HIERARCHICAL CONCEPT OSTLUND L, 1997, CAN J FOREST RES, V27, P1198 RAAB B, 1995, SVERIGES NATL ATLAS REESE H, 2002, COMPUT ELECTRON AGR, V37, P37 REESE H, 2003, AMBIO, V32, P542 REUNANEN P, 2002, ECOL APPL, V12, P1188 SHARMA S, 1996, APPL MULTIVARIATE TE SIIVONEN L, 1968, NODRDUROPAS DAGGDJUR TURNER MG, 1989, LANDSCAPE ECOL, V3, P3 TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 VANAPELDOORN RC, 1992, OIKOS, V65, P265 WIENS JA, 1989, FUNCT ECOL, V3, P385 WOLFF JO, 1997, CONSERV BIOL, V11, P945 WU JG, 2002, LANDSCAPE ECOL, V17, P761 ZAR JH, 1996, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000237487700003Lulea Univ Technol, Div Appl Geol, Landscape Ecol Grp, SE-97187 Lulea, Sweden. Int Inst Appl Syst Anal, A-2361 Laxenburg, Austria. Umea Univ, Dept Ecol & Environm Sci, SE-90187 Umea, Sweden. Swedish Univ Agr Sci, Dept Forest Resource Management & Genom, SE-90183 Umea, Sweden. Ecke, F, Lulea Univ Technol, Div Appl Geol, Landscape Ecol Grp, SE-97187 Lulea, Sweden. Frauke.Ecke@ltu.seEnglish<7jEdenius, L. Elmberg, J.1996^Landscape level effects of modern forestry on bird communities in North Swedish boreal forests325-338Landscape Ecology116boreal forest; North Sweden; bird community; landscape; clear cutting; tree species composition HABITAT; FINLAND; TAIGA; FRAGMENTATION; PATTERNS; FIRESArticleDec We address effects of large-scale forestry on landscape structure and the structure and composition of boreal bird communities in North Sweden. Specifically, we ask: after controlling for the effect of patch size, forest age and tree species composition, is there any residual effect attributable to the reduction in area of old forest? Pairs of landscape blocks (25 by 25 km) were selected to maximize area difference in human-induced disturbance, clear-cut as opposed to semi-natural old forest. Median distance to natural edge (wetlands, open water) from randomly selected points in forest was 250 and 200 m in high and low impact landscapes, respectively, indicating a high degree of 'natural' fragmentation of the pristine boreal landscape in the area. By contrast, median distance to clear-cut in uncut forest was 750 and 100 m, respectively. Clear-cuts in high impact landscapes were disproportionally more common in areas with contiguous forest land than in areas with spatially disjunct forest, implicating that forestry increases natural fragmentation of the landscape by subdividing larger forest tracts. Point counts along forestry roads showed that species richness and relative abundance of forest birds were higher in landscapes with low forestry impact. These differences can partly be explained by differences in age composition of forest and composition of tree species. After controlling for patch size, forest age and tree species composition, a significant effect of forestry impact remained for Sibirian species and the Tree pipit Anthus trivialis. Our results thus imply that this group of species and the Tree pipit may be sensitive to forest fragmentation. In contrast to previous Finnish studies, we found relatively small negative effects on relative abundance of species hypothesized to be negatively affected by large-scale clear-cutting forestry. However, our picture of the present does not contradict results from Finnish long-term population studies. Five factors may account for this: 1) clear-cut areas are not permanently transformed into other land use types, 2) planted forests are not completely inhabitable for species preferring older forest, 3) the majority of species in the regional pool are habitat generalists, 4) the region studied is still extensively covered with semi-natural forest, and 5) our study area is relatively close to contiguous boreal forest in Russia, a potential source area for taiga species.://A1996VY82900003 sISI Document Delivery No.: VY829 Times Cited: 32 Cited Reference Count: 35 Cited References: 1994, STAT YB FORESTRY OFF AHTI T, 1968, ANN BOT FENN, V5, P169 ANDREN H, 1994, OIKOS, V71, P355 ENGELMARK O, 1984, CAN J BOT, V62, P893 ENOKSSON B, 1995, LANDSCAPE ECOL, V10, P267 ESSEEN PA, 1992, ECOLOGICAL PRINCIPLE, P252 HAGGLUND B, 1977, STUD FOR SUEC, V138 HAILA Y, 1987, ANN ZOOL FENN, V24, P179 HAILA Y, 1987, ORNIS FENNICA, V64, P90 HAILA Y, 1990, BIOGEOGRAPHY ECOLOGY, P61 HELLE P, 1986, OIKOS, V46, P107 HELLE P, 1990, BIOGEOGRAPHY ECOLOGY, P299 HUNTER M, 1990, WILDLIFE FORESTS FOR HUNTER ML, 1993, BIOL CONSERV, V65, P115 JARVINEN O, 1976, ACTA ZOOL FENNICI, V145, P1 JARVINEN O, 1977, OIKOS, V29, P225 JARVINEN O, 1977, SILVA FENNICA, V11, P284 KEMPE G, 1992, 51 U AGR SCI DEP FOR LANDRES PB, 1988, CONSERV BIOL, V2, P316 LINDER P, 1992, SVENSK BOT TIDSKR, V86, P199 MIKKONEN AV, 1983, ORNIS SCAND, V14, P36 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 MONKKONEN M, 1994, ANN ZOOL FENN, V31, P61 MONKKONEN M, 1994, J BIOGEOGR, V21, P183 PASTOR J, IN PRESS FUNCTIONAL SIMBERLOFF D, 1978, ASTM STP, V652, P150 SOLONEN T, 1994, MEMORANDA SOC FAUNA, V70, P1 SVENSSON S, 1995, FAGELARET 1995, P11 SYRJANEN K, 1994, ANN ZOOL FENN, V31, P19 TIREN L, 1937, MEDDELANDEN STATENS, V30, P67 VAISANEN RA, 1986, ORNIS SCAND, V17, P282 VIRKKALA R, 1987, ANN ZOOL FENN, V24, P281 VOOUS KH, 1960, ATLAS EUROPEAN BIRDS WIENS JA, 1989, ECOLOGY BIRD COMMUNI ZACKRISSON O, 1977, OIKOS, V29, P22 0921-2973 Landsc. Ecol.ISI:A1996VY82900003DEdenius, L, SWEDISH UNIV AGR SCI,DEPT ANIM ECOL,S-90183 UMEA,SWEDEN.English|? PEdvardsen, Anette Halvorsen, Rune Norderhaug, Ann Pedersen, Oddvar Rydgren, Knut2010@Habitat specificity of patches in modern agricultural landscapes 1071-1083Landscape Ecology257AugHabitat specificity analysis provides a tool for partitioning landscape species diversity on landscape elements by separating patches with many rare specialist species from patches with the same number of species, all of which are common generalists and thus provide information of relevance to conservation goals at regional and national levels. Our analyses were based upon species data from 2201 patch elements in SE Norwegian modern agricultural landscapes. The context used for measuring habitat specificity strongly influences the results. In general the gamma diversity contribution and core habitat specificity calculated from the patch data set were correlated. High values for both measures were observed for woodland, pastures and road verges whereas midfield islets and boundary transitional types were ranked low, as opposed to findings in traditional, extensively managed agricultural landscapes. This is due to our study area representing intensively used agricultural landscape elements holding a more trivial species composition, in addition to ruderals being favoured by fertility and disturbance, a finding also being supported by the semi-natural affiliation index. Results obtained by use of checklist data from the same study area diverged from patch data. Caution is needed in interpretation of habitat specificity results obtained from checklist data, because modern agricultural landscapes contain several land types which are seldom surveyed by botanists, thus being under-represented in the data set. We propose the use of core habitat specificity and gamma diversity contribution in parallel to obtain a value neutral diversity assessment that addresses patch uniqueness and other properties of conservation interests.!://WOS:000279592100007Times Cited: 1 0921-2973WOS:00027959210000710.1007/s10980-010-9481-2t|?B3Ehlers, Libby P. W. Johnson, Chris J. Seip, Dale R.2014oMovement ecology of wolves across an industrial landscape supporting threatened populations of woodland caribou451-465Landscape Ecology293MarWoodland caribou (Rangifer tarandus caribou) are a species of increasing conservation concern across North America. Throughout much of boreal Canada, human developments, including forestry and energy development, are now accepted causes of the decline in the number and distribution of caribou. One of the hypothesised mechanisms for the decline is altered predator-prey dynamics. We quantified the impacts of a variety of industrial activities on gray wolf (Canis lupus) and caribou interactions at a regional scale. We used animal locations collected with global positioning system collars and field data to examine how a range of industrial developments influenced the movements of wolves. We quantified the speed of wolf movements and the tortuosity of movement paths at two spatiotemporal scales across forested boreal and mountainous environments occupied by woodland caribou. Habitat and disturbance features better explained wolf movements during the weekly scale. In general, linear movements increased during winter, which paralleled past studies that suggested linear travel by wolves was associated with deep snow and the increased maintenance and patrol of territories. Wolves decreased movement rates but not sinuosity within close proximity to disturbance features, thus implying behaviours near such features were more closely associated with prey searching and hunting. Alternatively, wolves increased movement rates and linear travel through areas with high densities of linear and non-linear industrial features; this response suggested that wolves avoided spending time in high-risk areas associated with human activities. Results of this study further our understanding of wolf distribution and behaviour in habitats supporting populations of caribou within a matrix of industrial developments.!://WOS:000331935500008Times Cited: 0 0921-2973WOS:00033193550000810.1007/s10980-013-9976-8_~?f&Eigenbrod, F. Hecnar, S. J. Fahrig, L.2008hAccessible habitat: an improved measure of the effects of habitat loss and roads on wildlife populations159-168Landscape Ecology23Habitat loss is known to be the main cause of the current global decline in biodiversity, and roads are thought to affect the persistence of many species by restricting movement between habitat patches. However, measuring the effects of roads and habitat loss separately means that the configuration of habitat relative to roads is not considered. We present a new measure of the combined effects of roads and habitat amount: accessible habitat. We define accessible habitat as the amount of habitat that can be reached from a focal habitat patch without crossing a road, and make available a GIS tool to calculate accessible habitat. We hypothesize that accessible habitat will be the best predictor of the effects of habitat loss and roads for any species for which roads are a major barrier to movement. We conducted a case study of the utility of the accessible habitat concept using a data set of anuran species richness from 27 ponds near a motorway. We defined habitat as forest in this example. We found that accessible habitat was not only a better predictor of species richness than total habitat in the landscape or distance to the motorway, but also that by failing to consider accessible habitat we would have incorrectly concluded that there was no effect of habitat amount on species richness."://WOS:000252636100005 Times Cited: 0WOS:000252636100005(10.1007/s10980-007-9174-7|ISSN 0921-2973|? Ekblom, Anneli Gillson, Lindsey2010Hierarchy and scale: testing the long term role of water, grazing and nitrogen in the savanna landscape of Limpopo National Park (Mozambique) 1529-1546Landscape Ecology2510DecThis paper compares vegetation dynamics at two sites in the savanna landscape of Limpopo National Park (PNL), Mozambique. In order to test the relationship between vegetation cover and hydrology, nutrient availability and disturbance from grazing and fire over the last 1,200 years at local (100 m(2)) scales, we use palaeoecological data (i.e. pollen assemblages, charcoal abundance, C/N ratio, stable isotopes and herbivore-associated spore abundance). Two pans governed by similar rainfall regimes (on average 600 mm/year) but different hydrologies are compared. Chixuludzi Pan is responsive to the Limpopo River and is more water rich than Radio Pan, which is situated in a dry landscape with little surface water. The analysis suggests that in savannas where water is scarce, the recruitment of woody taxa is constrained mainly by the availability of underground water. In the Radio Pan sequence, the present grassland savanna has been stable throughout the time studied. In contrast, the Chixuludzi Pan savanna landscape where local hydrology, due to the proximity of Limpopo River, allows for a higher water availability the relationship between grass-arboreal pollen suggests a greater variability in vegetation cover, and other factors such as grazing, herbivory and nitrogen availability are important as controlling mechanisms for woody cover. The historical depth of the analysis enables a sub-hierarchy of local scale process to be identified, in this case local hydrology. Local water availability is shown to override the effect of regional rainfall and, in turn, to control the influence of other local scale factors such as nutrients and grazing.!://WOS:000283371000006Times Cited: 0 0921-2973WOS:00028337100000610.1007/s10980-010-9522-xڽ7*Ekroos, Johan Rundlöf, Maj Smith, HenrikG2013wTrait-dependent responses of flower-visiting insects to distance to semi-natural grasslands and landscape heterogeneity 1283-1292Landscape Ecology287Springer NetherlandszAgricultural intensity Breeding habitat preference Colony cycle length Colony size Habitat specialist Larval diet Mobility 2013/08/01+http://dx.doi.org/10.1007/s10980-013-9864-2 0921-2973Landscape Ecol10.1007/s10980-013-9864-2English<7%Eldridge, D. J. Zaady, E. Shachak, M.2002]Microphytic crusts, shrub patches and water harvesting in the Negev Desert: the Shikim system587-597Landscape Ecology176.desert hydrology desert shrublands ecosystem services microphytic crust runoff and sediment production soil crust controls on ecosystem processes source-sink relationships water harvesting SOIL CRUSTS PHYSICAL-PROPERTIES WESTERN-NEGEV VEGETATION RUNOFF ISRAEL INFILTRATION WOODLAND MANAGEMENT AUSTRALIAArticleOctHuman-made contour banks are a central component of the Shikim water harvesting system in Israel's Negev Desert. Efficient water capture depends on the presence of a stable microphytic crust which directs surplus surface runoff into the banks where it is stored. We used simulated rainfall to examine the impact of soil surface disturbance on runoff and sediment transport, and the effect of this on the efficiency of resource capture within the Shikim system. Two disturbance regimes: 1) removal of the microphytic crust only, and 2) removal of the crust and shrub patches by cultivation, were compared with an undisturbed control. In the undisturbed state, 32% of rainfall was redistributed as runoff. This runoff penetrated approximately 27% deeper under the shrub patches compared with the microphytic crust. When the microphytic crust was destroyed by simulated trampling, the runoff coefficient declined to 13%, and there was no significant difference in water penetration between shrub and crust patches. Complete destruction of the shrub hummocks and crust by cultivation resulted in a decline in the runoff coefficient to 6%. The result of sustained disturbance in these patchy Negev shrublands is a breakdown in spatial heterogeneity, a loss of ecosystem function, a reduction in ecosystem goods and services such as plant diversity and production, and ultimately a reduction in pastoral productivity. These results reinforce the view that microphytic crusts are critical for the efficient operation of the Shikim water harvesting system. Given that practices such as cultivation and trampling which disturb microphytic crusts result in enhanced infiltration, crusts should be left intact to maximise the water harvesting efficiency in these desert landscapes.://000179774900008 ISI Document Delivery No.: 624RN Times Cited: 6 Cited Reference Count: 57 Cited References: *MIN INC, 1994, MIN REF MAN REL 10 1 BERGKAMP G, 1998, CATENA, V33, P201 BOCHET E, 1999, CATENA, V38, P23 BOEKEN B, 1994, ECOL APPL, V4, P702 BRUINS HJ, 1986, APPL GEOGR, V6, P13 CERDA A, 1997, J ARID ENVIRON, V36, P37 COLWELL JD, 1969, 5 CSIRO DIV SOILS CRITCHLEY W, 1991, MANUAL DESIGN CONSTR DAN J, 1977, BULLETIN, V168 DUNKERLEY DL, 1995, J ARID ENVIRON, V30, P41 ELAMAMI S, 1977, AFR ENV, V3, P107 ELDRIDGE DJ, 1999, ACTA OECOL, V20, P159 ELDRIDGE DJ, 2000, CATENA, V40, P323 ELKINS NZ, 1986, OECOLOGIA, V68, P521 EVENARI M, 1983, NEGEV CHALLENGE DESE FEINBRUNDOTHAN N, 1991, ANAL FLORA ERETZ ISR GALLE S, 2001, BANDED VEGETATION PA, P77 GARNER W, 1989, J ARID ENVIRON, V16, P257 GREENE RSB, 1992, AUST J SOIL RES, V30, P55 HAASE P, 1996, J VEG SCI, V7, P527 HIERNAUX P, 1999, ACTA OECOL, V20, P147 ISSA OM, 1999, CATENA, V37, P175 KOLARKAR AS, 1983, J ARID ENVIRON, V6, P59 KUTSCH H, 1983, APPL GEOGRAPHY DEV, V21, P108 LOPEZPORTILLO J, 1999, ACTA OECOL, V20, P197 LOVEDAY J, 1974, 54 BUR SOIL TECHN CO LUDWIG J, 1997, LANDSCAPE ECOLOGY FU LUDWIG JA, 1994, PACIFIC CONSERVATION, V1, P209 MACFADYEN WA, 1950, NATURE, V165, P121 MAUCHAMP A, 2001, BANDED VEGETATION PA, P146 MONTANA C, 2001, BANDED VEGETATION PA, P132 MORIN J, 1980, WATER RESOUR RES, V16, P1080 NIEMEIJER D, 1998, LAND DEGRAD DEV, V9, P323 NOBLE JC, 1998, RANGELAND J, V20, P206 NOYMEIR I, 1973, ANNU REV ECOL SYST, V4, P25 PEUGEOT C, 1997, J HYDROL, V188, P179 PICKUP G, 1985, AUSTR RANGELAND J, V7, P114 PUIGDEFABREGAS J, 1996, ADV HILLSLOPE PROCES, V2, P1027 REID KD, 1999, SOIL SCI SOC AM J, V63, P1869 REIJ C, 1990, 91 WORLD BANK, V1 ROSTAGNO CM, 1989, J RANGE MANAGE, V42, P382 SCHLESINGER WH, 1990, SCIENCE, V247, P1043 SCHULTEN JA, 1985, AM J BOT, V72, P1657 SEGHIERI J, 1999, ACTA OECOL, V20, P209 SHACHAK M, 1998, ECOSYSTEMS, V1, P475 SHACHAK M, 1999, ARID LANDS MANAGEMEN, P254 SHEIKH MI, 1984, FOREST ECOL MANAG, V8, P257 TEOMIM N, 1990, SOIL SURVEY SAYERET TONGWAY D, 1995, ENVIRON MONIT ASSESS, V37, P303 TONGWAY DJ, 1994, PACIFIC CONSERVATION, V1, P201 VALENTIN C, 1991, GEODERMA, V48, P201 VERRECCHIA E, 1995, J ARID ENVIRON, V29, P427 VESTE M, 2001, SUSTAINABLE LAND USE, P357 YAIR A, 1987, PROGR DESERT RES, P145 YAIR A, 1990, EARTH SURF PROCESSES, V15, P597 ZAADY E, 1994, AM J BOT, V81, P109 ZAADY E, 1997, PLANT SOIL, V190, P247 0921-2973 Landsc. Ecol.ISI:000179774900008Univ New S Wales, Sch Biol Earth & Environm Sci, Dept Land & Water Conservat, Ctr Nat Resources, Sydney, NSW 2052, Australia. Ben Gurion Univ Negev, Desertificat & Restorat Ecol Res Ctr, IL-84990 Sede Boqer, Israel. Ben Gurion Univ Negev, Jacob Blaustein Inst Desert Res, Mitrani Ctr Desert Ecol, IL-84990 Sede Boqer, Israel. Eldridge, DJ, Univ New S Wales, Sch Biol Earth & Environm Sci, Dept Land & Water Conservat, Ctr Nat Resources, Sydney, NSW 2052, Australia.English|?EElia, Mario Lafortezza, Raffaele Colangelo, Giuseppe Sanesi, Giovanni2014_A streamlined approach for the spatial allocation of fuel removals in wildland-urban interfaces 1771-1784Landscape Ecology2910Dec$Major concerns are arising on the expansion of wildland-urban interfaces defined as zones where infrastructures and other man-made systems interact with undeveloped areas. Wildland-urban interfaces create an environment in which fire can easily spread from forest fuels to human settlements. In this context, there is a need to prevent fire spread by determining the sound allocation of fuel treatment (fuel removal). To this end, the Spatial Allocation Index was developed as a streamlined approach to determine where and what type of forest areas may be eligible for fuel removal in terms of fire suppression. This approach was developed as a case study example using forest landscapes located in the province of Taranto (Apulia region) in southern Italy. By using geostatistical techniques, we scaled up 210 data points of plot-level fuel load and developed maps for different forest types. These spatial predictions were combined with other landscape-level variables such as population density, urban density, and road density. Through our modelling approach we were able to determine the fuel model types and spatial allocations of wildland areas that are likely to be treated by fuel removal. Our results suggest that the predominant forest typology requiring treatment in the study area is the Mediterranean maquis (shrub-land), which covers 44 % of the wildland-urban interface landscape. The areas on the map where the Spatial Allocation Index reaches its maximum value are those with the highest priority in terms of fuel removal; i.e., the highest number of people, houses, and roads benefitting from wildfire suppression. By adopting this streamlined approach, forest managers and decision makers may avail of a fast and effective tool to improve efforts in landscape management and budgeting of financial resources.!://WOS:000346920900011Times Cited: 0 0921-2973WOS:00034692090001110.1007/s10980-014-0070-7 <7H .Elkin, C. Reineking, B. Bigler, C. Bugmann, H.2012Do small-grain processes matter for landscape scale questions? Sensitivity of a forest landscape model to the formulation of tree growth rate697-711Landscape Ecology275tree growth gap model forest disturbances model uncertainty climate-change impacts vegetation response relative importance mountain forests european forests gap models management succession dynamics uncertaintyMay.Process-based forest landscape models are valuable tools for testing basic ecological theory and for projecting how forest landscapes may respond to climate change and other environmental shifts. However, the ability of these models to accurately predict environmentally-induced shifts in species distributions as well as changes in forest composition and structure is often contingent on the phenomenological representation of individual-level processes accurately scaling-up to landscape-level community dynamics. We use a spatially explicit landscape forest model (LandClim) to examine how three alternative formulations of individual tree growth (logistic, Gompertz, and von Bertalanffy) influence model results. Interactions between growth models and landscape characteristics (landscape heterogeneity and disturbance intensity) were tested to determine in what type of landscape simulation results were most sensitive to growth model structure. We found that simulation results were robust to growth function formulation when the results were assessed at a large spatial extent (landscape) and when coarse response variables, such as total forest biomass, were examined. However, results diverged when more detailed response variables, such as species composition within elevation bands, were considered. These differences were particularly prevalent in regions that included environmental transition zones where forest composition is strongly driven by growth-dependent competition. We found that neither landscape heterogeneity nor the intensity of landscape disturbances accentuated simulation sensitivity to growth model formulation. Our results indicate that at the landscape extent, simulation results are robust, but the reliability of model results at a finer resolution depends critically on accurate tree growth functions.://000303056100007-929JC Times Cited:0 Cited References Count:57 0921-2973Landscape EcolISI:000303056100007Elkin, C ETH, Dept Environm Sci, Univ Str 16, CH-8092 Zurich, Switzerland ETH, Dept Environm Sci, Univ Str 16, CH-8092 Zurich, Switzerland ETH, Dept Environm Sci, CH-8092 Zurich, Switzerland Univ Bayreuth, BayCEER, D-95440 Bayreuth, GermanyDOI 10.1007/s10980-012-9718-3English <7I @Elliott, C. P. Lindenmayer, D. B. Cunningham, S. A. Young, A. G.2012~Landscape context affects honeyeater communities and their foraging behaviour in Australia: implications for plant pollination393-404Landscape Ecology273fragmentation linear remnant large remnant emu bush floral visitation southern costa-rica habitat fragmentation forest fragmentation western-australia atlas data birds conservation woodland success lichenostomusMarWe investigated the species richness and composition of bird communities in mallee woodland remnants in a highly fragmented landscape, focusing specifically on honeyeaters and their foraging behaviour. We observed birds around flowering Eremophila glabra ssp. glabra plants in three replicated contexts: (1) the interior of large remnants, (2) linear remnants within similar to 3 km of a large remnant, and (3) linear remnants 5-7 km from a large remnant. We found species richness differed among elements, with an increase in the number of species that tolerate disturbed, open habitat and a decrease in the number of woodland-dependent species in linear elements. Honeyeater assemblages were similar in species richness and abundance among the elements, but differed in composition due to a higher number of large-sized honeyeater species in distant elements. Honeyeater movement patterns into a site and within a site were similar among the elements. Floral visitation varied among honeyeater species and was positively correlated with their abundance in the far element. Our results demonstrate that bird species respond differently to the spatial context of remnants in a fragmented landscape; however, the degree of isolation of linear remnants was not important. Linear remnants appear to be frequently used by honeyeaters, but the changes in community composition among the elements may influence the quality of pollination, which could have implications for plant reproduction.://000300087500007-889QE Times Cited:0 Cited References Count:62 0921-2973Landscape EcolISI:0003000875000074Elliott, CP CSIRO Plant Ind, GPO Box 1600, Canberra, ACT 2601, Australia CSIRO Plant Ind, GPO Box 1600, Canberra, ACT 2601, Australia CSIRO Plant Ind, Canberra, ACT 2601, Australia Australian Natl Univ, Fenner Sch Environm & Soc, Canberra, ACT 0200, Australia CSIRO Ecosyst Sci, Canberra, ACT 2601, AustraliaDOI 10.1007/s10980-011-9697-9English<7S9Elliott, N. C. Kieckhefer, R. W. Lee, J. H. French, B. W.1999VInfluence of within-field and landscape factors on aphid predator populations in wheat239-252Landscape Ecology143Coccinellidae Aphididae wheat spatial scale species diversity numerical response EASTERN SOUTH-DAKOTA COCCINELLIDAE COLEOPTERA GREENBUGS HOMOPTERA ALFALFA FIELDS SORGHUM EXTENT MAIZEArticleJun6The influence of prey density, within-field vegetation, and the composition and patchiness of the surrounding landscape on the abundance of insect predators of cereal aphids was studied in wheat fields in eastern South Dakota, USA. Cereal aphids, aphid predators, and within-field vegetation were sampled in 104 fields over a three year period (1988-1990). The composition and patchiness of the landscape surrounding each field were determined from high altitude aerial photographs. Five landscape variables, aggregated at three spatial scales ranging from 2.6 km(2) to 581 km(2), were measured from aerial photographs. Regression models incorporating within-field and landscape variables accounted for 27-49% of the variance in aphid predator abundance in wheat fields. Aphid predator species richness and species diversity were also related to within-field and landscape variables. Some predators were strongly influenced by variability in the composition and patchiness of the landscape surrounding a field at a particular spatial scale while others responded to variability at all scales. Overall, predator abundance, species richness, and species diversity increased with increasing vegetational diversity in wheat fields and with increasing amounts of non-cultivated lands and increasing patchiness in the surrounding landscape.://000081041200002 # ISI Document Delivery No.: 209HB Times Cited: 9 Cited Reference Count: 48 Cited References: *SAS I, 1988, SAS STAT US GUID VER ANDOW D, 1983, AGR ECOSYST ENVIRON, V9, P25 CODERRE D, 1987, CAN ENTOMOL, V119, P195 DAUBENMIRE R, 1959, NW SCI, V33, P43 DILLON WR, 1984, MULTIVARIATE ANAL ME DUELLI P, 1984, BIOL CHRYSOPIDAE, P110 DUELLI P, 1988, ECOLOGY EFFECTIVENES, P89 DUELLI P, 1990, BIOL CONSERV, V54, P193 DUNNING JB, 1992, OIKOS, V65, P169 ELLIOTT NC, 1990, ENVIRON ENTOMOL, V19, P1320 ELLIOTT NC, 1991, CAN ENTOMOL, V123, P13 ELLIOTT NC, 1998, IN PRESS SW ENTOMOLO EVANS EW, 1992, J KANSAS ENTOMOL SOC, V65, P30 EWERT MA, 1966, CAN ENTOMOL, V98, P999 FAHRIG L, 1994, CONSERV BIOL, V8, P50 FRAZER BD, 1976, J ENTOMOLOGICAL SOC, V73, P33 HEMPTINNE JL, 1988, ENTOMOPHAGA, V33, P505 HOAGLIN DC, 1983, UNDERSTANDING ROBUST HODEK I, 1993, EUR J ENTOMOL, V90, P403 HODEK I, 1996, ECOLOGY COCCINELLIDA HONEK A, 1982, Z ANGEW ENTOMOL, V94, P157 HONEK A, 1982, Z ANGEW ENTOMOL, V94, P311 HONEK A, 1986, ECOLOGY APHIDOPHAGA, P263 HONEK A, 1990, ACTA ENTOMOL BOHEMOS, V87, P336 HURLBERT SH, 1984, ECOL MONOGR, V54, P187 KIECKHEFER RW, 1992, GREAT LAKES ENTOMOL, V25, P15 KRING TJ, 1985, J ECON ENTOMOL, V78, P269 LANDIS DA, 1998, HDB PEST MANAGEMENT, P79 LATTIN JD, 1989, ANNU REV ENTOMOL, V34, P383 MCPHERSON JE, 1981, GREAT LAKES ENTOMOL, V14, P19 MICHELS GJ, 1997, ENVIRON ENTOMOL, V26, P4 NEUENSCHWANDER P, 1975, HILGARDIA, V43, P53 NEW TR, 1984, BIOL CHRYSOPIDAE, P160 PEARSON SM, 1993, LANDSCAPE ECOL, V8, P3 PEDLAR JH, 1997, J WILDLIFE MANAGE, V61, P102 PRINCIPI MM, 1984, BIOL CHRYSOPIDAE, P76 RICE ME, 1988, ENVIRON ENTOMOL, V17, P836 ROACH SH, 1991, ENVIRON ENTOMOL, V20, P540 RYSZKOWSKI L, 1993, LANDSCAPE ECOLOGY AG, P71 SHANNON CE, 1948, MATH THEORY COMMUNIC SMITH BC, 1965, CAN ENTOMOL, V97, P760 SMITH BC, 1971, CAN ENTOMOL, V103, P1115 SOLBRECK C, 1974, OECOLOGIA, V17, P205 SOTHERTON NW, 1989, ENTOMOLOGIST, V108, P135 VANDENBOSCH R, 1973, BIOL CONTROL INSECTS, P459 VANEMDEN HF, 1990, CRITICAL ISSUES BIOL, P63 WAY MJ, 1988, ENTOMOLOGY INDIGENOU, P183 ZADOKS JC, 1974, WEED RES, V14, P415 0921-2973 Landsc. Ecol.ISI:000081041200002ARS, USDA, Plant Sci Res Lab, Stillwater, OK 74075 USA. Elliott, NC, ARS, USDA, Plant Sci Res Lab, 1301 N Western St, Stillwater, OK 74075 USA.English <7J 'Ellis, R. D. McWhorter, T. J. Maron, M.20129Integrating landscape ecology and conservation physiology1-12Landscape Ecology271'body condition chronic stress habitat fragmentation habitat quality macrophysiology physiological indicators spatial ecology area-sensitive passerine habitat quality forest fragmentation corticosterone levels humoral immunity stress responses food abundance body condition bird declines woodlandJan$The need to understand how anthropogenic landscape alteration affects fauna populations has never been more pressing. The importance of developing an understanding of the processes behind local extinction is widely acknowledged, but inference from spatial patterns of fauna distribution continues to dominate. However, this approach is limited in its ability to generate strong predictions about future distributions and local extinctions, especially when population-level responses to landscape alteration are subject to long time lags. We review the potential for indices of physiological stress and condition to contribute to understanding of how landscape pattern affects species persistence. Such measures can indicate habitat quality from the perspective of the individual animal, and can reveal environmental stressors before their negative consequences begin to manifest at a population level. Spatial patterns of chronic stress may therefore yield valuable insight into how landscape alteration influences species. We propose that the emerging disciplines of conservation physiology and macrophysiology have much to offer spatial ecology, and have great potential to reveal the physiological pathways through which habitat alteration affects fauna populations and their persistence in fragmented landscapes.://000298228300001-864HI Times Cited:0 Cited References Count:72 0921-2973Landscape EcolISI:000298228300001Maron, M Univ Queensland, Sch Geog Planning & Environm Management, Ctr Spatial Environm Res, Landscape Ecol & Conservat Grp, Brisbane, Qld 4072, Australia Univ Queensland, Sch Geog Planning & Environm Management, Ctr Spatial Environm Res, Landscape Ecol & Conservat Grp, Brisbane, Qld 4072, Australia Univ Queensland, Sch Geog Planning & Environm Management, Ctr Spatial Environm Res, Landscape Ecol & Conservat Grp, Brisbane, Qld 4072, Australia Univ Adelaide, Sch Anim & Vet Sci, Roseworthy, SA 5371, AustraliaDOI 10.1007/s10980-011-9671-6English*?#-Enoksson, Bodil Angelstam, Per Larsson, Karin1995fDeciduous forest and resident birds: the problem of fragmentation within a coniferous forest landscape267-275Landscape Ecology105Ulandscape patch, taiga, Sweden, biogeography, distribution, resident birds, isolation|7O &Enoksson, B. Angelstam, P. Larsson, K.1995gDeciduous Forest and Resident Birds - the Problem of Fragmentation within a Coniferous Forest Landscape267-275Landscape Ecology105Olandscape patch taiga sweden biogeography distribution resident birds isolationOctSix species of resident birds were censused in patches of deciduous forest within a coniferous forest landscape in south central Sweden. Here, the forests have been subjected to active forestry for a long time, but with recently increased intensity. Although the forest cover is more or less continuous in this landscape, mature deciduous forest is now a rare element compared with the untouched forest. All censused patches were similar with regards to size, proportion and amount of deciduous trees, but were either isolated in the coniferous forest ('isolated patches') or near to other deciduous patches ('aggregated patches'). We concentrated on six species of resident birds, with moderate area requirements, that are tied to deciduous forest and whose ecology is well-known. The Nuthatch and the Marsh tit, which both show strict year-round territoriality and have a restricted dispersal phase, were significantly more likely to be found in aggregated than in isolated patches. No effect was found for the Great tit and the Blue tit, which are less territorial outside the breeding season and have a longer dispersal phase. Moreover, the Great tit is less specialized on deciduous forest than the other species, Also, the Long-tailed tit was negatively affected by isolation, which may be due to restricted dispersal and to larger area requirements of this flock-territorial species. The Hazel grouse, finally, was not affected, but this larger bird probably uses the forest in a different way from the smaller species. Our study clearly shows that fragmentation of one type of forest (deciduous) within another can have serious detrimental effects on forest-living species and raises important issues for forest management practices and conservation within a forest landscape.://A1995TD59500002-Td595 Times Cited:65 Cited References Count:0 0921-2973ISI:A1995TD59500002-Univ Uppsala,Dept Zool,S-75122 Uppsala,SwedenEnglish<7&Enoksson, B. Engelstam, P. Larsson, K.1996}Deciduous forest and resident birds: The problem of fragmentation within a coniferous forest landscape (vol 10, pg 267, 1995)U1-U1Landscape Ecology112Correction, AdditionApr://A1996UN74500005 ISI Document Delivery No.: UN745 Times Cited: 0 Cited Reference Count: 1 Cited References: ENOKSSON B, 1995, LANDSCAPE ECOL, V10, P267 0921-2973 Landsc. Ecol.ISI:A1996UN74500005Englisho<7VEntel, M. B. Hamilton, N. T. M.1999OModel description of dynamics of disturbance and recovery of natural landscapes277-281Landscape Ecology143.landscape disturbance scale statistical momentArticleJunWe consider the dynamic simulation model of landscapes proposed by Turner et al. (1993). In this model a 'landscape', represented by a square grid of 100x100 cells, is exposed to disturbances of a fixed size at random locations at specified time intervals. The affected area recovers through a series of seral stages and achieves a mature stage unless it is affected again by successive disturbances. Two non-dimensional parameters, determining the dynamics of the model, are T, the ratio of the disturbance interval to the time of recovery and S, the ratio of the size of the disturbance to the size of the landscape. The main outcomes of analysis are the means and standard deviations of the areas occupied by different seral stages. We show that these characteristics of the system can be calculated analytically. This facilitates the understanding of the results of the computer experiments, the analysis of the asymptotic behaviour of the system (for example when the disturbances become increasingly small but very frequent, T,S much less than 1) and of more complex regimes of external disturbances, e.g., of the combined effects on a landscape from several types of disturbances with different spatial and time scales.://000081041200005 ISI Document Delivery No.: 209HB Times Cited: 1 Cited Reference Count: 2 Cited References: KORN GA, 1968, MATH HDB SCI ENG TURNER MG, 1993, LANDSCAPE ECOL, V8, P213 0921-2973 Landsc. Ecol.ISI:000081041200005CSIRO Wildlife & Ecol, Lyneham, ACT 2602, Australia. Entel, MB, Monash Univ, Cooperat Res Ctr So Hemisphere Meteorol, Wellington Rd, Clayton, Vic 3168, Australia.English g|?5 Ernoult, Aude Alard, Didier2011Species richness of hedgerow habitats in changing agricultural landscapes: are alpha and gamma diversity shaped by the same factors?683-696Landscape Ecology265May Understanding the determinants of hedgerow plant diversity in agricultural landscapes remains a difficult task, because the potential drivers affect the complete range of biodiversity components (alpha to gamma diversity). We surveyed herbaceous plant communities (of a height < 1.5 m) in 84 hedgerows in the Seine river floodplain of France. Two types of potential drivers for species richness, accounting for landscape mosaic and hedgerow network, were recorded at both hedgerow and site scale. The distribution of species richness through the components of alpha hedgerow diversity (i.e. the average diversity within a habitat) and gamma hedgerow diversity (i.e. the total diversity across habitats) were assessed using additive partitioning methods, while the relationship between species diversity and its potential landscape drivers at both scales was modeled using Generalized Additive Models. Our results indicated that gamma hedgerow diversity is explained by the heterogeneity of the landscape structure, which is correlated with the mosaic of agricultural land use. At this scale, intrinsic properties of the configuration of the hedgerow networks have a weak influence on species richness. Alpha hedgerow diversity is also explained by landscape variables, accounting for both the configuration of agricultural mosaics and hedgerow networks, but to a lesser extent. Time lags for species responses are shown at both scales, and for the two types of drivers. Extinction or colonization debt may be indicated at both scales, while the remnant effects of former practices may also be responsible for such patterns at a local scale. We suggest that hedgerow management should take the specific parameters of both scales into account. At a local scale, management actions should aim to decrease the influence of adjacent land use when the impact is negative, through the implementation of extended buffer zones, while at the landscape and farm scales, agri-environmental schemes should be dedicated to the conservation of specific agricultural land uses.!://WOS:000291485100007Times Cited: 0 0921-2973WOS:00029148510000710.1007/s10980-011-9593-3<7%Ernoult, A. Bureau, F. Poudevigne, I.2003`Patterns of organisation in changing landscapes: implications for the management of biodiversity239-251Landscape Ecology183biodiversity fractals landscapes management organisation risk assessment system theory variograms HETEROGENEOUS LANDSCAPES ECOLOGICAL-SYSTEMS SEINE VALLEY DIVERSITY SCALE CONSERVATION DEPENDENCE COMPLEXITY DYNAMICS METRICSArticleAprDespite the widespread need to predict and assess the effects of landscape change on biodiversity, the array of tools available for this purpose is still limited. Species' patterns and human activities such as land use respond to the environment on their own suite of scales in space and time so that their interactions are overlapping but complex. It is difficult, therefore, to relate biodiversity to patterns described solely by metric assessments of spatial heterogeneity. In this methodological paper, we therefore propose consideration of two measures of landscape organisation which focus on the relationships between different properties of the landscape system ( e. g., soil type distribution, land use distribution), rather than on their description alone. Alpha organisation measures the degree to which the distribution of features such as land use deviate from a random distribution, measured here as fractal dimension from the semivariogram of a variable describing agricultural intensity. Beta organisation measures the degree of deviation by which the spatial distribution of one property ( e. g., human land use) is independent of the distribution of another (e.g., soil type) and was derived from relative mutual information (= redundancy) between the 'agricultural land use' and 'soil types'. These measures are illustrated in a rural landscape of the lower Seine valley, at two scales of observation, and at two dates ( 1963 and 1999) separated by substantial agricultural change due the European Common Agricultural Policy (= CAP). The results show that analysis of patterns of agricultural activity across a range of spatial scales (alpha organisation), or across the pattern of spatial variation in soil types (beta organisation) reveal how the agricultural actors respond to environmental constraints at different scales. This organisation concept relates to the metastability of landscape systems, and suggest possible correlation between high values of landscape organisation and high levels in biodiversity.://000183770600003 ISI Document Delivery No.: 694JD Times Cited: 9 Cited Reference Count: 55 Cited References: ALARD D, 1999, LANDSCAPE URBAN PLAN, V46, P29 ANTROP M, 2000, LANDSCAPE URBAN PLAN, V50, P43 BAKER WL, 1995, LANDSCAPE ECOL, V10, P143 BALENT G, 1998, ANN ZOOTECH, V47, P419 BORNETTE G, 1998, BIOL CONSERV, V85, P35 BURROUGH PA, 1981, NATURE, V294, P240 BURROUGH PA, 1998, PRINCIPLES GEOGRAPHI CULLINAN VI, 1992, LANDSCAPE ECOL, V7, P211 DALE VH, 1997, ECOL APPL, V7, P753 DECAENS T, IN PRESS PLANT SOIL DEPABLO CL, 1988, LANDSCAPE ECOLOGY, V1, P203 DUTOIT T, 1996, ECOLOGIE, V27, P5 ERIKSSON O, 1993, OIKOS, V68, P371 GIGON A, 1996, J VEG SCI, V7, P29 GILLER KE, 1997, APPL SOIL ECOL, V6, P3 GIREL J, 1994, ENVIRON MANAGE, V18, P203 GODRON M, 1983, DISTURBANCE ECOSYSTE, P12 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HUGHES JMR, 1995, VEGETATIO, V118, P17 HUSTON MA, 1994, BIOL DIVERSITY, V3, P64 JOHNSON AR, 1992, LANDSCAPE ECOL, V7, P63 JOHNSON GD, 2001, LANDSCAPE ECOL, V16, P597 JOURNEL AG, 1978, MINING GEOSTATISTICS KOLASA J, 1989, P NATL ACAD SCI USA, V86, P8837 KOLASA J, 1991, ECOL STUD, V86, P1 LAW BS, 1998, BIODIVERS CONSERV, V7, P323 LEDUC A, 1994, LANDSCAPE ECOL, V9, P279 LEVIN SA, 1992, ECOLOGY, V73, P1943 LEVIN SA, 1999, CONSERV ECOL, V3, P6 LI H, 1995, OIKOS, V73, P280 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MORRIS DW, 1992, EVOL ECOL, V6, P412 NOSS RF, 2000, ENVIRON SCI POLICY, V3, P321 ONEILL RV, 1996, LANDSCAPE ECOL, V11, P169 PALMER MW, 1988, VEGETATIO, V75, P91 PALMER MW, 1994, AM NAT, V144, P717 PANNATIER Y, 1996, VARIOWIN SOFTWARE SP PHIPPS M, 1981, J THEOR BIOL, V93, P253 PHIPPS M, 1991, DIVERSIDAD BIOL BIOL PHIPPS M, 1994, PEGASE OPERATION MAN PICKETT STA, 1995, SCIENCE, V269, P331 POUDEVIGNE I, 1997, LANDSCAPE URBAN PLAN, V38, P93 POUDEVIGNE I, 2002, RIVER RES APPL, V18, P239 RICOTTA C, 2000, ECOL MODEL, V125, P245 ROBINSON RA, 2002, J APPL ECOL, V39, P157 ROSSI RE, 1992, ECOL MONOGR, V62, P277 SWIFT MJ, 1996, FUNCTIONAL ROLES BIO TURNER SJ, 1991, QUANTITATIVE METHODS, P17 VITOUSEK PM, 1997, ECOL APPL, V7, P737 WARD JV, 1998, BIOL CONSERV, V83, P269 WHITE D, 1997, CONSERV BIOL, V11, P349 WIENS JA, 1993, OIKOS, V66, P369 WITH KA, 1994, LANDSCAPE ECOL, V9, P25 WITH KA, 1997, OIKOS, V78, P151 WYLIE JL, 1993, BIOL CONSERV, V63, P137 0921-2973 Landsc. Ecol.ISI:000183770600003Univ Rouen, Fac Sci, ECODIV, Ecol Lab, F-76821 Mont St Aignan, France. Poudevigne, I, Univ Rouen, Fac Sci, Landscape Syst Res Grp, F-76821 Mont St Aignan, France.English<7O2Ernoult, A. Freire-Diaz, S. Langlois, E. Alard, D.20067Are similar landscapes the result of similar histories?631-639Landscape Ecology215agricultural landscape; landscape ecology; landscape history; landscape metrics; multivariate analysis; Seine floodplain PLANT-SPECIES RICHNESS; AGRICULTURAL LANDSCAPES; RURAL LANDSCAPES; MULTIPLE SCALES; LAND-USE; BIODIVERSITY; PATTERNS; DIVERSITY; HABITAT; ORGANIZATIONArticleJulyThis landscape study was based on the sampling of 20 replicated landscape sites (1 km(2) each) that were located within the floodplain of the river Seine. For each site, 13 landscape variables were measured at three dates (1963-1985-2000). The aim of this study was to investigate the overall landscape variability through its different dimensions (space vs. time) and to assess the relative importance of each dimension. We used a new statistical method, i.e., partial triadic analysis (PTA), which allowed us to assess both (1) the spatial variability of the floodplain landscape and its dynamics in time and (2) the dynamic trajectories of the landscape variables for each site. The results showed, at the floodplain scale, the same landscape pattern has emerged since 1963, although a major trend was observed which consisted in a decrease in meadows resulting from an increase in arable crops. At the site scale, landscape sites, even if they were all influenced by this general trend during the 40-year period, showed contrasting trajectories. These results suggest that similar sites in 2000 do not necessarily share common histories and that contrasting sites in 2000 may have originated from similar patterns in 1963. The issue of biodiversity surrogates is then discussed, suggesting that new landscape metrics should be developed, emphasising spatial variability and (or) temporal dynamics.://000240500100001 ISI Document Delivery No.: 083ZE Times Cited: 0 Cited Reference Count: 44 Cited References: *FAO ISSS ISRIC, 1998, WORLD REF BAS SOIL R ALIAUME C, 1993, OCEANOL ACTA, V16, P291 BERLIN GAI, 2000, ACTA OECOL, V21, P125 BLANC L, 1998, B FR PECHE PISCIC, P1 BLANC L, 2000, DONNEES SPATIO TEMPO BOUMA J, 1998, AGR ECOSYST ENVIRON, V67, P103 BROSOFSKE KD, 1999, PLANT ECOL, V143, P203 BUREL F, 1990, LANDSCAPE ECOL, V4, P197 BUREL F, 2003, LANDSCAPE URBAN PLAN, V1018, P1 COUSINS SAO, 2001, ECOGRAPHY, V24, P461 DAUBER J, 2003, AGR ECOSYST ENVIRON, V2083, P1 DUELLI P, 1997, AGR ECOSYST ENVIRON, V62, P81 DUNN CP, 1991, QUANTITATIVE METHODS, P173 DUPOUEY JL, 2002, ECOLOGY, V83, P2978 ERNOULT A, 2003, LANDSCAPE ECOL, V18, P239 FJELLSTAD WJ, 1999, LANDSCAPE URBAN PLAN, V45, P177 FUSTEC E, 2000, FONCTIONS VALEURS ZO GARBUTT RA, 2002, BIOL CONSERV, V106, P273 HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HULSHOFF RM, 1995, LANDSCAPE ECOL, V10, P101 IHSE M, 1995, LANDSCAPE URBAN PLAN, V31, P21 JEANNERET P, 2003, AGR ECOSYST ENVIRON, V98, P311 LI HB, 2004, LANDSCAPE ECOL, V19, P389 LINDBORG R, 2004, ECOLOGY, V85, P1840 LINDENMAYER DB, 2000, BIODIVERS CONSERV, V9, P15 MCGARIGAL K, 1995, FRAGSTATS SPATIAL PA MEEUS JHA, 1993, SCI TOTAL ENVIRON, V129, P171 MEYBECK M, 1998, SEINE BASSIN FONCTIO MOSER D, 2002, LANDSCAPE ECOL, V17, P657 POUDEVIGNE I, 1997, LANDSCAPE URBAN PLAN, V38, P93 POUDEVIGNE I, 2003, LANDSCAPE ECOL, V18, P223 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 ROBINSON RA, 2002, J APPL ECOL, V39, P157 ROSSI JP, 2003, PEDOBIOLOGIA, V47, P1 SAUBERER N, 2004, BIOL CONSERV, V117, P181 SHRIVER WG, 2004, BIOL CONSERV, V119, P545 SODERSTROM B, 2001, BIODIVERS CONSERV, V10, P1839 THIOULOUSE J, 1987, ACTA OECOL, V8, P463 THIOULOUSE J, 1997, STAT COMPUT, V7, P75 VITOUSEK PM, 1994, ECOLOGY, V75, P1861 WIENS JA, 1989, FUNCT ECOL, V3, P385 WILSON WL, 2002, AGR ECOSYST ENVIRON, P1 WU JG, 2004, LANDSCAPE ECOL, V19, P125 ZOBEL M, 1997, TRENDS ECOL EVOL, V12, P266 0921-2973 Landsc. Ecol.ISI:000240500100001Univ Rennes 1, ECOBIO, UMR 6553, F-35042 Rennes, France. Univ Rouen, Fac Sci, Ecol Lab, ECODIV, F-76821 Mont St Aignan, France. Univ Rouen, Fac Lettres, Lab Geog, MTG, F-76821 Mont St Aignan, France. Univ Bordeaux 1, INRA, UMR 1202, BIOGECO, F-33405 Talence, France. Ernoult, A, Univ Rennes 1, ECOBIO, UMR 6553, Batiment CAREN,Campus Beaulieu,Ave Gal Leclerc, F-35042 Rennes, France. Aude.Ernoult@univ-rennes1.frEnglishU|?Ernst, Bevan W.2014RQuantifying landscape connectivity through the use of connectivity response curves963-978Landscape Ecology296Jul9Habitat connectivity is an essential component of biodiversity conservation. Simulated landscapes were manipulated to quantify the impact of changes to the amount, fragmentation and dispersion of habitat on a widely applied landscape connectivity metric, the probability of connectivity index. Index results for different landscape scenarios were plotted against the dispersal distances used for their calculation to create connectivity response curves for each scenario. Understanding index response to controlled changes in landscape structure at a range of spatial scales can be used to give context to comparison of alternative landscape management scenarios. Increased amounts of habitat, decreased fragmentation and decreased inter-patch distances resulted in increased connectivity index values. Connectivity response curves demonstrated increases in assessed connectivity for scenarios with continuous corridors or "stepping stone" connectors. The sensitivity of connectivity response curves to controlled changes in landscape structure indicate that this approach is able to detect and distinguish between different types of landscape changes, but that delineation of habitat and method of quantifying dispersal probability incorporate assumptions that must be recognized when interpreting results to guide landscape management. Representing landscape connectivity in this manner allows for the impacts of alternative landscape management strategies to be compared visually through comparative plots, or statistically through the parameters that describe connectivity response curves.!://WOS:000338331600004Times Cited: 1 0921-2973WOS:00033833160000410.1007/s10980-014-0046-7 c<7K =Eros, T. Olden, J. D. Schick, R. S. Schmera, D. Fortin, M. J.2012QCharacterizing connectivity relationships in freshwaters using patch-based graphs303-317Landscape Ecology272ecological networks spatial graphs graph theory stream network dendritic networks fragmentation landscape connectivity network analysis habitat patches riverine landscapes dendritic networks fish assemblages spatial graphs stream fishes food webs conservationFebSpatial graphs in landscape ecology and conservation have emerged recently as a powerful methodology to model patterns in the topology and connectivity of habitat patches (structural connectivity) and the movement of genes, individuals or populations among these patches (potential functional connectivity). Most spatial graph's applications to date have been in the terrestrial realm, whereas the use of spatially explicit graph-based methods in the freshwater sciences has lagged far behind. Although at first patch-based spatial graphs were not considered suitable for representing the branching network of riverine landscapes, here we argue that the application of graphs can be a useful tool for quantifying habitat connectivity of freshwater ecosystems. In this review we provide an overview of the potential of patch-based spatial graphs in freshwater ecology and conservation, and present a conceptual framework for the topological analysis of stream networks (i.e., riverscape graphs) from a hierarchical patch-based context. By highlighting the potential application of graph theory in freshwater sciences we hope to illustrate the generality of spatial network analyses in landscape ecology and conservation.://0003000887000139Sp. Iss. SI 889QQ Times Cited:0 Cited References Count:93 0921-2973Landscape EcolISI:000300088700013Eros, T Hungarian Acad Sci, Balaton Limnol Res Inst, Klebelsberg K U 3, H-8237 Tihany, Hungary Hungarian Acad Sci, Balaton Limnol Res Inst, Klebelsberg K U 3, H-8237 Tihany, Hungary Hungarian Acad Sci, Balaton Limnol Res Inst, H-8237 Tihany, Hungary Univ Washington, Sch Aquat & Fishery Sci, Seattle, WA 98195 USA Duke Univ, Nicholas Sch Environm, Durham, NC 27708 USA Univ Basel, Sect Conservat Biol, Dept Environm Sci, CH-4056 Basel, Switzerland Univ Toronto, Dept Ecol & Evolutionary Biol, Toronto, ON M5S 3G5, CanadaDOI 10.1007/s10980-011-9659-2English<7Estades, C. F.2001DThe effect of breeding-habitat patch size on bird population density161-173Landscape Ecology162bird density foraging patterns habitat patch size landscape mosaic resource distribution TROPICAL RAIN-FOREST WOODLAND FRAGMENTS NESTING SUCCESS SMALL WOODS COMMUNITIES LANDSCAPE ISLANDS ABUNDANCE EXTINCTION PREDATIONArticleFebAn individual-based simulation model was used to study the effect of the relative location of food and nest sites in the landscape on the relationship between the breeding habitat patch size and bird population density. The model predicted that when both food and nest sites are located exclusively in the breeding habitat patches, larger patches tend to harbor higher population densities. But when food starts to be added to the 'matrix' habitat and taken out of the breeding habitat the advantageous effect of larger patches diminishes and eventually the trend reverses, with small patches having higher population densities. This pattern arises from the combined effect of the existence of an extended foraging area around patches and an intrinsic advantage of large habitat patches associated with the concentration of food resources and potential colonizers. The effects of interspecific interactions and the management implications of the model are discussed.://000167936500007 ISI Document Delivery No.: 419EN Times Cited: 10 Cited Reference Count: 72 Cited References: AMBUEL B, 1983, ECOLOGY, V64, P1057 ANDERSEN MC, 1995, ECOL APPL, V5, P639 ANDREN H, 1985, OIKOS, V45, P273 ANDREN H, 1994, OIKOS, V71, P355 ARANGOVELEZ N, 1997, BIOL CONSERV, V81, P137 BELLAMY PE, 1996, J APPL ECOL, V33, P249 BENGTSON SA, 1983, OIKOS, V41, P507 BERG A, 1997, BIRD STUDY 3, V44, P355 BERNSTEIN C, 1988, J ANIM ECOL, V57, P1007 BLAKE JG, 1984, BIOL CONSERV, V30, P173 BLOCK WM, 1993, CURR ORNITHOL, V11, P35 BRITTINGHAM MC, 1983, BIOSCIENCE, V33, P31 BROWN JH, 1977, ECOLOGY, V58, P445 BRYAN AL, 1995, CONDOR, V97, P133 BUCKLEY FG, 1980, BEHAV MARINE ANIM, V4, P69 BURKE DM, 1998, AUK, V115, P96 CAREY AB, 1995, J RAPTOR RES, V29, P223 CHARNOV EL, 1976, THEORETICAL POPULATI, V9, P129 ERWIN RM, 1995, BIOL CONSERV, V71, P187 ESTADES CF, 1999, ECOL APPL, V9, P573 FREEMARK KE, 1986, BIOL CONSERV, V36, P115 FRETWELL SC, 1970, ACTA BIOTHEOR, V19, P16 GILPIN M, 1991, METAPOPULATION DYNAM GREER RD, 1988, COLON WATERBIRD, V11, P181 HAILA Y, 1987, ORNIS FENNICA, V64, P90 HALL LS, 1997, WILDLIFE SOC B, V25, P173 HERKERT JR, 1994, ECOL APPL, V4, P461 HINSLEY SA, 1995, ECOGRAPHY, V18, P41 HINSLEY SA, 1995, J AVIAN BIOL, V26, P94 HINSLEY SA, 1996, OECOLOGIA, V105, P100 HOOVER JP, 1995, AUK, V112, P146 KILGO JC, 1997, WILDLIFE SOC B, V25, P878 LOMAN J, 1991, CONSERV BIOL, V5, P176 MACARTHUR RH, 1967, THEORY ISLAND BIOGEO MACARTHUR RH, 1972, ECOLOGY, V53, P330 MARTIN JW, 1987, J RAPTOR RES, V21, P57 MARTIN TE, 1981, AUK, V98, P715 MAZEROLLE MJ, 1999, ECOSCIENCE, V6, P117 MCCOLLIN D, 1998, ECOGRAPHY, V21, P247 NEWTON I, 1967, J ANIM ECOL, V36, P721 NEWTON I, 1998, POPULATION LIMITATIO NILSSON SG, 1985, OECOLOGIA, V66, P516 NORTON MR, 2000, ECOGRAPHY, V23, P209 OPDAM P, 1991, LANDSCAPE ECOL, V5, P93 PATON PWC, 1994, CONSERV BIOL, V8, P17 PATTON DR, 1992, WILDLIFE HABITAT REL PIMM SL, 1988, AM NAT, V132, P757 PULLIAM HR, 1988, AM NAT, V132, P652 ROBBINS CS, 1989, WILDLIFE MONOGRA JUL, P1 ROBINSON SK, 1994, BIRD CONSERV INT, V4, P233 ROBINSON SK, 1995, SCIENCE, V267, P1987 ROBINSON SK, 1997, CONSERVATION HIGHLY, P154 ROBINSON SK, 1998, AUK, V115, P1 SCHAMBERGER M, 1982, HABITAT SUITABILITY SCHIECK J, 1995, CONSERV BIOL, V9, P1072 SHAFFER ML, 1987, VIABLE POPULATIONS C, P69 SIMBERLOFF D, 1982, AM NAT, V120, P41 SISK TD, 1997, ECOL APPL, V7, P1170 SMALL MF, 1988, OECOLOGIA, V76, P62 STEPHENS DW, 1986, FORAGING THEORY TERBORGH J, 1997, ECOLOGY, V78, P1494 TEWKSBURY JJ, 1998, ECOLOGY, V79, P2890 TILMAN D, 1997, SPATIAL ECOLOGY ROLE, P3 TURNER IM, 1996, J APPL ECOL, V33, P200 TURNER IM, 1996, TRENDS ECOL EVOL, V11, P330 WEIMERSKIRCH H, 1994, POLAR BIOL, V14, P123 WIENS JA, 1976, ANNU REV ECOL SYST, V7, P81 WIENS JA, 1995, IBIS, V137, S97 WIENS JA, 1995, MOSAIC LANDSCAPES EC, P1 WILCOVE DS, 1990, BIOGEOGRAPHY ECOLOGY, P319 WITH KA, 1995, ECOLOGY, V76, P2446 YAHNER RH, 1988, CONSERV BIOL, V2, P333 0921-2973 Landsc. Ecol.ISI:000167936500007Univ Chile, Dept Manejo Recursos Forestales, Santiago, Chile. Estades, CF, Univ Chile, Dept Manejo Recursos Forestales, Casilla 9206, Santiago, Chile.Englishp<7Estrada-Pena, A.2005`Effects of habitat suitability and landscape patterns on tick (Acarina) metapopulation processes529-541Landscape Ecology205density prediction; graph theory; Ixodes ricinus; landscape features; recruitment; traversability IXODES-RICINUS ACARI; LOGISTIC-REGRESSION; NORTHERN SPAIN; CONNECTIVITY; IXODIDAE; CONSERVATION; ABUNDANCE; ANIMALS; SYSTEMS; SPACEArticleJulTick density and population dynamics are important factors in the ecological processes involved in pathogen circulation in a habitat. These characteristics of tick populations are closely linked to habitat suitability, which reflects the limiting ecological factors and landscape features affecting tick populations; however, little work has been done on the regional assessment of habitat suitability. In this study, a regional model for the distribution and abundance of the tick Ixodes ricinus in central Spain is developed. An occurrence and an abundance model were constructed; climate and vegetation variables were found to be the main predictors of both occurrence and density in a relatively homogeneous matrix of habitat patches, whereas topographical variables were found to have small contributions and were therefore discarded. The residuals of the abundance model showed good correlation with the isolation of each patch. The predictive power of the abundance model was greatly enhanced by inclusion of the traversability (a measure of the permeability of each patch to the propagules of the metapopulation) and recruitment (an index of the relative importance of each patch to the traffic through the entire habitat network). The removal from the landscape of the patches whose recruitment values were in the top 10% has a critical effect on tick density, an effect not observed when patches are removed at random. These results indicate that permanent tick populations can be sustained only in landscapes containing a minimum network of viable sites. Graph theory and measurements of patch isolation should prove to be important elements in the forecasting of tick abundance and the management of the features underlying the landscape ecology of tick populations and pathogen circulation in the field.://000232205600003 ISI Document Delivery No.: 969AK Times Cited: 0 Cited Reference Count: 29 Cited References: *MATH SOFT, 1999, S PLUS 2000 GUID STA BENNETT AF, 1990, LANDSCAPE ECOL, V4, P109 BUNN AG, 2000, J ENVIRON MANAGE, V59, P265 BURGMAN MA, 1996, RISK ASSESSMENT CONS CARPENTER G, 1993, BIODIVERS CONSERV, V2, P667 CARROLL JF, 1996, J MED ENTOMOL, V33, P554 DANIEL M, 1990, J HYG EPID MICROB IM, V34, P243 DANIEL M, 1994, ECOLOGICAL DYNAMICS, P91 DIAZDELGADO R, 2001, FOREST ECOL MANAG, V147, P67 ESTRADAPENA A, 1999, EXP APPL ACAROL, V23, P337 ESTRADAPENA A, 2001, J MED ENTOMOL, V38, P361 ESTRADAPENA A, 2003, ECOGRAPHY, V26, P661 GRAY JS, 1998, ZBL BAKT-INT J MED M, V287, P211 HANSKI I, 1997, METAPOPULATION BIOL HUGHJONES M, 1989, PARASITOL TODAY, V5, P244 KITRON U, 1998, J MED ENTOMOL, V35, P435 LEHMANN A, 2003, ECOL MODEL, V160, P165 MATTHIOPOULOS J, 2003, ECOL MODEL, V159, P239 MITTLBOCK M, 1996, STAT MED, V15, P1987 MOILANEN A, 1998, ECOLOGY, V79, P2503 OSBORNE PE, 2001, J APPL ECOL, V38, P458 PEARCE J, 2000, ECOL MODEL, V133, P225 PULLIAM HR, 1988, AM NAT, V132, P652 RANDOLPH SE, 2000, ADV PARASIT, V47, P217 SONENSHINE DE, 1994, ECOLOGICAL DYNAMICS SWETS JA, 1988, SCIENCE, V240, P1285 URBAN D, 2001, ECOLOGY, V82, P1205 VASALLO M, 2000, EXP APPL ACAROL, V24, P941 VIDA S, 1993, COMPUT METH PROG BIO, V40, P95 0921-2973 Landsc. Ecol.ISI:000232205600003Fac Vet, Dept Parasitol, Zaragoza 50013, Spain. Estrada-Pena, A, Fac Vet, Dept Parasitol, Miguel Servet 177, Zaragoza 50013, Spain. aestrada@unizar.esEnglish<7k;Etheridge, D. A. MacLean, D. A. Wagner, R. G. Wilson, J. S.2006{Effects of intensive forest management on stand and landscape characteristics in northern New Brunswick, Canada (1945-2027)509-524Landscape Ecology214age class distribution; spruce budworm; intensive forest management; landscape metrics; historical landscape patterns; patch characteristics SPATIAL-PATTERN; DISTURBANCE; USA; COMMUNITIES; DYNAMICS; OREGON; SCALEArticleMayDHistorical and future projected landscape patterns and changes caused by harvesting and silviculture were evaluated for a 189,000 ha, intensively managed forest in New Brunswick, Canada. We compared changes in species composition, age classes, and patch characteristics (area, size, density, edge, shape, and core area) between 1945, 2002, and projections to 2027 (based on the landowner's spatial forest management plan). In 1945, the landbase was 40% softwood, 37% mixed hardwood-softwood, 10% hardwood, and 9% softwood-cedar. From 1945 to 2002 and 2027, respectively, softwood forest area increased by 2 and 11%, mixedwood decreased by 19 and 20%, and hardwood area increased by 15 and 14%, and softwood-cedar increased by 6% and then decreased by 7%. In 1945, forest > 70 years old comprised 85% of the landscape, but declined to 44% in 2002 and was projected to encompass 41% in 2027. Increased area harvested, decreasing harvest patch size, and protection against natural disturbances resulted in progressively smaller mean and less variable patch sizes from 1945 to 2002. Based upon the 25-year forest management plan, this trend was projected to continue, with the exception of nine patches > 1000 ha created by 2027, eight of which were softwood plantations. Stand type successional dynamics were highly variable in both harvested and non-harvested areas, and in some cases were unexpected. Few of the 1945 stand types remained static by 2002, with 42 and 35% of mixedwood shifting to softwood as a result of harvesting, and to hardwood as a result of both harvesting and spruce budworm (Choristoneura fumiferana Clem.) outbreaks in the 1950s and 1970s. This study demonstrates the strong cumulative effect of forest management on landscape patterns, especially the socially mandated drive for smaller clearcuts resulting in the loss of large patches.://000237487700005 ISI Document Delivery No.: 041WR Times Cited: 1 Cited Reference Count: 42 Cited References: *NBDNRE, 1998, EC LAND CLASS NEW BR *REMS INC, 1999, WOODST US GUID *REMS INC, 2000, STANL FUNCT OV *VANG FOR MAN SERV, 1993, FOR PROT PLANN SUST, B1 AXELSSON AL, 2002, LANDSCAPE ECOL, V17, P403 BALCH RE, 1952, BIRCH DIEBACK PROBLE BENDER DJ, 1998, ECOLOGY, V79, P517 BETTS MG, 2003, CAN J FOREST RES, V33, P1821 ELKIE PC, 1999, TM002 NWST ETHERIDGE DA, 2005, IN PRESS CAN J FOR R FORMAN RT, 1995, LAND MOSAICS ECOLOGY FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 GRENIER JW, 1945, FOREST INVENTORY IRV HARVEY BD, 2002, FOREST ECOL MANAG, V155, P369 HATCHER RJ, 1963, PUBLICATION CANADA D, V1014 HESSBURG PF, 1999, ECOL APPL, V9, P1232 HESSBURG PF, 2000, FOREST ECOL MANAG, V135, P53 HIGDON JW, 2005, FOREST ECOL MANAG, V204, P279 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 KRUMMEL JR, 1987, OIKOS, V48, P321 LANDRES PB, 1999, ECOL APPL, V9, P1179 LEE M, 2002, OIKOS, V96, P110 LEHMKUL JF, 1994, PNW328 USDA FOR SERC LOFMAN S, 2003, FOREST ECOL MANAG, V175, P247 LUSSIER O, 1947, FOREST INVENTORY IRV MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MILLER JN, 1997, LANDSCAPE ECOL, V12, P137 MLADENOFF DJ, 1993, ECOL APPL, V3, P293 PASTOR J, 1990, LANDSCAPE ECOL, V4, P55 PORTER KB, 2004, EMULATING NATURAL FO, P135 RADELOFF VC, 2000, ECOL APPL, V10, P233 REMPEL R, 1999, PATCH ANAL 2 0 RIPPLE WJ, 1991, BIOL CONSERV, V57, P73 RUSSELL EWB, 1993, J ECOL, V81, P647 SPIES TA, 1994, ECOL APPL, V4, P555 STAUS NL, 2002, LANDSCAPE ECOL, V17, P455 TANG SM, 1997, LANDSCAPE ECOL, V12, P349 TINKER DB, 1998, LANDSCAPE ECOL, V13, P149 TOTHILL JD, 1921, P ACAD ENTOMOL SOC, V7, P45 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 2003, LANDSCAPE ECOL, V18, P449 WALLIN DO, 1994, ECOL APPL, V4, P569 0921-2973 Landsc. Ecol.ISI:000237487700005@Univ New Brunswick, Fac Forestry & Environm Management, Fredericton, NB E3B 5A3, Canada. Univ Maine, Dept Forest Ecosyst Sci, Orono, ME USA. Univ Maine, Dept Forest Management, Orono, ME USA. MacLean, DA, Univ New Brunswick, Fac Forestry & Environm Management, POB 44555, Fredericton, NB E3B 5A3, Canada. macleand@unb.caEnglishڽ7)Etherington, ThomasR Penelope Holland, E.2013GLeast-cost path length versus accumulated-cost as connectivity measures 1223-1229Landscape Ecology287Springer NetherlandsAccumulated-cost Cost-distance Effective geographic distance Friction Functional distance Irregular landscape graph Least-cost modelling Regular landscape graph Resistance 2013/08/01+http://dx.doi.org/10.1007/s10980-013-9880-2 0921-2973Landscape Ecol10.1007/s10980-013-9880-2English?L !Etherington, Thomas Perry, George2012uUsing point process intensity to establish the spatio-temporal grain of continuous landscape tessellations and graphs 1083-1090Landscape Ecology278Springer NetherlandsBiomedical and Life SciencesvThe choice of grain (or resolution) for a landscape study will affect the findings of ecological investigations, so the grain adopted must be explicitly stated. However, stating the grain of the spatial data structure representing a landscape can be difficult as a variety of continuous tessellations or graphs of different regular and irregular geometries can be used. We demonstrate how spatial point process intensity (or density) can be used to define the grain of landscape tessellations and graphs with a variety of geometries. To illustrate this novel approach, we used analyses of radio-telemetry data for the brushtail possum ( Trichosurus vulpecula ) on the North Island of New Zealand to produce point patterns of differing intensities to create a continuous landscape tessellation and graph at different spatio-temporal scales. In doing so we highlight how point process intensity can provide a general way of reporting the grain of landscape tessellations and graphs. Therefore, this approach may facilitate communication of grain and so aid interpretation of ecological investigations and facilitate comparisons between studies.+http://dx.doi.org/10.1007/s10980-012-9789-1 0921-297310.1007/s10980-012-9789-1<7M Etherington, T. R.20122Least-cost modelling on irregular landscape graphs957-968Landscape Ecology277accumulated-cost-surface cost-surface delaunay triangulation dijkstra's algorithm functional connectivity graph theory least-cost path nearest-neighbour interpolation python triangulated irregular network connectivity habitatAugLeast-cost modelling is becoming widely used in landscape ecology to examine functional connectivity. Traditionally the least-cost modelling algorithm creates a regularly structured landscape graph for connectivity analysis by converting all the cells from a cost-surface into vertices in a landscape graph. However, use of a regular landscape graph is problematic as it: contains a great deal of redundant information that in turn increases processing times, is constructed in a deterministic manner that precludes examination of the effects of graph structure on connectivity measures, and is known to produce results with directional bias. I present, and provide Python code for, an algorithm to produce an irregular landscape graph from a cost-surface. Tests demonstrate that comparable results to those of the traditional regular landscape graph approach can be achieved, while at the same time reducing computational expense, enabling variations in graph structure to be incorporated into an analysis, and avoiding directional bias. Therefore, this approach may allow for more robust ecological decision-making when examining matters of functional connectivity using least-cost modelling.://000306068200003-969PP Times Cited:0 Cited References Count:27 0921-2973Landscape EcolISI:000306068200003Etherington, TR Univ Auckland, Sch Environm, Ctr Biodivers & Biosecur, Auckland 1, New Zealand Univ Auckland, Sch Environm, Ctr Biodivers & Biosecur, Auckland 1, New Zealand Univ Auckland, Sch Environm, Ctr Biodivers & Biosecur, Auckland 1, New ZealandDOI 10.1007/s10980-012-9747-yEnglish|?- Ethier, Kevin Fahrig, Lenore2011sPositive effects of forest fragmentation, independent of forest amount, on bat abundance in eastern Ontario, Canada865-876Landscape Ecology266JulWhile studies have found that bat abundance is positively related to the amount of forest cover in a landscape, the effects of forest fragmentation (breaking apart of forest, independent of amount) are less certain, with some indirect evidence for positive effects of fragmentation. However, in most of these studies, the variables used to quantify fragmentation are confounded with forest amount, making it difficult to interpret the results. The purpose of this study was to examine how forest amount and forest fragmentation independently affect bat abundance. We conducted acoustic bat surveys at the centers of 22 landscapes throughout eastern Ontario, Canada, where landscapes were chosen to avoid a correlation between forest amount and forest fragmentation (number of patches) at multiple spatial scales, while simultaneously controlling for other variables that could affect bat activity. We found that the effects of forest amount on bat relative abundance were mixed across species (positive for Lasiurus borealis, negative for Perimyotis subflavus and Lasionycteris noctivagans). When there was evidence for an effect of forest fragmentation, independent of forest amount, on bat relative abundance, the effect was positive (Myotis septentrionalis, Myotis lucifugus and Lasiurus borealis). We suggest that the mechanism driving the positive responses to fragmentation is higher landscape complementation in more fragmented landscapes; that is, increased access to both foraging and roosting sites for these bat species. We conclude that fragmented landscapes that maximize complementation between roosting and foraging sites should support a higher diversity and abundance of bats.!://WOS:000291485400008Times Cited: 0 0921-2973WOS:00029148540000810.1007/s10980-011-9614-2 k<7>Etzenhouser, M. J. Owens, M. K. Spalinger, D. E. Murden, S. B.1998DForaging behavior of browsing ruminants in a heterogeneous landscape55-64Landscape Ecology131fractals Acacia shrubs path tortuosity Capri hircus Odocoileus virginianus TAILED DEER MOVEMENT PATTERNS ENVIRONMENTS HERBIVORES SCALESArticleFebMovement patterns of white-tailed deer (Odocoileus virginianus) and Spanish goats (Carpa hircus) were mapped and analyzed to test the hypothesis that foraging movements and behaviors within an Acacia shrub community are significantly related to environmental heterogeneity. Animal response to plant community heterogeneity was characterized using foraging velocity and the animals' foraging path fractal dimension (Dd) Environmental heterogeneity was characterized using the perimeter:area fractal dimension, which represents the shape of shrubs, and the grid count fractal dimension, which represents shrub spatial distribution. The foraging paths of deer were straighter and more directed (D-d = 1.27).than those of goats (D-d = 1.53), and deer responded to the shape of shrub patches, more so than to shrub distribution. The tortuosity of goat foraging paths was apparently affected by distribution of blackbrush (Acacia rigidula) and shrubby bluesage (Salvia ballotiflora). Foraging velocity of deer was affected by the distribution and shape complexity of guajillo (A. berlandieri), which was a major dietary component. In contrast, foraging velocity of goats was affected by the shape complexity of the entire shrub community and by the distribution of ceniza (Leucophylum frutescens), a non-dietary, but prevalent component of the plant community. Results indicate that these two browsing herbivores perceive the same landscape differently.://000077256700005 ISI Document Delivery No.: 143LG Times Cited: 30 Cited Reference Count: 30 Cited References: ADDICOTT JF, 1987, OIKOS, V49, P340 BAILEY DW, 1995, APPL ANIM BEHAV SCI, V45, P183 BELL WJ, 1991, SEARCHING BEHAV BEHA CRIST TO, 1992, FUNCT ECOL, V6, P536 CRIST TO, 1994, OIKOS, V69, P37 DICKE M, 1988, OECOLOGIA, V100, P107 GILLINGHAM MP, 1989, CAN J ZOOL, V67, P1353 GROSS JE, 1995, LANDSCAPE ECOL, V10, P209 HERVEY RL, 1989, THESIS TEXAS A M U C JOHNSON AR, 1992, ECOLOGY, V73, P1968 KOERTH BH, 1991, J RANGE MANAGE, V44, P614 KOLASA J, 1991, ECOLOGICAL HETEROGEN KOTLIAR NB, 1990, OIKOS, V59, P253 LEDUC AL, 1994, LANDSCAPE ECOLOGY, V4, P279 MCGARIGAL K, 1994, FRAGSTATS 2 0 SPATIA MILNE BT, 1988, APPL MATH COMPUT, V27, P67 MILNE BT, 1991, QUANTITATIVE METHODS NAVEH Z, 1994, LANDSCAPE ECOLOGY TH ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 ONEILL RV, 1988, LANDSCAPE ECOL, V2, P63 RUSSELL RW, 1992, LANDSCAPE ECOLOGY, V7, P195 SENFT RL, 1987, BIOSCIENCE, V37, P789 SHIPLEY LA, 1996, FUNCT ECOL, V10, P234 SUGIHARA G, 1990, TRENDS ECOL EVOL, V5, P79 TURCHIN P, 1991, ECOLOGY, V72, P1253 WARD D, 1994, ECOLOGY, V75, P48 WIENS JA, 1989, LANDSCAPE ECOLOGY, V3, P87 WIENS JA, 1995, ECOLOGY, V76, P663 WITH KA, 1994, FUNCT ECOL, V8, P477 WITH KA, 1994, LANDSCAPE ECOL, V9, P25 0921-2973 Landsc. Ecol.ISI:000077256700005zTexas Agr Expt Stn, Uvalde, TX 78801 USA. Etzenhouser, MJ, Texas Agr Expt Stn, 1619 Garner Field Rd, Uvalde, TX 78801 USA.Englishڽ74/Evans, DanielM Turley, NashE Tewksbury, JoshuaJ2013AHabitat edge effects alter ant-guard protection against herbivory 1743-1754Landscape Ecology289Springer NetherlandsHabitat edges Multitrophic species interactions Ant–plant mutualism Insect herbivory Solanum americanum Savannah River Site, South Carolina, USA 2013/11/01+http://dx.doi.org/10.1007/s10980-013-9917-6 0921-2973Landscape Ecol10.1007/s10980-013-9917-6English{? XEycott, Amy Stewart, Gavin Buyung-Ali, Lisette Bowler, Diana Watts, Kevin Pullin, Andrew2012VA meta-analysis on the impact of different matrix structures on species movement rates 1263-1278Landscape Ecology279Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9781-9 0921-297310.1007/s10980-012-9781-9<7&Fabricius, C. Palmer, A. R. Burger, M.2002yLandscape diversity in a conservation area and commercial and communal rangeland in Xeric Succulent Thicket, South Africa531-537Landscape Ecology176varid savanna Biodiversity land use landscape ecology pixel diversity satellite imagery EASTERN CAPE PATTERN ECOSYSTEMSArticleOct\ Nature reserves in Xeric Succulent Thicket of South Africa contain a greater diversity of wildlife and correspondingly a greater diversity of disturbance agents than adjacent, unconserved freehold and communal rangeland. Although more lightly stocked, it is unknown whether protected areas contain a higher diversity of landscape patches (i. e., sub- landscape features such as bush clumps, termitariums, bare patches or animal wallows) which could influence the reflectance value of a single pixel depicting a 20 x 20 m area in a SPOT satellite image, than unconserved land. Our key questions were: How does patch diversity in a nature reserve compare with that on commercial and communal rangeland? Can pixel diversity in a SPOT satellite image be used to quantify these differences? And, is there a correlation between reflectance diversity in a SPOT image and patch diversity on the ground? As a first step, the coefficients of variation (CV) for 10 groups of 12 picture- element (pixel) values of a dry season SPOT satellite image were calculated for two commercial farms and a communal rangeland. The same data were collected on a nature reserve, 50 to 100 m inside the boundary between the reserve and the freehold or communal rangeland. Next, we recorded the variety of 20 x 20 m plots on the ground, also in groups of 12 plots, at the same geographical coordinates as the satellite- based measurements. The means of the satellite-based and ground- based indeces were significantly and positively correlated. In addition, the nature reserve displayed significantly higher pixel CVs than the communal rangeland, and also contained significantly higher ground- based diversity indeces than the freehold, and possibly the communal, rangeland. We postulate that the higher landscape patchiness in the nature reserve is a result of the diversity of disturbances caused by wildlife (especially megaherbivores) coupled with naturally low stocking rates, while the lower diversity in the communally managed rangeland is the result of continuous heavy grazing coupled with intensive fuelwood harvesting. The satellite- based technique is useful for identifying potential sites of high biodiversity, wherein more intensive sampling at a finer scale can be undertaken. It is, however, important to use dry season imagery because of the temporary 'masking' effect of ephemerals during the wet season.://000179774900004 ^ISI Document Delivery No.: 624RN Times Cited: 3 Cited Reference Count: 33 Cited References: *USACERL, 1994, GRASS 4 1 GEOGR RES ACOCKS JPH, 1988, MEMOIRS BOT SURVEY S, V59 AINSLIE A, 1994, POLICIES FEASIBLE SU BAKER WL, 1992, LANDSCAPE ECOL, V7, P291 BELL RHV, 1984, CONSERVATION WILDLIF, P93 CULLINAN VI, 1992, LANDSCAPE ECOL, V7, P211 FABRICIUS C, 2002, IN PRESS J APPL ECOL FORBES RG, 1991, J GRASSLAND SOC S AF, V8, P147 FORMAN RT, 1986, LANDSCAPE ECOLOGY FRANKLIN JF, 1993, ECOL APPL, V3, P202 FRIEDMAN SK, 1992, ENVIRON MANAGE, V16, P363 KERLEY GIH, 1995, ENVIRON MONIT ASSESS, V37, P211 LACOCK G, 1990, S AFRICAN J PHOTOGRA, V15, P231 LAPIN M, 1995, CONSERV BIOL, V9, P1148 LOW AB, 1996, VEGETATION S AFRICA MIDGLEY JJ, 1993, S AFR J BOT, V59, P496 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 MOOLMAN HJ, 1994, BIOL CONSERV, V68, P53 NILSSON C, 1995, J APPL ECOL, V32, P677 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PALMER AR, 1981, THESIS RHODES U GRAH PALMER AR, 1988, S AFRICAN J BOTANY, V54, P309 PALMER AR, 1990, J BIOGEOGR, V17, P35 PINO J, 2000, LANDSCAPE URBAN PLAN, V49, P35 RECHER HF, 1969, AM NAT, V103, P75 RUTHERFORD MC, 1986, MEMOIRS BOT SURVEY S, V54 SCHEINER SM, 1992, ECOLOGY, V73, P1860 SCHLUTER D, 1993, SPECIES DIVERSITY EC, P1 SCHULZE ED, 1994, BIODIVERSITY ECOSYST STUARTHILL GC, 1993, AFRICAN J RANGE FORA, V10, P1 TANSER FC, 1999, J ARID ENVIRON, V43, P477 TILMAN D, 1982, RESOURCE COMPETITION WHITFORD WG, 1978, J ARID ENVIRON, V1, P237 0921-2973 Landsc. Ecol.ISI:000179774900004?Rhodes Univ, Dept Environm Sci, ZA-6140 Grahamstown, South Africa. Range & Forage Inst, Agr Res Council, ZA-6140 Grahamstown, South Africa. Univ Cape Town, So African Frog Atlas Project, Avian Demog Unit, ZA-7700 Rondebosch, South Africa. Fabricius, C, Rhodes Univ, Dept Environm Sci, ZA-6140 Grahamstown, South Africa.EnglishJ<7.Fagan, W. F. Meir, E. Carroll, S. S. Wu, J. G.2001dThe ecology of urban landscapes: modeling housing starts as a density-dependent colonization process33-39Landscape Ecology161density dependence housing multiple spatial scales settling process urbanization DIFFUSION-LIMITED AGGREGATION INVADING ORGANISMS FOULING COMMUNITY NORTH-CAROLINA DISPERSAL STABILITY BEAUFORT SPREADArticleJanData on permits for new housing starts are a key source of information on recent changes in the urban landscape of central Arizona, USA. Drawing primarily on the conceptual parallels between the process of urban expansion and the spatial spread of non-human species, we outline a nested series of 'colonization' models that could be used to study changes in urban landscapes through simulations of housing starts. Within our probabilistic colonization framework, the ecological principle of density-dependence (operating simultaneously on different spatial scales) governs the positioning of new housing units. These simple models afford a great diversity of possible spatial patterns, ranging from tight clustering of houses to urban sprawl to more subtle patterns such as aversion of housing developments from (and aggregation near) different kinds of landscape features. These models can be parameterized from a variety of types of governmental housing data. Ultimately, such a framework could be used to contrast development patterns among cities and identify pertinent operational scales and factors influencing processes associated with urbanization.://000167389900003 $ISI Document Delivery No.: 409NN Times Cited: 5 Cited Reference Count: 46 Cited References: *MAG, 1999, POP GROWTH PROJ *SAS I, 1995, SAS STAT US GUID VER *UN CTR FOR HUM SE, 1996, URB WORLD GLOB REP H ADAMS CC, 1935, ECOLOGY, V16, P316 ADAMS CC, 1938, ECOLOGY, V19, P500 AGRESTI A, 1990, CATEGORICAL DATA ANA ALLEE WC, 1951, SOCIAL LIFE ANIMALS ANDOW DA, 1990, LANDSCAPE ECOL, V4, P177 BANKS JE, 1999, AGR FOREST ENTOMOL, V1, P165 BATTY M, 1994, FRACTAL CITIES BATTY M, 1996, DECISION SUPPORT GIS BURNS EK, 1992, APCG YB, P77 CAPUTO M, 1999, TRIBUNE, V50, A1 CAPUTO M, 1999, TRIBUNE, V50, A5 CERVENY RS, 1998, NATURE, V394, P561 CHAPIN FS, 1968, TRANSPORT RES, V2, P375 COLLINS JP, IN PRESS URBAN ECOLO COLLINS JP, UNPUB J HIST BIOL DEAN TA, 1980, OECOLOGIA, V46, P295 DENSHAM PJ, 1991, GEOGRAPHICAL INFORMA, P403 FAGERSTROM T, 1997, OIKOS, V80, P588 FERGUSON TW, 1997, FORBES, V159, P142 GOBER P, 1998, ARIZONA POLICY CHOIC, P40 GOTWAY CA, 1997, J AGRIC BIOL ENVIR S, V2, P157 GROOM MJ, 1998, AM NAT, V151, P487 HALLS JN, 1994, P 6 INT S SPAT DAT H, V1, P431 HOLMES EE, 1998, AM NAT, V151, P578 KOT M, 1996, ECOLOGY, V77, P2027 LEWIS MA, 1997, SPATIAL ECOLOGY ROLE LUBCHENCO J, 1998, SCIENCE, V279, P491 MCCULLAGH P, 1989, GEN LINEAR MODELS MEIR E, 1996, ECOBEAKER 1 0 ECOLOG MEIR E, 1999, ECOBEAKER 2 0 ECOLOG MESEV TV, 1995, ENVIRON PLANN A, V27, P759 NELDER JA, 1972, J ROYAL STATISTICA A, V135, P370 NOBLE DG, 1991, HOHOKAM ANCIENT PEOP REDMAN CL, 1992, HUMAN IMPACT ENV ANC, P35 SKELLAM JG, 1951, BIOMETRIKA, V38, P196 SUTHERLAND JP, 1977, ECOL MONOGR, V47, P425 SUTHERLAND JP, 1981, AM NAT, V118, P499 VITOUSEK PM, 1997, SCIENCE, V277, P494 WEISNER C, 1997, ACSM ASPRS ANN CONV, V13, P66 WHYTE WH, 1968, LAST LANDSCAPE WINTERER J, 1994, RICE PEST SCI MANAGE, P53 WITTEN TA, 1981, PHYS REV LETT, V47, P1400 WITTEN TA, 1983, PHYS REV B, V27, P5686 0921-2973 Landsc. Ecol.ISI:000167389900003Natl Ctr Ecol Anal & Synth, Santa Barbara, CA 93101 USA. Fagan, WF, Natl Ctr Ecol Anal & Synth, 735 State St Suite 300, Santa Barbara, CA 93101 USA.English <7N ,Fahey, R. T. Lorimer, C. G. Mladenoff, D. J.2012Habitat heterogeneity and life-history traits influence presettlement distributions of early-successional tree species in a late-successional, hemlock-hardwood landscape999-1013Landscape Ecology277public land survey eastern white pine landscape heterogeneity persistence fugitive species white-pine fire regimes red pine natural disturbances forest composition pre-settlement USA vegetation wisconsin michiganAug>In landscapes dominated by late-successional plant communities, early-successional species may lead a tenuous existence, persisting only as fugitives or relying on refuges in marginal habitats to provide a persistent seed source. The objective of this study was to relate fine-scale distributions of early-successional tree species in hemlock-hardwood forests of northern Wisconsin, USA to potential landscape persistence strategies. A special emphasis was placed on eastern white pine (Pinus strobus), a restoration priority in the region. Witness tree data from nineteenth century US Public Land Survey records (encompassing 40,610 km(2) and 106,790 trees) were used with modern environmental data to relate species distributions to habitat characteristics. Early-successional tree species had strong positive associations with marginal habitats such as inclusions of sandy soil and margins of lakes, wetlands, and rivers. Marginal habitats occupied similar to 44 % of the landscape, which may help account for the abundance of early-successional species in our study area relative to other hemlock-hardwood forests. Populations of early-successional species in marginal habitats could also have provided important seed sources for the upland mesic landscape matrix, as > 70 % of the landscape was within 200 m of these habitats. The degree to which early-successional species were limited to marginal habitats largely followed predictions based on species life-history characteristics, except that white pine was more common than expected in upland mesic habitats. These findings illustrate the potential importance of landscape heterogeneity for persistence of early-successional species in late-successional forest landscapes and provide baseline information on habitat associations and landscape dynamics that will be useful in restoration efforts.://000306068200006-969PP Times Cited:0 Cited References Count:65 0921-2973Landscape EcolISI:000306068200006Fahey, RT Morton Arboretum, 4100 Illinois Rte 53, Lisle, IL 60532 USA Morton Arboretum, 4100 Illinois Rte 53, Lisle, IL 60532 USA Univ Wisconsin, Dept Forest & Wildlife Ecol, Russell Labs 226, Madison, WI 53706 USADOI 10.1007/s10980-012-9754-zEnglish |? UFairfax, Russell Fensham, Rod Butler, Don Quinn, Kelvin Sigley, Bernice Holman, James2009@Effects of multiple fires on tree invasion in montane grasslands 1363-1373Landscape Ecology2410There is circumstantial evidence that grasslands on the Bunya Mountains were once maintained by Aboriginal burning, and with lack of fire under European management are being colonised by trees. To assess the efficacy of burning for maintaining grasslands, 119 fires were lit between 1996 and 2006. The total area of unburnt grasslands decreased by 27%, while grasslands burnt at least once decreased by 1%. The density of invading trees was recorded from fixed plots on 23 grasslands burnt between one and six times. Cassinia was virtually eliminated and the density of the Rainforest species guild slowly but continually declined. Acacia irrorata exhibited a humped response, with initial increases resulting from vegetative resprouting and gradual decline with persistent burning. Phyllodinous Acacia and Woodland trees were the least fire sensitive guilds, having stable or increased density with repeated burning. Multi-factor regression modelling detected no significant relationships between changes in woody plant density and the interval between fires, fire intensity, the initial density of large trees, an index of soil moisture, or the cumulative number of fires for any species guild. The survivorship of both Cassinia and Rainforest guilds was significantly lower with summer burning than winter burning, but a seasonal effect of burning was not evident for other guilds. The findings suggest that regardless of fire conditions, frequent burning will reduce the number of adult trees, maintain resprouts in an immature state, facilitate further fire and reduce the rate of grassland loss. Woodland species are especially resilient to fire, and burning to maintain grassy ecosystems will be most successful where the main colonisers are rainforest species and burning is conducted in summer. The findings suggest that the montane grasslands of the Bunya Mountains were maintained by anthropogenic burning and active fire management will prolong their existence.%://BIOSIS:PREV201000014111Times Cited: 0 0921-2973BIOSIS:PREV201000014111:10.1007/s10980-009-9388-y|?B RFaivre, Nicolas Roche, Philip Boer, Matthias M. McCaw, Lachie Grierson, Pauline F.2011Characterization of landscape pyrodiversity in Mediterranean environments: contrasts and similarities between south-western Australia and south-eastern France557-571Landscape Ecology264Apr9Landscape pyrodiversity encapsulates the range of spatiotemporal variability in disturbance by fire. There is a widely-held view that diversity in fire regimes promotes biological diversity (i.e., the Pyrodiversity-Biodiversity paradigm). However, this relationship needs to be examined more carefully as pyrodiversity at the landscape scale remains poorly defined and difficult to quantify. Here, we used a novel approach to analyze landscape pyrodiversity by selecting and quantifying appropriate descriptors of fire variability at the landscape level. We characterized and classified observed fire mosaics at the 1 km scale using temporal attributes (fire frequency, time-since-fire and mean fire interval) and a variety of spatial attributes derived from landscape metrics. We trialed our approach on a 50-year record of fire patterns in two Mediterranean environments; (1) in southern France where fire regimes are dominated by unplanned ('wild'-)fires and (2) in south-west Australia, where fire regimes are dominated by planned fires. We found that the landscape pyrodiversity of both regions was expressed by distinct gradients of both fire frequency and spatial diversity of fire patterns. As expected, the two environments were significantly different in landscape pyrodiversity, with contrasting mean fire frequency and mean time-since-fire patterns. However, we also found similarities between southern France and south-west Australia in the composition and configuration of their spatial fire patterns. Our results show that these two Mediterranean environments form a pyrodiversity continuum despite the disparate management regimes. Our findings also demonstrate that a quantitative characterization of pyrodiversity is central to developing new perspectives and practical tools for biodiversity conservation in fire-prone landscapes.!://WOS:000288807300009Times Cited: 1 0921-2973WOS:00028880730000910.1007/s10980-011-9582-6R?0Alessandra Falcucci Luigi Maiorano Luigi Boitani2007fChanges in land-use/land-cover patterns in Italy and their implications for biodiversity conservation 617-631Landscape Ecology224Land-use/land-cover change - Mediterranean - Re-forestation - Human-dominated landscape - GIS - Biodiversity - Map comparison - Landscape pattern - Spatial analysis - Conservation planning Land-use/land-cover change is the most important factor in causing biodiversity loss. The Mediterranean region has been affected by antropic disturbance for thousands of years, and is, nowadays, one of the most significantly altered hotspots in the world. However, in the last years a significant increase in forest cover has been measured. These new patterns are independent from planned conservation strategies and appear to have a substantial impact on landscapes and biodiversity. We used three land-use/land-cover maps (from 1960 to 2000) covering the Italian peninsula to analyze the pattern of land-use/land-cover change. We measured an increase in forests, especially in mountains, an increase in artificial areas, especially in coastal zones, and a decrease in pastures. Intensively cultivated areas showed a limited decrease while extensively cultivated ones showed a marked decrease. In the same period mammal and bird species followed a similar pattern, with forest birds, ungulates and carnivores increasing, and typically Mediterranean species decreasing. We suggest that our results may provide important information, which could be useful for conservation planning in the entire Mediterranean hotspot. We suggest that an increasing conservation effort should be made to protect the Mediterranean-type forests and scrublands, as well as traditional agricultural practices. Moreover, future conservation efforts should consider the broad socio-political and ecological processes that are most likely to occur across the whole hotspot, especially along coastal areas, and the network of protected areas should be functionally integrated in a conservation strategy that includes the human-dominated landscape. ?Falk, Huettmann2003LBook review, Spatial Modeling in Forest Ecology and Management: A Case Study215-217Landscape Ecology182*http://dx.doi.org/10.1023/A:1024473821551 10.1023/A:1024473821551 This revised version was published online in August 2006 with corrections to the Cover Date Falk Huettmann Email: falk@ucalgary.ca Falk Huettmann1 (1) Geography Dept.-Earth Science, University of Calgary, 2500 University Drive N.W., Calgary AB, T2N 1N4, Canada |?V (Falk, Karla J. Nol, Erica Burke, Dawn M.2011fWeak effect of edges on avian nesting success in fragmented and forested landscapes in Ontario, Canada239-251Landscape Ecology262FebWe studied the effects of anthropogenic edges on predation and parasitism of forest bird nests in an agriculturally fragmented landscape and a continuously forested landscape in Ontario, Canada. Nesting data were collected at 1937 nests across 10 species in the fragmented landscape from 2002-2008, and 464 nests across 4 species in the continuously forested landscape from 2006-2008. Brood parasitism only occurred in the fragmented landscape, and was positively related to the proportion of rural grassland and row crop habitats within 500-m of nests. Daily nest survival was negatively related to the density of roads within 500-m of nests in the fragmented landscape, but was not influenced by distance to anthropogenic edge in either landscape. Predation rates were higher in the fragmented landscape for Ovenbird and Rose-breasted Grosbeak nests, but did not differ between landscapes for Veery and American Redstart nests. Uniformly high predation in the fragmented landscape may be a result of (1) matrix predators that penetrate deep (> 300 m) into the forest interior, or (2) the additive effect of forest-dependent and matrix-associated predators that results in high predation pressure in both edge and interior habitats. Further research focused on the identification of nest predators, their population dynamics, and habitat use is required to understand the underlying mechanisms leading to uniformly high nest predation in fragmented landscapes.!://WOS:000286474900007Times Cited: 1 0921-2973WOS:00028647490000710.1007/s10980-010-9543-5#|?>Fan, Peilei Xie, Yaowen Qi, Jiaguo Chen, Jiquan Huang, Huiqing2014tVulnerability of a coupled natural and human system in a changing environment: dynamics of Lanzhou's urban landscape 1709-1723Landscape Ecology2910DecWe used a multidisciplinary approach to assess the vulnerability of a coupled natural and human (CNH) system in Lanzhou, China. Lanzhou's urban settlement and expansion depended highly on the waterway of the Yellow River and its surrounding geographic setting. Lanzhou's dramatic fluctuation of population was linked with its position as a bordering city between different geographic regions and the controls of ethnic/cultural groups. During the modern phase (1949 to the present), Lanzhou experienced rapid urban expansion, especially after 1979, propelled by industrialization policies by the national government. However, Lanzhou's environment degraded seriously with severe air, water, and soil pollution as well as low green coverage and affected urban climate, especially after the 1970s. We argue that geophysical factors, economic regimes, and institutional factors are all crucial in explaining the dynamics of the CNH system in Lanzhou.!://WOS:000346920900007Times Cited: 0 0921-2973WOS:00034692090000710.1007/s10980-014-0061-8<70Fang, S. F. Gertner, G. Wang, G. X. Anderson, A.2006XThe impact of misclassification in land use maps in the prediction of landscape dynamics233-242Landscape Ecology212hconfusion matrix; forest; land use map; logistic regression; spatial modeling; uncertainty; urban sprawlArticleFeb9Land use maps are widely used in modeling land use change, urban sprawl, and for other landscape related studies. A misclassification confusion matrix for land use maps is usually provided as a measure of their quality and uncertainty. However, this very important information is rarely considered in land use map based studies, especially in modeling landscape dynamics. Ignoring uncertainty of land use maps may cause models to provide unreliable predictions. This study is an attempt to investigate the impact of the accuracy of land use maps used as input for an urban sprawl model. In the study area, the regional confusion matrix has been localized using a topographical map. Based on the regional and local confusion matrices, several error levels have been defined. The results showed that a localized confusion matrix that reflected the characteristics of the study area had error rates that were much different than the regional confusion matrix. The predictions of the probability of urban sprawl based on the land use maps and defined error levels were quite different.://000235866400007 ISI Document Delivery No.: 019WC Times Cited: 0 Cited Reference Count: 8 Cited References: CONGALTON RG, 1999, ASSESSING ACCURACY R DEAL B, 2000, ENVIRON MODEL ASSESS, V5, P47 FANG S, 2005, IN PRESS LAND URBAN FANG SF, 2002, ENVIRON MANAGE, V30, P199 GERTNER GZ, 2002, INT UN FOR RES ORG C LUNETTA RS, 1991, PHOTOGRAMM ENG REM S, V57, P677 STEELE BM, 2003, ENVIRON ECOL STAT, V10, P333 WOLF PR, 1997, ADJUSTMENT COMPUTATI 0921-2973 Landsc. Ecol.ISI:000235866400007Univ Illinois, Dept Nat Resources & Environm Sci, Urbana, IL 61801 USA. USA, Corps Engineers, Construct Engn Res Lab, Champaign, IL 61824 USA. Gertner, G, Univ Illinois, Dept Nat Resources & Environm Sci, W503 Turner Hall,1102 S Goodwin Ave, Urbana, IL 61801 USA. gertner@uiuc.eduEnglish}?*Fang, S. F. Gertner, G. Z. Anderson, A. B.2007pPrediction of multinomial probability of land use change using a bisection decomposition and logistic regression419-430Landscape Ecology223bisection decomposition; conditional probability; land use; logistic regression; multinomial probability; urban development COVER CHANGE; CLASSIFICATION TREES; MODEL; DEFORESTATION; SIMULATION; DYNAMICS; PATTERN; SYSTEMS MarLand use change is an important research area in landscape ecology and urban development. Prediction of land use change (urban development) provides critical information for making the right policies and management plans in order to maintain and improve ecosystem and city functions. Logistic regression is a widely used method to predict binomial probabilities of land use change when just two responses (change and no-change) are considered. However, in practice, more than two types of change are encountered and multinomial probabilities are therefore needed. The existing methods for predicting multinomial probabilities have limits in building multinomial probability models and are often based on improper assumptions. This is due to the lack of proper methodology and inadequate software. In this study, a procedure has been developed for building models to predict the multinomial probabilities of land use change and urban development. The foundation of this procedure consists of a special bisection decomposition system for the decomposition of multiple-class systems to bi-class systems, conditional probability inference, and logistic regression for binomial probability models. A case study of urban development has been conducted to evaluate this procedure. The evaluation results demonstrated that different samples and bisection decomposition systems led to very similar quality and performance in the developed multinomial probability models, which indicates the high stability of the proposed procedure for this case study. ://000244455200007 0921-2973ISI:000244455200007?'7 Farina, A.1993<Editorial comment: From global to regional landscape ecology153-154Landscape Ecology83?North American landscape ecology vs. European landscape ecology|7 Farina, A.1993=Editorial Comment - from Global to Regional Landscape Ecology153-154Landscape Ecology83Sep://A1993MB34000001,Mb340 Times Cited:3 Cited References Count:0 0921-2973ISI:A1993MB34000001English <7> Farina, A.1997XLandscape structure and breeding bird distribution in a sub-Mediterranean agro-ecosystem365-378Landscape Ecology126Aulella watershed; Tuscany; sub-Mediterranean agro-ecosystem; Global Positioning System; Geographic Information Systems COMMUNITY STRUCTURE; SMALL MAMMALS; HABITAT; DYNAMICS; PATTERNS; ECOLOGYArticleDecRichness, abundance and distribution of birds were investigated in the Aulella watershed, a mountainous area of 300 km(2), located in the extreme northwestern corner of Tuscany, Italy in spring and summer, 1995. The study area encompasses five vegetation types (from Mediterranean maqui to upland beech forest) and three main land use categories (woodlands, mixed cultivated + urban areas, montane prairies). The recent history of land abandonment in the study area has produced a rapid expansion of shrubland and woodland, reducing cultivated areas to small patches interspersed in a woodland matrix. Richness, abundance and distribution of birds recorded at 414 points, randomly selected along secondary roads, and located using a Global Positioning System (GPS), were compared with topography, vegetation type and land use in a Geographic Information Systems (GIS) with a grid cell resolution of 200 x 200 m. Bird richness (55 species in all) and abundance are correlated: (a) negatively with the increasing altitude and increasing distance from cultivated areas; (b) positively with the increasing distance from woodlands and mountain prairies. Slope orientation appears to have a negligible effect on bird assemblages. Bird richness and abundance are significantly correlated with vegetation type. Cultivated areas support the highest bird richness and abundance that increase with patch size of the cultivated areas. Local extinction and/or reduction in within-species abundance of birds are expected to continue if the process of land abandonment continues.://000077684400002 QISI Document Delivery No.: 150UR Times Cited: 34 Cited Reference Count: 28 Cited References: ANGELSTAM P, 1987, OIKOS, V50, P123 BENNETT AF, 1990, LANDSCAPE ECOL, V4, P109 CAREY AB, 1992, ECOL MONOGR, V62, P223 FAHRIG L, 1985, ECOLOGY, V66, P1762 FARINA A, 1985, ATT 2 C NAZ SOC IT E, P679 FARINA A, 1987, ACTA ECOL OECOL GEN, V8, P145 FARINA A, 1987, B ZOOL, V54, P243 FARINA A, 1988, B ZOOL, V55, P327 FARINA A, 1989, AGR ECOSYST ENVIRON, V27, P177 FARINA A, 1991, OPTIONS MEDITERRANEE, V15, P121 FARINA A, 1995, CULTURAL LANDSCAPE U, P60 FARINA A, 1995, LANDSCAPE URBAN PLAN, V31, P269 FERRARINI E, 1982, B MUS S NAT LUNIGIAN, V2, P5 FORMAN R, 1995, LAND MOSAICS ECOLOGY GALLI AE, 1976, AUK, V93, P356 GUTZWILLER KJ, 1992, LANDSCAPE ECOL, V6, P293 HULSE DW, 1989, MCGIS 2 0 GEOGRAPHIC HUNTER JE, 1995, CONDOR, V97, P684 ILLNER H, 1992, B MUS SCI NAT LUNIGI, V8, P13 JOHNSTON CA, 1987, LANDSCAPE ECOLOGY, V1, P45 MUELLERDOMBOIS D, 1974, AIMS METHODS VEGETAT PICKETT STA, 1995, SCIENCE, V269, P331 PIELOU EC, 1977, MATH ECOLOGY ROBBINS CS, 1967, WILDLIFE, V102 SHANNON CE, 1948, BELL SYST TECH J, V27, P379 SZACKI J, 1991, LANDSCAPE ECOL, V5, P219 WIENS JA, 1993, OIKOS, V66, P369 ZOU XM, 1992, LANDSCAPE ECOL, V6, P221 0921-2973 Landsc. Ecol.ISI:000077684400002\Lunigiana Museum Nat Hist, Aulla, Italy. Farina, A, Lunigiana Museum Nat Hist, Aulla, Italy.English"<7Farina, A. Belgrano, A.20066The eco-field hypothesis: Toward a cognitive landscape5-17Landscape Ecology211biosemiotic; cognitive landscape; eco-field; information theory; Umwelt HETEROGENEOUS ENVIRONMENTS; SPATIAL HETEROGENEITY; MOVEMENT CORRIDORS; ECOLOGICAL-SYSTEMS; FORAGING BEHAVIOR; HABITAT PATCHES; CONNECTIVITY; INFORMATION; SCALE; PEROMYSCUSReviewJanCognition is recognized as an essential component of the living strategies of organisms and the use of cognitive approaches based on an organismic-centered-view is discussed as a strategy to aid the advancement of landscape ecology to a more independent scientific discipline. The incorporation of the theory of information, the theory of meaning and the Umwelt, and the biosemiotic models into the landscape ecology framework is described as the necessary step to create a common paradigmatic background and operational tools to develop basis for a cognitive landscape ecology. Three cognitive landscapes (neutrality-based landscape, individual-based landscape and observer-based landscape) have been described as the result of distinctive mechanisms to extract information from a cognitive matrix based on a growing literature of (bio)semiotic exchange. The eco-field hypothesis is presented as a new possibility to describe landscape processes according to an organismic-centered-view. The eco-field is defined as a spatial configuration carrier of a specific meaning perceived when a specific living function is activated. A species-specific cognitive landscape is composed of all the spatial configurations involved for all the living functions for a particular organism. Eco-field hypothesis offers a detailed vision of (habitat) environmental requirements and creates a novel conceptual bridge between niche, habitat, Umwelt and the methodological approaches of spatial ecology. Finally the eco-field hypothesis promises a new testing ground for experimental investigations in landscape ecology and in related disciplines including environmental psychology, cognitive ethology, cultural ecology, landscape aesthetics, design and planning.://000235887300002 SISI Document Delivery No.: 020DD Times Cited: 0 Cited Reference Count: 141 Cited References: ANDREASSEN HP, 1996, J APPL ECOL, V33, P63 ANTROP M, 1998, LANDSCAPE URBAN PLAN, V41, P155 APPLETON J, 1975, EXPERIENCE LANDSCAPE BARBIERI M, 2001, REV SEMIOTICS, V134, P1 BARBIERI M, 2003, HIST PHIL LIFE SCI, V25, P243 BARBIERI M, 2003, ORGANIC CODES BASCOMPTE J, 1997, LANDSCAPE ECOL, V12, P213 BASTIAN O, 2001, LANDSCAPE ECOL, V16, P757 BATESON G, 1973, STEPS ECOLOGY MIND BAUDRY J, 2003, LANDSCAPE ECOL, V18, P303 BEECHAM JA, 2001, BIOSYSTEMS, V61, P55 BEER CG, 1996, BEHAV P, V35, P215 BEIER P, 1998, CONSERV BIOL, V12, P1241 BENHAMOU S, 1996, BEHAV P, V35, P113 BENNETT ATD, 1996, J EXP BIOL, V199, P219 BEUGNON G, 1996, BEHAV PROCESS, V35, P55 BINGMAN VP, 2002, CURR OPIN NEUROBIOL, V12, P745 BIRO D, 2002, J EXP BIOL, V205, P3833 BISSONETTE JA, 1997, WILDLIFE LANDSCAPE E BISSONETTE JA, 2003, LANDSCAPE ECOLOGY RE BOURASSA SC, 1990, ENVIRON BEHAV, V22, P787 BOURASSA SC, 1991, AESTHETICS LANDSCAPE BRUMM H, 2002, ANIM BEHAV 5, V63, P891 CODY ML, 1985, HABITAT SELECTION BI, P3 CRIST TO, 1994, OIKOS, V69, P37 CRISTOL DA, 2003, ANIM BEHAV 2, V66, P317 CROPLEY DH, 1998, MEASUREMENT, V24, P237 CROPLEY DH, 1998, MEASUREMENT, V24, P249 DANCHIN E, 2004, SCIENCE, V305, P487 DANIELSON BJ, 2000, LANDSCAPE ECOL, V15, P323 DAY RL, 2003, PERSPECT BIOL MED, V46, P80 DEELY J, 2001, UMWELT SEMIOTICS, V134, P125 DICKE M, 2001, BIOCHEM SYST ECOL, V29, P981 DIFFENDORFER JE, 1995, ECOLOGY, V76, P827 DUKAS R, 1998, COGNITIVE ECOLOGY EV, P405 EDWARDS GR, 1996, APPL ANIM BEHAV SCI, V50, P147 FARINA A, 1993, LANDSCAPE ECOLOGY, V8, P153 FARINA A, 2004, ECOL RES, V19, P107 FARINA A, 2005, BIOSYSTEMS, V79, P235 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FORMAN RTT, 2003, ROAD ECOLOGY SCI SOL GALEA LAM, 1996, J EXP BIOL, V199, P195 GARDNER RH, 1991, QUANTITATIVE METHODS, P289 GIBSON JJ, 1979, ECOLOGICAL APPROACH GIL D, 2002, TRENDS ECOL EVOL, V17, P133 GOLLEY FB, 1993, HIST ECOSYSTEM CONCE GOODWIN BJ, 2003, LANDSCAPE ECOL, V18, P687 GRACE SL, 1995, OIKOS, V72, P99 GUTZWILLER KJ, 2002, APPL LANDSCAPE ECOLO HANSKI I, 1999, OIKOS, V87, P209 HANSKI IA, 1997, METAPOPULATION BIOL HARRISON RL, 1992, CONSERV BIOL, V6, P293 HAY GJ, 2001, LANDSCAPE ECOL, V16, P471 HE FL, 2002, LANDSCAPE ECOL, V17, P559 HEALY S, 2000, TRENDS ECOL EVOL, V15, P22 HIROSE N, 2002, COGNITIVE SYSTEMS RE, V3, P289 HJERMANN DO, 2000, ECOLOGY, V85, P1462 HOBBS R, 1997, LANDSCAPE URBAN PLAN, V37, P1 HOBBS RJ, 1994, PACIFIC CONSERVATION, V1, P170 HOFFMEYER J, 1997, EUROPEAN J SEMIOTIC, V9, P335 INGLIS IR, 2001, ANIM BEHAV 3, V62, P543 INGOLD T, 2000, PERCEPTION ENV ESSAY JI LJ, 2000, J PERS SOC PSYCHOL, V78, P943 JOHNSON AR, 1992, LANDSCAPE ECOL, V7, P63 JORDAN F, 2003, LANDSCAPE ECOL, V18, P83 JUN J, 2003, EVOL ECOL RES, V5, P297 KARBAN R, 2001, BIOCHEM SYST ECOL, V29, P995 KEITT TH, 1997, CONSERV ECOL, V1 KERKHOFF AJ, 2000, CONSERV ECOL, V4 KERR B, 2003, J THEOR BIOL, V220, P169 KOLASA J, 1991, ECOLOGICAL HETEROGEN KRAMPEN M, 1992, BIOSEMIOTICS SEMIOTI, P213 KULL K, 1998, SEMIOTICA, V120, P299 KULL K, 1998, SIGN SYSTEMS STUDIES, V26, P344 KULL K, 2000, SIGN SYSTEMS STUDIES, V28, P326 KULL K, 2005, J BIOSEMIOTICS, V1, P1 LIMA SL, 1996, TRENDS ECOL EVOL, V11, P131 LIU J, 2002, INTEGRATING LANDSCAP LUYMES DT, 1995, LANDSCAPE URBAN PLAN, V33, P391 MABRY KE, 2002, LANDSCAPE ECOL, V17, P629 MACARTHUR RH, 1967, THEORY ISLAND BIOGEO MANNING AD, 2004, OIKOS, V104, P621 MATTHYSEN E, 2002, LANDSCAPE ECOL, V17, P509 MILLER C, 2000, LANDSCAPE ECOL, V15, P145 MILNE BT, 1992, AM NAT, V139, P32 MITCHELL MS, 2003, LANDSCAPE ECOLOGY RE, P93 NAIMAN RJ, 1988, BIOSCIENCE, V38, P753 NAIMAN RJ, 1997, BIOSCIENCE, V47, P521 NASSAUER JI, 1995, LANDSCAPE ECOL, V10, P229 NAVEH Z, 1984, LANDSCAPE ECOLOGY NAVEH Z, 1995, LANDSCAPE URBAN PLAN, V32, P43 NAVEH Z, 2000, MULTIFUNCTIONAL LAND, P27 NICHOLLS CI, 2001, LANDSCAPE ECOL, V16, P133 NORRIS DR, 2004, SCIENCE, V306, P2249 NOTH W, 2005, J BIOSEMIOTICS, V1, P183 ODLINGSMEE FJ, 1988, ROLE BEHAV EVOLUTION ODLINGSMEE FJ, 2003, NICHE CONSTRUCTION N ODUM EP, 1977, SCIENCE, V195, P1289 ONEILL RV, 1999, ISSUES LANDSCAPE ECO, P1 ONEILL RV, 2001, ECOLOGY, V82, P3275 PAPI F, 1991, ORIENTATION BIRDS, P52 PETHERICK N, 2000, W GEOGRAPHY, V10, P9 PICKETT STA, 1995, SCIENCE, V269, P331 PLOWRIGHT RC, 1985, OIKOS, V44, P459 REAL LA, 1993, TRENDS ECOL EVOL, V8, P413 REINHARD J, 2004, NATURE, V427, P411 RISSER PG, 1984, SPECIAL PUBBLICATION, V2 RISSER PG, 1989, ECOLOGY ARABLE LAND, P247 SCHOOLEY RL, 2001, LANDSCAPE ECOL, V16, P267 SEBEOK TA, 1972, PERSPECTIVES ZOOSEMI SEBEOK TA, 1991, BIOSEMIOTICS SEMIOTI SEBEOK TA, 1995, 17 I ADV STUD COLL B SHAROV AA, 1998, SEMIOTICA, V120, P403 SHETTLEWORTH SJ, 2001, ANIM BEHAV 2, V61, P277 SIMBERLOFF D, 1992, CONSERV BIOL, V6, P493 SOUTHWICK EE, 1995, AM NAT, V146, P748 STAUFFER D, 1985, INTRO PERCOLATION TH STONIER T, 1990, INFORMATION INTERNAL STONIER T, 1996, BIOSYSTEMS, V38, P135 TRESS B, 2001, LANDSCAPE URBAN PLAN, V57, P137 TSCHARNTKE T, 2001, BIOCHEM SYST ECOL, V29, P1025 TURNER MG, 1987, LANDSCAPE HETEROGENE TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 2001, LANDSCAPE ECOLOGY TH UEXKULL JV, 1982, SEMIOTICA, V42, P25 UEXKULL JV, 1992, SEMIOTICA, V89, P319 ULRICH RS, 1983, BEHAV NATURAL ENV, P85 URI M, 1995, COPING UNCERTAINTY WALLACE LL, 1995, LANDSCAPE ECOL, V10, P75 WARD D, 1994, ECOLOGY, V75, P48 WELLNITZ TA, 2001, LANDSCAPE ECOL, V16, P111 WHITTINGTON J, 2004, ECOLOGY SOC, V9, P4 WICKLER W, 1971, MIMIKRY WIENS JA, 1992, LANDSCAPE ECOL, V7, P149 WIENS JA, 1993, OIKOS, V66, P369 WIENS JA, 1995, MOSAIC LANDSCAPES EC, P1 WITH KA, 1995, ECOLOGY, V76, P2446 WU JG, 2002, ECOL MODEL, V153, P1 WU JG, 2002, LANDSCAPE ECOL, V17, P355 ZIFF RM, 1986, PHYS REV LETT, V56, P545 ZONNEVELD IS, 1995, LAND ECOLOGY 0921-2973 Landsc. Ecol.ISI:000235887300002Univ Urbino, Inst Biomath, I-61029 Urbino, Italy. Natl Ctr Genome Resources, Santa Fe, NM 87505 USA. Farina, A, Univ Urbino, Inst Biomath, I-61029 Urbino, Italy. farina@uniurb.itEnglish? QFarina, Almo Lattanzi, Emanuele Malavasi, Rachele Pieretti, Nadia Piccioli, Luigi2011[Avian soundscapes and cognitive landscapes: theory, application and ecological perspectives 1257-1267Landscape Ecology269Springer NetherlandsEarth and Environmental ScienceOThe soundscape is proposed as a phenomenological entity with which to investigate environmental complexity. In particular, the avian soundtope, which is defined as a place in which sound is intentionally structured by different bird species, is regarded as an agency acting to achieve several goals. In fact, the soundtope could be viewed as a special case of an eco-field used by birds, not only to establish territorial ownership and patrol an area but also as a means of locating and evaluating the availability of many other material and immaterial resources. The meaning of the multifaceted acoustic pattern produced by bird communities during the breeding season is discussed here under the acoustic niche hypothesis in terms of community coalescence and the permanent establishment of an inter-specific communication network. Furthermore, the spatial and temporal dimensions of a bird soundscape have also been analyzed and discussed in terms of their relationship with environmental proxies. A new Acoustic Complexity Index (ACI), coupled with the implementation (ACI plug-in) of a specific sound editor (WaveSurfer©), is proposed as a way of processing sound data efficiently, thus providing new opportunities to use the bird soundscape signature for landscape characterization and describing the ecological dynamics of long-term monitoring schemes.+http://dx.doi.org/10.1007/s10980-011-9617-z 0921-297310.1007/s10980-011-9617-zZ|? kFarwig, N. Bailey, D. Bochud, E. Herrmann, J. D. Kindler, E. Reusser, N. Schuepp, C. Schmidt-Entling, M. H.2009aIsolation from forest reduces pollination, seed predation and insect scavenging in Swiss farmland919-927Landscape Ecology247Aug[Habitat loss and fragmentation lead to changes in species richness and composition which may affect ecosystem services. Yet, few studies distinguish between the effects of habitat loss and isolation, or how multiple ecosystem services may be affected simultaneously. We investigated the effects of variation in cover of woody and open semi-natural habitats and isolation from forest on the relative functioning of pollination, seed predation and insect scavenging in agricultural landscapes. We established 30 sites in grassland locations in the Swiss plateau around Berne. The sites varied independently in their isolation from forest edges, in the percentage of woody habitats and in the percentage of open semi-natural habitats in the surrounding landscape (500 m radius). We experimentally exposed primroses, sunflower seeds and cricket corpses during spring 2008. None of the three studied services was affected by variation in woody or open semi-natural habitat cover. However, the proportion of flowers setting seed was significantly reduced by isolation from forest. Further, seed predation and insect scavenging were significantly lower at isolated sites than at sites connected to woody habitat. This pattern was particularly pronounced for seeds and insect corpses that were enclosed by wire netting and thus inaccessible to vertebrates. Thus, all three studied services responded quite similarly to the landscape context. The observed small-scale determination of seed set, seed predation and insect scavenging contrasts with larger-scale determination of pollination and insect pest control found in other studies.://000268430900006Farwig, Nina Bailey, Debra Bochud, Estee Herrmann, John D. Kindler, Eveline Reusser, Niklaus Schueepp, Christof Schmidt-Entling, Martin H. 0921-2973ISI:00026843090000610.1007/s10980-009-9376-2=<7 -Fauth, P. T. Gustafson, E. J. Rabenold, K. N.2000]Using landscape metrics to model source habitat for Neotropical migrants in the midwestern US621-631Landscape Ecology157Cagricultural landscapes bird abundance GIS landscape structure midwestern US multivariate models Neotropical migrants reproductive success source-sink dynamics wood thrushes MIGRATORY BIRDS FOREST FRAGMENTATION REPRODUCTIVE SUCCESS NESTING SUCCESS DECIDUOUS FOREST TEMPERATE FOREST SPATIAL PATTERN POPULATION DYNAMICS SCALEArticleOctSize of a forest patch is a useful predictor of density and reproductive success of Neotropical migratory birds in much of eastern North America. Within these forested landscapes, large forest tracts appear to be sources - fragments in which surpluses of offspring are produced and can potentially colonize new fragments including woodlot sinks where reproduction fails to balance adult mortality. Within agricultural landscapes of the midwestern U.S., where forests are severely fragmented, high levels of brood parasitism by brown-headed cowbirds (Molothrus ater) and intense predation on nests generally result in low reproductive success for Neotropical migrants regardless of forest size. In some midwestern U.S. landscapes, however, the variation in reproductive success among forest fragments suggests that 'source' habitat could still exist for Neotropical migrants. We used vegetation, fragment and landscape metrics to develop multivariate models that attempt to explain the variation in abundance and reproductive success of Neotropical migrants nesting in an agricultural landscape in northern Indiana, USA. We produced models that reasonably described the pattern of species richness of Neotropical migrants and the abundance of wood thrushes (Hylocichla mustelina) and several other Neotropical migrant species within 14 forest fragments. In contrast, we were unable to produce useful models of the reproductive success of wood thrushes breeding in the same forest fragments. Our results suggest that (1) abundance patterns of Neotropical migrants are probably influenced by both landscape- and fragment-scale factors; (2) multivariate analyses of Neotropical migrant abundance are not useful in modeling the corresponding patterns of reproductive success; and (3) the location of any remaining 'source' habitat for Neotropical migrants breeding within agricultural landscapes in North America will be difficult to predict with indirect measures such as vegetation composition or landscape context. As a result, the potential for developing conservation strategies for Neotropical migrants will be limited without labor-intensive, direct measurements of demographic parameters.://000089421500003 ISI Document Delivery No.: 356AV Times Cited: 17 Cited Reference Count: 60 Cited References: *SAS I, 1995, SAS US GUID STAT VER AMBUEL B, 1983, ECOLOGY, V64, P1057 ASKINS RA, 1990, CURRENT ORNITHOLOGY, V7, P1 BLAKE JG, 1987, ECOLOGY, V68, P1724 BRAWN JD, 1996, ECOLOGY, V77, P3 BRITTINGHAM MC, 1983, BIOSCIENCE, V33, P31 BRITTINGHAM MC, 1996, J FIELD ORNITHOL, V67, P406 BURKE DM, 1998, AUK, V115, P96 DEGRAAF RM, 1995, NEOTROPICAL MIGRATOR DONOVAN TM, 1995, CONSERV BIOL, V9, P1380 FAABORG J, 1995, ECOLOGY MANAGEMENT N, P357 FAUTH PT, 1997, THESIS PURDUE U W LA FAUTH PT, 2000, AUK, V117, P194 FLATHER CH, 1996, ECOLOGY, V77, P28 FREEMARK KE, 1986, BIOL CONSERV, V36, P115 FREEMARK KE, 1995, ECOLOGY MANAGEMENT N, P381 FRIESEN L, 1999, CONSERV BIOL, V13, P338 GALE GA, 1997, CONSERV BIOL, V11, P246 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GIBBS JP, 1990, CONSERV BIOL, V4, P193 GUSTAFSON EJ, 1994, AM MIDL NAT, V131, P24 GUSTAFSON EJ, 1994, LANDSCAPE URBAN PLAN, V29, P117 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HAHN DC, 1995, CONSERV BIOL, V9, P1415 HILL GE, 1988, CONDOR, V90, P379 HOLMES RT, 1986, ECOL MONOGR, V56, P201 HOOVER JP, 1995, AUK, V112, P146 HUTTO RL, 1986, AUK, V103, P593 JAMES FC, 1970, AUDUBON FIELD NOTES, V24, P727 JAMES FC, 1990, ANNU REV ECOL SYST, V21, P129 LAYTON SM, 1986, CONDOR, V88, P206 LILLESAND TM, 1987, REMOTE SENSING IMAGE LYNCH JF, 1984, BIOL CONSERV, V28, P287 MAYFIELD HF, 1975, WILSON BULL, V87, P456 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PATON PWC, 1994, CONSERV BIOL, V8, P17 PEARSON SM, 1993, LANDSCAPE ECOL, V8, P3 PORNELUZI P, 1993, CONSERV BIOL, V7, P618 PROBST JR, 1987, AUK, V104, P234 PROBST JR, 1993, LANDSCAPE ECOL, V8, P257 PULLIAM HR, 1988, AM NAT, V132, P652 ROBBINS CS, 1989, WILDLIFE MONOGRA JUL, P1 ROBINSON SK, 1993, EFFECTS FOREST FRAGM ROBINSON SK, 1995, SCIENCE, V267, P1987 ROBINSON SK, 1999, IN PRESS ECOLOGY MAN ROTH RR, 1993, AUK, V110, P37 ROTHSTEIN SI, 1988, ANIM BEHAV, V36, P73 SAUER JR, 1997, N AM BREEDING BIRD S SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SMITH AT, 1990, CONSERV BIOL, V4, P320 SOKAL RR, 1981, BIOMETRY STEELE BB, 1992, ORNIS SCAND, V23, P33 TEMPLE SA, 1988, CONSERV BIOL, V2, P340 TRINE CL, 1998, CONSERV BIOL, V12, P576 TURNER SJ, 1991, QUANTITATIVE METHODS, P17 VILLARD MA, 1995, ECOLOGY, V76, P27 WHITCOMB RF, 1981, FOREST ISLAND DYNAMI, P125 WIENS JA, 1987, OIKOS, V48, P132 WIENS JA, 1994, IBIS, V137, P97 0921-2973 Landsc. Ecol.ISI:000089421500003nPurdue Univ, Dept Biol Sci, W Lafayette, IN 47907 USA. Fauth, PT, Drew Univ, Dept Biol, Madison, NJ 07940 USA.English n|?@ 8Feist, B. E. Steel, E. A. Jensen, D. W. Sather, D. N. D.2010Does the scale of our observational window affect our conclusions about correlations between endangered salmon populations and their habitat?727-743Landscape Ecology255Differences in the strength of species-habitat relationships across scales provide insights into the mechanisms that drive these relationships and guidance for designing in situ monitoring programs, conservation efforts and mechanistic studies. The scale of our observation can also impact the strength of perceived relationships between animals and habitat conditions. We examined the relationship between geographic information system (GIS)-based landscape data and Endangered Species Act-listed anadromous Pacific salmon (Oncorhynchus spp.) populations in three subbasins of the Columbia River basin, USA. We characterized the landscape data and ran our models at three spatial scales: local (stream reach), intermediate (6th field hydrologic units directly in contact with a given reach) and catchment (entire drainage basin). We addressed three questions about the effect of scale on relationships between salmon and GIS representations of landscape conditions: (1) at which scale does each predictor best correlate with salmon redd density, (2) at which scale is overall model fit maximized, and (3) how does a mixed-scale model compare with single scale models (mixed-scale meaning models that contain variables characterized at different spatial scales)? We developed mixed models to identify relationships between redd density and candidate explanatory variables at each of these spatial scales. Predictor variables had the strongest relationships with redd density when they were summarized over the catchment scale. Meanwhile strong models could be developed using landscape variables summarized at only the local scale. Model performance did not improve when we used suites of potential predictors summarized over multiple scales. Relationships between species abundance and land use or intrinsic habitat suitability detected at one scale cannot necessarily be extrapolated to other scales. Therefore, habitat restoration efforts should take place in the context of conditions found in the associated watershed or landscape.!://WOS:000276609800006Times Cited: 0 0921-2973WOS:00027660980000610.1007/s10980-010-9458-1<7"Feoli, E. Vuerich, L. G. Woldu, Z.2002fProcesses of environmental degradation and opportunities for rehabilitation in Adwa, Northern Ethiopia315-325Landscape Ecology174^correlation environment geomorphology land cover land use overlap process vegetation HIGHLANDSArticleH There are only a few studies of land cover-land use changes which provide an integrated assessment of the biophysical and societal causes and consequences of environmental degradation in Ethiopia. Our objectives were to determine the status of the environmental degradation, analyse and evaluate the relationships among vegetation, geomorphological and socio-economic factors contributing to environmental degradation, and propose opportunities for rehabilitation of these natural resources. Field and other environmental data in northern Ethiopia and those acquired by remote sensing techniques were used to accomplish these objectives. These were integrated with socio-economic data obtained from official sources using a Geographic Information System (GIS). Spatial information such as the percent of land cover-land use types and geomorphological categories, and the percent of each land cover-land use type in the geomorphological categories were calculated using Geographic Information System (GIS). The three most dominant features of the geomorphological categories (93.0%) are scarps and denuded rock slopes, erosion surfaces and badlands, while the three most dominant features in the land cover-land use types (71.3%) are croplands, open woodlands and bushlands. Badlands account for 38.7% of the geomorphological units and 41.8% of the croplands currently occur on badlands. Simple and partial correlation analyses were applied to explore the extent of the interaction between the anthropogenic and the natural system. The anthropogenic system is influenced by elevation, which is positively correlated with human population and livestock densities and area of croplands. The natural system finds its place only on steep slopes as shown by the positive correlation between woodland, slope, high potential erosion, scarps and denudational rock slopes. The study indicates that agriculture in the study area is in a critical environmental situation. A change of paradigm in land-use and development is needed to encourage participation of the landowners and users in the efforts to conserve the vegetation and the soil. This study provides sound options that could be used to rehabilitate the vegetation directly and to alleviate the current pressure on the land and improve human welfare indirectly. Matching the human and livestock densities with the carrying capacity of the land through recruitment of the surplus labour force for a modern economy, resettlement, off-farm employment and intensification of agriculture are the long and short-term actions that may contribute to the rehabilitation of the degraded areas.://000178391000002 <ISI Document Delivery No.: 600LF Times Cited: 1 Cited Reference Count: 28 Cited References: *CSA, 1998, 1994 POP HOUS CENS E *ITC, 1993, ILWIS 1 4 US MAN *WORLD BANK, 1992, WORLD DEV REP 1992 G ALMEIDA MD, 1954, SOME RECORDS ETHIOPI ALVAREZ F, 1970, PORTUGUESE EMBASSY A BOJO J, 1995, LAND DEGRADATION REH CARL T, 1992, ECOLOGICAL CHANGE, V5, P91 CROVELLO TJ, 1981, TAXON, V30, P563 EGZIABHER TB, 1998, PLANT BIOSYST, V132, P39 ELIAS E, 2000, MANAGING AFRICAS SOI, V13 EWEG HPA, 1998, LAND DEGRAD DEV, V9, P529 FATTOVICH R, 1997, SERIE ETIOPICA, V5, P81 FEOLI E, 1995, RIV ARG SUBTROPICALE, V89, P223 FEOLI E, 1996, SPATIAL ANAL PERSPEC, P175 LANZ TJ, 1996, AFR TODAY, V43, P157 MACHADO MJ, 1995, CSIC MONOGRAPH MADRI, V3, P163 MCDOUGALL I, 1975, NATURE, V254, P207 MELISSA L, 1991, POVERTY ENV DEV COUN, P48 PICHISERMOLLI R, 1957, WEBBIA, V13, P15 RAHMATO D, 1994, LAND TENURE LAND POL, P1 SHIFERAW B, 1997, FORUM DEV STUDIES, V2, P277 SUSAN J, 1991, DEV ENV SUSTAINING P, P59 THORNTHWAITE CW, 1948, GEOGR REV, V38, P55 VIRGO JR, 1977, GEODERMA, V20, P131 WALTER H, 1985, VEGETATION EARTH ECO WILSON RT, 1977, WEBBIA, V32, P236 WOLDU Z, 1986, VEGETATIO, V67, P3 ZELEKE G, 2000, GEOGRAPHICA BERNESIA 0921-2973 Landsc. Ecol.ISI:000178391000002Univ Addis Ababa, Natl Herbarium, Dept Biol, Addis Ababa, Ethiopia. Univ Trieste, Dept Biol, I-34127 Trieste, Italy. Woldu, Z, Univ Addis Ababa, Natl Herbarium, Dept Biol, POB 3434, Addis Ababa, Ethiopia.English<7 Fernandez, N.2005ISpatial patterns in European rabbit abundance after a population collapse897-910Landscape Ecology208Kconservation; epidemics; habitat heterogeneity; Mediterranean ecosystems; Oryctolagus cuniculus; population density; predictive abundance models; spatial scale DONANA-NATIONAL-PARK; VIRAL HEMORRHAGIC-DISEASE; ORYCTOLAGUS-CUNICULUS; IBERIAN LYNX; WILD RABBIT; VEGETATION STRUCTURE; RELATIVE ABUNDANCE; SOUTHERN SPAIN; ECOLOGY; SCALEArticleDecAssessing the associations between spatial patterns in population abundance and environmental heterogeneity is critical for understanding various population processes and for managing species and communities. This study evaluates responses in the abundance of the European rabbit (Oryctolagus cuniculus), an important prey for predators of conservation concern in Mediterranean ecosystems, to environmental heterogeneity at different spatial scales. Multi-scale habitat models of rabbit abundance in three areas of Donana, south-western Spain, were developed using a spatially extensive dataset of faecal pellet counts as an abundance index. The best models included habitat variables at the three spatial scales examined: distance from lagoons (broad scale), mean landscape shrub coverage and interspersion of pastures (home-range scale), and shrub and pasture cover (microhabitat scale). These variables may well have been related to the availability of food and refuge for the species at the different scales. However, the models' fit to data and their predictive accuracy for an independent sample varied among the study regions. Accurate predictions in some areas showed that the combination of variables at various spatial scales can provide a reliable method for assessing the abundance of ecologically complex species such as the European rabbit over large areas. On the other hand, the models failed to identify abundance patterns in a population that suffered the strongest demographic collapse after viral epidemics, underlining the difficulty of generalizing this approach. In the latter case, factors difficult to implement in static models such as disease history and prevalence, predator regulation and others may underlie the lack of association. Habitat models can provide useful guidelines for the management of landscape attributes relevant to rabbits and help improve the conservation of Mediterranean communities. However, other influential factors not obviously related to environmental heterogeneity should also be analyzed in more detail.://000233036400001 ISI Document Delivery No.: 980RR Times Cited: 3 Cited Reference Count: 65 Cited References: AARS J, 2000, AM NAT, V155, P252 AKAIKE H, 1973, 2 INT S INF THEOR, P267 BISSONETTE JA, 1997, WILDLIFE LANDSCAPE E, P368 BOYCE MS, 1999, TRENDS ECOL EVOL, V14, P268 BROWN JH, 1995, ECOLOGY, V76, P2028 BURNHAM KP, 1998, MODEL SELECTION INFE BUSTAMANTE J, 1997, BIOL CONSERV, V80, P153 CALVETE C, 1997, J ZOOL 2, V241, P271 CALVETE C, 1999, THESIS U ZARAGOZA ZA CHAMBERS JM, 1993, STAT MODELS S COOKE BD, 2002, REV SCI TECH OIE, V21, P347 COOPS NC, 2002, LANDSCAPE ECOL, V17, P173 DELIBES M, 1981, P WORLD LAG C U GUEL, P614 DWYER G, 1990, ECOL MONOGR, V60, P423 FA JE, 2001, ECOL MODEL, V144, P121 FERNANDEZ N, 2003, ECOL APPL, V13, P1310 FERNANDEZDELGAD.C, 1997, PRINCIPLES CONSERVAT, P458 FERRER M, 1993, AGUILA IMPERIAL FISHER RN, 2002, CONSERV BIOL, V16, P205 FLATHER CH, 1996, ECOLOGY, V77, P28 GOMEZSAL A, 1999, J VEG SCI, V10, P365 GUISAN A, 2000, ECOL MODEL, V135, P147 HURVICH CM, 1989, BIOMETRIKA, V76, P297 IVES AR, 1997, ECOLOGY, V78, P1907 JOHNSON DH, 1980, ECOLOGY, V61, P65 KEITT TH, 2002, ECOGRAPHY, V25, P616 KOTLIAR NB, 1990, OIKOS, V59, P253 KOTLIAR NB, 2000, CONSERV BIOL, V14, P1715 LETTY J, 2000, ANIM CONSERV 3, V3, P211 LICHSTEIN JW, 2002, ECOL APPL, V12, P836 LOMBARDI L, 2003, J MAMMAL, V84, P26 MANEL S, 2001, J APPL ECOL, V38, P921 MAZEROLLE MJ, 1999, ECOSCIENCE, V6, P117 MCCULLAGH P, 1989, GEN LINEAR MODELS MICOL T, 1994, J ANIM ECOL, V63, P851 MONTES C, 1998, RECONOCIMIENTO BIOFI MOREIRA JM, 1995, USOS COBERTURAS SUEL MORENO S, 1995, BIOL CONSERV, V73, P81 ORROCK JL, 2000, ECOL APPL, V10, P1356 PAINE RT, 1992, NATURE, V355, P73 PALOMARES F, 1995, CONSERV BIOL, V9, P295 PALOMARES F, 2001, J APPL ECOL, V38, P9 PALOMARES F, 2001, WILDLIFE MONOGR OCT, P1 PALOMARES F, 2001, WILDLIFE SOC B, V29, P578 PALOMARES F, 2003, MAMM BIOL, V68, P224 PARADIS E, 2002, OIKOS, V97, P293 PEARCE J, 2001, BIOL CONSERV, V98, P33 PECH RP, 1992, OECOLOGIA, V89, P102 RODRIGUEZ A, 1992, BIOL CONSERV, V61, P189 ROGERS PM, 1979, J APPL ECOL, V16, P691 RUSHTON SP, 1994, J APPL ECOL, V31, P313 SAAB V, 1999, ECOL APPL, V9, P135 SCHWEIGER EW, 1999, LANDSCAPE ECOLOGY SM, P175 SORIGUER RC, 1986, MAMMAL REV, V16, P197 SOUSA A, 2001, LANDSCAPE ECOL, V16, P391 THOMPSON HV, 1994, EUROPEAN RABBIT HIST THOMPSON JN, 1996, TRENDS ECOL EVOL, V11, P300 TRAVAINI A, 1997, BIODIVERS CONSERV, V6, P529 VENABLES WN, 1997, MODERN APPL STAT S P VILLAFUERTE R, 1994, J WILDLIFE DIS, V30, P176 VILLAFUERTE R, 1995, MAMMALIA, V59, P651 VILLAFUERTE R, 1997, REV ECOL-TERRE VIE, V52, P345 WELTZIN JF, 1997, ECOLOGY, V78, P751 WHITE GC, 1996, ECOLOGY, V77, P2549 WIENS JA, 1987, OIKOS, V48, P132 0921-2973 Landsc. Ecol.ISI:000233036400001Spanish Council Sci Res, CSIC, Dept Appl Biol, Donana Biol Stn, Seville 41013, Spain. Fernandez, N, UFZ, Ctr Environm Res Leipzig Halle, Dept Ecol Modelling, Permoserstr 15, D-04301 Leipzig, Germany. nestor.fernandez@ufz.deEnglish <7-Ferrari, J. R. Lookingbill, T. R. Neel, M. C.2007cTwo measures of landscape-graph connectivity: assessment across gradients in area and configuration 1315-1323Landscape Ecology229connectivity; fragmentation; graph theory; percolation theory; threshold HABITAT FRAGMENTATION; ECOLOGICAL THRESHOLDS; EXTINCTION THRESHOLDS; METRICS; CONSERVATION; BEHAVIOR; MODELS; POPULATIONS; MANAGEMENT; INDEXESArticleNovLandscape connectivity is critical to species persistence in the face of habitat loss and fragmentation. Graph theory is a well-defined method for quantifying connectivity that has tremendous potential for ecology, but its application has been limited to a small number of conservation scenarios, each with a fixed proportion of habitat. Because it is important to distinguish changes in habitat configuration from changes in habitat area in assessing the potential impacts of fragmentation, we investigated two metrics that measure these different influences on connectivity. The first metric, graph diameter, has been advocated as a useful measure of habitat configuration. We propose a second area-based metric that combines information on the amount of connected habitat and the amount of habitat in the largest patch. We calculated each metric across gradients in habitat area and configuration using multifractal neutral landscapes. The results identify critical connectivity thresholds as a function of the level of fragmentation and a parallel is drawn between the behavior of graph theory metrics and those of percolation theory. The combination of the two metrics provides a means for targeting sites most at risk of suffering low potential connectivity as a result of habitat fragmentation.://000250207500005 Cited Reference Count: 44 Cited References: BASCOMPTE J, 1996, J ANIM ECOL, V65, P465 BENDER DJ, 2003, LANDSCAPE ECOL, V18, P17 BUNN AG, 2000, J ENVIRON MANAGE, V59, P265 CALABRESE JM, 2004, FRONT ECOL ENVIRON, V2, P529 DEON R, 2002, CONSERV ECOL, V6 DIJKSTRA EW, 1959, NUMER MATH, V1, P269 FAGAN WF, 2001, ECOL LETT, V4, P132 FAHRIG L, 1985, ECOLOGY, V66, P1762 FAHRIG L, 1988, THEOR POPUL BIOL, V34, P194 FAHRIG L, 2001, BIOL CONSERV, V100, P65 FAHRIG L, 2003, ANNU REV ECOL EVOL S, V34, P487 FERRARI JR, 2005, THESIS U MARYLAND GARDNER RH, 1999, LANDSCAPE ECOLOGICAL, P280 GILLIS EA, 1999, J MAMMAL, V80, P933 GROFFMAN P, 2006, ECOSYSTEMS, V9, P1 GROSS J, 1999, GRAPH THEORY APPL HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HAYES B, 2000, AM SCI, V88, P104 HAYES B, 2000, AM SCI, V88, P9 KEITT TH, 1997, CONSERV ECOL, V1 LANDE R, 1987, AM NAT, V130, P624 LEVINS R, 1969, B ENTOMOL SOC AM, V15, P237 LEVINS R, 1970, LECT MATH LIFE SCI, V2, P77 LINDENMAYER DB, 2005, BIOL CONSERV, V124, P351 MCGARIGAL K, 2002, FRAG STATS SPATIAL S MOFFAT AS, 1994, SCIENCE, V263, P1090 MOILANEN A, 2002, ECOLOGY, V83, P1131 MURADIAN R, 2001, ECOL ECON, V38, P7 NEEL MC, 2004, LANDSCAPE ECOL, V19, P435 ONEILL RV, 1988, LANDSCAPE ECOL, V2, P63 PASCUALHORTAL L, 2006, LANDSCAPE ECOL, V21, P959 PIMM SL, 1995, P NATL ACAD SCI USA, V92, P9343 RAPPORT DJ, 1985, AM NAT, V125, P617 ROTHLEY KD, 2005, ENVIRON MODEL ASSESS, V10, P107 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 STATUFFER D, 1992, INTRO PERCOLATION TH URBAN D, 2001, ECOLOGY, V82, P1205 URBAN DL, 2003, LANDGRAPHS PACKAGE G URBAN DL, 2005, ECOLOGY, V86, P1996 VANLANGEVELDE F, 2000, ECOGRAPHY, V23, P614 WILCOVE DS, 1998, BIOSCIENCE, V48, P607 WINFREE R, 2005, AM NAT, V165, P707 WITH KA, 1997, CONSERV BIOL, V11, P1069 WITH KA, 1999, FOREST FRAGMENTATION, P97 0921-2973 Landsc. Ecol.ISI:000250207500005Univ Maryland, Ctr Environm Sci, Appalachian Lab, Frostburg, MD 21532 USA. Univ Maryland, Dept Entomol, College Pk, MD 20742 USA. Ferrari, JR, Univ Maryland, Ctr Environm Sci, Appalachian Lab, Frostburg, MD 21532 USA. jferrari@al.umces.eduEnglish<7!Ferrarini, A. Rossi, P. Rossi, O.2005lAscribing ecological meaning to habitat shape by means of a piecewise regression approach to fractal domains799-809Landscape Ecology207area-perimeter relation; Baganza stream watershed; habitat shape; Italy; Multivariate Adaptive Regression Splines LANDSCAPE PATTERNS; SPLINES; MARSArticleNov=A fractal dimension (FD) indicates the ability of a set of structures to fill the Euclidean space where it is embedded. For habitat boundaries, FD is bound to a plane, thus 1 <= FD <= 2. FD is low for simple shapes and increases as patches become more irregular. Some authors have found that FD metric delineating area-perimeter relation (APR) is best fitted through piecewise linear curves, where the slope of each line segment is one-half the FD over the corresponding scaling region. The detection of shifts in boundary FD of landscape habitats is a significant issue in ecology, since discontinuities could be an index of a substantial modification of the processes and dynamics that generate and maintain habitats. This work makes use of fractal analysis to examine the relationship between anthropogenic processes and habitat spatial patterns. It proposes two goals (1) suggesting Multivariate Adaptive Regression Splines (MARS(R)) as a fast and effective approach to discover shifts in APR of landscape patches; (2) explaining the substantial existence of such shifts using a set of human-related predictor variables. MARS methodology has been applied to 6 types of habitats within the Baganza stream watershed (Parma, Italy) and the discovered patterns have been correlated with anthropogenic variables that could influence APR. A standardized linear discriminant analysis (DA) has been used to predict FDs from the set of the employed predictors. DA corroborated the existence of breakpoints in APR and explained the contribute of predictor variables in determining the discovered shifts.://000233036300003 7ISI Document Delivery No.: 980RQ Times Cited: 1 Cited Reference Count: 38 Cited References: *CEC, 1991, 125873 CEC EUR BASKENT EZ, 1999, LANDSCAPE ECOL, V14, P83 BUECHNER M, 1989, LANDSCAPE ECOLOGY, V2, P191 CHEN JQ, 1992, ECOL APPL, V2, P387 COHEN J, 1988, STAT POWER ANAL BEHA CRAVEN P, 1979, NUMER MATH, V31, P317 DEVEAUX RD, 1993, COMPUT CHEM ENG, V17, P819 DEVEAUX RD, 1993, J GEOPHYS RES-OCEANS, V98, P20307 FERRARINI A, 2002, ITAL J REMOTE SENS, V22, P13 FORMAN RT, 1986, LANDSCAPE ECOLOGY FORMAN RT, 1995, LAND MOSAICS ECOLOGY FRANK IE, 1995, CHEMOMETR INTELL LAB, V27, P1 FRIEDMAN JH, 1991, ANN STAT, V19, P1 FRONTIER S, 1987, NATO ASI SERIES G, V14, P335 GROSSI L, 2001, ENVIRON ECOL STAT, V8, P253 HARDT RA, 1989, ECOLOGY, V70, P1252 HARRIS LD, 1979, OUR NATL LANDSCAPE T, P725 HASTINGS HM, 1993, FRACTALS USERS GUIDE IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 KRUMMEL JR, 1987, OIKOS, V48, P321 KUHNERT PM, 2000, COMPUT STAT DATA AN, V34, P371 LEWIS PAW, 1991, J AM STAT ASSOC, V86, P864 LIU AJ, 2001, LANDSCAPE ECOL, V16, P581 MANDELBROT BB, 1982, FRACTAL GEOMETRY NAT MILLER JN, 1997, LANDSCAPE ECOL, V12, P137 MLADENOFF DJ, 2001, APACK 2 17 ANAL SOFT, P52 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 ROSSI O, 1993, B ITAL ECOL SOC, V14, P46 ROSSI P, 1999, THESIS U PARMA PARMA, P250 ROSSI P, 2001, ITAL J REMOTE SENS, V20, P41 SCHONEWALDCOX CM, 1986, BIOL CONSERV, V38, P305 SEKULIC S, 1992, J CHEMOMETR, V6, P199 STEINBERG D, 1999, MARS USER GUIDE SUGIHARA G, 1990, TRENDS ECOL EVOL, V5, P79 THOMPSON DW, 1961, GROWTH FORM TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 USHER MB, 1991, HABITAT STRUCTURE PH, P373 WIENS JA, 1985, OIKOS, V45, P421 0921-2973 Landsc. Ecol.ISI:000233036300003Univ Parma, Dept Environm Sci, I-43100 Parma, Italy. Rossi, O, Univ Parma, Dept Environm Sci, Sci Ave 11-A, I-43100 Parma, Italy. o.rossi@unipr.itEnglishH|?KFerraz, Silvio F. B. Ferraz, Katia M. P. M. B. Cassiano, Carla C. Brancalion, Pedro Henrique S. da Luz, Daniela T. A. Azevedo, Thais N. Tambosi, Leandro R. Metzger, Jean Paul2014IHow good are tropical forest patches for ecosystem services provisioning?187-200Landscape Ecology292FebNative forests play an important role regarding ecosystem services related to biodiversity, water, and nutrient cycling, and the intensity of those services should be related to the amount, configuration and quality of the forest. However, in highly dynamic landscapes, such as some tropical regions, ecosystem services are potentially affected not only by the present landscape structure, but also by the historical land use. Here we propose a simple methodological framework to evaluate the contribution of past landscape dynamics and present landscape structure in the provision of ecosystem services. We applied this framework to a traditional agricultural landscape from the Brazilian Atlantic Forest hotspot, where natural forests cover has increased from 8 to 16 % in the last 60 years (1962-2008), and where old forests are being reduced while young forests are being regenerated. Forests of different ages, in association with current landscape structure, reveal a mosaic of forest patches under different conditions, implying different abilities to deliver ecosystem services. With the replacement of old-growth forests by young-regenerating forests and a high level of forest fragmentation, less than 1/4 of the current forest cover is able to fully satisfy the ecosystem service demands. To avoid such tendency, government policies should not only focus on increasing forest cover, but also in conserving old-growth forest fragments or increasing forest quality. The proposed methodology allows integrating historical land use and current landscape structure to evaluate ecosystem services provision and can be useful to establish programs of payment for ecosystem services.!://WOS:000331935100002Times Cited: 1 0921-2973WOS:00033193510000210.1007/s10980-014-9988-z|?Fialkowski, M. Bitner, A.20083Universal rules for fragmentation of land by humans 1013-1022Landscape Ecology239The morphology of parcel patterns created by humans both in urban and rural areas is investigated. The parcel size distribution function, f(a), provides a criterion, that enables unambiguous classification of each piece of land as city core, suburbs, or rural area. The morphology of the rural area corresponds to a scale-free structure and follows a power-law distribution f(a) similar to a(-n) of the parcel areas with the exponent n approximate to 1. In suburbs, the area distribution follows the log-normal distribution. In the city core, f(a) has an unimodal shape with an algebraically decaying tail, n = 2. Our study is based on data originating mainly from North America, the Hawaiian Islands, and Australia. For the regions analyzed, the characteristics of the parcel size distribution are universal and robust with respect to geographical, historical, and economical conditions accompanying development of a given area. The urbanization process can be described in terms of the changes of the morphology of the patterns of land fragmentation. In this formulation, the rural morphology, which can be thought as natural one because it exhibits a scale-free distribution of parcel sizes, is transformed into the artificial morphology developed in the city centers.!://WOS:000260283100002Times Cited: 0 0921-2973WOS:00026028310000210.1007/s10980-008-9268-x|?9 &Figueiredo, Joana Pereira, Henrique M.2011ARegime shifts in a socio-ecological model of farmland abandonment737-749Landscape Ecology265May]We developed a mathematical model with two-way linked socio-ecological dynamics to study farmland abandonment and to understand the regimes shifts of this socio-ecological system. The model considers that migration is a collective behavior socio-economically driven and that the ecosystem is dynamic. The model identifies equilibria that vary from mass migration, farmland abandonment, and forest regeneration, to no migration and forest eradication; partial migration and/or coexistence of farmland and forest also constitute possible equilibria. Overall, the model reflects farmland abandonment processes observed in the field and illustrates the importance of the complex interlinked mechanisms between the social and ecological systems determining farmland abandonment, that are not evident when approached independently. The model dynamics show that the hysteresis on the social dynamics renders regimes shifts difficult to reverse, and that this difficulty is accentuated when considering the ecological system dynamic. Similar models could be applied to other socio-ecological systems to help their management.!://WOS:000291485100011Times Cited: 0 0921-2973WOS:00029148510001110.1007/s10980-011-9605-3<7&Fisher, J. T. Boutin, S. Hannon, S. J.2005{The protean relationship between boreal forest landscape structure and red squirrel distribution at multiple spatial scales73-82Landscape Ecology201Atlanta; boreal forest; Canada; heterogeneity; landscape context; red squirrel; spatial scale TAMIASCIURUS-HUDSONICUS; HABITAT FRAGMENTATION; SMALL MAMMALS; ECOLOGY; CONTEXT; BIRDS; AREA; AUTOCORRELATION; SPECIALIZATION; CONNECTIVITYArticleJanThis paper investigates two fundamental questions in landscape ecology: what influence does landscape context, or the composition of the matrix, have on an animals' response to landscape structure, and how does this relationship extrapolate between landscapes? We investigate how the distribution of North American red squirrels (Tamiasciurus hudsonicus) in the boreal mixedwood forest is influenced by anthropogenically (forest harvest) and naturally (forest fire) derived landscape structure. We studied the presence and absence of red squirrels over two years in three landscape types: one managed for timber harvest, one recently burned by wildfire, and a third unburned unmanaged landscape. Landscape composition and configuration, measured at several spatial scales, predicted red squirrel's distribution in all three landscapes, but the significant landscape variables changed across spatial scales, across time, and across landscapes. These findings emphasize the variability in landscape structure/animal distribution relationships, and enforce the need to link pattern-finding studies, such as this one, with searches for the mechanisms behind the observed pattern.://000231223900006 N ISI Document Delivery No.: 955KD Times Cited: 2 Cited Reference Count: 52 Cited References: *SPSS INC, 1996, SPSS VERSION 7 5 ADDICOTT JF, 1987, OIKOS, V49, P340 ANDREN H, 1994, OIKOS, V71, P355 ANDREN H, 1997, OIKOS, V80, P193 BAUDRY J, 1988, MUNSTERSCHE GEOGRAPH, V29, P23 BECK MW, 1997, OIKOS, V78, P265 BOWMAN J, 2001, FOREST ECOL MANAG, V140, P249 BRIGHT PW, 1993, MAMMAL REV, V23, P101 BROTONS L, 2003, AM NAT, V162, P343 CORKUM C, 1999, P 1999 C SUST FOR MA, P29 CORKUM CV, 1999, THESIS U ALBERTA EDM DUNNING JB, 1992, OIKOS, V65, P169 EDENIUS L, 1997, ECOGRAPHY, V20, P425 FISHER JT, 1999, THESIS U ALBERTA EDM FISHER JT, 2000, LANDSCAPE ECOL, V15, P333 FORMAN RTT, 1997, LAND MOSAICS ECOLOGY GURNELL J, 1983, MAMMAL REV, V13, P133 HENEIN K, 1998, OIKOS, V81, P168 HOSMER DW, 1989, APPL LOGISTIC REGRES JOHNSON CJ, 2001, OECOLOGIA, V127, P590 KEMP GA, 1970, ECOLOGY, V51, P763 KOTLIAR NB, 1990, OIKOS, V59, P253 LARSEN KW, 1994, ECOLOGY, V75, P214 LAWTON JH, 1999, OIKOS, V84, P177 LEGENDRE P, 1993, ECOLOGY, V74, P1659 MCGARIGAL K, 1994, FRAGSTATS SPATIAL PA MENARD SW, 1995, APPL LOGISTIC REGRES MERRIAM G, 1988, LANDSCAPE ECOLOGY MA, P43 MERRIAM G, 1991, NATURE CONSERVATION, V2, P133 MIDDLETON J, 1983, J APPL ECOL, V20, P625 MONKKONEN M, 1999, OIKOS, V84, P302 NAGELKERKE NJD, 1991, BIOMETRIKA, V78, P691 PULLIAM HR, 1988, AM NAT, V132, P652 PULLIAM HR, 1991, AM NAT, V137, S5 REUNANEN P, 2002, ECOL APPL, V12, P1188 RIEGE DA, 1991, J MAMMAL, V72, P152 RODRIGUEZ A, 1999, J APPL ECOL, V36, P649 RUSCH DA, 1978, ECOLOGY, V59, P400 SMITH CC, 1968, ECOL MONOGR, V38, P31 SOKAL RR, 1978, BIOL J LINN SOC, V10, P229 STEFFANDEWENTER I, 2003, CONSERV BIOL, V17, P1036 STRONG W, 1992, PUBL T ALBERTA FORES, P245 TAYLOR PD, 1993, OIKOS, V68, P571 TURNER MG, 2001, LANDSCAPE ECOLOGY TH, P201 VANAPELDOORN RC, 1994, LANDSCAPE ECOL, V9, P227 VAUGHAN IP, 2003, CONSERV BIOL, V17, P1601 WEGNER JF, 1979, J APPL ECOL, V16, P349 WHEATLEY M, 2002, J MAMMAL, V83, P716 WIENS JA, 1976, ANNU REV ECOL SYST, V7, P81 WIENS JA, 1989, FUNCT ECOL, V3, P385 YAHNER RH, 1987, CAN FIELD NAT, V101, P586 ZAR JH, 1996, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000231223900006Univ Alberta, Dept Biol Sci, Edmonton, AB T6G 2E9, Canada. Fisher, JT, Alberta Res Council, Bag 4000, Vegreville, AB T9C 1T4, Canada. jason.fisher@arc.ab.caEnglish <7Fisher, J. T. Merriam, G.2000MResource patch array use by two squirrel species in an agricultural landscape333-338Landscape Ecology154agricultural mosaic landscape corn fencerow forest size fragmentation grey squirrel red squirrel soybeans SCIURUS-VULGARIS L RED SQUIRREL HABITAT FRAGMENTATION MAMMALS POPULATIONS CHIPMUNKS ELEMENTS FORESTArticleMayEastern grey squirrels (Sciurus carolinensis) and North American red squirrels (Tamiasciurus hudsonicus) were studied among wooded patches within an agricultural mosaic. Fifteen sites south of Ottawa, Canada, with differing landscape and local features were censused using tracking boards placed in a woods or wooded fencerow. Regression analyses of landscape compositional and physiognomic variables within a 1-km radius isolated the best predictors of grey and red squirrel abundance and activity. Grey squirrels were found in both small woods and fencerows in farm landscapes but were not found in large woods. A polynomial regression of wooded patch size explained 79% of the variance in grey squirrel abundance. Grey squirrel activity was correlated with the percent cover of soybeans in the landscape. Red squirrels were found in fencerows, small and large woods; activity was correlated with the percent cover of both woods and corn crop in the surrounding landscape. These results indicate that distributions of both species are influenced by multiple landscape elements, but that grey squirrels may rely on fragmented agricultural landscapes whereas red squirrels make more use of both native woodland and altered landscapes.://000086006700003 9ISI Document Delivery No.: 296DA Times Cited: 7 Cited Reference Count: 34 Cited References: *SAS I, 1990, SAS STAT US GUID VER ANDREN H, 1994, OIKOS, V70, P43 ANDREN H, 1994, OIKOS, V71, P355 BENNETT AF, 1994, BIOL CONSERV, V68, P155 BRIGHT PW, 1993, MAMMAL REV, V23, P101 CARROLL CR, 1992, CONSERV BIOL, P347 CELADA C, 1994, BIOL CONSERV, V69, P177 DOBBYN J, 1994, ATLAS MAMMALS ONTARI DUNNING JB, 1992, OIKOS, V65, P169 GURNELL J, 1983, MAMMAL REV, V13, P133 GURNELL J, 1984, ANIM BEHAV, V32, P1119 GURNELL J, 1987, NATURAL HIST SQUIRRE HENDERSON MT, 1985, BIOL CONSERV, V31, P95 HENEIN K, 1995, THESIS CARLETON U OT HURLBERT SH, 1984, ECOL MONOGR, V54, P187 KOPROWSKI J, 1991, J MAMMAL, V72, P267 KOTLIAR NB, 1990, OIKOS, V59, P253 KOZAKIEWICZ M, 1993, ACTA THERIOL, V38, P1 MERRIAM G, 1991, NATURE CONSERVATION, V2, P133 MIDDLETON J, 1983, J APPL ECOL, V20, P625 OGREN WL, 1973, SOYBEAN IMPROVEMENT, P391 PEDLAR JH, 1995, THESIS CARLETON U OT PETERSON RL, 1957, CHANGES FAUNA ONTARI, P43 RIEGE DA, 1991, J MAMMAL, V72, P152 SMALLWOOD PD, 1986, ECOLOGY, V67, P168 SZACKI J, 1993, ACTA THERIOL, V38, P113 TAPPER SC, 1986, J APPL ECOL, V23, P39 TAYLOR PD, 1993, OIKOS, V68, P571 VANAPELDOORN R, 1993, MAMMALIA, V57, P407 VANAPELDOORN RC, 1994, LANDSCAPE ECOL, V9, P227 VERBOOM B, 1990, LANDSCAPE ECOL, V4, P171 WAUTERS L, 1994, OIKOS, V69, P140 WEGNER J, 1990, BIOL CONSERV, V54, P263 WEGNER J, 1995, THESIS CARLETON U OT 0921-2973 Landsc. Ecol.ISI:000086006700003Carleton Univ, Landscape Ecol Lab, Ottawa, ON K1S 5B6, Canada. Fisher, JT, Univ Alberta, Dept Biol Sci, CW315 Biol Sci Bldg, Edmonton, AB T6G 2E9, Canada.Englishڽ7 1Fisichelli, NicholasA Frelich, LeeE Reich, PeterB2013VClimate and interrelated tree regeneration drivers in mixed temperate–boreal forests149-159Landscape Ecology281Springer NetherlandsoEcotone Overstory neighborhood effects Mixed temperate–boreal forest Tree regeneration Variation partitioning 2013/01/01+http://dx.doi.org/10.1007/s10980-012-9827-z 0921-2973Landscape Ecol10.1007/s10980-012-9827-zEnglish <70FitzGibbon, S. I. Putland, D. A. Goldizen, A. W.2007zThe importance of functional connectivity in the conservation of a ground-dwelling mammal in an urban Australian landscape 1513-1525Landscape Ecology2210bandicoot habitat fragmentation isoodon macrourus south-east queensland urbanisation urban ecology PATCH ISOLATION METRICS NEW-SOUTH-WALES HABITAT FRAGMENTATION FOREST FRAGMENTS ROADS TERRESTRIAL ECOLOGY BIRDS USAGEArticleDecNThe distribution of the northern brown bandicoot (Isoodon macrourus), a medium-sized ground-dwelling marsupial, was examined in habitat fragments within the urban landscape of the city of Brisbane, Australia. From surveys conducted in 68 fragments, bandicoots were found to be present in 33 (49%) despite widespread habitat loss and fragmentation. Logistic regression analysis revealed that of 13 measured independent variables, functional connectivity was the only factor that significantly predicted the presence of bandicoots within fragments, with connectivity positively correlated with the likelihood of occupation. Functional connectivity was equated to the likelihood of bandicoot immigration into the focal fragment from the nearest occupied fragment, based on the estimated resistance to movement offered by the intervening matrix. Within Brisbane, riparian habitat fragments typically have a relatively high level of functional connectivity, as thin strips of vegetation fringing waterways serve as corridors between larger riparian areas and facilitate the movement of bandicoots between patches. Analyses based on the Akaike Information Criterion revealed that the optimal model based on landscape context variables was convincingly better supported by the data than the optimal model produced from fragment characteristics. However, it is important to examine both internal attributes of habitat fragments and external features of the surrounding landscape when modelling the distribution of ground-dwelling fauna in urban environments, or other landscapes with a highly variable matrix. As urban centres throughout the world expand, it is crucial that the ecology of local wildlife be considered to ensure functional connection is maintained between habitat patches, especially for the conservation of species that are highly susceptible to fragmentation.://000250632100010ISI Document Delivery No.: 227BL Times Cited: 0 Cited Reference Count: 44 FitzGibbon, Sean I. Putland, David A. Goldizen, Anne W. 0921-2973 Landsc. Ecol.ISI:000250632100010Univ Queensland, Sch Integrated Biol, St Lucia, Qld 4072, Australia. FitzGibbon, SI, Univ Queensland, Sch Integrated Biol, St Lucia, Qld 4072, Australia. s.fitzgibbon@uq.edu.auEnglish,|? Fitzpatrick, Matt2011aComparative biogeography: discovering and classifying biogeographical patterns of a dynamic Earth 1049-1050Landscape Ecology267Aug!://WOS:000292705900012Times Cited: 0 0921-2973WOS:00029270590001210.1007/s10980-011-9598-y<7Flamm, R. O. Turner, M. G.1994NAlternative model formulations for a stochastic simulation of landscape change37-46Landscape Ecology91ArticleMar)Two stochastic model formulations, one using pixel-based transitions and the other patch-based, were compared by running simulations where the amount of information on which transitions were based was increased. Both model types adequately represented changes in the proportion of the landscape occupied by different land cover types. However, the pixel-based model underestimated contagion and overestimated the amount of edge. The patch-based model overestimated contagion and underestimated edge. Overall, the estimates more closely approximated the expected and the variances decreased as more information was added to the models. As expected, the model that most closely simulated the spatial pattern of the landscape was a 5-data-layer patch-based model that also included ownership boundaries as an additional layer. The simulation methods described provide a means to integrate socioeconomic and ecological information into a spatially-explicit transition model of landscape change and to simulate change at a scale similar to that occurring in a landscape.://A1994NC71800004 IISI Document Delivery No.: NC718 Times Cited: 22 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1994NC71800004KFLAMM, RO, OAK RIDGE NATL LAB,DIV ENVIRONM SCI,POB 2008,OAK RIDGE,TN 37831.English<7&Flamm, R. O. Ward, L. I. Weigle, B. L.2001oApplying a variable-shape spatial filter to map relative abundance of manatees (Trichechus manatus latirostris)279-288Landscape Ecology163spatial filter geographic information systems manatees marine mammals relative abundance AERIAL SURVEYS VISIBILITY BIAS FLORIDA FAUNAArticleApraPresented is a modified spatial filter, called a variable-shape filter, that was used to transform a map of point locations of Florida manatees (Trichechus manatus latirostris) to a contoured surface illustrating relative abundance. Rather than having a fixed polygon shape and size as conventional filters do, this method preserves constant filter area but conforms polygon shape to include only the desired land-cover categories-in this study, water. Variable-shape filter polygons are formed by starting with the cell that the point is located in and then adding the nearest contiguous cells of the desired land-cover category to the polygon until the area requirement is reached. Surfaces generated using the variable-shape filter were compared to those created with a conventional, circular, fixed-shape filter. Four filter sizes, based on an analysis of manatee hourly travel rates estimated from satellite and radio telemetry data, were used. Filter sizes, defined in terms of a circle's radius, were 125 m, which was the 25th percentile of the cumulative manatee travel-rate distribution; 325 m, the 50th percentile; 800 m, the 75th percentile; and 3,950 m, the 99th percentile. The fixed-shape and variable-shape filters differed principally in how their results were influenced by land. The variable-shape filter, programmed to maintain constant area, estimated animals to occur farther from shore than the fixed-shape filter did. Fixed-shape filter polygons were occasionally divided by land barriers, such as peninsulas, resulting in calculations of relative abundance estimates that were near the visual sighting in terms of euclidian distance but far in terms of manatee travel. The variable-shape filter was preferable primarily because it was more sensitive to manatee ecology: only cells contiguous to the animal's mapped location were included in the filter calculations.://000168194400007 UISI Document Delivery No.: 423TT Times Cited: 3 Cited Reference Count: 37 Cited References: *CITR COUNT FL, 1991, CITR COUNT COMPR PLA, P877 *MAR MAMM COMM, 1988, PREL ASS HAB PROT NE *US FISH WILDL SER, 1995, FLOR MAN REC PLAN 2 ACKERMAN BB, 1995, POPULATION BIOL FLOR, P13 ANDERSON PK, 1982, AUSTR WILDLIFE RES, V9, P69 BAYLISS P, 1986, AUST WILDLIFE RES, V13, P27 BENEDICT JB, 1967, J GLACIOL, V6, P817 CAMPBELL HW, 1976, FLORIDA NATURALIST, V49, P15 CAUGHLEY G, 1974, J WILDLIFE MANAGE, V38, P921 COLE JP, 1968, QUANTITATIVE GEOGRAP COOK RD, 1974, J AM STAT ASSOC, V69, P345 FANCY SG, 1988, FISH WILDLIFE SERVIC, V172 HARRIS RB, 1990, 30 US DEP INT FISH W HARTMAN DS, 1974, DISTRIBUTION STATUS HARTMAN DS, 1979, SPECIAL PUBLICATION, V5 IRVINE AB, 1982, FISH B-NOAA, V80, P621 KINNAIRD MF, 1983, 2 FLOR COOP FISH WIL KOCHMAN HI, 1985, J WILDLIFE MANAGE, V49, P921 MARSH H, 1989, J WILDLIFE MANAGE, V53, P1017 OLIVER MA, 1990, INT J GEOGR INF SYST, V4, P313 OSHEA TJ, 1985, J WILDLIFE MANAGE, V49, P1 PACKARD JM, 1983, 2 U FLOR FLOR COOP F PACKARD JM, 1983, 3 US FISH WILDL SERV PACKARD JM, 1985, J WILDLIFE MANAGE, V49, P347 PACKARD JM, 1986, COASTAL ZONE MANAGE, V14, P279 PROVANCHA JA, 1988, MARINE MAMMAL SCI, V4, P323 RATHBUN GB, 1990, FLORIDA MARINE RES I, V48 REID JP, 1995, POPULATION BIOL FLOR, P171 REYNOLDS JE, 1988, B8780600039 FLOR POW REYNOLDS JE, 1991, P 2 TAMP BAY AR SCI, P23 SAMUEL MD, 1981, J WILDLIFE MANAGE, V45, P993 SHANE SH, 1981, ABUNDANCE DISTRIBUTI STEINHORST RK, 1989, BIOMETRICS, V45, P415 WARD LI, 1993, GIS WORLD, V6, P34 WEIGLE BL, 1990, FLORIDA MARINE RES P, V49, P23 WOLFE ML, 1989, J WILDLIFE MANAGE, V53, P593 WRIGHT SD, 1995, POPULATION BIOL FLOR, P259 0921-2973 Landsc. Ecol.ISI:000168194400007Florida Marine Res Inst, St Petersburg, FL 33701 USA. Flamm, RO, Florida Marine Res Inst, 100 8th Ave SE, St Petersburg, FL 33701 USA.English<7)Flather, C. H. Brady, S. J. Inkley, D. B.1992Regional habitat appraisals of wildlife communities - a landscape-level evaluation of a resource planning model using avian distribution data137-147Landscape Ecology72tAVIAN COMMUNITY STRUCTURE; DIVERSITY; HABITAT STRUCTURE; RESOURCE PLANNING MODEL; SPATIAL PATTERNS; WILDLIFE HABITATArticleJul/A simple regional habitat model founded on the relation between vertical habitat complexity and species richness has been used to describe wildlife habitat in response to macroscale patterns in land use and land cover. While the model has a basis in ecological theory, it has not been subjected to rigorous testing. We evaluated the model's fundamental assumption on landscapes in the eastern forested region of the United States and found the model to be supported when we used a measure of avian community integrity during the breeding season. The model was improved by incorporating measures of horizontal heterogeneity, indicating that the vertical and horizontal structure of habitats should be considered in analyzing the response of wildlife to land resource policies that can affect broad land use patterns.://A1992JF61500006 IISI Document Delivery No.: JF615 Times Cited: 23 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1992JF615000060FLATHER, CH, US FOREST SERV,FT COLLINS,CO 80526.EnglishN|7 )Flather, C. H. Brady, S. J. Inkley, D. B.1992Regional Habitat Appraisals of Wildlife Communities - a Landscape-Level Evaluation of a Resource Planning-Model Using Avian Distribution Data137-147Landscape Ecology72oavian community structure diversity habitat structure resource planning model spatial patterns wildlife habitatJul2A simple regional habitat model founded on the relation between vertical habitat complexity and species richness has been used to describe wildlife habitat in response to macroscale patterns in land use and land cover. While the model has a basis in ecological theory, it has not been subjected to rigorous testing. We evaluated the model's fundamental assumption on landscapes in the eastern forested region of the United States and found the model to be supported when we used a measure of avian community integrity during the breeding season. The model was improved by incorporating measures of horizontal heterogeneity, indicating that the vertical and horizontal structure of habitats should be considered in analyzing the response of wildlife to land resource policies that can affect broad land use patterns.://A1992JF61500006-Jf615 Times Cited:25 Cited References Count:0 0921-2973ISI:A1992JF61500006.Flather, Ch Us Forest Serv,Ft Collins,Co 80526English|?S >Flatley, William T. Lafon, Charles W. Grissino-Mayer, Henri D.2011lClimatic and topographic controls on patterns of fire in the southern and central Appalachian Mountains, USA195-209Landscape Ecology262FebClimate and topography are two important controls on spatial patterns of fire disturbance in forests globally, via their influence on fuel moisture and fuel production. To assess the influences of climate and topography on fire disturbance patterns in a temperate forest region, we analyzed the mapped perimeters of fires that burned during 1930-2003 in two national parks in the eastern United States. These were Great Smoky Mountains National Park (GSMNP) in the southern Appalachian Mountains and Shenandoah National Park (SNP) in the central Appalachian Mountains. We conducted GIS analyses to assess trends in area burned under differing climatic conditions and across topographic gradients (elevation, slope position, and aspect). We developed a Classification and Regression Tree model in order to further explore the interactions between topography, climate, and fire. The results demonstrate that climate is a strong driver of both spatial and temporal patterns of wildfire. Fire was most prevalent in the drier SNP than the wetter GSMNP, and during drought years in both parks. Topography also influenced fire occurrence, with relatively dry south-facing aspects, ridges, and lower elevations burning most frequently. However, the strength of topographic trends varied according to the climatic context. Weaker topographic trends emerged in the drier SNP than GSMNP, and during low-PDSI (dry) years than high-PDSI (wet) years in both parks. The apparent influence of climate on the spatial patterning of fire suggests a more general concept, that disturbance-prone landscapes exhibit weaker fine-scale spatial patterning of disturbance than do less disturbance-prone landscapes.!://WOS:000286474900004Times Cited: 0 0921-2973WOS:00028647490000410.1007/s10980-010-9553-3<7`(Fleishman, E. Betrus, C. J. Blair, R. B.2003tEffects of spatial scale and taxonomic group on partitioning of butterfly and bird diversity in the Great Basin, USA675-685Landscape Ecology187Kadditive partitioning alpha diversity community similarity conservation Great Basin hierarchy theory non-parametric analysis of variance spatial scale species composition surrogate species western USA SPECIES-DIVERSITY ENVIRONMENTAL VARIABLES CLIMATE-CHANGE PATTERNS RICHNESS COMMUNITIES CONSERVATION ASSEMBLAGES COUNT BIOGEOGRAPHYArticleDifferent taxonomic groups perceive and respond to the environment at different scales. We examined the effects of spatial scale on diversity patterns of butterflies and birds in the central Great Basin of the western USA. We partitioned the landscape into three hierarchical spatial levels: mountain ranges, canyons, and sites within canyons. We evaluated the relative contribution of each level to species richness and quantified changes in species composition at each level. Using additive partitioning, we calculated the contribution of spatial level to overall species diversity. Both canyon and mountain range had significant effects on landscape- level species richness of butterflies and birds. Species composition of butterflies was more similar in space than species composition of birds, but assemblages of both groups that were closer together in space were less similar than assemblages that were further apart. These results likely reflect differences in resource specificity and the distribution of resources for each group. Additive partitioning showed that alpha diversity within canyon segments was the dominant component of overall species richness of butterflies but not of birds. As the size of a sampling unit increased, its contribution to overall species richness of birds increased monotonically, but the relationship between spatial scale and species richness of butterflies was not linear. Our work emphasizes that the most appropriate scales for studying and conserving different taxonomic groups are not the same. The ability of butterflies and birds to serve as surrogate measures of each other's diversity appears to be scale- dependent.://000186639000004 4 ISI Document Delivery No.: 744NR Times Cited: 7 Cited Reference Count: 61 Cited References: *AOU, 1992, BIRDS N AM ADDICOTT JF, 1987, OIKOS, V49, P340 ALLAN JD, 1975, OECOLOGIA, V18, P359 ALLEN TFH, 1982, HIERARCHY PERSPECTIV ANDERSON MJ, 2001, AUSTRAL ECOL, V26, P32 AUSTIN GT, 1987, GREAT BASIN NAT, V47, P186 BEHLE WH, 1978, GREAT BASIN NAT, V2, P55 BELTHOFF JR, 1998, GREAT BASIN NAT, V58, P167 BIBBY CJ, 2000, BIRD CENSUS TECHNIQU BROWN JH, 1978, GREAT BASIN NAT MEM, V2, P209 DEVRIES PJ, 1997, BIOL J LINN SOC, V62, P343 DOBKIN DS, 1998, J FIELD ORNITHOL, V69, P430 DROEGE S, 1998, CONSERV BIOL, V12, P1134 FLEISHMAN E, 1997, HOLARCTIC LEPIDOPTER, V4, P1 FLEISHMAN E, 1998, ECOLOGY, V79, P2482 FLEISHMAN E, 1999, GREAT BASIN NAT, V59, P50 FLEISHMAN E, 1999, OECOLOGIA, V119, P133 FLEISHMAN E, 2000, J BIOGEOGR, V27, P1209 FLEISHMAN E, 2001, BIOL J LINN SOC, V74, P501 FLEISHMAN E, 2001, CONSERV BIOL, V15, P1674 FLEISHMAN E, 2002, CONSERV BIOL, V16, P422 FLEISHMAN E, 2002, CONSERV BIOL, V16, P706 FOURNIER E, 2001, LANDSCAPE ECOL, V16, P17 GERING JC, CONSERVATION BIOL, V17, P488 GRAYSON DK, 1993, DESERTS PAST NATURAL GROSS KL, 2000, OIKOS, V89, P417 HARDING PT, 1995, ECOLOGY CONSERVATION, P3 HARPER KT, 1978, GREAT BASIN NAT, V2, P81 KING AW, 1991, QUANTITATIVE METHODS, P479 KOLASA J, 1989, ECOLOGY, V70, P36 KOTLIAR NB, 1990, OIKOS, V59, P253 KREMEN C, 1992, ECOL APPL, V2, P203 LANDE R, 1996, OIKOS, V76, P5 LINK WA, 1998, ECOL APPL, V8, P258 MACARTHUR RH, 1965, BIOL REV, V40, P510 MACNALLY R, 2002, IN PRESS ISSUES LAND MACNALLY R, 2003, BIOL CONSERV, V110, P21 MAGURRAN AE, 1988, ECOLOGICAL DIVERSITY MCARDLE BH, 2001, ECOLOGY, V82, P290 MCDONALD KA, 1992, CONSERV BIOL, V6, P409 MITTELBACH GG, 2001, ECOLOGY, V82, P2381 MORRISON ML, 2001, PREDICTING SPECIES O MURPHY DD, 1992, GLOBAL WARMING BIOL, P355 OSENBERG CW, 1999, ECOLOGY, V80, P1105 POLLARD E, 1993, MONITORING BUTTERFLI POLLARD E, 1998, BIOL CONSERV, V84, P17 PULLIN AS, 1995, ECOLOGY CONSERVATION REED JM, 1996, CONSERV BIOL, V10, P1283 SCHEINER SM, 2000, EVOL ECOL RES, V2, P791 SHAPIRO AM, 1975, ECOLOGY EVOLUTION CO, P181 SIEGEL RB, 2001, J FIELD ORNITHOL, V72, P228 SWENGEL AB, 1990, AM MIDL NAT, V124, P395 TAUSCH RJ, 1990, GREAT BASIN NAT, V50, P121 THOMAS CD, 1985, BIOL CONSERV, V33, P95 UNDERWOOD AJ, 1996, OECOLOGIA, V107, P212 UNDERWOOD AJ, 1998, AUST J ECOL, V23, P138 WAGNER HH, 2000, LANDSCAPE ECOL, V15, P219 WAIDE RB, 1999, ANNU REV ECOL SYST, V30, P257 WHITTAKER RH, 1977, EVOL BIOL, V10, P1 WILCOX BA, 1986, OECOLOGIA, V69, P188 WILLIS KJ, 2002, SCIENCE, V295, P1245 0921-2973 Landsc. Ecol.ISI:000186639000004Stanford Univ, Dept Biol Sci, Ctr Conservat Biol, Stanford, CA 94305 USA. Miami Univ, Dept Zool, Oxford, OH 45056 USA. Fleishman, E, Stanford Univ, Dept Biol Sci, Ctr Conservat Biol, Stanford, CA 94305 USA.Englishڽ7 WFletcher, RobertJ, Jr. Maxwell, ChristopherW, Jr. Andrews, JohnE Helmey-Hartman, WendyL2013mSignal detection theory clarifies the concept of perceptual range and its relevance to landscape connectivity57-67Landscape Ecology281Springer NetherlandscPerceptual ability Cactus bug Chelinidea vittiger Functional connectivity Functional grain Movement 2013/01/01+http://dx.doi.org/10.1007/s10980-012-9812-6 0921-2973Landscape Ecol10.1007/s10980-012-9812-6EnglishO|?Fletcher, R. J. Hutto, R. L.2008aPartitioning the multi-scale effects of human activity on the occurrence of riparian forest birds727-739Landscape Ecology236Conservationists, managers, and land planners are faced with the difficult task of balancing many issues regarding humans impacts on natural systems. Many of these potential impacts arise from local-scale and landscape-scale changes, but such changes often covary, which makes it difficult to isolate and compare independent effects arising from humans. We partition multi-scale impacts on riparian forest bird distribution in 105 patches along approximately 500 km of the Madison and Missouri Rivers, Montana, USA. To do so, we coupled environmental information from local (within-patch), patch, and landscape scales reflecting potential human impacts from grazing, invasive plant species, habitat loss and fragmentation, and human development with the distribution of 28 terrestrial breeding bird species in 2004 and 2005. Variation partitioning of the influence of different spatial scales suggested that local-scale vegetation gradients explained more unique variation in bird distribution than did information from patch and landscape scales. Partitioning potential human impacts revealed, however, that riparian habitat loss and fragmentation at the patch and landscape scales explained more unique variation than did local disturbances or landscape-scale development (i.e., building density in the surrounding landscape). When distribution was correlated with human disturbance, local-scale disturbance had more consistent impacts than other scales, with species showing consistent negative correlations with grazing but positive correlations with invasives. We conclude that while local vegetation structure best explains bird distribution, managers concerned with ongoing human influences in this system need to focus more on mitigating the effects of large-scale disturbances than on more local land use issues.!://WOS:000257210900008Times Cited: 0 0921-2973WOS:00025721090000810.1007/s10980-008-9233-8<7O 2Foltete, J. C. Clauzel, C. Vuidel, G. Tournant, P.2012MIntegrating graph-based connectivity metrics into species distribution models557-569Landscape Ecology274graph theory fragmented habitat metapopulation landscape connectivity landscape metric predictive model landscape connectivity habitat suitability conservation metapopulation centrality selection animals index guideAprSpecies distribution models (SDMs) are commonly used in ecology to map the probability of species occurrence on the basis of predictive factors describing the physical environment. We propose an improvement on SDMs by using graph methods to quantify landscape connectivity. After (1) mapping the habitat suitable for a given species, this approach consists in (2) building a landscape graph, (3) computing patch-based connectivity metrics, (4) extrapolating the values of those metrics to any point of space, and (5) integrating those connectivity metrics into a predictive model of presence. For a given species, this method can be used to interpret the significance of the metrics in the models in terms of population structure. The method is illustrated here by the construction of an SDM for the European tree frog in the region of Franche-Comt, (France). The results show that the connectivity metrics improve the explanatory power of the SDM and emphasize the important role of the habitat network.://000302346900007-919RS Times Cited:0 Cited References Count:39 0921-2973Landscape EcolISI:000302346900007BFoltete, JC Univ Franche Comte, CNRS, TheMA UMR 6049, 32 Rue Megevand, F-25030 Besancon, France Univ Franche Comte, CNRS, TheMA UMR 6049, 32 Rue Megevand, F-25030 Besancon, France Univ Franche Comte, CNRS, TheMA UMR 6049, F-25030 Besancon, France Univ Franche Comte, CNRS, Chronoenvironm UMR 6249, F-25030 Besancon, FranceDOI 10.1007/s10980-012-9709-4English|? $Fontaine, C. M. Rounsevell, M. D. A.2009TAn agent-based approach to model future residential pressure on a regional landscape 1237-1254Landscape Ecology249This paper presents a framework to model future residential demand for housing in a polycentric region. The model, called HI-LIFE (Household Interactions through LIFE cycle stages), builds on Agent-Based Modelling (ABM) paradigms. In contrast to traditional equilibrium-based urban economics models that assume a homogenous population of rational actors, ABM focuses on the diversity of heterogeneous household agents and their behaviour in time and in space. The model simulates land-use patterns at the regional scale by integrating qualitative knowledge of agent location preferences with quantitative analysis of urban growth dynamics within a high resolution spatial modelling framework. The model was calibrated for the region of East Anglia in the UK using a semi-quantitative procedure. Simulation of urban dynamics for the future was undertaken for a 25 year period with the assumption of a continuation of baseline behavioural trends. The results demonstrated non-uniform, spatial patterns of urban sprawl with some locations experiencing greater urban development pressure than others. The town of Brundall, in particular, has a large potential demand for residential housing because of its proximity to the principle city, Norwich. As Brundall is also located close to a national park and a river, new housing development in this area would increase the risk of ecological impacts and flood damage. By modelling explicitly agent behaviour and interactions, ABM can simulate the response and adaptation strategies of a population to changing circumstances. This makes ABM especially well suited to the analysis of environmental change and landscape ecology pressures through scenario modelling.!://WOS:000270739000008Times Cited: 0 0921-2973WOS:00027073900000810.1007/s10980-009-9378-0<7Forman, R. T. T.19959Some general principles of landscape and regional ecology133-142Landscape Ecology103AGGREGATE WITH OUTLIERS; GRAIN SIZE; INDISPENSABLE PATTERN; LAND MOSAIC; LANDSCAPE CHANGE; LANDSCAPE ECOLOGY; METAPOPULATION DYNAMICS; MOSAIC SEQUENCE; PATCH CORRIDOR MATRIX; PATCH SHAPE; PRINCIPLE; REGIONAL ECOLOGYArticleJunA dozen general principles of landscape and regional ecology are delineated to stimulate their evaluation, refinement, and usage. Brief background material and a few references provide entrees into the subjects. The principles are presented in four groups: landscapes and regions; patches and corridors; mosaics; and applications. Most appear useful in solving a wide range of environmental and societal land-use issues.://A1995RF27500002 IISI Document Delivery No.: RF275 Times Cited: 82 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1995RF27500002=FORMAN, RTT, HARVARD UNIV,GRAD SCH DESIGN,CAMBRIDGE,MA 02138.English|7Z Forman, R. T. T.19959Some General-Principles of Landscape and Regional Ecology133-142Landscape Ecology103aggregate with outliers grain size indispensable pattern land mosaic landscape change landscape ecology metapopulation dynamics mosaic sequence patch corridor matrix patch shape principle regional ecologyJunA dozen general principles of landscape and regional ecology are delineated to stimulate their evaluation, refinement, and usage. Brief background material and a few references provide entrees into the subjects. The principles are presented in four groups: landscapes and regions; patches and corridors; mosaics; and applications. Most appear useful in solving a wide range of environmental and societal land-use issues.://A1995RF27500002.Rf275 Times Cited:113 Cited References Count:0 0921-2973ISI:A1995RF27500002;Forman, Rtt Harvard Univ,Grad Sch Design,Cambridge,Ma 02138English<7dForman, R. T. T.19983Road ecology: A solution for the giant embracing usIII-VLandscape Ecology134Editorial MaterialAug://000079677000001 ISI Document Delivery No.: 185NY Times Cited: 8 Cited Reference Count: 16 Cited References: *DIENST WEG WAT, 1995, NAT OV WEG *NAT RES COUNC, 1997, SUST FUT ADDR LONG T *SCHWEIZ GES WILDT, 1995, WILDT STRASS VERK AANEN P, 1991, NATURE ENG CIVIL ENG BENNETT AF, 1991, NATURE CONSERVATION, V2, P99 CANTERS K, 1997, HABITAT FRAGMENTATIO ELLENBERG H, 1981, OKOLOGIE STRASSE, P19 EVINK GL, P INT C WILDL TRANSP EVINK GL, 1996, FLER5896 FLOR DEP TR FORMAN RTT, IN PRESS ANN REV ECO, V29 FORMAN RTT, IN PRESS WILDLIFE EC FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FORMAN RTT, 1997, HABITAT FRAGMENTATIO, P40 RECK H, 1993, STRASSEN LEBENSRAUME REIJNEN R, 1995, J APPL ECOL, V32, P187 SAUNDERS DA, 1991, NATURE CONSERVATION, V2 0921-2973 Landsc. Ecol.ISI:000079677000001|Harvard Univ, Grad Sch Design, Cambridge, MA 02138 USA. Forman, RTT, Harvard Univ, Grad Sch Design, Cambridge, MA 02138 USA.English!~?Forman, R. T. T.2008[The urban region: natural systems in our place, our nourishment, our home range, our future251-253Landscape Ecology233"://WOS:000254112100001 Times Cited: 0WOS:000254112100001(10.1007/s10980-008-9209-8|ISSN 0921-2973<7kFortin, M. J. Olson, R. J. Ferson, S. Iverson, L. Hunsaker, C. Edwards, G. Levine, D. Butera, K. Klemas, V.2000-Issues related to the detection of boundaries453-466Landscape Ecology155environmental change GIS landscape ecology modeling remote sensing riparian statistics wetland GEOGRAPHIC INFORMATION-SYSTEM WATER-QUALITY ECOLOGICAL BOUNDARIES WETLANDS FOREST DISCONTINUITIES DELINEATION PERSPECTIVE MANAGEMENT ECOSYSTEMSArticleJul7Ecotones are inherent features of landscapes, transitional zones, and play more than one functional role in ecosystem dynamics. The delineation of ecotones and environmental boundaries is therefore an important step in land-use management planning. The delineation of ecotones depends on the phenomenon of interest and the statistical methods used as well as the associated spatial and temporal resolution of the data available. In the context of delineating wetland and riparian ecosystems, various data types (field data, remotely sensed data) can be used to delineate ecotones. Methodological issues related to their detection need to be addressed, however, so that their management and monitoring can yield useful information about their dynamics and functional roles in ecosystems. The aim of this paper is to review boundary detection methods. Because the most appropriate methods to detect and characterize boundaries depend of the spatial resolution and the measurement type of the data, a wide range of approaches are presented: GIS, remote sensing and statistical ones.://000088036700005 ISI Document Delivery No.: 331UH Times Cited: 25 Cited Reference Count: 63 Cited References: *ESRI INC, 1993, ARC INFO GRID COMM R *SAMAB, 1996, 1 SAMAB USDA FOR SER *USA CORPS ENG, 1993, MISS PLAN EARTH TASK ARNOFF S, 1989, GEOGRAPHIC INFORMATI BAILEY RG, 1996, ECOSYSTEM GEOGRAPHY BEAUCHEMIN M, 1995, CAN J REMOTE SENS, V21, P518 BEVEN KJ, 1979, HYDROL SCI B, V24, P43 BURROUGH PA, 1986, MONOGRAPHS SOIL RESO, V12 BUTERA MK, 1983, IEEE T GEOSCI REMOTE, V21, P383 CANTONI V, 1997, ARTIFICIAL VISION IM CLARKE SE, 1991, ENVIRON MANAGE, V15, P847 CORNELEO RL, 1996, LANDSCAPE ECOL, V11, P307 CORNELIUS JM, 1991, ECOLOGY, V72, P2057 CRUMLEY CL, 1993, ECOL APPL, V3, P377 DECAMPS H, 1988, LANDSCAPE ECOLOGY, V1, P163 DEFRIES R, 1995, REMOTE SENS ENVIRON, V54, P209 EDWARDS G, 1995, P 17 INT CART C BARC, P1521 EDWARDS G, 1996, PHOTOGRAMM ENG REM S, V62, P377 FORTIN MJ, SPATIAC ECOLOGY UNCE FORTIN MJ, 1994, ECOLOGY, V75, P956 FORTIN MJ, 1995, OIKOS, V72, P323 FORTIN MJ, 1996, OIKOS, V77, P51 FORTIN MJ, 1997, CAN J FOREST RES, V27, P1851 GALLANT AL, 1989, EPA600389060 ENV RES GILLIAM JW, 1994, J ENVIRON QUAL, V23, P896 GOSSELINK JG, 1990, ECOLOGICAL PROCESS C GOSZ JR, 1993, ECOL APPL, V3, P369 GRIFFITH GE, 1997, EPA600R97022 NAT HLT HANSEN A, 1992, LANDSCAPE BOUNDARIES HARDISKY MA, 1986, BIOSCIENCE, V36, P453 HOLLAND MM, 1988, BIOL INT, V17, P47 HOLLAND MM, 1991, ECOTONES HORNBECK JW, 1992, ECOL APPL, V2, P238 HUNSAKER CT, 1995, BIOSCIENCE, V45, P193 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 IVERSON LR, 1997, LANDSCAPE ECOL, V12, P331 JENSON SK, 1988, PHOTOGRAMM ENG REMOT, V54, P1593 JOHNSON LB, 1997, FRESHWATER BIOL, V37, P193 JOHNSTON CA, 1987, LANDSCAPE ECOL, V1, P47 JOHNSTON CA, 1989, PHOTOGRAMM ENG REM S, V55, P1643 JOHNSTON CA, 1992, LANDSCAPE BOUNDARIES, P107 JUSTICE CO, 1985, INT J REMOTE SENS, V6, P1271 LUDWIG JA, 1987, ECOLOGY, V68, P448 MANDELBROT BB, 1982, FRACTAL GEOMETRY NAT MCCOY ED, 1986, ECOLOGY, V67, P749 MILNE BT, 1993, SOME MATH QUESTIONS, P109 NAIMAN RJ, 1990, ECOLOGY MANAGEMENT A NEILSON RP, 1991, ECOTONES ROLE LANDSC, P31 OMERNIK JM, 1987, ANN ASSOC AM GEOGR, V77, P118 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 OSBORNE LL, 1988, J ENVIRON MANAGE, V26, P9 PETERJOHN WT, 1984, ECOLOGY, V65, P1466 PITAS I, 1993, DIGITAL IMAGE PROCES RISSER PG, 1990, ECOLOGY MANAGEMENT A, P7 SELLERS PJ, 1988, B AM METEOROL SOC, V69, P22 STORY M, 1986, PHOTOGRAMM ENG REM S, V52, P397 SWANSON FJ, 1990, BIOSCIENCE, V40, P502 UPTON GJG, 1985, SPATIAL DATA ANAL EX, V1 VOUGHT LBM, 1994, AMBIO, V23, P342 WHIGHAM DF, 1986, WATERSHED RES PERSPE, P283 WHIGHAM DF, 1988, ENVIRON MANAGE, V12, P663 WIENS JA, 1985, OIKOS, V45, P421 WOLTER PT, 1995, PHOTOGRAMM ENG REM S, V61, P1129 0921-2973 Landsc. Ecol.ISI:000088036700005Simon Fraser Univ, Sch Resource & Environm Management, Burnaby, BC V5A 1SB, Canada. Fortin, MJ, Simon Fraser Univ, Sch Resource & Environm Management, Burnaby, BC V5A 1SB, Canada.English<7`Forys, E. Humphrey, S. R.1999hThe importance of patch attributes and context to the management and recovery of an endangered lagomorph177-185Landscape Ecology142Lower Keys marsh rabbit Sylvilagus palustris hefneri Lower Keys of Florida metapopulation structure patch occupancy patch attributes patch context habitat quality discriminant function analysis METAPOPULATION DYNAMICS HABITAT FRAGMENTATION MODELS HYPOTHESIS LANDSCAPE DENSITY RABBIT COREArticleApr We investigated the role of patch attributes and context on parch occupancy of the Lower Keys marsh rabbit (Sylvilagus palustris hefneri). The Lower Keys marsh rabbit is a federally endangered lagomorph endemic to the Lower Keys of Florida. The marsh rabbit occurs in subpopulations on patches of high marsh that interact to form a metapopulation. Between March 1991 and July 1993, all known parches of high marsh in the Lower Keys were surveyed for presence or absence of marsh rabbit pellets three rimes per year. Of the 59 habitat patches, 20 had pellets present during all of the surveys (occupied patches), 22 had pellets present during at least one survey (variable patches), and 17 never had any pellets present (empty). Ten variables were measured at each of the 59 patches; seven of these variables concerned attributes of the patch (food, cover, patch size), and three were patch context variables (distance of patch to other patches, distance of patch to other features). Two discriminant function analysis (DFA) were performed. The first DFA compared empty patches to occupied patches (both variably and consistently occupied). Patch isolation explained the most variation in parch occupancy followed by area. The second DFA compared the variably occupied sites with the consistently occupied sites, and patch attributes variables involving the type and height of vegetation were significant. Management efforts for the Lower Keys marsh rabbit should be aimed at both improving habitat quality and decreasing distance between patches.://000079802500007 ISI Document Delivery No.: 187RV Times Cited: 12 Cited Reference Count: 38 Cited References: 1990, FED REG, V55, P25588 *ARC INFO ENV SYST, 1990, ARC INF US GUID *SAS, 1988, SAS STAT US GUID REL BROWN JH, 1977, ECOLOGY, V58, P445 CANFIELD RH, 1941, J FOREST, V39, P388 CAPEN DE, 1986, WILDLIFE 2000 MODELI, P171 CHAPMAN JA, 1990, RABBITS HARES PIKAS, P1 CHEN E, 1990, ECOSYSTEMS FLORIDA, P11 DOBSON FS, 1985, AM NAT, V126, P855 DUNSON WA, 1982, COMP BIOCH PHYSL, P17 FORYS EA, 1995, THESIS U FLORIDA GAI FORYS EA, 1996, J MAMMAL, V77, P1042 FORYS EA, 1997, J WILDLIFE MANAGE, V61, P86 GILPIN ME, 1986, CONSERVATION BIOL SC, P19 GOTELLI NJ, 1991, AM NAT, V138, P768 GOTTFRIED BM, 1982, CAN J ZOOL, V60, P1660 GUTZWILLER KJ, 1987, CONDOR, V89, P534 GUTZWILLER KJ, 1992, LANDSCAPE ECOL, V6, P293 HANSKI I, 1982, OIKOS, V38, P210 HANSKI I, 1991, BIOL J LINN SOC, V42, P17 HANSKI I, 1991, BIOL J LINN SOC, V42, P3 HANSKI I, 1994, ECOLOGY, V75, P747 HARRISON S, 1994, LARGE SCALE ECOLOGY, P89 HENDERSON MT, 1985, BIOL CONSERV, V31, P95 HOLT RD, 1993, ECOLOGICAL COMMUNITI, P77 LACHENBRUCH PA, 1975, DISCRIMINANT ANAL LAMBERSON RH, 1992, CONSERV BIOL, V6, P505 LEVINS R, 1970, LECT MATH LIFE SCI, V2, P77 MORRISON DF, 1976, MULTIVARIATE STAT ME PIETZ PJ, 1983, J WILDLIFE MANAGE, V47, P686 SHANNON CE, 1949, MATH THEORY COMMUNIC SIMONETTI JA, 1982, OECOLOGIA, V54, P55 TOMKINS IR, 1935, J MAMMAL, V16, P201 VANAPELDOORN RC, 1992, OIKOS, V65, P265 VERBOOM B, 1990, LANDSCAPE ECOL, V4, P171 VERBOOM J, 1991, BIOL J LINN SOC, V42, P39 VILLARD MA, 1989, ECOLOGY CONSERVATION, P474 WOOD DH, 1988, AUST WILDLIFE RES, V15, P665 0921-2973 Landsc. Ecol.ISI:000079802500007|Univ Florida, Dept Wildlife Ecol & Conservat, Gainesville, FL 32611 USA. Forys, E, Eckerd Coll, St Petersburg, FL 33711 USA.Englishڽ71Foster, JaneR Townsend, PhilipA Mladenoff, DavidJ2013_Spatial dynamics of a gypsy moth defoliation outbreak and dependence on habitat characteristics 1307-1320Landscape Ecology287Springer Netherlands}Lymantria dispar L. Geostatistics Semivariograms Landsat Forest disturbance Dispersal Phenology Spatial patterns Appalachians 2013/08/01+http://dx.doi.org/10.1007/s10980-013-9879-8 0921-2973Landscape Ecol10.1007/s10980-013-9879-8EnglishT<7Fournier, E. Loreau, M.2001Respective roles of recent hedges and forest patch remnants in the maintenance of ground-beetle (Coleoptera : Carabidae) diversity in an agricultural landscape17-32Landscape Ecology161alpha, beta and gamma diversity additive partitioning agrosystem dispersal power ground beetles landscape structure BENEFICIAL ARTHROPODS SPECIES-DIVERSITY WING POLYMORPHISM SOURCE-SINK DYNAMICS METAPOPULATION COLONIZATION CONSERVATION HEATHLAND CORRIDORSArticleJanWe compared three kinds of habitats: small remnants of native forests, recent hedges and barley crops, in order to investigate their respective roles in the maintenance of carabid-beetle diversity in a 950-ha area of an intensive agricultural landscape. Carabid faunas in remnants differed weakly from these found in hedges and crops. In particular, small remnants had few typical forest carabid species and a large number of open-area or ubiquitous species. Different approaches in the measurement of alpha and beta -diversity (classical indices, and additive partitioning of Simpson's index) showed similar results: hedges supported a high alpha -diversity but habitat types were quite similar overall, with weak differences between open and closed or disturbed and undisturbed habitats. A comparison of species dispersal powers in the various habitat types showed that species with a low dispersal power were rare in all habitats. However, wing development measured on two dimorphic species revealed, surprisingly, that brachypterous individuals were mainly present in hedges, which were expected a priori to be more disturbed, than remnants hence less suitable for the establishment of populations with a low dispersal power. These results suggest that small remnants do not behave as 'climax' habitats in this intensive agricultural landscape, probably because of their small size and strong isolation. We discuss the interest of new undisturbed habitats, such as recent hedges, for the maintenance of carabid diversity at both the local and landscape scale.://000167389900002 ( ISI Document Delivery No.: 409NN Times Cited: 16 Cited Reference Count: 60 Cited References: AUKEMA B, 1986, CARABID BEETLES THEI, P91 BUREL F, 1989, LANDSCAPE ECOLOGY, V2, P215 BUREL F, 1992, LANDSCAPE ECOL, V6, P161 CHIVERTON PA, 1991, J APPL ECOL, V28, P1027 DAFONSECA JPC, 1969, REV ECOLOGIE BIOL SO, V6, P1 DAVIS ALV, 1994, AFR J ECOL, V32, P192 DENBOER PJ, 1970, OECOLOGIA, V4, P1 DENBOER PJ, 1977, MISCELL PAPERS LH WA, V14 DENBOER PJ, 1980, ENTOMOL GEN, V6, P107 DENBOER PJ, 1987, ACTA PHYTHOPATHOL EN, V22, P71 DESENDER K, 1987, ACTA PHYTHOPATHOL EN, V22, P85 DESENDER K, 1989, MED FAC LANDBOUWW RI, V54, P823 DESENDER K, 1996, CARABID BEETLES THEI, P101 DEVRIES HH, 1996, ANN ZOOL FENN, V33, P77 DIAS PC, 1996, TRENDS ECOL EVOL, V11, P326 DUNNING JB, 1992, OIKOS, V65, P468 ERIKSSON O, 1996, OIKOS, V77, P248 ERNSTING G, 1987, ACTA PHYTOPATHOLOGIC, V22, P135 FAHRIG L, 1985, ECOLOGY, V66, P1762 FOURNIER E, 1999, ECOGRAPHY, V22, P87 GILBERT F, 1998, P ROY SOC LOND B BIO, V265, P577 GRUTTKE H, 1994, CARABID BEETLES ECOL, P299 GUILLEMAIN M, 1997, ACTA OECOL, V18, P465 GUTIERREZ D, 1997, J BIOGEOGR, V24, P903 HILL NJ, 1972, J CHEM SOC FARADAY T, V2, P427 HOBBS RJ, 1993, BIOL CONSERV, V64, P231 HOBBS RJ, 1995, CONSERV BIOL, V9, P761 JEANNEL R, 1941, FAUNE FRANCE JEANNEL R, 1942, FAUNE FRANCE KINNUNEN H, 1996, ANN ZOOL FENN, V33, P165 KISS J, 1994, ECOLOGIE, V25, P127 LANDE R, 1996, OIKOS, V76, P5 LINDROTH CH, 1974, HDB IDENTIFICATION 2, V4 LINDROTH CH, 1992, GROUND BEETLES CAR 1 LOREAU M, 1984, ACAD ROY BELG B CLA, P125 LOREAU M, 1984, PEDOBIOLOGIA, V27, P269 LOREAU M, 1997, THEOR POPUL BIOL, V51, P79 LUFF ML, 1996, ANN ZOOL FENN, V33, P185 LYS JA, 1994, CARABID BEETLES ECOL, P451 MITCHELL B, 1963, J ANIM ECOL, V32, P289 MITCHELL B, 1963, J ANIM ECOL, V32, P377 NIEMELA J, 1993, CONSERV BIOL, V7, P551 PATIL GP, 1982, J AM STAT ASSOC, V77, P548 PETIT S, 1998, AGR ECOSYST ENVIRON, V69, P243 RANTA E, 1982, ANN ZOOL FENN, V19, P175 ROFF DA, 1984, OECOLOGIA, V63, P30 ROFF DA, 1994, EVOL ECOL, V8, P639 SAIMDERS D, 1992, CONS BIOL, V5, P18 SAUNDERS DA, 1993, BIOL CONSERV, V64, P185 SIMPSON EH, 1949, NATURE, V163, P688 SOTHERTON N, 1992, OUTLOOK AGR, V21, P219 SOUTHWOOD TRE, 1978, ECOLOGICAL METHODS TAYLOR LR, 1978, S R ENTOMOL SOC LOND, V9, P1 THIELE HU, 1977, CARABID BEETLES THEI THOMAS MB, 1992, J APPL ECOL, V29, P524 TISCHENDORF L, 1998, ECOL MODEL, V106, P107 WALLIN H, 1987, ACTA PHYTOPATH ENTOM, V22, P449 WEBB NR, 1989, BIOL CONSERV, V47, P153 WISSINGER SA, 1997, BIOL CONTROL, V10, P4 YATES CJ, 1997, RESTOR ECOL, V5, P28 0921-2973 Landsc. Ecol.ISI:000167389900002Ecole Normale Super, UMR 7625, Ecol Lab, F-75230 Paris 05, France. Fournier, E, INRA, Ctr Versailles, Unite Pathol Vegetale, Route St Cyr, F-78000 Versailles, France.English~<7RFrair, J. L. Merrill, E. H. Visscher, D. R. Fortin, D. Beyer, H. L. Morales, J. M.2005nScales of movement by elk (Cervus elaphus) in response to heterogeneity in forage resources and predation risk273-287Landscape Ecology203first-passage time; landscape structure; seismic lines; timber harvest; trade-offs AREA-RESTRICTED SEARCH; CORRELATED RANDOM-WALK; ROCKY-MOUNTAIN ELK; WOLVES CANIS-LUPUS; HABITAT SELECTION; LANDSCAPE STRUCTURE; SPATIAL SCALES; POPULATION-DYNAMICS; FUNCTIONAL-RESPONSE; SEASONAL MIGRATIONArticleAprLAnimals may respond to spatial and temporal heterogeneity by altering their movement patterns. The time an animal spends in an area of a given size is termed 'first-passage time' and can be used to identify the scales at which different movement processes occur. Using first-passage time and 2-h observations, we identified nested spatial scales representing three movement behaviours for elk (Cervus elaphus) - inactive/ resting (moves < 50 m), active/foraging (<(x)over bar> = 276.7 m, SD = 56.6), and active/relocating ((x) over bar = 1628.3 m, SD = 436.6). Our ability to identify inactive behaviour was limited by GPS accuracy. The scale separating relocating and foraging behaviour. ranged 550-1650 m across individuals and varied quadratically with the mean patch size of cutover forest in an animal's home range. We classified path segments into the 3 movement behaviours and related behaviours to local. environmental conditions. Elk were likely to be inactive in areas having a low predicted use by wolves (Canis lupus), farther than 50 in from anthropogenic linear clearings, and where microclimatic conditions were cool (high shrub cover and north to east-facing slopes). In contrast, elk were most likely to forage in areas having intermediate levels of herbaceous biomass and low movement costs. Elk were most likely to be relocating when in areas of high wolf use, when close to linear clearings, and in energetically costly situations such as moving upslope. We discuss how elk use of potential foraging habitats may be restricted in this landscape by risks imposed by predators, humans, or both.://000231824400003 ISI Document Delivery No.: 963RU Times Cited: 2 Cited Reference Count: 81 Cited References: *STATACORP, 2001, STAT REF MAN REL 7 AGER AA, 2003, J MAMMAL, V84, P1076 ALBON SD, 1992, OIKOS, V65, P502 BASCOMPTE J, 1997, LANDSCAPE ECOL, V12, P213 BATSCHELET E, 1981, CIRCULAR STAT BIOL BEGG CB, 1984, BIOMETRIKA, V71, P11 BERGMAN CM, 2000, OECOLOGIA, V123, P364 BEYER H, 2004, VEGETATION MAP DYNAM, P2 BOBEK B, 1978, J RANGE MANAGE, V31, P456 BOYCE MS, 2003, ECOSCIENCE, V10, P421 BROWN JK, 1976, CAN J FOREST RES, V6, P154 BURNHAM KP, 2002, MODEL SELECTION MULT CALLAGHAN C, 2002, THESIS U GUELPH GUEL COLLINS WB, 1978, J WILDLIFE MANAGE, V42, P799 COOK JG, 2002, N AM ELK ECOLOGY MAN, P259 DAURIAC JCA, 1983, J PHYS A-MATH GEN, V16, P4039 FAUCHALD P, 2003, ECOLOGY, V84, P282 FIRLE S, 1998, ECOLOGY, V79, P2113 FORTIN D, 2003, OECOLOGIA, V134, P219 FORTIN D, 2005, IN PRESS ECOLOGY FRAIR JL, 2004, J APPL ECOL, V41, P201 FRANKE A, 2004, ECOL MODEL, V173, P259 FRITZ H, 2003, P ROY SOC LOND B BIO, V270, P1143 FRYXELL JM, 1988, AFR J ECOL, V26, P17 GEHRING TM, 1995, THESIS U WISCONSIN S GIRARD I, 2002, J WILDLIFE MANAGE, V66, P1290 GREEN RA, 1990, J WILDLIFE MANAGE, V54, P272 HANLEY JA, 1982, RADIOLOGY, V143, P29 HASKELL DG, 1997, BEHAV ECOL, V8, P448 HAYDON DT, 2000, LANDSCAPE ECOL, V15, P407 HEBBLEWHITE M, 2002, CAN J ZOOL, V80, P789 HEBBLEWHITE M, 2002, CAN J ZOOL, V80, P800 HILLIS JM, 1991, P ELK VULN S MONT ST, P38 HOOGE PN, 1997, ANIMAL MOVEMENT EXTE HOSMER DW, 2000, APPL LOGISTIC REGRES JAMES ARC, 1999, THESIS U ALBERTA EDM JAMES ARC, 2000, J WILDLIFE MANAGE, V64, P154 JEDRZEJEWSKI W, 2001, CAN J ZOOL, V79, P1993 JOHNSON AR, 1992, LANDSCAPE ECOL, V7, P63 JOHNSON CJ, 2002, J ANIM ECOL, V71, P225 JONES PF, 2002, CAN FIELD NAT, V116, P183 JONSEN ID, 2000, OIKOS, V88, P553 KAREIVA PM, 1983, OECOLOGIA, V56, P234 KOJOLA I, 2004, J ZOOL 3, V263, P229 KUNKEL KE, 2000, CAN J ZOOL, V78, P150 LIMA SL, 1990, CAN J ZOOL, V68, P619 LIMA SL, 2002, CONSERV ECOL, V6, P11 LUNDBERG P, 1990, OIKOS, V58, P378 MACCRACKEN JG, 1993, J RANGE MANAGE, V46, P302 MANLY BFJ, 2002, RESOURCE SELECTION A MARELL A, 2002, CAN J ZOOL, V80, P854 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MCINTYRE NE, 1999, LANDSCAPE ECOL, V14, P437 MECH LD, 2002, CAN FIELD NAT, V116, P315 MERRILL EH, 1994, CAN J ZOOL, V72, P303 MORALES JM, 2004, ECOLOGY, V85, P2436 MORGANTINI LE, 1989, ARCTIC ALPINE RES, V21, P288 MYSTERUD A, 1998, ECOLOGY, V79, P1435 MYSTERUD A, 1999, J ZOOL 4, V247, P479 MYSTERUD A, 2001, J ANIM ECOL, V70, P915 NEWTON M, 1989, J WILDLIFE MANAGE, V53, P643 NIELSON SE, 2002, URSUS, V13, P45 NOLET BA, 2002, J ANIM ECOL, P451 PARKER KL, 1984, J WILDLIFE MANAGE, V48, P474 PENDERGAST JF, 1996, INT STAT REV, V64, P89 RAND DA, 1995, P ROY SOC LOND B BIO, V259, P111 SCHAEFER JA, 1995, ECOGRAPHY, V18, P333 SKALSKI GT, 2003, AM NAT, V161, P441 SKOVLIN JM, 2001, N AM ELK ECOLOGY MAN, P531 TURCHIN P, 1998, QUANTITATIVE ANAL MO TURNER MG, 2001, LANDSCAPE ECOLOGY TH VANDOOREN TJM, 2004, J ANIM ECOL, V73, P261 VARTHA EW, 1977, AGRON J, V69, P888 VERNES K, 2001, AUSTRAL ECOL, V26, P649 VISSCHER D, 2004, VEGETATION MAP DYNAM, P15 WALLACE LL, 1995, LANDSCAPE ECOL, V10, P75 WARD D, 1994, ECOLOGY, V75, P48 WHITE CA, 2003, FOREST ECOL MANAG, V181, P77 WITH KA, 1994, LANDSCAPE ECOL, V9, P25 WOLFF JO, 2003, CAN J ZOOL, V81, P266 ZAR JH, 1984, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000231824400003Univ Alberta, Dept Biol Sci, Edmonton, AB T6G 2E9, Canada. Univ Connecticut, Storrs, CT 06269 USA. Univ Laval, Dept Biol, Ste Foy, PQ G1K 7P4, Canada. Frair, JL, Univ Alberta, Dept Biol Sci, Edmonton, AB T6G 2E9, Canada. jfrair@ualberta.caEnglish? AFrancis, Clinton Paritsis, Juan Ortega, Catherine Cruz, Alexander2011jLandscape patterns of avian habitat use and nest success are affected by chronic gas well compressor noise 1269-1280Landscape Ecology269Springer NetherlandsEarth and Environmental ScienceeAnthropogenic noise is becoming a dominant component of soundscapes across the world and these altered acoustic conditions may have severe consequences for natural communities. We modeled noise amplitudes from gas well compressors across a 16 km 2 study area to estimate the influence of noise on avian habitat use and nest success. Using species with noise responses representative of other avian community members, across the study area we estimated gray flycatcher ( Empidonax wrightii) and western scrub-jay ( Aphelocoma californica ) occupancy, and gray flycatcher nest success, which is highly dependent on predation by western scrub-jays. We also explore how alternative noise management and mitigation scenarios may reduce area impacted by noise. Compressor noise affected 84.5% of our study area and occupancy of each species was approximately 5% lower than would be expected without compressor noise. In contrast, flycatcher nest success was 7% higher, reflecting a decreased rate of predation in noisy areas. Not all alternative management and mitigation scenarios reduced the proportion of area affected by noise; however, use of sound barrier walls around compressors could reduce the area affected by noise by 70% and maintain occupancy and nest success rates at levels close to those expected in a landscape without compressor noise. These results suggest that noise from compressors could be effectively managed and, because habitat use and nest success are only two of many ecological processes that may change with noise exposure, minimizing the anthropogenic component of soundscapes should be a conservation priority.+http://dx.doi.org/10.1007/s10980-011-9609-z 0921-297310.1007/s10980-011-9609-z ?P Francis, Robert2012/Climate change impacts on freshwater ecosystems 1079-1081Landscape Ecology277Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9750-3 0921-297310.1007/s10980-012-9750-3~?'Francois, C. Alexandre, L. Julliard, R.2008HEffects of landscape urbanization on magpie occupancy dynamics in France527-538Landscape Ecology235Responses of species to landscape modifications are generally documented through their distribution at a given time along an intensity gradient of land transformation. By focusing on patterns, we are limited to infer ecological processes occurring within a system and its response to environmental disturbances which can further change over time. Using diachronic datasets at the scale of France, we analyzed the spatial responses of the black-billed magpie, which has recently colonized cities, to landscape urbanization. This study applied recently developed statistical approaches incorporating detection uncertainty of the magpie, based on the capture-recapture statistical framework. We tested whether, and how, extinction and colonization mechanisms influenced variations of magpie occupancy from 2001 to 2005. In addition, we assessed the importance of the recent urbanization of the French countryside in determining population dynamics. Overall, our analysis proved that the proportion of urban areas and recent urbanization in France led to an increase in the probability of magpie occupancy. Unexpectedly, the species is concomitantly disappearing from the countryside, leading to a rapid change in the distribution of the species. This study stressed the importance of incorporating detection uncertainty in inference process about spatial dynamics. Overall, we show how useful it is to account for the dynamic evolution of the landscape in ecological studies."://WOS:000254964600004 Times Cited: 0WOS:000254964600004(10.1007/s10980-008-9211-1|ISSN 0921-2973 <7 Frank, D. H. Fish, D. Moy, F. H.1998ZLandscape features associated with Lyme disease risk in a suburban residential environment27-36Landscape Ecology131Lyme disease Ixodes scapularis tick epidemiology disease risk IXODES-DAMMINI ACARI SOUTHERN NEW-YORK MEDIUM-SIZED MAMMALS PEROMYSCUS-LEUCOPUS BORRELIA-BURGDORFERI DEER TICK WESTCHESTER-COUNTY SCAPULARIS ACARI ENDEMIC AREA IXODIDAEArticleFebThe landscape features of residential properties within two communities were studied in relation to the abundance of the tick vector Ixodes scapularis. Habitat types of 400 properties, located in a Lyme disease endemic area of Westchester Co., New York, USA, were categorized into lawn, ornamental, ecotone, woods, and stone wall as measured from aerial photographs and sampled for nymphal-stage ticks. Logistic regression results indicate that presence or absence of ticks is influenced by the proportion of either lawn or woodland, and total woodland area. Poisson regression results indicate the abundance of nymphs is negatively associated with proportion, area, and patch frequency of lawn, and positively associated with proportion, area, and patch frequency of woodland. Predictions of tick presence and abundance from landscape features at the scale of individual property is useful for implementing disease prevention measures.://000077256700003 ISI Document Delivery No.: 143LG Times Cited: 12 Cited Reference Count: 39 Cited References: *CDC, 1991, MMWR-MORBID MORTAL W, V40, P417 ADLER GH, 1992, PARASITOLOGY, V105, P105 ALLPORT S, 1990, SERMONS STONE STONE BARBOUR AG, 1993, SCIENCE, V260, P1610 BARRY RE, 1980, J MAMMAL, V61, P292 BATTALY GR, 1993, J MED ENTOMOL, V30, P740 COBLENTZ BE, 1970, J WILDLIFE MANAGE, V34, P535 CURRAN KL, 1993, J MED ENTOMOL, V30, P107 DENNIS DT, 1991, JAMA-J AM MED ASSOC, V266, P1269 DONOHUE JG, 1986, AM J TROP MED HYG, V36, P94 DUFFY DC, 1994, J MED ENTOMOL, V31, P152 FALCO RC, 1988, AM J EPIDEMIOL, V127, P826 FALCO RC, 1992, EXP APPL ACAROL, V14, P165 FISH D, 1989, J MED ENTOMOL, V26, P200 FISH D, 1990, J WILDLIFE DIS, V26, P339 FISH D, 1992, P 1 INT C TICK BORN, P274 FISH D, 1993, ECOLOGY ENV MANAGEME, P25 GINSBERG HS, 1989, J MED ENTOMOL, V26, P183 GLASS GE, 1992, INFECT DIS EPIDEMIOL, P65 JONGMAN RHG, 1987, DATA ANAL COMMUNITY KINGSLEY NP, 1985, NE95 USDA FOR SERV N KITRON U, 1991, PREV VET MED, V11, P243 LASTAVICA CC, 1992, NEW YORK STATE J MED, V92, P2 LEES AD, 1943, PARISITOLOGY, V37, P1 MAGNARELLI LA, 1988, J CLIN MICROBIOL, V26, P1138 MAUPIN GO, 1991, AM J EPIDEMIOL, V133, P1105 MCCAFFERY KR, 1974, J WILDLIFE MANAGE, V38, P215 MCCULLAGH P, 1983, GEN LINEAR MODELS MERRIAM G, 1990, LANDSCAPE ECOL, V4, P123 OLIVER JH, 1993, J MED ENTOMOL, V30, P54 PAVLOVSKY EN, 1966, NATURAL NIDALITY TRA PERSING DH, 1990, SCIENCE, V249, P1420 ROBINSON GR, 1992, SCIENCE, V257, P524 SHOUMATOFF A, 1979, WESTCHESTER PORTRAIT SILLINGS J, 1982, THESIS U MINNESOTA M SINCLAIR NR, 1967, U CONNECTICUT OCCASI, V1, P43 SPIELMAN A, 1985, ANNU REV ENTOMOL, V30, P439 STAFFORD KC, 1993, J MED ENTOMOL, V30, P762 WILSON ML, 1985, ANN ENTOMOL SOC AM, V78, P172 0921-2973 Landsc. Ecol.ISI:000077256700003New York Med Coll, Dept Community & Prevent Med, Valhalla, NY 10595 USA. Fish, D, New York Med Coll, Dept Community & Prevent Med, Valhalla, NY 10595 USA.English<7Frank, K. Wissel, C.1998jSpatial aspects of metapopulation survival - from model results to rules of thumb for landscape management363-379Landscape Ecology136landscape indices long-term persistence metapopulation rules of thumb for landscape management spatial configuration species' ecology stochastic model HABITAT CONNECTIVITY REGIONAL DYNAMICS RANDOM-WALK PATTERN CONSERVATION POPULATIONS DISPERSAL MOVEMENT ECOLOGYArticleDeczThe role of spatial configuration for metapopulation survival is analyzed by using a stochastic metapopulation model. This model reveals conditions which must be satisfied by the species' ecology and the landscape settings before a metapopulation can persist over a long term. Taking this as a basis, initial rules of thumb for landscape management are deduced. The following results are highlighted: (1) the critical correlation length d(c) of the extinction processes determines a spatial scale of the metapopulation dynamics. (2) Only species with a dispersal range d(c) above the correlation length d(c) are able to benefit from landscape management at all. (3) A certain metapopulation can only persist over a long term if no patch is inside the range of correlation of another one. (4) There is a hierarchy of importance in the characteristics of a spatial configuration (scale and type) and, hence, in the scopes of landscape management. To conclude, some general consequences for supporting species survival by management are discussed. Some prospects concerning the use of models for decision support in landscape planning are discussed.://000077308100003 ISI Document Delivery No.: 144HH Times Cited: 39 Cited Reference Count: 40 Cited References: BAARS MA, 1984, J ANIM ECOL, V53, P375 DENBOER PJ, 1981, OECOLOGIA, V50, P39 DOAK DF, 1994, ECOLOGY, V75, P615 DRECHSLER M, 1997, THEOR POPUL BIOL, V51, P9 ERRINGTON PL, 1946, Q REV BIOL, V41, P315 FISCHER S, 1996, IN PRESS J APPL ECOL FRANK K, 1994, Z OKOLOGIE NATURSCHU, V3, P167 GILPIN ME, 1990, LIVING PATCHY ENV, P177 GOODMAN D, 1987, VIABLE POPULATIONS C, P11 GOTTSCHALK E, 1996, SPECIES SURVIVAL FRA, P324 GRIMM V, 1996, SCI TOTAL ENVIRON, V183, P151 GYLLENBERG M, 1994, J MATH BIOL, V33, P35 HANSKI I, 1991, BIOL J LINN SOC, V42, P17 HANSKI I, 1994, J ANIM ECOL, V63, P151 HARRISON S, 1988, AM NAT, V132, P360 HARRISON S, 1989, OIKOS, V56, P1 KALKHOVEN JTR, 1995, PRINCIPLES TOOLS STU, P98 KAREIVA PM, 1983, OECOLOGIA, V56, P234 LEFKOVITCH LP, 1985, ECOL MODEL, V30, P297 LEVIN SA, 1992, ECOLOGY, V73, P1943 LEVINS R, 1969, B ENTOMOL SOC AM, V15, P237 MOLONEY KA, 1993, LECT NOTES BIOMATH, V96, P61 NAGYLAKI T, 1993, THEOR POPUL BIOL, V43, P217 NISBET RM, 1982, MODELLING FLUCTUATIN POSCHLOD P, 1996, SPECIES SURVIVAL FRA, P123 QUINN JF, 1987, CONSERV BIOL, V1, P198 SCHIPPERS P, 1996, ECOGRAPHY, V19, P97 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SETTELE S, 1988, NATUR LANDSCHAFT, V11, P467 SISK TD, 1993, NATURE CONSERVATION, V3, P57 STELTER C, 1997, J ANIM ECOL, V66, P508 TISCHENDORF L, 1997, IN PRESS ECOLOGICAL TISCHENDORF L, 1997, OIKOS, V79, P603 VERBOOM J, 1991, BIOL J LINN SOC, V42, P39 VERBOOM J, 1993, IALE STUDIES LANDSCA, V1, P172 WEAVER JL, 1996, CONSERV BIOL, V10, P964 WILCOVE DS, 1986, CONSERVATION BIOL SC, P237 WILSON GG, 1975, ECOLOGY EVOLUTION CO, P523 WISSEL C, 1994, ECOL STU AN, V106, P67 WOLFRAM S, 1992, MATH SYSTEM DOING MA 0921-2973 Landsc. Ecol.ISI:000077308100003Ctr Environm Res Leipzig Halle Ltd, UFZ, Dept Ecol Modelling, D-04301 Leipzig, Germany. Frank, K, Ctr Environm Res Leipzig Halle Ltd, UFZ, Dept Ecol Modelling, POB 2, D-04301 Leipzig, Germany.English|?JFrank, Susanne Fuerst, Christine Witt, Anke Koschke, Lars Makeschin, Franz2014hMaking use of the ecosystem services concept in regional planning-trade-offs from reducing water erosion 1377-1391Landscape Ecology298OctZIn this article we demonstrate how to integrate the ecosystem services concept into regional planning using the example of a case study in Saxony, Germany. We analysed how the reduction of water erosion as a regulating service impacts six other ecosystem services. Ecological integrity, provisioning services (provision of food and fibre, provision of biomass), regulating services (soil erosion protection, drought-risk regulation, flood regulation), and the cultural service landscape aesthetics are taken into account. Using a decision support software, we found that the greening of preferential discharge paths can reduce water erosion by 2-7 %. The introduction of hedgerows and the change in the soil management system from tillage to no-till practices revealed a reduction in the total soil loss by 33 and 89 %, respectively. A combination of the three erosion control measures-greening, hedgerows, and no-till management-reduced the soil loss most efficiently by 92 %. We found synergies between the measures for reducing erosion and the provision of ecological integrity, of regulating and cultural ecosystem services. In contrast, the impact on provisioning services was slightly negative. For the land use planning in the case study region we recommend therefore a combination of greening, hedges, and management change. We found that the applied integrated ecosystem services assessment approach, in combination with stakeholder involvement in the scenario development, helped communicating cross-sectoral effects of different management strategies in a comprehensive way and therefore supports regional planning.!://WOS:000342078600009Times Cited: 1 0921-2973WOS:00034207860000910.1007/s10980-014-9992-3?B'Jerry F. Franklin Richard T.T. Forman1987UCreating landscape patterns by forest cutting: Ecological consequences and principles5-18Landscape Ecology11\landscape pattern, patch size, forestry, forest cutting, forest management, game populationsLandscape structural characteristics, such as patch size, edge length, and configuration, are altered markedly when management regimes are imposed on primeval landscapes. The ecological consequences of clearcutting patterns were explored by using a model of the dispersed patch or checkerboard system currently practiced on federal forest lands in the western United States. Thresholds in landscape structure were observed on a gradient of percentages of landscape cutover. Probability of disturbance, e.g., wildfire and windthrow, and biotic components, e.g., species diversity and game populations, are highly sensitive to these structural changes. Altering the spatial configuration and size of clearcuts provides an opportunity to create alternative landscapes that differ significantly in their ecological characteristics. Both ecosystem and heterogeneous landscape perspectives are critical in resource management.K|?8Franklin, Jerry F. Hagmann, R. Keala Urgenson, Lauren S.2014eInteractions between societal goals and restoration of dry forest landscapes in western North America 1645-1655Landscape Ecology2910DecMillions of acres of dry, frequent-fire woodlands and forests in western North America are the focus of multi-million dollar ecosystem restoration and fuel treatment activities. Societal awareness and engagement with these ecosystems has intensified due to recent mega fires and projections for increased vulnerability of these systems to fire, insects, and drought-related stressors. Also, the importance of goods and services provided by dry forests has expanded to include many values, such as watershed protection, habitat for biodiversity, and recreation as well as timber. Public awareness of fire and other risks associated with current conditions in dry forests generally is high and broad support exists for active management over passive alternatives. Efforts to integrate scientific principles with societal goals in dry forest restoration programs are encouraging but significant social barriers remain related to funding, conflicting goals (e.g., smoke vs. human health and restoration vs. preservation of species habitat), and stakeholder trust. The limited area restored relative to the extensive vulnerable area suggests that the seriousness and complexity of the threats are not fully appreciated or not given sufficient priority for funding, despite stated preferences for restorative management. Hence, challenges remain. Societal choices ultimately determine the goals, extent, and methodology of dry forest restoration programs with science stimulating and informing policy and management decisions.!://WOS:000346920900002Times Cited: 0 0921-2973WOS:00034692090000210.1007/s10980-014-0077-0 |? .Fraterrigo, J. M. Pearson, S. M. Turner, M. G.2009XJoint effects of habitat configuration and temporal stochasticity on population dynamics863-877Landscape Ecology247AugHabitat configuration and temporal stochasticity in the environment are recognized as important drivers of population structure, yet few studies have examined the combined influence of these factors. We developed a spatially explicit simulation model to investigate how stochasticity in survival and reproduction influenced population dynamics on landscapes that differed in habitat configuration. Landscapes ranged from completely contiguous to highly fragmented, and simulated populations varied in mean survival probability (0.2, 0.4, 0.8) and dispersal capacity (1, 3, or 5 cells). Overall, habitat configuration had a large effect on populations, accounting for > 80% of the variation in population size when mean survival and dispersal capacity were held constant. Stochasticity in survival and reproduction were much less influential, accounting for < 1-14% of the variation in population size, but exacerbated the negative effects of habitat fragmentation by increasing the number of local extinctions in isolated patches. Stochasticity interacted strongly with both mean survival probability and habitat configuration. For example, survival stochasticity reduced population size when survival probability was high and habitat was fragmented, but had little effect on population size under other conditions. Reproductive stochasticity reduced population size irrespective of mean survival and habitat configuration, but had the largest effect when survival probability was intermediate and habitat was well connected. Stochasticity also enhanced the variability of population size in most cases. Contrary to expectations, increasing dispersal capacity did not increase population persistence, because the probability of finding suitable habitat within the dispersal neighborhood declined more for the same level of dispersal capacity when fragmentation was high compared to when it was low. These findings suggest that greater environmental variability, as might arise due to climate change, is likely to compound population losses due to habitat fragmentation and may directly reduce population size if reproductive output is compromised. It may also increase variability in population size.://000268430900002;Fraterrigo, Jennifer M. Pearson, Scott M. Turner, Monica G. 0921-2973ISI:00026843090000210.1007/s10980-009-9364-6<7Z.Fraterrigo, J. M. Turner, M. G. Pearson, S. M.2006\Interactions between past land use, life-history traits and understory spatial heterogeneity777-790Landscape Ecology215Cdispersal; herbaceous plants; land-use history; plant abundance; seed size; southern Appalachians; USA SECONDARY FOREST SUCCESSION; NORTHERN HARDWOOD FORESTS; OLD-GROWTH; ENVIRONMENTAL HETEROGENEITY; DISPERSAL LIMITATION; PLANT-COMMUNITIES; HABITAT CONFIGURATION; SEEDLING RECRUITMENT; INTEGRATED ANALYSIS; HERBACEOUS-LAYERArticleJulPast land use has contributed to variability in the distribution of herbaceous species by reducing plant abundance and altering species' chances of recolonizing suitable habitat. Land use may also influence plant heterogeneity by changing environmental conditions within stands. We compared the variability of understory herb abundance in southern Appalachian forests with different land-use histories to examine how past land use influenced plant heterogeneity. The cover of eleven focal. species or genera was estimated and mineral soil concentrations were determined during 2001 and 2002 in eight stands that were farmed, logged, or had no disturbance history (reference) in western North Carolina. Analysis of the coefficients of variation revealed that the abundance of understory plants was more heterogeneous in disturbed stands compared with reference stands. However, when nutrient availability differences were accounted for by detrending the plant cover data, understory variability within stands declined, and no differences between disturbed and reference stands could be distinguished. This finding suggests that nutrient availability has important effects on plant heterogeneity, which depend on past land use. Species dispersal, seed size, and phenology also explained variability in the spatial heterogeneity of plants, but generally only before soil nutrient differences were statistically controlled. In addition to demonstrating that past land use has long-term effects on plant heterogeneity, these results indicate that soil nutrients may play different roles in determining vegetation patterns in historically altered and unaltered forests.://000240500100012 ISI Document Delivery No.: 083ZE Times Cited: 0 Cited Reference Count: 78 Cited References: *SAMAB, 1996, 5 SAMAB USDA FOR SER ANDERSON RC, 1969, ECOLOGY, V50, P255 BEALS EW, 1964, ECOLOGY, V45, P777 BEATTY SW, 1984, ECOLOGY, V65, P1406 BELL G, 1994, EXPLOITATION ENV HET, P391 BELLEMARE J, 2002, J BIOGEOGR, V29, P1401 BOSSUYT B, 1999, J ECOL, V87, P628 BRATTON SP, 1976, AM NAT, V110, P679 BRAUN LE, 1950, DECIDUOUS FORESTS E BUTAYE J, 2002, J VEG SCI, V13, P27 CHESSON PL, 1981, AM NAT, V117, P923 CHRISTENSEN NL, 1984, J ECOL, V72, P25 CHRISTENSEN NL, 2003, HERBACEOUS LAYER FOR, P224 CLEVELAND WS, 1988, J AM STAT ASSOC, V83, P596 CLINGER W, 1976, ANN STAT, V4, P736 COMPTON JE, 2000, ECOLOGY, V81, P2314 COTTINGHAM KL, 2000, ECOL LETT, V3, P340 DAVIS DE, 2000, THERE ARE MOUNTAINS DAY KJ, 2003, J ECOL, V91, P305 DAY KJ, 2003, J ECOL, V91, P541 DUPOUEY JL, 2002, ECOLOGY, V83, P2978 DUPRE C, 2002, J ECOL, V90, P796 DZWONKO Z, 2002, ANN BOT-LONDON, V90, P245 EBERHARDT RW, 2003, ECOL APPL, V13, P68 EHRLEN J, 2000, ECOLOGY, V81, P1667 ERIKSSON O, 1995, FLORA, V190, P65 FARLEY RA, 1999, J ECOL, V87, P849 FLINN KM, 2005, FRONT ECOL ENVIRON, V3, P243 FRATERRIGO JM, 2005, ECOL MONOGR, V75, P215 FRELICH LE, 1998, J ECOL, V86, P149 FRELICH LE, 2003, J ECOL, V91, P283 GAUCH HG, 1982, MULTIVARIATE ANAL CO GILLIAM FS, 1993, B TORREY BOT CLUB, V120, P445 GILLIAM FS, 1995, ECOL APPL, V5, P947 GLEASON HA, 1991, MANUAL VASCULAR PLAN GREIGSMITH P, 1979, J ECOL, V67, P755 HALPERN CB, 1989, ECOLOGY, V70, P704 HICKS DJ, 1980, AM MIDL NAT, V104, P209 HOBBS RJ, 1985, OECOLOGIA, V67, P342 HONNAY O, 1999, FOREST ECOL MANAG, V115, P157 JACQUEMYN H, 2003, ECOGRAPHY, V26, P768 JURIK TW, 1985, OECOLOGIA, V66, P394 KING RS, 2004, ECOSYSTEMS, V7, P75 KOLB A, 2004, J VEG SCI, V15, P199 LEACH MK, 1999, ECOL MONOGR, V69, P353 LEVENE H, 1960, CONTRIBUTIONS PROBAB, V1, P278 MABRY C, 2000, J VEG SCI, V11, P213 MABRY CM, 2004, OIKOS, V107, P497 MANCERA JE, 2005, PLANT ECOL, V178, P39 MATHERON G, 1963, ECON GEOL, V58, P1246 MATLACK GR, 1994, ECOLOGY, V75, P1491 MCINTYRE S, 1994, J VEG SCI, V5, P373 MILLER TF, 2002, ECOL MONOGR, V72, P487 MOTZKIN G, 1996, ECOL MONOGR, V66, P345 MULLER RN, 1990, B TORREY BOT CLUB, V117, P101 NEWELL SJ, 1978, ECOLOGY, V59, P228 PALMER MW, 1990, COENOSES, V5, P79 PEARSON SM, 1998, CASTANEA, V63, P382 PETERKEN GF, 1984, J ECOL, V72, P155 RADFORD AE, 1964, MANUAL VASCULAR FLOR REED RA, 1993, J VEG SCI, V4, P329 RICHARD M, 2000, ECOGRAPHY, V23, P231 ROBERTSON GP, 1993, OECOLOGIA, V96, P451 ROSSI RE, 1992, ECOL MONOGR, V62, P277 SCHELLER RM, 2002, ECOL APPL, V12, P1329 SCHULTZ BB, 1985, SYST ZOOL, V34, P449 SCHWARZ PA, 2003, ECOLOGY, V84, P1862 SEABLOOM EW, 2005, ECOL MONOGR, V75, P199 STRUIK CJ, 1962, AM MIDL NAT, V68, P285 SVENNING JC, 2002, PLANT ECOL, V160, P169 TREXLER JC, 1993, ECOLOGY, V74, P1629 VERHEYEN K, 2001, J ECOL, V89, P829 VERHEYEN K, 2001, J VEG SCI, V12, P567 VERHEYEN K, 2003, J ECOL, V91, P731 WEAR DN, 1998, ECOSYSTEMS, V1, P575 WESTOBY M, 2002, ANNU REV ECOL SYST, V33, P125 WIJESINGHE DK, 1999, J ECOL, V87, P860 YARNELL SL, 1998, SRS18 USDA FS 0921-2973 Landsc. Ecol.ISI:000240500100012Univ Wisconsin, Dept Zool, Madison, WI 53706 USA. Iowa State Univ Sci & Technol, Dept Ecol Evolut & Organismal Biol, Ames, IA 50011 USA. Mars Hill Coll, Dept Biol, Mars Hill, NC 28754 USA. Fraterrigo, JM, Univ Wisconsin, Dept Zool, Madison, WI 53706 USA. jmfrater@iastate.eduEnglishڽ7 Frazier, AmyE Wang, Le2013OModeling landscape structure response across a gradient of land cover intensity233-246Landscape Ecology282Springer NetherlandslLand cover intensity Scalograms Landscape metrics Curve fitting Threshold Sub-pixel classification Saltcedar 2013/02/01+http://dx.doi.org/10.1007/s10980-012-9839-8 0921-2973Landscape Ecol10.1007/s10980-012-9839-8English|?Frazier, Amy E.2014HA new data aggregation technique to improve landscape metric downscaling 1261-1276Landscape Ecology297AugScale is a fundamental concept in landscape ecology and considerable attention has been given to the scale-dependent relationships of landscape metrics. Many metrics have been found to exhibit very consistent scaling relationships as map resolution (i.e., pixel or grain size) is increased. However, these scaling relationships tend to break down when attempting to 'downscale' them, and the scaling function is often unable to accurately predict metric values for finer resolutions than the original data. The reasons for this breakdown are not well understood. This research examines the downscaling behavior of metrics using various data aggregation techniques in an attempt to better understand the characteristics of metric scaling behavior. First, downscaling performance is examined using the traditional method of aggregation known as 'majority rules'. Second, a new data aggregation technique is introduced that utilizes fractional land cover abundances obtained from sub-pixel remote sensing classifications in order to capture a greater amount of the spatial heterogeneity present in the landscape. The goal of this new aggregation technique is to produce a more accurate scaling relationship that can be downscaled to predict metric values at fine resolutions. Results indicate that sub-pixel classifications have the potential to transform data aggregation to allow more accurate downscaling for certain landscapes, but accuracy is linked to the spatial heterogeneity of the landscape.!://WOS:000339831300014Times Cited: 0 0921-2973WOS:00033983130001410.1007/s10980-014-0066-3/ڽ7 JFreitas, MarcosWellausenDias Santos, JoãoRobertodos Alves, DiógenesSalas2013vLand-use and land-cover change processes in the Upper Uruguay Basin: linking environmental and socioeconomic variables311-327Landscape Ecology282Springer NetherlandsLand use and cover change Geographically weighted regression Canonical correspondence analysis Spatial clustering Landscape structure Nature and society 2013/02/01+http://dx.doi.org/10.1007/s10980-012-9838-9 0921-2973Landscape Ecol10.1007/s10980-012-9838-9Englishsڽ7Freudenberger, Lisa Hobson, PeterR Rupic, Slaven Pe’er, Guy Schluck, Martin Sauermann, Julia Kreft, Stefan Selva, Nuria Ibisch, PierreL2013Spatial road disturbance index (SPROADI) for conservation planning: a novel landscape index, demonstrated for the State of Brandenburg, Germany 1353-1369Landscape Ecology287Springer NetherlandsBuffer effect Landscape indices Landscape fragmentation Road impact Roadless areas Traffic volume Traffic disturbance Road ecology 2013/08/01+http://dx.doi.org/10.1007/s10980-013-9887-8 0921-2973Landscape Ecol10.1007/s10980-013-9887-8English<7Y=Frimpong, E. A. Ross-Davis, A. L. Lee, J. G. Broussard, S. R.2006Biophysical and socioeconomic factors explaining the extent of forest cover on private ownerships in a Midwestern (USA) agrarian landscape763-776Landscape Ecology215biophysical attributes; conservation programs; Indiana; landowner attributes; midwest; nonindustrial private forest; private lands policy; USA; variation partitioning ENVIRONMENTAL CONCERN; UNITED-STATES; SOCIAL BASES; MANAGEMENT; MOTIVATIONS; MICHIGAN; TIMEArticleJulAs landscape fragmentation continues to escalate, it is imperative that we improve our understanding of the factors that contribute to the creation and retention of forest on privately-owned land to most effectively design and implement conservation policy. This article presents the percentages of variation in the proportion of forest on private ownerships across an agriculturally-dominated landscape in north-central Indiana, USA that can be explained by biophysical characteristics, landowner (socioeconomic) attributes, and private landowner assistance programs. While biophysical characteristics of the land accounted for the majority of variation explained (17.35%, p < 0.0001, n = 194), attitudinal and demographic attributes of the landowners contributed significantly to explaining additional variation (7.97%, p < 0.0001), and overlapped with biophysical characteristics to explain another 17.31%. Program familiarity and enrollment did not explain a significant amount of the variation independent of either biophysical or landowner attributes. Private landowner assistance programs should broaden their objectives and increase incentives to appeal to the variety of landowners who possess the decision-making authority for most of the land in the region and the nation as a whole.://000240500100011 !ISI Document Delivery No.: 083ZE Times Cited: 0 Cited Reference Count: 43 Cited References: *US CENS BUR, 2005, STAT COUNT QUICK FAC *US GEOL SURV, 2004, NAT EL DAT SET ALIG RJ, 1990, SE60 USDA FOR SERV ANDERSON MJ, 1998, AUST J ECOL, V23, P158 AUCLAIR AN, 1976, ECOLOGY, V57, P431 BEACH RH, 2005, FOREST POLICY ECON, V7, P261 BERNARDIN L, 2002, INDIANA WATER RESOUR BEST C, 2001, AM PRIVATE FORESTS S, P268 BIRCH TW, 1996, RESOURCE B USDA NE, V134 BROWN DG, 2003, LANDSCAPE ECOL, V18, P777 BURGI M, 2002, ECOSYSTEMS, V5, P184 BUTLER BJ, 2004, J FOREST, V102, P4 DILLMAN D, 2000, MAIL INTERNET SURVEY EGAN AF, 2000, J FOREST, V98, P26 ERICKSON DL, 2002, LANDSCAPE URBAN PLAN, V58, P101 FRANZMEIER DP, 2001, PURDUE U COOPERAT ID, V72, P7 FRISSELL CA, 1996, WATER RESOUR BULL, V32, P229 GUBER DL, 2003, GRASSROOTS GREEN REV, P279 HULL RB, 2004, J FOREST, V102, P14 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 JONES RE, 1992, RURAL SOCIOL, V57, P28 KANAGY CL, 1995, REV RELIG RES, V37, P33 KENDRA A, 2005, FOREST SCI, V51, P142 LENGENDRE P, 1998, NATO ASI SERIES G, V14 LIDESTAV G, 2000, SCAND J FOREST RES, V15, P378 LONNSTEDT L, 1997, SCAND J FOREST RES, V12, P302 LOYLAND K, 1995, J FOREST ECON, V1, P219 MAGALHAES MF, 2002, FRESHWATER BIOL, V47, P1015 MALLOW CL, 1964, CHOOSING VARIABLES L MARSH PC, 1982, FISHERIES, V7, P16 MEDLEY KE, 1995, LANDSCAPE ECOL, V10, P161 MOORE JE, 2005, J WILDLIFE MANAGE, V69, P933 NETER J, 1996, APPL LINEAR STAT MOD NORUSIS MJ, 2003, SPSS 12 0 STAT PROCE ODUM WE, 1982, BIOSCIENCE, V32, P728 OMERNIK JM, 1987, ANN ASSOC AM GEOGR, V77, P118 PAN D, 1998, LANDSCAPE ECOL, V14, P35 ROYER JP, 1987, J FOREST, V85, P45 SCULL PR, 2004, J BIOGEOGR, V31, P1503 TURNER WM, 1997, WATERSHED RESTORATIO, P158 VANLIERE KD, 1980, PUBLIC OPIN QUART, V44, P181 WHITTAKER J, 1984, APPL STAT-J ROY ST C, V33, P52 ZHANG DW, 2001, LAND ECON, V77, P443 0921-2973 Landsc. Ecol.ISI:000240500100011?Purdue Univ, Dept Forestry & Nat Resources, W Lafayette, IN 47907 USA. Purdue Univ, Dept Agr Econ, W Lafayette, IN 47907 USA. Purdue Univ, Dept Forestry & Nat Resources, W Lafayette, IN 47907 USA. Ross-Davis, AL, Purdue Univ, Dept Forestry & Nat Resources, 715 W State St, W Lafayette, IN 47907 USA. arossdav@purdue.eduEnglish|? Fritschle, J. A.2009Pre-EuroAmerican settlement forests in Redwood National Park, California, USA: a reconstruction using line summaries in historic land surveys833-847Landscape Ecology246JulExtensive logging in the twentieth century destroyed much of the coniferous forests in the lower Redwood Creek basin of Redwood National Park. Restoration of cutover lands requires the identification of historical, pre-logging reference conditions. Field notes from the original Public Land Surveys were used to reconstruct the pre-EuroAmerican settlement forests. Most reconstructive studies based on historic surveys rely on bearing tree evidence over large areas to determine vegetation patterns over several hundreds to thousands of square kilometers. Due to the small size of the study area (approximately 200 km(2)), bearing tree evidence could not accurately reconstruct the vegetation at this scale. Instead, lists of the overstory and understory vegetation for each surveyed mile (line summaries) were employed. Analysis of line summaries evidence identified the historical importance, geographical range, and environmental influences on woody species and vegetation communities. Topography, especially elevation, and soil texture were significantly correlated with plot-scale ordination scores derived from non-metric multidimensional scaling. The influence of topography and distance to ocean coast on the historical distribution of dominant woody species concurs with findings from present-day field studies of local and regional old-growth forest. A comparison with present-day vegetation maps revealed that coast redwood (Sequoia sempervirens), Douglas fir (Pseudotsuga menziesii), Sitka spruce (Picea sitchensis), and red alder (Alnus rubra) experienced the most substantive changes in the vegetation as a result of twentieth century land use activities.://000268248100010Fritschle, Joy A. 0921-2973ISI:00026824810001010.1007/s10980-009-9361-98<7@Fritz, H. Said, S. Renaud, P. C. Mutake, S. Coid, C. Monicat, F.2003}The effects of agricultural fields and human settlements on the use of rivers by wildlife in the mid-Zambezi valley, Zimbabwe293-302Landscape Ecology183diversity GIS human settlements landscape species richness wildlife species Zimbabwe WILDEBEEST MIGRATION RESPONSE MODEL NATIONAL-PARK POPULATIONS REGRESSION KALAHARI IMPACT PASTORALISM COMPETITION EXTINCTIONArticleAprAfter the eradication of the Tse-Tse fly in the Mid-Zambezi valley, human settlements and fields extended mainly along the main rivers. In order to investigate the consequences of this human development on wildlife diversity we monitored three rivers of the Mid-Zambezi valley in Zimbabwe: Angwa, Manyame and Kadzi. The rivers were divided in segments of 200 m which were checked for spoors in order to assess the number of species and the number of individuals that used the segments. Human settlements were also recorded. We used a GIS to define the spatial characteristics of the fields present along the rivers, and related them to the distribution and abundance of wild species spoors in the river beds and banks. Our results show that the number of species in one segment of the river decreased with the increasing size of the field area bordering the segment. For all the major ungulate species, the numbers of individuals recorded per segment decreased with increasing field area. A similar trend was observed for small and medium-sized carnivores, though they were in lower numbers when present. Our analyses thus confirm that the extension of human agriculture in wildlife areas has an impact on most wild species, but we also define some threshold value of field size above which there seem to be an acceleration of the decrease in wildlife density and diversity: 3.2 ha for medium and small herbivores and carnivores; only the elephant seem to tolerate larger field area with a threshold value of 32 ha.://000183770600007 ISI Document Delivery No.: 694JD Times Cited: 2 Cited Reference Count: 48 Cited References: *BIOD PROJ, 2001, MANK AN MID ZAMB VAL ALLEN CR, 2001, BIOL CONSERV, V99, P135 AUSTIN MP, 1984, VEGETATIO, V55, P11 AYENI JSO, 1975, E AFR WILDL J, V13, P305 BENNETT AF, 1998, LINKAGES LANDSCAPE R BRASHARES JS, 2001, P ROY SOC LOND B BIO, V268, P2473 CHENJE M, 2000, STATE ENV ZAMBEZI BA CHILD G, 1991, GLOBAL TRENDS WILDLI CLEVELAND WS, 1979, J AM STAT ASSOC, V74, P829 CLEVELAND WS, 1985, SCIENCE, V229, P828 CORNELIUS C, 2001, CONSERV BIOL, V15, P1396 CUMMING DHM, 1993, WORLD C AN PROD P 7 DELEEUW J, 2001, BIOL CONSERV, V100, P297 DUTOIT JT, 1999, BIODIVERS CONSERV, V8, P1643 EHRLICH PR, 1988, BIODIVERSITY, P21 ELSTON DA, 1996, ECOLOGY, V77, P2538 FOX BJ, 2000, ISLAND BIOGEOGRAPHY, P19 FRITZ H, 1996, J APPL ECOL, V33, P589 HALLADAY P, 1995, CONSERVING BIODIVERS, P229 HOARE RE, 1999, J APPL ECOL, V36, P689 HUISMAN J, 1993, J VEG SCI, V4, P37 KNIGHT MH, 1988, J ARID ENVIRON, V15, P269 LANDRES PB, 1988, CONSERV BIOL, V2, P316 LEWIS DM, 1997, CONSERV BIOL, V11, P59 MANLY B, 1993, STAT DESIGN ANAL FIE MARTIN RB, 1986, COMMUNAL AREAS MANAG MITCHELL A, 1999, ESRI GUIDE GIS ANAL MORTBERG UM, 2001, LANDSCAPE ECOL, V16, P193 MUCHAAL PK, 1999, CONSERV BIOL, V13, P385 MURINDAGOMO F, 1989, AFRICA TECHNICAL DEP, P123 NAUGHTONTREVES L, 1998, CONSERV BIOL, V12, P156 NEWING H, 2001, BIODIVERS CONSERV, V10, P99 NEWMARK WD, 1994, CONSERV BIOL, V8, P249 ODLAND A, 1995, VEGETATIO, V120, P115 OWENSMITH N, 1993, P 17 INT GRASSL C NZ, P691 PRINS HHT, 1992, ENVIRON CONSERV, V19, P117 SERNEELS S, 2001, J BIOGEOGR, V28, P391 STANDER PE, 1997, J ZOOL 2, V242, P329 STANDER PE, 1998, J APPL ECOL, V35, P378 STEPHENS PA, 2001, BIOL CONSERV, V100, P307 TERBRAAK CJF, 1985, BIOMETRICS, V41, P859 TERBRAAK CJF, 1986, VEGETATIO, V65, P3 TREXLER JC, 1993, ECOLOGY, V74, P1629 VERLINDEN A, 1997, BIOL CONSERV, V82, P129 WESTERN D, 1989, CONSERVATION PARKS W WILLIAMSON D, 1988, AFR J ECOL, V26, P269 WOODROFFE R, 2000, ANIM CONSERV 2, V3, P165 YOUNG MD, 1993, WORLDS SAVANNAS, P321 0921-2973 Landsc. Ecol.ISI:000183770600007 CNRS, CEBC, UPR 1934, F-79360 Beauvoir Sur Niort, France. INRA, IRGM, F-31326 Castanet Tolosan, France. Biodivers Project, Harare, Zimbabwe. CIRAD EMVT, Econap, F-34032 Montpellier, France. Fritz, H, CNRS, CEBC, UPR 1934, POB 14, F-79360 Beauvoir Sur Niort, France.English ~?Fu, B. J. Lu, Y. H. Chen, L. D.20086Expanding the bridging capability of landscape ecology375-376Landscape Ecology234"://WOS:000254250400001 Times Cited: 0WOS:000254250400001(10.1007/s10980-008-9214-y|ISSN 0921-2973?.%Fuentes, E.R. R. Aviles A. Segura1989RLandscape Change under Indirect Effects of Human Use: the Savanna of Central Chile73-80Landscape Ecology222Chile, Seed survival, Herbivory, Landscape ecologyThe Chilean Intermediate Depression to the north of Santiago has experienced a physiognomical transformation from a Prosopis chilensis woodland to an Acacia caven savanna. Today P. chilensis trees are scarce and belong mostly to the larger size classes. By contrast A. caven seems to reproduce frequently and its populations consist of individuals of all size classes. In this paper we document these changes and report the results of tests aimed at determining the causes of these physiognomical changes. We found that livestock, leporids, introduced Mediterranean forbs and agriculture account for differences in seed dispersal and survival of A. caven and P. chilensis, which can explain the documented changes in the Chilean landscape.r|?;Fuerst, Christine Opdam, Paul Inostroza, Luis Luque, Sandra2014mEvaluating the role of ecosystem services in participatory land use planning: proposing a balanced score card 1435-1446Landscape Ecology298Oct The application of the ecosystem services (ES) concept in land use planning has great potential to enhance the awareness of planning actors on their interactions. At the same time it can contribute to improve the linkage between the role of land use patterns and the understanding of land system functioning and its contribution to human well-being. The concept should be developed in a way that can be applicable in socio-ecological systems where nature and society are capable of enhancing their roles mutually. The objective of this paper is to suggest a standardized scheme and generalizable criteria to assess how successful the application of the ES concept contributed to facilitate participatory planning. We consider three potential advantages and three critical aspects for how to improve the applicability and relevance of the ES concept in planning. Hereon based, we present a balanced score card tool for which we broke down to advantages and risks into concrete questions. We illustrate the application of this approach with two case studies, representatives of two major governance schemes in relation to land use planning. We demonstrate that the balanced score card approach helps to reveal potential imbalances regarding the consideration of different ES groups. It supports testing the potential of the ES concept to enhance or not interactions of local and regional actors. We conclude that the framework should be reconsidered after a set of case studies to be developed into a monitoring tool for supporting planning practices.!://WOS:000342078600013Times Cited: 0 0921-2973WOS:00034207860001310.1007/s10980-014-0052-9 ]<7Fuhlendorf, S. D. Smeins, F. E.1996NSpatial scale influence on longterm temporal patterns of a semi-arid grassland107-113Landscape Ecology112scaling; temporal patterns; equilibrium; stability; succession; predictability; variability; grassland; savannah; chaos; ecological scale; vegetation dynamics ECOLOGYArticleAprLongterm (45 years) temporal data were used to assess the influence of spatial scale on temporal patterns of a semi-arid west Texas grassland. Temporal basal area dynamics of common curlymesquite (Hilaria belangeri (Steud.) Nash) collected from permanent plots within two areas that were released from disturbance (longterm overgrazing and drought), were evaluated at two spatial scales (quadrat, site). Wiens (1989) proposed hypotheses to characterize the influence of scale on variability, predictability, and equilibrium. These hypotheses were tested for this grassland and temporal patterns observed were different for each spatial scale. The large scale (site) was characterized by low variation between units, high variation within units, high potential predictability, and possible movement toward a fluctuating but relatively stable or equilibrial state. At the small scale (quadrat), variation between units was high, predictability low, and there was no indication of movement toward a stable state; chaotic behavior may be expressed at this scale although the length of the temporal record may not be sufficient to evaluate this phenomenon.://A1996UN74500003 ISI Document Delivery No.: UN745 Times Cited: 14 Cited Reference Count: 25 Cited References: BEDWARD M, 1992, AUST J ECOL, V17, P133 BUTLER JL, 1988, OIKOS, V51, P306 CARLILE DW, 1989, LANDSCAPE ECOLOGY, V2, P203 COSTANZA R, 1994, LANDSCAPE ECOL, V9, P47 CRAWLEY MJ, 1990, POPULATION REGULATIO CULLINAN VI, 1992, LANDSCAPE ECOL, V7, P211 GLEICK J, 1987, CHAOS MAKING NEW SCI GREIGSMITH P, 1964, QUANTITATIVE PLANT E HASTINGS A, 1993, ANNU REV ECOL SYST, V24, P1 HATCH SL, 1990, MP1655 TX AGR EXP ST KLIJN F, 1994, LANDSCAPE ECOL, V9, P89 LEVIN SA, 1992, ECOLOGY, V73, P1943 MENGE BA, 1990, TRENDS ECOL EVOL, V5, P52 ONEILL RV, 1986, HIERARCHICAL CONCEPT ONEILL RV, 1989, LANDSCAPE ECOL, V3, P193 ONEILL RV, 1991, LANDSCAPE ECOL, V5, P137 RAHEL FJ, 1990, AM NAT, V136, P328 SCHAFFER WM, 1985, BIOSCIENCE, V35, P342 SMEINS FE, 1976, J RANGE MANAGE, V29, P24 SMEINS FE, 1988, EDWARDS PLATEAU VEGE SUGIHARA G, 1990, TRENDS ECOL EVOL, V5, P79 TILMAN D, 1991, NATURE, V353, P653 TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 TURNER SJ, 1992, QUANTITATIVE METHODS WIENS JA, 1989, FUNCT ECOL, V3, P385 0921-2973 Landsc. Ecol.ISI:A1996UN74500003UFuhlendorf, SD, TEXAS A&M UNIV,DEPT RANGELAND ECOL & MANAGEMENT,COLLEGE STN,TX 77843.Englishs<7CFuhlendorf, S. D. Woodward, A. J. W. Leslie, D. M. Shackford, J. S.2002{Multi-scale effects of habitat loss and fragmentation on lesser prairie-chicken populations of the US Southern Great Plains617-628Landscape Ecology177Jagriculture conservation ecology fragmentation grasslands hierarchy landscape change landscape dynamics landscape structure lesser prairie-chicken rangeland S. Great Plains USA scale species conservation LANDSCAPE STRUCTURE SEMIARID GRASSLAND BREEDING BIRDS SPATIAL SCALE LAND-USE ECOLOGY PATTERNS EXTINCTION COMMUNITIES MOVEMENTSArticleNov Large-scale patterns of land use and fragmentation have been associated with the decline of many imperiled wildlife populations. Lesser prairie-chickens (Tympanuchus pallidicinctus) are restricted to the southern Great Plains of North America, and their population and range have declined by > 90% over the past 100 years. Our objective was to examine scale-dependent relationships between landscape structure and change and long-term population trends for lesser prairie-chicken populations in the southern Great Plains. We used a geographic information system (GIS) to quantify landscape composition, pattern and change at multiple scales (extents) for fragmented agricultural landscapes surrounding 10 lesser prairie-chicken leks. Trend analysis of long-term population data was used to classify each population and landscape (declined, sustained). We analyzed metrics of landscape structure and change using a repeated measures analysis of variance to determine significant effects (alpha = 0.10) between declining and sustained landscapes across multiple scales. Four metrics of landscape structure and change (landscape change index, percent cropland, increases in tree-dominated cover types, and changes in edge density) contained significant interactions between population status and scale, indicating different scaling effects on landscapes with declining and stable populations. Any single spatial scale that was evaluated would not have given complete results of the influences of landscape structure and change on lesser prairie-chicken populations. The smallest spatial scales (452, 905, and 1,810 ha) predicted that changes in edge density and largest patch size were the only important variables, while large-scale analysis (7,238 ha) suggested that the amount of cropland, increase in trees (mostly Juniperus virginiana), and general landscape changes were most important. Changes in landscape structure over the past several decades had stronger relationships with dynamics of lesser prairie-chicken populations than current landscape structure. Observed changes suggest that these local populations may be appropriately viewed from a metapopulation perspective and future conservation efforts should evaluate effects of fragmentation on dispersal, colonization, and extinction patterns.://000179746400002 q ISI Document Delivery No.: 624EB Times Cited: 12 Cited Reference Count: 72 Cited References: *ENV SYST RES I IN, 1995, UND GIS ARCH INFO ME *SAS I, 1985, SAS US GUID STAT ALDRICH JW, 1963, J WILDLIFE MANAGE, V27, P529 ANDREN H, 1994, OIKOS, V71, P355 ARCHER S, 1994, ECOLOGICAL IMPLICATI, P13 BERGIN TM, 2000, LANDSCAPE ECOL, V15, P131 BISSONETTE JA, 1997, WILDLIFE LANDSCAPE E, P3 BURKE D, 1998, ECOGRAPHY, V21, P472 CANNON RW, 1981, J WILDLIFE MANAGE, V45, P521 CARLILE DW, 1989, LANDSCAPE ECOLOGY, V2, P203 COLLINS BT, 1990, SURVEY DESIGNS STAT, V90, P63 COPPEDGE BR, 2001, ECOL APPL, V11, P47 COSTANZA R, 1994, LANDSCAPE ECOL, V9, P47 CRAWFORD JA, 1976, J WILDLIFE MANAGE, V40, P96 CRAWFORD JA, 1980, P PRAIR GROUS S OKL, P1 CUTLER A, 1991, CONSERV BIOL, V5, P496 DAVISON VE, 1940, J WILDLIFE MANAGE, V4, P55 DEBINSKI DM, 2000, CONSERV BIOL, V14, P342 FARINA A, 2000, LANDSCAPE ECOLOGY AC FORMAN RTT, 1986, LANDSCAPE ECOLOGY FRITZ RS, 1979, OECOLOGIA, V42, P57 FUHLENDORF SD, 1996, ECOL MODEL, V90, P245 FUHLENDORF SD, 1996, LANDSCAPE ECOL, V11, P107 FUHLENDORF SD, 1999, J VEG SCI, V10, P731 FUHLENDORF SD, 2000, RESTORATION ECOLOGY, V10, P401 GARDNER RH, 1998, ECOLOGICAL SCALE THE, P17 GIESEN KM, 1994, PRAIRIE NATURALIST, V26, P175 GIESEN KM, 1994, SOUTHWEST NAT, V39, P96 GIESEN KM, 1998, BIRDS N AM, V364, P1 GLENN SM, 1992, LANDSCAPE ECOL, V7, P243 GREIGSMITH P, 1983, QUANTITATIVE PLANT E HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 JACKSON AS, 1963, J WILDLIFE MANAGE, V27, P733 JONES RE, 1963, J WILDLIFE MANAGE, V27, P757 KERSHAW KA, 1957, ECOLOGY, V38, P291 KNICK ST, 2000, ECOLOGY, V81, P220 KOLASA J, 1998, ECOLOGICAL SCALE THE, P55 LAW BS, 1998, BIODIVERS CONSERV, V7, P323 LEIMGRUBER P, 1994, J WILDLIFE MANAGE, V58, P254 LEOPOLD A, 1933, GAME MANAGEMENT LEVIN SA, 1992, ECOLOGY, V73, P1943 LITTELL RC, 1996, SAS SYSTEM MIXED MOD MCGARIGAL K, 1995, ECOL MONOGR, V65, P235 MENGE BA, 1990, TRENDS ECOL EVOL, V5, P52 MILLER JN, 1997, LANDSCAPE ECOL, V12, P137 MILNE BT, 1989, LANDSCAPE ECOL, V2, P101 MOSES LE, 1990, SURVEY DESIGNS STAT, V90, P71 NIEMUTH ND, 2000, J WILDLIFE MANAGE, V64, P278 ONEILL RV, 1986, HIERARCHICAL CONCEPT PULLIAM HR, 1988, AM NAT, V132, P652 PULLIAM HR, 1992, ECOL APPL, V2, P165 RILEY TZ, 1992, J WILDLIFE MANAGE, V56, P383 RILEY TZ, 1993, PRAIRIE NATURALIST, V25, P243 RILEY TZ, 1994, PRAIRIE NATURALIST, V26, P183 RITCHIE ME, 1997, WILDLIFE LANDSCAPE E, P160 RITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 RYAN MR, 1998, AM MIDL NAT, V140, P111 SAAB V, 1999, ECOL APPL, V9, P135 SCHNEIDER DC, 1994, QUANTITATIVE ECOLOGY STOMMEL H, 1963, SCIENCE, V139, P572 SUGIHARA G, 1990, TRENDS ECOL EVOL, V5, P79 SWETNAM TW, 1999, ECOL APPL, V9, P1189 TAYLOR MA, 1980, J WILDLIFE MANAGE, V44, P521 TAYLOR MA, 1980, RM77 US FOR SERV ROC TSCHARNTKE T, 1992, CONSERV BIOL, V6, P530 TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 TURNER MG, 1991, QUANTITATIVE METHODS TURNER MG, 1997, WILDLIFE LANDSCAPE E, P331 WIENS JA, 1989, FUNCT ECOL, V3, P385 WIENS JA, 1993, OIKOS, V66, P369 WIENS JA, 1995, ECOLOGY, V76, P663 WOODWARD AJW, 2001, AM MIDL NAT, V145, P261 0921-2973 Landsc. Ecol.ISI:000179746400002AOklahoma State Univ, Dept Plant & Soil Sci, Stillwater, OK 74078 USA. Oklahoma State Univ, Dept Zool, Biol Resources Div,US Geol Survey, Oklahoma Cooperat Fish & Wildlife Res Unit, Stillwater, OK 74078 USA. Fuhlendorf, SD, Oklahoma State Univ, Dept Plant & Soil Sci, Stillwater, OK 74078 USA. fuhlend@mail.pss.okstate.eduEnglish<7%Fukamachi, K. Oku, H. Nakashizuka, T.2001oThe change of a satoyama landscape and its causality in Kamiseya, Kyoto Prefecture, Japan between 1970 and 1995703-717Landscape Ecology168economic growth fragmentation land abandonment landscape change landscape diversity land use satoyama landscape (Japanese traditional rural landscape) AGRICULTURAL LANDSCAPES LAND-USE DIVERSITY DYNAMICS BIODIVERSITY VEGETATION PATTERNS REGION FRANCEArticleWe focused on patterns of land use in a particular satoyama landscape (Japanese traditional rural landscape, comprised of an integral social and ecological network of a village and its surroundings, such as agricultural lands, open forestlands and forests), and the effects of human activities upon them during Japan's economic growth of the last few decades. Changes of landscape patterns and their probable causes were traced since the beginning of the 1900s to the present, and clarified. Societal, economic and technological changes, especially those that occurred after 1970, were considered the focal points from which major landscape changes developed. We compared the spatial features, patterns of land use and landscape diversities of each land unit, defined in terms of both their natural and man-made conditions for the year 1970, to those of 1995. We found land-use diversity to be strongly related to changes in the patterns of land use, with a decrease in diversity for all land units after 1970. Diversity of forest-age distribution on the other hand, increased. These changes, with the complex, changing patterns of each land unit, could be explained by differences in accessibility from the village and variations in the topography, as well as land ownership of the land units. We selected those land units found to have responded to these factors between 1970 and 1995, and classified them into four types of pattern changes, determined mainly by accessibility and topography.://000175490900003 ISI Document Delivery No.: 550EP Times Cited: 6 Cited Reference Count: 36 Cited References: *ENV AG, 1991, RED DAT BOOK VERT JA *ENV AG, 1992, RED DAT BOOK INV JAP *JAP SOC PLANT TAX, 1993, RED DAT BOOK PLANTS ANTROP M, 1997, LANDSCAPE URBAN PLAN, V38, P105 BUREL F, 1995, AGR ECOSYST ENVIRON, V55, P193 DUELLI P, 1997, AGR ECOSYST ENVIRON, V62, P81 FUENTES ER, 1990, CHANGING LANDSCAPES, P165 FUKAMACHI K, 1997, J JAP I LANDSC ARCHI, V60, P521 FUKAMACHI K, 1998, J JAP I LANDSC ARCHI, V61, P276 FUKAMACHI K, 1999, KYOTO J JAP I LANDSC, V62, P687 HESTER AJ, 1996, BIOL CONSERV, V77, P41 HORI S, 1997, FORESTSCAPE DESIGN D IIDA S, 1995, FOREST ECOL MANAG, V73, P197 KAMADA M, 1990, JPN J ECOL, V40, P137 KAMADA M, 1996, LANDSCAPE ECOL, V11, P15 KAMADA M, 1997, LANDSCAPE URBAN PLAN, V37, P85 KAMEYAMA A, 1996, VEGETATION MANAGEMEN LAWRENCE D, 1998, LANDSCAPE ECOL, V13, P135 MEDLEY KE, 1995, LANDSCAPE ECOL, V10, P161 NAGAIKE T, 1997, J FOR RES, V2, P193 NAGAIKE T, 1999, LANDSCAPE URBAN PLAN, V43, P209 NAKAGOSHI N, 1992, LANDSCAPE ECOL, V7, P111 NAKAGOSHI N, 1997, J INT DEV COOP, V3, P1 NAKAJIMA M, 1996, J JAP GEOGR, V105, P547 NASSAUER JI, 1987, LANDSCAPE HETEROGENE, P199 NASSAUER JI, 1995, LANDSCAPE ECOL, V10, P229 OKADA I, 1999, ECOL RESTOR, V17, P131 OLSSON EGA, 2000, LANDSCAPE ECOL, V15, P155 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PAN DY, 1999, LANDSCAPE ECOL, V14, P35 POUDEVIGNE I, 1997, LANDSCAPE URBAN PLAN, V38, P93 REED RA, 1996, BIOL CONSERV, V75, P267 SAKAGUCHI K, 1966, JAP HUMAN GEOGR, V18, P39 SKANES HM, 1997, LANDSCAPE URBAN PLAN, V38, P61 TABATA H, 1997, SATOYAMA ITS CONSERV TURNER MG, 1996, ECOL APPL, V6, P1150 0921-2973 Landsc. Ecol.ISI:000175490900003Kansai Res Ctr, Forestry & Forest Prod Res Inst, Kyoto 6120855, Japan. Fukamachi, K, Kansai Res Ctr, Forestry & Forest Prod Res Inst, Kyoto 6120855, Japan.English<7jSFule, P. Z. Crouse, J. E. Heinlein, T. A. Moore, M. M. Covington, W. W. Verkamp, G.2003SMixed-severity fire regime in a high-elevation forest of Grand Canyon, Arizona, USA465-485Landscape Ecology185Abies age structure fire ecology fire scars Kaibab Plateau Picea Pinus Populus Pseudotsuga PONDEROSA PINE FORESTS UPPER MONTANE FORESTS NATIONAL-PARK SOUTHERN CASCADES CONIFER FORESTS MOUNTAIN-RANGE UNITED-STATES NORTH RIM HISTORY CALIFORNIAArticle Fire regime characteristics of high-elevation forests on the North Rim of the Grand Canyon, Arizona, were reconstructed from fire scar analysis, remote sensing, tree age, and forest structure measurements, a first attempt at detailed reconstruction of the transition from surface to stand-replacing fire patterns in the Southwest. Tree densities and fire-/non-fire-initiated groups were highly mixed over the landscape, so distinct fire-created stands could not be delineated from satellite imagery or the oldest available aerial photos. Surface fires were common from 1700 to 1879 in the 4,400 ha site, especially on S and W aspects. Fire dates frequently coincided with fire dates measured at study sites at lower elevation, suggesting that pre-1880 fire sizes may have been very large. Large fires, those scarring 25% or more of the sample trees, were relatively infrequent, averaging 31 years between burns. Four of the five major regional fire years occurred in the 1700s, followed by a 94-year gap until 1879. Fires typically occurred in significantly dry years ( Palmer Drought Stress Index), with severe drought in major regional fire years. Currently the forest is predominantly spruce-fir, mixed conifer, and aspen. In contrast, dendroecological reconstruction of past forest structure showed that the forest in 1880 was very open, corresponding closely with historical ( 1910) accounts of severe fires leaving partially denuded landscapes. Age structure and species composition were used to classify sampling points into fire-initiated and non-fire-initiated groups. Tree groups on nearly 60% of the plots were fire-initiated; the oldest such groups appeared to have originated after severe fires in 1782 or 1785. In 1880, all fire-initiated groups were less than 100 years old and nearly 25% of the groups were less than 20 years old. Non-fire-initiated groups were significantly older ( oldest 262 years in 1880), dominated by ponderosa pine, Douglas-fir, or white fir, and occurred preferentially on S and W slopes. The mixed-severity fire regime, transitioning from lower-elevation surface fires to mixed surface and stand-replacing fire at higher elevations, appeared not to have been stable over the temporal and spatial scales of this study. Information about historical fire regime and forest structure is valuable for managers but the information is probably less specific and stable for high-elevation forests than for low-elevation ponderosa pine forests.://000185827200002 % ISI Document Delivery No.: 730JG Times Cited: 9 Cited Reference Count: 55 Cited References: *USGS, 2000, NAT VEG CLASS STAND, P1 AGEE JK, 1993, FIRE ECOLOGY PACIFIC AGEE JK, 2001, NORTHWEST SCI, V75, P292 ALLEN CD, 2002, FIRE NATIVE PEOPLES, P143 ALTSCHUL JH, 1989, UNPUB MAN MODELS MAN APLET GH, 1988, ECOLOGY, V69, P312 APPLEQUIST MB, 1958, J FOREST, V56, P141 BAISAN CH, 1990, CAN J FOREST RES, V20, P1559 BAKER WL, 2001, CAN J FOREST RES, V31, P1205 BEATY RM, 2001, J BIOGEOGR, V28, P955 BERTOLETTE D, 2001, CROSSING BOUNDARIES, P45 COOK ER, 1996, TREE RINGS ENV HUMAN, P155 DIETERICH JH, 1984, FOREST SCI, V30, P238 FOSTER DR, 1996, TRENDS ECOL EVOL, V11, P419 FULE PZ, IN PRESS INT J WILDL FULE PZ, 1997, ECOL APPL, V7, P895 FULE PZ, 2000, P WILD SCI TIM CHANG, P242 FULE PZ, 2002, J BIOGEOGR, V29, P31 GANEY JL, 1994, WEST J APPL FOR, V9, P21 GRISSINOMAYER HD, 1995, RMGTR264 USDA FOR SE GRISSINOMAYER HD, 1999, INT J WILDLAND FIRE, V9, P37 GRISSINOMAYER HD, 2001, TREE-RING RES, V57, P115 HABECK JR, 1990, NORTHWEST ENVIRON J, V6, P271 HAWKSWORTH FG, 1990, WEST J APPL FOR, V5, P47 HEINSELMANN ML, 1973, QUATERNARY RES, V18, P32 HOLMES RL, 1983, TREE RING B, V43, P69 HUFFMAN DW, 2001, PONDEROSA PINE ECOSY, P3 JOHNSON EA, 1994, ADV ECOL RES, V25, P239 JOHNSON EA, 2001, FOREST FIRES BEHAV E KIPFMUELLER KF, 2000, J BIOGEOGR, V27, P71 LANG DM, 1910, UNPUB RECONNAISSANCE MAST JN, 1999, ECOL APPL, V9, P228 MEKO D, 1995, WATER RESOUR BULL, V31, P789 MERKLE J, 1954, ECOLOGY, V35, P316 MERKLE J, 1962, ECOLOGY, V43, P698 MINNICH RA, 2000, J BIOGEOGR, V27, P105 MITCHELL JE, 1993, RM222 USDA FOR SERV MOORE MM, UNPUB J VEGETATION S MURRAY MP, 1998, J BIOGEOGR, V25, P1071 NIKLASSON M, 2000, ECOLOGY, V81, P1484 RASMUSSEN DI, 1941, ECOL MONOGR, V11, P229 REEBERG P, 1995, INTGTR320 USDA FOR S RIPPLE WJ, 2000, BIOL CONSERV, V95, P361 SALZER MW, 2000, THESIS U ARIZONA TUC STEPHENS SL, 2001, INT J WILDLAND FIRE, V10, P161 STOKES MA, 1968, INTRO TREE RING DATI SWETNAM TW, 1996, P 2 LA MES FIR S 29, P11 SWETNAM TW, 1999, ECOL APPL, V9, P1189 SWETNAM TW, 2001, CHANGING PLANT LIFE, P95 TAYLOR AH, 2000, J BIOGEOGR, V27, P87 THOMAS JW, 1979, USDA FOR SERV AGR HD, V553, P60 WARREN PL, 1982, 9 U AR NAT PARK SERV WHITE AS, 1985, ECOLOGY, V66, P589 WHITE MA, 1993, VEGETATIO, V109, P161 WOLF JJ, 1998, PHYS GEOGR, V19, P1 0921-2973 Landsc. Ecol.ISI:000185827200002No Arizona Univ, Ecol Restorat Inst, Flagstaff, AZ 86011 USA. No Arizona Univ, Sch Forestry, Flagstaff, AZ 86011 USA. Natl Pk Serv, Anchorage, AK USA. Fule, PZ, No Arizona Univ, Ecol Restorat Inst, Flagstaff, AZ 86011 USA.English<7 Fuller, D. O.2001bForest fragmentation in Loudoun County, Virginia, USA evaluated with multitemporal landsat imagery627-642Landscape Ecology167eastern deciduous forests Landsat-7 landscape metrics thermal infrared remote sensing TROPICAL DEFORESTATION SATELLITE DATA LANDSCAPE BIRDS COVER AREAArticleOctIn order to study forest fragmentation in the Virginia, USA Piedmont, a series of Landsat images from 1973, 1987, and 1999 covering a rapidly developing area (Loudoun County) was used to classify forest from non-forest. The classified images were analyzed using a geographic information system (GIS) to determine the spatial and temporal patterns of fragmentation, and to relate these patterns to infrared radiance provided by Landsat Enhanced Thematic Mapper Plus (ETM+) band 6. The analysis was concentrated on eleven major watersheds of Loudoun County. The relationship between urbanized area per watershed and mean fragment size showed a strong negative decay form (r(2)=0.757, p <0.0001). Analysis of four landscape metrics showed increasing fragmentation of forest cover, particularly from 1987 to 1999, as well as an increase in forest edge and shape complexity. Of the landscape metrics used, the perimeter-to-area (P/A) ratio showed the strongest relationship with mean radiance of forest patches. In addition, there was a negative, linear relationship between distance from major roads and band 6 radiance of forested pixels. Overall, the study shows that landscape metrics can convey meaningful information on biophysical changes associated with forest fragmentation at broad scales. These changes suggest that ambient temperature increases associated with urban sprawl may have important, long-term implications for ecophysiological processes.://000172809400004 ISI Document Delivery No.: 503QG Times Cited: 12 Cited Reference Count: 36 Cited References: *G WASH U, 1999, LOUD COUNT ENV IND P *SOIL CONS SERV, 1994, STAT SOIL GEOGR DAT BIERREGAARD RO, 1992, BIOSCIENCE, V42, P859 BLOOM AL, 1978, GEOMORPHOLOGY SYSTEM BRAZEL A, 1999, ANN M ASS AM GEOGR H, P60 BROTHERS TS, 1992, CONSERV BIOL, V6, P91 CADENASSO ML, 1997, CAN J FOREST RES, V27, P774 CONGALTON RG, 1991, REMOTE SENS ENVIRON, V37, P35 DOE BR, 1999, EOS, V1, P4 EASTMAN JR, 1997, IDRISI WINDOWS FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FROHN RC, 1998, REMOTE SENSING LANDS GOETZ SJ, 2000, ASPRS C P CD ROM AM HAGAN JM, 1996, CONSERV BIOL, V10, P188 JI M, 1999, GEOCARTO INT, V14, P33 KLINE B, 2000, 1 RIVER BRIEF HIST U LARCHER W, 1980, PHYSL PLANT ECOLOGY LUQUE SS, 1994, LANDSCAPE ECOL, V9, P287 MEFFE GK, 1997, PRINCIPLES CONSERVAT OBRIEN KL, 1996, PROG PHYS GEOG, V20, P311 OKE TR, 1987, BOUNDARY LAYER CLIMA PRINCE SD, 1991, INT J REMOTE SENS, V12, P1313 QUATTROCHI DA, 1999, LANDSCAPE ECOL, V14, P577 RICKETTS TH, 1999, TERRESTRIAL ECOREGIO ROBBINS CS, 1989, WILDLIFE MONOGRA JUL, P1 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SAUNDERS SC, 1998, LANDSCAPE ECOL, V13, P381 SCHWARTZ MD, 1988, PHYSICAL GEOGR, V9, P151 SKOLE D, 1993, SCIENCE, V260, P1905 TAYLOR FG, 1974, PHENOLOGY SEASONALIT, P237 TUCKER CJ, 1977, APPL OPTICS, V16, P1151 VILLARD MA, 1999, CONSERV BIOL, V13, P774 VOGELMANN JE, 1995, CONSERV BIOL, V9, P439 WHITE MA, 2000, EOS T, V81, P1 WILLIAMS M, 1990, EARTH TRANSFORMED HU, P179 YUAN D, 1998, REMOTE SENS ENVIRON, V66, P166 0921-2973 Landsc. Ecol.ISI:000172809400004George Washington Univ, Dept Geog, Washington, DC 20052 USA. Fuller, DO, George Washington Univ, Dept Geog, Washington, DC 20052 USA.English<71FFullerton, A. H. Beechie, T. J. Baker, S. E. Hall, J. E. Barnas, K. A.2006Regional patterns of riparian characteristics in the interior Columbia River basin, Northwestern USA: applications for restoration planning 1347-1360Landscape Ecology218coarse-resolution analysis; riparian; Pacific salmon; land use and land cover; conservation plans LAND-USE; PACIFIC-NORTHWEST; SALMON HABITAT; CHINOOK SALMON; STREAMS; WATERSHEDS; MANAGEMENT; FLOODPLAIN; RESPONSES; SEDIMENTArticleNovRecent declines in anadromous Pacific salmonids (Oncorhynchus spp.) have been attributed, in part, to degradation of freshwater habitat. Because riparian areas directly affect instream habitat, assessing riparian characteristics is essential for predicting salmon habitat quality and for prioritizing restoration projects. We quantified land use modification of anadromous fish-bearing streams in the interior Columbia River basin at multiple resolutions. We identified riparian areas in several land use and land cover classes using remotely sensed data. We then interpreted aerial photographs at random locations within each class to quantify riparian modifications at a local (stream reach) scale. Riparian areas in agricultural and urban areas were significantly narrower (similar to 30 m, median) than those in forested or shrub/grass areas (similar to 70 m). The largest proportion of modified riparian areas occurred in low-gradient streams with floodplains in semi-arid ecoreaions. Riparian vegetation in these areas is unlikely to provide adequate in-stream functions. making, these areas a natural starting point for restoration prioritization. We investigated how existing riparian restoration projects were spatially related to riparian land use and found that restoration effort varied among subwatersheds. Effective strategies for restoring high quality salmon habitat will be watershed-specific and must restore natural watershed processes. By using a hierarchical analysis to identify regional strategies, restoration or conservation activity can be focused in specific basins and thereby increase the likelihood that efforts will significantly improve habitat conditions for listed salmonids.://000242089300013 ISI Document Delivery No.: 106GP Times Cited: 0 Cited Reference Count: 41 Cited References: *ACCDLSC, 1995, AS CREEK MOD WAT PLA *GRMWP, 1994, GRAND ROND MOD WAT P *IBMP, 2005, FOR STEW GUID WAT QU *NRCS, 2005, CONS PRACT STAND RIP *WFPR, 2005, GUID RIP MAN ZON ALLAN JD, 2004, ANNU REV ECOL EVOL S, V35, P257 BEECHIE T, 1999, FISHERIES, V24, P6 BEECHIE TJ, 2000, N AM J FISH MANAGE, V20, P436 BEECHIE TJ, 2003, NMFSNWFSC58 NOAA BERNHARDT ES, 2005, SCIENCE, V308, P636 BESCHTA RL, 1997, PACIFIC SALMON THEIR, P475 BILBY RE, 1989, T AM FISH SOC, V118, P368 BROADMEADOW S, 2004, HYDROL EARTH SYST SC, V8, P286 CONGALTON RG, 1999, ASSESSING ACCURACY R CRAMER SP, 2001, UNPUB RELATIONSHIP S DANIELS RB, 1996, SOIL SCI SOC AM J, V60, P246 FEIST BE, 2003, ANIM CONSERV 3, V6, P271 FENNESSY MS, 1997, CRIT REV ENV SCI TEC, V27, P285 FREEMAN RE, 2003, ECOL APPL, V13, P416 FRIMPONG EA, 2005, CAN J FISH AQUAT SCI, V62, P1 GERGEL SE, 2002, AQUAT SCI, V64, P118 GOODWIN CN, 1997, RESTOR ECOL, V15, P4 HALL JE, IN PRESS J AM WATER HARDING JS, 1998, P NATL ACAD SCI USA, V95, P14843 HYATT TL, 2004, RESTOR ECOL, V12, P175 KIFFNEY PM, 2003, J APPL ECOL, V40, P1060 KREUTZWEISER DP, 2001, CAN J FOREST RES, V31, P2134 LOWRANCE R, 2002, LANDSCAPE ECOLOGY AG LUNETTA RS, 1997, PHOTOGRAMM ENG REM S, V63, P1219 MCFALL JM, IN PRESS RESTOR ECOL NAIMAN RJ, 2005, RIPARIA ECOLOGY CONS OMERNIK JM, 1997, J AM WATER RESOUR AS, V33, P935 PAULSEN CM, 2001, T AM FISH SOC, V130, P347 QUIGLEY TM, 1997, PNWGTR405, V1, P335 RONI P, 2002, NORTH AM J FISH MANA, V22, P1 SNYDER CD, 2003, LANDSCAPE ECOL, V18, P647 SOMMER TR, 2001, CAN J FISH AQUAT SCI, V58, P325 STEHMAN SV, 1996, REMOTE SENS ENVIRON, V58, P169 STEIGER J, 2001, EARTH SURF PROC LAND, V26, P91 STOREY RG, 1997, HYDROBIOLOGIA, V353, P63 WICKHAM JD, 1997, PHOTOGRAMM ENG REM S, V63, P397 0921-2973 Landsc. Ecol.ISI:000242089300013NOAA Fisheries, Environm Conservat Div, NW Fisheries Sci Ctr, Seattle, WA 98112 USA. Fullerton, AH, NOAA Fisheries, Environm Conservat Div, NW Fisheries Sci Ctr, 2725 Montlake Blvd E, Seattle, WA 98112 USA. Aimee.Fullerton@noaa.govEnglish 5<7Q Fyfe, R. M. Woodbridge, J.2012aDifferences in time and space in vegetation patterning: analysis of pollen data from Dartmoor, UK745-760Landscape Ecology275pollen charcoal heterogeneity burning fire moorlands spatial analysis palaeoecology dartmoor midholocene environmental transition late-holocene vegetation land-use history new-england human impact fire forest climate landscape reconstructionsMayMoorlands perform a wide variety of roles within modern society. A vital component of these landscapes is the patterning of vegetation, and management of this requires a thorough understanding of the drivers of vegetation change. Although there has been a considerable body of research focussed on the processes that are important in patterning contemporary vegetation these typically lack any significant time-depth. Long-term data, using palaeoecological techniques, offer insights into drivers of vegetation change that are otherwise unachievable. This paper presents new palaeoecological data from Dartmoor (UK) to test two hypotheses: (1) that vegetation character of moorland is spatially homogenous through the past 8,000 years; and (2) that burning has a significant role in the development of open, grass-dominated, vegetation. Four peat cores spanning the past 8,000 years were subject to pollen and microcharcoal analysis. Thirty-seven radiocarbon age estimates were obtained to determine age-depth models for the pollen and charcoal stratigraphies. Differences within and between the pollen stratigraphies have been used as an indirect measure of landscape heterogeneity at a coarse scale. The data reveal periods of time during which differences in the vegetation (as sensed by pollen) around each site are small, and periods during which differences between vegetation are large. Periods of time characterised by greater spatial difference, and by inference greater heterogeneity, correlate with periods characterised by greater human exploitation of the landscape as revealed by archaeological evidence. Human activities therefore promote greater spatial patterning in the landscape. Fire alone is not an important control on long-term peatland vegetation development. The results are useful for conservation strategies by demonstrating variability in spatial diversity of vegetation patterns in the past, and pointing towards opportunities to recreate and maintain diverse vegetation mosaics.://000303056100010-929JC Times Cited:0 Cited References Count:89 0921-2973Landscape EcolISI:000303056100010Fyfe, RM Univ Plymouth, Sch Geog Earth & Environm Sci, Plymouth PL4 8AA, Devon, England Univ Plymouth, Sch Geog Earth & Environm Sci, Plymouth PL4 8AA, Devon, England Univ Plymouth, Sch Geog Earth & Environm Sci, Plymouth PL4 8AA, Devon, EnglandDOI 10.1007/s10980-012-9726-3English<7Gagne, S. A. Fahrig, L.2007jEffect of landscape context on anuran communities in breeding ponds in the National Capital Region, Canada205-215Landscape Ecology222land use; urbanization; agriculture; forest cover; Amphibian conservation; species richness; abundance SPECIES RICHNESS; LAND-USE; AMPHIBIANS; FRAGMENTATION; FROG; CONSEQUENCES; BIODIVERSITY; POPULATIONS; PREDATION; ABUNDANCEArticleFebLand cover change, predominantly habitat conversion to agricultural use and urbanization, has recently been recognized as the primary cause of biodiversity loss in terrestrial ecosystems. We evaluated the relative effects of urban and agricultural landscapes on anuran species richness and the abundance of six anuran species found at breeding ponds in and around the cities of Ottawa, Ontario and Gatineau, Quebec. We performed six call surveys at 29 permanent focal ponds surrounded by one of three landscape contexts: primarily urban, primarily agricultural, and primarily forested. We also measured three local pond variables to control for the effects of local habitat quality in our analyses. We found that anuran species richness was significantly lower in breeding ponds in urban landscapes compared to forested and agricultural landscapes, which exhibited no significant difference in species richness. The abundances of individual anuran species were also consistently lower in urban landscapes for all species except one, which exhibited no response to landscape type. Three species had their highest abundances in ponds in forested landscapes, whereas two species had their highest abundances in ponds in agricultural landscapes. We conclude that ponds embedded in urban landscapes support lower biodiversity than ponds in agricultural settings. We suggest that landscapes composed of a mosaic of forest and open habitats surrounding wetlands would hold the highest biodiversity of these species.://000243823900005 ISI Document Delivery No.: 130UG Times Cited: 0 Cited Reference Count: 48 Cited References: *CAN BIOD INF INF, 2004, URB BIOD ENV CAN OTT *ENV SYST RES I, 1999, ARC VIEW 3 2 X *INS, 2001, S PLUS 6 0 *MILL EC ASS, 2005, EC HUM WELL BEING BI, P86 *SPSS, 2003, SPSS 12 0 WIND ATAURI JA, 2001, LANDSCAPE ECOL, V16, P147 BENTON TG, 2003, TRENDS ECOL EVOL, V18, P182 BONIN J, 1997, AMPHIBIANS DECLINE C, P141 BRADLEY G, 1995, URBAN FOREST LANDSCA, P3 CARR LW, 2001, CONSERV BIOL, V15, P1071 CZECH B, 2000, BIOSCIENCE, V50, P593 DAM A, 2005, THESIS CARLETON U OT, P69 DEFRIES RS, 2004, FRONT ECOL ENVIRON, V2, P249 DEMAYNADIER PG, 2000, NAT AREA J, V20, P56 DUGUAY S, 2004, THESIS CARLETON U OT, P53 DUNFORD W, 2001, EFFECTS AGR URBAN LA, P91 FAHRIG L, 1995, BIOL CONSERV, V73, P177 FICETOLA GF, 2004, BIOL CONSERV, V119, P219 FOLEY JA, 2005, SCIENCE, V309, P570 GIBBS JP, 2005, ECOL APPL, V15, P1148 GRAY MJ, 2004, CONSERV BIOL, V18, P1368 GRIMM NB, 2000, BIOSCIENCE, V50, P571 GUERRY AD, 2002, CONSERV BIOL, V16, P745 HECNAR SJ, 1998, J BIOGEOGR, V25, P763 HEINEN JT, 1993, AM MIDL NAT, V130, P184 HOULAHAN JE, 2003, CAN J FISH AQUAT SCI, V60, P1078 JOHNSON CM, 2002, PREDICTING SPECIES O, P157 JOLY P, 2001, CONSERV BIOL, V15, P239 KNIGHT RL, 1998, STEWARDSHIP BOUNDARI KNUTSON MG, 1999, CONSERV BIOL, V13, P1437 KOLOZSVARY MB, 1999, CAN J ZOOL, V77, P1288 LAAN R, 1990, BIOL CONSERV, V54, P251 LEHTINEN RM, 1999, WETLANDS, V19, P1 MCGARIGAL K, 2002, FRAGSTATS SPATIAL PA MENSING DM, 1998, J ENVIRON MANAGE, V53, P349 PHELPS AM, 2001, THESIS U OTTAWA OTTA, P176 PLATT RH, 2004, ENVIRONMENT, V46, P11 POPE SE, 2000, ECOLOGY, V81, P2498 RELYEA RA, 2005, ECOL APPL, V15, P1118 RICHTER KO, 1995, WETLANDS, V15, P305 RILEY SPD, 2005, CONSERV BIOL, V19, P1894 SANZO D, 2006, ENVIRON POLLUT, V140, P247 STUART SN, 2004, SCIENCE, V306, P1783 TRENHAM PC, 2003, ECOL APPL, V13, P1522 WEYRAUCH SL, 2004, BIOL CONSERV, V115, P443 WILCOX BA, 1985, AM NAT, V125, P879 WILSON JD, 2003, CONSERV BIOL, V17, P763 WOODS M, 2003, MAMMAL REV, V33, P174 0921-2973 Landsc. Ecol.ISI:000243823900005Carleton Univ, Dept Biol, Ottawa, ON K1S 5B6, Canada. Carleton Univ, Ottawa Carleton Inst Biol, Geomat & Landscape Ecol Res Lab, Ottawa, ON K1S 5B6, Canada. Gagne, SA, Carleton Univ, Dept Biol, Colonel Dr, Ottawa, ON K1S 5B6, Canada. saraanne.gagne@gmail.comEnglish<7Galbraith, L. M. Burns, C. W.2007KLinking land-use, water body type and water quality in southern New Zealand231-241Landscape Ecology222wetlands; catchment; land cover; phosphorus; nitrogen; agriculture; eutrophication; drainage basin; lakes FRESH-WATER; TOTAL PHOSPHORUS; ORGANIC-MATTER; TOTAL NITROGEN; LAKES; ECOSYSTEMS; CHEMISTRYArticleFebyLand-use and vegetation cover have been linked to the nutrient levels (nitrogen, phosphorus) of surface waters in several countries. However, the links generally relate to streams and rivers, or to specific types of standing water, for example shallow lakes in a geologically defined region. We measured physical variables and nutrient chemistry of 45 water bodies representative of the wide range of lentic wetland environments (swamps, riverine wetlands, estuaries, reservoirs, shallow lakes, deep lakes) in Otago, New Zealand, and related these to catchment variables and land-use in order to assess the potential influence of catchment modification on water quality of these diverse wetlands. Catchment boundaries and land cover were derived from maps using ArcView GIS software. Our predictions that concentrations of nutrients and other components of water quality would correlate positively with the nature and intensity of catchment modification were confirmed in multivariate analyses. Physical and chemical measures were positively related to the extent of modification in the catchment (percentage of the catchment in pasture, planted forest, scrub and urban areas), and negatively related to lack of catchment modification (more of the catchment in bare ground, tussock grassland and indigenous forest). The strong negative correlations between nutrient concentrations, suspended sediment, water colour and the percentage of tussock cover in the catchment imply that increased conversion of the native tussock grassland to pastoral farming in Otago will increase nutrient concentrations and reduce water quality of the diverse lentic ecosystems.://000243823900007 ISI Document Delivery No.: 130UG Times Cited: 0 Cited Reference Count: 25 Cited References: *SPSS INC, 2000, SPSS WIND VERS 10 1 CUTHBERT ID, 1992, LIMNOL OCEANOGR, V37, P1319 DARCY P, 1997, CAN J FISH AQUAT SCI, V54, P2215 ELLIOTT S, 2002, LAKE MANAGERS HDB LA HURYN AD, 2003, NATURAL HIST SO NZ, P237 JOHNES P, 1996, FRESHWATER BIOL, V36, P451 LOUGHEED VL, 2001, CAN J FISH AQUAT SCI, V58, P1603 MABERLY SC, 2003, HYDROBIOLOGIA, V506, P83 MENZEL DW, 1964, LIMNOL OCEANOGR, V9, P138 MOSS B, 1998, ECOLOGY FRESH WATERS NEWSOME PFJ, 1987, WATER SOIL MISCELLAN, V112 PREPAS EE, 2001, CAN J FISH AQUAT SCI, V58, P1286 RASMUSSEN JB, 1989, LIMNOL OCEANOGR, V34, P1097 RILEY RH, 2003, NEW ZEAL J MAR FRESH, V37, P389 SCHINDLER DW, 1997, HYDROL PROCESS, V11, P1043 TERBRAAK CFJ, 1998, CANOCO REFERENCE MAN THOMAS JD, 1997, FRESHWATER BIOL, V38, P1 THOMPSON RM, 1998, TAIER CATCH S EC RES, P44 TONG STY, 2002, J ENVIRON MANAGE, V66, P377 TOWNSEND CR, 2001, UNPUB LAND USE IMPAC VALDERRAMA JC, 1981, MAR CHEM, V10, P109 WETZEL RG, 1991, LIMNOLOGICAL ANAL WETZEL RG, 1995, FRESHWATER BIOL, V33, P83 WICKHAM JD, 2005, LANDSCAPE ECOL, V20, P791 YOUNG RG, 1999, ECOL APPL, V9, P1359 0921-2973 Landsc. Ecol.ISI:000243823900007Univ Otago, Dept Zool, Dunedin, New Zealand. Burns, CW, Univ Otago, Dept Zool, Box 56,340 Great King St, Dunedin, New Zealand. carolyn.burns@stonebow.otago.ac.nzEnglish:|?bXGalbreath, Dana M. Ichinose, Tomohiro Furutani, Tomoyuki Yan, Wanglin Higuchi, Hiroyoshi2014Urbanization and its implications for avian aggression: a case study of urban black kites (Milvus migrans) along Sagami Bay in Japan169-178Landscape Ecology291JanUrbanization has caused countless changes in the lives, behaviors, and community structures of wild animals. Habitat loss in urban areas has led to the proliferation of certain species over others; in the case of birds, frugivores and certain predators can be found in abundance in cities. These birds, however, occasionally show novel behaviors that can cause stress within human-wildlife interactions. The black kite, Milvus migrans, for example, has displayed a tendency to attack humans for their food in certain urban areas in Japan. In order to determine how habitat availability and land-use types affected these aggressive tendencies, field observations were combined with GIS analysis of five locations along Sagami Bay in Japan. The following locations were assessed according to the amount of each land-use type present and the aggressive tendencies of each location's black kite population: Enoshima, Fujisawa; Kamakura Beach, Kamakura; Zushi Beach, Zushi; Oiso Beach, Oiso; and Iwa Beach, Manazuru. The aggression of each population, designated by the log of the aggression index, was found to be significantly affected by the amount of forest area per black kite, the amount of non-rice-paddy agricultural area per black kite, and the season. Thus, aggression was higher amongst populations with less forested or agricultural area within their foraging zones, and aggression increased during spring, which is the breeding season.!://WOS:000330827600013Times Cited: 0 0921-2973WOS:00033082760001310.1007/s10980-013-9951-4ڽ7 KGall, HeatherE Park, Jeryang Harman, CiaranJ Jawitz, JamesW Rao, P. SureshC2013TLandscape filtering of hydrologic and biogeochemical responses in managed catchments651-664Landscape Ecology284Springer NetherlandsHydro-climatic drivers Anthropogenic drivers Catchment responses Urban catchments Wet deposition Agricultural catchments Nutrient export 2013/04/01+http://dx.doi.org/10.1007/s10980-012-9829-x 0921-2973Landscape Ecol10.1007/s10980-012-9829-xEnglish |7/Gallardo-Cruz, J. Perez-Garcia, E. A. Meave, J.2009ybeta-Diversity and vegetation structure as influenced by slope aspect and altitude in a seasonally dry tropical landscape473-482Landscape Ecology244)environmental heterogeneity oaxaca state mexico plant diversity potential energy income modelling seasonally dry tropical forest topography vegetation structure alpha-diversity gamma-diversity species-richness patterns vascular plants costa-rica forest gradient transects variables responses treesAprTopography strongly affects the distribution of insolation in the terrain. Patterns of incoming solar radiation affect energy and water balances within a landscape, resulting in changes in vegetation attributes. Unlike other regions, in seasonally dry tropical forest areas the potential contribution of topography-related environmental heterogeneity to beta-diversity is unclear. In Mt. Cerro Verde (Oaxaca), S. Mexico, we: (1) modelled potential energy income for N- and S-facing slopes based on a digital elevation model, (2) examined the response of vegetation structure to slope aspect and altitude and (3) related variations in plant diversity to topography-related heterogeneity. Vegetation survey and modelling of potential energy income (SOLEI-32 model) were based on 30 plots equally distributed among three altitudinal belts defined for each slope of the mountain; combining the three altitudinal belts and the two slopes produced six environmental groups, represented by five vegetation plots each. Potential energy income was about 20% larger on the S than on the N slope (9,735 versus 8,138 MJ/m(2)), but it did not vary with altitude. In addition, the temporal behaviour of potential energy income throughout the year differed greatly between slopes. Vegetation structure did not show significant changes linked to the environmental gradients analysed, but altitude and aspect did affect beta-diversity. We argue that the classic model of slope aspect effect on vegetation needs reconsideration for tropical landscapes.://000263898100003-414XI Times Cited:0 Cited References Count:63 0921-2973ISI:000263898100003Gallardo-Cruz, J Univ Nacl Autonoma Mexico, Dept Ecol & Recursos Nat, Fac Ciencias, Ciudad Univ, Mexico City 04510, DF, Mexico Univ Nacl Autonoma Mexico, Dept Ecol & Recursos Nat, Fac Ciencias, Mexico City 04510, DF, MexicoDoi 10.1007/S10980-009-9332-1Englishڽ7 Galpern, Paul Manseau, Micheline2013OFinding the functional grain: comparing methods for scaling resistance surfaces 1269-1281Landscape Ecology287Springer NetherlandsGrains of connectivity Functional grain Landscape graphs Minimum planar graph Voronoi tessellation Effective distance Least-cost paths Landscape pattern Simulation 2013/08/01+http://dx.doi.org/10.1007/s10980-013-9873-1 0921-2973Landscape Ecol10.1007/s10980-013-9873-1Englishڽ7G1Gao, Peng Kupfer, JohnA Guo, Diansheng Lei, TingL2013^Identifying functionally connected habitat compartments with a novel regionalization technique 1949-1959Landscape Ecology2810Springer NetherlandsTEcoregionalization Graph theory Habitat connectivity Fragmentation Ring-tailed lemur 2013/12/01+http://dx.doi.org/10.1007/s10980-013-9938-1 0921-2973Landscape Ecol10.1007/s10980-013-9938-1English <7kGao, Q. Li, J. D. Zheng, H. Y.1996dA dynamic landscape simulation model for the alkaline grasslands on Songnen Plain in northeast China339-349Landscape Ecology116;alkaline grasslands; landscape dynamics; spatial simulationArticleDecA dynamic model was developed to simulate the variation of spatial species distribution patterns of the meadow steppe grasslands on Songnen Plain in northeast China. Simulation was performed to study the interaction between soil alkalization and vegetation development with special consideration given to spatial processes such as horizontal species migration and horizontal diffusion of soil alkali. The coverage of five species, Calamagrostis epigeios, Aneurolipidium chinense, Puccinellia tenuiflora, Aeluropus littoralis and Suaeda corniculata, and soil alkali were selected as 6 state variables. A positive feedback mechanism embedded in the model was that when the total plant coverage is large enough, the soil undergoes de-alkalization, which in turn helps improve further the plant growth condition. The de-alkalization is due to the improved soil physical properties indicated by a large amount of soil non-capillary pores coexisting with a large amount of belowground root biomass which allows alkaline solutes to leach from surface soil to underground water by means of precipitation. On the other hand, when the plant coverage is too small, soil alkalization takes place due to the deterioration of soil physical properties indicated by a small amount of plant root biomass and a large amount of capillary pores which enables evapotranspiration to bring up alkaline solutes to the surface soil. The alkalization of surface soil further hinders plant growth. The model was implemented using a software tool, SPAMOD, developed at Institute of Botany, the Chinese Academy of Sciences. The simulation results showed that the model was in very close agreement with five year field observations on a one-hectare fenced alkaline grassland, implying that the modeling approach used in this research is very appropriate for grassland landscape studies; that the spatial processes reflected as horizontal species migration and horizontal diffusion of soil alkali are very important for the recovery of A. chinense, the major grazed species with rhizoma as its main reproduction mechanism; and that the vanishing rate of S. corniculata, an indicator of serious soil alkalization, is very sensitive to the variation in the soil physical properties.://A1996VY82900004 1ISI Document Delivery No.: VY829 Times Cited: 14 Cited Reference Count: 5 Cited References: GAO Q, 1994, ACTA PHYTOECOL SINIC, V18, P56 LI BL, 1993, ECOL MODEL, V69, P287 LI J, 1988, ACTA BOT SIN, V30, P420 VAJDA S, 1987, AUTOMATICA, V23, P707 ZHENG H, 1993, VEGETATION SONGNEN P 0921-2973 Landsc. Ecol.ISI:A1996VY82900004AGao, Q, CHINESE ACAD SCI,INST BOT,BEIJING 100093,PEOPLES R CHINA.English z<7$Gao, Q. Yu, M. Yang, X. S. Wu, J. G.2001^Scaling simulation models for spatially heterogeneous ecosystems with diffusive transportation289-+Landscape Ecology164ecosystem simulation grassland landscape resolution songnen plain DYNAMICS ECOLOGY COMPLEXITY GRASSLANDS ABUNDANCE PATTERNS SYSTEMS SCALESArticleMayThe behavioral dependence of vegetation simulation models for spatially heterogeneous grasslands on simulation resolution was investigated. The dependence can be largely attributed to the non-linearity of the models. We showed that increasing scale or decreasing spatial resolution tended to overestimate the changing rate of an ecosystem using our landscape simulation model for alkaline grasslands in northeast China. A technique for scaling up simulation models with diffusive transportation was developed in this study by means of expanding the nonlinear driving functions in the model. The analysis showed that a simulation model for spatially heterogeneous landscapes might necessitate modification of both its mathematical structure and parameterization when applied to different scales. The scaling coefficients derived in this study were shown to be proportional to the variances or covariance of the spatially referenced variables, and can be estimated by running the model at a fine resolution for selected samples of the coarser grid cells. The technique was applied to a grassland landscape in northeast China and the results were compared with five-year observations on community succession. The comparison indicated that the proposed technique could effectively reduce overall scaling error of the model by as much as 80%, depending on the scaling difference between the fine and the coarse resolutions as well as the sampling scheme used.://000169516300001 bISI Document Delivery No.: 446MD Times Cited: 2 Cited Reference Count: 23 Cited References: ALLEN TFH, 1983, J THEOR BIOL, V101, P529 ALLEN TFH, 1991, ECOLOGICAL HETEROGEN, P47 ALLEN TFH, 1994, EVOL TREND PLANT, V7, P3 AUGER P, 1986, SYST RES, V3, P41 BONNER J, 1973, HIERARCHY THEORY CHA, P49 COLLINS SL, 1990, AM NAT, V135, P633 COLLINS SL, 1991, ECOLOGY, V72, P654 COLLINS SL, 1995, TRENDS ECOL EVOL, V10, P95 COSTANZA R, 1994, LANDSCAPE ECOL, V9, P47 FITZ HC, 1996, ECOL MODEL, V88, P263 FUHLENDORF SD, 1996, LANDSCAPE ECOL, V11, P107 GAO Q, 1996, ECOL MODEL, V85, P241 GAO Q, 1996, LANDSCAPE ECOL, V11, P339 KING AW, 1991, QUANTITATIVE METHODS, P479 LAWTON JH, 1987, NATURE, V325, P206 LEVIN SA, 1992, ECOLOGY, V73, P1943 LUCE RD, 1987, SCIENCE, V236, P1527 MAURER BA, 1987, J THEOR BIOL, V127, P97 ONEILL RV, 1989, LANDSCAPE ECOL, V3, P193 ONEILL RV, 1992, LANDSCAPE ECOL, V7, P55 WIENS JA, 1989, LANDSCAPE ECOLOGY, V3, P87 WU J, 1997, GEOGRAPHIC INFORMATI, V3, P30 WU JG, 1995, Q REV BIOL, V70, P439 0921-2973 Landsc. Ecol.ISI:000169516300001Beijing Normal Univ, Inst Resources Sci, MOE Key Lab Environm Change & Nat Disaster, Beijing 100875, Peoples R China. Gao, Q, Duke Univ, Dept Bot, Durham, NC 27708 USA.English <7;Gao, Q. O. Yang, X. S.1997`A relationship between spatial processes and a partial patchiness index in a grassland landscape321-330Landscape Ecology125necosystem modeling; gradient strength; grassland landscape; partial patchiness index SIMULATION-MODEL; PATTERNArticleOctA linear, semi-theoretical relationship between the coverage change of plant communities due to spatial processes and a partial patchiness index of the community distribution patterns in a grassland landscape was established by partitioning the overall coverage change into a spatial increment caused by species migration and a local increment due to local ecological processes. This relationship implies that patchiness of grassland landscapes can accelerate either recovery or degradation of a community, depending on the environmental conditions depicted by a parameter termed as gradient strength. The established relationship also has potential applications in simulating pattern dynamics of plant community distributions for a grassland landscape using a spatially homogeneous patch-scale model. The derived linear relationship was applied to a one-hectare alkaline grassland observatory in northeast China. Gradient strengths of two major plant community types were determined via linear regression from simulation results for selected subregions of the grassland. The calibrated linear relationship was then applied to the rest of the grassland landscape. Preliminary comparisons with complete spatial simulations and observations indicated that using this linear relationship with a patch-scale model can simulate the coverage changes as accurately as using a comprehensive spatial simulation model.://000077684100006 ISI Document Delivery No.: 150UN Times Cited: 3 Cited Reference Count: 18 Cited References: BAKER WL, 1989, LANDSCAPE ECOL, V2, P111 BURROUGH PA, 1986, PRINCIPLES GEOGRAPHI GAO Q, 1996, LANDSCAPE ECOL, V11, P339 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 LI H, 1989, THESIS OREGON STATE LI HB, 1993, LANDSCAPE ECOL, V8, P155 LI J, 1994, IN PRESS OPTIMAL MAN ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 ROMME WH, 1982, ECOL MONOGR, V52, P199 SHUGART HH, 1991, LONG TERM ECOLOGICAL, P211 SKLAR FH, 1986, P 1986 SUMMER COMPUT, P467 SKLAR FH, 1991, QUANTITATIVE METHODS, P239 TURNER MG, 1987, LANDSCAPE ECOL, V1, P29 TURNER MG, 1988, APPL MATH COMPUT, V27, P39 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 WIENS JA, 1992, LANDSCAPE BOUNDARIES, P217 WU JG, 1994, ECOL MONOGR, V64, P447 ZHENG H, 1993, VEGETATION SONGNEN P 0921-2973 Landsc. Ecol.ISI:000077684100006Univ Connecticut, Dept Nat Resources Management & Engn, Storrs, CT 06269 USA. Chinese Acad Sci, Inst Bot, Beijing 100093, Peoples R China. Yang, XS, Univ Connecticut, Dept Nat Resources Management & Engn, Storrs, CT 06269 USA.Englishڽ7 bGarbarino, Matteo Lingua, Emanuele Weisberg, PeterJ Bottero, Alessandra Meloni, Fabio Motta, Renzo2013`Land-use history and topographic gradients as driving factors of subalpine Larix decidua forests805-817Landscape Ecology285Springer NetherlandsLandscape pattern Land-use change Legacy effects Historical ecology Stand structure Larix decidua Forest grazing SEMs Italian Alps 2013/05/01+http://dx.doi.org/10.1007/s10980-012-9792-6 0921-2973Landscape Ecol10.1007/s10980-012-9792-6Englishx|?XGarcia, Adriano Consoli, Fernando Luis Conde Godoy, Wesley Augusto Ferreira, Claudia Pio2014A mathematical approach to simulate spatio-temporal patterns of an insect-pest, the corn rootworm Diabrotica speciosa (Coleoptera: Chrysomelidae) in intercropping systems 1531-1540Landscape Ecology299NovWe report on the use of a spatially explicit model and clustering analysis in order to investigate habitat manipulation as a strategy to regulate natural population densities of the insect-pest Diabrotica speciosa. Habitat manipulation involved four major agricultural plants used as hosts by this herbivore to compose intercropping landscapes. Available biological parameters for D. speciosa on bean, soybean, potato and corn obtained under laboratory conditions were used to group the homogeneous landscapes, composed by each host plant, by a similarity measure of host suitability either for larval survival and development, and adult survival and fecundity. The results pointed corn as the most dissimilar culture. Therefore, intercropping corn with any other crop system tested could reduce insect spread through landscape. This was proved using a cellular automata model which simulate the physiological and behavioural traits of this insect, and also different spatial configurations of the intercropping. Spatio-temporal patterns obtained by simulations demonstrated that the availability of corn bordering the field edge, which are areas more likely to invasion, is key for insect population control.!://WOS:000343648700006Times Cited: 0 0921-2973WOS:00034364870000610.1007/s10980-014-0073-4?YGarciaruiz, J. M. Lasanta, T. Ruizflano, P. Ortigosa, L. White, S. Gonzalez, C. Marti, C.1996dLand-use changes and sustainable development in mountain areas: a case study in the Spanish Pyrenees267-277Landscape Ecology115jland-use change, sustainability, farmland abandonment, reforestation, soil erosion, runoff, mountain areasLand-use changes affecting Mediterranean mountains represent the intensification of use in valley bottoms, accompanied by land-use conflicts, and a generalized abandonment of the hillslopes, which in the past were perfectly integrated in the system of land management. Farmland abandonment, reforestation, diminution of the livestock pressure and substitution of cereal crops by meadows are the most outstanding features of the recent land-use changes. The question is whether the new spatial organisation is in accordance with a longterm policy of sustainable development in mountain areas. The results obtained confirm that farmland abandonment on steep slopes - and the resulting colonization of old fields by a dense shrub cover - and afforestation contribute to control both soil erosion and surface runoff. As a result some of the most important rivers and alluvial fans have recently stabilized their sedimentary structures. |? 7Garden, Jenni G. McAlpine, Clive A. Possingham, Hugh P.2010Multi-scaled habitat considerations for conserving urban biodiversity: native reptiles and small mammals in Brisbane, Australia 1013-1028Landscape Ecology257AugThe rapid expansion of the world's urban population is a major driver of contemporary landscape change and ecosystem modification. Urbanisation destroys, degrades and fragments native ecosystems, replacing them with a heterogeneous matrix of urban development, parks, roads, and isolated remnant fragments of varying size and quality. This presents a major challenge for biodiversity conservation within urban areas. To make spatially explicit decisions about urban biodiversity conservation actions, urban planners and managers need to be able to separate the relative influence of landscape composition and configuration from patch and local (site)-scale variables for a range of fauna species. We address this problem using a hierarchical landscape approach for native, terrestrial reptiles and small mammals living in a fragmented semi-urban landscape of Brisbane, Australia. Generalised linear modelling and hierarchical partitioning analysis were applied to quantify the relative influence of landscape composition and configuration, patch size and shape, and local habitat composition and structure on the species' richness of mammal and reptile assemblages. Landscape structure (composition and configuration) and local-scale habitat structure variables were found to be most important for influencing reptile and mammal assemblages, although the relative importance of specific variables differed between reptile and mammal assemblages. These findings highlight the importance of considering landscape composition and configuration in addition to local habitat elements when planning and/or managing for the conservation of native, terrestrial fauna diversity in urban landscapes.!://WOS:000279592100003Times Cited: 0 0921-2973WOS:00027959210000310.1007/s10980-010-9476-zN<7hGardner, R. H.1996>Changes in editorship of Landscape Ecology - Robert H. Gardner321-321Landscape Ecology116Editorial MaterialDec://A1996VY82900001 HISI Document Delivery No.: VY829 Times Cited: 0 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1996VY82900001EnglishB<7SGardner, R. H.19974Transitions and opportunities: Notes from the editorR1-R1Landscape Ecology123Editorial MaterialJun://A1997XV63400001 HISI Document Delivery No.: XV634 Times Cited: 0 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1997XV63400001English~?O2Gardner, R. H. Jopp, F. Cary, G. J. Verburg, P. H.2008)World congress highlights need for action1-2Landscape Ecology231"://WOS:000251796100001 Times Cited: 0WOS:00025179610000110.1007/s10980-007-9183-6|~?=Gardner, R. H. Lookingbill, T. R. Townsend, P. A. Ferrari, J.2008,A new approach for rescaling land cover data513-526Landscape Ecology235ZThe resolution of satellite imagery must often be increased or decreased to fill data gaps or match preexisting project requirements. It is well known that a change in resolution introduces systematic errors of size, shape, location and amount of contiguous land cover types. Nevertheless, robust methods for rescaling landscape data are frequently required to assess patterns of landscape change through time and over large areas. We developed a new method for rescaling spatial data that allows map resolution (grain size) to be either increased or decreased while holding the total proportion of land cover types constant. The method uses a weighted sampling net of variable resolution to sample an existing map and then randomly selects from the frequency of cover types derived from this sample to assign the cover type for the corresponding location in the rescaled map. The properties of the sampling net had a variable effect on measures of landscape pattern with the characteristic patch size (S) the most robust metric and the number of clusters (A) the most variable. A comparison of up-scaled and down-scaled maps showed that this process is not symmetrical, producing different errors for increases versus decreases in grain size. Rescaling Landsat (30 m) imagery to the 10 m resolution of SPOT imagery for four National Park units within Maryland and Virginia resulted in errors due to rescaling that were small (1-2%) relative to the total error (similar to 11%) associated with these images. The new rescaling method is general because it provides a single method for increasing or decreasing resolution, can be applied to maps with multiple land cover types, allows grid geometry to be transformed (i.e., square to hexagonal grids), and provide a more consistent basis for landscape comparisons when maps must be derived from multiple sources of classified imagery."://WOS:000254964600003 Times Cited: 0WOS:000254964600003(10.1007/s10980-008-9213-z|ISSN 0921-2973?57Gardner, R.H. B.T. Milne M.G. Turner R.V. O'Neill1987@Neutral models for the analysis of broad-scale landscape pattern19-28Landscape Ecology11BScale, Resolution, Fractals, Percolation theory, Landscape patternThe relationship between a landscape process and observed patterns can be rigorously tested only if the expected pattern in the absence of the process is known. We used methods derived from percolation theory to construct neutral landscape models, i.e., models lacking effects due to topography, contagion, disturbance history, and related ecological processes. This paper analyzes the patterns generated by these models, and compares the results with observed landscape patterns. The analysis shows that number, size, and shape of patches changes as a function of p, the fraction of the landscape occupied by the habitat type of interest, and m, the linear dimension of the map. The adaptation of percolation theory to finite scales provides a base-line for statistical comparison with landscape data. When USGS land use data (LUDA) maps are compared to random maps produced by percolation models, significant differences in the number, size distribution, and the area/perimeter (fractal dimension) indices of patches were found. These results make it possible to define the appropriate scales at which disturbance and landscape processes interact to affect landscape patterns.?67Gardner, R. H. O'Neill, R. V. Turner, M. G. Dale, V. H.1989UQuantifying scale-dependent effects of animal movement with simple percolation models217-227Landscape Ecology33/4@scale, landscpae, critical threshold, extrapolation, extrapolateA simple model of animal movement on random and patterned landscapes was used to explore the problems of extrapolating information across a range of spatial scales. Simulation results indicate that simple relationships between pattern and process will produce a variety of scale-dependent effects. These theoretical studies can be used to design experiments for determining the nature of scale-dependent processes and to estimate parameters for extrapolating information across scales.<7Gardner, R. H. Urban, D. L.2007/Neutral models for testing landscape hypotheses15-29Landscape Ecology221neutral landscape models; pattern and process; landscape hypothesis testing; land cover analysis LAND-USE CHANGE; UNITED-STATES; SPATIAL-PATTERNS; CENTRAL AMAZON; NATURAL AREAS; PINE FORESTS; COVER CHANGE; USE HISTORY; METRICS; VEGETATIONArticleJanNeutral landscape models were originally developed to test the hypothesis that human-induced fragmentation produces patterns distinctly different from those associated with random processes. Other uses for neutral models have become apparent, including the development and testing of landscape metrics to characterize landscape pattern. Although metric development proved to be significant, the focus on metrics obscured the need for iterative hypothesis testing fundamental to the advancement of the discipline. We present here an example of an alternative neutral model and hypothesis designed to relate the process of landscape change to observed landscape patterns. The methods and program, QRULE, are described and options for statistical testing outlined. The results show that human fragmentation of landscapes results in a non-random association of land-cover types that can be describe by simple statistical methods. Options for additional landscape studies are discussed and access to QRULE described in the hope that these methods will be employed to advance our understanding of the processes that affect the structure and function in human dominated landscapes.://000243619800004 ISI Document Delivery No.: 127XO Times Cited: 0 Cited Reference Count: 73 Cited References: *NRC, 2001, GRAND CHALL ENV SCI *NRC, 2003, NEON ADDR NAT ENV CH ANDERSON DR, 2000, J WILDLIFE MANAGE, V64, P912 ANDERSON GS, 1997, LANDSCAPE ECOL, V12, P261 ANDOW DA, 1990, LANDSCAPE ECOL, V4, P177 BENNETT AF, 1994, BIOL CONSERV, V68, P155 BURNHAM KP, 1998, MODEL SELECTION INFE COPELAND JH, 1996, J GEOPHYS RES-ATMOS, V101, P7409 COSTANZA R, 1994, LANDSCAPE ECOL, V9, P47 DALE VH, 1994, CONSERV BIOL, V8, P1027 DELCOURT HR, 1983, QUATERNARY SCI REV, V1, P153 DISTEFANO J, 2004, FOREST ECOL MANAG, V187, P173 FAGAN WE, 1999, AM NAT, V153, P165 FAUTH PT, 2000, LANDSCAPE ECOL, V15, P621 FOLEY JA, 2005, SCIENCE, V309, P570 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FORTIN MJ, 2003, OIKOS, V102, P203 FOSTER DR, 1998, ECOSYSTEMS, V1, P96 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GARDNER RH, 1990, QUANTITATIVE METHODS, P289 GARDNER RH, 1999, LANDSCAPE ECOLOGICAL, P280 GARNDER RH, IN PRSS KEY TOPICS P GOETZ SJ, 2004, ECOSYSTEMS LAND USE, P263 GOTELLI NJ, 1996, NULL MODELS ECOLOGY GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 HANSKI I, 2005, EMBO REP, V6, P388 JOHNSON DH, 2002, J WILDLIFE MANAGE, V66, P272 JOHNSON NL, 1970, CONTINUOUS UNIVARIAT, V1 JOHNSON NL, 1970, CONTINUOUS UNIVARIAT, V2 KRUMMEL JR, 1987, OIKOS, V48, P321 LANGLOIS JP, 2001, LANDSCAPE ECOL, V16, P255 LAVOREL S, 1994, OIKOS, V71, P75 LINDBORG R, 2004, ECOLOGY, V85, P1840 MADDOX J, 1992, NATURE, V359, P35 MANLY BFJ, 1997, RANDOMIZATION BOOTST MCCAY DH, 2001, LANDSCAPE ECOL, V16, P89 MEYER WB, 1992, ANNU REV ECOL SYST, V23, P39 MLADENOFF DJ, 1999, SPATIAL MODELING FOR MOTZKIN G, 1999, J VEG SCI, V10, P903 NASSAUER JI, 1997, PACING NATURE CULTUR NEEL MC, 2004, LANDSCAPE ECOL, V19, P435 ONEILL RV, 1992, LANDSCAPE ECOL, V7, P55 ORWIG DA, 1994, CAN J FOREST RES, V24, P1216 OSHER LJ, 2003, BIOGEOCHEMISTRY, V65, P213 PEARSON SM, 1997, WILDLIFE LANDSCAPE E, P215 PLATT JR, 1964, SCIENCE, V146, P347 PLOTNICK RE, 1993, LANDSCAPE ECOL, V8, P201 PLOTNICK RE, 1993, LECT MATH LIFE SCI P, V23, P129 PLOTNICK RE, 1996, PHYS REV E B, V53, P5461 PYKE CR, 2004, FRONT ECOL ENVIRON, V2, P178 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 RIITTERS KH, 2002, ECOSYSTEMS, V5, P815 RIITTERS KH, 2005, ENVIRON MANAGE, V35, P483 RILEY RH, 1997, INT J REMOTE SENS, V18, P121 ROBINSON DH, 2002, J WILDLIFE MANAGE, V66, P263 ROMME WH, 1998, ECOSYSTEMS, V1, P524 STAUFFER D, 1992, INTRO PERCOLATION TH STOHLGREN TJ, 1998, GLOB CHANGE BIOL, V4, P495 TAVERNA K, 2005, LANDSCAPE ECOL, V20, P689 TISCHENDORF L, 2003, LANDSCAPE ECOL, V18, P41 TURNER MG, 1994, NAT AREA J, V14, P3 TURNER MG, 2001, LANDSCAPE ECOLOGY TH URBAN DL, 1987, BIOSCIENCE, V37, P119 URBAN DL, 2000, LANDSCAPE ECOL, V15, P603 URBAN DL, 2005, ECOLOGY, V86, P1996 VITOUSEK PM, 1997, SCIENCE, V277, P494 VOGELMANN JE, 2001, PHOTOGRAMM ENG REM S, V67, P650 WICKHAM JD, 1997, PHOTOGRAMM ENG REM S, V63, P397 WICKHAM JD, 2000, LANDSCAPE ECOL, V15, P171 WILLIAMS MR, 2004, BIOGEOCHEMISTRY, V68, P259 WITH KA, 1997, OIKOS, V79, P219 WU JG, 2002, LANDSCAPE ECOL, V17, P355 ZAR JH, 1996, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000243619800004Univ Maryland, Ctr Environm Sci, Appalachian Lab, Frostburg, MD 21532 USA. Duke Univ, Nicholas Sch Environm & Earth Sci, Durham, NC 27708 USA. Gardner, RH, Univ Maryland, Ctr Environm Sci, Appalachian Lab, Frostburg, MD 21532 USA. gardner@al.umces.eduEnglish!<7g!Garrabou, J. Riera, J. Zabala, M.1998ULandscape pattern indices applied to Mediterranean subtidal rocky benthic communities225-247Landscape Ecology134benthic community structure depth gradient temporal patterns Mediterranean benthic communities POPULATION-DYNAMICS DISTURBANCE ECOLOGY COMPETITION ORGANISMS CORALS GROWTHArticleAug Marine rocky benthic communities present rich contrasts in spatial pattern. Its quantification is a prerequisite for the comparison of spatial pattern across communities, for the evaluation of temporal changes, and for the analysis of the effects of pattern on ecological processes. This study pursues two goals: (1) to evaluate the potential application of landscape pattern indices to the description of spatial pattern in Mediterranean subtidal rocky benthic communities, and (2) to select a minimal set of informative, non-redundant indices for the description of spatial pattern in these communities. Four communities dwelling along a depth gradient were studied, two dominated by algae, and two dominated by clonal animals. The communities differed in species composition, dynamics and structure. Using traditional methods, previous studies had determined that, along this depth gradient, the heterogeneity of community spatial patterns increases, and their seasonal dynamics becomes dampened. We used a series of photographs (310 cm(2) each) of permanent sites taken monthly over a one year period to analyze community spatial pattern. We tested a total of 17 landscape pattern indices that quantify different aspects of spatial pattern (patch size and shape characteristics, diversity, contagion and interspersion), for differences among communities, and for differences through time within each community. Results show clear differences in patch characteristics (number, mean size, size variability and shape), diversity, contagion and interspersion indices, among communities. In some cases, significant temporal patterns were also found, and these were consistent with the seasonal dynamics formerly described for each community. Generally, spatial pattern was less heterogeneous, but more variable seasonally, in the shallower, algae-dominated communities, than in deeper communities dominated by clonal animals. These results indicate the existence of community-related characteristic spatial patterns, and characteristic spatial pattern dynamics, in subtidal rocky benthic communities. Moreover, trends found in this study were in agreement with previous studies of spatial pattern in Mediterranean rocky benthic communities. Based on this study, we selected number of patches, mean patch size, standard deviation of patch size, mean shape patch index, and Shannon's diversity index as the most suitable set of indices for the description of spatial pattern in Mediterranean subtidal rocky benthic communities.://000079677000004 ISI Document Delivery No.: 185NY Times Cited: 23 Cited Reference Count: 48 Cited References: BAK RPM, 1980, OECOLOGIA, V47, P147 BAK RPM, 1995, B MAR SCI, V56, P609 BALLESTEROS E, 1991, OECOL AQUAT, V10, P223 BALLESTEROS E, 1992, ELS VEGETALS ZONACIO BALLESTEROS E, 1993, MON SOC HIST NAT BAL, V2, P663 BARRY JP, 1991, ECOLOGICAL HETEROGEN, P270 BOUDOURESQUE CF, 1971, TETHYS, V3, P79 BRADBURY RH, 1983, MAR ECOL-PROG SER, V11, P265 BUSS LW, 1979, BIOL SYSTEMATICS COL CONNELL JH, 1970, ECOL MONOGR, V40, P49 CROWLEY PH, 1992, ANNU REV ECOL SYST, V23, P405 DAVIS AR, 1988, J EXP MAR BIOL ECOL, V117, P157 DAYTON PK, 1971, ECOL MONOGR, V41, P351 DAYTON PK, 1974, ECOL MONOGR, V44, P105 DAYTON PK, 1992, ECOL MONOGR, V62, P421 DENNY MW, 1985, LIMNOL OCEANOGR, V30, P1171 EDINGTON ES, 1987, RANDOMIZATION TESTS FARRANT PA, 1987, MAR BIOL, V96, P401 FELDMANN J, 1937, RECHERCHES VEGETATIO FORMAN RTT, 1986, LANDSCAPE ECOLOGY GENIN A, 1986, NATURE, V322, P59 GILI JM, 1985, PSZNI MAR ECOL, V6, P219 HAY ME, 1991, ECOLOGY FISHES CORAL, P96 HISCOCK K, 1980, SHORE ENV, V2, P323 HUGHES TP, 1985, ECOL MONOGR, V55, P141 HULSHOFF RM, 1995, LANDSCAPE ECOL, V10, P101 JACKSON JBC, 1979, BIOL SYSTEMATICS COL, P499 KEOUGH MJ, 1984, ECOLOGY, V65, P677 KOZIEL JA, 1981, BIOMETRICS, V37, P382 MANLY BFJ, 1991, RANDOMIZATION MONTE MCGARIGAL K, 1994, FRAGSTATS SPATIAL PA MCGARIGAL K, 1995, ECOL MONOGR, V65, P235 MURRAY SN, 1989, BOT MAR, V32, P457 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PAINE RT, 1966, AM NAT, V100, P65 PAINE RT, 1981, ECOL MONOGR, V51, P145 PORTER JW, 1992, AM ZOOL, V32, P625 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 ROS JD, 1985, W MEDITERRANEAN, P233 SARA M, 1970, S ZOOL SOC LOND, V25, P273 SEBENS KP, 1983, J EXP MAR BIOL ECOL, V72, P263 SEBENS KP, 1986, ECOL MONOGR, V56, P73 SHEPPARD CRC, 1979, MAR ECOL-PROG SER, V1, P273 TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 VAGO R, 1994, B MAR SCI, V55, P126 ZABALA M, 1989, SCI MAR, V53, P1 0921-2973 Landsc. Ecol.ISI:000079677000004Univ Barcelona, Dept Ecol, E-08028 Barcelona, Spain. Garrabou, J, Univ Barcelona, Dept Ecol, Diagonal 645, E-08028 Barcelona, Spain.English4~?w Garza, C.2008tRelating spatial scale to patterns of polychaete species diversity in coastal estuaries of the western United States107-121Landscape Ecology23Historically, studies in landscape ecology have investigated how variation in spatial scale can affect the complex interactions observed in an ecosystem. In this study I describe survey data collected as part of the United States National Coastal Assessment that were used to discern the role sampling scale can play in detecting the relationship between physical factors and patterns of polychaete species diversity in marine estuaries. In this survey, sampling sites were randomly selected at three spatial scales using a probability based site selection algorithm applied to a GIS representation of all U.S. west coast estuaries. At each sampling scale, data relating to species diversity and environmental condition were collected. My analyses revealed that polychaetes displayed an increase in diversity towards the equator. It appears that across latitude both the rate of increase in and total diversity were affected by variation in the spatial scale over which the survey was conducted. Variation in scale also affected interpretations of the magnitude to which physical factors may potentially relate to species diversity across latitude. The data suggested that increased sampling scales obscured negative relationships between physical factors and species diversity across the estuaries sampled in this study. The results of this study demonstrate how assessments of the strength of the relationship between physical factors and species diversity in coastal communities can be strongly affected by variation in sampling scale."://WOS:000252922800009 Times Cited: 0WOS:000252922800009(10.1007/s10980-007-9142-2|ISSN 0921-2973~|? Gaube, V. Kaiser, C. Wildenberg, M. Adensam, H. Fleissner, P. Kobler, J. Lutz, J. Schaumberger, A. Schaumberger, J. Smetschka, B. Wolf, A. Richter, A. Haberl, H.2009Combining agent-based and stock-flow modelling approaches in a participative analysis of the integrated land system in Reichraming, Austria 1149-1165Landscape Ecology249The integrated modelling of coupled socio-ecological systems in land-change science requires innovative model concepts capable of grasping the interrelations between socioeconomic and natural components. Here, we discuss the integrated socio-ecological model SERD (Simulation of Ecological Compatibility of Regional Development) that was developed for the municipality of Reichraming in Upper Austria in a participative 2-year process involving local stakeholders. SERD includes three main components: (1) an agent-based actors module that simulates decisions of farmsteads, the municipal administration and other important actors; (2) a spatially explicit (GIS based) land-use module that simulates land-use change at the level of individual parcels of land and (3) an integrated socio-ecological stock-flow module that simulates carbon and nitrogen flows through both socioeconomic and ecological system compartments. We report on outcomes of a scenario analysis that outlines possible future trajectories depending on both external (e.g. agricultural subsidies and prices) and internal (e.g. innovation, willingness to co-operate) factors. We find that both external and internal factors can affect the behaviour of the integrated system considerably. Local and regional policies are found to be able to counteract adverse global socioeconomic conditions to some extent, but not to reverse the trend altogether. We also find strong interdependencies between socioeconomic and ecological components of the system. Fully evaluating these interdependencies is, however, not possible at the local scale alone and will require explicit consideration of higher-level effects in future research.!://WOS:000270739000002Times Cited: 0 0921-2973WOS:00027073900000210.1007/s10980-009-9356-6 |? .Gaucherel, C. Griffon, S. Misson, L. Houet, T.2010OCombining process-based models for future biomass assessment at landscape scale201-215Landscape Ecology252 We need an integrated assessment of the bioenergy production at landscape scale for at least three main reasons: (1) it is predictable that we will soon have landscapes dedicated to bioenergy productions; (2) a number of "win-win" solutions combining several dedicated energy crops have been suggested for a better use of local climate, soil mosaic and production systems and (3) "well-to-wheels" analyses for the entire bioenergy production chain urge us to optimize the life cycle of bioenergies at large scales. In this context, we argue that the new generation of landscape models allows in silico experiments to estimate bioenergy distributions (in space and time) that are helpful for this integrated assessment of the bioenergy production. The main objective of this paper was to develop a detailed modeling methodology for this purpose. We aimed at illustrating and discussing the use of mechanistic models and their possible association to simulate future distributions of fuel biomass. We applied two separated landscape models dedicated to human-driven agricultural and climate-driven forested neighboring patches. These models were combined in the same theoretical (i.e. virtual) landscape for present as well as future scenarios by associating realistic agricultural production scenarios and B2-IPCC climate scenarios depending on the bioenergy type (crop or forest) concerned in each landscape patch. We then estimated esthetical impacts of our simulations by using 3D visualizations and a quantitative "depth" index to rank them. Results first showed that the transport cost at landscape scale was not correlated to the total biomass production, mainly due to landscape configuration constraints. Secondly, averaged index values of the four simulations were conditioned by agricultural practices, while temporal trends were conditioned by gradual climate changes. Thirdly, the most realistic simulated landscape combining intensive agricultural practices and climate change with atmospheric CO2 concentration increase corresponded to the lowest and unwanted bioenergy conversion inefficiency (the biomass production ratio over 100 years divided by the averaged transport cost) and to the most open landscape. Managing land use and land cover changes at landscape scale is probably one of the most powerful ways to mitigate negative (or magnify positive) effects of climate and human decisions on overall biomass productions.!://WOS:000274437100004Times Cited: 0 0921-2973WOS:00027443710000410.1007/s10980-009-9400-6<7Gautestad, A. O. Mysterud, I.1994"Are home ranges fractals - comment143-146Landscape Ecology92AHOME RANGE; FRACTAL; HABITAT UTILIZATION; SCALE; COMPLEX MOVEMENTNoteJun://A1994NU09400006 HISI Document Delivery No.: NU094 Times Cited: 2 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1994NU09400006HGAUTESTAD, AO, UNIV OSLO,DEPT BIOL,DIV ZOOL,POB 1050,N-0316 OSLO,NORWAY.EnglishH|? iGavier-Pizarro, Gregorio I. Radeloff, Volker C. Stewart, Susan I. Huebner, Cynthia D. Keuler, Nicholas S.2010QRural housing is related to plant invasions in forests of southern Wisconsin, USA 1505-1518Landscape Ecology2510DecForests throughout the US are invaded by non-native invasive plants. Rural housing may contribute to non-native plant invasions by introducing plants via landscaping, and by creating habitat conditions favorable for invaders. The objective of this paper was to test the hypothesis that rural housing is a significant factor explaining the distribution of invasive non-native plants in temperate forests of the Midwestern US. In the Baraboo Hills, Wisconsin, we sampled 105 plots in forest interiors. We recorded richness and abundance of the most common invasive non-native plants and measured rural housing, human-caused landscape fragmentation (e.g. roads and forest edges), forest structure and topography. We used regression analysis to identify the variables more related to the distribution of non-native invasive plants (best subset and hierarchical partitioning analyses for richness and abundance and logistic regression for presence/absence of individual species). Housing variables had the strongest association with richness of non-native invasive plants along with distance to forest edge and elevation, while the number of houses in a 1 km buffer around each plot was the variable most strongly associated with abundance of non-native invasive plants. Rhamnus cathartica and Lonicera spp. were most strongly associated with rural housing and fragmentation. Berberis thumbergii and Rosa multiflora were associated with gentle slopes and low elevation, while Alliaria petiolata was associated with higher cover of native vegetation and stands with no recent logging history. Housing development inside or adjacent to forests of high conservation value and the use of non-native invasive plants for landscaping should be discouraged.!://WOS:000283371000004Times Cited: 0 0921-2973WOS:00028337100000410.1007/s10980-010-9516-8l<7%Geertsema, W. Opdam, P. Kropff, M. J.2002ePlant strategies and agricultural landscapes: survival in spatially and temporally fragmented habitat263-279Landscape Ecology173biodiversity conceptual model dispersal landscape planning metapopulation seed bank FIELD BOUNDARY VEGETATION SEED DISPERSAL POPULATION-SIZE METAPOPULATION DYNAMICS CALCAREOUS GRASSLANDS SPECIES COMPOSITION PATTERNS COMMUNITIES MANAGEMENT WOODLANDArticleeIn agricultural landscapes many plant species are limited to the network of landscape elements that are not used for agricultural production. This habitat is fragmented in space and time due to anthropogenic, biotic and abiotic factors. Therefore, plant populations are spatially sub-divided and their persistence might be dependent on the spatial dynamics in the network of local populations. Dispersal characteristics and seed bank persistence are main determinants of colonization ability which in turn is a key determinant of metapopulation viability. We propose a conceptual model that relates plant population dynamics to habitat quality, configuration and dynamics. In this model, the habitat is arranged as a network of suitable and unsuitable patches, and the distribution of the patches is assumed to be dynamic in time. Based on dispersal and seed bank characteristics four plant strategies are distinguished: species having either long (> 100 m) or short (< 100 m) distance dispersal and either a long (> 5 yr) or short (< 5 yr) term persistent seed bank. We expect that species with contrasting strategies have different survival probabilities in landscapes with contrasting habitat arrangement in space and time. We found few empirical studies for testing the hypotheses based on the model. Therefore the relation between landscapes and plant survival needs to be further explored, especially the quantitative aspects. We propose an iterative process of empirical and modelling research to determine this relation and to define management options for multifunctional farms in which biodiversity is one of the land use aims.://000178082200005 SISI Document Delivery No.: 594ZK Times Cited: 11 Cited Reference Count: 84 Cited References: *CBS, 1993, BOT BAS REG *PERC NED, 1989, VER PERC TUSS 1900 ANTONOVICS J, 1994, ECOLOGICAL GENETICS, P146 BAKKER JP, 1988, LEVENDE NATUUR, V89, P173 BAKKER JP, 1996, ACTA BOT NEERL, V45, P461 BAKKER JP, 1999, TRENDS ECOL EVOL, V14, P63 BAUDRY J, 1993, LANDSCAPE URBAN PLAN, V24, P153 BAUDRY J, 1997, SPECIES DISPERSAL LA, P3 BEKKER RM, 1998, THESIS BOATMAN N, 1994, MONOGRAPH BRIT CROP, V58 BRANDT J, 2000, MULTIFUNCTIONAL LAND BULLE B, 1994, LANDSCHAP, V11, P19 CAIN ML, 2000, AM J BOT, V87, P1217 DANVIND M, 1997, J VEG SCI, V8, P271 DEFFONTAINES JP, 1995, LANDSCAPE URBAN PLAN, V31, P3 DESNOO GR, 1999, AGR ECOSYST ENVIRON, V73, P1 DZWONKO Z, 1993, J VEG SCI, V4, P693 ERIKSSON O, 1996, OIKOS, V77, P248 FALINSKA K, 1999, J ECOL, V87, P461 FISCHER M, 1997, CONSERV BIOL, V11, P727 FISCHER SF, 1996, J APPL ECOL, V33, P1206 FRANK K, 1998, LANDSCAPE ECOL, V13, P363 FROBORG H, 1997, J VEG SCI, V8, P395 FRY GLA, 1994, FIELD MARGINS INTEGR, P31 GEERTSEMA W, IN PRESS PLANT ECOLO GRASHOFBOKDAM C, 1997, J VEG SCI, V8, P21 GRASHOFBOKDAM CJ, 1998, J BIOGEOGR, V25, P837 GRASHOFBOKDAM CJ, 1998, MOL ECOL, V7, P165 GRIME JP, 1992, SEEDS ECOLOGY REGENE, P349 HANSKI I, 1985, ECOLOGY, V66, P335 HARRISON S, 2000, CONSERV BIOL, V14, P769 HARVEY CA, 2000, ECOL APPL, V10, P155 HAUGHTON AJ, 1998, 1998 BRIGHT C PESTS, P285 HERLIN ILS, 2000, LANDSCAPE ECOLOGY, V18, P229 HODGSON JG, 1995, ELECT COMP PLANT ECO HORLINGS I, 1996, THESIS KATHOLIEKE U HOWE HF, 1982, ANNU REV ECOL SYST, V13, P201 HUGHES L, 1994, J ECOL, V82, P933 HUSBAND BC, 1996, J ECOL, V84, P461 HUSBAND BC, 1998, J ECOL, V86, P1021 JOENJE W, 1994, FIELD MARGINS INTEGR, P323 KLEIJN D, 1997, ACTA BOT NEERL, V46, P175 KLEIJN D, 1998, AGR ECOSYST ENVIRON, V68, P13 KLEIJN D, 2000, J APPL ECOL, V37, P256 LAMONT BB, 1993, NATURE, V362, P211 LAVOREL S, 1998, ACTA OECOL, V19, P227 LECOEUR D, 1997, LANDSCAPE URBAN PLAN, V37, P57 LEVINS R, 1970, LECT MATH LIFE SCI, V2, P77 MARSHALL EJP, 1989, J APPL ECOL, V26, P247 MARSHALL EJP, 1995, LANDSCAPE URBAN PLAN, V31, P205 MCLAUGHLIN A, 1995, AGR ECOSYST ENVIRON, V55, P201 MELMAN TCP, 1988, MUNSTERSCHE GEOGRAFI, V29, P157 MERRIAM G, 1988, TRENDS ECOL EVOL, V3, P16 MIDDLETON J, 1983, J APPL ECOL, V20, P625 MOONEN AC, 2001, AGR ECOSYST ENVIRON, V86, P187 MOUNTFORD JO, 1994, FIELD MARGINS INTEGR, P105 NIPVANDERVOORT J, 1979, J BIOGEOGR, V6, P301 NOBLE IR, 1996, J VEG SCI, V7, P329 OPDAM P, CONCEPTS APPL LANDSC OPDAM P, IN PRESS LANDSCAPE E OPDAM P, 1990, SPECIES DISPERSAL AG, P1 OPDAM P, 2000, LANDSCHAP, V17, P45 OUBORG NJ, 1993, OIKOS, V66, P298 OUBORG NJ, 1999, J ECOL, V87, P551 PARR TW, 1988, J APPL ECOL, V25, P1073 POSCHLOD P, 1998, ACTA BOT NEERL, V47, P27 PRINS AH, 1998, ACTA BOT NEERL, V47, P71 QUINTANAASCENCIO RF, 1996, CONSERV BIOL, V10, P1210 RICHARDS CM, 2000, AM NAT, V155, P383 STRYKSTRA RJ, 1996, ACTA BOT NEERL, V45, P557 TERHEERDT GNJ, 1999, FUNCT ECOL, V13, P428 THOMPSON K, 1997, SOIL SEED BANKS NW E TILMAN D, 1997, ECOLOGY, V78, P81 VALVERDE T, 1997, J ECOL, V85, P193 VANDERMEIJDEN E, 1992, ACTA BOT NEERL, V41, P249 VANDERPIJL L, 1982, PRINCIPLES DISPERSAL VANDORP D, 1996, CAN J BOT, V74, P1956 VANDORP D, 1996, THESIS WAGENINGEN AG VANGROENENDAEL J, 2000, FOLIA GEOBOT, V35, P107 VANSTRIEN AJ, 1989, J APPL ECOL, V26, P989 VERBOOM J, 1993, LANDSCAPE ECOLOGY ST, P172 VOS CC, 2001, AM NAT, V157, P24 WILLSON MF, 1990, J VEG SCI, V1, P547 WILLSON MF, 1993, VEGETATIO, V107, P261 0921-2973 Landsc. Ecol.ISI:000178082200005ALTERRA Res Inst, NL-6700 AA Wageningen, Netherlands. Geertsema, W, ALTERRA Res Inst, POB 47, NL-6700 AA Wageningen, Netherlands.English#}?(Gelling, M. Macdonald, D. W. Mathews, F.2007qAre hedgerows the route to increased farmland small mammal density? Use of hedgerows in British pastoral habitats 1019-1032Landscape Ecology227Aug://000248381900005 0921-2973ISI:000248381900005<7 Gergel, S. E.2005_Spatial and non-spatial factors: When do they affect landscape indicators of watershed loading?177-189Landscape Ecology202landscape metrics; land use; monitoring; neutral landscape models; non-point source pollution; nutrient loading model; percolation theory; random maps; spatial models; spatial sensitivity analysis; water chemistry COEFFICIENT MODELING APPROACH; MID-ATLANTIC REGION; LAND-USE CHANGE; UNITED-STATES; SHORTGRASS STEPPE; NITROGEN EXPORT; RIPARIAN FOREST; ORGANIC-CARBON; QUALITY; MANAGEMENTArticleFeb=The percentage of a watershed occupied by agricultural areas is widely used to predict nutrient loadings and in-stream water chemistry because water quality is often linked to non-point sources in a watershed. Measures of the spatial location of source areas have generally not been incorporated into such landscape indicators although empirical evidence and watershed loading models suggest that spatially explicit information is useful for predicting loadings. I created a heuristic grid-based surface-flow model to address the discrepancies between spatially explicit and non-spatial approaches to understanding watershed loading. The mean and variance in loading were compared among thousands of simulated watersheds with varying percentages of randomly located source and sinks. The variability in loading among replicate landscapes was greatest for those landscapes with similar to 65% source areas. This variance peak suggests that considering the spatial arrangement of cover types is most important for watersheds with intermediate relative abundances of sources and sinks as the wide variety of different spatial configurations can lead to either very high or very low loading. Increasing the output from source pixels (relative to the amount absorbed by sink pixels) among different landscapes moved the peak in variance to landscapes with lower percentages of sources. A final scenario examined both broad- and fine-scale heterogeneity in source output to disentangle the relative contributions of spatial configuration, percentage of source covers, and heterogeneity of sources in governing variability in loading. In landscapes with high percentages of source pixels, fine-scale heterogeneity in source output was responsible for a greater portion of the total variability in loading among different watersheds than was spatial arrangement. These results provide several testable hypotheses for when spatial and non-spatial approaches might be most useful in relating land cover to water chemistry and suggest improvements for the spatial sensitivity analyses of eco-hydrologic watershed models.://000230299600005 ISI Document Delivery No.: 942RN Times Cited: 2 Cited Reference Count: 50 Cited References: ALEXANDER RB, 2002, BIOGEOCHEMISTRY, V57, P295 BAND LE, 2001, HYDROL PROCESS, V15, P2013 BOYER EW, 2002, BIOGEOCHEMISTRY, V57, P137 CAHN MD, 1994, SOIL SCI SOC AM J, V58, P1240 CAMBARDELLA CA, 1994, SOIL SCI SOC AM J, V58, P1501 CARPENTER SR, 1998, ISSUES ECOLOGY CORRELL DL, 1991, ROLE LANDSCAPE BOUND, P90 CRESSER MS, 2000, J APPL ECOL S1, V37, P171 DELGADO JA, 1996, BIOGEOCHEMISTRY, V32, P41 DELGADO JA, 2002, J SOIL WATER CONSERV, V57, P389 FISHER P, 1997, HYDROL PROCESS, V11, P241 GERGEL SE, 1999, ECOL APPL, V9, P1377 GERGEL SE, 2002, AQUAT SCI, V64, P118 GRIFFITH JA, 2002, WATER AIR SOIL POLL, V138, P181 GROFFMAN PM, 1997, SOIL SCI SOC AM J, V61, P323 HANRAHAN G, 2001, J ENVIRON QUAL, V30, P1738 HARDING JS, 1998, P NATL ACAD SCI USA, V95, P14834 HERLIHY AT, 1998, US WATER AIR SOIL PO, V105, P377 HILL AR, 2000, BIOGEOCHEMISTRY, V51, P193 HORNBERGER GM, 1998, ELEMENTS PHYS HYDROL JETTEN V, 2003, HYDROL PROCESS, V17, P887 JOHNES P, 1996, FRESHWATER BIOL, V36, P451 JOHNES PJ, 1996, J HYDROL, V183, P323 JOHNSON JH, 1997, SE GEOGRAPHER, V37, P1 JONES KB, 2000, ENVIRON MONIT ASSESS, V63, P159 JONES KB, 2000, ENVIRON MONIT ASSESS, V64, P227 JONES KB, 2001, LANDSCAPE ECOL, V16, P301 JORDAN TE, 1997, WATER RESOUR RES, V33, P2579 KELLING KA, 1998, COOPERATIVE EXTENSIO, V2809 KHOSLA R, 2002, J SOIL WATER CONSERV, V57, P513 KLEIN RD, 1979, WATER RESOURCES B, V15, P948 LEE KY, 2000, BIOGEOCHEMISTRY, V49, P143 LOWRANCE R, 1984, BIOSCIENCE, V34, P374 LOWRANCE R, 1992, J ENVIRON QUAL, V21, P401 LUDWIG JA, 2002, LANDSCAPE ECOL, V17, P157 MATTIKALLI NM, 1996, J ENVIRON MANAGE, V48, P263 MCCLAIN ME, 2003, ECOSYSTEMS, V6, P301 MOSIER AR, 1996, GLOBAL BIOGEOCHEM CY, V10, P387 MOUSSA R, 2002, HYDROL PROCESS, V16, P393 NORTON MM, 2000, ECOL ENG, V14, P337 PETERJOHN WT, 1984, ECOLOGY, V65, P1466 RICHARDS D, 1996, CANADIAN J FISHER S1, V53, P295 SCHUELER TR, 1992, WATERSHED RESTORATIO SPONSELLER RA, 2001, FRESHWATER BIOL, V46, P1409 TAGUE CL, 2001, HYDROL PROCESS, V15, P1415 TURNER MG, 2001, LANDSCAPE ECOLOGY TH VERCHOT LV, 2002, SOIL BIOL BIOCHEM, V34, P1691 WELLER DE, 1998, ECOL APPL, V8, P1156 WITH KA, 1997, OIKOS, V79, P219 ZAK DR, 1991, OECOLOGIA, V88, P189 0921-2973 Landsc. Ecol.ISI:000230299600005Univ British Columbia, Dept Forest Sci, Ctr Appl Conservat Res, Vancouver, BC V6T 1Z4, Canada. Gergel, SE, Univ British Columbia, Dept Forest Sci, Ctr Appl Conservat Res, 3008-2424 Main Mall, Vancouver, BC V6T 1Z4, Canada. sarah.gergel@ubc.caEnglish<7i Gibbs, J. P.1998IDistribution of woodland amphibians along a forest fragmentation gradient263-268Landscape Ecology134amphibians fragmentation disturbance salamanders frogs Plethodon cinereus Ambystoma maculatum Notophthalmus v. viridescens Pseudacris c. crucifer Rana sylvatica FROG RANA-SYLVATICA POPULATIONS EXTINCTION FLUCTUATIONS CONSERVATION COMMUNITIES PATTERNS HABITATArticleAugUnderstanding how changes;in land-use affect the distribution and abundance of organisms is an increasingly important question in landscaping ecology. Amphibians may be especially prone to local extinction resulting from important question in landscape ecology. Amphibians may be especially prone to local extinction resulting from human-caused transformation and fragmentation of their habitats owing to the spatially and temporally dynamic nature of their populations. In this study, distributions of five species of woodland amphibians with differing life histories were surveyed along a 10 km, spatially continuous gradient of forest fragmentation in southern Connecticut, U.S.A. Redback salamanders (Plethodon cinereus) and northern spring peepers (Pseudacris c. crucifer) occupied available habitat along the gradient's length. Wood frogs (Rana sylvatica) and spotted salamanders (Ambystoma maculatum) were absent from portions of the gradient where forest cover was reduced to below about 30%. Red-spotted newts (Notophthalmus v. viridescens) did not persist below a forest cover threshold of about 50%. Correlations between species' biological traits and their fragmentation tolerance imply that low density, population variability, and high mobility coupled with restricted habitat needs predispose woodland amphibians to local extinction caused by habitat fragmentation. These patterns are in contrast to the widely held notion that populations of the best dispersers are those most tolerant of habitat fragmentation.://000079677000006 DISI Document Delivery No.: 185NY Times Cited: 61 Cited Reference Count: 34 Cited References: ANDREN H, 1994, OIKOS, V71, P355 BERVEN KA, 1990, ECOLOGY, V71, P1599 BERVEN KA, 1990, EVOLUTION, V44, P2047 BLAIR RB, 1996, ECOL APPL, V6, P506 BLAUSTEIN AR, 1994, CONSERV BIOL, V8, P60 BOLGER DT, 1991, AM NAT, V137, P155 BRODIE ED, 1968, AM MIDL NAT, V80, P276 BURGMAN MA, 1993, RISK ASSESSMENT CONS BURTON TM, 1975, COPEIA, P541 COOKE AS, 1988, B BRIT HERPETOLOGICA, V26, P29 DEGRAAF RM, 1990, FOREST ECOL MANAG, V32, P155 EASTMAN JR, 1992, IDRISI FAHRIG L, 1994, CONSERV BIOL, V8, P50 FAHRIG L, 1995, BIOL CONSERV, V73, P177 FORMAN RTT, 1986, LANDSCAPE ECOLOGY GASCON C, 1991, ECOLOGY, V72, P1731 GILL DE, 1978, ECOL MONOGR, V48, P145 HEATWOLE H, 1962, ECOLOGY, V43, P460 KAREIVA P, 1995, NATURE, V373, P299 KLEMENS MW, 1993, STATE GEOLOGICAL NAT, V112 LAAN R, 1990, BIOL CONSERV, V54, P251 LUBCHENCO J, 1991, ECOLOGY, V72, P371 MCCARTHY MA, 1997, CONSERV BIOL, V11, P221 MONMONIER MS, 1974, AM CARTOGRAPHER, V2, P159 OPDAM P, 1993, LANDSCAPE ECOLOGY ST, P147 PECHMANN JHK, 1991, SCIENCE, V253, P892 SJOGREN P, 1991, BIOL J LINN SOC, V42, P135 VANGELDER JJ, 1973, OECOLOGIA, V13, P93 WHITCOMB RF, 1981, FOREST ISLAND DYNAMI, P125 WILBUR HM, 1980, ANNU REV ECOL SYST, V11, P67 WYMAN RL, 1987, ECOLOGY, V68, P1819 WYMAN RL, 1990, GLOBAL CLIMATE CHANG, P134 YAHNER RH, 1988, CONSERV BIOL, V2, P333 ZIMMERMAN BL, 1986, J BIOGEOGR, V13, P133 0921-2973 Landsc. Ecol.ISI:000079677000006Yale Univ, Sch Forestry & Environm Studies, New Haven, CT 06511 USA. Gibbs, JP, SUNY Coll Environm Sci & Forestry, 350 Illick Hall, Syracuse, NY 13210 USA.EnglishF|? 6Gibon, A. Sheeren, D. Monteil, C. Ladet, S. Balent, G.2010fModelling and simulating change in reforesting mountain landscapes using a social-ecological framework267-285Landscape Ecology252Natural reforestation of European mountain landscapes raises major environmental and societal issues. With local stakeholders in the Pyrenees National Park area (France), we studied agricultural landscape colonisation by ash (Fraxinus excelsior) to enlighten its impacts on biodiversity and other landscape functions of importance for the valley socio-economics. The study comprised an integrated assessment of land-use and land-cover change (LUCC) since the 1950s, and a scenario analysis of alternative future policy. We combined knowledge and methods from landscape ecology, land change and agricultural sciences, and a set of coordinated field studies to capture interactions and feedback in the local landscape/land-use system. Our results elicited the hierarchically-nested relationships between social and ecological processes. Agricultural change played a preeminent role in the spatial and temporal patterns of LUCC. Landscape colonisation by ash at the parcel level of organisation was merely controlled by grassland management, and in fact depended on the farmer's land management at the whole-farm level. LUCC patterns at the landscape level depended to a great extent on interactions between farm household behaviours and the spatial arrangement of landholdings within the landscape mosaic. Our results stressed the need to represent the local SES function at a fine scale to adequately capture scenarios of change in landscape functions. These findings orientated our modelling choices in the building an agent-based model for LUCC simulation (SMASH-Spatialized Multi-Agent System of landscape colonization by ASH). We discuss our method and results with reference to topical issues in interdisciplinary research into the sustainability of multifunctional landscapes.!://WOS:000274437100008Times Cited: 0 0921-2973WOS:00027443710000810.1007/s10980-009-9438-5(<7:Gilbert, M. Nageleisen, L. M. Franklin, A. Gregoire, J. C.2005Post-storm surveys reveal large-scale spatial patterns and influences of site factors, forest structure and diversity in endemic bark-beetle populations35-49Landscape Ecology201!bark-beetle; France; geostatistics; Ips sexdentatus; Ips typographus; metapopulation; non-host volatile; Pityogene schalcographus; Tomicus pimperda SOUTHERN PINE-BEETLE; IPS-TYPOGRAPHUS; NORWAY SPRUCE; TOMICUS-PINIPERDA; SHOOT BEETLE; PICEA-ABIES; SCOLYTIDAE; COLEOPTERA; VOLATILES; ATTACKArticleJanThe storm that struck France on december 26(th) and 28(th) 1999 felled 140 million m(3) of timber and had a high economic, social and landscape impact. This event offered the opportunity to study large-scale patterns in populations of forest insect pests that would benefit from the abundant breeding material. A large-scale survey was carried out in France in 2000 to sample the most frequently observed species developing on spruce (Ips typographus, Pityogene schalcographus) and pine (Tomicus piniperda, Ips sexdentatus) in 898 locations distributed throughout wind-damaged areas. The local abundance of each species scored on a 0 to 5 scale was analysed using geostatistical estimators to explore the extent and intensity of spatial autocorrelation, and was related to site, stand, and neighbourhood landscape metrics of the forest cover (in particular the interconnection with broadleaf forest patches) found within dispersal distance. All species but I. sexdentatus, which was much less abundant, displayed large-scale spatial dependence and regional variations in abundance. Lower infestation levels per tree (windfalls and standing trees) were observed in stands with a high proportion of wind-damaged trees, which was interpreted as the result of beetles distributing themselves among the available breeding material. More infestations were observed in wind-broken trees as compared to wind-felled trees. More importantly, populations showed significant relationships with the structure of coniferous stands (in particular with the number of coniferous patches). T piniperda population levels were negatively correlated to the amount of coniferous edge shared with broadleaf forest patches, possibly because of the disruptive effect of non-host volatiles on host-finding processes at the landscape-scale. The differences observed between species regarding patterns and relationships to site, stand, and forest cover characteristics are discussed in relation to the ecological characteristics of each species.://000231223900003 ISI Document Delivery No.: 955KD Times Cited: 0 Cited Reference Count: 51 Cited References: *CEC, 1994, CORINE LAND COV TECH *MET FRANC, 2003, NOMBR JOURS AV GEL N *MET FRANC, 2003, TEMP DEC 1999 ABGRALL JF, 1987, REV FORESTIERE FRANO, V34, P359 AMEZAGA I, 1998, FOREST ECOL MANAG, V109, P127 BEBI P, 2003, ECOLOGY, V84, P362 BERRYMAN AA, 1986, FOREST INSECTS PRINC, P125 BYERS JA, 1998, NATURWISSENSCHAFTEN, V85, P557 COULSON RN, 1979, ANNU REV ENTOMOL, V24, P417 COULSON RN, 1999, FOREST ECOL MANAG, V114, P471 DUTILLEUL P, 1993, BIOMETRICS, V49, P305 DUTILLEUL P, 2000, J APPL ENTOMOL, V124, P1 ELKIE P, 1999, PATCH ANAL USERS MAN FOLAY P, 1997, METAPOPULATION BIOL, P215 FORSSE E, 1989, THESIS SWEDISH AGR U FORTIN MJ, 1989, VEGETATIO, V83, P209 FRANKLIN A, 2001, THESIS FREE U BRUSSE GILBERT M, 2003, AGR FOREST ENTOMOL, V5, P1 GILBERT M, 2003, CAN J FOREST RES, V33, P712 GOTHLIN E, 2000, SCAND J FOREST RES, V15, P542 GREGOIRE JC, 1988, POPULATION DYNAMICS, P455 GUMPERTZ ML, 2000, FOREST SCI, V46, P95 HASSELL MP, 1997, SPATIAL ECOLOGY ROLE, P75 JACTEL H, 2002, J APPL ECOL, V39, P618 JACTEL H, 2003, IN PRESS IPM REV JAKUS R, 1998, J APPL ENTOMOL, V122, P543 KEITT TH, 2002, ECOGRAPHY, V25, P616 KOHNLE U, 1992, J APPL ENTOMOL, V114, P83 LANDMANN G, 2000, SANTE FORETS 1999 CA, P45 LEGENDRE P, 2002, ECOGRAPHY, V25, P601 LENNON JJ, 2000, ECOGRAPHY, V23, P101 LIEUTIER F, 2004, BARK WOOD BORING INS NAGELEISEN LM, 2000, SANTE FORETS 1999 CA NAGELEISEN LM, 2002, SANTE FORETS 2000 20, P70 NEE S, 1997, METAPOPULATION BIOL, P123 NEGRON JF, 1998, FOREST ECOL MANAG, V107, P71 NEGRON JF, 2000, ENVIRON ENTOMOL, V29, P20 PELTONEN M, 1997, SILVA FENNICA, V31, P129 PELTONEN M, 1998, FOREST ECOL MANAG, V103, P141 PELTONEN M, 1999, SCAND J FOREST RES, V14, P505 PELTONEN M, 2002, ECOLOGY, V83, P3120 PERKINS TE, 2002, FOREST ECOL MANAG, V157, P143 POLAND TM, 2000, J APPL ENTOMOL, V124, P63 POWERS JS, 1999, LANDSCAPE ECOL, V14, P105 REEVE JD, 1995, POPULATION DYNAMICS, P339 ROLAND J, 1993, OECOLOGIA, V93, P25 ROSSI RE, 1992, ECOL MONOGR, V62, P277 SCHLYTER F, 1990, ENTOMOL EXP APPL, V54, P163 SCHROEDER LM, 1999, FOREST ECOL MANAG, V123, P21 THIEL J, 1999, METHODOLOGY FOREST I, P236 ZHANG QH, 2003, OIKOS, V101, P299 0921-2973 Landsc. Ecol.ISI:000231223900003Free Univ Brussels, B-1050 Brussels, Belgium. Natl Fund Sci Res, Brussels, Belgium. Forest Hlth Dept, Nancy, France. Royal Belgian Inst Nat Sci, Brussels, Belgium. Gilbert, M, Free Univ Brussels, B-1050 Brussels, Belgium. mgilbert@ulb.ac.beEnglish^<7 Gillson, L.2004CEvidence of hierarchical patch dynamics in an east African savanna?883-894Landscape Ecology198Kenya; pollen; non-equilibrium; savanna ecology; stable isotopes; tsavo SEMIARID SAVANNAS; LANDSCAPE ECOLOGY; WOODY VEGETATION; COEXISTENCE; FIRE; DELTA-C-13; SERENGETI; WOODLANDS; SEDIMENTS; ELEPHANTArticleThe Hierarchical Patch Dynamics Paradigm provides a conceptual framework for linking pattern, process and scale in ecosystems, but there have been few attempts to test this theory because most ecological studies focus on only one spatial scale, or are limited in their temporal scope. Here I use palaeoecological techniques (analysis of fossil pollen and stable carbon isotopes) to compare vegetation heterogeneity in an east African savanna at three spatial scales, over hundreds of years. The data show that patterns of vegetation change are different at the three spatial scales of observation, and suggest that different ecological processes dominate tree abundance at micro, local and landscape scales. Interactions between plants, disturbance (e.g., by fire and herbivores), climate and soil type may influence tree density at differing spatial and temporal scales. This hierarchical explanation of savanna vegetation dynamics could inform future biodiversity conservation and management in savannas.://000226268600006 ISI Document Delivery No.: 886YI Times Cited: 3 Cited Reference Count: 53 Cited References: BENNETT KD, 2001, TRACKING ENV CHANGE, P355 BIRD MI, 1994, LIMNOL OCEANOGR, V39, P1845 BOND WJ, 2000, GLOBAL CHANGE BIOL, V9, P973 BONNEFILLE R, 1971, POLLEN SPORES, V13, P15 BONNEFILLE R, 1980, POLLENS SAVANNES AFR BURNETT C, 2003, ECOL MODEL, V168, P233 CAUGHLEY GJ, 1976, E AFR WILDL J, V14, P265 CERLING TE, 1992, PALAEOGEOGR PALAEOCL, V97, P241 COUGHENOUR MB, 1993, J BIOGEOGR, V20, P383 DUBLIN HT, 1990, J ANIM ECOL, V59, P1147 DUBLIN HT, 1995, SERENGETI, V2 EAGLESON PS, 1985, WATER RESOUR RES, V21, P1483 FROST P, 1986, BIOL INT, V10, P1 GILLSON L, 2004, J VEG SCI, V15, P339 HAMILTON A, 1982, ENV HIST E AFRICA HIGGINS SI, 2000, J ECOL, V88, P213 JELTSCH F, 1996, J ECOL, V84, P583 JELTSCH F, 1998, J ECOL, V86, P780 JOHNSON RW, 1985, ECOLOGY MANAGEMENT W, P1 KNOOP WT, 1985, J ECOL, V73, P235 LEUTHOLD W, 1996, AFR J ECOL, V34, P101 LEVIN SA, 1992, ECOLOGY, V73, P1943 MAHER L, 1972, REV PALAEOBOT PALYNO, V13, P95 MAY R, 1999, PHILOS T ROY SOC B, V354, P1951 MIDWOOD AJ, 1998, SOIL BIOL BIOCHEM, V30, P1301 MOORE PD, 1991, POLLEN ANAL NORTONGRIFFITHS M, 1979, SERENGETI DYNAMICS E, P310 ONEILL RV, 1986, HIERARCHICAL CONCEPT PEARSON RG, 2003, GLOBAL ECOL BIOGEOGR, V12, P361 PEARSON RG, 2004, ECOGRAPHY, V27, P285 PELLEW RAP, 1983, AFR J ECOL, V21, P41 PICKETT STA, 1987, VEGETATIO, V69, P109 PICKETT STA, 1989, OIKOS, V54, P129 POOLE GC, 2002, FRESHWATER BIOL, V47, P641 RAMSEY CB, 2000, OXCAL RITCHIE JC, 1985, NATURE, V314, P352 RITCHIE JC, 1987, NATURE, V330, P645 ROGERS KH, 2003, KRUGER EXPERIENCE EC, P189 SCHOLES RJ, 1997, ANNU REV ECOL SYST, V28, P517 SIKES NE, 1999, AFRICAN BIOGEOGRAPHY, P399 SKARPE C, 1992, J VEG SCI, V3, P293 SOWUNMI AS, 1995, GRANA, V34, P121 SUGITA S, 1994, J ECOL, V82, P881 SUGITA S, 1999, HOLOCENE, V9, P409 URBAN DL, 1987, BIOSCIENCE, V37, P119 VANCAMPO M, 1960, B I FRANCAIS AFRIQ A, V22, P1165 WALKER BH, 1982, ECOLOGY TROPICAL SAV, P556 WALTER H, 1971, ECOLOGY TROPICAL SUB, P556 WATT AS, 1947, J ECOLOGY, V35 WIJNGAARDEN W, 1985, ELEPHANTS TREES GRAS WU J, 1999, CANADIAN J REMOTE SE, V25, P367 WU JG, 1995, Q REV BIOL, V70, P439 WU JG, 2002, ECOL MODEL, V153, P7 0921-2973 Landsc. Ecol.ISI:000226268600006Univ Oxford, Environm Change Inst, Biodivers Res Grp, Long Term Ecol Lab, Oxford OX1 3TB, England. Gillson, L, Univ Oxford, Environm Change Inst, Biodivers Res Grp, Long Term Ecol Lab, 1A Mansfield Rd, Oxford OX1 3TB, England. lindsey.gillson@eci.ox.ac.ukEnglish*|7 Gillson, L.2009Landscapes in Time and Space149-155Landscape Ecology242landscape mosaics biocomplexity resilience thresholds adaptive cycles palaeo-invasions hierarchical patch dynamics east-african savanna infrequent disturbances fagus-sylvatica invasive spread picea-abies ecology conservation holocene scaleFebnLandscape ecology has a temporal dimension, and the role of past processes in shaping landscapes is increasingly recognised. To date, the interface between landscape ecology and palaeoecology has proved most productive in understanding the impacts of climate change and in discovering the extent of past human impacts on ecosystems. Further areas of synergy are emerging. This Perspective gives selected examples of five main areas of synergy between palaeoecology and landscape ecology: dynamic landscape mosaics; resilience and thresholds; biocomplexity; adaptive cycles; and in the landscape ecology of invasive spread.://000262828900001-399WB Times Cited:0 Cited References Count:57 0921-2973ISI:000262828900001Gillson, L Univ Cape Town, Plant Conservat Unit, Dept Bot, Private Bag X3, ZA-7701 Rondebosch, South Africa Univ Cape Town, Plant Conservat Unit, Dept Bot, ZA-7701 Rondebosch, South AfricaDoi 10.1007/S10980-008-9315-7English|?.Gillson, L. Ekblom, A. Willis, K. J. Froyd, C.2008[Holocene palaeo-invasions: the link between pattern, process and scale in invasion ecology?757-769Landscape Ecology237Invasion ecology has made rapid progress in recent years through synergies with landscape ecology, niche theory, evolutionary ecology and the ecology of climate change. The palaeo-record of Holocene invasions provides a rich but presently underexploited resource in exploring the pattern and process of invasions through time. In this paper, examples from the palaeo-literature are used to illustrate the spread of species through time and space, also revealing how interactions between invader and invaded communities change over the course of an invasion. The main issues addressed are adaptation and plant migration, ecological and evolutionary interactions through time, disturbance history and the landscape ecology of invasive spread. We consider invasions as a continuous variable, which may be influenced by different environmental or ecological variables at different stages of the invasion process, and we use palaeoecological examples to describe how ecological interactions change over the course of an invasion. Finally, the use of palaeoecological information to inform the management of invasions for biodiversity conservation is discussed.!://WOS:000258540300001Times Cited: 0 0921-2973WOS:00025854030000110.1007/s10980-008-9243-6-۽7 Gimmi, Urs Bugmann, Harald2013?Preface: integrating historical ecology and ecological modeling785-787Landscape Ecology285Springer Netherlands 2013/05/01+http://dx.doi.org/10.1007/s10980-013-9884-y 0921-2973Landscape Ecol10.1007/s10980-013-9884-yEnglish? ,Gimmi, Urs Lachat, Thibault Bürgi, Matthias2011QReconstructing the collapse of wetland networks in the Swiss lowlands 1850–2000 1071-1083Landscape Ecology268Springer NetherlandsEarth and Environmental ScienceIn Central Europe vast wetland areas have been converted into agricultural land over the past few centuries. Long-term spatially explicit reconstructions of wetland cover changes at regional scale are rare but such information is vital for setting appropriate wetland conservation and restoration goals. In this study wetland cover change over the past 150 years was analyzed for the Canton Zurich (Switzerland) using information from historical and current topographical maps. Mapping instructions changed significantly over time, i.e., wetlands were mapped more conservatively on older maps. Therefore a technique was developed to account for changes in mapping instructions and to reconstruct a series of comparable maps spanning 1850–2000. Wetland cover dramatically decreased from 13,759 ha in 1850 (more than 8% of the total study area) to 1,233 ha in 2000 (less than 1%). Largest loss is observed for the first half of the twentieth century when more than 50% of the total wetland loss occurred. In 1850, almost all wetland patches were connected in two large networks defined by a 500 m buffer around all wetland patches to account for typical dispersal distances of wetland animals. Despite extensive wetland loss, this networks remained largely intact until 1950, but then collapsed into many medium and small networks consisting of only few wetland patches. In addition to the direct loss of wetland habitats increased habitat fragmentation is limiting metapopulation dynamics and hindering genetic exchange between populations. Amphibians and other wetland animals are particularly prone to habitat fragmentation because of their limited migration abilities. This may lead to time-delayed extinction in the future because current species occurrence might rather reflect historical than current wetland cover and habitat configuration. Future restoration efforts should focus on reestablishing connectivity between remaining smaller wetland networks.+http://dx.doi.org/10.1007/s10980-011-9633-z 0921-297310.1007/s10980-011-9633-zڽ7 \Gimmi, Urs Poulter, Benjamin Wolf, Annett Portner, Hanspeter Weber, Pascale Bürgi, Matthias2013YSoil carbon pools in Swiss forests show legacy effects from historic forest litter raking835-846Landscape Ecology285Springer NetherlandseHistorical ecology Land-use legacy Soil carbon pool Biogeochemical modeling Recovery time Switzerland 2013/05/01+http://dx.doi.org/10.1007/s10980-012-9778-4 0921-2973Landscape Ecol10.1007/s10980-012-9778-4English,<7Gimona, A. Birnie, R. V.2001Spatio-temporal modelling of broad scale heterogeneity in soil moisture content: a basis for an ecologically meaningful classification of soil landscapes27-41Landscape Ecology171broad scale grasslands heather heterogeneity model soil landscapes soil moisture vegetation NITROGEN MINERALIZATION CLIMATE-CHANGE VEGETATION FLUXES NITRIFICATION TEMPERATURE INTEGRATION PREDICTION FORESTS WETNESSArticleWe describe the classification of landscapes characterised by mineral soil using a model that calculates soil moisture availability on a monthly basis. Scotland is used as a case study area. The model uses potential soil moisture deficit, estimated using broad scale (40 x 40 km) climate patterns, in conjunction with meteorological station measurements to obtain finer scale values of climatic soil moisture deficit. Point estimates of soil available water are obtained for soil characteristics using appropriate pedotransfer functions, and geostatistical techniques are used to upscale the results and interpolate to a 1-km grid. Known heterogeneity in soil physical characteristics is used to provide local corrections to the potential soil moisture deficit, estimated using the climatic variables above. Temporal profiles of monthly water content are modelled for each 1-km location and classified into six classes using unsupervised cluster analysis. The spatial distribution of these classes reflects regional variations in the availability of moisture and energy, on which finer-grained topographic patterns are superimposed. In the case study, the broad scale spatial heterogeneity of heathlands and grasslands on mineral soils in Scotland is shown to be strongly related to the soil moisture classification. The results can be used in studies investigating the patterns of distribution of communities at the landscape and regional scale.://000176014400003 ISI Document Delivery No.: 559FF Times Cited: 2 Cited Reference Count: 40 Cited References: ARMSTRONG HM, 1997, J APPL ECOL, V34, P166 BARDGETT RD, 1995, HEATHS MOORLAND CULT BARON JS, 1998, ECOL APPL, V8, P1037 BIBBY JS, 1982, LAND CAPABILITY CLAS BRIONES MJI, 1997, APPL SOIL ECOL, V6, P117 CHERTOV OG, 1997, ECOL MODEL, V94, P177 DEUTSCH CV, 1992, GSLIB GEOSTATISTICAL EDWARDS CA, 1996, BIOL ECOLOGY EARTHWO FIELD M, 1983, AGR WATER MANAGE, V6, P297 GOOVAERTS P, 1997, GEOSTATISTICS NATURA HAXELTINE A, 1996, J VEG SCI, V7, P651 HEUVELINK GBM, 1999, GEODERMA, V89, P47 HODKINSON ID, 1999, GLOB CHANGE BIOL, V5, P359 ISAAKS EH, 1989, INTRO APPL GEOSTATIS IVERSON LR, 1997, LANDSCAPE ECOL, V12, P331 JARVIS RA, 1984, SOIL SURVEY ENGLAND, V10 KABAT P, 1997, J HYDROL, V190, P363 LANCE AN, 1987, AGR CONSERVATION HIL LEIROS MC, 1999, SOIL BIOL BIOCHEM, V31, P227 LI J, 1999, J HYDROL, V220, P86 LILLY A, 1994, GEOFORUM, V25, P371 MACDONALD AM, 1994, ENVIRON POLLUT, V83, P245 MATTHEWS KB, 1994, CLIMATIC CHANGE, V28, P273 MORRIS SJ, 1998, LANDSCAPE ECOL, V13, P215 NEAVE HM, 1996, FOREST ECOL MANAG, V85, P197 NEAVE HM, 1998, FOREST ECOL MANAG, V106, P259 PENMAN HL, 1948, P ROY SOC LOND A MAT, V193, P120 RODRIGO A, 1997, ECOL MODEL, V102, P325 SALESKA SR, 1999, GLOB CHANGE BIOL, V5, P125 SELLERS PJ, 1997, J HYDROL, V190, P269 STEPHENSON NL, 1998, J BIOGEOGR, V25, P855 STRONG DT, 1998, AUST J SOIL RES, V36, P429 THOMPSON DBA, 1995, HLTH MOORLAND CULTUR THORNTHWAITE CW, 1948, GEOGR REV, V38, P55 VYAS AD, 1985, INT J REMOTE SENS, V6, P1153 WALESSMITH BG, 1971, METEOROLOGICAL SYSTE WEISHAMPEL JF, 1998, LANDSCAPE ECOLOGY, V14, P121 WHITTAKER RH, 1967, BIOL REV, V42, P207 WHITTAKER RH, 1978, ORDINATION PLANT COM, P7 YOKE KA, 1996, ENVIRON MONIT ASSESS, V39, P323 0921-2973 Landsc. Ecol.ISI:000176014400003MLURI, Land Use Change Programme, Aberdeen AB15 8QH, Scotland. Birnie, RV, MLURI, Land Use Change Programme, Aberdeen AB15 8QH, Scotland. rbirnie@macaulay.ac.ukEnglishj|7!Gimona, A. Messager, P. Occhi, M.2009uCORINE-based landscape indices weakly correlate with plant species richness in a northern European landscape transect53-64Landscape Ecology241distribution atlas indicators mars land cover flora pattern indexes agricultural landscapes ecological processes thematic resolution changing scale regional-scale metrics regression diversity forestJanWe present the results of one of the few available tests of how CORINE (CLC2000) is likely to perform as a basis for the calculation of landscape indices, for environmental monitoring over large areas. This paper investigates to what extent landscape structural indices based on this widely used European land cover database can be used to predict plant species richness in a 2,000 km(2) transect in the northeast of Scotland. We investigate both statistical and map resolution issues by comparing the performance of CORINE-based common landscape indices with the same indices derived from a much more detailed geographic data set. In our case study, only shape-related indices show correlation with species richness, but effect size, important for monitoring, is small. The results highlight the area-specific and map specific nature of the performance of landscape indices for protecting plant diversity.://000262506000005-395EI Times Cited:0 Cited References Count:79 0921-2973ISI:000262506000005Gimona, A Macaulay Inst, Aberdeen AB15 8QH, Scotland Univ Milan, Dipartimento Prod Vegetale, I-20133 Milan, Italy Macaulay Inst, Aberdeen AB15 8QH, ScotlandDoi 10.1007/S10980-008-9279-7English }?Gimona, A. van der Horst, D.2007dMapping hotspots of multiple landscape functions: a case study on farmland afforestation in Scotland 1255-1264Landscape Ecology228Oct://000248941900011 0921-2973ISI:000248941900011 }?Girvetz, E. H. Greco, S. E.2007gHow to define a patch: a spatial model for hierarchically delineating organism-specific habitat patches 1131-1142Landscape Ecology228Oct://000248941900002 0921-2973ISI:000248941900002a|? !Girvetz, Evan H. Greco, Steven E.2009Multi-scale predictive habitat suitability modeling based on hierarchically delineated patches: an example for yellow-billed cuckoos nesting in riparian forests, California, USA 1315-1329Landscape Ecology2410The discipline of landscape ecology recognizes the importance of measuring habitat suitability variables at spatial scales relevant to specific organisms. This paper uses a novel multi-scale hierarchical patch delineation method, PatchMorph, to measure landscape patch characteristics at two distinct spatial scales and statistically relate them to the presence of state-listed endangered yellow-billed cuckoos (Coccyzus americanus occidentalis) nesting in forest patches along the Sacramento River, California, USA. The landscape patch characteristics calculated were: patch thickness, area of cottonwood forest, area of riparian scrub, area of other mixed riparian forest, and total patch area. A third, regional spatial variable, delineating the north and south portions of study area was also analyzed for the effect of regional processes. Using field surveys, the landscape characteristics were related to patch occupancy by yellow-billed cuckoos. The area of cottonwood forest measured at the finest spatial scale of patches was found to be the most important factor determining yellow-billed cuckoo presence in the forest patches, while no patch characteristics at the larger scale of habitat patches were important. The regional spatial variable was important in two of the three analysis techniques. Model validation using an independent data set of surveys (conducted 1987-1990) found 76-82% model accuracy for all the statistical techniques used. Our results show that the spatial scale at which habitat characteristics are measured influences the suitability of forest patches. This multi-scale patch and model selection approach to habitat suitability analysis can readily be generalized for use with other organisms and systems.%://BIOSIS:PREV201000014107Times Cited: 0 0921-2973BIOSIS:PREV201000014107:10.1007/s10980-009-9384-2|?'Gledhill, D. G. James, P. Davies, D. H.2008OPond density as a determinant of aquatic species richness in an urban landscape 1219-1230Landscape Ecology2310Green spaces within urban areas provide services and benefits to human populations and habitat for a variety of species. Freshwater, in the form of rivers, canals, lakes, reservoirs and ponds, is an important component of urban greenspaces. This paper focuses on ponds; and specifically ponds within urban areas. This work is timely as during 2008 ponds were designated, in the UK, as habitats of national conservation importance. Yet, while farmland ponds have received considerable attention, there has been little work on the ecology and landscape ecology of urban ponds. Ecological data was collected from 37 ponds in the Borough of Halton (northwest England) over a period of 2 years (2005-2006). The median species richness in these ponds was 28 invertebrate species and 10 macrophyte species. A highly significant correlation was observed between pond density and species richness. The relationship between the richness of different taxa varied according to scale; becoming more significant within pond clusters than within a single pond. These findings have significance for those involved in planning and managing urban environments, further strengthening the need for functional ecological connectivity in urban areas. With pressure to increase infill development, and thus raise housing density, a greater understanding of the affect of urban design on pond ecology will be of importance to urban planners and ecologists alike.!://WOS:000261790600007Times Cited: 0 0921-2973WOS:00026179060000710.1007/s10980-008-9292-x<7)Glenn, S. M. Collins, S. L. Gibson, D. J.1992YDisturbances in tallgrass prairie - Local and regional effects on community heterogeneity243-251Landscape Ecology74RHIERARCHY; SCALE; DISTURBANCE; HETEROGENEITY; TALLGRASS PRAIRIE; PLANT COMMUNITIESArticleDecCommunity heterogeneity in tallgrass prairie was analyzed at regional and local levels to assess the effects of disturbances on community structure at different spatial scales. The sites were part of NASA's First ISLSCP Field Experiment (FIFE) in Kansas, and were located on grassland treatments that were undisturbed, and burned-only on Konze Prairie Research Natural Area, and grazed-only and grazed + burned on adjacent ranch land. Sites in grazed-only or grazed + burned treatments were less similar to each other, on a regional scale (15 x 15 km), than were burned-only or undisturbed sites. Grazing reduced the cover of dominant species, making space available for the establishment of immigrants from the region. Each site was different because of establishment by different species from the large regional species pool. At the local scale (0.1 ha), the most homogeneous treatments were those that were most heterogeneous at the regional scale. Undisturbed treatments at the local scale were the most heterogeneous compared to sites under other treatments. Therefore, regional responses to disturbances were more variable than local responses, and were not predictable from within-site analyses.://A1992KD83100002 IISI Document Delivery No.: KD831 Times Cited: 19 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1992KD83100002^GLENN, SM, UNIV OKLAHOMA,OKLAHOMA BIOL SURVEY,OKLAHOMA NAT HERITAGE INVENTORY,NORMAN,OK 73019.English}?4Gobster, P. H. Nassauer, J. I. Daniel, T. C. Fry, G.2007CThe shared landscape: what does aesthetics have to do with ecology?959-972Landscape Ecology227Aug://000248381900001 0921-2973ISI:000248381900001}?Godefroid, S. Koedam, N.2007XUrban plant species patterns are highly driven by density and function of built-up areas 1227-1239Landscape Ecology228Oct://000248941900009 0921-2973ISI:000248941900009?9 Golley, F. B.1987Introducing Landscape Ecology1-3Landscape Ecology11*Landscape ecology, Journal, Space and time?: Golley, F. B.1988/Future Directions in Landscape Ecology Research191-192Landscape Ecology14b?; Golley, F.B.1988Passing a milestone1-2Landscape Ecology21[?R Golley, F. B.1988Editor's comment123-124Landscape Ecology13?< Golley, F. B.1989-Landscape Ecology and Biological Conservation201-202Landscape Ecology24Landscape ecology, ConservationW?T Golley, F. B.1989A proper scale71-72Landscape Ecology22y?UGolley, F. B. 1989-International dimensions of landscape ecology137-138Landscape Ecology23d?W Golley, F. B.1989Progress in landscape ecology1-2Landscape Ecology31[?# Golley, F. B.1990Love of the land81-82Landscape Ecology42/3n?( Golley, F. B.1990#Inventing wheels - Editor's comment195-196Landscape Ecology44<7 Golley, F. B.1995Reaching a landmark3-4Landscape Ecology101Editorial MaterialFeb://A1995QL68700001 HISI Document Delivery No.: QL687 Times Cited: 3 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1995QL68700001English$<7i Golley, F. B.1996A state of transition321-323Landscape Ecology116Editorial MaterialDec://A1996VY82900002 HISI Document Delivery No.: VY829 Times Cited: 2 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1996VY82900002English}?Gonzales, E. K. Gergel, S. E.2007STesting assumptions of cost surface analysis-a tool for invasive species management 1155-1168Landscape Ecology228Oct://000248941900004 0921-2973ISI:000248941900004 <7#Gonzalez, J. Palahi, M. Pukkala, T.2005kIntegrating fire risk considerations in forest management planning in Spain - a landscape level perspective957-970Landscape Ecology208Catalonia; heuristics; spatial optimization; landscape structure PINUS-SYLVESTRIS L.; NORTHEAST SPAIN; YIELD MODEL; GROWTH; ECOSYSTEMS; CATALONIAArticleDecIt is reasonable to assume that there is a relationship between the spatial distribution of forest fuels and fire hazards. Therefore, if fire risk is to be included into numerical forest planning, the spatial distribution of risky and non-risky forest stands should be taken into account. The present study combines a stand-level fire risk model and landscape level optimization to solve forest planning problems in which the fire risk plays an important role. The key point of the method was to calculate forest level fire resistance metrics from stand level indices and use these metrics as objective variables in numerical optimization. This study shows that maximizing different landscape metrics produces very different landscape configurations with respect to the spatial arrangement of resistant and risky stands. The landscapes obtained by maximizing different metrics were tested with a fire spread simulator. These tests suggested that the mean fire resistance of the landscape, which is a non-spatial metric, is the most important factor affecting the burned area. However, spatial landscape metrics that decrease the continuity of fire resistance in the landscape can significantly improve the fire resistance of the landscape when used as additional objective variables.://000233036400005 ISI Document Delivery No.: 980RR Times Cited: 0 Cited Reference Count: 25 Cited References: *ICONA, 1993, 2 INV FOR NAC 1986 1 AGEE JK, 2000, FOREST ECOL MANAG, V127, P55 BORGES JG, 2002, MULTI OBJECTIVE FORE, P119 FINNEY MA, 2001, FOREST SCI, V47, P219 FINNEY MA, 2003, USDA FOR SERV P, P353 GLOVER F, 1993, MODERN HEURISTIC TEC, P70 GONZALEZ JR, 2005, UNPUB FIRE PROBABILI HEINONEN T, 2004, SILVA FENN, V38, P319 HIRSCH K, 2001, FOREST CHRON, V77, P357 KEELEY JE, 2001, CONSERV BIOL, V15, P1561 LOEHLE C, 2004, FOREST ECOL MANAG, V198, P261 MCGARIGAL K, 1995, 351 USDA PNW FOR SER MINNICH RA, 2001, CONSERV BIOL, V15, P1549 PALAHI M, 2002, THESIS U JOENSUU JOE, P58 PALAHI M, 2003, ANN FOR SCI, V60, P105 PALAHI M, 2004, INVESTIGACIONES AGRA, V13, P527 PUKKALA T, 1993, SCAND J FOR RES, V8, P560 PUKKALA T, 2002, MULTIOBJECTIVE FORES, P1 PUKKALA T, 2003, MONTE CALCULATION PL REEVES CR, 1993, MODERN HEURISTIC TEC SCHOENBERG FP, 2003, INT J WILDLAND FIRE, V12, P1 TABARA D, 1996, PERCEPCIO PROBLEMES TRASOBARES A, 2004, ANN FOREST SCI, V61, P9 TRASOBARES A, 2004, FOREST ECOL MANAG, V203, P49 VELEZ R, 2002, EFI P, V45, P35 0921-2973 Landsc. Ecol.ISI:000233036400005Forest Technol Ctr Catalonia, Solsona 25280, Spain. Univ Joensuu, Fac Forestry, FIN-80101 Joensuu, Finland. Gonzalez, J, Forest Technol Ctr Catalonia, Pujada Seminari S-N, Solsona 25280, Spain. jr.gongalez@ctfc.esEnglish<7cGonzalez-Abraham, C. E. Radeloff, V. C. Hammer, R. B. Hawbaker, T. J. Stewart, S. I. Clayton, M. K.2007HBuilding patterns and landscape fragmentation in northern Wisconsin, USA217-230Landscape Ecology222disturbance zone; landscape fragmentation; building density; spatial pattern of buildings; landscape legacies; rural sprawl; Wisconsin RESIDENTIAL DEVELOPMENT; LAKESHORE DEVELOPMENT; UNITED-STATES; PINE-BARRENS; LAND-COVER; FOREST; BIRDS; HABITAT; CONSEQUENCES; DISTURBANCEArticleFebHousing growth is prevalent in rural areas in the United States and landscape fragmentation is one of its many effects. Since the 1930s, rural sprawl has been increasing in areas rich in recreational amenities. The question is how housing growth has affected landscape fragmentation. We thus tested three hypotheses relating land cover and land ownership to density and spatial pattern of buildings, and examined whether building density or spatial pattern of buildings was a better predictor for landscape fragmentation. Housing locations were mapped from 117 1:24,000-scale USGS topographic maps across northern Wisconsin. Patch-level landscape metrics were calculated on the terrestrial area remaining after applying 50, 100 and 250 m disturbance zones around each building. Our results showed that building density and the spatial pattern of buildings were affected mostly by lake area, public land ownership, and the abundance of coniferous forest, agricultural land, and grassland. A full 40% of the houses were within 100 m of lakeshores. The clustering of buildings within 100 m of lakeshores limited fragmentation farther away. In contrast, agricultural and grassland areas were correlated with higher building density, higher fragmentation, and more dispersed building pattern possible legacies of agricultural settlement patterns. Understanding which factors influence building density and fragmentation is useful for landscape level planning and ecosystem management in northern Wisconsin and areas that share similar social and environmental constraints.://000243823900006 ISI Document Delivery No.: 130UG Times Cited: 0 Cited Reference Count: 58 Cited References: 1996, USGS NATL MAPPING PR *USFS, 2001, CHEQ NIC NAT FOR *WI DNR, 1998, WISCLAND LAND COV WL ANDERSON JR, 1976, 964 US DEP INT GEOL ANDREN H, 1994, OIKOS, V71, P355 ARENDT R, 1997, J AM PLANN ASSOC, V63, P137 BAWDEN DL, 1977, 4 PAPERS FARM FAMILY BLACK JD, 1925, DEP B USDA, V1295 BRITTINGHAM MC, 1983, BIOSCIENCE, V33, P31 BROWN DG, 2003, LANDSCAPE ECOL, V18, P777 CARSTENSEN VR, 1958, FARMS FOREST EVOLUTI CHATTERJEE S, 2000, REGRESSION ANAL EXAM CHRISTENSEN DL, 1996, ECOL APPL, V6, P1143 COLEMAN JS, 1993, WILDLIFE SOC B, V21, P381 DWYER JF, 2004, LANDSCAPE URBAN PLAN, V69, P153 FAHRIG L, 1997, J WILDLIFE MANAGE, V61, P603 FLADER SL, 1983, GREAT LAKES FOREST FORMAN RTT, 1986, LANDSCAPE ECOLOGY FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FRIES RF, 1951, EMPIRE PINE STORY LU FRIESEN LE, 1995, CONSERV BIOL, V9, P1408 FUGUITT GV, 1985, ANNU REV SOCIOL, V11, P259 FUGUITT GV, 1990, DEMOGRAPHY, V27, P589 GARBER SD, 1995, ECOL APPL, V5, P1151 GOBSTER PH, 2000, J FOREST, V98, P9 GOBSTER PH, 2004, LANDSCAPE URBAN PLAN, V69, P165 GOODMAN RB, 1932, FOREST LAND USE WISC HAMMER RB, 2004, LANDSCAPE URBAN PLAN, V69, P183 HANSEN AJ, 2002, BIOSCIENCE, V52, P151 HAWBAKER TJ, 2005, LANDSCAPE ECOL, V20, P609 HEIMLICH RE, 2001, 803 USDA EC RES SERV HOCKIN D, 1992, J ENVIRON MANAGE, V36, P253 HOSTETLER M, 1999, LANDSCAPE URBAN PLAN, V45, P15 KAREIVA P, 1990, PHILOS T ROY SOC B, V330, P175 KLUZA DA, 2000, ANIM CONSERV 1, V3, P15 LINDSAY AR, 2002, BIOL CONSERV, V107, P1 LONG L, 1997, ENVIRON PLANN A, V29, P1355 MCGRANAHAN DA, 1999, 781 USDA AGR EC EC R MILLER JR, 2000, LANDSCAPE URBAN PLAN, V50, P227 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 MURPHY RE, 1931, T WISC ACAD SCI, V26, P96 NAIMAN RJ, 1996, LANDSCAPE ECOL, V11, P193 NASSAUER JI, 1995, LANDSCAPE ECOL, V10, P229 RADELOFF VC, 1999, CAN J FOREST RES, V29, P1649 RADELOFF VC, 2001, FOREST SCI, V47, P229 RADELOFF VC, 2005, ECOL APPL, V15, P799 REESE HM, 2002, REMOTE SENS ENVIRON, V82, P224 RODGERS JA, 1995, CONSERV BIOL, V9, P89 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SCHNAIBERG J, 2002, ENVIRON MANAGE, V30, P24 SCHULTE LA, 2002, CAN J FOREST RES, V32, P1616 STEARNS FW, 1997, NC189 GEN, P1 THEOBALD DM, 1997, LANDSCAPE URBAN PLAN, V39, P25 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 2001, LANDSCAPE ECOLOGY TH UPTON G, 1985, SPATIAL DATA ANAL EX VOS CC, 2000, AM NAT, V183, P24 WOODFORD JE, 2003, BIOL CONSERV, V110, P277 0921-2973 Landsc. Ecol.ISI:000243823900006_Univ Wisconsin, Dept Forest Ecol & Management, Madison, WI 53706 USA. Univ Wisconsin, Dept Rural Sociol, Madison, WI 53706 USA. US Forest Serv, N Cent Res Stn, Evanston, IL 60201 USA. Univ Wisconsin, Dept Stat, Madison, WI 53706 USA. Radeloff, VC, Univ Wisconsin, Dept Forest Ecol & Management, 1630 Linden Dr, Madison, WI 53706 USA. radeloff@wisc.eduEnglish)ڽ7 nGonzález-Moreno, Pablo Pino, Joan Carreras, David Basnou, Corina Fernández-Rebollar, Iván Vilà, Montserrat2013XQuantifying the landscape influence on plant invasions in Mediterranean coastal habitats891-903Landscape Ecology285Springer NetherlandsNon-native plants Level of invasion Land-use and land-cover change Landscape configuration Spatial heterogeneity Species richness Urban area 2013/05/01+http://dx.doi.org/10.1007/s10980-013-9857-1 0921-2973Landscape Ecol10.1007/s10980-013-9857-1English~?V1Gonzalez-Varo, J. P. Lopez-Bao, J. V. Guitian, J.2008Presence and abundance of the Eurasian nuthatch Sitta europaea in relation to the size, isolation and the intensity of management of chestnut woodlands in the NW Iberian Peninsula79-89Landscape Ecology231Throughout most of the north-west Iberian Peninsula, chestnut (Castanea sativa) woods are the principal deciduous woodland, reflecting historical and ongoing exploitation of indigenous forests. These are traditionally managed woodlands with a patchy distribution. Eurasian nuthatches (Sitta europaea) inhabit mature deciduous woods, show high site fidelity, and are almost exclusively found in chestnut woods in the study area. We studied the presence and abundance of nuthatch breeding pairs over two consecutive years, in relation to the size, degree of isolation and intensity of management of 25 chestnut woods in NW Spain. Degree of isolation was assessed in view of the presence of other woodland within a 1-km band surrounding the study wood. Wood size was the only variable that significantly predicted the presence of breeding pairs (in at least one year, R-2 = 0.69; in both years, R-2 = 0.50). The number of pairs was strongly predicted by wood size, isolation and management (R-2 = 0.70 in 2004; R-2 = 0.84 in 2005); interestingly, more isolated woods had more breeding pairs. Breeding density was likewise significantly or near-significantly (P = 0.1) higher in small isolated woods, which is possibly attributable to lower juvenile dispersal in lightly forested areas and/or to lower predator density in smaller and more isolated patches. Breeding density was higher (though not significantly so) in more heavily managed woods, possibly due to the presence of larger chestnut crops and larger trees (with higher nuthatch prey abundance). Our findings highlight the complexity of the relationships between the patch properties and the three studied levels (presence, number and density of pairs), and also the importance of traditionally managed woodlands for the conservation of forest birds."://WOS:000251796100009 Times Cited: 0WOS:00025179610000910.1007/s10980-007-9166-7<7aGoodwin, B. J.2003>Is landscape connectivity a dependent or independent variable?687-699Landscape Ecology187Yempirical vs. modeling landscape connectivity landscape structure measures of connectivity movement behaviour research needs HEDGEROW NETWORK LANDSCAPE HABITAT PATCH CONNECTIVITY VOLE MICROTUS-OECONOMUS SMALL MAMMALS HETEROGENEOUS LANDSCAPES ABAX-PARALLELEPIPEDUS METAPOPULATION MODELS FRAGMENTED LANDSCAPE POPULATION-DYNAMICS FRACTAL LANDSCAPESReviewWith growing interest in landscape connectivity, it is timely to ask what research has been done and what remains to be done. I surveyed papers investigating landscape connectivity from 1985 to 2000. From these papers, I determined if connectivity had been treated as an independent or dependent variable, what connectivity metrics were used, and if the study took an empirical or modeling approach to studying connectivity. Most studies treated connectivity as an independent variable, despite how little we know about how landscape structure and organism movement behaviour interact to determine landscape connectivity. Structural measures of connectivity were more common than functional measures, particularly if connectivity was treated as an independent variable. Though there was a good balance between modeling and empirical approaches overall - studies dealing with connectivity as a dependent, functional variable were mainly modeling studies. Based on the research achieved thus far, future landscape connectivity research should focus on: ( 1 ) elucidating the relationship between landscape structure, organism movement behaviour, and landscape connectivity ( e. g., treating connectivity as a dependent variable ), ( 2 ) determining the relationships between different measures of connectivity, particularly structural and functional measures, and ( 3 ) empirically testing model predictions regarding landscape connectivity.://000186639000005 DISI Document Delivery No.: 744NR Times Cited: 14 Cited Reference Count: 112 Cited References: ADLER FR, 1994, THEOR POPUL BIOL, V45, P41 ANDREASSEN HP, 1996, J APPL ECOL, V33, P555 ANDREASSEN HP, 1996, J APPL ECOL, V33, P63 ANDREASSEN HP, 1998, ECOLOGY, V79, P1223 ANDREASSEN HP, 2001, ECOLOGY, V82, P2911 ARNOLD GW, 1993, BIOL CONSERV, V64, P219 AULT TR, 1998, ECOL MONOGR, V68, P25 BAARS MA, 1979, OECOLOGIA, V44, P125 BERGGREN A, 2001, J ANIM ECOL, V70, P663 BJORNSTAD ON, 1998, J ANIM ECOL, V67, P127 BROOKER L, 1999, CONSERV ECOL, V3 BROWN JH, 1977, ECOLOGY, V58, P445 BROWNE DR, 1999, LANDSCAPE ECOLOGY, V14, P53 BUNN AG, 2000, J ENVIRON MANAGE, V59, P265 BUREL F, 1989, LANDSCAPE ECOLOGY, V2, P215 CAIN DH, 1997, LANDSCAPE ECOL, V12, P199 CHARRIER S, 1997, AGR ECOSYST ENVIRON, V61, P133 CLERGEAU P, 1997, LANDSCAPE URBAN PLAN, V38, P37 COLLINGE SK, 1998, OIKOS, V82, P66 COLLINGE SK, 2000, ECOLOGY, V81, P2211 COLLINS RJ, 1997, LANDSCAPE ECOL, V12, P63 DANIELSON BJ, 2000, LANDSCAPE ECOL, V15, P323 DEMERS MN, 1995, CONSERV BIOL, V9, P1159 DOAK DF, 1992, THEOR POPUL BIOL, V41, P315 FAHRIG L, 1985, ECOLOGY, V66, P1762 FARMER AH, 1997, CONDOR, V99, P698 FITZGIBBON CD, 1997, J APPL ECOL, V34, P530 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY GARDNER RH, 1989, LANDSCAPE ECOL, V3, P217 GONZALEZ A, 1998, SCIENCE, V281, P2045 GOODWIN BJ, 2002, CAN J ZOOL, V80, P25 GOODWIN BJ, 2002, OIKOS, V99, P552 GRASHOFBOKDAM C, 1997, J VEG SCI, V8, P21 GREEN DG, 1994, PACIFIC CONSERVATION, V1, P194 GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HADDAD N, 2000, CONSERV BIOL, V14, P738 HANSKI I, 1997, METAPOPULATION DYNAM HANSKI I, 1999, OIKOS, V87, P209 HANSSON L, 1991, BIOL J LINN SOC, V42, P89 HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HENEIN K, 1990, LANDSCAPE ECOL, V4, P157 HENEIN K, 1998, OIKOS, V81, P168 HERZIG AL, 1995, ECOLOGY, V76, P2044 HESS G, 1996, ECOLOGY, V77, P1617 HESS GR, 1996, AM NAT, V148, P226 HJERMANN DO, 1996, J ANIM ECOL, V65, P768 HOBBS RJ, 1992, TRENDS ECOL EVOL, V7, P389 HOF J, 1996, ECOL MODEL, V88, P143 HOF J, 1997, ECOL APPL, V7, P1160 HUTCHINSON TF, 1998, AM MIDL NAT, V139, P383 JOHNSON AR, 1992, LANDSCAPE ECOL, V7, P63 KEITT TH, 1997, CONSERV ECOL, V1 KOZAKIEWICZ M, 1995, MOSAIC LANDSCAPES EC, P136 LAAN R, 1990, BIOL CONSERV, V54, P251 LAVOREL S, 1995, LANDSCAPE ECOL, V10, P277 LECOEUR D, 1997, LANDSCAPE URBAN PLAN, V37, P57 LECOMTE J, 1996, ACTA OECOL, V17, P585 LEFKOVITCH LP, 1985, ECOL MODEL, V30, P297 LIRO A, 1987, OECOLOGIA, V74, P438 MATTER SF, 1996, OECOLOGIA, V105, P447 MAUREMOOTO JR, 1995, AGR ECOSYST ENVIRON, V52, P141 MERRIAM G, 1984, P 1 INT SEM METH LAN, V1, P5 MERRIAM G, 1991, NATURE CONSERVATION, V2, P406 MERRIAM G, 1994, LANDSCAPE APPROACHES, P96 METZGER JP, 1997, ACTA OECOL, V18, P1 METZGER JP, 1997, LANDSCAPE URBAN PLAN, V37, P29 MILLS LS, 1995, CONSERV BIOL, V9, P395 PAILLAT G, 1996, ACTA OECOL, V17, P553 PETIT S, 1998, AGR ECOSYST ENVIRON, V69, P243 PETIT S, 1998, CR ACAD SCI III-VIE, V321, P55 PITHER J, 1998, OIKOS, V83, P166 PLOTNICK RE, 1993, LANDSCAPE ECOL, V8, P201 POTTER MA, 1990, NEW ZEAL J ECOL, V14, P17 REDDINGIUS J, 1970, OECOLOGIA, V5, P240 REUNANEN P, 2000, CONSERV BIOL, V14, P218 RHAINDS M, 1997, CAN ENTOMOL, V129, P927 RIJNSDORP AD, 1980, OECOLOGIA BERLIN, V45, P274 ROOT KV, 1998, ECOL APPL, V8, P854 ROSENBERG DK, 1998, CAN J ZOOL, V76, P117 RUCKELSHAUS M, 1997, CONSERV BIOL, V11, P1298 SCHIEGG K, 2000, ECOSCIENCE, V7, P290 SCHIPPERS P, 1996, ECOGRAPHY, V19, P97 SCHMIEGELOW FKA, 1997, ECOLOGY, V78, P1914 SCHULTZ CB, 2001, ECOLOGY, V82, P1879 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SPETICH MA, 1997, NAT AREA J, V17, P118 STEFFANDEWENTER I, 1999, OECOLOGIA, V121, P432 SWART J, 1996, ECOL MODEL, V93, P57 SZACKI J, 1991, LANDSCAPE ECOL, V5, P219 TAYLOR PD, 1993, OIKOS, V68, P571 TIEBOUT HM, 1997, CONSERV BIOL, V11, P620 TISCHENDORF L, 1997, ECOL MODEL, V103, P33 TISCHENDORF L, 2000, LANDSCAPE ECOL, V15, P633 TISCHENDORF L, 2000, OIKOS, V90, P7 TISCHENDORF L, 2001, LANDSCAPE ECOL, V16, P235 TRAVIS JMJ, 2000, ECOL LETT, V3, P163 TURCHIN P, 1991, ENVIRON ENTOMOL, V20, P955 TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 VANLANGEVELDE F, 2000, ECOGRAPHY, V23, P614 WALLIN H, 1988, OECOLOGIA, V77, P39 WEGNER JF, 1979, J APPL ECOL, V16, P349 WIENS JA, 1993, OIKOS, V66, P369 WIENS JA, 1997, OIKOS, V78, P257 WITH KA, 1995, ECOLOGY, V76, P2446 WITH KA, 1997, OIKOS, V78, P151 WITH KA, 1999, ECOLOGY, V80, P1340 WITH KA, 1999, LANDSCAPE ECOL, V14, P73 YEOMANS SR, 1995, ANIM BEHAV, V49, P977 ZABEL J, 1998, OECOLOGIA, V116, P419 ZOLLNER PA, 1997, OIKOS, V80, P51 0921-2973 Landsc. Ecol.ISI:000186639000005pInst Ecosyst Studies, Millbrook, NY 12545 USA. Goodwin, BJ, Univ N Dakota, Dept Biol, Grand Forks, ND 58202 USA.English?5j$R. Goossens E. D’Haluin G. Larnoe1991Satellite image interpretation (SPOT) for the survey of the ecological infrastructure in a small scaled landscape (Kempenland, Belgium)175-182Landscape Ecology53ISPOT, edge enhancement, ecological infrastructure, field pattern, BelgiumrThis paper deals with the problem of the detectability of the field pattern and the associated linear elements in the Kempenland (Belgium) using SPOT multispectral imagery. The SPOT images are edge-enhanced in order to put the ecological infrastructure in a clearer image display. The detectability is investigated in relation to the size and the shape of the land blocks. The influence on the detectability on SPOT images of the kinds of linear elements, bordering the land blocks, is investigated as well. The use of edge-enhanced SPOT images for (ecological) network analysis (connectivity and circuitry) is also discussed.|? #Goslee, Sarah C. Sanderson, Matt A.2010rLandscape context and plant community composition in grazed agricultural systems of the Northeastern United States 1029-1039Landscape Ecology257AugTemperate humid grazing lands are an important component of the landscape of the northeastern United States, as well as of the economy of this region. Unlike their European counterparts, little is known about the basic ecology of managed grasslands in this region. During an 8-year survey of 28 farms across the northeastern United States, we sampled the vegetation on 95 grazed plots, identifying 310 plant species, and collected data on topography, climate and soils. Landscape structure data were obtained from the National Land Cover Data (NLCD) 2001 for six radii (250-2,000 m) surrounding each site. The 500-m radius was most strongly related to plant community composition. Planned species composition was related only to site factors, while associated species were influenced by both site factors and landscape pattern. Species richness was unrelated to landscape structure for either group. Differing management effects on planned and associated species may explain the variation in their responses. Managed grasslands are a critical part of the interconnected landscape of the northeastern United States, and both affect and are affected by their surroundings.!://WOS:000279592100004Times Cited: 1 0921-2973WOS:00027959210000410.1007/s10980-010-9477-y3|?M !Gossner, Martin M. Mueller, Joerg2011The influence of species traits and q-metrics on scale-specific beta-diversity components of arthropod communities of temperate forests411-424Landscape Ecology263MarProtection of biodiversity and ecosystem functions requires a better understanding of spatial diversity. Here we studied diversity patterns of true bugs and saproxylic beetles, sampled in 28 forest stands of southern Germany, using a hierarchical nested design of five increasingly broader spatial levels: trap location, stratum, forest stand, forest site, and ecoregion. We predicted that: (1) for large body-sized species (as a surrogate for highly mobile species) and host generalist species (low host specificity), the proportion of beta-diversity decreases from small to large spatial scales; and (2) the differences between trait-based functional guilds in the proportion of beta-diversity increase with increasing weighting of more-abundant species. Our results indicated that the ecoregion level is the most important diversity scale for both taxa and among functional guilds sampled, followed by the forest stand level. Specialized species were more strongly affected on the ecoregion level than generalist species. Differences in the proportion of beta-diversity between functional guilds increased with increasing weighting of abundant species. The beta-diversity patterns based on body size and host specificity were similar for true bugs, but partly contrasting for saproxylic beetles. Our results suggest that (1) future conservation schemes should focus on establishing new conservation sites in new ecoregions, rather than on enlarging existing protected areas; (2) host specificity might be a more meaningful trait than body size to be considered in biodiversity studies; and (3) common conservation approaches restricted to only large, conspicuous, but rare species might result in a mismatch of important biodiversity scales.!://WOS:000288808100009Times Cited: 1 0921-2973WOS:00028880810000910.1007/s10980-010-9568-9 R|7jGottschalk, T. K. Diekotter, T. Ekschmitt, K. Weinmann, B. Kuhlmann, F. Purtauf, T. Dauber, J. Wolters, V.2007GImpact of agricultural subsidies on biodiversity at the landscape level643-656Landscape Ecology225land use scenarios faunal diversity modelling multiple spatial scales gis farmland bird populations agri-environment schemes species richness spatial autocorrelation habitat relationships scale conservation models heterogeneity communitiesMayAgricultural management is a major factor driving the change of faunal richness in anthropogenic landscapes. Thus, there is an urgent need to develop tools that allow decision-makers to understand better intended and unintended effects of agricultural policy measures on biodiversity. Here we demonstrate the potential of such a tool by combining a socio-economic model with the biodiversity model GEPARD to forecast the response of bird and carabid species richness to two scenarios of agricultural subsidies: (1) subsidies based on production levels and prices and (2) direct income support that is independent of production levels. We focussed on farmland of the Lahn-Dill area, Germany, as an example of European regions with low intensity farming. GEPARD predicts faunal richness and is based on multi-scaled resource-selection functions. Under both scenarios the area of predicted losses in species richness of birds and carabids was larger than the area of predicted gains in species richness. However, the area with predicted losses of avian richness was smaller under the direct income support scenario than under the production-based subsidy scenario, whereas the area with predicted losses of carabid species richness was smaller under the production-based subsidy scenario than under the direct income support. Yet locally, richness gains of up to four species were predicted for carabids under both scenarios. We conclude that the sometimes contrasting and heterogeneous responses of birds and carabids at different localities suggest the need for spatially targeted subsidy schemes. With the help of the GIS-based approach presented in this study, prediction maps on potential changes in local and regional species richness can be easily generated.://000246111800002-162TG Times Cited:2 Cited References Count:76 0921-2973ISI:000246111800002Gottschalk, TK Univ Giessen, IFZ Dept Anim Ecol, Heinrich Buff Ring 26-32, D-35392 Giessen, Germany Univ Giessen, IFZ Dept Anim Ecol, D-35392 Giessen, Germany Univ Giessen, Inst Agr & Food Syst Management, D-35390 Giessen, GermanyDoi 10.1007/S10980-006-9060-8English<7.Graf, R. F. Bollmann, K. Suter, W. Bugmann, H.2005QThe importance of spatial scale in habitat models: capercaillie in the Swiss Alps703-717Landscape Ecology206%conservation; landscape analysis; logistic regression; multi-scale habitat model; spatial scale; Switzerland; Tetrao urogallus RESOURCE SELECTION FUNCTIONS; LOGISTIC-REGRESSION; TETRAO-UROGALLUS; BREEDING SUCCESS; SPECIES DISTRIBUTIONS; MULTIPLE SCALES; FOREST; GROUSE; CONSERVATION; LANDSCAPEArticleSepThe role of scale in ecology is widely recognized as being of vital importance for understanding ecological patterns and processes. The capercaillie (Tetrao urogallus) is a forest grouse species with large spatial requirements and highly specialized habitat preferences. Habitat models at the forest stand scale can only partly explain capercaillie occurrence, and some studies at the landscape scale have emphasized the role of large-scale effects. We hypothesized that both the ability of single variables and multivariate models to explain capercaillie occurrence would vary with the spatial scale of the analysis. To test this hypothesis, we varied the grain size of our analysis from 1 to just over 1100 hectares and built univariate and multivariate habitat suitability models for capercaillie in the Swiss Alps. The variance explained by the univariate models was found to vary among the predictors and with spatial scale. Within the multivariate models, the best single-scale model (using all predictor variables at the same scale) worked at a scale equivalent to a small annual home range. The multi-scale model, in which each predictor variable was entered at the scale at which it had performed best in the univariate model, did slightly better than the best single-scale model. Our results confirm that habitat variables should be included at different spatial scales when species-habitat relationships are investigated.://000233600700006 ISI Document Delivery No.: 988KS Times Cited: 4 Cited Reference Count: 65 Cited References: AUGUSTIN NH, 1996, J APPL ECOL, V33, P339 BAINES D, 2004, J APPL ECOL, V41, P59 BERG A, 2004, ECOGRAPHY, V27, P83 BISSONETTE JA, 1997, WILDLIFE LANDSCAPE E, P3 BOYCE MS, 2002, ECOL MODEL, V157, P281 CARROLL C, 1999, CONSERV BIOL, V13, P1344 CUSHMAN SA, 2004, OIKOS, V105, P117 DELEO JM, 1993, 1 INT S UNC MOD AN I ELKIE PC, 1999, PATCH ANAL USERS MAN FIELDING AH, 1995, CONSERV BIOL, V9, P1466 FIELDING AH, 1997, ENVIRON CONSERV, V24, P38 FISCHER J, 2004, J APPL ECOL, V41, P32 FREEMARK KE, 1986, BIOL CONSERV, V36, P115 FUHLENDORF SD, 2002, LANDSCAPE ECOL, V17, P617 GIBSON LA, 2004, J APPL ECOL, V41, P213 GUISAN A, 2000, ECOL MODEL, V135, P147 HOSMER DW, 1989, APPL LOGISTIC REGRES JOHNSON CJ, 2004, J APPL ECOL, V41, P238 KEPPIE DM, 2003, WILDLIFE BIOL, V9, P385 KLAUS S, 1985, ACTA ORNITHOECOLOGIA, V1, P3 KLAUS S, 1986, AUERHUHNER KUMAR L, 1997, INT J GEOGR INF SCI, V11, P475 KURKI S, 1995, ECOGRAPHY, V18, P109 KURKI S, 2000, ECOLOGY, V81, P1985 LAWLER JJ, 2002, LANDSCAPE ECOL, V17, P233 LEVIN SA, 1992, ECOLOGY, V73, P1943 MACE RD, 1999, CONSERV BIOL, V13, P367 MACFADEN SW, 2002, FOREST SCI, V48, P243 MANLY BFJ, 2002, RESOURCE SELECTION A MCGARIGAL K, 2002, FRAG STATS SPATIAL P MENARD S, 2002, APPL LOGISTIC REGRES MLADENOFF DJ, 1998, J WILDLIFE MANAGE, V62, P1 MOLLET P, 2003, ORNITHOLOISCHE BEOBA, V100, P67 MONSERUD RA, 1992, ECOL MODEL, V62, P275 MORAN P, 1948, J ROYAL STATISTICAL, V10, P243 MOSS R, 2001, J ANIM ECOL, V70, P47 NAGELKERKE NJD, 1991, BIOMETRIKA, V78, P691 PEARCE J, 2000, ECOL MODEL, V128, P127 ROLSTAD J, 1988, CAN J ZOOL, V66, P670 ROLSTAD J, 1989, FINNISH GAME RES, V46, P43 ROTH P, 1975, ORNITHOLOGISCHE BEO, V72, P101 RUSHTON SP, 2004, J APPL ECOL, V41, P193 SACHOT S, 2003, BIOL CONSERV, V112, P373 SCHRODER B, 2000, THESIS TU BRAUNSCHWE SCHRODER B, 2002, WORKSH KOLP 2000, P201 SCHROTH KE, 1992, THESIS U MUNCHEN MUN SEGELBACHER G, 2003, WILDLIFE BIOL, V9, P267 SJOBERG K, 1996, FORESTED LANDSCAPES, P111 SMITH PA, 1994, GLOBAL ECOL BIOGEOGR, V4, P47 STEIGER P, 1994, WALDER SCHWEIZ STORCH I, 1994, BIOL CONSERV, V70, P237 STORCH I, 1995, J WILDLIFE MANAGE, V59, P392 STORCH I, 1997, WILDLIFE LANDSCAPE E, P310 STORCH I, 2000, GROUSE STATUS SURVEY STORCH I, 2000, WILDLIFE BIOL, V6, P195 STORCH I, 2000, WILDLIFE BIOL, V6, P305 STORCH I, 2002, CONSERV ECOL, V6 SUCHANT R, 2002, THESIS U FREIBURG FR THOMPSON CM, 2002, LANDSCAPE ECOL, V17, P569 WEGGE P, 1986, BEHAV ECOL SOCIOBIOL, V19, P401 WEGGE P, 1987, AUK, V104, P481 WIENS JA, 1989, FUNCT ECOL, V3, P385 ZABEL CJ, 2003, ECOL APPL, V13, P1027 ZIMMERMANN NE, 1999, J VEG SCI, V10, P469 ZIMMERMANN NE, 2001, FINAL REPORT MLP CLI 0921-2973 Landsc. Ecol.ISI:000233600700006Swiss Fed Res Inst WSL, CH-8903 Birmensdorf, Switzerland. ETH, Swiss Fed Inst Technol Zurich, Dept Environm Sci, CH-8092 Zurich, Switzerland. Graf, RF, Swiss Fed Res Inst WSL, Zurcherstr 111, CH-8903 Birmensdorf, Switzerland. roland.graf@alumni.ethz.chEnglish&}?HGraf, Roland F. Kramer-Schadt, Stephanie Fernandez, Nestor Grimm, Volker2007JWhat you see is where you go? Modeling dispersal in mountainous landscapes853-866Landscape Ecology226Jul&://BIOSIS:PREV200700463287 0921-2973BIOSIS:PREV200700463287 07 vGrashof-Bokdam, C. J. Chardon, J. P. Vos, C. C. Foppen, R. P. B. WallisDeVries, M. van der Veen, M. Meeuwsen, H. A. M.2009PThe synergistic effect of combining woodlands and green veining for biodiversity 1105-1121Landscape Ecology248SpringerUniv, Wageningen Res Ctr, Landscape Ctr N. L. A. A. Wageningen Netherlands Sovon Dutch Ctr Field Ornithol, N. L. D. G. Beek Ubbergen Netherlands Dutch Butterfly Conservat, N. L. A. M. Wageningen NetherlandsThe Netherlands Forest habitat Ecological networks Connectivity Species occurrence Regression analysis Dispersal capacity Habitat area requirements Habitat preference Landscape planningOctCombining nature reserves with small semi-natural elements (green veining) may improve the persistence of plant and animal species in fragmented landscapes. A better understanding of this synergy is essential to improve species diversity in the European Natura 2000 sites and in green veining elements. To test this hypothesis, we investigated the relationship between the occurrence of 40 forest plant and animal species in 1,000 km grid cells in the Netherlands and the spatial cohesion of the surrounding large woodlands and small woody elements. Two types of synergy were found. First, nine species were more often present if there was more cohesion of large elements; small elements enhanced this effect. Second, 11 other species were more often present when there was more cohesion of small elements; large elements enhanced this effect. Eight species showed both effects, indicating two-way synergy. The remaining 12 species preferred landscapes dominated by either large or small elements, or displayed no positive relationship whatsoever to woody elements. Species showing synergy often had a low dispersal capacity; the type of synergy seemed to be related to their habitat preference. These results imply that species diversity could be improved by integrating different policy instruments used for nature reserves and green veining. Using a zoning principle where green veins surround and connect nature reserves, the different spatial and habitat preferences of species can be secured. In this way a coherent network could become reality.://000269913600009ISI Document Delivery No.: 495RV Times Cited: 1 Cited Reference Count: 65 Grashof-Bokdam, Carla J. Chardon, J. Paul Vos, Claire C. Foppen, Ruud P. B. WallisDeVries, Michiel van der Veen, Marja Meeuwsen, Henk A. M. 0921-2973 DORDRECHT2009 Landsc. Ecol.ISI:000269913600009Landscape ecology~Grashof-Bokdam, CJ, Univ Wageningen & Res Ctr, Landscape Ctr, POB 47, NL-6700 AA Wageningen, Netherlands. carla.grashof@wur.nl10.1007/s10980-008-9274-zEnglish<7(Grashof-Bokdam, C. J. van Langevelde, F.2005YGreen veining: landscape determinants of biodiversity in European agricultural landscapes417-439Landscape Ecology204'isolation; management intensity; semi-natural landscape elements; spatial configuration; spatial structure; species-area curve FIELD BOUNDARY VEGETATION; AGRI-ENVIRONMENT SCHEMES; PLANT-SPECIES RICHNESS; LAND-USE; COMMUNITY STRUCTURE; FARMLAND BIRDS; PEAT AREAS; MANAGEMENT; DIVERSITY; HEDGEROWSArticleMayhMany semi-natural landscape elements, the so-called green veining, are disappearing from the intensively used agricultural landscapes of Europe. In order to develop or restore biodiversity in these networks, it is necessary to quantify the relation between biodiversity and amount, spatial arrangement and management intensity of green veining elements. In this review, we investigate whether biodiversity increases with the amount of green veining in an agricultural landscape following the species-area relationship, and whether a certain level of biodiversity can be reached at lower densities of green veining if green veining elements are better connected (higher spatial connectivity) or if they are managed less intensively (lower management intensity). We reviewed studies on aboveground biodiversity in green veining structures in 39 scientific papers on field and experimental studies within Europe. More of these studies focussed on management intensity than on amount or spatial configuration of green veining. Also more studies focussed on the spatial scale of individual landscape elements than on the farm or landscape scale, which may be caused by the large number of studies focussing on plant or invertebrate species. Species living at larger spatial scales, e.g. mammals and birds were not often studied at the level of green veining elements as they also use agricultural fields as part of their habitat. We could not verify the species-area relation for green veining, nor the effect of amount, spatial configuration or management intensity on this relation, because only few studies quantified the found effects and no studies were found on the effect of management intensity or spatial configuration on the species-area curve in green veining. We addressed the most important challenges for future field and model research in order to fill the identified gaps in knowledge.://000233035100005 ISI Document Delivery No.: 980RE Times Cited: 0 Cited Reference Count: 94 Cited References: *WAM, 2002, LANDSCHAP, V19, P112 ALTIERI MA, 1999, AGR ECOSYST ENVIRON, V74, P19 ANDERLIKWESINGE.G, 1996, VERH GES OKOL, V26, P711 ARNOLD GW, 1983, J APPL ECOL, V20, P731 ATAURI JA, 2001, LANDSCAPE ECOL, V16, P147 AUDE E, 2003, AGR ECOSYST ENVIRON, V99, P135 BACKMAN JPC, 2002, AGR ECOSYST ENVIRON, V89, P53 BAINES M, 1998, ECOGRAPHY, V21, P74 BARNASZAK J, 1992, AGR ECOSYST ENVIRON, V40, P179 BAUDRY J, 2000, J ENVIRON MANAGE, V60, P7 BAUDRY J, 2000, LANDSCAPE URBAN PLAN, V50, P119 BENTON TG, 2003, TRENDS ECOL EVOL, V18, P182 BINK FA, 1992, ECOLOGISCHE ATLAS DA BRANDT JJE, 2002, LANDSCAPE URBAN PLAN, V62, P37 BUGTER R, 2003, IALE WORLD C 2003 BUREL F, 1998, ACTA OECOL, V19, P47 BUREL F, 2004, LANDSCAPE URBAN PLAN, V67, P195 CHAMBERLAIN DE, 2000, J APPL ECOL, V37, P771 CONSTANT P, 1976, BOCAGES HIST ECOLOGI, P327 DABROWSKAPROT E, 1995, EKOL POL, V43, P51 DEBRUIJN O, 1979, LIMOSA, V52, P91 DELAPENA NM, 2003, LANDSCAPE ECOL, V18, P265 DELETTRE YR, 2000, FRESHWATER BIOL, V44, P399 DIGIULIO M, 2001, J APPL ECOL, V38, P310 DONALD PF, 2001, P ROY SOC LOND B BIO, V268, P25 DUELLI P, 1997, AGR ECOSYST ENVIRON, V62, P81 DUELLI P, 1998, BIODIVERS CONSERV, V7, P297 FALINSKI JB, 1985, G BOT IT, V119, P1 FEBER RE, 1997, AGR ECOSYST ENVIRON, V64, P133 FOPPEN RPB, 2000, CONSERV BIOL, V14, P1881 FORMAN RTT, 1984, ENVIRON MANAGE, V8, P495 FRECKLETON RP, 2002, J ECOL, V90, P419 FULLER RJ, 2001, AGR ECOSYST ENVIRON, V84, P79 GEERTSEMA W, 2002, THESIS WAGENINGEN U, P99 GRASHOFBOKDAM C, 1997, J VEG SCI, V8, P21 HAINESYOUNG RH, 2000, ACCOUNTING NATURE AS HALD AB, 2002, AGR ECOSYST ENVIRON, V89, P127 HANSKI I, 1991, BIOL J LINN SOC, V42, P3 HARPER JL, 1995, BIODIVERSITY MEASURE, P5 HEGARTY CA, 1994, MONOGRAPH, V58, P227 HENDERSON IG, 2000, J APPL ECOL, V37, P335 HILL MO, 1973, ECOLOGY, V54, P427 HINSLEY SA, 1998, GLOBAL ECOL BIOGEOGR, V7, P125 HUBBELL SP, 2001, UNIFIED THEORY BIODI JONGMAN RHG, 1996, ECOLOGICAL LANDSCAPE KLEIJN D, 1997, J APPL ECOL, V34, P1413 KLEIJN D, 2000, J APPL ECOL, V37, P256 KLEIJN D, 2001, NATURE, V413, P723 KLEIJN D, 2003, J APPL ECOL, V40, P947 KOZAKIEWICZ M, 1994, POLISH ECOLOGICAL ST, V20, P209 LECOEUR D, 1997, LANDSCAPE URBAN PLAN, V37, P57 LECOEUR D, 2002, AGR ECOSYST ENVIRON, V89, P23 LEVINS R, 1970, LECT MATH LIFE SCI, V2, P77 LYS JA, 1994, ENTOMOL EXP APPL, V73, P1 MA MH, 2002, AGR ECOSYST ENVIRON, V89, P137 MAGURRAN AE, 1988, ECOLOGICAL DIVERSITY MARGULES CR, 2000, NATURE, V405, P243 MCADAM JH, 1994, MONOGRAPH BCPC PUBLI, V58, P153 MOONEN AC, 2001, AGR ECOSYST ENVIRON, V86, P187 MOSER D, 2002, LANDSCAPE ECOL, V17, P657 MOUNTFORD JO, 1994, MONOGRAPH BRIT CROP, V58, P105 MUSKENS GJD, 2002, BOOMMARTERS WEGEN EE OLFF H, 2002, LANDSCAPE URBAN PLAN, V58, P83 OOSTENBRINK W, 1994, LANDSCHAP, V11, P3 OPDAM P, 2000, LANDSCHAP, V17, P45 OUIN A, 2002, AGR ECOSYST ENVIRON, V93, P45 PAINTER D, 1999, J APPL ECOL, V36, P33 PAOLETTI MG, 1999, AGR ECOSYST ENVIRON, V74, P1 PEET RK, 1974, ANNU REV ECOL SYST, V5, P285 PETIT S, 1998, BIODIVERS CONSERV, V7, P1549 PIMM SL, 2000, NATURE, V403, P843 RIFFELL SK, 1996, LANDSCAPE ECOL, V11, P157 SAARINEN K, 2002, AGR ECOSYST ENVIRON, V90, P59 SCHAFFERS AP, 2002, PLANT ECOL, V158, P247 SIRIWARDENA GM, 2000, ECOGRAPHY, V23, P702 SNOO GR, 1999, AGR ECOSYST ENVIRON, V73, P1 SPACKMAN SC, 1995, BIOL CONSERV, V73, P221 SPARKS TH, 1995, BIOL CONSERV, V73, P221 STEFFANDEWENTER I, 2000, ECOL LETT, V3, P449 TSCHARNTKE T, 1998, J APPL ECOL, V35, P708 TWISK W, 2003, AQUAT ECOL, V37, P191 VANDERMEER J, 1998, AGR ECOSYST ENVIRON, V67, P1 VANRUREMONDE RHAC, 1991, J VEG SCI, V2, P377 VANSTRIEN AJ, 1989, J APPL ECOL, V26, P989 VANSTRIEN AJ, 1991, THESIS U LEIDEN VERBOOM B, 1998, IBN SCI CONTRIBUTION, V10 VERBOOM J, 1993, IALE STUDIES LANDSCA, V1, P172 VOS CC, 1999, THESIS WAGENINGEN U WAGNER HH, 2001, LANDSCAPE ECOL, V16, P121 WAIDE RB, 1999, ANNU REV ECOL SYST, V30, P257 WEIBULL AC, 2000, ECOGRAPHY, V23, P743 WICKRAMASINGHE LP, 2003, J APPL ECOL, V40, P984 WOODRUFF DS, 2001, P NATL ACAD SCI USA, V98, P5471 ZECHMEISTER HG, 2001, BIODIVERS CONSERV, V10, P1609 0921-2973 Landsc. Ecol.ISI:000233035100005Alterra Green World Res, NL-6700 AA Wageningen, Netherlands. Univ Wageningen & Res Ctr, Dept Environm Sci, Resource Ecol Grp, NL-6708 PD Wageningen, Netherlands. Grashof-Bokdam, CJ, Alterra Green World Res, POB 47, NL-6700 AA Wageningen, Netherlands. carla.grashof@wur.nlEnglish|? WGraves, Tabitha Chandler, Richard B. Royle, J. Andrew Beier, Paul Kendall, Katherine C.2014,Estimating landscape resistance to dispersal 1201-1211Landscape Ecology297AugDispersal is an inherently spatial process that can be affected by habitat conditions in sites encountered by dispersers. Understanding landscape resistance to dispersal is important in connectivity studies and reserve design, but most existing methods use resistance functions with cost parameters that are subjectively chosen by the investigator. We develop an analytic approach allowing for direct estimation of resistance parameters that folds least cost path methods typically used in simulation approaches into a formal statistical model of dispersal distributions. The core of our model is a frequency distribution of dispersal distances expressed as least cost distance rather than Euclidean distance, and which includes terms for feature-specific costs to dispersal and sex (or other traits) of the disperser. The model requires only origin and settlement locations for multiple individuals, such as might be obtained from mark-recapture studies or parentage analyses, and maps of the relevant habitat features. To evaluate whether the model can estimate parameters correctly, we fit our model to data from simulated dispersers in three kinds of landscapes (in which resistance of environmental variables was categorical, continuous with a patchy configuration, or continuous in a trend pattern). We found maximum likelihood estimators of resistance and individual trait parameters to be approximately unbiased with moderate sample sizes. We applied the model to a small grizzly bear dataset to demonstrate how this approach could be used when the primary interest is in the prediction of costs and found that estimates were consistent with expectations based on bear ecology. Our method has important practical applications for testing hypotheses about dispersal ecology and can be used to inform connectivity planning efforts, via the resistance estimates and confidence intervals, which can be used to create a data-driven resistance surface.!://WOS:000339831300009Times Cited: 0 0921-2973WOS:00033983130000910.1007/s10980-014-0056-51?ZGTabitha A. Graves Sean Farley Michael I. Goldstein Christopher Servheen2007sIdentification of functional corridors with movement characteristics of brown bears on the Kenai Peninsula, Alaska 765-772Landscape Ecology225RConnectivity - Fragmentation - Habitat - Highways - Linkage zones - Ursus arctos We identified primary habitat and functional corridors across a landscape using Global Positioning System (GPS) collar locations of brown bears (Ursus arctos). After deriving density, speed, and angular deviation of movement, we classified landscape function for a group of animals with a cluster analysis. We described areas with high amounts of sinuous movement as primary habitat patches and areas with high amounts of very directional, fast movement as highly functional bear corridors. The time between bear locations and scale of analysis influenced the number and size of corridors identified. Bear locations should be collected at intervals ≤6 h to correctly identify travel corridors. Our corridor identification technique will help managers move beyond the theoretical discussion of corridors and linkage zones to active management of landscape features that will preserve connectivity.  ?<7R Graves, T. A. Wasserman, T. N. Ribeiro, M. C. Landguth, E. L. Spear, S. F. Balkenhol, N. Higgins, C. B. Fortin, M. J. Cushman, S. A. Waits, L. P.2012xThe influence of landscape characteristics and home-range size on the quantification of landscape-genetics relationships253-266Landscape Ecology272 least cost habitat resistance fragmentation genetic structure sampling error aggregation cohesiveness connectivity gene flow isolation-by-resistance female roe deer population-genetics mantel test flow connectivity behavior resistance regression diversity inferenceFeb^A common approach used to estimate landscape resistance involves comparing correlations of ecological and genetic distances calculated among individuals of a species. However, the location of sampled individuals may contain some degree of spatial uncertainty due to the natural variation of animals moving through their home range or measurement error in plant or animal locations. In this study, we evaluate the ways that spatial uncertainty, landscape characteristics, and genetic stochasticity interact to influence the strength and variability of conclusions about landscape-genetics relationships. We used a neutral landscape model to generate 45 landscapes composed of habitat and non-habitat, varying in percent habitat, aggregation, and structural connectivity (patch cohesion). We created true and alternate locations for 500 individuals, calculated ecological distances (least-cost paths), and simulated genetic distances among individuals. We compared correlations between ecological distances for true and alternate locations. We then simulated genotypes at 15 neutral loci and investigated whether the same influences could be detected in simple Mantel tests and while controlling for the effects of isolation-by distance using the partial Mantel test. Spatial uncertainty interacted with the percentage of habitat in the landscape, but led to only small reductions in correlations. Furthermore, the strongest correlations occurred with low percent habitat, high aggregation, and low to intermediate levels of cohesion. Overall genetic stochasticity was relatively low and was influenced by landscape characteristics.://0003000887000099Sp. Iss. SI 889QQ Times Cited:0 Cited References Count:51 0921-2973Landscape EcolISI:000300088700009Graves, TA No Arizona Univ, Sch Forestry, POB 15108, Flagstaff, AZ 86011 USA No Arizona Univ, Sch Forestry, POB 15108, Flagstaff, AZ 86011 USA No Arizona Univ, Sch Forestry, Flagstaff, AZ 86011 USA Univ Estadual Paulista UNESP, Dept Ecol, BR-13506900 Rio Claro, SP, Brazil Virginia Commonwealth Univ, Dept Integrat Life Sci, Richmond, VA 23284 USA Univ Montana, Div Biol Sci, Missoula, MT 59812 USA Orianne Soc, Clayton, GA 30525 USA Univ Idaho, Dept Fish & Wildlife Resources, Moscow, ID 83844 USA Univ Gottingen, Dept Forest Zool & Forest Conservat, D-37077 Gottingen, Germany Univ Toronto, Dept Ecol & Evolutionary Biol, Toronto, ON M5S 3G5, Canada US Forest Serv, Forest Serv Res Stn, Flagstaff, AZ 86011 USADOI 10.1007/s10980-011-9701-4English)<7%Gray, M. J. Smith, L. M. Leyva, R. I.2004bInfluence of agricultural landscape structure on a Southern High Plains, USA, amphibian assemblage719-729Landscape Ecology197amphibians; conservation; demographics; spatial metrics; wetlands HABITAT FRAGMENTATION; POPULATION SURVIVAL; ELEODES BEETLES; TOAD ABUNDANCE; PLAYA WETLANDS; METAPOPULATION; CONNECTIVITY; EXTINCTION; FROG; DISTRIBUTIONSArticle Landscape structure can influence demographics of spatially structured populations, particularly less vagile organisms such as amphibians. We examined the influence of agricultural landscape structure on community composition and relative abundance of the 4 most common amphibians in the Southern High Plains of central USA. Amphibian populations were monitored using pitfall traps and drift fence at 16 playa wetlands (8 playas/year) in 1999 and 2000. We quantified landscape structure surrounding each playa via estimating 13 spatial metrics that indexed playa isolation and inter-playa landscape complexity. Multivariate ordination and univariate correlations and regressions indicated that landscape structure was associated with community composition and relative abundance for 2 of the 4 amphibians. Spadefoots (Spea multiplicata, S. bombifrons) generally were positively associated with decreasing inter-playa distance and increasing inter-playa landscape complexity. Great Plains toads (Bufo cognatus) and barred tiger salamanders (Ambystoma tigrinum mavortium) usually were negatively associated with spadefoots but not influenced by landscape structure. Composition and relative abundance patterns were related to amphibian body size, which can influence species vagility and perception to landscape permeability. Spatial separation of these species in the multivariate ordination also may have been a consequence of differential competitive ability among species. These results suggest agricultural landscape structure may influence abundance and composition of spatially structured amphibian populations. This also is the first applied documentation that inter-patch landscape complexity can affect intra-patch community composition of amphibians as predicted by metapopulation theory. In the Southern High Plains, landscape complexity is positively associated with agricultural cultivation. Agricultural cultivation increases sedimentation, decreases hydroperiod, alters amphibian community dynamics, and negatively impacts postmetamorphic body size of amphibians in playa wetlands. Thus, conservation efforts should focus on preserving or restoring native landscape structure, hydroperiod, and connectivity among playas to maintain native amphibian populations and historic inter-playa movement.://000226384000002 0 ISI Document Delivery No.: 888OL Times Cited: 4 Cited Reference Count: 56 Cited References: ANDERSON AM, 1999, COPEIA 0507, P515 BASCOMPTE J, 1996, J ANIM ECOL, V65, P465 BUREL F, 1989, LANDSCAPE ECOLOGY, V2, P215 CRIST TO, 1992, FUNCT ECOL, V6, P536 DAYTON GH, 2001, OECOLOGIA, V129, P430 DODD CK, 1994, MEASURING MONITORING, P125 DRISCOLL DA, 1997, AUST J ECOL, V22, P185 FAHRIG L, 1985, ECOLOGY, V66, P1762 FAHRIG L, 1988, THEOR POPUL BIOL, V34, P194 FAHRIG L, 1994, CONSERV BIOL, V8, P50 GEHLBACH FR, 1967, YB AM PHILOS SOC, P266 GEHLBACH FR, 1969, PHYSIOL ZOOL, V42, P173 GRAY MJ, 2002, THESIS TEXAS TU LUBB GRAY MJ, 2004, IN PRESS CONSERVATIO, V18 GUERRY AD, 2002, CONSERV BIOL, V16, P745 GUTHERY FS, 1982, WILDLIFE SOC B, V10, P309 HESS GR, 1996, AM NAT, V148, P226 HEYER WR, 1994, MEASURING MONITORING HOULAHAN JE, 2000, NATURE, V404, P752 KNUTSON MG, 1999, CONSERV BIOL, V13, P1437 KOLOZSVARY MB, 1999, CAN J ZOOL, V77, P1288 LEFKOVITCH LP, 1985, ECOL MODEL, V30, P297 LUO HR, 1997, ECOL APPL, V7, P247 LUO HR, 1999, WETLANDS, V19, P176 MARSH DM, 1997, CONSERV BIOL, V11, P1323 MARSH DM, 2001, CONSERV BIOL, V15, P40 MCGARIGAL K, 1995, PNWGTR351 US FOR SER MCINTYRE NE, 2000, WEST N AM NATURALIST, V60, P1 MIAUD C, 2000, AMPHIBIA-REPTILIA, V21, P357 MILTON JS, 1995, INTRO PROBABILITY ST MORIN PJ, 1983, ECOL MONOGR, V53, P119 PETERS RH, 1983, ECOLOGICAL IMPLICATI POPE SE, 2000, ECOLOGY, V80, P2326 RITCHIE ME, 1997, WILDLIFE LANDSCAPE E, P160 ROSENZWEIG ML, 1995, SPECIES DIVERSITY SP ROTHERMEL BB, 2002, CONSERV BIOL, V16, P1324 SCRIBNER KT, 2001, BIOL CONSERV, V98, P201 SINSCH U, 1990, ETHOL ECOL EVOL, V2, P65 SINSCH U, 1997, OECOLOGIA, V112, P42 SJOGREN P, 1991, BIOL J LINN SOC, V42, P135 SMITH LM, 2002, CONSERV BIOL, V16, P964 SMITH LM, 2003, IN PRESS SW NATURALI, V50 SMITH LM, 2003, PLAYAS GREAT PLAINS STACEY PB, 1997, METAPOPULATION BIOL, P267 STAMPS JA, 1987, AM NAT, V129, P533 SZACKI J, 1999, LANDSCAPE ECOL, V14, P369 TAYLOR PD, 1993, OIKOS, V68, P571 TERBRAAK CJF, 1986, ECOLOGY, V67, P1167 TERBRAAK CJF, 1994, ECOSCIENCE, V1, P127 TERBRAAK CJF, 1995, DATA ANAL COMMUNITY, P91 TERBRAAK CJF, 1998, CANOCO REFERENCE MAN WIENS JA, 1997, METAPOPULATION BIOL, P43 WIENS JA, 1997, OIKOS, V78, P257 WILBUR HM, 1987, ECOLOGY, V68, P1437 WITH KA, 1994, FUNCT ECOL, V8, P477 WITH KA, 1995, ECOLOGY, V76, P2446 0921-2973 Landsc. Ecol.ISI:000226384000002Nature Conservancy, San Antonio, TX USA. Texas Tech Univ, Wildlife & Fisheries Management Inst, Lubbock, TX 79409 USA. Gray, MJ, Univ Tennessee, Dept Forestry Fisheries & Wildlife, Knoxville, TN 37996 USA. mattjgray@utk.eduEnglish<7Grear, J. S. Burns, C. E.2007Evaluating effects of low quality habitats on regional population growth in Peromyscus leucopus: Insights from field-parameterized spatial matrix models45-60Landscape Ecology221habitat quality; landscape; spatial; matrix model; Peromyscus; population; source; sink; white-footed mouse; North America; USA WHITE-FOOTED MICE; FOREST FRAGMENTS; MARKED ANIMALS; DENSITY; LANDSCAPE; SELECTION; DISPERSAL; RECAPTURE; DYNAMICS; SURVIVALArticleJanDue to complex population dynamics and source-sink metapopulation processes, animal fitness sometimes varies across landscapes in ways that cannot be deduced from simple density patterns. In this study, we examine spatial patterns in fitness using a combination of intensive field-based analyses of demography and migration and spatial matrix models of white-footed mouse (Peromyscus leucopus) population dynamics. We interpret asymptotic population growth rates from these spatial models as fitness-based measures of habitat-quality and use elasticity analysis to further explore model behavior and the roles of migration. In addition, we compare population growth rates at the spatial scale of single habitats and the landscape-level scale at which these habitats are assembled. To this end, we employ emerging techniques in multi-scale estimation of demography and movement and recently described vec-permutation methods for spatial matrix notation and analysis. Our findings indicate that the loss of low quality habitats or reductions in movement from these habitats into higher quality areas could negatively affect landscape-level population fitness.://000243619800006 5 ISI Document Delivery No.: 127XO Times Cited: 0 Cited Reference Count: 57 Cited References: *US FISH WILDL SER, 1981, EC SERV MAN, V103 ADLER GH, 1985, OIKOS, V45, P380 ANDERSON CS, 2003, CAN J ZOOL, V81, P897 BOWMAN JC, 2000, FOREST ECOL MANAG, V129, P119 BOWNE DR, 2004, LANDSCAPE ECOL, V19, P1 BROOKS RP, 1997, WILDLIFE SOC B, V25, P163 BURNHAM KP, 2002, MODEL SELECTION MULT BURNS CE, 2005, ECOLOGY, V86, P753 CASWELL H, 1994, ECOLOGY, V75, P1299 CASWELL H, 2001, MATRIX POPULATION MO DEGRAFF RM, 2001, NEW ENGLAND WILDLIFE DIAS PC, 1996, TRENDS ECOL EVOL, V11, P326 FRETWELL SC, 1970, ACTA BIOTHEOR, V19, P16 GREAR JS, 2005, ECOLOGY, V86, P960 HALAMA KJ, 1994, OIKOS, V69, P107 HARDING EK, 2002, BIOL CONSERV, V104, P227 HOWE RW, 1991, BIOL CONSERV, V57, P239 HUNTER CM, 2005, ECOL MODEL, V188, P15 KING JA, 1968, BIOL PEROMYSCUS RODE KOONS DN, 2005, ECOL MODEL, V185, P283 LEBRETON JD, 1992, ECOL MONOGR, V62, P67 LEBRETON JD, 2002, J APPL STAT, V29, P353 LEBRETON JD, 2003, OIKOS, V101, P253 LEFKOVITCH LP, 1985, ECOL MODEL, V30, P297 MIDDLETON DAJ, 1997, ECOL APPL, V7, P107 MILLAR JS, 1984, WINT ECOLOGY SMALL M, P253 MORRIS DW, 1989, EVOL ECOL, V3, P80 MORRIS DW, 1991, AM NAT, V138, P702 MORRIS DW, 2004, OIKOS, V107, P549 MORRIS WF, 2002, QUANTITATIVE CONSERV MURPHY MT, 2001, CONSERV BIOL, V15, P737 NUPP TE, 2000, J MAMMAL, V81, P512 NUPP TE, 2001, MAMM BIOL, V66, P345 OSTFELD RS, 1995, ECOL APPL, V5, P353 PICKETT STA, 1995, SCIENCE, V269, P331 PRADEL R, 1996, BIOMETRICS, V52, P703 PULLIAM HR, 1988, AM NAT, V132, P652 PULLIAM HR, 1991, AM NAT S, V137, P50 PULLIAM HR, 1992, ECOL APPL, V2, P165 PULLIAM HR, 1996, POPULATION DYNAMICS, P45 ROFF DA, 1974, OECOLOGIA, V15, P245 ROFF DA, 1974, OECOLOGIA, V15, P259 ROSENBLATT DL, 1999, AM MIDL NAT, V141, P115 SCHMIDHOLMES S, 2001, BIOL CONSERV, V99, P293 STEEN H, 2000, J ANIM ECOL, V69, P659 TERMAN CR, 1993, J MAMMAL, V74, P678 THOMAS CD, 1999, J ANIM ECOL, V68, P647 TILMAN D, 1997, SPATIAL ECOLOGY ROLE VANHORNE B, 1983, J WILDLIFE MANAGE, V47, P893 WATKINSON AR, 1995, J ANIM ECOL, V64, P126 WHEATLEY M, 2002, J MAMMAL, V83, P716 WHITAKER JO, 1998, MAMMALS E US WHITE GC, 1999, BIRD STUDY S, V46, P120 WIENS JA, 1989, FUNCT ECOL, V3, P385 WILLIAMS BK, 2002, ANAL MANAGEMENT ANIM WOLFF JO, 1985, CAN J ZOOL, V63, P2657 WOLFF JO, 1986, CAN FIELD NAT, V100, P186 0921-2973 Landsc. Ecol.ISI:000243619800006kUS EPA, Environm Res Lab, Off Res & Dev,Atlantic Ecol Div, Natl Hlth & Environm Effects Res Lab, Narragansett, RI 02882 USA. Yale Univ, Dept Ecol & Evolutionary Biol, New Haven, CT 06511 USA. Grear, JS, US EPA, Environm Res Lab, Off Res & Dev,Atlantic Ecol Div, Natl Hlth & Environm Effects Res Lab, 27 Tarzwell Dr, Narragansett, RI 02882 USA. grear.jason@epa.govEnglish|?LfGret-Regamey, Adrienne Rabe, Sven-Erik Crespo, Ricardo Lautenbach, Sven Ryffel, Andrea Schlup, Barbara2014|On the importance of non-linear relationships between landscape patterns and the sustainable provision of ecosystem services201-212Landscape Ecology292FebMarginal land use changes can abruptly result in non-marginal and irreversible changes in ecosystem functioning and the economic values that the ecosystem generates. This challenges the traditional ecosystem services (ESS) mapping approach, which has often made the assumption that ESS can be mapped uniquely to land use and land cover data. Using a functional fragmentation measure, we show how landscape pattern changes might lead to changes in the delivery of ESS. We map changes in ESS of dry calcareous grasslands under different land use change scenarios in a case study region in Switzerland. We selected three ESS known to be related to species diversity including carbon sequestration and pollination as regulating values and recreational experience as cultural value, and compared them to the value of two production services including food and timber production. Results show that the current unceasing fragmentation is particularly critical for the value of ESS provided by species-rich habitats. The article concludes that assessing landscape patterns is key for maintaining valuable ESS in the face of human use and fluctuating environment.!://WOS:000331935100003Times Cited: 3 0921-2973WOS:00033193510000310.1007/s10980-013-9957-yM<7Grevilliot, F. Muller, S.2001jGrassland ecotopes of the upper Meuse as references for habitats and biodiversity restoration: A synthesis19-33Landscape Ecology17 Supplement 1agricultural practices conservation value ecotopes hydrologic functioning upper Meuse floodplain ALLUVIAL MEADOWS WETLAND PLANTS VEGETATION AVAILABILITY MANAGEMENT YIELDArticle)The river valley of the French upper Meuse and its floodplain, constitutes a relatively natural ecosystem which still contains many endangered species of high conservation value. For example, several birds (Crex crex, Numenius arquata) as well as plant species (Gratiola officinalis, Inula britannica, Teucrium scordium, Ranunculus lingua and Mentha pulegium) which have declined seriously in France in recent times are found in the upper Meuse floodplain. Phytosociological studies and water level measurements have shown that the floristic diversity is mainly influenced by hydrological fluctuations and agricultural practices. The plant communities are structured along a topographical gradient in the high water bed reflecting the duration of floods and the ground water table depth. Agricultural practices have influenced the vegetation changes by selecting species adapted to particular management practices (e.g., fertiliser use, grazing, cutting regime). The data collected in this study from the upper Meuse as enabled 13 grassland and wetland ecotopes to be defined which are correlated with different environmental factors. Fertiliser use, grazing and reduction in the frequency of the cutting lead to a lower species richness because they encourage competitive species. However, it is also demonstrated, that maximum biodiversity is not always synonymous with high conservation value because some impoverished ecosystems, e.g., sedges and tall forb formations, may contain endangered plant and bird species. Knowledge of the boundaries between the different plant communities enables likely changes in floristic composition after modification of one or more site factors to be forecasted. Such factors include, water table depth and flood frequency, cutting regime, fertiliser use and grazing pressure. Thus, the definition of these ecotopes, corresponding to correlations between water regime, agricultural practice and vegetation composition, could lead to the establishment of guidelines for water and agricultural managements that could be involved in restoration projects.://000176041000003 ~ ISI Document Delivery No.: 559TG Times Cited: 2 Cited Reference Count: 61 Cited References: AUBLE GT, 1994, ECOL APPL, V4, P544 BAKKER JP, 1995, NORDDEUTSCHE NATURSC, V8, P42 BAKKER JP, 1996, ACTA BOT NEERL, V45, P461 BARENDREGT A, 1986, C PHYTOSOCIOLOGIQUE, V13, P603 BEKKER RM, 1997, SPECIES DISPERSAL LA, P247 BERENDSE F, 1992, BIOL CONSERV, V62, P59 BOBE V, 1987, ETUDE PHYTOECOLOGIQU BOURNERIAS M, 1978, COLLOQ PHYTOSOCIOL, V5, P90 BOUTIN C, 1993, J VEG SCI, V4, P591 BROYER J, 1991, CONSERVATION ECOSYST BROYER J, 1994, ALAUDA, V62, P1 BROYER J, 1995, ECOLOGIE, V26, P45 CARBIENER R, 1969, B SOC IND MULHOUSE, V734, P15 DEFOUCAULT B, 1984, THESIS ROUEN DELPECH R, 1989, 5 C NAT EC FRANC REC, P151 DENNY P, 1993, J INST WATER ENV MAN, V7, P387 DIERSSEN K, 1989, C PHYTOSOCIOLOGIQUE, V16, P484 DUVIGNEAUD J, 1958, B SOC ROY BOT BELG, V91, P7 ELBERSE WT, 1983, NETH J AGR SCI, V31, P63 FABER M, 1994, MEMOIRE MAITRISE GORDON IJ, 1990, B ECOLOGIE, V21, P49 GRANDET G, 1996, ETUDE ECLOGIQUE PRAI GREVILLIOT F, 1995, CR ACAD SCI III-VIE, V318, P491 GREVILLIOT F, 1997, ACTA BOT GALLICA, V143, P317 GREVILLIOT F, 1999, BIODIVERS CONSERV, V7, P1495 GRIME JP, 1975, J ECOL, V63, P393 GRIME JP, 1979, PLANT STRATEGIES VEG GROOTJANS AP, 1980, ACTA BOT NEERL, V5, P546 GUINOCHET M, 1973, PHYTOSOCIOLOGIE HARMAND D, 1992, HIST VALLEE MEUSE LO KREBS L, 1999, HYDROBIOLOGIA, V410, P195 KREBS L, 2000, THESIS U METZ FRANCE LAMBINON J, 1992, NOUVELLE FLORE BELGI MAGNANON S, 1991, THESIS U NANTES FRAN MATCHES AG, 1992, J PROD AGRIC, V5, P1 MCJANNET CL, 1995, FUNCT ECOL, V9, P231 MOUNTFORD JO, 1996, J VEG SCI, V7, P219 MULLER S, 1992, ANN SCI RESERVE BIOS, V2, P53 OLFF H, 1992, OECOLOGIA, V89, P412 OOMES MJM, 1992, J VEG SCI, V3, P271 OSBORNOVA J, 1990, STUDIES CENTRAL CZEC, V15, P25 PAUTOU G, 1975, THESIS U MED GRENOBL PLANTUREUX S, 1992, FOURRAGES, V132, P381 POSCHLOD P, 1996, SPECIES SURVIVAL FRA, P123 PRACH K, 1993, FOLIA GEOBOT PHYTOTX, V28, P1 REVILLIOT F, 1995, 37 IAVS S LARG AR VE, P115 REVILLIOT F, 1996, THESIS U METZ FRANCE SELINGERLOOTEN R, 1999, LANDSCAPE ECOL, V14, P213 SELINGERLOOTEN R, 2000, THESIS U METZ FRANCE SMITH RS, 1991, J APPL ECOL, V28, P42 THOMET P, 1993, LANDWIRTSCHAFT SCHWE, V6, P107 TINER RW, 1991, BIOSCIENCE, V41, P236 TINER RW, 1993, P ACAD NAT SCI PHILA, V144, P240 TRIVAUDEY MJ, 1995, THESIS U BESANCON VANDERVALK AG, 1981, ECOLOGY, V62, P688 VANDIGGELEN R, 1991, IAHS PUBL, V202, P71 VANDIGGELEN R, 1995, Z KULTURTECHNIK LAND, V36, P125 VINCENT V, 1997, ETUDE IMPACT MODIFIC WILLEMS JH, 1993, J VEG SCI, V4, P203 WILLMS WD, 1995, J RANGE MANAGE, V48, P423 WILSON SD, 1993, ECOLOGY, V74, P599 Suppl. 1 0921-2973 Landsc. Ecol.ISI:000176041000003Univ, Lab Phytoecol, Unite Rech EBSE, F-57070 Metz, France. Grevilliot, F, Univ, Lab Phytoecol, Unite Rech EBSE, Campus Bridoux,Rue Gen Delestraint, F-57070 Metz, France. fgrevilliot@viola.frEnglish7G?F. Grevilliot S. Muller2002jGrassland ecotopes of the upper Meuse as references for habitats and biodiversity restoration: A synthesis19-33Landscape Ecology170hAgricultural practices - Conservation value - Ecotopes - Hydrologic functioning - Upper Meuse floodplain*The river valley of the French upper Meuse and its floodplain, constitutes a relatively natural ecosystem which still contains many endangered species of high conservation value. For example, several birds (Crex crex, Numenius arquata) as well as plant species (Gratiola officinalis, Inula britannica, Teucrium scordium, Ranunculus lingua and Mentha pulegium) which have declined seriously in France in recent times are found in the upper Meuse floodplain. Phytosociological studies and water level measurements have shown that the floristic diversity is mainly influenced by hydrological fluctuations and agricultural practices. The plant communities are structured along a topographical gradient in the high water bed reflecting the duration of floods and the ground water table depth. Agricultural practices have influenced the vegetation changes by selecting species adapted to particular management practices (e.g., fertiliser use, grazing, cutting regime). The data collected in this study from the upper Meuse as enabled 13 grassland and wetland ecotopes to be defined which are correlated with different environmental factors. Fertiliser use, grazing and reduction in the frequency of the cutting lead to a lower species richness because they encourage competitive species. However, it is also demonstrated, that maximum biodiversity is not always synonymous with high conservation value because some impoverished ecosystems, e.g., sedges and tall forb formations, may contain endangered plant and bird species. Knowledge of the boundaries between the different plant communities enables likely changes in floristic composition after modification of one or more site factors to be forecasted. Such factors include, water table depth and flood frequency, cutting regime, fertiliser use and grazing pressure. Thus, the definition of these ecotopes, corresponding to correlations between water regime, agricultural practice and vegetation composition, could lead to the establishment of guidelines for water and agricultural managements that could be involved in restoration projects. *http://dx.doi.org/10.1023/A:1015225609385 -10.1023/A:1015225609385 F. Grevilliot Email: fgrevilliot@voila.fr References Auble G.T., Friedman J.M. and Scott M.L. 1994. 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Etude de l'impact des changements des pratiques agricoles sur la biodiversité végétale dans les prairies inondables du Val de Meuse: Présentation méthodologique et premiers résultats. Acta Bot. Gallica 143: 317-338. Grévilliot F., Krebs L. and Muller S. 1999. Comparative importance and interference of hydrological conditions and soil nutrient gradients in floristic biodiversity in flood meadows. Biodiv. Conserv. 7: 1495-1520. Grime J.P. 1979. Plant strategies and vegetation processes. John Wiley and Sons, Chichester, UK, 216 pp. Grime J.P. and Hunt R. 1975. Relative growth rate: its range and adaptive significance in a local flora. J. of Ecol. 63: 393-422. Grootjans A.P. and Ten Klooster, W.P.H. 1980. Changes of groundwater regime in wet meadows. Acta Bot. Neerl. 5/6: 546-554. Guinochet M. 1973. Phytosociologie. Masson, Paris, France, 227 pp. Harmand D. 1992. Histoire de la vallée de laMeuse Lorraine. Presse universitaire de Nancy, France, 146 pp. Hercent J.L. 1991. 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Sélinger-Looten R. 2000. Déterminisme de la biodiversité des formations herbacées alluviales du bassin versant de la Sarre. Thesis, Univ. Metz, France, 398 pp. Sélinger-Looten R., Grévilliot F. and Muller S. 1999. Structure of plant communities and landscape patterns in alluvial meadows of two flood plains in the north-east of France. Landsc. Ecol. 14: 213-229. Smith R.S. and Jones L. 1991. The phenology of mesotrophic grassland in the Pennine Dales, Northern England: Historic hay cutting dates, vegetation variation and plant species phenologies. J. Appl. Ecol. 28: 42-59. Thomet P. and Koch B. 1993. Langfristige Auswirkungen von Düngung und Schnittregime auf eine Heumatte. Landwirtschaft Schweiz 6: 107-114. Tiner R.W. 1991. The concept of hydrophyte for wetland identification. Bioscience 41: 236-247. Tiner R.W. 1993. Using plants as indicator of wetland. Proc. Acad. Nat. Sci. Philadelphia 144: 240-253. Trivaudey M.J. 1995. Contribution à l'étude phytosociologique des prairies alluviales de l'Est de la France (Vallées de la Saône, de la Seille, de l'Ognon, de la Lanterne et du Breuchin). Approche systémique. Thesis, Univ. de Besançon, 2 vol. Van der Valk A.G. and Davis C.B. 1981. Succession in wetlands: A gleasonian approach. Ecology 62: 688-696. Van Diggelen R., Grootjans A.P., Wierda A., Burkunk R. and Hoogendoorn J. 1991. Prediction of vegetation changes under different hydrological scenarios. Proc. of the Vienna symposium, IAHS 202: 71-79. Van Diggelen R., Grootjans A.P. and Wierda A. 1995. Hydro-Ecological Landscape Analysis: A Tool forWetland Restoration. Zeitschr. Kulturtechn. Landentwick. 36: 125-131. Vincent V. 1997. Etude de l'impact des modifications des pratiques agricoles sur la végétation des prairies inondables de la Nied. Premiers résultats. D.E.A. Sciences Agronomiques, Univ. de Metz-INPL Nancy, France, 40 pp. (+ annex). Willems J.H., Peet R.K. and Bik L. 1993. Changes in chalk grassland structure and species richness resulting from selective nutrient additions. J. Veget. Sci. 4: 203-212. Willms W.D. and Quinton D.A. 1995. Grazing effects on germinable seeds on the fescue prairie. J. Range Manag. 48: 423-430. Wilson S.D. and Tilman D. 1993. Plant competition and resource availibility in response to disturbance and fertilization. Ecology 74: 599-611. F. Grevilliot1 and S. Muller1 (1) Laboratoire de Phytoécologie (Unité de Recherches EBSE), Université, Campus de Bridoux, Rue du Général Delestraint, F-57070 Metz, France |?' Grilli, M. P.2010iThe role of landscape structure on the abundance of a disease vector planthopper: a quantitative approach383-394Landscape Ecology253eStudies of patchily distributed insect populations have made clear the importance of host patch size and degree of isolation in determining the distribution of these populations. For such populations, patch connectivity will have an effect on patterns of patch occupancy and regional dynamics. In the present study we performed a series of observations to estimate the effect of landscape structure on the abundance of Delphacodes kuscheli (Homoptera: Delphacidae), vector of "Mal de Rio Cuarto" disease to maize. Actively dispersing D. kuscheli individuals were collected in 19 sampling sites during the spring of 2004, using sticky traps placed at 2 m above ground level. Land use and landscape pattern were quantified, using Landsat 5 TM images for the area where each sampling site was placed. Four land use categories were considered in the analysis; winter pastures, winter cereals, perennial pasture and stubble. The spatial pattern analysis program FRAGSTATS was employed to estimate the patch area, patch proximity index, Total Class Area and the Mean Proximity Index for each of the land use categories in those sites where insect samples were taken. Partial Least Squares Regression analysis techniques were employed to relate the mean abundance of D. kuscheli and the landscape measures. Eighty percent of the variation of the mean insect abundance was explained by two first PLSR components. The proximity index of the local host patches, the amount of area left to stubble, local host patch area and total area of winter pastures were the most important variables affecting the abundance of dispersing D. kuscheli individuals. We found that the abundance of the dispersive fraction of the population of D. kuscheli is affected mostly by the surrounding landscape, particularly by the proximity of other host patches, and the permeability of the matrix represented by the stubble.!://WOS:000275122600005Times Cited: 0 0921-2973WOS:00027512260000510.1007/s10980-009-9422-0 |?S&Grimaldi, Michel Oszwald, Johan Doledec, Sylvain del Pilar Hurtado, Maria Miranda, Izildinha de Souza de Sartre, Xavier Arnauld de Assis, William Santos Castaneda, Edna Desjardins, Thierry Dubs, Florence Guevara, Edward Gond, Valery Santana Lima, Tamara Thaiz Marichal, Raphael Michelotti, Fernando Mitja, Danielle Noronha, Norberto Cornejo Delgado Oliveira, Mariana Nascimento Ramirez, Bertha Rodriguez, Gamaliel Sarrazin, Max da Silva, Mario Lopes, Jr. Silva Costa, Luiz Gonzaga de Souza, Simao Lindoso Veiga, Iran Velasquez, Elena Lavelle, Patrick2014iEcosystem services of regulation and support in Amazonian pioneer fronts: searching for landscape drivers311-328Landscape Ecology292FebvLandscape dynamics result from forestry and farming practices, both of which are expected to have diverse impacts on ecosystem services (ES). In this study, we investigated this general statement for regulating and supporting services via an assessment of ecosystem functions: climate regulation via carbon sequestration in soil and plant biomass, water cycle and soil erosion regulation via water infiltration in soil, and support for primary production via soil chemical quality and water storage. We tested the hypothesis that patterns of land-cover composition and structure significantly alter ES metrics at two different scales. We surveyed 54 farms in two Amazonian regions of Brazil and Colombia and assessed land-cover composition and structure from remote sensing data (farm scale) from 1990 to 2007. Simple and well-established methods were used to characterize soil and vegetation from five points in each farm (plot scale). Most ES metrics were significantly correlated with land-use (plot scale) and land-cover (farm scale) classifications; however, spatial variability in inherent soil properties, alone or in interaction with land-use or land-cover changes, contributed greatly to variability in ES metrics. Carbon stock in above-ground plant biomass and water infiltration rate decreased from forest to pasture land covers, whereas soil chemical quality and plant-available water storage capacity increased. Land-cover classifications based on structure metrics explained significantly less ES metric variation than those based on composition metrics. Land-cover composition dynamics explained 45 % (P < 0.001) of ES metric variance, 15 % by itself and 30 % in interaction with inherent soil properties. This study describes how ES evolve with landscape changes, specifying the contribution of spatial variability in the physical environment and highlighting trade-offs and synergies among ES.!://WOS:000331935100010Times Cited: 1 0921-2973WOS:00033193510001010.1007/s10980-013-9981-y~?rYGrober-Dunsmore, R. Frazer, T. K. Beets, J. P. Lindberg, W. J. Zwick, P. Funicelli, N. A.2008:Influence of landscape structure, on reef fish assemblages37-53Landscape Ecology23lManagement of tropical marine environments calls for interdisciplinary studies and innovative methodologies that consider processes occurring over broad spatial scales. We investigated relationships between landscape structure and reef fish assemblage structure in the US Virgin Islands. Measures of landscape structure were transformed into a reduced set of composite indices using principal component analyses (PCA) to synthesize data on the spatial patterning of the landscape structure of the study reefs. However, composite indices (e.g., habitat diversity) were not particularly informative for predicting reef fish assemblage structure. Rather, relationships were interpreted more easily when functional groups of fishes were related to individual habitat features. In particular, multiple reef fish parameters were strongly associated with reef context. Fishes responded to benthic habitat structure at multiple spatial scales, with various groups of fishes each correlated to a unique suite of variables. Accordingly, future experiments should be designed to test functional relationships based on the ecology of the organisms of interest. Our study demonstrates that landscape-scale habitat features influence reef fish communities, illustrating promise in applying a landscape ecology approach to better understand factors that structure coral reef ecosystems. Furthermore, our findings may prove useful in design of spatially-based conservation approaches such as marine protected areas (MPAs), because landscape-scale metrics may serve as proxies for areas with high species diversity and abundance within the coral reef landscape."://WOS:000252922800004 Times Cited: 0WOS:000252922800004(10.1007/s10980-007-9147-x|ISSN 0921-2973*<7nGrodzinski, M.1996Landscape ecology in UkraineU1-U1Landscape Ecology115Editorial MaterialOct://A1996VR02500001 HISI Document Delivery No.: VR025 Times Cited: 0 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1996VR02500001English <76Groffman, P. M. Tiedje, J. M. Mokma, D. L. Simkins, S.1992JRegional scale analysis of denitrification in north temperate forest soils45-53Landscape Ecology71ArticleAprPLarge scale analyses of biogeochemical processes are necessary for understanding anthropogenic effects on global climate and environmental quality. Regional scale estimates of denitrification from forest soils in southern lower Michigan USA were produced by stratifying the region into landscape experimental units using soil texture and natural drainage classes, and extrapolating data to larger areas using a geographic information system (GIS). Previous landscape-scale research established relationships between soil texture and drainage and denitrification and quantified annual denitrification N loss in nine soil texture/drainage groups. All forest soils within the region (64 series) were assigned to one of these nine groups based on their texture and drainage characteristics and were assigned an annual denitrification N loss value. A regional estimate of denitrification was produced by multiplying the areal extent of each of the nine soil groups by their annual denitrification N loss value. Loam-textured soils underlie 47% of the regional forest and accounted for 73% of the forest denitrification. Sandy soils were found under 44% of the regional forest but produced only 5% of the regional denitrification. Clay loam soils underlie 9% of the regional forest and produced 22% of the denitrification. Annual denitrification N loss for the region was estimated as 1.4 x 10(7) kg N/yr. We used denitrification enzyme activity (DEA) as a proxy for annual denitrification N loss to determine if the relationship between denitrification and soil texture and natural drainage that we observed at the landscape scale held up at the regional scale. DEA was measured in 22 soils across the region and was strongly related to soil texture and natural drainage (r2 = 0.61), suggesting that extrapolation of data from the landscape to the regional scale was justified.://A1992HX80900004 IISI Document Delivery No.: HX809 Times Cited: 19 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1992HX80900004FGROFFMAN, PM, UNIV RHODE ISL,DEPT NAT RESOURCES SCI,KINGSTON,RI 02881.English c<7Groffman, P. M. Turner, C. L.1995KPlant productivity and nitrogen gas fluxes in a tallgrass prairie landscape255-266Landscape Ecology1054DENITRIFICATION; NITROUS OXIDE; NDVI; REMOTE SENSINGArticleOctWe explored relationships between plant productivity and annual fluxes of nitrogen (N-2) and nitrous oxide (N2O) in a tallgrass prairie landscape in central Kansas. Our objective was to develop predictive relationships between these variables that could be used in conjunction with remote sensing information on plant productivity to produce large-area estimates of N gas fluxes. Our hypothesis was that there are inherent relationships between plant productivity and N gas fluxes in tallgrass prairie because both are controlled by water and N availability. The research was carried out as part of a multi-investigator project, the First ISLSCP Field Experiment (FIFE, ISLSCP = International Satellite Land Surface Climatology Program), directed toward the use of remote sensing to characterize land-atmosphere interactions. Fluxes of N-2 (denitrification) and N2O were measured using soil core techniques. Estimates of annual flux were produced by temporal extrapolation of measured rates. Annual aboveground net primary productivity (ANPP) was estimated from measurements of the maximum standing crop of plant biomass. There were strong relationships between ANPP and N gas fluxes, and between a satellite remote sensing-based index of plant productivity (normalized difference vegetation index, NDVI) and gas fluxes. We used these relationships to convert images of NDVI into images of N gas fluxes for one 83 ha watershed and for the entire 15 by 15 km FIFE site. These images were used to compute mean landscape gas fluxes (0.62 g N m(-2) y(-1) for N-2, 0.66 g N m(-2) y(-1) for N2O) and total N gas production for the two areas. Our flux and production values are useful for comparison with values produced by simulation models and site-specific studies, and for assessing the significance of N gas production to ecosystem and landscape scale processes related to nutrient cycling, water quality and atmospheric chemistry.://A1995TD59500001 IISI Document Delivery No.: TD595 Times Cited: 12 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1995TD59500001=GROFFMAN, PM, INST ECOSYST STUDIES,BOX AB,MILLBROOK,NY 12545.English d|?VJGrondin, Pierre Gauthier, Sylvie Borcard, Daniel Bergeron, Yves Noel, Jean2014lA new approach to ecological land classification for the Canadian boreal forest that integrates disturbances1-16Landscape Ecology291JanTraditional approaches to ecological land classification (ELC) can be enhanced by integrating, a priori, data describing disturbances (natural and human), in addition to the usual vegetation, climate, and physical environment data. To develop this new ELC model, we studied an area of about 175,000 km(2) in the Abies balsamea-Betula papyrifera and Picea mariana-feathermoss bioclimatic domains of the boreal forest of Qu,bec, in eastern Canada. Forest inventory plots and maps produced by the MinistSre des Ressources naturelles du Qu,bec from 1970 to 2000 were used to characterize 606 ecological districts (average area 200 km(2)) according to three vegetation themes (tree species, forest types, and potential vegetation-successional stages) and four sets of explanatory variables (climate, physical environment, natural and human disturbances). Redundancy, cluster (K-means) and variation partitioning analyses were used to delineate, describe, and compare homogeneous vegetation landscapes. The resulting ELC is hierarchical with three levels of observation. Among the 14 homogeneous landscapes composing the most detailed level, some are dominated by relatively young forests originating from fires dating back to the period centered on 1921. In others, forest stands are older (fires from the period centered on 1851), some are under the influence of insect outbreaks and fires (southern part), while the rest are strongly affected by human activities and Populus tremuloides expansion. For all the study area and for parts of it, partitioning reveals that natural disturbance is the dominant data set explaining spatial variation in vegetation. However, the combination of natural disturbances, climate, physical environment and human disturbances always explains a high proportion of variation. Our approach, called "ecological land classification of homogeneous vegetation landscapes", is more comprehensive than previous ELCs in that it combines the concepts and goals of both landscape ecology and ecosystem-based management.!://WOS:000330827600001Times Cited: 1 0921-2973WOS:00033082760000110.1007/s10980-013-9961-2 <7y*Groom, G. Mucher, C. A. Ihse, M. Wrbka, T.2006WRemote sensing in landscape ecology: experiences and perspectives in a European context391-408Landscape Ecology213classification; landscape ecology; landscape information; remote sensing LAND-COVER; AGRICULTURAL LANDSCAPES; VEGETATION STRUCTURE; CLASSIFICATION; PATTERNS; IMAGERY; ISSUES; FOREST; MODEL; MISRArticleAprYThat the relationship between remote sensing and landscape ecology is significant is due in large part to the strong spatial component within landscape ecology. However it is nevertheless necessary to have frequent overview of the interface between remote sensing and landscape ecology, particularly in the light of developments in the types of image data and techniques. The use of remote sensing within European landscape ecology provides a rich range of examples of the interface, including application of some of the latest types of image data. This paper is an overview of the interface that remote sensing has with European landscape ecology, with seven examples of the application of image data in European landscape ecology and examination of associated landscape classification issues. These examples are discussed in terms of the trends and the different roles for image data in landscape ecology that they illustrate, and in particular their classificatory and informational implications. It is suggested that with regard to classification there is a need for re-examination of the roles of image data.://000236968500007  ISI Document Delivery No.: 034ZD Times Cited: 0 Cited Reference Count: 47 Cited References: *COWI A S, 2002, DDO DENM DIG ORTH *EUR VEG SURV, 2003, SYNBIOSYS EUR *NAT ENV RES I, 2000, DAN AR INF SYST ADDINK EA, 2001, THESIS WAGENINGEN U ALLARD A, 2003, AMBIO, V32, P510 ALLARD A, 2003, THESIS STOCKHOLM U S BANKO G, 2003, AGR IMPACTS LANDSCAP, P317 BLASCHKE T, 2003, ADV ECOL SCI, V16, P33 BUGDEN JL, 2004, CAN J REMOTE SENS, V32, P195 BURNETT C, 2003, ECOL MODEL, V168, P233 CHEN JM, 2003, REMOTE SENS ENVIRON, V84, P516 DANSON FM, 1995, ADV ENV REMOTE SENSI, P171 DEBOER M, 2000, 0018 NRSP2 BCRS DIGREGORIO A, 2000, LAND COVER CLASSIFIC FOODY GM, 2004, INT J REMOTE SENS, V25, P2337 FULLER RM, 1994, PHOTOGRAMM ENG REM S, V60, P553 FULLER RM, 2000, CARTOGR J, V30, P15 GERARD F, 2003, INT J REMOTE SENS, V24, P1317 GOBRON N, 2002, IEEE T GEOSCI REMOTE, V40, P1574 GROOM GB, 1996, INT J REMOTE SENS, V17, P69 IHSE M, 1995, LANDSCAPE URBAN PLAN, V31, P21 INGHE O, 2001, STRATEGIC LANDSCAPE, P61 JACOBSEN A, 2000, CAN J REMOTE SENS, V26, P370 JEPSEN JU, 2004, AGR ECOSYST ENVIRON, V105, P581 LAU WL, 2003, INT J REMOTE SENS, V24, P1535 LOFVENHAFT K, 2002, LANDSCAPE URBAN PLAN, V58, P223 LOTSCH A, 2003, INT J REMOTE SENS, V24, P1997 MCMORROW JM, 2004, INT J REMOTE SENS, V25, P313 MUCHER CA, 2000, INT J REMOTE SENS, V21, P1159 MUCHER CA, 2004, 952 ALT PETERSEIL J, 2004, LAND USE POLICY, V21, P307 ROGAN J, 2004, PROG PLANN 4, V61, P301 SAWAYA KE, 2003, REMOTE SENS ENVIRON, V88, P144 SOKAL RR, 1974, SCIENCE, V185, P1115 STEINWENDNER J, 1998, INT ARCH PHOTOGRAMME, V32, P265 SUPPAN F, 1997, P GEOSPATIAL INFORM, V4, P673 SUPPAN F, 1999, NATURE CULTURE LANDS, P327 TAFT OW, 2003, ENVIRON MANAGE, V32, P268 THUNNISSEN HAM, 1992, INT J REMOTE SENS, V13, P1693 THUNNISSEN HAM, 1997, 9620 BCRS TOPPING CJ, 2003, ECOL MODEL, V167, P65 VANDERMEER FD, 2000, 19999936 USP2 BCRS WAGNER W, 2003, REMOTE SENS ENVIRON, V85, P125 WEIERS S, 2002, GEOGRAFISK TIDSSKRIF, V102, P59 WRBKA T, 1999, ADV ECOL SCI, V2, P209 WRBKA T, 1999, OPERATIONAL REMOTE S, P119 WU JG, 2002, LANDSCAPE ECOL, V17, P355 0921-2973 Landsc. Ecol.ISI:000236968500007Natl Env Res Inst, Dept Wildlife Ecol & Biodivers, DK-8410 Kaloe, Roende, Denmark. Alterra Green World Res, Ctr Geoinformat, Wageningen, Netherlands. Univ Stockholm, Unit Ecol Geog, Dept Phys Geog & Quaternary Geol, S-10691 Stockholm, Sweden. Univ Vienna, Inst Ecol & Conservat Biol, A-1010 Vienna, Austria. Groom, G, Natl Env Res Inst, Dept Wildlife Ecol & Biodivers, Grenaavej 14, DK-8410 Kaloe, Roende, Denmark. gbg@dmu.dkEnglish$??CGross, John E. Zank, Colleen Hobbs, N.Thompson Spalinger, Donald E.1995fMovement rules for herbivores in spatially heterogeneous envionments: responses to small scale pattern209-217Landscape Ecology1049Foraging, random walk, spatial heterogeneity, search rule|7U 3Gross, J. E. Zank, C. Hobbs, N. T. Spalinger, D. E.1995hMovement Rules for Herbivores in Spatially Heterogeneous Environments - Responses to Small-Scale Pattern209-217Landscape Ecology1046foraging random walk spatial heterogeneity search ruleAug.Foraging herbivores respond to the spatial pattern of resources at a variety of scales. At small scales of space and time, existing models capture the essence of the feeding process and successfully predict intake rates. Models that operate over larger scales have not exhibited a similar success, in part because we have a limited understanding of the rules used by animals to make decisions in spatially complex environments, or of the consequences of departing from these rules. To evaluate the rules that large herbivores use when navigating between forages, we examined movements of bighorn sheep foraging on apparent prey (alfalfa plants) in hand-constructed patches of plants. Observations of movements and path lengths were compared to simulations that used a variety of different rules-of-thumb to determine a search path. Rules used in simulations ranged from a random walk with various detection distances, to more complicated rules that solved a variant of the travelling salesman problem. Simulations of a random walk yielded movement lengths that exceeded observations by a factor of 3 for long detection distances, and by 30-fold for short detection distances. Observed move distances were most closely approximated by simulations based on a nearest-neighbor rule - over 75% of all moves by bighorn sheep were to the closest available plant. Movement rules based on random walks are clearly inappropriate for many herbivores that typically consume visually apparent plants, and we suggest the use of a nearest-neighbor rule for modelling foraging by large herbivores.://A1995RP98800003-Rp988 Times Cited:51 Cited References Count:0 0921-2973ISI:A1995RP98800003GGross, Je Colorado State Univ,Nat Resource Ecol Lab,Ft Collins,Co 80523EnglishM~?MLGrossinger, R. M. Striplen, C. J. Askevold, R. A. Brewster, E. Beller, E. E.2007pHistorical landscape ecology of an urbanized California valley: wetlands and woodlands in the Santa Clara Valley103-120Landscape Ecology22Historical records provide information to land managers and landscape ecologists attempting to understand current trajectories in altered landscapes. In this study, we synthesized a heterogeneous array of historical sources to reconstruct historical land cover in California's Santa Clara Valley (a.k.a. "Silicon Valley"). To increase and assess accuracy, we used the triangulation of overlapping, independent data sources and the application of certainty level standards. The region has been subject to extensive urbanization, so we also evaluated the applicability of historical landscape reconstructions to the altered landscape. We found evidence for five major land cover types prior to significant Euro-American modification. Valley freshwater marsh, wet meadow, alkali meadow, willow grove, and valley oak savanna have all experienced extreme decline (85-100%) since Euro-American settlement. However, comparison of historical land cover patterns to contemporary land use suggested several new strategies for environmental recovery, despite the limitations of surrounding urbanization. We also observed a temporal shift in riparian habitat along the mainstem of Coyote Creek, from a relatively open mixture of riparian scrub, sycamore woodland, and unvegetated gravel bars to dense riparian forest, likely resulting from stream flow regulation. By identifying former land cover patterns we provide a basis for evaluating local landscape change and setting restoration targets, including the identification of residual features and under-recognized land cover types. These findings suggest that reliable historical landscape reconstructions can be developed in the absence of standardized historical data sources and can be of value even in highly modified regions."://WOS:000251543600008 Times Cited: 0WOS:00025154360000810.1007/s10980-007-9122-6!~?I!Grossmann, E. B. Mladenoff, D. J.2007}Open woodland and savanna decline in a mixed-disturbance landscape (1938 to 1998) in the Northwest Wisconsin (USA) Sand Plain43-55Landscape Ecology22Our research illustrates how a landscape mosaic changes in association with a mixed natural-anthropogenic disturbance history. Our study area is the Northwest Wisconsin (USA) Sand Plain (NWSP), a region with a rich disturbance history including fire, insects and clearcut forestry. We integrated historic airphotos from 1938, 1960, 1980 and 1998 within a GIS to describe change among four landcover classes describing a canopy-closure gradient: closed forests, woodlands, savannas and "open barrens". Our work addresses two literature needs: empirical studies of mixed-disturbance landscapes, and nonforest habitats within a forest matrix. Our analysis shows that: the area of open barrens fluctuated, woodlands and savannas declined severely and closed forests increased through time. Falling median patch sizes and other landscape metrics suggest that the woodlands are becoming more fragmented. The landcover transitions driving this change vary according to time and place. The dominant transitions are toward closed forests from all classes, and transitions toward open barrens are also consistently important. The woodlands, savannas and open barrens habitats are mostly comprised of transient patches, persisting for less than 20 years. This contrasts with closed forests that often persist for 40 plus years. These changes are consistent with the disturbance regime that is shifting from fire- to forestry-dominance. Our results show a trend towards landscape simplification, manifest as losses of intermediate-density habitats (woodland and savanna) and shrinking patch sizes. The transient nature of the nonforest habitats shows that disturbance resulting in total or partial canopy removal will be vital for their conservation at a landscape scale."://WOS:000251543600004 Times Cited: 0WOS:00025154360000410.1007/s10980-007-9113-7W<7!Gu, W. D. Heikkila, R. Hanski, I.2002]Estimating the consequences of habitat fragmentation on extinction risk in dynamic landscapes699-710Landscape Ecology178boreal forest connectivity habitat loss metapopulation dynamics regional stochasticity METAPOPULATION DYNAMICS MODELS FORESTS CONNECTIVITY CONTINUITY CAPACITY FUNGUSArticleDecAnalyzing the population dynamic consequences of spatio-temporal changes in landscape structure is a formidable challenge for spatial ecology. One key population dynamic process in fragmented landscapes is the influence of isolation on colonization rate and thereby on the occurrence of species in habitat fragments, but it is not obvious how isolation should be measured in landscapes that are affected by on-going habitat loss and fragmentation. We suggest the following procedure for the measurement of spatio-temporal isolation. First, a historical record of habitat loss and fragmentation in the landscape is prepared based on snapshots of the extent of the suitable habitat for the focal species. Second, a metapopulation model is used to simulate the occurrence of the species in this landscape, assuming the empirically observed landscape change. The model-predicted pattern of habitat occupancy at a particular point in time (usually the present time) is then compared with empirical observations on the occurrence of the species. We describe a metapopulation model that has been constructed for this purpose, and we apply it to a changing landscape of boreal forests in eastern Finland. We give an example on the occurrence of four threatened polyporous fungi in 18 small fragments of old-growth forest. In none of the species does the current isolation of the fragments nor the time since their isolation explain the occurrence of the species in the study fragments, but in three species the model-predicted occupancy probability had a significant effect on the observed abundance of the species. The model-predicted occupancy probabilities were also calculated by ignoring past landscape changes, that is, by assuming that the landscape had remained in the present configuration for a long time. These probabilities had a significant effect on the abundance of only one of the four species, suggesting that the occurrence of the species tracks landscapes changes with a noticable time lag.://000181767400003 zISI Document Delivery No.: 659FV Times Cited: 19 Cited Reference Count: 41 Cited References: BADER P, 1995, BIOL CONSERV, V72, P355 BERG A, 1994, CONSERV BIOL, V8, P718 BROOKS TM, 1999, CONSERV BIOL, V13, P1140 DEBINSKI DM, 2000, CONSERV BIOL, V14, P342 DOAK DF, 1994, ECOLOGY, V75, P615 ESSEEN PA, 1992, ECOLOGICAL PRINCIPLE, P252 FOLEY P, 1997, METAPOPULATION BIOL, P215 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 HANSKI I, 1991, BIOL J LINN SOC, V42, P17 HANSKI I, 1994, J ANIM ECOL, V63, P151 HANSKI I, 1996, CONSERV BIOL, V10, P578 HANSKI I, 1998, NATURE, V396, P41 HANSKI I, 1999, METAPOPULATION ECOLO HANSKI I, 1999, OIKOS, V87, P209 HANSKI I, 2000, NATURE, V404, P755 HARRIS LD, 1984, FRAGMENTED FOREST HARRISON S, 1989, OIKOS, V56, P1 HECKERT JR, 1994, ECOLOGICAL APPL, V4, P461 HEYWOOD VH, 1995, GLOBAL BIODIVERSITY KOMONEN A, 2000, OIKOS, V90, P119 LOVEJOY TE, 1984, EXTINCTIONS, P295 MACARTHUR TH, 1967, THEORY ISLAND BIOGEO MARGULES CR, 1996, SPECIES SURVIVAL FRA, P93 MAY RM, 1995, EXTINCTION RATES MILNE BT, 1991, QUANTITATIVE METHODS, P199 MOILANEN A, 1998, AM NAT, V152, P530 MOILANEN A, 1999, ECOLOGY, V80, P1031 MOILANEN A, 2000, J ANIM ECOL, V69, P143 OHLSON M, 1997, BIOL CONSERV, V81, P221 OVASKAINEN O, 2001, THEOR POPUL BIOL, V60, P281 OVASKAINEN O, 2002, THEOR POPUL BIOL, V61, P285 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 ROBINSON GR, 1992, SCIENCE, V257, P524 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SETTELE J, 1996, SPECIES SURVIVAL FRA TERBRAAK JF, 1998, MODELING SPATIOTEMPO, P167 TILMAN D, 1994, NATURE, V371, P65 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 WAHLBERG N, 2002, ECOGRAPHY, V25, P224 0921-2973 Landsc. Ecol.ISI:0001817674000031Univ Helsinki, Dept Systemat & Ecol, Metapopulat Res Grp, FIN-00014 Helsinki, Finland. Kainuu Reg Environm Ctr, Res Ctr Friendship Pk, FIN-88900 Kuhmo, Finland. Hanski, I, Univ Helsinki, Dept Systemat & Ecol, Metapopulat Res Grp, POB 65,Viikinkaari 1, FIN-00014 Helsinki, Finland. ilkka.hanski@helsinki.fiEnglish <7S .Gu, Y. X. Howard, D. M. Wylie, B. K. Zhang, L.2012jMapping carbon flux uncertainty and selecting optimal locations for future flux towers in the Great Plains319-326Landscape Ecology273net ecosystem production (nep) regression tree models extrapolation mean absolute difference flux tower location great plains conterminous united-states combining modis ameriflux data co2 flux ecosystem variability respirationMar}Flux tower networks (e.g., AmeriFlux, Agriflux) provide continuous observations of ecosystem exchanges of carbon (e.g., net ecosystem exchange), water vapor (e.g., evapotranspiration), and energy between terrestrial ecosystems and the atmosphere. The long-term time series of flux tower data are essential for studying and understanding terrestrial carbon cycles, ecosystem services, and climate changes. Currently, there are 13 flux towers located within the Great Plains (GP). The towers are sparsely distributed and do not adequately represent the varieties of vegetation cover types, climate conditions, and geophysical and biophysical conditions in the GP. This study assessed how well the available flux towers represent the environmental conditions or "ecological envelopes" across the GP and identified optimal locations for future flux towers in the GP. Regression-based remote sensing and weather-driven net ecosystem production (NEP) models derived from different extrapolation ranges (10 and 50%) were used to identify areas where ecological conditions were poorly represented by the flux tower sites and years previously used for mapping grassland fluxes. The optimal lands suitable for future flux towers within the GP were mapped. Results from this study provide information to optimize the usefulness of future flux towers in the GP and serve as a proxy for the uncertainty of the NEP map.://000300087500001-889QE Times Cited:0 Cited References Count:21 0921-2973Landscape EcolISI:000300087500001Gu, Yx US Geol Survey USGS, Earth Resources Observat & Sci EROS, ASRC Res & Technol Solut, 47914 252nd St, Sioux Falls, SD 57198 USA US Geol Survey USGS, Earth Resources Observat & Sci EROS, ASRC Res & Technol Solut, 47914 252nd St, Sioux Falls, SD 57198 USA US Geol Survey USGS, Earth Resources Observat & Sci EROS, ASRC Res & Technol Solut, Sioux Falls, SD 57198 USA Stinger Ghaffarian Technol Inc, USGS EROS, Sioux Falls, SD 57198 USA Chinese Acad Sci, Key Lab Digital Earth, Ctr Earth Observat & Digital Earth, Beijing, Peoples R ChinaDOI 10.1007/s10980-011-9699-7English |74Guil, N. Hortal, J. Sanchez-Moreno, S. Machordom, A.2009Effects of macro and micro-environmental factors on the species richness of terrestrial tardigrade assemblages in an Iberian mountain environment375-390Landscape Ecology243)altitude climate diversity gradients iberian peninsula leaf litter soil tardigrada communities vegetation structure abundance scale humid tropical forest ecological distribution community structure bdelloid rotifers invertebrate communities microscopic animals puerto-rico diversity patterns scaleMarBTardigrade communities are affected by micro and macro-environmental conditions but only micro-environmental variables, and altitudinal gradients have been studied. We review previous reports of altitudinal effects and evaluate the influence by interacting macro- (climate, soils, biome, and others) and micro-environmental (vegetation, moss and leaf litter) factors on tardigrade assemblages at the Sierra de Guadarrama mountain range (Iberian Central System Mountains, Spain). Terrestrial tardigrade assemblages were sampled using standard cores to collect leaf litter and mosses growing on rocks. General Linear Models were used to examine relationships between Tardigrada species richness and abundance, and macro- and micro-environmental variables (altitude, habitat characteristics, local habitat structure and dominant leaf litter type, and two bioclimatic classifications). Variation partitioning techniques were used to separate the effects of altitude and habitat variation, and to quantify the independent influences of climate and soil, vegetation structure and dominant type of leaf litter. Altitude shows a unimodal relationship with tardigrade species richness, although its effect independent of habitat variation is negligible. The best predictors for species richness were bioclimatic classifications. Separate and combined effects of macro-environmental gradients (soil and climate), vegetation structure and leaf litter type are important determinants of richness. A model including both macro- and micro-environmental variables explained nearly 60% of tardigrade species richness in micro-scale plots. Abundance was significantly related only to soil composition and leaf litter type. Tardigrade abundance was not explained by macro-environmental gradients analysed here, despite a significant correlation between abundance and richness.://000263419500007-408EY Times Cited:0 Cited References Count:71 0921-2973ISI:000263419500007Guil, N Univ Copenhagen, Nat Hist Museum, Zool Museum, Univ Parken 15, DK-2100 Copenhagen OE, Denmark Univ Copenhagen, Nat Hist Museum, Zool Museum, DK-2100 Copenhagen OE, Denmark Univ London Imperial Coll Sci Technol & Med, Div Biol, NERC Ctr Populat Biol, Ascot SL5 7PY, Berks, England CSIC, Museo Nacl Ciencias Nat, Dept Biodiversidad & Biol Evolutiva, E-28006 Madrid, Spain Inst Nacl Invest & Tecnol Agr & Alimentaria INIA, Dept Protecc Vegetal, Madrid, SpainDoi 10.1007/S10980-008-9312-XEnglish<7"Guirado, M. Pino, J. Roda, F.2007Comparing the role of site disturbance and landscape properties on understory species richness in fragmented periurban Mediterranean forests117-129Landscape Ecology221Mforest condition; forest fragmentation; forest patches; human-induced disturbance; multiple linear regressions; patch history; plant species richness; synanthropic species WESTERN CARPATHIAN FOOTHILLS; HABITAT FRAGMENTATION; WOODLAND PATCHES; HERBACEOUS-LAYER; PLANT DIVERSITY; LAND-USE; CONSERVATION; VEGETATION; ROADS; BIODIVERSITYArticleJan2We hypothesized that the spatial configuration and dynamics of periurban forest patches in Barcelona (NE of Spain) played a minor role in determining plant species richness and assemblage compared to site conditions, and particularly to both direct (measured at plot level) and potential (inferred from landscape metrics) human-associated site disturbance. The presence of all understory vascular plants was recorded on 252 plots of 100 m(2) randomly selected within forest patches ranging in size from 0.25 ha to 218 ha. Species were divided into 6 groups, according to their ecology and conservation status. Site condition was assessed at plot level and included physical attributes, human-induced disturbance and Quercus spp. tree cover. Landscape structure and dynamics were assessed from patch metrics and patch history. We also calculated a set of landscape metrics related to potential human accessibility to forests. Results of multiple linear regressions indicated that the variance explained for non-forest species groups was higher than for forest species richness. Most of the main correlates corresponded to site disturbance variables related to direct human alteration, or to landscape variables associated to indirect human effects on forests: Quercus tree cover (a proxy for successional status) was the most important correlate of non-forest species richness, which decreased when Quercus tree cover increased. Human-induced disturbance was an important correlate of synanthropic and total species richness, which were higher in recently managed and in highly frequented forests. Potential human accessibility also affected the richness of most species groups. In contrast, patch size, patch shape and connectivity played a minor role, as did patch history. We conclude that human influence on species richness in periurban forests takes place on a small scale, whereas large-scale effects attributable to landscape structure and fragmentation are comparatively less important. Implications of these results for the conservation of plant species in periurban forests are discussed.://000243619800011 ISI Document Delivery No.: 127XO Times Cited: 0 Cited Reference Count: 74 Cited References: BASCOMPTE J, 2001, ECOL LETT, V4, P417 BOLOS O, 1990, FLORA MANUAL PAISOS BROSOFSKE KD, 2001, FOREST ECOL MANAG, V146, P75 BROTHERS TS, 1992, CONSERV BIOL, V6, P91 CLIFF AD, 1981, SPATIAL PROCESSES MO DECONCHAT M, 2001, ANN FOR SCI, V58, P315 DZWONKO Z, 1988, VEGETATIO, V76, P15 DZWONKO Z, 1989, OIKOS, V56, P77 DZWONKO Z, 1992, J BIOGEOGR, V19, P195 ELKIE P, 1999, PATCH ANAL USERS MAN ERIKSSON O, 1996, OIKOS, V77, P248 FAHRIG L, 2003, ANNU REV ECOL EVOL S, V34, P487 FORMAN RTT, 1992, LANDSCAPE BOUNDARIES, P236 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FORMAN RTT, 1998, ANNU REV ECOL SYST, V29, P207 FORTIN MJ, 1989, VEGETATIO, V83, P209 GIBB H, 2002, BIOL CONSERV, V106, P91 GILLIAM FS, 1995, ECOL APPL, V5, P947 GILLIAM SF, 2002, FOREST ECOL MANAG, V155, P3 GODEFROID S, 2003, GLOBAL ECOL BIOGEOGR, V12, P287 GODEFROID S, 2004, BIOL CONSERV, V119, P405 GONDARD H, 2001, BIODIVERS CONSERV, V10, P189 GRACIA C, 2000, INVENTARI ECOLOGIC F, V5 GRAHAM MH, 2003, ECOLOGY, V84, P2809 GRASHOFBOKDAM C, 1997, J VEG SCI, V8, P21 GROVE AT, 1996, MEDITERRANEAN DESERT GUIRADO M, 2002, THESIS CREAF BARCELO GUIRADO M, 2006, GLOBAL ECOL BIOGEOGR, V15, P50 HANSKI I, 1999, METAPOPULATION ECOLO HARRIS LD, 1988, CONSERV BIOL, V2, P330 HARRISON S, 1999, ECOGRAPHY, V22, P225 HERSPERGER AM, 2003, OIKOS, V101, P279 HOBBS ER, 1988, LANDSCAPE ECOLOGY, V1, P141 HOBBS RJ, 2000, INVASIVE SPECIES CHA, P385 HOLT RD, 1995, ECOLOGY, V76, P1610 HONNAY O, 1999, BIOL CONSERV, V87, P73 HONNAY O, 1999, FOREST ECOL MANAG, V115, P157 HONNAY O, 2002, BIODIVERS CONSERV, V11, P213 INGHE O, 1985, OIKOS, V45, P400 JACQUEMYN H, 2003, ECOGRAPHY, V26, P768 JELINSKI DE, 1992, AM J BOT, V79, P728 LEGENDRE P, 2002, ECOGRAPHY, V25, P601 LEVENSON JB, 1981, FOREST ISLAND DYNAMI, P13 LUKEN JO, 1991, LANDSCAPE URBAN PLAN, V20, P315 MAESTRE FT, 2004, DIVERS DISTRIB, V10, P21 MCDONNELL MJ, 1990, ECOLOGY, V71, P1232 MCKINNEY ML, 2002, BIOSCIENCE, V52, P883 MEFFE R, 1994, PRINCIPLES CONSERVAT MOFFATT SF, 2004, PLANT ECOL, V174, P119 MOONEY AH, 1988, BIODIVERSITY, P156 MURCIA C, 1995, TRENDS ECOL EVOL, V10, P58 PARENDES LA, 2000, CONSERV BIOL, V14, P64 PARROTTA JA, 2002, FOREST ECOL MANAG, V169, P243 PAUCHARD A, 2004, CONSERV BIOL, V18, P1 PETERKEN GF, 1984, J ECOL, V72, P155 PETIT S, 2004, LANDSCAPE ECOL, V19, P463 PONS X, 2000, MIRAMON SISTEMA INFO PYSEK P, 1998, J BIOGEOGR, V25, P155 ROBERTS MR, 1995, J VEG SCI, V6, P903 ROSS KA, 2002, J BIOGEOGR, V29, P749 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SELMANTS PC, 2003, FOREST ECOL MANAG, V185, P275 SPELLERBERG IF, 1998, GLOBAL ECOL BIOGEOGR, V7, P317 TELLERIA JL, 1999, ECOGRAPHY, V22, P13 TROMBULAK SC, 2000, CONSERV BIOL, V14, P18 VANRUREMONDE RHAC, 1991, J VEG SCI, V2, P377 VELLEND M, 2003, ECOLOGY, V84, P1158 VERDU JR, 2000, BIODIVERS CONSERV, V9, P1707 VERHEYEN K, 2004, ECOLOGY, V85, P3302 WATKINS RZ, 2003, CONSERV BIOL, V17, P411 WHITTAKER RJ, 2001, J BIOGEOGR, V16, P3 WIENS JA, 1992, LANDSCAPE BOUNDRIES, P216 WILCOVE DS, 1986, CONSERVATION BIOL SC, P237 WOOD A, 2000, ROOT CAUSES BIODIVER 0921-2973 Landsc. Ecol.ISI:000243619800011Autonomous Univ Barcelona, Ctr Ecol Res & Forestry Applicat CREAF, E-08193 Bellaterra, Spain. Univ Barcelona, Dept Plant Biol, E-08028 Barcelona, Spain. Guirado, M, Autonomous Univ Barcelona, Ctr Ecol Res & Forestry Applicat CREAF, E-08193 Bellaterra, Spain. m.guirado@creaf.uab.esEnglish#|? Guo, Qinfeng2014KSpecies invasions on islands: searching for general patterns and principles 1123-1131Landscape Ecology297AugNumerous islands worldwide are being increasingly invaded by exotic species. However, the effects of invading species on native floras remain underexplored, particularly whether island biogeography theory is applicable to native, exotic, and the newly assembled floras. Inter-group comparisons across different regions or island groups through a collection of individual studies have the potential of offering additional insights. Here, I comparatively analyze 10 datasets involving bird and plant invasions on nine island groups around the world and make detailed comparisons between two sets. I show that, although similarities exist, different taxonomic groups and different geographic settings exhibit drastically different invasion patterns on islands. Island biogeography theory still better explains native and overall (natives plus exotics) diversity patterns, such as the species-area-isolation relationships. In contrast, the corresponding patterns for exotic species are highly variable. The varying degrees of human intervention in species invasion relative to natural dispersal on different islands, along with differences between taxonomic groups, highlight the challenges of searching general patterns and applying island biogeography theories to island invasion and conservation.!://WOS:000339831300003Times Cited: 0 0921-2973WOS:00033983130000310.1007/s10980-014-0059-2$<7l.Guo, Z. W. Xiao, X. M. Gan, Y. L. Zheng, Y. J.2003Landscape planning for a rural ecosystem: case study of a resettlement area for residents from land submerged by the Three Gorges Reservoir, China503-512Landscape Ecology185ecoregion landscape planning land use multi-criteria optimal spatial planning rural ecosystem spatial pattern trade-off analysis RESTORATION ENVIRONMENT MANAGEMENT FRAMEWORK SERVICES WILDLIFE GISArticle;The goals of landscape planning are multiple for rural ecosystems of the resettlement area in the Hubei Province of China. They relate to the types, diversity and patterns of the ecosystems, and to the conservation of ecosystem functions and biodiversity. We were interested in the improvement of socio-economic conditions, and the promotion of the development of farmland ecosystems and natural forest ecosystems. The landscape planning took into account the conservation and the restoration of forestlands, and the reconstructions of farmlands, towns and villages. The areas of towns and villages were assigned by trade-off analysis balancing ecological, economic and social benefits. The spatial pattern of used lands was designed by a multi-criteria optimal spatial planning, resulting in the strengthening of some primary ecosystem functions. In the resettlement area forests will expand to a matrix, and cropland patches together with tree fences will form patch-corridor systems. Significant ecological, economic and social benefits can be derived from this landscape pattern.://000185827200004 &ISI Document Delivery No.: 730JG Times Cited: 0 Cited Reference Count: 33 Cited References: *BLMXC, 1995, SIT LAND US XINGSH C *BSXC, 1999, UNPUB NAT EC STAT DA *CYR, 1992, UNPUB REP ENV PLANN *ESRI, 1994, UND GIS ARC INFO MET BENNETT AF, 1990, LANDSCAPE ECOL, V4, P109 BROWN S, 1994, J ENVIRON MANAGE, V42, P349 BRYCE SA, 1996, ENVIRON MANAGE, V20, P297 BUREL F, 1990, LANDSCAPE ECOL, V4, P197 COSTANZA R, 1997, NATURE, V387, P253 CUSHMAN JH, 1995, NY TIMES 0122, P5 FEDOROWICK JM, 1993, LANDSCAPE URBAN PLAN, V27, P7 FORMAN R, 1986, LANDSCAPE ECOLOGY FORMAN R, 1995, LAND MOSAICS ECOLOGY FRANKLIN JF, 1993, ECOL APPL, V3, P202 GRUMBINE RE, 1994, CONSERV BIOL, V8, P27 GUO Z, 1998, J NATURAL RESOURCES, V13, P31 GUO Z, 2001, ECOLOGICAL EC, V139, P141 GUO ZW, 2000, ECOL APPL, V10, P925 HARRIS LD, 1989, PRESERVING COMMUNITI, P11 HENRY CP, 1995, ENVIRON MANAGE, V19, P903 HOBBS R, 1991, J ENVIRON MANAGE, V2, P161 KAY JJ, 1994, ALTERNATIVES, V20, P32 KONDOH K, 1993, EKISTICS, V60, P152 LEE RG, 1992, WATERSHED MANAGEMENT, P499 MORRIN M, 2002, INT J COLORECTAL DIS, V17, P30 PECCOL E, 1996, J ENVIRON MANAGE, V47, P355 SAMPLE VA, 1994, AM FOR, V100, P6 SLOCOMBE DS, 1993, ENVIRON MANAGE, V17, P289 SLOCOMBE DS, 1998, ENVIRON MANAGE, V22, P483 SOLLER DR, 1994, GEOTIMES, V39, P12 VITOUSEK PM, 1997, SCIENCE, V277, P494 WYANT JG, 1995, ENVIRON MANAGE, V19, P789 ZANABONI A, 1989, AGR ECOSYST ENVIRON, V27, P155 0921-2973 Landsc. Ecol.ISI:000185827200004Chinese Acad Sci, Inst Zool, State Key Lab Integrated Management Pest Insects, Beijing 100080, Peoples R China. Univ New Hampshire, Inst Study Earth Oceans & Space, Complex Syst Res Ctr, Durham, NH 03824 USA. Inst Stat Math, Minato Ku, Tokyo 1068569, Japan. Gan, YL, Chinese Acad Sci, Inst Zool, State Key Lab Integrated Management Pest Insects, 19 Zhongguancun Rd, Beijing 100080, Peoples R China.English? Gustafson, Eric20119Publishing landscape ecology research in the 21st century 1351-1354Landscape Ecology2610Springer NetherlandsEarth and Environmental Science+http://dx.doi.org/10.1007/s10980-011-9638-7 0921-297310.1007/s10980-011-9638-7$?T Gustafson, Eric2012JD. McKenzie, C. Miller and D.A. Falk (eds.): The Landscape Ecology of Fire925-926Landscape Ecology276Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9733-4 0921-297310.1007/s10980-012-9733-4۽7 Gustafson, EricJ2013+Using expert knowledge in landscape ecology365-366Landscape Ecology282Springer Netherlands 2013/02/01+http://dx.doi.org/10.1007/s10980-012-9824-2 0921-2973Landscape Ecol10.1007/s10980-012-9824-2Englishڽ7#Gustafson, EricJ2013When relationships estimated in the past cannot be used to predict the future: using mechanistic models to predict landscape ecological dynamics in a changing world 1429-1437Landscape Ecology288Springer NetherlandsLandscape modeling Forests Disturbances Climate change Global changes Mechanistic modeling Empirical modeling Phenomenological modeling 2013/10/01+http://dx.doi.org/10.1007/s10980-013-9927-4 0921-2973Landscape Ecol10.1007/s10980-013-9927-4Englishڽ75BGustafson, EricJ Kubiske, MarkE Sturtevant, BrianR Miranda, BrianR2013GScaling Aspen-FACE experimental results to century and landscape scales 1785-1800Landscape Ecology289Springer NetherlandswAspen-FACE Scaling Global change Ozone pollution Forest composition Carbon dynamics Forest landscape modeling LANDIS-II 2013/11/01+http://dx.doi.org/10.1007/s10980-013-9921-x 0921-2973Landscape Ecol10.1007/s10980-013-9921-xEnglish?AyGustafson, E.J. T.R. Crow1994yModeling the effects of forest harvesting on landscape structure and the spatial distribution of cowbird brood parasitism237-248Landscape Ecology94}spatial pattern, timber harvest, clearcutting, GIS model, habitat fragmentation, forest interior, forest edge, ERDAS, GISfrag k|7i Gustafson, E. J. Crow, T. R.1994yModeling the Effects of Forest Harvesting on Landscape Structure and the Spatial-Distribution of Cowbird Brood Parasitism237-248Landscape Ecology94spatial pattern timber harvest clearcutting gis model habitat fragmentation forest interior forest edge brown-headed cowbird brood parasitism neotropical migratory birdsDecTimber harvesting affects both composition and structure of the landscape and has important consequences for organisms using forest habitats. A timber harvest allocation model was constructed that allows the input of specific rules to allocate forest stands for clearcutting to generate landscape patterns reflecting the ''look and feel'' of managed landscapes. Various harvest strategies were simulated on four 237 km2 study areas in Indiana, USA. For each study area, the model was applied to simulate 80 years of management activity. The resulting landscape spatial patterns were quantified using a suite of landscape pattern metrics and plotted as a function of mean harvest size and total area of forest harvested per decade to produce response surfaces. When the mean clearcut size was 1 ha, the area of forest interior remaining on the landscape was dramatically reduced and the amount of forest edge on the landscape increased dramatically. The potential consequences of the patterns produced by the model were assessed for a generalized neotropical migrant forest bird using a GIS model that generates maps showing the spatial distribution of the relative vulnerability of forest birds to brood parasitism by brown-headed cowbirds. The model incorporates the location and relative quality of cowbird feeding sites, and the relation between parasitism rates and distance of forest from edge. The response surface relating mean harvest size and total area harvested to the mean value of vulnerability to cowbird brood parasitism had a shape similar to the response surfaces showing forest edge. The results of our study suggest that it is more difficult to maintain large contiguous blocks of undisturbed forest interior when harvests are small and dispersed, especially when producing high timber volumes is a management goal. The application of the cowbird model to landscapes managed under different strategies could help managers in deciding where harvest activity will produce the least negative impact on breeding forest birds.://A1994PX89500001-Px895 Times Cited:43 Cited References Count:0 0921-2973ISI:A1994PX89500001bGustafson, Ej Purdue Univ,N Centr Forest Exptl Stn,1158 Entomol Bldg,Room 220,W Lafayette,in 47907Englishg<7;Gustafson, E. J. Hammer, R. B. Radeloff, V. C. Potts, R. S.2005The relationship between environmental amenities and changing human settlement patterns between 1980 and 2000 in the midwestern USA773-789Landscape Ecology207causes of change; ecological amenities; environmental perceptions; housing density; human settlement patterns; landscape change; predictive model RESIDENTIAL PREFERENCES; UNITED-STATES; GROWTH; CONVERGENCE; LANDSCAPES; WISCONSIN; MODELS; INDEXArticleNov2 Natural resource amenities may be an attractor as people decide where they will live and invest in property. In the American Midwest these amenities range from lakes to forests to pastoral landscapes, depending on the ecological province. We used simple linear regression models to test the hypotheses that physiographic, land cover (composition and spatial pattern), forest characteristics, land use on undeveloped land, public ownership, soil productivity and proximity to urban centers predict changes in population, housing, and seasonal housing densities over a 10-year interval (1980-1990). We then generated multiple-regression models to predict population, total and seasonal housing density change in the most recent decade (1990-2000) based on ownership and ecological conditions in 1990 and tested them by comparing the predictions to actual change measured by the US Census Bureau. Our results indicate that the independent variables explained between 25 and 40% of the variability in population density change, 42-67% of the variability of total housing density change, and 13-32% of the variability in seasonal housing density change in the 1980s, depending on the province. The strength of the relationships between independent and dependent variables varied by province, and in some cases the sign varied as well. Topographic relief was significantly related to population growth in all provinces, and land cover composition and the presence of water was significantly related to total housing growth in all provinces. There was a surprisingly limited association of any of the independent variables to seasonal housing growth in the northern province, which is commonly perceived to attract seasonal use because of ecological amenities. Proximity to urban centers is related to population and housing density change, but not seasonal housing density change. Our tests indicated that models for population density change showed some utility, but the models for total and seasonal housing density generally performed poorly. Ecologic variables were consistently poor at predicting seasonal housing density change. Our results show that environmental characteristics appear to have some influence on the spatial distribution of population and housing change in the Midwest, although other factors that were not modeled are clearly dominant.://000233036300001 ISI Document Delivery No.: 980RQ Times Cited: 1 Cited Reference Count: 46 Cited References: *USDA, 1994, MISC PUB USDA, V1492 *USGS, 1990, US GEOL SURV DAT US, V5 AHN S, 2000, FOREST SCI, V46, P363 ANSELIN L, 1988, SPATIAL ECONOMETRICS ANSELIN L, 1991, GEOGR ANAL, V23, P112 BAILEY TC, 1995, INTERACTIVE SPATIAL BOARNET MG, 1998, J REGIONAL SCI, V38, P381 BURRIDGE P, 1980, J ROYAL STAT SOC B, V42, P107 CARLINO GA, 1996, REG SCI URBAN ECON, V26, P565 DELLER SC, 2001, AM J AGR ECON, V83, P352 DENT JB, 1979, SYSTEMS SIMULATION A FORTIN MJ, 1999, LANDSCAPE ECOLOGICAL, P253 FOSTER DR, 1992, J ECOL, V80, P753 FUGUITT GV, 1975, DEMOGRAPHY, V12, P491 FUGUITT GV, 1990, DEMOGRAPHY, V27, P589 GOBSTER PH, 2000, J FOREST, V98, P9 GRIFFITH DA, 1996, PRACTICAL HDB SPATIA, P1 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HAMMER RB, 2002, 200213 U WISC CTR DE HAMMER RB, 2004, LANDSCAPE URBAN PLAN, V69, P183 HENRY MS, 1997, J REGIONAL SCI, V37, P479 HENRY MS, 2001, INT REGIONAL SCI REV, V24, P171 JOHNSON KM, 2000, RURAL SOCIOL, V65, P27 KEYS J, 1995, ECOLOGICAL UNITS E U LEE J, 2001, STAT ANAL ARC VIEW G LESAGE JP, 1997, J REGIONAL ANAL POLI, V27, P83 LI HB, 1993, LANDSCAPE ECOL, V8, P155 LONG L, 1997, PROF GEOGR, V49, P431 MARCOUILLER DW, 2002, J PLAN LIT, V16, P515 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MCGARIGAL K, 2002, FRAGSTATS SPATIAL PA MCGRANAHAN DA, 1999, 781 USDA EC RES SERV MCGRANAHAN DA, 2002, RURAL AM, V17, P2 MENDENHALL W, 1989, 2 COURSE BUSINESS ST POTTS RS, 2004, NCGTR250 USDA FOR SE RADELOFF VC, 2000, IN PRESS CONSERV BIO RADELOFF VC, 2001, FOREST SCI, V47, P229 REY SJ, 1999, REG STUD, V33, P143 RIPPLE WJ, 1991, BIOL CONSERV, V57, P73 SCHNAIBERG J, 2002, ENVIRON MANAGE, V30, P24 SHANDS WE, 1977, LANDS NOBODY WANTED SO KS, 2001, AM J AGR ECON, V83, P1036 STEWART SI, 1994, J TRAVEL TOURISM MAR, V3, P69 TOBLER WR, 1970, EC GEOGRAPHY S, V46, P234 VOGELMANN JE, 2001, PHOTOGRAMM ENG REM S, V67, P650 WEAR DN, 1998, ECOSYSTEMS, V1, P575 0921-2973 Landsc. Ecol.ISI:000233036300001AForest Serv, USDA, N Cent Res Stn, Rhinelander, WI 54501 USA. Univ Wisconsin, Dept Rural Sociol, Appl Populat Lab, Madison, WI 53706 USA. Univ Wisconsin, Dept Forest Ecol & Management, Madison, WI 53706 USA. Gustafson, EJ, Forest Serv, USDA, N Cent Res Stn, 5985 Highway K, Rhinelander, WI 54501 USA. egustafson@fs.fed.usEnglish<7$2Gustafson, E. J. Lytle, D. E. Swaty, R. Loehle, C.2007ySimulating the cumulative effects of multiple forest management strategies on landscape measures of forest sustainability141-156Landscape Ecology221timber management; multiple owner landscapes; landscape pattern; HARVEST simulation model; sustainable forestry; biodiversity; forest products industry BIODIVERSITY; OWNERSHIP; FRAGMENTATION; CONSEQUENCES; DEERArticleJanWhile the cumulative effects of the actions of multiple owners have long been recognized as critically relevant to efforts to maintain sustainable forests at the landscape scale, few studies have addressed these effects. We used the HARVEST timber harvest simulator to predict the cumulative effects of four owner groups (two paper companies, a state forest and non-industrial private owners) with different management objectives on landscape pattern in an upper Michigan landscape managed primarily for timber production. We quantified trends in landscape pattern metrics that were linked to Montreal Process indicators of forest sustainability, and used a simple wildlife habitat model to project habitat trends. Our results showed that most trends were considered favorable for forest sustainability, but that some were not. The proportion of all age classes and some forest types moved closer to presettlement conditions. The trend for the size of uneven-aged patches was essentially flat while the average size of patches of the oldest and youngest age classes increased and the size of patches of the remaining age classes decreased. Forest fragmentation generally declined, but edge density of age classes increased. Late seral forest habitat increased while early successional habitat declined. The owners use different management systems that cumulatively produce a diversity of habitats. Our approach provides a tool to evaluate such cumulative effects on other landscapes owned by multiple owners. The approach holds promise for helping landowner groups develop and evaluate cooperative strategies to improve landscape patterns for forest sustainability.://000243619800013 PISI Document Delivery No.: 127XO Times Cited: 0 Cited Reference Count: 33 Cited References: *MI DEP NAT RES, 2001, IFMAP GAP UPP PEN LA *MONT PROC WORK GR, 1999, CRIT IND CONS SUST M ALVERSON WS, 1988, CONSERV BIOL, V2, P348 COMER PJ, 1995, MIGHIGANS PRESETTLEM DAVIS MB, 1981, FOREST SUCCESSION CO, P132 DAVIS MB, 1998, ECOLOGY, V79, P2641 DOEPKER RL, 2000, MIWILD MICHIGAN WILD FRELICH LE, 2002, FOREST DYNAMICS DIST GRUMBINE RE, 1994, CONSERV BIOL, V8, P27 GUSTAFSON EJ, 1999, LANDSCAPE ECOLOGICAL, P109 GUSTAFSON EJ, 1999, SPATIAL MODELING FOR, P309 GUSTAFSON EJ, 2002, COMPUT ELECTRON AGR, V33, P179 GUSTAFSON EJ, 2005, HARVEST WINDOWS V6 1 HANSEN AJ, 1991, BIOSCIENCE, V41, P382 HARPER KA, 2005, CONSERV BIOL, V19, P768 JORDAN JK, 2002, P LAND TYP ASS C DEV KEYS J, 1995, ECOLOGICAL UNITS E U KNIGHT RL, 1998, STEWARDSHIP BOUNDARI KURTTILA M, 2001, BOREAL ENVIRON RES, V6, P285 KURTTILA M, 2002, FOREST ECOL MANAG, V166, P69 KURTTILA M, 2003, LANDSCAPE ECOL, V18, P529 LUCIER AA, 1997, BIOMASS BIOENERG, V13, P193 MLADENOFF DJ, 1993, CONSERV BIOL, V7, P889 MLADENOFF DJ, 2004, APACK 2 23 ANAL SOFT MOORE MM, 1999, ECOL APPL, V9, P1266 PARKHURST GM, 2002, ECOL ECON, V41, P305 PETERSON A, 1998, GUIDEBOOK BEST MANAG POLASKY S, 2005, ECOL APPL, V15, P1387 REICE SR, 1994, AM SCI, V82, P424 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SCHULTE LA, 2001, J FOREST, V99, P5 SWANSON FJ, 1994, ECOSYSTEM MANAGEMENT, V2 WOOTTON JT, 2001, ECOL LETT, V4, P46 0921-2973 Landsc. Ecol.ISI:000243619800013USDA, Forest Serv, N Cent Res Stn, Rhinelander, WI 54501 USA. USDA, Forest Serv, N Cent Res Stn, Grand Rapids, MN 55744 USA. Nature Conservancy, Upper Peninsula Conservat Off, Marquette, MI 49855 USA. Natl Council Air & Stream Improvement, Naperville, IL 60540 USA. Nature Conservancy, Ohio Chapter, Dublin, OH 43017 USA. Gustafson, EJ, USDA, Forest Serv, N Cent Res Stn, 5985 Highway K, Rhinelander, WI 54501 USA. egustafson@fs.fed.usEnglish[?BGustafson, E. J. G. R. Parker1992SRelationships between landcover proportion and indices of landscape spatial pattern101-110Landscape Ecology72Fpercolation theory, indices, spatial pattern, fractal, proximity indexaRecent studies have related percolation theory and critical phenomena to the spatial pattern of landscapes. We generated simulated landscapes of forest and non-forest landcover to investigate the relationship between the proportion of forest (Pi) and indices of patch spatial pattern. One set of landscapes was generated by randomly assigning each pixel independently of other pixels, and a second set was generated by randomly assigning rectilinear clumps of pixels. Indices of spatial pattern were calculated and plotted against Pi. The random-clump landscapes were also compared with real agricultural landscapes. The results support the use of percolation models as neutral models in landscape ecology, and the performance of the indices studied.with these neutral models can be used to help interpret those indices calculated for real landscapes.$|7 Gustafson, E. J. Parker, G. R.1992SRelationships between Landcover Proportion and Indexes of Landscape Spatial Pattern101-110Landscape Ecology72Bpercolation theory indexes spatial pattern fractal proximity indexJul[Recent studies have related percolation theory and critical phenomena to the spatial pattern of landscapes. We generated simulated landscapes of forest and non-forest landcover to investigate the relationship between the proportion of forest (P(i)) and indices of patch spatial pattern. One set of landscapes was generated by randomly assigning each pixel independently of other pixels, and a second set was generated by randomly assigning rectilinear clumps of pixels. Indices of spatial pattern were calculated and plotted against P(i). The random-clump landscapes were also compared with real agricultural landscapes. The results support the use of percolation models as neutral models in landscape ecology, and the performance of the indices studied with these neutral models can be used to help interpret those indices calculated for real landscapes.://A1992JF61500003.Jf615 Times Cited:166 Cited References Count:0 0921-2973ISI:A1992JF61500003LGustafson, Ej Purdue Univ,Dept Forestry & Nat Resources,W Lafayette,in 47907EnglishP<7LGustafson, E. J. Zollner, P. A. Sturtevant, B. R. He, H. S. Mladenoff, D. J.2004nInfluence of forest management alternatives and land type on susceptibility to fire in northern Wisconsin, USA327-341Landscape Ecology193fire risk; LANDIS; management alternatives; simulation model; timber harvest; wildland-urban interface GREAT-LAKES REGION; PRESETTLEMENT FORESTS; LANDSCAPE MODEL; DISTURBANCE; SUCCESSION; SIMULATION; WILDFIRE; CLIMATE; STATESArticleWe used the LANDIS disturbance and succession model to study the effects of six alternative vegetation management scenarios on forest succession and the subsequent risk of canopy fire on a 2791 km(2) landscape in northern Wisconsin, USA. The study area is a mix of fire-prone and fire-resistant land types. The alternatives vary the spatial distribution of vegetation management activities to meet objectives primarily related to forest composition and recreation. The model simulates the spatial dynamics of differential reproduction, dispersal, and succession patterns using the vital attributes of species as they are influenced by the abiotic environment and disturbance. We simulated 50 replicates of each management alternative and recorded the presence of species age cohorts capable of sustaining canopy fire and the occurrence of fire over 250 years. We combined these maps of fuel and fire to map the probability of canopy fires across replicates for each alternative. Canopy fire probability varied considerably by land type. There was also a subtle, but significant effect of management alternative, and there was a significant interaction between land type and management alternative. The species associated with high-risk fuels (conifers) tend to be favored by management alternatives with more disturbances, whereas low disturbance levels favor low-risk northern hardwood systems dominated by sugar maple. The effect of management alternative on fire risk to individual human communities was not consistent across the landscape. Our results highlight the value of the LANDIS model for identifying specific locations where interacting factors of land type and management strategy increase fire risk.://000221878900007 ISI Document Delivery No.: 827DL Times Cited: 7 Cited Reference Count: 33 Cited References: *SAS I, 1990, SAS STAT US GUID VER, V2 *USDA FOR SERV, 1986, LAND RES MAN PLAN CH *USDA FOR SERV, 1999, DRAFT MAN AR PRESCR BURNS RM, 1990, HDB USDA FOREST SERV, V654, P877 CANHAM CD, 1984, ECOLOGY, V65, P803 CARDILLE JA, 2001, ECOL APPL, V11, P111 CARDILLE JA, 2001, INT J WILDLAND FIRE, V10, P145 CUMMING SG, 2001, ECOL APPL, V11, P97 FRELICH LE, 1991, ECOL MONOGR, V61, P145 FRELICH LE, 1999, ECOSYSTEMS, V2, P151 GUSTAFSON EJ, 2000, CAN J FOREST RES, V30, P32 HANSEN MH, 1992, NC151 USDA FOR SERV HE HS, 1999, ECOL MODEL, V114, P213 HE HS, 1999, ECOL MODEL, V119, P1 HE HS, 1999, ECOLOGY, V80, P81 HE HS, 2000, LANDIS SPATIALLY EXP HEINSELMAN ML, 1981, FIRE REGIMES ECOSYST, P7 HOST GE, 1996, ECOL APPL, V6, P608 KEYS J, 1995, ECOLOGICAL UNITS E U, P83 MACLEAN AL, 2003, P RMRS P, V29 MLADENOFF DJ, 1996, GIS ENV MODELING PRO, P175 MLADENOFF DJ, 1999, SPATIAL MODELING FOR, P125 MORRISON J, 1994, ECOSYSTEM MANAGEMENT, V2, P281 MUTCH RW, 1994, J FOREST, V92, P31 PASTOR J, 1986, BIOGEOCHEMISTRY, V2, P3 RADELOFF VC, IN PRESS CANADIAN J SOKAL RR, 1969, BIOMETRY STEARNS FW, 1997, LAKE STATES REGIONAL STEEL RGD, 1980, PRINCIPLES PROCEDURE STURTEVANT BR, 2003, LANDSCAPE ECOLOGY WOLTER PT, 1995, PHOTOGRAMM ENG REM S, V61, P1129 ZHANG QF, 1999, CAN J FOREST RES, V29, P106 ZOLLNER PA, UNPUB ECOLOGICAL APP 0921-2973 Landsc. Ecol.ISI:0002218789000075US Forest Serv, USDA, N Cent Res Stn, Rhinelander, WI 54501 USA. Univ Missouri, Sch Nat Resources, Columbia, MO 65211 USA. Univ Wisconsin, Dept Forest Ecol & Management, Madison, WI 53706 USA. Gustafson, EJ, US Forest Serv, USDA, N Cent Res Stn, 5985 Highway K, Rhinelander, WI 54501 USA. egustafson@fs.fed.usEnglishڽ761Güthlin, Denise Storch, Ilse Küchenhoff, Helmut2013RLandscape variables associated with relative abundance of generalist mesopredators 1687-1696Landscape Ecology289Springer NetherlandsYRed fox Feces counts Hunting bag Landscape diversity Landscape heterogeneity Edge density 2013/11/01+http://dx.doi.org/10.1007/s10980-013-9911-z 0921-2973Landscape Ecol10.1007/s10980-013-9911-zEnglishBڽ7 \Gutiérrez, David Harcourt, Jennifer Díez, SoniaB Gutiérrez Illán, Javier Wilson, RobertJ2013Models of presence–absence estimate abundance as well as (or even better than) models of abundance: the case of the butterfly Parnassius apollo401-413Landscape Ecology283Springer Netherlands~Apollo butterfly Conservation planning Distribution GLM Iberian Peninsula Information-theoretic approach Lepidoptera Mountains 2013/03/01+http://dx.doi.org/10.1007/s10980-013-9847-3 0921-2973Landscape Ecol10.1007/s10980-013-9847-3English ڽ7@Gutzwiller, KevinJ2013kIncreasing the chance that landscape- and regional-level hypotheses will reflect important spatial patterns 1849-1858Landscape Ecology2810Springer NetherlandsDistance-based Moran’s eigenvector maps Exploratory analysis Geographic mapping Graphical visualization Principal coordinates of neighbor matrices Spatial autocorrelation Spatial eigenvector analysis 2013/12/01+http://dx.doi.org/10.1007/s10980-013-9942-5 0921-2973Landscape Ecol10.1007/s10980-013-9942-5English?C)Gutzwiller, Kevin J. Anderson, Stanley H.1992iInterception of moving organisms: influences of patch shape, size, and orientation on community structure293-303Landscape Ecology64Wabundance, interception, nesting birds, patch orientation, richness, terrestrial matrixIsland biogeographers have predicted that in oceanic systems, oblong islands oriented perpendicular to the dispersal paths of organisms should intercept more species and individuals than (1) circular islands of the same size, and (2) oblong islands of equal area oriented parallel to the direction of travel. Landscape ecologists expect similar relations with habitat patches in a terrestrial matrix. Yet in neither situation is there adequate empirical information to permit conclusions about the prevalence of such effects. To test the hypothesis that intercept-related patch variables influence community structure on the landscape scale, we studied relations between the richness and abundance of cavity-nesting birds and patch shape, size, and orientation relative to a northerly migration path. The influences of other patch features on nest abundances were removed analytically. Multiple regression indicated that the mean and total number of nesting species, and nest abundances for migrants were significantly associated with patch orientation or a patch area x orientation interaction, but not patch shape. Nest abundances for permanent residents were not associated with patch shape or orientation, although area effects, possibly reflecting dispersal interception, were evident. These results are consistent with the hypothesis that stochastic interception of migrating or dispersing organisms influences patch community structure. In addition to richness and abundance effects apparent in this analysis, the sex ratio, age structure, growth rate, social structure, and genetic features of patch populations may also be influenced. The interception of moving organisms by patches may thus be a key factor influencing population and community persistence in reserves. If so, landscape structure could be manipulated to maximize the interception of dispersing or migrating organisms, or minimize it if the effects are undesirable.|?'Gutzwiller, Kevin J. Riffell, Samuel K.2014PRigor and transparency in statistical analyses can help to ensure valid research 1115-1122Landscape Ecology297AugAdherence to important assumptions of statistical methods has significant ramifications for development of new knowledge in landscape ecology for two fundamental reasons: these methods will continue to be used widely and will thus affect much of the research on which advances in landscape ecology will be founded; and the degree to which statistical methods are applied appropriately will influence the statistical validity of that research. Rigorous statistical analyses are essential because no discipline can efficiently advance scientifically if one of its primary approaches for generating new knowledge is used incorrectly. Assessing and communicating compliance with statistical assumptions should be standard practice in confirmatory analyses. Better understanding of the robustness of statistical methods to deviations from assumptions can improve investigators' decisions about which methods to apply. Explanations about the consequences of actual or possible violations of assumptions can clarify the validity of results. Many of the papers in a sample of 215 research articles published in Landscape Ecology during 2004-2013 exhibited substantial lack of clarity about adherence to statistical assumptions. Brief author statements about whether important statistical assumptions were adequately met would improve confidence in results. Ultimately, rigor and transparency in confirmatory statistical analyses will help to ensure the validity of landscape ecology research.!://WOS:000339831300002Times Cited: 0 0921-2973WOS:00033983130000210.1007/s10980-014-0063-6>ڽ7 Haas, Edwin Klatt, Steffen Fröhlich, Alexander Kraft, Philipp Werner, Christian Kiese, Ralf Grote, Rüdiger Breuer, Lutz Butterbach-Bahl, Klaus2013LandscapeDNDC: a process model for simulation of biosphere–atmosphere–hydrosphere exchange processes at site and regional scale615-636Landscape Ecology284Springer NetherlandsTRegionalization Greenhouse gas emissions Inventory DNDC LandscapeDNDC Model coupling 2013/04/01+http://dx.doi.org/10.1007/s10980-012-9772-x 0921-2973Landscape Ecol10.1007/s10980-012-9772-xEnglish? Guenter Haase1989GMedium scale landscape classification in the German Democratic Republic29-41Landscape Ecology31^landscape ecology, classification, German Democratic Republic, mapping, geochore, geom, surveyThe demands on an intensely-managed landscape require a regional landscape planning system, which balances the social-economic needs with geo-biological conditions. Planning needs a system of classification of the landscape, which is consistent and reflects the natural patterns, the potential capacity and the limits of natural units, and the history of human use. In the GDR we have created a classification scheme which identifies a variety of objects on the landscape, which can be mapped, and which represent the patterns of potential use and the limits on usages. A set of terms and definitions is presented, which represent hierarchical levels of this classification.ڽ7 *Haby, NerissaA Foulkes, Jeff Brook, BarryW2013SUsing climate variables to predict small mammal occurrence in hot, dry environments741-753Landscape Ecology284Springer NetherlandsGSmall mammal Rangelands Scale Species distribution model Climate change 2013/04/01+http://dx.doi.org/10.1007/s10980-013-9859-z 0921-2973Landscape Ecol10.1007/s10980-013-9859-zEnglish |?X JHagerty, Bridgette E. Nussear, Kenneth E. Esque, Todd C. Tracy, C. Richard2011SMaking molehills out of mountains: landscape genetics of the Mojave desert tortoise267-280Landscape Ecology262FebHeterogeneity in habitat often influences how organisms traverse the landscape matrix that connects populations. Understanding landscape connectivity is important to determine the ecological processes that influence those movements, which lead to evolutionary change due to gene flow. Here, we used landscape genetics and statistical models to evaluate hypotheses that could explain isolation among locations of the threatened Mojave desert tortoise (Gopherus agassizii). Within a causal modeling framework, we investigated three factors that can influence landscape connectivity: geographic distance, barriers to dispersal, and landscape friction. A statistical model of habitat suitability for the Mojave desert tortoise, based on topography, vegetation, and climate variables, was used as a proxy for landscape friction and barriers to dispersal. We quantified landscape friction with least-cost distances and with resistance distances among sampling locations. A set of diagnostic partial Mantel tests statistically separated the hypotheses of potential causes of genetic isolation. The best-supported model varied depending upon how landscape friction was quantified. Patterns of genetic structure were related to a combination of geographic distance and barriers as defined by least-cost distances, suggesting that mountain ranges and extremely low-elevation valleys influence connectivity at the regional scale beyond the tortoises' ability to disperse. However, geographic distance was the only influence detected using resistance distances, which we attributed to fundamental differences between the two ways of quantifying friction. Landscape friction, as we measured it, did not influence the observed patterns of genetic distances using either quantification. Barriers and distance may be more valuable predictors of observed population structure for species like the desert tortoise, which has high dispersal capability and a long generation time.!://WOS:000286474900009Times Cited: 1 0921-2973WOS:00028647490000910.1007/s10980-010-9550-6I<7Haines-Young, R. H.1992WThe use of remotely-sensed satellite imagery for landscape classification in Wales (UK)253-274Landscape Ecology74:LANDSCAPE CLASSIFICATION; LANDSCAPE SURVEY; REMOTE SENSINGArticleDec`Remotely-sensed satellite data from Landsat TM and MSS were processed digitally to make landscape classifications of three study areas of south east Wales. The classifications were constructed by classifying major variations in land cover mosaics within the areas, and using these data to group the 1 km x 1 km cells of the National Grid into landscape classes according to the combination of cover types found within them. The TWINSPAN algorithm, which is a polythetic, divisive classification method, was used as the basis of the study. The results showed that while satellite imagery could only be used to extract information about land cover, the close association betwen landscape, land cover and terrain meant that the major physical divisions in the study area could also be detected in the landscape classification. The landscape types recognised in the study were found to be consistent with those indicated in other independent data which relate to the areas. These data included the ITE Land Classes for Great Britain, and the Agricultural (June) Census statistics for England and Wales. The approach to landscape classification described allows landscape classifications to be made rapidly. These classifications can provide a sampling frameworks for landscape survey in areas where basic map data are lacking or resources for field survey are limited. The landscape classifications can also assist in making landscape evaluations since they allow different landscape types to be compared in respect of such properties such as their typicalness, rarity, naturalness and position on a geographical or ecological gradient.://A1992KD83100003 HISI Document Delivery No.: KD831 Times Cited: 5 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1992KD83100003FHAINESYOUNG, RH, UNIV NOTTINGHAM,DEPT GEOG,NOTTINGHAM NG7 2RD,ENGLAND.English|? !Haire, Sandra L. McGarigal, Kevin2010Effects of landscape patterns of fire severity on regenerating ponderosa pine forests (Pinus ponderosa) in New Mexico and Arizona, USA 1055-1069Landscape Ecology257Aug"Much of the current effort to restore southwestern ponderosa pine forests to historical conditions is predicated upon assumptions regarding the catastrophic effects of large fires that are now defining a new fire regime. To determine how spatial characteristics influence the process of ponderosa pine regeneration under this new regime, we mapped the spatial patterns of severity at areas that burned in 1960 (Saddle Mountain, AZ) and (La Mesa, NM) 1977 using pre- and post-fire aerial photography, and quantified characteristics of pine regeneration at sample plots in areas where all trees were killed by the fire event. We used generalized linear models to determine the relationship of ponderosa pine stem density to three spatial burn pattern metrics: (1) distance to nearest edge of lower severity; (2) neighborhood severity, measured at varying spatial scales, and (3) scaled seed dispersal kernel surfaces. Pine regeneration corresponded most closely with particular scales of measurement in both seed dispersal kernel and neighborhood severity. Spatial patterns of burning remained important to understanding regeneration even after consideration of subsequent disturbance and other environmental variables, with the exception of a few cases in which simpler models were equally well-supported by the data. Analysis of tree ages revealed slow progress in early post-fire years. Our observations suggest that populations spread in a moving front, as well as by remotely dispersed individuals. Based on our results, recent large fires cannot be summarily dismissed as catastrophic. We conclude that management should focus on the value and natural recovery of post-fire landscapes. Further, process centered restoration efforts could utilize our findings in formulating reference dynamics under a changing fire regime.!://WOS:000279592100006Times Cited: 0 0921-2973WOS:00027959210000610.1007/s10980-010-9480-3|?e 2Hall, Carolyn J. Jordaan, Adrian Frisk, Michael G.2011The historic influence of dams on diadromous fish habitat with a focus on river herring and hydrologic longitudinal connectivity95-107Landscape Ecology261Jan|The erection of dams alters habitat and longitudinal stream connectivity for migratory diadromous and potamodromous fish species and interrupts much of organismal exchange between freshwater and marine ecosystems. In the US, this disruption began with colonial settlement in the seventeenth century but little quantitative assessment of historical impact on accessible habitat and population size has been conducted. We used published surveys, GIS layers and historical documents to create a database of 1356 dams, which was then analyzed to determine the historical timeline of construction, use and resultant fragmentation of watersheds in Maine, US. Historical information on the anadromous river herring was used to determine natural upstream boundaries to migration and establish total potential alewife spawning habitat in nine watersheds with historic populations. Dams in Maine were constructed beginning in 1634 and by 1850 had reduced accessible lake area to less than 5% of the virgin 892 km(2) habitat and 20% of virgin stream habitat. There is a near total loss of accessible habitat by 1860 that followed a west-east pattern of European migration and settlement. Understanding historic trends allows current restoration targets to be assessed and prioritized within an ecosystem-based perspective and may inform expectations for future management of oceanic and freshwater living resources.!://WOS:000286004400009Times Cited: 2 0921-2973WOS:00028600440000910.1007/s10980-010-9539-1?E*Hall, F.G. D.E. Strebel P.J. Sellers1988gLinking knowledge among spatial and temporal scales: Vegetation, atmosphere, climate and remote sensing3-22Landscape Ecology21CGlobal models, Atmosphere, Climate, Remote sensing, FIFE, BiospherejGlobal scale modeling is reviewed with respect to global circulation models, biosphere-atmosphere models, and climate-biosphere models. These different models focus on short to long time scale interactions between atmospheric and surface systems. Remote sensing is shown to play a central role in acquisition of data for these models, and an experiment, termed FIFE, is described, which is the first attempt to take simultaneous land surface observations of meteorological and biophysical parameters at sufficient resolution to test hypotheses linking the vegetated surface and circulation within the lower atmosphere.|<7Hall, G. M. J. McGlone, M. S.2001fForest reconstruction and past climatic estimates for a deforested region of south-eastern New Zealand501-521Landscape Ecology166early Holocene climate forest-gap model New Zealand pollen taxa restoration HOLOCENE VEGETATION HISTORY CENTRAL OTAGO COMPUTER-MODEL NORTH-ISLAND SUCCESSION DYNAMICS GROWTH POLLEN RANGEArticleAug Predictions of species biomass from a forest simulation model were compared with pollen percentages for seven peatland sites in an area of Southland-Otago, New Zealand, now depleted of forest cover. Comparisons were made for the recent past 700-800 cal. yr BP) and for a period of the early Holocene (7000-8000 cal. yr BP). Satisfactory matches were obtained overall between predicted biomass and pollen for the recent dataset (r = 0.73, P < 0.001), in spite of expected poor correspondences for some pollen taxa known to be under-represented in the modem pollen rain. Nothofagus species tended to be over-represented by the simulation model, due most likely to dispersal limiting to their spread under actual conditions. Raising mean annual temperatures by 1C and lowering precipitation by up to 60% for the forest simulation produced a satisfactory match to the early Holocene site data (r = 0.69, P < 0.001). To test for consistency between recent and past periods, regressions for each period of modelled relative biomass against pollen percentages were compared, using all tree taxa from all sites. No discernible bias was found between the different climate regimes modelled. However, an examination of each site showed the dominant early-Holocene hardwood forests of Stewart Island were not reproduced by a simulation under the hypothesized past climate. These forests required a different set of conditions from those for the South Island sites. suggesting they grew under a different climatic regime. The low variation in climate among several of the sites tested the forest model's ability to reproduce the distinct forest communities identified from the pollen data. Comparisons with the pollen record improved confidence in the species attribute data used by the model, the completeness of the ecosystem processes explicitly modelled, and the disturbance regimes employed. A forest reconstruction of the region, under current climate conditions, indicated extensive areas of grassland and grassland-scrub vegetation could potentially be replaced by a range of podocarp, broadleaf, and beech forest types. Overall, the exercise suggested such approaches can improve our understanding of the processes required to restore forest in depleted landscapes and to model forest dynamics under changed climates.://000172548800003  ISI Document Delivery No.: 499AW Times Cited: 8 Cited Reference Count: 59 Cited References: *NZ MET SERV, 1969, NZ MET SERV MISC PUB, V109 *NZ SOIL BUR, 1968, NZ SOIL BUR B, V27 ABER JD, 1982, FOREST SCI, V28, P31 ALLAN HH, 1961, FLORA NZ, V1 ALLEN RB, 1988, NEW ZEAL J BOT, V26, P281 ALLEN RB, 1988, NZ J ECOL, V11, P21 ATKINSON IAE, 1997, LANDCARE RES SCI SER, V14, P70 BAYLIS GTS, 1980, NZ J ECOLOGY, V3, P151 BOTKIN DB, 1972, J ECOL, V60, P849 BUGMANN H, 2000, CLIMATIC CHANGE, V44, P265 BUGMANN HKM, 1996, CLIMATIC CHANGE, V34, P289 CARTER J, 1994, WAIPORI ECOLOGICAL D CRANWELL LM, 1936, GEOGRAFISKA ANN, V3, P308 FAHEY B, 1997, AGR FOREST METEOROL, V84, P69 FENNER J, 1992, MAR GEOL, V108, P383 GARNIER BJ, 1958, CLIMATE NZ GELLATLY AF, 1988, QUATERNARY SCI REV, V7, P227 HALL GMJ, 1992, FOREST RES I B, V182 HALL GMJ, 2000, ECOL APPL, V10, P115 HARRIS WF, 1986, 118 PAL NZ GEOL SURV LABRACHERIE M, 1989, PALEOCEANOGRAPHY, V4, P629 LEATHWICK JR, 2001, FUNCT ECOL, V15, P233 LYNN IH, 1991, 10 DSIR LAND RES MACPHAIL MK, 1983, TUATARA, V26, P37 MARTINSON DG, 1987, QUATERNARY RES, V27, P1 MCGLONE MS, 1983, NEW ZEAL J BOT, V21, P292 MCGLONE MS, 1989, NEW ZEAL J ECOL, V12, P115 MCGLONE MS, 1995, J ROY SOC NEW ZEAL, V25, P1 MCGLONE MS, 1996, NEW ZEAL J BOT, V34, P369 MCGLONE MS, 1997, ARCTIC ALPINE RES, V29, P32 MCGLONE MS, 1998, NEW ZEAL J BOT, V36, P91 MCGLONE MS, 1999, J QUATERNARY SCI, V14, P239 MCGLONE MS, 1999, QUATERN INT, V59, P17 MCGLONE MS, 2000, NZ J ECOL, V25, P1 MCINTOSH PD, 1990, PALAEOGEOGR PALAEOCL, V81, P95 MCKELLAR MH, 1973, NEW ZEAL J BOT, V11, P305 MILDENHALL DC, 1994, J ROYAL SOC NZ, V24, P219 MOLLOY L, 1988, SOILS NZ LANDSCAPE MORLEY JJ, 1993, GLOBAL CLIMATES LAST, P125 NELSON CS, 2000, PALAEOGEOGR PALAEOCL, V156, P103 NEWSOME PFJ, 1987, WATER SOIL MISCELLAN, V112 OGDEN J, 1985, NEW ZEAL J BOT, V23, P751 PASTOR J, 1986, BIOGEOCHEMISTRY, V2, P3 POCKNALL DT, 1980, NEW ZEAL J BOT, V18, P275 RASTETTER EB, 1996, BIOSCIENCE, V46, P190 SHUGART HH, 1977, J ENVIRON MANAGE, V5, P161 SHUGART HH, 1981, AUST J ECOL, V6, P149 SHUGART HH, 1984, THEORY FOREST DYNAMI SOLOMON AM, 1985, ANNU REV ECOL SYST, V16, P63 SOLOMON AM, 1992, CAN J FOREST RES, V22, P1727 STEWART GH, 1986, VEGETATIO, V68, P115 VANDERGOES MJ, 1997, J ROY SOC NEW ZEAL, V27, P53 WARDLE JA, 1984, NZ BEECHES ECOLOGY U WARDLE P, 1967, NEW ZEAL J BOT, V5, P276 WARDLE P, 1980, NZ J ECOL, V3, P23 WARDLE P, 1991, VEGETATION NZ WILLIAMS PW, 1999, HOLOCENE, V9, P649 YAMAMOTO SI, 1992, BOT MAG TOKYO, V105, P375 ZAR JH, 1996, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000172548800003dLandcare Res, Lincoln 8152, New Zealand. Hall, GMJ, Landcare Res, POB 69, Lincoln 8152, New Zealand.English?U IHall, Jaclyn Van Holt, Tracy Daniels, Amy Balthazar, Vincent Lambin, Eric2012bTrade-offs between tree cover, carbon storage and floristic biodiversity in reforesting landscapes 1135-1147Landscape Ecology278Springer NetherlandsBiomedical and Life Sciences*This study explores the relationships between an increase in tree cover area (i.e., natural and planted-tree land covers) and changes in forest carbon storage and the potential of a landscape to provide habitat for native floristic biodiversity. Four areas experiencing an increase in tree cover were analyzed. We developed a metric estimating the potential to support native biodiversity based on tree cover type (plantation or natural forests) and the landscape pattern of natural and anthropogenic land covers. We used published estimates for forest and plantation carbon stocks for each region. Focus regions in northwestern Costa Rica, northern Vietnam, southern Chile and highland Ecuador all showed an increase in tree cover area of 390 %, 260 %, 123 % and 418 %, respectively. Landscapes experiencing increases in natural secondary forest also experienced an increase in carbon stored above and below ground, and in the potential to support native floristic biodiversity. Study landscapes in Chile and Ecuador experiencing an expansion of exotic plantations saw their carbon stock decrease along with their potential to support native floristic biodiversity. This study shows that an increase in forest area does not necessarily imply an increased provision of ecosystem services when landscapes are reforesting with monoculture plantations of exotic tree species. Changes in the support of native biodiversity and the carbon stored in pulp rotation plantations, along with other ecosystem services, should be fully considered before implementing reforestation projects.+http://dx.doi.org/10.1007/s10980-012-9755-y 0921-297310.1007/s10980-012-9755-y|?%Hall, Laurie A. Beissinger, Steven R.2014IA practical toolbox for design and analysis of landscape genetics studies 1487-1504Landscape Ecology299NovWLandscape genetics integrates theory and analytical methods of population genetics and landscape ecology. Research in this area has increased in recent decades, creating a plethora of options for study design and analysis. Here we present a practical toolbox for the design and analysis of landscape genetics studies following a seven-step framework: (1) define the study objectives, (2) consider the spatial and temporal scale of the study, (3) design a sampling regime, (4) select a genetic marker, (5) generate genetic input data, (6) generate spatial input data, and (7) choose an analytical method that integrates genetic and spatial data. Study design considerations discussed include choices of spatial and temporal scale, sample size and spatial distribution, and genetic marker selection. We present analytical methods suitable for achieving different study objectives. As emerging technologies generate genetic and spatial data sets of increasing size, complexity, and resolution, landscape geneticists are challenged to execute hypothesis-driven research that combines empirical data and simulation modeling. The landscape genetics framework presented here can accommodate new design considerations and analyses, and facilitate integration of genetic and spatial data by guiding new landscape geneticists through study design, implementation, and analysis.!://WOS:000343648700003Times Cited: 2 0921-2973WOS:00034364870000310.1007/s10980-014-0082-3<7/Hall, O. Hay, G. J. Bouchard, A. Marceau, D. J.2004Detecting dominant landscape objects through multiple scales: An integration of object-specific methods and watershed segmentation59-76Landscape Ecology191complex system; critical landscape threshold; feature detection; hierarchy; IKONOS; marker-controlled watershed segmentation; multiscale; object-specific analysis; object-specific upscaling; scale domain SAINT-LAURENT QUEBEC; EDGE-DETECTION; ECOLOGY; REGIONArticleComplex systems, such as landscapes, are composed of different critical levels of organization where interactions are stronger within levels than among levels, and where each level operates at relatively distinct time and spatial scales. To detect significant features occurring at specific levels of organization in a landscape, two steps are required. First, a multiscale dataset must be generated from which these features can emerge. Second, a procedure must be developed to delineate individual image-objects and identify them as they change through scale. In this paper, we introduce a framework for the automatic definition of multiscale landscape features using object-specific techniques and marker-controlled watershed segmentation. By applying this framework to a high-resolution satellite scene, image-objects of varying size and shape can be delineated and studied individually at their characteristic scale of expression. This framework involves three main steps: 1) multiscale dataset generation using an object-specific analysis and upscaling technique, 2) marker-controlled watershed transformation to automatically delineate individual image-objects as they evolve through scale, and 3) landscape feature identification to assess the significance of these image-objects in terms of meaningful landscape features. This study was conducted on an agro-forested region in southwest Quebec, Canada, using IKONOS satellite data. Results show that image-objects tend to persist within one or two scale domains, and then suddenly disappear at the next, while new image-objects emerge at coarser scale domains. We suggest that these patterns are associated to sudden shifts in the entire image structure at certain scale domains, which may correspond to critical landscape thresholds.://000189394100005 . ISI Document Delivery No.: 780RA Times Cited: 3 Cited Reference Count: 57 Cited References: ALLEN TFH, 1982, HIERARCHY PERSPECTIV BEUCHER S, 1979, INT WORKSH IM PROC R BEUCHER S, 1990, P PROART VIS GROUP P, P1 BEUCHER S, 1992, SCANNING MICROSC S, V6, P299 BOUCHARD A, 1997, LANDSCAPE URBAN PLAN, V37, P99 BRUNELLI R, 1995, ARTIFICIAL INTELLIGE, V1549 CANNY J, 1986, IEEE T PATTERN ANAL, V8, P679 CONGALTON RG, 1983, PHOTOGRAMM ENG REM S, V49, P69 CURRAN PJ, 1998, PROG PHYS GEOG, V22, P61 DAUBECHIES I, 1988, COMMUN PURE APPL MAT, V41, P906 DEBLOIS S, 2001, LANDSCAPE ECOL, V16, P421 GARDNER RH, 1982, ECOLOGY, V63, P1771 HALL O, 2002, MEDDELANDEN STOCKHOL, V16, P101 HALL O, 2003, IN PRESS INT J APPL HARALICK RM, 1987, IEEE T PATTERN ANAL, V9, P532 HAY GJ, 1997, REMOTE SENS ENVIRON, V62, P1 HAY GJ, 2001, LANDSCAPE ECOL, V16, P471 HAY GJ, 2002, ECOL MODEL, V153, P27 HAY GJ, 2002, P JOINT INT S GEOSP, P532 HAY GJ, 2003, PHOTOGRAMMETRY REMOT, V57, P327 JENSEN JR, 1996, INTRO DIGITAL IMAGE, P257 KING AW, 1990, QUANTITATIVE METHODS, P479 KLINGER A, 1971, OPTIMIZING METHODS S, P303 KLINGER A, 1976, COMPUTER GRAPHICS IM, V5, P68 LEVIN SA, 1992, ECOLOGY, V73, P1943 LINDEBERG T, 1994, J APPL STAT, V21, P225 MALANSON GP, 1999, ANN ASSOC AM GEOGR, V89, P746 MANDELBROT B, 1967, SCIENCE, V156, P636 MARCEAU DJ, 1999, CAN J REMOTE SENS, V25, P357 MARCEAU DJ, 1999, CANADIAN J REMOTE SE, V25, P347 MARR D, 1980, P ROY SOC LOND B BIO, V207, P187 MATHER PM, 1999, COMPUTER PROCESSING, P292 MEENTEMEYER V, 1989, LANDSCAPE ECOLOGY, V3, P163 MERCIER C, 2001, ENVIRON MANAGE, V28, P777 MEYER F, 1990, J VIS COMMUN IMAGE R, V1, P21 MOELLERING H, 1972, GEOGR ANAL, V4, P34 ONEILL RV, 1988, SCALES GLOBAL CHANGE, P29 OPENSHAW S, 1984, CONCEPTS TECHNIQUES, P40 PAN DY, 1999, LANDSCAPE ECOL, V14, P35 RIDLER TW, 1978, IEEE T SYST MAN CYB, V8, P630 RIVEST JF, 1993, J ELECTRON IMAGING, V2, P326 SERRA J, 1982, IMAGE ANAL MATH MORP, P610 SIMARD H, 1996, CAN J FOREST RES, V26, P1670 SLATER PN, 1980, REMOTE SENSING OPTIC, P575 SOILLE P, 1999, HDB COMPUTER VISION, V2, P628 STARCK JL, 1998, IMAGE PROCESSING DAT, P285 TOBLER WR, 1970, EC GEOGRAPHY S, V46, P234 TURNER M, 2001, LANDSCAPE ECOLOGY TH, P375 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P245 VANDERHEIJDEN F, 1994, IMAGE BASED MEASUREM, P348 VINCENT L, 1991, IEEE T PATTERN ANAL, V13, P583 WALDROP MM, 1992, COMPLEXITY EMERGING, P380 WOODCOCK CE, 1987, REMOTE SENS ENVIRON, V21, P311 WU J, 1999, CANADIAN J REMOTE SE, V25, P367 WU JG, 1995, Q REV BIOL, V70, P439 WU JG, 2002, ECOL MODEL, V153, P1 WU JG, 2002, LANDSCAPE ECOL, V17, P355 0921-2973 Landsc. Ecol.ISI:000189394100005GStockholm Univ, Dept Phys Geog & Quaternary Geol, SE-10691 Stockholm, Sweden. Univ Montreal, Dept Geog, Geocomp Lab, Montreal, PQ H3C 3J7, Canada. Univ Montreal, Inst Rech Biol Vegetale, Montreal, PQ H1X 2B2, Canada. Hall, O, Stockholm Univ, Dept Phys Geog & Quaternary Geol, SE-10691 Stockholm, Sweden. ola.hall@humangeo.su.seEnglish|? Halvorsen, R. Edvardsen, A.2009,The concept of habitat specificity revisited851-861Landscape Ecology247Aug Habitat specificity indices reflect richness (alpha) and/or distinctiveness (beta) components of diversity. The latter may be defined by alpha and gamma (landscape) diversity in two alternative ways: multiplicatively ( beta = gamma/alpha ) and additively ( beta = gamma - alpha). We demonstrate that the original habitat specificity concept of Wagner and Edwards (Landscape Ecol 16:121-131, 2001) consists of three independent components: core habitat specificity (uniqueness of the species composition), patch area and patch species richness. We describe habitat specificity as a family of indices that may include either area or richness components, or none or both, and open for use of different types of mean in calculation of core habitat specificity. Core habitat specificity is a beta diversity measure: the effective number of completely distinct communities in the landscape. Habitat specificity weighted by species number is a gamma diversity measure: the effective number of species that a patch contributes to landscape richness. We compared 12 habitat specificity indices by theoretical reasoning and by use of field data (vascular plant species in SE Norwegian agricultural landscapes). Habitat specificity indices are strongly influenced by weights for patch area and patch species richness, and the relative contribution of rare vs. common species (type of mean). The relevance of properties emphasized by each habitat specificity index for evaluation of patches in a biodiversity context is discussed. Core habitat specificity is emphasized as an ecologically interpretable measure that specifically addresses patch uniqueness while habitat specificity weighted by species number combines species richness and species composition in ways relevant for conservation biological assessment.://000268430900001!Halvorsen, Rune Edvardsen, Anette 0921-2973ISI:00026843090000110.1007/s10980-009-9363-7 s<7t Hamazaki, T.19961Effects of patch shape on the number of organisms299-306Landscape Ecology115dpatch shape; immigration; oxidus gracilis; millipede COMMUNITY STRUCTURE; HABITAT GEOMETRY; DYNAMICSArticleOctuThis study examined effects of habitat patch shape on the abundance of organisms. The effects of patch shape were considered in terms of (1) immigration and emigration of organisms, (2) the amount of available resources in a patch and (3) spatial and temporal heterogeneity of the organisms and environment. I hypothesized that (1) the number of organisms would increase as patch shape elongates because organisms are more likely to encounter an elongated patch, (2) the number of organisms in a patch would remain constant for all patch shapes where the number of organisms in a patch was limited by the amount of resources, because patch shape does not change the patch area that is directly associated with the amount of patch resources, and (3) spatial and temporal variation of the abundance of organisms would increase as patch shape elongates because an elongated patch is more likely to interact with the variable surrounding matrix. Common millipedes, Oxidus gracilis, and their habitat, plywood boards of five shapes (width:length ratio; 1:1, 1:4, 1:9, 1:36, 1:144) with an area of 900 cm(2) were placed in forest and old field and the number of millipedes appearing under the boards was monitored. Significantly higher mean number of millipedes under the boards was observed at a patch with an elongated shape in the forest and the old field. A significant positive correlation was observed between perimeter length of a patch and the number of millipedes in the old field. The temporal and spatial variation of the number of millipedes was high in the old field. The spatial and temporal variation was higher for boards with elongated shape.://A1996VR02500007 qISI Document Delivery No.: VR025 Times Cited: 21 Cited Reference Count: 23 Cited References: APPEL AG, 1988, ENVIRON ENTOMOL, V17, P463 BUECHNER M, 1987, BIOL CONSERV, V41, P57 CAUSEY NB, 1943, AM MIDL NAT, V29, P670 CLOUDSLEYTHOMPS.JL, 1951, P ZOOL SOC LOND, V121, P253 COLE LC, 1946, ECOL MONOGR, V16, P49 DENDY A, 1995, 6 M AUG ASS ADV SCI, V6, P99 DIAMOND JM, 1976, THEORETICAL ECOLOGY, P163 EMMERICH JM, 1982, J WILDLIFE MANAGE, V43, P421 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 GAME M, 1980, NATURE, V287, P630 GUTZWILLER KJ, 1992, LANDSCAPE ECOL, V6, P293 HANSKI I, 1991, BIOL J LINN SOC, V42, P3 HARPER SJ, 1993, J MAMMAL, V74, P1045 LAUDENSLAYER WF, 1976, AUK, V93, P571 LAURANCE WF, 1991, BIOL CONSERV, V55, P77 NOSS RE, 1994, SAVING NATURES LEGAC PULLIAM HR, 1988, AM NAT, V132, P652 SAVORY T, 1971, BIOL CYPTOZOA STAMPS JA, 1987, AM NAT, V129, P533 STAMPS JA, 1987, AM ZOOL, V27, P307 TARPLEY WA, 1967, THESIS U GEORGIA ATH YAHNER RH, 1983, J WILDLIFE MANAGE, V47, P74 0921-2973 Landsc. Ecol.ISI:A1996VR025000074Hamazaki, T, UNIV GEORGIA,INST ECOL,ATHENS,GA 30602.English^<7o'Hamer, T. L. Flather, C. H. Noon, B. R.2006|Factors associated with grassland bird species richness: The relative roles of grassland area, landscape structure, and prey569-583Landscape Ecology2146AIC model-selection; Eastern Wyoming; grasshopper; habitat amount; habitat configuration; mark-recapture; matrix effects; Orthoptera; richness estimation; thematic mapper FOREST FRAGMENTATION; HABITAT FRAGMENTATION; BREEDING BIRDS; MATRIX MATTERS; COMMUNITIES; DYNAMICS; ECOLOGY; PATTERN; MODELS; HETEROGENEITYArticleMaygThe factors responsible for widespread declines of grassland birds in the United States are not well understood. This study, conducted in the short-grass prairie of eastern Wyoming, was designed to investigate the relationship between variation in habitat amount, landscape heterogeneity, prey resources, and spatial variation in grassland bird species richness. We estimated bird richness over a 5-year period (1994-1998) from 29 Breeding Bird Survey locations. Estimated bird richness was modeled as a function of landscape structure surrounding survey routes using satellite-based imagery (1996) and grasshopper density and richness, a potentially important prey of grassland birds. Model specification progressed from simple to complex explanations for spatial variation in bird richness. An information-theoretic approach was used to rank and select candidate models. Our best model included measurements of habitat amount, habitat arrangement, landscape matrix, and prey diversity. Grassland bird richness was positively associated with grassland habitat; was negatively associated with habitat dispersion; positively associated with edge habitats; negatively associated with landscape matrix attributes that may restrict movement of grassland bird; and positively related to grasshopper richness. Collectively, 62% of the spatial variation in grassland bird richness was accounted for by the model (adj-R-2 = 0.514). These results suggest that the distribution of grassland bird species is influenced by a complex mixture of factors that include habitat area affects, landscape pattern and composition, and the availability of prey.://000237487700009 l ISI Document Delivery No.: 041WR Times Cited: 0 Cited Reference Count: 74 Cited References: *SAS I, 1990, SAS STAT USERS GUIDE *WYOM AGR STAT SER, 2002, WYOM AGR STAT 2002 R ANDERSON JR, 1976, 964 US GEOL SURV ARRHENIUS O, 1921, J ECOL, V9, P95 BAILEY RG, 1995, PUBLICATION US FOR S, V1391, P108 BAILEY TC, 1995, INTERACTIVE SPATIAL BASCOMPTE J, 2001, ECOL LETT, V4, P417 BELISLE M, 2001, ECOLOGY, V82, P1893 BERRY JS, 1996, B USDA ANIMAL PLANT, V1809 BEST LB, 1995, AM MIDL NAT, V134, P1 BLOUINDEMERS G, 2001, ECOLOGY, V82, P2882 BORCHERT JR, 1950, ANN ASSOC AM GEOGR, V40, P1 BOULINIER T, 1998, ECOLOGY, V79, P1018 BOULINIER T, 2001, ECOLOGY, V82, P1159 BROWN JH, 1995, MACROECOLOGY BURKE IC, 1994, INTEGRATED REGIONAL, P79 BURNHAM KP, 2002, MODEL SELECTION MULT CAMPI MJ, 2001, ANIM CONSERV 2, V4, P121 CONGALTON RG, 1999, ASSESSING ACCURACY R DRAPER NR, 1981, APPL REGRESSION ANAL DROEGE S, 1990, SURVEY DESIGNS STAT, P1 DUNFORD W, 2005, LANDSCAPE ECOL, V20, P497 EHRLICH PR, 1988, BIRDERS HDB FIELD GU FAHRIG L, 2001, BIOL CONSERV, V100, P65 FAHRIG L, 2003, ANNU REV ECOL EVOL S, V34, P487 FLASPOHLER DJ, 2001, ECOL APPL, V11, P32 FLATHER CH, 2002, AM NAT, V159, P40 GLEASON HA, 1922, ECOLOGY, V3, P158 GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 HAINING R, 1990, SPATIAL DATA ANAL SO HANSEN AJ, 1992, LANDSCAPE ECOL, V7, P163 HERKERT JR, 1994, ECOL APPL, V4, P461 HERKERT JR, 1995, AM MIDL NAT, V134, P41 HERKERT JR, 1996, NC187 USDA FOR SERV, P89 HINES JE, 1999, BIRD STUDY S, V46, P209 HODGSON JG, 2005, BIOL CONSERV, V122, P263 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 JOHNSGARD PA, 1979, BIRDS GREAT PLAINS JOHNSON DH, 1980, ECOLOGY, V61, P65 KNOPF FL, 1994, STUDIES AVIAN BIOL, V15, P247 KUCHLER AW, 1993, POTENTIAL NATURAL VE LAUENROTH WK, 1999, GREAT PLAINS RES, V9, P223 LICHSTEIN JW, 2002, ECOL MONOGR, V72, P445 MAGURRAN AE, 1988, ECOLOGICAL DIVERSITY MCGARIGAL K, 1995, ECOL MONOGR, V65, P235 MCGARIGAL K, 2002, FRAGSTATS SPATIAL PA MOLLER AP, 2002, OECOLOGIA, V132, P492 MORAN PAP, 1950, BIOMETRIKA, V37, P17 NICHOLS JD, 1992, BIOSCIENCE, V42, P94 NICHOLS JD, 1998, CONSERV BIOL, V12, P1390 PETERJOHN BG, 1993, BIRD POPULATIONS, V1, P1 PETERJOHN BG, 1999, STUDIES AVIAN BIOL, V19, P27 PIMM SL, 1988, AM NAT, V132, P757 PIMM SL, 1991, BALANCE NATURE POFF NL, 1997, J N AM BENTHOL SOC, V16, P391 PULLIAM HR, 1986, AM ZOOL, V26, P71 RAPPORT DJ, 1985, AM NAT, V125, P617 RICKETTS TH, 2001, AM NAT, V158, P87 ROBINSON SK, 1995, SCIENCE, V267, P1987 ROSENZWEIG ML, 1995, SPECIES DIVERSITY SP SAMSON FB, 1996, PRAIRIE CONSERVATINO SCHELL SP, 1997, ENVIRON ENTOMOL, V26, P1056 SHAPIRO SS, 1965, BIOMETRIKA, V52, P591 SIEG CH, 1999, GREAT PLAINS RES, V9, P277 SIMS PL, 1988, N AM TERRESTRIAL VEG, P265 SMALL MF, 1988, OECOLOGIA, V76, P62 STUBBENDIECK J, 1988, RM158 USDA FOR SERV, P21 TJORVE E, 2003, J BIOGEOGR, V30, P827 WEAVER JE, 1954, N AM PRAIRIE WIENS JA, 1973, ECOL MONOGR, V43, P237 WIENS JA, 1979, OECOLOGIA, V42, P253 WIENS JA, 1981, STUDIES AVIAN BIOL, V6, P513 ZIMMERMAN K, 1998, WYOM GRASSH INF SYST 0921-2973 Landsc. Ecol.ISI:000237487700009Colorado State Univ, Dept Fishery & Wildlife Biol, Ft Collins, CO 80523 USA. US Forest Serv, Rocky Mt Res Stn, Ft Collins, CO 80526 USA. Hamer, TL, Colorado State Univ, Dept Fishery & Wildlife Biol, Ft Collins, CO 80523 USA. Tammy.Hamer@ColoState.eduEnglish<7Hammett, J. E.1992kThe shapes of adaptation - Historical ecology of anthropogenic Landscapes in the southeastern United States121-135Landscape Ecology72XHISTORICAL ECOLOGY; NATIVE NORTH AMERICANS; ANTHROPOGENIC LANDSCAPES; CORRIDORS; PATCHESArticleJulNative inhabitants of the Southeastern United States traditionally practiced land management strategies, including burning and clearing, that created 'anthropogenic landscapes'. From the viewpoint of landscape ecology, analysis of historic documents including drawings and deerkin maps from the sixteenth, seventeenth and eighteenth centuries depicted the Native Southeastern landscape as a series of circular patches surrounded by buffer areas. This character contrasted sharply with early European coastal settlements which were more typically rectangular in shape. Differences between Native American and European land use patterns and implied perceptions of the landscape reflect distinct differences in their respective cultural models and intentionality.://A1992JF61500005 IISI Document Delivery No.: JF615 Times Cited: 18 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1992JF61500005EHAMMETT, JE, UNIV N CAROLINA,ANTHROPOL RES LABS,CHAPEL HILL,NC 27514.English|7 Hammett, J. E.1992kThe Shapes of Adaptation - Historical Ecology of Anthropogenic Landscapes in the Southeastern United-States121-135Landscape Ecology72Thistorical ecology native north americans anthropogenic landscapes corridors patchesJulNative inhabitants of the Southeastern United States traditionally practiced land management strategies, including burning and clearing, that created 'anthropogenic landscapes'. From the viewpoint of landscape ecology, analysis of historic documents including drawings and deerkin maps from the sixteenth, seventeenth and eighteenth centuries depicted the Native Southeastern landscape as a series of circular patches surrounded by buffer areas. This character contrasted sharply with early European coastal settlements which were more typically rectangular in shape. Differences between Native American and European land use patterns and implied perceptions of the landscape reflect distinct differences in their respective cultural models and intentionality.://A1992JF61500005-Jf615 Times Cited:27 Cited References Count:0 0921-2973ISI:A1992JF61500005CHammett, Je Univ N Carolina,Anthropol Res Labs,Chapel Hill,Nc 27514English <71Hamre, L. N. Domaas, S. T. Austad, I. Rydgren, K.2007Land-cover and structural changes in a western Norwegian cultural landscape since 1865, based on an old cadastral map and a field survey 1563-1574Landscape Ecology2210cadastral map cultural landscape GIS land-cover change man-made structures map transformation statistical testing urnes stave church PLANT-SPECIES RICHNESS AGRICULTURAL LANDSCAPES AERIAL PHOTOGRAPHS RURAL LANDSCAPE HAY MEADOWS PATTERNS BIODIVERSITY MANAGEMENT GERMANY GISArticleDec-Many studies of land-cover and structural changes in cultural landscapes have used historical maps as a source for information about past land-cover. All transformations of historical maps onto modern coordinate systems are however burdened with difficulties when it comes to accuracy. We show that a detailed land survey of the present landscape may enable transformation of an old cadastral map directly onto the present terrain with very high accuracy. The detailed resulting map enabled us to locate remnants of semi-natural grasslands and man-made structures with continuity from 1865 and to test hypotheses about relationships between landscape changes and landscape characteristics. The main land-cover change 1865-2002 was decrease of arable fields, and addition of three new land-cover classes: horticultural, orchard and abandoned areas. Of the 330 man-made structures present in 1865, only 58 remained in 2002, while 63 new structures had been built after 1865. We found that semi-natural grasslands with continuity since 1865 were situated on ground with significantly lower production capacity than mean 1865 production capacity. The man-made structures with continuity since 1865 were also associated with areas with significantly lower production capacity than the 1865 mean, situated in significantly steeper terrain but not further from the hamlet. Our study illustrates the potential of digitised and accurately transformed historical cadastral maps combined with detailed field surveys for analysis of land-cover and structural changes in the cultural landscape.://000250632100014ISI Document Delivery No.: 227BL Times Cited: 0 Cited Reference Count: 52 Hamre, Liv Norunn Domaas, Stein Tage Austad, Ingvild Rydgren, Knut 0921-2973 Landsc. Ecol.ISI:000250632100014Sogn Og Fjordane Univ Coll, N-6851 Sogndal, Norway. Finnmark Cty Author, N-9815 Vasdo, Norway. Hamre, LN, Sogn Og Fjordane Univ Coll, POB 133, N-6851 Sogndal, Norway. liv.hamre@hisf.noEnglish|?- Hanan, E. J. Ross, M. S.2010sAcross-scale patterning of plant-soil-water interactions surrounding tree islands in Southern Everglades landscapes463-476Landscape Ecology253nThe freshwater Everglades is a complex system containing thousands of tree islands embedded within a marsh-grassland matrix. The tree island-marsh mosaic is shaped and maintained by hydrologic, edaphic and biological mechanisms that interact across multiple scales. Preserving tree islands requires a more integrated understanding of how scale-dependent phenomena interact in the larger freshwater system. The hierarchical patch dynamics paradigm provides a conceptual framework for exploring multi-scale interactions within complex systems. We used a three-tiered approach to examine the spatial variability and patterning of nutrients in relation to site parameters within and between two hydrologically defined Everglades landscapes: the freshwater Marl Prairie and the Ridge and Slough. Results were scale-dependent and complexly interrelated. Total carbon and nitrogen patterning were correlated with organic matter accumulation, driven by hydrologic conditions at the system scale. Total and bioavailable phosphorus were most strongly related to woody plant patterning within landscapes, and were found to be 3 to 11 times more concentrated in tree island soils compared to surrounding marshes. Below canopy resource islands in the slough were elongated in a downstream direction, indicating soil resource directional drift. Combined multi-scale results suggest that hydrology plays a significant role in landscape patterning and also the development and maintenance of tree islands. Once developed, tree islands appear to exert influence over the spatial distribution of nutrients, which can reciprocally affect other ecological processes.!://WOS:000275122600011Times Cited: 0 0921-2973WOS:00027512260001110.1007/s10980-009-9426-9 ? %Hanberry, Brice Palik, Brian He, Hong2012zComparison of historical and current forest surveys for detection of homogenization and mesophication of Minnesota forests 1495-1512Landscape Ecology2710Springer NetherlandsBiomedical and Life Sciences Intense harvesting and slash fires during the late 1800s and early 1900s led to homogenization throughout the Great Lakes region via the conversion from tamarack, pine, and spruce forests to aspen forests, which are supported by the forest products industry. Subsequently, mesophication occurred in the eastern United States due to fire suppression, transforming oak woodlands to mixed mesophytic forests. We explored both homogenization and mesophication at a regional scale by quantifying changes in community composition and density between historical General Land Office survey points and current USDA Forest Analysis and Inventory plots for Minnesota’s Laurentian Mixed and Eastern Broadleaf Forest provinces. We used the Morisita plotless density estimator and applied corrections for surveyor bias to estimate density for historical forests and we used known densities of FIA plots to predict current densities with random forests, an ensemble regression tree method, and terrain and soil predictor variables. Of the 43 ecological units used in the analysis, only one current community was similar to its historical counterpart. Within the Laurentian Mixed Forest province, forest density of primarily mature aspen stands is reduced slightly today compared to the tamarack-dominated forests of the past. Conversely, in the Eastern Broadleaf Forest province, forest densities have increased compared to historical pine and oak woodlands, due to increases of densely growing, fire-sensitive species. Ordinations of functional traits and structure showed substantial changes between current and historical communities as well as reduced differentiation among current communities compared to their historical counterparts. Homogenization in the Laurentian Mixed Forest is occurring by transition from early-successional to late-successional species, with associated changes in forest ecosystems, and homogenization and mesophication in the Eastern Broadleaf Forest are occurring by transition from disturbance-stabilized genera of open forest ecosystems to non-disturbance-dependent genera of dense forests. Despite different starting points of historical forest ecosystems in the Laurentian Mixed Forest and Eastern Broadleaf Forest, we found homogenization and mesophication to be interrelated in the convergence of composition and densities along a common trajectory to dense forests composed of late-successional species in Minnesota.+http://dx.doi.org/10.1007/s10980-012-9805-5 0921-297310.1007/s10980-012-9805-5|?a SHanberry, Brice B. Fraver, Shawn He, Hong S. Yang, Jian Dey, Dan C. Palik, Brian J.2011dSpatial pattern corrections and sample sizes for forest density estimates of historical tree surveys59-68Landscape Ecology261JanIThe U.S. General Land Office land surveys document trees present during European settlement. However, use of these surveys for calculating historical forest density and other derived metrics is limited by uncertainty about the performance of plotless density estimators under a range of conditions. Therefore, we tested two plotless density estimators, developed by Morisita and Pollard, for two, three, and four trees per survey point under simulated ranges of tree densities, non-uniform densities, and different tree spatial distributions. Based on these results, we developed estimator corrections and determined number of survey points needed for reliable density estimates. The Morisita estimator was accurate for densities ranging from 5 to 1,000 trees per unit area, non-uniform densities, random and regular spatial distribution, and outperformed the Pollard estimator. Estimators using points with two or three trees did need a simple correction to account for overestimation. Likewise, for clustered distributions, depending on the number of trees per survey point and the amount of clustering, there should be adjustment for a range of under and overestimation. Sample sizes for survey points with three or four trees should be at least 200 survey points, and 1,000 survey points will have density estimates within +/- 10% tolerance range of actual density. For survey points with two trees, the minimum sample size should be 600 survey points, and 2,000 survey points should be the target value. These results provide guidelines for researchers to improve density estimates of historical forests.!://WOS:000286004400006Times Cited: 0 0921-2973WOS:00028600440000610.1007/s10980-010-9533-7|?) iHansbauer, M. M. Storch, I. Knauer, F. Pilz, S. Kuchenhoff, H. Vegvari, Z. Pimentel, R. G. Metzger, J. P.2010qLandscape perception by forest understory birds in the Atlantic Rainforest: black-and-white versus shades of grey407-417Landscape Ecology253*Even among forest specialists, species-specific responses to anthropogenic forest fragmentation may vary considerably. Some appear to be confined to forest interiors, and perceive a fragmented landscape as a mosaic of suitable fragments and hostile matrix. Others, however, are able to make use of matrix habitats and perceive the landscape in shades of grey rather than black-and-white. We analysed data of 42 Chiroxiphia caudata (Blue Manakin), 10 Pyriglena leucoptera (White-shouldered Fire-eye) and 19 Sclerurus scansor (Rufous-breasted Leaftosser) radio-tracked in the Atlantic Rainforest of Brazil between 2003 and 2005. We illustrate how habitat preferences may determine how species respond to or perceive the landscape structure. We compared available with used habitat to develop a species-specific preference index for each of six habitat classes. All three species preferred old forest, but relative use of other classes differed significantly. S. scansor perceived great contrast between old forest and matrix, whereas the other two species perceived greater habitat continuity. For conservation planning, our study offers three important messages: (1) some forest specialist species are able to persist in highly fragmented landscapes; (2) some forest species may be able to make use of different anthropogenic habitat types to various degrees; whereas (3) others are restricted to the remaining forest fragments. Our study suggests species most confined to forest interiors to be considered as potential umbrella species for landscape-scale conservation planning.!://WOS:000275122600007Times Cited: 0 0921-2973WOS:00027512260000710.1007/s10980-009-9418-9<77Hansen, A. J. Rotella, J. J. Kraska, M. P. V. Brown, D.2000MSpatial patterns of primary productivity in the Greater Yellowstone Ecosystem505-522Landscape Ecology156abiotic controls Greater Yellowstone ecosystem landscape patterns net primary productivity NET PRIMARY PRODUCTION TALLGRASS PRAIRIE NATIONAL-PARK BIOMASS FIRE FORESTS MOUNTAINS DIVERSITY GRADIENTArticleAug Landscapes are often heterogeneous in abiotic factors such as topography, climate, and soil, yet little is known about how these factors may influence the spatial distribution of primary productivity. We report estimates of aboveground net primary productivity (ANPP) in 90 sample stands stratified by cover type and elevation class, and use the results to predict ANPP across a portion of the Greater Yellowstone Ecosystem. Tree ANPP was estimated by sampling tree density by species and diameter classes and estimating average annual diameter increment by tree coring. Biomass for current tree diameter and past tree diameter were calculated by species and diameter class for each stand using the dimension analysis software BIOPAK. Shrub ANPP was estimated by calculating current biomass from basal area using BIOPAK and dividing by the assumed average life span of the shrubs. Clipping at the end of the growing season was used to estimate herb ANPP. Differences in ANPP among cover types and elevation classes were examined with analysis of variance. Multiple regression was used to examine relationships between ANPP, and soil parent material, topography, and cover type. The best regression model was used to predict ANPP across the study area. We found ANPP was highest in cottonwood, Douglas-fir, and aspen stands, intermediate in various seral stages of lodgepole pine, and lowest in grassland and sagebrush cover types. Parent material explained significant variation in ANPP in mature and old-growth lodgepole pine stands, with rhyolite ash/loess being the most productive parent material type. ANPP decreased with increasing elevation in most cover types, possibly because low temperatures limit plant growth at higher elevations in the study area. ANPP was not related to elevation in mature and old-growth lodgepole pine stands, due to relatively rapid growth of subalpine fir at higher elevations. A regression model based on cover type and elevation explained 89% of the variation in ANPP among the sample stands. This model was used to generate a spatially continuous surface of predicted ANPP across the study area. The frequency distribution of predicted ANPP was skewed towards lower levels of ANPP, and only 6.3% of the study area had a predicted ANPP level exceeding 4500 kg/ha/yr. Patches high in predicted ANPP were primarily at lower elevations, outside of Yellowstone National Park, and near the national forest/private lands boundary. These patterns of ANPP may influence fire behavior, vertebrate population dynamics, and other ecological processes. The results reinforce the need for coordinated management across ownership boundaries in the Greater Yellowstone Ecosystem.://000088037200002 ISI Document Delivery No.: 331UN Times Cited: 22 Cited Reference Count: 45 Cited References: *ESRI, 1982, ARC INFO ON LINE DOC *SAS I INC, 1991, SAS STAT US GUID REL *US GEOL SURV, 1993, DAT US GUID 5 DIG EL AKAIKE H, 1973, INT S INF THEOR, P267 BAKER WL, 1992, LANDSCAPE ECOL, V7, P181 BARRETT SW, 1994, INT J WILDLAND FIRE, V4, P65 BORMANN FH, 1970, ECOL MONOGR, V40, P373 BOWERMAN TS, 1997, TARGHEE NATL FOREST BOYCE MS, 1991, GREATER YELLOWSTONE, P183 BRADLEY AF, 1992, GTRINT290 USDA FOR S BURKE IC, 1991, BIOSCIENCE, V41, P685 BURKE IC, 1997, ECOLOGY, V78, P1330 BURNHAM KP, 1992, WILDLIFE 2001 POPULA, P16 CROW TR, 1978, ECOLOGY, V59, P265 DAUBENMIRE R, 1952, ECOL MONOGR, V22, P301 DAVIS CE, 1996, SOIL SURVEY GALLATIN DESPAIN D, 1990, YELLOWSTONE VEGETATI GRAUMLICH LJ, 1989, ECOLOGY, V70, P405 HANSEN AJ, 1999, ECOL APPL, V9, P1459 HUSTON MA, 1994, BIOL DIVERSITY KEANE RE, 1996, TREE PHYSIOL, V16, P319 KEITER RB, 1991, GREATER YELLOWSTONE KNAPP AK, 1993, ECOLOGY, V74, P549 LAW BE, 1994, ECOL APPL, V4, P717 MA ZK, 1995, PHOTOGRAMM ENG REM S, V61, P435 MCGARIGAL K, 1994, FRAGSTATS SPATIAL PA MEANS JE, 1994, PNWGTR340 USDA FOR S PEARSON JA, 1987, ECOLOGY, V68, P1966 PERRY DA, 1994, FOREST ECOSYSTEMS PULLIAM HR, 1988, AM NAT, V132, P652 PULLIAM HR, 1991, AM NAT S, V137, P50 RAICH JW, 1997, ECOLOGY, V78, P707 RODMAN A, 1996, YCRNRSR962 ROMME WH, 1982, ECOL MONOGR, V52, P199 ROSENZWEIG ML, 1995, SPECIES DIVERSITY SP SABIN TE, 1990, SPECIAL PUBLICATION, V20 SINGH SP, 1994, ECOL MONOGR, V64, P401 TURNER CL, 1997, ECOLOGY, V78, P1832 TURNER MG, 1994, LANDSCAPE ECOL, V9, P59 VEBLEN TT, 1998, TERRESTRIAL VEGETATI WALSH SJ, 1994, AM SOC PHOTOG REMOTE, P151 WARING RH, 1985, FOREST ECOSYSTEMS CO WHITE JD, 1994, J VEG SCI, V5, P687 WHITTAKER RH, 1975, COMMUNITIES ECOSYSTE WHITTAKER RH, 1975, ECOLOGY, V56, P771 0921-2973 Landsc. Ecol.ISI:000088037200002wMontana State Univ, Dept Biol, Bozeman, MT 59717 USA. Hansen, AJ, Montana State Univ, Dept Biol, Bozeman, MT 59717 USA.Englishd<7Hansen, A. J. Urban, D. L.1992HAvian response to landscape pattern - the role of species life histories163-180Landscape Ecology73mAVIAN COMMUNITIES; EASTERN DECIDUOUS FOREST; LANDSCAPE PATTERN; LIFE-HISTORY TRAITS; PACIFIC NORTHWEST FORESTArticleSepTWe suggest that the life histories of species within communities may differ among geographic locations and that communities from distinct biomes may respond uniquely to a given trajectory of landscape change. This paper presents initial tests relevant to these hypotheses. First, the representation of various life-history guilds in avifaunas from the Eastern Deciduous (EDF) and Pacific Northwest (PNW) forests were compared. Three guilds contained more species in the EDF community (large patch and/or habitat interior guild, small patch and/or edge guild, and fragmentation-sensitive guild). The guild of predators requiring large forest tracts was better represented in the PNW. Next, the relative sensitivity of each community to habitat change was ranked based on the life-history traits of their species. The EDF avifauna had a significantly higher index of sensitivity to both forest fragmentation and to landscape change in general. Among the birds with high scores for sensitivity to landscape change were several species that have received little conservation attention thus far including some associated with open-canopy habitats. Lastly, the validity of using life histories to predict community response to landscape change was supported by the fact that the sensitivity scores for PNW species correlated significantly with independent data on species population trends. While more rigorous analyses are suggested, we conclude that knowledge of life histories is useful for predicting community response to landscape change and that conservation strategies should be uniquely tailored to local communities.://A1992JW40100003 IISI Document Delivery No.: JW401 Times Cited: 85 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1992JW40100003AHANSEN, AJ, OREGON STATE UNIV,DEPT FOREST SCI,CORVALLIS,OR 97331.Englishڽ7 qHansen, Raili Mander, Ülo Soosaar, Kaido Maddison, Martin Lõhmus, Krista Kupper, Priit Kanal, Arno Sõber, Jaak2013EGreenhouse gas fluxes in an open air humidity manipulation experiment637-649Landscape Ecology284Springer Netherlands@Carbon dioxide Climate change Methane Nitrous oxide Water vapour 2013/04/01+http://dx.doi.org/10.1007/s10980-012-9775-7 0921-2973Landscape Ecol10.1007/s10980-012-9775-7EnglishY<7 Hansson, L.1994QVertebrate distributions relative to clear-cut edges in a boreal forest landscape105-115Landscape Ecology92<MAMMALS; BIRDS; BOREAL FOREST; CLEAR-CUT; EDGE; DISTRIBUTIONArticleJunvClearcutting is the main method of harvesting boreal forests, to some extent mimicking natural disturbances by fire and wind-felling. Effects of clearcutting on vertebrate fauna in managed forests was examined by small mammal trapping in spring and autumn, winter censuses of mammal snow tracks and censuses of birds in spring and summer in one central and one edge (125 m) section of large clearcuts and mature forests, respectively. There was a separate clearcut fauna, at least on large clearcuts, that was well distinguished from the forest fauna. There was not any physiognomic ecotone but the forest fauna showed a marked edge effect with larger numbers of many species in the peripheral parts of the forest. In the forests examined, with a Western European bird fauna, there were no typical interior forest species, in contrast to northern taiga forests. The present forest species easily changed distributions seasonally and according to variations in snow conditions and food abundance. Such generalist species in the boreal forest will therefore vary considerably in local density according to landscape composition but will also show large-scale persistence. They may have been selected for as a result of man's restructuring of temperate and boreal landscapes, e.g. by forest management. Edge effects seem to arise for several reasons but will probably only apply to generalist species.://A1994NU09400003 IISI Document Delivery No.: NU094 Times Cited: 36 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1994NU09400003KHANSSON, L, SWEDISH UNIV AGR SCI,DEPT WILDLIFE ECOL,S-75007 UPPSALA,SWEDEN.English2?GHansson, L. P. Angelstam1991@Landscape ecology as a theoretical basis for nature conservation191-201Landscape Ecology54]landscape change, habitat fragmentation, conservation biology, management, climax, succession.Conservation of representative biotopes, single species populations or biodiversity usually embraces two or more biotopes, and is often affected by surrounding croplands. The conclusions from landscape ecological studies can, therefore, offer important contributions to conservation, especially at early levels of landscape change or habitat fragmentation. Indicator and keystone species are useful for monitoring and managing fragmented biotopes, respectively. Communities as well as single species are affected by the juxtaposition of successional and climax biotopes, which influence climatic equability, seasonality, productivity and dispersal. Low levels of fragmentation may result in ill-functioning communities, and greater fragmentation may result in species losses and ultimately in the loss of whole communities. Fragmented habitats retain species with high reproductive and dispersal rates and generalized habitat selection. New combinations of interacting species will lead to trivialization of earlier habitat-specific interactions. Validation of these concepts was made with data from a Swedish research program on fragmented biotopes in production landscapes. General reserve selection and methods of management for preserving climax communities, single specialized species and high biodiversity are suggested.R|?PHao, Lu Sun, Ge Liu, Yongqiang Gao, Zhiqiu He, Junjie Shi, Tingting Wu, Bingjuan2014lEffects of precipitation on grassland ecosystem restoration under grazing exclusion in Inner Mongolia, China 1657-1673Landscape Ecology2910DecChina launched the "Returning Grazing Lands to Grasslands" project about a decade ago to restore severely degraded grasslands. Grassland grazing exclusion was one of the experimental approaches for achieving the grand goal. Here, we evaluate the long-term regional ecological effects of grassland grazing exclusion in the Xilingol region of Inner Mongolia, China. The dynamics of grassland communities over 8 years (2004-2011) were continuously monitored at 11 research sites dominated by temperate steppe ecosystems. These sites represent the diverse landscapes of the Mongolian Plateau in the Arid, Semi-Arid, and Humid Climatic Zones that have varying precipitation levels. The community structure of degraded grasslands was found to recover quickly toward a benign state after grazing exclusion. The exclusion promoted an increase in mean plant community height, coverage, aboveground fresh biomass, and quality. The grasslands recovered fastest and most favorably in the Humid Zone followed by the Semi-Arid Zone and the Arid Zone. The increase in the aboveground biomass and vegetation height correlated significantly with the amount of total growing season precipitation. Precipitation therefore amplified the grazing exclusion effects on grassland restoration. Grazing exclusion was most effective in the relatively moist part of the study region. However, other factors such as global climate change and variability might have interacted with grazing management practices, thereby influencing the outcomes of grassland restoration efforts in Inner Mongolia. Future implementations of grassland ecosystem management should consider the regional climatic heterogeneity to maximize costs/benefits for achieving long-term ecosystem sustainability.!://WOS:000346920900003Times Cited: 0 0921-2973WOS:00034692090000310.1007/s10980-014-0092-1ڽ7 [Hardt, Elisa dos Santos, RozelyF Pablo, CarlosL Agar, PilarMartín Pereira-Silva, EricoF L.2013sUtility of landscape mosaics and boundaries in forest conservation decision making in the Atlantic Forest of Brazil385-399Landscape Ecology283Springer Netherlands]Landscape management Legal protection Change vector Landscape heterogeneity Landscape metrics 2013/03/01+http://dx.doi.org/10.1007/s10980-013-9845-5 0921-2973Landscape Ecol10.1007/s10980-013-9845-5EnglishM<7l,Hargis, C. D. Bissonette, J. A. David, J. L.1998UThe behavior of landscape metrics commonly used in the study of habitat fragmentation167-186Landscape Ecology133landscape ecology landscape measures fragmentation mean proximity index perimeter-area fractal dimension mass fractal dimension FRACTAL DIMENSION FOREST LANDSCAPE PATTERNS OREGON RANGE USAArticleJunA meaningful interpretation of landscape metrics is possible only when the limitations of each measure are fully understood, the range of attainable values is known, and the user is aware of potential shifts in the range of values due to characteristics of landscape patches. To examine the behavior of landscape metrics, we generated artificial landscapes that mimicked fragmentation processes while controlling the size and shape of patches in the landscape and the mode of disturbance growth. We developed nine series of increasingly fragmented landscapes and used these to investigate the behavior of edge density, contagion, mean nearest neighbor distance, mean proximity index, perimeter-area fractal dimension, and mass fractal dimension. We found that most of the measures were highly correlated, especially contagion and edge density, which had a near-perfect inverse correspondence. Many of the measures were linearly-associated with increasing disturbance until the proportion of disturbance on the landscape was approximately 0.40, with non-linear associations at higher proportions. None of the measures was able to differentiate between landscape patterns characterized by dispersed versus aggregated patches. The highest attainable value of each measure was altered by either patch size or shape, and in some cases, by both attributes. We summarize our findings by discussing the utility of each metric.://000079303300003 ISI Document Delivery No.: 179BH Times Cited: 105 Cited Reference Count: 37 Cited References: 1982, FED REG, V47, P43051 ANDREN H, 1994, OIKOS, V71, P355 BURROUGH PA, 1981, NATURE, V294, P240 BURROUGH PA, 1986, PRINCIPLES GEOGRAPHI DUNN CP, 1991, QUANTITATIVE METHODS, P173 FORMAN RTT, 1986, LANDSCAPE ECOLOGY GARDNER RH, 1991, QUANTITATIVE METHODS, P289 GROSSMAN T, 1987, J PHYS A, V20, L1193 GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 KLEINBAUM DG, 1988, APPL REGRESSION ANAL KRUMMEL JR, 1987, OIKOS, V48, P321 LI H, 1993, LANDSCAPE ECOL, V8, P63 LI HB, 1993, LANDSCAPE ECOL, V8, P155 LOVEJOY S, 1982, SCIENCE, V216, P185 MCGARIGAL K, 1995, ECOL MONOGR, V65, P235 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MILNE BT, 1991, QUANTITATIVE METHODS, P199 MILNE BT, 1992, AM NAT, V139, P32 MILNE BT, 1992, THEOR POPUL BIOL, V41, P337 MILNE BT, 1994, EASTSIDE FOREST ECOS, V2, P121 MUSICK HB, 1991, QUANTITATIVE METHODS, P289 OLSEN ER, 1993, PHOTOGRAMM ENG REM S, V59, P1517 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 RIPPLE WJ, 1991, BIOL CONSERV, V57, P73 RITCHIE M, UNPUB SCALE DEPENDEN RITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 ROBARDS FC, 1976, OBSERVATIONS 2760 BA ROGERS CA, 1993, THESIS S FRASER U BU SPETICH MA, 1997, NAT AREA J, V17, P118 SPIES TA, 1994, ECOL APPL, V4, P555 STAUFFERD, 1985, INTRO PERCOLATION TH TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 VOSS RF, 1984, J PHYS A-MATH GEN, V17, L373 VOSS RF, 1988, SCI FRACTAL IMAGES, P21 WALLIN DO, 1994, ECOL APPL, V4, P569 WHITCOMB RF, 1981, FOREST ISLAND DYNAMI, P125 0921-2973 Landsc. Ecol.ISI:000079303300003Utah State Univ, Coll Nat Resources, Utah Cooperat Fish & Wildlife Res Unit, US Geol Survey,Biol Resources Div, Logan, UT 84322 USA. Hargis, CD, Rocky Mt Forest & Range Expt Stn, SW Forest Sci Complex,2500 S Pine Knoll, Flagstaff, AZ 86001 USA.English <7/Hargrove, W. W. Hoffman, F. M. Efroymson, R. A.2005IA practical map-analysis tool for detecting potential dispersal corridors361-373Landscape Ecology204connectivity; fragmentation; matrix; metapopulation; movement; network; patch; preserve design; sink; source; travel path PATCH COLONIZATION; LANDSCAPESArticleMayWe describe the Pathway Analysis Through Habitat (PATH) tool, which can predict the location of potential corridors of animal movement between patches of habitat within any map. The algorithm works by launching virtual entities that we call 'walkers' from each patch of habitat in the map, simulating their travel as they Journey through land cover types in the intervening matrix, and finally arrive at a different habitat 'island.' Each walker is imbued with a Set Of User-specified habitat preferences that make its walking behavior resemble a particular animal species. Because the tool operates in parallel on a supercomputer, large numbers of walkers can be efficiently simulated. The importance of each habitat patch as a source or a sink for a species is calculated, consistent with existing concepts in the metapopulation literature. The manipulation of a series of contrived artificial landscapes demonstrates that the location of potential dispersal corridors and relative Source and sink importance among patches can be purposefully altered in expected ways. Finally, potential dispersal corridors are predicted among remnant woodlots within three actual landscape maps.://000233035100001 2ISI Document Delivery No.: 980RE Times Cited: 1 Cited Reference Count: 33 Cited References: ANDERSON GS, 1997, LANDSCAPE ECOL, V12, P261 BEIER P, 1998, CONSERV BIOL, V12, P1241 BENNETT AF, 1999, LINKAGES LANDSCAPE R BROWN JH, 1977, ECOLOGY, V58, P445 CANTWELL MD, 1993, LANDSCAPE ECOL, V8, P239 CARR MH, 2002, UNPUB FINAL REPORT S DANIELSON BJ, 2000, LANDSCAPE ECOL, V15, P323 DRAMSTAD WE, 1996, LANDSCAPE ECOLOGY PR DUNNING JB, 1995, CONSERV BIOL, V9, P542 FORMAN RTT, 1983, EKOL CSSR, V2, P375 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY GARDNER RH, 2003, ECOL MODEL, V171, P339 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 HADDAD N, 2000, CONSERV BIOL, V14, P738 HADDAD NM, 1999, ECOL APPL, V9, P623 HANSKI IA, 1997, METAPOPULATION BIOL HARGROVE WW, 2001, SCI AM, V256, P72 LEVINS R, 1969, B ENTOMOL SOC AM, V15, P237 MACARTHUR RH, 1967, THEORY ISLAND BIOGEO NOSS RF, 1987, CONSERV BIOL, V1, P159 OKUBO A, 1980, DIFFUSION ECOLOGICAL PULLIAM HR, 1988, AM NAT, V132, P652 PULLIAM HR, 1991, AM NAT, V137, P550 PULLIAM HR, 1992, ECOL APPL, V2, P165 PULLIAM HR, 1996, POPULATION DYNAMICS, P45 RIFFELL SK, 1996, LANDSCAPE ECOL, V11, P157 SIMBERLOFF D, 1987, CONSERV BIOL, V1, P63 SIMBERLOFF D, 1992, CONSERV BIOL, V6, P493 SISK TD, 2002, INTEGRATING LANDSCAP, P208 STAUFFER D, 1992, INTRO PERCOLATION TH TEWKSBURY JJ, 2002, P NATL ACAD SCI USA, V99, P12923 WALKER R, 1997, 1997 ESRI US C PUBL WALKER R, 1998, SENSE PLACE ATLAS IS, P113 0921-2973 Landsc. Ecol.ISI:000233035100001Oak Ridge Natl Lab, Div Environm Sci, Oak Ridge, TN 37831 USA. Oak Ridge Natl Lab, Div Math & Comp Sci, Oak Ridge, TN 37831 USA. Hargrove, WW, Oak Ridge Natl Lab, Div Environm Sci, POB 2008, Oak Ridge, TN 37831 USA. hnw@fire.esd.ornl.govEnglish &?IHargrove, W. W. Pickering, J.19926Pseudoreplication: A sine qua non for regional ecology251-258Landscape Ecology64Mstatistics, sampling, experimentation, experimental design, landscape ecology9We question whether classical experimentation is adequate for real progress in landscape or regional ecology. One cannot do classical experimentation unless one can replicate the treatment. There is conflict between the need to replicate and the need to study processes at appropriately large scales. Because of the difficulties in doing controlled field experiments at regional scales, we propose that landscape ecologists take greater advantage of natural field experiments. Natural experiments must be coordinated, standardized, and synchronized over space and through time, and will require the cooperation of multiple investigators. Distributed computer networks can help provide the automated region-wide monitoring which will supply natural experiments with pre-treatment data. Regions or landscapes need not be ‘replicated’, and indeed, cannot be. One can achieve a relational understanding between a system’s response and environmental characteristics. This understanding is not definitive, but allows for the development of testable hypotheses, in the classical sense. The confounding of space, time, and/or other environmental factors in pseudoreplicated natural experiments only allows for the development of hypotheses - ‘how-possibly’ explanations. Discrimination among competing hypotheses can be done at smaller scales and used to infer processes occurring at larger scales. Use of natural and controlled field experiments in complementary roles is a more promising approach than views of one or the other as methodologically inferior.|?YAHarris, Kimberley M. Dickinson, Katharine J. M. Whigham, Peter A.2014kFunctional connectivity and matrix quality: network analysis for a critically endangered New Zealand lizard41-53Landscape Ecology291JanAgricultural modification commonly leads to reductions in vegetation matrix quality and a resultant decrease in functional connectivity. In this study, a network analysis approach was used to assess the impact of agriculturally-induced reductions in vegetation matrix quality on the metapopulation dynamics of the critically endangered New Zealand grand skink (Oligosoma grande). Vegetation matrix quality was quantified in four sites exhibiting differing levels of modification within indigenous tussock grasslands in eastern Central Otago, New Zealand. Grand skink occupancy probability exhibited a positive correlation with the structural connectivity of primary habitat within the more modified study sites, whereas in the least modified site a complex matrix appeared to compensate for low structural connectivity. Results from this research indicate that the matrix is an important determinant of grand skink metapopulation dynamics and that an intricate balance exists between structural connectivity and the quality of the vegetation matrix. This research highlights the importance of assessing the impact of the matrix for individual species, particularly for conservation management.!://WOS:000330827600004Times Cited: 1 0921-2973WOS:00033082760000410.1007/s10980-013-9967-9 <7V ZHarrisson, K. A. Pavlova, A. Amos, J. N. Takeuchi, N. Lill, A. Radford, J. Q. Sunnucks, P.2012Fine-scale effects of habitat loss and fragmentation despite large-scale gene flow for some regionally declining woodland bird species813-827Landscape Ecology276dispersal demographic connectivity landscape connectivity genetic structure multilocus genotype data population-structure computer-program agricultural environments landscape dispersal differentiation conservation connectivity extinctionJulJHabitat loss and associated fragmentation effects are well-recognised threats to biodiversity. Loss of functional connectivity (mobility, gene flow and demographic continuity) could result in population decline in altered habitat, because smaller, isolated populations are more vulnerable to extinction. We tested whether substantial habitat reduction plus fragmentation is associated with reduced gene flow in three 'decliner' woodland-dependent bird species (eastern yellow robin, weebill and spotted pardalote) identified in earlier work to have declined disproportionately in heavily fragmented landscapes in the Box-Ironbark forest region in north-central Victoria, Australia. For these three decliners, and one 'tolerant' species (striated pardalote), we compared patterns of genetic diversity, relatedness, effective population size, sex-ratios and genic (allele frequency) differentiation among landscapes of different total tree cover, identified population subdivision at the regional scale, and explored fine-scale genotypic (individual-based genetic signature) structure. Unexpectedly high genetic connectivity across the study region was detected for 'decliner' and 'tolerant' species. Power analysis simulations suggest that moderate reductions in gene flow should have been detectable. However, there was evidence of local negative effects of reduced habitat extent and structural connectivity: slightly lower effective population sizes, lower genetic diversity, higher within-site relatedness and altered sex-ratios (for weebill and eastern yellow robin) in 10 x 10 km 'landscapes' with low vegetation cover. We conclude that reduced structural connectivity in the Box-Ironbark ecosystem may still allow sufficient gene flow to avoid the harmful effects of inbreeding in our study species. Although there may still be negative consequences of fragmentation for demographic connectivity, the high genetic connectivity of mobile bird species in this system suggests that reconnecting isolated habitat patches may be less important than increasing habitat extent and/or quality if these need to be traded off.://000305218000003-958DZ Times Cited:0 Cited References Count:67 0921-2973Landscape EcolISI:000305218000003|Harrisson, KA Monash Univ, Sch Biol Sci, Clayton Campus, Melbourne, Vic 3800, Australia Monash Univ, Sch Biol Sci, Clayton Campus, Melbourne, Vic 3800, Australia Monash Univ, Sch Biol Sci, Melbourne, Vic 3800, Australia Monash Univ, Australian Ctr Biodivers, Melbourne, Vic 3800, Australia Deakin Univ, Sch Life & Environm Sci, Landscape Ecol Res Grp, Burwood, Vic 3125, AustraliaDOI 10.1007/s10980-012-9743-2Englishn۽77 Hartel, Tibor2013T. Plieninger and C. Bieling (eds.): Resilience and the cultural landscape—Understanding and managing change in human shaped environments 1841-1843Landscape Ecology289Springer Netherlands 2013/11/01+http://dx.doi.org/10.1007/s10980-013-9922-9 0921-2973Landscape Ecol10.1007/s10980-013-9922-9English|?. ?Hartter, Joel Ryan, Sadie J. Southworth, Jane Chapman, Colin A.2011bLandscapes as continuous entities: forest disturbance and recovery in the Albertine Rift landscape877-890Landscape Ecology266JulKibale National Park, within the Albertine Rift, is known for its rich biodiversity. High human population density and agricultural conversion in the surrounding landscape have created enormous resource pressure on forest fragments outside the park. Kibale presents a complex protected forest landscape comprising intact forest inside the park, logged areas inside the park, a game corridor with degraded forest, and forest fragments in the landscape surrounding the park. To explore the effect of these different levels of forest management and protection over time, we assessed forest change over the previous three decades, using both discrete and continuous data analyses of satellite imagery. Park boundaries have remained fairly intact and forest cover has been maintained or increased inside the park, while there has been a high level of deforestation in the landscape surrounding the park. While absolute changes in land cover are important changes in vegetation productivity, within land cover classes are often more telling of longer term changes and future directions of change. The park has lower Normalized Difference Vegetation Index (NDVI) values than the forest fragments outside the park and the formerly logged area-probably due to forest regeneration and early succession stage. The corridor region has lower productivity, which is surprising given this is also a newer regrowth region and so should be similar to the logged and forest fragments. Overall, concern can be raised for the future trajectory of this park. Although forest cover has been maintained, forest health may be an issue, which for future management, climate change, biodiversity, and increased human pressure may signify troubling signs.!://WOS:000291485400009Times Cited: 0 0921-2973WOS:00029148540000910.1007/s10980-011-9616-0<7Harwood, W. Mac Nally, R.2005PGeometry of large woodland remnants and its influence on avifaunal distributions401-416Landscape Ecology204Australia; Bayesian analyses; birds; box-ironbark forests; habitat fragmentation; landscapes; patch shapes; peninsular effect HABITAT FRAGMENTATION; CENTRAL VICTORIA; EUCALYPT FORESTS; SPECIES RICHNESS; BAJA-CALIFORNIA; MONTANE FOREST; NEST PREDATION; LANDSCAPE; BIRDS; CONSERVATIONArticleMayIn fragmented landscapes, remnant vegetation almost always occurs as irregular shapes and frequently with peninsulas or lobes of habitat extending into the surrounding agricultural matrix. Historical time-series of many landscapes indicate that such lobes tend to be lost through time, making remnants more regularly shaped as more habitat is lost. Although the biogeographic peninsular effect suggests that the biodiversity value of lobes should be less than remnant interiors, R.T.T. Forman has suggested that lobes in fragmented, human-dominated landscapes may provide positive ecological functions. We considered the distribution and occurrence of birds in medium-sized (ca. 2000 ha) remnants of the box-ironbark forests of central Victoria, Australia. We compared transects placed in the interiors, along edges and in lobes, finding that in general woodland-dependent species occurred throughout lobes and edges in densities substantially greater than the interiors of the remnants (often ca. 2 kin from edges). We conducted analyses that weighted species' predilections to occupy the centres of large woodland areas using independent data. We found that: (1) species favouring centres of large woodland areas (measured using independent data) were distributed evenly throughout our study remnants; and (2) species capable of occupying smaller remnants (<= 80 ha) were more prevalent in lobes and along the straight edges of remnants. These results indicate that preservation of lobes is likely to be important for maintaining avian biodiversity in fragmented landscapes, and that the addition of lobes in reconstructing landscapes through revegetation may favour birds.://000233035100004 ISI Document Delivery No.: 980RE Times Cited: 0 Cited Reference Count: 66 Cited References: *UN ENV PROGR, 1995, GLOB BIOD ASS ANDERSON MJ, 2001, AUSTRAL ECOL, V26, P32 ANDREN H, 1994, OIKOS, V71, P355 BAQUERO RA, 2001, BIODIVERS CONSERV, V10, P29 BARBOSA A, 1996, Z SAUGETIERKD, V61, P236 BENNETT AF, 1999, LINKAGES LANDSCAPE R BENTLEY JM, 1997, CONSERV BIOL, V11, P1173 BERNARDO JM, 1994, BAYESIAN THEORY BUSACK SD, 1984, AM NAT, V123, P266 CAGNIN M, 1998, J BIOGEOGR, V25, P1105 CAMARGO JLC, 1995, J TROP ECOL, V11, P205 CAMPI MJ, 2001, ANIM CONSERV 2, V4, P121 CASGRAIN P, 2001, R PACKAGE MULTIVARIA CLARKE KR, 1993, AUST J ECOL, V18, P117 COLLINGE SK, 1998, OIKOS, V82, P66 DEBINSKI DM, 2000, CONSERV BIOL, V14, P342 DORAZIO RM, 2003, ECOL APPL, V13, P556 DOW DD, 1977, EMU, V77, P115 DRAMSTAD WE, 1996, LANDSCAPE ECOLOGY PR FAGAN WE, 1999, AM NAT, V153, P165 FAHRIG L, 2002, ECOL APPL, V12, P346 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FORMAN RTT, 1995, LANDSCAPE ECOL, V10, P133 GELMAN A, 1995, BAYESIAN DATA ANAL GILPIN ME, 1981, AM NAT, V118, P291 GREY MJ, 1997, WILDLIFE RES, V24, P631 GREY MJ, 1998, PAC CONS BIOL, V4, P55 HARPER KA, 2001, ECOLOGY, V82, P649 HARRISON S, 1999, ECOGRAPHY, V22, P225 HOBBS RJ, 1993, BIOL CONSERV, V64, P193 JAYNES ET, 2003, PROBABILITY THEORY L JOHNSON RA, 2002, J BIOGEOGR, V29, P1009 LAMBECK RJ, 1997, CONSERV BIOL, V11, P849 LANCE GN, 1967, AUST COMPUT J, V1, P15 LEE PM, 1989, BAYESIAN STAT LINDENMAYER DB, 2003, ECOL LETT, V6, P41 MACNALLY R, 1997, J AVIAN BIOL, V28, P171 MACNALLY R, 1999, AUST BIOL, V12, P138 MACNALLY R, 2000, BIOL CONSERV, V95, P7 MACNALLY R, 2002, J BIOGEOGR, V29, P395 MAJOR RE, 1996, AUST J ECOL, V21, P399 MAJOR RE, 2001, BIOL CONSERV, V102, P47 MANLY BFJ, 1997, RANDOMIZATION BOOTST MCGOLDRICK JM, 1998, ECOL RES, V13, P125 MILLER JR, 2000, ECOL APPL, V10, P1732 MILNE BT, 1984, ECOLOGY, V67, P967 MURCIA C, 1995, TRENDS ECOL EVOL, V10, P58 PALMER YV, 1955, TRACT YEARS STORY AR RAPOPORT EH, 1994, PHILOS T ROY SOC B, V343, P71 REID JRW, 1999, THREATENED DECLINING RESTREPO C, 1999, ECOLOGY, V80, P668 ROBINSON D, 1996, CONSERVING WOODLAND ROGERS CM, 1997, CONDOR, V99, P622 SIMBERLOFF D, 1992, CONSERV BIOL, V6, P493 SIMPSON GG, 1964, SYST ZOOL, V13, P57 SPIEGELHALTER DJ, 1982, J ROY STAT SOC B MET, V44, P377 SPIELGELHALTER D, 2003, WINBUGS VERSION 1 4 TACKABERRY R, 1996, GLOBAL ECOL BIOGEOGR, V5, P85 TAYLOR RJ, 1978, AM NAT, V112, P583 TRZCINSKI MK, 1999, ECOL APPL, V9, P586 VILLARD MA, 1999, CONSERV BIOL, V13, P774 WALTERS JR, 1999, BIOL CONSERV, V90, P13 WATSON DM, 1999, ECOGRAPHY, V22, P582 WATSON DM, 2000, PACIFIC CONSERVATION, V6, P46 WILSON J, 1999, VICTORIAN NAT, V116, P48 WOODGATE P, 1988, FOREST COVER CHANGES 0921-2973 Landsc. Ecol.ISI:000233035100004 Monash Univ, Anal Policy & Management Sch Biol Sci, Australian Ctr Biodivers, Melbourne, Vic 3800, Australia. Mac Nally, R, Monash Univ, Anal Policy & Management Sch Biol Sci, Australian Ctr Biodivers, Melbourne, Vic 3800, Australia. ralph.macnally@sci.monash.edu.auEnglish<7W ,Hassett, E. M. Stehman, S. V. Wickham, J. D.2012@Estimating landscape pattern metrics from a sample of land cover133-149Landscape Ecology271probability sampling design-based inference horvitz-thompson estimator stratified sampling land-cover change conterminous united-states indexes fragmentation ecology misclassification sensitivity completion indicators corridors trendsJanZAlthough landscape pattern metrics can be computed directly from wall-to-wall land-cover maps, statistical sampling offers a practical alternative when complete coverage land-cover information is unavailable. Partitioning a region into spatial units and then selecting a subset (sample) of these units introduces artificial patch edge and patch truncation effects that may lead to biased sample-based estimators of landscape pattern metrics. The bias and variance of sample-based estimators of status and change in landscape pattern metrics were evaluated for four 120-km x 120-km test regions with land cover provided by the 1992 and 2001 National Land-Cover Data of the United States. Bias was generally small for both the estimators of status and estimators of change in landscape pattern, but exceptions to this favorable result exist and it is advisable to assess bias for the specific metrics and region of interest in any given application. A 10-km x 10-km sample block generally yielded larger biases but smaller variances for the estimators relative to a 20-km x 20-km sample block. Stratified random sampling improved precision of the estimators relative to simple random sampling. The methodology developed to determine properties of sample-based estimators can be readily extended to evaluate other landscape pattern metrics, regions, and sample block sizes.://000298228300011-864HI Times Cited:0 Cited References Count:50 0921-2973Landscape EcolISI:000298228300011+Stehman, SV SUNY Coll Environm Sci & Forestry, 320 Bray Hall,1 Forestry Dr, Syracuse, NY 13210 USA SUNY Coll Environm Sci & Forestry, 320 Bray Hall,1 Forestry Dr, Syracuse, NY 13210 USA SUNY Coll Environm Sci & Forestry, Syracuse, NY 13210 USA US EPA, Div Environm Sci, Res Triangle Pk, NC 27711 USADOI 10.1007/s10980-011-9657-4English <7<Hawbaker, T. J. Radeloff, V. C. Hammer, R. B. Clayton, M. K.2005gRoad density and landscape pattern in relation to housing density, and ownership, land cover, and soils609-625Landscape Ecology205anthropogenic development; fragmentation; generalized least squares; human disturbance; pattern and process; road ecology; Wisconsin PRE-EUROPEAN SETTLEMENT; WISCONSIN PINE-BARRENS; FOREST LANDSCAPE; ROCKY-MOUNTAINS; UNITED-STATES; OLD-GROWTH; USA; FRAGMENTATION; MANAGEMENT; DYNAMICSArticleJulRoads are conspicuous components of landscapes and play a substantial role in defining landscape pattern. Previous studies have demonstrated the link between roads and their effects on ecological processes and landscape patterns. Less understood is the placement of roads, and hence the patterns imposed by roads on the landscape in relation to factors describing land use, land cover, and environmental heterogeneity. Our hypothesis was that variation in road density and landscape patterns created by roads can be explained in relation to variables describing land use, land cover, and environmental factors. We examined both road density and landscape patterns created by roads in relation to suitability of soil substrate as road subgrade, land cover, lake area and perimeter, land ownership, and housing density across 19 predominantly forested counties in northern Wisconsin, USA. Generalized least squares regression models showed that housing density and soils with excellent suitability for road subgrade were positively related to road density while wetland area was negatively related. These relationships were consistent across models for different road types. Landscape indices showed greater fragmentation by roads in areas with higher housing density, and agriculture, grassland, and coniferous forest area, but less fragmentation with higher deciduous forest, mixed forest, wetland, and lake area. These relationships provide insight into the complex relationships among social, institutional, and environmental factors that influence where roads occur on the landscape. Our results are important for understanding the impacts of roads on ecosystems and planning for their protection in the face of continued development.://000232205600009 ISI Document Delivery No.: 969AK Times Cited: 2 Cited Reference Count: 61 Cited References: *NAT RES CONS SERV, 1991, STAT SOIL GEOGR STAT *US BUR CENS, 1991, CENS POP HOUS 1990 S *US FOR SERV, 2001, CHEQ NIC NAT FOR HOM *US GEOL SURV, 1996, NAT MAPP PROGR TEC 1 *US GEOL SURV, 1998, NAT MAPP PROGR TEC 1 *WI COUNT FOR, 2003, WISC COUNT FOR ACR *WI DEP NAT RES, 1998, WISCL LAND COV *WI DEP NAT RES, 2001, WISC DNR 24K HYDR VE BERNHARDSEN T, 1999, GEOGRAPHIC INFORM SY BETCHEL G, 1989, HIST WISCONSIN HIGHW BOCKSTAEL N, 1995, ECOL ECON, V14, P43 BRABEC E, 2002, LANDSCAPE URBAN PLAN, V58, P255 CADUTO DP, 1999, GEOTECHNICAL ENG CHATTERJEE S, 2000, REGRESSION ANAL EXAM CROW TR, 1999, LANDSCAPE ECOL, V14, P449 CURTIS JT, 1959, VEGETATION WISCONSIN DALE VH, 1993, PHOTOGRAMM ENG REM S, V59, P997 DAVIS G, 1989, HIST WISCONSIN HIGHW DEKONING GHJ, 1998, AGR ECOSYST ENVIRON, V70, P231 EICHENLAUB VL, 1979, WEATHER CLIMATE GREA EWING R, 2001, TRANSPORT RES REC, V1780, P87 FLADER SL, 1983, GREAT LAKES FOREST E FORMAN RTT, 1986, LANDSCAPE ECOLOGY FORMAN RTT, 1998, ANNU REV ECOL SYST, V29, P207 FORMAN RTT, 2000, CONSERV BIOL, V14, P36 FORMAN RTT, 2003, ROAD ECOLOGY GRUBLER A, 1994, CHANGES LAND USE LAN, P287 HAARSMA CF, 2002, LANDSCAPE URBAN PLAN, V48, P125 HAMMER RB, 2004, LANDSCAPE URBAN PLAN, V69, P183 HAWBAKER TJ, 2004, CONSERV BIOL, V18, P1233 HESS PM, 2001, TRANSPORT RES REC, V17, P17 HOLE FD, 1976, GEOLOGICAL NATURAL H, V87 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 KOONTZ TM, 2001, SOC NATUR RESOUR, V14, P51 LAGRO JA, 1996, LANDSCAPE URBAN PLAN, V35, P1 LUGO AE, 2000, FOREST ECOL MANAG, V133, P167 MANTEL N, 1970, TECHNOMETRICS, V12, P621 MARTIN L, 1965, PHYS GEOGRAPHY WISCO MCGARIGAL K, 2001, LANDSCAPE ECOL, V16, P327 MILLER JR, 1996, LANDSCAPE ECOL, V11, P115 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 NOLAND RB, 2001, TRANSPORT RES A-POL, V35, P7 PINHEIRO JC, 2001, MIXED EFFECTS MODELS RADELOFF VC, 1999, CAN J FOREST RES, V29, P1649 RADELOFF VC, 2001, FOREST SCI, V47, P229 RALSTON BA, 1982, ANN ASSOC AM GEOGR, V72, P201 REED RA, 1996, CONSERV BIOL, V10, P1098 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 ROBINSON L, 2005, LANDSCAPE URBAN PLAN, V71, P51 ROSSI RE, 1992, ECOL MONOGR, V62, P277 SAUNDERS SC, 2002, BIOL CONSERV, V103, P209 SCHNAIBERG J, 2002, ENVIRON MANAGE, V3, P24 SPIES TA, 1994, ECOL APPL, V4, P555 THEOBALD DM, 1997, LANDSCAPE URBAN PLAN, V39, P25 THORSON JA, 1997, J HOUS ECON, V6, P81 TINKER DB, 1998, LANDSCAPE ECOL, V13, P149 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1996, ECOL APPL, V6, P1150 WALSH SE, 2003, ENVIRON MANAGE, V31, P198 WEAR DN, 1998, ECOSYSTEMS, V1, P575 WHITE MA, 1994, LANDSCAPE ECOL, V9, P191 0921-2973 Landsc. Ecol.ISI:000232205600009)Univ Wisconsin, Dept Forest Ecol & Management, Madison, WI 53706 USA. Univ Wisconsin, Dept Rural Sociol, Madison, WI 53706 USA. Univ Wisconsin, Dept Stat, Madison, WI 53706 USA. Hawbaker, TJ, Univ Wisconsin, Dept Forest Ecol & Management, 1630 Linden Dr, Madison, WI 53706 USA. tjhawbaker@wisc.eduEnglishb<7/Hay, G. J. Marceau, D. J. Dube, P. Bouchard, A.2001UA multiscale framework for landscape analysis: Object-specific analysis and upscaling471-490Landscape Ecology166domains of scale image-objects landscape thresholds MAUP multiscale object-specific analysis OSA OSU remote sensing scale upscaling REMOTE-SENSING DATA SPATIAL-RESOLUTION FOREST ECOSYSTEM SCALING-UP ECOLOGY PATTERN ENVIRONMENT VEGETATION TOPOGRAPHY MANAGEMENTArticleAug9Landscapes are complex systems that require a multiscale approach to fully understand, manage, and predict their behavior. Remote sensing technologies represent the primary data source for landscape analysis, but suffer from the modifiable areal unit problem (MAUP). To reduce the effects of MAUP when using remote sensing data for multiscale analysis we present a novel analytical and upscaling framework based on the spatial influence of the dominant objects composing a scene. By considering landscapes as hierarchical in nature, we theorize how a multiscale extension of this object-specific framework may assist in automatically defining critical landscape thresholds, domains of scale, ecotone boundaries, and the grain and extent at which scale-dependent ecological models could be developed and applied through scale.://000172548800001 : ISI Document Delivery No.: 499AW Times Cited: 24 Cited Reference Count: 69 Cited References: ALLEN TFH, 1982, HIERARCHY PERSPECTIV ALLEN TFH, 1991, ECOL STUD, V86, P47 AMRHEIN CG, 1996, GEOGRAPHICAL SYSTEMS, V3, P143 BENSON BJ, 1995, LANDSCAPE ECOL, V10, P113 BIAN L, 1993, PROF GEOGR, V45, P1 BOUCHARD A, 1997, LANDSCAPE URBAN PLAN, V37, P99 CALDWELL MM, 1993, SCALING PHYSL PROCES, P223 CHEN JQ, 1999, BIOSCIENCE, V49, P288 COVENEY P, 1991, ARROW TIME CULLINAN VI, 1997, LANDSCAPE ECOL, V12, P273 CURRAN PJ, 1998, PROG PHYS GEOG, V22, P61 DEFRIES RS, 1997, SCALE REMOTE SENSING, P231 DUDLEY G, 1991, OPERATIONAL GEOGRAPH, V9, P28 DUGGIN MJ, 1990, INT J REMOTE SENS, V11, P1669 EHLERINGER JR, 1993, SCALING PHYSL PROCES FOTHERINGHAM AS, 1989, ACCURACY SPATIAL DAT, P221 FOTHERINGHAM AS, 1991, ENVIRON PLANN A, V23, P1025 FREIDL MA, 1997, SCALE REMOTE SENSING, P113 FRIEDL MA, 1995, REMOTE SENS ENVIRON, V54, P233 GARDNER RH, 1982, ECOLOGY, V63, P1771 GARDNER RH, 1998, ECOLOGICAL SCALE THE, P17 HAY GJ, 1996, REMOTE SENS ENVIRON, V55, P108 HAY GJ, 1997, REMOTE SENS ENVIRON, V62, P1 HOLLAND MM, 1988, BIOL INT, V17, P47 HOLLING CS, 1992, ECOL MONOGR, V62, P447 HUNT L, 1996, GEOGRAPHICAL SYSTEMS, V3, P101 JARVIS PG, 1995, PLANT CELL ENVIRON, V18, P1079 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P29 JENSEN JR, 1986, INTRO DIGITAL IMAGE JOHNSTON CA, 1992, LANDSCAPE BOUNDARIES, P107 KAY J, 1995, PERSPECTIVES ECOLOGI, P49 KING AW, 1990, QUANTITATIVE METHODS, P479 KING AW, 1999, ISSUES LANDSCAPE ECO, P6 KIRK O, 1978, CHLOROPHYLLS PLASTIC, P64 LEVIN SA, 1992, ECOLOGY, V73, P1943 MANDELBROT B, 1967, SCIENCE, V156, P636 MARCEAU DJ, 1992, THESIS U WATERLOO MARCEAU DJ, 1994, REMOTE SENS ENVIRON, V49, P93 MARCEAU DJ, 1999, CAN J REMOTE SENS, V25, P342 MARCEAU DJ, 1999, CAN J REMOTE SENS, V25, P357 MARCEAU DJ, 1999, CANADIAN J REMOTE SE, V25, P347 MEENTEMEYER V, 1989, LANDSCAPE ECOLOGY, V3, P163 MOELLERING H, 1972, GEOGR ANAL, V4, P34 MOODY A, 1995, LANDSCAPE ECOL, V10, P363 NICOLIS G, 1989, EXPLORING COMPLEXITY ONEILL RV, 1986, HIERARCHICAL CONCEPT ONEILL RV, 1989, LANDSCAPE ECOL, V3, P193 ONEILL RV, 1996, LANDSCAPE ECOL, V11, P169 ONEILL RV, 1998, ECOLOGICAL SCALE THE, P3 OPENSHAW S, 1979, STAT APPL SPATIAL SC, P127 OPENSHAW S, 1981, QUANTITATIVE GEOGRAP, P60 OPENSHAW S, 1984, CONCEPTS TECHNIQUES, V38 PAN D, 2001, LANDSCAPE ECOL, V16, P99 PAXLENNEY M, 1997, REMOTE SENS ENVIRON, V61, P210 SLATER PN, 1980, REMOTE SENSING OPTIC SOURIAU M, 1994, INT J REMOTE SENS, V15, P2403 STEWART JB, 1998, INT J REMOTE SENS, V19, P181 TOWNSEND PA, 2000, REMOTE SENS ENVIRON, V72, P253 TREITZ P, 2000, REMOTE SENS ENVIRON, V72, P268 TURNER SJ, 1991, QUANTITATIVE METHODS, P19 USTIN SL, 1993, SCALING PHYSL PROCES, P339 WALSH SJ, 1997, SCALE REMOTE SENSING, P27 WESSMAN CA, 1989, INT J REMOTE SENS, V10, P1293 WIENS JA, 1989, FUNCT ECOL, V3, P385 WOODCOCK CE, 1987, REMOTE SENS ENVIRON, V21, P311 WU J, IN PRESS GEOGR INFOR, V6, P1 WU J, IN PRESS GEOGR INFOR, V6, P6 WU J, 1999, CANADIAN J REMOTE SE, V25, P367 WU JG, 1995, Q REV BIOL, V70, P439 0921-2973 Landsc. Ecol.ISI:000172548800001Univ Montreal, Dept Geog, Geocomp Lab, Montreal, PQ H3C 3J7, Canada. Hay, GJ, Univ Montreal, Dept Geog, Geocomp Lab, CP 6128,Succursale Ctr Ville, Montreal, PQ H3C 3J7, Canada.EnglishZ<7(Haydon, D. T. Friar, J. K. Pianka, E. R.2000pFire-driven dynamic mosaics in the Great Victoria Desert, Australia - II. A spatial and temporal landscape model407-423Landscape Ecology155SGreat Victoria Desert habitat mosaics intermediate disturbance landscape processes patch dynamics singular value decomposition spatial correlation succession time series analysis wild fires SINGULAR-VALUE DECOMPOSITION YELLOWSTONE-NATIONAL-PARK EMBEDDING DIMENSION AGE DISTRIBUTION BOREAL FORESTS DISTURBANCE PATTERN SPREAD FUEL SUCCESSIONArticleJulAn explicitly spatial, large scale, high resolution model of fire driven landscape dynamics in the Great Victoria Desert is constructed and parameterized to simulate frequency distributions of fire size and shape obtained from previous analyses of satellite chronosequences. We conclude that probabilities of fire spread cannot be constant over time, and that realistic distributions of fire size and plausible rates of fire spread can be obtained by assuming that fire spread is conditional on observed durations of windy conditions. Landscapes subject to this form of disturbance show large scale correlation structure many times greater than the average dimensions of single fires, and exhibit low frequency quasi-periodic stochastically driven oscillations in proportions of the landscape at different successional states over spatial scales exceeding 100,000 km(2). Average fire return intervals are similar to 30 yrs. Analysis of patch structure suggests that this landscape is composed of few large younger patches, embedded in a mature sea of surrounding habitat. Intermediate and late successional habitat must exist in more abundant patches somewhat smaller than young habitat. Numerous small patches of mature habitat are likely to be scattered throughout this younger habitat. The model predicts that fire size frequency distributions are relatively insensitive to changes of as much as +/- 50% of observed fire ignition frequency.://000088036700002 ISI Document Delivery No.: 331UH Times Cited: 5 Cited Reference Count: 62 Cited References: ABARBANEL HDI, 1993, REV MOD PHYS, V65, P1331 ANTONOVSKI MY, 1992, SYSTEMS ANAL GLOBAL, P373 BAKER WI, 1994, CONSERV BIOL, V8, P763 BAKER WL, 1991, ECOL MODEL, V56, P109 BAKER WL, 1993, OIKOS, V66, P6 BOYCHUK D, 1997, ECOL MODEL, V95, P145 BRADSTOCK RA, 1993, INT J WILDLAND FIRE, V3, P3 BRADSTOCK RA, 1996, CONSERV BIOL, V10, P776 BROOMHEAD DS, 1986, PHYSICA D, V20, P217 BROOMHEAD DS, 1988, PHYS REV A, V37, P5004 BURROWS N, 1991, J ARID ENVIRON, V20, P189 CHATFIELD C, 1996, ANAL TIMES SERIES IN CHENEY NP, 1993, INT J WILDLAND FIRE, V3, P31 CHENEY NP, 1995, INT J WILDLAND FIRE, V5, P237 DAVIS FW, 1993, PATCH DYNAMICS, P16 GARDNER RH, 1996, GLOBAL CHANGE TERRES, P149 GILL AM, 1995, CALMSCIENCE S, V4, P29 GILL AM, 1996, FOREST ECOL MANAG, V85, P261 GREEN DG, 1989, VEGETATIO, V82, P139 GRIFFIN GF, 1983, J ENVIRON MANAGE, V17, P311 GRIFFIN GF, 1984, ANTICIPATING INEVITA, P55 GRIFFIN GF, 1988, P INT GRASSL S HUHH HANSSON L, 1995, MOSAIC LANDSCAPES EC HAYDON DT, 1999, LANDSCAPE ECOL, V14, P373 HUSTON MA, 1996, BIOL DIVERSITY COEXI ISHAM V, 1991, MATH BIOSCI, V107, P209 IWASA Y, 1995, ECOL MODEL, V77, P257 JOHNSON EA, 1979, CAN J BOT, V57, P1374 JOHNSON EA, 1985, CAN J FOREST RES, V15, P214 JOHNSON EA, 1991, CAMBRIDGE STUDIES EC JOHNSON EA, 1994, ADV ECOL RES, V25, P239 KENDALL DG, 1956, 3RD BERK S MATH STAT, V4, P149 KIMBER RG, 1983, ARCHAEOLOGY OCEANIA, V18, P38 LI C, 1996, ECOL MODEL, V87, P143 LI C, 1997, ECOL MODEL, V99, P137 LINDENMAYER DB, 1995, FOREST ECOL MANAG, V74, P197 MCARTHUR AG, 1972, USE TREES SHRUBS DRY MCKENZIE D, 1996, INT J WILDLAND FIRE, V6, P165 MEES AI, 1987, PHYS REV A, V36, P340 MINNICH RA, 1997, INT J WILDLAND FIRE, V7, P221 MOLONEY KA, 1996, ECOLOGY, V77, P375 MORTON SR, 1995, J ENVIRON MANAGE, V43, P195 NASH CH, 1996, CAN J FOREST RES, V26, P1859 ONEILL RV, 1992, LANDSCAPE ECOL, V7, P19 PAINE RT, 1981, ECOL MONOGR, V51, P145 PALUS M, 1992, PHYSICA D, V55, P221 PIANKA ER, 1996, LONG TERM STUDIES VE, P191 PICKETT STA, 1985, ECOLOGY NATURAL DIST RAND DA, 1995, P ROY SOC LOND B BIO, V259, P111 RATZ A, 1995, INT J WILDLAND FIRE, V5, P25 REED WJ, 1998, FOREST SCI, V44, P465 ROMME WH, 1982, ECOL MONOGR, V52, P199 RUSSELLSMITH J, 1997, J APPL ECOL, V34, P748 SCHIMMEL J, 1997, CAN J FOREST RES, V27, P1207 STAUFFER D, 1992, INTRO PERCOLATION TH TAYLOR DL, 1973, ECOLOGY, V54, P1394 TURNER MG, 1994, J VEG SCI, V5, P731 TURNER MG, 1994, NAT AREA J, V14, P3 TURNER MG, 1997, ECOL MONOGR, V67, P411 VANWAGNER CE, 1978, CANADIAN J FOREST RE, V8, P220 WALLIN DO, 1996, FOREST ECOL MANAG, V85, P291 WU YG, 1996, ECOL MODEL, V93, P113 0921-2973 Landsc. Ecol.ISI:000088036700002qUniv Texas, Dept Zool, Austin, TX 78712 USA. Haydon, DT, Ctr Trop Vet Med, Roslin EH25 9RG, Midlothian, Scotland.English <7!(Haydon, D. T. Friar, J. K. Pianka, E. R.2000VFire-driven dynamic mosaics in the Great Victoria Desert, Australia - 1. Fire geometry373-381Landscape Ecology154ifire shape Great Victoria Desert habitat mosaics shape statistics succession wild fires WESTERN-AUSTRALIAArticleMayThe dominant ground cover in the Great Victoria Desert is porcupine grass or spinifex, a fire-prone perennial grass that grows in hummocks or tussocks. Lightning sets hundreds of wildfires annually in inland arid Australia, generating an ever changing spatial-temporal patchwork of habitats that differ in their state of post-fire recovery. The spatial configuration of this patchwork is determined by the size, shape, frequency and inter-spatial relationships of fires, and is likely to play a vital role in the maintenance of the desert biota. Chronosequences of satellite imagery spanning the years 1972-1991 are used to extract and describe the geometry of over 800 fires from fire scars. In the imagery study area, an average of 43 fires occur annually, fire size frequency distributions are roughly log-normal with mild right skew, with average area of 28 km(2), burning between 2 and 5% of the burnable landscape each year. Average fire return interval is estimated to be at least 20 years. These empirical findings are an important prerequisite for developing a more sophisticated understanding of the dynamics of the fire cycle in this ecosystem.://000086006700006 fISI Document Delivery No.: 296DA Times Cited: 8 Cited Reference Count: 28 Cited References: *ERDAS INC, 1995, ERDAS IM VERS 8 2 ALLAN GE, 1986, P 4 AUSTR RANG SOC C, P126 BARRETT EC, 1992, INTRO ENV REMOTE SEN BURBIDGE NT, 1943, J R SOC W AUST, V28, P149 BURROWS N, 1991, J ARID ENVIRON, V20, P189 EBERHART KE, 1987, CAN J FOREST RES, V17, P1207 GILL AM, 1981, FIRE AUSTR BIOTA GILL AM, 1995, CALMSCIENCE S, V4, P29 GREENSLADE P, 1986, NATURE CONSERVATION GRIFFIN GF, 1983, J ENVIRON MANAGE, V17, P311 GRIFFIN GF, 1984, ANTICIPATING INEVITA, P55 GRIFFIN GF, 1988, P INT GRASSL S HUHH HAYDON DT, FIRE DRIVEN DYNAMIC, V2 KIMBER RG, 1983, ARCHAEOLOGY OCEANIA, V18, P38 MASTERS P, 1996, WILDLIFE RES, V23, P39 MCALPINE RS, 1993, CAN J FOREST RES, V23, P1073 PIANKA E, 1992, RES EXPLOR, V8, P352 PIANKA ER, 1969, ECOLOGY, V50, P1012 PIANKA ER, 1986, ECOLOGY NATURAL HIST PIANKA ER, 1989, AM NAT, V134, P344 PIANKA ER, 1994, ACAD SINICA MONOGRAP, V14, P259 PIANKA ER, 1996, LONG TERM STUDIES VE, P191 PYNE SJ, 1991, BURNING BUSH FIRE HI RALPH W, 1984, ECOS CSIRO ENV RS, V40, P3 SHEPHARD M, 1995, GREAT VICTORIA DESER STOYAN D, 1994, FRACTALS RANDOM SHAP, P103 WIENS JA, 1997, METAPOPULATION BIOL, P43 WINKWORTH RE, 1967, AUSTR J BOTANY, V15, P107 0921-2973 Landsc. Ecol.ISI:000086006700006~Univ Texas, Dept Zool, Austin, TX 78712 USA. Haydon, DT, Ctr Trop Vet Med, Easter Bush, Roslin EH25 9RG, Midlothian, Scotland.English<7)Hayes, D. J. Sader, S. A. Schwartz, N. B.2002Analyzing a forest conversion history database to explore the spatial and temporal characteristics of land cover change in Guatemala's Maya Biosphere Reserve299-314Landscape Ecology174forest clearing Maya Biosphere Reserve remote sensing socio-economic and biophysical indicators Swidden agriculture VEGETATION REGROWTH TIME-SERIES DEFORESTATION IMAGERY PATTERNS HABITAT AMAZON RATES AREAArticlemWe analyzed forest clearing and regrowth over a 23-year time period for 21 forest concession and management units within the Maya Biosphere Reserve (MBR), Guatemala. The study area as a whole experienced a clearing rate of 0.16%/year from 1974 through 1997. The overall clearing rate appears rather low when averaged over the entire study area over 23 years because most of the reserve was inaccessible. However, despite the granting of legal protection to the MBR in 1990, clearing rates continued to rise, with the highest rates occurring in the most recent time period in the analysis, 1995 to 1997. Higher rates of clearing relative to regrowth occurred in newly established communities and in the Reserve's buffer zone, where the clearing of high forest was preferred for pasture development. Exploratory models were built and analyzed to examine the effects of various landscape variables on forest clearing. The different units in the analysis showed different relationships of forest clearing with variables such as forest cover type and distance to access (roads and river corridors). Where available, socio-economic household survey data helped to explain patterns and trends observed in the time series Landsat imagery. A strong relationship between forest clearing and distance to access was demonstrated. More clearing occurred further from roads during later time periods as farmers moved deeper into the forest to find land to clear. Communities inside the MBR that were less dependent on farming had forest clearing to regrowth ratios of one: one or less. These communities used fallow fields in greater proportions than communities in the Reserve's buffer zone. General trends in clearing by forest cover type suggest a preference for clearing high forest (bosque alto) types found on the higher elevation, better-drained soils, and fallow fields, and an avoidance of low-lying, seasonally flooded terrain (bajos). Satellite remote sensing observations of forest clearing and regrowth patterns can provide an objective source of information to complement socio-economic studies of the human driving forces in land cover and land use change.://000178391000001 7ISI Document Delivery No.: 600LF Times Cited: 9 Cited Reference Count: 39 Cited References: *ERDAS INC, 1997, ERDAS V 8 3 FIELD GU *ESRI, 1998, ARC VERS 7 2 1 COHEN WB, 1998, PHOTOGRAMM ENG REM S, V64, P293 CONGALTON RG, 1999, ASSESSING ACCURACY R CULBERT TP, 1993, MAYA CIVILIZATION DEPIETRI DE, 1995, J APPL ECOL, V32, P857 ECKHARDT DW, 1990, PHOTOGRAMM ENG REM S, V56, P1515 FEARNSIDE PM, 1986, AMBIO, V15, P74 FOX J, 1995, AMBIO, V24, P328 FROHN RC, 1996, INT J REMOTE SENS, V17, P3233 HALL FG, 1991, REMOTE SENS ENVIRON, V35, P11 HAYES DJ, 2001, PHOTOGRAMM ENG REM S, V67, P1067 JENSEN JR, 1995, PHOTOGRAMM ENG REM S, V61, P199 JENSEN JR, 1996, INTRO DIGITAL IMAGE KIMES DS, 1998, REMOTE SENS ENVIRON, V65, P112 KRISTENSEN PJ, 1997, INT WORKSH BIOD MONT, P129 LAMBIN EF, 1994, 1 EUR COMM LIU DS, 1993, FOREST ECOL MANAG, V57, P1 MEYER WB, 1994, CHANGES LAND USE LAN NATIONS JD, 1998, TIMBER TOURISTS TEMP RICE DS, 1991, NAT HIST, P10 RINDFUSS RR, 1998, PEOPLE PIXELS LINKIN, P1 RUNNING SW, 1986, ECOLOGY, V67, P273 SADER SA, 1988, BIOTROPICA, V20, P11 SADER SA, 1990, PHOTOGRAMM ENG REM S, V56, P1343 SADER SA, 1994, HUM ECOL, V22, P317 SADER SA, 1995, PHOTOGRAMM ENG REM S, V61, P1145 SADER SA, 1997, J FOREST, P27 SADER SA, 2001, INT J REMOTE SENS, V22, P1937 SCHWARTZ NB, 1990, FOREST SOC SCHWARTZ NB, 1998, UNPUB TIME SERIES CH SELLERS PJ, 1985, INT J REMOTE SENS, V6, P1335 SEVER TL, 1998, PEOPLE PIXELS LINKIN SINGH A, 1986, REMOTE SENSING TROPI SKOLE D, 1993, SCIENCE, V260, P1905 TUCKER CJ, 1979, REMOTE SENS ENVIRON, V8, P127 TURNER BL, 1994, AMBIO, V23, P91 TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 TURNER MG, 1991, QUANTITATIVE METHODS 0921-2973 Landsc. Ecol.ISI:000178391000001Univ Maine, Dept Forest Management, Orono, ME 04469 USA. Univ Delaware, Dept Anthropol, Newark, DE USA. Sader, SA, Univ Maine, Dept Forest Management, Orono, ME 04469 USA.English<7 Haynes, K. J. Cronin, J. T.2004MConfounding of patch quality and matrix effects in herbivore movement studies119-124Landscape Ecology192connectivity; dispersal; landscape ecology; matrix; metapopulation; patch quality LANDSCAPE CONNECTIVITY; NEST PREDATION; FOREST EDGES; HABITAT; DISPERSAL; SIZE; DYNAMICS; METAPOPULATION; VEGETATION; BEETLEArticleAlthough the landscape matrix is increasingly incorporated into spatial-ecological population studies, little consideration has been given to the likely possibility that patch quality is confounded with the composition of the matrix surrounding each patch. For example, the nutritional quality of host-plant patches to an herbivore may be highly correlated with matrix composition, consequently obfuscating the importance of the matrix itself to inter-patch dispersal. From a literature survey of the effects of the matrix on herbivore movement among host-plant patches, we found that 55% of the studies (6/11) failed to experimentally or statistically isolate the effects of the matrix from potential patch-quality effects on dispersal. Most studies consisted of mark-recapture experiments in natural landscapes where patch equality was not controlled or manipulated. Of the few studies that evaluated the relationship between matrix composition and patch quality, all of them (3/3) found that these two landscape factors covaried. These data suggest that in most matrix studies, effects of the matrix on dispersal may be wholly, or in part, due to underlying differences in patch quality.://000220452500001 ISI Document Delivery No.: 806SB Times Cited: 8 Cited Reference Count: 44 Cited References: AARS J, 1999, ECOLOGY, V80, P1648 BACH CE, 1984, ECOLOGY, V65, P175 BACH CE, 1988, ECOLOGY, V69, P1103 BEST LB, 2001, J WILDLIFE MANAGE, V65, P442 COCHRANE MA, 2002, J TROP ECOL 3, V18, P311 COOK A, 1994, PLANTHOPPERS THEIR E, P114 CRONIN JT, 2003, ECOLOGY, V84, P1506 FAHRIG L, 1985, ECOLOGY, V66, P1762 FELLER IC, 1995, ECOL MONOGR, V65, P477 GASCON C, 2000, SCIENCE, V288, P1356 GILBERT LE, 1973, AM NAT, V107, P58 GOODWIN BJ, 2002, CAN J ZOOL, V80, P24 GOODWIN BJ, 2002, OIKOS, V99, P552 GRATTON C, 2003, OECOLOGIA, V134, P487 HANSKI I, 1994, J ANIM ECOL, V63, P151 HANSKI I, 1999, METAPOPULATION ECOLO HANSKI I, 2002, OIKOS, V98, P87 HAYNES KJ, 2003, IN PRESS ECOLOGY, V84 HILL JK, 1996, J ANIM ECOL, V65, P725 JONSEN ID, 2001, OECOLOGIA, V127, P287 KAREIVA P, 1985, ECOLOGY, V66, P1809 KINDVALL O, 1999, J ANIM ECOL, V68, P172 KUUSSAARI M, 1996, J ANIM ECOL, V65, P791 LAWLER JJ, 2002, CONDOR, V104, P890 LAWRENCE WS, 1989, ECOLOGY, V70, P1679 MATTER SF, 2002, ECOL ENTOMOL, V27, P308 MOON DC, 2000, ECOL ENTOMOL, V25, P325 PARKER KC, 1991, J BIOGEOGR, V18, P151 PICKETT STA, 1995, SCIENCE, V269, P331 PITHER J, 1998, OIKOS, V83, P166 RAUSHER MD, 1981, ECOLOGY, V62, P1187 RICKETTS TH, 2001, AM NAT, V158, P87 RIES L, 2001, J ANIM ECOL, V70, P840 ROLAND J, 2000, ECOLOGY, V81, P1642 ROOS S, 2002, OECOLOGIA, V133, P608 SULTAN SE, 1998, J ECOL, V86, P363 SWAINE MD, 1996, J ECOL, V84, P419 TAYLOR PD, 1993, OIKOS, V68, P571 THOMAS CD, 1992, J ANIM ECOL, V61, P437 TISCHENDORF L, 2000, OIKOS, V90, P7 WEATHERS KC, 2001, CONSERV BIOL, V15, P1506 WIENS JA, 1985, OIKOS, V45, P421 WIENS JA, 1997, METAPOPULATION BIOL, P43 WILCOVE DS, 1985, ECOLOGY, V66, P1211 0921-2973 Landsc. Ecol.ISI:000220452500001Louisiana State Univ, Dept Biol Sci, Baton Rouge, LA 70803 USA. Haynes, KJ, Louisiana State Univ, Dept Biol Sci, Baton Rouge, LA 70803 USA. khayne4@lsu.eduEnglish<7#He, F. L. LaFrankie, J. V. Song, B.2002SScale dependence of tree abundance and richness in a tropical rain forest, Malaysia559-568Landscape Ecology176diversity mapping grain size Malaysia spatial variation tropical rain forest JANZEN-CONNELL MODEL SPATIAL SCALE PLANT-COMMUNITIES SPECIES RICHNESS DIVERSITY ECOLOGY PATTERNS DENSITY VEGETATION DYNAMICSArticleOctAbundance and richness are the two fundamental components of species diversity. They represent two distinct types of variables of which the former is additive when aggregated across scales while the latter is nonadditive. This study investigated the changes in the spatial patterns of abundance and richness of tree species across multiple scales in a tropical rain forest of Malaysia and their variations in different regions of the study area. The results showed that from fine to coarse scales abundance had a gradual and systematic change in pattern, whereas the change in richness was much less predictable and a 'hotspot' in richness at one scale may become a 'coldspot' at another. The study also demonstrated that different measures of diversity variation (e. g., variance and coefficient of variation) can result in different or even contradictory results which further complicated the interpretation of diversity patterns. Because of scale effect the commonly used measure of species diversity in terms of unit area (e. g., species/ m(2)) is misleading and of little use in comparing species diversity between different ecosystems. Extra care must be taken if management and conservation of species diversity have to be based on information gathered at a single scale.://000179774900006 oISI Document Delivery No.: 624RN Times Cited: 4 Cited Reference Count: 47 Cited References: ANTONOVICS J, 1980, ANNU REV ECOL SYST, V11, P411 ARRHENIUS O, 1921, J ECOL, V9, P95 AUGSPURGER CK, 1983, OIKOS, V40, P189 BARTHA S, 1998, ABSTR BOT, V22, P49 BORMANN FH, 1953, ECOLOGY, V34, P474 BROWN BJ, 1989, OIKOS, V54, P189 BURROUGH PA, 1987, DATA ANAL COMMUNITY, P213 CLARK DA, 1984, AM NAT, V124, P769 CLIFF AD, 1973, SPATIAL AUTOCORRELAT CONDIT R, 1996, J ECOL, V84, P549 CONNELL JH, 1971, DYNAMICS POPULATIONS, P298 CRAWLEY MJ, 2001, SCIENCE, V291, P864 DUNGAN JL, 2002, ECOGRAPHY, V25, P626 FORTIN MJ, 1989, VEGETATIO, V83, P209 FORTIN MJ, 1999, ECOSCIENCE, V6, P204 GASTON KJ, 1994, BIOL CONSERV, V67, P37 GREIGSMITH P, 1952, ANN BOT, V16, P293 GRIME JP, 1973, NATURE, V242, P344 GROSS KL, 2000, OIKOS, V89, P417 HALL P, 1998, MAN BIOSPH, V20, P63 HE F, 1994, ENV ECOLOGICAL STAT, V1, P265 HE FL, 1996, AM NAT, V148, P719 HORNE JK, 1995, OIKOS, V74, P18 JANZEN DH, 1970, AM NAT, V104, P501 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 JUHASZNAGY P, 1983, VEGETATIO, V51, P129 KOCHUMMEN KM, 1990, J TROPICAL FOREST SC, V3, P1 LEGENDRE P, 1989, VEGETATIO, V80, P107 LEGENDRE P, 1998, NUMERICAL ECOLOGY MANOKARAN N, 1999, PASOH 50 HA FOREST D MOELLERING H, 1972, GEOGR ANAL, V4, P34 MOUILLOT D, 1999, RES POPUL ECOL, V41, P203 PALMER MW, 1988, VEGETATIO, V75, P91 PETERSON D, 1998, SCALE ISSUES ECOLOGY PODANI J, 1984, ACTA BOT HUNGARICA, V30, P403 PODANI J, 1993, ABSTR BOT, V17, P37 RAY C, 1996, J ANIM ECOL, V65, P556 SCHUPP EW, 1992, AM NAT, V140, P526 STOHLGREN TJ, 1997, ECOL APPL, V7, P1064 STOMS DM, 1994, PROF GEOGR, V46, P346 TAYLOR PJ, 1977, QUANTITATIVE METHODS TILLYARD RJ, 1914, P LINNEAN SOC NEW S, V39, P21 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 WESTOBY M, 1993, SPECIES DIVERSITY EC, P170 WIENS JA, 1989, FUNCT ECOL, V3, P385 WILSON JB, 1998, J VEG SCI, V9, P213 WILSON JB, 1999, J VEG SCI, V10, P463 0921-2973 Landsc. Ecol.ISI:000179774900006gForestry Canada, Pacific Forestry Ctr, Canadian Forest Serv, Victoria, BC V8Z 1M5, Canada. Natl Inst Educ, Ctr Trop Forest Sci, Singapore 1025, Singapore. Clemson Univ, Belle W Baruch Inst Coastal Ecol & Forest Sci, Georgetown, SC 29442 USA. He, FL, Forestry Canada, Pacific Forestry Ctr, Canadian Forest Serv, 506 W Burnside Rd, Victoria, BC V8Z 1M5, Canada.English v<7)He, H. S. DeZonia, B. E. Mladenoff, D. J.2000DAn aggregation index (AI) to quantify spatial patterns of landscapes591-601Landscape Ecology157adjacency probability aggregation index AI contagion index landscape indices map resolution measurement resolution shape index spatial pattern CONTAGION METRICSArticleOctThere is often need to measure aggregation levels of spatial patterns within a single map class in landscape ecological studies. The contagion index (CI), shape index (SI), and probability of adjacency of the same class (Qi), all have certain limits when measuring aggregation of spatial patterns. We have developed an aggregation index (AI) that is class specific and independent of landscape composition. AI assumes that a class with the highest level of aggregation (AI =1) is comprised of pixels sharing the most possible edges. A class whose pixels share no edges (completely disaggregated) has the lowest level of aggregation (AI =0). AI is similar to SI and Qi, but it calculates aggregation more precisely than the latter two. We have evaluated the performance of AI under varied levels of (1) aggregation, (2) number of patches, (3) spatial resolutions, and (4) real species distribution maps at various spatial scales. AI was able to produce reasonable results under all these circumstances. Since it is class specific, it is more precise than CI, which measures overall landscape aggregation. Thus, AI provides a quantitative basis to correlate the spatial pattern of a class with a specific process. Since AI is a ratio variable, map units do not affect the calculation. It can be compared between classes from the same or different landscapes, or even the same classes from the same landscape under different resolutions.://000089421500001 tISI Document Delivery No.: 356AV Times Cited: 39 Cited Reference Count: 22 Cited References: CLARK MW, 1981, J INT ASS MATH GEOL, V13, P303 CUTIS JT, 1959, VEGETATION WISCONSIN FORMAN RTT, 1986, LANDSCAPE ECOLOGY GARDNER RH, 1991, QUANTITATIVE METHODS GRAHAM RL, 1991, ECOL APPL, V1, P196 GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 HAINESYOUNG R, 1996, PROG PHYS GEOG, V20, P418 LI HB, 1993, LANDSCAPE ECOL, V8, P155 MCGARIGAL K, 1994, SPATIAL PATTERN ANAL MEISEL JE, 1998, LANDSCAPE ECOL, V13, P347 MLADENOFF DJ, 1997, APACK 2 0 USERS GUID ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PATTON DR, 1975, WILDLIFE SOC B, V3, P171 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 RIITTERS KH, 1996, LANDSCAPE ECOL, V11, P197 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1989, ECOL MODEL, V48, P1 TURNER MG, 1990, PHOTOGRAMM ENG REM S, V56, P379 WICKHAM JD, 1995, INT J REMOTE SENS, V16, P3585 WICKHAM JD, 1996, INT J GEOGR INF SYST, V10, P891 WIENS JA, 1989, LANDSCAPE ECOLOGY, V3, P87 0921-2973 Landsc. Ecol.ISI:000089421500001Univ Wisconsin, Dept Forest Ecol & Management, Madison, WI 53706 USA. He, HS, Univ Wisconsin, Dept Forest Ecol & Management, 1630 Linden Dr, Madison, WI 53706 USA.English<7)He, H. S. DeZonia, B. E. Mladenoff, D. J.2001[An aggregation index (AI) to quantify spatial patterns of landscapes (vol 15, pg 591, 2000)87-87Landscape Ecology161 CorrectionJan://000167389900007 ISI Document Delivery No.: 409NN Times Cited: 0 Cited Reference Count: 1 Cited References: HE S, 2000, LANDSCAPE ECOL, V15, P591 0921-2973 Landsc. Ecol.ISI:000167389900007English|?B "He, H. S. White, S. K. Nigh, T. A.2010fValidating landtype associations using forest inventory and analysis data and neutral landscape models761-774Landscape Ecology255One of the principal uses of land type associations (LTAs) is to provide information on ecological patterns and potentials useful for identifying alternatives and setting vegetation management objectives at landscape and watershed scales. Since LTA identification and delineation is an iterative process involving subjective decisions, it is imperative that LTAs accurately capture measurable distinctions in vegetation. In this study, we provided a framework for validating LTAs in Missouri's. We chose a suite of variables from the Forest Inventory and Analysis database of the US Forest Service, an independent source, to capture a wide range of characteristics of the forest ecosystem. These variables included forest type, species composition, species diversity, species richness, site index, density of all trees 1 inch dbh and greater, and density of all trees 5 inch dbh and greater. First, the appropriateness of grouping LTAs into broader LTA types (identifications) was examined, and results suggest that species composition is more similar within LTA Type than among LTA Types. Second, a neutral model approach was used to evaluate the variables used in the study, and it was shown that forest type and the two density measures validated LTA adjacencies no more often than randomly delineated LTAs. Therefore, these three variables were removed from the analysis. Finally, comparisons of adjacent LTAs using statistical analysis of remaining variables resulted in the validation of 480 of the 623 compared adjacencies, showing a significant difference in at least one variable. Results of this study provide a quantitative measure of Missouri LTAs and reveal LTAs that have less distinction and need further refinements.!://WOS:000276609800008Times Cited: 0 0921-2973WOS:00027660980000810.1007/s10980-009-9446-50<7 "He, Z. B. Zhao, W. Z. Chang, X. L.2007The modifiable areal unit problem of spatial heterogeneity of plant community in the transitional zone between oasis and desert using semivariance analysis95-104Landscape Ecology221transitional zone between oasis and desert; spatial heterogeneity; the modifiable areal unit problem; scale effect; zoning effect LANDSCAPE ECOLOGYArticleJanThe modifiable areal unit problem has significant implications for ecological research that involve investigating and analyzing the spatial heterogeneity of plant community. In this paper, semivariance analysis was used to evaluate the spatial characteristics of plant community in the transitional zone between oasis and desert. The spatial structures of the plant community were characterized using exponent model variogram parameters, including nugget (C-0) range (A(0)) and sill (C-0+C). Two methods were employed to determine the scale effect of spatial heterogeneity. (1) A constant grain size (10x10 m(2)) and variational plot areas have been used to analyze spatial heterogeneity of the plant community. (2) The grain size was only changed to analyze spatial heterogeneity. In addition, the plot of 500x500 m(2) was clustered into nested units of different shapes and different directions to analyze zoning effect. Finally, using semivariance analysis, we obtained a suitable plot area and zoning approach to weaken the scale and zoning effects. The results showed that the effects of scale on different variogram parameters had significant difference. For example, C-0 and C-0+C were very sensitive at small scales, A(0) was influenced significantly by plot area at larger scales, and C-0 and A(0) were relatively sensitive to different zoning approaches. In order to get more representative characteristic of spatial heterogeneity of the plant community, the sampling area should be more than 200x200 m(2) for Nitraria sphaerocarpa populations, 100x100 m(2) for Reaumuria soongorica populations, and a grain size from 20x20 m(2) to 30x30 m(2) for both populations.://000243619800009 ISI Document Delivery No.: 127XO Times Cited: 0 Cited Reference Count: 19 Cited References: ARBIA G, 1989, ACCURACY SPATIAL DAT, P249 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FOTHERINGHAM AS, 1991, ENVIRON PLANN A, V23, P1025 GEHLKE CE, 1934, J AM STAT ASSOC, V29, P169 HE ZB, 2004, CHINESE J APPL ECOL, V15, P947 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 KING AW, 1991, LANDSCAPE ECOL, V5, P239 LI YC, 1997, ACTA ECOL SIN, V17, P393 MARCEAU DJ, 1999, CANADIAN J REMOTE SE, V25, P347 MEISEL JE, 1998, LANDSCAPE ECOL, V13, P347 ONEILL RV, 1979, SYSTEMS ANAL ECOSYST, P140 OPENSHAW S, 1977, ENVIRON PLANN A, V9, P169 OPENSHAW S, 1984, CATMOG, V38 ROBINSON WS, 1950, AM SOCIOL REV, V15, P351 URBAN DL, 1987, BIOSCIENCE, V37, P119 WU J, 1995, LECT MODERN ECOLOGY, P1 WU JG, 1994, ECOL MONOGR, V64, P447 WU JG, 1995, Q REV BIOL, V70, P439 YULE GU, 1950, INTRO THEORY STAT 0921-2973 Landsc. Ecol.ISI:000243619800009Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, Linze Inland River Basin Comprehens Res Stn, Chinese Ecosyst Network Res,Lab Basin Hydrol & Ec, Lanzhou 730000, Peoples R China. Yantai Normal Univ, Dept Geog & Tourism, Yantai 264025, Peoples R China. He, ZB, Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, Linze Inland River Basin Comprehens Res Stn, Chinese Ecosyst Network Res,Lab Basin Hydrol & Ec, Lanzhou 730000, Peoples R China. hzbmail@ns.lzb.ac.cnEnglish|?6Hegeman, Ericka E. Dickson, Brett G. Zachmann, Luke J.2014pProbabilistic models of fire occurrence across National Park Service units within the Mojave Desert Network, USA 1587-1600Landscape Ecology299NovThe frequency and size of wildfires within the Mojave Desert are increasing, possibly due to climate and land cover changes and associated increases in non-native invasive plant biomass, as measured by normalized difference vegetation index (NDVI). These patterns are of particular concern to resource managers in regions where native plant communities are not well adapted to fire. We used an information-theoretic and mixed-model approach to quantify the importance of multiple environmental variables in predicting, separately, the probabilities of occurrence of all fires and the occurrence large (>20 ha) fires in five management units administered by the National Park Service in the Mojave Desert Network and based on fire ignition data obtained for the period 1992-2011. Fire occurrence was strongly associated with areas close to roads, high maximum NDVI values in the year preceding ignition, the desert montane ecological zone, and high topographic roughness. Large fire probability was strongly associated with lightning-caused ignition events, high maximum NDVI values in the spring preceding ignition, high topographic roughness, the middle-elevation shrubland ecological zone, and areas further from roads. Our probabilistic models and maps can be used to explore patterns of fire occurrence based upon variability in NDVI values and to assess the vulnerability of Mojave Desert protected areas to undesirable fire events.!://WOS:000343648700010Times Cited: 0 0921-2973WOS:00034364870001010.1007/s10980-014-0078-z <7X %Heinanen, S. Erola, J. von Numers, M.2012High resolution species distribution models of two nesting water bird species: a study of transferability and predictive performance545-555Landscape Ecology274archipelago common eider generality gis herring gull habitat modelling independent data islands maxent regularization geographic distributions habitat models ecology size capercaillie conservation explanation archipelago population regressionAprSpecies distribution modelling is increasingly used in ecological studies and is particularly useful in conservation planning. Models are, however, typically created with a coarse resolution, although conservation planning often requires a high resolution. In this study we created high resolution models and explored central aspects of the modelling procedure; transferability and predictive performance of the models. We created models for two breeding water bird species, common eider Somateria mollissima and herring gull Larus argentatus, based on data from two regions in the Finnish archipelago (234 islands). We used seven variables which we considered as potential predictors of nest site location: distance to forest, distance to rock and distance to low vegetation, exposure, elevation, slope and curvature of the land surface. We tested the predictive ability of the models crosswise between the areas by using area under the receiver operating characteristic curve. The models were transferable between our study areas and the predictive performance varied from fair to excellent. The most important predictors overall were exposure and distance to forest. More general models, with higher regularization values in the Maxent software, had better transferability regarding predictive performance. However, when we fitted a model based on 60% of the data from both regions and evaluated the model on the remaining 40%, the most complex model had the highest accuracy. Extrapolation of SDMs, evaluated on data from the same region, should therefore always be done with caution as the most accurate model might not have the best transferability if it is not general enough.://000302346900006-919RS Times Cited:0 Cited References Count:43 0921-2973Landscape EcolISI:000302346900006Heinanen, S DHI, Agern Alle 5, DK-2970 Horsholm, Denmark DHI, Agern Alle 5, DK-2970 Horsholm, Denmark Abo Akad Univ, FIN-20520 Turku, FinlandDOI 10.1007/s10980-012-9705-8English <7T5Heinl, M. Neuenschwander, A. Sliva, J. Vanderpost, C.2006iInteractions between fire and flooding in a southern African floodplain system (Okavango Delta, Botswana)699-709Landscape Ecology215fire ecology; fire frequency; fire history; flood frequency; landsat; remote sensing; satellite images; savanna; swamp; wetland NATIONAL-PARK; HYDROLOGY; HISTORY; VEGETATIONArticleJulA series of 98 satellite images was analysed to reconstruct the fire and flood history of a floodplain system in southern Africa (Okavango Delta, Botswana). The data was used to investigate interactions between fire and flooding, and to determine the relevance of rainfall and flood-events for fire occurrences on floodplains and on drylands. The aims of the study are (1) to analyse and compare the fire frequency on floodplains and on adjacent drylands, (2) to investigate the influence of rainfall and flooding on the fire occurrence and (3) to determine correlations between fire frequency and flood frequency. The analyses show higher fire frequencies on floodplains than on drylands because of higher biomass production and fuel loads. The fire occurrence on drylands shows a correlation with annual rainfall events, while the fire frequency on floodplains is in principle determined by the flood frequency. Between floodplain types, clear differences in the susceptibility to fire where shown by analysing flood frequency vs. fire frequency. Here, the highest potential to burn was found for floodplains that get flooded about every second year. By calculating mean fire return intervals, the potential to burn could be specified for the different floodplain types.://000240500100006 ISI Document Delivery No.: 083ZE Times Cited: 0 Cited Reference Count: 18 Cited References: BOND WJ, 1996, POPULATION COMMUNITY, V14 BOND WJ, 1997, VEGETATION SO AFRICA, P421 CASSIDY L, 2003, THESIS U FLORIDA GAI DUPLESSIS WP, 1997, KOEDOE, V40, P63 ELLERY WN, 1993, AFR J ECOL, V31, P10 ELLERY WN, 2003, WETLANDS, V23, P357 HEINL M, 2006, IN PRESS J ARID ENV MCCARTHY TS, 1998, S AFR J GEOL, V101, P101 MCCARTHY TS, 2000, S AFR J SCI, V96, P25 NIX HA, 1983, ECOSYSTEMS WORLD, V13, P37 RUSSELLSMITH J, 1997, J APPL ECOL, V34, P748 SCHOLES RJ, 1996, J GEOPHYS RES-ATMOS, V101, P23667 SCHOLES RJ, 1997, VEGETATION SO AFRICA, P258 VANDEVIJVER C, 1999, 27 WAG U VANWILGEN BW, 1997, SO AFRICAN SAVANNAS, P27 VANWILGEN BW, 2000, S AFR J SCI, V96, P167 VANWILGEN BW, 2003, KRUGER EXPERIENCE EC, P149 VANWILGEN BW, 2004, CONSERV BIOL, V18, P1533 0921-2973 Landsc. Ecol.ISI:0002405001000069Tech Univ Munich, Chair Vegetat Ecol, D-85350 Freising Weihenstephan, Germany. Univ Texas, Ctr Space Res, Austin, TX 78759 USA. Univ Botswana, Harry Oppenheimer Okavango Res Ctr, Maun, Botswana. Heinl, M, Tech Univ Munich, Chair Vegetat Ecol, Hochanger 6, D-85350 Freising Weihenstephan, Germany. heinl@wzw.tum.deEnglish1<7jHeino, J. Muotka, T.2006dLandscape position, local environmental factors, and the structure of molluscan assemblages of lakes499-507Landscape Ecology214assemblage structure; dispersal; environmental filters; fingernail clams; snails; species richness FRESHWATER SNAIL POPULATIONS; SPECIES RICHNESS; ISLAND BIOGEOGRAPHY; NORTHERN WISCONSIN; EQUILIBRIUM-THEORY; SPATIAL-PATTERNS; DISPERSAL; DIVERSITY; METACOMMUNITY; GASTROPODSArticleMayBiotic communities are structured by both regional processes (e.g., dispersal) and local environmental conditions (e.g., stress). We examined the relative importance of landscape position (position within the hydrologic flow system and distance from other lakes) and local environmental factors in determining the assemblage structure of lake-dwelling snails and fingernail clams in a boreal landscape. Both landscape position and local environmental factors were highly influential in structuring the molluscan assemblages. In canonical correspondence analysis, 53.6% of snail and 48.2% of fingernail clam assemblage composition were accounted for by both sets of variables. The pure effects of landscape position were higher than those of environmental variables, and a considerable amount of variability was shared by the two sets of variables. In regression analysis, 95.5% of snail and 62.2% of fingernail clam species richness was accounted for by the explanatory variable groups, with most of the variability being related to shared effects, followed by landscape position. The effects of landscape position on species composition suggest that passive dispersal increases the similarity of molluscan assemblages in adjacent lakes. This process does not lead to an overall homogenisation of assemblage composition across the landscape, however, because local conditions set a strong environmental filter, excluding species that arrive at an unsuitable lake. These environmental filters may reflect either extinction probability (area, productivity) or species niche differences (calcium levels, abiotic stress). Landscape position may also be important in maintaining the species richness of lake-dwelling molluscan assemblages. By providing potential colonists, nearby source lakes are likely to be important in countering local extinctions. Our test of the relative importance of landscape position and local drivers of assemblage structure was partly confounded by their co-variation. Nevertheless, studying the relationship between landscape position and local variables is useful because it can tell us about the importance of local and regional processes in shaping lake communities.://000237487700004 <ISI Document Delivery No.: 041WR Times Cited: 0 Cited Reference Count: 34 Cited References: AHO J, 1966, ANN ZOOL FENN, V3, P287 AHO J, 1978, ANN ZOOL FENN, V15, P146 AHO J, 1978, ANN ZOOL FENN, V15, P155 BOAG DA, 1986, CAN J ZOOL, V64, P904 BOHONAK AJ, 2003, ECOL LETT, V6, P783 BOONE RB, 2000, J BIOGEOGR, V27, P457 BORCARD D, 1992, ECOLOGY, V73, P1045 BRIERS RA, 2003, GLOBAL ECOL BIOGEOGR, V12, P47 BRONMARK C, 1985, OECOLOGIA, V67, P127 COTTENIE K, 2003, ECOLOGY, V84, P991 COTTENIE K, 2003, FRESHWATER BIOL, V48, P823 ELMBERG J, 1993, ECOGRAPHY, V16, P251 FIGUEROLA J, 2002, FRESHWATER BIOL, V47, P483 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY HEINO J, 2002, ECOSCIENCE, V12, P141 HOLT RD, 1993, SPECIES DIVERSITY EC, P77 HUBBELL SP, 2001, UNIFIED NEUTRAL THEO HUSTON MA, 1999, OIKOS, V86, P393 KRATZ TK, 1997, FRESHWATER BIOL, V37, P209 LEGENDRE P, 1993, ECOLOGY, V74, P1659 LEGENDRE P, 1998, NUMERICAL ECOLOGY LEWIS DB, 2000, FRESHWATER BIOL, V43, P409 MAGNUSON JJ, 1998, ECOLOGY, V79, P2941 MOUQUET N, 2003, AM NAT, V162, P544 NILSSON SG, 1978, OIKOS, V31, P214 OLDEN JD, 2001, OECOLOGIA, V127, P572 PINELALLOUL B, 1995, ECOSCIENCE, V2, P1 QUINLAN R, 2003, FRESHWATER BIOL, V48, P1676 RIERA JL, 2000, FRESHWATER BIOL, V43, P301 SAVAGE AA, 1987, BIOL CONSERV, V42, P95 SORRANO PA, 1999, ECOSYSTEMS, V2, P395 TERBRAAK CJF, 2002, CANOCO WINDOWS VERSI TONN WM, 1982, ECOLOGY, V63, P1149 VAUGHN CC, 2000, ECOGRAPHY, V23, P11 0921-2973 Landsc. Ecol.ISI:000237487700004!Univ Oulu, Res Dept, Finnish Environm Inst, FIN-90014 Oulu, Finland. Finnish Environm Inst, Res Dept, FIN-00251 Helsinki, Finland. Univ Oulu, Dept Biol, FIN-90014 Oulu, Finland. Heino, J, Univ Oulu, Res Dept, Finnish Environm Inst, POB 413, FIN-90014 Oulu, Finland. jani.heino@ymparisto.fiEnglish {~?Heino, J. Mykra, H. Kotanen, J.2008Weak relationships between landscape characteristics and multiple facets of stream macroinvertebrate biodiversity in a boreal drainage basin417-426Landscape Ecology234Variability in biodiversity is often assessed based on species richness, and this adherence to a single index has been typical in studies of ecology, biogeography, and conservation in the past two decades. More recent studies have suggested that species richness alone is insufficient as a measure of biodiversity, mainly because it is not necessarily correlated with other measures of biodiversity. We examined (1) if nine indices embracing species diversity, functional diversity, and taxonomic distinctness of stream macroinvertebrate assemblages show congruent patterns, and (2) if these indices show similar relationships to landscape characteristics. Not all indices varied similarly and were thus not significantly correlated. There were three principal components that effectively described variation in the correlation structure of the nine indices. These three components were: (1) diversity and evenness indices, (2) two indices of taxonomic distinctness, and (3) species richness and functional richness. Four of the nine biodiversity indices examined showed no significant relationships to landscape-catchment characteristics, and even the significant correlations between the remaining five indices and explanatory variables were rather weak. However, species richness showed a rather strong quadratic relationship to catchment area. Our study provided a number of suggestions for future biodiversity studies at the landscape scale. First, given that different indices describe different components of biodiversity and are not strongly correlated, multiple indices should be considered in any study describing stream biodiversity. Second, despite the study was restricted to near-pristine streams, all indices showed considerable variation. Thus, this natural variability should be accounted for prior to the examination of anthropogenic effects on stream biodiversity. Third, landscape-catchment variables may have only limited value in explaining variability in biodiversity indices, at least in regions with no strong anthropogenic gradients in land-use."://WOS:000254250400005 Times Cited: 0WOS:000254250400005(10.1007/s10980-008-9199-6|ISSN 0921-2973<7-Heinz, S. K. Conradt, L. Wissel, C. Frank, K.2005bDispersal behaviour in fragmented landscapes: Deriving a practical formula for patch accessibility83-99Landscape Ecology201Edispersal function; metapopulation; patchy populations; movement behaviour; stochastic simulation model LEVEL PERCEPTUAL ABILITIES; BUTTERFLY MANIOLA-JURTINA; HETEROGENEOUS LANDSCAPES; METAPOPULATION STRUCTURE; CONNECTIVITY MEASURES; POPULATION-DYNAMICS; SYSTEMATIC SEARCH; ISOLATION METRICS; HABITAT NETWORK; MELITAEA-CINXIAArticleJanDispersal has been shown to be a key determinant of spatially structured populations. One crucial aspect is predicting patch accessibility: the probability r(ij) of a certain patch j being reached by individuals starting at another patch i. Patch accessibility r(ij) depends on both the landscape structure and the individuals' dispersal behaviour. To investigate the effects of these factors on r(ij), we developed a simulation model focusing on animal dispersal. Our model analyses show that there is an important intrinsic effect of the interplay between landscape structure and dispersal behaviour on patch accessibility: the competition between patches for migrants. We derive a formula for patch accessibility. This formula is very simple because it just takes distances into account: not only the distance between start patch and target patch, but also between the start patch and all the other patches in the landscape. Despite its simplicity, the formula is able to cover effects such as the competition for migrants. The formula was found to have high predictive power for a variety of movement behaviours (random walk with various degrees of correlation, Archimedean spirals and loops) in any given landscape. The formula can be interpreted as a generic function for patch accessibility for further population dynamics analyses. It also delivers insights into the consequences of dispersal in fragmented landscapes.://000231223900007 OISI Document Delivery No.: 955KD Times Cited: 6 Cited Reference Count: 80 Cited References: ADLER FR, 1994, THEOR POPUL BIOL, V45, P41 ANDERSON GS, 1997, LANDSCAPE ECOL, V12, P261 ARMSWORTH PR, 2001, AM NAT, V157, P434 BAGUETTE M, 2000, J APPL ECOL, V37, P100 BAVECO J, UNPUB AM NATURALIST BELL WJ, 1985, J INSECT PHYSIOL, V31, P837 BELL WJ, 1991, SEARCHING BEHAV BENDER DJ, 2003, LANDSCAPE ECOL, V18, P17 BRAKEFIELD PM, 1982, J ANIM ECOL, V51, P713 CAIN ML, 1985, ECOLOGY, V66, P876 CONRADT L, 2000, P ROY SOC LOND B BIO, V267, P1505 CONRADT L, 2001, OIKOS, V95, P416 CONRADT L, 2003, AM NAT, V161, P905 CRIST TO, 1992, FUNCT ECOL, V6, P536 DOAK DF, 1992, THEOR POPUL BIOL, V41, P315 DURIER V, 1999, ANIM LEARN BEHAV, V27, P108 DUSENBERY DB, 1992, SENSORY ECOLOGY ORGA ENDLER JA, 1977, GEOGRAPHIC VARIATION ETIENNE AS, 1998, NATURE, V396, P161 FAHRIG L, 1988, APPL MATH COMPUT, V27, P53 FAHRIG L, 1992, THEOR POPUL BIOL, V41, P300 FRANK K, 1998, LANDSCAPE ECOL, V13, P363 FRANK K, 2002, AM NAT, V159, P530 FRANK K, 2004, BIODIVERS CONSERV, V13, P189 FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 GOODWIN BJ, 2002, CAN J ZOOL, V80, P24 GUSTAFSON EJ, 1994, LANDSCAPE URBAN PLAN, V29, P117 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HANSKI I, 1994, BIOL CONSERV, V68, P167 HANSKI I, 1994, ECOLOGY, V75, P747 HANSKI I, 1994, J ANIM ECOL, V63, P151 HANSKI I, 1996, CONSERV BIOL, V10, P578 HANSKI I, 2000, ECOLOGY, V81, P239 HANSKI I, 2002, CONSERV BIOL, V16, P666 HANSKI IA, 1997, METAPOPULATION BIOL HANSSON L, 1998, OIKOS, V81, P55 HEINZ SK, 2004, THESIS PHILIPPS U MA HESS GR, 1996, AM NAT, V148, P226 HILL JK, 1996, J ANIM ECOL, V65, P725 HOFFMANN G, 1983, BEHAV ECOL SOCIOBIOL, V13, P93 HOKIT DG, 1999, ECOL APPL, V9, P124 JOHST K, 2002, OIKOS, V98, P263 KAREIVA PM, 1983, OECOLOGIA, V56, P234 KUUSSAARI M, 1996, J ANIM ECOL, V65, P791 LEVINS R, 1970, SOME MATH PROBLEMS B, P75 MCGARICAL K, 1995, PNWGTR351 USDA FOR S MCINTYRE NE, 1999, LANDSCAPE ECOL, V14, P437 MENZEL R, 1996, J EXP BIOL, V199, P141 MOILANEN A, 2001, OIKOS, V95, P147 MOTULSKY H, 2003, FITTING MODELS BIOL MULLER M, 1994, J COMP PHYSIOL A, V175, P525 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 OPDAM P, 1990, SPECIES DISPERSAL AG, P3 PULLIAM HR, 1992, ECOL APPL, V2, P165 RICKETTS TH, 2001, AM NAT, V158, P87 RIPPLE WJ, 1991, BIOL CONSERV, V57, P73 RUCKELSHAUS M, 1997, CONSERV BIOL, V11, P1298 SAKAMOTO Y, 1986, AKAIKE INFORMATION C SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 THOMAS CD, 2000, P ROY SOC LOND B BIO, V267, P139 TISCHENDORF L, 2000, OIKOS, V90, P7 TISCHENDORF L, 2001, LANDSCAPE ECOL, V16, P235 TISCHENDORF L, 2001, OIKOS, V95, P152 TISCHENDORF L, 2003, LANDSCAPE ECOL, V18, P41 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 VERBOOM J, 1991, OIKOS, V61, P149 VERBOOM J, 1993, LANDSCAPE ECOLOGY ST, P172 VOS CC, 2001, AM NAT, V157, P24 WEHNER R, 1996, J EXP BIOL, V199, P129 WIEGAND T, 1999, AM NAT, V154, P605 WIENS JA, 1993, OIKOS, V66, P369 WIENS JA, 1997, OIKOS, V78, P257 WITH KA, 1997, OIKOS, V78, P151 WITH KA, 1999, LANDSCAPE ECOL, V14, P73 WOLFENBARGER DO, 1949, AM MIDL NAT, V35, P1 YEOMANS SR, 1995, ANIM BEHAV, V49, P977 ZOLLNER PA, 1997, OIKOS, V80, P51 ZOLLNER PA, 1999, ECOLOGY, V80, P1019 ZOLLNER PA, 2000, LANDSCAPE ECOL, V15, P523 0921-2973 Landsc. Ecol.ISI:000231223900007&UFZ Ctr Environm Res Leipzig Halle, Dept Ecol Modelling, D-04301 Leipzig, Germany. Univ Leeds, Sch Biol, Ctr Biodivers & Conservat, Leeds LS2 9JT, W Yorkshire, England. Heinz, SK, UFZ Ctr Environm Res Leipzig Halle, Dept Ecol Modelling, POB 500136, D-04301 Leipzig, Germany. simone.heinz@ufz.deEnglish<7!Heinz, S. K. Wissel, C. Frank, K.2006HThe viability of metapopulations: Individual dispersal behaviour matters77-89Landscape Ecology211landscape assessment; landscape ranking; modelling; movement patterns; patchy populations HETEROGENEOUS LANDSCAPES; FRAGMENTED LANDSCAPES; INTERPATCH MOVEMENTS; SYSTEMATIC SEARCH; PATH-INTEGRATION; MODEL; PERSISTENCE; FORMULA; POPULATIONS; BUTTERFLIESArticleJanoMetapopulation models are frequently used for analysing species-landscape interactions and their effect on structure and dynamic of populations in fragmented landscapes. They especially support a better understanding of the viability of metapopulations. In such models, the processes determining metapopulation viability are often modelled in a simple way. Animals' dispersal between habitat fragments is mostly taken into account by using a simple dispersal function that assumes the underlying process of dispersal to be random movement. Species-specific dispersal behaviour such as a systematic search for habitat patches is likely to influence the viability of a metapopulation. Using a model for metapopulation viability analysis, we investigate whether such specific dispersal behaviour affects the predictions of ranking orders among alternative landscape configurations rated regarding their ability to carry viable metapopulations. To incorporate dispersal behaviour in the model, we use a submodel for the colonisation rates which allows different movement patterns to be considered (uncorrelated random walk, correlated random walk with various degrees of correlation, and loops). For each movement pattern, the landscape order is determined by comparing the resulting mean metapopulation lifetime T-m of different landscape configurations. Results show that landscape orders can change considerably between different movement patterns. We analyse whether and under what circumstances dispersal behaviour influences the ranking orders of landscapes. We find that the 'competition between patches for migrants' - i.e. the fact that dispersers immigrating into one patch are not longer available as colonisers for other patches - is an important factor driving the change in landscape ranks. The implications of our results for metapopulation modelling, planning and conservation are discussed.://000235887300007 ISI Document Delivery No.: 020DD Times Cited: 2 Cited Reference Count: 43 Cited References: ADLER FR, 1994, THEOR POPUL BIOL, V45, P41 BELL WJ, 1985, J INSECT PHYSIOL, V31, P837 CAIN ML, 1985, ECOLOGY, V66, P876 CONRADT L, 2000, P ROY SOC LOND B BIO, V267, P1505 CONRADT L, 2001, OIKOS, V95, P416 CONRADT L, 2003, AM NAT, V161, P905 DARROCH JN, 1965, J APPL PROBAB, V2, P88 DRECHSLER M, 2000, BIOL CONSERV, V94, P23 DURIER V, 1999, ANIM LEARN BEHAV, V27, P108 ETIENNE RS, 2000, J THEOR BIOL, V203, P33 FAHRIG L, 1992, THEOR POPUL BIOL, V41, P300 FRANK K, 1998, LANDSCAPE ECOL, V13, P363 FRANK K, 2002, AM NAT, V159, P530 FRANK K, 2002, META X SOFTWARE META FRANK K, 2004, BIODIVERS CONSERV, V13, P189 GILLIS S, 2004, WOMEN HIST REV, V13, P165 GRIMM V, 2004, BIODIVERS CONSERV, V13, P165 GRIMM V, 2004, OIKOS, V105, P501 HADDAD NM, 1999, ECOL APPL, V9, P612 HANSKI I, 1994, J ANIM ECOL, V63, P151 HANSKI I, 1999, METAPOPULATION ECOLO HANSKI I, 2000, NATURE, V404, P755 HEIN S, 2004, ECOL MODEL, V174, P411 HEINZ SK, 2004, THESIS PHILIPPS U MA HEINZ SK, 2005, LANDSCAPE ECOL, V20, P83 HOFFMANN G, 1983, BEHAV ECOL SOCIOBIOL, V13, P93 KEILSON J, 1979, APPL MATH SCI, V28 KING AW, 2002, ECOL MODEL, V147, P23 LIMA SL, 1996, TRENDS ECOL EVOL, V11, P131 LINDENMAYER DW, 1996, CONSERV BIOL, V10, P1 MERRIAM G, 1991, NATURE CONSERVATION, V2, P133 MORALES JM, 2002, ECOLOGY, V83, P2240 MULLER M, 1994, J COMP PHYSIOL A, V175, P525 OVASKAINEN O, 2002, AM NAT, V160, P612 POLLETT PK, 1997, P INT C MOD SIM, V2, P807 POSSINGHAM H, 2000, QUANTITATIVE METHODS, P291 ROITBERG BD, 1997, OIKOS, V80, P234 VERBOOM J, 1993, LANDSCAPE ECOLOGY ST, P172 VOS CC, 2001, AM NAT, V157, P24 WEAVER JL, 1996, CONSERV BIOL, V10, P964 WISSEL C, 1991, THEOR POPUL BIOL, V39, P315 ZOLLNER PA, 1997, OIKOS, V80, P51 ZOLLNER PA, 1999, ECOLOGY, V80, P1019 0921-2973 Landsc. Ecol.ISI:000235887300007UFZ Ctr Environm Res Leipzig Halle, Dept Ecol Modelling, D-04301 Leipzig, Germany. Univ Bergen, Dept Biol, N-5200 Bergen, Norway. Heinz, SK, UFZ Ctr Environm Res Leipzig Halle, Dept Ecol Modelling, POB 500136, D-04301 Leipzig, Germany. simone.heinz@bio.uib.noEnglish|?NHelfenstein, Julian Bauer, Lea Claluena, Aline Bolliger, Janine Kienast, Felix2014)Landscape ecology meets landscape science 1109-1113Landscape Ecology297AugLandscape ecology is a broad field in a patchwork of related disciplines. Giving landscape ecology a definition and delimiting it from related research areas is both a challenge and a necessity. Past endeavors have focused on expert opinions, analyses of published papers, and conference proceedings. We used a mix of all three, including a unique keyword analysis in two leading landscape-related journals, to highlight latest developments in landscape ecology between 2010 and 2013. Our analysis confirms the key topics of Wu (Landscape Ecol 28(1):1-11, 2013), and suggests that of those connectivity is dominating in terms of research output. However, we also found evidence that the borders of the journal Landscape Ecology are fuzzier than sketched in recent publications. There is a large overlap with the journal Landscape and Urban Planning, and in general a growing weight of conservation, landscape management, and planning related issues in the landscape ecology community. We conclude by encouraging the continued inclusion and strengthening of socio-ecological hot topics such as urban studies and landscape-human interactions in landscape ecological studies and subsequently in the journal landscape ecology.!://WOS:000339831300001Times Cited: 0 0921-2973WOS:00033983130000110.1007/s10980-014-0055-6<7 Helmer, E. H.20047Forest conservation and land development in Puerto Rico29-40Landscape Ecology191Caribbean; land-cover change; land-use change; urban growth; spatial modeling; tropical forest conservation FARMLAND CONVERSION; ECOLOGICAL-SOCIETY; COSTA-RICA; FRAGMENTATION; GROWTH; MASSACHUSETTS; DEFORESTATION; MANAGEMENT; LUQUILLO; RECOVERYArticleIn the Caribbean island of Puerto Rico, rapid land-use changes over the past century have included recent landcover conversion to urban/built-up lands. Observations of this land development adjacent to reserves or replacing dense forest call into question how the changes relate to forests or reserved lands. Using existing maps, this study first summarizes island-wide land-cover change between 1977-78 and 1991-92. Then, using binomial logit modeling, it seeks evidence that simple forest cover attributes, reserve locations, or existing land cover influence land development locations. Finally, this study quantifies land development, reserve protection and forest cover by ecological zone. Results indicate that 1) pasture is more likely to undergo land development than shrubland plus forest with low canopy density, 2) forest condition and conservation status appear unimportant in that development locations neither distinguish between classes of forest canopy development nor relate to forest patch size or reserve proximity, and 3) most land development occurs in the least-protected ecological zones. Outside the boundaries of strictly protected forest and other reserves, accessibility, proximity to existing urban areas, and perhaps desirable natural settings, serve to increase land development. Over the coming century, opportunities to address ecological zone gaps in the island's forest reserve system could be lost more rapidly in lowland ecological zones, which are relatively unprotected.://000189394100003 ISI Document Delivery No.: 780RA Times Cited: 1 Cited Reference Count: 52 Cited References: *ERDAS INC, 1999, ERDAS FIELD GUID AIDE TM, 1996, BIOTROPICA A, V28, P537 BARLOW SA, 1998, J FOREST, V96, P10 BEIER P, 1993, CONSERV BIOL, V7, P94 BIRDSEY RA, 1987, SO331 USDA FOR SERV, P5 BOCKSTAEL NE, 1996, AM J AGR ECON, V78, P1168 BRADSHAW TK, 1998, RURAL SOCIOL, V63, P1 BROWN S, 1990, J TROP ECOL, V6, P1 CHINEA D, 2003, FOREST ECOL MANAG, V180, P227 CHINEA JD, 2002, FOREST ECOL MANAG, V167, P165 CHRISTENSEN NL, 1996, ECOL APPL, V6, P665 COVICH AP, 1996, FOOD WEB TROPICAL RA, P434 COX GW, 1977, OIKOS, V28, P113 DRAGONI A, 2002, DIGITAL MAP PROTECTE EWEL JJ, 1973, ITF18 USDA FOR SERV FIGUEROACOLON J, 1996, HOLDRIDGE ECOLOGICAL FOSTER DR, 1998, ECOSYSTEMS, V1, P96 FRANCO PA, 1997, RES B USDA GASCON C, 1998, ZOOL-ANAL COMPLEX SY, V101, P273 GERSH J, 1995, URBAN LAND, V54, P32 GONZALEZ OMR, 2001, CARIBB J SCI, V37, P95 HELMER EH, 2000, ECOSYSTEMS, V3, P98 HELMER EH, 2002, CARIBB J SCI, V38, P165 HOLDRIDGE LR, 1967, LIFE ZONE ECOLOGY IRWIN EG, 2001, AGR ECOSYST ENVIRON, V85, P7 KARR JR, 1992, ECOSYSTEM HLTH NEW G, P223 KLINE JD, 2001, ECOSYSTEMS, V4, P3 KRUSHENSKY RD, 1995, GEN GEOLOGY MAP PUER LEVIA DF, 1998, LAND DEGRAD DEV, V9, P123 LOPEZ E, 2001, LANDSCAPE URBAN PLAN, V55, P271 LOPEZ TD, 2001, AMBIO, V30, P49 LUBCHENCO J, 1991, ECOLOGY, V72, P371 LUGO AE, 2004, IN PRESS FOREST ECOL POWELL GVN, 1995, CONSERV BIOL, V9, P354 RAMOS O, 1994, ACTA CIENTIFICA, V8, P63 RIVERA LW, 1998, FOREST ECOL MANAG, V108, P63 ROBINSON SK, 1995, SCIENCE, V267, P1987 RUDEL TK, 1993, TROPICAL DEFORESTATI RUDEL TK, 2000, PROF GEOGR, V52, P386 SADER SA, 1988, BIOTROPICA, V20, P11 SCATENA FN, 2001, IITFGTR11 USDA FOR S SCHNEIDER LC, 2001, AGR ECOSYST ENVIRON, V85, P83 SKOLE D, 1993, SCIENCE, V260, P1905 THEOBALD DM, 1998, GEOGRAPHICAL ENV MOD, V2, P65 THOMLINSON JR, 2000, LANDSCAPE URBAN PLAN, V49, P15 TOBLER WR, 1969, AREA, V1, P31 WADSWORTH FH, 1950, CARIBB FOR, V11, P38 WEAR DN, 1998, ECOSYSTEMS, V1, P575 WHITE MA, 1994, LANDSCAPE ECOL, V9, P191 WUNDERLE J, 2002, ASS TROP BIOL ANN M YEH AGO, 1999, HABITAT INT, V23, P373 ZIMMERMAN JK, 1995, FOREST ECOL MANAG, V77, P65 0921-2973 Landsc. Ecol.ISI:000189394100003Forest Serv, Int Inst Trop Forestry, USDA, Rio Piedras, PR 00926 USA. Helmer, EH, Forest Serv, Int Inst Trop Forestry, USDA, Jardin Bot Sur,1201 Calle Ceiba, Rio Piedras, PR 00926 USA. ehelmer@fs.fed.usEnglishi?SHendler, S. A.1988A comment on landscape values125-127Landscape Ecology13<? Henebry, Geoffrey2011ZBeyond words: effective graphics and metadata are keys to concise scientific communication 1355-1358Landscape Ecology2610Springer NetherlandsEarth and Environmental Science+http://dx.doi.org/10.1007/s10980-011-9672-5 0921-297310.1007/s10980-011-9672-5 +?OHenein, K. G. Merriam1990?The Elements of Connectivity where Corridor Quality Is Variable157-170Landscape Ecology42/3(Connectivity, Corridor, Landscape, Model]Small mammals in heterogeneous environments have been found to disperse along corridors connecting habitat patches. Corridors may have different survivability values depending on their size and the degree of cover they provide. This deterministic model tests the effects of varying corridor quality on the demographics of a metapopulation of Peromyscus leucopus. Two types of corridors are defined based on the probability of survival during a dispersal event. Results indicate that mortality during movement through corridors influences metapopulation demographics. We found that: 1. Any connection between two isolated patches is better than no connection at all in terms of persistence and population size at equilibrium. 2. Metapopulations with exclusively high quality corridors between patches have a larger population size at equilibrium than do those with one or more low quality corridors. 3. Increasing the number of high quality corridors between patches has a positive effect on the size of the metapopulation while increasing the number of low quality corridors has a negative effect. 4. The addition to a metapopulation of a patch connected by low quality corridors has a negative effect on the metapopulation size. This suggest the need for caution in planning corridors in a managed landscape. 5. There is no relationship between the number of corridors and the metapopulation size at equilibrium - when the number of connected patches is held constant. 6. Geometrically isolated patches connected by low quality corridors are most vulnerable to local extinctions. We conclude that corridor quality is an important element of connectivity. It contributes substantially to the effects of fragmentation and should be carefully considered by landscape planners.?Z)Zalmen Henkin Liat Hadar Imanuel Noy-Meir2007]Human-scale structural heterogeneity induced by grazing in a Mediterranean woodland landscape577-587Landscape Ecology224nAmenity value - Landscape visual qualities - Plant shapes - Structural profile - Vegetation gaps - Visibility A set of structural criteria to differentiate among types of a heterogeneous woodland landscape that are shaped by goat and cattle grazing was studied in northern Israel. The landscape was described with relation to the “human scale” of the observer, by mapping the dimensions, basic shapes, and distribution of gaps between individual plants on sites with various grazing management systems. The shapes of the trees and the bushes were drawn in situ and the ratio between plant height and the width of the adjacent open space was measured in order to define the various structural profiles of the vegetation. All the structural criteria clearly and significantly differentiated among grazing systems that created closed (no grazing), half-open (cattle and modern goat grazing) and open (traditional goat grazing) landscapes. The diversity of plant shapes was highest under the cattle and modern goat grazing management systems. In the ungrazed treatment, more than 60% of the gaps were defined as ‘inaccessible’ compared with only 10–15% under cattle grazing and modern goat grazing. The diversity of gap proportions was high, but their absolute number was low. Under traditional heavy goat grazing, there were only wide and open gaps. Under cattle grazing and modern goat-grazing management systems, a relatively large number of wide and open gaps were found, with small numbers of narrow and closed gaps. Overall, the various grazing systems were differentiated most clearly according to their transparency, accessibility, height of Quercus calliprinos, and gap distribution. We conclude that structural criteria provide an efficient and objective methodology for evaluating the effects of grazing on different components of Mediterranean woodland mosaic landscapes. Gڽ7 nHenne, PaulD Elkin, Ché Colombaroli, Daniele Samartin, Stéphanie Bugmann, Harald Heiri, Oliver Tinner, Willy2013Impacts of changing climate and land use on vegetation dynamics in a Mediterranean ecosystem: insights from paleoecology and dynamic modeling819-833Landscape Ecology285Springer NetherlandsuAbies alba Chironomids Fire ecology Holocene Italy Landscape model Mediterranean forest Neolithic Pollen Quercus ilex 2013/05/01+http://dx.doi.org/10.1007/s10980-012-9782-8 0921-2973Landscape Ecol10.1007/s10980-012-9782-8EnglishA|?-Hepinstall, J. A. Alberti, M. Marzluff, J. M.2008]Predicting land cover change and avian community responses in rapidly urbanizing environments 1257-1276Landscape Ecology2310We used an integrated modeling approach to simulate future land cover and predict the effects of future urban development and land cover on avian diversity in the Central Puget Sound region of Washington State, USA. We parameterized and applied a land cover change model (LCCM) that used output from a microsimulation model of urban development, UrbanSim, and biophysical site and landscape characteristics to simulate land cover 28 years into the future. We used 1991, 1995, and 1999 Landsat TM-derived land cover data and three different spatial partitions of our study area to develop six different estimations of the LCCM. We validated model simulations with 2002 land cover. We combined UrbanSim land use outputs and LCCM simulations to predict changes in avian species richness. Results indicate that landscape composition and configuration were important in explaining land cover change as well as avian species response to landscape change. Over the next 28 years, urban land cover was predicted to increase at the expense of agriculture and deciduous and mixed lowland forests. Land cover changes were predicted to reduce the total number of avian species, with losses primarily in native forest specialists and gains in common synanthropic species such as the American Crow (Corvus brachyrhynchos). The integrated modeling framework we present has potential applications in urban and natural resource planning and management and in assessing of the effects of policies on land development, land cover, and avian biodiversity.!://WOS:000261790600010Times Cited: 0 0921-2973WOS:00026179060001010.1007/s10980-008-9296-6? qHerfindal, Ivar Drever, Mark Høgda, Kjell-Arild Podruzny, Kevin Nudds, Thomas Grøtan, Vidar Sæther, Bernt-Erik2012VLandscape heterogeneity and the effect of environmental conditions on prairie wetlands 1435-1450Landscape Ecology2710Springer NetherlandsBiomedical and Life Sciences*Populations can vary considerably in their response to environmental fluctuations, and understanding the mechanisms behind this variation is vital for predicting effects of environmental variation and change on population dynamics. Such variation can be caused by spatial differences in how environmental conditions influence key parameters for the species, such as availability of food or breeding grounds. Knowing how these differences are distributed in the landscape allows us to identify areas that we can expect the highest impact of environmental change, and where predictions on population dynamical effects will be most precise. We evaluated how wetland dynamics in the North-American prairies (pond counts; a key parameter for several waterfowl populations) were related to spatial and temporal variation in the environment, as measured by weather variables, primary productivity and phenology derived from annual normalized difference vegetation index (NDVI) curves, and agricultural composition of the landscape. Spatial and temporal variation in pond counts were closely related to these environmental variables. However, correlation strength and predictive ability of these environmental variables on wetland dynamics varied considerably across the study area. This variation was related to landscape characteristics and to the spatial scaling of the wetland dynamics, such that areas with late onset of spring, low spring temperature, high primary productivity, and high proportion of cropland had more predictable and spatially-homogenous dynamics. The success of predicting environmental influences on wetlands from NDVI measures derived from satellite images indicates they will be useful tools for assessing effects of changing landscape and climatic conditions on wetland ecosystems and their wildlife populations.+http://dx.doi.org/10.1007/s10980-012-9798-0 0921-297310.1007/s10980-012-9798-0<7'Herlin, I. L. S. Fry, G. L. A.2000Dispersal of woody plants in forest edges and hedgerows in a Southern Swedish agricultural area: the role of site and landscape structure229-242Landscape Ecology153animal dispersal connectedness connectivity edges hedgerows landscape ecology landscape planning wind dispersal woody species OLD FIELD VEGETATION SEED DISPERSAL FRUIT CHARACTERISTICS FRUGIVOROUS BIRDS PATTERNS CONNECTIVITY PREDATION RAIN GERMINATION VERTEBRATESArticleAprThe distribution of woody vegetation was studied in forest edges and hedgerows in a 28 km(2) southern Swedish agricultural area, characterised by species-rich edge zones. The occurrence of 21 selected woody species (taxa) was related to differences in both edge structure and landscape structure. All the species studied were represented in both edge types, but a higher frequency of animal-dispersed species was found in hedgerows. Animal dispersed species were more affected by edge width and density than wind dispersed species. A higher number of wind-dispersed species were more frequent in forest edges, in hedgerows near to forest, or with a high proportion of forest within 500 m. A clear relationship was found between the number of physically connected elements in hedgerow networks and increasing frequency of occurrence for Corylus avellana, Crataegus spp., Euonymus europaeus, and Quercus robur; which indicate the ecological significance of connectedness for certain animal dispersed species. The study supports the general principle that woody species distribution and landscape structure are linked in a positive feedback loop. The results match findings from studies in other countries and are interpreted in the context of landscape processes and the ecological characteristics of woody plant species. We emphasise the importance of understanding dispersal mechanisms of woody species for the design and improvement of edge habitats in agricultural landscapes.://000085293300005  ISI Document Delivery No.: 283UB Times Cited: 6 Cited Reference Count: 75 Cited References: 1996, PC ARF INFO VERSION 1997, ARC VIEW VERSION 3 0 AHRLAND A, 1994, THESIS U YORK BARNEA A, 1992, ACTA OECOL, V13, P209 BAUDRY J, 1985, THESIS U RENNES 1 BAUDRY J, 1988, CONNECTIVITY LANDSCA, P23 BERG A, 1994, ECOGRAPHY, V17, P147 BERG A, 1996, BIODIVERS CONSERV, V5, P101 BUREL F, 1990, LANDSCAPE ECOL, V4, P197 BUREL F, 1990, SPECIES DISPERSAL AG, P238 BUREL F, 1995, LANDSCAPE URBAN PLAN, V33, P327 CAMERON RAD, 1980, FIELD STUDIES, V5, P177 CLERGEAU P, 1997, LANDSCAPE URBAN PLAN, V38, P37 CREMER K, 1995, AUSTR J SOIL WATER C, V8, P18 DEBUSSCHE M, 1994, OIKOS, V69, P414 DEMERS MN, 1995, CONSERV BIOL, V9, P1159 DOWDESWELL WH, 1987, HEDGEROWS VERGES EHRLEN J, 1993, OIKOS, V66, P107 ELLENBERG H, 1991, ZEIGERWERTE PFLANZEN ERIKSSON O, 1991, OECOLOGIA, V86, P463 FIRBANKS LG, 1997, FARM LANDSCAPES BIOD FISCHER KE, 1993, OIKOS, V66, P472 FORMAN RTT, 1984, ENVIRON MANAGE, V8, P495 FORMAN RTT, 1984, METHODOLOGY LANDSCAP, V5, P4 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FORMAN RTT, 1992, LANDSCAPE BOUNDARIES, P236 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FRITZ R, 1994, ECOSCIENCE, V1, P160 FRY G, 1991, SCI MANAGEMENT TEMPE, V31, P415 FRY G, 1997, LANDSCAPE URBAN PLAN, V37, P45 FUENTES M, 1995, OIKOS, V74, P324 GORCHOV DL, 1990, OIKOS, V58, P169 GOSZ JR, 1993, ECOL APPL, V3, P369 GRASHOFBOKDAM C, 1997, J VEG SCI, V8, P21 GRASHOFBOKDAM C, 1997, THESIS DLO I FORESTR GRIME JP, 1988, COMP PLANT ECOLOGY F HALLIDAY G, 1983, FLORA EUROPEA HARPER JL, 1995, BIODIVERSITY MEASURE, P5 HARVEY DR, 1990, SPECIES DISPERSAL AG, P256 HERRERA CM, 1984, OIKOS, V42, P166 HERRERA CM, 1985, OIKOS, V44, P132 HERRERA CM, 1989, OIKOS, V55, P250 HODGSON JG, 1990, SPECIES DISPERSAL AG, P65 HULTEN E, 1958, SVENSKA FLORA FARG IZHAKI I, 1989, OIKOS, V54, P23 JORDANO P, 1995, OIKOS, V71, P479 KOLLMAN J, 1995, ECOSCIENCE, V1, P213 KOLLMANN J, 1995, ACTA OECOL, V16, P313 KOLLMANN J, 1996, VEGETATIO, V125, P193 LACK PC, 1988, BIRD STUDY, V35, P133 LONARD RI, 1993, TEX J SCI, V45, P133 MACDONALD DW, 1990, SPECIES DISPERSAL AG, P18 MALANSON GP, 1997, LANDSCAPE ECOL, V12, P27 MANZUR MI, 1984, OIKOS, V43, P265 MARSHALL EJP, 1990, SPECIES DISPERSAL AG, P98 MCDONNELL MJ, 1983, OECOLOGIA, V56, P109 MCDONNELL MJ, 1986, B TORREY BOT CLUB, V113, P6 MERRIAM G, 1984, METHODOLOGY LANDSCAP, V1, P5 MYSTER RW, 1993, OIKOS, V66, P381 NILSSON SG, 1985, OIKOS, V44, P157 NOSS RF, 1991, LANDSCAPE LINKAGES B, P27 OPDAM P, 1992, SPECIES DISPERSAL AG, P4 PAHLSSON L, 1994, VEGETATIONSTYPER NOR, P665 PIPER JK, 1986, OIKOS, V46, P303 POLLARD E, 1974, HEDGES RIGONI P, 1988, MONTIE BOSCHI, V3, P15 ROMELL LG, 1938, VAXTERNAS LIV, V4, P278 SOUTHWOOD TRE, 1985, OIKOS, V44, P5 TAYLOR PD, 1993, OIKOS, V68, P571 TISCHENDORF L, 1997, OIKOS, V79, P603 TOYE EA, 1972, OHIO J SCI, V72, P211 VANDERPIJL L, 1972, PRINCIPLES DISPERSAL WIENS JA, 1987, OIKOS, V48, P132 WILLSON MF, 1983, OIKOS, V41, P27 WITH KA, 1997, OIKOS, V78, P151 0921-2973 Landsc. Ecol.ISI:000085293300005Dept Landscape Planning, S-23053 Alnarp, Sweden. Norwegian Inst Nat Res, Dept Landscape Ecol, N-0105 Oslo, Norway. Herlin, ILS, Dept Landscape Planning, POB 58, S-23053 Alnarp, Sweden.English <7 @Hernandez-Stefanoni, J. L. Dupuy, J. M. Tun-Dzul, F. May-Pat, F.2011|Influence of landscape structure and stand age on species density and biomass of a tropical dry forest across spatial scales355-370Landscape Ecology2634alpha diversity landscape patterns pcnm analysis spatial scales tropical dry forest succession variation partitioning vegetation structure neighbor matrices pcnm secondary forests shifting cultivation successional stages yucatan peninsula deciduous forest multiple scales ecological data rain-forest land-useMarThree central related issues in ecology are to identify spatial variation of ecological processes, to understand the relative influence of environmental and spatial variables, and to investigate the response of environmental variables at different spatial scales. These issues are particularly important for tropical dry forests, which have been comparatively less studied and are more threatened than other terrestrial ecosystems. This study aims to characterize relationships between community structure and landscape configuration and habitat type (stand age) considering different spatial scales for a tropical dry forest in Yucatan. Species density and above ground biomass were calculated from 276 sampling sites, while land cover classes were obtained from multi-spectral classification of a Spot 5 satellite imagery. Species density and biomass were related to stand age, landscape metrics of patch types (area, edge, shape, similarity and contrast) and principal coordinate of neighbor matrices (PCNM) variables using regression analysis. PCNM analysis was performed to interpret results in terms of spatial scales as well as to decompose variation into spatial, stand age and landscape structure components. Stand age was the most important variable for biomass, whereas landscape structure and spatial dependence had a comparable or even stronger influence on species density than stand age. At the very broad scale (8,000-10,500 m), stand age contributed most to biomass and landscape structure to species density. At the broad scale (2,000-8,000 m), stand age was the most important variable predicting both species density and biomass. Our results shed light on which landscape configurations could enhance plant diversity and above ground biomass.://000288808100005-740PY Times Cited:1 Cited References Count:64 0921-2973Landscape EcolISI:000288808100005=Ctr Invest Cient Yucatan AC, Unidad Recursos Nat, Calle 43,130 Colonia Chuburna Hidalgo, Merida 97200, Yucatan, Mexico Ctr Invest Cient Yucatan AC, Unidad Recursos Nat, Calle 43,130 Colonia Chuburna Hidalgo, Merida 97200, Yucatan, Mexico Ctr Invest Cient Yucatan AC, Unidad Recursos Nat, Merida 97200, Yucatan, MexicoDOI 10.1007/s10980-010-9561-3English|?\ 0Herrera, Jose M. Garcia, Daniel Morales, Juan M.2011UMatrix effects on plant-frugivore and plant-predator interactions in forest fragments125-135Landscape Ecology261JanxStructural features of both habitat remnants and surrounding matrix can be important for explaining plant population dynamics and ecosystem functions in human-impacted landscapes. However, little is known about how the structural features of the adjacent matrix affect biotic interactions and whether such context effects are subject to temporal variations. Using the hawthorn Crataegus monogyna in northern Spain, we studied matrix effects on two sequential plant-animal interactions, frugivory by birds and postdispersal seed predation by rodents. Using Hierarchical Linear Models, we compared the magnitude of both interactions on trees located in two patch types that strongly differed in structural features of the adjacent matrix habitat: patches totally surrounded by a degraded, structurally contrasted pastures (unconnected patches), and trees growing in patches adjacent to a lowly degraded, structurally similar mature forests (connected patches). We compared outcomes for 2005 and 2006, which were years with strong differences in community-wide fruit and seed abundance. Frugivory rate did not differ between patch types in either year, likely related to high mobility of birds. Seed predation rates were higher in unconnected patches than in connected ones, but only in 2005. We conclude that strong interannual fluctuations in resource availability are not rare in temperate systems and that recruitment rates could be frequently reduced within unconnected patches, thus collapsing plant regeneration processes of hawthorn populations. Overall, our results suggest that generalizations about potential effects of the matrix on plant-animal interactions within remnant patches must consider: (1) species-specific habitat responses of the organisms, (2) suitability of neighbouring habitats in terms of food supply, and (3) temporal variations in plant-resource availability for interacting animals.!://WOS:000286004400011Times Cited: 0 0921-2973WOS:00028600440001110.1007/s10980-010-9541-7|? XHerrmann, John D. Bailey, Debra Hofer, Gabriela Herzog, Felix Schmidt-Entling, Martin H.2010mSpiders associated with the meadow and tree canopies of orchards respond differently to habitat fragmentation 1375-1384Landscape Ecology259NovvThe response of animal communities to habitat quality and fragmentation may vary depending on microhabitat associations of species. For example, sensitivity of species to woody habitat fragmentation should increase with their degree of association with woody plants. We investigated effects of local and landscape factors on spider communities in different microhabitats within Swiss apple orchards. We expected a stronger negative effect of woody habitat fragmentation on spiders inhabiting tree canopies compared to spiders living in the meadow. The 30 orchards that we sampled varied in woody habitat amount and isolation at landscape and patch scales. Local factors included management intensity and plant diversity. Spiders associated with meadow were affected by plant diversity, but not by fragmentation. In contrast, spiders associated with canopies responded to isolation from other woody habitats. Surprisingly, we found both positive and negative effects of habitat isolation on local abundance. This indicates that differences in dispersal and/or biotic interactions shape the specific response to habitat isolation. The relative importance of local and landscape factors was in accordance with the microhabitat of the spiders. Thus, considering microhabitat associations can be important for identifying processes that would be overlooked if sampling were pooled for the whole habitat.!://WOS:000281981000006Times Cited: 1 0921-2973WOS:00028198100000610.1007/s10980-010-9518-6c<7L)Heske, E. J. Robinson, S. K. Brawn, J. D.1999`Predator activity and predation on songbird nests on forest-field edges in east-central Illinois345-354Landscape Ecology144~ecological trap edge effects habitat fragmentation Illinois nest predation raccoons SUCCESS FRAGMENTATION BIRDS ECOTONES SCALEArticleAug5We measured the activity of mammalian predators, numbers of singing male songbirds, and predation rates on nests of songbirds (152 natural, open-cup nests and 380 artificial nests) on 38 250 m transects located along various types of forest-field edges in a wildlife management area in east-central Illinois. We then related these variables to each other and to measures of the vegetative structure of our transects that we anticipated might influence predator activity or predation rates on nests of birds characteristic of edge and shrubland habitats. Mammalian predators, particularly raccoons (Procyon lotor), were abundant in the wildlife area and present on all transects surveyed. We did not find significant relationships among the variables we measured. Rather, rates of nest predation were consistently high (> 70%) and generally evenly distributed around our study site. Medium-sized, generalist mammalian predators in the midwestern United States reach their highest population densities in fragmented landscapes with abundant edge habitat, particularly agricultural edges. Areas of natural habitat in these landscapes dominated by agriculture may concentrate predators and act as ecological traps for nesting birds because they attract high densities of breeding birds that are subjected to high rates of nest predation.://000081305700003 ISI Document Delivery No.: 214AP Times Cited: 31 Cited Reference Count: 38 Cited References: ANDREN H, 1985, OIKOS, V45, P273 ANGELSTAM P, 1986, OIKOS, V47, P365 ASKINS RA, 1995, SCIENCE, V267, P1956 BIDER JR, 1968, ECOL MONOGR, V38, P269 BRAWN JD, 1996, ECOLOGY, V77, P3 COLE J, 1986, W76D ILL DEP NAT RES DIJAK WD, 1996, THESIS U MISSOURI CO DONOVAN TM, 1995, CONSERV BIOL, V9, P1380 DONOVAN TM, 1997, ECOLOGY, V78, P2064 FAABORG J, 1995, ECOLOGY MANAGEMENT N, P357 GATES JE, 1978, ECOLOGY, V59, P871 HENSLER GL, 1981, WILSON BULL, V93, P42 HESKE EJ, 1995, J MAMMAL, V76, P562 HINES JE, 1991, PROGRAM CONTRAST GEN, V25 HOFFMEISTER DF, 1989, MAMMALS ILLINOIS HUTTO RL, 1986, AUK, V103, P593 IVERSON LR, 1989, ILLINOIS NATURAL HIS, V11 MANKIN PC, 1997, CONSERVATION HIGHLY, P135 MARINI MA, 1995, BIOL CONSERV, V74, P302 MAYFIELD HF, 1975, WILSON BULL, V87, P456 MOLLER AP, 1989, OIKOS, V56, P240 MURCIA C, 1995, TRENDS ECOL EVOL, V10, P58 NEELY RD, 1987, ILLINOIS NATURAL HIS, V6 NIXON CM, 1978, ILLINOIS NATURAL HIS, V105 NOOJIBAIL G, 1995, MEADOWLARK, V4, P7 OEHLER JD, 1996, CAN J ZOOL, V74, P2070 PATON PWC, 1994, CONSERV BIOL, V8, P17 PEDLAR JH, 1997, J WILDLIFE MANAGE, V61, P102 RATTI JT, 1988, J WILDLIFE MANAGE, V52, P484 REITSMA LR, 1990, OIKOS, V57, P375 ROBINSON SK, 1995, SCIENCE, V267, P1978 SAUER JR, 1989, J WILDLIFE MANAGE, V53, P137 SMALL MF, 1988, OECOLOGIA, V76, P62 SUAREZ AV, 1997, CONSERV BIOL, V11, P928 VICKERY PD, 1992, OIKOS, V63, P281 WHELAN CJ, 1994, AUK, V111, P945 YAHNER RH, 1988, CONSERV BIOL, V2, P333 YAHNER RH, 1989, J WILDLIFE MANAGE, V53, P1135 0921-2973 Landsc. Ecol.ISI:000081305700003Illinois Nat Hist Survey, Champaign, IL 61820 USA. Heske, EJ, Illinois Nat Hist Survey, 607 E Peabody DR, Champaign, IL 61820 USA.Englishv?PHess, G.19944Pattern and error in landscape ecology: A commentary3-5Landscape Ecology91J|7| Hess, G.19945Pattern and Error in Landscape Ecology - a Commentary3-5Landscape Ecology91Mar://A1994NC71800001-Nc718 Times Cited:22 Cited References Count:0 0921-2973ISI:A1994NC71800001NHess, G N Carolina State Univ,Biomath Program,1509 Varsity Dr,Raleigh,Nc 27606English<7:Hess, G. R. Bay, J. M.1997GGenerating confidence intervals for composition-based landscape indexes309-320Landscape Ecology125landscape indexes; landscape diversity; accuracy assessment; uncertainty; classification error; error matrixes; bootstrapping REMOTELY-SENSED DATA; ACCURACY ASSESSMENT; HETEROGENEOUS LANDSCAPES; FOREST PATCHES; THEMATIC MAPS; ERROR; PATTERNS; CLASSIFICATION; DIVERSITY; IMPROVEArticleOctMany landscape indexes with ecological relevance have been proposed, including diversity indexes, dominance, fractal dimension, and patch size distribution. Classified land cover data in a geographic information system (GIS) are frequently used to calculate these indexes. However, a lack of methods for quantifying uncertainty in these measures makes it difficult to test hypothesized relations among landscape indexes and ecological processes. One source of uncertainty in landscape indexes is classification error in land cover data, which can be reported in the form of an error matrix. Some researchers have used error matrices to adjust extent estimates derived from classified land cover data. Because landscape diversity indexes depend only on landscape composition - the extent of each cover in a landscape - adjusted extent estimates may be used to calculate diversity indexes. We used a bootstrap procedure to extend this approach and generate confidence intervals for diversity indexes. Bootstrapping is a technique that allows one to estimate sample variability by resampling from the empirical probability distribution defined by a single sample. Using the empirical distribution defined by an error matrix, we generated a bootstrap sample of error matrixes. The sample of error matrixes was used to generate a sample of adjusted diversity indexes from which estimated confidence intervals for the diversity indexes were calculated. We also note that present methods for accuracy assessment are not sufficient for quantifying the uncertainty in landscape indexes that are sensitive to the size, shape, and spatial arrangement of patches. More information about the spatial structure of error is needed to calculate uncertainty for these indexes. Alternative approaches should be considered, including combining traditional accuracy assessments with other probability data generated during the classification procedure.://000077684100005  ISI Document Delivery No.: 150UN Times Cited: 13 Cited Reference Count: 52 Cited References: *MATHS INC, 1993, STATSC S PLUS GUID S ARONOFF S, 1982, PHOTOGRAM ENG REMOTE, V48, P1299 BARRETT GW, 1990, SUSTAINABLE AGR SYST, P624 BOWEN GW, 1981, PUBLICATION OAK RIDG BUCKLAND ST, 1994, INT J REMOTE SENS, V15, P1273 BURROUGH PA, 1981, NATURE, V294, P240 CARD DH, 1982, PHOTOGRAMMETRIC ENG, V48, P431 CONGALTON RG, 1988, PHOTOGRAMM ENG REM S, V54, P593 CONGALTON RG, 1988, PHOTOGRAMMETRIC ENG, V54, P587 CONGALTON RG, 1991, REMOTE SENS ENVIRON, V37, P35 CONGALTON RG, 1993, PHOTOGRAMM ENG REM S, V59, P641 CORVES C, 1994, INT J REMOTE SENS, V15, P1283 EFRON B, 1993, INTRO BOOTSTRAP FISHER PF, 1991, INT J GEOGR INF SYST, V5, P193 FLATHER CH, 1992, LANDSCAPE ECOL, V7, P137 FOODY GM, 1990, INT J REMOTE SENS, V11, P1935 GOPAL S, 1994, PHOTOGRAMM ENG REM S, V60, P181 GREEN EJ, 1993, PHOTOGRAMM ENG REM S, V59, P635 HAY AM, 1988, INT J REMOTE SENS, V9, P1395 HESS G, 1994, LANDSCAPE ECOL, V9, P3 HURLBERT SH, 1971, ECOLOGY, V52, P577 JANSSEN LLF, 1994, PHOTOGRAMM ENG REM S, V60, P419 JOHNSON AR, 1992, LANDSCAPE ECOL, V7, P63 KRUMMEL JR, 1987, OIKOS, V48, P321 LAGRO J, 1991, PHOTOGRAMM ENG REM S, V57, P285 LI HB, 1993, LANDSCAPE ECOL, V8, P155 LUNETTA RS, 1991, PHOTOGRAMM ENG REM S, V57, P677 MAGURRAN A, 1988, ECOLOGICAL DIVERSITY MANDELBROT BB, 1977, FRACTALS FORM CHANCE MILNE BT, 1988, APPL MATH COMPUT, V27, P67 MILNE BT, 1991, QUANTITATIVE METHODS, P199 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 ONEILL RV, 1988, LANDSCAPE ECOL, V2, P63 PATTON DR, 1975, WILDLIFE SOC B, V3, P171 PIELOU EC, 1975, ECOLOGICAL DIVERSITY PIELOU EC, 1977, MATH ECOLOGY PRISLEY SP, 1987, PHOTOGRAMM ENG REM S, V53, P1259 REX KD, 1990, LANDSCAPE ECOL, V4, P249 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 ROMME WH, 1982, BIOSCIENCE, V32, P664 STORY M, 1986, PHOTOGRAMM ENG REM S, V52, P397 TENEBEIN A, 1972, TECHNOMETRICS, V14, P187 TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1989, OIKOS, V55, P121 TURNER MG, 1991, QUANTITATIVE METHODS TURNER MG, 1995, BIOSCIENCE S, S29 WALSH SJ, 1987, PHOTOGRAMM ENG REM S, V53, P1423 WICKHAM JD, 1994, LANDSCAPE ECOL, V9, P7 WIENS JA, 1992, LANDSCAPE ECOL, V7, P149 WITH KA, 1994, LANDSCAPE ECOL, V9, P25 ZIPPERER WC, 1993, LANDSCAPE ECOL, V8, P177 0921-2973 Landsc. Ecol.ISI:000077684100005N Carolina State Univ, Dept Forestry, Raleigh, NC 27695 USA. N Carolina State Univ, Dept Stat, Raleigh, NC 27695 USA. Hess, GR, N Carolina State Univ, Dept Forestry, Box 8002, Raleigh, NC 27695 USA. grhess@ncsu.edu jeff_bay@ncsu.eduEnglish ~?G*Hessburg, P. F. Salter, R. B. James, K. M.2007Re-examining fire severity relations in pre-management era mixed conifer forests: inferences from landscape patterns of forest structure5-24Landscape Ecology22For some time, ecologists have known that spatial patterns of forest structure reflected disturbance and recovery history, disturbance severity and underlying influences of environmental gradients. In spite of this awareness, historical forest structure has been little used to expand knowledge of historical fire severity. Here, we used forest structure to predict pre-management era fire severity across three biogeoclimatic zones in eastern Washington State, USA, that contained extensive mixed conifer forests. We randomly selected 10% of the subwatersheds in each zone, delineated patch boundaries, and photo-interpreted the vegetation attributes of every patch in each subwatershed using the oldest available stereo-aerial photography. We statistically reconstructed the vegetation of any patch showing evidence of early selective harvesting, and then classified them as to their most recent fire severity. Classification used published percent canopy mortality definitions and a dichotomized procedure that considered the overstory and understory canopy cover and size class attributes of a patch, and the fire tolerance of its cover type. Mixed severity fires were most prevalent, regardless of forest type. The structure of mixed conifer patches, in particular, was formed by a mix of disturbance severities. In moist mixed conifer, stand replacement effects were more widespread in patches than surface fire effects, while in dry mixed conifer, surface fire effects were more widespread by nearly 2:1. However, evidence for low severity fires as the primary influence, or of abundant old park-like patches, was lacking in both the dry and moist mixed conifer forests. The relatively low abundance of old, park-like or similar forest patches, high abundance of young and intermediate-aged patches, and widespread evidence of partial stand and stand-replacing fire suggested that variable fire severity and nonequilibrium patch dynamics were primarily at work."://WOS:000251543600002 Times Cited: 0WOS:00025154360000210.1007/s10980-007-9098-2<7!Hietel, E. Waldhardt, R. Otte, A.2004UAnalysing land-cover changes in relation to environmental variables in Hesse, Germany473-489Landscape Ecology195agricultural land-cover change; CCA; environmental conditions; German marginal rural landscape; K-means partitioning; local scale; multi-temporal land-cover data CENTRAL NEW-ENGLAND; LANDSCAPE CHANGE; DYNAMICS; VEGETATION; DIVERSITY; PATTERNS; FRANCE; SCALE; USAArticleLand-use and land-cover changes affect ecological landscape functions and processes. Hence, landscape ecologists have a central interest in a comprehensive understanding of such changes. Our study focuses on the relationships between environmental conditions and agricultural land-cover changes. We present a method to (i) characterise the major spatial-temporal processes of land-cover changes, (ii) identify the correlations between environmental attributes and land-cover changes and (iii) derive potential environmental drivers of land-cover changes in a German marginal rural landscape. The method was applied to study land-cover dynamics from 1945 to 1998 in the districts of Erda, Steinbrucken and Eibelshausen, situated in the marginal rural landscape of the Lahn-Dill Highlands, Germany. We employed land-cover data gained by the interpretation of multi-temporal aerial photographs. Various environmental variables were introduced into the analyses. We identified physical landscape attributes (elevation, slope, aspect, available water capacity and soil texture) and structural landscape dimensions (patch size, patch shape and distance between patch and nearest settlement). With the aid of GIS, K-means partitioning and canonical correspondence analysis, we investigated land-cover trajectory types, land-cover transitions at individual time intervals and their relationships to these environmental variables. Our results show that, between 1945 and 1998, land-cover changes correlated with the physical attributes of the underlying landscape. On the other hand, the structural landscape dimensions correlated with land cover only in periods of minor land-cover changes (1972-98). Greater diversity of physical landscape attributes is correlated with greater land-cover dynamics. Besides the important influence of socio-economic factors, land-cover changes in the study areas took place within the relatively stable physical constraints of the underlying landscape.://000222941500002 ISI Document Delivery No.: 841OY Times Cited: 16 Cited Reference Count: 57 Cited References: *AG BOD, 1982, BOD KART *BUND VERBR ERN LA, 2001, AGR BUND *CTR BIOM WAG, 1998, CAN WIND 4 0 *HSL STAT OFF STAT, 1950, HESS GEM *STATSOFT INC, 2001, STAT WIND SOFTW SYST BAUDRY J, 1993, LANDSCAPE ECOLOGY AG, P21 BUREL F, 1995, AGR ECOSYST ENVIRON, V55, P193 CAIN DH, 1997, LANDSCAPE ECOL, V12, P199 CHEN LD, 2001, AGR ECOSYST ENVIRON, V86, P163 CHERRILL AJ, 1995, LANDSCAPE ECOL, V10, P197 DELBARRIO G, 1997, LANDSCAPE ECOL, V12, P95 ECKART K, 1998, AGRARGEOGRAPHIE DEUT FOSTER DR, 1992, J ECOL, V80, P753 FREDE HG, 1999, J RURAL ENG DEV, V40, P193 FUHRBOSSDORF K, 1999, VERH GES OKOL, V29, P519 FULLER TL, 1998, ECOSYSTEMS, V1, P76 HENKEL G, 1995, LANDLICHE RAUM HERZOG F, 2001, ENVIRON MANAGE, V27, P91 IRWIN EG, 2001, AGR ECOSYST ENVIRON, V85, P7 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 KEUNECKE K, 1997, THESIS U GIESSEN GER KOHL M, 1978, GIESSENER GEOGRAPHIS, V45 LAMBIN EF, 1997, PROG PHYS GEOG, V21, P375 LEGENDRE P, 1998, NUMERICAL ECOLOGY LIEB A, THESIS U MARBURG GER LOPEZ E, 2001, LANDSCAPE URBAN PLAN, V55, P271 MCGARIGAL K, 1994, FRAGSTATS SPATIAL PA MERRIAM G, 1988, TRENDS ECOL EVOL, V3, P16 MERTENS B, 2000, ANN ASSOC AM GEOGR, V90, P467 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 OEKLAND RH, 1990, SOMMERFELTIA S, V1, P1 OLSSON EGA, 2000, LANDSCAPE ECOL, V15, P155 PAN DY, 1999, LANDSCAPE ECOL, V14, P35 POUDEVIGNE I, 1997, LANDSCAPE URBAN PLAN, V38, P93 POWER J, 1995, LANDSCAPE URBAN PLAN, V31, P195 RESCIA AJ, 1997, J VEG SCI, V8, P343 ROTHKEGEL W, 1950, GESCH ENTWICKLUNG BO RUSSELL EJ, 1988, SOIL CONDITIONS PLAN SAUER S, 2000, MITTEILGN DTSCH BODE, V93, P200 SCHNEIDER LC, 2001, AGR ECOSYST ENVIRON, V85, P83 SEIFFERT P, 1994, ANAL BEWERTUNG KULTU SIMMERING D, 2001, TUEXENIA, V21, P51 SIMPSON JW, 1994, LANDSCAPE ECOL, V9, P261 SKANES HM, 1997, LANDSCAPE URBAN PLAN, V38, P61 SZIBALSKI M, 1999, J RURAL ENG DEV, V40, P228 TERBRAAK CJF, 1986, ECOLOGY, V67, P1167 TERBRAAK CJF, 1998, CANOCO REFERENCE MAN TURNER BL, 1994, AMBIO, V23, P91 TURNER MG, 1996, ECOL APPL, V6, P1150 VELDKAMP A, 1997, AGR SYST, V55, P19 VITOUSEK PM, 1997, SCIENCE, V277, P494 VONHANXLEDEN PS, 1972, MARBURGER GEOGRAPHIS, V54 VONTHUNEN JH, 1826, ISOLIERTE STAAT BEZI VOS W, 1993, LANDSCAPE URBAN PLAN, V27, P51 WALDHARDT R, 2000, RAUM Z SCHRIFTENREIH, V31, P121 WALDHARDT R, 2003, AGR ECOSYST ENVIRON, V98, P339 WEBER A, 2001, ECOL MODEL, V140, P125 0921-2973 Landsc. Ecol.ISI:000222941500002Univ Giessen, IFZ, Dept Landscape Ecol & Landscape Planning, D-35392 Giessen, Germany. Hietel, E, Univ Giessen, IFZ, Dept Landscape Ecol & Landscape Planning, Heinrich Buff Ring 26-32, D-35392 Giessen, Germany. elke.c.hietel@agrar.uni-giessen.deEnglish~?o;Hinchey, E. K. Nicholson, M. C. Zajac, R. N. Irlandi, E. A.20084Marine and coastal applications in landscape ecology1-5Landscape Ecology23Landscape ecology traditionally has been limited to the study of terrestrial systems; however, the questions and methods defining the science are equally relevant for marine and coastal systems. The reciprocal relationship between spatial pattern and ecological processes and the overarching effect of scale on this relationship was being explored in some marine and coastal settings as the general discipline of landscape ecology was evolving throughout the latter two decades of the last century. As with all components of the biosphere, an understanding of these relationships is critical for successful management of marine and coastal systems. In these systems, widely dispersed field or ship-based observations and lack of broad scale data have historically precluded quantification of large-scale patterns and processes and hindered management efforts. However, relatively recent advances in geographic information systems, remote sensing and computer technologies have begun to address these issues and are now permitting assessments of pattern and process in oceans. The intent of this special issue is to highlight research that is adapting the tools of landscape ecology to answer ecological questions within marine and coastal systems, to address the unique challenges faced in these landscapes, and to stimulate an exchange of ideas and solutions to common problems. Inspiration for this special issue of Landscape Ecology began with a special session on "Marine and Coastal Applications in Landscape Ecology" that was held at the 19th Annual Symposium of the United States Regional Association of the International Association for Landscape Ecology, March 31-April 2, 2004 in Las Vegas, Nevada."://WOS:000252922800001 Times Cited: 1WOS:000252922800001(10.1007/s10980-007-9141-3|ISSN 0921-2973<7Hinsley, S. A.2000(The costs of multiple patch use by birds765-775Landscape Ecology158breeding birds daily energy expenditure foraging behaviour gap-crossing habitat fragmentation optimal foraging parental costs Parus major time costs TITS PARUS-MAJOR ENERGY-EXPENDITURE FOREST FRAGMENTATION BODY-MASS GREAT TIT PIED FLYCATCHER BROOD LANDSCAPE HABITAT ADAPTATIONArticleDecBirds living in fragmented habitat may occupy territories comprising more than one patch. This paper uses a theoretical model to investigate the costs (in terms of time and energy) of crossing gaps between patches for birds feeding young in the nest, using the great tit (Parus major) as an example. When the proportion of foraging trips involving gap-crossing was small (25%), gaps of about 300-550 m (depending on body mass and flight speed) could be crossed without exceeding likely maximum sustainable daily energy expenditure (DEEmax). However, a penalty of time lost in crossing gaps of about one hour was incurred. For more gap-crossing (due to larger brood size and/or a greater proportion of gap-crossing trips), distances that could be crossed decreased rapidly to about 50-100 m and time lost increased to more than six hours. Crossing gaps at maximum range speed, rather than at the slower minimum power speed, reduced flight times by 42% and slightly reduced overall daily energy expenditure because the higher flight costs per minute were more than off-set by the shorter flight times. Smaller body mass (17 g versus 19 g) was advantageous for gap-crossing, the distances which could be crossed without exceeding DEEmax being almost doubled for the smaller mass. The influence of changes in wing morphology, fat load and prey load size on the energetics of gap-crossing were also considered. Although the model was constructed for a woodland bird, problems of time and energy expenditure associated with gap-crossing will affect many species which exploit patchy resources, especially when the spacing of the patches increases, for example due to habitat loss and modification. In landscapes where semi-natural habitat is highly fragmented and most surviving patches are small (e.g., many farming landscapes) the costs of multiple patch use may represent another mechanism by which habitat fragmentation reduces the reproductive potential of the inhabitants of habitat patches which are of acceptable or even good quality, but are small.://000165379700007 ISI Document Delivery No.: 375BM Times Cited: 25 Cited Reference Count: 46 Cited References: ANDREN H, 1992, ECOLOGY, V73, P794 ANDREN H, 1994, OIKOS, V71, P355 ANGELSTAM P, 1992, ECOLOGICAL PRINCIPLE, P9 BURKE DM, 1998, AUK, V115, P96 CAVITT JF, 1997, ECOLOGY, V78, P2512 COWIE RJ, 1988, J ANIM ECOL, V57, P611 CRAMP S, 1993, BIRDS W PALEARCTIC, V7, P255 CUTHILL I, 1990, ANIM BEHAV, V40, P1087 DESROCHERS A, 1997, CONSERV BIOL, V11, P1204 DIAS PC, 1996, OECOLOGIA, V107, P79 DRENT RH, 1980, ARDEA, V68, P225 DUNNING JB, 1992, OIKOS, V65, P169 EYBERT MC, 1995, BIOL CONSERV, V74, P195 FREED LA, 1981, ECOLOGY, V62, P1179 GIBB JA, 1955, BR BIRDS, V48, P49 GIBB JA, 1963, J ANIM ECOL, V32, P489 GOLDSTEIN DL, 1988, AM ZOOL, V28, P829 HILLSTROM L, 1995, FUNCT ECOL, V9, P807 HINSLEY SA, 1995, IBIS, V137, P418 HINSLEY SA, 1995, J AVIAN BIOL, V26, P94 HINSLEY SA, 1998, GLOBAL ECOL BIOGEOGR, V7, P125 HINSLEY SA, 1999, J AVIAN BIOL, V30, P271 HORAK P, 1995, OECOLOGIA, V102, P515 KIRKWOOD JK, 1983, COMP BIOCHEM PHYS A, V75, P1 MASMAN D, 1987, AUK, V104, P603 MERKLE MS, 1996, J ANIM ECOL, V65, P401 MORENO J, 1995, J ANIM ECOL, V64, P721 MURCIA C, 1995, TRENDS ECOL EVOL, V10, P58 NORBERG RA, 1981, AM NAT, V118, P838 PENNYCUICK CJ, 1989, BIRD FLIGHT PERFORMA PERRINS CM, 1979, BRIT TITS PIERSMA T, 1996, PHYSIOL ZOOL, V69, P191 RAIL JF, 1997, CONDOR, V99, P976 REID ML, 1988, OIKOS, V51, P115 RICKLEFS RE, 1974, AVIAN ENERGETICS, P152 ROLSTAD J, 1991, BIOL J LINN SOC, V42, P149 RYTKONEN S, 1996, J AVIAN BIOL, V27, P21 SANZ JJ, 1998, ARDEA, V86, P101 STEPHENS DW, 1986, FORAGING THEORY TATNER P, 1986, AUK, V103, P169 TAYLOR PD, 1993, OIKOS, V68, P571 TINBERGEN JM, 1994, FUNCT ECOL, V8, P563 TUCKER VA, 1968, J EXP BIOL, V48, P67 TUCKER VA, 1974, AVIAN ENERGETICS, P298 VANBALEN JH, 1973, ARDEA-T NED, V61, P1 WRIGHT J, 1998, J ANIM ECOL, V67, P620 0921-2973 Landsc. Ecol.ISI:000165379700007NERC, Inst Terr Ecol, Huntingdon PE28 2LS, Cambs, England. Hinsley, SA, NERC, Inst Terr Ecol, Huntingdon PE28 2LS, Cambs, England.English(~?dHinsley, S. A. Hill, R. A. Bellamy, P. E. Harrison, N. M. Speakman, J. R. Wilson, A. K. Ferns, P. N.2008eEffects of structural and functional habitat gaps on breeding woodland birds: working harder for less615-626Landscape Ecology235The effects of habitat gaps on breeding success and parental daily energy expenditure (DEE) were investigated in great tits (Parus major) and blue tits (Cyanistes caeruleus) in urban parkland (Cardiff, UK) compared with birds in deciduous woodland (eastern England, UK). Tree canopy height, the percentage of gap in the canopy and the percentage of oak (in the wood only) within a 30 m radius of nest boxes were obtained from airborne remote-sensed data. Breeding success was monitored and parental DEE (great tits: both habitats; blue tits: park only) was measured using doubly labelled water in birds feeding young. In the park, mean (+/- SD) tree height (7.5 +/- 4.7 m) was less than in the wood (10.6 +/- 4.5 m), but the incidence of gaps (32.7 +/- 22.6%) was greater (9.2 +/- 14.7%). Great tits and blue tits both reared fewer young in the park and chick body mass was also reduced in park-reared great tits. Park great tits had a higher DEE (86.3 +/- 12.3 kJ day(-1)) than those in the wood (78.0 +/- 11.7 kJ day(-1)) and, because of smaller brood sizes, worked about 64% harder for each chick reared. Tits in the park with more than about 35% gap around their boxes had higher DEEs than the average for the habitat. In the wood, great tits with less oak around their boxes worked harder than average. Thus structural gaps, and functional gaps generated by variation in the quality of foraging habitat, increased the costs of rearing young."://WOS:000254964600011 Times Cited: 0WOS:000254964600011(10.1007/s10980-008-9225-8|ISSN 0921-2973.?Q7 Hobbs, E. R.1988WSpecies richness of urban forest patches and implications for urban landscape diversity141-152Landscape Ecology13yTheory of island biogeography, Landscape ecology, Urban forests, Species richness, Landscape (gamma) diversity, MinnesotaThe vascular plant species richness of upland urban forest patches in St. Paul and Minneapolis, Minnesota, was found to be positively related to their size. There was no significant relationship between species richness and the distance of these patches to other patches. Mowing and trampling reduced species richness of patches, whereas planting increased richness. Landscape richness can be maintained at a relatively high level by leaving even small unmown forested patches within a more disturbed matrix. However, maximizing landscape diversity would require leaving large forest stands unmown. It is suggested that cultivation be deliberately used as a mechanism for increasing native species richness in urban forests.ڽ7$DHoffman, ForrestM Kumar, Jitendra Mills, RichardT Hargrove, WilliamW2013HRepresentativeness-based sampling network design for the State of Alaska 1567-1586Landscape Ecology288Springer NetherlandsOEcoregions Representativeness Network design Cluster analysis Alaska Permafrost 2013/10/01+http://dx.doi.org/10.1007/s10980-013-9902-0 0921-2973Landscape Ecol10.1007/s10980-013-9902-0English<7\$Holderegger, R. Kamm, U. Gugerli, F.2006KAdaptive vs. neutral genetic diversity: implications for landscape genetics797-807Landscape Ecology216adaptive genetic variation; heritability; landscape genetics; neutral genetic variation; population differentiation; quantitative genetics CONSERVATION; POPULATIONS; ECOLOGY; DIFFERENTIATION; DIVERGENCE; DISPERSAL; TRAITS; TREES; OAKSArticleAugQGenetic diversity is important for the maintenance of the viability and the evolutionary or adaptive potential of populations and species. However, there are two principal types of genetic diversity: adaptive and neutral - a fact widely neglected by non-specialists. We introduce these two types of genetic diversity and critically point to their potential uses and misuses in population or landscape genetic studies. First, most molecular-genetic laboratory techniques analyse neutral genetic variation. This means that the gene variants detected do not have any direct effect on fitness. This type of genetic variation is thus selectively neutral and tells us nothing about the adaptive or evolutionary potential of a population or a species. Nevertheless, neutral genetic markers have great potential for investigating processes such as gene flow, migration or dispersal. Hence, they allow us to empirically test the functional relevance of spatial indices such as connectivity used in landscape ecology. Second, adaptive genetic variation, i.e. genetic variation under natural selection, is analysed in quantitative genetic experiments under controlled and uniform environmental conditions. Unfortunately, the genetic variation (i.e. heritability) and population differentiation at quantitative, adaptive traits is not directly linked with neutral genetic diversity or differentiation. Thus, neutral genetic data cannot serve as a surrogate of adaptive genetic data. In summary, neutral genetic diversity is well suited for the study of processes within landscapes such as gene flow, while the evolutionary or adaptive potential of populations or species has to be assessed in quantitative genetic experiments. Landscape ecologists have to mind these differences between neutral and adaptive genetic variation when interpreting the results of landscape genetic studies.://000239484200002 @ISI Document Delivery No.: 069YA Times Cited: 3 Cited Reference Count: 39 Cited References: ANTOLIN MF, 2006, LANDSCAPE ECOL, V21, P867 CONNOR JK, 2004, PRIMER ECOLOGICAL GE DARWIN C, 1859, ORIGIN SPECIES MEANS FALCONER DS, 1996, INTRO QUANTITATIVE G FRANKHAM R, 2004, PRIMER CONSERVATION FUTUYMA DJ, 2005, EVOLUTION GODOY JA, 2001, MOL ECOL, V10, P2275 HARTL DL, 1997, PRINCIPLES POPULATIO HOLDEREGGER R, IN PRESS CHANGING WO JACKSON RB, 2002, TRENDS ECOL EVOL, V17, P409 KIMURA M, 1983, NEUTRAL THEORY MOL E KREMER A, 2002, FOREST ECOL MANAG, V156, P75 LATTA RG, 2003, NEW PHYTOL, V161, P51 LATTA RG, 2006, LANDSCAPE ECOL, V21, P809 LI HB, 2004, LANDSCAPE ECOL, V19, P389 LI WH, 1991, FUNDAMENTALS MOL EVO LOWE A, 2004, ECOLOGICAL GENETICS MANEL S, 2003, TRENDS ECOL EVOL, V18, P189 MCKAY JK, 2002, TRENDS ECOL EVOL, V17, P285 MERILA J, 2001, J EVOLUTION BIOL, V14, P892 OMEALLY D, 2005, BIOL CONSERV, V122, P395 PANNELL JR, 2006, LANDSCAPE ECOL, V21, P837 PEARMAN PB, 2001, CONSERV BIOL, V15, P780 PEARSE DE, 2004, CONSERV GENET, V5, P585 PETIT RJ, 2002, FOREST ECOL MANAG, V156, P5 REED DH, 2001, EVOLUTION, V55, P1095 REED DH, 2002, CONSERV BIOL, V17, P230 SAVOLAINEN O, 2004, FOREST ECOL MANAG, V197, P79 SCHWAEGERLE KE, 1986, EVOLUTION, V40, P506 SLATKIN M, 2005, MOL ECOL, V14, P67 SMOUSE PE, 2004, FOREST ECOL MANAG, V197, P21 SORK VL, 2006, LANDSCAPE ECOL, V21, P821 TURNER MG, 2001, LANDSCAPE ECOLOGY TH VANDEWOESTIJNE S, 2004, POPUL ECOL, V46, P281 WAGNER HH, 2006, LANDSCAPE ECOL, V21, P849 WIDMER A, 2001, TRENDS ECOL EVOL, V16, P267 WIENS JA, 1989, FUNCT ECOL, V3, P385 WRIGHT S, 1951, ANN EUGEN, V15, P323 WU JG, 2002, LANDSCAPE ECOL, V17, P355 0921-2973 Landsc. Ecol.ISI:000239484200002 WSL Swiss Fed Res Inst, Sect Ecol Genet, CH-8903 Birmensdorf, Switzerland. ETH Zentrum, Dept Environm Sci, CH-8092 Zurich, Switzerland. Holderegger, R, WSL Swiss Fed Res Inst, Sect Ecol Genet, Zurcherstr 111, CH-8903 Birmensdorf, Switzerland. rolf.holderegger@wsl.chEnglishW<7[Holderegger, R. Wagner, H. H.2006#A brief guide to landscape genetics793-796Landscape Ecology216ECOLOGYEditorial MaterialAug://000239484200001 ISI Document Delivery No.: 069YA Times Cited: 0 Cited Reference Count: 18 Cited References: ANTOLIN MF, 2006, LANDSCAPE ECOL, V21, P867 BAQUETTE M, 2004, BASIC APPL ECOL, V5, P213 BROQUET T, 2006, LANDSCAPE ECOL, V21, P877 HARTL DL, 1997, PRINCIPLES POPULATIO HOLDEREGGER R, IN PRESS CHANGING WO HOLDEREGGER R, 2006, LANDSCAPE ECOL, V21, P797 HOLZHAUER SIJ, 2006, LANDSCAPE ECOL, V21, P891 LATTA RG, 2006, LANDSCAPE ECOL, V21, P809 LI HB, 2004, LANDSCAPE ECOL, V19, P389 MANEL S, 2003, TRENDS ECOL EVOL, V18, P189 NEVILLE HM, 2006, LANDSCAPE ECOL, V21, P901 OVASKAINEN O, 2004, ECOLOGY GENETICS EVO, P73 PANNELL JR, 2006, LANDSCAPE ECOL, V21, P837 SORK VL, 2006, LANDSCAPE ECOL, V21, P821 TURNER MG, 2001, LANDSCAPE ECOLOGY TH WAGNER HH, 2006, LANDSCAPE ECOL, V21, P849 WHITLOCK MC, 1999, HEREDITY 2, V82, P117 WU JG, 2002, LANDSCAPE ECOL, V17, P355 0921-2973 Landsc. Ecol.ISI:000239484200001WSL Swiss Fed Res Inst, CH-8903 Birmensdorf, Switzerland. Wagner, HH, WSL Swiss Fed Res Inst, Zurcherstr 111, CH-8903 Birmensdorf, Switzerland. helene.wagner@wsl.chEnglish|?7Holdo, Ricardo M. Anderson, T. Michael Morrison, Thomas2014UPrecipitation, fire and demographic bottleneck dynamics in Serengeti tree populations 1613-1623Landscape Ecology299NovqTree size distributions are the outcome of demographic processes and disturbance events, and size distribution analysis provides a useful tool for understanding pattern and process in tree population dynamics. Demographic bottleneck mechanisms such as fire "traps" are important for driving tree cover dynamics in savanna systems, and bottlenecks might be expected to be revealed by bimodal size distributions in savanna tree communities. We tested the relative fit of monotonic and bimodal Weibull distributions to tree height distributions across 36 0.1-ha plots over 4 years in Serengeti National Park, Tanzania, using a Bayesian analysis. The plots were subjected to two fire treatments and spanned a mean annual rainfall gradient ranging from 600 to 900 mm year(-1). We found that Serengeti trees are highly bimodal in their height distributions, with a pronounced gap in the 1-3 m height range, suggesting that demographic bottlenecks are a pervasive feature of this system. We also found that pre- and post-bottleneck tree densities are increasing and declining over time, respectively. Pre-bottleneck density declined with fire and increased with mean annual precipitation, and exhibited a rainfall by fire interaction, with negative fire effects becoming more important at the wet extreme of our rainfall gradient. Overall, despite the negative effect of fire on pre-bottleneck trees, the density of the latter is increasing over time, suggesting that although recruitment into larger size classes has been tightly constrained in the past, there is mixed support for a role of fire in maintaining this pattern under current burning regimes.!://WOS:000343648700012Times Cited: 1 0921-2973WOS:00034364870001210.1007/s10980-014-0087-y |7)Holland, E. P. Aegerter, J. N. Dytham, C.2009QComparing resource representations and choosing scale in heterogeneous landscapes213-227Landscape Ecology242resource representation spatial statistics clustering landscape pattern modelling lacunarity lacunarity analysis spatial-pattern dispersion hypothesis fragmented landscape population-dynamics model behavior connectivity successFebEvery species experiences the landscape as a unique pattern of resource quality and heterogeneity. This subsequently affects aspects of life from the individual scale (fitness, home range size), to social group scale, up to landscape characteristics such as source-sink dynamics, connectivity and species diversity. Correctly characterising the quality and spatial pattern of resources is therefore key in modelling species' persistence and spread. However, although many measures of heterogeneity are available for binary and ordinal landscape patterns, few are directly applicable to landscapes with a continuous description of landscape quality. Lacunarity is a measure of the structure of gaps in the landscape, first used to describe properties of fractal landscapes. We develop lacunarity analysis to allow the direct comparison of pattern in binary and continuous landscapes with differing mean quality. Using simulated landscapes with varying degrees of spatial autocorrelation and resource distribution broadly describing the spectrum of resource quality experienced by specialists and generalists, we show how the measurement of spatial pattern changes when different distributions are used to describe landscape quality. Our metric indicates the scale of measurement at which the pattern is most different from random, and thus informs the choice of scale for modelled processes in the model landscape, and the appropriate extent for landscape study. Our metric can be used to distinguish between any spatial pattern or resource description, from a simple parametric distribution for landscape quality to the variety of resources likely to be encountered in real landscapes.://000262828900006-399WB Times Cited:0 Cited References Count:37 0921-2973ISI:000262828900006Holland, EP Cent Sci Lab, York YO41 1LZ, N Yorkshire, England Cent Sci Lab, York YO41 1LZ, N Yorkshire, England Univ York, Dept Biol, York YO10 5YW, N Yorkshire, EnglandDoi 10.1007/S10980-008-9300-1English[|? Holland, Jeffrey D.2010OIsolating spatial effects on beta diversity to inform forest landscape planning 1349-1362Landscape Ecology259Nov<Understanding the effects of landscapes on pest and non-pest species is necessary if regional landscape planning is to both control pests and conserve biodiversity. A first step is understanding of how both pests and non-pest species interact with the landscape configuration to determine the density of the two groups. While it is impossible to examine the occurrence and dispersal behavior of all species, different turnover rates in different species assemblages may offer general insights into responses of species assemblages. In this study I examine the distance decay of similarity of longhorned beetle assemblages in a large forest area in Indiana, USA, with minimal differences in habitat and few barriers to dispersal. Differences in beta diversity between groups are therefore likely due to dispersal distances. I found differences in turnover rates between species that decompose dead wood and those that attack living trees, and between species with different adult feeding habits. This suggests that management for simultaneous conservation and pest control is possible.!://WOS:000281981000004Times Cited: 0 0921-2973WOS:00028198100000410.1007/s10980-010-9499-5<7Hollenbeck, J. P. Ripple, W. J.2007RAspen patch and migratory bird relationships in the northern Yellowstone ecosystem 1411-1425Landscape Ecology229aspen; bird migration; interception; patch orientation; populus tremuloides; Yellowstone National Park CAVITY-NESTING BIRDS; ALTITUDINAL MIGRATION; SPECIES RICHNESS; AVIAN DIVERSITY; BREEDING BIRDS; FOREST; LANDSCAPE; HABITAT; SIZE; COMMUNITIESArticleNovWe evaluated the effects of aspen patch area and orientation (relative to North and an elevational gradient) on the early breeding season abundance and species richness of migratory and resident birds in the northern ungulate winter range of the Yellowstone ecosystem, USA. Using an information-theoretic model selection approach, we found patch area and basal area of aspen to be the most important covariates for long distance migrants, and patch orientation relative to elevational gradient the most important covariate for residents/short-distance migrants. Basal area of live aspen and aspen snags was marginally important for both migratory strategies, likely because aspen snags are an important habitat for most cavity-nesting species. Landscape ecological theory postulates passive interception of dispersing or migrating organisms by patches of suitable habitat. Our results suggest that residents/short-distance migrants are intercepted by patches that are oriented perpendicular to the elevational gradient of our study region resulting in greater abundances and species richness in those patches. However, long-distance migrants appear to use aspen patches without regard to orientation, but rather to patch area.://000250207500012 Cited Reference Count: 60 Cited References: *ENV RES SYST I, 2004, ARCGIS 9 US ARCMAP, P585 *W REG CLIM CTR, 2007, WWW DOC ANDERSON DR, 2001, J WILDLIFE MANAGE, V65, P373 ANDERSON DR, 2002, J WILDLIFE MANAGE, V66, P912 ANDERSON SH, 1974, ECOLOGY, V55, P828 BARMORE WJ, 2003, ECOLOGY UNGULATES TH, P524 BARNETT DT, 2001, SUSTAINING ASPEN W, P460 BARTOS DL, 1998, RANGELANDS, V20, P17 BARTOS DL, 2001, SUSTAINING ASPEN W L, P460 BLAKE JG, 1987, ECOLOGY, V68, P1724 BURNHAM KP, 2002, MODEL SELECTION MULT, P488 CATON EL, 1996, THESIS U MONTANA MIS, P115 DAVIS SK, 2004, AUK, V121, P1130 DESPAIN DG, 1990, YELLOWSTONE VEGETATI, P239 DILWORTH JR, 1985, LOG SCALING TIMBER C, P468 DOBKIN DS, 1995, CONDOR, V97, P694 FINCH DM, 1987, P ISS TECHN MAN IMP FISCHER J, 2002, BIOL CONSERV, V106, P129 FLACK JAD, 1976, BIRD POPULATIONS ASP, P97 FORMAN RTT, 1986, LANDSCAPE ECOLOGY, P619 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY, P632 FRANKLIN AB, 1997, THESIS COLO STATE, P184 GRAHAM CH, 2001, ECOL APPL, V11, P1709 GRANT TA, 1999, WILDLIFE SOC B, V27, P904 GRIFFISKYLE KL, 2003, BIOL CONSERV, V110, P375 GRIFFISKYLE KL, 2005, AM MIDL NAT, V153, P436 GUTHERY FS, 2005, J WILDLIFE MANAGE, V69, P457 GUTZWILLER KJ, 1992, LANDSCAPE ECOL, V6, P293 HAHN TP, 2004, AUK, V121, P1269 HANSEN AJ, 2002, CONSERV BIOL, V16, P1112 HOBSON KA, 2000, CONDOR, V102, P759 INOUYE DW, 2000, P NATL ACAD SCI USA, V97, P1630 INS CORP, 2001, SPLUS 6 WIND US GUID, P688 JOHN RA, 1995, THESIS U MONTANA MIS, P84 JOHNS BW, 1993, WILSON BULL, V105, P256 KAY CE, 1997, J FOREST, V95, P4 LAWLER JJ, 2002, CONDOR, V104, P890 LAWLER JJ, 2002, LANDSCAPE ECOL, V17, P233 LEVEY DJ, 1992, AM NAT, V140, P447 MACARTHUR R, 1961, ECOLOGY, V42, P594 MACARTHUR RH, 2001, THEORY ISLAND BIOGEO, P224 MARTIN TE, 1980, CONDOR, V82, P430 MCENEANEY T, 1996, FIELD CHECKLIST BIRD MCINTYRE NE, 1995, LANDSCAPE ECOL, V10, P85 MORRISSEY CA, 2004, CAN J ZOOL, V82, P800 PRESNALL CC, 1935, CONDOR, V37, P37 RABENOLD KN, 1985, AUK, V102, P805 RALPH CJ, 1995, MONITORING BIRD POPU, P187 RIPPLE WJ, 2000, BIOL CONSERV, V95, P361 SCHIECK J, 1995, RELATIONSHIPS STAND, P308 SKAGEN SK, 2005, CONDOR, V107, P212 SWALLOW SK, 1986, J WILDLIFE MANAGE, V50, P576 TAFT OW, 2006, LANDSCAPE ECOL, V21, P169 TUBELIS DP, 2004, OIKOS, V107, P634 TURCHI GM, 1995, WILSON BULL, V107, P463 WESTPHAL MI, 2003, LANDSCAPE ECOL, V18, P413 WHITCOMB RF, 1981, FOREST ISLAND DYNAMI, P311 WILLIAMS TC, 2001, AUK, V118, P389 WINTERNITZ BL, 1980, WORKSH P MAN W FOR G, P535 YONG W, 1997, SOUTHWEST NAT, V42, P137 0921-2973 Landsc. Ecol.ISI:000250207500012Oregon State Univ, Dept Forest Resources, Corvallis, OR 97331 USA. Hollenbeck, JP, Oregon State Univ, Dept Forest Resources, Corvallis, OR 97331 USA. Jeff.Hollenbeck@oregonstate.edu Bill.Ripple@oregonstate.eduEnglish!~?v*Hollister, J. W. August, P. V. Paul, J. F.2008Effects of spatial extent on landscape structure and sediment metal concentration relationships in small estuarine systems of the United States' Mid-Atlantic Coast91-106Landscape Ecology23Prior studies exploring the quantitative relationship between landscape structure metrics and the ecological condition of receiving waters have used a variety of sampling units (e.g., a watershed, or a buffer around a sampling station) at a variety of spatial scales to generate landscape metrics resulting in little consensus on which scales best describe land-water relationships. Additionally, the majority of these studies have focused on freshwater systems and it is not clear whether results are transferable to estuarine and marine systems. We examined how sampling unit scale controls the relationship between landscape structure and sediment metal concentrations, in small estuarine systems in the Mid-Atlantic region of the United States. We varied the spatial extent of the contributing watersheds used to calculate landscape structure and assessed linear relationships between estuarine sediment metal concentrations and the total area of developed and agricultural lands at each scale. Area of developed lands was consistently related to sediment metals while total agricultural land was not. Developed land had strongest associations with lead and copper; weakest with arsenic and chromium; and moderate associations with cadmium, mercury, and zinc. Local (i.e., less than 15-20 km from a sampling station) land uses have a greater impact than more distant land uses on the amount of toxic metals reaching estuarine sediments."://WOS:000252922800008 Times Cited: 0WOS:000252922800008(10.1007/s10980-007-9143-1|ISSN 0921-2973<7cFHolzhauer, S. I. J. Ekschmitt, K. Sander, A. C. Dauber, J. Wolters, V.2006dEffect of historic landscape change on the genetic structure of the bush-cricket Metrioptera roeseli891-899Landscape Ecology216genetic similarity; land-use dynamics; landscape connectivity; time lag FRAGMENTED LANDSCAPE; SPECIES RICHNESS; POPULATIONS; CONNECTIVITY; COLONIZATION; DISPERSAL; DYNAMICS; BEHAVIOR; FLOWArticleAugThis study investigates the impact of past and present landscape structure on the current genetic structure of the bush-cricket Metrioptera roeseli (Orthoptera, Tettigoniidae) in a rural landscape in Germany. Assuming that land-use types, such as grassland, arable land and forest, as well as linear structures, mainly roads, differentially affect the connectivity of the bush-cricket's habitat and therefore migration and gene flow, we correlated landscape parameters between sampling locations as derived from GIS-maps with genetic similarities between individual bush-crickets as estimated by RAPD-PCR. Fifty bush-crickets were sampled with distances between sampling locations varying between 15 m and 2 km. Corresponding landscape configurations were recorded in 8 years between 1945 and 1998. Landscape configuration 50 years ago appeared to have influenced the present genetic structure of the bush-cricket (R-2 = 0.18). Crossing roads and land use other than grassland along the transect between sampling locations tended to decrease genetic similarity, whereas grassland and parallel roads tended to increase genetic similarity between bush-crickets. Following shifts in land use during 1953-1973 the correlation between landscape and present genetic structure decreased gradually. Our study suggests that it needs time for the landscape to build a visible effect on the genetic structure of the bush-cricket population, and that this effect cannot be detected if the landscape changes faster than the genetic structure responds to it.://000239484200009 ISI Document Delivery No.: 069YA Times Cited: 1 Cited Reference Count: 35 Cited References: *ESRI, 1996, GIS ARCVIEW *SCAN CSPI, 1994, RFLPSCAN 2 01 US MAN BERGGREN A, 2001, J ANIM ECOL, V70, P663 BERGGREN A, 2002, CONSERV BIOL, V16, P1562 BUREL F, 1992, LANDSCAPE ECOL, V6, P161 BUREL F, 1998, ACTA OECOL, V19, P47 CHAMBERLAIN DE, 2000, J APPL ECOL, V37, P771 COULON A, 2004, MOL ECOL, V13, P2841 DEJONG J, 1991, FAUNA FLORA, V86, P214 DOYLE JJ, 1990, FOCUS, V12, P13 FAHRIG L, 1994, CONSERV BIOL, V8, P50 FUHRBOSSDORF K, 1999, VERH GES OKOL, V29, P519 GIBBS JP, 2001, BIOL CONSERV, V100, P15 GOODWIN BJ, 2003, LANDSCAPE ECOL, V18, P687 GURDEBEKE S, 2003, GENETICA, V119, P27 HADDAD N, 2000, CONSERV BIOL, V14, P738 HIETEL E, 2004, LANDSCAPE ECOL, V19, P473 INGRISCH S, 1986, OECOLOGIA, V70, P606 INGRISCH S, 1998, NEUE BREHM BUCHEREI, V629 KEYGHOBADI N, 1999, MOL ECOL, V8, P1481 KINDVALL O, 1998, OIKOS, V81, P449 LANDRY PA, 2001, OIKOS, V95, P136 LAUSSMANN H, 1999, MITTELEUROPAISCHE AG LEGENDRE P, 1994, EVOLUTION, V48, P1487 PETIT S, 1998, AGR ECOSYST ENVIRON, V69, P243 PURTAUF T, 2004, LANDSCAPE URBAN PLAN, V67, P185 RAMIREZ MG, 1999, HEREDITY 5, V83, P580 ROHLF FJ, 1992, NTSYSPC NUMERICAL TA SCHNEIDER S, 2000, ARLEQUIN VER 2 000 S STEINER N, 2002, BER LANDWIRTSCH, V80, P468 TAYLOR PD, 1993, OIKOS, V68, P571 VANDONGEN S, 1998, HEREDITY 1, V80, P92 VICKERY VR, 1965, ANN ENTOMOLOGICAL SO, V10, P165 WALDHARDT R, 2004, LANDSCAPE ECOL, V19, P211 WIENS JA, 1986, COMMUNITY ECOLOGY, P154 0921-2973 Landsc. Ecol.ISI:000239484200009Univ Giessen, Dept Anim Ecol, IFZ, D-35392 Giessen, Germany. Holzhauer, SIJ, Univ Giessen, Dept Anim Ecol, IFZ, Heinrich Buff Ring 26-32, D-35392 Giessen, Germany. Stephanie.Holzhauer@allzool.bio.uni-giessen.deEnglish?<7*Hong, B. G. Swaney, D. P. Weinstein, D. A.2006uSimulating spatial nitrogen dynamics in a forested reference watershed, Hubbard Brook Watershed 6, New Hampshire, USA195-211Landscape Ecology212forest biogeochemistry; nitrogen cycling; spatial modeling; watershed dynamics NORTHERN HARDWOOD FOREST; NEW-YORK; CATSKILL MOUNTAINS; AGRICULTURAL WATERSHEDS; NITRATE EXPORT; SOIL; NITRIFICATION; LANDSCAPE; MODEL; CHEMISTRYArticleFebVWe demonstrate that available information on spatial heterogeneity in biotic, topographic, and climatic variables within a forested watershed, Hubbard Brook Experimental Forest (HBEF) Watershed 6, New Hampshire, USA, was sufficient to reproduce the observed elevational pattern in stream NO3 concentration during the 1982-1992 period. Five gridded maps (N mineralization factor, N uptake factor, precipitation, elevation, and soil depth factor) were created from spatial datasets and successively added to the spatially explicit model SINIC-S as spatially varying input parameters. Adding more spatial information generally improved model predictions, with the exception of the soil depth factor. Ninety percent of the variation in the observed stream NO3 concentration was explained by the combination of the spatial variation of the N mineralization and N uptake factors. Simulated streamflow NO3 flux at the outlet point was improved slightly by introducing spatial variability in the model parameters. The model exhibited substantial cell-to-cell variation in soil N dynamics and NO3 loss within the watershed during the simulation period. The simulation results suggest that the spatial distributions of forest floor organic matter and standing biomass are most responsible for creating the elevational pattern in stream NO3 concentration within this watershed.://000235866400004  ISI Document Delivery No.: 019WC Times Cited: 1 Cited Reference Count: 58 Cited References: ABBOTT MB, 1986, J HYDROL, V87, P45 BAND LE, 2001, HYDROL PROCESS, V15, P2013 BEASLEY DB, 1982, J SOIL WATER CONSERV, V37, P113 BERG B, 2000, CAN J FOREST RES, V30, P122 BERNHARDT ES, 2002, ECOSYSTEMS, V5, P419 BIRKINSHAW SJ, 2000, J HYDROL, V230, P18 BOHLEN PJ, 2001, ECOLOGY, V82, P965 BOURAOUI F, 1997, J HYDROL, V203, P79 BRIERLEY EDR, 2001, PLANT SOIL, V229, P83 BRONSTERT A, 1999, HYDROL PROCESS, V13, P21 CAMPBELL GS, 1998, INTRO ENV BIOPHYSICS CHRIST MJ, 2002, FOREST ECOL MANAG, V159, P145 CLAY DE, 1997, J PROD AGRIC, V10, P446 FAZAKAS Z, 1999, AGR FOREST METEOROL, V98, P417 FEDERER CA, 1995, NE141 USDA FOR SERV FRELICH LE, 1993, ECOLOGY, V74, P513 GBONDOTUGBAWA SS, 2001, WATER RESOUR RES, V37, P1057 GRAY DM, 1993, HDB HYDROLOGY GUNTNER A, 1999, HYDROL PROCESS, V13, P1603 HALL RO, 2002, LIMNOL OCEANOGR, V47, P255 HINKLE SR, 2001, J HYDROL, V244, P157 HONG B, 2004, THESIS CORNELL U ITH HONG BG, 2005, WATER AIR SOIL POLL, V160, P293 JENKINS JC, 1999, ECOSYSTEMS, V2, P555 JOHNSON CE, 2000, ECOSYSTEMS, V3, P159 JOHNSON CE, 2000, SOIL SCI SOC AM J, V64, P1804 JOHNSSON H, 1987, AGR ECOSYST ENVIRON, V18, P333 KORTELAINEN P, 1997, GLOBAL BIOGEOCHEM CY, V11, P627 KUO WL, 1999, WATER RESOUR RES, V35, P3419 KUUSEMETS V, 2002, LANDSCAPE ECOL S1, V17, P59 LAVERMAN AM, 2000, SOIL BIOL BIOCHEM, V32, P1661 LAWRENCE GB, 2000, BIOGEOCHEMISTRY, V50, P21 LITAOR MI, 2002, LANDSCAPE ECOL, V17, P71 LOEHR RC, 1973, EPA SERIES LOVETT GM, 1996, CAN J FOREST RES, V26, P2134 LOVETT GM, 2000, ECOL APPL, V10, P73 MACKAY DS, 2001, ADV WATER RESOUR, V24, P1211 MANDERSCHEID B, 1995, WATER AIR SOIL POLL, V85, P1185 OLINE DK, 2002, LANDSCAPE ECOL, V17, P13 OLLINGER SV, 2002, ECOLOGY, V83, P339 PARTON WJ, 1983, NUTR CYCLING AGR ECO, P533 QUINN P, 1991, HYDROL PROCESS, V5, P59 QUINN PF, 1995, HYDROL PROCESS, V9, P161 RAWLS WJ, 1993, HDB HYDROLOGY RUPP TS, 2000, LANDSCAPE ECOL, V15, P383 RUTTER AJ, 1971, AGRICULTURAL METEORO, V9, P367 SHUTTLEWORTH WJ, 1993, HDB HYDROLOGY STEENHUIS TS, 1986, J HYDROL, V84, P221 VENTEREA RT, 2003, SOIL SCI SOC AM J, V67, P527 VERCHOT LV, 2001, SOIL BIOL BIOCHEM, V33, P1889 VITOUSEK PM, 1982, ECOL MONOGR, V52, P155 WEATHERS KC, 2000, ECOL APPL, V10, P528 WICKHAM JD, 2003, LANDSCAPE ECOL, V18, P195 WILLIARD KWJ, 1997, GLOBAL BIOGEOCHEM CY, V11, P649 WOLOCK DM, 1997, HYDROL PROCESS, V11, P1273 WOODBURY PB, 2002, ECOL MODEL, V150, P211 ZOLLWEG JA, 1994, THESIS CORNELL U ITH ZOLLWEG JA, 1996, T ASAE, V39, P1299 0921-2973 Landsc. Ecol.ISI:000235866400004Cornell Univ, Boyce Thompson Inst Plant Res, Ithaca, NY 14850 USA. Hong, BG, SUNY ESF, 106 Illick Hall,1 Forestry Dr, Syracuse, NY 13210 USA. bohong@mailbox.syr.eduEnglish#<7k(Hooten, M. B. Larsen, D. R. Wikle, C. K.2003hPredicting the spatial distribution of ground flora on large domains using a hierarchical Bayesian model487-502Landscape Ecology185Bayesian statistics Hierarchical Bayesian models landscape vegetation prediction spatial modeling Missouri USA Ozark Highlands AUTOCORRELATION VEGETATION ECOLOGY BINARY PATTERNArticleRAccomodation of important sources of uncertainty in ecological models is essential to realistically predicting ecological processes. The purpose of this project is to develop a robust methodology for modeling natural processes on a landscape while accounting for the variability in a process by utilizing environmental and spatial random effects. A hierarchical Bayesian framework has allowed the simultaneous integration of these effects. This framework naturally assumes variables to be random and the posterior distribution of the model provides probabilistic information about the process. Two species in the genus Desmodium were used as examples to illustrate the utility of the model in Southeast Missouri, USA. In addition, two validation techniques were applied to evaluate the qualitative and quantitative characteristics of the predictions.://000185827200003 'ISI Document Delivery No.: 730JG Times Cited: 4 Cited Reference Count: 44 Cited References: ALBERT JH, 1993, J AM STAT ASSOC, V88, P669 AUGUSTIN NH, 1996, J APPL ECOL, V33, P339 BEERS TW, 1966, J FOREST, V64, P691 BESAG J, 1974, J ROY STAT SOC B MET, V36, P192 BORCARD D, 1992, ECOLOGY, V73, P1045 BROOKSHIRE BL, 1997, P MISS OZ FOR EC PRO, P1 CHERRILL AJ, 1995, LANDSCAPE ECOL, V10, P197 CLARK JS, 2001, SCIENCE, V293, P657 CLAYTON D, 1997, GEN LINEAR MIXED MOD, P276 CRESSIE N, 1993, STAT SPATIAL DATA DAVIS FW, 1990, LANDSCAPE ECOL, V4, P69 DAY FP, 1974, ECOLOGY, V55, P1064 DIGGLE PJ, 1998, APPL STAT, V47, P299 ERICKSON RO, 1943, ANN MISSOURI BOT GAR, V30, P63 ERNST W, 1978, OECOLOG PLANTAR, V13, P175 FORMAN R, 1986, LANDSCAPE ECOLOGY FRANKLIN J, 1998, J VEG SCI, V9, P733 GILKS W, 1997, MARKOV CHAIN MONTE C GLEASON HA, 1926, B TORREY BOT CLUB, V53, P7 GRABNER J, 1996, UNPUB MOFEP BOT PRET GRABNER JK, 1997, P MISS OZ FOR EC PRO, P169 GRABNER JK, 2000, MISSOURI OZARK FORES, P107 GUISAN A, 1998, J VEG SCI, V9, P65 GUISAN A, 2000, ECOL MODEL, V135, P147 HOETING JA, 2000, J AGRIC BIOL ENVIR S, V5, P102 HOOTEN M, 2001, THESIS U MISSOURI CO JUSTICE C, 1998, IEEE T GEOSCIENCE RE, V96 KRYSTANSKY J, 2000, MISSOURI ECOLOGICAL LEGENDRE P, 1993, ECOLOGY, V74, P1659 LICHSTEIN JW, 2002, ECOL MONOGR, V72, P445 MCCULLOCH CE, 1994, J AM STAT ASSOC, V89, P330 MEINERT D, 1997, P MISS OZ FOR EC PRO, P169 NETER J, 1996, APPL LINEAR STAT MOD PIELOU E, 1977, MATH ECOLOGY RIPLEY B, 1981, SPATIAL STAT ROYLE J, 2001, PREDICTING SPECIES O SHUMWAY R, 2000, TIME SERIES ANAL ITS SMITH PA, 1994, GLOBAL ECOL BIOGEOGR, V4, P47 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 WHITTAKER RH, 1956, ECOL MONOGR, V26, P1 WIKLE CK, 2001, J AM STAT ASSOC, V96, P382 WIKLE CK, 2002, SPATIAL CLUSTER MODE, P199 ZAR J, 1984, BIOSTATISTICAL ANAL ZIMMERMANN NE, 1999, J VEG SCI, V10, P469 0921-2973 Landsc. Ecol.ISI:000185827200003Univ Missouri, Dept Stat, Columbia, MO 65211 USA. Univ Missouri, Dept Forestry, Columbia, MO 65211 USA. Hooten, MB, Univ Missouri, Dept Stat, 222 Math Sci Bldg, Columbia, MO 65211 USA.English/?SHoover, S.R. A.J. Parker1991DSpatial components of biotic diversity in landscapes of Georgia, USA125-136Landscape Ecology53Zspecies diversity, landscape diversity, landscape contrast, heterogeneity, spatial pattern*Traditional measures of species diversity and spatially-explicit measures of landscape diversity (derived from Romme 1982) are used to compare biotic diversity in six landscapes across Georgia, USA; two each from the Appalachian Highlands, Piedmont, and Coastal Plain. Species richness and evenness of plots generally increased from the Coastal Plain to the Appalachian Highlands. Community richness, landscape contrast, and landscape heterogeneity increased from the Appalachian Highlands to the Coastal Plain, opposite the gradient of topographic complexity. Coastal Plain landscapes possessed greater contrast and heterogeneity than landscapes in the other two physiographic provinces. This high level of landscape diversity is interpreted as a response to two factors: the increased role of human activity in shaping landscape structure, and the increased range of soil moisture regimes encountered in the sand-rich substrates of the Coastal Plain (from permanently flooded hydric communities to well drained xeric uplands only a few meters higher in elevation).|??6Hopkins, Kristina G. Bain, Daniel J. Copeland, Erin M.2014xReconstruction of a century of landscape modification and hydrologic change in a small urban watershed in Pittsburgh, PA413-424Landscape Ecology293Mar)Assessing the causes of stream impairments is challenging without a clear understanding of the spatiotemporal interactions among human infrastructure networks and hydrologic systems. Landscape change is often characterized using simplistic metrics that lump changes into generalized categories, such as impervious cover. We examined the evolution of human infrastructure in Panther Hollow, a small watershed in Pittsburgh, Pennsylvania to characterize the impacts of long-term (similar to 100 years) landscape change on stream flow. Results show that impervious cover in the catchment grew from 3 % in 1900 to 27 % in 2010. Growth was non-linear, with 60 % of the development occurring between 1904 and 1930. We then compared two models that predict changes in annual water yield, one model based on watershed impervious cover and one based on human infrastructure arrangement. The model based solely on impervious cover predicts excessive amounts of surface runoff relative to the infrastructure model and monitored yield. This discrepancy occurs because the impervious model does not account for the diversion of 50 % of the watershed drainage through the combined sewer system to an adjacent basin. In the Panther Hollow watershed, hydrology is dominated by a reduction in water yield, contrasting typical hydrologic changes associated with urbanization. Our analysis reveals the value of quantifying additional landscape metrics, such as infrastructure pattern and connectivity, which provide a more complete understanding of how human development alters natural hydrology.!://WOS:000331935500005Times Cited: 1 0921-2973WOS:00033193550000510.1007/s10980-013-9972-z;|? Hopkins, R. L.2009Use of landscape pattern metrics and multiscale data in aquatic species distribution models: a case study of a freshwater mussel943-955Landscape Ecology247AugThe distributions of freshwater mussels are controlled by landscape factors operating at multiple spatial scales. Changes in land use/land cover (LULC) have been implicated in severe population declines and range contractions of freshwater mussels across North America. Despite widespread recognition of multiscale influences few studies have addressed these issues when developing distribution models. Furthermore, most studies have disregarded the role of landscape pattern in regulating aquatic species distributions, focusing only on landscape composition. In this study, the distribution of Rabbitsfoot (Quadrula cylindrica) in the upper Green River system (Ohio River drainage) is modeled with environmental variables from multiple scales: subcatchment, riparian buffer, and reach buffer. Four types of landscape environment metrics are used, including: LULC pattern, LULC composition, soil composition, and geology composition. The study shows that LULC pattern metrics are very useful in modeling the distribution of Rabbitsfoot. Together with LULC compositional metrics, pattern metrics permit a more detailed analysis of functional linkages between aquatic species distributions and landscape structure. Moreover, the inclusion of multiple spatial scales is necessary to accurately model the hierarchical processes in stream systems. Geomorphic features play important roles in regulating species distributions at intermediate and large scales while LULC variables appear more influential at proximal scales.://000268430900008Hopkins, Robert L., II 0921-2973ISI:00026843090000810.1007/s10980-009-9373-5 |7;Horikawa, M. Tsuyama, I. Matsui, T. Kominami, Y. Tanaka, N.2009yAssessing the potential impacts of climate change on the alpine habitat suitability of Japanese stone pine (Pinus pumila)115-128Landscape Ecology2418phytosociological releve database (prdb) climatic variables classification tree model roc analysis regional climate model (rcm20) model for interdisciplinary research on climate (miroc) vulnerable area empty habitats sustainable habitats fagus-crenata forests distributions models land temperature accuracy shiftJanTo assess the potential distribution of Pinus pumila, a dominant species of the Japanese alpine zone, and areas of its habitats vulnerable to global warming, we predicted potential habitats under the current climate and two climate change scenarios (RCM20 and MIROC) for 2081-2100 using the classification tree (CT) model. The presence/absence records of P. pumila were extracted from the Phytosociological Relev, Database as response variables, and five climatic variables (warmth index, WI; minimum temperature for the coldest month, TMC; summer precipitation, PRS; maximum snow water equivalent, MSW; winter rainfall, WR) were used as predictor variables. Prediction accuracy of the CT evaluated by ROC analysis showed an AUC value of 0.97, being categorized as "excellent". We designated Third Mesh cells with an occurrence probability of 0.01 or greater as potential habitats and further divided them into suitable and marginal habitats based on the optimum threshold probability value (0.06) in ROC analysis. Deviance weighted scores revealed that WI was the largest contributing factor followed by MSW. Changes in habitat types from the current climate to the two scenarios were depicted within an observed distribution (Hayashi's distribution data). The area of suitable habitats under the current climate decreased to 25.0% and to 14.7% under the RCM20 and MIROC scenarios, respectively. Suitable habitats were predicted to remain on high mountains of two unconnected regions, central Honshu and Hokkaido, while they were predicted to vanish in Tohoku and southwestern Hokkaido. Thus P. pumila populations in these regions are vulnerable to climate change.://000262506000010-395EI Times Cited:0 Cited References Count:57 0921-2973ISI:000262506000010qHorikawa, M Forestry & Forest Prod Res Inst, Dept Plant Ecol, 1 Matsunosato, Tsukuba, Ibaraki 3058687, Japan Forestry & Forest Prod Res Inst, Dept Plant Ecol, Tsukuba, Ibaraki 3058687, Japan Forestry & Forest Prod Res Inst, Hokkaido Res Stn, Toyohira Ku, Sapporo, Hokkaido 0628516, Japan Forestry & Forest Prod Res Inst, Kansai Res Ctr, Fushimi Ku, Kyoto 6120855, JapanDoi 10.1007/S10980-008-9289-5English<7?4Hornfeldt, B. Christensen, P. Sandstrom, P. Ecke, F.2006RLong-term decline and local extinction of Clethrionomys rufocanus in boreal Sweden 1135-1150Landscape Ecology217tclear-cutting; cycles; density indices; grey-sided vole; habitat fragmentation; landscape matrix; local habitat preference; multiple regression; population dynamics; time-series DELAYED DENSITY-DEPENDENCE; NORTHERN SWEDEN; POPULATION FLUCTUATIONS; HABITAT FRAGMENTATION; VOLE POPULATION; FOREST FRAGMENTATION; LANDSCAPE STRUCTURE; CORRIDOR QUALITY; SMALL RODENTS; DYNAMICSArticleOctOver the past three decades in boreal Sweden, there has been a long-term decline of cyclic sympatric voles, leading to local extinctions of the most affected species, the grey-sided vole (Clethrionomys rufocanus). We monitored this decline by snap-trapping on 58 permanent plots spread over 100 km(2) in spring and fall from fall 1971-2003. The reason for the decline is largely unknown, although a common major factor is likely to be involved in the decline of C. rufocanus and of the coexisting voles. However, here we deal with the reasonability of one complementary hypothesis, the habitat fragmentation hypothesis, which assumes that part of the decline of C. rufocanus is caused by habitat (forest) destruction. There was considerable local variation in the decline among the 58 1-ha sampling plots, with respect to both density and timing of the decline; however, all declines ended up with local extinction almost without exception. Local declines were not associated with habitat destruction by clear-cutting within sampling-plots, as declines started about equally often before as after clear-cutting, which suggested that habitat destruction outside sampling plots could be involved. In a multiple regression analysis, local habitat preference (LHP; expressed as a ratio of observed to expected number of voles trapped per habitat) together with two habitat variables in the surrounding (2.5 x 2.5 km(2)) landscape matrix explained 56% of the variation among local cumulated densities of C. rufocanus and hence of local time-series. LHP was positively correlated and explained 31% of the variation, while connectivity among clear-cuts was negatively correlated and proximity among xeric-mesic mires was positively correlated and explained additional 16% and 9%, respectively. Even if the overall decline cannot be connected to local clear-cutting on sampling-plots, clear-cutting and hence habitat fragmentation/destruction in the surrounding landscapes potentially influenced grey-sided vole numbers negatively.://000241010900013 ISI Document Delivery No.: 091FA Times Cited: 0 Cited Reference Count: 72 Cited References: *IBP NORD, 1971, INT BIOL PROGR, V7 *MIN INC STAT COLL, 1998, MINITAB REL 12 WIND *SPSS INC, 2001, SPSS 11 5 1 AHTI T, 1968, ANN BOT FENN, V5, P169 ANDREASSEN HP, 1998, J ANIM ECOL, V67, P941 ANDREN H, 1988, ECOLOGY, V69, P544 ANDREN H, 1992, ECOLOGY, V73, P794 ANDREN H, 1994, OIKOS, V71, P355 ANDREN H, 1996, OIKOS, V76, P235 ANGELSTAM P, 1987, OIKOS, V50, P123 ARNBORG T, 1990, VEGETATIO, V90, P1 BATZLI GO, 2001, WILDLIFE 2001 POPULA, P831 BENNETT AF, 1994, BIOL CONSERV, V68, P155 BJORNSTAD ON, 1998, RES POPUL ECOL, V40, P77 CHRISTENSEN P, IN PRESS LANDSCAPE E CHRISTENSEN P, 2003, J MAMMAL, V84, P1292 DELATTRE P, 1996, LANDSCAPE ECOL, V11, P279 ECKE F, IN PRESS LANDSCAPE E ECKE F, 2001, ECOLOGICAL B, V49, P165 ECKE F, 2002, J APPL ECOL, V39, P781 ECKE F, 2003, EFFECTS LANDSCAPE PA EKERHOLM P, 2001, ECOGRAPHY, V24, P555 FAHRIG L, 2001, BIOL CONSERV, V100, P65 FEDRIANI JM, 2002, ECOSCIENCE, V9, P12 FORMAN RTT, 1986, LANDSCAPE ECOLOGY HAMBACK PA, 1998, J ANIM ECOL, V67, P544 HANSEN TF, 1999, P NATL ACAD SCI USA, V96, P986 HANSKI I, 1996, J ANIM ECOL, V65, P220 HANSSON L, 1974, FAUNA FLORA, V69, P91 HANSSON L, 1977, LANDSCAPE PLANNING, V4, P85 HANSSON L, 1985, OECOLOGIA, V67, P394 HANSSON L, 1988, TRENDS ECOL EVOL, V3, P195 HANSSON L, 1999, OIKOS, V86, P159 HARGIS CD, 1999, J APPL ECOL, V36, P157 HENEIN K, 1990, LANDSCAPE ECOL, V4, P157 HENTTONEN H, 2000, POLISH J ECOLOGY S, V48, P87 HORNFELDT B, 1978, OECOLOGIA BERL, V32, P141 HORNFELDT B, 1991, THESIS U UMEA SWEDEN HORNFELDT B, 1994, ECOLOGY, V75, P791 HORNFELDT B, 1995, REPORT WORLD WILDLIF, V3, P21 HORNFELDT B, 1998, FAUNA FLORA, V93, P137 HORNFELDT B, 2004, OIKOS, V107, P376 HORNFELDT B, 2005, MILJOOVERVAKNING SMA HUITU O, 2003, OECOLOGIA, V135, P209 IMS RA, 1987, OIKOS, V50, P103 JOHANNESEN E, 1999, ANN ZOOL FENN, V36, P215 KALELA O, 1957, ANN ACAD SCI FENN A4, V34, P1 KANEKO Y, 1998, RES POPUL ECOL, V40, P21 KAREIVA P, 1995, NATURE, V373, P299 LANDE R, 1987, AM NAT, V130, P624 LAPOLLA VN, 1993, LANDSCAPE ECOL, V8, P25 LARSSON TB, 1986, Z ANGEW ZOOL, V73, P435 LIDICKER WZ, 1988, J MAMMAL, V69, P225 LIDICKER WZ, 2000, OIKOS, V91, P435 LUNDMARK JE, 1986, SKOGSMARKENS EKOLOGI MARTINSSON B, 1993, ANN ZOOL FENN, V30, P31 MAZEROLLE MJ, 1999, ECOSCIENCE, V6, P117 MCGARIGAL K, 1995, 351 USDA FOR SERV MOILANEN A, 1998, ECOLOGY, V79, P2503 MONKKONEN M, 1997, ECOGRAPHYS, V20, P634 OKSANEN T, 1996, ECOGRAPHY, V19, P432 OKSANEN T, 1999, OIKOS, V86, P463 ORROCK JL, 2000, ECOL APPL, V10, P1356 OSTLUND L, 1997, CAN J FOREST RES, V27, P1198 PULLIAM HR, 1988, AM NAT, V132, P652 REUNANEN P, 2000, CONSERV BIOL, V14, P218 SIIVONEN L, 1968, NORDEUROPAS DAGGDJUR STENSETH NC, 1999, OIKOS, V87, P427 TKADLEC E, 2001, P ROY SOC LOND B BIO, V268, P1547 VANAPELDOORN RC, 1992, OIKOS, V65, P265 WIENS JA, 1989, FUNCT ECOL, V3, P385 WILCOVE DS, 1985, ECOLOGY, V66, P1212 0921-2973 Landsc. Ecol.ISI:000241010900013mUmea Univ, Dept Ecol & Environm Sci, SE-90187 Umea, Sweden. Swedish Univ Agr Sci, Dept Forest Resource Management & Geomat, SE-90183 Umea, Sweden. Lulea Univ Technol, Div Appl Geol, SE-97187 Lulea, Sweden. Int Inst Appl Syst Anal, A-2361 Laxenburg, Austria. Christensen, P, Umea Univ, Dept Ecol & Environm Sci, SE-90187 Umea, Sweden. pernilla.christensen@emg.umu.seEnglish6<7P(Horskins, K. Mather, P. B. Wilson, J. C.2006?Corridors and connectivity: when use and function do not equate641-655Landscape Ecology2154connectivity; gene flow; habitat use; matrix; Melomys cervinipes; populations; rainforest; Uromys caudimaculatus; wildlife corridor GRADIENT GEL-ELECTROPHORESIS; SOUTH-EASTERN AUSTRALIA; TROPICAL RAIN-FOREST; MITOCHONDRIAL-DNA; SMALL MAMMALS; GENE FLOW; POPULATIONS; CONSERVATION; DIFFERENTIATION; EXTINCTIONArticleJultConnectivity, or the integration of populations into a single demographic unit, is an often desired, but largely untested aspect of wildlife corridors. Using a corridor system that was established at least 85 years prior, we investigated the extent of connectivity provided. This was undertaken using a combined ecological and genetic approach with connectivity estimated by gene flow. Vegetation within the corridor was found to be comparable in physical structure and species composition to that within the connected patches and the two target species (Melomys cervinipes and Uromys caudimaculatus) were shown to occur along the corridor but not within the surrounding matrix. These factors indicated that the corridor was suitable for use as a model system. The population structure (weights of individuals, sex ratios and the percentage of juveniles) of both species were also similar within the corridor and the connected patches suggesting that the corridor provided the resources necessary to sustain breeding populations along its length. Despite this, populations in patches linked by the corridor were found to show the same significant levels of genetic differentiation as those in isolated habitats. M. cervinipes, but not U. caudimaculatus, also showed population differentiation within the continuous habitat. Although based on only one corridor system, these results clearly demonstrate that connectivity between connected populations will not always be achieved by the construction or retention of a corridor and that connectivity cannot be inferred solely from the presence of individuals, or breeding populations, within the corridor.://000240500100002 ISI Document Delivery No.: 083ZE Times Cited: 0 Cited Reference Count: 63 Cited References: *DELT T DEV LTD, 1999, HEM 2 1 *RAINF CONS SOC QU, 1986, TROP RAINF N QUEENSL AARS J, 1998, MOL ECOL, V7, P1383 AMOS W, 1998, PHILOS T ROY SOC B, V353, P177 BAUDRY J, 1988, CONNECTIVITY LANDSCA, P23 BENNETT AF, 1990, LANDSCAPE ECOL, V4, P109 BENNETT AF, 1999, LINKAGES LANDSCAPE R BIERREGAARD RO, 1997, TROPICAL FOREST REMN, P515 BOLEN EG, 1995, WILDLIFE ECOLOGY MAN BOLGER DT, 2001, BIOL CONSERV, V102, P213 BURGMAN MA, 1998, CONSERVATION BIOL AU CAMPBELL NJH, 1995, MOL ECOL, V4, P407 CHAND V, 2005, MOL ECOL NOTES, V5, P352 CROME F, 1994, PACIFIC CONSERVATION, V1, P328 DOWNES SJ, 1997, BIOL CONSERV, V82, P379 DOWNES SJ, 1997, CONSERV BIOL, V11, P718 FRANKHAM R, 1998, NATURE, V392, P441 FRAWLEY KJ, 1983, HIST FOREST LAND MAN FULLER SJ, 1997, MOL ECOL, V6, P145 GOOSEM M, 2001, WILDLIFE RES, V28, P351 GOUDET J, 1996, GENETICS, V144, P1933 HARRINGTON GN, 2001, J TROP ECOL 2, V17, P225 HARRIS LD, 1991, NATURE CONSERVATION, V2, P189 HYLAND BPM, 1999, AUSTR TROPICAL RAIN KOZAKIEWICZ M, 1993, ACTA THERIOL, V38, P1 KREBS CJ, 1989, ECOL METHODOL LEUNG LKP, 1993, PACIFIC CONSERVATION, V1, P58 LIDICKER WZ, 1987, MAMMALIAN DISPERSAL, P144 LINDENMAYER DB, 1994, WILDLIFE RES, V21, P323 LINDENMAYER DB, 2000, GENETICS DEMOGRAPHY, P173 MACMAHON JA, 2001, CONSERVATION BIOL RE, P245 MANSERGH IM, 1989, J WILDLIFE MANAGE, V53, P701 MCCAULEY DE, 1993, BIOTIC INTERACTIONS, P217 MECH SG, 2001, CONSERV BIOL, V15, P467 MERRIAM G, 1984, P 1 INT SEM METH LAN, P5 MERRIAM G, 1991, NATURE CONSERVATION, V2, P133 MERRIAM G, 1995, LANDSCAPE APPROACHES, P64 MEYER A, 1990, NATURE, V347, P550 MORITZ C, 1987, ANNU REV ECOL SYST, V18, P269 NEIGEL JE, 2002, CONSERV GENET, V3, P167 POLLARD JH, 1971, BIOMETRICS, V27, P991 PRIMACK RB, 1993, ESSENTIALS CONSERVAT RAYMOND M, 1995, J HERED, V86, P248 RICE WR, 1989, EVOLUTION, V43, P223 ROSENBAUM V, 1987, BIOPHYS CHEM, V26, P235 ROSENBERG DK, 1998, CAN J ZOOL, V76, P117 SACCHERI I, 1998, NATURE, V392, P491 SIMBERLOFF D, 1992, CONSERV BIOL, V6, P493 SLATKIN M, 1994, ECOLOGICAL GENETICS, P3 SMITH GC, 1984, AUST ZOOL, V21, P551 SOULE ME, 1991, NATURE CONSERVATION, V2, P3 SOULE ME, 1998, SCIENCE, V282, P1658 SOUTHWOOD TRE, 2000, ECOLOGICAL METHODS TAJIMA F, 1989, GENETICS, V123, P585 TRACEY JG, 1975, VEGETATION HUMID TRO VERNES K, 2003, AUSTRAL ECOL, V28, P471 WATTS CHS, 1981, RODENTS AUSTR WEIR BS, 1984, EVOLUTION, V38, P1358 WHITLOCK MC, 1999, HEREDITY 2, V82, P117 WILLIAMS KAW, 1999, NATIVE PLANTS QUEENS WINTER JW, 1991, CONSERVATOIN AUSTR F, P113 WOOD DH, 1971, AUST J ZOOL, V19, P371 WRIGHT S, 1978, EVOLUTION GENETICS P, V4 0921-2973 Landsc. Ecol.ISI:000240500100002Univ Queensland, Sch Nat Resource Sci, Brisbane, Qld 4001, Australia. Horskins, K, Univ Queensland, Sch Nat Resource Sci, R Block,GPO Box 2434,2 George St, Brisbane, Qld 4001, Australia. k.horskins@lycos.comEnglish~?H)Hotchkiss, S. C. Calcote, R. Lynch, E. A.2007qResponse of vegetation and fire to Little Ice Age climate change: regional continuity and landscape heterogeneity25-41Landscape Ecology22Late-Holocene climatic conditions in the upper Great Lakes region have changed sufficiently to produce significant changes in vegetation and fire regimes. The objective of this study was to determine how the vegetation mosaic and fire regimes on an oak (Quercus spp.)- and pine (Pines spp.)-dominated sand plain in northwestern Wisconsin responded to climatic changes of the past 1,200 years. We used pollen and charcoal records from a network of sites to investigate the range of natural variability of vegetation on a 1,500-km(2) landscape on the southern part of the sand plain. A major vegetation shift from jack pine (Pines banksiana) and red pine (P. resinosa) to increased abundance of white pine (P. strobus) occurred between 700 and 600 calendar years before present (cal yr BP), apparently corresponding to more mesic conditions regionally. A decrease in charcoal accumulation rate also occurred at most sites but was not synchronous with the vegetation change. At some sites there were further changes in vegetation and fire regimes occurring similar to 500-300 cal yr BP, but these changes were not as strong or unidirectional as those that occurred 700-600 cal yr BP. Our results suggest that both the composition and the distribution of vegetation of the southern part of the sand plain have been sensitive to relatively small climatic changes, and that the vegetation at the time of European settlement was a transitory phenomenon, rather than a long-term stable condition."://WOS:000251543600003 Times Cited: 0WOS:00025154360000310.1007/s10980-007-9133-3|? ZHouet, T. Loveland, T. R. Hubert-Moy, L. Gaucherel, C. Napton, D. Barnes, C. A. Sayler, K.2010ZExploring subtle land use and land cover changes: a framework for future landscape studies249-266Landscape Ecology252+Land cover and land use changes can have a wide variety of ecological effects, including significant impacts on soils and water quality. In rural areas, even subtle changes in farming practices can affect landscape features and functions, and consequently the environment. Fine-scale analyses have to be performed to better understand the land cover change processes. At the same time, models of land cover change have to be developed in order to anticipate where changes are more likely to occur next. Such predictive information is essential to propose and implement sustainable and efficient environmental policies. Future landscape studies can provide a framework to forecast how land use and land cover changes is likely to react differently to subtle changes. This paper proposes a four step framework to forecast landscape futures at fine scales by coupling scenarios and landscape modelling approaches. This methodology has been tested on two contrasting agricultural landscapes located in the United States and France, to identify possible landscape changes based on forecasting and backcasting agriculture intensification scenarios. Both examples demonstrate that relatively subtle land cover and land use changes can have a large impact on future landscapes. Results highlight how such subtle changes have to be considered in term of quantity, location, and frequency of land use and land cover to appropriately assess environmental impacts on water pollution (France) and soil erosion (US). The results highlight opportunities for improvements in landscape modelling.!://WOS:000274437100007Times Cited: 0 0921-2973WOS:00027443710000710.1007/s10980-009-9362-8|?" (Houet, T. Verburg, P. H. Loveland, T. R.2010+Monitoring and modelling landscape dynamics163-167Landscape Ecology252!://WOS:000274437100001Times Cited: 0 0921-2973WOS:00027443710000110.1007/s10980-009-9417-x<7Houlahan, J. E. Findlay, C. S.2004iEstimating the 'critical' distance at which adjacent land-use degrades wetland water and sediment quality677-690Landscape Ecology196buffer zones; landscape; phosphorous; nitrogen; scale; sediments; wetland management; Ontario; Canada MINNEAPOLIS ST-PAUL; CONSTRUCTED WETLANDS; AGRICULTURAL PHOSPHORUS; NUTRIENT-ENRICHMENT; COMMUNITY STRUCTURE; METROPOLITAN-AREA; BUFFER STRIPS; STREAM; NITROGEN; CHEMISTRYArticleAugConversion of forested lands to agriculture or urban/residential areas has been associated with declines in stream and lake water quality. Less attention has been paid to the effects of adjacent land-uses on wetland sediment and water quality and, perhaps more importantly, the spatial scales at which these effects occur. Here we address these issues by examining variation in water and sediment nutrient levels in 73 southeastern Ontario, Canada, wetlands. We modeled the relationship between water and sediment nutrient concentrations and various measures of adjacent land-use such as forest cover and road density, measured over increasing distances from the wetland edge. We found that water nitrogen and phosphorous levels were negatively correlated with forest cover at 2250 meters from the wetland edge, while sediment phosphorous levels were negatively correlated with wetland size and forest cover at 4000 meters and positively correlated with the proportion of land within 4000 meters that is itself wetland. These results suggest that the effects of adjacent land-use on wetland sediment and water quality can extend over comparatively large distances. As such, effective wetland conservation will not be achieved merely through the creation of narrow buffer zones between wetlands and more intensive land-uses. Rather, sustaining high wetland water quality will require maintaining a heterogeneous regional landscape containing relatively large areas of natural forest and wetlands.://000224100600007 ISI Document Delivery No.: 857FC Times Cited: 9 Cited Reference Count: 73 Cited References: *APHA, 1995, STAND METH EX WAT WA *EC WORK GROUP, 1989, EC LAND CLASS SER, V23 *GOV CAN, 1991, FED POL WETL CONS ALVAREZCOBELAS M, 2001, BIOL CONSERV, V97, P89 BEDFORD BL, 1999, ECOLOGY, V80, P2151 BENDELLYOUNG L, 1997, WATER AIR SOIL POLL, V96, P155 BENOIT M, 1999, REV FROESTIERE FRANC, V50, P162 BERKA C, 2001, WATER AIR SOIL POLL, V127, P389 BORMANN FH, 1979, PATTERN PROCESS FORE BROWN GH, 1972, TECHNOMETRICS, V14, P663 BRUNET RC, 1997, LANDSCAPE ECOL, V12, P171 CARTER MR, 1993, SOIL SAMPLING METHOD CASTELLE AJ, 1994, J ENVIRON QUAL, V23, P878 COMOLEO RE, 1996, LANDSCAPE ECOLOGY, V11, P307 CROSBIE B, 1999, CAN J FISH AQUAT SCI, V56, P1781 CUFFNEY TF, 2000, ENVIRON MONIT ASSESS, V64, P259 CURRIER JB, 1980, ENV IMPACT NONPOINT DETENBECK NE, 1993, LANDSCAPE ECOL, V8, P39 DETENBECK NE, 1996, ENVIRON MONIT ASSESS, V40, P11 DRAPER N, 1981, APPL REGRESSION ANAL EDLAND SD, 1994, ENV STAT ASESSMENT F EHRENFELD JG, 1991, J APPL ECOL, V28, P467 FINDLAY CS, 1997, CONSERV BIOL, V11, P1000 FULTON RJ, 1987, SUMM QUAT OTT REG IN GOPAL B, 1999, WATER SCI TECHNOL, V40, P27 GROWNS JE, 1992, AUST J ECOL, V17, P275 HAVLIN JL, 1998, SOIL FERTILITY FERTI HEFTING MM, 1998, ENVIRON POLLUT S1, V102, P521 HENSEL BR, 1991, J HYDROL, V126, P293 HUBBARD RK, 1994, WATER AIR SOIL POLL, V77, P409 HUNSAKER CT, 1995, BIOSCIENCE, V45, P193 JEPPESEN E, 1999, HYDROBIOLOGIA, V395, P419 JOFRE MB, 1999, ENVIRON TOXICOL CHEM, V18, P1806 JOHNSON LB, 1997, FRESHWATER BIOL, V37, P193 JOHNSTON CA, 1990, BIOGEOCHEMISTRY, V10, P105 JONES KB, 2001, LANDSCAPE ECOL, V16, P301 KEHEW AE, 1998, GROUND WATER, V36, P849 KERR JT, 1995, CONSERV BIOL, V9, P1528 KUUSEMETS V, 1999, WATER SCI TECHNOL, V40, P195 KUUSEMETS V, 2002, LANDSCAPE ECOL S1, V17, P59 LEGENDRE P, 1998, NUMERICAL ECOLOGY LEMLY AD, 2000, WETLANDS, V20, P91 LEWIS WM, 2001, WETLANDS EXPLAINED W MARION GM, 1996, ARCTIC ALPINE RES, V28, P339 MASON CF, 1999, J ENVIRON QUAL, V28, P82 MCFARLAND AMS, 1999, J ENVIRON QUAL, V28, P836 MILLER AJ, 1984, J ROY STAT SOC A GEN, V147, P389 MOORHEAD KK, 1999, WETLANDS, V19, P276 NIJHOFF M, 1983, HDB ENV IMPACTS FERT OWENS DS, 1996, J NATURAL RESOURCES, V25, P128 PATRICK WH, 1994, J ENVIRON QUAL, V23, P892 PATTY L, 1997, PESTIC SCI, V49, P243 PHILLIPS JD, 1989, J HYDROL, V110, P221 POIANI KA, 1996, LANDSCAPE ECOL, V11, P237 PRAIRIE YT, 1995, CAN J FISH AQUAT SCI, V52, P788 PRENTKI NT, 1978, FRESHWATER WETLANDS, P169 PREPAS EE, 2001, CAN J FISH AQUAT SCI, V58, P1286 PUGH AL, 1996, J HYDROL, V182, P83 REDDY KR, 1996, J ENVIRON QUAL, V25, P363 ROUSE JD, 1999, ENVIRON HEALTH PERSP, V107, P799 SCHULTZ RC, 1995, AGROFOREST SYST, V29, P201 SCHWARZ WL, 1996, LANDSCAPE ECOL, V11, P27 SHARPLEY AN, 1994, J ENVIRON QUAL, V23, P437 SPIELES DJ, 2000, WETLANDS, V20, P716 STELZER RS, 2001, LIMNOL OCEANOGR, V46, P356 SVENGSOUK LJ, 2001, AM MIDL NAT, V145, P309 TUFFORD DL, 1998, J ENVIRON QUAL, V27, P100 URI NP, 1999, AGR ENV UUSIKAMPPA J, 2000, J ENVIRON QUAL, V29, P151 WALBRIDGE MR, 1991, WETLANDS, V11, P417 WANG X, 2001, J ENVIRON MANAGE, V61, P25 ZALIDIS GC, 1999, ENVIRON MANAGE, V24, P193 ZHENG GJ, 2002, WATER RES, V36, P1457 0921-2973 Landsc. Ecol.ISI:000224100600007Univ New Brunswick, Dept Biol, St John, NB E2L 4L5, Canada. Univ Ottawa, Inst Environm, Ottawa, ON K1N 6N5, Canada. Houlahan, JE, Univ New Brunswick, Dept Biol, POB 5050, St John, NB E2L 4L5, Canada. jeffhoul@unbsj.caEnglish|?* =Houle, M. Fortin, D. Dussault, C. Courtois, R. Ouellet, J. P.2010]Cumulative effects of forestry on habitat use by gray wolf (Canis lupus) in the boreal forest419-433Landscape Ecology253lForest harvesting involves the creation of roads and cutblocks, both of which can influence animal habitat use. We evaluated the cumulative effects of forestry on habitat selection by six packs of gray wolf (Canis lupus) widely distributed in Quebec's boreal forest. Resource selection functions were used to evaluate cumulative effects at two levels. First, we studied how the response of wolves to roads and cutblocks varied within their home range (HR level) as a function of the local abundance of these habitat features. Second, we assessed whether differences in the response to roads and cutblocks observed among packs (inter-HR level) could be explained by variations in their average abundance among individual home ranges. At the HR level, we found that cumulative effects shaped habitat selection of wolves, and the nature of the effects varied during the year. For example, we detected a decrease in the selection of roads following an increase in local road density during the rendez-vous and the nomadic periods, but not during the denning period. At the inter-HR level, we found a functional response to logging activity only during the denning period. Packs with home ranges characterized by a larger proportion of recent cutblocks selected these cutblocks more strongly. We conclude that cumulative effects of logging activities occur at multiple levels, and these effects can have profound effects on habitat use by wolves, thereby influencing spatial predator-prey dynamics. Wildlife conservation and management in boreal ecosystems should thus account for cumulative impacts of anthropogenic features on animal distribution.!://WOS:000275122600008Times Cited: 0 0921-2973WOS:00027512260000810.1007/s10980-009-9420-2~?uHovel, K. A. Regan, H. M.2008Using an individual-based model to examine the roles of habitat fragmentation and behavior on predator-prey relationships in seagrass landscapes75-89Landscape Ecology23-Seagrasses, which form critical subtidal habitats for marine organisms worldwide, are fragmented via natural processes but are increasingly being fragmented and degraded by boating, fishing, and coastal development. We constructed an individual-based model to test how habitat fragmentation and loss influenced predator-prey interactions and cohort size for a group of settling juvenile blue crabs (Callinectes sapidus Rathbun) in seagrass landscapes. Using results from field studies suggesting that strong top-down processes influence the relationship between cannibalistic blue crab populations and seagrass landscape structure, we constructed a model in which prey (juvenile blue crabs) are eaten by mesopredators (larger blue crabs) which in turn are eaten by top-level predators (e.g., large fishes). In our model, we varied the following parameters within four increasingly fragmented seagrass landscapes to test for their relative effects on cohort size: juvenile blue crab (prey) predator avoidance response, hunting ability of mesopredators and predators, the presence of a top-level predator, and prey settlement routines. Generally, prey cohort size was maximized in the presence of top-level predators and when mesopredators and predators exhibited random searching behavior vs. directed hunting. Cohort size for stationary (tethered) prey was maximized in fragmented landscapes, which corresponds to results from field experiments, whereas mobile prey able to detect and avoid predators had higher survival in continuous landscapes. Prey settlement patterns had relatively small influences on cohort size. We conclude that the effects of seagrass fragmentation and loss on organisms such as blue crabs will depend heavily on behaviors of prey and predatory organisms and how these behaviors change with landscape structure."://WOS:000252922800007 Times Cited: 0WOS:000252922800007(10.1007/s10980-007-9148-9|ISSN 0921-2973ڽ7%Hovick, TorreJ Miller, JamesR2013LBroad-scale heterogeneity influences nest selection by Brown-headed Cowbirds 1493-1503Landscape Ecology288Springer NetherlandsZDemography Grasshopper Sparrow Grasslands Grazing Nest survival Parasitism Prescribed fire 2013/10/01+http://dx.doi.org/10.1007/s10980-013-9896-7 0921-2973Landscape Ecol10.1007/s10980-013-9896-7English<7 *Howell, C. A. Dijak, W. D. Thompson, F. R.2007QLandscape context and selection for forest edge by breeding Brown-headed Cowbirds273-284Landscape Ecology222.brown-headed cowbird; edge effects; forest fragmentation; habitat selection; home range; Illinois; landscape context; Missouri; Molothrus ater; neotropical migrant bird NESTING SUCCESS; HABITAT SELECTION; NEOTROPICAL MIGRANT; MOLOTHRUS-ATER; PARASITISM; ABUNDANCE; DENSITY; BIRDS; MECHANISMS; SONGBIRDSArticleFebRWe evaluated support for four alternate hypotheses explaining the distribution of breeding Brown-headed Cowbirds (Molothrus ater) in forests at varying distances from the forest edge in three Midwestern USA landscapes with varying amounts of forest fragmentation (core forest area ranged from 5 to 70%). We focused on breeding cowbirds' use of forest because of the risk of nest parasitism to forest-dwelling hosts and to identify factors affecting breeding cowbird habitat selection. We compared distances of cowbird locations in the forest from the forest edge ("edge distances") to distances of random forest locations in the entire landscape or within individual cowbird home ranges. We analyzed 1322 locations of 84 cowbirds across three landscapes. We found support for the landscape context hypothesis that breeding cowbird preference for forest edge varied with landscape context. Ninety percent of cowbird locations were within 150-350 m of forest edge, despite the overall availability of forest at greater distances from edge (as far as 500-1450 m) both within cowbird home ranges and the entire forested landscape. Cowbird preference for edge varied by landscape context largely due to differences in the availability of forest edge. In a highly fragmented forest cowbirds utilized the entire forest and likely viewed it as "all edge." In less fragmented forests, cowbirds preferred edge. We consider how variation in cowbird edge preference might relate to patterns in host abundance, host diversity, and host quality because cowbird movements indicate they are capable of using forest farther from edges.://000243823900010 ISI Document Delivery No.: 130UG Times Cited: 0 Cited Reference Count: 44 Cited References: *SAS I, 2000, VERS 8 02 BRITTINGHAM MC, 1983, BIOSCIENCE, V33, P31 BURNHAM KP, 2002, MODEL SELECTION INFE CHASKO GG, 1982, WILDL MONOGR, V82 COKER DR, 1995, J WILDLIFE MANAGE, V59, P631 CURSON DR, 2000, AUK, V117, P795 CURSON DR, 2003, J WILDLIFE MANAGE, V67, P520 DONOVAN TM, 1997, ECOLOGY, V78, P2064 DONOVAN TM, 2000, ECOLOGY MANAGEMENT C, P255 ELLIOTT PF, 1980, CONDOR, V82, P138 EVANS DR, 1997, WILSON BULL, V109, P470 FLASPOHLER DJ, 2001, ECOL APPL, V11, P32 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FRIESEN L, 1999, CONSERV BIOL, V13, P338 GATES JE, 1978, ECOLOGY, V59, P871 GATES JE, 1998, ECOL APPL, V8, P27 GUSTAFSON EJ, 2002, ECOL APPL, V12, P412 HAHN DC, 1995, CONSERV BIOL, V9, P1415 HANOWSKI JM, 1995, ENV CONCERNS RIGHTS, P276 HAUBER ME, 2001, CAN J ZOOL, V79, P1518 HOCHACHKA WM, 1999, STUDIES AVIAN BIOL, V18, P80 HOSOI SA, 2000, ANIM BEHAV 4, V59, P823 HOWELL CA, 2000, LANDSCAPE ECOL, V15, P547 JENSEN WE, 2005, OECOLOGIA, V142, P136 JONES J, 2001, AUK, V118, P557 KING DI, 1996, CONSERV BIOL, V10, P1380 LITELL RCC, 1996, SAS SYSTEM MIXED MOD MANOLIS JC, 2002, AUK, V119, P955 MCGARIGAL K, 2002, FRAGSTATS SPATIAL PA MORRIS DL, 1998, AUK, V115, P376 MORSE SF, 1999, CONSERV BIOL, V13, P327 MURCIA C, 1995, TRENDS ECOL EVOL, V10, P58 ORTEGA CP, 1998, COWBIRDS OTHER BROOD PATON PWC, 1994, CONSERV BIOL, V8, P17 ROBINSON SK, 1992, ECOLOGY CONSERVATION, P408 ROBINSON SK, 1994, BIRD CONSERV INT, V4, P233 ROBINSON SK, 1995, SCIENCE, V267, P1987 ROTHSTEIN SI, 1984, ECOLOGY, V65, P77 STEPHENS SS, 2003, BIOL CONSERV, V111, P101 TEMPLE SA, 1988, CONSERV BIOL, V2, P340 THOMPSON FR, 1994, AUK, V111, P979 THOMPSON FR, 2000, ECOLOGY MANAGEMENT C, P100 THOMPSON FR, 2000, ECOLOGY MANAGEMENT C, P271 WIENS JA, 1993, OIKOS, V66, P369 0921-2973 Landsc. Ecol.ISI:000243823900010Univ Missouri, Dept Biol, St Louis, MO 63121 USA. Univ Missouri, USDA, US Forest Serv, N Cent Forest Expt Stn, Columbia, MO 65211 USA. Howell, CA, PRBO Conservat Sci, 3820 Cypress Dr, Petaluma, CA 94954 USA. chowell@prbo.orgEnglish<7SHowell, C. A. Latta, S. C. Donovan, T. M. Porneluzi, P. A. Parks, G. R. Faaborg, J.2000GLandscape effects mediate breeding bird abundance in midwestern forests547-562Landscape Ecology156#avian abundance avian ecology edge effects fragmentation landscape sensitivity matrix Neotropical migratory birds patch size population trends OVENBIRD SEIURUS-AUROCAPILLUS MIGRATORY BIRDS HABITAT FRAGMENTATION NESTING SUCCESS PAIRING SUCCESS PATTERNS MANAGEMENT VIABILITY SELECTION MISSOURIArticleAugWe examine the influence of both local habitat and landscape variables on avian species abundance at forested study sites situated within fragmented and contiguous landscapes. The study was conducted over a six year period (1991-1996) at 10 study sites equally divided between the heavily forested Missouri Ozarks and forest fragments in central Missouri. We found greater species richness and diversity in the fragments, but there was a higher percentage of Neotropical migrants in the Ozarks. We found significant differences in the mean number of birds detected between the central Missouri fragments and the unfragmented Ozarks for 15 (63%) of 24 focal species. We used stepwise regression to determine which of 12 local vegetation variables and 4 landscape variables (forest cover, core area, edge density, and mean patch size) accounted for the greatest amount of variation in abundance for 24 bird species. Seven species (29%) were most sensitive to local vegetation variables, while 16 species (67%) responded most strongly to one of four landscape variables. Landscape variables are significant predictors of abundance for many bird species; resource managers should consider multiple measures of landscape sensitivity when making bird population management decisions.://000088037200005 ISI Document Delivery No.: 331UN Times Cited: 26 Cited Reference Count: 51 Cited References: *FISH WILDL SERV, 1980, EC SERV MAN, V102 *MONT COOP WILDL R, 1994, BBIRD PROT *SAS I INC, 1990, SAS US GUID STAT VER BLENDEN MD, 1986, WILDLIFE 2000 MODELI, P11 BOLGER DT, 1997, CONSERV BIOL, V11, P406 BRAWN JD, 1996, ECOLOGY, V77, P3 BURKE DM, 1998, AUK, V115, P96 CODY ML, 1985, HABITAT SELECTION BI DONOVAN TM, 1994, THESIS U MISSOURI CO DONOVAN TM, 1995, CONSERV BIOL, V9, P1380 DONOVAN TM, 1995, CONSERV BIOL, V9, P1396 DONOVAN TM, 1997, ECOLOGY, V78, P2064 DONOVAN TM, 1999, ECOLOGY MANAGEMENT C FAABORG J, 1980, T MISSOURI ACAD SCI, V14, P41 FAABORG J, 1995, ECOLOGY MANAGEMENT N, P357 FLATHER CH, 1996, ECOLOGY, V77, P28 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FREEMARK KE, 1995, ECOLOGY MANAGEMENT N, P381 GIBBS JP, 1990, CONSERV BIOL, V4, P193 HAGGERTY TM, 1995, BIRDS N AM HOOVER JP, 1998, WILSON BULL, V110, P375 HUNTER ML, 1990, WILDLIFE FORESTS FOR JACOBS B, 1997, MISSOURI BREEDING BI JAMES FC, 1992, ECOLOGY CONSERVATION, P43 JAMES FC, 1996, ECOLOGY, V77, P13 KABRICK JM, 1997, P MISS OZ FOR EC PRO, P150 KESSLER WB, 1992, ECOL APPL, V2, P221 LIU JG, 1995, CONSERV BIOL, V9, P62 MACARTHUR RH, 1967, THEORY ISLAND BIOGEO MORRISON ML, 1992, WILDLIFE HABITAT REL MURPHY DD, 1986, WILDLIFE 2000 MODELI, P287 NOSS RF, 1983, BIOSCIENCE, V33, P700 PATON PWC, 1994, CONSERV BIOL, V8, P17 PORNELUZI PA, 1999, CONSERV BIOL, V13, P1151 PULLIAM HR, 1988, AM NAT, V132, P652 RENJIFO LM, 1999, CONSERV BIOL, V13, P1124 ROBBINS CS, 1989, WILDLIFE MONOGRA JUL, P1 ROBINSON SK, 1995, SCIENCE, V267, P1987 ROSENTHAL R, 1985, CONTRAST ANAL FOCUSE SAUER JR, 1997, N AM BREEDING BIRD S SOKAL RR, 1981, BIOMETRY STEVENS J, 1992, APPL MULTIVARIATE ST TERBORGH JW, 1989, WHERE HAVE ALL BIRDS THOMAS L, 1996, ECOLOGY, V77, P49 THOMPSON FR, 1994, AUK, V111, P979 VANHORN MA, 1994, BIRDS N AM VANHORN MA, 1995, AUK, V112, P98 VERNER J, 1986, WILDLIFE 2000 MODELI VILLARD MA, 1993, AUK, V110, P759 WENNY DG, 1993, CONDOR, V95, P968 WUNDERLE JM, IN PRESS AUK 0921-2973 Landsc. Ecol.ISI:000088037200005Univ Missouri, Div Biol Sci, Columbia, MO 65211 USA. Howell, CA, Univ Missouri, Div Biol Sci, 110 Tucker Hall, Columbia, MO 65211 USA.English |7eHowell, J. E. Moore, C. T. Conroy, M. J. Hamrick, R. G. Cooper, R. J. Thackston, R. E. Carroll, J. P.2009zConservation of northern bobwhite on private lands in Georgia, USA under uncertainty about landscape-level habitat effects405-418Landscape Ecology243adaptive management colinus virginianus habitat hierarchical models monitoring northern bobwhite uncertainty model abundance optimization populations management state birds fishMar0Large-scale habitat enhancement programs for birds are becoming more widespread, however, most lack monitoring to resolve uncertainties and enhance program impact over time. Georgia's Bobwhite Quail Initiative (BQI) is a competitive, proposal-based system that provides incentives to landowners to establish habitat for northern bobwhites (Colinus virginianus). Using data from monitoring conducted in the program's first years (1999-2001), we developed alternative hierarchical models to predict bobwhite abundance in response to program habitat modifications on local and regional scales. Effects of habitat and habitat management on bobwhite population response varied among geographical scales, but high measurement variability rendered the specific nature of these scaled effects equivocal. Under some models, BQI had positive impact at both local farm scales (1, 9 km(2)), particularly when practice acres were clustered, whereas other credible models indicated that bird response did not depend on spatial arrangement of practices. Thus, uncertainty about landscape-level effects of management presents a challenge to program managers who must decide which proposals to accept. We demonstrate that optimal selection decisions can be made despite this uncertainty and that uncertainty can be reduced over time, with consequent improvement in management efficacy. However, such an adaptive approach to BQI program implementation would require the reestablishment of monitoring of bobwhite abundance, an effort for which funding was discontinued in 2002. For landscape-level conservation programs generally, our approach demonstrates the value in assessing multiple scales of impact of habitat modification programs, and it reveals the utility of addressing management uncertainty through multiple decision models and system monitoring.://000263419500009-408EY Times Cited:0 Cited References Count:39 0921-2973ISI:000263419500009=Moore, CT Univ Georgia, Warnell Sch Forestry & Nat Resources, USGS Patuxent Wildlife Res Ctr, US Geol Survey, 180 E Green St, Athens, GA 30602 USA Univ Georgia, Warnell Sch Forestry & Nat Resources, USGS Patuxent Wildlife Res Ctr, US Geol Survey, Athens, GA 30602 USA Univ Georgia, Warnell Sch Forestry & Nat Resources, Georgia Cooperat Fish & Wildlife Res Unit, Athens, GA 30602 USA Univ Georgia, Warnell Sch Forestry & Nat Resources, USGS Georgia Cooperat Fish & Wildlife Res, Athens, GA 30602 USA Georgia Dept Nat Resources, Wildlife Resources Div, Forsyth, GA 31029 USADoi 10.1007/S10980-008-9320-XEnglish? <Hu, Guang Feeley, Kenneth Wu, Jianguo Xu, Gaofu Yu, Mingjian2011}Determinants of plant species richness and patterns of nestedness in fragmented landscapes: evidence from land-bridge islands 1405-1417Landscape Ecology2610Springer NetherlandsEarth and Environmental ScienceLand-bridge islands formed by dam construction are considered to be “experimental” systems for studying the effects of habitat loss and fragmentation, offering many distinct advantages over terrestrial fragments. The Thousand Island Lake in Southeast China is one such land-bridge system with more than 1000 islands. Based on a field survey of vascular plant richness on 154 land-bridge islands during 2007–2008, we examined the effects of island and landscape attributes on plant species richness and patterns of species nestedness. We also examined the different responses of plant functional groups (classified according to growth form and shade tolerance) to fragmentation. We found that island area explained the greatest amount of variation in plant species richness. Island area and shape index positively affected species diversity and the degree of nestedness exhibited by plant communities while the perimeter to area ratio of the islands had a negative effect. Shade-tolerant plants were the most sensitive species group to habitat fragmentation. Isolation negatively affected the degree of nestedness in herb and shade-intolerant plants including species with various dispersal abilities in the fragmented landscape. Based on these results, we concluded that the effects of habitat loss and fragmentation on overall species richness depended mostly on the degree of habitat loss, but patterns of nestedness were generated from different ecological mechanisms due to species-specific responses to different characteristics of habitat patches.+http://dx.doi.org/10.1007/s10980-011-9662-7 0921-297310.1007/s10980-011-9662-7|?Q0Huang, Qingxu Robinson, Derek T. Parker, Dawn C.2014fQuantifying spatial-temporal change in land-cover and carbon storage among exurban residential parcels275-291Landscape Ecology292FebThe area of land occupied by exurban residential development is significant and has been increasing over the past several decades in the United States. Considerable attention has been drawn to the measurement of regional-scale patterns of land-cover change and assessment of its environmental and socioeconomic consequences. Yet little is known about the quantity of land-cover change within individual exurban residential parcels, which reflect homeowner preferences, land-management strategies, and the ecosystem services they generate. Similarly, little is known about the spatial autocorrelation of land cover among parcels and how it may change over time. Using a dataset delineating land-cover change within exurban residential parcels in southeastern Michigan from 1960 to 2000, the quantity and composition of land cover and carbon storage are examined. The spatial similarity of land-cover quantity among neighboring parcels is evaluated using local indicators of spatial association. Results show, among other findings, that (1) the number of exurban residential parcels, the quantity of tree cover, and amount of carbon storage increased steadily from 1960 to 2000; (2) the distribution of parcel sizes remained relatively constant and dominated by small parcels; (3) an increasing proportion of parcels were significantly similar to their neighbors; and (4) using a benefits transfer approach, new exurban parcels are estimated to store similar to 15,000-29,000 kg Cover the study period. The measured changes in land cover and carbon storage improve our understanding of how ecosystem services may change in human-dominated landscapes and provide evidence that policy opportunities are available to increase carbon management.!://WOS:000331935100008Times Cited: 2 0921-2973WOS:00033193510000810.1007/s10980-013-9963-0 <7Y 5Huang, Y. Wang, L. Wang, D. L. Li, Y. X. Alves, D. G.2012[The effect of plant spatial pattern within a patch on foraging selectivity of grazing sheep911-919Landscape Ecology276diet selection foraging decision plant spatial distribution spatial scale large herbivore diet selection searching behavior roe deer scales cattle heterogeneity mechanisms memory efficiencyJulPlant spatial pattern has been considered as one of the most important factors influencing forage selection of herbivores in natural grasslands. Previous work has emphasized the effects of spatial distribution patterns of food resource at the scale of whole plant communities. Our objective was to explore whether changes in spatial patterns of food within a patchy site affected forage selection of sheep within and among patches. We conducted a manipulative experiment using three native plant species of different palatability and abundance to artificially create three different quality patches in each treatment. We compared the effects of aggregated and randomly dispersed patterns, within high, medium, and low quality patches respectively, on sheep forage selection. Effects of plant spatial patterns within a patch on sheep forage selection of the patch itself strongly depended on the patch quality. For high quality patches, random dispersion of food resources significantly decreased sheep consumption of the palatable plant within the patch. This effect was reversed in low quality patches, and was not significant in medium quality patches. Changes in plant spatial patterns within high quality patches greatly influenced sheep forage selection of other patches. However, changes in plant spatial patterns within medium or low quality patches significantly influenced foraging responses of sheep only for high quality patches. We therefore conclude that high quality resource sites are the most influential and susceptible foraging areas. Our results highlight the importance of high quality resource sites when considering grazing grassland conservation and management.://000305218000010-958DZ Times Cited:0 Cited References Count:34 0921-2973Landscape EcolISI:000305218000010Wang, L NE Normal Univ, Inst Grassland Sci, Changchun 130024, Peoples R China NE Normal Univ, Inst Grassland Sci, Changchun 130024, Peoples R China NE Normal Univ, Inst Grassland Sci, Changchun 130024, Peoples R China Minist Educ, Key Lab Vegetat Ecol, Changchun 130024, Peoples R ChinaDOI 10.1007/s10980-012-9744-1English|?6BHuber, Patrick R. Greco, Steven E. Schumaker, Nathan H. Hobbs, Joe2014tA priori assessment of reintroduction strategies for a native ungulate: using HexSim to guide release site selection689-701Landscape Ecology294Apr6Reintroduction of native species to unoccupied portions of their historical range is a common management strategy to enhance the future viability of animal populations. This approach has met with mixed success, due to unforeseen impacts caused by human or other factors. Some of these impacts could potentially be mitigated through the use of anticipatory modeling coupled with appropriate management strategies prior to release. As part of an ongoing restoration program, we evaluated a portion of the former range of the tule elk (Cervus elaphus nannodes) in the Central Valley of California for potential reintroduction of a free-ranging herd. We used a new spatially explicit population model (HexSim) to analyze four different elk release scenarios. Each scenario corresponded to a different release location, and the model was used to compare simulated elk movement and population dynamics 25 years into the future. We also used HexSim to identify likely locations of human-elk conflict. Population forecasts after the 25-year period were highest (mean female population size of 169.6 per iteration) and potentially harmful barrier interactions were lowest (mean 8.6 per iteration) at the East Bear Creek site. These results indicate the East Bear Creek site release scenario as the most likely to result in a successful elk reintroduction, producing the most elk and generating the fewest human conflicts. We found HexSim to be a useful tool for this type of reintroduction planning and believe that other reintroduction efforts could benefit from this type of anticipatory modeling.!://WOS:000333533800011Times Cited: 0 0921-2973WOS:00033353380001110.1007/s10980-014-0006-2/|?= 'Huber, P. R. Greco, S. E. Thorne, J. H.2010vSpatial scale effects on conservation network design: trade-offs and omissions in regional versus local scale planning683-695Landscape Ecology255Ecological patterns and processes operate at a variety of spatial scales. Those which are regional in nature may not be effectively captured through the combination of conservation plans derived at the local level, where land use planning frequently takes place. Conversely, regional conservation plans may not identify resources important for conservation of intraregional ecological variation. We compare modeled conservation networks derived at regional and local scales from the same area in order to analyze the impact of scale effects on conservation planning. Using the MARXAN reserve selection algorithm and least cost corridor analysis we identified a potential regional conservation network for the Central Valley ecoregion of California, USA, from which we extracted those portions found within five individual counties. We then conducted the same analysis for each of the five counties. An overlay of the results from the two scales shows a general pattern of large differences in the identified networks. Especially noteworthy are the trade-offs and omissions evident at both scales of analysis and the disparateness of the identified corridors that connect core reserves. The results suggest that planning efforts limited to one scale will neglect biodiversity patterns and ecological processes that are important at other scales. An intersection of results from the two scales can potentially be used to prioritize areas for conservation found to be important at several spatial scales.!://WOS:000276609800003Times Cited: 0 0921-2973WOS:00027660980000310.1007/s10980-010-9447-4(?Z Huebner, Cynthia2012MInvasion ecology: still in the ‘establishment stage’ 50 years after Elton613-615Landscape Ecology274Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-011-9688-x 0921-297310.1007/s10980-011-9688-x<7<Huettmann, F. Diamond, A. W.2006ULarge-scale effects on the spatial distribution of seabirds in the Northwest Atlantic 1089-1108Landscape Ecology217$across-scale analysis; autocorrelation; binning; GIS; large-scale; Northwest Atlantic; PIROP seabird monitoring long-term database; seascape; seasonal seabird patches MARINE BIRDS; HABITAT SELECTION; LANDSCAPE ECOLOGY; SCHOOLING FISH; BERING SEA; ABUNDANCE; DYNAMICS; PATTERNS; INSECTS; MODELArticleOctUScale questions are particularly important for organisms which range over large areas, as pelagic seabirds do. The investigations of scale are of practical importance for describing patch size of predator and prey, determining the appropriate scale of study and correcting survey transects. We conducted this study in order to explore a substantially wider diversity of spatial scales than has previously been attempted in the pelagic bird literature. As an example of large monitoring datasets dealing with seabirds, we use the PIROP (Programme integre pour le recherche des oiseaux pelagiques) data set to investigate relevant large scale issues for these species in the Northwestern Atlantic. We analyzed autocorrelation within selected winter and summer transects, and for 1 degree analysis units ('bins') for data collected June-August 1966-1992. We also investigated effects of the analysis unit on counting results and on the links between seabirds and their environment (depth, sea surface salinity and temperature). We selected scales of 1, 2, 5 and 10 degrees analysis units; an ecological mapping scale ('Banks' not deeper than 200 m) and a political scale (management convention zones of the North Atlantic Fisheries Organization, NAFO) were also included. Using 'binning' of various scales, our results show that the Coefficient of Variation for seabird abundances varies among aggregation scales, and that seabird associations with their environment can show scale effects. Autocorrelation of analysis units indicated some distinct larger scale patch sizes for particular species during the breeding season.://000241010900010 ISI Document Delivery No.: 091FA Times Cited: 0 Cited Reference Count: 82 Cited References: *INTERA TYDAC, 1992, SPANS MAP US GUID *INTERA TYDAC, 1993, SPANS GIS REF MAN *INTERA TYDAC, 1995, INT SPANS WORKSH TEC *MATHS INC, 1995, S PLUS US MAN *MATHS INC, 1996, S PLUS GUID STAT MAT *MATHS INC, 1996, S PLUS SPAT STAT US *NAT OC ATM ADM, 1996, 5 MIN GRIDD EARTH TO *NAT OC ATM ADM, 1997, LIV ACC CLIM DAT ANGEL MV, 1993, LARGE SCALE ECOLOGY BAILEY RG, 1984, EASTSIDE FOREST ECOS, P95 BOURGERON PS, 1984, EASTSIDE FOREST ECOS, P45 BOWERS MA, 1999, LANDSCAPE ECOL, V14, P381 BRIGGS KT, 1987, STUD AVIAN BIOL, V11, P1 BROWN RGB, 1971, PIROP INSTRUCTION MA BROWN RGB, 1975, ATLAS E CANADIAN SEA BROWN RGB, 1986, REVISED ATLAS E CANA BUCKLAND ST, 1993, DISTANCE SAMPLING ES BUCKLAND ST, 2001, INTRO DISTANCE SAMPL CAMPHUYSEN CJ, 1995, BIOECO9310 EC DG 14 CSILLAG F, 2000, B ECOL SOC AM, V81, P230 CUSHMAN SA, 2002, LANDSCAPE ECOL, V17, P637 DIAMOND AW, 1986, 164 CAN WILDL SERV DIAMOND AW, 1993, STUDIES HIGH LATITUD, V3 EDWARDS PJ, 1993, LARGE SCALE ECOLOGY ELPHICK CS, 1993, CONDOR, V95, P33 GARTHE S, 1996, COLON WATERBIRD, V19, P232 GASTON AJ, 2004, SEABIRDS NATURAL HIS GOODCHILD MF, 1987, SPATIAL AUTOCORRELAT GREGORY RD, 1998, ECOGRAPHY, V21, P527 HASTIE TJ, 1990, MONOGRAPHS STAT APPL, V43 HAY GJ, 2001, LANDSCAPE ECOL, V16, P471 HOLLING CS, 1992, ECOL MONOGR, V62, P447 HUETTMANN F, 1997, ICES JMAR SCI, V54, P518 HUETTMANN F, 2000, THESIS U NEW BRUNSWI HUETTMANN F, 2001, ECOL MODEL, V141, P261 HUETTMANN F, 2001, J APPL STAT, V28, P843 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 JESPERSEN P, 1924, NATURE, V114, P281 JORGENSEN EE, 1999, J MAMMAL, V80, P421 KALUZNY SP, 1996, SPLUS SPATIALSTATS U KLOPATEK JM, 1999, LANDSCAPE ECOLOGICAL KRAWCHUK MA, 2003, OIKOS, V103, P153 LEGENDRE P, 1993, ECOLOGY, V74, P1659 LEVITUS S, 1994, WORLD OCEAN ATLAS 19 LOCK AR, 1994, GAZETTEER MARINE BIR MANLY BJ, 2002, RESOURCE SELECTION A MAY RM, 1993, LARGE SCALE ECOLOGY, P123 MEISEL JE, 1998, LANDSCAPE ECOL, V13, P347 MEYER CB, 2002, LANDSCAPE ECOL, V17, P95 MUELLERDOMBOIS D, 1974, AIMS METHODS VEGETAT, P574 NAUGLE DE, 1999, LANDSCAPE ECOL, V14, P267 NEWTON I, 1997, ECOGRAPHY, V20, P137 OSTRAND WD, 1998, CONDOR, V100, P709 PRIBIL S, 1997, CAN J ZOOL, V75, P1835 QUINN GP, 2002, EXPT DESIGN DATA ANA ROSHIER DA, 2001, LANDSCAPE ECOL, V16, P546 SAUNDERS SC, 1998, LANDSCAPE ECOL, V13, P381 SCHAEFER JA, 2000, LANDSCAPE ECOL, V15, P731 SCHNEEWEISS CA, 1992, PRODUCTION OPERATION, V1, P22 SCHNEIDER BH, 1990, AM BIOTECHNOL LAB, V8, P17 SCHNEIDER D, 1990, THOMAS WOLFE REV, V14, P23 SCHNEIDER DC, 1985, MAR ECOL-PROG SER, V25, P211 SCHNEIDER DC, 1986, MAR ECOL-PROG SER, V32, P237 SCHNEIDER DC, 1989, J FISH BIOL, V35, P109 SCHNEIDER DC, 1990, POLAR RES, V8, P89 SCHNEIDER DC, 1993, BIOL REV, V68, P579 SCHNEIDER DC, 1997, IBIS, V139, P175 SCHOOLEY RL, 2001, LANDSCAPE ECOL, V16, P267 SIEGEL C, 1995, MASTERING FOXPRO 2 6 SKOV HS, 1995, J BIOGEOGR, V22, P71 STENHOUSE IJ, 1996, SULA, V10, P219 TASKER ML, 1984, AUK, V101, P567 THOMPSON CM, 2002, AUK, V119, P8 THOMPSON CM, 2002, LANDSCAPE ECOL, V17, P568 TURNER MG, 2001, LANDSCAPE ECOLOGY TH VENABLES WN, 1994, MODERN APPL STAT S P VENABLES WN, 2002, MODERN APPL STAT S P WELLNITZ TA, 2001, LANDSCAPE ECOL, V16, P111 WHITERS MA, 1999, LANDSCAPE ECOLOGICAL, P205 WIENS JA, 1989, LANDSCAPE ECOLOGY, V3, P87 WU JG, 2002, LANDSCAPE ECOL, V17, P355 YEN PPW, 2004, ECOL MODEL, V171, P395 0921-2973 Landsc. Ecol.ISI:000241010900010vUniv New Brunswick, Atlantic Cooperat Wildlife Ecol Res Network, Fredericton, NB E3B 6C2, Canada. Univ New Brunswick, Fac Forestry & Environm Management, Fredericton, NB E3B 6C2, Canada. Univ New Brunswick, ACWERN, Fredericton, NB E3B 6E1, Canada. Huettmann, F, Univ Alaska Fairbanks, EWHALE Lab, Dept Biol & Wildlife, Inst Arctic Biol, Fairbanks, AK 99775 USA. fffh@uaf.eduEnglish 07 -Hulse, D. Branscomb, A. Enright, C. Bolte, J.2009XAnticipating floodplain trajectories: a comparison of two alternative futures approaches 1067-1090Landscape Ecology248SpringerNUniv Oregon, Eugene O. R. U. S. A. Oregon State Univ, Corvallis O. R. U. S. A.LAlternative future scenarios Variant/invariant analysis Agent-based modelingOctScenario-based investigations explore alternative future courses of action in a widening array of situations. Anticipating landscape patterns and the values behind them are recurring needs in such investigations. While it is accepted that how scenario assumptions are framed and who frames them matters, the sensitivity of resulting trajectories to contrasting scenario framing and modeling processes is rarely tested. Using comparable scenarios we contrast landscape change trajectories produced from two distinct approaches to modeling scenario assumptions: the first uses lay citizen groups and deterministic land allocation modeling, the second uses experts from biophysical and social sciences and agent-based modeling. Scenarios are defined and mapped for the year 2050 in western Oregon's Willamette River Basin along a gradient of conservation oriented to development-oriented assumptions using first citizen-based and then expert-based approaches. The landscape variability and trajectories for the citizen-based Conservation 2050 and Development 2050 scenarios are then characterized and compared with those of the expert-based Conservation 2050 and Development 2050 scenarios. Results distinguish areas where trajectories always vary regardless of approach or scenario from those that never vary. Policy influence on trajectory is illustrated using agent-based model results where land conversion serves purposes of wealth production and ecosystem function. Results depict areas with strong coupling between policy and trajectory as those places experiencing the same pattern of change over time regardless of scenario. Results also indicate that the greater the variability of a given scenario's trajectories, the more successful the scenario is at avoiding scarcity of wealth and ecosystem function.://000269913600007ISI Document Delivery No.: 495RV Times Cited: 2 Cited Reference Count: 70 Hulse, David Branscomb, Allan Enright, Chris Bolte, John 0921-2973 DORDRECHT2009 Landsc. Ecol.ISI:000269913600007Landscape ecology?Hulse, D, Univ Oregon, Eugene, OR 97403 USA. dhulse@uoregon.edu10.1007/s10980-008-9255-2English?THulshoff, R. Maureen1995.Landscape indices describing a Dutch Landscape101-111Landscape Ecology102pattern indices, land use development, quantification of changes in landscape pattern, dominace index, shape index, rate of change K|7a Hulshoff, R. M.1995.Landscape Indexes Describing a Dutch Landscape101-111Landscape Ecology102~pattern indexes land use development quantification of changes in landscape pattern dominance index shape index rate of changeAprWThe data set of a human modified Dutch landscape was used to evaluate whether landscape pattern indices developed in the United States are fit to describe a Dutch landscape. The grid based data set contains the development of land use over the period 1845-1982. The indices were divided in two groups: pattern indices and change indices. In the first group the proportion of each land use type (P), patch number (N), mean patch size (A) and two indices of patch shape (S1 and S2) were tested; in the second group the rate of change (C) was tested. Not all indices considered in this case study are suitable for the Dutch landscape. The dominance index (D) seems not to be sensitive enough to respond in a clear way to changes in the landscape studied. Shape index seems to be a complicated index, particularly in a human modified landscape like the Dutch, where the shape of natural patches is fixed by their man-made neighbours. The trends observed in the two shape indices considered in this study are not satisfactory since each index considers another aspects of shape (either the inferior-to-edge ratio or the complexity of the patch perimeter). None of the indices appears to give information on changes in the geographical position of the patches, which implies that nothing can be induced with respect to the real landscape dynamics. The indices have to be considered in combination to produce meaningful information. The combination of proportion of each land use (P) and the data of the transitions shows how the development in land use has been. Number of patches (N) together with the mean size of patches (A) gives a good indication of the pattern development. Further research is necessary to develop a useful method how to quantify the change in landscape pattern and to give an ecological meaning to the index value in relation to the process of changing pattern.://A1995QX34400004-Qx344 Times Cited:50 Cited References Count:0 0921-2973ISI:A1995QX34400004oHulshoff, Rm Univ Amsterdam,Landscape & Environm Res Grp,Nieuwe Prinsengracht 130,1018 Vz Amsterdam,NetherlandsEnglish6|7r WHunsaker, C. T. Oneill, R. V. Jackson, B. L. Timmins, S. P. Levine, D. A. Norton, D. J.1994*Sampling to Characterize Landscape Pattern207-226Landscape Ecology93SepCurrent reseach suggests that metrics of landscape pattern may reflect ecological processes operating at different scales and may provide an appropriate indicator for monitoring regional ecological changes. This paper examines the extent to which a 1/16 areal subset of the landscape using equally spaced 40-km2 hexagons can characterize the spatial extent of land cover types and landscape pattern (number of types of edges, patch shape complexity, dominance, and contagion). For 200-m resolution data the hexagon subset gives a reasonable estimate of overall landscape cover but may not be adequate for monitoring uncommon land cover types such as wetlands. For agriculture and forest, their proportion of the full landscape units is only outside the 95% confidence interval of the hexagon estimate 4-8% of the time, whereas the proportions for wetland and barren areas are outside the confidence interval 11-34% of the time. The hexagon subset a so does not appear to be adequate as the sole basis for monitoring landscape pattern. The values for contagion, dominance, and shape complexity calculated on the full landscape units are outside the 95% confidence interval of the hexagon estimate 27-76% of the time. Other statistical analyses include regressions between full landscape and hexagon subsets, mean differences and standard errors along with tests on number of positive and negative values, and percent relative error of hexagon estimates.://A1994PL16600004-Pl166 Times Cited:48 Cited References Count:0 0921-2973ISI:A1994PL16600004CHunsaker, Ct Oak Ridge Natl Lab,Div Environm Sci,Oak Ridge,Tn 37831EnglishI<7_Hunziker, M. Kienast, F.1999Potential impacts of changing agricultural activities on scenic beauty - a prototypical technique for automated rapid assessment161-176Landscape Ecology142landscape agriculture land abandonment reforestation aesthetics landscape preference social science image experiments pattern analysis GIS HABITAT CONNECTIVITY LANDSCAPE PATTERN NATIONAL-PARK MODEL INDEXES BIODIVERSITY PREFERENCE PERCEPTION SIMULATION AESTHETICSArticleAprAs a result of the liberalisation of the agricultural market, mountain regions in Central Europe are at great risk of experiencing increasing land abandonment and spontaneous reforestation. Prior to taking measures for landscape maintenance, the ecological and landscape-aesthetic consequences of land abandonment should be analysed. This paper addresses the aesthetic component of such analyses: we investigated whether lay people perceive land abandonment and spontaneous reforestation as a loss or a gain and developed a prototypical technique for rapid aesthetic assessment of reforestation scenarios for vast regions. First, we conducted image experiments to assess the respondents' reactions to increasing levels of reforestation. Based on these experiments we concluded that a medium degree of reforestation is most desirable. Second, we analysed the relationship between scenic beauty and landscape patterns and found that landscape preference values correlate significantly with various quantitative measures of the landscape pattern (e,g., diversity and contagion indices of grey-tone and colour images). Third, we applied a GIS-assisted 'moving-window' technique to transform spatially explicit remote-sensing data (in particular orthophotos) of a test region to spatially explicit data of landscape-pattern indices. Thanks to the significant positive correlation between pattern indices and landscape preference values, the resulting maps can preliminarily be interpreted as 'beauty'-maps of the test-region.://000079802500006 1 ISI Document Delivery No.: 187RV Times Cited: 15 Cited Reference Count: 60 Cited References: ANWANDER S, 1990, DIREKTZAHLUNGEN BERG BAKER BD, 1996, ECOL MODEL, V89, P147 BISHOP ID, 1989, LANDSCAPE J, V8, P92 BISHOP ID, 1994, LANDSCAPE URBAN PLAN, V30, P59 BOURASSA SC, 1991, AESTHETICS LANDSCAPE BROWN T, 1994, LANDSCAPE URBAN PLAN, V30, P49 BUREL F, 1995, AGR ECOSYST ENVIRON, V55, P193 DALE VH, 1994, CONSERV BIOL, V8, P1027 DANIEL TC, 1976, RM167 US FOR SERV FLAMM RO, 1994, LANDSCAPE ECOL, V9, P37 FRIEDRICHS J, 1985, METHODEN EMPIRISCHER GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 HADRIAN DR, 1988, LANDSCAPE URBAN PLAN, V16, P261 HAIDER W, 1994, FOREST CHRON, V70, P402 HOISL R, 1987, MAT FLURBEREINIGUNG, V11 HOLLENHORST SJ, 1993, FOREST SCI, V39, P28 HULSHOFF RM, 1995, LANDSCAPE ECOL, V10, P101 HUNZIKER M, 1992, GEOGR, P143 HUNZIKER M, 1995, LANDSCAPE URBAN PLAN, V31, P399 JARVIS D, 1990, LANDSC DESIGN NOV, P35 KANGAS J, 1993, SCAND J FOR RES, V8, P408 KAPLAN R, 1989, ENVIRON BEHAV, V21, P509 KAPLAN S, 1972, PERCEPT PSYCHOPHYS, V12, P354 KAPLAN S, 1979, P OUR NAT LANDSC C A LAMB RJ, 1990, LANDSCAPE URBAN PLAN, V19, P333 LI HB, 1993, LANDSCAPE ECOL, V8, P155 LIU JG, 1993, ECOL MODEL, V70, P63 MCGARIGAL K, 1994, FRAGSTATS SPATIAL PA NAIMAN RJ, 1993, ECOL APPL, V3, P209 NASSAUER JI, 1989, J SOIL WATER CONSERV, V44, P384 NASSAUER JI, 1992, LANDSCAPE ECOL, V6, P239 NOHL W, 1974, LANDSCHAFT PLUS STAD, P171 NOHL W, 1982, LANDSCHAFT PLUS STAD, V14, P49 NOHL W, 1988, NAT LANDSCH, V63, P106 OH K, 1994, LANDSCAPE URBAN PLAN, V28, P201 ONEILL RV, 1992, LANDSCAPE ECOL, V7, P55 OSGOOD CE, 1952, PSYCHOL B, V49 PECCOL E, 1996, J ENVIRON MANAGE, V47, P355 PINTOCORREIA T, IN PRESS FUTURE RURA PLOTNICK RE, 1993, LANDSCAPE ECOL, V8, P201 PURCELL AT, 1987, ENVIRON PLANN B, V14, P67 QI Y, 1996, LANDSCAPE ECOL, V11, P39 RABA A, 1997, THESIS U FREIBURG B RIBE RG, 1994, J ENVIRON MANAGE, V42, P199 RUZICKA M, 1993, EKOL BRATISLAVA, V12, P325 SCHIPPERS P, 1996, ECOGRAPHY, V19, P97 SCHROEDER HW, 1984, ENVIRON BEHAV, V16, P573 SCHROEDER HW, 1986, J ENVIRON MANAGE, V23, P325 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SHAFER EL, 1969, J LEISURE RES, V1, P1 SIMPSON EH, 1949, NATURE, V163, P688 STAMPS AE, 1997, EDRA, V28, P114 STEINITZ C, 1990, LANDSCAPE URBAN PLAN, V19, P213 TURNER MG, 1990, PHOTOGRAMM ENG REM S, V56, P379 TURNER MG, 1993, ECOL MODEL, V69, P163 TURNER MG, 1994, J VEG SCI, V5, P731 TURNER MG, 1994, NAT AREA J, V14, P3 ZUBE EH, 1973, LANDSCAPE ARCHIT, P370 ZUBE EH, 1974, U MASSACHUSETTS PU R, V741 0921-2973 Landsc. Ecol.ISI:000079802500006Swiss Fed Inst Forest Snow & Landscape Res, Dept Landscape Ecol, CH-8903 Birmensdorf, Switzerland. Hunziker, M, Swiss Fed Inst Forest Snow & Landscape Res, Dept Landscape Ecol, CH-8903 Birmensdorf, Switzerland.EnglishZ<7 =Hurme, E. Kurttila, M. Monkkonen, M. Heinonen, T. Pukkala, T.2007xMaintenance of flying squirrel habitat and timber harvest: a site-specific spatial model in forest planning calculations243-256Landscape Ecology222Finland; spatial forest planning; spatial objectives; stand neighborhood structure; suitable habitat PTEROMYS-VOLANS; WILDLIFE; EXTINCTION; OPTIMIZATION; CONSERVATION; BIODIVERSITY; CONSTRAINTS; LANDSCAPES; MOVEMENTS; OREGONArticleFebSpatial and temporal continuity of resources often benefits both ecological and economic goals in landscape management. Consideration of multiple and conflicting goals is also needed to view the future production possibilities of forests in successful forest management. Our aim was to estimate the production potential of a planning area in Finland by examining different forest management strategies from ecological and economic perspectives using long-term forest planning calculations. Economic objectives referred to timber production, whereas ecological objectives were based on suitable habitats for arboreal Siberian flying squirrel (Pteromys volans). Suitable habitats were defined using an empirical site-specific model, which includes a spatial variable reflecting the availability of habitat within an individual's activity area. Five alternative forest plans were worked out with different objectives for flying squirrel habitat and timber production. The alternative plans were compared with respect to values of objective variables at the end of the planning period of 60 years and against a production possibility frontier among net present value and flying squirrel habitat. Varying objective values in our analyses resulted from different utilization of production possibilities, and the changes were in line with the objectives used. The formation of flying squirrel habitat clusters in the landscape was enhanced, and it did not always incur severe reductions in harvestable timber volume. Possibilities to combine ecological and economic goals, both spatial and aspatial, in the planning process seems to be an encouraging alternative for the long-term forest management in the future.://000243823900008 ISI Document Delivery No.: 130UG Times Cited: 0 Cited Reference Count: 43 Cited References: 1994, METSANHOITOSUOSITUKS ARTHAUD GJ, 1996, CAN J FOREST RES, V26, P2191 BAILEY TC, 1995, INTERACTIVE SPATIAL BETTINGER P, 1999, ENVIRON MODEL ASSESS, V4, P143 BORGES JG, 1999, CAN J FOREST RES, V29, P1764 BOSTON K, 2001, FOREST ECOL MANAG, V145, P191 CALKIN DE, 2002, CAN J FOREST RES, V32, P1329 CARLSSON M, 1999, CAN J FOREST RES, V29, P1183 DOWSLAND KA, 1993, MODERN HEURISTIC TEC, P20 FORMAN RTT, 1986, LANDSCAPE ECOLOGY HAIGHT RG, 1995, ECOL APPL, V5, P767 HANSKI IK, 2000, J MAMMAL, V81, P798 HARRISON S, 1995, IALE STUDIES LANDSCA, V2, P293 HARRISON S, 1999, ECOGRAPHY, V22, P225 HEINONEN T, 2004, SILVA FENN, V38, P319 HOF J, 1994, FOREST SCI, V40, P177 HOF J, 1997, ECOL APPL, V7, P1160 HURME E, 2005, FOREST ECOL MANAG, V216, P241 JUUTINEN A, 2004, FOREST SCI, V50, P527 KANGAS J, 1996, CAN J FOREST RES, V26, P103 KARVONEN L, 2000, GUIDELINES LANDSCAPE KIRKPATRICK S, 1983, SCIENCE, V220, P4598 KURTTILA M, 2001, FOREST ECOL MANAG, V142, P127 KURTTILA M, 2002, FOREST ECOL MANAG, V166, P245 LANDE R, 1993, AM NAT, V142, P911 LICHTENSTEIN ME, 2003, LAND ECON, V79, P56 MASCOLELL A, 1995, MICROECONOMIC THEORY MICHALEWICZ Z, 2004, SOLVE IT MODERN HEUR MONKKONEN M, 1997, ECOGRAPHYS, V20, P634 MURADIAN R, 2001, ECOL ECON, V38, P7 MYKRA S, 1998, SILVA FENNICA, V32, P389 NALLE DJ, 2004, J ENVIRON ECON MANAG, V48, P997 OHMAN K, 2000, CAN J FOREST RES, V30, P1817 OHMAN K, 2003, FOREST ECOL MANAG, V176, P161 POLASKY S, 2005, ECOL APPL, V15, P1387 PUKKALA T, 1993, SCAND J FOR RES, V8, P560 PUKKALA T, 2004, UNPUB MONSU METSASUU RASSI P, 2001, SUOMEN LAJIEN UHANAL REUNANEN P, 2000, CONSERV BIOL, V14, P218 SCHUMAKER NH, 2004, ECOL APPL, V14, P381 SELONEN V, 2003, ECOGRAPHY, V26, P641 SESSIONS J, 1992, FOREST SCI, V38, P203 TILMAN D, 1994, NATURE, V371, P65 0921-2973 Landsc. Ecol.ISI:000243823900008GUniv Oulu, Dept Biol, FIN-90014 Oulu, Finland. Finnish Forest Res Inst, Joensuu Res Unit, FIN-01301 Joensuu, Finland. Univ Jyvaskyla, Dept Biol & Evnironm Sci, FIN-40014 Jyvaskyla, Finland. Univ Joensuu, Fac Forestry, FIN-80101 Joensuu, Finland. Hurme, E, Univ Oulu, Dept Biol, 3000, FIN-90014 Oulu, Finland. Eija.Hurme@oulu.fiEnglish6|? Hutchinson, Todd2011lCanaries in the catbird seat: The past, present and future of biological resources in a changing environment 1051-1052Landscape Ecology267Aug!://WOS:000292705900013Times Cited: 0 0921-2973WOS:00029270590001310.1007/s10980-011-9604-4n۽7 Hutchinson, Todd2013J. E. Keeley, W. J. Bond, R. A. Bradstock, J. G. Pausas, P. W. Rundel: Fire in Mediterranean ecosystems. Ecology, evolution and management571-572Landscape Ecology283Springer Netherlands 2013/03/01+http://dx.doi.org/10.1007/s10980-013-9850-8 0921-2973Landscape Ecol10.1007/s10980-013-9850-8Englishz|?A ;Hwang, Taehee Song, Conghe Vose, James M. Band, Lawrence E.2011`Topography-mediated controls on local vegetation phenology estimated from MODIS vegetation index541-556Landscape Ecology264Apr$Forest canopy phenology is an important constraint on annual water and carbon budgets, and responds to regional interannual climate variation. In steep terrain, there are complex spatial variations in phenology due to topographic influences on microclimate, community composition, and available soil moisture. In this study, we investigate spatial patterns of phenology in humid temperate forest as a function of topography. Moderate-resolution imaging spectro-radiometer (MODIS) vegetation indices are used to derive local patterns of topography-mediated vegetation phenology using a simple post-processing analysis and a non-linear model fitting. Elevation has the most explanatory power for all phenological variables with a strong linear relationship with mid-day of greenup period, following temperatures lapse rates. However, all other phenological variables show quadratic associations with elevation, reflecting an interaction between topoclimatic patterns of temperature and water availability. Radiation proxies also have significant explanatory power for all phenological variables. Though hillslope position cannot be adequately resolved at the MODIS spatial resolution (250 m) to discern impacts of local drainage conditions, extended periods of greenup/senescence are found to occur in wet years. These findings are strongly supported by previous field measurements at different topographic positions within the study area. The capability of detecting topography-mediated local phenology offers the potential to detect vegetation responses to climate change in mountainous terrain. In addition, the large, local variability of meteorological and edaphic conditions in steep terrain provides a unique opportunity to develop an understanding of canopy response to the interaction of climate and landscape conditions.!://WOS:000288807300008Times Cited: 1 0921-2973WOS:00028880730000810.1007/s10980-011-9580-8Pڽ7 ^Ikin, Karen Beaty, R. Matthew Lindenmayer, DavidB Knight, Emma Fischer, Joern Manning, AdrianD2013WPocket parks in a compact city: how do birds respond to increasing residential density?45-56Landscape Ecology281Springer NetherlandsBird diversity Object based image analysis Landscape composition Landscape configuration Planning and management Southeast Australia Spatial analysis Urban form Urban greenspace Urban sustainability 2013/01/01+http://dx.doi.org/10.1007/s10980-012-9811-7 0921-2973Landscape Ecol10.1007/s10980-012-9811-7English|?) +Imelda, Somodi Klara, Viragh Istvan, Miklos2011_A Bayesian MCMC approach to reconstruct spatial vegetation dynamics from sparse vegetation maps805-822Landscape Ecology266JulqIn studies of vegetation dynamics, data points describing the changes are often sparse, because changes were not recognized in early stages or investigations were part of different projects. The snapshots at hand often leave the nature of the dynamics unrevealed and only give a rough estimation of the directions of changes. Extrapolation of the dynamics with traditional cellular automaton modeling is also complicated in such cases, because rules often cannot be deduced from field data for each interaction. We developed a Bayesian MCMC method, using a discrete time stochastic cellular automaton model to reconstruct vegetation dynamics between vegetation maps available and provide estimation of vegetation pattern in years not surveyed. Spread capability of each vegetation type was characterized by a lateral spread parameter and another for establishment from species pool. The method was applied to a series of three vegetation maps depicting vegetation change at a grassland site following abandonment of grazing in north-eastern Hungary. The Markov chain explored the missing data space (missing maps) as well as the parameter space. Transitions by lateral expansion had a greater importance than the appearance of new vegetation types without spatial constraints at our site. We estimated the trajectory of change for each vegetation type, which bore a considerable non-linear element in most cases. To our best knowledge, this is the first work that tries to estimate vegetation transition parameters in a stochastic cellular automaton based on field measurements and provides a tool to reconstruct past dynamics from observed pattern.!://WOS:000291485400004Times Cited: 0 0921-2973WOS:00029148540000410.1007/s10980-011-9610-65|?(6Inclan, Diego J. Cerretti, Pierfilippo Marini, Lorenzo2014uInteractive effects of area and connectivity on the diversity of tachinid parasitoids in highly fragmented landscapes879-889Landscape Ecology295MayAlthough many empirical and theoretical studies have elucidated the effects of habitat fragmentation on the third trophic level, little attention has been paid to the impacts of this driver on more generalist groups of non-hymenopteran parasitoids. Here, we used the highly-diverse group of tachinid flies as an alternative model to test the effects of landscape fragmentation on insect parasitoids. Our aims were: (i) to evaluate the relative importance of habitat area and connectivity losses and their potential interaction on tachinid diversity, (ii) to test whether the effects of habitat fragmentation changes seasonally, and (iii) to further assess the effect of habitat diversity on tachinid diversity and whether different parasitoid-host associations modify the species richness response to fragmentation. In 2012 a pan-trap sampling was conducted in 18 semi-natural grasslands embedded in intensive agricultural landscapes along statistically orthogonal gradients of habitat area, connectivity and habitat diversity. We found an interaction between habitat area and connectivity indicating that tachinid abundance and species richness were more negatively affected by habitat loss in landscapes with low rather than with relatively large habitat connectivity. Although tachinid communities exhibited large within-year species turnover, we found that the effects of landscape fragmentation did not change seasonally. We found that habitat diversity and host association did not affect tachinid species diversity. Our results have important implications for biodiversity conservation as any attempts to mitigate the negative effects of habitat loss need to take the general level of habitat connectivity in the landscape into account.!://WOS:000334689900010Times Cited: 1 0921-2973WOS:00033468990001010.1007/s10980-014-0024-0<7[ &Ireland, K. B. Stan, A. B. Fule, P. Z.2012cBottom-up control of a northern Arizona ponderosa pine forest fire regime in a fragmented landscape983-997Landscape Ecology277fire history ponderosa fire scars dendrochronology synchrony climate interactions palmer drought severity index us southwest arizona low-severity fire southwestern united-states pinyon-juniper woodlands cross-scale analysis climate-change national-park grand-canyon USA history patternsAugoFire regimes often vary at fine spatial scales in response to factors such as topography or fuels while climate usually synchronizes fires across broader scales. We investigated the relative influence of top-down and bottom-up controls on fire occurrence in ponderosa pine (Pinus ponderosa) forests in a highly fragmented landscape at Mount Dellenbaugh, in northwestern Arizona. Our study area of 4,000 ha was characterized by patches of ponderosa pine forest in drainages that were separated by a matrix of pinyon-juniper woodlands, sagebrush shrublands, and perennial grasslands. We reconstructed fire histories from 135 fire-scarred trees in sixteen 25-ha sample sites placed in patches of mature ponderosa forest. We found that, among patches of ponderosa forest, fires were similar in terms of frequency but highly asynchronous in terms of individual years. Climate synchronized fire but only across broader spatial scales. Fires occurring at broader scales were associated with dry years that were preceded by several wet years. The remarkable level of asynchrony at finer scales suggests that bottom-up factors, such as site productivity and fuel continuity, were important in regulating fire at Mount Dellenbaugh. Understanding where bottom-up controls were historically influential is important for prioritizing areas that may best respond to fuel treatment under a warming climate.://000306068200005-969PP Times Cited:0 Cited References Count:46 0921-2973Landscape EcolISI:000306068200005Ireland, KB No Arizona Univ, Sch Forestry, Bldg 82,200 E Pine Knoll Dr, Flagstaff, AZ 86011 USA No Arizona Univ, Sch Forestry, Bldg 82,200 E Pine Knoll Dr, Flagstaff, AZ 86011 USA No Arizona Univ, Sch Forestry, Flagstaff, AZ 86011 USADOI 10.1007/s10980-012-9753-0English|? *Irwin, E. G. Jayaprakash, C. Munroe, D. K.2009ETowards a comprehensive framework for modeling urban spatial dynamics 1223-1236Landscape Ecology249The increasing availability of spatial micro data offers new potential for understanding the micro foundations of urban spatial dynamics. However, because urban systems are complex, induction alone is insufficient. Nonlinearities and path dependence imply that qualitatively new dynamics can emerge due to stochastic shocks or threshold effects. Given the policy needs for managing urban growth and decline and the growing desire for sustainable urban forms, models must be able not only to explain empirical regularities, but also characterize system-level dynamics and assess the plausible range of outcomes under alternative scenarios. Towards this end, we discuss a comprehensive modeling approach that is comprised of bottom-up and top-down models in which both inductive and deductive approaches are used to describe and explain urban spatial dynamics. We propose that this comprehensive modeling approach consists of three iterative tasks: (1) identify empirical regularities in the spatial pattern dynamics of key meso and macro variables; (2) explain these regularities with process-based micro models that link individual behavior to the emergence of meso and macro dynamics; and (3) determine the systems dynamical equations that characterize the relationships between micro processes and meso and macro pattern dynamics. Along the way, we also clarify types of complexity (input and output) and discuss dimensions of complexity (spatial, temporal, and behavioral). While no one to date has achieved this kind of comprehensive modeling, meaningful progress has been made in characterizing and explaining urban spatial dynamics. We highlight examples of this work from the recent literature and conclude with a discussion of key challenges.!://WOS:000270739000007Times Cited: 0 0921-2973WOS:00027073900000710.1007/s10980-009-9353-9 8<7\ -Isaacson, B. N. Serbin, S. P. Townsend, P. A.2012XDetection of relative differences in phenology of forest species using Landsat and MODIS529-543Landscape Ecology274vegetation phenology landsat modis forest autumn deciduous forest water index leaf-fall satellite imagery vegetation canopy dynamics USA classificationAprLandsat imagery is routinely used to characterize stand-level forest communities, but low temporal resolution makes pixel-wise characterization of phenology difficult. This limitation can be overcome by using multi-year imagery, but organizing Landsat scenes by calendar date ignores phenological gradients across the landscape as well as inter-annual differences in both scene- and pixel-wise phenology. We demonstrate how a spatially generalizable, phenologically-informed approach for re-ordering Landsat pixels can be used to characterize spatial variations in autumn senescence in several forest tree species. Using end-of-season estimates derived from MODIS phenology data, we determined the "days left in season" (DLiS) across Landsat images to produce a synthesized phenological trajectory of the normalized difference infrared index (NDII). We used ground-based species composition data in conjunction with the NDII trajectories to model autumn senescence by species. Absolute phenology differed by one and a half to 3 weeks between northern and southern Wisconsin, USA, but we show that the relative timing of phenology for individual species differs across regions by only 1-3 days when considering senescence with respect to the local end of the season. The progression of species senescence was consistent in lowland stands, starting with green and black ash, followed by silver maple, yellow birch, red maple, and tamarack. The image analyses suggest that senescence progressed more rapidly in southern than northern Wisconsin, starting earlier but taking about ten more days in the north. Our results support the use of MODIS phenological data with multi-year Landsat imagery to detect species with unique phenologies and identify how these vary across the landscape.://000302346900005-919RS Times Cited:0 Cited References Count:41 0921-2973Landscape EcolISI:000302346900005+Isaacson, BN Univ Wisconsin, Dept Forest & Wildlife Ecol, Russell Labs 226, 1630 Linden Dr, Madison, WI 53706 USA Univ Wisconsin, Dept Forest & Wildlife Ecol, Russell Labs 226, 1630 Linden Dr, Madison, WI 53706 USA Univ Wisconsin, Dept Forest & Wildlife Ecol, Russell Labs 226, Madison, WI 53706 USADOI 10.1007/s10980-012-9703-xEnglishV|?JCIverson, Louis Echeverria, Cristian Nahuelhual, Laura Luque, Sandra2014:Ecosystem services in changing landscapes: An introduction181-186Landscape Ecology292FebThe concept of ecosystem services from landscapes is rapidly gaining momentum as a language to communicate values and benefits to scientists and lay alike. Landscape ecology has an enormous contribution to make to this field, and one could argue, uniquely so. Tools developed or adapted for landscape ecology are being increasingly used to assist with the quantification, modelling, mapping, and valuing of ecosystem services. Several of these tools and methods encased therein are described among the eleven papers presented in this special issue, and their application has the potential to facilitate the management and promotion of services within ecosystems. Papers are associated with each of the four key categories of services that ecosystems provide to humans: supporting, provisioning, regulating, and cultural. The papers represent work conducted in eleven different countries, especially from South America. Each carries a unique approach to address a particular question pertaining to a particular set of ecosystem services. These studies are designed to inform and improve the economic, environmental and social values of the ecosystem services. This knowledge should help to develop new management alternatives for sustaining and planning ecosystems and the services they provide at different scales in space and time. We believe that these papers will create interest and inform management of some potential methods to evaluate ecosystem services at the landscape level with an integrative approach, offering new tools for management and conservation.!://WOS:000331935100001Times Cited: 3 0921-2973WOS:00033193510000110.1007/s10980-014-9993-2ڽ7 Iverson, LouisR McKenzie, Donald2013OTree-species range shifts in a changing climate: detecting, modeling, assisting879-889Landscape Ecology285Springer NetherlandsGSpecies distribution models Process-based Demography Assisted migration 2013/05/01+http://dx.doi.org/10.1007/s10980-013-9885-x 0921-2973Landscape Ecol10.1007/s10980-013-9885-xEnglish?V Iverson, L.R.1988iLand-use changes in Illinois, USA: The influence of landscape attributes on current and historic land use45-61Landscape Ecology21XGIS, soil, land use, presettlement vegetation, land-use change, fractal dimension, patchThe Illinois Geographic Information System was used to compare the soil and landscape attributes of the State with its historic vegetation, current land use, and patterns of land-use change over the past 160 years. Patch structural characteristics among land types in four geographic zones were also compared. The assessment of patch characteristics revealed a highly modified State with most land patches controlled by human influences and relatively few by topographic and hydrologic features. Correlation and regression analyses determined the relationships of land type and abundance within each of 50 general soil associations to properties of the soil associations - typically slope, texture, organic matter, productivity index, and available waterholding capacity. The distribution of the historic vegetation of the State and its current deciduous forests and nonforested wetlands related moderately (r^2>= 0.44) to various landscape attributes. Urban and other highly modified land types were less closely related.?W%Iverson, L.R. E.A. Cook R.L. Graham1994SRegional forest cover estimation via remote sensing: the calibration center concept159-174Landscape Ecology93GIS, AVHRR, correlation b|7o (Iverson, L. R. Cook, E. A. Graham, R. L.1994TRegional Forest Cover Estimation Via Remote-Sensing - the Calibration Center Concept159-174Landscape Ecology93geographic information system advanced very high resolution radiometer smoky mountains illinois forest remote sensing landsat tmSepeA method for combining Landsat Thematic Mapper (TM), Advanced Very High Resolution Radiometer (AVHRR) imagery, and other biogeographic data to estimate forest cover over large regions is applied and evaluated at two locations. In this method, TM data are used to classify a small area (calibration center) into forest/nonforest; the resulting forest cover map is then used in combination with AVHRR spectral data from the same area to develop an empirical relationship between percent forest cover and AVHRR pixel spectral signature; the resultant regression relationship between AVHRR band values and percent forest cover is then used to extrapolate forest cover for several hundred kilometers beyond the original TM calibration center. In the present study, the method was tested over two large regions in the eastern United States: areas centered on Illinois and on the Smoky Mountains on the North Carolina-Tennessee border. Estimates of percent forest cover for counties, after aggregating AVHRR pixel estimates within each county, were compared with independent ground-based estimates. County estimates were aggregated to derive estimates for states and regions. For the Illinois region, the overall correlation between county cover estimates was 0.89. Even better correlations (up to r = 0.96) resulted for the counties close to one another, in the same ecoregion, or in the same major land resource region as the calibration center. For the Smokies region, the correlations were significant but lower due to large influences of pine forests (suppressed spectral reflectance) in counties outside the hardwood-dominated calibration center. The method carries potential for estimating forest cover across the globe. It has special advantages in allowing the assessment of forest cover in highly fragmented landscapes, where individual AVHRR pixels (1 km2) are forested to varying degrees.://A1994PL16600001-Pl166 Times Cited:30 Cited References Count:0 0921-2973ISI:A1994PL166000018Iverson, Lr Us Forest Serv,359 Main Rd,Delaware,Oh 43015English<7<2Iverson, L. R. Dale, M. E. Scott, C. T. Prasad, A.1997lA GIS-derived integrated moisture index to predict forest composition and productivity of Ohio forests (USA)331-348Landscape Ecology125landscape ecology; site index; topography; Ohio; oak-hickory forests; integrated moisture index; GIS; spatial distribution; forest composition; DEM; resolution; scale GRADIENT; DYNAMICS; LANDFORM; ECOLOGY; TUNDRAArticleOctA geographic information system (GIS) approach was used in conjunction with forest-plot data to develop an integrated moisture index (IMI), which was then used to predict forest productivity (site index) and species composition for forests in Ohio. In this region, typical of eastern hardwoods across the Midwest and southern Appalachians, topographic aspect and position (rather than elevation) change drastically at the fine scale and strongly influence many ecological functions. Elevational contours, soil series mapping units, and plot locations were digitized for the Vinton Furnace Experimental Forest in southeastern Ohio and gridded to 7.5-m cells for GIS modeling. Several landscape features (a slope-aspect shading index, cumulative flow of water downslope, curvature of the landscape, and water-holding capacity of the soil) were used to create the IMI, which was then statistically analyzed with site-index values and composition data for plots. On the basis of IMI values for forest land harvested in the past 30 years, we estimated oak site index and the percentage composition of two major species groups in the region: oak (Quercus spp.), and yellow poplar (Liriodendron tulipifera) plus black cherry (Prunus serotina). The derived statistical relationships were then applied in the GIS to create maps of site index and composition, and verified with independent data. The maps show the oaks will dominate on dry, ridge top positions (i.e., low site index), while the yellow poplar and black cherry will predominate on mesic sites. Digital elevation models with coarser resolution (1:24K, 1:100K, 1:250K) also were tested in the same manner. We had generally good success for 1:24K, moderate success for 1:100K, but no success for 1:250K data. This simple and portable approach has the advantage of using readily available GIS information which is time-invariant and requires no fieldwork. The IMI can be used to better manage forest resources where moisture is limiting and to predict how the resource will change under various forms of ecosystem management.://000077684100007 ISI Document Delivery No.: 150UN Times Cited: 60 Cited Reference Count: 63 Cited References: *ENV SYST RES I, 1994, ARCD ON LIN DOC ARC *STATSC, 1993, STATSC GUID STAT MAT *US GEOL SURV, 1987, 5 US GEOL SURV ABRAMS MD, 1992, B TORREY BOT CLUB, V119, P19 ALLEN RB, 1990, CAN J BOT, V68, P193 BAND LE, 1988, APPLIED MATH COMPUTA, V27, P23 BEATLEY JC, 1959, B OHIO BIOL SURVEY, V1, P25 BECK DE, 1990, USDA FOR SERV AGR HD, V654, P406 BERGUSON WE, 1994, CAN J FOREST RES, V24, P1330 BEVEN K, 1986, SCALE PROBLEMS HYDRO, P107 BOWERSOX TW, 1972, FOREST SCI, V18, P278 CARMEAN WH, 1965, SOIL SCI SOC AM P, V29, P308 CROW TR, 1988, FOREST SCI, V34, P19 DENNIS DF, 1981, USDA RESOURCE B DUBRULE O, 1984, COMPUT GEOSCI, V10, P327 FOX L, 1985, PHOTOGRAMM ENG REM S, V51, P1745 FRALISH JS, 1994, ECOL APPL, V4, P134 FRANK TD, 1985, ARCTIC ALPINE RES, V17, P179 FRANKLIN J, 1995, PROG PHYS GEOGR, V19, P494 FROTHINGHAM EH, 1921, J FOREST, V16, P754 GARTEN CT, 1994, FOREST SCI, V40, P497 GOLET FC, 1993, 12 US DEP INT FISH W GOOD NF, 1972, B TORREY BOT CLUB, V99, P172 GRIFFITH DM, 1993, USDA RESOURCE B HEILIGMANN RB, 1985, NORTH J APPL FOR, V2, P17 HEPTING GH, 1971, USDA AGR HDB, V386 HILT DE, 1982, SO J APPL FORESTRY, V6, P53 HILT DE, 1985, P 5 CENTR HARDW FOR, P11 HODGES JD, 1993, OAK REGENERATION SER, P54 HOST GE, 1987, FOREST SCI, V33, P445 HUTNICK RJ, 1961, 142 USDA FOR SERV NE IVERSON LR, 1989, NATURAL HIST SURVEY, V11 IVERSON LR, 1994, EFFECTS LAND USE CHA, P67 IVERSON LR, 1994, ERIGENIA, V13, P4 IVERSON LR, 1996, CARING FOREST RES CH, P101 JENSON SK, 1988, PHOTOGRAMM ENG REMOT, V54, P1593 JONES JR, 1969, RM51 USDA FOR SERV JOURNEL AG, 1989, FUNDAMENTALS GEOSTAT KINGSLEY NP, 1970, USDA RESOURCE B LEE R, 1966, FOREST SCI, V12, P258 LIEFFERS VJ, 1987, CAN J BOT, V65, P1371 LLOYD AH, 1994, J VEG SCI, V5, P897 LOFTIS D, 1993, SE84 USDA FOR SERV LOUCKS OL, 1962, ECOL MONOGR, V32, P137 MADER DL, 1963, J FOREST, V61, P193 MARQUIS DA, 1990, USDA AGR HDB, V654, P594 MCNAB WH, 1993, CAN J FOREST RES, V23, P1100 MERZ RW, 1953, J FOREST, V51, P749 MITASOVA H, 1996, INT J GEOGR INF SYST, V10, P629 MONSERUD RA, 1984, FOREST LAND CLASSIFI, P167 OLIVER MA, 1990, INT J GEOGR INF SYST, V4, P313 POWELL DS, 1993, RM234 USDA FOR SERV ROBERTSON GP, 1987, ECOLOGY, V68, P744 ROGERS R, 1990, USDA AGR HDB, V654, P605 ROTH F, 1916, FOR Q, V15, P3 SKIDMORE AK, 1990, INT J GEOGR INF SYST, V4, P33 TAJCHMAN SJ, 1993, NO J AM FORESTRY, V10, P93 TRIMBLE GR, 1956, FOREST SCI, V2, P162 TRIMBLE GR, 1964, J FOREST, V62, P325 TWERY MJ, 1991, AI APPLICATIONS, V5, P45 WANG Q, 1991, SAF PUBLICATION, V9105, P538 WHITE DP, 1958, P 1 FOR SOILS C, P6 ZHU AX, 1994, CAN J REMOTE SENS, V20, P408 0921-2973 Landsc. Ecol.ISI:000077684100007USDA, US Forest Serv, NE Forest Expt Stn, Delaware, OH 43015 USA. Iverson, LR, USDA, US Forest Serv, NE Forest Expt Stn, 359 Main Rd, Delaware, OH 43015 USA.English?X(Iverson, L. R. Graham, R. L. Cook, E. A.1989?Applications of satellite remote sensing to forested ecosystems131-143Landscape Ecology32=satellite, remote sensing, forest ecosystems, GIS, monitoringSince the launch of the first civilian earth-observing satellite in 1972, satellite remote sensing has provided increasingly sophisticated information on the structure and function of forested ecosystems. Forest classification and mapping, common uses of satellite data, have improved over the years as a result of more discriminating sensors, better classification algorithms, and the use of geographic information systems to incorporate additional spatially referenced data such as topography. Land-use change, including conversion of forests for urban or agricultural development, can now be detected and rates of change calculated by superimposing satellite images taken at different dates. Landscape ecological questions regarding landscape pattern and the variables controlling observed patterns can be addressed using satellite imagery as can forestry and ecological questions regarding spatial variations in physiological characteristics, productivity, successional patterns, forest structure, and forest decline.<}?Iverson, L. R. Prasad, A. M.2007UUsing landscape analysis to assess and model tsunami damage in Aceh province, Sumatra323-331Landscape Ecology223tsunami damage; prediction; random forests; Indonesia; forests; developed areas; modeling damage; classification and regression trees; tsunami warning; mangroves MarThe nearly unprecedented loss of life resulting from the earthquake and tsunami of December 26, 2004, was greatest in the province of Aceh, Sumatra (Indonesia). We evaluated tsunami damage and built empirical vulnerability models of damage/no damage based on elevation, distance from shore, vegetation, and exposure. We found that highly predictive models are possible and that developed areas were far more likely to be damaged than forested zones. Modeling exercises such as this one, conducted in other vulnerable zones across the planet, would enable managers to create better warning and protection defenses, e. g., tree belts, against these destructive forces. ://000244455200001 0921-2973ISI:000244455200001~?QIverson, L. R. Prasad, A. M.2008(Modeling tsunami damage in Aceh: a reply7-10Landscape Ecology231In reply to the critique of Baird and Kerr, we emphasize that our model is a generalized vulnerability model, built from easily acquired data from anywhere in the world, to identify areas with probable susceptibility to large tsunamis-and discuss their other criticisms in detail. We also show that a rejection of the role of trees in helping protect vulnerable areas is not justified in light of existing evidence."://WOS:000251796100003 Times Cited: 0WOS:00025179610000310.1007/s10980-007-9180-9<7,Iverson, L. R. Schwartz, M. W. Prasad, A. M.2004|Potential colonization of newly available tree-species habitat under climate change: an analysis for five eastern US species787-799Landscape Ecology197biodiversity; climate change; eastern United States; global warming; landscape ecology; plant migration; range shifts PLANT MIGRATION RATES; UNITED-STATES; VEGETATION DISTRIBUTION; FOREST COVER; SEED DISPERSAL; NORTH-AMERICA; RANGE LIMITS; AVHRR DATA; MODEL; FRAGMENTATIONArticle`We used a combination of two models, DISTRIB and SHIFT, to estimate potential migration of five tree species into suitable habitat due to climate change over the next 100 years. These species, currently confined to the eastern half of the United States and not extending into Canada, are Diospyros virginiana (persimmon), Liquidambar styraciflua (sweetgum), Oxydendrum arboreum (sourwood), Pinus taeda (loblolly pine), and Quercus falcata var. falcata (southern red oak). DISTRIB uses a statistical approach to assess potential suitable habitat under equilibrium of 2 x CO2. SHIFT uses a cellular automata approach to estimate migration and is driven primarily by the abundance of the species near the boundary, forest density inside and outside of the boundary, and distance between cells. For each cell outside the current boundary, SHIFT creates an estimate of the probability that each unoccupied target cell will become colonized over 100 years. By evaluating the probability of colonization within the potential 'new' suitable habitat, we can estimate the proportion of new habitat that might be colonized within a century. This proportion is low (< 15%) for all five species, suggesting that there is a serious lag between the potential movement of suitable habitat and the potential for the species to migrate into the new habitat. However, humans could hasten the migration of certain species by physically moving the propagules, especially for certain rare species that are unable to move sufficiently through fragmented landscapes, or even more common species, e.g., beech, that have lost many of their animal dispersers.://000226384000007 ISI Document Delivery No.: 888OL Times Cited: 3 Cited Reference Count: 78 Cited References: *NAT ASS SYNTH TEA, 2000, CLIM CHANG IMP US PO *NAT ASS SYNTH TEA, 2001, CLIM CHANG IMP US PO *VEM MEMB, 1995, GLOBAL BIOGEOCHEMICA, V9, P407 ABER J, 2001, BIOSCIENCE, V51, P735 ABER JD, 1995, CLIMATE RES, V5, P207 BACHELET D, 2001, 508 USDA FOR SERV PA BACHELET D, 2001, ECOSYSTEMS, V4, P164 BOER GJ, 2000, CLIM DYNAM, V16, P427 BOX EO, 1999, CLIMATIC CHANGE, V41, P213 BURNS RM, 1990, AGR HDB, V654 BURNS RM, 1990, SILVICS N AM, V2 CAREY PD, 1996, GLOBAL ECOL BIOGEOGR, V5, P217 CLARK JS, 1998, AM NAT, V152, P204 CLARK JS, 1999, ECOLOGY, V80, P1475 CLARK JS, 2003, ECOLOGY, V84, P1979 DALE VH, 1997, ECOL APPL, V7, P753 DALE VH, 2001, BIOSCIENCE, V51, P723 DAVIS AJ, 1998, NATURE, V391, P783 DAVIS MB, 1981, FOREST SUCCESSION CO, P132 DAVIS MB, 1989, CLIMATIC CHANGE, V15, P75 DAVIS MB, 1992, GLOBAL WARMING BIOL, P297 DEHAYES DH, 2000, RESPONSES NO FORESTS, P495 DELCOURT HR, 1988, LANDSCAPE ECOL, V2, P23 DEVALL MS, 1998, PRODUCTIVITY SUSTAIN, P663 DYER JM, 1995, ECOL MODEL, V79, P199 GEAR AJ, 1991, SCIENCE, V251, P544 GUISAN A, 2000, PHYTOCOENOLOGIA, V30, P353 HANSEN AJ, 2001, BIOSCIENCE, V51, P765 HANSEN MH, 1992, NC151 USDA FOR SERV HE HS, 1999, ECOL MODEL, V114, P213 HIGGINS SI, 1999, AM NAT, V153, P464 HIGGINS SI, 2003, J ECOL, V91, P341 HIGGINS SI, 2003, OIKOS, V101, P354 HOUGHTON JT, 1995, CLIMATE CHANGE 1995 HUGHES L, 2000, TRENDS ECOL EVOL, V15, P56 HUNSAKER CT, 2001, SPATIAL UNCERTAINTY HUNTLEY B, 1995, J BIOGEOGR, V22, P967 IVERSON LR, 1989, INT J REMOTE SENS, V10, P1805 IVERSON LR, 1994, LANDSCAPE ECOL, V9, P159 IVERSON LR, 1998, ECOL MONOGR, V68, P465 IVERSON LR, 1999, ECOL MODEL, V115, P77 IVERSON LR, 1999, NE265 USDA FOR SERV IVERSON LR, 2002, FOREST ECOL MANAG, V155, P205 IVERSON LR, 2004, GLOBAL ECOL BIOGEOGR, V13, P209 JOYCE LA, 2000, 59 USDA FOR SERV RPA KIRILENKO AP, 1998, CLIMATIC CHANGE, V38, P15 KIRILENKO AP, 2000, ECOL MODEL, V132, P125 KIRSCHBAUM MUF, 2000, TREE PHYSIOL, V20, P309 LITTLE EL, 1971, MISC PUBL, V1146 LOEHLE C, 1998, J BIOGEOGR, V25, P735 MACARTHUR RH, 1972, GEOGRAPHICAL ECOLOGY MALCOLM JR, 2000, ECOSYSTEMS GLOBAL CL MALCOLM JR, 2002, J BIOGEOGR, V29, P835 MATLACK GR, 1994, ECOLOGY, V75, P1491 MCCARTHY JJ, 2001, CLIMATE CHANGE 2001 MELILLO JM, 1990, CLIMATE CHANGE IPCC, P283 MELILLO JM, 1996, CLIMATE CHANGE 1995, P445 MITCHELL JFB, 1995, NATURE, V376, P501 NEILSON RP, 1995, ECOL APPL, V5, P362 NEILSON RP, 1998, REGIONAL IMPACTS CLI, P439 OVERPECK JT, 1991, SCIENCE, V254, P692 PASTOR J, 1988, NATURE, V334, P55 PETERS RL, 1990, FOREST ECOL MANAG, V35, P13 PIELKE RA, 2002, CLIMATIC CHANGE, V52, P1 PITELKA LF, 1997, AM SCI, V85, P464 PORTNOY S, 1993, EVOL ECOL, V7, P25 PRASAD AM, 1999, CLIMATE CHANGE ATLAS SCHIMEL D, 2000, SCIENCE, V287, P2004 SCHWARTZ MW, 1993, BIODIVERS CONSERV, V2, P51 SCHWARTZ MW, 2001, ECOSYSTEMS, V4, P568 SHIGESADA N, 1997, BIOL INVASIONS THEOR SHRINER DS, 1998, REGIONAL IMPACTS CLI, P253 SYKES MT, 1996, CLIMATIC CHANGE, V34, P161 THOMAS CD, 2004, NATURE, V427, P145 WATSON RT, 2000, LAND USE LAND USE CH WILKINSON DM, 1997, J BIOGEOGR, V24, P61 YATES DN, 2000, CLIMATIC CHANGE, V44, P59 ZHU ZI, 1994, PHOTOGRAMM ENG REM S, V60, P525 0921-2973 Landsc. Ecol.ISI:000226384000007USDA, Forest Serv, NE Res Stn, Delaware, OH 43015 USA. Univ Calif Davis, Dept Environm Sci & Policy, Davis, CA 95616 USA. Iverson, LR, USDA, Forest Serv, NE Res Stn, 359 Main Rd, Delaware, OH 43015 USA. liverson@fs.fed.usEnglish <7] Jackson, H. B. Fahrig, L.2012/What size is a biologically relevant landscape?929-941Landscape Ecology277 landscape context spatial scale habitat fragmentation focal patch buffer informed dispersal habitat selection edge-mediated dispersal boundary behavior countryside biogeography habitat fragmentation dispersal distance behavior consequences movement dynamics birds biodiversity populationsAugThe spatial extent at which landscape structure best predicts population response, called the scale of effect, varies across species. An ability to predict the scale of effect of a landscape using species traits would make landscape study design more efficient and would enable landscape managers to plan at the appropriate scale. We used an individual based simulation model to predict how species traits influence the scale of effect. Specifically, we tested the effects of dispersal distance, reproductive rate, and informed movement behavior on the radius at which percent habitat cover best predicts population abundance in a focal area. Scale of effect for species with random movement behavior was compared to scale of effect for species with three (cumulative) levels of information use during dispersal: habitat based settlement, conspecific density based settlement, and gap-avoidance during movement. Consistent with a common belief among researchers, dispersal distance had a strong, positive influence on scale of effect. A general guideline for empiricists is to expect the radius of a landscape to be 4-9 times the median dispersal distance or 0.3-0.5 times the maximum dispersal distance of a species. Informed dispersal led to greater increases in population size than did increased reproductive rate. Similarly, informed dispersal led to more strongly decreased scales of effect than did reproductive rate. Most notably, gap-avoidance resulted in scales that were 0.2-0.5 times those of non-avoidant species. This is the first study to generate testable hypotheses concerning the mechanisms underlying the scale at which populations respond to the landscape.://000306068200001-969PP Times Cited:0 Cited References Count:43 0921-2973Landscape EcolISI:000306068200001#Jackson, HB Carleton Univ, Dept Biol, Geomat & Landscape Ecol Lab, 1125 Colonel Dr, Ottawa, ON K1S 5B6, Canada Carleton Univ, Dept Biol, Geomat & Landscape Ecol Lab, 1125 Colonel Dr, Ottawa, ON K1S 5B6, Canada Carleton Univ, Dept Biol, Geomat & Landscape Ecol Lab, Ottawa, ON K1S 5B6, CanadaDOI 10.1007/s10980-012-9757-9Englishv|?/ Jacobson, B. Peres-Neto, P. R.2010kQuantifying and disentangling dispersal in metacommunities: how close have we come? How far is there to go?495-507Landscape Ecology2548Much of ecological research centers around discovering the underlying factors for species distribution; three such factors are of central importance: local environment, landscape features and dispersal. While all have been simplified in the past, the recent increase in metapopulation and metacommunity research makes being able to quantify dispersal all that much more necessary. In order to increase our knowledge about metacommunities in the "real word", it is clearly time to start thinking critically about whether and how the methods that are currently available for measuring dispersal within metapopulations can be adapted. The goal of this contribution is to present and argue the technical difficulties involved in measuring dispersal within metacommunities through: (1) discussing the merits and pitfalls of some potential direct (e.g., mark-recapture) and indirect methods (e.g., isolation measures, patchiness) for studying the effects of dispersal at the metapopulation and metacommunity level; (2) discuss the types of questions that can be tackled at the metacommunity level in light of methodological decisions; and (3) make the point that the technical difficulties of measuring dispersal for multiple species may leave us with little other options than using indirect methods to estimate dispersal in metacommunities.!://WOS:000275444100001Times Cited: 0 0921-2973WOS:00027544410000110.1007/s10980-009-9442-9<71Jaeger, J. A. G.2000eLandscape division, splitting index, and effective mesh size: new measures of landscape fragmentation115-130Landscape Ecology152effective mesh size fragmentation phases landscape division landscape fragmentation landscape indices landscape pattern quantitative methods spatial heterogeneity splitting index PATTERNArticleFebAnthropogenic fragmentation of landscapes is known as a major reason for the loss of species in industrialized countries. Landscape fragmentation caused by roads, railway lines, extension of settlement areas, etc., further enhances the dispersion of pollutants and acoustic emissions and affects local climatic conditions, water balance, scenery, and land use. In this study, three new measures of fragmentation are introduced: degree of landscape division (D), splitting index (S), and effective mesh size (m). They characterize the anthropogenic penetration of landscapes from a geometric point of view and are calculated from the distribution function of the remaining patch sizes. First, D, S, and m are defined, their mathematical properties are discussed, and their reactions to the six fragmentation phases of perforation, incision, dissection, dissipation, shrinkage, and attrition are analysed. Then they are compared with five other known fragmentation indices with respect to nine suitability criteria such as intuitive interpretation, low sensivity to very small patches, monotonous reaction to different fragmentation phases, and detection of structural differences. Their ability to distinguish spatial patterns is illustrated by means of two series of model patterns. In particular, the effective mesh size (m), representing an intensive and area-proportionately additive measure, proves to be well suited for comparing the fragmentation of regions with differing total size.://000084522700004 :ISI Document Delivery No.: 270EP Times Cited: 44 Cited Reference Count: 33 Cited References: BERG M, 1994, FRESEN ENVIRON BULL, V3, P487 BOWEN GW, 1981, ORNL PUBLICATION, V1719 BURGESS RL, 1981, ECOLOGICAL STUDIES, V41 CHANDLER D, 1987, INTRO MODERN STAT ME DEGGAU M, 1992, 1070600103UBAFB92084 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 GAME M, 1980, NATURE, V287, P630 GEOGHEGAN J, 1997, ECOL ECON, V23, P251 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HABER W, 1993, OKOLOGISCHE GRUNDLAG HAINESYOUNG R, 1996, PROG PHYS GEOG, V20, P418 HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HARRIS LD, 1984, FRAGMENTED FOREST IS KRACKROBERG E, 1995, UGR MAT CONCEPT ACCO KREYSZIG E, 1979, STAT METHODEN IHRE A LI H, 1995, OIKOS, V73, P280 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MULLER D, 1998, NETZSTADT TRANSDISZI, P28 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PATTON DR, 1975, WILDLIFE SOC B, V3, P171 PLOTNICK RE, 1993, LANDSCAPE ECOL, V8, P201 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 RIITTERS KH, 1996, LANDSCAPE ECOL, V11, P197 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SCHMIDTBLEEK F, 1993, FRESEN ENVIRON BULL, V2, P407 STRAUMANN N, 1986, LECT NOTES PHYSICS, V265 TAYLOR PD, 1993, OIKOS, V68, P571 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1991, QUANTITATIVE METHODS VANDORP D, 1987, LANDSCAPE ECOLOGY, V1, P59 WETZEL RG, 1975, LIMNOLOGY 0921-2973 Landsc. Ecol.ISI:000084522700004Ctr Technol Assessment Baden Wurttemberg, D-70565 Stuttgart, Germany. Jaeger, JAG, Ctr Technol Assessment Baden Wurttemberg, Ind Str 5, D-70565 Stuttgart, Germany.English|?8James, A. I. Eldridge, D. J. Koen, T. B. Whitford, W. G.2008sLandscape position moderates how ant nests affect hydrology and soil chemistry across a Chihuahuan Desert watershed961-975Landscape Ecology238Ants moderate the supply of critical resources such as water and nutrients in desert environments by changing the physical arrangement of soils during nest construction. We measured water infiltration and soil physical and chemical properties on and off the nests of two ant species (Pogonomyrmex rugosus, Aphaenogaster cockerelli) across five sites at differing landscape positions within a Chihuahuan Desert watershed. Our aim was to test whether the effects of these long-lived ant nests on water infiltration and soil chemistry varied between ant species or across sites within a watershed. Water flow was generally slowest at the site with the highest silt and clay contents, and fastest at the site with sandy soils. Flow was generally greater through ant nest soils than adjacent non-nest soils, and we attribute this to increases in macropores in the nests. However, the effects of both ant nests and species varied among sites. Despite wide variation in soil chemical properties across all sites, ant nests had a consistent effect on soil chemical properties, with higher levels of carbon, nitrogen, sulphur, phosphorus and electrical conductivity on nests compared with non-nest soils. Our results demonstrate that while we can generalise about the effects of ant nests on water flow and nutrient levels, differences in soil type, nest density and ant species across sites are likely to moderate these effects.!://WOS:000259481900007Times Cited: 0 0921-2973WOS:00025948190000710.1007/s10980-008-9251-6d|? <James, Patrick M. A. Fleming, Richard A. Fortin, Marie-Josee2010Identifying significant scale-specific spatial boundaries using wavelets and null models: spruce budworm defoliation in Ontario, Canada as a case study873-887Landscape Ecology256JulWe combine wavelet analysis and multiple null models to identify significant spatial scales of pattern and spatial boundaries in historical spruce budworm defoliation in Ontario, Canada. Previous analyses of budworm defoliation in Ontario over the last two outbreaks have suggested three distinct zones of defoliation. We asked the following three questions: (1) is there statistical support for the existence of these three zones? (2) Are the locations of these boundaries consistent between outbreak periods? And (3) how does boundary identification depend on the spatial null model used? Defoliation data for the two outbreak periods (1941-1965 and 1966-2001), and the combined period (1941-2001) were analyzed using a 1D continuous wavelet transform. Boundaries were identified through comparison of wavelet power spectra of each outbreak period to reference distributions based on three different spatial null models: (1) a complete spatial randomness model, (2) an autoregressive model, and (3) a Gaussian random field model. The Gaussian random field model identified coarser scales of pattern than the autoregressive model. Locally, the Gaussian random field model found significant boundaries similar to those previously described, whereas the autoregressive model only did so for the first outbreak. These results indicate that the coarse scale spatial factors that influenced defoliation were more consistent between outbreaks relative to fine scale factors, and that previously described boundaries were strongly driven by the first outbreak. Wavelet analysis combined with spatial null models provides a powerful tool for identifying non-arbitrary scales of structure and significant spatial boundaries in non-stationary ecological data.!://WOS:000278526000005Times Cited: 0 0921-2973WOS:00027852600000510.1007/s10980-010-9465-2 ?.Jan, Bogaert Ranga, B. Myneni Yuri, Knyazikhin2002TA mathematical comment on the formulae for the aggregation index and the shape index87-90Landscape Ecology171Aggregation index - Index redundancy - Landscape metric - Perimeter - Pixel edge - Pixel geometry - Shape index - Spatial pattern Ina recent paper [Landscape Ecol. 15: 591–601 (2000)] He et al. describedanaggregation index AI i to measure pixelaggregation within a single class i. We show that thecommonly used shape index SI i is related to theproposed aggregation metric as SI i =(A i) +AI i(1 –(A i)), with(A i) dependent on class areaA i only. Moreover, it is shown that thenormalized shape index, SI i *,equals (1 – AI i). We conclude thatAI i does not provide any information notprovided by SI i, orSI i *.*http://dx.doi.org/10.1023/A:1015204923187 10.1023/A:1015204923187 Jan Bogaert Email: jan.bogaert@ua.ac.be References Bogaert J., Rousseau R., Van Hecke P. and Impens I. 2000. Alternative area-perimeter ratios for measurement of 2-D shape compactness of habitats. Applied Mathematics and Computation 111: 71-85. Bribiesca E. 1997. Measuring 2-D shape compactness using the contact perimeter. Computers and Mathematics with Applications 33: 1-9. He H.S., DeZonia B.E. and Mladenoff D.J. 2000. An aggregation index (AI) to quantify spatial patterns of landscapes. Landscape Ecology 15: 591-601. Johnsson K. 1995. Fragmentation index as a region based GIS operator. International Journal of Geographical Information Systems 9: 211-220. McGarigal K. and Marks B.J. 1995. FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. Gen. Tech. Rep. PNW-GTR-351. US Department of Agriculture, Forest Service, Pacific Northwest Research Station, Portland, OR, USA, 122 p. Miller J.N., Brooks R.P. and Croonquist M.J. 1997. Effects of landscape patterns on biotic communities. Landscape Ecology 12: 137-153. Milne B.T. 1991. Lessons from applying fractal models to landscape patterns. In: Turner M.G. and Gardner R.H. (eds), Quantitative Methods in Landscape Ecology-The Analysis and Interpretation of Landscape Heterogeneity. Springer-Verlag, New York, NY, USA, pp. 199-235. ONeill R.V., Krummel J.R., Gardner R.H., Sugihara G., Jackson B., DeAngelis D.L. et al. 1988. Indices of landscape pattern. Landscape Ecology 1: 153-162. Pearson S.M., Turner M.G. and Urban D.L. 1999. Effective exercises in teaching landscape ecology. In: Klopatek J.M. and Gardner R.H. (eds), Landscape Ecological Analysis-Issues and Applications. Springer-Verlag, New York, NY, USA, pp. 335-368. Jan Bogaert1 , Ranga B. Myneni1 and Yuri Knyazikhin1 (1) Department of Geography, Climate and Vegetation Research Group, Boston University, Boston, 02215-1401, USA |7Jansen, F. Zerbe, S. Succow, M.2009eChanges in landscape naturalness derived from a historical land register-a case study from NE Germany185-198Landscape Ecology242wcentral-europe species richness fuzzy-sets conservation restoration disturbance grasslands vegetation woodland patternsFeb://000262828900004-399WB Times Cited:0 Cited References Count:77 0921-2973ISI:000262828900004Jansen, F Ernst Moritz Arndt Univ Greifswald, Inst Bot & Landscape Ecol, Grimmer Str 88, D-17487 Greifswald, Germany Ernst Moritz Arndt Univ Greifswald, Inst Bot & Landscape Ecol, D-17487 Greifswald, GermanyDoi 10.1007/S10980-008-9297-5English<7h!Jansson, A. Folke, C. Langaas, S.1998sQuantifying the nitrogen retention capacity of natural wetlands in the large-scale drainage basin of the Baltic Sea249-262Landscape Ecology134GIS wetlands large-scale drainage basin nitrogen retention ecosystem services ECOSYSTEM SERVICES COASTAL WATERS NUTRIENTS BIODIVERSITY MANAGEMENT VALUATION GROWTH BOGSArticleAugKWe estimate the nitrogen retention capacity of natural wetlands in the 1.7 million km(2)Baltic Sea drainage basin, using a wetland GIS data base. There are approximately 138,000 km(2)of wetlands (bogs and fens) in the Baltic Sea drainage basin, corresponding to 8% of the area. The input of nitrogen to natural wetlands from atmospheric deposition was estimated to 55,000-161,000 ton y(-1) A map of the deposition of both wet and dry nitrogen is presented. The input from the human population was estimated to 255,000 ton y(-1) in terms of excretory release in processed sewage water. There may also be leakage from forests and agricultural land into the wetlands. Due to lack of data on hydrology and topography, such potential nitrogen sources are not accounted for here. The capacity of the wetlands to retain the atmospheric deposition of nitrogen was estimated to 34,000-99,000 ton y(-1) The potential retention by wetlands was estimated to 57,000-145,000 ton y(-1) when the nitrogen input from the human population was added. If drained wetlands were to be restored and their area added to the present wetland area, the nitrogen retention capacity was estimated to increase to 196,000-261,000 ton y(-1). Our results indicate that existing natural wetlands in the Baltic Sea drainage basin annually can retain an amount of nitrogen which corresponds to about 5-13% of annual total (natural and anthropogenic) nitrogen emissions entering the Baltic Sea. The ecosystem retention service performed by wetlands accounts for a substantial nitrogen removal, thereby reducing the eutrophication of the Baltic Sea.://000079677000005 ISI Document Delivery No.: 185NY Times Cited: 14 Cited Reference Count: 63 Cited References: *STAT SWED, 1993, BALT REG STAT RES EN *WRI, 1994, WORLD RES 1994 95 AERTS R, 1992, J ECOL, V80, P131 ANDERSSON A, 1994, THESIS STOCKHOLM U S ANDREASSONGREN LM, 1991, AMBIO, V20, P94 ASELMANN I, 1989, J ATMOS CHEM, V8, P307 BAKER LA, 1992, ECOL ENG, V1, P1 BURKE W, 1975, IRISH J AGR RES, V14, P163 COSTANZA R, 1989, ECOL ECON, V1, P335 COSTANZA R, 1990, BIOSCIENCE, V40, P91 COSTANZA R, 1993, AMBIO, V22, P88 COSTANZA R, 1997, NATURE, V387, P253 DAILY G, 1997, NATURES SERVICES SOC DEGROOT RS, 1992, FUNCTIONS NATURE EHRLICH PR, 1983, BIOSCIENCE, V33, P248 EHRLICH PR, 1997, NTURES SERVICES SOC, P151 ELOFSSON K, 1997, THESIS ETNIER C, 1991, ECOLOGICAL ENG WASTE EWEL K, 1984, CYPRESS SWAMPS EWEL KC, 1997, NATURES SERVICES SOC, P329 FITZ HC, IN PRESS ECOLOGICAL FITZ HC, 1993, EVERGLADES LANDSCAPE FLEISCHER S, 1991, AMBIO, V20, P271 FOLKE C, 1991, LINKING NATURAL ENV, P141 FOLKE C, 1991, LINKING NATURAL ENV, P77 GREN IM, IN PRESS ENV RESOURC GREN IM, 1994, BEIJER DISCUSSION PA, V54 HORNER RR, 1986, P C WETL FUNCT REH C HOWARDWILLIAMS C, 1985, FRESHWATER BIOL, V15, P391 IVERSEN T, 1991, 191 EMEPMSCW JACKS G, 1994, AMBIO, V23, P358 JANSSON M, 1994, AMBIO, V23, P320 JOHNSTON CA, 1990, BIOGEOCHEMISTRY, V10, P105 KADLEC RH, 1977, 1 U MICH WETL EC RES KADLEC RH, 1979, 3 U MICH WETL EC RES KADLEC RH, 1980, 4 U MICH WETL EC RES KADLEC RH, 1981, 5 U MICH WETL EC RES KALDEC RH, 1978, 2 U MICH WETL EC RES KLOCHAK RJ, 1993, VEGETATION PLANTING KNIGHT RL, 1992, ECOL ENG, V1, P97 KRYSANOVA V, 1989, ECOL MODEL, V49, P7 LARSSON U, 1985, AMBIO, V14, P9 LEONARDSSON L, 1994, 4176 SWED ENV AG LOFGREN S, 1990, HAV90 SWED ENV AG MALMER N, 1962, OPERA BOT, V7, P1 MANDER U, 1995, FUNCTIONAL APPRAISAL, P77 MITSCH WJ, 1992, ECOL ENG, V1, P27 MITSCH WJ, 1993, WETLANDS NICHOLS DS, 1983, J WATER POLLUT CON F, V55, P495 NORTON BG, 1992, AMBIO, V21, P244 ODUM EP, 1975, ECOLOGY ROSSWALL T, 1980, ECOLOGY SUBARCTIC MI, V30, P209 RYDLOV M, 1991, WETLANDS VITAL ECOSY SLAPOKAS T, 1991, THESIS SWEDISH U AGR SMALL E, 1972, ECOLOGY, V53, P498 SWECO, 1992, PREFEASIBILITY ST 2B SWEITZER J, 1996, AMBIO, V25, P191 TILTON DL, 1977, CAN J BOT, V55, P1291 TILTON DL, 1979, J ENVIRON QUAL, V8, P328 TORELL L, 1977, AMBIO SPECIAL REPORT, V5, P213 VANWILGEN BW, 1996, BIOSCIENCE, V46, P184 VERRY ES, 1982, ECOLOGY, V63, P1456 VITOUSEK PM, 1986, BIOSCIENCE, V36, P368 0921-2973 Landsc. Ecol.ISI:000079677000005Royal Swedish Acad Sci, Beijer Int Inst Ecol Econ, S-10405 Stockholm, Sweden. Jansson, A, Royal Swedish Acad Sci, Beijer Int Inst Ecol Econ, Box 50005, S-10405 Stockholm, Sweden.English<7WJansson, G. Angelstam, P.1999{Threshold levels of habitat composition for the presence of the long-tailed tit (Aegithalos caudatus) in a boreal landscape283-290Landscape Ecology143habitat isolation thresholds quantification deciduous long-tailed tit Aegithalos caudatus forest management conservation Sweden GROUSE BONASA-BONASIA EXTINCTION THRESHOLDS DEMOGRAPHIC-MODELS FOREST LANDSCAPE BREEDING BIRD FRAGMENTATION POPULATIONS ECOLOGY CONSERVATION COLONIZATIONArticleJunWe assessed the habitat patch occupancy of a deciduous-mixed forest specialist, the long-tailed tit (Aegithalos caudatus), in a 1000 km(2) conifer dominated landscape in relation to two landscape parameters, namely proportion and isolation of suitable habitat. Data from five consecutive spring seasons were used and within habitat variation controlled for. The occurrence of long-tailed tits was positively related to the amount of habitat within 1 km(2) (p=0.0007) and negatively related to the distance between habitat patches (p < 0.0001). When combined, the two variables explained > 78% of the variation in local patch occupancy. There were distinct thresholds in these landscape variables for the probability of local long-tailed tit presence. In the model the probability increased from 0.1 to 0.8 when interpatch distance decreased from 500 to 100 m with 5% total habitat coverage. With a total proportion of 15% suitable habitat, the same probability jump occurred when interpatch distance changed from 900 to 500 m. The general importance of defined measurements and quantified threshold levels for species conservation and landscape management is discussed.://000081041200006 ISI Document Delivery No.: 209HB Times Cited: 39 Cited Reference Count: 73 Cited References: ABERG J, 1995, OECOLOGIA, V103, P265 ANDREN H, 1994, OIKOS, V71, P355 ANDREN H, 1996, OIKOS, V76, P235 ANGELSTAM P, 1997, ECOLOGICAL B, V46, P191 APELDOORN RC, 1992, OIKOS, V65, P265 BASCOMPTE J, 1996, J ANIM ECOL, V65, P465 BLAKE JG, 1991, CONSERV BIOL, V5, P58 BLECKERT S, 1991, THESIS U GOTEBORG SW BOLGER DT, 1991, AM NAT, V137, P155 CARLSON A, 1995, 27 SWED U AGR SCI DE CONNOR EF, 1979, AM NAT, V113, P791 DANIELS RJR, 1994, J BIOSCIENCE, V19, P503 DONCASTER CP, 1996, OIKOS, V75, P335 DUNNING JB, 1992, OIKOS, V65, P169 DYTHAM C, 1995, OIKOS, V74, P340 EHNSTROM B, 1986, FAUNAVARD SKOGSBRUKE ENOKSSON B, 1995, LANDSCAPE ECOL, V10, P267 FARINA A, 1983, MONIT ZOOL ITAL, V17, P121 GASTON AJ, 1973, IBIS, V115, P330 HAILA Y, 1984, ANN ZOOL FENN, V21, P393 HAILA Y, 1993, ECOLOGY, V74, P714 HANSELL MH, 1994, J ORNITHOL, V135, P195 HANSKI I, 1991, BIOL J LINN SOC, V42, P3 HANSKI I, 1994, ECOLOGY, V75, P747 HARRIS LD, 1982, T N AM WILDL NAT RES, V47, P374 HARRIS LD, 1984, FRAGMENTED FOREST IS HARRISON RL, 1992, CONSERV BIOL, V6, P293 HATCHWELL BJ, 1996, IBIS, V138, P256 HENDERSON MT, 1985, BIOL CONSERV, V31, P95 HINSLEY SA, 1995, J AVIAN BIOL, V26, P94 IHSE M, 1993, 931 SKOGSST, P19 JOHNSON AR, 1992, LANDSCAPE ECOL, V7, P63 JOKIMAKI J, 1996, ORNIS FENNICA, V73, P97 KOOPOWITZ H, 1994, CONSERV BIOL, V8, P425 LAMBERSON RH, 1992, CONSERV BIOL, V6, P505 LAMPLAHTI J, 1985, ORNIS FENNICA, V62, P170 LANDE R, 1987, AM NAT, V130, P624 LANDE R, 1988, OECOLOGIA, V75, P601 LI HB, 1994, ECOLOGY, V75, P2446 LOVEJOY TE, 1986, CONSERVATION BIOL SC, P257 MATTHIAE PE, 1981, FOREST ISLAND DYNAMI, P55 MERRIAM G, 1992, LANDSCAPE BOUNDARIES, P150 MIKUSINSKI G, 1998, CONSERV BIOL, V12, P200 MORRISON ML, 1992, WILDLIFE HABITAT REL NAKAMURA T, 1969, MISC REP YAMASHINA I, V5, P1 NOSS RF, 1991, LANDSCAPE LINKAGES B OLSSON R, 1992, LEVANDE SKOG SKOGSBR ONEILL RV, 1988, LANDSCAPE ECOL, V2, P63 OPDAM P, 1984, J BIOGEOGR, V11, P473 OPDAM P, 1991, LANDSCAPE ECOL, V5, P93 OPDAM P, 1995, IBIS, V137, P139 PEARSON SM, 1993, LANDSCAPE ECOL, V8, P3 PENNANEN J, 1996, MODEL NATURAL FOREST ROSE M, 1991, SIGHT SOUND, V1, P9 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SIMBERLOFF D, 1995, IBIS, V137, S105 STAMPS JA, 1987, AM NAT, V129, P532 SVENSSON S, 1975, HANDLEDNING FOR SVEN SVENSSON S, 1996, OVERVAKNING AV FAGLA SWENSON JE, 1993, BEHAV ECOL, V4, P14 SWENSON JE, 1993, CAN J ZOOL, V71, P1303 TAYLOR PD, 1993, OIKOS, V68, P571 TELLERIA JL, 1995, BIOL CONSERV, V71, P61 TURNER MG, 1991, QUANTITATIVE METHODS, P3 VANDORP D, 1987, LANDSCAPE ECOLOGY, V1, P59 VERBOOM J, 1991, OIKOS, V61, P149 VILLARD MA, 1994, OECOLOGIA, V98, P393 WIENS JA, 1993, OIKOS, V66, P369 WIENS JA, 1995, IBIS, V137, S97 WILCOVE DS, 1986, CONSERVATION BIOL SC, P256 WITH KA, 1995, ECOLOGY, V76, P2446 WORTHEN WB, 1996, OIKOS, V76, P417 ZACKRISSON O, 1991, SKOG FORSKNING, V4, P13 0921-2973 Landsc. Ecol.ISI:000081041200006Swedish Univ Agr Sci, Grimso Wildlife Res Stn, Dept Conservat Biol, S-73091 Riddarhyttan, Sweden. Jansson, G, Swedish Univ Agr Sci, Grimso Wildlife Res Stn, Dept Conservat Biol, S-73091 Riddarhyttan, Sweden.Englishڽ7 DJauker, Birgit Krauss, Jochen Jauker, Frank Steffan-Dewenter, Ingolf2013RLinking life history traits to pollinator loss in fragmented calcareous grasslands107-120Landscape Ecology281Springer NetherlandsBiodiversity Community ecology Habitat fragmentation Species-area relationships Landscape diversity Bees Body size Sociality Trophic level 2013/01/01+http://dx.doi.org/10.1007/s10980-012-9820-6 0921-2973Landscape Ecol10.1007/s10980-012-9820-6English |74Jauker, F. Diekotter, T. Schwarzbach, F. Wolters, V.2009Pollinator dispersal in an agricultural matrix: opposing responses of wild bees and hoverflies to landscape structure and distance from main habitat547-555Landscape Ecology244apidae syrphidae landscape context distribution patterns crop pollination fragmented landscapes ecosystem service species loss land-use biodiversity diversity context communities abundanceAprSemi-natural habitats provide essential resources for pollinators within agricultural landscapes and may help maintain pollination services in agroecosystems. Yet, whether or not pollinators disperse from semi-natural habitat elements into the adjacent agricultural matrix may to a large extent depend on the quality of this matrix and the corresponding pollinator-specific life history traits. To investigate the effects of matrix quality on the distance decay of wild bees and hoverflies, six transects along vegetated field tracks originating at a large semi-natural main habitat and leading into the adjacent agricultural matrix were established in the Wetterau Region, central Hesse, Germany. Species richness of wild bees did not change with distance from the main habitat in landscapes with sufficient grassland cover in the surrounding landscape, but significantly declined when semi-natural grasslands where scarce and isolated in the adjacent agricultural matrix. Abundance of wild bees declined with distance regardless of matrix quality. Species richness of hoverflies did not decline with increasing distance in any landscape. Abundance even increased with distance to the main habitat independently of matrix quality. Thus, our data show that taxa of the pollinator guild may perceive landscapes quite differently. Because of their differing dispersal modes and resource requirements as compared to wild bees, hoverflies may play an important role in maintaining pollination services in agricultural landscapes unsuitable for bee species. Our results highlight the need for considering these taxon-specific differences when predicting the effect of landscape structure on pollinators.://000263898100009-414XI Times Cited:0 Cited References Count:51 0921-2973ISI:000263898100009Jauker, F Justus Liebig Univ, Dept Anim Ecol, Heinrich Buff Ring 26-32, D-35392 Giessen, Germany Justus Liebig Univ, Dept Anim Ecol, D-35392 Giessen, GermanyDoi 10.1007/S10980-009-9331-2English<73Jeanneret, P. Schupbach, B. Pfiffner, L. Walter, T.2003OArthropod reaction to landscape and habitat features in agricultural landscapes253-263Landscape Ecology183arthropods biodiversity canonical correspondence analysis environmental control landscape and habitat influence variation partitioning SPECIES RICHNESS BIODIVERSITY DIVERSITY GRASSLAND ARANEAE FIELD COMMUNITIES MANAGEMENT CARABIDAE DYNAMICSArticleAprDetermining explanatory environmental factors that lead to patterns of biodiversity in cultivated landscapes is an important step for the assessment of the impact of landscape changes. In the context of an assessment of the effect of agricultural national extensification programme on biodiversity, field data of 2 regions were collected according to a stratified sampling method. A distribution model of 3 indicator species taxa ( butterflies, spiders, and carabid beetles) is related to influencing factors by means of multivariate statistics (CCA, partial CCA). Hypothetical influencing factors are categorised as follows: (1) habitat (habitat type, management techniques) and (2) landscape (habitat heterogeneity, variability, diversity, proportion of natural and semi-natural areas). The correlation models developed for spider, carabid beetle and butterfly assemblages revealed that there are no general rules relating species diversity to habitat and landscape features. The relationship strongly depends on the organism and on the region under study. Therefore, biodiversity response to landscape and habitat changes has to be identified by means of a multi-indicator concept in different landscape situations.://000183770600004 < ISI Document Delivery No.: 694JD Times Cited: 12 Cited Reference Count: 55 Cited References: ALDERWEIRELDT M, 1989, AGR ECOSYST ENVIRON, V27, P293 ANDERSON MJ, 1998, AUST J ECOL, V23, P158 ASSELIN A, 1989, ACTA OECOL, V4, P143 ATAURI JA, 2001, LANDSCAPE ECOL, V16, P147 BOGGS CL, 1987, NUTR ECOLOGY INSECTS, P369 BORCARD D, 1992, ECOLOGY, V73, P1045 BORCARD D, 1994, ENVIRON ECOL STAT, V1, P37 BUREL F, 1992, LANDSCAPE ECOL, V6, P161 BUREL F, 1995, AGR ECOSYST ENVIRON, V55, P193 BUREL F, 1999, ECOLOGIE PAYSAGE CON CLAUSEN IHS, 1986, B BR ARACHNOL SOC, V7, P83 DEBINSKI DM, 1994, ECOL APPL, V4, P833 DENNIS P, 1992, AGR ECOSYST ENVIRON, V40, P95 DOVER JW, 1992, ENTOMOL GAZ, V43, P29 DUELLI P, 1990, SCHRIFTENREIHE LANDS, V32, P211 DUELLI P, 1997, AGR ECOSYST ENVIRON, V62, P81 DUFFEY E, 1974, P 6 INT AR C AMST, V4, P53 DUNNING JB, 1992, OIKOS, V65, P169 ERHARDT A, 1985, J APPL ECOL, V22, P849 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FORMAN RTT, 1995, LAND MOSAICS ECOLOGY HERZOG F, 2001, ECOSYSTEMS SUSTAINAB, V3, P397 HUSTON MA, 1995, BIOL DIVERSITY JEANMERET P, 2000, AGRARFORSCHUNG, V7, P112 JEANNERET P, 1999, HETEROGENEITY LANDSC, P85 JEANNERET P, 2002, IN PRESS J NATURE CO KRAMER I, 1996, AGRAROKOLOGIE, V17 KREMEN C, 1992, ECOL APPL, V2, P203 LEGENDRE P, 1998, DEV ENV MODELLING, V20 LUFF ML, 1989, J BIOGEOGR, V16, P121 LYS JA, 1994, PEDOBIOLOGIA, V38, P238 MARINO PC, 1996, ECOL APPL, V6, P276 MARTIN D, 1991, ARACHNOL MITT, V1, P5 MCCRACKEN DI, 2000, QUANTITATIVE APPROAC, P97 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 OUIN A, 2002, IN PRESS AGR ECOSYST PAOLETTI MG, 1999, AGR ECOSYST ENVIRON, V74, P1 PFIFFNER L, 2000, AGR ECOSYST ENVIRON, V78, P215 PFIFFNER L, 2000, AGRARFORSCHUNG, V7, P212 POZZI S, 2001, ECOSCIENCE, V8, P32 QUINN JF, 1983, AM NAT, V122, P602 SCRIBER JM, 1973, PSYCHE, V80, P355 SOUTHWOOD TRE, 1987, ORG COMMUNITIES PAST, P3 SPARKS TH, 1995, BIOL CONSERV, V73, P221 STRONG DR, 1984, INSECTS PLANTS TERBRAAK CJF, 1996, THESIS WAGENINGEN NE TERBRAAK CJF, 1998, CANOCO REFERENCE MAN THOMAS CD, 1992, J ANIM ECOL, V61, P437 THOMAS CD, 1997, METAPOPULATION BIOL, P359 TSCHARNTKE T, 2002, ECOL APPL, V12, P354 TURIN H, 1991, TIJDSCHR ENTOMOL, V134, P279 WAGNER HH, 2001, LANDSCAPE ECOL, V16, P121 WARREN MS, 1992, ECOLOGY BUTTERFLIES, P73 WEIBULL AC, 2002, THESIS U UPPSALA SWE WHITTAKER RH, 1956, ECOL MONOGR, V26, P1 0921-2973 Landsc. Ecol.ISI:000183770600004Swiss Fed Res Stn Agroecol & Agr FAL, CH-8046 Zurich, Switzerland. Res Inst Organ Agr, CH-5070 Frick, Switzerland. Jeanneret, P, Swiss Fed Res Stn Agroecol & Agr FAL, Reckenholzstr 191, CH-8046 Zurich, Switzerland.English |? *Jeganathan, C. Dash, J. Atkinson, Peter M.2010Characterising the spatial pattern of phenology for the tropical vegetation of India using multi-temporal MERIS chlorophyll data 1125-1141Landscape Ecology257AugbThe annual growth cycles of terrestrial ecosystems are related to long-term regional/global climatic patterns. Understanding vegetation phenology and its spatio-temporal variation is required to reveal and predict ongoing changes in Earth system dynamics. The study attempts to characterize the phenology of the major tropical vegetation types in India, since such information is not yet available for India. Multi-temporal Medium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) data were utilized to derive onset of greenness (OG) and end of senescence (ES) for four major tropical vegetation types. The study found that Fourier-smoothed results using the first four components revealed adequately the annual phenological variation of the natural vegetation types in India. From these smoothed data, inflection points were located iteratively through a spatio-temporal search, spanning over 18 months of 8-day composite data, per pixel such as to derive the OG and ES. The median OG and ES was extracted from the available annual results for the years 2003-04, 2004-05, 2005-06 and 2006-07. The GLC2000 land cover map (1 km spatial resolution) was utilized to determine the locations of the major vegetation types. The percentage of each vegetation type falling beneath a MTCI composite pixel (4.6 km spatial resolution) was calculated. MTCI composite pixels with homogeneity of a parts per thousand yen80% vegetative cover were used for examining pattern of phenology in different regions, different years and at different latitudes. The most common dates for the occurrence of OG for the tropical evergreen, semi-evergreen, moist-deciduous, and dry-deciduous vegetation types were found to be during February-April, January-April, March-May, and February-May, respectively. Similarly, for ES the most common dates were in February-April, January-April, February-April, and December-April, respectively. The phenological pattern was uniquely different for each vegetation type, as expected, and also differed with regions and latitudes. A general trend of early occurrence of OG in the lower latitudes was observed.!://WOS:000279592100011Times Cited: 1 0921-2973WOS:00027959210001110.1007/s10980-010-9490-1<<7|Jelinski, D. E. Wu, J. G.1996HThe modifiable areal unit problem and implications for landscape ecology129-140Landscape Ecology113modifiable areal unit problem; scale; aggregation; zoning systems; spatial analysis; spatial autocorrelation PATTERN; SCALE; VEGETATION; MODELSArticleJun{Landscape ecologists often deal with aggregated data and multiscaled spatial phenomena. Recognizing the sensitivity of the results of spatial analyses to the definition of units for which data are collected is critical to characterizing landscapes with minimal bias and avoidance of spurious relationships. We introduce and examine the effect of data aggregation on analysis of landscape structure as exemplified through what has become known, in the statistical and geographical literature, as the Modifiable Areal Unit Problem (MAW). The MAW applies to two separate, but interrelated, problems with spatial data analysis. The first is the ''scale problem'', where the same set of areal data is aggregated into several sets of larger areal units, with each combination leading to different data values and inferences. The second aspect of the MAW is the ''zoning problem'', where a given set of areal units is recombined into zones that are of the same size but located differently, again resulting in variation in data values and, consequently, different conclusions. We conduct a series of spatial autocorrelation analyses based on NDVI (Normalized Difference Vegetation Index) to demonstrate how the MAW may affect the results of landscape analysis. We conclude with a discussion of the broader-scale implications for the MAUP in landscape ecology and suggest approaches for dealing with this issue.://A1996UX47800001 ISI Document Delivery No.: UX478 Times Cited: 64 Cited Reference Count: 63 Cited References: ALLEN TFH, 1982, HIERARCHY AMRHEIN C, 1989, ACCURACY SPATIAL DAT, P229 BOX EO, 1989, VEGETATIO, V80, P71 BURKE IC, 1991, BIOSCIENCE, V41, P685 CLIFF AD, 1973, SPATIAL AUTOCORRELAT CRESSIE NAC, 1993, STAT SPATIAL DATA CULLINAN VI, 1992, LANDSCAPE ECOL, V7, P211 DEANGELIS DL, 1987, ECOL MONOGR, V57, P1 DEANGELIS DL, 1992, INDIVIDUAL BASED MOD ELLIOTTFISK DL, N AM TERRESTRIAL VEG, P33 ERRINGTON JC, 1973, J ECOL, V61, P99 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FOTHERINGHAM AS, 1989, ACCURACY SPATIAL DAT, P221 FOTHERINGHAM AS, 1991, ENVIRON PLANN A, V23, P1025 FOTHERINGHAM AS, 1993, INT J GEOGR INF SYST, V7, P3 GARDNER RH, 1982, ECOLOGY, V63, P1771 GEHLKE CE, 1934, J AM STAT ASSOC, V29, P169 GREIGSMITH P, 1952, ANN BOT, V16, P293 GREIGSMITH P, 1957, QWUANTITATIVE PLANT GREIGSMITH P, 1979, J ECOL, V67, P755 GREIGSMITH P, 1983, QUANTITATIVE PLANT E HALL FG, 1988, LANDSCAPE ECOLOGY, V2, P3 JELINSKI DE, 1994, ENV INFORMATION MANA, P41 JOHNSON DD, 1987, CANADIAN J REMOTE SE, V13, P68 KERSHAW KA, 1957, ECOLOGY, V38, P291 KERSHAW KA, 1964, QUANTITATIVE DYNAMIC LEGENDRE P, 1989, VEGETATIO, V80, P107 LEVIN SA, 1992, ECOLOGY, V73, P1943 LEVIN SA, 1993, SCALING PHYSL PROCES, P7 LOVELAND TR, 1991, PHOTOGRAMM ENG REM S, V57, P1453 MEENTEMEYER V, 1989, LANDSCAPE ECOLOGY, V3, P163 MILNE BT, 1988, APPL MATH COMPUT, V27, P67 NELLIS MD, 1989, LANDSCAPE ECOLOGY, V2, P93 ONEILL RV, 1986, HIERARCHICAL CONCEPT OPENSHAW S, 1977, ENVIRON PLANN A, P169 OPENSHAW S, 1979, STAT APPL SPATIAL SC, P127 OPENSHAW S, 1981, QUANTITATIVE GEOGRAP, P60 OPENSHAW S, 1984, CATMOG, V38 OPENSHAW S, 1987, INT J GEOGR INF SYST, V1, P35 OPENSHAW S, 1988, PAP REG SCI ASSOC, V64, P95 PACALA SW, 1985, AM NAT, V125, P385 PUTNAM SH, 1989, ENVIRON PLANN A, V21, P27 RASTETTER EB, 1992, ECOL APPL, V2, P55 ROBINSON WS, 1950, AM SOCIOL REV, V15, P351 ROSSWALL T, 1988, SCALES GLOBAL CHANGE ROUGHARDEN J, 1991, ECOLOGY, V72, P45 TAYLOR PJ, 1979, GEOGRAPHY ELECTIONS TOBLER WR, 1989, ACCURACY SPATIAL DAT, P115 TOWNSHEND JRG, 1990, INT J REMOTE SENS, V11, P149 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P235 TURNER SJ, 1981, QUANTITATIVE METHODS, P17 UPTON GJG, 1985, SPATIAL DATA ANAL EX, V1 URBAN DL, 1987, BIOSCIENCE, V37, P119 USHER MB, 1975, J ECOL, V63, P569 WIENS JA, 1989, LANDSCAPE ECOLOGY, V3, P87 WIENS JA, 1993, OIKOS, V66, P369 WILLIAMS E, 1995, IN PRESS PHOTOGRAMME WOODCOCK CE, 1987, REMOTE SENS ENVIRON, V21, P311 WU J, 1992, COENOSES, V7, P137 WU J, 1995, IN PRESS Q REV BIOL WU JG, 1994, ECOL MONOGR, V64, P447 YULE G, 1950, INTRO THEORY STAT 0921-2973 Landsc. Ecol.ISI:A1996UX47800001wJelinski, DE, UNIV NEBRASKA,DEPT FORESTRY FISHERIES & WILDLIFE,INST AGR & NAT RESOURCES,101 PLANT IND,LINCOLN,NE 68583.English? Jenerette, G. Shen, Weijun2012Experimental landscape ecology 1237-1248Landscape Ecology279Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9797-1 0921-297310.1007/s10980-012-9797-1}?NJenerette, G. D. Harlan, S. L. Brazel, A. Jones, N. Larsen, L. Stefanov, W. L.2007vRegional relationships between surface temperature, vegetation, and human settlement in a rapidly urbanizing ecosystem353-365Landscape Ecology223phoenix; urbanization; urban heat island; vegetation; path analysis; remote sensing; census; income; population density HEAT-ISLAND; LAND-USE; ECOLOGICAL-SYSTEMS; LANDSCAPE; CITIES; COVER; SCALE; CITY; URBANIZATION; MICROCLIMATE MarRegional climate change induced by rapid urbanization is responsible for and may result from changes in coupled human-ecological systems. Specifically, the distribution of urban vegetation may be an important intermediary between patterns of human settlement and regional climate spatial variability. To test this hypothesis we identified the relationships between surface temperature, one component of regional climate, vegetation, and human settlement patterns in the Phoenix, AZ, USA region. Combining satellite-derived surface temperature and vegetation data from an early summer day with US Census and topographic data, we found substantial surface temperature differences within the city that correlate primarily with an index of vegetation cover. Furthermore, both of these patterns vary systematically with the social characteristics of neighborhoods through the region. Overall, every $10,000 increase in neighborhood annual median household income was associated with a 0.28 degrees C decrease in surface temperature on an early summer day in Phoenix. Temperature variation within a neighborhood was negatively related to population density. A multivariate model generated using path analysis supports our hypothesis that social impacts on surface temperature occur primarily through modifications of vegetation cover. Higher income neighborhoods were associated with increased vegetation cover and higher density neighborhoods were associated with decreased vegetation variability. These results suggest that settlement patterns in the central Arizona region influence regional climate through multiple pathways that are heterogeneously distributed throughout the city. ://000244455200003 0921-2973ISI:000244455200003|?; Jenerette, G. D. Potere, D.2010NGlobal analysis and simulation of land-use change associated with urbanization657-670Landscape Ecology255A combination of rapid population growth and an accelerating demographic shift from rural to urbanized habitats has resulted in urbanization becoming an increasingly global phenomenon. Two alternate hypotheses describing urban landscape trajectories suggest urbanization is either leading to more homogeneous global patterns or urbanization has dichotomous trajectories of increasing dispersal or coalescence. To better understand the global variation in urban land-cover patterns and trajectories we described the variation in urban landscape structure for 120 cities distributed throughout the world assessed at circa 1990 and 2000. We coupled these data to a low-dimensional neighborhood based model of urban growth using a data-model fusion approach. Trajectories of urban growth were assessed using both the original data and model projections to 2030. The patterns of landscape change were related to both the rate of growth and income. The historical patterns of change showed a trend of increasing landscape complexity and this trend was projected to continue. Urban rate of growth was closely related to the change in several landscape metrics. Income was associated with landscape dynamics and this effect interacted with city size. Large cities were less sensitive to the income effect than small cities. Along with changes to the magnitude of each metric, the overall variation in metrics between years generally exhibited a decrease in variability and this variability was projected to continue decreasing. These findings supported the hypothesis that urban landscapes are becoming more homogeneous and that the dispersal-coalescing dichotomy represent endpoints rather than alternate states of urban growth.!://WOS:000276609800001Times Cited: 0 0921-2973WOS:00027660980000110.1007/s10980-010-9457-2<7Jenerette, G. D. Wu, J. G.2001UAnalysis and simulation of land-use change in the central Arizona-Phoenix region, USA611-626Landscape Ecology167CAP cellular automata genetic algorithm land use change Monte-Carlo urbanization COVER CHANGE MODEL DYNAMICS MANAGEMENT ECOLOGY URBANIZATIONArticleOct@To understand how urbanization has transformed the desert landscape in the central Arizona - Phoenix region of the United States, we conducted a series of spatial analyses of the land-use pattern from 1912-1995. The results of the spatial analysis show that the extent of urban area has increased exponentially for the past 83 years, and this urban expansion is correlated with the increase in population size for the same period of time. The accelerating urbanization process has increased the degree of fragmentation and structural complexity of the desert landscape. To simulate land-use change we developed a Markov-cellular automata model. Model parameters and neighborhood rules were obtained both empirically and with a modified genetic algorithm. Land-use maps for 1975 and 1995 were used to implement the model at two distinct spatial scales with a time step of one year. Model performance was evaluated using Monte-Carlo confidence interval estimation for selected landscape pattern indices. The coarse-scale model simulated the statistical patterns of the landscape at a higher accuracy than the fine-scale model. The empirically derived parameter set poorly simulated land-use change as compared to the optimized parameter set. In summary, our results showed that landscape pattern metrics (patch density, edge density, fractal dimension, contagion) together were able to effectively capture the trend in land-use associated with urbanization for this region. The Markov-cellular automata parameterized by a modified genetic algorithm reasonably replicated the change in land-use pattern.://000172809400003 6 ISI Document Delivery No.: 503QG Times Cited: 37 Cited Reference Count: 50 Cited References: ALLEN TFH, 1982, HIERARCHY PERSPECTIV ASNER GP, 1998, ECOL APPL, V8, P1022 BAKER WL, 1989, LANDSCAPE ECOL, V2, P111 BUCKLAND ST, 1984, BIOMETRICS, V40, P811 CHOMITZ KM, 1996, WORLD BANK ECON REV, V10, P487 CIRET C, 1989, CLIM DYNAM, V14, P409 CLARKE KC, 1997, ENVIRON PLANN B, V24, P247 COHEN JE, 1995, SCIENCE, V269, P341 COSTANZA R, 1994, LANDSCAPE ECOL, V9, P47 DALE VH, 1994, CONSERV BIOL, V8, P1027 DALE VH, 1994, CONSERV BIOL, V8, P196 FAHRIG L, 1994, CONSERV BIOL, V8, P50 FLAMM RO, 1994, LANDSCAPE ECOL, V9, P37 FORMAN RTT, 1998, ANNU REV ECOL SYST, V29, P207 GAMMAGE G, 1999, PHOENIX PERSPECTIVE GLOOR M, 2000, GLOBAL BIOGEOCHEM CY, V14, P407 HILBOURN R, 1997, ECOLOGICAL DETECTIVE HOBBS RJ, 1993, BIOL CONSERV, V64, P193 HOGWEG P, 1988, APPL MATH COMPUT, V27, P81 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 KAUFFMAN SA, 1993, ORIGINS ORDER SELF O KIRTLAND D, 1994, WORLD RESOURCE REV, V6, P206 KNOWLESYANEZ K, 1999, HIST LAND USE TEAM P LAL R, 2000, SOIL SCI, V165, P57 LANDIS JD, 1995, J AM PLANN ASSOC, V61, P438 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MITCHELL M, 1996, INTRO GENETIC ALGORI MITCHELL M, 1999, ANNU REV ECOL SYST, V30, P593 ONEILL RV, 1986, HIERARCHICAL CONCEPT PETERJOHN WT, 1984, ECOLOGY, V65, P1466 PICKETT STA, 1997, URBAN ECOSYSTEMS, V1, P185 POETER EP, 1997, GROUND WATER, V35, P250 REDMAN CL, 1992, HUMAN IMPACT ENV RIEBSAME WE, 1994, BIOSCIENCE, V44, P350 SIMPSON JR, 1993, OUTLOOK AGR, V22, P233 TURNER MG, 1987, LANDSCAPE ECOL, V1, P29 TURNER MG, 1988, APPL MATH COMPUT, V27, P39 TURNER MG, 1989, ECOL MODEL, V48, P1 TURNER MG, 1996, ECOL APPL, V6, P1150 VITOUSEK PM, 1994, ECOLOGY, V75, P1861 WALLIN DO, 1994, ECOL APPL, V4, P569 WARREN A, 1996, J ARID ENVIRON, V32, P75 WEAR DN, 1996, ECOL APPL, V6, P1173 WEAR DN, 1998, ECOSYSTEMS, V1, P575 WITH KA, 1995, ECOLOGY, V76, P2446 WU F, 1998, J ENVIRON MANAGE, V53, P293 WU J, 1997, GEOGRAPHIC INFORMATI, V3, P30 WU J, 1999, CANADIAN J REMOTE SE, V25, P367 WU JG, 1993, ECOL MODEL, V65, P221 WU JG, 1995, Q REV BIOL, V70, P439 0921-2973 Landsc. Ecol.ISI:000172809400003vArizona State Univ, Dept Biol, Tempe, AZ 85287 USA. Jenerette, GD, Arizona State Univ, Dept Biol, Tempe, AZ 85287 USA.English<7Jennings, D. B. Jarnagin, S. T.2002Changes in anthropogenic impervious surfaces, precipitation and daily streamflow discharge: a historical perspective in a mid-atlantic subwatershed471-489Landscape Ecology175historical aerial photography impervious surfaces precipitation streamflow urban landscape change UNITED-STATES URBANIZATION FISH FREQUENCY VARIABILITY HABITAT RUNOFF IMPACT TRENDS AREAArticleOctLAerial photography provides a historical vehicle for determining long-term urban landscape change and, with concurrent daily streamflow and precipitation records, allows the historical relationship of anthropogenic impervious surfaces and streamflow to be explored. Anthropogenic impervious surface area in the upper Accotink Creek subwatershed (near Annandala, Virginia, USA) was mapped from six dates of rectified historical aerial photography ranging from 1949 to 1994. Results show that anthropogenic impervious surface area has grown from approximately 3% in 1949 to 33% in 1994. Coincident to this period, analysis of historical mean daily streamflow shows a statistically significant increase in the streamflow discharge response ( per meter of precipitation) associated with "normal" and "extreme" daily precipitation levels. Significant changes were also observed in the frequency of daily streamflow discharge at given volumes above and below the historical daily mean. Simultaneously, the historical magnitude, frequency and pattern of precipitation values greater than or equal to 0 mm, greater than or equal to 6.0 mm and greater than or equal to 35.0 mm show either no statistically significant change or influence on streamflow. Historical changes in streamflow in this basin appear to be related to increases in anthropogenic impervious surface cover. Historical aerial photography is a viable tool for revealing long-term landscape and ecosystem relationships, and allows landscape investigations to extend beyond the temporal and spatial constraints of historical satellite remote sensing data.://000179388800008 ISI Document Delivery No.: 617YP Times Cited: 11 Cited Reference Count: 41 Cited References: *NAT CLIM DAT CTR, 1998, TD3200 NCDC *US EPA, 1994, QUAL OUR NAT WAT 199 *US GEOL SURV, 1996, NAT MAPP PROGR STAND *US GEOL SURV, 2001, WAT RES US ACC CREEK ALLEY WM, 1983, J HYDRAUL ENG-ASCE, V109, P313 ANDERSON DG, 1968, 2001C US GEOL SURV, P22 BIGGS BJF, 1995, FRESHWATER BIOL, V33, P419 BOOTH DB, 1990, WATER RESOUR BULL, V26, P407 BOOTH DB, 1997, J AM WATER RESOUR AS, V33, P1077 CAIRNS J, 1995, STORMWATER RUNOFF RE, P9 CONGALTON RG, 1999, ASSESSING ACCURACY R DINICOLA RS, 1989, 894052 US GEOL SURV GALLI J, 1991, THERMAL IMPACTS ASS GRAF WL, 1975, WATER RESOUR RES, V11, P690 HAACK BN, 1997, MANUAL PHOTOGRAPHIC, P517 HAMMER TR, 1972, WATER RESOUR RES, V8, P1530 HENSHAW PC, 2000, J AM WATER RESOUR AS, V36, P1219 HOLLIS GE, 1975, WATER RESOUR RES, V11, P431 JAMES W, 1994, STORMWATER RUNOFF RE, P103 JENSEN JR, 1983, MANUAL REMOTE SENSIN, V2, P1571 JENSEN JR, 1996, INTRO DIGITAL IMAGE JONES RC, 1987, WATER RESOURCES B, V23, P1047 KARL TR, 1989, CLIMATIC CHANGE, V15, P423 KARL TR, 1995, NATURE, V377, P217 KARL TR, 1998, B AM METEOROL SOC, V79, P231 KENNEN JG, 1999, J AM WATER RESOUR AS, V35, P939 KLEIN RD, 1979, WATER RESOURCES B, V15, P948 LEOPOLD LB, 1968, 554 US GEOL SURV LEOPOLD LB, 1973, GEOL SOC AM BULL, V84, P1845 LIGHT DL, 1993, PHOTOGRAMM ENG REM S, V59, P61 LIMBURG KE, 1990, ECOLOGY, V71, P1238 MAY CW, 1997, WATERSHED PROTECTION, V2, P483 MOSCRIP AL, 1997, J AM WATER RESOUR AS, V33, P1289 POFF NL, 1995, ECOLOGY, V76, P606 RAYYAN A, 2001, COMMUNICATION ROSE S, 2001, HYDROL PROCESS, V15, P1441 SCHUELER T, 1994, WATERSHED PROTECTION, V1, P100 SLONECKER E, 2001, REMOTE SENSING REV, V20, P227 WANG LZ, 2000, J AM WATER RESOUR AS, V36, P1173 WANG LZ, 2001, ENVIRON MANAGE, V28, P255 WEAVER LA, 1994, T AM FISH SOC, V123, P162 0921-2973 Landsc. Ecol.ISI:000179388800008bUS EPA, Reston, VA 20192 USA. Jennings, DB, US EPA, 12201 Sunrise Valley Dr, Reston, VA 20192 USA.English<77Jennings, M. D.20003Gap analysis: concepts, methods, and recent results5-20Landscape Ecology151biodiversity conservation large-area mapping gap analysis RESERVE SELECTION BIODIVERSITY DIVERSITY IDAHO MANAGEMENT VEGETATION LANDSCAPES HOTSPOTS FUTURE USAArticleJanRapid progress is being made in the conceptual, technical, and organizational requirements for generating synoptic multi- scale views of the earth's surface and its biological content. Using the spatially comprehensive data that are now available, researchers, land managers, and land-use planners can, for the first time, quantitatively place landscape units - from general categories such as 'Forests' or 'Cold-Deciduous Shrubland Formation' to more categories such as 'Picea glauca-Abies balsamea-Populus spp. Forest Alliance' - in their large-area contexts. The National Gap Analysis Program (GAP) has developed the technical and organizational capabilities necessary for the regular production and analysis of such information. This paper provides a brief overview of concepts and methods as well as some recent results from the GAP projects. Clearly, new frameworks for biogeographic information and organizational cooperation are needed if we are to have any hope of documenting the full range of species occurrences and ecological processes in ways meaningful to their management. The GAP experience provides one model for achieving these new frameworks.://000083830400002 ISI Document Delivery No.: 258GN Times Cited: 51 Cited Reference Count: 80 Cited References: *ESA VEG PAN, UNPUB IN STAND CLASS *FGDC, 1997, VEG INF CLASS STAND *GAP AN PROGR, 1998, HDB COND GAP AN *NAT CONS, 1996, SEL NAT CONS SCI DAT ALLEN CR, 1998, GAP ANAL B, V7 ALLEN TF, 1982, HIERARCHY PERSPECTIV AUSTIN MP, 1991, NATURE CONSERVATION, P37 BAILEY RG, 1995, DESCRIPTION ECOREGIO BOURGERON PS, 1994, PRELIMINARY VEGETATI BURLEY FW, 1988, BIODIVERSITY, P227 CAICCO SL, 1995, CONSERV BIOL, V9, P498 CONGALTON RG, 1991, REMOTE SENS ENVIRON, V37, P35 COOPERRIDER AY, 1986, INVENTORY MONITORING CRIST P, 1997, HDB CONDUCTING GAP A CRIST P, 1998, HDB CONDUCTING GAP A CRIST PJ, 1998, HDB CONDUCTING GAP A CSUTI B, 1996, GAP ANAL LANDSCAPE A CSUTI B, 1997, BIOL CONSERV, V80, P83 CSUTI B, 1998, HDB CONDUCTING GAP A DAVIS FW, 1990, INT J GEOGR INF SYST, V4, P55 DAVIS FW, 1991, GEOGRAPHIC INFORMATI DRAKE J, 1997, ALLIANCE LEVEL CLASS DUEVER LC, 1990, NEW YORK STATE MUSEU, V471, P22 EVE M, 1998, GAP LAND COVER MAPPI FENNER F, 1975, 19 AUSTR AC SCI FERTIG W, 1998, GAP ANAL B, V7 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FRANKLIN JF, 1993, ECOL APPL, V3, P202 GIBBONS JW, 1997, ENVIRON MANAGE, V21, P259 GROSSMAN DH, 1998, INT CLASSIFICATION E, V1 HALBERT SE, 1995, INSECTS CHANGING ENV, P499 JENNINGS MD, 1993, GAP ANAL TECHNICAL B, V2 JENNINGS MD, 1995, WILDLIFE SOC B, V23, P658 JENNINGS MD, 1996, GAP ANAL B, V5 JENNINGS MD, 1996, GAP ANAL LANDSCAPE A, P71 JENNINGS MD, 1996, GAP ANAL PROGR 1995 JENNINGS MD, 1997, GAP ANAL B, V6 KAREIVA P, 1993, NATURE, V365, P292 KEYS J, 1995, ECOLOGICAL UNITS E U LAWTON JH, 1995, EXTINCTION RATES LILLESAND TM, 1987, REMOTE SENSING IMAGE LOUCKS OL, 1995, B ECOL SOC AM, V76, P221 LOUCKS OL, 1996, B ECOL SOC AM, V77, P75 LUGO AE, 1988, BIODIVERSITY, P58 MANN CC, 1995, NOAHS CHOICE FUTURE MARGULES CR, 1991, NATURE CONSERVATION MCNAB WH, 1994, ADM PUBLICATION MERRILL EH, 1996, WYOMING GAP ANAL PRO MERRILL T, 1995, ENVIRON MANAGE, V19, P815 NOSS RF, 1987, BIOL CONSERV, V41, P11 NOSS RF, 1990, CONSERV BIOL, V4, P355 NOSS RF, 1991, PROTECTING HABITATS NOSS RF, 1991, REPORT FUND ANIMALS NOSS RF, 1994, SAVING NATURES LEGAC NOSS RF, 1995, 28 NAT BIOL SERV ONEILL RV, 1986, MONOGRAPHS POPULATIO ONEILL RV, 1996, GAP ANAL LANDSCAPE A, P7 PIMM SL, 1995, SCIENCE, V269, P347 PRENDERGAST JR, 1993, NATURE, V365, P335 PRESSEY RL, 1993, TRENDS ECOL EVOL, V8, P124 REID M, UNPUB CLASSIFICATION REID WV, 1998, TRENDS ECOL EVOL, V13, P275 SCOTT JM, 1987, BIOSCIENCE, V37, P782 SCOTT JM, 1993, WILDLIFE MONOGRAPHS, V123 SCOTT JM, 1998, ANN MO BOT GARD, V85, P34 SLAYMAKER DM, 1996, GAP ANAL LANDSCAPE A, P87 SMITH EL, 1996, ENDANGERED SPECIES B, V21, P8 SMITH KG, 1998, STATE WIDE BIODIVERS SNEDDON L, 1994, CLASSIFICATION DESCR SOWA SP, 1998, GAP ANAL B, V7 SPECHT RL, 1974, AUSTR J BOT SERIES S, V7 STOMS DM, 1994, HDB GAP ANAL STOMS DM, 1998, GREAT BASIN NAT, V58, P199 TEAR TH, 1993, SCIENCE, V262, P976 TERBORGH J, 1989, HAVE ALL BIRDS GONE THOMPSON BC, 1996, GAP ANAL BIODIVERSIT WEAKLEY AS, 1997, ALLIANCE LEVEL CLASS WHITTAKER RH, 1973, HDB VEGETATION SCI 5, P387 WRIGHT RG, UNPUB IDENTIFYING UN WRIGHT RG, 1994, CONSERV BIOL, V8, P207 0921-2973 Landsc. Ecol.ISI:000083830400002US Geol Survey, Natl Gap Anal Program, Moscow, ID 83843 USA. Jennings, MD, US Geol Survey, Natl Gap Anal Program, 530 S Asbury St,Suite 1, Moscow, ID 83843 USA.English <7^ =Jiang, J. DeAngelis, D. L. Smith, T. J. Teh, S. Y. Koh, H. L.2012Spatial pattern formation of coastal vegetation in response to external gradients and positive feedbacks affecting soil porewater salinity: a model study109-119Landscape Ecology271individual-based model positive feedback environmental gradient ecotone vegetation aggregation mangrove vegetation treeline ecotones mangrove forests simulation-model inland mangroves dynamics florida competition everglades australia habitatsJanCoastal vegetation of South Florida typically comprises salinity-tolerant mangroves bordering salinity-intolerant hardwood hammocks and fresh water marshes. Two primary ecological factors appear to influence the maintenance of mangrove/hammock ecotones against changes that might occur due to disturbances. One of these is a gradient in one or more environmental factors. The other is the action of positive feedback mechanisms, in which each vegetation community influences its local environment to favor itself, reinforcing the boundary between communities. The relative contributions of these two factors, however, can be hard to discern. A spatially explicit individual-based model of vegetation, coupled with a model of soil hydrology and salinity dynamics is presented here to simulate mangrove/hammock ecotones in the coastal margin habitats of South Florida. The model simulation results indicate that an environmental gradient of salinity, caused by tidal flux, is the key factor separating vegetation communities, while positive feedback involving the different interaction of each vegetation type with the vadose zone salinity increases the sharpness of boundaries, and maintains the ecological resilience of mangrove/hammock ecotones against small disturbances. Investigation of effects of precipitation on positive feedback indicates that the dry season, with its low precipitation, is the period of strongest positive feedback.://000298228300009-864HI Times Cited:1 Cited References Count:40 0921-2973Landscape EcolISI:000298228300009lDeAngelis, DL Univ Miami, Dept Biol, Coral Gables, FL 33124 USA Univ Miami, Dept Biol, Coral Gables, FL 33124 USA Univ Miami, Dept Biol, Coral Gables, FL 33124 USA US Geol Survey, SE Ecol Sci Ctr, St Petersburg, FL 33701 USA Univ Sains Malaysia, Sch Math Sci, Minden 11800, Penang, Malaysia Univ Sains Malaysia, Sch Civil Engn, Nibong Tebal 14300, Penang, MalaysiaDOI 10.1007/s10980-011-9689-9English <7dJin, K. R. Wu, Y. G.1997*Boundary-fitted grid in landscape modeling19-26Landscape Ecology121landscape modeling; curvilinear coordinates; boundary-fitted grid; spatial modeling; elliptic partial differential equation POPULATION-DYNAMICS; PATTERNArticleFebQLandscape modeling requires the delineation of system boundaries and interior features. Quite often, these components are complex and difficult to accurately represent. A rectangular grid is used to represent the study and adjacent non-study areas in most cases. When the non-study area occupies a large portion of the grid, computer memory is wasted, and computational time increases. An elliptical grid generator for non-orthogonal curvilinear coordinates is used to generate a boundary-fitted grid for a landscape model. In a boundary-fitted grid coordinate system, one coordinate axis follows the landscape domain boundary and is non-orthogonal to the second axis. The boundary-fitted grid uses elliptic partial differential equations to distribute grid points inside the landscape domain. Although the boundary-fitted grid follows the domain boundary, the grid pattern and point allocation remain structured. Thus, a landscape model can use a boundary-fitted grid without changing the model's data structure or the computational scheme. In this study, a boundary-fitted grid and a raster-based grid were applied to the Everglades Landscape Fire Model. Use of the boundary-fitted grid decreased model simulation time by about one fifth and computer storage by 58% relative to the raster-based grid. Also, the linear characteristics of interior geographical features such as rivers and airboat trails were preserved by the boundary-fitted grid, but not by the raster-based grid. This preservation provided a more reasonable base map for simulating ecological processes, such as fire across heterogenous landscapes.://A1997XQ44800003 ISI Document Delivery No.: XQ448 Times Cited: 2 Cited Reference Count: 25 Cited References: ANDERSON DA, 1984, COMPUTATIONAL FLUID EISEMAN PR, 1987, COMPUT METHOD APPL M, V64, P321 FONS WL, 1946, J AGR RES, V72, P93 HARGROVE WW, 1994, UNPUB ECOLOGICAL MOD HOFFMAN KA, 1993, COMPUTATIONAL FLUID, V1 HOFFMAN KA, 1993, COMPUTATIONAL FLUID, V2 HOLMES EE, 1994, ECOLOGY, V75, P17 JENSEN JR, 1995, PHOTOGRAMM ENG REM S, V61, P199 JIN KR, 1991, NGA8155 NASA MARSH S JIN KR, 1993, APPL 3D ADAPTIVE GRI, P394 LI SX, 1987, COMMUN ACM, V30, P621 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 MOLOFSKY J, 1994, ECOLOGY, V75, P30 PACALA SW, 1990, ECOL MONOGR, V60, P113 ROTHERMEL RC, 1972, INT115 USDA FOR SERV SHYY W, 1991, APPL NUMER MATH, V7, P263 THOMPSON JF, 1985, NUMERICAL GRID GENER TILMAN D, 1994, ECOLOGY, V75, P2 TURNER MG, 1994, ECOL APPL, V4, P472 VANCAMP KE, 1992, C USERS J, V10, P17 WARSI ZUA, 1982, NUMERICAL GRID GENER, P41 WU Y, 1991, THESIS U WYOMING LAR WU Y, 1996, IN PRESS ECOLOGICAL WU Y, 1997, IN PRESS ECOLOGICAL WYLIE CR, 1982, ADV ENG MATH 0921-2973 Landsc. Ecol.ISI:A1997XQ44800003_Jin, KR, S FLORIDA WATER MANAGEMENT DIST,ECOSYST RESTORAT DEPT,POB 24680,W PALM BEACH,FL 33416.Englishq<7rVJobin, B. Beaulieu, J. Grenier, M. Belanger, L. Maisonneuve, C. Bordage, D. Filion, B.2003PLandscape changes and ecological studies in agricultural regions, Quebec, Canada575-590Landscape Ecology186agricultural landscapes conservation ecoregion landscape delineation NABCI Quebec wildlife habitat ST-LAWRENCE VALLEY LAND CLASSIFICATION POPULATION TRENDS INTENSIFICATION BIRDS GRASSLAND EUROPE AREAArticleRMost landscape definitions in the western world are based on soil, climatic, or physiographic features and do not integrate humans as an integral part of the landscape. We present an approach where landscape types have been delineated in southern Quebec, Canada based on current land use where anthropogenic and agricultural activities are concentrated as a practical application of the holistic approach in landscape definition. Landsat-TM satellite images were classified and the 27 habitat classes were regrouped into 5 general land cover classes (cash crop, dairy farming, forest, anthropogenic, wetlands) and overlaid onto soil landscape polygons to characterize natural boundary units. Cluster analyses were used to aggregate these polygons into seven agricultural types of landscape forming a gradient from urban and high-intensity cash crop farming activities to landscapes dominated by a mosaic of agriculture and forested areas. Multivariate analyses of raw data and of socio-economic and farming practices variables were used to describe the defined types of landscape and these were projected over three established land classification systems of southern Quebec (Canadian ecoregions, North American Bird Conservation Initiative regions and Corn Heat Unit regions) to compare their similarity in terms of land cover and for planning of future ecological studies. Because agricultural landscapes are highly dynamic, they are bound to undergo changes in the near future. Our landscape delineation may serve as an experimental setup where landscape dynamics and wildlife populations and community structures could be monitored. Because the information we used to delineate and characterize agricultural landscape types is readily available in other countries, our approach could easily be adapted to similar data sources under and a wide variety of landscape types.://000185827300003 ISI Document Delivery No.: 730JH Times Cited: 6 Cited Reference Count: 51 Cited References: 2000, N AM BIRD CONSERVATI, P38 *CTR LAND BIOL RES, 1996, SOIL LANDSC CAN V 2 *MAP CORP, 2002, MAP PROF US GUID V7 *SAS I INC, 1988, SAS STAT US GUID REL *STAT CAN, 1997, AGR PROF QUEB CENS C *STAT CAN, 1997, HIST OV CAN AGR, P253 *WILDL HAB CAN, 2001, STAT WILDL HAB CAN 2 ASKINS RA, 1993, CURR ORNITHOL, V11, P1 BAILEY RG, 1983, ENVIRON MANAGE, V7, P365 BARRETT GW, 1992, J SUSTAIN AGR, V2, P83 BASTIAN O, 2001, LANDSCAPE ECOL, V16, P757 BELANGER L, 2002, LANDSCAPE ECOL, V17, P495 BELANGER L, 2002, REPORT HABITAT LAND BERNERT JA, 1997, ENVIRON MANAGE, V21, P405 BOOTSMA A, 1999, 991396 TECHN B CONTR, P25 BUNCE RGH, 1996, J BIOGEOGR, V23, P625 BUNCE RGH, 1996, J ENVIRON MANAGE, V47, P37 BUREL F, 1998, ACTA OECOL, V19, P47 BUTTNER G, 2002, 89 EUR ENV AG CANTERS KJ, 1991, LANDSCAPE ECOL, V5, P145 DONALD PF, 2001, P ROY SOC LOND B BIO, V268, P25 DRAMSTAD WE, 2002, J ENVIRON MANAGE, V64, P49 DUCRUC JP, 1994, LANDSCAPE ECOLOGY LA, P45 DUNN EH, 2000, 216 CWS, P40 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY, P632 FRANKLIN SE, 2000, FOREST CHRON, V76, P877 FREEMARK KE, 1995, ECOLOGY MANAGEMENT N, P381 GILPIN M, 1992, AGR ECOSYST ENVIRON, V42, P27 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 JOBIN B, 1996, AGR ECOSYST ENVIRON, V57, P103 JONGMAN RHG, 1995, DATA ANAL COMMUNITY, P299 KELLY WR, 1992, GEOSTANDARD NEWSLETT, V16, P3 LAMBIN EF, 2000, AGR ECOSYST ENVIRON, V82, P321 LEGENDRE P, 1998, NUMERICAL ECOLOGY, P853 LUQUE SS, 1994, LANDSCAPE ECOL, V9, P287 MAISONNEUVE C, 2001, E LOWLANDS INITIATIV, P26 MCDONNELL MJ, 1993, HUMAN COMPONENTS ECO PAQUETTE S, 2001, LANDSCAPE RES, V26, P367 PARODY JM, 2001, GLOBAL ECOL BIOGEOGR, V10, P305 PETERSON CH, 1993, AUSTR J ECOLOGY, V18, P2152 ROHLF FJ, 1998, NTSYSPC NUMERICAL TA RUBEC CDA, 1992, LANDSCAPE APPROACHES, P61 RUZICKA M, 1982, EKOLOGIA, V1, P297 SABINS FF, 1987, REMOTE SENSING PRINC, P449 STOATE C, 2001, J ENVIRON MANAGE, V63, P337 STORY M, 1986, PHOTOGRAMM ENG REM S, V52, P397 TERBRAAK CJF, 1998, CANOCO REFERENCE MAN, P352 TURNER MG, 1990, PHOTOGRAMM ENG REM S, V56, P379 WARNER RE, 1994, CONSERV BIOL, V8, P147 WU JG, 2002, LANDSCAPE ECOL, V17, P355 ZHENG DL, 1997, LANDSCAPE ECOL, V12, P241 0921-2973 Landsc. Ecol.ISI:0001858273000039Environm Canada, Canadian Wildlife Serv, St Foy, PQ G1V 4H5, Canada. Canards Illimites Canada, Quebec City, PQ G2J 1C2, Canada. Soc Faune & Parcs Quebec, Direct Rech Faune, Quebec City, PQ G1R 5V7, Canada. Jobin, B, Environm Canada, Canadian Wildlife Serv, 1141 Route Eglise,POB 10100, St Foy, PQ G1V 4H5, Canada.English?John, D. Waldron20032Book review, Tourism, Biodiversity and Information212-214Landscape Ecology182 book review*http://dx.doi.org/10.1023/A:1024467822301 10.1023/A:1024467822301 This revised version was published online in August 2006 with corrections to the Cover Date John D. Waldron Email: johndwaldron@yahoo.com John D. Waldron1 (1) Ecosystems Research Group School of Plant biology (Botany), University of Western Australia, Crawley, WA, 6009, Australia  ?]2Johnson, A.R. J.A. Wiens B.T. Milne T.O. Crist1992DAnimal movements and population-dynamics in heterogeneous landscapes63-75Landscape Ecology71Pdiffusion, fractal geometry, landscapes, microlandscapes, metapopulations, scale5Organisms respond to environmental heterogeneity at different scales and in different ways. These differences are consequences of how the movement characteristics of animals - their movement rates, directionality, turning frequencies, and turning angles - interact with patch and boundary features in landscape mosaics. The interactions of movement patterns with landscape features in turn produce spatial patterns in individual space-use, population dynamics and dispersion, gene flow, and the redistribution of nutrients and other materials. We describe several theoretical approaches for modeling the diffusion, foraging behavior, and population dynamics of animals in heterogeneous landscapes, including: (1) scaling relationships derived from percolation theory and fractal geometry, (2) extensions of traditional patch-based metapopulation models, and (3) individual-based, spatially explicit models governed by local rules. We conclude by emphasizing the need to couple theoretical models with empirical studies and the usefulness of ‘microlandscape’ investigations.|<7TJohnson, C. J. Boyce, M. S. Mulders, R. Gunn, A. Gau, R. J. Cluff, H. D. Case, R. L.2004bQuantifying patch distribution at multiple spatial scales: applications to wildlife-habitat models869-882Landscape Ecology198Canadian arctic; habitat; hierarchy; landscape pattern; local quadrat variance; resource selection; scale PLANT-COMMUNITIES; WOODLAND CARIBOU; HIERARCHICAL ANALYSIS; GRIZZLY BEARS; LANDSCAPE; SELECTION; PATTERN; ECOLOGY; CONSERVATION; RICHNESSArticle*Multiscale analyses are widely employed for wildlife-habitat studies. In most cases, however, each scale is considered discrete and little emphasis is placed on incorporating or measuring the responses of wildlife to resources across multiple scales. We modeled the responses of three Arctic wildlife species to vegetative resources distributed at two spatial scales: patches and collections of patches aggregated across a regional area. We defined a patch as a single or homogeneous collection of pixels representing I of 10 unique vegetation types. We employed a spatial pattern technique, three-term local quadrat variance, to quantify the distribution of patches at a larger regional scale. We used the distance at which the variance for each of 10 vegetation types peaked to define a moving window for calculating the density of patches. When measures of vegetation patch and density were applied to resource selection functions, the most parsimonious models for wolves and grizzly bears included covariates recorded at both scales. Seasonal resource selection by caribou was best described using a model consisting of only regional scale covariates. Our results suggest that for some species and environments simple patch-scale models may not capture the full range of spatial variation in resources to which wildlife may respond. For mobile animals that range across heterogeneous areas we recommend selection models that integrate resources occurring at a number of spatial scales. Patch density is a simple technique for representing such higher-order spatial patterns.://000226268600005 ISI Document Delivery No.: 886YI Times Cited: 4 Cited Reference Count: 66 Cited References: *EC STRAT WORK GRO, 1996, NAT EC FRAM CAN ALLEN TFH, 1982, HIERARCHY PERSPECTIV ANDERSON DR, 2000, J WILDLIFE MANAGE, V64, P912 ANDRZEJEWSKI R, 2002, ACTA THERIOL S1, V47, P81 APPS CD, 2001, J WILDLIFE MANAGE, V65, P65 ARTHUR SM, 1996, ECOLOGY, V77, P215 BAKKER KK, 2002, CONSERV BIOL, V16, P1638 BALLARD WB, 1995, OCCASIONAL PUBLICATI, V35, P461 BASKENT EZ, 1995, CAN J FOREST RES, V25, P1830 BENGTSSON J, 1994, TRENDS ECOL EVOL, V9, P246 BERGIN TM, 1992, CONDOR, V94, P903 BLUNDELL GM, 2001, ECOL MONOGR, V71, P469 CARROLL C, 2001, ECOL APPL, V11, P961 COMPTON BW, 2002, ECOLOGY, V83, P833 CSILLAG F, 2000, B ECOL SOC AM, V81, P230 DALE MRT, 1990, CAN J BOT, V68, P149 DALE MRT, 1998, J VEG SCI, V9, P805 DALE MRT, 1999, SPATIAL PATTERN ANAL DALE MRT, 2000, LANDSCAPE ECOL, V15, P467 DALE MRT, 2002, ECOGRAPHY, V25, P558 DIAZ S, 1998, J VEG SCI, V9, P113 DUNGAN JL, 2002, ECOGRAPHY, V25, P626 FERNANDEZ N, 2003, ECOL APPL, V13, P1310 FRANCIS AP, 2003, AM NAT, V161, P523 GUNN A, 2001, SEASONAL MOVEMENTS S GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P583 HALL LS, 1997, WILDLIFE SOC B, V25, P173 HARDIN J, 2001, GEN LINEAR MODELS EX HOBBS R, 1997, LANDSCAPE URBAN PLAN, V37, P1 HOSMER DW, 2000, APPL LOGISTIC REGRES HUSTON MA, 1999, OIKOS, V86, P393 JOHNSON CJ, 2001, OECOLOGIA, V127, P590 JOHNSON CJ, 2002, ECOL APPL, V12, P1840 JOHNSON CJ, 2002, J ANIM ECOL, V71, P225 JOHNSON CJ, 2004, IN PRESS CANADIAN EN JOHNSON DH, 1980, ECOLOGY, V61, P65 KIE JG, 2002, ECOLOGY, V83, P530 LEVIN SA, 1992, ECOLOGY, V73, P1943 MACE RD, 1999, CONSERV BIOL, V13, P367 MANLY BFJ, 2002, RESOURCE SELECTION A MATTHEWS S, 2001, VEGETATION CLASSIFIC MCGARIGAL K, 1995, PNW351 USDA FOR SERV MCINTYRE NE, 2000, LANDSCAPE ECOL, V15, P313 MCLOUGHLIN PD, 2002, OECOLOGIA, V132, P102 MENARD S, 1995, SAGE U PAPER SERIES MERRILL T, 1999, BIOL CONSERV, V87, P231 MLADENOFF DJ, 1995, CONSERV BIOL, V9, P279 MLADENOFF DJ, 1999, APACK ANAL SOFTWARE MORRIS DW, 1987, ECOLOGY, V68, P362 PALMER MW, 1988, VEGETATIO, V75, P91 PASCUAL M, 1999, ECOLOGY, V80, P2225 PAUSAS JG, 2001, J VEG SCI, V12, P153 PENDERGAST JF, 1996, INT STAT REV, V64, P89 PERRY JN, 2002, ECOGRAPHY, V25, P578 PLOTNICK RE, 1993, LANDSCAPE ECOL, V8, P201 RETTIE WJ, 2000, ECOGRAPHY, V23, P466 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 RIPLEY BD, 1978, J ECOL, V66, P965 ROSENBERG MS, 2002, PASSAGE PATTERN ANAL SAAB V, 1999, ECOL APPL, V9, P135 SCHAEFER JA, 1995, ECOGRAPHY, V18, P333 SENFT RL, 1987, BIOSCIENCE, V37, P789 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P245 VISWANATHAN GM, 1996, NATURE, V381, P413 WALTON LR, 2001, J MAMMAL, V82, P867 WIENS JA, 1989, FUNCT ECOL, V3, P385 0921-2973 Landsc. Ecol.ISI:000226268600005Univ Alberta, Dept Biol Sci, Edmonton, AB T6G 2E9, Canada. Govt NW Terr, Dept Resources Wildlife & Econ Dev, Yellowknife, NT X1A 2P9, Canada. Johnson, CJ, Univ No British Columbia, Ecosyst Sci & Management Program, 3333 Univ Way, Prince George, BC V2N 4Z9, Canada. johnsoch@unbc.caEnglish i<7=(Johnson, G. D. Myers, W. L. Patil, G. P.1999\Stochastic generating models for simulating hierarchically structured multi-cover landscapes413-421Landscape Ecology145kcategorical raster maps hierarchical landscape modeling landscape ecology spatial pattern analysis PATTERNSArticleOctFor simulating hierarchically structured raster maps of landscapes that consist of multiple land cover types, we extend the concept of neutral landscape models to provide a general Markovian model. A stochastic transition matrix provides the probability rules that govern landscape fragmentation processes by assigning finer resolution land cover categories, given coarser resolution categories. This matrix can either be changed or remain the same at different resolutions. The probability rules may be defined for simulating properties of an actual landscape or they may be specified in a truly neutral manner to evaluate the effects of particular transition probability rules. For illustration, model parameters are defined heuristically to simulate properites of actual watershed-delineated landscapes in Pennsylvania. Three landscapes were chosen; one is mostly forested, one is in a transitional state between mostly forested and a mixture of agriculture, urban and suburban land, while the third is fully developed with only remnant forest patches that are small and disconnected. For each landscape type, a small sample of raster maps are simulated in a Monte Carlo fashion to illustrate how an empirical distribution of landscape measurements can be obtained.://000082510000001 ISI Document Delivery No.: 234XQ Times Cited: 9 Cited Reference Count: 21 Cited References: DUBES RC, 1989, J APPL STAT, V16, P131 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GARDNER RH, 1992, ECOL STUD, V92, P259 GARDNER RH, 1993, HUMANS COMPONENTS EC, P208 JOHNSON GD, 1998, ECOSYSTEM HLTH, V4 JOHNSON GM, 1995, EARTH ISL J, V10, P2 KOTLIAR NB, 1990, OIKOS, V59, P253 LAVOREL S, 1993, OIKOS, V67, P521 LAVOREL S, 1995, LANDSCAPE ECOL, V10, P277 LI HB, 1993, LANDSCAPE ECOL, V8, P155 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MYERS W, 1997, ER9710 PENNS STAT U ONEILL RV, 1989, LANDSCAPE ECOL, V3, P193 ONEILL RV, 1992, LANDSCAPE ECOL, V7, P55 PEARSON SM, 1997, WILDLIFE LANDSCAPE E, P215 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 RIITTERS KH, 1996, LANDSCAPE ECOL, V11, P197 RIPLEY BD, 1988, STAT INFERENCE SPATI RITCHIE ME, 1997, WILDLIFE LANDSCAPE E, P160 STAUFFER D, 1985, INTRO PERCOLATION TH WITH KA, 1997, CONSERV BIOL, V11, P1069 0921-2973 Landsc. Ecol.ISI:000082510000001Penn State Univ, Dept Stat, Ctr Stat Ecol & Environm Stat, University Pk, PA 16802 USA. Johnson, GD, Penn State Univ, Dept Stat, Ctr Stat Ecol & Environm Stat, University Pk, PA 16802 USA.English'<74Johnson, G. D. Myers, W. L. Patil, G. P. Taillie, C.2001aCharacterizing watershed-delineated landscapes in Pennsylvania using conditional entropy profiles597-610Landscape Ecology167conditional entropy profiles landscape comparisons landscape ecology landscape monitoring landscape pattern measurements watersheds SPATIAL-RESOLUTION PREDICTABILITY PATTERNS FORESTSArticleOct When the objective is to characterize landscapes with respect to relative degree and type of forest (or other critical habitat) fragmentation, it is difficult to decide which variables to measure and what type of discriminatory analysis to apply. It is also desirable to incorporate multiple measurement scales. In response, a new method has been developed that responds to changes in both the marginal and spatial distributions of land cover in a raster map. Multiscale features of the map are captured in a sequence of successively coarsened resolutions based on the random filter for degrading raster map resolutions. Basically, the entropy of spatial pattern associated with a particular pixel resolution is calculated, conditional on the pattern of the next coarser 'parent' resolution. When the entropy is plotted as a function of changing resolution, we obtain a simple two-dimensional graph called a 'conditional entropy profile', thus providing a graphical visualization of multi-scale fragmentation patterns. Using eight-category raster maps derived from 30-meter resolution LANDSAT Thematic Mapper images, the conditional entropy profile was obtained for each of 102 watersheds covering the state of Pennsylvania (USA). A suite of more conventional single-resolution landscape measurements was also obtained for each watershed using the FRAGSTATS program. After dividing the watersheds into three major physiographic provinces, cluster analysis was performed within each province using various combinations of the FRAGSTATS variables, land cover proportions and variables describing the conditional entropy profiles. Measurements of both spatial pattern and marginal land cover proportions were necessary to clearly discriminate the watersheds into distinct clusters for most of the state; however, the Piedmont province essentially only required the land cover proportions. In addition to land cover proportions, only the variables describing a conditional entropy profile appeared to be necessary for the Ridge and Valley province, whereas only the FRAGSTATS variables appeared to be necessary for the Appalachian Plateaus province. Meanwhile, the graphical representation of conditional entropy profiles provided a visualization of multi-scale fragmentation that was quite sensitive to changing pattern.://000172809400002 ISI Document Delivery No.: 503QG Times Cited: 4 Cited Reference Count: 25 Cited References: BENSON BJ, 1995, LANDSCAPE ECOL, V10, P113 COLWELL RK, 1974, ECOLOGY, V55, P1148 COSTANZA R, 1994, LANDSCAPE ECOL, V9, P47 FROHN RC, 1998, REMOTE SENSING LANDS JOHNSON GD, 1995, COENOSES, V10, P123 JOHNSON GD, 1998, ECOSYST HEALTH, V4, P177 JOHNSON GD, 1998, P SECT STAT ENV, P63 JOHNSON GD, 1999, ECOL MODEL, V116, P293 JOHNSON GD, 1999, LANDSCAPE ECOL, V14, P413 JONES KB, 1997, EPA600R97130 KOTLIAR NB, 1990, OIKOS, V59, P253 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MIKAN CJ, 1994, B TORREY BOT CLUB, V121, P13 MILLER EW, 1995, GEOGRAPHY PENNSYLVAN MYERS W, 1999, ER9710 PENNS STAT U NOWACKI GJ, 1992, CAN J FOREST RES, V22, P790 ONEILL RV, 1989, LANDSCAPE ECOL, V3, P193 ONEILL RV, 1992, LANDSCAPE ECOL, V7, P55 ONEILL RV, 1996, LANDSCAPE ECOL, V11, P169 PATIL GP, 1982, J AM STAT ASSOC, V77, P548 PIELOU EC, 1975, ECOLOGICAL DIVERSITY QI Y, 1996, LANDSCAPE ECOL, V11, P39 TOWNSHEND JRG, 1988, INT J REMOTE SENS, V9, P187 WHITNEY GG, 1990, J ECOL, V78, P443 WIENS JA, 1989, FUNCT ECOL, V3, P385 0921-2973 Landsc. Ecol.ISI:000172809400002WPenn State Univ, Dept Stat, Ctr Stat Ecol & Environm Stat, University Pk, PA 16802 USA.English?^ Johnson, L.B.1990OAnalyzing Spatial and Temporal Phenomena Using Geographical Information Systems31-43Landscape Ecology417GIS, Natural resources, Spatial, Temporal, Applications@In ecological studies the recent emphasis on larger study areas over longer time spans has coincided with the development of geographical information systems (GIs). GISs are a set of computer hardware and software for analyzing and displaying spatially referenced features (i.e. , points, lines, polygons) with non-geographic attributes (i.e., species, age). In the fields of natural resources management and ecology the GIS has been used most frequently for 1) derivation of area or length measures, 2) spatial intersection functions such as file merging, analysis of spatial coincidence and detection of temporal change, 3) proximity analyses, and 4) derivation of data for input in simulation or growth models or calculation of specific metrics. Several current applications of GISs in ecology and natural resources are reviewed.?_ Johnson, W.C.1988vEstimating Dispersibility of Acer, Fraxinus and Tilia in Fragmented Landscapes from Patterns of Seedling Establishment175-187Landscape Ecology13DDispersal, Seeds, Wind, Samara, Wisconsin, Succession, Habitat patchRelative dispersibility of Tilia americana L., Acer saccharum Marsh. and Fraxinuspennsylvanica Marsh. was inferred from the ratio among species-specific regression coefficients (P) computed from seedling densitydistance plots. Density counts were made in spatially-uniform old fields adjacent to single seed sources or monotypic fencerows. Resultant seedling shadow curves approximate the negative exponential form expected for many seeds (log y = a-OX). This basic curve shape fit species of differing dispersibility, dispersal under a range of wind directions and one-year-old or all-aged cohorts. The ratios of (? were 1:2.6:3.2 for Tilia, Acer and Fraxinus, respectively, in order of increasing dispersibility. Vegetation patches isolated from seed sources by several hundred meters or more should have extremely low input of seeds, especially Tilia and Acer. The finding that Fraxinus disperses farther than Acer was unexpected, since the samaras of the former have faster terminal velocities. The relationship can be explained by better performance of Fraxinus samaras in the stronger winds experienced by trees in open landscapes, poorer formation of the samara abscission layer, and release of samaras following leaf abscission and during the winter when winds are the strongest. Both the samara plan and dispersal phenology need to be considered in estimating relative dispersibility among species.?`8 Johnston, C.1990!GIS: More than just a Pretty Face3-4Landscape Ecology41Check "GIS / Modeling" Folder I|?\Johnston, Carol A.2014GAgricultural expansion: land use shell game in the U.S. Northern Plains81-95Landscape Ecology291Jan7Land area planted to row crops has expanded globally with increased demand for food and biofuels. Agricultural expansion in the Dakota Prairie Pothole Region (DPPR), USA affects a variety of agricultural and non-agricultural land-use types, including grasslands and wetlands that provide critical wildlife habitat and other ecosystem services. The purpose of this study was to quantify recent changes in rural land cover/land use, analyze trends, and interpret results in relation to climate, agronomic practice, and ethanol production. The primary data sources were 1980-2012 statewide cropland data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service, and the USDA Cropland Data Layer, produced annually for the DPPR from 2006 through 2012. Area planted to corn or soybean row crops increased, and small grain (e.g., wheat, barley) area decreased significantly over the analysis period. Corn and soybean expanded by 27 % in the DPPR between 2010 and 2012 alone, an areal increase (+15,400 km(2)) larger than the U.S. state of Connecticut. This expansion displaced primarily small grains and grassland (e.g., pastures, haylands, remnant prairies). Grassland regularly exchanged land with corn and soybean, small grains, and wetlands and water. Corn and soybean had high inter-annual self-replacement values (68-80 %), and continuous corn/soy row cropping was the second most common combination over a three-year period, ranking after continuous grassland. Small grain self-replacement values were only 22-35 %, indicating frequent relocation in the landscape. Temporary gains in wetland and grassland area were attributed to unusually wet climatic conditions and late snowfalls that prevented crop planting. Nearly all of the region's ethanol refineries were located where corn and soybean crops constituted 50 % or more of the land area. Quantification of grassland losses in the U.S. Northern Plains requires evaluation of all land uses that interact with grasslands, and a longer term perspective that incorporates grassland as part of a normal land-use rotation.!://WOS:000330827600007Times Cited: 1 0921-2973WOS:00033082760000710.1007/s10980-013-9947-0?#Carol A. Johnston Robert J. Naiman1987aBoundary dynamics at the aquatic-terrestrial interface: The influence of beaver and geomorphology47-57Landscape Ecology11#beaver, castor, patches, boundariesBeaver (Castor canadensis) impoundments are used to illustrate the effect of large animals on the boundary dynamics of ‘patch bodies’, volumetric landscape units which have surficial boundaries with upper and lower strata, and lateral boundaries with adjacent patches within the same stratum. Patch bodies created by beaver impoundments include the beaver pond, the aerobic soil beneath the pond, and the underlying anaerobic soil. Beaver herbivory in the riparian zone creates an additional patch body concentric to the pond. Beaver and water are the primary biotic and abiotic vectors mediating fluxes across lateral patch body boundaries; vegetation and microbes are the primary biotic vectors mediating fluxes across surficial patch body boundaries. Basin geomorphology affects the permeability of pond boundaries (i.e., their ability to transmit, energy and materials) by affecting the kinetic energy of water, the surface-to-volume ratio of the impoundment, and the movement of beaver between the pond and the riparian foraging zone. We suggest that: (L) permeability of lateral boundaries to abiotic vectors is a function of kinetic energy; (2) within-patch retention of particulate matter transferred by abiotic vectors across lateral boundaries is maximized by a decrease in kinetic energy; (3) lateral patch boundaries between safe refuge and a resource used by an animal vector are most permeable when they are narrow; and (4) total amount of energy and materials transferred across surficial boundaries is maximized by increasing surface area.?!#Carol A. Johnston Robert J. Naiman'1990^The use of a geographic information system to analyze long-term landscape alteration by beaver5-19Landscape Ecology41hgeographic information systems, CIS, Castor canadensis, impoundments, hydrology, vegetation, transitionsA Geographic Information System (CIS) was used to analyze how beaver (Castor canadensis) have altered the hydrology and vegetation of Voyageurs National Park, Minnesota over a 46-year period. Maps of beaver ponds prepared from 1940, 1948, 1961, 1972, 1981, and 1986 aerial photographs were analyzed with a rasterbased CIS to determine impoundment hydrology and vegetation distributions for each map date. Overlay and classification techniques were used to qdantify hydrologic and vegetation changes between map dates. The CIS was superior to manual methods for some analyses (e.g., area measurement), and indispensible for others (e.g., transition analysis). Total area impounded increased from 1 Yo to 13% of the landscape between 1940 and 1986, as the beaver population increased from near extirpation to a density of 1 colony/km2. Most of the impoundment area increase occurred during the first two decades, when 77% of cumulative impoundment area was flooded. Once impounded >- 60% of the area maintained the same water depth or vegetation during any decade. CIS procedures were combined with field data to show that available nitrogen stocks nearly tripled between 1940 and 1986 as a result of beaver impoundment.|?= <Johnstone, Jill F. Rupp, T. Scott Olson, Mark Verbyla, David2011qModeling impacts of fire severity on successional trajectories and future fire behavior in Alaskan boreal forests487-500Landscape Ecology264Apr*Much of the boreal forest in western North America and Alaska experiences frequent, stand-replacing wildfires. Secondary succession after fire initiates most forest stands and variations in fire characteristics can have strong effects on pathways of succession. Variations in surface fire severity that influence whether regenerating forests are dominated by coniferous or deciduous species can feedback to influence future fire behaviour because of differences in forest flammability. We used a landscape model of fire and forest dynamics to explore the effects of different scenarios of surface fire severity on subsequent forest succession and potential fire activity in interior Alaska. Model simulations indicated that high levels of surface fire severity leading to a prolonged phase of deciduous forest dominance caused a reduction in landscape flammability and fewer large fire events. Under low surface fire severity, larger patches of contiguous conifer forest promoted fire spread and resulted in landscapes with shorter fire return intervals compared to scenarios of high surface severity. Nevertheless, these negative feedbacks between fire severity, deciduous forest cover, and landscape flammability were unable to fully compensate for greater fire activity under scenarios of severe climate warming. Model simulations suggest that the effects of climate warming on fire activity in Alaska's boreal forests may be partially but not completely mitigated by changes in fire severity that alter landscape patterns of forest composition and subsequent fire behaviour.!://WOS:000288807300004Times Cited: 0 0921-2973WOS:00028880730000410.1007/s10980-011-9574-6ڽ7 >Jonason, Dennis Smith, HenrikG Bengtsson, Jan Birkhofer, Klaus2013`Landscape simplification promotes weed seed predation by carabid beetles (Coleoptera: Carabidae)487-494Landscape Ecology283Springer NetherlandsAgri-environment schemes Agricultural intensification Biological control Ecosystem services Landscape complexity Organic farming 2013/03/01+http://dx.doi.org/10.1007/s10980-013-9848-2 0921-2973Landscape Ecol10.1007/s10980-013-9848-2Englishc<7gJones, K. B. Neale, A. C. Nash, M. S. Van Remortel, R. D. Wickham, J. D. Riitters, K. H. O'Neill, R. V.2001Predicting nutrient and sediment loadings to streams from landscape metrics: A multiple watershed study from the United States Mid-Atlantic Region301-312Landscape Ecology164landscape metrics nutrients in streams nutrient loadings watershed assessments QUALITY BASIN US CALIFORNIA WETLANDS FILTERS SCALEArticleMaysThere has been an increasing interest in evaluating the relative condition or health of water resources at regional and national scales. Of particular interest is an ability to identify those areas where surface and ground waters have the greatest potential for high levels of nutrient and sediment loadings. High levels of nutrient and sediment loadings can have adverse effects on both humans and aquatic ecosystems. We analyzed the ability of landscape metrics generated from readily available, spatial data to predict nutrient and sediment yield to streams in the Mid-Atlantic Region in the United States. We used landscape metric coverages generated from a previous assessment of the entire Mid-Atlantic Region, and a set of stream sample data from the U.S. Geological Survey. Landscape metrics consistently explained high amounts of variation in nitrogen yields to streams (65 to 86% of the total variation). They also explained 73 and 79% of the variability in dissolved phosphorus and suspended sediment. Although there were differences in the nitrogen, phosphorus, and sediment models, the amount of agriculture, riparian forests, and atmospheric nitrate deposition (nitrogen only) consistently explained a high proportion of the variation in these models. Differences in the models also suggest potential differences in landscape-stream relationships between ecoregions or biophysical settings. The results of the study suggest that readily available, spatial data can be used to assess potential nutrient and sediment loadings to streams, but that it will be important to develop and test landscape models in different biophysical settings.://000169516300002 rISI Document Delivery No.: 446MD Times Cited: 56 Cited Reference Count: 39 Cited References: *EPA, 1988, FUT RISK RES STRAT 1 *EPA, 1998, EPA600R98086 *ESRI, 1996, INTRO ARCV GIS *SAS, 1990, SAS SAT US GUID VERS, V2 ARNOLD CL, 1996, J AM PLANN ASSOC, V62, P243 ATOR SW, 1997, 974139 US GEOL SURV BEHRENDT H, 1999, ACTA HYDROCH HYDROB, V27, P274 BURNS JW, 1972, T AM FISH SOC, V101, P1 CHARBONNEAU R, 1993, ENVIRON MANAGE, V17, P453 CLARKE SE, 1991, ENVIRON MANAGE, V15, P847 COOPER JR, 1987, SOIL SCI SOC AM J, V51, P416 DEWHIT M, 1999, WAT SCI TECH, V39, P109 FRANKLIN JF, 1992, WATERSHED MANAGEMENT, P2572 HARDEN CP, 1992, PHYSICAL GEOGR, V13, P368 HEM JD, 1985, 2254 US GEOL SURV WA HERLIHY AT, 1998, WATER AIR SOIL POLL, V105, P377 HUNSAKER CT, 1992, ECOLOGICAL INDICATOR, P997 HUNSAKER CT, 1995, BIOSCIENCE, V45, P193 JONES KB, 1997, EPA600R97130 KARR JR, 1978, SCIENCE, V201, P229 LANGLAND MJ, 1998, OFR9817 US GEOL SURV LIKENS GE, 1977, BIOGEOCHEMISTRY FORE LOWRANCE RR, 1984, J SOIL WATER CONSERV, V40, P87 NETER J, 1996, APPL LINEAR REGRESSI OMERIK JM, 1987, SUPPL ANN AM ASS GEO, V11, P118 OMERNIK JM, 1981, J SOIL WATER CONSERV, V36, P227 ONEILL RV, 1997, BIOSCIENCE, V47, P513 PETERJOHN WT, 1984, ECOLOGY, V65, P1466 RAPPORT DJ, 1998, J ENVIRON MANAGE, V53, P1 ROTH NE, 1996, LANDSCAPE ECOL, V11, P141 SMITH RA, 1997, WATER RESOUR RES, V33, P2781 STENSLAND GJ, 1986, ACID DEPOSITION LONG, P128 VOGELMANN JE, 1998, ENVIRON MONIT ASSESS, V51, P415 WALKER J, 1993, J APPL ECOL, V30, P265 WELLER CM, 1996, ENVIRON MANAGE, V20, P731 WICKHAM JD, 1999, ENVIRON MANAGE, V24, P553 WISCHMEIER WH, 1978, AGR HDB, V537 YATES P, 1983, AGR ECOSYST ENVIRON, V9, P303 ZHU ZL, 2000, PHOTOGRAMM ENG REM S, V66, P1425 0921-2973 Landsc. Ecol.ISI:000169516300002LUS EPA, Las Vegas, NV 89193 USA. Jones, KB, US EPA, Las Vegas, NV 89193 USA.English |? eJones, K. Bruce Slonecker, E. Terrence Nash, Maliha S. Neale, Anne C. Wade, Timothy G. Hamann, Sharon2010Riparian habitat changes across the continental United States (1972-2003) and potential implications for sustaining ecosystem services 1261-1275Landscape Ecology258OctRiparian ecosystems are important elements in landscapes that often provide a disproportionately wide range of ecosystem services and conservation benefits. Their protection and restoration have been one of the top environmental management priorities across the US over the last several years. Despite the level of concern, visibility and management effort, little is known about trends in riparian habitats. Moreover, little is known about whether or not cumulative efforts to restore and protect riparian zones and floodplains are affecting the rates of riparian habitat change nationwide. To address these issues, we analyzed riparian land cover change between the early 1970s and the late 1990s/early 2000s using existing spatial data on hydrography and land cover. This included an analysis of land cover changes within 180 m riparian buffer zones, and at catchment scales, for 42,363 catchments across 63 ecoregions of the continental US. The total amount of forest and natural land cover (forests, shrublands, wetlands) in riparian buffers declined by 0.7 and 0.9%, respectively across the entire study period. Gains in grassland/shrubland accounted for the 0.2% lower percentage of total natural land cover loss relative to forests. Conversely, urban and developed land cover (urban, agriculture, and mechanically disturbed lands) increased by more than 1.3% within riparian buffers across the entire study period. Despite these changes, we documented an opposite trend of increasing proportions of natural and forest land cover in riparian buffers versus the catchment scale. We surmise that this trend might reflect a combination of natural recovery and cumulative efforts to protect riparian ecosystems across the US. However, existing models limit our ability to assess the impacts of these changes on specific ecosystem services. We discuss the implications of changes observed in this study on the sustainability of ecosystem services. We also recommend opportunties for future riparian change assessments.!://WOS:000281725700010YTimes Cited: 1 10th International Congress of Ecology Aug 16-21, 2009 Brisbane, AUSTRALIA 0921-2973WOS:00028172570001010.1007/s10980-010-9510-1ڽ7 Jones, K. Bruce Zurlini, Giovanni Kienast, Felix Petrosillo, Irene Edwards, Thomas Wade, TimothyG Li, Bai-lian Zaccarelli, Nicola2013vInforming landscape planning and design for sustaining ecosystem services from existing spatial patterns and knowledge 1175-1192Landscape Ecology286Springer NetherlandsLLandscape gradients Landscape pattern Ecosystem services Adaptive management 2013/07/01+http://dx.doi.org/10.1007/s10980-012-9794-4 0921-2973Landscape Ecol10.1007/s10980-012-9794-4English|?F _Jongman, Rob H. G. Bouwma, Irene M. Griffioen, Arjan Jones-Walters, Lawrence Van Doorn, Anne M.2011)The Pan European Ecological Network: PEEN311-326Landscape Ecology263MarThe pan European biological and landscape diversity strategy (PEBDLS) was developed under the auspices of the Council of Europe in order to achieve the effective implementation of the convention of biological diversity (CBD) at the European level. A key element of PEBLDS has been the development of the Pan European Ecological Network (PEEN) as a guiding vision for coherence in biodiversity conservation. PEEN has been developed in three subprojects: Central and Eastern Europe, completed in 2002; South-eastern Europe, completed in 2006; and Western Europe, also completed in 2006. The methodology of the development of the three maps has been broadly comparable but data availability, differences in national databases, technical developments and geographical differences caused variations in the detailed approach. One of the challenges was to find common denominators for the habitat data in Europe; this was solved differently for the subprojects. The project has resulted in three maps that together constitute the PEEN. They differ in terms of ecological coherence and the need for ecological corridors; for example, in Central and Western Europe corridors are essential to provide connectivity, while in Northern, Eastern and Southeastern Europe larger, coherent natural areas still exist. The future steps in developing PEEN should include the implementation of national ecological networks and, in particular, the pursuit of international coherence through the development of trans-European ecological corridors. The big challenge is to develop a common approach among the over 100 European-wide agencies that are responsible for biodiversity conservation.!://WOS:000288808100002Times Cited: 0 0921-2973WOS:00028880810000210.1007/s10980-010-9567-x<7zZJongman, R. H. G. Bunce, R. G. H. Metzger, M. J. Mucher, C. A. Howard, D. C. Mateus, V. L.2006SObjectives and applications of a statistical environmental stratification of Europe409-419Landscape Ecology213clustering; environmental reporting; environmental stratification; Europe; hierarchical approach; monitoring; principal components analysis; sampling strategy CLASSIFICATION; BRITAIN; CLIMATEArticleAprIStratifications are made to divide environmental gradients into convenient units and then to use these as areas in which objects and variables might have relatively consistent characteristics. Statistical classification is a useful approach for obtaining this insight into complex environmental patterns and help to simplify heterogeneity. Traditional classifications of the environment are mostly subjective and based on expert knowledge. They are largely intended for descriptive purposes. Present day techniques now allow for continent wide statistically based environmental stratifications that can be applied consistently throughout Europe. Such environmental stratifications can provide the basis for assessment and monitoring biodiversity, land cover and land use and be a starting point for reporting on the European environment. The stratification presented here allows upscaling and downscaling, if needed to reach specified objectives. It can be applied in environmental reporting. Its application as a framework for land cover estimation is elaborated using Portuguese Land cover data.://000236968500008 ISI Document Delivery No.: 034ZD Times Cited: 1 Cited Reference Count: 35 Cited References: *INT GROUP EARTH O, 2004, GLOB EARTH OBS SYST BISCHOFF NT, 1993, V79 NETH SCI COUNC G BRANDT J, 2001, TEMANORD SERIES BRANDT JJE, 2002, LANDSCAPE URBAN PLAN, V62, P37 BUNCE RGH, 1996, ECOLOGICAL LANDSCAPE, P82 BUNCE RGH, 1996, J ENVIRON MANAGE, V47, P37 BUNCE RGH, 1997, CAP REGIONS BUILDING, P187 BUNCE RGH, 2002, J ENVIRON MANAGE, V65, P121 BUNCE RGH, 2005, UNPUB BIOHAB MONIT 2 COCHRAN WG, 1977, SAMPLING TECHNIQUES DUCKWORTH JC, 2000, GLOBAL ECOL BIOGEOGR, V9, P197 GRUIJTER JJ, 2000, 070 GREEN WORLD RES HAINESYOUNG RH, 2000, ACCOUNTING NATURE AS HARRISON AR, 1993, LANDSCAPE ECOLOGY GE, P101 HOLDRIDGE LR, 1967, LIFE ZONE ECOLOGY HOWARD DC, 2000, QUANTITATIVE APPROAC, P61 JONES HE, 1985, J ENVIRON MANAGE, V20, P17 JONGMAN RHG, 1995, DATA ANAL COMMUNITY JONGMAN RHG, 2000, CONSEQUENCES LAND US, P11 KOPPEN W, 1900, GEOGR Z, V6, P593 KOPPEN W, 1900, GEOGR Z, V6, P657 LAKHANI KH, 1981, ECOLOGICAL MAPPING G, P8 LIEBHOLD AM, 2002, ECOGRAPHY, V25, P553 MATEUS VL, 2004, THESIS U EVORA PORTU MEEUS JHA, 1990, LANDSCAPE URBAN PLAN, V18, P289 METZGER MJ, 2004, QUANTITATIVE APPROAC, V27 METZGER MJ, 2005, UNPUB STAT STRATIFIC MILANOVA EV, 1993, WORLD MAP PRESENT DA MITCHELL TD, 2004, 55 U E ANGL TYND CTR PARRY ML, 1996, CLIMATIC CHANGE, V32, P185 PERRY JN, 2002, ECOGRAPHY, V25, P578 PETIT S, 1998, MIRABEL MODELS INTEG SHKARUBA AD, 2005, UNPUB ALTERRA REPORT, P2 STANNERS D, 1995, EUROPES ENV DOBRIS A VONHUMBOLDT A, 1867, IDEEEN GEOGRAPHIE PF 0921-2973 Landsc. Ecol.ISI:000236968500008Univ Wageningen & Res Ctr, Alterra, NL-6700 AA Wageningen, Netherlands. Univ Wageningen & Res Ctr, Plant Prod Syst, NL-6709 RZ Wageningen, Netherlands. Inst Terr Ecol, Merlewood Res Stn, Ctr Ecol & Hydrol, Grange Over Sands LA11 6JU, Cumbria, England. Univ Evora, Dept Planeamento Biofis & Paisagist, P-7000671 Evora, Portugal. Jongman, RHG, Univ Wageningen & Res Ctr, Alterra, POB 47, NL-6700 AA Wageningen, Netherlands. rob.jongman@wur.nlEnglishڽ7 OJongsomjit, Dennis Stralberg, Diana Gardali, Thomas Salas, Leonardo Wiens, John2013vBetween a rock and a hard place: the impacts of climate change and housing development on breeding birds in California187-200Landscape Ecology282Springer NetherlandssCalifornia Exurban development Generalized additive models Land-use change Species distribution models Urbanization 2013/02/01+http://dx.doi.org/10.1007/s10980-012-9825-1 0921-2973Landscape Ecol10.1007/s10980-012-9825-1English.}?0Jonsen, Ian D. Bourchier, Robert S. Roland, Jens2007jEffect of matrix habitat on the spread of flea beetle introductions for biological control of leafy spurge883-896Landscape Ecology226Jul&://BIOSIS:PREV200700463289 0921-2973BIOSIS:PREV200700463289<7XJonsen, I. D. Fahrig, L.1997VResponse of generalist and specialist insect herbivores to landscape spatial structure185-197Landscape Ecology123alfalfa; diversity; farmland; habitat patch; arthropods; isolation; landscape pattern; leafhoppers; scale; weevils SEED-FEEDING BUG; POPULATION-DYNAMICS; DIVERSE HABITATS; DENSITY; PATTERN; COLONIZATION; CONSERVATION; CICADELLIDAE; IMMIGRATION; LEAFHOPPERSArticleJunThe purpose of this study was to investigate the effect of changes in landscape pattern on generalist and specialist insects. We did this by comparing the species richness and abundance of generalist and specialist herbivorous insects in alfalfa (Medicago sativa, L.) fields on 26 agricultural landscapes that differed in spatial structure. The insects were from the families Curculionidae (Coleoptera), weevils, and Cicadellidae (Auchennorhyncha), leafhoppers. We hypothesized that: (1) generalist richness and abundance would be highest in landscapes with high diversity (Shannon-Wiener); (2) specialist richness and abundance would be highest in landscapes with (i) high percent cover alfalfa and (ii) low mean inter-patch distance. We tested for these effects after controlling for the patch-level effects of field size, field age, frequency of disturbance and vegetation texture. The important findings of the study are: (1) generalist richness and abundance increased with increasing landscape diversity and (2) isolation (percent cover alfalfa in the landscape and/or mean inter-patch distance) does not affect specialist insects. These results are significant because they indicate that both generalist and specialist insects may move over much larger distances than previously thought. This is one of the first studies to demonstrate a large scale effect of spatial structure on insects across a broad range of landscapes.://A1997XV63400006 ! ISI Document Delivery No.: XV634 Times Cited: 39 Cited Reference Count: 56 Cited References: ANDOW DA, 1983, ENV SOUND AGR, P91 ANDREN H, 1992, ECOLOGY, V73, P794 ARNETT RH, 1968, BEETLES UN STATES MA BACH CE, 1980, ECOLOGY, V61, P1515 BIERNE BP, 1956, CANADIAN ENTOMOLOG S, V2, P1 BORROR DJ, 1989, INTRO STUDY INSECTS BRIGHT DE, 1994, ANN ENTOMOL SOC AM, V87, P277 BROWN JH, 1977, ECOLOGY, V58, P445 CHAMBERS JM, 1989, STAT MODELS S CLARK WE, 1971, BIOL SERIES, V13, P1 COLL M, 1994, ECOLOGY, V75, P723 CONNELL JH, 1978, SCIENCE, V199, P1302 CROMARTIE WJ, 1981, CRC HDB PEST MANAGEM, V1, P223 DELONG DM, 1971, ANNU REV ENTOMOL, V16, P179 DUNNING JB, 1992, OIKOS, V65, P169 EVANS EW, 1983, ECOLOGY, V64, P648 FAHRIG L, UNPUB EFFECT HABITAT FAHRIG L, 1985, ECOLOGY, V66, P1762 FAHRIG L, 1992, THEOR POPUL BIOL, V41, P300 FAHRIG L, 1994, CONSERV BIOL, V8, P50 FLINN PW, 1990, J ECON ENTOMOL, V83, P1858 FORTIN MJ, 1989, VEGETATIO, V83, P209 HAMILTON KGA, 1983, CAN ENTOMOL, V115, P473 HANSKI I, 1994, PHILOS T ROY SOC B, V343, P19 HARRISON S, 1991, OIKOS, V62, P5 HASTINGS A, 1991, BIOL J LINN SOC, V42, P57 KAREIVA P, 1983, VARIABLE PLANTS HERB, P259 KAREIVA P, 1990, PHILOS T ROY SOC B, V330, P175 LANDE R, 1988, SCIENCE, V241, P1455 LANDE R, 1993, AM NAT, V142, P911 LEGENDRE P, 1989, VEGETATIO, V80, P107 LEGENDRE P, 1991, R PACKAGE MULTIDIMEN LEGENDRE P, 1993, ECOLOGY, V74, P1659 MASCANZONI D, 1986, ECOL ENTOMOL, V11, P387 MCLAIN DK, 1990, OIKOS, V58, P306 MERRIAM G, 1984, 1ST P INT SEM METH L, P5 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PIENKOWSKI RL, 1966, J ECON ENTOMOL, V59, P837 ROLAND J, 1996, NATURE, V381, P120 ROOT RB, 1973, ECOL MONOGR, V43, P95 RYSZKOWSKI L, 1993, LANDSCAPE ECOLOGY AG, P71 SCHABER BD, 1990, J ECON ENTOMOL, V83, P2427 SHELTON MD, 1983, ENVIRON ENTOMOL, V12, P296 SOLBRECK C, 1990, OIKOS, V58, P199 TAHVANAINEN JO, 1972, OECOLOGIA, V10, P321 TAYLOR PD, 1993, OIKOS, V68, P571 TAYLOR PD, 1995, OIKOS, V73, P43 THOMAS CD, 1992, J ANIM ECOL, V61, P437 TITUS EG, 1911, ANN ENTOMOL SOC AM, V4, P383 VENABLES WN, 1994, MODERN APPL STAT SPL WATKINSON AR, 1995, J ANIM ECOL, V64, P126 WEISZ R, 1994, J ECON ENTOMOL, V87, P723 WIENS JA, 1989, LANDSCAPE ECOLOGY, V3, P87 WITH KA, 1994, FUNCT ECOL, V8, P477 WITH KA, 1994, LANDSCAPE ECOL, V9, P25 0921-2973 Landsc. Ecol.ISI:A1997XV63400006ACARLETON UNIV,OTTAWA CARLETON INST BIOL,OTTAWA,ON K1S 5B6,CANADA.English2|? 0Jopp, Fred DeAngelis, Donald L. Trexler, Joel C.2010[Modeling seasonal dynamics of small fish cohorts in fluctuating freshwater marsh landscapes 1041-1054Landscape Ecology257AugSmall-bodied fishes constitute an important assemblage in many wetlands. In wetlands that dry periodically except for small permanent waterbodies, these fishes are quick to respond to change and can undergo large fluctuations in numbers and biomasses. An important aspect of landscapes that are mixtures of marsh and permanent waterbodies is that high rates of biomass production occur in the marshes during flooding phases, while the permanent waterbodies serve as refuges for many biotic components during the dry phases. The temporal and spatial dynamics of the small fishes are ecologically important, as these fishes provide a crucial food base for higher trophic levels, such as wading birds. We develop a simple model that is analytically tractable, describing the main processes of the spatio-temporal dynamics of a population of small-bodied fish in a seasonal wetland environment, consisting of marsh and permanent waterbodies. The population expands into newly flooded areas during the wet season and contracts during declining water levels in the dry season. If the marsh dries completely during these times (a drydown), the fish need refuge in permanent waterbodies. At least three new and general conclusions arise from the model: (1) there is an optimal rate at which fish should expand into a newly flooding area to maximize population production; (2) there is also a fluctuation amplitude of water level that maximizes fish production, and (3) there is an upper limit on the number of fish that can reach a permanent waterbody during a drydown, no matter how large the marsh surface area is that drains into the waterbody. Because water levels can be manipulated in many wetlands, it is useful to have an understanding of the role of these fluctuations.!://WOS:000279592100005Times Cited: 0 0921-2973WOS:00027959210000510.1007/s10980-010-9478-x<73Jordan, F. Baldi, A. Orci, K. M. Racz, I. Varga, Z.2003Characterizing the importance of habitat patches and corridors in maintaining the landscape connectivity of a Pholidoptera transsylvanica (Orthoptera) metapopulation83-92Landscape Ecology181connectivity ecological corridor Hungary landscape graph networks DYNAMIC LANDSCAPES SPECIES RICHNESS EXTINCTION FRAGMENTATION ECOLOGY CONSERVATION PERSISTENCE DESIGN POPULATIONS NETWORKSArticleJan)Since the fragmentation of natural habitats is one of the most serious problems for many endangered species, it is highly interesting to study the properties of fragmented landscapes. As a basic property, landscape connectivity and its effects on various ecological processes are frequently in focus. First, we discuss the relevance of some graph properties in quantifying connectivity. Then, we propose a method how to quantify the relative importance of habitat patches and corridors in maintaining landscape connectivity. Our combined index explicitly considers pure topological properties and topographical measures, like the quality of both patches (local population size) and corridors (permeability). Finally, for illustration, we analyze the landscape graph of the endangered, brachypterous bush-cricket Pholidoptera transsylvanica. The landscape contains 11 patches and 13 corridors and is situated on the Aggtelek Karst, NE-Hungary. We characterize the importance of each node and link of the graph by local and global network indices. We show how different measures of connectivity may suggest different conservation preferences. We conclude, accordingly to our present index, by identifying one specific habitat patch and one specific corridor being in the most critical positions in maintaining connectivity.://000181767500006 ISI Document Delivery No.: 659FW Times Cited: 8 Cited Reference Count: 56 Cited References: ALBERT R, 2000, NATURE, V406, P378 BALDI A, 1999, ACTA OECOL, V20, P125 BEIER P, 1998, CONSERV BIOL, V12, P1241 BURKEY TV, 1989, OIKOS, V55, P75 BURKEY TV, 1999, J THEOR BIOL, V199, P395 CABEZA M, 2001, TRENDS ECOL EVOL, V16, P242 CANTWELL MD, 1993, LANDSCAPE ECOL, V8, P239 CARLSON A, 2000, P ROY SOC LOND B BIO, V267, P1311 CROOKS KR, 1999, NATURE, V400, P563 DIAS PC, 1996, TRENDS ECOL EVOL, V11, P326 DUNNING JB, 1992, OIKOS, V65, P169 FAHRIG L, 1985, ECOLOGY, V66, P1762 GILBERT F, 1998, P ROY SOC LOND B BIO, V265, P577 HANSKI I, 1998, NATURE, V396, P41 HANSKI I, 1999, OIKOS, V87, P209 HARARY F, 1969, GRAPH THEORY HIGASHI M, 1991, THEORETICAL STUDIES IVANCIUC O, 1993, J MATH CHEM, V12, P309 JOHNSON MP, 2000, P ROY SOC LOND B BIO, V267, P1967 JORDAN F, 2000, ECOL MODEL, V128, P211 JORDAN F, 2001, COMMUNITY ECOLOGY, V2, P133 KEITT TH, 1997, CONSERV ECOL, V1 KEYMER JE, 2000, AM NAT, V156, P478 KRUESS A, 1994, SCIENCE, V264, P1581 LANDE R, 1988, SCIENCE, V241, P1455 MEGLECZ E, 1998, HEREDITAS, V128, P95 METZGER JP, 1997, ACTA OECOL, V18, P1 NAGY B, 1999, FAUNA AGGTELEK NATL, P83 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 ORCI KM, 1997, RES AGGTELEK NATL PA, P109 PICKETT STA, 1995, SCIENCE, V269, P331 PIMM SL, 1991, BALANCE NATURE PLAVSIC D, 1993, J MATH CHEM, V12, P235 PULLIAM HR, 1988, AM NAT, V132, P652 RACZ I, 1997, RES AGGTELEK NATL PA, P99 RICOTTA C, 2000, COMMUNITY ECOLOGY, V1, P89 SACCHERI I, 1998, NATURE, V392, P491 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SHAFFER ML, 1981, BIOSCIENCE, V31, P131 SPILLER DA, 1998, ECOLOGY, V79, P503 SUGIHARA G, 1984, P S APPL MATH, V30, P83 TAYLOR PD, 1993, OIKOS, V68, P571 THOMAS CD, 2000, P ROY SOC LOND B BIO, V267, P139 TIEBOUT HM, 1997, CONSERV BIOL, V11, P620 TILMAN D, 1994, NATURE, V371, P65 TISCHENDORF L, 2000, LANDSCAPE ECOL, V15, P633 TISCHENDORF L, 2000, OIKOS, V90, P7 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1989, OIKOS, V55, P121 URBAN D, 2001, ECOLOGY, V82, P1205 VANAPELDOORN RC, 1992, OIKOS, V65, P265 VARGA Z, 1997, RES AGGTELEK NATL PA, P87 VARGA ZV, 2000, VEGETATION DYNAMISM, P195 VARGASIPOS J, 1997, RES AGGTELEK NATL PA, P59 WIENS JA, 1993, OIKOS, V66, P369 ZABEL J, 1998, OECOLOGIA, V116, P419 0921-2973 Landsc. Ecol.ISI:000181767500006yLorand Eotvos Univ, Dept Genet, H-1117 Budapest, Hungary. Collegium Budapest, Inst Adv Study, Budapest, Hungary. Hungarian Natl Hist Museum, Anim Ecol Res Grp, Hungarian Acad Sci, H-1088 Budapest, Hungary. Univ Debrecen, Dept Evolut Zool & Human Biol, Debrecen, Hungary. Jordan, F, Lorand Eotvos Univ, Dept Genet, Pazmany PS 1-C, H-1117 Budapest, Hungary. jordanf@falco.elte.huEnglish <7;Jordan, F. Magura, T. Tothmeresz, B. Vasas, V. Kodobocz, V.2007sCarabids (Coleoptera : Carabidae) in a forest patchwork: a connectivity analysis of the Bereg Plain landscape graph 1527-1539Landscape Ecology2210landscape graph reachability isolation connectivity carabidae hungary directed graph GROUND BEETLES COLEOPTERA HABITAT FRAGMENTATION SPECIES LOSS CORRIDORS COMMUNITIES ASSEMBLAGES DIVERSITY PATCHES MATRIX METAPOPULATIONArticleDecFor many species, one important key to persistence is maintaining connectivity among local populations that allow for dispersal and gene flow. This is probably true for carabid species (Coleoptera:Carabidae) living in the fragmented forests of the Bereg Plain (NE Hungary and W Ukraine). Based on field data, we have drafted a landscape graph of the area representing the habitat network of these species. Graph nodes and links represented two kinds of landscape elements: habitat (forest) patches and corridors, respectively. The quality of habitat patches and corridors were ranked (from low (1) to high (4)), reflecting local population sizes in the case of patches and estimated permeability in the case of corridors. We analysed (1) the positional importance of landscape elements in maintaining the connectivity of the intact network, (2) the effect of inserting hypothetical corridors into the network, (3) the effects of improving the quality of the existing corridors, and (4) how to connect every patch in a cost-effective way. Our results set quantitative priorities for conservation practice by identifying important corridors: what to protect, what to build and what to improve. Several network analytical techniques were used to account for the directed (source-sink) and highly fragmented nature of the landscape graph. We provide conservation priority ranks for the landscape elements and discuss the conditions for the use of particular network indices. Our study could be of extreme relevance, since a new highway is being planned through the area.://000250632100011ISI Document Delivery No.: 227BL Times Cited: 0 Cited Reference Count: 53 Jordan, Ferenc Magura, Tibor Tothmeresz, Bela Vasas, Vera Kodobocz, Viktor 0921-2973 Landsc. Ecol.ISI:000250632100011Inst Adv Study, Collegium Budapest, H-1014 Budapest, Hungary. Hungarian Natl Hist Museum, Anim Ecol Res Grp HAS, Budapest, Hungary. Hortobagy Natl Park Directorate, Debrecen, Hungary. Debrecen Univ, Inst Ecol, Debrecen, Hungary. Lorand Eotvos Univ, Dept Plant Taxon & Ecol, Budapest, Hungary. Jordan, F, Inst Adv Study, Collegium Budapest, Szentharomsag 2, H-1014 Budapest, Hungary. jordan.ferenc@gmail.comEnglish<7+Jordan, G. J. Fortin, M. J. Lertzman, K. P.2005NAssessing spatial uncertainty associated with forest fire boundary delineation719-731Landscape Ecology206$boundary; fire scar; natural disturbance; location uncertainty; fuzzy sets; dendrochronology; forest management; surface fire; spatial methods BIOGEOCLIMATIC ECOSYSTEM CLASSIFICATION; ECOLOGICAL BOUNDARIES; BRITISH-COLUMBIA; WESTERN USA; MANAGEMENT; HISTORY; REGIMES; LANDSCAPES; FUTURE; TIMEArticleSep Uncertainty in managing forested landscapes arises from many sources, including complexities inherent in forest ecosystems and their disturbance processes. However, gaining knowledge about forested ecosystems at the landscape level is often impeded by limitations in collecting comprehensive, representative, as well as accurate data sets. Historical reference data sets about past disturbances are also mostly lacking. In the case of ground fires, however, records of past fires can be obtained by analyzing fire scars using dendrochronology. While the temporal series of disturbance can be determined, there is still uncertainty about the spatial limits of individual forest surface fires. Here, we investigate how a patch-based method (fuzzy set membership) and a boundary-based uncertainty method (boundary membership) can help determine the spatial uncertainty related to forest fire events and their boundary locations. We compare these methods using fire scar data from ponderosa pine (Pinus ponderosa) and Douglas-fir (Pseudotsuga menziesii) sampled at 33 1-ha plots in a 1500-ha study area within the Stein River watershed (British Columbia). Patch-based fire maps, using multiple constraints, were derived for years 1785-1937. We compared the resulting total fire event maps with the boundary-based method, finding that depending on values chosen for the patch-based method, negative correlation was present (though very modest: r = -0. 1, p <= 0.05) between some maps. However, significant positive correlation between maps (though again modest: r=0.22, p <= 0.05) was found under the least constrained patch-based methods, suggesting that fire patches are counted more than once in riparian zones. Our results suggest that these two methods provide complementary information about historical fire size and spatial limits. Quantifying spatial uncertainty about fire size and fire boundary location using a boundary membership method can contribute to not only understanding past fire regimes but also to providing better estimates of area burned.://000233600700007  ISI Document Delivery No.: 988KS Times Cited: 0 Cited Reference Count: 72 Cited References: *CLARKLABS, 2000, IDR PROJ *LUCO, 2000, GIS DAT *MOF, 2003, BIOG SUBZ VAR MAPP *MWLAP, 2002, BRIT COL PARKS STEIN *TERRASEER, 2001, BOUNDARYSEER ANDIA JBC, 2003, NEFROLOGIA S2, V23, P1 ARMSTRONG GW, 1999, CAN J FOREST RES, V29, P424 ARNO SF, 1988, METHOD DETERMINING F BAKER WL, 2001, CAN J FOREST RES, V31, P1205 BISSON PA, 2003, FOREST ECOL MANAG, V178, P213 BROWN DG, 1998, INT J GEOGR INF SCI, V12, P105 BURROUGH PA, 1998, PRINCIPLES GEOGRAPHI CAMP A, 1997, FOREST ECOL MANAG, V95, P63 CONGALTON RG, 1983, PHOTOGRAMM ENG REM S, V49, P69 DORNER B, 2002, LANDSCAPE ECOL, V17, P729 DRAGICEVIC S, 1999, CARTOGRAPHY GEOGRAPH, V2, P125 DRAGICEVIC S, 2000, INT J GEOGR INF SCI, V14, P225 DUNGAN JL, 2002, ECOGRAPHY, V25, P626 DWIRE KA, 2003, FOREST ECOL MANAG, V178, P61 EASTMAN R, 1999, DECISION SUPPORT TOO EDWARDS G, 1996, PHOTOGRAMMETRIC ENG, V62, P337 EDWARDS G, 2001, SPATIAL UNCERTAINTY, P158 EVERETT R, 2000, J SUSTAIN FOR, V11, P265 EVERETT RL, 2000, FOREST ECOL MANAG, V129, P207 EVERETT RL, 2001, CONTINUITY FIRE DIST FAGAN WF, 2003, BIOSCIENCE, V53, P730 FALL J, 1998, THESIS S FRASER U BU FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FORTIN MJ, 1995, OIKOS, V72, P323 FORTIN MJ, 2000, B ECOL SOC AM, V81, P201 FORTIN MJ, 2001, SPATIAL UNCERTAINTY, P158 GALINDOLEAL C, 1995, FOREST CHRON, V71, P601 GAVIN DG, 2003, ECOLOGY, V84, P186 GOODCHILD M, 1989, SPATIAL ACCURACY SPA, P107 GOODCHILD M, 2001, SPATIAL UNCERTAINTY GREILING D, 2002, BOUNDARYSEER HELP HEYERDAHL EK, 2001, ECOLOGY, V82, P660 HUNTER ML, 1993, BIOL CONSERV, V65, P115 JACQUEZ GM, 2000, J GEOGR SYST, V2, P221 JORDAN G, 2001, NAT DIST FOR MAN S M JORDAN GJ, 2002, THESIS S FRASER U BU KELLER CP, 1999, FR9697191 SRBC FOR R KELLER CP, 1999, HW96078RE FRBC FOR R KOHM KA, 1997, CREATING FORESTRY 21, P1 LERTZMAN K, 1998, NW SCI, V72, P4 LI ZL, 2000, GEOINFORMATICA, V4, P419 LILLESAND TM, 1994, REMOTE SENSING IMAGE LUDWIG D, 2001, ANNU REV ECOL SYST, V32, P481 MACKINNON A, 1992, FOREST CHRON, V68, P100 MARK DM, 1989, CARTOGRAPHICA, V26, P65 MARTIN MP, 1999, REMOTE SENSING LARGE, P101 MCINTIRE E, 2003, THESIS U BRIT COLUMB MEIDINGER D, 1991, ECOSYSTEMS BRIT COLU MITCHELL B, 1995, RESOURCE ENV MANAGEM, P406 MORGAN P, 1994, J SUSTAINABLE FOREST, V2, P87 NAIMAN RJ, 1991, ECOTONES, P130 PEREIRA JMC, 1999, REMOTE SENSING LARGE, P123 PEREIRA JMC, 1999, REMOTE SENSING LARGE, P139 POJAR J, 1987, FOREST ECOL MANAG, V22, P119 SCHUMM SA, 1965, AM J SCI, V263, P110 SMITH B, 1995, P COSIT 95, P475 SWANSON FJ, 1993, EASTSIDE FOREST ECOS, V2, P89 SWETNAM TW, 1999, ECOL APPL, V9, P1189 WALTERS C, 1997, CONSERV ECOL, V1, P1 WHITE G, 1991, STEIN VALLEY WILDERN WHITLOCK C, 2003, FOREST ECOL MANAG, V178, P5 WONG C, 1999, THESIS S FRASER U BU WRIGHT CS, 1996, THESIS U WASHINGTON ZADEH LA, 1965, INFORM CONTR, V8, P338 ZHAN FB, 1998, SOFT COMPUT, V2, P28 ZHANG FB, 2003, T GIS, V7, P67 ZHANG JX, 2001, INT J GEOGR INF SCI, V15, P175 0921-2973 Landsc. Ecol.ISI:000233600700007BSimon Fraser Univ, Sch Resource & Environm Management, Burnaby, BC V5A 1S6, Canada. Trinity Western Univ, Geog Program, Langley, BC V2Y 1Y1, Canada. Univ Toronto, Dept Zool, Toronto, ON M5S 3G5, Canada. Jordan, GJ, Simon Fraser Univ, Sch Resource & Environm Management, Burnaby, BC V5A 1S6, Canada. Geraldine.Jordan@twu.caEnglish ><7_ (Jordan, Y. C. Ghulam, A. Herrmann, R. B.2012uFloodplain ecosystem response to climate variability and land-cover and land-use change in Lower Missouri River basin843-857Landscape Ecology276remote sensing coefficient of variation normalized difference vegetation index land-cover and land-use change conservation biodiversity threats regime flowJulThis contribution aims at characterizing the extreme responses of Lower Missouri River basin ecosystems to land use modification and climate change over a 30-year temporal extent, using long term Landsat data archives spanning from 1975 to 2010. The inter-annual coefficient of variation (CoV) of normalized difference vegetation index was used as a measure of vegetation dynamics to address ecological consequences associated with climate change and the impact of land-cover/land-use change. The slope of a linear regression of inter-annual CoV over the entire time span was used as a sustainability indicator to assess the trend of vegetation dynamics from 1975 to 2010. Deduced vegetation dynamics were then associated with precipitation patterns, land surface temperature, and the impact of levees on alluvial hydrologic partitioning and river channelization reflecting the links between society and natural systems. The results show, a higher inter-annual accumulated vegetation index, and lower inter-annual CoV distributed over the uplands remaining virtually stable over the time frame investigated; relatively low vegetation index with larger CoV was observed over lowlands, indicating that climate change was not the only factor affecting ecosystem alterations in the Missouri River floodplain. We cautiously conclude that river channelization, suburbanization and agricultural activities were the possible potential driving forces behind vegetation cover alteration and habitat fragmentation on the Lower Missouri River floodplain.://000305218000005-958DZ Times Cited:0 Cited References Count:46 0921-2973Landscape EcolISI:000305218000005Ghulam, A St Louis Univ, Dept Earth & Atmospher Sci, Ctr Environm Sci, St Louis, MO 63103 USA St Louis Univ, Dept Earth & Atmospher Sci, Ctr Environm Sci, St Louis, MO 63103 USA St Louis Univ, Dept Earth & Atmospher Sci, Ctr Environm Sci, St Louis, MO 63103 USADOI 10.1007/s10980-012-9748-xEnglishڽ7&VJoseph, GrantS Seymour, ColleenL Cumming, GraemeS Mahlangu, Zacheus Cumming, DavidH M.2013MEscaping the flames: large termitaria as refugia from fire in miombo woodland 1505-1516Landscape Ecology288Springer NetherlandsChizarira National Park Elephant herbivory Macrotermes Ordinal logistic regression Resilience Resprouting Savanna Spatial heterogeneity 2013/10/01+http://dx.doi.org/10.1007/s10980-013-9897-6 0921-2973Landscape Ecol10.1007/s10980-013-9897-6English|?O kJoseph, Grant S. Cumming, Graeme S. Cumming, David H. M. Mahlangu, Zacheus Altwegg, Res Seymour, Colleen L.2011dLarge termitaria act as refugia for tall trees, deadwood and cavity-using birds in a miombo woodland439-448Landscape Ecology263MarRLandscape heterogeneity can play an important role in providing refugia and sustaining biodiversity in disturbed landscapes. Large Macrotermes (Isoptera) termite mounds in miombo woodlands form nutrient rich islands that sustain a different suite of woody plant species relative to the woodland matrix. We investigated the role of termitaria in providing habitat for cavity-using birds in miombo woodlands that had been greatly impacted by elephants and fire, by comparing the availability of habitat favored by cavity-using birds (tall trees, trees with deadwood, and cavities) on and off mounds, and then testing its effect on species richness and abundance of cavity-using birds. We surveyed 48 termitaria paired with 48 woodland matrix sites in the breeding season; and 54 matrix-termitarium pairs in the non-breeding season in Chizarira National Park, Zimbabwe. Generalized linear mixed-effects models showed that termitaria harboured significantly higher densities (ha(-1)) of habitat components considered important for cavity nesting birds. Density of trees >6 m in height and incidence of trees with deadwood was nearly 10 times greater on mounds than in the matrix, and the density of cavities was nine times higher on mounds compared to the matrix. A model selection procedure showed that termitaria provided refugia for cavity-using birds and contributed to the resilience of bird communities through high on-mound densities of trees with deadwood. Large termitaria thus appear to play an important role in maintaining functionally important components of the avifauna in heavily impacted Miombo woodlands.!://WOS:000288808100011Times Cited: 0 0921-2973WOS:00028880810001110.1007/s10980-011-9572-8?Joshua, Lawler2003TBook review, Integrated Public Lands Management: A Coarse-Scale Economic Perspective207-208Landscape Ecology182 book review\This revised version was published online in August 2006 with corrections to the Cover Date.*http://dx.doi.org/10.1023/A:1024403521393 D10.1023/A:1024403521393 Joshua Lawler Email: lawler.joshua@epa.gov YJoshua Lawler1 (1) U.S. Environmental Protection Agency Corvallis, Oregon, 97333, USA 9ڽ78lJosso, Céline Ralec, Anne Raymond, Lucie Saulais, Julia Baudry, Jacques Poinsot, Denis Cortesero, AnneMarie2013zEffects of field and landscape variables on crop colonization and biological control of the cabbage root fly Delia radicum 1697-1715Landscape Ecology289Springer NetherlandszDelia radicum Parasitism Predation Colonization Infestation Crop damages Spatial extent Pest management Biological control 2013/11/01+http://dx.doi.org/10.1007/s10980-013-9928-3 0921-2973Landscape Ecol10.1007/s10980-013-9928-3English?>*P.D. Jungerius J.V. Witter J.H. van Boxel1991kThe effects of changing wind regimes on the development of blowouts in the coastal dunes of The Netherlands41-48Landscape Ecology61/2bWind velocity, wind direction, extreme events, deflation, blowouts, coastal dunes, The NetherlandsTBlowouts are the main features of aeolian activity in many dune areas. To assess the impact of future climatic change on the geomorphological processes prevailing in a dune landscape it is essential to understand blowout formation and identify the meteorological parameters which are important. The development, that is, local erosion and accumulation, of six blowouts in a dune terrain along the Dutch coast has been related to wind velocity and wind direction, as measured at a nearby standard meteorological station. Blowout changes correlate best with wind velocities between 6.25 and 12.5 m/s (measured at 10 m height) which are the critical wind velocities for moving particles in the 0.15 to 0.42 mm range. These winds mostly blow from the southwest. Consequently, the blowouts are elongated in the same direction. Extreme aeolian events such as northwestern storms have little effect on blowout development compared to events which have a lower magnitude but occur with a higher frequency. An eventual shift towards higher effective wind velocities would probably result not in larger blowouts but in a break-down of the whole system, especially if this shift were accompanied by a change in wind direction. The accumulation of sand in the blowouts during storms should be seen as a first step of adaptation to a higher energy level.~?e0Kadoya, T. Suda, S. I. Tsubaki, Y. Washitani, I.2008YThe sensitivity of dragonflies to landscape structure differs between life-history groups149-158Landscape Ecology23Contrasting life-history strategies of long versus short pre-reproductive phases are known in adult dragonflies (Odonata) of temperate regions. Because the long-phase species spend a longer time in terrestrial habitats such as grasslands or woodlands during their pre-reproductive phase, we hypothesized that long-phase species would be more sensitive to landscape structure than short-phase species. To test this hypothesis, we conducted periodic censuses of adult dragonflies at small man-made ponds. We compared the two above functional groups in terms of the degree to which species occurrence depended on landscape structure. The difference among the two groups was not significant, but occurrence of long-phase species tended to depend on landscape structure. Long-phase species responded to landscape structure at larger spatial scales and showed stronger spatial autocorrelation in their occurrence among sampling ponds than short-phase species."://WOS:000252636100004 Times Cited: 0WOS:000252636100004(10.1007/s10980-007-9151-1|ISSN 0921-2973<7Kail, J. Hering, D.2005WUsing large wood to restore streams in Central Europe: potential use and likely effects755-772Landscape Ecology206Central Europe; large wood; stream restoration; Water Framework Directive MACROINVERTEBRATE FAUNA; HABITAT RESTORATION; PARTICULATE MATTER; LOWLAND RIVERS; DEBRIS DAMS; FISH; REINTRODUCTION; GUIDELINES; MANAGEMENT; MORPHOLOGYArticleSepThe potentials for the use of large wood (LW) in stream restoration projects were quantified for streams in Central Europe (total stream length assessed 44,880 km). Two different restoration methods were investigated: recruitment (passively allowing natural LW input) and placement (active introduction of large wood pieces into streams). The feasibility and potential effects of each method were studied for three different scenarios, according to the land-uses to be permitted on the floodplain: (a) only natural-non woody vegetation, forest, and fallow land occur on the floodplain, (b) including pasture and meadow, (c) including pasture, meadow, and cropland. Hydromorphological data were used to identify stream sections where LW recruitment or placement are feasible, and the likely effects of both restoration methods on channel hydromorphology were predicted. Passive recruitment is feasible for only a small percentage of the total channel length in the study area (similar to 1% for all three scenarios). Active placement of LW can be used in much higher extent: 6.5% if only natural non-woody vegetation, forest, and fallow land can occur on the floodplain, 20.2% if stream segments bordered by pasture and meadow are included, and 32% if cropland is included in addition. There are differences between (1) the lower-mountainous area, where a large number of channel segments can be restored yielding an improvement from a moderate/good to a good/excellent morphological status and (2) the lowlands, where only a small number of channel segments can be restored yielding an improvement from a bad to a moderate morphological state. The latter upgrading might be sufficient to reach a 'good ecological status' as defined by the EU Water Framework Directive. The results of this study show the suitability of large wood recruitment and placement as appropriate methods to markedly improve the hydromorphological state of a large proportion of the streams in the study area.://000233600700010  ISI Document Delivery No.: 988KS Times Cited: 1 Cited Reference Count: 52 Cited References: BENKE AC, 2003, AM FISH S S, V37, P149 BILBY RE, 1981, ECOLOGY, V62, P1234 BRAGG DC, 2000, RMRSGTR55 USDA BRIEM E, 2003, GB1 ATVDVWK, P176 BROOKES A, 1987, REGUL RIVER, V18, P3 BROOKS AP, 2004, RIVER RES APPL, V20, P513 BRUNKE M, 2001, REGUL RIVER, V17, P667 BUFFAGNI A, 2001, J LIMNOL S1, V60, P39 CEDERHOLM CJ, 1997, N AM J FISH MANAGE, V17, P947 COLLINS BD, 2002, RESTOR ECOL, V10, P237 CRISPIN V, 1993, N AM J FISH MANAGE, V13, P96 CROOK DA, 1999, MAR FRESHWATER RES, V50, P941 DOLLOFF CA, 2003, AM FISH S S, V37, P179 DUDLEY T, 1982, MELANDERIA, V39, P1 EHRMAN TP, 1992, J N AMER BENTHOL SOC, V11, P341 ELLENBERG H, 1996, VEGETATION MITTELEUR, P1095 FORE LS, 1996, J N AM BENTHOL SOC, V15, P212 GERHARD M, 2001, TOTHOLZ FLIESSGEWASS, P84 GIPPEL CJ, 1996, REGUL RIVER, V12, P223 GREGORY SV, 2003, AM FISH S S, V37, P315 GREGORY SV, 2003, AM FISH SOC S BETH, V37, P431 GURNELL AM, 1995, AQUAT CONSERV, V5, P143 GURNELL AM, 2003, AM FISH S S, V37, P75 HARMON ME, 1986, ADV ECOL RES, V15, P133 HERING D, 2000, INT REV HYDROBIOL, V85, P5 HERING D, 2004, HYDROBIOLOGIA, V516, P1 HILDEBRAND RH, 1998, N AM J FISH MANAGE, V18, P161 HOFFMANN A, 2000, INT REV HYDROBIOL, V85, P25 ILLIES J, 1978, LIMNOFAUNA EUROPAEA, P532 KAIL J, 2003, GEOMORPHOLOGY, V51, P207 KAIL J, 2004, THESIS U DUISBURG ES, P153 KONDOLF GM, 2000, RESTOR ECOL, V8, P48 LASSETTRE N, 2000, P INT C WOOD WORLD R, P38 LORENZ A, 2004, HYDROBIOLOGIA, V516, P107 MARCHANT R, 2002, FRESHWATER BIOL, V47, P1033 MASER C, 1994, FOREST SEA ECOLOGY W, P196 MCMAHON TE, 1989, CAN J FISH AQUAT SCI, V46, P1551 MEBANE CA, 1999, ENVIRON MONIT ASSESS, V67, P293 MURPHY ML, 1989, N AM J FISH MANAGE, V9, P427 MUTZ M, 2000, INT REV HYDROBIOL, V85, P107 PIEGAY H, 1997, GEOMORPHOLOGY, V19, P99 POTTGIESSER T, 2004, HDB ANGEANDTE LIMNOL, P3 RABENI CF, 1993, FRESHWATER BIOL, V29, P211 RAVEN PJ, 2002, AQUAT CONSERV, V12, P405 ROLAUFFS P, 2003, TAG DTSCH GES LIMN D, P98 RONI P, 2002, NORTH AM J FISH MANA, V22, P1 SCHMEDTJE U, 2001, TOP DOWN BOTTOM KONZ, P147 SMOCK LA, 1989, ECOLOGY, V70, P764 SMUKALLA R, 1994, MATERIALIEN, V7, P462 SPONSELLER RA, 2001, FRESHWATER BIOL, V46, P1409 VERDONSCHOT PFM, 2004, HYDROBIOLOGIA, V478, P131 WEIGEL BM, 2003, FRESHWATER BIOL, V48, P1440 0921-2973 Landsc. Ecol.ISI:000233600700010Univ Essen Gesamthsch, Fac Hydrobiol, Inst Ecol, D-45117 Essen, Germany. Kail, J, Univ Essen Gesamthsch, Fac Hydrobiol, Inst Ecol, Univ Str 5, D-45117 Essen, Germany. jochem.kail@uni-essen.deEnglish|?Kalinski, Adam Banbura, Miroslawa Gladalski, Michal Markowski, Marcin Skwarska, Joanna Wawrzyniak, Jaroslaw Zielinski, Piotr Cyzewska, Iwona Banbura, Jerzy2014jLandscape patterns of variation in blood glucose concentration of nestling blue tits (Cyanistes caeruleus) 1521-1530Landscape Ecology299NovIntegration of landscape ecology and conservation physiology has been recommended as a potentially useful way to investigate consequences of human-induced changes in habitats for animal populations. A central goal of this paper was to examine if a simple physiological parameter displays any consistent patterns of spatio-temporal variation. Blood glucose concentration in birds reflects their high metabolic demands and may be influenced by a number of environmental factors. Therefore we present results concerning variation in glucose concentration in the blood of c. 14-day-old nestling blue tits (Cyanistes caeruleus) in central Poland in an 8-year period, 2005-2012, in two landscapes: an urban parkland and a deciduous forest. The most important findings of the study were: (1) mean levels of blood glucose varied markedly among years, most probably due to variable weather conditions, (2) glucose concentrations were significantly higher in the parkland study site than in the forest site, (3) heavier nestlings had lower glucose levels, and (4) high glucose levels were negatively correlated with fledging and breeding success. Thus we have confirmed that a consistent spatio-temporal pattern really exists.!://WOS:000343648700005Times Cited: 0 0921-2973WOS:00034364870000510.1007/s10980-014-0071-6<70Kallimanis, A. S. Sgardelis, S. P. Halley, J. M.2002UAccuracy of fractal dimension estimates for small samples of ecological distributions281-297Landscape Ecology173apparent fractality estimation accuracy fractal dimension null landscape models spatial sampling species distributions RANDOM SPATIAL PATTERNS STATISTICAL PROPERTIES MULTIFRACTAL ANALYSIS LANDSCAPE PATTERNS SPECIES ABUNDANCE DATA SETS MODEL COMMUNITIES COMPLEXITY LIKELIHOODArticleWe carry out a simulation study of the estimation of fractal dimension in a grid-based setting typical of ecological species distributions, using null landscape models. We calculate the box-counting dimension for samples taken in various types of sampling geometry. Sampler geometries include simple blocks, Cantor grids and line transects. This method may be used to measure fractal dimension of a species distribution, but the accuracy depends on a number of criteria. The most important is sampling effort: any estimate will be inaccurate if the sampling effort is low. We also find the geometry of the sampler to be important. For a given sampling effort, schemes based on the Cantor grids performed better than either line transects or simple blocks. Sampling effort can be improved either by using a bigger sampler over a larger area or by repeated sampling of a smaller area: optimum performance is often a trade-off between these two mechanisms. However, performance is also highly sensitive to the type of fractal object being sampled, with certain types of object requiring a much greater effort for an accurate estimate of fractal dimension. These results raise the possibilities of using novel sampling techniques to estimate fractal dimension, when confronted with limited resources and time, but underline also the need for an understanding of the "type" of fractality expected in ecological situations.://000178082200006 ISI Document Delivery No.: 594ZK Times Cited: 2 Cited Reference Count: 53 Cited References: AZOVSKY AI, 2000, WEB ECOL, V1, P28 BELLEHUMEUR C, 1998, LANDSCAPE ECOL, V13, P15 BERNTSON GM, 1997, P ROY SOC LOND B BIO, V264, P1531 BORGANI S, 1993, PHYS REV E, V47, P3879 BUCZKOWSKI S, 1998, PHYSICA A, V252, P23 COLASANTI RL, 1993, FUNCT ECOL, V7, P169 CUTLER C, 1993, NONLINEAR TIME SERIE, V1, P1 DALE MR, 1998, SPATIAL PATTERN ANAL DALEY DJ, 1988, INTRO THEORY POINT P DRAKE JB, 2000, FOREST ECOL MANAG, V128, P121 FALCONER K, 1990, FRACTAL GEOMETRY FEDER J, 1988, FRACTALS GARDNER RH, 1999, LANDSCAPE ECOLOGICAL, P280 GUNNARSSON B, 1992, FUNCT ECOL, V6, P636 HALL P, 1993, BIOMETRIKA, V80, P246 HALLEY JM, 1994, OIKOS, V70, P435 HAMBURGER D, 1996, PHYS REV E A, V53, P3342 HASTINGS HM, 1993, FRACTALS USERS GUIDE HE FL, 2000, AM NAT, V156, P553 HENTSCHEL HGE, 1983, PHYSICA D, V8, P435 KEITT TH, 1997, ECOL MODEL, V102, P243 KRUMMEL JR, 1987, OIKOS, V48, P321 KUNIN WE, 1998, SCIENCE, V281, P1513 KUNIN WE, 2000, AM NAT, V156, P560 LAVOREL S, 1993, OIKOS, V67, P521 LEDUC A, 1994, LANDSCAPE ECOL, V9, P279 LI BL, 2000, ECOL MODEL, V132, P33 LIN YX, 1999, J STAT PLAN INFER, V80, P197 LOBO A, 1998, LANDSCAPE ECOL, V13, P111 LOEHLE C, 1996, ECOL MODEL, V85, P271 MANDELBROT BB, 1982, FRACTAL GEOMETRY NAT MANLY BFJ, 1997, RANDOMIZATION BOOTST MCINTYRE NE, 1999, OIKOS, V86, P129 MILNE BT, 1992, AM NAT, V139, P32 NIKORA VI, 1999, LANDSCAPE ECOL, V14, P17 OGATA Y, 1991, BIOMETRIKA, V78, P463 OLESCHKO K, 1998, SOIL TILL RES, V45, P389 PALMER MW, 1988, VEGETATIO, V75, P91 PALMER MW, 1992, AM NAT, V139, P375 PEITGEN HO, 1992, CHAOS FRACTALS NEW F PICKETT STA, 1995, SCIENCE, V269, P331 PLOTNICK RE, 1996, PHYS REV E B, V53, P5461 RAMSEY JB, 1990, NONLINEARITY, V3, P155 RICOTTA C, 2000, ECOL MODEL, V125, P245 RITCHIE ME, 1998, EVOL ECOL, V12, P309 SHORROCKS B, 1991, FUNCT ECOL, V5, P457 THEILER J, 1990, PHYS REV A, V41, P3038 TISCHENDORF L, 2001, LANDSCAPE ECOL, V16, P235 TURCOTTE DL, 1992, FRACTALS CHAOS GEOLO VEREJONES D, 1997, APPL TIME SERIES ANA, P359 WALLIS JR, 1970, WATER RESOUR RES, V6, P1583 WITH KA, 1999, CONSERV BIOL, V13, P314 WITH KA, 2001, BIOL CONSERV, V100, P75 0921-2973 Landsc. Ecol.ISI:000178082200006Aristotle Univ Thessaloniki, Sch Biol, Dept Ecol, GR-54006 Thessaloniki, Greece. Halley, JM, Aristotle Univ Thessaloniki, Sch Biol, Dept Ecol, UP Box 119, GR-54006 Thessaloniki, Greece.English~?*Kalwij, J. M. Milton, S. J. McGeoch, M. A.2008SRoad verges as invasion corridors? A spatial hierarchical test in an arid ecosystem439-451Landscape Ecology234Disturbed habitats are often swiftly colonized by alien plant species. Human inhabited areas may act as sources from which such aliens disperse, while road verges have been suggested as corridors facilitating their dispersal. We therefore hypothesized that (i) houses and urban areas are propagule sources from which aliens disperse, and that (ii) road verges act as corridors for their dispersal. We sampled presence and cover of aliens in 20 plots (6 x 25 m) per road at 5-km intervals for four roads, nested within three localities around cities (n = 240). Plots consisted of three adjacent nested transects. Houses (n = 3,349) were mapped within a 5-km radius from plots using topographical maps. Environmental processes as predictors of alien composition differed across spatial levels. At the broadest scale road-surface type, soil type, and competition from indigenous plants were the strongest predictors of alien composition. Within localities disturbance-related variables such as distance from dwellings and urban areas were associated with alien composition, but their effect differed between localities. Within roads, density and proximity of houses was related to higher alien species richness. Plot distance from urban areas, however, was not a significant predictor of alien richness or cover at any of the spatial levels, refuting the corridor hypothesis. Verges hosted but did not facilitate the spread of alien species. The scale dependence and multiplicity of mechanisms explaining alien plant communities found here highlight the importance of considering regional climatic gradients, landscape context and road-verge properties themselves when managing verges."://WOS:000254250400007 Times Cited: 0WOS:000254250400007(10.1007/s10980-008-9201-3|ISSN 0921-2973 *<7Kamada, M. Nakagoshi, N.1996dLandscape structure and the disturbance regime at three rural regions in Hiroshima Prefecture, Japan15-25Landscape Ecology111ldisturbance regime; land use; landscape structure; regional comparison; rural region HETEROGENEITY; DYNAMICSArticleFebUsing the vegetation maps of island, inland and mountainous rural regions in Hiroshima Prefecture in western Japan, landscape structures in terms of the size and number of patches are compared, and the characteristics of the disturbance regimes creating each landscape are discussed. Landscape structure in the island rural region is the most heterogeneous, because factors which alter the landscape structure are the most complex. This heterogeneity is established and kept by the agricultural land uses and natural disturbances such as forest fire and pine-disease. At the mountainous rural region, the landscape mosaic is characterized by the relatively large patches composed of conifer plantations and secondary deciduous oak forests. This is the result of the forestry. The inland region landscape is the most homogeneous, because factors which alter landscape structure are now absent. The complex of the physical, biological and anthropogenic forces makes the landscape unique to each region.://A1996UN74400002 _ISI Document Delivery No.: UN744 Times Cited: 16 Cited Reference Count: 28 Cited References: BASTIAN O, 1993, LANDSCAPE ECOL, V8, P139 BIRKS HH, 1988, CULTURAL LANDSCAPE P BRAUNBLANQUET J, 1964, PFLANZENSOZIOLOGIE G DANIELSON BJ, 1991, AM NAT, V138, P1105 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 HANSSON L, 1979, OIKOS, V33, P182 ISAGI Y, 1990, ECOL RES, V5, P163 JOHSON ED, 1991, CONIFEROUS FOREST EC, P77 KAMADA M, 1990, JPN J ECOL, V40, P137 KAMADA M, 1991, CONIFEROUS FOREST EC, P43 KANNEGIETER A, 1988, VETETATION MAPING, P335 MCDONNELL MJ, 1993, HUMANS COMPONENTS EC NAKAGOSHI N, 1987, ROLE FIRE ECOLOGICAL, P91 NAKAGOSHI N, 1989, MISC REP HIWA MUS NA, V28, P1 NAKAGOSHI N, 1990, B BIOL SOC HIROSHIMA, V56, P3 NAKAGOSHI N, 1992, LANDSCAPE ECOL, V7, P111 PULLIAM HR, 1992, ECOL APPL, V2, P165 ROMME WH, 1982, ECOL MONOGR, V52, P199 SOMEYA T, 1989, GEOGRAPHICAL SCI, V44, P53 SOULE ME, 1992, OIKOS, V63, P39 TOUYAMA Y, 1994, JPN J ECOL, V44, P21 TURNER MG, 1987, LANDSCAPE HETEROGENE TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1989, OIKOS, V55, P121 TURNER MG, 1993, LANDSCAPE ECOL, V8, P213 WHITE PS, 1985, ECOLOGY NATURAL DIST, P3 0921-2973 Landsc. Ecol.ISI:A1996UN74400002EKamada, M, TOKUSHIMA PREFECTURAL MUSEUM,HACHIMAN,TOKUSHIMA 770,JAPAN.Englishz|? ;Kamm, U. Gugerli, F. Rotach, P. Edwards, P. Holderegger, R.2010qOpen areas in a landscape enhance pollen-mediated gene flow of a tree species: evidence from northern Switzerland903-911Landscape Ecology256JulHabitat fragmentation often has negative consequences for genetic diversity, and thereby for the viability of populations. However, these negative consequences might be counteracted by gene flow as the latter provides functional connectivity between apparently isolated habitat fragments. Gene flow is itself influenced by landscape structure and composition, and it is therefore important to understand the relationship between gene flow and landscape structure and composition. We used linear LAD regression models to investigate the relationship between contemporary gene flow by pollen in the rare, insect-pollinated forest tree Sorbus domestica and several landscape features. None of the landscape components-which included closed forest, deep valleys, open land and settlements-proved to be an impermeable barrier to gene flow by pollen. We found evidence that settlements, large open areas, and a pronounced topography increased long-distance gene flow in the landscape as compared to a random model including all possible gene flow trajectories. These results are encouraging from a conservation view, as gene flow in species pollinated by generalist insects seems to provide functional connectivity and may help to maintain genetic diversity in rare plant species in fragmented landscapes.!://WOS:000278526000007Times Cited: 1 0921-2973WOS:00027852600000710.1007/s10980-010-9468-z}?Karau, E. C. Keane, R. E.2007ODetermining landscape extent for succession and disturbance simulation modeling993-1006Landscape Ecology227Aug://000248381900003 0921-2973ISI:000248381900003ڽ79=Karaus, Ute Larsen, Stefano Guillong, Helene Tockner, Klement2013bThe contribution of lateral aquatic habitats to insect diversity along river corridors in the Alps 1755-1767Landscape Ecology289Springer NetherlandsnBeta-diversity Conservation Diversity partitioning EPT taxa Floodplains Spatial scales Floodplain Biodiversity 2013/11/01+http://dx.doi.org/10.1007/s10980-013-9918-5 0921-2973Landscape Ecol10.1007/s10980-013-9918-5English=|?6 Karl, J. W. Maurer, B. A.2010Multivariate correlations between imagery and field measurements across scales: comparing pixel aggregation and image segmentation591-605Landscape Ecology254To successfully use remotely-sensed data in landscape-level management, questions as to the relevance of image data to landscape patterns and optimal scales of analysis must be addressed. Object-based image analysis, segmenting images into homogeneous regions called objects, has been suggested for increasing accuracy of remotely-sensed products, but little research has gone into determining image object size with regard to scaling of ecosystem properties. We looked at how segmentation of high-resolution Ikonos and medium-resolution Landsat images into successively coarser objects affected multivariate correlations between image data and eight percent-cover measurements of a sagebrush ecosystem. We also looked at changes in correlation as imagery was aggregated into larger square pixels. We found similar canonical correlations between field and image data at the finest scales, but higher for image segmentation than pixel aggregation for both images when scale increased. For image segmentation, correlations between the canonical variables and original field variables were invariant with respect to size of the image objects, suggesting linear scaling of vegetation cover in our study system. We detected a scaling threshold with the Ikonos segmentation and confirmed with a semi-variogram of the sample data. Below the threshold interpretation of the canonical variables was consistent: scale levels differed primarily in the amount of detail portrayed. Above the threshold, meaning of the canonical variables changed. This approach proved useful for evaluating overall utility of images to address an objective, and identified scaling limits for analysis. Selection of appropriate scale for analysis will ultimately depend on the objective being considered.!://WOS:000275444100008Times Cited: 0 0921-2973WOS:00027544410000810.1007/s10980-009-9439-4?` Kashian, Daniel2012ADistilling a complex subdiscipline down for introductory students921-923Landscape Ecology276Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9712-9 0921-297310.1007/s10980-012-9712-9|? 4Kattwinkel, M. Strauss, B. Biedermann, R. Kleyer, M.2009`Modelling multi-species response to landscape dynamics: mosaic cycles support urban biodiversity929-941Landscape Ecology247Aug<The importance of the spatial as well as the temporal structure of habitat patches for urban biodiversity has been recognised, but rarely quantified. In dynamic environments the rate of habitat destruction and recreation (i.e. the landscape turnover rate), the minimum amount of potential habitat, its spatial configuration as well as the environmental conditions determining habitat quality are crucial factors for species occurrence. We analysed species responses to environmental parameters and to the spatio-temporal configuration of urban brownfield habitats in a multi-species approach (37 plant and 43 insect species). Species presence/absence data and soil parameters, site age, vegetation structure and landscape context were recorded by random stratified sampling at 133 study plots in industrial areas in the city of Bremen (Germany). Based on the field data, we predicted species occurrences by species distribution models using a multi-model inference approach. Predicted species communities were driven by successional age both at the scale of a single building lot and at the landscape scale. Minimum average succession time of brownfield habitats required to support all and especially regionally rare species depended on the proportion of available open space; the larger the potential habitat area the faster the acceptable turnover. Most plant, grasshopper, and leafhopper species modelled could be maintained at an intermediate turnover rate (mean age of 10-15 years) and a proportion of open sites of at least 40%. Our modelling approach provides the opportunity of inferring optimal spatio-temporal landscape configurations for urban conservation management from patch scale species-environment relationships. The results indicate that urban planning should incorporate land use dynamics into the management of urban biodiversity.://000268430900007DKattwinkel, Mira Strauss, Barbara Biedermann, Robert Kleyer, Michael 0921-2973ISI:00026843090000710.1007/s10980-009-9371-7<7s(Kaye, M. W. Stohlgren, T. J. Binkley, D.2003NAspen structure and variability in Rocky Mountain National Park, Colorado, USA591-603Landscape Ecology186belt transects aspen decline conifer invasion elk browsing Populus tremuloides PLANT DIVERSITY AMERICAN ASPENS TREMBLING ASPEN FRONT RANGE FIRE ELK FOREST SIZE PINE REGENERATIONArticle)Elk, fire and climate have influenced aspen populations in the Rocky Mountains, but mostly subjective studies have characterized these factors. A broad-scale perspective may shed new light on the status of aspen in the region. We collected field measurements of aspen (Populus tremuloides Michx.) patches encountered within 36 randomly located belt transects in 340 km(2) of Rocky Mountain National Park, Colorado, to quantify the aspen population. Aspen covered 5.6% of the area in the transects, much more than expected based on previously collected remotely sensed data. The distribution and structure of aspen patches were highly heterogeneous throughout the study area. Of the 123 aspen patches encountered in the 238 ha surveyed, all but one showed signs of elk browsing or had conifer species mixed with the aspen stems. No significant difference occurred in aspen basal area, density, regeneration, browsing of regeneration and patch size, between areas of concentrated elk use (elk winter range) and areas of dispersed elk use (elk summer range). Two-thirds of the aspen patches were mixed with conifer species. We concluded that the population of aspen in our study area is highly variable in structure and that, at a landscape-scale, evidence of elk browsing is widespread but evidence of aspen decline is not.://000185827300004 ISI Document Delivery No.: 730JH Times Cited: 3 Cited Reference Count: 47 Cited References: BAKER FS, 1925, USDA B, V1291 BAKER WL, 1997, ECOGRAPHY, V20, P155 BARNES BV, 1966, ECOLOGY, V47, P439 BARNETT DT, 2001, LANDSCAPE ECOL, V16, P569 BARTOS DL, 1998, RANGELANDS, V20, P17 BERRY J, 1997, SCI BASED ASSESSMENT BETTERS DR, 1981, J FOREST, V79, P673 BROWN PM, 1999, LANDSCAPE ECOL, V14, P513 CHEN HYH, 1998, CAN J FOREST RES, V28, P1743 CHONG GW, 2001, SUSTAINING ASPEN W L, P261 DEBYLE NV, 1985, ASPEN ECOLOGY MANAGE, P135 DEBYLE NV, 1987, WEST J APPL FOR, V2, P73 DONNEGAN JA, 2001, CAN J FOREST RES, V31, P1526 GOSZ JR, 1980, ECOLOGY, V61, P507 HESSL A, 2002, BIOSCIENCE, V52, P1011 HESSL AE, 2002, J BIOGEOGR, V29, P889 HINDS TE, 1985, ASPEN ECOLOGY MANAGE, P135 HOUSTON DB, 1982, NO YELLOWSTONE ELK JOHNSON CW, 1985, ASPEN ECOLOGY MANAGE, P185 JONES JR, 1985, ASPEN ECOLOGY MANAGE, P11 KAUFMANN MR, 2000, CAN J FOREST RES, V30, P698 KAY CE, 1997, J FOREST, V95, P4 KEMPERMAN JA, 1976, CAN J BOT, V54, P2603 LOOPE LL, 1973, QUATERNARY RES, V3, P425 MUEGGLER WF, 1989, WEST J APPL FOR, V4, P41 MUTCH RW, 1970, ECOLOGY, V51, P1046 OLMSTED CE, 1979, N AM ELK ECOLOGY BEH, P89 OLMSTED CE, 1997, UNPUB 20 YEARS CHANG PACKARD FM, 1942, ECOLOGY, V23, P478 PARKER AJ, 1983, GREAT BASIN NAT, V43, P447 PEET RK, 2000, N AM TERRESTRIAL VEG, P75 RIPPLE WJ, 2000, BIOL CONSERV, V95, P361 ROMME WH, 1995, ECOLOGY, V76, P2097 ROMME WH, 2001, SUSTAINING ASPEN W L, P243 SHEPPERD WD, 2001, CAN J FOREST RES, V31, P739 SINGER FJ, 1998, WILDLIFE SOC B, V26, P375 STOHLGREN TJ, 1997, ECOL APPL, V7, P1064 STOHLGREN TJ, 1997, LANDSCAPE ECOL, V12, P155 STOHLGREN TJ, 1999, ECOL MONOGR, V69, P25 SUZUKI K, 1999, LANDSCAPE ECOL, V14, P231 TILMAN D, 1985, AM NAT, V125, P827 TURCHI GM, 1995, WILSON BULL, V107, P463 VEBLEN TT, 2000, ECOL APPL, V10, P1178 VEBLEN TT, 2000, FOREST FRAGMENTATION, P31 WAGNER FW, 1995, WILDLIFE POLICIES US WHITE CA, 1998, WILDLIFE SOC B, V26, P449 WRIGHT HA, 1982, FIRE ECOLOGY US CANA 0921-2973 Landsc. Ecol.ISI:000185827300004Colorado State Univ, Dept Forest Sci, Ft Collins, CO 80523 USA. Colorado State Univ, USGS, Nat Resource Ecol Lab, Ft Collins, CO 80523 USA. Kaye, MW, Arizona State Univ, Ctr Environm Studies, POB 873211, Tempe, AZ 85287 USA.English u?a =Keane, Robert Gray, Kathy Bacciu, Valentina Leirfallom, Signe2012nSpatial scaling of wildland fuels for six forest and rangeland ecosystems of the northern Rocky Mountains, USA 1213-1234Landscape Ecology278Springer NetherlandsBiomedical and Life SciencesWildland fuels are important to fire managers because they can be manipulated to achieve management goals, such as restoring ecosystems, decreasing fire intensity, minimizing plant mortality, and reducing erosion. However, it is difficult to accurately measure, describe, and map wildland fuels because of the great variability of wildland fuelbed properties over space and time. Few have quantified the scale of this variability across space to understand its effect on fire spread, burning intensity, and ecological effects. This study investigated the spatial variability of loading (biomass) across major surface and canopy fuel components in low elevation northern Rocky Mountain forest and rangeland ecosystems to determine the inherent scale of surface fuel and canopy fuel distributions. Biomass loadings (kg m −2 ) were measured for seven surface fuel components—four downed dead woody fuel size classes (0–6 mm, 6–25 mm, 25–75 mm, and 75 + mm), duff plus litter, shrub, and herb—using a spatially nested plot sampling design within a 1 km 2 square sampling grid installed at six sites in the northern US Rocky Mountains. Bulk density, biomass, and cover of the forest canopy were also measured for each plot in the grid. Surface fuel loadings were estimated using a combination of photoload and destructive collection methods at many distances within the grid. We quantified spatial variability of fuel component loading using spatial variograms, and found that each fuel component had its own inherent scale with fine fuels varying at scales of 1–5 m, coarse fuels at 10–150 m, and canopy fuels from 100 to 500 m. Using regression analyses, we computed a scaling factor of 4.6 m for fuel particle diameter (4.6 m increase in scale with each cm increase in particle diameter). Findings from this study can be used to design fuel sampling projects, classify fuelbeds, and map fuel characteristics, such as loading, to account for the inherent scale of fuel distributions to get more accurate fuel loading estimations.+http://dx.doi.org/10.1007/s10980-012-9773-9 0921-297310.1007/s10980-012-9773-9<7Y$Keane, R. E. Morgan, P. White, J. D.1999gTemporal patterns of ecosystem processes on simulated landscapes in Glacier National Park, Montana, USA311-329Landscape Ecology143simulation modeling landscape pattern Fire-BGC fire modeling forest succession modeling AGE-CLASS DISTRIBUTION CLIMATE CHANGE NORTHWESTERN MINNESOTA SPATIAL HETEROGENEITY REGIONAL APPLICATIONS GENERAL-MODEL FIRE REGIMES FOREST VEGETATION DISTURBANCEArticleJun3The mechanistic, spatially-explicit fire succession model, Fire-BGC (a Fire BioGeoChemical succession model) was used to investigate long-term trends in landscape pattern under historical and future fire regimes and present and future climate regimes for two 46 000 ha landscapes in Glacier National Park, Montana, USA. Fire-BGC has two spatial and temporal resolutions in the simulation architecture where ecological processes that act at a landscape level, such as fire, are simulated annually from information contained in spatial data layers, while stand-level processes such as photosynthesis, transpiration, and decomposition are simulated both daily and annually. Fire is spread across the landscape using the FARSITE fire growth model and subsequent fire effects are simulated at the stand-level. Fire-BGC was used to simulate changes in landscape pattern over 250 years under four scenarios: (1) complete fire exclusion under current climate, (2) historical wildfire occurrence and current climate, (3) complete fire exclusion under a possible future climate, (4) future wildfire occurrence and future climate. Simulated maps of dominant tree species, aboveground standing crop, leaf area index, and net primary productivity (NPP) were contrasted across scenarios using the metrics of patch density, edge density, evenness, contagion, and interspersion. Simulation results indicate that fire influences landscape pattern metrics more that climate alone by creating more diverse, fragmented, and disconnected landscapes. Fires were more frequent, larger, and more intense under a future climate regime. Landscape metrics showed different trends for the process-based NPP map when compared to the cover type map. It may be important to augment landscape analyses with process-based layers as well as structural and compositional layers.://000081041200008 sISI Document Delivery No.: 209HB Times Cited: 20 Cited Reference Count: 87 Cited References: *US CERL, 1990, GRASS 4 0 REF MAN US ALBINI FA, 1976, COMPUTER BASED MODEL ARNO SF, 1985, INT177 USDA FOR SERV BAKER WL, 1989, CAN J FOREST RES, V19, P700 BAKER WL, 1991, ECOL MODEL, V56, P109 BAKER WL, 1992, ECOLOGY, V73, P1879 BAKER WL, 1995, LANDSCAPE ECOL, V10, P143 BARRETT SW, 1986, FIRE HIST GLACIER NA BARRETT SW, 1991, CAN J FOREST RES, V21, P1711 BARRETT SW, 1997, IN PRESS FIRE EPISON BEVINS CD, 1994, 12 C FIR FOR MET OCT, P252 BEVINS CD, 1994, IN PRESS P IUFRO GRO BOLLE HJ, 1986, SCOPE, V29, P157 BORMANN FH, 1979, PATTERN PROCESS FORE BOSSEL H, 1988, B U CALIFORNIA, V1927 BUGMANN HKM, 1996, ECOLOGY, V77, P2055 CHEN JQ, 1996, CONSERV BIOL, V10, P854 CLARK JS, 1988, NATURE, V334, P233 CLARK JS, 1990, ECOL MONOGR, V60, P135 CRUTZEN PJ, 1993, FIRE ENV ECOLOGICAL DAVIS KM, 1980, P FIR HIST WORKSH OC, P69 DIXON RK, 1990, PROCESS MODELLING FO FERGUSON SA, 1997, PNWGTR499 USDA FOR S FINKLIN AI, 1986, INT204 USDA FOR SERV FINNEY MA, 1994, 12TH C FIR FOR MET S, P138 FISCHER WC, 1987, INT223 USDA INT RES FLANNIGAN MD, 1991, CAN J FOREST RES, V21, P66 FORMAN RTT, 1995, LANDSCAPE MOSAICS EC FOSBERG MA, 1993, FIRE ENV ECOLOGICAL FRIED JS, 1991, P S SYST AN FOR RES, P377 GARDNER RH, 1996, IGBP BOOK SERIES, V2, P149 GRAHAM RL, 1990, BIOSCIENCE, V40, P575 HABECK JR, 1963, NW SCI, V37, P165 HABECK JR, 1967, P MONT ACAD SCI, V27, P36 HABECK JR, 1968, ECOLOGY, V49, P872 HABECK JR, 1970, FIRE ECOLOGY INVESTI HABECK JR, 1970, VEGETATION GLACIER N HABECK JR, 1973, QUATERNARY RES, V3, P408 HEINRISHS EA, 1988, PLANT STRESS INSECT HEINSELMAN ML, 1981, P C FIR REG EC PROP, P7 HOWARD JA, 1991, REMOTE SENSING FORES HUNGERFORD RD, 1989, INT414 USDA FOR SERV JENSEN JR, 1986, INTRO DIGITAL IMAGE JENSEN ME, 1993, EASTSIDE FOREST ECOS, V2, P249 JOHNSON EA, 1979, CAN J BOT, V57, P1374 KASISCHKE ES, 1995, ECOL APPL, V5, P437 KEANE RE, 1989, INT266 USDA FOR SERV KEANE RE, 1990, COMPILER, V8, P24 KEANE RE, 1990, ECOLOGY, V71, P189 KEANE RE, 1996, INT484 USDA FOR SERV KEANE RE, 1996, TREE PHYSIOL, V16, P319 KEANE RE, 1997, WORLD RESOURCE REV, V9, P177 KEANE RE, 1998, IN PRESS TALL TIMBER KESSELL SR, 1979, GRADIENT MODELING RE KIMMINS JP, 1993, NORX328 FOR CAN NO F LI HB, 1994, ECOLOGY, V75, P2446 MARSDEN MA, 1983, J ENVIRON MANAGE, V16, P45 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MCGUIRE AD, 1995, PRODUCTIVITY AM FORE MINORE D, 1979, PNW87 USDA FOR SERV MLADENOFF DJ, 1993, ECOL APPL, V3, P294 MUTCH RW, 1993, PNWGTR310 USDA FOR S MUTCH RW, 1994, J FOREST, V92, P31 OVERPECK JT, 1990, NATURE, V343, P51 PEET RK, 1988, N AM TERRESTRIAL VEG, P63 PETERS RL, 1990, FOREST ECOL MANAG, V35, P13 PFISTER RD, 1977, INT34 USDA FOR SERV PICKETT STA, 1985, ECOLOGY NATURAL DIST RATZ A, 1995, INT J WILDLAND FIRE, V5, P5 REED KL, 1980, FOREST SCI, V26, P33 REED WJ, 1994, FOREST SCI, V40, P104 ROBERTS DW, 1996, ECOL MODEL, V90, P175 ROTHERMAL RC, 1972, INT115 USDA FOR SERV RUNDEL PW, 1982, PHYSL PLANT RESPONSE, P501 RUNNING SW, 1988, ECOL MODEL, V42, P125 RUNNING SW, 1991, TREE PHYSIOL, V9, P147 RYAN KC, 1988, CAN J FOREST RES, V18, P1291 RYAN KC, 1991, ENVIRON INT, V17, P169 SWANSON FJ, 1990, CHANGING LANDSCAPES, P191 TURNER MG, 1991, QUANTITATIVE METHODS TURNER MG, 1994, J VEG SCI, V5, P731 VANWAGNER CE, 1978, CANADIAN J FOREST RE, V8, P220 VEBLEN TT, 1994, J ECOL, V82, P125 WARING RH, 1985, FOREST ECOSYSTEMS CO WAY DW, 1973, TERRAIN ANAL WRIGHT HA, 1982, FIRE ECOLOGY US CANA WRIGHT HE, 1974, SCIENCE, V186, P487 0921-2973 Landsc. Ecol.ISI:000081041200008US Forest Serv, USDA, Rocky Mt Res Stn, Intermt Fire Sci Lab, Missoula, MT 59807 USA. Keane, RE, US Forest Serv, USDA, Rocky Mt Res Stn, Intermt Fire Sci Lab, POB 8089, Missoula, MT 59807 USA.English<74Kearns, F. R. Kelly, N. M. Carter, J. L. Resh, V. H.2005OA method for the use of landscape metrics in freshwater research and management113-125Landscape Ecology201California; freshwater; pattern metrics; San Jose; spatial configuration; urban ecology; water quality MULTIPLE SPATIAL SCALES; LAND-USE; BIOTIC INTEGRITY; URBAN LANDSCAPE; UNITED-STATES; PATTERN; COVER; STREAMS; MACROINVERTEBRATES; GRADIENTArticleJanFreshwater research and management efforts could be greatly enhanced by a better understanding of the relationship between landscape-scale factors and water quality indicators. This is particularly true in urban areas, where land transformation impacts stream systems at a variety of scales. Despite advances in landscape quantification methods, several studies attempting to elucidate the relationship between land use/land cover (LULC) and water quality have resulted in mixed conclusions. However, these studies have largely relied on compositional landscape metrics. For urban and urbanizing watersheds in particular, the use of metrics that capture spatial pattern may further aid in distinguishing the effects of various urban growth patterns, as well as exploring the interplay between environmental and socioeconomic variables. However, to be truly useful for freshwater applications, pattern metrics must be optimized based on iaracteristic watershed properties and common water quality point sampling methods. Using a freely vailable LULC data set for the Santa Clara Basin, California, USA, we quantified landscape composition and configuration for subwatershed areas upstream of individual sampling sites, reducing the number of metrics based on: (1) sensitivity to changes in extent and (2) redundancy, as determined by a multivariate factor analysis. The first two factors, interpreted as (1) patch density and distribution and (2) patch shape and landscape subdivision, explained approximately 85% of the variation in the data set, and are highly reflective of the heterogeneous urban development pattern found in the study area. Although offering slightly less explanatory power, compositional metrics can provide important contextual information.://000231223900009 ISI Document Delivery No.: 955KD Times Cited: 2 Cited Reference Count: 43 Cited References: *SANT CLAR BAS WAT, 2000, WAT CHAR REP *US GEOL SURV, 2000, NAT LAND COV DAT CAL *WORLD BANK, 2004, URB CIT FACTS FIG ALLAN JD, 1997, FRESHWATER BIOL, V37, P149 BARBOUR MT, 1997, HUM ECOL RISK ASSESS, V3, P933 BASNYAT P, 1999, ENVIRON MANAGE, V23, P539 BASNYAT P, 2000, FOREST ECOL MANAG, V128, P65 CIFALDI RL, 2004, LANDSCAPE URBAN PLAN, V66, P107 COOPER SD, 1998, AUST J ECOL, V23, P27 CROISSANT C, 2004, AGR ECOSYST ENVIRON, V101, P219 DOVCIAK AL, 2002, ENVIRON MANAGE, V30, P365 GASITH A, 1999, ANNU REV ECOL SYST, V30, P51 GERGEL SE, 2002, AQUAT SCI, V64, P118 GRIFFITH JA, 2000, LANDSCAPE URBAN PLAN, V52, P45 GRIFFITH JA, 2002, WATER AIR SOIL POLL, V138, P181 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HEROLD M, IN PRESS COMPUTERS E HERZOG F, 2001, ENVIRON MONIT ASSESS, V72, P37 HYNES HBN, 1975, VERH INT VEREIN LIMN, V19, P1 JOHNSON LB, 1997, FRESHWATER BIOL, V37, P113 JONES KB, 2000, ENVIRON MONIT ASSESS, V64, P227 KNIGHTON DK, 1984, FLUVIAL FORMS PROCES LAMMERT M, 1999, ENVIRON MANAGE, V23, P257 LUCK M, 2002, LANDSCAPE ECOL, V17, P327 MCDONNELL MJ, 1990, ECOLOGY, V71, P1231 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MCLAUGHLIN RJ, 2001, GEOLOGIC MAPS STRUCT MERTES LAK, 2002, FRESHWATER BIOL, V47, P799 MORLEY SA, 2002, CONSERV BIOL, V16, P1498 NAGENDRA H, 2004, AGR ECOSYST ENVIRON, V101, P111 PARKER DC, 2004, AGR ECOSYST ENVIRON, V101, P223 PAUL MJ, 2001, ANNU REV ECOL SYST, V32, P333 RICHARDS C, 1994, WATER RESOUR BULL, V30, P729 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 ROTH NE, 1996, LANDSCAPE ECOL, V11, P141 ROY AH, 2003, FRESHWATER BIOL, V48, P329 SAURA S, 2001, PHOTOGRAMM ENG REM S, V67, P1027 SPONSELLER RA, 2001, FRESHWATER BIOL, V46, P1409 THEOBALD DM, 2004, FRONT ECOL ENVIRON, V2, P139 TURNER MG, 2001, LANDSCAPE ECOLOGY TH VOGELMANN JE, 2001, PHOTOGRAMM ENG REM S, V67, P650 WANG L, 1998, N AM J FISH MANAGE, V18, P775 WEAR DN, 1998, ECOL APPL, V8, P619 0921-2973 Landsc. Ecol.ISI:000231223900009 Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA. US Geol Survey, Menlo Pk, CA 94025 USA. Kearns, FR, Univ Calif Berkeley, Dept Environm Sci Policy & Management, 45 Mulford Hall,3114, Berkeley, CA 94720 USA. fkearns@nature.berkeley.eduEnglish<7 Keitt, T. H.2000-Spectral representation of neutral landscapes479-493Landscape Ecology155Fourier fractal landscape neutral scaling spectral synthesis wavelet SPATIAL PATTERN MULTIFRACTAL FORMALISM FRACTAL LANDSCAPES MULTISCALE SOURCES WAVELET-TRANSFORM DISTURBANCE LACUNARITY EARTHQUAKES GEOMETRY DYNAMICSArticleJul(Pattern in ecological landscapes is often the result of different processes operating at different scales. Neutral landscape models were introduced in landscape ecology to differentiate patterns that are the result of simple random processes from patterns that arise from more complex ecological processes. Recent studies have used increasingly complex neutral models that incorporate contagion and other constraints on random patterns, as well as using neutral landscapes as input to spatial simulation models. Here, I consider a common mathematical framework based on spectral transforms that represents all neutral landscape models in terms of sets of spectral basis functions. Fractal and multi-fractal models are considered, as well as models with multiple scaling regions and anisotropy. All of the models considered are shown to be variations on a basic theme: a scaling relation between frequency and amplitude of spectral components. Two example landscapes examined showed long-range correlations (distances up to 1000 km) consistent with fractal scaling.://000088036700007 ISI Document Delivery No.: 331UH Times Cited: 31 Cited Reference Count: 50 Cited References: ALLAIN C, 1991, PHYS REV A, V44, P3552 ARNEODO A, 1988, PHYS REV LETT, V61, P2281 BAMSLEY MF, 1988, FRACTAL EVERYWHERE BRADSHAW GA, 1992, J ECOL, V80, P205 BRADSHAW GA, 1994, ENVIRON POLLUT, V83, P135 BURROUGH PA, 1983, J SOIL SCI, V34, P577 BURROUGH PA, 1983, J SOIL SCI, V34, P599 CRESSIE NAC, 1993, STAT SPATIAL DATA DALE MRT, 1998, J VEG SCI, V9, P805 DAUBECHIES I, 1992, CBMS NSF REGIONAL C DUTILLEUL P, 1998, ECOLOGICAL SCALE THE, P387 EVANS DL, 1993, WORLD RESOURCE REV, V5, P66 FEDER HJS, 1991, SPONTANEOUS FOPRMATI, P107 FEDER J, 1988, FRACTALS GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GARDNER RH, 1989, LANDSCAPE ECOL, V3, P217 GARDNER RH, 1991, QUANTITATIVE METHODS, P289 GARDNER RH, 1992, ROLE LANDSCAPE BOUND, P76 GELLER RJ, 1997, SCIENCE, V275, P1616 GOLDENFELD N, 1992, LECT PHASE TRANSITIO GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HASTINGS HM, 1993, FRACTALS USERS GUIDE HOCHBERG ME, 1998, AM NAT, V152, P620 HOLLING CS, 1992, ECOL MONOGR, V62, P447 KEITT TH, 1995, J THEOR BIOL, V172, P127 KRUMMEL JR, 1987, OIKOS, V48, P321 LAVOREL S, 1995, LANDSCAPE ECOL, V10, P277 MALAMUD BD, 1998, SCIENCE, V281, P1840 MANDELBROT B, 1982, FRACTAL GEOMETRY NAT MILNE BT, 1992, AM NAT, V139, P32 MILNE BT, 1996, ECOLOGY, V77, P805 MOLONEY KA, 1996, ECOLOGY, V77, P375 MUZY JF, 1991, PHYS REV LETT, V67, P3515 MUZY JF, 1993, PHYS REV E, V47, P875 OLAMI Z, 1992, PHYS REV LETT, V68, P1244 ONEILL RV, 1992, LANDSCAPE ECOL, V7, P19 ONEILL RV, 1992, LANDSCAPE ECOL, V7, P55 OTT E, 1993, CHAOS DYNAMICAL SYST PALMER MW, 1988, VEGETATIO, V75, P91 PALMER MW, 1992, AM NAT, V139, P375 PEITGEN H, 1988, SCI FRACTAL IMAGES PLOTNICK RE, 1993, LANDSCAPE ECOL, V8, P201 PLOTNICK RE, 1996, PHYS REV E B, V53, P5461 RENSHAW E, 1984, VEGETATIO, V56, P75 SOLE RV, 1995, J THEOR BIOL, V173, P31 STAUFFER D, 1985, INTRO PERCOLATION TH THOMPSON JN, 1994, COEVOLUTIONARY PROCE TURNER MG, 1989, OIKOS, V55, P121 WITH KA, 1995, ECOLOGY, V76, P2446 WITH KA, 1997, OIKOS, V79, P219 0921-2973 Landsc. Ecol.ISI:000088036700007Univ Calif Santa Barbara, Natl Ctr Ecol Anal & Synth, Santa Barbara, CA 93101 USA. Keitt, TH, Univ Calif Santa Barbara, Natl Ctr Ecol Anal & Synth, Santa Barbara, CA 93101 USA.English~?k;Kellogg, L. K. B. McKenzie, D. Peterson, D. L. Hessl, A. E.2008Spatial models for inferring topographic controls on historical low-severity fire in the eastern Cascade Range of Washington, USA227-240Landscape Ecology23wFire regimes are complex systems that represent an aggregate of spatial and temporal events whose statistical properties are scale dependent. Despite the breadth of research regarding the spatial controls on fire regime variability, few datasets are available with sufficient resolution to test spatially explicit hypotheses. We used a spatially distributed network of georeferenced fire-scarred trees to investigate the spatial structure of fire occurrence at multiple scales. Mantel's tests and geostatistical analysis of fire-occurrence time series led to inferences about the mechanisms that generated spatial patterns of historical fire synchrony (multiple trees recording fire in a single year) in eastern Washington, USA. The spatial autocorrelation structure of historical fire regimes varied within and among sites, with clearer patterns in the complex rugged terrain of the Cascade Range than in more open and rolling terrain further north and east. Results illustrate that the statistical spatial characteristics of fire regimes change with landform characteristics within a forest type, suggesting that simple relationships between fire frequency, fire synchrony, and forest type do not exist. Quantifying the spatial structures in fire occurrence associated with topographic variation showed that fire regime variability depends on both landscape structure and the scale of measurement. Spatially explicit fire-scar data open new possibilities for analysis and interpretation, potentially informing the design and application of fire management on landscapes, including hazardous fuel treatments and the use of fire for ecosystem restoration."://WOS:000252636100010 Times Cited: 0WOS:000252636100010(10.1007/s10980-007-9188-1|ISSN 0921-2973,<7 Kelly, N. M.2001hChanges to the landscape pattern of coastal North Carolina wetlands under the Clean Water Act, 1984-19923-16Landscape Ecology161North Carolina Section 404 permit process coastal wetlands landscape scale GIS classified Landsat imagery COMPENSATORY MITIGATION RESTORATION QUALITY ISSUES NEED USAArticleJana Wetland management in the United States is organized through a permit process that requires a permit be filed with the U.S. Army Corps of Engineers prior to wetland alteration. A collection of these permits from 1984 through 1992 was analyzed in conjunction with classified Landsat Thematic Mapper data from 1984 and 1992 in order to quantify changes to wetland habitat in the study area in coastal North Carolina. The wetland management process in the U.S. focuses on a site-by-site review, possibly overlooking important changes to wetlands at the landscape-scale. These the two datasets were used to determine if wetland habitat loss was occurring at permit sites, but also to determine if landscape-scale wetland fragmentation and reorganization were occurring in the area surrounding each permit site under the wetland management process. The use of these two datasets attempted to span two scales: the site-specific scale often used in the management of wetlands, and the landscape-scale where effects of such management are evident. Important conclusions from the research include the following. First, while several sources imply that coastal wetlands are disproportionately protected as a result of the widespread recognition of their habitat value, estuarine wetlands were altered much more frequently in the study area than their inland counterparts. Second, despite federal level efforts that require compensatory mitigation when wetland habitat is lost, such mitigation was required in only three percent of permits, ensuring wetland loss. Third, correlation between estimates of wetland loss from the Permit Record and from the remotely sensed record was minimal, highlighting the problems inherent to wetland delineation and implying alterations to habitat not evidenced in the permit record. Finally, landscape-scale changes of loss, fragmentation and habitat reorganization have occurred in estuarine emergent wetland habitat in areas adjacent to several permit sites, implying unanticipated additional impacts to permitted actions. Wetland loss at the permit site occurred with additional fragmentation in 80 percent of the sites examined. The results highlight the lack of agreement between management and landscape-scale wetland structure, function and change, and imply the importance of examining the spatial context of permit sites in the permit review and evaluation procedure.://000167389900001  ISI Document Delivery No.: 409NN Times Cited: 14 Cited Reference Count: 50 Cited References: *MONT AUD SOC, 1993, PROT MONT WETL OV MO *TRIMBL NAV LTD, 1994, PRO XL SYST OP MAN *US GEOL SURV, 1996, 2425 US GEOL SURV ASPINALL RJ, 1994, ENV INFORMATION MANA, P377 BEDFORD BL, 1988, ENVIRON MANAGE, V12, P751 BEDFORD BL, 1996, ECOL APPL, V6, P57 BELL SS, 1997, RESTOR ECOL, V5, P318 BERRY JF, 1993, WETLANDS GUIDE SCI L, P278 COULSON RN, 1990, QUANTITATIVE METHODS, P153 COWARDIN LM, 1979, CLASSIFICATION WETLA DENNISON MS, 1993, WETLANDS GUIDE SCI L DETENBECK NE, 1993, LANDSCAPE ECOL, V8, P39 DOBSON JE, 1995, 123 NOAA NMFS COASTW DUNN CP, 1990, QUANTITATIVE METHODS, P173 EBDON D, 1994, STAT GEOGRAPHY FROHN RC, 1998, REMOTE SENSING LANDS GROSS MF, 1987, PHOTOGRAMMETRIC ENG, V53, P1577 HADDAD KD, 1992, GLOBAL CHANGE ED, V1 HAIG SM, 1998, CONSERV BIOL, V12, P749 HARDISKY MA, 1986, BIOSCIENCE, V36, P453 HARRIS N, 1988, HABITAT INT, V12, P5 HOLMAN RE, 1995, UNCWRRI953 N CAR STA HURD JD, 1992, COASTAL WETLAND MAPP, V1 JOHNSTON CA, 1990, BIOGEOCHEMISTRY, V10, P105 JOHNSTON CA, 1998, GEOGRAPHIC INFORMATI KELLY NM, 1996, THESIS U COLORADO BO KENTULA ME, 1992, ENVIRON MANAGE, V16, P109 LEIBOWITZ SG, 1992, EPA600R92167 LEIDY RA, 1992, BIOSCIENCE, V42, P58 LLEWELLYN DW, 1996, CONSERV BIOL, V10, P1446 MARSH LL, 1996, MITIGATION BANKING T MITSCH WJ, 1993, WETLANDS MOORHEAD KK, 1999, WETLANDS, V19, P276 PATIENCE N, 1993, NMFSSEFSC319 US NAT RACE MS, 1996, ECOL APPL, V6, P94 RIVERA JA, 1992, P 1 THEM C REM SENS SCHWARZ WL, 1996, LANDSCAPE ECOL, V11, P27 SEMLITSCH RD, 1998, CONSERV BIOL, V12, P1129 SNYDER JP, 1987, 1395 US GEOL SURV STOW DA, 1994, LANDSCAPE ECOLOGY GI, P11 STUDT J, 1996, MITIGATION BANKING T, P37 THAYER GW, 1978, WETLAND FUNCTION VAL TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 TURNER S, 1991, QUANTITATIVE METHODS, P3 WELLER CM, 1996, ENVIRON MANAGE, V20, P731 WELLER MW, 1988, ENVIRON MANAGE, V12, P695 WILLIAMS RB, 1972, CHESAPEAKE SCI, V13, P69 WU Y, 1997, ECOL APPL, V7, P286 ZEDLER JB, 1996, ECOL APPL, V6, P33 ZEDLER JB, 1996, ECOL APPL, V6, P84 0921-2973 Landsc. Ecol.ISI:000167389900001Univ Calif Berkeley, Ecosyst Sci Div, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA. Kelly, NM, Univ Calif Berkeley, Ecosyst Sci Div, Dept Environm Sci Policy & Management, 151 Hilgard Hall 3110, Berkeley, CA 94720 USA.English0|? $Kennedy, Maureen C. McKenzie, Donald2010nUsing a stochastic model and cross-scale analysis to evaluate controls on historical low-severity fire regimes 1561-1573Landscape Ecology2510DecFire-scarred trees provide a deep temporal record of historical fire activity, but identifying the mechanisms therein that controlled landscape fire patterns is not straightforward. We use a spatially correlated metric for fire co-occurrence between pairs of trees (the Sorensen distance variogram), with output from a neutral model for fire history, to infer the relative strength of top-down vs. bottom-up controls on historical fire regimes. An inverse modeling procedure finds combinations of neutral-model parameters that produce Sorensen distance variograms with statistical properties similar to those observed from two landscapes in eastern Washington, USA, with contrasting topography. We find the most parsimonious model structure that is able to replicate the observed patterns and the parameters of this model provide surrogates for the predominance of top-down vs. bottom-up controls. Simulations with relatively low spread probability produce irregular fire perimeters and variograms similar to those from the topographically complex landscape. With higher spread probabilities fires exhibit regular perimeters and variograms similar to those from the simpler landscape. We demonstrate that cross-scale properties of the fire-scar record, even without historical fuels and weather data, document how complex topography creates strong bottom-up controls on fire spread. This control is weaker in simpler topography, and may be compromised in a future climate with more severe weather events.!://WOS:000283371000008Times Cited: 0 0921-2973WOS:00028337100000810.1007/s10980-010-9527-5x<72Kennedy, R. E. Turner, D. P. Cohen, W. B. Guzy, M.2006CA method to efficiently apply a biogeochemical model to a landscape213-224Landscape Ecology212biome-BGC; carbon modeling; interpolation; mapping; net ecosystem production; net primary production; Oregon FOREST PRODUCTIVITY; COMPLEX TERRAIN; WESTERN OREGON; GREAT-PLAINS; CLIMATE; DISTURBANCE; ECOSYSTEMS; CARBON; SCALEArticleFebBiogeochemical models offer an important means of understanding carbon dynamics, but the computational complexity of many models means that modeling all grid cells on a large landscape is computationally burdensome. Because most biogeochemical models ignore adjacency effects between cells, however, a more efficient approach is possible. Recognizing that spatial variation in model outputs is solely a function of spatial variation in input driver variables such as climate, we developed a method to sample the model outputs in input variable space rather than geographic space, and to then use simple interpolation in input variable space to estimate values for the remainder of the landscape. We tested the method in a 100 kmx260 km area of western Oregon, U.S.A. , comparing interpolated maps of net primary production (NPP) and net ecosystem production (NEP) with maps from an exhaustive, wall-to-wall run of the model. The interpolation method can match spatial patterns of model behavior well (correlations > 0.8) using samples of only 5 t o 15% of the landscape. Compression of temporal variation in input drivers is a key step in the process, with choice of input variables for compression largely determining the upper bounds on the degree of match between interpolated and original maps. The method is applicable to any model that does not consider adjacency effects, and could free up computational expense for a variety of other computational burdens, including spatial sensitivity analyses, alternative scenario testing, or finer grain-size mapping.://000235866400005 eISI Document Delivery No.: 019WC Times Cited: 1 Cited Reference Count: 28 Cited References: ABER JD, 1992, OECOLOGIA, V92, P463 ACEVEDO MF, 2001, SIMULATION, V77, P53 ALEXANDROV GA, 2002, ECOL MODEL, V148, P293 BAND LE, 1991, ECOL MODEL, V56, P171 BOX GEP, 1987, EMPIRICAL MODEL BUIL BURKE IC, 1991, BIOSCIENCE, V41, P685 COOPS NC, 2001, CAN J FOREST RES, V31, P143 FRANKLIN SE, 2001, SPATIAL UNCERTAINTY, P402 FRIEDMAN LW, 1996, SIMULATION METAMODEL GARMAN SL, 2004, ECOL MODEL, V175, P319 JONGMAN RHG, 1995, DATA ANAL COMMUNITY KERN JS, 1997, SOIL PROCESSES CARBO, P29 LAW BE, 2004, GLOBAL CHANGE BIOL, V10, P1429 MELILLO JM, 1995, GLOBAL BIOGEOCHEM CY, V9, P407 MYERS RH, 2002, RESPONSE SURFACE MET OLLINGER SV, 1998, LANDSCAPE ECOL, V13, P323 PARTON WJ, 1987, SOIL SCI SOC AM J, V51, P1173 PETERS DPC, 2004, OIKOS, V106, P627 RUNNING SW, 1993, SCALING ECOPHYSIOLOG, P388 THORNTON P, 1998, THESIS U MONTANA THORNTON PE, 1997, J HYDROL, V190, P214 THORNTON PE, 2000, AGR FOREST METEOROL, V104, P255 THORNTON PE, 2002, AGR FOREST METEOROL, V113, P185 URBAN DL, 1999, SPATIAL MODELING FOR, P70 WARING RH, 1979, SCIENCE, V204, P1380 WHITE MA, 2000, EARTH INTERACT WILLIAMS M, 1997, ECOL APPL, V7, P882 WILLIAMS M, 2001, ECOL APPL, V11, P1800 0921-2973 Landsc. Ecol.ISI:000235866400005Oregon State Univ, Dept Forest Sci, Corvallis, OR 97331 USA. Forest Serv, USDA, PNW Res Stn, Corvallis, OR 97331 USA. Kennedy, RE, Forest Serv, USDA, PNW Res Stn, 3200 SW Jefferson Way, Corvallis, OR 97331 USA. robert.kennedy@fs.fed.usEnglish[~?U-Kennedy, R. S. H. Spies, T. A. Gregory, M. J.2008|Relationships of dead wood patterns with biophysical characteristics and ownership according to scale in Coastal Oregon, USA55-68Landscape Ecology231 Dead wood patterns and dynamics vary with biophysical factors, disturbance history, ownership, and management practices; the relative importance of these factors is poorly understood, especially at landscape to regional scales. This study examined current dead wood amounts in the Coastal Province of Oregon, USA, at multiple spatial scales. Objectives were to: (1) describe current regional amounts of several characteristics of dead wood; (2) compare dead wood amounts across ownerships; (3) determine the relative importance, according to spatial scale, of biophysical and ownership characteristics, to regional dead wood abundance. Dead wood plot data were evaluated with respect to explanatory variables at four spatial scales of resolution: plots, subwatersheds, watersheds and subbasins. The relationships of dead wood characteristics with biophysical attributes and ownership were diverse and scale-specific. Region-wide dead wood abundance and types varied among ownerships, with public lands typically having higher amounts of dead wood and more large dead wood than private lands. Regression analysis of total dead wood volume indicated that ownership was important at the subbasin scale. Growing season moisture stress was important at plot, subwatershed, and watershed scales. Topography was important at the two coarser scales. Multivariate analysis of dead wood gradients showed that ownership was important at all scales, topography at the subbasin scale, historical vegetation at watershed and subbasin scales, and current vegetation at plot and subwatershed scales. Management for dead wood and related biodiversity at watershed to landscape scales should consider the distinct dynamics of snags and logs, the importance of historical effects, and the relevance of ownership patterns."://WOS:000251796100007 Times Cited: 0WOS:00025179610000710.1007/s10980-007-9164-9?Z0Jay D. Kerby Samuel D. Fuhlendorf David M. Engle2007gLandscape heterogeneity and fire behavior: scale-dependent feedback between fire and grazing processes 507-516Landscape Ecology224hBurning - Herbivory - Landscape pattern - Modeling - Shifting mosaics - Simulation - Vegetation biomass Fire and grazing are ecological processes that frequently interact to modify landscape patterns of vegetation. There is empirical and theoretical evidence that response of herbivores to heterogeneity is scale-dependent however the relationship between fire and scale of heterogeneity is not well defined. We examined the relationship between fire behavior and spatial scale (i.e., patch grain) of fuel heterogeneity. We created four heterogeneous landscapes modeled after those created by a fire–grazing interaction that differed in grain size of fuel patches. Fire spread was simulated through each model landscape from 80 independent, randomly located ignition points. Burn area, burn shape complexity and the proportion of area burnt by different fire types (headfire, backfire and flankfire) were all affected by the grain of fuel patch. The area fires burned in heterogeneous landscapes interacted with the fuel load present in the patch where ignition occurred. Burn complexity was greater in landscapes with small patch grain than in landscapes with large patch grain. The proportion of each fire type (backfire, flankfire and headfire) was similar among all landscapes regardless of patch grain but the variance of burned area within each of the three fire types differed among treatments of patch grain. Our landscape fire simulation supports the supposition that feedbacks between landscape patterns and ecological processes are scale-dependent, in this case spatial scale of fuel loading altering fire spread through the landscape. ?bKesner, B. T. V. Meentemeyer1989@A regional analysis of total nitron in an agricultural landscape151-163Landscape Ecology23rnitrogen balance, agricultural watershed, regional analysis, GIS, map analysis package, Georgia, landscape ecologyTechniques for modeling spatial variability in the loss, gain, and storage of total nitrogen (N) in an agricultural landscape were developed utilizing a geographic information system (GIS) based on the Map Analysis Package (C.D. Tomlin, Yale University). The study area is a well-monitored portion (upper 114.9 km2) of the Little River Watershed, located near Tifton, Georgia, U.S.A. On the basis of measured N in the soil and vegetation, and the gains and losses of N by stream discharge, fertilizer, precipitation, N fixation, crop harvest, etc., it was possible to quantify and map source and sink regions of Total N, and to calculate a mass balance of N for an entire year. Results indicate massive flows of N, especially from anthropogenic sources. However, for the watershed as a whole, the N is virtually in balance with a small accretion occurring mostly in the riparian zones. Stream discharge of total N indicates that this landscape is well-buffered against excessive losses of N despite the large agricultural inputs.@<7$Kie, J. G. Ager, A. A. Bowyer, R. T.2005sLandscape-level movements of North American elk (Cervus elaphus): effects of habitat patch structure and topography289-300Landscape Ecology203dendritic; habitat; landscape structure; movements; North American elk; patch ROCKY-MOUNTAIN ELK; SPATIAL HETEROGENEITY; MULE DEER; ROOSEVELT ELK; RANDOM-WALK; HOME-RANGE; PATTERNS; BEHAVIOR; MODELS; DISPLACEMENTArticleAprWe examined movements of North American elk (Cervus elaphus) in northeastern Oregon, USA. Movement vectors at 449 locations over a 7762 ha area were calculated based on 16,724 sequential observations of 94 female elk-year combinations during spring (15 April-14 May) 1993, 1995, 1996. We calculated movement vectors at the start of morning and evening feeding bouts (0500, 1900 h) and during periods of least activity (0 100, 1500 h). Here, we measured characteristics of habitat patches (habitat type, mean patch size, coefficient of variation in patch size, edge density, mean shape index, and mean nearest neighbor) at two levels of habitat grain (eight habitat types, two habitat types) and at three spatial scales (250, 500, and 1000 m) around each movement vector. We also measured topographic features around each vector including distance to nearest stream, direction of drainage, elevation, slope, and convexity (a measure of ridge top vs. valley bottom land form). We used mixed models adjusted for positive spatial correlation among vectors to examine the relationship between vector length, or speed of movement, and habitat patch characteristics, and between vector direction and topographic features. Speed of movements by elk were not related to characteristics of habitat patches that we measured. The direction of movement, however, was dependent on topography. Elk were more likely to move parallel to major drainages than perpendicular to them. Furthermore, elk were less likely to move perpendicular to drainages when close to the nearest stream, in valley bottoms vs. ridge tops, and on steep slopes. The dendritic nature of movements by elk with respect to topography may help elucidate ecosystem processes such as nutrient flows, nutrient cycling, and successional trajectories of plant communities.://000231824400004 ! ISI Document Delivery No.: 963RU Times Cited: 2 Cited Reference Count: 66 Cited References: *ESRI, 2001, ARC GIS VERS 8 1 *INS CORP, 2001, S PLUS 6 WIND US GUI *SAS I INC, 1999, SAS STAT US GUID VER AGER AA, 2003, J MAMMAL, V84, P1076 AUGUSTINE DJ, 1998, J WILDLIFE MANAGE, V62, P1165 BEIER P, 1990, WILDLIFE MONOGR, V109, P1 BERGMAN CM, 2000, OECOLOGIA, V123, P364 BOWMAN GB, 1980, J WILDLIFE MANAGE, V44, P806 BOWYER RT, 1981, J MAMMAL, V62, P574 BOWYER RT, 2002, J WILDLIFE MANAGE, V66, P536 BRILLINGER DR, 2001, DATA ANAL STAT FDN, P369 BRILLINGER DR, 2002, B BRAZ MATH SOC, V33, P93 BRILLINGER DR, 2004, J STAT PLAN INFER, V122, P43 BURNHAM KP, 1998, MODEL SELECTION INFE CARTER J, 1999, ECOL MODEL, V119, P29 CLEVELAND WS, 1992, STAT MODELS S, P309 CLUTTONBROCK TH, 1978, NATURE, V273, P191 COLE EK, 1997, J WILDLIFE MANAGE, V61, P1115 DANA PH, 1989, P 18 ANN TECHN S INT, P53 DEMPSTER JP, 1986, OIKOS, V46, P413 DUNNING JB, 1992, OIKOS, V65, P169 FINDHOLT SL, 1996, NORTHWEST SCI, V70, P273 FOCARDI S, 1996, J ANIM ECOL, V65, P606 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY GOOD SV, 1997, EVOLUTION, V51, P1296 GREEN RA, 1990, J WILDLIFE MANAGE, V54, P272 GROSS JE, 1995, LANDSCAPE ECOL, V10, P209 GRUNBAUM D, 1998, AM NAT, V151, P97 HASTIE TJ, 1992, STAT MODELS S, P195 HOBBS NT, 1996, J WILDLIFE MANAGE, V60, P695 HOLT RD, 1984, AM NAT, V124, P377 IVES AR, 1995, OIKOS, V74, P366 JOHNSON BK, 2000, J WILDLIFE MANAGE, V64, P685 KIE JG, 2001, NORTHWEST SCI, V75, P55 KIE JG, 2002, ECOLOGY, V83, P530 KIE JG, 2003, MAMMAL COMMUNITY DYN, P296 KVAMME K, 1988, QUANTIFYING PRESENT, P325 LECKENBY DA, 1984, 14 OR DEP FISH WILDL, P1 LIMA SL, 1996, TRENDS ECOL EVOL, V11, P131 LITTELL RC, 1996, SAS SYSTEM MIXED MOD LLOYD AL, 1996, J THEOR BIOL, V179, P1 MCCORQUODALE SM, 1993, J WILDLIFE MANAGE, V57, P881 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MOE SR, 1994, CAN J ZOOL, V72, P1735 MOLVAR EM, 1993, OECOLOGIA, V94, P472 MOORCROFT PR, 1999, ECOLOGY, V80, P1656 PACALA SW, 1982, THEOR POPUL BIOL, V21, P92 PARKER KL, 1984, J WILDLIFE MANAGE, V48, P474 PASTOR J, 1992, AM NAT, V139, P690 PREISLER HK, 1999, P AM STAT ASS VOLUME, V15, P643 PREISLER HK, 2001, P IUFRO 4 11 C SESS, P1 PREISLER HK, 2004, ENVIRONMETRICS, V15, P643 RICE WR, 1989, EVOLUTION, V43, P223 ROTH RR, 1976, ECOLOGY, V57, P773 ROWLAND MM, 1997, PNWGTR396 USDA FOR S SKOVLIN JM, 1967, PNWRP44 USDA FOR SER SKOVLIN JM, 1982, ELK N AM ECOLOGY MAN, P369 STENSETH NC, 1980, OIKOS, V35, P165 STEWART KM, 2002, J MAMMAL, V83, P229 STROHMEYER DC, 1996, NORTHWEST SCI, V70, P79 TURCHIN P, 1998, QUANTITATIVE ANAL MO TURNER MG, 1993, ECOL MODEL, V69, P163 VORE JM, 2001, WILDLIFE SOC B, V29, P720 WHITE KAJ, 1996, P ROY SOC LOND B BIO, V263, P299 WU H, 2000, ECOL MODEL, V132, P115 ZOLLNER PA, 1999, ECOLOGY, V80, P1019 0921-2973 Landsc. Ecol.ISI:000231824400004US Forest Serv, Pacific NW Res Stn, La Grande, OR 97850 USA. Idaho State Univ, Dept Biol Sci, Pocatello, ID 83209 USA. Kie, JG, US Forest Serv, Pacific NW Res Stn, 1401 Gekeler Lane, La Grande, OR 97850 USA. jkie@fs.fed.usEnglish?9 Felix Kienast1991Simulated effects of increasing atmospheric CO, and changing climate on the successional characteristics of Alpine forest ecosystems225-238Landscape Ecology54forest simulation, CO, fertilization, forest succession model, JABOWAIFORET type model, vegetation dynamics, Alpine forests, climatic change #Possible effects of changing climate and increasing CO, on forest stand development were simulated using a forest succession model of the JABOWA/FORET type. The model was previously tested for its ability to generate plausible community patterns for Alpine forest sites ranging from 220 m to 2000 m a.s.l., and from xeric to mesic soil moisture conditions. Each model run covers a period of 1000 yrs and is based on the averaged successional characteristics of 50 forest plots with an individual size of 1/12 ha. These small forest patches serve as basic units to model establishment, growth, and death of individual trees. The simulated CO, scenario assumes linear climate change as atmospheric CO, concentration increases from 310 p1/1 to 620 pl/l and finally to 1340 pl/l. Direct effects of increasing CO, on tree growth were modeled using treering and growth chamber data. The simulation experiment proved to be a useful tool for evaluating possible vegetation changes that might occur under C0,-induced warming. On xeric sites from the colline to the high montane belt, the simulated climate change causes drastic soil water losses due to elevated evapotranspiration rates. This translates into a significant biomass decrease and even to a loss of forest on xeric low-elevation sites. Biomass gains can be reported from mesic to intermediate sites between 600 and 2000 m a.s.1. Increasing CO, and warming alters the species composition of the simulated communities considerably. In today's montane and subalpine belt an invasion of deciduous tree species can be expected. They outcompete most conifers which in turn may migrate to today's alpine belt. Some of these changes occur as early as 40 yrs after climate begins to change. This corresponds to a mean annual warming of 1.5"C compared with today's mean temperatures.?Kienast, Felix1993iAnalysis of historic landscape patterns with a geographical information system - a methodological outline103-118Landscape Ecology82historic land use, CIS, land information system, landscape history, statistical analysis, information theory, fractals, edge, barriers, habitats, landscape evolutionvVarious methods for storing, retrieving, and analyzing historic land use records by means of electronic data processing are evaluated. The procedures are illustrated with data from a pilot study on the Swiss Plateau which is part of a broader landscape historical monitoring program at the Swiss Federal Institute of Forest, Snow and Landscape Research. The land use matrix was derived from topographic maps, aerial photographs and other land use records and spans approximately 100 yrs with an updating cycle of 7 to 20 yrs. A special technique was developed to generate series of digital maps and to superimpose the data layers of various time steps. Each landscape element is described with time-stamped attributes to ensure access to the entire “life history” from any point in space or time. The proposed data model proved to be a powerful tool for routine updating of digital maps. It can be used by practitioners as well as scientists working with Geographical Information Systems (ARC/INFO or similar package). With this procedure, disturbance maps over any number of available updates can be quickly generated, allowing the user to identify zones of similar degrading or upgrading tendency. The procedures for analyzing changing landscape structures include calculation of information theoretic indices (diversity, dominance), calculation of fractals, edge analysis, as well as landscape assessment along random traverses. The latter proved to be especially powerful, where barrier/habitat frequencies were evaluated. On the basis of all parameters calculated, landscape structures on the study plot seem to be ecologically most favorable in the 1930’s followed by a strong degradation in the World War IIand the post-World War I1 period. In contrast to many hypotheses, the landscape structures in the second half of the 19th century were structurally less favorable than between 1900 and 1930. |7 Kienast, F.1993iAnalysis of Historic Landscape Patterns with a Geographical Information-System - a Methodological Outline103-118Landscape Ecology82historic land use gis land information system landscape history statistical analysis information theory fractals edge barriers habitats landscape evolutionJuntVarious methods for storing, retrieving, and analyzing historic land use records by means of electronic data processing are evaluated. The procedures are illustrated with data from a pilot study on the Swiss Plateau which is part of a broader landscape historical monitoring program at the Swiss Federal Institute of Forest, Snow and Landscape Research. The land use matrix was derived from topographic maps, aerial photographs and other land use records and spans approximately 100 yrs with an updating cycle of 7 to 20 yrs. A special technique was developed to generate series of digital maps and to superimpose the data layers of various time steps. Each landscape element is described with time-stamped attributes to ensure access to the entire ''life history'' from any point in space or time. The proposed data model proved to be a powerful tool for routine updating of digital maps. It can be used by practitioners as well as scientists working with Geographical Information Systems (ARC/INFO or similar package). With this procedure, disturbance maps over any number of available updates can be quickly generated, allowing the user to identify zones of similar degrading or upgrading tendency. The procedures for analyzing changing landscape structures include calculation of information theoretic indices (diversity, dominance), calculation of fractals, edge analysis, as well as landscape assessment along random traverses. The latter proved to be especially powerful, where barrier/habitat frequencies were evaluated. On the basis of all parameters calculated, landscape structures on the study plot seem to be ecologically most favorable in the 1930's followed by a strong degradation in the World War II- and the post-World War II period. In contrast to many hypotheses, the landscape structures in the second half of the 19th century were structurally less favorable than between 1900 and 1930.://A1993LM22200003-Lm222 Times Cited:48 Cited References Count:0 0921-2973ISI:A1993LM22200003iKienast, F Swiss Fed Inst Forest Snow & Landscape Res,Dept Landscape Ecol,Ch-8903 Birmensdorf,SwitzerlandEnglish۽7 Killingbeck, KeithT2013Nature bats last?783-784Landscape Ecology284Springer Netherlands 2013/04/01+http://dx.doi.org/10.1007/s10980-013-9871-3 0921-2973Landscape Ecol10.1007/s10980-013-9871-3English$|?Kindlmann, P. Burel, F.2008Connectivity measures: a review879-890Landscape Ecology2389One of the central problems in contemporary ecology and conservation biology is the drastic change of landscapes induced by anthropogenic activities, resulting in habitat loss and fragmentation. For many wild living species, local extinctions of fragmented populations are common and recolonization is critical for regional survival. Successful recolonization depends on the availability of dispersing individuals and the degree of landscape connectivity. The obvious implications of landscape connectivity for conservation biology have led to a proliferation of connectivity measures. However, general relationships between landscape connectivity and landscape structure are lacking, and so are the relationships between different connectivity metrics. Consequently, there is a need to develop landscape metrics that more accurately characterize the landscape with an emphasis on the underlying processes. Here we review various definitions of landscape connectivity, explain their mathematical connotations, and make some unifying conclusions and suggestions for future research.!://WOS:000259481900001Times Cited: 0 0921-2973WOS:00025948190000110.1007/s10980-008-9245-4>?e*King, A. W. Johnson, A. R. O'Neill, R. V.1991GTransmutation and functional representation of heterogeneous landscapes239-253Landscape Ecology54?model aggregation, scaling, spatial transmutation, scale effectModels of local small-scale ecological processes can be used to describe related processes at larger spatial scales if the influences of increased scale and heterogeneity are carefully considered. In this paper we consider the changes in the functional representation of an ecological process that can occur as one moves from a local small-scale model to a model of the aggregate expression of that process for a larger spatial extent. We call these changes “spatial transmutation”. We specifically examine landscape heterogeneity as a cause of transmutation. Spatial transmutation as a consequence of landscape heterogeneity is a source of error in the prediction of aggregate landscape behavior from smaller scale models. However, we also demonstrate a procedure for taking advantage of spatial transmutation to develop appropriately scaled landscape functions. First a mathematical function describing the process of interest as a local function of local variables is defined. The spatial heterogeneity of the local variables is described by their statistical distribution in the landscape. The aggregate landscape expression of the local process is then predicted by calculating the expected value of the local function, explicitly integrating landscape heterogeneity. Monte Carlo simulation is used to repeat the local-to-landscape extrapolation for a variety of landscape patterns. Finally, the extrapolated landscape results are regressed on landscape variables to define response functions that explain a useful fraction of the total variation in landscape behavior. The response functions are hypotheses about the functional representation of the local process at the larger spatial scale.|? Kirk, T. A. Zielinski, W. J.2009Developing and testing a landscape habitat suitability model for the American marten (Martes americana) in the Cascades mountains of California759-773Landscape Ecology246JulJWe used field surveys and Geographic Information System data to identify landscape-scale habitat associations of American martens (Martes americana) and to develop a model to predict their occurrence in northeastern California. Systematic surveys using primarily enclosed track plates, with 10-km spacing, were conducted across a 27,700 km(2) area of largely forested, mountain terrain. Martens were detected at 20/184 (10.8%) of the sample units, aggregated in three distinct regions. We investigated habitat selection at multiple scales using circular assessment areas of 3, 20, and 80 km(2). The model for the largest assessment area best fit the data and included the following predictors: amount of reproductive habitat, number of habitat patches and land ownership category. These results support the hypothesis that martens select habitat based upon broad scale landscape conditions and that these conditions vary with ownership. We tested the model using an independent set of data, collected primarily during the winter. Poor fit of the test data in some locations raised concerns that our model, which was developed using data collected during the snow-free season, may not predict winter distribution well. We are investigating possible causes for the seasonal variation and until they can be incorporated our model represents a conservative view of marten habitat suitability based on summer occupancy. During the summer months, which is the reproductive season, martens are predicted to occur largely in relatively undisturbed landscapes where high-elevation, late-successional forests are common.://000268248100005%Kirk, Thomas A. Zielinski, William J. 0921-2973ISI:00026824810000510.1007/s10980-009-9349-5<7nKitzberger, T. Veblen, T. T.19996Fire-induced changes in northern Patagonian landscapes1-15Landscape Ecology141Austrocedrus change detection disturbance fire exclusion landscape pattern Nothofagus Patagonia NATIONAL-PARK FOREST DISTURBANCE DYNAMICS SETTLEMENT VEGETATIONArticleFebIn northern Patagonia, Argentina we quantify changes in fire frequency along a gradient from mesic Nothofagus dombeyi forest to xeric woodlands of Austrocedrus chilensis at the steppe ecotone, and we examine patterns of vegetation change coincident with the changes in fire regimes across a range of spatial scales. At a regional scale changes in land cover types are documented by comparing 1:250 000 scale cover type maps from 1913 and 1985. Changes in landscape structure are analyzed by comparing vegetation patterns on 1:24 000 scale aerial photographs taken in 1940 and 1970. Fire frequency peaked in the late nineteenth-century due to widespread burning and clearing of forests by European settlers late in the century. Subsequently, fire frequency declined dramatically about 1910 due to the cessation of intentional fires and has remained low due to increasingly effective fire exclusion. At a regional scale there has been a dramatic increase during the twentieth century in the proportion of forest cover relative to areas mapped as recent burns or shrublands in 1913. Remnant forest patches that survived the widespread late-nineteenth century burning have coalesced to form more continuous forest covers, and formerly continuous areas of shrublands have become dissected by forest. Under reduced fire frequency there has been a shift in dominance from short-lived resprouting species (mostly shrubs) towards longer-lived species and obligate seed-dispersers such as Austrocedrus chilensis and Nothofagus dombeyi. Due to limited seed dispersal of these tree species, the spatial configuration of remnant forest patches plays a key role in subsequent changes in landscape pattern.://000079005100001 ISI Document Delivery No.: 173XM Times Cited: 19 Cited Reference Count: 35 Cited References: AGEE JK, 1989, ECOLOGY, V70, P23 BAKER WL, 1992, ECOLOGY, V73, P1879 BARROS V, 1983, UNPUB CARTAS PRECIPI BURNS BR, 1993, J BIOGEOGR, V20, P669 COVINGTON WW, 1994, J FOREST, V92, P39 DEPIETRI DE, 1992, BIOL CONSERV, V62, P127 EASTMAN JR, 1990, IDRISI GRID BASED GE ERICKSEN W, 1971, Z AUSL LANDWIRTSCHAF, V10, P24 FUENTES ER, 1984, OECOLOGIA, V62, P405 GOBBI M, 1995, PLANT INVASIONS GEN, P105 HARRIS LJ, 1984, FRAGMENTED FOREST IS HEINSELMAN ML, 1973, QUATERNARY RES, V3, P329 JOHNSON AC, 1985, MAR ENVIRON RES, V15, P1 KITZBERGER T, UNPUB SPATIAL TEMPOR KITZBERGER T, 1994, THESIS U COLORADO BO KITZBERGER T, 1997, J BIOGEOGR, V24, P35 LEGENDRE L, 1983, IMPACTO GANADERIA 1 MCBRIDE JR, 1983, TREE RING B, V43, P51 MCGARRIGAL K, 1993, UNPUB FRAGSTATS SPAT MERMOZ M, 1986, MAPA VEGETACION PARQ RAFFAELE E, 1996, INT J ECOLOGY ENV SC, V22, P59 STORY M, 1986, PHOTOGRAMM ENG REM S, V52, P397 TURNER MG, 1989, OIKOS, V55, P121 TURNER MG, 1994, LANDSCAPE ECOL, V9, P59 VANWAGNER CE, 1978, CANADIAN J FOREST RE, V8, P220 VEBLEN TT, 1987, VEGETATIO, V71, P113 VEBLEN TT, 1988, ANN ASSOC AM GEOGR, V78, P93 VEBLEN TT, 1988, QUATERNARY RES, V30, P331 VEBLEN TT, 1992, CONSERV BIOL, V6, P71 VEBLEN TT, 1992, J VEG SCI, V3, P507 VEBLEN TT, 1995, ECOLOGY SO CONIFERS, P120 VEBLEN TT, 1996, ECOLOGY BIOGEOGRAPHY, P293 VILLALBA R, 1995, THESIS U COLORADO BO VILLALBA R, 1997, J ECOL, V85, P113 WILLIS B, 1914, NO PATAGONIA CHARACT, V1 0921-2973 Landsc. Ecol.ISI:000079005100001Univ Nacl Comahue, Dept Ecol, RA-8400 Bariloche, Rio Negro, Argentina. Kitzberger, T, Univ Nacl Comahue, Dept Ecol, EP Univ, RA-8400 Bariloche, Rio Negro, Argentina.Englishڽ7 %Klein Goldewijk, Kees Verburg, PeterH2013mUncertainties in global-scale reconstructions of historical land use: an illustration using the HYDE data set861-877Landscape Ecology285Springer Netherlands?Historic land use Land cover Reconstructions Uncertainty Global 2013/05/01+http://dx.doi.org/10.1007/s10980-013-9877-x 0921-2973Landscape Ecol10.1007/s10980-013-9877-xEnglishڽ7MPKlein, Tommy Holzkämper, Annelie Calanca, Pierluigi Seppelt, Ralf Fuhrer, Jürg2013iAdapting agricultural land management to climate change: a regional multi-objective optimization approach 2029-2047Landscape Ecology2810Springer NetherlandsmAgricultural land management Adaptation to climate change Crop modeling Regional optimization Multi-objective 2013/12/01+http://dx.doi.org/10.1007/s10980-013-9939-0 0921-2973Landscape Ecol10.1007/s10980-013-9939-0English |7u Klijn, F. Dehaes, H. A. U.1994]A Hierarchical Approach to Ecosystems and Its Implications for Ecological Land Classification89-104Landscape Ecology92Lecosystem (ecological land) classification hierarchy (theory) spatial scalesJunAA hierarchical paradigm may help to better understand patterns of ecosystems. In this article we present and argue a framework for hierarchical ecosystem classification and mapping. It is based on a hierarchical model of an ecosystem fully incorporating abiotic components. We propose a nomenclature for hierarchical ecosystem classification based on common practice in ecological land classification and considerations on comprehensiveness which is inspired on and closely follows the Canadian terminology, but incorporating some frequently used European concepts. The relation between classification characteristics and the spatial and temporal hierarchy of ecosystem components is discussed. We exemplify that the approach is particularly valuable as a comprehensive tool for scientific analyses on behalf of environmental policy.://A1994NU09400002-Nu094 Times Cited:67 Cited References Count:0 0921-2973ISI:A1994NU09400002=Klijn, F Ctr Environm Sci,Pob 9518,2300 Ra Leiden,NetherlandsEnglish<7c#Kline, J. D. Azuma, D. L. Moses, A.2003UModeling the spatially dynamic distribution of humans in the Oregon (USA) Coast Range347-361Landscape Ecology184ecological economics forest/urban interface land use change landscape modeling western Oregon USA LAND-USE CHANGE ECOLOGY GROWTH FOREST REGION DEFORESTATION MANAGEMENT LANDSCAPES DISTRICT TIMBERArticleA common approach to land use change analyses in multidisciplinary landscape-level studies is to delineate discrete forest and non-forest or urban and non-urban land use categories to serve as inputs into sets of integrated sub-models describing socioeconomic and ecological processes. Such discrete land use categories, however, may be inappropriate when the socioeconomic and ecological processes under study are sensitive to a range of human habitation. In this paper, we characterize the spatial dynamic distribution of humans throughout the forest landscape of western Oregon (USA). We develop an empirical model describing the spatial distribution and rate of change in historic building densities as a function of a gravity index of development pressure, existing building densities, slope, elevation, and existing land use zoning. We use the empirical model to project changes in building densities that are applied to a 1995 base map of building density to describe future spatial distributions of buildings over time. The projected building density maps serve as inputs into a multidisciplinary landscape-level analysis of socioeconomic and ecological processes in Oregon's Coast Range Mountains.://000185919200001 ISI Document Delivery No.: 732AT Times Cited: 5 Cited Reference Count: 44 Cited References: *NRCS, 1999, SUMM REP 1997 NAT RE *OR DEP REV, 1998, SPEC ASS FOR *US BUR CENS, 1992, CENS POP HOUS AZUMA DL, 1999, LAND USE CHANGE NONF BARLOW R, 1978, LAND RESOURCE EC EC BARLOW SA, 1998, J FOREST, V96, P10 BOCKSTAEL NE, 1996, AM J AGR ECON, V78, P1168 CAPOZZA DR, 1989, J URBAN ECON, V26, P295 EGAN AF, 2000, J FOREST, V98, P26 FAGAN WF, 2001, LANDSCAPE ECOL, V16, P33 FORTIN MJ, 1989, VEGETATIO, V83, P209 FRANZEN R, 1998, SUNDAY OREGONIA 1213 FRAYER WE, 1999, J FOREST, V97, P4 FUJITA M, 1982, J URBAN ECON, V12, P22 GEOGHEGAN J, 2001, AGR ECOSYST ENVIRON, V85, P25 GREENE WH, 1995, ECONOMETRIC ANAL GREENE WH, 1997, LIMDEP VERSION 7 0 U HAINING R, 1990, SPATIAL DATA ANAL SO HAUSER JR, 1978, OPER RES, V26, P406 HAYNES KE, 1984, GRAVITY SPATIAL INTE HELMER EH, 2000, ECOSYSTEMS, V3, P98 IRWIN EG, 2001, AGR ECOSYST ENVIRON, V85, P7 JENERETTE GD, 2001, LANDSCAPE ECOL, V16, P611 KLINE JD, 1999, GROWTH CHANGE, V30, P3 KLINE JD, 2000, LAND USE POLICY, V17, P349 KLINE JD, 2001, ECOSYSTEMS, V4, P3 MCGINNIS WJ, 1996, PNWGTR377 USDA FOR S MILLOY RE, 2000, NY TIMES 0810 MILLS ES, 1980, URBAN EC MIYAO T, 1981, DYNAMIC ANAL URBAN E NELSON GC, 1997, AM J AGR ECON, V79, P80 NUSSER SM, 1997, ENVIRON ECOL STAT, V4, P181 REILLY WJ, 1929, U TEXAS B, V2944 SCHNEIDER LC, 2001, AGR ECOSYST ENVIRON, V85, P83 SCHOORL JM, 2001, AGR ECOSYST ENVIRON, V85, P281 SERNEELS S, 2001, AGR ECOSYST ENVIRON, V85, P65 SHI YJ, 1997, LAND ECON, V73, P90 SPIES TA, 2002, INTEGRATING LANDSCAP, P179 SWENSON JJ, 2000, LANDSCAPE ECOL, V15, P713 TURNER MG, 1996, ECOL APPL, V6, P1150 WALSH SJ, 2001, AGR ECOSYST ENVIRON, V85, P47 WEAR DN, 1998, ECOSYSTEMS, V1, P575 WEAR DN, 1999, FOREST ECOL MANAG, V118, P107 WHEATON WC, 1982, J URBAN ECON, V12, P1 0921-2973 Landsc. Ecol.ISI:000185919200001Pacific NW Res Stn, Forestry Sci Lab, Corvallis, OR 97331 USA. Pacific NW Res Stn, Forestry Sci Lab, Portland, OR 97208 USA. Oregon State Univ, Dept Forest Sci, Corvallis, OR 97331 USA. Kline, JD, Pacific NW Res Stn, Forestry Sci Lab, 3200 SW Jefferson Way, Corvallis, OR 97331 USA.English|?Y 3Klug, Page E. Wisely, Samantha M. With, Kimberly A.2011Population genetic structure and landscape connectivity of the Eastern Yellowbelly Racer (Coluber constrictor flaviventris) in the contiguous tallgrass prairie of northeastern Kansas, USA281-294Landscape Ecology262FebWThe tallgrass prairie of North America has undergone widespread habitat loss and fragmentation (< 4% remains). The Flint Hills region of Kansas and Oklahoma is the largest tallgrass prairie remaining and therefore provides an opportunity to study the population genetic structure of grassland species in a relatively contiguous landscape and set a baseline for evaluating changes when the habitat is fragmented. We adopted a landscape genetics approach to identify how landscape structure affected dispersal, population genetic structure, and landscape connectivity of the Eastern Yellowbelly Racer (Coluber constrictor flaviventris) across a 13,500-km(2) landscape in northeastern Kansas, USA. The racer population had high allelic diversity, high heterozygosity, and was maintaining migration-drift equilibrium. Autocorrelation between genetic and geographic distance revealed that racers exhibited restricted dispersal within 3 km, and isolation-by-distance. Significant isolation-by-distance occurred at broad regional scales (> 100 km), but because of sufficient gene flow between locations, we were unable to define discrete subpopulations using Bayesian clustering analyses. Resistance distance, which considers the permeability of habitats, did not explain significant variation in genetic distance beyond Euclidean distance alone, suggesting that racers are not currently influenced by landscape composition. In northeastern Kansas, racers appear to be an abundant and continuously distributed snake that perceives the landscape as well connected with no cover type currently impeding snake dispersal or gene flow.!://WOS:000286474900010Times Cited: 0 0921-2973WOS:00028647490001010.1007/s10980-010-9554-2 <7b (Knappova, J. Hemrova, L. Munzbergova, Z.2012Colonization of central European abandoned fields by dry grassland species depends on the species richness of the source habitats: a new approach for measuring habitat isolation97-108Landscape Ecology271@agricultural landscape connectivity czech republic dispersal diversity fragmentation festuco-brometea secondary succession land-use history seminatural grasslands fragmented landscapes calcareous grasslands connectivity measures agricultural landscape community structure plant colonization extinction debt arable fieldsJanAbandoned fields are perceived as potential habitats for species of threatened semi-natural dry grasslands. However, information is lacking regarding how the spontaneous colonization of abandoned fields depends on the broader spatial context. We recorded the occurrence of 87 target species in 46 abandoned fields and 339 dry grasslands. We tested the effect of the isolation of abandoned fields from source grasslands on the number of dry grassland species occurring in abandoned fields either with or without habitat characteristics being used as covariates. The isolation of the fields was calculated using the distance and area (I (A) ) or distance and species richness (I (S) ) of source habitats. I (S) always explained the number of grassland species in the abandoned fields better than I (A) . The effect of isolation became smaller or even non-significant with the inclusion of covariates; it also changed with the method used for measuring distance (edge-to-edge or center-to-center), and it was lower when other abandoned fields were considered as additional source habitats. The different performance of the two isolation measures can be explained by the weak species-area relationship in the grasslands, indicating differences in their habitat quality. Species richness is a better proxy of habitat importance in terms of propagule source than habitat area, and the new isolation measure is therefore suitable for studying the effects of landscape structure on species richness in landscapes presenting a weak species-area relationship, such as areas exhibiting pronounced effects of land-use history. Inclusion of habitat characteristics as covariates may considerably alter conclusions regarding the effect of isolation, which might actually be overestimated when assessed separately.://000298228300008-864HI Times Cited:0 Cited References Count:57 0921-2973Landscape EcolISI:000298228300008}Knappova, J Acad Sci Czech Republic, Inst Bot, Zamek 1, CS-25243 Pruhonice, Czech Republic Acad Sci Czech Republic, Inst Bot, Zamek 1, CS-25243 Pruhonice, Czech Republic Acad Sci Czech Republic, Inst Bot, CS-25243 Pruhonice, Czech Republic Charles Univ Prague, Dept Bot, Fac Sci, Prague 12801, Czech Republic Charles Univ Prague, Fac Sci, Dept Ecol, CR-12844 Prague, Czech RepublicDOI 10.1007/s10980-011-9680-5English<78Knick, S. T. Rotenberry, J. T.1997WLandscape characteristics of disturbed shrubsteppe habitats in southwestern Idaho (USA)287-297Landscape Ecology125agriculture; Artemisia tridentata; Bromus tectorum; disturbance regime; exotic annual grassland; habitat fragmentation; landscape characteristics; military training; shrubsteppe; wildfire SPATIAL HETEROGENEITY; FIRE; ENVIRONMENT; COEXISTENCE; VEGETATION; DIVERSITYArticleOct We compared 5 zones in shrubsteppe habitats of southwestern Idaho to determine the effect of differing disturbance combinations on landscapes that once shared historically similar disturbance regimes. The primary consequence of agriculture, wildfires, and extensive fires ignited by the military during training activities was loss of native shrubs from the landscape. Agriculture created large square blocks on the landscape, and the landscape contained fewer small patches and more large shrub patches than non-agricultural areas. In contrast, fires left a more fragmented landscape. Repeated fires did not change the distribution of patch sizes, but decreased the total area of remaining shrublands and increased the distance between remaining shrub patches that provide seed sources. Military training with tracked vehicles was associated with a landscape characterized by small, closely spaced, shrub patches. Our results support the general model hypothesized for conversion of shrublands to annual grasslands by disturbance. Larger shrub patches in our region, historically resistant to fire spread and large-scale fires because of a perennial bunchgrass understory, were more fragmented than small patches. Presence of cheatgrass (Bromus tectorum), an exotic annual, was positively related to landscape patchiness and negatively related to number of shrub cells. Thus, cheatgrass dominance can contribute to further fragmentation and loss of the shrub patch by facilitating spread of subsequent fires, carried by continuous fuels, through the patch. The synergistic processes of fragmentation of shrub patches by disturbance, invasion and subsequent dominance by exotic annuals, and fire are converting shrubsteppe in southwestern Idaho to a new state dominated by exotic annual grasslands and high fire frequencies.://000077684100003 ISI Document Delivery No.: 150UN Times Cited: 19 Cited Reference Count: 44 Cited References: *ENV SYST RES I IN, 1993, ARC INFO VER 6 11 *SAS STAT I, 1990, SAS STAT US GUID VER, V2 *US DEP INT, 1979, SNAK RIV BIRDS PREY *US DEP INT, 1995, DRAFT MAN PLAN SNAK ALLEN EB, 1995, P WILDL SHRUB AR LAN, P7 AUGUST P, 1994, PHOTOGRAMM ENG REM S, V60, P41 BRAUN CE, 1976, WILSON B, V88, P165 BURROUGH PA, 1986, PRINCIPLES GEOGRAPHI CALLAWAY RM, 1993, ECOLOGY, V74, P1567 CASWELL H, 1993, SPECIES DIVERSITY EC, P99 CONNELL JH, 1978, SCIENCE, V199, P1302 DANTONIO CM, 1992, ANNU REV ECOL SYST, V23, P63 FLOYD DA, 1982, VEGETATIO, V50, P185 FORMAN RTT, 1986, LANDSCAPE ECOLOGY HARRIS LD, 1984, FRAGMENTED FOREST IS HOLT RD, 1984, AM NAT, V124, P377 KLEMMEDSON JO, 1964, BOT REV, V30, P226 KNICK ST, 1995, CONSERV BIOL, V9, P1059 KNICK ST, 1997, J WILDLIFE MANAGE, V61, P75 KNICK ST, 1997, PHOTOGRAMM ENG REM S, V63, P79 KOCHERT MN, 1986, RANGELANDS, V8, P217 KRUMMEL JR, 1987, OIKOS, V48, P321 LI HB, 1994, ECOLOGY, V75, P2446 MERRIAM G, 1988, TRENDS ECOL EVOL, V3, P16 MILLER TE, 1982, AM NAT, V120, P533 MILNE BT, 1991, QUANTITATIVE METHODS, P199 PALMER MW, 1992, AM NAT, V139, P375 PETERS EF, 1994, P EC MAN ANN RANG, P31 PICKETT STA, 1985, ECOLOGY NATURAL DIST SCHLESINGER WH, 1990, SCIENCE, V247, P1043 SHUGART HH, 1985, ECOLOGY NATURAL DIST, P353 SOUSA WP, 1984, ANNU REV ECOL SYST, V15, P353 TURNER MG, 1987, LANDSCAPE HETEROGENE TURNER MG, 1987, LANDSCAPE HETEROGENE, P85 TURNER MG, 1989, OIKOS, V55, P121 TURNER MG, 1991, QUANTITATIVE METHODS TURNER MG, 1994, J VEG SCI, V5, P731 TURNER MG, 1995, ECOL APPL, V5, P12 WHISENANT SG, 1990, P S CHEATGR INV SHRU, P4 WIENS JA, 1977, AM SCI, V65, P590 YENSEN DL, 1982, GRAZING HIST SW IDAH YENSEN DL, 1984, S BIOL ATR REL CHEN, P28 YOUNG JA, 1978, J RANGE MANAGE, V31, P283 YOUNG JA, 1989, WEED SCI, V37, P201 0921-2973 Landsc. Ecol.ISI:000077684100003 US Geol Survey, Raptor Res & Tech Assistance Ctr, Boise, ID 83706 USA. Univ Calif Riverside, Nat Reserve Syst, Riverside, CA 92521 USA. Univ Calif Riverside, Dept Biol, Riverside, CA 92521 USA. Knick, ST, US Geol Survey, Raptor Res & Tech Assistance Ctr, 970 Lusk St, Boise, ID 83706 USA.English<7)Knight, C. L. Briggs, J. M. Nellis, M. D.1994OExpansion of gallery forest on Konza Prairie Research Natural Area, Kansas, USA117-125Landscape Ecology92CGALLERY FOREST; HISTORICAL LANDUSE; BURNING; TALLGRASS PRAIRIE; GISArticleJunTo determine the dynamics of the spatial extent of gallery forest on Konza Prairie Research Natural Area (KPRNA), aerial photographs taken over a 46 year time frame were digitized into an ARC-INFO Geographic Information System (GIS). A Global Positioning System (GPS) was used to collect ground control points to co-register the photographs for each year. Gallery forest areas for the three major drainage boundaries (Kings Creek, Shane Creek, and White Pasture) were analyzed to assess the uniformity of change in the landscape system. Results indicated that the total gallery forest area on KPRNA has increased in area from 157 ha in 1939 to over 241 ha in 1985. During this time, there was an increase in the total number of patches and a decrease in the mean size of forest patches. However, the rate of increase was not consistent over this time period, nor was it uniform from one drainage basin or stream order to another. Detailed spatial analysis of the forested area with a geomorphology and digital elevation model of Konza Prairie showed that in 1985, 58% of the forest was on alluvial/colluvial soil, yet only 15% of that soil type was forested. In addition, over 70% of the forest was on the 0-15% slope interval, but only 15 - 20% of that slope interval was forested. These results may be attributed to a variety of factors such as changing management practices (i.e., frequency of fires and herbicide spraying) and the temporal constraints on extent to which the gallery forest can expand across the landscape.://A1994NU09400004 IISI Document Delivery No.: NU094 Times Cited: 47 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1994NU09400004JKNIGHT, CL, KANSAS STATE UNIV AGR & APPL SCI,DEPT GEOG,MANHATTAN,KS 66506.English|7w )Knight, C. L. Briggs, J. M. Nellis, M. D.1994OExpansion of Gallery Forest on Konza-Prairie-Research-Natural-Area, Kansas, USA117-125Landscape Ecology92?gallery forest historical landuse burning tallgrass prairie gisJunTo determine the dynamics of the spatial extent of gallery forest on Konza Prairie Research Natural Area (KPRNA), aerial photographs taken over a 46 year time frame were digitized into an ARC-INFO Geographic Information System (GIS). A Global Positioning System (GPS) was used to collect ground control points to co-register the photographs for each year. Gallery forest areas for the three major drainage boundaries (Kings Creek, Shane Creek, and White Pasture) were analyzed to assess the uniformity of change in the landscape system. Results indicated that the total gallery forest area on KPRNA has increased in area from 157 ha in 1939 to over 241 ha in 1985. During this time, there was an increase in the total number of patches and a decrease in the mean size of forest patches. However, the rate of increase was not consistent over this time period, nor was it uniform from one drainage basin or stream order to another. Detailed spatial analysis of the forested area with a geomorphology and digital elevation model of Konza Prairie showed that in 1985, 58% of the forest was on alluvial/colluvial soil, yet only 15% of that soil type was forested. In addition, over 70% of the forest was on the 0-15% slope interval, but only 15 - 20% of that slope interval was forested. These results may be attributed to a variety of factors such as changing management practices (i.e., frequency of fires and herbicide spraying) and the temporal constraints on extent to which the gallery forest can expand across the landscape.://A1994NU09400004-Nu094 Times Cited:50 Cited References Count:0 0921-2973ISI:A1994NU09400004HKnight, Cl Kansas State Univ Agr & Appl Sci,Dept Geog,Manhattan,Ks 66506Englishu<7R!Ko, D. W. He, H. S. Larsen, D. R.2006KSimulating private land ownership fragmentation in the Missouri Ozarks, USA671-686Landscape Ecology215Forest Land Ownership Spatial Simulation (FLOSS); neutral landscape model; non-industrial private forestland (NIPF); private ownership fragmentation (parcelization); Public Land Survey System (PLSS) LANDSCAPE PATTERNS; ECOLOGY; FOREST; HABITAT; COVERArticleJulNIncreasing land ownership fragmentation in the United States is causing concerns with respect to its ecological implications for forested landscapes. This is especially relevant given that human influence is one of the most significant driving forces affecting the forest landscape. A method for generating realistic land ownership maps is needed to evaluate the effects of ownership fragmentation on forest landscapes in combination with other natural processes captured in forest process models. Ownership patterns from human activities usually generate landscape boundary shapes different from those arising from natural processes. Spatial characteristics among ownership types - e.g., private, public ownership - may also differ. To address these issues, we developed the Fragmented Land Ownership Spatial Simulator (FLOSS) to generate ownership patterns that reflect the Public Land Survey System (PLSS) shapes and various patch size distributions among different types of ownership (e.g., private, public). To evaluate FLOSS performance, we compared the simulated patterns with various ownership fragmentation levels to the actual ownership patterns in the Missouri Ozarks by using selected landscape indices. FLOSS generated landscapes with spatial characteristics similar to actual landscapes, suggesting that it can simulate different levels of ownership fragmentation. This will allow FLOSS to serve as a feasible tool for evaluating forest management applications by spatially allocating various management scenarios in a realistic way. The potentials and limitations of FLOSS application are discussed.://000240500100004 ]ISI Document Delivery No.: 083ZE Times Cited: 0 Cited Reference Count: 36 Cited References: 1999, IRON COUNTY 1999 PLA 2000, BUTLER COUNTY 2000 P 2000, WAYNE COUNTY 2000 PL 2001, REYNOLDS COUNTY 2001 2001, RIPLEY COUNTY 2001 P BIRCH T, 1996, RESOURCE B NE, V136 BOTKIN DB, 1990, DISCORDANT HARMONIES DEBINSKI DM, 2000, CONSERV BIOL, V14, P342 DUBEY SD, 1967, TECHNOMETRICS, V9, P119 EFRON B, 1993, INTRODUCTION BOOTSTR EVANS M, 1993, STAT DISTRIBUTIONS FORTIN MJ, 2003, OIKOS, V102, P203 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GARDNER RH, 1999, LANDSCAPE ECOLOGICAL, P280 HARGROVE WW, 1992, LANDSCAPE ECOL, V6, P251 HE HS, 2000, LANDSCAPE ECOL, V15, P591 MCGARIGAL K, 1994, PNWGTR351 USDA FOR S MILNE BT, 1988, APPL MATH COMPUT, V27, P67 MILNE BT, 1989, QUANTITATIVE METHODS MLADENOFF DJ, 1995, CONSERV BIOL, V9, P279 MOSER WK, 2003, RESOURCE B NC, V226 ONEILL RV, 1992, LANDSCAPE ECOL, V7, P55 RADELOFF VC, 2000, OIKOS, V90, P417 SAURA S, 2000, LANDSCAPE ECOL, V15, P661 SPIES TA, 1994, ECOL APPL, V4, P555 TINKER DB, 1998, LANDSCAPE ECOL, V13, P149 TRZCINSKI MK, 1999, ECOL APPL, V9, P586 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P245 TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 TURNER MG, 1996, ECOL APPL, V6, P1150 VENABLES WN, 2002, MODERN APPL STAT S S WALLIN DO, 1994, ECOL APPL, V4, P569 WHITE CA, 1983, HIST RECTANGULAR SUR WIENS JA, 1989, FUNCT ECOL, V3, P385 WU SJ, 2002, J JAPAN STAT SOC, V32, P155 YAFFEE SLP, 1996, ECOSYSTEM MANAGEMENT 0921-2973 Landsc. Ecol.ISI:000240500100004Univ Missouri, Dept Forestry, Columbia, MO 65211 USA. Ko, DW, Univ Missouri, Dept Forestry, 203 Anheuser Busch Nat Resources Bldg, Columbia, MO 65211 USA. dwk248@mizzou.eduEnglishP<7Kochy, M. Wilson, S. D.2005dVariation in nitrogen deposition and available soil nitrogen in a forest-grassland ecotone in Canada191-202Landscape Ecology202Aspen parkland; Canada; fire; forest invasion; grazing; shrubland; sub-boreal; vegetation type; soil type ATMOSPHERIC DEPOSITION; TALLGRASS PRAIRIE; OXIDE EMISSIONS; PRESCRIBED FIRE; ECOSYSTEM; DYNAMICS; CANOPY; VEGETATION; MANAGEMENT; NUTRIENTArticleFebaRegional variation in nitrogen (N) deposition increases plant productivity and decreases species diversity, but landscape- or local -scale influences on N deposition are less well-known. Using ion-exchange resin, we measured variation of N deposition and soil N availability within Elk Island National Park in the ecotone between grassland and boreal forest in western Canada. The park receives regionally high amounts of atmospheric N deposition (22 kg ha(-1) yr(-1)). N deposition was on average higher ton clay-rich luvisols than on brunisols, and areas burned 1-15 years previously received more atmospheric N than unburned sites. We suggest that the effects of previous fires and soil type on deposition rate act through differences in canopy structure. The magnitude of these effects varied with the presence of ungulate grazers (bison, moose, elk) and vegetation type (forest, shrubland, grassland). Available soil N (ammonium and nitrate) was higher in burned than unburned sites in the absence of grazing, suggesting an effect of deposition. On grazed sites, differences between fire treatments were small, presumably because the removal of biomass by grazers reduced the effect of fire. Aspen invades native grassland in this region, and our results suggest that fire without grazing might reinforce the expansion of forest into grassland facilitated by N deposition.://000230299600006 % ISI Document Delivery No.: 942RN Times Cited: 1 Cited Reference Count: 60 Cited References: *IFIA FAOANO, 2001, GLOB EST GAS EM NH3 ABER JD, 1992, TRENDS ECOL EVOL, V7, P220 ARCHER SR, 1994, HDB AGR METEOROLOGY, P245 BAILEY AW, 1990, J RANGE MANAGE, V43, P212 BEIER C, 1989, ENVIRON POLLUT, V60, P257 BOBBINK R, 1998, J ECOL, V86, P717 BORK EW, 1997, CAN J BOT, V75, P1518 BROWN JR, 1998, J VEG SCI, V9, P829 CAIRNS AL, 1980, J WILDLIFE MANAGE, V44, P849 CAMPBELL ID, 2000, PALAEOGEOGR PALAEOCL, V164, P279 CORRE MD, 1999, BIOGEOCHEMISTRY, V44, P29 CROWN PH, 1977, 38 ALB I PED DANELL K, 2003, FOREST ECOL MANAG, V181, P67 DAVIS MA, 1998, J ECOL, V86, P652 DIAZ S, 1992, J VEG SCI, V3, P689 FACELLI JM, 1986, PHYTOCOENOLOGIA, V14, P263 FALKENGRENGRERUP U, 1989, AMBIO, V18, P179 FENN ME, 1998, ECOL APPL, V8, P706 FENSHAM RJ, 1992, AUST J BOT, V40, P123 FRANK DA, 1998, OECOLOGIA, V117, P564 GIBLIN AE, 1994, SOIL SCI SOC AM J, V58, P1154 GROFFMAN PM, 2000, GLOBAL BIOGEOCHEM CY, V14, P1061 GRUNDMANN GL, 1993, NEW PHYTOL, V124, P259 HARRELL WC, 2001, J RANGE MANAGE, V54, P685 HARRINGTON A, 2000, FORTUNE, V142, P188 HULBERT LC, 1969, ECOLOGY, V50, P874 JEFFERIES RL, 1997, TRENDS ECOL EVOL, V12, P74 KAZADA M, 1993, AGR ECOSYST ENVIRON, V47, P135 KELLMAN M, 1982, J BIOGEOGR, V9, P193 KNAPP AK, 1986, BIOSCIENCE, V36, P662 KOCHY M, 1997, ECOLOGY, V78, P732 KOCHY M, 1999, THESIS U REGINA REGI KOCHY M, 2000, OIKOS, V91, P385 KOCHY M, 2001, J ECOL, V89, P807 LEMKE RL, 1998, SOIL SCI SOC AM J, V62, P1096 LINDBERG SE, 1986, SCIENCE, V231, P141 LOVETT GM, 1999, ECOL APPL, V9, P1330 MARTON RB, 1956, J FOREST, V54, P468 MATSON P, 1997, NUTR CYCL AGROECOSYS, V48, P1 MOHN J, 2000, FOREST ECOL MANAG, V137, P113 NASON GE, 1988, SOIL SCI SOC AM J, V52, P821 OURA N, 2001, WATER AIR SOIL POL 2, V130, P673 PETERSEN EB, 1992, ECOLOGY MANAGEMENT U PETERSON DW, 2001, ECOL APPL, V11, P914 PIIRAINEN S, 1998, WATER AIR SOIL POLL, V105, P165 POTTER CS, 1991, J ECOL, V79, P97 RENNENBERG H, 1998, NEW PHYTOL, V139, P71 RISSER PG, 1982, ECOLOGY, V63, P1342 ROMO JT, 1993, AM MIDL NAT, V130, P106 SEASTEDT TR, 1985, OECOLOGIA, V66, P88 SHACHAK M, 1998, ECOL APPL, V8, P455 TANNER RL, 1990, ACIDIC PRECIPITATION, V3, P1 UNDERWOOD AJ, 1997, EXPT ECOLOGY THEIR L VANAUKEN OW, 2000, ANNU REV ECOL SYST, V31, P197 VANDOBBEN HF, 1999, FOREST ECOL MANAG, V114, P83 VILA M, 2001, FOREST ECOL MANAG, V147, P3 WAN SQ, 2001, ECOL APPL, V11, P1349 WEATHERS KC, 2001, CONSERV BIOL, V15, P1506 WOODMANSEE RG, 1979, PERSPECTIVES GRASSLA, P117 ZLOTIN R, 1980, ROLE ANIMALS BIOL CY 0921-2973 Landsc. Ecol.ISI:000230299600006Univ Regina, Dept Biol, Regina, SK S4S 0A2, Canada. Kochy, M, Univ Potsdam, Dept Biochem & Biol, Postfach 60 15 53, D-14415 Potsdam, Germany. martin.koechy@gmx.netEnglish <7c AKoen, E. L. Bowman, J. Garroway, C. J. Mills, S. C. Wilson, P. J.20122Landscape resistance and American marten gene flow29-43Landscape Ecology271Rboreal forest circuitscape conditional genetic distance dispersal graph theory landscape genetics map boundary martes americana ontario spatial principal component analysis mink mustela-vison microsatellite markers population-structure forest management industrial forest spatial-analysis circuit-theory habitat use inference connectivityJan!Landscape heterogeneity can influence animal dispersal by causing a directional bias in dispersal rate, as certain landscape configurations might promote, impede, or prevent movement and gene flow. In forested landscapes, logging operations often contribute to heterogeneity that can reduce functional connectivity for some species. American martens (Martes americana) are one such species, as they are considered specialists of late-seral coniferous forests. We assessed marten gene flow to test the hypothesis that habitat management has maintained landscape connectivity for martens in the managed forests of Ontario, Canada. We genotyped 653 martens at 12 microsatellite loci, sampled from 29 sites across Ontario. We expected that if forest management has an effect on marten gene flow, we would see a correlation between effective resistance, estimated by circuit theory, and genetic distance, estimated by population graphs. Although we found a positive relationship between effective resistance and genetic distance (Mantel r = 0.249, P < 0.001), marten gene flow was better described by isolation by Euclidean distance (Mantel r = 0.410, P < 0.001). Our results suggest that managed forests in Ontario are well connected for marten and neither impede nor promote marten gene flow at the provincial scale.://000298228300003-864HI Times Cited:1 Cited References Count:78 0921-2973Landscape EcolISI:000298228300003Koen, EL Trent Univ, Ontario Minist Nat Resources, Wildlife Res & Dev Sect, 2140 E Bank Dr, Peterborough, ON K9J 7B8, Canada Trent Univ, Ontario Minist Nat Resources, Wildlife Res & Dev Sect, 2140 E Bank Dr, Peterborough, ON K9J 7B8, Canada Trent Univ, Ontario Minist Nat Resources, Wildlife Res & Dev Sect, Peterborough, ON K9J 7B8, Canada Ontario Minist Nat Resources, NE Sci & Informat Sect, S Porcupine, ON P0N 1H0, Canada Trent Univ, Dept Biol, Peterborough, ON K9J 7B8, CanadaDOI 10.1007/s10980-011-9675-2English&? Koerner, Sally2011HThe utilization of remote sensing and modeling: savannas from a distance 1199-1200Landscape Ecology268Springer NetherlandsEarth and Environmental Science+http://dx.doi.org/10.1007/s10980-011-9634-y 0921-297310.1007/s10980-011-9634-yڽ7Koerner, SallyE Collins, ScottL2013sSmall-scale patch structure in North American and South African grasslands responds differently to fire and grazing 1293-1306Landscape Ecology287Springer NetherlandsiDominance-diversity Grass-forb interaction Heterogeneity Konza Prairie Kruger National Park Semi-variance 2013/08/01+http://dx.doi.org/10.1007/s10980-013-9866-0 0921-2973Landscape Ecol10.1007/s10980-013-9866-0English<7SKohler, F. Gillet, F. Reust, S. Wagner, H. H. Gadallah, F. Gobat, J. M. Buttler, A.2006PSpatial and seasonal patterns of cattle habitat use in a mountain wooded pasture281-295Landscape Ecology212Oautocorrelation; dung deposition; herbage removal; Jura mountains; principal coordinates of neighbour matrices; redundancy analysis; silvopastoral landscape; Switzerland; trampling; variance partitioning FREE-RANGING CATTLE; LANDSCAPE ECOLOGY; TEMPORAL PATTERNS; GRAZING BEHAVIOR; LONG-TERM; RED DEER; SCALE; RANGELAND; SYSTEMS; FORESTArticleFeb\Management-oriented models of cattle habitat use often treat grazing pressure as a single variable summarizing all cattle activities. This paper addresses the following questions: How does the spatial pattern of cattle effects vary between cattle activities in a highly heterogeneous landscape? Do these patterns change over the grazing season as forage availability decreases? What are the respective roles of natural and management-introduced structures? We estimated the intensity of herbage removal, dung deposition and trampling after each of three grazing periods on a grid of 25 m x25 m cells covering an entire paddock in the Swiss Jura Mountains. We found no significant positive correlations between cattle effects. Spatial patterns weakened through the season for grazing and trampling, whereas dunging patterns changed little between grazing periods. Redundancy analysis showed that different cattle effects were correlated with different environmental variables and that the importance of management-introduced variables was highest for herbage removal. Autocorrelograms and partial redundancy analyses using principal coordinates of neighbour matrices suggested that dunging patterns were more coarse-grained than the others. Systematic differences in the spatial and seasonal patterns of cattle effects may result in complex interactions with vegetation involving feedback effects through nutrient shift, with strong implications for ecosystem management. In heterogeneous environments, such as pasture-woodland landscapes, spatially explicit models of vegetation dynamics need to model cattle effects separately.://000235866400011 # ISI Document Delivery No.: 019WC Times Cited: 1 Cited Reference Count: 66 Cited References: *R DEV COR TEAM, 2004, R LANG ENV STAT COMP ANDERSON DM, 1980, J RANGE MANAGE, V33, P217 BAILEY DW, 1996, J RANGE MANAGE, V49, P386 BAILEY DW, 2001, J ANIM SCI, V79, P1883 BORCARD D, 1992, ECOLOGY, V73, P1045 BORCARD D, 2001, SPACEMAKER PROGRAM BORCARD D, 2002, ECOL MODEL, V153, P51 BORCARD D, 2004, ECOLOGY, V85, P1826 BRINDAMOUR A, 2005, LIMNOL OCEANOGR, V50, P465 COOK CW, 1966, J RANGE MANAGE, V19, P200 COSTA G, 1990, FOURRAGES, V123, P305 COUGHENOUR MB, 1991, J RANGE MANAGE, V44, P530 COUSINS SAO, 2003, LANDSCAPE ECOL, V18, P315 DECKERS JA, 1998, WORLD REFERENCE BASE DUNGAN JL, 2002, ECOGRAPHY, V25, P626 DUTILLEUL P, 1993, BIOMETRICS, V49, P305 ETIENNE M, 1996, W EUROPEAN SILVOPAST GANDER A, 2003, B GEOBOT I ETH, V69, P3 GILLET F, 1996, J VEG SCI, V7, P13 GILLET F, 2002, ECOLOGICAL MODELLING, V187, P267 HAHN BD, 1999, AGR SYST, V62, P29 HART RH, 1993, J RANGE MANAGE, V46, P81 HAVLICEK E, 1996, ETUDE GESION SOLS, V3, P167 HESTER AJ, 1998, J APPL ECOL, V35, P772 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 JEWELL P, 2002, THESIS ETHZ ZURICH KOHLER F, 2004, J VEG SCI, V15, P143 LEGENDRE P, 1993, ECOLOGY, V74, P1659 LEGENDRE P, 1998, NUMERICAL ECOLOGY LEGENDRE P, 2001, PROGRAM MOD T TEST MARSH R, 1970, HERB ABSTR, V40, P123 MCGECHAN MB, 2004, AGR ECOSYST ENVIRON, V103, P149 MILLER RF, 1976, J RANGE MANAGE, V29, P367 MITLOHNER FM, 2001, J ANIM SCI, V79, P2327 OKLAND RH, 1994, J VEG SCI, V5, P117 OLFF H, 1998, TRENDS ECOL EVOL, V13, P261 OSUJI PO, 1974, J RANGE MANAGE, V27, P437 OWENS MK, 1991, J RANGE MANAGE, V44, P118 PERRENOUD A, 2003, EXPLOITATION DURABLE PETERSON PR, 1996, NUTR CYCLING FORAGE, P203 PETERSON RA, 1955, J RANGE MANAGE, V8, P51 PETERSON RG, 1956, AGRON J, V48, P440 PINCHAK WE, 1991, J RANGE MANAGE, V44, P267 PRATT RM, 1986, J APPL ECOL, V23, P539 PUTMAN RJ, 1987, J APPL ECOL, V24, P369 RICE RW, 1983, DEV ENV MODELLING, V5, P475 ROATH LR, 1982, J RANGE MANAGE, V35, P332 ROOVERS P, 2004, APPL VEG SCI, V7, P111 SCHUTZ M, 2003, FOREST ECOL MANAG, V181, P177 SENFT RL, 1985, J RANGE MANAGE, V38, P82 SENFT RL, 1987, BIOSCIENCE, V37, P789 SHIYOMI M, 1999, ECOL MODEL, V119, P231 TATE KW, 2003, J RANGE MANAGE, V56, P432 TERBRAAK CJF, 2002, CANOCO REFERENCE MAN THOMPSON CM, 2002, LANDSCAPE ECOL, V17, P569 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 2001, LANDSCAPE ECOLOGY TH VANOENE H, 1999, ECOSYSTEMS, V2, P122 VANREES H, 1983, J RANGE MANAGE, V36, P740 VERWEIJ PA, 1995, THESIS INT I GEOINFO WEBER GE, 1998, J APPL ECOL, V35, P687 WHITE SL, 2001, J ENVIRON QUAL, V30, P2180 WIENS JA, 1989, FUNCT ECOL, V3, P385 WU JG, 2002, ECOL MODEL, V153, P7 WU JG, 2002, LANDSCAPE ECOL, V17, P355 WU JG, 2004, LANDSCAPE ECOL, V19, P125 0921-2973 Landsc. Ecol.ISI:000235866400011Univ Neuchatel, Lab Plant Ecol, CH-2007 Neuchatel, Switzerland. Swiss Fed Res Stn, WSL, CH-1015 Lausanne, Switzerland. Ecole Polytech Fed Lausanne, Swiss Fed Inst Technol, Lab Ecol Syst, CH-1015 Lausanne, Switzerland. Swiss Fed Res Inst, WSL, CH-8903 Birmensdorf, Switzerland. Gillet, F, Ecole Polytech Fed Lausanne, ENAC, ISTE, ECOS, Ecublens Stn 2, CH-1015 Lausanne, Switzerland. francois.gillet@epfl.chEnglishi<7"Koivula, M. J. Vermeulen, H. J. W.2005VHighways and forest fragmentation - effects on carabid beetles (Coleoptera, Carabidae)911-926Landscape Ecology208Carabidae; fragmentation; highway; isolation; mark-recapture; traffic HABITAT DESTRUCTION; EXTINCTION DEBT; GROUND BEETLES; ROADS; CONSERVATION; ASSEMBLAGES; POPULATIONS; COMPETITION; DISPERSAL; MOVEMENTSArticleDecWe conducted two studies on how highways affect their adjacent habitats by sampling carabid beetles (Coleoptera, Carabidae) in patches of formerly continuous forest next to highways. (1) We sampled carabids at 14 highway intersections near Helsinki, Finland. Each intersection (constructed 2-40 years ago) had two forested patches to study: a remnant (0.5-37.4 ha) and, isolated from the remnant by an intersection lane, an islet (size 0.2-1.8 ha). Pitfall trap catch data (2301 carabids, 25 species) showed that remnants hosted higher catches of three carabid species, and slightly higher species richness, than islets (patch-size effect). Time since intersection construction had no apparent effect on carabids. Traffic volume along the intersection lane determined the assemblage structure of carabids in dry patches, and the abundance of a forest carabid Calathus micropterus. Compared to moist patches, drier patches hosted lower catches of four generalist species; they also had different assemblages of carabids (habitat-type effect). An interaction between patch size and habitat type for a forest generalist Pterostichus oblongopunctatus indicated that the patch-size effect was dependent on habitat type. (2) We examined possible dispersal of carabids among forested patches that were separated by highway lanes in Drenthe, the Netherlands. We released 2696 marked individuals of 10 species, and recaptured 376 using dry pitfall traps. We found no evidence for inter-patch movement for nine forest species, but 22 of 225 recaptured individuals of Poecilus versicolor, an eurytopic open-habitat species, had crossed the highway. Catches of seven forest species were also significantly lower in the road verges, compared to the adjacent forests. These two studies suggest that (i) decreasing patch size negatively affects forest-carabid catch and overall species richness, (ii) habitat type can affect the intensity of the patch-size effect, (iii) carabid assemblages of forest fragments vary with traffic volume (which may be linked with urbanization), (iv) forest carabids rarely cross highways, and (v) open habitats associated with road margins are dispersal barriers for forest carabids.://000233036400002 ISI Document Delivery No.: 980RR Times Cited: 2 Cited Reference Count: 53 Cited References: 2003, ROAD FACTS 2003 *R DEV COR TEAM, 2004, R LANG ENV STAT COMP BATTIN J, 2004, CONSERV BIOL, V18, P1482 BORG I, 1997, MODERN MULTIDIMENSIO BREIMAN L, 1998, CLASSIFICATION REGRE DEATH G, 2002, ECOLOGY, V83, P1105 DENBOER PJ, 1977, MISCELLANEOUS PAPERS, V14, P1 DENBOER PJ, 1990, J EVOLUTION BIOL, V3, P19 DEVRIES HH, 1996, THESIS U WAGENINGEN DICKSON BG, 2002, J WILDLIFE MANAGE, V66, P1235 DUFRENE M, 1997, ECOL MONOGR, V67, P345 DUFRENE M, 1998, PROGRAM INDVAL VERSI DYER SJ, 2002, CAN J ZOOL, V80, P839 EISTO AK, 2000, CONSERV BIOL, V14, P1413 EVERSHAM BC, 1994, BIODIVERS CONSERV, V3, P538 FORMAN RTT, 1998, ANNU REV ECOL SYST, V29, P207 FORMAN RTT, 2000, CONSERV BIOL, V14, P31 FORMAN RTT, 2003, ROAD ECOLOGY SCI SOL GLOYNE CC, 2001, WILDLIFE BIOL, V7, P117 HALME E, 1993, ANN ZOOL FENN, V30, P17 HANSKI I, 1999, METAPOPULATION ECOLO HOURDEQUIN M, 2000, CONSERV BIOL, V14, P16 JONGMAN RHG, 1995, DATA ANAL COMMUNITY KELLER I, 2003, P ROY SOC LOND B BIO, V270, P417 KINNUNEN H, 1999, THESIS U HELSINKI KOIVULA M, 2002, FOREST ECOL MANAG, V167, P103 KOIVULA M, 2003, ENTOMOL FENNICA, V14, P1 KOIVULA M, 2003, PROTECT WHAT WE KNOW, P287 KOIVULA M, 2004, J INSECT CONSERVATIO, V8, P297 KOIVULA M, 2005, EUROPEAN CARABIDOLOG, P151 LEGENDRE P, 1998, NUMERICAL ECOLOGY LINDQUIST A, 1985, STOCHASTICS, V15, P1 LINDROTH CH, 1986, CARABIDAE COLEOPTE 2, V15 LINDROTH CH, 1992, GROUND BEETLES CAR 1 LOEHLE C, 1996, ECOL APPL, V6, P784 LOREAU M, 1990, OIKOS, V58, P25 LOREAU M, 1992, ANN ZOOL FENN, V28, P49 MADER HJ, 1984, BIOL CONSERV, V29, P81 MADER HJ, 1990, BIOL CONSERV, V54, P209 MCDONNELL MJ, 1997, URBAN ECOSYSTEMS, V1, P21 MURCIA C, 1995, TRENDS ECOL EVOL, V10, P58 NIEMELA J, 1993, OIKOS, V66, P325 NIEMELA J, 1993, PERSPECTIVES INSECT, P29 NIEMELA J, 1999, DIVERS DISTRIB, V5, P121 SCHOTZCHRISTENS.B, 1965, NAT JUTL, V11, P11 SOKAL RR, 1995, BIOMETRY PRINCIPLES THIELE HU, 1977, ZOOPHYSIOL ECOL, V10, P369 TILMAN D, 1994, NATURE, V371, P65 TROMBULAK SC, 2000, CONSERV BIOL, V14, P18 TURIN H, 1991, TIJDSCHR ENTOMOL, V134, P279 VANHUIZEN THP, 1980, ENTOMOL BER, V40, P166 VERMEULEN HJW, 1994, BIOL CONSERV, V69, P339 VERMEULEN HJW, 1995, THESIS U WAGENINGEN 0921-2973 Landsc. Ecol.ISI:000233036400002Univ Alberta, Dept Renewable Resources, Edmonton, AB T6G 2E3, Canada. Secretariaat Stichting WBBS, NL-9409 TV Loon, Netherlands. Koivula, MJ, Univ Alberta, Dept Renewable Resources, 4-42 Earth Sci Bldg, Edmonton, AB T6G 2E3, Canada. mkoivula@ualberta.caEnglish2}?$Kondolf, G. M. Piegay, H. Landon, N.2007JChanges in the riparian zone of the lower Eygues River, France, since 1830367-384Landscape Ecology223historical analysis; channel changes; land use; human impacts; river restoration and conservation; riparian vegetation CHANNEL; TAGLIAMENTO; COMMUNITIES; DIVERSITY; FORESTS; ALPS MarThe riparian forests along braided rivers are dynamic, frequently rejuvenated by floods and channel changes, and thus dominated by pioneer to middle stages of succession; they are sites of high biodiversity in some regions. The Lower Eygues River (drainage area 1150 km 2 in southeastern France) is such a braided river system with large alluvial forests dominated by Salix alba, Populus alba, and P. nigra. It was identified as a site of ecological interest by the EU under the Natura 2000 program. Such forests elsewhere in Europe have been identified as reference ecosystems. We documented the historical evolution of this alluvial forest from detailed (1:2500 scale) early 19th C parcel maps, early 20th C topographic maps, aerial photography from 1947 to 1996, and field surveys of topography and riparian vegetation in 1997-1998. Our results show that in 1830, the channel was wide, aggraded, and agricultural pressure extended literally to the channel edge. With decline in the rural population and reduced agricultural and grazing pressure in the catchment, erosion rates declined. Reduced sediment supply led to channel narrowing and incision. This channel narrowing, coupled with reduced agricultural pressure along the banks, has allowed riparian forest to colonize former active channel areas, especially within late 19th-century 20th century flood dykes. In recent decades, aggregate mining, and clearing for recreation and agriculture have fragmented the forest. Thus, the alluvial forest of the Lower Eygues is largely an artifact of changing human land-use over the past century, a context that should frame efforts for preservation and restoration. ://000244455200004 0921-2973ISI:000244455200004|? CKong, Weijing Sun, Osbert Jianxin Chen, Yaning Yu, Yi Tian, Ziqiang2010hPatch-level based vegetation change and environmental drivers in Tarim River drainage area of West China 1447-1455Landscape Ecology259NovjInformation on vegetation-related land cover change and the principle drivers is critical for environmental management and assessment of desertification processes in arid environments. In this study, we investigated patch-level based changes in vegetation and other major land cover types in lower Tarim River drainage area in Xinjiang, West China, and examined the impacts of environmental factors on those changes. Patterns of land cover change were analyzed for the time sequence of 1987-1999-2004 based on satellite-derived land classification maps, and their relationships with environmental factors were determined using Redundancy Analysis (RDA). Environmental variables used in the analysis included altitude, slope, aspect, patch shape index (fractal dimension), patch area, distance to water body, distance to settlements, and distance to main roads. We found that during the study period, 26% of the land experienced cover changes, much of which were the types from the natural riparian and upland vegetation to other land covers. The natural riparian and upland vegetation patches were transformed mostly to desert and some to farmlands, indicating expanding desertification processes of the region. A significant fraction of the natural riparian and upland vegetation experienced a phase of alkalinity before becoming desert, suggesting that drought is not the exclusive environmental driver of desertification in the study area. Overall, only a small proportion of the variance in vegetation-related land cover change is explainable by environmental variables included in this study, especially during 1987-1999, indicating that patch-level based vegetation change in this region is partly attributable to environmental perturbations. The apparent transformation from the natural riparian and upland vegetation to desert indicates an on-going process of desertification in the region.!://WOS:000281981000011Times Cited: 0 0921-2973WOS:00028198100001110.1007/s10980-010-9505-y |?[ 0Koniak, Gili Noy-Meir, Imanuel Perevolotsky, Avi2011kModelling dynamics of ecosystem services basket in Mediterranean landscapes: a tool for rational management109-124Landscape Ecology261Jan@Natural ecosystems are life-supporting systems providing diverse ecosystem services (ESs) and benefits to human societies: e.g., food and clean water, recreation opportunities or climate regulation. The contribution of natural and semi-natural ecosystems to the provision of such services depends to a large extent on vegetation structure and composition, which, in turn, change as a result of interactions between human decisions about land management, and spontaneous biological and environmental processes. Rational management of these dynamic ecosystems requires an ability to predict short- and long-term effects of management decisions on the desired ESs. The vegetation then contributes to, and modifies, the products and services obtained from the land. We applied mathematical modeling to study these complex relationships. We developed a model for a Mediterranean ecosystem which predicts the dynamics of multiple services in response to management scenarios, mediated by vegetation changes. Six representative ESs representing different groups were selected, based on available scientific information, for a detailed study: (1) density of geophytes, (2) potential contribution to honey production, (3) energy density of fleshy fruits foraged by birds, (4) forage for goats, (5) forage for cattle, and (6) carbon retention in woody plants. Mean contributions to each service by different vegetation cover types were estimated, and the overall service provided by the site was calculated as a weighted mean of these contributions. Services were measured in their appropriate units and subsequently standardized to a percentage of the maximum value observed in the study area. We attempted to combine all studied ESs, despite their different nature, into one "ESs basket". This paper presents the dynamics of simulated vegetation composition and values of services in response to management scenarios involving grazing, fire and their combinations. Our approach can help land managers to evaluate alternative management scenarios by presenting the "services basket" obtained from the entire managed area.!://WOS:000286004400010Times Cited: 0 0921-2973WOS:00028600440001010.1007/s10980-010-9540-8ڽ7 ,Kool, JohnathanT Moilanen, Atte Treml, EricA2013=Population connectivity: recent advances and new perspectives165-185Landscape Ecology282Springer Netherlands^Dispersal Spatial ecology Review Tracking Population genetics Modeling Conservation Management 2013/02/01+http://dx.doi.org/10.1007/s10980-012-9819-z 0921-2973Landscape Ecol10.1007/s10980-012-9819-zEnglish<7d $Koomen, E. Opdam, P. Steingrover, E.2012@Adapting complex multi-level landscape systems to climate change469-471Landscape Ecology274Sclimate change climate adaptation landscape systems multi-level approach adaptationApr[Adaptation to climate change is becoming a prominent issue in both landscape research and land-use planning. Current research focuses mainly on the description of potential impacts for different societal sectors and in general fails to provide useful information to help define climate adaptation strategies and specific policy measures or development plans. This editorial briefly explores the reasons why this may be the case and proposes a conceptual framework for more effective climate adaptation research. Furthermore, it introduces three papers that address adaptation of landscape systems to climate change as an integrated multi-level challenge. The included papers focus on the relationship between climate-induced changes in the natural system and the economics-oriented societal system and specifically address the interdependencies across scales.://000302346900001-919RS Times Cited:0 Cited References Count:12 0921-2973Landscape EcolISI:000302346900001Koomen, E Vrije Univ Amsterdam, Fac Econ, De Boelelaan 1105, NL-1081 HV Amsterdam, Netherlands Vrije Univ Amsterdam, Fac Econ, De Boelelaan 1105, NL-1081 HV Amsterdam, Netherlands Vrije Univ Amsterdam, Fac Econ, NL-1081 HV Amsterdam, Netherlands Vrije Univ Amsterdam, Business Adm, NL-1081 HV Amsterdam, Netherlands Alterra Wageningen UR, Landscape Ctr, NL-6708 PB Wageningen, Netherlands Wageningen Univ, Land Use Planning Grp, NL-6708 PB Wageningen, NetherlandsDOI 10.1007/s10980-012-9721-8English<79Koper, N. Schmiegelow, F. K. A.2006uA multi-scaled analysis of avian response to habitat amount and fragmentation in the Canadian dry mixed-grass prairie 1045-1059Landscape Ecology217KAkaike's Information Criterion; Canada; habitat loss and fragmentation; mixed-effects models; mixed-grass prairie; model selection; nest success; prairie birds; spatial scale DUCK NEST SUCCESS; GOODNESS-OF-FIT; POTHOLE REGION; SOUTHERN SASKATCHEWAN; LANDSCAPE STRUCTURE; AREA SENSITIVITY; PATCH SIZE; BIRDS; CONSERVATION; ABUNDANCEArticleOctPrevious research has suggested that ducks and songbirds may benefit from prairie landscapes that consist primarily of contiguous grasslands. However, the relative importance of landscape-level vs. local characteristics on mechanisms underlying observed patterns is unclear. We measured effects of grassland amount and fragmentation on upland and wetland songbird and duck density and nest success, and on some nest predators, across 16 landscapes in southern Alberta, Canada. We compared these landscape-level effects with local-scale responses, including distance to various edges and vegetation characteristics. We also evaluated several statistical approaches to comparing effects of habitat characteristics at multiple spatial scales. Few species were influenced by grassland amount or fragmentation. In contrast, distance to edge and local vegetation characteristics had significant effects on densities and nest success of many species. Previous studies that reported effects of landscape characteristics may have detected patterns driven by local mechanisms. As a corollary, results were very sensitive to statistical model structure; landscape level effects were much less apparent when local characteristics were included in the models.://000241010900007 ISI Document Delivery No.: 091FA Times Cited: 0 Cited Reference Count: 75 Cited References: *CTR TOP INF, 2000, UPD ROAD NETW URN PR *INS CORP, 2001, S PLUS 6 WIND GUID S, V1 *PRAIR FARM REH AM, 2002, PFRA UNG LANDC CAN P *R FDN STAT COMP, 2002, R PROJ STAT COMP *SAS I INC, 2001, SAS SYST WIND VERS 8 ARTMANN MJ, 2001, WILDLIFE SOC B, V29, P232 AUSTIN JE, 1995, BIRDS N AM, V163, P1 AUSTIN JE, 1998, BIRDS N AM, V338, P1 AUSTIN JE, 2001, ENVIRON MONIT ASSESS, V69, P29 BAKKER KK, 2002, CONSERV BIOL, V16, P1638 BEASON RC, 1995, BIRDS N AM, V195, P1 BENDER DJ, 1998, ECOLOGY, V79, P517 BERGIN TM, 2000, LANDSCAPE ECOL, V15, P131 BEYER H, 2003, HAWTHS ANAL TOOLS BURNHAM KP, 1998, MODEL SELECTION INFE CHALFOUN AD, 2002, CONSERV BIOL, V16, P306 DAVIS SK, 1999, WILSON BULL, V111, P389 DAVIS SK, 2004, AUK, V121, P1130 DINSMORE SJ, 2002, ECOLOGY, V83, P3476 DONOVAN TM, 2001, ECOL APPL, V11, P871 DRILLING N, 2002, BIRDS N AM, V658, P1 DUBOWY PJ, 1996, BIRDS N AM, V217, P1 FAHRIG L, 1998, ECOL MODEL, V105, P273 FAHRIG L, 2003, ANNU REV ECOL EVOL S, V34, P487 FLASPOHLER DJ, 2001, ECOL APPL, V11, P32 FLATHER CH, 2002, AM NAT, V159, P40 FLETCHER RJ, 2002, J WILDLIFE MANAGE, V66, P1011 GIBBS JP, 2000, CONSERV BIOL, V14, P314 GREENWOOD RJ, 1995, WILDLIFE MONOGR, V128, P1 GUZY MJ, 1999, BIRDS N AM, V448, P1 HERKERT JR, 1995, AM MIDL NAT, V134, P41 HERKERT JR, 2003, CONSERV BIOL, V17, P587 HILL DP, 1997, BIRDS N AM, V288, P1 HOEKMAN ST, 2002, J WILDLIFE MANAGE, V66, P883 HOEKSTRA JM, 2005, ECOL LETT, V8, P23 HOLLAND JD, 2004, BIOSCIENCE, V54, P227 HUGHES JP, 1999, J WILDLIFE MANAGE, V63, P523 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 JIANG JM, 2001, ANN STAT, V29, P1137 JOHNSON DH, 2001, AUK, V118, P24 JONES SL, 2002, BIRDS N AM, V624, P1 KNICK ST, 1995, CONSERV BIOL, V9, P1059 KOPER N, 2004, THESIS U ALBERTA EDM KROODSMA DE, 1997, BIRDS N AM, V308, P1 LANYON WE, 1994, BIRDS N AM, V104, P1 LESCHACK CR, 1997, BIRDS N AM, V283, P1 LI HB, 2004, LANDSCAPE ECOL, V19, P389 LOWTHER PE, 1993, BIRDS N AM, V47, P1 MCGARIGAL K, 2002, ECOL APPL, V12, P335 MCGARIGAL K, 2002, FRAGSTATS SPATIAL PA NAUGLE DE, 2001, WETLANDS, V21, P1 OCONNOR RJ, 1999, STUDIES AVIAN BIOL, V19, P45 PENDERGAST JF, 1996, INT STAT REV, V64, P89 PHILLIPS ML, 2003, J WILDLIFE MANAGE, V67, P104 PINHEIRO JC, 2000, MIXED EFFECTS MODELS QUINN GP, 2002, EXPT DESIGN DATA ANA RIBIC CA, 2001, AM MIDL NAT, V146, P105 ROBBINS MB, 1999, BIRDS N AM, V439, P1 ROHWER FC, 2002, BIRDS N AM, V625, P1 SCHINDLER DW, 2001, CAN J FISH AQUAT SCI, V58, P18 SODERSTROM B, 2000, CONSERV BIOL, V14, P522 STEPHENS SE, 2003, BIOL CONSERV, V115, P101 TWEDT DJ, 1995, BIRDS N AM, V192, P1 VANDERHAEGEN WM, 2000, CONSERV BIOL, V14, P1145 VILLARD MA, 1999, CONSERV BIOL, V13, P774 WHEELWRIGHT NT, 1993, BIRDS N AM, V45, P1 WIENS JA, 1969, ORNITHOL MONOGR, V8, P1 WIENS JA, 1989, FUNCT ECOL, V3, P385 WIENS JA, 1994, IBIS, V137, P97 WINTER M, 1999, CONSERV BIOL, V13, P1424 WINTER M, 2003, PRAIRIE NATURALIST, V35, P197 WITH KA, 1995, ECOLOGY, V76, P2446 WU JG, 2004, LANDSCAPE ECOL, V19, P125 YASUKAWA K, 1995, BIRDS N AM, V184, P1 ZHENG BY, 2000, STAT MED, V19, P1265 0921-2973 Landsc. Ecol.ISI:000241010900007Univ Alberta, Dept Renewable Resources, Edmonton, AB T6G 2H1, Canada. Koper, N, Univ Manitoba, Inst Nat Resources, Winnipeg, MB R3T 2N2, Canada. koper@cc.umanitoba.caEnglishE}?9Koper, Nicola Schmiegelow, Fiona K. A. Merrill, Evelyn H.2007xResiduals cannot distinguish between ecological effects of habitat amount and fragmentation: implications for the debate811-820Landscape Ecology226Jul&://BIOSIS:PREV200700463284 0921-2973BIOSIS:PREV200700463284|? 1Koper, Nicola Walker, David J. Champagne, Janessa2009]Nonlinear effects of distance to habitat edge on Sprague's pipits in southern Alberta, Canada 1287-1297Landscape Ecology2410Effects of habitat edge may influence habitat quality, but landscape-scale implications of edge effects have rarely been quantified. Sprague's pipit (Anthus spragueii), a grassland obligate songbird, is declining rapidly throughout its range. Although habitat loss is implicated in the decline, the causes are not well understood. We conducted 290 point counts across a 120 x 130 km study area in southern Alberta, Canada, between 2000 and 2002, and used nonlinear regression to determine effects of distance to water, roads, and cropland or forage habitats on relative abundance of Sprague's pipits. We then used a geographic information system (GIS) to determine the effect of edges on habitat suitability as indexed by relative abundance. Sprague's pipit relative abundances declined by 25% from the maximum predicted relative abundance within 900 m (CI = 660-1,280) of croplands or forage crops, and 340 m (CI = 280-460) of wetlands, but there was no effect of roads. Fewer than 1% of grassland patches in the study area contained any habitat far enough away from edge that they would be predicted to support at least 75% of the relative abundance of pipits expected in the absence of edge effects. Only 33% of the landscape can support 75% or more of the relative abundance expected in the absence of edge effects, as a result of habitat conversion or edge effects. Sprague's pipit populations may be declining in part because edge effects greatly magnify effects of habitat loss.%://BIOSIS:PREV201000014105Times Cited: 0 0921-2973BIOSIS:PREV201000014105:10.1007/s10980-009-9375-3|?/Kopperoinen, Leena Itkonen, Pekka Niemela, Jari2014Using expert knowledge in combining green infrastructure and ecosystem services in land use planning: an insight into a new place-based methodology 1361-1375Landscape Ecology298OctGreen infrastructure (GI) is a strategic planning instrument to achieve sustainable development. The main functions of GI are to protect biodiversity and safeguard and enhance the provision of ecosystem services (ES). In this paper we present the development of a semi-quantitative place-based method, aiming at assessing GI based on the provision potential of all main ES. Our method combines a wide spectrum of GIS data with expert assessments. Here we focus especially on how interaction with experts and local and regional actors impacted the method development. Our results showed that involving experts in dataset selection is very useful in compiling the most relevant data for the assessment of ES. Expert knowledge is also valuable in evaluating the actual coverage and quality of datasets. By involving both experts and local and regional actors in assessing ES provision potential we can add local knowledge to the general scientific understanding. Qualitative assessments can be complemented with quantitative data in our method. The resulting maps support land use planning, as they assist in identifying the multifunctional key areas of GI and in examining the provision potential of various ES. The group discussions involved in our method provided an additional benefit, as the experts and local and regional actors felt that this discussion platform enhanced their understanding of both GI and ES.!://WOS:000342078600008Times Cited: 2 0921-2973WOS:00034207860000810.1007/s10980-014-0014-2 <7WKou, X. J. Baker, W. L.2006LA landscape model quantifies error in reconstructing fire history from scars735-745Landscape Ecology215error analysis; fire history; fire scars; paleoecology; spatial model SOUTHERN CASCADES; FOREST; REGIMES; CALIFORNIA; SIZES; USAArticleJulqReconstructing fire regimes from fire scars is widely used in fire ecology to understand the role of fire and to determine prescriptions for restoring fire, but systematic analyses of the accuracy of fire-regime reconstruction have never been done. Errors in reconstruction may lead to a misunderstanding of the role of fire or incorrect restoration prescriptions. Here, a stochastic landscape model is used to quantitatively assess the accuracy of a commonly used statistic, the composite fire interval (CFI), as an estimator of the population mean fire interval or fire rotation, which are the central parameters useful in comparing fire regimes. Seven factors, that may affect accuracy, are explored. Two control the fire regime, one controls the scarring process, and the other four define the sampling and analysis procedure. Results show that: (1) CFI can be from 0.15 to 5.0 times the population mean fire interval, a range of more than 30 times; (2) all factors, except population mean fire interval, significantly affect accuracy; (3) accuracy shows predictable patterns that could be useful in designing a sound sampling scheme and choosing a proper analysis method. However, the complexity of effects of these factors and the need for some prior knowledge of them make it difficult to design sampling and analysis procedures to accurately estimate the population mean fire interval.://000240500100009 ISI Document Delivery No.: 083ZE Times Cited: 1 Cited Reference Count: 24 Cited References: ARNO SF, 1983, INT301 USDA FOR SERV BAKER WL, IN PRESS INT J WILDL BAKER WL, 2001, CAN J FOREST RES, V31, P1205 BEATY RM, 2001, J BIOGEOGR, V28, P955 CHOU YH, 1993, FOREST SCI, V39, P835 CUMMING SG, 2001, CAN J FOREST RES, V31, P1297 DIETERICH JH, 1980, P FIR HIST WORKSH, P8 DIETERICH JH, 1980, RM200 USDA FOR SERV EBERHART KE, 1987, CAN J FOREST RES, V17, P1207 GRISSINOMAYER HD, 1995, THESIS U ARIZONA TUC JOHNSON EA, 1994, ADV ECOL RES, V25, P239 KEELEY JE, 2000, WILDERNESS SCI TIME, V5, P255 KIPFMUELLER KF, 2000, J BIOGEOGR, V27, P71 KOU X, 1997, THESIS NE FORESTRY U MCBRIDE JR, 1983, TREE RING B, V43, P51 MILLER C, 1999, CAN J FOREST RES, V29, P202 MILLER C, 2000, LANDSCAPE ECOL, V15, P145 MORITZ MA, 1997, ECOL APPL, V7, P1252 NIKLASSON M, 2000, ECOLOGY, V81, P1484 ROMME WR, 1980, P FIR HIST WORKSH OC, P135 SACKETT SS, 1980, RM392 USDA FOR SERV TAYLOR AH, 2000, J BIOGEOGR, V27, P87 TAYLOR AR, 1969, INT90 USDA FOR SERV ZACKRISSON O, 1977, OIKOS, V29, P22 0921-2973 Landsc. Ecol.ISI:000240500100009Univ Wyoming, Dept Geog, Dept 3371, Laramie, WY 82071 USA. Beijing Normal Univ, Coll Life Sci, Beijing 150040, Peoples R China. Baker, WL, Univ Wyoming, Dept Geog, Dept 3371, 1000 E Univ Ave, Laramie, WY 82071 USA. bakerwl@uwyo.eduEnglish.<7P8Kozakiewicz, M. Gortat, T. Kozakiewicz, A. Barkowska, M.1999REffects of habitat fragmentation on four rodent species in a Polish farm landscape391-400Landscape Ecology144field-forest mosaic landscape heterogeneity metapopulation small rodents space use patterns AGRICULTURAL LANDSCAPE CLETHRIONOMYS-GLAREOLUS BANK VOLES POPULATION MOVEMENTS APODEMUS MAMMALS MICEArticleAugBank vole, striped field mouse, wood mouse, and yellow-necked mouse populations were studied in a mosaic of field and forest habitats. Live-trapping was carried out in 8 woodlots of different sizes (1.5-9.5 ha), situated 5 to 900 m from each other and surrounded by agricultural fields. Near the study area a dense, several hundred hectare forest complex was situated. It was found that the densities of all the studied species' populations in the woodlots were positively correlated with woodlot quality. For local bank vole populations a positive correlation of density with the surface area and circumference of woodlots, as well as with the area/circumference ratio was found. A negative correlation was found for population density and the distance between a given woodlot and the forest complex. For the yellow-necked mouse a positive correlation occurred between the density of local populations and the distance to the nearest neighboring woodlot. For the striped field mouse a positive correlation was found only between the population density in each woodlot and the distance to the forest complex. The wood mouse was insensitive to the variations in woodlot features present except for woodlot quality, and hence was probably responding in density to some other factors. Four rodent species, coexisting in the field-forest habitat mosaic demonstrated different reactions to its spatial characteristics, which were mainly related to different habitat preferences, spatial behavior, and mobility of individuals of the studied species.://000081305700007 ISI Document Delivery No.: 214AP Times Cited: 6 Cited Reference Count: 34 Cited References: ALIBHAI SK, 1985, S ZOOLOGICAL SOC LON, V55, P277 ANDREN H, 1994, OIKOS, V71, P355 ANGELSTAM P, 1992, ECOLOGICAL PRINCIPLE, P252 BAUCHAU V, 1991, RONGEUR ESPACE, P275 BERGSTEDT B, 1966, OIKOS, V17, P150 ESSEEN PA, 1992, ECOLOGICAL PRINCIPLE, P252 GEUSE P, 1985, ACTA ZOOL FENN, V173, P65 HANSKI I, 1997, METAPOPULATION BIOL, P5 HARRIS LD, 1984, FRAGMENTED FOREST IS HARRIS LD, 1988, ENVIRON MANAGE, V12, P675 HARRISON S, 1991, METAPOPULATION DYNAM, P73 KOZAKIEWICZ M, 1985, ACTA THERIOL, V30, P193 KOZAKIEWICZ M, 1993, ACTA THERIOL, V38, P1 KOZAKIEWICZ M, 1993, LANDSCAPE ECOL, V8, P19 KOZAKIEWICZ M, 1994, POLISH ECOLOGICAL ST, V20, P209 KOZAKIEWICZ M, 1995, LANDSCAPE APPROACHES, P78 LEVINS R, 1970, SOME MATH QUESTIONS, V2, P75 LIRO A, 1987, OECOLOGIA, V74, P438 MEFFE GK, 1994, PRINCIPLES CONSERVAT MERRIAM G, 1990, CHANGING LANDSCAPES, P121 MONTGOMERY WI, 1985, S ZOOL SOC LOND, V55, P89 NEWSON R, 1963, ECOLOGY, V44, P110 PULLIAM HR, 1988, AM NAT, V132, P652 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SMITH AT, 1997, METAPOPULATION BIOL, P407 SZACKI J, 1991, LANDSCAPE ECOL, V5, P219 SZACKI J, 1999, LANDSCAPE ECOL, V14, P369 VANAPELDOORN RC, 1992, OIKOS, V65, P265 VANDORP D, 1987, LANDSCAPE ECOLOGY, V1, P59 VERBOOM B, 1990, LANDSCAPE ECOL, V4, P171 VERBOOM J, 1991, OIKOS, V61, P149 VERBOOM J, 1993, IALE STUDIES LANDSCA, V1, P172 VIITALA J, 1985, ANN ZOOL FENN, V22, P359 ZHANG Z, 1991, ACTA THERIOL, V36, P239 0921-2973 Landsc. Ecol.ISI:000081305700007Univ Warsaw, Dept Ecol, PL-00927 Warsaw, Poland. Kozakiewicz, M, Univ Warsaw, Dept Ecol, Ul Krakowskie Przedmiescie 26-28, PL-00927 Warsaw, Poland.English<77Kozakiewicz, M. Kozakiewicz, A. Lukowski, A. Gortat, T.1993OUse of space by bank voles (Clethrionomys glareolus) in a Polish farm landscape19-24Landscape Ecology81CSMALL MAMMALS; MOVEMENT; MOSAIC FARMLAND; METAPOPULATION; MIGRATIONArticleMarMovements of bank voles (Clethrionomys glareolus) were studied in a farmland mosaic in poland. Distances crossed by animals in short-time periods are significantly longer in heterogenous than in homogenous habitats. In long-time and large-spatial scales, a significant portion of the animals in a population travel among habitat elements of the mosaic, reducing the degree of isolation of patch populations and decreasing the probability of local extinction.://A1993KW95800002 IISI Document Delivery No.: KW958 Times Cited: 13 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1993KW95800002hKOZAKIEWICZ, M, WARSAW UNIV,INST ZOOL,DEPT ECOL,UL KRAKOWSKIE PRZEDMIESCIE 26-28,PL-00927 WARSAW,POLAND.English|7 7Kozakiewicz, M. Kozakiewicz, A. Lukowski, A. Gortat, T.1993OUse of Space by Bank Voles (Clethrionomys-Glareolus) in a Polish Farm Landscape19-24Landscape Ecology81?small mammals movement mosaic farmland metapopulation migrationMarMovements of bank voles (Clethrionomys glareolus) were studied in a farmland mosaic in poland. Distances crossed by animals in short-time periods are significantly longer in heterogenous than in homogenous habitats. In long-time and large-spatial scales, a significant portion of the animals in a population travel among habitat elements of the mosaic, reducing the degree of isolation of patch populations and decreasing the probability of local extinction.://A1993KW95800002-Kw958 Times Cited:17 Cited References Count:0 0921-2973ISI:A1993KW95800002fKozakiewicz, M Warsaw Univ,Inst Zool,Dept Ecol,Ul Krakowskie Przedmiescie 26-28,Pl-00927 Warsaw,PolandEnglish|?> IKramer-Schadt, Stephanie Kaiser, Tobias S. Frank, Karin Wiegand, Thorsten2011oAnalyzing the effect of stepping stones on target patch colonisation in structured landscapes for Eurasian lynx501-513Landscape Ecology264AprQWith habitat loss and fragmentation having become two of the major threats to the viability of species, the question of how to manage landscapes for species conservation has attracted much attention. In this context, the planning of stepping stones has been proposed to increase connectivity in fragmented landscapes. We present a simulation study with a neutral landscape approach to assess the effects of stepping stones on colonization success. To that end, we used a spatially explicit, calibrated population model of the European lynx (Lynx lynx) coupled with structured landscapes, in which we could control the landscape parameters of dispersal habitat coverage and contagion, as well as the number and size of stepping stones available for breeding. In general, we found that colonization success increased with increasing habitat coverage but decreased with increasing habitat contagion, while the introduction of stepping stones had significant effects in critical situations. Especially at low to medium dispersal habitat coverage and high disperser mortality, stepping stones had a positive effect on colonization success when they were large enough to produce new dispersers, but negative effects when they were small and located in a way that dispersers would be distracted from more suitable breeding habitat patches. The latter clearly constituted a shading effect and argues for a thorough consideration of the trade-offs related to stepping stone size and location when implementing stepping stones as a conservation measure, especially when the number of individuals of conservation concern is low.!://WOS:000288807300005Times Cited: 0 0921-2973WOS:00028880730000510.1007/s10980-011-9576-4<7Kratochwil, A. Schwabe, A.1994Coincidences between different landscape ecological zones and growth forms of cembran pine (Pinus-cembra l) in sub-alpine habitats of the central Alps175-190Landscape Ecology93pCEMBRAN PINE; NUTCRACKER; MULTIPLE TRUNK TREES; INTRASPECIFIC COEXISTENCE; AREA OF GLACIER RECESSION; TIMBERLINEArticleSep6The 'forgotten' depots of the European Nutcracker (Nucifraga c. caryocatactes) often 'lead' to the development of tufts of Pinus cembra. In many cases the other individuals of such tufts are not suppressed by the fittest one, rather there is an intraspecific coexistence up to the senescent stage of the trees. There are fusions of separate trunks, and so frequently the individual history of older trees can only be reconstructed by studying sutures, crown structures or trunk cross sections. Different types of trunk fusions are worked out. By means of transect counting the occurrence of these 'multiple trunk trees' is documented quantitatively in different landscape ecological zones of the Engadin region (the Grisons, Switzerland). The data base is 3024 counted microsites of Pinus cembra individuals arising from seeds, including 5272 living individuals. These 'multiple trunk trees' significantly play an important role in the landscape ecological zones of recent glacier recession and at the alpine timberline. Their growth forms have a higher biomechanical stability.://A1994PL16600002 HISI Document Delivery No.: PL166 Times Cited: 0 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1994PL16600002lKRATOCHWIL, A, UNIV OSNABRUCK,FACHBEREICH BIOL CHEM,FACHGEBIET OKOL,BARBARASTR 11,D-49069 OSNABRUCK,GERMANY.English? )Krause, Bernie Gage, Stuart Joo, Wooyeong2011mMeasuring and interpreting the temporal variability in the soundscape at four places in Sequoia National Park 1247-1256Landscape Ecology269Springer NetherlandsEarth and Environmental ScienceQThe soundscape was recorded in four selected places in Sequoia National Park CA, to quantify and assess the diurnal and seasonal character of the park’s soundscape. The recording sites were selected to represent a combination of elevation and vegetation diversity. Hour-long sound recordings were made by four individuals at each place during fall, spring, summer and winter at dawn, midday, dusk, and midnight with identical recording instrumentation. The recordings of the soundscape were made in an old growth forest (Crescent Meadow), in a foothill oak savanna (Sycamore Spring), in an upland savanna chaparral (Shepherd Saddle) and in a foothill riparian location adjacent to the Kiawah River (Buckeye Flat). Sound recordings were analyzed using a normalized Power Spectral Density (PSD) algorithm and partitioned into 1 kHz intervals based on 12 subsamples from each of the 64 h-long sound recordings. Biological signals (biophony) were based on the highest PSD value within the range of 2–8 kHz. A multilevel analysis (MLA) was used to examine temporal patterns of biophony at four locations in Sequoia National Park. Unsupervised Landsat Thematic Mapper Satellite Imagery identified 25 vegetation regimes in Sequoia National Park. Satellite signatures of the habitat where recordings were made were extracted from the imagery to scale to the region.+http://dx.doi.org/10.1007/s10980-011-9639-6 0921-297310.1007/s10980-011-9639-6~?g%Ktitorov, P. Bairlein, F. Dubinin, M.2008jThe importance of landscape context for songbirds on migration: body mass gain is related to habitat cover169-179Landscape Ecology23Landscape context influences many aspects of songbird ecology during the breeding season. The importance of landscape context at stopover sites for migrating songbirds, however, has received less attention. In particular, landscape context may affect the availability and quality of food for refueling during stopovers, which is critical for successful migration. We evaluated the influence of woody habitat cover in the surroundings of stopover sites at several spatial extents on the hourly changes of body mass in two species of European-African forest-dwelling songbird migrants (Willow Warbler, Phylloscopus trochilus, and the Eurasian Redstart, Phoenicurus phoenicurus). Data were sampled by standardized methods from a network of ringing stations throughout Europe during the falls of 1994-1996. In both species, hourly body mass gain calculated for first captures increased with woody habitat cover. We found a similar logarithmic relationship for both species, although for Willow Warblers mass gain was more strongly related to the habitat cover within 5 km, in contrast to 3 km for Redstarts. For Willow Warblers, where sufficient data are available for each year, the relationship is consistent over the years. The shape of the relationship suggests existence of a threshold of landscape suitability for refueling at stopover sites: in sites with less than 10% of woody habitat cover, birds tend to lose body mass or to gain mass at a lower rate."://WOS:000252636100006 Times Cited: 0WOS:000252636100006(10.1007/s10980-007-9177-4|ISSN 0921-2973p|? 6Kuhman, Timothy R. Pearson, Scott M. Turner, Monica G.2010Effects of land-use history and the contemporary landscape on non-native plant invasion at local and regional scales in the forest-dominated southern Appalachians 1433-1445Landscape Ecology259NovDetermining what factors explain the distribution of non-native invasive plants that can spread in forest-dominated landscapes could advance understanding of the invasion process and identify forest areas most susceptible to invasion. We conducted roadside surveys to determine the presence and abundance of 15 non-native plant species known to invade forests in western North Carolina, USA. Generalized linear models were used to examine how contemporary and historic land use, landscape context, and topography influenced presence and abundance of the species at local and regional scales. The most commonly encountered species were Microstegium vimineum, Rosa multiflora, Lonicera japonica, Celastrus orbiculatus, Ligustrum sinense, and Dioscorea oppositifolia. At the regional scale, distance to city center was the most important explanatory variable, with species more likely present and more abundant in watersheds closer to Asheville, NC. Many focal species were also more common in watersheds at lower elevation and with less forest cover. At the local scale, elevation was important for explaining the species' presence, but forest cover and land-use history were more important for explaining their abundance. In general, species were more common in plots with less forest cover and more area reforested since the 1940s. Our results underscore the importance of considering both the contemporary landscape and historic land use to understand plant invasion in forest-dominated landscapes.!://WOS:000281981000010Times Cited: 1 0921-2973WOS:00028198100001010.1007/s10980-010-9500-3|? &Kun, Adam Oborny, Beata Dieckmann, Ulf2009CIntermediate landscape disturbance maximizes metapopulation density 1341-1350Landscape Ecology2410The viability of metapopulations in fragmented landscapes has become a central theme in conservation biology. Landscape fragmentation is increasingly recognized as a dynamical process: in many situations, the quality of local habitats must be expected to undergo continual changes. Here we assess the implications of such recurrent local disturbances for the equilibrium density of metapopulations. Using a spatially explicit lattice model in which the considered metapopulation as well as the underlying landscape pattern change dynamically, we show that equilibrium metapopulation density is maximized at intermediate frequencies of local landscape disturbance. On both sides around this maximum, the metapopulation may go extinct. We show how the position and shape of the intermediate viability maximum is responding to changes in the landscape's overall habitat quality and the population's propensity for local extinction. We interpret our findings in terms of a dual effect of intensified landscape disturbances, which on the one hand exterminate local populations and on the other hand enhance a metapopulation's capacity for spreading between habitat clusters.%://BIOSIS:PREV201000014109Times Cited: 0 0921-2973BIOSIS:PREV201000014109:10.1007/s10980-009-9386-0}?!Kupfer, John A. Farris, Calvin A.2007cIncorporating spatial non-stationarity of regression coefficients into predictive vegetation models837-852Landscape Ecology226Jul&://BIOSIS:PREV200700463286 0921-2973BIOSIS:PREV200700463286 <7Kupfer, J. A. Malanson, G. P.1993XObserved and modeled directional change in riparian forest composition at a cutbank edge185-199Landscape Ecology83IEDGE EFFECT; FLOODPLAIN; IOWA; RETROGRESSION; RIPARIAN FOREST; SUCCESSIONArticleSepLateral migrations of river meanders create transient, spatially transgressive edges where the advancing cutbank edge encroaches upon interior floodplain forest communities. This spatial movement of edge toward the forest interior should initiate directional changes in species composition within a forest plot as it is affected by a changing microclimate and hydrological regime. We found that cutbank edge and forest interior sites in an Iowa floodplain contained markedly different plant assemblages. Species commonly associated with later stages of succession dominated interior sites while cutbank edge sites favored secondary, successional species. Assuming that the cutbank edge sites once contained vegetation similar to that surveyed in the floodplain interior, the observed changes in community structure accompanying channel migration are suggestive of retrograde succession, or retrogression. To link cutbank erosional processes with retrogressional processes, we modified a computer simulation model already in use for floodplain environments. We incorporated the changing edge effects and compared model projections with the data collected from the field sites using detrended correspondence analysis. Without changes, the simulation projected a site compositionally similar to the sampled interior forest. When the changes were initiated, the simulated site progressively took on compositional characteristics similar to the riparian edge sites. Because we included only those forcing functions that would be initiated by cutbank erosion, the model supports the hypothesis that the spatially progressive edge effect results in a directional change in forest community composition analogous to retrogression. Our results demonstrate an interesting linkage between successional and fluvial-geomorphic processes and indicate that site dynamics may be controlled differently in landscapes where sites are progressively created and destroyed than where recurrent disturbances affect the same site.://A1993MB34000005 IISI Document Delivery No.: MB340 Times Cited: 11 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1993MB340000053KUPFER, JA, UNIV IOWA,DEPT GEOG,IOWA CITY,IA 52242.EnglishI<7nKurttila, M. Pukkala, T.2003xCombining holding-level economic goals with spatial landscape-level goals in the planning of multiple ownership forestry529-541Landscape Ecology185flying squirrel hierarchical forest planning multi-objective forest planning private forest holdings spatial objectives utility function Finland FLYING SQUIRREL PTEROMYS-VOLANS FRAGMENTATION FINLAND AREAS PLANSArticleCIn Finland, management of biological diversity at the landscape level is complicated by the relatively small size of the holdings. To alleviate this problem, this study presents a hierarchical planning model that aims at combining spatial landscape-level ecological goals with holding-level owner-specific goals. The influence of ecological objectives extends across holding borders, but their impact is greatest in areas where they are least in conflict with the owners' goals. This feature, which results in minimum losses to individual landowners, can be called ecological efficiency. In the case study, the ecological objective was to cluster the breeding and foraging areas of flying squirrel (Pteromys volans). Other sets of objectives were related to individual holdings according to the various preferences of the forest owners. The forest plan produced by the presented planning model was compared with two other forest plans: 1) a combination of independent forest holding level plans, which were assumed to represent the outcome of the current planning tradition, and 2) an area-level plan, where the holding borders and holding-specific objectives were not taken into account. The same objective variables and objective weights were used in all plans. All the plans were produced for six planning areas (ranging from 404.6 to 984.9 ha) and 110 forest holdings (ranging from 0.6 to 449.8 ha) within these areas. The case-study results were promising: with the model presented here, the spatial structure of flying squirrel breeding and foraging areas could be improved with only minor losses in holding-level objectives. The spatial structure of the landscape after the 60-year planning period was very close to the area-level plan. This outcome was made possible by synchronizing the treatment proposals across forest-holding borders. The outcome of the model seems promising also from the practical standpoint: because the variation in the objectives of forest owners is efficiently taken into account in optimization, only rarely do the solutions suggest that the holding-level targets be compromised.://000185827200006 ISI Document Delivery No.: 730JG Times Cited: 8 Cited Reference Count: 41 Cited References: *FINN ENV, 2000, 437 FINN ENV *LAK OY ED AB, 1997, METS PER *LUONN METS, 1994, METSAKESKUS TAPION J, V6 ANDREN H, 1994, OIKOS, V71, P355 BOSTON K, 1999, FOREST SCI, V45, P292 CONNELLY B, 1996, P WORKSH HIER APPR F, P1 DAVIS LS, 1991, FOREST SCI, V37, P200 DAVIS RG, 1993, CAN J FOREST RES, V23, P1078 DOWSLAND KA, 1993, MODERN HEURISTIC TEC, P20 ESSEEN PA, 1992, ECOLOGICAL PRINCIPLE, P252 FRIES C, 1998, SCAND J FOREST RES, V13, P370 HANSKI IK, 1998, WILDLIFE BIOL, V4, P33 HANSKI IK, 2000, J MAMMAL, V81, P798 HARRISON S, 1995, IALE STUDIES LANDSCA, V2, P293 HOF JG, 1987, NATUR RESOUR MODEL, V1, P245 HUHTA E, 1999, AUK, V116, P528 IHALAINEN R, 1992, FINNISH FOREST RES I, V405, P41 JOKIMAKI J, 2000, FINNISH FORREST RES, V779, P7 KANGAS J, 1992, PUBLICATIONS SCI, V24 KARPPINEN H, 1998, J FOREST EC, V4, P147 KARPPINEN H, 1998, SILVA FENNICA, V32, P43 KURTTILA M, 2001, BOREAL ENVIRON RES, V6, P285 KURTTILA M, 2001, FOREST ECOL MANAG, V142, P127 KURTTILA M, 2002, FOREST ECOL MANAG, V166, P245 KURTTILA M, 2002, FOREST ECOL MANAG, V166, P69 MCGARIGAL K, 1995, FRAGSTATS SPATIAL PA, P351 MONKKONEN L, 1997, ECOGRAPHY, V20, P634 NAVON D, 1986, TIMS STUDIES MANAGEM, V21, P353 OHMAN K, 2000, CAN J FOREST RES, V30, P1817 OKSANENPELTOLA L, 1995, TYOTEHOSEURAN METSAT, V546 PUKKALA T, 1988, SCANDINAVIAN J FORES, V5, P263 PUKKALA T, 1993, SCAND J FOR RES, V8, P560 PUKKALA T, 1995, LANDSCAPE URBAN PLAN, V32, P185 PUKKALA T, 1997, SILVA FENNICA, V31, P417 PUKKALA T, 2001, UNPUB MONSU METSASUU PUKKALA T, 2003, IN PRESS FOREST POLI PYKALAINEN J, 2001, FOREST POLICY ECON, V2, P293 REUNANEN P, 2000, CONSERV BIOL, V14, P218 REUNANEN P, 2002, ECOL APPL, V12, P1188 VANLANGEVELDE F, 2000, LANDSCAPE ECOL, V15, P243 WEINTRAUB A, 1991, FOREST SCI, V37, P439 0921-2973 Landsc. Ecol.ISI:000185827200006Finnish Forest Res Inst, Joensuu Res Ctr, FIN-80101 Joensuu, Finland. Univ Joensuu, Fac Forestry, FIN-80101 Joensuu, Finland. Kurttila, M, Finnish Forest Res Inst, Joensuu Res Ctr, POB 68, FIN-80101 Joensuu, Finland. mikko.kurttila@metla.fiEnglish T<7Kuusemets, V. Mander, U.20012Nutrient flows and management of a small watershed59-68Landscape Ecology17 supplement 1buffer zones constructed wetlands nitrogen and phosphorus runoff watershed management LAND-USE CHANGE PHOSPHORUS STRATEGIES CATCHMENTS RESERVOIRS POLLUTION WETLANDS DYNAMICS ESTONIA LOSSESArticleNutrient leaching from agricultural areas is one of the main concerns of watershed management. The paper examines nitrogen and phosphorus leaching from different parts of small agricultural watershed (378 ha) that was divided into 6 subcatchments. The calculations of nutrient outflow are based on the detailed measurement at the time of intensive agricultural activities during 5 years (1987-1991). The results show that nutrient leaching can vary very much even in such a small catchment area. The retention of nitrogen and phosphorus took place in the storage lake: 3,900 and 2.2 kc, ha(-1) year(-1), respectively. At the same time, in the small subcatchment with high shallow groundwater outflow value, the nitrogen and phosphorus outflow was 233 and 0.90 kg ha(-1) year(-1), respectively. The most effective mitigation method is establishing buffer zones on the banks of the stream. A buffer zone of 460 m length would remove 2,200 to 2,640 kg N and 12 to 15 kg P a year, a constructed wetland on the stream would remove 1,660 to 2,760 kc, N and 3 to 4.5 kg P a year. The detailed study gives good opportunity to estimate most critical areas where application of mitigation methods is most needed and ecologically and economically effective.://000176041000006 +ISI Document Delivery No.: 559TG Times Cited: 5 Cited Reference Count: 25 Cited References: *APHA, 1981, STAND METH EX WAT WA ARHEIMER B, 1994, AMBIO, V23, P378 BASTIAN O, 1999, ANAL OKOLOGISCHE BEW, V2 BEHRENDT H, 1996, WATER SCI TECHNOL, V33, P175 BLACKWELL MSA, 1999, WATER SCI TECHNOL, V39, P157 COLLINGE SK, 1996, LANDSCAPE URBAN PLAN, V36, P59 FLEISCHER S, 1991, VERH INT VEREIN LIMN, V24, P1753 FORMAN RTT, 1986, LANDSCAPE ECOLOGY HAYCOCK NE, 1995, LANDSCAPE URBAN PLAN, V31, P313 JENSEN JJ, 1998, ENVIRON POLLUT S1, V102, P741 KUUSEMETS V, 1999, WATER SCI TECHNOL, V40, P195 LOWRANCE R, 1984, BIOSCIENCE, V34, P374 MANDER U, 1994, FUNCTIONAL APPRAISAL, P77 MANDER U, 1995, LANDSCAPE URBAN PLAN, V31, P333 MANDER U, 1997, ECOLOGICAL ENG WASTE, P263 MANDER U, 1997, WATER SCI TECHNOL, V35, P323 MANDER U, 1998, INT REV HYDROBIOL, V83, P639 MANDER U, 1998, LANDSCAPE URBAN PLAN, V41, P229 MANDER U, 2000, LANDSCAPE ECOL, V15, P187 PETERJOHN WT, 1984, ECOLOGY, V65, P1466 PETERSEN RC, 1992, RIVER CONSERVATION M, P293 PINAY G, 1988, REGUL RIVER, V2, P507 PIONKE HB, 2000, ECOL ENG, V14, P325 SHARPLEY AN, 1994, J ENVIRON QUAL, V23, P437 STRASKRABA M, 1996, WATER SCI TECHNOL, V33, P73 Suppl. 1 0921-2973 Landsc. Ecol.ISI:000176041000006Univ Tartu, Inst Geog, EE-51014 Tartu, Estonia. Kuusemets, V, Univ Tartu, Inst Geog, 46 Vanemuise St, EE-51014 Tartu, Estonia. valdo@ut.eeEnglishH۽7:$Kyba, ChristopherC M. Hölker, Franz2013NDo artificially illuminated skies affect biodiversity in nocturnal landscapes? 1637-1640Landscape Ecology289Springer Netherlands 2013/11/01+http://dx.doi.org/10.1007/s10980-013-9936-3 0921-2973Landscape Ecol10.1007/s10980-013-9936-3English|?# <La Morgia, V. Malenotti, Elisa Badino, Guido Bona, Francesca2011Where do we go from here? Dispersal simulations shed light on the role of landscape structure in determining animal redistribution after reintroduction969-981Landscape Ecology267Aug.Reintroduction projects represent viable options for animal conservation. They allow the establishment of new local populations and may contribute to recreating functional networks within a metapopulation. In the latter case, landscape connectivity may be a major determinant of the phase of spread of the reintroduced populations. Here, we deal with an example of a red deer (Cervus elaphus) translocation planned to enable the connection among existing isolated populations of the species in the Italian Alps. Our aim was to assess whether the analysis of landscape suitability and the simulation of dispersal of released individuals could shed light on the actual process of population spread. For these purposes, we adopted a modelling approach using radiotracking data to develop a habitat suitability map. On the basis of this map, we simulated the dispersal of the animals after release and we then compared the simulation results with the outcome of null models and with the observed population redistribution. The results suggest that the spread of the subpopulation was easier north-westward than southward. Taking into account landscape suitability, our simulations produced a reliable estimate of the ease of colonization of the valleys neighbouring the release-site and they allowed the identification and validation of a potential pathway for animal dispersal. The suitability model based on the monitoring of individuals in the earliest phase of establishment shed light on the spread of the population and on its potential connections with other deer subpopulations.!://WOS:000292705900006Times Cited: 0 0921-2973WOS:00029270590000610.1007/s10980-011-9621-3|?;LaCroix, J. J. Li, Q. L. Chen, J. Q. Henderson, R. John, R.2008GEdge effects on fire spread in a disturbed Northern Wisconsin landscape 1081-1092Landscape Ecology239The effect of area-of-edge influence (AEI) on fire size and movement was simulated by considering the distribution of single and multiple edges in the Chequamegon-Nicolet National Forest in Northern Wisconsin, USA. Six hypothetical landscapes with different delineations of AEIs were created for simulating fire spread using FARSITE to evaluate the influence of edges on the rate and direction of fire spread. The burned area differed significantly among the six landscapes. In the three scenarios with buffered edges, the burned area increased by 35% with high loading fuel in AEIs, while it decreased by 21 and 46% with medium and low fuel loading in the AEIs, respectively, as compared to the no edge scenario. In two scenarios we delineated the area-of-multiple-edge influence (AMEI) and placed more than one high loading fuel within it. This increased the burned area by 5% from the high buffered edge scenario and by 40% from the control. When the depth-of-edge influence (DEI) was doubled to 60 m using AMEI with high fuels, the burned area increased by 20% from the high buffered edge scenario and by 60% from the control. We found that low and medium fuel loading slowed the fire spread and over time, caused the fire front to change direction. In high fuel loading scenarios, AEIs acted as corridors facilitating the fire spread by providing a contiguous patch of fuel which allowed fires to increase in size and pulled the fire front in the same direction.!://WOS:000260283100007Times Cited: 0 0921-2973WOS:00026028310000710.1007/s10980-008-9265-0? James LaGro 2007\Rutherford H. Platt, 2004. Land use and society: geography, law, and public policy, 2nd ed. 633-634Landscape Ecology224 Book ReviewZ<7y LaGro, J. A.1998RLandscape context of rural residential development in southeastern Wisconsin (USA)65-77Landscape Ecology132urbanization rural land use housing landscape change private sewage systems public policy URBANIZING AREA POPULATION ECOLOGY RESOURCESArticleAprPrivate on-site sewage systems serve residential development in rural landscapes throughout the United States. In the State of Wisconsin, three major types of private sewage systems facilitate residential development on sites that span gradients in slope, soil permeability, depth to bedrock, and depth to water-table. Conventional soil-absorption sewage treatment systems are constructed on sites with minimal physiographic constraints; more highly engineered alternative sewage treatment systems are installed on sites with moderate to severe constraints; holding tanks provide no on-site sewage treatment and are employed on sites with the most severe physiographic limitations. An environmental impact statement (EIS), prepared in 1979 on the proposed widespread use of alternative private sewage systems, suggested that alternative systems might facilitate in-fill development on poor sites near existing cities and lead to compact, higher density development patterns. The research reported in this paper tested the validity of this EIS scenario by comparing development patterns associated with a sample of conventional systems, alternative systems, and holding tanks installed during the 1980s in Ozaukee County, Wisconsin. Land use data, soils data, and other site attribute data were assembled and analyzed in a vector geographic information system (GIS). Because each type of private sewage system has a unique set of siting criteria, the three sets of sampled systems are located in significantly different physiographic regions within the County. Collectively, installations of all three systems facilitated scattered residential development throughout the rural landscape. This development consists of relatively small residential patches dispersed within an agricultural matrix. Wastewater management technology, if not constrained by public policies or other socioeconomic factors, can be an important anthropogenic factor influencing both the process and pattern of landscape change.://000077256800001 ISI Document Delivery No.: 143LH Times Cited: 6 Cited Reference Count: 37 Cited References: *SE WISC REG PLANN, 1966, 8 SE WISC REG PLANN *US BUR CENS, 1993, 1990 CENS POP, V1 *US CUR CENS, 1983, 1980 CENS POP, V1 *USDA, 1970, SOIL SURV OZ COUNT W *WISC DEP HLTH SOC, 1979, FIN ENV IMP STAT 3 A *WISD DEP IND LAB, 1990, ONS SEW SYST PLAN SU CHRISTALLER W, 1966, CENTRAL PLACES SO GE COCHRANE WW, 1979, DEV AM AGR HIST ANAL COMELEO RL, 1996, LANDSCAPE ECOL, V11, P307 CONVERSE JC, 1987, T AM SOC ASGR ENG, V30, P362 DANDEKAR HC, 1994, ORDERING SPACE TYPES, P97 ENGELS TM, 1994, CONSERV BIOL, V8, P286 FORMAN RTT, 1995, LANDSCAPE ECOL, V10, P133 FUGUITT GV, 1989, RURAL SMALL TOWN AM FUGUITT GV, 1990, DEMOGRAPHY, V27, P589 GARSON GD, 1992, SAGE U PAPER SERIES GLANTZ SA, 1992, PRIMER BIOSTATISTICS GOUDIE A, 1994, HUMAN IMPACT NATURAL HANSON ME, 1989, J AM PLANNING AS SPR, P169 HOLLAND CC, 1995, WETLANDS, V15, P336 JOHNSON EAJ, 1970, ORG SPACE DEV COUNTR KAMADA M, 1996, LANDSCAPE ECOL, V11, P15 KELLOGG RL, 1994, J SOIL WATER CONSERV, V49, P521 LAGRO JA, 1994, LANDSCAPE URBAN PLAN, V28, P143 LAGRO JA, 1996, LANDSCAPE URBAN PLAN, V35, P1 LEVY PS, 1991, SAMPLING POPULATIONS LOESCH A, 1954, EC LOCATION MCDONNELL MJ, 1993, HUMANS COMPONENTS EC MEDLEY KE, 1995, PROF GEOGR, V47, P159 NAIMAN RJ, 1996, LANDSCAPE ECOL, V11, P193 NASSAUER JI, 1995, LANDSCAPE ECOL, V10, P229 PIMENTEL D, 1994, POPUL ENVIRON, V15, P347 POPPER FJ, 1981, AM LAND FORUM, V2, P8 TURNER MG, 1991, QUANTITATIVE METHODS, P232 VITOUSEK PM, 1994, ECOLOGY, V75, P1861 WARDWELL JM, 1980, NEW DIRECTIONS URBAN, P71 ZONNEVELD IS, 1990, CHANGING LANDSCAPES 0921-2973 Landsc. Ecol.ISI:000077256800001Univ Wisconsin, Dept Landscape Architecture, Madison, WI 53706 USA. Univ Wisconsin, Inst Environm Studies, Madison, WI 53706 USA. LaGro, JA, Univ Wisconsin, Dept Landscape Architecture, 1450 Linden Dr, Madison, WI 53706 USA.Englishh|7 Lagro, J. A. Degloria, S. D.1992ULand-Use Dynamics within an Urbanizing Nonmetropolitan County in New-York-State (USA)275-289Landscape Ecology74DecLand use/land cover data for fifteen minor civil divisions (MCDs) in Ulster County, New York (USA) were interpreted from 1968 and 1985 aerial photographs. These data were combined with ancillary physiographic and demographic data as raster layers within a computerized geographic information system (GIS). Class to class changes in land use/land cover were quantified for a study area approximately 30 kilometers by 50 kilometers. The relationships between the land use/land cover variables and the ancillary variables were modeled in a series of weighted least squares regressions employing data spatially aggregated by general soil map unit (N = 44). Between 1968 and 1985, nearly one-third of the study area changed to another land use/land cover class. Land in the urban class increased from 6.7% to 17.8% of the study area, while the forest class declined from 65.0% to 55.2%, and the agriculture class declined from 12.7% to 8.9%. Gains and losses in the remaining five major (Level 1) land use/land cover classes were relatively small. Land use changes primarily involved the conversion of land from the forest, agriculture, and vacant classes to the urban class, and from the agriculture class to the forest and vacant classes. Variables accounting for the variance in the land use/land cover class proportions of the soil units were population density, highway proximity, distance to urban centers, mean elevation, mean slope gradient, and soil suitability for farming and for urban development.://A1992KD83100004-Kd831 Times Cited:27 Cited References Count:0 0921-2973ISI:A1992KD83100004QLagro, Ja Univ Wisconsin,Dept Landscape Architecture,25 Agr Hall,Madison,Wi 53706English?hLaGro, J.A. Jr. DeGloria, S.D.1992VLand use dynamics within an urbanizing non-metropolitan county in New York state (USA)275-289Landscape Ecology74Land use/land cover data for fifteen minor civil divisions (MCDs) in Ulster County, New York (USA) were interpreted from 1968 and 1985 aerial photographs. These data were combined with ancillary physiographic and demographic data raster layers within a computerized geographic information system(GIS). Class to class changes in land use/land cover were quantified for a study area approximately 30 kilometers by 50 kilometers. The relationships between the land use/land cover variables and the ancillary variables were modeled in a series of weighted least squares regressions employing data spatially aggregated by general soil map unit(N=44). Between 1968 and 1985, nearly one-third of the study area changed to another land use/land cover class. Land in the urban class increased from 6.7% to 17.8% of the study area, while the forest class declined from 65.0% to 55.2%, and the agriculture class declined from 12.7% to 8.9%. Gains and losses in the remaining five major(Level I) land use/land cover classes were relatively small. Land use changes primarily involved the conversion of land from the forest, agriculture, and vacant classes to the urban class, and from the agriculture class to the forest and vacant classes. Variables accounting for the variance in the land use/land cover class proportions of the soil units were population density, highway proximity, distance to urban centers, mean elevation, mean slope gradient, and soil suitability for farming and for urban development.|?" &Laita, A. Kotiaho, J. S. Monkkonen, M.2011OGraph-theoretic connectivity measures: what do they tell us about connectivity?951-967Landscape Ecology267AugGraph-theoretic connectivity analyses have received much attention in connectivity evaluation during the last few years. Here, we explore the underlying conceptual differences of various graph-theoretic connectivity measures. Based on connectivity analyses from three reserve networks in forested landscapes in Central Finland, we illustrate how these conceptual differences cause inconsistent connectivity evaluations at both the landscape and patch level. Our results also illustrate how the characteristics of the networks (patch density) may affect the performance of the different measures. Many of the connectivity measures react to changes in habitat connectivity in an ecologically undesirable manner. Patch prioritisations based on a node removal analysis were sensitive to the connectivity measure they were based on. The patch prioritisations derived from different measures showed a disparity in terms of how much weight they put on patch size versus patch location and how they value patch location. Although graphs operate at the interface of structure and function, there is still much to do for incorporating the inferred ecological process into graph structures and analyses. If graph analyses are going to be used for real-world management and conservation purposes, a more thorough understanding of the caveats and justifications of the graph-theoretic connectivity measures will be needed.!://WOS:000292705900005Times Cited: 0 0921-2973WOS:00029270590000510.1007/s10980-011-9620-4|? Lakes, T. Muller, D. Kruger, C.2009hCropland change in southern Romania: a comparison of logistic regressions and artificial neural networks 1195-1206Landscape Ecology249Changes in cropland have been the dominating land use changes in Central and Eastern Europe, with cropland abandonment frequently exceeding cropland expansion. However, surprisingly little is known about the rates, spatial patterns, and determinants of cropland change in Eastern Europe. We study cropland changes between 1995 and 2005 in Arges, County in Southern Romania with two distinct modeling techniques. We apply and compare spatially explicit logistic regressions with artificial neural networks (ANN) using an integrated socioeconomic and environmental dataset. The logistic regressions allow identifying the determinants of cropland changes, but cannot deal with non-linear and complex functional relationships nor with collinearity between variables. ANNs relax some of these rigorous assumptions inherent in conventional statistical modeling, but likewise have drawbacks such as the unknown contribution of the parameters to the outcome of interest. We compare the outcomes of both modeling techniques quantitatively using several goodness-of-fit statistics. The resulting spatial predictions serve to delineate hotspots of change that indicate areas that are under more eminent threat of future abandonment. The two modeling techniques address two controversial issues of concern for land-change scientists: (1) to identify the spatial determinants that conditioned the observed changes and (2) to deal with complex functional relationships between influencing variables and land use processes. The spatially explicit insights into patterns of cropland change and in particular into hotspots of change derived from multiple methods provide useful information for decision-makers.!://WOS:000270739000005Times Cited: 0 0921-2973WOS:00027073900000510.1007/s10980-009-9404-2b|?_NLande, Unni S. Herfindal, Ivar Willebrand, Tomas Moa, Pal F. Storaas, Torstein2014^Landscape characteristics explain large-scale variation in demographic traits in forest grouse127-139Landscape Ecology291JanThe effects of landscape composition on species and populations have become increasingly important due to large and rapid habitat changes worldwide. In particular, concern is raised for several forest-dwelling species such as capercaillie and black grouse, because their habitats are continuously changing and deteriorating from human development. Conservation of these species is linked to sustainable forest management that seeks to benefit multiple species, which demands knowledge about demographic rates in relation to forest composition and structure. We related the spatial variation in adult density and chick production of capercaillie and black grouse to landscape characteristics from 13 areas within the boreal forest of Norway. Linear mixed effects models showed that black grouse and capercaillie had similar associations to landscape characteristics. Adult density of both species was positively related to the proportion of old forest (> 80 years), but only if the area had large proportions of mid to high productive forests. Chick production was negatively related to the proportion of old forest, but positively to habitat diversity and more so for black grouse compared to capercaillie. However, the result for chick production suggest that other forest types also are important, and that forest grouse needs a variety of habitats during their life history stages. Management that seeks to simultaneously conserve populations of black grouse and capercaillie needs to ensure a matrix of various forest types. A special focus must be on the critical life history of local populations to successfully preserve viable populations, for black grouse and capercaillie this implies protection of old and mid to high productive forest while keeping a heterogeneous landscape.!://WOS:000330827600010Times Cited: 1 0921-2973WOS:00033082760001010.1007/s10980-013-9960-3%ڽ7;lLander, TonyaA Klein, EtienneK Stoeckel, Solenn Mariette, Stéphanie Musch, Brigitte Oddou-Muratorio, Sylvie2013yInterpreting realized pollen flow in terms of pollinator travel paths and land-use resistance in heterogeneous landscapes 1769-1783Landscape Ecology289Springer NetherlandsgPrunus avium France Weighted distance Spatially explicit mating model Parentage analysis Microsatellite 2013/11/01+http://dx.doi.org/10.1007/s10980-013-9920-y 0921-2973Landscape Ecol10.1007/s10980-013-9920-yEnglishT|?-Lane-deGraaf, K. E. Fuentes, A. Hollocher, H.2014hLandscape genetics reveal fine-scale boundaries in island populations of Indonesian long-tailed macaques 1505-1519Landscape Ecology299NovHuman activities directly and indirectly influence the gene flow of wildlife populations, significantly affecting their population structure. On Bali, Indonesia, long-tailed macaque (Macaca fascicularis) populations are associated with relatively undisturbed forest remnants, providing resources for macaques through human worship practices. To evaluate the long-term impact of this anthropogenic landscape on gene flow in macaques, we measured the microsatellite heterozygosity and genetic distance of 15 populations across the island. We then used assignment tests to measure more contemporary movement between populations. We found significant population structure across the island and found that despite this significant structuring, contemporary macaque dispersal across the island is relatively high, with a number of first generation migrants detected. Moreover, we identified one population in the core of the island that acts as a magnet for migrants, receiving 50 % of the first generation migrants in this analysis. Finally, we used individual-level Bayesian clustering analysis combined with kriging techniques to measure fine-scale genetic structure and identify significant boundaries relative to the landscape. Significant genetic structure suggests that the existence of forested temple sites and long-term co-existence with humans may have contributed to relative isolation between populations, even though macaques are known for their high dispersal abilities. However, more recent changes in land use practices in Bali, such as reallocation of lands for tourism, are influencing the patterns of dispersal and increasing the movement of individuals between novel sites, shifting the population structure of the macaques and potentially reducing island-wide genetic diversity.!://WOS:000343648700004Times Cited: 0 0921-2973WOS:00034364870000410.1007/s10980-014-0069-0 +<7e ?Lange, R. Diekotter, T. Schiffmann, L. A. Wolters, V. Durka, W.2012Matrix quality and habitat configuration interactively determine functional connectivity in a widespread bush cricket at a small spatial scale381-392Landscape Ecology273%agricultural landscapes dispersal landscape genetics gene flow pholidoptera griseoaptera population genetic structure hierarchical f-statistics pholidoptera-griseoaptera population differentiation genetic differentiation movement patterns genotyping errors fragmentation landscapes forest areaMarUnlike rare or specialised species, widespread abundant species have often been neglected when studying effects of habitat fragmentation. However, recently, it was shown that in the widespread abundant bush cricket Pholidoptera griseoaptera gene flow becomes restricted when the share of suitable habitat dropped below a threshold of 20% at the landscape scale. Here, using the same highly fragmented landscape, we studied the impact of habitat configuration and matrix quality on genetic variation and population differentiation of P. griseoaptera at a small spatial scale. We investigated four clusters of three populations that were either disconnected or connected and had either low quality (arable land) or high quality (grassland) matrix. The number of alleles was significantly lower in disconnected than in connected clusters, irrespective of matrix quality. Genetic differentiation was equally high in the two disconnected clusters and in the connected cluster with low quality matrix (G (ST) a parts per thousand yen 0.030; D a parts per thousand yen 0.082), whereas it was significantly reduced when connected habitats were embedded in a high quality grassland matrix (G (ST) = 0.004; D = 0.011). Analyses of least-cost paths showed that grassy landscape elements in fact represent high quality matrix, but that linear grassy margins are costly for dispersal. The effect of habitat configuration on genetic diversity may be explained by lower effective population sizes in disconnected habitats. The fact that only the connected populations in high quality matrix were not differentiated indicates that landscape management should simultaneously consider habitat configuration and matrix quality to effectively promote small and dispersal-limited species, also at small spatial scales.://000300087500006-889QE Times Cited:0 Cited References Count:66 0921-2973Landscape EcolISI:0003000875000069Lange, R Univ Giessen, IFZ Dept Anim Ecol, Heinrich Buff Ring 26-32, D-35392 Giessen, Germany Univ Giessen, IFZ Dept Anim Ecol, Heinrich Buff Ring 26-32, D-35392 Giessen, Germany Univ Giessen, IFZ Dept Anim Ecol, D-35392 Giessen, Germany UFZ Helmholtz Ctr Environm Res, Dept Community Ecol, D-06120 Halle, GermanyDOI 10.1007/s10980-011-9692-1English<71Langlois, J. P. Fahrig, L. Merriam, G. Artsob, H.2001RLandscape structure influences continental distribution of hantavirus in deer mice255-266Landscape Ecology1635landscape structure landscape composition landscape configuration habitat fragmentation metapopulation epidemiology hantavirus Sin Nombre virus deer mouse scale SMALL MAMMAL COMMUNITY HABITAT FRAGMENTATION PEROMYSCUS-MANICULATUS GENETIC IDENTIFICATION FOREST CONNECTIVITY PATCH MOVEMENTS RESPONSES POPULATIONSArticleAprpWe hypothesized that landscape structure affects movement of individuals through the landscape, which affects the rate and pattern of disease transmission. Based on this hypothesis, we predicted a relationship between landscape structure and disease incidence in spatially structured populations. We tested this prediction for hantavirus incidence in deer mice (Penomysens moniculatus), using a novel index of habitat fragmentation for transect data. A series of four stepwise logistic regression analyses were conducted on serological and ecological data from 2837 mice from 101 sites across Canada. The significant variables, ranked in decreasing order of size of their effect on virus incidence were: human buildings, landscape composition (amount of deer mouse habitat in the 1-km radius landscape surrounding each site), landscape configuration (fragmentation of deer mouse habitat in the 1-km radius landscape surrounding each site), mean annual temperature, and seasonal variation. Our results suggest that epidemiological models should consider not only the demographic structure of the host population, but its spatial structure as well, as inferred from landscape structure. Landscape structure can have a greater effect on the pattern of distribution of a virus in its host population than other ecological variables such as climate and seasonal change. The usefulness of landscape data in epidemiological models depends on the use of the appropriate spatial scale, which can be determined empirically. Epidemiological models with a spatially structured host population can benefit from the explicit consideration of landscape structure.://000168194400005 k ISI Document Delivery No.: 423TT Times Cited: 13 Cited Reference Count: 63 Cited References: *CDC, 1994, ENZ IMM DET IGG ANT *EC WORK GROUP, 1989, EC LAND CLASS SER, V23 *SAS I, 1996, SAS US GUID STAT VER ANDREASSEN HP, 1996, J APPL ECOL, V33, P555 ASHTON WD, 1972, GRIFFINS STAT MONOGR, V32 BAARS MA, 1979, OECOLOGIA, V44, P125 BAKER RH, 1968, SPECIAL PUBLICATION, V2 BARRY RE, 1984, J MAMMAL, V65, P145 BLAIR WF, 1950, EVOLUTION, V4, P253 BOWERS MA, 1996, OECOLOGIA, V105, P107 BOWERS MA, 1999, LANDSCAPE ECOL, V14, P381 BUCKNER CA, 1985, J MAMMAL, V66, P299 CARLETON MD, 1989, ADV STUDY PEROMYSCUS CHARRIER S, 1997, AGR ECOSYST ENVIRON, V61, P133 CHILDS JE, 1994, J INFECT DIS, V169, P1271 CHIZHIKOV VE, 1996, AM SOC VIR 15 ANN M COLLINS RJ, 1997, LANDSCAPE ECOL, V12, P63 DIAZ M, 1999, ACTA OECOL, V20, P39 DIFFENDORFER JE, 1995, ECOLOGY, V76, P827 DOOLEY JL, 1998, ECOLOGY, V79, P969 DUNNING JB, 1992, OIKOS, V65, P169 FAHRIG L, 1994, CONSERV BIOL, V8, P50 FAHRIG L, 1997, J WILDLIFE MANAGE, V61, P603 GODFRYD A, 1986, WILDLIFE 2000 MODELL, P321 GUSTAFSON EJ, 1994, LANDSCAPE URBAN PLAN, V29, P117 HANSSON L, 1991, BIOL J LINN SOC, V42, P89 HENEIN K, 1990, LANDSCAPE ECOL, V4, P157 HOOPER ET, 1968, SPECIAL PUBLICATION, V2 KAUFMAN DW, 1989, ADV STUDY PEROMYSCUS KITRON U, 1998, J MED ENTOMOL, V35, P435 KREMSATER L, 1999, FOREST FRAGMENTATION, P117 LAWTON JH, 1994, LARGE SCALE ECOLOGY, P41 LEDUC JW, 1987, LAB ANIM SCI, V37, P413 LEE HW, 1989, PROG MED VIROL, V36, P62 MANSON RH, 1999, LANDSCAPE ECOL, V14, P355 MATTER SF, 1996, OECOLOGIA, V105, P447 MORRIS DW, 1992, EVOL ECOL, V6, P412 MORZUNOV SP, 1996, AM SOC VIR 15 ANN M NEE S, 1994, NATURE, V367, P123 NICHOL ST, 1993, SCIENCE, V262, P914 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 OSTFELD RS, 1995, ECOL APPL, V5, P353 PARREN SG, 1985, J MAMMAL, V66, P36 PIELOU EC, 1977, MATH ECOLOGY PITHER J, 1998, OIKOS, V83, P166 RIJNSDORP AD, 1980, OECOLOGIA BERLIN, V45, P274 ROSENBERG KV, 1986, WILDLIFE 2000 MODELI, P263 ROWE JE, 1995, VIROLOGY, V213, P122 SEKGOROROANE GB, 1995, CAN J ZOOL, V73, P1432 STAH CD, 1980, J MAMMAL, V61, P141 STICKEL LF, 1968, SPECIAL PUBLICATION, V2 TAYLOR PD, 1993, OIKOS, V68, P571 TAYLOR PD, 1996, LANDSCAPE ECOL, V11, P181 TEFERI T, 1993, CAN FIELD NAT, V107, P109 TERMAN CR, 1968, SPECIAL PUBLICATION, V2 TISCHENDORF L, 2000, LANDSCAPE ECOL, V15, P633 TISCHENDORF L, 2000, OIKOS, V90, P7 WALLIN H, 1988, OECOLOGIA, V77, P39 WECKER SC, 1963, ECOL MONOGR, V33, P307 WOLFF JO, 1982, J MAMMAL, V63, P666 WOLFF JO, 1989, ADV STUDY PEROMYSCUS WOLFF JO, 1997, CONSERV BIOL, V11, P945 YAHNER RH, 1992, AM MIDL NAT, V127, P381 0921-2973 Landsc. Ecol.ISI:000168194400005Carleton Univ, Ottawa Carleton Inst Biol, Landscape Ecol Lab, Ottawa, ON K1S 5B6, Canada. Fahrig, L, Carleton Univ, Ottawa Carleton Inst Biol, Landscape Ecol Lab, 1125 Colonel Dr, Ottawa, ON K1S 5B6, Canada.Englishڽ7':LaPoint, Scott Gallery, Paul Wikelski, Martin Kays, Roland2013?Animal behavior, cost-based corridor models, and real corridors 1615-1630Landscape Ecology288Springer NetherlandsiAnimal movement Carnivore Circuit theory Connectivity Conservation Fisher Least-cost path Martes pennanti 2013/10/01+http://dx.doi.org/10.1007/s10980-013-9910-0 0921-2973Landscape Ecol10.1007/s10980-013-9910-0English<7Lapolla, V. N. Barrett, G. W.1993oEffects of corridor width and presence on the population dynamics of the meadow vole (Microtus pennsylvanicus) 25-37Landscape Ecology81oLANDSCAPE ECOLOGY; CORRIDORS; MEADOW VOLE; MICROTUS-PENNSYLVANICUS DISPERSAL; POPULATION DYNAMICS; CONNECTIVITYArticleMarWe tested the effects of increased landscape corridor width and corridor presence on the population dynamics and home range use of the meadow vole (microtus pennsylvanicus) within a small-scale fragmented landscape. Our objective was to observe how populations behaved in patchy landscapes where the animals home range exceeded or equaled patch size. We used a small-scale replicated experiment consisting of three sets of two patches each, unconnected or interconnected by 1-m or 5-m wide-corridors, established in an old-field community (S.W. Ohio). Control (0-m) treatments supported significantly lower vole densities than either corridor treatment. Females were the dominant resident sex establishing smaller home ranges (< 150m2) than males (> 450m2). Significantly more male voles dispersed between patches with corridors than between patches without corridors. However, no difference was observed regarding the number of male voles dispersing between patches connected by corridors when compared to the number dispersing across treatments. Dispersal between connected patches was restricted to corridors based on tracking tube data. Corridor presence was more important than corridor width regarding the movement of male voles within their home range.://A1993KW95800003 IISI Document Delivery No.: KW958 Times Cited: 63 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1993KW958000032LAPOLLA, VN, MIAMI UNIV,DEPT ZOOL,OXFORD,OH 45056.English|7 Lapolla, V. N. Barrett, G. W.1993nEffects of Corridor Width and Presence on the Population-Dynamics of the Meadow Vole (Microtus-Pennsylvanicus)25-37Landscape Ecology81jlandscape ecology corridors meadow vole microtus-pennsylvanicus dispersal population dynamics connectivityMarWe tested the effects of increased landscape corridor width and corridor presence on the population dynamics and home range use of the meadow vole (microtus pennsylvanicus) within a small-scale fragmented landscape. Our objective was to observe how populations behaved in patchy landscapes where the animals home range exceeded or equaled patch size. We used a small-scale replicated experiment consisting of three sets of two patches each, unconnected or interconnected by 1-m or 5-m wide-corridors, established in an old-field community (S.W. Ohio). Control (0-m) treatments supported significantly lower vole densities than either corridor treatment. Females were the dominant resident sex establishing smaller home ranges (< 150m2) than males (> 450m2). Significantly more male voles dispersed between patches with corridors than between patches without corridors. However, no difference was observed regarding the number of male voles dispersing between patches connected by corridors when compared to the number dispersing across treatments. Dispersal between connected patches was restricted to corridors based on tracking tube data. Corridor presence was more important than corridor width regarding the movement of male voles within their home range.://A1993KW95800003-Kw958 Times Cited:65 Cited References Count:0 0921-2973ISI:A1993KW958000030Lapolla, Vn Miami Univ,Dept Zool,Oxford,Oh 45056English <7wLarsen, D. R. Bliss, L. C.1998@An analysis of structure of tree seedling populations on a Lahar307-322Landscape Ecology135Xspatial pattern community structure tree seedlings Mount St Helens Ripley's K lacunarityArticleOct+The structure of a tree seedling population is dependent on the interaction of several processes including seed dispersal, germination, survival, and competition on a physical landscape. Structural components (composition, size distributions, spatial distributions, age distributions, density, and history) of a tree seedling population on the Muddy River Lahar on the east side of Mount St. Helens were examined over a range of extents (1/10 m to 1000 m). Many of these component have rarely been examined at the larger extents listed here. Composition reflected distances to seed source and seed morphology. Seedling sizes are inversely proportional to depth to a buried soil if one existed. Spatial patterns indicated that seedling are clustered for tree seedlings less than 200 m apart, random for tree seedling from 200 m to 400 m and uniform for seedling greater than 400 m apart. This was confirmed by two measures of multidimensional spatial point pattern. Age distributions did not reflect the size distributions; old seedlings could be almost any size, young seedlings were constrained to be small in size. Densities appear to be typical for forests in the area. History of disturbance events (the lahar establishment, and successive ash, pumice, and erosion) has strongly influenced this tree seedling community.://000165537200003 HISI Document Delivery No.: V2651 Times Cited: 6 Cited Reference Count: 35 Cited References: ADAMS AB, 1987, NORTHWEST SCI, V61, P160 BEARDSLEY GF, 1930, ECOLOGY, V11, P326 BESAG JE, 1973, B INT STAT I, V45, P153 BROWN GS, 1965, 38 NZ FOR, P1 BYTH K, 1980, BIOMETRICS, V36, P279 CHAPIN IFS, 1994, ECOL MONOGR, V64, P149 CRESSIE NAC, 1993, STAT SPATIAL DATA DELMORAL R, 1993, J VEG SCI, V4, P223 DIGGLE PJ, 1983, STAT ANAL SPATIAL PO FRENZEN PM, 1988, CAN J BOT, V66, P130 FRENZEN PM, 1990, NW SCI, V64, P263 GETIS A, 1987, ECOLOGY, V68, P473 GREEN PJ, 1978, COMPUT J, V21, P168 GREENE DF, 1989, ECOLOGY, V70, P339 HALPERN CB, 1983, AM MIDL NAT, V110, P97 HARPER JL, 1977, POPULATION BIOL PLAN HOLGATE P, 1964, BIOMETRICS, V20, P647 HOLGATE P, 1965, J ECOL, V53, P261 HOPKINS B, 1954, ANN BOT-LONDON, V18, P213 KELLER SAC, 1986, MOUNT ST HELENS 5 YE KIMURA W, 1991, ECOL RES, V6, P63 KNOX RG, 1989, ECOLOGY, V70, P1153 LEE DT, 1980, INT J COMPUT INF SCI, V9, P219 MILLER TE, 1987, ECOLOGY, V68, P1201 MOORE PG, 1953, ANN BOT-LONDON, V17, P57 MOORE PG, 1954, ECOLOGY, V35, P222 MOUNTFORD MD, 1961, J ECOL, V49, P271 PLOTNICK RE, 1993, LANDSCAPE ECOL, V8, P201 PLOTNICK RE, 1996, PHYS REV E B, V53, P5461 RENNOLLS K, 1993, STOCHASTIC SPATIAL M RIPLEY BD, 1976, ANN PROBAB, V4, P983 RIPLEY BD, 1981, SPATIAL STAT SKELLAM JG, 1952, BIOMETRIKA, V39, P346 TOMPPO E, 1986, COMMUNICATIONES I FO, V138, P65 WILSON SD, 1995, ECOLOGY, V76, P1169 0921-2973 Landsc. Ecol.ISI:000165537200003Univ Missouri, Sch Nat Resources, Columbia, MO 65211 USA. Univ Washington, Dept Bot KB15, Seattle, WA 98195 USA. Larsen, DR, Univ Missouri, Sch Nat Resources, 1-30 Agr Bldg, Columbia, MO 65211 USA.English<7Larsen, J. K. Madsen, J.2000Effects of wind turbines and other physical elements on field utilization by pink-footed geese (Anser brachyrhynchus): A landscape perspective755-764Landscape Ecology158avoidance distance GIS habitat loss landscape physical elements pink-footed geese waterbirds windbreaks wind turbines DISTURBANCEArticleDecw The effects of wind turbines and other physical landscape elements on field utilization by wintering pink-footed geese (Anser brachyrhynchus) were studied in a Danish farmland landscape. Within the study area geese were feeding on pastures, which together with cereals were the main crop types. Apart from wind turbines a variety of potentially disturbing landscape elements was present, e.g., high-power lines, windbreaks, roads and settlements. Patterns of field use were assessed by measuring goose dropping densities along transects perpendicular to wind farms (with turbines in clusters and in lines) and other landscape elements. Local effects were expressed in terms of 'avoidance distance', i.e., the distance from a given landscape element to the point at which 50% of maximal dropping density was reached. The spatial distribution of landscape elements within an eight km radius from the goose roost was determined from aerial photographs. The area occupied by various elements, together with the adjacent zones which were not available to geese due to their associated avoidance distances, were quantified using Geographic Information System (GIS). The avoidance distance of wind farms with turbines in lines and in clusters were ca 100 m and ca 200 m, respectively. Geese did not enter the area between turbines within the cluster. At the landscape level, the combined effect of physical elements other than wind turbines caused an effective loss of 68% of the total field area (40 km(2)). Wind turbines caused an additional loss of 4% of the field area. However, of the remaining area available to geese (13 km(2)), wind turbines caused a loss of 13% of the total area. The habitat loss per turbine was higher for the wind farm with turbines arranged in a large cluster than for wind farms with turbines in small clusters or lines. This difference was mainly due to the fact that wind farms in small clusters or with a linear layout were generally placed close to roads or other elements with existing associated avoidance zones, whereas the large cluster was placed in the open farmland area. The avoidance zones associated with physical elements in the landscape do not take into account possible synergistic effects and, hence, actual field areas affected are likely to be minimum estimates. Implications of these findings for planning of wind farms in areas of conservation interest to geese are discussed.://000165379700006 ISI Document Delivery No.: 375BM Times Cited: 7 Cited Reference Count: 14 Cited References: 1996, EF FUGLEBESKYTTELSES DIRKSEN S, 1998, WIND ENERGY LANDSCAP, P99 FOX AD, 1997, J APPL ECOL, V34, P1 GUILLEMETTE M, 1998, 227 NERI GUILLEMETTE M, 1999, 263 NERI KRUCKENBERG H, 1999, NATUR LANDSCHAFT, V74, P420 MADSEN J, 1985, BIOL CONSERV, V33, P53 MADSEN J, 1985, ORNIS SCAND, V16, P222 MADSEN J, 1996, WILDLIFE BIOL, V2, P1 MADSEN J, 1998, VEJLERNES NATUR STAT, P163 MADSEN J, 1999, WETLANDS INT PUBLICA, V48, P82 PERCIVAL SM, 1999, WIND ENERGY CONVERSI, P345 WINKELMAN JE, 1989, 8915 RIN WINKELMAN JE, 1992, 925 RIN DLO I BOS NA 0921-2973 Landsc. Ecol.ISI:000165379700006Natl Environm Res Inst, Dept Coastal Zone Ecol, DK-8410 Ronde, Denmark. Larsen, JK, Carl Bro AS, Nordlandsvej 60, DK-8410 Risskov, Denmark.English|? KLarsen, R. T. Bissonette, J. A. Flinders, J. T. Hooten, M. B. Wilson, T. L.2010NSummer spatial patterning of chukars in relation to free water in western Utah135-145Landscape Ecology251Free water is considered important to wildlife in arid regions. In the western United States, thousands of water developments have been built to benefit wildlife in arid landscapes. Agencies and researchers have yet to clearly demonstrate their effectiveness. We combined a spatial analysis of summer chukar (Alectoris chukar) covey locations with dietary composition analysis in western Utah. Our specific objectives were to determine if chukars showed a spatial pattern that suggested association with free water in four study areas and to document summer dietary moisture content in relation to average distance from water. The observed data for the Cedar Mountains study area fell within the middle of the random mean distance to water distribution suggesting no association with free water. The observed mean distance to water for the other three areas was much closer than expected compared to a random spatial process, suggesting the importance of free water to these populations. Dietary moisture content of chukar food items from the Cedar Mountains (59%) was significantly greater (P < 0.05) than that of birds from Box Elder (44%) and Keg-Dugway (44%). Water developments on the Cedar Mountains are likely ineffective for chukars. Spatial patterns on the other areas, however, suggest association with free water and our results demonstrate the need for site-specific considerations. Researchers should be aware of the potential to satisfy water demand with pre-formed and metabolic water for a variety of species in studies that address the effects of wildlife water developments. We encourage incorporation of spatial structure in model error components in future ecological research.!://WOS:000273479100011Times Cited: 0 0921-2973WOS:00027347910001110.1007/s10980-009-9407-z?jLathrop, R.G. D.L. Peterson1992@Identifying structural self-similarity in mountainous landscapes233-238Landscape Ecology64Hmodel, fractals, ladnscape pattern, ecosystem, self-similarity, fractalsDigital elevation model data were used to partition a mountainous landscape (northwestern Montana, USA) into watershed/hillslope terrain units at several different spatial scales. Fractal analysis of the perimeter to area relationships of the resulting partition polygons identified statistical self-similarity across a range of spatial scales (approximately four orders of magnitude in partition area). The fractal dimension was higher for a relatively complex fluvially-dominated terrain than for a structurally simpler glacially-dominated terrain (1.23 vs. 1.02, respectively). The structural self-similarity exhibited by this landscape has direct implications in scaling up ecosystem process models for landscape to regional simulations.<7] Latta, R. G.2006OIntegrating patterns across multiple genetic markers to infer spatial processes809-820Landscape Ecology216coalescent; F-st; migration-drift equilibrium; ponderosa pine; Q(st); selection ADAPTIVE POPULATION DIVERGENCE; CHLOROPLAST DNA DIVERSITY; PINUS-FLEXILIS JAMES; PONDEROSA PINE; MITOCHONDRIAL-DNA; QUANTITATIVE TRAITS; MICROSATELLITE LOCI; NATURAL-SELECTION; GENOME SCANS; SILENE ALBAArticleAugLandscape geneticists can take considerable advantage of differences in the action of evolutionary forces (mutation, migration, selection, and drift) on different loci within the genome. Appropriate comparisons among loci allow researchers to isolate and study the effects of these processes. For example, the organelles are typically inherited maternally (but occasionally paternally), and so will experience migration only when females or seeds disperse (males or pollen in the paternally inherited organelles). Thus, the comparison with biparentally inherited loci allows inferences about the differential migration rates of male vs. female animals or of seeds vs. pollen in plants. Conversely, all biparentally inherited nuclear loci should experience the same levels of migration and drift. Thus, loci that show unusually large levels of variation across the landscape (as compared with the bulk of loci) may be reflecting the action of spatially varying natural selection (local adaptation). Such comparisons are conceptually straightforward, but are complicated by the high intrinsic variability of stochastic neutral processes. Careful statistical analysis is needed to avoid over-interpreting differences among loci. Inferences will be most robust when both genetic and non-genetic data can be integrated, and the collaboration of landscape ecologists with geneticists promises to be particularly fruitful.://000239484200003 ISI Document Delivery No.: 069YA Times Cited: 2 Cited Reference Count: 75 Cited References: ALLENDORF FW, 2000, EVOLUTION, V54, P640 AUSTERLITZ F, 2004, MOL ECOL, V13, P937 BEAUMONT MA, 1996, P ROY SOC LOND B BIO, V263, P1619 BEAUMONT MA, 2004, MOL ECOL, V13, P969 BLACK WC, 2001, ANNU REV ENTOMOL, V46, P441 CONKLE MT, 1988, PONDEROSA PINE SPECI, P27 CRANDALL KA, 2000, TRENDS ECOL EVOL, V15, P290 DEINNOCENTIIS S, 2001, MOL ECOL, V10, P2163 DHUYVETTER H, 2004, MOL ECOL, V13, P1065 DONG JS, 1994, GENETICS, V136, P1187 DRAKE JW, 1998, GENETICS, V148, P1667 EANES WF, 1999, ANNU REV ECOL SYST, V30, P301 ENNOS RA, 1994, HEREDITY, V72, P250 ENNOS RA, 1999, MOL SYSTEMATICS PLAN, P1 ESTOUP A, 2001, GENETICS, V159, P1671 EXCOFFIER L, 2000, J HERED, V91, P506 FALCONER DS, 1996, INTRO QUANTITATIVE G HAMRICK JL, 1992, POPULATION GENETICS, P95 HEDRICK PW, 1999, EVOLUTION, V53, P313 HOLDEREGGER R, 2006, LANDSCAPE ECOL, V21, P797 HONG YP, 1993, GENETICS, V135, P1187 HUDSON RR, 1990, OXF SURV EVOL BIOL, V7, P1 JARAMILLOCORREA JP, 2001, MOL ECOL, V10, P2729 JOHANSEN AD, 2003, MOL ECOL, V12, P293 KARL SA, 1992, SCIENCE, V256, P100 KOHN MH, 2000, P NATL ACAD SCI USA, V97, P7911 LASCOUX M, 2004, PHILOS T ROY SOC B, V359, P197 LATTA RG, 1997, GENETICS, V146, P1153 LATTA RG, 1998, EVOLUTION, V52, P61 LATTA RG, 1999, EVOLUTION, V53, P769 LATTA RG, 2004, NEW PHYTOL, V151, P63 LENORMAND T, 1999, NATURE, V400, P861 LEWONTIN RC, 1973, GENETICS, V74, P175 LEWONTIN RC, 1991, GENETICS, V128, P657 LYNCH M, 1999, EVOLUTION, V53, P100 MANEL S, 2003, TRENDS ECOL EVOL, V18, P189 MCCAULEY DE, 1994, P NATL ACAD SCI USA, V91, P8127 MCCAULEY DE, 1996, AM J BOT, V83, P727 MCKAY JK, 2002, TRENDS ECOL EVOL, V17, P285 MERILA J, 2001, J EVOLUTION BIOL, V14, P892 MILLIGAN BG, 1991, CURR GENET, V19, P411 MITTON JB, 2000, MOL ECOL, V9, P91 MITTON JB, 2004, MOL ECOL, V13, P1259 NEIGEL JE, 1997, ANNU REV ECOL SYST, V28, P105 NIEBLING CR, 1990, CAN J FOREST RES, V20, P298 NORDBORG M, 2001, HDB STAT GENETICS, P179 OAKSHOTT JG, 1982, EVOLUTION, V36, P86 ODDOUMURATORIO S, 2001, EVOLUTION, V55, P1123 PANNELL JR, 2006, LANDSCAPE ECOL, V21, P837 PETIT E, 2002, TRENDS ECOL EVOL, V17, P28 PETIT RJ, 1993, HEREDITY, V71, P630 PODOLSKY RH, 1995, GENETICS, V140, P733 POGSON GH, 1995, GENETICS, V139, P375 POWERS DA, 1993, OXFORD SURVEYS EVOLU, V9, P49 REHFELDT GE, 1999, ECOL MONOGR, V69, P375 RICE SH, 2004, EVOLUTIONARY THEORY RICHARDSON BA, 2002, MOL ECOL, V11, P215 RICHARDSON DM, 1998, ECOLOGY BIOGEOGRAPHY ROSENBERG NA, 2002, NAT REV GENET, V3, P380 ROSS KG, 2001, DISPERSAL, P29 SCRIBNER KT, 1994, MOL BIOL EVOL, V11, P737 SLATKIN M, 1995, GENETICS, V139, P457 SLATKIN M, 2001, EVOL GENET, P418 SORK VL, 2006, LANDSCAPE ECOL, V21, P821 SPITZE K, 1993, GENETICS, V135, P367 SQUIRRELL J, 2001, AM J BOT, V88, P1409 STORZ JF, 2005, MOL ECOL, V14, P671 VITALIS R, 2001, GENETICS, V158, P1811 WAGNER DB, 1992, POPULATION GENETICS, P373 WATT WB, 2003, MOL ECOL, V12, P1265 WEIR BS, 1991, GENETIC DATA ANAL WHITLOCK MC, 1999, HEREDITY 2, V82, P117 WRIGHT S, 1951, ANN EUGEN, V15, P323 WRIGHT S, 1952, GENETICS, V37, P312 ZOUROS E, 2000, GENES GENET SYST, V75, P313 0921-2973 Landsc. Ecol.ISI:000239484200003Dalhousie Univ, Dept Biol, Halifax, NS B2H 4J1, Canada. Latta, RG, Dalhousie Univ, Dept Biol, Halifax, NS B2H 4J1, Canada. Robert.Latta@Dal.caEnglish$?KJ. Lauga J. Joachim1992XModelling the effects of forest fragmentation on certain species of forestbreeding birds183-193Landscape Ecology63>forest fragmentation, breeding birds, modelling, incidence map6The influence of forest fragmentation was assessed on the abundance of six forest-breeding bird species. The study area (2327 sq Km) was located in south-west France. The forest cover, extracted from a Landsat MSS scene, was first reduced to a grid of 5865 quadrats, each 650 by 650 m. Two values were attributed with each quadrat: Quadrat Forest Cover (QFC), expressed in percent; and a local measure of forest fragmentation - the Neighbouring Forest Cover (NFC) - expressed on a 0-1000 scale. The distribution of six forestbreeding species was sampled on 556 quadrats. For each species, the local abundance appears to be more correlated with the fragmentation-oriented NFC value than with the local QFC value. For three species out of six (song thrush, robin, chaffinch) an incidence model, based on the Logistic regression, was built. A correct fit was obtained. An incidence map of these species was then built up over the whole study area. Their regional status was then estimated, for a sampling cost of less than 10% of censusing all the area.+?Laura, R. Musacchio2002SBryn Green and Willem Vos, Threatened Land-scapes: Conserving Cultural Environments190-191Landscape Ecology172 book reviewsZThis revised version was published online in July 2006 with corrections to the Cover Date.*http://dx.doi.org/10.1023/A:1019501821354 `10.1023/A:1019501821354 References : Akçakaya H.R. 1998. RAMAS-GIS: Linking landscape data with population viability analysis. Ver 3.0. Applied Biomathematics. Setauket, NY, USA. Brook B.W. et al. 2000. Predictive accuracy of population viability analysis in conservation biology. Nature 404, 385-387. Hanksi I. 1994. A practical model of metapopulation dynamcis. J. Anim. Ecol. 63, 151-162. Hanski I. 1999. Metapopulation Ecology. Oxford University Press, Oxford, UK. Lacy R.C. 1993. VORTEX: A computer simulation model for population viability analysis. Wild. Res. 20, 45-65. Menges E.S. 2000. Applications of population viability analyses in plant conservation. In: P. Sjögren-Gulve and T. Ebenhard (eds.), The Use of Population Viability Analyses in Conservation Planning. Ecological Bulletins 48, pp. 73-84, Lund, Sweden. Shaffer M.L. 1981. Minimum viable population sizes for species conservation. Bioscience 31, 131-134. Tuljapurkar S. and Caswell H. (eds.) 1996. Structure Population Models in Marine, Terrestrial and Freshwater Systems. Chapman and Hall, New York, NY, USA. School of Planning Landscape Architecture and the Center for Environmental Studies, Arizona State University, Tempe, AZ 85287-2005, USA|7P (Lavorel, S. Gardner, R. H. Oneill, R. V.1995BDispersal of Annual Plants in Hierarchically Structured Landscapes277-289Landscape Ecology1058landscape ecology hierarchy seed dispersal annual plantsOctThe scale at which plants utilize spatially distributed resources may be determined by their ability to locate sites that can sustain population growth. We developed a spatially-explicit model of the dispersal of annual plants in landscapes which were hierarchically structured, i.e., the spatial pattern of suitable sites was nested and scale-dependent. Results show that colonizing ability and extinction probability are most sensitive to the mean dispersal distance of the species. Dispersal out of the parental site, but within the immediate neighborhood, was the most efficient means for popolation expansion. When landscape patterns change with scale then dispersal distances determine the spatial scales of habitat utilization. As a complicating factor, the type of statistical distribution of dispersal distances also influences the colonizing ability. However, the importance of dispersal distance mean and distribution decreased as the number and connectance of suitable sites increased. The results suggest that landscape models which consider the interaction between scale dependent changes in landscape pattern and species dispersal and establishment characteristics are relevant to many issues in community ecology, invasion biology, and conservation biology.://A1995TD59500003-Td595 Times Cited:40 Cited References Count:0 0921-2973ISI:A1995TD59500003JLavorel, S Cnrs,Ctr Ecol Fonct & Evolut,Bp 5051,F-34033 Montpellier,FranceEnglishF?mLavorel, S. M. S. Smith N. Reid1997RSpread of mistletoes (Amyena preissii) in fragmented woodlands: a simulation studyLandscape Ecology Manuscript%<7^!Lavorel, S. Smith, M. S. Reid, N.1999]Spread of mistletoes (Amyema preissii) in fragmented Australian woodlands: a simulation study147-160Landscape Ecology142invasion ornithochory mistletoe Amyema preissii fragmented landscape arid woodland simulation model HIERARCHICALLY STRUCTURED LANDSCAPES FRUIT REMOVAL DISPERSAL HONEYEATERS BIRDS FLOWERPECKERS SURVIVAL MODELS SIZEArticleApr A simulation model was used to study the interaction between landscape pattern and components of the dispersal strategy of the mistletoe Amyema preissii by mistletoe birds (Dicaeum hirundinaceum). The landscape was modelled as a map of host trees for the mistletoes, characterised by the total density and clumpiness of trees. A landscape was considered as a set of equal sized bird territories, with the majority of seeds produced in such a territory dispersed within that area. Age-specific birth and death rates of mistletoes were measured in the field. Seed dispersal was characterised by four parameters: the fraction of within-tree seed dispersal, the ratio of attractiveness to birds of tree canopy volume over attractiveness of mistletoe fruit number, seed survival, and the fraction of seeds leaving their original territory. A sensitivity analysis was carried out using a factorial design on landscape type and dispersal parameters. General linear modelling of mistletoe population size after 100 years showed that, in a given landscape, seed survival was the strongest determinant, Total mistletoe population also increased exponentially with tree density, but the number of mistletoes per tree decreased. Population size depended on tree clumping as well, with larger mistletoe populations sustained by woodlands with clumped trees. For a given level of seed survival, population size increased when birds were more attracted by canopy volume than by fruit crop. The strongest increase in population size occured for a combination of low tree density with high relative attractiveness. The relative effects of the fraction of within-tree dispersal and tree density depended on seed survival. For lower survival, fraction of within-tree dispersal determined population size more strongly while for higher survival, tree density became the dominant factor Population size was negatively correlated with the fraction of within-tree dispersal. Finally, population size strongly increased only if dispersal out of a bird's territory represented 10% of the seed crop, a high value which seems unlikely in the field. The results support the hypothesis that woodland fragmentation promotes invasion by mistletoes. Although simulated mistletoe populations deviated from our natural population in having an excess of young individuals, sensitivity analysis produced several non-intuitive results and is thus valuable in focussing further efforts on field data collection. This study also illustrates how a simulation model of population dynamics can help in determining control strategies for an invasive organism. A reduction in seed survival and disinfection of larger trees would appear to be the most efficient strategy.://000079802500005 ISI Document Delivery No.: 187RV Times Cited: 8 Cited Reference Count: 39 Cited References: DENSLOW JS, 1987, CAN J BOT, V65, P1229 DUNNING JB, 1992, OIKOS, V65, P169 FAHRIG L, 1985, ECOLOGY, V66, P1762 GARDNER RH, 1987, LANDSCAPE ECOL, V3, P76 GARDNER RH, 1991, QUANTITATIVE METHODS, P289 GARDNER RH, 1993, HUMANS COMPONENTS EC, P208 GRICE AC, 1994, AUST J ECOL, V19, P10 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 HAWKSWORTH FG, 1983, BIOL MISTLETOES, P317 HOBBS RH, 1992, CONS BIOL, V6, P325 HOWE HF, 1979, AM NAT, V114, P925 JORDANO P, 1987, ECOLOGY, V68, P1711 KAREIVA P, 1986, COMMUNITY ECOLOGY, P192 LAVOREL S, 1993, OIKOS, V67, P521 LAVOREL S, 1995, LANDSCAPE ECOL, V10, P277 MCINTYRE S, 1992, CONSERV BIOL, V6, P146 MILNE BT, 1992, AM NAT, V139, P32 MILNE BT, 1992, THEOR POPUL BIOL, V41, P337 MURPHY SR, 1993, OECOLOGIA, V93, P171 ONEILL RV, 1988, LANDSCAPE ECOL, V2, P63 OVERTON JM, 1994, J ECOL, V82, P711 PERRY JN, 1993, J ECOL, V81, P453 REID N, IN PRESS AUSTR J BOT REID N, 1987, EMU, V87, P130 REID N, 1988, AUST J BOT, V36, P299 REID N, 1989, ECOLOGY, V70, P137 REID N, 1990, AUST J ECOL, V15, P175 REID N, 1991, AUST J ECOL, V16, P457 REID N, 1992, AUST J ECOL, V17, P219 REID N, 1995, FOREST CANOPIES, P285 REID N, 1995, P C DIEB REDR RUR TR, P40 SARGENT S, 1990, ECOLOGY, V71, P1289 SMITH RB, 1976, CANADIAN J FOREST RE, V6, P225 THEBAUD C, 1992, OIKOS, V65, P391 THOMSON VE, 1983, BOT GAZ, V114, P124 WITH KA, 1997, OIKOS, V79, P219 WU JG, 1994, ECOL MONOGR, V64, P447 YAN ZG, 1993, AUST J ECOL, V18, P419 YAN ZG, 1995, J APPL ECOL, V32, P778 0921-2973 Landsc. Ecol.ISI:000079802500005Australian Natl Univ, Res Sch Biol Sci, Canberra, ACT 0200, Australia. Lavorel, S, CNRS, UPR 9056, Ctr Ecol Fonct & Evolut, F-34293 Montpellier 5, France.Englishb<7Lawler, J. J. Edwards, T. C.2002Landscape patterns as habitat predictors: building and testing models for cavity-nesting birds in the Uinta Mountains of Utah, USA233-245Landscape Ecology173habitat mapping habitat models mountain chickadee nest-site selection northern flicker prediction red-naped sapsucker tree swallow FOREST WOODLANDS EDGEArticleQThe ability to predict species occurrences quickly is often crucial for managers and conservation biologists with limited time and funds. We used measured associations with landscape patterns to build accurate predictive habitat models that were quickly and easily applied (i.e., required no additional data collection in the field to make predictions). We used classification trees (a nonparametric alternative to discriminant function analysis, logistic regression, and other generalized linear models) to model nesting habitat of red-naped sapsuckers (Sphyrapicus nuchalis), northern flickers (Colaptes auratus), tree swallows (Tachycineta bicolor), and mountain chickadees (Parus gambeli) in the Uinta Mountains of northeastern Utah, USA. We then tested the predictive capability of the models with independent data collected in the field the following year. The models built for the northern flicker, red-naped sapsucker, and tree swallow were relatively accurate (84%, 80%, and 75% nests correctly classified, respectively) compared to the models for the mountain chickadee (50% nests correctly classified). All four models were more selective than a null model that predicted habitat based solely on a gross association with aspen forests. We conclude that associations with landscape patterns can be used to build relatively accurate, easy to use, predictive models for some species. Our results stress, however, that both selecting the proper scale at which to assess landscape associations and empirically testing the models derived from those associations are crucial for building useful predictive models.://000178082200003 ISI Document Delivery No.: 594ZK Times Cited: 10 Cited Reference Count: 42 Cited References: *JAD, 1976, BIRD POP ASP FOR W N *MATHS INC, 1998, S PLUS 4 3 *US FISH WILDL SER, 1981, STAND DEV SUIT IND M BRAWN JD, 1988, CONDOR, V90, P61 BREIMAN L, 1984, CLASSIFICATION REGRE CODY ML, 1985, HABITAT SELECTION BI CONNER RN, 1977, WILSON B, V89, P122 DAVIS F, 1993, GAP ANAL GEOGRAPHIC DEATH G, 2000, ECOLOGY, V81, P3178 DOBKIN DS, 1995, CONDOR, V97, P694 DUNNING JB, 1993, CRC HDB AVIAN BODY EDWARDS TC, 1996, CONSERV BIOL, V10, P263 EHRLICH PR, 1988, AM BIRDS, V42, P357 EVANS KE, 1979, MANAGEMENT N CENTRAL, P214 FIELDING AH, 1995, CONSERV BIOL, V9, P1466 FIELDING AH, 1997, ENVIRON CONSERV, V24, P38 FREEMARK KE, 1986, BIOL CONSERV, V36, P115 FREEMARK KE, 1995, ECOLOGY MANAGEMENT N, P381 GUTZWILLER KJ, 1987, CONDOR, V89, P534 HANSEN AJ, 1992, ECOLOGICAL STUDIES, V92 HAWROT RY, 1996, AUK, V113, P586 HILDEN O, 1965, ANN ZOOL FENN, V2, P53 KARL JW, 1999, WILDLIFE SOC B, V27, P357 LAUDENSLAYER WF, 1976, AUK, V93, P571 MCGARIGAL K, 1993, PW351 USDA FOR SERV PETERSON AT, 1999, ECOL MODEL, V117, P159 RAPHAEL MG, 1984, WILDLIFE MONOGR, V86, P1 RAPHAEL MG, 1986, ECOLOGY CONSERVATION, P129 RENDELL WB, 1990, WILSON BULL, V102, P634 ROBERTSON RJ, 1992, BIRDS N AM, P1 ROBINSON SK, 1992, ECOLOGY CONSERVATION, P408 SALWASSER H, 1982, CALIFORNIAS WILDLIFE, P34 STAUFFER DF, 1986, WILDLIFE 2000 MODELI, P71 VANHORNE B, 1991, FISH WILDLIFE RES, V8 VENABLES WN, 1997, MODERN APPL STAT S P VERNER J, 1980, PSW37 PAC SW FOR RAN VERNER J, 1986, WILDLIFE 2000 MODELI WIENS JA, 1989, FUNCT ECOL, V3, P385 WILCOVE DS, 1985, ECOLOGY, V66, P1211 WINTERNITZ BL, 1980, INT86 US FOR SERV GE, P247 WITH KA, 1994, LANDSCAPE ECOL, V9, P25 ZWEIG MH, 1993, CLIN CHEM, V39, P561 0921-2973 Landsc. Ecol.ISI:000178082200003}Utah State Univ, Dept Fisheries & Wildlife, Logan, UT 84322 USA. Lawler, JJ, US EPA, 200 SW 35th St, Corvallis, OR 97333 USA.English<7TLawler, J. J. O'Connor, R. J. Hunsaker, C. T. Jones, K. B. Loveland, T. R. White, D.2004The effects of habitat resolution on models of avian diversity and distributions: a comparison of two land-cover classifications515-530Landscape Ecology195jbird species richness; Blackcapped Chickadee; classification; House Wren; land-cover; landscape pattern; Ovenbird; Pine Siskin; predictive modeling; Red-eyed Vireo; Savannah Sparrow; USA CONTERMINOUS UNITED-STATES; BIRD SPECIES-DIVERSITY; CAVITY-NESTING BIRDS; SPATIAL SCALE; HIERARCHICAL ANALYSIS; LANDSCAPE PATTERN; BREEDING BIRDS; RICHNESS; SELECTION; ECOLOGYArticlesQuantifying patterns is a key element of landscape analysis. One aspect of this quantification of particular importance to landscape ecologists is the classification of continuous variables to produce categorical variables such as land-cover type or elevation stratum. Although landscape ecologists are fully aware of the importance of spatial resolution in ecological investigations, the potential importance of the resolution of classifications has received little attention. Here we demonstrate the effects of using two different land-cover classifications to predict avian species richness and the occurrences of six individual species across the conterminous United States. We compared models built with a data set based on 14 coarsely resolved land-cover variables to models built with a data set based on 160 finely resolved land-cover variables. In general, comparable models built with the two data sets fit the data to similar degrees, but often produced strikingly different predictions in various parts of the country. By comparing the predictions made by pairs of models, we determined in which regions of the US predictions were most sensitive to differences in land-cover classification. In general, these sensitive areas were different for four of the individual species and for predictions of species richness, indicating that alternate classifications will have different effects in the analyses of different ecological phenomena and that these effects will likely vary geographically. Our results lead us to emphasize the importance of the resolution to which continuous variables are classified in the design of ecological studies.://000222941500005 ISI Document Delivery No.: 841OY Times Cited: 3 Cited Reference Count: 64 Cited References: *HCN, 1996, MONTHL PREC TEMP DAT ABRAMSKY Z, 1984, NATURE, V309, P150 ANDERSON JR, 1976, US GEOLOGICAL SURVEY, V964 ANDERSON SH, 1974, ECOLOGY, V55, P828 BERGIN TM, 1992, CONDOR, V94, P903 BREIMAN L, 1984, CLASSIFICATION REGRE BROWN JH, 1977, SCIENCE, V196, P880 CLARK LA, 1992, STAT MODELS S, P377 CODY ML, 1978, ECOL MONOGR, V48, P351 COLLINS SL, 1983, AUK, V100, P382 CURRIE DJ, 1991, AM NAT, V137, P27 CURRIE DJ, 1999, ECOSCIENCE, V6, P392 DALY C, 1994, J APPL METEOROL, V33, P140 DANKO DM, 1992, GEOINFO SYSTEMS, V2, P29 DEATH G, 2000, ECOLOGY, V81, P3178 DINIZ JAF, 2003, GLOBAL ECOL BIOGEOGR, V12, P53 DUFRENE M, 1997, ECOL MONOGR, V67, P345 GASTON KJ, 2000, NATURE, V405, P220 GITHAIGAMWICIGI JMW, 2002, J BIOGEOGR, V29, P1067 GUTZWILLER KJ, 1987, CONDOR, V89, P534 HARGIS CD, 1997, WILDLIFE LANDSCAPE E, P231 HAWKINS BA, 2003, ECOLOGY, V84, P1608 HERRERA CM, 1978, AUK, V95, P496 HILDEN O, 1965, ANN ZOOL FENN, V2, P53 HUNSAKER CT, 1994, LANDSCAPE ECOL, V9, P207 HUTTO RL, 1985, HABITAT SELECTION BI, P455 IVERSON LR, 1998, ECOL MONOGR, V68, P465 JONES KB, 2000, ENVIRON MONIT ASSESS, V63, P159 LAWLER JJ, 2002, LANDSCAPE ECOL, V17, P233 LOVELAND TR, 1991, PHOTOGRAMM ENG REM S, V57, P1453 LOVELAND TR, 1995, ANN ASSOC AM GEOGR, V85, P339 LUOTO M, 2002, J BIOGEOGR, V29, P1027 MACARTHUR RH, 1966, AM NAT, V100, P319 MARKS D, 1990, BIOSPHERIC FEEDBACKS MCCOMB WC, 2002, FOREST SCI, V48, P203 MILLER T, 1994, P STAT COMP SECT AM, P158 OCONNOR RJ, 1996, BIODIVERSITY LETT, V3, P97 OCONNOR RJ, 1999, STUDIES AVIAN BIOL, V19, P45 OLDEN JD, 2002, FRESHWATER BIOL, V47, P1976 OMERNIK JM, 1987, ANN ASSOC AM GEOGR, V77, P118 ONEILL RV, 1986, MONOGRAPHS POPULATIO, V23 ONEILL RV, 1991, LANDSCAPE ECOL, V5, P137 PIANKA ER, 1966, AM NAT, V100, P33 PIANKA ER, 1967, ECOLOGY, V48, P333 QI Y, 1996, LANDSCAPE ECOL, V11, P39 RAHBEK C, 2001, P NATL ACAD SCI USA, V98, P4534 RATHERT D, 1999, J BIOGEOGR, V26, P257 RECHER HF, 1969, AM NAT, V103, P75 RICKLEFS RE, 1980, AUK, V97, P38 ROBBINS CS, 1986, FISH WILDLIFE SERVIC, V157 SAAB V, 1999, ECOL APPL, V9, P135 SCHALL JJ, 1978, SCIENCE, V201, P679 SCOTT JM, 1993, WILDLIFE MONOGR, P1 STEFFANDEWENTER I, 2002, ECOLOGY, V83, P1421 STEHMAN SV, 2003, REMOTE SENS ENVIRON, V86, P500 TERBORGH J, 1977, ECOLOGY, V58, P1007 TIMMONS SP, 1995, GIS ENV MODELING PRO, P473 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 VANRENSBURG BJ, 2002, AM NAT, V159, P566 VENABLES WN, 1994, MODERN APPL STAT SPL WHITE D, 1992, CARTOGR GEOGR INFORM, V19, P5 WHITTAKER RH, 1960, ECOL MONOGR, V30, P279 WIENS JA, 1989, FUNCT ECOL, V3, P385 WILLIAMS SE, 2002, ECOLOGY, V83, P1317 0921-2973 Landsc. Ecol.ISI:000222941500005_Univ Maine, Dept Wildlife Ecol, Orono, ME 04469 USA. US Forest Serv, USDA, Pacific SW Res Stn, Fresno, CA 93710 USA. US EPA, Las Vegas, NV 89193 USA. USGS, EROS Data Ctr, Sioux Falls, SD 57198 USA. Univ Maine, Margaret Chase Smith Ctr Publ Policy, Orono, ME 04469 USA. Lawler, JJ, US EPA, 200 SW 35th St, Corvallis, OR 97333 USA. lawler.joshua@epa.govEnglishj<7j&Lawrence, D. Peart, D. R. Leighton, M.1998nThe impact of shifting cultivation on a rainforest landscape in West Kalimantan: spatial and temporal dynamics135-148Landscape Ecology133shifting cultivation land-use change deforestation rainforest landscape West Kalimantan Indonesia LAND-USE CHANGE SWIDDEN AGRICULTURE TROPICAL FOREST SATELLITE DATA DEFORESTATION INDONESIA FRAGMENTATION GARDENS RUBBER SYSTEMArticleJunTo assess the role of shifting cultivation in the loss of rainforests in Indonesia, we examined the spatial and temporal dynamics of traditional land-use north of Gunung Palung National Park in West Kalimantan. We analyzed the abundance, size, frequency, and stature (by tree size) of discrete management units (patches) as a function of land-use category and distance from the village. Data were gathered from point samples along six 1.5-km transects through the landscape surrounding the Dayak village of Kembera. Most land was managed for rice, with 5% in current production, 12% in wet-rice fallows (regenerating swamp forest), and 62% in dry-rice fallows (regenerating upland forest). The proportion of land in dry-rice increased with distance from the village; rubber gardens (17% of the total area), dominated close to the village. The size of rubber trees declined with distance, reflecting the recent establishment of rubber gardens far from the village. Fruit gardens accounted for only 4% of the area. From interviews in Kembera and three other villages, we estimated rates of primary forest clearing and documented changes in land-use. Most rice fields were cleared from secondary forest fallows. However, 17% of dry-rice fields and 9% of wet-rice fields were cleared from primary forest in 1990, resulting in the loss of approximately 12 ha of primary forest per village. Almost all dry-rice fields cleared from primary forest were immediately converted to rubber gardens, as were 39% of all dry-rice fields cleared from fallows. The rate of primary forest conversion increased dramatically from 1990 to 1995, due not to soil degradation or population growth but rather to changes in the socio-economic and political environment faced by shifting cultivators. Although the loss of primary forest is appreciable under shifting cultivation, the impact is less than that of the major alternative land-uses in the region: timber extraction and oil palm plantations.://000079303300001 &ISI Document Delivery No.: 179BH Times Cited: 23 Cited Reference Count: 44 Cited References: *FAO, 1993, FOR RES ASS 1990 TRO ABELL TM, 1988, J WORLD FOREST RESOU, V3, P111 ANDERSON AB, 1990, ALTERNATIVES DEFORES CANNON CH, 1994, FOREST ECOL MANAG, V67, P49 CHATELAIN C, 1996, BIODIVERS CONSERV, V5, P37 COLLINS M, 1991, CONSERVATION ATLAS T CURRAN LM, 1992, APPL RES RECOMMENDAT DENSLOW JS, 1988, PEOPLE TROPICAL RAIN DIRZO R, 1992, CONSERV BIOL, V6, P84 DOVE MR, 1985, BORNEO RES B, V17, P95 DOVE MR, 1985, SWIDDEN AGR INDONESI DOVE MR, 1993, ECON BOT, V47, P136 FEENY D, 1984, AGR EXPANSION FOREST FREEMAN DJ, 1955, REPORT IBAN SARAWAK GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GRAINGER A, 1984, J WORLD FOREST RESOU, V1, P3 HOUGHTON RA, 1994, BIOSCIENCE, V44, P305 INOUE M, 1990, AGROFOREST SYST, V12, P269 JESSUP T, 1981, BORNEO RES B, V13, P16 KARTAWINATA K, 1984, ENVIRONMENTALIST, V4, P87 KLEINMAN PJA, 1996, AGRON J, V88, P122 KUMMER DM, 1992, AGROFOREST SYST, V18, P31 LAWRENCE D, 1996, TROPICAL BIODIVERSIT, V3, P297 LAWRENCE DC, 1995, CONSERV BIOL, V9, P76 LAWRENCE DC, 1996, AGROFOREST SYST, V34, P83 MACKIE C, 1987, P C IMP MAN ACT TROP, P465 MARY F, 1987, AGROFOREST SYST, V5, P27 MICHON G, 1991, DAMAR GARDENS EXISTI MORAN EF, 1994, BIOSCIENCE, V44, P329 MYERS N, 1993, ENVIRON CONSERV, V20, P9 NYE PH, 1960, SOIL SHIFTING CULTIV OJIMA DS, 1994, BIOSCIENCE, V44, P300 OSUNADE MAA, 1991, J ECOLOGY ENV SCI, V17, P201 PADOCH C, 1985, HUM ECOL, V13, P271 PADOCH C, 1993, PERSPECTIVES BIODIVE, P167 POFFENBERGER M, 1990, KEEPERS FOREST POORE MED, 1968, J ECOL, V56, P143 REPETTO R, 1988, FOREST TREES GOVT PO RISWAN S, 1995, VEGETATIO, V121, P41 SAINTPIERRE C, 1991, AGROFOREST SYST, V133, P159 SALAFSKY N, 1994, AGROFOREST SYST, V28, P237 SKOLE D, 1993, SCIENCE, V260, P1905 SKOLE DL, 1994, BIOSCIENCE, V44, P314 YAVITT JB, 1995, J TROP ECOL, V11, P391 0921-2973 Landsc. Ecol.ISI:000079303300001bDuke Univ, Dept Bot, Durham, NC 27708 USA. Lawrence, D, Duke Univ, Dept Bot, Durham, NC 27708 USA.Englishm|? !Lazrak, E. Mari, J. F. Benoit, M.2010JLandscape regularity modelling for environmental challenges in agriculture169-183Landscape Ecology252MIn agricultural landscapes, methods to identify and describe meaningful landscape patterns play an important role to understand the interaction between landscape organization and ecological processes. We propose an innovative stochastic modelling method of agricultural landscape organization where the temporal regularities in land-use are first identified through recognized Land-Use Successions before locating these successions in landscapes. These time-space regularities within landscapes are extracted using a new data mining method based on Hidden Markov Models. We applied this methodological proposal to the Niort Plain (West of France). We built a temporo-spatial analysis for this case study through spatially explicit analysis of Land-Use Succession dynamics. Implications and perspectives of such an approach, which links together the temporal and the spatial dimensions of the agricultural organization, are discussed by assessing the relationship between the agricultural landscape patterns defined using this approach and ecological data through an illustrative example of bird nests.!://WOS:000274437100002Times Cited: 0 0921-2973WOS:00027443710000210.1007/s10980-009-9399-8|? 1Le Mitouard, E. Bellido, A. Guiller, A. Madec, L.2010Spatial structure of shell polychromatism in Cepaea hortensis in relation to a gradient of landscape fragmentation in Western France123-134Landscape Ecology251Because of their highly polymorphic shell patterns, Cepaea land snails have been the subject of numerous studies in ecological genetics. Here, we investigated the spatial structure of polychromatism in Cepaea hortensis in agricultural landscapes with zones from low to high hedgerow densities. Our main purpose was to search for a relationship between landscape composition and spatial structuring of chromatism. Despite significant spatial heterogeneity in the three landscapes sampled, only the high hedgerow density landscape showed a significant spatial structuring of shell polymorphism. In order to understand this result, an investigation of daily movement patterns in relation to habitat form was carried out on a mark-release experiment under semi-artificial conditions. This experiment revealed a strong influence of a linear corridor on snail dispersal. In the field, spatial heterogeneity of shell polymorphism, related to the effects of genetic drift, was shaped by restricted dispersal in narrow corridors. In the more enclosed one, i.e. where hedgerow density was the highest, the significant spatial structure we detected involved a balance between local genetic drift and environmentally mediated gene flow. This isolation-by-distance pattern resulted from direct gene exchange through fields between neighbouring populations. When applying landscape distances based on hedgerow length, no significant spatial correlation with polychromatism was found. In the more fragmented sites, random genetic drift seemed to be the prevailing force and, at the scale of the whole sampled area, selective pressures potentially interfere with these genetic drift-dispersal events.!://WOS:000273479100010Times Cited: 0 0921-2973WOS:00027347910001010.1007/s10980-009-9406-0 ? mLeblond, Mathieu Frair, Jacqueline Fortin, Daniel Dussault, Christian Ouellet, Jean-Pierre Courtois, Réhaume2011Assessing the influence of resource covariates at multiple spatial scales: an application to forest-dwelling caribou faced with intensive human activity 1433-1446Landscape Ecology2610Springer NetherlandsEarth and Environmental Science,Efforts in isolating the relative effects of resources and disturbances on animal-distribution patterns remain hindered by the difficulty of accounting for multiple scales of resource selection by animals with seasonally dynamic drivers. We developed multi-scale, seasonal models to explore how local resource selection by the threatened forest-dwelling woodland caribou ( Rangifer tarandus caribou ) was influenced by both broad-scale landscape context and local resource heterogeneity in the intensively managed region of Charlevoix, Québec, Canada, located on the southern border of the North American caribou range. We estimated resource selection functions using 23 GPS-collared caribou monitored from 2004 to 2006 and landscape data on vegetation classes, terrain conditions, and roads. We found evidence of thresholds in road “proximity” effects (up to 1.25 km), which underscores the importance of including landscape context variables in addition to locally measured variables, and of fitting seasonal-specific models given temporal variation in the magnitude of selection and optimal scale of measurement. Open lichen woodlands were an important cover type for caribou during winter and spring, whereas deciduous forests, wetlands, and even young disturbed stands became important during calving and summer. Caribou consistently avoided roads and rugged terrain conditions at both local and landscape levels. Landscape context fundamentally constrains the choices available to animals, and we showed that failing to consider landscape context, or arbitrarily choosing an inappropriate scale for measuring covariates, may provide biased inferences with respect to habitat selection patterns. Effective habitat management for rare or declining species should carefully consider the hierarchical nature of habitat selection.+http://dx.doi.org/10.1007/s10980-011-9647-6 0921-297310.1007/s10980-011-9647-6U? ;Lechner, Alex Langford, William Bekessy, Sarah Jones, Simon2012MAre landscape ecologists addressing uncertainty in their remote sensing data? 1249-1261Landscape Ecology279Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9791-7 0921-297310.1007/s10980-012-9791-7_?o7&Leduc, A. Y.T. Prairie Y. Bergeron1994MFractal dimension estimates of a fragmented landscape: Sources of variability279-286Landscape Ecology94qsemivariogram, anisotropy, grain size effect, scale effect, self-similarity, characteristic scales, geostatistics|7m %Leduc, A. Prairie, Y. T. Bergeron, Y.1994NFractal Dimension Estimates of a Fragmented Landscape - Sources of Variability279-286Landscape Ecology947semivariogram anisotropy grain size effect scale effectDecAlthough often seen as a scale-independent measure, we show that the fractal dimension of the forest cover of the Cazaville Region changes with spatial scale. Sources of variability in the estimation of fractal dimensions are multiple. First, the measured phenomenon does not always show the properties of a pure fractal for all scales, but rather exhibits local self-similarity within certain scale ranges. Moreover, some sampling components such as area of sampling unit, the use of a transect in the estimation of the variability of a plane, the location, and the orientation of a transect all affect, to different degrees, the estimation of the fractal dimension. This paper assesses the relative importance of these components in the estimation of the fractal dimension of the spatial distribution of woodlots in a fragmented landscape. Results show that different sources of variability should be considered when comparing fractal dimensions from different studies or regions.://A1994PX89500005-Px895 Times Cited:24 Cited References Count:0 0921-2973ISI:A1994PX89500005]Leduc, A Univ Quebec,Rech Ecol Forestiere Grp,Cp 8888,Succursale a,Montreal,Pq H3c 3p8,CanadaEnglishpڽ7-Lee, Ying-Chieh Yeh, Chia-Tsung Huang, Shu-Li2013-Energy hierarchy and landscape sustainability 1151-1159Landscape Ecology286Springer Netherlands=Emergy Energy hierarchy Landscape sustainability Transformity 2013/07/01+http://dx.doi.org/10.1007/s10980-012-9706-7 0921-2973Landscape Ecol10.1007/s10980-012-9706-7English ?7_Lawrence A. Leitner Christopher P. Dunn Glenn R. Guntenspergen Fo, rest Stearns David M. Sharpe1991oEffects of site, landscape features, and fire regime on vegetation patterns in presettlement southern Wisconsin203-217Landscape Ecology54Jdisturbance, fire, heterogeneity, landscape pattern, topography, WisconsinThe presettlement tree cover (1831 -33) of 3 townships in a southern Wisconsin landscape was analyzed using original survey records. Four forest types were identified: closed forest, open forest, savanna, and prairie. Comparisons of vegetation types and landscape pattern were made between the east and west sides of the Pecatonica River, which bisects the landscape and could have acted as a natural fire barrier. West of the river, presettlement tree species richness and diversity were lower and trees were smaller in diameter and less dense than to the east. The major vegetation types to the west were prairie (42(rlo of landscape) and savanna (400'10), both fire-susceptible types. Prairie was more common on gentle slopes than on other landforms. To the east, the landscape was 70% forested (closed plus open forest). Here, prairie was more frequent on steep dry sites. These vegetation differences, including the contrasting landscape placement of prairie, are attributed to distinct site characteristics and to disturbance (fire) regimes, with the west likely having more frequent fires. In terms of the four vegetation types, the east landscape was more homogeneous, being dominated by closed forest (50%). West of the Pecatonica River, the landscape was more heterogeneous because of the high proportion of both prairie and savanna; however, in terms of flammability of vegetation, the west was essentially homogeneous (82% prairie plus savanna).q~?W.Leonard, R. Legendre, P. Jean, M. Bouchard, A.2008zUsing the landscape morphometric context to resolve spatial patterns of submerged macrophyte communities in a fluvial lake91-105Landscape Ecology231 This study investigates the spatial heterogeneity of macrophyte communities in a fluvio-lacustrine landscape. We analysed the importance of the geomorphological point/bay pattern in structuring aquatic plant assemblages inside a 20-km-long littoral segment of a large fluvial lake. The abundance of 21 macrophyte species was surveyed in 232 quadrats along 24 transects perpendicular to the lakeshore. Two contrasting plant communities were identified, corresponding to the bay and point morphology of the study zone: a bay community characterized by Chara sp. and a point community dominated by Butomus umbellatus f. vallisneriifolius, Vallisneria americana, Potamogeton richardsonii and Myriophyllum sp. We subsequently investigated the spatial patterns within the bay and point communities. From a dataset containing local environmental variables, landscape morphometric descriptors, and spatial geographical positions of the sampling sites, variation partitioning of the species abundance table showed that more than two-thirds of the explained variation was spatially structured. Around half of the spatially structured variation was due to the spatially structured environment. We identified important broad-scale patterns in the vegetation correlated to the local environmental variables, mainly depth and sediment richness. The remaining half of the spatially structured variation in the aquatic plant communities was explained by the landscape morphometric context; shoreline complexity of the bay or point, relative width, duration of wind exposure, and fetch were the landscape descriptors explaining most of this variation. Our results indicate that the landscape morphometric context can resolve as much spatial patterning as environmental variables and should be considered when studying a large lake ecosystem."://WOS:000251796100010 Times Cited: 0WOS:00025179610001010.1007/s10980-007-9168-5>}?NLepczyk, Christopher A. Hammer, Roger B. Stewart, Susan I. Radeloff, Volker C.2007\Spatiotemporal dynamics of housing growth hotspots in the North Central US from 1940 to 2000939-952Landscape Ecology226Jul&://BIOSIS:PREV200700463293 0921-2973BIOSIS:PREV200700463293 I|?? !Levick, Shaun R. Rogers, Kevin H.2011;Context-dependent vegetation dynamics in an African savanna515-528Landscape Ecology264Apr2Understanding the spatio-temporal dynamics of ecological systems is fundamental to their successful management and conservation. Much research and debate has focused on identifying underlying drivers of vegetation change in savannas, yet few have considered the influence of spatial context and heterogeneity. Our goal was to develop deeper understanding of woody vegetation spatio-temporal dynamics through spatially explicit utilization of historical aerial photography and airborne LiDAR (light detection and ranging). We first assessed temporal change in woody vegetation cover through object-based image analysis of an aerial photography record that spanned 59 years from 1942 to 2001. Secondly, we tested the spatial relationships between environmental variables and patterns of woody structure and dynamics at broad (100 ha), medium (10 ha) and fine-scales (1 ha) through canonical correspondence analysis (CCA). Finally, we used LiDAR derived vegetation heights to explore current woody vegetation structure in the context of historical patterns of change. Total percentage woody cover was stable over time, but woody dynamics were highly variable at smaller scales and displayed distinct spatial trends across the landscape. Losses of woody cover on the diverse alluvial substrates were countered by increases of cover on the hillslopes. Analysis of current woody structure in the context of historical change revealed that the increases took place in the form of shrub encroachment and not the replacement of tall trees. We infer that mammalian herbivory contributed substantially to the losses on lowland alluvial soils, whilst shrub encroachment on the upland hillslopes likely stemmed from changes in fire regime and climate. Deeper reflection on spatial variability is needed in the debate around drivers of change in savanna systems, as spatial patterns of change revealed that different drivers underlie vegetation dynamics in different landscape contexts. Spatial heterogeneity needs explicit consideration in the exploration of pattern-process relationships in ecological systems.!://WOS:000288807300006Times Cited: 0 0921-2973WOS:00028880730000610.1007/s10980-011-9578-2,}?CLewis, David Bruce Grimm, Nancy B. Harms, Tamara K. Schade, John D.2007USubsystems, flowpaths, and the spatial variability of nitrogen in a fluvial ecosystem911-924Landscape Ecology226Jul&://BIOSIS:PREV200700463291 0921-2973BIOSIS:PREV200700463291,<7 Leyk, S. Zimmermann, N. E.2007OImproving land change detection based on uncertain survey maps using fuzzy sets257-272Landscape Ecology222predictive uncertainty modelling; fuzzy sets; land cover change analysis; classification bias; correction of survey maps; area estimation ACCURACY ASSESSMENT; THEMATIC MAPS; CLASSIFICATION; MODELSArticleFebIn this paper we present a method for correcting inherent classification bias in historical survey maps with which subsequent land cover change analysis can be improved. We linked generalized linear modelling techniques for spatial uncertainty prediction to fuzzy set based operations. The predicted uncertainty information was used to compute fuzzy memberships of forest and non-forest classes at each location. These memberships were used to reclassify the original map based on decision rules, which take into consideration the differences in identification likelihood during the historical mapping. Since the forest area was underestimated in the original mapping, the process allows to correct this bias by favouring forest, especially where uncertainty was high. The analyses were performed in a cross-wise manner between two study areas in order to examine whether the bias correction algorithm would still hold in an independent test area. Our approach resulted in a significant improvement of the original map as indicated by an increase of the Normalized Mutual Information from 0.26 and 0.36 to 0.38 and 0.45 for the cross-wise test against reference maps in Pontresina and St. Moritz, respectively. Consequently subsequent land cover change assessments could be considerably improved by reducing the deviations from a reference change by almost 50 percent. We concluded that the use of logistic regression techniques for uncertainty modelling based on topographic gradients and fuzzy set operations are useful tools for predictively reducing uncertainty in maps and land cover change models. The procedure allows to get more reliable area estimates of crisp classes and it improves the computation of the fuzzy areas of classes. The approach has limitations when the original map shows high initial accuracy.://000243823900009 IISI Document Delivery No.: 130UG Times Cited: 0 Cited Reference Count: 37 Cited References: *INS, 2001, S PLUS 6 WIND US GUI AHLQVIST O, 2003, INT J GEOGR INF SCI, V17, P223 ANDREFOUET S, 2000, IEEE T GEOSCI REMO 1, V38, P257 BAKER WL, 1989, LANDSCAPE ECOL, V2, P111 BEZDEK JC, 1981, PATTERN RECOGNITION BINAGHI E, 1999, PATTERN RECOGN LETT, V20, P935 BOLLIGER J, 2005, ECOGRAPHY, V28, P141 BROWN DG, 1998, INT J GEOGR INF SCI, V12, P105 BURROUGH P, 1998, PRINCIPLES GEOGRAPHI BURROUGH PA, 1989, J SOIL SCI, V40, P477 CHENG T, 2001, J GEOGRAPH INFORM SC, V15, P27 COHEN J, 1960, EDUC PSYCHOL MEAS, V20, P37 COPPIN P, 2004, INT J REMOTE SENS, V25, P1565 DUBOIS D, 2000, FUNDAMENTALS FUZZY S FISHER P, 2000, FUZZY SET SYST, V113, P7 FONTE CC, 2004, INT J GEOGR INF SCI, V18, P127 FOODY GM, 1996, INT J REMOTE SENS, V17, P1317 FORBES AD, 1995, J CLIN MONITOR, V11, P189 GOPAL S, 1994, PHOTOGRAMM ENG REM S, V60, P181 GUISAN A, 2000, ECOL MODEL, V135, P147 JAGER G, 2000, IEEE T GEOSCI REMOTE, V38, P1462 KIENAST F, 1993, LANDSCAPE ECOL, V8, P103 KLIR GJ, 1999, UNCERTAINITY BASED I KRISHNAPURAM R, 1993, IEEE T FUZZY SYST, V1, P98 LEWIS HG, 2001, INT J REMOTE SENS, V22, P3223 LEYK S, 2004, LECT NOTES COMPUT SC, V3234, P191 LEYK S, 2005, T GIS, V9, P291 LU D, 2004, INT J REMOTE SENS, V25, P2365 MATSAKIS P, 2000, REMOTE SENS ENVIRON, V74, P516 PLEWE B, 2002, T GIS, V6, P431 POWER C, 2001, INT J GEOGR INF SCI, V15, P77 ROBINSON VB, 1988, COMPUT ENVIRON URBAN, V12, P89 ROBINSON VB, 2003, T GIS, V7, P3 RUSPINI EH, 1969, INFORM CONTR, V15, P22 STEELE BM, 1998, REMOTE SENS ENVIRON, V66, P192 WOODCOCK CE, 2000, INT J GEOGR INF SCI, V14, P153 ZADEH LA, 1965, INFORM CONTR, V8, P338 0921-2973 Landsc. Ecol.ISI:000243823900009Univ Zurich, Dept Geog, CH-8057 Zurich, Switzerland. Swiss Fed Res Inst, Land Use Dynam, WSL, CH-8903 Birmensdorf, Switzerland. Leyk, S, Univ Zurich, Dept Geog, Winterhurerstr 190, CH-8057 Zurich, Switzerland. leyks@bluewin.chEnglish <7f Li, A. Wu, J. G. Huang, J. H.2012Distinguishing between human-induced and climate-driven vegetation changes: a critical application of RESTREND in inner Mongolia969-982Landscape Ecology277land use and land cover change arid landscape dynamics ndvi residuals trend (restrend) analysis land use policy grassland vegetation inner mongolia proxy global assessment landscape ecology land degradation steppe degradation use efficiency china desertification grassland sahel scaleAugChanges in the spatiotemporal pattern of vegetation alter the structure and function of landscapes, consequently affecting biodiversity and ecological processes. Distinguishing human-induced vegetation changes from those driven by environmental variations is critically important for ecological understanding and management of landscapes. The main objectives of this study were to detect human-induced vegetation changes and evaluate the impacts of land use policies in the Xilingol grassland region of Inner Mongolia, using the NDVI-based residual trend (RESTREND) method. Our results show that human activity (livestock grazing) was the primary driver for the observed vegetation changes during the period of 1981-2006. Specifically, vegetation became increasingly degraded from the early 1980s when the land use policy-the Household Production Responsibility System-led to soaring stocking rates for about two decades. Since 2000, new institutional arrangements for grassland restoration and conservation helped curb and even reverse the increasing trend in stocking rates, resulting in large-scale vegetation improvements in the region. These results suggest that most of the degraded grasslands in the Xilingol region can recover through ecologically sound land use policies or institutional arrangements that keep stocking rates under control. Our study has also demonstrated that the RESTREND method is a useful tool to help identify human-induced vegetation changes in arid and semiarid landscapes where plant cover and production are highly coupled with precipitation. To effectively use the method, however, one needs to carefully deal with the problems of heterogeneity and scale in space and time, both of which may lead to erroneous results and misleading interpretations.://000306068200004-969PP Times Cited:0 Cited References Count:56 0921-2973Landscape EcolISI:000306068200004PHuang, JH Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China Chinese Acad Sci, Grad Univ, Beijing 100049, Peoples R China Arizona State Univ, Sch Life Sci, Tempe, AZ 85287 USA Arizona State Univ, Global Inst Sustainabil, Tempe, AZ 85287 USA Inner Mongolia Univ, Sino US Ctr Conservat Energy & Sustainabil Sci, Hohhot 010021, Peoples R ChinaDOI 10.1007/s10980-012-9751-2English <7E"Li, C. Corns, I. G. W. Yang, R. C.1999OFire frequency and size distribution under natural conditions: a new hypothesis533-542Landscape Ecology146fire frequency fire model fire size fire size distribution natural fire regime FOREST TEMPORAL DYNAMICS DISTURBANCE LANDSCAPE MODELArticleDecDecisions for sustainable forest resources management require a better understanding of forest dynamics as a result of disturbances. Forest fires are one of the major types of natural disturbances in many forest landscapes. Existing fire regime models can be used in evaluating the influence of a fire regime on landscape dynamics, but these models require users to define fire frequency and its size distribution as separate characteristics of a fire regime before running the models. By using a long-term spatial fire regime model, we tested the hypothesis that fire frequency and its size distribution are correlated with each other under natural conditions. Our study demonstrates that the hypothesis can not be rejected and the correlation between fire frequency and its size distribution was robust. Thus, the natural fire size distribution can be estimated when the fire return interval for a given forest landscape is known, if the natural fire size distribution can be approximated by a negative exponential probability distribution. This result simplifies the description of a fire regime from two parameters to one in some existing fire regime models. This simplification is limited to a 'let burn' scenario.://000082563500002 ISI Document Delivery No.: 235VP Times Cited: 11 Cited Reference Count: 30 Cited References: *FOR CAN FIR DANG, 1992, STX3 FOR CAN SCI SUS BAKER WL, 1989, ECOLOGY, V70, P23 BAKER WL, 1991, ECOL MODEL, V56, P109 BAKER WL, 1992, ECOLOGY, V73, P1879 BAKER WL, 1995, LANDSCAPE ECOL, V10, P143 BOYCHUK D, 1997, ECOL MODEL, V95, P145 CUMMING SG, 1995, EXPT HABITAT FRAGMEN GRANSTROM A, 1993, J VEG SCI, V4, P737 GRUBB PJ, 1986, RESILIENCE MEDITERRA, P21 HEINSELMAN ML, 1973, QUATERNARY RES, V3, P329 HIRSCH KG, 1996, 7 NAT RES CAN CAN FO HOLLING CS, 1996, GLOBAL CHANGE TERRES, P346 JOHNSON EA, 1992, FIRE VEGETATION DYNA KEANE RE, 1996, INTRP484 USDA FOR SE LI C, 1995, WATER AIR SOIL POLL, V82, P429 LI C, 1996, ECOL MODEL, V87, P143 LI C, 1997, ECOL MODEL, V99, P137 LI C, 1999, IN PRESS ECOLOGY MAN MALANSON GP, 1987, ROLE FIRE ECOLOGICAL, P49 MERRILL DF, 1987, GLOSSARY FOREST FIRE PICKETT STA, 1985, ECOLOGY NATURAL DIST, P371 PRENTICE IC, 1993, ECOL MODEL, V65, P51 RENKIN RA, 1992, CAN J FOREST RES, V22, P37 ROSS SM, 1972, INTRO PROBABILITY MO ROTHERMEL RC, 1972, INT115 USDA FOR SERV TURNER MG, 1994, LANDSCAPE ECOL, V9, P59 TURNER MG, 1994, NAT AREA J, V14, P3 VANWAGNER CE, 1978, CANADIAN J FOREST RE, V8, P220 VANWAGTENDONK JW, 1986, P NAT WILD RES C CUR, P2 VENABLES WN, 1994, MODERN APPL STAT S P 0921-2973 Landsc. Ecol.ISI:000082563500002Canadian Forestry Serv, No Forestry Ctr, Edmonton, AB T6H 3S5, Canada. Li, C, Canadian Forestry Serv, No Forestry Ctr, 5320-122 St, Edmonton, AB T6H 3S5, Canada.English,ڽ7B"Li, Cheng Li, Junxiang Wu, Jianguo2013zQuantifying the speed, growth modes, and landscape pattern changes of urbanization: a hierarchical patch dynamics approach 1875-1888Landscape Ecology2810Springer NetherlandsUrbanization Urban growth modes Landscape pattern analysis Hierarchical patch dynamics Diffusion-coalescence hypothesis Landscape structural homogenization Yangtze River Delta, China 2013/12/01+http://dx.doi.org/10.1007/s10980-013-9933-6 0921-2973Landscape Ecol10.1007/s10980-013-9933-6English?q2Li, H. Franklin, J. F. Swanson, F. J. Spies, T. A.1993EDeveloping alternative forest cutting patterns: A simulation approach63-75Landscape Ecology81Ewildlife habitat, forest management, fragmentation, simulation, index<|7 2Li, H. Franklin, J. F. Swanson, F. J. Spies, T. A.1993FDeveloping Alternative Forest Cutting Patterns - a Simulation Approach63-75Landscape Ecology81Slandscape ecology simulation index wildlife habitat forest management fragmentationMarThis study examines effects of different forest cutting patterns on habitat fragmentation in managed forest landscapes. We use computer simulation to conduct experiments in which we examine effects of different cutting patterns, cutting-unit size, and special constraints (e.g., a forest reserve, a stream system, or a road system) on landscape patterns. Fragmentation indices are used to quantify structural changes over the cutting cycle and among different treatments of the experiments. Degree of fragmentation varies greatly among the five cutting patterns used; aggregation of cutting units results in low degree and gradual change of fragmentation. Cutting patterns with larger cutting units and additional landscape constraints also lead to lower degree of fragmentation. Moreover, differences in fragmentation among the treatments are not observed until 30% or 50% of the landscape is cut.://A1993KW95800005-Kw958 Times Cited:97 Cited References Count:0 0921-2973ISI:A1993KW95800005(Li, H Duke Univ,Dept Bot,Durham,Nc 27706English@|7 Li, H. B. Reynolds, J. F.1993@A New Contagion Index to Quantify Spatial Patterns of Landscapes155-162Landscape Ecology83Ocontagion index spatial pattern probability information index landscape ecologySepA contagion index was proposed by O'Neill et al. (1988) to quantify spatial patterns of landscapes. However, this index is insensitive to changes in spatial pattern. We present a new contagion index that corrects an error in the mathematical formulation of the original contagion index. The error is identified mathematically. The contagion indices (both original and new) are then evaluated against simulated landscapes.://A1993MB34000002.Mb340 Times Cited:121 Cited References Count:0 0921-2973ISI:A1993MB34000002)Li, Hb Duke Univ,Dept Bot,Durham,Nc 27706English<7Li, H. B. Wu, J. G.2004#Use and misuse of landscape indices389-399Landscape Ecology194conceptual flaws; GIS and map data; landscape pattern analysis; pattern and process; scale PATTERN METRICS; SPATIAL HETEROGENEITY; CHANGING SCALE; ECOLOGY; PSEUDOREPLICATION; SENSITIVITY; HABITATArticle:Landscape ecology has generated much excitement in the past two decades. One reason was that it brought spatial analysis and modeling to the forefront of ecological research. However, high expectations for landscape analysis to improve our understanding and prediction of ecological processes have largely been unfulfilled. We identified three kinds of critical issues: conceptual flaws in landscape pattern analysis, inherent limitations of landscape indices, and improper use of pattern indices. For example, many landscape analyses treat quantitative description of spatial pattern as an end itself and fail to explore relationships between pattern and process. Landscape indices and map data are sometimes used without testing their ecological relevance, which may not only confound interpretation of results, but also lead to meaningless results. In addition, correlation analysis with indices is impeded by the lack of data because of difficulties in large-scale experimentation and by complicated behavior of indices because of their varying responses to changes in scale and spatial pattern. These problems represent significant challenges to landscape pattern analysis, especially in terms of relating pattern to process. In this perspective paper, we examine the underlying problems of these challenges and offer some solutions.://000221879000004 ISI Document Delivery No.: 827DM Times Cited: 39 Cited Reference Count: 55 Cited References: ALLEN RFH, 1984, RM110 USDA FOR SERV BIAN L, 1999, PHOTOGRAMM ENG REM S, V65, P73 BRANDT J, 1998, KEY CONCEPTS LANDSCA, P421 CALE WG, 1989, BIOSCIENCE, V39, P600 CARPENTER SR, 1992, ECOLOGY, V73, P453 CARPENTER SR, 1996, ECOLOGY, V77, P453 DALE MRT, 1999, SPATIAL PATTERN ANAL FLATHER CH, 1996, ECOLOGY, V77, P28 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HAINESYOUNG R, 1996, PROG PHYS GEOG, V20, P418 HAMEL PB, 1992, LAND MANAGERS GUIDE HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HARGROVE WW, 1992, LANDSCAPE ECOL, V6, P251 HARRIS LD, 2000, LANDSCAPE ECOLOGY TO, P91 HURLBERT SH, 1971, ECOLOGY, V52, P577 HURLBERT SH, 1984, ECOL MONOGR, V54, P187 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 JUSTICE CO, 1989, INT J REMOTE SENS, V10, P1539 KRUMMEL JR, 1987, OIKOS, V48, P321 LEVIN SA, 1992, ECOLOGY, V73, P1943 LI H, 1995, OIKOS, V73, P280 LI HB, 1993, LANDSCAPE ECOL, V8, P155 LI HB, 1994, ECOLOGY, V75, P2446 LI HB, 2000, COMPUT ELECTRON AGR, V27, P263 LOVEJOY S, 1982, SCIENCE, V216, P185 LUDWIG JA, 2000, ECOSYSTEMS, V3, P84 MILNE BT, 1991, QUANTITATIVE METHODS, P199 NAVEH Z, 1984, LANDSCAPE ECOLOGY TH OKSANEN L, 2001, OIKOS, V94, P27 ONEILL RV, 1986, HIERARCHICAL CONCEPT ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 ONEILL RV, 1999, ECOSYST HEALTH, V5, P225 OPENSHAW S, 1984, MODIFIABLE AREAL UNI PICKETT STA, 1994, ECOLOGICAL UNDERSTAN PICKETT STA, 1995, SCIENCE, V269, P331 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 RISSER PG, 1984, ILLINOIS NATURAL HIS, V2 SAURA S, 2001, PHOTOGRAMM ENG REM S, V67, P1027 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 TURNER MG, 1991, QUANTITATIVE METHODS TURNER MG, 2001, LANDSCAPE ECOLOGY TH URBAN DL, 1987, BIOSCIENCE, V37, P119 WICKHAM JD, 1995, INT J REMOTE SENS, V16, P3585 WICKHAM JD, 1997, PHOTOGRAMM ENG REM S, V63, P397 WIENS JA, 1989, FUNCT ECOL, V3, P385 WIENS JA, 1993, OIKOS, V66, P369 WU J, 1999, CANADIAN J REMOTE SE, V25, P367 WU J, 2000, LANDSCAPE ECOLOGY PA WU JG, 1995, Q REV BIOL, V70, P439 WU JG, 2002, LANDSCAPE ECOL, V17, P355 WU JG, 2002, LANDSCAPE ECOL, V17, P761 WU JG, 2004, LANDSCAPE ECOL, V19, P125 0921-2973 Landsc. Ecol.ISI:000221879000004US Forest Serv, USDA, Ctr Forested Wetlands Res, Charleston, SC 29414 USA. Arizona State Univ, Sch Life Sci, Fac Ecol Evolut & Environm Sci, Tempe, AZ 85287 USA. Li, HB, US Forest Serv, USDA, Ctr Forested Wetlands Res, 2730 Savannah Highway, Charleston, SC 29414 USA. hli@fs.fed.usEnglishڽ7(:Li, Junxiang Li, Cheng Zhu, Feige Song, Conghe Wu, Jianguo2013OSpatiotemporal pattern of urbanization in Shanghai, China between 1989 and 2005 1545-1565Landscape Ecology288Springer NetherlandsnLandscape pattern Landscape metrics Gradient analysis Urbanization Thematic resolution Urban growth hypothesis 2013/10/01+http://dx.doi.org/10.1007/s10980-013-9901-1 0921-2973Landscape Ecol10.1007/s10980-013-9901-1English[|? aLi, Taian Shilling, Fraser Thorne, James Li, Fengmin Schott, Heidi Boynton, Ryan Berry, Alison M.2010;Fragmentation of China's landscape by roads and urban areas839-853Landscape Ecology256JulChina's major paved road-ways (national roads, provincial roads, and county roads), railways and urban development are rapidly expanding. A likely consequence of this fast-paced growth is landscape fragmentation and disruption of ecological flows. In order to provide ecological information to infrastructure planners and environmental managers for use in landscape conservation, land-division from development must be measured. We used the effective-mesh-size (M(eff)) method to provide the first evaluation of the degree of landscape division in China, caused by paved roads, railways, and urban areas. Using M(eff), we found that fragmentation by major transportation systems and urban areas in China varied widely, from the least-impacted west to the most impacted south and east of China. Almost all eastern provinces and counties, especially areas near big cities, have high levels of fragmentation. Several eastern-Chinese provinces and biogeographic regions have among the most severe landscape fragmentation in the world, while others are comparable to the least-developed areas of Europe and California. Threatened plant hotspots and areas with high mammal species diversity occurred in both highly fragmented and less fragmented areas, though future road development threatens already moderately divided landscapes. To conserve threatened biodiversity and landscapes, we recommend that national and regional planners in China consider existing land division before making decisions about further road development and improvement.!://WOS:000278526000003Times Cited: 0 0921-2973WOS:00027852600000310.1007/s10980-010-9461-6ڽ7 3Li, Xiuzhen Sun, Yongguang Mander, Ülo He, Yanlong2013eEffects of land use intensity on soil nutrient distribution after reclamation in an estuary landscape699-707Landscape Ecology284Springer NetherlandsOReclamation time Land use intensity Soil nutrients distribution Yangtze estuary 2013/04/01+http://dx.doi.org/10.1007/s10980-012-9796-2 0921-2973Landscape Ecol10.1007/s10980-012-9796-2EnglishJ<7(.Li, X. H. Li, D. M. Ma, Z. J. Schneider, D. C.2006QNest site use by crested ibis: dependence of a multifactor model on spatial scale 1207-1216Landscape Ecology218habitat; logistic regression; multiscale analysis; nest site use; Nipponia nippon; geographic information system; reintroduction; scaling; semivariogram LANDSCAPE PATTERN-ANALYSIS; INVENTORY DATA; HABITAT; ECOLOGY; PRODUCTIVITY; BIRDS; PREYArticleNovThe crested ibis (Nipponia nippon), a species at the brink of extinction in 1981, remain restricted to a small (25 km radius) area of temperate forests in central China. To improve the chances of successful reintroduction into new areas we developed a multifactor logistic regression model of habitat association at multiple scales. Using habitat variables, i.e. vegetation, human impact, elevation, and wetland, we compared occupied and unoccupied sites at grain sizes ranging from I to 6400 ha. The goodness-of-fit of the habitat suitability model depended on grain size, with the best fit (most information) at a grain size of 2 ha. Semivariograms showed the habitat variables at control sites have a gradient pattern, yet the crested ibis had their specific habitat preferences, and only selected a narrow range from the available gradient. Our results indicated that spatial scale needs to be considered in developing habitat models for applications such as conservation planning.://000242089300004 ISI Document Delivery No.: 106GP Times Cited: 0 Cited Reference Count: 43 Cited References: *BIRDLIFE INT, 2003, NIPP NIPP IUCN 2003 *SAS I INC, 1999, SAS SYST 8 0 *YANG COUNT AGR DI, 1986, REP AGR DIV YOUNG CO ANAND M, 2001, COMMUNITY ECOL, V2, P161 BEVERS M, 1999, J ANIM ECOL, V68, P976 CAO YH, 1994, CHINESE FOREST, P28 CODY ML, 1981, BIOSCIENCE, V31, P107 HATTEN JR, 2003, J WILDLIFE MANAGE, V67, P774 HULBERT IAR, 2001, J APPL ECOL, V38, P869 JAKOBSSON U, 2004, SCAND J CARING SCI, V18, P437 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 JENKINS JC, 2001, ECOL APPL, V11, P1174 JOHNSON DH, 1980, ECOLOGY, V61, P65 LEVIN SA, 1992, ECOLOGY, V73, P1943 LI XH, 1998, ECOL RES, V13, P323 LI XH, 2001, CHINA BIODIVERS, V9, P352 LI XH, 2002, ACTA ZOOL SINICA, V48, P725 LI XH, 2002, ECOL RES, V17, P565 LIU YZ, 1981, ACTA ZOOL SINICA, V27, P273 MA ZJ, 2001, ZOOL RES, V22, P46 MACKINNON JL, 2001, J ANIM ECOL, V70, P101 MARCEAU DJ, 1999, CANADIAN J REMOTE SE, V25, P347 NI J, 2003, FOREST ECOL MANAG, V176, P485 OPENSHAW S, 1979, STAT APPL SPATIAL SC, P127 QI Y, 1996, LANDSCAPE ECOL, V11, P39 ROBINSON RA, 2004, IBIS S2, V146, P87 ROSE GA, 1990, ECOLOGY, V71, P33 SCHNEIDER DC, 1986, MAR ECOL-PROG SER, V32, P237 SCHNEIDER DC, 1994, QUANTITATIVE ECOLOGY SCHNEIDER DC, 2001, BIOSCIENCE, V51, P545 SHI D, 1991, J NW U, V21, P37 SHI DC, 1991, J NW U S, V21, P15 SHI DC, 1991, J NW U S, V21, P25 SOKAL RR, 1995, BIOMETRY STORE R, 2003, ECOL MODEL, V169, P1 VEIT RR, 1993, J ANIM ECOL, V62, P551 WANG ZY, 1985, J ECOL, P10 WANG ZY, 1993, J HANZHONG NORMAL CO, V11, P59 WANG ZY, 1994, J NW U, V24, P1 WANG ZY, 1995, J HANZHONG NORMAL CO, V13, P54 WU J, 2000, GEOGRAPHIC INFORMATI, V6, P1 WU JG, 2004, LANDSCAPE ECOL, V19, P125 ZHAI TQ, 1991, J HANZHONG NORMAL CO, P72 0921-2973 Landsc. Ecol.ISI:000242089300004Univ New Brunswick, Dept Biol, St John, NB E2L 4L5, Canada. Chinese Acad Sci, Inst Zool, Beijing 100080, Peoples R China. Fudan Univ, Minist Educ, Sch Life Sci, Inst Biodivers Sci,Key Lab Biodivers Sci & Ecol E, Shanghai 200433, Peoples R China. Mem Univ Newfoundland, Ctr Ocean Sci, St John, NF A1C 5S7, Canada. Li, XH, Univ New Brunswick, Dept Biol, St John, NB E2L 4L5, Canada. xinhai.li@gmail.comEnglish {<7g 7Li, X. M. Zhou, W. Q. Ouyang, Z. Y. Xu, W. H. Zheng, H.2012Spatial pattern of greenspace affects land surface temperature: evidence from the heavily urbanized Beijing metropolitan area, China887-898Landscape Ecology276+urban heat island urban greenspace landscape metrics configuration spatial autocorrelation spatial autoregression greenspace planning thermal infrared remote sensing heat-island environment relationships autoregressive models landscape pattern united-states vegetation indianapolis ecology cover airJulOThe urban heat island describes the phenomenon that air/surface temperatures are higher in urban areas compared to their surrounding rural areas. Numerous studies have shown that increased percent cover of greenspace (PLAND) can significantly decrease land surface temperatures (LST). Fewer studies, however, have investigated the effects of configuration of greenspace on LST. This paper aims to fill this gap using Beijing, China as a case study. PLAND along with six configuration metrics were used to measure the composition and configuration of greenspace. The metrics were calculated based on a greenspace map derived from SPOT imagery, and LST data were retrieved from Landsat TM thermal band. Ordinary least squares regression and spatial autoregression were employed to investigate the relationship between LST and spatial pattern of greenspace using the census tract as the analytical unit. The results showed that PLAND was the most important predictor of LST. A 10 % increase in PLAND resulted in approximately a 0.86 A degrees C decrease in LST. Configuration of greenspace also significantly affected LST. Given a fixed amount of greenspace, LST increased significantly with increased patch density. In addition, the variance of LST was largely explained by both composition and configuration of greenspace. The unique variation explained by the composition was relatively small, and was close to that of the configuration. Results from this study can expand our understanding of the relationship between LST and vegetation, and provide insights for improving urban greenspace planning and management.://000305218000008-958DZ Times Cited:0 Cited References Count:56 0921-2973Landscape EcolISI:000305218000008KOuyang, ZY Chinese Acad Sci, State Key Lab Urban & Reg Ecol, Res Ctr Ecoenvironm Sci, Beijing 100085, Peoples R China Chinese Acad Sci, State Key Lab Urban & Reg Ecol, Res Ctr Ecoenvironm Sci, Beijing 100085, Peoples R China Chinese Acad Sci, State Key Lab Urban & Reg Ecol, Res Ctr Ecoenvironm Sci, Beijing 100085, Peoples R ChinaDOI 10.1007/s10980-012-9731-6English?h Liang, Jingjing2012:Mapping large-scale forest dynamics: a geospatial approach 1091-1108Landscape Ecology278Springer NetherlandsBiomedical and Life SciencesDigital map of forest dynamics is emerging as a useful research and management tool. As a key issue to address in developing digital maps of forest dynamics, spatial autocorrelation has been distinguished into “true” and “false” gradients. Previous ecological models are mostly focused on either “true” or “false” gradient, and little has been studied to simultaneously account for both gradients in a single model. The main objective of this study was to incorporate both gradients of spatial autocorrelation in a deterministic geospatial model to provide improved accuracy and reliability in future digital maps of forest dynamics. The mapping was based on two underlying assumptions— unit homogeneity and intrinsic stationarity . This study shows that when the factors causing the spatial non-stationarity have been accounted for, forest states could become a stationary process. A prototype geospatial model was developed for the Alaska boreal forest to study current and future stockings across the region. With areas of the highest basal area increment rate projected to cluster along the major rivers and the lowest near the four major urban developments in Alaska, it was hypothesized that moisture limitation and inappropriate human interference were the main factors affecting the stocking rates. These results could be of unprecedented value, especially for the majority of Alaska boreal region where little information is available.+http://dx.doi.org/10.1007/s10980-012-9767-7 0921-297310.1007/s10980-012-9767-7|7Liang, L. Schwartz, M.2009LLandscape phenology: an integrative approach to seasonal vegetation dynamics465-472Landscape Ecology244landscape phenology temperate mixed forest spatiotemporal analysis scaling land surface phenology functional types global change modisAprNThis brief report addresses the theory and methodology of landscape phenology (LP), along with synopsis of a case study conducted in the northern Wisconsin temperate mixed forest. LP engages questions related to ecosystem phenology, landscape genetics, and vegetation change science across multiple scales, which have rarely been addressed by existing studies. Intensive in situ observations, remote sensing data, and spatiotemporal analysis are employed for understanding patterns and processes within the complexity of seasonal landscape dynamics. A hierarchical upscaling approach is also introduced. Results from the case study suggest that plot-scale phenology lacks spatial autocorrelation and varies individualistically, with genetic heterogeneity overriding small microenvironmental gradients. However, at the landscape level, forest phenology responds coherently to weather fluctuations. The resultant LP index confirms the relative reliability of moderate resolution imaging spectroradiometer (MODIS)-based land surface phenology (LSP). Due to technological advancement in spatial data acquisition and analysis, LP has the ability to connect conventional plant phenology studies back to their intricate ecological context, and provides a new approach to validating coarse-scale monitoring and modeling of LSP and other seasonal ecosystem processes.://000263898100002-414XI Times Cited:0 Cited References Count:22 0921-2973ISI:000263898100002wLiang, L Univ Wisconsin, Dept Geog, POB 413, Milwaukee, WI 53211 USA Univ Wisconsin, Dept Geog, Milwaukee, WI 53211 USADoi 10.1007/S10980-009-9328-XEnglish O<7i &Liang, Y. He, H. S. Yang, J. Wu, Z. W.2012Coupling ecosystem and landscape models to study the effects of plot number and location on prediction of forest landscape change 1031-1044Landscape Ecology277plot number plot location landscape prediction ecosystem and landscape modeling environmental heterogeneity landis changbai mountains northeastern china thematic accuracy species response climate-change mountain area united-states large-scale land-cover simulation reserveAug5A fundamental but unsolved dilemma is that observation and prediction scales are often mismatched. Reconciling this mismatch largely depends on how to design samples on a heterogeneous landscape. In this study, we used a coupled modeling approach to investigate the effects of plot number and location on predicting tree species distribution at the landscape scale. We used an ecosystem process model (LINKAGES) to generate tree species response to the environment (a land type) at the plot scale. To explore realistic parameterization scenarios we used results from LINKAGES simulations on species establishment probabilities under the current and warming climate. This allowed us to design a series of plot number and location scenarios at the landscape scale. Species establishment probabilities for different land types were then used as input for the forest landscape model (LANDIS) that simulated tree species distribution at the landscape scale. To investigate the effects of plot number and location on forest landscape predictions, LANDIS considered effects of climate warming only for the land types in which experimental plots were placed; otherwise inputs for the current climate were used. We then statistically examined the relationships of response variables (species percent area) among these scenarios and the reference scenario in which plots were placed on all land types of the study area. Our results showed that for species highly or moderately sensitive to environmental heterogeneity, increasing plot numbers to cover as many land types as possible is the strategy to accurately predict species distribution at the landscape scale. In contrast, for species insensitive to environmental heterogeneity, plot location was more important than plot number. In this case, placing plots in land types with large area of species distribution is warranted. For some moderately sensitive species that experienced intense disturbance, results were different in different simulation periods. Results from this study may provide insights into sample design for forest landscape predictions.://000306068200008-969PP Times Cited:0 Cited References Count:45 0921-2973Landscape EcolISI:000306068200008fHe, Hs Univ Missouri, Sch Nat Resources, 203M Anheuser Busch Nat Resources Bldg, Columbia, MO 65211 USA Univ Missouri, Sch Nat Resources, 203M Anheuser Busch Nat Resources Bldg, Columbia, MO 65211 USA Univ Missouri, Sch Nat Resources, Columbia, MO 65211 USA Chinese Acad Sci, Inst Appl Ecol, State Key Lab Forest & Soil Ecol, Shenyang 110016, Peoples R ChinaDOI 10.1007/s10980-012-9759-7English'|?Liang, Youjia Liu, Lijun2014MModeling urban growth in the middle basin of the Heihe River, northwest China 1725-1739Landscape Ecology2910DecThe middle basin of Heihe River has witnessed rapid urban growth and excessive agricultural activities during the last two decades, mainly because of its economic development and increasing population pressure. In this study, we aimed to understand the growth dynamics of the region, to forecast its future expansion, and to provide a basis for regional management. We calibrated and validated a SLEUTH model with historical data derived from different sources, which comprised remotely sensed and strategic planning data records from 1995, 2000, 2005, and 2009. Three scenarios based on local regional ecological planning were designed to simulate the spatial pattern of urban growth in different conditions. The first scenario allowed urban expansion without any additional managed growth limitations and the continuation of the actual historical trend. The second scenario was limited based on environmental considerations and managed growth was assumed with moderate protection. The third scenario simulated managed growth with strict protection on wetland reserves and productive agricultural areas in the study area. We consider that the results of these models of growth in the study area obtained under different scenarios are of great potential use to city managers and stakeholders. We also suggest that scale sensitivity and spatial accuracy are among the factors that must be considered in practical applications. We urge future researchers to build on the present study to produce models for similar regions in northwest China.!://WOS:000346920900008Times Cited: 0 0921-2973WOS:00034692090000810.1007/s10980-014-0089-9m<7JLidicker, W. Z.1999`Responses of mammals to habitat edges: a landscape perspective - Preface to this Special Edition331Landscape Ecology144Editorial MaterialAug://000081305700001 HISI Document Delivery No.: 214AP Times Cited: 0 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:000081305700001EnglishN<7KLidicker, W. Z.19992Responses of mammals to habitat edges: an overview333-343Landscape Ecology144boundary effects conservation corridor ecotone fragment landscape matrix metapopulation patch spillover predation POPULATION-DYNAMICS MOVEMENT CORRIDORS LAND-USE VOLE LANDSCAPE CONSERVATION FRAGMENTATION ECOSYSTEMS ABUNDANCE GEOMETRYArticleAugLife generates discontinuites (boundaries) in the distribution of matter and energy. One class of these constitutes the edges between habitat-types; these are fundamental structures in landscape functioning, and hence are of central importance in conservation biology. The symposium on which this series of papers is based focused on the responses of mammals to habitat edges. A diversity of views are represented, and a variety of edge related behaviors illustrated. A survey of general ecology texts dating back to 1933 demonstrates a decline of interest in ecotones and edge effects extending into the 1980's but showing a resurgence of interest in the 1990's. Habitat edges are defined operationally with respect to particular focal species leading to a number of important corollary features. The variety of phenomena subsumed under 'edge effects' is emphasized, and an initial attempt at classification is proposed based primarily on the presence or absence of emergent properties in edge response behaviors (matrix vs. ecotonal effects). This scheme provides for clear null hypotheses needed to distinguish the two types, enlightens mechanistic explanations of edge effects, and encourages predictions about the results of untested management schemes or other novel situations. The use and design of landscape corridors are tied to edge related behaviors. A functional and general definition of corridors is urged, so that their effectiveness can be judged with respect to specified attributes rather than to a general collection of things that might be termed corridors. Linear habitat patches are specifically excluded from the definition. Studies on small mammals have contributed to our understanding of the potential role of corridors in metapopulation dynamics. Fine versus coarse grained perceptions of environment by different species will generate ecotonal edge effects such as spillover predation. In general, the effects on landscape processes of various species operating on different spatial scales seems a fruitful direction for future research.://000081305700002 ISI Document Delivery No.: 214AP Times Cited: 51 Cited Reference Count: 63 Cited References: ANDERSON GS, 1997, LANDSCAPE ECOL, V12, P261 ANDREASSEN HP, 1996, J APPL ECOL, V33, P555 ANDREASSEN HP, 1996, J APPL ECOL, V33, P63 ANDREASSEN HP, 1998, ECOLOGY, V79, P1223 BASCOMPTE J, 1997, LANDSCAPE ECOL, V12, P213 BERG KW, 1995, THESIS U OSLO BUECHNER M, 1987, BIOL CONSERV, V41, P57 CLEMENTS FE, 1904, STUDIES VEGETATION S, V3 CLEMENTS FE, 1997, AM NAT, V31, P968 DAILY GC, 1996, P NATL ACAD SCI USA, V93, P11709 DELATTRE P, 1992, AGR ECOSYST ENVIRON, V39, P153 DELATTRE P, 1996, LANDSCAPE ECOL, V11, P279 DELATTRE P, 1999, LANDSCAPE ECOL, V14 DUELLI P, 1990, BIOL CONSERV, V54, P193 FORMAN RTT, 1986, LANDSCAPE ECOLOGY GIRAUDOUX P, 1997, AGR ECOSYST ENVIRON, V66, P47 GOSZ JR, 1993, ECOL APPL, V3, P369 HANSEN AJ, 1992, ECOLOGICAL STUDIES, V92 HESKE EJ, 1995, J MAMMAL, V76, P562 HOBBS RJ, 1992, TRENDS ECOL EVOL, V7, P389 LAPOLLA VN, 1993, LANDSCAPE ECOL, V8, P25 LAURANCE WF, 1991, CONSERV BIOL, V5, P79 LAURANCE WF, 1995, LANDSCAPE APPROACHES, P46 LAURANCE WF, 1997, SCIENCE, V278, P1117 LAURANCE WF, 1997, TROPICAL FOREST REMN LAURANCE WF, 1997, TROPICAL FOREST REMN, P502 LAURANCE WF, 1997, TROPICAL FOREST REMN, P71 LEOPOLD A, 1933, GAME MANAGEMENT LIDICKER WZ, 1988, OIKOS, V53, P278 LIDICKER WZ, 1992, ANIMAL DISPERSAL SMA, P21 LIDICKER WZ, 1992, LANDSCAPE ECOL, V6, P259 LIDICKER WZ, 1995, LANDSCAPE APPROACHES, P3 LIDICKER WZ, 1996, METAPOPULATIONS WILD, P85 LIDICKER WZ, 1999, LANDSCAPE ECOLOGY SM, P211 LIRO A, 1987, OECOLOGIA, V74, P438 LORENZ GC, 1990, AM MIDL NAT, V123, P348 MCCULLOUGH DR, 1996, METAPOPULATIONS WILD MERRIAM G, 1990, LANDSCAPE ECOL, V4, P123 MERRIAM G, 1991, NATURE CONSERVATION, V2, P133 MILLS LS, 1996, NATL PARKS PROTECTED, P199 MURCIA C, 1995, TRENDS ECOL EVOL, V10, P58 OKSANEN T, 1992, EVOL ECOL, V6, P383 OKSANEN T, 1995, LANDSCAPE APPROACHES, P122 PETERSON JL, 1996, THESIS U CALIFORNIA RISSER PG, 1995, BIOSCIENCE, V45, P318 ROSENBERG DK, 1997, BIOSCIENCE, V47, P677 SAUNDERS DA, 1991, NATURE CONSERVATION, V2 SIMBERLOFF D, 1987, CONSERV BIOL, V1, P63 SIMBERLOFF D, 1992, CONSERV BIOL, V6, P493 SOULE ME, 1991, NATURE CONSERVATION, V2, P3 STAMPS JA, 1987, AM NAT, V129, P533 STAMPS JA, 1987, AM ZOOL, V27, P307 SZACKI J, 1991, LANDSCAPE ECOL, V5, P219 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 WALLACE JB, 1997, SCIENCE, V277, P102 WEGNER J, 1990, BIOL CONSERV, V54, P263 WIENS JA, 1985, OIKOS, V45, P421 WIENS JA, 1996, METAPOPULATIONS WILD, P53 WOLFF JO, 1980, CAN J ZOOL, V58, P1800 WOLFF JO, 1996, CAN J ZOOL, V74, P1826 WOLFF JO, 1997, CONSERV BIOL, V11, P945 YAHNER RH, 1983, J WILDLIFE MANAGE, V47, P74 YAHNER RH, 1988, CONSERV BIOL, V2, P333 0921-2973 Landsc. Ecol.ISI:000081305700002Univ Calif Berkeley, Museum Vertebrate Zool, Berkeley, CA 94720 USA. Lidicker, WZ, Univ Calif Berkeley, Museum Vertebrate Zool, Berkeley, CA 94720 USA.English!?P7W.Z. Lidicker Jr.l J.O. Wolff L.N. Lidicker M.H. Smith1992JUtilization of a habitat mosaic by cotton rats during a population decline259-268Landscape Ecology64Sigmodon hispidus, habitat mosaic, sex-age cohorts, survivorship, density decline, landscape, population dynamics, electromorphsThis study describes the demographic features of a population of Sigmodon hispidus utilizing the habitat mosaic provided by a Carolina Bay on the Atlantic coastal plain of South Carolina. A total of 71 cotton rats were captured 160 times on a 4 ha grid during a winter decline from 25/ha to less that l/ha. Body weights of adults declined until early February and then increased; those of subadults grew very slowly until February followed by a spurt in growth. Weight gain did not differ between survivors and non-survivors for males, but female survivors gained 1.5 g per week more than non-survivors. Female subadults exhibited higher mortality early in the decline and males later. Adult females were randomly distributed across 8 microhabitats, whereas adult males were almost exclusively confined to heavy Rubus cover. Subadult males used wet sites more than any other cohort; subadult females were widely distributed using drier sites most frequently. By the end of the decline, all survivors were localized in Rubus-dominated patches. No statistically significant changes in electromorph genotypes or allele frequencies were detected, but survivors had a higher frequency of the F-allele at the adenylate kinase locus than did non-survivors (42.3% vs. 16.7%). Our findings affirm the importance of a landscape perspective in understanding the population dynamics of cotton rats, and show how a habitat mosaic influences survival differentially among sex-age cohorts.|?'mLieskovsky, Juraj Kenderessy, Pavol Spulerova, Jana Lieskovsky, Tibor Koleda, Peter Kienast, Felix Gimmi, Urs2014Factors affecting the persistence of traditional agricultural landscapes in Slovakia during the collectivization of agriculture867-877Landscape Ecology295MayECollectivization of agriculture (1950s-1970s) was one of the most important periods in landscape development in Slovakia. Traditionally managed agricultural landscapes, that covered more than half of the Slovak territory, were transformed into large-scale fields and only fragments of traditional agricultural landscapes survived. We mapped the remaining traditional agricultural landscapes using aerial photos and historical maps. We then statistically analyzed the various geographical factors and their influence on the transformation process of traditional and collectivized fields, i.e., slope steepness, soil fertility, distance from settlements and isolation from regional capital cities. The comparison was performed using classification tree analysis. We constructed a set of decision rules that explain why fields were managed traditionally or collectivized. Our findings show that traditional agricultural fields were more likely to persist on steep terrain, less fertile soils, and on locations that were closer to the settlements, but more isolated from the regional capital cities. Steepness played the most important role: small-scale fields located on steep areas were not accessible to heavy machinery and therefore, frequently survived the collectivization. We show that the selected geographical factors are good explanatory variables for the collectivization of arable fields and orchards. For vineyards and grasslands, however, the explanatory power of the selected geographical factors is lower, and we suspect that other factors, not depicted in the analysis play an important role.!://WOS:000334689900009Times Cited: 1 0921-2973WOS:00033468990000910.1007/s10980-014-0023-1|?PLima, Leticia S. Coe, Michael T. Soares Filho, Britaldo S. Cuadra, Santiago V. Dias, Livia C. P. Costa, Marcos H. Lima, Leandro S. Rodrigues, Hermann O.2014Feedbacks between deforestation, climate, and hydrology in the Southwestern Amazon: implications for the provision of ecosystem services261-274Landscape Ecology292FebForests, through the regulation of regional water balances, provide a number of ecosystem services, including water for agriculture, hydroelectric power generation, navigation, industry, fisheries, and human consumption. Large-scale deforestation triggers complex non-linear interactions between the atmosphere and biosphere, which may impair such important ecosystem services. This is the case for the Southwestern Amazon, where three important river basins (Jurua, Purus, and Madeira) are undergoing significant land-use changes. Here, we investigate the potential impacts of deforestation throughout the Amazon on the seasonal and annual water balances of these river basins using coupled climatic and hydrologic models under several deforestation scenarios. Simulations without climate response to deforestation show an increase in river discharge proportional to the area deforested in each basin, whereas those with climate response produce progressive reductions in mean annual precipitation over all three basins. In this case, deforestation decreases the mean annual discharge of the Jurua and Purus rivers, but increases that of the Madeira, because the deforestation-induced reduction in evapotranspiration is large enough to increase runoff and thus offset the reduction in precipitation. The effects of Amazon deforestation on river discharge are scale-dependent and vary across and within river basins. Reduction in precipitation due to deforestation is most severe at the end of the dry season. As a result, deforestation increases the dry-season length and the seasonal amplitude of water flow. These effects may aggravate the economic losses from large droughts and floods, such as those experienced in recent years (2005, 2010 and 2009, 2012, respectively).!://WOS:000331935100007Times Cited: 0 0921-2973WOS:00033193510000710.1007/s10980-013-9962-1 |? 3Lin, Yang Han, Guodong Zhao, Mengli Chang, Scott X.2010wSpatial vegetation patterns as early signs of desertification: a case study of a desert steppe in Inner Mongolia, China 1519-1527Landscape Ecology2510Dec-Proper assessment and early detection of land degradation and desertification is extremely important in arid and semi-arid ecosystems. Recent research has proposed to use the characteristics of spatial vegetation patterns, such as parameters derived from power-law modeling of vegetation patches, for detecting the early signs of desertification. However, contradictory results have been reported regarding the suitability of those proposed indicators. We used an experiment with multiple grazing intensities as an analog of a desertification gradient and evaluated the performance of two predictors of desertification: percent plant cover and a transition from a patch-area distribution characterized by a power law to another portrayed by a truncated power law, in a desert steppe in Inner Mongolia, China. We found that spatial metrics, such as the largest patch index and coefficient of variation of mean patch area had negative linear relationships with grazing intensity, suggesting that vegetation patches became more fragmented and homogeneous under higher grazing pressure. Using a binning-based method to analyze our dataset, we found that the patch-area relationship deviated from a power-law to a truncated power-law model with increasing grazing pressure, while the truncated power law was a better fit than the power law for all plots when binning was not used. These results suggest that the selection of methodology is crucial in using power-law models to detect changes in vegetation patterns. Plant cover was significantly correlated with stocking rate and all spatial metrics evaluated; however, the relationship between cover and vegetation spatial pattern still deserves a thorough examination, especially in other types of ecosystems, before using cover as a universal early sign of desertification. Our results highlight a strong connection between the vegetation spatial pattern and the desertification associated with heavy grazing and suggest that future studies should incorporate information about vegetation spatial pattern in monitoring desertification processes.!://WOS:000283371000005Times Cited: 2 0921-2973WOS:00028337100000510.1007/s10980-010-9520-z@<7Lindemann, J. D. Baker, W. L.2001\Attributes of blowdown patches from a severe wind event in the Southern Rocky Mountains, USA313-325Landscape Ecology164Colorado disturbance regime GIS landscape structure patch attributes windthrow YELLOWSTONE-NATIONAL-PARK SUB-ALPINE FORESTS CATASTROPHIC WIND LARGE DISTURBANCES DYNAMICS PATTERNS MANAGEMENT SUCCESSION WINDTHROW HISTORYArticleMay1There is increasing interest in large, infrequent, natural disturbances and how they affect ecosystems. Attributes of patches produced by some natural disturbances, such as blowdowns, have seldom been measured. We measured attributes of patches produced by a large blowdown (over 10 000 ha) in northern Colorado, USA in 1997. The blowdown produced 402, 655, or 756 patches, based on three different concepts of a blowdown patch. An inverse-J relationship shows that most patches are small in size (< 200 ha), while few are large. Most patches have a high percentage of blown-down trees (> 50% down). Blowdown patches are highly variable in their size, perimeter length, and distance to the nearest patch. The blowdown patches are larger and have more complex shapes than patches in the surrounding forest. Mean size of blowdown patches (25 ha) may be smaller than those of crown fires in a nearby forest, but similar total areas may be affected. About 75% of the blowdown area is within 125 m of a forest not blown down, so natural tree regeneration should not be a problem. About 16,400 ha of mature spruce-fir forest is susceptible to first-year attack by spruce beetles, as this forest is within the expected dispersal distance (1.2 km) from blowdown patches where beetle reproduction is favored. Timber harvest patches differ from blowdown patches in size and distance to nearest patch. It also may be inappropriate to mimic forest blowdown patches using timber harvesting in this region, due to the rare occurrence of large blowdowns, their spatial restriction, and other factors.://000169516300003 ISI Document Delivery No.: 446MD Times Cited: 5 Cited Reference Count: 42 Cited References: *ERDAS INC, 1997, ERDAS FIELD GUID *ESRI, 1994, MAP PROJ *ESRI, 1996, US ARCV GIS *USA CERL, 1997, GRASS US MAN VERS 4 *USDA, R2RIS OR US GUID ALEXANDER RR, 1974, RM121 USDA FOR SERV ATTIWILL PM, 1994, FOREST ECOL MANAG, V63, P247 BAKER WL, IN PRESS PROFESSIONA BAKER WL, 1990, ARCTIC ALPINE RES, V22, P65 BAKER WL, 1992, LANDSCAPE ECOL, V7, P181 BAKER WL, 1992, LANDSCAPE ECOL, V7, P291 BAKER WL, 1999, SPATIAL MODELING FOR, P277 BAKER WL, 2000, FOREST FRAGMENTATION, P221 BERGERON Y, 1997, FOREST ECOL MANAG, V92, P235 BRADSHAW RHW, 1994, FOREST LANDSCAPE RES, V1, P95 CLINTON BD, 2000, FOREST ECOL MANAG, V126, P51 EVERHAM EM, 1996, BOT REV, V62, P113 FLAHERTY PH, 2000, THESIS U WYOMING LAR FOSTER DR, 1988, J ECOL, V76, P105 FOSTER DR, 1988, J ECOL, V76, P135 FOSTER DR, 1992, J ECOL, V80, P79 FUJITA TT, 1989, MON WEA REV, V117, P1913 HANEY A, 1997, ECOSYSTEM MANAGEMENT, P1 MOULTON C, 1999, CASPER STAR TRI 1025 NOWACKI GJ, 1998, PNWGTR421 USDA FOR S OTT L, 1988, INTRO STAT METHODS D PRICE K, 1998, NORTHWEST SCI, V72, P30 QUINE CP, 1998, FORESTRY, V71, P87 QUINE CP, 1999, FORESTRY, V72, P337 REBERTUS AJ, 1997, ECOLOGY, V78, P678 SCHMID JM, 1970, RM178 USDA ROCK MOUN SCHMID JM, 1977, RM49 ROCK MOUNT FOR SINTON DS, 1996, THESIS OREGON STATE TURNER MG, 1994, J VEG SCI, V5, P731 TURNER MG, 1997, BIOSCIENCE, V47, P758 TURNER MG, 1997, ECOL MONOGR, V67, P411 TURNER MG, 1998, ECOSYSTEMS, V1, P511 VEBLEN TT, 1991, CAN J FOREST RES, V21, P242 VOSE JM, 1997, P FIR EFF RAR END SP, P149 WALLIN DO, 1996, FOREST ECOL MANAG, V85, P291 WERNER RA, 1997, PNWRP501 USDA FOR SE WESLEY DA, 1998, 8 C MOUNT MET 3 7 AU, P25 0921-2973 Landsc. Ecol.ISI:000169516300003Univ Wyoming, Dept Geog & Recreat, Laramie, WY 82071 USA. Lindemann, JD, Univ Wyoming, Dept Geog & Recreat, Laramie, WY 82071 USA.Englishڽ7%Lindenmayer, DavidB Cunningham, SaulA2013JSix principles for managing forests as ecologically sustainable ecosystems 1099-1110Landscape Ecology286Springer NetherlandsEcologically sustainable landscape management Landscape management principles Commodity production landscapes Conservation management Land sparing 2013/07/01+http://dx.doi.org/10.1007/s10980-012-9720-9 0921-2973Landscape Ecol10.1007/s10980-012-9720-9English <7JLindenmayer, D. B. Cunningham, R. Crane, M. Michael, D. Montague-Drake, R.20077Farmland bird responses to intersecting replanted areas 1555-1562Landscape Ecology2210agricultural landscapes replanting temperate woodlands Australia HABITAT FRAGMENTATION SPECIES RICHNESS LANDSCAPE CORRIDORS AUTOCORRELATION SITEArticleDecFDespite increasing revegetation of cleared landscapes around the world, there is limited research on the implications of different types of plantings for birdlife. We examined the "intersection effect", whereby species richness is higher at the intersection of "corridors" or vegetation strips for birds inhabiting replanted areas. We also examined individual species responses. Replicated sites at the intersections of plantings were compared with "internal controls" (located in the same plantings similar to 100 m from intersections), "external controls"(sites in isolated linear plantings), and block plantings. We surveyed the 39 sites in our experimental design repeatedly - on different days by different observers and in different seasons. We found no significant difference in species richness between intersections and block plantings, but intersections had higher species richness than isolated linear strips and the internal controls. Similar results were found for bird assemblage scores derived by correspondence analysis. We found evidence of extra-variation at the farm-level for species richness and derived assemblage scores, suggesting a farm-scale response. This suggests the importance of other (often unmeasured) factors at the farm level (e.g. baiting for feral animals). Our results suggest that replanting programs aimed at maximizing bird species richness may benefit from consideration of planting geometry. In particular, linking strip plantings to create intersections and/or establishing block plantings appear to be superior to isolated strips for aggregate species richness.://000250632100013ISI Document Delivery No.: 227BL Times Cited: 0 Cited Reference Count: 47 Lindenmayer, David B. Cunningham, Ross Crane, Mason Michael, Damian Montague-Drake, Rebecca 0921-2973 Landsc. Ecol.ISI:000250632100013Australian Natl Univ, Fenner Sch Environm & Soc, Canberra, ACT 0200, Australia. Lindenmayer, DB, Australian Natl Univ, Fenner Sch Environm & Soc, WK Hancock Bldg W 43, Canberra, ACT 0200, Australia. david.lindenmayer@anu.edu.auEnglish$q<7$Lindenmayer, D. B. Possingham, H. P.1996Modelling the inter-relationships between habitat patchiness, dispersal capability and metapopulation persistence of the endangered species, Leadbeater's possum, in south-eastern Australia79-105Landscape Ecology112vhabitat patchiness; metapopulation dynamics; population viability analysis; forest fragmentation; Leadbeater's possum; forest management; south-eastern Australia MONTANE ASH FORESTS; POPULATION VIABILITY ANALYSIS; HOLLOW-BEARING TREES; ARBOREAL MARSUPIALS; CENTRAL HIGHLANDS; GYMNOBELIDEUS-LEADBEATERI; SMALL MAMMALS; SOUTHEASTERN AUSTRALIA; WILDLIFE CORRIDORS; CONSERVATIONArticleApr A computer simulation model was used to derive estimates of the probability of extinction of populations of the endangered species, Leadbeater's Possum (Gymnobelideus leadbeateri), inhabiting ensembles of habitat patches within two wood production forest blocks in central Victoria, south-eastern Australia. Data on the habitat patches were extracted from forest inventory information that had been captured in the database of a Geographic Information System (GIS). Our analyses focussed on a range of issues associated with the size, number and spatial configuration of patches of potentially suitable habitat that occur within the Ada and Steavenson Forest Blocks. The sensitivity of extinction risks in these two areas to variations in the movement capability of G. leadbeateri was also examined. Our analyses highlighted major differences in the likelihood of persistence of populations of G. leadbeateri between the Ada and Steavenson Forest Blocks. These were attributed to differences in the spatial distribution and size of remnant old growth habitat patches as well as the impacts of wildfires. In addition, simulation modelling revealed a different relative contribution of various individual patches, and ensembles of patches, to metapopulation persistence in the two study areas. In those scenarios for the Ada Forest Block in which the impacts of wild-fires were not modelled, our analyses indicated that a few relatively large, linked patches were crucial for the persistence of the species and their loss elevated estimates of the probability of extinction to almost 100%. A different outcome was recorded from simulations of the Steavenson Forest Block which, in comparison with the Ada Forest Block, is characterized by larger and more numerous areas of well connected patches of old growth forest and where we included the impacts of wildfires in the analysis. In this case, metapopulation persistence was not reliant on any single patch, or small set of patches, of old growth forest. We found that in some circumstances the probability that a patch is occupied whilst the metapopulation is extant may be a good measure of its value for metapopulation viability. Another important outcome from our analyses was that estimates of extinction probability were influenced both by the size and the spatial arrangement of habitat patches. This result emphasizes the importance for modelling metapopulation dynamics of accurate spatial information on habitat patchiness, such as the data used in this study which were derived from a GIS. The values for the predicted probability of extinction were significantly influenced by a range of complex inter-acting factors including: (1) the occurrence and extent of wildfires, (2) the addition of logging exclusion areas such as forest on steep and rocky terrain to create a larger and more complex patch structure, (3) estimates of the quality of the habitat within the logging exclusion areas, and (4) the movement capability of G. leadbeateri. Very high values for the probability of extinction of populations of G. leadbeateri were recorded from many of the simulations of the Ada and Steavenson Forest Blocks. This finding is the result of the limited areas of suitable old growth forest habitat for the species in the two areas that were targeted for analysis. Hence, there appears to be insufficient old growth forest in either of the two forest blocks to be confident that they will support populations of G. leadbeateri in the long-term, particularly ifa wildfire were to occur in the next 150 years. The results of sensitivity analyses indicated that estimates of the probability of extinction of G. leadbeateri varied considerably in response to differences in the values for movement capability modelled. This highlighted the need for data on the dispersal behaviour of the species.://A1996UN74500002 ISI Document Delivery No.: UN745 Times Cited: 36 Cited Reference Count: 95 Cited References: 1971, GOVT GAZETTE 0310 *DEP CONS FOR LAND, 1989, COD PRACT COD FOR PR *GOV VICT, 1986, 9 GOV VICT *GOV VICT, 1992, FLOR FAUN GAUR STRAT *LAND CONS COUNC, 1993, PROP REC AKCAKAYA HR, 1995, BIOL CONSERV, V73, P169 ASHTON DH, 1981, FIRE AUSTR BIOTA, P339 BENNETT AF, 1990, LANDSCAPE ECOL, V4, P109 BENNETT AF, 1994, BIOL CONSERV, V68, P155 BOYCE MS, 1992, ANNU REV ECOL SYST, V23, P481 BROWN JH, 1977, ECOLOGY, V58, P445 FAHRIG L, 1985, ECOLOGY, V66, P1762 FORNEY KA, 1989, CONSERV BIOL, V3, P45 FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 GARRETT MG, 1988, J MAMMAL, V69, P236 GOLDINGAY RL, 1993, INT C MOD SIM, P609 HANSKI I, 1994, TRENDS ECOL EVOL, V9, P131 HARRIS LD, 1984, FRAGMENTED FOREST HARRIS RB, 1987, CONSERV BIOL, V1, P72 HENDERSON MT, 1985, BIOL CONSERV, V31, P95 HENEIN K, 1990, LANDSCAPE ECOL, V4, P157 KINDVALL O, 1992, CONSERV BIOL, V6, P520 LACY RC, 1990, MANAGEMENT CONSERVAT, P131 LACY RC, 1995, BIOL CONSERV, V73, P131 LAMBERSON RH, 1992, CONSERV BIOL, V6, P505 LAMBERSON RH, 1994, CONSERV BIOL, V8, P185 LANDE R, 1988, OECOLOGIA, V75, P601 LAURANCE WF, 1990, J MAMMAL, V71, P641 LINDENMAYER DB, 1989, THESIS AUSTR NATL U LINDENMAYER DB, 1989, VICTORIAN NAT, V106, P174 LINDENMAYER DB, 1990, AUSTR FORESTRY, V53, P61 LINDENMAYER DB, 1990, BIOL CONSERV, V54, P133 LINDENMAYER DB, 1990, SEARCH, V21, P156 LINDENMAYER DB, 1991, AUST J ECOL, V16, P91 LINDENMAYER DB, 1991, AUSTR J ZOOLOGY, V39, P57 LINDENMAYER DB, 1991, BIOL CONSERV, V56, P295 LINDENMAYER DB, 1991, FOREST ECOL MANAG, V40, P289 LINDENMAYER DB, 1991, J BIOGEOGR, V18, P371 LINDENMAYER DB, 1992, 6 VSO DEP CONS ENV N LINDENMAYER DB, 1992, VICTORIAN NAT, V109, P181 LINDENMAYER DB, 1993, BIOL CONSERV, V66, P207 LINDENMAYER DB, 1993, C P GIS 93, P529 LINDENMAYER DB, 1993, CONSERV BIOL, V7, P627 LINDENMAYER DB, 1993, ENVIRON MANAGE, V17, P745 LINDENMAYER DB, 1993, FOREST ECOL MANAG, V60, P77 LINDENMAYER DB, 1993, INT C MOD SIM PERTH, P615 LINDENMAYER DB, 1993, PACIFIC CONSERV BIOL, V1, P13 LINDENMAYER DB, 1993, WILDLIFE RES, V20, P68 LINDENMAYER DB, 1994, AUST J ECOL, V19, P169 LINDENMAYER DB, 1994, AUST J ENV MANAGE, V1, P56 LINDENMAYER DB, 1994, BIOL CONSERV, V70, P143 LINDENMAYER DB, 1994, FOREST ECOL MANAG, V67, P113 LINDENMAYER DB, 1994, WILDLIFE RES, V21, P323 LINDENMAYER DB, 1995, BIOL CONSERV, V73, P119 LINDENMAYER DB, 1995, FOREST ECOL MANAG, V74, P197 LINDENMAYER DB, 1995, FOREST ECOL MANAG, V74, P223 LORENZ GC, 1990, AM MIDL NAT, V123, P348 LOVEJOY TE, 1986, CONSERVATION BIOL SC, P257 LOYN RH, 1985, AUST FORESTRY, V48, P95 MACFARLANE MA, 1991, A RYLAH I TECHNICAL, V111 MAGUIRE LA, 1988, CONSERV BIOL, V2, P6 MEGGS RA, 1991, WILDLIFE RES, V18, P589 MERRIAM G, 1990, LANDSCAPE ECOL, V4, P123 MURPHY DD, 1992, ECOL APPL, V2, P3 NELSON ME, 1993, J MAMMAL, V74, P316 NOBLE WS, 1977, ORDEL FIRE WEEK STAT NORTON TW, 1991, P 9 BIENN C MOD SIM, P442 NOSS RF, 1987, CONSERV BIOL, V1, P159 NOSS RF, 1991, LANDSCAPE LINKAGES B, P27 PAHL LI, 1988, BIOL CONSERV, V46, P71 POSSINGHAM HP, 1991, CONSERVATION AUSTR F, P35 POSSINGHAM HP, 1991, EVALUATION POPULATIO POSSINGHAM HP, 1992, MATH COMPUT SIMULAT, V33, P367 POSSINGHAM HP, 1993, DEC INT C MOD SIM PE, P633 POSSINGHAM HP, 1993, PACIF CONSERV BIOL, V1, P39 POSSINGHAM HP, 1994, BIOL CONSERV, V70, P265 POSSINGHAM HP, 1994, IN PRESS BIOL CONSER POSSINGHAM HP, 1995, BIOL CONSERV, V73, P143 SHAFFER ML, 1990, CONSERV BIOL, V4, P39 SIMBERLOFF D, 1992, CONSERV BIOL, V6, P493 SMITH A, 1984, AUST WILDLIFE RES, V11, P265 SMITH AP, 1980, THESIS MONASH U MELB SMITH AP, 1982, SPECIES RISK RES AUS, P127 SMITH AP, 1984, POSSUMS GLIDERS, P359 SMITH AP, 1988, AUST WILDLIFE RES, V15, P347 SMITH AP, 1992, FOREST ECOL MANAG, V49, P311 SMITH AT, 1980, ECOLOGY, V61, P8 SMITH RB, 1985, AUST FORESTRY, V48, P252 TEMPLE SA, 1988, CONSERV BIOL, V2, P340 THOMAS JW, 1990, CONSERVATION STRATEG THOMAS VC, 1989, THESIS LA TROBE U ME VANDORP D, 1987, LANDSCAPE ECOLOGY, V1, P59 WILCOVE DS, 1986, CONSERVATION BIOL SC, P237 WILCOX BA, 1985, AM NAT, V125, P879 WILKINSON HE, 1961, VICTORIAN NAT, V78, P97 0921-2973 Landsc. Ecol.ISI:A1996UN74500002bLindenmayer, DB, AUSTRALIAN NATL UNIV,CTR RESOURCE & ENVIRONM STUDIES,CANBERRA,ACT 0200,AUSTRALIA.English "07 gLindenmayer, D. B. Wood, J. T. Cunningham, R. B. Crane, M. Macgregor, C. Michael, D. Montague-Drake, R.2009Experimental evidence of the effects of a changed matrix on conserving biodiversity within patches of native forest in an industrial plantation landscape 1091-1103Landscape Ecology248SpringerAustralian Natl Univ, Fenner Sch Environm Soc, Canberra A. C. T. Australia Australian Natl Univ, Stat Consulting Unit Canberra A. C. T. AustraliaLandscape context Landscape experiment Birds Arboreal marsupials South-eastern Australia Ecologically sustainable management of plantationsOctWe implemented a replicated before-after-control-impact (BACI) experiment to quantify vertebrate response in native forest patches to a major change in the surrounding exotic Radiata Pine (Pinus radiata) plantation. We contrasted vertebrate occupancy of patches of native eucalypt forest where the surrounding stands of exotic Radiata Pine (Pinus radiata) were clearfelled (termed "treatment patches") with matched "control patches" where surrounding pine stands remained unlogged. Different species of arboreal marsupials varied in their response to our experimental treatments. The Common Ringtail Possum was unaffected by cutting of the surrounding pine stands, whereas all sightings of the Mountain Brushtail Possum were in control patches. For birds, species richness was significantly reduced by 4-9 species in treatment patches. Birds with cup and dome nests were those negatively affected by the cutting of the surrounding pine stands. They may be susceptible to altered microclimatic conditions or increasing levels of nest predation when the surrounding pine matrix is clearfelled. Our study emphasized how the biota inhabiting retained patches of native forest within plantation landscapes can be changed when stands of surrounding Radiata Pine are clearfelled. In the case of birds, more species will be maintained within eucalypt patches if logging is scheduled so that not all the surrounding pine plantation is clearfelled at once.://000269913600008ISI Document Delivery No.: 495RV Times Cited: 2 Cited Reference Count: 73 Lindenmayer, David B. Wood, Jeff T. Cunningham, Ross B. Crane, Mason Macgregor, Christopher Michael, Damian Montague-Drake, Rebecca 0921-2973 DORDRECHT2009 Landsc. Ecol.ISI:000269913600008Landscape ecologyLindenmayer, DB, Australian Natl Univ, Fenner Sch Environm & Soc, WK Hancock Bldg W 43, Canberra, ACT 0200, Australia. david.lindenmayer@anu.edu.au10.1007/s10980-008-9244-5English<78Linke, J. Franklin, S. E. Huettmann, F. Stenhouse, G. B.2005VSeismic cutlines, changing landscape metrics and grizzly bear landscape use in Alberta811-826Landscape Ecology207<binning; generalized linear models (GLM); GPS locations; landscape configuration; landscape ecology; landscape structure; satellite imagery; seismic cutlines; Ursus arctos RESOURCE-EXTRACTION INDUSTRIES; HABITAT SELECTION; YELLOWHEAD ECOSYSTEM; SWAN MOUNTAINS; MONTANA; ROADS; FRAGMENTATION; FOREST; ECOLOGY; PATTERNArticleNovBesides providing habitat to the grizzly bear (Ursus arctos) and other wildlife, the Rocky Mountain foothills of Alberta, Canada hosts considerable mining, seismic oil and gas exploration and production, and forest harvesting activities. Worldwide, such human activities influence the configuration and composition of the landscape. We assessed seismic cutline effects on landscape structure and grizzly bear use during early summer of 1999 and 2000. We studied five female and two male bears, which were GPS-collared in the spring following den emergence. The area available to this population was stratified into 49 km(2) hexagon-shaped sub-landscapes. The scale of this stratification was determined by patterns of bear movement. Fourteen compositional and configurational landscape metrics were calculated within each landscape unit, and bear use points were pooled or 'binned' within each unit. Landscape use was related to landscape metrics using a Generalized Linear Model (GLM). We found that seismic cutline proportion did not explain landscape use by grizzly bears; however secondary effects of cutlines on landscape structure did. Declining use was mainly associated with increasing proportions of closed forest, and increasing variation of inter-patch distances, while use was mainly increasing with increasing mean patch size. An earlier investigation had demonstrated that adding seismic cutlines to grizzly bear habitat caused increases in the variation of inter-patch distances. Since the landscape structure of this grizzly bear population will continue to change as a function of increased levels of resource extraction activities in the near future, it is crucial to further study the detailed meaning of landscape structure at the large and small scale for effective conservation efforts.://000233036300004 U ISI Document Delivery No.: 980RQ Times Cited: 1 Cited Reference Count: 63 Cited References: *MATHS, 1999, SPLUS 2000 PROF REL BOX GEP, 1970, TIME SERIES ANAL FOR BOYCE MS, 1999, TRENDS ECOL EVOL, V14, P268 BURNHAM KP, 2002, MODEL SELECTION INFE CHAPIN TG, 1998, CONSERV BIOL, V12, P1327 DAVIDSON C, 1998, WILDLIFE SOC B, V26, P32 DIAZ NM, 1996, J FOREST, V94, P12 EVANS IS, 1972, SPATIAL ANAL GEOMORP, P17 FORMAN RTT, 1997, LAND MOSAICS ECOLOGY FORTIN MJ, 1999, LANDSCAPE ECOLOGICAL FRAIR JL, 2004, J APPL ECOL, V41, P201 FRANKLIN SE, 2001, CAN J REMOTE SENS, V27, P579 FROHN RC, 1998, REMOTE SENSING LANDS GIBEAU ML, 2000, THESIS U CALGARY CAL GOTTSCHALK T, 2005, IN PRESS INT J REMOT HAMER D, 1983, ECOLOGICAL STUDIES G HAMER D, 1987, INT C BEAR RES MANAG, V7, P199 HARREL F, 2001, REGRESSION MODELING HERRERO S, 1985, BEAR ATTACKS THEIR C HOOGE PN, 1997, ANIMAL MOVEMENT EXTE HUETTMANN F, 2000, THESIS U NEW BRUNSWI HUETTMANN F, 2003, Z JAGDWISS, V49, P219 JOHNSON DH, 1980, ECOLOGY, V61, P65 KNUTSON MG, 1999, CONSERV BIOL, V13, P1437 LAURIN R, 1992, FUNDAMENTALS SPATIAL LEVIN SA, 1992, ECOLOGY, V73, P1943 LEVINE N, 1999, CRIMESTAT SPATIAL ST LINKE J, 2002, FOOT HILLS MODEL FOR, P82 LINKE J, 2003, FOOTHILLS MODEL FORE, P68 LINKE J, 2003, THESIS U CALGARY CAL MACE RD, 1996, J APPL ECOL, V33, P1395 MACE RD, 1999, CONSERV BIOL, V13, P367 MANLY BFJ, 1993, RESOURCE SELECTION A MATTSON DJ, 1987, INT C BEAR RES MANAG, V7, P259 MCCULLAGH P, 1989, GEN LINEAR MODELS MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MCGARIGAL K, 2001, LANDSCAPE ECOL, V16, P327 MCGARIGAL K, 2002, FRAGSTATS SPATIAL PA MCLELLAN BN, 1988, J APPL ECOL, V25, P451 MCLELLAN BN, 1989, J APPL ECOL, V26, P371 MCLELLAN BN, 2001, J WILDLIFE MANAGE, V65, P92 MENARD S, 2001, SAGE U PAPER SERIES MUNROE RHM, 2003, FOOTHILLS MODEL FORE, P19 NAGY JA, 1989, AECV88R1 NIELSEN SE, 2002, ECOSCIENCE, V10, P1 NIELSEN SE, 2002, FOOTHILLS MODEL FORE, P17 NIELSEN SE, 2002, URSUS, V13, P153 POPPLEWELL C, 2001, THESIS U CALGARY CAL POPPLEWELL C, 2003, URSUS, V14, P27 POTVIN F, 2001, ECOSCIENCE, V8, P399 QUINN GP, 2002, EXPT DESIGN DATA ANA REED RA, 1996, CONSERV BIOL, V10, P1098 RIPLEY BD, 1976, J APPL PROBAB, V13, P255 SCHNEIDER RR, 2003, CONSERV ECOL, V7 SERVHEEN C, 1983, J WILDLIFE MANAGE, V47, P1026 STENHOUSE G, 2000, FOOTHILLS MODEL FORE STENHOUSE G, 2005, IN PRESS URSUS STUARTSMITH AK, 1997, J WILDLIFE MANAGE, V6, P623 TURCHIN P, 1998, QUANTITATIVE ANAL MO VENABLES WN, 2002, MODERN APPL STAT SPL WALLER JS, 1997, J WILDLIFE MANAGE, V61, P1032 WHITE GC, 1990, ANAL WILDLIFE RADIO WIENS JA, 1989, FUNCT ECOL, V3, P385 0921-2973 Landsc. Ecol.ISI:000233036300004Univ Calgary, Dept Geog, Calgary, AB T2N 1N4, Canada. Alberta Sustainable Resource Dept, Forest Wildlife Div, Hinton, AB T7V 1X6, Canada. Linke, J, 443 RR 628, Durham Bridge, NB E6C 1A4, Canada. Linkejulia@hotmail.comEnglish |7`Linke, J. McDermid, G. J. Pape, A. D. McLane, A. J. Laskin, D. N. Hall-Beyer, M. Franklin, S. E.2009ZThe influence of patch-delineation mismatches on multi-temporal landscape pattern analysis157-170Landscape Ecology242backdating change analysis landscape metrics patch boundary slivers updating land-cover change satellite sensor imagery habitat fragmentation forest fragmentation spatial-resolution area metrics disturbance indexes USAFebLInvestigations of land-cover change often employ metrics designed to quantify changes in landscape structure through time, using analyses of land cover maps derived from the classification of remote sensing images from two or more time periods. Unfortunately, the validity of these landscape pattern analyses (LPA) can be compromised by the presence of spurious change, i.e., differences between map products caused by classification error rather than real changes on the ground. To reduce this problem, multi-temporal time series of land-cover maps can be constructed by updating (projecting forward in time) and backdating (projecting backward in time) an existing reference map, wherein regions of change are delineated through bi-temporal change analysis and overlaid onto the reference map. However, this procedure itself creates challenges, because sliver patches can occur in cases where the boundaries of the change regions do not exactly match the land-cover patches in the reference map. In this paper, we describe how sliver patches can inadvertently be created through the backdating and updating of land-cover maps, and document their impact on the magnitude and trajectory of four popular landscape metrics: number of patches (NP), edge density (ED), mean patch size (MPS), and mean shape index (MSI). In our findings, sliver patches led to significant distortions in both the value and temporal behaviour of metrics. In backdated maps, these distortions caused metric trajectories to appear more conservative, suggesting lower rates of change for ED and inverse trajectories for NP, MPS and MSI. In updated maps, slivers caused metric trajectories to appear more extreme and exaggerated, suggesting higher rates of change for all four metrics. Our research underscores the need to eliminate sliver patches from any study dealing with multi-temporal LPA.://000262828900002-399WB Times Cited:1 Cited References Count:64 0921-2973ISI:000262828900002Linke, J Univ Calgary, Dept Geog, 2500 Univ Dr NW, Calgary, AB T2N 1N4, Canada Univ Calgary, Dept Geog, Calgary, AB T2N 1N4, Canada Univ Saskatoon, Dept Geog, Saskatoon, SK S7N 4P3, CanadaDoi 10.1007/S10980-008-9290-ZEnglish<7+Litaor, M. I. Seastedt, T. R. Walker, D. A.2001WSpatial analysis of selected soil attributes across an alpine topographic/snow gradient71-85Landscape Ecology171alpine landscape Colorado fractal analysis geostatistical modeling Rocky Mountains LANDSCAPE PATTERNS IRON-OXIDES FRONT-RANGE LONG-TERM TUNDRA NITROGEN COLOR REGIONALIZATION AVAILABILITY CURVESArticleThe impact of the topographic/snow gradient on soil processes in alpine tundra on Niwot Ridge of the Colorado Front Range (Rocky mts, USA) was assessed using geostatistical modeling and a fractal approach. The mean snow depth, which measured between 1984 and 2000, exhibited a smooth spatial continuity across the study grid area (550 x 400 meter). Soil color variables showed a nested structure that was attributed to a confounded effect of various soil-forming factors on catenary processes. The spatial structure of texture classes exhibited no spatial structure and was explained by data sparsity, cryoturbation, and biological processes that mask the expected long-distance variations (i.e., 550-m) of the catenary processes. Organic C, pH, bulk density, and soil moisture content showed various degrees of spatial continuity, but all indicated that the topographic/snow gradient is not the only dominant soil-forming factor in this alpine ecosystem. The estimated fractal dimension D for the grid landform and the mean snow depth varied between 1.2 and 1.4, indicating that they vary smoothly with long-range variation. The estimated D of the soil variables ranged between 1.6 and 1.8, showing a noisy appearance with short-range variations. These results strongly suggest that most small and micro-scale variations in the alpine soil environs resulted from the combined effect of cryoturbation, biological activity, parent-material and eolian deposition, whereas the large-scale variations originated as a result of the topographic/snow gradient.://000176014400006 >ISI Document Delivery No.: 559FF Times Cited: 2 Cited Reference Count: 38 Cited References: BARRON V, 1986, J SOIL SCI, V37, P499 BENEDICT JB, 1992, 49 U COL I ARCT ALP BOUMA J, 1987, INT I AEROSPACE SURV, V6, P106 BOWMAN WD, 1993, ECOLOGY, V74, P2085 BOWMAN WD, 1994, OECOLOGIA, V97, P93 BREGT AK, 1987, GEODERMA, V39, P281 BURNS SF, 1982, SPACE TIME GEOMORPHO, P25 BURROUGH PA, 1983, J SOIL SCI, V34, P577 BURROUGH PA, 1994, GEODERMA, V62, P311 BURROUGH PA, 1994, MONOGRAPHS SOIL RESO, V12 CRESSIE N, 1988, MATH GEOL, V20, P405 DEUTSCH CV, 1992, GSLIB GEOSTATISTICAL FISK MC, 1998, ECOLOGY, V79, P2253 FRANK TD, 1988, PHOTOGRAMM ENG REM S, V54, P1727 GOOVAERTS P, 1993, SOIL SCI SOC AM J, V57, P372 INGERSOLL RC, 1997, BIOSCIENCE, V47, P310 ISAAKS EH, 1989, INTRO APPL GEOSTATIS LITAOR MI, 1987, GEOCHIM COSMOCHIM AC, V51, P1285 LITAOR MI, 1987, SOIL SCI SOC AM J, V51, P142 LITAOR MI, 1996, GEODERMA, V70, P37 MAHANEY WC, 1988, CATENA, V15, P17 MANDELBROT BB, 1982, FRACTAL GEOMETRY NAT MAY DE, 1982, ECOLOGICAL STUDIES C, P35 MCBRATNEY AB, 1983, SOIL SCI, V135, P177 MELVILLE MD, 1985, J SOIL SCI, V36, P495 OLEAR HA, 1994, OECOLOGIA, V99, P95 SCHEINOST AC, 1997, ADV GEOECOL, V30, P23 SCHEINOST AC, 1997, GEODERMA, V78, P129 SCHEINOST AC, 1999, SOIL SCI SOC AM J, V63, P1463 SCHUEGRAF KF, 1993, P INT REL PHYS S, V31, P7 STELTZER H, 1998, ECOSYSTEMS, V1, P464 TAYLOR RV, 1994, ARCTIC ALPINE RES, V26, P14 TIETJE O, 1993, SOIL SCI SOC AM J, V57, P1088 WALKER DA, 1993, BIOSCIENCE, V43, P287 WALKER DA, 1994, P 50 ANN E W SNOW C, P407 WEBSTER R, 1990, SPATIAL INFORMATION WEST AE, 1999, BIOGEOCHEMISTRY, V45, P243 WILLIAMS MW, 1998, ARCTIC ALPINE RES, V30, P26 0921-2973 Landsc. Ecol.ISI:000176014400006Tel Hai Acad Coll, Dept Biotechnol & Environm Sci, IL-12210 Upper Galilee, Israel. Litaor, MI, Tel Hai Acad Coll, Dept Biotechnol & Environm Sci, IL-12210 Upper Galilee, Israel. litaori@telhai.ac.ilEnglish"?*M. Iggy Litaor T. R. Seastedt D. A. Walker2002WSpatial analysis of selected soil attributes across an alpine topographic/snow gradient71-85Landscape Ecology171ZAlpine landscape - Colorado - Fractal analysis - Geostatistical modeling - Rocky mountainsThe impact of the topographic/snow gradient on soil processes in alpinetundra on Niwot Ridge of the Colorado Front Range (Rocky mts, USA) was assessedusinggeostatistical modeling and a fractal approach. The mean snow depth, whichmeasured between 1984 and 2000, exhibited a smooth spatial continuity acrossthestudy grid area (550 × 400 meter). Soil color variables showed a nestedstructure that was attributed to a confounded effect of various soil-formingfactors on catenary processes. The spatial structure of texture classesexhibited no spatial structure and was explained by data sparsity,cryoturbation, and biological processes that mask the expected long-distancevariations (i.e., 550-m) of the catenary processes. Organic C, pH, bulkdensity,and soil moisture content showed various degrees of spatial continuity, but allindicated that the topographic/snow gradient is not the only dominantsoil-forming factor in this alpine ecosystem. The estimated fractal dimensionDfor the grid landform and the mean snow depth varied between 1.2 and 1.4,indicating that they vary smoothly with long-range variation. The estimatedDofthe soil variables ranged between 1.6 and 1.8, showing a noisy appearance withshort-range variations. These results strongly suggest that most small andmicro-scale variations in the alpine soil environs resulted from the combinedeffect of cryoturbation, biological activity, parent-material and eoliandeposition, whereas the large-scale variations originated as a result of thetopographic/snow gradient.*http://dx.doi.org/10.1023/A:1015216400909 R10.1023/A:1015216400909 M. Iggy Litaor Email: litaori@telhai.ac.il References Barron V. and Torrent J. 1986. Use of the Kubelk-Munk theory to study the influence of iron oxides on soil color. Jour. Soil Sci. 37: 499-510. Benedict J.B. 1992. Field and laboratory studies of patterned ground in a Colorado alpine region. Occasional Paper No. 49. Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO, USA, 38p. Bouma J. and van Lanen J.A.J. 1987. Transfer functions and thresholds values: From soil characteristics to land qualities. In: Bech K.J. (ed.), Quantified Land Evaluation. Proc. Worksh. ISSS and SSSA, Washington, DC. 27 Apr.-2 May 1986. Int. Inst. Aerospace Surv. Earth Sci. Publ. no. 6. ITC Publ., Enschede, the Netherlands, pp. 106-110. Bowman W.D., Theodose T.A., Schardt J.C. and Conant R.T. 1993. Constraints of nutrient availability on primary production in two alpine tundra communities. Ecology 74: 2085-2097. Bowman W.D. and Conant R.T. 1994. Shoot growth dynamics and photosynthetic response to increased nitrogen availability in the alpine willow Salix glauca. Oecologia 97: 93-99. Bregt A.K., Bouma J. and Jellinek M. 1987. Comparison of thematic maps derived from a soil map and from kriging point data. Geoderma 39: 281-291. Burns S.F. and Tonkin P.J. 1982. Soil-geomorphic models and the spatial distribution and development of alpine soils. In: Thorne C.E. (ed.), Space and Time in Geomorphology. Allen & Unwin, London, UK, pp. 25-43. Burrough P.A. 1994. Principles of Geographical Information Systems for Land Resources Assessment. Monographs on Soil and Resources Survey No 12. Oxford Science Publication, Clarendon Press, Oxford, UK. Burrough P.A., Bouma J. and Yates S.R. 1994. The state of the art in pedometrics. Geoderma 62: 311-326. Burrough P.A. 1983. Multiscale sources of spatial variation in soil. I. The application of fractal concepts to nested levels of soil variation. Jour. Soil Sci. 34: 577-597. Cressie N. 1988. Spatial prediction and ordinary kriging. Math. Geol. 20: 405-421. Deutsch C.V. and Journel A.G. 1992. GSLIB-Geostatistical Software Library and Users Guide. Oxford University Press, New York, 340p. Fisk M.C., Schmidt S.K. and Seastedt T.R. 1998. Topographic patterns of above-and belowground production and nitrogen cycling in alpine tundra. Ecology 79: 2253-2266. Frank T.D. 1988. Mapping dominant vegetation communities in the Colorado Rocky Mountain Range with LANDSAT thematic mapper and digital terrain data. Photogrammetric Engineering and Remote Sensing 54: 1727-1734. Goovaerts P. and Chiang C.N. 1993. Temporal persistence of spatial patterns for mineralizable nitrogen and selected soil properties. Soil Sci. Soc. Am. J. 57: 372-381. Ingersoll R.C., Seastedt T.R. and Hartman M.A. 1997. A Model Information Management System for Ecological Research. Bio-Science 47: 310-316. Isaaks E.H. and Srivastava M.R. 1989. An Introduction to Applied Geostatistics. Oxford University Press, New York, NY, USA, 561 p. Litaor M.I. 1987a. The influence of eolian dust on the genesis of alpine soils in the Front, Range, Colorado. Soil Science Society of America Journal 51: 142-147. Litaor M.I. 1987b. Aluminum chemistry: fractionation, speciation, and mineral equilibria of soil interstitial waters of an alpine watershed, Front Range, Colorado. Geochem. et Cosmochim. Acta. 51: 1285-1295. Litaor M.I., Mancinelli R. and Halfpenny J. 1996. The influence of Pocket Gophers on the status of nutrients in alpine soils. Geoderma 70: 37-48. Mandelbrot B.B. 1982. The Fractal Geometry of Nature. Freeman, New York, NY, USA. May D.E. and Webber P.J. 1982. Spatial and temporal variation of the vegetation and its productivity on Niwot Ridge, Colorado. In: Halfpenny J.C. (ed.), Ecological Studies in the Colorado Alpine. Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO, USA, pp. 35-62. Mahaney W.C. and Fahey B.D. 1988. Extractable Fe and Al in late Pleistocene and Holocene paleosols on Niwot Ridge, Colorado Front Range. Catena 15: 17-26. McBratney A.B. and Webster R. 1983. How many observations are needed for regional estimation of soil properties? Soil Sci. 135: 177-183. Melville M.D. and Atkinson G. 1985. Soil colour: its measurement and its designation in models of uniform colour space. J Soil Sci. 36: 495-512. OLear H.A. and Seastedt T.R. 1994. Landscape patterns of litter decomposition in alpine tundra. Oecologia 99: 95-101. Scheinost A.C. and Schwertzmann U. 1999. Color identification of iron oxides and hydroxysulfates: Use and limitations. Soil Sci. Soc. Am. J. 63: 1463-1471. Scheinost A.C., Sinowski W. and Auerswald K. 1997a. Regionalization of soil buffering functions: A new concept applied to K/Ca exchange curves. Advances in GeoEcology 30: 23-38. Scheinost A.C., Sinowski W. and Auerswald K. 1997b. Regionalization of soil water retention curves in a highly variable soilscape, I. Developing a new pedotransfer function. Geoderma 78: 129-143. Schulze D.G., Van Scoyoc G.E., Henderson T.L., Baumgardner M.F., Negal J.L. and Stott D.E. 1993. Significance of organic matter in determining soil colors. In: Bigham and Ciolkosz (eds), Soil Color. SSSA Special Publication Number 31. Soil Science Society of America Inc., Madison, WI, USA, pp. 71-91. Steltzer H. and Bowman W.D. 1998. Differential influence of plant species on soil nitrogen transformations within moist meadow alpine tundra. Ecosystems 1: 464-474. Taylor R.V. and Seastedt T.R. 1994. Short-and long-term patterns of soil moisture in alpine tundra. Arctic and alpine Research 26: 14-20. Tietje O. and Tapkenhinrichs M. 1993. Evaluation of pedo-trans function. Soil Sci. Soc. Am. J. 57: 1088-1095. Walker D.A., Krantz W.B., Price E.T., Lewis B.E. and Tabler R.D. 1994. Hierarchic studies of snow-ecosystem interactions: a 100 year snow alteration experiment. In: Proceedings of the 50th Eastern Snow Conference, pp. 407-414. Walker D.A., Halfpenny J.C., Walker M.D. and Wessman C.A. 1993. Long-term studies of snow-vegetation interactions. Bio-Science 43: 287-301. Webster R. and Oliver M.A. 1990. Statistical Methods in Soil and Land Resource Survey. Spatial Information System. Oxford University Press, New York, NY, USA, 316 p. West A.E., Brooks P.D., Fisk M.C., Smith L.K., Holland E.A., Jaeger C.H. et al. 1999. Landscape patterns of CH4 fluxes in an alpine tundra ecosystem. Biogeochemistry 45: 243-264. Williams M.W., Brooks P.D. and Seastedt T. 1998. Nitrogen and carbon soil dynamics in response to climate change in a high-elevation ecosystem in the Rocky Mountains, USA. Arctic and Alpine Research 30: 26-30. 2M. Iggy Litaor1 , T.R. Seastedt2 and D.A. Walker3 (1) Department of Biotechnology and Environmental Sciences, Tel-Hai Academic College, Upper Galilee, 12210, Israel (2) EPOB, and INSTAAR, University of Colorado, 80309-0450 Boulder, USA (3) University of Alaska, Fairbanks, Fairbanks, 99775-7000, USA <7Liu, A. J. Cameron, G. N.2001PAnalysis of landscape patterns in coastal wetlands of Galveston Bay, Texas (USA)581-595Landscape Ecology167fractal dimension Galveston Bay GIS historical database human disturbance landscape ecology spatial patterns wetlands RIPARIAN FOREST SALT-MARSH FRACTALS HABITAT EDGEArticleOctHHigh productivity and accessibility have made coastal wetlands attractive sites for human settlements. This study analyzed the patterns of wetland landscapes in Galveston Bay, Texas, USA. The first objective of the study was to describe the relationships between the fractal dimension of wetland boundaries and those factors which affect the wetland landscapes (e.g., land use, type of vegetation, size, location, and level of human disturbance). The second objective was to construct a historical database to contrast wetland areas which had experienced different levels of disturbance between 1956 and 1989. The fractal dimension, a measure of how much of the geographical space is filled by boundaries, was measured by the perimeter-area method. The fractal dimension of wetlands was significantly affected by land use, type of vegetation, size, and level of anthropogenic disturbance. In addition, increasing the size of buffers around roads did not significantly affect the fractal dimension of wetlands. Landscape indices, such as fractal dimension, dominance, and diversity, were used to characterize spatial heterogeneity in the historical database. Lake Stephenson, an area of low anthropogenic disturbance, experienced no changes in wetland composition and abundance over time. Anahuac, an area of medium disturbance, experienced changes in both wetland composition and abundance. Texas City, an area of high disturbance, experienced a change in wetland composition. These differences can be associated with the type and level of disturbance present; however, more evidence is needed to determine whether certain landscape patterns have stable, intrinsic properties which allow persistence in the face of disturbance. These results will be informative to resource managers determining how wetlands can be managed as natural resources and nature reserves.://000172809400001  ISI Document Delivery No.: 503QG Times Cited: 6 Cited Reference Count: 51 Cited References: *SAS, 1982, US GUID STAT ANDERSON JR, 1976, 964 US GEOL SURV ANDREWS A, 1990, AUSTR ZOOLOGIST, V26, P130 BENTON AR, 1979, RSC102 BROWDER JA, 1989, REMOTE SENS ENVIRON, V56, P871 BRUCE KA, 1997, NAT AREA J, V17, P255 COWARDIN LM, 1979, FWSOBS7931 US FISH W CRAIG NJ, 1979, ENVIRON MANAGE, V3, P133 DAHL TE, 1990, WETLAND LOSSES US 17 DAHL TE, 1991, WETLAND STATUS TREND FAHRIG L, 1995, BIOL CONSERV, V72, P1 FALCONER K, 1990, FRACTAL GEOMETRY MAT FINDLAY CS, 1997, CONSERV BIOL, V11, P1000 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FRAYER WE, 1983, STATUS TRENDS WETLAN GAGLIANO SM, 1973, 14 LOUIS STAT U COAS GAGLIANO SM, 1981, T GULF COAST ASS GEO, V31, P295 GIBBS JP, 1993, WETLANDS, V13, P25 HENDERSON MT, 1985, BIOL CONSERV, V31, P95 HOLLAND MM, 1991, ECOTONES ROLE LANDSC JOHNSTON CA, 1991, CRIT REV ENV CONTR, V21, P491 KENT C, 1982, CANADIAN J FISHERIES, V39, P847 KRUMMEL JR, 1987, OIKOS, V48, P321 LAM NSN, 1992, PROF GEOGR, V44, P88 LONSDALE WM, 1994, BIOL CONSERV, V69, P277 MANDELBROT BB, 1977, FRACTALS FORM CHANCE MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MCLEESE RL, 1977, J ENVIRON QUAL, V6, P467 MELTZER MI, 1992, J APPL ECOL, V29, P635 MERRIAM G, 1989, LANDSCAPE ECOLOGY, V2, P227 MILLAR JB, 1971, J HYDROL, V14, P259 MILNE BT, 1991, LANDSCAPE URBAN PLAN, V21, P81 MILNE BT, 1992, AM NAT, V139, P32 MINELLO TJ, 1994, WETLANDS, V14, P184 MITSCH WJ, 1993, WETLANDS MOULTON DW, 1997, TEXAS COASTAL WETLAN ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PETERJOHN WT, 1984, ECOLOGY, V65, P1466 PETERSON GW, 1994, ESTUARIES, V17, P235 PINAY G, 1988, REGUL RIVER, V2, P507 REX KD, 1990, LANDSCAPE ECOL, V4, P249 SHAW SP, 1956, 39 US DEP INT FISH W SHIPLEY FS, 1994, GBNEP44 SNEDECOR GW, 1980, STAT METHODS, P384 SOULE ME, 1992, OIKOS, V63, P39 SUGIHARA G, 1990, TRENDS ECOL EVOL, V5, P79 TURNER MG, 1987, LANDSCAPE HETEROGENE TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 WHITE WA, 1993, PUBLICATION GALVESTO WIENS JA, 1992, ECOL STUD, V92, P217 YOUNG KR, 1994, CONSERV BIOL, V8, P972 0921-2973 Landsc. Ecol.ISI:000172809400001vUniv Houston, Dept Biol, Houston, TX 77204 USA. Cameron, GN, Univ Cincinnati, Dept Biol Sci, Cincinnati, OH 45221 USA.English|?uLiu, Dan Chen, Yang Cai, Wenwen Dong, Wenjie Xiao, Jingfeng Chen, Jiquan Zhang, Haicheng Xia, Jiangzhou Yuan, Wenping2014JThe contribution of China's Grain to Green Program to carbon sequestration 1675-1688Landscape Ecology2910Dec"Forests play an important role in regulating atmospheric carbon dioxide concentration and mitigating the greenhouse effect. The Grain to Green Program (GGP) is one of the largest ecological programs in China, and it aims at converting croplands on steep slopes to forests. However, the magnitude and distribution of carbon sequestration induced by GGP remain unknown. In this study, we estimated the changes in carbon fluxes and stocks caused by forests converted from croplands under the GGP using a process-based ecosystem model (i.e., IBIS). Our results showed that the converted areas from croplands to forests under the GGP program could sequester 110.45 Tg C by 2020, and 524.36 Tg C by the end of this century. The sequestration capacity showed substantial spatial variations with large sequestration in southern China. The economic benefits of carbon sequestration from the GGP were also estimated according to the current carbon price. The estimated economic benefits ranged from $8.84 to $44.20 billion from 2000 through 2100, which may exceed the current total investment ($38.99 billion) on the program. As the GGP program continues and forests grow, the impact of this program will be even larger in the future, making a more considerable contribution to China's carbon sink over the upcoming decades.!://WOS:000346920900004Times Cited: 2 0921-2973WOS:00034692090000410.1007/s10980-014-0081-4|?Liu, Juichieh Opdam, Paul2014hValuing ecosystem services in community-based landscape planning: introducing a wellbeing-based approach 1347-1360Landscape Ecology298OctThe challenge of incorporating the concept of ecosystem services in landscape planning has been widely acknowledged, yet values of ecosystem services are not well considered in current landscape planning and environmental governance. This is particularly the case when local stakeholders are strongly involved in decision making about adapting the landscape to future demands and challenges. Engagement of stakeholders introduces a variety of interests and motives that result in diverging value interpretations. Moreover, participative planning approaches are based on learning processes, implying that the perceptions of value evolve during the planning process. Current valuation approaches are not able to support such process. Therefore we argue that there is a need for a novel view on the mechanism of integrating valuation in the different stages of community-based landscape planning, as well as for tools based on this mechanism. By revisiting the original conception of ecosystem services and redefining the value of an ecosystem service as its comparative importance to human wellbeing, we develop a conceptual framework for incorporating ecosystem service valuation that captures the full spectrum of value and value changes. We acknowledge that in the social interactions during the planning process values are redefined, negotiated and reframed in the context of the local landscape. Therefore, we propose a valuation mechanism that evolves through the phases of the cyclic planning process. We illustrate the use of this mechanism by proposing a tool that supports stakeholder groups in building a value-based vision on landscape adaptation that contributes to all wellbeing dimensions.!://WOS:000342078600007Times Cited: 3 0921-2973WOS:00034207860000710.1007/s10980-014-0045-82|?9&Liu, Wenping Holst, Jirko Yu, Zhenrong2014iThresholds of landscape change: a new tool to manage green infrastructure and social-economic development729-743Landscape Ecology294AprAn understanding of how and where a landscape can be improved with green infrastructure is important for the development of land-use policies. However, it is still a big challenge to manage landscapes due to a lack of condition-based diagnosis and consistent conflicts with social-economic interests. The purpose of this study is to identify the thresholds of landscape change and to explore new reference lines of policy decision-making for balancing social-economic development and green infrastructure management. Five different landscape types and their thresholds of landscape change were identified using parametric and piecewise linear models in the district of Haidian, Beijing, PR China, and their changes and social-economic drivers were analyzed with principal component analysis and a stepwise linear regression model for the time period 1991-2010. It is shown that different thresholds of different landscapes do exist and can be identified by the area of their key elements of green infrastructure. Integrating these thresholds into a social-economic context, it is shown where and how social-economic variables can be manipulated quantitatively to achieve development targets with respect to green infrastructure in individual towns and the entire district. Green infrastructure can be managed by changing just a small proportion of social-economic investment. This paper provides a useful tool to achieve a sustainable development by balancing green infrastructure with social-economic interests.!://WOS:000333533800014Times Cited: 0 0921-2973WOS:00033353380001410.1007/s10980-014-0007-1 <7j 3Liu, X. P. Lao, C. H. Li, X. Liu, Y. L. Chen, Y. M.2012jAn integrated approach of remote sensing, GIS and swarm intelligence for zoning protected ecological areas447-463Landscape Ecology273remote sensing gis aco zoning protected ecological areas ant colony optimization open water features land-use allocation pearl river delta habitat heterogeneity cellular-automata index ndwi multicriteria conservation selectionMarInterest in protecting ecological areas is increasing because of land uses conflicts and environmental pressures. The optimal zoning of protected ecological areas belongs to a NP-hard problem because it is subject to both box and spatial constraints. A challenge in solving area optimization problems emerges with the increasing size of a study region. In this article, an integrated approach of remote sensing, GIS and modified ant colony optimization (ACO) is proposed for application in zoning protected ecological areas. Significant modifications have been made in the conventional ACO so that it can be further extended to solve zoning problems in large regions. An improved selection strategy is designed to accelerate the progress of sites selection for artificial ants. Another important modification in ACO is to incorporate the neighborhood diffusion strategy into pheromone updating. The optimal objective is to generate protected areas that maximize both ecological suitability and spatial compactness. The modified ACO model has been successfully applied to a case study involving an area of 25,483 cells in Dongguan, Guangdong, China. The experiments have demonstrated that the proposed model is an efficient and effective optimization technique for generating optimal protection. The modified ACO model only requires approximately 119 s for determining near-optimal solutions. Furthermore, the proposed method performs better than other methods, including simulated annealing, genetic algorithm, iterative relaxation, basic ACO, and density slicing.://000300087500011-889QE Times Cited:0 Cited References Count:46 0921-2973Landscape EcolISI:000300087500011lLiu, XP Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou 510275, Guangdong, Peoples R China Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou 510275, Guangdong, Peoples R China Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou 510275, Guangdong, Peoples R China Sun Yat Sen Univ, Guangdong Key Lab Urbanizat & Geosimulat, Guangzhou 510275, Guangdong, Peoples R ChinaDOI 10.1007/s10980-011-9684-1English|?< 9Liu, X. P. Li, X. Chen, Y. M. Tan, Z. Z. Li, S. Y. Ai, B.2010_A new landscape index for quantifying urban expansion using multi-temporal remotely sensed data671-682Landscape Ecology255Landscape metrics or indices have been commonly used for quantifying landscape patterns. However, most of these indices are generally focused on simple analysis and description of the characterization of the geometric and spatial properties of categorical map patterns. These indices can hardly obtain the information about the spatio-temporal dynamic changes of landscape patterns, especially when multi-temporal remote sensing data are used. In this paper, a new landscape index, i.e., landscape expansion index (LEI), is proposed to solve such problems. In contrast with conventional landscape indices which are capable of reflecting the spatial characteristics for only one single time point, LEI and its variants can capture the information of the formation processes of a landscape pattern. This allows one to quantify the dynamic changes in two or more time points. These proposed indices have been applied to the measurement of the urban expansion of Dongguan in Guangdong province, China, for the period of 1988-2006. The analysis identifies three urban growth types, i.e., infilling, edge-expansion and outlying. A further analysis of different values of LEI in each period reveals a general temporal transition between phases of diffusion and coalescence in urban growth. This implies that the regularity in the spatiotemporal pattern of urban development in Dongguan, is consistent with the explanations according to urban development theories.!://WOS:000276609800002Times Cited: 0 0921-2973WOS:00027660980000210.1007/s10980-010-9454-5(|?HLiu, Yunhui Rothenwoehrer, Christoph Scherber, Christoph Batary, Peter Elek, Zoltan Steckel, Juliane Erasmi, Stefan Tscharntke, Teja Westphal, Catrin2014nFunctional beetle diversity in managed grasslands: effects of region, landscape context and land use intensity529-540Landscape Ecology293MarjCurrent biodiversity conservation policies have so far had limited success because they are mainly targeted to the scale of individual fields with little concern on different responses of organism groups at larger spatial scales. We investigated the relative impacts of multi-scale factors, including local land use intensity, landscape context and region, on functional groups of beetles (Coleoptera). In 2008, beetles were suction-sampled from 95 managed grasslands in three regions, ranging from Southern to Northern Germany. The results showed that region was the most important factor affecting the abundance of herbivores and the abundance and species composition of predators and decomposers. Herbivores were not affected by landscape context and land use intensity. The species composition of the predator communities changed with land use intensity, but only in interaction with landscape context. Interestingly, decomposer abundance was negatively related to land use intensity in low-diversity landscapes, whereas in high-diversity landscapes the relation was positive, possibly due to enhanced spillover effects in complex landscapes. We conclude that (i) management at multiple scales, from local sites to landscapes and regions, is essential for managing biodiversity, (ii) beetle predators and decomposers are more affected than herbivores, supporting the hypothesis that higher trophic levels are more sensitive to environmental change, and (iii) sustaining biological control and decomposition services in managed grassland needs a diverse landscape, while effects of local land use intensity may depend on landscape context.!://WOS:000331935500014Times Cited: 1 0921-2973WOS:00033193550001410.1007/s10980-014-9987-0|?0Liu, Zhifeng He, Chunyang Zhou, Yuyu Wu, Jianguo2014hHow much of the world's land has been urbanized, really? A hierarchical framework for avoiding confusion763-771Landscape Ecology295MaydUrbanization has transformed the world's landscapes, resulting in a series of ecological and environmental problems. To assess urbanization impacts and improve sustainability, one of the first questions that we must address is: how much of the world's land has been urbanized? Unfortunately, the estimates of the global urban land reported in the literature vary widely from less than 1-3 % primarily because different definitions of urban land were used. To evade confusion, here we propose a hierarchical framework for representing and communicating the spatial extent of the world's urbanized land at the global, regional, and more local levels. The hierarchical framework consists of three spatially nested definitions: "urban area" that is delineated by administrative boundaries, "built-up area" that is dominated by artificial surfaces, and "impervious surface area" that is devoid of life. These are really three different measures of urbanization. In 2010, the global urban land was close to 3 %, the global built-up area was about 0.65 %, and the global impervious surface area was merely 0.45 %, of the word's total land area (excluding Antarctica and Greenland). We argue that this hierarchy of urban land measures, in particular the ratios between them, can also facilitate better understanding the biophysical and socioeconomic processes and impacts of urbanization.!://WOS:000334689900001Times Cited: 1 0921-2973WOS:00033468990000110.1007/s10980-014-0034-y <7k FLizee, M. H. Manel, S. Mauffrey, J. F. Tatoni, T. Deschamps-Cottin, M.2012zMatrix configuration and patch isolation influences override the species-area relationship for urban butterfly communities159-169Landscape Ecology272connectivity hierarchical partitioning landscape metrics public parks remote sensing rhopalocera island biogeography hypothesis fragmented landscapes habitat patches land-use diversity biodiversity heterogeneity connectivity gradient conservationFebAThe aim of this paper is to examine the role of urban public parks in maintaining connectivity and butterfly assemblages. Using a regression framework, we first test the relative importance of park size and isolation in predicting abundance and species richness of butterfly assemblages across a set of 24 public parks within a large metropolitan area, Marseille (South-East France). Then, we focus on landscape features that affect diversity patterns of the recorded butterfly communities. In this second part, the urban landscape surrounding each park is described (within a 1 x 1 km window) according to two major components: vegetated areas (habitat patches) and impervious or built areas (matrix patches). Specifically, we aim to test whether the incorporation of this built component (matrix) in the landscape analysis provides new insights into the understanding of ecological connectivity in the urban environment. We found a significant effect of both matrix configuration (shape complexity of the built patches) and distance from regional species pool (park isolation) on diversity of butterflies that overrides park size in their contribution to variation in species richness. This result suggests that many previous studies of interactions between biodiversity and urban landscape have overlooked the influence of the built elements.://0003000887000029Sp. Iss. SI 889QQ Times Cited:1 Cited References Count:62 0921-2973Landscape EcolISI:000300088700002Lizee, MH Univ Aix Marseille 1, Populat Environm Dev Lab, UMR 151, 3 Pl Victor Hugo, F-13331 Marseille 03, France Univ Aix Marseille 1, Populat Environm Dev Lab, UMR 151, 3 Pl Victor Hugo, F-13331 Marseille 03, France Univ Aix Marseille 1, Populat Environm Dev Lab, UMR 151, F-13331 Marseille 03, France Fac Sci & Tech St Jerome, Mediterranean Inst Ecol & Paleoecol, UMR 6116, F-13397 Marseille 20, FranceDOI 10.1007/s10980-011-9651-xEnglish<7.Lloret, F. Calvo, E. Pons, X. Diaz-Delgado, R.2002AWildfires and landscape patterns in the Eastern Iberian peninsula745-759Landscape Ecology178fire regime fragmentation GIS land cover landscape homogenization landscape pattern mediterranean landscape NDVI pine forest shrubland YELLOWSTONE-NATIONAL-PARK BOREAL FOREST FIRE VEGETATION SPAIN DISTURBANCE ECOSYSTEMS SUCCESSION SATELLITE HETEROGENEITYArticleDecfThe relations between disturbance regime and landscape patterns have been developed from a theoretical perspective, but few studies have tested these relations when forces promoting opposing heterogeneity patterns are simultaneously operating on a landscape. This work provides quantitative evidence of these relations in areas dominated by human activity, showing that landscape heterogeneity decreases disturbance spread. In turn, disturbance introduces a source of landscape heterogeneity, but it is not enough to counterbalance the homogeneity trend due to agricultural abandonment. Land cover changes and wildfire occurrence (fires larger than 0.3 km(2)) have been monitored in the Tivissa municipality (208.4 km(2)) (Catalonia, NE Spain) from 1956 to 1993. Land cover maps were obtained from 1956, 1978 and 1993 and they were overlaid with fire occurrence maps obtained for the 1975-1995 period from 60 m resolution remote sensing images, which allow the identification of burned areas by sudden drops in Normalized Difference Vegetation Index (NDVI). Changes in landscape patterns in relation to fire regime have been analyzed considering several parameters: patch density, mean patch size, mean distance to the nearest neighbour of the same category, edge density, and the Shannon diversity index. In the 1956-1993 period there is a trend to increasing landscape homogenization due to the expansion of shrublands linked to a decrease in forest surface, and to the abandonment of agricultural lands. This trend, however, is not constant along all the period. Fires are more likely to occur in woody, homogenous areas, increasing landscape heterogeneity, as observed in the 1978-1993 period. This increase in heterogeneity does not counterbalance the general trend to landscape homogenization as a consequence of agricultural abandonment and the coalescence of natural vegetation patches.://000181767400006 ISI Document Delivery No.: 659FV Times Cited: 10 Cited Reference Count: 63 Cited References: ANDERSON GL, 1993, REMOTE SENS ENVIRON, V45, P165 ARIANOUTSOU M, 2000, ECOLOGY BIOGEOGRAPHY, P269 ATTIWILL PM, 1994, FOREST ECOL MANAG, V63, P247 BAKER WI, 1994, CONSERV BIOL, V8, P763 BARBERO M, 1998, ECOLOGY BIOGEOGRAPHY, P153 BOLOS O, 1967, MEMORIAS REAL ACAD C BURGAN RE, 1998, INT J WILDLAND FIRE, V8, P159 CASGRAIN P, 1999, R PACKAGE MULTIVARIA CASTELLNOU M, 1997, PRINCIPIS GESTIO DEL DAVIS FW, 1994, ROLE FIRE MEDITERRAN DEANGELIS DL, 1985, ECOL MODEL, V29, P399 DEBUSSCHE M, 1999, GLOBAL ECOL BIOGEOGR, V8, P3 DELCOURT HR, 1996, LANDSCAPE ECOL, V11, P363 DIAZDELGADO R, 2000, THESIS U AUTONOMA BA DIAZDELGADO R, 2002, ECOLOGY, V83, P2293 DOUGLAS T, 1996, GLOBAL ECOL BIOGEOGR, V5, P258 ESCARRE J, 1983, ACTA OECOL-OEC PLANT, V4, P221 FERNANDEZ A, 1997, REMOTE SENS ENVIRON, V60, P153 FERNANDEZALES R, 1992, LANDSCAPE ECOLOGY, V7, P3 FORMAN RT, 1995, LAND MOSAICS ECOLOGY FORTIN MJ, 1993, DESIGN ANAL ECOLOGIC, P342 FORTIN MJ, 1999, LANDSCAPE ECOLOGICAL, P253 GAMON JA, 1995, ECOL APPL, V5, P28 GIRALT E, 1990, HIST EC CATALUNYA CO, V2, P121 HANES TL, 1971, ECOL MONOGR, V41, P27 HAYDON DT, 2000, LANDSCAPE ECOL, V15, P373 HERRANZ JM, 1997, ECOSCIENCE, V4, P86 JOHNSON EA, 1998, J VEG SCI, V9, P603 KASSISCHKE ES, 1993, REMOTE SENS ENVIRON, V45, P61 KEELEY JE, 1986, RESILIENCE MEDITERRA, P95 KNICK ST, 1997, LANDSCAPE ECOL, V12, P287 KOZLOWSKI TT, 1974, FIRE ECOSYSTEMS KRUMMEL JR, 1987, OIKOS, V48, P321 MASALLES RM, 1987, ECOSISTEMES TERRESTR, P27 MATHER PM, 1999, COMPUTER PROCESSING MCGARIGAL K, 1995, FRAGSTATS SPATIAL PA MORENO JM, 1998, LARGE FOREST FIRES, P159 NATHAN R, 2000, ECOLOGY BIOGEOGRAPHY, P105 NAVEH Z, 1990, LANDSCAPE ECOLOGY PALA V, 1995, PHOTOGRAMMETRIC ENG, V7, P935 PEREIRA AC, 1996, INT J REMOTE SENS, V17, P1925 PICKET ST, 1985, ECOLOGY NATURAL DIST PINO J, 2000, LANDSCAPE URBAN PLAN, V49, P35 PINOL J, 1998, CLIMATIC CHANGE, V38, P345 PONS X, 1994, REMOTE SENS ENVIRON, V48, P191 PONS X, 2000, MIRAMON SISTEMA INFO QUATTROCHI DA, 1991, QUANTITATIVE METHODS, P51 REAL J, 2000, ARDEOLA, V47, P93 ROBERTS DW, 1996, ECOL MODEL, V90, P175 ROMME WH, 1982, ECOL MONOGR, V52, P199 SALVADOR R, 2000, INT J REMOTE SENS, V21, P655 TERRADAS J, 1998, FIRE MANAGEMENT LAND, P297 TRABAUD L, 1980, VEGETATIO, V43, P49 TRABAUD L, 1987, ROLE FIRE ECOLOGICAL, P65 TRABAUD L, 1993, FIRE ENV ECOLOGICAL, P277 TRABAUD L, 2000, ECOLOGY BIOGEOGRAPHY, P257 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1989, OIKOS, V55, P121 TURNER MG, 1994, J VEG SCI, V5, P731 TURNER MG, 1994, LANDSCAPE ECOL, V9, P59 TURNER MG, 1997, ECOL MONOGR, V67, P411 VALETTE JC, 1979, INFLAMMABILITE ESPEC WEIR JMH, 2000, ECOL APPL, V10, P1162 0921-2973 Landsc. Ecol.ISI:000181767400006nUniv Autonoma Barcelona, Ctr Ecol Res & Forestry Applicat, E-08193 Barcelona, Spain. Univ Autonoma Barcelona, Unitat Ecol, Dept Biol Anim Biol Vegetal & Ecol, E-08193 Barcelona, Spain. Univ Autonoma Barcelona, Dept Geog, E-08193 Barcelona, Spain. Lloret, F, Univ Autonoma Barcelona, Ctr Ecol Res & Forestry Applicat, E-08193 Barcelona, Spain. Francisco.Lloret@uab.esEnglish<7},Lobo, A. Moloney, K. Chic, O. Chiariello, N.1998kAnalysis of fine-scale spatial pattern of a grassland from remotely-sensed imagery and field collected data111-131Landscape Ecology1323vegetation pattern serpentine grassland disturbance Thomomys bottae geostatistics remote sensing fractal spatial simulation NDVI Fast Fourier Transform FRACTAL LANDSCAPES SERPENTINE GRASSLAND COMMUNITY STRUCTURE GOPHER DISTURBANCE MULTISCALE SOURCES SOIL PROPERTIES ECOLOGY VARIABILITY DIMENSIONS VARIOGRAMSArticleAprrAn important practical problem in the analysis of spatial pattern in ecological systems is that requires spatially-intensive data, with both fine resolution and large extent. Such information is often difficult to obtain from field-measured variables. Digital imagery can offer a valuable, alternative source of information in the analysis of ecological pattern. In the present paper, we use remotely-sensed imagery to provide a link between field-based information and spatially-explicit modeling of ecological processes. We analyzed one digitized color infrared aerial photograph of a serpentine grassland to develop a detailed digital map of land cover categories (31.24 m x 50.04 m of extent and 135 mm of resolution), and an image of vegetation index (proportional to the amount of green biomass cover in the field). We conducted a variogram analysis of the spatial pattern of both field-measured (microtopography, soil depth) and image-derived (land cover map, vegetation index, gopher disturbance) landscape variables, and used a statistical simulation method to produce random realizations of the image of vegetation index based upon our characterization of its spatial structure. The analysis revealed strong relationships in the spatial distribution of the ecological variables (e.g., gopher mounds and perennial grasses are found primarily on deeper soils) and a non-fractal nested spatial pattern in the distribution of green biomass as measured by the vegetation index. The spatial pattern of the vegetation index was composed of three basic components: an exponential trend from 0 m to 4 m, which is related to local ecological processes, a linear trend at broader scales, which is related to a general change in topography across the study site, and a superimposed periodic structure, which is related to the regular spacing of deeper soils within the study site. Simulations of the image of vegetation index confirmed our interpretation of the variograms. The simulations also illustrated the limits Of statistical analysis and interpolations based solely on the semivariogram, because they cannot adequately characterize spatial discontinuities.://000077256800005 ISI Document Delivery No.: 143LH Times Cited: 21 Cited Reference Count: 78 Cited References: *STAT SCI, 1993, S PLUS PROGR MAN VER *US ARM CORPS ENG, 1991, GRASS 4 0 US REG MAN ARMSTRONG AC, 1986, J SOIL SCI, V37, P641 BARBOUR MG, 1987, TERRESTRIAL PLANT EC BIONDINI ME, 1994, AM NAT, V143, P1026 BURROUGH PA, 1983, J SOIL SCI, V34, P577 BURROUGH PA, 1983, J SOIL SCI, V34, P599 CLIFF AD, 1981, SPATIAL PROCESSES MO COFFIN DP, 1989, LANDSCAPE ECOL, V3, P19 COHEN WB, 1990, REMOTE SENS ENVIRON, V34, P167 CRESSIE NAC, 1993, STAT SPATIAL DATA CURRAN PJ, 1988, REMOTE SENS ENVIRON, V24, P493 CURRAN PJ, 1989, IEEE T GEOSCI REMOTE, V27, P620 DEUTSCH CV, 1992, GSLIB GEOSTATISTICAL DIGGLE PJ, 1983, STAT ANAL SPATIAL PO FORMAN RTT, 1986, LANDSCAPE ECOLOGY GONZALEZ RC, 1977, DIGITAL IMAGE PROCES HOBBS RJ, 1985, OECOLOGIA, V67, P342 HOBBS RJ, 1985, OECOLOGIA, V67, P519 HOBBS RJ, 1987, VEGETATIO, V69, P141 HOBBS RJ, 1991, ECOLOGY, V72, P59 HUENNEKE LF, 1990, ECOLOGY, V71, P478 JOHNSON AR, 1992, ECOLOGY, V73, P1968 JOURNEL AG, 1978, MINING GEOSTATISTICS JUPP DLB, 1988, IEEE T GEOSCI REMOTE, V26, P463 JUPP DLB, 1989, IEEE T GEOSCI REMOTE, V27, P247 KOIDE RT, 1987, OECOLOGIA, V72, P284 LEDUC A, 1994, LANDSCAPE ECOL, V9, P279 LEVIN SA, 1974, P NATL ACAD SCI USA, V71, P2744 LEVIN SA, 1992, ECOLOGY, V73, P1943 LOBO A, IN PRESS INT J REMOT LOBO A, 1997, IN PRESS IEEE T GEOS MANDELBROT BB, 1983, FRACTAL GEOMETRY NAT MARK DM, 1984, J INT ASS MATH GEOL, V16, P671 MATHERTON G, 1965, THEORIE VARIABLES RE MCNAUGHTON SJ, 1968, ECOLOGY, V49, P962 MILNE BT, 1989, LANDSCAPE ECOL, V2, P101 MILNE BT, 1991, QUANTITATIVE METHODS, P199 MILNE BT, 1992, AM NAT, V139, P32 MOLONEY KA, 1991, LANDSCAPE ECOL, V5, P163 MOLONEY KA, 1993, PATCH DYNAMICS, P61 MOLONEY KA, 1996, IN PRESS ECOLOGY MURPHY DD, 1989, GRASSLAND STRUCTURE, P201 OLIVER MA, 1986, EARTH SURF PROCESSES, V11, P491 ONEILL RV, 1988, LANDSCAPE ECOL, V2, P63 PALMER MW, 1988, VEGETATIO, V75, P91 PALMER MW, 1990, COENOSES, V5, P79 PALMER MW, 1992, AM NAT, V139, P375 PARDOIGUZQUIZA E, 1993, MATH GEOL, V25, P177 PASTOR J, 1988, NATURE, V334, P55 PIANKA E, 1978, EOVLUTIONARY ECOLOGY PRICE JC, 1995, REMOTE SENS ENVIRON, V52, P55 RAMSTEIN G, 1989, INT J REMOTE SENS, V10, P1049 REED RA, 1993, J VEG SCI, V4, P329 RICHARDS JA, 1993, REMOTE SENSING DIGIT RIPLEY BD, 1981, SPATIAL STAT ROBERTSON GP, 1987, ECOLOGY, V68, P744 ROBERTSON GP, 1988, ECOLOGY, V69, P1517 ROSSI RE, 1992, ECOL MONOGR, V62, P277 SAUPE D, 1988, SCI FRACTAL IMAGES, P71 STEELE JH, 1978, SSPATIAL PATTERNS PL TILMAN R, 1982, RESOURCE COMPETITION TURNER MG, 1987, LANDSCAPE HETEROGENE TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER SJ, 1991, QUANTITATIVE METHODS, P17 UPTON GJG, 1985, SPATIAL DATA ANAL EX, V1 URBAN DL, 1987, BIOSCIENCE, V37, P119 VOSS RF, 1988, SCI FRACTAL IMAGES, P21 WALKER RB, 1954, ECOLOGY, V35, P259 WATT AS, 1947, J ECOL, V35, P1 WEBSTER R, 1989, REMOTE SENS ENVIRON, V29, P67 WEBSTER R, 1990, STAT METHODS SOIL LA WHITTAKER RH, 1975, COMMUNITIES ECOSYSTE WHITTAKER RH, 1977, THEORETICAL POPULATI, V12, P117 WIENS JA, 1989, FUNCT ECOL, V3, P385 WOOD D, 1988, DISCRETE COMPUT GEOM, V3, P349 WOODCOCK CE, 1988, REMOTE SENS ENVIRON, V25, P323 WU JG, 1994, ECOL MONOGR, V64, P447 0921-2973 Landsc. Ecol.ISI:000077256800005CSIC, Inst Ciencies Terra, E-08028 Barcelona, Spain. Lobo, A, CSIC, Inst Ciencies Terra, Marti Franques S-N, E-08028 Barcelona, Spain. alobo@ija.csic.esEnglish?0 Craig Loehle1990Home range:A fractal approach39-52Landscape Ecology51Bhome range, fractal, telemetry, foraging, behavior, spatial models1Most current methods for describing animal home range assume that it may be represented as a Euclidean type shape such as a bell shaped curve or a closed polygon. Landscape ecology has increasingly shown that ecological objects are more often highly fragmented and irregular. A fractal approach to description of animal home range was thus developed. For each point where the animal was observed, a circle centered on this point was first laid down to represent the area searched for prey by the animal during a short time interval. In this way the behavior of the animal and differences between species can be represented. Next, a fine grid is laid over the map and the height of each grid square computed by the number of circles that overlap that square. Then, the fractal dimension of the resultant 3-D surface is calculated at several scales. From an analysis of data from a hawk, the existence of perching behavior can be inferred, as well as the observation that at coarse scales the hawk behavior is self-similar and resembles a random walk. The home range thus analyzed in no way resembles a closed figure such as a polygon because it is highly fragmented. Further analysis showed that the fractal measures are relatively insensitive to sample size and to measurement error. Code is included for performing the analyses.<7 Loehle, C.1994 Home ranges reconsidered - reply147-149Landscape Ecology920TERRITORIALITY; FRACTALS; MINIMUM CONVEX POLYGONNoteJun://A1994NU09400007 HISI Document Delivery No.: NU094 Times Cited: 3 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1994NU09400007>LOEHLE, C, ARGONNE NATL LAB,DIV ENVIRONM RES,ARGONNE,IL 60439.English<7z#Loehle, C. Li, B. L. Sundell, R. C.1996MForest spread and phase transitions at forest-prairie ecotones in Kansas, USA225-235Landscape Ecology114fire; fractals; grassland; percolation; stability; succession INVASION PERCOLATION; GENERAL EPIDEMIC; MODELS; FIRES; LANDSCAPE; BEHAVIOR; AREAArticleAugThe spread of gallery forest habitat into upland areas is of substantial interest to resource managers because such spread has many implications for the management of grassland and forest habitats. This study used a dynamic percolation model to examine the potential rates of spread or invasion of forest in eastern Kansas. Aerial photos taken 16 years apart at the Fort Riley training base were used to calibrate a spatially explicit contagion model of forest spread to interpolate and extrapolate the forest spread processes. Results fit the actual pattern of spread well, as measured by both visual inspection and a multiscale fractal measure of pattern. Comparisons to a long-term fire-exclusion experiment in Geary County, Kansas, and to the Konza Prairie also provided validation. Both the simulation and the 100-year Geary County series showed an interesting pattern of forest spread. Spread was slow and steady until about 20% forest cover was reached, at which point the rate increased. We conclude that this self-accelerating response is due to spatial patterns created by the spreading forest that tend to accelerate the growth process after a critical point is reached. On the basis of theoretical study and experimental simulation of the percolation phase transitions, we suggest that fractal dimensions in a transient ecotone of binary mixtures (e.g., trees and grasses) should range between 1.56 and 1.8958, and the critical fractal dimension during ecotonal phase transitions should be 1.7951. This critical point of about 18.5% forest cover that we predicted was close to the observed result and might represent a phase transition at the forest-prairie ecotone.://A1996VC12700005 mISI Document Delivery No.: VC127 Times Cited: 31 Cited Reference Count: 45 Cited References: ABRAMS MD, 1986, S PRESCR BURN MIDW S, P73 ABRAMS MD, 1986, VEGETATIO, V65, P29 BRAGG TB, 1976, J RANGE MANAGE, V29, P19 BROADBENT SR, 1957, P CAMBRIDGE PHIL SOC, V53, P629 CARDY JL, 1985, J PHYS A, V18, L267 CASTI J, 1982, ECOLOGICAL MODELLING, V14, P293 COX JT, 1988, STOCH PROC APPL, V30, P171 FLORY PJ, 1941, J AM CHEM SOC, V63, P3083 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GATTO M, 1987, VEGETATIO, V69, P213 GOSZ JR, 1989, LANDSCAPE ECOLOGY, V3, P229 GOSZ JR, 1992, LANDSCAPE BOUNDARIES, P55 GRASSBERGER P, 1983, MATH BIOSCI, V63, P157 KAY JJ, 1992, ECOLOGICAL INDICATOR, V1, P159 KNIGHT CL, 1994, LANDSCAPE ECOL, V9, P117 KOTECKY R, 1993, PHASE TRANSITION MAT KUCERA CL, 1960, IOWA STATE J SCI, V34, P635 KUULASMAA K, 1982, J APPL PROBAB, V19, P745 KUULASMAA K, 1984, J APPL PROBAB, V21, P911 LENORMAND R, 1985, PHYS REV LETT, V54, P2226 LI BL, 1992, CHIN J ECOL, V11, P28 LI BL, 1993, ECOL MODEL, V69, P287 LI BL, 1995, IN PRESS ECOLOGICAL LOEHLE C, 1989, VEGETATIO, V79, P109 LOEHLE C, 1994, ECOL MODEL, V73, P311 LOEHLE C, 1995, IN PRESS ECOLOGICAL LUDWIG D, 1978, J ANIM ECOL, V47, P315 MCKAY G, 1984, J PHYS A, V17, L757 MILNE BT, 1995, IN PRESS ECOLOGY MOLLISON D, 1977, J ROY STAT SOC B MET, V39, P283 MOLLISON D, 1985, POPULATION DYNAMICS, P291 MOLLISON D, 1986, PHILOS T ROY SOC B, V314, P675 OHTSUKI T, 1986, J PHYS A, V19, L281 ONEILL RV, 1989, LANDSCAPE ECOL, V3, P193 REX KD, 1990, LANDSCAPE ECOL, V4, P249 RISSER PG, 1995, BIOSCIENCE, V45, P318 SAHIMI H, 1994, APPLICATINOS PERCOLA STAUFFER D, 1985, INTRO PERCOLATION TH STINCHCOMBE RB, 1990, FRACTALS NATURAL SCI, P17 STOCKMAYER WH, 1943, J CHEM PHYS, V11, P45 UZUNOV DI, 1993, INTRO THEORY CRITICA VONNIESSEN W, 1986, J PHYS A, V19, L289 WILKINSON D, 1983, J PHYS A-MATH GEN, V16, P3365 YUKALOV VI, 1990, LECT PHASE TRANSITIO ZALLEN R, 1983, PHYSICS AMORPHOUS SO 0921-2973 Landsc. Ecol.ISI:A1996VC12700005DLoehle, C, ARGONNE NATL LAB, 9700 S CASS AVE, ARGONNE, IL 60439 USA.English?6 Jon Loman1991lSmall mammal and raptor densities in habitat islands; area effects in a south Swedish agricultural landscape183-189Landscape Ecology53CThere was no significant correlation between the size of habitat islands in cropped fields and the density of field vole, bank vole, and common shrew populations during autumn. Despite this, winter densities of perching raptors were considerably higher in small islands than in large one. Explanations for this, apparently suboptimal, hunting pattern are discussed. The distribution should increase predation mortality for small rodents in small compared to large patches and may have been the cause of the higher winter mortality actually found for field voles in small patches.|?G YLong, Robert A. Donovan, Therese M. MacKay, Paula Zielinski, William J. Buzas, Jeffrey S.2011OPredicting carnivore occurrence with noninvasive surveys and occupancy modeling327-340Landscape Ecology263MarTerrestrial carnivores typically have large home ranges and exist at low population densities, thus presenting challenges to wildlife researchers. We employed multiple, noninvasive survey methods-scat detection dogs, remote cameras, and hair snares-to collect detection-nondetection data for elusive American black bears (Ursus americanus), fishers (Martes pennanti), and bobcats (Lynx rufus) throughout the rugged Vermont landscape. We analyzed these data using occupancy modeling that explicitly incorporated detectability as well as habitat and landscape variables. For black bears, percentage of forested land within 5 km of survey sites was an important positive predictor of occupancy, and percentage of human developed land within 5 km was a negative predictor. Although the relationship was less clear for bobcats, occupancy appeared positively related to the percentage of both mixed forest and forested wetland habitat within 1 km of survey sites. The relationship between specific covariates and fisher occupancy was unclear, with no specific habitat or landscape variables directly related to occupancy. For all species, we used model averaging to predict occurrence across the study area. Receiver operating characteristic (ROC) analyses of our black bear and fisher models suggested that occupancy modeling efforts with data from noninvasive surveys could be useful for carnivore conservation and management, as they provide insights into habitat use at the regional and landscape scale without requiring capture or direct observation of study species.!://WOS:000288808100003Times Cited: 1 0921-2973WOS:00028880810000310.1007/s10980-010-9547-1<7Lookingbill, T. Urban, D.2004aAn empirical approach towards improved spatial estimates of soil moisture for vegetation analysis417-433Landscape Ecology1944gravimetric and volumetric soil moisture content; HJ Andrews Experimental Forest; landscape-scale; regression; semivariance analysis; spatial variability FOREST ECOSYSTEM PROCESSES; MOUNTAINOUS TERRAIN; SOLAR-RADIATION; WATERSHED SCALE; OREGON; PRECIPITATION; COMMUNITIES; PATTERN; GROWTH; EVAPOTRANSPIRATIONArticleLandscape-level spatial estimates of soil water content are critical to understanding ecological processes and predicting watershed response to environmental change. Because soil moisture influences are highly variable at the landscape scale, most meteorological datasets are not detailed enough to depict spatial trends in the water balance at these extents. We propose a tactical approach to gather high-resolution field data for use in soil moisture models. Using these data, we (1) describe general soil moisture trends for a 6400 ha watershed in the Oregon Western Cascades, USA (2) use this description to identify environmental variables to stratify across in collecting data for a statistical explanatory model of soil moisture spatial pattern at the onset of seasonal drought, and (3) examine the spatial scale of variability in soil moisture measurements compared to the scale of variability in potential explanatory factors. The results indicate that soil moisture dynamics and controls are different for different soil depths across this mountainous watershed. Soil moisture variability exhibits complex spatial patterns that can be partially estimated (p to 50 percent of the variation accounted) with easily measurable climatic and terrain variables. The analysis incorporates both macroscale (climate) and mesoscale (topographic drainage and radiation) influences on the water balance. Without additional data on the distribution of edaphic and biotic factors, we are not able to model the variability of soil moisture at the microscale. The regression approach can be used to extrapolate field measurements across similar topographic areas to examine spatial patterns in forest vegetation and moisture-controlled ecological processes.://000221879000006 ISI Document Delivery No.: 827DM Times Cited: 4 Cited Reference Count: 47 Cited References: *ESRI, 1994, ARC INF 7 BAND LE, 1993, AGR FOREST METEOROL, V63, P93 BARRY RG, 1992, MOUNTAIN WEATHER CLI BEERS TW, 1966, J FOREST, V64, P691 BEVEN K, 1993, CHANNEL NETWORK HYDR BEVEN KJ, 1979, HYDROL SCI B, V24, P43 BOYER DG, 1990, SOIL SCI, V149, P383 BRADY NC, 1999, NATURE PROPERTIES SO CHRISTENSEN NL, 1996, ECOL APPL, V6, P665 CLARK JS, 1990, BIOGEOCHEMISTRY, V11, P1 CRAMER W, 1999, TERRESTRIAL BIOSPHER, P88 CRAVE A, 1997, HYDROL PROCESS, V11, P203 DALY C, 1994, J APPL METEOROL, V33, P140 DODORICO P, 2000, WATER RESOUR RES, V36, P2209 DUBAYAH R, 1995, INT J GEOGR INF SYST, V9, P405 FRANKLIN JF, 1988, NATURAL VEGETATION O GRAYSON RB, 1997, WATER RESOUR RES, V33, P2897 GRIER CC, 1977, ECOL MONOGR, V47, P373 HELVEY JD, 1972, SOIL SCI SOC AM P, V36, P954 HERKELRATH WN, 1991, WATER RESOUR RES, V27, P857 IVERSON LR, 1997, LANDSCAPE ECOL, V12, P331 JENNY H, 1980, SOIL RESOURE LEGENDRE P, 1989, VEGETATIO, V80, P107 LOOKINGBILL TR, 2003, AGR FOREST METEOROL, V114, P141 MACKAY DS, 1997, HYDROL PROCESS, V11, P1197 MCKEE A, 1998, B ECOL SOC AM, V79, P241 MILLER C, 1999, ECOSYSTEMS, V2, P76 MOORE ID, 1988, T AM SOC AGR ENG, V31, P1098 MOORE ID, 1991, HYDROL PROCESS, V5, P3 NEILSON RP, 1991, ECOTONES ROLE LANDSC, P31 NIKOLOV NT, 1992, ECOL MODEL, V61, P149 OHMANN JL, 1998, ECOL MONOGR, V68, P151 PARKER AJ, 1982, PHYSICAL GEOGR, V3, P160 PASTOR J, 1988, NATURE, V334, P55 PHILLIPS DL, 1992, AGR FOREST METEOROL, V58, P119 POST DA, 2001, ADV WATER RESOUR, V24, P1195 RICHARDSON CW, 1981, WATER RESOUR RES, V17, P182 RUNNING SW, 1987, CAN J FOREST RES, V17, P472 SMITH J, 2002, MAPPING THERMAL CLIM SOKAL RR, 1995, BIOMETRY STEPHENSON NL, 1990, AM NAT, V135, P649 STEPHENSON NL, 1998, J BIOGEOGR, V25, P855 URBAN DL, 2000, LANDSCAPE ECOL, V15, P603 VERTESSY RA, 1996, TREE PHYSIOL, V16, P221 WESTERN AW, 1998, HYDROL PROCESS, V12, P1851 YEAKLEY JA, 1998, HYDROL EARTH SYST SC, V2, P41 ZOBEL DB, 1976, ECOL MONOGR, V46, P135 0921-2973 Landsc. Ecol.ISI:000221879000006Duke Univ, Nicholas Sch Environm & Earth Sci, Durham, NC 27708 USA. Lookingbill, T, Univ N Carolina, Dept Geog, CB3220, Chapel Hill, NC 27599 USA. todd.lookingbill@unc.eduEnglishڽ7[Looy, Kris Cavillon, Cyril Tormos, Thierry Piffady, Jérémy Landry, Philippe Souchon, Yves2013pA scale-sensitive connectivity analysis to identify ecological networks and conservation value in river networks 1239-1249Landscape Ecology287Springer NetherlandsoEcological niche factor analysis Integral index connectivity Network analysis Hydro-morphological quality Otter 2013/08/01+http://dx.doi.org/10.1007/s10980-013-9869-x 0921-2973Landscape Ecol10.1007/s10980-013-9869-xEnglish[<7)Lopez, R. D. Davis, C. B. Fennessy, M. S.2001[Ecological relationships between landscape change and plant guilds in depressional wetlands43-56Landscape Ecology171depressional wetland ecological indicator ecological inertia fragmentation gradient island biogeography Ohio plant guild COLONIZATION VEGETATION ISLANDS LAKESArticlePlant guilds used to measure the relationships between wetland plant community characteristics and landscape change around 31 depressional wetlands in central Ohio, USA. Characteristics of certain plant guilds within each wetland site are correlated with changes in: (a) area of urban land cover, forest, grassland, agriculture, and open-water in the local vicinity of the wetland; (b) inter-wetland distance; and (c) wetland size (area). Taxa richness is negatively correlated with inter-wetland distance for all plant guilds, except submersed herbaceous plants. Taxa richness of the submersed herbaceous plant guild (usually less than 20% of the total number of plant species at a wetland) is positively correlated with the area of open-water in the local landscape and with the area of the wetland site itself. Significant positive correlations also exist between the area of open-water in the vicinity of the wetland and the proportion of submersed herbaceous plant taxa at the site, the number of native submersed herbaceous plant species, the submersed herbaceous plant perennial-to-annual ratio, and the number of avian-dispersed submersed herbaceous plant species at a site. The results suggest that a) the dominance of submersed herbaceous plant species at a site is related to dispersal constraints between wetlands, and (b) the relatively slower physiological response of woody plants to local landscape change may result in their contribution to greater,ecological inertia' in the plant community as a whole. For these reasons, relationships between the plant community and land cover change may not always be observed unless analyzed at the level of plant-guild.://000176014400004 J ISI Document Delivery No.: 559FF Times Cited: 4 Cited Reference Count: 54 Cited References: *OH DEP NAT RES, 1999, LIST INV THREAT INV *US ACOE, 1987, Y871 US ACOE DEP ARM *US EPA, 1990, EPA440590004 *US EPA, 1994, EPA841R94001 ADAMUS PR, 1990, EPA600390073 ENV RES ANDERSON JR, 1976, 964 USGS ANDREAS BK, 1995, WRPDE8 US ARM CORPS BRINSON M, 1993, WRPDE4 US ARM CORPS CATLING PM, 1986, CAN J BOT, V64, P724 CHAPIN FS, 1991, BIOSCIENCE, V41, P29 COWARDIN LM, 1979, US FISH WILDLIFE SER DAHL TE, 1990, WETLANDS LOSSES US 1 DERVOORT JN, 1979, J BIOGEOGR, V6, P301 DIAMOND JM, 1974, SCIENCE, V184, P803 DZWONKO Z, 1988, VEGETATIO, V76, P15 FALKNER E, 1994, AERIAL MAPPING METHO FENNESSY MS, 1998, ASSESSMENT WETLANDS FENNESSY MS, 1998, TESTING FLORISTIC QU FORMAN RTT, 1995, LAND MOSAICS GACIA E, 1994, FRESHWATER BIOL, V32, P73 GALATOWITSCH SM, 1996, ECOL APPL, V6, P102 GODWIN H, 1923, J ECOL, V11, P160 GREEN RH, 1979, SAMPLING DESIGN STAT HARRIS LD, 1984, FRAGMENTED FOREST IS JENSEN JR, 1996, INTRO DIGITAL IMAGE JONES KB, 2001, LANDSCAPE ECOL, V16, P301 KARR JR, 1997, EPA235R97001 U WASH KEDDY PA, 1993, ECOLOGICAL INTEGRITY LEIBOWITZ SG, 1992, EPA600R92167 LILLESAND TM, 1994, REMOTE SENSING IMAGE LOPEZ RD, 1999, THESIS LYON JG, 1981, THESIS MICHIGAN LYON JG, 2001, WETLAND LANDSCAPE CH MACARTHUR R, 1967, THEORY ISLAND BIOGEO MAGURRAN AE, 1988, ECOLOGICAL DIVERSITY MCDONNELL MJ, 1983, OECOLOGIA, V56, P109 MCDONNELL MJ, 1984, P 1 INT SEM METH LAN, V2 MOLLER TR, 1985, OIKOS, V45, P8 MUELLERDOMBOIS D, 1974, AIMS METHODS VEGETAT ODURR EP, 1985, BIOSCIENCE, V35, P419 OPDAM P, 1993, LANDSCAPE ECOLOGY ST PETERSON SA, 1996, EPA620R97002 REED PB, 1988, 88263 US FISH WILDL RIDLEY HN, 1930, DISPERSAL PLANTS WOR SIMBERLOFF DS, 1970, ECOLOGY, V51, P934 SIMPSON JW, 1994, LANDSCAPE ECOL, V9, P261 STRITTHOLT JR, 1995, CONSERV BIOL, V9, P1492 VANDERVALK AG, 1981, ECOLOGY, V62, P688 VOSS EG, 1972, GYMNOSPERMS MONOCOTS VOSS EG, 1985, DICOTS SAURURACEAE C VOSS EG, 1996, DICOTS PYROLACEAE CO WILHELM G, 1988, T 53 N AM WILDL NAT, P361 YODER C, 1991, P WAT QUAL STAND 21, P95 ZAR JH, 1984, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000176014400004Ohio State Univ, Sch Nat Resources, Columbus, OH 43210 USA. Lopez, RD, US EPA, Natl Exposure Res Lab, Div Environm Sci, Off Res & Dev, Las Vegas, NV 89193 USA. fennessym@kenyon.eduEnglishc<7CLopez-Barrera, F. Manson, R. H. Gonzalez-Espinosa, M. Newton, A. C.2007]Effects of varying forest edge permeability on seed dispersal in a neotropical montane forest189-203Landscape Ecology222oak; Quercus; highlands of Chiapas; rodents; acorn dispersal; seed predation; masting; edge contrast OLD FIELD EDGE; SMALL MAMMALS; ECOLOGICAL BOUNDARIES; RODENT POPULATIONS; HABITAT EDGES; TREE SEED; PREDATION; CHIAPAS; MEXICO; OAKArticleFebHard (high-contrast with pastures) and soft (low-contrast with old-fields) forest edges created by slash-and-burn agriculture have become common landscape features in regions dominated by neotropical montane forest. However, little is know about the impacts of such edge types on forest regeneration dynamics. The consequences of varying forest edge permeability for oak acorn dispersal were investigated in a forest mosaic in the Highlands of Chiapas, Mexico. Rates of acorn production and removal, as well as the abundance and composition of small mammal seed consumers, were monitored along these different edge types (hard vs. soft) at specific distances from forest edges into forest patches and adjacent grasslands during two consecutive years. Results show that acorn removal declined significantly only in grasslands of sites characterised by hard edges (Logistic regression, P < 0.05). Movements of metal-tagged acorns support the hypothesis that soft edges are more permeable to small mammals, with rodents moving acorns up to 15 m into grasslands of sites with soft edges. In sites with hard edges, higher rates of acorn dispersal were recorded from the forest edge towards the forest interior. Peromyscus spp. were the main acorn predators and/or dispersers of acorns present in our study sites. Rates of acorn removal during a non-masting year were greater than the subsequent mast-seeding year (85% removal within 138 days vs. 75% within 213 days), demonstrating that mast seeding may allow some seeds to escape predation. The implications of these results for oak dispersal and regeneration along edges in fragmented tropical forest landscapes are discussed.://000243823900004 ISI Document Delivery No.: 130UG Times Cited: 0 Cited Reference Count: 57 Cited References: BONFIL C, 1999, APPL VEG SCI, V2, P189 BOWERS MA, 1993, OECOLOGIA, V94, P247 BRIGGS JM, 1989, J MAMMAL, V70, P35 BROTHERS TS, 1992, CONSERV BIOL, V6, P91 CADENASSO ML, 2000, J ECOL, V88, P31 CADENASSO ML, 2001, CONSERV BIOL, V15, P91 CADENASSO ML, 2003, BIOSCIENCE, V53, P750 DESROCHERS A, 2003, LANDSCAPE ECOL, V18, P543 DONOVAN TM, 1997, ECOLOGY, V78, P2064 DUELLI P, 1990, BIOL CONSERV, V54, P193 FOX GA, 2000, DESIGN ANAL ECOLOGIC, P235 GONZALEZESPINOSA M, 1991, J VEG SCI, V2, P351 GRIBKO LS, 1995, TREE PLANTERS NOTES, V46, P143 HARPER KA, 2005, CONSERV BIOL, V19, P768 HARRINGTON GN, 2001, J TROP ECOL 2, V17, P225 HOLMQUIST JG, 1998, OIKOS, V81, P558 HONNAY O, 2002, FOREST ECOL MANAG, V161, P109 HORVATH A, 2001, STUD NEOTROP FAUNA E, V36, P169 HOVLAND N, 1999, OECOLOGIA, V121, P236 HOWELL NG, 1999, GUIDE BIRDS MEXICO N HUBBARD JA, 1999, J VEG SCI, V10, P739 JANSEN PA, 2001, NOURAGUES DYNAMICS P, P275 JANZEN DH, 1971, ANNU REV ECOL SYST, V2, P465 JENSEN TS, 1982, OECOLOGIA, V54, P184 KALCOUNISRUPPELL MC, 2002, J MAMMAL, V83, P614 KOLLMANN J, 2002, PLANT ECOL, V164, P249 LAURANCE WF, 2001, TRENDS ECOL EVOL, V16, P70 LIDICKER WZ, 1999, LANDSCAPE ECOL, V14, P333 LOPEZBARRERA F, 2003, THESIS U EDINBURGH E LOPEZBARRERA F, 2005, FOREST ECOL MANAG, V217, P67 LOPEZBARRERA F, 2006, FOREST ECOL MANAG, V225, P234 MANSON RH, 1998, ECOSCIENCE, V5, P183 MANSON RH, 1998, OIKOS, V82, P37 MANSON RH, 1999, LANDSCAPE ECOL, V14, P335 MANSON RH, 2001, ECOLOGY, V82, P3320 MEINERS SJ, 2002, AM J BOT, V89, P466 MEINERS SJ, 2003, PLANT ECOL, V168, P45 MUELLERDOMBOIS D, 1974, AIMS METHODS VEGETAT NIXON KC, 1993, BIOL DIVERSITY MEXIC, P447 OSTFELD RS, 1996, BIOSCIENCE, V46, P323 OSTFELD RS, 1997, ECOLOGY, V78, P1531 PRICE MV, 1986, SEED DISPERSAL, P191 QUINTANAASCENCI.PF, 1992, B TORREY BOT CLUB, V119, P6 REID FA, 1997, FIELD GUIDE MAMMALS RIES L, 2004, ANNU REV ECOL EVOL S, V35, P491 SANTOS T, 1997, FOREST ECOL MANAG, V98, P181 SCHNURR JL, 2002, OIKOS, V96, P402 SOKAL RR, 1998, BIOMETRY PRINCIPLES SONG SJ, 1999, ECOSCIENCE, V6, P521 SORK VL, 1984, ECOLOGY, V65, P1020 STAMPS JA, 1987, AM NAT, V129, P533 STEELE MA, 2001, J MAMMAL, V82, P35 STEVENS SM, 1998, BIOL CONSERV, V85, P1 STRAYER DL, 2003, BIOSCIENCE, V53, P723 WEATHERS KC, 2001, CONSERV BIOL, V15, P1506 WOLFF JO, 1996, J MAMMAL, V77, P850 ZOLLNER PA, 2000, LANDSCAPE ECOL, V15, P523 0921-2973 Landsc. Ecol.ISI:000243823900004INECOL AG, Inst Ecol, Dept Funct Ecol, Xalapa 91070, Veracruz, Mexico. Univ Edinburgh, Sch Geosci, Inst Environm & Atmospher Sci, Edinburgh EH9 3JU, Midlothian, Scotland. Coll So Borderlands, ECOSUR, Dept Terr Ecol & Systemat, Biodivers Conservat Div, Chiapas 29200, Mexico. Bournemouth Univ, Sch Conservat Sci, Poole BH12 5BB, Dorset, England. Lopez-Barrera, F, INECOL AG, Inst Ecol, Dept Funct Ecol, Km 2-5,Carretera Antigua Coatepec 351, Xalapa 91070, Veracruz, Mexico. fabiola@ecologia.edu.mxEnglishh|?E 2Lopez-Lopez, P. Liminana, R. Mellone, U. Urios, V.2010xFrom the Mediterranean Sea to Madagascar: Are there ecological barriers for the long-distance migrant Eleonora's falcon?803-813Landscape Ecology255 We examined the connection between landscape characteristics and behaviour of a long-distance migratory raptor. Our main goal was to test whether long-distance migratory birds adjust their migration programme according to the different characteristics of the habitats crossed during the journey with special emphasis in the so-called "ecological barriers", inhospitable environments such as deserts, ice fields, seas and mountain ranges, where the opportunities to fulfil energy requirements are low or absent and environmental factors could be extremely severe. To this end, 11 Eleonora's falcons were tracked by satellite telemetry in their ca. 9000 km autumn migration route from colonies located in Western Mediterranean to their wintering grounds in Madagascar during 2007 and 2008. Our results show that Eleonora's falcons migrated during day and night-time, adjusting migration speed and daily distance in relation to the crossed region. Unlike other migrant species, Eleonora's falcons did not avoid ecological barriers by making unnecessary detours around them or converging on narrow corridors. Nocturnal migration and higher daily distances were observed when flying across the Sahara Desert and the Mozambique Channel. The circadian pattern of activity budget shows that Eleonora's falcon relies on an internal navigation mechanism that works during both day and night. Finally, our results suggest that the Sahara is an ecological barrier not only for passerines but also for raptors migrating within the Palaearctic-African flyway.!://WOS:000276609800011Times Cited: 0 0921-2973WOS:00027660980001110.1007/s10980-010-9460-7?Y<Alison Loram Jamie Tratalos Philip H. Warren Kevin J. Gaston2007XUrban domestic gardens (X): the extent & structure of the resource in five major cities 601-615Landscape Ecology224CDomestic gardens - Green space - Housing - Land use - Urbanisation &Private domestic gardens are known to constitute a considerable proportion of “green space” in urban areas and are therefore of potential significance for maintaining biodiversity and ecosystem service provision in such areas. However, little is known about the actual size and nature of this resource. This study provides the first detailed audit and comparison of the size and structure of the domestic garden resource across different cities in the U.K. (Edinburgh, Belfast, Leicester, Oxford and Cardiff). The urban area of each city covered by domestic gardens ranged from 21.8% to 26.8% and was positively correlated with variation in human population density and housing density. In a random sample of at least 500 houses in each city, 99% had associated gardens, the mean areas of which ranged from 155.4 m2 to 253.0 m2 and were closely associated with housing type (terraced, semi-detached or detached houses). Relatively small gardens (< 400 m2) contributed disproportionately to the total garden area of each city, being more numerous than larger gardens. There was no clear relationship between garden area and distance to the edge of any of the cities. These and other results are discussed in terms of the potential role of urban gardens as wildlife habitats and the implications for housing policy.  <7l %Loss, S. R. Niemi, G. J. Blair, R. B.2012Invasions of non-native earthworms related to population declines of ground-nesting songbirds across a regional extent in northern hardwood forests of North America683-696Landscape Ecology275hermit thrush invasive earthworms lumbricus minnesota, USA ovenbird wisconsin, USA habitat fragmentation infectious-disease bird populations pairing success boreal forests managed forest united-states ovenbird landscapes minnesotaMayNon-native invasive earthworms (Lumbricus spp.) substantially change previously earthworm-free hardwood forests of North America by consuming the leaf litter layer, reducing cover and richness of herbaceous plants, and increasing dominance of sedges and grasses. These changes have been associated with reduced density of Ovenbirds (Seiurus aurocapilla) and Hermit Thrushes (Catharus guttatus) in 10-20 ha forest stands, and with reduced Ovenbird nesting success. Whether earthworms reduce songbird populations across a regional extent is unclear. We investigated relationships among Lumbricus, vegetation structure, landscape patterns of forest cover, and density of four ground-nesting songbird species at points scattered across the Chequamegon-Nicolet (Wisconsin) and Chippewa (Minnesota) National Forests, USA. In both national forests, Ovenbird density was significantly lower at invaded points than Lumbricus-free points, but only in sugar maple (Acer saccharum) and sugar maple/basswood (Tilia americana) (hereafter, maple-basswood) woodlands. Density of the Hermit Thrush, Black-and-white Warbler (Mniotilta varia), and Veery (Catharus fuscescens) did not differ in relation to Lumbricus. In maple-basswood forests, Lumbricus biomass was the best predictor of Ovenbird density, with greater biomass associated with reduced density. Vegetation structure and landscape pattern variables received weak support as density predictors. Across all forest types, Ovenbird density was most strongly related to forest cover within 500 and 1,000 m radii. Our results suggest that earthworm invasions may pose a regional threat to Ovenbirds within maple-basswood forests of the U.S. northern Midwest.://000303056100006-929JC Times Cited:1 Cited References Count:63 0921-2973Landscape EcolISI:000303056100006Loss, SR Smithsonian Migratory Bird Ctr, Natl Zool Pk,Box 37012,MRC 5503, Washington, DC 20013 USA Smithsonian Migratory Bird Ctr, Natl Zool Pk,Box 37012,MRC 5503, Washington, DC 20013 USA Smithsonian Migratory Bird Ctr, Washington, DC 20013 USA Univ Minnesota, Conservat Biol Grad Program, St Paul, MN 55108 USA Univ Minnesota, Nat Resources Res Inst, Dept Biol, Duluth, MN 55812 USA Univ Minnesota, Dept Fisheries Wildlife & Conservat Biol, St Paul, MN 55108 USADOI 10.1007/s10980-012-9717-4English?Louis, R. Iverson20037Book review, Early Forestry and Conservation in America208-210Landscape Ecology182\This revised version was published online in August 2006 with corrections to the Cover Date.*http://dx.doi.org/10.1023/A:1024415805463 D10.1023/A:1024415805463 Louis R. Iverson Email: liverson@fs.fed.us cLouis R. Iverson1 (1) USDA Forest Service Northeastern Research Station Delaware, OH 43015, USA  |?9 =Louzada, J. Lima, A. P. Matavelli, R. Zambaldi, L. Barlow, J.2010wCommunity structure of dung beetles in Amazonian savannas: role of fire disturbance, vegetation and landscape structure631-641Landscape Ecology254xUnderstanding the relative influence of environmental and spatial variables in driving variation in species diversity and composition is an important and growing area of ecological research. We examined how fire, local vegetation structure and landscape configuration interact to influence dung beetle communities in Amazonian savannas, using both hierarchical partitioning and variance partitioning techniques to quantify independent effects. We captured a total of 3,334 dung beetles from 15 species at 22 savanna plots in 2003. The species accumulation curve was close to reaching an asymptote at a regional scale, but curves were variable at the plot level where total abundance ranged from 17 to 410 individuals. Most plots were dominated by just three species that accounted for 87.7% of all individuals sampled. Hierarchical partitioning revealed the strong independent and positive effect of percentage forest cover in the surrounding landscape on total dung beetle abundance and species richness, and richness of uncommon species and the tunneler guild. Forest cover also had a negative effect on community evenness. None of the variables that related to fire affected community metrics. The minimal direct influence of fire was supported by variance partitioning: partialling out the influence of spatial position and vegetation removed all of the individual explanation attributable to fire, whereas 8% of the variance was explained by vegetation and 28% was explained by spatial variables (when partialling out effects of the other two variables). Space-fire and vegetation-fire joint effects explained 14 and 10% of the dung beetle community variability, respectively. These results suggest that much of the variation in dung beetle assemblages in savannas can be attributed to the spatial location of sites, forest cover (which increased the occurrence of uncommon species), and the indirect effects of fires on vegetation (that was also dependent on spatial location). Our study also highlights the utility of partitioning techniques for examining the importance of environment variables such as fire that can be strongly influenced by spatial location.!://WOS:000275444100011Times Cited: 0 0921-2973WOS:00027544410001110.1007/s10980-010-9448-3ڽ7)!Lovell, SarahTaylor Taylor, JohnR2013dSupplying urban ecosystem services through multifunctional green infrastructure in the United States 1447-1463Landscape Ecology288Springer Netherlands]Social–ecological systems Resilience Transformation Multifunctionality Green infrastructure 2013/10/01+http://dx.doi.org/10.1007/s10980-013-9912-y 0921-2973Landscape Ecol10.1007/s10980-013-9912-yEnglish)<7uKLovett-Doust, J. Biernacki, M. Page, R. Chan, M. Natgunarajah, R. Timis, G.2003{Effects of land ownership and landscape-level factors on rare-species richness in natural areas of southern Ontario, Canada621-633Landscape Ecology186biodiversity conservation habitat land ownership landscape-level effects land-use natural areas rare species fragmentation BIODIVERSITY CONSERVATION ECOSYSTEM USA MANAGEMENTArticle Surprisingly few studies have considered the extent to which the nature of the ownership of land is associated with differences in biodiversity. We analysed ownership and other landscape-level effects on rare-species richness for both globally- and regionally-rare biota (including birds, herpetofauna, butterflies, mammals, and plants) in 289 designated natural areas (NAs) in southern Ontario, Canada. Information about each NA - including area, number of plant communities, ownership status and details of species diversity were collected from published sources. Length of perimeter of NA, relative isolation, and an estimate of fragmentation were measured using image analysis and GIS techniques. NAs were in general relatively small, with mean area of 158 ha (median 85 ha, range from 0.9 to 1278 ha) for private NAs; public NAs had mean area of 132 ha (median 16 ha, range from 0.1 to 1481 ha). Mean number of plant communities was 4.6 (median 4, range 1- 13) at private NAs and 3.8 (median 3, range 1- 16) at public NAs. Our results show that, of several landscape-level factors, area had the greatest effects on rare-species richness and other biotic indices. Effects of area were followed by effects of plant community diversity, however this was itself significantly affected by area and the extent of perimeter of the NA. Both these factors were followed by effects of ownership of the NA and by effects of isolation of the NA (represented by minimum distance to nearest NA and by number of NAs in 10 km radius). Other landscape-level factors did not appear to have overall significant effects. Variation in area accounted for 0.1% to 29% of variation in number of rare species, with lower values for globally- rare, than for regionally-rare taxa. For all biotic groups, public ownership of NAs was associated with significantly greater rare-species richness compared to private ownership, even after other factors such as area were controlled. For all globally- rare biota except butterflies, area of NA had greater effects on rare-species richness than did ownership. Richness of regionally-rare birds was more affected by plant community diversity than by area of NA. Number of recorded plant communities accounted from 2.1% of variation in number of globally- rare plant species to as high as 31% of variation in regionally-rare butterflies. The diversity of plant communities was itself influenced by total site area (accounting for 45% of variation), extent of elongation of the NA, and both external- and interior-edge perimeters. Public NAs had greatest numbers of rare biota and so should be a significant focus for conservation programs. Smaller, privately-owned patches of natural area dominate (by number and area) in this densely populated region and their significance should not be overlooked.://000185827300006 M ISI Document Delivery No.: 730JH Times Cited: 4 Cited Reference Count: 52 Cited References: *GOV ONT, 1997, CENS STAT 1996 *GOV ONT, 2000, ONT POP PROJ 1999 20 *METR TOR REG CONS, 1982, ENV SIGN AR STUD *NAT HER INF CTR, 1999, LISTS ONT SPEC *US GOV ACC OFF, 1995, GAORCED9516 ADGER WN, 2000, ECOL ECON, V35, P75 ALLEN GM, 1990, CONSERVING CAROLINIA BROWNELL VR, 1995, LOWER TRENT REGION N, V1 BROWNELL VR, 1995, LOWER TRENT REGION N, V2 BURKE DM, 2000, ECOL APPL, V10, P1749 CAIRNS J, 1996, BIODIVERS CONSERV, V5, P1085 COSTANZA R, 1997, NATURE, V387, P253 CRAIG J, 2000, ANNU REV ECOL SYST, V31, P61 CROW TR, 1999, LANDSCAPE ECOL, V14, P449 DAILY G, 1997, NATURES SERVICES SOC DALE VH, 2000, ECOL APPL, V10, P639 DELCOURT HR, 2000, N AM TERRESTRIAL VEG, P357 FALKNER MB, 1997, NAT AREA J, V17, P324 FREEMARK KE, 1986, BIOL CONSERV, V31, P95 GOBIN A, 2001, LANDSCAPE URBAN PLAN, V55, P185 GROVES CR, 2000, PRECIOUS HERITAGE ST, P275 HALE ML, 2001, SCIENCE, V293, P2246 HEAGY A, 1993, HAMILTONWENTWORTH NA, V1 HEAGY A, 1995, HAMILTONWENTWORTH NA, V2 HOLLING CS, 1996, CONSERV BIOL, V10, P328 JAMES A, 2000, NATURE, V404, P120 KAMSTRA J, 1995, LIFE SCI INVENTORY E KEITT TH, 1997, CONSERV ECOL, V1 KINDSCHER K, 1997, NAT AREA J, V17, P131 LARSON BM, 1999, WOODLAND HERITAGE SO LEE H, 1998, ECOLOGICAL LAND CLAS LOVETTDOUST J, 2001, LANDSCAPE ECOL, V16, P743 MASTER LL, 1991, CONSERV BIOL, V5, P559 MCARTHUR R, 1967, THEORY ISLAND BIOGEO NEWMASTER SG, 1998, ONTARIO PLANT LIST OLDHAM MJ, 1983, ENV SIGNIFICANT AREA PEARCE C, 1993, SIZE INTEGRITY STAND, P100 PIMM SL, 1995, SCIENCE, V269, P347 PLATT RH, 1996, LAND USE SOC RAMSEY R, 1988, INFORMATION B ONTARI RICKETTS TH, 1999, TERRESTRIAL ECOREGIO RILEY JL, 1996, ECOLOGICAL SURVEY NI, V1 SALA OE, 2000, SCIENCE, V287, P1770 SPIES TA, 1994, ECOL APPL, V4, P555 STEIN BA, 1995, OUR LIVING RESOURCES, P389 THEBERGE JB, 1989, LEGACY NATURAL HIST THOMAS RC, 1997, BIOL CONSERV, V82, P243 VITOUSEK PM, 1997, SCIENCE, V277, P494 WHITELAW S, 1996, HEALTH EDUC RES, V11, P349 WILSON E, 1992, DIVERSITY LIFE WRIGHT RG, 2001, BIOL CONSERV, V98, P97 ZAR J, 1999, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000185827300006Univ Windsor, Dept Biol Sci, Windsor, ON N9B 3P4, Canada. Univ Memphis, Dept Biol, Memphis, TN 38152 USA. Lovett-Doust, J, Univ Windsor, Dept Biol Sci, Windsor, ON N9B 3P4, Canada.English <7Lovett-Doust, J. Kuntz, K.2001Land ownership and other landscape-level effects on biodiversity in southern Ontario's Niagara Escarpment Biosphere Reserve, Canada743-755Landscape Ecology168sbiodiversity conservation land management landscape ecology Niagara Escarpment ownership CONSERVATION ECOSYSTEM USAArticleWe investigated effects of landscape-level factors on measures of biodiversity using published descriptions for 98 significant natural areas along the Niagara Escarpment. This is a 725 km, largely forested, Paleozoic limestone escarpment that, excepting the Great Lakes, is the most prominent topographical feature of southern Ontario, Canada. Results show highly significant differences in mean site size and extent of forest interior among natural areas of different ownership classes, with larger and more forested sites being under mixed (private + public) ownership, but no significant difference between sites of public and private ownership. Analysis of covariance demonstrated that after controlling for differences in landscape-level factors (total size of natural area, extent of forest interior, extent of landform heterogeneity and geographic location), most measures of biotic diversity (including the number of vegetation community types, provincially rare vascular plants, and regionally and locally rare breeding birds) differed significantly among sites of private, public and mixed ownership. In general, values at public and mixed ownership sites were greatest, with significantly lower biodiversity values at privately-owned sites. Furthermore it would seem not to be a product of public bodies having historically purchased the largest sites or most-forested sites, since there is no significant difference between the mean size of publically-owned and privately-owned sites. Results of stepwise multiple regression confirm the well known relation between size of a natural area and variation in both total, and rare species diversity. Since public sites have generally more species than private sites, they are essential elements of any conservation network.://000175490900006 ISI Document Delivery No.: 550EP Times Cited: 5 Cited Reference Count: 20 Cited References: *NHIC, 1999, LISTS ONT SPEC BURKE DM, 2000, ECOL APPL, V10, P1749 BURKE VJ, 2000, LANDSCAPE ECOL, V15, P1 CADOTTE MW, 2001, UNPUB TAXONOMIC ECOL CROW TR, 1999, LANDSCAPE ECOL, V14, P449 DAILY GC, 2000, NATURE, V403, P243 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY GLENN SM, 1989, J BIOGEOGR, V16, P261 GROVES CR, 2000, PRECIOUS HERITAGE ST, P275 HARDIN G, 1968, SCIENCE, V162, P1243 JAMES A, 2000, NATURE, V404, P120 KINDSCHER K, 1997, NAT AREA J, V17, P131 LARSON BM, 1999, WOODLAND HERITAGE SO LOVETTDOUST J, 2001, UNPUB LAND OWNERSHIP NORTEN DA, 2000, CONSERV BIOL, V14, P1221 PEARCE C, 1993, SIZE INTEGRITY STAND, P100 PICKETT STA, 1978, BIOL CONSERV, V13, P27 RILEY JL, 1996, 9601 SR ONT MIN NAT THOMAS RC, 1997, BIOL CONSERV, V82, P243 WEAVER M, 1981, J BIOGEOGR, V8, P199 0921-2973 Landsc. Ecol.ISI:000175490900006|Univ Windsor, Dept Biol, Windsor, ON N9B 3P4, Canada. Lovett-Doust, J, Univ Windsor, Dept Biol, Windsor, ON N9B 3P4, Canada.English |?> +Lozano, F. J. Suarez-Seoane, S. De Luis, E.2010Effects of wildfires on environmental variability: a comparative analysis using different spectral indices, patch metrics and thematic resolutions697-710Landscape Ecology255Knowledge on environmental variability and how it is affected by disturbances is crucial for understanding patterns of biodiversity and determining adequate conservation strategies. The aim of this study is to assess environmental variability in patches undergoing post-fire vegetation recovery, identifying trends of change and their relevant drivers. We particularly evaluate: the value of three spectral indices derived from Landsat satellite data [Normalized Burn Ratio (NBR), Normalized Difference Vegetation Index (NDVI) and Wetness Component of the Tasseled Cap Transformation (TCW)] for describing secondary succession; the effectiveness of three metrics (diversity, evenness and richness) as indicators of patch variability; and how thematic resolution can affect the perception of environmental variability patterns. While the system was previously characterised as highly resilient from estimations of vegetation cover, here we noted that more time is required to fully recover pre-fire environmental variability. Using mean diversity as indicator of patch variability, we found similar patterns of temporal change for the three spectral indices (NBR, NDVI and TCW). Analogous conclusions could be drawn for richness and evenness. Patch variability, measured as diversity, showed consistent patterns across thematic resolutions, although values increased with the number of spectral classes. However, when the variance of diversity was plotted against thematic resolution, different scale dependencies were detected for those three spectral indices, yielding a dissimilar perception of patch variability. In general terms, NDVI was the best performing spectral index to assess patterns of vegetation recovery, while TCW was the worst. Finally, burned patches were classified into three classes with similar trends of change in environmental variability, which were strongly related to fire severity, elevation and vegetation type.!://WOS:000276609800004Times Cited: 0 0921-2973WOS:00027660980000410.1007/s10980-010-9453-6|?.Lu, Nan Fu, Bojie Jin, Tiantian Chang, Ruiying2014Trade-off analyses of multiple ecosystem services by plantations along a precipitation gradient across Loess Plateau landscapes 1697-1708Landscape Ecology2910DecTrade-off is defined as a situation where one ecosystem service (ES) increases while another decreases. In a broader sense, trade-off also refers to unidirectional changes with uneven paces or rates in ESs. Although trade-off analysis for multiple ESs is more integral for ecosystem assessment and management, studies regarding trade-offs are rare in the literature, especially at the landscape scale or across large environmental gradients. Here, we evaluated the co-variations of multiple ESs of black locust (Robinia pseudoacacia) plantations along a precipitation gradient (400-650 mm) on the Loess Plateau using a quantitative trade-off approach. The multiple ESs had complex relationships, with significant regional variations along the gradient. Aboveground carbon, soil organic carbon (SOC), soil total nitrogen (STN), and soil water content (SWC) showed increasing trends with precipitation, but understory plant diversity (UPD) did not. The highest trade-offs were between UPD and SWC and the lowest trade-offs were between SOC and STN among all of the ES pairs. The differences in the trade-offs of varied ES combinations could be the result of unique competition relationships, mass allocation strategies, and time lags. Stand age appeared to be another critical variable in determining the values of ESs and their trade-offs along the precipitation gradient. The decreasing SWC with stand age indicated that the gaining of the other ESs was at the cost of SWC consumption. Because multiple ESs and their trade-offs exhibit high spatial variations across the landscape, spatially explicit management is needed to maintain the benefits while mitigating negative impacts in this water-limited landscape.!://WOS:000346920900006Times Cited: 1 0921-2973WOS:00034692090000610.1007/s10980-014-0101-4ڽ7 :Luck, GaryW Smallbone, Lisa Threlfall, Caragh Law, Bradley2013ZPatterns in bat functional guilds across multiple urban centres in south-eastern Australia455-469Landscape Ecology283Springer Netherlands~Australia Bat activity Bat diversity Bayesian analysis Functional traits Guilds Microchiroptera Urban ecology Urban landscapes 2013/03/01+http://dx.doi.org/10.1007/s10980-012-9842-0 0921-2973Landscape Ecol10.1007/s10980-012-9842-0English5<7Luck, M. Wu, J. G.2002oA gradient analysis of urban landscape pattern: a case study from the Phoenix metropolitan region, Arizona, USA327-339Landscape Ecology174gradient analysis land use pattern landscape metrics urban ecology urbanization CELLULAR-AUTOMATA ECOLOGY ECOSYSTEM FORM DYNAMICS BALANCEArticleTUrbanization is arguably the most dramatic form of land transformation that profoundly influences biological diversity and human life. Quantifying landscape pattern and its change is essential for the monitoring and assessment of ecological consequences of urbanization. Combining gradient analysis with landscape metrics, we attempted to quantify the spatial pattern of urbanization in the Phoenix metropolitan area, Arizona, USA. Several landscape metrics were computed along a 165 km long and 15 km wide transect with a moving window. The research was designed to address four research questions: How do different land use types change with distance away from the urban center? Do different land use types have their own unique spatial signatures? Can urbanization gradients be detected using landscape pattern analysis? How do the urban gradients differ among landscape metrics? The answers to these questions were generally affirmative and informative. The results showed that the spatial pattern of urbanization could be reliably quantified using landscape metrics with a gradient analysis approach, and the location of the urbanization center could be identified precisely and consistently with multiple indices. Different land use types exhibited distinctive, but not necessarily unique, spatial signatures that were dependent on specific landscape metrics. The changes in landscape pattern along the transect have important ecological implications, and quantifying the urbanization gradient, as illustrated in this paper, is an important first step to linking pattern with processes in urban ecological studies.://000178391000003 l ISI Document Delivery No.: 600LF Times Cited: 32 Cited Reference Count: 58 Cited References: ALLEN PM, 1979, J SOC BIOL STRUCT, V2, P269 ANTROP M, 2000, LANDSCAPE URBAN PLAN, V50, P43 BAKER LA, 2001, ECOSYSTEMS, V4, P582 BATTY M, 1989, ENVIRON PLANN A, V21, P1447 BATTY M, 1997, J AM PLANN ASSOC, V63, P266 BLAIR R, 1996, ECOL APPL, P506 BREUSTE J, 1998, URBAN ECOLOGY BURGESS EW, 1925, CITY, P47 CHRISTALLER W, 1933, CENTRAL PLACES SO GE COLLINS JP, 2000, AM SCI, V88, P416 COOK EA, 1991, LANDSC RES, V16, P8 COUCLELIS H, 1985, ENVIRON PLANN A, V17, P585 FORESMAN TW, 1997, URBAN ECOSYSTEMS, V1, P201 FROHN RC, 1998, REMOTE SENSING LANDS GRIMM NB, 2000, BIOSCIENCE, V50, P571 HARRIS CD, 1945, ANN AM ACAD POLIT SS, V242, P7 HESS G, 1994, LANDSCAPE ECOL, V9, P3 HESS GR, 1997, LANDSCAPE ECOL, V12, P309 HOBBS ER, 1988, LANDSCAPE ECOLOGY, V1, P141 HOYT H, 1939, STRUCTURE GROWTH RES HUNSAKER CT, 1994, LANDSCAPE ECOL, V9, P207 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 JENERETTE GD, 2001, LANDSCAPE ECOL, V16, P611 KNOWLESYANEZ K, 1999, HIST LAND USE PHASE KOWARIK I, 1990, URBAN ECOL, P45 LOSCH A, 1954, EC LOCATION LOUCKS OL, 1994, ECOLOGICAL CITY, P49 LUCK MA, 2001, ECOSYSTEMS, V4, P782 MCDONNELL MJ, 1990, ECOLOGY, V71, P1232 MCDONNELL MJ, 1997, URBAN ECOSYSTEMS, V1, P21 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MCINTYRE NE, 2001, URBAN ECOSYST, V4, P5 NAVEH Z, 1984, LANDSCAPE ECOLOGY TH ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PARK RE, 1925, CITY PICKETT STA, 1997, URBAN ECOSYSTEMS, V1, P185 PORTUGALI J, 2000, SELF ORG CITY POUYAT RV, 1991, WATER AIR SOIL POLL, V57, P797 POUYAT RV, 1995, J ENVIRON QUAL, V24, P516 REDMAN CL, 1999, ECOSYSTEMS, V2, P296 SCHWEITZER F, 1997, SELF ORG COMPLEX STR SUKOPP H, 1990, URBAN ECOLOGY PLANTS, P2 SUKOPP H, 1998, URBAN ECOL, P3 TOBLER W, 1979, PHILOS GEOGRAPHY, P379 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 VONTHUNEN JH, 1825, ISOLIERTE STAAT BEZI WHITE R, 1993, ENVIRON PLANN A, V25, P1175 WHITTAKER RH, 1975, COMMUNITIES ECOSYSTE WILSON AG, 1976, ENVIRON PLANN A, V8, P351 WILSON AG, 1981, CATASTROPHY THEORY B WONG D, 1990, GEOGRAFISKA ANN B, V72, P89 WU J, 2000, GEOGRAPHICAL INFORMA, V6, P6 WU J, 2000, LANDSCAPE ECOLOGY PA WU J, 2002, IN PRESS ECOL MODELL WU JG, 1995, Q REV BIOL, V70, P439 ZHU W, 1999, SOIL BIOL BIOCHEM, P1091 ZIPPERER WC, 2000, ECOL APPL, V10, P685 0921-2973 Landsc. Ecol.ISI:000178391000003Arizona State Univ, Dept Plant Biol, Landscape Ecol & Modeling Lab, Tempe, AZ 85287 USA. Wu, JG, Arizona State Univ, Dept Plant Biol, Landscape Ecol & Modeling Lab, Tempe, AZ 85287 USA.English <7m OLudford, A. Cole, V. J. Porri, F. McQuaid, C. D. Nakin, M. D. V. Erlandsson, J.2012[Testing source-sink theory: the spill-over of mussel recruits beyond marine protected areas859-868Landscape Ecology276connectivity intertidal metapopulation marine reserve mussels source-sink perna-perna southern-africa brown mussel rocky shores tidal height reserves management settlement dynamics habitatJulSource-sink theory has contributed to our understanding of the function of protected areas, particularly due to their role as population sources. Marine reserves are a preferred management tool for the conservation of natural populations, creating areas of good quality habitat and thus improving population connectivity by enhancing larval supply and recruitment among shores. Despite recent advances in the study of protected areas in the context of the source-sink theory, rigorous and empirical testing of marine reserves as metapopulation sources for the adjacent areas remain largely unexplored. We investigated the role of marine reserves as population sources, whether there was spill-over beyond the reserve boundaries and if so, whether spill-over was directional. We measured percentage cover and recruitment of mussels (Perna perna) at two reserves and two comparably sized exploited control areas on the south-east coast of South Africa where unprotected populations are severely affected by artisanal exploitation. Adult abundances were enhanced within reserves, but decreased towards their edges. We predicted that recruitment would mirror adult abundances and show directionality, with northern shores having greater recruitment following the prevalent northward flow of near-shore currents. There were, however, no correlations between adult abundances and recruitment for any months or shores, and no clear spatial patterns in recruitment (i.e. similar patterns occurred at reserves and controls). The results emphasise that, while reserves may act as important refuges by protecting adult abundances, their influence on promoting recovery of near-by exploited shores through larval spill-over may be overestimated.://000305218000006-958DZ Times Cited:0 Cited References Count:60 0921-2973Landscape EcolISI:000305218000006Ludford, A Rhodes Univ, Coastal Res Grp, Dept Zool & Entomol, POB 94, Grahamstown, South Africa Rhodes Univ, Coastal Res Grp, Dept Zool & Entomol, POB 94, Grahamstown, South Africa Rhodes Univ, Coastal Res Grp, Dept Zool & Entomol, Grahamstown, South Africa Walter Sisulu Univ, Dept Zool, ZA-5100 Mthatha, South Africa Novia Univ Appl Sci, Abo Akad Univ, ARONIA Coastal Zone Res Team, Ekenas 10600, Finland Stockholm Univ, Dept Syst Ecol, S-10691 Stockholm, SwedenDOI 10.1007/s10980-012-9739-yEnglish <79Ludwig, J. A. Bastin, G. N. Wallace, J. F. McVicar, T. R.2007QAssessing landscape health by scaling with remote sensing: when is it not enough?163-169Landscape Ecology222_drylands; indicators; monitoring; rangelands; scale VEGETATION CONDITION; RANGELANDS; AUSTRALIAArticleFebAssessment of the health of landscapes, by monitoring their condition over space and time, is needed to better understand the processes for sustaining or, in many cases, repairing them. Remote sensing is a tool that can efficiently identify and assess areas of landscape damage at different scales and help land managers solve specific problems. Remote sensing may appear to be a panacea for all monitoring situations but sometimes the information it provides is not enough by itself. In this paper we give examples of both scenarios-when remote sensing alone is adequate and when it is not. When remotely sensed data alone is not sufficient, monitoring problems can be solved by incorporating additional finer scale data. We use a five-step procedure based on scaling to help land managers answer the question: when is remote sensing data alone not sufficient to underpin the information needs required to achieve a specific management goal?://000243823900001 ~ISI Document Delivery No.: 130UG Times Cited: 0 Cited Reference Count: 34 Cited References: *MILL EC ASS, 2003, EC HUM WELL BEING FR ASH A, 2004, HLTH RANGELANDS PRIN, P69 BARTLEY R, 2006, IN PRESS HYDROLOGY P BASTIN GN, 2005, AUSTR COLLABORATIVE BASTIN GN, 2006, ECOL MANAG RESTOR S1, V7, S71 BROOKER L, 2002, LANDSCAPE URBAN PLAN, V60, P185 CACCETTA PA, 2000, P 10 AUSTR REM SENS, P97 GUNDERSON LH, 2002, PANARCHY UNDERSTANDI HOBBS RJ, 1990, AUSTR ECOSYSTEMS 200, P93 LAMBECK RJ, 1993, ASSESSMENT CONSERVAT LAMBECK RJ, 1999, 2 URL DEP ENV HERT B LUDWIG JA, 2005, ECOL SOC, V10 LUDWIG JA, 2006, IN PRESS ECOL INDIC MCVICAR TR, 1998, AGR SYST, V57, P399 MCVICAR TR, 2002, IAR MONOGRAPH, V84, P205 MCVICAR TR, 2003, REV PREDICTIVE MODEL PATIL GP, 2002, MANAGING HLTH ECOSYS, P559 PRINCE SD, 2002, GLOBAL DESERTIFICATI, P23 PRINGLE HJR, 2006, IN PRESS LANDSC ECOL, V21 RYAN P, 2004, ECOL MANAGE RESTOR, V5, P85 SAUNDERS DA, 1987, NATURE CONSERVATION SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SMITH DMS, 2000, AUSTR J ENV MANAGEME, V7, P190 TONGWAY DJ, 2004, LANDSCAPE FUNCTION A WALLACE J, 2006, ECOL MANAG RESTOR S1, V7, S31 WALLACE JF, 1998, STATE ENV TECHNICAL WALLACE JF, 2004, AUSTRAL ECOL, V29, P100 WESSMAN CA, 2006, SCALING UNCERTAINTY, P147 WHITE DH, 2000, AGR SCI, V13, P27 WIENS JA, 1989, FUNCT ECOL, V3, P385 WOINARSKI JCZ, 2003, RANGELAND J, V25, P157 WOODCOCK CE, 1987, REMOTE SENS ENVIRON, V21, P311 WU J, 1999, CANADIAN J REMOTE SE, V25, P367 WU J, 2006, SCALING UNCERTAINTY, V3 0921-2973 Landsc. Ecol.ISI:000243823900001Trop Savannas Cooperat Res Ctr, Atherton, Qld 4883, Australia. CSIRO Sustainable Ecosyst, Atherton, Qld 4883, Australia. CSIRO Sustainable Ecosyst, Ctr Arid Zone Res, Alice Springs, NT 0871, Australia. CSIRO Math & Informat Sci, Floreat, WA 6151, Australia. CSIRO Land & Water, Canberra, ACT 2601, Australia. eWater Cooperat Res Ctr, Canberra, ACT 2601, Australia. Ludwig, JA, Trop Savannas Cooperat Res Ctr, POB 780, Atherton, Qld 4883, Australia. john.ludwig@csiro.auEnglishi<7HLudwig, J. A. Eager, R. W. Bastin, G. N. Chewings, V. H. Liedloff, A. C.2002GA leakiness index for assessing landscape function using remote sensing157-171Landscape Ecology172landscape metrics patch cover patch orientation patch size spatial pattern tropical savanna vegetation patchiness VEGETATION PATCHES SEMIARID WOODLANDS SPATIAL PATTERNS SOIL-EROSION WIND EROSION TIGER BUSH COVER AUSTRALIA RUNOFF SIZEArticleEThe cover, number, size, shape, spatial arrangement and orientation of vegetation patches are attributes that have been used to indicate how well landscapes function to retain, not 'leak', vital system resources such as rainwater and soil. We derived and tested a directional leakiness index (DLI) for this resource retention function. We used simulated landscape maps where resource flows over map surfaces were directional and where landscape patch attributes were known. Although DLI was most strongly related to patch cover, it also logically related to patch number, size, shape, arrangement and orientation. If the direction of resource flow is multi-directional, a variant of DLI, the multi-directional leakiness index (MDLI) can be used. The utility of DLI and MDLI was demonstrated by applying these indices to three Australian savanna landscapes differing in their remotely sensed vegetation patch attributes. These leakiness indices clearly positioned these three landscapes along a function-dysfunction continuum, where dysfunctional landscapes are leaky (poorly retain resources).://000177049100004 R ISI Document Delivery No.: 577ET Times Cited: 17 Cited Reference Count: 49 Cited References: *SPSS INC, 2000, SIGMAPLOT 2000 PROGR ANDERSON VJ, 1997, AUST J BOT, V45, P331 BURKE IC, 1999, ECOSYSTEMS, V2, P422 CARROLL C, 2000, TROP GRASSLANDS, V34, P254 CROSS AF, 1999, PLANT ECOL, V145, P11 FINDLATER PA, 1990, AUST J SOIL RES, V28, P609 FREEBAIRN DM, 1989, AUST J SOIL RES, V27, P199 FREEBAIRN DM, 1991, CLIMATIC RISK CROP P, P283 GALLE S, 1999, CATENA, V37, P197 GARDNER RH, 1999, LANDSCAPE ECOLOGICAL, P280 HE HS, 2000, LANDSCAPE ECOL, V15, P591 JAEGER JAG, 2000, LANDSCAPE ECOL, V15, P115 JOHNS GG, 1983, AUSTR RANGELAND J, V5, P3 KINLOCH JE, 2000, P 10 AUSTR REM SENS LANG RD, 1984, J SOIL CONSERVATION, V40, P56 LEYS JF, 1991, VEGETATIO, V91, P49 LI BL, 1997, ECOL MODEL, V102, P353 LI HB, 1994, ECOLOGY, V75, P2446 LUDWIG JA, 1995, LANDSCAPE ECOL, V10, P51 LUDWIG JA, 1999, CATENA, V37, P257 LUDWIG JA, 1999, LANDSCAPE ECOL, V14, P557 LUDWIG JA, 1999, RANGELAND J, V21, P135 LUDWIG JA, 2000, ECOSYSTEMS, V3, P84 LUDWIG JA, 2000, ENVIRON MONIT ASSESS, V44, P167 LUDWIG JA, 2000, RANGELAND DESERTIFIC, P39 MCINTYRE NE, 2000, LANDSCAPE ECOL, V15, P313 MCIVOR JG, 1995, AUST J EXP AGR ANIM, V35, P55 MILES JR, 1994, AUSTR J SOIL WATER C, V7, P41 PICKUP G, 1985, AUSTR RANGELAND J, V7, P114 PICKUP G, 1993, REMOTE SENS ENVIRON, V43, P243 PICKUP G, 1996, EARTH SURF PROC LAND, V21, P517 PICKUP G, 2000, INT J REMOTE SENS, V21, P339 PRESSLAND AJ, 1982, AUST RANGELAND J, V4, P16 REID KD, 1999, SOIL SCI SOC AM J, V63, P1869 REYNOLDS JF, 1997, PLANT FUNCTIONAL TYP, P195 REYNOLDS JF, 1999, ECOL MONOGR, V69, P69 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 SCANLAN JC, 1996, RANGELAND J, V18, P33 SCHLESINGER WH, 2000, BIOGEOCHEMISTRY, V49, P69 TANAKA S, 2001, INT J REMOTE SENS, V22, P1 TISCHENDORF L, 2001, LANDSCAPE ECOL, V16, P235 TONGWAY DJ, 1997, LANDSCAPE ECOLOGY FU, P13 VALENTIN C, 1999, CATENA, V37, P1 WHISENANT SG, 1999, REPAIRING DAMAGED WI WIENS JA, 1997, OIKOS, V78, P257 WILLIAMS MAJ, 1978, STUDIES AUSTR ARID Z, V3, P79 WITH KA, 1999, ECOLOGY, V80, P1340 WU XB, 2000, J ECOL, V88, P790 WU XB, 2001, ENVIRON PLANN B, V28, P433 0921-2973 Landsc. Ecol.ISI:000177049100004Trop Savannas Management Cooperat Res Ctr, Atherton, Qld 4883, Australia. Ludwig, JA, Trop Savannas Management Cooperat Res Ctr, POB 780, Atherton, Qld 4883, Australia.English?{!Ludwig, John A. Tongway, David J.1995USpatial organisation of landscapes and its function in semi-arid woodlands, Australia51-63Landscape Ecology101Qlandscapes, organisation, patches, processes, scale, function, semi-arid woodland `|7h Ludwig, J. A. Tongway, D. J.1995TSpatial-Organization of Landscapes and Its Function in Semiarid Woodlands, Australia51-63Landscape Ecology101Klandscapes organization patches processes scale function semiarid woodlandsFebThe spatial organisation of three major landscape types within the semi-arid woodlands of eastern Australia was studied by a detailed analysis of gradient-oriented transects (gradsects). The aim was to characterise the spatial organisation of each landscape, and to account for that organisation in functional terms related to the differential concentration of scarce resources by identifiable processes. Terrain, vegetation and soils data were collected along each gradsect. Boundary analysis was used to identify the types of landscape units at a range of scales. Soil analyses were used to determine the degree of differential concentration of nutrients within these units, and to infer the role of fluvial and aeolian processes in maintaining them. All three major landscape systems were found to be highly organised systems with distinctive resource-rich units or patches separated by more open, resource-poor zones. At the largest scale, distinct groves of trees were separated by open intergroves. At smaller-scales, individual trees, large shrubs, clumps of shrubs, fallen logs and clumps of grasses constituted discrete patches dispersed across the landscape. Our soil analyses confirmed that these patches act as sinks by filtering and concentrating nutrients lost from source areas (e.g., intergroves). We suggest that fluvial runoff-runon and aeolian saltation-deposition are the physical processes involved in these concentration effects, and in building and maintaining patches; biological activities also maintain patches. This organisation of patches as dispersed resource filters (at different scales) has the overall function of conserving limited resources within semi-arid landscape systems. Understanding the role of landscape patchiness in conserving scarce resources has important implications for managing these landscapes for sustainable land use, and for the rehabilitation of landscapes already degraded.://A1995QL68700005.Ql687 Times Cited:147 Cited References Count:0 0921-2973ISI:A1995QL68700005FLudwig, Ja Csiro,Div Wildlife & Ecol,Pob 84,Lyneham,Act 2602,AustraliaEnglish<7GELudwig, J. A. Tongway, D. J. Eager, R. W. Williams, R. J. Cook, G. D.1999gFine-scale vegetation patches decline in size and cover with increasing rainfall in Australian savannas557-566Landscape Ecology146ground-layer landscape function patch spacing runoff soil texture tree-layer NORTHERN AUSTRALIA LANDSCAPE ECOLOGY GRADIENT NUTRIENTS MOISTUREArticleDec%Fine-scale vegetation patches (< 5 m in width) are critically important in many landscapes because they function to obstruct surface flows of water and wind. These obstructions increase the infiltration of runoff and the capture of nutrients in runoff sediments and in wind-blown soil and litter. The importance of redistribution of runoff into runon patches from spaces between patches (fetches) is likely to be greater in drier than in wetter environments. In this paper we examine the hypothesis that the ratio of fetch to patch decreases as rainfall increases, and that this trend will be most evident on intermediate-textured soils because these soils are more prone to runoff. We measured fine-scale patches on 38 sites with sand, loam or clay soils. Sites were located along a 1000-mm rainfall gradient in the savannas of northern Australia. The width and intercept length of patches and the fetch between patches was measuring along line transects of 100-120 m oriented down slope. We found that the ratio of fetch to patch area did not decrease with decreasing rainfall, but increased on both sand and loam soils. This result was because with increasing rainfall mean spacing between patches disproportionally increased while mean patch size and cover declined. The cover of patches was negatively correlated with tree canopy cover, which significantly increased with rainfall. This negative correlation suggests that in higher rainfall savannas the size and spacing of ground-layer patches is controlled by the tree layer, and that as rainfall decreases this control decreases and runoff-runon processes increasingly structure the landscape. For savannas on clay soils these trends were not significant except that on the highest rainfall sites the cover of ground-layer patches was nearly 100% while trees were absent.://000082563500004 ISI Document Delivery No.: 235VP Times Cited: 23 Cited Reference Count: 34 Cited References: ANDERSON VJ, 1997, AUST J BOT, V45, P331 ANDREW MH, 1983, AUST J ECOL, V8, P265 ASH AJ, 1996, FUTURE TROPICAL SAVA BONHAM CD, 1989, MEASUREMENTS TERREST BRAITHWAITE RW, 1985, ECOLOGY MANAGEMENT W, P359 CLEWETT JF, 1994, AUSTR RAINMAN RAINFA COOK GD, 1994, AUST J ECOL, V19, P359 DUFF GA, 1997, AUST J BOT, V45, P211 ELDRIDGE DJ, 1993, AUST J SOIL RES, V31, P509 FRIEDEL MH, 1994, RANGELAND J, V16, P16 GILLISON AN, 1985, J ENVIRON MANAGE, V20, P103 LUDWIG JA, 1994, PACIFIC CONSERVATION, V1, P209 LUDWIG JA, 1995, LANDSCAPE ECOL, V10, P51 MCIVOR JG, 1995, AUST J EXP AGR ANIM, V35, P55 MOTT J, 1979, AUST J SOIL RES, V17, P483 NOYMEIR I, 1981, ARID LAND ECOSYSTEMS, V2, P411 SCANLAN JC, 1990, AUST J ECOL, V15, P191 SCANLAN JC, 1996, RANGELAND J, V18, P47 SCHOLES RJ, 1997, ANNU REV ECOL SYST, V28, P517 SCHULZE ED, 1998, AUST J PLANT PHYSIOL, V25, P413 TONGWAY DJ, 1994, PACIFIC CONSERVATION, V1, P201 TONGWAY DJ, 1995, MANUAL SOIL CONDITIO TONGWAY DJ, 1997, LANDSCAPE ECOLOGY FU, P17 TONGWAY DJ, 1997, LANDSCAPE ECOLOGY FU, P53 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 WALKER BH, 1993, AMBIO, V22, P80 WALKER BH, 1996, RANGELANDS SUSTAINAB, V2, P22 WALKER BH, 1997, AUST J ECOL, V22, P125 WALKER BH, 1997, J BIOGEOGR, V24, P813 WIENS JA, 1993, OIKOS, V66, P369 WILLIAMS MAJ, 1969, NATURE, V22, P763 WILLIAMS RJ, 1996, J BIOGEOGR, V23, P747 WILLIAMS RJ, 1999, AUST J ECOL, V24, P50 WILSON BA, 1990, 49 CONS COMM NO TERR 0921-2973 Landsc. Ecol.ISI:000082563500004Trop Savannas Cooperat Res Ctr, Darwin, NT 0822, Australia. CSIRO, Darwin, NT 0822, Australia. CSIRO, Canberra, ACT 2601, Australia. Ludwig, JA, Trop Savannas Cooperat Res Ctr, PMB 44, Darwin, NT 0822, Australia.English|7!Ludwig, T. Storch, I. Graf, R. F.2009]Historic landscape change and habitat loss: the case of black grouse in Lower Saxony, Germany533-546Landscape Ecology244tetrao tetrix distribution topographic maps historic land use logistic regression tetrao-tetrix farmland birds fragmentation populations success europe models scaleAprThe declines of many specialist bird species in the agricultural landscapes of Central Europe have resulted in small and isolated populations. In the case of the black grouse, a ground-nesting bird species with large spatial requirements, empiric evidence about underlying landscape changes is scarce. In this study, we examined land cover and land cover changes in a farmland-forest mosaic in eastern Lower Saxony, Germany and how they affect occurrence and persistence of black grouse. Spatial information came from historic topographic maps from 1958 to 1975. The results show profound conversions of habitat to forest and farmland but also an increase in settlement area. Habitat conversions and suburbanization were negative correlates of black grouse persistence. Habitat models from before and after a decline period differed in some of the predictors and suggest black grouse habitat to be more diverse before the land cover changes. Our study confirms that land use factors at a landscape scale extent contribute to explain black grouse occurrence and thus can complement important small scale factors like the quality and size of individual habitat patches. Results also show that landscape factors affect black grouse distribution predominantly from an area much greater than an individual black grouse home range. Our models may be further evaluated on present-day landscapes and might be used to evaluate large-scale habitat availability for black grouse.://000263898100008-414XI Times Cited:0 Cited References Count:40 0921-2973ISI:0002638981000085Ludwig, T Univ Freiburg, Inst Forest Zool, Dept Wildlife Ecol & Management, Tennenbacher Str 4, D-79106 Freiburg, Germany Univ Freiburg, Inst Forest Zool, Dept Wildlife Ecol & Management, D-79106 Freiburg, Germany Zurich Univ Appl Sci ZHAW, Wildlife & Landscape Management Unit, CH-8820 Wadenswil, SwitzerlandDoi 10.1007/S10980-009-9330-3English<7 Lugo, A. E.2002MCan we manage tropical landscapes? - an answer from the Caribbean perspective601-615Landscape Ecology177<biodiversity Caribbean islands deforestation development fragmentation Puerto Rico reforestation secondary forests tropical forests tropical landscapes NATIVE FOREST REGENERATION CENTRAL NEW-ENGLAND PUERTO-RICO LAND-USE COSTA-RICA NATURAL DISTURBANCE ABANDONED PASTURES BRAZILIAN AMAZON EASTERN AMAZONIA RAIN-FORESTSReviewNovHumans have used Caribbean island landscapes for millennia. The conversion of wild lands to built-up lands or to agricultural lands in these tropical countries follows predictable patterns. Conversion of moist forest life zones and fertile flatlands is faster than conversion of wet and rain forest life zones and low fertility steep lands. In Puerto Rico, these trends are leading to increased built-up areas, environmental surprises, and increased dependence on external subsidies. Changes over the past 50 yr also include a reversal in deforestation and increase in forest patch size in spite of increasing human population density. Present forests have different species composition than the original ones but are indistinguishable in physiognomy and basic function. The reversal of deforestation and forest fragmentation trends, if accompanied by an understanding of the forces that cause the reversal, can result in the development of tools for landscape management. Tropical landscape management requires understanding and application of natural resilience mechanisms of ecosystems, greater use of ecological engineering approaches to infrastructure development, enforcement of zoning laws, enlightened economic development policies, and an understanding and agreement of a conservation vision among all sectors of society. Mixing species in new combinations to form new ecosystems is a necessary step in the development of future landscapes.://000179746400001 dISI Document Delivery No.: 624EB Times Cited: 8 Cited Reference Count: 120 Cited References: 1981, AMBIO, V10, P274 *DNR, 1975, ZON COST PUERT RIC C AIDE TM, 1995, FOREST ECOL MANAG, V77, P77 AIDE TM, 1996, BIOTROPICA A, V28, P537 AIDE TM, 2000, RESTOR ECOL, V8, P328 BARROW CJ, 1991, LAND DEGRADATION DEV BATISSE M, 1996, NATURE RESOUR, V32, P20 BATIZ FLR, 1996, ISLAND PARADOX PUERT BELLER W, 1990, SUSTAINABLE DEV ENV BIERREGAARD RO, 1992, BIOSCIENCE, V42, P1168 BIRDSEY RA, 1982, RESOURCE B USDA BIRDSEY RA, 1987, SO331 USDA FOR SERV BRIGHT C, 1999, WORLD WATCH CONTENTS, V12, P12 BRIGHT C, 2000, FUTURIST, V34, P41 BROWN RC, 2001, POWDER TECHNOL, V119, P68 BROWN S, 1994, EFFECTS LAND USE CHA, P117 BURGESS RL, 1981, FOREST ISLAND DYNAMI BURGESS RL, 1981, FOREST ISLAND DYNAMI, P267 CHOMITZ KM, 1996, WORLD BANK ECON REV, V10, P487 COLON SM, 1998, THESIS U PUERTO RICO DELLOPEZ MT, 2001, AMBIO, V30, P49 FINEGAN B, 1996, TRENDS ECOL EVOL, V11, P119 FORMAN RTT, 1996, CONSERVATION FAUNAL, P537 FOSTER DR, 1992, J ECOL, V80, P722 FOSTER DR, 1997, BIOSCIENCE, V47, P437 FOSTER DR, 1998, ECOSYSTEMS, V1, P497 FOSTER DR, 1998, ECOSYSTEMS, V1, P96 FOSTER DR, 1998, NORTHEAST NAT, V5, P111 FOSTER DR, 1999, ECOL APPL, V9, P555 FOSTER MS, 1998, BIOTROPICA, V30, P470 FRANCO PA, 1997, RESOURCE B USDA FULLER TL, 1998, ECOSYSTEMS, V1, P76 GARCIAMONTIEL DC, 1994, FOREST ECOL MANAG, V63, P57 GOMEZPOMPA A, 1995, TROPICAL FORESTS MAN, P408 GONZALEZ OMR, 2001, CARIBBEAN J SCI, V37 HABER W, 1990, CHANGING LANDSCAPES, P217 HALL CAS, 1986, ENERGY RESOURCE QUAL HALL CAS, 2000, QUANTIFYING SUSTAINA HALL CAS, 2000, QUANTIFYING SUSTAINA, P121 HALL CAS, 2000, QUANTIFYING SUSTAINA, P2 HAMMOND DS, 1998, CONSERV BIOL, V12, P944 HARRISON S, 1991, INTERCIENCIA, V16, P83 HELMER EH, 1999, LANDSCAPE ECOLOGY SE HOLDRIDGE LR, 1967, LIFE ZONE ECOLOGY HOLLING CS, 1986, SUSTAINABLE DEV BIOS, P292 HUNTER JM, 1995, SOC SCI MED, V40, P1331 IVERSON LR, 1994, EFFECTS LAND USE CHA, P67 JOGLAR RL, 1996, CONTRIBUTIONS W INDI, P371 KILINE JD, 1999, GROWTH CHANGE, V30, P3 KRAMER EA, 1997, TROPICAL FOREST REMN, P386 LAMB FB, 1966, MAHOGANY TROPICAL AM LAURANCE WF, 1997, TROPICAL FOREST REMN LEOPOLD A, 1933, J FOREST, V31, P634 LEOPOLD A, 1993, ROUND RIVER J A LEOP, P145 LIOGIER HA, 1990, B COMICION PUERTORRI LUGO AE, 1981, AMBIO, V10, P318 LUGO AE, 1982, B ACAD ARTES CIENCIA, V19, P1 LUGO AE, 1986, PLANT SOIL, V96, P185 LUGO AE, 1988, BIODIVERSITY, P58 LUGO AE, 1988, ENVIRONMENT, V30, P16 LUGO AE, 1991, NATURE RESOUR, V27, P27 LUGO AE, 1995, TROPICAL FORESTS MAN, P3 LUGO AE, 1996, 53 YEAR RECORD LAND LUGO AE, 1996, ENV DEV EC, V1, P128 LUGO AE, 2001, IITF16 LUHO AE, 1996, BIODIVERSITY MANAGED, P280 LUHO AE, 1998, PROTECTION GLOBAL BI, P34 LUHO AE, 2001, BIODIVERSITY CARIBBE, P92 MEYER WB, 1994, CHANGES LAND USE LAN MORAN EF, 1996, ECOL ECON, V18, P41 MORAN EF, 1998, PEOPLE PIXELS LINKIN, P94 MOTZKIN G, 1996, ECOL MONOGR, V66, P345 MURPHY LS, 1916, B USDA, V354 NELSON BW, 1994, ECOLOGY, V75, P853 NEPSTAD D, 1990, ALTERNATIVES DEFORES, P215 NEPSTAD D, 1998, CONSERV BIOL, V12, P951 ODUM EP, 1990, CHANGING LANDSCAPES, P137 ODUM HT, 1962, B NEW HAVEN CONNECTI, V652, P55 ODUM HT, 1988, SCIENCE, V242, P1132 ODUM HT, 1995, MAXIMUM POWER, P311 ODUM HT, 1996, ECOL ENG, V6, P7 ODUM HT, 2001, PROSPEROUS WAY DOWN PARROTTA JA, 1997, FOREST ECOL MANAG, V99, P1 PETERS EC, 1997, LIFE DEATH CORAL REE, P114 PICKETT STA, 1985, ECOLOGY NATURAL DIST PIMENTEL D, 1992, BIOSCIENCE, V42, P354 PRENDERGAST JR, 1999, CONSERV BIOL, V13, P484 PURATA SE, 1986, J TROP ECOL, V2, P257 RAMOS O, 1994, ACTA CIENTIFICA, V8, P63 RAMOS O, 1996, ASSESSING NE PUERTO RICHARDS JF, 1990, EARTH TRANSFORMED HU, P161 RICHARDSON LL, 1998, TRENDS ECOL EVOL, V13, P438 RISSER PG, 1995, LANDSCAPE ECOLOGY, V10, P129 RIVERA LW, 1998, FOREST ECOL MANAG, V108, P63 ROBERTS RC, 1942, USDA SERIES 1936, V8 RUDEL TK, 2000, PROF GEOGR, V52, P186 RUZICKA M, 1990, CHANGING LANDSCAPES, P233 SADER SA, 1988, BIOTROPICA, V20, P11 SCATENA FN, 1991, BIOTROPICA, V23, P317 SHAFER CL, 1999, ENVIRON MANAGE, V23, P49 SILVER WL, 2000, RESTOR ECOL, V8, P394 SNYDER NFR, 1987, PARROTS LUQUILLO NAT SOUSA WP, 1984, ANNU REV ECOL SYST, V15, P353 STAALAND H, 1998, AMBIO, V27, P456 STALLARD RF, 2001, CONSERV BIOL, V15, P943 THOMLINSON JR, 1996, BIOTROPICA A, V28, P525 TOMBLIN J, 1981, AMBIO, V10, P340 TOSI JA, 1964, ECON GEOGR, V40, P189 TUCKER JM, 1998, INTERCIENCIA, V23, P64 TURNER BL, 1990, EARTH TRANSFORMED HU TURNER IM, 1996, TRENDS ECOL EVOL, V11, P330 UHL C, 1988, J ECOL, V76, P663 VELDKAMP E, 1992, LAND DEGRAD REHABIL, V3, P71 WADSWORTH FH, 1985, TURRIALBA, V35, P11 WADSWORTH FH, 1995, TROPICAL FORESTS MAN, P33 WILLIG MR, 1996, BIOTROPICA A, V28, P471 WOODWELL GM, 1990, EARTH TRANSITION PAT WUNDERLE JM, 1997, FOREST ECOL MANAG, V99, P223 ZIMMERMAN JK, 1995, FOREST ECOL MANAG, V77, P65 ZONNEVELD IS, 1990, CHANGING LANDSCAPES 0921-2973 Landsc. Ecol.ISI:000179746400001US Forest Serv, Int Inst Trop Forestry, USDA, Rio Piedras, PR 00928 USA. Lugo, AE, US Forest Serv, Int Inst Trop Forestry, USDA, POB 25000, Rio Piedras, PR 00928 USA.Englishn|?I ULuis Hernandez-Stefanoni, J. Manuel Dupuy, Juan Tun-Dzul, Fernando May-Pat, Filogonio2011|Influence of landscape structure and stand age on species density and biomass of a tropical dry forest across spatial scales355-370Landscape Ecology263MarThree central related issues in ecology are to identify spatial variation of ecological processes, to understand the relative influence of environmental and spatial variables, and to investigate the response of environmental variables at different spatial scales. These issues are particularly important for tropical dry forests, which have been comparatively less studied and are more threatened than other terrestrial ecosystems. This study aims to characterize relationships between community structure and landscape configuration and habitat type (stand age) considering different spatial scales for a tropical dry forest in Yucatan. Species density and above ground biomass were calculated from 276 sampling sites, while land cover classes were obtained from multi-spectral classification of a Spot 5 satellite imagery. Species density and biomass were related to stand age, landscape metrics of patch types (area, edge, shape, similarity and contrast) and principal coordinate of neighbor matrices (PCNM) variables using regression analysis. PCNM analysis was performed to interpret results in terms of spatial scales as well as to decompose variation into spatial, stand age and landscape structure components. Stand age was the most important variable for biomass, whereas landscape structure and spatial dependence had a comparable or even stronger influence on species density than stand age. At the very broad scale (8,000-10,500 m), stand age contributed most to biomass and landscape structure to species density. At the broad scale (2,000-8,000 m), stand age was the most important variable predicting both species density and biomass. Our results shed light on which landscape configurations could enhance plant diversity and above ground biomass.!://WOS:000288808100005Times Cited: 0 0921-2973WOS:00028880810000510.1007/s10980-010-9561-3|?2Lundberg, J. Andersson, E. Cleary, G. Elmqvist, T.2008SLinkages beyond borders: targeting spatial processes in fragmented urban landscapes717-726Landscape Ecology236FManagement of ecosystems often focuses on specific species chosen for their habitat demand, public appeal, or levels of threat. We propose a complementary framework for choosing focal species, the mobile link concept, which allows managers to focus on spatial processes and deal with multi-scale ecological dynamics. Spatial processes are important for three reasons: maintenance, re-organization, and restoration of ecological values. We illustrate the framework with a case study of the Eurasian Jay, a mobile link species of importance for the oak forest regeneration in the Stockholm National Urban Park, Sweden, and its surroundings. The case study concludes with a conceptual model for how the framework can be applied in management. The model is based on a review of published data complemented with a seed predation experiment and mapping of Jay territories to reduce the risk of applying non-urban site-specific information in an urban setting. Our case study shows that the mobile link approach has several advantages: (1) Reducing the vulnerability of ecological functions to disturbances and fluctuations in resources allocated to management, (2) Reducing management costs by maintaining natural processes, and (3) Maintaining gene flow and genetic diversity at a landscape level. We argue that management that includes mobile link organisms is an important step towards the prevention of ecosystem degradation and biodiversity loss in increasingly fragmented landscapes. Identifying and managing mobile links is a way to align management with the ecologically relevant scales in any landscape.!://WOS:000257210900007Times Cited: 0 0921-2973WOS:00025721090000710.1007/s10980-008-9232-9 <7"Lundquist, J. E. Sommerfeld, R. A.2002Use of Fourier transforms to define landscape scales of analysis for disturbances: a case study of thinned and unthinned forest stands445-454Landscape Ecology175Black Hills National Forest disturbance impact forest diseases impact assessment remote sensing South Dakota USA ECOLOGY PATTERNArticleOctAVarious disturbances such as disease and management practices cause canopy gaps that change patterns of forest stand structure. This study examined the usefulness of digital image analysis using aerial photos, Fourier Tranforms, and cluster analysis to investigate how different spatial statistics are affected by spatial scale. The specific aims were to: 1) evaluate how a Fourier filter could be used to classify canopy gap sizes objectively, 2) determine which statistics might be useful for detecting and measuring disturbance impacts, and 3) examine the potential for this method to determine spatial domains in a pair of ponderosa pine ( Pinus ponderosa) stands in the Black Hills of South Dakota, USA. The eventual goal is to develop an operational method of assessing the impacts of natural disturbances such as disease. Results indicated that several spatial metrics discriminated between harvested and unharvested stands. We hypothesize that these metrics will be useful as spatial measures of disease impact if the analyses are performed on specific size classes of forest gaps.://000179388800006 ISI Document Delivery No.: 617YP Times Cited: 2 Cited Reference Count: 25 Cited References: ALLEN TFH, 1982, HIERARCHY PERSPECTIV BAKER WL, 1992, LANDSCAPE ECOL, V7, P181 CARLILE DW, 1989, LANDSCAPE ECOLOGY, V2, P203 CULLINAN VI, 1992, LANDSCAPE ECOL, V7, P211 DAYTON PK, 1984, NEW ECOLOGY NOVEL AP, P457 HARGIS CD, 1997, WILDLIFE LANDSCAPE E, P231 HORNE JK, 1995, OIKOS, V74, P18 HUTCHINSON GE, 1965, ECOLOGICAL THEATER E KORNER C, 1993, BIODIVERSITY ECOSYST, P117 LEVIN SA, 1992, ECOLOGY, V73, P1943 LUNDQUIST JE, 1995, FOREST ECOL MANAG, V74, P37 MAURER BA, 1985, ECOL MONOGR, V55, P295 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MEISEL JE, 1998, LANDSCAPE ECOL, V13, P347 MORRIS DW, 1987, ECOLOGY, V68, P362 ONEILL RV, 1986, HIERARCHICAL CONCEPT QI Y, 1996, LANDSCAPE ECOL, V11, P39 RYKIEL EJ, 1988, LANDSCAPE ECOLOGY, V1, P129 SMITH DM, 1986, PRACTICE SILVICULTUR SOMMERFELD RA, 1994, GEOPHYS RES LETT, V21, P2821 SOMMERFELD RA, 1998, 1 INT C GEOSP INF AG, P1 STARK RW, 1987, CRITICAL REV PLANT S, V5, P161 TURNER SJ, 1991, QUANTITATIVE METHODS, P18 WIENS JA, 1989, FUNCT ECOL, V3, P385 WOODCOCK CE, 1987, REMOTE SENS ENVIRON, V21, P311 0921-2973 Landsc. Ecol.ISI:000179388800006US Forest Serv, Rocky Mt Res Stn, USDA, Ft Collins, CO 80526 USA. Lundquist, JE, US Forest Serv, Rocky Mt Res Stn, USDA, 240 W Prospect Rd, Ft Collins, CO 80526 USA.English|? FLuo, Xu He, Hong S. Liang, Yu Wang, Wen J. Wu, Zhiwei Fraser, Jacob S.2014uSpatial simulation of the effect of fire and harvest on aboveground tree biomass in boreal forests of Northeast China 1187-1200Landscape Ecology297AugFire and timber harvest are two major forest disturbances in boreal forests. Predicting the dynamics of boreal forest biomass requires accounting for both of those effects. Related stochasticity and other uncertainties can produce great variation in predicted responses of forests to fire and timber harvest. In this study, we investigated the effects of fire and timber harvest on landscape-level predictions of the tree component of stand biomass in a boreal forest landscape in Northeast China. We used a forest landscape model (LANDIS PRO) to predict the tree biomass over three time intervals (0-50, 50-150, and 150-300 years). We then compared the simulated results of fire and timber harvest and their interactions with observed biomass and its spatial distribution over short-, mid-, and long-term intervals. For additional prediction comparisons, we observed uncut, unburned stands (i.e., the succession-only scenario). Compared to the succession-only scenario, we found that predicted biomass was reduced by 3.8 +/- A 2.1, 9.1 +/- A 3.6, and 11.2 +/- A 5.1 tons/ha in fire-only, harvest-only, and combined fire and harvest scenarios, respectively. Our results indicated that the effect of harvest on biomass exceeded that of fire, and that the interaction of fire and harvest was more effective in reducing biomass than the effects of fire or harvest separately. Biomass predictions that did not consider effects of fire and timber harvest tended to inflate biomass estimates. The spatial distribution of tree biomass moreover changed with simulation period. These results have important implications in designing prescriptions for improving forest sustainability.!://WOS:000339831300008Times Cited: 1 0921-2973WOS:00033983130000810.1007/s10980-014-0051-x<7'Luoto, M. Toivonen, T. Heikkinen, R. K.2002yPrediction of total and rare plant species richness in agricultural landscapes from satellite images and topographic data195-217Landscape Ecology173biodiversity GIS GLM model hotspot probability map satellite image species richness DIVERSITY PATTERNS ECOLOGY VARIABLES HABITAT VEGETATION MODELS REGRESSION WILDLIFE GRADIENTArticleThe diversity of future landscapes might depend on our ability to predict their potential species richness. The predictability of patterns of vascular plant species richness in a Finnish agricultural river landscape was studied using generalized linear modeling, floristic records from fifty-three 0.25-km grid squares in the "core" study area, and environmental variables derived from Landsat TM images and a digital elevation model. We built multiple regression models for the total number of plant species and the number of rarities, and validated the accuracy of the derived models with a test set of 52 grid squares. We tentatively extrapolated the models from the core study area to the whole study area of 601 km(2) and produced species richness probability maps using GIS techniques. The results suggest that the local 'hotspots' of total flora (grid squares with > 200 species) are mainly found in river valleys, where habitat diversity is high and a semi-open agricultural-forest mosaic occurs. The 'hotspots' of rare species (grid squares with > 4 rare species) are also found in river valleys, in sites where extensive semi-natural grasslands and herb-rich deciduous forests occur on steep slopes. We conclude that environmental variables derived from satellite images and topographic data can be used as approximate surrogates of plant species diversity in agricultural landscapes. Modeling of biological diversity based on satellite images and GIS can provide useful information needed in land use planning. However, due to the potential pitfalls in processing satellite imagery and model-building procedures, the results of predictive models should be carefully interpreted.://000178082200001 ISI Document Delivery No.: 594ZK Times Cited: 25 Cited Reference Count: 69 Cited References: *FINN MET I, 1991, CLIM STAT FINL 1961 AUGUSTIN NH, 1996, J APPL ECOL, V33, P339 AUSTIN MP, 1984, VEGETATIO, V55, P11 AUSTIN MP, 1991, NATURE CONSERVATION, P31 AUSTIN MP, 1996, AUST J ECOL, V21, P154 AUSTIN MP, 1999, ECOGRAPHY, V22, P465 BIRKS HJB, 1996, ECOGRAPHY, V19, P332 BURROUGH PA, 1998, PRINCIPLES GEOGRAPHY BUSTAMANTE J, 1997, BIOL CONSERV, V80, P153 CHERRIL AJ, 1995, LANDSCAPE ECOLOGY, V4, P197 CORTIJO FJ, 1998, INT J REMOTE SENS, V19, P1591 CRACKNELL AP, 1998, INT J REMOTE SENS, V19, P2025 CRAWLEY MJ, 1993, GLIM ECOLOGISTS CURRIE DJ, 1991, AM NAT, V137, P27 DEBINSKI K, 1999, INT J REMOTE SENS, V17, P3281 ESSEEN PA, 1992, ECOLOGICAL PRINCIPLE, P254 EUROLA S, 1984, EUROPEAN MIRES, P11 EYRE MD, 1989, J APPL ECOL, V26, P159 FISHER P, 1997, INT J REMOTE SENS, V18, P679 FLACK VF, 1987, AM STAT, V41, P84 GASTON KJ, 1994, RARITY GASTON KJ, 1996, BIODIVERSITY BIOL NU, P77 GRIFFITHS GH, 1993, LANDSCAPE ECOLOGY GE, P255 GRIFFITHS GH, 2000, INT J REMOTE SENS, V21, P2537 HAMETAHTI L, 1986, RETKEILYKASVIO FIELD HEIKKINEN RK, 1996, VEGETATIO, V126, P151 HILL NM, 1992, ECOLOGY, V73, P1852 HOLMES KW, 2000, J HYDROL, V233, P154 HORNBERG G, 1998, BIOSCIENCE, V48, P795 IVERSON LR, 1997, LANDSCAPE ECOL, V12, P331 JAMES FC, 1990, ANNU REV ECOL SYST, V21, P129 KOHN DD, 1994, J ECOL, V82, P367 KONTULA T, 2000, FINNISH ENV, V306, P1 KOTIRANTA H, 1998, RED DATA BOOK E FENN LEHTOMAA L, 2000, REGIONAL ENV SERIES, V160 LILLESAND TM, 1994, REMOTE SENSING IMAGE LUOTO M, 2000, PLANT ECOL, V149, P157 MACNALLY R, 2000, BIODIVERS CONSERV, V9, P655 MARGULES CR, 1987, OECOLOGIA, V71, P229 MARGULES CR, 1991, NATURE CONSERVATION MCCULLAGH P, 1989, GEN LINEAR MODELS MCGARICAL K, 1994, FRAGSTATS SPATIAL PA MCINTYRE S, 1994, CONSERV BIOL, V8, P521 MILLER RI, 1986, J BIOGEOGR, V13, P293 NAGENDRA H, 1999, J APPL ECOL, V36, P388 NICHOLLS AO, 1991, NATURE CONSERVATION, P54 NILSSON C, 1988, BIOL CONSERV, V44, P201 PAYNE CD, 1986, GLIM SYSTEM RELEASE PHILIPPI TE, 1993, DESIGN ANAL ECOLOGIC, P183 PRENDERGAST JR, 1993, NATURE, V365, P335 PYKALA J, 1998, SUOMEN LUONNON MONIM, P184 RASSI P, 1992, UHANALAISTEN ELAINTE RICHARDS JA, 1996, REMOTE SENS ENVIRON, V57, P1616 RICHERSON PJ, 1980, AM NAT, V116, P504 ROSSI E, 1996, BIOL CONSERV, V77, P227 SCOTT JM, 1993, WILDLIFE MONOGR, P1 SPELLERBERG IF, 1992, EVALUATION ASSESSMEN STOMS DM, 1992, PHOTOGRAMM ENG REM S, V58, P1587 STOMS DM, 1993, INT J REMOTE SENS, V14, P1839 STOUTJESDIJK P, 1992, MICROCLIMATE VEGETAT TONTERI T, 1994, ANN ZOOL FENN, V31, P53 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 URBAN DL, 1987, BIOSCIENCE, V37, P119 VANDECASTLE J, 1998, ECOLOGICAL SCALE THE WALKER PA, 1990, J BIOGEOGR, V17, P279 WHITTAKER RH, 1956, ECOL MONOGR, V26, P1 WIENS JA, 1986, COMMUNITY ECOLOGY, P154 WOHLGEMUTH T, 1998, BIODIVERS CONSERV, V7, P159 YEE TW, 1991, J VEG SCI, V2, P587 0921-2973 Landsc. Ecol.ISI:000178082200001Finnish Environm Inst, GIS & Remote Sensing Unit, FIN-00251 Helsinki, Finland. Luoto, M, Finnish Environm Inst, GIS & Remote Sensing Unit, FIN-00251 Helsinki, Finland.English<7n !Luque, S. Saura, S. Fortin, M. J.2012~Landscape connectivity analysis for conservation: insights from combining new methods with ecological and genetic data PREFACE153-157Landscape Ecology272oenvironmental-factors habitat availability colonization hypotheses migration patches indexes graphs models flowFeb://0003000887000019Sp. Iss. SI 889QQ Times Cited:0 Cited References Count:25 0921-2973Landscape EcolISI:000300088700001Luque, S Inst Agr & Environm Engn Res, Mt Ecosyst Res Unit, 2 Rue Papeterie, F-38402 St Martin Dheres, France Inst Agr & Environm Engn Res, Mt Ecosyst Res Unit, 2 Rue Papeterie, F-38402 St Martin Dheres, France Inst Agr & Environm Engn Res, Mt Ecosyst Res Unit, F-38402 St Martin Dheres, France Univ Politecn Madrid, ETSI Montes, Madrid, Spain Univ Toronto, Dept Ecol & Evolutionary Biol, Toronto, ON, CanadaDOI 10.1007/s10980-011-9700-5English<7)Luque, S. S. Lathrop, R. G. Bognar, J. A.1994PTemporal and spatial changes in an area of the New Jersey Pine Barrens landscape287-300Landscape Ecology94]LANDSCAPE FRAGMENTATION; TEMPORAL CHANGES; SPATIAL PATTERNS; LAND COVER; NEW-JERSEY PINELANDSArticleDecIn order to document the extent of landscape fragmentation for a section of the New Jersey Pine Barrens region, we have used satellite image and spatial analysis to monitor landscape change between 1972 and 1988. Land-cover patterns were quantified by mean, number, and size of patches; and amount of edges between land cover types. During the intervening sixteen year period, fractal dimension, diversity, and contagion generally decreased while dominance, disturbance and edges increased, indicating a trend to a more dissected and disturbed landscape. There was an increase in the number of forest patches and a significant decrease in the average size of forest patches. In contrast, the mean patch size for the non-forest category has increased as a result of a coalescence of patches. The landscape fragmentation is shown by a downward shift in the distribution of forest patches by size class. These changes in landscape pattern have implications for many ecological processes and resources. Management practices need to consider landscape fragmentation in the Pinelands National Reserve in order to preserve the essential character of the Pine Barrens landscape.://A1994PX89500006 IISI Document Delivery No.: PX895 Times Cited: 29 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1994PX89500006iLUQUE, SS, RUTGERS STATE UNIV,COOK COLL,CTR REMOTE SENSING & SPATIAL ANAL,POB 231,NEW BRUNSWICK,NJ 08903.English|7n )Luque, S. S. Lathrop, R. G. Bognar, J. A.1994PTemporal and Spatial Changes in an Area of the New-Jersey Pine-Barrens Landscape287-300Landscape Ecology94Ylandscape fragmentation temporal changes spatial patterns land cover new-jersey pinelandsDecIn order to document the extent of landscape fragmentation for a section of the New Jersey Pine Barrens region, we have used satellite image and spatial analysis to monitor landscape change between 1972 and 1988. Land-cover patterns were quantified by mean, number, and size of patches; and amount of edges between land cover types. During the intervening sixteen year period, fractal dimension, diversity, and contagion generally decreased while dominance, disturbance and edges increased, indicating a trend to a more dissected and disturbed landscape. There was an increase in the number of forest patches and a significant decrease in the average size of forest patches. In contrast, the mean patch size for the non-forest category has increased as a result of a coalescence of patches. The landscape fragmentation is shown by a downward shift in the distribution of forest patches by size class. These changes in landscape pattern have implications for many ecological processes and resources. Management practices need to consider landscape fragmentation in the Pinelands National Reserve in order to preserve the essential character of the Pine Barrens landscape.://A1994PX89500006-Px895 Times Cited:40 Cited References Count:0 0921-2973ISI:A1994PX89500006gLuque, Ss Rutgers State Univ,Cook Coll,Ctr Remote Sensing & Spatial Anal,Pob 231,New Brunswick,Nj 08903English<7fLurz, P. W. W. Rushton, S. P. Wauters, L. A. Bertolino, S. Currado, I. Mazzoglio, P. Shirley, M. D. F.2001ZPredicting grey squirrel expansion in North Italy: a spatially explicit modelling approach407-420Landscape Ecology165alien species conservation forest damage GIS landscape structure Sciurus carolinensis EURASIAN RED SQUIRREL SCIURUS-VULGARIS L FOOD AVAILABILITY GRAY SQUIRRELS POPULATION FRAGMENTATION CAROLINENSIS MANAGEMENT LANDSCAPES DISPERSALArticleJulThere is growing concern about the spread of the North American grey squirrel (Sciurus carolinensis) in northern Italy which were introduced into Piedmont in 1948. They have since spread across the Po-plain covering an area of approximately 450 km(2) and continue to expand their range. In parallel to what has been observed in Britain and Ireland, grey squirrels replace the native red squirrel (S. vulgaris) and damage poplar (Populus) plantations through bark-stripping. Spatially explicit population dynamics models have been successfully used to predict the spread of grey squirrels in East Anglia, England. We extended a previous approach employing a sensitivity analysis where life history and other demographic inputs are generated using Latin Hypercube Sampling from the known ranges of each input parameter, and applied it to Italy using field data collected in Piedmont. The analysis indicated that reproductive output was the most important factor determining total population size present in Piedmont. The structure and composition of woodland habitats around the introduction site suggested that initial grey squirrel expansion would have been slow and subject to emigration rates from the available habitat blocks. A comparison of the 1996 survey results with model predictions indicated that a mean litter size of three young gave the best fit with the observed distribution and we use this to predict future grey squirrel spread. We also present a `worst case' scenario in which grey squirrels experience improved reproductive success due to the availability of high quality habitats beyond the Po plain. In both cases they could disperse along existing continuous woodland corridors into France between 2039-2048. The case of the grey squirrel highlights the problems of implementing conservation conventions and the resulting conflicts between wildlife management, public perception and local political support and the narrow time frame that is available to control alien species effectively before it is too late. If allowed to spread, grey squirrels have the potential of becoming a European forest pest species and are likely to replace the native red squirrel in large parts of its range.://000170952100003 ISI Document Delivery No.: 471WR Times Cited: 17 Cited Reference Count: 47 Cited References: ADREN H, 1994, OIKOS, V71, P355 ANDREN H, 1994, OIKOS, V70, P43 BARRETO GR, 1998, ANIMAL CONSERVATION, V1, P129 BART J, 1995, ECOL APPL, V5, P411 BERTOLINO S, 1999, RIV PIEM ST NAT, V20, P215 CELADA C, 1994, BIOL CONSERV, V69, P177 CHITTY D, 1996, LEMMINGS COMMIT SUIC CURRADO I, 1987, ANN FAC SCI AGRARIA, V14, P307 CURRADO I, 1998, SPECIAL PUBLICATION, V6, P263 DAGNALL J, 1995, ECOLOGY EVOLUTIONARY, P249 FIELDING AH, 1997, ENVIRON CONSERV, V24, P38 FRNACIS B, 1993, GLIM SYSTEM RELEASE GENOVESI P, 1998, IUCN B, P25 GURNELL J, 1983, MAMMAL REV, V13, P133 GURNELL J, 1987, NATURAL HIST SQUIRRE, P201 GURNELL J, 1993, MAMMAL REV, V23, P127 GURNELL J, 1996, J APPL ECOL, V33, P325 GURNELL J, 1997, HDB BRIT MAMMALS, P186 HODDER K, 1998, SPECIAL PUBLICATION, V6, P267 KENWARD RE, 1983, MAMMAL REV, V13, P159 KENWARD RE, 1998, J ZOOL 1, V244, P7 KOPROWSKI JL, 1991, J MAMMAL, V72, P367 KOPROWSKI JL, 1993, CAN J ZOOL, V71, P224 KOPROWSKI JL, 1994, MAMMALIAN SPECIES, V480, P1 LEVER C, 1994, NATURALIZED ANIMALS LIMA SL, 1996, TRENDS ECOL EVOL, V11, P131 LURZ PWW, 1995, FOREST ECOL MANAG, V79, P79 LURZ PWW, 1997, ANIM BEHAV 2, V54, P427 MCCARTHY MA, 1995, BIOL CONSERV, V73, P93 NIXON CM, 1975, J WILDLIFE MANAGE, V39, P426 RODRIGUEZ A, 1999, J APPL ECOL, V36, P649 RUSHTON SP, 1995, SCOTTISH NATURAL HER, V76 RUSHTON SP, 1997, J APPL ECOL, V34, P1137 RUSHTON SP, 1999, ANIMAL CONSERVATION, V2, P111 SHORTEN M, 1951, P ZOOL SOC LOND, V121, P427 SMITH DFE, 1999, THESIS QUEEN MERY WE THOMPSON DC, 1978, BEHAVIOUR, V64, P305 VERBOOM B, 1990, LANDSCAPE ECOL, V4, P171 VOSE D, 1996, QUANTIATIVE RISK ANA WAUTERS L, 1993, BEHAV ECOL SOCIOBIOL, V33, P159 WAUTERS L, 1994, OIKOS, V69, P140 WAUTERS LA, 1995, ECOLOGY, V76, P2460 WAUTERS LA, 1997, CONSERVATION RED SQU, P79 WAUTERS LA, 1997, WILDL BIOL, V3, P117 WAUTERS LA, 1999, ETHOLOGY, V105, P1053 WAUTERS LA, 2000, ECOL RES, V15, P217 WESTERVELT JM, 1990, N8722 ADP US ARM CON 0921-2973 Landsc. Ecol.ISI:000170952100003Univ Newcastle Upon Tyne, Ctr Land Life Sci Modelling, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England. Lurz, PWW, Univ Newcastle Upon Tyne, Ctr Land Life Sci Modelling, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England.Englishl? 'Lynch, Emma Joyce, Damon Fristrup, Kurt2011IAn assessment of noise audibility and sound levels in U.S. National Parks 1297-1309Landscape Ecology269Springer NetherlandsEarth and Environmental Science)Throughout the United States, opportunities to experience noise-free intervals are disappearing. Rapidly increasing energy development, infrastructure expansion, and urbanization continue to fragment the acoustical landscape. Within this context, the National Park Service endeavors to protect acoustical resources because they are essential to park ecology and central to the visitor experience. The Park Service monitors acoustical resources in order to determine current conditions, and forecast the effects of potential management decisions. By community noise standards, background sound levels in parks are relatively low. By wilderness criteria, levels of noise audibility are remarkably high. A large percentage of the noise sources measured in national parks (such as highways or commercial jet traffic) originates outside park boundaries and beyond the management jurisdiction of NPS. Many parks have adopted noise mitigation plans, but the regional and national scales of most noise sources call for conservation and management efforts on similar scales.+http://dx.doi.org/10.1007/s10980-011-9643-x 0921-297310.1007/s10980-011-9643-x<77Lynn, H. Mohler, C. L. DeGloria, S. D. McCulloch, C. E.1995GError assessment in decision-tree models applied to vegetation analysis323-335Landscape Ecology106Vscale; GIS; accuracy; robustness; prediction NEW-YORK; TOMPKINS COUNTY; FORESTS; KAPPAArticleDecMethods were developed to evaluate the performance of a decision-tree model used to predict landscape-level patterns of potential forest vegetation in central New York State. The model integrated environmental databases and knowledge on distribution of vegetation. Soil and terrain decision-tree variables were derived by processing state-wide soil geographic databases and digital terrain data. Variables used as model inputs were soil parent material, soil drainage, soil acidity, slope position, slope gradient, and slope azimuth. Landscape-scale maps of potential vegetation were derived through sequential map overlay operations using a geographic information system (GIS). A verification sample of 276 field plots was analyzed to determine: (1) agreement between GIS-derived estimates of decision-tree variables and direct field measurements, (2) agreement between vegetation distributions predicted using GIS-derived estimates and using field observations, (3) effect of misclassification costs on prediction agreement, (4) influence of particular environmental variables on model predictions, and (5) misclassification rates of the decision-tree model. Results indicate that the prediction model was most sensitive to drainage and slope gradient, and that the imprecision of the input data led to a high frequency of incorrect predictions of vegetation. However, in many cases of misclassification the predicted vegetation was similar to that of the field plots so that the cost of errors was less than expected from the misclassification rate alone. Moreover, since common vegetation types were more accurately predicted than rare types, the model appears to be reasonably good at predicting vegetation for a randomly selected plot in the landscape. The error assessment methodology developed for this study provides a useful approach for determining the accuracy and sensitivity of landscape-scale environmental models, and indicates the need to develop appropriate field sampling procedures for verifying the predictions of such models.://A1995TN14300001 ISI Document Delivery No.: TN143 Times Cited: 9 Cited Reference Count: 36 Cited References: 1981, USDA SOIL CONSERVATI, V296 1987, DATA USERS GUIDE 1991, FIELD GUIDE 1991, MISC PUBL USDA, V1492 AICKIN M, 1990, BIOMETRICS, V46, P293 BRENNAN RL, 1981, EDUC PSYCHOL MEAS, V41, P687 BURROUGH PA, 1986, PRINCIPLES GEOGRAPHI CLINE MG, 1977, SOILS NEW YORK LANDS, V119 COHEN J, 1960, EDUC PSYCHOL MEAS, V20, P37 FLEISS JL, 1981, STATISTICAL METHODS GARDNER RH, 1980, WATER RESOUR RES, V16, P659 GOODCHILD M, 1989, ACCURACY SPATIAL DAT GOODCHILD MF, 1992, INT J GEOGR INF SYST, V6, P87 HEUVELINK GBM, 1993, NETHERLANDS GEOGRAPH, V163 HILL MO, 1975, J ECOL, V63, P597 HUENNEKE LF, 1982, B TORREY BOT CLUB, V109, P51 HUTTON FZ, 1971, SOIL SURVEY CAYUGA C HUTTON FZ, 1972, SOIL SURVEY SENECA C LEWIN DC, 1974, AM MIDL NAT, V91, P315 MARKS PL, 1992, NEW YORK STATE MUSEU, V484, P1 MOHLER CL, UNPUB VEGETATION ENV MOHLER CL, 1991, P ROCHESTER ACAD SCI, V17, P55 MOORE DM, 1991, ENVIRON MANAGE, V15, P59 NEELEY JA, 1965, SOIL SURVEY TOMPKINS ONEILL RV, 1973, RADIONUCLIDES ECOSYS, P898 PUGLIA SP, 1979, SOIL SURVEY SCHUYLER RASTETTER EB, 1992, ECOL APPL, V2, P55 REYBOLD WU, 1989, J SOIL WATER CONSERV, V44, P28 ROSSI RE, 1993, ECOL APPL, V3, P719 SALTELLI A, 1993, COMPUT STAT DATA AN, V15, P211 SEISCHAB FK, 1985, AM MIDL NAT, V114, P77 SEISCHAB FK, 1990, B TORREY BOT CLUB, V117, P27 SMITH BE, 1993, B TORREY BOT CLUB, V120, P229 SNYDER JP, 1982, GEOL SURVERY B, V1532 WHITTAKER RH, 1960, ECOL MONOGR, V30, P279 WILDING LP, 1983, GENESIS SOIL TAXONOM, V1 0921-2973 Landsc. Ecol.ISI:A1995TN14300001CLynn, H, CORNELL UNIV,BIOMETR UNIT,338 WARREN HALL,ITHACA,NY 14853.English^<7Mabry, K. E. Barrett, G. W.2002_Effects of corridors on home range sizes and interpatch movements of three small mammal species629-636Landscape Ecology177 corridor fragmentation landscape matrix movement Peromyscus gossypinus Peromyscus polionotus Sigmodon hispidus VOLE MICROTUS-PENNSYLVANICUS RAT SIGMODON-HISPIDUS POPULATION-DYNAMICS LANDSCAPE CONNECTIVITY HABITAT FRAGMENTATION PATCHES MATRIX RESPONSES PATTERNS SPACEArticleNovCorridors are predicted to benefit populations in patchy habitats by promoting movement, which should increase population densities, gene flow, and recolonization of extinct patch populations. However, few investigators have considered use of the total landscape, particularly the possibility of interpatch movement through matrix habitat, by small mammals. This study compares home range sizes of 3 species of small mammals, the cotton mouse (Peromyscus gossypinus), old-field mouse (P. polionotus) and cotton rat (Sigmodon hispidus) between patches with and without corridors. The study site was in S. Carolina, USA. Corridor presence did not have a statistically significant influence on average home range size. Habitat specialization and sex influenced the probability of an individual moving between 2 patches without corridors. The results of this study suggest that small mammals may be more capable of interpatch movement without corridors than is frequently assumed.://000179746400003 ISI Document Delivery No.: 624EB Times Cited: 10 Cited Reference Count: 44 Cited References: *SAS I, 2001, SAS VERS 8 2 AARS J, 1999, ECOLOGY, V80, P1648 ABERG J, 1995, OECOLOGIA, V103, P265 ANDREN H, 1994, OIKOS, V71, P355 BEIER P, 1998, CONSERV BIOL, V12, P1241 BJORNSTAD ON, 1998, J ANIM ECOL, V67, P127 BOWERS MA, 1996, OECOLOGIA, V105, P107 BOWNE DR, 1999, LANDSCAPE ECOL, V14, P53 BRIESE LA, 1974, J MAMMAL, V55, P615 CAMERON GN, 1981, MAMM SPECIES, V158, P1 CAMERON GN, 1985, OECOLOGIA, V68, P133 CHOATE JR, 1998, J MAMMAL, V79, P1416 COFFMAN CJ, 2001, OIKOS, V93, P3 COLLINS RJ, 1997, LANDSCAPE ECOL, V12, P63 COTHRAN GE, 1991, MAMMALS SAVANNAH RIV DANIELSON BJ, 1999, LANDSCAPE ECOLOGY SM, P89 DANIELSON BJ, 2000, LANDSCAPE ECOL, V15, P323 DAVISBORN R, 2000, CAN J ZOOL, V78, P864 DUNNING JB, 1992, OIKOS, V65, P169 FAHRIG L, 2001, BIOL CONSERV, V100, P65 GASCON C, 1999, BIOL CONSERV, V91, P223 GOLLEY FB, 1965, J MAMMAL, V76, P238 HADDAD NM, 1999, ECOL APPL, V9, P612 HARRIS S, 1990, MAMMAL REV, V20, P97 KIE JG, 1996, WILDLIFE SOC B, V24, P342 KOZAKIEWICZ M, 1993, ACTA THERIOL, V38, P1 LAPOLLA VN, 1993, LANDSCAPE ECOL, V8, P25 LIDICKER WZ, 1999, LANDSCAPE ECOL, V14, P333 MABRY KE, 2001, THESIS U GEORGIA ATH MCINTYRE S, 1999, CONSERV BIOL, V13, P1282 MOHR CO, 1947, AM MIDL NAT, V37, P223 OTT RL, 1993, INTRO STAT METHODS D PITHER J, 1998, OIKOS, V83, P166 RENJIFO LM, 2001, ECOL APPL, V11, P14 RICKETTS TH, 2001, AM NAT, V158, P87 ROSENBERG DK, 1997, BIOSCIENCE, V47, P677 STAMPS JA, 1987, AM NAT, V129, P533 STICKEL LF, 1954, BIOL PEROMYSCUS, P373 TISCHENDORF L, 2000, OIKOS, V90, P7 TURCHIN P, 1998, QUANTITATIVE ANAL MO WHITE GC, 1990, ANAL WILDLIFE RADIOT WOLFE JL, 1977, MAMM SPECIES, V70, P1 WOLFF JO, 1985, CAN J ZOOL, V63, P2657 YAHNER RH, 1997, CONSERV BIOL, V11, P569 0921-2973 Landsc. Ecol.ISI:000179746400003tUniv Georgia, Inst Ecol, Athens, GA 30602 USA. Mabry, KE, Univ Calif Davis, Sect Evolut & Ecol, Davis, CA 95616 USA.English|?8MacDonald, Darla Hatton Bark, Rosalind H. Coggan, Anthea2014jIs ecosystem service research used by decision-makers? A case study of the Murray-Darling Basin, Australia 1447-1460Landscape Ecology298OctThis paper investigates the accessibility and usefulness of the Ecosystem Services (ES) framework to policy analysts. Using a mixed methods approach of document analysis and semi-structured interviews we examine how an ES assessment of the benefits of restoring water to the Murray-Darling Basin (MDB) in Australia has been used by government agencies in policy and planning. The ES assessment links changes in water management under the Basin Plan with modelled changes in water quality, river flows and inundation patterns and in turn to modelled freshwater and estuarine ecosystem response. These ecological responses were expressed in terms of incremental ES benefits which were valued monetarily using a variety of valuation techniques. To investigate how these pieces of information were used in the policy debate around the re-allocation of water in the MDB, semi-structured interviews were conducted with 20 Australian, State, and local government officials as well as academics and consultants. The interviews were designed to uncover the complex information dissemination process through networks within and among agencies. The results are mixed as to whether the assessment served to influence public policy. The report has been utilized and cited by Australian federal agencies, the downstream State of South Australia and conservation-based NGOs in their position statements and as such has been used as evidence in support of re-allocation of water in the MDB. A number of interview participants commented that the ES assessment raised awareness and this may lead to broader usage of the information and framework in the implementation phase of MDB water reform.!://WOS:000342078600014Times Cited: 1 0921-2973WOS:00034207860001410.1007/s10980-014-0021-3|?Macedo, Diego R. Hughes, Robert M. Ligeiro, Raphael Ferreira, Wander R. Castro, Miriam A. Junqueira, Nara T. Oliveira, Deborah R. Firmiano, Kele R. Kaufmann, Philip R. Pompeu, Paulo S. Callisto, Marcos2014vThe relative influence of catchment and site variables on fish and macroinvertebrate richness in cerrado biome streams 1001-1016Landscape Ecology296JulLandscape and site-scale data analyses aid the interpretation of biological data and thereby help us develop more cost-effective natural resource management strategies. Our study focused on environmental influences on stream assemblages and we evaluated how three classes of environmental variables (geophysical landscape, land use and cover, and site habitat), influence fish and macroinvertebrate assemblage richness in the Brazilian Cerrado biome. We analyzed our data through use of multiple linear regression (MLR) models using the three classes of predictor variables alone and in combination. The four MLR models explained dissimilar amounts of benthic macroinvertebrate taxa richness (geophysical landscape R (2) a parts per thousand 35 %, land use and cover R (2) a parts per thousand 28 %, site habitat R (2) a parts per thousand 36 %, and combined R (2) a parts per thousand 51 %). For fish assemblages, geophysical landscape, land use and cover, site habitat, and combined models explained R (2) a parts per thousand 28 %, R (2) a parts per thousand 10 %, R (2) a parts per thousand 31 %, and R (2) a parts per thousand 47 % of the variability in fish species richness, respectively. We conclude that (1) environmental variables differed in the degree to which they explain assemblage richness, (2) the amounts of variance in assemblage richness explained by geophysical landscape and site habitat were similar, (3) the variables explained more variability in macroinvertebrate taxa richness than in fish species richness, and (4) all three classes of environmental variables studied were useful for explaining assemblage richness in Cerrado headwater streams. These results help us to understand the drivers of assemblage patterns at regional scales in tropical areas.!://WOS:000338331600007Times Cited: 1 0921-2973WOS:00033833160000710.1007/s10980-014-0036-9? MacPherson, Jenny Bright, Paul2011Metapopulation dynamics and a landscape approach to conservation of lowland water voles (<i>Arvicola amphibius</i>) 1395-1404Landscape Ecology2610Springer NetherlandsEarth and Environmental ScienceEffective conservation management for species that function as metapopulations requires an understanding of population dynamics at the landscape scale. The water vole, Arvicola amphibius , is one such species. Water voles have recently undergone a significant decline in the UK, as a result of habitat loss and predation from the introduced American mink, Neovison vison . Large reed bed and grazing marsh sites can provide refuge habitats for water voles from mink predation, in which case populations within these sites could sustain metapopulations in the surrounding landscape where conditions are less favourable. We carried out a study using a stochastic patch occupancy model to determine the long term viability of water vole metapopulations in the wider landscape around a series of extensive reed bed and grazing marsh sites designated as National Key Sites for water voles. The results of our model simulations show that a large protected core site, or mainland, is essential in maintaining the long term viability of these systems. Our results also show how these metapopulations could be enhanced by increasing patch numbers through habitat creation and/or restoration and suggest what the minimum effective size of created or restored patches should be. The study shows how population modelling can provide insight into some effective practical ways of enhancing the viability of water vole metapopulations at the landscape scale. Furthermore it demonstrates that extensive wetlands are an appropriate focus for water vole conservation measures.+http://dx.doi.org/10.1007/s10980-011-9669-0 0921-297310.1007/s10980-011-9669-0 |?( -MacRaild, L. M. Radford, J. Q. Bennett, A. F.2010hNon-linear effects of landscape properties on mistletoe parasitism in fragmented agricultural landscapes395-406Landscape Ecology253@Ecological processes such as plant-animal interactions have a critical role in shaping the structure and function of ecosystems, but little is known of how such processes are modified by changes in landscape structure. We investigated the effect of landscape change on mistletoe parasitism in fragmented agricultural environments by surveying mistletoes on eucalypt host trees in 24 landscapes, each 100 km(2) in size, in south-eastern Australia. Landscapes were selected to represent a gradient in extent (from 60% to 2% cover) and spatial pattern of remnant wooded vegetation. Mistletoes were surveyed at 15 sites in each landscape, stratified to sample five types of wooded elements in proportion to their relative cover. The incidence per landscape of box mistletoe (Amyema miquelii), the most common species, was best explained by the extent of wooded cover (non-linear relationship) and mean annual rainfall. Higher incidence occurred in landscapes with intermediate levels of cover (15-30%) and higher rainfall (> 500 mm). Importantly, a marked non-linear decline in the incidence of A. miquelii in low-cover landscapes implies a disproportionate loss of this species in remaining wooded vegetation, greater than that attributable to decreasing forest cover. The most likely mechanism is the effect of landscape change on the mistletoebird (Dicaeum hirundinaceum), the primary seed-dispersal vector for A. miquelii. Our results are consistent with observations that habitat fragmentation initially enhances mistletoe occurrence in agricultural environments; but in this region, when wooded vegetation fell below a threshold of similar to 15% landscape cover, the incidence of A. miquelii declined precipitously. Conservation management will benefit from greater understanding of the components of landscape structure that most influence ecological processes, such as mistletoe parasitism and other plant-animal mutualisms, and the critical stages in such relationships. This will facilitate action before critical thresholds are crossed and cascading effects extend to other aspects of ecosystem function.!://WOS:000275122600006Times Cited: 0 0921-2973WOS:00027512260000610.1007/s10980-009-9414-0z|?Madsen, J. Boertmann, D.2008aAnimal behavioral adaptation to changing landscapes: spring-staging geese habituate to wind farms 1007-1011Landscape Ecology239JWind farms are positioned in open landscapes and may cause loss of wildlife habitat due to disturbance, fragmentation, and infrastructure development. Especially flocking geese, swans, ducks and waders are regarded as vulnerable to wind farm development. We compared past and current displacement effects of two onshore wind farms and a line of land-based turbines on spring-staging pink-footed geese (Anser brachyrhynchus) to see if there was evidence of habituation. In one wind farm area, geese previously (1998) (Larsen and Madsen 2000) kept a distance of c. 200 m (the distance at which 50% of peak densities is reached) and they did not go between the turbines; today (2008) they keep a distance of c. 100 m, but do still not enter the wind farm area. In another wind farm, where foraging geese previously (2000) kept a distance of more than 100 m and did not enter the wind farm, they now (2008) forage between the wind turbines and keep a distance of c. 40 m to turbines. In 1998, geese kept a distance of 125 m to a line of turbines, compared to 50 m now. We conclude that geese have behaviorally adapted to changing landscapes created by wind farms. The difference in avoidance between the sites may be due to the sizes of the turbines which in this study were small in both rotor-swept area and in height compared to more recent "industry standard" of 2.5 and 3.0 MW turbines. The study points to the need for longer term studies to properly assess the impact of wind farms on wildlife, including consequent increased risks from inclement weather events of feeding, rafting, and migrating waterfowl.!://WOS:000260283100001Times Cited: 0 0921-2973WOS:00026028310000110.1007/s10980-008-9269-9 t<7Magda, D. Gonnet, J. F.2001Consequences of less intensive farming on the landscape: an example of vegetation dominance by Chaerophyllum aureum in the meadows of a Pyrenean valley in France491-500Landscape Ecology166Chaerophyllum aureum grassland invasion land use changes polyphenols population seed dispersal GRASSLANDS MANAGEMENT DISPERSAL PASTURES ECOLOGYArticleAugThe impact of agricultural practices on the dynamics of weed invasion in a rural landscape was studied by describing the spatial distribution of Chaerophyllum aureum populations colonising less intensive managed hay meadows. Polyphenol compounds were used as individual markers to identify the structure of C aureum diversity, in terms of its scale and patterns, within and between fields along the bottom of a Pyrenean valley. The results revealed, firstly, the existence of a dominant 'genotype' successfully colonising the entire area, and secondly, the maintenance of high levels of polyphenol diversity within five different populations. This spatial arrangement of 'genetic' population diversity was obviously not related to the natural reproduction and dispersal patterns of this species, but to human practices of hay production, the principal effect of which is to mix seeds of different genetic origin and thus accelerate and amplify the colonisation process of adapted 'genotypes'.://000172548800002 ISI Document Delivery No.: 499AW Times Cited: 1 Cited Reference Count: 26 Cited References: AULD BA, 1986, ECOLOGY BIOL INVASIO, P79 BAKKER JP, 1996, ACTA BOT NEERL, V45, P461 BEKKER RM, 1997, P 6 ANN IALE 5UK C S BOYET C, 1989, BIOCHEM SYST ECOL, V17, P443 BUTTENSCHON J, 1988, ASPECTS APPL BIOL, V16, P373 CROWDEN RK, 1969, PHYTOCHEMISTRY, V8, P1963 FIASSON JL, 1987, BIOCH SYST ECOL, V15, P225 FISCHER SF, 1996, J APPL ECOL, V33, P1206 GONNET JF, 1980, BIOCH SYST ECOL, V8, P55 GONNET JF, 1983, PHYTOCHEMISTRY, V22, P1421 GONNET JF, 1986, BIOCH SYST ECOL, V14, P409 GONNET JF, 1989, BIOCH SYST ECOL, V20, P149 GONNET JF, 1989, THESIS U C BERNARD L GRIME JP, 1988, COMP PLANT ECOLOGY HOBBS RJ, 1995, CONSERV BIOL, V9, P761 JURGENS CR, 1992, TOOLS SPATIAL ANAL L LONSDALE WM, 1993, J ECOL, V81, P513 MACK RN, 1985, STUDIES PLANT DEMOGR, P127 MAGDA D, 2000, J VEG SCI, V11, P485 MCKENZIE FR, 1997, TROP GRASSLANDS, V31, P24 POSCHLOD P, 1996, SPECIES SURVIVAL FRA, P123 SANLAVILLE C, 1988, AGRONOMIE, V8, P341 STOHLGREN TJ, 1999, ECOL APPL, V9, P45 STRYKSTRA RJ, 1997, P 6 ANN IALE UK C SE TSUYUZAKI S, 1996, AM J BOT, V83, P1422 VEGELIN K, 1997, P 6 ANN IALE 5UK C S 0921-2973 Landsc. Ecol.ISI:000172548800002INRA, SAD, Unite Agron, F-31326 Castanet Tolosan, France. Magda, D, INRA, SAD, Unite Agron, BP 27, F-31326 Castanet Tolosan, France.English |7*Magle, S. B. Theobald, D. M. Crooks, K. R.2009A comparison of metrics predicting landscape connectivity for a highly interactive species along an urban gradient in Colorado, USA267-280Landscape Ecology242connectivity landscape metrics prairie dog urban ecology habitat fragmentation tailed prairie dogs patch isolation metrics cynomys-ludovicianus spatial ecology metapopulation dynamics conservation habitat fragmentation urbanization biodiversityFeb@Many organisms persist in fragmented habitat where movement between patches is essential for long-term demographic and genetic stability. In the absence of direct observation of movement, connectivity or isolation metrics are useful to characterize potential patch-level connectivity. However, multiple metrics exist at varying levels of complexity, and empirical data on species distribution are rarely used to compare performance of metrics. We compared 12 connectivity metrics of varying degrees of complexity to determine which metric best predicts the distribution of prairie dog colonies along an urban gradient of 385 isolated habitat patches in Denver, Colorado, USA. We found that a modified version of the incidence function model including area-weighting of patches and a cost-weighted distance surface best predicted occupancy, where we assumed roads were fairly impermeable to movement, and low-lying drainages provided dispersal corridors. We also found this result to be robust to a range of cost weight parameters. Our results suggest that metrics should incorporate both patch area and the composition of the surrounding matrix. These results provide guidance for improved landscape habitat modeling in fragmented landscapes and can help identify target habitat for conservation and management of prairie dogs in urban systems.://000262828900010-399WB Times Cited:0 Cited References Count:76 0921-2973ISI:000262828900010AMagle, SB Univ Wisconsin, Nelson Inst Environm Studies, 70 Sci Hall, Madison, WI 53706 USA Colorado State Univ, Dept Fish Wildlife & Conservat Biol, Ft Collins, CO 80523 USA Colorado State Univ, Dept Human Dimens Nat Resources, Ft Collins, CO 80523 USA Colorado State Univ, Nat Resource Ecol Lab, Ft Collins, CO 80523 USADoi 10.1007/S10980-008-9304-XEnglish8|?8 %Magura, T. Horvath, R. Tothmeresz, B.2010PEffects of urbanization on ground-dwelling spiders in forest patches, in Hungary621-629Landscape Ecology254Effects of urbanization on ground-dwelling spiders (Araneae) were studied using pitfall traps along an urban-suburban-rural forest gradient in Debrecen (Hungary). We found that overall spider species richness was significantly higher in the urban sites compared to the suburban and rural ones. The increased diversity was due to the significantly more open-habitat species in the assemblages at the urban sites. This suggests that species from the surrounding matrix (grasslands and arable lands) penetrated the disturbed urban sites. The ratio of forest species was significantly higher in the rural sites than in the suburban and urban ones, suggesting that forest species are indeed sensitive to the disturbance caused by urbanization. Canonical correspondence analysis revealed that the species composition changed remarkably along the urbanization gradient. Open-habitat spiders were associated with the urban sites of higher ground and air temperature. Forest spiders were characteristic of the rural sites with higher amount of decaying woods. Our findings suggest that the overall diversity was not the most appropriate indicator of disturbance; species with different habitat affinity should be analyzed separately to get an ecologically relevant picture of the effect of urbanization.!://WOS:000275444100010Times Cited: 0 0921-2973WOS:00027544410001010.1007/s10980-009-9445-6N<7$Magura, T. Tothmeresz, B. Molnar, T.2004eChanges in carabid beetle assemblages along an urbanisation gradient in the city of Debrecen, Hungary747-759Landscape Ecology197tcarabid beetles; GlobeNet; human disturbance; increased disturbance hypothesis; intermediate disturbance hypothesis; mean body size hypothesis; species richness; urbanisation SMALL-SCALE HETEROGENEITY; URBAN-RURAL GRADIENTS; GROUND-BEETLES; AGRICULTURAL LANDSCAPE; HABITAT FRAGMENTATION; SPATIAL-DISTRIBUTION; SUCCESSION GRADIENT; FORESTRY CYCLE; BOREAL FOREST; COLEOPTERAArticle2Responses of carabid beetles (Coleoptera: Carabidae) to urbanisation were studied along an urban-suburban-rural gradient representing decreasing intensities of human disturbance. Carabids were collected by pitfall trapping during their activity period in lowland oak forest patches in the city of Debrecen, Eastern Hungary. The average number of carabid species was significantly higher in the rural and urban areas compared to the suburban one. The high overall species richness in the urban area was due to the presence of species preferring open habitats. The species richness of forest specialist carabids significantly increased along the urban-rural gradient. The overall carabid abundance was significantly higher in the rural than the other two areas. The results did not support the hypothesis that overall diversity should decrease in response to habitat disturbance. They also contradicted the intermediate disturbance hypothesis: species richness was not the highest in the moderately disturbed suburban area. In the urban area, opportunistic species dominated. The average carabid body size was significantly larger in the rural and suburban areas than in the more disturbed urban area. Multivariate methods detected changes in species composition and abundance structure along the urban-rural gradient. Significant proportion of the variation in abundance and species richness was explained by the heterogeneity of environmental variables (ground temperature, surface temperature, humidity, cover of decaying wood material, herbs, canopy layer, and by the amount of prey).://000226384000004 n ISI Document Delivery No.: 888OL Times Cited: 5 Cited Reference Count: 67 Cited References: ALARUIKKA DM, 2003, J INSECT CONSERVATIO, V6, P195 BLAKE S, 1994, PEDOBIOLOGIA, V38, P502 BRYAN KM, 1984, ECOL ENTOMOL, V9, P251 BURKE D, 1998, ECOGRAPHY, V21, P472 BUTTERFIELD J, 1997, ECOGRAPHY, V20, P614 CONNELL JH, 1978, SCIENCE, V199, P1302 DAVIES KF, 1998, J ANIM ECOL, V67, P460 DAVIS BNK, 1978, DIVERSITY INSECT FAU, P126 DENBOER PJ, 1985, OECOLOGIA, V67, P322 DESENDER K, 1999, BELG J ZOOL, V129, P139 DIDHAM RK, 1996, TRENDS ECOL EVOL, V11, P255 DUFRENE M, 1997, ECOL MONOGR, V67, P345 ELEK Z, 2001, WEB ECOLOGY, V2, P32 EYRE MD, 2002, J INSECT CONSERVATIO, V6, P25 FOURNIER E, 1999, ECOGRAPHY, V22, P87 FOURNIER E, 2001, LANDSCAPE ECOL, V16, P17 GILBERT OL, 1989, ECOLOGY URBAN HABITA GODEFROID S, 2003, LANDSCAPE URBAN PLAN, V54, P1 GRAY JS, 1987, ORG COMMUNITIES PAST, P53 GRAY JS, 1989, BIOL J LINN SOC, V37, P19 GUILLEMAIN M, 1997, ACTA OECOL, V18, P465 HOLLIDAY NJ, 1991, CAN ENTOMOL, V123, P1369 HURKA K, 1996, CARABIDAE CZECH SLOV KOIVULA M, 1999, ECOGRAPHY, V22, P424 KOIVULA M, 2002, BIODIVERS CONSERV, V11, P1269 KOIVULA M, 2002, FOREST ECOL MANAG, V167, P103 KUTNER M, 1996, APPL LINEAR STAT MOD LEGENDRE P, 1998, NUMERICAL ECOLOGY LOVEI GL, 1984, PEDOBIOLOGIA, V26, P271 LOVEI GL, 1996, ANNU REV ENTOMOL, V41, P231 MADER HJ, 1984, BIOL CONSERV, V29, P81 MADER HJ, 1990, BIOL CONSERV, V54, P209 MAGURA T, 1997, ACTA ZOOL ACAD SCI H, V43, P173 MAGURA T, 2000, ACTA ZOOL ACAD SCI H, V46, P1 MAGURA T, 2000, BIOL CONSERV, V93, P95 MAGURA T, 2001, BIODIVERS CONSERV, V10, P287 MAGURA T, 2001, J BIOGEOGR, V28, P129 MAGURA T, 2002, EUR J SOIL BIOL, V38, P291 MAGURA T, 2002, FOREST ECOL MANAG, V157, P23 MAGURA T, 2003, BIODIVERS CONSERV, V12, P73 MCDONNELL MJ, 1990, ECOLOGY, V71, P1232 MCDONNELL MJ, 1997, URBAN ECOSYSTEMS, V1, P21 MCINTYRE NE, 2001, LANDSCAPE URBAN PLAN, V52, P257 NAEEM S, 1994, NATURE, V368, P734 NIEMELA J, 1992, J BIOGEOGR, V19, P173 NIEMELA J, 1994, PERSPECTIVES INSECT, P29 NIEMELA J, 1996, ECOGRAPHY, V19, P352 NIEMELA J, 1999, BIODIVERS CONSERV, V8, P119 NIEMELA J, 2000, J INSECT CONSERV, V4, P3 NIEMELA J, 2002, LANDSCAPE ECOL, V17, P387 NIEMELA JK, 1994, ECOGRAPHY, V17, P166 POCS T, 1997, ABSTR BOTANICA, V21, P135 POUYAT RV, 1997, URBAN ECOSYSTEMS, V1, P117 PROBST JR, 1991, J FOREST, V89, P12 RAINIO J, 2003, BIODIVERS CONSERV, V12, P489 SCOTT WA, 2002, BIOL CONSERV, V110, P197 SERGEEVA TK, 1994, CARABID BEETLES ECOL, P367 SOKAL RR, 1995, BIOMETRY SPENCE JR, 1988, MEMOIRS ENTOMOLOGICA, P151 SPENCE JR, 1994, CAN ENTOMOL, V126, P881 SPENCE JR, 1996, ANN ZOOL FENN, V33, P173 STORK N, 1990, ROLE GROUND BEETLES SUSTEK Z, 1987, BIOLOGIA, V42, P145 THIELE HU, 1977, CARABID BEETLES THEI TONTERI T, 1990, ANN BOT FENN, V27, P337 VIDA G, 1978, ENVIRON CONSERV, V5, P127 WOOTTON JT, 1998, AM NAT, V152, P803 0921-2973 Landsc. Ecol.ISI:000226384000004Hortobagy Natl Pk Directorate, H-4002 Debrecen, Hungary. Debrecen Univ, Inst Ecol, H-4010 Debrecen, Hungary. Debrecen Univ, Dept Zool, H-4010 Debrecen, Hungary. Magura, T, Hortobagy Natl Pk Directorate, POB 216, H-4002 Debrecen, Hungary. magura@www.hnp.huEnglish<7Maheu-Giroux, M. de Blois, S.2007QLandscape ecology of Phragmites australis invasion in networks of linear wetlands285-301Landscape Ecology222Iinvasive species; agricultural weed; common reed; corridor; linear habitat; autoregressive model; network-K function; road ecology; spatial point pattern analysis; autocorrelation POINT PATTERN-ANALYSIS; COMMON REED; SPATIAL AUTOCORRELATION; K-FUNCTION; AGRICULTURAL LANDSCAPE; CRYPTIC INVASION; SPREAD; MODEL; WATER; POPULATIONSArticleFebThe interaction between landscape structure and spatial patterns of plant invasion has been little addressed by ecologists despite the new insights it can provide. Because of their spatial configuration as highly connected networks, linear wetlands such as roadside or agricultural ditches, can serve as corridors facilitating invasion at the landscape scale, but species dynamics in these important habitats are not well known. We conducted a landscape scale analysis of Phragmites australis invasion patterns (1985-2002 and 1987-2002) in two periurban areas of southern Quebec (Canada) focusing on the interaction between the network of linear wetlands and the adjacent land-uses. Results show that, at the beginning of the reference period, the two landscapes were relatively non-invaded and populations occurred mostly in roadside habitats which then served as invasion foci into other parts of the landscape. The intrinsic rates of increase of P. australis populations in linear anthropogenic habitats were generally higher than those reported for natural wetlands. Riparian habitats along streams and rivers were little invaded compared to anthropogenic linear wetlands, except when they intersected transportation rights-of-way. Bivariate spatial point pattern analysis of colonization events using both Euclidian and network distances generally showed spatial dependence (association) to source populations. An autologistic regression model that included landscape and edaphic variables selected transportation rights-of-way as the best predictor of P. australis occurrence patterns in one of the landscapes. Given the high invasion rates observed, managers of linear wetlands should carefully monitor expansion patterns especially when roads intersect landscapes of conservation or economic value.://000243823900011 ISI Document Delivery No.: 130UG Times Cited: 0 Cited Reference Count: 63 Cited References: *AGR CAN, 1952, CART SOLS IL MONTR J *AGR CAN, 1991, CART GEOL COMT CHAMB *USDA, 2003, NAT RES CONS SERV AILSTOCK M, 2001, RESTOR ECOL, V21, P49 AKAIKE H, 1973, 2 INT S INF THEOR, P267 AUGUSTIN NH, 1996, J APPL ECOL, V33, P339 BADDELEY A, 2005, J STAT SOFTW, V12, P1 BEAUCHEMIN S, 1998, J ENVIRON QUAL, V27, P721 BETTS MG, 2006, ECOL MODEL, V191, P197 CATLING PM, 2003, CAN BOT ASS B, V36, P4 DEBLOIS S, 2004, ENVIRON MANAGE, V33, P606 DECKERS B, 2005, ECOGRAPHY, V28, P99 DELISLE F, 2003, J BIOGEOGR, V30, P1 DOMON G, 1993, LANDSCAPE URBAN PLAN, V25, P53 EKSTAM B, 1999, SEED SCI RES, V9, P157 FORMAN RTT, 1998, ANNU REV ECOL SYST, V29, P207 FOXCROFT LC, 2004, DIVERS DISTRIB, V10, P427 GRATTON C, 2005, RESTOR ECOL, V13, P358 GUMPERTZ ML, 2000, FOREST SCI, V46, P97 HAASE P, 1995, J VEG SCI, V6, P575 HAVENS KJ, 1997, ENVIRON MANAGE, V21, P599 HEWITT JE, 1997, J EXP MAR BIOL ECOL, V216, P77 HUDON C, 2005, ECOSCIENCE, V12, P347 JAMIESON A, 2003, CAN BIOSYST ENG, V45 KEITT TH, 2002, ECOGRAPHY, V25, P616 KELLER BEM, 2000, WETLANDS ECOLOGY MAN, V8, P391 KLUTE DS, 2002, PREDICTING SPECIES O, P335 KOTSCHY KA, 2000, FOLIA GEOBOT, V35, P363 KRISTENSEN SP, 2002, J ENVIRON MANAGE, V66, P171 KRUMSCHEID P, 1989, AQUAT BOT, V35, P57 LAMONTAGNE L, 1997, AGR AGROALIMENTAIRE, P59 LATHROP RG, 2003, ESTUARIES, V26, P423 LAVOIE C, 2003, J BIOGEOGR, V30, P537 LEE KW, 2004, KOREAN J REMOTE SENS, V20, P57 LEGENDRE P, 1989, VEGETATIO, V80, P107 LEGENDRE P, 1993, ECOLOGY, V74, P1659 LICHSTEIN JW, 2002, ECOL MONOGR, V72, P445 MAHEUGIROUX M, 2005, AQUAT BOT, V83, P310 MAL TK, 2004, CAN J PLANT SCI, V84, P365 MCKEE J, 1996, NEW PHYTOL, V133, P233 MORAN PAP, 1950, BIOMETRIKA, V37, P17 NAGELKERKE NJD, 1991, BIOMETRIKA, V78, P691 NAYLOR S, 2003, WATER SCI TECHNOL, V48, P215 OHSER J, 1983, MATH OPERATIONSFORSC, V14, P63 OKABE A, 2001, GEOGR ANAL, V33, P271 OKABE A, 2004, SANET TOOLBOX SPATIA RIPLEY BD, 1976, J APPL PROBAB, V13, P255 ROUGET M, 2003, AM NAT, V162, P713 SALTONSTALL K, 2002, P NATL ACAD SCI USA, V99, P2445 SALTONSTALL K, 2003, WETLANDS, V23, P1043 SCHRODER P, 2005, Z NATURFORSCH C, V60, P317 SPOONER PG, 2004, APPL VEG SCI, V7, P61 SPOONER PG, 2004, LANDSCAPE ECOL, V19, P491 SUN G, 1999, WATER SCI TECHNOL, V40, P139 VASQUEZ EA, 2005, MAR ECOL-PROG SER, V298, P1 WEINSTEIN MP, 1999, ESTUARIES, V22, P793 WEISSER PJ, 1981, BOTHALIA, V13, P553 WIEGAND T, 1998, AM NAT, V152, P321 WIEGAND T, 2004, OIKOS, V104, P209 WIEGAND T, 2006, J ECOL, V94, P825 WILCOX KL, 2003, J GREAT LAKES RES, V29, P664 WITH KA, 2002, CONSERV BIOL, V16, P1192 ZEDLER JB, 2004, CRIT REV PLANT SCI, V23, P431 0921-2973 Landsc. Ecol.ISI:000243823900011McGill Univ, Dept Plant Sci, Ste Anne De Bellevue, PQ H9X 3V9, Canada. de Blois, S, McGill Univ, Sch Environm, 3534 Univ St, Montreal, PQ H3A 2A7, Canada. sylvie.deblois@mcgill.caEnglish<7eMalanson, G. P.19976Effects of feedbacks and seed rain on ecotone patterns27-38Landscape Ecology121ecotone; positive feedback; seed rain; simulation; treeline ALPINE TREELINE ECOTONE; PLANT-COMMUNITIES; NATIONAL-PARK; FOREST; MODEL; VEGETATION; GRADIENTS; DYNAMICS; REGENERATION; COMPETITIONArticleFebEcotones can be abrupt changes in vegetation on gradual abiotic gradients, such as some treelines, and so have been considered as potential indicators of response to climatic change and regulators of fluxes across landscapes. Factors of positive feedback for growth and establishment and seed rain from source areas have been suggested as playing a role in such patterns and dynamics. The effects of variation in feedback strength and seed rain on the abrupt pattern have not, however, been assessed. A spatially explicit computer simulation is used to represent an ecotone as might occur at a mountain treeline. The steepness of the abiotic gradient determines the general location of the treeline, while the strength of feedback determines how abrupt it is. Increased seed rain and seedling survival modify the dominant patterns by creating patches of krummholz or small seedings. The feedbacks are spatially autocorrelated and so create waves of mortality and regeneration on the simulated slopes comparable to dynamics observed on some mountains. These dynamics may mean that the pattern at the ecotone at any point in time is ephemeral and may respond differently to environmental change.://A1997XQ44800004 P ISI Document Delivery No.: XQ448 Times Cited: 30 Cited Reference Count: 51 Cited References: ALLEN TR, 1996, SPATIAL COMPOSITIONA ARMAND AD, 1992, LANDSCAPE BOUNDARIES, P360 AUSTIN MP, 1989, VEGETATIO, V83, P35 BENEDICT JB, 1984, ECOLOGY, V65, P820 BILLINGS WD, 1969, VEGETATIO, V19, P192 BONAN GB, 1992, SYSTEMS ANAL GLOBAL, P404 BOTKIN DB, 1972, IBM J RES DEV, V16, P101 BOTKIN DB, 1993, FOREST DYNAMICS BROWN DG, 1994, J VEG SCI, V5, P641 BUTLER DR, 1994, PHYTOCOENOLOGIA, V22, P485 CAIRNS DM, 1994, PHYSICAL GEOGR, V15, P104 CHALITA S, 1994, CLIM DYNAM, V10, P231 CLEMENTS FE, 1905, RES METHODS ECOLOGY FOSTER JR, 1988, J ECOL, V76, P172 GOMI S, 1956, SAISHUU TO SHIIKU, V18, P66 GOSZ JR, 1989, LANDSCAPE ECOLOGY, V3, P229 GREEN DG, 1990, MATH COMPUT MODEL, V13, P75 HAEFNER JW, 1991, ECOL MODEL, V56, P221 HANSON JS, 1990, ECOL MODEL, V49, P277 HARDT RA, 1989, ECOLOGY, V70, P1252 HUSTON M, 1987, AM NAT, V130, P168 HUSTON M, 1992, INDIVIDUAL BASED MOD, P408 KUPFER JA, 1993, LANDSCAPE ECOL, V8, P185 MALANSON GP, 1994, PHYSICAL GEOGR, V15, P166 MALANSON GP, 1996, ECOL MODEL, V87, P91 MALANSON GP, 1996, GIS ENV MODELING PRO, P243 MALANSON GP, 1996, UNPUB EFFECTS DISPER MILNE BT, 1996, IN PRESS ECOLOGY NEILSON RP, 1993, ECOL APPL, V3, P385 NOBLE IR, 1993, ECOL APPL, V3, P396 PORTNOY S, 1993, EVOL ECOL, V7, P25 PULLIAM HR, 1988, AM NAT, V132, P652 RISSER PG, 1995, BIOSCIENCE, V45, P318 SATO K, 1993, ECOLOGY, V74, P1538 SHUGART HH, 1977, J ENVIRON MANAGE, V5, P161 SHUGART HH, 1988, CAN J BOT, V66, P2634 SLATYER RO, 1992, LANDSCAPE BOUNDARIES, P346 SMITH T, 1989, VEGETATIO, V83, P49 STEVENS GC, 1991, ANNU REV ECOL SYST, V22, P177 STEVENS GC, 1992, AM NAT, V140, P893 TIMONEY KP, 1993, J VEG SCI, V4, P387 TRANQUILLINI W, 1979, PHYSL ECOLOGY ALPINE VANDERMAAREL E, 1990, J VEG SCI, V1, P135 WALSH SJ, 1992, GEOGRAPHICAL SNAPSHO, P167 WALSH SJ, 1994, J VEG SCI, V5, P657 WEISBERG PJ, 1995, CAN J FOREST RES, V25, P1326 WILSON JB, 1992, ADV ECOL RES, V23, P263 WILSON WG, 1995, UNPUB COOPERATION CO WOODWARD FI, 1993, ECOL APPL, V3, P404 YAMAMURA N, 1976, B MATH BIOL, V38, P517 ZOONEVELD IS, 1995, J VEG SCI, V5, P441 0921-2973 Landsc. Ecol.ISI:A1997XQ44800004IMalanson, GP, UNIV IOWA,CTR GLOBAL & REG ENVIRONM RES,IOWA CITY,IA 52246.Englishp<7"Malard, F. Tockner, K. Ward, J. V.20006Physico-chemical heterogeneity in a glacial riverscape679-695Landscape Ecology158flow path flood pulse glacial river hydrological connectivity riverscape heterogeneity water chemistry water source FLOODPLAIN LAKES HYDROLOGICAL CONNECTIVITY NUTRIENT DYNAMICS WATER ECOSYSTEMS STREAMS CONTRACTION GROUNDWATER SWITZERLAND EXPANSIONArticleDecSpatio-temporal heterogeneity in physico-chemical conditions associated with the annual expansion/contraction cycle in a complex glacial flood plain of the Swiss Alps was investigated employing a landscape approach. The diverse and dynamic aquatic habitats of the flood plain were visualized as an aquatic mosaic or riverscape. Based on samples collected at ca. monthly intervals for 1.5 yr along 17 floodplain transects, the 3 components of riverscape heterogeneity, extent, composition, and configuration, were quantified using categorical maps and indices of landscape patterns for turbidity and specific conductance. Changes in the spatial heterogeneity of 13 other physico-chemical parameters were further analyzed by means of a within-dates principal component analysis. Riverscape heterogeneity (RH), quantified by applying several indices of landscape pattern to turbidity and specific conductance data, was minimum during groundwater-dominated base flow in winter. Despite an increase in surface connectivity in the channel network with rising discharge, RH rose in spring and summer as additional chemically-distinct water sources (i.e., snowmelt runoff and glacial ablation) contributed to surface flow within the flood plain. Most other physico-chemical variables measured during this study exhibited the same spatio-temporal heterogeneity as turbidity and specific conductance. Overall, the glacial flood plain shifted from a monotonous physico-chemical riverscape in winter to a complex mosaic in summer, this seasonal pattern being clearly driven by hydrological factors operating at the catchment scale rather than by autogenic processes within individual water bodies. Although RH exhibited a predictable annual pattern in response to the seasonal flow regime, we expect the channel network to undergo future modifications from stochastic factors associated with flood events and long-term changes reflecting movements of the glaciers.://000165379700001 + ISI Document Delivery No.: 375BM Times Cited: 26 Cited Reference Count: 54 Cited References: *APHA, 1989, STAND METH EX WAT WA *DEV, 1985, DTSCH EINH WASS AMOROS C, 1988, MUNSTERSCHE GEOGRAPH, V29, P125 BAYLEY PB, 1995, BIOSCIENCE, V45, P153 BENCALA KE, 1993, J N AMER BENTHOL SOC, V12, P44 BONETTO C, 1994, ARCH HYDROBIOL, V131, P277 BORNETTE G, 1991, J VEG SCI, V2, P497 BURT TP, 1996, FLOODPLAIN PROCESSES, P461 CHARLES DF, 1991, ACIDIC DEPOSITION AQ CHESSEL D, 1996, ADE SOFTWARE MULTIVA COOPER SD, 1997, J N AM BENTHOL SOC, V16, P174 DEVRIES JJ, 1995, J HYDROL, V170, P15 DOLE MJ, 1983, VIE MILIEU, V33, P219 DOLEDEC S, 1987, ACTA OECOL-OEC GEN, V8, P403 DOLEDEC S, 1991, ADV ECOLOGY, V1, P133 DOWNES MT, 1978, WATER RES, V12, P673 FORSBERG BR, 1988, LIMNOL OCEANOGR, V33, P41 FURCH K, 1993, ARCH HYDROBIOL, V128, P277 GREGORY KJ, 1987, GLACIOFLUVIAL SEDIME, P87 GURNELL AM, 1987, GLACIOFLUVIAL SEDIME GURNELL AM, 1999, CATENA, V38, P223 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HAMILTON SK, 1987, LIMNOL OCEANOGR, V32, P1277 HEILER G, 1995, REGUL RIVER, V11, P351 HOOVER SR, 1991, LANDSCAPE ECOL, V5, P125 JUGET J, 1976, B ECOL, V7, P479 JUNK WJ, 1989, CANADIAN SPECIAL PUB, V106, P110 JUNK WJ, 1997, CENTRAL AMAZOON FLOO KNOWLTON MF, 1997, WETLANDS, V17, P468 MAIZELS JK, 1983, SPECIAL PUBLICATION, V6, P251 MALARD F, 1999, ARCT ANTARCT ALP RES, V31, P135 MILNER AM, 1994, FRESHWATER BIOL, V32, P295 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PARCH K, 1996, FLOODPLAIN ECOLOGY M PIELOU EC, 1975, ECOLOGICAL DIVERSITY ROBINSON CT, 1998, FRESHWATER BIOL, V40, P215 ROMME WH, 1982, ECOL MONOGR, V52, P199 ROUX AL, 1982, CARTOGRAPHIE POLYTHE SPREAFICO M, 1992, HYDROLOGICAL ATLAS S STANLEY EH, 1997, BIOSCIENCE, V47, P427 THIOULOUSE J, 1989, COMPUT APPL BIOSCI, V5, P287 TOCKNER K, 1997, ARCH HYDROBIOL, V140, P433 TOCKNER K, 1999, FRESHWATER BIOL, V41, P521 TREMOLIERES M, 1993, HYDROBIOLOGIA, V254, P133 TURNER JV, 1990, WATER RESOUR RES, V26, P3005 TURNER MG, 1991, QUANTITATIVE METHODS, P3 UEHLINGER U, 1984, VERH INT VER THEOR A, V22, P163 UEHLINGER U, 1998, IAHS PUBL, V248, P419 VANDENBRINK FWB, 1993, BIOGEOCHEMISTRY, V19, P103 VOGLER P, 1965, FORTSCHR WASSERCHEM, V2, P109 WARD JV, 1995, REGUL RIVER, V11, P105 WARD JV, 1997, GAIA, V6, P52 WARD JV, 1999, HYDROL PROCESS, V13, P277 WIENS JA, 1995, MOSAIC LANDSCAPES EC, P1 0921-2973 Landsc. Ecol.ISI:000165379700001ETH, EAWAG, Dept Limnol, CH-8600 Dubendorf, Switzerland. Malard, F, Univ Lyon 1, CNRS, ESA 5023, Bat 403,43 Bd 11 Novembre 1918, F-69622 Villeurbanne, France.English |?WMalavasi, Marco Carboni, Marta Cutini, Maurizio Carranza, Maria L. Acosta, Alicia T. R.2014Landscape fragmentation, land-use legacy and propagule pressure promote plant invasion on coastal dunes: a patch-based approach 1541-1550Landscape Ecology299NovwCoastal dunes and sand areas are reported to be among the habitats most invaded by alien species in Europe. Landscape pattern could be a significant driver in invasion processes in parallel with land-use legacy. Fragmentation of natural habitats combined with the availability of propagules from the surrounding matrix may enhance the invisibility of ecological communities. Based on multitemporal land cover maps (1954-2008) and a floristic database, we analyzed how habitat fragmentation, propagule pressure and land-use legacy have affected alien plants' presence and richness on natural dune patches along the Lazio Coast (Central Italy). Floristic data were derived from an existing geodatabase of random vegetation plots (64 m(2)). A set of landscape patch-based metrics, considered to be adequate proxies of the main processes affecting alien invasion and richness, was calculated. First, we fit a generalized linear model (GLM) with binomial errors to assess which landscape metrics are influencing patch invasion. Second, we extracted invaded patches and, with GLMs, we investigated how landscape metrics affect average alien species richness. Alien invasion and alien richness seem to be affected by different processes: although alien invasion of each patch is strongly associated with its landuse legacy, the richness of aliens is more affected by landscape fragmentation and by the propagule pressure to which patch is exposed. By integrating spatial and temporal landscape metrics with floristic data, we were able to disentangle the relations of landscape fragmentation, propagule pressure and land-use legacy with the presence and richness of alien plants. The methodological approach here adopted could be easily extended to other alien species and ecosystems, offering scientifically sound support to prevent the high economic costs derived from both the control and the eradication of aliens.!://WOS:000343648700007Times Cited: 0 0921-2973WOS:00034364870000710.1007/s10980-014-0074-3<7Malkinson, D. Kadmon, R.2006jThe effects of inter-plant interactions and density-dependent disturbances on vegetation pattern formation259-270Landscape Ecology212disturbance; interactions; neighborhood effect; spatially explicit models; spatial pattern SPATIAL-PATTERN; HETEROGENEOUS LANDSCAPES; POSITIVE INTERACTIONS; POPULATION-DYNAMICS; COMMUNITIES; SPREAD; MODEL; COMPETITION; SUCCESSION; ECOLOGYArticleFeb Ecological interactions among individuals and disturbances are two important agents of pattern formation. In this study we investigated the interrelationships between interactions among individuals and large scale disturbances, and the resulting patterns. We categorized disturbances into three general classes, (1) those whose probability of occurrence increases with increased densities of vegetation, such as fire and disease, (2) those with a decreasing probability of occurrence with increasing vegetation densities, such as sand movement, and (3) disturbances that occur independently of vegetation densities, such as flooding. The ecological interactions among individuals were also divided to three classes: competition, facilitation and neutrality. We systematically investigated how these two types of processes interact to generate spatial patterns, using simulation models that were partially based on data collected from a shrub community in the Nizzana sand dune ecosystem. The results indicated that the different types of disturbances have fundamentally different effects on spatial patterns. Positive density-dependent disturbances, regardless of the type of interactions among individuals with which they were simulated, generated uniform spatial patterns. Patterns formed by interactions between decreasing or density independent disturbances with the different class interactions among individuals were more variable. These differences are attributed to the manner in which the difference disturbance types propagate in space.://000235866400009 ISI Document Delivery No.: 019WC Times Cited: 0 Cited Reference Count: 41 Cited References: *ENV SYST RES I IN, 1991, ARC INFO COMM REF US BAROT S, 1999, ECOLOGY, V80, P1987 BERKOWICZ SM, 1995, ARID ECOSYSTEMS, P1 CALDARELLI G, 2001, EUROPHYS LETT, V56, P510 CALLAWAY RM, 1997, ECOLOGY, V78, P1958 CALLAWAY RM, 2002, NATURE, V417, P844 COPPEDGE BR, 2001, LANDSCAPE ECOL, V16, P677 CRESSIE NAC, 1993, STAT SPATIAL DATA DEUTSCHMAN DH, 1997, SCI ONLINE, V237 ECCLES NS, 1999, PLANT ECOL, V142, P71 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GRIMMETT G, 1999, PERCOLATION HAASE P, 1996, J VEG SCI, V7, P527 HALLEY JM, 1994, OIKOS, V70, P435 HARGROVE WW, 2000, ECOL MODEL, V135, P243 JELTSCH F, 1994, ECOLOGICAL MODELLING, V75, P11 JELTSCH F, 2002, PROG BOT, V63, P326 KADMON R, 1995, ADV GEOECOLOGY, V28, P125 LANCASTER N, 1998, EARTH SURF PROC LAND, V23, P69 LEVIN SA, 1992, ECOLOGY, V73, P1943 LOEHLE C, 1996, LANDSCAPE ECOL, V11, P225 MALKINSON D, 2003, J VEG SCI, V14, P213 MALKINSON D, 2003, THESIS HEBREW U JERU MANDELBROT BB, 1975, FRACTAL GEOMETRY NAT MICHELI ER, 2002, EARTH SURF PROC LAND, V27, P687 MILLER C, 1999, CAN J FOREST RES, V29, P202 MOLOFSKY J, 1994, ECOLOGY, V75, P30 OHMANN JL, 1998, ECOL MONOGR, V68, P151 ONEILL RV, 1992, LANDSCAPE ECOL, V7, P19 ORBACH R, 1986, SCIENCE, V231, P814 PETERSON GD, 2002, ECOSYSTEMS, V5, P329 PLOTNICK RE, 2002, ECOL MODEL, V147, P171 RIPLEY BD, 1976, J APPL PROBAB, V13, P255 STOLL P, 2001, ECOLOGY, V82, P319 TANG SM, 1997, LANDSCAPE ECOL, V12, P349 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1989, OIKOS, V55, P121 TURNER MG, 1997, ECOL MONOGR, V67, P411 VANANDEL J, 1981, VEGETATIO, V45, P155 WIEGAND T, 1998, AM NAT, V152, P321 WIMBERLY MC, 2001, ECOLOGY, V82, P1443 0921-2973 Landsc. Ecol.ISI:000235866400009Univ Haifa, Dept Geog, Golan Res Inst, IL-31999 Haifa, Israel. Hebrew Univ Jerusalem, Dept Evolut Systemat & Ecol, Jerusalem, Israel. Malkinson, D, Univ Haifa, Dept Geog, Golan Res Inst, IL-31999 Haifa, Israel. dmalk@geo.haifa.ac.ilEnglish<7$!Mander, U. Kull, A. Kuusemets, V.2000MNutrient flows and land use change in a rural catchment: a modelling approach187-199Landscape Ecology153BOD5 catchment empirical model land use change land use scenarios nitrogen phosphorus runoff SO4 WATER-QUALITY WETLANDS NITROGEN RUNOFF MANAGEMENT SIMULATION PHOSPHORUS TRANSPORT POLLUTION DYNAMICSArticleAprNDue largely to unprecedented land-use changes in the Porijogi River catchment (southern Estonia) losses of nutrients and organic matter have decreased significantly. During the period 1987-1997 abandoned lands increased from 1.7 to 10.5% and arable lands decreased from 41.8 to 23.9%. At the same time, the runoff of total-N, total-P, SO4 and organic matter (after BOD5) decreased from 25.9 to 5.1, 0.32 to 0.13, 78 to 48, and 7.4 to 3.5 kg ha(-1) yr(-1), respectively. The most significant decreases occurred in agricultural subcatchments while the changes were insignificant in the forested upper course catchment. A simple empirical model which incorporates land-use pattern, fertilization intensity, soil parameters and water discharge accurately described the variations of total-N and total-P runoff in both the whole catchment and its agricultural subcatchments (R-2 varies from 0.95-0.99 for N to 0.49-0.93 for P). In small agricultural subcatchments the rate of fertilization is found the most important factor for nitrogen runoff, whereas in larger mosaic watersheds land use pattern plays the main role. Seven alternative scenarios compiled on the base of the empirical model allow to forecast potential nitrogen and phosphorus losses from the catchment. This information can be used in further landscape and regional planning of the whole region.://000085293300002  ISI Document Delivery No.: 283UB Times Cited: 9 Cited Reference Count: 48 Cited References: *APHA, 1981, STAND METH EX WAT WA *EPA, 1992, EPA841R92002 OFF WAT ANDERSEN HE, 1998, P 3 INT C DIFF POLL, P177 ANDERSEN JM, 1994, HYDROBIOLOGIA, V276, P499 ARHEIMER B, 1994, AMBIO, V23, P378 ARNOLD JG, 1993, APPL ADV INFORMATION BASTIAN O, 1994, ANAL OKOLOGISCHE BEW BEASLEY DB, 1980, T ASAE, V23, P938 BERGSTROM S, 1987, HYDROLOG SCI J, V32, P191 BICKNELL BR, 1984, J WATER SCI TECHNOL, V17, P114 BORAH DK, 1989, T ASAE, V32, P881 DILLAHA TA, 1989, WATER ENV SOC, V1, P419 FLEISCHER S, 1988, VERH INT VEREIN LIMN, V23, P181 FORMAN RTT, 1986, LANDSCAPE ECOLOGY GILLIAM JW, 1994, J ENVIRON QUAL, V23, P896 GRIMVALL A, IN PRESS ECOLOGICAL JANSSON M, 1994, AMBIO, V23, P320 JOELSSON A, 1998, P 3 INT C DIFF POLL, P149 JOHNSTON CA, 1990, BIOGEOCHEMISTRY, V10, P105 JORDAN TE, 1986, CATCHMENT RES PERSPE, P57 KELLY JM, 1988, J ENVIRON QUAL, V17, P463 KERSEBAUM KC, 1995, SCENARIO STUDIES RUR, P117 KRONVANG B, 1993, AMBIO, V22, P176 LARSEN SE, 1998, P 3 INT C DIFF POLL, P184 LOWRANCE R, 1985, J SOIL WATER CONSERV, V40, P87 LOWRANCE R, 1988, J ENVIRON QUAL, V17, P737 MANDER U, 1989, PETERMANNS GEOGRAPHI, V4, P233 MANDER U, 1994, GEOJOURNAL, V33, P45 MANDER U, 1995, LANDSCAPE URBAN PLAN, V31, P333 MANDER U, 1996, LANDBAUFORSCHUNG VOL, V165, P105 MANDER U, 1997, ECOL ENG, V8, P299 MANDER U, 1998, LANDSCAPE URBAN PLAN, V41, P229 MILLER RE, 1979, SIAM J COMPUT, V8, P42 MITSCH WJ, 1992, ECOL ENG, V1, P27 PALANG H, 1998, DISSERTATIONES GEOGR, V6 PETERJOHN WT, 1984, ECOLOGY, V65, P1466 RAAGMAA G, 1997, EESTI TULEVIKUSTSENA REKOLAINEN S, 1991, J HYDROL, V128, P237 RIPL W, 1995, ECOL MODEL, V78, P61 SANDNER E, 1993, ABHANDLUNGEN SACHSIS, V58, P1 SCHREIBER JD, 1987, J ENVIRON QUAL, V16, P6 SHLOSSER IJ, 1981, WATER RES B, V17, P233 VAREP E, 1964, ACTA COMMENTATIONES, V156, P3 WHIGHAM DF, 1988, ENVIRON MANAGE, V12, P663 WHITE FC, 1981, J SOIL WATER CONSERV, V36, P172 WISCHMEIER WH, 1978, USDA AGR HDB, V537 YARBRO LA, 1984, ENVIRON MANAGE, V8, P151 YOUNG RA, 1987, 35 USDA 0921-2973 Landsc. Ecol.ISI:000085293300002{Univ Tartu, Inst Geog, EE-51014 Tartu, Estonia. Mander, U, Univ Tartu, Inst Geog, 46 Vanemuise St, EE-51014 Tartu, Estonia.English۽7 (Mander, Ülo Li, Xiuzhen Wassen, MartinJ2013#Biogeochemical fluxes in landscapes577-581Landscape Ecology284Springer Netherlands 2013/04/01+http://dx.doi.org/10.1007/s10980-013-9875-z 0921-2973Landscape Ecol10.1007/s10980-013-9875-zEnglish G<7o +Mandryk, M. Reidsma, P. van Ittersum, M. K.2012aScenarios of long-term farm structural change for application in climate change impact assessment509-527Landscape Ecology274agriculture adaptation climate change farm structural change flevoland agricultural land-use future policy adaptation diversification vulnerability productivity consequences variability performanceApr Towards 2050, climate change is one of the possible drivers that will change the farming landscape, but market, policy and technological development may be at least equally important. In the last decade, many studies assessed impacts of climate change and specific adaptation strategies. However, adaptation to climate change must be considered in the context of other driving forces that will cause farms of the future to look differently from today's farms. In this paper we use a historical analysis of the influence of different drivers on farm structure, complemented with literature and stakeholder consultations, to assess future structural change of farms in a region under different plausible futures. As climate change is one of the drivers considered, this study thus puts climate change impact and adaptation into the context of other drivers. The province of Flevoland in the north of The Netherlands was used as case study, with arable farming as the main activity. To account for the heterogeneity of farms and to indicate possible directions of farm structural change, a farm typology was developed. Trends in past developments in farm types were analyzed with data from the Dutch agricultural census. The historical analysis allowed to detect the relative importance of driving forces that contributed to farm structural changes. Simultaneously, scenario assumptions about changes in these driving forces elaborated at global and European levels, were downscaled for Flevoland, to regional and farm type level in order to project impacts of drivers on farm structural change towards 2050. Input from stakeholders was also used to detail the downscaled scenarios and to derive historical and future relationships between drivers and farm structural change. These downscaled scenarios and future driver-farm structural change relationships were used to derive quantitative estimations of farm structural change at regional and farm type level in Flevoland. In addition, stakeholder input was used to also derive images of future farms in Flevoland. The estimated farm structural changes differed substantially between the two scenarios. Our estimations of farm structural change provide a proper context for assessing impacts of and adaptation to climate change in 2050 at crop and farm level.://000302346900004-919RS Times Cited:0 Cited References Count:57 0921-2973Landscape EcolISI:000302346900004Mandryk, M Wageningen Univ, Plant Prod Syst Grp, POB 430, NL-6700 AK Wageningen, Netherlands Wageningen Univ, Plant Prod Syst Grp, POB 430, NL-6700 AK Wageningen, Netherlands Wageningen Univ, Plant Prod Syst Grp, NL-6700 AK Wageningen, NetherlandsDOI 10.1007/s10980-012-9714-7English?~^Manicacci, D. I. Olivieri V. Perrot A. Atlan P.-H. Gouyon J.-M. Prosperi D. Couvet1992BLandscape ecology: population genetics at the metapopulation level147-159Landscape Ecology63Ereproductive systems, life history traits, non-equilibrium, dispersalhDistribution of genetic diversity in a landscape depends on both within and among population processes. Selective pressures within populations have traditionally been studied by population genetics, which usually assumes that populations are at equilibrium. However, when selection pressures within and among populations are different, landscape processes are required to define an equilibrium (landscape being defined as the habitat of a set of populations called a metapopulation, and populations will differ depending on their situation in the landscape, i.e. their age and the state of neighboring populations). We examine reproduction systems and life history traits, for which variation depends on landscape processes. Predictions of their states in a metapopulation are drawn from theoretical models, and confronted to observations collected in natural populations.j<7VManier, D. J. Hobbs, N. T. Theobald, D. M. Reich, R. M. Kalkhan, M. A. Campbell, M. R.2005aCanopy dynamics and human caused disturbance on a semi-arid landscape in the Rocky Mountains, USA1-17Landscape Ecology201land cover change; disturbance; fire suppression; forest expansion; management effects; pinon-juniper; sagebrush; spatial heterogeneity; temporal dynamics FIRE HISTORY; JUNIPER ENCROACHMENT; WESTERN JUNIPER; NATIONAL-PARK; INVASIONArticleJanInvasion of grasslands by woody plants has been identified as a key indicator of changes in ecosystem structure and function in and and semi-arid rangelands throughout the world. We investigated changes in the balance between woody and herbaceous components of a semi-arid landscape in western Colorado (USA) using historical aerial photography. Aerial photographs from 1937, 1965-67, and 1994 were sampled at matched locations within overlapping photographs. We modeled change in spatial pattern and heterogeneity across the entire landscape and found a small, net decrease in woody canopy cover; however means disguised normal distributions of change that demonstrated offsetting increases and decreases. We described a region of widespread canopy decline within pinon-juniper forests between 2300 and 2600 m (7500-8500 feet) and a region of predominant increase at lower elevations, between 1800 and 2250 in (5900-7400 feet). It remains unclear whether this shift was driven by climate or by human-caused or natural disturbance. Mean conifer cover decreased within coniferous forests, which counteracted a trend of increased conifer cover in mixed forests, savanna-like woodlands, and the shrub steppe. Disturbance had a significant interaction with cover change in several communities, including forests, savanna and shrublands. Anthropogenic disturbances counteracted successional trends toward canopy closure more than wildfires. but this did not entirely explain observed canopy decline. The natural dynamics in this region also caused diverse changes rather than a simple progression towards increased forest cover. Importantly, temporal change in vegetation varied spatially across the landscape illustrating the importance of landscape level, spatially explicit analyses in characterizing temporal dynamics.://000231223900001 ISI Document Delivery No.: 955KD Times Cited: 0 Cited Reference Count: 26 Cited References: *ESRI, 2000, ARCVIEW *SOIL CONS SERV, 1974, MAPS TAX REP AGTERBERG FP, 1984, TREND SURFACE ANAL ANDERSON RC, 1999, SAVANNAS BARRENS ROC BACHELET D, 2000, ECOL MODEL, V134, P229 BAILEY RG, 1995, DESCRIPTION ECOREGIO BAKER WL, IN PRESS FOREST ECOL BOOTS BN, 1980, ECON GEOGR, V56, P248 BROWN JR, 1999, ECOLOGY, V80, P2385 BURKHARDT JW, 1976, ECOLOGY, V57, P472 EFRON B, 1993, INTRO BOOTSTRAP FLOYD ML, 2000, ECOL APPL, V10, P1666 FORMAN RTT, 1997, LAND MOSAICS ECOLOGY HE HS, 1999, ECOLOGY, V80, P81 HEVESI JA, 1992, J APPL METEOROL, V31, P661 JOY S, 2002, THESIS COLORADO STAT MAST JN, 1997, FOREST ECOL MANAG, V93, P181 MAUS P, 1996, EM714025 USDA REM SE MILLER RE, 1995, GREAT BASIN NAT, V55, P37 MILLER RF, 1999, J RANGE MANAGE, V52, P550 PIELKE R, 2001, LONG TERM CLIMATE RE SCHLOEDER CA, 2001, SOIL SCI SOC AM J, V65, P470 SCHRUPP DL, 2000, COLORADO GAP ANAL PR TAYLOR AH, 1998, FOREST ECOL MANAG, V111, P285 TURNER MG, 2003, BIOSCIENCE, V53, P46 WALL TG, 2001, J RANGE MANAGE, V54, P691 0921-2973 Landsc. Ecol.ISI:000231223900001@Colorado State Univ, Nat Resource Ecol Lab, Ft Collins, CO 80523 USA. Colorado Div Wildlife, Habitat Sect, Ft Collins, CO 80526 USA. Colorado State Univ, Dept Forest Sci, Ft Collins, CO 80523 USA. Manier, DJ, Colorado State Univ, Nat Resource Ecol Lab, 200 W Lake St, Ft Collins, CO 80523 USA. dmanier@nrel.colostate.eduEnglish<7Manies, K. L. Mladenoff, D. J.2000oTesting methods to produce landscape-scale presettlement vegetation maps from the US public land survey records741-754Landscape Ecology158forest landscape hemlock-hardwoods interpolation kriging Sylvania Wilderness Area Michigan US Public Land Survey PRE-EUROPEAN SETTLEMENT OLD-GROWTH SPATIAL PATTERN FOREST FIREArticleDecThe U.S. Public Land Survey (PLS) notebooks are one of the best records of the pre-European settlement landscape and are widely used to recreate presettlement vegetation maps. The purpose of this study was to evaluate the relative ability of several interpolation techniques to map this vegetation, as sampled by the PLS surveyors, at the landscape level. Field data from Sylvania Wilderness Area, MI (U.S.A.), sampled at the same scale as the PLS data, were used for this test. Sylvania is comprised of a forested landscape similar to that present during presettlement times. Data were analyzed using two Arc/Info interpolation processes and indicator kriging. The resulting maps were compared to a 'correct' map of Sylvania, which was classified from aerial photographs. We found that while the interpolation methods used accurately estimated the relative forest composition of the landscape and the order of dominance of different vegetation types, they were unable to accurately estimate the actual area occupied by each vegetation type. Nor were any of the methods we tested able to recreate the landscape patterns found in the natural landscape. The most likely cause for these inabilities is the scale at which the field data (and hence the PLS data) were recorded. Therefore, these interpolation methods should not be used with the PLS data to recreate pre-European settlement vegetation at small scales (e.g., less than several townships or areas < 10(4) ha). Recommendations are given for ways to increase the accuracy of these vegetation maps.://000165379700005 ISI Document Delivery No.: 375BM Times Cited: 25 Cited Reference Count: 32 Cited References: *ESRI INC, 1994, ARC INFO 7 0 CELL BA *MATHS INC, 1996, S PLUS SPAT STATS US *SON, 1995, SON COMB PRO EL DIST *WI DEP NAT RES, 1992, PUBL WISC DEP NAT RE BATEK MJ, 1999, J BIOGEOGR, V26, P397 BOURDO EA, 1956, ECOLOGY, V37, P754 COMER PJ, 1996, 23 NAT AR 15 N AM PR DELCOURT HR, 1996, LANDSCAPE ECOL, V11, P363 FASSETT NC, 1944, WISCONSIN ACAD SCI A, V36, P33 FINLEY RW, 1951, THESIS U WISCONSIN M FOSTER DR, 1996, TRENDS ECOL EVOL, V11, P419 FRELICH LE, 1993, ECOLOGY, V74, P513 GALATOWITSCH SM, 1990, GREAT BASIN NAT, V50, P181 GRIMM EC, 1984, ECOL MONOGR, V54, P291 HUSHEN TW, 1966, MICH BOT, V5, P192 ISAAKS EH, 1989, INTRO APPL GEOSTATIS IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 JORDAN JK, 1973, UNPUB SOIL RESOURCES KAPP RO, 1978, MICH BOT, V17, P3 LILLESAND TM, 1979, REMOTE SENSING IMAGE MANIES KL, 1997, THESIS U WISCONSIN M MLADENOFF DJ, 1980, T WISC ACAD SCI, V68, P74 MLADENOFF DJ, 1993, DEFINING SUSTAINABLE, P145 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 PASTOR J, 1990, LANDSCAPE ECOL, V4, P55 RADELOFF VC, 1999, CAN J FOREST RES, V29, P1649 RUNKLE JR, 1982, ECOLOGY, V63, P1533 STEWART LO, 1935, PUBLIC LAND SURVEYS STROESSNER WJ, 1966, WISCONSIN ACAD SCI A, V55, P167 TINER RW, 1987, ATLANTIC WHITE CEDAR, P339 WHITE MA, 1994, LANDSCAPE ECOL, V9, P191 WHITNEY GG, 1994, COASTAL WILDERNESS F 0921-2973 Landsc. Ecol.ISI:000165379700005Univ Wisconsin, Dept Forest Ecol & Management, Madison, WI 53706 USA. Manies, KL, US Geol Survey, 345 Middlefield Rd, Menlo Park, CA 94025 USA.English<7>9Manning, A. D. Lindenmayer, D. B. Barry, S. C. Nix, H. A.2006|Multi-scale site and landscape effects on the vulnerable superb parrot of south-eastern Australia during the breeding season 1119-1133Landscape Ecology217Blakely's red gum; Continua - Umwelt; ecological restoration; private land; scattered paddock trees; superb parrot CONSERVATION; REPRODUCTION; RESTORATION; INSECTS; ECOLOGY; HABITAT; MODELS; TREESArticleOctThe threatened superb parrot of south-eastern Australia exemplifies many of the challenges associated with research on wide-raging organisms which live 'off-reserve'. Challenges include that most land is privately owned and that landscape use by such organisms does not always conform to traditional schematic and categorical landscape/fragmentation models. A multi-scale approach for embedding the detection of site-level and landscape context effects into landscape sampling design and subsequent statistical analysis is presented. The superb parrot was found scattered at varying densities throughout the agricultural landscapes of the South-West Slopes, much of which was privately owned. It responded to site-level variables and the surrounding landscape context. Overall, the superb parrot favoured lower elevation sites which were dominated by scattered, open woodlands, where Blakely's red gum was a significant component. Mean plant productivity within 2 km, levels of woody tree cover within 3 km and (with caveats) length of roads within 3 km had a major effect on site-level response, indicating conditions in the surrounding local landscape are important to the superb parrot. This multi-scale response requires a multi-scale conservation and restoration strategy. The importance of open tree cover and amounts of Blakely's red gum are a matter for concern, due to a general lack of tree regeneration and the particular susceptibility of Blakely's red gum to dieback. The scattered trees in the agricultural matrix were important to the superb parrot, suggesting that it views these landscapes as a continuum of usable habitat. Strategies for restoration of larger habitat remnants should also include regeneration of trees in scattered pattern in the wider landscape, and Blakely's red gum should be part of any strategy along with other key species such as yellow and white box. The landscape sampling approach successfully addressed the challenges of whole-landscape research. This highlights the value of 'off-reserve' studies across whole landscapes.://000241010900012 lISI Document Delivery No.: 091FA Times Cited: 0 Cited Reference Count: 45 Cited References: *AUSTR GREENH OFF, 2002, GREENH GAS EM LAND U *IUCN, 2002, 2002 IUCN RED LIST T *NSW NPWS, 2002, WHIT BOX YELL BOX BL BENNETT AF, 1991, NATURE CONSERVATION, V2, P99 BENNETT AF, 1997, PACIFIC CONSERVATION, V3, P244 BENSON JS, 1999, SETTING SCENE NATIVE BRAITHWAITE LW, 1993, AUSTR FORESTRY, V56, P4 BURNHAM KP, 1998, MODEL SELECTION INFE CHAMBERS JM, 1992, STAT MODELS S WADSWO CUSHMAN SA, 2002, LANDSCAPE ECOL, V17, P637 DAVEY C, 1997, CANBERRA BIRD NOTES, V22, P1 DORROUGH J, 2005, BIOL CONSERV, V123, P55 FERRIER S, 2002, BIODIVERS CONSERV, V11, P2275 FOX LR, 1983, AUST J ECOL, V8, P139 FRITH HJ, 1953, EMU, V53, P324 GIBBS G, 2002, COMPAR FUNCT GENOM, V3, P205 HAILA Y, 2002, ECOL APPL, V12, P321 HIGGINS PJ, 1999, HDB AUSTR NZ ANTARCT, V4 HILTY J, 2003, CONSERV BIOL, V17, P132 JACKSON LL, 2002, FARM NATURAL HABITAT, P39 JOURNET ARP, 1980, ECOL ENTOMOL, V5, P249 KADMON R, 2004, ECOL APPL, V14, P401 LANDSBERG J, 1990, AUST J ECOL, V15, P73 LINDENMAYER DB, 2000, BIODIVERS CONSERV, V9, P15 LUMSDEN LF, 2005, BIOL CONSERV, V122, P205 MANNING AD, 2004, BIOL CONSERV, V120, P363 MANNING AD, 2004, OIKOS, V104, P621 MCGARIGAL K, 1995, ECOL MONOGR, V65, P235 MCGARIGAL K, 2002, ECOL APPL, V12, P335 MCINTYRE S, 1999, CONSERV BIOL, V13, P1282 MEETENMEYER V, 1987, LANDSCAPE HETEROGENE, P15 NIX HA, 1976, P 16 INT ORN C, P272 NIX HA, 1991, RAINFOREST ANIMALS A, V1 NORTEN DA, 2000, CONSERV BIOL, V14, P1221 REID N, 2000, AUSTR BIOL CONSERVAT, P127 SCHNEIDER DC, 1994, QUANTITATIVE ECOLOGY SCHRADER NW, 1980, AUSTR BIRDS, V14, P45 VONUEXKULL J, 1926, THEORETICAL BIOL VONUEXKULL J, 1957, INSTINCTIVE BEHAV DE WALKER J, 1998, AUSTR SOIL LAND SURV, P58 WEBSTER R, 1988, REPORT SERIES, V12 WEBSTER R, 1992, MANAGEMENT CONSERVAT WIENS JA, 1981, STUDIES AVIAN BIOL, V6, P513 WIENS JA, 1993, OIKOS, V66, P369 YATES CJ, 1997, AUST J BOT, V45, P949 0921-2973 Landsc. Ecol.ISI:000241010900012Australian Natl Univ, Ctr Resource & Environm Studies, Canberra, ACT 0200, Australia. Bur Rural Sci, Kingston, ACT 2604, Australia. Manning, AD, Australian Natl Univ, Ctr Resource & Environm Studies, Canberra, ACT 0200, Australia. adrianm@cres.anu.edu.auEnglish/<7M*Manson, R. H. Ostfeld, R. S. Canham, C. D.1999SResponses of a small mammal community to heterogeneity along forest-old-field edges355-367Landscape Ecology144NBlarina brevicauda competition ecological model system ecotones edge effects forest edge macrohabitat microhabitat Microtus pennsylvanicus old-field Peromyscus leucopus predation seed predation seedling LANDSCAPE ECOLOGY HABITAT FRAGMENTATION PEROMYSCUS-LEUCOPUS MEADOW VOLES PATCH RODENTS PREDATION MICROTUS MICROHABITAT CONSERVATIONArticleAugDespite the importance of edges effects in ecological systems, the causes and consequences of animal responses to habitat edges are largely unknown. We used three years of live-trapping and measures of the plant community around trap stations to explore the responses of white-footed mice (Peromyscus leucopus), meadow voles (Microtus pennsylvanicus), and short-tailed shrews (Blarina brevicauda) to forest-field edges in upstate New York. We found that capture probabilities of voles were highest in grass- and forb-dominated micro-habitats and in old-field zones distant from the forest edge. In contrast, capture probabilities of white-footed mice were highest in shrub-dominated microhabitats and in zones near the forest edge. Short-tailed shrews did not show strong micro- or macrohabitat associations. The responses by voles, the competitive dominant in our system, to variation along forest-field edges were more consistent across years than were those of the competitively inferior, white-footed mouse. Mice were less likely to use the old-field interiors when vole density was high than when it was low, suggesting competitive displacement of mice by voles. Finally, we found good agreement between the spatial activity patterns of mice and voles in old-fields and their impacts on patterns of survival of tree seeds and seedlings in concurrent studies. These results suggest that a dynamic interaction exists between the plant and animal communities along forest edges.://000081305700004 r ISI Document Delivery No.: 214AP Times Cited: 25 Cited Reference Count: 59 Cited References: *SAS I INC, 1990, SAS STAT US GUID VER ADLER GH, 1985, OIKOS, V45, P380 ANDREASSEN HP, 1996, J APPL ECOL, V33, P63 BATZLI GO, 1985, AM SOC MAMMALOGISTS, V8, P779 BERG KW, 1995, THESIS U OSLO BOONSTRA R, 1982, CAN J ZOOL, V60, P438 BOWERS MA, 1991, OIKOS, V60, P180 BOWERS MA, 1993, OECOLOGIA, V94, P247 BOWERS MA, 1996, OECOLOGIA, V105, P107 BOWERS MA, 1997, J MAMMAL, V78, P999 BRYANT JP, 1991, ANNU REV ECOL SYST, V22, P431 BUCKNER CA, 1985, J MAMMAL, V66, P299 BUECHNER M, 1987, BIOL CONSERV, V41, P57 CAPPUCCINO N, 1997, OECOLOGIA, V110, P69 DIFFENDORFER JE, 1995, ECOLOGY, V76, P827 DONOVAN TM, 1997, ECOLOGY, V78, P2064 DUELLI P, 1990, BIOL CONSERV, V54, P193 DUESER RD, 1978, ECOLOGY, V59, P89 EADIE WR, 1952, J MAMMAL, V33, P185 FULK GW, 1972, J MAMMAL, V53, P461 GETZ LL, 1985, SPECIAL PUBLICATION, V8, P286 GLIZENSTEIN JS, 1990, B TORREY BOT CLUB, V117, P106 GRANT PR, 1971, CAN J ZOOL, V49, P1043 GRANT PR, 1971, J ANIM ECOL, V40, P323 HALLETT JG, 1983, OIKOS, V40, P175 HANSEN AJ, 1992, ECOLOGICAL STUDIES, V92 HARPER SJ, 1993, J MAMMAL, V74, P1045 HESKE EJ, 1995, J MAMMAL, V76, P562 IMS RA, 1989, NATURE, V342, P21 KAUFMAN DW, 1983, AM MIDL NAT, V110, P177 LEVIN SA, 1992, ECOLOGY, V73, P1943 LIDICKER WZ, 1995, LANDSCAPE APPROACHES LIDICKER WZ, 1996, METAPOPULATIONS WILD, P85 LIDICKER WZ, 1998, IN PRESS LANDSCAPE E LIMA SL, 1990, CAN J ZOOL, V68, P619 MANSON RH, 1998, ECOSCIENCE, V5, P183 MANSON RH, 1998, OIKOS, V82, P37 MCLOSKEY RT, 1975, J MAMMAL, V56, P119 MILLS LS, 1995, CONSERV BIOL, V9, P395 MILLS LS, 1996, NATL PARKS PROTECTED, P199 MORRIS DW, 1983, CAN J ZOOL, V61, P1517 MURCIA C, 1995, TRENDS ECOL EVOL, V10, P58 NUPP TE, 1996, CAN J ZOOL, V74, P467 OSTFELD RS, 1992, EFFECTS RESOURCE DIS OSTFELD RS, 1997, ECOLOGY, V78, P1531 OSTFELD RS, 1999, LANDSCAPE ECOLOGY SM PASTOR J, 1993, ECOLOGY, V74, P467 PEARSON PG, 1959, ECOLOGY, V40, P249 PICKETT STA, 1995, SCIENCE, V269, P331 RISSER PG, 1995, BIOSCIENCE, V45, P318 ROBINSON GR, 1992, SCIENCE, V257, P524 SEAMON JO, 1996, CAN J ZOOL, V74, P1130 STAMPS JA, 1987, AM NAT, V129, P533 TAMARIN RH, 1984, CAN J ZOOL, V62, P1796 TURNER MG, 1994, ECOL APPL, V4, P472 WIENS JA, 1985, OIKOS, V45, P421 WIENS JA, 1993, OIKOS, V66, P369 WOLFF JO, 1997, CONSERV BIOL, V11, P945 YAHNER RH, 1988, CONSERV BIOL, V2, P333 0921-2973 Landsc. Ecol.ISI:000081305700004rInst Ecosyst Studies, Millbrook, NY 12545 USA. Ostfeld, RS, Inst Ecosyst Studies, Box AB, Millbrook, NY 12545 USA.EnglishT|? aMansuy, Nicolas Boulanger, Yan Terrier, Aurelie Gauthier, Sylvie Robitaille, Andre Bergeron, Yves2014nSpatial attributes of fire regime in eastern Canada: influences of regional landscape physiography and climate 1157-1170Landscape Ecology297AugThe characterization of the fire regime in the boreal forest rarely considers spatial attributes other than fire size. This study investigates the spatial attributes of fires using the physiography of the landscape as a spatial constraint at a regional scale. Using the Canadian National Fire Database, the size, shape, orientation and eccentricity were assessed for 1,136 fires between 1970 and 2010 in Quebec's boreal forest and were summarized by ecodistrict. These spatial metrics were used to cluster 33 ecodistricts into homogeneous fire zones and then to determine which environmental variables (climate, topography, hydrography, and surficial deposits) influence the spatial attributes of fires. Analyses showed that 28 out of 33 ecodistricts belonging to a given fire zone were spatially contiguous, suggesting that factors driving the spatial attributes of fire are acting at a regional scale. Indeed, the orientation and size of fires vary significantly among the zones and are driven by the spatial orientation of the landscape and the seasonal regional climate. In some zones, prevailing winds during periods conducive to fire events parallel to the orientation of the landscape may favour the occurrence of very large fires (> 100,000 ha). Conversely, an orientation of the landscape opposite to the prevailing winds may act as a natural firebreak and limit the fire size and orientation. This study highlights the need to consider the synergistic relationship between the landscape spatial patterns and the climate regime over the spatial attributes of fire at supra-regional scale. Further scale-dependant studies are needed to improve our understanding of the spatial factors controlling the spatial attributes of fire.!://WOS:000339831300006Times Cited: 1 0921-2973WOS:00033983130000610.1007/s10980-014-0049-4 <7*Manton, M. G. Angelstam, P. Mikusinski, G.2005Modelling habitat suitability for deciduous forest focal species - a sensitivity analysis using different satellite land cover data827-839Landscape Ecology207(birds; conservation planning; forests; Geographic Information Systems; habitat networks; habitat modelling; land management; remote sensing; Sweden WOODPECKER DENDROCOPOS-MINOR; GROUSE BONASA-BONASIA; MANAGED BOREAL; CONSERVATION; UMBRELLA; ECOLOGY; FRAGMENTATION; LANDSCAPE; DIVERSITY; THRESHOLDArticleNovWe explored the usefulness of three satellite land cover data sets available to land managers in south-central Sweden for conservation planning using four deciduous forest focal resident bird species with different habitat requirements. Habitat suitability models using empirical species-specific habitat parameters and a Geographic Information System were applied to evaluate and compare the degree of consistency among three different land cover data sets. The study area encompassed 10,000 km(2) in a landscape mosaic of managed boreal forests and is within the distribution range of all four focal species. Although the three land cover data sets indicated similar total amounts of deciduous forest, the habitat suitability models showed that different land cover data yielded inconsistent results regarding the amount and distribution of suitable habitat within 5x5 km grid cells. Given this sensitivity to the choice of land cover data sets, the habitat suitability models showed positive relationships among the selected focal species for each land cover data set separately. As expected, decreasing amounts of suitable habitat were identified for species with higher specialisation. Thus, because habitat suitability models are an appropriate way to gain insight into the functionality and connectivity of habitat networks, land cover data must be carefully evaluated and if necessary combined with other landscape information for effective conservation planning.://000233036300005 ISI Document Delivery No.: 980RQ Times Cited: 1 Cited Reference Count: 85 Cited References: 1992, TERRAIN TYPE CLASSIF 1999, FARNEBOFJARDENS NATI 2002, EVALUATION EFFECTS F 2002, SVERIGEKLASSNINGEN, V1 *ERSI, 2000, ARCVIEW 3 2A *LIAIS UN LISB, 1998, 3 MIN C PROT FOR EUR *NORD COUNC MIN, 1983, REPR TYP NAT NORD CO *SOF, 1990, SVER FAGL, V2 ABERG J, 1995, OECOLOGIA, V103, P265 ABERG J, 2003, FOREST ECOL MANAG, V175, P437 ANGELSTAM P, 1994, ANN ZOOL FENN, V31, P157 ANGELSTAM P, 1997, ECOLOGICAL B, V46, P191 ANGELSTAM P, 2001, SCAND J FOR RES S, V3, P38 ANGELSTAM P, 2002, P 2002 ANN IALE UK U, P25 ANGELSTAM P, 2003, 200326 LANSST DAL MI ANGELSTAM P, 2003, AMBIO, V33, P594 ANGELSTAM P, 2004, ECOL B, V51, P149 ANGELSTAM P, 2004, ECOL B, V51, P29 ANGELSTAM P, 2004, ECOL B, V51, P427 ANGELSTAM P, 2004, ECOL B, V51, P487 ANGELSTAM PK, 2003, ANN ZOOL FENN, V40, P473 AULEN G, 1988, 14 SWED U AGR SCI DE BLECKERT S, 1991, THESIS U GOTHENBURG BURNETT C, 2003, ECOL MODEL, V168, P233 CARLSON A, 2000, FOREST ECOL MANAG, V131, P215 CRAMP S, 1977, BIRDS W PALAEARCTIC DYTHAM C, 1995, OIKOS, V65, P169 ESSEEN PA, 1997, ECOLOGICAL B, V46, P16 FAHRIG L, 2002, ECOL APPL, V12, P346 FLEISHMAN E, 2000, ECOL APPL, V10, P569 FRANCOLOPEZ H, 2001, REMOTE SENS ENVIRON, V77, P251 GASTON AJ, 1973, IBIS, V115, P330 GERGEL SE, 2002, LEARNING LANDSCAPE E GIBSON LA, 2004, BIOL CONSERV, V117, P143 GUISAN A, 2000, ECOL MODEL, V135, P147 GURNELL J, 2002, BIOL CONSERV, V105, P53 HANSSON L, 1997, ECOLOGICAL B, V46, P1 HESS GR, 2002, LANDSCAPE URBAN PLAN, V58, P25 HEYWOOD I, 2002, INTRO GEOGRAPHICAL I HOGSTAD O, 1994, FAUNA NORV C, V17, P75 HOLMGREN J, 2004, REMOTE SENS ENVIRON, V90, P415 HOLMGREN P, 1998, SCAND J FOREST RES, V13, P90 HOLMSTEDT S, 1996, FAGLAR VID FARNEBOFJ, P36 HOLMSTROM H, 2001, THESIS SWEDISH U AGR JANSSON G, 1999, LANDSCAPE ECOL, V14, P283 JANSSON G, 2003, SCAND J FOREST RES, V18, P225 JANSSON G, 2004, ECOL B, V51, P259 KORPILAHTI E, 2002, SILVA FENN, V36 LAMBECK RJ, 1997, CONSERV BIOL, V11, P849 LAMBECK RJ, 1999, 2 ENV AUSTR LARSSON S, 2001, SCAN J FOR RES S, V3, P1 LARSSON TB, 2001, ECOLOGICAL B, V50, P1 LAWLER JJ, 2004, LANDSCAPE ECOL, V19, P517 MACKEY BG, 1999, DIGITAL TERRAIN ANAL, P391 MARGULES CR, 2000, NATURE, V405, P243 MARTIKAINEN P, 1998, CONSERV BIOL, V12, P293 MCCOMB W, 1999, MAINTAINING BIODIVER, P335 MEYER M, 1990, J FOREST, P10 MIKUSINSKI G, 1998, CONSERV BIOL, V12, P200 MIKUSINSKI G, 1999, NATURE CULTURE LANDS, P220 MIKUSINSKI G, 2003, AMBIO, V33, P520 NAKAMURA T, 1969, MISC REP YAMASHINA I, V5, P1 OLSSON O, 1998, THESIS LUND U SWEDEN OPDAM P, 1995, IBIS, V137, P139 PETERKEN GF, 1996, NATURAL WOODLAND ECO, P522 RAIVIO S, 2001, SCAND J FOR RES S, V3, P99 RAMETSTEINER E, 2004, ECOL B, V51, P51 RANNEBY B, 2003, P 30 INT S REM SENS REESE H, 2003, AMBIO, V33, P542 ROBERGE JM, 2004, CONSERV BIOL, V18, P76 SCOTT JM, 2002, PREDICTING SPECIES O SHOROHOVA E, 2004, ECOL B, V51, P137 SIITONEN J, 2001, ECOLOGICAL B, V49, P11 SNOW DW, 1998, BIRDS W PALAEARCTIC STORE R, 2003, ECOL MODEL, V169, P1 SUCHANT R, 2004, ECOL B, V51, P455 SVENSSON S, 1999, SVENSK FAGELATLAS S, V31 SWENSON JE, 1995, P INT S GROUS, V6, P155 THIES M, 2004, REMOTE SENSING SPA 8, V36 VILLARD MA, 1994, OECOLOGIA, V98, P393 WIKTANDER U, 1992, ORNIS FENNICA, V69, P113 WIKTANDER U, 2001, BIOL CONSERV, V100, P387 WOODHOUSE S, 2000, COMPUTERS ENV URBAN, V24, P79 YOUNG JE, 2004, ECOL B, V51, P367 YOUNG TP, 2000, BIOL CONSERV, V92, P73 0921-2973 Landsc. Ecol.ISI:000233036300005Univ Orebro, Ctr Landscape Ecol, Dept Nat Sci, SE-70182 Orebro, Sweden. Charles Sturt Univ, Sch Environm & Informat Sci, Albury, NSW 2640, Australia. Swedish Univ Agr Sci, Fac Forest Sci, Sch Forest Engineers, SE-73921 Skinnskatteberg, Sweden. Swedish Univ Agr Sci, Dept Conservat Biol, SE-73091 Riddarhyttan, Sweden. Manton, MG, Univ Orebro, Ctr Landscape Ecol, Dept Nat Sci, SE-70182 Orebro, Sweden. micmanton@yahoo.com.auEnglish|? eManuel Alvarez-Martinez, Jose Stoorvogel, Jetse J. Suarez-Seoane, Susana de Luis Calabuig, Estanislao2010Uncertainty analysis as a tool for refining land dynamics modelling on changing landscapes: a case study in a Spanish Natural Park 1385-1404Landscape Ecology259NovIn this study we developed a methodology aimed at improving the assessment of inter-annual land cover dynamics from hard classified remotely sensed data in heterogeneous and resilient landscapes. The methodology is implemented for the Spanish Natural Park of Sierra de Ancares, where human interference during the last century has resulted in the destruction and fragmentation of the original land cover. We ran supervised classifications, with a maximum likelihood algorithm (Maxlike), on a temporal series of Landsat images (1991-2005), followed by an uncertainty assessment using fuzzy classifications and confusion indices (CIs). This allowed us to show how much (and where) of the resulting maps contained a substantial amount of error, distinguishing data that might be useful to measure land change from data that are not particularly useful when applying a post-classification comparison methodology. In this way, we can detect true changes not skewed by the effects of uncertainty. Even if patterns of change were always coherent amongst years, they were more realistic after reducing uncertainty, in spite of a substantial decrease in the number of available pixels (i.e. unmasked by the method). We then computed land cover dynamics by means of a model specifically designed to determine the frequency of disturbances (mainly fire events) and the vegetation recovery time during the study period. Model outputs showed correlated landscape patterns at a broad scale and provided useful results to explore land cover change from pattern to process.!://WOS:000281981000007Times Cited: 1 0921-2973WOS:00028198100000710.1007/s10980-010-9492-z|? Mapelli, F. J. Kittlein, M. J.2009rInfluence of patch and landscape characteristics on the distribution of the subterranean rodent Ctenomys porteousi723-733Landscape Ecology246JulThe understanding and prediction of the responses of animal populations to habitat fragmentation is a central issue in applied ecology. The identification of habitat variables associated to patch occupancy is particularly important when habitat quality is affected by human activities. Here, we analyze the influence of patch and landscape characteristics on patch occupancy by the subterranean herbivorous rodent Ctenomys porteousi. Patch occupancy was monitored in a network of 63 habitat patches identified by satellite imagery analysis which extends along almost the whole distributional range for C. porteousi. Suitable habitat for the occurrence of C. porteousi is highly fragmented and represents < 10% of the total area in its distributional range. The distribution of C. porteousi in the patch network is affected not only by characteristics of the habitat patches, but also by those of the surrounding landscape matrix. Significant differences between occupied and empty patches were found in several environmental variables. Overall, occupied patches were larger, less vegetated, more connected, and had larger neighbor patches than empty patches. A stepwise procedure on a generalized linear model selected four habitat variables that explain patch occupancy in C. porteousi; it included the effects of habitat quality in the matrix surrounding the patch, average vegetation cover in the patch, minimum vegetation cover in the matrix surrounding the patch, and the area of the nearest neighbor patch. These results indicate that patch occupancy in C. porteousi is strongly influenced by the availability and quality of habitat both in the patch and in the surrounding landscape matrix.://000268248100002)Mapelli, Fernando J. Kittlein, Marcelo J. 0921-2973ISI:00026824810000210.1007/s10980-009-9352-x0|?Marchesan, D. Carthew, S. M.2008oUse of space by the yellow-footed antechinus, Antechinus flavipes, in a fragmented landscape in South Australia741-752Landscape Ecology236An understanding of how individual species are able to persist and move within fragmented landscapes is critical for elucidating the effects of fragmentation and aiding in the management of species. Here, we studied movement behaviour of the dasyurid Antechinus flavipes in a heavily fragmented landscape using trapping and radiotracking. We assessed the ability of animals to move within and amongst small (< 6 ha) remnants and make use of the matrix, and investigated how females used the available space within remnants. Seventeen between-remnant movements were detected from 428 recaptures, ranging in length from 30 to 720 m and averaging 352 m. Most were by adult males during the breeding season, with 40% more than 500 m. Landscape types traversed would have included exotic pine plantations, open grazed areas and roads. Between-site movements of juveniles were only detected on three occasions. However, few young males were captured as adults, suggesting high dispersal rates and considerable matrix use. Conversely, despite high female recapture rates, again only three between-site movements were recorded. Radiotracking further indicated that females confined foraging to remnants, with occasional forays to isolated trees in paddocks. Female home range areas were similar for remnants and forest (0.04-0.66 ha). A. flavipes is clearly able to persist in very small patches of native vegetation in the landscape studied here. Its long-term persistence appears dependent on the ability of females to maintain a presence in the small remnants, and of unrelated males to move between remnants to breed with resident females. This study illustrates the importance of recognising the occurrence of metapopulations in fragmented landscapes for conservation management.!://WOS:000257210900009Times Cited: 0 0921-2973WOS:00025721090000910.1007/s10980-008-9234-7i|?GSMargriter, Sandra C. Bruland, Gregory L. Kudray, Gregory M. Lepczyk, Christopher A.2014iUsing indicators of land-use development intensity to assess the condition of coastal wetlands in Hawai'i517-528Landscape Ecology293MarAlthough wetland condition assessment procedures have been developed, validated, and calibrated in the continental United States, they have not yet been fully developed or field-tested for wetlands in Hawai'i. In order to address the need for comprehensive assessment methods for Hawaiian coastal wetlands, our research compared three indicators of landscape condition (landscape development intensity, road density, and forest cover) with wetland condition as measured by rapid assessment methods (RAM) and detailed field data collected on soil and water quality. We predicted that wetlands located in the least developed landscapes would have more nutrient rich soils, yet lower nutrient levels in the surface water, and would receive the highest rapid assessment scores. The hypotheses of our study were generally supported. However, while the correlations between landscape variables and delta N-15 isotopes and CRAM scores were relatively strong, the correlations between the landscape indicators and the other Level II and III field indicators were not very strong. These results suggest that further calibration and refinement of metrics is needed in order to more accurately assess the condition of Hawaiian coastal wetlands. A more detailed land use map, in addition to more comprehensive assessments of wetland water quality and biotic integrity would likely improve the relationships between indicators of landscape condition and wetland condition. Nonetheless, our research demonstrated that landscape analysis at larger scales (1,000 m buffers and watersheds) could provide managers with valuable information on how regional stressors may be affecting wetland water quality (measured as delta N-15 in plant tissue) as well as overall wetland condition (RAM scores).!://WOS:000331935500013Times Cited: 1 0921-2973WOS:00033193550001310.1007/s10980-013-9985-7?Mark, Schwartz2002The Use of Population Viability Analyses in Conser-vation Planning. In: Per Sjögren-Gulve and Tobjörn Ebenhardv use of novel dichotomy that is of particular interest to the landscape ecologist: whether the PVA is spatially189-190Landscape Ecology172 book reviewsZThis revised version was published online in July 2006 with corrections to the Cover Date.*http://dx.doi.org/10.1023/A:1019564321411 h10.1023/A:1019564321411 reference: Akçakaya H.R. 1998. RAMAS-GIS: Linking landscape data with population viability analysis. Ver 3.0. Applied Biomathematics. Setauket, NY, USA. Brook B.W. et al. 2000. Predictive accuracy of population viability analysis in conservation biology. Nature 404, 385-387. Hanksi I. 1994. A practical model of metapopulation dynamcis. J. Anim. Ecol. 63, 151-162. Hanski I. 1999. Metapopulation Ecology. Oxford University Press, Oxford, UK. Lacy R.C. 1993. VORTEX: A computer simulation model for population viability analysis. Wild. Res. 20, 45-65. Menges E.S. 2000. Applications of population viability analyses in plant conservation. In: P. Sjögren-Gulve and T. Ebenhard (eds.), The Use of Population Viability Analyses in Conservation Planning. Ecological Bulletins 48, pp. 73-84, Lund, Sweden. Shaffer M.L. 1981. Minimum viable population sizes for species conservation. Bioscience 31, 131-134. Tuljapurkar S. and Caswell H. (eds.) 1996. Structure Population Models in Marine, Terrestrial and Freshwater Systems. Chapman and Hall, New York, NY, USA. Department of Environmental Science and Policy, University of California, Davis, 1 Shields Avenue, Davis, CA, 95616, California, USA~?<Martin, B. A. Shao, G. Swihart, R. K. Parker, G. R. Tang, L.2008wImplications of shared edge length between land cover types for landscape quality: the case of Midwestern US, 1940-1998391-402Landscape Ecology234=The north-central region of Indiana in the Midwestern United States was covered by deciduous forest, but was largely cleared for agriculture during the 1800s. The landscape has experienced tremendous change due to forest restoration, urban expansion, and reservoir construction since the early 1900s. At the same time, ecological health and environmental quality have been dramatically degraded in the region. We used simple landscape indices, such as land proportion, TE, and Shared Edge Length (SEL) between any two classes, to examine changes in the spatial patterning of six land cover types, including agriculture, grassland, closed-canopy forest, open-canopy forest, urban, and water, using aerial photographs dating from 1940 to 1998. The landscape's domination by agriculture did not change (65% in 1940 and 57% in 1998), but there were net gains in area for closed-canopy forest (79%), urban (256%), and water (125%). Several landscape indices did not change much but SEL between closed-canopy forest and urban increased over seven fold, and SEL between water and urban increased over eight fold from 1940 to 1998. More forestlands and water bodies were exposed to human activities. The clumped pattern of forest, water, and urban in a landscape can be ecologically detrimental and should be considered in future land-use decisions."://WOS:000254250400003 Times Cited: 0WOS:000254250400003(10.1007/s10980-008-9197-8|ISSN 0921-2973V<7;/Martin, M. J. R. De Pablo, C. L. De Agar, P. M.2006LLandscape changes over time: comparison of land uses, boundaries and mosaics 1075-1088Landscape Ecology217conditional entropy; landscape diversity; relative frequency profiles; types of landscape elements SPATIAL ARRANGEMENT; NORTHERN SPAIN; SOIL-EROSION; PATTERNS; PATCHES; CONNECTIVITY; MANAGEMENT; DIVERSITY; COMPLEXITY; ECOLOGYArticleOctChanges in the landscape from 1946 to 1999 were studied according to changes in the land uses, boundaries and mosaics therein. The abundances of the different categories of these three landscape elements were calculated using land use maps. Their frequency profiles were compared based on their richness, evenness and diversity. Richness of land uses does not noticeably change. However, these slight changes are spatially perceptible in the landscape when changes in the boundaries and mosaics are considered. For the three landscape elements the least diverse landscapes are obtained in the initial year. The highest landscape diversity is reached, however, in the intermediate years when boundaries or mosaics are considered, whereas the highest value based on land uses occurs in the final period studied. Considering that land uses, boundaries and mosaics provide different information on landscape characteristics and qualities, conditional entropy analyses were conducted in order to ascertain which of the types of landscape elements is most related to landscape change. Boundaries are the element most related to landscape change. Mosaics, however, are the element that best describe each of the years because they integrate the information on land uses and boundaries. From an ecological and management point of view, the three elements should be considered as opposed to just land uses. They compliment each other in the information provided by each one in relation to changes occurring and the effects thereof on landscape structure and functioning.://000241010900009  ISI Document Delivery No.: 091FA Times Cited: 0 Cited Reference Count: 66 Cited References: *THINKSP INC, 1998, MF WORKS BAKER WL, 1989, LANDSCAPE ECOL, V2, P111 BERNALDEZ FG, 1981, ECOLOGIA PAISAJE CANTWELL MD, 1993, LANDSCAPE ECOL, V8, P239 DEAGAR PM, 1995, ENVIRON MANAGE, V19, P345 DEPABLO CL, 1987, ESPACE GEOGRAPHIQUE, V2, P115 DEPABLO CL, 1988, LANDSCAPE ECOLOGY, V1, P203 DESMET PJJ, 1999, GEOGRAPHIC INFORM RE FAHRIG L, 1985, ECOLOGY, V66, P1762 FAHRIG L, 1988, ECOLOGY, V69, P468 FORMAN RTT, 1981, BIOSCIENCE, V31, P733 FORMAN RTT, 1981, P INT C NETH SOC LAN, P35 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FORTIN MJ, 1994, ECOLOGY, V75, P956 GOSZ JR, 1991, ECOTONES ROLE LANDSC, P8 GOSZ JR, 1993, ECOL APPL, V3, P369 HABER W, 1990, PHYSL ECOLOGY JAPAN, V27, P131 HABERMAN SJ, 1973, BIOMETRICS, V29, P205 HAMAZAKI T, 1996, LANDSCAPE ECOL, V11, P299 HANSEN AJ, 1988, BIOL INT, V17, P9 HANSEN AJ, 1992, LANDSCAPE BOUNDARIES, P423 HANSSON L, 1995, MOSAIC LANDSCAPE ECO HILL MO, 1980, VEGETATIO, V42, P47 ISHE M, 1995, LANDSCAPE URBAN PLAN, V31, P21 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 JOHNSON GD, 2001, LANDSCAPE ECOL, V16, P597 JOHNSON LB, 1990, LANDSCAPE ECOL, V4, P31 KEARNS FR, 2005, LANDSCAPE ECOL, V20, P113 LI BL, 1995, ECOL MODEL, V82, P247 LI H, 1993, LANDSCAPE ECOL, V8, P63 LI HB, 1993, LANDSCAPE ECOL, V8, P155 LUDWIG B, 1995, CATENA, V25, P227 MARGALEF R, 1979, OIKOS, V33, P152 METZGER JP, 1996, LANDSCAPE ECOL, V11, P65 MOREIRA F, 2001, LANDSCAPE ECOL, V16, P557 MUNOZ MAD, 1984, ANAL GEOGRAFIA U COM, V4, P133 NAVEH Z, 1982, ADV ECOL RES, V12, P189 OLSSON EGA, 2000, LANDSCAPE ECOL, V15, P155 PALMER MA, 2000, LANDSCAPE ECOL, V15, P563 PAN DY, 1999, LANDSCAPE ECOL, V14, P35 PARKER DC, 2004, AGR ECOSYST ENVIRON, V101, P223 PHIPPS M, 1981, PERSPECTIVES LANDSCA, P57 RAMOS A, 1984, MEMORIA MAPA FORMACI RESCIA AJ, 1994, J VEG SCI, V5, P505 RESCIA AJ, 1997, J VEG SCI, V8, P343 ROLDAN MMJ, 2003, MULTIFUNCTIONAL LAND, V3, P55 ROMME WH, 1982, ECOL MONOGR, V52, P199 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SHANNON C, 1949, MATH THEORY COMMUNIC SIMPSON JW, 1994, LANDSCAPE ECOL, V9, P261 SWANSON FJ, 1990, BIOSCIENCE, V40, P502 TURNER MG, 1987, LANDSCAPE ECOL, V1, P29 TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 UBALDE JM, 1999, PIRINEOS, V153, P101 VANDAELE K, 1995, CATENA, V25, P213 VANDERMAAREL E, 1990, J VEG SCI, V1, P135 VANOOST K, 2000, LANDSCAPE ECOL, V15, P577 WIENS JA, 1985, OIKOS, V45, P421 WIENS JA, 1992, LANDSCAPE BOUNDARIES, P217 WILCOX BP, 2003, ECOL MONOGR, V73, P192 WITH KA, 1997, OIKOS, V78, P151 WOODMANSEE RG, 1990, CHANGING LANDSCAPES, P57 ZIPPERER WC, 1993, LANDSCAPE ECOL, V8, P177 ZONNEVELD IS, 1989, LANDSCAPE ECOLOGY, V1, P37 ZONNEVELD IS, 1989, LANDSCAPE ECOLOGY, V3, P67 0921-2973 Landsc. Ecol.ISI:000241010900009CIAM Environm Res Ctr Fernando Gonzalez Bernaldez, Madrid 28791, Spain. Univ Complutense, Fac Biol, Dept Ecol, E-28040 Madrid, Spain. Martin, MJR, CIAM Environm Res Ctr Fernando Gonzalez Bernaldez, C San Sebastian,71,Soto Real, Madrid 28791, Spain. mariajose.roldan@madrid.orgEnglish1<7&Martinez, J. J. I. Mokady, O. Wool, D.2005TPatch size and patch quality of gall-inducing aphids in a mosaic landscape in Israel 1013-1024Landscape Ecology208'dispersal; edge effect; F-statistics; genetic drift; herbivory; isolation by distance; Mediterranean vegetation; metapopulation; Nm; RAPD-PCR MACROSIPHONIELLA-TANACETARIA HOMOPTERA; GENETIC-MARKERS; DNA POLYMORPHISMS; POPULATIONS; DISPERSAL; INSECTS; TREES; FLOW; DIFFERENTIATION; SPECIALIZATIONArticleDecs For weak flying insects feeding on two different host plants during their life cycle, such as gall-inducing aphids, patch and matrix characteristics may play a critical role in patch occupancy and population size in occupied patches. The aims of the present study were to define the basic patch size of Baizongia pistaciae (L) (Aphididae, Fordini), an aphid inducing galls on Pistacia palaestina Boiss (Anacardiaceae) using a genetic approach, and to estimate the impact of landscape structure and patch quality on patch occupancy and gall density on occupied trees of this aphid and four other closely related species. Using 42 genetic markers detected by RAPD-PCR in 117 clones of the galling aphid Baizongia pistaciae, we calculated Wright's F statistics and estimated the number of winged migrants between demes. We found that host trees at least 150 m apart supported genetically differentiated demes of B. pistaciae, and formed distinct patches. Since the annual cycle of this aphid involves alternation between two different hosts, P. palaestina trees and Poaceae roots, patch - the smallest area that sustains a deme - is a relatively small area that must be composed of at least a single P. palaestina tree and nearby secondary hosts. To assess the impact of landscape structure and patch quality on patch occupancy and gall abundance in occupied patches, two field surveys of P. palaestina trees in natural Mediterranean maquis were performed. Among the five species of gall-inducing aphids found, B. pistaciae was the most abundant of those surveyed. Host trees were occupied more often in the ecotone, the transition zone between Mediterranean closed maquis and open bata, than in the maquis. Mature and old trees were more often occupied than young ones, and shrubs more often than tree-like plants. There was no difference in the proportion of occupied trees between isolated host trees or those growing in groups. Species richness showed similar trends. We also found no significant differences in gall abundance in occupied trees among tree quality categories, except that trees growing in the ecotone tended to carry more galls than those growing in the maquis. In conclusion, the best patch of gall-inducing aphids seems to be a small area, composed of an old shrub of P. palaestina standing in an open landscape with nearby secondary hosts, grass roots, available for colonization by winged migrants.://000233036400009 T ISI Document Delivery No.: 980RR Times Cited: 0 Cited Reference Count: 51 Cited References: BLACK WC, 1992, B ENTOMOL RES, V82, P151 BLACKMAN RL, 1994, APHIDS WORLDS TREES BODENHEIMER FS, 1957, APHIDOIDEA MIDDLE E BOURNOVILLE R, 2000, B ENTOMOL RES, V90, P33 DEBARRO PJ, 1995, MOL ECOL, V4, P375 DENNO RF, 1991, HABITAT STRUCTURE PH, P169 FAHRIG L, 1998, ECOSYSTEMS, V1, P197 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FRIESEN N, 2000, PLANT BIOLOGY, V2, P297 FULLER SJ, 1999, MOL ECOL, V8, P1867 HANSKI I, 2000, ECOLOGY, V81, P239 HARRY M, 1998, ANN SOC ENTOMOL FR, V34, P9 JOHNSON PCD, 2002, MOL ECOL, V11, P1525 JULIAO GR, 2004, BIODIVERS CONSERV, V13, P2055 KARBAN R, 1990, OIKOS, V59, P27 KOMATSU T, 1995, ECOL ENTOMOL, V20, P33 KOTZE DJ, 2001, BIODIVERS CONSERV, V10, P443 LAW BS, 1998, BIODIVERS CONSERV, V7, P323 LOXDALE HD, 1990, B ENTOMOL RES, V80, P331 LOXDALE HD, 1990, J ANIM ECOL, V59, P497 LOXDALE HD, 1993, BIOL REV, V68, P291 LOXDALE HD, 1998, B ENTOMOL RES, V88, P577 LOXDALE HD, 1999, PHILOS T ROY SOC B, V354, P1479 LUSHAI G, 1997, ENTOMOL EXP APPL, V85, P199 MASSONNET B, 2002, MOL ECOL, V11, P2511 MASSONNET B, 2004, HEREDITY, V93, P577 MILLER MP, 1997, TOOLS POPULATION GEN MILLER NJ, 2003, HEREDITY, V91, P217 MOPPER S, 1991, HABITAT STRUCTURE PH PEREZ T, 1998, MOL ECOL, V7, P1347 PETERSON MA, 1998, AM NAT, V152, P428 PRICE PW, 1997, INSECT ECOLOGY RICKETTS TH, 2001, AM NAT, V158, P87 SETZER RW, 1980, ANN ENTOMOLOGICAL SO, V73, P227 SOKAL RR, 1981, BIOMETRY STAMPS WT, 1998, AGROFOREST SYST, V39, P73 SUNNUCKS P, 1997, MOL ECOL, V6, P1059 TANG JM, 1996, MED VET ENTOMOL, V10, P228 VANDEWOESTIJNE S, 2004, POPUL ECOL, V46, P281 VANZANDT PA, 1998, AM NAT, V152, P595 WARD SA, 1998, J ANIM ECOL, V67, P763 WEIR BS, 1984, EVOLUTION, V38, P1358 WELSH J, 1995, PCR STRATEGIES, P249 WILLIAMS JGK, 1990, NUCLEIC ACIDS RES, V18, P6531 WOOL D, 1995, ISRAEL J ZOOL, V41, P591 WOOL D, 1998, EUR J ENTOMOL, V95, P41 WOOL D, 2004, ANNU REV ENTOMOL, V49, P175 WRIGHT S, 1951, ANN EUGEN, V15, P323 ZOHARA M, 1973, MANS IMPACT VEGETATI, P287 ZOHARY M, 1952, PALESTINE J BOT, V5, P187 ZWOLFER H, 1958, Z ANGEW ENTOMOL, V43, P1 0921-2973 Landsc. Ecol.ISI:000233036400009Tel Aviv Univ, George S Wise Fac Life Sci, Inst Nat Conservat Res, IL-69978 Tel Aviv, Israel. Tel Aviv Univ, George S Wise Fac Life Sci, Dept Zool, IL-69978 Tel Aviv, Israel. Martinez, JJI, Tel Hai Acad Coll, IL-12210 Tel Hai, Upper Galilee, Israel. martinez@telhai.ac.ilEnglish<7U,Martinko, E. A. Hagen, R. H. Griffith, J. A.2006ESuccessional change in the insect community of a fragmented landscape711-721Landscape Ecology2158abundance; habitat fragmentation; insect community; insecta; old field; resource concentration; secondary succession; species diversity; species richness; sweep-net OLD FIELD SUCCESSION; HABITAT FRAGMENTATION; SPECIES RICHNESS; SECONDARY SUCCESSION; POPULATION-DENSITY; PLANT; DIVERSITY; DYNAMICS; PATTERNS; AREAArticleJulHabitat fragmentation strongly affects insect species diversity and community composition, but few studies have examined landscape effects on long term development of insect communities. As mobile consumers, insects should be sensitive to both local plant community and landscape context. We tested this prediction using sweep-net transects to sample insect communities for 8 years at an experimentally fragmented old-field site in northeastern Kansas, USA. The site included habitat patches undergoing secondary succession, surrounded by a low turf matrix. During the first 5 years, plant richness and cover were measured in patches. Insect species richness, total density, and trophic diversity increased over time on all transects. Cover of woody plants and perennial forbs increased each year, adding structural complexity to successional patches and potentially contributing to increased insect diversity. Within years, insect richness was significantly greater on transects through large successional patches (5000 m(2)) than on transects through fragmented arrays of 6 medium-sized (total area 1728 m(2)) or 15 small (480 m(2)) patches. However, plant cover did not differ among patch types and was uncorrelated with insect richness within years. Insect richness was strongly correlated with insect density, but trophic and a diversities did not differ among patch types, indicating that patch insect communities were subsets of a common species pool. We argue that differences in insect richness resulted from landscape effects on the size of these subsets, not patch succession rates. Greater insect richness on large patches can be explained as a community-level consequence of population responses to resource concentration.://000240500100007 ISI Document Delivery No.: 083ZE Times Cited: 0 Cited Reference Count: 47 Cited References: BROWN VK, 1983, OECOLOGIA, V56, P220 COLLINGE SK, 1998, OIKOS, V82, P66 COLLINGE SK, 2000, ECOLOGY, V81, P2211 COLLINGE SK, 2002, LANDSCAPE ECOL, V17, P647 CONNOR EF, 2000, ECOLOGY, V81, P734 COOK WM, 2002, ECOL LETT, V5, P619 COOK WM, 2005, ECOLOGY, V86, P1267 CORBET SA, 1995, AGR ECOSYST ENVIRON, V53, P201 DEBINSKI DM, 2000, CONSERV BIOL, V14, P342 DIDHAM RK, 1996, TRENDS ECOL EVOL, V11, P255 DIFFENDORFER JE, 1995, ECOLOGY, V76, P827 FAHRIG L, 2003, ANNU REV ECOL EVOL S, V34, P487 GLASSER JW, 1982, AM NAT, V119, P375 GLEASON HA, 1927, ECOLOGY, V8, P299 GOLDEN DM, 1999, OECOLOGIA, V98, P8 GOTELLI NJ, 2001, ECOL LETT, V4, P379 HECK KL, 1975, ECOLOGY, V56, P1459 HENDRIX SD, 1988, J ANIM ECOL, V57, P1053 HOLT RD, 1992, THEOR POPUL BIOL, V41, P354 HOLT RD, 1995, ARABLE ECOSYSTEMS 21, P147 HOLT RD, 1995, ECOLOGY, V76, P1610 HUNTER MD, 2002, AGR FOREST ENTOMOL, V4, P159 JACQUEMYN H, 2001, J BIOGEOGR, V28, P801 KAREIVA P, 1983, VARIABLE PLANTS HERB, P259 KRAUSS J, 2003, J BIOGEOGR, V30, P889 MARTINKO EA, 1976, THESIS U KANSAS LAWR MCGARIGAL K, 2002, ECOL APPL, V12, P335 NOVOTNY V, 1994, OIKOS, V70, P223 OLIVER I, 1996, CONSERV BIOL, V10, P99 PRESTON FW, 1962, ECOLOGY, V43, P185 RICKETTS TH, 2001, AM NAT, V158, P87 ROBINSON GR, 1992, SCIENCE, V257, P524 ROOT RB, 1973, ECOL MONOGR, V43, P95 ROSENZWEIG ML, 1995, SPEICES DIVERSITY SP SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SIEMANN E, 1999, ECOGRAPHY, V22, P406 SOUTHWOOD TRE, 1977, J ANIM ECOL, V46, P337 SOUTHWOOD TRE, 1979, BIOL J LINN SOC, V12, P327 STAMPS JA, 1987, AM NAT, V129, P533 STONER KJL, 2004, ECOL APPL, V14, P1306 TAYLOR LR, 1976, J ANIM ECOL, V45, P255 TSCHARNTKE T, 2004, ANNU REV ENTOMOL, V49, P405 TURNER MG, 2005, ECOLOGY, V86, P1967 VITOUSEK PM, 1997, SCIENCE, V277, P494 WATSON DM, 2002, J BIOGEOGR, V29, P823 WINER BJ, 1991, STAT PRINCIPLES EXPT YAO J, 1999, ECOGRAPHY, V22, P715 0921-2973 Landsc. Ecol.ISI:000240500100007 Dept Ecol & Evolutionary Biol, Lawrence, KS 66047 USA. Kansas Biol Survey, Lawrence, KS 66047 USA. Univ Kansas, Dept Geog, Lawrence, KS 66045 USA. Hagen, RH, Dept Ecol & Evolutionary Biol, Takeru Higuchi Bldg,2101 Constant Ave, Lawrence, KS 66047 USA. rhagen@ku.eduEnglish? NMartins da Silva, Pedro Berg, Matty Serrano, Artur Dubs, Florence Sousa, José2012oEnvironmental factors at different spatial scales governing soil fauna community patterns in fragmented forests 1337-1349Landscape Ecology279Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9788-2 0921-297310.1007/s10980-012-9788-2|?<Mascarenhas, Andre Ramos, Tomas B. Haase, Dagmar Santos, Rui2014[Integration of ecosystem services in spatial planning: a survey on regional planners' views 1287-1300Landscape Ecology298OctlSpatial plans shape land-use changes, which in turn are main drivers of anthropogenic ecosystem alterations, therefore influencing the ecosystem services (ES) delivered by a given territory. However, integration of the ES concept in policies and plans is reported as poor in literature. The main goal of this research is to gain insight on the views and perceptions of Portuguese regional spatial planners regarding the ES concept and its integration in spatial plans. For that we designed and administered a questionnaire survey aimed at practitioners and decision-makers from Portuguese regional spatial planning authorities. The survey focused on issues such as the level of awareness and knowledge of the ES concept among planners, the perceived level of current ES integration in regional spatial plans and corresponding strategic environmental assessments, the main factors that either facilitate or obstruct that integration, or the level of importance given to ES integration in the planning process. Findings show that planners know the ES concept, they consider it as important to be integrated in spatial planning and, interestingly, that it is already rather integrated in existing plans. They believe that planning teams and authorities have skilled human resources for ES integration. However, they revealed a low knowledge on the main initiatives intended to push ecosystem services into the political agenda, like for example the Millennium Ecosystem Assessment. The questionnaire used can be easily transferred into other spatial planning contexts to draw, e.g. a broader European picture on ES integration in spatial planning.!://WOS:000342078600002Times Cited: 1 0921-2973WOS:00034207860000210.1007/s10980-014-0012-4|?[dMassicotte, Philippe Frenette, Jean-Jacques Proulx, Raphael Pinel-Alloul, Bernadette Bertolo, Andrea2014}Riverscape heterogeneity explains spatial variation in zooplankton functional evenness and biomass in a large river ecosystem67-79Landscape Ecology291JanEcologists have long focused on local-scale phenomena (i.e. local environment variables) and assumed that spatial processes were unimportant factors influencing both the community structure and the functional diversity of aquatic communities. In this paper we used zooplankton assemblages in a typical large river (St. Lawrence River) as a biological model to examine the roles of (1) local environmental conditions (physicochemical characteristics of the water column), (2) broad-scale connectivity (a proxy for dispersion potential), and (3) habitat heterogeneity (a proxy for niche diversity) on the structure and the diversity of lotic communities. Together, these three sets of descriptors explained respectively 52, 49 and 59 % of the variation in zooplankton total biomass, functional diversity and community structure. After partialling out the roles of local environmental conditions and broad-scale connectivity, we demonstrated that habitat heterogeneity alone is a key driver of zooplankton total biomass and functional evenness at the riverscape level. In homogeneous and temporally stable habitats, zooplankton communities had higher biomass and functional evenness but lower species richness. Conversely, zooplankton had lower biomass and higher species richness in heterogeneous and unstable habitats, suggesting that zooplankton species can coexist because disturbances prevent competitive exclusion from occurring. This is the first study to reveal how local environmental conditions, spatial connectivity and habitat heterogeneity operate jointly to determine the functional diversity and structure of aquatic communities in a natural ecosystem.!://WOS:000330827600006Times Cited: 0 0921-2973WOS:00033082760000610.1007/s10980-013-9946-1O<7Mast, J. N. Wolf, J. J.2004{Ecotonal changes and altered tree spatial patterns in lower mixed-conifer forests, Grand Canyon National Park, Arizona, USA167-180Landscape Ecology192dendrochronology; ecotone; mixed-conifer; patch structure; ponderosa pine; spatial analysis; white fir COLORADO FRONT RANGE; PONDEROSA PINE FORESTS; AGE STRUCTURE; STAND DEVELOPMENT; FIRE HISTORY; NORTH RIM; REGENERATION; DYNAMICS; CLIMATE; DISTURBANCEArticle%This research analyzes patch development and determines tree spatial patterns along the lower mixed-conifer ecotone on the North Rim of Grand Canyon National Park in Arizona (U.S.A.). Patterns of patch development were interpreted from spatial analyses, based on tree age and size, and past records of disturbance and climate. Five plots in the ecotone between mixed conifer forests and monospecific stands of ponderosa pine (Pinus ponderosa) were studied for patterns of patch development. The methods used include: (1) size-structure analyses, to compare species patch development; (2) dendrochronological dating of tree establishment; (3) tree ring master chronology, to determine periods of suppressed growth, compared to a Palmer Drought Severity Index; and (4) spatial analyses by species composition, size and age, with univariate and bivariate analyses of spatial association and spatial autocorrelation. We found an increased density of shade-tolerant and fire-intolerant species namely clusters of pole-sized white fir, and fewer large ponderosa pine.://000220452500005 1ISI Document Delivery No.: 806SB Times Cited: 9 Cited Reference Count: 96 Cited References: ALLEN CD, 1998, P NATL ACAD SCI USA, V95, P14839 ALLEN CD, 2002, W WILDERNESS FIRE NA, CH5 ALTSCHUL JH, 1989, MAN MODELS MANAGEMEN BENNETT PS, 1973, UNPUB FIRE ECOLOGY P BESAG JE, 1977, APPLIED STATISTICS, V26, P327 BONNICKSEN TM, 1985, ENVIRON MANAGE, V9, P479 BURKHARDT JW, 1976, ECOLOGY, V57, P472 BURNS RM, 1990, AGR HDB USDA, V654 CLIFF AD, 1973, SPATIAL AUTOCORRELAT CLIFF AD, 1981, SPATIAL PROCESSES MO COOK ER, 1984, PROGRAM ARSTAN USERS COOPER CF, 1960, ECOL MONOGR, V30, P129 COOPER CF, 1961, ECOLOGY, V42, P493 COTTAM WP, 1940, J FOREST, V38, P613 COVINGTON WW, 1992, RM213 US FOR SERV RO, P81 COVINGTON WW, 1994, ASSESSING FOREST ECO, P13 COVINGTON WW, 1994, J FOREST, V92, P39 COVINGTON WW, 1997, J FOREST, V95, P23 CREER LH, 1958, PUB UTAH U, V32 DEUTSCHMAN DH, 1993, PATCH DYNAMICS, P184 DIETERICH JH, 1983, FOREST ECOL MANAG, V6, P13 DIETERICH JH, 1984, FOREST SCI, V30, P238 DIGGLE PJ, 1983, STAT ANAL SPATIAL PO DUNCAN RP, 1990, SPATIAL ANAL PROGRAM DUNCAN RP, 1991, CAN J FOREST RES, V21, P1703 FOSTER JH, 1917, J FOREST, V15, P442 FRANKLIN J, 1985, VEGETATIO, V64, P29 FRITTS HC, 1989, ADV ECOL RES, V19, P111 GETIS A, 1987, ECOLOGY, V68, P473 GOOD BJ, 1982, B TORREY BOT CLUB, V109, P529 GRISSINOMAYER HD, 1993, INT TREE RING DATA B HAASE P, 1995, J VEG SCI, V6, P575 HANSEN AJ, 1988, BIOL INT SPECIAL ISS, V17, P37 HARRINGTON MG, 1990, P S EFF FIR MAN SW N, P122 HOLMES RL, 1983, TREE RING B, V43, P69 HUGHES JD, 1978, HOUSE STONE LIGHT HU JOHNSEN TN, 1962, ECOL MONOGR, V32, P187 KILGORE BM, 1975, FOREST SCI, V21, P83 LAESSLE AM, 1965, ECOLOGY, V46, P65 LAVEN RD, 1992, P FIR HIST WORKSH U, P46 LEGENDRE P, 1989, VEGETATIO, V80, P107 LEGENDRE P, 1993, ECOLOGY, V74, P1659 LEOPOLD A, 1943, GRASS BRUSH TIMBER F, V22, P2 LOTWICK HW, 1982, J ROY STAT SOC B MET, V44, P406 MARR J, 1961, U COLORADO STUDIES B, V8 MARRIOT FHC, 1979, APPLIED STATISTICS, V28, P75 MAST JN, 1997, FOREST ECOL MANAG, V93, P187 MAST JN, 1998, J BIOGEOGR, V25, P743 MAST JN, 1999, CAN J FOREST RES, V29, P575 MAST JN, 1999, ECOL APPL, V9, P228 MAURER SG, 1990, VISITORS GUIDE KAIBA MEAD P, 1930, THESIS U CHICAGO CHI MERKLE J, 1954, ECOLOGY, V35, P316 MERRIAM CH, 1890, N AM FAUNA, V3, P1 MOIR WH, 1997, SONGBIRD ECOLOGY SW, P3 MOORE MM, 1999, ECOLOGICAL APPL, V9, P4 MORAN PAP, 1950, BIOMETRIKA, V37, P17 NAKASHIZUKA T, 1982, JAP J ECOL, V32, P57 NOBLE IR, 1993, ECOL APPL, V3, P396 ODLAND J, 1988, SPATIAL AUTOCORRELAT OLIVER CD, 1990, FOREST STAND DYNAMIC OVERPECK JT, 1990, NATURE, V343, P51 PARKER AJ, 1986, FOREST SCI, V32, P339 PARSONS DJ, 1986, ENVIRON MANAGE, V10, P21 PARSONS DJ, 1996, SCI ECOSYSTEM MANAGE, P25 PEET RK, 1981, VEGETATIO, V45, P3 PEET RK, 1987, BIOSCIENCE, V37, P586 READ J, 1988, J ECOL, V76, P558 REJMANEK M, 1996, ECOLOGY, V77, P1655 RICHARDSON DM, 1991, AM NAT, V137, P639 RICHARDSON DM, 1994, J BIOGEOGR, V21, P511 RIPLEY BD, 1977, J ROY STAT SOC B MET, V39, P172 RIPLEY BD, 1981, SPATIAL STAT SAVAGAE M, 1989, THESIS U COLORADO BO SAVAGE M, 1990, ECOLOGY, V71, P2374 SAVAGE M, 1991, ANN ASSOC AM GEOGR, V81, P271 SAVAGE M, 1996, ECOSCIENCE, V3, P310 SIROIS L, 1991, ECOLOGY, V72, P619 STEIN SJ, 1988, FOREST ECOL MANAG, V25, P139 STEWART OC, 1956, MANS ROLE CHANGING F, P115 STOKES MA, 1968, INTRO TREE RING DATI SWETNAM TW, 1994, P 2 LA MES FIR S NAT SZWAGRZYK J, 1992, FOREST ECOL MANAG, V51, P301 UPTON GJG, 1985, SPATIAL DATA ANAL EX, V1 VALE TR, 1978, AM MIDL NAT, V100, P277 VALE TR, 1982, RESOURCE PUBL G WASH VEBLEN TT, 1981, J BIOGEOGR, V8, P211 VEBLEN TT, 1991, COLORADO FRONT RANGE VEBLEN TT, 1991, J BIOGEOGR, V18, P707 VEIRS SD, 1988, UNPUB LINE POINT INT VISSER H, 1995, FOREST SCI, V41, P297 WHIPPLE SA, 1980, B TORREY BOTANICAL C, V107, P71 WHITE AS, 1985, ECOLOGY, V66, P589 WHITE MA, 1993, VEGETATIO, V109, P161 WOLF JJ, 1998, PHYS GEOGR, V19, P1 WRIGHT RD, 1966, BOT GAZ, V127, P184 0921-2973 Landsc. Ecol.ISI:000220452500005Carthage Coll, Dept Geog, Kenosha, WI 53140 USA. Univ Wisconsin Parkside, Dept Geog, Kenosha, WI 53141 USA. Mast, JN, Carthage Coll, Dept Geog, Kenosha, WI 53140 USA. JMast@carthage.eduEnglish A|?UrMastrangelo, Matias E. Weyland, Federico Villarino, Sebastian H. Barral, Maria P. Nahuelhual, Laura Laterra, Pedro2014jConcepts and methods for landscape multifunctionality and a unifying framework based on ecosystem services345-358Landscape Ecology292FebThe potential of landscapes to supply multiple benefits to society beyond commodities production has received increasing research and policy attention. Linking the concept of multifunctionality with the ecosystem services (ES) approach offers a promising avenue for producing scientific evidence to inform landscape planning, e. g., about the relative utility of land-sharing and land-sparing. However, the value for decision-making of ES-based multifunctionality assessments has been constrained by a significant conceptual and methodological dispersion. To contribute towards a cohesive framework for landscape multifunctionality, we analyse case studies of joint ES supply regarding ten criteria designed to ultimately answer four aspects: (i) the multifunctionality of what (e. g., landscapes), (ii) the type of multifunctionality (e. g., based on ES synergies), (iii) the procedure of multifunctionality assessments, and (iv) the purpose of multifunctionality. We constructed a typology of methodological approaches based on scores for criteria describing the evaluation method and the level of stakeholder participation in assessments of joint ES supply. Surveyed studies and underlying types of methodological approaches (spatial, socio-spatial, functional, spatio-functional) differed in most criteria. We illustrate the influence of methodological divergence on planning recommendations by comparing two studies employing contrasting approaches (spatial and functional) to assess the joint supply of wildlife habitat and agricultural production in the Argentine Chaco. We distinguish between a pattern-based and process-based multifunctionality, where the latter can only be detected through approaches considering the ecological processes (e. g., ES complementarities) supporting the supply of multiple ES (functional and spatio-functional). Finally, we propose an integrated approach for assessing a socially-relevant process-based multifunctionality.!://WOS:000331935100012Times Cited: 2 0921-2973WOS:00033193510001210.1007/s10980-013-9959-9^|7Matisziw, T. C. Murray, A. T.2009'Connectivity change in habitat networks89-100Landscape Ecology241spatial structure habitat change network analysis fragmentation nature reserves landscape ecology conservation ecology landscape connectivity reserve design climate-change spatial ecology protected areas extinction risk conservation biodiversity corridors patchesJan4Habitat management is essential for safeguarding important flora and fauna. Further, habitat connectivity is a crucial component for maintaining biodiversity given that it is known to have implications for species persistence. However, damage to habitat due to natural and human induced hazards can alter spatial relationships between habitats, potentially impacting biodiversity. Therefore, the susceptibility of spatial relationships to patch loss and associated connectivity degradation is obviously an important factor in maintaining existing or planned habitat networks. Identifying patches vital to connectivity is critical both for effectively prioritizing protection (e.g., enhancing habitat connectivity) and establishing disaster mitigation measures (e.g., stemming the spread of habitat loss). This paper presents a methodology for characterizing connectivity associated with habitat networks. Methods for evaluating habitat network connectivity change are formalized. Examples are presented to facilitate analysis of connectivity in the management of biodiversity.://000262506000008-395EI Times Cited:0 Cited References Count:53 0921-2973ISI:000262506000008Matisziw, TC Univ Missouri, Dept Geog, 8 Stewart Hall, Columbia, MO 65211 USA Univ Missouri, Dept Geog, Columbia, MO 65211 USA Univ Missouri, Dept Civil & Environm Engn, Columbia, MO 65211 USA Arizona State Univ, Sch Geog Sci, Tempe, AZ 85287 USADoi 10.1007/S10980-008-9282-ZEnglish|?oMatsinos, Y. G. Mazaris, A. D. Papadimitriou, K. D. Mniestris, A. Hatzigiannidis, G. Maioglou, D. Pantis, J. D.2008LSpatio-temporal variability in human and natural sounds in a rural landscape945-959Landscape Ecology2381The study of landscape structure and functions, including the underlying ecological and anthropogenic processes has traditionally relied on visual aspects without considering information of non-visionary cues, e.g. auditory. In this work we applied a complementary approach for the study of landscapes using qualitative information for the sonic environment. In particular we studied the qualitative linkages between landscape structure and functions and daily sound patterns. The main objectives were the investigation of the spatial and temporal variability in sound perception, and the identification of the dominant sound categories (anthropogenic, biological, geophysical originated sounds) in relation to landscape characteristics. Our results showed significant spatio-temporal variability in the intensity of different sound categories, which reflects distinct soundscape patterns. Temporal sound variability reflected the daily cycle of anthropogenic activities and biological processes, whereas the spatial sound viability was mainly shaped by landscape attributes. The combination of the visual landscape information and its emergent acoustic profile enhances our perception and understanding of nature and this integrated approach may have many practical applications in landscape management, monitoring and planning.!://WOS:000259481900006Times Cited: 0 0921-2973WOS:00025948190000610.1007/s10980-008-9250-7ڽ7<Matson, Emily Bart, David2013pInteractions among fire legacies, grazing and topography predict shrub encroachment in post-agricultural páramo 1829-1840Landscape Ecology289Springer NetherlandsQWoody encroachment Shrub invasion Grasslands Alpine Land-use legacy Ecuador Andes 2013/11/01+http://dx.doi.org/10.1007/s10980-013-9926-5 0921-2973Landscape Ecol10.1007/s10980-013-9926-5English <7DMatthews, R. B. Gilbert, N. G. Roach, A. Polhill, J. G. Gotts, N. M.20075Agent-based land-use models: a review of applications 1447-1459Landscape Ecology2210agent-based modelling land-use complexity policy analysis interactions decision-making DECISION-SUPPORT-SYSTEMS MULTIAGENT SYSTEM SIMULATION-MODELS ECOLOGICAL THEORY MANAGEMENT LANDSCAPE INTEGRATION COMPLEXITY VIETNAM GAMEArticleDecOAgent-based modelling is an approach that has been receiving attention by the land use modelling community in recent years, mainly because it offers a way of incorporating the influence of human decision-making on land use in a mechanistic, formal, and spatially explicit way, taking into account social interaction, adaptation, and decision-making at different levels. Specific advantages of agent-based models include their ability to model individual decision-making entities and their interactions, to incorporate social processes and non-monetary influences on decision-making, and to dynamically link social and environmental processes. A number of such models are now beginning to appear-it is timely, therefore, to review the uses to which agent-based land use models have been put so far, and to discuss some of the relevant lessons learnt, also drawing on those from other areas of simulation modelling, in relation to future applications. In this paper, we review applications of agent-based land use models under the headings of (a) policy analysis and planning, (b) participatory modelling, (c) explaining spatial patterns of land use or settlement, (d) testing social science concepts and (e) explaining land use functions. The greatest use of such models so far has been by the research community as tools for organising knowledge from empirical studies, and for exploring theoretical aspects of particular systems. However, there is a need to demonstrate that such models are able to solve problems in the real world better than traditional modelling approaches. It is concluded that in terms of decision support, agent-based land-use models are probably more useful as research tools to develop an underlying knowledge base which can then be developed together with end-users into simple rules-of-thumb, rather than as operational decision support tools.://000250632100005ISI Document Delivery No.: 227BL Times Cited: 0 Cited Reference Count: 73 Matthews, Robin B. Gilbert, Nigel G. Roach, Alan Polhill, J. Gary Gotts, Nick M. 0921-2973 Landsc. Ecol.ISI:000250632100005Macaulay Land Use Res Inst, Integrated Land Use Syst Grp, Aberdeen AB15 8QH, Scotland. Univ Surrey, Dept Sociol, Guildford GU2 7XH, Surrey, England. Matthews, RB, Macaulay Land Use Res Inst, Integrated Land Use Syst Grp, Aberdeen AB15 8QH, Scotland. r.matthews@macaulay.ac.ukEnglish|?M`Matthews, Stephen N. Iverson, Louis R. Peters, Matthew P. Prasad, Anantha M. Subburayalu, Sakthi2014mAssessing and comparing risk to climate changes among forested locations: implications for ecosystem services213-228Landscape Ecology292Feb\Forests provide key ecosystem services (ES) and the extent to which the ES are realized varies spatially, with forest composition and cultural context, and in breadth, depending on the dominant tree species inhabiting an area. We address the question of how climate change may impact ES within the temperate and diverse forests of the eastern United States. We quantify the vulnerability to changes in forest habitat by 2100, based on the overall pressures of community change from an aggregation of current and potential future habitats for 134 tree species at each of 149 US Department of Defense installations. To do so, we derive an index, Forest-Related Index of Climate Vulnerability, composed of several indicators of vulnerability for each site. Further, a risk matrix (likelihood 9 consequences) provides a visual cue to compare vulnerabilities among species (example from Pennsylvania) or among sites [example for Acer saccharum (sugar maple) in Vermont vs. Kentucky]. Potential changes in specific ES can then be qualitatively examined. For example in Pennsylvania, the loss of the provisioning services (wood products) of Prunus serotina (black cherry) and Fraxinus americana (white ash) habitat projected for the future will not likely be compensated for by concomitant increases in Juniperus virginiana (redcedar) and Pinus echinata (shortleaf pine) habitat. Taken together, this approach provides a conceptual framework that allows for consideration of how potential changes in tree species habitats, as impacted by climate change, can be combined to explore relative changes in important ES that forests provide.!://WOS:000331935100004Times Cited: 1 0921-2973WOS:00033193510000410.1007/s10980-013-9965-y|? &Matthews, Stephen N. Rodewald, Paul G.2010Movement behaviour of a forest songbird in an urbanized landscape: the relative importance of patch-level effects and body condition during migratory stopover955-965Landscape Ecology256JulkWith expansion of urban areas worldwide, migrating songbirds increasingly encounter fragmented landscapes where habitat patches are embedded in an urban matrix, yet how migrating birds respond to urbanization is poorly understood. Our research evaluated the relative importance of patch-level effects and body condition to movement behaviour of songbirds during migratory stopover within an urban landscape. We experimentally relocated 91 migrant Swainson's thrushes (Catharus ustulatus) fitted with 0.66 g radio-transmitters to seven forest patches that differed in area (0.7-38.4 ha) and degree of urbanization within central Ohio, USA, May 2004-2007. Fine-scale movement rate of thrushes (n = 55) did not differ among urban forest sites, but birds in low energetic condition moved at higher rates, indicating an energetically mediated influence on movement behaviour. In larger sites, Swainson's thrushes (n = 59) had greater coarse-level movement during the first 3 days and utilized areas farther from forest edge, indicating stronger influence by patch-level factors. Thrushes exhibited strong site tenacity, with only five individuals (7%) leaving release patches prior to migratory departure. Movement outside the release patch only occurred at the smallest forest patches (0.7 and 4.5 ha), suggesting that these sites were too small to meet needs of some individuals. Swainson's thrushes exhibited edge avoidance and apparent area sensitivity within urban forest patches during stopover, implying that conservation of larger patches within urban and other fragmented landscapes may benefit this species and other migrant forest birds.!://WOS:000278526000011Times Cited: 3 0921-2973WOS:00027852600001110.1007/s10980-010-9475-0 G<7 Matthysen, E.2002`Boundary effects on dispersal between habitat patches by forest birds (Parus major, P-caeruleus)509-515Landscape Ecology176Belgium Blue Tit direction emigration forest fragmentation Great Tit GREAT TIT POPULATION-DYNAMICS DIFFUSION-MODELS BLUE TIT CONNECTIVITY RECRUITMENT MIGRATION MOVEMENT GEOMETRYArticleOctThe behaviour of individuals in response to patch boundaries is a crucial element in many dispersal models. Diffusion- based models of dispersal predict that both the likelihood and direction of dispersal from a habitat patch are influenced by the starting position of a disperser in relation to the patch boundary. An alternative view is that the decision to disperse between patches is uncoupled from movements within the patch of departure. The latter situation is most likely in the case of relatively mobile animals living in small patches with strongly reflecting boundaries. I tested the relationship between proximity to a boundary and natal dispersal in Great and Blue Tits born in relatively small (7- 11 ha) forest patches with high population density in northern Belgium. Birds that were born closer to the forest edge were not more likely to be recruited outside than inside the natal patch. However, Great Tits showed a significant tendency to emigrate in the direction of the nearest patch border. No such effect was found in Blue Tits. A possible explanation is that in Great Tits the direction of dispersal, but not the decision to emigrate, is influenced by a process of familiarization with the area around the natal territory, including areas across the patch border.://000179774900002 ISI Document Delivery No.: 624RN Times Cited: 9 Cited Reference Count: 31 Cited References: BEISSINGER SR, 1998, J WILDLIFE MANAGE, V62, P821 BJORNSTAD ON, 1999, TRENDS ECOL EVOL, V14, P427 BOONE RB, 1996, LANDSCAPE ECOL, V11, P51 CANTRELL RS, 1999, THEOR POPUL BIOL, V55, P189 DESROCHERS A, 1997, CONSERV BIOL, V11, P1204 DHONDT AA, 1980, ECOLOGY, V61, P1291 DRENT PJ, 1983, THESIS U GRONINGEN G DUNNING JB, 1995, ECOL APPL, V5, P3 GRUBB TC, 1999, AUK, V116, P618 HADDAD NM, 1999, AM NAT, V153, P215 HANSKI I, 1999, METAPOPULATION ECOLO HINSLEY SA, 2000, LANDSCAPE ECOL, V15, P765 JOHNSON AR, 1992, LANDSCAPE ECOL, V7, P63 KAREIVA P, 1995, NATURE, V373, P299 KAREIVA PM, 1983, OECOLOGIA, V56, P234 KINDVALL O, 2000, ECOL MODEL, V129, P101 KUUSSAARI M, 1996, J ANIM ECOL, V65, P791 LAMBRECHTS MM, 1999, OIKOS, V86, P147 LITTELL RC, 1996, SAS SYSTEM MIXED MOD MACHTANS CS, 1996, CONSERV BIOL, V10, P1 MATTHYSEN E, 2001, ECOGRAPHY, V24, P33 NOUR N, 1998, OECOLOGIA, V114, P522 RUCKELSHAUS M, 1997, CONSERV BIOL, V11, P1298 SAUNDERS DA, 1991, NATURE CONSERVATION, V2, P421 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 STAMPS JA, 1987, AM NAT, V129, P533 TISCHENDORF L, 1997, OIKOS, V79, P603 TISCHENDORF L, 2000, LANDSCAPE ECOL, V15, P633 TRAVIS JMJ, 2000, ECOL LETT, V3, P163 VANNOORDWIJK AJ, 1984, J ANIM ECOL, V53, P533 VERHULST S, 1997, ECOLOGY, V78, P864 0921-2973 Landsc. Ecol.ISI:000179774900002Univ Instelling Antwerp, Dept Biol, B-2610 Wilrijk, Belgium. Matthysen, E, Univ Instelling Antwerp, Dept Biol, B-2610 Wilrijk, Belgium.English<76Maurice, K. R. Welch, J. M. Brown, C. P. Latham, R. E.2004SPocono mesic till barrens in retreat: topography, fire and forest contagion effects603-620Landscape Ecology196mesic till barrens; forest contagion effect; USA; Pennsylvania-northeastern; fire effects; geomorphology effects; GIS landscape analysis TREE INVASION; OLD FIELDS; COLONIZATION; DISPERSAL; SPREADArticleAugThe Pocono mesic till barrens (PMTB) are a unique assemblage of fire-maintained shrub communities that support numerous rare species. Historically these barrens covered a large area in the vicinity of Long Pond, Pennsylvania, USA. However, due largely to regional fire suppression instituted in the early 1960s, over 70% of the area covered by barrens succeeded to fire-intolerant forest that does not support the rare species. We investigated the influence of forest proximity on barrens succession across three geomorphic types during periods of high fire frequency and fire suppression, testing the hypothesis that forest processes such as seed rain, shading, and detrital enrichment of soils enhances barrens succession through a contagion effect. Evidence of a forest contagion effect should be shown by increased rates of barrens succession with increasing proximity to the nearest forest edge. In order to detect a forest contagion effect, barrens persistence and barrens succession were modeled in proximity zones of 0-50 m, 50-100 m, 100-200 m, and greater than 200 m from the nearest forest edge. We used existing GIS data layers for fire, geomorphology, and vegetation distribution in 1938, 1963, and 1992. The layers were modified and overlain using ArcView software to determine persistence and succession rates for each unique combination of layers in each proximity zone from 1938 to 1963 (pre-fire suppression) and 1963 to 1992 (postfire suppression). ANCOVA results indicate that proximity to the nearest forest edge significantly affected barrens persistence rates in both time periods, but succession rates were significantly affected in 1938 to 1963 only. Twenty-eight percent of the 1938 barrens succeeded to forest by 1963; 56% of the 1963 barrens became forest by 1992. Results support previous findings that barrens persistence is enhanced by increased fire frequency, and that barrens persist longer where they overlie flat glacial till than on other geomorphology types.://000224100600003 wISI Document Delivery No.: 857FC Times Cited: 0 Cited Reference Count: 35 Cited References: *ENV SYST RES I, 1998, US ARCV GIS *STATS INC, 1994, STAT 4 1 WIND ABRAMS MD, 1998, BIOSCIENCE, V48, P355 ANDERSON RC, 1999, SAVANNAS BARRENS ROC ARNHEIM C, 1995, ENVIRON PLANN A, V27, P105 BERG TM, 1977, GEOLOGY MINERAL RESO BREDEN TF, 1984, THESIS RUTGERS STATE CROWL GH, 1980, 71 PENNS DEP CONS NA DAVIS AF, 1991, NATURAL AREAS INVENT EBERHARDT RW, 2000, J TORREY BOT SOC, V127, P115 FORMAN RTT, 1986, LANDSCAPE ECOLOGY GILL DS, 1991, ECOL MONOGR, V61, P183 GLESS JT, 1997, SO POCONOS FOCUS ARE GURIES RP, 1984, FOREST SCI, V30, P434 HARDT RA, 1989, ECOLOGY, V70, P1252 HILL JD, 1995, ECOL APPL, V5, P459 HUGHES JW, 1988, B TORREY BOT CLUB, V115, P89 LATHAM RE, 1996, B TORREY BOT CLUB, V123, P330 LATHAM RE, 1997, EC SOC AM NAT CONS J LATHAM RE, 2003, FOREST ECOL MANAG, V185, P21 LOEHLE C, 1996, LANDSCAPE ECOL, V11, P225 MCDONNELL MJ, 1990, B ECOL SOC AM, V71, P246 MOODY ME, 1988, J APPL ECOL, V25, P1009 MYSTER RW, 1992, B TORREY BOT CLUB, V119, P141 MYSTER RW, 1993, BOT REV, V59, P251 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SEVON WD, 1975, 194CD PENNS DEP CONS SEVON WD, 1975, 195AB PENNS DEP CONS SOKAL RR, 1995, BIOMETRY PRINCIPLES THOMPSON JE, 1995, THESIS U PENNSYLVANI UNDERWOOD AJ, 1997, EXPT ECOLOGY THEIR L URBAN DL, 1987, BIOSCIENCE, V37, P119 VANVUUREN MMI, 1992, BIOGEOCHEMISTRY, V16, P151 WIBIRALSKE AW, 2004, IN PRESS CANADIAN J ZAR JH, 1984, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000224100600003xW Chester Univ, Dept Geog, W Chester, PA 19383 USA. Swarthmore Coll, Dept Biol, Swarthmore, PA 19081 USA. Normandeau Associates, Spring City, PA 19475 USA. New Mexico State Univ, Dept Geog, Las Cruces, NM 88003 USA. Continental Conservat, Rose Valley, PA 19086 USA. Welch, JM, W Chester Univ, Dept Geog, W Chester, PA 19383 USA. jwelch@wcupa.edu rel@continentalconservation.usEnglishfڽ7 eMayor, ÁngelesG Kéfi, Sonia Bautista, Susana Rodríguez, Francisco Cartení, Fabrizio Rietkerk, Max2013Feedbacks between vegetation pattern and resource loss dramatically decrease ecosystem resilience and restoration potential in a simple dryland model931-942Landscape Ecology285Springer NetherlandsResource-leakiness feedbacks Vegetation spatial pattern Hydrological connectivity Desertification Resilience Restoration potential Dryland ecosystems 2013/05/01+http://dx.doi.org/10.1007/s10980-013-9870-4 0921-2973Landscape Ecol10.1007/s10980-013-9870-4English|? SMazaris, A. D. Kallimanis, A. S. Chatzigianidis, G. Papadimitriou, K. Pantis, J. D.2009fSpatiotemporal analysis of an acoustic environment: interactions between landscape features and sounds817-831Landscape Ecology246JulSo far landscape analysis meant analysis of the spatial pattern of land cover or land use. However, biological organisms do not perceive the landscape only as land cover or land use, but they use all their senses, in order to become familiar with and react to their surroundings. We analyzed the acoustic environment as an additional layer of spatial information in landscape analysis, shortening the monopoly of visual patterns as landscape descriptors. We recorded sounds from a rural protected area into seven categories based on their origin, and examined their spatiotemporal variability and their correlation with landscape characteristics. The sounds were distinguished as Foreground or Background sounds. Foreground sounds correspond to sharp sounds originating near the observer and usually are understood as signals of urgent information, triggering reactions; while background sounds carry information over longer distances and may be used as landmarks to help individuals find their bearing even in the absence of visual signs. We found that the acoustic environment varies both temporally and spatially reflecting anthropogenic, geophysical and biological activities. The spatial pattern of the background sounds correlates, to an extent, with the visually perceived landscape features, but it does not correlate with the spatial pattern of the foreground sounds, which do not correlate strongly with the landscape pattern. This spatial pattern mismatch between acoustic environment and landscape, along with the highly dynamic nature of the acoustic environment compared to the relatively static nature of the land cover and land use spatial pattern highlight a limitation of the classical landscape analysis, and expands our understanding of the cognitive landscape.://000268248100009lMazaris, Antonios D. Kallimanis, Athanasios S. Chatzigianidis, George Papadimitriou, Kimonas Pantis, John D. 0921-2973ISI:00026824810000910.1007/s10980-009-9360-x(<7Mazerolle, M. J.2005ADrainage ditches facilitate frog movements in a hostile landscape579-590Landscape Ecology205amphibians; corridor; habitat loss; movement; peat mining; peatland; survival rate; trench STREAM AMPHIBIANS; HABITAT CORRIDORS; SPECIES RICHNESS; MARKED ANIMALS; BUFO-BUFO; CONNECTIVITY; POPULATIONS; DISPERSAL; SURVIVAL; CONSERVATIONArticleJuleDitches are common in landscapes influenced by agricultural, forestry, and peat mining activities, and their value as corridors remains unassessed. Pond-breeding amphibians can encounter hostile environments when moving between breeding, summering, or hibernation sites, and are likely to benefit from the presence of ditches in the landscape. Within a system consisting of ditch networks in bogs mined for peat in eastern New Brunswick, Canada, I quantified the breeding, survival, and movements of green frogs (Rana clamitans melanota) in drainage ditches and also surveyed peat fields. Frogs rarely ventured on peat fields and most individuals frequented drainage ditches containing water, particularly in late summer. Though frogs did not breed in ditches, their survival rate in ditches was high (88%). Ditches did not hinder frog movements, as frogs moved independently of the current. Results indicate that drainage ditches containing water enable some movements between habitats isolated by peat mining, in contrast to peat surfaces, and suggest they function as amphibian movement corridors. Thus, such drainage ditches may mitigate the effects of peat extraction on amphibian populations. At the very least, these structures provide an alternative to hostile peat surfaces. This study highlights that small-scale corridors are potentially valuable in population dynamics.://000232205600007 ISI Document Delivery No.: 969AK Times Cited: 0 Cited Reference Count: 76 Cited References: ANDERSON DR, 2000, J WILDLIFE MANAGE, V64, P912 ANDREASSEN HP, 1996, J APPL ECOL, V33, P63 ARMITAGE PD, 2003, AQUAT CONSERV, V13, P165 BECHET A, 2003, J APPL ECOL, V40, P553 BEIER P, 1998, CONSERV BIOL, V12, P1241 BELISLE M, 2002, LANDSCAPE ECOL, V17, P219 BONIN J, 1997, AMPHIBIANS DECLINE C, P141 BONNET X, 1999, BIOL CONSERV, V89, P39 BOUDJEMADI K, 1999, J ANIM ECOL, V68, P1207 BURNHAM KP, 2002, MODEL SELECTION MULT CHANMCLEOD ACA, 2003, J WILDLIFE MANAGE, V67, P663 CHOQUET R, 2003, U CARE USERS GUIDE V COFFMAN CJ, 2001, OIKOS, V93, P3 CORN PS, 1989, FOREST ECOL MANAG, V29, P39 COULSON JC, 1990, J APPL ECOL, V27, P549 DALE JM, 1985, CAN J ZOOL, V63, P97 DELAGE V, 2000, ECOSCIENCE, V7, P149 DEMERS MN, 1993, LANDSCAPE ECOL, V8, P93 DONNELLY MA, 1994, MEASURING MONITORING, P277 FAHRIG L, 1995, BIOL CONSERV, V73, P177 FREDA J, 1992, J HERPETOL, V26, P429 GIBBS JP, 1998, J WILDLIFE MANAGE, V62, P584 GILLESPIE GR, 2002, BIOL CONSERV, V106, P141 GORHAM E, 1984, CAN J FISH AQUAT SCI, V41, P1256 HADDAD NM, 1999, ECOL APPL, V9, P612 HADDAD NM, 1999, ECOL APPL, V9, P623 HENEIN K, 1990, LANDSCAPE ECOL, V4, P157 HITCHINGS SP, 1998, J EVOLUTION BIOL, V11, P269 HOMAN RN, 2003, ANIM CONSERV 1, V6, P11 HOSMER DW, 1989, APPL LOGISTIC REGRES HUDGENS BR, 2003, AM NAT, V161, P808 JOENSUU S, 2002, SCAND J FOREST RES, V17, P238 JOHNSTON B, 2002, CAN J ZOOL, V80, P2170 JOLY P, 2001, CONSERV BIOL, V15, P239 KNUTSON MG, 1999, CONSERV BIOL, V13, P1437 KOLOZSVARY MB, 1999, CAN J ZOOL, V77, P1288 LEBRETON JD, 1992, ECOL MONOGR, V62, P67 LECOMTE J, 2004, J ANIM ECOL, V73, P179 MADER HJ, 1984, BIOL CONSERV, V29, P81 MASTERS JEG, 2002, HYDROBIOLOGIA, V483, P185 MAURITZEN M, 1999, J APPL ECOL, V36, P409 MAZEROLLE MJ, 2001, J HERPETOL, V35, P13 MAZEROLLE MJ, 2003, BIOL CONSERV, V113, P215 MAZEROLLE MJ, 2003, WETLANDS, V23, P708 MCCULLAGH P, 1989, GEN LINEAR MODELS MERRIAM G, 1991, NATURE CONSERVATION, V2, P133 OSEEN KL, 2002, OECOLOGIA, V133, P616 PAINTER D, 1999, J APPL ECOL, V36, P33 PILLIOD DS, 2002, CAN J ZOOL, V80, P1849 POLLOCK KH, 1990, WILDLIFE MONOGR, P1 POPE SE, 2000, ECOLOGY, V81, P2498 POULIN M, 1999, APPL VEG SCI, V2, P169 POULIN M, 2001, ECOLOGIE TOURBIERES, P503 POWER ME, 1990, ECOLOGY, V71, P897 REH W, 1990, BIOL CONSERV, V54, P239 REIJNEN R, 1995, J APPL ECOL, V32, P187 RICHTER SC, 2001, J HERPETOL, V35, P316 ROLAND J, 2000, ECOLOGY, V81, P1642 ROSENBERG DK, 1998, CAN J ZOOL, V76, P117 ROTHERMEL BB, 2002, CONSERV BIOL, V16, P1324 RUEFENACHT B, 1995, BIOL CONSERV, V71, P269 SAKAI HF, 1997, J WILDLIFE MANAGE, V61, P343 SCHMIDT BR, 1999, AMPHIBIA-REPTILIA, V20, P97 SEMLITSCH RD, 2000, J WILDLIFE MANAGE, V64, P615 SEMLITSCH RD, 2003, CONSERV BIOL, V17, P1219 SIMBERLOFF D, 1992, CONSERV BIOL, V6, P493 SINSCH U, 1990, ETHOL ECOL EVOL, V2, P65 TIEBOUT HM, 1997, CONSERV BIOL, V11, P620 TISCHENDORF L, 1997, OIKOS, V79, P603 VITT DH, 1994, MEMOIRS ENTOMOLOGICA, V169, P7 WELSH HH, 1998, ECOL APPL, V8, P1118 WHEELER BD, 1995, RESTORATION DAMAGED WHITE GC, 1999, BIRD STUDY S, V46, P120 WILLIAMS P, 2004, BIOL CONSERV, V115, P329 WOODFORD JE, 2003, BIOL CONSERV, V110, P277 WRIGHT AH, 1949, HDB FROGS TOADS US C 0921-2973 Landsc. Ecol.ISI:000232205600007Univ Laval, Ctr Rech Biol Forestiere, Quebec City, PQ G1K 7P4, Canada. Mazerolle, MJ, USGS, Patuxent Wildlife Res Ctr, 12100 Beach Forest Rd, Laurel, MD 20708 USA. mmazerolle@usgs.govEnglishz<7McAlpine, C. A. Eyre, T. J.2002Testing landscape metrics as indicators of habitat loss and fragmentation in continuous eucalypt forests (Queensland, Australia)711-728Landscape Ecology178{forest birds gliders landscape structure Montreal Process sub-tropical Australia CONSERVATION EXTINCTION FRAMEWORK CRITERIAArticleDecLandscape metrics are widely applied in landscape ecology to quantify landscape structure. However, many are poorly tested and require rigorous validation if they are to serve as reliable indicators of habitat loss and fragmentation, such as Montreal Process Indicator 1.1e. We apply a landscape ecology theory, supported by exploratory and confirmatory statistical techniques, to empirically test landscape metrics for reporting Montreal Process Indicator 1.1e in continuous dry eucalypt forests of sub-tropical Queensland, Australia. Target biota examined included: the Yellow-bellied Glider (Petaurus australis); the diversity of nectar and sap feeding glider species including P. australis, the Sugar Glider P. breviceps, the Squirrel Glider P. norfolcensis, and the Feathertail Glider Acrobates pygmaeus; six diurnal forest birds species; total diurnal bird species diversity; and the density of nectar-feeding diurnal bird species. Two scales of influence were considered: the stand-scale (2 ha), and a series of radial landscape extents (500 m - 2 km; 78 - 1250 ha) surrounding each fauna transect. For all biota, stand-scale structural and compositional attributes were found to be more influential than landscape metrics. For the Yellow-bellied Glider, the proportion of trace habitats with a residual element of old spotted-gum/ironbark eucalypt trees was a significant landscape metric at the 2 km landscape extent. This is a measure of habitat loss rather than habitat fragmentation. For the diversity of nectar and sap feeding glider species, the proportion of trace habitats with a high coefficient of variation in patch size at the 750 m extent was a significant landscape metric. None of the landscape metrics tested was important for diurnal forest birds. We conclude that no single landscape metric adequately captures the response of the region's forest biota per se. This poses a major challenge to regional reporting of Montreal Process Indicator 1.1e, fragmentation of forest types.://000181767400004 k ISI Document Delivery No.: 659FV Times Cited: 9 Cited Reference Count: 67 Cited References: 1995, CRITERIA INDICATORS *COM AUSTR DEP PRI, 1998, FRAM RG SUBN LEV CRI *QUEENSL DEP NAT R, 1998, SUST FOR MAN TECHN R *STATS INC, 1995, STATISTICA WIND ADDICOTT JF, 1987, OIKOS, V49, P340 AKAIKE H, 1973, 2 INT S INF THEOR, P267 AKAIKE H, 1985, CELEBRATION STAT, P1 BELBIN L, 1992, MULTIVAR BEHAV RES, V27, P417 BELBIN L, 1995, PATN PATTERN ANAL PA BISSONETTE JA, 1997, WILDLIFE LANDSCAPE E, P3 BRAND DG, 1997, BIOMASS BIOENERG, V13, P247 BUNNELL FL, 1997, FOREST CHRON, V73, P679 CALE PG, 1994, PACIFIC CONSERV BIOL, V1, P183 CATTERALL CP, 1993, BIRDS THEIR HABITATS CATTERALL CP, 1997, PACIFIC CONSERVATION, V3, P262 DIGBY PG, 1987, MULTIVARIATE ANAL EC DUNNING JB, 1992, OIKOS, V65, P169 EYRE TJ, 1997, FOREST ECOL MANAG, V98, P281 EYRE TJ, 1998, SYSTEMATIC VERTEBRAT FAHRIG L, 1997, J WILDLIFE MANAGE, V61, P603 FAHRIG L, 1999, FOREST FRAGMENTATION, P87 FAHRIG L, 1999, ISSUES LANDSCAPE ECO, P145 FAHRIG L, 2001, BIOL CONSERV, V100, P65 FLORENCE RG, 1996, ECOLOGY SILVICULTURE FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 GARMAN SL, 1999, FOREST FRAGMENTATION, P61 GOLDINGAY RG, 1991, AUSTR J ECOLOGY, P491 GOLDINGAY RL, 1991, CONSERVATION AUSTR F, P365 GRIMES RF, 1979, 17 DEP FOR HAINESYOUNG R, 1996, PROG PHYS GEOG, V20, P418 HANSEN AJ, 1992, LANDSCAPE BOUNDARIES HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HOBBS RJ, 1999, LANDSCAPE ECOLOGICAL, P11 JOHNSTON RJ, 1986, MULTIVARIATE STAT AN JOLLIFFE IT, 1986, PRINCIPAL COMPONENT KENNY DA, 1979, CORRELATION CAUSALIT KING AW, 1997, WILDLIFE LANDSCAPE E, P185 KOLASA J, 1991, ECOLOGICAL HETEROGEN, P1 KOTLIAR NB, 1990, OIKOS, V59, P253 LAURANCE WF, 1997, TROPICAL FOREST REMN LI CC, 1975, PATH ANAL PRIMER LINDENMAYER DB, 1997, AUST J ECOL, V22, P340 LINDENMAYER DB, 1999, BIOL CONSERV, V88, P387 LINDENMAYER DB, 1999, BIOL CONSERV, V89, P83 LINDENMAYER DB, 2002, FOREST ECOL MANAG, V159, P203 LOYN RH, 2001, CRITERIA INDICATORS, P391 MCALPINE CA, 1999, RANGELAND J, V21, P104 MCALPINE CA, 2002, AUSTR FORESTRY, V64, P232 MCALPINE CA, 2002, IN PRESS RANGELAND J, V24 MCDONALD RP, 1990, PSYCHOL BULL, V107, P247 MCGARIGAL K, 1994, FRAGSTATS SPATIAL PA MCGARIGAL K, 1995, ECOL MONOGR, V65, P235 MCINTYRE S, 1992, CONSERV BIOL, V6, P146 NOSS RF, 1999, FOREST ECOL MANAG, V115, P135 PRABHU R, 2001, CRITERIA INDICATORS, P39 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 ROCHELLE JA, 1999, FOREST FRAGMENTATION SCARTH P, 2001, CAN J REMOTE SENS, V27, P129 SHIPLEY B, 2000, CAUSE CORRELATION BI SMITH A, 1984, POSSUMS GLIDERS SORBOM D, 1992, 2 GENERATION MULTIVA, P341 STEIGER JH, 1995, STRUCTURAL EQUATION TABACHNICH BG, 2001, USING MULTIVARIATE S TANAKA JS, 1989, BRIT J MATH STAT P 2, V42, P233 TILMAN D, 1994, NATURE, V371, P65 WIENS JA, 1994, IBIS, V137, P97 WIENS JA, 1995, MOSAIC LANDSCAPES EC, P1 0921-2973 Landsc. Ecol.ISI:000181767400004mUniv Queensland, Sch Geog Planning & Architecture, Brisbane, Qld 4072, Australia. Univ Queensland, Ctr Ecol, Brisbane, Qld 4072, Australia. Queensland Parks & Wildlife Serv, Sustainable Forestry Sci Unit, Indooroopilly, Qld 4068, Australia. McAlpine, CA, Univ Queensland, Sch Geog Planning & Architecture, Brisbane, Qld 4072, Australia. c.mcalpine@mailbox.uq.edu.auEnglish|? McAlpine, Clive A. Seabrook, Leonie M. Rhodes, Jonathan R. Maron, Martine Smith, Carl Bowen, Michiala E. Butler, Sarah A. Powell, Owen Ryan, Justin G. Fyfe, Christine T. Adams-Hosking, Christine Smith, Andrew Robertson, Oliver Howes, Alison Cattarino, Lorenzo2010mCan a problem-solving approach strengthen landscape ecology's contribution to sustainable landscape planning? 1155-1168Landscape Ecology258OctMThe need to avert unacceptable and irreversible environmental change is the most urgent challenge facing society. Landscape ecology has the capacity to help address these challenges by providing spatially-explicit solutions to landscape sustainability problems. However, despite a large body of research, the real impact of landscape ecology on sustainable landscape management and planning is still limited. In this paper, we first outline a typology of landscape sustainability problems which serves to guide landscape ecologists in the problem-solving process. We then outline a formal problem-solving approach, whereby landscape ecologists can better bring about disciplinary integration, a consideration of multiple landscape functions over long time scales, and a focus on decision making. This framework explicitly considers multiple ecological objectives and socio-economic constraints, the spatial allocation of scarce resources to address these objectives, and the timing of the implementation of management actions. It aims to make explicit the problem-solving objectives, management options and the system understanding required to make sustainable landscape planning decisions. We propose that by adopting a more problem-solving approach, landscape ecologists can make a significant contribution towards realising sustainable future landscapes.!://WOS:000281725700003YTimes Cited: 2 10th International Congress of Ecology Aug 16-21, 2009 Brisbane, AUSTRALIA 0921-2973WOS:00028172570000310.1007/s10980-010-9514-x/<7 McCay, D. H.2001ZSpatial patterns of sand pine invasion into longleaf pine forests in the Florida Panhandle89-98Landscape Ecology162Florida landscape change land use history longleaf pine pine invasion sand pine SUB-ALPINE MEADOWS PLANT-COMMUNITIES VEGETATION CHANGE NATIONAL-PARK LANDSCAPE DETERMINANTS WASHINGTON FIRE USAArticleFebLand use practices since European settlement have had profound effects on the composition and structure of certain forested ecosystems in the southeastern U.S. Coastal Plain. One significant change since the turn of the century has been the invasion of upland pine forests by sand pine in the state of Florida panhandle and peninsula. This study quantified sand pine extent and expansion and examined links between sand pine distribution and environmental factors in the Florida panhandle. Geographic information system analysis using aerial photographs (1949 and 1994) showed sand pine expansion and also increased canopy cover of sand pine over time. There was a high rate of conversion of longleaf pine to sand pine from 1949 to 1994 (44%), and conversion of sparse sand pine stands to dense sand pine stands (69%). Therefore, widespread changes in the Florida landscape were evident during a relatively short time period. Adjacency analyses showed a strong negative association between longleaf pine and dense sand pine and a positive association between riparian vegetation and dense sand pine. Distribution of sand pine across elevation demonstrated that sand pine expanded inland and upland into longleaf-pine forests. In 1949, sand pine was selectively located on sites below 30 m in elevations; by 1994, sparse and moderately dense sand-pine stands were found at all elevations. Thus, any area that may receive an input of sand pine seeds, most notably from riparian areas, is vulnerable to establishment.://000167936500001 ISI Document Delivery No.: 419EN Times Cited: 5 Cited Reference Count: 44 Cited References: *ENV SYST RES I, 1997, ARC VERS 7 0 3 *FL NAT AR INV, 1994, EGL NAT COMM SURV YE *FL NAT FOR 1911, 1911, EGL AIR FORC BAS FOR *USAF, 1993, NAT RES MAN PLANT EG BRENDEMUEHL RH, 1990, SILVICS N AM, V1, P294 BRITT RW, 1973, P SAND PIN S BROWN JR, 1998, LANDSCAPE ECOL, V13, P93 BURNS RM, 1969, SE103 USDA FOR SERV CLEWELL AF, 1981, NATURAL SETTING VEGE COOPER RW, 1959, 30 USDA FOR SERV DEFERRARI CM, 1994, J VEG SCI, V5, P247 FULE PZ, 1998, PLANT ECOL, V134, P197 FULE PZ, 2000, FOREST SCI, V46, P52 GREENE DF, 1989, CAN GEOGR, V33, P78 JACOBS J, 1974, OECOLOGIA, V14, P413 JAKUBOS B, 1993, ARCTIC ALPINE RES, V25, P382 JENKINS SH, 1979, OECOLOGIA BERL, V44, P112 JOHNSON EA, 1987, CAN J BOT, V65, P853 LAESSLE AM, 1965, ECOLOGY, V46, P65 LIGHT SS, 1995, BARRIERS BRIDGES REN LITTLE EL, 1952, J FOREST, V50, P204 MAST JN, 1999, ECOL APPL, V9, P228 MCCAY DH, 2000, ECOSYSTEMS, V3, P283 MCCUNE B, 1988, AM J BOT, V75, P353 MENGES ES, 1993, J VEG SCI, V4, P375 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 MYERS RL, 1985, B TORREY BOT CLUB, V112, P241 MYERS RL, 1987, B TORREY BOT CLUB, V114, P21 PAINE RT, 1998, ECOSYSTEMS, V1, P535 PARKER AJ, IN PRESS ANN ASS AM PARKER KC, 1997, J TORREY BOT SOC, V124, P22 PASTOR J, 1990, LANDSCAPE ECOL, V4, P55 PASTOR J, 1992, WATERSHED MANAGEMENT, P324 PROVENCHER L, 1999, EFFECTS HARDWOOD RED RICHARDSON DM, 1991, AM NAT, V137, P639 RICHARDSON DM, 1994, J BIOGEOGR, V21, P511 ROBERTS EV, 1931, EGLIN AIR FORCE BASE SCHUMM SA, 1995, GEOMORPHOLOGY, V12, P281 SPRUGEL DG, 1991, BIOL CONSERV, V58, P1 STEINAUER EM, 1987, AM MIDL NAT, V118, P358 TAYLOR AH, 1990, PROF GEOGR, V42, P457 VENO PA, 1976, ECOLOGY, V57, P498 WAHLENBERG WG, 1946, LONGLEAF PINE ITS US WOODWARD A, 1995, ARCTIC ALPINE RES, V27, P217 0921-2973 Landsc. Ecol.ISI:000167936500001lColgate Univ, Dept Geog, Hamilton, NY 13346 USA. McCay, DH, Colgate Univ, Dept Geog, Hamilton, NY 13346 USA.English|7Mccleery, R. A.2009OChanges in fox squirrel anti-predator behaviors across the urban-rural gradient483-493Landscape Ecology244anti-predator behavior vigilance squirrel urban urban-rural gradient predation risk tangential approach patch-use vigilance ecology discrimination conservation responses ecosystem survivalAprVPredator stimuli created by humans in the urban environment may alter animals' anti-predator behaviors. I hypothesized that habituation would cause anti-predator behaviors to decrease in urban settings in response to humans. Additionally, I hypothesized that populations habituated to humans would show reduced responses to other predator stimuli. I observed three populations of squirrels (urban, suburban and rural) responses to human approaches, red-tailed hawk vocalizations (Buteo jamaicensis) and coyote (Canis latrans) vocalizations. Mahalanobis distances of anti-predator behaviors in response to human approaches were consistent with the urban-rural gradient. Flight initiation distances (X (2) = 26.33, df = 2, P < 0.001) and amount of time dedicated to anti-predator behavior (X (2) = 10.94, df = 2, P = 0.004) in response to human approaches were also consistent with the urban-rural gradient. Supporting the habituation hypothesis, naive juvenile squirrels increased flight initiation distances (X (2) = 35.89, df = 1, P < 0.001) and time dedicated to anti-predator behaviors (X (2) = 9.46, df = 1, P = 0.002) relative to adult squirrels in the same urban environment. Time dedicated to anti-predator behaviors differed among all three sites in response to both coyote (X (2) = 9.83, df = 2, P = 0.007) and hawk (X (2) = 6.50, df = 2, P = 0.035) vocalizations. Responses to both vocalizations on rural sites (coyote = 45%, hawk = 55%) greater than twice that found on the urban sites (coyote = 11%, hawk = 20%). This is possibly the first case of a transfer of habituation demonstrated under field conditions.://000263898100004-414XI Times Cited:0 Cited References Count:48 0921-2973ISI:000263898100004Mccleery, RA Texas A&M Univ, Dept Wildlife & Fisheries Sci, College Stn, TX 77843 USA Texas A&M Univ, Dept Wildlife & Fisheries Sci, College Stn, TX 77843 USADoi 10.1007/S10980-009-9323-2English|?McDonnell, M. J. Hahs, A. K.2008The use of gradient analysis studies in advancing our understanding of the ecology of urbanizing landscapes: current status and future directions 1143-1155Landscape Ecology2310~Over the past decade, the urban-rural gradient approach has been effectively used to study the ecology of cities and towns around the world. These studies have focused on understanding the distribution of plants and animals as well as ecosystem processes along gradients of urbanization that run from densely urbanized inner city to more rural exurban environments. We reviewed 300 papers investigating urbanization gradients that were published in peer-reviewed journals between 1990 and May 2007. Sixty-three percent of the papers investigated the distribution of organisms along urbanization gradients. Only five papers addressed the measures used to quantify the urbanization gradient itself. Within the papers addressing the distribution of organisms, 49% investigated the responses of birds to urbanization gradients, and < 10% of the papers investigated more cryptic organisms. Most of these studies utilized a variety of broad measures of urbanization, but future advances in the field will require the development of some standardized broad measures to facilitate comparisons between cities. More specific measures of urbanization can be used to gain a mechanistic understanding of species and ecosystem responses to urbanization gradients. While the gradient approach has made a significant contribution to our understanding of the ecology of cities and towns, there is now a need to address our current knowledge gaps so that the field can reach its full potential. We present two examples of research questions that demonstrate how we can enhance our understanding of urbanization gradients, and the ecological knowledge that we can obtain from them.!://WOS:000261790600002Times Cited: 1 0921-2973WOS:00026179060000210.1007/s10980-008-9253-4<70McGarigal, K. Romme, W. H. Crist, M. Roworth, E.2001hCumulative effects of roads and logging on landscape structure in the San Juan Mountains, Colorado (USA)327-349Landscape Ecology164cumulative effects forest management fragmentation landscape change landscape pattern landscape structure logging roads SUB-ALPINE FORESTS ROCKY-MOUNTAINS STAND DEVELOPMENT BREEDING BIRDS FIR FOREST CLEAR-CUT FRAGMENTATION RESPONSES DYNAMICS OREGONArticleMay In the southern Rocky Mountains of temperate North America, the effects of Euro-American activities on disturbance regimes and landscape patterns have been less ubiquitous and less straightforward in high-elevation landscapes than in low-elevation landscapes. Despite apparently little change in the natural disturbance regime, there is increasing concern that forest management activities related mainly to timber harvest and to the extensive network of roads constructed to support timber harvest, fire control, and recreation since the late 1800s have altered disturbance regimes and landscape structure. We investigated the magnitude of change in landscape structure resulting from roads and logging since the onset of timber harvest activities in 1950. We found limited evidence for significant impacts in our study area when all lands within the landscape were considered. The relatively minor changes we observed reflected the vast buffering capacity of the large proportion of lands managed for purposes other than timber (e.g., wilderness). Significant changes in landscape structure and fragmentation of mature forest were, however, evident on lands designated as suitable timberlands. Roughly half of the mature coniferous forest was converted to young stands; mean patch size and core area declined by 40% and 25%, respectively, and contrast-weighted edge density increased 2- to 3-fold. Overall, roads had a greater impact on landscape structure than logging in our study area. Indeed, the 3-fold increase in road density between 1950-1993 accounted for most of the changes in landscape configuration associated with mean patch size, edge density, and core area. The extent of area evaluated and the period over which change was evaluated had a large impact on the magnitude of change detected and our conclusions regarding the ecological significance of those changes. Specifically, the cumulative impact on landscape structure was negligible over a 10-year period, but was notable over a 40-year period. In addition, the magnitude of change in landscape structure between 1950-1993 varied as a function of landscape extent. At the scale of the 228 000 ha landscape, change in landscape structure was trivial, suggesting that the landscape was capable of fully incorporating the disturbances with minimal impact. However, at intermediate scales of 1000-10 000 ha landscapes, change in landscape structure was quite evident, suggesting that there may be an optimal range of scales for detecting changes in landscape structure within the study area.://000169516300004 ISI Document Delivery No.: 446MD Times Cited: 22 Cited Reference Count: 93 Cited References: 1971, UNPUB SW STUDIES CTR, V1 *ESRI INC, 1995, UND GIS ARC INFO MET *SAN JUAN NAT FOR, 1972, UNPUB TIMB MAN PLAN AGREE JK, 1999, FOREST FRAGMENTATION, P43 BAISAN CH, 1997, RMRP330 USDA FOR SER BAKER WL, 1992, ECOLOGY, V73, P1879 BAKER WL, 1994, LANDSCAPE STRUCTURE BAKER WL, 2000, FOREST FRAGMENTATION, P97 BENNINGERTRUAX M, 1992, LANDSCAPE ECOL, V6, P269 BESSIE WC, 1995, ECOLOGY, V76, P747 BLAIR R, 1996, W SAN JUAN MOUNTAINS BOYCE MS, 1997, ECOSYSTEM MANAGEMENT BREW DC, 1996, W SAN JUAN MOUNTAINS, P18 CAMPBELL JA, 1996, W SAN JUAN MOUNTAINS, P54 CHEN JQ, 1990, NORTHWEST ENVIRON J, V6, P424 CHEN JQ, 1992, ECOL APPL, V2, P387 CHEN JQ, 1993, AGR FOREST METEOROL, V63, P219 COVINGTON WW, 1992, OLD GROWTH FORESTS S, P81 DOBKIN DS, 1994, CONSERVATION MANAGEM ELLINGSON JA, 1996, W SAN JUAN MOUNTAINS, P38 ELLINGSON JA, 1996, W SAN JUAN MOUNTAINS, P68 FAHRIG L, 1995, BIOL CONSERV, V73, P177 FLOYDHANNA L, 1996, W SAN JUAN MOUNTAINS, P143 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FORMAN RTT, 1998, ANNU REV ECOL SYST, V29, P207 FORMAN RTT, 2000, CONSERV BIOL, V14, P31 FORMAN RTT, 2000, CONSERV BIOL, V14, P36 FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 FRANKLIN JF, 1997, ECOSYSTEM MANAGEMENT, P21 GILPIN ME, 1991, METAPOPULATION DYNAM GRUMBINE RE, 1994, CONSERV BIOL, V8, P27 HANSEN AJ, 1999, MAINTAINING BIODIVER HARGIS CD, 1997, WILDLIFE LANDSCAPE E, P231 HEJL SJ, 1992, NORTHWEST ENVIRON J, V8, P119 HEJL SJ, 1995, ECOLOGY MANAGEMENT N, P220 JAMIESON DW, 1996, W SAN JUAN MOUNTAINS, P159 KEEN RA, 1996, W SAN JUAN MOUNTAINS, P113 KNIGHT RL, 2000, FOREST FRAGMENTATION KOHM KA, 1997, CREATING FORESTRY 21 LEHMKUHL JF, 1991, WILDLIFE VEGETATION, P35 LERTZMAN KP, 1991, CAN J FOREST RES, V21, P1730 LI H, 1995, OIKOS, V73, P280 LOVEJOY TE, 1986, CONSERVATION BIOL SC, P257 LYON LJ, 1980, J WILDLIFE MANAGE, V44, P352 MCCLELLAN BN, 1988, J APPL ECOL, V25, P451 MCGARIGAL K, 1995, ECOL MONOGR, V65, P235 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MILLER JR, 1996, LANDSCAPE ECOL, V11, P115 MOODY A, 1995, LANDSCAPE ECOL, V10, P363 MURCIA C, 1995, TRENDS ECOL EVOL, V10, P58 NORSE E, 1986, CONSERVING BIOL DIVE PEARSON GA, 1950, AGR MONOGRAPH, V6 PULLIAM HR, 1988, AM NAT, V132, P652 REED RA, 1996, BIOL CONSERV, V75, P267 REED RA, 1996, CONSERV BIOL, V10, P1098 RIPPLE WJ, 1991, BIOL CONSERV, V57, P73 RITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 ROBBINS CS, 1989, WILDLIFE MONOG, V103 ROBINSON SK, 1995, SCIENCE, V267, P1987 ROCHELLE JA, 1999, FORST FRAGMENTATION ROMME WH, 1989, BIOSCIENCE, V39, P695 ROMME WH, 1992, OLD GROWTH FORESTS S, P154 ROMME WH, 1998, UNPUB LANDSCAPE COND ROOVERS LM, 1993, NAT AREA J, V13, P256 ROSEN PC, 1994, BIOL CONSERV, V68, P143 ROST GR, 1979, J WILDLIFE MANAGE, V43, P634 RUGGIERO LF, 1994, RM254 USDA FOR SERV SAMSON FB, 1996, ECOSYSTEM MANAGEMENT SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SCHMID JM, 1996, RMGTR275 USDA FOR SE SCHMIEGELOW FKA, 1997, ECOLOGY, V78, P1914 SHINNEMAN DJ, 1996, THESIS U WYOMING LAR SIMPSON EH, 1949, NATURE, V163, P688 SOMERS LP, 1996, W SAN JUAN MOUNTAINS, P175 SPENCER AW, 1996, W SAN JUAN MOUNTAINS, P129 SPIES TA, 1994, ECOL APPL, V4, P555 TEMPLE SA, 1986, EWILDLIFE 2000 MODEL, P261 TEMPLE SA, 1986, WILDLIFE 2000 MODELI, P301 TINKER DB, 1997, LANDSCAPE ECOL, V12, P1 TROMBULAK SC, 2000, CONSERV BIOL, V14, P18 TRZCINSKI MK, 1999, ECOL APPL, V9, P586 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 VAILLANCOURT DA, 1995, THESIS U WYOMING LAR VEBLEN TT, 1989, CAN J FOREST RES, V19, P1218 VEBLEN TT, 1991, ECOLOGY, V72, P213 VEBLEN TT, 1991, J BIOGEOGR, V18, P707 VILLARD MA, 1999, CONSERV BIOL, V13, P774 VOGT KA, 1997, ECOSYSTEMS BALANCING WALLIN DO, 1996, FOREST ECOL MANAG, V85, P291 WEIR JMH, 1995, P S FIR WILD PARK MA, P275 WHITCOMB RF, 1981, FOREST ISLAND DYNAMI, P125 WIENS JA, 1989, FUNCT ECOL, V3, P385 0921-2973 Landsc. Ecol.ISI:000169516300004Univ Massachusetts, Dept Nat Resources Conservat, Amherst, MA 01003 USA. McGarigal, K, Univ Massachusetts, Dept Nat Resources Conservat, Amherst, MA 01003 USA.English t|7&McGarigal, K. Tagil, S. Cushman, S. A.2009^Surface metrics: an alternative to patch metrics for the quantification of landscape structure433-450Landscape Ecology243landscape gradient model surface patterns landscape heterogeneity landscape metrics landscape pattern ecology vegetation roughness scale fragmentation patterns systems model areaMar5Modern landscape ecology is based on the patch mosaic paradigm, in which landscapes are conceptualized and analyzed as mosaics of discrete patches. While this model has been widely successful, there are many situations where it is more meaningful to model landscape structure based on continuous rather than discrete spatial heterogeneity. The growing field of surface metrology offers a variety of surface metrics for quantifying landscape gradients, yet these metrics are largely unknown and/or unused by landscape ecologists. In this paper, we describe a suite of surface metrics with potential for landscape ecological application. We assessed the redundancy among metrics and sought to find groups of similarly behaved metrics by examining metric performance across 264 sample landscapes in western Turkey. For comparative purposes and to evaluate the robustness of the observed patterns, we examined 16 different patch mosaic models and 18 different landscape gradient models of landscape structure. Surface metrics were highly redundant, but less so than patch metrics, and consistently aggregated into four cohesive clusters of similarly behaved metrics representing surface roughness, shape of the surface height distribution, and angular and radial surface texture. While the surface roughness metrics have strong analogs among the patch metrics, the other surface components are largely unique to landscape gradients. We contend that the surface properties we identified are nearly universal and have potential to offer new insights into landscape pattern-process relationships.://000263419500011-408EY Times Cited:0 Cited References Count:49 0921-2973ISI:000263419500011McGarigal, K Univ Massachusetts, Dept Nat Resources Conservat, Amherst, MA 01003 USA Univ Massachusetts, Dept Nat Resources Conservat, Amherst, MA 01003 USA Balikesir Univ, Dept Geog, TR-10100 Balikesir, Turkey USDA Forest Serv, Rocky Mt Res Stn, Forestry Sci Lab, Missoula, MT 59801 USADoi 10.1007/S10980-009-9327-YEnglishڽ7 #McGinnis, Stephanie Kerans, BillieL2013ILand use and host community characteristics as predictors of disease risk29-44Landscape Ecology281Springer NetherlandssWhirling disease Rainbow trout Land use Myxobolus cerebralis Tubifex tubifex Montana Degradation Landscape Zoonotic 2013/01/01+http://dx.doi.org/10.1007/s10980-012-9810-8 0921-2973Landscape Ecol10.1007/s10980-012-9810-8EnglishQ۽7?0McIntyre, NancyE Iverson, LouisR Turner, MonicaG2013JA 27-year perspective on landscape ecology from the US-IALE annual meeting 1845-1848Landscape Ecology2810Springer Netherlands 2013/12/01+http://dx.doi.org/10.1007/s10980-013-9944-3 0921-2973Landscape Ecol10.1007/s10980-013-9944-3Englishڽ7 "McIntyre, NancyE Strauss, RichardE2013qA new, multi-scaled graph visualization approach: an example within the playa wetland network of the Great Plains769-782Landscape Ecology284Springer Netherlands3Contour mapping Graph theory Network Sliding window 2013/04/01+http://dx.doi.org/10.1007/s10980-013-9862-4 0921-2973Landscape Ecol10.1007/s10980-013-9862-4EnglishZ<7McIntyre, N. E.1995/Effects of forest patch size on avian diversity85-99Landscape Ecology102.AVIAN DIVERSITY; GEORGIA; LANDSCAPE PATCHINESSArticleAprThe effects of landscape patchiness on the diversity of birds of the Georgia Piedmont were investigated during 1993. Birds were sampled along line transects within relatively large (10-13.25 ha) and small (less than 3.25 ha) forest patches located within nonforest agricultural landscapes. Patterns of habitat use in these patches were compared to those in contiguous forest patches larger than 13.25 ha. Analysis of variance revealed significant differences in diversity between large and small woodlots and between contiguous and fragmented landscapes, especially in terms of the numbers of edge and interior species and winter-resident, summer-resident, and year-round birds observed.://A1995QX34400003 IISI Document Delivery No.: QX344 Times Cited: 27 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1995QX34400003@MCINTYRE, NE, COLORADO STATE UNIV,DEPT BIOL,FT COLLINS,CO 80523.English-<7?McIntyre, N. E. Wiens, J. A.1999Interactions between landscape structure and animal behavior: the roles of heterogeneously distributed resources and food deprivation on movement patterns437-447Landscape Ecology145food deprivation movement resource distribution DARKLING BEETLES COLEOPTERA SEARCHING BEHAVIOR SPATIAL-DISTRIBUTION TENEBRIONID BEETLES SHORTGRASS PRAIRIE POPULATION-SIZE HABITAT SCALE ORIENTATION RESPONSESArticleOctTo examine how resource distributions affect the movement behaviors of fed and food-deprived Eleodes extricata Say darkling beetles (Coleoptera: Tenebrionidae), we experimentally manipulated the dispersion of food to create clumped, random, and uniform distributions in an otherwise homogeneous 25-m(2) experimental field landscape. Quantitative measures of the tortuosity, net linear displacement, overall path length, and velocity of beetle movement pathways showed that food-deprived beetles generally moved more slowly and over shorter distances than did fed beetles. This effect was mediated by the spatial distribution of food, however; food distributed randomly over the landscape evoked more tortuous paths over larger overall distances. The foraging movements of food-deprived beetles were most different from those of fed individuals in treatments with randomly distributed food resources. These results show that the influence of spatial structure on individuals depends not only on the arrangement of pattern but also on the function that the structure plays. Thus, 'spatial structure' is defined not only by physical characteristics of the landscape but also by how that structure is used by animals.://000082510000003 ISI Document Delivery No.: 234XQ Times Cited: 24 Cited Reference Count: 75 Cited References: *SAS I INC, 1996, SAS STAT SOFTW CHANG ANDREASSEN HP, 1996, J APPL ECOL, V33, P555 ANDREASSEN HP, 1996, J APPL ECOL, V33, P63 ARDITI R, 1988, AM NAT, V131, P837 BAARS MA, 1979, OECOLOGIA, V44, P125 BELL WJ, 1979, J INSECT PHYSIOL, V25, P631 BELL WJ, 1985, ANIM BEHAV, V33, P436 BELL WJ, 1990, ANNU REV ENTOMOL, V35, P447 BELL WJ, 1991, SEARCHING BEHAV BEHA BERNSTEIN C, 1988, J ANIM ECOL, V57, P1007 BURKE VJ, 1997, US IALE NEWSLETTER, V13, P6 CALKINS CO, 1973, ANN ENTOMOL SOC AM, V66, P527 CARTAR RV, 1997, OECOLOGIA, V112, P430 CARTER MC, 1982, J ANIM ECOL, V51, P865 CRAWFORD CS, 1981, BIOL DESERT INVERTEB CRESSWELL JE, 1997, OIKOS, V78, P546 CRIST TO, 1992, FUNCT ECOL, V6, P536 CRIST TO, 1995, J ANIM ECOL, V64, P733 DEROOS AM, 1991, P ROY SOC LOND B BIO, V246, P117 DICKE M, 1988, PHYSIOL ENTOMOL, V13, P393 DOYEN JT, 1974, ANN ENTOMOLOGICAL SO, V67, P617 DUSENBERY DB, 1989, J THEOR BIOL, V136, P309 DUVALL D, 1994, AM ZOOL, V34, A78 EDWARDS GR, 1994, J ANIM ECOL, V63, P816 EVANS HF, 1976, ECOL ENTOMOL, V1, P163 FROMM JE, 1987, PHYSIOL ENTOMOL, V12, P297 GARDNER RH, 1989, LANDSCAPE ECOL, V3, P217 GARDNER RH, 1991, ECOTONES ROLE LANDSC, P76 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 HASSELL MP, 1978, ANNU REV ECOL SYST, V9, P75 HASTINGS HM, 1993, FRACTALS USERS GUIDE HOLLING CS, 1966, MEM ENTOMOL SOC CAN, V48 IMS RA, 1993, BIOL CONSERV, V63, P261 IMS RA, 1995, MOSAIC LANDSCAPES EC, P85 JANDER R, 1975, ANNU REV ECOL SYST, V6, P171 JANDER R, 1982, BIOL SOCIAL INSECTS, P28 JOHNSON AR, 1992, ECOLOGY, V73, P1968 KAREIVA P, 1985, ECOLOGY, V66, P1809 KOTLIAR NB, 1990, OIKOS, V59, P253 LAUENROTH WK, 1991, ECOSYSTEMS WORLD A, V8, P183 LEVIN DA, 1971, EVOLUTION, V25, P113 LUDWIG JA, 1988, STAT ECOLOGY PRIMER MANDELBROT BB, 1983, FRACTAL GEOMETRY NAT MAYNARDSMITH J, 1978, ANNU REV ECOL SYST, V9, P31 MCINTYRE NE, 1997, AM MIDL NAT, V138, P230 MCINTYRE NE, 1997, ANN ENTOMOL SOC AM, V90, P260 MERRIAM G, 1988, TRENDS ECOL EVOL, V3, P16 MILNE BT, 1992, THEOR POPUL BIOL, V41, P337 MITCHELL B, 1963, J ANIM ECOL, V32, P289 MOLS PJM, 1979, 18 AG U MOLS PJM, 1987, ACTA PHYTOPATHOL ENT, V22, P187 OLLASON JG, 1980, THEOR POPUL BIOL, V18, P44 PARMENTER RR, 1988, ENVIRON ENTOMOL, V17, P280 PYKE GH, 1984, ANNU REV ECOL SYST, V15, P523 ROGERS LE, 1988, ANN ENTOMOL SOC AM, V81, P782 ROSE GA, 1990, ECOLOGY, V71, P33 SOKAL RR, 1981, BIOMETRY TINBERGEN N, 1967, BEHAVIOUR, V28, P307 TORTORICI C, 1986, ANIM BEHAV, V34, P1568 TRIOLA MF, 1995, ELEMENTARY STAT TURCHIN P, 1991, ECOLOGY, V72, P1253 VAIL SG, 1993, AM NAT, V141, P199 WHICKER AD, 1987, ECOL ENTOMOL, V12, P97 WIENS JA, 1989, FUNCT ECOL, V3, P385 WIENS JA, 1989, LANDSCAPE ECOLOGY, V3, P87 WIENS JA, 1993, ENVIRON ENTOMOL, V22, P709 WIENS JA, 1993, OIKOS, V66, P369 WIENS JA, 1995, ECOLOGY, V76, P663 WIENS JA, 1995, MOSAIC LANDSCAPES EC, P1 WIENS JA, 1997, OIKOS, V78, P257 WITH KA, 1994, LANDSCAPE ECOL, V9, P25 WITH KA, 1995, ECOLOGY, V76, P2446 WITH KA, 1997, OIKOS, V79, P219 WITH KA, 1997, US IALE NEWSLETTER, V13, P13 YOUNT VA, 1971, THESIS COLORADO STAT 0921-2973 Landsc. Ecol.ISI:000082510000003Colorado State Univ, Dept Biol, Ft Collins, CO 80523 USA. McIntyre, NE, Arizona State Univ, Ctr Environm Studies, Box 873211, Tempe, AZ 85287 USA.English J<7McIntyre, N. E. Wiens, J. A.2000AA novel use of the lacunarity index to discern landscape function313-321Landscape Ecology154lacunarity landscape function landscape pattern landscape use scale TENEBRIONID BEETLES SHORTGRASS PRAIRIE ECOLOGY MOVEMENTS HABITAT COLEOPTERA SELECTION PATTERNS TEXTUREArticleMayDiscerning the function of a landscape involves comparing landscape use with spatial patterns. To do this requires both quantification of landscape use and landscape pattern and a means of comparing the two. An index of lacunarity has been used to quantify spatial pattern (specifically, habitat contagion). We demonstrate a new way of using the lacunarity index to quantify landscape function as well. We calculated lacunarity to describe landscape patchiness of experimental landscapes with respect to patterns of habitat and non-habitat areas (the previous use of lacunarity) as well as to describe patterns of patch use by animals in those landscapes, irrespective of habitat-patch patterns (a novel application of lacunarity). We demonstrate a disparity between landscape pattern and landscape use. This finding suggests that drawing generalizations of, and making predictions about, how animals respond to landscape spatial structure may not be straightforward.://000086006700001 ISI Document Delivery No.: 296DA Times Cited: 14 Cited Reference Count: 37 Cited References: *SAS I INC, 1988, SAS STATR US GUID RE ALLAIN C, 1991, PHYS REV A, V44, P3552 BAIN MB, 1988, AQUATIC RESOURCE RES, V883 CALKINS CO, 1973, ANN ENTOMOL SOC AM, V66, P527 CODY RP, 1991, APPL STAT SASR PROGR CRIST TO, 1992, FUNCT ECOL, V6, P536 CRIST TO, 1995, J ANIM ECOL, V64, P723 DOYEN JT, 1974, ANN ENTOMOLOGICAL SO, V67, P617 EBERT TA, 1990, THESIS COLORADO STAT FAHRIG L, 1994, CONSERV BIOL, V8, P50 HENEBRY GM, 1995, INT J REMOTE SENS, V16, P565 HOBBS R, 1997, LANDSCAPE URBAN PLAN, V37, P1 JOHNSON AR, 1992, ECOLOGY, V73, P1968 LIN B, 1986, J PHYS A, V19, L49 MANDELBROT BB, 1983, FRACTAL GEOMETRY NAT MCCLEAN SA, 1998, J WILDLIFE MANAGE, V62, P793 MCINTYRE NE, IN PRESS ECOLOGY MCINTYRE NE, 1997, AM MIDL NAT, V138, P230 MLADENOFF DJ, 1998, J WILDLIFE MANAGE, V62, P1 PLOTNICK RE, 1993, LANDSCAPE ECOL, V8, P201 PLOTNICK RE, 1996, PHYS REV E B, V53, P5461 RIITTERS KH, 1996, LANDSCAPE ECOL, V11, P197 ROGERS LE, 1988, ANN ENTOMOL SOC AM, V81, P782 SCHROEDER R, 1986, FWSOBS821028 SHORT HL, 1984, FWSOBS821070 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 VANHORNE B, 1991, US FISH WILDLIFE SER, V8 WHICKER AD, 1983, THESIS COLORADO STAT WHICKER AD, 1987, ECOL ENTOMOL, V12, P97 WIENS JA, 1989, LANDSCAPE ECOLOGY, V3, P87 WIENS JA, 1992, LANDSCAPE ECOL, V7, P149 WIENS JA, 1993, ENVIRON ENTOMOL, V22, P709 WIENS JA, 1996, METAPOPULATIONS WILD, P53 WIENS JA, 1997, OIKOS, V78, P257 WITH KA, 1995, ECOLOGY, V76, P2446 WITH KA, 1997, OIKOS, V79, P219 YOUNT VA, 1971, THESIS COLORADO STAT 0921-2973 Landsc. Ecol.ISI:000086006700001Colorado State Univ, Dept Biol, Ft Collins, CO 80523 USA. Colorado State Univ, Grad Degree Program Ecol, Ft Collins, CO 80523 USA. McIntyre, NE, Arizona State Univ, Ctr Environm Studies, Box 873211, Tempe, AZ 85287 USA.Englishv<7+McKenzie, D. Hessl, A. E. Kellogg, L. K. B.2006IUsing neutral models to identify constraints on low-severity fire regimes139-152Landscape Ecology211 fire regimes; hazard function; low-severity fire; neutral models; Ponderosa pine; stochastic process; Weibull; WMPI PONDEROSA PINE FORESTS; AMERICAN SOUTHWEST; FRACTAL LANDSCAPES; PACIFIC-NORTHWEST; UNITED-STATES; HISTORY; MOUNTAINS; FREQUENCY; DISTURBANCE; COLORADOArticleJanClimate, topography, fuel loadings, and human activities all affect spatial and temporal patterns of fire occurrence. Because fire is modeled as a stochastic process, for which each fire history is only one realization, a simulation approach is necessary to understand baseline variability, thereby identifying constraints, or forcing functions, that affect fire regimes. With a suitable neutral model, characteristics of natural fire regimes estimated from fire history data can be compared to a "null hypothesis". We generated random landscapes of fire-scarred trees via a point process with sequential spatial inhibition. Random ignition points, fire sizes, and fire years were drawn from uniform and exponential family probability distributions. We compared two characteristics of neutral fire regimes to those from five watersheds in eastern Washington that have experienced low-severity fire. Composite fire intervals (CFIs) at multiple spatial scales displayed similar monotonic decreases with increasing sample area in neutral vs. real landscapes, although patterns of residuals from statistical models differed. In contrast, parameters of the Weibull distribution associated with temporal trends in fire hazard exhibited different forms of scale dependence in real vs. simulated data. Clear patterns in neutral landscapes suggest that deviations from them in empirical data represent real constraints on fire regimes (e.g., topography, fuels). As with any null model, however, neutral fire-regime models need to be carefully tuned to avoid confounding these constraints with artifacts of modeling. Neutral models show promise for investigating low-severity fire regimes to separate intrinsic properties of stochastic processes from the effects of climate, fuel loadings, topography, and management.://000235887300011  ISI Document Delivery No.: 020DD Times Cited: 0 Cited Reference Count: 62 Cited References: *INS INC, 2002, SPLUS 6 WIND AGEE JK, 1993, FIRE ECOLOGY PACIFIC BAKER WL, 1989, CAN J FOREST RES, V19, P700 BAKER WL, 2001, CAN J FOREST RES, V31, P1205 BARNETT V, 1976, J ROYAL STATISTICA A, V139, P318 BOYD R, 1999, INDIANS FIRE LAND PA, P1 CAMP A, 1997, FOREST ECOL MANAG, V95, P63 CASWELL H, 1976, ECOL MONOGR, V46, P327 CLARK JS, 1989, OIKOS, V56, P17 CLARK JS, 1990, ECOL MONOGR, V60, P135 CLARK JS, 1996, AM NAT, V148, P976 DAVISON AC, 1997, BOOTSTRAP METHODS TH EFRON B, 1993, INTRO BOOTSTRAP EVANS M, 1993, STAT DISTRIBUTIONS EVERETT RL, 2000, FOREST ECOL MANAG, V129, P207 FALK DA, 2003, FIRE FUEL TREATMENTS FALK DA, 2004, THESIS U ARIZONA TUC GALBRAITH WA, 1991, RANGELANDS, V13, P213 GARDNER RH, 1991, QUANTITATIVE METHODS, CH11 GOTELLI NJ, 1996, NULL MODELS ECOLOGY GREEN DG, 1994, PACIFIC CONSERVATION, V1, P194 GRISSINOMAYER HD, 1995, THESIS U ARIZONA TUC GRISSINOMAYER HD, 1999, INT J WILDLAND FIRE, V9, P37 GRISSINOMAYER HD, 2000, HOLOCENE, V10, P213 GRISSINOMAYER HD, 2004, ECOLOGY, V85, P1708 HESSL AE, 2004, ECOL APPL, V14, P425 HEYERDAHL EK, 1995, EPA600R96081 OFF RES HEYERDAHL EK, 2001, ECOLOGY, V82, P660 HOSMER DW, 1999, APPL SURVIVAL ANAL HUBBLE SP, 2001, UNIFIED NEUTRAL THEO JOHNSON EA, 1994, ADV ECOL RES, V25, P239 KEITT TH, 1997, CONSERV ECOL, V1, P1 KELLOGG LKB, 2004, THESIS U WASHINGTON KIMURA M, 1983, NEUTRAL THEORY MOL E LANDRES PB, 1999, ECOL APPL, V9, P1179 LEGENDRE P, 2002, ECOGRAPHY, V25, P601 LERTZMAN K, 1998, NW SCI, V72, P4 LI C, 2002, ECOL MODEL, V154, P103 LYNCH JA, 2003, J GEOPHYS RES, V107, P8152 MALAMUD BD, 1998, SCIENCE, V281, P1840 MCKENZIE D, 2000, ECOL APPL, V10, P1497 MCKENZIE D, 2004, EMULATING NATURAL FO, CH7 MILNE BT, 1992, AM NAT, V139, P32 MILNE BT, 1996, ECOLOGY, V77, P805 PALMER MW, 1992, AM NAT, V139, P375 PRICHARD SJ, 2003, THESIS U WASHINGTON PYNE SJ, 2001, YEAR FIRES STORY GRE REED WJ, 2002, ECOL MODEL, V150, P239 RIPLEY BD, 1987, STOCHASTIC SIMULATIO ROBBINS WG, 1994, PNWGTR319 USDA FOR S ROBBINS WG, 1999, INDIANS FIRE LAND PA, P219 RORIG ML, 1999, J APPL METEOROL, V38, P1565 ROSENZWEIG ML, 1995, SPECIES DIVERSITY SP ROSS JA, 1999, INDIANS FIRE LAND PA, P1 ROSS S, 1988, 1 COURSE PROBABILITY SCHMOLDT DL, 1999, PNWGTR455 USDA FOR S SWETNAM TW, 1990, SCIENCE, V249, P1017 SWETNAM TW, 1999, ECOL APPL, V9, P1189 TAYLOR AH, 2003, ECOL APPL, V13, P704 VEBLEN TT, 2000, ECOL APPL, V10, P1178 WEIHER E, 1999, ECOLOGICAL ASSEMBLY WITH KA, 1997, CONSERV BIOL, V11, P1069 0921-2973 Landsc. Ecol.ISI:000235887300011US Forest Serv, Pacific Wildland Fire Sci Lab, USDA, Seattle, WA 98103 USA. W Virginia Univ, Dept Geol & Geog, Morgantown, WV 26506 USA. McKenzie, D, US Forest Serv, Pacific Wildland Fire Sci Lab, USDA, 400 N,34th St,Suite 201, Seattle, WA 98103 USA. donaldmckenzie@fs.fed.usEnglishw|?2 -McWethy, D. B. Hansen, A. J. Verschuyl, J. P.2010^Bird response to disturbance varies with forest productivity in the northwestern United States533-549Landscape Ecology2547Huston's Dynamic Equilibrium Hypothesis predicts that the response of biodiversity to disturbance varies with productivity. Because disturbance is thought to break competitive advantage of dominant species in productive ecosystems, species richness is predicted to increase with disturbance frequency in productive systems. Recovery of plant biomass following disturbance is also predicted to be faster in productive systems. Here we provide the first test of Huston's hypothesis in the context of setting harvest rates in managed forests for achieving biodiversity objectives. We examined predictions relating to vegetation and bird response to disturbance and succession in productive and less productive forests in western Oregon and Washington, USA. We found that measurements of understory cover and shrub diversity were higher in young, productive stands than less productive stands of similar age. Later-seral forests in productive environments (mean age = 67 years) had less variable and more complete canopy closure than similar-age forests in less favorable settings. At the stand scale, bird abundance and richness decreased with canopy closure in highly productive forests whereas bird abundance and richness increased with canopy closure in less productive forests. At the landscape scale, bird abundance and richness within stands increased with increasing levels of disturbance in the surrounding landscape within highly productive forests, whereas bird abundance and richness decreased with increasing disturbance in the surrounding landscape within less productive forests. Our results indicate that bird response to disturbance varies across levels of productivity and suggest that bird species abundance and associated species richness will be maximized through relatively more frequent disturbance in highly productive systems.!://WOS:000275444100004Times Cited: 0 0921-2973WOS:00027544410000410.1007/s10980-009-9437-66?p Medley, Kimberly2012[I.P. Martini and W. Chesworth (eds.): Landscapes and Societies. Selected Cases, 1st Edition927-928Landscape Ecology276Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9738-z 0921-297310.1007/s10980-012-9738-z c<7DMedley, K. E. Okey, B. W. Barrett, G. W. Lucas, M. F. Renwick, W. H.1995_Landscape change with agricultural intensification in a rural watershed, southwestern Ohio, USA161-176Landscape Ecology103iAGROECOSYSTEM ECOLOGY; CASH GRAIN PRODUCTION; FOREST FRAGMENTATION; LAND USE CHANGE; LAND OWNER ATTITUDESArticleJunSpecialized cash grain production, emergent in the midwestern United States during the post-WWII era, typifies the Upper Four Mile Creek watershed in southwestern Ohio. This style of agriculture intensifies cropland use, with consequent increases in soil erosion and stream sedimentation - a serious problem in the lower reservoir, Acton Lake. Agricultural statistics and aerial photographs compiled between 1934 and 1984 were used to quantify agricultural dynamics and landscape change in the watershed, including land-use apportionment, diversity, and the structural configuration of forest, woodland, and old-field/brushland patches and corridors. A questionnaire sent to all land owners in the basin documented farm-level characteristics and factors that influence management decisions. Crop diversity (H') in Preble County, Ohio decreased from 1.42 in 1934 to 1.17 in 1982, as corn and soybeans dominated the landscape mosaic. Yields rose, but net profits were reduced by declining prices per bushel and increases in fertilizer and petroleum-based subsidies. Landuse diversity in the county also declined (H' = 1.37 in 1934 tot 0.80 in 1982) in response to cropland expansion, whereas forest land in the watershed increased from 1605 to 2603 ha. Fragmentation declined and the landscape became polarized after 1956, with a concentration of agricultural patches in the upper watershed and forest-patch coalescence in stream gullies and state park land in the lower watershed. The questionnaire (similar to 29% return) further supported, at the farm-level, observed regional trends toward expansion (farm coalescence and lease contracts) and specialization (conversion toward corn and soybeans). The most important factors influencing farm size and management were better equipment and family traditions. Thus, cultural and technological factors that operate at the farm-level, coupled with meso-scale variation in the physical conditions of a catchment basin, tend to influence landscape-level patterns more than regional socioeconomics and governmental policies.://A1995RF27500004 IISI Document Delivery No.: RF275 Times Cited: 46 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1995RF27500004CMEDLEY, KE, MIAMI UNIV,DEPT GEOG,217 SHIDELER HALL,OXFORD,OH 45056.English?DH.T.H.M. Meekes1991PThe possible impact of climatic change on the avian community of dune ecosystems99-103Landscape Ecology61/2$Dunes, bird habitats, sea level riseJThe possible effects of climatic change for the avifauna in the dunes, especially in the Netherlands, were analyzed with two different approaches. It is concluded that although there will be an influence on most species, only three or four species may be threatened, whereas two species may even benefit from the possible changes.P<7Meentemeyer, R. K. Moody, A.2000_Rapid sampling of plant species composition for assessing vegetation patterns in rugged terrain697-711Landscape Ecology158Zchaparral landscape scale remote sensing vegetation pattern vegetation sampling CALIFORNIAArticleDecDetailed species composition data are rapidly collected using a high-powered telescope from remote vantage points at two scales: site level and patch level. Patches constitute areas of homogeneous vegetation composition. Multiple samples of species composition are randomly located within the patches. These data are used as site-level data and are also aggregated to provide species composition data at the patch level. The site- and patch-level data are spatially integrated with high resolution (10 m), topographically-derived fields of environmental conditions, such as solar radiation, air temperature, and topographic moisture index in order to evaluate the applicability of the sampling method for modeling relationships between species composition and environmental processes. The methodology provides a balance between sampling efficiency and the accuracy of field data. Application of the method is appropriate for environments where terrain and canopy characteristics permit open visibility of the landscape. We evaluate the nature of data resulting from an implementation of the remote sampling methodology in a steep watershed dominated by closed-canopy chaparral. Analyses indicate that there is minimal bias associated with scaling the data from the site level to the patch level, despite variable patch sizes. Analysis of variance and correlation tests show that the internal floristic and environmental variability of patches is low and stable across the entire sample of patches. Comparison of regression tree models of species cover at the two scales indicates that there is little scale-dependence in the ecological processes that govern patterns of species composition between the site level and patch level. High explanatory power of the regression tree models suggests that the vegetation data are characterized at an appropriate scale to model landscape-level patterns of species composition as driven by topographically-mediated processes. Patch-level sampling reduces the influence of local stochasticity and micro-scale processes. Comparison of models between the two scales can be useful for assessing the processes and associated scales of variability governing spatial patterns of plant species.://000165379700002 ISI Document Delivery No.: 375BM Times Cited: 4 Cited Reference Count: 30 Cited References: AUSTIN MP, 1995, 4 CSIRO DIV WILDL EC AUSTIN MP, 1995, 5 COMM SCI IND RES O BEVEN KJ, 1979, HYDROL SCI B, V24, P43 BIGING GS, 1995, CANADIAN J REMOTE SE, V21, P357 BOLSTAD PV, 1998, LANDSCAPE ECOL, V13, P271 BULLOCK SH, 1978, MADRONO, V25, P104 CHRISTENSEN NL, 1975, ECOL MONOGR, V45, P29 CLARK LA, 1993, STAT MODELS DAVIS FW, 1990, LANDSCAPE ECOL, V4, P69 DAVIS SD, 1998, LANDSCAPE DISTURBANC DIBBLEE TW, 1986, GEOLOGIC MAP SANTA B DUBAYAH R, 1992, WATER RESOUR RES, V28, P2469 FRANKLIN J, IN PRESS TERRAIN ANA FRANKLIN J, 1995, PROG PHYS GEOG, V19, P474 FRANKLIN J, 1998, J VEG SCI GREIGSMITH P, 1983, QUANTITATIVE PLANT E HASTIE TJ, 1993, STAT MODELS KEELEY JE, 1986, RESILIENCE MEDITERRA KEELEY JE, 1991, BOT REV, V57, P81 KEELEY JE, 1998, LANDSCAPE DISTURBANC KENT M, 1992, VEGETATION DESCRIPTI KERSHAW KA, 1975, QUANTITATIVE DYNAMIC MAUSEL PW, 1992, PHOTOGRAMM ENG REM S, V58, P1189 MICHAELSEN J, 1994, J VEG SCI, V5, P673 MILLER PC, 1983, OECOLOGIA, V56, P385 PICKUP G, 1995, INT J REMOTE SENS, V16, P1647 RUNNING SW, 1987, CAN J FOREST RES, V17, P472 STOHLGREN TJ, 1997, LANDSCAPE ECOL, V12, P155 WELLS PV, 1962, ECOL MONOGR, V32, P79 XU X, 1999, EOS T AM GEOPHYS UN, V80, P317 0921-2973 Landsc. Ecol.ISI:000165379700002~Univ N Carolina, Dept Geog, Chapel Hill, NC 27599 USA. Meentemeyer, RK, Univ N Carolina, Dept Geog, Chapel Hill, NC 27599 USA.English?Meentemeyer, V.19893Geographical perspectives of space, time, and scale163-173Landscape Ecology33/4scale, hierarchyڽ7 Meffert, PeterJ Dziock, Frank2013IThe influence of urbanisation on diversity and trait composition of birds943-957Landscape Ecology285Springer NetherlandsYUrbanisation Fourth-corner analysis Biotic homogenisation Urban matrix Community assembly 2013/05/01+http://dx.doi.org/10.1007/s10980-013-9867-z 0921-2973Landscape Ecol10.1007/s10980-013-9867-zEnglish<7Meisel, J. E. Turner, M. G.1998MScale detection in real and artificial landscapes using semivariance analysis347-362Landscape Ecology136scale detection semivariance analysis semivariogram spatial heterogeneity spatial statistics ungulate foraging Yellowstone National Park GEOSTATISTICAL ANALYSIS SOIL PROPERTIES PATTERNS HETEROGENEITY ECOSYSTEM ECOLOGY ENVIRONMENT VARIOGRAMSArticleDec Semivariance analysis is potentially useful to landscape ecologists for detecting scales of variability in spatial data. We used semivariance analysis to compare spatial patterns of winter foraging by large ungulates with those of environmental variables that influence forage availability in northern Yellowstone National Park, Wyoming. In addition, we evaluated (1) the ability of semivariograms to detect known scales of variability in artificial maps with one or more distinct scales of pattern, and (2) the influence of the amount and spatial distribution of absent data on semivariogram results and interpretation. Semivariograms of environmental data sets (aspect, elevation, habitat type, and slope) for the entire northern Yellowstone landscape clearly identified the dominant scale of variability in each map layer, while semivariograms of ungulate foraging data from discontinuous study areas were difficult to interpret. Semivariograms of binary maps composed of a single scale of pattern showed clear interpretable results: the range accurately reflected the size of the blocks of which the maps were constructed. Semivariograms of multiple scale maps and hierarchical maps exhibited pronounced inflections which could be used to distinguish two or three distinct scales of pattern. To assess the sensitivity of semivariance analysis to absent data, often the product of cloud interference or incomplete data collection, we deliberately masked (deleted) portions of continuous northern Yellowstone map layers, using single scale artificial maps as masks. The sensitivity of semivariance analysis to random deletions from the data was related to both the size of the deleted blocks, and the total proportion of the original data set that was removed. Small blocks could be deleted in very high proportions without degrading the semivariogram results. When the size of deleted blocks was large relative to the size of the map, the corresponding variograms became sensitive to the total proportion of data removed: variograms were difficult or impossible to interpret when the proportion of data deleted was high. Despite success with artificial maps, standard semivariance analysis is unlikely to detect multiple scales of pattern in real ecological data. Semivariance analysis is recommended as an effective technique for quantifying some spatial characteristics of ecological data, and may provide insight into the scales of processes that structure landscapes.://000077308100002 [ ISI Document Delivery No.: 144HH Times Cited: 32 Cited Reference Count: 52 Cited References: *US CERL, 1991, GEOGR RES AN SUPP SY ALLEN TFH, 1982, HIERARCHY BALL ST, 1993, CROP SCI, V33, P931 BARMORE WJ, 1980, POPULATION CHARACTER BELL G, 1993, OECOLOGIA, V96, P114 BURROUGH PA, 1986, PRINCIPLES GEOGRAPHI CARLILE DW, 1989, LANDSCAPE ECOLOGY, V2, P203 CRAIGHEAD JJ, 1972, WILDLIFE MONOGRAPHS, V29 CULLINAN VI, 1992, LANDSCAPE ECOL, V7, P211 DANIELSON BJ, 1991, AM NAT, V138, P1105 DAVID M, 1977, GEOSTATISTICAL ORE R DELCOURT HR, 1988, LANDSCAPE ECOL, V2, P23 DESPAIN DG, 1991, YELLOWSTONE VEGETATI DEUTSCH CV, 1992, GSLIB GEOSTATISTICAL GARDNER RH, LANDSCAPE ECOLOGICAL GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GARDNER RH, 1991, QUANTITATIVE METHODS, P289 GARDNER RH, 1998, ECOLOGICAL SCALE THE GREIGSMITH P, 1983, QUANTITATIVE PLANT E HANSEN AJ, 1992, LANDSCAPE ECOL, V7, P163 HOLLING CS, 1992, ECOL MONOGR, V62, P447 HOUSTON DB, 1982, NO YELLOWSTONE ELK E ISAAKS EH, 1989, INTRO APPL GEOSTATIS ISTOK JD, 1993, GROUND WATER, V31, P63 KAREIVA P, 1995, NATURE, V373, P299 KEMENY JG, 1993, TRUEBASIC MACINTOSH KORNER TW, 1989, FOURIER ANAL KOTLIAR NB, 1990, OIKOS, V59, P253 KRUMMEL JR, 1987, OIKOS, V48, P321 LACAZE B, 1994, INT J REMOTE SENS, V15, P2437 LEGENDRE P, 1989, VEGETATIO, V80, P107 LEVIN SA, 1992, ECOLOGY, V73, P1943 MATHERON G, 1963, ECON GEOL, V58, P1246 MCBRATNEY AB, 1986, J SOIL SCI, V37, P617 ONEILL RV, 1986, HIERARCHICAL CONCEPT ONEILL RV, 1991, LANDSCAPE ECOL, V5, P137 PEARSON SM, 1995, ECOL APPL, V5, P744 PEARSON SM, 1996, BIODIVERSITY MANAGED, P77 PLOTNICK RE, 1993, LANDSCAPE ECOL, V8, P201 PLOTNICK RE, 1996, PHYSICAL REV E, V53, P1 ROSSI RE, 1992, ECOL MONOGR, V62, P277 SCHNEIDER DC, 1986, MAR ECOL-PROG SER, V32, P237 SENFT RL, 1987, BIOSCIENCE, V39, P716 SUGIHARA G, 1990, TRENDS ECOL EVOL, V5, P79 SWANSON FJ, 1988, BIOSCIENCE, V38, P92 TOBLER WR, 1970, EC GEOGRAPHY S, V46, P234 TURNER MG, 1997, LANDSCAPE ECOLOGY PR, P331 TURNER SJ, 1991, QUANTITATIVE METHODS, P17 WARD D, 1994, ECOLOGY, V75, P45 WATT AS, 1947, J ECOL, V35, P1 WEBSTER R, 1992, J SOIL SCI, V43, P177 WITH KA, 1997, OIKOS, V79, P219 0921-2973 Landsc. Ecol.ISI:000077308100002{Univ Wisconsin, Dept Zool, Madison, WI 53706 USA. Turner, MG, Univ Wisconsin, Dept Zool, Birge Hall, Madison, WI 53706 USA.English |7AMelles, S. J. Badzinski, D. Fortin, M. J. Csillag, F. Lindsay, K.2009IDisentangling habitat and social drivers of nesting patterns in songbirds519-531Landscape Ecology244+point pattern analysis spatial aggregation wilsonia citrina conspecific attraction pair-correlation function warblers wilsonia-citrina hooded warblers conspecific attraction public information spatial-patterns extrapair paternity semiarid shrubland empidonax-minimus least flycatchers point patternsAprNest locations of breeding birds are often spatially clustered. This tendency to nest together has generally been related to a patchy distribution of nesting habitat in landscape studies, but behavioral studies of species with clustered breeding patterns draw attention to the importance of social and biotic factors. Indeed, it is becoming increasingly apparent that the breeding system of many territorial, migrant birds may be semi-colonial. The reasons for, and extent of, spatial clustering in their breeding systems are not well understood. Our goal was to tease apart the influence of habitat availability and social drivers of clustered breeding in a neotropical migrant species, the hooded warbler (Wilsonia citrina). To test alternative hypotheses related to clustered habitat or conspecific attraction, we combined a habitat classification based on remote sensing with point pattern analysis of nesting sites. Nest locations (n = 150, 1999-2004), collected in a 1213 ha forested area of Southern Ontario (Canada), were analyzed at multiple spatial scales. Ripley's K and pair-correlation functions g (uni- and bivariate) were used to test whether nests were clustered merely because potential nesting habitat was also clustered, or whether nests were additionally clustered with respect to conspecifics. Nest locations tended to be significantly clustered at intermediate distances (particularly between 240 and 420 m). Nests were randomly distributed within available habitat at larger distance scales, up to 1500 m. A reasonable hypothesis to explain the detected additional clustering, and one that is consistent with the results of several behavioral studies, is that females pack their nests more tightly than the available habitat requires to be situated closer to their neighbors' mates. Linking spatially explicit, point pattern analysis with strong inference based on Monte Carlo tests may bring us closer to understanding the generality and reasons behind conspecific attraction at different spatial scales.://000263898100007-414XI Times Cited:0 Cited References Count:54 0921-2973ISI:000263898100007(Melles, SJ Environm Canada, 867 Lakeshore Rd, Burlington, ON L7R 4A6, Canada Univ Toronto, Dept Ecol & Evolutionary Biol, Toronto, ON M5S 3G5, Canada Bird Studies Canada, Port Rowan, ON N0E 1M0, Canada Univ Toronto, Dept Geog, Toronto, ON M5S 3G5, Canada Environm Canada, Hull, PQ K1A 0H3, CanadaDoi 10.1007/S10980-009-9329-9English<7+Mennechez, G. Schtickzelle, N. Baguette, M.2003Metapopulation dynamics of the bog fritillary butterfly: comparison of demographic parameters and dispersal between a continuous and a highly fragmented landscape279-291Landscape Ecology183conservation Capture-Mark-Recapture habitat fragmentation patch size specialist butterfly PROCLOSSIANA-EUNOMIA LEPIDOPTERA HABITAT FRAGMENTATION SPATIAL STRUCTURE POPULATION NYMPHALIDAE CONSERVATION MIGRATION MOVEMENTS CONSEQUENCES EXTINCTIONArticleAprWe investigated the effects of habitat loss and fragmentation on population functioning. We compared demography ( daily and total population sizes) and dispersal ( dispersal rate and dispersal kernels) of the bog fritillary butterfly in two 6-km(2) landscapes differing in their degree of fragmentation. In 2000, we conducted a Capture-Mark-Recapture experiment in a highly fragmented system in the marginal part of the species distribution ( Belgium) and in a more continuous system in the central part of its distribution ( Finland). A total of 293 and 947 butterflies were marked with 286 and 190 recapture events recorded in the fragmented and the continuous system respectively. Our results suggest that habitat loss and fragmentation affect dispersal more than demography. Although density was lower in the continuous system, it remains in the yearly range of variation observed on 10 generations in the fragmented system. However, in the fragmented system, the dispersal rate dropped drastically (39 vs. 64%) and females moved longer distances. Patch area had a significant effect on migration in the fragmented system only. From our results, we propose the definition of a new parameter, the minimal patch area (MPA) needed to establish a local population in highly fragmented landscapes.://000183770600006 nISI Document Delivery No.: 694JD Times Cited: 15 Cited Reference Count: 46 Cited References: ANDREASSEN HP, 1998, J ANIM ECOL, V67, P941 BAGUETTE M, IN PRESS COMPTES REN BAGUETTE M, 1994, ECOL ENTOMOL, V19, P1 BAGUETTE M, 1996, ACTA OECOL, V17, P225 BAGUETTE M, 1996, ACTA OECOL, V17, P225 BAGUETTE M, 2000, J APPL ECOL, V37, P100 BERGMAN KO, 2001, BIOL CONSERV, V102, P183 BOUMA J, 1998, AGR ECOSYST ENVIRON, V67, P103 BURNHAM KP, 1998, MODEL SELECTION INFE DEBINSKI DM, 2000, CONSERV BIOL, V14, P342 DIAS PC, 1996, TRENDS ECOL EVOL, V11, P326 DIFFENDORFER JE, 1995, ECOLOGY, V76, P827 DIFFENDORFER JE, 1995, LANDSCAPE APPROACHES, P175 DOOLEY JL, 1998, ECOLOGY, V79, P969 FAHRIG L, 2001, BIOL CONSERV, V100, P65 GOODWILLIE R, 1980, TOURBIERES EUROPE CO HANSKI I, 1991, BIOL J LINN SOC, V42, P17 HANSKI I, 1991, METAPOPULATION DYNAM HANSKI I, 1995, OIKOS, V72, P21 HANSKI I, 1995, POPULATION DYNAMICS, P149 HANSKI I, 1996, AM NAT, V147, P527 HANSKI I, 1997, METAPOPULATION BIOL HANSKI I, 1999, METAPOPULATION ECOLO HANSKI I, 2001, NATURWISSENSCHAFTEN, V88, P372 HEINO M, 2001, AM NAT, V157, P495 HILL JK, 1996, J ANIM ECOL, V65, P725 LEVINS R, 1969, B ENTOMOL SOC AM, V15, P237 MAES D, 2001, BIOL CONSERV, V99, P263 MCGARIGAL K, 1994, FRAGSTATS SPATIAL PA MIKKOLA K, 1983, NOTA LEPIDOPTEROLOGI, V6, P216 MOUSSON L, 1999, BIOL CONSERV, V87, P285 NEVE G, 1996, J APPL ECOL, V33, P14 OLIVIERI I, 1997, METAPOPULATION BIOL, P293 PETIT S, 2001, OIKOS, V92, P491 PULLIAM HR, 1988, AM NAT, V132, P652 SACCHERI I, 1998, NATURE, V392, P491 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SCHTICKZELLE N, 2002, OIKOS, V97, P349 SOULE ME, 1986, CONSERVATION BIOL SC THOMAS CD, 1992, OECOLOGIA, V92, P563 THOMAS CD, 1997, METAPOPULATION BIOL, P359 THOMAS CD, 1999, J ANIM ECOL, V68, P647 VAISANEN R, 1992, ANN ZOOL FENN, V29, P75 VANDONGEN S, 1994, ACTA OECOL, V15, P193 WILCOX BA, 1985, AM NAT, V125, P879 WOLFF JO, 1997, CONSERV BIOL, V11, P945 0921-2973 Landsc. Ecol.ISI:000183770600006Univ Catholique Louvain, Biodivers Res Ctr, B-1348 Louvain, Belgium. Baguette, M, Univ Catholique Louvain, Biodivers Res Ctr, 4 Pl Croix Sud, B-1348 Louvain, Belgium.English|?Mercuri, Anna Maria2014Genesis and evolution of the cultural landscape in central Mediterranean: the 'where, when and how' through the palynological approach 1799-1810Landscape Ecology2910DecCultural landscapes are priority research themes addressed in many fields of knowledge. Botanists can explore the ecological, formal and cognitive level of cultural landscapes with different approaches. Palynologists study both palaeoenvironmental (off-site) and archaeological (on-site) records and are, therefore, in a privileged corner to observe the origin and history of present landscapes, what is their true nature and vocation, what must be preserved or transformed for the future. The study of an archaeological site shows short space-time events and the behaviour of a few people. In order, though, to attain a regional and cross-area cultural landscape reconstruction, many sites must be studied as part of a regional multi-point site and with an interdisciplinary approach. The likelihood to observe human-induced environments in pollen diagrams depends on the nature and productivity of human-related plant species. In the Mediterranean area, many Palaeolithic, Mesolithic and Neolithic sites point to the long-term action on the environment. However, the pollen signal of pre-Holocene and early Holocene human impact is ambiguous or weak. The effects of culture became evident, and possibly irreversible, as a consequence of human permanence in a certain land. In the Bronze age, the establishment of human-induced environments was evident from the combination of decrease of forest cover and increase of cereal and synanthropic pollen types in pollen records.!://WOS:000346920900013Times Cited: 3 0921-2973WOS:00034692090001310.1007/s10980-014-0093-0?<Gray Merriam Michal Kozakiewicz Etsuko Tsuchiya Karen Hawley1989^Barriers as boundaries for metapopulations and demes of Peromyscus Zeucopus in farm landscapes227-235Landscape Ecology24\extinctions, forest fragments, gene flow, hierarchy, roads, small mammals, landscape ecologyzEffects of potential barriers (roads and cultivated fields) on both demographic and genetic features of subpopulations of white-footed mice were studied near Ottawa, Canada. Live trapping, colored bait and track registry were used to study animal movements across roads on four 1.44 ha areas each within a small forest bisected by a narrow gravel road. The genetic study was done in 11 other forest fragments separated from each other by cultivated fields. Frequencies of three electrophoretic variants of salivary amylases were established for mice caught in each patch of wood and genetic similarity of subpopulations was calculated. Movements of mice across the roads were very infrequent (quantitative barrier), although movements adjacent to roads were frequent and long enough to cross the roads. Salivary amylase data showed that studied subpopulations were genetically very similar although the sample was intentionally biased toward demographic isolation. Results are discussed in terms of possible hierarchical relationships of metapopulations and genetic demes in the context of landscape ecology, management and conservation practice.?Gray Merriam Alain Lanoue1990dCorridor Use by Small Mammals: Field Measurement for Three Experimental Types of Peromyscus leucopus123-131Landscape Ecology42/3fBehavior, Connectivity, Corridor movement, Dispersal, Landscape movement, Telemetry, Landscape ecologyEighteen mice of each of 3 types were radio-tagged and released at 6 standard points in farmland fencerows. Mice were residents (trapped on site) or translocated from distant forest or from distant corn fields. Of total (net) distance moved, most was in fencerows; 77% for residents, 83% for mice translocated from cropland and 92% for mice translocated from forest. Structurally complex fencerows were preferred significantly over intermediate or simple structures by all types of mice. Time spent in movement was not a linear function of distance moved and averaged from 12.5 to 16.5% of total available activity time. Total distance moved in 2 nights averaged 287 to 422 m and area explored averaged 0.67 to 1.15 ha and ranged to 11 .O ha; both exceed literature values for this species in forest. This enlarged scale of landscape use illustrates the potential importance of landscape-specific behaviour. The measurement of rate of corridor use also is discussed.<7Metzger, J. P.2002Landscape dynamics and equilibrium in areas of slash-and-burn agriculture with short and long fallow period (Bragantina region, NE Brazilian Amazon)419-431Landscape Ecology175Brazilian Amazon fallow period landscape dynamics landscape equilibrium secondary forests slash-and-burn agriculture sustainability tropical deforestation LAND-USE SECONDARY FORESTS EASTERN AMAZONIA THEMATIC MAPPER PATTERNS DEFORESTATION DISTURBANCE MANAGEMENT VEGETATION ESTUARYArticleOcthFallow periods used in slash-and-burn agriculture in the Bragantina region, the oldest agricultural frontier in the Brazilian Amazon, are being reduced. The objective of this study was to analyze the effects of a shortened fallow period on the Bragantina landscape dynamics and equilibrium. Dynamics were characterized by landscape structural changes, particularly in the spatial distribution of secondary forests, and by transition matrix. Equilibrium was defined by temporal and spatial parameters, and by the increment of agricultural areas from 1985 to 1996, analyzed with 6 LANDSAT-TM images. I worked with 6 areas of 250 ha each, 3 with short fallow periods (2-4 years) and 3 with long fallow periods (about 10 years). Results showed that short fallow period areas did not present an equilibrium situation. In these areas, developed secondary vegetation tended to disappear and agricultural areas were being expanded at an average rate of 3% per year. Landscape structure changes pointed out that a reduction in fallow period was occurring in already short fallow period areas. Long fallow period areas presented a shifting mosaic steady-state condition, where punctual changes due to agricultural uses were compensated by field abandonment rate. Both agricultural uses and field abandonment rates were lower in long fallow period areas when compared with short ones. Comparisons with indigenous traditional cropping-fallow cycles indicate that sustainable conditions could be maintained with 11 years of fallow for each cropping year, while shorter cycles would break down the system if agricultural improvements are not implemented.://000179388800004  ISI Document Delivery No.: 617YP Times Cited: 3 Cited Reference Count: 54 Cited References: *RADAMBRASIL, 1973, FOLH SA 23 SAO LUIS ATTIWILL PM, 1994, FOREST ECOL MANAG, V63, P247 BECKERMAN S, 1987, COMP FARMING SYSTEMS, P55 BOORMANN FH, 1979, PATTERN PROCESS FORE BRONDIZIO E, 1996, PHOTOGRAMM ENG REM S, V62, P921 BRONDIZIO ES, 1994, HUM ECOL, V22, P249 BROWN LA, 1970, ECON GEOGR, V46, P393 BROWN S, 1990, J TROP ECOL, V6, P1 CONKLIN HC, 1961, CURR ANTHROPOL, V2, P27 DEJONG W, 1997, AGR ECOSYST ENVIRON, V62, P187 DENICH M, 1991, THESIS G AUGUST U GO DINIZ TDA, 1986, 40 EMBRAPA CPATU FEARNSIDE PM, 1986, HUMAN CARRYING CAPAC FEARNSIDE PM, 1996, FOREST ECOL MANAG, V80, P21 FEARNSIDE PM, 1996, FOREST ECOL MANAG, V80, P35 FOX J, 1995, AMBIO, V24, P328 FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 FUJISAKA S, 1996, AGR ECOSYST ENVIRON, V59, P115 HOLSCHER D, 1997, NUTR CYCL AGROECOSYS, V47, P49 HOUGHTON RA, 1991, FOREST ECOL MANAG, V38, P143 KLEINN C, 1993, SAMPLING ASPECTS TRE KOPPEN W, 1936, HDB KLIMATOLOGIE LAWRENCE D, 1998, LANDSCAPE ECOL, V13, P135 LI H, 1993, LANDSCAPE ECOL, V8, P63 LI Y, 1994, P AM SOC PHOTOGRAMME, P350 MAUSEL P, 1993, GEOCARTO INT, V4, P61 METZGER JP, 1996, LANDSCAPE ECOL, V11, P65 METZGER JP, 2001, BIOTA NEOTROPICA MILLER PM, 1998, BIOTROPICA, V30, P538 MORAN EF, 1981, DEV AMAZON MORAN EF, 1994, BIOSCIENCE, V44, P329 MULLER E, 1993, REMOTE SENS ENVIRON, V45, P295 NEPSTAD DC, 1996, FOREST PATCHES TROPI, P133 NORMAN MJT, 1984, ECOLOGY TROPICAL FOO PENTEADO AR, 1967, PROBLEMAS COLONIZACA RIPPLE WJ, 1991, BIOL CONSERV, V57, P73 ROMME WH, 1982, ECOL MONOGR, V52, P199 SANCHEZ PA, 1976, PROPERTIES MANAGEMEN SCATENA FN, 1996, ECOL ECON, V18, P29 SERRAO EAS, 1996, ECOL ECON, V18, P3 SILVA BNR, 1994, LEVANTAMENTO DETALHA SMITH NJH, 1981, SCIENCE, V214, P755 SOKAL RR, 1995, BIOMETRY PRINCIPLES THOMLINSON JR, 1996, BIOTROPICA A, V28, P525 TUCKER JM, 1998, INTERCIENCIA, V23, P64 TURNER MG, 1993, LANDSCAPE ECOL, V8, P213 VALVERDE O, 1967, RODOVIA BELEM BRASIL VASCONCELOS HL, 1999, BIODIVERS CONSERV, V8, P409 VIEIRA ICG, 1996, THESIS U STIRLING SC VIEIRA ICG, 1999, CATIE REUNIOES TECNI, V9, P89 VIELHAUER K, 1998, P 3 SHIFT WORKSH MAN, P49 WALKER R, 1996, ECOL ECON, V18, P67 WALKER RT, 1997, REV EC SOCIOLOGIA RU, V35, P115 ZIPPERER WC, 1993, LANDSCAPE ECOL, V8, P177 0921-2973 Landsc. Ecol.ISI:000179388800004Univ Sao Paulo, Inst Biosci, Dept Ecol, BR-05508900 Sao Paulo, Brazil. Metzger, JP, Univ Sao Paulo, Inst Biosci, Dept Ecol, Rua Matao 321,Travessa 14, BR-05508900 Sao Paulo, Brazil.English ~?Metzger, J. P.2008ELandscape ecology: perspectives based on the 2007 IALE world congress501-504Landscape Ecology235"://WOS:000254964600001 Times Cited: 0WOS:000254964600001(10.1007/s10980-008-9217-8|ISSN 0921-2973 <7Metzger, J. P. Muller, E.1996GCharacterizing the complexity of landscape boundaries by remote sensing65-77Landscape Ecology112boundary; covert; landscape indices; landscape physiognomy; fragmentation; diversity; remote sensing PATTERNS; ECOSYSTEMS; DIVERSITY; ECOTONES; PATCHES; ECOLOGYArticleAprThis paper presents a method for characterizing the complexity of landscape boundaries by remote sensing. This characterization is supported by a new boundary typology, that takes into account points where three or more landcovers converge (i.e., convergency points or coverts). Landscape boundary richness and diversity indices were proposed and calculated over 19 landscapes in South-East Brazil. Results showed that landscape boundaries, especially convergency points, provided an enrichment in landscape pattern analysis. Landcover boundary diversities were significantly related to landcover shape: elongated riparian units had the highest values for boundary diversity and coverts proportion indices. On the other hand, landscape analysis showed that indices of shape, richness, diversity and coverts proportion provided an additional evaluation of landcover spatial distribution within the landscape.://A1996UN74500001 RISI Document Delivery No.: UN745 Times Cited: 18 Cited Reference Count: 34 Cited References: BURROUGH PA, 1981, NATURE, V294, P240 BURROUGH PA, 1986, PRINCIPLES GEOGRAPHI DECAMPS H, 1994, AQUATIC ECOLOGY SCAL, P1 FORMAN RTT, 1981, BIOSCIENCE, V31, P733 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FORTIN MJ, 1994, ECOLOGY, V75, P956 GATES JE, 1978, ECOLOGY, V59, P871 GIOMETTI ALB, 1993, THESIS STATE U SAO P HANSEN A, 1992, SCI COMMITTEE PROBLE HARRIS LD, 1979, OUR NATL LANDSCAPE T, P725 HOLLAND MM, 1988, NEW LOOK ECOTONES EM, P47 HOLLAND MM, 1991, ROLE LANDSCAPE BOUND JOHNSTON CA, 1989, PHOTOGRAMM ENG REM S, V55, P1643 JOHNSTON CA, 1991, LANDSCAPE BOUNDARIES, P107 KRUMMEL JR, 1987, OIKOS, V48, P321 LAGRO J, 1991, PHOTOGRAMM ENG REM S, V57, P285 LI H, 1993, LANDSCAPE ECOL, V8, P63 LI HB, 1993, LANDSCAPE ECOL, V8, P155 LOVEJOY TE, 1986, CONSERVATION BIOL SC, P257 MAIER MH, 1983, THESIS FEDERAL U SAO MEIJERINK AMJ, 1985, ITC J, P283 NAIMAN RJ, 1988, J N AM BENTHOL SOC, V7, P289 NAIMAN RJ, 1990, ECOLOGY MANAGEMENT A OLSEN ER, 1993, PHOTOGRAMM ENG REM S, V59, P1517 PINAY G, 1988, REGUL RIVER, V2, P507 ROMME WH, 1982, ECOL MONOGR, V52, P199 SERRA J, 1982, IMAGE ANAL MATH MORP STRAHLER AN, 1957, T AM GEOPHYSICAL UNI, V38, P913 TABACCHI E, 1995, CAN J BOT, V73, P33 TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 WARNER WS, 1990, ITC J, P24 WIENS JA, 1985, OIKOS, V45, P421 WIENS JA, 1993, OIKOS, V66, P369 ZIPPERER WC, 1993, LANDSCAPE ECOL, V8, P177 0921-2973 Landsc. Ecol.ISI:A1996UN74500001VMetzger, JP, CNRS,CTR ECOL SYST FLUVIAUX,29 RUE JEANNE MARVIG,F-31055 TOULOUSE,FRANCE.English?Ej)F. van der Meulen J.V. Witter S.M. Arens1991sThe use of a GIS in assessing the impacts of sea level rise on nature conservation along the Dutch coast: 1990-2090105-113Landscape Ecology61/2WCoastal dune management, Netherlands, sea level rise, CIS, ecological effect assessment The Dutch coastline is expected to change considerably during the next 100 years. Erosion will prevail, although accretion will occur locally. To establish a new policy for coastal defence management an integrated policy analysis study was performed. Major dune functions (nature conservation, recreation, public drinking water supply, housing and industry) have been inventarized by using a Geographic Information System. This study reports on the part of the analysis which takes nature conservation interests into account. Evaluation of nature interests has been based on the criteria: rarity and diversity of plant species c.q. vegetation types, succession stage, and completeness. This results in a classification of nature into five classes, based on abiotic as well as biotic characteristics of the landscape. Losses of nature interests were studied due to: loss of land because of shoreline retreat, to remodelling of the foredune ridge, and to changes of the dune groundwater level. An evaluation is given of the methods used to assess ecological impacts. Ideas are presented for further research on the prediction of ecological impacts and on coastline management which combines traditional coastal defence with nature conservation.<7'Meyer, C. B. Miller, S. L. Ralph, C. J.2002oMulti-scale landscape and seascape patterns associated with marbled murrelet nesting areas on the US west coast95-115Landscape Ecology172Brachyramphus marmoratus fidelity fragmentation landscape murrelet old-growth scale spatial temporal OLD-GROWTH FORESTS HABITAT ASSOCIATIONS SITE FIDELITY WASHINGTON CALIFORNIA MOVEMENTS OFFSHORE SUCCESS OREGON RANGEArticleHabitat for wide-ranging species should be addressed at multiple scales to fully understand factors that limit populations. The marbled murrelet (Brachyramphus marmoratus), a threatened seabird, forages on the ocean and nests inland in large trees. We developed statistical relationships between murrelet use (occupancy and abundance) and habitat variables quantified across many spatial scales (statewide to local) and two time periods in California and southern Oregon, USA. We also addressed (1) if old-growth forest fragmentation was negatively associated with murrelet use, and (2) if some nesting areas are more important than others due to their proximity to high quality marine habitat. Most landscapes used for nesting were restricted to low elevation areas with frequent fog. Birds were most abundant in unfragmented old-growth forests located within a matrix of mature second-growth forest. Murrelets were less likely to occupy old-growth habitat if it was isolated (> 5 km) from other nesting murrelets. We found a time lag in response to fragmentation, where at least a few years were required before birds abandoned fragmented forests. Compared to landscapes with little to no murrelet use, landscapes with many murrelets were closer to the ocean's bays, river mouths, sandy shores, submarine canyons, and marine waters with consistently high primary productivity. Within local landscapes (less than or equal to 800 ha), inland factors limited bird abundance, but at the broadest landscape scale studied (3200 ha), proximity to marine habitat was most limiting. Management should focus on protecting or creating large, contiguous old-growth forest stands, especially in low-elevation areas near productive marine habitat.://000177049100001 } ISI Document Delivery No.: 577ET Times Cited: 10 Cited Reference Count: 52 Cited References: *CTTF, 1993, REP CAL TIMB TASK FO *SAS I, 1990, SAS STAT US GUID REL AGEE JK, 1993, FIRE ECOLOGY PACIFIC ATZET TR, 1982, R6RANGE1021982 US FO BURKETT EE, 1995, ECOLOGY CONSERVATION, P247 BURNHAM KP, 1998, MODEL SELECTION INFE CHEN JQ, 1993, AGR FOREST METEOROL, V63, P219 CLARK RG, 1999, ECOLOGY, V80, P272 CODY ML, 1973, ECOLOGY, V54, P31 CONGALTON RG, 1993, PHOTOGRAMM ENG REM S, V59, P529 CRESSIE NAC, 1993, STAT SPATIAL DATA DALY C, 1994, J APPL METEOROL, V33, P140 DANIEL TW, 1942, COMP TRANSPIRATION R DILLINGHAM CP, 1995, NW NATURALIST, V76, P33 DIVOKY GJ, 1995, USDA PAC SW, V152, P83 FRANKLIN JG, 1973, PNW8 US FOR SERV FREILICH JE, 2000, CONSERV BIOL, V14, P1479 GANTER B, 1998, AUK, V115, P642 GRENIER JJ, 1995, USDA PAC SW, V152, P191 HAIG SM, 1998, CONSERV BIOL, V12, P749 HAMER TE, 1995, USDA PAC SW, V152, P163 HAMER TE, 1995, USDA PAC SW, V152, P69 HANSEN AJ, 1991, BIOSCIENCE, V41, P382 HOSMER DW, 1989, APPL LOGISTIC REGRES HUNT GL, 1995, USDA PAC SW, V152, P219 JODICE PGR, 2000, CONDOR, V102, P275 LABISKY RF, 1999, J WILDLIFE MANAGE, V63, P872 LEPTICH DJ, 1989, J WILDLIFE MANAGE, V53, P880 MANLEY IA, 1999, PACIFIC SEABIRDS, V26, P40 MARVIN GA, 2001, COPEIA 0216, P108 MARZLUFF JM, 1999, FOREST FRAGMENTATION, P155 MCGARIGAL K, 1995, PNWGTR351 US FOR SER MEYER CB, 1999, MARBLED MURRELET USE MEYER CB, 2002, IN PRESS CONSERVATIO MILLER GS, 1997, RECOVERY PLAN THREAT MILLER SL, 1995, USDA PAC SW, V152, P205 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 NELSON SK, 1995, USDA PAC SW, V152, P57 NELSON SK, 1995, USDA PAC SW, V152, P89 NETER J, 1989, APPL LINEAR REGRESSI PATON PWC, 1994, CONSERV BIOL, V8, P17 PULLIAM HR, 1988, AM NAT, V132, P652 RALPH CJ, 1993, 1 OR STAT U OR COOP RALPH CJ, 1995, USDA PAC SW, V152, P353 RAPHAEL MG, 1995, USDA PAC SW, V152, P177 SCHOENHERR JR, 1991, CAN J ZOOL, V69, P583 SOMERS RH, 1962, AM SOCIOL REV, V27, P799 STRONG CS, 1995, NW NAT, V76, P99 VANHORNE B, 1983, J WILDLIFE MANAGE, V47, P893 VAROUJEAN DH, 1995, ECOLOGY CONSERVATION, P337 WIENS JA, 1986, COMMUNITY ECOLOGY, P145 ZINKE PJ, 1977, TERRESTRIAL VEGETATI, P679 0921-2973 Landsc. Ecol.ISI:000177049100001rUniv Wyoming, Dept Bot, Laramie, WY 82071 USA. Meyer, CB, Univ Wyoming, Dept Bot, POB 3165, Laramie, WY 82071 USA.English^|?C Michel, Matt J. Knouft, Jason H.2014kThe effects of environmental change on the spatial and environmental determinants of community-level traits467-477Landscape Ecology293MarAn advantage of trait-based approaches to ecology is the ability to predict the response of a species assemblage to environmental change through trait-environment relationships. Because species assemblages are also known to be affected by spatial processes, variation in community-level traits may be similarly affected by spatial structure. Furthermore, the importance of spatial structure may vary with changes to the environment. Using a dataset describing a local stream fish assemblage and environmental variables, we examine the relative contribution of environmental and spatial factors in explaining variation in community-level traits across seasons. We also test for any spatial structuring of community-level traits. For most traits, seasonal environmental change did not seem to alter the relative importance of environmental factors. Traits that did not vary consistently with environmental variables across seasons exhibited significant spatial structure. Overall, relationships between traits and environmental variables seemed to operate on a continuum with 'environmental traits' (those that were strongly correlated with environmental variables in response to environmental change) at one end to 'spatial traits' (those that did not correlate with environments, but exhibited spatial structure) at the other. We suggest that the distinction between these types of traits is important, as different modeling approaches would be appropriate in using community-level traits to predict the response of species assemblages to environmental change.!://WOS:000331935500009Times Cited: 1 0921-2973WOS:00033193550000910.1007/s10980-013-9977-7D}?+Michel, N. Burel, F. Legendre, P. Butet, A.2007Role of habitat and landscape in structuring small mammal assemblages in hedgerow networks of contrasted farming landscapes in Brittany, France 1241-1253Landscape Ecology228Oct://000248941900010 0921-2973ISI:000248941900010I?Ladislav Miklos1989WThe general ecological model of the Slovak Socialist Republic -Methodology and contents43-51Landscape Ecology31hCzechoslovakia, CSSR, Slovakia, ecological model, planning, landscape management, stability, disturbance9Development of the general ecological model (EM) of the CSSR has been included in the state program for environmental policy - the Ecoprogramme of the CSSR - at a scale of 1 : 1 000 000 for the entire Czechoslovak territory and at a scale of 1500 000 for the Czech Socialist Republic (CSR) and the Slovak Socialist Republic (SSR). The objective of the first EM stage was to make a survey of spatial differentiation of the major ecological problems of the country. The EM consists of four parts, three analytical and one synthetic. These parts are: a. The ecological state (value) of the current spatial structure of the landscape. b. Ecological stress factors in the landscape. c. Protection of nature and natural resources. From the spatial synthesis of these three groups (from their spatial encounters), the following synthetic group of conditions was obtained: d. Regional ecological problems, a system of ecologically stable areas, environmental stress factors and factors endangering the ecological stability of the landscape, the natural resources and the human environment..|? Millard, A.2008pSemi-natural vegetation and its relationship to designated urban green space at the landscape scale in Leeds, UK 1231-1241Landscape Ecology2310The species composition of semi-natural vegetation in urban areas is influenced by a diversity of factors operating at a variety of spatial scales. This study investigates relationships at the landscape scale between species numbers of semi-natural plant communities and variations in the nature of designated urban green space. Species' records were obtained from a survey of tetrads (2 km x 2 km) across a contiguous central area of built-up landscape and nearby satellite settlements in the metropolitan borough of Leeds, northern England. Plant species were categorised into natives, archaeophytes, neophytes, casuals and conservation-designated species. The type and extent of designated urban green space within a tetrad was determined using GIS. There was more built-up and designated green space area in the central urban area than in the satellite settlements. However, this difference was not reflected statistically significantly in plant category species' numbers. Numbers of native species correlated positively with areas of green space designated for relatively high nature conservation value. Neophytes and casuals correlated positively with semi-natural green space lacking rare native species or high native species richness but designated principally for local community accessibility. The value of such spaces and the importance of their appropriate management, not only for community benefits like individual physical health and mental well-being, but also for overall urban plant biodiversity, is highlighted.!://WOS:000261790600008Times Cited: 0 0921-2973WOS:00026179060000810.1007/s10980-008-9256-1<73Miller, C. Urban, D. L.20005Connectivity of forest fuels and surface fire regimes145-154Landscape Ecology152connectivity correlation length elevation gradient fire spread forest gap model fuel characteristics mixed conifer forest Sierra Nevada surface fire regime SEQUOIA-NATIONAL-PARK MIXED-CONIFER FOREST SIERRA-NEVADA MOUNTAINOUS TERRAIN CALIFORNIA HISTORY MODELSArticleFebThe connectivity of a landscape can influence the dynamics of disturbances such as fire. In fire-adapted ecosystems, fire suppression may increase the connectivity of fuels and could result in qualitatively different fire patterns and behavior. We used a spatially explicit forest simulation model developed for the Sierra Nevada to investigate how the frequency of surface fires influences the connectivity of burnable area within a forest stand, and how this connectivity varies along an elevation gradient. Connectivity of burnable area was a function of fuel loads, fuel moisture, and fuel bed bulk density. Our analysis isolated the effects of fuel moisture and fuel bed bulk density to emphasize the influence of fuel loads on connectivity. Connectivity was inversely related to fire frequency and generally increased with elevation. However, certain conditions of fuel moisture and fuel bed bulk density obscured these relationships. Nonlinear patterns in connectivity across the elevation gradient occurred as a result of gradients in fuel loads and fuel bed bulk density that are simulated by the model. Changes in connectivity with elevation could affect how readily fires can spread from low elevation sites to higher elevations.://000084522700006 VISI Document Delivery No.: 270EP Times Cited: 22 Cited Reference Count: 44 Cited References: ALBINI FA, 1976, INT30 USDA FOR SERV ANDERSON AJ, 1991, PHYSIOL MOL PLANT P, V38, P1 ANDERSON RS, 1990, J ECOL, V78, P470 ANDREWS PL, 1986, INT194 USDA FOR SERV BROWN JK, 1985, INT337 USDA FOR SERV CAPRIO AC, 1995, P S FIR WILD PARK MA, P173 COHEN JD, 1985, PSW82 USDA FOR SERV DALY C, 1994, J APPL METEOROL, V33, P140 DAVIS FW, 1994, ROLE FIRE MEDITERRAN, P117 DAVIS OK, 1985, QUATERNARY RES, V24, P322 DEEMING JE, 1972, RM84 USDA FOR SERV GARDNER RH, IN PRESS LANDSCAPE E GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GARDNER RH, 1990, QUANTITATIVE METHODS, P289 GREEN DG, 1983, ECOL MODEL, V20, P21 KEIFER M, 1991, THESIS U ARIZONA TUC KILGORE BM, 1979, ECOLOGY, V60, P129 MCKELVEY KS, 1996, SIERRA NEVADA ECOSYS, V2, P1033 MILLER C, 1999, CAN J FOREST RES, V29, P202 MILLER C, 1999, ECOL MODEL, V114, P113 MUTCH LS, 1998, FOREST SCI, V44, P341 NIKOLOV NT, 1992, ECOL MODEL, V61, P149 PARSONS DJ, 1978, J FOREST, V76, P104 PARSONS DJ, 1979, FOREST ECOL MANAG, V2, P21 PITCHER DC, 1987, CAN J FOREST RES, V17, P582 RIND D, 1989, CLIMATIC CHANGE, V14, P5 ROTHERMEL RC, 1972, INT115 USDA FOR SERV RUNNING SW, 1987, CAN J FOREST RES, V17, P472 RYAN KC, 1988, CAN J FOREST RES, V18, P1291 SKINNER CN, 1996, SIERRA NEVADA ECOSYS, V2, P1041 STAUFFER D, 1985, INTRO PERCOLATION TH STEPHENS SL, 1995, THESIS U CALIFORNIA STEPHENSON NL, 1988, THESIS CORNELL U ITH SWETNAM TW, 1993, SCIENCE, V262, P885 TURNER MG, 1989, OIKOS, V55, P121 TURNER MG, 1990, QUANTITATIVE METHODS, P323 TURNER MG, 1994, J VEG SCI, V5, P731 TURNER MG, 1994, LANDSCAPE ECOL, V9, P59 URBAN DL, 1991, FOREST ECOL MANAG, V42, P95 VANKAT JL, 1978, J BIOGEOGR, V5, P377 VANWAGNER CE, 1973, CAN J FOREST RES, V3, P373 VANWAGTENDONK JW, 1996, INT J WILDLAND FIRE, V6, P117 VNWAGTENDONK JW, 1998, W J APPL FORESTRY, V13, P73 WARNER TE, 1980, P FIR HIST WORKSH, P89 0921-2973 Landsc. Ecol.ISI:000084522700006Colorado State Univ, Grad Degree Program Ecol, Ft Collins, CO USA. Miller, C, USDA, US Forest Serv, Aldo Leopold Wilderness Res Inst, Missoula, MT 59807 USA.EnglishI۽7 Miller, Jim2013jM. J. McDonnell, A. K. Hahs, and J. H. Breuste (Eds.): Ecology of cities and towns: a comparative approach161-162Landscape Ecology281Springer Netherlands 2013/01/01+http://dx.doi.org/10.1007/s10980-012-9813-5 0921-2973Landscape Ecol10.1007/s10980-012-9813-5English c<7U-Miller, J. N. Brooks, R. P. Croonquist, M. J.19973Effects of landscape patterns on biotic communities137-153Landscape Ecology123Wlandscape disturbance; diversity; contagion; anthropogenic effects NEW-JERSEY; RIPARIANArticleJunA comparative evaluation was performed using descriptors of landscape and land cover patterns as to how they relate to varying levels of anthropogenic disturbance and the structure of biotic communities. A spatial analysis program (a modified version of SPAN) was used to compute measures of land cover diversity, dominance, contagion, scaled dominance and contagion, fractal dimension of land cover patches, mean forest-wetland patch size, amount of forest edge, clustering of selected forest types, and the largest cover patches within two 100-km(2) watersheds of the Ridge and Valley province of central Pennsylvania. Landscape pattern analysis was conducted on a subwatershed basis, emphasizing different levels of residential-agricultural versus forest land cover, the major difference between the two watersheds. Bird and vascular plant guilds were chosen to represent the overall biotic community. The general descriptors of diversity, contagion, mean forest-wetland patch size, proportion of forest cover, and the amount of forest edge were most effective in reflecting the disturbance levels within the watersheds and changes in guild composition for both birds and plants.://A1997XV63400003 ISI Document Delivery No.: XV634 Times Cited: 49 Cited Reference Count: 20 Cited References: ANDERSON JR, 1976, 964 US DEP INT BAZZAZ FA, 1983, DISTURBANCE ECOSYSTE BROOKS RP, 1990, ANAL WETLANDRIPARIAN BROOKS RP, 1990, J PENNSYLVANIA ACAD, V64, P93 BROOKS RP, 1991, BIOL CRITERIA RES RE, P81 BROOKS RP, 1991, P INT S WETL RIV COR, P387 CROONQUIST MJ, 1990, THESIS PENNSYLVANIA CROONQUIST MJ, 1991, ENVIRON MANAGE, V15, P701 CROONQUIST MJ, 1993, J SOIL WATER CONSERV, V48, P65 FORMAN RTT, 1976, OECOLOGIA BERL, V26, P1 GALLI AE, 1976, AUK, V93, P356 KENDALL MG, 1938, BIOMETRIKA 1/2, V30, P81 KRUMMEL JR, 1987, OIKOS, V48, P321 LAUDENSLAYER WF, 1986, WILDLIFE 2000 MODELI, P331 MILLER JN, 1991, THESIS PENSYLVANIA S NAVEH Z, 1984, LANDSCAPE ECOLOGY TH ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 ROBBINS CS, 1980, NC51 USDA, P198 TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 YAHNER RH, 1988, CONSERV BIOL, V2, P333 0921-2973 Landsc. Ecol.ISI:A1997XV63400003dMiller, JN, PENN STATE UNIV,INTERCOLL GRAD PROGRAM ECOL,FOREST RESOURCES LAB,UNIVERSITY PK,PA 16802.Englishg<74Miller, J. R. Joyce, L. A. Knight, R. L. King, R. M.1996DForest roads and landscape structure in the southern Rocky Mountains115-127Landscape Ecology112roads; Colorado; fragmentation; conservation; landscape structure SMALL MAMMALS; SPATIAL PATTERN; OLD-GROWTH; USA; POPULATIONS; DYNAMICS; ECOLOGY; RAINArticleAprRoadless areas on public lands may serve as environmental baselines against which human-caused impacts on landscape structure can be measured. We examined landscape structure across a gradient of road densities, from no roads to heavily roaded, and across several spatial scales. Our study area was comprised of 46,000 ha on the Roosevelt National Forest in north-central Colorado. When forest stands were delineated on the basis of seral stage and covertype, no relationship was evident between average stand size and road density. Topography appeared to exert a greater influence on average stand size than did road density. There was a significant cant positive con-elation between the fractal dimension of forest stands and road density across all scales. Early-seral stands existed in greater proportions adjacent to roads, suggesting that the effects of roads on landscape structure are somewhat localized. We also looked at changes in landscape structure when stand boundaries were delineated by roads in addition to covertype and seral stage: Overall, there was a large increase in small stands with simple shapes, concurrent with a decline in the number of stands > 100 ha. We conclude that attempts to quantify the departure from naturalness in roaded areas requires an understanding of the factors controlling the structure of unroaded landscapes, particularly where the influence of topography is great. Because roads in forested landscapes influence a variety of biotic and abiotic processes, we suggest that roads should be considered as an inherent component of landscape structure. Furthermore, plans involving both the routing of new roads and the closure of existing ones should be designed so as to optimize the structure of landscape mosaics, given a set of conservation goals.://A1996UN74500004 T ISI Document Delivery No.: UN745 Times Cited: 19 Cited Reference Count: 57 Cited References: *ESRI, 1991, ARC INF US GUID *US FOR SERV, 1979, ROADL AR REV EV RARE ADAMS LW, 1983, J APPL ECOL, V20, P403 ALES RF, 1992, LANDSCAPE ECOL, V7, P3 BAKER WL, 1992, ECOLOGY, V73, P1879 BAKER WL, 1993, OIKOS, V66, P66 BAKOWSKI C, 1988, ACTA THERIOL, V33, P345 BENNETT AF, 1991, NATURE CONSERVATION, V2, P99 BIDER JR, 1968, ECOL MONOGR, V38, P269 BURNETT SE, 1992, WILDLIFE RES, V19, P95 BUTTERY R, 1987, MANAGING FORESTED LA, P43 CHEN JQ, 1992, ECOL APPL, V2, P387 COVINGTON WW, 1992, OLD GROWTH FORESTS S, P81 DANIEL WW, 1990, APPLIED NONPARAMETRI ERICKSON K, 1985, ATLAS COLORADO FERRIS CR, 1979, J WILDLIFE MANAGE, V43, P421 FORMAN R, 1986, LANDSCAPE ECOLOGY FOSTER DR, 1992, J ECOL, V80, P753 FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 FRANKLIN JF, 1993, ECOL APPL, V3, P202 HARRIS L, 1984, FRAGMENTED FOREST KNIGHT DH, 1987, LANDSCAPE HETEROGENE, P59 KRUMMEL JR, 1987, OIKOS, V48, P321 LAGRO JA, 1992, LANDSCAPE ECOL, V7, P275 LOVEJOY S, 1982, SCIENCE, V216, P185 LUQUE SS, 1994, LANDSCAPE ECOL, V9, P287 MANDELBROT BB, 1977, FRACTALS FORM CHANCE MARR JW, 1961, U COLORADO STUDIES S, V8 MCLELLAN BN, 1988, J APPL ECOL, V25, P451 MIELKE PW, 1984, HDB STATISTICS, V4, P813 MIELKE PW, 1991, EARTH-SCI REV, V31, P55 MILLER JR, 1995, BIOL CONSERV, V72, P371 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 MORGANTINI L, 1980, N AM ELK ECOLOGY BEH, P132 MUTEL C, 1984, GRASSLAND GLACIER NORSE E, 1986, CONSERVING BIOL DIVE NOSS RF, 1992, WILD EARTH, P10 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 OXLEY DJ, 1974, J APPL ECOL, V11, P51 PACE F, 1991, LANDSCAPE LINKAGES B, P105 PASTOR J, 1990, LANDSCAPE ECOL, V4, P55 PATTON DR, 1975, WILDLIFE SOC B, V3, P171 RANNEY JW, 1981, FOREST ISLAND DYNAMI, P67 RIPPLE WJ, 1991, BIOL CONSERV, V57, P73 ROMME WH, 1981, ECOLOGY, V62, P319 SCHONEWALDCOX C, 1992, CONSERVATION BIOL TH, P373 SLAUSEN WL, 1991, USER MANUAL BLOSSOM SMALL M, 1988, OECOLOGIA, V72, P62 SPIES TA, 1994, ECOL APPL, V4, P555 SWANSON FJ, 1988, BIOSCIENCE, V38, P92 THIEL RP, 1985, AM MIDL NAT, V113, P404 TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 WHITTAKER RH, 1960, ECOL MONOGR, V30, P279 WIENS JA, 1989, FUNCT ECOL, V3, P385 WILLIAMS B, 1991, T N AM WILDL NAT RES, V56, P613 ZIPPERER WC, 1993, LANDSCAPE ECOL, V8, P177 0921-2973 Landsc. Ecol.ISI:A1996UN74500004GCOLORADO STATE UNIV,DEPT WILDLIFE & FISHERIES BIOL,FT COLLINS,CO 80523.Englisha?.Ronald I. Miller Simon N. Stuart Kim M. Howell1989sA methodology for analyzing rare species distribution patterns utilizing GIS technology: The rare birds of Tanzania173-189Landscape Ecology23Slandscape ecology, conservation, avifauna, Tanzania, Africa, CIS, species diversity)A simple, straightforward, cartographic modelling technique is presented for measuring relations between environmental characteristics and rare species distribution patterns. This approach is corroborated by digitizing rare bird distribution data for Tanzania and statistically analyzing these patterns in relation to geographic and environmental variables. Of the available natural resource data for Africa, only the vegetation and soils data appeared accurate enough to represent regional natural resource distribution patterns. Available data for Tanzania at the regional scale is not currently precise or comprehensive enough to analyze ongoing dynamic ecological processes. Statistical relations, associated with a study quadrangle within Tanzania, are documented for these parameters. Final confirmation of the accuracy of predictions about rare species diversity patterns will ensue from future field observations. When confirmed, this methodology can be used for setting conservation priorities in biologically little known regions of the world.<7Millward, A. A. Kraft, C. E.2004|Physical influences of landscape on a large-extent ecological disturbance: the northeastern North American ice storm of 199899-111Landscape Ecology191Adirondacks; forest damage; ice storm; landsat; large-extent ecological disturbance; spatial pattern; topography; variogram analysis LANDSAT TM DATA; NEW-YORK; HARDWOOD FOREST; NEW-ENGLAND; VEGETATION INDEXES; IMPACTS; DAMAGE; MOUNTAIN; PATTERNS; RECOVERYArticleThe 1998 ice storm was a large-extent ecological disturbance that severely affected the eastern Adirondack forests of northern New York. Ice damage produced widespread breakage of limbs and trunks in susceptible trees. Although ice storms are common within northeastern North American forests, the magnitude and extent of the 1998 storm far exceeded damage caused by typical ice storms in the recent past. While plot and stand-scale ecological impacts of ice storms have received attention insofar as tree species vulnerability, stand age susceptibility, and microhabitat alterations, larger-extent damage patterns have not been previously evaluated. The normalized difference vegetation index (NDVI) was employed to assess forest vigor and canopy density in atmospherically corrected Landsat Thematic Mapper (TM) satellite imagery of the Adirondacks. Digital change analysis of the baseline forest condition (1990 NDVI data), and the condition encountered in a post-storm image (1998 NDVI data) was conducted. Forest damage was separated from natural variations in canopy reflectance by employing a generalized linear model that incorporated in situ measurements. A robust empirical variogram analysis revealed that locations of tree damage were significantly correlated for distances up to 300 meters. Intensely-damaged forest exhibited greater spatial dependence, but over a smaller distance. Canopy damage was not greater proximate to stream and forest boundaries, and did not follow our hypothesis of decreasing damage with distance from the boundary. Overall, we show that local topography (elevation and aspect), forest composition (deciduous or coniferous), and the meteorological characteristics of the disturbance event acted together to determine the spatial extent of ice storm damage.://000189394100007 ISI Document Delivery No.: 780RA Times Cited: 6 Cited Reference Count: 51 Cited References: *US EPA, 1993, N AM LANDSC CHAR NAL BAKER WL, 1993, OIKOS, V66, P66 BOOSE ER, 2001, ECOL MONOGR, V71, P27 BURNETT JS, 2002, ASSESSING DIFFERING CAMPBELL JB, 1996, INTRO REMOTE SENSING CARVELL KL, 1957, J FOREST, V55, P130 CHAVEZ PS, 1989, PHOTOGRAMM ENG REM S, V55, P1285 CHAVEZ PS, 1996, PHOTOGRAMM ENG REM S, V62, P1025 CRESSIE N, 1980, J INT ASS MATH GEOL, V12, P115 DALE VH, 2001, BIOSCIENCE, V51, P723 DEGAETANO AT, 1999, AMS 11 C APPL CLIM D, P390 DEGAETANO AT, 2000, B AM METEOROL SOC, V81, P237 DUGUAY SM, 2001, ENVIRON MONIT ASSESS, V67, P97 DUPIGNYGIROUX LA, 2003, INT J REMOTE SENS, V24, P2105 EKSTRAND S, 1994, REMOTE SENS ENVIRON, V47, P291 FORMAN RTT, 1987, LANDSCAPE HETEROGENE, P261 FOSTER DR, 1992, J ECOL, V80, P79 FOSTER DR, 1998, ECOSYSTEMS, V1, P497 HOOPER MC, 2001, CAN J BOT, V79, P70 IRLAND LC, 1998, J FOREST, V96, P32 IRLAND LC, 2000, SCI TOTAL ENVIRON, V262, P231 JENSEN JR, 1996, INTRO DIGITAL IMAGE JONES J, 2001, ECOLOGY, V82, P2628 JONES J, 2001, ECOSCIENCE, V8, P513 KALUZNY SP, 1998, S SPATIAL STATS KAUFMAN YJ, 1992, IEEE T GEOSCI REMOTE, V30, P261 KRAFT CE, 2002, CAN J FISH AQUAT SCI, V59, P1677 LILLESAND TM, 2000, REMOTE SENSING IMAGE MAC MJ, 1998, STATUS TRENDS NATION MANION PD, 2001, FOREST CHRON, V77, P619 MANION PD, 2001, FOREST SCI, V47, P542 MATHERON G, 1963, ECON GEOL, V58, P1246 MCDONALD AJ, 1998, REMOTE SENS ENVIRON, V66, P250 MONMONIER M, 1982, COMPUTER ASSISTED CA MOU P, 2000, J TORREY BOT SOC, V127, P66 NAVEH Z, 1995, LANDSCAPE URBAN PLAN, V32, P43 OTT L, 2001, INTRO STAT METHODS D PETERSON GD, 2002, ECOSYSTEMS, V5, P329 RHOADS AG, 2002, CAN J FOREST RES, V32, P1763 ROLLINS MG, 2002, LANDSCAPE ECOL, V17, P539 RUBIN BD, 2001, FOREST CHRON, V77, P613 SEISCHAB FK, 1993, B TORREY BOT CLUB, V120, P64 SONG C, 2001, REMOTE SENS ENVIRON, V75, P230 SWANSON FJ, 1998, BIOSCIENCE, V48, P681 SWETNAM TW, 1999, ECOL APPL, V9, P1189 TEILLET PM, 1997, REMOTE SENS ENVIRON, V61, P139 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1998, ECOSYSTEMS, V1, P493 VIEDMA O, 1997, REMOTE SENS ENVIRON, V61, P383 VOGELMANN JE, 2001, PHOTOGRAMM ENG REM S, V67, P650 WEATHERS KC, 2000, ECOL APPL, V10, P528 0921-2973 Landsc. Ecol.ISI:000189394100007Univ Waterloo, Dept Geog, Waterloo, ON N2L 3G1, Canada. Cornell Univ, Dept Nat Resources, Ithaca, NY 14853 USA. Millward, AA, Univ Waterloo, Dept Geog, Waterloo, ON N2L 3G1, Canada. aamillwa@fes.uwaterloo.caEnglishc?8+Milne, B.T. K.M. Johnston R.T.T. Forman1989SScale-dependent Proximity of Wildlife Habitat in a Spatially-neutral Bayesian Model101-110Landscape Ecology22alandscape ecology, white-tailed deer, New Brunswick Canada, scaling, habitat, distribution, modelOrganisms may be constrained by the energetic costs incurred while obtaining resources in fragmented landscapes. We used a spatially neutral model of deer wintering habitat to evaluate the effects of landscape fragmentation on the aggregation of deer habitat. The spatially neutral model used Bayesian probabilities to predict where deer wintering areas occurred. The probabilities were conditional on 12 landscape variables measured at 22,750 contiguous 0.4 ha locations. The model predicted deer habitat at each location independently, thereby enabling a comparison of habitat aggregation in observed, simulated, and random distributions of deer habitat. The predictions of the neutral model exhibited greater fragmentation than observed in nature, suggesting that suitable, yet isolated, locations were not visited by deer. The most suitable sites for deer were clumped in the neutral model, regardless of scale. The inclusion of less suitable sites preserved significant aggregation at fine scales but not at broad scales. Species operate at different scales within a landscape, so ecologists, nature reserve designers and natural resource planners may benefit from models that focus on the proximity of habitat sites as a function of both spatial scale and habitat quality.m.s..|? )Milne, E. Aspinall, R. J. Veldkamp, T. A.2009QIntegrated modelling of natural and social systems in land change science PREFACE 1145-1147Landscape Ecology249!://WOS:000270739000001Times Cited: 0 0921-2973WOS:00027073900000110.1007/s10980-009-9392-2T? Robert J. Milne Lorne P. Bennett2007oBiodiversity and ecological value of conservation lands in agricultural landscapes of southern Ontario, Canada 657-670Landscape Ecology225Ecological value - Integrated assessment - Multifunctional - Biodiversity - Anuran - Avian - Connectivity - Rarity - Sub-watershed - Patch size In eastern North America, large forest patches have been the primary target of biodiversity conservation. This conservation strategy ignores land units that combine to form the complex emergent rural landscapes typical of this region. In addition, many studies have focussed on one wildlife group at a single spatial scale. In this paper, studies of avian and anuran populations at regional and landscape scales have been integrated to assess the ecological value of agricultural mosaics in southern Ontario on the basis of the maintenance of faunal biodiversity. Field surveys of avian and anuran populations were conducted between 2001 and 2004 at the watershed and sub-watershed levels. The ecological values of land units were based on a combination of several components including species richness, species of conservation concern (rarity), abundance, and landscape parameters (patch size and connectivity). It was determined that habitats such as thicket swamps, coniferous plantations and cultural savannas can play an important role in the overall biodiversity and ecological value of the agricultural landscape. Thicket swamps at the edge of agricultural fields or roads provided excellent breeding habitat for anurans. Coniferous plantations and cultural savannas attracted many birds of conservation concern. In many cases, the land units that provided high ecological value for birds did not score well for frogs. Higher scores for avian and anuran populations were recorded along the Niagara Escarpment and other protected areas as expected. However, some private land areas scored high, some spatially connected to the protected areas and therefore providing an opportunity for private land owners to enter into a management arrangement with the local agencies. ڽ7 zMitsch, WilliamJ Bernal, Blanca Nahlik, AmandaM Mander, Ülo Zhang, Li Anderson, ChristopherJ Jørgensen, SvenE Brix, Hans2013$Wetlands, carbon, and climate change583-597Landscape Ecology284Springer NetherlandsdCarbon dioxide Carbon sequestration Marsh Methane Methanogenesis Peatland Swamp Global carbon budget 2013/04/01+http://dx.doi.org/10.1007/s10980-012-9758-8 0921-2973Landscape Ecol10.1007/s10980-012-9758-8English?2William J. Mitsch1991bEstimating primary productivity of forested wetland communities in different hydrologic landscapes75-92Landscape Ecology52Qwetland, bottomland forest, Kentucky, primary productivity, Ohio River, hydrologyFive forested wetland sites in western Kentucky with hydrologic regimes varying from seasonally to continuously flooded were investigated for net above-ground biomass productivity (litter fall plus biomass growth) and for possible indicators of that productivity, including abiotic (flooding frequency and depth, phosphorus concentrations in water and sediments) and biotic (biomass, tree density, basal area, structural complexity, and mean height) indices. Net biomass productivity ranged from 205 g m-2y-1 for a stagnant semipermanently flooded Taxodium swamp to 1,334 g rnP2y-l in a bottomland forest along the Ohio River. Productivity was highest in wetlands with pulsing hydroperiods, intermediate with slowly flowing systems, and lowest with stagnant conditions. Surface water flooding of the wetlands during the growing season ranged from 17 to 100 percent of the year and did not predict productivity. Phosphorus concentrations in water and in sediments were not correlated to one another and did not, by themselves, predict productivity. No single abiotic variable predicted the exact ranking of productivity of the sites. Of the biotic variables, average tree diameter was inversely related to productivity.<7.Mladenoff, D. J.2000UntitledIII-IIILandscape Ecology152Editorial MaterialFeb://000084522700001 HISI Document Delivery No.: 270EP Times Cited: 0 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:000084522700001English<7?*Mladenoff, D. J. Niemi, G. J. White, M. A.1997Effects of changing landscape pattern and USGS land cover data variability on ecoregion discrimination across a forest-agriculture gradient379-396Landscape Ecology126ecoregions; land cover data; LUDA; principal components analysis; Landsat TM; forest ecosystems; scale; resolution; grain; biodiversity; ecotone; habitat; monitoring SPATIAL PATTERN; UNITED-STATES; ECOLOGY; COMMUNITIES; HABITATArticleDecWe examined the use of coarse resolution land cover data (USGS LUDA) to accurately discriminate ecoregions and landscape-scale features important to biodiversity monitoring and management. We used land cover composition and landscape indices, correlation and principal components analysis, and comparison with finer-grained Landsat TM data, to assess how well LUDA data discriminate changing patterns across an agriculture-forest gradient in Minnesota, U.S.A. We found LUDA data to be most accurate at general class levels of agriculture and forest dominance (Anderson Level I), but inconsistent and limited in ecotonal areas of the gradient and within forested portions of the study region at finer classes (Anderson Level II). We expected LUDA to over-represent major (matrix) cover types and under-represent minor types, but this was not consistent with all classes. 1) Land cover types respond individualistically across the gradient, changing landscape grain as well as their spatial distribution and abundance. 2) Agriculture is not over-represented where it is the dominant land cover type, but forest is over-represented where it is dominant. 3) Individual forest types are under-represented in an open land matrix. 4) Within forested areas, mixed deciduous-coniferous forest is over-represented by several orders of magnitude and the separate conifer and hardwood types under-represented. Across gradual, transitional agriculture-forest areas, LUDA cover class dominance changes abruptly in a stair-step fashion. In general, rare cover types that are discrete, such as forest in agriculture or wetlands or water in forest, are more accurately represented than cover classes having lower contrast with the matrix. Northward across the gradient, important changes in the proportions of conifer and deciduous forest mixtures occur at scales not discriminated by LUDA data. Results suggest that finer-grained data are needed to map within-state ecoregions and discriminate important landscape characteristics. LUDA data, or similar coarse resolution data sources, should be used with caution and the biases fully understood before being applied in regional landscape management.://000077684400003 k ISI Document Delivery No.: 150UR Times Cited: 8 Cited Reference Count: 50 Cited References: *ESRI INC, 1990, ARC INFO US MAN ALBERT DA, 1995, NC178 USDA FOR SERV ANDERSON JR, 1976, 964 US GEOL SURV ASKINS RA, 1987, BIOL CONSERV, V39, P129 BAILEY RG, 1994, ECOREGIONS SUBREGION BAUER ME, 1994, PHOTOGRAMM ENG REM S, V60, P287 BRITTINGHAM MC, 1983, BIOSCIENCE, V33, P31 FEGEAS RG, 1983, 895E US GEOL SURV FLATHER CH, 1992, LANDSCAPE ECOL, V7, P137 FLATHER CH, 1994, RM241 USDA FOR SERV FORMAN RTT, 1986, LANDSCAPE ECOLOGY FRANKLIN JF, 1993, DEFINING SUSTAINABLE, P127 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GREEN JC, 1980, BIRDS SUPERIOR NATL GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 HANSEN AJ, 1992, LANDSCAPE ECOL, V7, P163 HARRIS LD, 1984, FRAGMENTED FOREST IS HAWROT RY, IN PRESS AUK HEINSELMAN ML, 1973, QUATERNARY RES, V3, P329 HESS G, 1994, LANDSCAPE ECOL, V9, P3 HUNSAKER CT, 1994, LANDSCAPE ECOL, V9, P207 IVERSON LR, 1989, ILLINOIS NATURAL HIS, V11 IVERSON LR, 1994, LANDSCAPE ECOL, V9, P159 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 KRUMMEL JR, 1987, OIKOS, V48, P321 LEBART L, 1984, MULTIVARIATE DESCRIP LOVELAND TR, 1991, PHOTOGRAMM ENG REM S, V57, P1453 LUDWIG JA, 1988, STAT ECOLOGY MANDELBROT BB, 1977, FRACTAL GEOMETRY NAT MLADENOFF DJ, 1993, DEFINING SUSTAINABLE, P145 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 MLADENOFF DJ, 1994, REMOTE SENSING GIS E, P219 MLADENOFF DJ, 1995, CONSERV BIOL, V9, P279 MOODY A, 1994, PHOTOGRAMM ENG REM S, V60, P585 NIEMI JR, UNPUB FOREST FRAGMEN ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PASTOR J, 1992, SYSTEMS ANAL GLOBAL, P216 RIPPLE WJ, 1994, PHOTOGRAMM ENG REM S, V60, P533 SENFT RL, 1987, BIOSCIENCE, V37, P789 SHANNON CE, 1962, MATH THEORY COMMUNIC TURNER MG, 1987, LANDSCAPE HETEROGENE TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P245 TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 WICKHAM JD, 1995, INT J REMOTE SENS, V16, P3585 WICKHAM JD, 1996, IN PRESS PHOTOGRAMME, V62 WOLTER PT, 1995, P 10 ANN LANDSC EC S, P183 WOLTER PT, 1995, PHOTOGRAMM ENG REM S, V61, P1129 ZHU ZI, 1994, PHOTOGRAMM ENG REM S, V60, P525 0921-2973 Landsc. Ecol.ISI:000077684400003zUniv Wisconsin, Dept Forestry, Madison, WI 53706 USA. Mladenoff, DJ, Univ Wisconsin, Dept Forestry, Madison, WI 53706 USA.English?&Moloney, K.A. A. Morin S.A. Levin1991NInterpreting ecological patterns generated through simple stochastic processes163-174Landscape Ecology53The analysis of spatial patterns is fundamental to understanding ecological processes across geographic scales. Through an analysis of two simple, one-dimensional stochastic models, we develop a framework for identifying the scale of processes producing pattern. We show that for some simple model systems spectral analysis identifies exactly the scale of pattern formation. In other, more complicated systems, autocorrelation analysis appears to yield greater insight into the scale of the dynamics producing pattern; in these, the relative importance of processes at different scales can be determined directly from the change in slope of the autocorrelation function. In general, it is not possible to state which technique will be most useful in the analysis of pattern. Spectral analysis and autocorrelation analysis represent duals that can be extended and applied to more complex systems, potentially yielding insight into the nature of a wide variety of spatially determined ecological processes.<7xTMonjeau, J. A. Birney, E. C. Ghermandi, L. Sikes, R. S. Margutti, L. Phillips, C. J.1998RPlants, small mammals, and the hierarchical landscape classifications of Patagonia285-306Landscape Ecology135ghierarchical landscape classifications Patagonia small mammals plants floristic composition communitiesArticleOctKAssemblages of plants were studied at 14 sites in northern Patagonia corresponding to localities at which we (Monjeau et al. 1997) earlier studied the relationship between small mammal assemblages and landscape classifications. This allowed us to test predictions that both plants and small mammals correspond to the more inclusive hierarchical landscape divisions but that plants track better than small mammals the less inclusive divisions. Species presence or absence of plants at each locality was used in a series of multivariate analyses and compared by correlation analysis with those generated from small mammal species data. Assemblages of both plants and small mammals corresponded to the upper divisions, which are based on climatic and geomorphological features, but small mammal assemblages did not correspond to the lower divisions of the landscape classifications. Three factors are considered as explanations for the observed differences between plants and small mammals: a) small mammal habitat is determined more by plant growth form than by plant species; b) trophic level differences between the two groups; and c) species pool size affects the resolution of microhabitat correspondence. Our data indicate that both plant assemblages and small mammal assemblages respond to climatic and geomorphological features, which is in contrast to the paradigm that mammal assemblages simply follow plant assemblages. We also attempted to reconcile classification systems in Patagonia by proposing a nomenclatural system based on a hierarchical classification. In the system proposed, ecoregion is the lowest division small mammal assemblages can recognize in Patagonia. Finally, we conclude that the hierarchical nature of landscapes based on a holistic view of environments reflects real entities that are not just the perceptions of landscape ecologists.://000165537200002 oISI Document Delivery No.: V2651 Times Cited: 4 Cited Reference Count: 89 Cited References: *SAS I INC, 1990, SAS US GUID STAT VER AGUIAR MR, 1988, ANN BOTANICA, V46, P103 BAILEY RG, 1987, LANDSCAPE URBAN PLAN, V14, P313 BEESKOW AM, 1982, CONTRIBUCIONES CTR N, V66, P1 BERTILLER MB, 1981, 7 REUN ARG EC, P10 BERTILLER MB, 1995, J ARID ENVIRON, V29, P85 BIRNEY EC, 1976, ECOLOGY, V57, P1043 BIRNEY EC, 1996, MASTOZOOLOGIA NEOTRO, V3, P171 BOUCHARD A, 1991, QUANTITATIVE APPROAC, P123 BOX EO, 1981, VEGETATIO, V45, P127 BOX EO, 1989, VEGETATIO, V80, P71 BRAN D, 1992, COMUNICACION TECNICA, V3, P1 CABRERA AL, 1969, B SOC ARGENT BOT, V11, P271 CABRERA AL, 1971, B SOC ARGENT BOT, V14, P1 CAIN SA, 1944, FDN PLANT GEOGRAPHY CEI JM, 1969, J HERPETOL, V3, P1 CEI JM, 1985, B ASOCIACION HERPETO, V1, P1 CLEMENTS FE, 1939, BIOECOLOGY CORREA MN, 1969, FLORA PATAGONICA R 2, V8 CORREA MN, 1971, FLORA PATAGONICA R 7, V8 CORREA MN, 1978, FLORA PATAGONICA R 3, V8 CORREA MN, 1984, FLORA PATAGONICA 4A, V8 CORREA MN, 1984, FLORA PATAGONICA 4B, V8 CORREA MN, 1988, FLORA PATAGONICA R 5, V8 CRESPO JA, 1963, NEOTROPICA, V9, P61 CROWELL KL, 1962, ECOLOGY, V43, P75 DELVALLE HF, 1995, EVALUACION ESTADO AC, P37 ERWIN TL, 1982, COLEOPTERISTS B, V36, P74 ERWIN TL, 1983, TROPICAL RAIN FOREST, P59 FORMAN RTT, 1986, LANDSCAPE ECOLOGY GALLARDO JM, 1983, TEMPERATE DESERTS SE, P454 GAUCH HG, 1982, MULTIVARIATE ANAL CO GLANZ WE, 1977, THESIS U CALIFORNIA GOLLUSCIO RA, 1982, B SOC ARGENTINA BOTA, V21, P299 GRABHERR G, 1993, VEGETATION DYNAMICS, P218 GRANT WE, 1979, J MAMMAL, V60, P23 HANSEN AS, 1992, LANDSCAPE BOUNDARIES HOLDRIDGE LR, 1947, SCIENCE, V105, P367 HOLLAND MM, 1991, ECOTONES ROLE LANDSC, P1 JARDINE N, 1972, TAXONOMY PHYTOGEOGRA, P381 JOBAGGY EG, 1996, J VEG SCI, V7, P599 JONGMAN RHG, 1987, DATA ANAL COMMUNITY KELT DA, 1994, J MAMMAL, V75, P890 KLIJN F, 1994, LANDSCAPE ECOL, V9, P89 KRAPOVICKAS A, 1969, REV FAC A, V15, P36 LEAL AR, 1972, B SOC ARGENT BOT, V13, P89 LORES M, 1982, MEMORIA TECNICA INTA, V5, P72 LOZADA M, 1996, MAMMALIAN SPECIES, V540, P1 MACARTHUR RH, 1966, AM NAT, V100, P319 MACMAHON JA, 1976, EVOLUTION DESERT BIO, P133 MANTEL N, 1967, CANCER RES, V27, P209 MARCOLIN A, 1983, TEMPERATE DESERTS SE, P435 MATEUCCI SD, 1982, ORG AM STATES, V22 MENNI RC, 1995, ENVIRON BIOL FISH, V42, P15 MERRIAM CH, 1890, N AM FAUNA, V3, P1 MERRIAM CH, 1894, NATL GEOGRAPHIC MAGA, V6, P229 MESERVE PL, 1978, J BIOGEOGR, V5, P135 MESERVE PL, 1981, J ANIM ECOL, V50, P745 MESERVE PL, 1981, J MAMMAL, V62, P304 MONJEAU JA, 1989, THESIS U NACL LA PLA MONJEAU JA, 1994, MASTOZOOLOGIA NEOTRO, V1, P143 MORTON SR, 1994, AUST J ZOOL, V42, P501 MOVIA CP, 1983, TEMPERATE DESERTS SE, P438 MUELLERDOMBOIS D, 1974, AIMS METHODS VEGETAT MYERS VI, 1983, MANUAL REMOTE SENSIN, V2, CH33 NAIMAN RJ, 1988, J N AM BENTHOL SOC, V7, P289 PARMENTER RR, 1983, OECOLOGIA, V59, P145 PARUELO JM, 1991, QUANTITATIVE APPROAC, P183 PATTERSON BD, 1989, J MAMMAL, V70, P67 PATTERSON BD, 1990, J MAMMAL, V71, P620 PEARSON OP, 1982, MAMMALIAN BIOL S AM, V6, P129 PROHASKA F, 1976, WORLD SURVEY CLIMATO, V12, P13 PROHASKA F, 1982, WORLD SURVEY CLIMATO RAPOPORT EH, 1982, AREOGRAPHY GEOGRAPHI ROHLF FJ, 1982, NT SYS NUMERICAL TAX ROWE JS, 1961, ECOLOGY, V42, P420 SCHULTZ AM, 1967, NATURAL RESOURCES QU SORIANO A, 1949, LILLOA, V20, P193 SORIANO A, 1956, REV INVEST AGRICOLAS, V10, P323 SORIANO A, 1983, TEMPERATE DESERTS SE, P423 SORIANO A, 1992, GLOBAL ECOL BIOGEOGR, V2, P82 TERBRAAK CJF, 1988, ADV ECOL RES, V18, P271 TILMAN D, 1982, RESOURCE PARTITIONIN URBAN DL, 1987, BIOSCIENCE, V37, P119 VOLKHEIMER W, 1983, TEMPERATE DESERTS SE, P425 WALTER H, 1983, TEMPERATE DESERTS SE, P432 WIENS JA, 1985, OIKOS, V45, P421 WILSON EO, 1992, DIVERSITY LIFE ZONNEVELD IS, 1989, LANDSCAPE ECOLOGY, V3, P67 0921-2973 Landsc. Ecol.ISI:000165537200002OUniv Minnesota, Bell Museum Nat Hist, St Paul, MN 55108 USA. Univ Minnesota, Dept Ecol Evolut & Behav, St Paul, MN 55108 USA. Univ Nacl Comahue, Dept Ecol, Bariloche, Rio Negro, Argentina. Illinois State Univ, Dept Biol Sci, Normal, IL 61761 USA. Monjeau, JA, Univ Minnesota, Bell Museum Nat Hist, 100 Ecol Bldg, St Paul, MN 55108 USA.English? GMontague-Drake, Rebecca Lindenmayer, David Cunningham, Ross Stein, John2011A reverse keystone species affects the landscape distribution of woodland avifauna: a case study using the Noisy Miner (<i>Manorina melanocephala</i>) and other Australian birds 1383-1394Landscape Ecology2610Springer NetherlandsEarth and Environmental ScienceWe explored the effects of a purported ‘reverse keystone species’, the Noisy Miner ( Manorina melanocephala ) using a long-term, large-scale dataset. Specifically, we identify whether this aggressive bird affects the landscape distribution patterns of other avifauna, by displacing them into, or restricting their distribution to, less productive areas, and in so doing, adheres to ‘isoleg theory’. We sought to determine the effect of abundance of the Noisy Miner on the abundance of other birds (individual species and groups), and determine whether that effect was consistent with varying site productivity, using a negative binomial distribution with a logarithmic link function, and an offset variable to account for variations in search effort. Relationships between abundance of Noisy Miners and habitat variables were examined using a Poisson distribution with a logarithmic link function scaled for extra-variation (quasi-Poisson regression). We demonstrate that when Noisy Miner abundance is low, many small passerine species are more abundant on high productivity sites. However, as Noisy Miner abundance increases, small passerine abundance decreases, with this decrease most apparent on productive sites. The same patterns were not evident for birds considered ‘non-competitors’ of the Noisy Miner. We identify that both site productivity and vegetation structure influence the abundance of the Noisy Miner. We reveal that the species increasingly tolerates ‘less desirable’ habitat attributes with increasing site productivity. The preference of the Noisy Miner for productive areas is likely to have deleterious impacts on the long-term survival and reproductive success of other Australian woodland bird species, many of which have already undergone severe declines.+http://dx.doi.org/10.1007/s10980-011-9665-4 0921-297310.1007/s10980-011-9665-4<7$Monteil, C. Deconchat, M. Balent, G.2005^Simple neural network reveals unexpected patterns of bird species richness in forest fragments513-527Landscape Ecology205birds; explanatory power; forest fragmentation; neural network; species-area relationships SMALL WOODS; HABITAT FRAGMENTATION; SOUTHWESTERN FRANCE; LANDSCAPE PATTERNS; BREEDING BIRDS; COMMUNITIES; MODELS; AREA; BIODIVERSITY; PREDICTIONArticleJulqThe study of links between bird species richness and forest fragmentation contributes to a better understanding of landscape biodiversity. Difficulties arise from the necessity to deal with multiple non-linear relationships between the involved variables. Neural network models provide an interesting solution thanks to their internal set of non-linear neuron-like components. Their ability is well established for prediction, but their complex structure limits the understanding of underlying processes. To open the 'black box' and get a more transparent 'glass box' model, we selected a simple neural network ( 2 inputs, 1 hidden layer with 3 neurons and 1 output neuron), that improves the prediction of birds species richness ( lower root mean square error) compared to linear, log-linear and logistic models, and simple enough to analyze its internal components and identify patterns in the data. The first hidden neuron provided a sigmoid relationship related to the forest area, the second was like a Boolean operator separating two groups according to the distance to the nearest source forest larger than 100 ha, and the third acted on the smallest isolated woodlots. We revealed a group of isolated woodlots with a higher species richness than less isolated woodlots for a given forest area. This result, unexpected according to the literature, was not obvious in the raw data, and could be explained by a regional differentiation in fragmentation history. Our neural network showed its ability to improve prediction accuracy in respect to other models, to remain ecologically understandable and to give new insights into data exploration.://000232205600002 u ISI Document Delivery No.: 969AK Times Cited: 0 Cited Reference Count: 57 Cited References: BALENT G, 1988, ACTA OECO OECO GEN, V9, P247 BALENT G, 1992, LANDSCAPE ECOL, V6, P195 BASCOMPTE J, 1996, J ANIM ECOL, V65, P465 BELLAMY PE, 1996, J APPL ECOL, V33, P249 BISHOP C, 1995, NEURAL NETWORKS PATT BROSSE S, 1999, ECOL MODEL, V120, P299 BROWN JR, 1996, ENVIRON MANAGE, V20, P289 CANTERS F, 1997, PHOTOGRAMM ENG REM S, V63, P403 DECONCHAT M, 1996, ETUD RECH S, V29, P15 DECONCHAT M, 2001, FORESTRY, V74, P105 DEMUTH H, 1998, NEURAL NETWORK TOOLB EJRNAES R, 2002, ECOL APPL, V12, P1180 FAHRIG L, 2003, ANNU REV ECOL EVOL S, V34, P487 FIELDING AH, 1997, ENVIRON CONSERV, V24, P38 FLATHER CH, 1996, J BIOGEOGR, V23, P155 GILBERT N, 1999, SIMULATION SOCIAL SC GOLLEY FB, 1989, LANDSCAPE ECOL, V2, P201 GRANHOLM SL, 1983, CONDOR, V85, P243 GUYON JP, 1996, ETUD RECH S, V29, P139 HAILA Y, 1996, OIKOS, V76, P536 HILBERT DW, 2001, ECOL MODEL, V146, P311 HILBORN R, 1997, ECOLOGICAL DETECTIVE HINSLEY SA, 1998, GLOBAL ECOL BIOGEOGR, V7, P125 HOF J, 1996, ECOL MODEL, V88, P143 HUTTO RL, 1986, AUK, V103, P593 ICARAN C, 1995, BIODIVERSITE BOISEME JANSSON G, 1999, LANDSCAPE ECOL, V14, P283 JOACHIM J, 1996, ETUD RECH S, V29, P53 JOACHIM J, 1997, ATLAS OISEAUX NICHEU JOKIMAKI J, 1996, ORNIS FENNICA, V73, P97 JORGENSEN SE, 1999, ECOL MODEL, V120, P75 KOHAVI R, 1995, LECT NOTES ARTIF INT, V912, P174 LEK S, 1996, ECOL MODEL, V90, P39 LEK S, 1999, ECOL MODEL, V120, P65 LESCOURRET F, 1994, J ENVIRON MANAGE, V40, P317 LIU JG, 1999, ECOL APPL, V9, P186 LYNCH JF, 1984, BIOL CONSERV, V28, P287 MANEL S, 1999, ECOL MODEL, V120, P337 MUNOZ J, 2004, J VEG SCI, V15, P285 OLDEN JD, 2002, ECOL MODEL, V154, P135 OLDEN JD, 2004, ECOL MODEL, V178, P389 OPDAM P, 1984, J BIOGEOGR, V11, P473 OPDAM P, 1985, BIOL CONSERV, V34, P333 OPDAM P, 1990, T IUGB C TRONDH, P373 OPDAM P, 1993, LANDSCAPE ECOLOGY ST, P147 RIVALS I, 1999, NEURAL COMPUT, V11, P863 RUMELHART DE, 1986, NATURE, V323, P533 SARLE W, 2002, WHAT ARE CROSS VALID SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SEGINER I, 1994, J AGR ENG RES, V59, P203 SKLAR FH, 2001, SPATIAL UNCERTAINTY, P15 STEGEMANN JA, 1999, NEURAL COMPUT APPL, V8, P290 TRZCINSKI MK, 1999, ECOL APPL, V9, P586 WERNER H, 2001, ECOL MODEL, V146, P289 WHITCOMB RF, 1988, FOREST ISLAND DYNAMI, P125 WILLIAMS MR, 1996, GLOBAL ECOL BIOGEOGR, V5, P91 YAHNER RH, 1997, WILSON BULL, V109, P595 0921-2973 Landsc. Ecol.ISI:000232205600002INRA, INPT ENSAT, DYNAFOR, UMR 1201, F-31326 Castanet Tolosan, France. Monteil, C, INRA, INPT ENSAT, DYNAFOR, UMR 1201, BP 107, F-31326 Castanet Tolosan, France. monteil@ensat.frEnglishY<7Moody, A. Woodcock, C. E.1995oThe influence of scale and the spatial characteristics of landscapes on land-cover mapping using remote sensing363-379Landscape Ecology106xscale; spatial pattern; proportion error; regression tree; indicator variable; remote sensing; land-cover SYSTEM; MODELSArticleDecStatistical analyses provide a means for assessing relationships between landscape spatial pattern and errors in the estimates of cover-type proportions as land-cover data are aggregated to coarser scales. Results from a multiple-linear regression model suggest that as patch sizes, variance/mean ratio, and initial proportions of cover types increase, the proportion error moves in a positive direction and is governed by the interaction of the spatial characteristics and the scale of aggregation. However, the standard linear model does not account for the different directions of scale-dependent proportion error since some classes become larger and others become smaller as the scene is aggregated. Addition of indicator variables representing class-type significantly improves the performance by allowing the model to respond differently to different classes. A regression tree model provides a much simpler fit to the complex scaling behavior through an interaction between patch size and aggregation scale. An understanding of the relationships between landscape pattern, scale, and proportion error may advance methods for correcting land-cover area estimates. Such methods could also facilitate high-resolution calibration and validation of coarse-scale remote-sensing-based land-cover mapping algorithms. Ongoing initiatives to produce global land-cover datasets from remote sensing, such as efforts within the IGBP and the EOS MODIS Land-Team, include significant emphasis on high level calibration and validation activities of this nature.://A1995TN14300004 XISI Document Delivery No.: TN143 Times Cited: 36 Cited Reference Count: 38 Cited References: 1991, GRASS 4 0 USERS REFE BAKER WL, 1992, LANDSCAPE ECOL, V7, P291 BAKER WL, 1993, OIKOS, V66, P66 CHAMBERS JM, 1992, STATISTICAL MODELS CRESSIE NAC, 1993, STATISTICS SPATIAL D CULLINAN VI, 1992, LANDSCAPE ECOL, V7, P211 DAVIS FW, 1990, P AM MET SOC S FIFE, P11 FIELD CB, 1993, SCALING PHYSL PROCES, P1 GERVIN JC, 1985, INT J REMOTE SENS, V6, P47 GETIS A, 1978, MODELS SPATIAL PROCE GOPAL S, 1994, PHOTOGRAMM ENG REM S, V60, P181 HESS G, 1994, LANDSCAPE ECOL, V9, P3 JUPP DLB, 1988, IEEE T GEOSCI REMOTE, V26, P463 KLEINBAUM DG, 1978, APPLIED REGRESSION A LATTY RS, 1981, S MACHINE PROCESSING, P384 LI HB, 1993, LANDSCAPE ECOL, V8, P155 MARCEAU DJ, 1994, REMOTE SENS ENVIRON, V49, P93 MEENTEMEYER V, 1987, LANDSCAPE HETEROGENE, P15 MILNE BT, 1992, AM NAT, V139, P32 MOODY A, 1994, PHOTOGRAMM ENG REM S, V60, P585 NELLIS MD, 1989, LANDSCAPE ECOLOGY, V2, P93 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 RAFFY M, 1992, REMOTE SENS ENVIRON, V40, P101 RUNNING S, 1994, IN PRESS INT J REMOT SALOMONSON VV, 1989, IEEE T GEOSCI REMOTE, V27, P145 STOMS DM, 1994, PROF GEOGR, V46, P346 STRAHLER A, 1994, NASA11 DOC TOWNSHEND JRG, 1988, INT J REMOTE SENS, V9, P187 TOWNSHEND JRG, 1990, INT J REMOTE SENS, V11, P149 TOWNSHEND JRG, 1992, IGBP20 INT GEOSPH BI TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P245 TURNER SJ, 1991, QUANTITATIVE METHODS, P17 UNWIN D, 1981, INTRO SPATIAL ANAL WOODCOCK CE, 1987, REMOTE SENS ENVIRON, V21, P311 WOODCOCK CE, 1992, 4TH P BIENN REM SENS, P378 WOODCOCK CE, 1994, ACCURACY ASSESSMENT WOODCOCK CE, 1994, REMOTE SENS ENVIRON, V50, P240 0921-2973 Landsc. Ecol.ISI:A1995TN143000049Moody, A, UNIV N CAROLINA,DEPT GEOG,CHAPEL HILL,NC 27599.EnglishE<75Morales, J. M. Fortin, D. Frair, J. L. Merrill, E. H.2005IAdaptive models for large herbivore movements in heterogeneous landscapes301-316Landscape Ecology203Cervus elaphus; foraging; neural networks; spatial; ungulate WAPITI CERVUS-ELAPHUS; MAMMALIAN HERBIVORES; FUNCTIONAL-RESPONSE; ECOLOGICAL LANDSCAPES; SAMPLING INFORMATION; SEARCHING BEHAVIOR; YELLOWSTONE ELK; FORAGE QUALITY; BISON; FOODArticleAprqIt is usually assumed that landscape heterogeneity influences animal movements, but understanding of such processes is limited. Understanding the effects of landscape heterogeneity on the movements of large herbivores such as North American elk is considered very important for their management. Most simulation studies on movements of large herbivores use predetermined behavioral rules based on empirical observations, or simply on what seems reasonable for animals to do. Here we did not impose movement rules but instead we considered that animals had higher fitness (hence better performance) when they managed to avoid predators, and when they acquired important fat reserves before winter. Individual decision-making was modeled with neural networks that received as input those variables suspected to be important in determining movement efficiency. Energetic gains and losses were tracked based on known physiological characteristics of ruminants. A genetic algorithm was used to improve the overall performance of the decision processes in different landscapes and ultimately to select certain movement behaviors. We found more variability in movement patterns in heterogeneous landscapes. Emergent properties of movement paths were concentration of activities in well-defined areas and an alternation between small, localized movement with larger, exploratory movements. Even though our simulated individuals moved shorter distances that actual elk, we found similarities in several aspects of their movement patterns such as in the distributions of distance moved and turning angles, and a tendency to return to previously visited areas.://000231824400005 ISI Document Delivery No.: 963RU Times Cited: 3 Cited Reference Count: 66 Cited References: ADLER PB, 2001, OECOLOGIA, V128, P465 ANDERSON JA, 1995, INTRO NEURAL NETWORK BAILEY DW, 1996, J RANGE MANAGE, V49, P386 BEECHAM JA, 1998, ECOL MODEL, V113, P141 BELOVSKY GE, 1984, AM NAT, V124, P97 BERGMAN CM, 2000, FUNCT ECOL, V14, P61 BOLKER B, 1997, THEOR POPUL BIOL, V52, P179 CAIN ML, 1991, ECOLOGY, V72, P2137 COOK JG, 2002, N AM ELK ECOLOGY MAN, P259 COOK RC, 2004, J MAMMAL, V85, P714 DELGIUDICE GD, 2001, WILDLIFE MONOGR OCT, P1 DIECKMANN U, 2000, GEOMETRY ECOLOGICAL FARNSWORTH KD, 1996, FUNCT ECOL, V10, P678 FARNSWORTH KD, 1999, AM NAT, V153, P509 FORTIN D, 2002, ECOL MODEL, V153, P279 FORTIN D, 2002, ECOLOGY, V83, P970 FORTIN D, 2003, BEHAV ECOL SOCIOBIOL, V54, P194 FORTIN D, 2004, ECOLOGY, V85, P2312 FRAIR JL, 2004, LANDSCAPE ECOLOGY FRYXELL JM, 1988, AM NAT, V131, P781 FRYXELL JM, 1991, AM NAT, V138, P478 GOLDBERG DE, 1989, GENETIC ALGORITHMS S GRIMM V, 1996, SCI TOTAL ENVIRON, V183, P151 GROSS JE, 1993, ECOLOGY, V74, P778 HUDSON RJ, 1985, BIOENERGETICS WILD H HUDSON RJ, 1987, J RANGE MANAGE, V40, P71 HUSE G, 1998, FISH RES, V37, P163 HUSE G, 1999, EVOL ECOL, V13, P469 ILLIUS AW, 1987, J ANIM ECOL, V56, P989 ILLIUS AW, 1992, OECOLOGIA, V89, P428 JIANG Z, 1992, CAN J ZOOL, V70, P675 JOHNSON CJ, 2002, J ANIM ECOL, V71, P225 JUNG HG, 1985, J RANGE MANAGE, V38, P302 KAREIVA P, 1987, AM NAT, V130, P233 KEELING MJ, 2000, SCIENCE, V290, P1758 KOT M, 1996, ECOLOGY, V77, P2027 LAW R, 2003, ECOLOGY, V84, P252 LEWIS MA, 1993, NATURE, V366, P738 LEWIS MA, 1997, SPATIAL ECOLOGY ROLE, P46 LIMA SL, 1996, TRENDS ECOL EVOL, V11, P131 MCNAUGHTON SJ, 1984, AM NAT, V124, P863 MITCHELL M, 1995, ARTIFICIAL LIFE OVER, P267 MITCHELL WA, 2002, OIKOS, V99, P249 MOEN R, 1997, ECOLOGY, V78, P505 MORALES JM, 2002, AM NAT, V160, P531 MORALES JM, 2002, ECOLOGY, V83, P2240 MORALES JM, 2004, ECOLOGY, V89, P2436 MURRELL DJ, 2000, J ANIM ECOL, V69, P471 PARKER KL, 1984, J WILDLIFE MANAGE, V48, P474 PASTOR J, 1997, J MAMMAL, V78, P1040 ROBBINS CT, 1993, WILDLIFE FEEDING NUT SCHMIDT KA, 2003, ECOLOGY, V84, P3276 SCHMITZ OJ, 1997, ECOLOGY, V78, P1388 SHIPLEY LA, 1996, FUNCT ECOL, V10, P234 SPALINGER DE, 1992, AM NAT, V140, P325 STRAND E, 2002, AM NAT, V159, P624 TILMAN D, 1997, SPATIAL ECOLOGY ROLE TURCHIN P, 1998, QUANTITATIVE ANAL MO TURCHIN P, 2001, ECOLOGY, V82, P1521 TURNER MG, 1993, ECOL MODEL, V69, P163 TURNER MG, 1994, ECOL APPL, V4, P472 WHITLEY D, 2001, INFORM SOFTWARE TECH, V43, P817 WIENS JA, 1993, OIKOS, V66, P369 WILMSHURST JF, 1995, BEHAV ECOL, V6, P209 WILMSHURST JF, 2000, P ROY SOC LOND B BIO, V267, P345 ZOLLNER PA, 1999, ECOLOGY, V80, P1019 0921-2973 Landsc. Ecol.ISI:000231824400005Univ Connecticut, Storrs, CT 06269 USA. Univ Laval, Dept Biol, Ste Foy, PQ G1K 7P4, Canada. Univ Alberta, Dept Biol Sci, Edmonton, AB T6G 2E9, Canada. Morales, JM, Univ Connecticut, 75 N Eagleville Rd,U-43, Storrs, CT 06269 USA. juan.morales@uconn.eduEnglishJ|? ;Moreira, E. Costa, S. Aguiar, A. P. Camara, G. Carneiro, T.20093Dynamical coupling of multiscale land change models 1183-1194Landscape Ecology249%No single model or scale can fully capture the causes of land change. For a given region, land changes may have different impacts at different places. Limits and opportunities imposed by biophysical and socio-economic conditions, such as local policies and accessibility, may induce distinct land change trajectories. These local land change trajectories may, in turn, indirectly affect other places, as local actions interact with higher-level driving forces. Such intraregional interdependencies cannot be captured by studies at a single scale, calling for multiscale and multilocality studies. This paper proposes a software organization for building computational models that support dynamical linking of multiple scales. This structure couples different types of models, such as cell-space models with agent-based models. We show how results in multiscale models can flow both in bottom-up and top-down directions, thus allowing feedback from local actors to regional scales. The proposal is general and independent of specific software, and it is effective to model intraregional, bottom-up and top-down interactions in land change models. To show the model's potential, we develop a case study that shows how a multiscale model for the Brazilian Amazonia can include feedbacks between local to regional scales.!://WOS:000270739000004Times Cited: 0 0921-2973WOS:00027073900000410.1007/s10980-009-9397-x|? CMoreira, Francisco Catry, Filipe X. Rego, Francisco Bacao, Fernando2010`Size-dependent pattern of wildfire ignitions in Portugal: when do ignitions turn into big fires? 1405-1417Landscape Ecology259NovNot all wildfire ignitions result in burned areas of a similar size. The aim of this study was to explore whether there was a size-dependent pattern (in terms of resulting burned area) of fire ignitions in Portugal. For that purpose we characterised 71,618 fire ignitions occurring in the country in the period 2001-2003, in terms of population density in the local parish, land cover type and distance to roads. We then assigned each ignition into subsets of five classes according to the resulting burned area: > 5 ha, > 50 ha, > 100 ha, > 250 ha, > 500 ha. The probability of an ignition resulting in different burned area classes was modelled using binary logistic regression, and the relative importance, strength and signal (positive or negative) of the three explanatory variables compared across the models obtained for the different classes. Finally, we explored the implications of land cover and population density changes during the period 1990-2000 in Portugal for the likelihood of ignitions resulting in wildfires > 500 ha. Population density was the more important variable explaining the resulting burned area, with the probability of an ignition resulting in a large burned area being inversely related to population density. In terms of land cover, ignitions resulting in large burned areas were more likely to occur in shrubland and forest areas. Finally, ignitions farther away from roads were more likely to result in large burns. The current land cover trends (decrease of agricultural land and increase in shrublands) and population trends (decline in population densities except near the coast) are increasing the probability that ignitions will result in large fires in vast regions of the country.!://WOS:000281981000008Times Cited: 0 0921-2973WOS:00028198100000810.1007/s10980-010-9491-0<73Moreira, F. Ferreira, P. G. Rego, F. C. Bunting, S.2001ZLandscape changes and breeding bird assemblages in northwestern Portugal: the role of fire175-187Landscape Ecology162Rbirds diversity fire land abandonment landscape change Portugal DIVERSITY AVIFAUNAArticleFebFire is a major driving force of landscape change in the Mediterranean region. The objectives of this paper were to explore the implications of landscape change and wildfires in a region of northwestern Portugal for the diversity of breeding birds. Land use cover for the years 1958, 1968, 1983 and 1995 was obtained from aerial photography for a study area of 3700 ha. Breeding bird assemblages in each of six land use categories were characterized in 1998 using point counts. The main landscape changes in the study area across the 40 years were a decrease in the area of agricultural land and low shrublands (respectively 29% and 48%) and an increase in forests and tall shrublands (both over 95%). Bird assemblages showed increased richness and diversity across the gradient: low shrublands --> tall shrublands --> conifer --> mixed --> deciduous --> agricultural areas. Many of the species with narrow niche breadth (specialists) were associated with agricultural areas and deciduous forests. In spite of the low diversity of burned areas (mostly shrublands) a few specialist species depend on this habitat. Thus, the current fire regime probably contributes to maintaining bird diversity at the landscape level. There was an inverse relationship between landscape diversity and estimated bird diversity across the last 40 years. Landscape management actions to preserve bird diversity should focus on the maintenance of agricultural land and deciduous forests. In parallel, a wider use of prescribed burning and grazing is suggested. This would contribute to maintaining low shrublands in the landscape, useful both as an habitat for some bird species and as fuel breaks for preventing the occurrence of large wildfires.://000167936500008 ISI Document Delivery No.: 419EN Times Cited: 10 Cited Reference Count: 38 Cited References: *EUR COMM, 1996, FOR FIR S EUR UN *STATS INC, 1995, STATISTICA WIND COMP BLONDEL J, 1999, BIOL WILDLIFE MEDITE COSTA JC, 1998, QUERCETEA, V1, P5 DESANTE DF, 1981, STUD AVIAN BIOL, V6, P177 EASTMAN JR, 1990, IDRISI GRID BASED GE EDENIUS L, 1996, LANDSCAPE ECOL, V11, P325 ETIENNE M, 1998, LANDSCAPE DISTURBANC, P127 FARINA A, 1997, LANDSCAPE ECOL, V12, P365 FARINA A, 1998, PRINCIPLES METHODS L GAUCH HG, 1982, MULTIVARIATE ANAL CO GIBBS JP, 1990, CONSERV BIOL, V4, P193 HAGEMEIJER WJM, 1997, EBCC ATLAS EUROPEAN HELTSHE JF, 1985, ECOLOGY, V66, P107 JONGMAN RHG, 1995, DATA ANAL COMMUNITY LEVINS R, 1968, EVOLUTIONS CHANGING MCCOLLIN D, 1998, ECOGRAPHY, V21, P247 MCGARRIGAL K, 1995, GTR351 USDA FOR SERV MOREIRA F, UNPUB LANDSC ECOL MORENO JM, 1998, LARGE FOREST FIRES, P159 PREISS E, 1997, LANDSCAPE ECOL, V12, P51 PRODON R, 1981, OIKOS, V37, P21 PRODON R, 1987, ROLE FIRE ECOLOGICAL, P121 REGO F, 1992, RESPONSES FOREST ECO, P367 REYNOLDS RT, 1980, CONDOR, V82, P309 RIBEIRO O, 1987, GEOGRAFIA PORTUGAL RICE WR, 1989, EVOLUTION, V43, P223 RUFINO R, 1989, ATLAS AVES QUE NIDIF RUNDEL PW, 1998, LANDSCAPE DISTURBANC, P3 SIEGEL S, 1988, NONPARAMETRIC STAT B SNEATH PHA, 1973, NUMERICAL TAXONOMY SOKAL RR, 1981, BIOMETRY SPARKS TH, 1996, AGR ECOSYST ENVIRON, V60, P1 TERBRAAK CJF, 1987, CANOCO FORTRAN PROGR TUCKER GM, 1994, BIRDLIFE CONSERVATIO, V3 WIENS JA, 1989, ECOLOGY BIRD COMMUNI ZAHL S, 1977, ECOLOGY, V58, P907 ZAR JH, 1996, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000167936500008Inst Super Agron, Ctr Ecol Aplicada Prof Baeta Neves, P-1349017 Lisbon, Portugal. Moreira, F, Inst Super Agron, Ctr Ecol Aplicada Prof Baeta Neves, P-1349017 Lisbon, Portugal.English I<7'Moreira, F. Rego, F. C. Ferreira, P. G.2001yTemporal (1958-1995) pattern of change in a cultural landscape of northwestern Portugal: implications for fire occurrence557-567Landscape Ecology166\afforestation agricultural abandonment fire landscape changes Portugal socioeconomy DYNAMICSArticleAugIn this paper we test the hypothesis that landscape changes in a region of Northern Portugal (Minho) in the last 40 years could be predicted from socioeconomic and political history. The major predicted changes were related to agricultural abandonment and afforestation. We further predicted that these changes contributed to increased fire risk. Analysis of aerial photography for the years 1958, 1968, 1983 and 1995 in a study area of 3700 ha revealed a significant decline in agricultural areas and low shrublands and an increase in tall shrublands and forests. This represented a 20-40% increase in fuel accumulation at a landscape level, suggesting that the abandonment of farming activities is a major driving force of increasing fire occurrence in the region. With one exception, all the predictions were partly or totally confirmed. This study confirms that socioeconomic factors might explain a significant part of the variation in landscape composition across time, in the Mediterranean region.://000172548800006 ISI Document Delivery No.: 499AW Times Cited: 19 Cited Reference Count: 39 Cited References: *CCRN, 1995, EST AMB ORD TERR REG *ESRI, 1992, UND GIS ARC INF METH *EUR COMM, 1996, FOR FIR S EUR UN *I NAC EST, 1954, INQ AS EXPL AGR CONT *I NAC EST, 1960, 10 REC GER POP *I NAC EST, 1979, REC AGR CONT *I NAC EST, 1981, REC POP HAB *I NAC EST, 1989, REC GER AGR *I NAC EST, 1989, REC POP HAB *I NAC EST, 1993, CENS 91 13 REC GER P *MIN AGR, 1940, PLAN POV FLOR CALDAS EQC, 1941, PROBLEMA DETERMINACA CALDAS EQC, 1994, MEMORIA MONOGRAFICA COSTA JC, 1998, QUERCETEA, V1, P5 DEQUEIROZ JBR, 1920, CONCELHO GUIMARAES S DUNN CP, 1991, QUANTITATIVE METHODS, P173 EASTMAN JR, 1990, IDRISI GRID BASED GE ETIENNE M, 1998, LANDSCAPE DISTURBANC, P127 FARINA A, 1998, PRINCIPLES METHODS L FINAN TJ, 1993, STRUCTURAL CHANGE SM, P46 FORMAN RT, 1997, ECOLOGY LANDSCAPES R FOX MD, 1987, ROLE FIRE ECOLOGICAL, P23 GARDNER RH, 1991, QUANTITATIVE METHODS, P519 KIENAST F, 1993, LANDSCAPE ECOL, V8, P103 LAGRO JA, 1992, LANDSCAPE ECOL, V7, P275 LUQUE SS, 1994, LANDSCAPE ECOL, V9, P287 MALANSON GP, 1987, ROLE FIRE ECOLOGICAL, P49 MANLY BF, 1993, RESOURCE SELECTION A MCGARRIGAL K, 1995, GTR351 USDA FOR SERV MORENO JM, 1998, LARGE FOREST FIRES, P159 MULLER MR, 1994, LANDSCAPE ECOL, V9, P151 PARKS PJ, 1991, QUANTITATIVE METHODS, P309 REGO F, 1992, RESPONSES FOREST ECO, P367 RIBEIRO O, 1987, GEOGRAFIA PORTUGAL SIMPSON JW, 1994, LANDSCAPE ECOL, V9, P261 SOKAL RR, 1981, BIOMETRY TURNER MG, 1990, QUANTITATIVE METHODS, P323 VASCONCELOS MJ, 1998, P 3 INT C FOR FIR RE, P2111 VIEIRA JAN, 1995, MEDITERRANEO, V7, P173 0921-2973 Landsc. Ecol.ISI:000172548800006Inst Super Agron, Ctr Ecol Aplicada Prof Baeta Neves, P-1349017 Lisbon, Portugal. Moreira, F, Inst Super Agron, Ctr Ecol Aplicada Prof Baeta Neves, P-1349017 Lisbon, Portugal.English <7Moreira, F. Russo, D.2007nModelling the impact of agricultural abandonment and wildfires on vertebrate diversity in Mediterranean Europe 1461-1476Landscape Ecology2210amphibians birds conservation fire landscape mammals farmland reptiles LANDSCAPE STRUCTURE BIRD COMMUNITIES LAND ABANDONMENT NORTHERN SPAIN NATIONAL-PARK FIRE CONSERVATION HETEROGENEITY BIODIVERSITY MANAGEMENTArticleDecAgricultural land abandonment, widespread in the Mediterranean, is leading to a recovery of scrubland and forests which are replacing open habitats and increasing wildfire events. Using published data, we modelled the global and regional impact of abandonment and wildfires on 554 species of terrestrial vertebrates occurring in Mediterranean Europe. For all groups except amphibians, open habitats or farmland sustained higher species richness. Open habitats showed regional differences in their conservation value, western areas being particularly important for birds and amphibians and eastern areas for reptiles. Scrublands hosted fewer species than open habitats, farmland and forest, but sustained several endemic birds and mammals. The greater species richness of forests was mostly due to species widespread in Europe. Wildfires promote scrubland expansion in detriment of forest; because more species are associated to eastern forests, fire is predicted to affect more seriously this region. Scrubland conservation value was found to be highest in the west, where fire might have a positive impact. Fire regime, however, plays a crucial role. Although large fires have a negative impact, small-scale fires may favour biodiversity in abandoned areas. Due to the intrinsic difficulty in managing abandoned land to preserve the original Mediterranean vertebrate diversity, the best option to achieve this goal is the development of policies designed to make farmers and traditional farmland survive.://000250632100006jISI Document Delivery No.: 227BL Times Cited: 0 Cited Reference Count: 63 Moreira, Francisco Russo, Danilo 0921-2973 Landsc. Ecol.ISI:000250632100006,Univ Tecn Lisbon, Inst Agron, Ctr Appl Ecol Prof Baeta Neves, P-1349017 Lisbon, Portugal. Univ Naples Federico 2, Fac Agr, Appl Ecol Lab, Dept Ar Bo Pa Ve, I-80055 Naples, Italy. Moreira, F, Univ Tecn Lisbon, Inst Agron, Ctr Appl Ecol Prof Baeta Neves, P-1349017 Lisbon, Portugal. fmoreira@isa.utl.ptEnglishl|?% Morellet, Nicolas Van Moorter, Bram Cargnelutti, Bruno Angibault, Jean-Marc Lourtet, Bruno Merlet, Joel Ladet, Sylvie Hewison, A. J. Mark2011cLandscape composition influences roe deer habitat selection at both home range and landscape scales999-1010Landscape Ecology267AugUnderstanding how patterns of habitat selection vary in relation to landscape structure is essential to predict ecological responses of species to global change and inform management. We investigated behavioural plasticity in habitat selection of roe deer (Capreolus capreolus) in relation to variable habitat availability across a heterogeneous agricultural landscape at the home range and landscape scales. As expected, woodland was heavily selected, but we found no functional response for this habitat, i.e. no shift in habitat selection with changing habitat availability, possibly due to the presence of hedgerows which were increasingly selected as woodlands were less abundant. Hedgerows may thus function as a substitutable habitat for woodlands by providing roe deer with similar resources. We observed a functional response in the use of hedgerows, implying some degree of landscape complementation between hedgerows and open habitats, which may in part compensate for lower woodland availability. We also expected selection for woodland to be highest at the wider spatial scale, especially when this habitat was limiting. However, our results did not support this hypothesis, but rather indicated a marked influence of habitat composition, as both the availability and distribution of resources conditioned habitat selection. There was no marked between-sex difference in the pattern of habitat selection at either scale or between seasons at the landscape scale, however, within the home range, selection did differ between seasons. We conclude that landscape structure has a marked impact on roe deer habitat selection in agricultural landscapes through processes such as landscape complementation and supplementation.!://WOS:000292705900008Times Cited: 0 0921-2973WOS:00029270590000810.1007/s10980-011-9624-0|?RMoreno, Javier Palomo, Ignacio Escalera, Javier Martin-Lopez, Berta Montes, Carlos2014Incorporating ecosystem services into ecosystem-based management to deal with complexity: a participative mental model approach 1407-1421Landscape Ecology298OctIntegrating ecosystem services into ecosystem-based management (EBM) is currently one of the most relevant challenges for management. For that purpose, it is necessary to depict the relationships established between ecosystems and society considering the delivery, use and governance of ecosystem services. One effective way of doing so involves collaboration between researchers, who scientifically study the system, and managers, who have specific experience and technical knowledge. With this aim, we held two workshops in 2011 in the National Parks of Doana and Sierra Nevada, Andalusia (Spain), with researchers and managers from the protected areas at different organizational levels: local, regional and national. Taking the participative mental model technique as an inspiration, we developed a tool that was used as a means to allow a holistic analysis of ecosystem services from an interdisciplinary and participative perspective. We found that participatory mental models, help integrating ecosystem services into EBM as it includes stakeholders' proposals and knowledge. For the implementation of ecosystem services for management, we discuss the necessity of navigating a process that requires considerable changes, not only in using new concepts such as ecosystem services, but also in the management structures that govern the services. This process would require closer interaction between citizens, researchers and managers, and the creation of new participation spaces that include ecosystem service beneficiaries located beyond protected areas.!://WOS:000342078600011Times Cited: 2 0921-2973WOS:00034207860001110.1007/s10980-014-0053-8|? #Morgan, Jessica L. Gergel, Sarah E.2010`Quantifying historic landscape heterogeneity from aerial photographs using object-based analysis985-998Landscape Ecology257AugtSpatial landscape heterogeneity is routinely used to characterize ecological processes, particularly over time. Critical to the use of landscape heterogeneity as an ecological indicator, is a consistent and quantitative definition, especially in terms of a baseline description. As the oldest and most frequently used form of remotely sensed data, aerial photographs are a unique source of detailed, historic landscape information with the potential to provide this baseline data. Using aerial photographs, texture information, and terrain data of an unharvested watershed in 1937/1938, we quantify baseline heterogeneity. To do this, we explore the use of a relatively new spatial method which utilizes an object-based approach to quantify landscape pattern over multiple spatial scales. Based on quantitative metrics derived from our object-based analysis, the primary dimensions of landscape heterogeneity were first identified using factor analysis, and subsequently summarized with cluster analysis. Sixteen distinct elements of heterogeneity were identified which explained over 76% of the overall variance within the original factors. Several elements of heterogeneity extracted using this approach are common in landscape ecology, including patch compaction, shape, size, texture, and neighboring characteristics (context). However, new elements of spatial heterogeneity were also identified, representing tonal, textural, topographic, and positional variability over multiple spatial scales. We also explored differences in heterogeneity between landscape types of contrasting structure and ecology (riparian versus upland). Few quantitative differences were identified between landscapes, despite obvious ecological and biophysical differences. The results of this analysis provide an alternative description of baseline landscape heterogeneity, which recognizes elements not previously identified.!://WOS:000279592100001Times Cited: 0 0921-2973WOS:00027959210000110.1007/s10980-010-9474-1~?5Morilhat, C. Bernard, N. Foltete, J. C. Giraudoux, P.2008pNeighbourhood landscape effect on population kinetics of the fossorial water vole (Arvicola terrestris scherman)569-579Landscape Ecology235This paper addresses the issue of whether landscape structure affects A. terrestris population kinetics on a neighbourhood spatial scale, and if so, at what spatial scale is that effect at its maximum. We investigated how the growth of A. terrestris populations is influenced by the landscape context of parcels used for hay production in the French Jura Mountains. Five landscape metrics (relative area of grassland, mean patch area of grassland, patch density of grassland, woodland patch density in grassland, grassland-woodland edge density) were computed over an increasing radius around each parcel (max. 3 km). Redundancy analysis showed that the extent, rate and early onset of A. terrestris population growth were favoured in open grassland areas. Landscape effects on A. terrestris populations as determined by the five metrics are scale-dependent: mean patch area of grassland, patch density of grassland and woodland patch density in grassland had an impact on a grassland parcel within a neighbourhood radius of about 800 m, while relative area of grassland and grassland-woodland edge density had an impact within a neighbourhood radius of about 400 m. Those findings corroborate earlier hypotheses about a multifactorial regulation of A. terrestris populations and a spatial hierarchy of regulating factors. They have potential implications in terms of landscape management and small mammal pest control."://WOS:000254964600007 Times Cited: 0WOS:000254964600007(10.1007/s10980-008-9216-9|ISSN 0921-2973o<7fMorris, S. J. Boerner, R. E. J.1998aLandscape patterns of nitrogen mineralization and nitrification in southern Ohio hardwood forests215-224Landscape Ecology134znitrogen mineralization nitrification organic carbon scale Ohio SOIL CHEMISTRY VARIABILITY ECOSYSTEMS DYNAMICS INPUT SCALEArticleAugcThis study quantified nitrogen mineralization and nitrification potentials in soils of hardwood forests of southern Ohio at three spatial scales: (1) the regional scale, represented by four study areas of 90-120 ha separated by 3-65 km, (2) the local scale, represented by three contiguous watersheds within each study area, and (3) the topographic scale, represented by xeric, intermediate, and mesic sites within each watershed, as defined by a GIS-generated Integrated Moisture Index (IMI). Organic C, NO3- pool size, net N mineralization, proportional nitrification, and net nitrification potentials all varied among study sites (i.e. at the regional scale). Using path analysis, we were able to construct scale-independent causal models explaining 30-35% of the variance in organic C and potential net N mineralization and >70% of the variance in potential net NO3- production. Site- and scale-specific differences in geology and/or land use history among study sites were likely responsible for the variation not explained by the path analysis. At the local scale, there were significant variations in organic C and inorganic N pool sizes among watersheds within a study site in two of the four study sites. In addition, most parameters we measured varied significantly along the topographic gradient (i.e. with long-term soil moisture availability/IMI). Based on our results, scaling up models of nitrification from plot scale to the regional scale should be straightforward, whereas scaling up organic C storage and N mineralization will require incorporation of independent scaling paradigms at three (or more) spatial scales.://000079677000003 ISI Document Delivery No.: 185NY Times Cited: 24 Cited Reference Count: 30 Cited References: *SAS, 1985, STAT AN SYST US GUID *SAS, 1995, STAT AN SYST US GUID ABER JD, 1989, BIOSCIENCE, V39, P378 ALLISON LE, 1965, METHODS SOIL ANAL, V2, P1367 ARBUCKLE JL, 1995, AMOS USERS GUIDE BOERNER REJ, 1989, SOIL BIOL BIOCHEM, V21, P795 BOERNER REJ, 1995, APPL SOIL ECOL, V2, P243 BOERNER REJ, 1997, IN PRESS RESTORING M GARTEN CT, 1994, FOREST SCI, V40, P497 HAMMER RD, 1987, SOIL SCI SOC AM J, V51, P1320 HENDERSHOT WH, 1993, SOIL SAMPLING METHOD, P141 HURLBERT SH, 1984, ECOL MONOGR, V54, P187 IVERSON LR, 1997, IN PRESS RESTORING M KILLHAM K, 1994, SOIL ECOLOGY LEE JJ, 1979, FOREST SCI, V23, P393 LIKENS GE, 1975, P INTECOL S COUPL LA, P7 MORRIS SJ, 1997, IN PRESS FOR ECOL MA PARKIN TB, 1993, J ENVIRON QUAL, V22, P409 PLYMALE AE, 1987, FOREST ECOL MANAG, V21, P21 ROBERTSON GP, 1982, PHIL T R SOC LOND B, V296, P445 SCHIMEL DS, 1993, BIOTIC INTERACTIONS, P45 SUTHERLAND EK, 1997, IN PRESS RESTORING M TIETEMA A, 1993, FOREST ECOL MANAG, V57, P29 VANDEGEIJN SC, 1993, VEGETATIO, V104, P283 VITOUSEK PM, 1982, ECOL MONOGR, V52, P155 VITOUSEK PM, 1985, FOREST SCI, V31, P122 WALLEY FL, 1996, SOIL BIOL BIOCHEM, V28, P383 WOLFE JN, 1949, OHIO BIOL SURV B, V41, P1 ZAK DR, 1989, CAN J FOREST RES, V19, P1521 ZAK DR, 1994, ECOLOGY, V75, P2333 0921-2973 Landsc. Ecol.ISI:000079677000003Ohio State Univ, Dept Plant Biol, Columbus, OH 43210 USA. Morris, SJ, Ohio State Univ, Dept Plant Biol, 1735 Neil Ave, Columbus, OH 43210 USA.EnglishR<7Mortberg, U. M.2001RResident bird species in urban forest remnants; landscape and habitat perspectives193-203Landscape Ecology163resident forest birds urban fragmentation landscape pattern habitat quality FRAGMENTATION DISTRIBUTIONS ENVIRONMENTS EXTINCTION COMMUNITY ABUNDANCE SELECTION WOODSArticleApr The aim of this study was to investigate the effects of habitat loss, fragmentation and habitat quality on sedentary forest birds in an urban and suburban environment. The study area was situated in Stockholm, the capital of Sweden, embracing the city centre, suburbs and parts of the rural surroundings. Breeding forest birds were surveyed in 51 forested sample sites (2-700 ha) and five species of resident birds were selected for further studies: willow tit (Parus montanus), crested tit (P. cristatus) and coal tit (P. ater) representing coniferous forest and marsh tit (P. palustris) and nuthatch (Sitta europaea) representing deciduous forest. A spatial landscape analysis was made using a geographical information system (GIS). In 21 of the smaller sites (2-200 ha), a field study was conducted to examine habitat quality parameters like vegetation age, structure and composition, and human-induced disturbance. The probability of occurrence (breeding) of bird species as functions of landscape and habitat descriptors was tested using logistic regression. All investigated species of the Parus guild showed high probabilities of occurrence only in forest patches larger than 200-400 ha, and was not present in patches smaller than 10-30 ha. This meant that patches of presumably suitable habitat (coniferous vs. moist deciduous forest) were left unoccupied. The amount of standing dead and decaying trees provided additional explanation for the distribution of the willow tit. Large areas of urban open land, industrial land use and large bodies of water had a negative influence on the probability of occurrence of several species, which indicate that they were sensitive to isolation. The probability of occurrence of the marsh tit was also influenced by distance to other sample sites with marsh tits. Unlike the Parus species, the nuthatch was breeding in most of the parks and forest remnants. This species prefers mature deciduous forest, mainly oak, which habitat was common in the urban environment. The nuthatch was only absent in some of the smallest (a few ha) forest fragments, with a mean distance between forest patches in the surroundings of over 100 m. The study showed that large forest areas and a high amount of forest in the landscape are important for the investigated resident birds that are not adapted to the urban environment. Vast areas without tree-cover seemed to be poor habitat and/or restrict dispersal. Strips of high-quality habitats, including standing trees with nest-holes, were not entirely absent in the urban and suburban environment.://000168194400001 ISI Document Delivery No.: 423TT Times Cited: 19 Cited Reference Count: 42 Cited References: *MUN SOLL, 1991, ENV PROT PLAN *SWED ENV PROT AG, 1984, BIOL INV NORM FAGL ANDREN H, 1997, OIKOS, V80, P193 ANGELSTAM P, 1992, ECOLOGICAL PRINCIPLE BEISSINGER SR, 1982, CONDOR, V84, P75 BOLGER DT, 1997, CONSERV BIOL, V11, P406 CLERGEAU P, 1998, CONDOR, V100, P413 DEGRAAF RM, 1991, LANDSCAPE URBAN PLAN, V21, P173 ENOKSSON B, 1995, LANDSCAPE ECOL, V10, P267 ESSEEN PA, 1997, ECOLOGICAL B, V46, P16 FAHRIG L, 1997, J WILDLIFE MANAGE, V61, P603 FARINA A, 1997, LANDSCAPE ECOL, V12, P365 GILBERT OL, 1989, ECOLOGY URBAN HABITA HAGAN JM, 1996, CONSERV BIOL, V10, P188 HANSKI I, 1998, OIKOS, V83, P390 HANSSON L, 1995, MOSAIC LANDSCAPES EC HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HELLE P, 1984, ORNIS FENNICA, V61, P121 HELLE P, 1986, OIKOS, V46, P107 HINSLEY SA, 1996, OECOLOGIA, V105, P100 JOKIMAKI J, 1996, ORNIS FENNICA, V73, P97 JOKIMAKI J, 1998, LANDSCAPE URBAN PLAN, V39, P253 KOSKIMIES P, 1989, DISTRIBUTION NUMBERS LENS L, 1996, J AVIAN BIOL, V27, P41 MCDONNELL MJ, 1997, URBAN ECOSYSTEMS, V1, P21 MCGARIGAL K, 1995, 351 PNW US FOR SERV MORTBERG UM, 1996, THESIS ROYAL I TECHN MORTBERG UM, 1998, KEY CONCEPTS LANDSCA, P239 NILSSON SG, 1997, ECOLOGICAL B, V46, P61 OPDAM P, 1995, IBIS, V137, P139 OPDAM P, 1997, LANDECONET STUDY BIO REIJNEN R, 1997, BIODIVERS CONSERV, V6, P567 SAUVAJOT RM, 1998, URBAN ECOSYSTEMS, V2, P279 SJOGRENGULVE P, 1996, METAPOPULATIONS WILD SWETNAM RD, 1998, LANDSCAPE URBAN PLAN, V41, P3 TILGHMAN NG, 1987, LANDSCAPE URBAN PLAN, V14, P481 VANDERZANDE AN, 1984, BIOL CONSERV, V30, P1 VANDORP D, 1987, LANDSCAPE ECOLOGY, V1, P59 VILLARD MA, 1999, CONSERV BIOL, V13, P774 WALBRIDGE MR, 1997, URBAN ECOSYSTEMS, V1, P1 WIENS JA, 1994, IBIS, V137, P97 WITH KA, 1997, OIKOS, V78, P151 0921-2973 Landsc. Ecol.ISI:000168194400001Royal Inst Technol, Div Land & Water Resources, S-10044 Stockholm, Sweden. Mortberg, UM, Royal Inst Technol, Div Land & Water Resources, S-10044 Stockholm, Sweden.Englishm~?zMortelliti, A. Boitani, L.2008Interaction of food resources and landscape structure in determining the probability of patch use by carnivores in fragmented landscapes285-298Landscape Ecology233Studies on the distribution of mammalian carnivores in fragmented landscapes have focused mainly on structural aspects such as patch and landscape features; similarly, habitat connectivity is usually associated with landscape structure. The influence of food resources on carnivore patch use and the important effect on habitat connectivity have been overlooked. The aim of this study is to evaluate the relative importance of food resources on patch use patterns and to test if food availability can overcome structural constraints on patch use. We carried out a patch-use survey of two carnivores: the beech marten (Martes foina) and the badger (Meles meles) in a sample of 39 woodland patches in a fragmented landscape in central Italy. We used the logistic model to investigate the relative effects on carnivore distribution of patch, patch neighbourhood and landscape scale variables as well as the relative abundance of food resources. Our results show how carnivore movements in fragmented landscapes are determined not only by patch/landscape structure but also by the relative abundance of food resources. The important take-home message of our research is that, within certain structural limits (e.g. within certain limits of patch isolation), by modifying the relative amount of resources and their distribution, it is possible to increase suitability in smaller/relatively isolated patches. Conversely, however, there are certain thresholds above which an increase in resources will not achieve high probability of presence. Our findings have important and generalizable consequences for highly fragmented landscapes in areas where it may not be possible to increase patch sizes and/or reduce isolation so, for instance, forest regimes that will increase resource availability could be implemented."://WOS:000254112100004 Times Cited: 0WOS:000254112100004(10.1007/s10980-007-9182-7|ISSN 0921-2973|?b 2Morzillo, Anita T. Ferrari, Joseph R. Liu, Jianguo2011An integration of habitat evaluation, individual based modeling, and graph theory for a potential black bear population recovery in southeastern Texas, USA69-81Landscape Ecology261JanPopulation recovery is difficult for species that require large contiguous areas of habitat, particularly within areas of heterogeneous land ownerships. Ecologically, potential for recovery success requires assessment of quantity, quality, and distribution of available habitat. Our objective was to evaluate habitat for a possible Louisiana black bear recovery in southeastern Texas. First, we categorized land cover and identified remote areas of highly suitable habitat. Next, we used the individual based simulation model J-walk to estimate ability of female black bears to move among remote habitat patches. Then, we applied graph theory to J-walk output to evaluate overall connectivity of remote habitat. An estimated 225,626 ha of remote habitat were identified in 901 patches, most of which was located within the eastern half of the study area. Network analysis showed specific areas where targeted conservation efforts may help black bear population expansion throughout the study region. Ultimately, enough habitat area exists to sustain a black bear population and it is best connected among public and private lands largely within the eastern half of the study area. Habitat evaluation will need to be revisited if black bears establish themselves locally and actual habitat use data become available. Regardless, our analysis demonstrates an important first step that may be incorporated into a larger adaptive management framework, updated, and replicated as more-detailed habitat suitability and land use data are available.!://WOS:000286004400007Times Cited: 1 0921-2973WOS:00028600440000710.1007/s10980-010-9536-4}?>Moser, B. Jaeger, J. A. G. Tappeiner, U. Tasser, E. Eiselt, B.2007kModification of the effective mesh size for measuring landscape fragmentation to solve the boundary problem447-459Landscape Ecology2237cross-boundary connections procedure; cutting-out procedure; scale; spatial extent; landscape metrics; landscape indices; spatial heterogeneity; environmental indicators; environmental monitoring; South Tyrol HABITAT FRAGMENTATION; GENE FLOW; PATTERN; METRICS; CONSEQUENCES; POPULATIONS; INDEXES; SCALE; ROADS Mar$Patch-based landscape metrics can be biased by the boundaries and the extent of a reporting unit if the boundaries fragment patches. We call this the "boundary problem''. The effective mesh size m(eff) is a convenient method to quantify landscape fragmentation, that is based on the probability that two points chosen randomly in a region will be connected, e. g., not be separated by roads, railroads, or urban development. The cutting-out (CUT) procedure, used in the original computation of m(eff), suffers from the boundary problem because the boundaries of the reporting units are considered to be additional barriers. Therefore, m(eff) will be underestimated, particularly if reporting units are embedded within the broader landscape. In this paper, we present a solution to overcome this limitation by a new method called "cross-boundary connections'' (CBC) procedure. It attributes the connections between two points that are located in different reporting units to both reporting units. We systematically compare the CBC procedure to the CUT procedure and show that the boundary problem is intrinsic to the CUT procedure, while the CBC procedure is independent of the size and administrative boundaries of reporting units. In addition, we elucidate the superior performance of the new procedure in the case study of South Tyrol where meff is being used for sustainability reporting on the level of municipalities. The new CBC procedure eliminates the bias due to the boundaries and the size of reporting units in measuring landscape fragmentation through m(eff). ://000244455200009 0921-2973ISI:000244455200009<7LMoser, D. Zechmeister, H. G. Plutzar, C. Sauberer, N. Wrbka, T. Grabherr, G.2002gLandscape patch shape complexity as an effective measure for plant species richness in rural landscapes657-669Landscape Ecology177biodiversity prediction bryophytes landscape indices rural landscape vascular plants REGIONAL-SCALE INDICATOR TAXA BIODIVERSITY DIVERSITY PATTERNS ENVIRONMENT FINLAND COMPLEMENTARITY CONSERVATION AGRICULTUREArticleNov/The application of landscape patch shape complexity as a predictor of vascular plant and bryophyte species richness is analysed. Several common complexity indices (shape index, fractal dimension, comparison to the area of the minimum bounding rectangle) are tested for their predictive power for plant species richness. One new robust measure for shape complexity is presented which overcomes some disadvantages of common complexity measures applied to high resolution analysis of agricultural landscapes based on aerial photographs. The new index is based on the number of shape characterising points along a polygon's boundary. This new measure shows promising predictive capabilities for species richness of vascular plants and bryophytes (correlation coefficient: 0.85 for vascular plants, 0.74 for bryophytes).://000179746400006 ISI Document Delivery No.: 624EB Times Cited: 28 Cited Reference Count: 54 Cited References: ABENSPERGTRAUN M, 1996, PACIFIC CONSERVATION, V2, P375 ALARD D, 1999, LANDSCAPE URBAN PLAN, V46, P29 ANDERSEN AN, 1995, BIOL CONSERV, V73, P39 AUSTIN MP, 1996, AUST J ECOL, V21, P154 BALMFORD A, 1996, P ROY SOC LOND B BIO, V263, P1871 CURRIE DJ, 1991, AM NAT, V137, P27 DOUGLAS DH, 1973, CANADIAN CARTOGRAPHE, V10, P112 DRAMSTAD WE, 1998, KEY CONCEPTS LANDSCA, P36 DUELLI P, 1997, AGR ECOSYST ENVIRON, V62, P81 FAITH DP, 1996, BIODIVERS CONSERV, V5, P399 FINDLAY CS, 1997, CONSERV BIOL, V11, P1000 FORMAN RTT, 1992, LANDSCAPE BOUNDARIES, P236 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FORMAN RTT, 1999, LANDSCAPE ECOLOGICAL, P35 GASTON KJ, 2000, PROG PHYS GEOG, V24, P117 GIERLOFFEMDEN HG, 1989, ENZYKLOPADIE KARTOGR, V4 GRIFFITHS GH, 2000, INT J REMOTE SENS, V21, P2685 HAINESYOUNG R, 1996, PROG PHYS GEOG, V20, P418 HEIKKINEN RK, 1997, BIODIVERS CONSERV, V6, P1181 HIETALAKOIVU R, 1999, LANDSCAPE URBAN PLAN, V46, P103 HOOVER SR, 1991, LANDSCAPE ECOL, V5, P125 HOWARD PC, 1998, NATURE, V394, P472 HULSHOFF RM, 1995, LANDSCAPE ECOL, V10, P101 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 KAMMERBAUER J, 1999, AGR ECOSYST ENVIRON, V75, P93 KRUMMEL JR, 1987, OIKOS, V48, P321 LAWTON JH, 1998, NATURE, V391, P72 LINDER HP, 1991, J BIOGEOGR, V18, P509 LOIBL W, 2001, OEFZSS0124 BV SEIB LUOTO M, 2000, PLANT ECOL, V149, P157 MANDELBROT B, 1983, FRACTAL GEOMETRY NAT MANDER U, 1999, LANDSCAPE URBAN PLAN, V46, P169 MARGULES CR, 1987, OECOLOGIA, V71, P229 MCGARIGAL K, 1995, 351 PNV US FOR SERV MILLER JN, 1997, LANDSCAPE ECOL, V12, P137 MILNE BT, 1990, QUANTITATIVE METHODS, P99 NICHOLS WF, 1998, CONSERV BIOL, V12, P371 NOVAKOVA J, 1997, EKOL BRATISLAVA, V16, P233 OBRIEN EM, 1998, J BIOGEOGR, V25, P379 ODUM EP, 1989, CHANGING LANDSCAPES, P137 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 ONEILL RV, 1996, LANDSCAPE ECOL, V11, P169 PALMER MW, 1995, NAT AREA J, V15, P124 PEARSON DL, 1992, CONSERV BIOL, V6, P376 PRENDERGAST JR, 1993, NATURE, V365, P335 RATHERT D, 1999, J BIOGEOGR, V26, P257 REX KD, 1990, LANDSCAPE ECOL, V4, P249 RICHERSON PJ, 1980, AM NAT, V116, P504 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 VIROLAINEN KM, 2000, P ROY SOC LOND B BIO, V267, P1143 WOHLGEMUTH T, 1998, BIODIVERS CONSERV, V7, P159 ZECHMEISTER HG, 2001, BIODIVERS CONSERV, V10, P1609 0921-2973 Landsc. Ecol.ISI:000179746400006Univ Vienna, Dept Conservat Biol Vegetat & Landscape Ecol, A-1091 Vienna, Austria. Moser, D, Univ Vienna, Dept Conservat Biol Vegetat & Landscape Ecol, Althanstr 14, A-1091 Vienna, Austria.English<7- Moss, M. R.2000ZInterdisciplinarity, landscape ecology and the 'Transformation of Agricultural Landscapes'303-311Landscape Ecology153Hagricultural landscapes interdisciplinary landscape ecology land systemsArticleAprThe theme, the 'Transformation of Agricultural Landscapes' is used as a context for examining the current status of landscape ecology and its ability to provide a critical set of responses to a defined range of environmental issues. The links between academic structures and the public demand for landscape-based information raises the potential for landscape ecology to provide solutions. Current approaches within landscape ecology are examined and the dominance of the interdisciplinary approach is found to be deficient. A solution is for the land(scape) system itself to become the initial focus of landscape research. A land system has its own systematic properties which extend beyond the biological dominance of ecosystem science which to many is the basis for landscape ecology. For knowledge of the landscape itself to emerge, landscape ecology must develop more as a discipline with its own theoretical bases and foci than as an interdisciplinary area.://000085293300011 ISI Document Delivery No.: 283UB Times Cited: 21 Cited Reference Count: 15 Cited References: *IALE EX COMM, 1998, B INT ASS LANDSCAPE, V16, P1 DICASTRI F, 1986, GEOJOURNAL, V13, P299 DOMON G, 1995, LANDSCAPE ECOLOGY LA HOBBS R, 1997, LANDSCAPE URBAN PLAN, V37, P1 MOSS MR, 1988, LANDSCAPE ECOLOGY MA NAVEH Z, 1994, LANDSCAPE ECOLOGY TH RICHLING A, 1994, LANDSCAPE RES ITS AP RISSER PG, 1984, NAT HIST SURV SPEC P, V2, P1 RUBEC CDA, 1988, LANDSCAPE ECOLOGY MA, P51 RUBEC CDA, 1992, LANDSCAPE APPROACHES, P61 TJALLINGII SP, 1982, PERSPECTIVES LANDSCA WIENS JA, 1992, LANDSCAPE ECOL, V7, P149 WIKEN E, 1997, REFLECTIONS HOME PLA, P1 ZONNEVELD IS, 1988, LANDSCAPE ECOLOGY MA, P3 ZONNEVELD IS, 1990, CHANGING LANDSCAPES 0921-2973 Landsc. Ecol.ISI:000085293300011Univ Guelph, Fac Environm Sci, Guelph, ON N1G 2W1, Canada. Moss, MR, Univ Guelph, Fac Environm Sci, Guelph, ON N1G 2W1, Canada.English<7*Mou, P. Jones, R. H. Guo, D. L. Lister, A.2005yRegeneration strategies, disturbance and plant interactions as organizers of vegetation spatial patterns in a pine forest971-987Landscape Ecology2082Dichanthelium; forest disturbance; geostatistics; Myrica cerifera; Pinus elliottii; plant regeneration; Quercus; Rhus copallina; spatial heterogeneity OLD-FIELD SUCCESSION; TREE ESTABLISHMENT; SPECIES-RICHNESS; SOUTH-CAROLINA; SOIL-MOISTURE; HETEROGENEITY; COMMUNITIES; VARIABILITY; ENVIRONMENT; MECHANISMSArticleDecTo determine how vegetation pattern in early successional forests may be related to plant traits and types of disturbance, we measured percent cover of individual taxa annually in a South Carolina Pinus elliottii forest, starting one year before, and ending four years after harvest and tree girdling disturbances were applied. The 17 most important taxa surveyed were grouped into four regeneration strategies chosen a priori, and the spatial patterns of these groups and of the soil were investigated using global variability, semivariograms and kriged maps. We also examined spatial correlations across years, across taxa, and between species and soil disturbance. Seed bank taxa represented by Dichanthelium spp. increased rapidly and formed large patches, and then quickly declined. Taxa that regenerate by newly dispersed seeds, represented by Rhus copallina and Rubus spp. occurred at first in a few patches, and became widespread later. Stump sprouters, represented by Quercus spp. and Myrica cerifera, had rapid increases in cover, but their spatial patterns were largely determined by their pre-disturbance patterns. Prunus serotina, which relies on both sprouting and dispersed seed, had moderate cover and a random distribution. Within-species temporal correlation of spatial pattern was lower in girdled than in harvested plots, and was not clearly related to regeneration strategy. Forest floor disturbance was patchy and affected the pattern of Dichanthelium spp. in the harvested plots. Negative correlations between herbs and woody plants in harvested plots reflected the role of biotic (i.e., successional) filters on vegetation pattern. Surprisingly, no spatial correlations were detected between the nitrogen fixer, Myrica cerifera and other taxa in this N-limited system. In comparing the spatial and temporal patterns, we found kriged maps more informative than analysis of semivariograms alone. The maps and correlation statistics demonstrated that regeneration traits, spatial patterns of soil disturbances, and interactions among taxa influence dynamics of the spatial patterns of the plants. We also demonstrated that disturbance types affected the importance and interactions among these three factors, and caused different spatial patterns of the plant taxa.://000233036400006 - ISI Document Delivery No.: 980RR Times Cited: 0 Cited Reference Count: 57 Cited References: BATTLES JJ, 2001, FOREST ECOL MANAG, V146, P211 BEATTY SW, 2003, HERBACEOUS LAYER FOR, P177 CALVINOCANCELA M, 2002, J ECOL, V90, P775 CHRISTENSEN NL, 2000, N AM TERRESTRIAL VEG, P397 CODY ML, 2000, J VEG SCI, V11, P251 COLLINS SL, 2000, OIKOS, V91, P285 DANELL K, 1991, ECOLOGY, V72, P1350 DAVIS JC, 1986, STAT DATA ANAL GEOLO, P646 DENSLOW JS, 1985, ECOLOGY NATURAL DIST, P307 DESTEVEN D, 1991, ECOLOGY, V72, P1066 DESTEVEN D, 1991, ECOLOGY, V72, P1076 DUTILLEUL P, 1993, BIOMETRICS, V49, P305 EHRENFELD JG, 1997, J ECOL, V85, P785 FOWLER N, 1982, J ECOL, V70, P77 FRIEDMAN SK, 2001, J ECOL, V89, P538 GILLIAM FS, 2003, HERBACEOUS LAYER FOR, P198 GRIFFITH DA, 1978, GEOGR ANAL, V10, P296 GROSS KL, 1995, J ECOL, V83, P357 GRUBB PJ, 1977, BIOL REV, V52, P107 GUO D, 2002, J ECOL, V90, P338 GUO DL, 2004, OECOLOGIA, V138, P613 HARPER JL, 1965, J ECOL, V53, P273 HOOK PB, 1991, PLANT SOIL, V138, P247 HUENNEKE LF, 1986, AM MIDL NAT, V115, P328 ISAAKS EH, 1989, APPL GEOSTATISTICS, P561 JACKSON RB, 1993, J ECOL, V81, P683 JONSSON BG, 1990, J ECOL, V78, P924 LAVOREL S, 1998, ACTA OECOL, V19, P227 LECHOWICZ MJ, 1991, J ECOL, V79, P687 LEGENDRE P, 1993, ECOLOGY, V74, P1659 LI H, 1995, OIKOS, V73, P280 LISTER AJ, 2000, CAN J FOREST RES, V30, P145 LODHI MAK, 1989, J CHEM ECOL, V15, P429 MEREDIEU C, 1996, SOIL SCI, V161, P29 MITCHELL RJ, 1993, ECOL APPL, V3, P167 MOU P, 1993, J APPL ECOL, V30, P661 MUELLERDOMBOIS D, 1974, AIMS METHODS VEGETAT, P547 NICOTRA AB, 1999, ECOLOGY, V80, P1908 PALMER MW, 1990, COENOSES, V5, P79 PALMER MW, 1990, J VEG SCI, V1, P57 PALMER MW, 2000, J VEG SCI, V11, P841 PASTOR J, 1999, ECOSYSTEMS, V2, P439 PICKETT STA, 1985, ECOLOGY NATURAL DIST, P472 PICKETT STA, 1995, SCIENCE, V269, P331 REED RA, 1993, J VEG SCI, V4, P329 ROBERTSON GP, 1994, EXPLOITATION ENV HET, P237 ROSSI RE, 1992, ECOL MONOGR, V62, P277 SCHLESINGER WH, 1996, ECOLOGY, V77, P364 SUMMER U, 2000, OECOLOGIA, V122, P284 TOLLIVER KS, 1995, AM MIDL NAT, V133, P256 WALLACE CSA, 2000, COMPUT GEOSCI, V26, P397 WATT AS, 1947, J ECOL, V35, P1 WIEGAND T, 1997, J VEG SCI, V8, P163 WILLEMS JH, 1993, J VEG SCI, V4, P203 WILSON SD, 2000, ECOLOGICAL CONSEQUEN, P53 WOODS KD, 2000, J ECOL, V88, P167 YODZIS P, 1986, COMMUNITY ECOLOGY, P480 0921-2973 Landsc. Ecol.ISI:0002330364000060Univ N Carolina, Dept Biol, Greensboro, NC 27402 USA. Virginia Tech, Dept Biol Sci, Blacksburg, VA 24061 USA. Peking Univ, Dept Ecol, Beijing 100871, Peoples R China. US Forest Serv, USDA, NE Expt Stn, Newtown Sq, PA 19073 USA. Mou, P, Univ N Carolina, Dept Biol, Greensboro, NC 27402 USA. ppmou@uncg.eduEnglishq<7_=Mouillot, F. Ratte, J. P. Joffre, R. Moreno, J. M. Rambal, S.2003bSome determinants of the spatio-temporal fire cycle in a mediterranean landscape (Corsica, France)665-674Landscape Ecology187fire history fire regime land use land abandonment landscape analysis Mediterranean basin PLANT-COMMUNITIES SPATIAL PATTERNS CLIMATE-CHANGE SOIL-MOISTURE FOREST-FIRES VEGETATION SPAIN DYNAMICS GERMINATION CALIFORNIAArticleLBased on recent needs to accurately understand fire regimes and post- fire vegetation resilience at a supra- level for carbon cycle studies, this article focusses on the coupled history of fire and vegetation pattern for 40 years on a fire- prone area in central Corsica ( France ). This area has been submitted since the beginning of the 20th century to land abandonment and the remaining land management has been largely controlled by frequent fires. Our objectives were to rebuild vegetation and fire maps in order to determine the factors which have driven the spatial and temporal distribution of fires on the area, what were the feed backs on the vegetation dynamics, and the long- term consequences of this inter- relationship. The results show a stable but high frequency of small fires, coupled with forest expansion over the study period. The results particularly illustrate the spatial distribution of fires according to topography and vegetation, leading to a strong contrast between areas never burnt and areas which have been burnt up to 7 times. Fires, when occuring, affect on average 9 to 12% of the S, SE and SW facing slopes ( compared to only 2 to 5% for the N facing slopes ), spread recurrently over ridge tops, affect all the vegetation types but reburn preferentially shrublands and grasslands. As these fire- proning parameters have also been shown to decrease the regeneration capacity of forests, this study highlights the needs in spatial studies ( both in terms of fire spread and vegetation dynamic ) to accurately apprehend vegetation dynamic and functionning in fire- prone areas.://000186639000003 ISI Document Delivery No.: 744NR Times Cited: 7 Cited Reference Count: 53 Cited References: *FAO, 2001, GLOB FOR FIR ASS 199 AMANDIER L, 1984, ELEMENTS ZONAGE AGRO ARIANOUTSOUFARA.M, 1984, ACTA OECOL-OEC PLANT, V5, P387 BARRY JP, 1975, HIST VEGETATION COMM BEVEN K, 1983, J HYDROL, V65, P139 BOLSTAD PV, 1998, LANDSCAPE ECOL, V13, P271 CERUTTI F, 1990, REV FORESTIERE FRANC, V42, P46 CRAMER W, 2001, FOREST ECOL MANAG, V147, P1 DEBUSSCHE M, 2001, J VEG SCI, V12, P81 DIAZDELGADO R, 2001, FOREST ECOL MANAG, V147, P67 FARACO AM, 1993, ROLE FIRE MEDITERRAN, P101 GARCIAFAYOS P, 1998, ACTA OECOL, V19, P357 GODRON M, 1968, CODE RELEVE METHODIQ HERRANZ JM, 1997, ECOSCIENCE, V4, P86 IVERSON LR, 1997, LANDSCAPE ECOL, V12, P331 JOFFRE LM, 1981, COMPTES PATRIMOINE N JOFFRE LM, 1982, EVOLUTION UTILISATIO JOFFRE R, 1982, FOURRAGES, V91, P73 LAVOREL S, 1995, LANDSCAPE ECOL, V10, P277 LEHOUEROU HN, 1987, ECOLOGIA MEDITERRANE, V13, P13 LEHOUEROU HN, 1992, CLIMATIC CHANGE MEDI, P175 LOOKINGBILL TR, 2000, J VEG SCI, V11, P607 MARTIN P, 1992, AUST J BOT, V40, P717 MESLEARD F, 1991, J VEG SCI, V2, P155 MILLER PC, 1983, OECOLOGIA, V56, P385 MOODY A, 2001, J VEG SCI, V12, P41 MORENO JM, 1998, LARGE FOREST FIRES, P159 MOUILLOT F, 2001, FOREST ECOL MANAG, V147, P75 MOUILLOT F, 2002, GLOBAL CHANGE BIOL, V8, P423 MOUILLOT F, 2003, IN PRESS J VEGETATIO NOBLE IR, 1980, VEGETATIO, V43, P5 NOYMEIR I, 1995, J VEG SCI, V6, P701 OSTENDORF B, 1993, LANDSCAPE ECOL, V8, P229 PAUSAS JG, 1997, J VEG SCI, V8, P703 PAUSAS JG, 1998, FIRE MANAGEMENT LAND, P327 PAUSAS JG, 1999, ACTA OECOL, V20, P499 PEREZ B, 1998, PLANT ECOL, V139, P91 RAMBAL S, 1998, LARGE FOREST FIRES, P187 RICOTTA C, 2001, ECOL MODEL, V141, P307 ROTHERMEL RC, 1972, MATH MODEL PREDICTIN SCHIMEL D, 2000, SCIENCE, V287, P2004 SHAKESBY RA, 1993, INT J WILDLAND FIRE, V3, P95 TRABAUD L, 1973, NOTICE CARTES GRANDE TRABAUD L, 1981, VEGETATIO, V46, P105 TRABAUD L, 1985, FOREST ECOL MANAG, V13, P137 TRABAUD L, 1996, LANDSCAPE ECOL, V11, P215 TURNER MG, 1989, OIKOS, V55, P121 TURNER MG, 1997, ECOL MONOGR, V67, P411 VAZQUEZ A, 2001, FOREST ECOL MANAG, V147, P55 VILA M, 2001, FOREST ECOL MANAG, V147, P3 WESTERN AW, 1999, WATER RESOUR RES, V35, P797 WITH KA, 1999, LANDSCAPE ECOL, V14, P73 ZHENG DL, 1996, LANDSCAPE ECOL, V11, P3 0921-2973 Landsc. Ecol.ISI:000186639000003CNRS, CEFE, DREAM Unit, F-34293 Montpellier 5, France. Univ Castilla La Mancha, Dept Environm Sci, E-45071 Toledo, Spain. Univ Corsica, Lab Biol & Ecol, F-20250 Corte, France. Mouillot, F, Carnegie Inst Washington, Dept Global Ecol, 260 Panama St, Stanford, CA 94305 USA.English <7<Mouillot, F. Ratte, J. P. Joffre, R. Mouillot, D. Rambal, S.2005qLong-term forest dynamic after land abandonment in a fire prone Mediterranean landscape (central Corsica, France)101-112Landscape Ecology201land cover change; landscape patterns; Mediterranean-type ecosystem; transition matrix SOIL SEED BANK; QUERCUS-ILEX L; VEGETATION DYNAMICS; PINUS-HALEPENSIS; FUNCTIONAL TYPES; PLANT-COMMUNITIES; ERICA-ARBOREA; PATTERN; SHRUB; GERMINATIONArticleJanTwo hundred years of landscape changes were studied on a 3,760 ha area of central Corsica (France) representing a typical Mediterranean environment. Different historical sources, including an accurate land-cover map from 1774 and statistics on land cover from 1848 and 1913, were used. Three additional maps (1960, 1975 and 1990) were drawn, and a complete fire history from 1957 to 1997 was created. Forests expanded slowly by a border effect. Forest expansion was more rapid in unburnt sites (0.59% per year) than in burnt sites (0.23% per year), mostly because the initial amount of forests was greater. Because of the border effect, the combination of past landscape pattern and short distance colonization abilities of forest species may have allowed the shrublands to persist in some places after land abandonment. This persistence may explain the pattern of fire in the landscape, since shrubland burn more readily than forests.://000231223900008 ] ISI Document Delivery No.: 955KD Times Cited: 2 Cited Reference Count: 75 Cited References: 1744, HIST UNIVERSELLE, CH11 1968, CODE RELEVE METHODIQ 1987, J VEGETATION SCI, V6, P465 1987, PLANT RESPONS STRESS 1996, ECOLOGY, P94 1998, LANDSCAPE DEGRADATIO, P127 ALBITRECCIA A, 1942, PLAN TERRIER CORSE 1 AMANDIER L, 1984, ELEMENTS ZONAGE AGRO BACILIERI R, 1994, ACTA OECOL, V15, P417 BARBARA PF, 1990, ADV PHOTOCHEM, V15, P1 BARRY JP, 1975, HIST VEGETATION UNE BOURCET J, 1996, REV FOR FR, V48, P563 BRAGG TB, 1976, J RANGE MANAGE, V29, P19 CALLAWAY RM, 1993, ECOLOGY, V74, P1567 CARATINI R, 1995, HIST PEUPLE CORSE CARCAILLET C, 1997, J VEG SCI, V8, P85 CARMEL Y, 1999, PLANT ECOL, V145, P243 CARMEL Y, 2001, ECOL APPL, V11, P268 DEBUSSCHE M, 1987, ACTA OECOL, V8, P317 DEBUSSCHE M, 1992, LANDSCAPE ECOL, V6, P133 DEBUSSCHE M, 1999, GLOBAL ECOL BIOGEOGR, V8, P3 DEBUSSCHE M, 2001, J VEG SCI, V12, P81 DESIMONE SA, 2001, ECOL APPL, V11, P1101 FERRANDIS P, 1999, PLANT ECOL, V144, P103 FRANKLIN J, 1998, J VEG SCI, V9, P733 FUENTES ER, 1984, OECOLOGIA, V62, P405 GARCIAFAYOS P, 1995, J VEG SCI, V6, P691 GARCIAFAYOS P, 1998, ACTA OECOL, V19, P357 GARCIARUIZ JM, 1996, LANDSCAPE ECOL, V11, P267 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GREENE DF, 1996, ECOLOGY, V77, P595 GRIME JP, 1977, AM NAT, V111, P1169 HILBERT DW, 1990, ACTA OECOL, V11, P181 HOLT RD, 1995, ECOLOGY, V76, P1610 JOFFRE LM, 1981, COMPTES PATRIMOINE N JOFFRE LM, 1982, EVOLUTION UTILISATIO KADMON R, 1999, REMOTE SENS ENVIRON, V68, P164 KEELEY JE, 1994, ECOLOGY BIOGEOGRAPHY, P239 LAVOREL S, 1995, LANDSCAPE ECOL, V10, P277 LEHOUEROU HN, 1992, CLIMATIC CHANGE MEDI, P175 LENCLUD G, 1980, ECOLOGIA MEDITERRANE, V6, P173 LEPART J, 1992, LANDSCAPE BOUNDARIES, P76 LEPART J, 1993, BIOGEOGRAPHY MEDITER, P159 LOOKINGBILL TR, 2000, J VEG SCI, V11, P607 MAST JN, 1997, FOREST ECOL MANAG, V93, P181 MESLEARD F, 1991, J VEG SCI, V2, P155 MOREIRA F, 2001, LANDSCAPE ECOL, V16, P557 MOUILLOT F, 1998, 14 C FIR FOR MET LUS MOUILLOT F, 2002, GLOBAL CHANGE BIOL, V8, P423 MOUILLOT F, 2003, LANDSCAPE ECOL, V18, P665 NEEMAN G, 1996, J VEG SCI, V7, P465 NEEMAN G, 1999, PLANT ECOL, V145, P235 NOBLE IR, 1980, VEGETATIO, V43, P5 NOBLE IR, 1981, CONCEPTS MODELS SUCC PAUSAS JG, 1999, J VEG SCI, V10, P717 PAUSAS JG, 1999, PLANT ECOL, V140, P27 PAUSAS JG, 2003, J VEG SCI, V14, P365 PAUSAS JG, 2004, CLIMATIC CHANGE, V63, P337 PIGOTT CD, 1993, J ECOL, V81, P557 PITTE JR, 1986, TERRES CASTANIDES POESEN JW, 1998, GEOMORPHOLOGY, V23, P323 REILLE M, 1992, NEW PHYTOL, V122, P359 ROCHE P, 1998, J VEG SCI, V9, P221 ROUSSEAU JJ, 1765, PROJET CONSTITUTION SMITH BE, 1993, B TORREY BOT CLUB, V120, P229 TATONI T, 1994, ACTA OECOL, V15, P43447 TRABAUD L, 1973, NOTICE CARTES GRANDE TRABAUD L, 1994, INT C FOR FIR RES, V2, P545 TRABAUD L, 1996, LANDSCAPE ECOL, V11, P215 TRABAUD L, 1997, CAN J BOT, V75, P1012 TURNER MG, 1989, OIKOS, V55, P121 TURNER MG, 1997, ECOL MONOGR, V67, P411 VAZQUEZ A, 2001, FOREST ECOL MANAG, V147, P55 VERDU M, 1996, FUNCT ECOL, V10, P275 WITH KA, 1999, LANDSCAPE ECOL, V14, P73 0921-2973 Landsc. Ecol.ISI:000231223900008CNRS, DREAM CEFE, IRD UR 060, F-34293 Montpellier, France. CNRS, UMR 5119, UM2, F-34095 Montpellier, France. Mouillot, F, CNRS, DREAM CEFE, IRD UR 060, F-34293 Montpellier, France. mouillot@cefe.cnrs.frEnglish|?E_Mudrak, Erika L. Schafer, Jennifer L. Fuentes-Ramirez, Andres Holzapfel, Claus Moloney, Kirk A.2014VPredictive modeling of spatial patterns of soil nutrients related to fertility islands491-505Landscape Ecology293MarvIn arid shrublands, soil resources are patchily distributed around shrub canopies, forming well-studied "islands of fertility.'' While soil nutrient patterns have previously been characterized quantitatively, we develop a predictive model that explicitly considers the distance from shrubs of varying canopy sizes. In 1-ha macroplots in both the Sonoran and Mojave Deserts, we used Plant Root Simulator (TM) probes to measure nutrient availability along transects extending north and south from creosote bushes (Larrea tridentata). We modeled the decline of nutrients with distance from focal shrubs using hierarchical mixed models that included the effects of transect direction and shrub canopy size. Of the nutrients considered, nitrogen and potassium had the strongest response to distance from focal shrubs. In the Sonora, both depended on canopy size and had different patterns to the north versus the south. In the Mojave, potassium depended on size and direction, but nitrogen only on canopy size. We used the fitted model equations and the location and canopy size of all Larrea shrubs within the macroplots to estimate nutrient concentrations at a 20 cm resolution. This produced maps showing nutrient "hotspots'' centered on Larrea. Our models predicted up to 60 % of the variation in nutrient availability the following growing season. Our models efficiently used a moderate number of sample locations to predict nutrient concentrations over a large area, given easily measured values of shrub size and location. Our method can be applied to many systems with patchily distributed resources focused around major structural landscape features.!://WOS:000331935500011Times Cited: 1 0921-2973WOS:00033193550001110.1007/s10980-013-9979-5,<7Muller, M. R. Middleton, J.1994QA Markov model of land-use change dynamics in the Niagara region, Ontario, Canada151-157Landscape Ecology92ArticleJuniRegional Niagara is the site of an intense three-way land-use conflict among urban, agricultural and natural uses. Large scale spatial and temporal land-use data were used to investigate the dynamics of land-use change in this area. A first order Markov chain was used as a stochastic model to make quantitative comparisons of the land-use changes between discrete time periods extending from 1935 to 1981. The Markov model allowed for two main conclusions about the historic dynamics of land-use change in the Regional Municipality of Niagara. 1. The urbanization of agricultural land was the predominant land-use change. 2. A continuing 'exchange' of land area occurs between wooded and agricultural land-use categories that has little effect on the net amount of wooded land but which could undermine the long-term ecological value of remaining natural areas in Niagara.://A1994NU09400008 IISI Document Delivery No.: NU094 Times Cited: 23 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1994NU09400008ZMULLER, MR, BROCK UNIV,INST URBAN & ENVIRONM STUDIES,ST CATHARINES L2S 3A1,ONTARIO,CANADA.English|7Munoz-Reinoso, J. C.2009ZBoundaries and scales in shrublands of the DoA +/- ana Biological Reserve, southwest Spain509-518Landscape Ecology244boundaries donana ecocline ecotone nested hierarchy split moving window shifting transition stationary transition donana-national-park plant community boundaries sw spain ecological boundaries west spain vegetation discontinuities dynamics ecotones modelApr*To verify that the stabilized sand dunes of DoA +/- ana, southwest Spain, are hierarchically nested, vegetation was sampled along topographic gradients at three spatial scales and Split Moving Window Boundary Analysis was applied to identify vegetation boundaries and ecotones. At small scale, only one window width was used, while for boundaries detection at upper scales the information from five windows was pooled. Environmental factors controlling plant composition were studied along topographic gradients, and diversity was estimated within the boundaries. According to several theoretical frameworks, I discuss the types of boundaries produced at different scales. Lower level boundaries are characterized by transitory gradients linked to local exchanges; intermediate boundaries are symmetric and very stable over the time; the large scale boundary is asymmetric with strong inherent abiotic constraints reinforced by strong biotic feedbacks. In spite of a similar plant composition, a plant community, the mixed shrub, works as an ecocline or an ecotone depending on the spatial scale considered. A certain parallelism exists between shrub composition along dune slopes and dune generations; however, processes at upper scale constraint plant composition at lower scale resulting in different mature formations.://000263898100006-414XI Times Cited:0 Cited References Count:45 0921-2973ISI:000263898100006Munoz-Reinoso, JC Univ Seville, Dept Biol Vegetal & Ecol, Apdo 1095, E-41080 Seville, Spain Univ Seville, Dept Biol Vegetal & Ecol, E-41080 Seville, SpainDoi 10.1007/S10980-009-9325-0English(<7 Munoz-Reinoso, J. C. Novo, F. G.2005HMultiscale control of vegetation patterns: the case of Donana (SW Spain)51-61Landscape Ecology201Donana; hydrology; sand dunes; scale; split moving window; vegetation pattern; water availability NATIONAL-PARK; DUNE-SLACK; STABILIZED DUNES; NEW-ZEALAND; DISCONTINUITIES; FLUCTUATION; ECOSYSTEMS; SUCCESSION; DISTANCE; ECOLOGYArticleJanThe early studies about the plant ecology of Donana carried out at a small scale showed that the main process controlling vegetation composition of the stabilized dunes was soil water availability. However, the extrapolation of this model to larger spatial scales failed to explain observed vegetation patterns. In this work, the vegetation patterns and the processes causing them are studied at a larger scale. Data of topography, soil pH, electrical conductivity, and available iron allowed to distinguish three large geomorphologic zones on the stabilized dunes of the Donana Biological Reserve which correspond to different dune building episodes. Different dune episodes showed differences in both water table depth and dynamics, which are due to groundwater flow systems of different scale. It is further manifested by differences in shrub composition. The results show that geomorphology controls the vegetation pattern at different scales mediated through water availability. Differences in water availability are due to the connection to groundwater flow systems of contrasted scale. On a small scale (10-10(2) in), along dune slopes, there is a gradient from dune ridges to slacks, from xerophyte to hygrophyte vegetation types. On a mesoscale (10(2)-10(3) m), there are several dune episodes with variable topographic altitude, dominated by different types of xerophytes. On a regional scale (>10(3) m), the discharges of the regional aquifer produce strong environmental and biotic stresses resulting in a mixed community.://000231223900004 ISI Document Delivery No.: 955KD Times Cited: 0 Cited Reference Count: 52 Cited References: *ITGE, 1992, HIDR PARQ NAC DON EN ALES RF, 1992, LANDSCAPE ECOL, V7, P3 ALLEN TEH, 1982, HIERARCHY PERSPECTIV ALLEN TEH, 1992, UNIFIED ECOLOGY ALLIER CF, 1974, MAPA ECOLOGICO RESER BERNALDEZ FG, 1971, C PHYTOSOCIOLOGIQUES, V1, P185 BERNALDEZ FG, 1975, ISRAEL J BOT, V24, P106 BERNALDEZ FG, 1975, ISRAEL J BOT, V24, P173 CORNELIUS JM, 1991, ECOLOGY, V72, P2057 CORONA MG, 1988, VEGETATIO, V75, P73 CRAWFORD RMM, 1989, STUDIES PLANT SURVIV CUSTODIO E, 1992, COMPORTAMIENTO PAPEL CUSTODIO E, 1992, HIDROGEOL RECURS HID, V16, P425 CUSTODIO E, 1995, BASES ECOLOGICAS PAR, P43 DICASTRI F, 1988, GEO J, V17, P5 DICKINSON KJM, 1994, J BIOGEOGR, V21, P259 FORMAN RTT, 1986, LANDSCAPE ECOLOGY GROOTJANS AP, 1991, J VEG SCI, V2, P545 JOHNSTON CA, 1992, LANDSCAPE BOUNDARIES, P107 LEGENDRE L, 1983, NUMERICAL ECOLOGY LUDWIG JA, 1987, ECOLOGY, V68, P448 MERINO J, 1976, OECOLOG PLANTAR, V11, P1 MERINO J, 1981, COMPONENTS PRODUCTIV, P197 MIELKE PW, 1991, EARTH-SCI REV, V31, P55 NAVEH Z, 1984, LANDSCAPE ECOLOGY TH NOVO FG, 1979, ECOLOGICAL PROCESSES, P571 NOVO FG, 1997, ECOSY WORLD C, V2, P453 OJEDA JF, 1987, ICONA MAPA MONOG, V49 ONEILL RV, 1989, LANDSCAPE ECOL, V3, P193 RANWELL DS, 1972, ECOLOGY SALT MARSHES REINOSO JC, 1996, LIMNETICA, V12, P53 REINOSO JCM, 1997, THESIS U SEVILLA SPA REINOSO JCM, 2001, J COASTAL RES, V17, P90 REINOSO JCM, 2001, J COASTAL RES, V242, P197 RODRIGUEZRAMIREZ A, 1996, QUATERNARY SCI REV, V15, P803 ROLDAN I, 1993, THESIS U SEVILLA SPA SUSO J, 1993, J HYDROL, V141, P239 SYKES MT, 1987, VEGETATIO, V71, P13 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P245 TURNER SJ, 1990, QUANTITATIVE METHODS, P17 VALDES B, 1987, FLORA VASCULAR ANDAL VANDENASSEM J, 1967, BEHAVIOUR S, V16, P1 VANDERMAAREL E, 1990, J VEG SCI, V1, P135 VANDERMAAREL E, 1997, ECOSY WORLD C, V2, P505 VANLEEUWEN CG, 1971, ACTA BOT NEERL, V20, P191 VANNEY JR, 1979, TYPES RELIEFS LITTOR WEBSTER R, 1973, MATH GEOL, V5, P27 WIENS JA, 1985, OIKOS, V45, P421 WIENS JA, 1989, FUNCT ECOL, V3, P385 WIERENGA PJ, 1987, J ARID ENVIRON, V13, P53 ZAR JH, 1984, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000231223900004Univ Sevilla, Dept Organism Biol & Ecol, Seville, Spain. Munoz-Reinoso, JC, Univ Sevilla, Dept Organism Biol & Ecol, Seville, Spain. reinoso@us.esEnglishڽ7 GMuratet, Audrey Lorrillière, Romain Clergeau, Philippe Fontaine, Colin2013TEvaluation of landscape connectivity at community level using satellite-derived NDVI95-105Landscape Ecology281Springer Netherlands|Graph theory Flux Habitat fragmentation Least-cost path Network Permeability Plant community Satellite imagery Urban ecology 2013/01/01+http://dx.doi.org/10.1007/s10980-012-9817-1 0921-2973Landscape Ecol10.1007/s10980-012-9817-1English<7Murwira, A. Skidmore, A. K.2005qThe response of elephants to the spatial heterogeneity of vegetation in a Southern African agricultural landscape217-234Landscape Ecology202African elephant; dominant scale; intensity; NDVI; spatial heterogeneity; windowed variogram ECOLOGY; PATTERN; HABITAT; ZIMBABWE; FOREST; SCALE; NDVI; CLASSIFICATION; MOVEMENTS; ECOSYSTEMArticleFebBased on the agricultural landscape of the Sebungwe in Zimbabwe, we investigated whether and how the spatial distribution of the African elephant (Loxodonta africana) responded to spatial heterogeneity of vegetation cover based on data of the early 1980s and early 1990s. We also investigated whether and how elephant distribution responded to changes in spatial heterogeneity between the early 1980s and early 1990s. Vegetation cover was estimated from a normalised difference vegetation index (NDVI). Spatial heterogeneity was estimated from a new approach based on the intensity (i.e., the maximum variance exhibited when a spatially distributed landscape property such as vegetation cover is measured with a successively increasing window size or scale) and dominant scale (i.e., the scale or window size at which the intensity is displayed). We used a variogram to quantify the dominant scale (i.e., range) and intensity (i.e., sill) of NDVI based congruent windows (i.e., 3.84 km x 3.84 km in a 61 km x 61 km landscape). The results indicated that elephants consistently responded to the dominant scale of spatial heterogeneity in a unimodal fashion with the peak elephant presence occurring in environments with dominant scales of spatial heterogeneity of around 457-734 m. Both the intensity and dominant scale of spatial heterogeneity predicted 65 and 68% of the variance in elephant presence in the early 1980s and in the early 1990s respectively. Also, changes in the intensity and dominant scale of spatial heterogeneity predicted 61% of the variance in the change in elephant distribution. The results imply that management decisions must take into consideration the influence of the levels of spatial heterogeneity on elephants in order to ensure elephant persistence in agricultural landscapes.://000230299600008 ISI Document Delivery No.: 942RN Times Cited: 0 Cited Reference Count: 63 Cited References: *ITC RG, 2002, INT LAND WAT INF SYS *IUCN, 2002, IUCN RED LIST THREAT ADLER PB, 2001, OECOLOGIA, V128, P465 BIRKY AK, 2001, ECOL MODEL, V143, P43 BURTON M, 1999, ECOL ECON, V30, P93 COHEN WB, 1990, REMOTE SENS ENVIRON, V34, P167 CUMMING DHM, 1981, PROBLEMS MANAGEMENT, P91 CUMMING DHM, 1997, LAND USE CHANGES WIL, V1 CURRAN PJ, 1988, REMOTE SENS ENVIRON, V24, P493 DIGGLE PJ, 1983, STAT ANAL SPATIAL PO DUNHAM KM, 1986, AFR J ECOL, V24, P287 DUTOIT JT, 1995, AMBIO, V24, P2 DUTOIT R, 1985, NEW SCI, V105, P33 FAHRIG L, 2001, BIOL CONSERV, V100, P65 FOTHERINGHAM AS, 2000, QUANTITATIVE GEOGRAP GOODCHILD MF, 1997, SCALE REMOTE SENSING, P1 GOWARD SN, 1987, ADV SPACE RES, V7, P165 GRIFFITH JA, 2000, LANDSCAPE URBAN PLAN, V52, P45 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 GUY PR, 1976, E AFR WILDL J, V14, P285 GUY PR, 1976, S AFR J WILDL RES, V6, P55 HILL MJ, 2003, REMOTE SENS ENVIRON, V84, P367 HOARE RE, 1999, CONSERV BIOL, V13, P633 JANSSON G, 2002, FOREST ECOL MANAG, V157, P77 JOHNSON AR, 1992, LANDSCAPE ECOL, V7, P63 KAREIVA P, 1995, NATURE, V373, P299 KERR JT, 2003, IN PRESS TRENDS ECOL KINGDON J, 2001, KINGDON FIELD GUIDE LAM L, 2001, INTRO S PLUS CANDIEN LEGENDRE P, 1989, VEGETATIO, V80, P107 LEGENDRE P, 1998, NUMERICAL ECOLOGY LEVIN SA, 1992, ECOLOGY, V73, P1943 LI X, 2001, J ARID ENVIRON, V48, P521 LOGAN BI, 2002, GEOFORUM, V33, P1 LOS SO, 1998, LINKAGES GLOBAL VEGE LYNAM AJ, 1999, BIOL CONSERV, V91, P191 MCGRIGAL K, 2002, GRADIENT CONCEPT LAN MIRWIRA A, 2003, INT J GEOGRAPHICAL I MORRISON ML, 1992, WILDLIFE HABITAT REL MYERS DE, 1997, SCALE REMOTE SENSING, P273 OINDO BO, 2001, INT J REMOTE SENSORS, V23, P285 OSBORN FV, 2003, AFR J ECOL, V41, P68 PEARSON DM, 2002, J ENVIRON MANAGE, V64, P85 PICKETT STA, 1997, WILDLIFE LANDSCAPE E, P101 RIETKERK M, 2002, ECOL MODEL, V149, P1 SAID MY, 2003, MULTISCALE PERSPECTI SCHOLES RJ, 1997, VEGETATION SO AFRICA, P258 SONG C, 2001, REMOTE SENS ENVIRON, V75, P230 SOUTHWOOD TRE, 1977, J ANIM ECOL, V46, P337 SPARROW AD, 1999, TRENDS ECOL EVOL, V14, P422 TIMBERLAKE JR, 1993, KIRKIA, V14, P171 TREITZ P, 2000, REMOTE SENS ENVIRON, V72, P268 TUCKER CJ, 1986, INT J REMOTE SENS, V7, P1395 TURNER DP, 1999, REMOTE SENS ENVIRON, V70, P52 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1997, WILDLIFE LANDSCAPE E, P331 WACKERNAGEL H, 1998, MULTIVARIATE GEOSTAT WALSH JS, 1997, SCALE REMOTE SENSING, P27 WALSH SJ, 2001, AGR ECOSYST ENVIRON, V85, P47 WEBSTER R, 2000, GEODERMA, V97, P149 WIENS JA, 1989, FUNCT ECOL, V3, P385 WITH KA, 1995, ECOLOGY, V76, P2446 YAPP RH, 1922, J ECOL, V10, P1 0921-2973 Landsc. Ecol.ISI:000230299600008Univ Zimbabwe, Dept Geog & Environm Sci, Harare, Zimbabwe. Int Inst Geoinformat Sci & Earth Observ ITC, NL-7500 AA Enschede, Netherlands. Murwira, A, Univ Zimbabwe, Dept Geog & Environm Sci, POB MP167, Harare, Zimbabwe. murwira@itc.nlEnglish&۽7 Musacchio, LauraR2013AKey concepts and research priorities for landscape sustainability995-998Landscape Ecology286Springer Netherlands 2013/07/01+http://dx.doi.org/10.1007/s10980-013-9909-6 0921-2973Landscape Ecol10.1007/s10980-013-9909-6Englishڽ7 Musacchio, LauraR2013rCultivating deep care: integrating landscape ecological research into the cultural dimension of ecosystem services 1025-1038Landscape Ecology286Springer NetherlandsoEcosystem services Landscape sustainability Urban landscapes Biodiversity Landscape perception Human well-being 2013/07/01+http://dx.doi.org/10.1007/s10980-013-9907-8 0921-2973Landscape Ecol10.1007/s10980-013-9907-8English(?XLaura R. Musacchio2007|M. Kat Anderson, Tending the Wild: Native American Knowledge and the Management of California’s Natural Resources, 526 pp 637-638Landscape Ecology224<7 Musacchio, L. R.2009yThe ecology and culture of landscape sustainability: emerging knowledge and innovation in landscape research and practice989-992Landscape Ecology248multifunctional landscapesEditorial MaterialOct://000269913600001pISI Document Delivery No.: 495RV Times Cited: 1 Cited Reference Count: 30 Musacchio, Laura R. Springer Dordrecht 0921-2973 Landsc. Ecol.ISI:000269913600001[Musacchio, Laura R.] Univ Minnesota, Landscape Architecture Program, Minneapolis, MN 55455 USA. [Musacchio, Laura R.] Univ Minnesota, Conservat Biol Program, Minneapolis, MN 55455 USA. [Musacchio, Laura R.] Univ Minnesota, Urban & Reg Planning Program, Minneapolis, MN 55455 USA. [Musacchio, Laura R.] Univ Minnesota, Water Resources Sci Program, Minneapolis, MN 55455 USA. Musacchio, LR, Univ Minnesota, Landscape Architecture Program, 89 Church St SE, Minneapolis, MN 55455 USA. musac003@umn.edu10.1007/s10980-009-9393-1English ;07 Musacchio, L. R.2009The scientific basis for the design of landscape sustainability: A conceptual framework for translational landscape research and practice of designed landscapes and the six Es of landscape sustainability993-1013Landscape Ecology248SpringerUniv Minnesota, Landscape Architecture Program Minneapolis M. N. U. S. A. Univ Minnesota, Conservat Biol Program Minneapolis M. N. U. S. A. Univ Minnesota, Urban Reg Planning Program, Minneapolis M. N. U. S. A. Univ Minnesota, Water Resources Sci Program Minneapolis M. N. U. S. A.Sustainability science Translational landscape research and practice Landscape sustainability Urbanization Globalization Coupled human and natural systems Designed landscapes Complex place-based problems Human-nature interactions Biodiversity conservationOctpLandscape researchers and practitioners, using the lens of sustainability science, are breaking new ground about how people's behaviors and actions influence the structure, function, and change of designed landscapes in an urbanizing world. The phrase-the scientific basis of the design for landscape sustainability-is used to describe how sustainability science can contribute to translational landscape research and practice about the systemic relationships among landscape sustainability, people's contact with nature, and complex place-based problems. In the first section of this article, important definitions about the scientific basis of the design for landscape sustainability are reviewed including the six Es of landscape sustainability-environment, economic, equity, aesthetics, experience, and ethics. A conceptual framework about the six Es of landscape sustainability for designed landscapes is introduced. The interrelatedness, opportunities, contradictions, and limitations of the conceptual framework are discussed in relation to human health/security, ecosystem services, biodiversity, and resource management. The conceptual framework about the six Es of landscape sustainability for designed landscapes follows the tradition in which landscape researchers and practitioners synthesize emerging trends into conceptual frameworks for advancing basic and applied activities.://000269913600002^ISI Document Delivery No.: 495RV Times Cited: 1 Cited Reference Count: 215 Musacchio, Laura R. 0921-2973 DORDRECHT2009 Landsc. Ecol.ISI:000269913600002Landscape ecology{Musacchio, LR, Univ Minnesota, Landscape Architecture Program, 89 Church St SE, Minneapolis, MN 55455 USA. musac003@umn.edu10.1007/s10980-009-9396-yEnglish(|?Z Musacchio, Laura R.2011aThe grand challenge to operationalize landscape sustainability and the design-in-science paradigm1-5Landscape Ecology261Jan!://WOS:000286004400001Times Cited: 3 0921-2973WOS:00028600440000110.1007/s10980-010-9562-2>}?%Muster, S. Elsenbeer, H. Conedera, M.2007Small-scale effects of historical land use and topography on post-cultural tree species composition in an Alpine valley in southern Switzerland 1187-1199Landscape Ecology228Oct://000248941900006 0921-2973ISI:000248941900006ڽ7 @Myint, SoeW Wentz, ElizabethA Brazel, AnthonyJ Quattrochi, DaleA2013MThe impact of distinct anthropogenic and vegetation features on urban warming959-978Landscape Ecology285Springer Netherlands_Land surface temperature Urban land cover QuickBird ASTER High albedo roof Dark surface Phoenix 2013/05/01+http://dx.doi.org/10.1007/s10980-013-9868-y 0921-2973Landscape Ecol10.1007/s10980-013-9868-yEnglish<79-Myster, R. W. Thomlinson, J. R. Larsen, M. C.1997PPredicting landslide vegetation in patches on landscape gradients in Puerto Rico299-307Landscape Ecology125Luquillo Experimental Forest; rain forest; elevation; slope; age; area; aspect; volcaniclastic; diorite; road association DETRENDED CORRESPONDENCE-ANALYSIS; SHIFTING MOSAIC LANDSCAPE; LUQUILLO MOUNTAINS; DISTURBANCE; FOREST; SUCCESSION; WOODLAND; PLANTArticleOctWe explored the predictive value of common landscape characteristics for landslide vegetative stages in the Luquillo Experimental Forest of Puerto Rico using four different analyses. Maximum likelihood logistic regression showed that aspect, age, and substrate type could be used to predict vegetative structural stage. In addition it showed that the structural complexity of the vegetation was greater in landslides (1) facing the southeast (away from the dominant wind direction of recent hurricanes), (2) that were older, and (3) that had volcaniclastic rather than dioritic substrate. Multiple regression indicated that both elevation and age could be used to predict the current vegetation, and that vegetation complexity was greater both at lower elevation and in older landslides. Pearson product-moment correlation coefficients showed that (1) the presence of volcaniclastic substrate in landslides was negatively correlated with aspect, age, and elevation, (2) that road association and age were positively correlated, and (3) that slope was negatively correlated with area. Finally, principal components analysis showed that landslides were differentiated on axes defined primarily by age, aspect class, and elevation in the positive direction, and by volcaniclastic substrate in the negative direction. Because several statistical techniques indicated that age, aspect, elevation, and substrate were important in determining vegetation complexity on landslides, we conclude that landslide succession is influenced by variation in these landscape traits. In particular, we would expect to find more successional; development on landslides which are older, face away from hurricane winds, are at lower elevation, and are on volcaniclastic substrate. Finally, our results lead into a hierarchical conceptual model of succession on landscapes where the biota respond first to either gradients or disturbance depending on their relative severity, and then to more local biotic mechanisms such as dispersal, predation and competition.://000077684100004 ISI Document Delivery No.: 150UN Times Cited: 13 Cited Reference Count: 41 Cited References: *SAS I INC, 1985, SAS US GUID STAT VER ALLEN MF, 1991, ECOLOGY MYCORRHIZAE BAZZAZ FA, 1979, ANNU REV ECOL SYST, V10, P351 BOOSE ER, 1994, ECOL MONOGR, V64, P369 BROWN ET, 1995, EARTH PLANET SC LETT, V129, P193 CLARK JS, 1991, ECOLOGY, V72, P1102 CLARK JS, 1991, ECOLOGY, V72, P1119 DALLING JW, 1994, BIOTROPICA, V26, P392 EWEL JJ, 1973, ITF18 US FOR SERV FERNANDEZ DS, 1995, TROP ECOL, V36, P73 FORMAN RTT, 1986, LANDSCAPE ECOLOGY GARWOOD NC, 1979, SCIENCE, V205, P997 GUARIGUATA MR, 1990, 89257 US GEOL SURV GUARIGUATA MR, 1990, J ECOL, V78, P814 HILL MO, 1980, VEGETATIO, V42, P47 KACHIGAN SK, 1991, MULTIVARIATE STAT AN LARSEN MC, 1991, GEOLOGICAL SOC AM AB, V23, A256 LARSEN MC, 1992, CARIBB J SCI, V28, P113 LARSEN MC, 1993, GEOGR ANN A, V75, P13 LARSEN MC, 1995, AM GEOPHYSICAL UNI S, V76, S309 LARSEN MC, 1996, 954029 US GEOL SURV LUNDGREN L, 1978, GEOGRAFISKAANNALER, V60, P91 MYSTER RW, J TROPICAL ECOLOGY MYSTER RW, 1990, AM MIDL NAT, V124, P125 MYSTER RW, 1995, BIOTROPICA, V27, P149 NASH D, 1987, SLOPE STABILITY, P11 PIELOU EC, 1984, INTERPRETATION ECOLO RISSER PG, 1987, LANDSCAPE HETEROGENE, V64, P123 SCATENA FN, 1989, SO72 US FOR SERV SO SIMON A, 1990, GEOMORPHOLOGY, V3, P263 SOKAL RR, 1981, BIOMETRY SOUSA WP, 1984, ANNU REV ECOL SYST, V15, P353 SWANSON FJ, 1982, US IBP SYNTHESIS SER, V14, CH8 TURNER MG, 1987, ECOLOGICAL STUDIES, V64 TURNER MG, 1991, ECOL STUD, V82, P134 WAIDE RB, 1992, TROPICAL FORESTS TRA, P173 WALKER LR, 1993, BIOTROPICA, V25, P408 WALKER LR, 1994, J VEG SCI, V5, P525 WALKER LR, 1995, J TROP ECOL, V11, P473 WARTENBERG D, 1987, AM NAT, V129, P434 WEAVER PL, 1990, BIOTROPICA, V22, P83 0921-2973 Landsc. Ecol.ISI:000077684100004Univ Puerto Rico, Inst Trop Ecosyst Studies, San Juan, PR 00936 USA. US Geol Survey, GSA Ctr, Guaynabo, PR 00965 USA. Myster, RW, Univ Puerto Rico, Inst Trop Ecosyst Studies, POB 363682, San Juan, PR 00936 USA.English<7FNagasaka, A. Nakamura, F.1999iThe influences of land-use changes on hydrology and riparian environment in a northern Japanese landscape543-556Landscape Ecology146channelization Coarse woody debris hydrology land-use riparian ecosystem stream temperature COARSE WOODY DEBRIS CUMULATIVE IMPACTS STREAM VEGETATION MANAGEMENTArticleDecTemporal changes in a hydrological system and riparian ecosystem were examined with reference to land-use conversion in order to clarify the linkages between these two systems. First, the hydrological system of the Toikanbetsu River basin was divided into three components that measure water retention, inundation and conveyance. Variation in the hydrological system was expressed as a basis of delineating the three components and estimating their functions. The rainfall-runoff system was also examined using a model which can predict responses of surface-, subsurface- and base flows on rainfall intensity. Second, areas and fragmentation of the riparian forests, maximum stream temperature in summer and amount of coarse woody debris (CWD) were selected as parameters indicating the condition of the riparian ecosystem. Temporal changes in stream temperature and amount of CWD were estimated using multiple regression analysis and analysis of variance, respectively. The results indicated that the hydrological system has been altered since the 1970s, increasing flood peaks by 1.5-2.5 times and shortening peak appearance by 7 hours. Riparian forests have been disappearing since the 1960s due to extensive development of agricultural lands and river channelization. The summer maximum stream temperature increased from 22 degrees C in 1947 to 28 degrees C at present. The amount of CWD should substantially decrease with river channelization and associated forest cutting. Fish favoring cool water, such as masu salmon, could survive in 1947 although they are forced to migrate to cooler forested upstream tributaries now. The ecological systems were closely related to and distinctly altered by land-use. Finally, we propose a new perspective for understanding the two interrelated systems. Riparian ecosystems can be restored by restoring water retention and inundation functions, which also reduce the flood hazard generated by elevated flood peaks.://000082563500003 @ ISI Document Delivery No.: 235VP Times Cited: 11 Cited Reference Count: 54 Cited References: 1974, HIST HORONOBE TOWN *HOKK U EXP FOR, 1992, OUTL HOKK U EXP FOR *SYSTAT INC, 1992, SYSTAT STAT VERS 5 2 *TOIK ED DEP HIST, 1988, HIST TOIK 80 YEARS ABE T, 1996, J JAPANESE FORESTRY, V78, P36 ALLAN JD, 1995, STREAM ECOLOGY STRUC ANDRUS CW, 1988, CAN J FISH AQUAT SCI, V45, P2080 BARTON DR, 1985, N AM J FISH MANAGE, V5, P364 BEVEN KJ, 1994, TERRAIN ANAL DISTRIB BIBLY RE, 1991, CAN J FISH AQUAT SCI, V48, P2499 BLACKIE JR, 1985, HYDROLOGICAL FORECAS, P311 BOON PJ, 1992, RIVER CONSERVATION M BROOKES A, 1988, CHANNELIZED RIVERS BROWN GW, 1969, WATER RESOUR RES, V5, P68 CLARKE RT, 1994, STAT MODELLING HYDRO CUMMINS KW, 1989, BIOSCIENCE, V39, P24 DICKERT TG, 1985, ENVIRON IMPACT ASSES, V5, P37 DUNNE T, 1978, WATER ENV PLANNING FISHER SG, 1973, ENERGY FLOW BEAR BRO, P421 FORMAN RTT, 1986, LANDSCAPE ECOLOGY GOSSELINK JG, 1990, BIOSCIENCE, V40, P588 GREGORY SV, 1991, BIOSCIENCE, V41, P540 GURNELL AM, 1995, GEOMORPHOLOGY, V13, P49 HARMON ME, 1986, ADV ECOL RES, V15, P133 INOUE M, 1994, JPN J ECOL, V44, P151 INOUE M, 1997, CAN J FISH AQUAT SCI, V54, P1331 ITO A, 1993, WATER SCI, V37, P64 KARR JR, 1991, ECOL APPL, V1, P66 KISHI C, 1995, STRUCTURE FUNCTION R, P83 LEE LC, 1988, ENVIRON MANAGE, V12, P591 MASER C, 1994, FOREST SEA ECOLOGY W MAYAMA H, 1993, ENV RIVER ENG, P111 MCGURK BJ, 1989, PSW110 USDA FOR SERV, P157 MERABTENE T, 1997, MEM FACULTY ENG KYUS, V57, P107 MIZUMURA K, 1995, J HYDRAUL ENG-ASCE, V121, P812 MURAI H, 1975, B GOV FOREST EXP STA, V274, P23 MURPHY ML, 1989, N AM J FISH MANAGE, V9, P427 NAKAMURA F, 1989, J JPN FOREST SOC, V71, P387 NAKAMURA F, 1994, CAN J FOREST RES, V24, P2395 NAKAMURA F, 1995, T JPN GEOMORPHOL UNI, V16, P237 NETER J, 1990, APPL LINEAR STAT MOD NORUSIS MJ, 1993, SPSS WINDOWS BASE SY OKUNISHI K, 1990, B DISASTER PREV RES, V40, P143 POTTER KW, 1991, WATER RESOUR RES, V27, P845 SCHLOSS AJ, 1985, 370 USDI BUR LAND MA SCHLOSSER IJ, 1981, ENVIRON MANAGE, V5, P233 SEDELL JR, 1984, VERH INT VER LIMNOL, V22, P1828 SPEAKER RW, 1984, VERH INT VER LIMNOL, V22, P1835 SUGAWARA M, 1974, METHOD RUNOFF ESTIMA SUGIMOTO S, 1997, J FOREST RES, V2, P103 SWANSON FJ, 1976, PNW56 USDA FOR SERV TAKAHASHI G, 1984, JAPANESE J LIMNOLOGY, V45, P178 TAKAHASHI Y, 1971, LAND USE CHANGES FLO WALLACE JB, 1996, ECOL APPL, V6, P140 0921-2973 Landsc. Ecol.ISI:000082563500003Hokkaido Forestry Res Inst, Koshunai, Bibai 0790198, Japan. Hokkaido Univ, Fac Agr, Dept Forest Sci, Sapporo, Hokkaido 060, Japan. Nagasaka, A, Hokkaido Forestry Res Inst, Koshunai, Bibai 0790198, Japan.English <7BNagashima, K. Sands, R. Whyte, A. G. D. Bilek, E. M. Nakagoshi, N.2001JForestry expansion and land-use patterns in the Nelson Region, New Zealand719-729Landscape Ecology168pconjoint analysis distribution pattern management policy physical attributes socio-economic environment DYNAMICSArticleThe expansion of plantation forestry in New Zealand during the last century has altered the landscape and will continue to do so in the future. The implementation of recent resource management policy, the 1991 Resource Management Act (RMA), will also influence the impact of future plantation expansion on the landscape. It is necessary to analyze current land-use patterns in order to predict effects on future landscapes. This study analyzed the current land-use patterns of the Nelson region by examining the relationship between land-use and site conditions and by characterizing the distribution pattern of land-use depending on distance from the city. The distribution pattern was considered from an economic perspective, based on the Barlowe's model of land use distribution. The relationship between the current land-use pattern and previous land management policy was also examined using the Land Use Capability. Consequently, in addition to the physical attributes of the land, the influence of land-use management policy was obvious. Thus the RMA will undoubtedly influence land-use changes in the future. It is therefore necessary to understand the factors determining changes in land-use patterns in conjunction with the district plan of the RMA to predict future changes in land-use.://000175490900004 cISI Document Delivery No.: 550EP Times Cited: 0 Cited Reference Count: 30 Cited References: *NZ MIN AGR FOR, 1998, NZ FOR STAT 1997 *NZ MIN AGR FOR, 1999, NAT EX FOR DESCR 199 *NZ MIN FOR, 1994, REG STUD *NZ MIN FOR, 1997, NZ FOR GROW WOOD PRO *NZ MIN WORKS, 1969, UNPUB LAND US CAP SU *NZ WAT SOIL DIV S, 1971, LAND US CAP SURV HDB *SAS I INC, 1998, STATV STAT *SPSS INC, 1997, MAN SPSS CONJ 8 0 J *SPSS INC, 1999, US GUID SPSS BAS 10 *STAT NZ, 1998, 1996 CENS POP DWELL BARLOWE R, 1986, LAND RESOURCE EC EC DUNN ES, 1954, LOCATION AGR PRODUCT ELY RT, 1940, LAND EC FORMAN RTT, 1995, LAND MOSAICS GRINER BP, 1996, CONJOINT ANAL WATER HALL P, 1966, VONTHUNENS ISOLATED HARMSWORTH GR, 1996, LAND USE CAPABILITY IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 JOHNSON F, 1995, T9502 TRIANGL EC RES LAGRO JA, 1992, LANDSCAPE ECOL, V7, P275 LYNN IH, 1985, WATER SOIL MISCELLAN, V73 MACLAREN JP, 1996, FRI B, V198 MANDER U, 2000, LANDSCAPE PERSPECTIV MASUI Y, 1996, PROG CELL CYC RES, V2, P1 MCALOON J, 1997, NELSON REGIONAL HIST MCKELVEY P, 1995, STEEPLAND FORESTS HI NAKAGOSHI N, 1992, LANDSCAPE ECOL, V7, P111 NEWSOME PFJ, 1992, NZ LAND RESOURCE INV STEVENS BH, 1968, PAPERS REGIONAL SCI, V21, P19 TAYLOR NH, 1970, SOIL BUREAU B, V25 0921-2973 Landsc. Ecol.ISI:000175490900004Hiroshima Univ, Grad Sch Int Dev & Cooperat, Higashihiroshima 7398529, Japan. Nakagoshi, N, Hiroshima Univ, Grad Sch Int Dev & Cooperat, 1-5-1 Kagamiyama, Higashihiroshima 7398529, Japan.English~?TBNagendra, H. Pareeth, S. Sharma, B. Schweik, C. M. Adhikari, K. R.2008tForest fragmentation and regrowth in an institutional mosaic of community, government and private ownership in Nepal41-54Landscape Ecology231IThis study analyzes forest change in an area of Nepal that signifies a delicate balance between sustaining the needs and livelihood of a sizable human population dependent on forest products, and an effort to protect important wildlife and other natural resources. The study area, a portion of the Chitwan valley district of Nepal, represents what may be becoming a common institutional mosaic in many countries of the world who have a population reliant on forest products for their livelihood: (1) a national park; (2) a designated park buffer involving participatory forest management programs; (3) scattered patches of designated community forest; and (4) large areas of adjacent landscape made up of mostly private landholdings under agricultural practices. Utilizing Landsat images from 1989 and 2000, we analyze land cover change in each of these management zones using landscape ecology metrics and quantifying proportional distributions of land cover categories. Our results show significant differences in terms of land cover dynamics and landscape spatial pattern between these land ownership classes. These findings indicate that community-based institutions (participatory management programs in the park buffer and the designated community forests) are capable of halting or even reversing trends in deforestation and forest fragmentation."://WOS:000251796100006 Times Cited: 0WOS:00025179610000610.1007/s10980-007-9162-y`<7y&Nagendra, H. Southworth, J. Tucker, C.2003kAccessibility as a determinant of landscape transformation in western Honduras: linking pattern and process141-158Landscape Ecology182elevation Honduras land cover trajectories land use change landscape metrics roads LAND-COVER-CHANGE CENTRAL RONDONIA FOREST FRAGMENTATION SOUTHERN CAMEROON SATELLITE IMAGES COSTA-RICA DEFORESTATION AMAZON VEGETATION FEEDBACKSArticleThis study evaluates the relationship between landscape accessibility and land cover change in Western Honduras, and demonstrates how these relationships are influenced by social and economic processes of land use change in the region. The study area presents a complex mosaic of land cover change processes that involve approximately equal amounts of reforestation and deforestation. Landsat Thematic Mapper (TM) satellite imagery of 1987, 1991 and 1996 was used to create three single date classifications and a land cover change image depicting the sequence of changes in land cover between 1987 - 1991 - 1996. An accessibility analysis examined land cover change and landscape fragmentation relative to elevation and distance from roads. Between 1987 and 1991, results follow 'expected' trends, with more accessible areas experiencing greater deforestation and fragmentation. Between 1991 and 1996 this trend reverses. Increased deforestation is found in areas distant from roads, and at higher elevations; a result of government policies promoting expansion of mountain coffee production for export. A ban on logging, and abandonment of marginally productive agricultural fields due to agricultural intensification in other parts of the landscape, has led to increased regrowth in accessible regions of the landscape. Roads and elevation also present different obstacles in terms of their accessibility, with the smallest patches of cyclical clearing and regrowth, relating mostly to the agricultural fallow cycle, found at the highest elevations but located close to roads. This research highlights the need to locate analyses of land cover change within the context of local socio-economic policies and land use processes.://000183770300004 Q ISI Document Delivery No.: 694JB Times Cited: 20 Cited Reference Count: 49 Cited References: *I HOND CAF, 1997, B EST 1970 1996 *US NAT RES COUNC, 1999, GLOB ENV CHANG RES P ALVES DS, 1999, INT J REMOTE SENS, V20, P2877 ANDRADE EZ, 1990, MODALIDADES LLUVIA H BORJAS MC, 1992, COMO SUBSISTEN CAMPE DALE VH, 1993, PHOTOGRAMM ENG REM S, V59, P997 DUNCAN BW, 1999, LANDSCAPE ECOL, V14, P291 FOODY GM, 2002, REMOTE SENS ENVIRON, V80, P185 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY GEIST HJ, 2002, BIOSCIENCE, V52, P143 GREEN GM, 1990, SCIENCE, V248, P212 GRIFFITHS GH, 2000, INT J REMOTE SENS, V21, P2537 HAINESYOUNG R, 1996, PROG PHYS GEOG, V20, P418 HALL FG, 1991, REMOTE SENS ENVIRON, V35, P11 HELMER EH, 2000, ECOSYSTEMS, V3, P98 JENSEN JR, 1996, INTRO DIGITAL IMAGE, P318 JENSEN JR, 2000, REMOTE SENSING ENV E KAIMOWITZ D, 1997, AMBIO, V26, P537 LAMBIN EF, 2001, GLOBAL ENVIRON CHANG, V11, P261 LAURANCE WF, 2001, CONSERV BIOL, V15, P1529 LAURANCE WF, 2001, SCIENCE, V291, P438 LUDEKE AK, 1990, J ENVIRON MANAGE, V31, P247 MAKI S, 2001, ENVIRON CONSERV, V28, P199 MCGARIGAL K, 1995, PNW351 USDA FOR SERV MERTENS B, 1997, APPL GEOGR, V17, P143 MERTENS B, 2000, ANN ASSOC AM GEOGR, V90, P467 MORAN EF, 1994, BIOSCIENCE, V44, P329 MUNROE D, 2001, C P AM AGR EC ASS AA MUNROE DK, 2002, AGR ECON, V27, P355 NELSON GC, 1997, AM J AGR ECON, V79, P80 NEPSTAD D, 2001, FOREST ECOL MANAG, V154, P395 OCHOAGAONA S, 2000, APPL GEOGR, V20, P17 PEARSON DM, 2002, J ENVIRON MANAGE, V64, P85 PETIT C, 2001, INT J REMOTE SENS, V22, P3435 PORTILLO P, 1984, GEOGRAFIA HONDURAS RIITTERS K, 2000, CONSERV ECOL, V4 SADER SA, 1988, BIOTROPICA, V20, P11 SADER SA, 1995, PHOTOGRAMM ENG REM S, V61, P1145 SOARES BS, 2001, BIOSCIENCE, V51, P1059 SOKAL RR, 1987, INTRO BIOSTATISTICS SOUTHWORTH J, 2001, MT RES DEV, V21, P276 SOUTHWORTH J, 2002, LANDSCAPE RES, V27, P253 STONE TA, 1991, FOREST ECOL MANAG, V38, P291 THOMLINSON JR, 1999, REMOTE SENS ENVIRON, V70, P16 TUCKER CM, 1996, THESIS U ARIZONA TUC TUCKER CM, 1999, HUM ECOL, V27, P201 TUCKER CM, 1999, MESOAMERICA, V37, P111 WILLIAMS LO, 1981, USEFUL PLANTS CENTRA, V24, P3 WOOD CH, 1998, PEOPLE PIXELS LINKIN, P70 0921-2973 Landsc. Ecol.ISI:000183770300004)Indiana Univ, Ctr Study Inst Populat & Environm Change, Bloomington, IN 47408 USA. Univ Florida, Dept Geog, Gainesville, FL 32611 USA. Univ Florida, LUECI, Gainesville, FL 32611 USA. Nagendra, H, Indiana Univ, Ctr Study Inst Populat & Environm Change, 408 N Indiana Ave, Bloomington, IN 47408 USA.English|?T4Nahuelhual, L. Carmona, A. Aguayo, M. Echeverria, C.2014{Land use change and ecosystem services provision: a case study of recreation and ecotourism opportunities in southern Chile329-344Landscape Ecology292FebzLand use and cover change (LUCC) is among the most important factors affecting ecosystem services. This study examines the influence of LUCC on recreation and ecotourism opportunities over three decades in southern Chile. An in-depth analysis of the transition matrix was conducted based on Landsat images from 1976, 1985, 1999 and 2007. Main LUCC trajectories were linked to two ecosystem service indicators: (i) Recreation and ecotourism potential, measured in a 0- 100 point scale; and (ii) Recreation and ecotourism opportunities, measured in visitors/ha. A total of 900 trajectories occurred in the landscape between 1976 and 2007. The most important trajectories in terms of area, were the recent degradation of old-growth to secondary forest between 1999 and 2007 (23,290 ha; 13.5 % of landscape), and the early clearing of shrublands for agriculture and pasture land between 1976 and 1985 (7,187 ha, 4.2 % of landscape). In turn, the single most influential trajectory on the magnitude of the indicators was early and permanent degradation of old-growth forest to secondary forest. As a result of these landscape changes, recreation and ecotourism opportunities for the entire landscape were reduced from 65,050 persons in 1976 to 25,038 persons in 1985, further declining to 22,346 and 21,608 persons in 1999 and 2007, respectively. This decrease resulted from changes in specific attributes (i.e. emblematic flora and fauna and forest structure) that were affected by forest degradation and fragmentation. These results highlight the substantial impact of LUCC on recreation opportunity decline, which mirrors biodiversity losses in the study area.!://WOS:000331935100011Times Cited: 3 0921-2973WOS:00033193510001110.1007/s10980-013-9958-x? YNaidoo, Robin Preez, Pierre Stuart-Hill, Greg Chris Weaver, L. Jago, Mark Wegmann, Martin2012YFactors affecting intraspecific variation in home range size of a large African herbivore 1523-1534Landscape Ecology2710Springer NetherlandsBiomedical and Life SciencesFactors affecting intraspecific variation in home range size have rarely been examined using modern statistical and remote sensing methods. This is especially true for animals in seasonal savanna environments in Africa, despite this biome’s importance for both conservation and development goals. We studied the impacts of spatial and temporal variability in environmental conditions, along with individual and social factors, on home range sizes in African buffalo ( Syncerus caffer ) in northeastern Namibia. Our data set spans 4 years, is derived from 32 satellite tracking collars, and contains over 35,000 GPS locations. We used the local convex hull method to estimate home range size from 31 buffalo captured at 6 sites. We used a variety of remotely sensed data to characterize potential anthropogenic and natural boundaries, as well as seasonal and temporal heterogeneity in environmental conditions. Using an information-theoretic, mixed effects approach, our analyses showed that home ranges varied over two orders of magnitude and are among the largest recorded for this species. Variables relating to vegetation and habitat boundaries were more important than abiotic environmental conditions and individual or social factors in explaining variation in home range size. The relative contributions of environmental, individual, social, and linear boundary variables to intraspecific home range size have rarely been examined and prior to this had not been assessed for any species in seasonal savannas of Africa. Understanding the factors that condition space-use patterns of wildlife in this area will lead to better-informed conservation and sustainable development decisions.+http://dx.doi.org/10.1007/s10980-012-9807-3 0921-297310.1007/s10980-012-9807-3<7v Naiman, R. J.1996$Water, society and landscape ecology193-196Landscape Ecology114 PERSPECTIVEEditorial MaterialAug://A1996VC12700001 9ISI Document Delivery No.: VC127 Times Cited: 6 Cited Reference Count: 23 Cited References: BENKE AC, 1990, J N AMER BENTHOL SOC, V9, P77 BERRY M, 1995, IN PRESS IEEE COMPUT CALDWELL LK, 1990, LANDSCAPE ECOL, V5, P3 DICASTRI F, 1984, ECOLOGY PRACTICE, V1 DYNESIUS M, 1994, SCIENCE, V266, P753 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FRANCKO DA, 1983, QUENCH THIRST GLEICK PH, 1993, WATER CRISIS LEVINE JS, 1992, GLOBAL CLIMATE CHANG, P1 NAIMAN RJ, 1992, P C WAT RES BAL ENV, P5 NAIMAN RJ, 1995, FRESHWATER IMPERATIV NAIMAN RJ, 1995, SCIENCE, V270, P584 NAIMAN RJ, 1996, CREATING FORESTRY 21 NASSAUER JI, 1995, LANDSCAPE ECOL, V10, P229 NAVEH Z, 1991, LANDSCAPE ECOL, V5, P65 ORR DW, 1994, EARTH MIND ED ENV HU PALMER T, 1994, LIFELINES CASE RIVER PETTS GE, 1984, IMPOUNDED RIVERS RISSER PG, 1987, LANDSCAPE HETEROGENE, P3 TURNER BL, 1990, EARTH TRANSFORMED HU TURNER MG, 1996, IN PRESS ECOLOGICAL VOS CC, 1993, LANDSCAPE ECOLOGY ST WEAR DN, 1996, IN PRESS ECOLOGICAL 0921-2973 Landsc. Ecol.ISI:A1996VC12700001ONaiman, RJ, UNIV WASHINGTON,CTR STREAMSIDE STUDIES,BOX 352100,SEATTLE,WA 98195.English <7Nakagoshi, N. Kondo, T.2001BEcological land evaluation for nature redevelopment in river areas83-93Landscape Ecology17 supplement 1Kcorridor evaluation GIS river enhancement BIRD ASSEMBLAGES FOREST CORRIDORSArticleLandscape enhancement projects are under way at the Yamanakadani and Kadowaki rivers, which run through the campus of Hiroshima University, Japan. At both sites, the ecological value of land was determined from two aspects: (1) value as vegetation and (2) value to birds. To evaluate the vegetation, we selected conservation sites and suitable sites for enhancement considering rarity and recovery potential of vegetation, and access to users and construction equipment. We determined that the area of forest, the number of forest vertical layers, and forest pattern help sustain avian diversity and contribute toward the area functioning as an avian corridor.://000176041000008 PISI Document Delivery No.: 559TG Times Cited: 1 Cited Reference Count: 28 Cited References: *NAT CONS BUR AS A, 1994, REP 4 NAT VEG SURV ASKIN RA, BIOL CONSERV, V39, P129 DMOWSKI K, 1990, LANDSCAPE ECOL, V4, P99 ERDELEN M, 1984, OECOLOGIA, V61, P277 FORMAN RTT, 1983, EKOL CSSR, V2, P375 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FORMAN RTT, 1995, LAND MOSAIC ECOLOGY FREEMARK KE, 1986, BIOL CONSERV, V36, P115 GATES JE, 1981, AM MIDL NAT, V105, P189 HANSKI IA, 1997, METAPOPULATION BIOL HARMS WB, 1990, CHANGING LANDSCAPES, P73 HOWE RW, 1984, ECOLOGY, V65, P1585 HUDSON WE, 1991, LANDSCAPE LINKAGES B IDE H, 1976, APPL PHYTOSOC, V4, P26 JOSEF B, 1993, GRUNDLAGEN BIOTOPSCH KAMEYAMA A, 1973, APPL PHYTOSOC, V2, P1 KAMEYAMA A, 1975, APPL PHYTOSOC, V4, P1 KONDO T, 1999, J JPN I LANDSCAPE AR, V62, P603 KROODSMA RL, 1984, WILSON BULL, V96, P426 KURAMOTO N, 1995, J JPN I LANDSCAPE AR, V58, P408 MACARTHUR R, 1961, ECOLOGY, V42, P594 MACHTANS CS, 1996, CONSERV BIOL, V10, P1366 MALANSON GP, 1993, RIPARIAN LANDSCAPES NANCY EM, 1995, LANDSCAPE ECOL, V10, P85 NAVEH Z, 1984, LANDSCAPE ECOLOGY TH NOMURA K, 1999, J ENVIRON SCI, V11, P188 VANDORP D, 1987, LANDSCAPE ECOLOGY, V1, P59 ZONNEVELD IS, 1995, LAND ECOLOGY INTRO L Suppl. 1 0921-2973 Landsc. Ecol.ISI:000176041000008Hiroshima Univ, Grad Sch Int Dev & Cooperat, Higashihiroshima 7398529, Japan. Nakagoshi, N, Hiroshima Univ, Grad Sch Int Dev & Cooperat, Higashihiroshima 7398529, Japan. nobu@hiroshima-u.ac.jpEnglishx<7Nakagoshi, N. Ohta, Y.1992jFactors affecting the dynamics of vegetation in the landscapes of Shimokamagari Island, southwestern Japan111-119Landscape Ecology72oAGRICULTURAL ECONOMICS; CITRUS FRUIT PRODUCTION; ISLAND; LANDSCAPE; RURAL FOREST; SITE CONDITION; SOCIAL CHANGEArticleJul!On Shimokamagari, an island of the Seto Island Sea, patterns of vegetation in the landscape were studied using vegetation maps. Relationships between social and economic changes, site conditions and the vegetation were examined from a historical perspective. In the process of economic development, mandarin orange production became important on this island. However, over-production, a reduction in the price of mandarin oranges and low-temperature damage to orange trees caused large citrus orchards to be abandoned. A plant community dominated by kudzu appeared in the abandoned orchards and the pine forests, as well. These changes in orchards were connected with the natural site conditions, such as soil, geology, inclination, elevation, direction of slope, and also with artificial conditions, such as density of working paths. Another factor causing change was the replacement of the organic fertilizer of litter from forests by chemical fertilizer since the 1960's. As a result, medium and small forests of pine became tall forests and tall forests of pine changed into tall oak forests. In the human-dominated areas, the major factors affecting the process of vegetation were economic activities, and after the abandonment of the farm-lands, forest succession were controlled by natural site conditions.://A1992JF61500004 HISI Document Delivery No.: JF615 Times Cited: 5 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1992JF61500004iNAKAGOSHI, N, HIROSHIMA UNIV,FAC INTEGRATED ARTS & SCI,DEPT ENVIRONM STUDIES,NAKA KU,HIROSHIMA 730,JAPAN.EnglishA|7 Nakagoshi, N. Ohta, Y.1992jFactors Affecting the Dynamics of Vegetation in the Landscapes of Shimokamagari-Island, Southwestern Japan111-119Landscape Ecology72iagricultural economics citrus fruit production island landscape rural forest site condition social changeJul)On Shimokamagari, an island of the Seto Island Sea, patterns of vegetation in the landscape were studied using vegetation maps. Relationships between social and economic changes, site conditions and the vegetation were examined from a historical perspective. In the process of economic development, mandarin orange production became important on this island. However, over-production, a reduction in the price of mandarin oranges and low-temperature damage to orange trees caused large citrus orchards to be abandoned. A plant community dominated by kudzu appeared in the abandoned orchards and the pine forests, as well. These changes in orchards were connected with the natural site conditions, such as soil, geology, inclination, elevation, direction of slope, and also with artificial conditions, such as density of working paths. Another factor causing change was the replacement of the organic fertilizer of litter from forests by chemical fertilizer since the 1960's. As a result, medium and small forests of pine became tall forests and tall forests of pine changed into tall oak forests. In the human-dominated areas, the major factors affecting the process of vegetation were economic activities, and after the abandonment of the farm-lands, forest succession were controlled by natural site conditions.://A1992JF61500004,Jf615 Times Cited:7 Cited References Count:0 0921-2973ISI:A1992JF61500004gNakagoshi, N Hiroshima Univ,Fac Integrated Arts & Sci,Dept Environm Studies,Naka Ku,Hiroshima 730,JapanEnglish P<7s Nams, V. O.1996LThe VFractal: A new estimator for fractal dimension of animal movement paths289-297Landscape Ecology1157LANDSCAPE STRUCTURE; TRACKING; PATTERNS; MAMMALS; SCALEArticleOctuFractal measurements of animal movement paths have been used to analyze how animals view habitats at different spatial scales. One problem has been the absence of error estimates for fractal d estimators. To address this weakness, I present and test 4 new estimators for measuring fractal dimension at different spatial scales, along with estimates of their variation. The estimators are based on dividing the movement path into pairs of steps, forming V's, and then estimating various statistics from each V. I measured the performance of these estimators by comparing them to the traditional divider d method, using data generated by two different animal movement models. The estimator based on the net distance between the two steps and the cos turning angle was most accurate, giving estimates similar to those of the traditionally-used divider d method. Precision increased with longer and straighter paths. Strengths of this new estimator are that it can estimate fractal d at different spatial scales, give an estimate of variation, and combine data from many separate path segments which have been gathered at various spatial scales.://A1996VR02500006 LISI Document Delivery No.: VR025 Times Cited: 30 Cited Reference Count: 17 Cited References: BENHAMOU S, 1990, BEHAV PROCESS, V22, P235 BOONSTRA R, 1986, CAN J ZOOL, V64, P1034 CRIST TO, 1992, FUNCT ECOL, V6, P536 DICKE M, 1988, PHYSIOL ENTOMOL, V13, P393 EFRON B, 1991, SCIENCE, V253, P390 GOODYEAR NC, 1989, J WILDLIFE MANAGE, V53, P941 KOTLIAR NB, 1990, OIKOS, V59, P253 KRUMMEL JR, 1987, OIKOS, V48, P321 LEMEN CA, 1985, J MAMMAL, V66, P134 MANDELBROT B, 1967, SCIENCE, V156, P636 MILNE BT, 1991, QUANTITATIVE METHODS, P199 SHERRY TW, 1988, AUK, V105, P350 SUGIHARA G, 1990, TRENDS ECOL EVOL, V5, P79 WIENS JA, 1993, ENVIRON ENTOMOL, V22, P709 WITH KA, 1994, FUNCT ECOL, V8, P477 WITH KA, 1994, LANDSCAPE ECOL, V9, P25 ZHANG ZQ, 1993, OECOLOGIA, V96, P24 0921-2973 Landsc. Ecol.ISI:A1996VR02500006INams, VO, NOVA SCOTIA AGR COLL,DEPT BIOL,BOX 550,TRURO,NS B2N 5E3,CANADA.English|?3Nams, Vilis O.20143Tortuosity of habitat edges affects animal movement655-663Landscape Ecology294Apr Animal travel between habitat patches affects populations, communities, and ecosystems. I used computer simulations to test whether animals form an emergent response to edges-i.e., whether simply responding to an edge causes an animal to behave as if it can recognize edge tortuosity. Animals were simulated inside a habitat patch that contained a tortuous edge and three straight edges. I varied the following parameters: scale of edge tortuosity, edge crossing probability, and avoidance/attraction to edges. Permeability estimates were standardized to remove the effects of edge length, path shape, path size, and distance to animals. Results showed that when animals are attracted to edges, or are neutral to edges and have a high edge-crossing probability, edge tortuosity does not affect permeability. However, when animals avoid edges, or are neutral to edges and have a low edge-crossing probability, then permeability is higher at smaller scales. Linking this to body size suggests that larger animals who avoid edges have increased edge permeability compared to smaller animals. Edge tortuosity also affects where animals cross edges and what direction they travel after crossing them. Thus, edge tortuosity can affect metapopulation dynamics in more ways than simply due to an increase in edge length.!://WOS:000333533800008Times Cited: 0 0921-2973WOS:00033353380000810.1007/s10980-014-0008-0#?OJoan Iverson Nassauer1992:The appearance of ecological systems as a matter of policy239-250Landscape Ecology64Environmental policy should explicitly address the appearance of the landscape because people make inferences about ecological quality from the look of the land. Where appearances are misleading, failing to portray ecological degradation or ecological health, public opinion may be ill-informed, with consequences for environmental policy. This paper argues that while ecology is a scientific concept, landscape perception is a social process. If we do not recognize this difference, we have problems with the appearance of ecological systems. Three influential problems are discussed: 1) the problem of the false identity of ecological systems, 2) the problem of design and planning as deceit about ecological systems, and 3) the problem of invisible ecological systems. These problems for environmental policy may be resolved in part if landscape planners and policy-makers use socially-recognized signs to display human intentions for ecological systems. Specifically, planning and policy can include socially-recognized signs of beauty and stewardship to display human care for ecological systems. An example in United States federal agricultural policy is described.c<7Nassauer, J. I.1995(Culture and changing landscape structure229-237Landscape Ecology1046CULTURE; CHANGE; PERCEPTION; THEORY; LANDSCAPE ECOLOGYArticleAugCulture changes landscapes and culture is embodied by landscapes. Both aspects of this dynamic are encompassed by landscape ecology, but neither has been examined sufficiently to produce cultural theory within the field. This paper describes four broad cultural principles for landscape ecology, under which more precise principles might be organized. A central underlying premise is that culture and landscape interact in a feed-back loop in which culture structures landscapes and landscapes inculcate culture. The following broad principles are proposed: 1. Human landscape perception, cognition, and values directly affect the landscape and are affected by the landscape. 2. Cultural conventions powerfully influence landscape pattern in both inhabited and apparently natural landscapes. 3. Cultural concepts of nature are different from scientific concepts of ecological function. 4. The appearance of landscapes communicates cultural values. Both the study of landscapes at a human scale and experimentation with possible landscapes, landscape patterns invented to accommodate ecological function, are recommended as means of achieving more precise cultural principles.://A1995RP98800005 IISI Document Delivery No.: RP988 Times Cited: 58 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1995RP98800005^NASSAUER, JI, UNIV MINNESOTA,DEPT LANDSCAPE ARCHITECTURE,89 CHURCH ST SE,MINNEAPOLIS,MN 55455.English<7Nassauer, J. I. Corry, R. C.2004.Using normative scenarios in landscape ecology343-356Landscape Ecology194agriculture; futures; interdisciplinary; landscape change; planning; policy; scenarios DECISION-MAKING; MANAGEMENT; ECOSYSTEM; MODELS; SIMULATION; PATTERNS; DYNAMICS; DESIGNS; FUTURE; IOWAArticleThe normative landscape scenario is one of many types of scenario methods that are used by landscape ecologists. We describe how normative landscape scenarios are different from other types and how these differences create special potential for engaging science to build landscape policy and for exploring scientific questions in realistic simulated landscapes. We describe criteria and a method for generating normative scenarios to realize this potential in both policy and landscape ecology research. Finally, we describe how the method and criteria apply to an interdisciplinary project that proposed alternative scenarios for federal agricultural policy and related futures for agricultural watersheds in Iowa, USA.://000221879000001 u ISI Document Delivery No.: 827DM Times Cited: 3 Cited Reference Count: 67 Cited References: *IA STAT U, 1996, IOW SOIL PROP INT DA *RIZA, 1996, EC NETW RIV REH SCEN *SCI ADV BOARD, 1995, HOR US FOR PROT ENV *USDA, 2001, FOOD AGR POL TAK STO AHERN J, 2001, LANDSCAPE ECOLOGICAL AHERN J, 2002, ECOLOGY DESIGN FRAME, P397 BANTAYAN NC, 1998, LANDSCAPE URBAN PLAN, V43, P35 BECK MB, 2002, ENV FORESIGHT MODELS BECK MB, 2002, ENV FORESIGHT MODELS, P207 BIERZYCHUDEK P, 1999, ECOL APPL, V9, P1278 CAZA C, 1994, ENVISIONING FUTURE C COCKS D, 1999, FENN C ENV CANB ACT, P75 COINER C, 2001, ECOL ECON, V38, P119 COLE S, 2001, J AM PLANN ASSOC, V67, P372 CORRY RC, 2002, THESIS U MICHIGAN AN COUNTRYMAN DW, 2000, J SOIL WATER CONSERV, V55, P152 CRUSE RM, 1990, FARMING SYSTEMS IOWA, P39 EMMELIN L, 1994, ENVISIONING FUTURE C, P19 EXNER DN, 1999, AM J ALTERNATIVE AGR, V14, P69 FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 FREEMARK K, 1995, LANDSCAPE URBAN PLAN, V31, P99 FREEMARK KE, 1996, MODELING RISKS BIODI FRY GLA, 2001, LANDSCAPE URBAN PLAN, V57, P159 GOUDY W, 1994, IOWAS COUNTIES SELEC GUSTAFSON EJ, 1998, ENVIRON MANAGE, V22, P777 HAMBLIN A, 1999, FENN C ENV CANB ACT HAMMOND AL, 1998, WHICH WORLD SCENARIO HANSSON L, 1995, MOSAIC LANDSCAPES EC HOBBS R, 1997, LANDSCAPE URBAN PLAN, V37, P1 HULSE D, 2000, LANDSCAPE J, V19, P1 HULSE D, 2002, WILLAMETTE RIVER BAS JENERETTE GD, 2001, LANDSCAPE ECOL, V16, P611 JOHNSON GD, 1999, LANDSCAPE ECOL, V14, P413 JONES S, 1999, LANDSCAPE J, V18, P65 KEANE RE, 1999, LANDSCAPE ECOL, V14, P311 KEITT TH, 2000, LANDSCAPE ECOL, V15, P479 NASSAUER JI, 1999, RURAL WATERSHEDS POL NASSAUER JI, 2002, J SOIL WATER CONSERV, V57, A44 OPDAM P, 2002, LANDSCAPE ECOLOGY, V16, P767 PEARSON SM, 1999, ECOL APPL, V9, P1288 PETERSON GD, 2003, CONSERV BIOL, V17, P358 RALLS K, 1995, CONSERV BIOL, V9, P175 RIBE R, 1998, LANDSCAPE ECOL, V13, P1 RISSER PG, 1984, LANDSCAPE ECOLOGY DI RUSTIGIAN HL, 2003, LANDSCAPE ECOL, V18, P65 SALA OE, 2000, SCIENCE, V287 SAMSON FB, 1996, J SOIL WATER CONSERV, V51, P288 SANTELMANN M, 2001, APPL ECOLOGICAL PRIN, P226 SANTELMANN MV, 2004, LANDSCAPE ECOL, V19, P357 SCHOONENBOOM IJ, 1995, SCENARIO STUDIES RUR, P15 SCHWARTZ P, 1991, ART LONG VIEW STEINITZ C, 1990, LANDSCAPE J, V9, P136 STEINITZ C, 2001, APPL ECOLOGICAL PRIN STEINITZ C, 2002, ECOLOGY DESIGN, P231 STEINITZ C, 2003, ALTERNATIVE FUTURES SWETNAM RD, 1998, LANDSCAPE URBAN PLAN, V41, P3 TILMAN D, 2001, SCIENCE, V292, P281 TISCHENDORF L, 2001, LANDSCAPE ECOL, V16, P235 TRESS B, 2003, IN PRESS LANDSCAPE U TURNER MG, 1994, LANDSCAPE ECOL, V9, P59 TURNER MG, 2001, LANDSCAPE ECOLOGY TH VACHE KB, 2002, J AM WATER RESOUR AS, V38, P773 VARIS O, 2002, ENV FORESIGHT MODELS, P169 WACHS M, 2001, J AM PLANN ASSOC, V67, P367 WAIDE JB, 1995, PRELIMINARY MASTER A WHITE D, 1997, CONSERV BIOL, V11, P349 WICKHAM JD, 2000, LANDSCAPE ECOL, V15, P495 0921-2973 Landsc. Ecol.ISI:000221879000001Univ Michigan, Sch Nat Resources & Environm, Ann Arbor, MI 48109 USA. Univ Guelph, Sch Environm Design & Rural Dev, Guelph, ON N1G 2W1, Canada. Nassauer, JI, Univ Michigan, Sch Nat Resources & Environm, 430 E Univ Ave, Ann Arbor, MI 48109 USA. nassauer@umich.eduEnglish|?Nassauer, J. I. Opdam, P.2008;Design in science: extending the landscape ecology paradigm633-644Landscape Ecology236Landscape ecological science has produced knowledge about the relationship between landscape pattern and landscape processes, but it has been less effective in transferring this knowledge to society. We argue that design is a common ground for scientists and practitioners to bring scientific knowledge into decision making about landscape change, and we therefore propose that the pattern-process paradigm should be extended to include a third part: design. In this context, we define design as any intentional change of landscape pattern for the purpose of sustainably providing ecosystem services while recognizably meeting societal needs and respecting societal values. We see both the activity of design and the resulting design pattern as opportunities for science: as a research method and as topic of research. To place design within landscape ecology science, we develop an analytic framework based on the concept of knowledge innovation, and we apply the framework to two cases in which design has been used as part of science. In these cases, design elicited innovation in society and in science: the design concept was incorporated in societal action to improve landscape function, and it also initiated scientific questions about pattern-process relations. We conclude that landscape design created collaboratively by scientists and practitioners in many disciplines improves the impact of landscape science in society and enhances the saliency and legitimacy of landscape ecological scientific knowledge.!://WOS:000257210900001Times Cited: 0 0921-2973WOS:00025721090000110.1007/s10980-008-9226-7<7U9Naugle, D. E. Higgins, K. F. Nusser, S. M. Johnson, W. C.1999EScale-dependent habitat use in three species of prairie wetland birds267-276Landscape Ecology143landscape structure matrix patches prairie wetland birds scale South Dakota LANDSCAPE ECOLOGY DABBLING DUCK POINT COUNTS SELECTION PATTERNS NUMBERS MARSHArticleJunWe evaluated the influence of scale on habitat use for three wetland-obligate bird species with divergent life history characteristics and possible scale-dependent criteria for nesting and foraging in South Dakota, USA. A stratified, two-stage cluster sample was used to randomly select survey wetlands within strata defined by region, wetland density, and wetland surface area. We used 18-m (0.1 ha) fixed radius circular-plots to survey birds in 412 semipermanent wetlands during the summers of 1995 and 1996. Variation in habitat use by pied-billed grebes (Podilymbus podiceps) and yellow-headed blackbirds (Xanthocephalus xanthocephalus), two sedentary species that rarely exploit resources outside the vicinity of nest wetlands, was explained solely by within-patch variation. Yellow-headed blackbirds were a cosmopolitan species that commonly nested in small wetlands, whereas pied-billed grebes were an area-sensitive species that used larger wetlands regardless of landscape pattern. Area requirements for black terns (Chlidonias niger), a vagile species that typically forages up to 4 km away from the nest wetland, fluctuated in response to landscape structure. Black tern area requirements were small (6.5 ha) in heterogeneous landscapes compared to those in homogeneous landscapes (15.4-32.6 ha). Low wetland density landscapes composed of small wetlands, where few nesting wetlands occurred and potential food sources were spread over large distances, were not widely used by black terns. Landscape-level measurements related to black tern occurrence extended past relationships between wetlands into the surrounding matrix. Black terns were more likely to occur in landscapes where grasslands had not been tilled for agricultural production. Our findings represent empirical evidence that characteristics of entire landscapes, rather than individual patches, must be quantified to assess habitat suitability for wide-ranging species that use resources over large areas.://000081041200004 ISI Document Delivery No.: 209HB Times Cited: 28 Cited Reference Count: 47 Cited References: ADDICOTT JF, 1987, OIKOS, V49, P340 BAILEY AW, 1968, ECOLOGY, V49, P1 BOLLINGER EK, 1988, J WILDLIFE MANAGE, V52, P777 BROWN M, 1986, J WILDLIFE MANAGE, V50, P392 CAITHAMER DF, 1997, WATERFOWL POPULATION DAUBENMIRE R, 1959, NW SCI, V33, P43 DUNN EH, 1909, BIRDS N AM, P1 EDWARDS DK, 1981, STUD AVIAN BIOL, V6, P170 FLATHER CH, 1996, ECOLOGY, V77, P28 FORMAN RTT, 1995, LAND MOSIACS ECOLOGY FULLER RJ, 1984, BIRD STUDY, V31, P195 GRUE CE, 1986, T N AM WILDL NAT RES, V51, P357 HANDS HM, 1989, STATUS BLACK TERN NO HANSSON L, 1991, LANDSCAPE ECOL, V5, P191 HEMESATH LM, 1993, PRAIRIE NATURALIST, V25, P1 HENSHER D, 1981, APPL DISCRETE CHOICE HERKERT JR, 1994, ECOL APPL, V4, P461 HICKEY JM, 1997, COLON WATERBIRD, V20, P582 HOSMER DW, 1989, APPL LOGISTIC REGRES JOHNSON RR, 1995, GREAT PLAINS RES, V5, P309 JOHNSON RR, 1997, WETLAND RESOURCES E KAMINSKI RM, 1981, J WILDLIFE MANAGE, V45, P1 KAMINSKI RM, 1984, J WILDLIFE MANAGE, V48, P37 KANTRUD HA, 1984, J WILDLIFE MANAGE, V48, P426 KANTRUD HA, 1986, 3 US FISH WILDL SERV KOOPOWITZ H, 1994, CONSERV BIOL, V8, P425 MEENTEMEYER V, 1989, LANDSCAPE ECOLOGY, V3, P163 MURKIN HR, 1997, ECOL APPL, V7, P1144 NAUGLE DE, 1997, CAN FIELD NAT, V111, P595 NOVAK PG, 1992, MIGRATORY NONGAME BI, P149 PEARSON SM, 1993, LANDSCAPE ECOL, V8, P3 PEARSON SM, 1996, BIODIVERSITY MANAGED, P77 REYNOLDS RT, 1980, CONDOR, V82, P309 ROBBINS CS, 1989, WILDL MONOGR, V103 SCOTT JM, 1981, STUDIES AVIAN BIOL, V6, P409 STEWART RE, 1971, US FISH WILDL SERV R, V92 STOMS DM, 1992, PHOTOGRAMM ENG REM S, V58, P1587 STOMS DM, 1994, HDB GAP ANAL TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1991, QUANTITATIVE METHODS TWEDT DJ, 1995, BIRDS N AM, P1 VANDERVALK A, 1989, NO PRAIRIE WETLANDS VANREESSIEWERT KL, 1996, WETLANDS, V16, P577 VERNER J, 1986, AUK, V103, P117 VOS CC, 1995, LANDSCAPE ECOLOGY, V11, P203 WELLER MW, 1965, 43 IOW AGR HOM EC EX WIENS JA, 1989, FUNCT ECOL, V3, P385 0921-2973 Landsc. Ecol.ISI:000081041200004S Dakota State Univ, Dept Wildlife & Fisheries Sci, Brookings, SD 57007 USA. Naugle, DE, Univ Wisconsin, Coll Nat Resources, Stevens Point, WI 54481 USA.English?B Zev Naveh1987YBiocybernetic and thermodynamic perspectives of landscape functions and land use patterns75-83Landscape Ecology125ecosystem, cybernetics, thermodynamics, human ecologyThis paper develops and applies two concepts which are fundamental to landscape ecology. These concepts concern biocybernetics, which is the theory of regulation of biological and ecological systems, and thermodynamics, especially the flux of energy and the production of entropy. The landscape state factors, including site conditions and fluxes of energy, materials, and organisms, are shaped by the biocybernetic and thermodynamic processes. This theory provides us a way of understanding and discussing complex human interactions with landscape systems, expressing our concept of the whole landscape system (what I have termed the Total Human Ecosystem), and linking landscape ecology with several of the most powerfully creative ideas in modern science.? Naveh, Z.1991sSome remarks on recent developments in landscape ecology as a transdisciplinary ecological and geographical science65-73Landscape Ecology52)<7 Naveh, Z.2007-In memoriam of Francsco Di Castri (1930-2005)5-6Landscape Ecology221Biographical-ItemJan://000243619800002 }ISI Document Delivery No.: 127XO Times Cited: 0 Cited Reference Count: 1 Cited References: DICASTRI F, PUBLICATION LIST 0921-2973 Landsc. Ecol.ISI:000243619800002Technion Israel Inst Technol, Fac Civil & Environm Engn, IL-32000 Haifa, Israel. Naveh, Z, Technion Israel Inst Technol, Fac Civil & Environm Engn, IL-32000 Haifa, Israel. z.nave@hotmail.comEnglish<7 Naveh, Z.2007$Landscape ecology and sustainability 1437-1440Landscape Ecology2210Editorial MaterialDec://000250632100002TISI Document Delivery No.: 227BL Times Cited: 0 Cited Reference Count: 13 Naveh, Zev 0921-2973 Landsc. Ecol.ISI:000250632100002Technion Israel Inst Technol, Fac Civil & Environm Engn, IL-32000 Haifa, Israel. Naveh, Z, Technion Israel Inst Technol, Fac Civil & Environm Engn, IL-32000 Haifa, Israel. znave@technion.ac.ilEnglish<7 (Neel, M. C. McGarigal, K. Cushman, S. A.2004XBehavior of class-level landscape metrics across gradients of class aggregation and area435-455Landscape Ecology194connectivity; fragmentation; landscape pattern analysis; neutral landscape models; FRAGSTATS QUANTIFY SPATIAL-PATTERNS; FOREST-BREEDING BIRDS; HABITAT FRAGMENTATION; POPULATION SURVIVAL; MULTISCALE ANALYSIS; NEST PREDATION; LAND-COVER; EDGES; CONNECTIVITY; SCALEArticleyHabitat loss and fragmentation processes strongly affect biodiversity conservation in landscapes undergoing anthropogenic land use changes. Many attempts have been made to use landscape structure metrics to quantify the independent and joint effects of these processes. Unfortunately, ecological interpretation of those metrics has been plagued by lack of thorough understanding of their theoretical behavior. We explored behavior of 50 metrics in neutral landscapes across a 21-step gradient in aggregation and a 19-step gradient in area using a full factorial design with 100 replicates of each of the 399 combinations of the two factors to assess how well metrics reflected changes in landscape structure. Metric values from real landscapes were used to determine the extent of neutral landscape space that is represented in real landscapes. We grouped metrics into three major behavioral classes: strongly related to focal class area (n = 15), strongly related to aggregation (n = 7), and jointly responding to area and aggregation (n = 28). Metrics strongly related to class area exhibited a variety of distinct behaviors, and many of these metrics have unique interpretations that make each of them particularly useful in certain applications. Metrics strongly related to aggregation, independent of class area, are particularly useful in assessing effects of fragmentation. Moreover, metrics in this group exhibited a range of specific behaviors, highlighting subtle but different aspects of landscape aggregation even though we controlled only one aspect of aggregation. The non-linear behavior exhibited by many metrics renders interpretation difficult and use of linear analytical techniques inappropriate under many circumstances. Ultimately, comprehensive characterization of landscapes undergoing habitat loss and fragmentation will require using several metrics distributed across behavioral groups.://000221879000007 D ISI Document Delivery No.: 827DM Times Cited: 9 Cited Reference Count: 61 Cited References: *MATHWORKS INC, 2001, MATLAB *SAS I INC, 1999, SAS VERS 8 01 BELISLE M, 2002, CONSERV ECOL, V5, P480 BENDER DJ, 1998, ECOLOGY, V79, P517 BERGIN TM, 2000, LANDSCAPE ECOL, V15, P131 BOGAERT J, 2002, LANDSCAPE ECOLOGY, V17, P87 BOULET M, 2000, CAN FIELD NAT, V114, P83 BURKE DM, 2000, ECOL APPL, V10, P1749 CAIN DH, 1997, LANDSCAPE ECOL, V12, P199 CHEN JQ, 1995, ECOL APPL, V5, P74 DEMAYNADIER PG, 1998, CONSERV BIOL, V12, P340 EUSKIRCHEN ES, 2001, FOREST ECOL MANAG, V148, P93 FAHRIG L, 1985, ECOLOGY, V66, P1762 FAHRIG L, 1998, ECOL MODEL, V105, P273 FAHRIG L, 1998, ECOSYSTEMS, V1, P197 FAHRIG L, 2002, ECOL APPL, V12, P346 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GARDNER RH, 1999, LANDSCAPE ECOLOGICAL, P280 GEHLHAUSEN SM, 2000, PLANT ECOL, V147, P21 GIBBS JP, 1998, J WILDLIFE MANAGE, V62, P584 GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HARGIS CD, 1997, WILDLIFE LANDSCAPE E, P231 HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HAYDON DT, 1999, ECOSCIENCE, V6, P316 HE HS, 2000, LANDSCAPE ECOL, V15, P591 HESKE EJ, 2001, WILDLIFE SOC B, V29, P52 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 JAEGER JAG, 2000, LANDSCAPE ECOL, V15, P115 KAREIVA P, 1995, NATURE, V373, P299 KEITT TH, 1997, CONSERV ECOL, V1 KRUMMEL JR, 1987, OIKOS, V48, P321 LI HB, 1993, LANDSCAPE ECOL, V8, P155 MANCKE RG, 2000, ECOL APPL, V10, P598 MCGARIGAL K, 1995, ECOL MONOGR, V65, P235 MCGARIGAL K, 1995, PNW351 USDA GTR FOR MCGARIGAL K, 2002, ENCY ENV, V2, P1135 MCGARIGAL K, 2002, FRAGSTATS SPATIAL PA MERRIAM DF, 1966, J GEOPHYS RES, V71, P1105 MILNE BT, 1988, APPL MATH COMPUT, V27, P67 MOILANEN A, 2002, ECOLOGY, V83, P1131 ONEILL RV, 1996, LANDSCAPE ECOL, V11, P169 ONEILL RV, 1997, BIOSCIENCE, V47, P513 RIITTERS K, 2000, CONSERV ECOL, V4, P27 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 RIPPLE WJ, 1991, BIOL CONSERVATION, V57 ROBINSON AH, 1957, ANN ASSOC AM GEOGR, V47, P379 ROBINSON AH, 1962, ANN ASSOC AM GEOGR, V52, P414 SAUPE D, 1988, SCI FRACTAL IMAGES, P71 SAURA S, 2000, LANDSCAPE ECOL, V15, P661 SAURA S, 2002, INT J REMOTE SENS, V23, P4853 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 STAUFFER DF, 1985, INTRO PERCOLATION TH TRZCINSKI MK, 1999, ECOL APPL, V9, P586 TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 WICKHAM JD, 1999, LANDSCAPE ECOL, V14, P137 WICKHAM JD, 2000, J AM WATER RESOUR AS, V36, P1417 WITH KA, 1997, OIKOS, V78, P151 WITH KA, 2001, BIOL CONSERV, V100, P75 WU JG, 2002, LANDSCAPE ECOL, V17, P761 0921-2973 Landsc. Ecol.ISI:000221879000007Univ Massachusetts, Holdsworth Nat Resources Ctr, Dept Nat Resources Conservat, Amherst, MA 01003 USA. Neel, MC, Univ Maryland, Dept Nat Resource Sci & Landscape Architecture, 2116 Plant Sci Bldg, College Pk, MD 20742 USA. mneel@umd.eduEnglish _<7&Neilson, R. P. King, G. A. Koerper, G.1992Toward a rule-based biome model27-43Landscape Ecology71MBIOGEOGRAPHY; BIOME; CLIMATE; MODEL; UNITED-STATES; VEGETATION; WATER BALANCEArticleAprvCurrent projections of the response of the biosphere to global climatic change indicate as much as 50% to 90% spatial displacement of extratropical biomes. The mechanism of spatial shift could be dominated by either 1) competitive displacement of northern biomes by southern biomes, or 2) drought-induced dieback of areas susceptible to change. The current suite of global biosphere models cannot distinguish between these two processes, thus determining the need for a mechanistically based biome model. The first steps have been taken towards the development of a rule-based, mechanistic model of regional biomes at a continental scale. The computer model is based on a suite of empirically generated conceptual models of biome distribution. With a few exceptions the conceptual models are based on the regional water balance and the potential supply of water to vegetation from two different soil layers, surface for grasses and deep for woody vegetation. The seasonality of precipitation largely determines the amount and timing of recharge of each of these soil layers and thus, the potential mixture of vegetative life-forms that could be supported under a specific climate. The current configuration of rules accounts for the potential natural vegetation at about 94% of 1211 climate stations over the conterminous U.S. Increased temperatures, due to global warming, would 1) reduce the supply of soil moisture over much of the U.S. by reducing the volume of snow and increasing winter runoff, and 2) increase the potential evapotranspiration (PET). These processes combined would likely produce widespread drought-induced dieback in the nation's biomes. The model is in an early stage of development and will require several enhancements, including explicit simulation of PET, extension to boreal and tropical biomes, a shift from steady-state to transient dynamics, and validation on other continents.://A1992HX80900003 IISI Document Delivery No.: HX809 Times Cited: 58 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1992HX80900003YNEILSON, RP, OREGON STATE UNIV,US EPA,ENVIRONM RES LAB,200 SW 35TH ST,CORVALLIS,OR 97333.English?Nellis, M.D. J. M. Briggs1989UThe effect of spatial scale on Konza landscape classification using textural analysis93-100Landscape Ecology22^spatial scale, textural analysis, tallgrass prairie, remote sensing, landscape ecology, KansasSpatial scale is inherent in the definition of landscape heterogeneity and diversity. For example, a landscape may appear heterogeneous at one scale but quite homogeneous at another scale. In assessing the impact of burning and grazing on the Konza Prairie Research Natural Area (a tallgrass prairie), spatial scale is extremely important. Textural contrast algorithms were applied to various scales of remote sensing data and related to landscape units for assessment of heterogeneity under a variety of burning treatments. Acquired data sets included Landsat multispectral scanner (MSS), with 80 m resolution, Landsat thematic mapper (TM), with 30 m resolution, and high resolution density sliced aerial photography (with a 5 m resolution). Results suggest that heterogeneous areas of dense patchiness (e.g., unburned areas) must be analyzed at a finer scale than more homogeneous areas which are burned at least every four years.,|?]VNelson, Kellen N. Rocca, Monique E. Diskin, Matthew Aoki, Carissa F. Romme, William H.2014Predictors of bark beetle activity and scale-dependent spatial heterogeneity change during the course of an outbreak in a subalpine forest97-109Landscape Ecology291JanClimate conditions and forest structure interact to determine the extent and severity of bark beetle outbreaks, yet the relative importance of each may vary though the course of an outbreak. In 2008, we conducted field surveys and reconstructed forest conditions at multiple stages within a recent mountain pine beetle (MPB) outbreak in Rocky Mountain National Park, Colorado. At each stage in the outbreak, we examined changes in (1) lodgepole pine mortality and surviving stand structure, (2) the influence of topographic versus stand structure variables on mortality rates, and (3) stand complexity and landscape heterogeneity. Lodgepole pine mortality reduced basal area by 71 %, but only 47 % of stems were killed. Relative to pre-outbreak stands, surviving stands had lower mean dbh (11.0 vs. 17.4 cm), lower basal area (8.5 vs. 29.3 m(2) ha(-1)), lower density (915 vs. 1,393 stems ha(-1)), and higher proportions of non-host species (23.1 vs. 10.6 % m(2) ha(-1)). Factors predicting mortality rates changed through the course of the outbreak. Tree mortality during the early stage of the outbreak was associated with warm, dry sites and abundant large trees. During the middle and late stages, mortality was associated with stand structure alone. Stand complexity increased, as defined by stand-scale variability in density, basal area, and the proportion of susceptible trees. Landscape heterogeneity decreased according to semi-variograms of tree diameter and basal area. Increased stand complexity may inhibit future MPB population development, but decreased landscape heterogeneity may facilitate outbreak spread across the landscape if a future outbreak were to irrupt.!://WOS:000330827600008Times Cited: 3 0921-2973WOS:00033082760000810.1007/s10980-013-9954-1?QR.W. Nero J.J. Magnuson1992[Effects of changing spatial scale on acoustic observations of patchiness in the Gulf Stream279-291Landscape Ecology641patchiness, nekton, Gulf Stream, acoustics, scaleWe examine the influence of spatial scale on studies of nektonic patchiness at the north edge of the Gulf Stream by altering the grain size of acoustic cross sections and applying a patch-finding algorithm. From original ‘pictures’ of 180 pixels deep by 540- 1260 pixels long, we averaged depth and length, to give 9 scales ranging from fine grain (1 m vertical x 25 m horizontal sized pixels) to coarse grain (12 m x 300 m sized pixels). Measures of overall echo intensity within patches were the most predictable and showed little change with scale. Measures of variability of the echo within patches showed simple negative trends with scale and were best measured at fine spatial scales. Patch size and shape related variables have a more complex relationship with scale with differences between day and night transects more pronounced at intermediate scales. This suggests behavioral patch forming mechanisms within the nekton occur at a specific grain size (4 m vertical x 100 m horizontal) within the Gulf Stream front.I|?-Neubauer, Scott C.2014eOn the challenges of modeling the net radiative forcing of wetlands: reconsidering Mitsch et al. 2013571-577Landscape Ecology294AprWetlands play a role in regulating global climate by removing carbon dioxide (CO2) from the atmosphere and sequestering it as soil carbon, and by emitting methane (CH4) and nitrous oxide (N2O) to the atmosphere. In a recent article in this journal (Mitsch et al. Landscape Ecol 28:583-597, 2013), CO2 sequestration and CH4 emissions were modeled for several freshwater wetlands that vary in vegetation type, climate, and hydrology. The authors of that study made significant errors that caused them to underestimate the importance of wetland CH4 emissions on climate dynamics. Here, I reanalyze the Mitsch et al. dataset and show that all of their wetlands had an initial warming effect but eventually caused negative net radiative forcing within similar to 60-14,000 years, depending on the ratio of CO2 sequestration to CH4 emissions. The addition of a N2O component to the model suggested that typical wetland N2O emission rates would contribute only a minor burden to wetland radiative forcing, although specific application of this three-gas model is limited by the paucity of sites where CO2 sequestration, CH4 emission, and N2O exchange rates have all been measured. Across the landscape, many natural wetlands may already cause negative net radiative forcing when integrated over their lifetime. However, caution should be applied when using carbon sequestration as a rationale for designing wetland construction and restoration projects since freshwater wetlands may have a net positive (warming) effect on climate for decades to centuries or longer.!://WOS:000333533800002Times Cited: 3 0921-2973WOS:00033353380000210.1007/s10980-014-9986-1|? bNeumann, K. Elbersen, B. S. Verburg, P. H. Staritsky, I. Perez-Soba, M. de Vries, W. Rienks, W. A.20099Modelling the spatial distribution of livestock in Europe 1207-1222Landscape Ecology249Livestock remains the world's largest user of land and is strongly related to grassland and feed-crop production. Assessments of environmental impacts of livestock farming require detailed knowledge of the presence of livestock, farming practices, and environmental conditions. The present Europe-wide livestock distribution information is generally restricted to a spatial resolution of NUTS 2 ( province level). This paper presents a modelling approach to determine the spatial distribution of livestock at the landscape level. Location factors for livestock occurrence were explored and applied to consistent and harmonized EU-wide regional statistics to produce a detailed spatial distribution of livestock numbers. Both an expert-based and an empirical approach were applied in order to disaggregate the data to grid level. The resulting livestock maps were validated. Results differ between the two downscaling approaches but also between livestock types and countries. While both the expert-based and empirical approach are equally suited to modelling herbivores, in general, the spatial distribution of monogastrics can be better modelled by applying the empirical approach.!://WOS:000270739000006Times Cited: 1 0921-2973WOS:00027073900000610.1007/s10980-009-9357-5<7d+Neville, H. M. Dunham, J. B. Peacock, M. M.2006rLandscape attributes and life history variability shape genetic structure of trout populations in a stream network901-916Landscape Ecology216bottlenecks; connectivity; cutthroat trout; dispersal; effective population size; founder effects; habitat structure; landscape genetics; metapopulation; Oncorhynchus clarkii LAHONTAN CUTTHROAT TROUT; MAXIMUM-LIKELIHOOD-ESTIMATION; TRUTTA L. POPULATIONS; SALMON SALMO-SALAR; MICROSATELLITE LOCI; CONSERVATION IMPLICATIONS; METAPOPULATION DYNAMICS; COALESCENT APPROACH; TEMPORAL-CHANGES; MIGRATIONArticleAugSpatial and temporal landscape patterns have long been recognized to influence biological processes, but these processes often operate at scales that are difficult to study by conventional means. Inferences from genetic markers can overcome some of these limitations. We used a landscape genetics approach to test hypotheses concerning landscape processes influencing the demography of Lahontan cutthroat trout in a complex stream network in the Great Basin desert of the western US. Predictions were tested with population- and individual-based analyses of microsatellite DNA variation, reflecting patterns of dispersal, population stability, and local effective population sizes. Complementary genetic inferences suggested samples from migratory corridors housed a mixture of fish from tributaries, as predicted based on assumed migratory life histories in those habitats. Also as predicted, populations presumed to have greater proportions of migratory fish or from physically connected, large, or high quality habitats had higher genetic variability and reduced genetic differentiation from other populations. Populations thought to contain largely non-migratory individuals generally showed the opposite pattern, suggesting behavioral isolation. Estimated effective sizes were small, and we identified significant and severe genetic bottlenecks in several populations that were isolated, recently founded, or that inhabit streams that desiccate frequently. Overall, this work suggested that Lahontan cutthroat trout populations in stream networks are affected by a combination of landscape and metapopulation processes. Results also demonstrated that genetic patterns can reveal unexpected processes, even within a system that is well studied from a conventional ecological perspective.://000239484200010 ;ISI Document Delivery No.: 069YA Times Cited: 1 Cited Reference Count: 82 Cited References: ALLAN DJ, 2004, ANN REV ECOL EVOL SY, V35 ANGERS B, 1995, J FISH BIOL A, V47, P177 ANGERS B, 1999, MOL ECOL, V8, P1043 ARSENAULT HN, 2003, THESIS U NEVADA RENO BEERLI P, 1999, GENETICS, V152, P763 BEERLI P, 2001, P NATL ACAD SCI USA, V98, P4563 BEHNKE RJ, 1992, NATIVE TROUT W N AM BERRY O, 2005, CONSERV BIOL, V19, P855 COLYER W, 2002, THESIS UTAH STATE U CORNUET JM, 1999, GENETICS, V153, P1989 COSTELLO AB, 2003, EVOLUTION, V57, P328 COUVET D, 2002, CONSERV BIOL, V16, P369 DAVIES N, 1999, TRENDS ECOL EVOL, V14, P17 DUNHAM JB, 1996, THESIS U NEVADA RENO DUNHAM JB, 1997, N AM J FISH MANAGE, V17, P1126 DUNHAM JB, 1999, T AM FISH SOC, V128, P875 DUNHAM JB, 2002, PREDICTING SPECIES O, P327 DUNHAM JB, 2003, FOREST ECOL MANAG, V178, P183 FAUSCH KD, 2002, BIOSCIENCE, V52, P483 FLEISHMAN E, 2002, CONSERV BIOL, V16, P706 FUNK WC, 2005, MOL ECOL, V14, P483 GARZA JC, 2001, MOL ECOL, V10, P305 GERLACH G, 2000, CONSERV BIOL, V14, P1066 GOUDET J, 2001, FSTAT PROGRAM ESTIMA GOWAN C, 1994, CAN J FISH AQUAT SCI, V51, P2626 HALE ML, 2001, SCIENCE, V293, P2246 HANSEN MM, 1997, MOL ECOL, V6, P469 HANSEN MM, 1998, HEREDITY 5, V81, P493 HANSKI I, 1994, TRENDS ECOL EVOL, V9, P131 HANSKI I, 1997, METAPOPULATION BIOL, P1 HANSKI I, 1999, METAPOPULATION ECOLO HANSKI I, 2001, AM NAT, V158, P341 HANSKI I, 2002, OIKOS, V98, P87 HANSKI I, 2004, ECOL LETT, V7, P958 HARTL DL, 1997, PRINCIPLES POPULATIO HEDRICK PW, 1997, METAPOPULATION BIOL, P166 HEDRICK PW, 1999, EVOLUTION, V53, P313 HENDRY AP, 2004, EVOLUTION ILLUMINATE, P93 INGRAM KK, 2003, ECOLOGY, V84, P2832 JONSSON B, 1993, REV FISH BIOL FISHER, V3, P348 KNUTSEN H, 2001, HEREDITY 2, V87, P207 LEVINS R, 1969, B ENTOMOL SOC AM, V15, P237 MACARTHUR RH, 1967, THEORY ISLAND BIOGEO MANEL S, 2003, TRENDS ECOL EVOL, V18, P189 MCCONNELL SK, 1995, CAN J FISH AQUAT SCI, V52, P1863 MOILANEN A, 1999, ECOLOGY, V80, P1031 MONTGOMERY DR, 1999, J AM WATER RESOUR AS, V35, P397 MORRIS DB, 1996, CAN J FISH AQUAT SCI, V53, P120 NAKANO S, 1996, FRESHWATER BIOL, V36, P711 NASLUND I, 1993, ECOL FRESHW FISH, V2, P51 NEI M, 1987, MOL EVOLUTIONARY GEN NEVILLE H, IN PRESS CONNECTIVIT NIELSEN JL, 2002, T AM FISH SOC, V131, P376 NORTHCOTE TG, 1988, POL ARCH HYDROBIOL, V35, P409 OREILLY PT, 1996, CAN J FISH AQUAT SCI, V53, P2292 OSTERGAARD S, 2003, MOL ECOL, V12, P3123 PARKER HG, 2004, SCIENCE, V304, P1160 PEACOCK MM, 2004, MOL ECOL NOTES, V4, P557 PRITCHARD JK, 2000, GENETICS, V155, P945 PULLIAM HR, 1988, AM NAT, V132, P652 RAY C, 2001, BIOL CONSERV, V100, P3 RIEMAN BE, 2000, ECOL FRESHW FISH, V9, P51 SACCHERI I, 1998, NATURE, V392, P491 SCHLOSSER IJ, 1995, AM FISH S S, V17, P392 SCHLOSSER IJ, 1995, HYDROBIOLOGIA, V303, P71 SCHNEIDER S, 2000, ARLEQUIN VER 2 0000 SCHRANK AJ, 2004, CAN J FISH AQUAT SCI, V61, P1528 SCRIBNER KT, 1996, CAN J FISH AQUAT SCI, V53, P833 SLATKIN M, 1985, ANNU REV ECOL SYST, V16, P393 SMEDBOL RK, 2002, FISH FISH, V3, P20 STEINBERG EK, 2002, MOL BIOL EVOL, V19, P1198 TABERLET P, 1999, BIOL J LINN SOC, V68, P41 TAYLOR EB, 2003, MOL ECOL, V12, P2609 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 2003, BIOSCIENCE, V53, P46 WALKER SR, 2003, LANDCAPE ECOLOGY, V18, P185 WAPLES RS, 1990, CAN J FISH AQUAT SCI, V47, P968 WEBER JL, 1993, HUM MOL GENET, V2, P1123 WEIR BS, 1984, EVOLUTION, V38, P1358 WHITLOCK MC, 1999, HEREDITY 2, V82, P117 WIENS JA, 2002, FRESHWATER BIOL, V47, P501 WOFFORD JEB, 2005, ECOL APPL, V15, P638 0921-2973 Landsc. Ecol.ISI:000239484200010Univ Nevada, Dept Biol 314, Reno, NV 89557 USA. Rocky Mt Res Stn, Boise, ID 83702 USA. USGS FRESC Corvallis Res Grp, Corvallis, OR 97331 USA. Neville, HM, Univ Nevada, Dept Biol 314, Reno, NV 89557 USA. hneville@unr.nevada.eduEnglish <7+Nicholls, C. I. Parrella, M. Altieri, M. A.2001The effects of a vegetational corridor on the abundance and dispersal of insect biodiversity within a northern California organic vineyard133-146Landscape Ecology162xbiological control landscape ecology leafhoppers thrips vineyards ARTHROPODS DIVERSIFICATION LEAFHOPPER FARMLAND CEREALSArticleFebDuring 1996 and 1997, two adjacent 2.5 has organic vineyard blocks (A and B) were monitored to assess the distributional and abundance patterns of the Western grape leafhopper Erythroneura elegantula Osborn (Homoptera: Cicadellidae) and its parasitoid Anagrus epos Girault (Hymenoptera: Mymaridae), Western flower thrips Frankliniella occidentalis (Pergande) and generalist predators. The main difference between blocks was that block A was cut across by a corridor composed of 65 flowering plant species which was connected to the surrounding riparian habitat, whereas block B had no plant corridor. In both years, leafhopper adults and nymphs and thrips tended to be more numerous in the middle rows of block A and less abundant in border rows close to the forest and corridor where predators were more abundant. The complex of predators circulating through the corridor moved to the adjacent vine rows and exerted a regulatory impact on herbivores present in such rows. In block B all insects were evenly distributed over the field, no obvious density gradient was detected from the edges into the center of the field. Although it is suspected that A. epos depended on food resources of the corridor, it did not display a gradient from this rich flowering area into the middle of the field. Likewise no differences in rates of egg parasitism of leafhoppers could be detected in vines near the corridor or in the vineyard center. The presence of riparian habitats enhanced predator colonization and abundance on adjacent vineyards, although this influence was limited by the distance to which natural enemies dispersed into the vineyard. However, the corridor amplified this influence by enhancing timely circulation and dispersal movement of predators into the center of the field.://000167936500005 ISI Document Delivery No.: 419EN Times Cited: 16 Cited Reference Count: 20 Cited References: ALTIERI MA, 1994, BIODIVERSITY PEST MA BAUDRY J, 1984, METHODOLOGY LANDSCAP, V1, P55 COOMBES DS, 1986, ANN APPL BIOL, V108, P461 CORBETT A, 1993, ENVIRON ENTOMOL, V22, P519 CORBETT A, 1996, ECOL ENTOMOL, V21, P155 DOUTT RL, 1973, ENVIRON ENTOMOL, V2, P381 DUELLI P, 1990, BIOL CONSERV, V54, P193 FLAHERTY DL, 1992, GRAPE PEST MANAGEMEN FRY G, 1995, ECOLOGY INTEGRATED F, P177 KIDO H, 1984, AM J ENOL VITICULT, V35, P156 LEWIS T, 1965, SCI HORTICULTURE, V17, P74 LYS JA, 1994, ENTOMOL EXP APPL, V73, P1 MURPHY BC, 1996, ENVIRON ENTOMOL, V25, P495 NENTWIG W, 1998, CONSERVATION BIOL CO, P133 POLLARD E, 1968, J APPL ECOL, V5, P649 ROSENBERG DK, 1997, BIOSCIENCE, V47, P677 SETTLE WH, 1990, ECOLOGY, V71, P1461 SOTHERTON NW, 1984, ANN APPL BIOL, V105, P423 THOMAS MB, 1991, J APPL ECOL, V28, P906 WRATTEN SD, 1988, ENV MANAGEMENT AGR 0921-2973 Landsc. Ecol.ISI:000167936500005Univ Calif Cooperat Extens Alameda Cty, Alameda, CA 94502 USA. Nicholls, CI, Univ Calif Cooperat Extens Alameda Cty, 1131 Harbor Bay Pkwy,Suite 131, Alameda, CA 94502 USA.Englishڽ7 -Nicol, Samuel Roach, JenniferK Griffith, Brad2013nSpatial heterogeneity in statistical power to detect changes in lake area in Alaskan National Wildlife Refuges507-517Landscape Ecology283Springer NetherlandspStatistical power Mixed model Lake drying Alaska Temporal sampling Regional trend Trend detection Climate change 2013/03/01+http://dx.doi.org/10.1007/s10980-013-9853-5 0921-2973Landscape Ecol10.1007/s10980-013-9853-5English<7]Niemela, J. Kotze, D. J. Venn, S. Penev, L. Stoyanov, I. Spence, J. Hartley, D. de Oca, E. M.2002lCarabid beetle assemblages (Coleoptera, Carabidae) across urban-rural gradients: an international comparison387-401Landscape Ecology175uBulgaria Canada Carabidae Finland urban-rural gradients urbanisation DIVERSITY ECOLOGY FOREST BIODIVERSITY MANAGEMENTArticleOctbWe studied communities of carabid beetles in residual forest patches along urban-suburban-rural gradients in three cities (Helsinki, Finland; Sofia, Bulgaria and Edmonton, Canada) to examine their responses to urbanisation. Only Finnish carabids showed a marked division of community structure along the gradient. In Bulgaria and Canada, carabids did not separate into distinct urban, suburban and rural communities. Our results provide some support for the predictions that species richness will decrease, that opportunistic species will gain dominance, and that small-sized species will become more numerous under disturbance such as that provided by urbanisation. The rather weak and varied response of carabids to this disturbance suggests that local factors and their interaction are of primary importance for community composition. Occurrence of reasonably similar carabid communities across the gradient at each of the three levels of urbanisation suggests that habitat changes commonly associated with urbanisation have not affected the ecological integrity of carabid assemblages in residual urban forest patches.://000179388800002 ISI Document Delivery No.: 617YP Times Cited: 19 Cited Reference Count: 52 Cited References: AHTI T, 1968, ANN BOT FENN, V5, P169 BAEV PV, 1995, BIODIV PROGRAM CALCU BERG A, 1994, CONSERV BIOL, V8, P718 BLAKE S, 1994, PEDOBIOLOGIA, V38, P502 CLARKE KR, 1994, CHANGE MARINE COMMUN COLWELL RK, 1994, PHILOS T ROY SOC B, V345, P101 CONNELL JH, 1978, SCIENCE, V199, P1302 DAVIS BNK, 1978, DIVERSITY INSECT FAU, P126 DAVIS BNK, 1978, LONDON NATURALIST, V58, P15 DESENDER K, 1991, ELYTRON, P239 DESENDER K, 1994, CARABID BEETLES ECOL DESENDER KRC, 1996, ANN ZOOL FENN, V33, P65 DOUGLAS I, 1992, URBAN NATURE MAGAZIN, V1, P15 DUFRENE M, 1997, ECOL MONOGR, V67, P345 EVERSHAM BC, 1996, ANN ZOOL FENN, V33, P149 FRANKIE GW, 1978, ANNU REV ENTOMOL, V23, P367 FREUDE H, 1976, KAFER MITTELEUROPAS, V2, P1 GILLER PS, 1996, BIODIVERS CONSERV, V5, P135 GRAY JS, 1987, ORG COMMUNITIES PAST, P53 GRAY JS, 1989, BIOL J LINN SOC, V37, P19 HALME E, 1993, ANN ZOOL FENN, V30, P17 HELIOVAARA K, 1984, ACTA FOR FENN, V189, P1 HURKA K, 1996, CARABIDAE CZECH SLOV LINDQUIST A, 1985, STOCHASTICS, V15, P1 LINDROTH CH, 1961, OPUSC ENTOMOL, P1 LINDROTH CH, 1963, OPUSCULA ENTOMOLOG S, V24, P201 LINDROTH CH, 1966, OPUSC ENT S, V29, P409 LINDROTH CH, 1968, OPUSCULA ENTOMOLOG S, V33, P649 LINDROTH CH, 1969, OPUSCULA ENTOMOLOG S, V34, P945 LINDROTH CH, 1986, FAUNA ENTOMOLOGICA 2, V15 LOVEI GL, 1996, ANNU REV ENTOMOL, V41, P231 LUFF ML, 1996, ANN ZOOL FENN, V33, P185 MAGURA T, 2000, ACTA ZOOL ACAD SCI H, V46, P1 MCDONNELL MJ, 1990, ECOLOGY, V71, P1232 MCDONNELL MJ, 1993, HUMANS COMPONENTS EC, P175 MCDONNELL MJ, 1997, URBAN ECOSYSTEMS, V1, P21 NAEEM S, 1994, NATURE, V368, P734 NIEMELA J, 1991, OIKOS, V62, P351 NIEMELA J, 1994, PERSPECTIVES INSECT, P29 NIEMELA J, 1996, ANN ZOOL FENN, V33, P1 NIEMELA J, 1999, BIODIVERS CONSERV, V8, P119 NIEMELA J, 2000, J INSECT CONSERV, V4, P3 NIEMELA J, 2000, URBAN ECOSYSTEMS, V3, P57 POUYAT RV, 1997, URBAN ECOSYSTEMS, V1, P117 PROBST JR, 1991, J FOREST, V89, P12 PUTMAN RJ, 1996, COMMUNITY ECOLOGY SOKAL RR, 1995, BIOMETRY SPENCE JR, 1988, MEMOIRS ENTOMOLOGICA, P151 STORK N, 1990, ROLE GROUND BEETLES TONTERI T, 1990, ANN BOT FENN, V27, P337 VANDRUFF LW, 1995, URBAN ECOLOGY BASIS, P203 WOOTTON JT, 1998, AM NAT, V152, P803 0921-2973 Landsc. Ecol.ISI:000179388800002Univ Helsinki, Dept Systemat & Ecol, Div Populat Biol, FIN-00014 Helsinki, Finland. Niemela, J, Univ Helsinki, Dept Systemat & Ecol, Div Populat Biol, POB 17, FIN-00014 Helsinki, Finland.English<7o(Nikora, V. I. Pearson, C. P. Shankar, U.1999@Scaling properties in landscape patterns: New Zealand experience17-33Landscape Ecology141landscape patchiness scaling fractal dimensions self-similarity self-affinity neutral landscape models FRACTAL GEOMETRY CONNECTIVITY SIMULATION MODELSArticleFebIn this paper we present a case study of spatial structure in landscape patterns for the North and South Islands of New Zealand. The aim was to characterise quantitatively landscape heterogeneity and investigate its possible scaling properties. The study examines spatial heterogeneity, in particular patchiness, at a range of spatial scales, to help build understanding on the effects of landscape heterogeneity on water movement in particular, and landscape ecology in general. We used spatial information on various landscape properties (soils, hydrogeology, vegetation, topography) generated from the New Zealand Land Resource Inventory. To analyse this data set we applied various methods of fractal analyses following the hypothesis that patchiness in selected landscape properties demonstrates fractal scaling behaviour at two structural levels: (1) individual patches; and (2) mosaics (sets) of patches. Individual patches revealed scaling behaviour for both patch shape and boundary. We found self-affinity in patch shape with Hurst exponent H from 0.75 to 0.95. We also showed that patch boundaries in most cases were self-similar and in a few cases of large patches were self-affine. The degree of self-affinity was lower for finer patches. Similarly, when patch scale decreases the orientation of patches tends to be uniformly distributed, though patch orientation on average is clearly correlated with broad scale geological structures. These results reflect a tendency to isotropic behaviour of individual patches from broad to finer scales. Mosaics of patches also revealed fractal scaling in the total patch boundaries, patch centers of mass, and in patch area distribution. All these reflect a special organisation in patchiness represented in fractal patch clustering. General relationships which interconnect fractal scaling exponents were derived and tested. These relationships show how scaling properties of individual patches affect-those for mosaics of patches and vice-versa. To explain similarity in scaling behaviour in patchiness of different types we suggest that the Self-Organised Criticality concept should be used. Also, potential applications of our results in landscape ecology are discussed, especially in relation to improved neutral landscape models.://000079005100002 mISI Document Delivery No.: 173XM Times Cited: 16 Cited Reference Count: 40 Cited References: *ESRI, 1992, UND GIS ARC INFO MET BAK P, 1996, NATURE WORKS SCI SEL BOUR O, 1997, WATER RESOUR RES, V33, P1567 CLAUSEN B, 1995, J HYDROL, V173, P111 DUNCAN MJ, 1991, WS1423 HYDR CTR FEDER J, 1988, FRACTALS GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GARDNER RH, 1993, HUMANS COMPONENTS EC, P208 GOODCHILD MF, 1987, ANN ASSOC AM GEOGR, V77, P265 GRASSBERGER P, 1983, PHYS REV LETT, V50, P346 HASTINGS HM, 1993, FRACTALS USERS GUIDE HUTCHINSON PD, 1990, PUBLICATION HYDROLOG, V22 KING AW, 1991, QUANTITATIVE METHODS, P479 KRUMMEL JR, 1987, OIKOS, V48, P321 LAGRO J, 1991, PHOTOGRAMM ENG REM S, V57, P285 LEVIN SA, 1993, LECT NOTES BIOMATEMA LIEBOVITCH LS, 1989, PHYS LETT A, V141, P386 MANDELBROT BB, 1983, FRACTAL GEOMETRY NAT MATSUSHITA M, 1989, PHYSICA D, V38, P246 MCKERCHAR AI, 1991, J HYDROL NZ, V30, P65 MILNE BT, 1991, QUANTITATIVE METHODS, P199 MILNE BT, 1992, AM NAT, V139, P32 MILNE BT, 1992, THEOR POPUL BIOL, V41, P337 MOON FC, 1987, CHAOTIC VIBRATIONS NEWSOME PFJ, 1992, NZ LAND RESOURCE INV NIKORA VI, 1993, WATER RESOUR RES, V29, P3561 OUCHI S, 1992, GEOMORPHOLOGY, V5, P115 PEARSON CP, 1991, J HYDROL N Z, V30, P77 PEARSON CP, 1995, J HYDROL, V33, P94 PUIGDEFABREGAS J, 1996, ADV HILLSLOPE PROCES, V2, P1027 SAPOZHNIKOV V, 1995, J PHYS A-MATH GEN, V28, P559 SARRAILLE J, 1992, PROGRAM CALCULATING SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SEYFRIED MS, 1995, WATER RESOUR RES, V31, P173 TURCOTTE DL, 1992, FRACTALS CHAOS GEOLO TURNER MG, 1991, QUANTITATIVE METHODS WIENS JA, 1997, OIKOS, V78, P257 WITH KA, 1997, OIKOS, V78, P151 WITH KA, 1997, OIKOS, V79, P219 WU JG, 1997, ECOL MODEL, V101, P325 0921-2973 Landsc. Ecol.ISI:000079005100002Natl Inst Water & Atmospher Res Ltd, Christchurch, New Zealand. Nikora, VI, Natl Inst Water & Atmospher Res Ltd, POB 8602, Christchurch, New Zealand.EnglishX?#Nobukazu, Nakagoshi Toshiaki, Kondo2002BEcological land evaluation for nature redevelopment in river areas83-93Landscape Ecology170/Corridor - Evaluation - GIS - River enhancementLandscape enhancement projects are under way at the Yamanakadani and Kadowaki rivers, which run through the campus of Hiroshima University, Japan. At both sites, the ecological value of land was determined from two aspects: (1) value as vegetation and (2) value to birds. To evaluate the vegetation, we selected conservation sites and suitable sites for enhancement considering rarity and recovery potential of vegetation, and access to users and construction equipment. We determined that the area of forest, the number of forest vertical layers, and forest pattern help sustain avian diversity and contribute toward the area functioning as an avian corridor. *http://dx.doi.org/10.1023/A:1015285828041 10.1023/A:1015285828041 Nobukazu Nakagoshi Email: nobu@hiroshima-u.ac.jp Phone: 81 824 24 6511 Fax: 81 824 24 0758 References Askin R.A., Philbrick M.J. and Sugeno D.S. Relationship between the regional abundance of forest and the composition of forest bird communities. Biol. Conserv. 39: 129-152. Dmowski K. and Kozakiewicz M. 1990. Influence of shrub corridor on movements of passerine birds to a lake littoral zone. Landscape Ecol. 4: 99-108. Erdelen M. 1984. Bird communities and vegetation structure. 1. Correlations and comparisons of simple and diversity indices. Oecologia 61: 277-284. Forman R.T.T. 1983. Corridors in a landscape: Their ecological structure and function. Ekologia (CSSR) 2: 375-387. Forman R.T.T., 1995. Land Mosaic. The Ecology of Landscapes and Regions. Cambridge University Press, Cambridge, UK. Forman R.T.T. and Godron M. 1986. Landscape Ecology. John Wiley and Sons, New York, NY, USA. Freemark K.E. and Merriam H.G. 1986. Importance of area and habitat heterogeneity to bird assemblages in temperate forest fragment. Biol. Conserv. 36: 115-141. Gates J.E. and Mosher J.A. 1981. A functional approach to estimating habitat edge width for birds. Am. Midland Nat. 105: 189-192. Hanski I.A. and Gilpin M.E. 1997. Metapopulation biology. Academic Press, San Diego, USA. Harms W.B. and Opdam P. 1990. Woods as habitat patches for birds: Application in landscape planning in the Netherlands. In: Zonnevelt I.S. and Forman R.T.T. (eds.), Changing Landscape. Springer-Verlag, New York, NY, USA, pp. 73-97. Howe R.W. 1984. Local dynamics of bird assemblages in Australia and North America. Ecology 65(5): 1585-1601. Hudson W.E. 1991. Landscape linkages and biodiversity. Island Press, Washington DC, USA. Ide H., Kameyama A., Takeuchi K., Inoue K. and Munehisa I., 1976 Phytosociological study on the roadside vegetation. Appl. Phytosoc. 4: 26-44 (in Japanese with English summary). Josef B. 1993. Grundlagen des Biotopschutzes fur Tiere (4. Auflage). Bundesamt fur Naturschutz, Bonn, Germany. Kameyama A. 1973. Phytosociological studies for rural land use planning. 1. Appl. Phytosoc 2: 1-22 (in Japanese with English summary). Kameyama A., Ide H., Ito N., Katuno T. and Inoue K. 1975. Phytosociological discussion on programme of road construction. Appl. Phytosoc 4: 1-225 (in Japanese with English summary). Kondo T., Nakagoshi N. Tanimoto S., 1999. Landscape-ecological evaluation of biotope planning in the riparian area of Hiroshima University. J. Jpn. Instit. Landscape Architect. 62: 603-606 (in Japanese with English summary). Kroodsma R.L., 1984. Effect of edge on breeding forest bird species. Wilson Bull 96: 426-436. Kuramoto N., Hioki Y., Kameyama A., Yabu S., Katuno T., Haruta A. and Inoue I. 1995. Conservation biology and biotope planning (1). J. Jpn. Instit. Landscape Architect. 58: 408-414 (in Japanese). MacArthur R.H. and MacArthur J.W., 1961. On bird species diversity. Ecology 42: 594-598. Machtans C., Villard M. and Hannon S. 1996. Use of riparian buffer strips as movement corridors by forest birds. Conserv. Biol. 10: 1366-1379. Malanson G.P., 1993. Riparian Landscapes. Cambridge University Press, Cambridge, UK. Nancy E.M., 1995. Effects of forest patch size on avian diversity. Landscape Ecol. 10: 85-99. Naveh Z. and Lieberman A.S. 1984. Landscape Ecology. Theory Springer-Verlag, New York, NY, USA. Nomura K. and Nakagoshi N. 1999. Quantification of spatial structures in two landscape regions. J. Environ. Sci. 11: 188-194. The Nature Conservation Bureau and Asia Air Survey 1994. Report of the Fourth National Vegetation Survey. The Environment Agency, Tokyo (in Japanese with English summary). van Dorp D. and Opdam P. 1987. Effect of patch size, isolation and regional abundance on forest bird communities. Landscape Ecol. 1: 59-73. Zonneveld I.S. 1995. Land Ecology. An Introduction to Landscape Ecology as a Base for Land Evaluation, Land Management and Conservation. SPB Academic Publishing, Amsterdam, The Netherlands Nobukazu Nakagoshi1 and Toshiaki Kondo1 (1) Graduate School for International Development and Cooperation, Hiroshima University, Higashi-Hiroshima 739-8529, Japan ?CV. Noest1991|Simulated impact of sea level rise on phreatic level and vegetation of dune slacks in the Voorne dune area (The Netherlands)89-97Landscape Ecology61/2Ysea level rise, phreatic level, dune slack vegetation, interaction model, the NetherlandsEffects of sea level rise and different coastline management options on the phreatic level in a coastal dune area are calculated, using a scenario with 60 cm sea level rise in the course of the next century, resulting from global climatic changes. Changes in the phreatic level - both lowering and rising - are evaluated for their effects on the dune slack vegetation, using a newly developed interaction model ‘hydrology-vegetation’. Some indications of changes in nature conservation values are presented.7<7%$Norderhaug, A. Ihse, M. Pedersen, O.2000UBiotope patterns and abundance of meadow plant species in a Norwegian rural landscape201-218Landscape Ecology153biotope pattern fragmentation hay meadows landscape diversity Norway species diversity POLLINATION ECOLOGY RARE FRAGMENTATION POPULATION HABITAT EUROPE FLOWArticleAprPThe main purpose of this study was to describe the relative importance of hay meadows and other types of semi-natural grasslands for species diversity and to focus on the impact of the fragmentation of hay meadows on species diversity. The study area was the rural districts of Hjartdal and Seljord in the county of Telemark, southern Norway. Interrelationships between the landscape and vegetation were revealed by combining research at three hierarchical levels, i.e. the landscape, biotope and species levels. A descriptive and analytical technique based on CIR aerial photo interpretation was developed for the landscape mesoscale. The historical background of the landscape and former biotope patterns were described, since traditional and sustained management is an important parameter in the landscape ecological analysis. The vegetation of different grassland biotopes was classified and numerically analysed. The results of the aerial photo interpretation revealed a landscape with considerable complexity and high biodiversity both at landscape level and at biotope and species level, due to the many traditional hay meadows and pastures still left in this area. The results also showed that the remaining fragments of traditional hay meadows are of vital importance for biological diversity. They had the highest average number of species per subplot and furthermore contained species that did not occur in any other grassland biotopes. In addition, the largest populations of several grassland species were found in the traditionally managed hay meadows. Unfertilised pastures and verges along small roads were also species-rich but were not in this connection substitutes for the hay meadows, nor were the `modern' hay meadows or the verges along the main roads. The spatial distribution and configuration of the biotopes and the abundance of meadow plant species within the study area suggest that in order to maintain species diversity it may be important to preserve and manage all the remaining fragments of traditional hay meadows. The surrounding environment, the matrix, should also be managed appropriately.://000085293300003 ' ISI Document Delivery No.: 283UB Times Cited: 19 Cited Reference Count: 66 Cited References: *DIR NAT, 1994, SENTR UTV NASJ REG V ANDREN H, 1994, OIKOS, V71, P355 BASTIAN O, 1993, LANDSCAPE ECOL, V8, P139 BENGTSSONLINDSJ.S, 1991, ECOL B, V41, P388 BRANDT J, 1993, P 2 CONNECT WORKSH L, P89 COLLINS SL, 1990, AM NAT, V135, P633 COUSINS SAO, 1996, OVERVAKNING STRATEGI, P6 DRAMSTAD WE, 1996, THESIS AGR U NORWAY EILERTSEN O, 1988, U TRONDHEIM VITENSK, V1, P5 EILERTSEN O, 1990, J VEG SCI, V1, P261 EKMAN SR, 1968, 1 STOCKH U NAT I ERIKSSON A, 1995, ECOGRAPHY, V18, P310 FLATIN T, 1942, SELJORD, V1 FORMAN RTT, 1984, P 1 INT SEM METH LAN, P4 FORMAN RTT, 1986, LANDSCAPE ECOLOGY GARCIA A, 1992, AGR ECOSYST ENVIRON, V40, P219 HAEGGSTROM CA, 1987, BIOTOPER NORDISKA KU, P70 HANDEL SN, 1983, POLLINATION BIOL, P163 HODGSON JG, 1986, BIOL CONSERV, V36, P199 HUGHES J, 1988, CULTURAL LANDSCAPE P, P91 IHSE M, 1965, INT J HERITAGE STUDI, V1, P156 IHSE M, 1988, CULTURAL LANDSCAPE P, P154 IHSE M, 1994, FRAGMENTATION AGR LA, P194 IHSE M, 1995, URBAN PLANNING, V41, P11 IHSE M, 1996, KARTBLADET, V2, P32 JOHANSSON CE, 1993, BEBYGGELSESHISTORISK, V26, P24 KIELLANDLUND J, 1992, HDB FELTREGISTRERING KIENAST F, 1993, LANDSCAPE ECOL, V8, P103 KULL K, 1991, J VEG SCI, V2, P715 LEVIN DA, 1974, EVOL BIOL, V7, P139 LEVIN DA, 1981, ANN MO BOT GARD, V68, P233 LID J, 1985, NORSKSVENSK FINSK FL LID J, 1994, NORSK FLORA LOSVIK MH, 1993, LANDSCAPE ECOLOGY AG MACARTHUR RH, 1967, THEORY ISLAND BIOGEO MENGES ES, 1991, GENETICS CONSERVATIO, P45 MOEN A, 1993, HDB FELTREGISTRERING NEEF E, 1981, SITZUNGSBERICHTE MN, V115, P6 NORDERHAUG A, IN PRESS PERFORMANCE NORDERHAUG A, 1988, URTERIKE SLATTEENGER, P3 NORDERHAUG A, 1993, P 2 CONNECT WORKSH L, P60 NORDERHAUG A, 1995, NORD J BOT, V15, P243 NORDERHAUG A, 1997, BLYTTIA, V55, P73 OLESEN JM, 1989, OECOLOGIA, V79, P205 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 OOSTERMEIJER JGB, 1989, OECOLOGIA, V78, P302 OOSTERMEIJER JGB, 1994, OECOLOGIA, V97, P289 OPDAM P, 1990, SPECIES DISPERSAL AG, P3 PAHLSSON L, 1994, VEGETATIONSTYPER NOR, P665 PEDERSEN O, 1988, BIOL DATA PROGRAM PC PETANIDOU T, 1995, ACTA BOT NEERL, V44, P55 PETANIDOU T, 1995, NEW PHYTOL, V129, P155 ROHLF FJ, 1994, NTSYS PC NUMERICAL T ROMELL LG, 1942, GOTLANDSANGET DESS F SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SJORS H, 1954, ACTA PHYTOGEOGR SUEC, V34 SKOV F, 1995, P 2 CONNECT WORKSH L, P15 SOKAL RR, 1958, U KANSAS SCI B, V38, P1409 SPORRONG U, 1993, BEBYGGELSESHISTORISK, V26, P71 SVENSSON R, 1988, SVENSK BOT TIDSKR, V82, P458 SVENSSON R, 1990, SVENSK BOT TIDSKR, V84, P9 TERBRAAK CJF, 1987, CANOCO FORTRAN PROGR TERBRAAK CJF, 1990, UPDATES NOTES CANOCO TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 VERKAAR HJ, 1990, SPECIES DISPERSAL AG, P82 WILLSON MF, 1992, ECOLOGY REGENERATION, P61 0921-2973 Landsc. Ecol.ISI:000085293300003Sogn & Fjordane Coll, N-6851 Sogndal, Norway. Stockholm Univ, Dept Phys Geog, Unit Ecol Geog, S-10691 Stockholm, Sweden. Univ Oslo, Bot Garden & Museum, N-0562 Oslo, Norway. Norderhaug, A, Sogn & Fjordane Coll, Box 133, N-6851 Sogndal, Norway.English%|?>rNowicki, Piotr Vrabec, Vladimir Binzenhoefer, Birgit Feil, Johann Zaksek, Barbara Hovestadt, Thomas Settele, Josef2014JButterfly dispersal in inhospitable matrix: rare, risky, but long-distance401-412Landscape Ecology293MarMetapopulation models typically assume that suitable habitats occupied by local populations and unsuitable matrix separating them form a 'black-and-white' landscape mosaic, in which dispersal is primarily determined by the spatial configuration of habitat patches. In reality, however, the matrix composition is also likely to influence dispersal. Using intensive mark-recapture surveys we investigated inter-patch movements in Maculinea (Phengaris) nausithous and M. teleius occurring sympatrically in six metapopulations. Three of these metapopulations had the matrix dominated by forest, an inhospitable environment for grassland butterflies, whereas in the remaining three the matrix was mostly composed of open environments. Dispersal parameters derived with the Virtual Migration model revealed significant differences between both groups of metapopulations. Both species had a lower propensity to emigrate from their natal habitat patches, and they suffered substantially higher dispersal mortality in the metapopulations with forest matrix. On the other hand, mean dispersal distances were roughly an order of magnitude longer in forest matrix as compared with open landscapes (ca. 500-1,500 vs. 100-200 m). Our results suggest that inhospitable forest matrix induces strong selection against dispersal, leading to a reduced emigration rate. At the same time, the selection may promote emigrants with good dispersal abilities, which are able to perform long-distance movements. Thus, while it is generally believed that a matrix structurally similar to the habitat of a species should improve the functional connectivity of habitat patches, our findings imply that this may not necessarily be the case.!://WOS:000331935500004Times Cited: 0 0921-2973WOS:00033193550000410.1007/s10980-013-9971-0<7RNunes, M. C. S. Vasconcelos, M. J. Pereira, J. M. C. Dasgupta, N. Alldredge, R. J.2005KLand cover type and fire in Portugal: do fires burn land cover selectively?661-673Landscape Ecology206C-max statistic; fuel type selection; mathematical morphology; multiple comparison; permutation technique; resource selection NORTHERN BAJA-CALIFORNIA; RESOURCE SELECTION; STATISTICAL TECHNIQUES; SOUTHERN-CALIFORNIA; REGIMES; WILDFIRE; AGEArticleSepUThe purpose of this study is to investigate if, or under what conditions, fires select given land cover types for burning. If fires burn unselectively then the land cover composition (the proportional area of various land cover types) of individual fires should approximate the land cover composition available in their neighborhood. In this study we test this hypothesis by performing statistical analyses of a data set consisting of paired vectors with the proportions of land cover types present in burned areas and in their respective surroundings. The statistical methods employed (a permutation technique and the C,,,,, statistic) are commonly used in resource selection studies where data is subject to a unit-sum constraint. The results of the analysis of 506 fires that burned in Portugal in 1991 indicate that fires are selective, with small fires exhibiting stronger land cover preferences than large fires. According to the results of a multiple comparison analysis performed for small fires, there is a marked preference for shrubland followed by other forest cover types, while agriculture is clearly avoided. A similar analysis is performed to test if fire selectivity is related to the ecological region where it occurs. The results obtained in this study contribute to the discussion on the relative importance of fuels as a drivers of fire spread.://000233600700003 uISI Document Delivery No.: 988KS Times Cited: 0 Cited Reference Count: 39 Cited References: *COMM EUR, 2001, SYST COMM INF INC FO *DGF, 2001, INV FLOR NAC PORT CO AGEE JK, 1997, NORTHWEST SCI, V71, P153 ALLDREDGE JR, 1986, J WILDLIFE MANAGE, V50, P157 ALLDREDGE JR, 1992, J WILDLIFE MANAGE, V56, P1 ALLDREDGE JR, 1998, J AGRIC BIOL ENVIR S, V3, P237 ANDERSON HE, 1982, INT122 USDA FOR SERV BIONDINI ME, 1991, COMPUTER ASSISTED VE, P221 BUNTING S, 1988, RANGELANDS, V10, P251 CADE SB, 2001, USER MANUAL BLOSSOM CUMMING SG, 2001, ECOL APPL, V11, P97 DASGUPTA N, 1998, J AGRIC BIOL ENVIR S, V3, P323 DASGUPTA N, 2002, J AGRIC BIOL ENVIR S, V7, P208 DIAZDELGADO R, 2001, FOREST ECOL MANAG, V147, P67 FRANCISCO R, 1992, RESPONSES FOREST ECO, P367 KEELEY JE, 1999, SCIENCE, V284, P1829 KEELEY JE, 2003, ECOL STU AN, V160, P218 MANIQUE J, 1985, ESTACAO AGRONOMICA N MANLY L, 1993, RESOURCE SELECTION A MCCLEAN SA, 1998, J WILDLIFE MANAGE, V62, P793 MIELKE PW, 1986, J STAT PLAN INFER, V13, P377 MINNICH RA, 1983, SCIENCE, V219, P1287 MINNICH RA, 1997, INT J WILDLAND FIRE, V7, P221 MOREIRA F, 2001, LANDSCAPE ECOL, V16, P557 MORENO JM, 1999, MEDITERRANEAN DESERT, V1, P115 MORITZ MA, 2003, ECOLOGY, V84, P351 MORITZ MA, 2004, FRONT ECOL ENVIRON, V2, P67 NOGUEIRA CDS, 1990, INFORMACAO, V2, P18 PAUL WM, 2001, PERMUTATION METHODS PENA A, 1996, ROTEIROS NATUREZA TE PEREIRA JMC, 2003, FIRE RISK BURNED ARE PEREIRA MG, IN PRESS FOREST METE ROTHERMEL RC, 1973, J FOREST, V71, P640 SERRA JP, 1982, IMAGE ANAL MATH MORP SILVA JM, 1990, REV FORESTIERE FRANC, V40, P337 SILVA T, 2004, ESTIMATIVA EMISSOES VASCONCELOS MJP, 2001, PHOTOGRAMMETRIC ENG, V67, P73 VELEZ RM, 2000, COMBUSTIBLES FORESTA ZAR JH, 1999, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000233600700003Inst Invest Cient Trop, P-1300142 Lisbon, Portugal. Inst Super Agron, Ctr Estudos Florestais, P-1349018 Lisbon, Portugal. Inst Super Agron, Dept Engn Florestal, P-1349018 Lisbon, Portugal. Washington State Univ, Dept Stat, Pullman, WA 99164 USA. Inst Super Agron, Ctr Ecol Aplicada Baeta Neves, P-1349017 Lisbon, Portugal. Nunes, MCS, Inst Invest Cient Trop, Travessa Conde Ribeira 9, P-1300142 Lisbon, Portugal. mcarmonunes@mail.ptEnglish 1|? O'Farrell, P. J. Reyers, B. Le Maitre, D. C. Milton, S. J. Egoh, B. Maherry, A. Colvin, C. Atkinson, D. De Lange, W. Blignaut, J. N. Cowling, R. M.2010kMulti-functional landscapes in semi arid environments: implications for biodiversity and ecosystem services 1231-1246Landscape Ecology258Oct+Synergies between biodiversity conservation objectives and ecosystem service management were investigated in the Succulent Karoo biome (83,000 km(2)) of South Africa, a recognised biodiversity hotspot. Our study complemented a previous biodiversity assessment with an ecosystem service assessment. Stakeholder engagement and expert consultation focussed our investigations on surface water, ground water, grazing and tourism as the key services in this region. The key ecosystem services and service hotspots were modelled and mapped. The congruence between these services, and between biodiversity priorities and ecosystem service priorities, were assessed and considered in relation to known threats. Generally low levels of overlap were found between these ecosystem services, with the exception of surface and ground water which had an 80% overlap. The overlap between ecosystem service hotspots and individual biodiversity priority areas was generally low. Four of the seven priority areas assessed have more than 20% of their areas classified as important for services. In specific cases, particular service levels could be used to justify the management of a specific biodiversity priority area for conservation. Adopting a biome scale hotspot approach to assessing service supply highlighted key management areas. However, it underplayed local level dependence on particular services, not effectively capturing the welfare implications associated with diminishing and limited service provision. We conclude that regional scale (biome level) approaches need to be combined with local level investigations (municipal level). Given the regional heterogeneity and varied nature of the impacts of drivers and threats, diverse approaches are required to steer land management towards sustainable multifunctional landscape strategies.!://WOS:000281725700008YTimes Cited: 3 10th International Congress of Ecology Aug 16-21, 2009 Brisbane, AUSTRALIA 0921-2973WOS:00028172570000810.1007/s10980-010-9495-9 C<7+O'Neill, J. Walsh, M.20007Landscape conflicts: preferences, identities and rights281-289Landscape Ecology153Acontingent valuation identity landscape valuation property rightsArticleApr_Landscapes are public environments in which different communities and individuals dwell and which matter to them in ways which are not always consistent. As such they are open to strong conflicts about what the future of landscapes ought to be and who has an entitlement to involvement in a decision about that future. How should such conflicts be resolved? One influential approach is that embodied in the practice of cost-benefit analysis: the strength of preferences for different landscapes is measured by individuals' willingness to pay and the potential Pareto improvement efficiency criterion is employed as a rule of choice. This paper contends that this approach is flawed. It examines an economic valuation study of landscapes in the Yorkshire Dales. Drawing on interviews with farmers in the Dales and on in-depth discussion groups with respondents to other economic valuation studies, it argues that landscape conflicts involve issues of identity that cannot be captured in terms of preference satisfaction and conflicts of perceived rights which could not in principle be resolved by cost-benefit analysis.://000085293300009 ISI Document Delivery No.: 283UB Times Cited: 6 Cited Reference Count: 20 Cited References: BURGESS J, 1995, VALUING NATURE WHAT DEFOE D, 1962, TOUR WHOLE ISLAND GR HICKS J, 1981, WEALTH WELFARE JACOBS M, 1997, VALUING NATURE EC ET NASSAUER JI, 1988, HORTSCIENCE, V23, P973 NASSAUER JI, 1989, J SOIL WATER CONSERV, V44, P384 OCONNOR M, 1995, J INCOME DISTRIBUTIO, V5, P145 ONEILL J, 1993, ECOLOGY POLICY POLIT ONEILL J, 1996, ENV POL, V5, P752 ONEILL J, 1997, CROSS CULTURAL PROTE ONEILL J, 1997, TIME NARRATIVE ENV P ONEILL J, 1997, VALUING NATURE ORIORDAN T, 1993, J ENV PLANNING MANAG, V36, P123 SAMUELS W, 1972, LAW EC INT PERSPECTI SCHMID A, 1978, PROPERTY POWER PUBLI SYLVAN R, 1995, UNPUB DOMINANT BRIT VATN A, 1994, J ENVIRON ECON MANAG, V26, P129 WALSH M, 1996, FIELDS APART WHAT FA WALSH M, 1997, N W GEOGRAPHER, V1, P17 WILLIS KG, 1992, LANDSCAPE URBAN PLAN, V23, P17 0921-2973 Landsc. Ecol.ISI:000085293300009Univ Lancaster, Dept Philosophy, Lancaster LA1 4YT, England. Univ Lancaster, Ctr Study Environm Change, Lancaster LA1 4YT, England. O'Neill, J, Univ Lancaster, Dept Philosophy, Lancaster LA1 4YT, England.English?vO'Neill,R. V. Hunsaker, C. T. Timmins, S. P. Timmins, B. L. Jackson, K. B. Jones, K. B. Riitters, K. H. Wickham, J. D.1996CScale problems in reporting landscape pattern at the regional scale169-180Landscape Ecology113"scale effect, grain, extent, indexe?(O'Neill, R.V. A.R. Johnson A.W. King19892A hierarchical framework for the analysis of scale193-205Landscape Ecology33/4Dhierarchy theory, nonequilibrium, thermodynamics, catastrophe theoryxLandscapes are complex ecological systems that operate over broad spatiotemporal scales. Hierarchy theory conceptualizes such systems as composed of relatively isolated levels, each operating at a distinct time and space scale. This paper explores some basic properties of scaled systems with a view toward taking advantage of the scaled structure in predicting system dynamics. Three basic properties are explored: (1) hierarchical structuring, (2) disequilibrium, and (3) metastability. These three properties lead to three conclusions about complex ecological systems. First, predictions about landscape dynamics can often be based on constraints that directly result from scaled structure. Biotic potential and environmental limits form a constraint envelope, analogous to a niche hypervolume, within which the landscape system must operate. Second, within the constraint envelope, thermodynamic and other limiting factors may produce attractors toward which individual landscapes will tend to move. Third, because of changes in biotic potential and environmental conditions, both the constraint envelope and the local attractors change through time. Changes in the constraint structure may involve critical thresholds that result in radical changes in the state of the system. An attempt is made to define measurements to predict whether a specific landscape is approaching a critical threshold.e?7O'Neill, R.V. B.T. Milne M.G. Turner R.H. Gardner19881Resource utilization scales and landscape pattern63-69Landscape Ecology21IPercolation theory, Probability theory, Landscape ecology, Scale, PatterniThe spatial patterning of resources constrains the movement of consumers on the landscape. Percolation theory predicts that an organism can move freely if its critical resource or habitat occupies 59.28% of the landscape. Sparse resources require an organism to operate on larger resource utilization scales. Multiple critical resources necessitate larger scales, while substitutable resources ease the scale requirements. Contagious spatial patterns require larger scales to permit movement between resource clusters. The study indicates a strong link between spatial pattern and ecological processes on a landscape.X?LO'Neill, R.V. S.J. Turner V.I. Cullinan D.P. Coffin R. Cook et al.19912Multiple Landscape Scales: An Intersite Comparison137-144Landscape Ecology53SHierarchy theoty, scales, detection of multiple scales of pattern, pattern analysis:Vegetation transect data from three locations were analyzed to determine if multiple scales of pattern could be detected. The sites included a semiarid grassland in New Mexico, a series of calcareous openings in a deciduous forest in Tennessee, and a shrub-steppe system in Washington. The data were explored with four statistical techniques. A scale of pattern was accepted if detected by more than one analytical method or localed by a single method in multiple taxa. The analyses indicated 3 - 5 scales of pattern on all three sites, as predicted by Hierarchy Theory.z?O’Neill, R.V. Krummel, J.R. Gardner, R.H. Sugihara, G. Jackson, B. DeAngelis, D.L. Milne, B.T. Turner, M.G. Zygmunt, B. Christensen, S.W. Dale, V.H. Graham, R.L.1988Indices of landscape pattern153-162Landscape Ecology13$Index, Dominance, Contagion, Fractal{Landscape ecology deals with the patterning of ecosystems in space. Methods are needed to quantify aspects of spatial pattern that can be correlated with ecological processes. The present paper develops three indices of pattern derived from information theory and fractal geometry. Using digitized maps, the indices are calculated for 94 quadrangles covering most of the eastern United States. The indices are shown to be reasonably independent of each other and to capture major features of landscape pattern. One of the indices, the fractal dimension, is shown to be correlated with the degree of human manipulation of the landscape.><71Oba, G. Post, E. Syvertsen, P. O. Stenseth, N. C.2000dBush cover and range condition assessments in relation to landscape and grazing in southern Ethiopia535-546Landscape Ecology156bare soil Booran bush cover dry savannah grass cover grazing pressure landscape patch types landscape units pastoralists land use soil erosion southern Ethiopia ECOSYSTEMSArticleAug'Progressive growth of bush cover in dry savannahs is responsible for declines in range conditions. In southern Ethiopia, the Booran pastoralists assisted our understanding of spatial patterns of bush cover and range conditions in 54 landscape patch types grouped into six landscape units within an area of 30 000 km(2). The size of landscape patches sampled was 625 m(2). We assessed the relationships between bush cover, grass cover and bare soil and grazing pressure and soil erosion and changes in range condition. Externally, political conflicts and internally, break down of land use, and official bans on the use of fire promoted bush cover and the decline in range conditions. Bush cover was negatively correlated with grass cover, and positively correlated with bare soil. Grass cover was negatively correlated with bare soil and grazing pressure in most landscape patch types. Grazing pressure was not significantly correlated with bush cover or bare soil, while soil erosion was directly related to bare soil. Soil erosion was absent in 64% of the landscape patch types, and seemingly not a threat to the rangelands. The relationship between bush cover, grass cover, bare soil and soil erosion is complex and related to climate, landscape geology, and patterns of land use. Main threats to range conditions are bush climax, loss of grass cover and unpalatable forbs. Currently, > 70% of the landscape patch types are in poor to fair range conditions. Decline in range conditions, unless reversed, will jeopardise the pastoral production system in southern Ethiopia.://000088037200004 ISI Document Delivery No.: 331UN Times Cited: 13 Cited Reference Count: 35 Cited References: *GRM INT, 1990, RANG MAN CONS INP SO *NAT RES COUNC, 1994, RANG HLTH NEW METH C *SYSTAT INC, 1992, SYSTAT STAT WIND VER ADAMS M, 1996, IS ECOSYSTEM CHANGE BASSI M, 1997, PASTORALISTS ETHNICI, P23 BILLE JC, 1983, 13 JEPSS ILCA BILLE JC, 1983, 14 JEPSS ILCA BIOT Y, 1993, RANGE ECOLOGY DISEQU, P153 BROWN JR, 1998, LANDSCAPE ECOL, V13, P93 COPPOCK DL, 1994, BORANA PLATEAU SO ET COSSINS NJ, 1987, AGR SYST, V25, P199 COSSINS NJ, 1988, AGR SYST, V27, P117 COSSINS NJ, 1988, AGR SYST, V27, P250 COUGHENOUR MB, 1991, J RANGE MANAGE, V44, P530 DOUGILL A, 1995, PASTORAL NETWORK C, V38 DUBLIN HT, 1990, J ANIM ECOL, V59, P1147 HARRIS DR, 1980, HUMAN ECOLOGY SAVANN, P4 HUNTLEY BJ, 1982, ECOLOGY TROPICAL SAV, P101 JELTSCH F, 1997, J APPL ECOL, V34, P1497 LEGESSE A, 1973, GADA 3 APPROACHES ST LENZIGRILLINI CR, 1996, AFR J ECOL, V34, P333 LUDWIG JA, 1996, 5 INT RANG C RANG SU, P65 SCHLESINGER WH, 1990, SCIENCE, V247, P1043 SCHOLES RJ, 1993, AFRICAN SAVANNA SYNT SCHOLES RJ, 1997, ANNU REV ECOL SYST, V28, P517 SINCLAIR ARE, 1979, SERENGETI DYNAMICS E, P1 SKARPE C, 1991, AMBIO, V20, P351 SMITH LE, 1988, VEGETATION SCI APPL, P113 SOULE PT, 1999, J RANGE MANAGE, V52, P525 STAFFORDSMITH M, 1993, RANGE ECOLOGY DISEQU, P196 VANWIJINGAARDEN W, 1985, ITC PUBLICATION, V4 WALKER BH, 1980, HUMAN ECOLOGY SAVANN, P339 WESTERN D, 1979, HUM ECOL, V7, P75 WHITE F, 1980, NATURAL RESOURCES RE, V20 WILDING R, 1985, 15B JEPSS ILCA 0921-2973 Landsc. Ecol.ISI:000088037200004Univ Oslo, Dept Biol, Div Zool, N-0316 Oslo, Norway. Oba, G, Agr Univ Norway, Noragr Ctr Int Environm & Dev, POB 5001, N-1432 As Nlh, Norway.English]<7cObeysekera, J. Rutchey, K.19972Selection of scale for Everglades landscape models7-18Landscape Ecology121PATTERNS; GEOMETRY; ECOLOGYArticleFeb/This article addresses the problem of determining the optimal ''Model Grain'' or spatial resolution (scale) for landscape modeling in the Everglades. Selecting an appropriate scale for landscape modeling is a critical task that is necessary before using spatial data for model development. How the landscape is viewed in a simulation model is dependent on the scale (cell size) in which it is created. Given that different processes usually have different rates of fluctuations (frequencies), the question of selection of an appropriate modeling scale is a difficult one and most relevant to developing spatial ecosystem models. The question of choosing the appropriate scale for modeling is addressed using the landscape indices (e.g., cover fraction, diversity index, fractal dimension, and transition probabilities) recently developed for quantifying overall characteristics of spatial patterns. A vegetation map of an Everglades impoundment area developed from SPOT satellite data was used in the analyses. The data from this original 20 x 20 m data set was spatially aggregated to a 40 x 40 m resolution and incremented by 40 meters on up to 1000 x 1000 m (i.e., 40, 80, 120, 160... 1000) scale. The primary focus was on the loss of information and the variation of spatial indices as a function of broadening ''Model Grain'' or scale. Cover fraction and diversity indices with broadening scale indicate important features, such as tree islands and brush mixture communities in the landscape, nearly disappear at or beyond the 700 m scale. The fractal analyses indicate that the area perimeter relationship changes quite rapidly after about 100 m scale. These results and others reported in the paper should be useful for setting appropriate objectives and expectations for Everglades landscape models built to varying spatial scales.://A1997XQ44800002 ISI Document Delivery No.: XQ448 Times Cited: 17 Cited Reference Count: 48 Cited References: *SAS I, 1990, SAS STAT US GUID VER BARNSLEY M, 1988, FRACTALS EVERYWHERE BRADBURY RH, 1984, MAR ECOL-PROG SER, V14, P295 BURROUGH PA, 1981, NATURE, V294, P240 BURROUGH PA, 1983, J SOIL SCI, V34, P577 BURROUGH PA, 1984, B I MATH ITS APPLICA, V20, P36 BURROUGH PA, 1986, PRINCIPLES GEOGRAPHI COSTANZA R, 1992, EVERGLADES LANDSCAPE CRAIGHEAD FC, 1971, TREES S FLORIDA, V1 CULLINAN VI, 1992, LANDSCAPE ECOL, V7, P211 DAVIS SM, 1991, AQUAT BOT, V40, P203 DAVIS SM, 1994, EVERGLADES ECOSYSTEM DEBUSK WF, 1994, SOIL SCI AM J, V58 DECOLA L, 1989, PHOTOGRAMM ENG REM S, V55, P601 DINEEN JW, 1972, DEPTH REPORT CENTRAL, V1 DINEEN JW, 1974, DEPTH REPORT CENTRAL, V2 FEDER J, 1988, FRACTALS FITZ CH, 1993, EVERGLADES LANDSCAPE FROTIER S, 1987, NATO ASI SERIES G, V14 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GUNDERSON LH, 1988, INTERDISCIPLINARY AP HOLLING CS, 1992, ECOL MONOGR, V62, P447 JENSEN JR, 1995, PHOTOGRAMM ENG REM S, V61, P199 KING AW, 1987, QUANTITATIVE METHODS KRUMMEL JR, 1987, OIKOS, V48, P321 LI HB, 1993, LANDSCAPE ECOL, V8, P155 LOVEJOY S, 1982, SCIENCE, V216, P185 LUDWIG JA, 1988, STAT ECOLOGY PREMIER MANDELBROT BB, 1977, FRACTALS FORM CHANCE MEETEMEYER V, 1987, LANDSCAPE HETEROGENE MILNE BT, 1988, APPL MATH COMPUT, V27, P67 MILNE BT, 1991, QUANTITATIVE METHODS MILNE BT, 1992, AM NAT, V139, P32 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PASTOR J, 1990, LANDSCAPE ECOL, V4, P55 PIELOU EC, 1975, ECOLOGICAL DIVERSITY RISSER PG, 1984, SPEC PUBL ILLINOIS N, V2 RUTCHEY K, 1994, PHOTOGRAMM ENG REM S, V60, P767 SHANNON CE, 1949, MATH THEORY COMMUNIC TURNER MG, 1987, LANDSCAPE ECOL, V1, P29 TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 TURNER MG, 1989, ECOL MODEL, V48, P1 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 TURNER MG, 1991, QUANTITATIVE METHODS URBAN DL, 1987, BIOSCIENCE, V37, P119 URBAN NH, 1993, AQUATIC BOTANY, V46 WORTH DF, 1988, TECHNICAL PUBLICATIO, V882 0921-2973 Landsc. Ecol.ISI:A1997XQ44800002EObeysekera, J, S FLORIDA WATER MANAGEMENT DIST,W PALM BEACH,FL 33416.English <7q Ockinger, E. Bergman, K. O. Franzen, M. Kadlec, T. Krauss, J. Kuussaari, M. Poyry, J. Smith, H. G. Steffan-Dewenter, I. Bommarco, R.2012ZThe landscape matrix modifies the effect of habitat fragmentation in grassland butterflies121-131Landscape Ecology271biodiversity butterflies connectivity habitat loss island biogeography landscape matrix metapopulation species-area relationship species richness seminatural grasslands area relationships mixed models responses dispersal diversity density context heterogeneityJanThe landscape matrix is suggested to influence the effect of habitat fragmentation on species richness, but the generality of this prediction has not been tested. Here, we used data from 10 independent studies on butterfly species richness, where the matrix surrounding grassland patches was dominated by either forest or arable land to test if matrix land use influenced the response of species richness to patch area and connectivity. To account for the possibility that some of the observed species use the matrix as their main or complementary habitat, we analysed the effects on total species richness and on the richness of grassland specialist and non-specialist (generalists and specialists on other habitat types) butterflies separately. Specialists and non-specialists were defined separately for each dataset. Total species richness and the richness of grassland specialist butterflies were positively related to patch area and forest cover in the matrix, and negatively to patch isolation. The strength of the species-area relationship was modified by matrix land use and had a slope that decreased with increasing forest cover in the matrix. Potential mechanisms for the weaker effect of grassland fragmentation in forest-dominated landscapes are (1) that the forest matrix is more heterogeneous and contains more resources, (2) that small grassland patches in a matrix dominated by arable land suffer more from negative edge effects or (3) that the arable matrix constitutes a stronger barrier to dispersal between populations. Regardless of the mechanisms, our results show that there are general effects of matrix land use across landscapes and regions, and that landscape management that increases matrix quality can be a complement to habitat restoration and re-creation in fragmented landscapes.://000298228300010-864HI Times Cited:1 Cited References Count:55 0921-2973Landscape EcolISI:000298228300010Ockinger, E Swedish Univ Agr Sci, Dept Ecol, POB 7044, SE-75007 Uppsala, Sweden Swedish Univ Agr Sci, Dept Ecol, POB 7044, SE-75007 Uppsala, Sweden Swedish Univ Agr Sci, Dept Ecol, SE-75007 Uppsala, Sweden Linkoping Univ, Div Ecol, IFM Biol, SE-58183 Linkoping, Sweden UFZ, Helmholtz Ctr Environm Res, Dept Community Ecol, D-06120 Halle, Germany Czech Univ Life Sci, Fac Environm Sci, Dept Ecol, Prague 16521, Czech Republic Acad Sci Czech Republic, Inst Entomol, CR-37005 Ceske Budejovice, Czech Republic Univ Wurzburg, Dept Anim Ecol & Trop Biol, Bioctr, D-97074 Wurzburg, Germany Finnish Environm Inst, Ecosyst Change Unit, Helsinki 00251, Finland Lund Univ, Dept Biol, SE-22362 Lund, Sweden Lund Univ, Ctr Environm & Climate Res, SE-22362 Lund, SwedenDOI 10.1007/s10980-011-9686-zEnglish~?SOckinger, E. Smith, H. G.2008JDo corridors promote dispersal in grassland butterflies and other insects?27-40Landscape Ecology231Ecological corridors are frequently suggested to increase connectivity in fragmented landscapes even though the empirical evidence for this is still limited. Here, we studied whether corridors, in the form of linear grass strips promote the dispersal of three grassland butterflies, using mark-recapture technique in an agricultural landscape in southern Sweden. We found no effects of the presence of corridors or of corridor length on inter-patch dispersal probabilities. Instead, dispersal probabilities appeared to be related to the quality, areas and population densities of the source and recipient patches. For two of the species, the density of captured individuals along corridors was better predicted by the corridor length than by the straight-line distance from a pasture, suggesting that short-distance movements within habitat patches result in a diffusion of individuals along corridors. A literature review revealed that only 16 published studies had explicitly studied the effect of corridors on insect movement. The context in which studies were performed appeared to affect whether corridors facilitated dispersal or not. All seven studies where the corridors consisted of open areas surrounded by forest showed positive effects, while only two out of six studies where corridors consisted of grassland surrounded by other open habitats showed positive effects of corridors. Our results clearly demonstrate that corridors do not always have positive effects on insect dispersal and that the effect seems to depend on the quality of the surrounding matrix, on the spatial scale in which the study is performed and on whether true dispersal or routine movements are considered."://WOS:000251796100005 Times Cited: 0WOS:00025179610000510.1007/s10980-007-9167-6ڽ7LDOkanga, Sharon Cumming, GraemeS Hockey, PhillipA R. Peters, JeffreyL2013VLandscape structure influences avian malaria ecology in the Western Cape, South Africa 2019-2028Landscape Ecology2810Springer NetherlandsOLandscape composition Heterogeneity Species richness Avian malaria Urbanization 2013/12/01+http://dx.doi.org/10.1007/s10980-013-9949-y 0921-2973Landscape Ecol10.1007/s10980-013-9949-yEnglishZ<74tOkland, R. H. Bratli, H. Dramstad, W. E. Edvardsen, A. Engan, G. Fjellstad, W. Heegaard, E. Pedersen, O. Solstad, H.2006Scale-dependent importance of environment, land use and landscape structure for species richness and composition of SE Norwegian modern agricultural landscapes969-987Landscape Ecology217Lland use intensity; landscape structure; patch; spatial scale; spatial variation; variation partitioning; vascular plants ELLENBERG INDICATOR VALUES; RURAL HEMIBOREAL LANDSCAPE; FIELD BOUNDARY VEGETATION; GRADIENT ANALYSIS; HABITAT HETEROGENEITY; RELATIVE IMPORTANCE; NORTHERN FINLAND; VASCULAR PLANTS; SPATIAL SCALES; GREAT-BRITAINReviewOctzKnowledge of variation in vascular plant species richness and species composition in modern agricultural landscapes is important for appropriate biodiversity management. From species lists for 2201 land-type patches in 16 1-km(2) plots five data sets differing in sampling-unit size from patch to plot were prepared. Variation in each data set was partitioned into seven sources: patch geometry, patch type, geographic location, plot affiliation, habitat diversity, ecological factors, and land-use intensity. Patch species richness was highly predictable (75% of variance explained) by patch area, within-patch heterogeneity and patch type. Plot species richness was, however, not predictable by any explanatory variable, most likely because all studied landscapes contained all main patch types - ploughed land, woodland, grassland and other open land - and hence had a large core of common species. Patch species composition was explained by variation along major environmental complex gradients but appeared nested to lower degrees in modern than in traditional agricultural landscapes because species-poor parts of the landscape do not contain well-defined subsets of the species pool of species-rich parts. Variation in species composition was scale dependent because the relative importance of specific complex gradients changed with increasing sampling-unit size, and because the amount of randomness in data sets decreased with increasing sampling-unit size. Our results indicate that broad landscape structural changes will have consequences for landscape-scale species richness that are hard or impossible to predict by simple surrogate variables.://000241010900002 )ISI Document Delivery No.: 091FA Times Cited: 0 Cited Reference Count: 100 Cited References: 1992, ARCVIEW GIS 3 2 ENV 2004, R VERSION 2 0 0 WIND ARAUJO MB, 2004, J BIOGEOGR, V31, P1037 ARRHENIUS O, 1921, J ECOL, V9, P95 AUNE B, 1993, DET NORSKE METEOROLO, P1 AUSTIN MP, 1999, ECOGRAPHY, V22, P465 BELLEHUMEUR C, 1997, PLANT ECOL, V130, P89 BENTON TG, 2003, TRENDS ECOL EVOL, V18, P182 BIRKS HJB, 1993, REV PALAEOBOT PALYNO, V79, P153 BIRKS HJB, 1996, ECOGRAPHY, V19, P332 BORCARD D, 1992, ECOLOGY, V73, P1045 BRATLI H, 2006, IN PRESS AGR ECOSYST BROSE U, 2001, ECOGRAPHY, V24, P722 BUREL F, 1998, ACTA OECOL, V19, P47 COUSINS SAO, 2001, ECOGRAPHY, V24, P461 COUSINS SAO, 2002, LANDSCAPE ECOL, V17, P517 CRAWLEY MJ, 2001, SCIENCE, V291, P864 DAUBER J, 2003, AGR ECOSYST ENVIRON, V98, P321 DESNOO GR, 1997, AGR ECOSYST ENVIRON, V66, P223 DIEKMANN M, 2003, BASIC APPL ECOL, V4, P493 DRAMSTAD WE, 2002, J ENVIRON MANAGE, V64, P49 DUMORTIER M, 2002, FOREST ECOL MANAG, V158, P85 DUNGAN JL, 2002, ECOGRAPHY, V25, P626 EDVARDSEN A, 2006, IN PRESS AQUAT BOT EJRNAES R, 2000, J VEG SCI, V11, P573 ELLENBERG H, 2001, SCRIPTA GEOBOT, V3, P1 ERIKSSON O, 1993, OIKOS, V68, P371 EWALD J, 2003, FOLIA GEOBOT, V38, P357 FEDOROFF E, 2005, AGR ECOSYST ENVIRON, V105, P283 FJELLSTAD WJ, 1999, LANDSCAPE URBAN PLAN, V45, P177 FJELLSTAD WJ, 2001, NORW J GEOGR, V55, P71 FORLAND EJ, 1993, DNMI KLIMAAVDELINGEN, V39, P1 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FOTHERINGHAM AS, 1989, ACCURACY SPATIAL DAT, P221 GAUCH HG, 1982, ECOLOGY, V63, P1643 GREENACRE MJ, 1984, THEORY APPL CORRESPO GRYTNES JA, 1999, NORD J BOT, V19, P489 HAINESYOUNG R, 2003, J ENVIRON MANAGE, V67, P267 HARTE J, 2005, ECOL MONOGR, V75, P179 HAY GJ, 2001, LANDSCAPE ECOL, V16, P471 HEIKKINEN RK, 1996, ECOGRAPHY, V19, P341 HEIKKINEN RK, 1997, BIODIVERS CONSERV, V6, P1181 HIETALAKOIVU R, 1999, LANDSCAPE URBAN PLAN, V46, P103 HILL MO, 1979, DECORANA FORTRAN PRO HILL MO, 1997, J VEG SCI, V8, P579 JEANNERET P, 2003, AGR ECOSYST ENVIRON, V98, P311 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 KLEIJN D, 1997, J APPL ECOL, V34, P1413 KLEIJN D, 2000, J APPL ECOL, V37, P256 LECOEUR D, 1997, LANDSCAPE URBAN PLAN, V37, P57 LEGENDRE P, 1998, NUMERICAL ECOLOGY LENNARTSSON T, 2001, J ECOL, V89, P451 LI HB, 2004, LANDSCAPE ECOL, V19, P389 LINDBORG R, 2004, ECOLOGY, V85, P1840 LUOTO M, 2002, LANDSCAPE ECOL, V17, P195 LUOTO M, 2003, AMBIO, V32, P447 MCCULLAGH P, 1989, GEN LINEAR MODELS MEISEL JE, 1998, LANDSCAPE ECOL, V13, P347 MOEN A, 1998, NASJONALATLAS NORGE MOSER D, 2002, LANDSCAPE ECOL, V17, P657 MYKLESTAD A, 2004, BIOL CONSERV, V118, P133 MYKLESTAD A, 2004, GRASS FORAGE SCI, V59, P136 NORDERHAUG A, 2000, LANDSCAPE ECOL, V15, P201 OKLAND RH, 1985, SOMMERFELTIA, V2, P1 OKLAND RH, 1990, SOMMERFELTIA S, V1, P1 OKLAND RH, 1990, VEGETATIO, V87, P187 OKLAND RH, 1999, J VEG SCI, V10, P131 OKLAND RH, 1999, OIKOS, V87, P488 OKLAND RH, 2001, SOMMERFELTIA, V29, P1 OKLAND RH, 2003, ECOLOGY, V84, P1909 OKLAND RH, 2003, J VEG SCI, V14, P693 OKSANEN J, 2004, PACKAGE VEGAN VERSIO ONEILL RV, 1986, HIERARCHICAL CONCEPT OPENSHAW S, 1979, STAT APPL SPATIAL SC, P127 PALMER MW, 1994, AM NAT, V144, P717 PEDERSEN B, 1990, NORD J BOT, V10, P163 ROBINSON RA, 2002, J APPL ECOL, V39, P157 SCHAFFERS AP, 2000, J VEG SCI, V11, P225 SCOTT WA, 2003, PLANT ECOL, V165, P101 SHMIDA A, 1984, VEGETATIO, V58, P29 SMART SM, 2003, J ENVIRON MANAGE, V67, P239 SVENNING JC, 2002, BIOL CONSERV, V104, P133 TERBRAAK CJF, 1986, ECOLOGY, V67, P1167 TERBRAAK CJF, 2002, CANOCO REFERENCE MAN TIKKA PM, 2001, LANDSCAPE ECOL, V16, P659 TILMAN D, 2001, SCIENCE, V294, P843 VANDVIK V, 2002, PLANT ECOL, V162, P233 VENABLES WN, 2002, MODERN APPL STAT S WAGNER HH, 2001, LANDSCAPE ECOL, V16, P121 WALDHARDT R, 2004, LANDSCAPE ECOL, V19, P211 WAMELINK GWW, 2002, J VEG SCI, V13, P269 WHITTAKER RH, 1956, ECOL MONOGR, V26, P1 WHITTAKER RH, 1967, BIOL REV, V42, P207 WHITTAKER RJ, 2005, DIVERS DISTRIB, V11, P3 WIENS JA, 1989, FUNCT ECOL, V3, P385 WILSON WL, 2003, AGR ECOSYST ENVIRON, V94, P249 WU JG, 1994, ECOL MONOGR, V64, P447 WU JG, 2002, LANDSCAPE ECOL, V17, P355 WU JG, 2004, LANDSCAPE ECOL, V19, P125 ZOBEL M, 1992, OIKOS, V65, P314 0921-2973 Landsc. Ecol.ISI:000241010900002Univ Oslo, Dept Bot, Nat Hist Museum, N-0318 Oslo, Norway. Okland, RH, Univ Oslo, Dept Bot, Nat Hist Museum, POB 1172, N-0318 Oslo, Norway. r.h.okland@nhm.uio.noEnglish<7Oline, D. K. Grant, M. C.2001FScaling patterns of biomass and soil properties: an empirical analysis13-26Landscape Ecology171Colorado Front Range environmental gradients geostatistics multiple scales Rocky mts scaling patterns soils FRACTAL DIMENSIONS SPATIAL-DISTRIBUTION MULTISCALE SOURCES VEGETATION VARIABILITY LANDSCAPES MOISTURE MONTANA SCALES USAArticleWe argue that studies at multiple scales must necessarily change the extent of measurements, not just the spacing, in order to effectively capture information regarding processes at multiple scales. We have implemented a multi-scale sampling scheme using transects of 10 cm, 1 m, 10 m, 100 m, and 1 km at each of four sites along an elevational gradient from dry foothills forest to alpine tundra in the Front Range of Colorado; these four sites form an additional transect of 22 km. Along each of these transects we took ten equally spaced soil cores and measured variables important in determining both microbial and plant community structure: soil water content, organic matter content, pH, and total soil biomass. With this sampling scheme we are able to treat scale as an independent variable in our analyses, and our data show that both particular sites and particular variables can determine whether estimates of mean values are scale-dependent or not. A geostatistical analysis using all of our data shows common relationships between scales across ecologically diverse sites; biomass shows the most complex pattern of distribution across scales, as measured by fractal dimension. Our analyses also reveal the inadequacy of several standard geostatistical models when applied to data from multiple scales of measurement - we recommend the use of the bounded power law model in such cases. We hypothesize that because biological communities must respond simultaneously to multiple variables with differing patterns of spatial variation, the spatial variation of biological communities will be at least as complex as the most complex environmental variable at any given site.://000176014400002 ISI Document Delivery No.: 559FF Times Cited: 7 Cited Reference Count: 28 Cited References: AMARASEKARE P, 1994, OECOLOGIA, V100, P166 BARTLETT RJ, 1988, SOIL SCI SOC AM J, V52, P1191 BERNTSON GM, 1997, P ROY SOC LOND B BIO, V264, P1531 BIAN L, 1993, PROF GEOGR, V45, P1 BROSOFSKE KD, 1999, PLANT ECOL, V143, P203 BURROUGH PA, 1981, NATURE, V294, P240 BURROUGH PA, 1983, J SOIL SCI, V34, P577 BURROUGH PA, 1983, J SOIL SCI, V34, P599 CAIRNS DM, 1999, PHYS GEOGR, V20, P256 CHILES JP, 1999, GEOSTATISTICS MODELI CRESSIE N, 1980, J INT ASS MATH GEOL, V12, P115 CULLINAN VI, 1997, LANDSCAPE ECOL, V12, P273 DECKER KLM, 1999, CAN J FOREST RES, V29, P232 GREENLAND D, 1989, ARCTIC ALPINE RES, V21, P380 JACKSON RB, 1993, J ECOL, V81, P683 KOTILAR NB, 1996, VEGETATIO, V127, P117 LIPSON DA, 1999, ECOLOGY, V80, P1623 LOEHLE C, 1996, ECOL MODEL, V85, P271 MARK DM, 1984, J INT ASS MATH GEOL, V16, P671 MARR, 1961, U COLORADO STUDIES S, V8 MILNE BT, 1988, APPL MATH COMPUT, V27, P67 MORRIS SJ, 1999, SOIL BIOL BIOCHEM, V31, P1375 RODRIGUEZITURBE I, 1995, GEOPHYS RES LETT, V22, P2757 ROGERS DL, 1999, EVOLUTION, V53, P74 WALKER DA, 1993, BIOSCIENCE, V43, P287 WESTERN AW, 1999, J HYDROL, V217, P203 YANG J, 1995, SOIL SCI, V160, P371 YOST RS, 1982, SOIL SCI SOC AM J, V46, P1028 0921-2973 Landsc. Ecol.ISI:000176014400002Univ Colorado, Dept Environm Populat & Organism Biol, Boulder, CO 80309 USA. Oline, DK, So Oregon State Coll, Dept Biol, 1250 Siskiyou Blvd, Ashland, OR 97520 USA. olined@sou.eduEnglish<7v*Ollinger, S. V. Aber, J. D. Federer, C. A.1998`Estimating regional forest productivity and water yield using an ecosystem model linked to a GIS323-334Landscape Ecology135Hforest productivity NPP runoff climate nitrogen northeastern US modelingArticleOctWe used the PnET-II model of forest carbon and water balances to estimate regional forest productivity and runoff for the northeastern United States. The model was run at 30 are sec resolution (approximately 1 km) in conjunction with a Geographic Information System that contained monthly climate data and a satellite-derived land cover map. Predicted net primary production (NPP) ranged from 700 to 1450 g m(-2) yr(-1) with a regional mean of 1084 g m-2 yr(-1). Validation at a number of locations within the region showed close agreement between predicted and observed values. Disagreement at two sites was proportional to differences between measured foliar N concentrations and values used in the model. Predicted runoff ranged from 24 to 150 cm yr(-1) with a regional mean of 63 cm yr(-1). Predictions agreed well with observed values from U.S. Geologic Survey watersheds across the region although there was a slight bias towards overprediction at high elevations and underprediction at lower elevations. Spatial patterns in NPP followed patterns of precipitation and growing degree days, depending on the degree of predicted water versus energy limitation within each forest type. Randomized sensitivity analyses indicated that NPP within hardwood and pine forests was limited by variables controlling water availability (precipitation and soil water holding capacity) to a greater extent than foliar nitrogen, suggesting greater limitations by water than nitrogen for these forest types. In contrast, spruce-fir NPP was not sensitive to water availability and was highly sensitivity to foliar N, indicating greater limitation by available nitrogen. Although more work is needed to fully understand the relative importance of water versus nitrogen limitation in northeastern forests, these results suggests that spatial patterns of NPP for hardwoods and pines can be largely captured using currently available data sets, while substantial uncertainties exist for spruce-fir.://000165537200004 ISI Document Delivery No.: V2651 Times Cited: 29 Cited Reference Count: 36 Cited References: *SCS, 1991, US SOIL CONS SERV MI, V1492 ABER JD, 1992, OECOLOGIA, V92, P463 ABER JD, 1995, CLIMATE RES, V5, P207 ABER JD, 1996, OECOLOGIA, V106, P257 ABER JD, 1997, ECOL MODEL, V101, P61 BALDOCCHI DD, 1987, J APPL ECOL, V24, P251 BOLSTER KL, 1996, CAN J FOREST RES, V26, P590 BURKE IC, 1990, LANDSCAPE ECOL, V4, P45 CLAPP RB, 1978, WATER RESOUR RES, V9, P1599 ELLSWORTH DS, 1993, OECOLOGIA, V96, P169 FEDERER CA, 1978, 19 U NEW HAMPSH WAT FIELD C, 1986, EC PLANT FORM FUNCTI, P25 FOSTER DR, 1992, J ECOL, V80, P753 HAMILTON LC, 1989, STAT STATA KINGSLEY NP, 1985, NE95 USDA FOR SERV LATHROP RG, 1994, INT J REMOTE SENS, V15, P2695 LATHROP RG, 1995, ECOL MODEL, V82, P1 MAGILL AH, 1996, FOREST ECOL MANAG, V84, P29 MAGILL AH, 1997, ECOL APPL, V7, P402 MARKS PL, 1974, ECOL MONOGR, V44, P73 MARTIN ME, 1997, ECOL APPL, V7, P431 MCGUIRE AD, 1992, GLOBAL BIOGEOCHEM CY, V6, P101 MELILLO JM, 1995, GLOBAL BIOGEOCHEM CY, V9, P407 NEILSON RP, 1995, ECOL APPL, V5, P362 NEWMAN SD, 1994, J NEAR INFRARED SPEC, V2, P5 OLLINGER SV, 1995, NE191 USDA FOR SERV PARTON WJ, 1988, BIOGEOCHEMISTRY, V5, P109 RAICH JW, 1991, ECOL APPL, V1, P399 REICH PB, 1995, OECOLOGIA, V104, P24 REINERS WA, 1979, ECOLOGY, V60, P403 RUNNING SW, 1991, TREE PHYSIOL, V9, P147 SCHIMEL DS, 1996, GLOBAL BIOGEOCHEM CY, V10, P677 SINCLAIR TR, 1984, BIOSCIENCE, V34, P36 SLACK JR, 1992, 92129 US GEOL SURV SPRUGEL DG, 1984, ECOL MONOGR, V54, P165 WHITTAKER RH, 1974, ECOL MONOGR, V44, P233 0921-2973 Landsc. Ecol.ISI:000165537200004Univ New Hampshire, Complex Syst Res Ctr, Inst Study Earth Oceans & Space, Durham, NH 03824 USA. US Forest Serv, USDA, NE Forest Expt Stn, Durham, NH 03824 USA. Ollinger, SV, Univ New Hampshire, Complex Syst Res Ctr, Inst Study Earth Oceans & Space, Durham, NH 03824 USA.English<72Olofsson, J. Hulme, P. E. Oksanen, L. Suominen, O.2005xEffects of mammalian herbivores on revegetation of disturbed areas in the forest-tundra ecotone in northern Fennoscandia351-359Landscape Ecology2036disturbance; gap; germination; grey-sided vole; herbivory; Norwegian lemming; reindeer; seedling establishment; species richness GRAZED SALT-MARSH; EMPETRUM-HERMAPHRODITUM; SEEDLING ESTABLISHMENT; VERTEBRATE HERBIVORES; SPATIAL HETEROGENEITY; PLANT-COMMUNITIES; GRASSLAND PLANTS; REINDEER; RESPONSES; ECOSYSTEMArticleAprHerbivores influence the structure of plant communities in arctic-alpine ecosystems. However, little is known of the effect of herbivores on plant colonisation following disturbance, and on its variability depending on the identity of herbivores and the characteristics of the habitats. To quantify the role of large and small vertebrate herbivores, we established exclosures of two different mesh sizes around disturbed subplots in forest and nearby tundra habitats in four contrasting locations in the forest-tundra ecotone in northernmost Sweden and Norway. The study revealed that herbivores influenced the abundance but not the species composition of regenerating vegetation. Gaps were colonised by the dominant species in the surrounding vegetation. The only exception to this expectation was Empetrum nigrum, which failed to colonise gaps even though it dominated undisturbed vegetation. Significant effects of herbivory were only detected when both small and large herbivores were excluded. Herbivores decreased the abundance of three of the most common species Vaccinium myrtillus, Vaccinium vitis idaea, and Deschampsia flexuosa. The effect of herbivory on the abundance of these three species did not differ between habitats and locations. However, the composition of the regenerating vegetation differed between habitats and locations. The disturbance treatment increased the species richness on the scale of plots, habitats, and sites. However, on the scale of whole locations, all species found in disturbed areas were also found in undisturbed areas, suggesting that the natural disturbance regime in arctic landscapes is high enough to sustain colonising species.://000231824400010 ISI Document Delivery No.: 963RU Times Cited: 0 Cited Reference Count: 55 Cited References: ADLER PB, 2001, OECOLOGIA, V128, P465 ARCHIBOLD OW, 1984, CAN FIELD NAT, V98, P337 BATZLI GO, 1980, ARCTIC ECOSYSTEM COA BAZELY DR, 1985, J APPL ECOL, V22, P693 BAZELY DR, 1986, J ECOL, V74, P693 BAZELY DR, 1989, J ECOL, V77, P24 BRATHEN KA, 2001, J VEG SCI, V12, P473 BROWN JR, 1988, VEGETATIO, V73, P73 BULLOCK JM, 1995, OIKOS, V72, P273 CHAMBERS JC, 1995, ECOLOGY, V76, P2124 COLLINS SL, 1991, ECOLOGY, V72, P654 CRAWLEY MJ, 1997, PLANT ECOL, P401 CRAWLEY MJ, 2002, STAT COMPUTING INTRO EDWARDS GR, 1999, J ECOL, V87, P423 FORBES BC, 1999, BIOL CONSERV, V88, P15 FREEDMAN B, 1982, CAN J BOT, V60, P2112 GRELLMANN D, 2002, OIKOS, V98, P190 GRUBB PJ, 1977, BIOL REV, V52, P107 HAGEN D, 2002, POLAR RES, V21, P37 HALLINGBACK T, 1981, MOSSOR FALTHANDBOK HANSKI I, 1993, AM NAT, V142, P17 HARPER JL, 1977, POPULATION BIOL PLAN HULME PE, 1994, J ECOL, V82, P873 HULME PE, 1996, J ECOL, V84, P43 HULME PE, 1996, J ECOL, V84, P609 JEFFERIES RL, 1994, OIKOS, V71, P193 JONASSON S, 1988, OIKOS, V52, P101 JONASSON S, 1992, OIKOS, V63, P420 KALELA O, 1957, ANN ACAD SCI FENN A4, V34, P1 KOTANEN PM, 1997, CAN J BOT, V75, P352 MCNAUGHTON SJ, 1983, ECOL MONOGR, V53, P291 MOBERG R, 1982, LAVAR FALTHANDBOK MOEN J, 1993, ARCTIC ALPINE RES, V25, P130 MOSSBERG B, 1995, NORDISKA FLORAN MULDER CPH, 1998, ECOL MONOGR, V68, P275 MULDER CPH, 1999, PERSPECT PLANT ECOL, V2, P29 NILSSON MC, 1992, J CHEM ECOL, V18, P1857 NILSSON MC, 1994, OECOLOGIA, V98, P1 OLOFSSON J, 2001, ECOGRAPHY, V24, P13 OLOFSSON J, 2002, OIKOS, V96, P265 OLOFSSON J, 2002, OIKOS, V96, P507 OLOFSSON J, 2004, OIKOS, V105, P386 OLOFSSON J, 2004, OIKOS, V126, P324 QUINN GP, 2002, EXPT DESIGN DATA ANA SOMMER U, 2000, OECOLOGIA, V122, P284 STARK S, 2002, ECOLOGY, V83, P2736 TIHOMIROV BA, 1959, T AKAD NAUK BOT I KO VANDERWAL R, 2001, J VEG SCI, V12, P705 VANDERWAL R, 2004, ECOGRAPHY, V27, P242 VIRTANEN R, 1997, OIKOS, V79, P155 WALKER DA, 1991, J APPL ECOL, V28, P244 WARDLE DA, 1997, SCIENCE, V277, P1296 WELLING P, 2001, J VEG SCI, V13, P217 WILLIAMS RJ, 1992, J ECOL, V80, P343 ZACKRISSON O, 1992, CAN J FOREST RES, V22, P1210 0921-2973 Landsc. Ecol.ISI:000231824400010Umea Univ, Dept Ecol & Environm Sci, S-90187 Umea, Sweden. Ctr Ecol & Hydrol Banchory, Banchory AB31 4BW, Kincardine, Scotland. Univ Turku, Dept Biol, Sect Ecol, FIN-20014 Turku, Finland. Olofsson, J, Umea Univ, Dept Ecol & Environm Sci, S-90187 Umea, Sweden. johan.olofsson@emg.umu.seEnglishJ<74,Olsson, E. G. A. Austrheim, G. Grenne, S. N.2000bLandscape change patterns in mountains, land use and environmental diversity, Mid-Norway 1960-1993155-170Landscape Ecology152biodiversity conservation disturbance forest succession fragmentation grazing land use change mountain semi-natural grasslands sub-alpine sustainable agriculture FRAGMENTATION PLANTSArticleFebThe Norwegain mountains have had a central role in the subsistence agroecosystems by providing vast biological resources for humans and their livestock since 4000-3500 BP as indicated by paleoecological records. Later with the development of the summer farming system the use of the mountains was intensified. This long-term use of the mountains has shaped a montane cultural landscape by livestock grazing, mowing for hay, fuel collection and a variety of other uses. The result is a significant increase of the grassland areas at the expense of the forest. Those semi-natural grasslands and heathlands with specific biological diversity have until recently dominated the mountains but are today decreasing due to forest invasion - which in turn is a result of changes in human land use. The present paper focuses on changes in landscape pattern and differences in landscape development in two mountain valleys with summer farming activities, in Mid-Norway, over the period 1960s-1990s, and seeks to interpret the changes in relation to differential land use and environmental factors. This study contributes examples from human shaped ecosystems in mountains where the fragmentation of semi-natural habitats is addressed. A set of landscape pattern indices commonly used in landscape ecological studies is also used here, and their ecological relevance in the present context is dealt with. The implications of changed land use for biodiversity conservation in those mountains and the relationships to future sustainable agriculture is also briefly discussed.://000084522700007 ISI Document Delivery No.: 270EP Times Cited: 27 Cited Reference Count: 54 Cited References: *AGR STAT NORW, 1997, AGR STAT *CART INSTR, 1993, 190 AP CART INSTR *ESRI, 1990, GIS ESRI ESRI IMPL S *ESRI, 1992, GIS ESRI ESRI IMPL S *NORD COUNC MIN, 1984, NAT REG NORD *STATSSK, 1994, UNPUB SKOGST BUD END AAS B, 1995, AMS VARIA, V24, P89 ALLAN NJR, 1988, HUMAN IMPACT MOUNTAI ANDREN H, 1995, MOSAIC LANDSCAPES EC, P225 ANGELSTAM P, 1992, ECOLOGICAL PRINCIPLE, P9 AUNE B, 1993, NORSKE METEOROL I RA, V2, P1 AUSTRHEIM G, IN PRESS PLANT ECOLO AUSTRHEIM G, 1998, THESIS NORWEGIAN U T AUSTRHEIM G, 1999, BIOL CONSERV, V87, P369 BENGTSSONLINDSJ.S, 1991, ECOL B, V41, P388 EASTMAN JR, 1995, USERS GUIDE VERSION FISCHER M, 1997, CONSERV BIOL, V11, P727 FORLAND EJ, 1993, NORSKE METEOROL I RA, V39, P1 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FREMSTAD E, 1997, VEGETASJONSTYPER NOR FULLER RM, 1986, J BIOGEOGR, V13, P327 GRENNE SN, 1998, THESIS NTNU TRONDHEI GRONTVEDT E, 1997, THESIS NTNU TRONDHEI GUNNARSDOTTIR H, 1996, THESIS U OSLO HOBBS RJ, 1992, CONSERV BIOL, V6, P324 HULSHOFF RM, 1995, LANDSCAPE ECOL, V10, P101 IMS RA, 1995, MOSAIC LANDSCAPES EC, P85 INGELOG T, 1994, FLORAVARD ODLINGSLAN JORDAL JB, 1997, SOPP NATURBETESMARKE KAREIVA P, 1987, NATURE, V326, P388 KVAMME M, 1992, VEGETASJONSHISTORISK LAVOREL S, 1999, OIKOS, V84, P480 LEPART J, 1992, LANDSCAPE BOUNDARIES, P76 MCINTYRE S, 1992, CONSERV BIOL, V6, P146 MCINTYRE S, 1994, PACIFIC CONS BIOL, V1, P234 MENGES ES, 1990, CONSERV BIOL, V4, P52 OLSSON EGA, UNPUB MOUNTAIN RES D OLSSON EGA, 1995, 2 FYLK SORTR OLSSON GA, 1996, INFALLSVINKLAR PA BI, P12 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PAUS A, 1987, ARKEOLOGISK SERIE, P1 PREISS E, 1997, LANDSCAPE ECOL, V12, P51 PRICE LW, 1981, MOUNTAINS MAN STUDY REED RA, 1996, BIOL CONSERV, V75, P267 REINTON L, 1955, SAETERBRUKET NOREG, V1 REINTON L, 1957, SAETERBRUKET NOREG, V2 REINTON L, 1961, SAETERBRUKET NOREG, V3 RESCIA AJ, 1997, J VEG SCI, V8, P343 SKANES H, 1996, THESIS U STOCKHOLM S TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 VANDIJK G, 1991, CONSERVATION LOWLAND, P15 VANDORP D, 1997, LANDSCAPE ECOL, V12, P39 WIDEN B, 1987, NORD J BOT, V7, P687 0921-2973 Landsc. Ecol.ISI:000084522700007Norwegian Univ Sci & Technol, Dept Bot, N-7491 Trondheim, Norway. Olsson, EGA, Norwegian Univ Sci & Technol, Dept Bot, N-7491 Trondheim, Norway.EnglishN<7*/Onate, J. J. Andersen, E. Peco, B. Primdahl, J.2000{Agri-environmental schemes and the European agricultural landscapes: the role of indicators as valuing tools for evaluation271-280Landscape Ecology153cagricultural landscapes agri-environmental policy Europe indicators on policy effects CENTRAL SPAINArticleAprIn Europe most conservation values, from biodiversity to scenic sites, are integral parts of agricultural landscapes. When these landscapes change as a result of agricultural policies, natural values - species, habitats, landscapes - are usually affected. Until recently however, these values have not been part of agricultural policies. The impacts of such new policies are difficult to evaluate because landscapes are complex and diverse, and the effects of policy are rarely immediate or causal. This paper evaluates the potential effects of Agri-environmental Regulation EC 2078/92 on European agricultural landscapes through the use of agri-environmental indicators (AEIs) on policy effects. After discussing the general framework of the evaluation methodology through the use of AEIs, we distinguish two types of agri-environmental policy (AEP) effects: policy performances and policy outcomes. The impediments to direct measurement of policy outcomes are stated. The potential for measuring policy performances are checked in two case study areas, one in Spain and one in Denmark, characterized by extensive agricultural land-uses and by the dual process of intensification/abandonment that is threatening their natural values. Both study areas are currently targeted by agri-environmental schemes under Reg. 2078/92. The realisability or availability of suitable statistical data to construct and report each AEI is stated for both types of effects. A problem of scale and content is found in most of the available statistics for assessing policy outcomes and the need for data at farm level is concluded to be indispensable if policy performances are to be measured. Effects of policy performance are measured for key selected AEIs in each study area on the basis of the results of a field survey based on questionnaires of participating and non-participating farmers in the AEP schemes. The main effects may be catalogued as improvement effects or protection effects since they represent a change in participant over non-participant farmers' decisions. Finally, the importance of this type of policy evaluation approach is discussed in the light of the likely future development of AEP in the European Union.://000085293300008 'ISI Document Delivery No.: 283UB Times Cited: 8 Cited Reference Count: 46 Cited References: *EUR COMM, 1988, 88501 COM *ORG EC COOP DEV, 1993, ENV MON, V83 *ORG EC COOP DEV, 1997, ENV IND AGR *WORLD WILDL FUND, 1995, MEAS PROGR BIOINT IP AGGER P, 1988, LANDSCAPE ECOL, V1, P227 ALES RF, 1992, LANDSCAPE ECOL, V7, P3 ALONSO JC, 1996, BIOL CONSERV, V77, P79 ANDERSEN E, 1998, MILJOVENLIGE JORDBRU ASBIRK S, 1991, RODLISTE 90 BALDOCK D, 1996, FARMING MARGINS ABAN BARRETT GW, 1992, J SUSTAIN AGR, V2, P83 BENAYAS JMR, 1990, J VEG SCI, V1, P461 BERNALDEZ FG, 1989, LANDSCAPE ECOLOGY, V2, P3 BETHE F, 1996, MARGINALIZATION AGR BIRKS HH, 1988, CULTURAL LANDSCAPE P BROUWER F, 1995, INDICATORS MONITOR A BROUWER F, 1999, AGR ENV EUROPE ROLE BULLER H, IN PRESS AGRIENVIRON BUNCE RGH, 1993, LANDSCAPE ECOLOGY AG DEPUTTER J, 1995, GREENING EUROPES AGR FLORIN M, IN PRESS INT J ECOLO GULINCK H, 1986, AGR ECOSYST ENVIRON, V16, P79 HAMMOND A, 1995, ENV INDICATORS SYSTE JENSEN J, 1987, STRANDENGE NATURVENL LARSEN SN, 1995, FERSKE ENGE BESKYTTE LIPSKY M, 1980, STREET LEVEL BUREAUC MACRAE T, 1995, N AM WORKSH MON EC A, P118 MARTINEZ C, 1994, BIOL CONSERV, V67, P125 MCKENZIE DH, 1992, ECOLOGICAL INDICATOR, V1 MCKENZIE DH, 1992, ECOLOGICAL INDICATOR, V2 OCONNOR RJ, 1986, FARMING BIRDS ONATE JJ, 1997, REV ESPANOLA EC AGRA, V179, P297 PAIN DJ, 1997, FARMING BIRDS EUROPE PARRIS K, 1997, OECD OBSERVER DEC PECO B, 1999, AGR ENV EUROPE ROLE, P137 POTTER C, 1988, GEOGRAPHY RURAL CHAN PRIMDAHL J, 1997, CAP REGIONS BUILDING PRIP C, 1995, BIOL MANGFOLD DANMAR RITSON C, 1997, COMMON AGR POLICY SCHEELE M, 1996, EUROPEAN ENV CAP REF, P3 SUAREZ V, 1996, FARMING BIRDS EUROPE, P297 SUMPSI JM, 1995, ENV LAND USE ISSUES VINK APA, 1983, LANDSCAPE ECOLOGY LA WHITBY M, 1996, EUROPEAN ENV CAP REF WINTER S, 1994, IMPLEMENTING EFFEKTI ZONNEVELD IS, 1988, LANDSCAPE ECOLOGY MA, P3 0921-2973 Landsc. Ecol.ISI:000085293300008Royal Vet & Agr Univ, Dept Econ & Nat Resources, Copenhagen, Denmark. Univ Autonoma Madrid, Dept Ecol, Madrid, Spain. Onate, JJ, Univ Europea Madrid CEES, Dept Environm, Madrid, Spain.English 9~?Oneal, A. S. Rotenberry, J. T.2008QRiparian plant composition in an urbanizing landscape in southern California, USA553-567Landscape Ecology235In coastal southern California, natural riparian corridors occur in a landscape mosaic comprised of human land uses (mainly urban and suburban development) interspersed among undeveloped areas, primarily native shrublands. We asked, does the composition of the landscape surrounding a riparian survey point influence plant species distribution, community composition, or habitat structure? We expected, for example, that invasive non-native species might be more abundant as the amount of surrounding urbanization increased. We surveyed 137 points in riparian vegetation in Orange County, California, along an urbanization gradient. Using logistic regression we analyzed 79 individual plant species' distributions, finding 20 negatively associated and 12 positively associated with the amount of development within a 1-km radius around the survey points, even after accounting for the effects of elevation. However, after summarizing plant community composition with Detrended Correspondence Analysis we observed that, overall, community composition was not statistically correlated with the amount of development surrounding a survey point once the association between development and elevation was taken into account. Non-native species were not particularly associated with increasing development, but instead were distributed throughout vegetation and urbanization gradients. However, the extent of the tree and herb layers (structural attributes) was associated with development, with the tree layer increasing and the herb layer decreasing as urbanization increased. Thus, although the degree of surrounding urbanization appears to influence the distribution of a number of individual plant species, overall composition of the community in our study system seemed relatively unaffected. Instead, we suggest that community composition reflected larger-scale environmental conditions, such as stream order and other variables associated with elevation, and/or regional-scale disturbances, such as historic grazing or enhanced atmospheric deposition of nitrogen."://WOS:000254964600006 Times Cited: 0WOS:000254964600006(10.1007/s10980-008-9210-2|ISSN 0921-29730|7 *Oneill, R. V. Gardner, R. H. Turner, M. G.19923A Hierarchical Neutral Model for Landscape Analysis55-61Landscape Ecology71,hierarchy theory percolation theory curdlingAprEmpirical studies have revealed scaled structure on a variety of landscapes. Understanding processes that produce these structures requires neutral models with hierarchical structure. The present study presents a method for generating random maps possessing a variety of hierarchical structures. The properties of these scaled landscapes are analyzed and compared to patterns on totally random, unstructured landscapes. Hierarchical structure permits percolation (i.e., continuous habitat spanning the landscape) under a greater variety of conditions than found on totally random landscapes. Habitat clusters on structured maps tend to have smaller perimeters. The clusters tend to be less clumped on sparsely occupied landscapes and more clumped in densely occupied conditions. Hierarchical structure changes the expected spatial properties of the landscape, indicating a strong need for this new generation of neutral models.://A1992HX80900005-Hx809 Times Cited:56 Cited References Count:0 0921-2973ISI:A1992HX80900005AOneill, Rv Oak Ridge Natl Lab,Div Environm Sci,Oak Ridge,Tn 37831English|7 7Oneill, R. V. Gardner, R. H. Turner, M. G. Romme, W. H.19928Epidemiology Theory and Disturbance Spread on Landscapes19-26Landscape Ecology71-disturbance spatial pattern landscape ecologyApr Epidemiology models, modified to include landscape pattern, are used to examine the relative importance of landscape geometry and disturbance dynamics in determining the spatial extent of a disturbance, such as a fire. The models indicate that, except for very small values for the probability of spread, a disturbance tends to propagate to all susceptible sites that can be reached. Therefore, spatial pattern, rather than disturbance dynamics, will ordinarily determine the total extent of a single disturbance event. The models also indicate that a single disturbance will seldom become endemic, i.e., always present on the landscape. However, increasing disturbance frequency can lead to a landscape in which the proportion of susceptible, disturbed, and recovering sites are relatively constant.://A1992HX80900002-Hx809 Times Cited:19 Cited References Count:0 0921-2973ISI:A1992HX80900002AOneill, Rv Oak Ridge Natl Lab,Div Environm Sci,Oak Ridge,Tn 37831English? Opdam, P.1991\Metapopulation Theory and Habitat Fragmentation: A Review of Holarctic Breeding Bird Studies93-106Landscape Ecology52hLandscape ecology, Habitat fragmentation, Metapopulation, Forest birds, Dispersal, Patch size, IsolationMetapopulations are conceived as spatially structured populations consisting of distinct units (subpopulations), separated by space or barriers, and connected by dispersal movements. Metapopulations characteristically demonstrate a turnover of local populations going extinct and becoming re-established, resulting in a distribution pattern that shifts over time. Metapopulation theory is used to analyse the effects of habitat fragmentation on birds in the temperate zone, integrating various explanations for the paucity of species in isolated ecotopes. There is some evidence that turnover of local populations occurs in fragmented systems. A few studies based on time series demonstrate the local extinction rate to be related to the size of the habitat fragment, whereas the recolonization rate depends on the degree of isolation. Most evidence comes from short-term pattern studies in which the probability of occurrence was found to depend on the size of habitat fragments, on their relative position in the landscape and on the density of corridors lowering the landscape resistance. These data are consistent with predictions from metapopulation theory. However, almost all investigations. consider wood fragmentation in agricultural landscapes, and there-is a great need for studies in naturally fragmented landscapes as well as for studies focussing on other, less predictable, habitat types.<7 Opdam, P.20074Deconstructing and reassembling the landscape system 1445-1446Landscape Ecology2210Editorial MaterialDec://000250632100004TISI Document Delivery No.: 227BL Times Cited: 0 Cited Reference Count: 4 Opdam, Paul 0921-2973 Landsc. Ecol.ISI:000250632100004Wageningen Univ, Dept Land Use Planning & Alterra, Wageningen, Netherlands. Opdam, P, Wageningen Univ, Dept Land Use Planning & Alterra, Wageningen, Netherlands. Paul.Opdam@wur.nlEnglish|? Opdam, Paul2010Learning science from practice821-823Landscape Ecology256Jul!://WOS:000278526000001Times Cited: 1 0921-2973WOS:00027852600000110.1007/s10980-010-9485-yD<7Opdam, P. Foppen, R. Vos, C.2001JBridging the gap between ecology and spatial planning in landscape ecology767-779Landscape Ecology168application of empirical data dispersal corridors habitat network integration of pattern and process approach landscape planning metapopulation studies AGRICULTURAL LANDSCAPE HABITAT FRAGMENTATION METAPOPULATIONS CONNECTIVITY AUSTRALIA SURVIVAL SYSTEMS INDEXES PATTERN POSSUMArticlecLandscapes are studied by pattern (the geographical approach) and by process (the ecological approach within landscape ecology). The future of landscape ecology depends on whether the two approaches can be integrated. We present an approach to bridge the gap between the many detailed process Studies on species, and applied activities such as landscape evaluation and design, which require integrated knowledge. The approach consists of four components: 1) Empirical case studies of different scales, organisms and processes. 2) Modeling studies to extrapolate empirical studies across space and time. 3) Modeling studies to produce guidelines and standards for landscape conditions. 4) Methods and tools for integration to the landscape level, which can be built into multidisciplinary tools for design and evaluation. We conclude that in the landscape ecological literature, the steps I and 2 are well represented, whereas the steps 3 and 4 are mostly neglected. We challenge landscape ecologists to push landscape ecology to a higher level of maturation and to further develop its profile as a problem-oriented science.://000175490900008 ISI Document Delivery No.: 550EP Times Cited: 9 Cited Reference Count: 72 Cited References: *IALE, IALE B, V16, P1 *INT UN CONS NAT N, 1995, RIV CORR HUNG STRAT *NPP, 1990, NAT POL PLAN *SOVON, 1987, ATL NED VOGE AHERN J, 1999, ISSUES LANDSCAPE ECO, P119 ANDREN H, 1996, OIKOS, V76, P235 BASTIAN O, 1998, LANDSCAPE URBAN PLAN, V41, P163 BAUDRY J, 1988, MUNSTERSCHE GEOGRAPH, V29, P23 BENNETT AF, 1999, LINKAGES LANDSCAPE BONNER J, 1994, NEW SCI, V143, P30 BRUINDERINK GG, 2002, UNPUB BIOL CONS CHARDON JP, 2000, EUROPEAN WATER MANAG, V3, P35 DUHME F, 1998, LANDSCAPE URBAN PLAN, V41, P249 FAHRIG L, 1985, ECOLOGY, V66, P1762 FAHRIG L, 1999, ISSUES LANDSCAPE ECO, P145 FOPPEN R, 1999, ARDEA, V86, P113 FOPPEN R, 2000, LANDSCAP, V16, P99 FOPPEN R, 2002, UNPUB OCCURRENCE RED FOPPEN RPB, 2000, CONSERV BIOL, V14, P1881 FORMAN RTT, 1982, PERSPECTIVES LANDSCA, P35 HAASE G, 1989, LANDSCAPE ECOL, V3, P29 HADDAD NM, 1999, AM NAT, V153, P215 HAINESYOUNG R, 1999, ISSUES LANDSCAPE ECO, P33 HANSKI I, 1994, J ANIM ECOL, V63, P151 HANSKI I, 1997, METAPOPULATION BIOL, P5 HARMS BH, 1993, LANDSCAPE ECOLOGY ST, P197 HENDERSON MT, 1985, BIOL CONSERV, V31, P95 JONGMAN AHG, 1996, MN27 EUR CTR NAT CON KREBS CJ, 1985, ECOLOGY EXPT ANAL DI LEVINS R, 1970, SOME MATH PROBLEMS B, P77 LI BL, 2000, LANDSCAPE URBAN PLAN, V50, P27 LINDENMAYER DB, 1995, BIODIVERS CONSERV, V4, P984 LINDENMAYER DB, 1995, BIOL CONSERV, V73, P119 MIKLOS L, 1989, LANDSCAPE ECOL, V3, P43 MONKKONEN M, 1999, OIKOS, V84, P302 MOSS M, 1999, ISSUES LANDSCAPE ECO, P138 MOSS MR, 2000, LANDSCAPE ECOL, V15, P303 NAVEH Z, 1987, LANDSCAPE ECOL, V1, P75 NAVEH Z, 2000, LANDSCAPE URBAN PLAN, V50, P7 NEEF E, 1982, PERSPECTIVES LANDSCA, P19 ODUM EP, 1971, FUNDAMENTALS ECOLOGY OPDAM P, 1985, BIOL CONSERV, V34, P333 OPDAM P, 1988, P 2 INT SEM INT ASS, P75 OPDAM P, 1991, LANDSCAPE ECOL, V5, P93 OPDAM P, 1995, IBIS, V137, P139 OPDAM P, 2001, CONCEPTS APPL LANDSC OPDAM P, 2001, IN PRESS CONSERVING OPDAM P, 2002, UNPUB LANDSCAPE COHE PHIPPS M, 1982, P 1 INT C LANDSC EC, P57 RUZIKA M, 1982, PERSPECTIVES LANDSCA, P99 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SMITH AT, 1997, METAPOPULATION BIOL, P407 TAKEUCHI K, 1989, LANDSCAPE ECOLOGY, V3, P53 TAYLOR B, 1991, BIOL J LINN SOC, V42, P177 TERBRAAK CJF, 1998, MODELING SPATIOTEMPO, P167 THOMAS CD, 1997, METAPOPULATION BIOL, P359 TISCHENDORF L, 1997, OIKOS, V79, P603 TJALLINGII SP, 1982, P 1 INT C LANDSC EC VANDORP D, 1987, LANDSCAPE ECOLOGY, V1, P59 VANLIER HN, 1998, LANDSCAPE URBAN PLAN, V41, P83 VEEN AWL, 1982, PERSPECTIVES LANDSCA, P49 VERBOOM J, 1991, OIKOS, V61, P149 VERBOOM J, 2001, BIOL CONSERV, V100, P89 VERMEULEN HJW, 1995, THESIS WAGENINGEN AG VOS CC, 1998, J APPL ECOL, V35, P44 VOS CC, 2000, ECOL B, V48, P165 VOS CC, 2001, AM NAT, V157, P24 VOS CC, 2001, IN PRESS CNCEPTS APP VOS CC, 2002, UNPUB LANDSC ECOL WIENS JA, 1997, METAPOPULATION BIOL, P43 WITH KA, 1999, CONS BIOL, V13, P14 ZONNEVELD IS, 1982, PERSPECTIVES LANDSCA, P9 0921-2973 Landsc. Ecol.ISI:000175490900008Univ Wageningen & Res Ctr, ALTERRA, Dept Landscape Ecol, NL-6700 AA Wageningen, Netherlands. Opdam, P, Univ Wageningen & Res Ctr, ALTERRA, Dept Landscape Ecol, Postbus 47, NL-6700 AA Wageningen, Netherlands.English[|? Opdam, P. Luque, S. Jones, K. B.2009[Changing landscapes to accommodate for climate change impacts: a call for landscape ecology715-721Landscape Ecology246JulPredictions of climate change suggest major changes in temperature, rainfall as well as in frequency and timing of extreme weather, all in varying degrees and patterns around the world. Although the details of these patterns changes are still uncertain, we can be sure of profound effects on ecological processes in and functioning of landscapes. The impact of climate change will affect all types of land use, ecosystem services, as well as the behavior of humans. The core business of Landscape Ecology is the interaction of landscape patterns and processes. Most of these interactions will be affected by changing climate patterns, so clearly within the focus of our science. Nevertheless, climate change received little attention from landscape ecologists. Are we missing the boat? Why is it that our science does not contribute to building a knowledge base to help solving this immense problem? Why is there so little attention paid to adaptation of landscape to climate change? With this editorial article IALE would like to receive inputs from the Landscape Ecology scientific community in related research on adaptation of landscapes to climate change, on tools or approaches to help landscape planners and stakeholders to this new challenge where landscape ecology can play a key role.://000268248100001)Opdam, Paul Luque, Sandra Jones, K. Bruce 0921-2973ISI:00026824810000110.1007/s10980-009-9377-1Hڽ7*Opdam, Paul Nassauer, JoanIverson Wang, Zhifang Albert, Christian Bentrup, Gary Castella, Jean-Christophe McAlpine, Clive Liu, Jianguo Sheppard, Stephen Swaffield, Simon2013/Science for action at the local landscape scale 1439-1445Landscape Ecology288Springer NetherlandsCommunity-based landscape planning Cross-disciplinary synthesis Capacity building Science–practice interface Sustainability Transdisciplinary science 2013/10/01+http://dx.doi.org/10.1007/s10980-013-9925-6 0921-2973Landscape Ecol10.1007/s10980-013-9925-6English<7w!Opdam, P. Verboom, J. Pouwels, R.2003ZLandscape cohesion: an index for the conservation potential of landscapes for biodiversity113-126Landscape Ecology182biodiversity habitat fragmentation landscape cohesion landscape indices landscape planning metapopulation persistence network cohesion spatial cohesion HABITAT FRAGMENTATION AGRICULTURAL LANDSCAPE METAPOPULATIONS POPULATIONS CONNECTIVITY BIRDS SURVIVAL RESERVES DYNAMICS WOODLANDArticleIn urbanising landscapes, planning for sustainable biodiversity occurs in a context of multifunctional land use. Important conditions for species persistence are habitat quality, the amount and configuration of habitat and the permeability of the landscape matrix. For planning purposes, these determinants should be integrated into simple indicators for spatial conditions of persistence probability. We propose a framework of three related indices. The cohesion index is based on the ecology of metapopulations in a habitat network. We discuss how an indicator for species persistence in such a network could be developed. To translate this network index into an area index, we propose the concept of spatial cohesion. Habitat cohesion and spatial cohesion are defined and measured for single species or, at best, for species profiles. Since species differ in their perception of the same landscape, different species will rate different values of these indices for the same landscape. Because landscapes are rarely planned for single species, we further propose the index of landscape cohesion, which integrates the spatial cohesion indices of different species. Indices based on these concepts can be built into GIS tools for landscape assessment. We illustrate different applications of these indices, and emphasise the distinction between ecological and political decisions in developing and applying such tools.://000183770300002 ISI Document Delivery No.: 694JB Times Cited: 22 Cited Reference Count: 72 Cited References: 1997, NATUURVERKENNING 97 ADLER FR, 1994, THEOR POPUL BIOL, V45, P41 AHERN J, 1999, ISSUES LANDSCAPE ECO, P119 ANDREN H, 1994, OIKOS, V71, P355 ANDREN H, 1996, OIKOS, V76, P235 DOAK D, 1989, CONSERV BIOL, V3, P389 DUNNING JB, 1995, CONSERV BIOL, V9, P542 ETTIENNE RS, 2001, AM NAT, V158, P389 FAHRIG L, 1994, CONSERV BIOL, V8, P50 FAHRIG L, 1999, ISSUES LANDSCAPE ECO, P145 FAHRIG L, 2001, BIOL CONSERV, V100, P65 FOPPEN R, 2001, WAGENINGEN U ALTERRA, V4 FOPPEN RPB, 2000, CONSERV BIOL, V14, P1881 FRANK K, 1998, LANDSCAPE ECOL, V13, P363 FRANK K, 2002, AM NAT, V159, P530 GEERTSEMA W, 2002, LANDSCAPE ECOL, V17, P263 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HANSKI I, 1994, J ANIM ECOL, V63, P151 HANSKI I, 1997, METAPOPULATION BIOL, P5 HANSKI I, 1997, METAPOPULATION BIOL, P69 HANSKI I, 1999, OIKOS, V87, P209 HARMS BH, 1993, LANDSCAPE ECOLOGY ST, P197 HARRISON S, 1988, AM NAT, V132, P360 HENDERSON MT, 1985, BIOL CONSERV, V31, P95 HOOGEVEEN YR, 2001, ANAL RUIMTELIJKE SAM LANDE R, 1987, AM NAT, V130, P624 LINDENMAYER DB, 1995, BIODIVERS CONSERV, V4, P984 LINDENMAYER DB, 1995, BIOL CONSERV, V73, P119 LOMOLINO MV, 1994, BIOL CONSERV, V69, P243 MARGULES CR, 1988, BIOL CONSERV, V43, P63 MARGULES CR, 1999, ISSUES LANDSCAPE ECO, P83 MATTHYSEN E, 1996, ECOGRAPHY, V19, P72 MERRIAM G, 1988, TRENDS ECOL EVOL, V3, P16 MONKKONEN M, 1999, OIKOS, V84, P302 MOSS M, 1999, ISSUES LANDSCAPE ECO, P138 NASSAUER JI, 1999, ISSUES LANDSCAPE ECO, P129 OPDAM P, 1988, MUNSTERSCHE GEOGRAPH, V29, P75 OPDAM P, 1991, LANDSCAPE ECOL, V5, P93 OPDAM P, 1993, LANDSCAPE ECOLOGY ST, P147 OPDAM P, 1995, IBIS, V137, P139 OPDAM P, 2002, APPL LANDSCAPE ECOLO, P381 OPDAM P, 2002, CONSERVING BIRD BIOD, P202 OPDAM P, 2002, LANDSCAPE ECOLOGY, V16, P767 POSSINGHAM HP, 1994, BIOL CONSERV, V70, P227 POUWELS R, 2002, 492 ALT PRESSEY RL, 1989, BIOL CONSERV, V50, P263 REIJNEN R, 1998, 372 I FOR NAT RES REIJNEN R, 2000, WEG MET MINSTE WEERS SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SJOGREN P, 1991, BIOL J LINN SOC, V42, P135 SMITH AT, 1997, METAPOPULATION BIOL, P407 SUTCLIFFE OL, 1996, CONSERV BIOL, V10, P1359 TERBRAAK CJF, 1998, MODELING SPATIOTEMPO, P167 THEOBALD DM, 2000, LANDSCAPE ECOL, V15, P35 THOMAS CD, 1997, METAPOPULATION BIOL, P359 THOMAS CD, 1999, J ANIM ECOL, V68, P647 TILMAN D, 1997, SPATIAL ECOLOGY ROLE VANDORP D, 1987, LANDSCAPE ECOLOGY, V1, P59 VERBOOM J, 1991, LANDSCHAP, V8, P3 VERBOOM J, 1991, OIKOS, V61, P149 VERBOOM J, 1993, LANDSCAPE ECOLOGY ST, P172 VERBOOM J, 2001, BIOL CONSERV, V100, P89 VILLARD MA, 1995, ECOLOGY, V76, P27 VILLARD MA, 1999, CONSERV BIOL, V13, P774 VOS CC, 1998, J APPL ECOL, V35, P44 VOS CC, 2000, ECOL B, V48, P165 VOS CC, 2001, AM NAT, V157, P24 VOS CC, 2002, APPL LANDSCAPE ECOLO, P84 WAHLBERG N, 1996, SCIENCE, V273, P1536 WIENS JA, 1997, METAPOPULATION BIOL, P43 WITH KA, 1997, OIKOS, V78, P151 WITH KA, 1999, CONS BIOL, V13, P14 0921-2973 Landsc. Ecol.ISI:000183770300002*Univ Wageningen & Res Ctr, Dept Landscape Ecol, Alterra, NL-6700 AA Wageningen, Netherlands. Univ Wageningen & Res Ctr, Nat Conservat & Plant Ecol Grp, NL-6700 AA Wageningen, Netherlands. Opdam, P, Univ Wageningen & Res Ctr, Dept Landscape Ecol, Alterra, POB 47, NL-6700 AA Wageningen, Netherlands.English? :Orrock, John Curler, Gregory Danielson, Brent Coyle, David2011wLarge-scale experimental landscapes reveal distinctive effects of patch shape and connectivity on arthropod communities 1361-1372Landscape Ecology2610Springer NetherlandsEarth and Environmental Science9The size, shape, and isolation of habitat patches can affect organism behavior and population dynamics, but little is known about the relative role of shape and connectivity in affecting ecological communities at large spatial scales. Using six sampling sessions from July 2001 until August 2002, we collected 33,685 arthropods throughout seven 12-ha experimental landscapes consisting of clear-cut patches surrounded by a matrix of mature pine forest. Patches were explicitly designed to manipulate connectivity (via habitat corridors) independently of area and edge effects. We found that patch shape, rather than connectivity, affected ground-dwelling arthropod richness and beta diversity (i.e. turnover of genera among patches). Arthropod communities contained fewer genera and exhibited less turnover in high-edge connected and high-edge unconnected patches relative to low-edge unconnected patches of similar area. Connectivity, rather than patch shape, affected the evenness of ground-dwelling arthropod communities; regardless of patch shape, high-edge connected patches had lower evenness than low- or high-edge unconnected patches. Among the most abundant arthropod orders, increased richness in low-edge unconnected patches was largely due to increased richness of Coleoptera, whereas Hymenoptera played an important role in the lower evenness in connected patches and patterns of turnover. These findings suggest that anthropogenic habitat alteration can have distinct effects on ground-dwelling arthropod communities that arise due to changes in shape and connectivity. Moreover, this work suggests that corridors, which are common conservation tools that change both patch shape and connectivity, can have multiple effects on arthropod communities via different mechanisms, and each effect may alter components of community structure.+http://dx.doi.org/10.1007/s10980-011-9656-5 0921-297310.1007/s10980-011-9656-5|??Ostapowicz, K. Vogt, P. Riitters, K. H. Kozak, J. Estreguil, C.2008:Impact of scale on morphological spatial pattern of forest 1107-1117Landscape Ecology239Assessing and monitoring landscape pattern structure from multi-scale land-cover maps can utilize morphological spatial pattern analysis (MSPA), only if various influences of scale are known and taken into account. This paper lays part of the foundation for applying MSPA analysis in landscape monitoring by quantifying scale effects on six classes of spatial patterns called: core, edge, perforation, branch, connector and islet. Four forest maps were selected with different forest composition and configuration. The sensitivity of MSPA to scale was studied by comparing frequencies of pattern classes in total forest area for various combinations of pixel size (P) and size parameter (S). It was found that the quantification of forest pattern with MSPA is sensitive to scale. Differences in initial composition and configuration influence the amount but not the general tendencies of the variations of morphological spatial pattern (MSP) class proportions with scale. Increase of P led to data generalization resulting in either a removal of the small size features or their potential transformation into other non-core MSP classes, while an increase of S decreases the MSP core area and this process may transform small core areas into the MSP class islet. We established that the behavior of the MSPA classes with changing scale can be categorized as consistent and robust scaling relations in the forms of linear, power, or logarithmic functions over a range of scales.!://WOS:000260283100009Times Cited: 0 0921-2973WOS:00026028310000910.1007/s10980-008-9271-2<7Ostendorf, B. Reynolds, J. F.1993xRelationships between a terrain-based hydrologic model and patch-scale vegetation patterns in an arctic tundra landscape229-237Landscape Ecology84ArticleDecImplicit in the relationship between vegetation patterns and landforms is the influence of topography on the water regime at the patch scale. Hence, based on the numerous process-based studies linking plant structure and function to water in the arctic, we hypothesize that the general pattern of arctic landscapes can be explained by a mesotopographic variable such as water drainage. In this paper, we test this hypothesis by examining the spatial relationship between patterns of vegetation and the water regime in a small watershed in northern Alaska. Using gridded elevation data, we develop a model (T-HYDRO) to generate a 2-dimensional water flow field for the watershed and compare this to vegetation patterns as given by 1) a vegetation map developed from aerial photographs in conjunction with extensive field sampling; and 2) a normalized difference vegetation index (NDVI). Our results show that it is possible to account for about 43% of the spatial variance in NDVI, which supports our hypothesis. In spite of its limitations, the correspondence of patterns presented in this paper provides encouraging evidence that we can find simple approaches to stratify landscapes and that it is possible to overcome the frequently made assumption of spatial homogeneity in ecosystems modeling.://A1993MN73600001 IISI Document Delivery No.: MN736 Times Cited: 15 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1993MN73600001<OSTENDORF, B, BITOK,POSTFACH 101251,W-8580 BAYREUTH,GERMANY.English=<7mOstendorf, B. Reynolds, J. F.1998FA model of arctic tundra vegetation derived from topographic gradients187-201Landscape Ecology133vegetation pattern tussock tundra landscapes topography water drainage scaling up BROOKS-RANGE-FOOTHILLS CLASSIFICATION ACCURACY LANDSCAPE PATTERNS ALASKA DYNAMICS TERRAIN WATER PATCH DISTURBANCEArticleJunWe present a topographically-derived vegetation model (TVM) that predicts the landscape patterns of arctic vegetation types in the foothills of the Brooks Range in northern Alaska. In the Arctic there is a strong relationship between water and plant structure and function and TVM is based on the relationships between vegetation types and slope (tan beta) and discharge (delta), two independent variables that can be easily derived from digital terrain data. Both slope and discharge relate to hydrological similarity within a landscape: slope determines the gravitational hydrological gradient and hence influences flow velocity, whereas discharge patterns are computed based on upslope area and quantify lateral flow amount. TVM was developed and parameterized based on vegetation data from a small 2.2 km(2) watershed and its application was tested in a larger 22 km(2) region. For the watershed, TVM performed quite well, having a high spatial resolution and a goodness-of-fit ranging from 71-78%, depending on the functions used. For the larger region, the strength of the vegetation types predictions drops somewhat to between 56-59%. We discuss the various sources of error and limitations of the model for purposes of extrapolation.://000079303300004 ISI Document Delivery No.: 179BH Times Cited: 20 Cited Reference Count: 62 Cited References: BEVEN KJ, 1979, HYDROL SCI B, V24, P43 BILLINGS WD, 1959, ECOLOGY, V40, P388 BILLINGS WD, 1992, GLOBAL WARMING BIOL, P233 BLISS LC, 1984, HOLARCTIC ECOL, V7, P305 BONAN GB, 1993, CLIMATIC CHANGE, V24, P281 BROWN DG, 1994, J VEG SCI, V5, P641 BRZEZIECKI B, 1995, J VEG SCI, V6, P257 CARSTENSEN LW, 1987, AM CARTOGRAPHER, V14, P345 CHAPIN FS, 1988, ECOLOGY, V69, P693 CHAPIN FS, 1992, ARCTIC ECOSYSTEMS CH, P3 CONGALTON RG, 1983, PHOTOGRAMM ENG REM S, V49, P1671 CONGALTON RG, 1983, PHOTOGRAMM ENG REM S, V49, P69 CONGALTON RG, 1991, REMOTE SENS ENVIRON, V37, P35 COSTANZA R, 1989, ECOLOGICAL MODELLING, V47, P199 COSTANZA R, 1990, BIOSCIENCE, V40, P91 DANGELIS DL, 1994, EVERGLADES ECOSYSTEM, P9 DAVIS FW, 1990, LANDSCAPE ECOL, V4, P69 DEMOLENAAR JG, 1987, ARCTIC ALPINE RES, V19, P414 DONNER A, 1996, BIOMETRICS, V52, P176 EVANS BM, 1989, HOLARCTIC ECOL, V12, P270 EVERETT KR, 1988, PERMAFROST, V1, P574 GEBAUER RLE, 1995, OECOLOGIA, V104, P330 GOWARD SN, 1995, J BIOGEOGR, V22, P549 HASTINGS SJ, 1989, HOLARCTIC ECOL, V12, P304 HENDERSONSELLERS B, 1996, ECOL MODEL, V86, R7 HUDSON WD, 1987, PHOTOGRAMM ENG REM S, V53, P421 JASIENIUK MA, 1982, CAN J BOT, V60, P2581 KANE DL, 1992, ARCTIC ECOSYSTEMS CH, P35 LEADLEY PW, 1996, ECOL STU AN, V120, P387 LENIHAN JM, 1993, J VEG SCI, V4, P667 LI H, 1997, SCALE REMOTE SENSING, P211 MARTIN P, 1992, CLIM DYNAM, V7, P1 MATTHESSEARS U, 1988, ARCTIC ALPINE RES, V20, P342 MONSERUD RA, 1992, ECOL MODEL, V62, P275 NEILSON RP, 1995, ECOL APPL, V5, P362 OBERBAUER SF, 1996, ECOL STU AN, V120, P223 OLOUGHLIN EM, 1986, WATER RESOUR RES, V22, P794 OSTENDORF B, 1993, LANDSCAPE ECOL, V8, P229 OSTENDORF B, 1996, ARCTIC ALPINE RES, V28, P318 OSTENDORF B, 1996, BAYREUTHER FORUM OKO, V26 OSTENDORF B, 1996, ECOL STU AN, V120, P369 PETERSON KM, 1980, ARCTIC ALPINE RES, V12, P473 PRENTICE IC, 1991, GLOBAL CHANGES PAST, P365 REYNOLDS JF, 1996, ECOL STU AN, V120, P293 REYNOLDS JF, 1996, ECOL STU AN, V120, P3 REYNOLDS JF, 1996, ECOLOGICAL STUDIES S, V120, P460 ROSENFIELD GH, 1986, PHOTOGRAMM ENG REM S, V52, P223 SHAVER GR, 1991, ECOL MONOGR, V61, P1 SHEPARD D, 1968, P 23 NAT C ACM, P517 SHUGART HH, 1984, THEORY FOREST DYNAMI STOW D, 1989, INT J REMOTE SENS, V10, P1451 TURNER MG, 1989, ECOL MODEL, V48, P1 TURNER MG, 1991, QUANTITATIVE METHODS, P323 WALKER DA, 1983, PERMAFROST, P1332 WALKER DA, 1989, HOLARCTIC ECOL, V12, P238 WALKER DA, 1993, BIOSCIENCE, V43, P287 WALKER DA, 1996, ECOL STU AN, V120, P35 WALKER MD, 1994, J VEG SCI, V5, P843 WEBBER PJ, 1977, ARCTIC ALPINE ENV, P445 WEBBER PJ, 1978, VEGETATION PRODUCTIO, P37 WOODWARD FI, 1992, NEW PHYTOL, V122, P239 WU JG, 1995, Q REV BIOL, V70, P439 0921-2973 Landsc. Ecol.ISI:000079303300004European Acad Bozen, Dept Alpine Environm, I-39100 Bolzano, Italy. Ostendorf, B, European Acad Bozen, Dept Alpine Environm, Piazza Duomo 3, I-39100 Bolzano, Italy.English?.Annette Otte Dietmar Simmering Volkmar Wolters2007cBiodiversity at the landscape level: recent concepts and perspectives for multifunctional land use 639-642Landscape Ecology225ڽ7C,Ou, Jinpei Liu, Xiaoping Li, Xia Chen, Yimin2013_Quantifying the relationship between urban forms and carbon emissions using panel data analysis 1889-1907Landscape Ecology2810Springer Netherlands0Urban forms Carbon emissions Panel data analysis 2013/12/01+http://dx.doi.org/10.1007/s10980-013-9943-4 0921-2973Landscape Ecol10.1007/s10980-013-9943-4English<7pAOvalle, C. Del Pozo, A. Casado, M. A. Acosta, B. de Miguel, J. M.2006Consequences of landscape heterogeneity on grassland diversity and productivity in the espinal agroforestry system of central Chile585-594Landscape Ecology214geomorphology; grazing; land use; species richness; woody plant cover VEGETATION; PATTERNS; CALIFORNIA; APPRAISAL; RICHNESS; TREES; STATE; SPAINArticleMay<The current land use system in the anthropogenic savannas (Espinales) of the Mediterranean climate region of Chile, has resulted in considerable heterogeneity at the landscape level which is associated with different covers of the legume tree, Acacia caven. The effects of landscape heterogeneity on the diversity and productivity of herbaceous plant communities were studied in 29 plots of 1000 m(2), with a wide range of woody cover. A detrended correspondence analysis of the species x plots matrix explained 73% of the total variation and revealed the existence of two trends of variation in floristic composition: one associated with physiographic position (hillsides and flatlands) and the other related to the number of years since the last cutting, or coppicing, of A. caven. Despite the great majority of the original herbaceous species having disappeared as a result of the prevailing land use system, some native species have been able to survive especially on hillside areas with low grazing intensity. Woody cover was a good indicator of spatial heterogeneity and land use history. It was also correlated with stocking rate, above-ground biomass of herbaceous vegetation, and soil fertility (organic matter, nitrogen and phosphorus concentration), both on hillsides and flatlands. The relationship between woody cover and herbaceous plant species richness was significant and unimodal in flat land areas, and linear, and marginally significant, on hillsides. The consequences of land use changes on the conservation of the ecological and productive values of grasslands are analyzed.://000237487700010 ISI Document Delivery No.: 041WR Times Cited: 0 Cited Reference Count: 41 Cited References: *SAS I INC, 2000, GUID PERS COMP ARMESTO JJ, 1985, REV CHIL HIST NAT, V58, P9 ARONSON J, 1992, ANN MISSOURI BOT GAR, V79, P558 ARONSON J, 1993, RESTORATION ECOLOGY, V1, P168 ARONSON J, 1993, RESTORATION ECOLOGY, V1, P8 ARONSON J, 1998, ECOLOGICAL STUDIES S, V136, P155 ARONSON J, 2002, AGROFOREST SYST, V56, P155 ARROYO MTK, 1999, HOTSPOTS EARTHS BIOL, P122 BELBIN L, 1987, PATN PATTERN ANAL PA BUREL F, 2001, ECOLOGIE PAYSAGE CASADO MA, 1985, VEGETATIO, V64, P75 CASADO MA, 2004, PLANT ECOL, V170, P83 CONNELL JH, 1978, SCIENCE, V199, P1302 DAGET P, 1971, ANN AGRON, V22, P5 DELPOZO A, 2002, PLANT ECOL, V159, P119 DEMIGUEL JM, 1997, J RANGE MANAGE, V50, P85 DEMIGUEL JM, 1999, REV CHIL HIST NAT, V72, P547 FORMAN RTT, 1995, LAND MOSAICS GOMEZSAL A, 1992, VEGETATIO, V99, P345 GRACE JB, 1999, PERSPECT PLANT ECOL, V2, P1 GULMON SL, 1977, FLORA, V166, P261 HOLMGREN M, 2000, J ARID ENVIRON, V44, P197 HUSTON MA, 1994, BIOL DIVERSITY NOYMEIR I, 1979, MANAGEMENT SEMIARID, P113 NOYMEIR I, 1989, J ECOL, V77, P290 OVALLE C, 1987, OECOLOG PLANTAR, V8, P385 OVALLE C, 1990, AGROFOREST SYST, V10, P213 OVALLE C, 1994, AGR SECANO INTERIOS OVALLE C, 1996, FOREST ECOL MANAG, V86, P129 OVALLE C, 1996, PLANT SOIL, V179, P131 OVALLE C, 1999, ARID SOIL RES REHAB, V13, P369 PAUSAS JG, 2001, J VEG SCI, V12, P153 PICKETT STA, 1985, ECOLOGY NATURAL DIST PINEDA FD, 1981, VEGETATIO, V44, P165 RIVASMARTINEZ S, 1977, ANAL I BOT CAVANILLE, V34, P355 RIVASMARTINEZ S, 1977, COLL PHYTOSOCIOL, V6, P55 RIVASMARTINEZ S, 1978, DOCUMENTS PHYTOSOCIO, V2, P377 ROSENZWEIG ML, 1995, SPECIES DIVERSITY SP SAX DF, 2002, DIVERS DISTRIB, V8, P193 SOLBRIG OT, 1977, CONVERGENT EVOLUTION, P13 TURNER MG, 1987, ECOLOGICAL STUDIES, V64 0921-2973 Landsc. Ecol.ISI:000237487700010Univ Talca, Fac Ciencias Agrarias, Talca, Chile. INIA, CRI Quilamapu, Chillan, Chile. Univ Complutense Madrid, Fac Biol, Dept Ecol, E-28040 Madrid, Spain. Del Pozo, A, Univ Talca, Fac Ciencias Agrarias, Casilla 747, Talca, Chile. adelpozo@utalca.clEnglish<7t3Overgaard, H. J. Ekbom, B. Suwonkerd, W. Takagi, M.2003Effect of landscape structure on anopheline mosquito density and diversity in northern Thailand: Implications for malaria transmission and control605-619Landscape Ecology186anopheles landscape ecology landscape metrics landscape management malaria mosquitoes SOUTHEAST-ASIA CULICIDAE DIPTERA POPULATION VILLAGE ECOLOGY MINIMUS FRAGMENTATION MANAGEMENT ABUNDANCEArticle The influence of landscape structure on anopheline mosquito density and diversity was studied in a comparison of agricultural and forested landscapes in northern Thailand. Agriculture locations had significantly higher landscape diversity, more patches, smaller mean patch sizes, and more complex patch shapes than forest locations. Mosquito collections were undertaken during both dry and wet seasons from October 1997 to December 1999. The density of two forest-associated species, Anopheles maculatus s.s. and Anopheles minimus s.l., both primary malaria vectors in Thailand, was significantly higher in forest locations in at least one season. The density of two paddy field-associated species, Anopheles aconitus and Anopheles hyrcanus group did not differ between locations. Anopheles aconitus is a secondary malaria vector and An. hyrcanus group is not considered as a vector in Thailand. The density of An. minimus s.l. was positively related to forest mean patch size, various water and paddy field landscape metrics and negatively related to landscape diversity. Anopheles hyrcanus group was also positively related to water metrics. Anopheline species diversity was negatively related to landscape diversity. Forest fragmentation resulting from human economic activities often increases landscape heterogeneity, which may result in a reduction in anopheline species diversity, as was the case in this study. There are indications that the effect of fruit orchards on anopheline diversity might be different in the dry season compared to the wet season. Fruit orchard landscape metrics affected species diversity negatively in the dry season and positively in the wet season. One reason for this could be that pesticides are typically applied in fruit orchards during the dry season. The conversion of forests to fruit orchards is a major land-use change in northern Thailand. These results show the complexity of vector status in northern Thailand and that vector and agriculture pest control are intricately interrelated. It is therefore important to include both the public health and agricultural sectors in controlling malaria vectors in the country. Our results also indicate that if landscape management should be used for malaria control in northern Thailand large-scale reduction and fragmentation of forest cover would be needed. Such drastic actions do not agree well with current global objectives concerning forest and biodiversity conservation.://000185827300005 ISI Document Delivery No.: 730JH Times Cited: 4 Cited Reference Count: 72 Cited References: *FAO, 1999, STAT WORLDS FOR 1999 *MAL DIV, 1998, ANN REP MIN PUBL HLT *MET DEP, 1999, YEARL REC JAN 1977 1 *SAS I, 1996, SAS STAT US GUID VER *UMETR AB, 1994, US GUID SIMC S VERS *WHO, 1975, MAN PRACT ENT MAL 2 AULT SK, 1994, AM J TROP MED, V50, P35 BAIMAI V, 1993, J AM MOSQUITO CONTR, V9, P59 BECK LR, 1994, AM J TROP MED, V51, P271 BRUCECHWATT LJ, 1985, ESSENTIAL MALARIOLOG BUNGE J, 1993, J AM STAT ASSOC, V88, P364 BUTRAPORN P, 1986, SE ASIAN J TROPICAL, V17, P386 CHAO A, 1984, SCAND J STAT, V11, P265 DIDHAM RK, 1996, TRENDS ECOL EVOL, V11, P255 DUNNING JB, 1992, OIKOS, V65, P169 EASTON ER, 1994, J AM MOSQUITO CONTR, V10, P540 EYLES DE, 1964, B WORLD HEALTH ORGAN, V30, P7 GARCIA R, 1979, AGROECOSYSTEMS, V5, P295 GIBBS JP, 2001, ECOL APPL, V11, P79 GINGRICH JB, 1990, J MED ENTOMOL, V27, P1016 GOULD DJ, 1967, T ROY SOC TROP MED H, V61, P441 GREEN CA, 1985, BIOL J LINN SOC, V4, P321 GREEN CA, 1990, MED VET ENTOMOL, V4, P25 HARBACH RE, 1987, J AM MOSQUITO CONTR, V3, P296 HARRISON BA, 1975, CONTRIB AM ENTOMOL I, V12, P1 HARRISON BA, 1980, CONTR AM ENTOMOL I, V17, P1 HARRISON BA, 1990, MOSQ SYST, V22, P196 HII JLK, 1997, J MED ENTOMOL, V34, P193 HO C, 1962, CHINA MED J, V81, P71 HOOVER SR, 1991, LANDSCAPE ECOL, V5, P125 ISMAIL IAH, 1975, ACTA TROP, V32, P206 ISMAIL IAH, 1978, ACTA TROP, V35, P69 JONSEN ID, 1997, LANDSCAPE ECOL, V12, P185 KITRON U, 1987, INT J HEALTH SERV, V17, P295 KLEIN BC, 1989, ECOLOGY, V70, P1715 LWIN M, 1991, SE ASIAN J TROPICAL, V22, P509 MAHESWARY NP, 1992, SE ASIAN J TROPICAL, V23, P798 MARTENS M, 1983, J SCI FOOD AGR, V34, P715 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MYO P, 1988, TROPICAL BIOMEDICINE, V5, P161 OVERGAARD HJ, 2002, ENVIRON ENTOMOL, V31, P134 PEYTON EL, 1966, ILLUSTRATED KEY FEMA PEYTON EL, 1979, MOSQ SYST, V11, P40 POOLSUWAN S, 1995, SE ASIAN J TROP MED, V26, P3 PRAKASH A, 1997, SE ASIAN J TROP MED, V28, P610 PRESTON FW, 1948, ECOLOGY, V29, P254 RAO TR, 1984, ANOPHELINES INDIA RATTANARITHIKUL R, 1973, ILLUSTRATED KEY ANOP RATTANARITHIKUL R, 1986, MOSQ SYST, V18, P246 RATTANARITHIKUL R, 1994, SE ASIAN J TROP MED, V25, P1 REID JA, 1968, STUD I MED RES MALAY, V31, P1 RODRIGUEZ AD, 1996, J MED ENTOMOL, V33, P39 ROSENBERG R, 1990, T ROY SOC TROP MED H, V84, P22 SAWADWONGPORN R, 1972, PICTORIAL KEY ANOPHE SINGHANETRARENA.A, 1993, SOC SCI MED, V37, P1147 SINGHASIVANON P, 1999, SE ASIAN J TROPICAL, V30, P399 SMITH T, 1995, ACTA TROP, V59, P1 SOMBOON P, 1998, SE ASIAN J TROPICAL, V29, P3 SUWONKERD W, 2002, BASIC APPL ECOL, V3, P197 TAKAGI M, 1995, JPN J TROP MED HYG, V23, P177 THIES C, 1999, SCIENCE, V285, P893 THOMSON MC, 1996, ANN TROP MED PARASIT, V90, P243 THOMSON RCM, 1940, J MALAR I INDIA, V3, P265 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1990, ECOLOGICAL STUDIES S, V82 UPATHAM ES, 1988, SE ASIAN J TROPICAL, V19, P259 WEHNER R, 2000, THESIS U HOHENHEIM S WEIBULL AC, 2000, ECOGRAPHY, V23, P743 WIENS JA, 1976, ANNU REV ECOL SYST, V7, P81 WILKINSON RN, 1978, J MED ENTOMOL, V14, P666 WOLD H, 1985, ENCY STATISTICAL SCI, V6, P581 WOOD BL, 1992, INT J REMOTE SENS, V13, P2813 0921-2973 Landsc. Ecol.ISI:000185827300005NAgr Univ Norway, Dept Forest Sci, N-1432 As, Norway. Swedish Univ Agr Sci, Dept Entomol, Uppsala, Sweden. Minist Publ Hlth, Off Vector Borne Dis Control 2, Chiang Mai 50200, Thailand. Nagasaki Univ, Inst Trop Med, Dept Med Entomol, Nagasaki 8528523, Japan. Overgaard, HJ, Agr Univ Norway, Dept Forest Sci, Box 5044, N-1432 As, Norway.EnglishC<7Owen-Smith, N.2004YFunctional heterogeneity in resources within landscapes and herbivore population dynamics761-771Landscape Ecology197fragmentation; large mammals; metaphysiological model; resource patches; Serengeti Nationaal Park; Tanzania; ungulates; waterpoints VEGETATION SYSTEMS; ISLE ROYALE; MODELS; STABILITY; CONSTRAINTS; ECOSYSTEMS; WILDEBEEST; MANAGEMENT; SELECTION; DENSITYArticleLarge mammalian herbivores are notorious for their propensity towards population irruptions and crashes, yet many herbivore populations remain relatively stable. I explore how resource heterogeneity within landscapes dampens population instability, using a metaphysiological modelling approach considering patch state distributions. Resource heterogeneity is functionally stabilizing through spreading consumption away from preferred resources before these become critically depleted. Lower-quality resources act as a buffer against starvation during critical periods of the seasonal cycle. Enriching resource quality is destabilizing, even if patch diversity is maintained, because food quantity then becomes the limitation. The potential consequences of landscape fragmentation are explored using the Serengeti ecosystem, characterised by broadscale resource gradients, as a hypothetical example. Further insights provided by the model are illustrated with specific examples concerning the effects of patch scales and waterpoint distribution. A metaphysiological modelling approach enables the basic consequences of landscape heterogeneity to be distinguished from further effects that may arise from specific patch scales and configurations, without the distracting detail of spatially explicit models.://000226384000005 ) ISI Document Delivery No.: 888OL Times Cited: 1 Cited Reference Count: 48 Cited References: BART J, 1995, ECOL APPL, V5, P411 BRANDNER TA, 1990, ECOLOGY, V71, P155 BROOKS PM, 1983, MANAGEMENT LARGE MAM, P51 CASWELL H, 1992, INDIVIDUAL BASED MOD, P36 CAUGHLEY G, 1976, THEORETICAL ECOLOGY, P94 CLUTTONBROCK TH, 1991, J ANIM ECOL, V60, P593 CLUTTONBROCK TH, 1997, AM NAT, V149, P196 CLUTTONBROCK TH, 2002, PHILOS T ROY SOC B, V357, P1285 CONROY MJ, 1995, ECOL APPL, V5, P17 DUNNING JB, 1995, ECOL APPL, V5, P3 ELLIS JE, 1988, J RANGE MANAGE, V41, P450 FRYXELL JM, 1988, AM NAT, V131, P781 GAYLARD A, 2003, KRUGER EXPERIENCE EC, P171 GETZ WM, 1993, EVOL ECOL, V7, P287 GETZ WM, 2001, ADV ECOLOGICAL THEOR, P194 GRENFELL BT, 1998, NATURE, V394, P674 GRIMM V, 1999, ECOL MODEL, V115, P129 HASSELL MP, 1973, J ANIM ECOL, V42, P693 HASTINGS A, 1977, THEOR POPUL BIOL, V12, P37 HATCH GP, 1997, AFRICAN J RANGE FORA, V14, P17 ILLIUS AW, 1999, ECOL APPL, V9, P798 KLEIN DR, 1968, J WILDLIFE MANAGE, V32, P350 KOLASA J, 1991, ECOLOGICAL HETEROGEN, P3 MCCULLOUGH DR, 1997, SCI OVERABUNDANCE DE, P69 MDUMA SAR, 1999, J ANIM ECOL, V68, P1101 OTTICHILO WK, 1999, AFRICAN J ECOLOGY, V38, P202 OWENSMITH N, 1988, MEGAHERBIVORES INFLU OWENSMITH N, 1989, J ZOOLOGY LONDON, V219, P2943 OWENSMITH N, 1994, ECOLOGY, V75, P1050 OWENSMITH N, 1996, S AFR J WILDL RES, V26, P107 OWENSMITH N, 1999, AFRICAN BIOGEOGRAPHY, P138 OWENSMITH N, 2002, ADAPTIVE HERBIVORE E OWENSMITH N, 2002, ECOL MODEL, V149, P153 OWENSMITH N, 2002, S AFR J SCI, V98, P445 PETERSON RO, 1999, ECOL APPL, V9, P10 REDFERN JV, 2003, ECOLOGY, V84, P2092 RITCHIE ME, 1999, NATURE, V400, P557 ROSENZWEIG ML, 1971, SCIENCE, V171, P385 SCOONES I, 1993, RANGE ECOLOGY DISEQU, P62 SHACKLETON CM, 1993, DEV SO AFRICA, V10, P65 SINCLAIR ARE, 1979, SERENGETI DYNAMICS E, P31 STEPHENS DW, 1986, FORAGING THEORY TAPER ML, 2002, J WILDLIFE MANAGE, V66, P106 TURNER MG, 1995, ECOL APPL, V5, P12 VANAARDE R, 1999, ANIM CONSERV, V2, P287 WALKER BH, 1987, J APPL ECOL, V24, P381 WILLIAMSON DT, 1988, AFR J ECOL, V26, P341 WILMSHURST JF, 2000, P ROY SOC LOND B BIO, V267, P345 0921-2973 Landsc. Ecol.ISI:000226384000005Univ Witwatersrand, Ctr African Ecol, Sch Anim Plant & Environm Sci, ZA-2050 Wits, South Africa. Owen-Smith, N, Univ Witwatersrand, Ctr African Ecol, Sch Anim Plant & Environm Sci, ZA-2050 Wits, South Africa. norman@gecko.biol.wits.ac.zaEnglish<7Owen-Smith, N.2005YFunctional heterogeneity in resources within landscapes and herbivore population dynamics317-317Landscape Ecology203fragmentation; large mammals; metaphysiological model; resource patches; Serengeti National Park; Tanzania; ungulates; waterpointsArticleApr://000231824400006 HISI Document Delivery No.: 963RU Times Cited: 0 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:000231824400006Univ Witwatersrand, Sch Anim Plant & Environm Sci, Ctr African Ecol, ZA-2050 Wits, South Africa. Owen-Smith, N, Univ Witwatersrand, Sch Anim Plant & Environm Sci, Ctr African Ecol, ZA-2050 Wits, South Africa. norman@gecko.biol.wits.ac.zaEnglish Z|?='Pagella, Timothy F. Sinclair, Fergus L.2014Development and use of a typology of mapping tools to assess their fitness for supporting management of ecosystem service provision383-399Landscape Ecology293MarThe importance of land use in affecting a range of ecosystem services (ES) provided from rural landscapes is increasingly recognised, creating an imperative for tools to assist in managing impacts of land use on ES provision. Many stakeholders, at a range of scales, are involved, including policy makers and implementers, land users and people receiving the services. Here, we develop a new and comprehensive typology of ES maps by expanding the basic stock-flow-receptor concept to create a set of map categories that embraces requirements for management of ES provision. We then use this typology as a framework for assessment of approaches to mapping ES. Most approaches have considered natural capital stocks of few services, at large scales (>1,000 km(2)) and coarse resolution (>100 m(2)). Emphasis has been on areas of ES generation, with little attention to flows, limiting the extent to which reception of services, interactions amongst services, and impacts on different stakeholders are considered. Most approaches focused on a bounded watershed or administrative unit, with little attention to landscape evolution, or to the definition of system boundaries that encompass flows from source to reception for different services. Although uncertainty is inherent in both input data and the services that are mapped, this is rarely acknowledged, quantified or presented. These features of current mapping approaches constrain their usefulness for informing the management of ES provision from rural landscapes. Key areas for future development are (1) maps at scales and resolutions that connect field scale management options to local landscape impacts; (2) mapping flows, and defining landscape boundaries, that include complete pathways, from source to reception; (3) calculating and presenting information on synergies and trade-offs amongst services; and (4) incorporating stakeholder knowledge and perspectives in the generation and interpretation of maps to bound and communicate uncertainty and improve their legitimacy.!://WOS:000331935500003Times Cited: 2 0921-2973WOS:00033193550000310.1007/s10980-013-9983-9 |?Palacios-Agundez, Igone Fernandez de Manuel, Beatriz Rodriguez-Loinaz, Gloria Pena, Lorena Ametzaga-Arregi, Ibone Alday, Josu G. Casado-Arzuaga, Izaskun Madariaga, Iosu Arana, Xabier Onaindia, Miren2014fIntegrating stakeholders' demands and scientific knowledge on ecosystem services in landscape planning 1423-1433Landscape Ecology298OctThe conflict between conservation and timber production is shifting in regions such as Biscay (Basque Country, northern Spain) where planted forests are no longer profitable without public subsidies and environmentalist claim that public subsidies should be reoriented to the regeneration of natural forest. This paper develops an approach that integrates scientific knowledge and stakeholders' demands to provide decision-making guidelines for the development of new landscape planning strategies while considering ecosystem services. First, a participatory process was conducted to develop a community vision for the region's sustainable future considering the opportunities and constrains provided by the landscape and its ecosystems. In the participatory process forest management was considered an important driver for the region`s landscape development and forest multi-functionality was envisioned as a feasible attractive alternative. The participatory process identified a knowledge gap on the synergies and trade-offs between biodiversity and carbon storage and how these depend on different forest types. Second, to study the existing synergies and trade-offs between biodiversity and carbon storage and disentangle the identified knowledge gap, a GIS-based research was conducted based on spatially explicit indicators. Our spatial analysis results showed that natural forests' contribution to biodiversity and carbon storage is higher than that of the plantations with exotic species in the region. The results from the spatial analysis converged with those from the participatory process in the suitability of promoting, where possible and appropriate, natural forest ecosystems restoration. This iterative learning and decision making process is already showing its effectiveness for decision making, with concrete examples of how the results obtained with the applied approach are being included in planning and decision-making processes.!://WOS:000342078600012Times Cited: 2 0921-2973WOS:00034207860001210.1007/s10980-014-9994-1<7vLPalang, H. Printsmann, A. Gyuro, E. K. Urbanc, M. Skowronek, E. Woloszyn, W.2006<The forgotten rural landscapes of Central and Eastern Europe347-357Landscape Ecology213Talienation; Central and Eastern Europe; diversity; landscape change HOLISTIC ASPECTSArticleAprInteractions between nature and man - the underlying forces in landscape - have over time caused diversity. Usually, geographers and landscape ecologists deal with spatial diversity; in this paper, we would like to also consider temporal diversity. We argue that Central and Eastern European landscapes (using the examples of Estonia, Hungary, Poland and Slovenia) are much more diverse in time (layers) than Western European ones. This difference requires the use of different indicators in order to measure and study landscapes and special problems, threats, and possibilities of management and future development - but most important is the consideration of different perceptions. We also show that this diversity reduces the readability of landscapes, creating miscommunication and a transformation of meanings. We further argue that the link between humans and landscape is lost in Central and Eastern European countries due to temporal diversity, and that this link will be created anew in a globalizing world. To overcome alienation, we need slightly different classifications/typologies for each country in this region, with the aim of a sound future management of cultural landscapes.://000236968500004 ISI Document Delivery No.: 034ZD Times Cited: 0 Cited Reference Count: 51 Cited References: *BELGEO, 2004, SPEC ISS EUR LANDSC *TOWN IND POL REP, 1924, LUBLIN VOIVODSHIP, V4 *TOWN IND POL REP, 1924, LVIV VOIVODSHIP, V13 ALUMAE H, 2003, LANDSCAPE INTERFACES, P124 ANTROP M, 2000, AGR ECOSYST ENVIRON, V77, P17 ANTROP M, 2000, LANDSCAPE URBAN PLAN, V50, P43 ANTROP M, 2004, LANDSCAPE URBAN PLAN, V67, P9 BASTIAN O, 2003, DEV PERSPECTIVES LAN BOURASSA SC, 1991, AESTHETICS LANDSCAPE BOURDIEU P, 1977, OUTLINE THEORY PRACT BRANCELJ IR, 1998, SLOVENIJA POKRAJINE, P234 BURACZYNSKI J, 1997, ROZTOCZE STRUCTURE R CHALUPCZAK H, 1998, NATL MINORITIES POLA CLAVAL P, 2005, LANDSCAPE URBAN PLAN, V70, P9 COSGROVE D, 2003, LANDSCAPE INTERFACES, P15 COSGROVE DE, 1984, SOCIAL FORMATION SYM CRANG M, 1998, CULTURAL GEOGRAPHY DUNCAN J, 1995, PROG HUM GEOG, V19, P414 DUNCAN JS, 1994, PROG HUM GEOG, V18, P361 ESPERSEN S, 1998, SHAPING LAND FUTURE, V3, P596 GABROVEC M, 1997, GEOGRAFSKI ZBORNIK, V37, P7 GUSTAVSSON R, 2003, LANDSCAPE INTERFACES, P319 GYURO EK, 2000, FHNPARK FOLDRAJZI IN GYURO EK, 2002, IN PRESS C P INGOLD T, 2000, PERCEPTION ENV ESSAY JONES M, 1991, NORSK GEOGRAFISK TID, V45, P153 JONES M, 2003, LANDSCAPE INTERFACES, P21 KEISTERI T, 1990, FENNIA, V168, P31 LOWENTHAL D, 1985, IS FOREIGN COUNTRY LOWENTHAL D, 1997, UNDERSTANDING ORDINA, P180 LOWENTHAL D, 1999, NORSK GEOGRAFISK TID, V53, P139 MARCUCCI DJ, 2000, LANDSCAPE URBAN PLAN, V49, P67 MASSEY D, 2001, T I BRIT GEOGR, V26, P257 MITCHELL D, 2003, PROG HUM GEOG, V27, P787 MORRIS C, 2004, J RURAL STUD, V20, P95 NAVEH Z, 1994, LANDSCAPE ECOLOGY TH OLWIG KR, 2002, LANDSCAPE NATURE BOD PALANG H, 2000, LANDSCAPE URBAN PLAN, V50, P85 PALANG H, 2002, RAHV SEM KOHT JA PAI, V2, P51 RELPH E, 1986, PLACE PLACELESSNESS SAUER CO, 1925, U CALIFORNIA PUBLICA, V2, P19 SCHAMA S, 1995, LANDSCAPE MEMORY SKOWRONEK E, 1999, THESIS UMCS LUBLIN SKOWRONEK E, 2003, LANDSCAPE INTERFACES, P71 SOINI K, 2004, RURAL LANDSCAPES PRO, P83 SOOVALI H, 2003, ADV ECOLOGICAL SCI, V19, P925 SOOVALI H, 2003, C LANDSC LAW JUST OS URBANC M, 2002, CULTURAL LANDSCAPES URBANC M, 2002, POSKUS TIPOLOGIJE KU VALK H, 1996, PALVE VANAPATT JA PI, V4 WIDGREN M, 2004, RURAL LANDSCAPES PRO, P455 0921-2973 Landsc. Ecol.ISI:000236968500004Univ Western Hungary, Sopron, Hungary. Anton Melik Geog Inst, Ljubljana, Slovenia. Marie Curie Sklodowska Univ, Lublin, Poland. Univ Tartu, Inst Geog, Tartu, Estonia. Palang, H, Tallinn Univ, Inst Ecol, Uus Sadama 5, EE-10120 Tallinn, Estonia. palang@eco.edu.eeEnglish<7<Palmer, M. A. Swan, C. M. Nelson, K. Silver, P. Alvestad, R.2000oStreambed landscapes: evidence that stream invertebrates respond to the type and spatial arrangement of patches563-576Landscape Ecology156decomposition invertebrates leaf packs patch dynamics patchiness spatial ecology streams BENTHIC INVERTEBRATES TRANSPORT PROCESSES DYNAMICS CONCEPT LEAF PACKS COMMUNITY HABITAT ECOLOGY CONNECTIVITY REFUGIA SCALESArticleAug The availability and spatial arrangement of habitat patches are known to strongly influence fauna in terrestrial ecosystems. The importance of patch arrangement is not well-studied within running-water systems where flow-induced movements of patches and of fauna could decouple habitat characteristics and faunal habitat preferences. Using small, stream-dwelling invertebrates, we asked if fauna in such systems can distinguish among patch types and if patch arrangement at their 'landscape scale' (i.e., within a streambed across which they move and forage) can be linked to faunal abundance. We quantified the spatial distribution of sand and leaf patches at multiple sites on a streambed at regular intervals over a 1 1/2 yr period, estimated faunal abundance in the two patch types, and experimentally determined if faunal colonization varied among leaf patches that were similar structurally but differed in their potential microbial food resources. We show that despite their small size and limited swimming abilities, these stream invertebrates did respond to patch type, that specific characteristics of an individual patch influenced faunal colonization, and that the spatial arrangement of patches on the streambed was linked to field abundances. Larval chironomids and adult copepods were more abundant in leaves than in sand and preferentially colonized leaf patches made with rapidly decomposing leaves that harbored higher microbial (bacteria and fungi) abundances over leaf patches with more refractory leaves and lower microbial abundances. Further, statistical models that included spatially-explicit data on patch arrangement (e.g., patch contagion, distance between patches) explained significantly more variation in faunal abundance, than models that included only nonspatial information (e.g., date, time since last flood). Despite the fact that these fauna live in a highly dynamic environment with variable flow rates during the year, unstable patch configurations, and seasonal changes in total abundance, our findings suggest a need for aquatic ecologists to test the hypothesis that small-scale landscape attributes within streams (e.g., leaf patch aggregation) may be important to faunal dynamics. If patch aggregation has negative consequences for stream biota, streambed 'landscapes' may be fundamentally different from many terrestrial landscapes due to the inherent connectivity provided by the water and the over-riding importance of patch edges. Regardless of these differences, our findings suggest that the spatial configuration of patches in a landscape may have consequences for fauna even in highly dynamic systems, in which patches move and fauna periodically experience high levels of passive dispersal.://000088037200006 ISI Document Delivery No.: 331UN Times Cited: 41 Cited Reference Count: 73 Cited References: *SAS I INC, 1989, SAS STAT US GUID VER ALLAN JD, 1995, STREAM ECOLOGY STRUC BORCHARDT MA, 1995, J N AMER BENTHOL SOC, V14, P269 BOSCH W, 1978, GEOG ANAL, V10, P241 CROWL TA, 1997, J N AM BENTHOL SOC, V16, P277 DAVIS JC, 1986, STAT DATA ANAL GEOLO DOBSON M, 1994, FRESHWATER BIOL, V32, P565 DOOLEY JL, 1998, ECOLOGY, V79, P969 DOWNES BJ, 1990, OIKOS, V59, P411 DOWNES BJ, 1993, FRESHWATER BIOL, V30, P119 EPSTEIN SS, 1995, MAR ECOL-PROG SER, V117, P289 FAHRIG L, 1985, ECOLOGY, V66, P1762 FAHRIG L, 1988, ECOLOGY, V69, P468 FAHRIG L, 1994, CONSERV BIOL, V8, P50 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FRID CLJ, 1989, OIKOS, V56, P137 GARDNER RH, 1991, QUANTITATIVE METHODS, P289 GRASSLE JP, 1992, J MAR RES, V50, P617 HAKENKAMP CH, 1997, THESIS U MARYLAND CO HALL RO, 1995, J N AMER BENTHOL SOC, V14, P269 HAMAZAKI T, 1996, LANDSCAPE ECOL, V11, P299 HANSKI I, 1995, MOSAIC LANDSCAPES EC, P203 HANSSON L, 1995, MOSAIC LANDSCAPES EC HILDREW AG, 1994, AQUATIC ECOLOGY SCAL, P21 JOHNSON AR, 1992, LANDSCAPE ECOL, V7, P63 JOHNSON LB, 1997, FRESHWATER BIOL, V37, P113 KLEINBAUM DG, 1988, APPL REGRESSION ANAL KOHLER SL, 1992, ECOL MONOGR, V62, P165 LAMPERT W, 1984, MANUAL METHODS ASSES, CH10 LANCASTER J, 1993, J N AMER BENTHOL SOC, V12, P385 LANCASTER J, 1996, CAN J FISH AQUAT SCI, V53, P572 LANCASTER J, 1997, J N AM BENTHOL SOC, V16, P221 LEFF LG, 1989, HYDROBIOLOGIA, V182, P219 LITTELL RC, 1991, SAS SYSTEM LINEAR MO MCAULIFFE JR, 1984, ECOLOGY, V65, P894 MURPHY JF, 1998, FRESHWATER BIOL, V39, P325 NEWELL SY, 1988, APPL ENVIRON MICROB, V54, P1876 OLIVER DR, 1971, A REV ENT, V16, P211 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PAHLWOSTL C, 1998, ECOLOGICAL SCALE THE, P141 PALMER MA, 1990, J N AMER BENTHOL SOC, V9, P17 PALMER MA, 1992, LIMNOL OCEANOGR, V37, P329 PALMER MA, 1996, OECOLOGIA, V105, P247 PALMER MA, 1996, TRENDS ECOL EVOL, V11, P322 PALMER TM, 1995, OECOLOGIA, V104, P476 PECKARSKY BL, 1980, ECOLOGY, V61, P1283 PERLMUTTER DG, 1991, ECOLOGY, V72, P2170 PETERSEN RC, 1974, FRESHWATER BIOL, V4, P343 POFF NL, 1991, CAN J FISH AQUAT SCI, V48, P1926 POFF NL, 1993, OECOLOGIA, V95, P202 PRINGLE CM, 1988, J N AM BENTHOL SOC, V7, P503 ROBERTSON AL, 1995, FRESHWATER BIOL, V33, P469 ROTH NE, 1996, LANDSCAPE ECOL, V11, P141 SARNELLE O, 1993, OECOLOGIA, V96, P208 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SEDELL JR, 1990, ENVIRON MANAGE, V14, P711 SHOFNER MA, 1999, THESIS U MARYLAND CO SIH A, 1994, ECOLOGY, V75, P1199 SILVER P, 2000, DENSITY INDEPENDENT SOKAL RR, 1981, BIOMETRY SOUTHWOOD TRE, 1977, J ANIM ECOL, V46, P337 STANKOMISHIC SS, 1999, IN PRESS FRESH BIOL SUBERKROPP K, 1996, APPL ENVIRON MICROB, V62, P1610 SWAN CM, 1997, THESIS U MARYLAND CO SWAN CM, 2000, IN PRESS FRESHW BIOL THOMSON JD, 1996, ECOLOGY, V77, P1698 TOWNSEND CR, 1989, J N AM BENTHOL SOC, V8, P36 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 WARD AK, 1996, METHODS STREAM ECOLO, P233 WEBSTER JR, 1986, ANNU REV ECOL SYST, V17, P567 WIENS JA, 1993, OIKOS, V66, P369 WITH KA, 1997, OIKOS, V78, P151 WU JG, 1995, Q REV BIOL, V70, P439 0921-2973 Landsc. Ecol.ISI:000088037200006sUniv Maryland, Dept Biol, College Pk, MD 20742 USA. Palmer, MA, Univ Maryland, Dept Biol, College Pk, MD 20742 USA.English<7;Palmer, S. C. F. Gordon, I. J. Hester, A. J. Pakeman, R. J.2004WIntroducing spatial grazing impacts into the prediction of moorland vegetation dynamics817-827Landscape Ecology198Calluna vulgaris; sheep; simulation model; spatial heterogeneity; ungulates; utilisation DEER CERVUS-ELAPHUS; VULGARIS L. HULL; RED DEER; NORTHEAST SCOTLAND; HEATHER MOORLAND; ECOLOGICAL KNOWLEDGE; LARGE HERBIVORES; HILL VEGETATION; GREAT-BRITAIN; SHEEPArticleGrazing by large herbivores is a major determinant of vegetation dynamics in many semi-natural ecosystems, including the replacement of heather moorland by rough grassland in the British uplands. Herbivore foraging is influenced by vegetation patterns and, in turn, their grazing drives vegetation dynamics. Although vegetation impacts are local, spatially heterogeneous local impacts can have different consequences as would the same impacts distributed uniformly. We constructed a simulation model of the spatial effects of grazing by sheep on the vegetation dynamics of heather moorland, a vegetation community of international conservation importance in the UK. The model comprised three sub-models to predict (1) annual average heather utilisation, (2) spatial variation in heather utilisation (higher near the edge of grass patches) and (3) competition between heather and grass. Here we compare the predicted heather utilisation and vegetation dynamics of the spatial model, relative to those of a non-spatial model. The spatial model resulted in a reduced loss of heather cover for a given sheep stocking rate. The model demonstrates how spatial interactions between large herbivores and their forage drive vegetation dynamics, leading to changes in community structure and composition. Indeed, omitting spatial effects in grazing models may lead to inaccurate predictions. We have shown that ecosystem modelling, based around an iterative dialogue between developers and experienced researchers, has the potential to make a substantial contribution towards the conservation and management of vulnerable landscapes. Combining modelling with experimental studies will facilitate progress towards understanding long-term vegetation/herbivore dynamics.://000226268600001 ISI Document Delivery No.: 886YI Times Cited: 1 Cited Reference Count: 47 Cited References: ALONSO I, 2001, J VEG SCI, V12, P249 ANDREW MH, 1988, TRENDS ECOL EVOL, V3, P336 ARMSTRONG HM, 1997, J APPL ECOL, V34, P166 ARMSTRONG HM, 1997, J APPL ECOL, V34, P186 ARMSTRONG HM, 2000, CAN J ZOOL, V78, P1604 BUCHANAN GM, 2003, BIRD STUDY 2, V50, P97 CHARLES WN, 1977, J APPL ECOL, V14, P55 CLARK RF, 1995, PEDIATR EMERG CARE, V11, P32 CLARKE JL, 1995, J APPL ECOL, V32, P166 COUGHENOUR MB, 1991, J RANGE MANAGE, V44, P530 CUARTAS P, 2000, ACTA THERIOL, V45, P309 DENNIS P, 2001, AGR ECOSYST ENVIRON, V86, P39 FRASER MD, 1997, J APPL ECOL, V34, P668 GARDNER SM, 1997, BIOL CONSERV, V81, P275 GIMINGHAM CH, 1949, J ECOL, V37, P100 GORDON IJ, 1989, J APPL ECOL, V26, P53 GRANT SA, 1971, J BRIT GRASSLAND SOC, V26, P51 GRANT SA, 1978, J BRIT GRASSLAND SOC, V33, P289 GRANT SA, 1982, GRASS FORAGE SCI, V37, P311 HARTLEY SE, 1999, J ECOL, V87, P330 HESTER AJ, 1996, J ZOOL 4, V240, P609 HESTER AJ, 1998, J APPL ECOL, V35, P772 HOBBS NT, 2003, FOREST ECOL MANAG, V181, P223 HOLT RD, 1995, ECOL APPL, V5, P20 HUNTER RF, 1962, J ECOL, V50, P561 ILLIUS AW, 1987, J ANIM ECOL, V56, P989 JEPPESEN JL, 1987, DANISH REV GAME BIOL, V13 MCVEAN DN, 1962, PLANT COMMUNITIES SC OSBORNE BC, 1984, J APPL ECOL, V21, P497 PAKEMAN RJ, 2003, BIOL CONSERV, V114, P389 PALMER SCF, 1997, GRASS FORAGE SCI, V52, P408 PALMER SCF, 2000, J APPL ECOL, V37, P616 PALMER SCF, 2003, ECOLOGY, V84, P2877 PEARCEHIGGINS JW, 2002, ASPECTS APPL BIOL, V67, P155 PICKUP G, 1994, J APPL ECOL, V31, P231 RASTETTER EB, 1992, ECOL APPL, V2, P55 RATCLIFFE DA, 1988, ECOLOGICAL CHANGE UP, P3 READ JM, 2002, BIOL CONSERV, V105, P279 STAINES BW, 1976, J ZOOL LOND, V180, P1 STAINES BW, 1994, SCOTTISH NATURAL HER, V31 THOMPSON DBA, 1995, BIOL CONSERV, V71, P163 WATT AS, 1955, J ECOL, V43, P490 WELCH D, 1984, J APPL ECOL, V21, P179 WELCH D, 1984, J APPL ECOL, V21, P197 WELCH D, 1984, J APPL ECOL, V21, P209 WELCH D, 1995, J APPL ECOL, V32, P596 WHITE CA, 2003, FOREST ECOL MANAG, V181, P77 0921-2973 Landsc. Ecol.ISI:000226268600001Ctr Ecol & Hydrol, Banchory Res Stn, Banchory AB31 4BW, Aberdeen, Scotland. Macaulay Land Use Res Inst, Aberdeen AB15 8QH, Scotland. Palmer, SCF, Ctr Ecol & Hydrol, Banchory Res Stn, Hill Brathens, Banchory AB31 4BW, Aberdeen, Scotland. scfp@ceh.ac.ukEnglish <7;Palmer, S. C. F. Gordon, I. J. Hester, A. J. Pakeman, R. J.2005WIntroducing spatial grazing impacts into the prediction of moorland vegetation dynamics335-335Landscape Ecology203XCalluna vulgaris; sheep; simulation model; spatial heterogeneity; ungulates; utilisationArticleAprGrazing by large herbivores is a major determinant of vegetation dynamics in many semi-natural ecosystems, including the replacement of heather moorland by rough grassland in the British uplands. Herbivore foraging is influenced by vegetation patterns and, in turn, their grazing drives vegetation dynamics. Although vegetation impacts are local, spatially heterogeneous local impacts can have different consequences as would the same impact distributed uniformly. We constructed a simulation model of the spatial effects of grazing by sheep on the vegetation dynamics of heather moorland, a vegetation community of international conservation importance in the UK. The model comprised three sub-models to predict (1) annual average heather utilisation, (2) spatial variation in heather utilisation (higher near the edge of grass patches) and (3) competition between heather and grass. Here we compare the predicted heather utilisation and vegetation dynamics of the spatial model, relative to those of a non-spatial model. The spatial model resulted in a reduced loss of heather cover for a given sheep stocking rate. The model demonstrates how spatial interactions between large herbivores and their forage drive vegetation dynamics, leading to changes in community structure and composition. Indeed, omitting spatial effects in grazing models may lead to inaccurate predictions. We have shown that ecosystem modelling, based around an iterative dialogue between developers and experienced researchers, has the potential to make a substantial contribution towards the conservation and management of vulnerable landscapes. Combining modelling with experimental studies will facilitate progress towards understanding long-term vegetation/herbivore dynamics.://000231824400008 HISI Document Delivery No.: 963RU Times Cited: 0 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:000231824400008Ctr Ecol & Hydrol, Banchory Res Stn, Banchory AB31 4BW, Kincardine, Scotland. Macaulay Inst, Aberdeen AB15 8QH, Scotland. Palmer, SCF, Ctr Ecol & Hydrol, Banchory Res Stn, Hill Brathens, Banchory AB31 4BW, Kincardine, Scotland. scfp@ceh.ac.ukEnglish<7*Pan, D. Domon, G. Marceau, D. Bouchard, A.2001Spatial pattern of coniferous and deciduous forest patches in an Eastern North America agricultural landscape: the influence of land use and physical attributes99-110Landscape Ecology162 agricultural landscape Canada forest patch geographical information system land use physical attributes Quebec remote sensing spatial pattern HAUT-SAINT-LAURENT THUJA-OCCIDENTALIS SOUTHERN QUEBEC NOTARY DEEDS WHITE CEDAR DYNAMICS SUCCESSION VEGETATION HABITAT HISTORYArticleFebIn agricultural landscapes, most studies have investigated the influence of the spatial pattern of forest patches on other ecological phenomena and processes, such as animal movement and biodiversity. However, few have focused on explaining the spatial pattern of the forest patches themselves. Understanding how these patterns relate to the processes that generate them is fundamental in developing a sound theory of landscape ecology, and in devising rational management strategies. In this paper, the pattern of the overall forest patches, as well as the pattern of deciduous and coniferous patches in an agricultural landscape of Southern Quebec, Canada, were analyzed and related to landscape physical attributes and land use, using remote sensing, geographic information systems and statistical methods. Results show that the role of landscape physical attributes on forest patch pattern has been modified by land use. In the study area, coniferous or deciduous patches are not associated with a specific surface deposit. In addition, physical attributes explain only a small proportion of the abundance of conifers on past abandoned land compared with land-use factors. Physical attributes only indirectly influence the forest pattern because they strongly influence the land-use practices. Our results reveal a conifer recovery process with the abandonment of agricultural land. On past abandoned land, conifers expand with increasing stand age, mostly by invasion from neighboring coniferous patches. Spatially, coniferous patches are usually located on the margins of the overall forest patches, and they are connected to non-forest land-use types such as crop and pasture, the latter being the most important. By showing the importance of some coniferous forest types that did not exist in the precolonial forest, a new perspective emerges when landscape, especially, land-use dynamics are taken into account.://000167936500002 V ISI Document Delivery No.: 419EN Times Cited: 10 Cited Reference Count: 57 Cited References: 1982, NORMALES CLIMATIQUES *SAS I INC, 1988, SAS STAT US GUID REL *US CERL, 1991, GEOGR RES AN SUPP SY BARITEAU L, 1988, THESIS U MONTREAL MO BLANCHET B, 1982, CEDRIERES QUEBEC ETU BOLGER DT, 1991, AM NAT, V137, P155 BORMANN FH, 1979, PATTERN PROCESS FORE BOUCHARD A, 1985, CAH GEOGR QUE, V29, P79 BOUCHARD A, 1989, CAN J FOREST RES, V19, P1146 BOUCHARD A, 1997, LANDSCAPE URBAN PLAN, V37, P99 BRISSON J, 1988, CAN J BOT, V66, P1192 BURGESS RL, 1981, FOREST ISLAND DYNAMI CURTIS JD, 1944, J FOREST, V42, P756 CURTIS JD, 1946, ECOLOGY, V27, P23 CURTIS JT, 1956, MANS ROLE CHANGING F, P721 DANSEREAU P, 1946, CONTR I BOT U MONTRE, V60 DANSEREAU P, 1959, CONTR I BOT U MONTRE, V75 DEBLOIS S, 1995, J VEG SCI, V6, P531 DOMON G, 1989, THESIS U MONTREAL MO FOSTER DR, 1992, J ECOL, V80, P753 FOSTER DR, 1993, HUMANS COMPONENTS EC, P91 FOWELLS HA, 1965, USDA AGR HDB, V271 GLOBENSKY Y, 1981, 198 GOUV QUEB MIN EN GRANDTNER MM, 1966, VEGETATION FORESTIER GRIGAL DF, 1975, ECOL MONOGR, V45, P389 HARRIS LD, 1984, FRAGMENTED FOREST IS HERMY M, 1994, NATO ASI SER, V20, P123 JOHNSTON WF, 1990, SILVICS N AM, V1, P580 KEEVER C, 1983, AM MIDL NAT, V110, P397 KOERNER W, 1997, J ECOL, V85, P351 KRUMMEL JR, 1987, OIKOS, V48, P321 LAMY S, 1999, CAN J FOREST RES, V29, P1383 LEDUC A, 1992, J VEG SCI, V3, P69 LOVEJOY S, 1982, SCIENCE, V216, P185 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MCINTYRE NE, 1995, LANDSCAPE ECOL, V10, P85 MEILLEUR A, 1994, VEGETATIO, V111, P173 OOSTING HJ, 1942, AM MIDL NAT, V28, P1 PAN DY, 1999, LANDSCAPE ECOL, V14, P35 PASTOR J, 1990, LANDSCAPE ECOL, V4, P55 PETERKEN GF, 1993, STUDIES HIST ECOLOGY, P31 PETERSON CJ, 1995, J ECOL, V83, P449 PICKETT STA, 1985, ECOLOGY NATURAL DIST RANNEY JW, 1981, FOREST ISLAND DYNAMI, P67 ROWE JS, 1972, ENV CANADA PUBL F, V1300 SAUCIER I, 1986, THESIS U MONTREAL MO SCOTT ML, 1987, AM MIDL NAT, V117, P10 SELLAR R, 1988, HIST HUNTINGDON SEIG SHARPE DM, 1987, LANDSCAPE HETEROGENE, P137 SIMARD H, 1996, CAN J FOREST RES, V26, P1670 VANAPELDOORN RC, 1994, LANDSCAPE ECOL, V9, P227 VANDORP D, 1987, LANDSCAPE ECOLOGY, V1, P59 WENDEL GW, 1990, SILVICS N AM, V1, P476 WHITE MA, 1994, LANDSCAPE ECOL, V9, P191 WHITNEY GG, 1987, J ECOL, V75, P667 WILSON CV, 1971, CLIMAT QUEBEC ATLAS WILSON RW, 1965, USDA AGR HDB, V271, P329 0921-2973 Landsc. Ecol.ISI:000167936500002Univ Montreal, Inst Rech Biol Vegetale, Montreal, PQ H1X 2B2, Canada. Pan, D, Univ Montreal, Inst Rech Biol Vegetale, 4101 Est,Rue Sherbrooke, Montreal, PQ H1X 2B2, Canada.English<7p.Pan, D. Y. Domon, G. de Blois, S. Bouchard, A.1999Temporal (1958-1993) and spatial patterns of land use changes in Haut-Saint-Laurent (Quebec, Canada) and their relation to landscape physical attributes35-52Landscape Ecology141/canonical correspondence analysis geographical information system geomorphological deposit landscape index land use change patch and field scale physical attribute Quebec AGRICULTURAL LANDSCAPE INFORMATION-SYSTEM SOUTHERN QUEBEC NOTARY DEEDS 19TH-CENTURY DYNAMICS TRANSFORMATION HARDWOODS FORESTS GROWTHArticleFebIn the last few years, landscape researchers have sought to understand temporal and spatial patterns of landscape changes in order to develop comprehensive models of land cover dynamics. To do so, most studies have used similar methods to quantify structural patterns, usually by comparing various landscape structural indices through time. Whereas the necessity for complementary approaches which might provide insights into landscape dynamics at some finer scale relevant to local managers has been expressed, few studies have proposed alternative methodologies. Moreover, the important relationship between the physical constraints of the landscape and land use dynamics has been seldom emphasized. Here we propose a methodological outline which was applied to the study of a rural landscape of Southern Quebec, Canada, to detect spatial and temporal ( 1958 to 1993) patterns of land cover changes at field, patch and landscape level. We then relate these patterns to the underlying physical structure of landscape elements using GIS and canonical correspondence analyses. We use the different geomorphological deposit types as stable discriminant factors which may constrain land use. Canonical correspondence analyses showed relations of land use and land use changes to the physical attributes of the landscape elements, whereas spatial analyses revealed very dynamic patterns at finer spatial and temporal scales. They highlighted the fact that not only the physical attributes of the landscape elements but also their spatial configuration were important determinants of land use dynamics in this area. Thus more land use changes occurred at the boundary between geomorphological deposit types than in ally other locations. This trend is apparent for specific small-size changes (e.g. forest to crop), but not for the large-size ones (e.g. abandoned land to forest). Although land use changes are triggered by socioeconomic forces in this area, these changes are nevertheless constrained by the underlying physical landscape structure. A thorough comprehension of historical changes will enhance our capability to predict future landscape dynamics and devise more effective landscape management strategies.://000079005100003 ISI Document Delivery No.: 173XM Times Cited: 46 Cited Reference Count: 58 Cited References: *BUR STAT QUEB, 1986, STAT AGR PECH AL *EC WORK GROUP, 1989, EC LAND CLASS SER, V23 *INTERA TYDAC, 1991, SPANS SPAT AN SYST R *SAS I, 1988, SAS US GUID *STAT CAN, 1971, 96805 STAT CAN BUR F *STAT CAN, 1986, 96107 STAT CAN BUR F *US CERL, 1991, GEOGR RES AN SUPP SY BARITEAU L, 1988, THESIS U MONTREAL BAUDRY J, 1988, CONNECTIVITY LANDSCA BAUDRY J, 1993, LANDSCAPE ECOLOGY AG, P21 BOUCHARD A, 1985, CAH GEOGR QUE, V29, P79 BOUCHARD A, 1989, CAN J FOREST RES, V19, P1146 BOUCHARD A, 1997, LANDSCAPE URBAN PLAN, V37, P99 BOUDREAU C, 1997, TERRITOIRE ATLAS HIS BRUAN EL, 1950, DECIDUOUS FORESTS E BURROUGH PA, 1986, PRINCIPLES GEOGRAPHI CHENCHIK A, 1995, CLONTECHNIQUES, V10, P5 CHRISMAN NR, 1989, ACCURACY SPATIAL DAT, P21 COGLIASTRO A, 1993, CAN J FOREST RES, V23, P199 COGLIASTRO A, 1997, FOREST ECOL MANAG, V96, P49 DEBLOIS S, 1995, J VEG SCI, V6, P531 DOMON G, 1990, THESIS U MONTREAL DOMON G, 1993, LANDSCAPE URBAN PLAN, V25, P53 DUNN CP, 1991, QUANTITATIVE METHODS, P173 FAHRIG L, 1985, ECOLOGY, V66, P1762 FORMAN RTT, 1984, ENVIRON MANAGE, V8, P495 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FOSTER DR, 1992, J ECOL, V80, P753 GLOBENSKY Y, 1981, 198 GOV QUEB MIN EN HANSEN AJ, 1992, LANDSCAPE BOUNDARIES HULSHOFF RM, 1995, LANDSCAPE ECOL, V10, P101 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 JACOBS J, 1974, OECOLOGIA, V14, P413 JEAN M, 1991, ENVIRON MANAGE, V15, P241 JENKINS SH, 1979, OECOLOGIA BERL, V44, P112 JOHNSTON CA, 1989, PHOTOGRAMM ENG REM S, V55, P1643 KIENAST F, 1993, LANDSCAPE ECOL, V8, P103 MAILLOUX A, 1954, ETUDE PEDOLOGIQUE SO MEDLEY KE, 1995, LANDSCAPE ECOL, V10, P161 MEILLEUR A, 1994, VEGETATIO, V111, P173 MERRIAM G, 1988, TRENDS ECOL EVOL, V3, P16 MORISSET M, 1987, AGR FAMILIALE QUEBEC MURCIA C, 1995, TRENDS ECOL EVOL, V10, P58 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PAQUETTE S, 1997, LANDSCAPE URBAN PLAN, V37, P197 PASTOR J, 1990, LANDSCAPE ECOL, V4, P55 ROY L, 1998, UNPUB INFLUENCE PHYS SEGUIN N, 1980, AGR COLONISATION QUE SIMARD H, 1996, CAN J FOREST RES, V26, P1670 SIMPSON JW, 1994, LANDSCAPE ECOL, V9, P261 SPARKS TH, 1996, AGR ECOSYST ENVIRON, V60, P1 TERBRAAK CJF, 1987, CANOCO FORTRAN PROGR TERBRAAK CJF, 1988, ADV ECOL RES, V18, P271 TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 TURNER MG, 1996, ECOL APPL, V6, P1150 WIENS JA, 1995, MOSAIC LANDSCAPES EC, P1 ZONNEVELD IS, 1995, LAND ECOLOGY 0921-2973 Landsc. Ecol.ISI:000079005100003Univ Montreal, Fac Amenagement, Montreal, PQ H3C 3J7, Canada. Domon, G, Univ Montreal, Fac Amenagement, CP 6128,Succursale Ctr Ville, Montreal, PQ H3C 3J7, Canada.English<7_Pannell, J. R. Dorken, M. E.2006Colonisation as a common denominator in plant metapopulations and range expansions: effects on genetic diversity and sexual systems837-848Landscape Ecology216androdioecy; Baker's Law; colonisation; dioecy; F-ST; genetic diversity; metapopulation dynamics; monoecy; population subdivision; range expansion; self-compatibility; tristyly EICHHORNIA-PANICULATA PONTEDERIACEAE; SAGITTARIA-LATIFOLIA ALISMATACEAE; DECODON-VERTICILLATUS LYTHRACEAE; RECURRENT LOCAL EXTINCTION; SILENE-VULGARIS; POPULATION BOTTLENECKS; ISLAND POPULATIONS; SELF-FERTILIZATION; EVOLUTION; DIFFERENTIATIONArticleAugColonisation plays a central role in both the initial occupancy of a region through range expansions as well as in metapopulations, where local extinctions are balanced by re-colonisations. In this paper, we review the effects that colonisation is expected to have on patterns of genetic variation within a species, and we draw attention to the possibility of interpreting these patterns as signatures of colonisation in the past. We briefly review theoretical predictions for the effect of colonisation on both neutral genetic diversity and on variation at genetic loci that regulate the sexual system of plant populations. The sexual system represents a particularly important trait in this context because it is affected by both selection during colonisation, and because it influences gene flow amongst populations. Finally, we introduce four case studies of plant species that show variation in their sexual systems that is consistent with theoretical predictions.://000239484200005 ISI Document Delivery No.: 069YA Times Cited: 3 Cited Reference Count: 75 Cited References: AUSTERLITZ F, 1997, THEOR POPUL BIOL, V51, P148 AUSTERLITZ F, 2000, GENETICS, V154, P1309 AVISE JC, 2000, PHYLOGEOGRAPHY HIST BAKER HG, 1953, S SOC EXP BIOL, V7, P114 BAKER HG, 1955, EVOLUTION, V9, P347 BARRETT SCH, 1985, BIOL J LINN SOC, V25, P41 BARRETT SCH, 1989, EVOLUTION, V43, P1398 BARRETT SCH, 1999, MOL SYSTEMATICS PLAN, P74 BARRETT SCH, 2002, NAT REV GENET, V3, P274 BROWN AHD, 1979, THEOR POPUL BIOL, V15, P1 BULLOCK JM, 2002, DISPERSAL ECOLOGY CHARLESWORTH B, 1997, GENET RES, V70, P155 CHARLESWORTH B, 2003, ANNU REV ECOL EVOL S, V34, P99 CHARLESWORTH D, 2001, INTEGRATING ECOLOGY, P73 CHARLESWORTH D, 2003, PHILOS T ROY SOC B, V358, P1051 CRUZAN MB, 2000, TRENDS ECOL EVOL, V15, P491 DORKEN ME, 2001, J ECOL, V89, P339 DORKEN ME, 2002, EVOLUTION, V56, P31 DORKEN ME, 2003, EVOLUTION, V57, P1973 DORKEN ME, 2004, MOL ECOL, V13, P2699 DURAND B, 1963, ANN SCI NATURELLES B, V12, P579 ECKERT CG, 1999, EVOLUTION, V53, P1079 FLANAGAN NS, 2004, P NATL ACAD SCI USA, V101, P9704 FRECKLETON RP, 2002, J ECOL, V90, P419 GAGGIOTTI OE, 2004, MOL ECOL, V13, P811 GLOVER DE, 1987, HEREDITY, V59, P7 GOLDSTEIN DB, 1999, MICROSATELLITES EVOL HAMILTON WD, 1967, SCIENCE, V156, P477 HAMRICK JL, 1996, PHILOS T ROY SOC B, V351, P1291 HARTL DL, 1997, PRINCIPLES POPULATIO HEWITT G, 2000, NATURE, V405, P907 HOLDEREGGER R, 2006, LANDSCAPE ECOL, V21, P797 HUSBAND BC, 1991, HEREDITY, V66, P287 HUSBAND BC, 1995, HEREDITY 6, V75, P549 IVES AR, 2002, SCIENCE, V295, P454 LECORRE V, 1998, J EVOLUTION BIOL, V11, P495 LUIKART G, 1998, J HERED, V89, P238 LUIKART G, 1998, MOL ECOL, V7, P963 MANEL S, 2003, TRENDS ECOL EVOL, V18, P189 MCCAULEY DE, 2003, MOL ECOL, V12, P3227 NEI M, 1987, MOL EVOLUTIONARY GEN NORDBORG M, 2001, HDB STAT GENETICS, P179 OLIVIERI I, 1997, METAPOPULATION BIOL, P293 OLMSTEAD RG, 1994, AM J BOT, V81, P1205 OLSON MS, 2002, EVOLUTION, V56, P253 OUBORG NJ, 2004, ECOLOGY GENETICS EVO, P447 PANNELL J, 1997, EVOLUTION, V51, P10 PANNELL JR, 1998, EVOLUTION, V52, P657 PANNELL JR, 1999, EVOLUTION, V53, P664 PANNELL JR, 2000, PHILOS T ROY SOC B, V355, P1851 PANNELL JR, 2001, EVOL ECOL, V14, P195 PANNELL JR, 2003, EVOLUTION, V57, P949 PANNELL JR, 2003, J ECOL, V91, P485 PANNELL JR, 2004, BIOL J LINN SOC, V82, P547 PETIT RJ, 2003, SCIENCE, V300, P1563 POLLAK E, 1987, GENETICS, V117, P353 PONS O, 1996, GENETICS, V144, P1237 PROVAN J, 2001, TRENDS ECOL EVOL, V16, P142 RONCE O, 2004, METAPOPULATION BIOL, P227 SALTONSTALL K, 2003, MOL ECOL, V12, P1689 SCHAAL BA, 1998, MOL ECOL, V7, P465 SCHAAL BA, 2003, J HERED, V94, P197 SLATKIN M, 1977, THEOR POPUL BIOL, V12, P253 SMITH JM, 1974, GENET RES, V23, P23 STEBBINS GL, 1950, VARIATION EVOLUTION STEBBINS GL, 1957, AM NAT, V91, P337 STEHLIK I, 2002, AM J BOT, V89, P2007 TAYLOR DR, 1999, EVOLUTION, V53, P745 WADE MJ, 1988, EVOLUTION, V42, P995 WAKELEY J, 2001, GENETICS, V159, P893 WAKELEY J, 2004, METAPOPULATION BIOL, P175 WHITLOCK MC, 1990, EVOLUTION, V44, P1717 WHITLOCK MC, 1997, GENETICS, V146, P427 WHITLOCK MC, 1999, HEREDITY 2, V82, P117 WOOTEN JW, 1971, EVOLUTION, V25, P549 0921-2973 Landsc. Ecol.ISI:000239484200005Univ Oxford, Dept Plant Sci, Oxford OX1 3RB, England. Pannell, JR, Univ Oxford, Dept Plant Sci, S Parks Rd, Oxford OX1 3RB, England. john.pannell@plants.ox.ac.ukEnglishLڽ7 ?Panzacchi, Manuela Van Moorter, Bram Jordhøy, Per Strand, Olav2013Learning from the past to predict the future: using archaeological findings and GPS data to quantify reindeer sensitivity to anthropogenic disturbance in Norway847-859Landscape Ecology285Springer NetherlandsLandscape connectivity Historic ecology Anthropogenic disturbance Migration corridors Infrastructures Roads Dams Cabins Power lines Cumulative effects 2013/05/01+http://dx.doi.org/10.1007/s10980-012-9793-5 0921-2973Landscape Ecol10.1007/s10980-012-9793-5EnglishP|? 4Parisien, M. A. Miller, C. Ager, A. A. Finney, M. A.2010DUse of artificial landscapes to isolate controls on burn probability79-93Landscape Ecology251%Techniques for modeling burn probability (BP) combine the stochastic components of fire regimes (ignitions and weather) with sophisticated fire growth algorithms to produce high-resolution spatial estimates of the relative likelihood of burning. Despite the numerous investigations of fire patterns from either observed or simulated sources, the specific influence of environmental factors on BP patterns is not well understood. This study examined the relative effects of ignitions, fuels, and weather on mean BP and spatial patterns in BP (i.e., BP variability) using highly simplified artificial landscapes and wildfire simulation methods. Our results showed that a limited set of inputs yielded a wide range of responses in the mean and spatial patterning of BP. The input factors contributed unequally to mean BP and to BP variability: so-called top-down controls (weather) primarily influenced mean BP, whereas bottom-up influences (ignitions and fuels) were mainly responsible for the spatial patterns of BP. However, confounding effects and interactions among factors suggest that fully separating top-down and bottom-up controls may be impossible. Furthermore, interactions among input variables produced unanticipated but explainable BP patterns, hinting at complex topological dependencies among the main determinants of fire spread and the resulting BP. The results will improve our understanding of the spatial ecology of fire regimes and help in the interpretation of patterns of fire likelihood on real landscapes as part of future wildfire risk assessments.!://WOS:000273479100007Times Cited: 0 0921-2973WOS:00027347910000710.1007/s10980-009-9398-9|?( >Paritsis, Juan Veblen, Thomas T. Smith, Jeremy M. Holz, Andres2011[Spatial prediction of caterpillar (Ormiscodes) defoliation in Patagonian Nothofagus forests791-803Landscape Ecology266JulIn the temperate forests of the southern Andes, southern beech species (Nothofagus), the dominant tree species of the region, experience severe defoliation caused by caterpillars of the Ormiscodes genus (Lepidoptera: Saturniidae). Despite the recent increase in defoliation frequency in some areas, there is no quantitative information on the spatial extent and dynamics of these outbreaks. This study examines the spatial patterns of O. amphimone outbreaks in relation to landscape heterogeneity. We mapped defoliation events caused by O. amphimone in northern (ca. 40-41 degrees S) and southern Patagonian (ca. 49 degrees S) Nothofagus forests from Landsat imagery and analyzed their spatial associations with vegetation cover type, topography (elevation, slope angle, aspect) and mean annual precipitation using overlay analyses. We used these data and relationships to develop a logistic regression model in order to generate maps of predicted susceptibility to defoliation by O. amphimone for each study area. Forests of N. pumilio are typically more susceptible to O. amphimone outbreaks than lower elevation forests of other Nothofagus species (N. dombeyi and N. antarctica). Stands located at intermediate elevations and on gentle slopes (<15 degrees) are also more susceptible to defoliation than higher and lower elevation stands located on high angle slopes. Stands in areas with intermediate to high precipitation, relative to the distribution of Nothofagus along the precipitation gradient, are more susceptible to O. amphimone attack than are drier areas. Our study represents the first mapping and spatial analysis of insect defoliator outbreaks in Nothofagus forests in South America.!://WOS:000291485400003Times Cited: 0 0921-2973WOS:00029148540000310.1007/s10980-011-9608-0<7aPartel, M. Mandla, R. Zobel, M.1999sLandscape history of a calcareous (alvar) grassland in Hanila, western Estonia, during the last three hundred years187-196Landscape Ecology142calcareous grassland community management GIS landscape history SPECIES RICHNESS PLANT-COMMUNITIES SEED BANK VEGETATION SUCCESSION DYNAMICS LAND EXTINCTION PATTERNS CANADAArticleApriThe landscape history of the largest calcareous seminatural alvar site (ca. 700 ha) in Estonia, is described with the help of a historical map from 1705 and aerial photographs from 1951, and recent vegetation mapping from 1991-1996. The seminatural, species rich alvar grasslands originate and are maintained by grazing of domestic animals. Three hundred years ago the area was mainly open grassland with sparse shrubs and some fields. Forty years ago the vegetation pattern was similar, with some smaller forests and forest clear-cut areas present. Now, since grazing has ceased for ca. 40 years, only 30% of the area remains as open grassland and 70% as forest. Identification of clusters of field layer vegetation using the program TABORD resulted in 8 clusters, which agreed with the empirically determined community types. The field layer within the young pine forest (up to 20 year old pines) is similar to the open alvar grassland. In older forests, the field layer has already changed. There were no phytosociological differences found between ancient grasslands and grasslands on former arable fields or forest clear-cut areas. Decrease in species richness, compared to open grassland. was most drastic in forests of age 20-40 years where the canopy was most closed. Forests have spread more extensively in areas with deeper soil. The continuation of traditional management (grazing and tree cutting) in alvar grasslands is urgently needed in order to keep seminatural alvar grasslands open. The possibility to restore open grasslands remains as long as there is a pool of grassland species available, especially in younger forests.://000079802500008 ISI Document Delivery No.: 187RV Times Cited: 24 Cited Reference Count: 64 Cited References: AAVIKSOO K, 1993, LANDSCAPE ECOL, V8, P287 ALEKSANDROVA VD, 1964, FIELD GEOBOTANY, V3, P300 AUG H, 1983, EESTI NSV LOODUSLIKE BAKKER JP, 1989, NATURE MANAGEMENT GR BAKKER JP, 1996, J VEG SCI, V7, P165 BELCHER JW, 1992, CAN J BOT, V70, P1279 BENGTSSONLINDSJ.S, 1991, ECOL B, V41, P388 BERGLUND BE, 1991, ECOLOGICAL B, V41, P1 BOBBINK R, 1987, BIOL CONSERV, V40, P301 BURRICHTER V, 1993, PHYTOCOENOLOGIA, V23, P427 CATLING PM, 1995, CAN FIELD NAT, V109, P143 EASTMAN JR, 1993, IDRISI UPDATE MANUAL EILART J, 1963, SCRIPTA BOT, V3, P1 EJRNAES R, 1995, J ENVIRON MANAGE, V41, P171 ERIKSSON A, 1995, ECOGRAPHY, V18, P310 FOSTER DR, 1988, J ECOL, V76, P105 GIBSON CWD, 1987, BIOL CONSERV, V42, P165 GIBSON CWD, 1991, BIOL CONSERV, V58, P297 GIBSON CWD, 1991, J VEG SCI, V2, P291 GIBSON CWD, 1992, J APPL ECOL, V29, P120 GLENNLEWIN DC, 1992, PLANT SUCCESSION THE, P11 HAEGGSTROM CA, 1983, ACTA BOT FENN, V120, P1 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 JACKEL AK, 1994, BER I LANDSCHAFTS PF, V3, P123 JONES JR, 1993, TOSCA REFERENCE GUID KAHK J, 1992, EESTI TALURAHVA AJAL KALAMEES R, 1997, FOLIA GEOBOT PHYTOTX, V32, P1 KIENAST F, 1993, LANDSCAPE ECOL, V8, P103 KNAPP R, 1974, HDB VEGETATION SCI, V8, P43 KRAHULEC F, 1986, NORD J BOT, V6, P797 KRALL H, 1980, EESTI NSV LOODUSLIKE KUCHLER AW, 1967, VEGETATION MAPPING KUKK U, 1995, EESTI LOODUS, V4, P112 KULL K, 1991, J VEG SCI, V2, P711 LAASIMER L, 1965, EESTI NSV TAIMKATE LAASIMER L, 1973, EESTI LOODUS, V11, P683 LOHMUS E, 1984, EESTI METSAKASVUKOHA LOUGAS V, 1975, T ESTONIAN ACAD SCI, V1, P85 MANDEL M, 1975, T ESTON ACAD SCI, V1, P74 MANDEL M, 1982, T ESTON ACAD SCI, V4, P381 MASLOV AA, 1990, SPATIAL PROCESSES PL, P83 OOMES JMJ, 1990, J VEG SCI, V1, P333 OUBORG NJ, 1993, OIKOS, V66, P298 PARTEL M, 1995, ECOGRAPHY, V18, P83 PARTEL M, 1996, OIKOS, V75, P111 PEET RK, 1990, B ECOL SOC AM, V71, P283 REINTAM L, 1995, SOIL FERTILIZATION, P122 REJMANEK M, 1988, ACTA PHYTOGEOGR SUEC, V76, P67 ROOMUSOKS A, 1983, EESTI ALUSPOHJA GEOL ROSEN E, 1982, ACTA PHYTOGEOGR SUEC, V72, P1 SCHAEFER CA, 1997, J VEG SCI, V8, P797 VALLNER L, 1988, J GEODYN, V9, P215 VANDERMAAREL E, 1978, VEGETATIO, V38, P143 VANDERMAAREL E, 1988, ACTA PHYTOGEOGR SUEC, V76, P53 VANDERMAAREL E, 1989, OIKOS, V56, P364 VANDERMAAREL E, 1993, J VEG SCI, V4, P179 VANDIJK G, 1991, CONSERVATION LOWLAND, P15 VANDORP D, 1985, VEGETATIO, V58, P123 VILBASTE G, 1938, LAANEMAA MAATEADUSLI, P47 WESTHOFF V, 1971, SCI MANAGEMENT ANIMA, P3 ZOBEL M, 1984, EESTI LOODUS, V6, P372 ZOBEL M, 1992, NORD J BOT, V12, P249 ZOBEL M, 1996, J VEG SCI, V7, P203 ZOBEL M, 1997, TRENDS ECOL EVOL, V12, P266 0921-2973 Landsc. Ecol.ISI:000079802500008Tartu State Univ, Inst Bot & Ecol, EE-51005 Tartu, Estonia. Partel, M, Tartu State Univ, Inst Bot & Ecol, Lai 40, EE-51005 Tartu, Estonia.English <73Pascual-Hortal, L. Saura, S.2006Comparison and development of new graph-based landscape connectivity indices: towards the priorization of habitat patches and corridors for conservation959-967Landscape Ecology217connectivity; conservation priorities; corridors; graph theory; habitat fragmentation; habitat loss; landscape metrics; landscape planning; patches; spatial indices HETEROGENEOUS LANDSCAPES; FRAGMENTATION; RESISTANCEArticleOctThe loss of connectivity of natural areas is a major threat for wildlife dispersal and survival and for the conservation of biodiversity in general. Thus, there is an increasing interest in considering connectivity in landscape planning and habitat conservation. In this context, graph structures have been shown to be a powerful and effective way of both representing the landscape pattern as a network and performing complex analysis regarding landscape connectivity. Many indices have been used for connectivity analyses so far but comparatively very little efforts have been made to understand their behaviour and sensitivity to spatial changes, which seriously undermines their adequate interpretation and usefulness. We systematically compare a set of ten graph-based connectivity indices, evaluating their reaction to different types of change that can occur in the landscape (habitat patches loss, corridors loss, etc.) and their effectiveness for identifying which landscape elements are more critical for habitat conservation. Many of the available indices were found to present serious limitations that make them inadequate as a basis for conservation planning. We present a new index (IIC) that achieves all the properties of an ideal index according to our analysis. We suggest that the connectivity problem should be considered within the wider concept of habitat availability, which considers a habitat patch itself as a space where connectivity exists, integrating habitat amount and connectivity between habitat patches in a single measure.://000241010900001 ISI Document Delivery No.: 091FA Times Cited: 1 Cited Reference Count: 19 Cited References: BUNN AG, 2000, J ENVIRON MANAGE, V59, P265 CALABRESE JM, 2004, FRONT ECOL ENVIRON, V2, P529 GRASHOFBOKDAM C, 1997, J VEG SCI, V8, P21 JAEGER JAG, 2000, LANDSCAPE ECOL, V15, P115 JOHNSON AR, 1992, LANDSCAPE ECOL, V7, P63 JORDAN F, 2003, LANDSCAPE ECOL, V18, P83 KEITT TH, 1997, CONSERV ECOL, V1 LI HB, 2004, LANDSCAPE ECOL, V19, P389 MOILANEN A, 2002, ECOLOGY, V83, P1131 PULLIAM HR, 1988, AM NAT, V132, P652 RICOTTA C, 2000, COMMUNITY ECOLOGY, V1, P89 SCHIPPERS P, 1996, ECOGRAPHY, V19, P97 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 STEVENS VM, 2004, LANDSCAPE ECOL, V19, P829 TAYLOR PD, 1993, OIKOS, V68, P571 TISCHENDORF L, 2000, LANDSCAPE ECOL, V15, P633 TISCHENDORF L, 2000, OIKOS, V90, P7 URBAN D, 2001, ECOLOGY, V82, P1205 VERBEYLEN G, 2003, LANDSCAPE ECOL, V18, P791 0921-2973 Landsc. Ecol.ISI:000241010900001Univ Lleida, Dept Agroforestry Engn, Higher Tech Sch Agrarian Engn ETSEA, Lleida 25198, Spain. Saura, S, Univ Lleida, Dept Agroforestry Engn, Higher Tech Sch Agrarian Engn ETSEA, Av Rovira Roure 191, Lleida 25198, Spain. ssaura@eagrof.udl.esEnglish <7hPasher, J. King, D. J.2006GLandscape fragmentation and ice storm damage in eastern ontario forests477-483Landscape Ecology214damage; disturbance; fragmentation metrics; general linear model; ice storm; lacunarity; landscape extent; temperate forest ENVIRONMENTAL DATA; LACUNARITY; DISTURBANCES; ECOLOGY; PATTERNArticleMayDWith return times between 20 and 100 years, ice storms are a primary disturbance type for temperate forests of eastern North America. Many studies have been conducted at the forest patch and plot scales to examine relations between damage and variables describing site, composition and structure. This paper presents results from a landscape scale study of fragmentation relations with damage in eastern Ontario forests. Data previously collected for two independent and spatially non-overlapping patch level damage studies were used. A Generalized Linear Model (GLM) was used to analyse relations between damage and fragmentation metrics representing patch isolation, edge density, and the relative size and distribution of patches in the landscape. The metrics were applied using spatial extents of 1 x 1 km and 4 x 4 km, following analyses of the variability of numbers of patches and of the lacunarity of forest patterns over a range of extents. The results showed that patch isolation, as measured by the mean Euclidean distance between patches (ENN) was significantly related to damage.://000237487700002 ISI Document Delivery No.: 041WR Times Cited: 0 Cited Reference Count: 25 Cited References: *ENV CAN, 1998, WORST IC STORM CAN H ALLAIN C, 1991, PHYS REV A, V44, P3552 BRUEDERLE LP, 1985, B TORREY BOT CLUB, V112, P167 BUTSON C, 2005, IN PRESS INT J REMOT CHARBONNEAU NC, 2003, THESIS DEPT BIOL CAR DALE MRT, 2000, LANDSCAPE ECOL, V15, P467 FOSTER DR, 1998, ECOSYSTEMS, V1, P497 HAUER RJ, 1994, PUBLICATION U ILLINO JAEGER JAG, 2000, LANDSCAPE ECOL, V15, P115 KING DJ, 2005, NAT HAZARDS, V35, P321 LAUTENSCHLAGER RA, 1999, FOREST CHRON, V75, P633 LEMON PC, 1961, B TORREY BOT CLUB, V88, P21 MCGARIGAL K, 2002, FRAGSTATS SPATIAL PA MILLWARD AA, 2004, LANDSCAPE ECOL, V19, P99 OLTHOF I, 2004, REMOTE SENS ENVIRON, V89, P484 PELLIKKA PKE, 2000, CANADIAN J REMOTE SE, V26, P394 PLOTNICK RE, 1993, LANDSCAPE ECOL, V8, P201 PROULX OJ, 2001, CAN J FOREST RES, V31, P1758 RHOADS AG, 2002, CAN J FOREST RES, V32, P1763 SMITH KT, 1998, WINTER STORM INJURY SMITH WH, 1998, J FOREST, V96, P32 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1998, ECOSYSTEMS, V1, P493 VANDYKE ORP, 1999, 112 SCSS WEAR DN, 2002, SO FOREST RESOURCE A 0921-2973 Landsc. Ecol.ISI:000237487700002Carleton Univ, Dept Geog, Ottawa, ON K1S 5B6, Canada. Carleton Univ, Dept Environm Studies, Ottawa, ON K1S 5B6, Canada. King, DJ, Carleton Univ, Dept Geog, 1125 Colonel Dr, Ottawa, ON K1S 5B6, Canada. doug_king@carleton.caEnglish8ڽ7 YPasher, Jon Mitchell, ScottW King, DouglasJ Fahrig, Lenore Smith, AdamC Lindsay, KathrynE2013mOptimizing landscape selection for estimating relative effects of landscape variables on ecological responses371-383Landscape Ecology283Springer NetherlandsSite selection Experimental field design Landscape heterogeneity GIS Multi-scale analysis Landscape structure Landscape composition Landscape configuration 2013/03/01+http://dx.doi.org/10.1007/s10980-013-9852-6 0921-2973Landscape Ecol10.1007/s10980-013-9852-6English?"John Pastor Michael Broschart1990<The spatial pattern of a northern conifer-hardwood landscape55-68Landscape Ecology41Acer saccharum, fractals, geographic information systems, northern landscapes, old growth, soils, spatial pattern, Tsuga canadensisA geographic information system, fractal analyses, and statistical methods were used to examine the spatial distributions of old growth hemlock, northern hardwood, mixed hardwood/hemlock stands and wetlands with respect to each other and also soils and topography. Greater than 80% of the stands of any covertype were less than 20 ha in area. Nearly pure hemlock and northern hardwood stands were associated with soils having a fragipan, while mixed hardwood/hemlock stands were associated with sandier soils. Hemlock stands weredistributed independently of hardwood and mixed hardwood/hemlock stands, but hardwood and mixed hardwood/hemlock stands were usually surrounded by hemlock. Bogs and lakes were usually surrounded by hemlock stands and are distributed independently of hardwood stands. The shapes of all stands vary from extremely simple to extremely complex, with a general tendency for hemlock stands to be more convoluted than hardwoods. The analyses suggest segregation across soil types and a disturbance regime favoring the establishment of hardwoods and mixed hardwood/hemlock stands in a hemlock matrix as reasons for the origin of the observed spatial patterns.[|?D Patrick, D. A. Gibbs, J. P.2010WPopulation structure and movements of freshwater turtles across a road-density gradient791-801Landscape Ecology2554Understanding interactions between roadways and population structure and movements of wildlife is key to mitigating "road effects" associated with increasing urbanization of the landscape. Aquatic turtles are a useful focal group because (1) population persistence is sensitive to mortality of individuals upon roads; (2) turtles frequently move among wetlands and encounter roads, and (3) turtles are an important component of vertebrate biomass in aquatic ecosystems. From 2005 to 2007, we examined the effects of urbanization on local- and landscape-scale populations of turtles. To do so, we sampled and marked turtles in 15 ponds arranged along a steep, urban-rural gradient in central New York State. We captured 494 turtles, representing 327 individuals, the majority of which were common snapping turtles Chelydra serpentina (n = 191) and eastern painted turtles Chrysemys picta picta (n = 122). At the local population (pond) scale, a higher proportion of female snapping turtles in ponds was associated with lower road densities within 500 m of ponds. The mean size of both species of turtle increased in ponds with a lower density of roads within 100 m. At the landscape-level, we observed fewer turtles dispersing through urbanized habitat than forested, and fewer movements through areas with a higher density of roads. Our study suggests that roads alter both local- and landscape-level turtle populations through a loss of female turtles, and by reducing movement between ponds. By extension, the study targets key landscape features upon which to focus mitigation efforts.!://WOS:000276609800010Times Cited: 0 0921-2973WOS:00027660980001010.1007/s10980-010-9459-0 <7|Pausas, J. G. Austin, M. P.1998TPotential impact of harvesting for the long-term conservation of arboreal marsupials103-109Landscape Ecology132harvesting logging forest management landscape arboreal marsupials simulation SOUTH-EAST AUSTRALIA MONTANE ASH FORESTS WILDLIFE CORRIDORS CENTRAL HIGHLANDS COMPUTER-MODEL DIVERSITY ABUNDANCE VICTORIA WALES FAUNAArticleAprlWe used a simulation approach to study the trade-off between forest harvesting and the conservation of arboreal marsupials in managed eucalypt forests of south-eastern New South Wales (Australia). The EDEN gap model is used to predict tree biomass harvested and the resulting shifts in habitat quality (HQ) for arboreal marsupials under different harvesting scenarios. These harvesting scenarios generate a gradient of biomass harvested by varying rotation length and tree retention in different topographic positions. The results suggest that the shape of the curve of reduction of HQ along the harvesting gradient is very sensitive to topographic position and hence to the proportion of topographic units in the landscape. Consequently arboreal marsupial management in logged forests will be region-dependent as each region will have its own pattern of landscape complexity.://000077256800004 ISI Document Delivery No.: 143LH Times Cited: 5 Cited Reference Count: 23 Cited References: AUSTIN MP, 1978, LAND USE S COAST NEW, V2, P44 AUSTIN MP, 1990, ECOL MONOGR, V60, P161 AUSTIN MP, 1996, AUST J ECOL, V21, P154 BOTKIN DB, 1972, J ECOL, V60, P849 BRAITHWAITE LW, 1984, AUST WILDLIFE RES, V11, P41 CHAPIN FS, 1992, TRENDS ECOL EVOL, V7, P107 FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 HANSEN AJ, 1993, ECOL APPL, V3, P481 HANSEN AJ, 1995, ECOL APPL, V5, P535 LINDENMAYER DB, 1991, BIOL CONSERV, V56, P295 LINDENMAYER DB, 1993, BIOL CONSERV, V66, P207 LINDENMAYER DB, 1994, RISK EXTINCTION RANK LINDENMAYER DB, 1994, WILDLIFE RES, V21, P323 MARGULES CR, 1995, BIORAP GUIDELINES US PAUSAS JG, 1995, FOREST ECOL MANAG, V78, P39 PAUSAS JG, 1997, ECOL APPL, V7 PRESSEY RL, 1993, TRENDS ECOL EVOL, V8, P124 SHUGART HH, 1981, AUST J ECOL, V6, P149 SHUGART HH, 1984, THEORY FOREST DYNAMI STRASSER MJ, 1996, AUST J ECOL, V21, P341 TURNER MG, 1995, ECOL APPL, V5, P12 TYNDALEBISCOE CH, 1975, AUST FORESTRY, V38, P117 URBAN DL, 1992, PLANT SUCCESSION THE, P249 0921-2973 Landsc. Ecol.ISI:000077256800004CSIRO, Div Wildlife & Ecol, Lyneham, ACT 2602, Australia. Pausas, JG, Ctr Estud Ambietnales Mediterraneo, Carrer 4 Sector Oest,Parc Tecnol, Valencia 46980, Spain.English<7 Pe'er, G. Heinz, S. K. Frank, K.2006LConnectivity in heterogeneous landscapes: Analyzing the effect of topography47-61Landscape Ecology211`accessibility pattern; animal movement; butterflies; connectivity; dispersal; ecologically-scale landscape indices; hilltopping; individual-based model; summit-accessibility; topography CHECKERSPOT BUTTERFLIES; METAPOPULATION DYNAMICS; FRAGMENTED LANDSCAPES; POPULATION-DYNAMICS; HABITAT NETWORK; DISPERSAL; MODEL; EXTINCTION; CONSERVATION; PERSISTENCEArticleJanSAnimal response to landscape heterogeneity directs dispersal and affects connectivity between populations. Topographical heterogeneity is a major source of landscape heterogeneity, which is rarely studied in the contexts of movement, dispersal, or connectivity. The current study aims at characterizing and quantifying the impacts of topography on landscape connectivity. We focus on 'hilltopping' behavior in butterflies, a dispersal-like behavior where males and virgin females ascend to mountain summits and mate there. Our approach integrates three elements: an individual-based model for simulating animal movements across topographically heterogeneous landscapes; a formula for the accessibility of patches in homogenous landscapes; and a graphical analysis of the plots of the simulation-based vs. the formula-based accessibility values. We characterize the functional relationship between accessibility values and landscape structure (referred to as 'accessibility patterns') and analyze the influence of two factors: the intensity of the individuals' response to topography, and the level of topographical noise. We show that, despite the diversity of topographical landscapes, animal response to topography results in the formation of two, quantifiable accessibility patterns. We term them 'effectively homogeneous' and 'effectively channeled'. The latter, in which individuals move toward a single summit, prevails over a wide range of behavioral and spatial parameters. Therefore, 'channeled' accessibilities may occur in a variety of landscapes and contexts. Our work provides novel tools for understanding and predicting accessibility patterns in heterogeneous landscapes. These tools are essential for linking movement behavior, movement patterns and connectivity. We also present new insights into the practical value of ecologically scaled landscape indices.://000235887300005 ISI Document Delivery No.: 020DD Times Cited: 1 Cited Reference Count: 58 Cited References: ADLER FR, 1994, THEOR POPUL BIOL, V45, P41 ANDERSON GS, 1997, LANDSCAPE ECOL, V12, P261 BAGUETTE M, 2000, J APPL ECOL, V37, P100 BAKKER VJ, 2004, CONSERV BIOL, V18, P689 BASCOMPTE J, 1996, J ANIM ECOL, V65, P465 CHARDON JP, 2003, LANDSCAPE ECOL, V18, P561 EHRLICH PR, 1988, AM NAT, V132, P460 FADAMIRO HY, 1998, J INSECT BEHAV, V11, P549 FAHRIG L, 1992, THEOR POPUL BIOL, V41, P300 FERRERAS P, 2001, BIOL CONSERV, V100, P125 FRANK K, 1998, LANDSCAPE ECOL, V13, P363 FRANK K, 2002, AM NAT, V159, P530 FRANK K, 2004, BIODIVERS CONSERV, V13, P189 FRANK K, 2005, AM NAT, V165, P374 GRIMM V, 1999, ECOL MODEL, V115, P129 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HADDAD NM, 1999, ECOL APPL, V9, P623 HANSKI I, 1994, BIOL CONSERV, V68, P167 HANSKI I, 1994, ECOLOGY, V75, P747 HANSKI I, 1994, J ANIM ECOL, V63, P151 HANSKI I, 1996, AM NAT, V147, P527 HANSKI I, 1996, CONSERV BIOL, V10, P578 HANSKI I, 2000, ECOLOGY, V81, P239 HANSKI I, 2002, CONSERV BIOL, V16, P666 HARRISON S, 1989, ECOLOGY, V70, P1236 HEINZ SK, 2005, LANDSCAPE ECOL, V20, P83 HESS GR, 1996, AM NAT, V148, P226 LEVINS R, 1970, AM MATH SOC, P75 LOWE WH, 2003, ECOLOGY, V84, P2145 NATHAN R, 2001, TRENDS ECOL EVOL, V16, P481 NEVE G, 1996, ACTA OECOL, V17, P621 OPDAM P, 1990, SPECIES DISPERSAL AG, P3 PEER G, 2003, THESIS B GURION U NE PEER G, 2004, ANIM BEHAV 4, V68, P825 PEER G, 2005, CONSERV BIOL, V19, P1997 PHILLIPS JB, 1996, J THEOR BIOL, V180, P309 RIES L, 2001, J ANIM ECOL, V70, P840 ROLAND J, 2000, ECOLOGY, V81, P1642 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SHIELDS O, 1967, J RES LEPIDOPTERA, V6, P69 SHKEDY Y, 2000, CONSERV BIOL, V14, P200 SINGER MC, 1992, AM NAT, V140, P654 SOUTH AB, 2002, DISPERSAL ECOLOGY, P327 SUTCLIFFE OL, 2003, LANDSCAPE URBAN PLAN, V63, P15 TENNENT WT, 1995, ENTOMOLOGISTS RECORD, V106, P57 THOMAS CD, 2000, P ROY SOC LOND B BIO, V267, P139 TISCHENDORF L, 2000, OIKOS, V90, P7 TISCHENDORF L, 2003, LANDSCAPE ECOL, V18, P41 TURCHIN P, 1998, QUANTITATIVE ANAL MO VOS CC, 2001, AM NAT, V157, P24 WALLRAFF HG, 2000, J THEOR BIOL, V205, P133 WICKMAN PO, 1988, ZOOL J LINN SOC-LOND, V93, P357 WIEGAND T, 1999, AM NAT, V154, P605 WIENS JA, 1993, OIKOS, V66, P369 WIENS JA, 2001, DISPERSAL, P96 WILTSCHKO R, 2003, ANIM BEHAV 2, V65, P257 YAMANAKA T, 2003, ECOL MODEL, V161, P35 0921-2973 Landsc. Ecol.ISI:000235887300005ZUFZ Ctr Environm Res, Dept Ecol Modelling, Leipzig, Germany. Univ Bergen, Dept Biol, Bergen, Norway. Ben Gurion Univ Negev, Jacob Blaustein Inst Desert Res, Mitrani Dept Desert Ecol, Sede Boqer, Israel. Pe'er, G, Hebrew Univ Jerusalem, Inst Life Sci, Dept Evolut Systemat & Ecol, Givat Ram Campus, IL-91904 Jerusalem, Israel. peerg@vms.huji.ac.ilEnglish|? #Pearson, Diane M. Gorman, Julian T.2010Exploring the relevance of a landscape ecological paradigm for sustainable landscapes and livelihoods: A case-application from the Northern Territory Australia 1169-1183Landscape Ecology258Oct+Global change is exacerbating the need for more effective mechanisms and approaches for working towards economic, social/cultural and environmental sustainability. It is now well recognised that science for sustainability will require integrated problem-focussed research that is by nature trans-disciplinary. Resolutions to both global and regional scale issues must involve participation of a diverse number of stakeholders. One region that would benefit greatly from such an integrated approach is the Northern Territory of Australia. This area is home to some of the most pristine savanna landscapes in the world and it is also occupied by one of the oldest living human cultures which are still in existence today. However, in recent years there has been increasing pressure to develop this region. The Northern Territory is also facing problems associated with having a growing Aboriginal population with deepening health and social problems. So as well as needing to facilitate adaptation in response to global change and development for economic prosperity of the region, there is an obligation to alter management practices to reduce social disadvantage. In light of this, it will be important that future landscapes are multifunctional and designed to ensure the preservation of biological and cultural diversity, as well as having provision for the livelihoods of the people that live within them. This article recommends the adoption of a landscape ecological approach for strategic development and sustainable planning, which captures and incorporates the values and identities of the different stakeholders, as well as engaging them in a continuous, adaptive process of planning and management, and in doing so discusses the importance of human ecological holism as part of the conceptual framework for landscape ecology.!://WOS:000281725700004YTimes Cited: 1 10th International Congress of Ecology Aug 16-21, 2009 Brisbane, AUSTRALIA 0921-2973WOS:00028172570000410.1007/s10980-010-9498-6-|? $Pearson, Diane M. McAlpine, Clive A.2010OLandscape ecology: an integrated science for sustainability in a changing world 1151-1154Landscape Ecology258Oct!://WOS:000281725700002Times Cited: 1 0921-2973WOS:00028172570000210.1007/s10980-010-9512-z<7Pearson, S. M.1993bThe spatial extent and relative influence of landscape-level factors on wintering bird populations3-18Landscape Ecology81*SPECIES DIVERSITY; PATCHES; GRAIN; GEORGIAArticleMarThe influences of the landscape matrix (complex of habitats surrounding a study plot) and within-patch vegetation were studied in bird communities wintering in the piedmont of Georgia, USA. Variation at the landscape and within-patch levels was controlled to reduce the likelihood of confounding and spurious relationships. The landscape matrix within 500 m of each study plot was quantified from aerial photographs. Statistical models using landscape matrix and within-patch vegetation variables explained 73-84% of variation in bird abundance and diversity among sites with landscape matrix variables accounting for 30-90% of the variation. Variation in bird species richness and diversity was explained solely by landscape variables. Models for individual species such as Carolina Wrens (Thyrothorus ludovicianus) and Rufous-sided Towhees (Pipilo erythrophthalmus) had r2 > 0.80, with the landscape matrix variables accounting for the majority of this variation. However, other species like Northern Cardinals (Cardinalis cardinalis) and White-throated Sparrows (Zonotrichia albicollis) were most strongly influenced by within-plot vegetation. The landscape influence extended beyond habitats immediately adjacent to the study plots as indicated by significant variables describing variation in more distant habitat patches. These analyses illustrate a technique for comparing the strength of within-patch versus landscape influences and measuring the spatial extent of the landscape influence in fine-grained landscapes.://A1993KW95800001 IISI Document Delivery No.: KW958 Times Cited: 99 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1993KW95800001UPEARSON, SM, OAK RIDGE NATL LAB,DIV ENVIRONM SCI,POB 2008,MS 6038,OAK RIDGE,TN 37831.EnglishK<73Pedroli, B. de Blust, G. van Looy, K. van Rooij, S.20013Setting targets in strategies for river restoration5-18Landscape Ecology17 Supplement 1Vhabitat network Meuse population persistence river restoration setting targets HABITATArticleSince about 90% of the natural floodplain area of rivers in Europe has been reclaimed and now lacks river dynamics, nature rehabilitation along rivers is of crucial importance for the restoration of their natural function. Flood protection, self-purification of surface water, groundwater recharge, species protection and migration are all involved in this process. It is now generally recognised that rivers form natural arteries in Europe but are also of economic importance and are recognisable cultural landscape. Many examples are already available of successful small river restoration projects. Several species thought to be extinct have now reappeared and characteristic species have also expanded in recent years. This paper concentrates on the concept of setting targets for river restoration as exemplified by the Meuse River. A modelling exercise shows the restraints of current habitat configuration and the potential for habitat restoration along the river. A policy analysis, using a strategic approach, illustrates the influence of the decision making process on the targets for natural river development. River dynamics play a key factor in determining the potential for persistent populations of target animal species along the river, with the help of an expert system (LARCH, Landscape ecological Analysis and Rules for the Configuration of Habitat). The potentials for the increase of dispersion and biodiversity and the maximisation of ecological benefits at different scales, are also considered.://000176041000002 ISI Document Delivery No.: 559TG Times Cited: 7 Cited Reference Count: 37 Cited References: 1994, NATUR 2000 NORDRHEIN *ARB REN HOCHRH, 1996, HOCHRH FACHT LEB HOC AMOROS C, 1993, HYDROSYSTEMES FLUVIA BAYLEY PB, 1991, REGUL RIVER, V6, P75 BILLEN G, 1995, ECOSYSTEMS WORLD, V22, P389 BOON PJ, 1992, RIVER CONSERVATION M, P11 CALS MJR, 1998, AQUAT CONSERV, V8, P61 CHARDON JP, 2000, EUROPEAN WATER MANAG, V3, P35 DAHM CN, 1995, RESTOR ECOL, V3, P225 DEBLUST G, 1985, BIOL WAARDERINGSKAAR FOPPEN RPB, 1998, NEW CONCEPTS SUSTAIN, P85 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY GALLOWAY GE, 2000, NEW APPROACHES RIVER, P51 GORE JA, 1985, RESTORATION RIVERS S HAVINGA H, 2000, NEW APPROACHES RIVER, P15 JUNK WJ, 1989, CANADIAN SPECIAL PUB, V106, P110 KERN K, 1992, RIVER CONSERVATION M, P321 LENDERS HJR, 1998, NEW CONCEPTS SUSTAIN, P35 LORENZ CM, 1997, REGUL RIVER, V13, P501 PEDROLI B, 1996, LANDSCHAP, V13, P97 PEDROLI B, 1999, ISSUES LANDSCAPE ECO, P103 PEDROLI GBM, 1998, NEW CONCEPTS SUSTAIN, P67 PETTS G, 1990, WATER ENG LANDSCAPE, P188 PETTS GE, 1996, FLUVIAL HYDROSYSTEM PETTS GE, 1997, CONT HYDROLOGY HOLIS, P241 REIJNEN R, 1995, PUBLICATIONS REPORTS SCHAMA S, 1995, LANDSCAPE MEMORY STATZNER B, 1986, FRESHWATER BIOL, V16, P127 VANACKER S, 1998, 984 I NAT VANDERKAATS JA, 1994, WATER SCI TECHNOLOGY VANDEVEN GP, 1993, MAN MADE LOWLANDS HI VANLOOY K, 1995, WETENSCHAPPELIJKE ME VANLOOY K, 1997, NATUURHISTORISCH MAA, V86, P155 VANNOTE RL, 1980, CAN J FISH AQUAT SCI, V37, P130 VERBOOM J, 2001, BIOL CONSERV, V100, P89 VOS CC, 2001, AM NAT, V157, P24 WARD JV, 1989, J N AM BENTHOL SOC, V8, P2 Suppl. 1 0921-2973 Landsc. Ecol.ISI:000176041000002Alterra Green World Res, Landscape Ecol Dept, Wageningen, Netherlands. Inst Nat Conservat Flemish Community, Brussels, Belgium. Pedroli, B, Alterra Green World Res, Landscape Ecol Dept, Wageningen, Netherlands. b.pedroli@alterra.wag-ur.nlEnglish<7Pedroli, B. Harms, B.2001\Restoration and planning for sustainable river management: Concepts and tools - Introduction1-3Landscape Ecology17 supplement 1REHABILITATIONEditorial Material://000176041000001 ISI Document Delivery No.: 559TG Times Cited: 0 Cited Reference Count: 15 Cited References: *IRC, 1987, RHIN ACT PROGR TECHN AMOROS C, 1987, ENVIRON MANAGE, V11, P607 BAYLEY PB, 1991, REGUL RIVER, V6, P75 BILLEN G, 1995, ECOSYSTEMS WORLD, V22, P389 DEWAAL LC, 1995, ARCH HYDROBIOL S101, V3, P679 DISTER E, 1990, REGUL RIVER, V5, P1 HANSEN HO, 1996, RIVER RESTORATION DA LARGE ARG, 1994, RIVERS HDB HYDROLOGI, V2, P401 MIDDLEKOOP H, 1997, NETHERLANDS GEOGRAPH, V124 MILNER AM, 1994, RIVERS HDB, V2, P76 POSTMA R, 1995, 95060 RIZA MIN VERK RAMADE F, 1995, NATO ADV SCI I SERIE, V1, P28 THEILING CH, 1995, REGUL RIVER, V11, P227 VANDERKRAATS JA, 1994, WATER SCI TECHNOLOGY VANDIJK GM, 1995, REGUL RIVER, V11, P377 Suppl. 1 0921-2973 Landsc. Ecol.ISI:000176041000001Univ Wageningen & Res Ctr, Alterra Green World Res, NL-6700 AA Wageningen, Netherlands. Pedroli, B, Univ Wageningen & Res Ctr, Alterra Green World Res, POB 47, NL-6700 AA Wageningen, Netherlands.Englishn<7sPedroli, B. Pinto-Correia, T.2006RLandscape - what's in it? European landscape research at a turning point - Preface313-313Landscape Ecology213Editorial MaterialApr://000236968500001 HISI Document Delivery No.: 034ZD Times Cited: 0 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:000236968500001Alterra Wageningen UR, Landscape Ctr, NL-6700 AA Wageningen, Netherlands. Univ Evora, Dept Landscape & Biophys Planning, Evora, Portugal. Pedroli, B, Alterra Wageningen UR, Landscape Ctr, POB 47, NL-6700 AA Wageningen, Netherlands. bas.pedroli@wur.nlEnglish s<7{)Pedroli, B. Pinto-Correia, T. Cornish, P.2006iLandscape - what's in it? Trends in European landscape science and priority themes for concerted research421-430Landscape Ecology213FEurope; landscape ecology; landscape research; research agenda ECOLOGYArticleAprxReflecting on the other papers in this special issue, this synopsis characterises some essential trends in European Landscape Ecology, including the challenges it is facing in society. It describes the various perspectives on the 'contents' of landscape that are currently being practiced, and especially considers the notion of 'environment' as something intrinsic to human activity. Landscape classification and typology are discussed in their potential but limited use for landscape science. The specificity of the European approach appears to be related to the large diversity of cultural landscapes, currently losing their functional ties with the land-use systems that had formed them. European landscape research reports show a large commitment to this decreasing diversity, a dedication characterised by a strong sense of 'loss and grief'. On the other hand, it is concluded that European landscape research has a specific niche with a clear focus on applied landscape studies explicitly including people's perceptions and images, as well as the participation of the public and stakeholders. Since globalisation tends to reinforce the detachment of people from their environment; an increased effort is needed to compensate for this effect, and therefore the consideration of the various dimensions of the landscape is today more pertinent than ever. Meeting the challenges of present landscapes, in the face of new multifunctional demands in old diverse landscapes, requires more than before the combination of various perspectives and methods, and of various scales of application, in order to design innovative and adaptive paths for the future.://000236968500009 ISI Document Delivery No.: 034ZD Times Cited: 0 Cited Reference Count: 16 Cited References: 2000, AM HERITAGE DICT ENG *COUNC EUR, 2000, EUR LANDSC CONV T LA, V6 *OECD, 2002, P NORW OECD EXP M AG BRANDT J, 2004, MULTIFUNCTIONAL LAND, V1 BURGI M, 2004, LANDSCAPE ECOL, V19, P857 CRONON W, 1996, UNCOMMON GROUND RETH DAILY GC, 1997, NATURES SERVICES SOC DEGROOT RS, 2006, IN PRESS LANDSCAPE U HOBBS R, 1997, LANDSCAPE URBAN PLAN, V37, P1 JACKSON W, 1989, ECOLOGY, V70, P1591 KLIJN J, 2000, LANDSCAPE ECOLOGY LA NASSAUER JI, 2004, LANDSCAPE ECOL, V19, P343 PEDROLI B, 2002, LANDSCAPE ECOL S1, V17, P5 TRESS G, 2004, LANDSCAPE ECOL, V20, P479 WASCHER DM, 2005, EUROPEAN LANDSCAPE C WU JG, 2002, LANDSCAPE ECOL, V17, P355 0921-2973 Landsc. Ecol.ISI:000236968500009NUniv Wageningen & Res Ctr, Alterra, Landscape Ctr, NL-6700 AA Wageningen, Netherlands. Univ Evora, Dept Landscape & Biophys Planning, P-7000 Evora, Portugal. Univ Western Sydney, Penrith, NSW 1797, Australia. Pedroli, B, Univ Wageningen & Res Ctr, Alterra, Landscape Ctr, POB 47, NL-6700 AA Wageningen, Netherlands. bas.pedroli@wur.nlEnglish?, G. Bas M. Pedroli Guus J. Borger1990JHistorical land use and hydrology, A case study from eastern Noord-Brabant237-248Landscape Ecology44Slandscape ecology, historical geography, land use, groundwater, Kempen, NetherlandsThe historical geography of the landscape of a lowland brook valley in the sandy Kempen area(eastern Brabant, Netherlands) shows the interaction of ecological processes and land use, and helps to understand processes in the present landscape. In this location the human influence, especially on the groundwater hydrology, played a major role in the development of the landscape. Levels and flow of different types of groundwater interacted with vegetation development and human interference, to produce landscape patterns. Four main stages have been identified. In the prehistoric period, a natural deciduous forest covered the higher grounds, ombrotrophic peat was formed in the valley, and groundwater was relatively deep. In the medieval stage man settled on the edge of the valley, cleared parts of the forest and dug part of the peat. Groundwater levels were raised, which increased the rate of groundwater discharge and increased the amount of associated lowland peat formation in the valley. This tendency continued in modern times, when the area was completely deforested. Groundwater levels increased further due to decreased evapotranspiration, which gave rise to the use of ponds for fish and for water mills. Finally, in the most recent period the groundwater level has been lowered by extensive artificial drainage, partly on a regional scale. It was concluded that evaluation of historical changes in the landscape help provide landscape planners with a sound idea of the nature of the landscape.|7 Pedroli, G. B. M. Borger, G. J.1990KHistorical Land-Use and Hydrology - a Case-Study from Eastern Noord-Brabant237-248Landscape Ecology44Nlandscape ecology historical geography land use groundwater kempen netherlandsSepThe historical geography of the landscape of a lowland brook valley in the sandy Kempen area (eastern Brabant, Netherlands) shows the interaction of ecological processes and land use, and helps to understand processes in the present landscape. In this location the human influence, especially on the groundwater hydrology, played a major role in the development of the landscape. Levels and flow of different types of groundwater interacted with vegetation development and human interference, to produce landscape patterns. Four main stages have been identified. In the prehistoric period, a natural deciduous forest covered the higher grounds, ombrotrophic peat was formed in the valley, and groundwater was relatively deep. In the medieval stage man settled on the edge of the valley, cleared parts of the forest and dug part of the peat. Groundwater levels were raised, which increased the rate of groundwater discharge and increased the amount of associated lowland peat formation in the valley. This tendency continued in modern times, when the area was completely deforested. Groundwater levels increased further due to decreased evapotranspiration, which gave rise to the use of ponds for fish and for water mills. Finally, in the most recent period the groundwater level has been lowered by extensive artificial drainage, partly on a regional scale. It was concluded that evaluation of historical changes in the landscape help provide landscape planners with a sound idea of the nature of the landscape.://A1990EV85800005,Ev858 Times Cited:5 Cited References Count:0 0921-2973ISI:A1990EV85800005Univ Amsterdam,Landscape & Environm Res Grp,1093 Bs Amsterdam,Netherlands Univ Amsterdam,Seminar Hist Geog,1011 Nh Amsterdam,NetherlandsEnglish<70Peinetti, H. R. Kalkhan, M. A. Coughenour, M. B.2002nLong-term changes in willow spatial distribution on the elk winter range of Rocky Mountain National Park (USA)341-354Landscape Ecology174beaver impoundments Colorado elk browsing hydrology riparian areas rocky mountains vegetation transitions willow UNGULATE HERBIVORY SALIX MONTICOLA BEAVER YELLOWSTONE ECOSYSTEMS DYNAMICS COLONIZATION RECRUITMENT POPULATION ECOLOGYArticleWe determined changes in willow (Salix spp.) cover in two valleys of the eastern slope of Rocky Mountain National Park, Colorado, USA, and related these changes to suspected causative factors. Changes in vegetation were inferred from digital maps generated from aerial photo-interpretation and field surveys conducted with a global positioning system. The decrease in riparian shrub cover was approximately 20% in both valleys over the period between 1937/46 and 1996, while the decline in tall willow (>2 m tall) cover was estimated to be approximately 55% in both valleys. Suppressed willows (<1.5 m tall) were predominantly located in areas affected by flooding and in areas where major river reductions were observed. Both valleys had sites that were being colonized by willows in wet meadows, and open areas created by flood disturbance. The potential causes of willow decline are many. Willow decline was associated with simplification of river spatial pattern, i.e., less complex branching and channelization, and a large flood disturbance. The causes of the reduction in river meanders were not determined, but are likely related to a decline in beavers, an increase in elk, and, possibly climate change. An increase in elk placed increased browsing pressure on willow during the period of the willow decline. Other factors such as climate changes and human activities could have also contributed to the willow decline. The persistence of these riparian ecosystems depends in large part on biotic interactions, particularly between willow, beaver, and elk.://000178391000004 ISI Document Delivery No.: 600LF Times Cited: 8 Cited Reference Count: 71 Cited References: ALLIENDE MC, 1989, J ECOL, V77, P1029 ALSTAD KP, 1999, OECOLOGIA, V120, P375 BAKER WL, 1997, ECOGRAPHY, V20, P155 BARNETT DT, 1999, CLIMATE CHANGE ELK W BARON J, 1992, BIOGEOCHEMISTRY SUBA, P142 BENEDICT JB, 1992, ARCTIC ALPINE RES, V24, P1 BENEDICT JB, 1999, ARCT ANTARCT ALP RES, V31, P1 BERGSTROM R, 1987, J ECOL, V75, P533 BERRY J, 1997, SCI BASED ASSESSMENT BERTNESS MD, 1997, ECOLOGY, V78, P1990 BOND WJ, 1994, BIODIVERSITY ECOSYST, P237 BRADLEY CE, 1986, CAN J BOT, V64, P1433 BUCHHOLTZ CW, 1983, ROCKY MOUNTAIN NATL CHADDE SW, 1991, GREATER YELLOWSTONE, P231 CLEMMER P, 1994, 173710 US DEP INT BU COLLINS WB, 1997, CAN FIELD NAT, V111, P567 COTTRELL TR, 1995, CAN J FOREST RES, V25, P215 DECAMPS H, 1988, LANDSCAPE ECOLOGY, V1, P163 ESTES M, 1939, LIB B COLORADO STATE, V6 FRYXELL FM, 1928, J MAMMAL, V9, P129 GREGORY SV, 1991, BIOSCIENCE, V41, P540 GUSE NG, 1966, THESIS COLORADO STAT GYSEL LW, 1960, J FOREST, V58, P696 HESS K, 1993, ROCKY TIMES ROCKY MO HEYWOOD VH, 1995, GLOBAL BIODIVERSITY HICKMAN SD, 1964, UNPUB BEAVER CENSUS HOBBS NT, 1996, J WILDLIFE MANAGE, V60, P695 JARRET RD, 1993, ROCKY MOUNTAIN NATIO, P1 JOHNSON LB, 1997, FRESHWATER BIOL, V37, P113 JOHNSTON CA, 1987, LANDSCAPE ECOL, V1, P47 JOHNSTON CA, 1990, CAN J FOREST RES, V20, P1036 JOHNSTON CA, 1990, ECOLOGY, V71, P1617 JOHNSTON CA, 1990, LANDSCAPE ECOL, V4, P5 KAY CE, 1990, THESIS UTAH STATE U KAY CE, 1992, P S EC MAN RIP SHRUB, P92 KAY CE, 1994, HUM NATURE, V5, P359 KAY CE, 1994, NAT RESOUR ENV ISS, V1, P23 KAY CE, 1997, J RANGE MANAGE, V50, P139 KEIGLEY RB, 1993, ROCKY MOUNTAIN NATL, P193 KIEGLEY RB, 1998, INTEGRATIVE BIOL, V1, P133 KINDSCHY RR, 1989, WILDLIFE SOC B, V17, P290 LORING JA, 1893, COMMUNICATION 0528 MILLER JR, 1995, BIOL CONSERV, V72, P371 MILLS EA, 1913, BEAVER WORLD NAIMAN RJ, 1984, OECOLOGIA, V62, P150 NAIMAN RJ, 1988, BIOSCIENCE, V38, P750 NAIMAN RJ, 1988, BIOSCIENCE, V38, P753 OLMSTED CE, 1979, N AM ELK ECOLOGY BEH, P89 PACKARD FM, 1947, J MAMMAL, V28, P219 PACKARD FM, 1947, J MAMMAL, V28, P4 PASTOR J, 1992, AM NAT, V139, P690 PATTEN DT, 1968, ECOLOGY, V49, P1107 PATTEN DT, 1998, WETLANDS, V18, P498 PEINETTI HR, 2001, OECOLOGIA, V127, P334 RATCLIFF HM, 1941, T N A WILD C, V6, P132 RAVEN JA, 1992, P ROY SOC EDINB B, V98, P49 REMILLARD MM, 1987, LANDSCAPE HETEROGENE, P103 RIPPLE WJ, 2000, BIOL CONSERV, V95, P361 ROTH NE, 1996, LANDSCAPE ECOL, V11, P141 SAGE R, 1846, SCENES ROCKY MOUNTAI SINGER FJ, 1994, J RANGE MANAGE, V47, P435 SINGER FJ, 1998, WILDLIFE SOC B, V26, P375 SINGER FJ, 1998, WILDLIFE SOC B, V26, P419 SPRAGUE AE, 1925, GAME MORE PLENTIFUL SPRAGUE AE, 2002, MY 1 WINTER ESTES PA STEVENS DR, 1980, BEAVER POPULATIONS E STEVENS DR, 1980, ROMO13 NAT PARK SERV USTIN SL, 1993, SCALING PHYSL PROCES, P339 WAGNER F, 1995, WILDLIFE POLICIES US WAGNER FH, 1995, J RANGE MANAGE, V48, P475 WOOTTON JT, 1994, ECOLOGY, V75, P151 0921-2973 Landsc. Ecol.ISI:000178391000004Colorado State Univ, Nat Resource Ecol Lab, Ft Collins, CO 80523 USA. Univ Nacl La Pampa, Fac Agron, RA-6300 Santa Rosa, Argentina. Peinetti, HR, Colorado State Univ, Nat Resource Ecol Lab, Ft Collins, CO 80523 USA.English? QPekin, Burak Jung, Jinha Villanueva-Rivera, Luis Pijanowski, Bryan Ahumada, Jorge2012Modeling acoustic diversity using soundscape recordings and LIDAR-derived metrics of vertical forest structure in a neotropical rainforest 1513-1522Landscape Ecology2710Springer NetherlandsBiomedical and Life SciencesCWe determined the relationship between acoustic diversity and metrics of vertical forest structure derived from light detection and ranging (LIDAR) data in a neotropical rainforest in Costa Rica. We then used the LIDAR-derived metrics to predict acoustic diversity across the forest landscape. Sound recordings were obtained from 14 sites for six consecutive days during dusk chorus (6 pm). Acoustic diversity was calculated for each day as the total intensity across acoustic frequency bands using the Shannon index and then averaged over the 6 days at each site. A 10 m radius around each site was used to obtain several LIDAR-derived metrics describing the vertical structural attributes of the forest canopy. Multiple linear regression (MLR) with Akaike information criterion was used to determine a top-ranked model with acoustic diversity as the dependent variable and the LIDAR metrics as independent variables. Acoustic diversity was modeled for forested areas (where canopy height was >20 m) at 20 m resolution using coefficients obtained from the MLR, and a hotspot analysis was conducted on the resulting layer. Acoustic diversity was strongly correlated ( R 2 = 0.75) with the LIDAR metrics suggesting that LIDAR-derived metrics can be used to determine canopy structural attributes important to vocal fauna species. The hotspot analysis revealed that the spatial distribution of these canopy structural attributes across the La Selva forest is not random. Our approach can be used to identify forest patches of potentially high acoustic diversity for conservation or management purposes.+http://dx.doi.org/10.1007/s10980-012-9806-4 0921-297310.1007/s10980-012-9806-4}?&Pennington, Deana D. Collins, Scott L.2007ZResponse of an aridland ecosystem to interannual climate variability and prolonged drought897-910Landscape Ecology226Jul&://BIOSIS:PREV200700463290 0921-2973BIOSIS:PREV200700463290ڽ7DPenteado, HomeroM2013Assessing the effects of applying landscape ecological spatial concepts on future habitat quantity and quality in an urbanizing landscape 1909-1921Landscape Ecology2810Springer NetherlandsSpatial concept Urban open space scenarios Compact versus dispersed development Habitat quantity and quality Landscape planning Portland Metro 2013/12/01+http://dx.doi.org/10.1007/s10980-013-9940-7 0921-2973Landscape Ecol10.1007/s10980-013-9940-7English1ڽ7+JPeterman, WilliamE Rittenhouse, TracyA G. Earl, JuliaE Semlitsch, RaymondD2013Demographic network and multi-season occupancy modeling of Rana sylvatica reveal spatial and temporal patterns of population connectivity and persistence 1601-1613Landscape Ecology288Springer NetherlandsuFunctional connectivity Graph theory Missouri Ozark Source–sink dynamics Spatially structured populations Wood frog 2013/10/01+http://dx.doi.org/10.1007/s10980-013-9906-9 0921-2973Landscape Ecol10.1007/s10980-013-9906-9English<7ePeters, D. P. C. Gosz, J. R. Pockman, W. T. Small, E. E. Parmenter, R. R. Collins, S. L. Muldavin, E.2006gIntegrating patch and boundary dynamics to understand and predict biotic transitions at multiple scales19-33Landscape Ecology211directional transitions; ecotones; positive feedbacks; shifting transitions; stationary transitions SOUTHERN NEW-MEXICO; GRASSLAND-SHRUBLAND ECOTONE; PLANT-SPECIES DOMINANCE; LANDSCAPE ECOLOGY; VEGETATION CHANGE; SPATIAL-PATTERNS; CLIMATE-CHANGE; HABITAT EDGES; DESERT; RESPONSESArticleJanHuman modification of landscapes overlying natural environmental heterogeneity is resulting in an increase in the numbers and types of ecological patches and their intervening boundaries. In this paper, we describe an operational framework for understanding and predicting dynamics of these biotic transitions for a range of environmental conditions across multiple spatial scales. We define biotic transitions as the boundary and the neighboring states, a more general definition than typically denoted by the terms boundary, ecotone, edge or gradient. We use concepts of patch dynamics to understand the structural properties of biotic transitions and to predict changes in boundaries through time and across space. We develop testable hypotheses, and illustrate the utility of our approach with examples from arid and semiarid ecosystems. Our framework provides new insights and predictions as to how landscapes may respond to future changes in climate and other environmental drivers.://000235887300003 ISI Document Delivery No.: 020DD Times Cited: 2 Cited Reference Count: 76 Cited References: ABRAHAMS AD, 1995, GEOMORPHOLOGY, V13, P37 ALFTINE KJ, 2004, J VEG SCI, V15, P3 ALLEN CD, 1998, P NATL ACAD SCI USA, V95, P14839 ANAND M, 2001, COMMUNITY ECOL, V2, P161 ARCHER S, 1988, ECOL MONOGR, V58, P111 BARNES PW, 1996, OECOLOGIA, V105, P493 BELNAP J, 2003, BIOSCIENCE, V53, P739 BHARK EW, 2003, ECOSYSTEMS, V6, P185 BORMANN FH, 1979, PATTERN PROCESS FORE BUXBAUM CAZ, 2003, THESIS U NEW MEXICO CADENASSO ML, 2003, BIOSCIENCE, V53, P750 CURTIS JT, 1959, VEGETATION WISCONSIN FAGAN WE, 1999, AM NAT, V153, P165 FAGAN WF, 2003, BIOSCIENCE, V53, P730 FIELDS MJ, 1999, J VEG SCI, V10, P123 FUENTES JD, 2000, B AM METEOROL SOC, V81, P1537 GOSZ JR, 1993, ECOL APPL, V3, P369 GOSZ RJ, 1996, J ARID ENVIRON, V34, P101 GROVER HD, 1990, CLIMATIC CHANGE, V17, P305 HANSEN AJ, 1992, LANDSCAPE BOUNDARIES HOLLAND MM, 1988, BIOL INT, V17, P47 HOOD EW, 2003, ECOSYSTEMS, V6, P31 JOBBAGY EG, 2000, GLOBAL ECOL BIOGEOGR, V9, P253 KAREIVA P, 1995, NATURE, V373, P299 KIEFT TL, 1998, ECOLOGY, V79, P671 KORNER C, 1998, OECOLOGIA, V115, P445 KOTLIAR NB, 1990, OIKOS, V59, P253 KROELDULAY G, 2004, J VEG SCI, V15, P531 LIDICKER WZ, 1999, LANDSCAPE ECOL, V14, P333 LLOYD KM, 2000, J VEG SCI, V11, P903 LUDWIG JA, 2000, ECOSYSTEMS, V3, P84 LYFORD FP, 1969, WATER RESOUR RES, V5, P1373 MACK RN, 2000, ECOL APPL, V10, P689 MALANSON GP, 2001, J VEG SCI, V12, P743 MAST JN, 2004, LANDSCAPE ECOL, V19, P167 MCINTYRE NE, 1999, ECOLOGY, V80, P2261 MILNE BT, 1996, ECOLOGY, V77, P805 MILNE BT, 2003, CLIMATE VARIABILITY, P286 MONTANA C, 1990, J ECOL, V78, P789 NEILSON RP, 1993, ECOL APPL, V3, P385 NOBLE IR, 1993, ECOL APPL, V3, P396 NOSS RF, 1997, PRINCIPLES CONSERVAT PENUELAS J, 2003, GLOBAL CHANGE BIOL, V9, P131 PETERS DPC, UNPUB J VEGET SCI PETERS DPC, 2000, J VEG SCI, V11, P493 PETERS DPC, 2002, AM J BOT, V89, P1616 PETERS DPC, 2002, ECOL MODEL, V152, P5 PETERS DPC, 2004, P NATL ACAD SCI USA, V101, P15130 PICKETT STA, 1978, BIOL CONSERV, V13, P27 PICKETT STA, 1985, ECOLOGY NATURAL DIST PICKETT STA, 1995, SCIENCE, V269, P331 PUTH LM, 2001, CONSERV BIOL, V15, P21 RANGO A, 2002, J ARID ENVIRON, V50, P549 RISSER PG, 1995, BIOSCIENCE, V45, P318 RYERSON DE, 2001, J VEG SCI, V12, P167 SANCHEZ BC, 2002, J ARID ENVIRON, V50, P247 SCHAUER AJ, 1998, GREAT BASIN NAT, V58, P273 SCHLESINGER WH, 1990, SCIENCE, V247, P1043 SCHLESINGER WH, 2000, BIOGEOCHEMISTRY, V49, P69 SEASTEDT TR, 2004, BIOSCIENCE, V54, P111 SHAW MR, 2001, GLOBAL CHANGE BIOL, V7, P193 VANDERMAAREL E, 1990, J VEG SCI, V1, P135 WALKER S, 2003, J VEG SCI, V14, P579 WATT AS, 1947, J ECOL, V35, P1 WEATHERS KC, 2001, CONSERV BIOL, V15, P1506 WEAVER JE, 1943, ECOL MONOGR, V13, P62 WELTZIN JF, 1999, ECOL MONOGR, V69, P513 WIENS JA, 1985, OIKOS, V45, P421 WIENS JA, 1993, OIKOS, V66, P369 WIENS JA, 2002, FRESHWATER BIOL, V47, P501 WILSON JB, 1992, ADV ECOL RES, V23, P263 WITH KA, 1997, OIKOS, V78, P151 WITH KA, 1999, ECOLOGY, V80, P1340 WU J, 1999, CANADIAN J REMOTE SE, V25, P367 WU JG, 1995, Q REV BIOL, V70, P439 WU XB, 2005, IN PRESS LANDSCAPE E 0921-2973 Landsc. Ecol.ISI:000235887300003New Mexico State Univ, USDA ARS, Las Cruces, NM 88003 USA. Univ New Mexico, Dept Biol, Albuquerque, NM 87131 USA. Univ Colorado, Dept Geol Sci, Boulder, CO 80309 USA. Valles Caldera Natl Preserve, Los Alamos, NM 87544 USA. New Mexico Nat Heritage Program, Albuquerque, NM 87131 USA. Peters, DPC, New Mexico State Univ, USDA ARS, Jornada Expt Range,Box 30003,MSC 3JER,2995 Knox S, Las Cruces, NM 88003 USA. debpeter@nmsu.eduEnglish|?@Peters, J. Verhoest, N. E. C. Samson, R. Boeckx, P. De Baets, B.2008hWetland vegetation distribution modelling for the identification of constraining environmental variables 1049-1065Landscape Ecology239Wetland ecosystems are of primary concern for nature conservation and restoration. Adequate conservation and restoration strategies emerge from a scientific comprehension of wetland properties and processes. Hereby, the understanding of plant species and vegetation patterns in relation to environmental gradients is an important issue. The modelling approaches in this study statistically relate vegetation patterns to measured environmental gradients in a lowland wetland ecosystem. Measured environmental gradients included groundwater quantity and quality aspects, soil properties and vegetation management. Among this variety, the objective was to identify the key environmental gradients constraining the vegetation, using recently developed methodologies within the modelling approaches. Comparison of results indicated that different environmental gradients were considered to be important by different methodologies.!://WOS:000260283100005Times Cited: 0 0921-2973WOS:00026028310000510.1007/s10980-008-9261-4 2<7Petit, C. C. Lambin, E. F.2002Impact of data integration technique on historical land-use/land-cover change: Comparing historical maps with remote sensing data in the Belgian Ardennes117-132Landscape Ecology172cartography data integration historical maps land-cover change landscape metrics map generalisation Northern European landscape remote sensing SENSED DATAArticleHistorical reconstructions of land-use/cover change often require comparing maps derived from different sources. The objective of this study was to measure land-use/cover changes over the last 225 years at the scale of a Belgian landscape, Lierneux in Ardennes, on the basis of a heterogeneous time series of land cover data. The comparability between the land-cover maps was increased following a method of data integration by map generalisation. Two types of time series were built by integrating the maps either by reference to the initial map of the time series or by pair of successive maps. Land-cover change detection was performed on the initial time series without data integration and on the two types of integrated time series. Results reveal that land cover and landscape structure have been subject to profound changes in Lierneux since 1775, with an annual rate of change at the landscape level of up to 1.40%. The major land-cover change processes observed are expansion of grasslands-croplands and reforestation with coniferous species, leading to a more fragmented landscape structure. The annual rates of land-cover change estimated from integrated data are significantly different from the annual rates of change estimated without a prior integration of the data. There is a trade-off between going as far back in time as possible versus performing change detection as accurately as possible.://000177049100002 .ISI Document Delivery No.: 577ET Times Cited: 13 Cited Reference Count: 26 Cited References: BUGMANN H, 2000, PAGES NEWSLETTER, V8, P26 CONGALTON RG, 1991, REMOTE SENS ENVIRON, V37, P35 COPPIN PR, 1996, REMOTE SENSING REV, V13, P207 COUSINS SAO, 2001, LANDSCAPE ECOL, V16, P41 DEFRIES RS, 1997, SCALE REMOTE SENSING, P231 DESLOOVER JR, 1980, MINISTERE BELGE AGR, V12 GOODCHILD M, 1992, ACCURACY SPATIAL DAT HOUGHTON RA, 1994, BIOSCIENCE, V44, P305 HOUGHTON RA, 1999, SCIENCE, V285, P574 HOYOIS G, 1949, ARDENNE ARDENNAIS JONES PD, 2001, SCIENCE, V292, P662 LAMBIN EF, 1997, PROG PHYS GEOG, V21, P375 LEMOINEISABEAU C, 1978, ACT C INT SPA 8 11 S, P8 LUVALL JC, 1997, SCALE REMOTE SENSING, P169 MOODY A, 1994, PHOTOGRAMM ENG REM S, V60, P585 OLDFIELD F, 2000, PAGES NEWSLETTER, V8, P21 PETIT CC, 2002, IN PRESS GLOBAL CHAN PETIT CC, 2002, INT J GEOGR INF SYST, V15, P785 REID RS, 2000, LANDSCAPE ECOL, V15, P339 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 ROBINSON A, 1978, ELEMENTS CARTOGRAPHY SALA OE, 2000, SCIENCE, V287, P1770 SINGH A, 1989, INT J REMOTE SENS, V10, P989 TURNER MG, 1991, QUANTITATIVE METHODS VERHEYEN K, 1999, J BIOGEOGR, V26, P1115 WICKHAM JD, 2000, LANDSCAPE ECOL, V15, P495 0921-2973 Landsc. Ecol.ISI:000177049100002Univ Louvain, Dept Geog, B-1348 Louvain, Belgium. Petit, CC, Univ Louvain, Dept Geog, 3 Pl Louis Pasteur, B-1348 Louvain, Belgium.English<7MPetit, S. Griffiths, L. Smart, S. S. Smith, G. M. Stuart, R. C. Wright, S. M.2004kEffects of area and isolation of woodland patches on herbaceous plant species richness across Great Britain463-471Landscape Ecology195BAncient Woodland Indicator species; connectivity; dispersal corridor; fragmentation; hedgerows; landscape structure; monitoring; species-area relationship ELLENBERG INDICATOR VALUES; AGRICULTURAL LANDSCAPE; CENTRAL LINCOLNSHIRE; POPULATION-SIZE; FOREST PATCHES; GROUND FLORA; LAND-COVER; VEGETATION; HABITAT; FRAGMENTATIONArticleRichness of Ancient Woodland Indicator plant species was analysed in 308 woodland patches that were surveyed during the Countryside Survey of Great Britain carried out in 1998. The Countryside Survey recorded vegetation plots and landscape structure in 569 stratified 1 km sample squares and developed a remotely-sensed land cover map of the UK. Using these datasets, we tested the hypothesis that Ancient Woodland Indicator species richness in woodland fragments was limited by patch area, shape and spatial isolation and that woodland patches located in the lowland region of Great Britain would respond differently than those in the upland region. The variation in Ancient Woodland Indicator species richness in the British lowlands (n = 218) was mainly explained by patch area and two measures of connectivity, the length of hedgerows and lines of trees in the 1 km square and the area of woodland within 500 m of the vegetation plot. By contrast, variation in Ancient Woodland Indicator species richness in the British uplands (n = 90) was related to Ellenberg scores of the vegetation communities sampled -a surrogate for habitat quality-and no significant effect of spatial structure was detected. It therefore appears that the degree of fragmentation of woodland in the British lowlands limits the distribution of Ancient Woodland Indicator species, while in the uplands, failed colonisation is a matter of habitat quality rather than a result of landscape structure.://000222941500001 ISI Document Delivery No.: 841OY Times Cited: 4 Cited Reference Count: 59 Cited References: *ESRI, 1991, ARC INFO *SAS I INC, 1999, SAS REL 8 02 BASTIN L, 1999, LANDSCAPE ECOL, V14, P493 BAUDRY J, 1985, THESIS U RENNES 1 FR BRUNET J, 2000, J VEG SCI, V11, P515 BUNCE RGH, 1996, J BIOGEOGR, V23, P625 BUNCE RGH, 1999, ECOFACT, V1 BUTAYE J, 2001, ECOGRAPHY, V24, P369 DIEKMANN M, 1997, J VEG SCI, V8, P855 DZWONKO Z, 1988, VEGETATIO, V76, P15 DZWONKO Z, 1993, J VEG SCI, V4, P693 ELLENBERG H, 1991, SCRIPTA GEOBOT, V18, P1 ERTSEN ACD, 1998, PLANT ECOL, V135, P113 FIRBANK LG, 2003, J ENVIRON MANAGE, V67, P207 FULLER RM, 2002, CARTOGR J, V39, P15 GRAAE BJ, 2000, J VEG SCI, V11, P881 GRASHOFBOKDAM C, 1997, J VEG SCI, V8, P21 HAINESYOUNG R, 2003, J ENVIRON MANAGE, V67, P267 HAINESYOUNG RH, 2000, ACCOUNTING NATURE AS HILL MO, 1997, J VEG SCI, V8, P579 HILL MO, 1999, ECOFACT, V2 HILL MO, 2000, J APPL ECOL, V37, P3 HONNAY O, 1999, BIOL CONSERV, V87, P73 HONNAY O, 1999, FOREST ECOL MANAG, V115, P157 HOWARD DC, 1991, 153 FRDA FOR CAN HOWARD DC, 2003, J ENVIRON MANAGE, V67, P219 JACKSON DL, 2000, 307 JOINT NAT CONS JACQUEMYN H, 2001, J BIOGEOGR, V28, P801 JACQUEMYN H, 2001, J VEG SCI, V12, P635 JACQUEMYN H, 2002, OECOLOGIA, V130, P617 KIRBY KJ, 2001, FORESTRY, V74, P219 KOERNER W, 1997, J ECOL, V85, P351 LAMIERE S, 2000, J VEG SCI, V11, P695 LEVENSON JB, 1981, FOREST ISLAND DYNAMI, P13 MASON CF, 2002, BIODIVERS CONSERV, V11, P1773 MATLACK GR, 1994, ECOLOGY, V75, P1491 MCCOLLIN D, 2000, J ENVIRON MANAGE, V60, P77 MENGES ES, 1991, GENETICS CONSERVATIO, P47 OUBORG NJ, 1995, J ECOL, V83, P369 PETERKEN GF, 1974, BIOL CONSERV, V6, P239 PETERKEN GF, 1981, J ECOL, V69, P781 PETERKEN GF, 1984, J ECOL, V72, P155 PETIT S, 2003, J ENVIRON MANAGE, V67, P229 POLLARD E, 1973, J ECOL, V61, P341 PRESTON CD, 2002, CHANGING FLORA UK RACKAM O, 1976, TREES WOODLANDS BRIT ROSE F, 1999, BRIT WILDLIFE, V10, P241 SARLOVHERLIN IL, 2000, LANDSCAPE ECOL, V15, P229 SCHAFFERS AP, 2000, J VEG SCI, V11, P225 SHAFFER ML, 1981, BIOSCIENCE, V31, P131 SMART SM, 2000, BIODIVERS CONSERV, V9, P811 SMART SM, 2001, HEDGEROWS WORLD THEI, P137 SMART SM, 2002, ENGLISH NATURE RES A, V461 SMART SM, 2003, J ENVIRON MANAGE, V67, P239 TERBRAAK CJF, 1986, MATH BIOSCI, V78, P57 THOMPSON K, 1994, BIODIVERSITY TEMPERA, P61 USHER MB, 1979, J APPL ECOL, V16, P213 VANRUREMONDE RHAC, 1991, J VEG SCI, V2, P377 WIDEN B, 1993, BIOL J LINN SOC, V50, P179 0921-2973 Landsc. Ecol.ISI:000222941500001LAncaster Environm Ctr, Ctr Ecol & Hydrol, Lancaster LA1 4AP, England. Ctr Ecol & Hydrol, Monks Wood Res Stn, Huntingdon PE28 2LS, Cambs, England. Petit, S, LAncaster Environm Ctr, Ctr Ecol & Hydrol, Lib Ave, Lancaster LA1 4AP, England. spet@ceh.ac.ukEnglish j<7r <Pettit, C. Bishop, I. Sposito, V. Aurambout, J. P. Sheth, F.2012SDeveloping a multi-scale visualisation framework for use in climate change response487-508Landscape Ecology274digital globes systems thinking climate change landscape planning landscape visualisation planning support-system landscape visualization scenic beauty national-park management realism perceptions australia scenarios benefitsApr^Climate change is predicted to impact countries, regions and localities differently. However, common to the predicted impacts is a global trend toward increased levels of carbon dioxide and rising sea levels. Governments and communities need to take into account the likely impacts of climate on the landscape, both built and natural. There is a growing and significant body of climate change research. Much of this information produced by domain experts for a range of disciplines is complex and difficult for planners, decision makers and communities to act upon. The need to communicate often complex scientific information which can be used to assist in the planning cycle is a key challenge. This paper draws from a range of international examples of the use of visualisation in the context of landscape planning to communicate climate change impact and adaptation options within the context of the planning cycle. Missing from the literature, however, is a multi-scalar approach which allows decision makers, planners and communities to seamlessly explore scenarios at their special level of interest, as well as to collectively understand what is driving these at a larger scale, and what the implications are at ever more local levels. Visualisation tools such as digital globes provide one way to bring together multi-scaled spatial-temporal datasets. We present an initial development with this goal in mind. Future research is required to determine the best tools for communicating particular complex scientific data and also to better understand how visualisation can be used to improve the landscape planning process.://000302346900003-919RS Times Cited:0 Cited References Count:78 0921-2973Landscape EcolISI:000302346900003Pettit, C Univ Melbourne, Fac Architecture Bldg & Planning, Architecture Bldg, Parkville, Vic 3010, Australia Univ Melbourne, Fac Architecture Bldg & Planning, Architecture Bldg, Parkville, Vic 3010, Australia Univ Melbourne, Fac Architecture Bldg & Planning, Parkville, Vic 3010, Australia Victorian Dept Primary Ind, Carlton, Vic 3052, Australia Univ Melbourne, Dept Infrastruct Engn, Parkville, Vic 3010, AustraliaDOI 10.1007/s10980-012-9716-5English? >Pezzi, Giovanna Maresi, Giorgio Conedera, Marco Ferrari, Carlo2011wWoody species composition of chestnut stands in the Northern Apennines: the result of 200 years of changes in land use 1463-1476Landscape Ecology2610Springer NetherlandsEarth and Environmental ScienceChestnut stands (orchards and coppices) are among the most typical elements of the southern European mountain landscape and a protected habitat (9260 Castanea sativa woods) according to the European Union (Directive 92/43/EEC). As an anthropogenic landscape, they require specific measures to address preservation or to guide their evolutionary trend. In the Northern Apennines, a landscape multiscalar-multitemporal approach was adopted to highlight factors that have acted on the evolution of this habitat and which still might affect either its preservation or its evolutionary dynamics. Using a diachronic GIS-approach, we analyzed old cadastral maps (drawn up 200 years ago), and aerial photographs. Both the present distribution pattern of the woody species and the incidence of important chestnut diseases were also surveyed. The factors explaining the current extent and species composition of the local chestnut forests confirm their status as an anthropogenic habitat. The present landscape distribution of chestnut woods is heavily linked to past human settlements. Chestnut blight and ink disease are more an indirect reason for past felling activities than an actual direct cause of damage to trees, because of the hypovirulence spread and the limited incidence of the ink disease. Vegetation dynamics of abandoned chestnut forests evolved only partly towards deciduous Beech and Hop Hornbeam stands, thus suggesting both the possibility of a recovery of this cultivation and the need for new criteria for its management.+http://dx.doi.org/10.1007/s10980-011-9661-8 0921-297310.1007/s10980-011-9661-8v<7Z*Pfeffer, K. Pebesma, E. J. Burrough, P. A.2003RMapping alpine vegetation using vegetation observations and topographic attributes759-776Landscape Ecology188alpine vegetation classification digital elevation model ordination universal kriging CANONICAL CORRESPONDENCE-ANALYSIS FUZZY K-MEANS PATTERNS AREA CLASSIFICATION ENVIRONMENT PREDICTION TERRAIN MODELSArticleLocal planning in mountain areas requires spatial information on site factors such as vegetation that is commonly lacking in rugged terrain. This study demonstrates a procedure for the efficient acquisition of a vegetation map using topographic attributes and nominal vegetation data sampled in the field. Topographic attributes were derived from a digital elevation model (DEM) and nominal vegetation data were reduced to normalised scores by detrended correspondence analysis (DCA). The procedure for mapping vegetation types addressed the relations between DCA scores and topographic attributes, spatial correlation of DCA scores and classification of predicted DCA scores based on a cluster analysis of DCA scores at observation locations. The modelled vegetation classes corresponded with the impression obtained in the field. We also showed that the final result is rather sensitive to which samples are included in the analysis.://000188716100003 ISI Document Delivery No.: 770HA Times Cited: 8 Cited Reference Count: 42 Cited References: *GETS, 2001, EUR RES NETW APPL GE *ILW DEP, 1998, ILW 2 1 WIND INT LAN BIE SW, 1973, PHOTOGRAMMETRIA, V29, P189 BIO AMF, 2000, THESIS UTRECHT BURROUGH PA, 1991, SPATIAL VARIABILITIE, P89 BURROUGH PA, 1998, PRINCIPLES GEOGRAPHI BURROUGH PA, 2000, FUZZY SET SYST, V113, P37 BURROUGH PA, 2001, LANDSCAPE ECOL, V16, P523 DAVIS JC, 1986, STAT DATA ANAL GEOLO ELLENBERG H, 1991, ZEIGERWERTE PFLANZEN FRANKLIN J, 1995, PROG PHYS GEOG, V19, P474 FRANKLIN J, 2000, TERRAIN ANAL PRINCIP, P331 GILLISON AN, 1985, J ENVIRON MANAGE, V20, P103 GOTTFRIED M, 1998, ARCTIC ALPINE RES, V30, P207 GRABHERR G, 1985, DAMAGE VEGETATION RE GUISAN A, 1998, J VEG SCI, V9, P65 GUISAN A, 1999, PLANT ECOL, V143, P107 GUISAN A, 2000, ECOL MODEL, V135, P147 GUISAN A, 2002, ECOL MODEL, V157, P89 HOERSCH B, 2002, COMPUTERS ENV URBAN, V26, P113 HORN BKP, 1981, P IEEE, V69, P14 JANSSEN LLF, 1991, KNOWLEDGE BASED IMAG JONGMAN R, 1995, DATA ANAL COMMUNITY MACQUEEN J, 1967, 5TH P BERK S MATH ST, V1, P281 MEENTEMEYER RK, 2000, LANDSCAPE ECOL, V15, P697 MOORE ID, 1991, HYDROL PROCESS, V5, P3 NAGENDRA H, 2001, INT J REMOTE SENS, V22, P2377 PEBESMA EJ, 1996, THESIS U UTRECHT UTR PEBESMA EJ, 1998, COMPUT GEOSCI, V24, P17 PFEFFER K, 2002, C P IEMS 2002 LUG 24, P24 PURTSCHELLER F, 1978, SAMMLUNG GEOLOGISCHE, V53, P1 REISIGL H, 1987, ALPENPFLANZEN LEBENS SKIDMORE AK, 1989, INT J GEOGR INF SYST, V3, P323 TAPPEINER U, 1998, ECOL MODEL, V113, P225 TERBRAAK CJF, 1986, ECOLOGY, V67, P1167 TERBRAAK CJF, 1987, VEGETATIO, V69, P69 TERBRAAK CJF, 1995, UNIMODAL MODELS RELA TERBRAAK CJF, 1998, CANOCO, V4 VANDAM O, 2001, THESIS UTRECHT WESSELING CG, 1996, T GIS, V1, P40 WILSON JP, 2000, TERRAIN ANAL PRINCIP, P1 ZEVENBERGEN LW, 1987, EARTH SURF PROCESSES, V12, P47 0921-2973 Landsc. Ecol.ISI:000188716100003Univ Utrecht, Fac Geog Sci, Utrecht Ctr Environm & Landscape Dynam 1, NL-3508 TC Utrecht, Netherlands. Pfeffer, K, Univ Utrecht, Fac Geog Sci, Utrecht Ctr Environm & Landscape Dynam 1, NL-3508 TC Utrecht, Netherlands. k.pfeffer@uva.nlEnglish<7b,Phillips, J. D. Gares, P. A. Slattery, M. C.19999Agricultural soil redistribution and landscape complexity197-211Landscape Ecology142soil landscape soil redistribution soil transformations landscape complexity entropy scale SELF-ORGANIZATION DETERMINISTIC UNCERTAINTY COASTAL-PLAIN EVOLUTION PEDOGENESIS EROSION MODELArticleApr-A number of hypotheses and conceptual models, particularly those emphasizing nonlinear dynamics and self-organization, postulate increases or decreases in complexity in the evolution of drainage basins, topography, soils, ecosystems, and other earth surface systems. Accordingly, it is important to determine under what circumstances and at what scales either trend might occur. This paper is concerned with changes in soil landscape complexity due to redistribution of sediment by fluvial, aeolian, and tillage processes at historical time scales in an agricultural field system near Grifton, North Carolina. Soil mapping and soil stratigraphic investigations were used to identify and map soil changes associated with erosion and deposition by water, wind, and tillage; reconstruct the pre-agricultural soil pattern; and identify transformations between soil types. The Kolmogorov entropy of the pre- and post-agricultural landscapes was then compared. The soil transformations associated with erosion and deposition coated four distinct new soils and made possible new transformations among soil series, increasing the number of soil types from seven to 11 and the number of possible transformations from 14 to 22. However, the entropy and complexity of the soil landscape decreased, with associated increases in information and redundancy. The mass redistributions created a lower-entropy landscape by concentrating particular soils and soil transformations in specific landscape settings. This result is contrary to studies showing a trend toward increasing pedological complexity at comparable spatial scales, but over much longer time scales. These results point to the importance of temporal scale, and to the fact that environmental complexity is influenced by factors other than the number of different landscape units present.://000079802500009 ISI Document Delivery No.: 187RV Times Cited: 18 Cited Reference Count: 36 Cited References: *SOIL SURV DIV STA, 1993, SOIL SURV MAN BROOKS DR, 1988, EVOLUTION ENTROPY BURROUGH PA, 1983, J SOIL SCI, V34, P577 CAMPBELL JB, 1979, ANN ASSOC AM GEOGR, V69, P544 CARTER RWG, 1991, COASTAL SEDIMENTS 91, P934 CULLING WEH, 1988, EARTH SURF PROCESSES, V13, P619 FULLEN MA, 1995, SOIL TECHNOL, V8, P1 HALLET B, 1990, EARTH-SCI REV, V29, P57 HUGGETT RJ, 1995, GEOECOLOGY EVOLUTION IBANEZ JJ, 1990, CATENA, V17, P573 IBANEZ JJ, 1994, Z GEOMORPHOL, V38, P105 IBANEZ JJ, 1995, CATENA, V24, P215 JOHNSON DL, 1987, SOIL SCI, V143, P349 JOHNSON DL, 1990, QUATERNARY RES, V33, P306 KAUFFMAN SA, 1993, ORIGINS ORDER SELF O KAY JJ, 1991, ENVIRON MANAGE, V15, P483 KING GJ, 1983, CAN J SOIL SCI, V63, P657 KLEISS HJ, 1994, SOIL SCI, V157, P373 KREZNOR WR, 1989, SOIL SCI SOC AM J, V53, P1763 LI M, 1997, INTRO KOLMOGOROV COM MCBRATNEY AB, 1992, AUST J SOIL RES, V30, P913 MCRAE SG, 1988, PRACTICAL PEDOLOGY MOKMA DL, 1996, J SOIL WATER CONSERV, V51, P171 NAHON DB, 1991, GEODERMA, V51, P5 PAHLWOSTL C, 1995, DYNAMIC NATURE ECOSY PHILLIPS J, 1995, GEOMORPHOLOGY, V14, P57 PHILLIPS J, 1997, GEOGR ANAL, V29, P1 PHILLIPS JD, 1988, EARTH SURFACE P LAND, V23, P481 PHILLIPS JD, 1993, PHYSICAL GEOGR, V14, P566 PHILLIPS JD, 1994, EARTH SURF PROCESSES, V19, P389 PHILLIPS JD, 1995, PROG PHYS GEOG, V19, P309 PHILLIPS JD, 1996, GEODERMA, V73, P147 PHILLIPS JD, 1996, SCI NATURE GEOMORPHO, P315 PHILLIPS JD, 1997, ANN ASSOC AM GEOGR, V87, P197 RIGON R, 1994, J GEOPHYS RES-SOLID, V99, P11971 ULANOWICZ RE, 1980, J THEOR BIOL, V85, P223 0921-2973 Landsc. Ecol.ISI:000079802500009Texas A&M Univ, Coll Geosci, Dept Geog, College Stn, TX 77843 USA. Phillips, JD, Texas A&M Univ, Coll Geosci, Dept Geog, College Stn, TX 77843 USA.English m|7Pickens, B. A. Root, K. V.2009_Behavior as a tool for assessing a managed landscape: a case study of the Karner blue butterfly243-251Landscape Ecology242management karner blue butterfly lycaeides melissa oak savanna oviposition disturbance fire prescribed burning spatial dynamics ohio (USA) lycaeides-melissa-samuelis oak savanna habitat quality host-plant fire frequency metapopulation oviposition lepidoptera diversity patternsFebIn an increasingly human-dominated landscape, effective management of disturbance-maintained ecosystems, such as grasslands and savannas, is critical to the conservation of biodiversity. Yet, the response of individual organisms to landscapes created by disturbances and management is rarely studied. In this study, we examined the endangered Karner blue butterfly, Lycaeides melissa samuelis, in a heterogeneous oak savanna. Our objective was to quantify the butterfly's habitat use and behavior to assess the effects of prescribed burning. The oak savanna management in Ohio, USA divides each Karner blue site (n = 4) into three units. Each one-third unit is then burned, mowed, or unmanaged in an annual rotation within each site, and the result is a fire return interval of similar to 3 years. Our surveys measured habitat use, while behavior observations quantified reproduction and foraging for the two annual broods. Our habitat use results showed burned treatments were recolonized quickly, but there was not a clear selection for burned treatments. Foraging rates were similar in all treatments; however, females oviposited significantly less in unmanaged treatments (only 5 of 127 ovipositions). This oviposition preference was likely due to habitat degradation and the availability of recently burned, early successional habitat. Since Karner blues avoided reproduction in units unburned for a parts per thousand yen4 years, these units could be burned to create high quality early successional habitat. These results demonstrate how behavioral decisions can be pivotal forces driving spatial population dynamics. Our case study demonstrates how a fine-scale landscape perspective combined with measurements of behavioral processes can assist with management decision-making.://000262828900008-399WB Times Cited:0 Cited References Count:52 0921-2973ISI:000262828900008Pickens, BA Louisiana State Univ, Sch Renewable Nat Resources, Rm 227,RNR Bldg, Baton Rouge, LA 70803 USA Louisiana State Univ, Sch Renewable Nat Resources, Baton Rouge, LA 70803 USA Bowling Green State Univ, Dept Biol Sci, Bowling Green, OH 43403 USADoi 10.1007/S10980-008-9302-ZEnglish9?s Piechnik, Denise2012^Agriculture, biodiversity, and markets: livelihoods and agroecology in comparative perspective617-619Landscape Ecology274Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-011-9690-3 0921-297310.1007/s10980-011-9690-3? IPiechnik, Denise Goslee, Sarah Veith, Tamie Bishop, Joseph Brooks, Robert2012mTopographic placement of management practices in riparian zones to reduce water quality impacts from pastures 1307-1319Landscape Ecology279Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9783-7 0921-297310.1007/s10980-012-9783-7?Pielke, R. A. R. Avissar1990>Influence of landscape structure on local and regional climate133-155Landscape Ecology42/3Sland use, climate, climate change, land use alteration, landscape patterns, weatherThis paper discusses the physical linkage between the surface and the atmosphere, and demonstrates how even slight changes in surface conditions can have a pronounced effect on weather and climate. Observational and modeling evidence are presented to demonstrate the influence of landscape type on the overlying atmospheric conditions. The albedo, and the fractional partitioning of atmospheric turbulent heat flux into sensible and latent fluxes is shown to be particularly important in directly affecting local and regional weather and climate. It is concluded that adequate assessment of global climate and climate change cannot be achieved unless mesoscale landscape characteristics and their changes over time can be accurately determined.Q|?U !Pierce, Andrew D. Taylor, Alan H.2011Fire severity and seed source influence lodgepole pine (Pinus contorta var. murrayana) regeneration in the southern cascades, Lassen volcanic National Park, California225-237Landscape Ecology262FebRocky Mountain lodgepole pine, (Pinus contorta var. latifolia) regenerates quickly after high severity fire because seeds from serotinous cones are released immediately post-fire. Sierra lodgepole pine (P. contorta var. murrayana) forests burn with variable intensity resulting in different levels of severity and because this variety of lodgepole pine does not have serotinous cones, little is known about what factors influence post-fire regeneration. This study quantifies tree regeneration in a low, moderate, and high severity burn patch in a Sierra lodgepole forest 24 years after fire. Regeneration was measured in ten plots in each severity type. In each plot, we quantified pre- and post-fire forest structure (basal area, density), counted and aged tree seedlings and saplings of all species, and measured distance to the nearest seed bearing tree. There was no difference in the density of seedlings and saplings among severity classes. Distance and direction to the nearest seed bearing lodgepole pine were the best predictors of lodgepole seedling and sapling density in high severity plots. In contrast to Rocky Mountain lodgepole pine, regeneration of Sierra lodgepole pine appears to rely on in-seeding from surviving trees in low or moderate severity burn patches or live trees next to high severity burn patches. Our data demonstrate that Sierra lodgepole pine follows stand development pathways hypothesized for non-serotinous stands of Rocky Mountain lodgepole pine.!://WOS:000286474900006Times Cited: 0 0921-2973WOS:00028647490000610.1007/s10980-010-9556-0<7'Pierce, K. B. Lookingbill, T. Urban, D.2005iA simple method for estimating potential relative radiation (PRR) for landscape-scale vegetation analysis137-147Landscape Ecology202aspect; DEM; GIS; solar insolation; species-environment interactions; topographic effects; vegetation distribution MOUNTAINOUS TERRAIN; FOREST ECOSYSTEM; SOIL-MOISTURE; NATIONAL-PARK; OAK FORESTS; CALIFORNIA; PATTERNS; GRADIENT; VARIABLES; CLIMATEArticleFeb3Radiation is one of the primary influences on vegetation composition and spatial pattern. Topographic orientation is often used as a proxy for relative radiation load due to its effects on evaporative demand and local temperature. Common methods for incorporating this information (i.e., site measures of slope and aspect) fail to include daily or annual changes in solar orientation and shading effects from local topography. As a result, these static measures do not incorporate the level of spatial and temporal heterogeneity required to examine vegetation patterns at the landscape level. We developed a widely applicable method for estimating potential relative radiation (PRR) using digital elevation data and a widely used geographic information system (Arc/Info). We found significant differences among four increasingly comprehensive radiation proxies. Our GIS-based proxy compared well with estimates from more data-intensive and computationally rigorous radiation models. We note that several recent studies have not found strong correlations between vegetation pattern and landscape-scale differences in radiation. We suggest that these findings may be due to the use of proxies that were not accurately capturing variability in radiation, and we recommend PRR or similar measures for use in future vegetation analyses.://000230299600002 ISI Document Delivery No.: 942RN Times Cited: 1 Cited Reference Count: 53 Cited References: *ESRI, 1994, ENV SYST AUSTIN MP, 1990, ECOL MONOGR, V60, P161 BAND LE, 1991, ECOL MODEL, V56, P171 BEERS TW, 1966, J FOREST, V64, P691 BOLSTAD P, 1998, LANDSCAPE ECOLOGY, V13, P695 BONAN GB, 1988, THESIS U VIRGINIA CH BROWN DG, 1994, J VEG SCI, V5, P641 BUNN AG, 2003, ARCT ANTARCT ALP RES, V35, P323 CALLAWAY RM, 1998, AM MIDL NAT, V118, P107 CAMPBELL GS, 1998, INTRO ENV BIOPHYSICS CHEN JQ, 1999, BIOSCIENCE, V49, P288 CLINTON BD, 1994, AM MIDL NAT, V132, P308 DALY C, 1994, J APPL METEOROL, V33, P140 DAVIS FW, 1990, LANDSCAPE ECOL, V4, P69 DAY FP, 1974, ECOLOGY, V55, P1064 DONNEGAN JA, 1999, ECOLOGY, V80, P1370 DOZIER J, 1990, IEEE T GEOSCI REMOTE, V28, P963 DUBAYAH R, 1995, INT J GEOGR INF SYST, V9, P405 DUBAYAH RC, 1994, J VEG SCI, V5, P627 DYRNESS CT, 1974, PRELIMINARY CLASSIFI FRANK EC, 1966, RM18 USDA FOR SERV FRANKLIN J, 1998, J VEG SCI, V9, P733 FRANKLIN J, 2000, TERRAIN ANAL PRINCIP, P331 FRANKLIN JF, 1988, NATURAL VEGETATION O FU P, 1999, P 19 ANN ESRI US C S GEIGER RJ, 1965, CLIMATE NEAR GROUND GREENLAND D, 1996, 930477 PNW USDA FOR GRIER CC, 1977, ECOL MONOGR, V47, P373 GUISAN A, 1998, J VEG SCI, V9, P65 KESSELL SR, 1979, GRADIENT MODELING RE KLEIN SA, 1977, SOL ENERGY, V19, P325 LOOKINGBILL T, 2004, LANDSCAPE ECOL, V19, P417 LOOKINGBILL TR, 2003, AGR FOREST METEOROL, V114, P141 MACKEY BG, 2000, TERRAIN ANAL PRINCIP, P391 MCCAY DH, 1997, J TORREY BOT SOC, V124, P160 MCKENNEY DW, 1999, INT J GEOGR INF SCI, V13, P49 MILLER C, 1999, ECOL MODEL, V114, P113 NIKOLOV NT, 1992, ECOL MODEL, V61, P149 PARK AD, 2001, FOREST ECOL MANAG, V144, P213 PARKER AJ, 1995, B TORREY BOT CLUB, V122, P58 RAVEN PH, 1992, BIOL PLANTS RUNNING SW, 1987, CAN J FOREST RES, V17, P472 SMITH J, 2002, THESIS OREGON STATE STEPHENSON NL, 1993, T P SERIES, V9, P93 STEPHENSON NL, 1998, J BIOGEOGR, V25, P855 SWANSON FJ, 1988, BIOSCIENCE, V38, P92 THORNTON PE, 1997, J HYDROL, V190, P214 URBAN DL, 2000, LANDSCAPE ECOL, V15, P603 VANKAT JL, 1978, J BIOGEOGR, V5, P377 WHITTAKER RH, 1956, ECOL MONOGR, V26, P1 WHITTAKER RH, 1960, ECOL MONOGR, V30, P279 WILSON JP, 2000, TERRAIN ANAL PRINCIP, P97 YEAKLEY JA, 1998, HYDROL EARTH SYST SC, V2, P41 0921-2973 Landsc. Ecol.ISI:000230299600002Duke Univ, Nicholas Sch Environm & Earth Sci, Durham, NC 27708 USA. Pierce, KB, Duke Univ, Nicholas Sch Environm & Earth Sci, Durham, NC 27708 USA. kpierce@fs.fed.usEnglish5?"Pierce, lars L. Running, Steven W.1995mThe effects of aggregating sub-grid land surface variation on large-scale estimates of net primary production239-253Landscape Ecology104Rnet primary production, landscape aggregation, ecosystem process model, bias, MAUPGot the journal[|7X Pierce, L. L. Running, S. W.1995lThe Effects of Aggregating Subgrid Land-Surface Variation on Large-Scale Estimates of Net Primary Production239-253Landscape Ecology104Inet primary production landscape aggregation ecosystem process model biasAugThe use of large grid cell databases (1/2 degrees to 5 degrees) to drive nonlinear ecosystem process models may create an incompatibility of scales which can often lead to biased outputs. Global simulations of net primary production (NPP) often assume that bias due to averaging of sub-grid variations in climate, topography, soils, and vegetation is minimal, yet the magnitude and behavior of this bias on estimates of NPP are largely unknown. The effects of averaging sub-grid land surface variations on NPP estimates were evaluated by simulating a 1 degrees x 1 degrees land surface area as represented by four successive levels of landscape complexity, ranging from a single computation to 8,456 computations of NPP for the study area. Averaging sub-grid cell landscape variations typical of the northern US Rocky Mountains can result in overestimates of NPP as large as 30%. Aggregating climate within the 1 degrees cell contributed up to 50% of the bias to NPP estimates, while aggregating topography, soils, and vegetation was of secondary importance. Careful partitioning of complex landscapes can efficiently reduce the magnitude of this overestimation.://A1995RP98800006-Rp988 Times Cited:29 Cited References Count:0 0921-2973ISI:A1995RP988000066Pierce, Ll Univ Montana,Sch Forestry,Missoula,Mt 59812English|?W+Pierri-Daunt, Ana Beatriz Tanaka, Marcel O.2014kAssessing habitat fragmentation on marine epifaunal macroinvertebrate communities: an experimental approach17-28Landscape Ecology291JaniHabitat fragmentation is considered a major cause of biodiversity loss, both on terrestrial and marine environments. Understanding the effects of habitat fragmentation on the structure and dynamics of natural communities is extremely important to support management actions for biodiversity conservation. However, the effects of habitat fragmentation on marine communities are still poorly understood. Here we evaluated whether habitat fragmentation affects the structure of epifaunal communities in the sublittoral zone, in the northern coast of So Paulo state, Brazil. Five experimental landscapes were constructed, each one forming a large continuous patch. After 4 weeks, each landscape was cut on three patches of different sizes. Epifaunal macroinvertebrate communities were sampled at the edge and interior of experimental landscapes before manipulation to evaluate edge effects. After four more weeks, communities from the three patch sizes were also sampled to evaluate patch size effects. We compared the diversity of communities at different levels of fragmentation by total abundance, rarefied taxon richness, Shannon-Wiener diversity index, Simpson's dominance index, and abundance of dominant taxa. Higher taxon richness and gastropod abundance were recorded in the patch edges, but no significant differences were found among patch sizes. We found a significant effect of habitat fragmentation, with lower abundances of Gammaridea (the dominant taxon), Ophyuroidea, and Pycnogonida after the experimental fragmentation. Lower abundances of dominant taxa resulted in higher diversity and lower dominance in fragmented landscapes when compared to integral, pre-manipulation landscapes. Our results suggest that fragmentation of landscapes in the system studied can reduce dominance, and that even small patch sizes can be important for the conservation of macroinvertebrate diversity.!://WOS:000330827600002Times Cited: 0 0921-2973WOS:00033082760000210.1007/s10980-013-9970-1<7APieterse, N. M. de Venterink, H. Schot, P. P. Verkroost, A. W. M.2005[Is nutrient contamination of groundwater causing eutrophication of groundwater-fed meadows?743-753Landscape Ecology206chloride tracing; ecological restoration; environmental quality; groundwater pollution; nature management; nutrient-enrichment FRESH-WATER WETLANDS; VEGETATION RESPONSE; N-MINERALIZATION; NITRATE REMOVAL; CHESAPEAKE BAY; COASTAL-PLAIN; WET MEADOWS; LAND-USE; PHOSPHORUS; FORESTArticleSepThere is an ongoing debate as to whether nutrient contamination of groundwater under agricultural fields may cause nutrient-enrichment and subsequent eutrophication in discharge areas. Often, there is only circumstantial evidence to support this supposition (proximity of agricultural fields, direction of water flow, highly productive vegetation). Research on solute transport along a flow path is necessary to evaluate the risk for eutrophication. In this paper we present results of such a study. Two transects were established in a discharge meadow, a few meters downstream from fertilized cornfields. Highly productive vegetation in parts of the meadow suggested nutrient-enrichment caused by inflow of contaminated groundwater. This supposition was supported by an analysis of groundwater flow paths, residence times and chloride as tracer for pollution. However, the fate of nutrients along the flow path indicated otherwise. While we found high concentrations of DIN (dissolved inorganic nitrogen), P and K under the cornfields, DIN and P concentrations drop below detection limit when groundwater enters the meadow. Only K progressed into the meadow but did not enter the root zone. We conclude that (1) polluted groundwater from the cornfields did not cause the nutrient-enrichment, as indicated by the highly productive vegetation. Restoration projects in discharge areas should not focus upon measures in upstream areas if only circumstantial evidence is available. Solute transport should be considered as well. (2) Because K clearly showed to be the most mobile nutrient, its importance for nutrient-enrichment in discharge wetlands merits more attention in future research.://000233600700009 O ISI Document Delivery No.: 988KS Times Cited: 1 Cited Reference Count: 56 Cited References: 1992, UN C ENV DEV UN RIO, V1 *NETH STAT, 1998, STATL ALTMAN SJ, 1995, J ENVIRON QUAL, V24, P707 APPELO CAJ, 1993, GEOCHEMISTRY GROUNDW BARRY DAJ, 1993, J ENVIRON QUAL, V22, P767 BIJLMAKERS LL, 1987, LANDSCHAP, V4, P49 BOHLKE JK, 1995, WATER RESOUR RES, V31, P2319 BOUTT DF, 2001, GROUND WATER, V39, P24 CHAPIN FSI, 2002, PRINCIPLES TERRESTRI DAVIS JC, 1986, STAT DATA ANAL GEOLO DORGE J, 1994, ECOL MODEL, V75, P409 GARRITSEN AC, 1988, STROMINGSSTELSELS WA GROOTJANS AP, 1985, ACTA OECOL-OEC PLANT, V6, P403 GROOTJANS AP, 1986, ACTA OECOL-OEC PLANT, V7, P3 GROSS KL, 1995, J ECOL, V83, P357 HESSEN DO, 1997, WATER RES, V31, P1813 HILL AR, 1996, J ENVIRON QUAL, V25, P743 HURLBERT SH, 1984, ECOL MONOGR, V54, P187 JEMISON JM, 1994, J ENVIRON QUAL, V23, P337 KHAKURAL BR, 1993, J ENVIRON QUAL, V22, P839 KOERSELMAN W, 1992, FENS BOGS NETHERLAND, P397 KRONVANG B, 1992, WATER RES, V26, P1347 LOWRANCE R, 1995, J ENVIRON QUAL, V24, P808 LOWRANCE R, 1997, ENVIRON MANAGE, V21, P687 MALTBY E, 1994, GLOBAL WETLANDS OLD, P637 MARTIN JF, 1997, ECOL MODEL, V105, P1 MCCOLLIN D, 2000, BIOL CONSERV, V92, P249 MEIJBOOM F, 1991, ROOT ECOLOGY ITS PRA MEYER JL, 1979, ECOLOGY, V60, P1255 NORTON MM, 2000, ECOL ENG, V14, P337 OENEMA O, 1995, 1 LNV VROM V W OLFF H, 1994, PLANT SOIL, V163, P217 OOMES MJM, 1996, J APPL ECOL, V33, P576 PEDROLI GBM, 1989, THESIS U AMSTERDAM PIETERSE NM, 1998, DEMONSTRATION PROJEC, V2 PIETERSE NM, 1998, DEMONSTRATION PROJEC, V3 POIANI KA, 1996, LANDSCAPE ECOL, V11, P237 REFSGAARD JC, 1999, J HYDROL, V221, P117 RICH TCG, 1996, BIOL CONSERV, V75, P217 RICHARDSON CJ, 1985, SCIENCE, V228, P1424 SCHAMINEE JHJ, 1996, VEGETATIE NEDERLAND SCHNABEL RR, 1996, J ENVIRON QUAL, V25, P1230 SCHOT PP, 1992, J HYDROL, V134, P297 SPALDING RF, 1993, J ENVIRON QUAL, V22, P392 STANNERS D, 1995, EUROPES ENV DOBRIS A STUYFZAND PJ, 1983, H 2 O, V16, P87 VANDERAART PJM, 1988, LANDSCAP, V5, P253 VANDUREN IC, 1997, PLANT ECOL, V133, P91 VENTERINK HO, 2002, ECOL APPL, V12, P1010 VENTERINK HO, 2002, PLANT SOIL, V243, P119 VERHOEVEN JTA, 1988, VEGETATION INLAND WA, P249 VERHOEVEN JTA, 1996, TRENDS ECOL EVOL, V11, P494 VIGHI M, 1991, J ENVIRON QUAL, V20, P439 WEERTS HTJ, 1996, COMPLEX CONFINING LA WILLEMS HPL, 1997, WATER RES, V31, P841 WOSTEN JHM, 1994, 18 SCDLO 0921-2973 Landsc. Ecol.ISI:000233600700009Univ Utrecht, Fac Geosci, NL-3508 TC Utrecht, Netherlands. Pieterse, NM, Netherlands Inst Spatial Res, POB 30314, NL-2500 GH The Hague, Netherlands. pieterse@rpb.nlEnglishL<7NPieterse, N. M. Verkroost, A. W. M. Wassen, M. Venterink, H. O. Kwakernaak, C.2001NA decision support system for restoration planning of stream valley ecosystems69-81Landscape Ecology17 supplement 1decision support systems ecological economics ecological models landscape planning restoration VEGETATION RESPONSE ECOLOGICAL MODELS NETHERLANDS MANAGEMENT HYDROLOGY SCALES RANGE GISArticleDespite efforts that have been put into conservation, there is a continuing loss of species and ecosystems in Western Europe. There is a growing awareness that restoration is an essential step to stop this tide. Unfortunately, there is lack of understanding about the multitude of functions and the complexity of spatial interactions in a landscape. The focus of this paper is to demonstrate that an Integrated Decision Support System (IDSS) is indispensable to offer insight in this complexity and to design efficient restoration programmes. The IDSS is applied in a lowland catchment on the border between The Netherlands and Belgium and leads to the following recommendations: (1) The site conditions on the location where restoration is planned must be close to the range that is required for the target ecosystem. (2) The manager has to decide for the most attainable targetecosystem, and accept the inevitable loss of other ecosystems as a result from this choice. (3) Restoration planning involves that the optimal measure for each catchment, subcatchment or region is assessed, being ecological, urban or agricultural. (4) For each ecosystem an optimal set of measures must be selected. An analysis of the restoration efficiency (ecological gain divided by economic costs) is crucial for this selection.://000176041000007 ISI Document Delivery No.: 559TG Times Cited: 5 Cited Reference Count: 44 Cited References: 1990, VEGETATIEONDERZOEK, V5 BERVOETS L, 1990, ONDERZOEK NAAR VERSP BIO AMF, 2000, THESIS UTRECHT U UTR BURROUGH PA, 1995, ASA CSSA SSSA BOUYOU CLEMEN T, 1998, ECOL MODEL, V108, P107 CONNOLLY RD, 1997, J HYDROL, V193, P183 COSTANZA R, 1996, ECOL APPL, V6, P978 DEBLUST G, 1985, D1985250521 MIN VOLK DEWIT M, 1999, THESIS UTRECHT U UTR DEWIT MJM, 2000, HYDROBIOLOGIA, V410, P123 DODDS WK, 1998, WATER RES, V32 FITZ HC, 1996, ECOL MODEL, V88, P263 GARRITSEN AC, 1993, CHO TNO M ED NETH, P67 GROOTJANS AP, 1980, INT S IVV 1979, P143 GROOTJANS AP, 1985, ACTA OECOL-OEC PLANT, V6, P403 GROSSMANN WD, 1994, ECOL MODEL, V75, P21 HARBAUGH AW, 1990, COMPUTER PROGRAM CAL HEUVELINK GBM, 1989, INT J GEOGR INF SYST, V3, P303 KLUGE W, 1994, ECOL MODEL, V75, P399 KWAKERNAAK C, 1998, RIVER DOMMEL, V7 LATOUR JB, 1993, SCI TOTAL ENVIRON S, P1513 LUIJENDIJK J, 1997, H2O, V30, P100 LUIJENDIJK J, 1997, H2O, V30, P705 MCCOLLIN D, 2000, BIOL CONSERV, V92, P249 MILLER D, 1994, ENV INFORMATION MANA, P497 OOMES MJM, 1996, J APPL ECOL, V33, P576 PEDROLI GBM, 1989, THESIS U AMSTERDAM A PEDROLI GBM, 1990, LANDSCAPE ECOL, V4, P237 PIETERSE NM, 1998, RIVER DOMMEL, V2 PIETERSE NM, 1998, RIVER DOMMEL, V3 QIONG G, 1997, ECOL MODEL, V98, P163 RICH TCG, 1996, BIOL CONSERV, V75, P217 RUNHAAR J, 1996, BIOL CONSERV, V76, P269 RUNHAAR J, 1997, WETLANDS, V17, P528 STANNERS D, 1995, EUROPES ENV DOBRIS A THUNNISSEN HR, 1992, GRONDGEBRUIKSDATABAN, V168 TURNER RK, 2000, ECOL ECON, V35, P7 VANHORSSEN PW, 1999, LANDSCAPE ECOL, V14, P253 VANIERLAND EC, 1996, ECOL ENG, V7, P251 VENTERINK HO, 1997, ECOL MODEL, V101, P347 VENTERINK HO, 1998, RIVER DOMMEL, V5 VENTERINK HO, 1998, RIVER DOMMEL, V6 VERDONSCHOT PFM, 1990, THESIS WAGENINGEN AG WITTE JPM, 1993, USE HYDROECOLOGICAL, P31 Suppl. 1 0921-2973 Landsc. Ecol.ISI:000176041000007Univ Utrecht, Dept Environm Sci, NL-3508 TC Utrecht, Netherlands. Alterra Green World Res, Dept Water & Environm, Wageningen, Netherlands. Pieterse, NM, Dept Watermanagement & Hydrol, Grontmij Grp, POB 203, NL-3730 AE De Bilt, Netherlands. nico.pieterse@geog.uu.nlEnglish-?KN. M. Pieterse A. W. M. Verkroost M. Wassen H. Olde Venterink C. Kwakernaak2002NA decision support system for restoration planning of stream valley ecosystems69-81Landscape Ecology170fDecision support systems - Ecological economics - Ecological models - Landscape planning - Restoration Despite efforts that have been put into conservation, there is a continuing loss of species and ecosystems in Western Europe. There is a growing awareness that restoration is an essential step to stop this tide. Unfortunately, there is lack of understanding about the multitude of functions and the complexity of spatial interactions in a landscape. The focus of this paper is to demonstrate that an Integrated Decision Support System (IDSS) is indispensable to offer insight in this complexity and to design efficient restoration programmes. The IDSS is applied in a lowland catchment on the border between The Netherlands and Belgium and leads to the following recommendations: (1) The site conditions on the location where restoration is planned must be close to the range that is required for the target ecosystem. (2) The manager has to decide for the most attainable targetecosystem, and accept the inevitable loss of other ecosystems as a result from this choice. (3) Restoration planning involves that the optimal measure for each catchment, subcatchment or region is assessed, being ecological, urban or agricultural. (4) For each ecosystem an optimal set of measures must be selected. An analysis of the restoration efficiency (ecological gain divided by economic costs) is crucial for this selection. *http://dx.doi.org/10.1023/A:1015233811203 $10.1023/A:1015233811203 N. M. Pieterse Email: nico.pieterse@geog.uu.nl References Anonymous, 1990. Vegetatieonderzoek. 5: Kartering Midden-en Oost-Brabant. Karteerhandleiding, Provincie Noord-Brabant. Reeks Landschapsonderzoek no.13, Den Bosch, The Netherlands. Bervoets L. and Schneiders A. 1990. Onderzoek naar de Verspreiding en de typologie van de ecologisch waardevolle waterlopen in het Vlaamse gewest. Algemene Methodologie, Rapport Universitaire Instelling Antwerpen, Antwerpen, Belgium. Bio A.M.F. 2000. Does Vegetation Suit our Models. Data and Model Assumptions and the Assessment of Species Distribution in Space. Ph.D. Thesis, Utrecht University, Utrecht, The Netherlands, 192 pp. Burrough P.A. 1995. 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Coördinatiecentrum van de Biologische Waarderingskaart. De Wit M. 1999. Nutrient Fluxes in the Rhine and Elbe Basins. Ph.D. Thesis, Utrecht University, Utrecht, The Netherlands, 163 pp. De Wit M. 2000. Modelling nutrient fluxes from source to river load: a macroscopic analysis applied to the Rhine and Elbe basins. Hydrobiologia 410: 123-130. Dodds W.K., Hones J.R. and Welch E.B., 1998. Suggested classification of stream trophic state: Distributions of temperate stream types by chlorophyll, total nitrogen, and phosphorus. Water Res. 32(5). Fitz H.C. et al. 1996. Development of a general ecosystem model for a range of scales and ecosystems. Ecol. Model., 88: 263-295. Garritsen A.C. 1993. Linking hydrological and ecological models, The use of hydro-ecological models in the Netherlands: CHOTNO meeting, Ede, The Netherlands, pp. 67-79. Grootjans A.P. 1980. Distribution of plant communities along rivulets in relation to hydrology and management. In: O. Wilmanns and R. Tüxen (eds.), Berichte über die internationalen symposien der I.V.V. 1979. Cramer verlag, Germany, pp. 143-170. Grootjans A.P., Schipper P.C. and van der Windt H.J. 1985. Influence of drainage on N-mineralisation and vegetation response in wet meadows I. Calthion palustris stands. Acta Oecol., 6(20): 403-417. Grossmann W.D. 1994. Socio-economic ecological models: criteria for evaluation of state-of-the-art models shown on four case studies. Ecol. Model. 75/76: 21-36. Harbaugh A.W., 1990. A computer program for calculating subregional water budgets using results from the U.S. Geological Survey modular finite-difference ground-water flow model, U.S. Geological Survey, Reston, Virginia, USA. Heuvelink G.B.M., Burrough P.A. and Stein A., 1989. Propagation of errors in spatial modeling with GIS. Internl. J. Geogr. Inform. Syst. 3(4): 303-322. Kluge W., Muller-Buschbaum P. and Theesen L. 1994. Parameter acquisition for modelling exchange processes between terristrial and aquatic ecosystems. Ecol. Model. 75/76: 399-408. Kwakernaak C., Van der Windt N., Van der Gaast J., Van Os J. and Pieterse N.M. 1998. Demonstration Project for the Development of Integrated Management Plans for Catchment Areas of Small Trans-Border Lowland Rivers: The River Dommel. 7. Naar een ecologisch herstel van het Dommeldal; Scenario's voor het EU-project LIFE-Dommel, Winand Staring Centrum for Integrated Land, Soil and Water Research (SC-DLO), Wageningen, The Netherlands. Latour J.B. and Reiling R. 1993. A multiple stress model for vegetation ('MOVE'); a tool for scenario studies and standard setting. Sci. Total Environ. Suppl: 1513-1526. Luijendijk J. and Helmich F.A.M. 1997. Hydrologische bufferzones tegen verdere verdroging natuurgebieden. Praktijkstudie provincie Noord-Brabant. H2O 30(4): 100-103. Luijendijk J. and Straatman R. 1997. Ecohydrologische effectvoorspelling winplaats Luyksgestel. H2O 30(23): 705-708. McCollin D., Moore L. and Sparks T. 2000. The flora of a cultural landscape: environmental determinants of change revealed using archival sources. Biol. Conserv., 92: 249-263. Miller D. 1994. Coupling of process-based vegetation models to GIS and knowledge-based systems for analysis of vegetation change. In W.K. Michenen, J.W. Brunt and S.G. Stafford (eds.), Environmental Information Management and Analysis: Ecosystem to Global Scales. Taylor & Francis, New York, NY, USA, pp. 497-509. Olde Venterink H., Pieterse N.M., Wassen M.J. and Verkroost A.W.M. 1998a. Demonstration Project for the Development of Integrated Management Plans for Catchment Areas of Small Trans-Border Lowland Rivers: The River Dommel. 5. Alnion, an Ecohydrological Response Model for Wet and Moist Woodlands in Brook Valleys. Department of Environmental Science, Utrecht University, Utrecht, The Netherlands. Olde Venterink H., Pieterse N.M., Wassen M.J. and Verkroost A.W.M. 1998b. Demonstration Project for the Development of Integrated Management Plans for Catchment Areas of Small Trans-Border Lowland Rivers: The River Dommel. 6. Ecostream, A Response Model for Aquatic Ecosystems in Lowland Streams., Department of Environmental Science, Utrecht University, Utrecht, The Netherlands. Olde Venterink H. and Wassen M.J. 1997. A comparison of six models predicting vegetation response to hydrological habitat change. Ecol. Model. 101: 347-261. Oomes M.J.M., Olff H. and Altena H.J. 1996. Effects of vegetation management and raising the water table on nutrient dynamics and vegetation change in a wet grassland. J. Appl. Ecol. 33: 576-588. Pedroli G.B.M. 1989. The Nature of Landscape. PhD Thesis, University of Amsterdam, Amsterdam, The Netherlands. Pedroli G.B.M. and Borger G.J., 1990. Historical land use and hydrology, a case study from eastern Noord-Brabant. Landscape Ecol. 4: 237-248. Pieterse N.M., Olde Venterink H., Schot P.P. and Verkroost A.W.M. 1998a. 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A GIS-based plant prediction model for wetland ecosystems. Landscape Ecol., 14: 253-265. van Ierland E.C. and de Man, N.Y.H. 1996. Ecological engineering: First steps towards economic analysis. Ecol. Engin. 7: 251-371. Verdonschot P.F.M. 1990. Ecological Characterization of Surface Waters in the Province of Overijssel. PhD Thesis, Wageningen Agricultural University, Wageningen, The Netherlands, 255 pp. Witte J.P.M., Groen C.L.G., van der Meijden R. and Nienhuis J.G. 1993. DEMNAT: a national model for the effects of water management on the vegetation. In: J.C. Hooghart and C.W.S. Posthumus (eds.), The use of hydro-ecological models in the Netherlands. TNO Committee on Hydrological Research, Ede, The Netherlands, pp. 31-51 N. M. Pieterse1, 2 , A. W. M. Verkroost1, M. Wassen1, H. Olde Venterink1, 3 and C. Kwakernaak4 (1) Department of Environmental Science, Utrecht University, The Netherlands (2) Present address: Grontmij Group, Department of Watermanagement and Hydrology, PO Box 203, 3730 AE De Bilt, The Netherlands (3) Present address: IHE, Wetland Ecosystems, PO Box 3015, 2601 DA Delft, The Netherlands (4) Department of Water and the Environment, Alterra Green World Research, Wageningen, The Netherlands %? Pijanowski, Bryan Farina, Almo20117Introduction to the special issue on soundscape ecology 1209-1211Landscape Ecology269Springer NetherlandsEarth and Environmental Science+http://dx.doi.org/10.1007/s10980-011-9655-6 0921-297310.1007/s10980-011-9655-6? IPijanowski, Bryan Farina, Almo Gage, Stuart Dumyahn, Sarah Krause, Bernie2011SWhat is soundscape ecology? An introduction and overview of an emerging new science 1213-1232Landscape Ecology269Springer NetherlandsEarth and Environmental ScienceWe summarize the foundational elements of a new area of research we call soundscape ecology. The study of sound in landscapes is based on an understanding of how sound, from various sources—biological, geophysical and anthropogenic—can be used to understand coupled natural-human dynamics across different spatial and temporal scales. Useful terms, such as soundscapes, biophony, geophony and anthrophony, are introduced and defined. The intellectual foundations of soundscape ecology are described—those of spatial ecology, bioacoustics, urban environmental acoustics and acoustic ecology. We argue that soundscape ecology differs from the humanities driven focus of acoustic ecology although soundscape ecology will likely need its rich vocabulary and conservation ethic. An integrative framework is presented that describes how climate, land transformations, biodiversity patterns, timing of life history events and human activities create the dynamic soundscape. We also summarize what is currently known about factors that control temporal soundscape dynamics and variability across spatial gradients. Several different phonic interactions (e.g., how anthrophony affects biophony) are also described. Soundscape ecology tools that will be needed are also discussed along with the several ways in which soundscapes need to be managed. This summary article helps frame the other more application-oriented papers that appear in this special issue.+http://dx.doi.org/10.1007/s10980-011-9600-8 0921-297310.1007/s10980-011-9600-8|? sPijanowski, B. C. Iverson, L. R. Drew, C. A. Bulley, H. N. N. Rhemtulla, J. M. Wimberly, M. C. Bartsch, A. Peng, J.2010tAddressing the interplay of poverty and the ecology of landscapes: a Grand Challenge Topic for landscape ecologists?5-16Landscape Ecology251-We argue for the landscape ecology community to adopt the study of poverty and the ecology of landscapes as a Grand Challenge Topic. We present five areas of possible research foci that we believe that landscape ecologists can join with other social and environmental scientists to increase scientific understanding of this pressing issue: (1) scale and poverty; (2) landscape structure and human well-being; (3) social and ecological processes linked to spatial patterns in landscapes; (4) conservation and poverty, and (5) applying the landscape ecologist's toolkit. A brief set of recommendations for landscape ecologists is also presented. These include the need to utilize broad frameworks that integrate social and ecological variables, build capacity to do this kind of work through the development of strong collaborations of researchers in developed and developing countries, create databases in international locations where extreme poverty exists, and create a new generation of researchers capable of addressing this pressing social and environmental issue.!://WOS:000273479100002Times Cited: 1 0921-2973WOS:00027347910000210.1007/s10980-009-9415-zm?G)G. Pinay A. Fabre Ph. Vervier F. Gazelle1992:Control of C,N,P distribution in soils of riparian forests121-132Landscape Ecology63>floodplain, geomorphology, sediment, nutrients, organic carbonIt is now well accepted that riparian forests have an important role in regulating upstream/downstream flow of matter and energy in river ecosystems. Since geomorphic processes determine the structure of channels and floodplains, we have investigated whether different geomorphic features of riparian forests had any effects on the ability of their soils to retain nutrients and organic carbon. Willow riparian forests were chosen within the annual floodplain of the Garonne River, southwest France, to represent two different geomorphic types. Erosional types of riparian forests (E-type) were characterized by sand deposition on their soils because of high current velocity which hampered fine particle deposition. Depositional types of riparian forests (D-type) were characterized by slower overflow velocity; consequently silt and clay were dominant in their soils. Soil samples were taken at the end of the vegetation growth period, coinciding with low water levels prior to annual floods. Erosion and sedimentation processes affected the distribution of total C,N, and P contents in riparian forest soils, since they were significantly correlated with soil grain size. D-type riparian forest soils act as a sink for upstream/downstream nutrients and carbon flows during floods through accumulation of total C,N and P from year to year. In contrast, E-type riparian forests act as potential nutrient sources during high water periods, since they may release from their soils large amounts of easily available C, N and P into the river. These results demonstrate that nutrients and carbon retention ability of riparian forests soils should be analyzed through their geomorphic features rather than by their vegetation composition. Even if they belong to the same vegetation succession, riparian forests should not be considered as a homogeneous buffering system for upstream/downstream flows of nutrients and organic carbon. }|7Pinto, N. Keitt, T. H.2009[Beyond the least-cost path: evaluating corridor redundancy using a graph-theoretic approach253-266Landscape Ecology242agroecosystems atlantic forest brazil functional connectivity corridors cost distance dispersal fragmentation graph theory matrix migration shortest path landscape connectivity coffee agroecosystems southern mexico conservation forest biodiversity quality matrix plantations managementFebThe impact of the landscape matrix on patterns of animal movement and population dynamics has been widely recognized by ecologists. However, few tools are available to model the matrix's influence on the length, relative quality, and redundancy of dispersal routes connecting habitat patches. Many GIS software packages can use land use/land cover maps to identify the route of least resistance between two points-the least-cost path. The limitation of this type of analysis is that only a single path is identified, even though alternative paths with comparable costs might exist. In this paper, we implemented two graph theory methods that extend the least-cost path approach: the Conditional Minimum Transit Cost (CMTC) tool and the Multiple Shortest Paths (MSPs) tool. Both methods enable the visualization of multiple dispersal routes that, together, are assumed to form a corridor. We show that corridors containing alternative dispersal routes emerge when favorable habitat is randomly distributed in space. As clusters of favorable habitat start forming, corridors become less redundant and dispersal bottlenecks become visible. Our approach is illustrated using data from a real landscape in the Brazilian Atlantic forest. We explored the effect of small, localized disturbance on dispersal routes linking conservation units. Simulated habitat destruction caused the appearance of alternative dispersal routes, or caused existing corridors to become narrower. These changes were observed even in the absence of significant differences in the length or cost of least-cost paths. Last, we discuss applications to animal movement studies and conservation initiatives.://000262828900009-399WB Times Cited:0 Cited References Count:48 0921-2973ISI:000262828900009|Pinto, N Jet Prop Lab, 4800 Oak Grove Dr, Pasadena, CA 91109 USA Univ Texas Austin, Sect Integrat Biol, Austin, TX 78712 USADoi 10.1007/S10980-008-9303-YEnglish<7u+Pinto-Correia, T. Gustavsson, R. Pirnat, J.2006Bridging the gap between centrally defined policies and local decisions - Towards more sensitive and creative rural landscape management333-346Landscape Ecology213yauthenticity; contextual knowledge; local level; multi-functionality; rural landscapes; stakeholders CONSERVATION; FUTUREArticleAprEuropean policies and instruments such as the Common Agricultural Policy (CAP) and many instruments for nature and landscape conservation in Europe have for some decades been dominated by centralisation and standardisation. This paper shows that this has led to the neglect of contextual and place-related approaches and an unnecessarily high degree of over-simplification. Recently, as a reaction to this over-simplification, diversity and specific character has been particularly stressed in many European and national strategies for rural landscapes and conservation, but the processes of simplification still continue. Using examples from mixed agriculture and forestry landscapes in Portugal, Slovenia and Sweden, this paper aims to contribute to understanding the gap between centrally defined strategies for rural landscapes and awareness and management practices at local level. The three countries are situated at the outer fringes of Europe, and are complementary with their different degrees of urbanisation, forest distribution and tree-richness in the agricultural landscapes. Furthermore, the aim is to show how local landscape management is driven and to identify factors contributing to a better use of public policies through a participatory process with visions for the future. Systems of landscape classifications such as landscape character assessment often recognise the specific character of these landscapes, but have so far achieved very little for the preservation of their locally specific values, nor have they contributed to the development and the creation of new visions for future management. Such systems could contribute much more if they could be opened to adaptation on a more local scale in communication-led management planning.://000236968500003 ~ ISI Document Delivery No.: 034ZD Times Cited: 0 Cited Reference Count: 70 Cited References: *COUNC EUR, 2000, EUR LANDSC CONV T LA, P6 *ECNC, 1997, ACT THEM, V4 *UNECE, 1998, CONV ACC INF PUBL PA *UNEP ECNC COUNC E, 1996, PAN EUR BIOL LANDSC ALPHANDERY P, 1990, COURRIER CELLULE ENV, V90, P14 ALVESSON M, 1994, TOLKNING REFLEKTION AMBROISE R, 1998, COURRIER ENV INRA, V34, P5 BACHAREL F, 1999, LAND USE CHANGES THE, V24 BALDOCK DM, 1993, NATURE CONSERVATION BALDOCK DM, 1996, FARMING MARGINS ABAN BERLEANT A, 1997, LIVING LANDSCAPE AES BERLEANT A, 2004, RETHINKING AESTHETIC BETHE F, 1995, MARGINALISATION AGR BISHOP K, 2004, COUNTRYSIDE PLANNING BRADY E, 2003, AESTHETICS NATURAL E BREMAN BC, 2003, COPING MARGINALIZATI BULLER H, 2000, AGRIENVIRONMENTAL PO CAREWREID J, 1994, STRATEGIES NATL SUST CARLSON A, 2000, AESTHETICS ENV APPRE CRONON W, 1996, UNCOMMON GROUND RETH DABREU AC, 2004, COLECCAO ESTUDOS, V10 DRAMSTAD W, 2003, P NIJOS OECD EXP M A EDEN P, 2000, AGRIENVIRONMENTAL PO FISK JW, 2000, FACILITATING SUSTAIN FOSTER C, 2000, RESTORING NATURE PER, P71 GAGO JM, 1998, SOCIAL SCI BRIDGE GERDEHAG P, 1999, BYGDEN DAR VINDEN VA GIBBONS M, 1994, NEW PRODUCTION KNOWL GREEN B, 2001, THREATENED LANDSCAPE GUSTAVSSON R, 1995, LANDSKAPSFORANDRINGA GUSTAVSSON R, 2003, LANDSCAPE INTERFACES HAGEDORN K, 2002, ENV COOPERATION I CH HANSEN B, 1991, DSR LANDSKABSSERIE, V1 HELMFRID S, 1994, LANDSCAPE SETTLEMENT HLADNIK D, 2005, ECOL ENG ILBERY B, 1998, GEOGRAPHY RURAL CHAN JOLLIVET M, 1997, VERS RURAL POSTINDUS, P77 KLIJN J, 2000, LANDSCAPE ECOLOGY LA LOWE P, 1998, PARTICIPATION RURAL LOWE P, 2000, CAP REGIMES EUROPEAN, P31 MARQUES TS, 2004, PORTUGAL TRANSICAO S MARUSIC J, 1998, REGIONAL DISTRIBUTIO MORMONT M, 1999, ENV SOC, V21, P67 NILSSON M, 2003, J ENV POLICY PLANNIN, V5, P333 NOWOTNY H, 2002, RETHINKING SCI KNOWL OLIVEIRA R, 2003, P NATO WORKSH NOV PO ORIORDAN T, 1998, TRANSITION SUSTAINAB, V21 PEDROLI B, 2000, LANDSCAPE OUR HOME L PERELMAN C, 2004, BRUT OSTL BOKF S PINTA ER, 2000, CORRECTIONAL MENTAL, V1, P81 PINTOCORREIA T, 1998, FOREST LANDSCAPE RES, V1, P491 PINTOCORREIA T, 2000, LANDSCAPE URBAN PLAN, V50, P95 PINTOCORREIA T, 2004, WAG UR FRON, V4, P135 PIRNAT J, 2000, LANDSCAPE URBAN PLAN, V52, P135 PRETTY J, 2000, FACILITATING SUSTAIN, P23 PRIMDAHL J, 2004, UNPUB C LANDSC RES L RAMIREZ JL, 1995, NORDISKA I SAMHALLSP, V13, P2 ROLING NG, 2003, FACILITATING SUSTAIN SCHOLTES P, 1999, ENV SOC, V22 SELMAN P, 2004, WAGENINGEN UR FRONTI, V4 SPORRONG U, 1995, SWEDISH LANDSCAPES STANNERS D, 1995, EUROPES ENV DOBRIS A TERWAN P, 2004, VALUES AGRARIAN LAND TOULMIN S, 1972, HUMAN UNDERSTANDING VANWOERKUM C, 2000, FACILITATING SUSTAIN VOS W, 1993, P SCI WORKSH EC RES, P81 WAGEMAN M, 2000, FACILITATING SUSTAIN WARBURTON D, 2004, COUNTRYSIDE PLANNING WHITBY M, 1996, EUROPEAN ENV CAP REF WILSON GA, 2001, T I BRIT GEOGR, V26, P77 0921-2973 Landsc. Ecol.ISI:000236968500003OUniv Evora, Dept Landscape & Biophys Planning, P-7000 Evora, Portugal. Swedish Univ Agr Sci, Dept Landscape Planning, Alnarp, Sweden. Univ Ljubljana, Dept Forestry & Renewable Forest Resources, Ljubljana 61000, Slovenia. Pinto-Correia, T, Univ Evora, Dept Landscape & Biophys Planning, Rua Romao, P-7000 Evora, Portugal. mtpc@uevora.ptEnglishF|?* RPiqueray, Julien Cristofoli, Sara Bisteau, Emmanuelle Palm, Rodolphe Mahy, Gregory2011Testing coexistence of extinction debt and colonization credit in fragmented calcareous grasslands with complex historical dynamics823-836Landscape Ecology266JulCalcareous grasslands are among the most species-rich ecosystems in temperate countries. However, these ecosystems have suffered from fragmentation and destruction during the last century. We studied the response of calcareous grassland plant diversity to landscape changes in Belgium. Results indicated that high area loss (since 1965) old habitat patches exhibited an extinction debt inverse to low area loss old habitat patches, little depending on the area loss threshold (60%, 70%, 80% or 90%) considered for the distinction between the high and low area loss patches. However, human activities also created new habitat patches in the landscape and therefore provided opportunities for calcareous grassland plant species to colonize new habitats. This also provided opportunities to study species colonization abilities in the context of habitat restoration. We analyzed species richness in new patches compared to old patches in order to detect colonization credit. We detected the presence of a colonization credit in new patches when using high loss old patches (area loss >80%, exhibiting an extinction debt) or all old patches as a reference. However, when the reference was low loss old patches alone (area loss <80%, less likely to exhibit an extinction debt), no colonization credit was detected. In addition, species composition was similar between new patches and old patches. These results are encouraging for restoration programs. However, the results indicated that the presence of an extinction debt in reference habitats could lead to inaccurate conclusions in restoration monitoring. Therefore, extinction debt should be considered when choosing reference habitats to evaluate restoration success.!://WOS:000291485400005Times Cited: 0 0921-2973WOS:00029148540000510.1007/s10980-011-9611-5B<7Plieninger, T.2006Habitat loss, fragmentation, and alteration - Quantifying the impact of land-use changes on a Spanish dehesa landscape by use of aerial photography and GIS91-105Landscape Ecology211extensification; image processing; intensification; landscape change; land-use; Mediterranean; Quercus ilex; rangelands; rural landscapes; Spain MEDITERRANEAN REGION; SOUTHERN SPAIN; SIZE STRUCTURE; OAK; CONSERVATION; REGENERATION; MANAGEMENT; RANGELANDS; PORTUGAL; FORESTSArticleJanMediterranean agroforestry landscapes, dehesas, experience significant structural changes that affect their ability to support habitats for a rich biodiversity. The goal of this study is to provide quantitative information on loss, fragmentation, and alteration of holm oak (Quercus ilex) stands over a 42-year period, based on two sites in the lowlands of Caceres province, Spain. Aerial photography and orthoimages from 1956, 1984, and 1998 were processed in a geographic information system (GIS). Important changes in demography and land-use were rural depopulation, abandonment of traditional agricultural activities, and a sharp increase in livestock stocking levels. These were related to intensification and extensification of land-uses determined by national and EU agricultural policies. Results of the land cover analysis indicated that dehesas suffered an annual 0.27% and 0.04% decrease in cover in the two sites. From 1984 loss rate had markedly accelerated (0.83% and 0.30%). Most dehesas were lost by shrub encroachment or conversion to open grassland. Fragmentation through roads increased by 28% and 45%, while rural buildings decreased by 17% and 50% from 1956 to 1998. Mean tree density decreased from 1956 to 1984, but a recovery was found since 1984. Significant factors determining stand densities in most time points were altitude (related with different land-uses and geological substrates), ownership, and proximity to villages. This suggests that stand structure is controlled both by human interventions and ecological settings. The findings support the view that opposite trends of land abandonment and intensification of land-uses arise in most northern Mediterranean countries as an effect of the EU Common Agricultural Policy.://000235887300008  ISI Document Delivery No.: 020DD Times Cited: 0 Cited Reference Count: 63 Cited References: *COMM EUR COMM, 1991, CORINE LAND COV *MAPA, 1986, SUP SIERR NORT EV PA ASHTON MS, 2000, SILVICULTURAL BASIS, P207 AULD TD, 1993, BIOL CONSERV, V65, P165 COMINS JS, 1993, LANDSCAPE URBAN PLAN, V23, P155 COPPEDGE BR, 2001, LANDSCAPE ECOL, V16, P677 DELEONLLAMAZARE.A, 1991, CARACTERIZACION AGRO DEVESAALCARAZ JA, 1995, VEGETACION FLORA EXT DIAZ M, 1993, Z SAUGETIERKD, V58, P302 DIAZ M, 1995, FARMING EDGE NATURE, P103 DIAZ M, 1996, BIOL CONSERV, V75, P119 DIAZ M, 1997, FARMING BIRDS EUROPE, P178 DIAZ M, 2001, BENEFICIOS COMERCIAL, P269 DYTHAM C, 2002, CHOOSING USING STAT ELENAROSSELLO M, 1980, AGR LATIFUNDIARA PEN, P287 ELENAROSSELLO M, 1987, CARBON ENCINA DEHESA FAHRIG L, 1997, J WILDLIFE MANAGE, V61, P606 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FORMAN RTT, 1995, LAND MOSAICS ECOLOGY GONZALEZBERNALD.F, 1969, B SOC ESPANOLA HIST, V67, P265 GREEN BH, 2001, THREATENED LANDSCAPE, P139 GROVE AT, 2001, NATURE MEDITERRANEAN GURRIAGASCON JL, 2001, POLBACION DINAMICA D JANSEN LJM, 2002, AGR ECOSYST ENVIRON, V91, P89 JOFFRE R, 1988, ACTA OECOL, V9, P405 JOFFRE R, 1988, AGROFOREST SYST, V6, P71 JOFFRE R, 1999, AGROFOREST SYST, V45, P57 LYRINTZIS GA, 1996, ENVIRON CONSERV, V23, P140 MARANONARANA T, 1985, AN EDAFOL AGROBIOL, V54, P1183 MARISCALLORENTE P, 2001, BENIFICIOS COMERCIAL, P216 MARISCALLORENTE T, 2001, AN EDAFOL AGROBIOL, P216 MARTIN J, 2002, BIOL CONSERV, V108, P213 MCPHERSON GR, 1997, ECOLOGY MANAGEMENT N MEFFE GK, 1997, PRINCIPLES CONSERVAT MONTERO G, 1998, AGR SOSTENIBLE, P519 MOREIRA F, 2001, LANDSCAPE ECOL, V16, P557 MORILLO C, 2000, BIOL CONSERV, V65, P165 MOTOYAOLIVER JM, 1993, ENCINAS ENCINARES ONATE JJ, 1998, J ENVIRON MANAGE, V52, P227 PEREVOLOTSKY A, 1998, BIOSCIENCE, V48, P1007 PEREZ MR, 1990, LANDSCAPE URBAN PLAN, V18, P211 PINTOCORREIA T, 1999, LANDSCAPE URBAN PLAN, V46, P125 PLIENINGER T, 2003, ENVIRON CONSERV, V30, P61 PLIENINGER T, 2004, J ARID ENVIRON, V57, P345 PULIDO FJ, 1992, AEGYPIUS, V10, P39 PULIDO FJ, 1992, ARDEOLA, V39, P63 PULIDO FJ, 2001, FOREST ECOL MANAG, V146, P1 PULIDO FJ, 2002, GESTION FORESTAL DEH PULIDO FJ, 2005, ECOSCIENCE, V12, P92 SANMIGUELAYANZ A, 2001, BENEFICIOS COMERCIAL, P313 SANTOS T, 2002, BIOL CONSERV, V105, P113 SIVERTSEN DP, 1995, CONSERVING BIODIVERS, P29 STEINHARDT U, 1999, ENV INDICES SYSTEMS, P237 STEPHENS A, 1998, DICT AGR TAILLEFUMIER F, 2003, CATENA, V51, P267 TANRIVERMIS H, 2003, J ARID ENVIRON, V54, P553 TELLERIA JL, 1992, BIRD NUMBERS 1992 DI, P57 TUCKER GM, 1997, HABITATS BIRDS EUROP VIEJO JL, 1989, BIOL CONSERV, V48, P101 VOS W, 1993, LANDSCAPE URBAN PLAN, V24, P63 VUORELA N, 2002, LANDSCAPE RES, V27, P141 WASCHER DM, 2001, THREATENED LANDSCAPE, P129 WESTOBY M, 1989, J RANGE MANAGE, V42, P266 0921-2973 Landsc. Ecol.ISI:000235887300008Univ Freiburg, Inst Landscape Management, D-79106 Freiburg, Germany. Plieninger, T, Univ Freiburg, Inst Landscape Management, Tennenbacher Str 4, D-79106 Freiburg, Germany. tobias.plieninger@landespflege.uni-freiburg.deEnglishU?y,Plotnick, R.E. R.H. Gardner R.V. O'Neill19933Lacunarity indices as measures of landscape texture201-211Landscape Ecology839lacunarity, landscape texture, spatial analysis, fractals||7 ,Plotnick, R. E. Gardner, R. H. Oneill, R. V.19933Lacunarity Indexes as Measures of Landscape Texture201-211Landscape Ecology836lacunarity landscape texture spatial analysis fractalsSepLacunarity analysis is a multi-scaled method of determining the texture associated with patterns of spatial dispersion (i.e., habitat types or species locations) for one-, two-, and three-dimensional data. Lacunarity provides a parsimonious analysis of the overall fraction of a map or transect covered by the attribute of interest, the degree of contagion, the presence of self-similarity, the presence and scale of randomness, and the existence of hierarchical structure. For self-similar patterns, it can be used to determine the fractal dimension. The method is easily implemented on the computer and provides readily interpretable graphic results. Differences in pattern can be detected even among very sparsely occupied maps.://A1993MB34000006.Mb340 Times Cited:129 Cited References Count:0 0921-2973ISI:A1993MB34000006BPlotnick, Re Univ Illinois,Dept Geol Sci,Box 4348,Chicago,Il 60680English |?CPlue, J. Hermy, M. Verheyen, K. Thuillier, P. Saguez, R. Decocq, G.2008XPersistent changes in forest vegetation and seed bank 1,600 years after human occupation673-688Landscape Ecology236Past land use is an important factor determining vegetation in temperate deciduous forests. Little is known about the long-term persistence of these impacts on vegetation but especially on the seed bank. This study assessed whether soil characteristics remain altered 1,600 years after human occupation and if this yielded persistent differences in forest plant communities and their seed bank in particular. Compiegne forest is located in northern-France and has a history of continuous forest cover since the end of Roman times. Twenty-four Gallo-Roman and 24 unoccupied sites were sampled and data were analysed using paired sample tests to investigate whether soil, vegetation and seed bank still differed significantly. The soil was persistently altered on the Gallo-Roman sites resulting in elevated phosphorus levels and pH (dependent on initial soil conditions) which translated into increased vegetation and seed bank species richness. Though spatially isolated, Gallo-Roman sites supported both a homogenized vegetation and seed bank. Vegetation differences were not the only driver behind seed bank differences. Similarity between vegetation and seed bank was low and the possibility existed that agricultural ruderals were introduced via the former land use. Ancient human occupation leaves a persistent trace on forest soil, vegetation and seed bank and appears to do so at least 1,600 years after the former occupation. The geochemical alterations created an entirely different habitat causing not only vegetation but also the seed bank to have altered and homogenized composition and characteristics. Seed bank differences likely persisted by the traditional forest management and altered forest environment.!://WOS:000257210900004Times Cited: 0 0921-2973WOS:00025721090000410.1007/s10980-008-9229-4 ~?ipPocewicz, A. Nielsen-Pincus, M. Goldberg, C. S. Johnson, M. H. Morgan, P. Force, J. E. Waits, L. P. Vierling, L.2008lPredicting land use change: comparison of models based on landowner surveys and historical land cover trends195-210Landscape Ecology23{To make informed planning decisions, community leaders, elected officials, scientists, and natural resource managers must be able to evaluate potential effects of policies on land use change. Many land use change models use remotely-sensed images to make predictions based on historical trends. One alternative is a survey-based approach in which landowners' stated intentions are modeled. The objectives of our research were to: (1) develop a survey-based landowner decision model (SBM) to simulate future land use changes, (2) compare projections from the SBM with those from a trend-based model (TBM), and (3) demonstrate how two alternative policy scenarios can be incorporated into the SBM and compared. We modeled relationships between land management decisions, collected from a mail survey of private landowners, and the landscape, using remotely-sensed imagery and ownership parcel data. We found that SBM projections were within the range of TBM projections and that the SBM was less affected by errors in image classification. Our analysis of alternative policies demonstrates the importance of understanding potential effects of targeted land use policies. While policies oriented toward increasing enrollment in the Conservation Reserve Program (CRP) resulted in a large (11-13%) increase in CRP lands, policies targeting increased forest thinning on private non-industrial lands increased low-density forest projections by only 1%. The SBM approach is particularly appropriate for landscapes including many landowners, because it reflects the decision-making of the landowners whose individual actions will result in collective landscape change."://WOS:000252636100008 Times Cited: 0WOS:000252636100008(10.1007/s10980-007-9159-6|ISSN 0921-2973'<7{+Poiani, K. A. Bedford, B. L. Merrill, M. D.1996cA GIS-based index for relating landscape characteristics to potential nitrogen leaching to wetlands237-255Landscape Ecology1149wetlands; non-point source pollution; nitrogen; watershed; leaching; geographic information system; landscape; groundwater GEOGRAPHIC INFORMATION-SYSTEMS; NONPOINT-SOURCE POLLUTION; TEMPERATE FOREST ECOSYSTEMS; JERSEY PINE BARRENS; WATER-QUALITY; GROUND-WATER; RIPARIAN FORESTS; DENITRIFICATION; NITRATE; DYNAMICSArticleAugWe developed a spatially-explicit, quantitative Nitrogen Leaching Index to assess the potential for non-point source subsurface nitrogen pollution to wetlands. The index was based on the leaching potential of the watershed soils, the amount of nitrogen available for leaching, and the spatial position of nitrogen sources in the watershed. A raster or cell-based geographic information system (GIS) was used to estimate the necessary data inputs for calculating the index, such as soil hydrologic group, land use/soil type combination, groundwater residence time, and location of septic systems. The Total and Average Watershed Nitrogen Leaching Index (TWNLI and AWNLI) were calculated by summing and averaging, respectively, individual cell contributions over a watershed. Analysis of nine wetland watersheds in central New York state, USA, with mixed forest and agricultural land uses illustrated the use of the index for identifying and ranking wetlands with potential nitrogen pollution. Results showed that the spatial characteristics of a watershed potentially can effect subsurface nitrogen delivery to groundwater-dominated wetlands. The use of an index based on watershed soils, topography, and land use may be useful for assessing potential nitrogen pollution to wetlands at a regional scale.://A1996VC12700006 h ISI Document Delivery No.: VC127 Times Cited: 11 Cited Reference Count: 70 Cited References: *CORN U DEP GEOL, 1959, 31 ANN FIELD M NEW Y *US SOIL CONS SERV, 1965, SOIL SURV ABER JD, 1991, ECOL APPL, V1, P303 ABER JD, 1992, TRENDS ECOL EVOL, V7, P220 ABER JD, 1993, ECOLOGICAL APPL, V3, P15 AERTS R, 1988, VEGETATIO, V76, P63 BARRY DAJ, 1993, J ENVIRON QUAL, V22, P767 BLOOM AL, 1970, NEW YORK STATE GEOLO BORMANN FH, 1979, PATTERN PROCESS FORE BURROUGH PA, 1986, PRINCIPLES GEOGRAPHI BUTLER TJ, 1995, ATMOS ENVIRON, V29, P1253 COOPER AB, 1990, HYDROBIOLOGIA, V202, P13 DETENBECK NE, 1993, LANDSCAPE ECOL, V8, P39 DUXBURY JM, 1982, NATURE, V298, P462 EASTMAN JR, 1992, IDRISI TECHNICAL REF EASTMAN JR, 1992, IDRISI USERS GUIDE V EHRENFELD JG, 1983, BIOL CONSERV, V25, P353 EHRENFELD JG, 1991, J APPL ECOL, V28, P467 EVANS BM, 1990, J SOIL WATER CONSERV, V45, P242 FREEZE RA, 1979, GROUNDWATER GOLD AJ, 1990, J SOIL WATER CONSERV, V45, P305 GOODCHILD MF, 1993, ENV MODELING GIS, P94 GROFFMAN PM, 1989, SOIL BIOL BIOCHEM, V21, P613 GROFFMAN PM, 1992, J ENVIRON QUAL, V21, P666 HALL DW, 1993, WATER RESOUR BULL, V29, P55 HALLIDAY SL, 1991, WATER RESOUR BULL, V27, P237 HAMLETT JM, 1992, J SOIL WATER CONSERV, V47, P399 HANSON GC, 1994, ECOL APPL, V4, P750 HEATWOLE CD, 1991, APPLIED ENG AGR, V7, P692 HILL AR, 1989, BIOGEOCHEMISTRY, V8, P167 HILL AR, 1990, HYDROBIOLOGIA, V206, P39 HILL AR, 1991, BIOGEOCHEMISTRY, V14, P209 HINTON MJ, 1993, J HYDROL, V142, P229 HUGHES HBF, 1985, BURBS SIMULATION NIT JAMISON JM, 1994, J ENVIRON QUAL, V23, P337 JENSON SK, 1988, PHOTOGRAMM ENG REMOT, V54, P1593 JOHNSTON CA, 1990, BIOGEOCHEMISTRY, V10, P105 JOHNSTON CA, 1991, CRIT REV ENV CONTR, V21, P491 KEENEY D, 1986, CRC CRIT R ENVIRON, V16, P257 LABAUGH JW, 1986, WATER RESOUR BULL, V22, P1 LEVINE DA, 1993, ORNL ENV SCI DIV PUB, V3993 LOWRANCE R, 1984, BIOSCIENCE, V34, P374 MCNAMARA JP, 1992, J HYDROL, V140, P279 MEISINGER JJ, 1991, MANAGING NITROGEN GR, P85 MOORE DRJ, 1989, BIOL CONSERV, V47, P203 MORGAN MD, 1986, BIOL CONSERV, V35, P143 MORRIS JT, 1988, ENVIRON SCI TECHNOL, V22, P832 MORRIS JT, 1991, ANNU REV ECOL SYST, V22, P257 NEELY RK, 1989, NO PRAIRIE WETLANDS, P91 PARSONS LL, 1991, SOIL SCI SOC AM J, V55, P90 PETACH MC, 1991, GEODERMA, V48, P245 PETERJOHN WT, 1984, ECOLOGY, V65, P1466 PIERCE FJ, 1991, MANAGING NITROGEN GR, P259 PIONKE HB, 1991, MANAGING NITROGEN GR, P237 POIANI KA, 1995, J SOIL WATER CONSERV, V50, P613 REID S, 1994, NDSS NITROGEN DECISI SIVERTUN A, 1988, INT J GEOGR INF SYST, V2, P365 SMITH RL, 1988, APPL ENVIRON MICROB, V54, P1071 SPALDING RF, 1994, SCI TOTAL ENVIRON, V141, P17 STARR RC, 1993, GROUND WATER, V31, P934 TILMAN D, 1986, ECOLOGY, V67, P555 TIM US, 1992, WATER RESOUR BULL, V28, P877 TIM US, 1994, J ENVIRON QUAL, V23, P25 VANKESSEL C, 1993, SOIL SCI SOC AM J, V57, P988 VENTURA SJ, 1993, WATER RESOUR BULL, V29, P189 VONENGELN OD, 1959, FINGER LAKES REGION WALSH SJ, 1987, PHOTOGRAMM ENG REM S, V53, P1423 WEISKEL PK, 1991, WATER RESOUR RES, V27, P2929 WILLIAMS JR, 1991, MANAGING NITROGEN GR, P59 WINTER TC, 1981, WATER RESOUR B, V17, P82 0921-2973 Landsc. Ecol.ISI:A1996VC12700006*CORNELL UNIV,CTR ENVIRONM,ITHACA,NY 14853.English~? =Polakowska, Aleksandra Fortin, Marie-Josée Couturier, Andrew2012Quantifying the spatial relationship between bird species’ distributions and landscape feature boundaries in southern Ontario, Canada 1481-1493Landscape Ecology2710Springer NetherlandsBiomedical and Life SciencesUnderstanding what features of the landscape affect species distribution is critical to effectively implement conservation strategies. This study investigates how a boundary analysis framework can be used to characterize the spatial association between boundaries (i.e., spatial locations of high rates of change) in bird species’ distributions and landscape features at the regional scale. The study area covers 92,000 km 2 in southern Ontario (Canada) and extends from the Great Lakes-St. Lawrence biome to the southern Canadian Shield biome. Landcover composition was derived from Ontario Land Cover data (1991–1998; 7 types) and elevation data were derived from the Canada3D digital elevation model. Bird distributions were estimated using indicator kriging based on point counts obtained from the Ontario Breeding Bird Atlas data (2001–2005; 60 species). Boundaries were delineated for both data types using a 10 × 10 km cell resolution. Spatial boundary overlap statistics were used to quantify the spatial relationship between landscape features and bird boundaries and tested using a randomization procedure. There was significant positive association and spatial overlap between delineated landscape feature boundaries and bird boundaries. The number of spatially overlapping cells between the two boundary types was 67 out of 164 (41 %) and 76 % of cells were within 11.42 km of each other. These results were statistically significant ( P < 0.001) and suggest a strong spatial relationship between high rates of change in landscape features and bird species’ distributions at the regional scale. A boundary analysis framework could be used to identify boundary shifts in response to climate change and anticipate changes in species distributions.+http://dx.doi.org/10.1007/s10980-012-9804-6 0921-297310.1007/s10980-012-9804-6F|? Polhill, J. G. Gotts, N. M.2009DOntologies for transparent integrated human-natural system modelling 1255-1267Landscape Ecology2490We propose an approach to modular agent-based land use modelling, based on ontologies in their computer science sense: formal representations of conceptualisations. The approach is primarily aimed at addressing the issue of model transparency. Human-natural systems models involve large numbers of submodels, making them difficult to understand for those not involved in their construction. We show that using ontologies to represent the structure and state of a simulation model improves transparency in two ways: First, the information about the structure and state is decoupled from the simulation software and can be independently processed. Second, the logics on which ontologies are based reflect more commonsense understandings of the relationships among concepts than those of computer programming languages.!://WOS:000270739000009Times Cited: 0 0921-2973WOS:00027073900000910.1007/s10980-009-9381-5 ڽ7 jPolyakov, Maksym Rowles, AlexeiD Radford, JamesQ Bennett, AndrewF Park, Geoff Roberts, Anna Pannell, David2013iUsing habitat extent and composition to predict the occurrence of woodland birds in fragmented landscapes329-341Landscape Ecology282Springer NetherlandsbHabitat fragmentation Patches Landscape context Woodland birds Probability of occurrence Australia 2013/02/01+http://dx.doi.org/10.1007/s10980-012-9831-3 0921-2973Landscape Ecol10.1007/s10980-012-9831-3English |?</Pontius, Robert Gilmore, Jr. Parmentier, Benoit2014ERecommendations for using the relative operating characteristic (ROC)367-382Landscape Ecology293MarThe relative operating characteristic (ROC) is a widely-used method to measure diagnostic signals including predictions of land changes, species distributions, and ecological niches. The ROC measures the degree to which presence for a Boolean variable is associated with high ranks of an index. The ROC curve plots the rate of true positives versus the rate of false positives obtained from the comparison between the Boolean variable and multiple diagnoses derived from thresholds applied to the index. The area under the ROC curve (AUC) is a summary metric, which is commonly reported and frequently criticized. Our manuscript recommends four improvements in the use and interpretation of the ROC curve and its AUC by: (1) highlighting important threshold points on the ROC curve, (2) interpreting the shape of the ROC curve, (3) defining lower and upper bounds for the AUC, and (4) mapping the density of the presence within each bin of the ROC curve. These recommendations encourage scientists to interpret the rich information that the ROC curve can reveal, in a manner that goes far beyond the potentially misleading AUC. We illustrate the benefit of our recommendations by assessing the prediction of land change in a suburban landscape.!://WOS:000331935500002Times Cited: 2 0921-2973WOS:00033193550000210.1007/s10980-013-9984-83<7@-Pontius, R. G. Versluis, A. J. Malizia, N. R.2006BVisualizing certainty of extrapolations from models of land change 1151-1166Landscape Ecology217accuracy; calibration; error; land cover; land use; map; Massachusetts; prediction; uncertainty; validation CATEGORICAL MAPS; USA; VALIDATION; MASSACHUSETTS; TRANSITIONS; LANDSCAPES; DEPENDENCE; LOCATIONArticleOctThis article presents a method to estimate and to visualize the certainty of land change models as they extrapolate beyond the time interval for which empirical data exist. The method to project the certainty relies on measurements of model performance during a validation run with historic data and on the assumption that the model's accuracy approaches randomness as it predicts farther into the future. A land change model typically predicts each pixel as exactly one category for each year. This article presents a technique to convert those predictions into conditional probabilities. As an example, we use the model Geomod to extrapolate forest change over a century for the Plum Island Ecosystems, which is a Long Term Ecological Research site of the United States' National Science Foundation. Geomod uses calibration information between 1971 and 1985 in order to predict the changes from 1985 to 1999, at which point the validation procedure measures the model's predictive accuracy. Then the model is re-calibrated with information from 1985 to 1999 in order to extrapolate into the future, assuming a business as usual scenario. As time progresses, the expected accuracy approaches 0.5, which is the probability at which the model's prediction is as accurate as a random prediction, since the application involves two categories. The extrapolated accuracy of the prediction for the entire study area in the year 2097 is 68%. The method is designed to work with any number of categories so it can be used with a variety of land change models.://000241010900014 ISI Document Delivery No.: 091FA Times Cited: 0 Cited Reference Count: 35 Cited References: *AM RIV, 2003, AM MOST END RIV 2003 *IRWA IPSW RIV WAT, 2003, IPSW RIV WAT MAN PLA BROWN DG, 2005, INT J GEOGR INF SCI, V19, P153 CRONON W, 1983, CHANGES LAND FOSTER DR, 2004, FORESTS TIME ENV CON HAGEN A, 2003, INT J GEOGR INF SCI, V17, P235 JANTZ CA, 2003, ENVIRON PLANN B, V30, P251 JENERETTE GD, 2001, LANDSCAPE ECOL, V16, P611 KEANE RE, 1999, LANDSCAPE ECOL, V14, P311 KLINE JD, 2003, LANDSCAPE ECOL, V18, P347 KOK K, 2001, AGR ECOSYST ENVIRON, V85, P223 LURZ PWW, 2001, LANDSCAPE ECOL, V16, P407 ONEILL RV, 1986, MONOGRAPHS POPULATIO, V23 PIJANOWSKI BC, 2002, COMPUTERS ENV URBAN, V26, P553 PIJANOWSKI BC, 2005, INT J GEOGR INF SCI, V19, P197 PONTIUS RG, 2000, PHOTOGRAMM ENG REM S, V66, P1011 PONTIUS RG, 2001, AGR ECOSYST ENVIRON, V85, P191 PONTIUS RG, 2001, AGR ECOSYST ENVIRON, V85, P239 PONTIUS RG, 2002, PHOTOGRAMM ENG REM S, V68, P1041 PONTIUS RG, 2003, J GEOGRAPHICAL SYSTE, V5, P253 PONTIUS RG, 2003, T GIS, V7, P467 PONTIUS RG, 2004, ECOL MODEL, V179, P445 PONTIUS RG, 2004, GEOJOURNAL, V61, P325 PONTIUS RG, 2005, ENVIRON PLANN B, V32, P211 PONTIUS RG, 2005, INT J GEOGR INF SYST, V19, P243 SANTELMANN MV, 2004, LANDSCAPE ECOL, V19, P357 SCHNEIDER LC, 2001, AGR ECOSYST ENVIRON, V85, P83 VELDKAMP A, 2001, AGR ECOSYST ENVIRON, V85, P1 VELDKAMP A, 2004, J ENVIRON MANAGE, V72, P1 VERBURG PH, 2004, LANDSCAPE ECOL, V19, P77 VERBURG PH, 2005, INT J GEOGR INF SCI, V19, P99 WALKER R, 2003, PHOTOGRAMM ENG REM S, V69, P1271 WEAR DN, 1998, ECOSYSTEMS, V1, P575 WEAVER K, 2004, LANDSCAPE ECOL, V19, P273 ZARRIELLO PJ, 2000, 004029 US DEP INT US 0921-2973 Landsc. Ecol.ISI:000241010900014Clark Univ, Dept Int Dev Community & Environm, Grad Sch Geog, George Perkins Marsh Inst, Worcester, MA 01610 USA. Pontius, RG, Clark Univ, Dept Int Dev Community & Environm, Grad Sch Geog, George Perkins Marsh Inst, 950 Main St, Worcester, MA 01610 USA. rpontius@clarku.eduEnglish <7t Poos, M. S. Jackson, D. A.2012~Impact of species-specific dispersal and regional stochasticity on estimates of population viability in stream metapopulations405-416Landscape Ecology273metapopulations dispersal population viability analysis stochastic patch-occupancy models parameter estimates patch occupancy models environmental stochasticity clinostomus-elongatus landscape indexes extinction times redside dace dynamics behavior habitat sizeMarSpecies dispersal is a central component of metapopulation models. Spatially realistic metapopulation models, such as stochastic patch-occupancy models (SPOMs), quantify species dispersal using estimates of colonization potential based on inter-patch distance (distance decay model). In this study we compare the parameterization of SPOMs with dispersal and patch dynamics quantified directly from empirical data. For this purpose we monitored two metapopulations of an endangered minnow, redside dace (Clinostomus elongatus), using mark-recapture techniques across 43 patches, re-sampled across a 1 year period. More than 2,000 fish were marked with visible implant elastomer tags coded for patch location and dispersal and patch dynamics were monitored. We found that species-specific dispersal and distance decay models provided qualitatively similar rankings of viable patches; however, there were differences of several orders of magnitude in the estimated intrinsic mean times to extinction, from 24 and 148 years to 362 and > 100,000 years, depending on the population. We also found that the rate of regional stochasicity had a dramatic impact for the estimate of species viability, and in one case altered the trajectory of our metapopulation from viable to non-viable. The divergent estimates in time to extinction times were likely due to a combination species-specific behavior, the dendritic nature of stream metapopulations, and the rate of regional stochasticity. We demonstrate the importance of developing comparative analyses using species- and patch-specific data when determining quantitative estimates for mean time to extinction, which in the case of redside dace, were highly sensitive to different estimates of dispersal.://000300087500008-889QE Times Cited:0 Cited References Count:61 0921-2973Landscape EcolISI:000300087500008Poos, MS Great Lakes Lab Fisheries & Aquat Sci Fisheries &, 867 Lakeshore Rd, Burlington, ON L7R 4A6, Canada Great Lakes Lab Fisheries & Aquat Sci Fisheries &, 867 Lakeshore Rd, Burlington, ON L7R 4A6, Canada Univ Toronto, Dept Ecol & Evolutionary Biol, Toronto, ON M5S 3G5, CanadaDOI 10.1007/s10980-011-9683-2Englishڽ7"Potschin, Marion Haines-Young, Roy2013MLandscapes, sustainability and the place-based analysis of ecosystem services 1053-1065Landscape Ecology286Springer Netherlands}Ecosystem assessments Ecosystem approach Ecosystem services Place-based approaches Sustainability science Cultural landscapes 2013/07/01+http://dx.doi.org/10.1007/s10980-012-9756-x 0921-2973Landscape Ecol10.1007/s10980-012-9756-xEnglishV|?5Potter, Christopher2014Microclimate influences on vegetation water availability and net primary production in coastal ecosystems of Central California677-687Landscape Ecology294Apr Field sampling and satellite remote sensing were used to test the hypothesis that site microclimate variability leading to divergent soil water use by vegetation types is closely associated with variability in annual net primary productivity (NPP) at the landscape scale. A simulation model based on satellite observations of seasonal phenology was used to estimate NPP of grassland, shrubland, and conifer forest vegetation types on the Central California coast near Big Sur. Daily microclimate at the soil surface was monitored over 4 years (2008-2011) for each vegetation type to infer soil moisture controls on plant production. Grassland soils were found to have lower soil organic matter content and were subjected to extreme radiation and wind events, and thereby dry-down faster with daily spring-summer warming than do shrubland or redwood forest soils. This reduced moisture microclimate affected the water stress on grassland plants to reduce NPP fluxes from April to October each year on the Central Coast far sooner than for shrubland or redwood stands. Results from this study suggested that the satellite-observed canopy greenness variations represented can be used to quantify plant production in coastal ecosystems at the landscape scale of defined microclimate variation.!://WOS:000333533800010Times Cited: 0 0921-2973WOS:00033353380001010.1007/s10980-014-0002-6<7e6Potter, D. U. Gosz, J. R. Molles, M. C. Scuderi, L. A.1998:Lightning, precipitation and vegetation at landscape scale203-214Landscape Ecology134klightning research precipitation vegetation monsoon GIS TREE-RING RECORD MEXICAN MONSOON MODEL TEMPERATURESArticleAugWe investigated the question "Is there a relationship between seasonality in precipitation and vegetative cover in Pole Canyon, NM?" GIS and statistical methods were used to determine the degree of association between either summer or winter precipitation and percent canopy cover for trees, graminoids and total vegetation. Monsoon (summer) precipitation was predicted for the years 1986-1994 from lightning strike and relative humidity data by multiple regression. Winter precipitation, the percent of annual precipitation that occurs during winter, and vegetative cover were derived from the Forest Service Terrestrial Ecosystem Survey. Vegetation and precipitation data were ranked and classified (e.g., high, medium, low) and cross-tabulations were generated to compare the spatial distribution of vegetation classes within each precipitation class. Results indicate that seasonality in precipitation affects the distribution and spatial pattern of vegetation at landscape scales. Winter precipitation is a key factor that influences the distribution and spatial pattern of tree cover. Monsoon precipitation may affect the spatial pattern of graminoid cover where Bouteloua gracilis dominates. Winter precipitation may affect the distribution and spatial pattern of graminoid cover where Festuca arizonica dominates. Some of the unexplained relationships may be due to competition between trees and graminoids for moisture and other limiting factors. The importance of temperature was implicit in the division between summer (monsoon) and winter seasons. Annual precipitation, elevation, topography and edaphic factors probably contributed to the observed relationships.://000079677000002 $ISI Document Delivery No.: 185NY Times Cited: 0 Cited Reference Count: 45 Cited References: *ENV SYST RES I IN, 1994, INTR ARC INFO VERS 7 *ENV SYST RES I IN, 1994, INTR ARCV *LIGHTN LOC PROT I, 1986, ADV LIGHTN DIR FIND *SAS I INC, 1988, SAS STAT US GUID REL *SPSS INC, 1990, SPSS PCPLUS 4 0 BAS *USDA, 1986, TERR EC SURV HDB *USDA, 1994, UNPUB POL CAN EC MAN BATTAN LJ, 1965, J ATMOS SCI, V22, P79 BETANCOURT JL, 1990, PACKRAT MIDDENS LAST BETANCOURT JL, 1993, MANAGING PINON JUNIP, P42 BRIFFA KR, 1990, NATURE, V346, P434 DAHM CN, 1992, TROUBLED WATERS GREE, P250 DAHM CN, 1994, PUBLICATION U WASHIN, V8, P12 DOUGLAS MW, 1993, J CLIMATE, V6, P1665 FRITTS HC, 1976, TREE RINGS CLIMATE GOSZ JR, 1993, ANAL RELATIONSIPS LI GOSZ JR, 1993, ECOL APPL, V3, P369 GOSZ JR, 1995, ECOL APPL, V5, P1141 GOTTFRIED GJ, 1995, ECOLOGY DIVERSITY SU, P95 HOLDRIDGE LR, 1947, SCIENCE, V105, P267 KANE RJ, 1993, NATL WEATHER DIGEST, V17 KESSELL SR, 1979, GRADIENT MODELING RE LENIHAN JM, 1993, J BIOGEOGR, V20, P615 MAIER MW, 1984, 7 INT C ATM EL JUN 3, P305 MILLER G, 1993, TERRESTRIAL ECOSYSTE MOLLES MC, 1990, J N AMER BENTHOL SOC, V9, P68 MOLLES MC, 1992, NHRI S SERIES, V7, P197 MORAN JM, 1995, ESSENTIALS WEATHER NEILSON RP, 1986, SCIENCE, V232, P27 NEILSON RP, 1992, LANDSCAPE ECOL, V7, P27 NEILSON RP, 1995, ECOL APPL, V5, P362 NEILSON RP, 1996, COMMUNICATION ODUM EP, 1993, ECOLOGY OUR ENDANGER PIPEGRASS MV, 1978, JG EOPHYS RES C, P11193 POTTER DU, 1996, DESIRED FUTURE CONDI, P113 POTTER DU, 1996, THESIS U NEW MEXICO SCUDERI LA, 1993, SCIENCE, V259, P1433 SILVERTOWN J, 1994, ECOLOGY, V75, P2430 STAR J, 1990, GEOGRAPHIC INFORMATI STENSRUD DJ, 1995, J CLIMATE, V8, P1775 SWETNAM TW, 1995, P 2 LA MES FIR S MAR VORPAHL JA, 1970, SCIENCE, V169, P860 WALKER DA, 1993, BIOSCIENCE, V43, P287 YEAKLEY JA, 1994, LANDSCAPE ECOL, V9, P249 ZAR JH, 1974, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000079677000002USDA, Forest Serv, SW Reg Watershed & Air Management, Albuquerque, NM 87102 USA. Potter, DU, USDA, Forest Serv, SW Reg Watershed & Air Management, 517 Gold Ave, Albuquerque, NM 87102 USA.English?u Potter, Kevin2012DMolecular approaches in natural resource conservation and management467-468Landscape Ecology273Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-011-9679-y 0921-297310.1007/s10980-011-9679-yI<7~Poudevigne, I. Baudry, J.2003kThe implication of past and present landscape patterns for biodiversity research: introduction and overview223-225Landscape Ecology183SCALE HABITAT ECOLOGYEditorial MaterialApr://000183770600001 ISI Document Delivery No.: 694JD Times Cited: 5 Cited Reference Count: 26 Cited References: ARNAUD JF, 2003, LANDSCAPE ECOL, V18, P333 BAUDRY J, 2003, LANDSCAPE ECOL, V18, P303 BERLUNG BE, 1991, ECOLOGICAL B BRADLEY DC, 2002, FRESHWATER BIOL, V47, P161 BUREL F, 1999, IN PRESS ECOLOGIE PA COUSINS SAO, 2003, LANDSCAPE ECOL, V18, P315 CUBIZOLLE H, 2003, LANDSCAPE ECOL, V18, P227 CULLINAN VI, 1992, LANDSCAPE ECOL, V7, P211 DELAPENA NM, 2003, LANDSCAPE ECOL, V18, P265 DONLAN CJ, 2002, J APPL ECOL, V39, P235 ERNOULT A, 2003, LANDSCAPE ECOL, V18, P239 FRITZ H, 2003, LANDSCAPE ECOL, V18, P293 GODRON M, 1983, DISTURBANCE ECOSYSTE, P12 GREEN BH, 1990, GRASS FORAGE SCI, V45, P365 HUSTON MA, 1994, BIOL DIVERSITY, V3, P64 JABERG C, 2001, J APPL ECOL, V38, P1169 JEANNERET P, 2003, LANDSCAPE ECOL, V18, P253 LEVIN SA, 1992, ECOLOGY, V73, P1943 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MENNECHEZ G, 2003, LANDSCAPE ECOL, V18, P279 ORMEROD SJ, 2002, J APPL ECOL, V39, P1 POUDEVIGNE I, 2002, APPL GEOGRAPHIC INFO, P183 ROBIN M, 2002, J HETEROCYCLIC CHEM, V39, P1 SUAREZSEOANE S, 2002, J APPL ECOL, V39, P755 SUTER GW, 1993, ECOLOGICAL RISK ASSE WHITFIELD DP, 2001, J APPL ECOL, V38, P1208 0921-2973 Landsc. Ecol.ISI:000183770600001Univ Rouen, Fac Sci, Landscape Syst Res Grp, F-76821 Mont St Aignan, France. INRA, SAD Armor, F-35042 Rennes, France. Poudevigne, I, Univ Rouen, Fac Sci, Landscape Syst Res Grp, F-76821 Mont St Aignan, France.English|? )Poulin, Jean-Francois Villard, Marc-Andre2011xEdge effect and matrix influence on the nest survival of an old forest specialist, the Brown Creeper (Certhia americana)911-922Landscape Ecology267AugConservation strategies should be based on a solid understanding of processes underlying species response to landscape change. In forests fragmented by agriculture, elevated nest predation rates have been reported in many forest bird species, especially near edges. In intensively-managed forest landscapes, timber harvesting might also be associated with negative edge effects or broader "context" effects on some species when the matrix provides additional resources to their major nest predators. In this study, we hypothesized that proximity to a forest edge and proportion of cone-producing plantations will increase nest predation risk in fragments of relatively undisturbed forest. We focused on the Brown Creeper (Certhia americana), an indicator species of late-seral forests. We compared habitat configuration and composition at four spatial scales (0.14, 0.5, 1 and 2 km) around 54 nests and related daily nest survival rate to the distance to the nearest forest edge, mean patch size of late-seral forest (r = 141 m), proportion of non-forested lands (r = 141 m), density of maintained roads (r = 1 km), proportion of cone-producing spruce plantations (r = 2 km), and year. The best model included distance to the nearest edge and proportion of cone-producing plantations. Distance of nests to the nearest edge was the best individual predictor of daily nest survival. A larger sample of nests showed a significant threshold in distance to the nearest forest edge; nests located at least 100 m away were more likely to fledge young. These results suggest that even in managed forest landscapes, matrix effects can be important and some bird species may exhibit negative edge effects.!://WOS:000292705900002Times Cited: 0 0921-2973WOS:00029270590000210.1007/s10980-011-9615-1#|?lPouyat, R. V. Yesilonis, I. D. Szlavecz, K. Csuzdi, C. Hornung, E. Korsos, Z. Russell-Anelli, J. Giorgio, V.2008XResponse of forest soil properties to urbanization gradients in three metropolitan areas 1187-1203Landscape Ecology2310We investigated the effects of urban environments on the chemical properties of forest soils in the metropolitan areas of Baltimore, New York, and Budapest. We hypothesized that soils in forest patches in each city will exhibit changes in chemistry corresponding to urbanization gradients, but more strongly with various urban metrics than distance to the urban core. Moreover, differences in parent material and development patterns would differentially affect the soil chemical response in each metropolitan area. Results showed that soil chemical properties varied with measures of urban land use in all three cities, including distance to the urban core, which was an unexpected result. Moreover, the results showed that the spatial extent and amount of change was greater in New York than in Baltimore and Budapest for those elements that showed a relationship to the urbanization gradient (Pb, Cu, and to a lesser extent Ca). The spatial relationship of the soil chemical properties to distance varied from city to city. In New York, concentrations of Pb, Cu, and Ca decreased to approximately background concentrations at 75 km from the urban core. By contrast, concentrations of these elements decreased closer to the urban core in Baltimore and Budapest. Moreover, a threshold was reached at about 75% urban land use above which concentrations of Pb and Cu increased by more than twofold relative to concentrations below this threshold. Results of this study suggest that forest soils are responding to urbanization gradients in all three cities, though characteristics of each city (spatial pattern of development, parent material, and pollution sources) influenced the soil chemical response.!://WOS:000261790600005Times Cited: 0 0921-2973WOS:00026179060000510.1007/s10980-008-9288-6|?!#Pouzols, Federico M. Moilanen, Atte2014FA method for building corridors in spatial conservation prioritization789-801Landscape Ecology295MayWe introduce a novel approach to building corridors in spatial conservation prioritization. The underlying working principle is the use of a penalty structure in an iterative algorithm used for producing a spatial priority ranking. The penalty term aims to prevent loss or degradation of structural connections, or, equivalently, to promote to a higher rank landscape elements that are required to keep networks connected. The proposed method shows several convenient properties: (1) it does not require a priori specification of habitat patches, end points or related thresholds, (2) it does not rely on resistance coefficients for different habitats, (3) it does not require species targets, and (4) the cost of additional connectivity via corridors can be quantified in terms of habitat quality lost across species. Corridor strength and width parameters control the trade-off between increased structural connectivity via corridors and other considerations relevant to conservation planning. Habitat suitability or dispersal suitability layers used in the analysis can be species specific, thus allowing analysis both in terms of structural and functional connectivity. The proposed method can also be used for targeting habitat restoration, by identifying areas of low habitat quality included in corridors. These methods have been implemented in the Zonation software, and can be applied to large scale and high resolution spatial prioritization, effectively integrating corridor design and spatial conservation prioritization. Since the method operates on novel principles and combines with a large number of features already operational in Zonation, we expect it to be of utility in spatial conservation planning.!://WOS:000334689900003Times Cited: 0 0921-2973WOS:00033468990000310.1007/s10980-014-0031-1<7[4Powers, J. S. Sollins, P. Harmon, M. E. Jones, J. A.1999]Plant-pest interactions in time and space: A Douglas-fir bark beetle outbreak as a case study105-120Landscape Ecology142bark beetle epidemic Douglas-fir hierarchy theory multiple spatial and temporal scales DENDROCTONUS-PSEUDOTSUGAE LANDSCAPE PATTERNSArticleAprKA conceptual model of Douglas-fir bark beetle (Dendroctonus pseudotsugae) dynamics and associated host tree mortality across multiple spatial and temporal scales was developed, then used to guide a study of the association between the occurrence of beetle-killed trees and factors that might render trees more susceptible to attack. Longterm records of beetle kill showed that beetle epidemics were associated with windstorms and drought at statewide and local spatial scales. At the landscape scale, beetle kill was associated with (i) portions of the landscape that were potentially drier (southern aspects, lower elevations) and (ii) portions of the landscape that had more mature and old-growth conifer vegetation. The patches of beetle-killed trees were aggregated with respect to other patches at scales of approximately 1 and 4 km. At the scale of the individual tree, there was not a strong relationship between beetle kill and resistance to attack measured by tree growth rate prior to attack. Our results show that landscape-scale phenomena and temporal patterns were more strongly correlated with beetle-kill events than was recent growth history at the scale of individual trees. We suggest that the multi-scale approach we employed is useful for elucidating the relative roles of fine- versus coarse-scale constraints on ecological processes.://000079802500002 !ISI Document Delivery No.: 187RV Times Cited: 12 Cited Reference Count: 38 Cited References: *MANG INC, 1993, STATGR REF MAN VERS *NAT CLIM DAT CTR, 1962, STORM DAT UN WEATH P, V4 *SAS I, 1992, P229 SAS ATKINS MD, 1959, CAN ENTOMOL, V91, P283 ATKINS MD, 1960, 6 WORLD FOR C P SEAT, V2, P857 BARBOSA P, 1989, INTRO FOREST SHADE T BERRYMAN AA, 1982, ENVIRON ENTOMOL, V11, P544 BOOTS BN, 1988, POINT PATTERN ANAL BOX GE, 1976, TIME SERIES ANAL FOR CASTELLO JD, 1995, BIOSCIENCE, V45, P16 COHEN WB, 1995, INT J REMOTE SENS, V16, P721 FRANKLIN JF, 1973, NATURAL VEGETATION O FRANKLIN JF, 1979, FOREST SOILS DOUGLAS, P93 FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 FURNISS MM, 1962, J ECON ENTOMOL, V55, P486 FURNISS MM, 1979, INT59 USDA FOR SERV FURNISS MM, 1981, HAZ RAT SYST FOR INS GODFRAY HCJ, 1997, NATURE, V386, P660 GRAUMLICH LJ, 1987, ANN ASSOC AM GEOGR, V77, P19 KAUFMANN MR, 1986, TREE PHYSIOL, V2, P47 KUSHMAUL RJ, 1979, FOREST SCI, V25, P656 LARSSON S, 1989, OIKOS, V56, P277 LESSARD ED, 1990, GREAT BASIN NAT, V50, P333 MANION PD, 1981, TREE DIS CONCEPTS, P324 MCGARIGAL K, 1994, FRAGSTATS SPATIAL PA MCMULLEN LH, 1961, FOREST SCI, V7, P197 MOEUR M, 1993, FOREST SCI, V39, P756 MUELLERDOMBOIS D, 1986, ANNU REV ECOL SYST, V17, P224 ORR PW, 1963, WINDTHROWN TIMBER SU POWERS JS, 1995, THESIS OREGON STATE RUDINSKY JA, 1966, CAN ENTOMOL, V98, P98 SINTON DS, 1996, THESIS OREGON STATE TURCHIN P, 1990, NATURE, V344, P660 TURCHIN P, 1991, ENVIRON ENTOMOL, V20, P401 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 WARING RH, 1980, 65 OR STAT U FOR RES WARING RH, 1985, FOREST ECOSYSTEMS CO WRIGHT LC, 1984, CAN ENTOMOL, V116, P293 0921-2973 Landsc. Ecol.ISI:000079802500002Oregon State Univ, Dept Forest Sci, Forestry Sci Lab 020, Corvallis, OR 97331 USA. Powers, JS, Duke Univ, Nicholas Sch Environm, POB 90328, Durham, NC 27708 USA.English?v +Powney, Gary Broaders, Lorraine Oliver, Tom2012xTowards a measure of functional connectivity: local synchrony matches small scale movements in a woodland edge butterfly 1109-1120Landscape Ecology278Springer NetherlandsBiomedical and Life SciencesThis study investigates the sensitivity of local synchrony to movement patterns of the Ringlet butterfly ( Aphantopus hyperantus ). We examine whether population synchrony, describing the correlated fluctuations of conspecific populations, may prove an effective surrogate measure for monitoring functional connectivity in this species without the requirement of exhaustive sampling. We compared the effect on population synchrony of two different distance measures, direct (Euclidean) distance and distance via woodland rides and edges, and also of habitat matrix composition. Population synchrony of A. hyperantus was calculated as the pairwise correlation between population time-series using 20 years of data from UK butterfly monitoring scheme transects. Local population synchrony was better explained by distance via woodland edges than direct distance, especially for woodland-dominated transects. These results are consistent with mark-recapture data previously collected on the Ringlet butterfly. The results indicate a sensitivity of population synchrony to butterfly local dispersal behaviour, particularly, to the use of habitat corridors and other functional dispersal routes. Population synchrony is considered to have potential as a surrogate measure of functional connectivity. With development, this method could become a valuable conservation tool for identifying important landscape features which promote species’ connectivity.+http://dx.doi.org/10.1007/s10980-012-9771-y 0921-297310.1007/s10980-012-9771-y+?w Prasad, Anantha2012QMelanie Lenart: Life in the hothouse: how a living planet survives climate change611-612Landscape Ecology274Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9724-5 0921-297310.1007/s10980-012-9724-5|?% kPrasad, A. M. Iverson, L. R. Peters, M. P. Bossenbroek, J. M. Matthews, S. N. Sydnor, T. D. Schwartz, M. W.2010`Modeling the invasive emerald ash borer risk of spread using a spatially explicit cellular model353-369Landscape Ecology253The emerald ash borer (EAB, Agrilus planipennis) is decimating native ashes (Fraxinus sp.) throughout midwestern North America, killing millions of trees over the years. With plenty of ash available throughout the continent, the spread of this destructive insect is likely to continue. We estimate that the insect has been moving along a "front" at about 20 km/year since about 1998, but more alarming is its long-range dispersal into new locations facilitated by human activities. We describe a spatially explicit cell-based model used to calculate risk of spread in Ohio, by combining the insect's flight and short-range dispersal ("insect flight") with human-facilitated, long-range dispersal ("insect ride"). This hybrid model requires estimates of EAB abundance, ash abundance, major roads and traffic density, campground size and usage, distance from the core infested zone, wood products industry size and type of wood usage, and human population density. With the "insect flight" model, probability of movement is dependent on EAB abundance in the source cells, the quantity of ash in the target cells, and the distances between them. With the "insect-ride" model, we modify the value related to ash abundance based on factors related to potential human-assisted movements of EAB-infested ash wood or just hitchhiking insects. We attempt to show the advantage of our model compared to statistical approaches and to justify its practical value to field managers working with imperfect knowledge. We stress the importance of the road network in distributing insects to new geographically dispersed sites in Ohio, where 84% were within 1 km of a major highway.!://WOS:000275122600003Times Cited: 0 0921-2973WOS:00027512260000310.1007/s10980-009-9434-9n<7/Prasifka, J. R. Heinz, K. M. Minzenmayer, R. R.2004Relationships of landscape, prey and agronomic variables to the abundance of generalist predators in cotton (Gossypium hirsutum) fields709-717Landscape Ecology197diversity; Hippodamia; natural enemies; Orius; scale; vegetation; Texas; USA FARMING PRACTICE INFLUENCE; BIOLOGICAL-CONTROL; GRAIN-SORGHUM; WITHIN-FIELD; APHIDS; AGROECOSYSTEMS; AGRICULTURE; DIVERSITYArticle}A two-year field study investigated the possible effects of grain sorghum (Sorghum bicolor [L.] Moench) and uncultivated areas on the abundance of generalist predators in commercially-managed cotton (Gossypium hirsutum W fields in Texas, USA. From 63 to 70 fields were sampled for pests and predators over nine consecutive weeks during early stages of cotton development. Additional data on agronomic practices and landscape composition at three spatial scales were also collected for each field. Stepwise regression analyses were used to determine the relationships of landscape, agronomic and prey variables to the abundance of generalist predators. Because the variables most closely linked to predator levels could vary over time, separate regressions were conducted for three time periods corresponding to stages of grain sorghum growth (half-bloom, hard-dough, maturity) in each year. Significant relationships between predator abundance and agricultural landscape composition appear in both years and in all three time periods, but the specific relationships of landscape variables to cotton predator levels differed between and within years. At maturity in 2001, predator levels rose as the amount of uncultivated land from 1.6 to 3.2 km distant and the perimeter shared with grain sorghum increased. During 2002, the area of grain sorghum (half-bloom) and uncultivated land (hard-dough) within 1.6 km of cotton fields were both positively related to predator numbers. Cotton planting dates and the abundance of cotton fleahoppers (Pseudatomoscelis seriatus [Reuter]) were also strongly linked to predator numbers during both years. Results suggest that the total amount of grain sorghum or uncultivated land in an area is more important than the presence of these habitats adjacent to cotton fields, and that landscape composition may sometimes be the most important factor in determining predator abundance.://000226384000001 ISI Document Delivery No.: 888OL Times Cited: 1 Cited Reference Count: 31 Cited References: *JAND SCI, 1995, SIGM IM AN SOFTW CHA *MAP CORP, 2000, MAP PROF US GUID *SPSS INC, 2000, SPSS BAS 10 0 BRIEF ALTIERI MA, 1982, CROP PROT, V1, P405 ANDOW DA, 1991, ANNU REV ENTOMOL, V36, P561 ANDOW DA, 1991, ENVIRON ENTOMOL, V20, P1228 BEETS WC, 1982, MULTIPLE CROPPING TR BRAZZLE JR, 1997, ENVIRON ENTOMOL, V26, P995 BREENE RG, 1989, SOUTHWEST ENTOMOL, V14, P159 ELLIOTT NC, 1999, LANDSCAPE ECOL, V14, P239 ELLIOTT NC, 2002, BIOL CONTROL, V24, P214 ELLIOTT NC, 2002, ENVIRON ENTOMOL, V31, P253 FYE RE, 1972, ENVIRON ENTOMOL, V6, P790 FYE RE, 1972, PANS, V18, P143 HIETALAKOIVU R, 2002, AGR ECOSYST ENVIRON, V91, P273 LANDIS DA, 2000, ANNU REV ENTOMOL, V45, P175 LEVINS R, 1969, B ENTOMOL SOC AM, V15, P237 LOPEZ EG, 1976, J ECON ENTOMOL, V69, P198 MENALLED FD, 1999, ECOL APPL, V9, P634 NICKEL JL, 1973, B ENTOMOL SOC AM, V19, P136 OSTMAN O, 2001, BASIC APPL ECOL, V2, P365 OSTMAN O, 2001, ECOL APPL, V11, P480 PIANKA ER, 1994, EVOLUTIONARY ECOLOGY, P26 PRASIFKA JR, 1999, BIOL CONTROL, V16, P223 PRASIFKA JR, 2003, ENVIRON ENTOMOL, V33, P282 RABB RL, 1976, THEORY PRACTICE BIOL, P233 ROOT RB, 1973, ECOL MONOGR, V43, P95 SANSONE CG, 2001, ENVIRON ENTOMOL, V30, P112 SLOSSER JE, 1998, SOUTHWEST ENTOMOL, V23, P31 THIES C, 1999, SCIENCE, V285, P893 VANDERLIP RL, 1993, KANSAS AGR EXPT STAT, V1203 0921-2973 Landsc. Ecol.ISI:000226384000001Texas A&M Univ, Dept Entomol, College Stn, TX 77843 USA. Texas A&M Univ, Ballinger, TX 76821 USA. Heinz, KM, Texas A&M Univ, Dept Entomol, College Stn, TX 77843 USA. kmheinz@neo.tamu.eduEnglish <7x Pratt, N. L. Barrett, G. W.2012fTiming of breeding in Ochrotomys nuttalli and Peromyscus leucopus is related to a latitudinal isotherm599-610Landscape Ecology2746breeding season geographic isotherm mean annual temperature ochrotomys nuttalli peromyscus leucopus reproduction temperate deciduous forest biome white-footed mice snakes elaphe-obsoleta small-mammal fauna black rat snakes sub-tropical population golden mouse density-dependence forest edge acorn mast dynamicsAprPrevious comparative studies on patterns of reproduction in small-mammal species focus primarily on latitudinal differences in average litter size. Few studies compare reproductive patterns among northern and southern populations at the landscape scale. Our study compares differences in seasonal patterns of reproduction in northern and southern populations of the golden mouse, Ochrotomys nuttalli, and the white-footed mouse, Peromyscus leucopus. These are remarkably similar species with regard to bioenergetics, body mass, feeding behavior, home-range size, natural history, nest-site preference, and periods of activity. Both species also exhibit very similar intraspecific seasonal patterns of reproduction across their respective geographic ranges. We found that O. nuttalli and P. leucopus switch from a summer breeding season, extending from late spring through early autumn in the north to a winter breeding season extending from late autumn through early spring in the south, near the isotherm where mean annual temperature is 15.6A degrees C (60A degrees F), or approximately 35A degrees A N latitude. This latitudinal isotherm provides a geographic benchmark to address future changes in patterns of reproduction attributed to climate change. Findings also suggest that length of the breeding season and patterns of reproduction between species partially explain why P. leucopus is typically more abundant than O. nuttalli in similar habitat types.://000302346900010-919RS Times Cited:0 Cited References Count:92 0921-2973Landscape EcolISI:000302346900010*Barrett, GW Univ Georgia, Eugene P Odum Chair Ecol, Eugene P Odum Sch Ecol, 140 E Green ST, Athens, GA 30602 USA Univ Georgia, Eugene P Odum Chair Ecol, Eugene P Odum Sch Ecol, 140 E Green ST, Athens, GA 30602 USA Univ Georgia, Eugene P Odum Chair Ecol, Eugene P Odum Sch Ecol, Athens, GA 30602 USADOI 10.1007/s10980-012-9708-5English Z<7g&Preiss, E. Martin, J. L. Debussche, M.1997pRural depopulation and recent landscape changes in a Mediterranean region: Consequences to the breeding avifauna51-61Landscape Ecology121avifauna; land-use changes; Mediterranean; rural depopulation; secondary succession; vegetation structure BIRD COMMUNITIES; SUCCESSION; MECHANISMS; MODELSArticleFebLWe studied the vegetational and avifaunistic changes following rural depopulation in an area covering 2,600 ha north of Montpellier (Southern France). The study area is covered by a mosaic of Mediterranean habitats that includes cultivation, grasslands, shrublands, and woodlands and is representative of the natural features present and of the human usage practiced so far in this part of the Mediterranean. We sampled the vegetation and the bird fauna in the same 193 census plots in 1978 and in 1992. At both the habitat and landscape scales the cover of woody plants increased significantly. Open habitats tend to disappear. As a consequence the abundance of open-habitat bird species decreased significantly whereas the abundance of forest birds increased significantly. These changes favor a pool of forest species widespread in western Europe and reduce habitat availability for open habitat and shrubland species. Many of the latter are Mediterranean species whose distribution in Western Europe could become reduced under current landscape dynamics, Our observation of more woodlands and their typical birds and of less open habitats and their associated avifauna is not consistent with the traditional worry shown by the public and the managers about the regression of forests and woodlands in the Northern Mediterranean as a consequence of fire.://A1997XQ44800006 ISI Document Delivery No.: XQ448 Times Cited: 28 Cited Reference Count: 32 Cited References: *GROUP RECH INT MO, 1985, ET EC SOC EC ZON MED *SAS I, 1985, SAS US GUID AAVIKSOO K, 1993, LANDSCAPE ECOL, V8, P287 ALES RF, 1992, LANDSCAPE ECOL, V7, P3 BARBERO M, 1990, FORET MEDITERRANEENE, V12, P194 BARRY JP, 1960, ANNEE BIOL, V36, P311 BLONDEL J, 1981, STUDIES AVIAN BIOL, V6, P414 BLONDEL J, 1988, OECOLOGIA, V75, P83 DAGET P, 1977, VEGETATIO, V34, P87 DEBUSSCHE M, 1983, CARTE ISOHYETES INTE DEBUSSCHE M, 1984, CARTES PHYSIONOMIQUE DEBUSSCHE M, 1987, ACTA OECOL, V8, P317 EVERITT BS, 1977, ANAL CONTINGENCY TAB JARVINEN O, 1989, ECOLOGICAL IMPACT AC, P39 LAUGA J, 1992, LANDSCAPE ECOL, V6, P183 LEPART J, 1983, B ECOL, V14, P133 LEPART J, 1992, LANDSCAPE BOUNDARIES, P76 LEROYLADURIE E, 1966, PAYSANS LANGUEDOC MARTIN JL, 1996, J BIOGEOGR, V23, P169 OCONNOR RJ, 1986, FARMING BIRDS OPDAM P, 1985, BIOL CONSERV, V34, P333 PICKETT STA, 1987, BOT REV, V53, P335 PICKETT STA, 1989, LONG TERM ECOLOGICAL, P71 PRODON R, 1981, OIKOS, V37, P21 ROUSVOAL D, 1973, ETUDE CLIMAT THERMIQ SCHWABE A, 1991, VEGETATIO, V95, P1 VIRKKALA R, 1991, BIOL CONSERV, V56, P223 VIRKKALA R, 1991, OIKOS, V62, P59 VITOUSEK PM, 1994, ECOLOGY, V75, P1861 YEATMANBERTHELO.D, 1991, ATLAS OISEAUX FRANCE YEATMANBERTHELO.D, 1994, NOUVEL ATLAS OISEAUX ZBINDEN N, 1981, ORNITHOL BEOB, V78, P217 0921-2973 Landsc. Ecol.ISI:A1997XQ448000068CNRS,CTR ECOL FONCT & EVOLUT,F-34033 MONTPELLIER,FRANCE.English<7BPrice, S. J. Marks, D. R. Howe, R. W. Hanowski, J. M. Niemi, G. J.2005The importance of spatial scale for conservation and assessment of anuran populations in coastal wetlands of the western Great Lakes, USA441-454Landscape Ecology204-amphibians; frogs; habitat associations; Lake Huron; Lake Michigan; landscape; logistic regression; predictive models; urbanization POND WATER CHEMISTRY; FROG RANA-SYLVATICA; SPECIES RICHNESS; LANDSCAPE COMPOSITION; BREEDING AMPHIBIANS; STOPPING RULES; CLIMATE-CHANGE; BUFFER ZONES; GREEN BAY; HABITATArticleMayDistributions of pond-breeding amphibians may be influenced by habitat factors at different spatial scales. We used anuran calling surveys to investigate the association between 5 anuran species and habitat variables measured within 100, 500, 1000, and 3000 m of sampling points at 63 coastal wetlands along the US shores of Lake Michigan and Lake Huron. Stepwise logistic regression was used to create predictive models for each species at each spatial scale. Our results confirm the view that habitat variables at multiple scales influence frog distributions, but the strength of predictive models was significantly affected by the spatial scale at which habitat variables were derived. Remotely sensed habitat variables within a 3000 m radius were among the most effective predictors of occurrence for American toad (Bufo americanus), eastern gray treefrog (Hyla versicolor), spring peeper (Pseudacris crucifer), and green frog (Rana clamitans melanota). The western chorus frog (Pseudacris triseriata) was predicted most effectively by variables derived within a 500 m radius. For the most part, these anurans exhibited species-specific responses to habitat variables; however the suite of landscape-scale variables associated with urban land use appeared in all species' regression models. Associations with landscape-scale variables coupled with well-documented habitat needs at local breeding sites suggest that conservation and assessment of frogs and toads in coastal wetlands should consider the influence of habitat variables at multiple spatial scales.://000233035100006 ISI Document Delivery No.: 980RE Times Cited: 1 Cited Reference Count: 87 Cited References: *ENV CAN, 1995, STAT GREAT LAK 1995 *ERDAS INC, 1999, ERDAS FIELD GUID VER *ESRI, 1996, ARCVIEW GIS GEOGR IN *GRAPHPAD SOFTW IN, 2003, GRAPHPAD PRISM 4 *NAT CONS GREAT LA, 1994, CONS BIOL DIV GREAT *SAS I INC, 1999, SAS VERS 8 *US GEOL SURV, 2002, NAT LAND COV CLASS ASHLEY EP, 1996, CAN FIELD NAT, V110, P403 BAILEY RG, 1995, DESCRIPTION ECOREGIO BEEBEE TJC, 1985, AMPHIBIA-REPTILIA, V6, P35 BENDEL RB, 1977, J AM STAT ASSOC, V72, P46 BERVEN KA, 1990, EVOLUTION, V44, P2047 BOSLEY TR, 1978, T WISC ACAD SCI ART, V66, P235 BRADLEY JV, 1968, DISTRIBUTION FREE ST BRAZNER JC, 1997, J GREAT LAKES RES, V23, P36 BRAZNER JC, 2000, AM MIDL NAT, V143, P250 BROWN JH, 1977, ECOLOGY, V58, P445 CARR LW, 2001, CONSERV BIOL, V15, P1071 CASPER GS, 1996, GEOGRAPHIC DISTRIBUT COLLINS JP, 1979, OCCASIONAL PAPERS MU, V686, P1 COSTANZA MC, 1979, J AM STAT ASSOC, V74, P777 DANIEL WW, 1990, APPL NONPARAMETRIC S DANZ N, IN PRESS ENV MONITOR DEMAYNADIER PG, 1999, J WILDLIFE MANAGE, V63, P441 DODD CK, 1998, CONSERV BIOL, V12, P331 DODD CK, 2003, AMPHIBIAN CONSERVATI, P94 DODGE D, 1995, AQUATIC HABITAT WETL FAHRIG L, 1995, BIOL CONSERV, V73, P177 FINDLAY CS, 1997, CONSERV BIOL, V11, P1000 GIBBONS JW, 2003, WETLANDS, V23, P630 GIBBS JP, 1998, LANDSCAPE ECOL, V13, P263 GILL DE, 1978, ECOL MONOGR, V48, P145 GLOOSCHENKO V, 1992, CAN J FISH AQUAT SCI, V49, P114 GUERRY AD, 2002, CONSERV BIOL, V16, P745 HANSKI I, 1997, METAPOPULATION BIOL, P5 HARDING JH, 1997, AMPHIBIANS REPTILES HARRIS HJ, 1981, SEL P MIDW C WETL VA, P363 HARTMANN HC, 1990, CLIMATIC CHANGE, V17, P49 HECNAR SJ, 1996, FRESHWATER BIOL, V36, P7 HECNAR SJ, 1997, CONSERV BIOL, V11, P670 HECNAR SJ, 1998, J BIOGEOGR, V25, P763 HECNAR SJ, 2004, AQUA ECOSYST HLTH MA, V7, P289 HENSHER DA, 1981, APPL DISCRETE CHOICE HITCHINGS SP, 1997, HEREDITY 2, V79, P117 HOSMER DW, 1989, APPL LOGISTIC REGRES JOHNSON CM, 2002, PREDICTING SPECIES O, P157 JOLY P, 2001, CONSERV BIOL, V15, P239 KARR JR, 1981, FISHERIES, V6, P21 KEOUGH JR, 1999, WETLANDS, V19, P821 KLUTE DS, 2002, PREDICTING SPECIES O, P335 KNUTSON MG, 1999, CONSERV BIOL, V13, P1437 KOLOZSVARY MB, 1999, CAN J ZOOL, V77, P1288 KRAMER DC, 1973, J HERPETOL, V7, P231 LAWLER SP, 1999, CONSERV BIOL, V13, P613 LEHTINEN RM, 1999, WETLANDS, V19, P1 MARSH DM, 2001, CONSERV BIOL, V15, P40 MAYNARD L, 1997, COASTAL WETLANDS MITSCH WJ, 2000, WETLANDS MLADENOFF DJ, 2001, APACK 2 22 SOFTWARE MORRISON ML, 2002, PREDICTING SPECIES O, P43 MORTSCH LD, 1998, CLIMATIC CHANGE, V40, P391 MUNGER JC, 1998, CONSERV BIOL, V12, P320 OLDHAM RS, 1966, CAN J ZOOL, V44, P63 PAVIGNANO I, 1990, AMPHIBIA-REPTILIA, V11, P311 PENTECOST ED, 1976, ENV STATUS LAKE MICH, V16 PERRET N, 2003, J ANIM ECOL, V72, P567 POPE SE, 2000, ECOLOGY, V81, P2498 REH W, 1990, BIOL CONSERV, V54, P239 RICHTER KO, 1995, WETLANDS, V15, P305 ROTHERMEL BB, 2002, CONSERV BIOL, V16, P1324 SCHROEDER EE, 1976, AM MIDL NAT, V95, P471 SEMLITSCH RD, 1988, COPEIA, P290 SEMLITSCH RD, 1998, CONSERV BIOL, V12, P1113 SEMLITSCH RD, 1998, CONSERV BIOL, V12, P1129 SEMLITSCH RD, 2000, J WILDLIFE MANAGE, V64, P615 SEMLITSCH RD, 2003, CONSERV BIOL, V17, P1219 SHANNON CE, 1949, MATH THEORY COMMUNIC SIMON TP, 2003, BIOL RESPONSE SIGNAT SINSCH U, 1990, ETHOL ECOL EVOL, V2, P65 SJOGREN P, 1991, BIOL J LINN SOC, V42, P135 SJOGRENGULVE P, 1996, METAPOPULATIONS WILD, P111 SKELLY DK, 1999, ECOLOGY, V80, P2326 SQUIRE T, 2002, HERPETOLOGICA, V58, P119 VOGT RC, 1981, NATURAL HIST AMPHIBI WEEBER RC, 2000, MARSH MONITORING PRO WHILLANS TH, 1979, J GREAT LAKES RES, V5, P195 WRIGHT AH, 1949, HDB FROGS TOADS 0921-2973 Landsc. Ecol.ISI:000233035100006@Univ Wisconsin, Cofrin Ctr Biodivers, Green Bay, WI 54311 USA. Univ Minnesota, Nat Resources Res Inst, Duluth, MN 55811 USA. Davidson Coll, Dept Biol, Davidson, NC 28035 USA. APHIS Wildlife Serv, USDA, Okemos, MI 48864 USA. Howe, RW, Univ Wisconsin, Cofrin Ctr Biodivers, MAC 212, Green Bay, WI 54311 USA. hower@uwgb.eduEnglish<7,-Pringle, H. J. R. Watson, I. W. Tinley, K. L.2006Landscape improvement, or ongoing degradation - reconciling apparent contradictions from the and rangelands of Western Australia 1267-1279Landscape Ecology218=arid shrublands; catchment function; ecological organisation; hierarchy; landscape function; landscape processes; monitoring; policy; rangeland monitoring; reporting NONEQUILIBRIUM CONCEPTS; HIERARCHICAL APPROACH; VEGETATION DYNAMICS; DESIGN ISSUES; ECOSYSTEM; ECOLOGY; SYSTEMS; DESERTIFICATION; BIODIVERSITY; BALANCEArticleNovRecent quantitative site-based monitoring and qualitative aerial and ground traverses provide contrasting assessments of the health of much of the arid shrublands of Western Australia extensively grazed by livestock ('rangelands'). Although these results seem incompatible, we explain the apparent contradictions based on landscape succession processes operating at multiple levels of ecological organisation. Specifically, we suggest that the intact areas in which site-based monitoring is conducted are contracting as catchment canalisation and desiccation increase. However, the impacts of these processes have not yet become manifest at the site scale. The site-based system addresses important regional questions. These relate to the large, relatively intact areas away from most active surface flows, which should be a focus for resource conservation, given practical limits to repairing widespread degradation with low management inputs. We provide a complementary set of questions to provide a more comprehensive audit of rangeland dynamics in the context of underlying hierarchical landscape patterns and processes that might threaten intact areas. We recognise the need to match questions and levels of ecological organisation and the implications these have for sampling. We also recognise the difficulty in producing concise statements of change for clients when reporting on complex ecological issues and processes. Without a clearly articulated, and well understood, hierarchical model of pattern and process within which apparently contradictory findings can be reported meaningfully, policy makers may be confused by the results, with the consequent risk of policy inaction.://000242089300008 b ISI Document Delivery No.: 106GP Times Cited: 0 Cited Reference Count: 56 Cited References: ALLEN TFH, 1982, HIERARCHY PERSPECTIV ALLEN TFH, 1984, RM110 USDA FOR SERV ALLEN TFH, 1992, UNIFIED ECOLOGY BASTIN GN, 2002, ECOL INDIC, V1, P247 BERGKAMP G, 1995, ENVIRON MONIT ASSESS, V37, P59 BRISKE DD, 2003, J APPL ECOL, V40, P601 BRISKE DD, 2005, RANGELAND ECOL MANAG, V58, P1 CHRISTIAN CS, 1953, CSIRO AUSTR LAND RES COUGHENOUR MB, 1993, J BIOGEOGR, V20, P383 CURRY PJ, 1994, INVENTORY CONDITION, P430 DEANGELIS DL, 1987, ECOL MONOGR, V57, P1 EVE MD, 1999, ENVIRON MONIT ASSESS, V54, P205 FRIEDEL MH, 1993, J ARID ENVIRON, V24, P241 FRIEDEL MH, 1994, RANGELAND J, V16, P16 FUHLENDORF SD, 1998, PLANT ECOL, V138, P89 FUHLENDORF SD, 1999, J VEG SCI, V10, P731 GREEN JW, 1985, CENSUS VASCULAR PLAN HACKER RB, 1984, AUST J BOT, V32, P239 HACKER RB, 1987, AUSTR J BOT, V35, P135 HOLM AM, 1987, AUSTR RANGELAND J, V9, P14 ILLIUS AW, 1999, ECOL APPL, V9, P798 ILLIUS AW, 2000, OIKOS, V89, P283 KING LC, 1963, S AFRICAN SCENERY TX LEVIN SA, 1992, ECOLOGY, V73, P1943 LUDWIG JA, 1995, ENVIRON MONIT ASSESS, V37, P231 LUDWIG JA, 2000, ENVIRON MONIT ASSESS, V64, P164 MORTON SR, 1995, J ENVIRON MANAGE, V43, P195 NICHOLLS AO, 2003, WAY FORWARD, V1, P49 NICHOLSON S, 2002, SHIFTING CAMP, P312 ONEILL RO, 1986, HIERARCHICAL CONCEPT PICKETT STA, 1999, ECOSYSTEMS WORLD, V16, P707 PICKUP G, 1985, AUSTR RANGELAND J, V7, P114 PICKUP G, 1989, AUSTR RANGELAND J, V11, P74 PRINGLE H, 2001, J AGR W AUSTR, V42, P30 PRINGLE H, 2001, P NO AUSTR BEEF IND, P49 PRINGLE HJR, 2003, ECOL MANAGE RESTOR, V4, P180 PRINGLE HJR, 2003, P 2003 INT RANG C JU PRINGLE HJR, 2004, AUSTRAL ECOL, V29, P31 PRINGLE HJR, 2004, LIVING OUTBACK, P195 PURVIS JR, 1986, AUSTR RANGELAND J, V8, P110 RYERSON DE, 2001, J VEG SCI, V12, P167 SMYTH AK, 2004, AUSTRAL ECOL, V29, P3 TINLEY K, 2001, P NO AUSTR BEEF IND, P11 TINLEY KL, 1977, THESIS U PRETORIA PR, P198 TINLEY KL, 1982, ECOL STUD, V42, P175 TINLEY KL, 1987, NATURE CONSERVATION, P347 TINLEY KL, 2002, SHIFTING CAMP, P349 TONGWAY DJ, 2004, LANDSCAPE FUNCTION A WATSON I, 2003, RANGE MANAGE NEWSLET, P11 WATSON I, 2004, AUSTRAL ECOL, V29, P16 WATSON IW, 1997, J ECOL, V85, P815 WATSON IW, 1998, RANGE MANGE NEWSLETT, P1 WILCOX DG, 1972, REPORT CONDITION GAS WU J, 1999, CANADIAN J REMOTE SE, V25, P367 WU JG, 1995, Q REV BIOL, V70, P439 WU JG, 2002, ECOL MODEL, V153, P7 0921-2973 Landsc. Ecol.ISI:000242089300008Dept Agr, Ctr Management Arid Environm, Perth, WA, Australia. Curtin Univ Technol, Perth, WA 6001, Australia. Dept Conservat & Land Management, Wanneroo, WA 6946, Australia. Watson, IW, Dept Agr, Ctr Management Arid Environm, Perth, WA, Australia. iwatson@agric.wa.gov.auEnglish <7y )Prist, P. R. Michalski, F. Metzger, J. P.2012`How deforestation pattern in the Amazon influences vertebrate richness and community composition799-812Landscape Ecology276large vertebrates deforestation patterns landscape ecology landscape configuration species persistence brazilian amazon habitat fragmentation forest fragments local extinctions brazilian amazon landscape mammals birds area abundance consequencesJulxThe effects of habitat configuration on species persistence are predicted to be most apparent when remaining habitat cover is below 30%. We tested this prediction by comparing vertebrate communities in 21 landscapes located in the southern Amazonia, including 7 control landscapes (similar to 100% of forest cover) and 14 fragmented landscapes (4 x 4 km). The fragmented landscapes retained similar proportions of forest (similar to 25%), but had contrasting configurations, resulting from two different deforestation patterns: the "fish-bone pattern" common in small properties, and the large-property pattern generally used by large ranchers. Vertebrates were surveyed in all landscapes in February-July 2009 with interviews (n = 150). We found a significant difference in reported species richness among the fish-bone, large-property, and control areas (mean = 29.3, 38.8 and 43.5 respectively). Control areas and large-properties tended to have a higher number of specialist species (mean = 13.7, and 11.7, respectively), when compared with the fish-bone pattern (5.1). Vertebrate community composition in the control and large-properties was more similar to one another than to those of the fish-bone landscapes. The number of fragments was the main factor affecting the persistence of species, being negatively associated with specialist species richness. Species richness was also positively related with the size of the largest fragment structurally connected to the studied landscapes (i.e., a regional scale effect). Our results demonstrated that the large-property pattern, which results in less fragmented landscapes, can maintain a more diverse community of large vertebrates, including top predators, which are considered fundamental for maintaining ecosystem integrity. These results support the hypothesis that landscape configuration contributes to the persistence and/or extirpation of species.://000305218000002-958DZ Times Cited:0 Cited References Count:53 0921-2973Landscape EcolISI:000305218000002Prist, PR Univ Sao Paulo, Dept Ecol, Biosci Inst, Rua Matao 321,Travessa 14, BR-05508900 Sao Paulo, Brazil Univ Sao Paulo, Dept Ecol, Biosci Inst, Rua Matao 321,Travessa 14, BR-05508900 Sao Paulo, Brazil Univ Sao Paulo, Dept Ecol, Biosci Inst, BR-05508900 Sao Paulo, Brazil Univ Fed Amapa, Postgrad Programme Trop Biodivers, BR-68902280 Macapa, AP, Brazil Procarnivoros Inst, BR-12945010 Atibaia, SP, BrazilDOI 10.1007/s10980-012-9729-0English<7Probst, J. R. Weinrich, J.1993URelating Kirtlands warbler population to changing landscape composition and structure257-271Landscape Ecology84zBREEDING DENSITY; CARRYING CAPACITY; DENDROICA-KIRTLANDII; FIRE ECOLOGY; MINIMUM AREA REQUIREMENTS; POPULATION PROJECTIONSArticleDecThe population of male Kirtland's warbler (Dendroica kirtlandii) in the breeding season has averaged 206 from 1971 to 1987. The Kirtland's warbler occupies dense jack pine (Pinus banksiana) barrens from 5 to 23 years old and from 1.4 to 5.0 m high, formerly of wildfire origin. In 1984, 73% of the males censused were found in habitat naturally regenerated from wildfire or prescribed burning. The rest were in plantations (11%) orin harvested, unburned jack pine stands stocked by natural regeneration (16%). Twenty-two percent (630 of 2,886) of the Kirtland's warbler males counted in the annual censuses from 1971 through 1984 were found in 26 stands that were unburned and naturally regenerated following harvest. From 1982 to 1987, suitable regenerating areas were barely sufficient to replace currently occupied maturing stands, so population growth was impeded. Ecosystems of suitable size and regeneration characteristics (wildfire and plantation) doubled in area by 1989. In response, the population of Kirtland's warblers increased from 167 to 398 males between 1987 and 1992, but they withdrew almost entirely from the unburned, unplanted barrens by 1989 when the area of more suitable regeneration types increased. Minimum (368 males) and maximum (542 males) population estimates for 1996 were calculated based on 1984 average density (1.9 males per 40 ha) and peak population in burns (2.8 males per 40 ha).://A1993MN73600003 IISI Document Delivery No.: MN736 Times Cited: 19 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1993MN73600003GPROBST, JR, US FOREST SERV,N CENT FOREST EXPT STN,RHINELANDER,WI 54501.English|?Procopio, N. A. Bunnell, J. F.2008|Stream and wetland landscape patterns in watersheds with different cranberry agriculture histories, southern New Jersey, USA771-786Landscape Ecology237Stream and wetland-landscape patterns in watersheds that drain active-cranberry bogs, abandoned-cranberry bogs, and forest land with no history of cranberry agriculture were compared at three different levels of detail. Stream-pattern variables included drainage density, sinuosity, and the number, density, and length of ditches. Landscape-pattern measures included wetland-patch structure (the size, shape, and number of wetland patches) and cover-type composition. The results of the stream-pattern analysis indicated that the effect of past and present cranberry agriculture on stream-drainage patterns was limited primarily to the occurrence of ditches. A greater number, density, median length, and total length of ditches were observed in cranberry and abandoned-bog basins compared to forest basins. Drainage density and sinuosity of the remaining non-ditched stream segments did not differ between basin types. Excluding areas of active-cranberry bogs where the native vegetation was removed, there was no significant difference in the relative number, size, shape, and composition of the remaining vegetation-cover types between the three basin types. The exact type and extent of vegetation removed to establish bogs in the active and abandoned basins are not known, but based on soil type and vegetation class associations, it was estimated that the largest losses were of pitch pine lowlands and cedar swamps.!://WOS:000258540300002Times Cited: 0 0921-2973WOS:00025854030000210.1007/s10980-008-9235-6n|? Proulx, Raphael Fahrig, Lenore2010^Detecting human-driven deviations from trajectories in landscape composition and configuration 1479-1487Landscape Ecology2510Dec4While landscape trajectories are increasingly used for tracking change in processes such as agricultural intensification and urbanization, analyses that combine environmental and human disturbances remain scarce. The aim of this study was to investigate the relationship between Shannon evenness, a measure of landscape composition, and spatial contagion, a measure of landscape configuration, within sixteen Canadian regions covering a gradient of land-uses and human disturbances: natural, semi-natural, urban, and agricultural. The agricultural regions showed generally lower variation in contagion and evenness and overall lower contagion values (smaller patches), leading to steeper contagion-evenness slopes than in the other region categories. In addition, the sampled agricultural regions were much more similar to each other than were the sampled regions within each of the other three region categories. These results indicate that the process of agricultural development (at least in western Canada) leads to a reduction in pattern variation and an alteration of the expected relationships among pattern metrics in agricultural regions. This possibility is supported by a neutral model of patch dynamics, suggesting that the characteristic scale of disturbances is a generic structuring process of landscape trajectories.!://WOS:000283371000002Times Cited: 0 0921-2973WOS:00028337100000210.1007/s10980-010-9523-9 <7z Pryke, J. S. Samways, M. J.2012MConservation management of complex natural forest and plantation edge effects73-85Landscape Ecology271edge zones arthropods invertebrates biodiversity multi-taxa multi-taxon grasslands pitfall trap diameter species richness ecological networks invertebrates biodiversity butterflies landscape habitat models hymenopteraJanbTimber plantation forestry is a major threat to indigenous grassland biodiversity, with ecological networks (ENs) currently being used to mitigate this threat. Being composed mostly of linear corridors, ENs create more edge than would occur naturally. To determine the minimum width of corridors for maximising biodiversity conservation, we need first to establish the extent of edge effects from plantation blocks into corridors. We compared arthropod diversity along transects that ran from within plantation blocks into grassland corridors. We also studied the edge effects of natural forest adjacent to natural grasslands within ENs. Sites in grasslands of neighbouring protected areas acted as natural reference sites against which the biodiversity of the EN transects were compared. Two types of exotic plantation trees and various tree age classes were studied. We found a 32 m edge zone from plantation blocks into grassland corridors. Few significant edge effects from plantation blocks occurred at greater distances than this, which suggested that grassland corridors with a width < 64 m are essentially all edge. However, and importantly, this situation was complex, as different arthropod taxonomic groups responded differently to edges of plantation blocks and natural forest patches. Natural forest supported many additional species, not just within the forest, but also in associated grassland corridors. This means that maintaining natural forest imbedded within the ENs will protect both indigenous grassland and indigenous forest species as well as help maintain biodiversity across this timber production landscape.://000298228300006-864HI Times Cited:1 Cited References Count:48 0921-2973Landscape EcolISI:000298228300006Pryke, JS Univ Stellenbosch, Dept Conservat Ecol & Entomol, Private Bag X1, ZA-7602 Matieland, South Africa Univ Stellenbosch, Dept Conservat Ecol & Entomol, Private Bag X1, ZA-7602 Matieland, South Africa Univ Stellenbosch, Dept Conservat Ecol & Entomol, ZA-7602 Matieland, South AfricaDOI 10.1007/s10980-011-9668-1English:|?E Pueyo, Salvador2011Desertification and power laws305-309Landscape Ecology263MarRThere is an ongoing controversy on the use of the patch-size distribution as an early warning signal for abrupt shifts to a desertified state in Mediterranean arid landscapes. This controversy started with Kefi et al.'s suggestion that, when approaching the transition point to widespread desertification, vegetation patches would switch from a power-law (PL) to a truncated power-law (TPL) distribution. Here I show that, for fundamental reasons, no untruncated power law can be found in this context, irrespective of the level of degradation. This result does not deny the importance of the findings by Kefi et al., but means that these have to be reinterpreted by moving from the PL/TPL dichotomy to other categorizations of the patch-size distribution. Physical constraints on patch-size distributions have general interest for landscape ecology.!://WOS:000288808100001Times Cited: 0 0921-2973WOS:00028880810000110.1007/s10980-010-9569-8 9|? 'Pullinger, Michael G. Johnson, Chris J.2010Maintaining or restoring connectivity of modified landscapes: evaluating the least-cost path model with multiple sources of ecological information 1547-1560Landscape Ecology2510DecHabitat connectivity is an important element of functioning landscapes for mobile organisms. Maintenance or creation of movement corridors is one conservation strategy for reducing the negative effects of habitat fragmentation. Numerous spatial models exist to predict the location of movement corridors. Few studies, however, have investigated the effectiveness of these methods for predicting actual movement paths. We used an expert-based model and a resource selection function (RSF) to predict least-cost paths of woodland caribou. Using independent data for model evaluation, we found that the expert-based model was a poor predictor of long-distance animal movements; in comparison, the RSF model was effective at predicting habitat selection by caribou. We used the Path Deviation Index (PDI), cumulative path cost, and sinuosity to quantitatively compare the spatial differences between inferred caribou movement paths and predicted least-cost paths, and quasi-random null models of directional movement. Predicted movement paths were on average straighter than inferred movement paths for collared caribou. The PDI indicated that the least-cost paths were no better at predicting the inferred paths than either of two null models-straight line paths and randomly generated paths. We found statistically significant differences in cumulative cost scores for the main effects of model and path type; however, post-hoc comparisons were non-significant suggesting no difference among inferred, random, and predicted least cost paths. Paths generated from an expert based cost surface were more sinuous than those premised on the RSF model, but neither differed from the inferred path. Although our results are specific to one species, they highlight the importance of model evaluation when planning for habitat connectivity. We recommend that conservation planners adopt similar techniques when validating the effectiveness of movement corridors for other populations and species.!://WOS:000283371000007Times Cited: 0 0921-2973WOS:00028337100000710.1007/s10980-010-9526-6ڽ7=4Puma, IngaP Lathrop, RichardG, Jr. Keuler, NicholasS2013\A large-scale fire suppression edge-effect on forest composition in the New Jersey Pinelands 1815-1827Landscape Ecology289Springer Netherlands^Edge-effect Wildfire Forest ecology Succession Wildland–urban interface New Jersey Pinelands 2013/11/01+http://dx.doi.org/10.1007/s10980-013-9924-7 0921-2973Landscape Ecol10.1007/s10980-013-9924-7English:<7Puth, L. M. Allen, T. F. H.2005Potential corridors for the rusty crayfish, Orconectes rusticus, in northern Wisconsin (USA) lakes: Lessons for exotic invasions567-577Landscape Ecology205anthropogenic effects; connectivity; corridors; exotic species; invasion; Orconectes rusticus; rusty crayfish; streams; Wisconsin TRAIL CORRIDORS; NATIONAL-PARK; GREAT-LAKES; HABITAT; DISPERSAL; PREDATION; MOVEMENT; DISPLACEMENT; CONSERVATION; MANAGEMENTArticleJul We sampled 35 lakes in northern Wisconsin to determine the presence of Orconectes rusticus, the rusty crayfish, and related this pattern to several parameters pertaining to potential invasion routes that could influence the distribution of these crayfish in the lakes. The presence of rusty crayfish in lakes was positively related to an index of human use and negatively related to the length of stream connections to other lakes containing the crayfish. Humans appear to act as vectors allowing crayfish to travel along discontinuous routes that otherwise would be inaccessible to them, and thus, provide crayfish with spatially discontinuous corridors that increase the probability of movement by channelizing the space between lakes. In contrast, streams correspond closely to the traditional definition of terrestrial corridors, in that they are spatially continuous. This distribution pattern suggests colonization operating via two corridors with two spatial scales, making management of the invasion of rusty crayfish complex.://000232205600006 C ISI Document Delivery No.: 969AK Times Cited: 0 Cited Reference Count: 48 Cited References: AARS J, 1999, ECOLOGY, V80, P1648 ALLEN TFH, 1982, HIERARCHY PERSPECTIV ALLEN TFH, 1984, RM110 USDA BENNETT AF, 1990, HABITAT CORRIDORS TH BENNETT AF, 1994, BIOL CONSERV, V68, P155 BENNINGERTRUAX M, 1992, LANDSCAPE ECOL, V6, P269 BREEN B, 1991, GARBAGE-INDEP ENV Q, V3, P18 BROWN JH, 1998, BIOGEOGRAPHY BUBB DH, 2004, FRESHWATER BIOL, V49, P357 BUCHAN LAJ, 1999, ECOL APPL, V9, P254 CAPELLI GM, 1982, LIMNOL OCEANOGR, V27, P741 CAPELLI GM, 1983, J CRUSTACEAN BIOL, V3, P548 CARLSSON B, 1992, OMEGA-INT J MANAGE S, V20, P11 CHARLEBOIS PM, 1996, J N AM BENTHOL SOC, V15, P551 CREASER EP, 1931, PAPERS MICHIGAN ACAD, V13, P257 CREASER EP, 1932, T WISC ACAD SCI, V27, P321 DIDONATO GT, 1993, CAN J FISH AQUAT SCI, V50, P1484 FORMAN RTT, 1983, EKOL CSSR, V2, P375 FRASER DF, 1999, ECOLOGY, V80, P597 GRIFFITHS RW, 1991, CAN J FISH AQUAT SCI, V48, P1381 HARRISON RL, 1992, CONSERV BIOL, V6, P293 HILL AM, 1994, ECOLOGY, V75, P2118 HOBBS RJ, 1992, TRENDS ECOL EVOL, V7, P389 HRABIK TR, 1999, CAN J FISH AQUAT S1, V56, P35 LIDICKER WZ, 1999, LANDSCAPE ECOL, V14, P333 LIGHT T, 2003, FRESHWATER BIOL, V48, P1886 LODGE DM, 1985, NAT HIST, V8, P33 LODGE DM, 1994, NORD J FRESHWATER RE, V69, P111 LONEY B, 1991, NATURE CONSERVATION, V2, P299 LORMAN JG, 1978, FISHERIES, V3, P8 MAGNUSON JJ, 1975, S WAT QUAL MAN BIOL, P66 MAGNUSON JJ, 1976, T AM FISH SOC, V1, P1 MILLS EL, 1993, J GREAT LAKES RES, V19, P1 NICHOLLS AO, 1991, NATURE CONSERVATION, V2, P49 NOSS RF, 1987, CONSERV BIOL, V1, P159 OLSEN TM, 1991, CAN J FISH AQUAT SCI, V48, P1853 PACE F, 1991, LANDSCAPE LINKAGES B, P105 PANETTA FD, 1991, NATURE CONSERVATION, V2, P341 PERRY WL, 1997, CAN J FISH AQUAT SCI, V54, P120 PUTH LM, 2001, CONSERV BIOL, V15, P21 SAUNDERS DA, 1991, NATURE CONSERVATION, V2, P421 SAVIDGE JA, 1987, ECOLOGY, V68, P660 SIMBERLOFF D, 1987, CONSERV BIOL, V1, P63 SIMBERLOFF D, 1992, CONSERV BIOL, V6, P493 SOKAL RR, 1995, BIOMETRY PRINCIPLES SOULE ME, 1991, NATURE CONSERVATION, V2, P3 TAYLOR CA, 1996, J CRUSTACEAN BIOL, V16, P547 TYSER RW, 1992, CONSERV BIOL, V6, P253 0921-2973 Landsc. Ecol.ISI:000232205600006Univ Wisconsin, Dept Bot, Madison, WI 53706 USA. Puth, LM, Yale Univ, Sch Forestry & Environm, 370 Prospect St, New Haven, CT 06520 USA. linda.puth@yale.eduEnglish<7HQi, Y. Henderson, M. Xu, M. Chen, J. Shi, P. J. He, C. Y. Skinner, G. W.2004`Evolving core-periphery interactions in a rapidly expanding urban landscape: The case of Beijing375-388Landscape Ecology194Beijing; core-periphery; hierarchical regional space; landscape dynamics; urbanization; land use change model LAND-USE CHANGE; CHINA; MODEL; EVOLUTION; DYNAMICS; GISArticle^We characterized and analyzed the dynamics of a rapidly expanding urban landscape of Beijing Municipality, based on the Hierarchical Regional Space (HRS) model. We focused on ecological processes such as flows of energy, materials and population between the urban core and its periphery, and how these processes co-evolved with urbanization. We treated the HRS as an alternative to the cellular automata ( CA) approach to characterizing and modeling of landscape dynamics. With LANDSAT data, we showed that the urban area of Beijing expanded from 269 km(2) to 901 km(2) in the period from 1975 to 1997, an increase of 2.35 times in 22 years. Meanwhile, a number of secondary urban centers formed on areas that used to be sparsely populated around the city. These secondary centers quickly expanded and ultimately merged with each other and with the urban core. The changes in spatial pattern and organization were accompanied by evolution of urban functions and particularly the interactions between the urban core and its periphery. We demonstrated a dramatic increase in dependence of the urban core on the periphery as well as the core's influence on the periphery with a case analysis of the vegetable supply to Beijing. The tightening link between the city and its periphery reinforces the urbanization process and further drives the transformation of the region's landscape. We conclude that the HRS model is capable of characterizing the patterns and processes of complex and dynamic landscapes such as the case of Beijing, and this model has great potential for quantitative modeling of human dominated landscapes as well.://000221879000003 ISI Document Delivery No.: 827DM Times Cited: 1 Cited Reference Count: 43 Cited References: *IPCC, 2001, CLIM CHANG 2001 SCI AHL V, 1996, HIERARCHY THEORY VIS ANDERSON JR, 1976, 964 US GEOL SURV BASKIN CW, 1966, CENTRAL PLACES SO GE BATTY M, 1994, REG STUD, V28, P553 BESSEY KM, 2002, ECOSYSTEMS, V5, P360 CARTIER C, 2002, MOD CHINA, V28, P79 CHAPIN F, 2000, ECOLOGICAL STUDIES, V152 CHASEDUNN C, 1991, CORE PERIPHERY RELAT CLARKE KC, 1998, INT J GEOGR INF SCI, V12, P699 COSTANZA R, 1977, ENERGY ANAL MODELS U, P96 CRISSMAN LW, 1976, REGIONAL ANAL, V1, P183 HAGERSTRAND T, 1967, NE STUDY GEOGRAPHY, V13, P1 HENDERSON M, 1999, P INT S GEOINF SOC A HOUGHTON RA, 1999, SCIENCE, V285, P574 HUANG SL, 1998, ENVIRON PLANN B, V25, P391 JENERETTE GD, 2001, LANDSCAPE ECOL, V16, P611 KRUGMAN P, 1991, J POLIT ECON, V99, P483 LANDIS J, 1998, ENVIRON PLANN B, V25, P795 LAVELY W, 1989, J ASIAN STUD, V48, P100 LUCK MA, 2001, ECOSYSTEMS, V4, P782 MANN S, 1984, MOD CHINA, V10, P79 PONTIUS RG, 1993, COORDINATED RES PROG, V4 QI Y, 1994, THESIS SUNY ESF SYRA QI Y, 1996, GEO INFO SCI, V2, P24 QIAO X, 1998, J BEIJING AGR COLL, V13, P82 REED WJ, 2002, J REGIONAL SCI, V42, P1 SHI PJ, 2001, P IGBP LUCC C AUG 27 SKINNER GW, 1977, CITY LATE IMPERIAL C, P275 SKINNER GW, 1978, CHINA Q, V76, P733 SKINNER GW, 1994, CORNELL E ASIA SERIE, V70 SKINNER GW, 2000, SOC SCI HIST, V24, P613 SKOLE D, 1993, SCIENCE, V260, P1909 TURNER BL, 1993, 24 IGBP VONTHUNEN JH, 1842, ISOLIERERTE STAAT BZ VONTHUNEN JH, 1966, ISOLATED STATE WALLERSTEIN I, 1991, GEOPOLITICS GEOCULTU WEGENER M, 1994, J AM PLANN ASSOC, V60, P17 WILSON AG, 1977, MODELS CITIES REGION, P1 WOLDENBERG MJ, 1971, P COLSTON RES SOC, V22, P147 WU JG, 1995, Q REV BIOL, V70, P439 WU JG, 2002, ECOL MODEL, V153, P7 ZIPF GK, 1949, HUMAN BEHAV PRINCIPL 0921-2973 Landsc. Ecol.ISI:000221879000003Beijing Normal Univ, Coll Resources & Environm, Beijing 100875, Peoples R China. Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA. Rutgers State Univ, Dept Ecol, Evolut & Nat Resources Ctr Remote Sensing & Spati, New Brunswick, NJ 08901 USA. Univ Calif Davis, Dept Anthropol, Davis, CA 95616 USA. Qi, Y, Beijing Normal Univ, Coll Resources & Environm, Beijing 100875, Peoples R China. yqi@nature.berkeley.eduEnglish<7Qi, Y. Wu, J. G.1996yEffects of changing spatial resolution on the results of landscape pattern analysis using spatial autocorrelation indices39-49Landscape Ecology111landscape patterns; spatial analysis; spatial autocorrelation; scale effect; grain size; Moran Coefficient; Geary Ratio; Cliff-Ord statistic DYNAMICS; ECOLOGY; SCALE; STATISTICS; MODELArticleFebUnderstanding the relationship between pattern and scale is a central issue in landscape ecology. Pattern analysis is necessarily a critical step to achieve this understanding. Pattern and scale are inseparable in theory and in reality. Pattern occurs on different scales, and scale affects pattern to be observed. The objective of our study is to investigate how changing scale might affect the results of landscape pattern analysis using three commonly adopted spatial autocorrelation indices, i.e., Moran Coefficient, Geary Ratio, and Cliff-Ord statistic. The data sets used in this study are spatially referenced digital data sets of topography and biomass in 1972 of Peninsular Malaysia. Our results show that all three autocorrelation indices were scale-dependent. In other words, the degree of spatial autocorrelation measured by these indices vary with the spatial scale on which analysis was performed. While all the data sets show a positive spatial autocorrelation across a range of scales, Moran coefficient and Cliff-Ord statistic decrease and Geary Ratio increases with increasing grain size, indicating an overall decline in the degree of spatial autocorrelation with scale. The effect of changing scale varies in their magnitude and rate of change when different types of landscape data are used. We have also explored why this could happen by examining the formulation of the Moran coefficient. The pattern of change in spatial autocorrelation with scale exhibits threshold behavior, i.e., scale effects fade away after certain spatial scales are reached (for elevation). We recommend that multiple methods be used for pattern analysis whenever feasible, and that scale effects must be taken into account in all spatial analysis.://A1996UN74400004 ISI Document Delivery No.: UN744 Times Cited: 47 Cited Reference Count: 44 Cited References: ALLEN TFH, 1982, HIERARCHY PERSPECTIV BROWN S, 1994, EFFECTS LAND USE CHA, P117 BURGESS RL, 1981, FOREST ISLAND DYNAMI CLIFF AD, 1973, SPATIAL AUTOCORRELAT CLIFF AD, 1981, SPATIAL PROCESSES MO COSTANZA R, 1994, LANDSCAPE ECOL, V9, P47 CULLINAN VI, 1992, LANDSCAPE ECOL, V7, P211 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FORTIN MJ, 1989, VEGETATIO, V83, P209 GETIS A, 1978, MODELS SPATIAL PROCE GETIS A, 1992, GEOGR ANAL, V24, P189 GOODCHILD MF, 1986, CONCEPTS TECHNIQUES, V47 GREIGSMITH P, 1952, ANN BOT, V16, P293 GRIFFITH DA, 1988, SPECIAL TOPICS EXPLO GRIFFITH DA, 1990, PROF GEOGR, V42, P481 KERSHAW KA, 1957, ECOLOGY, V38, P291 LEGENDRE P, 1989, VEGETATIO, V80, P107 LEGENDRE P, 1993, ECOLOGY, V74, P1659 LEVIN SA, 1992, ECOLOGY, V73, P1943 LEVIN SA, 1993, PATCH DYNAMICS MEENTEMEYER V, 1987, LANDSCAPE HETEROGENE, P15 MILNE BT, 1988, APPL MATH COMPUT, V27, P67 MORRIS DW, 1987, ECOLOGY, V68, P362 NELLIS MD, 1989, LANDSCAPE ECOLOGY, V2, P93 ODLAND J, SAGE PUBLICATIONS ONEILL RV, 1986, HIERARCHICAL CONCEPT ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 OPDAM P, 1991, LANDSCAPE ECOL, V5, P93 RISSER PG, 1984, SPECIAL PUBLICATION, V2 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P245 TURNER MG, 1991, QUANTITATIVE METHODS WIENS JA, 1989, LANDSCAPE ECOLOGY, V3, P87 WIENS JA, 1993, OIKOS, V66, P369 WU J, 1992, CHIN J ECOL, V11, P41 WU J, 1992, COENOSES, V7, P137 WU J, 1992, P 4 INT C AS EXPT PO WU J, 1994, P 6 INT C EC INTECOL, P165 WU J, 1995, IN PRESS ACADEMIC PR WU JG, 1991, B MATH BIOL, V53, P911 WU JG, 1991, ECOL MODEL, V58, P249 WU JG, 1993, ECOL MODEL, V65, P221 WU JG, 1994, ECOL MONOGR, V64, P447 ZONNEVELD IS, 1990, CHANGING LANDSCAPES 0921-2973 Landsc. Ecol.ISI:A1996UN74400004<UNIV CALIF SAN DIEGO,SCRIPPS INST OCEANOG,LA JOLLA,CA 92093.English|? Qian, Song S.2014;Statistics in ecology is for making a "principled" argument937-939Landscape Ecology296Jul!://WOS:000338331600001Times Cited: 0 0921-2973WOS:00033833160000110.1007/s10980-014-0042-y <7IQuattrochi, D. A. Luvall, J. C.1999hThermal infrared remote sensing for analysis of landscape ecological processes: methods and applications577-598Landscape Ecology146+land-atmosphere energy exchanges landscape thermal responses thermal infrared remote sensing SURFACE-ENERGY BALANCE SOIL-WATER CONTENT NOAA-AVHRR DATA LAND-SURFACE DAILY EVAPOTRANSPIRATION MULTISPECTRAL SCANNER REGIONAL EVAPOTRANSPIRATION TEMPERATURE MEASUREMENTS SPATIAL-DISTRIBUTION SATELLITE DATAReviewDecThermal infrared (TIR) remote sensing data can provide important measurements of surface energy fluxes and temperatures, which are integral to understanding landscape processes and responses. One example of this is the successful application of TIR remote sensing data to estimate evapotranspiration and soil moisture, where results from a number of studies suggest that satellite-based measurements from TIR remote sensing data can lead to more accurate regional-scale estimates of daily evapotranspiration. With further refinement in analytical techniques and models, the use of TIR data from airborne and satellite sensors could be very useful for parameterizing surface moisture conditions and developing better simulations of landscape energy exchange over a variety of conditions and space and time scales. Thus, TIR remote sensing data can significantly contribute to the observation, measurement, and analysis of energy balance characteristics (i.e., the fluxes and redistribution of thermal energy within and across the land surface) as an implicit and important aspect of landscape dynamics and landscape functioning. The application of TIR remote sensing data in landscape ecological studies has been limited, however, for several fundamental reasons that relate primarily to the perceived difficulty in use and availability of these data by the landscape ecology community, and from the fragmentation of references on TIR remote sensing throughout the scientific literature. It is our purpose here to provide evidence from work that has employed TIR remote sensing for analysis of landscape characteristics to illustrate how these data can provide important data for the improved measurement of landscape energy response and energy flux relationships. We examine the direct or indirect use of TIR remote sensing data to analyze landscape biophysical characteristics, thereby offering some insight on how these data can be used more robustly to further the understanding and modeling of landscape ecological processes.://000082563500006 ISI Document Delivery No.: 235VP Times Cited: 15 Cited Reference Count: 112 Cited References: *EOS, 1995, MTPE EOS REF HDB *EOS, 1997, MTPE EOS DAT PROD HD, V1 *FIFE, 1992, J GEOPHYS RES, V97, P18343 *MTPE, 1995, MTPE EOS REF HDB ANDERSON JE, 1992, GEOCARTO INT, V7, P3 ANDERSON JM, 1984, INT J REMOTE SENS, V5, P1 ARTIS DA, 1982, REMOTE SENS ENVIRON, V12, P313 ASRAR G, 1989, THEORY APPL OPTICAL ASTLING EG, 1989, ASPRSACSM ANN CONV F, V3, P217 BERK AL, 1989, MODTRAN MODERATE RES BOYD DS, 1996, INT J REMOTE SENS, V17, P249 BUETTNER KJK, 1965, J GEOPHYS RES, V70, P1329 CARLSON TN, 1981, J APPL METEOROL, V20, P67 CARLSON TN, 1986, REMOTE SENSING REV, V1, P197 CARLSON TN, 1989, REMOTE SENS ENVIRON, V29, P197 CARLSON TN, 1995, REMOTE SENS ENVIRON, V54, P161 CHEN E, 1979, J APPL METEOROL, V18, P992 CHEN E, 1982, J APPL METEOROL, V121, P1528 CHOUDHURY BJ, 1991, REV GEOPHYS, V29, P217 CRACKNELL AP, 1996, INT J REMOTE SENS, V17, P431 DAVIS AP, 1988, APPL THERMAL IMAGING, P1 DONNER BL, 1986, FOREST SCI, V32, P614 ESTES JE, 1983, MANUAL REMOTE SENSIN, P987 FRIEDL MA, 1994, REMOTE SENS ENVIRON, V48, P1 GAUTHIER F, 1994, INT J REMOTE SENS, V15, P1981 GILLESPIE AR, 1984, GEOPHYS RES LETT, V11, P1153 GILLIES RR, 1995, J APPL METEOROL, V34, P745 GILLIES RR, 1997, INT J REMOTE SENS, V18, P3145 GOODIN DG, 1995, GEOCARTO INT, V2, P19 GOOSSENS R, 1991, LANDSCAPE ECOL, V5, P175 GOWARD SN, 1985, REMOTE SENS ENVIRON, V18, P137 GRAETZ RD, 1990, REMOTE SENSING BIOSP, P5 GREEGOR DH, 1986, BIOSCIENCE, V36, P429 GRIGGS M, 1968, J GEOPHYS RES, V73, P7545 HAINESYOUNG RH, 1992, LANDSCAPE ECOL, V7, P253 HAINESYOUNG RH, 1994, LANDSCAPE ECOLOGY GI HALL FG, 1988, LANDSCAPE ECOLOGY, V2, P3 HALL FG, 1992, J GEOPHYS RES-ATMOS, V97, P19061 HEILMAN JL, 1976, REMOTE SENS ENVIRON, V5, P137 HOBBS RJ, 1990, REMOTE SENSING BIOSP, P203 HOLBO HR, 1989, REMOTE SENS ENVIRON, V27, P11 IDSO SB, 1975, SCIENCE, V189, P991 IDSO SB, 1976, J APPL METEOROL, V15, P811 IVERSON LR, 1994, LANDSCAPE ECOL, V9, P159 JACKSON RH, 1986, J MOD AFR STUD, V24, P1 KAHLE AB, 1984, REMOTE SENS ENVIRON, V16, P211 KAHLE AB, 1987, GEOPHYSICS, V52, P858 KALMA JD, 1986, J CLIMATOL, V6, P413 KIDDER SQ, 1995, SATELLITE METEOROLOG KNEIZYS FX, 1983, 846 US AIR FORC GEOP KUSTAS WP, 1994, AGR FOREST METEOROL, V71, P337 LAGOUARDE JP, 1992, BOUND-LAY METEOROL, V44, P245 LAMBIN EF, 1996, INT J REMOTE SENS, V17, P463 LANDSBERG HE, 1981, URBAN CLIMATE LAYMON C, 1998, GEOMORPHOLOGY, V21, P329 LILLESAND TM, 1987, REMOTE SENSING IMAGE LO CP, 1997, INT J REMOTE SENS, V18, P287 LUVALL JC, 1989, REMOTE SENS ENVIRON, V27, P1 LUVALL JC, 1990, PHOTOGRAMM ENG REM S, V56, P1393 LUVALL JC, 1991, QUANTITATIVE METHODS, P127 LUVALL JC, 1997, IN PRESS LANDSCAPE E LUVALL JC, 1997, SCALE REMOTE SENSING, P169 METZGER JP, 1996, LANDSCAPE ECOL, V11, P65 MILLER DH, 1981, ENERGY SURFACE EARTH MOODY A, 1995, LANDSCAPE ECOL, V10, P363 MORAN MS, 1991, J ENVIRON QUAL, V20, P725 NELLIS MD, 1982, REMOTE SENS ENVIRON, V12, P229 NELLIS MD, 1989, LANDSCAPE ECOLOGY, V2, P93 NEMANI R, 1993, J APPL METEOROL, V32, P548 NEMANI RR, 1989, AGR FOREST METEOROL, V44, P245 NEMANI RR, 1989, J APPL METEOROL, V28, P276 NICHOL JE, 1995, PHOTOGRAMM ENG REM S, V61, P1159 NIEUWENHUIS GJA, 1985, INT J REMOTE SENS, V6, P1319 NORMAN JM, 1995, REMOTE SENS ENVIRON, V51, P157 OKE TR, 1987, BOUNDARY LAYER CLIMA OTTLE C, 1994, J HYDROL, V158, P241 PALLUCONI FD, 1985, JPL PUBLICATION, V8532 PETERSEN GW, 1987, REMOTE SENS ENVIRON, V23, P253 PETERSON DL, 1989, THEORY APPL OPTICAL, P429 PIERCE LL, 1988, REMOTE SENS ENVIRON, V24, P405 PIERCE LL, 1990, PHOTOGRAMM ENG REM S, V56, P579 PRICE JC, 1977, J GEOPHYS RES, V82, P2582 PRICE JC, 1980, WATER RESOUR RES, V16, P787 PRICE JC, 1982, IEEE T GEOSCI REMOTE, V20, P286 PRICE JC, 1989, THEORY APPL OPTICAL, P578 QUATTROCHI DA, 1991, QUANTITATIVE METHODS, P51 QUATTROCHI DA, 1994, INT J REMOTE SENS, V15, P1991 QUATTROCHI DA, 1995, REMOTE SENSING REV, V12, P255 QUATTROCHI DA, 1998, ATMOS ENVIRON, V32, P19 REGINATO RJ, 1976, J GEOPHYS RES, V81, P1617 REGINATO RJ, 1985, REMOTE SENS ENVIRON, V18, P75 REUTTER H, 1994, INT J REMOTE SENS, V15, P95 RISSER PG, 1984, ILLINOIS NATURAL HIS, V2 RISSER PG, 1987, LANDSCAPE HETEROGENE, P3 SADER SA, 1986, REMOTE SENS ENVIRON, V19, P105 SANDHOLT I, 1993, REMOTE SENS ENVIRON, V46, P164 SCHNEIDER ED, 1994, MATH COMPUT MODEL, V19, P25 SEGUIN B, 1983, INT J REMOTE SENS, V4, P371 SELLERS P, 1995, B AM METEOROL SOC, V76, P1549 SELLERS PJ, 1992, J GEOPHYS RES-ATMOS, V97, P18345 SELLERS PJ, 1995, REMOTE SENS ENVIRON, V51, P3 SELLERS PJ, 1997, J GEOPHYS RES-ATMOS, V102, P28731 SHORT NM, 1982, NASA SOER GJR, 1980, REMOTE SENS ENVIRON, V9, P27 SUGITA M, 1993, INT J REMOTE SENS, V14, P1659 SUN JL, 1994, J APPL METEOROL, V33, P1341 TACONET O, 1986, J CLIM APPL METEOROL, V25, P1752 TACONET O, 1986, J CLIM APPL METEOROL, V25, P284 TUCKER CJ, 1985, SCIENCE, V227, P369 TURNER MG, 1991, QUANTITATIVE METHODS VIDAL A, 1989, INT J REMOTE SENS, V10, P1327 WILSON SB, 1986, INT J REMOTE SENS, V7, P379 0921-2973 Landsc. Ecol.ISI:000082563500006NASA, Global Hydrol & Climate Ctr, George C Marshall Space Flight Ctr, Marshall Space Flight Ce, AL 35812 USA. Quattrochi, DA, NASA, Global Hydrol & Climate Ctr, George C Marshall Space Flight Ctr, SD60, Marshall Space Flight Ce, AL 35812 USA.English !|?0Quinn, John E. Johnson, Ron J. Brandle, James R.2014IIdentifying opportunities for conservation embedded in cropland anthromes 1811-1819Landscape Ecology2910DecAnthromes characterize terrestrial ecological patterns in terms of human populations and how these populations use the land. However, data are needed to assess the conservation value of habitats embedded in anthromes, particularly when possible conservation opportunities do not reflect the traditional focus of conservation in a region. One such region is the central Great Plains of North America where the grassland biome has been replaced by a cropland anthrome with a landscape mosaic dominated by arable crops with small patches of grass and woody cover embedded within. Grassland birds have been the primary focus of avian conservation research and practice, a reflection of the biome classification. Yet conservation of other bird species may be a missed conservation opportunity better identified via anthromes. In this project we evaluated the variation in abundance of shrubland and open forest birds in response to heterogeneity and availability of woody and grass cover at local (100 m) and landscape (5,000 m) scales. We found that local heterogeneity, a trait of croplands not grasslands, was the best predictor of abundance, with five species of conservation concern more abundant in heterogeneous sites. There was limited response to woody cover and a mixed response across scale to grassland cover with local response positive and landscape negative. These data suggest that increasing heterogeneity in the Great Plains cropland anthrome may provide a unique conservation opportunity. In particular, farm systems have the capacity to complement regional species conservation efforts by increasing heterogeneity. Importantly these conservation efforts may not come at the expense of grassland bird conservation or crop production. The limited response to extensive grassland cover at the larger scale suggests that in Great Plains agroecosystems, a diverse mix of crops, pasture, and linear habitats would allow farmers to continue to produce food while contributing to the conservation of species of concern.!://WOS:000346920900014Times Cited: 0 0921-2973WOS:00034692090001410.1007/s10980-014-0098-8u|?gQuintas-Soriano, Cristina Castro, Antonio J. Garcia-Llorente, Marina Cabello, Javier Castro, Hermelindo2014XFrom supply to social demand: a landscape-scale analysis of the water regulation service 1069-1082Landscape Ecology296JulWorldwide water managers and policy makers are faced by the increasing demands for limited and scarce water resources, particularly in semi-arid ecosystems. This study assesses water regulation service in semi-arid ecosystems of the southeastern Iberian Peninsula. Comparisons between the supply-demand sides were analyzed across different landscape units. We mapped the biophysical supply as the potential groundwater recharged by aquifers and water supplies from reservoirs. The social demand was focused on an analysis of water consumed or used for irrigation and the stakeholder's perceptions regarding water regulation importance and vulnerability. Results show that some landscape units are able to maintain and conserve water regulation service when the volume of recharge water by aquifers and the water supply from reservoirs is greater than its consumption (e.g. rural landscape units). However, we also found potential social conflicts in landscape units where water consumption and use is much greater than the water recharge and supply. This particularly occurs in the non-protected littoral areas with the highest water consumption and where water is perceived as a non-important and vulnerable natural resource. Overall, our results emphasized the importance of assessing ecosystem services from both supply to demand sides, for identifying social conflicts and potential trade-offs, and to provide practical information about how to integrate the ecosystem service research into landscape management and planning.!://WOS:000338331600011Times Cited: 3 0921-2973WOS:00033833160001110.1007/s10980-014-0032-0<7SRanius, T. Kindvall, O.2006xExtinction risk of wood-living model species in forest landscapes as related to forest history and conservation strategy687-698Landscape Ecology215coarse woody debris; extinction debt; population viability analysis; restoration; saproxylic; SLOSS OLD-GROWTH FORESTS; DEAD WOOD; NORWAY SPRUCE; BOREAL FOREST; HABITAT LOSS; BIODIVERSITY; RESTORATION; MANAGEMENT; SWEDEN; REQUIREMENTSArticleJulDead wood is a critical resource for biodiversity in boreal forests. We analysed the persistence of five model species inhabiting dead wood. By parameterising a metapopulation model (the incidence function model), the model species were all assigned characteristics that makes it likely that they have disappeared from some (20%) forest landscapes with a long history of forest management. In the metapopulation model, a forest stand (5 ha) was regarded as a habitat patch. The amount of habitat in each patch was obtained from models of dead wood dynamics of Norway spruce in central Sweden. Dead wood generated by altered management over the entire landscape was found to be less efficient in reducing extinction risks in comparison to the same amount of dead wood generated by protecting reserves. Because generation of dead wood by altered management is often less expensive than setting aside reserves, it is difficult to determine which conservation measure is most cost-efficient. In a landscape subjected to forestry for the first time, it was better to preserve a few large reserves than many small ones. However, in a managed, highly fragmented forest landscape it was better to set aside many small reserves. The reason for this was that small plots with high habitat quality could be selected, while large reserves originally contained habitats both of high and low quality, and the rate of habitat quality increase was low. A strategy for biodiversity conservation in a managed forest landscape should include information about the history of the landscape, the current amount and spatial distribution of forest habitats, and the potential for rapid restoration of forest habitats, both on managed and unmanaged forest land.://000240500100005 ISI Document Delivery No.: 083ZE Times Cited: 0 Cited Reference Count: 43 Cited References: 2000, SVENSK FSC STANDARD 2001, IUCN RED LIST CATEGO 2003, ENNALLISTAMINEN SUOJ 2004, SKOGSSTATISTISK ARSB AKCAKAYA HR, 2004, CONSERV BIOL, V18, P526 AXELSSON AL, 2001, FOREST ECOL MANAG, V147, P109 BAKER WL, 1999, SPATIAL MODELING FOR, P333 BERGLUND H, 2003, BIOL CONSERV, V112, P319 BRYANT D, 1997, LAST FRONTIER FOREST BURKEY TV, 1995, CONSERV BIOL, V9, P527 DAHLBERG A, 2004, VEDELEVANDE ARTERS K DIAMOND JM, 1975, BIOL CONSERV, V7, P129 EDMAN M, 2004, ECOL APPL, V14, P893 EDMAN M, 2004, OIKOS, V104, P35 ESSEEN PA, 1997, ECOLOGICAL B, V46, P16 FRIDMAN J, 2000, FOREST ECOL MANAG, V131, P23 GARDENFORS U, 2005, 2005 RED LIST SWEDIS HANSKI I, 1994, J ANIM ECOL, V63, P151 HANSKI I, 1999, METAPOPULATION ECOLO HANSKI I, 2000, ANN ZOOL FENN, V37, P271 HAUTALA H, 2004, BIODIVERS CONSERV, V13, P1541 HUXEL GR, 1999, RESTOR ECOL, V7, P309 JONSELL M, 1998, BIODIVERS CONSERV, V7, P749 JONSELL M, 1999, J INSECT CONSERVATIO, V3, P145 JONSSON BG, 2005, SILVA FENN, V39, P289 JONSSON M, 2003, ECOL ENTOMOL, V28, P159 JONSSON M, 2006, BIOL CONSERV, V127, P443 KOUKI J, 2001, SCAND J FOR RES S, V3, P27 KUULUVAINEN T, 2002, SILVA FENN, V36, P409 LARSSON S, 2001, SCAND J FOR RES S, V3, P5 LINDENMAYER DB, 2002, CONSERVING FOREST BI LINDHE A, 2004, FOREST ECOL MANAG, V203, P1 NILSSON SG, 2003, ENTOMOL TIDSKR, V124, P137 PUTZ FE, 2001, CONSERV BIOL, V15, P7 RAIVIO S, 2001, SCAND J FOR RES S, V9, P99 RANIUS T, 2003, FOREST ECOL MANAG, V182, P13 RANIUS T, 2004, BIOL CONSERV, V119, P51 RANIUS T, 2004, CAN J FOREST RES, V34, P1025 SIITONEN J, 2000, BIOL CONSERV, V94, P211 SIITONEN J, 2001, ECOLOGICAL B, V49, P11 SINGER MT, 1997, CAN J FOREST RES, V27, P1222 SJOGRENGULVE P, 2000, ECOLOGICAL B, V48, P53 WRIGHT SJ, 1983, OIKOS, V41, P466 0921-2973 Landsc. Ecol.ISI:000240500100005Swedish Univ Agr Sci, Dept Entomol, SE-75007 Uppsala, Sweden. Swedish Specias Informat Ctr, SE-75007 Uppsala, Sweden. Ranius, T, Swedish Univ Agr Sci, Dept Entomol, POB 7044, SE-75007 Uppsala, Sweden. thomas.ranius@entom.slu.seEnglish <7{-Ratas, U. Puurmann, E. Roosaare, J. Rivis, R.2003fA landscape-geochemical approach in insular studies as exemplified by islets of the eastern Baltic Sea173-184Landscape Ecology182Zbird island landscape geochemistry sea regression shoreline sodium soil vegetation ESTONIAArticleThe main objective of our investigations is to find out the primary geochemical properties of insular landscapes in order to ascertain the landscape stability on an area of land uplifting in the conditions of a regressive sea. Therefore we focus our study on the landscapes of Kolga Bay islets, which are located near the Estonian coast in the Gulf of Finland. A landscape-geochemical approach of landscape study improves the mapping of insular landscapes and understanding of processes of landscape development. Besides land use changes, land uplift and marine influence shape the landscape patterns of island through topography and subsurface water. We propose geochemical typology of landscapes based on substance movement (eluvial, superwatery, subwatery), field studies on islands, and chemical analysis of soil and water samples. From a landscape geochemical perspective, types of matter fluxes mainly control stability of an insular landscape. Interactions between geochemical, ecosystem and geomorphic processes reveal that islands behave as systems, rather than merely a sequence of interdependent soil-vegetation complexes along topographic gradients.://000183770300006 ISI Document Delivery No.: 694JB Times Cited: 0 Cited Reference Count: 25 Cited References: CHORLEY RJ, 1971, PHYSICAL GEOGRAPHY S FORMAN RT, 1986, LANDSCAPE ECOLOGY FORTESCUE JAC, 1980, ENV GEOCHEMISTRY HOL GLAZOVSKAYA MA, 1981, TEKHNOGENNYE POTOKI, P7 GLAZOWSKAYA MA, 1964, GEOCHEMICAL FUNDAMEN HOWARD J, 1980, GEOFORUM, V11, P85 JANSSON AM, 1991, LINKING NATURAL ENV, P97 KARBLANE H, 1996, HDB PLANT NUTR FERTI MILNE G, 1989, SOIL MORPHOLOGY GENS, P361 NOBLE IR, 1999, INTEGRATING HYDROLOG, P297 PAAL J, 1997, CLASSIFICATION ESTON PEIL T, 1999, STOCKHOLM STUDIES HU, V8 PERELMAN AI, 1975, LANDSCAPE GEOCHEMIST POLYNOW B, 1956, SELECTED WORKS PUURMANN E, 1990, SOV SOIL SCI, V22, P25 RATAS U, 1988, GENESIS ISLETS GEOCO RATAS U, 1995, J COASTAL CONSERVATI, V1, P119 RATAS U, 1997, PUBLICATION I ECOLOG, V5, P66 RATAS U, 2000, ESTONIA GEOGRAPHICAL, P124 VALLNER L, 1988, J GEODYN, V9, P215 VESTERGAARD P, 1978, MEDDR GRONLAND, V204, P1 VILBERG G, 1933, TARTU, V239, P231 VILBERG G, 1933, TARTU, V39, P131 ZONNEVELD IS, ECOSYSTEM CLASSIFICA, V23, P94 ZONNEVELD IS, 1989, LANDSCAPE ECOLOGY, V3, P67 0921-2973 Landsc. Ecol.ISI:000183770300006Tallin Pedag Univ, Inst Ecol, EE-10137 Tallinn, Estonia. Silma Nat Reserve, EE-91301 Vormst, Estonia. Univ Tartu, Inst Geog, EE-51014 Tartu, Estonia. Ratas, U, Tallin Pedag Univ, Inst Ecol, Kevade St 2, EE-10137 Tallinn, Estonia.English|7Ravi, S. D'odorico, P.2009zPost-fire resource redistribution and fertility island dynamics in shrub encroached desert grasslands: a modeling approach325-335Landscape Ecology243land degradation desertification shrub encroachment soil erosion fires woody plant encroachment semiarid shrubland cellular-automata grazing systems global change wind erosion land-use savanna fire desertificationMarA common form of land degradation in desert grasslands is associated with the relatively rapid encroachment of woody plants, a process that has important implications on ecosystem structure and function, as well as on the soil hydrological and biogeochemical properties. Until recently this grassland to shrubland transition was thought to be highly irreversible. However recent studies have shown that at the early stages of shrub encroachment in desert grasslands, there exists a very dynamic shrub-grass transition state with enough grass connectivity between the shrub islands to allow for fire spread. In this state fire could play a major role in determining the dominance of grasses and their recovery from the effects of overgrazing. Using a spatially explicit cellular automata model, we show how the patch-scale feedbacks between fires and soil erosion affects resource redistribution and vegetation dynamics in a mixed grass-shrub plant community at landscape to regional scales. The results of this study indicate that at its early stages, the grassland-to-shrubland transition can be reversible and that the feedbacks between fire and soil erosion processes may play a major role in determining the reversibility of the system.://000263419500003-408EY Times Cited:2 Cited References Count:39 0921-2973ISI:000263419500003Ravi, S Univ Arizona, Tucson, AZ 85721 USA Univ Arizona, Tucson, AZ 85721 USA Univ Virginia, Dept Environm Sci, Charlottesville, VA 22904 USADoi 10.1007/S10980-008-9307-7English|?1 #Rayfield, B. Fortin, M. J. Fall, A.2010LThe sensitivity of least-cost habitat graphs to relative cost surface values519-532Landscape Ecology254Maintaining and restoring connectivity among high-quality habitat patches is recognized as an important goal for the conservation of animal populations. To provide an efficient measure of potential connectivity pathways in heterogeneous landscapes, least-cost route analysis has been combined with graph-theoretical techniques. In this study we use spatially explicit least-cost habitat graphs to examine how matrix quality and spatial configuration influence assessments of habitat connectivity. We generated artificial landscapes comprised of three landcover types ranked consistently from low to high quality: inhospitable matrix, hospitable matrix, and habitat. We controlled the area and degree of fragmentation of each landcover in a factorial experiment for a total of 20 combinations replicated 100 times. In each landscape we compared eight sets of relative landcover qualities (cost values of 1 for habitat, between 1.5 and 150 for hospitable matrix, and 3-10,000 for inhospitable matrix). We found that the spatial location of least-cost routes was sensitive to differences in relative cost values assigned to landcover types and that the degree of sensitivity depended on the spatial structure of the landscape. Highest sensitivity was found in landscapes with fragmented habitat and between 20 and 50% hospitable matrix; sensitivity decreased as habitat fragmentation decreased and the amount of hospitable matrix increased. As a means of coping with this sensitivity, we propose identifying multiple low-cost routes between pairs of habitat patches that collectively delineate probable movement zones. These probable movement zones account for uncertainty in least-cost routes and may be more robust to variation in landcover cost values.!://WOS:000275444100003Times Cited: 0 0921-2973WOS:00027544410000310.1007/s10980-009-9436-7|?/Read, C. F. Duncan, D. H. Vesk, P. A. Elith, J.2008Biological soil crust distribution is related to patterns of fragmentation and landuse in a dryland agricultural landscape of southern Australia 1093-1105Landscape Ecology239The dryland agricultural landscape of north-west Victoria, Australia, includes isolated remnants of eucalypt woodland that are exposed to ongoing disturbance from sheep grazing and cropping activity. Biological soil crusts are a functionally important feature of these woodland communities. We used a modern form of regression (boosted regression tree (BRT) models) to investigate relationships between crust abundance and environmental and landscape variables. We also investigated whether the use of broad morphological groups of crust organisms is more informative than simply measuring total crust cover. Remnant size was the single most influential variable for crust abundance, with negligible crust cover in small patches (< 5 ha). The BRT model also identified relationships between crust abundance and available P, soil C and perennial grass. We argue that disturbance from stock grazing and camping is the mechanism driving these relationships. Other variables related to crust abundance were proximity to the windward edge, litter cover and tree cover. Morphological groups showed a differential response to some variables, suggesting assessment of total cover may mask important patterns in community structure. Crust disturbance represents a serious issue for maintenance of ecosystem function in the study region, particularly loss of crusts from small remnants because the majority of remnants are small.!://WOS:000260283100008Times Cited: 0 0921-2973WOS:00026028310000810.1007/s10980-008-9270-3ڽ7 ?Reding, DawnM Cushman, SamuelA Gosselink, ToddE Clark, WilliamR2013sLinking movement behavior and fine-scale genetic structure to model landscape connectivity for bobcats (Lynx rufus)471-486Landscape Ecology283Springer NetherlandsmLandscape genetics Least cost path analysis Telemetry Resource selection function Effective distance Movement 2013/03/01+http://dx.doi.org/10.1007/s10980-012-9844-y 0921-2973Landscape Ecol10.1007/s10980-012-9844-yEnglish |? @Redon, Mathilde Berges, Laurent Cordonnier, Thomas Luque, Sandra2014bEffects of increasing landscape heterogeneity on local plant species richness: how much is enough?773-787Landscape Ecology295May]Contemporary landscape ecology continues to explore the causes and consequences of landscape heterogeneity across a range of scales, and demands for the scientific underpinnings of landscape planning and management still remains high. The spatial distribution of resources can be a key element in determining habitat quality, and that in turn is directly related to the level of heterogeneity in the system. In this sense, forest habitat mosaics may be more affected by lack of heterogeneity than by structural fragmentation. Nonetheless, increasing spatial heterogeneity at a given spatial scale can also decrease habitat patch size, with potential negative consequences for specialist species. Such dual effect may lead to hump-backed shape relationships between species diversity and heterogeneity, leading to three related assumptions: (i) at low levels of heterogeneity, an increase in heterogeneity favours local and regional species richness, (ii) there is an optimum heterogeneity level at which a maximum number of species is reached, (iii) further increase in spatial heterogeneity has a negative effect on local and regional species richness, due to increasing adverse effects of habitat fragmentation. In this study, we investigated the existence of a hump-shaped relationship between local plant species richness and increasing forest landscape heterogeneity on a complex mosaic in the French Alps. Forest landscape heterogeneity was quantified with five independent criteria. We found significant quadratic relationships between local forest species richness and two heterogeneity criteria indicators, showing a slight decrease of forest species richness at very high heterogeneity levels. Species richness-landscape heterogeneity relationships varied according to the heterogeneity metrics involved and the type of species richness considered. Our results support the assumption that intermediate levels of heterogeneity may support more species than very high levels of heterogeneity, although we were not able to conclude for a systematic negative effect of very high levels of heterogeneity on local plant species richness.!://WOS:000334689900002Times Cited: 0 0921-2973WOS:00033468990000210.1007/s10980-014-0027-x:<7QReid, R. S. Kruska, R. L. Muthui, N. Taye, A. Wotton, S. Wilson, C. J. Mulatu, W.2000Land-use and land-cover dynamics in response to changes in climatic, biological and socio-political forces: the case of southwestern Ethiopia339-355Landscape Ecology154driving forces Ethiopia land-cover change land tenure policy land-use change settlement policy trypanosomosis tsetse DEVELOPING-COUNTRIES CATTLEArticleMayFew studies of land-use/land-cover change provide an integrated assessment of the driving forces and consequences of that change, particularly in Africa. Our objectives were to determine how driving forces at different scales change over time, how these forces affect the dynamics and patterns of land use/land cover, and how land-use/land-cover change affects ecological properties at the landscape scale. To accomplish these objectives, we first developed a way to identify the causes and consequences of change at a landscape scale by integrating tools from ecology and the social sciences and then applied these methods to a case study in Ghibe Valley, southwestern Ethiopia. Maps of land-use/land-cover change were created from aerial photography and Landsat TM imagery for the period, 1957-1993. A method called 'ecological time lines' was developed to elicit landscape-scale explanations for changes from long-term residents. Cropland expanded at twice the speed recently (1987-1993) than two decades ago (1957-1973), but also contracted rapidly between 1973-1987. Rapid land-use/land cover change was caused by the combined effects of drought and migration, changes in settlement and land tenure policy, and changes in the severity of the livestock disease, trypanosomosis, which is transmitted by the tsetse fly. The scale of the causes and consequences of land-use/land-cover change varied from local to sub-national (regional) to international and the links between causes and consequences crossed scales. At the landscape scale, each cause affected the location and pattern of land use/land cover differently. The contraction of cropland increased grass biomass and cover, woody plant cover, the frequency and extent of savanna burning, and the abundance of wildlife. With recent control of the tsetse fly, these ecological changes are being reversed. These complex patterns are discussed in the context of scaling issues and current conceptual models of land-use/land-cover change.://000086006700004 ISI Document Delivery No.: 296DA Times Cited: 25 Cited Reference Count: 58 Cited References: *CONSTR ENG RES LA, 1993, GRASS 4 1 US REF MAN *PROV MIL ADM COUN, 1975, 31 PMAC ALLEN TFH, 1982, HIERARCHY PERSPECTIV BAUER B, 1992, TROP MED PARASITOL, V43, P41 BILSBORROW RE, 1987, WORLD DEV, V15, P183 BILSBORROW RE, 1992, AMBIO, V21, P37 BLAIKIE P, 1987, LAND DEGRADATION SOC BOSERUP E, 1965, CONDITIONS AGR GROWT BOSERUP E, 1981, POPULATION TECHNOLOG BROWN K, 1994, CAUSES DEFORESTATION CAMPBELL DJ, 1990, FOOD FOODWAYS, V4, P143 CLEAVER KM, 1994, REVERSING SPIRAL POP CONELLY WT, 1994, HUM ECOL, V22, P145 DEJENE A, 1990, ENV FAMINE POLITICS FORD J, 1971, ROLE TRYPANOSOMIASIS FOX J, 1995, AMBIO, V24, P328 GOVEREH J, 1998, INTEGRATED APPROACH, P165 GRUBLER A, 1994, CHANGES LAND USE LAN, P287 HOSTE CM, 1987, THESIS U P M CURIE P HOUGHTON RA, 1994, BIOSCIENCE, V44, P305 JAHNKE HE, 1988, ILCA ILRAD LIVESTOCK, P3 JORDAN AM, 1986, TRYPANOSOMIASIS CONT KALU AU, 1991, TROPICAL ANIMAL HLTH, V23, P215 KAMUANGA M, 1998, INTEGRATED APPROACH, P222 KATES RW, 1992, ENVIRONMENT, V34, P4 KLINK CA, 1993, WORLDS SAVANNAS EC D, P259 LEAK SGA, 1993, ACTA TROP, V53, P121 LEAK SGA, 1995, B ENTOMOL RES, V85, P241 LELE U, 1989, 4 MADIA WORLD BANK MCCANN JC, 1995, PEOPLE PLOW AGR HIST, P1800 MCMILLAN DE, 1993, SERIES RIVER BLINDNE MURPHREE MW, 1993, WORLDS SAVANNAS EC D, P139 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PENNER JE, 1994, CHANGES LAND USE LAN, P175 REED D, 1996, STRUCTURAL ADJUSTMEN REID RS, 1995, P 5 INT RANG C SALT, P468 REID RS, 1997, J APPL ECOL, V34, P731 RIEBSAME WE, 1994, BIOSCIENCE, V44, P350 ROBINSON JB, 1991, INT SOC SCI J, V43, P629 ROCKWELL RC, 1994, CHANGES LAND USE LAN, P357 RUBENSON S, 1991, AMBIO, V20, P179 SANDERSON S, 1994, CHANGES LAND USE LAN, P329 SCHMINK M, 1987, LANDS RISK 3 WORLD L, P38 SLINGENBERGH J, 1992, WORLD ANIM REV, V70, P30 SNYDER KA, 1996, HUM ECOL, V24, P315 STEDMANEDWARDS P, 1998, ROOT CAUSES BIODIVER STONICH S, 1995, SOCIAL CAUSES ENV DE SWALLOW BM, 1998, INTEGRATED APPROACH, P67 SWARTZ N, 1995, SOCIAL CAUSES ENV DE SWYNNERTON CFM, 1936, T ROYAL ENTOMOLOGICA, V84, P1 TURNER BL, 1990, GLOBAL ENVIRON CHANG, V1, P14 TURNER BL, 1991, QUANTITATIVE METHODS TURNER BL, 1994, CHANGES LAND USE LAN, P3 TURTON D, 1988, ECOLOGY SURVIVAL, P261 WANGUI E, 1997, COLLABORATIVE RES EN, P22 WILLIAMS M, 1994, CHANGES LAND USE LAN, P97 WILSON CJ, 1997, CONSERV BIOL, V11, P435 YOUNG MD, 1993, WORLDS SAVANNAS EC D, P81 0921-2973 Landsc. Ecol.ISI:000086006700004Int Livestock Res Inst, Nairobi, Kenya. Int Livestock Res Inst, Addis Abeba, Ethiopia. Reid, RS, Int Livestock Res Inst, POB 30709, Nairobi, Kenya.English'<7Remillard, M. M. Welch, R. A.1992oGIS technologies for aquatic macrophyte studies. 1. Database development and changes in the aquatic environment151-162Landscape Ecology73`GEOGRAPHIC INFORMATION SYSTEM (GIS); DATABASE DEVELOPMENT; AQUATIC MACROPHYTES; LANDSCAPE CHANGEArticleSepGeographic information system (GIS) and digital database technologies provide a link between landscape-scale ecological studies and resource management applications. A case study involves the development of an extensive GIS database for upper Lake Marion, South Carolina that includes macrophyte distributions for 1972-1988, bathymetry, sedimentation and water chemistry. This database was utilized to assess changes in the aquatic environment related to management practices such as herbicide applications for aquatic plant control. Although the herbicides were found to be very effective, spraying must be repeated annually to maintain open water areas clear of aquatic vegetation. Without herbicides macrophytes quickly reinvade and proceed in normal successional patterns to establish submergent and emergent aquatic plant beds. The PC-based procedures developed in this study can be utilized by local resource managers to assess the impact of management practices on the aquatic environment.://A1992JW40100002 IISI Document Delivery No.: JW401 Times Cited: 12 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1992JW40100002WREMILLARD, MM, UNIV GEORGIA,DEPT GEOG,CTR REMOTE SENSING & MAPPING SCI,ATHENS,GA 30602.English<7Remillard, M. M. Welch, R. A.1993GGIS technologies for aquatic macrophyte studies - modeling applications163-175Landscape Ecology83\GEOGRAPHIC INFORMATION SYSTEM (GIS); REMOTE SENSING; AQUATIC MACROPHYTES; LANDSCAPE MODELINGArticleSepA GIS database developed for Lake Marion, South Carolina was utilized to assess existing relationships between aquatic macrophyte distributions and environmental parameters affecting plant growth. The significance of water depth, sedimentation, nitrogen, phosphorus, top dissolved oxygen, bottom dissolved oxygen, percent light and absolute light was tested using GIS overlay techniques and the Chi Square test of independence. Specific levels of the eight parameters found to be spatially related to aquatic vegetation were then utilized to develop a provisional cartographic model describing optimum growth conditions for aquatic macrophytes. Model validation by comparing predicted vegetation with actual vegetation distributions indicated only water depth and sedimentation data layers are necessary for predicting more than 90 percent of emergent and submergent distributions. Resource managers can use this model to identify lake areas that are susceptible to excessive macrophyte growth and require special attention.://A1993MB34000003 IISI Document Delivery No.: MB340 Times Cited: 10 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1993MB34000003WREMILLARD, MM, UNIV GEORGIA,DEPT GEOG,CTR REMOTE SENSING & MAPPING SCI,ATHENS,GA 30602.Englishڽ7,#Remmel, TarmoK Fortin, Marie-Josée2013HCategorical, class-focused map patterns: characterization and comparison 1587-1599Landscape Ecology288Springer NetherlandsVExpectation Comparison Random chance Fragmentation Spatial autocorrelation Binary maps 2013/10/01+http://dx.doi.org/10.1007/s10980-013-9905-x 0921-2973Landscape Ecol10.1007/s10980-013-9905-xEnglish3<7YRempel, R. S. Kushneriuk, R. S.2003The influence of sampling scheme and interpolation method on the power to detect spatial effects of forest birds in Ontario (Canada)741-757Landscape Ecology188habitat associations interpolation kriging landscape ecology power analysis spatial accuracy assessment spatial ecology songbird population abundance STATISTICAL POWER LANDSCAPE PATTERNS POPULATION TRENDS SCALE ECOLOGY AUTOCORRELATION FRAGMENTATION GEOSTATISTICS PREDICTION SIMULATIONArticleSpatial ecology is becoming an increasingly important component of resource management, and the general monitoring of how human activities affect the distribution and abundance of wildlife. Yet most work on the reliability of sampling strategies is based on a non-spatial analysis of variance paradigm, and little work has been done assessing the power of alternative spatial methods for creating reliable maps of animal abundance. Such a map forms a critical response variable for multiple scale studies relating landscape structure to biotic function. The power to reconstruct patterns of distribution and abundance is influenced by sample placement strategy and density, the nature of spatial auto-correlation among points, and by the technique used to extrapolate points into an animal abundance map. Faced with uncertainty concerning the influence of these factors, we chose to first synthesize a model reference system of known properties and then evaluate the relative performance of alternative sampling and mapping procedures using it. We used published habitat associations of tree nesting boreal neo-tropical birds, a classified habitat map from the Manitou Lakes area of northwestern Ontario, and point count means and variances determined from field studies in boreal Canada to create 4 simulated models of avian abundance to function as reference maps. Four point sampling strategies were evaluated by 4 spatial mapping methods. We found mixed-cluster sampling to be an effective point sampling strategy, particularly when high habitat fragmentation was avoided by restricting samples to habitat patches > 10 ha in size. We also found that of the 4 mapping methods, only stratified ordinary point kriging (OPK) was able to generate maps that reproduced an embedded landscape-scale spatial effect that reduced nesting bird abundance in areas of higher forest age-class fragmentation. Global OPK was effective only for detecting broader, regional-scale differences.://000188716100002  ISI Document Delivery No.: 770HA Times Cited: 4 Cited Reference Count: 49 Cited References: ANDREN H, 1994, OIKOS, V71, P355 AUSTEN MJW, 2001, CONDOR, V103, P701 BELLEHUMEUR C, 1998, LANDSCAPE ECOL, V13, P15 BENEDETTICECCHI L, 2001, ECOL APPL, V11, P783 BOONE RB, 2000, LANDSCAPE ECOL, V15, P63 BOULINIER T, 2001, ECOLOGY, V82, P1159 BURROUGH PA, 2001, ENVIRON ECOL STAT, V8, P361 CARLSON M, 2001, THESIS U ALBERTA EDM DALE MRT, 2002, ECOSCIENCE, V9, P162 DAVIS BM, 1987, MATH GEOL, V19, P242 DESSARD H, 1999, ANN FOR SCI, V56, P651 ELKIE PC, 2001, FOREST ECOL MANAG, V147, P253 ELLIOTT JM, 1977, SOME METHODS STAT AN FORTIN MJ, 1989, VEGETATIO, V83, P209 FORTIN MJ, 2002, ECOSCIENCE, V9, P213 FOSTER DR, 1998, ECOSYSTEMS, V1, P497 FOSTER JR, 2001, FOREST ECOL MANAG, V151, P211 GOOVAERTS P, 1997, GEOSTATISTICS NATURA GUNNARSSON F, 1998, SCAND J FOREST RES, V13, P237 HALL FG, 1988, LANDSCAPE ECOLOGY, V2, P3 HAYES JP, 1997, CONSERV BIOL, V11, P273 HOBSON KA, 1999, ECOL APPL, V9, P849 HOBSON KA, 2000, ECOSCIENCE, V7, P267 HUNSAKER CT, 2001, SPATIAL UNCERTAINTY KOTLIAR NB, 1990, OIKOS, V59, P253 LEGENDRE P, 1989, VEGETATIO, V80, P107 LEGENDRE P, 1993, ECOLOGY, V74, P1659 LICHSTEIN JW, 2002, ECOL MONOGR, V72, P445 LIEBHOLD AM, 2002, ECOGRAPHY, V25, P553 LIN YP, 2001, ENVIRON MONIT ASSESS, V69, P239 LOWELL K, 1999, SPATIAL ACCURACY ASS MCKENNEY DW, 1998, CAN J ZOOL, V76, P1922 MEISEL JE, 1998, LANDSCAPE ECOL, V13, P347 POTVIN F, 2001, ECOSCIENCE, V8, P399 ROSSI RE, 1992, ECOL MONOGR, V62, P277 ROY PS, 2000, BIOL CONSERV, V95, P95 ROYLE JA, 1999, J AGRIC BIOL ENVIR S, V4, P29 RYAN KC, 2002, SILVA FENN, V36, P13 SADAHIRO Y, 1999, 9 CSIS U TOK DEP URB SAURA S, 2000, LANDSCAPE ECOL, V15, P661 STEIDL RJ, 1997, J WILDLIFE MANAGE, V61, P270 THOMPSON FR, 2002, J FIELD ORNITHOL, V73, P141 VALLIANT R, 2000, FINITE POPULATION SA VANGROENIGEN JW, 2000, GEODERMA, V97, P223 VENIER LA, 1999, J BIOGEOGR, V26, P315 VERNIER PR, 2002, PREDICTING SPECIES O, P559 VILLARD MA, 1996, ECOLOGY, V77, P59 WALLERMAN J, 2002, CAN J FOREST RES, V32, P509 ZAR JH, 1984, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000188716100002Lakehead Univ, Ontario Minist Nat Resources, Ctr No Forest Ecosyst Res, Thunder Bay, ON P7B 5E1, Canada. Rempel, RS, Lakehead Univ, Ontario Minist Nat Resources, Ctr No Forest Ecosyst Res, Thunder Bay, ON P7B 5E1, Canada. rob.rempel@mnr.gov.on.caEnglish |?bRen, Yin Deng, Luying Zuo, Shudi Luo, Yunjian Shao, Guofan Wei, Xiaohua Hua, Lizhong Yang, Yusheng2014Geographical modeling of spatial interaction between human activity and forest connectivity in an urban landscape of southeast China 1741-1758Landscape Ecology2910Dec{Geographical detector models provide a quantitative approach for evaluating spatial correlations among ecological factors, population density and landscape connectivity. Here, we used a geographical model to assess the influence of different gradients of urbanization, human activities and various environmental factors on the connectivity of urban forest landscapes in Xiamen, China from 1996 to 2006. Our overarching hypothesis is that human activity has modified certain ecological factors in a way that has affected the connectivity of urban forest landscapes. Therefore, spatiotemporal distributions of landscape connectivity should be similar to those of ecological factors and can be represented quantitatively. Integral indices of connectivity and population density were employed to represent urban forest landscape connectivity and human activity, respectively. We then simulated the spatial relationship between forest patches and population density with Conefor 2.6 software. A geographical detector model was used to identify the dominant factors that affect urban forest landscape connectivity. The results showed that a distance of 600 m was the threshold of node importance. Mean annual temperature, mean annual precipitation, elevation, patch area, population density and dominant species had significant effects on the node importance. Mean annual temperature was more significant than population density in controlling the spatial pattern of the delta of the integral index of connectivity (dIIC). The spatial interaction between population density and various ecological factors as well as their linearly enhanced or nonlinearity enhanced urban forest landscape connectivity. In conclusion, a combination of graph theory and geographical detector models is effective for quantitatively evaluating interactive relationships among ecological factors, population density and landscape connectivity.!://WOS:000346920900009Times Cited: 0 0921-2973WOS:00034692090000910.1007/s10980-014-0094-z ~?hRenfrew, R. B. Ribic, C. A.2008WMulti-scale models of grassland passerine abundance in a fragmented system in Wisconsin181-193Landscape Ecology23Fragmentation of grasslands has been implicated in grassland bird population declines. Multi-scale models are being increasingly used to assess potential factors that influence grassland bird presence, abundance, and productivity. However, studies rarely assess fragmentation metrics, and seldom evaluate more than two scales or interactions among scales. We evaluated the relative importance of characteristics at multiple scales to patterns in relative abundance of Savannah Sparrow (Passerculus sandwichensis), Grasshopper Sparrow (Ammodramus savannarum), Eastern Meadowlark (Sturnella magna), and Bobolink (Dolichonyx oryzivorus). We surveyed birds in 74 southwestern Wisconsin pastures from 1997 to 1999 and compared models with explanatory variables from multiple scales: within-patch vegetation structure (microhabitat), patch (macrohabitat), and three landscape extents. We also examined interactions between macrohabitat and landscape factors. Core area of pastures was an important predictor of relative abundance, and composition of the landscape was more important than configuration. Relative abundance was frequently higher in pastures with more core area and in landscapes with more grassland and less wooded area. The direction and strength of the effect of core pasture size on relative abundance changed depending on amount of wooded area in the landscape. Relative abundance of grassland birds was associated with landscape variables more frequently at the 1200-m scale than at smaller scales. To develop better predictive models, parameters at multiple scales and their interactive effects should be included, and results should be evaluated in the context of microhabitat variability, landscape composition, and fragmentation in the study area."://WOS:000252636100007 Times Cited: 0WOS:000252636100007(10.1007/s10980-007-9179-2|ISSN 0921-2973n<7'Renofalt, B. M. Jansson, R. Nilsson, C.2005=Spatial patterns of plant invasiveness in a riparian corridor165-176Landscape Ecology202Helianthus annuus; invasiveness; Northern Sweden; riparian vegetation; river; species richness; Vindel River SPECIES RICHNESS; UNITED-STATES; BOREAL RIVERS; HOT-SPOTS; DIVERSITY; INVASIBILITY; INVASION; DISPERSAL; SCALE; COMMUNITIESArticleFeb Analysis of landscape-scale patterns of plant invasiveness can assist in interpreting spatial patterns of plant species richness. We investigated downstream variation in plant invasiveness in the riparian corridor of the free-flowing Vindel River in northern Sweden by introducing seeds of an alien species, Helianthus annuus, in 0.25 m(2) plots of natural vegetation from mountain headwaters to the coast and found a significant downstream pattern with middle reaches having the highest invasiveness. We related invasiveness to species richness, both on a reach scale (200-m long stretches of riverbank encompassing the experimental plots) and on the scale of experimental plots. We found no significant correlation between plant invasiveness and species richness, neither at the reach nor at the plot scale. The number of available soil substrates shows a significant positive quadratic relationship with location along the river and substrate fineness shows a near significant negative quadratic relationship with location along the river, with middle reaches having coarser substrates. Several studies have shown that plant species richness in riparian corridors often exhibits a quadratic pattern with highest species richness in the middle reaches of a river, similar to the pattern we found for invasiveness. Although species richness per se might not be a primary factor for invasibility, the same habitat conditions as those supporting plant species richness, can help in explaining large-scale patterns of plant invasion in riparian zones.://000230299600004 > ISI Document Delivery No.: 942RN Times Cited: 1 Cited Reference Count: 52 Cited References: *USDA, 2004, US INV WEEDS ALVAREZ ME, 2002, ECOL APPL, V12, P1434 ANDERSSON E, 2000, J BIOGEOGR, V27, P1095 ANDERSSON E, 2000, REGUL RIVER, V16, P83 ANDERSSON E, 2002, FRESHWATER BIOL, V47, P1674 ANGSTROM A, 1974, SVERIGES KLIMAT BROWN RL, 2003, ECOLOGY, V84, P32 BYERS JE, 2003, ECOLOGY, V84, P1428 CHORLEY R, 1984, GEOMORPHOLOGY DEFERRARI CM, 1994, J VEG SCI, V5, P247 DEUTSCHEWITZ K, 2003, GLOBAL ECOL BIOGEOGR, V12, P299 DITOMASO JM, 1998, WEED TECHNOL, V12, P326 ELTON CS, 1958, ECOLOGY INVASIONS AN FORMAN RTT, 1986, LANDSCAPE ECOLOGY FOSTER BL, 2003, J ECOL, V91, P999 GOULD WA, 1997, CAN J BOT, V75, P1748 JANSSON R, 2000, ECOLOGY, V81, P899 KNOPS JMH, 1999, ECOL LETT, V2, P286 KROK TOB, 1984, SVENSK FLORA LEMAITRE DC, 2002, FOREST ECOL MANAG, V160, P143 LEVINE JM, 1999, OIKOS, V87, P15 LEVINE JM, 2000, SCIENCE, V288, P852 LEVINE JM, 2001, OIKOS, V95, P397 LONSDALE WM, 1999, ECOLOGY, V80, P1522 MACK RN, 2000, ECOL APPL, V10, P689 MALANSON GP, 1993, RIPARIAN LANDSCAPES MAY RM, 1975, ECOLOGY EVOLUTION CO, P81 MERRITT DM, 2002, ECOL APPL, V12, P1071 NAEEM S, 2000, OIKOS, V91, P97 NILSSON C, 1989, ECOLOGY, V70, P77 NILSSON C, 1991, J APPL ECOL, V28, P963 NILSSON C, 1991, J BIOGEOGR, V18, P533 NILSSON C, 1995, REGUL RIVER, V11, P55 NILSSON C, 1999, ACTA PHYTOGEOGRAPHIC, V84, P135 PIMENTEL D, 2000, BIOSCIENCE, V50, P53 PLANTYTABACCHI AM, 1996, CONSERV BIOL, V10, P598 PRIEURRICHARD AH, 2000, ECOL LETT, V3, P412 SAX DF, 2002, DIVERS DISTRIB, V8, P193 STACHOWICZ JJ, 1999, SCIENCE, V286, P1577 STADLER J, 2000, ECOGRAPHY, V23, P169 STOHLGREN TJ, 1999, ECOL MONOGR, V69, P25 SUNDBORG A, 1980, 51 UNGI UPPS U DEP P TILMAN D, 1997, ECOLOGY, V78, P81 TREXLER JC, 1993, ECOLOGY, V74, P1629 VITOUSEK PM, 1997, NEW ZEAL J ECOL, V21, P1 WARD JV, 2002, FRESHWATER BIOL, V47, P517 WARDLE DA, 2001, OIKOS, V95, P161 WILCOVE DS, 1998, BIOSCIENCE, V48, P607 WITH KA, 2002, CONSERV BIOL, V16, P1192 WRIGHT JF, 1984, FRESHWATER BIOL, V14, P221 ZAVALETA E, 2000, AMBIO, V29, P462 ZOBEL M, 2000, ECOLOGY, V81, P3274 0921-2973 Landsc. Ecol.ISI:000230299600004Umea Univ, Dept Ecol & Environm Sci, Landscape Ecol Grp, SE-90187 Umea, Sweden. Mid Sweden Univ, Dept Nat & Environm Sci, SE-85170 Sundsvall, Sweden. Renofalt, BM, Umea Univ, Dept Ecol & Environm Sci, Landscape Ecol Grp, Uminova Sci Pk, SE-90187 Umea, Sweden. birgitta.renofalt@eg.umu.seEnglish_|?%Requena-Mullor, Juan M. Lopez, Enrique Castro, Antonio J. Cabello, Javier Virgos, Emilio Gonzalez-Miras, Emilio Castro, Hermelindo2014fModeling spatial distribution of European badger in arid landscapes: an ecosystem functioning approach843-855Landscape Ecology295MayUnderstanding the factors determining the spatial distribution of species is a major challenge in ecology and conservation. This study tests the use of ecosystem functioning variables, derived from satellite imagery data, to explore their potential use in modeling the distribution of the European badger in Mediterranean arid environments. We found that the performance of distribution models was enhanced by the inclusion of variables derived from the Enhanced Vegetation Index (EVI), such as mean EVI (a proxy for primary production), the coefficient of variation of mean EVI (an indicator of seasonality), and the standard deviation of mean EVI (representing spatial heterogeneity of primary production). We also found that distributions predicted by remote sensing data were consistent with the ecological preferences of badger in those environments, which may be explained by the link between EVI-derived variables and the spatial and temporal variability of food resource availability. In conclusion, we suggest the incorporation of variables associated with ecosystem function into species modeling exercises as a useful tool for improving decision-making related to wildlife conservation and management.!://WOS:000334689900007Times Cited: 0 0921-2973WOS:00033468990000710.1007/s10980-014-0020-4|?'Restani, M. Davies, J. M. Newton, W. E.2008aImportance of agricultural landscapes to nesting burrowing owls in the Northern Great Plains, USA977-987Landscape Ecology238Anthropogenic habitat loss and fragmentation are the principle factors causing declines of grassland birds. Declines in burrowing owl (Athene cunicularia) populations have been extensive and have been linked to habitat loss, primarily the decline of black-tailed prairie dog (Cynomys ludovicianus) colonies. Development of habitat use models is a research priority and will aid conservation of owls inhabiting human-altered landscapes. From 2001 to 2004 we located 160 burrowing owl nests on prairie dog colonies on the Little Missouri National Grassland in North Dakota. We used multiple linear regression and Akaike's Information Criterion to estimate the relationship between cover type characteristics surrounding prairie dog colonies and (1) number of owl pairs per colony and (2) reproductive success. Models were developed for two spatial scales, within 600 m and 2,000 m radii of nests for cropland, crested wheatgrass (Agropyron cristatum), grassland, and prairie dog colonies. We also included number of patches as a metric of landscape fragmentation. Annually, fewer than 30% of prairie dog colonies were occupied by owls. None of the models at the 600 m scale explained variation in number of owl pairs or reproductive success. However, models at the 2,000 m scale did explain number of owl pairs and reproductive success. Models included cropland, crested wheatgrass, and prairie dog colonies. Grasslands were not included in any of the models and had low importance values, although percentage grassland surrounding colonies was high. Management that protects prairie dog colonies bordering cropland and crested wheatgrass should be implemented to maintain nesting habitat of burrowing owls.!://WOS:000259481900008Times Cited: 0 0921-2973WOS:00025948190000810.1007/s10980-008-9259-yr?Rex, K.D. G.P. Malanson1990,The Fractal Shape of Riparian Forest Patches249-258Landscape Ecology445Fractals, Floodplain, Iowa, Rivers, Landscape ecologyRemnant patches of a forest corridor were examined along the Iowa and Cedar Rivers, Iowa. A fractal dimension was found for these patches which was incorporated with the perimeter: area ratio in an index of shape. This index was then regressed on 5 hydrogeomorphic variables hypothesized to represent processes which were derived from topographic maps; the impact variable used was the proportion of perimeter that was occupied by a road, railroad, transmission line, urban or other built area, or a straight line judged to be agricultural. Three variables remained significant in a reduced model: human impact, valley width, and stream sinuosity, but together the three accounted for only 24% of the variance in patch shape. The fractal perimeter: area ratio increased with human impact, probably because of reduced area, and decreased with valley width, which allowed more extensive forest on wide floodplains, and with sinuosity, which resulted in small patches isolated on the interior of meanders. These results indicate that in this landscape the hydrogeomorphic structures play a role, but that human impact is more significant in its effect on the shape of remnant forest patches. Other structures, such as the regional topography, may account for the unexplained variance. The inded of shape used here may be useful as an independent variable in studies of ecological processes affected by patch shape and form and as a guide to conservation. ?{ ?Reyers, Belinda O’Farrell, Patrick Nel, Jeanne Wilson, Kerrie2012WExpanding the conservation toolbox: conservation planning of multifunctional landscapes 1121-1134Landscape Ecology278Springer NetherlandsBiomedical and Life SciencesAn area of convergence appears to be emerging between the approaches of conservation planning and the concepts of multifunctional landscapes, which if exploited correctly may assist in overcoming the resource and other constraints faced by biodiversity conservation, while at the same time furthering the aims of multifunctional landscapes to improve production abilities and overall sustainability. Using a multi-zone conservation planning approach, we explore the conservation costs, benefits to biodiversity conservation and possible ecosystem service payments associated with various land-use configurations, in the Little Karoo of South Africa, in order to develop and showcase a multifunctional landscape planning approach and its data requirements, as well as the possible cost savings to conservation agencies. The study uses four conservation planning scenarios, five land-use types, their conservation costs and biodiversity benefits, as well as possible payments from carbon sequestration and tourism. We find that the costs and biodiversity benefits associated with different land-uses varies substantially between land-uses, and also spatially within a land-use type. By incorporating this variation into a multi-zone conservation planning approach land-uses can be allocated in a way that achieves biodiversity targets while at the same time reducing costs by up to 50 % when compared with traditional binary approaches to conservation. Despite some challenges presented by cost and ecosystem service value data and the determination of land-use impacts on biodiversity and ecosystem services, the ability of conservation planning approaches to reflect differential contributions of particular land-uses to biodiversity targets and ecosystem services holds much potential for conservation planning, for multifunctional landscape objectives and for growing the resources and partnerships available to the establishment of sustainable and resilient landscapes.+http://dx.doi.org/10.1007/s10980-012-9761-0 0921-297310.1007/s10980-012-9761-0~?N!Rhemtulla, J. M. Mladenoff, D. J.2007(Why history matters in landscape ecology1-3Landscape Ecology22 Suppl. 1 "://WOS:000251543600001 Times Cited: 0WOS:00025154360000110.1007/s10980-007-9163-x~?J0Rhemtulla, J. M. Mladenoff, D. J. Clayton, M. K.2007qRegional land-cover conversion in the US upper Midwest: magnitude of change and limited recovery (1850-1935-1993)57-75Landscape Ecology22kLand-use legacies can persist for hundreds to thousands of years, influencing plant species composition, nutrient cycling, water flows, and climate. To understand how land use has affected regional land-cover composition in Wisconsin (USA), we assessed the magnitude and direction of change in land cover between: (1) c.1850, at the onset of Euro-American settlement; (2) c.1935, the period of maximum clearing for agriculture following widespread forest logging; and (3) 1993, which, especially in northern Wisconsin, follows farm abandonment and forest recovery. We derived land-cover maps using U.S. Public Land Survey records (c.1850), the Wisconsin Land Economic Inventory (c.1935), and Landsat TM satellite data (1993). We stratified Wisconsin (145,000 km(2)) into two ecological provinces and used spatial error models, multinomial logistic regression, and non-metric multi-dimensional scaling ordination to examine change. Between 1850 and 1935, forest cover in the North declined from 84% to 56%, cropland increased to 24%, and mixed/coniferous forests and savannas were replaced by deciduous forests. In the South, formerly dominant savannas (69%) and prairies (6%) were mostly converted to cropland (51%) and pasture (11%). Remnant deciduous savannas and coniferous forests and savannas were replaced by deciduous forests. Remarkably little recovery to pre-settlement land-cover classes occurred from 1935 to 1993. Less cropland was abandoned than expected, and there was little net gain in coniferous/mixed forest. Based on these general land-cover classes, current cover is significantly different from that in 1850, but not from that in 1935, and thus continues to reflect historical logging and agricultural patterns. These results provide a historical framework for measuring associated changes in ecosystem function and can be used to guide restoration where desirable and feasible."://WOS:000251543600005 Times Cited: 0WOS:00025154360000510.1007/s10980-007-9117-3*t<7Z)Ribe, R. Morganti, R. Hulse, D. Shull, R.1998A management driven investigation of landscape patterns of northern spotted owl nesting territories in the high Cascades of Oregon1-13Landscape Ecology131Onorthern spotted owl landscape index habitat model Cascade Mountains HOME RANGEArticleFebQInvestigations using available data sought to guide short-term management decisions regarding the needs of northern spotted owl in the high Cascade Mountains of Oregon. Landscape attributes and pattern indices were measured and tested for identification of areas likely to contain northern spotted owl nests. Predictive models indicating planning standards were developed. Most landscape ecological indices were not useful. Results indicate the owl favors landscapes dominated by patches that meet definitions of late seral forest nesting habitat. The owl optimally nests in such patches at least 570 hectares in size. Landscapes with some edges, particularly around nesting habitat patches evidently do not adversely affect the owl, perhaps because they provide prey. Landscapes with extensive edges, particularly between openings and forests not suitable for nesting, are not as likely to be selected. The results are largely consistent with the owl's recovery plans, provide guidance for management, and require refinement through additional research, particularly to better determine home range sizes.://000077256700001 #ISI Document Delivery No.: 143LG Times Cited: 6 Cited Reference Count: 45 Cited References: Cited Reference Count: 45 Cited References: Carey, A.B., J.A. Reid and S.P. Horton, 1990. Spotted owl home range and habitat use in Southern Oregon Coast Ranges. J. Wildl. Manage. 54(1): 11–17. Coonce, L.F, 1990. Winema National Forest Land and Resource Management Plan. USDA Forest Service, Pacific Northwest Region, Winema National Forest, Klamath Falls, Oregon. Cutler, T.L. and D.W. Hays, 1991, Food habits of northern spot- ted owls in high elevation forests of Pelican Butte, Southwestern Oregon. Northwestern Naturalist 72: 66–69. Diaz, N. and D. Apostal, 1992. Forest landscape analysis and design: a process for developing and implementing land man- agement objectives for landscape patterns. USDA Forest Service, Region 6, Publication ECO-TP-043-92. Forman, R.T.T. and M. Godron, 1986. Landscape Ecology. John Wiley and Sons, New York. Forsman, E.D, 1980. Habitat utilization by spotted owls in the west- central Cascades of Oregon. Dissertation, Oregon State Univer- sity, Corvallis, Oregon. Forsman, E.D. and E.C. Meslow, 1984. Distribution and biology of the spotted owl in Oregon. Wildl. Monogr. 87: 1–64. Franklin, J.F. and C.T. Dyrness, 1973. Natural vegetation of Ore- gon and Washington. Oregon State University Press, Corvallis, Oregon. Franklin, J.F. and R.T.T. Forman, 1987. Creating landscape patterns by forest cutting: ecological consequences and principles. Land- sc. Ecol. 1(1): 5–18. Hansen, A.J., T.A. Spies, F.J. Swanson and J.L. Ohmann, 1991. Conserving biodiversity in managed forests: lessons from natural forests. Biosci. 41(6): 382–392. Hansen, J. and D. Urban, 1992. Avian response to landscape pattern: the role of species’ life histories. Landsc. Ecol. 7(3): 163–180. Hardy, R. 1992. (pers. comm.). USDA Forest Service, Winema National Forest, Klamath Ranger District, Wildlife Biology Office. Harris, L.D. 1984. The fragmented forest: island biogeography the- ory and the preservation of biotic diversity. University of Chicago Press, Chicago, Illinois. Harris L.D. 1988. Edge effects and the conservation of biotic diver- sity. Conserv. Biol. 2: 330–332. Haugen, J. 1993. Fourteen potential indicators of northern spotted owl habitat, statistical analysis: report to the Klamath District ranger on Klamath District ecosystem analysis. Winema Nation- al Forest, Klamath Falls, Oregon. Hopkins, W.E. 1979. Plant associations of south Chiloquin and Klamath Ranger Districts, Winema National Forest. USDA For- est Service, Pacific Northwest Region, Report R6-Ecol-70-005, Portland, Oregon. Hulse, D.W. and R.Z. Melnick, 1990. GIS as an aid to rural land- scape protection. In: Proceedings: Resource Technology ’90, Second International Symposium on Advanced Technology in Natural Resource Management. American Society for Photgram- metry and Remote Sensing, Bethesda, Maryland. Jahns, P. 1992. Owl habitat parameters: report to the Klamath Dis- trict ranger on site specific spotted owl habitat. Winema National Forest, Klamath Falls, Oregon. Krummel, J.R., R.H. Gardner, G. Sugihara, R.V. O’Neill and P.R. Coleman. 1987. Landscape patterns in a disturbed environment. Oikos 48: 321–324. Li, H. 1989. Spatial-temporal pattern analysis of managed forest landscapes: a simulation approach. Dissertation, Oregon State University, Corvallis, Oregon. Li, H. and J. Franklin, 1988. Landscape ecology: a new conceptual framework in ecology. Advance in Ecology (China) 5(1): 23–33. Loehle, C. 1990. Home range: a fractal approach. Landsc. Ecol. 5: 39–52. Lujan, M. Jr., D.R. Knowles, J. Turner, M. Plenert, J. Bart, R.G. Anthony, M. Berg, J.H. Beuter, W. Elmore, J. Fay, R.J. Gutierrez, H.T. Heintz, Jr., R.S. Holthausen, K. Lathrop, K. Mays, R.H. Nafziger, M. Pagel, C. Sproul, E.E. Starkey and J.C. Tappenier, 1992. Draft recovery plan for the northern spotted owl. USDI Fish and Wildlife Service, Washington, DC. Mandelbrot, B.B. 1977. Fractals; form, chance and dimension. Free- man, San Francisco. Maser, C., B.R. Mate, J.F. Franklin and C.T. Dyrness, 1981. Natural history of Oregon coast mammals. USDA Forest Service General Technical Report PNW-133. Portland, Oregon. 496 pp. McGarigal, K. and B. Marks, 1993. FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. Forest Sci- ence Department, Oregon State University, Corvallis, Oregon. McLellan, C.H., A.P. Dobson, D.S. Wilcove and J.F. Lynch, 1986. Effects of forest fragmentation on new- and old-world bird com- munities: empirical observations and theoretical implications. In: Wildlife 2000: Modeling Habitat Relationships of Terrestri- al Vertebrates. pp. 305–313. Edited by J. Verner, M.L. Morrsion and C.J. Ralph. University of Wisconsin Press, Madison, Wis- consin. Morganti, R. in press. Landscape patterns in wildlife habitat: the landscape ecology of the northern spotted owl in the eastern high Cascades of southern Oregon: a preliminary test of pattern indices. J. Remote Sens. Ollieu, M. 1992. Report from the regional director of forest pest managment, functional assistance trip to the Winema National Forest. USDA Forest Service, Pacific Northwest Region, Port- land, Oregon. O’Neill, R.V., J.R. Krummel, R.H. Gardner, G. Sugihara, B. Jack- son, D.L. DeAngelis, B.T. Milne, M.G. Turner, B. Zygmunt, S.W. Christensen, V.H. Dale and R.L. Graham, 1988. Indices of landcape pattern. Landsc. Ecol. 1(3): 153–162. Patton, D.R. 1992 Wildlife habitat relationships in forested ecosys- tems. Timber Press, Portland, Oregon. Perry, D.A. 1988. An overview of sustainable forestry. J. Pest. Ref. 8: 8–12. Perry, D.A. and M.P. Amaranthus, 1997. Disturbance, recovery, and stability. In: Creating a forestry for the 21st century. pp. 31–56. Edited by K.A. Kohm and J.F. Franklin. Island Press, Washing- ton, DC. Perry, D.A. and J. Maghembe, 1989. Ecosystem concepts and cur- rent trends in forest management: time for reappraisal. For. Ecol. and Manage. 26: 123–140. Ripple, W.J., G.A. Bradshaw and T.A. Spies, 1991. Measuring for- est landscape patterns in the Cascade Range of Oregon, USA. Conserv. Biol. 57: 73–88. Rosenberg, K.V. and M.G. Raphael, 1986. Effects of forest fragmen- tation on vertebrates in Douglas-fir forests. In: Wildlife 2000: modeling habitat relationships of terrestrial vertebrates. pp. 263– 272. Edited by J. Verner, M.L. Morrison and C.J. Ralph. Univer- sity of Wisconsin Press, Madison, Wisconsin. Thomas, J.W. (Technical Editor), 1979. Wildlife habitats in man- aged forests: the Blue Mountains of Oregon and Washington. USDA Forest Service, Agricultural Handbook No. 553, Wash- ington, DC. Thomas, J.W., E.D. Forsman, J.B. Lint, E.C. Meslow, B.R. Noon and J. Verner. 1990. A conservation strategy for the northern spotted owl: report of the interagency scientific committee to address the conservation of the northern spotted owl. USDA For- est Service, USDI Bureau of Land Management, USDI Fish and Wildlife Service, USDI National Park Service, Washington, DC. Thomas, J.W., M.G. Raphael, R.G. Anthony, E.D. Forsman, A.G. Gunderson, R.S. Holthausen, B.G. Marcot, G.H. Reeves, J.R. Sedell and D.M. Solis, 1993. Viability assessments and manage- ment considerations for species associated with late-successional and old-growth forests of the pacific northwest: the report of the scientific analysis team (SAT). USDA Forest Service, National Research Office, Washington, DC. Turner, M.R. 1990. Spatial and temporal analysis of landscape pat- terns. Landsc. Ecol. 4(1): 21–30. Turner, M.R., R. Constanza and F.H. Sklar, 1989. Methods to eval- uate the performance of spatial simulation models. Ecol. Model. 48: 1–18. U.S. Department of Agriculture and U.S. Department of Interi- or, 1994. Record of decision: for amendments to forest service and bureau of land management planning documents within the range of the northern spotted owl; and standards and guide- lines: for management of habitat for late-successional and old- growth forest related species within the range of the northern spotted owl. U.S. Government Printing Office, Document 1994- 589-111/00001 Region no. 10. U.S. Fish and Wildlife Service, 1990. 1990 status review: northern spotted owl; Strix occidentalis caurina. Report to the Fish and Wildlife Service. Portland, Oregon. U.S. Department of the Inte- rior. U.S. Fish and Wildlife Service, U.S. Bureau of Land Management and U.S. Department of Agriculture Forest Service. 1994. Sec- tion 7 consultation guidance for the forest ecosystem plan: fis- cal year 1994 and 1995 projects. Memorandum of understanding dated December 22, 1994. Wallin, D.O., F.J. Swanson and B. Marks, 1994. Landscape pat- tern response to changes in the pattern-generation rules: land-use legacies in forestry. Ecol. Applic. 4(3): 569–580. 0921-2973 Landsc. Ecol.ISI:000077256700001Univ Oregon, Inst Sustainable Environm, Eugene, OR 97403 USA. Ribe, R, Univ Oregon, Inst Sustainable Environm, 5234, Eugene, OR 97403 USA.Englishk|?4 Ribeiro, Raquel Carretero, Miguel A. Sillero, Neftali Alarcos, Gonzalo Ortiz-Santaliestra, Manuel Lizana, Miguel Llorente, Gustavo A.2011[The pond network: can structural connectivity reflect on (amphibian) biodiversity patterns?673-682Landscape Ecology265MayLandscape connectivity is a very recurrent theme in landscape ecology as it is considered pivotal for the long term conservation of any organism's populations. Nevertheless, this complex concept is still surrounded by uncertainty and confusion, largely due to the separation between structural and functional connectivity. Amphibians are the most threatened vertebrates around the globe, in Europe mostly due to habitat alteration, and to their particular life cycle. Pond breeding amphibians are considered to be organised in metapopulations, enhancing the importance of landscape connectivity in this group of animals. We sampled the amphibian species present in two pond groups in Central Western Spain. We applied the graph theory framework to these two pond networks in order to determine the importance of each pond for the entire network connectivity. We related the pond importance for connectivity with the species richness present in each pond. We tested if connectivity (partially) determined the presence of the amphibian species sampled using logistic regression. The results show that the structural connectivity of the pond network impacts on the amphibian species richness pattern and that the importance of the pond for the connectivity of the network is an important factor for the presence of some species. Our results, hence, attest the importance of (structural) landscape connectivity determining the pattern of amphibian (functional) colonization in discrete ponds.!://WOS:000291485100006Times Cited: 0 0921-2973WOS:00029148510000610.1007/s10980-011-9592-4,?5Ricardo, D. Lopez Craig, B. Davis M. Siobhan Fennessy2002[Ecological relationships between landscape change and plant guilds in depressional wetlands43-56Landscape Ecology171Depressional wetland - Ecological indicator - Ecological inertia - Fragmentation - Gradient - Island biogeography - Ohio - Plant guildqPlant guilds used to measure the relationships between wetlandplant community characteristics and landscape change around 31 depressionalwetlands in central Ohio, USA. Characteristics of certain plant guilds withineach wetland site are correlated with changes in: (a) area of urban land cover,forest, grassland, agriculture, and open-water in the local vicinity ofthe wetland; (b) inter-wetland distance; and (c) wetland size (area).Taxa richness is negatively correlated with inter-wetland distance forall plant guilds, except submersed herbaceous plants. Taxa richness of thesubmersed herbaceous plant guild (usually less than 20% of the totalnumber of plant species at a wetland) is positively correlated with the area ofopen-water in the local landscape and with the areaofthe wetland site itself. Significant positive correlationsalso exist between the area of open-water in the vicinity of the wetlandand the proportion of submersed herbaceous plant taxa at the site, the numberofnative submersed herbaceous plant species, the submersed herbaceous plantperennial-to-annual ratio, and the number ofavian-dispersed submersed herbaceous plant species at a site. Theresults suggest that (a) the dominance of submersed herbaceousplantspecies at a site is related to dispersal constraints between wetlands, and (b)the relatively slower physiological response of woody plants to local landscapechange may result in their contribution to greater ecologicalinertia in the plant community as a whole. For these reasons,relationships between the plant community and land cover change may not alwaysbe observed unless analyzed at the level of plant-guild.*http://dx.doi.org/10.1023/A:1015203802047 $10.1023/A:1015203802047 Ricardo D. Lopez Email: lopez.ricardo@epa.gov Craig B. Davis Email: davis.80@osu.edu M. Siobhan Fennessy Email: fennessym@kenyon.edu References Adamus P.R. and Brandt K. 1990. Impacts on Quality of Inland Wetlands of the United States: A Survey of Indicators, Techniques, and Applications of Community Level Biomonitoring Data. EPA/600/3-90/073. U.S. Environmental Protection Agency Environmental Research Laboratory, Corvalis, Oregon, USA. A Land Use and Land Cover Classification System for Use with Remote Sensor Data. USGS Professional Paper 964. Anderson J.R., Hardy E.E., Roach J.T. and Witmer R.E. 1976.. Andreas B.K. and Lichvar R.W. 1995. Floristic Index for Assessment Standards: A Case Study for Northern Ohio. Wetlands Research Program Technical Report WRP-DE-8. U.S. Army Corps of Engineers Waterways Experiment Station, Vicksburg, Mississippi, USA. Brinson M. 1993. A Hydrogeomorphic Classification for Wetlands. Report WRP-DE-4. U.S. Army Corps of Engineers Waterways Experiment Station, Vicksburg, Mississippi, USA. Catling P.M., Freedman B., Stewart C., Kerekes J.J. and Lefkovitch L.P. 1986. Aquatic plants of acid lakes in Kejimkujik National Park, Nova Scotia; floristic composition and relation to water chemistry. Canadian Journal of Botany 64: 724-729. Chapin F.S. 1991. Integrated response of plants to stress. Bio-Science 41: 29-36. Cowardin L.M., Carter V., Golet F.C. and LaRoe E.T. 1979. Classification of Wetlands and Deepwater Habitats of the United States. U.S. Fish and Wildlife Service Publication FWS/OBS-79/31. U.S. Fish and Wildlife Service, Washington, D.C., USA. Dahl T.E. 1990. Wetlands Losses in the United States, 1780s to 1980s. U.S. Fish andWildlife Service, Washington, D.C., USA. Diamond J.M. 1974. Colonization of exploded volcanic islands by birds: The supertramp strategy. Science 184: 803-806. Dzwonko Z. and Loster S. 1988. Species richness of small woodlands on the western Carpathian foothills. Vegetatio 76: 15-27. Falkner E. 1994. Aerial Mapping: Methods and Applications. Lewis Publ., Boca Raton, Florida, USA. Fennessy M.S., Geho R., Elifritz B. and Lopez R. 1998a. Testing the Floristic Quality Assessment Index as an Indicator of Riparian Wetland Quality. Final Report to U.S. EPA. Ohio Environmental Protection Agency, Division of Surface Water, Columbus, Ohio, USA. Fennessy M.S., Gray M., Lopez R. and Mack M. 1998b. An Assessment of Wetlands Using Reference Sites. Final Report to U.S. EPA. Ohio Environmental Protection Agency, Division of Surface Water, Columbus, Ohio, USA. Forman R.T.T. 1995. Land Mosaics. Cambridge University Press, New York, New York, USA. Gacia E., Ballesteros E., Camarero L., Delgado O., Palau A., Riera J.L. et al. 1994. Macrophytes from lakes in the eastern Pyrenees: Community composition and ordination in relation to environmental factors. Freshwater Biology 32: 73-81. Galatowitsch S.M. and van der Valk A.G. 1996. The vegetation of restored and natural prairie wetlands. Ecological Applications 6: 102-112. Godwin H. 1923. Dispersal of pond floras. Journal of Ecology 11: 160-164. Green R.H. 1979. Sampling Design and Statistical Methods for Environmental Biologists. J. Wiley and Sons, New York, New York, USA. Harris L.D. 1984. The Fragmented Forest: Island Biogeography Theory and the Preservation of Biotic Diversity. University of Chicago Press, Chicago, Illinois, USA. Jensen J.R. 1996. Introductory Digital Image Processing: A Remote Sensing Perspective. 2nd edn. Prentice Hall, Upper Saddle River, New Jersey, USA. Jones K.B., Neale A.C., Nash M.S., Van Remortel R.D., Wickham J.D., Riitters K.H. et al. 2001. Predicting nutrient and sediment loadings to streams from landscape metrics: A multiple watershed study from the United States Mid-Atlantic Region. Landscape Ecology 16: 301-312. Karr J.R. and Chu E.W. 1997. Biological Monitoring and Assessment: Using Multimetric Indexes Effectively. EPA/235/R97/001. University of Washington, Seattle, Washington, USA. Keddy P.A., Lee H.T. and Wisheu I.C. 1993. Choosing Indicators of Ecosystem Integrity: Wetlands as a Model System. In: Woodley S., Kay J. and Francis G. (eds), Ecological Integrity and the Management of Ecosystems. St. Lucie Press, Delray Beach, Florida, USA. Leibowitz S.G., Abbruzzese B., Adamus P.R., Hughes L.E. and Irish J.T. 1992. sA Synoptic Approach to Cumulative Impact Assessment: A Proposed Methodology. EPA/600/R-92/167. U.S. Environmental Protection Agency, Corvalis, Oregon, USA. Lillesand T.M. and Kiefer R.W. 1994. Remote Sensing and Image Interpretation. J. Wiley and Sons, New York, New York, USA. Lopez R.D. 1999. An Ecological Assessment of the Relationships Between Landscape Structure and Depressional-Wetland Ecosystem Status Along Environmental Gradients in Central Ohio. PhD Dissertation. Lyon J.G. 1981. The Influence of Lake Michigan Water Levels on Wetland Soils and Distribution of Plants in the Straits of Mackinac, Michigan. PhD Dissertation. Lyon J.G. 2001.Wetland Landscape Characterization: GIS, Remote Sensing, and Image Analysis. Ann Arbor Press, Chelsea, Michigan, USA. MacArthur R. and Wilson E.O. 1967. The Theory of Island Biogeography. Princeton University Press, Princeton, New Jersey, USA. Magurran A.E. 1988. Ecological Diversity and its Measurement. Princeton University Press, Princeton, New Jersey, USA. McDonnell M.J. 1984. Interactions between landscape elements: Dispersal of bird disseminated plants in post-agricultural landscapes. In: Brandt J. and Agger P. (eds), Proceedings of the First International Seminar on Methodology in Landscape Ecological Research and Planning. Vol. 2. Roskilde Universitersforlag GoeRuc, Roskilde, Denmark. McDonnell M.J. and Stiles E.W. 1983. The structural complexity of old field vegetation and the recruitment of bird-dispersed plant species. Oecologia 56: 109-116. Moller T.R. and Rordam C.P. 1985. Species numbers of vascular plants in relation to area, isolation, and age of ponds in Denmark. Oikos 45: 8-16. Mueller-Dombois D. and Ellenberg H. 1974. Aims and Methods of Vegetation Ecology. Wiley and Sons, London, UK. Nip-van der Voort J., Hengeveld R. and Haeck J. 1979. Immigration rates of plant succession in three Dutch polders. Journal of Biogeography 6: 301-308. Odum E.P. 1985. Trends expected in stressed ecosystems. Bio-Science 35: 419-422. Ohio Department of Natural Resources 1999. List of Invasive, Threatened Invasive, and Potentially Invasive Plant List for Ohio. Ohio Department of Natural Resources, Columbus, Ohio, USA. Opdam P., Apeldoorn R.V., Schotman A. and Kalkhoven J. 1993. Population responses to landscape fragmentation. In: Vos C.C. and Opdam P. (eds), Landscape Ecology of a Stressed Environment. Chapman and Hall, London, UK. Peterson S.A., Carpenter L., Guntenspergen G. and Cowardin L.M. (eds) 1996. Pilot Test of Wetland Condition Indicators in the Prairie Pothole Region of the United States. EPA/620/R-97/002. U.S. Environmental Protection Agency, Corvalis, Oregon, USA. Reed P.B. 1988. National List of Plant Species that Occur in Wetlands. U.S. Fish and Wildlife Service Biological Report 88(26.3). U.S. Fish and Wildlife Service, Washington D.C., USA. Ridley H.N. 1930. The Dispersal of Plants Throughout the World. L. Reeve and Co. LTD, Ashford, Kent, UK. Simberloff D. and Wilson E.O. 1970. Experimental zoogeography of islands. A two-year record of colonization. Ecology 51: 934-937. Simpson J.W., Boerner R.E.J., DeMers M.N., Berns L.A., Artigas F.J. and Silva A. 1994. Forty-eight years of landscape change on two contiguous Ohio landscapes. Landscape Ecology 9: 261-270. Strittholt J.R. and Boerner R.E.J. 1995. Applying biodiversity gap analysis in a regional nature reserve design for the edge of Appalachia, Ohio (U.S.A.). Conservation Biology 9: 1492-1505. U.S. ACOE (U.S. Army Corps of Engineers) 1987. Corps of Engineers-Wetlands Delineation Manual. Technical Report Y-87-1. Department of the Army, Washington D.C., USA. U.S. EPA (U.S. Environmental Protection Agency) 1990. Biological Criteria: National Program Guidance for Surface Waters. EPA-440/5-90-004. U.S. Environmental Protection Agency, Washington DC, USA. U.S. EPA (U.S. Environmental Protection Agency) 1994. National Water Quality Inventory. EPA-841-R-94-001. U.S. Environmental Protection Agency, Washington D.C., USA. van der Valk A.G. 1981. Succession in wetlands: A Gleasonian approach. Ecology 62: 688-696. Voss E.G. 1972. Part I, Gymnosperms and Monocots. Voss E.G. 1985. Part II, Dicots, Saururaceae-Cornaceae. Voss E.G. 1996. Part III, Dicots, Pyrolaceae-Compositae. Wilhelm G. and Ladd D. 1988. Natural Area Assessment in the Chicago Region. In: Transactions of the Fifty-third North American Wildlife and Natural Resources Conference (Louisville, Kentucky). Wildlife Management Institute, Washington, D.C., USA, pp. 361-375. Yoder C. 1991. Answering some concerns about biological criteria based on experiences in Ohio. In: Proceedings of Water Quality Standards for the 21st Century. U.S. Environmental Protection Agency, Washington, D.C., USA, pp. 95-104. Zar J.H. 1984. Biostatistical Analysis. Prentice Hall, Englewood Cliffs, New Jersey, USA. PSchool of Natural Resources Columbus, The Ohio State University, Ohio 43210, USA M|7KRicci, B. Franck, P. Toubon, J. F. Bouvier, J. C. Sauphanor, B. Lavigne, C.2009WThe influence of landscape on insect pest dynamics: a case study in southeastern France337-349Landscape Ecology243codling moth correlation cydia pomonella gis habitat hedgerow orchard pest management tortricidae windbreak different spatial scales winter oilseed rape cydia-pomonella codling moth agricultural landscapes habitat area management diversity field biodiversityMarManaging the spatial distribution of crop and non-crop habitats over landscapes could be used as a means to reduce insect pest densities. In this study, we investigated whether or not landscape characteristics affected the number of codling moths in commercial orchards. To do this, we collected overwintering larvae in 2006 and 2007 in 76 orchards over a 70 kmA(2) area in southeastern France. We analysed variations in the number of larvae using correlation tests and linear models. As independent variables, we took both characteristics of focus orchards (pear vs. apple, organic vs. conventional orchards) and of their surrounding landscape (orchard density and hedgerow network attributes) into account in buffers with widths varying from 50 to 500 m. Although the codling moth is specialised on orchards, the number of codling moths was lower in orchards within a high orchard density area. There was some indication that this effect was mostly due to the density of conventional orchards and thus to the intensity of insecticide treatments. Conversely, we found no particular effect of abandoned or organic orchards. In 2006, the number of codling moths was also significantly lower in a focus orchard when the hedgerow network acted as a protection against the prevailing wind. Finally, major effects of landscape variables on the number of codling moths were observed for distances of less than 150 m from the focus orchards, suggesting that codling moth management should be organised over areas of about 16 ha.://000263419500004-408EY Times Cited:0 Cited References Count:40 0921-2973ISI:000263419500004Ricci, B French Natl Inst Agr Res, INRA, UR Plantes & Syst Culture Horticoles 1115, F-84000 Avignon, France French Natl Inst Agr Res, INRA, UR Plantes & Syst Culture Horticoles 1115, F-84000 Avignon, FranceDoi 10.1007/S10980-008-9308-6English|? Richard, Yvan Armstrong, Doug P.2010The importance of integrating landscape ecology in habitat models: isolation-driven occurrence of north island robins in a fragmented landscape 1363-1374Landscape Ecology259Nov`Although the role of habitat fragmentation in species declines is well recognised, the effect of habitat quality on species distributions is often studied using presence-absence models that ignore metapopulation dynamics. We compared three approaches to model the presence-absence of North Island robins in 400 sites among 74 fragments of native forest in a 15,000-ha agricultural landscape in New Zealand. The first approach only considered local habitat characteristics, the second approach only considered metapopulation factors (patch size and isolation), and the third approach combined these two types of factors. The distribution of North Island robins was best predicted by patch isolation, as their probability of occurrence was negatively correlated with isolation from neighbouring patches and from the closest major forests, which probably acted as a source of immigrants. The inclusion of habitat factors gave only a slight increase in predictive power and indicated that robins were more likely to occur in areas with tall canopy, tall understory and low density of young trees. We modelled the effect of isolation using an index of functional patch connectivity based on dispersal behaviour of radio-tracked juveniles, and this functional index greatly improved the models in comparison to classical indices relying on Euclidean distances. This study highlights the need to incorporate functional indices of isolation in presence-absence models in fragmented landscapes, as species occurrence can otherwise be a misleading predictor of habitat quality and lead to wrong interpretations and management recommendations.!://WOS:000281981000005Times Cited: 0 0921-2973WOS:00028198100000510.1007/s10980-010-9488-8<7*Rickers, J. R. Queen, L. P. Arthaud, G. J.1995/A proximity-based approach to assessing habitat309-321Landscape Ecology1058ASPEN; HABITAT; HABITAT SUITABILITY INDEX; RUFFED GROUSEArticleOct1Planning for either a single species, multiple species, or ecosystems is greatly dependent on spatial interactions in the landscape. Problems exist for evaluating wildlife habitat changes over large ranges of space and time. This paper illustrates the use of Geographic Information Systems (GIS) to evaluate habitat for a single species, ruffed grouse (Bonasa umbellus), following a time series of forest harvests. A habitat suitability model for ruffed grouse is utilized on a two-township study area in north-central Minnesota to assess the habitat suitability changes over time using an even-aged area-control harvesting plan. The results are presented as a habitat quality change map and a contingency table, representing the movement of habitat class areas between time periods resulting from the proposed harvesting. We developed a neighborhood definition to allow for spatially varying habitat values. This work illustrates the ability to 'look ahead' and 'around' in estimating the impact on wildlife habitat resulting from alternative future management activities.://A1995TD59500005 HISI Document Delivery No.: TD595 Times Cited: 9 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1995TD595000056UNIV MINNESOTA,DEPT FOREST RESOURCES,ST PAUL,MN 55108.English q<7| %Rico, Y. Boehmer, H. J. Wagner, H. H.2012vDeterminants of actual functional connectivity for calcareous grassland communities linked by rotational sheep grazing199-209Landscape Ecology272colonization rates species occupancy regeneration niches dispersal vector incidence function model germany distance seed dispersal habitat fragmentation genetic consequences plant traits landscape colonization conservation populations extinction managementFebIn fragmented landscapes, plant species persistence depends on functional connectivity in terms of pollen flow to maintain genetic diversity within populations, and seed dispersal to re-colonize habitat patches following local extinction. Connectivity in plants is commonly modeled as a function of the physical distance between patches, without testing alternative dispersal vectors. In addition, pre- and post-dispersal processes such as seed production and establishment are likely to affect patch colonization rates. Here, we test alternative models of potential functional connectivity with different assumptions on source patch effects (patch area and species occupancy) and dispersal (relating to distance among patches, matrix composition, and sheep grazing routes) against empirical patch colonization rates at the community level (actual functional connectivity), accounting for post-dispersal effects in terms of structural elements providing regeneration niches for establishment. Our analyses are based on two surveys in 1989 and in 2009 of 48 habitat specialist plants in 62 previously abandoned calcareous grassland patches in the Southern Franconian Alb in Bavaria, Germany. The best connectivity model S-i, as identified by multi-model inference, combined distance along sheep grazing routes including consistently and intermittently grazed patches with mean species occupancy in 1989 as a proxy for pre-dispersal effects. Community-level patch colonization rates depended to equal degrees on connectivity and post-dispersal process. Our study highlights that actual functional connectivity of calcareous grassland communities cannot be approximated by structural connectivity based on physical distance alone, and modeling of functional connectivity needs to consider pre- and post-dispersal processes.://0003000887000059Sp. Iss. SI 889QQ Times Cited:0 Cited References Count:52 0921-2973Landscape EcolISI:000300088700005Rico, Y Univ Toronto, Dept Ecol & Evolutionary Biol, 3359 Mississauga Rd, Mississauga, ON L5L, Canada Univ Toronto, Dept Ecol & Evolutionary Biol, 3359 Mississauga Rd, Mississauga, ON L5L, Canada Univ Toronto, Dept Ecol & Evolutionary Biol, Mississauga, ON L5L, Canada Tech Univ Munich, Dept Ecol & Ecosyst Management, LOEK, D-85350 Freising Weihenstephan, Germany Univ Bonn, Interdisciplinary Latin Amer Ctr ILZ, D-53113 Bonn, GermanyDOI 10.1007/s10980-011-9648-5English*|?@XRiedinger, Verena Renner, Marion Rundlof, Maj Steffan-Dewenter, Ingolf Holzschuh, Andrea2014OEarly mass-flowering crops mitigate pollinator dilution in late-flowering crops425-435Landscape Ecology293MarPrevious studies focused mainly on the provision of ecosystem services by species movements between semi-natural and managed habitats, whereas data on spillover effects between two managed habitats or between habitats that provide target resources in non-overlapping time periods are lacking. We studied densities of three pollinator groups on sunflower fields as a late mass-flowering crop in 16 landscapes that differed in the relative cover of oil-seed rape as an early mass-flowering crop, in the relative cover of sunflowers and in the relative cover of semi-natural habitats. Our aim was to evaluate dynamics between two crops with non-overlapping flowering periods. Densities of bumble bees in late-flowering sunflower fields were enhanced by early-flowering oil-seed rape. Highest bumble bee densities in the late-flowering crop were reached in landscapes that combined high relative covers of oil-seed rape and semi-natural habitats. Further, low relative covers of oil-seed rape in spring led to decreased bumble bee densities in late-flowering sunflower fields in landscapes with high relative covers of sunflower fields (dilution effect), whereas in landscapes with high relative covers of oil-seed rape, no dilution of bumble bees was found. Thus, our results indicate that early mass-flowering crops can mitigate pollinator dilution in crops flowering later in the season. We conclude that the management of landscape-scale patterns of early and late mass-flowering crops together with semi-natural habitats could be used to ensure crop pollination services. Similar processes could also apply for other species groups and may be an important, but so far disregarded, determinant of population densities in agroecosystems.!://WOS:000331935500006Times Cited: 1 0921-2973WOS:00033193550000610.1007/s10980-013-9973-y_۽7-Riemann, Rachel2013zMartin Dodge, Rob Kitchin, and Chris Perkins: The Map Reader: theories of mapping practice and cartographic representation 1635-1636Landscape Ecology288Springer Netherlands 2013/10/01+http://dx.doi.org/10.1007/s10980-013-9899-4 0921-2973Landscape Ecol10.1007/s10980-013-9899-4English=<7~ Riffell, S. K. Gutzwiller, K. J.1996TPlant-species richness in corridor intersections: Is intersection shape influential?157-168Landscape Ecology113 agricultural landscapes; conservation biology; corridors; fencerows; intersection shape; networks; nodes; plant dispersal; plant-species richness; restoration ecology OLD FIELD VEGETATION; SMALL MAMMALS; WOODY-PLANTS; DISPERSAL; HABITAT; BIRDS; SEED; SHELTERBELTS; RECRUITMENT; SUCCESSIONArticleJun Corridor intersections constitute nodes that can be more mesic than the intersecting corridors themselves. Such microclimatic conditions may lead to an ''intersection effect,'' in which plant richness is higher in the intersection than in the corridors. We hypothesized that an additional factor contributing to intersection effects is the movement of plants along corridors into intersections by way of bird- and mammal-dispersed seeds. If this hypothesis is correct, one would expect intersection-shape effects, defined herein as differences in intersection richness associated with the number of possible avenues for plant influx into the intersection. Specifically, richness in intersections should be lowest for L-shape intersections (two avenues), higher for T-shape intersections (three avenues), and highest for X-shape intersections (four avenues). We used data from fencerow networks to test this hypothesis about corridor intersections. During October 1992 and March 1993, we determined woody- and herbaceous-plant richness for 25 intersections and their associated fencerows in central Texas, USA. We compared two measures of intersection richness among the three intersection shapes: richness of plants dispersed primarily by birds and mammals (vertebrate-dispersed plant richness), and richness of plants dispersed primarily by wind, ants or other means (non-vertebrate dispersed plant richness). Vertebrate-dispersed plant richness differed significantly among intersection shapes, but no differences in nonvertebrate dispersed plant richness were evident, which is what one would expect if the number of avenues for vertebrate vectors into an intersection was an important factor influencing intersection richness. The intersection-shape effects we found were not attributable to fencerow features (amount of woody cover, width, presence of breaks) or intersection characteristics (amount of woody cover, size, distance to nearest connected intersection or patch). Our results from fencerow networks support the hypothesis that intersection effects on plant richness are influenced by intersection shape via the number of intersecting corridors. Understanding patterns and processes that occur in networks is important for conservation biologists because intersections in networks have the potential to function as refugia for plant species that require conditions more mesic than those of the surrounding matrix. Networks also may be valuable as in situ sources of seed for managers attempting to restore plant communities in the matrix.://A1996UX47800003 ISI Document Delivery No.: UX478 Times Cited: 12 Cited Reference Count: 47 Cited References: *SAS I INC, 1989, SAS STAT US GUID VER, V2 BENNETT AF, 1994, BIOL CONSERV, V68, P155 BENNINGERTRUAX M, 1992, LANDSCAPE ECOL, V6, P269 BEST LB, 1983, WILDLIFE SOC B, V11, P243 CHAMBERS JC, 1994, ANNU REV ECOL SYST, V25, P263 CONSTANT P, 1976, BOCAGES HIST ECOLOGI, P327 DIXON WJ, 1992, BMDP STATISTICAL SOF, V1 FORMAN RTT, 1984, ENVIRON MANAGE, V8, P495 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FRITZ R, 1993, BIOL CONSERV, V64, P141 FRITZ R, 1994, ECOSCIENCE, V1, P160 GUTWILLER KJ, 1987, CONDOR, V89, P534 HATCH SL, 1990, CHECKLIST VASCULAR P HELLIWELL DR, 1975, BIOL CONSERV, V7, P61 HENDERSON MT, 1985, BIOL CONSERV, V31, P95 HOLM S, 1979, SCAND J STAT, V6, P65 JOHNSON WC, 1985, AM MIDL NAT, V113, P319 LACK PC, 1988, BIRD STUDY, V35, P133 LOWER JC, 1975, GEOGRAPHY MOVEMENT MAHLER WF, 1988, SHINNERS MANUAL N CE MCCLANAHAN TR, 1986, VEGETATIO, V65, P175 MCCLANAHAN TR, 1993, CONSERV BIOL, V7, P279 MCDONNELL MJ, 1983, OECOLOGIA, V56, P109 MCDONNELL MJ, 1986, B TORREY BOT CLUB, V113, P6 MERRIAM G, 1990, LANDSCAPE ECOL, V4, P123 MERRIAM G, 1993, NATURE CONSERVATION, V3, P71 MILLER RG, 1981, SIMULTANEOUS STATIST MUELLERDOMBOIS D, 1974, AIMS METHODS VEGETAT NETER J, 1974, APPL LINEAR STAT MOD NOSS RF, 1986, ENVIRON MANAGE, V10, P299 NOSS RF, 1987, CONSERV BIOL, V1, P159 OTT L, 1993, INTRO STATISTICAL ME RICE WR, 1989, EVOLUTION, V43, P223 ROBINSON GR, 1992, ENVIRON MANAGE, V16, P265 ROBINSON GR, 1993, CONSERV BIOL, V7, P271 ROSENBERG NJ, 1983, MICROCLIMATE BIOL EN SCHROEDER RL, 1992, WILDLIFE SOC B, V20, P264 SHALAWAY SD, 1985, WILDLIFE SOC B, V13, P302 SIMBERLOFF D, 1987, CONSERV BIOL, V1, P63 SIMBERLOFF D, 1992, CONSERV BIOL, V6, P493 VERTS BJ, 1967, BIOL STRIPED SKUNK WEGNER JF, 1979, J APPL ECOL, V16, P349 WILLMOT A, 1980, J ECOL, V68, P269 WILLSON MF, 1986, CURRENT ORNITHOLOGY, V3, P223 WILLSON MF, 1993, OIKOS, V67, P159 YAHNER RH, 1983, J WILDLIFE MANAGE, V47, P74 ZAR JH, 1984, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:A1996UX478000030BAYLOR UNIV,DEPT ENVIRONM STUDIES,WACO,TX 76798.English<7v(Riffell, S. K. Keas, B. E. Burton, T. M.2003XBirds in North American Great Lakes coastal wet meadows: is landscape context important?95-111Landscape Ecology182!birds Great Lakes coastal wetlands landscape context Michigan principal component analysis regression analysis wet meadows wetland conservation and management SPECIES RICHNESS ARTIFICIAL NESTS RELATIVE INFLUENCE BREEDING BIRDS HABITAT USE COMMUNITIES PREDATION DIVERSITY AREA FRAGMENTATIONArticleLandscape context can influence species richness, abundance, or probability of patch-use by birds. Little is known, however, about the effects of landscape context on birds in wetland-dominated landscapes. This lack of knowledge is alarming because many wetlands are threatened by development and other human impacts, while serving critical functions as migratory, breeding and foraging habitat. To address this lack of knowledge, we censused birds in North American Great Lakes coastal wet meadows located along the northern Lake Huron shoreline in Michigan (USA) during 1997 and 1998. Using a suite of multivariate techniques, we first accounted for effects of area and within-patch habitat characteristics before testing for effects of landscape context. Most bird variables were significantly related to landscape context, and two major patterns were apparent. First, avian species richness, abundance, and probability of patch-use by some species were higher for wet meadows located in complex contexts ( adjacent to many patch types) compared to simpler contexts ( adjacent to only one patch type). Second, these variables were higher for wet meadows located in wetland contexts compared to contexts that were terrestrial and road-impacted, dominated by open water habitats, or dominated by forested wetland habitats. Conservation plans for wetlands have focused on saving large wetlands and creating the vegetative habitat structure required by birds, but they should go further and explicitly consider the landscape context of wetlands as well. Specifically, wetlands located in complex and/or wetland contexts should have a higher conservation value than similar wetlands located in simpler, more terrestrial contexts.://000183770300001 wISI Document Delivery No.: 694JB Times Cited: 6 Cited Reference Count: 81 Cited References: *SAS I INC, 1989, SAS STAT US GUID VER *SAS I INC, 1997, SAS STAT SOFTW CHANG ANDREN H, 1995, MOSAIC LANDSCAPES EC, P225 BAYNE EM, 1997, CONSERV BIOL, V11, P1418 BEDFORD KW, 1992, J GREAT LAKES RES, V18, P571 BERGIN TM, 1997, WILSON BULL, V109, P437 BLAIR RB, 1996, ECOL APPL, V6, P506 BLOUTIN C, 1998, ECOLOGICAL APPL, V8, P544 BOCK CE, 1999, STUDIES AVIAN BIOL, V19, P131 BOLGER DT, 1997, CONSERV BIOL, V11, P406 BOWERS MA, 1996, ECOL APPL, V6, P1135 BREWER R, 1991, ATLAS BREEDING BIRDS BROWN M, 1986, J WILDLIFE MANAGE, V50, P392 BROWN M, 1991, J IOWA ACAD SCI, V98, P124 CALME S, 2000, J BIOGEOGR, V27, P725 CAM E, 2000, ECOL APPL, V10, P1196 CANTERO JJ, 1999, OIKOS, V87, P346 CRAIG RJ, 1992, WILSON BULL, V104, P295 DRAPER NR, 1981, APPL REGRESSION ANAL EHRENFELD JG, 1990, WETLAND ECOLOGY MANA, P63 ESTADES CF, 1999, ECOL APPL, V9, P573 FAIRBAIRN SE, 2001, WETLANDS, V21, P41 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FORYS E, 1999, LANDSCAPE ECOL, V14, P177 FREEMARK KE, 1995, ECOLOGY MANAGEMENT N, P381 FRIESEN LE, 1995, CONSERV BIOL, V9, P1408 GATHMAN JP, 1999, INVERTEBRATES FRESHW, P949 GIBBS JP, 1993, J WILDLIFE MANAGE, V57, P27 GROVER AM, 1995, WETLANDS, V15, P108 GUTZWILLER KJ, 1987, CONDOR, V89, P534 GUTZWILLER KJ, 2001, ECOL APPL, V11, P1517 HELZER CJ, 1999, ECOL APPL, V9, P1448 HERKERT JR, 1994, ECOL APPL, V4, P461 HOLM S, 1979, SCAND J STAT, V6, P65 HOSMER DW, 1989, APPL LOGISTIC REGRES JOBIN B, 1997, J WILDLIFE MANAGE, V61, P792 KALDEC JA, 1992, ECOLOGY MANAGEMENT B, P590 KEOUGH JR, 1999, WETLANDS, V19, P821 LEWIS DB, 2000, FRESHWATER BIOL, V43, P409 LIU JG, 1999, ECOL APPL, V9, P186 MILLER RG, 1981, SIMULTANEOUS STAT IN MINC LD, 1998, GREAT LAKES COASTAL MITSCH WJ, 1993, WETLANDS MITSCH WJ, 2000, ECOL ECON, V35, P25 MORRISON ML, 1998, WILDLIFE HABITAT REL MYERS RH, 1989, CLASSICAL MODERN REG NAUGLE DE, 1999, LANDSCAPE ECOL, V14, P267 ORIANS GH, 1980, MONOGRAPHS POPULATIO, V14 PATON PWC, 1994, CONSERV BIOL, V8, P17 PEARSON SM, 1993, LANDSCAPE ECOL, V8, P3 PICMAN J, 1993, AUK, V110, P89 PRINCE HH, 1992, J GREAT LAKES RES, V18, P673 PRINCE HH, 1995, LAKE HURON ECOSYSTEM, P247 RAHBEK C, 1997, AM NAT, V149, P875 RALPH CJ, 1995, PSWGTR149 USDA FOR S RENCHER AC, 1992, AM STAT, V46, P217 RICE WR, 1989, EVOLUTION, V43, P223 RIFFELL SK, 2000, THESIS MICHIGAN STAT RIFFELL SK, 2001, WETLANDS, V21, P492 RISCH SJ, 1983, ENVIRON ENTOMOL, V12, P625 ROBBINS CS, 1981, STUD AVIAN BIOL, V6, P301 ROTENBERRY JT, 1980, ECOLOGY, V61, P1228 SAAB V, 1999, ECOL APPL, V9, P135 SISK TD, 1997, ECOL APPL, V7, P1170 SKAGEN SK, 1994, WILSON BULL, V106, P91 SZARO RC, 1985, CONDOR, V87, P511 TAYLOR PD, 1993, OIKOS, V68, P571 TERRES JK, 1980, AUDUBON SOC ENCY N A THOMPSON FR, 1995, MONITORING BIRD POPU, P45 TILTON DL, 1978, WETLAND FUNCTIONS VA, P267 TREXLER JC, 1993, ECOLOGY, V74, P1629 VERNER J, 1966, ECOLOGY, V47, P143 VICKERY PD, 1994, CONSERV BIOL, V8, P1087 VICKERY PD, 1999, STUDIES AVIAN BIOL, V19, P2 VILLARD MA, 1999, CONSERV BIOL, V13, P774 WEBB NR, 1984, J APPL ECOL, V21, P921 WELLER MW, 1999, WETLAND BIRDS WESTFALL PH, 1999, MULTIPLE COMP MULTIP WESTMORELAND D, 1985, AUK, V102, P774 WILCOX DA, 1995, LAKE HURON ECOSYSTEM, P223 ZEDLER JB, 2000, TRENDS ECOL EVOL, V15, P402 0921-2973 Landsc. Ecol.ISI:000183770300001CMichigan State Univ, Dept Zool, E Lansing, MI 48824 USA. Michigan State Univ, Ctr Integrat Studies gen Sci, E Lansing, MI 48824 USA. Ohio No Univ, Dept Biol Sci, Ada, OH 45810 USA. Michigan State Univ, Dept Fisheries & Wildlife, E Lansing, MI 48824 USA. Riffell, SK, Michigan State Univ, Dept Zool, E Lansing, MI 48824 USA.English? Riitters, Kurt2011Creativity abhors prescription 1359-1359Landscape Ecology2610Springer NetherlandsEarth and Environmental Science+http://dx.doi.org/10.1007/s10980-011-9673-4 0921-297310.1007/s10980-011-9673-4?fRiitters, K. H. R. V. O'Neill C. T. Hunsaker J. D. Wickham D. H. Yankee K. B. J. Timmins B. L. Jackson1995<A factor analysis of landscape pattern and structure metrics23-39Landscape Ecology101|7f uRiitters, K. H. Oneill, R. V. Hunsaker, C. T. Wickham, J. D. Yankee, D. H. Timmins, S. P. Jones, K. B. Jackson, B. L.1995<A Factor-Analysis of Landscape Pattern and Structure Metrics23-39Landscape Ecology101FebPFifty-five metrics of landscape pattern and structure were calculated for 85 maps of land use and land cover. A multivariate factor analysis was used to identify the common axes (or dimensions) of pattern and structure which were measured by a reduced set of 26 metrics. The first six factors explained about 87% of the variation in the 26 landscape metrics. These factors were interpreted as composite measures of average patch compaction, overall image texture, average patch shape, patch perimeter-area scaling, number of attribute classes, and large-patch density-area scaling. We suggest that these factors can be represented in a simpler way by six univariate metrics - average perimeter-area ratio, contagion, standardized patch shape, patch perimeter-area area scaling, number of attribute classes, and large-patch density-area scaling.://A1995QL68700003.Ql687 Times Cited:251 Cited References Count:0 0921-2973ISI:A1995QL687000034Riitters, Kh Tennessee Valley Author,Norris,Tn 37828English|75 9Riitters, K. H. ONeill, R. V. Wickham, J. D. Jones, K. B.19962A note on contagion indices for landscape analysis197-202Landscape Ecology114Vspatial pattern image texture information index computation statistics spatial patternAug#The landscape contagion index measures the degree of clumping of attributes on raster maps. The index is computed from the frequencies by which different pairs of attributes occur as adjacent pixels on a map. Because there are subtle differences in the way the attribute adjacencies may be tabulated, the standard index formula may not always apply, and published index values may not be comparable. This paper derives formulas for the contagion index that apply for different ways of tabulating attribute adjacencies - with and without preserving the order of pixels in pairs, and by using two different ways of determining pixel adjacency. When the order of pixels in pairs is preserved, the standard formula is obtained. When the order is not preserved, a new formula is obtained because the number of possible attribute adjacency states is smaller. Estimated contagion is also smaller when each pixel pair is counted twice (instead of once) because double-counting pixel adjacencies makes the attribute adjacency matrix symmetric across the main diagonal.://A1996VC12700002.Vc127 Times Cited:19 Cited References Count:15 0921-2973ISI:A1996VC12700002VRiitters, KH Tennessee Valley Author,Hist Forestry Bldg,17 Ridgeway Rd,Norris,Tn 37828English}?;Riitters, K. H. Vogt, P. Soille, P. Kozak, J. Estreguil, C.2007INeutral model analysis of landscape patterns from mathematical morphology 1033-1043Landscape Ecology227Aug://000248381900006 0921-2973ISI:000248381900006~<7|aRiksen, M. Ketner-Oostra, R. van Turnhout, C. Nijssen, M. Goossens, D. Jungerius, P. D. Spaan, W.2006Will we lose the last active inland drift sands of Western Europe? The origin and development of the inland drift-sand ecotype in the Netherlands431-447Landscape Ecology213udrift-sand ecotype; nature conservation; the Netherlands; wind erosion CAMPYLOPUS-INTROFLEXUS; DUNE AREA; MOSS; SOILSArticleApr In the Netherlands the total active inland drift-sand area has been declining rapidly during the last 50 years. To preserve the inland drift sands, it is necessary to understand its origin and development and the role of human activity in this semi-natural ecotype. The objective of this literature review is to describe the development of the drift-sand ecotopes, to explain the rapid decline of the active drift sands, and to develop a management strategy for the remaining active drift sands. Inland drift-sand landscapes are relatively young landscapes of Holocene age. They often occur as oval-shaped cells with a length of 1.5 to over 6 km in the direction of the prevailing wind. These cells presumably represent reactivated deposits of Younger Cover Sands. Large-scale erosion events in combination with human activity suppressed the development of vegetation. After the change in land use in the first half of the 20th century in which most of the drift sands were re-afforested, the vegetation succession started to show a progressive development. In this stage inland drift-sand ecotopes developed in most of the remaining drift sands with all forms of the typical succession stages from bare sand to forest. The rate at which this development took place mainly depended on the geomorphological development stage of the area, the area size and human activity. Since the 1960s the increased nitrogen deposition has accelerated the vegetation succession, not only resulting in a further decline of the drift sands, but also in a loss of the fragile balance between the different ecotopes and loss of its typical habitants like the Tree Grayling and Tawny Pipit. Most drift-sand vegetation and fauna need the presence of bare sand nearby and a certain level of erosion activity to survive. To preserve the drift-sand ecotype, it is therefore recommended to keep the area affected by erosion sufficiently large (process management). In the meantime one should also 'maintain' or increase the wind force in the drift-sand area by suppressing the growth of high vegetation and removing trees, which form a wind barrier. In areas which are less suitable for reactivation, one could restore the mosaic vegetation by removing the vegetation on a limited scale (pattern management). More research is needed to develop a more balanced management strategy and to develop a management tool for the managers of inland drift sands. Also the role of the increased nitrogen deposition in the regeneration process needs further investigation in order to find an effective way to suppress its effect. The development of management strategies for the Dutch inland drift sands might be of great value to drift-sand areas in Western Europe where nature conservationists start to show more interest in the restoration of former drift-sand areas.://000236968500010 ISI Document Delivery No.: 034ZD Times Cited: 0 Cited Reference Count: 49 Cited References: *SOVON, 2002, ATLAS NEDERLANDSE BR, V5 ALMQUIST S, 1971, OIKOS, V22, P225 APTROOT A, 1998, 029 IKC NAT BAKKER T, 2003, PREADVIES STUIFZANDE BAL D, 2001, HDB NATUURDOELTYPEN BIERMANN R, 1997, PHYTOCOENOLOGIA, V27, P257 BIJLSMA RG, 1978, LIMOSA, V51, P107 BIJLSMA RG, 1990, LIMOSA, V63, P80 BIJLSMA RG, 2001, ALGEMENE SCHAARSE VO BINK FA, 1992, ECOLOGISCHE ATLAS DA BRUIJNS MFM, 1951, NETHERLANDS ENV INSE BUIJSMAN E, 2004, ANN SURVEY AIR QUALI CASTEL I, 1989, Z GEOMORPHOL, V33, P1 CASTEL IIY, 1991, THESIS U UTRECHT DANIELS FJA, 1996, STRATIOTES, V13, P37 DURING HJ, 1979, LINDBERGIA, V5, P2 DURING HJ, 1990, CLONAL GROWTH PLANTS, P153 EQUIHUA M, 1993, J ECOL, V81, P359 HEIDINGA HA, 1984, GEOL MIJNBOUW, V63, P241 HOBBS VJ, 1987, J ECOL, V75, P177 KETNEROOSTRA R, 1994, 941 STAATSB KETNEROOSTRA R, 1994, BUXBAUMIELLA, V35, P4 KETNEROOSTRA R, 1998, LEVENDE NATUUR, V99, P272 KETNEROOSTRA R, 2003, RESULTATEN EFFECT GE KETNEROOSTRA R, 2005, ACTIEF BEHEER BEHO 1 KLEUKERS RMJ, 1997, SPRINKHANEN KREKELS KOOMEN A, 2004, LANDSCHAP, V3, P159 KOSTER EA, 1978, PUBLICATIES FYSISCH KOSTER EA, 2005, PHYS GEOGRAPHY W EUR, P139 LONDO G, 2002, LINDBERGIA, V27, P63 MASSELINK AK, 1994, STRATIOTES, V8, P32 NIJSSEN M, 2001, GEVOLGEN VERZURING V PANNEKOEK AJ, 1956, GEOLOGISCHE GESCHIED PAPE JC, 1970, GEODERMA, V4, P229 PLUIS JLA, 1994, VEGETATIO, V113, P41 RIKSEN MJPM, 2001, LAND DEGRAD DEV, V12, P1 SCHADLER M, 1999, ENTOMOL GEN, V24, P125 SCHIMMEL H, 1975, NATUUR LANDSCHAP, V29, P1 SHREEVE TG, 1990, ECOL ENTOMOL, V15, P201 STARING WCH, 1962, HUISBOEK LANDMAN NED TESCH P, 1926, ZANDVERSTUIVINGEN BI VANBATH BS, 1977, AGRARISCHE GESCHIEDE VANDENANCKER JAM, 2003, ONTWIKKELINGSMOGELIJ VANDENBERGH S, 2004, THESIS WAGENINGEN U VANDERMEULEN F, 1987, P K NED AKAD C BIOL, V90, P73 VANEMBDEN AE, 1968, KOOTWIJKERZAND VEGET VANTURNHOUT C, 2005, LIMOSA, V78, P1 VOGELS J, 2004, EFFECTEN VERMOSSING WEEDA EJ, 1985, NEDERLANDSE OECOLOGI, V1 0921-2973 Landsc. Ecol.ISI:000236968500010yWageningen Univ, Dept Environm Sci, Eros & Soil & Water Conservat Grp, NL-6709 PA Wageningen, Netherlands. Univ Wageningen & Res Ctr, Dept Environm Sci, Nat Conservat & Plant Ecol Grp, NL-6708 PD Wageningen, Netherlands. SOVON, Dutch Ctr Field Ornithol, NL-6573 DG Beekbergen, Netherlands. Radboud Univ Nijmegen, Dept Environm Studies, NL-6500 GL Nijmegen, Netherlands. Radboud Univ Nijmegen, Dept Anim Ecol, NL-6500 GL Nijmegen, Netherlands. Radboud Univ Nijmegen, Stichting Bargerveen Dept Anim Ecol, NL-6500 GL Nijmegen, Netherlands. Catholic Univ Louvain, Phys & Reg Geog Res Grp, B-3000 Louvain, Belgium. Univ Paris 12, Lab Interuniv Syst Atmospher, F-94010 Creteil, France. Geomorphol & Landscape, NL-6717 LM Ede, Netherlands. Riksen, M, Wageningen Univ, Dept Environm Sci, Eros & Soil & Water Conservat Grp, Nieuwe Kanaal 11, NL-6709 PA Wageningen, Netherlands. Michel.Riksen@WUR.nlEnglish/۽7 Risser, PaulG Iverson, LouisR2013>30 years later—landscape ecology: directions and approaches367-369Landscape Ecology283Springer Netherlands 2013/03/01+http://dx.doi.org/10.1007/s10980-013-9856-2 0921-2973Landscape Ecol10.1007/s10980-013-9856-2English6|7Y Risser, P. G.19953The Allerton Park Workshop Revisited - a Commentary129-132Landscape Ecology103Jun://A1995RF27500001,Rf275 Times Cited:1 Cited References Count:0 0921-2973ISI:A1995RF275000013Risser, Pg Miami Univ,Off President,Oxford,Oh 45056EnglishJ|?XRiutta, Terhi Slade, Eleanor M. Morecroft, Michael D. Bebber, Daniel P. Malhi, Yadvinder2014YLiving on the edge: quantifying the structure of a fragmented forest landscape in England949-961Landscape Ecology296JulForest ecosystems have been widely fragmented by human land use, inducing significant microclimatic and biological changes at the forest edge. If we are to rigorously assess the ecological impacts of habitat fragmentation, there is a need to effectively quantify the amount of edge habitat within a landscape, and to allow this to be modelled for individual species and processes. Edge effect may extend only a few metres or as far as several kilometres, depending on the species or process in question. Therefore, rather than attempting to quantify the amount of edge habitat by using a fixed, case-specific distance to distinguish between edge and core, the area of habitat within continuously-varying distances from the forest edge is of greater utility. We quantified the degree of fragmentation of forests in England, where forests cover 10 % of the land area. We calculated the distance from within the forest patches to the nearest edge (forest vs. non-forest) and other landscape indices, such as mean patch size, edge density and distance to the nearest neighbour. Of the total forest area, 37 % was within 30 m and 74 % within 100 m of the nearest edge. This highlights that, in fragmented landscapes, the habitats close to the edge form a considerable proportion of the total habitat area. We then show how these edge estimates can be combined with ecological response functions, to allow us to generate biologically meaningful estimates of the impacts of fragmentation at a landscape scale.!://WOS:000338331600003Times Cited: 4 0921-2973WOS:00033833160000310.1007/s10980-014-0025-z |? WRiva-Murray, Karen Riemann, Rachel Murdoch, Peter Fischer, Jeffrey M. Brightbill, Robin2010Landscape characteristics affecting streams in urbanizing regions of the Delaware River Basin (New Jersey, New York, and Pennsylvania, U.S.) 1489-1503Landscape Ecology2510Dec~Widespread and increasing urbanization has resulted in the need to assess, monitor, and understand its effects on stream water quality. Identifying relations between stream ecological condition and urban intensity indicators such as impervious surface provides important, but insufficient information to effectively address planning and management needs in such areas. In this study we investigate those specific landscape metrics which are functionally linked to indicators of stream ecological condition, and in particular, identify those characteristics that exacerbate or mitigate changes in ecological condition over and above impervious surface. The approach used addresses challenges associated with redundancy of landscape metrics, and links landscape pattern and composition to an indicator of stream ecological condition across a broad area of the eastern United States. Macroinvertebrate samples were collected during 2000-2001 from forty-two sites in the Delaware River Basin, and landscape data of high spatial and thematic resolution were obtained from photointerpretation of 1999 imagery. An ordination-derived 'biotic score' was positively correlated with assemblage tolerance, and with urban-related chemical characteristics such as chloride concentration and an index of potential pesticide toxicity. Impervious surface explained 56% of the variation in biotic score, but the variation explained increased to as high as 83% with the incorporation of a second land use, cover, or configuration metric at catchment or riparian scales. These include land use class-specific cover metrics such as percent of urban land with tree cover, forest fragmentation metrics such as aggregation index, riparian metrics such as percent tree cover, and metrics related to urban aggregation. Study results indicate that these metrics will be important to monitor in urbanizing areas in addition to impervious surface.!://WOS:000283371000003Times Cited: 0 0921-2973WOS:00028337100000310.1007/s10980-010-9513-y !|7+Rizkalla, C. E. Moore, J. E. Swihart, R. K.2009WModeling patch occupancy: Relative performance of ecologically scaled landscape indices77-88Landscape Ecology241connectivity forest rodent metapopulation niche breadth patch area habitat fragmentation peromyscus-leucopus metapopulation dynamics bird communities forest rodents small mammals corridor use quality connectivity conservationJanDIn fragmented landscapes, the likelihood that a species occupies a particular habitat patch is thought to be a function of both patch area and patch isolation. Ecologically scaled landscape indices (ESLIs) combine a species' ecological profile, i.e., area requirements and dispersal ability, with indices of patch area and connectivity. Since their introduction, ESLIs for area have been modified to incorporate patch quality. ESLIs for connectivity have been modified to incorporate niche breadth, which may influence a species' ease in crossing the non-habitat matrix between patches. We evaluated the ability of 4 ESLIs, the original and modified indices of area and connectivity, to explain patterns in patch occupancy of 5 forest rodents. Occupancy of eastern gray squirrels (Sciurus carolinensis), North American red squirrels (Tamiasciurus hudsconicus), fox squirrels (Sciurus niger), white-footed mice (Peromyscus leucopus), and eastern chipmunks (Tamias striatus) was modeled at 471 sites in 35 landscapes sampled from the upper Wabash River basin in Indiana. Models containing ESLIs received support for gray squirrels, red squirrels, and chipmunks. Modified ESLIs were important in models for red squirrels. However, none of the models demonstrated high predictive ability. Incorporating habitat quality and using surrogate measures of dispersal can have important effects on model results. Additionally, different responses of species to area, isolation, and habitat quality suggest that generalizing patterns of metapopulation dynamics was not justified, even across closely related species.://000262506000007-395EI Times Cited:0 Cited References Count:40 0921-2973ISI:000262506000007Rizkalla, CE Disneys Anim Kingdom, POB 10000, Lake Buena Vista, FL 32830 USA Purdue Univ, Dept Forestry & Nat Resources, W Lafayette, IN 47907 USADoi 10.1007/S10980-008-9281-0English<72Rizkalla, C. E. Swihart, R. K.2006qCommunity structure and differential responses of aquatic turtles to agriculturally induced habitat fragmentation 1361-1375Landscape Ecology218*abundance; fragmentation; northern map turtle; nestedness; occupancy; midland painted turtle; red-eared slider; common snapping turtle; eastern spiny softshell CHELYDRA-SERPENTINA; RANGE BOUNDARIES; ROAD MORTALITY; SITE OCCUPANCY; NICHE BREADTH; HOME-RANGE; LANDSCAPE; MOVEMENTS; MODELS; POPULATIONArticleNovSeveral studies have shown that wetland loss and habitat fragmentation can alter diversity and abundance of herpetofauna, but taxonomic attention has been skewed towards amphibians. We assessed responses of aquatic turtles to features at multiple spatial scales in an intensively farmed region of the Midwestern United States. Spatially hierarchical sampling was conducted from 2001 to 2003 in 35 randomly selected 23-km(2) cells throughout the upper Wabash River basin in Indiana. Hoop nets were used at wetlands to capture common snapping turtles (Chelydra serpentina serpentina) (n=258), midland painted turtles (Chrysemys picta marginata) (151), eastern spiny softshells (Apalone spinifera spinifera) (70), red-eared sliders (Trachemys scripta elegans) (59), northern map turtles (Graptemys geographica) (27), false map turtles (Graptemys pseudogeographica pseudogeographica) (6), Blanding's turtles (Emydoidea blandingii) (3), and stinkpot turtles (Sternotherus odoratus) (3). We examined the degree to which these aquatic species were nonrandomly distributed in 14 landscapes. Assemblages of turtles generally were random and the extent of nestedness was influenced by the diversity of landcover, the proportion of grassland, and the total length of roads in each landscape. The occurrence and abundance of several species also were modeled to test hypotheses regarding the importance of site, patch, and landscape-level variables. Red-eared sliders appeared to be most sensitive to habitat fragmentation, whereas painted turtles, snapping turtles, map turtles, and spiny softshells were less affected. Factors at multiple spatial scales affect turtle distributions, suggesting differential responses to landscape fragmentation.://000242089300014  ISI Document Delivery No.: 106GP Times Cited: 0 Cited Reference Count: 60 Cited References: AKAIKE H, 1973, 2 INT S INF THEOR, P267 ANDERSON RV, 2002, J FRESHWATER ECOL, V17, P171 ATMAR W, 1993, OECOLOGIA, V96, P373 ATMAR W, 1995, NESTEDNESS TEMPERATU BODIE JR, 2000, ECOGRAPHY, V23, P444 BODIE JR, 2000, OECOLOGIA, V122, P138 BURNHAM KP, 2002, MODEL SELECTION MULT CAGLE FR, 1939, COPEIA, P170 CONANT R, 1998, FIELD GUIDE REPTILES CONNER CA, 2005, AM MIDL NAT, V153, P428 COWARDIN LM, 1979, FWSOBS7931 US DEP IN, P103 CUNNINGHAM RB, 2005, ECOLOGY, V86, P1135 DAHL TE, 1990, WETLANDS LOSSES US 1, P13 DONNERWRIGHT DM, 1999, CAN J ZOOL, V77, P989 DRESLIK MJ, 2005, J FRESHWATER ECOL, V20, P149 FIELDING AH, 1997, ENVIRON CONSERV, V24, P38 FINDLAY CS, 1997, CONSERV BIOL, V11, P1000 FISCHER J, 2002, OIKOS, V99, P193 FLEISHMAN E, 2002, CONSERV BIOL, V16, P706 GALAT DL, 1998, BIOSCIENCE, V48, P721 GALOIS P, 2002, J HERPETOL, V36, P402 GIBBONS JW, 1970, AM MIDL NAT, V83, P404 GIBBS JP, 2005, CONSERV BIOL, V19, P552 GU WD, 2004, BIOL CONSERV, V116, P195 HARTMAN MR, 1994, THESIS PURDUE U W LA, P100 HAXTON T, 2000, CAN FIELD NAT, V114, P106 HOULAHAN JE, 2004, LANDSCAPE ECOL, V19, P677 JOHNSON CM, 2002, PREDICTING SPECIES O, P157 KNAPP RA, 2003, ECOL APPL, V13, P1069 KOLOZSVARY MB, 1999, CAN J ZOOL, V77, P1288 LAMBERT D, 1992, TECHNOMETRICS, V34, P1 LINDEMAN PV, 2001, CHELONIAN CONSERV BI, V4, P206 LONG JS, 1997, REGRESSION MODELS CA LOVICH JE, 1995, OUR LIVING RESOURCES, P902 MACKENZIE DI, 2003, ECOLOGY, V84, P2200 MARCHAND MN, 2004, CONSERV BIOL, V18, P758 MCGARIGAL K, 2002, FRAGSTATS SPATIAL PA MINTON SA, 2001, AMPHIBIANS REPTILES MITCHELL JC, 2000, TURTLE CONSERVATION, P5 MOLL D, 2004, ECOLOGY EXPLOITATION MOLL EO, 2000, TURTLE CONSERVATION, P126 PETTIT KE, 1995, CAN FIELD NAT, V109, P192 PLUTO TG, 1988, J HERPETOL, V22, P152 RAUDENBUSH SW, 2002, HIERARCHICAL LINEAR ROWE JW, 1991, J HERPETOL, V25, P178 ROWE JW, 2003, J HERPETOL, V37, P342 RUSSELL KR, 2002, FOREST ECOL MANAG, V163, P43 SCHUMAKER NH, 2004, ECOL APPL, V14, P381 SEMLITSCH RD, 1998, CONSERV BIOL, V12, P1113 SEXTON OJ, 1959, ECOL MONOGR, V29, P113 STEEN DA, 2004, CONSERV BIOL, V18, P1143 STONE PA, 1993, J HERPETOL, V27, P13 SWIHART RK, 2003, DIVERS DISTRIB, V9, P1 SWIHART RK, 2004, CONSERVING BIODIVERS, P3 SWIHART RK, 2006, DIVERS DISTRIB, V12, P277 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 WELSH AH, 1996, ECOL MODEL, V88, P297 WEYRAUCH SL, 2004, BIOL CONSERV, V115, P443 WHITE D, 1997, CONSERV BIOL, V11, P349 WRIGHT DH, 1998, OECOLOGIA, V113, P1 0921-2973 Landsc. Ecol.ISI:000242089300014Purdue Univ, Dept Forestry & Nat Resources, W Lafayette, IN 47907 USA. Rizkalla, CE, Purdue Univ, Dept Forestry & Nat Resources, 195 Marsteller St, W Lafayette, IN 47907 USA. crizkall@purdue.eduEnglishڽ7I@Robertson, Oliver Maron, Martine Buckley, Yvonne McAlpine, Clive2013ZIncidence of competitors and landscape structure as predictors of woodland-dependent birds 1975-1987Landscape Ecology2810Springer NetherlandstHabitat fragmentation Hierarchical partitioning Interspecific competition Model averaging Noisy miner Woodland birds 2013/12/01+http://dx.doi.org/10.1007/s10980-013-9934-5 0921-2973Landscape Ecol10.1007/s10980-013-9934-5English<7,Robichaud, I. Villard, M. A. Machtans, C. S.2002eEffects of forest regeneration on songbird movements in a managed forest landscape of Alberta, Canada247-262Landscape Ecology173AAlberta Canada boreal mixedwood forest connectivity corridors dispersal forest songbirds forestry generalised additive models movements riparian buffer strip GENERALIZED ADDITIVE-MODELS BARRO-COLORADO ISLAND BREEDING DISPERSAL POSTFLEDGING DISPERSAL TEMPERATE FOREST BUFFER STRIPS BOREAL FOREST BIRDS HABITAT CONNECTIVITYArticleRecent studies have shown that barrier effects exist even in relatively vagile species such as forest songbirds. The objectives of this study were to determine whether a 560 x 100 m riparian buffer strip of mature forest was used as a movement corridor by forest songbirds and, if so, to what extent corridor effects persisted as woody vegetation regenerated in the adjacent clearcut. Over a 4-yr period, juvenile movement rates decreased in the riparian buffer strip and increased in the regenerating clearcut. Adult movement rates increased in the riparian buffer strip in the first year after logging, then gradually decreased, while still increasing in the regenerating clearcut. However, both juvenile and adult movement rates were higher in the buffer strip than in an undisturbed control site. Results suggest that most adults we captured held territories in the vicinity of the net lanes, and that most of the juveniles captured were dispersing away from their natal territory. Four years after harvest, juvenile movement rates were higher in the regenerating clearcut than in the riparian buffer strip, but several species had not yet been captured or detected in the regeneration. Our results suggest that the use of the riparian buffer strip as a movement corridor decreased with forest regeneration for both adults and juveniles. However, the buffer strip still acted as a movement corridor for the following species: Philadelphia and Red-eyed Vireos, Red-breasted Nuthatch, and Ovenbird.://000178082200004  ISI Document Delivery No.: 594ZK Times Cited: 7 Cited Reference Count: 68 Cited References: *AM ORN UN, 1998, CHECK LIST N AM BIRD ANDERS AD, 1998, AUK, V115, P349 ASKINS RA, 1987, BIOL CONSERV, V39, P129 ASKINS RA, 1987, WILSON BULL, V99, P7 BARLING RD, 1994, ENVIRON MANAGE, V18, P543 BAUDRY J, 1988, CONNECTIVITY LANDSCA, P23 BAYNE EM, 2001, CONDOR, V103, P343 BEIER P, 1998, CONSERV BIOL, V12, P1241 BELISLE M, 2001, ECOLOGY, V82, P1893 BIBBY CJ, 1992, BIRD CENSUS TECHNIQU BURKE DM, 1998, AUK, V115, P96 CLARKE AL, 1997, OIKOS, V79, P429 DESROCHERS A, 1997, CONSERV BIOL, V11, P1204 DICKSON KM, 1982, FACTORS INFLUENCING DUNNING JB, 1995, CONSERV BIOL, V9, P542 FAHRIG L, 1985, ECOLOGY, V66, P1762 FALLS JB, 1994, BIRDS N AM FEWSTER RM, 2000, ECOLOGY, V81, P1970 FREEMARK KE, 1986, BIOL CONSERV, V36, P115 GOBEIL JF, UNPUB OIKOS GREENWOOD PJ, 1980, ANIM BEHAV, V28, P1140 GREENWOOD PJ, 1982, ANNU REV ECOL SYST, V13, P1 HAAS CA, 1995, CONSERV BIOL, V9, P845 HANSSON L, 1991, BIOL J LINN SOC, V42, P89 HASTIE T, 1986, STAT SCI, V1, P297 HASTIE T, 1990, MONOGRAPH STAT APPL, V43 HORNBECK JW, 1986, NORTH J APPL FOR, V3, P97 JOHNSON EA, 1998, J VEG SCI, V9, P603 JOHNSON ML, 1990, ANNU REV ECOL SYST, V21, P449 JOHNSON WC, 1985, AM MIDL NAT, V113, P319 KARR JR, 1982, AM NAT, V119, P220 KOFORD RR, 1994, WILSON BULL, V106, P121 LENS L, 1994, IBIS, V136, P147 MACHTANS CS, 1996, CONSERV BIOL, V10, P1366 MATTHYSEN E, 1995, OIKOS, V72, P375 MERRIAM G, 1984, P 1 INT SEM METH LAN, P5 MERRIAM G, 1988, TRENDS ECOL EVOL, V3, P16 MERRIAM G, 1991, NATURE CONSERVATION, V2, P133 MERRIAM G, 1993, NATURE CONSERVATION, V3, P71 MORTON ML, 1991, ORNIS SCAND, V22, P98 MORTON ML, 1997, ARDEA, V85, P145 NOLAN V, 1978, ORNITHOL MONOGR, V26, P1 PARADIS E, 1998, J ANIM ECOL, V67, P518 PATON PWC, 1994, CONSERV BIOL, V8, P17 PETERMAN RM, 1990, CAN J FISH AQUAT SCI, V47, P2 PITOCCHELLI J, 1993, BIRDS N AM PREISLER HK, 1997, FOREST SCI, V43, P71 PYLE P, 1997, IDENTIFICATION GUI 1 RAIL JF, 1997, CONDOR, V99, P976 ROBBINS CS, 1989, WILDLIFE MONOGRA JUL, P1 ROWE JS, 1972, CFS PUBLICATION, V3000 SCHMIEGELOW FKA, 1993, T N AM WILDL NAT RES, V58, P584 SCHMIEGELOW FKA, 1997, ECOLOGY, V78, P1914 SIEVING KE, 1996, AUK, V113, P944 SMITH SM, 1995, ECOLOGY, V76, P1997 STCLAIR CC, 1998, WINTER RESPONSES FOR STOUFFER PC, 1995, ECOLOGY, V76, P2429 SUTCLIFFE OL, 1996, CONSERV BIOL, V10, P1359 TAYLOR PD, 1993, OIKOS, V68, P571 TERBORGH J, 1969, ECOLOGY, V50, P765 THIEBOUT HM, 1997, CONSERV BIOL, V11, P620 TONTERI T, 1994, ANN ZOOL FENN, V31, P53 VEGARIVERA JH, 1998, CONDOR, V100, P69 VILLARD MA, 1995, ECOLOGY, V76, P27 WEGNER JF, 1979, J APPL ECOL, V16, P349 WIENS JA, 1993, OIKOS, V66, P369 WILLIS EO, 1974, ECOL MONOGR, V44, P153 YEE TW, 1991, J VEG SCI, V2, P587 0921-2973 Landsc. Ecol.ISI:000178082200004xUniv Moncton, Dept Biol, Moncton, NB E1A 3E9, Canada. Villard, MA, Univ Moncton, Dept Biol, Moncton, NB E1A 3E9, Canada.English7ڽ7 -Robillard, Audrey Garant, Dany Bélisle, Marc2013The Swallow and the Sparrow: how agricultural intensification affects abundance, nest site selection and competitive interactions201-215Landscape Ecology282Springer NetherlandsAbundance Agricultural intensification House sparrow Interspecific nest-site competition Landscape structure Nest-box occupancy Passer domesticus Tachycineta bicolor Tree swallow 2013/02/01+http://dx.doi.org/10.1007/s10980-012-9828-y 0921-2973Landscape Ecol10.1007/s10980-012-9828-yEnglishڽ7E@Robinson, StacieJ Samuel, MichaelD Rolley, RobertE Shelton, Paul2013vUsing landscape epidemiological models to understand the distribution of chronic wasting disease in the Midwestern USA 1923-1935Landscape Ecology2810Springer NetherlandssEpidemiological modeling Chronic wasting disease Illinois Risk mapping Wildlife disease Wisconsin White-tailed deer 2013/12/01+http://dx.doi.org/10.1007/s10980-013-9919-4 0921-2973Landscape Ecol10.1007/s10980-013-9919-4English|?A 8Robles, C. D. Garza, C. Desharnais, R. A. Donahue, M. J.2010ELandscape patterns in boundary intensity: a case study of mussel beds745-759Landscape Ecology255This work examines the proposition that positive interactions among neighboring individuals within a population may produce landscape patterns in boundary intensity. The large scale patterns emerge because the interactions favor an aggregated distribution in the face of a potential limiting factor, and the strength of that factor varies over the landscape. The consequences of spatially varying neighborhood processes were explored using cellular automata simulating the structure of mussel beds in 2-dimensional intertidal landscapes, each characterized by a vertical gradient of tidal immersion and a horizontal gradient of wave energy. Running the model with and without the neighborhood processes demonstrated that the facilitating neighborhood processes elevate intensity above that caused by the gradients, and consequently abrupt (high intensity) boundaries emerged in the midst of gradual environmental variation. Trends generated on the 2-D landscape by the model were compared with those in photo-mosaics of intertidal mussel beds, Mytilus californianus on rocky shores of the British Columbia. The analysis involved interpolation of boundary locations using a spatially-constrained cluster algorithm, and then estimation of the corresponding boundary intensities using a landscape index aggregation (CLUMPY). The general similarity between predicted and real trends in intensity over the wave energy gradients suggests that spatially varying neighborhood processes determine much of the landscape scale variation in boundary intensity, while certain discrepancies (e.g. a more rapid rise of observed intensities with increasing wave exposure) suggest modifications of the theory and new empirical work.!://WOS:000276609800007Times Cited: 0 0921-2973WOS:00027660980000710.1007/s10980-010-9450-9 ]}?KRodriguez, W. August, P. V. Wang, Y. Q. Paul, J. F. Gold, A. Rubinstein, N.2007hEmpirical relationships between land use/cover and estuarine condition in the Northeastern United States403-417Landscape Ecology223landscape analysis; estuarine condition; water quality; GIS COASTAL WATER-QUALITY; MID-ATLANTIC; WAQUOIT BAY; SEDIMENT CONTAMINATION; NITROGEN; EUTROPHICATION; MASSACHUSETTS; CONSEQUENCES; MARINE; ENRICHMENT MarK Land-water interactions were examined in three regions in the Virginian Biogeographic Province; the southern shore of Cape Cod, Massachusetts; the Hudson/Raritan region of New York; and the eastern shore of the Delmarva (Delaware/Maryland/Virginia) Peninsula. Cumulative distribution functions were used to evaluate similarity in environmental condition among estuaries. Spatial-setting variables (location in a river, coastal lagoon, or in open waters) were associated with variation for some measures of estuarine condition. Patterns of coastal urban and agriculture gradients were measured and their relationship with indicators of estuarine condition was modeled statistically. When estuaries were pooled, the highest variation explained by spatial-setting variables was found for dissolved oxygen (DO, R-2 = 0.44) and salinity (R-2 = 0.58), with DO decreasing in river locations and salinity decreasing with rainfall and sampling locations near rivers. The explanatory power for the other indicator variables was low and varied from 6% to 27%. Rainfall explained some of the variation (R-2 = 0.23) in total suspended solids. Moderate (0.4 < vertical bar r vertical bar < 0.7) to strong (vertical bar r vertical bar 0.7) linear associations were found between total urban area and measures of estuarine condition. Within regions, total urban area was positively associated with Silver (r = 0.59), Cadmium (r = 0.65), and Mercury (r = 0.47) in Cape Cod, and inversely related to DO (r = -0.65) in the Hudson/Raritan region. No associations were found in the Delmarva Peninsula study area. Total area of agriculture showed a moderate association with Arsenic in Cape Cod, but no other associations were found in the other two regions. Our analyses show a measurable impact of urban land use on coastal ecosystem condition over large areas of the northeastern United States. This pattern was most evident when many different landscapes were considered simultaneously. The relationship between urban development and estuarine condition were weaker within the individual regions studied. The use of land use/cover models for predicting estuarine condition is a challenging task that warrants enhancements in the type, quantity, and quality of data to improve our ability to discern relationships between anthropogenic activities on land and the condition of coastal environments. ://000244455200006 0921-2973ISI:0002444552000061|?ZCRoesner, Sascha Mussard-Forster, Emily Lorenc, Tomas Mueller, Joerg2014^Recreation shapes a "landscape of fear" for a threatened forest bird species in Central Europe55-66Landscape Ecology291JanPredators can create a "landscape of fear" that influences the spatial distribution of their prey. Understanding whether human activity similarly affects the distribution of species beyond habitat suitability is crucial but difficult to assess for conservation managers. Here, we assessed the effect of recreation and forestry activity on a threatened forest-dwelling umbrella species, the Capercaillie (Tetrao urogallus). We followed the citizen science approach on the landscape scale in the Bohemian Forest. We analyzed species data non-invasively collected through intensive fieldwork by volunteers and assessed human activity in the entire study area by analyzing expert questionnaires. The study area extends over 119,000 ha and harbors one of the largest relict populations of this grouse species in Central European low mountain ranges. Our statistical models revealed a negative impact of recreational activities on the intensity of habitat use of the birds within suitable habitats, thereby pointing toward a landscape of fear. The influence of forestry activity, in contrast, was not clear. In comparison to existing regional tourism impact studies, we were able to elevate the examination to the landscape scale. Our results underlined the relevance of recreation in limiting the species' habitat on an entire landscape and allow us to conclude that habitat managers should set aside well-defined zones without recreational activities to preserve the refuge of this umbrella species.!://WOS:000330827600005Times Cited: 2 0921-2973WOS:00033082760000510.1007/s10980-013-9964-z J?} $Roger, Erin Bino, Gilad Ramp, Daniel2012ILinking habitat suitability and road mortalities across geographic ranges 1167-1181Landscape Ecology278Springer NetherlandsBiomedical and Life Sciences Protected areas are established to conserve biodiversity and facilitate resilience to threatening processes. Yet protected areas are not isolated environmental compounds. Many threats breach their borders, including transportation infrastructure. Despite an abundance of roads in many protected areas, the impact of roads on biota within these protected areas is usually unaccounted for in threat mitigation efforts. As landscapes become further developed and the importance of protected areas increases, knowledge of how roads impact on the persistence of species at large scales and whether protected areas provide relief from this process is vital. We took a two-staged approach to analysing landscape-scale habitat use and road-kill impacts of the common wombat ( Vombatus ursinus ), a large, widely distributed herbivore, within New South Wales (NSW), Australia. Firstly, we modelled their state-wide distribution from atlas records and evaluated the relationship between habitat suitability and wombat road fatalities at that scale. Secondly, we used local-scale fatality data to derive an annual estimate of wombats killed within an optimal habitat area. We then combined these two approaches to derive a measure of total wombats killed on roads within the protected area network. Our results showed that common wombats have a broad distribution (290,981 km 2 ), one quarter (24.9 %) of their distribution lies within protected areas, and the percentage of optimal habitat contained within protected areas is 35.6 %, far greater than the COP10 guidelines of 17 %. Problematically, optimal habitat within protected areas was not a barrier to the effects of road-kill, as we estimated that the total annual count of wombat road-kill in optimal habitat within protected areas could be as high as 13.6 % of the total NSW population. These findings suggest that although protected areas are important spatial refuges for biodiversity, greater effort should be made to evaluate how reserves confer resilience from the impacts of roads across geographic ranges.+http://dx.doi.org/10.1007/s10980-012-9769-5 0921-297310.1007/s10980-012-9769-5x|?+(Rolhauser, Andres G. Batista, William B.2014hFrom pattern to process: estimating expansion rates of a forest tree species in a protected palm savanna919-931Landscape Ecology295May-We assessed the possible influences of dominant tree density (Butia yatay palm trees) and fire on the expansion of a riparian tree population (Myrcianthes cisplatensis) over El Palmar National Park, a protected savanna in Argentina. Our approach is based on Skellam's model of population expansion, which predicts that populations with density-independent reproduction and random dispersal will exhibit Gaussian-shaped expansion fronts. Using Poisson regression, we fitted Gaussian curves to Myrcianthes density data collected at varying distances from a riparian forest, within four environmental conditions resulting from combinations of palm density (dense and sparse) and fire history (burned and unburned). Based on the estimated parameters, we derived statistics appropriate to compare attained expansion velocity, mean squared effective dispersal distance, and density-independent population growth among environmental conditions. We also analyzed the effects of palm density, fire history, and distance from the riparian forest on local maximum size of Myrcianthes individuals. Gaussian curves fitted the data reasonably well and slightly better than two alternative front models. Palm density and fire history interacted to control Myrcianthes spread, making unburned dense palm savannas the preferential avenue for Myrcianthes population expansion across the landscape. Limitation of Myrcianthes expansion by fire appeared to result from low survival of small individuals to fire, whereas facilitation of Myrcianthes expansion by palm trees may have resulted from increased population growth. Our results stress the interactive role of fire regime and local biotic influences in determining propagule pressure and tree establishment at the forefront, and the overall vulnerability of savannas to colonization by forest species.!://WOS:000334689900013Times Cited: 0 0921-2973WOS:00033468990001310.1007/s10980-014-0029-8<7%Rollins, M. G. Morgan, P. Swetnam, T.2002oLandscape-scale controls over 20(th) century fire occurrence in two large Rocky Mountain (USA) wilderness areas539-557Landscape Ecology176fire atlases fire ecology fire history fire regimes pattern-process interactions Rocky Mountains YELLOWSTONE-NATIONAL-PARK UNITED-STATES AMERICAN SOUTHWEST NORTHERN ROCKIES FOREST PATTERNS HISTORY REGIMES PRECIPITATION CALIFORNIAArticleOctTopography, vegetation, and climate act together to determine the spatial patterns of fires at landscape scales. Knowledge of landscape- fire- climate relations at these broad scales (1,000s ha to 100,000s ha) is limited and is largely based on inferences and extrapolations from fire histories reconstructed from finer scales. In this study, we used long time series of fire perimeter data (fire atlases) and data for topography, vegetation, and climate to evaluate relationships between large 20 (th) century fires and landscape characteristics in two contrasting areas: the 486,673- ha Gila/ Aldo Leopold Wilderness Complex (GALWC) in New Mexico, USA, and the 785,090- ha Selway- Bitterroot Wilderness Complex (SBWC) in Idaho and Montana, USA. There were important similarities and differences in gradients of topography, vegetation, and climate for areas with different fire frequencies, both within and between study areas. These unique and general relationships, when compared between study areas, highlight important characteristics of fire regimes in the Northern and Southern Rocky Mountains of the Western United States. Results suggest that amount and horizontal continuity of herbaceous fuels limit the frequency and spread of surface fires in the GALWC, while the moisture status of large fuels and crown fuels limits the frequency of moderate- to- high severity fires in the SBWC. These empirically described spatial and temporal relationships between fire, landscape attributes, and climate increase understanding of interactions among broad- scale ecosystem processes. Results also provide a historical baseline for fire management planning over broad spatial and temporal scales in each wilderness complex.://000179774900005 }ISI Document Delivery No.: 624RN Times Cited: 15 Cited Reference Count: 86 Cited References: *ESRI, 1998, ARC INF 7 2 2 SOFTW *USDA FOR SERV, 1993, NAT INT FIR MAN INT *USGS, 1965, US GEOL SURV B, V87 ABOLT RA, 1996, THESIS U ARIZONA TUC AGEE JK, 1993, FIRE ECOLOGY PACIFIC ALBINI F, 1976, GTRINT30 USDA FOR SE ARNO SF, 1976, RPINT187 USDA FOR SE ARNO SF, 1980, J FOREST, V78, P460 ARNO SF, 1993, GTRINT294 USDA FOR S BAISAN CH, 1990, CAN J FOREST RES, V20, P1559 BARRETT SW, 1982, J FOREST, V80, P647 BARRETT SW, 1991, P 11 C FIR FOR MET A, P299 BARRETT SW, 1997, INTGTR370 USDA FOR S BARROWS JS, 1978, 16568CA USDA FOR SER BARTON AM, 1994, B TORREY BOT CLUB, V121, P121 BESCHTA RL, 1976, AGR EXPT STATION TEC, V228 BOYD R, 1999, INDIANS FIRE LAND BROWN JAH, 1972, J HYDROL, V15, P77 BROWN JK, 1994, INT J WILDLAND FIRE, V4, P157 CHOU YH, 1990, PHOTOGRAMM ENG REM S, V56, P1507 CHRISTENSEN NL, 1996, ECOL APPL, V6, P665 COOK ER, 1999, J CLIMATE, V12, P1145 COOPER CF, 1961, ECOLOGY, V42, P493 COOPER SV, 1991, GTRINT236 USDA FOR S COVINGTON WW, 1994, J SUSTAINABLE FOREST, V2, P13 COVINGTON WW, 1994, J SUSTAINABLE FOREST, V2, P153 DAUBENMIRE R, 1968, ADV ECOL RES, V5, P209 DAUBENMIRE R, 1968, PLANT COMMUNITIES TX DETTINGER MD, 1998, J CLIMATE, V11, P3095 ENGELMARK O, 1987, ANN BOT FENN, V24, P317 FINKLIN AI, 1983, WEATHER CLIMATE SELW FINNEY MA, 1998, RMRSRP4 USDA FOR SER FRANK EC, 1966, RM18 USDA FOR SERV R FROST WW, 1982, SELWAY BITTERROOT WI FUQUAY DM, 1979, RPINT217 USDA FOR SE GARCIA L, 1978, GILA NATL FOREST ANN GARCIA LC, 1997, PRESCRIBED NATURAL F GREENWOOD WR, 1973, RECONNAISSANCE GEOLO GRISSINOMAYER HD, 1995, BIODIVERSITY MANAGEM, P399 GRISSINOMAYER HD, 2000, HOLOCENE, V10, P213 GRUELL GE, 1982, GTRINT130 USDA FOR S GRUELL GE, 1985, P S WORKSH WILD FIR HABECK JR, 1972, INTR172001 USDA FOR HABECK JR, 1973, QUATERNARY RES, V3, P408 HEYERDAHL EK, 2001, ECOLOGY, V82, P660 JENSEN ME, 1993, PNWGTR213 USDA FOR S JOHNSON EA, 1992, FIRE VEGETATION DYNA KAUFMANN MR, 1994, GTRRM246 USDA FOR SE KEANE RE, 1998, GTR3 RMRS USDA FOR S KEANE RE, 1999, LANDSCAPE ECOL, V14, P311 KEANE RE, 2000, RMRSGTR46CD USDA FOR KUSHLA JD, 1997, FOREST ECOL MANAG, V95, P97 LARSEN JA, 1922, MON WEATHER REV, V49, P55 LOUGH JM, 1987, CLIMATIC CHANGE, V10, P219 MARTIN RE, 1982, FOREST SUCCESSION ST, P92 MCCABE GJ, 1999, INT J CLIMATOL, V19, P1399 MCKELVEY KS, 1996, 20 CENTURY FIRE PATT MINNICH RA, 1983, SCIENCE, V219, P1287 MOORE B, 1996, LOCHSA STORY LAND ET MORGAN P, 2001, INT J WILDLAND FIRE, V10, P329 NOBLE IR, 1980, VEGETATIO, V43, P5 PALMER WC, 1965, 45 US DEP COMM WEAT PERRY GLW, 1998, PROG PHYS GEOG, V22, P222 PFISTER RD, 1980, FOREST SCI, V26, P52 PYNE SJ, 1996, INTRO WILDLAND FIRE ROLLINS MG, 2000, THESIS U ARIZONA TUC ROLLINS MG, 2001, CAN J FOREST RES, V31, P2107 ROMME WH, 1981, ECOLOGY, V62, P319 ROMME WH, 1982, ECOL MONOGR, V52, P199 ROTHERMEL RC, 1983, GTRINT143 USDA FOR S SAVAGE M, 1990, ECOLOGY, V71, P2374 SCHROEDER MJ, 1970, USDA FOREST SERVICE, V360 STEPHENSON NL, 1990, AM NAT, V135, P649 STRAUSS D, 1989, FOREST SCI, V35, P319 SWANSON FJ, 1981, FIRE REGIMES ECOSYST, P410 SWETNAM TW, 1985, P S WORKSH WILD FIR, P390 SWETNAM TW, 1990, SCIENCE, V249, P1017 SWETNAM TW, 1993, SCIENCE, V262, P85 SWETNAM TW, 1996, P 2 MES FIR S MARCH SWETNAM TW, 1998, J CLIMATE, V11, P3128 TURNER MG, 1995, SCI BIODIVERSITY SS, P29 TURNER MG, 1997, ECOL MONOGR, V67, P411 VEBLEN TT, 1999, ECOL MONOGR, V69, P47 WARING RH, 1998, FOREST ECOSYSTEMS AN WEAVER H, 1951, J FOREST, V49, P93 WHITTAKER RH, 1965, ECOLOGY, V46, P429 0921-2973 Landsc. Ecol.ISI:000179774900005US Forest Serv, USDA, Fire Sci Lab, Missoula, MT 59807 USA. Univ Idaho, Coll Nat Resources, Dept Forest Resources, Moscow, ID 83844 USA. Univ Arizona, Tree Ring Res Lab, Tucson, AZ 85721 USA. Rollins, MG, US Forest Serv, USDA, Fire Sci Lab, 5775 Hwy 10 W, Missoula, MT 59807 USA.English |75Romero, S. Campbell, J. F. Nechols, J. R. With, K. A.2009RMovement behavior in response to landscape structure: the role of functional grain39-51Landscape Ecology241search strategy grain size perceptive resolution space use red flour beetle tribolium castaneum fragmented landscapes population consequences dispersal behavior fractal landscapes animal movements patch structure habitat connectivity heterogeneity ecologyJanLandscape structure can influence the fine-scale movement behavior of dispersing animals, which ultimately may influence ecological patterns and processes at broader scales. Functional grain refers to the finest scale at which an organism responds to spatial heterogeneity among patches and extends to the limits of its perceptual range. To determine the functional grain of a model insect, red flour beetle (Tribolium castaneum), we examined its movement behavior in response to experimental flour landscapes. Landscape structure was varied by manipulating habitat abundance (0%, 10%, 30%, and 100%) and grain size of patches (fine-2 x 2 cm, intermediate-5 x 5 cm, and coarse-10 x 10 cm) in 50 x 50 cm landscapes. Pathway metrics indicated that beetles used a similar proportion of all landscape types. Several pathway metrics indicated a graded response from the fine to the coarse grain landscape. Lacunarity analysis of beetle pathways indicated a non-linear change in space use between the fine and intermediate landscapes and the coarse-grained landscape. Beetles moved more slowly and tortuously (with many turns), and remained longer in both the overall landscape and individual patches, in fine-grained compared to coarse-grained landscapes. Our research demonstrates how detailed examination of movement pathways and measures of lacunarity can be useful in determining functional grain. Spatially explicit, organism-centered studies focusing on behavioral responses to different habitat configurations can serve as an important first step to identify behavioral rules of movement that may ultimately lead to more accurate predictions of space use in landscapes.://000262506000004-395EI Times Cited:0 Cited References Count:44 0921-2973ISI:000262506000004Romero, S Univ Kentucky, Dept Entomol, Agr Sci Ctr N S225, Lexington, KY 40546 USA Kansas State Univ, Dept Entomol, Manhattan, KS 66506 USA USDA ARS Grain Mkt, Prod & Res Ctr, Manhattan, KS 66502 USA Kansas State Univ, Div Biol, Manhattan, KS 66506 USADoi 10.1007/S10980-008-9278-8English~?MRomero-Calcerrada, Raul Novillo, C. J. Millington, J. D. A. Gomez-Jimenez, I.2008kGIS analysis of spatial patterns of human-caused wildfire ignition risk in the SW of Madrid (Central Spain)341-354Landscape Ecology233The majority of wildfires in Spain are caused by human activities. However, much wildfire research has focused on the biological and physical aspects of wildfire, with comparatively less attention given to the importance of socio-economic factors. With recent changes in human activity and settlement patterns in many parts of Spain, potentially contributing to the increases in wildfire occurrence recently observed, the need to consider human activity in models of wildfire risk for this region are apparent. Here we use a method from Bayesian statistics, the weights of evidence (WofE) model, to examine the causal factors of wildfires in the south west of the Madrid region for two differently defined wildfire seasons. We also produce predictive maps of wildfire risk. Our results show that spatial patterns of wildfire ignition are strongly associated with human access to the natural landscape, with proximity to urban areas and roads found to be the most important causal factors We suggest these characteristics and recent socio-economic trends in Spain may be producing landscapes and wildfire ignition risk characteristics that are increasingly similar to Mediterranean regions with historically stronger economies, such as California, where the urban-wildland interface is large and recreation in forested areas is high. We also find that the WofE model is useful for estimating future wildfire risk. We suggest the methods presented here will be useful to optimize time, human resources and fire management funds in areas where urbanization is increasing the urban-forest interface and where human activity is an important cause of wildfire ignition.&://BIOSIS:PREV200800296342 Times Cited: 0BIOSIS:PREV200800296342w?Romme, William H.1988(News of interest to landscape ecologists253-254Landscape Ecology14_? <Rooney, Rebecca Bayley, Suzanne Creed, Irena Wilson, Matthew2012VThe accuracy of land cover-based wetland assessments is influenced by landscape extent 1321-1335Landscape Ecology279Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9784-6 0921-297310.1007/s10980-012-9784-6|? %Rooney, Rebecca C. Bayley, Suzanne E.2011Relative influence of local- and landscape-level habitat quality on aquatic plant diversity in shallow open-water wetlands in Alberta's boreal zone: direct and indirect effects 1023-1034Landscape Ecology267AugReclamation usually involves modification of the local environment to achieve some biotic target, but if the influence of Landscape Condition on that target is great, we may fail to meet it despite efforts at the local-level. We sought to determine the relative influence of local- and landscape-level habitat on aquatic plant diversity in shallow open-water wetlands. Furthermore, we asked whether the influence of Landscape Condition should be attributed to direct (dispersal-related) effects, or to the indirect effect of landscape variables that influence local habitat quality. Finally, we asked if spatial scale (300-2000 m) would affect conclusions about the relative influence of local- and landscape-level effects. Using structural equation modeling, we found that Local Condition is consistently more influential than Landscape Condition. As landscape size increases, the relative importance of Landscape Condition declines and there is a trade-off between its direct and indirect components. At a parts per thousand currency sign500 m direct landscape effects were of greater importance than indirect effects, whereas indirect effects of Landscape Condition became more important at a parts per thousand yen1500 m. This suggests that the dominant mechanism by which land use influences diversity depends on the spatial extent of the landscape. We recommend that reclamation designs include a high proportion of wetland habitat and incorporate seeding/planting if diverse plant communities are desired. Additionally, we note that the influence of the landscape is strongest within 300 m. Thus, the focus of reclamation efforts should remain at the in-lake level and the immediate surroundings: this is where efforts will achieve the greatest effect on aquatic plant diversity.!://WOS:000292705900010Times Cited: 0 0921-2973WOS:00029270590001010.1007/s10980-011-9629-8|?)`Roscioni, Federica Rebelo, Hugo Russo, Danilo Carranza, Maria Laura Di Febbraro, Mirko Loy, Anna2014ZA modelling approach to infer the effects of wind farms on landscape connectivity for bats891-903Landscape Ecology295May}Little is known about the potentially disrupting effects of wind farms on the habitat connectivity of flying vertebrates at the landscape scale. We developed a regional-scale model to assess the wind farm impact on bat migration and commuting routes. The model was implemented for the bat Nyctalus leisleri in a region of central Italy currently undergoing considerable wind farm development. A Species Distribution Model (SDM) for N. leisleri was generated using the MaxEnt algorithm based on 47 presence records (reduced to 19 after the autocorrelation procedure) and 10 environmental variables derived from topographic and land cover maps. We used the SDM to create a map of connectivity using the software UNICOR to identify potential commuting corridors (PCCs). The incidence of each wind farm on bat flight corridors was assessed by overlaying the existing (380) and planned (195) turbine locations onto the PCCs. The SDM was statistically robust (AUC > 0.8). Most of the corridors were concentrated in the western part of the region, which hosts the largest suitable areas for the species; most of the existing (54 %) and planned (72 %) wind farms interfered with important corridors connecting the western and the eastern parts of the region. Our results provide key information on the impact of the wind farm industry on biodiversity on a regional scale. The novel approach adopted, based on SDM and connectivity analysis, could be easily extended to other flying vertebrates and landscapes and constitutes a promising planning tool necessary for harmonizing the development of renewable energy infrastructures with issues of biodiversity conservation.!://WOS:000334689900011Times Cited: 3 0921-2973WOS:00033468990001110.1007/s10980-014-0030-2? Rosen, R.1989#Similitude, similarity, and scaling207-216Landscape Ecology33/4 similitude, scaling, bifurcationAn exceptionally rich and colorful literature, drawn in almost equal parts from pure mathematics, from the sciences, and from the technologies, has grown up over the years, which bear in different ways on the topics under discussion. It is the intent of the present paper to survey this far-flung literature, point out some of the commonalities and interrelationships which underlie it, and briefly indicate how it has been and can be applied. To my knowledge, this kind of review has not been attempted before. <7=Roshier, D. A. Robertson, A. I. Kingsford, R. T. Green, D. G.2001Continental-scale interactions with temporary resources may explain the paradox of large populations of desert waterbirds in Australia547-556Landscape Ecology166Australian arid zone connectivity landscape structure realised habitat availability temporary wetlands waterbirds NEW-SOUTH-WALES ARID AUSTRALIA MACQUARIE MARSHES COOPER CREEK LAKE EYRE LANDSCAPE ABUNDANCE HABITAT CONNECTIVITY DYNAMICSArticleAugArid Australia supports extraordinary numbers of waterbirds. We show that the solution to this seeming paradox lies in considering the availability of temporary wetland habitat in the context of the birds dispersal capability and fluctuations in the abundance of wetlands in time and space. For species with large dispersal capabilities, the Lake Eyre Basin of central Australia, amongst the driest regions on the continent, has the highest habitat availability for waterbirds. Analyses of landscape structure show that the wetlands of the Lake Eyre Basin are highly interconnected and linked by broad pathways to wetter parts of south-eastern Australia. These analyses illustrate that organism traits and patch dynamics affect realised habitat availability and indicate that the processes that structure populations may operate at much larger spatial scales than those at which humans usually seek to manage the landscape.://000172548800005 S ISI Document Delivery No.: 499AW Times Cited: 15 Cited Reference Count: 49 Cited References: ARTHUR SM, 1996, ECOLOGY, V77, P215 BOHNINGGAESE K, 1994, OIKOS, V70, P121 BOWLER JM, 1981, HYDROBIOLOGIA, V82, P431 BRIGGS SV, 1985, AUST J MAR FRESH RES, V36, P707 BRIGGS SV, 1991, CONSERVATION MANAGEM CANTWELL MD, 1993, LANDSCAPE ECOL, V8, P239 COLLINS SL, 1991, ECOLOGY, V72, P654 FLATHER CH, 1996, ECOLOGY, V77, P28 FRITH HJ, 1959, CSIRO WILDLIFE RES, V4, P108 FRITH HJ, 1962, CSIRO WILDLIFE RES, V7, P50 FRITH HJ, 1963, CSIRO WILDLIFE RES, V8, P119 GREEN DG, 1994, PACIFIC CONSERVATION, V1, P194 HAIG SM, 1998, CONSERV BIOL, V12, P749 HALSE SA, 1998, INT J ECOL ENV SCI, V24, P207 JOHNSON AR, 1996, GIS ENV MODELING PRO, P451 KEITT TH, 1997, CONSERV ECOL, V1 KING RA, 1998, GENET MED, V1, P1 KINGSFORD RT, 1991, DISTRIBUTION ABUNDAN KINGSFORD RT, 1993, BIOL CONSERV, V65, P141 KINGSFORD RT, 1994, BIOL CONSERV, V69, P219 KINGSFORD RT, 1995, ENVIRON MANAGE, V19, P867 KINGSFORD RT, 1995, J ARID ENVIRON, V29, P421 KINGSFORD RT, 1998, COLON WATERBIRD, V21, P159 KINGSFORD RT, 1999, BIOL CONSERV, V88, P231 KNIGHTON AD, 1994, HYDROL PROCESS, V8, P137 KOTWICKI V, 1986, FLOODS LAKE EYRE KOTWICKI V, 1998, PALAEOGEOGR PALAEOCL, V144, P265 MAHER MT, 1992, RANGELAND J, V14, P128 MARCHANT S, 1990, HDB AUSTR NZ ANTARCT, V1 MINTON C, 1995, WINGSPAN JUN, P13 MORRISH RB, 1998, WETLANDS DRY LAND UN, P77 NORMAN FI, 1991, AUST J ECOL, V16, P485 NORMAN FL, 1970, EMU, V70, P126 PUCKRIDGE JT, 1998, MAR FRESHWATER RES, V49, P55 PUCKRIDGE JT, 1998, WETLANDS DRY LAND UN, P87 ROSHIER DA, IN PRESS AUST ECOL ROSHIER DA, 1999, THESIS C STURT U WAG STAFFORDSMITH DM, 1990, J ARID ENVIRON, V18, P255 TAYLOR PD, 1993, OIKOS, V68, P571 TIMMS BV, 1993, HYDROBIOLOGIA, V267, P269 TIMMS BV, 1997, INT J SALT LAKE RES, V5, P287 TIMMS BV, 1998, INT J SALT LAKE RES, V7, P113 TIMMS BV, 1998, WETLANDS DRY LAND UN, P123 WALKER KF, 1985, HYDROBIOLOGIA, V125, P111 WATERMAN MH, 1992, CORELLA, V16, P123 WIENS JA, 1987, OIKOS, V48, P132 WILEY MJ, 1997, FRESHWATER BIOL, V37, P133 WILLIAMS ED, 1981, ECOLOGICAL BIOGEOGRA, P1079 WOODALL PF, 1985, AUST WILDLIFE RES, V12, P495 0921-2973 Landsc. Ecol.ISI:000172548800005Charles Sturt Univ, Sch Sci & Technol, Johnstone Ctr, Wagga Wagga, NSW 2678, Australia. Roshier, DA, Charles Sturt Univ, Sch Sci & Technol, Johnstone Ctr, Locked Bag 588, Wagga Wagga, NSW 2678, Australia.English9<7$Ross, J. A. Matter, S. F. Roland, J.2005bEdge avoidance and movement of the butterfly Parnassius smintheus in matrix and non-matrix habitat127-135Landscape Ecology202Alberta; dispersal; ecotone; emigration; migration; patch; Rocky Mountains METAPOPULATION DYNAMICS; LANDSCAPE CONNECTIVITY; FRAGMENTED LANDSCAPES; DISPERSAL; RESPONSES; BEHAVIOR; PATCH; CONSERVATION; IMMIGRATION; BOUNDARIESArticleFeb=We experimentally examined edge effects and movement patterns of the butterfly Parnassius smintheus in two habitat types, its preferred meadow habitat, and intervening forest matrix habitat. We followed the movement of 46 butterflies released at either 5 or 20m from a forest edge in either forest or meadow habitat. In contrast to theoretical predictions, we found that butterflies flew less frequently, shorter distances, and at lower rates in matrix habitat than they did in meadow habitat. Distance from the edge had little effect on these aspects of movement. Flight was strongly influenced by light levels with butterflies flying more readily at higher light levels. Light levels were higher in meadows than in forest explaining much of the difference in movement patterns. Turning angles showed that butterflies flying in meadow habitat avoided forest edges and that this effect extended nearly 25 m into meadows. Analysis of net displacement from the forest edge reinforced this result and showed that there may be attraction to the meadow for butterflies flying within forest.://000230299600001 ISI Document Delivery No.: 942RN Times Cited: 2 Cited Reference Count: 42 Cited References: BELISLE M, 2002, LANDSCAPE ECOL, V17, P219 BOWNE DR, 1999, LANDSCAPE ECOL, V14, P53 BRDAR CL, 2000, THESIS U ALBERTA EDM CONNOR EF, 1983, ECOLOGY, V64, P191 CRONE EE, 2001, ECOLOGY, V82, P831 EHRLICH PR, 2003, BUTTERFLIES ECOLOGY FOWNES S, 2002, ECOL ENTOMOL, V27, P457 GOBEIL JF, 2002, OIKOS, V98, P447 HADDAD NM, 1999, ECOL APPL, V9, P612 HANSKI I, 1994, J ANIM ECOL, V63, P151 HANSKI I, 1999, METAPOPULATION ECOLO HEIN S, 2003, ECOL ENTOMOL, V28, P432 IDE JY, 2002, ECOL ENTOMOL, V27, P33 JONSEN ID, 2001, OECOLOGIA, V127, P287 KEYGHOBADI N, 1999, MOL ECOL, V8, P1481 KURAS T, 2000, KLAPALEKIANA, V36, P93 KUUSSAARI M, 1996, J ANIM ECOL, V65, P791 LAND MF, 1997, ANNU REV ENTOMOL, V42, P147 LIMA SL, 1990, CAN J ZOOL, V68, P619 MATTER SF, 1996, OECOLOGIA, V105, P447 MATTER SF, 1996, VA J SCI, V47, P19 MATTER SF, 1997, OECOLOGIA, V110, P533 MATTER SF, 2002, ECOL ENTOMOL, V27, P308 MATTER SF, 2004, IN PRESS ECOLOGICAL MERCKX T, 2003, P ROY SOC LOND B BIO, V270, P1815 MOILANEN A, 1998, ECOLOGY, V79, P2503 MOILANEN A, 2002, ECOLOGY, V83, P1131 PITHER J, 1998, OIKOS, V83, P166 PRYKE SR, 2001, BIOL CONSERV, V101, P85 PULLIAM HR, 1988, AM NAT, V132, P652 RACETTE G, 1992, PHYTOPROTECTION, V73, P85 RICKETTS TH, 2001, AM NAT, V158, P87 RIES L, 2001, J ANIM ECOL, V70, P840 ROLAND J, 2000, ECOLOGY, V81, P1642 RUTOWSKI RL, 2001, BEHAVIOUR 1, V138, P31 SCHTICKZELLE N, 2003, J ANIM ECOL, V72, P533 SHULTZ CB, 2001, ECOLOGY, V82, P1879 SIMBERLOFF D, 1992, CONSERV BIOL, V6, P493 THOMAS CD, 1996, AM NAT, V148, P957 TISCHENDORF L, 2000, OIKOS, V90, P7 TURCHIN P, 1991, ECOLOGY, V72, P1253 VAISANEN R, 1985, NOTULAE ENTOMOLOGICA, V65, P109 0921-2973 Landsc. Ecol.ISI:000230299600001KUniv Cincinnati, Dept Biol Sci, Cincinnati, OH 45203 USA. Cincinnati Museum Ctr, Cincinnati, OH 45203 USA. Truman State Univ, Div Sci, Kirksville, MO 63501 USA. Univ Alberta, Dept Biol Sci, Edmonton, AB T6G 2E9, Canada. Matter, SF, Univ Cincinnati, Dept Biol Sci, 1301 Western Ave, Cincinnati, OH 45203 USA. smatter@cincymuseum.orgEnglish)<7}(Roth, N. E. Allan, J. D. Erickson, D. L.1996SLandscape influences on stream biotic integrity assessed at multiple spatial scales141-156Landscape Ecology113FISH COMMUNITIES; AGRICULTURAL WATERSHEDS; RIPARIAN; MANAGEMENT; HABITAT; QUALITY; CLASSIFICATION; PERSPECTIVE; RECOVERY; FORESTSArticleJunHThe biological integrity of stream ecosystems depends critically on human activities that affect land use/cover along stream margins and possibly throughout the catchment. We evaluated stream condition using an Index of Biotic Integrity (IBI) and a habitat index (HI), and compared these measures to landscape and riparian conditions assessed at different spatial scales in a largely agricultural Midwestern watershed. Our goal was to determine whether land use/cover was an effective predictor of stream integrity, and if so, at what spatial scale. Twenty-three sites in first-through third-order headwater streams were surveyed by electrofishing and site IBIs were calculated based on ten metrics of the fish collection. Habitat features were characterized through field observation, and site HIs calculated from nine instream and bank metrics. Field surveys, aerial photograph interpretation, and geographic information system (GIS) analyses provided assessments of forested land and other vegetation covers at the local, reach, and regional (catchment) scales. The range of conditions among the 23 sites varied from poor to very good based on IBI and KI scores, and habitat and fish assemblage measures were highly correlated. Stream biotic integrity and habitat quality were negatively correlated with the extent of agriculture and positively correlated with extent of wetlands and forest. Correlations were strongest at the catchment scale (IBI with % area as agriculture, r(2) = 0.50, HI with agriculture, r(2) = 0.76), and tended to become weak and non-significant at local scales. Local riparian vegetation was a weak secondary predictor of stream integrity. In this watershed, regional land use is the primary determinant of stream conditions, able to overwhelm the ability of local site vegetation to support high-quality habitat and biotic communities.://A1996UX47800002 ISI Document Delivery No.: UX478 Times Cited: 187 Cited Reference Count: 48 Cited References: *MDNR, 1990, CURR US INV DAT COLL *MDNR, 1991, 51 GLEAS MICH DNR SU *OH EPA, 1989, BIOL CRIT PROT AQ LI, V3 ANDERSON JR, 1976, 964 GEOL SURV BARTON DR, 1985, N AM J FISH MANAGE, V5, P364 BECKER GC, 1983, FISHES WISCONSIN BERKMAN HE, 1987, ENVIRON BIOL FISH, V18, P285 DELONG MD, 1991, ENVIRON MANAGE, V15, P565 DELONG MD, 1993, HYDROBIOLOGIA, V262, P77 DETENBECK NE, 1992, ENVIRON MANAGE, V16, P33 FAUSCH KD, 1990, AM FISHERIES SOC S, V8, P123 FAUSCH KD, 1992, CAN J FISH AQUAT SCI, V49, P682 FRISSELL CA, 1986, ENVIRON MANAGE, V10, P199 GATZ AJ, 1993, OHIO J SCI, V93, P95 GREGORY SV, 1991, BIOSCIENCE, V41, P540 KARR JR, 1978, SCIENCE, V201, P229 KARR JR, 1985, BIOSCIENCE, V35, P90 KARR JR, 1986, ILLINOIS NATURAL HIS, V5 KARR JR, 1991, ECOL APPL, V1, P66 LOWRANCE R, 1984, BIOSCIENCE, V34, P374 MARSH PC, 1982, FISHERIES, V7, P16 MARSH PC, 1982, FISHERIES, V7, P24 MATTHEWS WJ, 1987, COMMUNITY EVOLUTIONA MILLER RR, 1989, FISHERIES, V14, P22 MINSHALL GW, 1985, CAN J FISH AQUAT SCI, V42, P1045 NAIMAN RJ, 1992, WATERSHED MANAGEMENT NAIMAN RJ, 1993, ECOL APPL, V3, P209 OMERNIK JM, 1981, J SOIL WATER CONSERV, V36, P227 ONEILL RV, 1989, LANDSCAPE ECOL, V3, P193 OSBORNE LL, 1988, J ENVIRON MANAGE, V26, P9 OSBORNE LL, 1993, FRESHWATER BIOL, V29, P243 PETERJOHN WT, 1984, ECOLOGY, V65, P1466 PETERSEN RC, 1987, AMBIO, V16, P166 PETERSEN RC, 1992, FRESHWATER BIOL, V27, P295 PLATTS WS, 1983, INT138 US FOR SERV ROTH NE, 1994, THESIS U MICHIGAN SCHLOSSER IJ, 1982, ECOL MONOGR, V52, P395 SCHLOSSER IJ, 1991, BIOSCIENCE, V41, P704 SCOTT WB, 1973, B FISH RES BOARD CAN, V184 SEDELL JR, 1990, ENVIRON MANAGE, V14, P711 SMITH GR, 1981, MICHIGAN ACAD, V13, P275 STEEDMAN RJ, 1988, CANADIAN J FISHERIES, V45, P492 STRAHLER AN, 1957, T AM GEOPHYSICAL UNI, V38, P913 SWEENEY BW, 1992, WATER SCI TECHNOL, V26, P2653 TRAUTMAN MB, 1981, FISHES OHIO VANNOTE RL, 1980, CAN J FISH AQUAT SCI, V37, P130 WHITTIER TR, 1987, EPA600387025 YANT P, 1980, UNPUB FISH FAUNAL CH 0921-2973 Landsc. Ecol.ISI:A1996UX47800002<UNIV MICHIGAN,SCH NAT RESOURCES ENVIRONM,ANN ARBOR,MI 48109.English .}?(Roy, A. H. Freeman, B. J. Freeman, M. C.2007MRiparian influences on stream fish assemblage structure in urbanizing streams385-402Landscape Ecology223riparian buffer; catchment; urban; land use/cover; land-water interface; piedmont; stream; fish MULTIPLE SPATIAL SCALES; LAND-USE; BIOTIC INTEGRITY; COMMUNITY COMPOSITION; LANDSCAPE ECOLOGY; ECOSYSTEMS; HABITAT; WATER; QUALITY; ZONES Mar@We assessed the influence of land cover at multiple spatial extents on fish assemblage integrity, and the degree to which riparian forests can mitigate the negative effects of catchment urbanization on stream fish assemblages. Riparian cover (urban, forest, and agriculture) was determined within 30 m buffers at longitudinal distances of 200 m, 1 km, and the entire network upstream of 59 non-nested fish sampling locations. Catchment and riparian land cover within the upstream network were highly correlated, so we were unable to distinguish between those variables. Most fish assemblage variables were related to % forest and % urban land cover, with the strongest relations at the largest spatial extent of land cover (catchment), followed by riparian land cover in the 1-km and 200-m reach, respectively. For fish variables related to urban land cover in the catchment, we asked whether the influence of riparian land cover on fish assemblages was dependent on the amount of urban development in the catchment. Several fish assemblage metrics (endemic richness, endemic: cosmopolitan abundance, insectivorous cyprinid richness and abundance, and fluvial specialist richness) were all best predicted by single variable models with % urban land cover. However, endemic: cosmopolitan richness, cosmopolitan abundance, and lentic tolerant abundance were related to % forest cover in the 1-km stream reach, but only in streams that had < 15% catchment urban land cover. In these cases, catchment urbanization overwhelmed the potential mitigating effects of riparian forests on stream fishes. Together, these results suggest that catchment land cover is an important driver of fish assemblages in urbanizing catchments, and riparian forests are important but not sufficient for protecting stream ecosystems from the impacts of high levels of urbanization. ://000244455200005 0921-2973ISI:000244455200005G?~ Royo, Alejandro2012mGardner T. Monitoring Forest Biodiversity: Improving Conservation Through Ecologically-Responsible Management151-152Landscape Ecology271Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-011-9660-9 0921-297310.1007/s10980-011-9660-9,?Rudis, Victor A.1995`Regional forest fragmentation effects on bottonland hardwood community types and resource values291-307Landscape Ecology105zanthropogenic uses, forest resource surveys, forested wetland habitat, ownership, regional effects, southern United States2|7Q Rudis, V. A.1995`Regional Forest Fragmentation Effects on Bottomland Hardwood Community Types and Resource Values291-307Landscape Ecology105uanthropogenic uses forest resource surveys forested wetland habitat ownership regional effects southern united statesOct)In human-dominated regions, forest vegetation removal impacts remaining ecosystems but regional-scale biological consequences and resource value changes are not well known. Using forest resource survey data, I examined current bottomland hardwood community types and a range of fragment size classes in the south central United States. Analyses examined resource value indicators, appraised tree-based flood zone and shade tolerance indices, and identified potential regional-scale processes. Findings revealed that the largest fragments had fewer tree species, reduced anthropogenic use evidence, and more older and wetter community types than small fragments. Results also suggested the need for incorporating hydrologic, geomorphic, and understory vegetation parameters in regional forest resource monitoring efforts. Two regional-scale processes are hypothesized: (1) forest fragmentation occurs more frequently in drier habitats and dry zone (inundated less than or equal to 2 months annually), younger seral stage bottomland community types; and (2) forest fragmentation induces establishment of drier habitats or dry zone, younger seral stage community types. Both hypotheses suggest that regional forest fragmentation impacts survival of distinct community types, anthropogenic uses, and multiple resource values.://A1995TD59500004-Td595 Times Cited:16 Cited References Count:0 0921-2973ISI:A1995TD59500004^Rudis, Va Us Forest Serv,Forestry Inventory & Anal Unit,So Res Stn,Pob 906,Starkville,Ms 39759English |7Ruiz, J. Domon, G.2009Analysis of landscape pattern change trajectories within areas of intensive agricultural use: case study in a watershed of southern Qu,bec, Canada419-432Landscape Ecology243landscape change rural landscape driving forces cadastral division ward clustering saint-laurent quebec biophysical factors land-use dynamics perceptions hedgerows policyMarThis study aimed at capturing the spatial variability of landscape patterns and their trajectories of change from 1950 to 2000 within a watershed, which is representative of areas of intensive agricultural use. After an analysis of landscape features changes for the entire watershed based on aerial photographs, hierarchical clustering analysis provided a typology of landscape patterns for the cadastral lots. Following that, the trajectory of change of each lot was characterized (nature, importance, direction, rate of change). Seven types of landscape patterns are distinguished by the relative importance of different classes of landscape features and 51 trajectories of change were identified for the lots. The analysis shows that although the majority of lots were subjected to a homogenization of their landscape patterns since 1950, this trend is not entirely uniform and that since 2000 it occurs alongside trends towards diversification of certain landscape features on some lots. Furthermore, nearly a third of the lots are not following the main trajectories of change detected. Thus, the results suggest that extrinsic forces (policies, technologies) that are directing main changes in areas of intensive agricultural use toward uniformity could be modulated by internal forces (uses and values of the population). A better understanding of theses internal forces seems crucial to manage landscapes. From a methodology standpoint, although the hierarchical clustering analyses appear useful for understanding the spatial and temporal variability of landscape patterns, particular attention must be given to validating the typology chosen to characterize them.://000263419500010-408EY Times Cited:0 Cited References Count:30 0921-2973ISI:000263419500010Ruiz, J Univ Montreal, Chair Landscape & Environm Design, Fac Environm Design, CP 6128,Succ Ctr Ville, Montreal, PQ H3C 3J7, Canada Univ Montreal, Chair Landscape & Environm Design, Fac Environm Design, Montreal, PQ H3C 3J7, CanadaDoi 10.1007/S10980-009-9321-4English`|?FRuiz, Luis Parikh, Niki Heintzman, Lucas J. Collins, Steven D. Starr, Scott M. Wright, Christopher K. Henebry, Geoffrey M. van Gestel, Natasja McIntyre, Nancy E.2014GDynamic connectivity of temporary wetlands in the southern Great Plains507-516Landscape Ecology293MarWe quantified fluctuations in the status of individual patches (wetlands) in supporting connectivity within a network of playas, temporary wetlands of the southern Great Plains of North America that are loci for regional biodiversity. We used remote sensing imagery to delineate the location of surface waters in >8,000 playa basins in a similar to 31,900 km(2) portion of Texas and quantified connectivity in this region from 2007 to 2011. We ranked playas as stepping-stones, cutpoints, and hubs at different levels of environmental conditions (regionally wet, dry, and average periods of precipitation) for dispersal distances ranging from 0.5 to 34 km, representing a range of species' vagilities, to provide baseline dynamics within an area likely to experience disrupted connectivity due to anthropogenic activities. An individual playa's status as a stepping-stone, cutpoint, or hub was highly variable over time (only a single playa was a top 20 stepping-stone, cutpoint, or hub in >50 % of all of the dates examined). Coalescence of the inundated playa network usually occurred at >= 10 km dispersal distance and depended on wetland density, indicating that critical thresholds in connectivity arose from synergistic effects of dispersal ability (spatial scale) and wet playa occurrence (a function of precipitation). Organisms with dispersal capabilities limited to <10 km routinely experienced effective isolation during our study. Connectivity is thus a dynamic emergent landscape property, so management to maintain connectivity for wildlife within ephemeral habitats like inundated playas will need to move beyond a patch-based focus to a network focus by including connectivity as a dynamic landscape property.!://WOS:000331935500012Times Cited: 0 0921-2973WOS:00033193550001210.1007/s10980-013-9980-z<7z$Ruiz-Luna, A. Berlanga-Robles, C. A.2003rLand use, land cover changes and coastal lagoon surface reduction associated with urban growth in northwest Mexico159-171Landscape Ecology182coastal lagoons cumulative impact LULC remote sensing urban development OF-CALIFORNIA MANAGEMENT ESTUARY IMPACTS ASSEMBLAGES LANDSCAPE WETLANDS PATTERNS SINALOAArticleCoastal land use and land cover changes, emphasizing the alterations of coastal lagoons, were assessed in northwest Mexico using satellite imagery processing. Supervised classifications of a Landsat series (1973 - 1997) and the coefficients Kappa (K) and Tau (tau), were used to assess the area and verify the accuracy of the classification of six informational classes ( urban area, aquatic systems, mangrove, agriculture, natural vegetation, and aquaculture). Pixel-by-pixel change detection among dates was evaluated using the Kappa Index of Agreement (KIA). Besides the overall estimation of the aquatic systems class, variations in the three lagoons present in the study area were analyzed individually. Measures of agreement between the classification and reference data indicate that the accuracy for the classification ranked from moderate to high (K = 0.76 +/- 0.07; tau = 0.77 +/- 0.06). From 1973 to 1997 urban area has doubled, growing to the north and the northeast, extending mainly over natural vegetation and agricultural land. La Escopama and El Sabalo, two of the lagoons studied, reduced their size to less than half that estimated in 1973, but the main estuarine system in the study area, Estero de Urias - El Infiernillo, has maintained its area without noticeable changes. However, the surrounding landscape in Estero de Urias - Infiernillo is changing from natural vegetation and agriculture to urban land use. Consequently, to limit as much as possible changes in the area to natural causes, some management measures must be considered to design urban development plans and to recover and preserve the natural areas, on a broad scale rather than a local spatial scale.://000183770300005 ISI Document Delivery No.: 694JB Times Cited: 6 Cited Reference Count: 37 Cited References: *INEGI, 1993, MAZ SIN EST MUN STAT *INEGI, 1999, STAT YB EST SIN BAILY B, 1996, OCEAN COAST MANAGE, V32, P85 BEDFORD BL, 1999, WETLANDS, V19, P775 BERAUD LJL, 1996, HIST ACTORS URBANIZA BERLANGA RCA, 1999, THESIS NATL AUTONOMO BRONDIZIO ES, 1994, HUM ECOL, V22, P249 CONGALTON RG, 1999, ASSESSING ACCURACY R CUARON AD, 2000, CONSERV BIOL, V14, P1676 DELAGARZA SR, 1985, THESIS U AUTONOMA SI EASTMAN JR, 1995, IDRISI WINDOWS USERS GREEN EP, 1996, COAST MANAGE, V24, P1 GRIGNETTI A, 1997, INT J REMOTE SENS, V18, P1307 GRIMM NB, 2000, BIOSCIENCE, V50, P571 HELMER EH, 2000, INT J REMOTE SENS, V21, P2163 JACKSON JBC, 2001, SCIENCE, V293, P629 JI CY, 2001, INT J REMOTE SENS, V22, P1441 JOHNSTON CA, 1994, WETLANDS, V14, P49 LANDGREBE D, 1995, INTRO MULTISPEC LANDIS JR, 1977, BIOMETRICS, V33, P159 LUQUE SS, 2000, INT J REMOTE SENS, V21, P2589 MA ZK, 1995, PHOTOGRAMM ENG REM S, V61, P435 MAS JF, 1997, P 4 INT C REM SENS M, V1, P159 MCCOLD LN, 1996, ENVIRON MANAGE, V20, P767 MCCREARY S, 1992, COAST MANAGE, V20, P219 MENDEZ N, 2002, OCEANOL ACTA, V25, P139 OCHOAIZAGUIRRE MJ, 2002, BOT MAR, V45, P130 OREGAN PR, 1996, J COASTAL RES, V12, P192 RAMIREZ ZJR, 1998, THESIS CIAD MAZATLAN RINGROSE S, 1997, INT J REMOTE SENS, V18, P2337 RUELASINZUNZA JR, 2000, ENVIRON POLLUT, V107, P437 RUIZ LA, 1998, P 5 INT C ENV LA HAB RUIZLUNA A, 1999, ESTUAR COAST SHELF S, V49, P37 SOTOJIMENEZ MF, 2001, ESTUAR COAST SHELF S, V53, P259 VANMANSVELT JD, 1999, CHECKLIST SUSTAINABL VEGA AE, 1998, HIST MAZATLAN MUNICI, P21 ZALIDIS GC, 1997, WETLANDS, V17, P339 0921-2973 Landsc. Ecol.ISI:000183770300005sAC Unidad Mazatlan, CIAD, Mexico City, DF, Mexico. Ruiz-Luna, A, AC Unidad Mazatlan, CIAD, Mexico City, DF, Mexico.English<7"*Rupp, T. S. Starfield, A. M. Chapin, F. S.2000yA frame-based spatially explicit model of subarctic vegetation response to climatic change: comparison with a point model383-400Landscape Ecology154Eboreal forest climatic change explicit fire insects landscape dynamics model spatially subarctic transient dynamics treeline FOREST ECOSYSTEM PROCESSES YELLOWSTONE-NATIONAL-PARK EASTERN NORTH-AMERICA STATE-FACTOR CONTROL LAND-USE CHANGE BOREAL FORESTS REGIONAL APPLICATIONS TRANSIENT-RESPONSE FIRE SUPPRESSION INTERIOR ALASKAReviewMayAn important challenge in global-change research is to simulate short-term transient changes in climate, disturbance regime, and recruitment that drive long-term vegetation distributions. Spatial features (e.g., topographic barriers) and processes, including disturbance propagation and seed dispersal, largely control these short-term transient changes. Here we present a frame-based spatially explicit model (ALFRESCO) that simulates landscape-level response of vegetation to transient changes in climate and explicitly represents the spatial processes of disturbance propagation and seed dispersal. The spatial model and the point model from which it was developed showed similar results in some cases, but diverged in situations where interactions among neighboring cells (fire spread and seed dispersal) were crucial. Topographic barriers had little influence on fire size in low-flammability vegetation types, but reduced the average fire size and increased the number of fires in highly flammable vegetation (dry grassland). Large fires were more common in landscapes with large contiguous patches of two vegetation types while a more heterogeneous vegetation distribution increased fires in the less flammable vegetation type. When climate was held constant for thousands of years on a hypothetical landscape with the same initial vegetation, the spatial and point models produced identical results for some climates (cold, warm, and hot mesic), but produced markedly different results at current climate and when much drier conditions were imposed under a hot climate. Spruce migration into upland tundra was slowed or prevented by topographic barriers, depending on the size of the corridor. We suggest that frame-based, spatially explicit models of vegetation response to climate change are a useful tool to investigate both short- and long-term transients in vegetation at the regional scale. We also suggest that it is difficult to anticipate when non-spatial models will be reliable and when spatially explicit models are essential. ALFRESCO provides an important link between models of landscape-level vegetation dynamics and larger spatio-temporal models of global climate change.://000086006700007 'ISI Document Delivery No.: 296DA Times Cited: 20 Cited Reference Count: 106 Cited References: 1994, ALASKA LAND CHARACTE *AL FIR SERV, 1992, 1992 FIR STAT SEAS S *NRC, 1994, ROL TERR EC GLOB CHA ALBINI FA, 1976, COMPUTER BASED MODEL ANDERSON PM, 1988, QUATERNARY RES, V29, P263 ANTONOVSKI MY, 1992, SYSTEMS ANAL GLOBAL, P373 BAKER WL, 1991, ECOL MODEL, V56, P109 BAKER WL, 1992, ECOLOGY, V73, P1879 BAKER WL, 1993, OIKOS, V66, P66 BLISS LC, 1992, ARCTIC ECOSYSTEMS CH, P58 BONAN GB, 1990, CAN J FOREST RES, V20, P1077 BONAN GB, 1992, NATURE, V359, P716 BONAN GB, 1995, CLIMATIC CHANGE, V29, P145 BRUBAKER LB, 1983, QUATERNARY RES, V20, P194 CATTLE H, 1995, PHILOS T ROY SOC A, V352, P201 CHAPIN FS, 1997, CLIMATIC CHANGE, V35, P449 CHROSCIEWICZ Z, 1986, CAN J FOREST RES, V16, P157 CLARK JS, 1988, NATURE, V334, P233 CLARK JS, 1991, ECOLOGY, V72, P1102 CLARK JS, 1996, AM NAT, V148, P976 CLARK JS, 1996, ECOLOGY, V77, P2148 CLARK JS, 1998, ECOL MONOGR, V68, P213 CLARK JS, 1998, IN PRESS ECOLOGY CRAMER WP, 1993, VEGETATION DYNAMICS, P190 DALE VH, 1997, ECOL APPL, V7, P753 DAVIS MB, 1981, FOREST SUCCESSION CO, P132 DAVIS MB, 1983, ANN MO BOT GARD, V70, P550 DAVIS MB, 1985, QUATERNARY RES, V23, P327 DAVIS MB, 1986, COMMUNITY ECOLOGY, P269 EDWARDS ME, 1989, ARCTIC ALPINE RES, V21, P296 FASTIE CL, 1995, ECOLOGY, V76, P1899 FINNEY MA, 1998, RMRSRP4 USDA FOR SER FLANNIGAN MD, 1988, J APPL METEOROL, V27, P441 FLANNIGAN MD, 1991, CAN J FOREST RES, V21, P66 FOLEY JA, 1994, NATURE, V371, P52 GARDNER RH, 1996, GLOBAL CHANGE TERRES, P149 GREEN DG, 1989, VEGETATIO, V82, P139 GREENE DF, 1995, CAN J BOT, V73, P1036 GREENE DF, 1996, ECOLOGY, V77, P595 GREENE DF, 1997, J ECOL, V85, P329 HADLEY KS, 1994, B TORREY BOT CLUB, V121, P47 HOBBIE SE, 1998, ECOLOGY, V79, P1526 HOLLING CS, 1992, SYSTEMS ANAL GLOBAL, P170 HOPKINS DM, 1982, PALEOECOLOGY BERINGI HOUGHTON JT, 1990, CLIMATE CHANGE IPCC HU FS, 1993, CAN J BOT, V71, P1133 JOHNSON EA, 1992, FIRE VEGETATION DYNA KALLIO P, 1973, REP KEVO SUBARCTIC R, V10, P55 KASISCHKE ES, 1995, REMOTE SENS ENVIRON, V51, P263 KEANE RE, 1996, INTRP484 USDA FOR SE KELLOMAKI S, 1992, VEGETATIO, V102, P47 KIELLAND K, 1997, OIKOS, V80, P25 KITTEL TGF, IN PRESS GLOBAL CHAN LARSEN JA, 1965, ECOL MONOGR, V35, P37 LENIHAN JM, 1995, CLIMATIC CHANGE, V30, P27 LOEHLE C, 1996, ECOL MODEL, V90, P1 MATTSON WJ, 1987, BIOSCIENCE, V37, P110 MCCAUGHEY WW, 1986, P S CON TREE SEED IN, P50 NEILSON RP, 1992, LANDSCAPE ECOL, V7, P27 NEILSON RP, 1993, ECOL APPL, V3, P385 NIKOLOV NT, 1995, INTERIOR W GLOBAL CH, P78 NOBLE IR, 1980, VEGETATIO, V43, P5 NOBLE IR, 1987, VEGETATIO, V69, P115 NOBLE IR, 1993, ECOL APPL, V3, P396 PASTOR J, 1986, BIOGEOCHEMISTRY, V2, P3 PASTOR J, 1988, NATURE, V334, P55 PASTOR J, 1992, AM NAT, V139, P690 PAYETTE S, 1985, NATURE, V313, P570 PAYETTE S, 1992, SYSTEMS ANAL GLOBAL, P170 PRENTICE IC, 1991, GLOBAL ECOL BIOGEOGR, V1, P129 PRENTICE IC, 1992, J BIOGEOGR, V19, P117 RATZ A, 1995, INT J WILDLAND FIRE, V5, P25 ROBINSON CH, 1998, ECOLOGY, V79, P856 ROTHERMEL RC, 1972, INT115 US FOR SERV RUNNING SW, 1988, ECOL MODEL, V42, P125 RUNNING SW, 1991, TREE PHYSIOL, V9, P147 SELKREGG LL, 1974, ALASKA REGIONAL PROF, V5 SELKREGG LL, 1974, ALASKA REGIONAL PROF, V6 SHUGART HH, 1992, ANNU REV ECOL SYST, V23, P15 SMITH TM, 1993, NATURE, V361, P523 SOLOMON AM, 1984, STATE CHANGE FOREST, P333 SOLOMON AM, 1986, OECOLOGIA, V68, P567 SOLOMON AM, 1992, SYSTEMS ANAL GLOBAL, P170 STARFIELD AM, 1993, AI APPLICATIONS, V7, P1 STARFIELD AM, 1996, ECOL APPL, V6, P842 STOCKS BJ, 1991, GLOBAL BIOMASS BURNI, P197 SUSOTT RA, 1982, FOREST SCI, V28, P404 SYLVESTER TW, 1981, CAN J BOT, V59, P898 THORNTHWAITE CW, 1957, PUBLICATIONS CLIMATO, V10, P183 TORN MS, 1992, CLIMATIC CHANGE, V21, P257 TRIGG WM, 1971, FIRE SEASON CLIMATIC TURNER MG, 1989, OIKOS, V55, P121 TURNER MG, 1993, LANDSCAPE ECOL, V8, P213 TURNER MG, 1994, J VEG SCI, V5, P731 TURNER MG, 1994, LANDSCAPE ECOL, V9, P59 TURNER MG, 1994, NAT AREA J, V14, P3 TURNER MG, 1997, ECOL MONOGR, V67, P411 VANCLEVE K, 1981, FOREST SUCCESSION CO, P185 VANCLEVE K, 1991, BIOSCIENCE, V41, P78 VANCLEVE K, 1996, ARCTIC ALPINE RES, V28, P388 VANWAGNER CE, 1983, ROLE FIRE NO CIRCUMP, P65 VIERECK LA, 1973, QUATERNARY RES, V3, P465 VIERECK LA, 1979, HOLARCTIC ECOL, V2, P228 VIERECK LA, 1984, POTENTIAL EFFECTS CA, P129 WOLFRAM S, 1984, NATURE, V311, P419 ZASADA JC, 1978, PNW65 USDA FOR SERV 0921-2973 Landsc. Ecol.ISI:000086006700007Univ Minnesota, Dept Ecol Evolut & Behav, St Paul, MN 55108 USA. Univ Alaska, Inst Arctic Biol, Fairbanks, AK 99775 USA. Rupp, TS, Univ Alaska, Forest Soils Lab, Fairbanks, AK 99775 USA.English/|?< ORusch, Adrien Valantin-Morison, Muriel Sarthou, Jean-Pierre Roger-Estrade, Jean2011`Multi-scale effects of landscape complexity and crop management on pollen beetle parasitism rate473-486Landscape Ecology264AprImproving our understanding about how natural enemies respond to semi-natural habitats and crop management scattered in the landscape may contribute to the development of ecologically based pest management strategies maximising biological control services. We investigated how soil tillage and semi-natural habitats influenced the parasitism rates of pollen beetle (Meligethes aeneus F.) larvae at 8 different spatial scales (from 250 to 2000 m radius circular sectors) in 42 oilseed rape (OSR) fields. We used multimodel inference approaches to identify and rank the influence of soil tillage and semi-natural habitats on parasitism rates, and to quantify the importance of each scale. Parasitism rates were due to three univoltine parasitoid species (Tersilochus heterocerus, Phradis morionellus and P. interstitialis) and varied from 0 to 98%. We found that both fine and large scales contributed to explain significantly parasitism rates, indicating that biological control of pollen beetle is a multi-scale process. At the 250 m scale, parasitism rates of T. heterocerus were positively related to the proportion of semi-natural habitats and the proximity to previous year OSR fields. At large scales (1500 to 2000 m), parasitism rates of T. heterocerus were positively related to semi-natural habitats and negatively related to the proportion of previous year OSR fields with conventional soil tillage. Parasitism rates of Phradis spp. were only positively related to the proportion of semi-natural habitats at the 1250 and 1500 m scales. These multi-scale effects are discussed in relation to the influence of semi-natural habitats and soil tillage on parasitoid populations and their movement behaviours within the landscape.!://WOS:000288807300003Times Cited: 0 0921-2973WOS:00028880730000310.1007/s10980-011-9573-7 ?4Russell, R.W. G.L. Hunt K.O. Coyle R.T. Cooney1992TForaging in a fractal environment: spatial patterns in a marine predator-prey system195-209Landscape Ecology73Xfractal dimension, spatial correlation, predators, resources, foraging, animal movementsSpatial relationships between predators and prey have important implications for landscape processes and patterns. Highly mobile oceanic birds and their patchily distributed prey constitute an accessible model system for studying these relationships. High-frequency echosounders can be used together with simultaneous direct visual observations to quantitatively describe the distributions of seabird consumers and their resources over a wide range of spatial scales, yielding information which is rarely available in terrestrial systems. Recent fine-scale investigations which have used acoustics to study the distribution of foraging marine birds have reported weak or ephemeral spatial associations between the birds and their prey. These results are inconsistent with predictions of optimal foraging, but several considerations suggest that traditional foraging models do not adequately describe resource acquisition in marine environments. Relative to their terrestrial counterparts, oceanic ‘landscapes’ are structurally very simple, but they generally lack visual cues about resource availability. An emerging view assumes that perceptually constrained organisms searching for food in multiscale environments should respond to patterns of resource abundance over a continuum of scales. We explore fractal geometry as a possible tool for quantifying this view and for describing spatial dispersion patterns that result from foraging behavior. Data on an Alaskan seabird (least auklet [Aethiapusilla]a) nd its zooplanktonic food resources suggest that fractal approaches can yield new ecological insights into complex spatial patterns deriving from animal movements.|7 5Russell, R. W. Hunt, G. L. Coyle, K. O. Cooney, R. T.1992UForaging in a Fractal Environment - Spatial Patterns in a Marine Predator-Prey System195-209Landscape Ecology73rfractal dimension spatial correlation predators consumers resources seabirds zooplankton foraging animal movementsSepSpatial relationships between predators and prey have important implications for landscape processes and patterns. Highly mobile oceanic birds and their patchily distributed prey constitute an accessible model system for studying these relationships. High-frequency echosounders can be used together with simultaneous direct visual observations to quantitatively describe the distributions of seabird consumers and their resources over a wide range of spatial scales, yielding information which is rarely available in terrestrial systems. Recent fine-scale investigations which have used acoustics to study the distribution of foraging marine birds have reported weak or ephemeral spatial associations between the birds and their prey. These results are inconsistent with predictions of optimal foraging, but several considerations suggest that traditional foraging models do not adequately describe resource acquisition in marine environments. Relative to their terrestrial counterparts, oceanic 'landscapes' are structurally very simple, but they generally lack visual cues about resource availability. An emerging view assumes that perceptually constrained organisms searching for food in multiscale environments should respond to patterns of resource abundance over a continuum of scales. We explore fractal geometry as a possible tool for quantifying this view and for describing spatial dispersion patterns that result from foraging behavior. Data on an Alaskan seabird (least auklet [Aethia pusilla]) and its zooplanktonic food resources suggest that fractal approaches can yield new ecological insights into complex spatial patterns deriving from animal movements.://A1992JW40100005-Jw401 Times Cited:45 Cited References Count:0 0921-2973ISI:A1992JW40100005KRussell, Rw Univ Calif Irvine,Dept Ecol & Evolutionary Biol,Irvine,Ca 92717English <7Russell, W. H. Jones, C.2001~The effects of timber harvesting on the structure and composition of adjacent old-growth coast redwood forest, California, USA731-741Landscape Ecology168edge effects geographical information system preserve redwood Sequoia sempervirens NATURE-RESERVES EDGE CONSERVATION VEGETATION DESIGN MODELArticleData collected across timber harvest boundaries on nine sites within the Redwood National and State Park management area in California, USA, were used to estimate the effective size of old-growth coast redwood preserves. Fourteen variables related to stand structure and composition, wildlife habitat, and physical environment were significantly correlated to distance from the timber harvest boundary using multiple regression analysis. A maximum depth of edge influence of 200 m was determined for variables exhibiting a significant correlation to the distance from the harvest edge. A spatial analysis using ArcView indicated that 53% of the old growth preserved within the study area was influenced by edge conditions, leaving 47% as effective old-growth.://000175490900005 ISI Document Delivery No.: 550EP Times Cited: 1 Cited Reference Count: 27 Cited References: BEEDY EC, 1981, CONDOR, V83, P97 BROTHERS TS, 1993, NAT AREA J, V13, P268 BURGESS RL, 1981, FOREST ISLAND DYNAMI BURKE DM, 1998, NAT AREA J, V18, P45 CHEN J, 1992, ECOL APPL, V2, P5167 DIAMOND JM, 1975, BIOL CONSERV, V7, P129 FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 GATES JE, 1978, ECOLOGY, V59, P871 HANLEY TA, 1983, J WILDLIFE MANAGE, V47, P237 HARRIS LD, 1984, FRAGMENTED FOREST IS HARRIS LD, 1988, CONSERV BIOL, V2, P330 JANZEN DH, 1983, OIKOS, V41, P402 LAURANCE WF, 1991, BIOL CONSERV, V55, P77 LAURANCE WF, 1991, BIOL CONSERV, V57, P205 MACARTHUR RH, 1967, THEORY ISLAND BIOGEO MARCOT BG, 1983, J FOREST, V81, P526 MATLACK GR, 1993, BIOL CONSERV, V66, P185 MURCIA C, 1995, TRENDS ECOL EVOL, V10, P58 OOSTING HJ, 1948, STUDY PLANT COMMUNIT PATTON DR, 1975, WILDLIFE SOC B, V3, P171 PETERKEN GF, 1996, NATURAL WOODLAND ECO PIELOU EC, 1975, ECOLOGICAL DIVERSITY RIPPLE WJ, 1991, BIOL CONSERV, V57, P73 RUSSELL WH, 2000, P C REST MAN COAST R RUSSELL WH, 2000, P WILD SCI TIM CHANG SCHONEWALDCOX CM, 1986, BIOL CONSERV, V38, P305 YOUNG A, 1994, BIOL CONSERV, V67, P63 0921-2973 Landsc. Ecol.ISI:000175490900005USGS, WERC, Golden Gate Field Stn, Sausalito, CA 94965 USA. Redwood Natl Pk, Orick, CA 95555 USA. Russell, WH, USGS, WERC, Golden Gate Field Stn, Ft Cronkhite,Bldg 1063, Sausalito, CA 94965 USA.EnglishF<73Rustigian, H. L. Santelmann, M. V. Schumaker, N. H.2003aAssessing the potential impacts of alternative landscape designs on amphibian population dynamics65-81Landscape Ecology181agriculture amphibians future scenarios Iowa landscape change population dynamics spatially explicit population model TREEFROG HYLA-CHRYSOSCELIS SPECIES RICHNESS HABITAT FRAGMENTATION COMPLEX LANDSCAPES AMBYSTOMA-TIGRINUM MOVEMENT PATTERNS UNITED-STATES LIFE-HISTORY RANA-AURORA FROGReviewJanAn individual-based, spatially explicit population model was used to predict the consequences of future land-use alternatives for populations of four amphibian species in two central Iowa (midwest USA) agricultural watersheds. The model included both breeding and upland habitat and incorporated effects of climatic variation and demographic stochasticity. Data requirements of the model include life history characteristics, dispersal behavior, habitat affinities, as well as land use and landcover in geographic information systems databases. Future scenarios were ranked according to change in breeder abundance, saturation, and distribution, compared to baseline conditions. Sensitivity of simulation results to changes in model parameters was also examined. Simulated results suggest that while all four species modeled are likely to persist under present and future scenario conditions, two may be more at risk from future landscape change. Although the study species are all widespread generalists regarded as having a low conservation priority, they depend on wetlands and ponds, increasingly endangered habitats in agricultural landscapes. Broader conservation strategies in the region would ensure that these currently common organisms do not become the endangered species of the future.://000181767500005 ISI Document Delivery No.: 659FW Times Cited: 11 Cited Reference Count: 101 Cited References: *IL DEP CONS, 1995, NISC DISC SPEC INF L ASHLEY EP, 1996, CAN FIELD NAT, V110, P403 BEEBEE TJC, 1996, ECOLOGY CONSERVATION BERRILL M, 1997, AMPHIBIANS DECLINE C, P233 BLAIR WF, 1953, COPEIA, P208 BLAIR WF, 1957, COLD SPRING HARB SYM, V22, P273 BLAUSTEIN AR, 1990, TRENDS ECOL EVOL, V5, P203 BONIN J, 1997, AMPHIBIANS DECLINE C, P141 CALEF GW, 1973, ECOLOGY, V54, P741 CASPER GS, 1996, GEOGRAPHIC DISTRIBUT CHRISTIANSEN JL, 1981, P IOWA ACAD SCI, V88, P24 CHRISTIANSEN JL, 1991, NONGAME TECHNICAL SE, V2 CHRISTIANSEN JL, 1998, J IOWA ACAD SCI, V105, P109 CHRISTIANSEN JL, 1998, P MIDW DECL AMPH C D COLLINS JT, 1993, AMPHIBIANS REPTILES DASH MC, 1980, ECOLOGY, V61, P1025 DIANA SG, 1998, STATUS CONSERVATION, P266 DOAK DF, 1994, ECOLOGY, V75, P615 DODD CK, 1993, COPEIA, P605 DODD CK, 1998, CONSERV BIOL, V12, P331 DOLE JW, 1965, ECOLOGY, V46, P236 DOUGLAS ME, 1981, COPEIA, P460 DUNNING JB, 1992, OIKOS, V65, P169 DUNNING JB, 1995, ECOL APPL, V5, P3 DUVICK DN, 1981, WATER RESOUR RES, V17, P1183 ERLICH PR, 1988, BIODIVERSITY, P21 FINDLAY CS, 1997, CONSERV BIOL, V11, P1000 FOPPEN RPB, 2000, CONSERV BIOL, V14, P1881 FREEMARK K, 1995, LANDSCAPE RETROSPECT FREEMARK K, 1995, LANDSCAPE URBAN PLAN, V31, P99 FRIEDL TWP, 1997, HERPETOLOGICA, V53, P321 GIBBS JP, 1993, WETLANDS, V13, P25 GIBBS JP, 1998, J WILDLIFE MANAGE, V62, P584 HALLEY JM, 1996, J APPL ECOL, V33, P455 HARDING JH, 1997, AMPHIBIANS REPTILES HECNAR SJ, 1997, AMPHIBIANS DECLINE C, P1 HECNAR SJ, 1997, BIOL CONSERV, V79, P123 HELGEN J, 1998, STATUS CONSERVATION, P288 HERKERT JR, 1991, ILLINOIS NATURAL HIS, V34, P393 JAMESON DL, 1955, AM MIDL NAT, V54, P342 JAMESON DL, 1956, COPEIA, P25 JAMESON DL, 1957, COPEIA, P221 JOHNALDER HB, 1990, COPEIA, P856 JORGENSEN SE, 1986, FUNDAMENTALS ECOLOGI KARL TR, 1984, J CLIM APPL METEOROL, V23, P950 KNUTSON MG, 1999, CONSERV BIOL, V13, P1437 KRAMER DC, 1973, J HERPETOL, V7, P231 KRAMER DC, 1974, J HERPETOL, V8, P245 KRAMER DC, 1978, J HERPETOL, V12, P119 LAAN R, 1990, BIOL CONSERV, V54, P251 LANNOO MJ, 1994, AM MIDL NAT, V131, P311 LEHTINEN RM, 1999, WETLANDS, V19, P1 LEJA WT, 1998, STATUS CONSERVATION, P345 MADISON DM, 1998, COPEIA 0501, P402 MANN W, 1991, GLOBAL ECOL BIOGEOGR, V1, P36 MCGARIGAL K, 1994, FRAGSTATS SPATIAL PA MCNEELY JA, 1995, GLOBAL BIODIVERSITY, P711 MINTON SA, 1972, AMPHIBIANS REPTILES NASSAUER JI, 2002, J SOIL WATER CONSERV, V57, A44 OLDFIELD B, 1994, AMPHIBIANS REPTILES OLDHAM RS, 1966, CAN J ZOOL, V44, P63 ORGAN JA, 1961, ECOL MONOGR, V31, P189 OUELLET M, 1997, J WILDLIFE DIS, V33, P95 OVASKA K, 1997, CAN J ZOOL, V75, P1081 PEARSON PG, 1955, ECOL MONOGR, V25, P233 PETRANKA JW, 1998, SALAMANDERS US CANAD POPE SE, 2000, ECOLOGY, V81, P2498 PRIOR JC, 1991, LANDFORMS IOWA PTACEK MB, 1996, HERPETOLOGICA, V52, P323 PULLIAM HR, 1992, ECOL APPL, V2, P165 RISSER PG, 1988, BIODIVERSITY, P176 RITKE ME, 1990, J HERPETOL, V24, P135 RITKE ME, 1991, J HERPETOL, V25, P123 RUSTIGIAN H, 1999, ASSESSING POTENTIAL SANTELMANN M, ALTERNATIVE FUTURES SANTELMANN M, 2001, APPL ECOLOGICAL PRIN SCHUMAKER NH, 1998, EPA600R98135 ENV RES SEALE DB, 1982, COPEIA, P627 SEMLITSCH RD, 1983, COPEIA, P608 SEMLITSCH RD, 1987, COPEIA, P61 SEMLITSCH RD, 1996, LONG TERM STUDIES VE, P217 SEVER DM, 1978, P INDIANA ACAD SCI, V87, P189 SEXTON OJ, 1986, T MISSOURI ACAD SCI, V20, P25 SINSCH U, 1990, ETHOL ECOL EVOL, V2, P65 SJOGRENGULVE P, 1998, ECOSCIENCE, V5, P31 SKELLY DK, 1995, ECOLOGY, V76, P150 SKELLY DK, 1996, COPEIA 0801, P599 SMITH DC, 1990, EVOLUTION, V44, P1529 SMITH DD, 1981, P IOWA ACAD SCI, V88, P7 SMITH PW, 1961, ILLINOIS NAT HIST SU, V28, P1 SOULE ME, 1991, SCIENCE, V253, P744 TAYLOR PD, 1993, OIKOS, V68, P571 TURNER FB, 1959, ECOLOGY, V40, P175 VOGT RC, 1981, NATURAL HIST AMPHIBI VOS CC, 1995, LANDSCAPE ECOLOGY, V11, P203 VOS CC, 1998, J APPL ECOL, V35, P44 WAKE DB, 1991, SCIENCE, V253, P860 WALDMAN B, 1992, AM ZOOL, V32, P18 WHITFORD WG, 1966, COPEIA, P515 WILBUR HM, 1987, ECOLOGY, V68, P1437 WRIGHT AH, 1949, HDB FROGS TOADS 0921-2973 Landsc. Ecol.ISI:000181767500005Oregon State Univ, Dept Geosci, Corvallis, OR 97331 USA. US EPA, Off Res & Dev, Natl Hlth & Environm Effects Res Lab, Western Ecol Div, Corvallis, OR 97333 USA. Rustigian, HL, Montana State Univ, Dept Ecol, Bozeman, MT 59717 USA. hrustigian@montana.eduEnglish|? Rutchey, Ken Godin, Jason2009Determining an appropriate minimum mapping unit in vegetation mapping for ecosystem restoration: a case study from the Everglades, USA 1351-1362Landscape Ecology2410This paper documents the analyses that were conducted with regards to investigating an appropriate Minimum Mapping Unit (MMU) to be used to capture the potential changes in vegetation patterns for a 10,924 square km restoration project being conducted in south Florida, USA. Spatial landscape and class metrics that were shown to change predictably with increasing grain size were adopted from previous studies and applied to a multi-scale analysis. Specifically, this study examines the effects of changing grain size on landscape metrics, utilizing empirical data from a real landscape encompassing 234,913 ha of south Florida's Everglades. The objective was to identify critical thresholds within landscape metrics, which can be used to provide insight in determining an appropriate MMU for vegetation mapping. Results from this study demonstrate that vegetation heterogeneity will exhibit dissimilar patterns when investigating the loss of information within landscape and class metrics, as grain size is increased. These results also support previous findings that suggest that landscape metric "scalograms" (the response curves of landscape metrics to changing grain size), are more likely to be successful for linking landscape pattern to ecological processes as both pattern and process in ecological systems often operate on multiple scales. This study also incorporates an economic cost for various grain dependant vegetation mapping scales. A final selection of the 50 x 50 m grain size for mapping vegetation was based on this study's investigation of the "scalograms", the costs, and a composite best professional judgment of seasoned scientists having extensive experience within these ecosystems.%://BIOSIS:PREV201000014110Times Cited: 0 0921-2973BIOSIS:PREV201000014110:10.1007/s10980-009-9387-z|? 2Ryan, Justin G. McAlpine, Clive A. Ludwig, John A.2010[Integrated vegetation designs for enhancing water retention and recycling in agroecosystems 1277-1288Landscape Ecology258Oct`Long term studies have shown strong links between vegetation clearing and rainfall declines and more intense droughts. Many agroecosystems are exposed to more extreme weather and further declines in rainfall under climate change unless adaptations increase the retention of water in landscapes, and its recycling back to the lower atmosphere. Vegetation systems provide vital feedbacks to mechanisms that underpin water vapour recycling between micro- and meso-scales. Various heterogeneous forms of vegetation can help generate atmospheric conditions conducive to precipitation, and therefore, increase the resilience of agroecosystems to drought and climatic extremes. The aim of this paper is to demonstrate how vegetation can be designed for agroecosystems to enhance recycling of water vapour to the atmosphere through the regulation of surface water and wind, and heat fluxes. The structure of the paper revolves around five functions of integrated vegetation designs that can help underpin the restoration of water recycling through enhanced retention of stormwater, protection from wind, moistening and cooling the landscape, production of plant litter, and contribution toward regional scale climate and catchment functioning. We also present two supplementary functions relevant to land and natural resource managers which may also be integrated using these designs.!://WOS:000281725700011YTimes Cited: 3 10th International Congress of Ecology Aug 16-21, 2009 Brisbane, AUSTRALIA 0921-2973WOS:00028172570001110.1007/s10980-010-9509-7? WE.J.Jr. Rykiel Robert N. Coulson Peter J.H. Sharpe Timothy F.H. Allen Richard O. Flamm1988KDisturbance propagation by bark beetles as an episodic landscape phenomenon129-139Landscape Ecology13Pdisturbance, landscape, episode, lightning, bark beetle, hierarchy, scale, modelNLandscapes are the resultant of ecological processes and events operating on many different space-time scales. Large scale disturbance is recognized as a major influence on landscape patterns, but the impact of small scale events is often overlooked. We develop an hierarchical framework to relate lightning and bark beetle population dynamics to the southern pine forest landscape using the concepts of: disturbance propagation and amplification. The low level lightning disturbance can be propagated to the landscape level when weather and forest stand structure facilitate bark beetle epidemics. We identify epidemics as biotically-driven episodes that alter landscape structure. The concept of the landscape as the spatial dimension of these episodes is represented in a conceptual model linking insect-host and landscape mosaic interactions.<7B,Ryszkowski, L. Bartoszewicz, A. Kedziora, A.1999ZManagement of matter fluxes by biogeochemical barriers at the agricultural landscape level479-492Landscape Ecology145oagricultural landscape evapotranspiration ground water flux meadows non-point pollution shelterbelts PHOSPHORUSArticleOctLong-term studies of the influence of biogeochemical barriers (shelterbelts and stretches of meadows) on water cycling and control of ground water pollution in an agricultural landscape have shown that more solar energy is used for evapotranspiration in shelterbelts than in cultivated fields or meadows. Therefore, annual water runoff from cultivated fields is about 170% higher than from coniferous forest, 60% higher than deciduous forest and 16% higher than meadows. The differences in evapotranspiration rates between shelterbelts and meadows increases when additional energy input for evapotranspiration is provided by transport of heat from cultivated fields to these habitats by advection. The average water percolation time through the unsaturated zone of soils varies by 100%. A shelterbelt, having a mixed species composition, more effectively screens the passage of chemical compounds dissolved in ground water than shelterbelts composed of one tree species. Peat soils have a very high cation exchange capacity which increases the efficiency of riparian meadows for the control of ground water pollution. Natural landscape features which assist in controlling matter cycles are of great importance for modifying chemical outputs from agricultural watersheds.://000082510000006 ISI Document Delivery No.: 234XQ Times Cited: 3 Cited Reference Count: 48 Cited References: *OECD, 1986, WAT POLL FERT PEST BARTOSZEWICZ A, 1979, ROCZNIKI AKAD ROLNIC, V91, P1 BARTOSZEWICZ A, 1990, OBIEG WODY BARIERY B, P127 BARTOSZEWICZ A, 1994, ROCZNIKI AKAD ROLNIC, V250, P5 BOROWIEC S, 1988, ROLNICTWO, V45, P27 BURT TP, 1993, NITRATE PROCESSES PA, P341 COOPER AB, 1990, HYDROBIOLOGIA, V202, P12 COOPER JR, 1987, SOIL SCI SOC AM J, V51, P416 COSSER PR, 1989, AUST J MAR FRESH RES, V40, P613 DILLAHA TA, 1989, T ASAE, V32, P513 FOLKENMARK M, 1991, LAND USE CHANGES EUR, P127 FOTYMA M, 1987, CHEMICZNE PODSTAWY Z HILLBRICHTILKOW.A, 1995, PHOSPHORUS GLOBAL EN, P201 JACOBS TC, 1985, J ENVIRON QUAL, V14, P472 KAUPPI L, 1990, ECOLOGICAL SUSTAINAB, P43 KEDZIORA A, 1989, ECOL INT, V17, P1 KEDZIORA A, 1990, OBIEG WODY BARIERY B, P47 KEDZIORA A, 1995, PHOSPHORUS GLOBAL EN, P229 KNAUER N, 1989, Z KULTURTECHNIK LAND, V30, P365 KNOWLES R, 1981, ECOL B STOCKHOLM, V33, P315 KRYGOWSKI B, 1961, PHYSICAL GEOGRAPHY 1 LAWFORD RG, 1993, EARTH SYSTEM RESPONS, P73 LVOVICH MJ, 1993, EARTH TRANSFORMED HU, P235 MARCINEK J, 1990, OBIEG WODY BARIERY B, P69 MARCINEK J, 1990, PRACE KOMISJI NAUK R, V69, P71 MARGOWSKI Z, 1976, POL ECOL STUD, V2, P5 MISZTAL M, 1990, POL J SOIL SCI, V23, P37 MUSCUTT AD, 1993, AGR ECOSYST ENVIRON, V45, P59 OMERNIK JM, 1981, J SOIL WATER CONSERV, V36, P227 PASLAWSKI Z, 1990, OBIEG WODY BARIERY B, P59 PAULUKEVICIUS G, 1981, ECOLOGICAL ROLE FORE PETERJOHN WT, 1984, ECOLOGY, V65, P1466 PHILIPS JD, 1989, J HYDROL, V10, P221 PINAY G, 1988, REGUL RIVER, V2, P507 POKOJSKA U, 1988, ROCZNIKI GLEBOZNAWCZ, V39, P51 PRUSINKEIWICZ Z, 1990, EFFECT SHELTERBELT N, P108 RYSZKOWSKI L, 1984, EKOLOGICZNE MEDYCZNE, P61 RYSZKOWSKI L, 1987, LANDSCAPE ECOL, V1, P85 RYSZKOWSKI L, 1989, AGR ECOSYST ENVIRON, V27, P107 RYSZKOWSKI L, 1989, ECOLOGY ARABLE LAND, P241 RYSZKOWSKI L, 1989, PHOSPHORUS CYCLES TE, P178 RYSZKOWSKI L, 1992, POSTEPY NAUK ROLNICZ, V4, P3 RYSZKOWSKI L, 1993, HYDROBIOLOGIA, V251, P239 SCHROEDER G, 1968, LADWIRTSCHAFTLICHER STOUTJESDIJK PH, 1992, MICROCLIMATE VEGETAT TRACZYK T, 1985, POL ECOL STUD, P455 VANEK V, 1991, WATER RES, V25, P409 YOUNG RA, 1980, J ENVIRON QUAL, V9, P483 0921-2973 Landsc. Ecol.ISI:000082510000006Polish Acad Sci, Res Ctr Agr & Forest Environm, Poznan, Poland. Ryszkowski, L, Polish Acad Sci, Res Ctr Agr & Forest Environm, Poznan, Poland.English? BL. Ryszkowski A. Kqdziora1987LImpact of agricultural landscape structure on energy flow and water cycling185-94Landscape Ecology12Jenergy flow, water cycling, evapotranspiration, primary production, albedoIn long term studies the following climatological characteristics were measured or calculated: air and soil temperature, sunshine, wind speed, vapor pressure, saturation deficit, precipitation, humidity, incoming and reflected solar energy, energy emitted by active surfaces and primary production. Taking into account the relationships between climatological characteristics, the growth stages of vegetation, and relations between heat balance components, the fluxes of energy used for evapotranspiration, air, and soil heating were estimated in various ecosystems composing the agricultural landscape. The energy contained in biomass production of various crops was estimated also. Aggregate estimates of energy flow connected with evapotranspiration, and soil and air heating were calculated for eight model landscapes which differed by the plant cover structure. A higher variability of energy fluxes was observed for individual ecosystems than for agricultural landscapes. It was shown that the structure of the plant cover has an important bearing on energy flow and water cycling both by direct and indirect influences. Shelterbelts are especially important in their influence on energy flow and water cycling. I<7 Rytwinski, T. Fahrig, L.20078Effect of road density on abundance of white-footed mice 1501-1512Landscape Ecology2210road density relative abundance small mammal peromyscus leucopus rural and urban landscapes population subdivision habitat fragmentation local extinction recolonization movement predator release tracking tubes SMALL-MAMMAL POPULATIONS LONG-DISTANCE MOVEMENTS COARSE WOODY DEBRIS PEROMYSCUS-LEUCOPUS MICROTUS-OCHROGASTER DEERMICE PEROMYSCUS SIGMODON-HISPIDUS HABITAT ISOLATION UNITED-STATES FORESTArticleDecwWhile several studies have demonstrated that roads can act as barriers to small mammal movement, the relationship between road density and small mammal abundance has not yet been investigated. In southeastern Ontario, Peromyscus leucopus (white-footed mice) suffer high over-winter mortality rates, resulting in small springtime populations and frequent local extinctions. Peromyscus leucopus movement is known to be inhibited by roads, which should result in lower rates of immigration into and recolonization of habitats in landscapes with high road density. We tested two predictions: (1) Forest sites situated in landscapes with high road densities have a higher chance of P. leucopus being absent during the early spring than forest sites situated in landscapes with low road densities and (2) P. leucopus populations during the summer are smaller in forest sites situated in landscapes with high road densities than in landscapes with low road densities. We sampled P. leucopus in focal patches within nineteen landscapes (7 rural, low-road-density landscapes; 7 rural, high-road-density landscapes; 5 urban landscapes). There was no significant relationship between road density and the presence/absence of P. leucopus during the early spring. We found a significant positive effect of road density on P. leucopus relative abundance during the summer, even when we excluded the urban landscapes and based the analysis on only the 14 rural landscapes. Our results suggest that any negative effect of roads on P. leucopus populations, created by their inhibition to moving across roads, is far outweighed by some positive effect of roads on P. leucopus abundance. We suggest that the two most likely explanations are that roads are positively correlated with an important as-yet-undetermined component of habitat quality, or that roads positively affect P. leucopus by negatively affecting their predators.://000250632100009iISI Document Delivery No.: 227BL Times Cited: 0 Cited Reference Count: 67 Rytwinski, Trina Fahrig, Lenore 0921-2973 Landsc. Ecol.ISI:000250632100009Carleton Univ, GLEL, Ottawa Carleton Inst Biol, Ottawa, ON K1S 5B6, Canada. Rytwinski, T, Carleton Univ, GLEL, Ottawa Carleton Inst Biol, 1125 Colonel Dr, Ottawa, ON K1S 5B6, Canada. trytwins@connect.carleton.caEnglish<7Said, S. Servanty, S.2005GThe influence of landscape structure on female roe deer home-range size 1003-1012Landscape Ecology208Capreolus capreolus; edge density; generalized linear mixed model; landscape structure WHITE-TAILED DEER; BODY-SIZE; MULE DEER; ECOLOGICAL IMPACTS; POPULATION-DENSITY; INCREASING NUMBERS; ANIMAL MOVEMENTS; HABITAT QUALITY; SCALE; MASSArticleDecAnimal distribution and abundance are greatly affected by the availability of their food resources, which also depends on landscape structure. Lothar hurricane in 1999 had profoundly modified the structure of the forests in France, affecting the habitat quality of ungulates. We tested whether the variations in home-range size of 23 female roe deer were influenced by the fragmentation of the landscape caused by Lothar in the Chize forest, namely by the increase in heterogeneity associated with the localized massive tree felling. Home-range size was studied in the summers of 2001 and 2002 and we found that variation in home-range size was mainly explained by only one landscape variable: edge density. Home-range size decreased as edge density increased, which is consistent with the fact that edges are good browsing habitats for roe deer. The result of this study suggests that, after 2 years, the hurricane had improved the quality of the home ranges by creating more forest heterogeneity and increasing the contacts between the different vegetation patches within the home range. These results highlight the fact that spatial heterogeneity is likely to be a key factor influencing the distribution and local population density.://000233036400008 Y ISI Document Delivery No.: 980RR Times Cited: 2 Cited Reference Count: 62 Cited References: *SPSS INC, 1999, SPSS BAS 10 0 US GUI ALVERSON WS, 1988, CONSERV BIOL, V2, P348 ANDERSEN R, 1998, EUROPEAN ROE DEER BI AUGUSTINE DJ, 1998, CONSERV BIOL, V12, P995 BERTRAND MR, 1996, J WILDLIFE MANAGE, V60, P899 BOUCHER S, 2004, ECOSCIENCE, V11, P286 BOWERS MA, 1990, CAN J ZOOL, V68, P2016 CATTELL RB, 1966, MULTIVARIATE BEHAVIO, V1, P245 CEDERLUND G, 1994, J MAMMAL, V75, P1005 COTE SD, 2004, ANNU REV ECOL EVOL S, V35, P113 DANELL K, 1991, ECOLOGY, V72, P1624 DEMMENT MW, 1985, AM NAT, V125, P641 ELKIE PC, 1999, PATCH ANAL USERS MAN FORMAN RTT, 1976, OECOLOGIA BERL, V26, P1 FRETWELL SC, 1970, ACTA BIOTHEOR, V19, P16 FRITZ H, 2003, LANDSCAPE ECOL, V18, P293 FULLER RJ, 2001, FORESTRY, V74, P193 FULLER RJ, 2001, FORESTRY, V74, P289 GAILLARD JM, 1993, J ANIM ECOL, V62, P778 GILL RMA, 2001, FORESTRY, V74, P209 GITTLEMAN JL, 1982, BEHAV ECOL SOCIOBIOL, V10, P57 HANSTEEN TL, 1997, J WILDLIFE MANAGE, V61, P280 HARESTAD AS, 1979, ECOLOGY, V60, P389 HARRIS S, 1990, MAMMAL REV, V20, P97 HEWISON AJM, 1998, EUROPEAN ROE DEER BI, P189 HOOGE PN, 1997, ANIMAL MOVEMENT EXTE HUNTER ML, 1990, WILDLIFE FORESTS FOR HURLBERT SH, 1984, ECOL MONOGR, V54, P187 JOHNSON DH, 1980, ECOLOGY, V61, P65 JOLLIFFE IT, 1972, APPL STAT, V21, P160 JOLLIFFE IT, 1973, APPL STATIST, V22, P21 KIE JG, 2002, ECOLOGY, V83, P530 KJELLANDER P, 2004, OECOLOGIA, V139, P478 LITTLE RC, 1991, SAS SYSTEM LINEAR MO MANLY BFJ, 2002, RESOURCE SELECTION A MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MCNAB BK, 1963, AM NAT, V97, P133 MYSTERUD A, 2001, OECOLOGIA, V127, P30 NICHOLSON MC, 1997, J MAMMAL, V78, P483 PETTORELLI N, 2001, OECOLOGIA, V128, P400 PETTORELLI N, 2002, P ROY SOC LOND B BIO, V269, P747 PETTORELLI N, 2003, OECOLOGIA, V137, P363 REIMOSER F, 2003, J NAT CONSERV, V10, P243 RELYEA RA, 2000, J WILDLIFE MANAGE, V64, P146 SAID S, IN PRESS J ZOOLOGY SAID S, 2000, ACTA OECOL, V21, P193 SAID S, 2001, PLANT ECOL, V162, P67 SANJOSE C, 1998, ETHOLOGY, V104, P721 SEAMAN DE, 1996, ECOLOGY, V77, P2075 SILVERMAN BW, 1986, DENSITY ESTIMATION S SINCLAIR ARE, 1997, SCI OVERABUNDANCE DE, P380 SWIHART RK, 1985, ECOLOGY, V66, P1176 SWIHART RK, 1985, J WILDLIFE MANAGE, V49, P1019 SWIHART RK, 1986, ECOLOGY, V67, P255 SWIHART RK, 1988, ECOLOGY, V69, P393 THIOULOUSE J, 1997, ADE 4 MULTIVARIATE A TUFTO J, 1996, J ANIM ECOL, V65, P715 WAHLSTROM LK, 1995, OECOLOGIA, V103, P302 WALLER DM, 1997, WILDLIFE SOC B, V25, P217 WHITE GC, 1990, ANAL WILDLIFE RADIO WIDMER O, 2004, FOREST ECOL MANAG, V195, P237 WORTON BJ, 1989, ECOLOGY, V70, P164 0921-2973 Landsc. Ecol.ISI:000233036400008UCNRS, CEBC, UPR 1934, F-79360 Beauvoir Sur Niort, France. Ctr Natl Etud & Rech Appl Cervides Sangliers, Off Natl Chasse & Faune Sauvage, F-75017 Paris, France. Univ Lyon 1, Unite Mixte Rech 5558, F-69622 Villeurbanne, France. Said, S, CNRS, CEBC, UPR 1934, BP 14 Villiers en Bois, F-79360 Beauvoir Sur Niort, France. sonia.said@oncfs.gouv.frEnglish|?C %Saint-Germain, Michel Drapeau, Pierre2011Response of saprophagous wood-boring beetles (Coleoptera: Cerambycidae) to severe habitat loss due to logging in an aspen-dominated boreal landscape573-586Landscape Ecology264AprXLogging significantly reduces the proportion of late-seral stands in managed boreal landscapes. Availability of habitat elements typical of these stand types, such as standing dead wood, decreases, and dependant species may have their abundance reduced or become locally extirpated, potentially affecting the ecosystem processes/services in which they take part. We evaluated the impact of habitat loss on saprophagous wood-boring beetles (Coleoptera: Cerambycidae) in an aspen-dominated landscape intensively logged for the past 30 years. Sixty natural snags of middle decay class were chosen along a gradient of habitat loss and disturbance age, cut down and dissected for beetle larvae. We then assessed relationships between species occurrence and percentage of residual cover and age of disturbance at spatial scales ranging from 40 to 2000 m radii. The most common species, Anthophylax attenuatus, showed no response, being abundant regardless of the intensity of habitat loss. The second most common species, Bellamira scalaris, showed a negative response, especially in sites which had been fragmented for a longer time. A third species, Trachysida mutabilis, showed an inverse trend, having a higher probability of presence where habitat loss was more severe. Our study shows that some saprophagous wood-borers do react negatively to habitat loss, but that within a relatively homogenous group the response can vary significantly between species. Saprophagous wood-borers should be considered potentially sensitive to habitat loss, and their response to fragmentation remains to be evaluated on a longer time frame.!://WOS:000288807300010Times Cited: 0 0921-2973WOS:00028880730001010.1007/s10980-011-9587-1t|? -Salek, Miroslav Svobodova, Jana Zasadil, Petr2010mEdge effect of low-traffic forest roads on bird communities in secondary production forests in central Europe 1113-1124Landscape Ecology257AugWorldwide forests fragmentation has lead to a massive increase of habitat edges, creating both negative and positive impacts on birds. While busy highways dissecting forested areas create edges which are known to reduce bird densities due to the disturbing effect of noise, the impacts of logging forest roads with low traffic volumes have rarely been studied. In this study, we compared species richness and similarity of canopy, cavity and shrub guilds of birds along low-traffic forest roads, in forest interior, and at forest edges in secondary forests in central Europe, where the forests have passed through extensive changes toward uniformly compact growths dominated by production conifers. Although we found tree diversity as positively affecting bird richness across all habitats, the bird richness along forest roads was higher than in forest interior but lower than along forest edges. The shrub guild of birds along forest roads resembled this guild along forest edges while canopy and cavity guilds at the roads were more similar to these guilds in forest interior. Forest interior had the highest probability for some guild to be absent. We conclude that low-traffic roads lead to increase of habitat heterogeneity in structurally poor forests and attract birds due to additional habitat attributes-including better light conditions-that are scarce in forest interior. Therefore, broader support for higher structural diversification of uniform plantations in central European production forests would benefit bird communities inhabiting these areas.!://WOS:000279592100010Times Cited: 1 0921-2973WOS:00027959210001010.1007/s10980-010-9487-9<7z6Sanderson, E. W. Zhang, M. Ustin, S. L. Rejmankova, E.1998IGeostatistical scaling of canopy water content in a California salt marsh79-92Landscape Ecology132geostatistics scaling grain extent canopy water content salt marsh remote sensing Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) SPATIAL AUTOCORRELATION LANDSCAPE PATTERN RESOLUTION ECOLOGY HETEROGENEITY EXTRACTION AVIRIS FOREST ERROR COVERArticleAprqRemote sensing data are typically collected at a scale which is larger in both grain and extent than traditional ecological measurements. To compare with remotely sensed data on a one-to-one basis, field measurements frequently must be rescaled to match the grain of image data. Once a one-to-one correspondence is established, it may be possible to extrapolate site based relationships over a wider extent. This paper presents a methodology for rescaling the grain of ecological field data to match the grain of remotely sensed data and gives an example of the method in verification of remote sensing estimates of canopy water content in a tidal salt marsh. We measured canopy water content at 169 points on a semi-regular grid in the Petaluma Marsh, CA. A variogram describing the spatial correlation structure of the canopy water content was calculated and modeled. Ordinary kriging estimates of the canopy water content were calculated over blocks corresponding to image pixels acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). A water content index was determined from the reflectance data by calculating the area of a water absorption feature at 970 nm. A regression developed between the blocks and the pixels at the site was extrapolated over the image to obtain an estimate of canopy water content for the entire marsh. The patterns of canopy water content at the site and landscape levels suggest that different processes are important for determining patterns of canopy water content at different spatial extents. The errors involved in the rescaling procedures and the remote sensing interpretation are discussed.://000077256800002 ISI Document Delivery No.: 143LH Times Cited: 10 Cited Reference Count: 57 Cited References: ALLEN TFH, 1993, EVOL TREND PLANT, V7, P3 ATKINSON PM, 1992, REMOTE SENS ENVIRON, V41, P45 ATKINSON PM, 1994, REMOTE SENS ENVIRON, V48, P1 ATKINSON PM, 1996, INT J REMOTE SENS, V17, P3735 BARKHADLE AMI, 1994, LANDSCAPE ECOL, V9, P79 CAMERON GN, 1972, ECOLOGY, V53, P58 CLARK RN, 1984, J GEOPHYS RES, V89, P6329 CURRAN PJ, 1988, REMOTE SENS ENVIRON, V24, P493 ENGLUND E, 1988, EPA600488033 ENV MON FREW JE, 1990, THESIS U CALIFORNIA FUHLENDORF SD, 1996, LANDSCAPE ECOL, V11, P107 GAO BC, 1993, REMOTE SENS ENVIRON, V44, P165 GARDNER RH, 1982, ECOLOGY, V63, P1771 HAINESYOUNG RH, 1992, LANDSCAPE ECOL, V7, P253 HICKMAN JC, 1993, JEPSON MANUAL HIGHER HINDE HP, 1954, ECOL MONOGR, V24, P209 HYPPANEN H, 1996, INT J REMOTE SENS, V17, P3441 ISSAKS EH, 1989, INTRO APPL GEOSTATIS IVERSON LR, 1994, LANDSCAPE ECOL, V9, P158 JACKSON RB, 1993, ECOLOGY, V74, P612 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 JOSSELYN M, 1983, ECOLOGY SAN FRANCISC KNIGHT CL, 1994, LANDSCAPE ECOL, V9, P117 KRUSE FA, 1993, REMOTE SENS ENVIRON, V44, P145 LEGENDRE P, 1989, VEGETATIO, V80, P107 LEVIN SA, 1992, ECOLOGY, V73, P1943 LILLESAND TM, 1987, REMOTE SENSING IMAGE MAHALL BE, 1976, J ECOL, V64, P421 MANKIN JB, 1975, NEW DIRECTIONS ANA 1, V5 MOODY A, 1995, LANDSCAPE ECOL, V10, P363 MUSICK HB, 1991, QUANTITATIVE METHODS ONEILL RV, 1986, HIERARCHICAL CONCEPT ONEILL RV, 1996, LANDSCAPE ECOL, V11, P169 PINZON JE, 1995, P 5 ANN JPL AIRB EAR PRICE JC, 1994, REMOTE SENS ENVIRON, V49, P181 QI Y, 1996, LANDSCAPE ECOL, V11, P39 QUATTROCHI DA, 1991, QUANTITATIVE METHODS RAFFY M, 1994, INT J REMOTE SENS, V15, P2353 RAFFY M, 1994, INT J REMOTE SENS, V15, P2359 RASTETTER EB, 1992, ECOL APPL, V2, P55 ROSSI RE, 1992, ECOL MONOGR, V62, P277 ROSSI RE, 1994, REMOTE SENS ENVIRON, V49, P32 SCHLESINGER WH, 1996, ECOLOGY, V77, P364 TUCKER CJ, 1979, REMOTE SENS ENVIRON, V8, P127 TURNER SJ, 1991, QUANTITATIVE METHODS USTIN SL, 1993, SCALING PHYSL PROCES, P339 USTIN SLR, 1981, BOT GAZ, V143, P368 VANDERMEER F, 1994, INT J REMOTE SENS, V15, P2193 VANE G, 1993, REMOTE SENS ENVIRON, V44, P127 VERSTRAETE MM, 1996, REMOTE SENS ENVIRON, V58, P201 VITOUSEK PM, 1991, PHYSL PROCESSES LEAF WARING RH, 1991, SCALING PHYSL PROCES WEINS JA, 1989, FUNCT ECOL, V3, P385 WESSMAN CA, 1992, ANNU REV ECOL SYST, V23, P175 WOODCOCK CE, 1987, REMOTE SENS ENVIRON, V21, P311 YATES SR, 1989, GEOSTATISTICS WASTE ZHANG M, 1997, ECOL APPL, V7, P1039 0921-2973 Landsc. Ecol.ISI:000077256800002Univ Calif Davis, Dept Land Air & Water Resources, Davis, CA 95616 USA. Univ Calif Davis, Div Environm Studies, Davis, CA 95616 USA. Univ Calif Davis, Div Environm Studies, Davis, CA 95616 USA. Sanderson, EW, Univ Calif Davis, Dept Land Air & Water Resources, Davis, CA 95616 USA.English<7Sandin, L. Johnson, R. K.2004jLocal, landscape and regional factors structuring benthic macroinvertebrate assemblages in Swedish streams501-514Landscape Ecology195>benthic macroinvertebrates; landscape scale; multivariate analysis; Partial Canonical Correspondence Analysis; regional scale; running waters; spatial scale MULTIPLE SPATIAL SCALES; ECOLOGICAL VARIATION; COMMUNITY STRUCTURE; HABITAT STRUCTURE; BIOTIC INTEGRITY; SPECIES TRAITS; LAND-USE; CATCHMENT; PATTERNS; FRAMEWORKArticle+A total of 694 streams were sampled for benthic macroinvertebrates in the autumn of 1995 as part of the Swedish national stream survey. After removal of sites considered as impacted, data from 428 streams as well as a large number of environmental variables were used to determine the relative importance of local, landscape, and large scale factors in explaining the variability in species composition of benthic stream macroinvertebrates. The environmental variables were divided into seven explanatory variable groups: local physical, local chemical, catchment land use/cover, catchment bedrock geology, Quaternary geology in catchment, regional factors (such as ecoregion) and spatial position. Partial Canonical Correspondence Analysis was used to partition the total explained variance in the species data into these variable groups. The pure (or unique) effects of the seven variable groups accounted for 69.1%, and combinations of variable groups (interaction terms) the remaining 30.9% of the total explained variability. Local scale variables such as in-stream substratum, vegetation in and near the stream (riparian zone), and some chemical variables were most strongly associated with the among-site variability. Local physical (24.4%) and local chemical (20.4%) variables explained the largest part of the among-site variability of community assemblages. These results are of importance when planning conservation and management measurements, implementing large-scale biomonitoring programs, and predicting how human alterations will affect running water ecosystems.://000222941500004 i ISI Document Delivery No.: 841OY Times Cited: 10 Cited Reference Count: 49 Cited References: *EUR COMM STAND, 1994, 27828 EN EUR COMM ST *NORD COUNC MIN, 1984, NAT REG NORD ALLAN JD, 1997, FRESHWATER BIOL, V37, P107 ALLAN JD, 1997, FRESHWATER BIOL, V37, P149 ALLEN THF, 1982, HIERARCHY PERSPECTIV BORCARD D, 1992, ECOLOGY, V73, P1045 BORCARD D, 1994, ENVIRON ECOL STAT, V1, P37 CARTER JL, 1996, FRESHWATER BIOL, V35, P109 CORKUM LD, 1989, FRESHWATER BIOL, V21, P191 FISHER SG, 1994, AQUATIC ECOLOGY SCAL, P575 FREDEN C, 1994, GEOLOGY FRISSELL CA, 1986, ENVIRON MANAGE, V10, P199 HAWKINS CP, 2000, J N AM BENTHOL SOC, V19, P541 HEINO J, 2002, J N AM BENTHOL SOC, V21, P397 HENRIKSEN A, 1992, AMBIO, V21, P356 HILL MO, 1980, VEGETATIO, V42, P47 HYNES HBN, 1975, VERH INT VEREIN LIMN, V19, P1 JOHNSON LB, 1997, FRESHWATER BIOL, V37, P193 JOHNSON RK, 2002, FRESHWATER BIOL, V47, P1840 JONGMAN RHG, 1995, DATA ANAL COMMUNITY LAMMERT M, 1999, ENVIRON MANAGE, V23, P257 LEVIN SA, 1992, ECOLOGY, V73, P1943 LIU QH, 1995, WATER AIR SOIL POLL, V85, P1587 LIU QH, 1997, ENVIRONMETRICS, V8, P75 MALMQVIST B, 1994, ECOGRAPHY, V17, P9 MALMQVIST B, 2000, ARCH HYDROBIOL, V150, P29 MEOT A, 1998, ENVIRON ECOL STAT, V5, P1 MINSHALL GW, 1984, ECOLOGY AQUATIC INSE, P358 MINSHALL GW, 1988, J N AM BENTHOL SOC, V7, P263 OKLAND RH, 1994, J VEG SCI, V5, P117 ORMEROD SJ, 1993, J APPL ECOL, V30, P13 POFF NL, 1997, J N AM BENTHOL SOC, V16, P391 RICHARDS C, 1993, FRESHWATER BIOL, V29, P285 RICHARDS C, 1996, CAN J FISH AQUAT S1, V53, P295 RICHARDS C, 1997, FRESHWATER BIOL, V37, P219 ROTH NE, 1996, LANDSCAPE ECOL, V11, P141 SANDIN L, 2000, J N AM BENTHOL SOC, V19, P462 SANDIN L, 2003, ECOGRAPHY, V26, P269 STATZNER B, 1986, FRESHWATER BIOL, V16, P127 STATZNER B, 1988, J N AM BENTHOL SOC, V7, P307 TERBRAAK CJF, 1988, ADV ECOL RES, V18, P272 TERBRAAK CJF, 1988, CLASSIFICATION RELAT, P551 TERBRAAK CJF, 1990, UPDATE NOTES CANOCO TERBRAAK CJF, 1998, CANOCO REFERENCE MAN TONN WM, 1990, T AM FISH SOC, V119, P337 TOWNSEND CR, 1997, FRESHWATER BIOL, V37, P177 WIBERGLARSEN P, 2000, FRESHWATER BIOL, V43, P633 WILANDER A, 1998, 4813 SNV STAT NAT WILEY MJ, 1997, FRESHWATER BIOL, V37, P133 0921-2973 Landsc. Ecol.ISI:000222941500004Swedish Univ Agr Sci, Dept Environm Assessment, S-75007 Uppsala, Sweden. Sandin, L, Swedish Univ Agr Sci, Dept Environm Assessment, POB 7050, S-75007 Uppsala, Sweden.English <7 *Sangermano, F. Toledano, J. Eastman, J. R.2012dLand cover change in the Bolivian Amazon and its implications for REDD plus and endemic biodiversity571-584Landscape Ecology274deforestation carbon emissions biodiversity conservation land cover change climate-change forest degradation deforestation conservation emissions models roads basinAprTropical deforestation is a major contributor to green house gas emissions in developing countries. Incentive mechanisms, such as reducing emissions from deforestation and forest degradation (REDD), are currently being considered as a possible emissions reduction and offset solution. Although REDD has expanded its scope to include co-benefits such as sustainable management of forests and biodiversity conservation (known as REDD+), current carbon-base methodologies do not specifically target projects for the parallel protection of these co-benefits. This study demonstrates the incorporation of both carbon and biodiversity benefits within REDD+ in the Bolivian Amazon, through the analysis of land cover change and future change scenario modeling to the year 2050. Current protected areas within the Bolivian Amazon were evaluated for REDD+ project potential by identifying concordant patterns of carbon content, species biodiversity and deforestation vulnerability. Biodiversity-based versus carbon-based protection schemes were evaluated and protected areas were prioritized using irreplaceability-vulnerability plots. Deforestation projection scenarios to the year 2050 varied depending on the historical period analyzed, producing low, intermediate and high deforestation scenarios. All scenarios showed increasing deforestation pressure in the northern region of Bolivia along with high levels of biodiversity loss. Expected reductions in the carbon pool ranged from 8 to 48%, for the low and high demand scenarios respectively. Some protected areas presented large numbers of endemic species, high concentrations of carbon and high deforestation vulnerability, demonstrating the potential for win-win REDD+ projects in Bolivia.://000302346900008-919RS Times Cited:2 Cited References Count:60 0921-2973Landscape EcolISI:000302346900008Sangermano, F Clark Univ, Clark Labs, 950 Main St, Worcester, MA 01610 USA Clark Univ, Clark Labs, 950 Main St, Worcester, MA 01610 USA Clark Univ, Clark Labs, Worcester, MA 01610 USADOI 10.1007/s10980-012-9710-yEnglishJ?@E. Sanjaume J. Pardo1991kThe possible influence of sea level rise on the precarious dunes of Devesa del Saler Beach, Valencia, Spain57-64Landscape Ecology61/2jSea level rise, urbanisation, dune restoration, sediment supply, wash over, Valencia lagoon, mediterraneanThe Saler Beach dune field in Spain was partially destroyed between 1970 and 1973 due to building development. Presently great efforts to restore some dunes has begun. The possible consequence of a sea level rise for the Saler dune field is discussed according to different scenarios.<7Santelmann, M. V. White, D. Freemark, K. Nassauer, J. I. Eilers, J. M. Vache, K. B. Danielson, B. J. Corry, R. C. Clark, M. E. Polasky, S. Cruse, R. M. Sifneos, J. Rustigian, H. Coiner, C. Wu, J. Debinski, D.2004:Assessing alternative futures for agriculture in Iowa, USA357-374Landscape Ecology194agriculture; biodiversity; socio-economics; scenarios; water quality WATER-QUALITY; LANDSCAPE DESIGNS; MISSISSIPPI RIVER; UNITED-STATES; BIODIVERSITY; CONSERVATION; CONSEQUENCES; MANAGEMENT; SCENARIOS; WILDLIFEArticleThe contributions of current agricultural practices to environmental degradation and the social problems facing agricultural regions are well known. However, landscape-scale alternatives to current trends have not been fully explored nor their potential impacts quantified. To address this research need, our interdisciplinary team designed three alternative future scenarios for two watersheds in Iowa, USA, and used spatially-explicit models to evaluate the potential consequences of changes in farmland management. This paper summarizes and integrates the results of this interdisciplinary research project into an assessment of the designed alternatives intended to improve our understanding of landscape ecology in agricultural ecosystems and to inform agricultural policy. Scenario futures were digitized into a Geographic Information System (GIS), visualized with maps and simulated images, and evaluated for multiple endpoints to assess impacts of land use change on water quality, social and economic goals, and native flora and fauna. The Biodiversity scenario, targeting restoration of indigenous biodiversity, ranked higher than the current landscape for all endpoints (biodiversity, water quality, farmer preference, and profitability). The Biodiversity scenario ranked higher than the Production scenario (which focused on profitable agricultural production) in all endpoints but profitability, for which the two scenarios scored similarly, and also ranked higher than the Water Quality scenario in all endpoints except water quality. The Water Quality scenario, which targeted improvement in water quality, ranked highest of all landscapes in potential water quality and higher than the current landscape and the Production scenario in all but profitability. Our results indicate that innovative agricultural practices targeting environmental improvements may be acceptable to farmers and could substantially reduce the environmental impacts of agriculture in this region.://000221879000002 ISI Document Delivery No.: 827DM Times Cited: 7 Cited Reference Count: 54 Cited References: *US BUR CENS, 2001, STAT ABSTR US 2001 *US GAO, 1999, GAORCED99205 *US OTA, 1995, OTAENV640 C US *USDA, 1996, GEOGR HOP *USDA, 1997, PLANTS DAT VERS 3 5 *USDA, 1999, USDA STAT B, V955 AHERN J, 1999, LANDSCAPE ECOLOGICAL, P175 ALEXANDER RB, 1996, P GULF MEX HYP MAN C ARCURY TA, 1990, HUM ORGAN, V49, P300 ARNOLD JG, 1995, J HYDRAUL ENG-ASCE, V121, P171 BAKER JP, 2004, IN PRESS ECOLOGICAL BECHER KD, 2000, J AM WATER RESOUR AS, V36, P161 BENDER DJ, 1998, ECOLOGY, V79, P517 BLAKE JG, 1987, ECOLOGY, V68, P1724 COINER C, 2001, ECOL ECON, V38, P119 COLLINGE SK, 1996, LANDSCAPE URBAN PLAN, V36, P59 DUNNING JB, 1995, ECOL APPL, V5, P3 DUPRE C, 2002, J ECOL, V90, P796 EILERS LJ, 1994, VASCULAR PLANTS IOWA FARRAR D, 1981, P IOWA ACAD SCI, V88, P1 FREEMARK K, 1995, LANDSCAPE RETROSPECT FREEMARK K, 1995, LANDSCAPE URBAN PLAN, V31, P99 HATFIELD JL, 1999, J ENVIRON QUAL, V28, P11 KLOPATEK JM, 1979, ENVIRON CONSERV, V6, P191 KREBS JR, 1999, NATURE, V400, P611 LAMY F, 2002, J AM WATER RESOUR AS, V38, P517 LEVINS R, 1966, AM SCI, V54, P421 LIKENS GE, 1977, BIOGEOCHEMISTRY FORE MATSON PA, 1997, SCIENCE, V277, P504 MITSCH WJ, 2001, BIOSCIENCE, V51, P373 NASSAUER JI, 1999, RURAL WATERSHEDS POL NASSAUER JI, 2002, J SOIL WATER CONSERV, V57, A44 PETERSON GD, 2003, CONSERV BIOL, V17, P358 PRESSEY RL, 1993, TRENDS ECOL EVOL, V8, P124 PRIOR J, 1991, LANDFORMS IOWA PUCKETT LJ, 1994, 944001 USGS RABB GB, 1995, BIODIVERS CONSERV, V4, P536 ROBINSON CA, 1996, SOIL SCI SOC AM J, V60, P264 ROSENZWEIG ML, 1999, SCIENCE, V284, P276 RUSTIGIAN H, 1999, THESIS OREGON STATE RUSTIGIAN HL, 2003, LANDSCAPE ECOL, V18, P65 SALA OE, 2000, SCIENCE, V287, P1770 SANTELMANN M, 2001, APPL ECOLOGICAL PRIN SCHILLING KE, 2000, J AM WATER RESOUR AS, V36, P1101 SCHOUP M, 1999, THESIS U IOWA IOWA C STARFIELD AM, 1997, J WILDLIFE MANAGE, V61, P261 STEINITZ C, 2003, ALTERNATIVE FUTURES TRESS B, 2003, LANDSCAPE URBAN PLAN, V64, P161 VACHE KB, 2002, J AM WATER RESOUR AS, V38, P773 VITOUSEK PM, 1997, ECOL APPL, V7, P737 VITOUSEK PM, 1997, SCIENCE, V277, P494 WHITE D, 1997, CONSERV BIOL, V11, P349 WHITE D, 1999, LANDSCAPE ECOLOGICAL, P127 WILLIAMS JR, 1988, EPIC EROSION PRODUCT, V1 0921-2973 Landsc. Ecol.ISI:000221879000002Oregon State Univ, Dept Geosci, Corvallis, OR 97331 USA. Canadian Wildlife Serv, Natl Wildlife Res Ctr, Ottawa, ON K1A 0H3, Canada. Univ Michigan, Sch Nat Resources & Environm, Ann Arbor, MI 48109 USA. E&S Environm Chem, Corvallis, OR USA. Oregon State Univ, Dept Bioresource Engn, Corvallis, OR 97331 USA. Iowa State Univ, Dept Ecol Evolut & Organismal Biol, Ames, IA 50011 USA. Univ Minnesota, Dept Appl Econ & Ecol, St Paul, MN 55108 USA. Univ Minnesota, Dept Evolut & Behav, St Paul, MN 55108 USA. Iowa State Univ, Dept Agron, Ames, IA 50011 USA. Oregon State Univ, Dept Agr & Resource Econ, Corvallis, OR 97331 USA. Santelmann, MV, Oregon State Univ, Dept Geosci, Corvallis, OR 97331 USA. santelmm@onid.orst.eduEnglish.|?vSato, Chloe F. Wood, Jeff T. Schroder, Mellesa Michael, Damian R. Osborne, William S. Green, Ken Lindenmayer, David B.2014rDesigning for conservation outcomes: the value of remnant habitat for reptiles on ski runs in subalpine landscapes 1225-1236Landscape Ecology297AugSubalpine ecosystems are centres of endemism that are important for biodiversity. However, these areas are under threat from the creation, expansion and continued modification of ski runs, activities that have largely negative effects on wildlife. Despite this threat, research on the impacts of ski runs is limited for reptiles-particularly regarding the value of remnant vegetation retained on ski runs. Here we quantify the effects of habitat loss and fragmentation (i.e., patch size, patch isolation and edge effects) on the abundance of a common subalpine lizard and on thermal regimes (a key determinant of lizard distribution) in an Australian ski resort. The number of lizards observed differed significantly with habitat type (ski runs vs. forested areas) and patch isolation, but not patch size. In addition, the edges of patches supported more lizards than any other habitat type. These patterns of lizard distribution can be explained, in part, by the differing thermal regimes in each habitat. Ski runs had significantly higher ground surface temperatures than any other habitat type, precluding their use for a considerable proportion of the activity period of a lizard. In comparison, edges were characterised by lower temperatures than ski runs, but higher temperatures than the core of forested areas, potentially providing a favourable environment for thermoregulation. Based on our results, we conclude that although modified ski runs have a negative effect on lizards, patches of remnant vegetation retained on ski runs are of value for reptiles and their conservation could help mitigate the negative effects of habitat loss caused by ski run creation.!://WOS:000339831300011Times Cited: 0 0921-2973WOS:00033983130001110.1007/s10980-014-0058-3|? =Sattler, T. Duelli, P. Obrist, M. K. Arlettaz, R. Moretti, M.2010fResponse of arthropod species richness and functional groups to urban habitat structure and management941-954Landscape Ecology256JulZUrban areas are a particular landscape matrix characterized by a fine-grained spatial arrangement of very diverse habitats (urban mosaic). We investigated arthropods to analyse biodiversity-habitat associations along five environmental gradients (age, impervious area, management, configuration, composition) in three Swiss cities (96 study sites). We considered total species richness and species richness within different functional groups (zoophagous, phytophagous, pollinator, low mobility, and high mobility species). Information theoretical model selection procedures were applied and predictions were calculated based on weighted models. Urban areas yielded on average 284 arthropod species (range: 169-361), with species richness correlating mostly with heterogeneity indices (configuration and composition). Species richness also increased with age of urban settlement, while enlarged proportions of impervious area and intensified habitat management was negatively correlated. Functional groups showed contrasted, specific responses to environmental variables. Overall, we found surprisingly little variation in species richness along the gradients, which is possibly due to the fine-grained spatial interlinkage of good (heterogeneous) and bad (sealed) habitats. The highly fragmented nature of urban areas may not represent a major obstacle for the arthropods currently existing in cities because they have probably been selected for tolerance to fragmentation and for high colonisation potential. Given that built areas are becoming denser, increasing spatial heterogeneity of the urban green offers potential for counteracting the detrimental effects of densification upon urban biodiversity. By quantifying the expected effects along environmental gradients, this study provides guidance for managers to set priorities when enhancing urban arthropod species richness.!://WOS:000278526000010Times Cited: 0 0921-2973WOS:00027852600001010.1007/s10980-010-9473-24<78Saunders, S. C. Chen, J. Q. Crow, T. R. Brosofske, K. D.1998dHierarchical relationships between landscape structure and temperature in a managed forest landscape381-395Landscape Ecology136hierarchy landscape structure microclimate pattern-process scale wavelet analysis YELLOWSTONE-NATIONAL-PARK WAVELET ANALYSIS CLEAR-CUT SCALE ECOLOGY GROWTH FRAGMENTATION HETEROGENEITY PATTERNS VARIANCEArticleDec Management may influence abiotic environments differently across time and spatial scale, greatly influencing perceptions of fragmentation of the landscape. It is vital to consider a priori the spatial scales that are most relevant to an investigation, and to reflect on the influence that scale may have on conclusions. While the importance of scale in understanding ecological patterns and processes has been widely recognized, few researchers have investigated how the relationships between pattern and process change across spatial and temporal scales. We used wavelet analysis to examine the multiscale structure of surface and soil temperature, measured every 5 m across a 3820 m transect within a national forest in northern Wisconsin. Temperature functioned as an indicator - or end product - of processes associated with energy budget dynamics, such as radiative inputs, evapotranspiration and convective losses across the landscape. We hoped to determine whether functional relationships between landscape structure and temperature could be generalized, by examining patterns and relationships at multiple spatial scales and time periods during the day. The pattern of temperature varied between surface and soil temperature and among daily time periods. Wavelet variances indicated that no single scale dominated the pattern in temperature at any time, though values were highest at finest scales and at midday. Using general linear models, we explained 38% to 60% of the variation in temperature along the transect. Broad categorical variables describing the vegetation patch in which a point was located and the closest vegetation patch of a different type (landscape context) were important in models of both surface and soil temperature across time periods. Variables associated with slope and microtopography were more commonly incorporated into models explaining variation in soil temperature, whereas variables associated with vegetation or ground cover explained more variation in surface temperature. We examined correlations between wavelet transforms of temperature and vegetation (i.e., structural) pattern to determine whether these associations occurred at predictable scales or were consistent across time. Correlations between transforms characteristically had two peaks; one at finer scales of 100 to 150 m and one at broader scales of >300 m. These scales differed among times of day and between surface and soil temperatures. Our results indicate that temperature structure is distinct from vegetation structure and is spatially and temporally dynamic. There did not appear to be any single scale at which it was more relevant to study temperature or this pattern-process relationship, although the strongest relationships between vegetation structure and temperature occurred within a predictable range of scales. Forest managers and conservation biologists must recognize the dynamic relationship between temperature and structure across landscapes and incorporate the landscape elements created by temperature-structure interactions into management decisions.://000077308100004 eISI Document Delivery No.: 144HH Times Cited: 23 Cited Reference Count: 46 Cited References: *CHEQ NAT FOR WASH, 1993, LANDSC LEV AN DES FU ALBERT DA, 1995, NC178 GTR USDA FOR S BRADSHAW GA, 1991, THESIS OREGON STATE BRADSHAW GA, 1992, J ECOL, V80, P205 CHEN JQ, 1993, AGR FOREST METEOROL, V63, P219 CHEN JQ, 1995, ECOL APPL, V5, P74 CHEN JQ, 1996, CONSERV BIOL, V10, P854 CHRISTENSEN NL, 1996, ECOL APPL, V6, P665 DOAK DF, 1992, THEOR POPUL BIOL, V41, P315 DONOVAN TM, 1995, CONSERV BIOL, V9, P1380 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FORTIN MJ, 1994, ECOLOGY, V75, P956 FORTIN MJ, 1996, OIKOS, V77, P51 FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 FRANKLIN JF, 1997, ECOSYSTEM MANAGEMENT, P21 GAO W, 1993, J APPL METEOROL, V32, P1717 GARDNER RH, 1989, LANDSCAPE ECOL, V3, P217 GILPIN ME, 1991, METAPOPULATION DYNAM GRAPS A, 1995, IEEE COMPUT SCI ENG, V2, P50 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 HANSEN AJ, 1993, ECOL APPL, V3, P481 HANSEN AJ, 1995, ECOL APPL, V5, P555 HEINSELMAN ML, 1981, FOREST SUCCESSION CO, P374 HOLLING CS, 1992, ECOL MONOGR, V62, P447 HORNE JK, 1994, OIKOS, V70, P201 HORNE JK, 1995, OIKOS, V74, P18 HUEY RB, 1991, AM NAT, V137, P91 HUTCHINSON GE, 1953, P ACAD NAT SCI PHILA, V105, P1 LERTZMAN KP, 1997, RAINFORESTS HOME PRO, P361 LEVIN SA, 1992, ECOLOGY, V73, P1943 LOVEJOY TE, 1986, CONSERVATION BIOL SC, P257 MACARTHUR RH, 1964, P NATL ACAD SCI USA, V51, P1207 MILLER DR, 1980, AGR METEOROL, V22, P53 PEARSON SM, 1995, ECOL APPL, V5, P744 PERRY DA, 1994, FOREST ECOSYSTEMS PICKETT STA, 1985, ECOLOGY NATURAL DIST REED RA, 1996, CONSERV BIOL, V10, P1098 STAGE AR, 1976, FOREST SCI, V22, P457 SWANSON FJ, 1988, BIOSCIENCE, V38, P92 TURNER MG, 1987, LANDSCAPE HETEROGENI TURNER MG, 1994, J VEG SCI, V5, P731 WEBER LH, 1986, DEEP-SEA RES, V33, P1327 WIENS JA, 1989, FUNCTIONAL ECOLOGY, V3, P383 WIENS JA, 1993, OIKOS, V66, P369 WITH KA, 1997, OIKOS, V78, P151 XU M, 1997, IN PRESS CLIMATE RES 0921-2973 Landsc. Ecol.ISI:000077308100004Michigan Technol Univ, Sch Forestry & Wood Prod, Houghton, MI 49931 USA. Saunders, SC, Michigan Technol Univ, Sch Forestry & Wood Prod, Houghton, MI 49931 USA.English<7 Saura, S.2004bEffects of remote sensor spatial resolution and data aggregation on selected fragmentation indices197-209Landscape Ecology1922fragmentation index; grain; landscape pattern; pixel size; power law; pattern aggregation; scale; spatial configuration; spatial resolution POINT-SPREAD FUNCTION; LANDSCAPE PATTERN; LAND-COVER; HABITAT FRAGMENTATION; VEGETATION INDEXES; BRITISH-COLUMBIA; REGIONAL-SCALE; SATELLITE DATA; METRICS; SIMULATIONArticleAnalyzing the effect of scale on landscape pattern indices has been a key research topic in landscape ecology. The lack of comparability of fragmentation indices across spatial resolutions seriously limits their usefulness while multi-scale remotely sensed data are becoming increasingly available. In this paper, we examine the effect of spatial resolution on six common fragmentation indices that are being used within the Third Spanish National Forest Inventory. We analyse categorical data derived from simultaneously gathered Landsat-TM and IRS-WiFS satellite images, as well as TM patterns aggregated to coarser resolutions through majority rules. In general, majority rules tend to produce more fragmented patterns than actual sensor ones. It is suggested that sensor point spread function should be specifically considered to improve comparability among satellite images of varying pixel sizes. Power scaling-laws were found between spatial resolution and several fragmentation indices, with mean prediction errors under 10% for number of patches and mean patch size and under 5% for edge length. All metrics but patch cohesion indicate lower fragmentation at coarser spatial resolutions. In fact, an arbitrarily large value of patch cohesion can be obtained by resampling the pattern to smaller pixel sizes. An explanation and simple solution for correcting this undesired behaviour is provided. Landscape division and largest patch index were found to be the least sensitive indices to spatial resolution effects.://000220452500007 ISI Document Delivery No.: 806SB Times Cited: 13 Cited Reference Count: 46 Cited References: *MIN MED AMB, 2002, TERC INV FOR NAC *NRSA, 1995, IRS 1C DAT US HDB ANDREN H, 1994, OIKOS, V71, P355 BENSON BJ, 1995, LANDSCAPE ECOLOGY, V10, P13 BREAKER LC, 1990, J GEOPHYS RES-OCEANS, V95, P9701 CHUVIECO E, 1999, INT J REMOTE SENS, V20, P2331 CHUVIECO E, 2002, TELEDETECCION AMBIEN CRACKNELL AP, 1998, INT J REMOTE SENS, V19, P2025 FEDER J, 1988, FRACTALS FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FORSTER BC, 1994, ISPRS J PHOTOGRAMM, V49, P32 FROHN RC, 1998, REMOTE SENSING LANDS GRIFFITHS GH, 2000, INT J REMOTE SENS, V21, P2685 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HANSEN MJ, 2001, REMOTE SENS ENVIRON, V77, P50 HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HLAVKA CA, 1997, INT J REMOTE SENS, V18, P2253 HUANG CQ, 2002, REMOTE SENS ENVIRON, V80, P203 IMBERNON J, 2001, INT J REMOTE SENS, V22, P1753 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 JAEGER JAG, 2000, LANDSCAPE ECOL, V15, P115 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 JUSTICE CO, 1989, INT J REMOTE SENS, V10, P1539 KORVIN G, 1992, FRACTAL MODELS EARTH LI BL, 1997, ECOL MODEL, V102, P353 LI H, 1993, LANDSCAPE ECOL, V8, P63 LUQUE SS, 1994, LANDSCAPE ECOL, V9, P287 LUQUE SS, 2000, INT J REMOTE SENS, V21, P2613 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MYNENI RB, 1995, IEEE T GEOSCI REMOTE, V33, P481 ONEILL RV, 1996, LANDSCAPE ECOL, V11, P169 OPENSHAW S, 1984, MODIFIABLE AREAL UNI SACHS DL, 1998, CAN J FOREST RES, V28, P23 SAURA S, 2000, LANDSCAPE ECOL, V15, P661 SAURA S, 2001, PHOTOGRAMM ENG REM S, V67, P1027 SAURA S, 2001, THESIS U POLITECNICA SAURA S, 2002, INT J REMOTE SENS, V23, P4853 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 TEILLET PM, 1997, REMOTE SENS ENVIRON, V61, P139 TISCHENDORF L, 2001, LANDSCAPE ECOL, V16, P235 TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 TURNER MG, 1989, ECOL MODEL, V48, P1 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 WICKHAM JD, 1995, INT J REMOTE SENS, V16, P3585 WU J, 2000, GEOGRAPHICAL INFORMA, V6, P6 WU JG, 2002, LANDSCAPE ECOL, V17, P761 0921-2973 Landsc. Ecol.ISI:000220452500007Univ Lleida, Higher Tech Sch Agrarian Engn, Dept Agroforestry Engn, Lleida 25198, Spain. Saura, S, Univ Lleida, Higher Tech Sch Agrarian Engn, Dept Agroforestry Engn, Av Alcalde Rovira Roure 191, Lleida 25198, Spain. ssaura@eagrof.udl.esEnglish<7Saura, S. Carballal, P.2004Discrimination of native and exotic forest patterns through shape irregularity indices: An analysis in the landscapes of Galicia, Spain647-662Landscape Ecology1963boundaries complexity; forest patterns; landscape configuration; native and exotic forests; pure and mixed forests; shape elongation; shape irregularity; shape metrics; spatial indices; tree species richness SATELLITE IMAGERY; SPATIAL PATTERN; PATCH SHAPE; DEFORESTATION; METRICS; INFORMATION; RESERVES; USAArticleAug]Landscapes resulting from human activity may be expected to present simpler shapes than more natural landscapes. In the case of forest landscapes, the boundaries of native forest patches may be more irregular than those of exotic forest plantations. There is however a lack of quantitative results to this respect, and it is not clear which shape indices are more adequate for such discrimination. In this study, we analysed the shape of a large number of forest classes in the region of Galicia ( Spain) using the Spanish Forest Map at a scale 1: 50 000 as the spatial information source. We considered a set of fifteen shape irregularity indices including those that have been commonly used in landscape ecology studies. We found systematic differences in the shape of the analysed forest classes, with native forests presenting both more complex and elongated boundaries than exotic forests. We suggest that these differences are due to the combined effects of human action and other topographical and hydrological factors. The only index that perfectly discriminated both types of forest was the mean circumscribing circle index. Other six indices provided also a significantly good discrimination: density of shape characteristic points, area-weighted mean perimeter-area ratio, area-weighted mean contiguity index, mean shape index, perimeter-area fractal dimension and mean largest axis index. Comparisons of pure and mixed forests with the same dominant species indicated that an increase in tree species richness is in general associated with more irregular boundaries in the forest. Discarding indices on the basis of a high statistical correlation may not be an adequate procedure to retain the best-performing indices. Finally, we discussed several limitations of some frequently used indices that may be relevant to prevent an improper characterization of landscape shape.://000224100600006 7ISI Document Delivery No.: 857FC Times Cited: 3 Cited Reference Count: 43 Cited References: *COMM EUR COMM, 1993, 12585EN EUR COMM EUR *MIN MED AMB, 2002, TERC INV FOR NAC AUSTIN RF, 1984, SPATIAL STAT MODELS, P293 BAKER WL, 1992, LANDSCAPE ECOL, V7, P291 BOGAERT J, 1999, ENVIRON ECOL STAT, V6, P275 BOGAERT J, 2002, LANDSCAPE ECOLOGY, V17, P87 CROW TR, 1999, LANDSCAPE ECOL, V14, P449 CUMMING S, 2002, LANDSCAPE ECOL, V17, P433 DAVIS JC, 1986, STAT DATA ANAL GEOLO DORNER B, 2002, LANDSCAPE ECOL, V17, P729 FEDER J, 1988, FRACTALS FOLEY JD, 1995, COMPUTER GRAPHICS PR FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FROHN RC, 1996, INT J REMOTE SENS, V17, P3233 GARRABOU J, 1998, LANDSCAPE ECOL, V13, P225 HAINESYOUNG R, 1996, PROG PHYS GEOG, V20, P418 HE HS, 2000, LANDSCAPE ECOL, V15, P591 HULSHOFF RM, 1995, LANDSCAPE ECOL, V10, P101 IMBERNON J, 2001, INT J REMOTE SENS, V22, P1753 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 KRUMMEL JR, 1987, OIKOS, V48, P321 LAGRO J, 1991, PHOTOGRAMM ENG REM S, V57, P285 LEDUC A, 1994, LANDSCAPE ECOL, V9, P279 LINDEMANN JD, 2001, LANDSCAPE ECOL, V16, P313 LUQUE SS, 2000, INT J REMOTE SENS, V21, P2613 MADRIGAL A, 1994, ORDENACION MONTES AR MANDELBROT BB, 1983, FRACTAL GEOMETRY NAT MANUEL C, 2002, TRANSFORMACION HIST MCGARIGAL K, 2002, FRAGSTATS SPATIAL PA MLADENOFF DJ, 1993, ECOL APPL, V3, P294 MOSER D, 2002, LANDSCAPE ECOL, V17, P657 PASTOR J, 1990, LANDSCAPE ECOL, V4, P55 PERALTA P, 2000, INT J REMOTE SENS, V21, P2555 PIETRZAK M, 1989, SERIA GEOGRAFIA, V45 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 RIVASMARTINEZ S, 1987, MEMORIA MAPA SERIES ROIS M, 2001, FINE GALICIA EUROPEA SACHS DL, 1998, CAN J FOREST RES, V28, P23 SAURA S, 2001, PHOTOGRAMM ENG REM S, V67, P1027 SAURA S, 2002, INT J REMOTE SENS, V23, P4853 SWED FS, 1943, ANN MATH STAT, V14, P66 TISCHENDORF L, 2001, LANDSCAPE ECOL, V16, P235 XIA L, 1996, INT J REMOTE SENS, V17, P1473 0921-2973 Landsc. Ecol.ISI:000224100600006Univ Lleida, Higher Tech Sch Agr Engn, Dept Agroforestry Engn, Lleida, Spain. Saura, S, Univ Lleida, Higher Tech Sch Agr Engn, Dept Agroforestry Engn, Av Alcalde Rovira Roure 191, Lleida, Spain. ssaura@eagrof.udl.esEnglishc<7 Saura, S. Martinez-Millan, J.2000DLandscape patterns simulation with a modified random clusters method661-678Landscape Ecology157landscape models landscape patterns percolation spatial patterns stochastic spatial simulation thematic and categorical maps HABITAT FRAGMENTATION CONNECTIVITY INDEXES HETEROGENEITY COEXISTENCE DISTURBANCE STRATEGIES DISPERSAL MODELSArticleOct4A new modified random clusters method for the simulation of landscape the matic spatial patterns is presented. It produces more realistic and general results than landscape models that have been commonly used to date in the field of landscape ecology. Simulated patterns are said to be realistic, apart from their patchy and irregular appearance, because the values of the spatial indices as a function of habitat abundance measured in real landscape patterns (number of patches, edge length and patch cohesion index) can be replicated with the proposed landscape model. It allows a wide range of spatial patterns to be obtained, in which fragmentation and habitat abundance can be systematically and independently varied. Furthermore, a degree of control over the irregularity of the shapes of the simulated landscapes can be achieved, and it is also possible to simulate patterns with anisotropy. The proposed method is easy to implement and requires little computation time, which enhances the practical possibilities of this method in different areas of landscape ecology.://000089421500006 3 ISI Document Delivery No.: 356AV Times Cited: 21 Cited Reference Count: 51 Cited References: ANDREN H, 1994, OIKOS, V71, P355 BRUS DJ, 1997, GEODERMA, V80, P1 BUNDE A, 1991, FRACTALS DISORDERED, P51 CHUVIECO E, 1990, FUNDAMENTOS TELEDETE DEUTSCH CV, 1992, GSLIB GEOSTATISTICAL FAHRIG L, 1985, ECOLOGY, V66, P1762 FEDER J, 1988, FRACTALS FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GARDNER RH, 1989, LANDSCAPE ECOL, V3, P217 GARDNER RH, 1991, ECOTONES ROLE LANDSC, P52 GARDNER RH, 1991, QUANTITATIVE METHODS, P289 GOTWAY CA, 1996, P SPAT ACC ASS NAT R, P30 GREEN DG, 1994, PACIFIC CONSERVATION, V1, P194 GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 GUZMAN M, 1993, ESTRUCTURAS FRACTALE HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HOMER CG, 1997, PHOTOGRAMM ENG REM S, V63, P59 LAM NSN, 1990, PHOTOGRAMM ENG REM S, V56, P187 LAVOREL S, 1994, OIKOS, V71, P75 LAVOREL S, 1995, LANDSCAPE ECOL, V10, P277 LI H, 1993, LANDSCAPE ECOL, V8, P63 LI HB, 1993, LANDSCAPE ECOL, V8, P155 LI HB, 1994, ECOLOGY, V75, P2446 MOLONEY KA, 1996, ECOLOGY, V77, P375 MYERS DE, 1996, P SPAT ACC ASS NAT R, P23 ONEILL RV, 1988, LANDSCAPE ECOL, V2, P3 ONEILL RV, 1992, LANDSCAPE ECOL, V7, P55 PALMER MW, 1992, AM NAT, V139, P375 PLOTNICK RE, 1993, LANDSCAPE ECOL, V8, P201 SAUPE D, 1988, SCI FRACTAL IMAGES, P71 SAURA S, 1998, SIMULACION MAPAS TEM SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SRIVASTAVA RM, 1996, P SPAT ACC ASS NAT R, P13 STAUFFER D, 1985, INTRO PERCOLATION TH THOMAS IL, 1980, PHOTOGRAMMETRIC ENG, V46, P1201 TRAUB B, 1997, 971 FOSTL BIOM TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 TURNER MG, 1989, ECOL MODEL, V48, P1 TURNER MG, 1989, OIKOS, V55, P121 TURNER MG, 1990, PHOTOGRAMM ENG REM S, V56, P379 TURNER MG, 1991, ECOTONES ROLE LANDSC, P52 VANDORP D, 1987, LANDSCAPE ECOLOGY, V1, P59 WIENS JA, 1997, OIKOS, V78, P257 WILCOX BA, 1985, AM NAT, V125, P879 WITH KA, 1995, ECOLOGY, V76, P2446 WITH KA, 1997, OIKOS, V78, P151 WITH KA, 1997, OIKOS, V79, P219 ZIFF RM, 1986, PHYS REV LETT, V56, P545 ZOHRER F, 1978, 12 BLM USDI BUR LAND 0921-2973 Landsc. Ecol.ISI:000089421500006Univ Politecn Madrid, ETS Ingenieros Montes, Dept Econ & Gest Explotac & Ind Forestales, E-28040 Madrid, Spain. Saura, S, Univ Politecn Madrid, ETS Ingenieros Montes, Dept Econ & Gest Explotac & Ind Forestales, Ciudad Univ S-N, E-28040 Madrid, Spain.English<7@Saveraid, E. H. Debinski, D. M. Kindscher, K. Jakubauskas, M. E.2001A comparison of satellite data and landscape variables in predicting bird species occurrences in the Greater Yellowstone Ecosystem, USA71-83Landscape Ecology161heterogeneous landscapes predicting bird species occurrences remote sensing satellite imagery wildlife species habitats HABITAT FRAGMENTATION FOREST FRAGMENTS BREEDING BIRDS AREA GIS POPULATIONS DISTRIBUTIONS BIODIVERSITY CONSERVATION IMAGERYArticleJanWe compare the accuracy of predicting the occurrence of 11 bird species in montane meadows of the Greater Yellowstone National Park ecosystem, in the states of Montana and Wyoming, USA. We used remotely sensed, landscape, and habitat data. The meadow type, as determined from the remotely sensed data, was highly correlated with abundances of six of the 11 bird species. Landscape variables significant in predicting occurrence were selected using a stepwise multiple regression for each bird species. These variables were then used in a multiple regression with the variable meadow type. As expected, the abundances of the generalist species (American Robin, Dark-eyed Junco, White-crowned Sparrow, Brewer's Blackbird, and Chipping Sparrow) were not strongly correlated with landscape variables or meadow type. Conversely, abundances of the Common Snipe, Common Yellowthroat, Lincoln's Sparrow, Savannah Sparrow, Vesper Sparrow, and Yellow Warbler were highly correlated with meadow type and landscape variables such as percent cover of willow (Salix spp.), graminoid, woody vegetation, sagebrush (Artemisia spp.), and graminoid and shrub biomass. The results from our study indicate that remotely sensed data are applicable for estimating potential habitats for bird species in the different types of montane meadows. However, to improve predictions about species in specific sites or areas, we recommend the use of additional landscape metrics and habitat data collected in the field.://000167389900006 - ISI Document Delivery No.: 409NN Times Cited: 18 Cited Reference Count: 50 Cited References: *SAS I INC, 1990, SAS STAT US GUID VER ASPINALL R, 1993, PHOTOGRAMM ENG REM S, V59, P537 BEARD KH, 1999, CONSERV BIOL, V13, P1108 BLAKE JG, 1987, ECOLOGY, V68, P1724 BOWER JE, 1990, FIELD LAB METHODS GE CICERO C, 1997, GREAT BASIN NAT, V57, P104 CODY ML, 1985, HABITAT SELECTION BI DAUBENMIRE R, 1959, NW SCI, V33, P43 DEBINSKI DM, 1999, INT J REMOTE SENS, V20, P3281 DETTMERS R, 1999, ECOL APPL, V9, P152 DUNNING JB, 1992, OIKOS, V65, P169 ESTADES CF, 1997, CONDOR, V99, P719 FAHRIG L, 1994, CONSERV BIOL, V8, P50 FRANK TD, 1988, PHOTOGRAMM ENG REM S, V54, P1727 FREEMARK KE, 1986, BIOL CONSERV, V36, P115 GILL FB, 1995, ORNITHOLOGY HAGAN JM, 1996, CONSERV BIOL, V10, P188 HAILA Y, 1993, ECOLOGY, V74, P714 HANEY JC, 1986, AM BIRDS, V40, P396 HEPINSTALL JA, 1997, PHOTOGRAMM ENG REM S, V63, P1231 HERKERT JR, 1994, ECOL APPL, V4, P461 JAKUBAUSKAS ME, 1998, GEOCARTO INT, V13, P65 JORGENSEN AF, 1996, INT J REMOTE SENS, V17, P91 KINDSCHER K, 1998, WETLANDS ECOLOGY MAN, V5, P265 LESCOURRET F, 1994, J ENVIRON MANAGE, V58, P249 MACARTHUR R, 1961, ECOLOGY, V42, P594 MACK EL, 1997, J APPL ECOL, V34, P1222 MAY PG, 1982, OECOLOGIA, V55, P208 MCADOO JK, 1989, J WILDLIFE MANAGE, V53, P494 MCCOY T, 1996, THESIS U MISSOURI CO MCGARIGAL K, 1994, FRAGSTATS SPATIAL PA PATTERSON MP, 1996, AM MIDL NAT, V135, P153 PEARCE CM, 1991, ARCTIC, V44, P49 PEARSON SM, 1993, LANDSCAPE ECOL, V8, P3 SALT GW, 1957, CONDOR, V59, P373 SAVERAID EH, 1999, THESIS IOWA STATE U SCOTT JM, 1993, WILDLIFE MONOGR, P1 SCOTT JM, 1996, GAP ANAL LANDSCAPE A STOMS DM, 1993, INT J REMOTE SENS, V14, P1839 TUCKER K, 1997, LANDSCAPE ECOL, V12, P77 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P245 VANDORP D, 1987, LANDSCAPE ECOLOGY, V1, P59 VICKERY PD, 1992, AUK, V109, P697 VICKERY PD, 1994, CONSERV BIOL, V8, P1087 WIENS JA, 1969, ORNITHOL MONOGR, V8, P1 WIENS JA, 1974, AM MIDL NAT, V91, P195 WIENS JA, 1985, OIKOS, V45, P421 WIENS JA, 1995, IBIS, V137, S97 WILLSON MF, 1974, ECOLOGY, V55, P1017 0921-2973 Landsc. Ecol.ISI:000167389900006wIowa State Univ, Dept Anim Ecol, Ames, IA 50011 USA. Debinski, DM, Iowa State Univ, Dept Anim Ecol, Ames, IA 50011 USA.English<7-Schaefer, J. A. Bergman, C. M. Luttich, S. N.2000:Site fidelity of female caribou at multiple spatial scales731-739Landscape Ecology158caribou migratory null model philopatry Rangifer tarandus sedentary site fidelity spatial scale WHITE-TAILED DEER WOODLAND CARIBOU HABITAT SELECTION BLACK BRANT SATELLITE TELEMETRY RANGIFER-TARANDUS BRITISH-COLUMBIA RANGE FIDELITY HERD DYNAMICSArticleDecStudies of site fidelity have been hampered by arbitrary designations of spatial scale and the lack of null models for comparison. We generated null expectations of fidelity at different scales from the distribution of radio-tracked animals in a population. We applied the models to space use of satellite-tracked caribou (Rangifer tarandus caribou), the most vagile nonvolant terrestrial animal, from populations representing sedentary and migratory ecotypes. We compared distances between consecutive-year locations of adult females to expectations based on the total range and seasonal range of each population. At the scale of the total range, sedentary and migratory caribou displayed remarkably similar philopatry, despite a 30-fold difference in size of their population ranges, from time of calving (late May) to breeding (late October). The most intense fidelity occurred during post-calving when, on average, sedentary and migratory females returned to as near as 6.7 km and 123 km, respectively, of locations occupied the previous year. At the scale of the seasonal range, the ecotypes differed. Sedentary caribou still displayed fidelity from calving to breeding; migratory caribou exhibited fidelity only during late autumn. For migratory, but not sedentary caribou, inter-year distances during winter were negatively correlated with age, implying that older females were more philopatric. We conclude that reproductive activities delimit the season of fidelity of female caribou of both ecotypes, and that scale-dependent ecotypic differences in fidelity may reflect different factors of population limitation. A spatially-explicit approach to site fidelity is essential for synthesizing patterns across studies.://000165379700004 ISI Document Delivery No.: 375BM Times Cited: 15 Cited Reference Count: 58 Cited References: AYCRIGG JL, 1997, J MAMMAL, V78, P468 BELL G, 1993, OECOLOGIA, V96, P114 BERGERUD AT, 1986, CAN J ZOOL, V64, P1515 BERGERUD AT, 1988, TRENDS ECOL EVOL, V3, P68 BERGERUD AT, 1990, ANIM BEHAV, V39, P360 BERGERUD AT, 1996, RANGIFER, V9, P95 BERGMAN CM, 2000, IN PRESS OECOLOGIA BERRY JD, 1985, J WILDLIFE MANAGE, V49, P237 BROWN WK, 1985, MCGILL SUBARCTIC RES, V40, P57 CAMERON RD, 1986, RANGIFER, V1, P51 COUTURIER S, 1990, ARCTIC, V43, P9 COUTURIER S, 1996, RANGIFER, V9, P283 CRETE M, 1993, CAN J ZOOL, V71, P2291 DUSEK GL, 1989, WILDLIFE MONOGR, V104, P1 EDGE WD, 1985, J WILDLIFE MANAGE, V49, P741 FANCY SG, 1991, CAN J ZOOL, V69, P1736 FERGUSON SH, 1988, OECOLOGIA, V76, P236 FESTABIANCHET M, 1986, CAN J ZOOL, V64, P2126 FLYNN L, 1999, J AVIAN BIOL, V30, P47 FOLT CL, 1998, CAN J FISH AQUAT S1, V55, P9 FRYXELL JM, 1988, AM NAT, V131, P781 GARROTT RA, 1987, J WILDLIFE MANAGE, V51, P634 GREENWOOD PJ, 1980, ANIM BEHAV, V28, P1140 GUNN A, 1986, RANGIFER, V1, P151 HEARN BJ, 1990, CAN J ZOOL, V68, P276 IRONS DB, 1998, ECOLOGY, V79, P647 JOHNSON OW, 1993, WILSON BULL, V105, P60 KEATING KA, 1991, J WILDLIFE MANAGE, V55, P160 KEATING KA, 1994, J WILDLIFE MANAGE, V58, P414 LEWIS M, 1996, MAR MAMMAL SCI, V12, P138 LINDBERG MS, 1997, CONDOR, V99, P25 LINDBERG MS, 1998, AUK, V115, P436 LINDBERG MS, 1998, ECOLOGY, V79, P1893 LINNELL JDC, 1995, WILDLIFE SOC B, V23, P31 MANSEAU M, 1996, J ECOL, V84, P503 MESSIER F, 1988, ARCTIC, V41, P279 MYERS JP, 1988, P INT ORNITHOL C, V19, P604 PHILLIPS DM, 1998, J MAMMAL, V79, P180 POWER ME, 1984, J ANIM ECOL, V53, P357 RAMSAY MA, 1990, J MAMMAL, V71, P233 RETTIE WJ, 1998, CAN J ZOOL, V76, P251 RETTIE WJ, 1998, THESIS U SASKATCHEWA ROBERTSON G, 1999, AUK, V116, P20 SCHAEFER JA, 1994, CAN J BOT, V72, P1264 SCHAEFER JA, 1995, ECOGRAPHY, V18, P333 SCHAEFER JA, 1999, J WILDLIFE MANAGE, V63, P580 SCHNEIDER DC, 1994, QUANTITATIVE ECOLOGY SEIP DR, 1992, CAN J ZOOL, V70, P1494 SWITZER PV, 1997, BEHAV ECOL SOCIOBIOL, V40, P307 TIERSON WC, 1985, J WILDLIFE MANAGE, V49, P760 TOUPIN B, 1996, ARCTIC, V49, P375 VALKENBURG P, 1986, RANGIFER, V1, P315 VANDEELEN TR, 1998, J WILDLIFE MANAGE, V62, P205 VANDYKE FG, 1998, J WILDLIFE MANAGE, V62, P1020 VANSTAADEN MJ, 1995, Z SAUGETIERKD, V60, P150 WHITE GC, 1990, ANAL WILDLIFE RADIOT WHITTEN KR, 1995, J WILDLIFE MANAGE, V59, P273 WIENS JA, 1989, FUNCT ECOL, V3, P385 0921-2973 Landsc. Ecol.ISI:000165379700004Dept Forest Resources & Agrifoods, Labrador, NF A0P 1E0, Canada. Schaefer, JA, Trent Univ, Dept Biol, Peterborough, ON K9J 7B8, Canada.English <7 FSchaller, N. Lazrak, E. G. Martin, P. Mari, J. F. Aubry, C. Benoit, M.2012_Combining farmers' decision rules and landscape stochastic regularities for landscape modelling433-446Landscape Ecology273*land-use dynamic on-farm survey conceptual model data mining crop succession crop allocation spatiotemporal analysis landscape agronomy landscape patterns land-use change spatial-distribution farming practices making processes regional-scale farmland bird cover change dynamics organization systemsMarLandscape spatial organization (LSO) strongly impacts many environmental issues. Modelling agricultural landscapes and describing meaningful landscape patterns are thus regarded as key-issues for designing sustainable landscapes. Agricultural landscapes are mostly designed by farmers. Their decisions dealing with crop choices and crop allocation to land can be generic and result in landscape regularities, which determine LSO. This paper comes within the emerging discipline called "landscape agronomy", aiming at studying the organization of farming practices at the landscape scale. We here aim at articulating the farm and the landscape scales for landscape modelling. To do so, we develop an original approach consisting in the combination of two methods used separately so far: the identification of explicit farmer decision rules through on-farm surveys methods and the identification of landscape stochastic regularities through data-mining. We applied this approach to the Niort plain landscape in France. Results show that generic farmer decision rules dealing with sunflower or maize area and location within landscapes are consistent with spatiotemporal regularities identified at the landscape scale. It results in a segmentation of the landscape, based on both its spatial and temporal organization and partly explained by generic farmer decision rules. This consistency between results points out that the two modelling methods aid one another for land-use modelling at landscape scale and for understanding the driving forces of its spatial organization. Despite some remaining challenges, our study in landscape agronomy accounts for both spatial and temporal dimensions of crop allocation: it allows the drawing of new spatial patterns coherent with land-use dynamics at the landscape scale, which improves the links to the scale of ecological processes and therefore contributes to landscape ecology.://000300087500010-889QE Times Cited:0 Cited References Count:64 0921-2973Landscape EcolISI:000300087500010Schaller, N AgroParisTech, INRA, SAD APT, UMR 1048, Batiment EGER,BP 01, F-78850 Thiverval Grignon, France AgroParisTech, INRA, SAD APT, UMR 1048, Batiment EGER,BP 01, F-78850 Thiverval Grignon, France AgroParisTech, INRA, SAD APT, UMR 1048, F-78850 Thiverval Grignon, France INRA, SAD ASTER, UR 055, F-88500 Mirecourt, France INRIA Grand Est, CNRS, UMR 7503, LORIA, F-54506 Vandoeuvre Les Nancy, FranceDOI 10.1007/s10980-011-9691-2English|?,Scharf, Elizabeth A.2014@Deep time: the emerging role of archaeology in landscape ecology563-569Landscape Ecology294AprGiven the goals of landscape ecology, information from archaeological sites provides a useful source of evidence regarding cultural practices, anthropogenic change, local conditions, and distributions of organisms at a variety of scales across both space and time. Due to the time depth available from the archaeological record, long-term processes can be studied and issues of land use legacies, human influence on landscape heterogeneity, and system histories can be addressed. Archaeological data can produce a diachronic record of past population size, population structure, biogeography, age-at-death, and migration patterns, useful for making ecosystem and wildlife management decisions. Researchers can use archaeological knowledge to differentiate between native and alien taxa, inform restoration plans, identify sustainable harvesting practices, account for modern distributions of taxa, predict future biogeographic changes, and elucidate the interplay of long- and short-term ecological processes.!://WOS:000333533800001Times Cited: 2 0921-2973WOS:00033353380000110.1007/s10980-014-9997-y ? lScheller, Robert Spencer, Wayne Rustigian-Romsos, Heather Syphard, Alexandra Ward, Brendan Strittholt, James2011yUsing stochastic simulation to evaluate competing risks of wildfires and fuels management on an isolated forest carnivore 1491-1504Landscape Ecology2610Springer NetherlandsEarth and Environmental Science Natural resource managers are often challenged with balancing requirements to maintain wildlife populations and to reduce risks of catastrophic or dangerous wildfires. This challenge is exemplified in the Sierra Nevada of California, where proposals to thin vegetation to reduce wildfire risks have been highly controversial, in part because vegetation treatments could adversely affect an imperiled population of the fisher ( Martes pennanti ) located in the southern Sierra Nevada. The fisher is an uncommon forest carnivore associated with the types of dense, structurally complex forests often targeted for fuel reduction treatments. Vegetation thinning and removal of dead-wood structures would reduce fisher habitat value and remove essential habitat elements used by fishers for resting and denning. However, crown-replacing wildfires also threaten the population’s habitat, potentially over much broader areas than the treatments intended to reduce wildfire risks. To investigate the potential relative risks of wildfires and fuels treatments on this isolated fisher population, we coupled three spatial models to simulate the stochastic and interacting effects of wildfires and fuels management on fisher habitat and population size: a spatially dynamic forest succession and disturbance model, a fisher habitat model, and a fisher metapopulation model, which assumed that fisher fecundity and survivorship correlate with habitat quality. We systematically varied fuel treatment rate, treatment intensity, and fire regime, and assessed their relative effects on the modeled fisher population over 60 years. After estimating the number of adult female fishers remaining at the end of each simulation scenario, we compared the immediate negative effects of fuel treatments to the longer-term positive effect of fuel treatment (via reduction of fire hazard) using structural equation modeling. Our simulations suggest that the direct, negative effects of fuel treatments on fisher population size are generally smaller than the indirect, positive effects of fuel treatments, because fuels treatments reduced the probability of large wildfires that can damage and fragment habitat over larger areas. The benefits of fuel treatments varied by elevation and treatment location with the highest net benefits to fisher found at higher elevations and within higher quality fisher habitat. Simulated fire regime also had a large effect with the largest net benefit of fuel treatments occurring when a more severe fire regime was simulated. However, there was large uncertainty in our projections due to stochastic spatial and temporal wildfires dynamic and fisher population dynamics. Our results demonstrate the difficulty of projecting future populations in systems characterized by large, infrequent, stochastic disturbances. Nevertheless, these coupled models offer a useful decision-support system for evaluating the relative effects of alternative management scenarios; and uncertainties can be reduced as additional data accumulate to refine and validate the models.+http://dx.doi.org/10.1007/s10980-011-9663-6 0921-297310.1007/s10980-011-9663-6|7 Scheller, R. M. Mladenoff, D. J.2007An ecological classification of forest landscape simulation models: tools and strategies for understanding broad-scale forested ecosystems491-505Landscape Ecology224 landscape ecology forest models simulation models gap models ecosystem process models fuzzy-systems theory climate-change vegetation dynamics spatially explicit boreal forest gap models heterogeneous landscapes species composition northern wisconsin fire suppressionAprnComputer models are increasingly being used by forest ecologists and managers to simulate long-term forest landscape change. We review models of forest landscape change from an ecological rather than methodological perspective. We developed a classification based on the representation of three ecological criteria: spatial interactions, tree species community dynamics, and ecosystem processes. Spatial interactions are processes that spread across a landscape and depend upon spatial context and landscape configuration. Communities of tree species may change over time or can be defined a priori. Ecosystem process representation may range from no representation to a highly mechanistic, detailed representation. Our classification highlights the implicit assumptions of each model group and helps define the problem set for which each model group is most appropriate. We also provide a brief history of forest landscape simulation models, summarize the current trends in methods, and consider how forest landscape models may evolve and continue to contribute to forest ecology and management. Our classification and review can provide novice modelers with the ecological context for understanding or choosing an appropriate model for their specific hypotheses. In addition, our review clarifies the challenges and opportunities that confront practicing model users and model developers.://000245296600002/151NF Times Cited:12 Cited References Count:118 0921-2973ISI:000245296600002Scheller, RM Univ Wisconsin, Dept Forest Ecol & Management, 1630 Linden Dr, Madison, WI 53706 USA Univ Wisconsin, Dept Forest Ecol & Management, Madison, WI 53706 USADoi 10.1007/S10980-006-9048-4English |?NkSchindler, Stefan Sebesvari, Zita Damm, Christian Euller, Katrin Mauerhofer, Volker Schneidergruber, Anna Biro, Marianna Essl, Franz Kanka, Robert Lauwaars, Sophie G. Schulz-Zunkel, Christiane van der Sluis, Theo Kropik, Michaela Gasso, Viktor Krug, Andreas Pusch, Martin T. Zulka, Klaus Peter Lazowski, Werner Hainz-Renetzeder, Christa Henle, Klaus Wrbka, Thomas2014^Multifunctionality of floodplain landscapes: relating management options to ecosystem services229-244Landscape Ecology292FebThe concept of green infrastructure has been recently taken up by the European Commission for ensuring the provision of ecosystem services (ESS). It aims at the supply of multiple ESS in a given landscape, however, the effects of a full suite of management options on multiple ESS and landscape multifunctionality have rarely been assessed. In this paper we use European floodplain landscapes as example to develop an expert based qualitative conceptual model for the assessment of impacts of landscape scale interventions on multifunctionality. European floodplain landscapes are particularly useful for such approach as they originally provided a high variety and quantity of ESS that has declined due to the strong human impact these landscapes have experienced. We provide an overview of the effects of floodplain management options on landscape multifunctionality by assessing the effects of 38 floodplain management interventions on 21 relevant ESS, as well as on overall ESS supply. We found that restoration and rehabilitation consistently increased the multifunctionality of the landscape by enhancing supply of provisioning, regulation/maintenance, and cultural services. In contrast, conventional technical regulation measures and interventions related to extraction, infrastructure and intensive land use cause decrease in multifunctionality and negative effects for the supply of all three aspects of ESS. The overview of the effects of interventions shall provide guidance for decision makers at multiple governance levels. The presented conceptual model could be effectively applied for other landscapes that have potential for a supply of a high diversity of ESS.!://WOS:000331935100005Times Cited: 3 0921-2973WOS:00033193510000510.1007/s10980-014-9989-y|?L zSchipper, Aafke M. Koffijberg, Kees van Weperen, Marije Atsma, Guido Ragas, Ad M. J. Hendriks, A. Jan Leuven, Rob S. E. W.2011eThe distribution of a threatened migratory bird species in a patchy landscape: a multi-scale analysis397-410Landscape Ecology263Mar=Understanding the driving forces behind the distribution of threatened species is critical to set priorities for conservation measures and spatial planning. We examined the distribution of a globally threatened bird, the corncrake (Crex crex), in the lowland floodplains of the Rhine River, which provide an important breeding habitat for the species. We related corncrake distribution to landscape characteristics (area, shape, texture, diversity) at three spatial scales: distinct floodplain units ("floodplain scale"), circular zones around individual observations ("home range scale"), and individual patches ("patch scale") using logistic regression. Potential intrinsic spatial patterns in the corncrake data were accounted for by including geographic coordinates and an autocovariate as predictors in the regression analysis. The autocovariate was the most important predictor of corncrake occurrence, probably reflecting the strong conspecific attraction that is characteristic of the species. Significant landscape predictors mainly pertained to area characteristics at the patch scale and the home range scale; the probability of corncrake occurrence increased with potential habitat area, patch area, and nature reserve area. The median potential habitat patch size associated with corncrake occurrence was 11.3 ha; 90% of the corncrake records were associated with patches at least 2.2 ha in size. These results indicate that the corncrake is an area-sensitive species, possibly governed by the males' tendency to reside near other males while maintaining distinct territories. Our results imply that corncrake habitat conservation schemes should focus on the preservation of sufficient potential habitat area and that existing management measures, like delayed mowing, should be implemented in relatively large, preferably contiguous areas.!://WOS:000288808100008Times Cited: 1 0921-2973WOS:00028880810000810.1007/s10980-010-9566-y j07 rSchippers, P. Grashof-Bokdam, C. J. Verboom, J. Baveco, J. M. Jochem, R. Meeuwsen, H. A. M. Van Adrichem, M. H. C.2009~Sacrificing patches for linear habitat elements enhances metapopulation performance of woodland birds in fragmented landscapes 1123-1133Landscape Ecology248SpringerJUniv, Wageningen Res Ctr, Landscape Ctr N. L. A. A. Wageningen NetherlandskSLOSS Woodland birds Linear elements Hedgerows Patch size Metapopulation Dispersal Synergy Landscape designOctvIt is generally assumed that large patches of natural habitat are better for the survival of species than the same amount of habitat in smaller fragments or linear elements like hedges and tree rows. We use a spatially explicit individual-based model of a woodland bird to explore this hypothesis. We specifically ask whether mixtures of large, small and linear habitat elements are better for population performance than landscapes that consist of only large elements. With equal carrying capacity, metapopulations perform equally or better in heterogeneous landscape types that are a mix of linear, large and small habitat elements. We call this increased metapopulation performance of large and small elements "synergy". These mixed conditions are superior because the small linear elements facilitate dispersal while patches secure the population in the long run because they have a lower extinction risk. The linear elements are able to catch and guide dispersing animals which results in higher connectivity between patches leading to higher metapopulation survival. Our results suggest that landscape designers should not always seek to conserve and create larger units but might better strive for more variable landscapes with mixtures of patch sizes and shapes. This is especially important when smaller units play a key role in connecting patches and dispersal through the matrix is poor.://000269913600010ISI Document Delivery No.: 495RV Times Cited: 1 Cited Reference Count: 42 Schippers, Peter Grashof-Bokdam, Carla J. Verboom, Jana Baveco, Johannes M. Jochem, Rene Meeuwsen, Henk A. M. Van Adrichem, Marjolein H. C. 0921-2973 DORDRECHT2009 Landsc. Ecol.ISI:000269913600010Landscape ecologyzSchippers, P, Univ Wageningen & Res Ctr, Landscape Ctr, POB 47, NL-6700 AA Wageningen, Netherlands. peter.schippers@wur.nl10.1007/s10980-008-9313-9English|?@ 5Schleicher, Andrea Biedermann, Robert Kleyer, Michael2011WDispersal traits determine plant response to habitat connectivity in an urban landscape529-540Landscape Ecology264AprIdentification of trait syndromes that make species vulnerable to habitat fragmentation is essential in predicting biodiversity change. Plants are considered particularly vulnerable if their capacities for persistence in and for dispersal among local habitats are low. Here we investigated the influence of easily measured functional traits on the presence of 45 plant species in an urban landscape in north-west Germany where patches were separated by distances consistent with regular plant dispersal range. To describe the spatial configuration of patches we calculated species-specific patch connectivities. Then we assessed plant connectivity responses in distribution models calculated from connectivities and environmental predictors. Twenty (45%) of the analysed species showed a positive connectivity response after accounting for species-specific habitat requirements. These species differed from non-responsive species by functional traits associated with dispersal, including reduced seed numbers and higher terminal velocities relative to non-responsive species. Persistence traits played however no role which we attribute to the environmental conditions of urban habitats and their spatiotemporal characteristics. Our study underlines that even ruderal plants experience dispersal limitation and demonstrates that easily measured functional traits may be used as indicators of fragmentation vulnerability in urban systems allowing generalizations to larger species sets.!://WOS:000288807300007Times Cited: 1 0921-2973WOS:00028880730000710.1007/s10980-011-9579-1_<7Schmidt, E. Bock, C. E.2005eHabitat associations and population trends of two hawks in an urbanizing grassland region in Colorado469-478Landscape Ecology204birds; Buteo; exurbanization; grasslands; hawks; open space; population trends; urbanization OPEN-SPACE GRASSLANDS; LANDSCAPE; ABUNDANCE; CONSERVATION; BIODIVERSITY; SUBURBAN; PEOPLEArticleMayeDespite increasing interest in the ecological effects of urbanization, relatively little is known about its effects in grasslands. We examined population trends and habitat associations of two predators, the rough-legged hawk (Buteo lagopus) and the red-tailed hawk (B. jamaicensis), in a rapidly urbanizing grassland region at the western edge of the North American Great Plains. Count data indicate that rough-legged hawk populations declined in the area by nearly 75% between 1971 and 2003, at the same time that numbers of red-tailed hawks more than tripled. These changes were not part of wider regional trends, nor were they buffered by developnient of an open space system in one of the urbanizing counties. While the human population grew steadily over the 33-year period, hawk numbers did not begin to change significantly until the early 1980s, suggesting landscape threshold responses to development. Rough-legged hawks remaining in the area between 1999 and 2002 avoided human settlements and hunted in places with tracts of treeless grassland. In contrast.. red-tailed hawks selected relatively tall perches in trees or on utility poles from which to hunt. in areas closer to buildings and roads than randomly selected plots, and remained abundant in the mosaic of developed and rural agricultural lands. The failure of the grassland open space system to sustain the rough-legged hawk, and other bird species characteristic of treeless open prairie, illustrates the challenges of conserving fauna with apparent hypersensitivity to the three-dimensional habitat complexity that accompanies even modest amounts of development.://000233035100008 fISI Document Delivery No.: 980RE Times Cited: 0 Cited Reference Count: 40 Cited References: *CO DIV WILDL, 2000, NAT DIV INF SOURC CO *NAT AUD SOC, 2003, CHRISTM BIRD COUNT *SAS I, 1999, STATV 5 0 1 *US BUR CENS, 2000, CENS 2000 DAT US BECHARD MJ, 2002, BIRDS N AM, V641 BERRY ME, 1998, CONDOR, V100, P601 BETTS ND, 1913, U COLORADO STUDIES, V10, P177 BOCK CE, 1999, STUDIES AVIAN BIOL, V19, P131 BOCK CE, 2002, CONSERV BIOL, V16, P1653 BOCK J, 1998, NEURAL PLAST, V6, P17 BOSAKOWSKI T, 1997, J RAPTOR RES, V31, P26 BUTCHER GS, 1990, WILDLIFE SOC B, V18, P129 DAILY GC, 2001, ECOL APPL, V11, P1 GARRISON BA, 1993, J FIELD ORNITHOL, V64, P566 GRIMM NB, 2000, BIOSCIENCE, V50, P571 HAIRE SL, 2000, LANDSCAPE URBAN PLAN, V48, P65 HENDERSON J, 1909, U COLORADO STUD, V6, P219 JOHNSON WC, 2004, BIOL CONSERV, V115, P487 JONES ZF, 2002, CONDOR, V104, P643 LONG ME, 1996, NATL GEOGR, V190, P80 LUCK GW, 2004, P NATL ACAD SCI USA, V101, P182 MAESTAS JD, 2003, CONSERV BIOL, V17, P1425 MARZLUFF JM, 2001, AVIAN ECOLOGY CONSER MCDONNELL MJ, 1990, ECOLOGY, V71, P1232 MILLER JR, 2001, AVIAN ECOLOGY CONSER, P117 MILLER JR, 2002, CONSERV BIOL, V16, P330 MUTEL CF, 1992, GRASSLAND GLACIER NA PRESTON CR, 1993, BIRDS N AM, V52 PRESTON CR, 1996, RAPTORS HUMAN LANDSC, P365 ROSENZWEIG ML, 2003, WIN WIN ECOLOGY EART SAMSON FB, 1996, PRAIRIE CONSERVATION SAUER JR, 1990, 90 US FISH WILDL SER SCHNELL GD, 1968, CONDOR, V70, P373 STOUT WE, 1998, J RAPTOR RES, V32, P221 THEOBALD DM, 2003, CONSERV BIOL, V17, P1624 THEOBALD DM, 2004, FRONT ECOL ENVIRON, V2, P139 VESTAL AG, 1914, BOT GAZ, V58, P377 WELKOWITZ J, 1991, INTRO STAT BEHAV SCI WITH KA, 1995, ECOLOGY, V76, P2446 ZAZLOWSKY D, 1995, WILDERNESS, V58, P25 0921-2973 Landsc. Ecol.ISI:000233035100008Univ Colorado, Dept Ecol & Evolutionary Biol, Boulder, CO 80309 USA. Bock, CE, Univ Colorado, Dept Ecol & Evolutionary Biol, Boulder, CO 80309 USA. carl.bock@colorado.eduEnglish? RSchmidt, Paige McCleery, Robert Lopez, Roel Silvy, Nova Schmidt, Jason Perry, Neil2011Influence of patch, habitat, and landscape characteristics on patterns of Lower Keys marsh rabbit occurrence following Hurricane Wilma 1419-1431Landscape Ecology2610Springer NetherlandsEarth and Environmental ScienceDegradation of coastal systems has led to increased impacts from hurricanes and storm surges and is of concern for coastal endemics species. Understanding the influence of disturbance on coastal populations like the endangered Lower Keys marsh rabbit ( Sylvilagus palustris hefneri ) is important to understanding long-term dynamics and for recovery planning. We evaluated the effect of disturbance on the rabbits by determining which patch, habitat, and landscape characteristics influenced habitat use following Hurricane Wilma. We determined patch-level occurrence 6–9 months prior to Hurricane Wilma, within 6 months following the hurricane, and 2 years after the storm to quantify rates of patch abandonment and recurrence. We observed high patch abandonment (37.5% of used patches) 6 months after Hurricane Wilma and low rates of recurrence (38.1% of abandoned patches) 2 years after the storm, an indication that this storm further threatened marsh rabbit viability. We found the proportion of salt-tolerant (e.g., mangroves and scrub mangroves) and salt-intolerant (e.g., freshwater wetlands) vegetation within LKMR patches were negatively and positively correlated with probability of patch abandonment, respectively. We found patch size and the number of used patches surrounding abandoned patches were positively correlated with probability of recurrence. We suggest habitat use following this hurricane was driven by the differential response of non-primary habitats to saline overwash and habitat loss from past development that reduced the size and number of local populations. Our findings demonstrate habitat use studies should be conducted following disturbance and should incorporate on-going effects of development and climate change.+http://dx.doi.org/10.1007/s10980-011-9654-7 0921-297310.1007/s10980-011-9654-7/۽7NSchmitt, Kristen2013HMeeting minimum ethical scrutiny: the climate change policy conversation 2049-2050Landscape Ecology2810Springer Netherlands 2013/12/01+http://dx.doi.org/10.1007/s10980-013-9931-8 0921-2973Landscape Ecol10.1007/s10980-013-9931-8English<7-5Schoennagel, T. Turner, M. G. Kashian, D. M. Fall, A.2006vInfluence of fire regimes on lodgepole pine stand age and density across the Yellowstone National Park (USA) landscape 1281-1296Landscape Ecology218'landscape modeling; Pinus contorta var. latifolia; postfire regeneration; stand density; succession; Yellowstone National Park SUB-ALPINE FORESTS; SHIFTING MOSAIC LANDSCAPE; LEAF-AREA; STRUCTURAL DEVELOPMENT; CARBON ALLOCATION; CLIMATE-CHANGE; BOREAL FOREST; PATTERNS; HETEROGENEITY; VARIABILITYArticleNovA probabilistic spatial model was created based on empirical data to examine the influence of different fire regimes on stand structure of lodgepole pine (Pinus contorta var. latifolia) forests across a > 500,000-ha landscape in Yellowstone National Park, Wyoming, USA. We asked how variation in the frequency of large fire events affects (1) the mean and annual variability of age and tree density (defined by postfire sapling density and subsequent stand density) of lodgepole pine stands and (2) the spatial pattern of stand age and density across the landscape. The model incorporates spatial and temporal variation in fire and serotiny in predicting postfire sapling densities of lodgepole pine. Empirical self-thinning and in-filling curves alter initital postfire sapling densities over decades to centuries. In response to a six-fold increase in the probability of large fires (0.003 to 0.018 year), mean stand age declined from 291 to 121 years. Mean stand density did not increase appreciably at high elevations (1,029 to 1,249 stems ha(-1)) where serotiny was low and postfire sapling density was relatively low (1,252 to 2,203 stems ha(-1)). At low elevations, where prefire serotiny and postfire lodgepole pine density are high, mean stand densities increased from 2,807 to 7,664 stems ha(-1). Spatially, the patterns of stand age became more simplified across the landscape, yet patterns of stand density became more complex. In response to more frequent stand replacing fires, very high annual variability in postfire sapling density is expected, with higher means and greater variation in stand density across lodgepole pine landscapes, especially in the few decades following large fires.://000242089300009 h ISI Document Delivery No.: 106GP Times Cited: 0 Cited Reference Count: 62 Cited References: ANHOLD JA, 1996, WEST J APPL FOR, V11, P50 BAKER WL, 1991, ECOL MODEL, V56, P109 BALLING RC, 1992, AGR FOREST METEOROL, V60, P285 BEBI P, 2003, ECOLOGY, V84, P362 BESSIE WC, 1995, ECOLOGY, V76, P747 CHRISTENSEN NL, 1989, BIOSCIENCE, V39, P678 CHUVIECO E, 1999, INT J REMOTE SENS, V20, P2331 CLARK JS, 1991, ECOLOGY, V72, P1102 CLARK JS, 1991, ECOLOGY, V72, P1119 COVINGTON WW, 1994, J FOREST, V92, P39 CRITCHFIELD WB, 1980, WO37 USFS DALE VH, 1989, CAN J FOREST RES, V19, P1581 DALE VH, 2001, BIOSCIENCE, V51, P723 DESPAIN DG, 1990, YELLOWSTONE VEGETATI FALL A, 2001, ECOL MODEL, V141, P1 FOSTER DR, 1998, ECOSYSTEMS, V1, P497 FOWELLS HA, 1965, AGR HDB USDA, V271 FRANKLIN JF, 2002, FOREST ECOL MANAG, V155, P399 GARDNER RH, 1996, GLOBAL CHANGE TERRES, P149 HARMON ME, 1990, SCIENCE, V247, P699 HEINSELMAN ML, 1978, FIRE REGIMES ECOSYST, P7 JAKUBAUSKAS ME, 1996, REMOTE SENS ENVIRON, V56, P118 JOHNSON EA, 1989, ECOLOGY, V70, P1335 JOHNSON EA, 1993, CAN J FOREST RES, V23, P1213 JOHNSON EA, 1994, ADV ECOL RES, V25, P239 JOHNSON EA, 2001, CONSERV BIOL, V15, P1554 KASHIAN DM, 2004, CAN J FOREST RES, V34, P2263 KASHIAN DM, 2005, ECOLOGY, V86, P643 KASHIAN DM, 2005, ECOSYSTEMS, V8, P48 LAMONT BB, 1991, BOT REV, V57, P278 LITTON CM, 2004, ECOL APPL, V14, P460 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MILLSPAUGH SH, 2000, GEOLOGY, V28, P211 MOONEY HA, 1999, TERRESTRIAL BIOSPHER, P141 NEEMAN G, 1999, PLANT ECOL, V145, P235 PARKER AJ, 1994, CAN J FOREST RES, V24, P2020 PEARSON JA, 1984, CAN J FOREST RES, V14, P259 PEARSON SM, 1995, ECOL APPL, V5, P744 PERRY DA, 1977, RN238 USDA PETERSON DL, 1994, MOUNTAIN ENV CHANGIN, P234 PICKETT STA, 1985, ECOLOGY NATURAL DIST RADELOFF VC, 2004, FOREST ECOL MANAG, V189, P133 ROMME WH, 1982, ECOL MONOGR, V52, P199 ROMME WH, 1989, BIOSCIENCE, V39, P695 RYKIEL EJ, 1996, ECOL MODEL, V90, P229 SCHOENNAGEL T, 2003, ECOLOGY, V84, P2967 SCHOENNAGEL T, 2004, BIOSCIENCE, V54, P661 SCHOENNAGEL T, 2004, J VEG SCI, V15, P797 SCHOENNAGEL T, 2005, IN PRESS ECOL APPL SMITH DW, 2003, BIOSCIENCE, V53, P330 SMITH FW, 1999, FOREST SCI, V45, P333 SMITHWICK EAH, 2005, IN PRESS ECOSYSTEMS TAYLOR D, 1972, ECOLOGY, V54, P1394 TINKER DB, 1994, CAN J FOREST RES, V24, P897 TINKER DB, 2003, LANDSCAPE ECOL, V18, P427 TURNER MG, 1994, J VEG SCI, V5, P731 TURNER MG, 1997, ECOL MONOGR, V67, P411 TURNER MG, 1999, INT J WILDLAND FIRE, V9, P21 TURNER MG, 2003, FRONT ECOL ENVIRON, V1, P351 TURNER MG, 2004, ECOSYSTEMS, V7, P751 VEBLEN TT, 1994, J ECOL, V82, P125 WEIR JMH, 2000, ECOL APPL, V10, P1162 0921-2973 Landsc. Ecol.ISI:000242089300009Univ Colorado, Dept Geog, Boulder, CO 80309 USA. Univ Wisconsin, Dept Zool, Madison, WI 53706 USA. Simon Fraser Univ, Sch Resource & Environm Management, Burnaby, BC V5A 1S6, Canada. Schoennagel, T, Univ Colorado, Dept Geog, 260 UCB, Boulder, CO 80309 USA. tschoe@colorado.eduEnglish<7Schooley, R. L. Wiens, J. A.2001GDispersion of kangaroo rat mounds at multiple scales in New Mexico, USA267-277Landscape Ecology163burrows desert rodents Dipodomys spectabilis grazing K-function patch disturbances scale semiarid grasslands spatial point patterns DESERT RODENT COMMUNITY DIPODOMYS-SPECTABILIS CHIHUAHUAN DESERT SPATIAL-ORGANIZATION LONG-TERM GRASSLAND PATTERNS ECOLOGY POPULATION DISTURBANCESArticleAprBurrowing mammals create disturbances that increase the ecological heterogeneity of landscapes. In desert systems, banner-tailed kangaroo rats (Dipodomys spectabilis) construct large mounds that greatly influence the spatial patterning of soils, plants, and animals. The overall effects of the patches generated by D. spectabilis depend on the dispersion patterns of the mounds; these patterns may be sensitive to scale and landscape position. We examined the distribution of D. spectabilis mounds across multiple scales in four 40-ha grassland plots in New Mexico, USA. We used Ripley's K-function for our point-pattern analysis. The dispersion patterns of mounds were generally scale-sensitive but depended somewhat on plot-level densities, which were related to topographic position and grazing history. Mound spacing was either regular or random at small scales (0-50 m), random or aggregated at intermediate scales (50-300 m), and aggregated at large scales (300-3000 m). This scale-dependency of pattern reflected spatial domains in which different biotic (territoriality, dispersal, grazing) and abiotic (soil texture and drainage) factors exerted strong influences. How other organisms perceive the spatial patterning of mounds will depend on the extent of their movements. Patches may appear regular to one species but aggregated to another. The dispersion of D. spectabilis mounds also has implications for the spatial structuring of desert rodent communities. D. spectabilis excludes smaller species of kangaroo rats from areas around their mounds; they create spatial heterogeneity in behavioral dominance that may influence the distribution of subordinate species at multiple scales.://000168194400006 ISI Document Delivery No.: 423TT Times Cited: 7 Cited Reference Count: 60 Cited References: *MATHS, 1997, S PLUS US GUID *USDA, 1988, SOIL SURV SOC COUNT ADAMS ES, 1995, OECOLOGIA, V102, P156 ADDICOTT JF, 1987, OIKOS, V49, P340 ALLRED KW, 1993, FIELD GUIDE GRASSES AMARASEKARE P, 1994, OECOLOGIA, V100, P166 ANDERSEN AN, 1994, OECOLOGIA, V98, P15 ANDERSEN M, 1992, OECOLOGIA, V91, P134 ANDERSEN MC, 1999, J ARID ENVIRON, V41, P147 BAILEY TC, 1995, INTERACTIVE SPATIAL BEST TL, 1972, AM MIDL NAT, V87, P201 BEST TL, 1988, MAMMALIAN SPECIES, V311, P1 BOWERS MA, 1987, OECOLOGIA, V72, P77 BOWERS MA, 1992, OECOLOGIA, V92, P242 BROWN JH, 1990, SCIENCE, V250, P1705 CAMPBELL DJ, 1992, OECOLOGIA, V92, P548 CHEW RM, 1992, J ARID ENVIRON, V22, P375 CRESSIE NA, 1991, STAT SPATIAL DATA CRIST TO, 1996, OIKOS, V76, P301 FIELDS MJ, 1999, J VEG SCI, V10, P123 FRYE RJ, 1983, OECOLOGIA, V59, P74 GETIS A, 1987, ECOLOGY, V68, P473 GORDON DM, 1996, ECOLOGY, V77, P2393 GOSZ JR, 1993, ECOL APPL, V3, P369 GUO QF, 1996, OECOLOGIA, V106, P247 HAASE P, 1995, J VEG SCI, V6, P575 HANSELL MH, 1993, FUNCT ECOL, V7, P5 HAWKINS LK, 1992, J ARID ENVIRON, V23, P199 HESKE EJ, 1993, OECOLOGIA, V95, P520 HUNTLY N, 1988, BIOSCIENCE, V38, P786 JONES CG, 1994, OIKOS, V69, P373 JONES WT, 1984, BEHAV ECOL SOCIOBIOL, V15, P151 JONES WT, 1988, ECOLOGY, V69, P1466 KLAAS BA, 2000, ECOGRAPHY, V23, P246 KOTLIAR NB, 1990, OIKOS, V59, P253 LAWTON JH, 1994, OIKOS, V71, P367 LEHMAN CL, 1997, SPATIAL ECOLOGY ROLE, P185 LEVIN SA, 1992, ECOLOGY, V73, P1943 LIMA SL, 1996, TRENDS ECOL EVOL, V11, P131 MOEUR M, 1993, FOREST SCI, V39, P756 MOORHEAD DL, 1988, AM MIDL NAT, V120, P443 MOROKA N, 1982, J RANGE MANAGE, V35, P707 MUN HT, 1990, J ARID ENVIRON, V18, P165 PARMENTER RR, 1995, DESERT GRASSLAND, P196 PETERSON DL, 1998, ECOLOGICAL SCALE THE RANDALL JA, 1984, BEHAV ECOL SOCIOBIOL, V16, P11 REICH RM, 1998, QUANTITATIVE SPATIAL RIPLEY BD, 1976, J APPL PROBAB, V13, P255 SCHOOLEY RL, 2000, OECOLOGIA, V125, P142 SCHRODER GD, 1975, J MAMMAL, V56, P363 SCHRODER GD, 1979, ECOLOGY, V60, P657 TILMAN D, 1997, SPATIAL ECOLOGY ROLE, P3 VALONE TJ, 1995, J MAMMAL, V76, P428 WASER PM, 1991, ECOLOGY, V72, P771 WHICKER AD, 1988, BIOSCIENCE, V38, P778 WHITFORD WG, 1999, J ARID ENVIRON, V41, P203 WIENS JA, 1985, ECOLOGY NATURAL DIST, P169 WIENS JA, 1989, FUNCT ECOL, V3, P385 WIENS JA, 1989, LANDSCAPE ECOLOGY, V3, P87 WITH KA, 1994, LANDSCAPE ECOL, V9, P25 0921-2973 Landsc. Ecol.ISI:000168194400006Colorado State Univ, Dept Biol, Ft Collins, CO 80523 USA. Schooley, RL, Colorado State Univ, Dept Biol, Ft Collins, CO 80523 USA.EnglishC<7Schooley, R. L. Wiens, J. A.2004SMovements of cactus bugs: patch transfers, matrix resistance, and edge permeability801-810Landscape Ecology1976animal movements; Chelinidea vittiger; Colorado; USA; connectivity; dispersal; fragmentation; habitat boundaries; landscape structure; Opuntia; patchy population LANDSCAPE STRUCTURE; FRAGMENTED LANDSCAPES; HABITAT FRAGMENTATION; DISPERSAL; CONNECTIVITY; BOUNDARIES; RESPONSES; BEHAVIOR; ECOLOGY; METAPOPULATIONArticleIndividual movement is a key process affecting the distribution of animals in heterogeneous landscapes. For specialist species in patchy habitat, a central issue is how dispersal distances are related to landscape structure. We compared dispersal distances for cactus bugs (Chelinidea vittiger) on two naturally fragmented landscapes (:! 4% suitable habitat) with different matrix structures (i.e., vegetation height of nonsuitable habitat between suitable patches). Using mark-release-recapture studies, we determined that most transfers between cactus patches occurred during the mating season. Dispersal distances were reduced by > 50% on the landscape that had reduced structural connectivity due to relatively high matrix structure and low patch density. An experiment with detailed movement pathways demonstrated that greater matrix structure decreased mean step lengths, reduced directionality, and thus decreased net displacement by > 60%. However, habitat edges between two matrix elements that differed substantially in resistance to movement were completely permeable. Therefore, the difference in distributions of dispersal distances between the two landscapes mainly reflected the average resistance of matrix habitat and not the level of matrix heterogeneity per se. Our study highlights the merits of combining estimates of dispersal distances with insights on mechanisms from detailed movement pathways, and emphasizes the difficulty of treating dispersal distances of species as fixed traits independent of landscape structure.://000226384000008  ISI Document Delivery No.: 888OL Times Cited: 9 Cited Reference Count: 51 Cited References: ABERG J, 1995, OECOLOGIA, V103, P265 BAKER M, 1995, CONDOR, V97, P663 BATSCHELET E, 1981, CIRCULAR STAT BIOL COLLINGE SK, 2002, LANDSCAPE ECOL, V17, P647 CONOVER WJ, 1980, PRACTICAL NONPARAMET DEVOL JE, 1973, ENVIRON ENTOMOL, V2, P231 DODD AP, 1940, BIOL CAMPAIGN PRICKL DOOLEY JL, 1998, ECOLOGY, V79, P969 GOODWIN BJ, 2002, CAN J ZOOL, V80, P24 GOODWIN BJ, 2002, OIKOS, V99, P552 HADDAD NM, 1999, AM NAT, V153, P215 HAMLIN JC, 1924, ANN ENTOMOLOGICAL SO, V17, P193 HANSKI I, 2001, DISPERSAL, P283 HARGROVE WW, 1992, LANDSCAPE ECOL, V6, P251 HARRISON S, 1997, METAPOPULATION BIOL, P27 IMS RA, 1997, METAPOPULATION BIOL, P247 JOLY P, 2001, CONSERV BIOL, V15, P239 JONSEN ID, 2001, OECOLOGIA, V127, P287 KINDVALL O, 1999, J ANIM ECOL, V68, P172 KOENIG WD, 2000, CONDOR, V102, P492 KUUSSAARI M, 1996, J ANIM ECOL, V65, P791 LIMA SL, 1996, TRENDS ECOL EVOL, V11, P131 MANN J, 1969, US NATL MUSEUM B, V256 MATTHYSEN E, 1995, OIKOS, V72, P375 MENNECHEZ G, 2003, LANDSCAPE ECOL, V18, P279 MORALES JM, 2002, AM NAT, V160, P531 OKSANEN L, 2001, OIKOS, V94, P27 PETIT S, 1998, AGR ECOSYST ENVIRON, V69, P243 PITHER J, 1998, OIKOS, V83, P166 RICKETTS TH, 2001, AM NAT, V158, P87 RIES L, 2001, J ANIM ECOL, V70, P840 ROLAND J, 2000, ECOLOGY, V81, P1642 SCHNEIDER C, 2003, ECOL ENTOMOL, V28, P252 SCHOOLEY RL, 2002, THESIS COLORADO STAT SCHOOLEY RL, 2003, OIKOS, V102, P559 SCHTICKZELLE N, 2003, J ANIM ECOL, V72, P533 SCHULTZ CB, 2001, ECOLOGY, V82, P1879 STAMPS JA, 1987, AM NAT, V129, P533 TAYLOR PD, 1993, OIKOS, V68, P571 TISCHENDORF L, 2000, OIKOS, V90, P7 TURCHIN P, 1998, QUANTITATIVE ANAL MO VANDERMEER J, 2001, AM MIDL NAT, V145, P188 WIENS JA, 1985, OIKOS, V45, P421 WIENS JA, 1989, LANDSCAPE ECOLOGY, V3, P87 WIENS JA, 1993, ENVIRON ENTOMOL, V22, P709 WIENS JA, 1993, OIKOS, V66, P369 WIENS JA, 1997, OIKOS, V78, P257 WIENS JA, 2001, DISPERSAL, P96 WITH KA, 1995, ECOLOGY, V76, P2446 WOLFF JO, 1997, CONSERV BIOL, V11, P945 WRATTEN SD, 2003, OECOLOGIA, V134, P605 0921-2973 Landsc. Ecol.ISI:000226384000008Colorado State Univ, Dept Biol, Ft Collins, CO 80523 USA. Colorado State Univ, Grad Degree Program Ecol, Ft Collins, CO 80523 USA. Schooley, RL, Colorado State Univ, Dept Biol, Ft Collins, CO 80523 USA. schooley_r@firn.eduEnglish}?ISchulte, L. A. Mladenoff, D. J. Crow, T. R. Merrick, L. C. Cleland, D. T.2007AHomogenization of northern US Great Lakes forests due to land use 1089-1103Landscape Ecology227Aug://000248381900010 0921-2973ISI:000248381900010~?,Schulte, L. A. Rickenbach, M. Merrick, L. C.2008_Ecological and economic benefits of cross-boundary coordination among private forest landowners481-496Landscape Ecology234A significant challenge facing forestry today is managing private forests sustainably in the face of continued ownership fragmentation (i.e., parcelization). Cross-boundary coordination-where forest practices are coordinated across multiple properties-has been proposed as a mechanism by which landscape-level ecological and economic benefits may be accrued in privately-owned landscapes, but few tests of the concept exist. Using a case study approach, we quantify the extent to which ownership-centric forest management is constrained by economies of scale and misses opportunities to achieve ecological objectives in three landscapes in Wisconsin, USA. Methods are based on existing forest management plans and include spatial analysis of patch distributions and shapes, simulation of forest practices, and calculation of net present value over a 20-year horizon. Our results indicate substantial opportunity for cross-boundary coordination: between 62% and 88% of the managed properties within our study landscapes were adjacent to other properties with forest management plans. At a patch scale, coordination can result in ecological benefits that can be accrued into the future (e.g., maintenance of large patches and natural ecosystem boundaries). Because these landscapes are already highly parcelized, however, coordination offers little opportunity to impact the overall landscape-scale structure. Greater economies of scale can also be gained by coordinating forest practices, including increases in the size (16-99%) and volume of timber sales (16-94%), and a modest economic advantage (3-6%). As first steps, investment in data infrastructure and professional training are required to support cross-boundary multi-ownership forest management. More broadly is the need to shift from policies and practices that are largely ownership-centric to those that include and better incorporate landscape-centric perspectives."://WOS:000254250400010 Times Cited: 0WOS:000254250400010(10.1007/s10980-008-9207-x|ISSN 0921-2973w<7m3Schumacher, S. Reineking, B. Sibold, J. Bugmann, H.2006TModeling the impact of climate and vegetation on fire regimes in mountain landscapes539-554Landscape Ecology214climate change; disturbances; fire; landscape model; mountain forest dynamics COLORADO FRONT RANGE; PONDEROSA PINE FORESTS; COARSE WOODY DEBRIS; SUB-ALPINE FOREST; DECOMPOSITION RATES; SPATIALLY EXPLICIT; UNITED-STATES; SUCCESSION; BIOMASS; CONSUMPTIONArticleMay8Assessing the long-term dynamics of mountain landscapes that are influenced by large-scale natural and anthropogenic disturbances and a changing climate is a complex subject. In this study, a landscape-level ecological model was modified to this end. We describe the structure and evaluation of the fire sub-model of the new landscape model LANDCLIM, which was designed to simulate climate-fire-vegetation dynamics. We applied the model to an extended elevational gradient in the Colorado Front Range to test its ability to simulate vegetation composition and the strongly varying fire regime along the gradient. The simulated sequence of forest types along the gradient corresponded to the one observed, and the location of ecotones lay within the range of observed values. The model captured the range of observed fire rotations and reproduced realistic fire size distributions. Although the results are subject to considerable uncertainty, we conclude that LANDCLIM can be used to explore the relative differences of fire regimes between strongly different climatic conditions.://000237487700007 ISI Document Delivery No.: 041WR Times Cited: 1 Cited Reference Count: 66 Cited References: *IPCC, 2001, CONTR WORK GROUP 1 3 *SMA, 2003, ANN SCHW MET ANST *USDS FOR SERV, 2001, AR ROOS NAT FOR GEOG AGEE JK, 1987, CAN J FOREST RES, V17, P697 ALBINI FA, 1976, INT30 USDA FOR SERV ANDERSON MD, 2003, FIRE EFFECTS INFORM APLET GH, 1989, J ECOL, V77, P70 ARNO SF, 2000, RMRSGTR42 USDA FOR S, V2, P97 BAKER WL, 1991, ECOL MODEL, V56, P109 BESSIE WC, 1995, ECOLOGY, V76, P747 BINKLEY D, 2003, FOREST ECOL MANAG, V172, P271 BOTKIN DB, 1993, FOREST DYNAMICS ECOL BROWN JK, 1991, FOREST SCI, V37, P1550 BROWN TJ, 2000, J MICROBIOL METH, V42, P203 BUECHLING A, 2004, CAN J FOREST RES, V34, P1259 BUGMANN H, 1994, THESIS SWISS FEDERAL BUGMANN H, 1998, FOREST ECOL MANAG, V103, P247 BUGMANN H, 2001, FOREST ECOL MANAG, V145, P43 BUGMANN HKM, 2000, ECOL APPL, V10, P95 BURNS RM, 1990, AGR HDB, V654 CHRISTENSEN O, 1977, OIKOS, V28, P177 ELLENBERG H, 1996, VEGETATION MITTELEUR FAHNESTOCK GR, 1983, J FOREST, V81, P653 FINNEY MA, 1998, RMRSRP4 USDA FOR SER GARDNER RH, 1999, SPATIAL MODELING FOR, P1693 HALL SA, 2005, FOREST ECOL MANAG, V208, P189 HARGROVE WW, 2000, ECOL MODEL, V135, P243 HARMON ME, 1986, ADV ECOL RES, V15, P133 HE HS, 1999, ECOLOGY, V80, P81 HE HS, 1999, ECOSYSTEMS, V2, P308 HEFTI R, 1986, ZUSTAND GEFAHRDUNG D HEINIMANN HR, 1998, METHODEN ANAL BEWERT HILLGARTER FW, 1971, THESIS SWISS FEDERAL HOWARD JL, 2003, FIRE EFFECTS INFORM JOHNSON EA, 1992, FIRE VEGETATION DYNA KEANE RE, 1996, INTRP484 USDA FOR SE KEANE RE, 2004, ECOL MODEL, V179, P3 KIPFMUELLER KF, 2000, J BIOGEOGR, V27, P71 KORB JE, 2001, PLANT ECOL, V157, P1 KORNER C, 1998, OECOLOGIA, V115, P445 MACKENSEN J, 2003, AUST J BOT, V51, P27 MEENTEMEYER V, 1978, ECOLOGY, V59, P465 NASH CH, 1996, CAN J FOREST RES, V26, P1859 OLIVER CD, 1996, FOREST STAND DYNAMIC PAULSEN J, 1995, BIOL KOHLENSTOFFVORR PEET RK, 1978, VEGETATIO, V37, P65 PEET RK, 2000, N AM TERRESTRIAL VEG, P75 ROMME WH, 1981, ECOLOGY, V62, P319 ROTHERMEL RC, 1972, INT115 USDA FOR SERV RYAN KC, 1988, CAN J FOREST RES, V18, P1291 SCHROEDER P, 1997, FOREST SCI, V43, P424 SCHUMACHER S, 2004, ECOL MODEL, V180, P175 SCHUMACHER S, 2004, THESIS SWISS FEDERAL SIBOLD JS, 2001, FOREST FIRE REGIME U SIBOLD JS, 2005, SPATIAL TEMPORAL VAR STAUFFER D, 1995, PERKOLATIONSTHEORIE STEINBERG PD, 2002, FIRE EFFECTS INFORM STOHLGREN TJ, 2002, ROCKY MOUNTAIN FUTUR, P203 SWETNAM TW, 1990, SCIENCE, V249, P1017 UCHYTIL RJ, 1991, FIRE EFFECTS INFORM VANWAGNER CE, 1973, CAN J FOREST RES, V3, P373 VEBLEN TT, 1994, J ECOL, V82, P125 VEBLEN TT, 2000, ECOL APPL, V10, P1178 VEBLEN TT, 2000, FOREST FRAGMENTATION, P31 YODA K, 1993, J BIOL OSAKA CITY U, P107 ZUMBUHL G, 1986, NATURRAUM DESSEN NUT, P139 0921-2973 Landsc. Ecol.ISI:000237487700007ETH Zentrum, Dept Environm Sci Forest Ecol, Swiss Fed Inst Technol, CH-8092 Zurich, Switzerland. Univ Colorado, Dept Geog, Boulder, CO 80209 USA. Bugmann, H, ETH Zentrum, Dept Environm Sci Forest Ecol, Swiss Fed Inst Technol, HG G21-3, CH-8092 Zurich, Switzerland. harald.bugmann@ethz.chEnglish'|?.Schumaker, Nathan H. Brookes, Allen Dunk, Jeffrey R. Woodbridge, Brian Heinrichs, Julie A. Lawler, Joshua J. Carroll, Carlos LaPlante, David2014ZMapping sources, sinks, and connectivity using a simulation model of northern spotted owls579-592Landscape Ecology294AprSource-sink dynamics are an emergent property of complex species-landscape interactions. A better understanding of how human activities affect source-sink dynamics has the potential to inform and improve the management of species of conservation concern. Here we use a study of the northern spotted owl (Strix occidentalis caurina) to introduce new methods for quantifying source-sink dynamics that simultaneously describe the population-wide consequences of changes to landscape connectivity. Our spotted owl model is mechanistic, spatially-explicit, individual-based, and incorporates competition with barred owls (Strix varia). Our observations of spotted owl source-sink dynamics could not have been inferred solely from habitat quality, and were sensitive to landscape connectivity and the spatial sampling schemes employed by the model. We conclude that a clear understanding of source-sink dynamics can best be obtained from sampling simultaneously at multiple spatial scales. Our methodology is general, can be readily adapted to other systems, and will work with population models ranging from simple and low-parameter to complex and data-intensive.!://WOS:000333533800003Times Cited: 4 0921-2973WOS:00033353380000310.1007/s10980-014-0004-4?Angelika Schwabe1989nVegetation complexes of flowing-water habitats and their importance for the differentiation of landscape units237-253Landscape Ecology24Wvegetation complexes, running watercourses, Black forest, spatial distribution patternsAn inductive method for recognizing vegetation complexes is presented. These complexes can be used to define landscape units. The method is demonstrated with regard to the river and rivulet valleys of the Black Forest in south-western Germany. It is based on surveys of locally occurring plant communities in homogeneous landscape units, using a cover-abundance scale for the areal extension of each community. The communities have first been established on the basis of the usual releves of small homogeneous plots. The surveys are called sigma relevks (sigma = Greek for sum), Sigma relevCs can be arranged in tables by the usual classification method in order to establish vegetation complexes. Characteristic and differential communities can be elaborated to characterize the vegetation complexes. The specific spatial distribution of each complex reflects certain physical-geographical and anthropo-geographical characteristics. Some applied aspects can be included for each vegetation complex, for example, lists of woody species typical for a landscape unit. From the point of view of water economy such a survey is useful since many efforts are being made to plant woody species in accordance with natural conditions along river and rivulet embankments.۽7 Schwartz, MarkW2013:Strategies for conserving plants through (re) introduction163-164Landscape Ecology281Springer Netherlands 2013/01/01+http://dx.doi.org/10.1007/s10980-012-9823-3 0921-2973Landscape Ecol10.1007/s10980-012-9823-3English?*Schwarz, W.L. Malanson, G.P. Weirich, F.H.1996TEffect of landscape position on the sediment chemistry of abandoned channel wetlands27-38Landscape ecology111Zabandoned channels, floodplain, nitrogen, organic matter, phosphorous, potassium, sediment|7B -Schwarz, W. L. Malanson, G. P. Weirich, F. H.1996TEffect of landscape position on the sediment chemistry of abandoned-channel wetlands27-38Landscape Ecology111abandoned channels floodplain nitrogen organic matter phosphorous potassium sediment rhone river vegetation france forest lakesFeb The nature of sediments in abandoned channels is an important component of their development as floodplain wetlands. The texture, organic matter, phosphorous, potassium, and nitrogen content of sediments were determined for abandoned channels along the Iowa and Cedar Rivers near their confluence in Iowa. Differences in the levels of these constituents were examined among categories of three landscape gradients: present connectivity to the river, time since abandonment, and proximity to agricultural land use. Local scale processes of ecological development are seen in the importance of time for increased organic matter and nitrogen. Basin scale processes of sediment transport and deposition are revealed by the importance of connectivity for decreases in these two elements, and by the counter-intuitive findings for nitrogen and especially phosphorous and potassium in relation to agricultural proximity. Location on a floodplain is important for differentiating development, but it cannot be reduced to univariate gradients.://A1996UN74400003.Un744 Times Cited:16 Cited References Count:39 0921-2973ISI:A1996UN74400003&Univ Iowa,Dept Geog,Iowa City,Ia 52242Englishj<753Schweiger, O. Dormann, C. F. Bailey, D. Frenzel, M.2006Occurrence pattern of Pararge aegeria (Lepidoptera : Nymphalidae) with respect to local habitat suitability, climate and landscape structure989-1001Landscape Ecology217'butterfly; distribution; fragmentation; habitat quality; logistic regression; occurrence probability; predictive habitat model BRITISH BUTTERFLIES; METAPOPULATION DYNAMICS; FRAGMENTED LANDSCAPE; CONSERVATION BIOLOGY; SPATIAL VARIABILITY; MATE LOCATION; MODELS; TEMPERATURE; ECOLOGY; BIODIVERSITYArticleOctDistribution patterns of wild species are affected by environmental variables, such as climate, anthropogenic land use or habitat quality, which act simultaneously at different scales. To examine the relative importance of particular factors and scales on population response we investigated the speckled wood butterfly Pararge aegeria (L.) as a model organism occupying semi-natural habitats. Its distribution was recorded in 23 study sites (5 x 5 km) over a 2 year study period. The sites were located in agricultural landscapes within seven Temperate European countries. Environmental predictors were mapped at a local and a regional scale. Logistic regression models were then developed to represent humid (beneficial) and dry (adverse) weather conditions during larval development. The humid year model predicted that P. aegeria is equally but generally not very dependent on local and regional factors, resulting in generally high occurrence probabilities. In contrast, the dry year model predicted severe restrictions of P. aegeria to both high quality patches and landscapes with beneficial structural and climatic preconditions. As both models resulted in entirely different predictions, our study showed that the sensitivity of P. aegeria to local and landscape features might change, and that factors of less importance could easily become limiting factors. The results stress that high quality landscape is important at both the local and regional scale even for species that are considered relatively robust. They also sound a note of caution when predictions about population response for management purposes are based on just a single or a few year(s) of observation.://000241010900003 ISI Document Delivery No.: 091FA Times Cited: 0 Cited Reference Count: 70 Cited References: *ENV SYST RES I, 2003, ESRI ARCGIS 8 X *IPCC, 1998, REG IMP CLIM CHANG A *R DEV COR TEAM, 2004, R LANG ENV STAT COMP BAGUETTE M, 2003, CR BIOL, V326, P200 BRESLOW NE, 1993, J AM STAT ASSOC, V88, P9 BRUNZEL S, 2002, J INSECT BEHAV, V15, P739 BUGTER RJF, 2001, PUBLICATIONES I GEOG, V92, P632 CHARDON JP, 2003, LANDSCAPE ECOL, V18, P561 COWLEY MJR, 1999, P ROY SOC LOND B BIO, V266, P1587 COWLEY MJR, 2000, J APPL ECOL S1, V37, P60 CRAWLEY MJ, 2002, STAT COMPUTING INTRO CUMMING GS, 2000, J BIOGEOGR, V27, P441 CUSHMAN SA, 2002, LANDSCAPE ECOL, V17, P637 DAVIES NB, 1978, ANIM BEHAV, V26, P138 DUELLI P, 1997, AGR ECOSYST ENVIRON, V62, P81 EBERT G, 1991, SCHMETTERLINGE BADEN FIELDING AH, 1997, ENVIRON CONSERV, V24, P38 GASTON KJ, 1999, OIKOS, V84, P353 GIBSON LA, 2004, J APPL ECOL, V41, P213 HANSKI I, 1997, METAPOPULATION BIOL HANSKI I, 1999, OIKOS, V87, P209 HANSKI I, 2000, NATURE, V404, P755 HERZOG F, 2006, EUR J AGRON, V24, P165 HESSELBARTH G, 1995, TAGFALTER TURKEI HILL JK, 1999, P ROY SOC LOND B BIO, V266, P1197 HILL JK, 2001, ECOL LETT, V4, P313 HIRZEL A, 2002, ECOL MODEL, V157, P331 JEANNERET P, 2003, AGR ECOSYST ENVIRON, V98, P311 KUUSSAARI M, 1996, J ANIM ECOL, V65, P791 LAWTON JH, 1996, OIKOS, V75, P145 LEGATES DR, 1990, INT J CLIMATOL, V10, P111 LEGATES DR, 1990, THEOR APPL CLIMATOL, V41, P11 LEGENDRE P, 1998, NUMERICAL ECOLOGY LEONCORTES JL, 1999, ECOGRAPHY, V22, P643 MACNALLY R, 2000, BIODIVERS CONSERV, V9, P655 MACNALLY R, 2002, BIODIVERS CONSERV, V11, P1397 MANEL S, 2001, J APPL ECOL, V38, P921 MCGARIGAL K, 1995, PNWGTR351 MENNECHEZ G, 2004, OIKOS, V106, P243 MERCKX T, 2003, P ROY SOC LOND B BIO, V270, P1815 MERCKX T, 2005, ANIM BEHAV 2, V70, P411 OPDAM P, 2003, LANDSCAPE ECOL, V18, P113 PARMESAN C, 1999, NATURE, V399, P579 PETERSON TC, 1997, B AM METEOROL SOC, V78, P2837 PETIT S, 2001, OIKOS, V92, P491 POLLARD E, 1988, J APPL ECOL, V25, P819 POLLARD E, 1996, ECOL ENTOMOL, V21, P365 QUINN GP, 2002, EXPT DESIGN DATA ANA ROY DB, 2001, J ANIM ECOL, V70, P201 RUSHTON SP, 2004, J APPL ECOL, V41, P193 SAKAMOTO Y, 1986, AKAIKE INFORM CRITER SETTELE J, 1999, TAGFALTER DEUTSCHLAN SHREEVE TG, 1984, OIKOS, V42, P371 SHREEVE TG, 1986, ECOL ENTOMOL, V11, P229 SHREEVE TG, 1986, ECOL ENTOMOL, V11, P325 SHREEVE TG, 1992, ECOLOGY BUTTERFLIES, P120 SHREEVE TG, 1995, ECOLOGY CONSERVATION, P37 SHREEVE TG, 2004, OIKOS, V106, P404 SUMMERVILLE KS, 2001, ECOLOGY, V82, P1360 THOMAS CD, 1995, BIOL CONSERV, V73, P59 THOMAS CD, 1997, METAPOPULATION BIOL, P359 THOMAS CD, 1999, J ANIM ECOL, V68, P647 THOMAS JA, 2004, SCIENCE, V303, P1879 TILMAN D, 1997, SPATIAL ECOLOGY VANDYCK H, 1997, ANIM BEHAV 1, V53, P39 VENABLES WN, 2002, MODERN APPL STAT S WAGNER HH, 2000, LANDSCAPE ECOL, V15, P219 WARREN MS, 2001, NATURE, V414, P65 WETTSTEIN W, 1999, J APPL ECOL, V36, P363 WIKLUND C, 1983, OIKOS, V40, P53 0921-2973 Landsc. Ecol.ISI:000241010900003yUFZ, Ctr Environm Res Leipzig Halle, Dept Community Ecol, D-06120 Halle, Germany. UFZ, Ctr Environm Res Leipzig Halle, Dept Appl Landscape Ecol, D-06120 Halle, Germany. FAL Swiss Fed Res Stn Agroecol & Agr, CH-8046 Zurich, Switzerland. Schweiger, O, UFZ, Ctr Environm Res Leipzig Halle, Dept Community Ecol, Theodor Lieser Str 4, D-06120 Halle, Germany. oliver.schweiger@ufz.deEnglish~?#Schwemmer, P. Garthe, S. Mundry, R.2008}Area utilization of gulls in a coastal farmland landscape: habitat mosaic supports niche segregation of opportunistic species355-367Landscape Ecology233The intensively farmed coastal lowland landscape of Germany, adjacent to the North Sea, provides important foraging opportunities for Black-headed, Common, Herring and Lesser Black-backed gull (Larus ridibundus, L. canus, L. argentatus and L. fuscus). We expected that spatial and temporal utilization of the landscape mosaic as well as behavioural traits and utilization of food resources would differ between these closely related species, facilitating niche segregation. We recorded habitat types and their utilization by the four species over a whole year. Furthermore, we related species abundance to several abiotic parameters. Black-headed and Common gulls were the most numerous species in the study area throughout the year. In general, the former species preferred bare fields with recently prepared soils and was often associated with tractors in the fields, whereas the latter species was most often found on pastures. Black-headed gulls seem to have a higher ability to exploit ephemeral, food sources associated with human activities whereas common gulls prefer habitats with low human activity and with naturally distributed prey. The most prominent abiotic parameter influencing gull abundance was presence of tractors. Black-headed gulls have most likely benefited from recent changes in agricultural practice, particularly the increase in cropped land, while Common gulls may have suffered from a decline in pastures. At present, utilization of the farmland habitat mosaic leads to niche segregation and supports coexistence, as two of the four gull species mainly forage in the marine environment, while there is significant habitat partitioning between the other two temporally, spatially and behaviourally."://WOS:000254112100009 Times Cited: 0WOS:000254112100009(10.1007/s10980-008-9194-y|ISSN 0921-2973"? Scott, Charles2011CLindenmayer DB and Likens GE (eds): Effective ecological monitoring 1505-1506Landscape Ecology2610Springer NetherlandsEarth and Environmental Science+http://dx.doi.org/10.1007/s10980-011-9658-3 0921-297310.1007/s10980-011-9658-3<7Seagle, S. W. McNaughton, S. J.1992gSpatial variation in forage nutrient concentrations and the distribution of Serengeti grazing ungulates229-241Landscape Ecology74BSERENGETI; UNGULATES; NUTRITIONAL REQUIREMENTS; LANDSCAPE; GRAZINGArticleDecResident grazing ungulates in the Serengeti National Park, Tanzania, are conspicuously patchy in their distribution among regions of the Park. Linear programming models that maximize nitrogen (N) consumption by foraging ungulates in Serengeti regions having high and low resident animal densities were compared using forage ingestion rate and twelve nutritional requirements as simultaneously imposed constraints on forage choice. Model results indicate that (1) growing season N or crude protein is not limiting in either region although greater N ingestion is possible within the eastern corridor under other nutritional constraints, (2) grazing ungulates in the eastern corridor region occur in greater density and are capable of balancing dietary requirements solely from forage while simultaneously consuming more protein than ungulates in the northeast region, and (3) rarer landscape elements are most capable of providing ungulate dietary requirements in both the northeast and eastern corridor. These results provide a nutritional basis to understand patchy spatial distributions of grazers within Serengeti regions and landscapes, and provide a partial test of the hypothesis that large generalist herbivores should graze rare forages more frequently. The ability of uncommon landscape elements to support ungulate grazing over the growing season is supported by previous ecosystem studies that demonstrate the capability of grass forages for compensatory growth and the ability of grazing to stimulate rapid nutrient recycling.://A1992KD83100001 IISI Document Delivery No.: KD831 Times Cited: 24 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1992KD83100001FSEAGLE, SW, UNIV MARYLAND,APPALACHIAN ENVIRONM LAB,FROSTBURG,MD 21532.Englishx|?YSebert-Cuvillier, E. Simon-Goyheneche, V. Paccaut, F. Chabrerie, O. Goubet, O. Decocq, G.2008sSpatial spread of an alien tree species in a heterogeneous forest landscape: a spatially realistic simulation model787-801Landscape Ecology237The effect of environmental heterogeneity on spatial spread of invasive species has received little attention in the literature. Altering landscape heterogeneity may be a suitable strategy to control invaders in man-made landscapes. We use a population-based, spatially realistic matrix model to explore mechanisms underlying the observed invasion patterns of an alien tree species, Prunus serotina Ehrh., in a heterogeneous managed forest. By altering several parameters in the simulation, we test for various hypotheses regarding the role of several mechanisms on invasion dynamics, including spatial heterogeneity, seed dispersers, site of first introduction, large-scale natural disturbances, and forest management. We observe that landscape heterogeneity makes the invasion highly directional resulting from two mechanisms: (1) irregular jumps, which occur rarely via long-distance dispersers and create new founder populations in distant suitable areas, and (2) regular, continuous diffusion toward adjacent cells via short- and mid-distance vectors. At the landscape scale, spatial heterogeneity increases the invasion speed but decreases the final invasion extent. Hence, natural disturbances (such as severe storms) appear to facilitate invasion spread, while forest management can have contrasting effects such as decreasing invasibility at the stand scale by increasing the proportion of light interception at the canopy level. The site of initial introduction influences the invasion process but without altering the final outcome. Our model represents the real landscape and incorporates the range of dispersal modes, making it a powerful tool to explore the interactions between environmental heterogeneity and invasion dynamics, as well as for managing plant invaders.!://WOS:000258540300003Times Cited: 0 0921-2973WOS:00025854030000310.1007/s10980-008-9237-4 <7 8Segoli, M. Ungar, E. D. Giladi, I. Arnon, A. Shachak, M.2012[Untangling the positive and negative effects of shrubs on herbaceous vegetation in drylands899-910Landscape Ecology276landscape modulator multiple-layer landscape diversity competition facilitation sarcopoterium spinosum ecosystem engineer ecosystem engineers sarcopoterium-spinosum soil-moisture facilitation plant patterns desert annuals interference environmentsJulWoody vegetation, as an ecosystem engineer, can modulate the landscape such that the levels of resources in its vicinity undergo positive and negative changes as far as the herbaceous vegetation is concerned. To better understand how these processes play out in a semi-arid ecosystem, we examined resource modulation by woody vegetation, and the response of herbaceous vegetation to that modulation, at a fine spatial scale. Experimental manipulations were employed to separate the positive and negative effects of water, light and seed dispersal in determining herbaceous species density and biomass in three patch types within and adjacent to the shrub (core, periphery and open). We synthesized our results into a multilayered landscape diversity (MLLD) model. Woody vegetation creates distinct multilayered resource patches at its core and periphery which do not correspond to the dichotomous structural pattern of shrub canopy versus intershrub background. The combined effect of these multilayered resource patches had higher herbaceous species density (8.2 vs. 4.0 species 400 cm(-2)) and herbaceous biomass (5.4 vs. 1.0 g 400 cm(-2)) in the periphery than in the core (3-yr averages). The periphery's net positive effects are due to enhancement of soil properties (water infiltration depth of 11.1 cm at periphery vs. 8.1 cm at core), while the core's net negative effects are due to modulation of seed (seed abundance per seed trap of 44.2 at periphery vs. 3.0 at core) and light availability (PAR transmittance of 41.9 % at periphery vs. 16.5 % at core) by the shrub canopy. Thus, when examined at this fine spatial resolution, woody vegetation has both net positive and net negative effects on herbaceous vegetation. Analysis of our results by means of the MLLD model emphasizes the importance of examining the landscape at the spatial scale of the modulated resources and of recognizing different patch types and their differing effects on herbaceous vegetation.://000305218000009-958DZ Times Cited:0 Cited References Count:52 0921-2973Landscape EcolISI:000305218000009GSegoli, M Univ Calif Davis, Dept Plant Sci, 1 Shields Ave, Davis, CA 95616 USA Univ Calif Davis, Dept Plant Sci, 1 Shields Ave, Davis, CA 95616 USA Ben Gurion Univ Negev, Mitrani Dept Desert Ecol, BIDR, IL-84990 Sede Boqer, Israel Agr Res Org, Volcani Ctr, Dept Agron & Nat Resources, Inst Plant Sci, IL-50250 Bet Dagan, IsraelDOI 10.1007/s10980-012-9736-1Englishڽ7.Segurado, Pedro Branco, Paulo Ferreira, MariaT2013UPrioritizing restoration of structural connectivity in rivers: a graph based approach 1231-1238Landscape Ecology287Springer NetherlandsQConnectivity Conservation planning Fishes Graph theory Portugal Restoration River 2013/08/01+http://dx.doi.org/10.1007/s10980-013-9883-z 0921-2973Landscape Ecol10.1007/s10980-013-9883-zEnglish n<7c-Selinger-Looten, R. Grevilliot, E. Muller, S.1999yStructure of plant communities and landscape patterns in alluvial meadows of two flood plains in the north-east of France213-229Landscape Ecology142iflood plain French alluvial meadows landscape structure land use regional comparison ECOLOGY BIODIVERSITYArticleAprFlood frequency and agricultural pressure can effect pattern and diversity in the plant communities and the landscape of flood plain meadows. The flood plains of north-east France are valuable semi-natural ecosystems with a high diversity of plants. This study was carried out in two valleys with plant communities showing the same zonation along a moisture gradient. About 350 measurements in each valley were carried out on 50 m(2) sampling sites, Two study areas were intensively measured within each of the two valleys (1300 ha in total). Hydrological, geological and human factors have determined the unique landscape pattern of each valley. Using vegetation maps (1/5000) of the two valleys, landscape structure in terms of the size, number and form of patches were compared and the characteristics of the disturbance regimes (natural and human disturbance) creating each landscape are analysed. Variations of landscape indices are discussed in relation to the increase in agricultural pressure. Using quantitative parameters of landscape ecology to analyse vegetation mosaics provides an assessment of agricultural pressure and natural constraints on the flood plain scale. Agricultural intensification led to a decrease of meadow complexity whose natural rough shapes are made straight. Moreover flooded meadows lost thus natural connectivity with ditches and river which determined biodiversity and ecological processes of flood plains.://000079802500010 _ISI Document Delivery No.: 187RV Times Cited: 3 Cited Reference Count: 28 Cited References: ALARD D, 1994, J ENVIRON MANAGE, V42, P91 AMBROISE R, 1992, REFLEXION MISSION PA AMOROS C, 1993, HYDROSYSTEMES FLUVIA BANASOVA V, 1994, EKOLOGIA BRATISLAVA, V1, P125 BASTIAN O, 1993, LANDSCAPE ECOL, V8, P139 BRANDT J, 1985, P IGU DESSAU, P52 BROYER J, 1994, ALAUDA, V59, P129 BROYER J, 1995, ECOLOGIE, V26, P45 CARBIENER R, 1969, B SOC IND MULHOUSE, V734, P15 DELPECH R, 1989, 5 C NAT EC FRANC REC, P151 DUVIGNEAUD J, 1958, B SOC ROY BOT BELG, V91, P7 FORMAN RTT, 1986, LANDSCAPE ECOLOGY GREEN BH, 1990, GRASS FORAGE SCI, V45, P365 GREVILLIOT F, 1996, THESIS U METZ LUBCHENCO J, 1991, ECOLOGY, V72, P371 NAIMAN RJ, 1993, ECOL APPL, V3, P209 OTAHELOVA H, 1994, MONITORING ECOLOGICA, P121 POTT R, 1992, GARTENBAUWISSENSCHAF, V57, P157 RISSER PG, 1984, ILLINOIS NATURAL HIS, V2 RISSER PG, 1992, ECOSYSTEM REHABILITA, V1, P37 SCHLACHT H, 1987, NATUROPA, P21 SELINGER R, 1995, DETERMINISME BIODIVE TRABAUD L, 1996, LANDSCAPE ECOL, V11, P215 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 VANDIGGELEN R, 1995, Z KULTURTECHNIK LAND, V36, P125 WEDIN DA, 1990, OECOLOGIA, V84, P433 WIENS JA, 1989, FUNCT ECOL, V3, P385 WIENS JA, 1993, OIKOS, V66, P369 0921-2973 Landsc. Ecol.ISI:000079802500010UFR Sci, Unite Rech EBSE, Lab Phytoecol, F-57045 Metz 01, France. Selinger-Looten, R, UFR Sci, Unite Rech EBSE, Lab Phytoecol, Ile Saulcy, F-57045 Metz 01, France.English|?# (Selonen, V. Hanski, I. K. Desrochers, A.20105Measuring habitat availability for dispersing animals331-335Landscape Ecology253Understanding dispersal is central to ecology and evolution. To integrate habitat selection and dispersal it is important to compare habitat used for movement to those available in the landscape, i.e. found in an area that an animal could access in a given time period. Here, we explore ways of determining available habitat for dispersing individuals, illustrated by recent studies on habitat selection of dispersers.!://WOS:000275122600001Times Cited: 1 0921-2973WOS:00027512260000110.1007/s10980-009-9432-y<77Sengupta, R. Middleton, B. Yan, C. Zuro, M. Hartman, H.2005xLandscape characteristics of Rhizophora mangle forests and propagule deposition in coastal environments of Florida (USA)63-72Landscape Ecology201$coastal wetlands; dispersal; fragmentation; GIS; landscape connectivity; modeling; recruitment limitation; remote sensing; restoration ecology AVICENNIA-MARINA PROPAGULES; MANGROVE FOREST; SATELLITE DATA; EARLY GROWTH; SEED BANKS; DISPERSAL; RECRUITMENT; CONNECTIVITY; REGENERATION; AUSTRALIAArticleJanField dispersal studies are seldom conducted at regional scales even though reliable information on mid-range dispersal distance is essential for models of colonization. The purpose of this study was to examine the potential distance of dispersal of Rhizophora mangle propagules by comparing deposition density with landscape characteristics of mangrove forests. Propagule density was estimated at various distances to mangrove sources (R. mangle) on beaches in southwestern Florida in both high-and low-energy environments, either facing open gulf waters vs. sheltered, respectively. Remote sensing and Geographic Information Systems were used to identify source forests and to determine their landscape characteristics (forest size and distance to deposition area) for the regression analyses. Our results indicated that increasing density of propagules stranded on beaches was related negatively to the distance of the deposition sites from the nearest stands of R. mangle and that deposition was greatly diminished 2 kin or more from the source. Measures of fragmentation such as the area of the R. mangle forests were related to propagule deposition but only in low-energy environments. Our results suggest that geographic models involving the colonization of coastal mangrove systems should include dispersal dynamics at mid-range scales, i.e., for our purposes here, beyond the local scale of the forest and up to 5 kin distant. Studies of mangrove propagule deposition at various spatial scales are key to understanding regeneration limitations in natural gaps and restoration areas. Therefore, our study of mid-range propagule dispersal has broad application to plant ecology, restoration, and modeling.://000231223900005 = ISI Document Delivery No.: 955KD Times Cited: 3 Cited Reference Count: 62 Cited References: *ESRI, 1999, ARCV GIS 3 2 *SAS I INC, 1997, SAS JMP VERS 3 2 1 *USDA, 2003, INT TAX INF SYST BLASCO F, 1986, P 20 INT S REM SENS, V3, P1465 BUCHANAN RA, 1989, BUSH REVEGETATION CHAN HT, 1985, MALAYSIAN FORESTER, V48, P324 CLARK JS, 1999, AM J BOT, V86, P1 CLARKE PJ, 1991, AUST J BOT, V39, P77 CLARKE PJ, 1993, AQUAT BOT, V45, P195 CLARKE PJ, 1993, OECOLOGIA, V93, P548 CLARKE PJ, 2000, BIOTROPICA, V32, P642 CLARKE PJ, 2001, J ECOL, V89, P648 CLARKE PJ, 2002, J ECOL, V90, P728 CLARKE PJ, 2004, J ECOL, V92, P203 DAVIS JH, 1940, PAP TORTUGAS LAB, V32, P304 DELANGE WP, 1994, J COASTAL RES, V10, P539 DOAK DF, 1994, ECOLOGY, V75, P615 DODD RS, 2000, NEW PHYTOL, V145, P115 DODD RS, 2002, TREES-STRUCT FUNCT, V16, P80 DREXLER J, 2001, PAC SCI, V55, P17 DUKE NC, 1992, TROPICAL MANGROVE EC, P63 DUKE NC, 2001, WETLANDS ECOLOGY MAN, V9, P257 EBBESMEYER CC, 1992, EOS T AM GEOPHYS UN, V73, P361 FEHRING WK, 1985, P TAMP BAY AR SCI IN, P512 GAO J, 1999, INT J REMOTE SENS, V20, P2823 GREEN EP, 1998, INT J REMOTE SENS, V19, P935 GU WD, 2002, LANDSCAPE ECOL, V17, P699 GUPPY HB, 1906, OBSERVATIONS NATURAL, V2 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 HARPER JL, 1977, POPULATION BIOL PLAN HIGGINS SI, 2003, ECOLOGY, V84, P1945 JENSEN JR, 1991, GEOCARTO INT, V2, P13 LEWIS RR, 1977, P 2 ANN C COAST SOC, P31 LEWIS RR, 1986, NEW COLL ENV STUDIES, V37, P159 LEWIS RR, 1990, WETLAND CREATION RES, P73 LONG BG, 1996, ESTUAR COAST SHELF S, V43, P373 MACARTHUR RH, 1967, THEORY ISLAND BIOGEO MANSON FJ, 2001, MAR FRESHWATER RES, V52, P787 MANSON FJ, 2003, ESTUARINE COASTAL SH, V57, P657 MCGUINNESS KA, 1997, OECOLOGIA, V109, P80 MIDDLETON B, 2000, PLANT ECOL, V146, P169 MIDDLETON BA, 1999, WETLAND RESTORATION MIDDLETON BA, 2003, J APPL ECOL, V40, P1025 MINCHINTON TE, 2001, J ECOL, V89, P888 MURRAY DR, 1986, SEED DISPERSAL NATHAN R, 2001, ENCY BIODIVERSITY, P127 NOSS RF, 1986, ENVIRON MANAGE, V10, P299 ODUM WE, 1990, ECOSYSTEMS FLORIDA, P517 PITHER J, 1998, OIKOS, V83, P166 RABINOWITZ D, 1978, J BIOGEOGR, V5, P113 RIDLEY HN, 1930, DISPERSAL PLANTS WOR SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SOKAL RR, 1995, BIOMETRY SOUSA WP, 2003, OECOLOGIA, V137, P436 STEINKE TD, 1975, P INT S BIOL MAN MAN, V2, P404 TAYLOR PD, 1993, OIKOS, V68, P571 TISCHENDORF L, 2000, LANDSCAPE ECOL, V15, P633 TOMLINSON PB, 1986, BOT MANGROVES TYAGI AP, 2003, WETLANDS ECOLOGY MAN, V11, P167 WITH KA, 1995, ECOLOGY, V76, P2446 WOLANSKI E, 1992, HYDROBIOLOGIA, V247, P141 ZANN LP, 1995, OUR SEA OUR FUTURE S 0921-2973 Landsc. Ecol.ISI:000231223900005HSo Illinois Univ, Dept Plant Biol, Carbondale, IL 62901 USA. So Illinois Univ, Dept Geog, Carbondale, IL 62901 USA. McGill Univ, Dept Geog, Montreal, PQ H3A, Canada. US Geol Survey, Natl Wetlands Res Ctr, Lafayette, LA 70506 USA. Middleton, B, So Illinois Univ, Dept Plant Biol, Carbondale, IL 62901 USA. beth_middleton@usgs.govEnglishP<7Seto, K. C. Fragkias, M.2005wQuantifying spatiotemporal patterns of urban land-use change in four cities of China with time series landscape metrics871-888Landscape Ecology207China; Landsat TM; landscape pattern metrics; Pearl River Delta; spatiotemporal patterns; time series landscape metrics analysis; urban growth; urbanization PEARL RIVER DELTA; GRADIENT ANALYSIS; TM DATA; TRANSFORMATION; SHANGHAI; GLOBALIZATION; SIMULATION; ECONOMICS; ARIZONA; SPRAWLArticleNovThis paper provides a dynamic inter- and intra-city analysis of spatial and temporal patterns of urban land-use change. It is the first comparative analysis of a system of rapidly developing cities with landscape pattern metrics. Using ten classified Landsat Thematic Mapper images acquired from 1988 to 1999, we quantify the annual rate of urban land-use change for four cities in southern China. The classified images were used to generate annual maps of urban extent, and landscape metrics were calculated and analyzed spatiotemporally across three buffer zones for each city for each year. The study shows that for comprehensive understanding of the shapes and trajectories of urban expansion, a spatiotemporal landscape metrics analysis across buffer zones is an improvement over using only urban growth rates. This type of analysis can also be used to infer underlying social, economic, and political processes that drive the observed urban forms. The results indicate that urban form can be quite malleable over relatively short periods of time. Despite different economic development and policy histories, the four cities exhibit common patterns in their shape, size, and growth rates, suggesting a convergence toward a standard urban form.://000233036300008  ISI Document Delivery No.: 980RQ Times Cited: 5 Cited Reference Count: 56 Cited References: *STAT BUR GUANGD, 2001, STAT YB GUANGD *UN, 2002, WORLD URB PROSP 2001 *UNCHS, 2002, STAT WORLDS CIT REP ALONSO W, 1964, LOCATION LAND USE ANAS A, 1998, J ECON LIT, V36, P1426 BATTY M, 1988, ENVIRON PLANN B, V15, P461 BEAUREGARD RA, 1995, WORLD CITIES WORLD S, P232 BEAVERSTOCK JV, 2000, APPL GEOGR, V20, P43 CARTIER C, 2001, J CONT CHINA, V10, P445 CIFALDI RL, 2004, LANDSCAPE URBAN PLAN, V66, P107 CLAWSON M, 1962, LAND ECON, V38, P99 COLLINS JB, 1996, REMOTE SENS ENVIRON, V56, P66 CRIST EP, 1984, IEEE T GEOSCI REMOTE, V22, P256 FUJITA M, 2002, EC AGGLOMERATION CIT FUNG T, 1990, IEEE T GEOSCI REMOTE, V28 GEOGHEGAN J, 1997, ECOL ECON, V23, P251 GU CL, 2003, HABITAT INT, V27, P107 HARVEY RO, 1965, LAND ECON, V41, P1 HENDERSON JV, 1988, URBAN DEV THEORY FAC HEROLD M, 2002, ENVIRON PLANN A, V34, P1443 HEROLD M, 2003, REMOTE SENS ENVIRON, V86, P286 HU W, 1997, LAND USE POLICY, V14, P175 IVES AR, 1998, ECOSYSTEMS, V1, P35 JENERETTE GD, 2001, LANDSCAPE ECOL, V16, P611 JENKS M, 2000, COMPACT CITIES SUSTA JIM CY, 2001, GEOGR J 4, V167, P358 KAREIVA P, 1995, NATURE, V373, P299 KNOX PL, 1991, ANN ASSOC AM GEOGR, V81, P181 LAI LWC, 1995, LAND USE POLICY, V12, P281 LEAF M, 1998, J PLAN EDUC RES, V18, P145 LIN GCS, 2002, CITIES, V19, P299 LUCK M, 2002, LANDSCAPE ECOL, V17, P327 MCGARIGAL K, 2002, FRAGSTATS SPATIAL PA MELILLO JM, 2003, INTERACTIONS MAJOR B MUTH R, 1961, ECONOMETRICA, V29, P1 NG MK, 1999, INT PLANNING STUDIES, V4, P7 OPENSHAW S, 1984, MODIFIABLE AREAL UNI PARK RE, 1925, CITY PATAKI DE, 2003, J GEOPHYSICAL RES AT REMPEL RS, 2003, PATCH ANAL EXTENSION RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 SASSEN S, 2001, GLOBAL CITY SCARPACI JL, 2000, URBAN GEOGR, V21, P659 SCHNEIDER A, IN PRESS ENV PLAN B SETO KC, 2000, NATURE, V406, P121 SETO KC, 2002, INT J REMOTE SENS, V23, P1985 SETO KC, 2003, LAND ECON, V79, P106 SHARKAWY MA, 1995, J REAL ESTATE LIT, V3, P47 SONG C, 2001, REMOTE SENS ENVIRON, V75, P230 STEFFEN WL, 2004, GLOBAL CHANGE EARTH VONTHUNEN JH, 1875, ISOLIRTE STAAT WICKHAM JD, 1994, LANDSCAPE ECOL, V9, P7 WU FL, 2003, J URBAN AFF, V25, P55 WU JG, 2002, LANDSCAPE ECOL, V17, P761 ZHANG LQ, 2004, LANDSCAPE URBAN PLAN, V69, P1 ZHAO B, 2003, J ENVIRON SCI-CHINA, V15, P205 0921-2973 Landsc. Ecol.ISI:000233036300008Stanford Univ, Dept Geol & Environm Sci, Stanford, CA 94305 USA. Stanford Univ, Ctr Environm Sci & Policy, Stanford Inst Int Studies, Stanford, CA 94305 USA. Seto, KC, Stanford Univ, Dept Geol & Environm Sci, Stanford, CA 94305 USA. kseto@stanford.eduEnglishڽ7 3Severns, PaulM McIntire, EliotJ B. Schultz, CherylB2013_Evaluating functional connectivity with matrix behavior uncertainty for an endangered butterfly559-569Landscape Ecology283Springer NetherlandszHabitat fragmentation Functional connectivity SEIBM Biased correlated random walk Matrix configuration Habitat restoration 2013/03/01+http://dx.doi.org/10.1007/s10980-013-9860-6 0921-2973Landscape Ecol10.1007/s10980-013-9860-6English?? Jan Sevink1991ASoil development in the coastal dunes and its relation to climate49-56Landscape Ecology61/2soil, dune, climateFreely drained soils in humid climates are marked by rather rapid leaching, acidification and, eventually, podzolisation, because of of the high permeability and low acid buffering capacity of the sands. In cooler climates podzols may develop within a few centuries, whereas in warmer or less humid climates podzols require several milennia or longer periods to form. In dry climates soils contain little organic matter. Clay and soluble soil components accumulate and soil salinity may be high due to salt spray. If drainage is poor, organic matter tends to accumulate and in cooler climates peat formation becomes prominent. Soil salinity increases with increasing aridity. Effects of climatic changes can only be predicted in qualitative terms and concern changes in the pedogenic trends and in the rates of the processes described. It is suggested to execute comparative studies of well-dated soils in different climatic zones in order to quantify these effects.m|?] :Shanahan, Danielle F. Possingham, Hugh P. Riginos, Cynthia2011yModels based on individual level movement predict spatial patterns of genetic relatedness for two Australian forest birds137-148Landscape Ecology261JanFine-scale landscape change can alter dispersal patterns of animals, thus influencing connectivity or gene flow within a population. Furthermore, dispersal patterns of different species may be influenced by the landscape in varying ways. Our research first aimed to examine whether the spatial genetic structure within populations of closely related bird species differs in response to the same landscape. Second, we examined whether individual-level movement characteristics are a mechanistic driver of these differences. We generated a priori predictions of how landscape features will influence dispersal (particularly the response of individuals to habitat boundaries both natural and human-induced) based on a movement model developed by Fahrig (Funct Ecol 21:1003-1015, 2007). This model allowed us to predict genetic relatedness patterns in populations of two passerine bird species with different life-history traits from Queensland, Australia (yellow-throated scrubwren Sericornis citreogularis, a habitat specialist; white-browed scrubwren Sericornis frontalis, a habitat generalist). We quantified our predictions using cost-distance modelling and compared these to observed pairwise genetic distances (a (r) ) between individuals as calculated from microsatellite markers. Mantel tests showed that our a priori models correlated with genetic distance. Euclidean distance was most closely correlated to genetic distance for the generalist species (r = 0.093, P = 0.002), and landscape models that included the avoidance of unsuitable habitat were best for the specialist species (r = 0.107, P = 0.001). Our study showed that predictable movement characteristics may be the mechanism driving differences in genetic relatedness patterns within populations of different bird species.!://WOS:000286004400012Times Cited: 1 0921-2973WOS:00028600440001210.1007/s10980-010-9542-6A~?Shao, G. F. Wu, J. G.2008GOn the accuracy of landscape pattern analysis using remote sensing data505-511Landscape Ecology235,Advances in remote sensing technologies have provided practical means for land use and land cover mapping which is critically important for landscape ecological studies. However, all classifications of remote sensing data are subject to different kinds of errors, and these errors can be carried over or propagated in subsequent landscape pattern analysis. When these uncertainties go unreported, as they do commonly in the literature, they become hidden errors. While this is apparently an important issue in the study of landscapes from either a biophysical or socioeconomic perspective, limited progress has been made in resolving this problem. Here we discuss how errors of mapped data can affect landscape metrics and possible strategies which can help improve the reliability of landscape pattern analysis."://WOS:000254964600002 Times Cited: 0WOS:000254964600002(10.1007/s10980-008-9215-x|ISSN 0921-2973S? BMarlyn L. Shelton1987bIrrigation induced change in vegetation and evapotranspiration in the Central Valley of California95-105Landscape Ecology12Gevapotranspiration, California, irrigation, agriculture, prairie, marshLandscape changes in the Central Valley of California, USA, have been dramatic over the past 100 years. Irrigated agriculture has replaced natural communities of California prairie, riparian forest, tule marsh, valley oak savannah, and San Joaquin saltbrush. This paper addresses the implication of vegetation change on evapotranspiration as a consequence of these changes. It was found that an increase in irrigated agriculture and a 60% reduction in the aerial extent of native vegetation has not produced significant changes in the moisture transfer to the atmosphere. The apparent reason for this result is that irrigated agriculture has substituted one actively transpiring surface for another and, therefore, has not significantly altered the transpiration flux of the landscape. 3|?1 ;Shen, Weijun Lin, Yongbiao Jenerette, G. Darrel Wu, Jianguo2011oBlowing litter across a landscape: effects on ecosystem nutrient flux and implications for landscape management629-644Landscape Ecology265MayLateral flows in landscape mosaics represent a fundamentally important process in landscape ecology, but are still poorly understood in general. For example, windblown litter nutrient transfer across a landscape has rarely been studied from an ecosystem perspective. In this study we measured the litter nutrient transfer from an Acacia mangium plantation to a Dimocarpus longan orchard in an agroforestry landscape for 3 years from January 2002 to December 2004. About 11% of the total litterfall of the acacia plantation were transported to the longan orchard annually, accounting for ca. 9-59% of the total litter nutrient input of the longan orchard. The windblown litter transfer showed high spatial variation mainly caused by wind speed and directions. Slope positions 5 m away from the source acacia plantation received significantly greater amount of allochthonous acacia litter than those 10 m away, and the northwest-facing slope of the longan orchard received 2 to 3-fold more litter than the southeast-and south-facing slopes because of the prevailing southeasterly wind in the region. To explore how different management practices may influence the litterfall, leaf production, and soil nutrient status of the two ecosystems, we developed a Meta-Ecosystem Litter Transfer (MELT) model to simulate the processes of litter-related transformation (production, deposition, and decomposition) and transfer (wind- and management-driven movement). Our simulation results suggest that less than 30% of acacia litter should be transferred to the longan orchard in order for the acacia plantation to sustain itself and maximize production of the longan. Connectivity of nutrient flow between adjacent ecosystems as shown here leads to a functional meta-ecosystem with higher landscape-scale production of ecosystem services. That is, managing this connectivity through landscape design or active litter transfers can lead to large changes in overall landscape functioning and service production.!://WOS:000291485100003Times Cited: 0 0921-2973WOS:00029148510000310.1007/s10980-011-9599-x |? LSherren, Kate Fischer, Joern Clayton, Helena Schirmer, Jacki Dovers, Stephen2010Integration by case, place and process: transdisciplinary research for sustainable grazing in the Lachlan River catchment, Australia 1219-1230Landscape Ecology258Oct=In a context of global agricultural intensification, integrating conservation and agricultural production is a major challenge. We have tackled the problem using a transdisciplinary research framework. Our work focuses on part of the upper Lachlan River catchment in southeastern Australia. The region is dominated by livestock grazing, and is part of an internationally recognised threatened ecoregion because most native woodland vegetation has been cleared. In productive areas, most remnant vegetation occurs as scattered and isolated paddock trees, which are dying from old age and not regenerating due to agricultural practices. The policy context and industry trends present additional risks for sparse trees. These declining trees provide many ecosystem services, including enhanced water infiltration, shade for livestock, aesthetic and cultural values, and habitat for native species. Our research aims to identify management options and policy settings that enable landscape-scale tree regeneration while maintaining grazing production. Our findings highlight tensions between the trajectory of tree cover in the region and stakeholder values. Under status quo management, many scattered and isolated paddock trees will be lost from farms, although most farmers would like to see them persist. Case studies on selected farms reveal management strategies that may be more sustainable in terms of tree regeneration and agricultural productivity, such as rotational grazing. In addition to these applied insights, our work provides a case study illustrating how a transdisciplinary study can be conducted efficiently by a small team. Our pragmatic approach has successfully combined targeted disciplinary activities with strategic collaborations and stakeholder engagement, all united by shared landscape, case graziers, and outreach activities.!://WOS:000281725700007YTimes Cited: 1 10th International Congress of Ecology Aug 16-21, 2009 Brisbane, AUSTRALIA 0921-2973WOS:00028172570000710.1007/s10980-010-9494-x|?<Shi, Tingting Liu, Yongqiang Zhang, Libo Hao, Lu Gao, Zhiqiu2014PBurning in agricultural landscapes: an emerging natural and human issue in China 1785-1798Landscape Ecology2910DecBurning is one of the most widely used methods for removing crop residues during harvest seasons. It cleans fields faster and costs less in comparison to other residue removal methods. Agricultural burning, however, has been recently limited or banned during harvest seasons in China, mainly due to the air quality and human health concerns raised from its use. This paper reviews recent studies on the burning of agricultural landscapes in China to understand the natural (environmental and ecological) and human (economic and social) impacts and identifies uncertainties, gaps, and future research needs. The total annual crop straw output in China is more than 600 billon kg, with about 110, 130, and 230 billion kg coming from rice, wheat, and corn, respectively. Agricultural burning removes about one-fourth of total crop straw and emits about 140-240, 1.6-2.2, and 0.5-0.14 billion kg of CO2, PM2.5, and black carbon, respectively. Agricultural burning accounts for upto half of the total PM10 concentrations in the major burning regions during harvesting periods. Burning emissions contribute to regional haze and smog events. Therefore, limiting or banning agricultural burning is a necessary measure for reducing air pollution in China. The estimations of total burned crop straw amounts and emission factors are the major uncertainty sources for emission estimates. More studies are needed to better describe the smoke plume rise, dispersion, and interactions with weather and climate and to simulate the ecological impacts of agricultural burning. Effective alternatives need to be explored in order to provide solutions for farmers to remove agricultural residues in the wake of the burning ban.!://WOS:000346920900012Times Cited: 0 0921-2973WOS:00034692090001210.1007/s10980-014-0060-9 h<7]Silbernagel, J.2003NSpatial theory in early conservation design: examples from Aldo Leopold's work635-646Landscape Ecology187ArticleGAldo Leopold is well known in North America as a conservationist, author, and promoter of the Land Ethic. Although Leopold's work is rarely included in the realm of landscape ecology, he left several illustrations of an early spatial theory for conservation. While European geographer Troll published the term ' landscape ecology' in 1939, Leopold was discovering the role of spatial configuration in European working landscapes, and began to apply the landscape ecology concepts to wildlife management and cooperative conservation in the US. With his own spatial language he wrote, mapped, and applied elements of pattern, process, and connectedness in the landscape. In this perspective piece I use three examples from Leopold's work to demonstrate his contribution to spatial theory in early conservation design. First, this paper deciphers spatial elements conveyed through Leopold's writing, drawing, and teaching in the early 1930s. Second, I re- interpret Leopold's observations of the spatial design of remises from his visit to Silesia, Europe. Third, I show how the lessons from Silesia were applied to a landscape in Wisconsin, USA, involving both farmers and townspeople in cooperative implementation of a remise system. Collectively, a new perspective emerges on the early dialogue of landscape ecology and conservation across continents.://000186639000001 ]ISI Document Delivery No.: 744NR Times Cited: 0 Cited Reference Count: 12 Cited References: CALLICOTT JB, 1999, A LEOPOLD HLTH LAND FLADER SL, 1991, RIVER MOTHER GOD OTH FORMAN RTT, 1986, LANDSCAPE ECOLOGY GUTHERY FS, 1992, WILDLIFE SOC B, V20, P340 LEOPOLD A, 1986, GAME MANAGEMENT MCCABE RA, 1987, A LEOPOLD PROFESSOR MEINE C, 1988, A LEOPOLD HIS LIFE W MORRIS E, 2001, RISE T ROOSEVELT SANDERSON J, 2000, LANDSCAPE ECOLOGY TO SCHREIBER KF, 1990, CHANGING LANDSCAPES, P21 TURNER MG, 2001, LANDSCAPE ECOLOGY TH ZONNEVELD IS, 1995, LAND ECOLOGY 0921-2973 Landsc. Ecol.ISI:000186639000001Univ Wisconsin, Dept Landscape Architecture, Madison, WI 53706 USA. Silbernagel, J, Univ Wisconsin, Dept Landscape Architecture, Room 12 Agr Hall,1450 Linden Dr, Madison, WI 53706 USA.English?Janet Silbernagel2007Designing Small Parks: A Manual for Addressing Social and Ecological Concerns: A Forsyth and L.R. Musacchio, with F. Fitzgerald 635-636Landscape Ecology224 BOOK REVIEW? Silbernagel, Janet20122Landscape ecology in Asian cultures: a book review775-776Landscape Ecology275Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9707-6 0921-297310.1007/s10980-012-9707-6(<7[5Silbernagel, J. Martin, S. R. Gale, M. R. Chen, J. Q.1997Prehistoric, historic, and present settlement patterns related to ecological hierarchy in the Eastern Upper Peninsula of Michigan, USA223-240Landscape Ecology124cultural ecology; settlement patterns; landtype associations; archaeology; General Land Office surveyors' notes; LandSAT; digital elevation model UPPER GREAT-LAKES; LAND CLASSIFICATION; UNITED-STATES; FORESTS; PRESETTLEMENT; LANDSCAPES; ECOSYSTEMS; REGIONArticleAugThe distribution of human occupation across a landscape provides information about how people use the landscape, about patterns of economic development, and about social interactions of human groups. When the distributions are examined over several thousand years, we gain an evolutionary understanding, not only of the people and their cultural patterns, but also of physical landscape development. The focus of this assessment was to examine and compare settlement patterns of prehistoric, historic, and present time periods, based on known cultural sites in the Eastern Upper Peninsula of Michigan, U.S.A., and to generate hypotheses about the interaction of settlement pattern and landscape change at multiple scales. Patterns of settlement among the three time periods were compared at three geographic scales: by subregional ecosystems, by landscape ecosystems and by terrain characteristics. The Michigan Bureau of History database of archaeological sites was searched for prehistoric habitation sites of Middle or Late Woodland period (ca. 3000-300 years before present). Historic occupations were drawn from pre-European settlement landscape data based on General Land Office survey notes of the 1850s. We extracted ''urban'' categories from land cover classified from Landsat Thematic Mapper imagery to measure present occupations. Spatial patterns and dynamics of settlement areas in each time period were examined using the ARC/INFO geographic information system (GIS). Results showed a tendency for settlement in all time periods on the bedrock and lowland landscape groups near Great Lakes shorelines, generally occupying slopes less than two percent. The distribution of present occupations, in terms of both slope aspect and geographic subregion (multi-scalar), was similar to the distribution of prehistoric occupations. Both prehistoric and present sites were primarily south facing and were frequently found along Green Bay and Lake Michigan shorelines.://A1997XV63300003 ISI Document Delivery No.: XV633 Times Cited: 11 Cited Reference Count: 65 Cited References: *ECOMAP, 1993, NAT HIER FRAM ECOL U *ERDAS, 1994, ERDAS FIELD GUID ALBERT DA, 1986, REGIONAL LANDSCAPE E ALBERT DA, 1995, NC178 USDA FOR SERV ALLEN TFH, 1982, HIERARCHY PERSPECTIV ANDERTON JA, 1993, HERITAGE PROGRAM MON, V1 BAILEY RG, 1994, ECOREGIONS SUBREGION BAILEY RG, 1996, ENVIRON MONIT ASSESS, V39, P21 BAKER WL, 1992, ECOLOGY, V73, P1879 BENCHLEY ED, 1988, 89 U WISC MILW ARCH BIGONY BA, 1968, UNPUB ARCHAEOLOGICAL BOURDO EA, 1956, ECOLOGY, V37, P754 CANHAM CD, 1978, THESIS U WISCONSIN M CANHAM CD, 1984, ECOLOGY, V65, P803 CRUMLEY CL, 1994, HIST ECOLOGY CULTURA CURTIS JT, 1959, VEGETATION WISCONSIN DENSMORE F, 1974, 44 ANN REP BUR AM ET, P275 DUNHAM SB, 1995, CULTURAL RESOURCE EV FARRAND WR, 1982, QUATERNARY GEOLOGY M FORMAN RTT, 1987, ECOL STUD, V64, P213 FRANZEN J, 1986, 4 HIAW NAT FOR CULT FRELICH LE, 1991, ECOL MONOGR, V61, P145 FRELICH LE, 1995, NAT AREA J, V15, P157 GARY M, 1974, GLOSSARY GEOLOGY GOLLEY FB, 1995, LANDSCAPE ECOL, V10, P3 GRAUMLICH LJ, 1993, ECOLOGY, V74, P826 HAMMER RD, 1995, SOIL SCI SOC AM J, V59, P509 HAMMETT JE, 1992, LANDSCAPE ECOL, V7, P121 HOLMAN MB, 1978, THESIS MICHIGAN STAT HOUGH M, 1990, OUT PLACE RESTORING HUDGINS B, 1961, MICHIGAN GEOGRAPHIC KELSO GK, 1993, LANDSCAPE J, V12, P143 KINEITZ WV, 1947, CRANBROOK I SCI B, V25 KINEITZ WV, 1991, INDIANS W GREAT LAKE KLIJN F, 1994, LANDSCAPE ECOL, V9, P89 KOHL JG, 1985, KITCHI GAMI LIFE LAK LORIMER CG, 1977, ECOLOGY, V58, P139 LORIMER CG, 1980, P FIR HIST WORKSH 20 LORIMER CG, 1985, CAN J FOREST RES, V15, P200 LOVIS WA, 1979, 36 MICH STAT U MUS A MACLEAN GA, 1994, INVENTORY DEER HABIT MARTIN HM, 1957, MICHIGAN GEOLOGICAL, V49 MARTIN PE, 1979, 3 MICH TECHN U CULT MARTIN SR, 1985, THESIS MICHIGAN STAT MCGLADE J, 1995, ANTIQUITY, V69, P113 NASSAUER JI, 1987, ECOL STUD, V64, P199 NASSAUER JI, 1995, LANDSCAPE ECOL, V10, P229 PALIK BJ, 1992, AM MIDL NAT, V127, P327 PETERSON WL, 1986, US GEOLOGICAL SURVEY, V1652 PRICE DL, 1994, THESIS MICHIGAN STAT RISSER PG, 1987, ECOL STUD, V64, P3 ROSSIGNOL J, 1992, SPACE TIME ARCHAEOLO ROWE JS, 1991, ECOLOGICAL LAND CLAS, P7 ROWE JS, 1996, ENVIRON MONIT ASSESS, V39, P11 SANTER RA, 1977, MICHIGAN HEART GREAT SCHOOLCRAFT HR, 1970, NARRATIVE J TRAVELS SENNIGER EJ, 1963, ATLAS MICHIGAN SILBERNAGEL J, 1996, THESIS MICHIGAN TECH STAFFORD CR, 1995, J ARCHAEOL METHOD TH, V2, P69 TANNER HH, 1987, ATLAS GREAT LAKES IN TRYGG JW, 1969, COMPOSITE MAP US LAN UHLIG PWC, 1996, ENVIRON MONIT ASSESS, V39, P59 URBAN DL, 1987, BIOSCIENCE, V37, P119 VEATCH JO, 1959, PRESETTLEMENT FOREST WHITNEY GG, 1986, ECOLOGY, V67, P1548 0921-2973 Landsc. Ecol.ISI:A1997XV63300003aSilbernagel, J, WASHINGTON STATE UNIV, DEPT HORT & LANDSCAPE ARCHITECTURE, PULLMAN, WA 99164 USA.English T<7 ?Silva, F. R. Oliveira, T. A. L. Gibbs, J. P. Rossa-Feres, D. C.2012An experimental assessment of landscape configuration effects on frog and toad abundance and diversity in tropical agro-savannah landscapes of southeastern Brazil87-96Landscape Ecology271 brazil frogs generalized linear mixed models isolation landscape semi-deciduous atlantic forest terrestrial habitats species richness amphibian declines population declines forest fragments atlantic forest global decline habitat split conservation dynamics wetlandsJan2Amphibians are an imperiled group of vertebrate animals that typically have biphasic life histories involving a shift from aquatic larval habitats to terrestrial adult habitats. Habitat loss is the greatest threat to amphibians and the importance of the spatial configuration of terrestrial and breeding habitats upon the landscape in determining amphibian persistence is poorly known. The information gap is particularly acute in tropical landscapes that simultaneously host the greatest and most imperiled amphibian fauna on Earth. We installed 125 artificial ponds at different distances from forest fragments embedded in an agricultural matrix in southeastern Brazil. Constructed ponds attracted 13 anuran species; ponds at the forest fragment-matrix transition hosted a greater abundance and higher species richness of frogs and toads than those installed either far from or well within forest fragments. Forest fragments larger than 70 ha in agricultural areas harbored more individuals than smaller fragments. Our results indicate that landscape configuration has an important influence on frog and toad distribution and abundance in tropical agricultural landscapes and we suggest guidelines for maintaining favorable configurations of aquatic and terrestrial habitats for conserving this rich and imperiled species suite.://000298228300007-864HI Times Cited:1 Cited References Count:59 0921-2973Landscape EcolISI:000298228300007?Silva, FR Univ Fed Sao Carlos, UFSCar, Campus Sorocaba,Rodovia Joao Leme dos Santos,Km 1, BR-18052780 Sorocaba, SP, Brazil Univ Fed Sao Carlos, UFSCar, Campus Sorocaba,Rodovia Joao Leme dos Santos,Km 1, BR-18052780 Sorocaba, SP, Brazil Univ Fed Sao Carlos, UFSCar, BR-18052780 Sorocaba, SP, Brazil Univ Sao Paulo State Julio de Mesquita Filho UNES, Grad Program Anim Biol, BR-15054000 Sao Jose Do Rio Preto, SP, Brazil SUNY Coll Environm Sci & Forestry, Dept Environm & Forest Biol, Syracuse, NY 13210 USA UNESP, Dept Bot & Zool, BR-15054000 Sao Jose Do Rio Preto, SP, BrazilDOI 10.1007/s10980-011-9670-7English|? _Silveira, Leandro Sollmann, Rahel Jacomo, Anah T. A. Diniz Filho, Jose A. F. Torres, Natalia M.2014vThe potential for large-scale wildlife corridors between protected areas in Brazil using the jaguar as a model species 1213-1223Landscape Ecology297AugNMost large reserves in Brazil do not hold viable populations of jaguars to guarantee the species' long-term survival. Corridors linking populations have been identified as a potential tool to avoid negative effects of isolation, increasing population viability. Here, we performed a Brazil-wide evaluation of potential large scale corridors connecting protected jaguar populations. Six variables (human population size, dam reservoir size, number of dams, roads, railways and cities) expected to negatively impact jaguar movement were analyzed across 180 potential corridors connecting 298 protected jaguar areas. We established overall disturbance scores for the corridors using a principal components analysis and compared them among the Brazilian biomes. We further investigated which variables separated biomes using a canonical variates analysis. The Atlantic Forest and the semi-arid Caatinga have the most impacted potential corridors, whereas the Amazon and Pantanal still have the best potential corridors. Corridor quality in the Cerrado grasslands was intermediate. All variables but human population size and corridor length contributed significantly to differences in corridor variables among biomes. Our conclusions suggest that we need to plan the implementation of large scale corridors in the Amazon, Pantanal and particularly the Cerrado soon, while potential corridors might still be economically viable. In the much more impacted Atlantic Forest and Caatinga, the need for conservation actions is strongest, but logistical difficulties and costs may turn implementation of corridors unfeasible.!://WOS:000339831300010Times Cited: 0 0921-2973WOS:00033983130001010.1007/s10980-014-0057-4<7*$Simmering, D. Waldhardt, R. Otte, A.2006{Quantifying determinants contributing to plant species richness in mosaic landscapes: a single- and multi-patch perspective 1233-1251Landscape Ecology218Mbiodiversity; Germany; habitat diversity; habitat specificity; linear structures; marginal landscape; conservation value; modelling; spatial heterogeneity; species-area curve AGRICULTURAL LANDSCAPES; DIVERSITY PATTERNS; AREA RELATIONSHIP; GAMMA-DIVERSITY; BETA-DIVERSITY; SPATIAL SCALE; LAND-COVER; BIODIVERSITY; HABITAT; COMMUNITIESArticleNovDespite good theoretical knowledge about determinants of plant species richness in mosaic landscapes, validations based on complete surveys are scarce. We conducted a case study in a highly fragmented, traditional agricultural landscape. In 199 patches of 20 representative multi-patch-plots (MPPs, I ha) we recorded a total of 371 plant species. In addition to an additive partitioning of species diversity at the (a) patch- and (b) MPP-scale, we adopted the recently proposed 'specificity' measure to quantify the contribution of a spatial subunit to landscape species richness (subunit-to-landscape-contribution, SLC). SLC-values were calculated at both scales with respect to various spatial extents. General regression models were used to quantify the relative importance of hypothesis-driven determinants for species richness and SLC-values. At the patch scale, habitat type was the main determinant of species richness, followed by area and elongated shape. For SLC-values, area was more important than habitat type, and its relevance increased with the extent of the considered landscape. Influences of elongated shape and vegetation context were minor. Differences between habitat types were pronounced for species richness and also partly scale-dependent for SLC-values. Relevant predictors at the MPP-scale were nonlinear habitat richness, the gradient from anthropogenic to seminatural vegetation, and the proportions of natural vegetation and rare habitats. Linear elements and habitat configuration did not contribute to species richness and SLC. Results at the MPP-scale were in complete accordance with the predictions of the mosaic concept. Hence, our study represents its first empirical validation for plant species diversity in mosaic landscapes.://000242089300006 ISI Document Delivery No.: 106GP Times Cited: 0 Cited Reference Count: 78 Cited References: *STATSOFT INC, 2001, STATISTICA WINDOWS ALARD D, 2000, J VEG SCI, V11, P287 ALLAN JD, 1975, OECOLOGIA, V18, P359 ARRHENIUS O, 1921, J ECOL, V9, P95 BAUDRY J, 2000, LANDSCAPE URBAN PLAN, V50, P119 BOSSUYT B, 2004, BASIC APPL ECOL, V5, P321 BROSE U, 2001, ECOGRAPHY, V24, P722 BRUUN HH, 2000, ECOGRAPHY, V23, P641 BRUUN HH, 2001, NORD J BOT, V21, P607 BUREL F, 1998, ACTA OECOL, V19, P47 CONNOR EF, 1979, AM NAT, V113, P791 CRIST TO, 2003, AM NAT, V162, P734 DAUBER J, 2003, AGR ECOSYST ENVIRON, V98, P321 DAVIS JC, 1986, STAT DATA ANAL GEOLO DUELLI P, 1992, VERH GES OEKOLOGIE B, V21, P379 DUELLI P, 1997, AGR ECOSYST ENVIRON, V62, P81 ELLENBERG H, 1996, VEGETATION MITTELEUR ERIKSSON A, 1995, ECOGRAPHY, V18, P310 FAHRIG L, 2005, ISSUES PERSPECTIVES, P3 FIRBANK LG, 2005, ANN APPL BIOL, V146, P163 FLEISHMAN E, 2003, LANDSCAPE ECOL, V18, P675 FORMAN RT, 2002, APPLYING LANDSCAPE E, R7 FORMAN RTT, 1995, LAND MOSAICS GERING JC, 2002, ECOL LETT, V5, P433 GERING JC, 2003, CONSERV BIOL, V17, P488 GEROWITT B, 2003, WEED RES, V43, P227 GRIFFITH DA, 1982, ANN ASSOC AM GEOGR, V72, P332 GUTZWILLER KJ, 2002, APPL LANDSCAPE ECOLO HANSKI I, 1997, SCIENCE, V275, P397 HANSSON L, 1991, LANDSCAPE ECOL, V5, P191 HIETALAKOIVU R, 2004, AGR ECOSYST ENVIRON, V101, P9 HIETEL E, 2004, LANDSCAPE ECOL, V19, P473 HIETEL E, 2005, J ENVIRON MANAGE, V75, P133 HOFFMANNKROLL R, 2003, AGR ECOSYST ENVIRON, V98, P363 HUSTON MA, 1994, BIOL DIVERSITY COEXI JEANNERET P, 2003, AGR ECOSYST ENVIRON, V98, P311 KEELEY JE, 2005, J VEG SCI, V16, P249 KENT M, 1992, VEGETATION DESCRIPTI KUNIN WE, 1997, BIOL CONSERV, V82, P369 LANDE R, 1996, OIKOS, V76, P5 LECOEUR D, 2002, AGR ECOSYST ENVIRON, V89, P23 LEGENDRE P, 1998, NUMERICAL ECOLOGY LEWONTIN RC, 1972, EVOLUTIONARY BIOL, V6, P381 LIU J, 2002, INTEGRATING LANDSCAP LOREAU M, 2000, ECOL LETT, V3, P73 MA MH, 2002, AGR ECOSYST ENVIRON, V89, P137 MAGURRAN AE, 2000, MEASURING BIOL DIVER MANTEL N, 1967, CANCER RES, V27, P209 MARSHALL EJR, 2002, AGR ECOSYST ENVIRON, V89, P5 MCCUNE B, 1999, PC ORD MULTIVARIATE MCGARIGAL K, 1995, PNWGTR351, P1 NESSHOVER C, 1999, BAYREUTHER FORUM OKO, V69, P1 ORTEGA M, 2004, ENVIRON MONIT ASSESS, V95, P97 PETERSEIL J, 2004, LAND USE POLICY, V21, P307 POTTS MD, 2001, SAMPLING BIODIVERSIT, P29 PRESTON FW, 1960, ECOLOGY, V41, P611 RETZER V, 1999, BAYREUTHER FORUM OKO, V69, P117 RICOTTA C, 2003, ACTA BIOTHEOR, V51, P91 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 ROSENZWEIG ML, 1995, SPECIES DIVERSITY SP SCHEINER SM, 2003, GLOBAL ECOL BIOGEOGR, V12, P441 SCHEINER SM, 2004, GLOBAL ECOL BIOGEOGR, V13, P479 SIMMERING D, 2001, TUEXENIA, V21, P51 STEINER NC, 2003, AGR ECOSYST ENVIRON, V98, P353 STEVENS J, 2002, APPL MULTIVARIATE ST STOATE C, 2001, J ENVIRON MANAGE, V63, P337 STOHLGREN TJ, 1995, VEGETATIO, V117, P113 STOHLGREN TJ, 1997, ENVIRON MONIT ASSESS, V48, P25 TILZEY M, 2000, LAND USE POLICY, V17, P279 TJORVE E, 2002, ECOGRAPHY, V25, P17 TRIANTIS KA, 2003, J BIOGEOGR, V30, P19 VEECH JA, 2002, OIKOS, V99, P3 WAGNER HH, 2000, LANDSCAPE ECOL, V15, P219 WAGNER HH, 2001, LANDSCAPE ECOL, V16, P121 WALDHARDT R, 2004, LANDSCAPE ECOL, V19, P211 WEBER D, 2004, GLOBAL ECOL BIOGEOGR, V13, P97 WHITTAKER RH, 1972, TAXON, V21, P213 WIENS JA, 2005, ISSUES PERSPECTIVES, P365 0921-2973 Landsc. Ecol.ISI:000242089300006Univ Giessen, Inst Landscape Ecol & Resources Management, Interdisciplinary Res Ctr Biosyst Land Use & Nutr, Div Landscape Ecol & Landscape Planning, D-35392 Giessen, Germany. Simmering, D, Univ Giessen, Inst Landscape Ecol & Resources Management, Interdisciplinary Res Ctr Biosyst Land Use & Nutr, Div Landscape Ecol & Landscape Planning, Heinrich Buff Ring 26-32, D-35392 Giessen, Germany. dietmar.simmering@agrar.uni-giessen.deEnglish|7 ,Simmons, M. A. Cullinan, V. I. Thomas, J. M.19928Satellite Imagery as a Tool to Evaluate Ecological Scale77-85Landscape Ecology72JulMethods for detecting scale and dispersion of plant cover developed by Carlile et al. (1989, Landscape Ecology 2: 203-213) were adapted to information obtained from satellite imagery. Scales were found to be on the order of 100 m in the shrub-steppe area of southeastern Washington. General agreement between the remotely sensed data and plant cover using the variance and correlation methods of Carlile et al. indicate that remote sensing information can be used in the design of field studies for measuring the processes controlling plant cover in semi-arid areas; the agreement also suggests that the methods have broad applicability in the determination of scale and dispersion.://A1992JF61500001-Jf615 Times Cited:10 Cited References Count:0 0921-2973ISI:A1992JF615000012Simmons, Ma Pacific Nw Lab, Richland, Wa 99352 USAEnglish=|7:Simon, J. A. Snodgrass, J. W. Casey, R. E. Sparling, D. W.2009QSpatial correlates of amphibian use of constructed wetlands in an urban landscape361-373Landscape Ecology243urbanization stormwater management impervious surface anura caudata habitat use stormwater treatment ponds adjacent land-use species richness sediment quality great-lakes conservation populations ontario water frogMarMany amphibian species rely on both aquatic and terrestrial habitats to complete their life cycles. Therefore, processes operating both within the aquatic breeding habitat, and in the surrounding uplands may influence species distributions and community composition. Moreover, changes in land use adjacent to breeding site may degrade aquatic habitats. To assess land use effects on pond-breeding amphibian assemblages, we investigated relationships between land use, breeding habitat conditions, and breeding amphibian use of constructed wetlands in urban environments of the Baltimore metropolitan area, USA. Forest and impervious surface associations with species richness and occurrence occurred at spatial scales ranging from 50 to 1,000 m, with strongest relationships at 500 m. Forest and impervious surface cover within 1,000 m of ponds were also related to water and sediment quality, which in turn were capable of explaining a proportion of the observed variation in species richness and occurrence. Taken together, our results suggest that forest and other land covers within relatively proximal distances to ponds (i.e., within 50-1,000 m) may be influencing species richness directly via the provisioning of upland habitat, and indirectly via influences on within pond habitat quality.://000263419500006-408EY Times Cited:0 Cited References Count:46 0921-2973ISI:000263419500006Snodgrass, JW Towson Univ, Dept Biol Sci, 8000 York Rd, Towson, MD 21252 USA Towson Univ, Dept Biol Sci, Towson, MD 21252 USA Towson Univ, Dept Chem, Towson, MD 21252 USA So Illinois Univ, Dept Zool, Carbondale, IL 62901 USADoi 10.1007/S10980-008-9311-YEnglish <7TSimpson, J. W. Boerner, R. E. J. Demers, M. N. Berns, L. A. Artigas, F. J. Silva, A.1994<48 years of landscape change on 2 contiguous Ohio landscapes261-270Landscape Ecology94ArticleDecThis study analyzes the current and historic structure of two contiguous, rural landscapes covering approximately 242 km2 in central Ohio, USA: a till plain landscape with relatively homogeneous topography and soils, and a moraine landscape with greater geomorphological diversity and heterogeneity. These landscapes were chosen because they were both heavily dominated by agriculture during 1900-1940 and were both initially surveyed by the metes-and-bounds system. They differed, however, in the temporal pattern of settlement and development and in the inherent agricultural capability of their soils. We combined analysis of aerial photographs from 1940, 1957, 1971, and 1988 with historical archives and other available mapped data in a GIS data base to facilitate analysis of both spatial and temporal patterns of change. On the moraine, the agricultural matrix decreased over time as forest, urban/suburban areas, and industry increased. In contrast, on the till plain agricultural landcover increased through 1988, with concommitant decreases in upland forest and oak savanna. The moraine landscape exhibited greater diversity and equitability than the till plain on each date. The till plain had its greatest diversity and equitability in 1940, whereas the moraine increased in diversity and equitability during each time period. The undulating topography of the moraine encouraged landcover dynamism rather than stability, whereas the more homogeneous till plain exhibited considerable inertia. Patch and matrix shape remained constant and predominantly angular over the 48 year study period. Differences in the physical environment, especially topography and soil capability, and the socioeconomic environment, especially agricultural policies and patterns of urbanization, resulted in these two contiguous landscapes having different trajectories of change. It is clear from this study that socioeconomic factors must be combined with the physical settings to fully understand patterns of change in human-dominated landscapes.://A1994PX89500003 IISI Document Delivery No.: PX895 Times Cited: 35 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1994PX89500003KSIMPSON, JW, OHIO STATE UNIV,DEPT LANDSCAPE ARCHITECTURE,COLUMBUS,OH 43210.English~?Singkran, N. Meixler, M. S.2008fInfluences of habitat and land cover on fish distributions along a tributary to Lake Ontario, New York539-551Landscape Ecology235Influences of habitat and land cover on fish distributions were determined along a lentic-lotic gradient along a tributary to Lake Ontario, New York. Nonmetric multidimensional scaling, cluster analysis, and specific characterization methods were used to classify the fish species into five groups based on their similar patterns of distribution, species-specific habitat relationship, and relative abundance observed along the gradient. A stepwise regression approach was used to select the best habitat and land cover variables to explain variations in the distribution pattern of each fish group. Distribution patterns of the five fish groups were significantly explained by either a set of the selected habitat or land cover predictor variables or a combination of both. Of the 10 habitat variables, water depth, current velocity, aquatic plants, algae, woody debris, sand, and rock-bedrock were selected to explain the variations in distribution patterns of one or more fish groups. Of the 16 land cover types, evergreen wetlands, evergreen plantations, successional shrubs, shrub swamps, roads, and urban areas were selected to explain the variations in distribution patterns of at least one fish group."://WOS:000254964600005 Times Cited: 0WOS:000254964600005(10.1007/s10980-008-9212-0|ISSN 0921-2973 H|? $Sirami, C. Brotons, L. Martin, J. L.2009WDo bird spatial distribution patterns reflect population trends in changing landscapes?893-906Landscape Ecology247AugStrong relations between population trends and spatial distribution have been suggested at the regional scale: declining species should have more fragmented distributions because decline causes range retractions towards optimal habitats, whereas increasing species should have more aggregated distributions, because colonization processes are constrained by distance. Most analyses of the effects of land use changes on animal populations are diachronic studies of population dynamics or synchronic studies of species habitat selection. Few studies take simultaneously into account temporal changes in habitat distribution and changes in species spatial distribution. We applied the above rationale to the landscape scale and analysed how population declines, increases or stability, as diagnosed in a long term study, correlate with population connectivity or fragmentation at that scale. We used data on changes in faunal distribution and information on temporal changes in the vegetation in a Mediterranean area that had been subjected to land abandonment. We found that species declining at the landscape scale had retracting fragmented distributions and that expanding species had expanding continuous distributions. However, for the latter, we suggest that the factors involved are related to landscape structure and not to dispersal mediated meta-population processes, which are of little relevance at this local scale. We also show that even species that are numerically stable can show fragmentation of their distribution and major spatial distribution shifts in response to land use changes, especially in species that have low occurrence levels or that are associated with transitory habitats such as heterogeneous shrublands (e.g. Sylvia melanocephala). Studying the spatial structure of species distribution patterns at the landscape scale may provide information about population declines and increases both at the regional and the landscape scale and can improve our understanding of short-term risks of local extinction.://0002684309000040Sirami, Clelia Brotons, Lluis Martin, Jean-Louis 0921-2973ISI:00026843090000410.1007/s10980-009-9365-5D|? $Sirami, C. Brotons, L. Martin, J. L.2010nDo bird spatial distribution patterns reflect population trends in changing landscapes? (vol 24, pg 893, 2009)159-160Landscape Ecology251!://WOS:000273479100013Times Cited: 0 0921-2973WOS:00027347910001310.1007/s10980-009-9419-8b|??Sitas, Nadia Prozesky, Heidi E. Esler, Karen J. Reyers, Belinda2014~Opportunities and challenges for mainstreaming ecosystem services in development planning: perspectives from a landscape level 1315-1331Landscape Ecology298OctDespite much progress in ecosystem services research, a gap still appears to exist between this research and the implementation of landscape management and development activities on the ground, especially within a developing country context. If ecosystem service science is to be operationalised and used by decision-makers directing local development, an in-depth understanding of the implementation context for landscape planning and management, and of the opportunities and challenges for ecosystem services in this context are needed. Very little is known about these opportunities and constraints, largely because of the absence of methods to explore the complexity of the landscape planning, management and implementation context and the possibilities of integrating scientific information into these processes within a real-world setting. This study aims to address this need for information and methods, by focusing on a region in South Africa with a long history of ecosystem service research and stakeholder engagement, and testing a social science approach to explore opportunities and challenges for integrating ecosystem services in landscape planning processes and policies. Our methodological approach recognises the importance of social processes and legitimacy in decision-making, emphasizing the need to engage with the potential end-users of ecosystem service research in order to ensure the relevance of the research. While we discovered challenges for mainstreaming ecosystem service at a local level, we also found strong opportunities in the multi-sectoral planning processes driving development and in how the concept of ecosystem services is framed and aligned with development priorities, especially those relating to disaster risk reduction.!://WOS:000342078600004Times Cited: 2 0921-2973WOS:00034207860000410.1007/s10980-013-9952-3<7Skinner, C. N.1995mChange in spatial characteristics of forest openings in the Klamath Mountains of northwestern California, USA219-228Landscape Ecology104gCALIFORNIA; FOREST OPENINGS; KLAMATH MOUNTAINS; SPATIAL ATTRIBUTES; LANDSCAPE CHANGE; LANDSCAPE ECOLOGYArticleAugChange in the spatial characteristics of forest openings was investigated in three forested watersheds in northwestern Siskiyou County, California totalling approximately 24,600 hectares. Watersheds with minimal human disturbance were chosen for study. However, fire suppression has been pervasive throughout. Characteristics of forest openings (area, perimeter, distance between neighboring openings) were measured on aerial photographs taken 41 years apart. An index of regional form was determined for the landscape. Shape complexity for each opening was calculated using two indices based upon fractals. Significant differences were found using the Kolmogorov-Smirnov two-sample test between the perimeters, areas, distance from sample point to nearest opening, and distance between neighboring openings. The perimeters and areas became smaller, and the distances from the sample point to the nearest opening and between neighboring openings became greater over the 41 years between aerial photo sets. The estimated area occupied by openings decreased from 25.8% to 15.6% of the study area. No significant difference was found in the shape of the openings except as the shape indices were influenced by changes in size of the openings.://A1995RP98800004 IISI Document Delivery No.: RP988 Times Cited: 19 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1995RP98800004eSKINNER, CN, US FOREST SERV,PACIFIC SW RES STN,SILVICULTURE LAB,2400 WASHINGTON AVE,REDDING,CA 96001.Englishs~?{Sklenicka, P. Salek, M.2008pOwnership and soil quality as sources of agricultural land fragmentation in highly fragmented ownership patterns299-311Landscape Ecology2333The relation between landscape structure and its drivers is a central issue in studies of landscape ecology. However, agricultural land fragmentation is dealt with in only a few such studies. We have investigated the effects of ownership and soil quality on agricultural land fragmentation in the highly fragmented ownership patterns that characterize some of the transition countries of Central and Eastern Europe. Using patch-scale spatial data generated from GIS, Minimal Adequate Models, based on ANOVA, were performed to test for the effects of ownership and soil quality patterns on arable land and grassland fragmentation across 483 study areas. The results show that there are important differences in the predictors of fragmentation between arable land and grassland. Grassland fragmentation was found to be associated particularly with ownership fragmentation, whereas arable land fragmentation tended to be driven mainly by soil conditions. A higher proportion of public ownership supports the more frequent appearance of larger patches. We found a significantly positive relationship between natural soil fertility and arable land fragmentation, while there was a strongly negative relationship between natural soil fertility and grassland fragmentation. Soil quality diversity was observed to be the most important driver affecting arable land fragmentation, but only a non-significant driver of grassland fragmentation. The study provides arguments for intervention aimed at reducing the huge differences between the levels of land-ownership and the land-use fragmentation."://WOS:000254112100005 Times Cited: 0WOS:000254112100005(10.1007/s10980-007-9185-4|ISSN 0921-29730ڽ7 vSkórka, Piotr Nowicki, Piotr Lenda, Magdalena Witek, Magdalena Śliwińska, EwaB Settele, Josef Woyciechowski, Michal2013Different flight behaviour of the endangered scarce large blue butterfly Phengaris teleius (Lepidoptera: Lycaenidae) within and outside its habitat patches533-546Landscape Ecology283Springer NetherlandsHDispersal Fragmentation Maculinea Metapopulation Movement Patch boundary 2013/03/01+http://dx.doi.org/10.1007/s10980-013-9855-3 0921-2973Landscape Ecol10.1007/s10980-013-9855-3English R<7 Slotte, H.20013Harvesting of leaf-hay shaped the Swedish landscape691-702Landscape Ecology168[agricultural history deciduous forest fodder forest history human impact leaf-hay livestockArticleThe hypothesis that the harvesting of leaf-hay was of great importance in agriculture and consequently had a substantial impact on deciduous forest areas is verified. The main sources are ethnological records collected from elderly informants, mainly between 1920 and 1940. At many farmsteads, leaf-hay was the main, and sometimes only, fodder used for sheep and goats. Information is presented from different districts in Sweden on the number of leaf-sheaves normally harvested at farmsteads and consumed during winter per goat and sheep (the median is 200). It is estimated that nearly 200 million leaf-sheaves were consumed annually by sheep and goats in Sweden around 1850. Horses, cattle and swine were also given leaf-hay, but the amount consumed has not been estimated because of poorer sources. The harvested quantity indicates that the greater part of the Swedish deciduous forest landscape in populated areas was exploited in the 19th century; at least one million hectares of land covered by deciduous trees were exploited. In forested areas, most of the leaf-hay was harvested on outland, usually by felling trees. In plain areas in the southern half of Sweden, a larger part was harvested on the infields, where pollards were also more common. The use of leaf-hay declined during the 19th century Swedish agrarian revolution. During the first half of the 20th century, the practice was also abandoned in forested areas.://000175490900002 ISI Document Delivery No.: 550EP Times Cited: 2 Cited Reference Count: 31 Cited References: *LEX, 1845, LEX LANDTH *SCB, 1959, HIST STAT SVER VAD L *SCB, 2000, NAT SIFFR 2000 NAT E AHTI T, 1968, ANN BOT FENN, V5, P169 BARGIONI E, 1998, ECOLOGICAL HIST EURO, P43 BERGENDORFF C, 1982, SVENSK BOT TIDSKR, V76, P91 BERGENDORFF C, 1996, SOLMED, V17, P235 BRAUNER J, 1756, TANKAR WID SKOTSELN CARLSSON A, 1996, SOLMED, V17, P69 GADD CJ, 1999, SVENSK JORDBRUKSSTAT GORANSSON H, 1995, THESES PAPERS ARCHAE, V6 GORANSSON H, 1996, SOLMED, V17, P409 HAAS JN, 1992, FESTSCHRIFT ZOLLER D, V196, P469 HAEGGSTROM CA, 1998, NORDENSKIOLD SAMFUND, V58, P15 HALSTEAD P, 1998, RURAL HIST, V9, P211 JANSSON P, 1968, VITTINGEBONDES DAGBO KARDELL L, 1996, SOLMED, V17, P13 MALMSTROM C, 1939, MEDD STATENS SKOGSFO, V31, P171 RACKHAM O, 1980, ANCIENT WOODLAND ITS RASMUSSEN P, 1990, ACTA ARCHAEOL, V60, P71 RASMUSSEN P, 1990, EXPT RECONSTRUCTION, P77 SIGAUT F, 1982, QUAD STORICI, V17, P49 SJOBECK M, 1933, YMER, V53, P33 SJORS H, 1965, ACTA PHYTOGEOGR SUEC, V50, P48 SLOTTE H, 1992, SVENSK BOT TISKR, V86, P63 SLOTTE H, 1993, SVENSK BOT TIDSKRIFT, V87, P283 SLOTTE H, 1996, SOLMED, V17, P1 SLOTTE H, 1999, AGRARHISTORIA, V2, P1 SLOTTE H, 2000, ACTA U AGR SUECIAE A, V236 STAAF M, 1759, KORTA FRAGOR SWAR UT TROELSSMITH S, 1953, ERTEBOLLEKULTUR BOND, P5 0921-2973 Landsc. Ecol.ISI:000175490900002Dept Landscape Planning, Ultuna Sect Agr Hist, S-75007 Uppsala, Sweden. Slotte, H, Dept Landscape Planning, Ultuna Sect Agr Hist, Box 7012, S-75007 Uppsala, Sweden.Englishs|7Sluiter, R. de Jong, S. M.2007USpatial patterns of Mediterranean land abandonment and related land cover transitions559-576Landscape Ecology224france aerial photography change detection land cover change old-fields landscape vegetation classification succession dynamicsAprIn Mediterranean France, land abandonment is a widespread change. To understand and predict the land abandonment process and its consequences, land cover change models are used. An essential step in the development of a land cover change model is the identification and quantification of the factors controlling land cover change. In this paper we present a change detection study using aerial photographs in combination with an extensive dataset of field data and geographical data, to identify and quantify these factors for a study area in Mediterranean France, 60 km west of the city of Montpellier. We distinguished 11 land cover change classes and 7 associated "time since abandonment" classes at a detailed scale. Several environmental and non-environmental factors were found to be important variables for the land abandonment process. Differences in soil class explain a large part of the land abandonment pattern and the associated transition paths and transition rates. Most abandoned lands are located on regosols and lithosols, which are marginal soils with respect to water holding capacity. Within soil classes, we could recognise different transition paths and transition rates. However, within the 55 years covered by this dataset detailed transitions from pioneer vegetation to vegetation higher in the succession, as described by other authors, were only found for a limited number of vegetation/soil combinations. We relate these slow transitions for some areas to ongoing grazing and for some other areas to irreversible degradation.://000245296600007-151NF Times Cited:3 Cited References Count:38 0921-2973ISI:000245296600007Sluiter, R Univ Utrecht, Fac Geosci, POB 80115, NL-3508 TC Utrecht, Netherlands Univ Utrecht, Fac Geosci, NL-3508 TC Utrecht, NetherlandsDoi 10.1007/S10980-006-9049-3Englishڽ7 ^Smith, AndrewG McAlpine, CliveA Rhodes, JonathanR Lunney, Daniel Seabrook, Leonie Baxter, Greg2013zOut on a limb: habitat use of a specialist folivore, the koala, at the edge of its range in a modified semi-arid landscape415-426Landscape Ecology283Springer NetherlandsXLandscape change Resource use Landscape supplementation Refugia Climate extremes Drought 2013/03/01+http://dx.doi.org/10.1007/s10980-013-9846-4 0921-2973Landscape Ecol10.1007/s10980-013-9846-4English|? ?Smith, Adam C. Koper, Nicola Francis, Charles M. Fahrig, Lenore2009kConfronting collinearity: comparing methods for disentangling the effects of habitat loss and fragmentation 1271-1285Landscape Ecology2410Estimating the relative importance of habitat loss and fragmentation is necessary to estimate the potential benefits of specific management actions and to ensure that limited conservation resources are used efficiently. However, estimating relative effects is complicated because the two processes are highly correlated. Previous studies have used a wide variety of statistical methods to separate their effects and we speculated that the published results may have been influenced by the methods used. We used simulations to determine whether, under identical conditions, the following 7 methods generate different estimates of relative importance for realistically correlated landscape predictors: residual regression, model or variable selection, averaged coefficients from all supported models, summed Akaike weights, classical variance partitioning, hierarchical variance partitioning, and a multiple regression model with no adjustments for collinearity. We found that different methods generated different rankings of the predictors and that some metrics were strongly biased. Residual regression and variance partitioning were highly biased by correlations among predictors and the bias depended on the direction of a predictor's effect (positive vs. negative). Our results suggest that many efforts to deal with the correlation between amount and fragmentation may have done more harm than good. If confounding effects are controlled and adequate thought is given to the ecological mechanisms behind modeled predictors, then standardized partial regression coefficients are unbiased estimates of the relative importance of amount and fragmentation, even when predictors are highly correlated.%://BIOSIS:PREV201000014104Times Cited: 0 0921-2973BIOSIS:PREV201000014104:10.1007/s10980-009-9383-3D<74Smith, E. R. McKinnis, P. Tran, L. T. O'Neill, R. V.2006iThe effects of uncertainty on estimating the relative environmental quality of watersheds across a region225-231Landscape Ecology212}data uncertainty; integrated environmental assessment; Monte Carlo simulation MID-ATLANTIC REGION; VULNERABILITY; SENSITIVITYArticleFebcLandscape ecologists may be faced with ranking the relative environmental quality of watersheds across a region. The rankings would be based on measured or modeled variables with inherent sources of error. This paper examines the impact of data uncertainty on the ranking assigned to watersheds. The approach is Monte Carlo simulation in which the individual variables are considered to be estimated with uncertainty. The results show that watersheds in the best and the worst condition have rankings that are robust to uncertainty but intermediate watersheds may be difficult or impossible to assign to a rank.://000235866400006 DISI Document Delivery No.: 019WC Times Cited: 0 Cited Reference Count: 16 Cited References: *USGS, 1982, 878A USGS BARTELL SM, 1983, ENVIRON TOXICOL CHEM, V2, P19 BARTELL SM, 1992, ECOLOGICAL RISK ESTI BOUGHTON DA, 1999, ECOSYST HEALTH, V5, P312 GARDNER RH, 1981, ECOL MODEL, V12, P173 GARDNER RH, 1983, UNCERTAINTY FORECAST, P245 HUFF DD, 1982, EARTH SURF PROCESSES, V7, P91 JONES KB, 1997, EPA600R97130 OFF RES LOCANTORE NW, 2004, ENVIRON MONIT ASSESS, V94, P249 ONEILL RV, 1979, SYSTEMS ANAL ECOSYST, P23 ONEILL RV, 1981, HEALTH PHYS, V40, P760 SMITH ER, 2003, EPA600R03082 TRAN LT, 2002, ENVIRON MANAGE, V29, P845 WICKHAM JD, 1997, PHOTOGRAMM ENG REM S, V63, P397 WICKHAM JD, 1999, ENVIRON MANAGE, V24, P553 WICKHAM JD, 2000, LANDSCAPE ECOL, V15, P495 0921-2973 Landsc. Ecol.ISI:000235866400006Florida Atlantic Univ, Dept Geosci, Boca Raton, FL 33433 USA. US EPA, Washington, DC 20460 USA. Tran, LT, Florida Atlantic Univ, Dept Geosci, 777 Glades Rd,PS 336, Boca Raton, FL 33433 USA. ltran@fau.eduEnglish(|?7 qSmith, Matthew J. Betts, Matthew G. Forbes, Graham J. Kehler, Daniel G. Bourgeois, Maryse C. Flemming, Stephen P.2011iIndependent effects of connectivity predict homing success by northern flying squirrel in a forest mosaic709-721Landscape Ecology265MayLandscape composition and configuration, often termed as habitat loss and fragmentation, are predicted to reduce species population viability, partly due to the restriction of movement in the landscape. Unfortunately, measuring the effects of habitat loss and fragmentation on functional connectivity is challenging because these variables are confounded, and often the motivation for movement by target species is unknown. Our objective was to determine the independent effects of landscape connectivity from the perspective of a mature forest specialist-the northern flying squirrel (Glaucomys sabrinus). To standardize movement motivation, we translocated 119 squirrels, at varying distances (0.18-3.8 km) from their home range across landscapes representing gradients in both habitat loss and fragmentation. We measured the physical connectedness of mature forest using an index of connectivity (landscape coincidence probability). Patches were considered connected if they were within the mean gliding distance of a flying squirrel. Homing success increased in landscapes with a higher connectivity index. However, homing time was not strongly predicted by habitat amount, connectivity index, or mean nearest neighbour and was best explained as a simple function of sex and distance translocated. Our study shows support for the independent effects of landscape configuration on animal movement at a spatial scale that encompasses several home ranges. We conclude that connectivity of mature forest should be considered for the conservation of some mature forest specialists, even in forest mosaics where the distinction between habitat and movement corridors are less distinct.!://WOS:000291485100009Times Cited: 0 0921-2973WOS:00029148510000910.1007/s10980-011-9595-1<75Smith, R. M. Gaston, K. J. Warren, P. H. Thompson, K.2005^Urban domestic gardens (V): relationships between landcover composition, housing and landscape235-253Landscape Ecology202backyard; green space; home gardens; housing; land use; urbanisation BIODIVERSITY; FRAGMENTATION; ENVIRONMENT; COMMUNITIES; HEDGEHOGS; HABITATS; GRADIENT; ECOLOGY; AREASArticleFeb`The contribution to urban green space by private or domestic gardens in residential zones was investigated in the city of Sheffield, UK, as part of a wider study of the garden resource and its associated biodiversity. The attributes of 61 gardens, including patterns of landcover and vegetation cover, were explored in relation to housing characteristics and the nature of the surrounding landscape. The number of surrounding houses, and the areas of buildings and of roads were negatively correlated with garden area. The proportion of a housing parcel comprising garden increased with parcel size, although the proportion that was rear garden remained relatively constant. Garden size played an overwhelming role in determining garden composition: larger gardens supported more landcovers, contained greater extents of three-quarters of the recorded landcovers, and were more likely to contain trees taller than 2 m, vegetable patches, and composting sites. Unvegetated landcovers made greater proportional contributions as garden size declined. All categories of vegetation canopy increased with garden size, and large gardens supported disproportionately greater cover above 3 m. House age was a less significant factor determining garden landcover. Gardens of newer houses were more likely to occur towards the edge of the urban area, and older properties, that contained fewer hedges, possessed less canopy between 2-3 m. The extent and occurrence of different landcovers in gardens, and their consequences for wildlife, are considered for residential patches in urban areas. The implications for urban planners are discussed.://000230299600009 ISI Document Delivery No.: 942RN Times Cited: 1 Cited Reference Count: 48 Cited References: *DEFRA, 2003, WORK GRAIN NAT BIOD *DETR, 1999, PLANN POL GUID 3 HOU *DETR, 2000, OUR TOWNS CIT FUT DE *LOND BIOD PARTN, 2001, PRIV GARD *UNDP UNEP WB WRI, 2000, WORLD RES 2000 2001 *UNDSD, 2003, AG 21 AINES C, 2000, MAKE WILDLIFE GARDEN BOLUND P, 1999, ECOL ECON, V29, P293 CANNON A, 2000, GARDEN BIRD WATCH HD CURDS T, 1985, J BIOL EDUC, V19, P71 DAILY GC, 1997, NATURES SERVICES SOC, P1 DAVIS BNK, 1979, LOND NAT, V58, P15 DENYS C, 1998, OECOLOGIA, V113, P269 DICKMAN CR, 1987, J ANIM ECOL, V56, P629 DICKMAN CR, 1987, J APPL ECOL, V24, P337 DONCASTER CP, 1994, OIKOS, V69, P182 DUNNETT N, 2000, HORTTECHNOLOGY, V10, P40 FERNANDEZJURICIC E, 2000, CONSERV BIOL, V14, P513 GASTON KJ, IN PRESS BIODIVERSIT GERMAINE SS, 2001, BIOL CONSERV, V97, P229 GOULSON D, 2002, OECOLOGIA, V130, P267 HAMILTON G, 1992, LIVING GARDEN PRACTI HESSAYON DG, 1973, GARDEN BOOK EUROPE HEY D, 1998, HIST SHEFFIELD HILL F, 1996, WILDLIFE GARDENING P JOKIMAKI J, 1999, URBAN ECOSYSTEMS, V3, P21 KINZIG AP, 2001, ENCY BIODIVERSITY, V5, P733 KUSCHEL G, 1990, 3 DSIR PLANT PROT LIU JG, 2003, NATURE, V421, P530 MASON CF, 2000, DIVERS DISTRIB, V6, P189 MCCALL A, 1997, SCOTTISH NATURAL HER MIOTK P, 1996, ZOOL ANZ, V235, P101 MIYASHITA T, 1998, BIOL CONSERV, V86, P357 MORAN MD, 2003, OIKOS, V100, P403 NIEMELA J, 1999, BIODIVERS CONSERV, V8, P119 ODEGAARD F, 2000, DIVERS DISTRIB, V6, P45 OWEN J, 1991, ECOLOGY GARDEN 1 15 ROBINSON RA, 2002, J APPL ECOL, V39, P157 RONDININI C, 2002, FUNCT ECOL, V16, P504 SAVARD JPL, 2000, LANDSCAPE URBAN PLAN, V48, P131 SAVILLE B, 1997, SECRET GARDEN REPORT SOULE ME, 1988, CONSERV BIOL, V2, P75 STACE C, 1997, NEW FLORA BRIT ISLES SUKOPP H, 1999, ECOSYSTEMS DISTURBED, V16, P397 SWAN MJS, 1993, HERPTILE SITES, V1 THOMPSON K, 2003, J VEG SCI, V14, P71 THOMPSON K, 2004, J VEG SCI, V15, P371 VICKERY ML, 1995, ECOLOGY CONSERVATION, P123 0921-2973 Landsc. Ecol.ISI:000230299600009Univ Sheffield, Dept Anim & Plant Sci, Sheffield S10 2TN, S Yorkshire, England. Smith, RM, 12 Chestnut Grove, York YO26 6LE, N Yorkshire, England. r.m.smith@sheffield.ac.ukEnglishڽ72Smith, VincentM Greene, RobertB Silbernagel, Janet2013tThe social and spatial dynamics of community food production: a landscape approach to policy and program development 1415-1426Landscape Ecology287Springer NetherlandsqUrban agriculture Urban planning Community food security Community food production Socioeconomics Spatial pattern 2013/08/01+http://dx.doi.org/10.1007/s10980-013-9891-z 0921-2973Landscape Ecol10.1007/s10980-013-9891-zEnglish<7b0Smithwick, E. A. H. Harmon, M. E. Domingo, J. B.2003qModeling multiscale effects of light limitations and edge-induced mortality on carbon stores in forest landscapes701-721Landscape Ecology187additive model carbon disturbance emergent behaviors forest edges horizontal interactions light models scale spatial pattern wind CATASTROPHIC WIND PACIFIC-NORTHWEST DYNAMICS PATTERNS FRAGMENTATION RESPONSES ENGLAND DAMAGE USAArticleAnalyses of carbon ( C ) dynamics at broad scales usually do not consider spatial interactions. The assumption is that C dynamics can be modeled within homogenous ( i. e., even- aged ) patches and then summed to predict broad- scale dynamics ( an additive approach ). The goal of this paper is to elucidate the scales over which this additive approach is sufficient to explain observed C dynamics at broad scales. We define emergent " behaviors" ( vs. emergent " properties" ) as those behaviors that cannot be predicted solely from the additive properties of units at a finer scale. We used a forest process model to check for possible emergent behaviors due to pattern-process interactions at multiple levels, from the patch to the landscape. Specifically, using artificial forest landscapes with various spatial structures, we estimated the relative effects of edge- induced, tree mortality ( mainly due to wind ) and light limitations on C dynamics. Emergent behaviors were observed at all levels examined, indicating that emergent behaviors did not cease as one proceeded from the patch to the landscape level, as we had expected. However, the magnitude of the emergent behaviors depended on the level of spatial interaction considered as well as the type and intensity of the processes included. In all simulations, interactions of light and wind processes resulted in significant emergent behaviors only when parameters controlling wind mortality were set to the highest levels observed in the literature. In one simulation, the magnitude of emergent behaviors differed among the landscapes, indicating that interactions among patches may not be accounted for by an additive correction for edge effects unless spatial interactions are addressed. The implication is that some C dynamics in fragmented landscapes may not be captured at broad- scales using an additive approach, whereas in other cases spatial interactions are small enough to be ignored.://000186639000006 'ISI Document Delivery No.: 744NR Times Cited: 2 Cited Reference Count: 33 Cited References: ACKER SA, 1998, FOREST BIODIVERSITY, P93 BAKER WL, 1989, LANDSCAPE ECOL, V2, P111 BROWN S, 1996, AMBIO, V25, P273 CHEN JQ, 1992, ECOL APPL, V2, P387 COHEN WB, 1996, BIOSCIENCE, V46, P836 DESJARDINS RL, 1997, J GEOPHYS RES, V102, P125 DESJARDINS RL, 1997, J GEOPHYS RES, V102, P133 DESJARDINS RL, 1997, J GEOPHYS RES, V102, P29 FERREIRA LV, 1997, CONSERV BIOL, V11, P797 FOSTER DR, 1988, J ECOL, V76, P135 FOSTER DR, 1992, J ECOL, V80, P79 GOULDEN ML, 1996, GLOB CHANGE BIOL, V2, P169 HARMON ME, 2001, USERS GUIDE STANDCAR HARMON ME, 2002, IN PRESS CANADIAN J HOUGHTON RA, 2000, NATURE, V403, P301 KAHARABATA SK, 1997, J GEOPHYS RES-ATMOS, V102, P29113 KING AW, 1991, LANDSCAPE ECOLOGY, V5, P238 KRUMMEL JR, 1987, OIKOS, V48, P321 LAURANCE WF, 1998, ECOLOGY, V79, P2032 LI BL, 2000, ECOL MODEL, V132, P33 LIDICKER WZ, 1999, LANDSCAPE ECOL, V14, P333 LOVEJOY TE, 1984, EXTINCTIONS, P295 PARSONS WFJ, 1994, ECOL APPL, V4, P354 RANNEY JW, 1981, FOREST ISLAND DYNAMI, P67 RISSER PG, 1999, LANDSCAPE ECOLOGICAL, P3 SALT GW, 1979, AM NAT, V113, P145 SCHULZE ED, 2000, SCIENCE, V289, P2058 SINTON DS, 2000, ECOLOGY, V81, P2539 SMITHWICK EAH, 2002, ECOL APPL, V12, P1303 WATSON R, 2000, LAND USE LAND USE CH WILLIAMSLINERA G, 1990, J ECOL, V78, P356 WITH KA, 1997, CONSERV BIOL, V11, P1069 WOFSY SC, 1993, SCIENCE, V260, P1314 0921-2973 Landsc. Ecol.ISI:000186639000006Oregon State Univ, Dept Forest Sci, Corvallis, OR 97331 USA. Smithwick, EAH, Univ Wisconsin, Dept Zool, Birge Hall,430 Lincoln Dr, Madison, WI 53706 USA.English<70Smithwick, E. A. H. Harmon, M. E. Domingo, J. B.2007zChanging temporal patterns of forest carbon stores and net ecosystem carbon balance: The stand to landscape transformation77-94Landscape Ecology221landscape; carbon; disturbance; fire; harvest; NECB; NPP; model PACIFIC-NORTHWEST; FIRE FREQUENCY; BOREAL FOREST; PRODUCTIVITY; DISTURBANCE; MODELS; SCALE; USA; SEQUESTRATION; ATMOSPHEREArticleJanShort- and long-term patterns of net ecosystem carbon balance (NECB) for small, relatively uniform forest stands have been examined in detail, but the same is not true for landscapes, especially those with heterogeneous disturbance histories. In this paper, we explore the effect of two contrasting types of disturbances (i.e., fire and tree harvest) on landscape level NECB by using an ecosystem process model that explicitly accounts for changes in carbon (C) stores as a function of disturbance regimes. The latter were defined by the average disturbance interval, the regularity of the disturbance interval (i.e., random, based on a Poisson frequency distribution, or regular), the amount of C removed by the disturbance (i.e., severity), and the relative abundance of stands in the landscape with unique disturbance histories. We used the model to create over 300 hypothetical landscapes, each with a different disturbance regime, by simulating up to 200 unique stand histories and averaging their total C stores. Mean NECB and its year-to-year variability was computed by calculating the difference in mean total C stores from one year to the next. Results indicated that landscape C stores were higher for random than for regular disturbance intervals, and increased as the mean disturbance interval increased and as the disturbance severity decreased. For example, C storage was reduced by 58% when the fire interval was shortened from 250 years to 100 years. Average landscape NECB was not significantly different than zero for any of the simulated landscapes. Year-to-year variability in landscape NECB, however, was related to the landscape disturbance regime; increasing with disturbance severity and frequency, and higher for random versus regular disturbance intervals. We conclude that landscape C stores of forest systems can be predicted using the concept of disturbance regimes, a result that may be a useful for adjusting estimates of C storage to broad scales that are solely based on physiological processes.://000243619800008 ISI Document Delivery No.: 127XO Times Cited: 0 Cited Reference Count: 41 Cited References: APPS MJ, 2000, GLOBAL CLIMATE CHANG, P107 BAKER WL, 1989, CAN J FOREST RES, V19, P700 BONDLAMBERTY B, 2004, GLOBAL CHANGE BIOL, V10, P473 BORMANN FH, 1979, AM SCI, V67, P660 CHAPIN FS, IN PRESS ECOSYSTEMS EUSKIRCHEN ES, 2002, ECOL MODEL, V154, P75 GOULDEN ML, 1996, GLOB CHANGE BIOL, V2, P169 HARMON ME, 1996, CLIMATIC CHANGE, V33, P521 HARMON ME, 2001, J FOREST, V99, P24 HARMON ME, 2001, USERS GUIDE STANDCAR HARMON ME, 2002, CAN J FOREST RES, V32, P863 HOUGHTON RA, 1999, TELLUS B, V51, P298 HOUGHTON RA, 2003, GLOBAL CHANGE BIOL, V9, P500 JANISCH JE, 2002, TREE PHYSIOL, V22, P77 JOHNSON EA, 1985, CAN J FOREST RES, V15, P214 JOHNSON EA, 1994, ADV ECOL RES, V25, P239 KUHLBUSCH TAJ, 1996, J GEOPHYS RES, V101, P23 KUHLBUSCH TAJ, 1996, J GEOPHYS RES, V101, P651 KUHLBUSCH TAJ, 1996, J GEOPHYS RES, V101, P666 KURZ WA, 1998, MITIGATION ADAPTATIO, V2, P405 LAW BE, 2000, GLOB CHANGE BIOL, V6, P155 LAW BE, 2004, GLOBAL CHANGE BIOL, V10, P1429 PACALA SW, 2001, SCIENCE, V292, P2316 PENG CH, 1999, ECOL MODEL, V122, P175 RAISON RJ, 1979, PL SOIL, V51, P73 ROMME WH, 1982, BIOSCIENCE, V32, P664 SCHIMEL DS, 1997, ECOL MONOGR, V67, P251 SCHIMEL DS, 2001, NATURE, V414, P169 SHUGART HH, 1981, AM SCI, V69, P647 SMITHWICK EAH, 2002, ECOL APPL, V12, P1303 SMITHWICK EAH, 2002, THESIS OREGON STATE SMITHWICK EAH, 2003, LANDSCAPE ECOL, V18, P701 SMITHWICK EAH, 2005, ECOSYSTEMS, V8, P163 SUN OJ, 2004, GLOBAL CHANGE BIOL, V10, P1470 TANS PP, 1990, SCIENCE, V247, P1431 THORNLEY JHM, 2004, TREE PHYSIOL, V24, P765 TURNER MG, 1993, LANDSCAPE ECOL, V8, P213 VANWAGNER CE, 1978, CANADIAN J FOREST RE, V8, P220 WATT AS, 1947, J ECOL, V35, P1 WIRTH C, 2002, PLANT SOIL, V242, P41 ZACKRISSON O, 1996, OIKOS, V77, P10 0921-2973 Landsc. Ecol.ISI:000243619800008&Univ Wisconsin, Dept Zool, Madison, WI 53706 USA. Oregon State Univ, Dept Forest Sci, Corvallis, OR 97330 USA. Univ Wisconsin, Dept Forest Ecol & Management, Madison, WI 53706 USA. Smithwick, EAH, Univ Wisconsin, Dept Zool, Birge Hall,430 Lincoln Dr, Madison, WI 53706 USA. easmithwick@wisc.eduEnglish r|7#Snep, R. P. H. Ottburg, F. G. W. A.2008The 'habitat backbone' as strategy to conserve pioneer species in dynamic port habitats: lessons from the natterjack toad (Bufo calamita) in the Port of Antwerp (Belgium) 1277-1289Landscape Ecology2310urban ecology habitat backbone dynamic habitat pioneer species port area business site industrial site habitat network metapopulation natterjack toad bufo calamita urban landscape populations persistence fragmentsDec^Biodiversity conservation in economic areas like ports has recently become more important in the European Union due to a stricter interpretation of nature protection laws. In this study we develop a planning and design strategy-the 'habitat backbone'aEuro"with which to support the long-term survival of pioneer species that occur in ports and have low dispersal abilities. For those species, long-term survival in port areas is uncertain because supply of their habitats (on vacant lots) is capricious and depends on land use dynamics. By gaining knowledge about spatial and temporal characteristics of these dynamics we were able to develop a solution to conserve such species. Our solution is based on the creation of permanent habitat-defined as a 'backbone'aEuro"on (semi-) public land with an overall carrying capacity sufficient to support persistent populations. This best ensures long-term survival, and the backbone may also act as refugium. Satellite populations that emerge on adjacent vacant lots will thereby add to the persistence of the overall metapopulation. Management of permanent habitat is focused on retaining early-successional stages of vegetation. Implementing this strategy in the case of the natterjack toad in the Port of Antwerp taught us that realization of a habitat backbone is possible only if landowners, local governments and environmental NGOs cooperate. In the case at hand, such cooperation resulted in a plan that should ensure a coherent and persistent habitat network in which a chorus of some 1,400 natterjack toads could be accommodated-more than the number of toads currently observed.://000261790600011-385CL Times Cited:0 Cited References Count:41 0921-2973ISI:000261790600011Snep, RPH Alterra Wageningen UR, POB 47, NL-6700 AA Wageningen, Netherlands Alterra Wageningen UR, NL-6700 AA Wageningen, NetherlandsDoi 10.1007/S10980-008-9266-ZEnglish|?#5Snow, Nathan P. Williams, David M. Porter, William F.2014RA landscape-based approach for delineating hotspots of wildlife-vehicle collisions817-829Landscape Ecology295MayBImposing human perceptions about the scales of ecological processes can produce unreliable scientific inferences in wildlife research and possibly misinform mitigation strategies. An example of this disconnect occurs in studies of wildlife-vehicle collisions (WVCs). Subjective procedures are often used to delineate hotspots of WVCs, resulting in hotspots that are not spatially independent. We developed a new approach that identifies independent hotspots using attributes of the landscape to inform delineations instead of subjective measures. First, we generated a candidate set of grouping scenarios using unique combinations of kernel-density estimation parameterization (i.e., bandwidth and isopleth values). Next, we associated the groups of WVCs with attributes of the surrounding landscape. Finally, we identified the grouping scenario with the highest amount of variation in the landscape among the groups. The highest variation corresponded to hotspots that were most distinguishable from each other (i.e., most independent) based on the surrounding landscape. We tested our approach on 3 species of wildlife [island foxes (Urocyon littoralis) on San Clemente Island, CA; white-tailed deer (Odocoileus virginianus) in Onondaga County, NY; and moose (Alces alces) in western Maine] that exemplified varying degrees of space-use in different landscapes. We found that the landscape-based approach was able to effectively delineate independent hotspots for each species without using subjective measures. The landscape-based approach delineated fewer or larger hotspots than currently used methods, suggesting a reduction in spatial dependency among hotspots. Variation in the landscape indicated that hotspots may be larger than previously identified; therefore current mitigation strategies should be adjusted to include larger areas of high risk.!://WOS:000334689900005Times Cited: 0 0921-2973WOS:00033468990000510.1007/s10980-014-0018-y<7^6Snyder, C. D. Young, J. A. Villella, R. Lemarie, D. P.2003NInfluences of upland and riparian land use patterns on stream biotic integrity647-664Landscape Ecology187biotic integrity fish assemblages gradient land use riparian scale stream habitat urban water quality FISH COMMUNITIES WISCONSIN STREAMS HABITAT STRUCTURE WATER-QUALITY INDEX LANDSCAPE ECOSYSTEM COVER CLASSIFICATION PERSPECTIVEArticlemWe explored land use, fish assemblage structure, and stream habitat associations in 20 catchments in Opequon Creek watershed, West Virginia. The purpose was to determine the relative importance of urban and agriculture land use on stream biotic integrity, and to evaluate the spatial scale ( i. e., whole- catchment vs riparian buffer) at which land use effects were most pronounced. We found that index of biological integrity ( IBI) scores were strongly associated with extent of urban land use in individual catchments. Sites that received ratings of poor or very poor based on IBI scores had > 7% of urban land use in their respective catchments. Habitat correlations suggested that urban land use disrupted flow regime, reduced water quality, and altered stream channels. In contrast, we found no meaningful relationship between agricultural land use and IBI at either whole- catchment or riparian scales despite strong correlations between percent agriculture and several important stream habitat measures, including nitrate concentrations, proportion of fine sediments in riffles, and the abundance of fish cover. We also found that variation in gradient ( channel slope) influenced responses of fish assemblages to land use. Urban land use was more disruptive to biological integrity in catchments with steeper channel slopes. Based on comparisons of our results in the topographically diverse Opequon Creek watershed with results from watersheds in flatter terrains, we hypothesize that the potential for riparian forests to mitigate effects of deleterious land uses in upland portions of the watershed is inversely related to gradient.://000186639000002 ISI Document Delivery No.: 744NR Times Cited: 13 Cited Reference Count: 56 Cited References: *US EPA, 2000, EPA841F00006 ANGERMEIER PL, 1995, CAN J FISH AQUAT SCI, V52, P936 BARTON DR, 1985, N AM J FISH MANAGE, V5, P364 BISSON PA, 1987, CONTRIBUTION U WASHI, V57, P143 BROWNE FX, 1981, J WATER POLLUTION CO, V53, P901 CORRELL DL, 1992, ESTUARIES, V15, P431 CUMMINS KW, 1962, AM MIDL NAT, V67, P477 CUMMINS KW, 1992, RIVER CONSERVATION M, P125 DAVIES PE, 1994, AUST J MAR FRESH RES, V45, P1289 FRISSELL CA, 1986, ENVIRON MANAGE, V10, P199 GORMAN OT, 1978, ECOLOGY, V59, P507 GREENBERG AE, 1992, STANDARD METHODS EXA GREGORY KJ, 1992, RIVER CONSERVATION M, P255 GREGORY SV, 1991, BIOSCIENCE, V41, P540 HAWKINS CP, 1993, FISHERIES, V18, P3 HYNES HBN, 1975, VERH INT VEREIN LIMN, V19, P1 IMHOF JG, 1991, T 56 N AM WILDL NAT, P269 JUDY RD, 1984, FWSOBS8406 KARR JR, 1991, ECOL APPL, V1, P66 KLAUDA R, 1998, ENVIRON MONIT ASSESS, V51, P299 LAMMERT M, 1999, ENVIRON MANAGE, V23, P257 LEOPOLD LB, 1968, 554 US GEOL SURV LYDY MJ, 2000, ARCH ENVIRON CON TOX, V39, P523 LYONS J, 1992, N AM J FISH MANAGE, V12, P198 MCCORMICK FH, 2001, T AM FISH SOC, V130, P857 MCDONNELL MJ, 1990, ECOLOGY, V71, P1232 NAIMAN RJ, 1990, ECOLOGY MANAGEMENT A NAIMAN RJ, 1992, RIVER CONSERVATION M, P93 NAIMAN RJ, 1993, ECOL APPL, V3, P209 OSBORNE LL, 1988, J ENVIRON MANAGE, V26, P9 PERTERJOHN WT, 1984, ECOLOGY, V65, P1466 POFF NL, 1990, ENVIRON MANAGE, V14, P629 RABENI CF, 1995, HYDROBIOLOGIA, V303, P211 RICHARDS C, 1996, CAN J FISH AQUAT S1, V53, P295 RISSER PG, 1990, ECOLOGY MANAGEMENT A, P7 ROSGEN DL, 1994, CATENA, V22, P169 ROTH N, 1998, ENVIRON MONIT ASSESS, V51, P89 ROTH NE, 1996, LANDSCAPE ECOL, V11, P141 ROTH NE, 2000, CBWPMANTAEA00 VERS I SCHIEMER F, 1992, NETH J ZOOL, V42, P323 SCHLEIGER SL, 2000, T AM FISH SOC, V129, P1118 SCHLOSSER IJ, 1982, ECOL MONOGR, V52, P395 SCHLOSSER IJ, 1991, BIOSCIENCE, V41, P704 SHELDON AL, 1995, CAN J FISH AQUAT SCI, V52, P23 STAUFFER JC, 2000, CAN J FISH AQUAT SCI, V57, P307 STEEDMAN RJ, 1988, CANADIAN J FISHERIES, V45, P492 SWEENEY BW, 1992, WATER SCI TECHNOL, V26, P2653 VANNOTE RL, 1980, CAN J FISH AQUAT SCI, V37, P130 VOGELMANN JE, 1998, ENVIRON MONIT ASSESS, V51, P415 VOGELMANN JE, 1998, PHOTOGRAMM ENG REM S, V64, P45 WALLACE JB, 1999, ECOL MONOGR, V69, P409 WANG LZ, 1997, FISHERIES, V22, P6 WANG LZ, 2000, J AM WATER RESOUR AS, V36, P1173 WISSMAR RC, 1990, ECOLOGY MANAGEMENT A, P65 WOOTTON RJ, 1990, ECOLOGY TELEOST FISH ZAMPELLA RA, 1994, WATER RESOUR BULL, V30, P605 0921-2973 Landsc. Ecol.ISI:000186639000002US Geol Survey, Leetown Sci Ctr, Biol Resources Div, Kearneysville, WV 25430 USA. Snyder, CD, US Geol Survey, Leetown Sci Ctr, Biol Resources Div, Kearneysville, WV 25430 USA.English <7 }Soares, B. Silvestrini, R. Nepstad, D. Brando, P. Rodrigues, H. Alencar, A. Coe, M. Locks, C. Lima, L. Hissa, L. Stickler, C.2012tForest fragmentation, climate change and understory fire regimes on the Amazonian landscapes of the Xingu headwaters585-598Landscape Ecology274carbon fluxes landscape dynamics landscape metrics spatially-explicit modeling land-use management brazilian amazon land-use cellular-automata rain-forest deforestation dieback carbon dynamics model emissionsApr#Understory fire modeling is a key tool to investigate the cornerstone concept of landscape ecology, i.e. how ecological processes relate to landscape structure and dynamics. Within this context, we developed FISC-a model that simulates fire ignition and spread and its effects on the forest carbon balance. FISC is dynamically coupled to a land-use change model to simulate fire regimes on the Amazonian landscapes of the Xingu Headwaters under deforestation, climate change, and land-use management scenarios. FISC incorporates a stochastic cellular automata approach to simulate fire spread across agricultural and forested lands. CARLUC, nested in FISC, simulates fuel dynamics, forest regrowth, and carbon emissions. Simulations of fire regimes under modeled scenarios revealed that the major current and future driver of understory fires is forest fragmentation rather than climate change. Fire intensity proved closely related to the landscape structure of the remaining forest. While climate change may increase the percentage of forest burned outside protected areas by 30% over the next four decades, deforestation alone may double it. Nevertheless, a scenario of forest recovery and better land-use management would abate fire intensity by 18% even in the face of climate change. Over this time period, the total carbon balance of the Xingu's forests varies from an average net sink of 1.6 ton ha(-1) year(-1) in the absence of climate change, fire and deforestation to a source of -0.1 ton ha(-1) year(-1) in a scenario that incorporates these three processes.://000302346900009-919RS Times Cited:0 Cited References Count:51 0921-2973Landscape EcolISI:000302346900009Univ Fed Minas Gerais, Ctr Sensoriamento Remoto, Av Antonio Carlos 6627, BR-31270900 Belo Horizonte, MG, Brazil Univ Fed Minas Gerais, Ctr Sensoriamento Remoto, Av Antonio Carlos 6627, BR-31270900 Belo Horizonte, MG, Brazil Univ Fed Minas Gerais, Ctr Sensoriamento Remoto, BR-31270900 Belo Horizonte, MG, Brazil Inst Pesquisa Ambiental Amazonia IPAM, BR-66035170 Belem, Para, Brazil Woods Hole Res Ctr, Falmouth, MA 02540 USA Alianca Terra, BR-74670600 Goiania, Go, BrazilDOI 10.1007/s10980-012-9723-6English0|? FSohl, T. L. Loveland, T. R. Sleeter, B. M. Sayler, K. L. Barnes, C. A.2010HAddressing foundational elements of regional land-use change forecasting233-247Landscape Ecology252Regional land-use models must address several foundational elements, including understanding geographic setting, establishing regional land-use histories, modeling process and representing drivers of change, representing local land-use patterns, managing issues of scale and complexity, and development of scenarios. Key difficulties include managing an array of biophysical and socioeconomic processes across multiple spatial and temporal scales, and acquiring and utilizing empirical data to support the analysis of those processes. The Southeastern and Pacific Northwest regions of the United States, two heavily forested regions with significant forest industries, are examined in the context of these foundational elements. Geographic setting fundamentally affects both the primary land cover (forest) in the two regions, and the structure and form of land use (forestry). Land-use histories of the regions can be used to parameterize land-use models, validate model performance, and explore land-use scenarios. Drivers of change in the two regions are many and varied, with issues of scale and complexity posing significant challenges. Careful scenario development can be used to simplify process-based land-use models, and can improve our ability to address specific research questions. The successful modeling of land-use change in these two areas requires integration of both top-down and bottom-up drivers of change, using scenario frameworks to both guide and simplify the modeling process. Modular approaches, with utilization and integration of existing process models, allow regional land-use modelers the opportunity to better represent primary drivers of land-use change. However, availability of data to represent driving forces remains a primary obstacle.!://WOS:000274437100006Times Cited: 0 0921-2973WOS:00027443710000610.1007/s10980-009-9391-3<7Sondgerath, D. Schroder, B.2001mPopulation dynamics and habitat connectivity affecting the spatial spread of populations - a simulation study57-70Landscape Ecology171cellular automaton dispersal habitat suitability habitat connectivity Leslie matrix population dynamics spatially explicit modeling stepping stone habitats LANDSCAPE STRUCTURE METAPOPULATION PERSISTENCE EXPLICIT MODEL DISPERSAL FRAGMENTATION ENVIRONMENTS THRESHOLDS ABUNDANCE MAMMALSArticleIn this paper we show how the spatial configuration of habitat quality affects the spatial spread of a population in a heterogeneous environment. Our main result is that for species with limited dispersal ability and a landscape with isolated habitats, stepping stone patches of habitat greatly increase the ability of species to disperse. Our results show that increasing reproductive rate first enables and then accelerates spatial spread, whereas increasing the connectivity has a remarkable effect only in case of low reproductive rates. The importance of landscape structure varied according to the demographic characteristics of the population. To show this we present a spatially explicit habitat model taking into account population dynamics and habitat connectivity. The population dynamics are based on a matrix projection model and are calculated on each cell of a regular lattice. The parameters of the Leslie matrix depend on habitat suitability as well as density. Dispersal between adjacent cells takes place either unrestricted or with higher probability in the direction of a higher habitat quality (restricted dispersal). Connectivity is maintained by corridors and stepping stones of optimal habitat quality in our fragmented model landscape containing a mosaic of different habitat suitabilities. The cellular automaton model serves as a basis for investigating different combinations of parameter values and spatial arrangements of cells with high and low quality.://000176014400005 ISI Document Delivery No.: 559FF Times Cited: 10 Cited Reference Count: 75 Cited References: *US FISH WILDL SER, 1980, HAB EV PROC HEP ADLER GH, 1985, OECOLOGIA, V66, P178 AKCAKAYA HR, 1995, BIOL CONSERV, V73, P169 AKCAKAYA HR, 1997, CONSERV BIOL, V11, P422 AMARASEKARE P, 1998, THEOR POPUL BIOL, V53, P44 ANDREN H, 1994, OIKOS, V71, P355 APPELT M, 1997, J INSECT CONSERV, V1, P205 BASCOMPTE J, 1998, MODELING SPATIOTEMPO BOTSFORD LW, 1996, STRUCTURED POPULATIO, P371 BOWNE DR, 1999, LANDSCAPE ECOL, V14, P53 BROOKER L, 1999, CONS ECOL, V3 BURGMAN MA, 1993, RISK ASSESSMENT CONS CANTWELL MD, 1993, LANDSCAPE ECOL, V8, P239 CASWELL H, 1989, MATRIX POPULATION MO CASWELL H, 1996, STRUCTURED POPULATIO, P19 CZARAN T, 1998, SPATIOTEMPORAL MODEL CZARAN T, 1998, TRENDS ECOL EVOL, V13, P294 DEANGELIS DL, 1988, ECOLOGICAL MODELLING, V43, P57 DICOLA G, 1999, ECOLOGICAL ENTOMOLOG, P503 DOAK DF, 1992, THEOR POPUL BIOL, V41, P315 DUNNING JB, 1995, ECOL APPL, V5, P3 FAHRIG L, 1991, QUANTITATIVE METHODS, P417 FAHRIG L, 1998, ECOL MODEL, V105, P273 GARDNER RH, 1989, LANDSCAPE ECOL, V3, P217 GARDNER RH, 1993, HUMANS COMPONENTS EC, P208 GRIEBELER EM, 2000, J INSECT CONSERV, V4, P225 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HANSKI I, 1995, OIKOS, V72, P21 HENEIN K, 1990, LANDSCAPE ECOL, V4, P157 HOSMER DW, 1989, APPL LOGISTIC REGRES HUGHES TP, 1987, AM NAT, V129, P818 INGRISCH S, 1998, HEUSCHRECKEN MITTELE JELTSCH F, 1998, J ECOL, V86, P780 KAREIVA P, 1990, PHILOS T ROY SOC B, V330, P175 KEITT TH, 1997, CONS ECOL, V1 KLEYER M, 1999, Z OKOLOGIE NATURSCHU, V8, P177 LAW R, 1990, ECOLOGY, V71, P1863 LEFKOVITCH LP, 1965, BIOMETRICS, V21, P1 LESLIE PH, 1945, BIOMETRIKA 3, V33, P183 LETCHER BH, 1998, BIOL CONSERV, V86, P1 LINDENMAYER DB, 1996, LANDSCAPE ECOL, V11, P79 MCINTYRE NE, 1999, OIKOS, V86, P129 MILNE BT, 1996, ECOLOGY, V77, P805 MORRISON ML, 1998, WILDLIFE HABITAT REL ONEILL RV, 1988, LANDSCAPE ECOL, V2, P63 PHIPPS MJ, 1992, INDIVIDUAL BASED MOD, P165 POFF NL, 1997, J N AM BENTHOL SOC, V16, P263 ROOT KV, 1998, ECOL APPL, V8, P854 RUXTON GD, 1996, B MATH BIOL, V58, P643 SCHRAEDER T, 1999, AM J SPEECH-LANG PAT, V8, P195 SCHRODER B, 2000, THESIS TU BRAUNSCHWE SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SONDGERATH D, 1996, ECOL MODEL, V91, P67 STAUFFER D, 1991, INTRO PERCOLATION TH STORM GL, 1993, ARCH ENVIRON CON TOX, V25, P428 SZACKI J, 1999, LANDSCAPE ECOL, V14, P369 TAYLOR PD, 1993, OIKOS, V68, P571 TILMAN D, 1997, SPATIAL ECOLOGY ROLE, P3 TISCHENDORF L, 2000, LANDSCAPE ECOL, V15, P633 TISCHENDORF L, 2000, OIKOS, V90, P7 TRAVIS JMJ, 1998, P ROY SOC LOND B BIO, V265, P17 TREXLER JC, 1993, ECOLOGY, V74, P1629 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 WAGNER TL, 1984, ANN ENTOMOL SOC AM, V77, P475 WEIMAR JR, 1997, SIMULATION CELLULAR WIEGAND T, 1999, AM NAT, V154, P605 WIENS JA, 1989, LANDSCAPE ECOLOGY, V3, P87 WIENS JA, 1993, OIKOS, V66, P369 WIENS JA, 1995, MOSAIC LANDSCAPES EC, P1 WIENS JA, 1997, OIKOS, V78, P257 WISSEL C, 1991, MOSAIC CYCLE CONCEPT, P22 WITH KA, 1994, LANDSCAPE ECOL, V9, P25 WITH KA, 1995, ECOLOGY, V76, P2446 WITH KA, 1997, OIKOS, V78, P151 WITH KA, 1999, CONSERV BIOL, V13, P314 0921-2973 Landsc. Ecol.ISI:000176014400005Tech Univ Carolo Wilhelmina Braunschweig, Inst Geoecol, D-38106 Braunschweig, Germany. Schroder, B, Univ Oldenburg, Dept Biol Earth & Environm Sci, Landscape Ecol Grp, D-26111 Oldenburg, Germany. boris.schroeder@uni-oldenburg.deEnglish|?&5Sonnier, Gregory Jamoneau, Aurelien Decocq, Guillaume2014bEvidence for a direct negative effect of habitat fragmentation on forest herb functional diversity857-866Landscape Ecology295MayHThe effects of habitat fragmentation on species richness and composition have been extensively studied. However, little is known about how fragmentation affects functional diversity patterns. Fragmentation can indeed affect functional diversity directly (e.g. by promoting traits associated to long-distance dispersal when fragment isolation increases) or indirectly (e.g. by decreasing species richness, hence trait diversity, when fragment area decreases). Here, we used structural equation modeling to determine whether factors associated to forest fragmentation, namely area, habitat heterogeneity, spatial isolation and age have a direct effect on forest herb functional diversity. Using occurrence data from 243 forest fragments located in northern France and six plant life-history traits, we estimated species richness and calculated functional diversity in each of these 243 forest fragments. We found that species richness was the primary driver of functional diversity in these fragments, with a strong positive and direct relationship between species richness and functional diversity. Interestingly, both fragment isolation and age had a direct negative effect on functional diversity independent of their effects on species richness. Isolation selected life-history traits associated with long-distance dispersal, while age selected for life-history traits typical of forest habitat specialists. Isolated and/or older forest fragments are thus at greater risk of local species and functional extinctions, and hence making these forest fragments particularly vulnerable to future global changes.!://WOS:000334689900008Times Cited: 0 0921-2973WOS:00033468990000810.1007/s10980-014-0022-2><7^Sork, V. L. Smouse, P. E.2006>Genetic analysis of landscape connectivity in tree populations821-836Landscape Ecology216Wgene flow; genetic diversity; genetic structure; habitat fragmentation; isolation; landscape connectivity; pollen dispersal; seed dispersal DISTANCE SEED DISPERSAL; TROPICAL DRY FOREST; POLLEN FLOW; 2-GENERATION ANALYSIS; PATERNITY ANALYSIS; MULTILOCUS GENOTYPES; REPRODUCTIVE SUCCESS; PARENTAGE ANALYSIS; ASSIGNMENT METHODS; PLANT-POPULATIONSArticleAugGenetic connectivity in plant populations is determined by gene movement within and among populations. When populations become genetically isolated, they are at risk of loss of genetic diversity that is critical to the long-term survival of populations. Anthropogenic landscape change and habitat fragmentation have become so pervasive that they may threaten the genetic connectivity of many plant species. The theoretical consequences of such changes are generally understood, but it is not immediately apparent how concerned we should be for real organisms, distributed across real landscapes. Our goals here are to describe how one can study gene movement of both pollen and seeds in the context of changing landscapes and to explain what we have learned so far. In the first part, we will cover methods of describing pollen movement and then review evidence for the impact of fragmentation in terms of both the level of pollen flow into populations and the genetic diversity of the resulting progeny. In the second part, we will describe methods for contemporary seed movement, and describe findings about gene flow and genetic diversity resulting from seed movement. Evidence for pollen flow suggests high connectivity, but it appears that seed dispersal into fragments may create genetic bottlenecks due to limited seed sources. Future work should address the interaction of pollen and seed flow and attention needs to be paid to both gene flow and the diversity of the incoming gene pool. Moreover, if future work is to model the impact of changing landscapes on propagule movement, with all of its ensuing consequences for genetic connectivity and demographic processes, we will need an effective integration of population genetics and landscape ecology.://000239484200004 ISI Document Delivery No.: 069YA Times Cited: 5 Cited Reference Count: 83 Cited References: ABRAMOWITZ M, 1964, HDB MATH FUNCTIONS F ADAMS WT, 1992, AM NAT, V140, P762 ALDRICH PR, 1998, SCIENCE, V281, P103 AUSTERLITZ F, 2001, GENETICS, V157, P851 AUSTERLITZ F, 2002, GENETICS, V161, P355 AUSTERLITZ F, 2003, HEREDITY, V90, P282 AUSTERLITZ F, 2004, MOL ECOL, V13, P937 BERRY O, 2004, MOL ECOL, V13, P551 BOSSEMA I, 1979, BEHAVIOUR, V70, P1 BROOKSHIRE B, 1993, P 9 CENTR HARDW FOR, P289 BURCZYK J, 2002, MOL ECOL, V11, P2379 BURCZYK J, 2004, EVOLUTION, V58, P956 BURCZYK J, 2004, FOREST GENETICS, V11, P179 CLARK JS, 1998, AM NAT, V152, P204 COCKERHAM CC, 1993, EVOLUTION, V47, P855 CORNUET JM, 1999, GENETICS, V153, P1989 DALLING JW, 2002, J ECOL, V90, P714 DARLEYHILL S, 1981, OECOLOGIA, V50, P231 DAVIS MB, 1981, FOREST SUCCESSION CO, P132 DEVLIN B, 1990, EVOLUTION, V44, P248 DICK CW, 2003, MOL ECOL, V12, P753 DOW BD, 1996, MOL ECOL, V5, P615 DUNPHY BK, 2004, INT J PLANT SCI, V165, P427 DYER RJ, 2002, THESIS U MISSOURI ST ELLSTRAND NC, 1984, AM NAT, V123, P819 ELLSTRAND NC, 1993, ANNU REV ECOL SYST, V24, P217 EPPERSON BK, 2003, GEOGRAPHICAL GENETIC ESSENMOLLER E, 1938, MITT ANTHR GES WIEN, V68, P9 EXCOFFIER L, 1992, GENETICS, V131, P491 FERNANDEZ MJJ, IN PRESS BIOTROPICA FERNANDEZ MJJ, 2005, J HERED FRANKHAM R, 2002, INTRO CONSERVAT6ION FUCHS EJ, 2003, CONSERV BIOL, V17, P149 GERBER S, 2003, MOL ECOL NOTES, V3, P479 GODOY JA, 2001, MOL ECOL, V10, P2275 GRIVET D, 2005, MOL ECOL, V14, P3585 HAMRICK JL, 2000, FOREST CONSERVATION, P81 HAMRICK JL, 2004, FOREST ECOL MANAG, V197, P323 HARRISON S, 1996, TRENDS ECOL EVOL, V11, P180 HE TH, 2004, MOL ECOL, V13, P1099 HOLDEREGGER R, LANDSCAPE ECOL IRWIN AJ, 2003, HEREDITY, V90, P187 JAMES T, 1998, BIOTROPICA, V30, P587 KABRICK JM, 2002, P 2 MISS OZ FOR EC S, P84 LECORRE V, 1997, GENET RES, V69, P117 LEDIG FT, 1992, OIKOS, V63, P87 MANEL S, 2003, TRENDS ECOL EVOL, V18, P189 MANEL S, 2005, TRENDS ECOL EVOL, V20, P136 MARSHALL TC, 1998, MOL ECOL, V7, P639 MCLACHLAN JS, 2005, ECOLOGY, V86, P2088 MEAGHER TR, 1987, ECOLOGY, V68, P803 NASON JD, 1996, J BIOGEOGR, V23, P501 NASON JD, 1997, J HERED, V88, P264 PAETKAU D, 2004, MOL ECOL, V13, P55 PEAKALL R, 1995, MOL ECOL, V4, P135 PIELOU EC, 1979, BIOGEOGRAPHY PRITCHARD JK, 2000, GENETICS, V155, P945 RANNALA B, 1997, P NATL ACAD SCI USA, V94, P9197 RITLAND K, 1989, EVOLUTION, V43, P848 RITLAND K, 1990, J HERED, V81, P235 ROBLEDOARNUNCIO JJ, 2004, MOL ECOL, V13, P2567 ROCHA OJ, 2001, AM J BOT, V88, P1600 ROEDER K, 1989, BIOMETRICS, V45, P363 RUSSO SE, 2004, ECOL LETT, V7, P1058 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SCHNABEL A, 1998, ADV MOL ECOLOGY, P173 SCHNABEL A, 1998, MOL ECOL, V7, P819 SEZEN UU, 2005, SCIENCE, V307, P891 SMOUSE PE, 1998, J HERED, V89, P143 SMOUSE PE, 1999, J EVOLUTION BIOL, V12, P1069 SMOUSE PE, 2001, EVOLUTION, V55, P260 SMOUSE PE, 2004, FOREST ECOL MANAG, V197, P21 SOONS MB, 2004, ECOLOGY, V85, P3056 SORK VL, 1999, TRENDS ECOL EVOL, V14, P219 SORK VL, 2002, MOL ECOL, V11, P1657 SORK VL, 2005, AM J BOT, V92, P262 STREIFF R, 1999, MOL ECOL, V8, P831 WHITE GM, 2002, P NATL ACAD SCI USA, V99, P2038 WRIGHT S, 1943, GENETICS, V28, P114 WRIGHT S, 1946, GENETICS, V31, P39 WRIGHT SJ, 2001, BIOTROPICA, V33, P583 YOUNG A, 1996, TRENDS ECOL EVOL, V11, P413 YOUNG AG, 2000, GENETICS DEMOGRAPHY 0921-2973 Landsc. Ecol.ISI:000239484200004RUniv Calif Los Angeles, Dept Ecol & Evolut Biol, Los Angeles, CA 90095 USA. Univ Calif Los Angeles, Inst Environm, Los Angeles, CA 90095 USA. Rutgers State Univ, Dept Ecol Evolut & Nat Resources, New Brunswick, NJ 08901 USA. Sork, VL, Univ Calif Los Angeles, Dept Ecol & Evolut Biol, Box 951606, Los Angeles, CA 90095 USA. vlsork@ucla.eduEnglish <7Sousa, A. Garcia-Murillo, P.2001jCan place names be used as indicators of landscape changes? Application to the Donana Natural Park (Spain)391-406Landscape Ecology165eAbalario Donana Spain forestry cultivation lagoons landscape peat bogs place names vegetation BRITAINArticleJul|This work broaches the possibility of using place names as indicators of original landscapes that have been much transformed. The reconstruction of landscape elements from place names is commonly disputed because such daring notion is impossible to demonstrate. The present case avoids this by making a preliminary study of changes in the landscape using conventional methods. With the knowledge gained from objective and reliable sources, the possibility is analyzed of whether place names are a reflection of landscape changes taking place over a considerable period of time (the last few centuries). It is concluded that, for the present case study, in natural areas with a high rate of change of land use (Donana Natural Park), place names indicate not only changes in the landscape, but also how such changes are perceived. In the study area, this is especially clear regarding the fens.://000170952100002 WISI Document Delivery No.: 471WR Times Cited: 3 Cited Reference Count: 34 Cited References: *CONS POL TERR, 1984, EST SIST REC UT TOP *CTR EST TERR URB, 1990, CONS OBR PUBL TRANSP *CTR EST TERR URB, 1990, CONS OBR PUBL TRANSP, V5 ALCAZAR A, 1988, ESTUDIOS GEOGRAFICOS, V192, P329 ALLUE JL, 1990, ATLAS FITOCLIMATICO AYBES C, 1995, MAMMAL REV, V25, P201 BERNALDEZ FG, 1981, ECOLOGIA PAISAJE BERNALDEZ FG, 1992, PAISAJES AGUA TERMIN BOISSEAU S, 1998, IBIS, V140, P482 BORNAECHEA A, 1984, ESTUDIOS GEOGRAFICOS, V177, P483 CALVO JL, 1992, INT CTR ADV MEDITERR COROMINAS J, 1972, TOPICA HESPERICA COROMINAS J, 1997, BREVE DICCIONARIO ET DEDIEGO VG, 1959, ARCH HISPALENSE, P93 DEDIEGO VG, 1972, TOPONIMIA ZONA JEREZ EKWALL E, 1990, CONCISE OXFORD DICT ESPINA J, 1992, PROGRAMA RECUPERACIO, V3 ESPINA J, 1993, INTERVENCIONES PUBLI, P95 FIGUEROA LM, 1981, TERRES ALMENARA COST GELLING M, 1984, PLACE NAMES LANDSCAP GELLING M, 1987, LEEDS STUDIES ENGLIS, V18, P173 GORDON MD, 1988, TOPONIMIA SIERRA NOR GORDON MD, 1991, ESTUDIO LEXICOSEMANT LITTON RB, 1968, PSW49 USDA MADOZ P, 1848, DICCIONARIO GEOGRAFI MURILLO PG, 1995, ANAL JARD BOT MADRID, V53, P245 MURILLO PG, 1997, LAGASCALIA, V19, P737 MURILLO PG, 1999, LAGASCALIA, V21, P111 OJEDA JF, 1987, ORG TERRITORIO DONAN ONTIVEROS AL, 1987, SEMINARIO PAISAJE DE ONTIVEROS AL, 1991, CAZA PAISAJE GEOGRAF RACKHAM O, 1986, HIST COUNTRYSIDE SOUSA A, 1998, HUELVA ERIA, V46, P165 SOUSA A, 2000, TOPONIMOS COMO INDIC 0921-2973 Landsc. Ecol.ISI:000170952100002Univ Sevilla, Dept Biol Vegetal & Ecol, E-41080 Seville, Spain. Sousa, A, Univ Sevilla, Dept Biol Vegetal & Ecol, Apdo 874, E-41080 Seville, Spain.English|? kSpies, Thomas A. Giesen, Thomas W. Swanson, Frederick J. Franklin, Jerry F. Lach, Denise Johnson, K. Norman2010Climate change adaptation strategies for federal forests of the Pacific Northwest, USA: ecological, policy, and socio-economic perspectives 1185-1199Landscape Ecology258OctConserving biological diversity in a changing climate poses major challenges for land managers and society. Effective adaptive strategies for dealing with climate change require a socio-ecological systems perspective. We highlight some of the projected ecological responses to climate change in the Pacific Northwest, U.S.A and identify possible adaptive actions that federal forest managers could take. The forest landscape, ownership patterns and recent shift toward ecologically based forest management provide a good starting place for conserving biological diversity under climate change. Nevertheless, undesirable changes in species and ecosystems will occur and a number of adaptive actions could be undertaken to lessen the effects of climate change on forest ecosystems. These include: manipulation of stand and landscape structure to increase ecological resistance and resilience; movement of species and genotypes; and engaging in regional, multi-ownership planning to make adaptive actions more effective. Although the language and goals of environmental laws and policies were developed under the assumption of stable climate and disturbance regimes, they appear to be flexible enough to accommodate many adaptive actions. It is less certain, however, if sufficient social license and economic capacity exist to undertake these actions. Given the history of contentious and litigious debate about federal forest management in this region, it is likely that some of these actions will be seen as double-edge swords, spurring social resistance, especially where actions involve cutting trees. Given uncertainties and complexity, collaborative efforts that promote learning (e.g. adaptive management groups) must be rejuvenated and expanded.!://WOS:000281725700005YTimes Cited: 1 10th International Congress of Ecology Aug 16-21, 2009 Brisbane, AUSTRALIA 0921-2973WOS:00028172570000510.1007/s10980-010-9483-0~?|Spiesman, B. J. Cumming, G. S.2008mCommunities in context: the influences of multiscale environmental variation on local ant community structure313-325Landscape Ecology233We explored the ways in which environmental variation at multiple spatial scales influences the organization of ant species into local communities. Ground-dwelling ants were sampled in sandhill habitat at 33 locations throughout northern Florida, USA. Variance partitioning of local, landscape, and regional datasets using partial redundancy analysis indicates that ant community composition is significantly influenced by environmental variability across all scales of analysis. Habitat generalists appear to replace habitat specialists at sites with high proportions of matrix habitat in the surrounding landscape. Conversely, habitat specialists appear to replace habitat generalists at sites with more sandhill habitat in the surrounding landscape and greater amounts of bare ground locally. Local niche differentiation leading to species-sorting, combined with the effects of spatially structured dispersal dynamics at landscape scales, may explain this pattern of community structure. Regional influences on local ant communities were correlated with geographical and environmental gradients at distinct regional scales. Therefore, local ant communities appear to be simultaneously structured by different processes that occur at separate spatial scales: local, landscape, and regional scales defined by spatial extent. Our results illustrate the importance of considering multiscale influences on patterns of organization in ecological communities."://WOS:000254112100006 Times Cited: 0WOS:000254112100006(10.1007/s10980-007-9186-3|ISSN 0921-2973<7/Spooner, P. G. Lunt, I. D. Okabe, A. Shiode, S.2004^Spatial analysis of roadside Acacia populations on a road network using the network K-function491-499Landscape Ecology195Acacia; anthropogenic disturbance; field margins; kernel estimation; road verge; stream ecology MAPPED POINT PATTERNS; LIFE-HISTORY; LANDSCAPE; DISTURBANCE; ECOLOGY; VEGETATION; ESTUARIES; VERGESArticleSpatial patterning of plant distributions has long been recognised as being important in understanding underlying ecological processes. Ripley's K-function is a frequently used method for studying the spatial pattern of mapped point data in ecology. However, application of this method to point patterns on road networks is inappropriate, as the K-function assumes an infinite homogenous environment in calculating Euclidean distances. A new technique for analysing the distribution of points on a network has been developed, called the network K-function (for univariate analysis) and network cross K-function (for bivariate analysis). To investigate its applicability for ecological data-sets, this method was applied to point location data for roadside populations of three Acacia species in a fragmented agricultural landscape of south-eastern Australia. Kernel estimations of the observed density of spatial point patterns for each species showed strong spatial heterogeneity. Combined univariate and bivariate network K-function analyses confirmed significant clustering of populations at various scales, and spatial patterns of Acacia decora suggests that roadworks activities may have a stronger controlling influence than environmental determinants on population dynamics. The network K-function method will become a useful statistical tool for the analyses of ecological data along roads, field margins, streams and other networks.://000222941500003 ISI Document Delivery No.: 841OY Times Cited: 4 Cited Reference Count: 44 Cited References: ANDREWS A, 1990, AUSTR ZOOLOGIST, V26, P130 BAILEY TC, 1995, INTERACTIVE SPATIAL BENNETT AF, 1991, NATURE CONSERVATION, V2, P99 BULL L, 1997, LOCKHART SHIRE ROADS CALE P, 1990, P ECOLOGICAL SOC AUS, V16, P359 CARR LW, 2002, APPL LANDSCAPE ECOLO, P225 CLARK JS, 1991, ECOLOGY, V72, P1102 COOPER SD, 1997, J N AM BENTHOL SOC, V16, P174 DALE MRT, 1999, SPATIAL PATTERN ANAL DEBLOIS S, 2002, ECOGRAPHY, V25, P244 DEBSKI I, 2000, J TROP ECOL 3, V16, P387 DIGGLE PJ, 1983, STAT ANAL SPATIAL PO FORMAN RTT, 1998, ANNU REV ECOL SYST, V29, P207 FORMAN RTT, 1998, LANDSCAPE ECOL, V13, R3 FORMAN RTT, 1999, P 3 INT C WILDL EC T, P118 GETIS A, 1987, ECOLOGY, V68, P473 HAASE P, 1995, J VEG SCI, V6, P575 HOBBS RJ, 1994, CONSERVATION BIOL AU, P77 HOOGE PN, 2002, ANIMAL MOVEMENT ANAL KENKEL NC, 1988, ECOLOGY, V69, P1017 LECOEUR D, 2002, AGR ECOSYST ENVIRON, V89, P23 LITTLE LS, 1997, J EXP MAR BIOL ECOL, V213, P1 MCINTYRE S, 1995, J ECOL, V83, P31 MILLER H, 1994, GEOGRAPHICAL SYSTEMS, V1, P157 MILLER HJ, 1999, GEOGR ANAL, V31, P187 MOLONEY KA, 1996, ECOLOGY, V77, P375 MOTZKIN G, 1996, ECOL MONOGR, V66, P345 OKABE A, 1996, GEOGR ANAL, V28, P330 OKABE A, 2001, GEOGR ANAL, V33, P271 OKABE A, 2002, P 2 INT C GEOGR INF OKABE A, 2002, SANET TOOLBOX SPATIA PODANI J, 1997, J VEG SCI, V8, P259 RATHBUN SL, 1998, ENVIRONMETRICS, V9, P109 RIPLEY BD, 1976, J APPL PROBAB, V13, P255 RIPLEY BD, 1981, SPATIAL STAT SPOONER PG, 2004, IN PRESS BIOL CONSER SZWAGRZYK J, 1993, J VEG SCI, V4, P469 TAME T, 1992, ACACIAS SE AUSTR TURNER MG, 1990, QUANTITATIVE METHODS, P323 VERMEULEN HJW, 1995, LANDSCAPE URBAN PLAN, V31, P233 WAY JM, 1977, BIOL CONSERV, V12, P65 WEST PW, 1984, AUST J ECOL, V9, P405 YAMADA I, 2003, P 82 TRANSP RES BOAR YATES CJ, 1997, AUST J BOT, V45, P949 0921-2973 Landsc. Ecol.ISI:000222941500003Charles Sturt Univ, Johnstone Ctr, Albury, NSW 2640, Australia. Univ Tokyo, Ctr Spatial Informat Sci, Bunkyo Ku, Tokyo 1138656, Japan. Spooner, PG, Charles Sturt Univ, Johnstone Ctr, POB 789, Albury, NSW 2640, Australia. pspooner@csu.edu.auEnglish |?$pSt-Louis, V. Forester, J. D. Pelletier, D. Belisle, M. Desrochers, A. Rayfield, B. Wulder, M. A. Cardille, J. A.2014vCircuit theory emphasizes the importance of edge-crossing decisions in dispersal-scale movements of a forest passerine831-841Landscape Ecology295May" Measuring landscape connectivity in ways that reflect an animal's propensity or reluctance to move across a given landscape is key for planning effective conservation strategies. Resistance distance, based on circuit theory, is one such measure relevant for modeling how broad-scale animal movements over long time periods may lead to gene flow across the landscape. Despite the success of circuit theory in landscape genetic studies, its applicability to model finer-scale processes such as the movement patterns of individual animals within their breeding grounds (e.g., while prospecting for territories) has yet to be tested. Here, we applied both circuit models and least-cost models to understand the relationship between landscape connectivity and return time of Ovenbirds (Seiurus aurocapilla) that had been translocated at least 20 km from their home territory near Qu,bec City, Canada. Using an iterative optimization process, we derived resistance values for three cover types (forest, edge, and open) that resulted in resistance distance values that best explained Ovenbird return times. We also identified the cover-type resistance values that yielded length of least-cost path estimates that best explained return times of the translocated birds. The circuit theory and least-cost path methods were equally supported by the data despite being based on different sets of resistance values. The optimal resistance values for calculating resistance distance indicated that for Ovenbirds, traversing a given distance of edge habitat presented a substantially greater resistance than that of open areas. On the other hand, optimized resistances of edge and open were very similar for calculating length of least-cost path. The circuit theory approach suggested that for an Ovenbird moving through fragmented habitat, the number of forest-open transitions (i.e., edge-crossings) that an individual must make is critical to understanding return times after translocation. The least-cost path approach, on the other hand, suggested that the birds strongly avoid all open areas, regardless of size. Circuit theory offers an important new approach for understanding landscapes from the perspective of individuals moving within their breeding range, at finer spatial scales and shorter time scales than have been previously considered.!://WOS:000334689900006Times Cited: 1 0921-2973WOS:00033468990000610.1007/s10980-014-0019-x<7)St-Louis, V. Fortin, M. J. Desrochers, A.2004jSpatial association between forest heterogeneity and breeding territory boundaries of two forest songbirds591-601Landscape Ecology196 edge; forest heterogeneity; overlap statistics; redundancy analysis; soft boundaries; songbirds; temperate forest; territory delineation; Quebec; Canada THROATED BLUE WARBLERS; ECOLOGICAL BOUNDARIES; HABITAT SELECTION; BIRDS; COMPETITION; DELINEATION; TESTS; SIZE; EDGEArticleAugVHuman activities and natural disturbances create spatial heterogeneity within forested landscapes, leading to both sharp and gradual boundaries in vegetation and abiotic attributes, such as rocks. Those boundaries may affect the detailed delineation of avian territories (\independently of their general location), but their role is largely unknown. We tested, using a spatial analysis approach, whether spatial heterogeneity of vegetation and abiotic attributes were associated with territory boundaries of ten black-throated blue warblers (Dendroica caerulescens) and 14 ovenbirds (Seiurus aurocapillus). The study was conducted during summer 1999 in a mature deciduous forest near Quebec City, Canada. Singing males were mapped from repeated surveys at 756 points, 25 m apart, on a 49 ha grid. Spatial heterogeneity was obtained from 27 attributes measured at each point. Boundaries of bird territories, vegetation, and abiotic attributes were delineated using the lattice-wombling boundary detection algorithm. The spatial association between territory and microhabitat boundaries was computed using the spatial overlap statistics. There was significant spatial overlap between territory boundaries and those of 15 and 17 attributes for black- throated blue warbler and ovenbird, respectively. The attributes most strongly associated with territory boundaries were conifer seedling cover, grass and total vegetation cover between 0-2 m high for black- throated blue warbler and fern cover, vegetation-covered rocks and shrub diversity for ovenbird. Complementary to this, a redundancy analysis (RDA) was used to compare attributes associated with the general occurrence of males to those whose boundaries were associated specifically with territory boundaries. Most attributes whose boundaries were associated with territory boundaries did not correspond to "resource attributes", i.e., those where birds were detected most frequently. We conclude that soft boundaries associated with spatial heterogeneity may help shape forest bird territories by providing landmarks not necessarily related to resources used within territories.://000224100600002 ISI Document Delivery No.: 857FC Times Cited: 3 Cited Reference Count: 38 Cited References: ANDREN H, 1994, OIKOS, V71, P355 BAMFORD R, 1986, Q J FOREST, V80, P115 BOURSKI OV, 2000, OIKOS, V88, P341 COLIN JB, 1992, TERRITORY MAPPING ME EASON PK, 1999, ANIM BEHAV 1, V58, P85 FALLS JB, 1981, STUDIES AVIAN BIOL, V6, P86 FORTIN MJ, 1994, ECOLOGY, V75, P956 FORTIN MJ, 1995, OIKOS, V72, P323 FORTIN MJ, 1996, OIKOS, V77, P51 FORTIN MJ, 1997, CAN J FOREST RES, V27, P1851 HOLMES RT, 1996, J ANIM ECOL, V65, P183 HOLWAY DA, 1991, CONDOR, V93, P575 HOOGE PN, 1997, ANIMAL MOVEMENT EXTE HUTTO RL, 1985, HABITAT SELECTION BI, P455 JACQUEZ GM, 1995, STAT MED, V14, P2343 JOKIMAKI J, 1998, CAN J FOREST RES, V28, P1068 KAUFMANN JH, 1983, BIOL REV, V58, P1 KLOPFER PH, 1985, HABITAT SELECTION BI, P435 LACK D, 1954, NATURAL REGULATION A LEGENDRE P, 1998, NUMERICAL ECOLOGY LIVERMAN MC, 1986, WILDLIFE 2000 MODELL NICE MM, 1937, T LINNAEAN SOC NEW Y, V4, P1 ORTEGA YK, 1999, AUK, V116, P937 PALMER MW, 1993, ECOLOGY, V74, P2215 PAQUIN R, 1996, EMAN OCCASIONAL PAPE, V2 RAIL JF, 1997, CONDOR, V99, P976 REID ML, 1988, OIKOS, V51, P115 SMITH TM, 1987, ECOLOGY, V68, P695 SODHI NS, 1999, WILSON BULL, V111, P70 STEELE BB, 1992, ORNIS SCAND, V23, P33 STEELE BB, 1993, CONDOR, V95, P568 STENGER J, 1959, WILSON B, V71, P125 TERBRAAK CJF, 1994, ECOSCIENCE, V1, P127 TERBRAAK CJF, 1998, CANOCO REFERENCE MAN VILLARD MA, 1999, 199921 SUST FOR MAN WHITCOMB RF, 1981, FOREST ISLAND DYNAMI, P125 WORTON BJ, 1989, ECOLOGY, V70, P164 YAHNER RH, 1988, CONSERV BIOL, V2, P333 0921-2973 Landsc. Ecol.ISI:000224100600002Univ Montreal, Dept Biol Sci, Montreal, PQ H3C 3J7, Canada. Univ Wisconsin, Dept Forest Ecol & Management, Madison, WI 53706 USA. Univ Toronto, Dept Zool, Toronto, ON M5S 3G5, Canada. Univ Laval, Fac Forestry & Geomat, Forest Biol Res Ctr, Quebec City, PQ G1K 7P4, Canada. St-Louis, V, Univ Montreal, Dept Biol Sci, CP 6128,Succ Ctr Ville, Montreal, PQ H3C 3J7, Canada. vstlouis@wisc.eduEnglish`|?: PSt-Louis, V. Pidgeon, A. M. Clayton, M. K. Locke, B. A. Bash, D. Radeloff, V. C.2010Habitat variables explain Loggerhead Shrike occurrence in the northern Chihuahuan Desert, but are poor correlates of fitness measures643-654Landscape Ecology254Conservation efforts should be based on habitat models that identify areas of high quality and that are built at spatial scales that are ecologically relevant. In this study, we developed habitat models for the Loggerhead Shrike (Lanius ludovicianus) in the Chihuahuan Desert of New Mexico to answer two questions: (1) are highly used habitats of high quality for shrikes in terms of individual fitness? and (2) what are the spatial scales of habitat associations relevant to this species? Our study area was Fort Bliss Army Reserve (New Mexico). Bird abundance was obtained from 10 min point counts conducted at forty-two 108 ha plots during a 3-year period. Measures of fitness were obtained by tracking a total of 73 nests over the 3 years. Habitat variables were measured at spatial scales ranging from broad to intermediate to local. We related habitat use and measures of fitness to habitat variables using Bayesian model averaging. We found a significant relationship between bird abundance and measures of fitness averaged across nesting birds in each plot (correlation up to 0.61). This suggests that measures of habitat use are indicative of habitat quality in the vicinity of Fort Bliss. Local- and intermediate-scale variables best explained shrike occurrence. Habitat variables were not related to any measures of fitness. A better understanding of the factors that limit individual bird fitness is therefore necessary to identify areas of high conservation value for this species.!://WOS:000275444100012Times Cited: 0 0921-2973WOS:00027544410001210.1007/s10980-010-9451-8T|? YStambaugh, Michael C. Dey, Daniel C. Guyette, Richard P. He, Hong S. Marschall, Joseph M.2011WSpatial patterning of fuels and fire hazard across a central US deciduous forest region923-935Landscape Ecology267AugInformation describing spatial and temporal variability of forest fuel conditions is essential to assessing overall fire hazard and risk. Limited information exists describing spatial characteristics of fuels in the eastern deciduous forest region, particularly in dry oak-dominated regions that historically burned relatively frequently. From an extensive fuels survey of unmanaged forest lands (1,446 plots) we described fuel loadings and spatial patterns of fine and coarse fuels. We attempted to explain the variability in fuel loading of each time-lag fuel class using landscape and seasonal variables through a multiple regression modeling approach. Size class distributions of woody fuels were generally homogeneous across the region except in the glaciated portions of Illinois where loadings appeared lower. Temporally, litter depths progressively decreased from leaffall (November). A fire hazard model that combined seasonal changes in litter depth and fuel moisture content depicted the degree of regional spatial variability during the transition between extreme dry and wet conditions. In the future, fire hazard indices could be paired with ignition probabilities in order to assess spatio-temporal variability of fire risk within the region.!://WOS:000292705900003Times Cited: 0 0921-2973WOS:00029270590000310.1007/s10980-011-9618-ySڽ7 0Standish, RachelJ Hobbs, RichardJ Miller, JamesR2013Improving city life: options for ecological restoration in urban landscapes and how these might influence interactions between people and nature 1213-1221Landscape Ecology286Springer NetherlandsBiodiversity conservation Cultural services Ecosystem services Human-nature interactions Human well-being Novel ecosystems Urban ecology Urban ecosystems Urban green space Urban planning 2013/07/01+http://dx.doi.org/10.1007/s10980-012-9752-1 0921-2973Landscape Ecol10.1007/s10980-012-9752-1English<7*Stanfield, B. J. Bliss, J. C. Spies, T. A.2002kLand ownership and landscape structure: a spatial analysis of sixty-six Oregon (USA) Coast Range watersheds685-697Landscape Ecology178forest habitat land ownership concentration land ownership land tenure landscape structure Oregon Coast Range watershed INVESTMENT FORESTSArticleDecPatterns of land ownership and forest cover are related in complex and ecologically significant ways. Using a Geographic Information System and regression analysis, we tested for spatial relationships between the structure of land ownership and forest cover across 66 watersheds in the state of Oregon (USA), Coast Range mountains. We found that in these watersheds (1) forest cover diversity increased with land ownership diversity, (2) size of forest patches increased with size of land ownership patches, and (3) connectivity of forest cover increased with connectivity of land ownership. Land ownership structure explained between 29% and 40% of the variability of forest cover structure across these watersheds. Driving this relationship are unique associations among particular ownership classes and various forest cover classes. The USDA Forest Service and the USDI Bureau of Land Management were associated with mature forest cover; private industry was associated with young forest cover; nonindustrial private forest owners were associated with a wide diversity of cover classes. Watersheds with mixed ownership appear to provide greater forest cover diversity, whereas watersheds with concentrated ownership provide less diverse but more connected forest cover. Results suggest that land ownership patterns are strongly correlated with forest cover patterns. Therefore, understanding landscape structure requires consideration of land ownership institutions, dynamics, and patterns.://000181767400002 @ISI Document Delivery No.: 659FV Times Cited: 7 Cited Reference Count: 40 Cited References: *ATT CONS INC, 1994, W OR IND LAND OWN AZUMA DL, 1999, FORESTS FARMS PEOPLE BETTINGER P, 2000, PHASE 1 REPORT DEV L BIRCH T, 1996, USDA B BLISS JC, 1988, SOC NATUR RESOUR, V1, P365 BLISS JC, 1998, SOC NATUR RESOUR, V11, P401 BUTLER BJ, IN PRESS LAND OWNERS CLEAVES DA, 1995, WEST J APPL FOR, V10, P66 COHEN WB, 1995, INT J REMOTE SENS, V16, P721 CRONON W, 1983, CHANGES LAND INDIANS CROW TR, 1999, LANDSCAPE ECOL, V14, P449 DILWORTH JR, 1956, THESIS U WASHINGTON ECKERT PJ, 1998, THESIS U WASHINGTON FAHRIG L, 1999, FOREST FRAGMENTATION, P87 FRANKLIN JF, 1973, PNW8 USDA FOR SERV P FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 GARMAN S, 1999, FOREST FRAGMENTATION, P62 GAVENTA J, 1998, WHO OWNS AM SOCIAL C, P227 GEISLER C, 1993, RURAL SOCIOL, V58, P532 HEASLEY L, 1995, WHO OWNS AM SOCIAL C, P182 LANGSTON N, 1995, FOREST DREAMS FOREST MACLEAN CD, 1990, RESOURCE B USDA MCCOMB WC, 1993, J FOREST, V91, P31 MCGARIGAL K, 1995, ECOL MONOGR, V65, P235 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MEDLEY KE, 1995, LANDSCAPE ECOL, V10, P161 MLADENOFF DJ, 1995, CONSERV BIOL, V9, P279 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 RAMSEY FL, 1997, STAT SLEUTH COURSE M ROBBINS WG, 1988, HARD TIMES PARADISE ROMM J, 1987, FOREST SCI, V33, P197 SHANNON C, 1949, MATH THEORY COMMUNIC SISOCK ML, 1998, THESIS AUBURN U AUBU SPIES TA, 1994, ECOL APPL, V4, P555 SPIES TA, 2002, INTEGRATING LANDSCAP STANFIELD BJ, 2001, THESIS OREGON STATE STRAKA TJ, 1984, J FOREST, V82, P495 TURNER MG, 1996, ECOL APPL, V6, P1150 WELLS G, 1999, TILLAMOOK CREATED FO WHITE R, 1980, LAND USE ENV SOCIAL 0921-2973 Landsc. Ecol.ISI:000181767400002Oregon State Univ, Dept Forest Resources, Corvallis, OR 97331 USA. US Forest Serv, USDA, Pacific NW Forest Res Stn, Corvallis, OR 97331 USA. Bliss, JC, Oregon State Univ, Dept Forest Resources, Corvallis, OR 97331 USA. John.Bliss@orst.eduEnglish|?9Starr, Scott M. Benstead, Jonathan P. Sponseller, Ryan A.2014dSpatial and temporal organization of macroinvertebrate assemblages in a lowland floodplain ecosystem 1017-1031Landscape Ecology296Jul]An important goal in ecology is to understand controls on community structure in spatially and temporally heterogeneous landscapes, a challenge for which riverine floodplains provide ideal laboratories. We evaluated how spatial position, local habitat features, and seasonal flooding interact to shape aquatic invertebrate community composition in an unregulated riverine floodplain in western Alabama (USA). We quantified sediment invertebrate assemblages and habitat variables at 23 sites over a 15-month period. Dissolved oxygen (DO) varied seasonally and among habitats, with sites less connected to the river channel experiencing frequent hypoxia (< 2 mg O-2 L-1) at the sediment-water interface. Differences in water temperature among sites were lowest (< 1 A degrees C) during winter floodplain inundation, but increased to > 14 A degrees C during spring and summer as sites became isolated. Overall, local habitat conditions were more important in explaining patterns in assemblage structure than was spatial position in the floodplain (e.g., distance to the main river channel). DO was an important predictor of taxonomic richness among sites, which was highest where hydrologic connections to the main river channel were strongest. Compositional heterogeneity across the floodplain was lowest immediately following inundation and increased as individual sites became hydrologically isolated. Our results illustrate how geomorphic structure and seasonal flooding interact to shape floodplain aquatic assemblages. The flood pulse of lowland rivers influences biodiversity through effects of connectivity on hydrologic flushing in different floodplain habitats, which may prevent the development of harsh environmental conditions that exclude certain taxa. Such interactions highlight the ongoing consequences of river regulation for taxonomically diverse floodplain ecosystems.!://WOS:000338331600008Times Cited: 0 0921-2973WOS:00033833160000810.1007/s10980-014-0037-8<7<Staus, N. L. Strittholt, J. R. DellaSala, D. A. Robinson, R.2002cRate and pattern of forest disturbance in the Klamath-Siskiyou ecoregion, USA between 1972 and 1992455-470Landscape Ecology175forest disturbance fragmentation Klamath-Siskiyou ecoregion land cover change landscape pattern remote sensing SOUTHERN APPALACHIAN HIGHLANDS LANDSCAPE CHANGE OLYMPIC PENINSULA TRAIL CORRIDORS WESTERN OREGON NATIONAL-PARK UNITED-STATES OLD-GROWTH MOUNTAINS HABITATArticleOctWe classified NALC (North American Landscape Characterization) imagery to forest-nonforest and examined forest change between 1972 and 1992 in the Klamath-Siskiyou ecoregion ( USA) in relation to land ownership and fifth level watersheds. We also analyzed changes in forest patterns by land ownership for three major river basins within the ecoregion (Eel, Klamath, and Rogue) using FRAGSTATS. Overall, forests covered 66.8% of the ecoregion in 1972 and 62.1% in 1992. Approximately 10.5% of the forest area was disturbed overall, translating into an annual disturbance rate of 0.53%. Although public lands accounted for a slightly higher total area of forest disturbance, private lands were cut at a slightly higher rate. Forest disturbance within fifth level watersheds averaged 13.2%, but reached as high as 93.2%. For the three river basins where spatial pattern of forest disturbance was analyzed, private lands were already more fragmented than public lands in 1972. Over the 20-year time period, forest fragmentation increased on all ownerships. Fragmentation rates on public lands were high for all basins especially the Rogue. Clearcut logging on private lands was generally in larger adjacent tracts, whereas cuts on public lands were generally smaller and more dispersed. Our results illustrate the importance of considering landscape change history when planning for effective biodiversity conservation in forested ecoregions and when formulating ecologically sustainable forest management strategies.://000179388800007 ISI Document Delivery No.: 617YP Times Cited: 8 Cited Reference Count: 82 Cited References: *CA DEP FISH GAM, 2000, CAL NAT DIV DAT *ESRI INC, 1999, ARCV GIS *ORWATER, 1996, OR WAT *SP TEAL DAT CTR G, 1999, CALWATER V 2 2 ALLEN TFH, 1992, UNIFIED ECOLOGY ATZET T, 1992, P S BIOD NW CAL OCT, P40 BARTHALOW JM, 1989, 13 US FISH WILDL SER BAUER A, 1990, CAN J ZOOL, V68, P613 BENNINGERTRUAX M, 1992, LANDSCAPE ECOL, V6, P269 CHEN JQ, 1992, ECOL APPL, V2, P387 COHEN WB, IN PRESS ECOSYSTEMS COHEN WB, 1995, INT J REMOTE SENS, V16, P721 COHEN WB, 1998, PHOTOGRAMM ENG REM S, V64, P293 CSUTI B, 1997, DISTRIBUTION HABITAT CUSHMAN SA, 2000, LANDSCAPE ECOL, V15, P643 DELLASALA DA, 1999, NAT AREA J, V19, P300 DELLASALA DA, 2001, NAT AREA J, V21, P124 ERDAS INC, 1994, ERDAS IM V8 2 ESSIG D, 1998, DILEMMA APPL UNIFORM FEARNSIDE PM, 1990, DEFORESTATION RATE B FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 FRISSELL CA, 1996, PRIORITIZATION AQUAT GREEN GM, 1990, SCIENCE, V248, P212 GROVER KE, 1986, J WILDLIFE MANAGE, V50, P466 HALL FG, 1991, ECOLOGY, V72, P628 HARRIS LD, 1984, FRAGMENTED FOREST HESTER AJ, 1996, BIOL CONSERV, V77, P41 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 KAUTH RJ, 1976, P S MACHINE PROCES B, V4, P41 KRUCKEBERG AR, 1984, CALIFORNIAN SERPENTI LALANDE J, 1999, INDIANS FIRE LAND PA, P255 LEHMKUHL JF, 1991, WILDLIFE VEGETATION, P425 LUNETTA RS, 1994, 12 S LAND INF SPAC B, P24 LUQUE SS, 1994, LANDSCAPE ECOL, V9, P287 MADER HJ, 1984, BIOL CONSERV, V29, P81 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MLADENOFF DJ, 1996, GIS ENV MODELING PRO, P175 MOYLE PB, 1998, CONSERV BIOL, V12, P1318 NELSON R, 1987, INT J REMOTE SENS, V8, P1767 NOSS RF, 1999, NAT AREA J, V19, P392 OLSSON EGA, 2000, LANDSCAPE ECOL, V15, P155 PEARSON SM, 1999, ECOL APPL, V9, P1288 PERRY DA, 1994, FOREST ECOSYSTEMS REED RA, 1996, CONSERV BIOL, V10, P1098 REEVES GH, 1993, T AM FISH SOC, V122, P309 RICKETTS TH, 1999, CONSERVATION ASSESSM, V1 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 RIPPLE WJ, 1991, BIOL CONSERV, V57, P73 RIPPLE WJ, 1991, J WILDLIFE MANAGE, V55, P316 SACHS DL, 1998, CAN J FOREST RES, V28, P23 SADER SA, 1988, BIOTROPICA, V20, P11 SAWYER JO, 1996, ENDURING FORESTS NO, P20 SAWYER JO, 2000, REDWOOD FOREST HIST, P7 SIMPSON JW, 1994, LANDSCAPE ECOL, V9, P261 SKINNER CN, 1995, LANDSCAPE ECOL, V10, P219 SKINNER CN, 1997, P FIR EFF THREAT END, P203 SPENCE BC, 1996, TR4501966057 MANT CO SPIES TA, 1994, ECOL APPL, V4, P555 STAUS NL, 2001, CONSERVATION PLANNIN STRITTHOLT JR, 1994, THESIS OHIO STATE U STRITTHOLT JR, 1995, LANDSCAPE CHANGE TIL STRITTHOLT JR, 1999, CONSERVATION ASSESSM STRITTHOLT JR, 2001, CONSERV BIOL, V15, P1742 SWETNAM TW, 1996, FIRE EFFECTS SW FORE, P11 TAYLOR AL, 1976, CONDOR, V78, P560 THEUER FD, 1984, FWSOBS8415 TROMBULAK SC, 2000, CONSERV BIOL, V14, P18 TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 TURNER MG, 1996, ECOL APPL, V6, P1150 TYSER RW, 1992, CONSERV BIOL, V6, P253 VANCEBORLAND KW, 1999, THESIS OREGON STATE VOGELMANN JE, 1998, ENVIRON MONIT ASSESS, V51, P415 WAGNER DH, 1997, CTR PLANT DIVERSITY, V3, P74 WALLACE DR, 1992, WILDERNESS, V56, P10 WHITCOMB RF, 1981, FOREST ISLAND DYNAMI, P124 WHITNEY S, 1985, AUDUBON SOC NATURE G WHITTAKER RH, 1960, ECOL MONOGR, V30, P279 WILCOVE DS, 1986, CONSERVATION BIOL SC, P237 YAHNER RH, 1988, CONSERV BIOL, V2, P333 YANG L, 2001, REMOTE SENS ENVIRON, V76, P418 ZHENG DL, 1997, LANDSCAPE ECOL, V12, P241 ZIPPERER WC, 1993, LANDSCAPE ECOL, V8, P177 0921-2973 Landsc. Ecol.ISI:000179388800007Conservat Biol Inst, Corvallis, OR 97333 USA. Strittholt, JR, Conservat Biol Inst, 260 SW Madison Ave,Suite 106, Corvallis, OR 97333 USA.English? Steele, J.H.1989The ocean 'landscape'185-192Landscape Ecology33/4!Ocean, scale, ecosystems, spectrabThe ocean has a complex physical structure at all scales in space 2nd time, with ‘peaks’ at certain wave numbers and frequencies. Pelagic ecosystems show regular progressions in size of organisms, life cycle, spatial ambit, and trophic status. Thus, physiological and ecological parameters are closely coupled to spatial and temporal physical scales. =? ISteen-Adams, Michelle Mladenoff, David Langston, Nancy Liu, Feng Zhu, Jun2011Influence of biophysical factors and differences in Ojibwe reservation versus Euro-American social histories on forest landscape change in northern Wisconsin, USA 1165-1178Landscape Ecology268Springer NetherlandsEarth and Environmental ScienceLandscape ecology studies have demonstrated that past modifications of the landscape frequently influence its structure, highlighting the utility of integrating historical perspectives from the fields of historical ecology and environmental history. Yet questions remain for historically-informed landscape ecology, especially the relative influence of social factors, compared to biophysical factors, on long-term land-cover change. Moreover, methods are needed to more effectively link history to ecology, specifically to illuminate the underlying political, economic, and cultural forces that influence heterogeneous human drivers of land-cover change. In northern Wisconsin, USA, we assess the magnitude of human historical forces, relative to biophysical factors, on land-cover change of a landscape dominated by eastern white pine ( Pinus strobus L.) forest before Euro-American settlement. First, we characterize land-cover transitions of pine-dominant sites over three intervals (1860–1931; 1931–1951; 1951–1987). Transition analysis shows that white pine was replaced by secondary successional forest communities and agricultural land-covers. Second, we assess the relative influence of a socio-historical variable (“on-/off-Indian reservation”), soil texture (clay and sand), and elevation on land-cover transition. On the Lake Superior clay plain, models that combine socio-historical and biophysical variables best explain long-term land-cover change. The socio-historical variable dominates: the magnitude and rate of land-cover change differs among regions exposed to contrasting human histories. Third, we developed an integrative environmental history-landscape ecology approach, thereby facilitating linkage of observed land-cover transitions to broader political, economic, and cultural forces. These results are relevant to other landscape investigations that integrate history and ecology.+http://dx.doi.org/10.1007/s10980-011-9630-2 0921-297310.1007/s10980-011-9630-2/?j*Frederick R. Steiner Douglas A. Osterman1988QLandscape planning: a working method applied to a case study of soil conservation213-226Landscape Ecology14Vlandscape ecology, soil erosion, agroecology, grassland, Palouse, Washington watershedA working method for landscape planning is proposed. There are 11 steps in this method. In step one, an issue (or set of related issues) is identified as posing a problem or an opportunity to people and/or the environment. In step two, a goal (or several goals) is established to address the problem. In steps three and four, ecological inventories and analyses are conducted at two scales, first at the regional level (drainage basins are suggested as an appropriate unit) and then at the landscape level (watersheds are recommended). These inventories and analyses consider human ecology as well as bio-physical processes. Step five involves detailedstudies, such as suitability analyses, that link inventory and analysis information to the problem(s) and goal(s). In step six, concepts are developed that lead to a landscape (watershed) master plan in step seven. During step eight, the plan is explained through a systematic educational effort to the affected public. In step nine, detailed designs are developed. In step 10 the plan and designs are implemented. Step 11 involves administering and monitoring the plan. The method is explained through an example of soil conservation planning. The case study was undertaken in the Missouri Flat Creek watershed of the Palouse region in the Pacific Northwest (U.S.A.) to help achieve the goals for erosion control established by the federal Food Security Act of 1985 and state clean water legislation.|? LSteingrover, Eveliene G. Geertsema, Willemien van Wingerden, Walter K. R. E.2010Designing agricultural landscapes for natural pest control: a transdisciplinary approach in the Hoeksche Waard (The Netherlands)825-838Landscape Ecology256Jul_The green-blue network of semi-natural non-crop landscape elements in agricultural landscapes has the potential to enhance natural pest control by providing various resources for the survival of beneficial insects that suppress crop pests. A study was done in the Hoeksche Waard to explore how generic scientific knowledge about the relationship between the spatial structure of the green-blue network and enhancement of natural pest control can be applied by stakeholders. The Hoeksche Waard is an agricultural area in the Netherlands, characterized by arable fields and an extensive network of dikes, creeks, ditches and field margins. Together with stakeholders from the area the research team developed spatial norms and design rules for the design of a green-blue network that supports natural pest control. The stakeholders represented different interests in the area: farmers, nature and landscape conservationists, water managers, and local and regional politicians. Knowledge about the spatial relationship among beneficial insects, pests and landscape structure is incomplete. We conclude that to apply scientific knowledge about natural pest control and the role of green-blue networks to stakeholders so that they can apply it in landscape change, knowledge transfer has to be transparent, area specific, understandable, practical and incorporate local knowledge.!://WOS:000278526000002Times Cited: 0 0921-2973WOS:00027852600000210.1007/s10980-010-9489-7 H<7Steinhardt, U. Volk, M.2001xAn investigation of water and matter balance on the meso-landscape scale: A hierarchical approach for landscape research1-12Landscape Ecology171lGIS-coupled modeling hierarchy land use scenarios landscape planning landscape water balance mesoscale MODELArticleThe realization of strategies for sustainable land use assumes specific research concepts from the local to the global scale (micro-, meso- and macroscale). Therefore, landscape ecological science has to provide investigation methods for all these different scales. By combining "top-down" and "bottom-up" approaches in addition to coupled GIS-model applications and traditional methods, the investigation of landscape ecological structures and processes seems to be possible. The presented studies show this approach on examples of two study areas in Eastern Germany: A watershed of 400 km(2) and an administrative district of about 4000 km(2). The scale-specific applicability of several models and methods were tested for these investigations, and the validation of the calculated results are presented. An important outcome of the project should be the prevention of conflicts between agriculture, water management and soil, and water and nature conservation based on recommendations for land use variants with decreased pollutant loading within agricultural areas. The scale specific investigations can be considered as a base for establishing sustainable land use.://000176014400001 ZISI Document Delivery No.: 559FF Times Cited: 2 Cited Reference Count: 29 Cited References: *AG BOD, 1994, BOD KART *BGR, HANN GEOL JB *SACHS LAND LANDW, 1996, ER 2D 3D COMP SIM BO *STAT BUND, 1996, CORINE LAND COV DAT ARNOLD JG, 1993, J HYDROL, V142, P47 FRANKLIN IM, 1997, TRANSFUSION MED, V7, P63 GLUGLA G, 1997, DOKUMENTATION ANWEND GRAYSON RB, 1992, WATER RESOUR RES, V26, P2659 HAYCOCK NE, 1993, LANDSCAPE SENSITIVIT, P261 HELMING K, 1999, REGIONALISIERUNG LAN, P221 HICKEY R, 1994, COMPUT ENVIRON URBAN, V18, P365 KIEMSTEDT H, 1997, 39S ORT KLIJN JA, 1995, 100 WIN STAR CTR INT KRYSANOVA V, 1998, ECOL MODEL, V106, P261 LESER H, 1997, LANDSCHAFTSOKOLOGIE NEEF E, 1967, THEORETISCHEN GRUNDL ONEILL, 1986, HIERARCHICAL CONCEPT PETRY D, 1998, KEY CONCEPTS LANDSCA, P405 RIITTERS KH, 1997, LANDSCAPE ATLAS CHES RODER M, 1998, ERFASSUNG BEWERTUNG SAUERBORN P, 1994, BONNER BODENKUNDLICH, V13 SCHWERTMANN U, 1990, BODENEROSION WASSER SRINIVASAN R, 1993, P APPL ADV INF TECHN, P475 STEINHARDT U, 1999, P 5 WORLD C IALE LAN, V2 STEINHARDT U, 2000, PETERMANNS GEOGR MIT, V144, P80 VOLK M, 1998, 698 GIS, P349 VOLK M, 1999, GEOOKODYNAMIK, V20, P193 VOLK M, 1999, REGIONAL PROSPERITY, P201 WISHMEIER WH, 1978, AGR HDB USDA, V537 0921-2973 Landsc. Ecol.ISI:000176014400001Environm Res Ctr, Dept Appl Landscape Ecol, D-04301 Leipzig, Germany. Steinhardt, U, Environm Res Ctr, Dept Appl Landscape Ecol, POB 2, D-04301 Leipzig, Germany. volk@alok.ufz.deEnglish/}?DStevens, Carly J. Fraser, Iain Mitchley, Jonathan Thomas, Matthew B.2007WMaking ecological science policy-relevant: issues of scale and disciplinary integration799-809Landscape Ecology226Jul&://BIOSIS:PREV200700463283 0921-2973BIOSIS:PREV200700463283<7HStevens, V. M. Polus, E. Wesselingh, R. A. Schtickzelle, N. Baguette, M.2004Quantifying functional connectivity: experimental evidence for patch-specific resistance in the Natterjack toad (Bufo calamita)829-842Landscape Ecology198Aarena-experiment; Belgium; dispersal behaviour; functional connectivity; landscape; locomotor performance; matrix resistance; metapopulation; permeability LANDSCAPE STRUCTURE; METAPOPULATION DYNAMICS; HABITAT FRAGMENTATION; DISPERSAL BEHAVIOR; FRACTAL LANDSCAPES; BODY SIZE; POPULATION; MOVEMENT; CONSERVATION; EXTINCTIONArticleDespite the importance assigned to inter-patch movements in fragmented systems, the structure of landscape between suitable habitat patches, the matrix, is often considered as to be of minor interest, or totally ignored. Consequently, models predicting metapopulation dynamics typically assume that dispersal and movement abilities are independent of the composition of the matrix. The predictions of such models should be invalided if that crucial assumption is unverified. In order to test the hypothesis of a patch-specific resistance, we led an experimental study to assess the matrix effects on the movement ability of juvenile Natterjack toads (Bufo calamita). The movement behaviour of first year toadlets, the dispersal stage in this species, was investigated in an arena experiment. Toadlet mobility was assessed in five landscape components that were mimicked in the lab: sandy soil, road, forest, agricultural field, and pasture. We analysed several movement components including move length, speed, efficiency and turning angle distribution. Our results showed that movement ability was strongly affected by the land cover, even if body size modulated the behavioural responses of toadlets. Performances were the best in the arenas mimicking sand and roads, and the worst in the forest arena, toadlet moves being three to five times less effective in the latter. The mobility was intermediate in the two other arenas. We propose here a new method to quantify functional connectivity, based on quantitative estimates of relative values for resistance of landscape components. This method offers a reliable alternative for resistance value estimates to subjective,expert advice' or inference from genetic population structure.://000226268600002 ISI Document Delivery No.: 886YI Times Cited: 10 Cited Reference Count: 66 Cited References: ADRIAENSEN F, 2003, LANDSCAPE URBAN PLAN, V64, P233 BAGUETTE M, 2000, J APPL ECOL, V37, P100 BAGUETTE M, 2003, OIKOS, V101, P661 BECK CW, 2000, FUNCT ECOL, V14, P32 BEEBEE TJC, 1979, BIOL CONSERV, V16, P107 BEEBEE TJC, 1983, NATTERJACK TOAD BEEBEE TJC, 1985, J ZOOL, V205, P1 BENNETT AF, 1990, LANDSCAPE ECOL, V4, P109 BERGGREN A, 2002, CONSERV BIOL, V16, P1562 BROOKER L, 1999, CONSERV ECOL, V3 BROWN JH, 1977, ECOLOGY, V58, P445 CHARDON JP, 2003, LANDSCAPE ECOL, V18, P561 CHARRIER S, 1997, AGR ECOSYST ENVIRON, V61, P133 CRIST TO, 1992, FUNCT ECOL, V6, P536 DENTON JS, 1993, ANIM BEHAV, V46, P1169 DONCASTER CP, 2001, J ANIM ECOL, V70, P33 DRISCOLL DA, 1997, AUST J ECOL, V22, P185 FAHRIG L, 1985, ECOLOGY, V66, P1762 FAHRIG L, 1995, BIOL CONSERV, V73, P172 FAHRIG L, 2002, ECOL APPL, V12, P346 FISHER NI, 1993, STAT ANAL CIRCULAR D GATHOYE JL, 1998, RESERVES NATURELLES, V4, P4 GOATER CP, 1993, OIKOS, V66, P129 GOODWIN BJ, 2002, CAN J ZOOL, V80, P24 GRIFFITHS RA, 1997, AQUAT CONSERV, V7, P119 HADDAD NM, 1999, ECOL APPL, V9, P612 HANSKI I, 1998, NATURE, V396, P41 HANSKI I, 1999, METAPOPULATION ECOLO HANSKI I, 1999, OIKOS, V87, P209 HANSKI I, 2000, ECOLOGY, V81, P239 HANSKI IA, 1997, METAPOPULATION BIOL HARRISON S, 1988, AM NAT, V132, P360 HARRISON S, 1994, LARGE SCALE ECOLOGY, P111 HILL MF, 1999, ECOL LETT, V2, P121 HITCHINGS SP, 1997, HEREDITY 2, V79, P117 IMS RA, 1997, METAPOPULATION BIOL, P247 JONSEN ID, 2000, OIKOS, V88, P553 KELLER LF, 2002, TRENDS ECOL EVOL, V17, P230 KING AW, 2002, ECOL MODEL, V147, P23 MARSH RL, 1994, COMP VERTEBRATE EXER, P51 MENNECHEZ G, 2003, LANDSCAPE ECOL, V18, P279 PERCSY C, 1997, PROJET ATLAS HERPETO RICKETTS TH, 2001, AM NAT, V158, P87 ROWE G, 2000, OIKOS, V88, P641 RUCKELSHAUS M, 1997, CONSERV BIOL, V11, P1298 RUSTIGIAN HL, 2003, LANDSCAPE ECOL, V18, P65 SCHTICKZELLE N, 2004, OIKOS, V104, P277 SINSCH U, 1997, OECOLOGIA, V112, P42 SORCI G, 1994, AM NAT, V144, P153 SOUTH A, 1999, CONSERV BIOL, V13, P1039 STAMPS JA, 1987, AM NAT, V129, P533 STEPHENSON JR, 2001, CURR PHARM BIOTECHNO, V2, P47 STEVENS VM, 2003, HERPETOL J, V13, P59 TEJEDO M, 1992, ANIM BEHAV, V44, P557 TEJEDO M, 1992, J ZOOL, V228, P545 TEJEDO M, 2000, COPEIA 0508, P448 THOMAS CD, 1992, J ANIM ECOL, V61, P437 TURCHIN P, 1998, QUANTITATIVE ANAL MO VANDEWOESTIJNE S, 2002, HEREDITY, V89, P439 WIENS JA, 1989, LANDSCAPE ECOLOGY, V3, P87 WIENS JA, 1997, METAPOPULATION BIOL, P43 WIENS JA, 1997, OIKOS, V78, P257 WIENS JA, 2001, DISPERSAL, P96 WILCOX BA, 1985, AM NAT, V125, P879 WITH KA, 1994, FUNCT ECOL, V8, P477 WITH KA, 1999, ECOLOGY, V80, P1340 0921-2973 Landsc. Ecol.ISI:000226268600002Univ Catholique Louvain, Biodivers Res Ctr, B-1348 Louvain, Belgium. Baguette, M, Univ Catholique Louvain, Biodivers Res Ctr, 4 Croix Sud, B-1348 Louvain, Belgium. baguette@ecol.ucl.ac.beEnglish<7~Stiles, J. H. Jones, R. H.1998]Distribution of the red imported fire ant, Solenopsis invicta, in road and powerline habitats335-346Landscape Ecology136ant abundance corridor exotic species invasion powerline cuts roads Solenopsis invicta spatial pattern FOREST FRAGMENTATION NATIVE ANTS INVASION NORTH HYMENOPTERA FORMICIDAE CORRIDORS WILDLIFE ECOLOGY EDGESArticleDecFor early-successional species, road and powerline cuts through forests provide refugia and source populations for invading adjacent forest gaps. Within an 800 km(2) forest matrix in South Carolina, we determined if width, disturbance frequency or linear features of road and powerline cuts influenced the mound distribution of the red imported fire ant, Solenopsis invicta Buren. For each of five linear habitat types, differing in width and disturbance frequency, we mapped all mounds located within ten 500 m segments. Mean mound density was lowest in narrow, infrequently-disturbed closed-canopy dirt road habitats (8.8 mounds/ha). For types with an opening in the forest canopy (i.e., open dirt road, gravel road, paved road and powerline cut), mean mound density was highest in narrow habitats where disturbance was intermediate (open dirt roads, 86.5 mounds/ha). It was lowest in wide habitats where disturbance was infrequent (powerline cuts, 27.6 mounds/ha). Mean mound size was greater in infrequently-disturbed powerline cuts than in frequently-disturbed paved roads. Mounds were located significantly closer to road or forest edges than expected by random. In all types except dirt roads, mounds were more common toward northern edges, and more so as the orientation of the linear habitat changed from north/south to east/west. These data suggest that narrow, disturbed habitats are more suitable for fire ant establishment and success than wider ones, and that the distribution of fire ants in linear habitats is not as uniform as it has been shown to be in pastures. A decrease in roadside disturbance and an increase in shade, especially along the northern edge, may result in lower fire ant mound density in these linear habitats.://000077308100001 (ISI Document Delivery No.: 144HH Times Cited: 8 Cited Reference Count: 43 Cited References: *SAS I INC, 1996, SAS STAT SOFTWARE CH *USDA, 1990, SOIL SURV SAV RIV PL ADAMS ES, 1995, OECOLOGIA, V102, P156 ALLEN CR, 1994, TEX J SCI, V46, P51 AMOR RL, 1976, WEED RES, V16, P111 BANKS WA, 1990, FLA ENTOMOL, V73, P198 BARONIURBANI C, 1974, ENVIRON ENTOMOL, V3, P755 BENNETT AF, 1991, NATURE CONSERVATION, V2, P99 BROWN WM, 1980, J PHILOS SPORT, V7, P15 BUREN WF, 1974, NY ENTOMOLOGICAL SOC, V82, P113 CAMILO GR, 1990, APPL MYRMECOLOGY WOR, P190 DEMERS MN, 1993, LANDSCAPE ECOL, V8, P93 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY GETZ LL, 1978, J MAMMAL, V59, P208 HAYS SB, 1982, J GEORGIA ENTOMOLOGI, V17, P267 HUBBARD MD, 1977, INSECT SOC, V24, P3 KROODSMA RL, 1982, BIOL CONSERV, V23, P79 LEWIS SA, 1991, NATURE CONSERVATION, V2, P99 LOFGREN CS, 1975, ANNU REV ENTOMOL, V29, P1 MADER HJ, 1984, BIOL CONSERV, V29, P81 MATLACK GR, 1993, BIOL CONSERV, V66, P185 MAXWELL FG, 1982, P S IMP FIR ANT, P67 MERRIAM G, 1989, LANDSCAPE ECOLOGY, V2, P227 MORRIS JR, 1993, SOUTHWEST NAT, V38, P136 PORTER SD, 1988, ANN ENTOMOL SOC AM, V81, P913 PORTER SD, 1988, J INSECT PHYSIOL, V34, P1127 PORTER SD, 1990, ECOLOGY, V71, P2095 PORTER SD, 1992, J ECON ENTOMOL, V85, P1154 REAGAN TE, 1986, FIRE ANTS LEAF CUTTI, P58 REED RA, 1996, CONSERV BIOL, V10, P1098 RICH AC, 1994, CONSERV BIOL, V8, P1109 SOKAL RR, 1995, BIOMETRY SUMMERLIN JW, 1976, J ECON ENTOMOL, V69, P73 TEDDERS WL, 1990, ENVIRON ENTOMOL, V19, P45 TSCHINKEL WR, 1986, FIRE ANTS LEAF CUTTI, P72 TSCHINKEL WR, 1988, ANN ENTOMOL SOC AM, V81, P76 TSCHINKEL WR, 1993, ECOL MONOGR, V63, P425 VERMEULEN HJW, 1994, BIOL CONSERV, V69, P339 VINSON SB, 1994, EXOTIC ANTS BIOL IMP, P240 WALES BA, 1972, ECOL MONOGR, V42, P451 WARNER RE, 1992, BIOL CONSERV, V59, P1 WOJCIK DP, 1983, FLA ENTOMOL, V66, P101 YAHNER RH, 1988, CONSERV BIOL, V2, P333 0921-2973 Landsc. Ecol.ISI:000077308100001Virginia Polytech Inst & State Univ, Dept Biol, Blacksburg, VA 24061 USA. Stiles, JH, Virginia Polytech Inst & State Univ, Dept Biol, Blacksburg, VA 24061 USA. jstiles@vt.eduEnglish<7VtStohlgren, T. J. Coughenour, M. B. Chong, G. W. Binkley, D. Kalkhan, M. A. Schell, L. D. Buckley, D. J. Berry, J. K.1997%Landscape analysis of plant diversity155-170Landscape Ecology123map accuracy assessment; geographic information systems; keystone ecosystems; plant species richness patterns; wildlife models; ecosystem models SAMPLING METHOD; POPULATION; BIODIVERSITY; ENVIRONMENTS; VEGETATION; USAArticleJunU Studies to identify gaps in the protection of habitat for species of concern have been inconclusive and hampered by single-scale or poor multi-scale sampling methods, large minimum mapping units (MMU's of 2 ha to 100 ha), limited and subjectively selected field observations, and poor mathematical and ecological models. We overcome these obstacles with improved multi-scale sampling techniques, smaller MMU's (< 0.02 ha), an unbiased sampling design based on double sampling, improved mathematical models including species-area curves corrected for habitat heterogeneity and geographic information system-based ecological models. We apply this landscape analysis approach to address resource issues in Rocky Mountain National Park, Colorado. Specifically, we quantify the effects of elk grazing on plant diversity, identify areas of high or unique plant diversity needing increased protection, and evaluate the patterns of non-native plant species on the landscape. Double sampling techniques use satellite imagery, aerial photography, and field data to stratify homogeneous and heterogeneous units and ''keystone ecosystems'' (ecosystems that contain or support a high number of species or have distinctive species compositions). We show how a multi-scale vegetation sampling design, species-area curves, analyses of within-and between-vegetation type species overlap, and geographic information system (GIS) models can be used to quantify landscape-scale patterns of vascular plant diversity in the Park. The new multi-scale vegetation plot techniques quickly differentiated plant species differences in paired study sites, Three plots in the Ouzel Burn area (burned in 1978) contained 75 plant species, while only 17 plant species were found in paired plots outside the burn. Riparian areas contained 109 plant species, compared to just 55 species in paired plots in adjacent forests. However, plant species richness patterns inside and outside elk exclosures were more complex, One elk exclosure contained more species than its adjacent open range (52 species inside and 48 species outside). Two elk exclosures contained fewer species inside than outside (105 and 41 species inside and 112 and 74 species outside, respectively). However, there was only 26% to 48% overlap (using Jaccard's Coefficient) of plant species composition inside and outside the exclosures. One elk exclosure had 13% cover of non-indigenous species inside the exclosure compared to 4% outside, but non-indigenous species cover varied by location. We compared plant diversity patterns from vegetation maps made with 100 ha, 50 ha, 2 ha, and 0.02 ha MMU's in the 754 ha Beaver Meadows study area using four 0.025 ha and twenty-one 0.1 ha multi-scale vegetation plots. Preliminary data suggested that the 2 ha MMU provided an accurate estimate of the number of plant species (-14%) for a study area, but the number of habitats (polygons) was reduced by 67%, and aspen, a unique and important habitat type, was missed entirely, We describe a hypothesis-driven approach to the design and implementation of geospatial databases for local resource monitoring and ecosystem management.://A1997XV63400004 ISI Document Delivery No.: XV634 Times Cited: 35 Cited Reference Count: 43 Cited References: AGEE JK, 1988, ECOSYSTEM MANAGEMENT BERRY JK, 1993, BEYOND MAPPING CONCE BOERSMA M, 1991, ECOL MODEL, V55, P219 BROWN JH, 1984, AM NAT, V124, P255 BUCKLEY DJ, 1993, 2 INT C INT GIS ENV BURGMAN MA, 1993, RISK ASSESSMENT CONS CHADDE SW, 1991, GREATER YELLOWSTONE, P231 CHAPIN FS, 1986, AM NAT, V127, P48 CONGALTON RG, 1991, REMOTE SENS ENVIRON, V37, P35 COUGHENOUR MB, 1991, GREATER YELLOWSTONE, P209 COUGHENOUR MB, 1991, P RES TECHN 90 2 INT COUGHENOUR MB, 1992, ECOLOGICAL INDICATOR, V1, P787 COUGHENOUR MB, 1993, SAVANNA LANDSCAPE RE DEBYLE NV, 1985, ASPEN ECOLOGY MANAGE, P115 DEBYLE NV, 1985, ASPEN ECOLOGY MANAGE, P135 FRANKLIN JF, 1993, ECOL APPL, V3, P202 HOLLAND EA, 1992, AM NAT, V140, P685 JONES JR, 1985, ASPEN ECOLOGY MANAGE, P77 KALKHAN MA, 1994, THESIS COLORADO STAT KALKHAN MA, 1995, 9 ANN S GEOGR INF SY KREBS CJ, 1989, ECOLOGICAL METHODOLO LAROE ET, 1993, ENDANGERED SPECIES U, V10, P3 LEVIN SA, 1976, ANNU REV ECOL SYST, V7, P287 LIU JG, 1993, ECOL MODEL, V70, P51 MAYBECK PS, 1979, STOCHASTIC MODELS ES MCINNES PF, 1992, ECOLOGY, V73, P2059 MUEGGLER WF, 1985, ASPEN ECOLOGY MANAGE, P129 NOSS RF, 1983, BIOSCIENCE, V33, P700 PASTOR J, 1987, ALCES, V23, P107 PEET RK, 1988, N AM TERRESTRIAL VEG, P64 PIELOU EC, 1961, J ECOL, V49, P255 PIELOU EC, 1977, MATH ECOLOGY PULLIAM HR, 1988, AM NAT, V132, P652 PULLIAM HR, 1992, ECOL APPL, V2, P165 ROMME WH, 1995, ECOLOGY, V76, P2097 SALT GW, 1957, CONDOR, V59, P373 SCOTT JM, 1993, WILDLIFE MONOGR, V123, P1 SHMIDA A, 1984, ISRAEL J BOT, V33, P41 SHUGART HH, 1984, THEORY FOREST DYNAMI STOHLGREN TJ, 1994, ECOLOGICAL TIME SERI, P209 STOHLGREN TJ, 1995, BIOL CONSERV, V71, P97 STOHLGREN TJ, 1995, VEGETATIO, V117, P113 STRITTHOLT JR, 1995, CONSERV BIOL, V9, P1492 0921-2973 Landsc. Ecol.ISI:A1997XV63400004oStohlgren, TJ, COLORADO STATE UNIV,NAT RESOURCE ECOL LAB,ROCKY MT FIELD STN,NATL BIOL SERV,FT COLLINS,CO 80523.Englishd<78 Stoms, D. M.2000HGAP management status and regional indicators of threats to biodiversity21-33Landscape Ecology151biodiversity California ecological indicators gap analysis land use projected human population growth road density index zoning LAND-USE CONFLICTS FOREST FRAGMENTATION WOLF HABITAT CONSERVATION LANDSCAPE CALIFORNIA VEGETATION DENSITY AREAS ROADSArticleJan'Conservation assessment requires quantitative criteria for evaluating the relative degree of threat faced by species or ecological communities. Identifying appropriate criteria for communities is complicated because the species inhabiting them can have many different responses to land uses and other forms of environmental stress. The Gap Analysis Program (GAP) uses summary data on the proportion of the community that is protected as an estimate of its vulnerability. Management status from a gap analysis of California was compared with three ecological indicators (permitted land uses, human population growth, and the spatial extent of road effects) that more directly represent impacts on biodiversity. The classification of management status appears to provide a crude first approximation of these three indicators. Public and private lands that are not formally protected were susceptible to extensive land use conversion or resource extraction in both rural and urban settings. Some plant community types are more susceptible to future infringement by human population increases that were not well predicted by management status alone. Other community types have a high road density despite being moderately well protected. It is suggested that indicators such as future growth and current road effects could complement status in rating the potential vulnerability of plant communities and setting conservation priorities. The choice of indicators will depend on the threatening processes in a given region and the availability of spatial data to map or model them.://000083830400003 ISI Document Delivery No.: 258GN Times Cited: 21 Cited Reference Count: 45 Cited References: *BUR CENS, 1989, TIGER LIN PREC FIL *CAL DEP FIN, 1997, INT COUNT POP PROJ *USDA FOR SERV, 1998, FOR SERV ROADS SYNTH AWIMBO JA, 1996, BIOL CONSERV, V75, P177 BEARDSLEY K, 1993, NAT AREA J, V13, P177 CHOMITZ KM, 1996, WORLD BANK ECON REV, V10, P487 CLARKE KC, 1997, ENVIRON PLANN B, V24, P247 COGAN C, 1997, P 17 ANN ESRI US C DALE VH, 1994, CONSERV BIOL, V8, P196 DAVIS FW, 1996, SIERRA NEVADA ECOSYS, V2, P1503 DAVIS FW, 1996, SIERRA NEVADA ECOSYS, V2, P671 DAVIS FW, 1998, CALIFORNIA GAP ANAL DINERSTEIN E, 1993, CONSERV BIOL, V7, P53 DUANE TP, 1996, SIERRA NEVADA ECOSYS, V2, P235 FORMAN RTT, 1997, HABITAT FRAGMENTATIO, P40 FORMAN RTT, 1998, ANNU REV ECOL SYST, V29, P207 FORMAN RTT, 1998, LANDSCAPE ECOL, V13, R3 FORMAN RTT, 1998, P INT C WILDL EC TRA, P78 GONZALEZREBELES C, 1998, PHOTOGRAMM ENG REM S, V64, P1115 JONES KB, 1997, EPA600R97130 OFF RES KLOPATEK JM, 1979, ENVIRON CONSERV, V6, P191 KUITUNEN M, 1998, ENVIRON MANAGE, V22, P297 LAURANCE WF, 1991, CONSERV BIOL, V5, P79 LYON LJ, 1983, J FOREST, V81, P592 MASTER LL, 1991, CONSERV BIOL, V5, P559 MILLSAP BA, 1990, WILDLIFE MONOGR, V111, P1 MLADENOFF DJ, 1995, CONSERV BIOL, V9, P279 MOYLE PB, 1998, CONSERV BIOL, V12, P1318 MYERS N, 1988, ENVIRONMENTALIST, V8, P1 NANTEL P, 1998, BIOL CONSERV, V84, P223 NOSS RF, 1987, BIOL CONSERV, V41, P11 NOSS RF, 1995, 28 NAT BIOL SERV NOSS RF, 1996, NATL PARKS PROTECTED, P91 REED RA, 1996, CONSERV BIOL, V10, P1098 RICH AC, 1994, CONSERV BIOL, V8, P1109 SCHONEWALDCOX C, 1992, CONSERVATION BIOL TH, P373 SCOTT JM, 1993, WILDLIFE MONOGR, P1 SPIES TA, 1994, ECOL APPL, V4, P555 STOMS DM, 1998, GREAT BASIN NAT, V58, P199 STRITTHOLT JR, 1995, CONSERV BIOL, V9, P1492 THIEL RP, 1985, AM MIDL NAT, V113, P404 TINKER DB, 1998, LANDSCAPE ECOL, V13, P149 TURNER MG, 1996, ECOL APPL, V6, P1150 USHER MB, 1986, WILDLIFE CONSERVATIO WHITE D, 1997, CONSERV BIOL, V11, P349 0921-2973 Landsc. Ecol.ISI:000083830400003Univ Calif Santa Barbara, Inst Computat Earth Syst Sci, Santa Barbara, CA 93106 USA. Stoms, DM, Univ Calif Santa Barbara, Inst Computat Earth Syst Sci, Santa Barbara, CA 93106 USA.English<7!Storch, I. Woitke, E. Krieger, S.2005ZLandscape-scale edge effect in predation risk in forest-farmland mosaics of central Europe927-940Landscape Ecology208artificial nests; ecotones; experiment; fragmentation; landscape geometry; nest predation; spillover predation ARTIFICIAL GROUND NESTS; FOX VULPES-VULPES; RED FOX; HABITAT FRAGMENTATION; REPRODUCTIVE SUCCESS; SITE SELECTION; BAVARIAN ALPS; BLACK GROUSE; CAPERCAILLIE; METAANALYSISArticleDecoAvian nest predation is known to increase with the degree of forest fragmentation. A common explanation is that farmland allows for high densities of generalist predators, and predators penetrating into the forest cause higher nest losses at forest-farmland edges than in forest interiors. In contrast to numerous patch-level studies of forest edge effects conducted earlier, we broadened the spatial extent to the landscape. We tested the hypothesis of increased predation near farmland over distances of > 4 km from forest-farmland edges into forest interiors in five mountain ranges in Germany, using artificial ground nests. We considered two landscape settings: (1) Transitions between a forest matrix and a farmland matrix, and (2) farmland patches within a forest matrix. Nest losses were not significantly higher in vicinity to a farmland matrix, but proximity to a pasture within the forest matrix strongly increased predation risk. We speculate that these differences resulted from landscape geometry. Farmland patches and matrix alike are highly attractive to generalist predators, and are regularly visited by red foxes from the forest. Predators that traverse the forest and take prey along the way, will cause a concentration of predation risk towards a patch (pasture), but not towards an adjacent matrix (farming lowlands), of feeding habitat. Contrary to previous evidence that edge effects in nest predation level off after 50 m, nest fate was related to distance to pastures across the entire study extent of 4.1 km. Our results suggest that landscape context and predator mobility may greatly affect spatial predation patterns.://000233036400003 ` ISI Document Delivery No.: 980RR Times Cited: 0 Cited Reference Count: 64 Cited References: *DJV, 1994, DJV HDB *DJV, 2004, DJV HDB ANDREN H, 1985, OIKOS, V45, P273 ANDREN H, 1988, ECOLOGY, V69, P544 ANDREN H, 1992, ECOLOGY, V73, P794 ANDREN H, 1995, MOSAIC LANDSCAPES EC, P225 ANGELSTAM P, 1986, OIKOS, V47, P365 BANG P, 1986, BLV BESTIMMUNGSBUCH, V9 BATARY P, 2004, CONSERV BIOL, V18, P389 BAUER UM, 2002, EMBO REP, V3, P39 BAYNE EM, 1997, CONSERV BIOL, V11, P1418 BERBERICH W, 1992, 17 BERCHT NAT PARK BERGIN TM, 2000, LANDSCAPE ECOL, V15, P131 BURKE DM, 2004, CONSERV BIOL, V18, P381 CHALFOUN AD, 2002, CONSERV BIOL, V16, P306 CURRAN LM, 1999, SCIENCE, V286, P2184 DONOVAN TM, 1997, ECOLOGY, V78, P2064 FLASPOHLER DJ, 2001, CONSERV BIOL, V15, P173 FORMAN RTT, 1998, ANNU REV ECOL SYST, V29, P207 HARTLEY MJ, 1998, CONSERV BIOL, V12, P465 HEIBL C, 2003, THESIS TU MUNICH HUHTA E, 1996, ECOGRAPHY, V19, P85 JANKO C, 2003, THESIS U HOHENHEIM G KAPHEGYI T, 2002, THESIS U FREIBURG GE, P95 KAREIVA P, 1987, NATURE, V326, P388 KNAUER F, 2001, UNPUB UBERSICHT PRAD, P200 KURKI S, 1995, ECOGRAPHY, V18, P109 KURKI S, 2000, ECOLOGY, V81, P1985 LAHTI DC, 2001, BIOL CONSERV, V99, P365 LARIVIERE S, 1999, CONDOR, V101, P718 LAURANCE WF, 2000, TRENDS ECOL EVOL, V15, P134 LIDICKER WZ, 1999, LANDSCAPE ECOL, V14, P333 LINDINGER W, 1998, INT J MASS SPECTROM, V173, P191 MACDONALD DW, 1977, MAMMAL REV, V7, P7 MAJOR RE, 1996, IBIS, V138, P298 MOLLER AP, 1989, OIKOS, V56, P240 OKSANEN T, 1992, EVOL ECOL, V6, P383 OKSANEN T, 1995, MAMMALIAN ECOLOGY CO, P122 PATON PWC, 1994, CONSERV BIOL, V8, P17 PETERS HA, 2001, BIOTROPICA, V33, P60 PIETZ PJ, 2000, J WILDLIFE MANAGE, V64, P71 REYNOLDS JC, 1990, NETHERLANDS ORGANISA, P172 ROBINSON SK, 1995, SCIENCE, V267, P1987 RODEWALD AD, 2001, ECOLOGY, V82, P3493 RUSSELL AJM, 2004, EUROPEAN J WILDLIFE, V50 STORAAS T, 1987, J WILDLIFE MANAGE, V51, P167 STORAAS T, 1988, J WILDLIFE MANAGE, V52, P123 STORCH I, 1991, ORNIS SCAND, V22, P213 STORCH I, 1991, Z JAGDWISS, V37, P267 STORCH I, 1994, BIOL CONSERV, V70, P237 STORCH I, 2001, J BIRDS W PALEARCTIC, V3, P1 STORCH I, 2003, WILDLIFE BIOL, V9, P301 THIEL D, 2002, THESIS U ZURICH ZURI THOMPSON FR, 2004, CONSERV BIOL, V18, P373 VOS A, 1993, THESIS U MUNICH VOS A, 1995, ANN ZOOL FENN, V32, P93 VOS A, 2003, J VET MED B, V50, P477 WEBBON CC, 2004, J APPL ECOL, V41, P768 WILCOVE DS, 1985, ECOLOGY, V66, P1211 WILCOVE DS, 1986, CONSERVATION BIOL SC, P237 WILLEBRAND T, 1988, AUK, V105, P378 WILSON GR, 1998, CONDOR, V100, P357 YAHNER RH, 1997, WILDLIFE SOC B, V25, P158 ZANETTE L, 2002, BIOL CONSERV, V103, P323 0921-2973 Landsc. Ecol.ISI:000233036400003Univ Freiburg, Coll Forest & Environm Sci, Dept Wildlife Ecol & Management, D-79085 Freiburg, Germany. Tech Univ Munich, Wildlife Res & Management Unit, D-8050 Freising Weihenstephan, Germany. Univ Munich, Inst Stat, Stablab, Munich, Germany. Storch, I, Univ Freiburg, Coll Forest & Environm Sci, Dept Wildlife Ecol & Management, Tennenbacherstr 4, D-79085 Freiburg, Germany. ilse.storch@wildlife.uni-freiburg.deEnglish |? VStoy, P. C. Williams, M. Disney, M. Prieto-Blanco, A. Huntley, B. Baxter, R. Lewis, P.2009uUpscaling as ecological information transfer: a simple framework with application to Arctic ecosystem carbon exchange971-986Landscape Ecology247Aug(Transferring ecological information across scale often involves spatial aggregation, which alters information content and may bias estimates if the scaling process is nonlinear. Here, a potential solution, the preservation of the information content of fine-scale measurements, is highlighted using modeled net ecosystem exchange (NEE) of an Arctic tundra landscape as an example. The variance of aggregated normalized difference vegetation index (NDVI), measured from an airborne platform, decreased linearly with log(scale), resulting in a linear relationship between log(scale) and the scale-wise modeled NEE estimate. Preserving three units of information, the mean, variance and skewness of fine-scale NDVI observations, resulted in upscaled NEE estimates that deviated less than 4% from the fine-scale estimate. Preserving only the mean and variance resulted in nearly 23% NEE bias, and preserving only the mean resulted in larger error and a change in sign from CO2 sink to source. Compressing NDVI maps by 70-75% using wavelet thresholding with the Haar and Coiflet basis functions resulted in 13% NEE bias across the study domain. Applying unique scale-dependent transfer functions between NDVI and leaf area index (LAI) decreased, but did not remove, bias in modeled flux in a smaller expanse using handheld NDVI observations. Quantifying the parameters of statistical distributions to preserve ecological information reduces bias when upscaling and makes possible spatial data assimilation to further reduce errors in estimates of ecological processes across scale.://000268430900010mStoy, Paul C. Williams, Mathew Disney, Mathias Prieto-Blanco, Ana Huntley, Brian Baxter, Robert Lewis, Philip 0921-2973ISI:00026843090001010.1007/s10980-009-9367-3<74Stroh, J. C. Archer, S. Doolittle, J. A. Wilding, L.2001`Detection of edaphic discontinuities with ground-penetrating radar and electromagnetic induction377-390Landscape Ecology165apparent conductivity argillic horizon edaphic discontinuity plant-soil relationships soil soil mapping soil map unit boundaries soil survey spatial variation SOIL ELECTRICAL-CONDUCTIVITY DEPTH RELATIONS SALINITY SAVANNA VARIABILITY DYNAMICS METERArticleJul~Quantification of edaphic properties which may regulate the spatial distribution of vegetation is often limited by the expense and labor associated with collecting and analyzing soil samples. Here we evaluate the utility of two technologies, ground-penetrating radar (GPR) and electromagnetic induction (EMI), for rapid, extensive and non-destructive mapping of diagnostic subsurface features and soil series map unit boundaries. Strong reflectance from fine-textured, near-surface soils obscured radar signal reflectance from deeper horizons at our field test site in the Rio Grande Plains of southern Texas, USA. As a result, ground-penetrating radar did not delineate known edaphic contrasts along catena gradients. In contrast, EMI consistently distinguished boundaries of soil map units. In several instances, gradients or contrasting inclusions within map units were also identified. In addition, the location and boundary of calcic or cambic-horizon inclusions embedded within a laterally co-extensive and well-developed argillic horizon were consistently predicted. Correlations between EMI assessments of apparent conductivity (ECa) and soil properties such as CEC, pH, particle size distribution and extractable bases were low (i.e., explained <6% of the variance), or non-significant. As a result, EMI has a high prospecting utility, but cannot necessarily be used to explain the basis for edaphic contrasts. Results suggest EMI can be a cost-effective tool for soil survey and exploration applications in plant ecology. As such, it is potentially useful for rapidly locating and mapping subsurface discontinuities, thereby reducing the number of ground truth soil samples needed for accurate mapping of soil map unit boundaries. An application, addressing hypotheses proposed to explain the role of edaphic heterogeneity in regulating woody plant distribution in a savanna parkland landscape, is presented.://000170952100001 ISI Document Delivery No.: 471WR Times Cited: 3 Cited Reference Count: 55 Cited References: *SAS I, 1990, SAS STAT US GUID *SOIL SURV STAFF, 1981, UNPUB USDA AGR HDB, V18, CH4 *SOIL SURV STAFF, 1984, 1 USDA SCS *USDA, 1979, SOIL SURV J WELLS CO AMMONS JT, 1989, SOIL SURVEY HORIZONS, V30, P66 ARCHER S, 1995, ECOSCIENCE, V2, P83 ARCHER S, 2001, GLOBAL BIOGEOCHEMICA, P115 BOETTINGER JL, 1997, ARID SOIL RES REHAB, V11, P375 BORK EW, 1998, J RANGE MANAGE, V51, P469 BOUTTON TW, 1998, GEODERMA, V82, P5 BRADY NC, 1984, NATURE PROPERTY SOIL BRESLER EB, 1932, SALINE SODIC SOILS BRUS DJ, 1992, GEODERMA, V55, P79 CANNON ME, 1994, CAN J SOIL SCI, V74, P335 COLLINS ME, 1987, SOIL SCI SOC AM J, V51, P491 COOK PG, 1992, J HYDROL, V130, P201 CORWIN DL, 1990, COMMUN SOIL SCI PLAN, V21, P861 DANIELS DJ, 1988, IEE P F, V135, P278 DEJONG E, 1979, SOIL SCI SOC AM J, V43, P810 DOOLITTLE JA, 1987, SSSA SPECIAL PUBLICA, V20 DOOLITTLE JA, 1994, J SOIL WATER CONSERV, V49, P552 DOOLITTLE JA, 1995, SOIL SURVEY HORIZONS, V36, P36 ELYOUSSOUFI M, 1992, THESIS TEXAS A M U C GREENHOUSE JP, 1983, GROUND WATER MONIT R, V3, P47 GUCKIAN WJ, 1987, SOILS CAPITA RES ARE, P6 GUJARATI D, 1992, ESSENTIALS EC HENDRICKX JMH, 1992, SOIL SCI SOC AM J, V56, P1933 HOSMER DW, 1988, APPL LOGISTIC REGRES KACHANOSKI RG, 1988, CAN J SOIL SCI, V68, P715 KAWASAKI K, 1988, COLD REG SCI TECH, V15, P279 KITCHEN NR, 1996, J SOIL WATER CONSERV, V51, P336 LOOMIS LE, 1989, THESIS TEXAS A M U C MCAULIFFE JR, 1994, ECOL MONOGR, V64, P111 MCBRIDE RA, 1990, SOIL SCI SOC AM J, V54, P936 MCNEILL JD, 1980, ELECTROMAGNETIC TERR MCNEILL JD, 1986, GEONICS EM38 GROUND MCNEILL JD, 1991, GEOEXPLORATION, V27, P67 MOKMA DL, 1990, SOIL SCI SOC AM J, V54, P936 NETTLETON WD, 1994, SOIL SCI SOC AM J, V56, P1190 RHOADES JD, 1981, SOIL SCI SOC AM J, V45, P255 RHOADES JD, 1990, COMMUN SOIL SCI PLAN, V21, P837 SCANLAN JC, 1991, J VEG SCI, V2, P625 SCIFRES CJ, 1987, TEXAS AGR EXP STA B SHIH SF, 1984, SOIL SCI SOC AM J, V46, P651 STOKER R, 1996, GROWTH RATE AGE CLAS STOKES CJ, 1999, THESIS TEXAS A M U C THIEN SJ, 1979, J AGRON ED, V8, P54 TRUMAN CC, 1988, J SOIL WATER CONSERV, V43, P341 WATTS SE, 1993, THESIS TEXAS A M U C WATTS SE, 1993, THESIS USDA WILLIAMS BG, 1982, AUST J SOIL RES, V20, P107 WILLIAMS BG, 1987, AUST J SOIL RES, V25, P21 WILLIAMS BG, 1990, SPATIAL VARIABILITY WOLLENHAUPT NC, 1986, CAN J SOIL SCI, V66, P315 ZALASIEWICZ JA, 1985, Q J ENGLISH GEOL, V18, P136 0921-2973 Landsc. Ecol.ISI:000170952100001lTexas A&M Univ, College Stn, TX 77843 USA. Stroh, JC, Morningside Coll, Dept Biol, Sioux City, IA 51106 USA.English<7@Sturtevant, B. R. Zollner, P. A. Gustafson, E. J. Cleland, D. T.2004pHuman influence on the abundance and connectivity of high-risk fuels in mixed forests of northern Wisconsin, USA235-253Landscape Ecology193fire risk; fire suppression; fuel distribution; LANDIS; landscape pattern; simulation model; succession; timber harvest GREAT-LAKES REGION; HARDWOOD FORESTS; SPATIAL-PATTERN; LANDSCAPE MODEL; BOREAL FOREST; DISTURBANCE; SUCCESSION; WILDFIRE; FIRE; SIMULATIONArticleThough fire is considered a "natural" disturbance, humans heavily influence modern wildfire regimes. Humans influence fires both directly, by igniting and suppressing fires, and indirectly, by either altering vegetation, climate, or both. We used the LANDIS disturbance and succession model to compare the relative importance of a direct human influence (suppression of low intensity surface fires) with an indirect human influence (timber harvest ) on the long-term abundance and connectivity of high-risk fuel in a 2791 km(2) landscape characterized by a mixture of northern hardwood and boreal tree species in northern Wisconsin. High risk fuels were defined as a combination of sites recently disturbed by wind and sites containing conifer species/cohorts that might serve as "ladder fuel" to carry a surface fire into the canopy. Two levels of surface fire suppression (high/current and low) and three harvest alternatives (no harvest, hardwood emphasis, and pine emphasis) were compared in a 2 x 3 factorial design using 5 replicated simulations per treatment combination over a 250-year period. Multivariate analysis of variance indicated that the landscape pattern of high-risk fuel (proportion of landscape, mean patch size, nearest neighbor distance, and juxtaposition with non fuel sites) was significantly influenced by both surface fire suppression and by forest harvest (p > 0.0001). However, the two human influences also interacted with each other (p > 0.001), because fire suppression was less likely to influence fuel connectivity when harvest disturbance was simultaneously applied. Temporal patterns observed for each of seven conifer species indicated that disturbances by either fire or harvest encouraged the establishment of moderately shade-tolerant conifer species by disturbing the dominant shade tolerant competitor, sugar maple. Our results conflict with commonly reported relationships between fire suppression and fire risk observed within the interior west of the United States, and illustrate the importance of understanding key interactions between natural disturbance, human disturbance, and successional responses to these disturbance types that will eventually dictate future fire risk.://000221878900002 ISI Document Delivery No.: 827DL Times Cited: 6 Cited Reference Count: 54 Cited References: *USDA, 1994, USDA NAT RES CONS SE, V1492 ABER JD, 1991, TERRESTRIAL ECOSYSTE ALMENDINGER JC, 1998, ECOLOGICAL LAND CLAS BORMANN FH, 1979, AM SCI, V67, P660 BURNS RM, 1990, AGR HDB USDA FOREST, V654 CANHAM CD, 1984, ECOLOGY, V65, P803 CARDILLE JA, 2001, ECOL APPL, V11, P111 CARDILLE JA, 2001, INT J WILDLAND FIRE, V10, P145 CLELAND DT, 1997, ECOSYSTEM MANAGEMENT, P181 CLELAND DT, 2004, LANDSCAPE ECOLOGY, V19 CUMMING SG, 2001, ECOL APPL, V11, P97 CURTIS JT, 1959, VEGETATION WISCONSIN FRELICH LE, 1991, ECOL MONOGR, V61, P145 FRELICH LE, 1995, ECOSCIENCE, V2, P148 FRELICH LE, 1999, ECOSYSTEMS, V2, P151 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 GUSTAFSON EJ, 2000, CAN J FOREST RES, V30, P32 GUSTAFSON EJ, 2004, LANDSCAPE ECOLOGY, V19 HANSEN MH, 1992, NC151 USDA FOR SERV HE HS, 1999, ECOL MODEL, V114, P213 HE HS, 1999, ECOL MODEL, V119, P1 HE HS, 1999, ECOLOGY, V80, P81 HEINSELMAN ML, 1954, J FOREST, V52, P737 HEINSELMAN ML, 1973, QUATERNARY RES, V3, P329 HESSBURG PF, 1999, ECOL APPL, V9, P1232 HOLLING CS, 1996, CONSERV BIOL, V10, P328 HOST GE, 1996, ECOL APPL, V6, P608 JOHNSON EA, 2001, CONSERV BIOL, V15, P1554 KAFKA V, 2001, INT J WILDLAND FIRE, V10, P119 KEYS J, 1995, ECOLOGICAL UNITS E U LILLESAND T, 1998, UPPER MIDWEST GAP AN MACLEAN AL, 2003, P RMRS P, V29, P289 MCCUNE B, 1988, AM J BOT, V75, P353 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MILLER C, 2000, ECOL APPL, V10, P85 MLADENOFF DJ, 1993, CONSERV BIOL, V7, P889 MLADENOFF DJ, 1993, DEFINING SUSTAINABLE, P145 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 MLADENOFF DJ, 1999, SPATIAL MODELING FOR, P125 MOORE MM, 1999, ECOL APPL, V9, P1266 MUTCH RW, 1995, P C FOR HLTH FIR DAN, P18 PASTOR J, 1986, BIOGEOCHEMISTRY, V2, P3 PASTOR J, 1992, SYSTEMS ANAL GLOBAL, P216 RADELOFF VC, 1998, T WISC ACAD SCI, V86, P189 RADELOFF VC, 1999, CAN J FOREST RES, V29, P1649 ROMME WH, 1982, ECOL MONOGR, V52, P199 SMITH T, 1989, VEGETATIO, V83, P49 SPIES TA, 1994, ECOL APPL, V4, P555 STAUFFER D, 1985, INTRO PERCOLATION TH STEARNS FW, 1997, USDA N CENT, V189, P8 STEPHENSON NL, 1999, ECOL APPL, V9, P1253 TURNER MG, 1989, OIKOS, V55, P121 WOLTER PT, 1995, PHOTOGRAMM ENG REM S, V61, P1129 ZAR JH, 1999, BIOSTATISTICAL ANAL 0921-2973 Landsc. Ecol.ISI:000221878900002US Forest Serv, USDA, N Cent Res Stn, Rhinelander, WI 54501 USA. Sturtevant, BR, US Forest Serv, USDA, N Cent Res Stn, 5985 Highway K, Rhinelander, WI 54501 USA. bsturtevant@fs.fed.usEnglishj<73Suarez, E. R. Tierney, G. L. Fahey, T. J. Fahey, R.2006qExploring patterns of exotic earthworm distribution in a temperate hardwood forest in south-central New York, USA297-306Landscape Ecology212earthworm invasion; exotic earthworm distribution; habitat quality; northern hardwood forests DENDROBAENA-OCTAEDRA LUMBRICIDAE; TALLGRASS PRAIRIE; UPLAND FOREST; ABUNDANCE; INVASION; COMMUNITY; LITTER; HIMALAYAS; DYNAMICS; DENSITYArticleFebYExotic earthworms invading forests in Canada and northeastern United States that were naturally devoid of large detritivores cause major changes in ecosystem function. To assess their long-term impacts, studies are needed to elucidate the factors that control the patterns of earthworm invasion at the landscape level. We analyzed the distribution patterns of exotic earthworms in a northern hardwood forest in south-central New York (USA), as explained by landscape variables thought to be important in determining earthworm distribution. Forest type, slope angle, elevation, and the distance to agricultural clearings and wet refugia were significant predictors of earthworm presence, whereas local wetness index and the distance to streams and roads were not. Forest type and distance to agricultural clearings were the two most significant predictors. Our data suggest that areas close to agricultural clearings, dominated by mixed hardwoods, and located towards valley bottoms or on gentle slopes are very likely to support communities of exotic earthworms. Steeper slopes, areas dominated by American beech or eastern hemlock, and locations in the core of extensive forest landscapes have lower probabilities of invasion by exotic earthworms. When applied to a nearby area, our statistical model correctly predicted earthworm presence for 67% of 377 sampling points. Most of the mistakes were incorrect predictions of earthworm absence, suggesting that our statistical model slightly underestimated earthworm presence, possibly because of the pervasive influence of active agricultural fields adjacent to the test site.://000235866400012 ISI Document Delivery No.: 019WC Times Cited: 0 Cited Reference Count: 38 Cited References: ALBAN DH, 1994, APPL SOIL ECOL, V1, P243 BAILEY DE, 2002, NORTHWEST SCI, V76, P26 BHADAURIA T, 2000, SOIL BIOL BIOCHEM, V32, P2045 BOHLEN PJ, 1997, ECOL APPL, V7, P1341 BOHLEN PJ, 2004, ECOSYSTEMS, V7, P1 BOHLEN PJ, 2004, FRONT ECOL ENVIRON, V2, P427 CALLAHAM MA, 1999, PEDOBIOLOGIA, V43, P507 DECAENS T, 2001, ECOGRAPHY, V24, P671 DYMOND P, 1997, SOIL BIOL BIOCHEM, V29, P265 EDWARDS CA, 1963, SOIL ORGANISMS, P76 FAHEY TJ, 1998, J TORREY BOT SOC, V125, P51 FAIN JJ, 1994, B TORREY BOT CLUB, V121, P130 FRAGOSO C, 1993, SOIL ORGANIC MATTER, P231 GONZALEZ G, 1999, BIOTROPICA, V31, P486 GUNDALE MJ, 2002, CONSERV BIOL, V16, P1555 HALE CM, 2004, THESIS U MINNESOTA HALE CM, 2005, ECOL APPL, V15, P848 HENDRIX PF, 1992, SOIL BIOL BIOCHEM, V24, P1357 HENDRIX PF, 2002, BIOSCIENCE, V52, P801 JAMES SW, 1982, PEDOBIOLOGIA, V24, P37 KAUSHAL BR, 1999, EUR J SOIL BIOL, V35, P171 KING HGC, 1967, PEDOBIOLOGIA, V7, P192 KUSS O, 2002, STAT MED, V21, P3789 LANGMAID KK, 1964, CAN J SOIL SCI, V44, P34 LIANG KY, 1986, BIOMETRIKA, V73, P13 MARGERIE P, 2001, EUR J SOIL BIOL, V37, P291 MARINISSEN JCY, 1992, OECOLOGIA, V91, P371 MOORE ID, 1991, HYDROL PROCESS, V5, P1 MUYS B, 1992, SOIL BIOL BIOCHEM, V24, P1459 SCHEU S, 1994, ECOLOGY, V75, P2348 SCHEU S, 2003, OIKOS, V101, P225 SCHWERT DP, 1979, CAN FIELD NAT, V93, P180 SUAREZ E, IN PRESS BIOL INVASI SUAREZ E, IN PRESS ECOL APPL WELBOURN ML, 1979, THESIS CORNELL U ITH WILLS A, 2003, BIOL FERT SOILS, V39, P94 ZOU X, 1995, SOIL BIOL BIOGEOCHEM, V29, P627 ZOU XM, 1993, BIOL FERT SOILS, V15, P35 0921-2973 Landsc. Ecol.ISI:000235866400012Cornell Univ, Dept Nat Resources, Ithaca, NY 14853 USA. Suarez, ER, Wildlife Conservat Soc Ecuador, San Francisco 441 & Mariano Echeverria,Apartado P, Quito, Ecuador. esuarez@wcs.orgEnglish <7 2Suarez-Rubio, M. Lookingbill, T. R. Wainger, L. A.2012Modeling exurban development near Washington, DC, USA: comparison of a pattern-based model and a spatially-explicit econometric model 1045-1061Landscape Ecology277land-use change low-density residential development hazard model natural amenities sleuth urban-fringe land-use change remotely-sensed data urban-growth cellular-automata residential development tropical deforestation cross classifications socioeconomic data united-states open spaceAugQThe development of private rural lands can significantly fragment landscapes, with potentially negative consequences on ecosystem services. Models of land-use trends beyond the urban fringe are therefore useful for developing policy to manage these environmental effects. However, land-use change models have been primarily applied in urban environments, and it is unclear whether they can adequately predict exurban growth. This study compared the ability of two urban growth models to project exurban development in north-central Virginia and western Maryland over a 24-year period. Pattern-based urban growth models (such as SLEUTH) are widely used, but largely mimic patterns that emerge from historic conditions rather than allowing landowner decision-making to project change. In contrast, spatially-explicit econometric models (such as the complementary log-log hazard assessed in this study) model landowner choices as profit-maximizing behavior subject to market and regulatory constraints. We evaluated the two raster-based models by comparing model predictions to observed exurban conversion at pixel and county scales. The SLEUTH model was more successful at matching the total amount of new growth at the county scale than it was at the pixel scale, suggesting its most appropriate use in exurban areas is as a blunt instrument to forewarn potential coarse-scale losses of natural resources. The econometric model performed significantly better than SLEUTH at both scales, although it was not completely successful in fulfilling its promise of projecting changes that were sensitive to policy. The lack of significance of some policy variables may have resulted from insufficient variation in drivers over our study area or time period, but also suggests that drivers of land use change in exurban environments may differ from those identified for urban areas.://000306068200009-969PP Times Cited:0 Cited References Count:78 0921-2973Landscape EcolISI:000306068200009Suarez-Rubio, M Univ Nat Resources & Life Sci, Inst Zool, Dept Integrat Biol & Biodivers Res, Gregor Mendel Str 33, A-1180 Vienna, Austria Univ Nat Resources & Life Sci, Inst Zool, Dept Integrat Biol & Biodivers Res, Gregor Mendel Str 33, A-1180 Vienna, Austria Univ Maryland, Ctr Environm Sci, Appalachian Lab, Frostburg, MD 21532 USA Univ Richmond, Dept Geog & Environm, Richmond, VA 23173 USA Univ Maryland, Ctr Environm Sci, Chesapeake Biol Lab, Solomons, MD 20688 USADOI 10.1007/s10980-012-9760-1English<7 Suffling, R.1993XInduction of vertical zones in sub-alpine valley forests by avalanche-formed fuel breaks127-138Landscape Ecology82MFOREST PINE; AVALANCHE; VEGETATION ZONATION; ALBERTA; ROCKY MOUNTAINS; CANADAArticleJunVertical zonation of forests in high mountains is normally explained in terms of climatic variation, but avalanche tracks can act as fuel-breaks in southern Alberta Rocky Mountain forests. This is an additional way of explaining the spruce-fir (Picea engelmannii (Parry) Engelm. - Abies lascioparpa (Hook.) Nutt.) and lodgepole pine (Pinus contorta Dougl. var. latifolia Wats.) communities of the upper and lower sub-alpine zones. The hypotheses are that: 1) Fires start more often at lower than high altitude and that, as they spread into high valleys, 2) they are halted where avalanche tracks reach the valley bottom from both slopes. Also, (3) the average return interval of fires will be greater above this ''avalanche block'', and 4) vegetation above the block will consist primarily of near-climax, fire-intolerant communities. These hypotheses were tested using the Highwood Pass (50-degrees-21'N, 114-degrees-26'W) in the Rocky Mountains of southern Alberta, Canada. Maps of avalanche tracks and past fires, a point-centered quarter survey of forest stands, and disturbance histories established by increment coring were used to test the hypotheses which were all upheld. Thus avalanche tracks are one of the complex of factors limiting fires in the sub-alpine zone of the Alberta Rocky Mountains. The results, additionally, imply that vertical vegetation zones in temperate high mountains are influenced, not only by climatic factors, but also by avalanches and other landforms.://A1993LM22200005 HISI Document Delivery No.: LM222 Times Cited: 8 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1993LM22200005PSUFFLING, R, UNIV WATERLOO,FAC ENVIRONM STUDIES,WATERLOO N2L 3G1,ONTARIO,CANADA.English)}?.Sullivan, S. M. P. Watzin, M. C. Keeton, W. S.2007qA riverscape perspective on habitat associations among riverine bird assemblages in the Lake Champlain Basin, USA 1169-1186Landscape Ecology228Oct://000248941900005 0921-2973ISI:000248941900005 |7.Sun, D. F. Dawson, R. Li, H. Wei, R. Li, B. G.2007bA landscape connectivity index for assessing desertification: a case study of Minqin County, China531-543Landscape Ecology224~landscape connectivity cost-distance land use types desertification assessment china changing scale gis environment model areaAprAs a global and regional environmental problem, desertification assessment is an instrumental component in developing global/regional actions plans aimed at preventing and/or eradicating desertification issues. Using a landscape assessment approach allows for relatively quick assessments of desertification that can then be used in developing practicable application plans at the regional level in desertification prevention planning and decision-making. This study was conducted to determine whether a cost-distance connectivity index could both reveal evidence of, and act as an indicator for, desertification. Cost-distance, a simple GIS-calculated connectivity measure, was applied to a 1997 land use map to indicate desertification in Minqin County, China. The results showed that connectivity based on cost-distance follows basic landscape ecological principles including species-area relations and edge effects, and indicates desertification. Although grain size had a significant effect on the cost-distance index, especially at patch boundaries, log cost-distance closely corresponded with degree of desertification within grain size. Changing the extent of analysis had no significant effect on the cost-distance index and its relevance to degree of desertification. The Minqin County landscape had a high level of connectivity, although the area's grasslands, oasis irrigated cultivated lands, alkali-saline lands and forestlands played important roles in resisting desertification. Three areas require restoration of native vegetation or afforestion to cut the connectivity of desertified patches. The application of connectivity based on cost-distance provides a straightforward, easily visualized description of desertification. In addition, land use data is readily available in China, allowing for relatively easy and quick assessments of regional level desertification for planning and decision-making.://000245296600005-151NF Times Cited:1 Cited References Count:37 0921-2973ISI:000245296600005jWei, R Peking Univ, Coll Environm Sci, Lab Earth Surface Proc, Beijing 100871, Peoples R China Peking Univ, Coll Environm Sci, Lab Earth Surface Proc, Beijing 100871, Peoples R China China Agr Univ, Coll Nat Resources & Envir, Lab Plant Soil Interact Proc, Minist Educ, Beijing 100094, Peoples R China Beijing Acad Agr & Forestry, Beijing 100089, Peoples R ChinaDoi 10.1007/S10980-006-9046-6English )<7 Sundar, K. S. G. Kittur, S. A.2012Methodological, temporal and spatial factors affecting modeled occupancy of resident birds in the perennially cultivated landscape of Uttar Pradesh, India59-71Landscape Ecology271farmland birds intensity of cultivation multi-season occupancy remnant habitat estimating site occupancy agricultural environments farmland birds rice fields land conservation england habitat walesJanBiodiversity persistence in non-woody tropical farmlands is poorly explored, and multi-species assessments with robust landscape-scale designs are sparse. Modeled species occupancy in agricultural mosaics is affected by multiple factors including survey methods (convenience-based versus systematic), landscape-scale agriculture-related variables, and extent of remnant habitat. Changes in seasonal crops can additionally alter landscape and habitat conditions thereby influencing species occupancy. We investigated how these factors affect modeled occupancy of 56 resident bird species using a landscape-scale multi-season occupancy framework across 24 intensively cultivated and human-dominated districts in Uttar Pradesh state, north India. Convenience-based roadside observations provided considerable differences in occupancy estimates and associations with remnant habitat and intensity of cultivation relative to systematic transect counts, and appeared to bias results to roadside conditions. Modeled occupancy of only open-area species improved with increasing intensity of cultivation, while remnant habitat improved modeled occupancy of scrubland, wetland and woodland species. Strong seasonal differences in occupancy were apparent for most species across all habitat guilds. Further habitat loss will be most detrimental to resident scrubland, wetland and woodland species. Uttar Pradesh's agricultural landscape has a high conservation value, but will require a landscape-level approach to maintain the observed high species richness. Obtaining ecological information from unexplored landscapes using robust landscape-scale surveys offers substantial advantages to understand factors affecting species occupancy, and is necessary for efficient conservation planning.://000298228300005-864HI Times Cited:0 Cited References Count:39 0921-2973Landscape EcolISI:000298228300005Sundar, KSG Int Crane Fdn, E11376,Shady Lane Rd, Baraboo, WI 53913 USA Int Crane Fdn, E11376,Shady Lane Rd, Baraboo, WI 53913 USA Univ Minnesota, Conservat Biol Program, St Paul, MN 55108 USADOI 10.1007/s10980-011-9666-3English<7R2Suzuki, K. Suzuki, H. Binkley, D. Stohlgren, T. J.1999YAspen regeneration in the Colorado Front Range: differences at local and landscape scales231-237Landscape Ecology143_elk Cervus elaphus herbivore effects National Park management PLANT DIVERSITY NATIONAL-PARK ELKArticleJunElk (Cervus elaphus) populations in Rocky Mountain National Park are higher than at any time in the past century, and heavy browsing by elk may interfere with aspen (Populus tremuloides Michx.) regneration. We used aerial photographs to identify all aspen stands within Rocky Mountain National Park, and all aspen stands within the elk winter range range (defined as 2400 to 2800 m elevation) in three portions of the adjacent Roosevelt National Forest. From this population of aspen stands, we randomly selected 57 stands for evaluation of aspen regeneration. Stands that contained stems younger than 30 years and taller than 2.5 m tall were classified as regenerating successfully. Only 20% of the aspen stands in Estes Valley contained a cohort of regenerating aspen stems, whereas 45-to-75% of aspen stands across the larger landscape of the Front Range had regenerating cohorts of aspen. Within the elk winter range of the Roosevelt National Forest, 13 of 17 aspen stands were regenerating. In the elk winter range on the east side of the Park but outside of Estes Valley, 11 of 15 aspen stands were regenerating successfully. Only a few aspen stands exist in the elk winter range on the western side of the Park, and none of the five aspen stands sampled in Kawuneeche Valley had a regenerating cohort. The lack of regeneration in Kawuneeche Valley may result from locally heavy elk use in both winter and summer. In the summer elk range at higher elevations in the Park (2800 to 3200 m), 16 of 23 stands had regenerated. At landscape scales, all locations outside of the heavily impacted Estes Valley averaged about two cohorts/stand that regenerated after the mid-1960s. All stands that lacked a regenerating cohort showed evidence of moderate-to-severe damage from elk browsing of stems. No regenerating stands showed evidence of severe browsing. We conclude that at landscape scales, regeneration within aspen stands is very common across the Front Range, except in local areas of the highest elk use where little regeneration has occurred in the past 30 years.://000081041200001 KISI Document Delivery No.: 209HB Times Cited: 22 Cited Reference Count: 23 Cited References: *CO DIV WILDL, 1996, ELK HAB DAT *USDA FOR SERV, 1982, 22 USDA FOR SERV BAKER WL, 1997, ECOGRAPHY, V20, P155 BERRY J, 1997, SCI BASED ASSESSMENT BROWN JK, 1986, INT205 USDA FOR SERV DEBYLE NV, 1985, ASPEN ECOLOGY MANAGE, P135 KAY CE, 1997, J FOREST, V95, P4 KREBILL RG, 1972, INT129 USDA FOR SERV LARKINS KF, 1997, THESIS U NO COLORADO MOWRER HT, 1987, RM476 USDA FOR SERV MUTEL CF, 1984, GRASSLAND GLACIER OLMSTED CE, 1977, THESIS U COLORADO BO OLMSTED CE, 1979, N AM ELK ECOLOGY BEH, P89 ROMME WH, 1995, ECOLOGY, V76, P2097 ROMME WH, 1997, NAT AREA J, V17, P17 SHEPPERD WD, 1981, SIT MAN 2 INT SPEC A, V1 SHEPPERD WD, 1991, THESIS COLORADO STAT SHEPPERD WD, 1994, SUSTAINABLE ECOLOGIC, P344 SOKAL R, 1981, BIOMETRY STOHLGREN T, 1998, IN PRESS ECOLOGY STOHLGREN TJ, 1997, ENVIRON MONIT ASSESS, V48, P25 STOHLGREN TJ, 1997, LANDSCAPE ECOL, V12, P155 TURCHI GM, 1995, WILSON BULL, V107, P463 0921-2973 Landsc. Ecol.ISI:000081041200001Colorado State Univ, Grad Degree Program Ecol, Ft Collins, CO 80523 USA. Binkley, D, Colorado State Univ, Grad Degree Program Ecol, Ft Collins, CO 80523 USA.EnglishH<7!Svoray, T. Mazor, S. Pua, B.2007xHow is shrub cover related to soil moisture and patch geometry in the fragmented landscape of the Northern Negev desert?105-116Landscape Ecology221 aerial photographs; digital elevation models (DEM); fuzzy logic; patch scale; geographical information systems (GIS) PINYON-JUNIPER WOODLAND; HABITAT FRAGMENTATION; SLOPE ASPECT; FUZZY-LOGIC; VEGETATION; ECOSYSTEM; CLIMATE; DESERTIFICATION; COLONIZATION; COEXISTENCEArticleJanAmong the major challenges of landscape ecologists is to develop relatively simple models to quantify ecological processes over large areas. Application of such models can be well demonstrated in fragmented semi-arid ecosystems where competition over resources is intense due to habitat loss, however, only a few studies have done so. Our aim was to model and study the integrated effect of spatial variation in potential soil moisture and patch size and shape on shrub-grass ratio (SGR) in a semi-arid fragmented environment. We specifically ask: (i) what factors most strongly relate to SGR in large remnant patches (> 1.6 ha), and (ii) do different factors more strongly relate to SGR in small patches (< 1.6 ha)? The study was carried out using 60 patches within a semi-arid fragmented environment in the Northern Negev of Israel. Aerial photographs and digital elevation models were used to map six environmental variables: wetness index, aspect, rock cover, rock pattern, patch area, and patch shape. The variables were designed in GIS and were modeled using fuzzy logic procedures to predict SGR, and these predictions were compared to shrub cover maps extracted using maximum likelihood classification of aerial photographs taken in September 2003. We found that in the study area, factors indicating potential soil moisture are most strongly related to SGR in large patches, whereas patch geometric attributes are more strongly relate to SGR in small patches.://000243619800010 ~ ISI Document Delivery No.: 127XO Times Cited: 0 Cited Reference Count: 51 Cited References: ACKERMANN O, 2004, CATENA, V57, P309 BARKUTIEL P, 2005, EUR IALE C LANDSC EC BARLING RD, 1994, WATER RESOUR RES, V30, P1029 BELSKY AJ, 1994, ECOLOGY, V75, P922 BOJORQUEZTAPIA LA, 2002, ENVIRON MANAGE, V30, P418 BRESHEARS DD, 1999, LANDSCAPE ECOL, V14, P465 BUCHBINDER B, 1996, GEOLOGICAL MAP HASHP BURROUGH PA, 2000, PRINCIPALS GEOGRAPHI CANFIELD HE, 2001, CATENA, V44, P1 COLLINGE SK, 2002, LANDSCAPE ECOL, V17, P647 DAN Y, 1988, MAN ENV SO SHEFELAH, P50 DANIN A, 1988, MAN ENV SO SHEFELAH, P59 DEBINSKI DM, 2000, CONSERV BIOL, V14, P342 DEBLOIS S, 2002, ECOGRAPHY, V25, P244 DEMERES MN, 2000, FUNDAMENTALS GEOGRAP EFRAT E, 1994, RURAL GEOGRAPHY ISRA FAHRIG L, 2003, ANNU REV ECOL EVOL S, V34, P487 FERNANDEZILLESCAS CP, 2003, ECOL MONOGR, V73, P207 FORMAN RTT, 1986, LANDSCAPE ECOLOGY GIBBS JP, 2001, BIOL CONSERV, V100, P15 HAILA Y, 2002, ECOL APPL, V12, P321 HILLERISLAMBERS R, 2001, ECOLOGY, V82, P50 HOUSE JI, 2003, J BIOGEOGR, V30, P1763 KUTIEL P, 1992, ISRAEL J BOT, V41, P243 LEHOUEROU HN, 1996, J ARID ENVIRON, V34, P133 LEVIN SA, 1974, AM NAT, V108, P207 MARSHALL EJR, 2002, AGR ECOSYST ENVIRON, V89, P5 MILNE BT, 1996, ECOLOGY, V77, P805 NOYMEIR I, 1973, ANNU REV ECOL SYST, V4, P25 POESEN J, 1994, CATENA, V23, P1 POESEN JW, 1998, GEOMORPHOLOGY, V23, P323 REID KD, 1999, SOIL SCI SOC AM J, V63, P1869 ROBINSON VB, 2003, T GIS, V7, P3 SANKARAN M, 2004, ECOL LETT, V7, P480 SCHLESINGER WH, 1990, SCIENCE, V247, P1043 SCHLESINGER WH, 1996, ECOLOGY, V77, P364 SCHOLES RJ, 1997, ANNU REV ECOL SYST, V28, P517 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SHARON D, 2002, EARTH SURF PROC LAND, V27, P867 SHMIDA A, 1984, VEGETATIO, V58, P29 SHOSHANY M, 2002, REMOTE SENS ENVIRON, V82, P5 STERNBERG M, 2001, ECOL RES, V16, P335 SVORAY T, 2004, ECOL MODEL, V180, P537 SVORAY T, 2005, IEEE GEOSCI REMOTE S, V2, P211 VANWIJK MT, 2002, WATER RESOUR RES, V38 WALKER JP, 1999, WATER RESOUR RES, V35, P2259 WALTER H, 1971, ECOLOGY TROPICAL SUB WILBY A, 2004, OIKOS, V106, P209 YAIR A, 2002, GEOMORPHOLOGY, V42, P43 YAO J, 1999, ECOGRAPHY, V22, P715 ZANGVIL A, 1988, MAN ENV SO SHEFELAH, P42 0921-2973 Landsc. Ecol.ISI:000243619800010Ben Gurion Univ Negev, Dept Geog & Environm Dev, IL-84105 Beer Sheva, Israel. Svoray, T, Ben Gurion Univ Negev, Dept Geog & Environm Dev, IL-84105 Beer Sheva, Israel. tsvoray@bgu.ac.ilEnglish9۽7 Swaffield, Simon2013SEmpowering landscape ecology-connecting science to governance through design values 1193-1201Landscape Ecology286Springer Netherlands 2013/07/01+http://dx.doi.org/10.1007/s10980-012-9765-9 0921-2973Landscape Ecol10.1007/s10980-012-9765-9Englishn<7tSwaffield, S. Primdahl, J.2006USpatial concepts in landscape analysis and policy: some implications of globalisation315-331Landscape Ecology213yChristchurch New Zealand; Copenhagen; Edge city; globalisation; landscape analysis; urban fringe ECOLOGY; ZEALAND; EUROPEArticleApr Globalisation accelerates the dynamics of the network society and economy, in which distant relationships become functionally more significant than local landscape relationships. This presents challenges and opportunities for landscape analysis. Using social scientific concepts of global and local space, and ecological concepts of hierarchy, two qualitative case studies are undertaken of urban fringe landscapes in Copenhagen, Denmark, and Christchurch, New Zealand. They reveal a convergence of landscape pattern over time, but this disguises significant differences in underlying socio-economic process and institutional response. There are several implications for landscape analysis and policy. First, there is a need for studies grounded in particular landscapes that acknowledge both local spatial landscape relationships and non spatial 'global' processes. Second, the transformation of landscapes through urbanisation provides a useful focus for the connection of landscape ecological understanding of landscape systems with social scientific understanding of human agency and social structure. Third, there is a significant challenge in how to develop local and regional institutions and policies that have the capacity to utilise and apply these diverse analytical perspectives.://000236968500002 ISI Document Delivery No.: 034ZD Times Cited: 0 Cited Reference Count: 74 Cited References: *CHRISTCH CIT COUN, 2000, WAT WETL ASS MAN STR *COUNTR COM, 1996, CCX41 COUNTR COMM *EGNSPL, 1948, SKITS EGNSPL STORK T *HOV UDV, 2003, REG 2003 DEB *INT ASS LANDSC EC, 1998, INT ASS LANDSCAPE EC, V16, P1 *INT UN CONS NAT, 1994, GUID PROT AR MAN INT *PARL COMM ENV, 2001, MAN CHANG PAR SUST D *UN C ENV DEV, 1992, AG 21 PROGR ACT SUST AARDMAND A, 1993, DANSK BYPLANLAEGNING AHERN J, 2002, GREENWAYS STRATEGIC ALLEN TFH, 1982, HIERARCHY PERSPECTIV ANTROP M, 2000, LANDSCAPE ECOL, V15, P257 BRANDT J, 2000, LANDSCAPE ECOL, V15, P181 CASTELLS M, 2000, RISE NETWORK SOC COOMBES BL, 2003, ENVIRON PLANN B, V30, P201 CORNER J, 1996, TAKING MEASURES AM L CORNER J, 1999, RECOVERING LANDSCAPE CZERNIAK J, 2001, CASE DOWNSVIEW PARK ELSON M, 1986, GREEN BELTS CONFLICT FABOS JG, 1978, MELAND LANDSCAPE PLA FABOS JG, 1995, GREENWAYS BEGINNING FORMAN RTT, 1986, LANDSCAPE ECOLOGY FORMAN RTT, 1995, LAND MOSAICS ECOLOGY GARE AE, 2000, INT J SUST DEV WORLD, V7, P277 GARREAU J, 1991, EDGE CITIES GIDDENS A, 1999, RUNAWAY WORLD GLOBAL GRAHAM S, 2001, SPLINTERING URBANISM GREGORY D, 1993, GEOGRAPHICAL IMAGINA HANDLEY J, 1998, LANDSCAPE RES, V23, P133 HARVEY D, 1996, JUSTICE NATURE GEOGR HEALEY P, 1997, COLLABORATIVE PLANNI HEIDEGGER M, 1977, BASIC WRITINGS HOUGH M, 1995, CITIES NATURAL PROCE KNUDSEN T, 1988, STORBYEN STOBES KOBE LAMMERS GW, 1996, ECNC PUBLICATIONS SE, V1, P101 LEFEBVRE H, 1991, PRODUCTION SPACE LEHERON R, 1996, CHANGING PLACES NZ 9 LYNCH K, 1960, IMAGE CITY LYNCH K, 1976, MANAGING SENSE REGIO MABBUTT JA, 1968, LAND EVALUATION MACKAYE B, 1928, NEW EXPLORATION MCHARG I, 1969, DESIGN NATURE MCKINNON M, 1997, NZ HIST ATLAS MEMON PA, 2003, NZ GEOGRAPHER, V59, P27 MEURK CD, 2000, LANDSCAPE URBAN PLAN, V50, P129 MORAN W, 1980, OUR LAND OUR FUTURE MOSS MR, 2000, LANDSCAPE ECOL, V15, P303 NASSAUER J, 1997, PLACING NATURE CLTUR NAVEH Z, 1993, LANDSCAPE ECOLOGY TH NDUBISI F, 2002, ECOLOGICAL PLANNING NIELSEN B, 2002, BYPLAN, V2, P70 NILAS C, 2003, BYPLAN, V1, P23 OCONNOR KF, 1993, ENV PLANNING NZ OGSTRUP S, 1996, RES SERIES DSR TRYK, V14 OLWIG K, 2002, LANDSCAPE NATURE BOD OLWIG KR, 1996, ANN ASSOC AM GEOGR, V86, P630 PATTERSON D, 1997, LANDSCAPE URBAN PLAN, V36, P327 PICKETT STA, 2001, ANNU REV ECOL SYST, V32, P127 RASMUSSEN SE, 1994, KOBENHAVN BYSAMFUNDS RELPH E, 1993, DWELLING SEEING DESI SPIRN AW, 1988, LANDSCAPE J, V7, P108 SPIRN AW, 1998, LANGUAGE LANDSCAPE STEINITZ C, 1976, HAND DRAWN OVERLAYS, P444 SWAFFIELD SR, 2003, AUSTRALASIAN FORESTR THAYER RL, 2003, LIFEPLACE BIOREGIONA THOMASSEN O, 1980, LYSE DAGE SORTE NAET WARSON A, 2000, ARCHITECTURAL REC, V188, P28 WATERTON C, 2002, SOC STUD SCI, V32, P177 WOOD R, 2001, LANDSCAPE RES, V26, P45 WU JG, 1995, Q REV BIOL, V70, P439 WU JG, 2004, LANDSCAPE ECOL, V19, P125 YOUNG T, 2000, LANDSCAPE J, V19, P46 ZIMMERMAN J, 2001, URBAN GEOGR, V22, P249 ZONNEVELD IS, 1995, LAND ECOLOGY 0921-2973 Landsc. Ecol.ISI:000236968500002Lincoln Univ, Environm Soc & Design Div, Canterbury, New Zealand. KVL Univ, Copenhagen, Denmark. Swaffield, S, Lincoln Univ, Environm Soc & Design Div, POB 84, Canterbury, New Zealand. swaffies@lincoln.ac.nzEnglish<7Sweeney, B. A. Cook, J. E.2001fA landscape-level assessment of understory diversity in upland forests of North-Central Wisconsin, USA55-69Landscape Ecology161affinity analysis alpha diversity beta diversity gamma diversity habitat types landscape ecology mosaic diversity understory upland forests SPECIES-DIVERSITY GREAT-LAKES NEW-ENGLAND PATTERNS GROWTH COMMUNITIES 2ND-GROWTH SEEDLINGS MICHIGAN HISTORYArticleJanxThe study measured landscape level diversity of the understory plants of mature, upland forests in north-central Wisconsin USA. Habitat types were used to segregate the landscape along a moisture-nutrient gradient. Forty sites that had closed canopies, had been undisturbed for at least 20 years, and were at least 8 ha in size were used. The percent cover of groundlayer species was ocularly estimated in 12-18 randomly located, one meter square plots in June and August, 1995. Shrub cover was estimated by the line intercept method. Alpha, beta and gamma diversity were determined for early and late summer periods separately. Gamma diversity was quantified using a new method, affinity analysis, which generates a list of modal and outlier sites and calculates mosaic diversity, a measure of landscape complexity. Generally, communities in the middle of the moisture-nutrient gradient were modal, whereas those at the mesic end of the gradient were outlier. Mosaic diversity values were very similar for early summer and late summer (2.88 +/-0.04, 2.95 +/-0.03, respectively), but was much higher for both periods combined (3.95 +/-0.07). Whittaker's Index (beta diversity) revealed varying rates of species turnover along presumed moisture and nutrient gradients, whereas species densities and richness were relatively constant among habitat types. A one-way analysis of variance of Shannon-Weaver values found no significant differences among habitat types (p greater than or equal to0.05). Regional diversity mainly resulted from high beta values which appears to be primarily a function of the moisture gradient. The other factors influencing compositional differences among sites are variation in site history, especially disturbance, with niche partitioning and differences in seed dispersal capacity having a minor influence. The affinity analysis method indicated that sampling once per season is inadequate, and that many types of sites are modal. This method for estimating gamma (landscape) diversity shows considerable promise, but information on the processes that produce outlier sites is needed to fully understand and use the results of this method.://000167389900005 ISI Document Delivery No.: 409NN Times Cited: 4 Cited Reference Count: 56 Cited References: ADAMS DE, 1980, AM J BOT, V67, P381 ALATALO RV, 1981, OIKOS, V37, P199 ANGERMEIER PL, 1998, ECOLOGY, V79, P911 AUCLAIR AN, 1971, AM NAT, V105, P499 BAKKEN PN, 1995, THESIS U WISCONSIN S BAKKEN PN, 1998, NO J APPL FOR, V15, P116 BEATTY SW, 1984, ECOLOGY, V65, P1406 BENAYAS JMR, 1995, J VEG SCI, V6, P95 BONHAM CD, 1989, MEASUREMENTS TERREST CALEY MJ, 1997, ECOLOGY, V78, P70 CANFIELD RH, 1941, J FOREST, V39, P388 COOK JE, 1996, FOREST SCI, V42, P67 CORNELL HV, 1993, SPECIES DIVERSITY EC, P243 CROZIER CR, 1984, OECOLOGIA, V62, P337 CURTIS JT, 1959, VEGETATION WISCONSIN DZWONKO Z, 1989, OIKOS, V56, P77 FASSNACHT KS, 1998, NJ APPL FOR, V15, P69 FRELICH LE, 1995, NAT AREA J, V15, P157 GOEBEL PC, 1999, NAT AREA J, V19, P12 GRAUMLICH LJ, 1993, ECOLOGY, V74, P826 GRUMBINE RE, 1994, CONSERV BIOL, V8, P27 HOEHENE LM, 1981, FOREST ISLAND DYNAMI, P42 HOLE FD, 1976, SOILS WISCINSON HUEBNER CD, 1995, AM MIDL NAT, V134, P155 HURLBERT SH, 1971, ECOLOGY, V52, P577 KOTAR J, 1988, FIELD GUIDE FOREST H LEVENSON JB, 1980, 3 CENTR HARDW C P, P219 MAGURRAN AE, 1988, ECOLOGICAL DIVERSITY MATLACK GR, 1994, ECOLOGY, V75, P1491 MCCLENAHEN JR, 1995, 10 CENTR HARDW C P, P60 MCCUNE B, 1981, ECOLOGY, V62, P1196 METZGER F, 1981, AM MIDL NAT, V105, P44 MULLER RN, 1978, ECOL MONOGR, V48, P1 NOSS RF, 1983, BIOSCIENCE, V33, P700 PEET RK, 1974, ANNU REV ECOL SYST, V5, P285 PELOQUIN RL, 1999, NAT AREA J, V19, P121 RAUSCHER HM, 1984, NC240 USDA FOR SERV REY BJM, 1993, J VEG SCI, V4, P103 RICKLEFS RE, 1993, EC NATURE ROGERS RS, 1978, CAN J BOT, V56, P843 ROGERS RS, 1980, ECOLOGY, V61, P178 ROGERS RS, 1981, ECOLOGY, V62, P1634 SCHEINER SM, 1992, ECOLOGY, V73, P1860 SCHEINER SM, 1994, CAN J BOT, V72, P217 SCHEINER SM, 1994, EVOL ECOL, V8, P331 SCHMIDT TL, 1997, USDA FOREST SERVICE SPENCER JS, 1988, USDA FOREST SERVICE STEARNS F, 1986, P NO HARDW RES MAN P, P51 SWEENEY BA, 1996, THESIS U WISCONSIN S TILMAN D, 1985, AM NAT, V125, P827 TILMAN D, 1993, SPECIES DIVERSITY EC, P13 WALTERS MB, 1997, CAN J FOREST RES, V27, P237 WHITNEY GG, 1988, J ECOL, V76, P867 WILSON MV, 1984, J ECOL, V72, P1055 WOODS KD, 1989, ECOLOGY, V70, P681 WOODS KD, 1993, AM MIDL NAT, V130, P62 0921-2973 Landsc. Ecol.ISI:000167389900005Univ Wisconsin, Coll Nat Resources, Stevens Point, WI 54481 USA. Cook, JE, Univ Wisconsin, Coll Nat Resources, Stevens Point, WI 54481 USA.English }? Sweeney, S. Jurek, M. Bednar, M.2007aUsing place names to interpret former floodplain connectivity in the Morava River, Czech Republic 1007-1018Landscape Ecology227Aug://000248381900004 0921-2973ISI:000248381900004<7Swenson, J. J. Franklin, J.2000^The effects of future urban development on habitat fragmentation in the Santa Monica Mountains713-730Landscape Ecology158coastal sage scrub habitat fragmentation landscape pattern indices land use change simulation modeling Santa Monica Mountains LAND-USE FOREST LANDSCAPE SPATIAL PATTERN DYNAMICS MODEL BIODIVERSITY WILDLIFE INDEXES OREGON AREASArticleDec}A site suitability model of urban development was created for the Santa Monica Mountains in southern California, USA, to project to what degree future development might fragment the natural habitat. The purpose was to help prioritize land acquisition for the Santa Monica Mountains National Recreation Area and examine to what extent projected urban development would affect distinct vegetation classes. The model included both environmental constraints (slope angle), and spatial factors related to urban planning (proximity to roads and existing development, proposed development, and areas zoned for development). It implemented a stochastic component; areas projected to have high development potential in the suitability model were randomly selected for development. Ownership tracts were used as the spatial unit of development in order to give the model spatial realism and not arbitrarily `develop' grid cells. Using different assumptions and parameters, the model projected the pattern of development from similar to5 to similar to 25 years hence (based on recent development rates in the area). While < 25% of the remaining natural landscape is removed under these scenarios, up to 30% of core (interior) habitat area is lost and edge length between natural vegetation and development increases as much as 45%. Measures of landscape shape complexity increased with area developed and number of patches of natural habitat increased four- to nine-fold, depending upon model parameters. This increase in fragmentation occurs because of the existing patterns of land ownership, where private ('developable') land is interspersed with preserved park lands.://000165379700003 ISI Document Delivery No.: 375BM Times Cited: 23 Cited Reference Count: 79 Cited References: *ENV SYST RES I, 1991, ARC INF VERS 6 0 GEO *LOS ANG COUNT, 1981, MAL SANT MON MOUNT I *NAT PARK SERV, 1984, LAND PROT PLAN *NAT PARK SERV, 1987, LAND PROT PLAN *NAT PARK SERV, 1991, LAND PROT PLAN *NAT PARK SERV, 1993, DRAFT RES MAN PLAN *NAT PARK SERV, 1994, NAT RES RES PROSP ALBERTS AC, 1993, INTERFACE ECOLOGY LA, P103 BAKER WL, 1989, LANDSCAPE ECOL, V2, P111 BEIER P, 1993, CONSERV BIOL, V7, P94 CHURCH RL, 1996, BIOL CONSERV, V76, P106 DALE VH, 1993, PHOTOGRAMM ENG REM S, V59, P997 DOBSON AP, 1997, SCIENCE, V275, P550 FRANKLIN J, 1997, SCALE REMOTE SENSING, P141 FRANKLIN J, 1997, UNPUB TECHNICAL REPO FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 FRANKLIN JF, 1993, ECOL APPL, V3, P202 GOPAL S, 1994, PHOTOGRAMM ENG REM S, V60, P181 GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 HAINESYOUNG R, 1996, PROG PHYS GEOG, V20, P418 HOPKINS LD, 1977, J AM I PLANNERS, V43, P386 HUDSON W, 1991, LANDSCAPE LINKAGES B HUNSAKER CT, 1993, ENV MODELING GIS, P248 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 KAIN JF, 1986, HDB REGIONAL URBAN E, V2 KAMRANT D, 1995, THESIS CALIFORNIA ST KEELEY JE, 1988, N AM TERRESTRIAL VEG, P165 LAGRO JA, 1992, LANDSCAPE ECOL, V7, P275 LANDIS JD, 1994, ENVIRON PLANN B, V21, P399 LI H, 1993, LANDSCAPE ECOL, V8, P63 MARGULES C, 1981, BIOL CONSERV, V21, P79 MARKMAN M, 1994, SEMIN ONCOL, V21, P1 MCGARIGAL K, 1994, FRAGSTATS SPAT PATT MLADENOFF DJ, 1993, ECOL APPL, V3, P294 MOONEY HA, 1977, TERRESTRIAL VEGETATI, P471 MOSER WA, 1991, J URBAN PLAN D-ASCE, V117, P85 MURPHY DD, 1988, BIODIVERSITY, P71 NOSS RF, 1983, BIOSCIENCE, V33, P700 NOSS RF, 1990, CONSERV BIOL, V4, P355 OLEARY JF, 1992, 2 CAL DEP FISH GAM C OLEARY JF, 1994, CALIFORNIA WILDLIFE, V10 OLEARY JF, 1995, SPECIAL PUBLICATION, V3, P24 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PAVLIK BM, 1992, OAKS CALIFORNIA PLANTRICH RF, 1990, EXAMPLES RESOURCE IN, P49 PUTNAM SH, 1983, INTEGRATED URBAN MOD QUINN RD, 1990, PSW202 USDA FOR SERV RIPPLE WJ, 1991, BIOL CONSERV, V57, P73 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SAWYER JO, 1995, MANUAL CALIFORNIA VE SCHOENHERR AA, 1990, SPECIAL PUBLICATION, V3 SKLAR FH, 1991, QUANTITATIVE METHODS, P239 SOULE ME, 1988, CONSERV BIOL, V2, P75 SOULE ME, 1991, J AM PLANN ASSOC, V57, P313 SOULE ME, 1991, LANDSCAPE LINKAGES B, P91 SOULE ME, 1992, OIKOS, V63, P39 SPIES TA, 1994, ECOL APPL, V4, P555 SPIES TA, 1999, CLAMS COASTAL LANDSC STEINITZ C, 1998, ALTERNATIVES FUTURES STOMS DM, 1998, NAT AREA J, V18, P338 SWENSON J, 1995, THESIS SAN DIEGO STA THEOBALD DM, 1998, GEOGRAPHICAL ENV MOD, V2, P65 TOMLIN CD, 1991, GEOGRAPHIC INFORMATI TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1991, QUANTITATIVE METHODS TURNER MG, 1991, QUANTITATIVE METHODS, P323 TURNER MG, 1996, ECOL APPL, V6, P1150 USHER MB, 1987, NATURE CONSERVATION, P103 WEAR DN, 1996, ECOL APPL, V6, P1173 WESTMAN WE, 1981, ECOLOGY, V62, P439 WHITLEY DL, 1993, GIS WORLD, V6, P48 WICKHAM JD, 1997, PHOTOGRAMM ENG REM S, V63, P397 WILCOVE DS, 1986, CONSERVATION BIOL SC, P237 WILCOX BA, 1984, NATL PARKS CONSERVAT, P639 WILCOX BA, 1985, AM NAT, V125, P879 WILKIE DS, 1988, ECOL MODEL, V41, P307 WILSON AG, 1974, URBAN REGIONAL MODEL WOODCOCK CE, 1994, REMOTE SENS ENVIRON, V50, P240 ZINK TA, 1995, RESTOR ECOL, V3, P304 0921-2973 Landsc. Ecol.ISI:000165379700003San Diego State Univ, Dept Geog, San Diego, CA 92182 USA. Swenson, JJ, Oregon State Univ, Dept Forest Sci, Peavy Hall 154, Corvallis, OR 97331 USA.English @}?)Syphard, A. D. Clarke, K. C. Franklin, J.2007YSimulating fire frequency and urban growth in southern California coastal shrublands, USA431-445Landscape Ecology223chaparral; coastal sage scrub; exotic grass; fire; LANDIS; landscape model; model coupling; urban growth model; wildland urban interface CELLULAR-AUTOMATON MODEL; LANDSCAPE PATTERNS; SAN-FRANCISCO; REGIMES; IMPACTS; DISTURBANCE; SUCCESSION Mar?Fire is an important natural disturbance in the Mediterranean-climate coastal shrublands of southern California. However, anthropogenic ignitions have increased fire frequency to the point that it threatens the persistence of some shrub species and favors the expansion of exotic annual grasses. Because human settlement is a primary driver of increased ignitions, we integrated a landscape model of disturbance and succession (LANDIS) with an urban growth model (UGM) to simulate the combined effects of urban development and high fire frequency on the distribution of coastal shrublands. We tested whether urban development would contribute to an expansion of the wildland-urban interface (WUI) and/or change in average fire return intervals and compared the relative impacts of direct habitat loss and altered fire regimes on functional vegetation types. We also evaluated two methods of integrating the simulation models. The development pattern predicted by the UGM was predominantly aggregated, which minimized the expansion of the WUI and increase in fire frequency, suggesting that fire risk may be higher at intermediate levels of urbanization due to the spatial arrangement of ignition sources and fuel. The comparison of model coupling methods illustrated how cumulative effects of repeated fires may occur gradually as urban development expands across the landscape. Coastal sage scrub species and resprouting chaparral were more susceptible to direct habitat loss, but increased fire frequency was more of a concern to obligate seeder species that germinate from a persistent seed bank. Simulating different scenarios of fire frequency and urban growth within one modeling framework can help managers locate areas of highest risk and determine which vegetation types are most vulnerable to direct habitat loss, altered fire regimes, or both. ://000244455200008 0921-2973ISI:000244455200008<7N Szacki, J.1999\Spatially structured populations: how much do they match the classic metapopulation concept?369-379Landscape Ecology144dispersal landscape long range movements metapopulation small mammals SMALL MAMMALS PATCHY ENVIRONMENTS LANDSCAPE MOVEMENTS CONSERVATION MICROTUS HABITATS RODENT PALLAS FIELDArticleAugIn the classic metapopulation concept a specific range of animal movements is assumed, not too large and not too small. Thus, knowledge of animal mobility is necessary to determine the degree to which a given population matches a specific metapopulation model. It seems that usually small mammal mobility is underestimated, and this has important consequences for the way we view metapopulation dynamics. Data on small mammal movements (Clethrionomys glareolus and Apodemus flavicollis) are presented in this paper. The material was collected in a two year study in western Poland using a set of six woodlots of different sizes and degree of isolation, located among agricultural fields. Various methods were used in the study: colored bait, live-trapping, and radio-telemetry. It is suggested that the populations under study match the concept of patchy population (sensu Harrison 1991), being poorly isolated in individual patches and with the range of animal movements encompassing the whole set of patches. Moreover, the use of patches changes between seasons according to changing needs and/or resource abundance in the woodlots. Density and composition of local populations may be influenced both by the patch area and its isolation, and also by the filtering effect of the matrix that depends on the season. In this context it is pointed out that more attention should be paid to the matrix, both in research practice and conservation as it is a factor influencing population functioning in quantitative and qualitative ways. It is suggested that any generalizations about population spatial organization may be impossible without more detailed knowledge of long distance movements of focal animals and their use of matrix.://000081305700005 ISI Document Delivery No.: 214AP Times Cited: 19 Cited Reference Count: 42 Cited References: ABERG J, 1995, OECOLOGIA, V103, P265 ANDRZEJEWSKI R, 1999, IN PRESS ACTA THERIO DANIELSON BJ, 1992, EVOL ECOL, V6, P399 DICKMAN CR, 1995, J ARID ENVIRON, V31, P441 DIFFENDORFER JE, 1995, ECOLOGY, V76, P827 DJAWDAN M, 1988, J MAMMAL, V69, P765 DUNNING JB, 1992, OIKOS, V65, P169 FAHRIG L, 1994, CONSERV BIOL, V8, P50 GOTTFRIED BM, 1979, AM MIDL NAT, V102, P105 GOTTFRIED BM, 1982, CAN J ZOOL, V60, P1660 GURNELL J, 1989, J ZOOL, V217, P241 HANSKI IA, 1997, METAPOPULATION BIOL HANSSON L, 1987, HOLARCTIC ECOL, V10, P154 HARRISON S, 1991, BIOL J LINN SOC, V42, P73 HENDERSON MT, 1985, BIOL CONSERV, V31, P95 HOLISOVA V, 1968, SMALL MAMMALS NEWSLE, V2, P36 KNIGHT TW, 1996, ECOLOGY, V77, P1756 KOTLIAR NB, 1990, OIKOS, V59, P253 KOZAKIEWICZ M, 1989, HOLARCTIC ECOL, V12, P106 KOZAKIEWICZ M, 1993, LANDSCAPE ECOL, V8, P19 KOZAKIEWICZ M, 1994, POLISH ECOLOGICAL ST, V20, P209 KOZAKIEWICZ M, 1995, LANDSCAPE APPROACHES, P78 LEVINS R, 1970, SOME MATH PROBLEMS B, P75 LIDICKER WZ, 1987, MAMMALIAN DISPERSAL, P144 LIDICKER WZ, 1996, METAPOPULATIONS WILD, P85 LIDICKER WZ, 1998, IN PRESS LANDSCAPE E LIRO A, 1987, OECOLOGIA, V74, P438 MERRIAM G, 1988, TRENDS ECOL EVOL, V3, P16 MIDDLETON J, 1981, J APPL ECOL, V18, P703 PICKETT STA, 1978, BIOL CONSERV, V13, P27 PRICE MV, 1994, J MAMMAL, V75, P929 ROBINSON WL, 1965, AM MIDL NAT, V73, P188 SHEPPE W, 1967, AM MIDL NAT, V78, P471 SOMSOOK S, 1991, Z SAUGETIERKD, V56, P200 SZACKI J, 1991, LANDSCAPE ECOL, V5, P219 SZACKI J, 1993, ACTA THERIOL, V38, P113 TAYLOR PD, 1993, OIKOS, V68, P571 TEW T, 1988, P 2 INT BEH EC C VAN, P103 WEGNER J, 1990, BIOL CONSERV, V54, P263 WELLS JV, 1995, WILDLIFE SOC B, V23, P458 WIENS JA, 1976, ANNU REV ECOL SYST, V7, P81 WIENS JA, 1997, METAPOPULATION BIOL, P43 0921-2973 Landsc. Ecol.ISI:0000813057000059Szacki, J, Mandarynki St 10,M25, PL-02796 Warsaw, Poland.English<?8Jakub Szacki Anna Liro19919Movements of small mammals in the heterogeneous landscape219-224Landscape Ecology54Distances and directions of Apodemus agrarius and Clethrionomus glareolus movements were studied using snap traps and colored bait. The longest distances traversed exceeded 1500 m. Some directions of movement were significantly more common. High variability in the number of captures along traplines suggests distinct movement routes. Small mammals appear to base their movement on the landscape and not on individual biotopes.M?.j7Eric Tabacchi Anne-Marie Planty-Tabacchi Odile Decamps1990PContinuity and discontinuity of the riparian vegetation along a fluvial corridor9-20Landscape Ecology511riparian vegetation, river continuum, connectanceThe concept of continuity/discontinuity is applied to the riparian vegetation of the corridor of the River Adour (S.W. France), in order to precisely define longitudinal structure, and to test the degree of floristic continuity of the fluvial axis. The measure of floristic connectance along the river course is based on presence/absence data, and is applied to successive stretches of the river, at various resolution levels. This analysis shows that the River Adour corridor cannot be assumed to be floristically continuous. The observed discontinuities may correspond to two types of change in the riparian vegetation: zones of slow change (high level of floristic connectance) or zones of sharp change (low level of floristic connectance). <7Taft, O. W. Haig, S. M.2006[Importance of wetland landscape structure to shorebirds wintering in an agricultural valley169-184Landscape Ecology2125Dunlin (Calidris alpina); habitat use; Killdeer (Charadrius vociferus); landscape context; landscape planning; Oregon; wetland conservation; Willamette Valley FRANCISCO BAY ESTUARY; MOVEMENT PATTERNS; HABITAT PREFERENCES; WESTERN SANDPIPERS; WILLAMETTE-VALLEY; CONSERVATION; BIRDS; POPULATIONS; OREGON; REGIONArticleFebOnly recently has the influence of landscape structure on habitat use been a research focus in wetland systems. During non-breeding periods when food can be locally limited, wetland spatial pattern across a landscape may be of great importance in determining wetland use. We studied the influence of landscape structure on abundances of wintering Dunlin (Calidris alpina) and Killdeer (Charadrius vociferus) observed on wetlands in the agricultural Willamette Valley of Oregon, USA, during two winters (1999-2000, 2000-2001) of differing rainfall. We examined (1) shorebird use within a sample of 100 km(2) regions differing in landscape structure (hectares of shorebird habitat [wet, unvegetated]) and (2) use of sites differing in landscape context (area of shorebird habitat within a species-defined radius). For use of sites, we also assessed the influence of two local characteristics: percent of soil exposed and area of wet habitat. We analyzed data using linear regression and information-theoretic modeling. During the dry winter (2000-2001), Dunlin were attracted to regions with more wetland habitat and their abundances at sites increased with greater area of shorebird habitat within both the site and the surrounding landscape. In contrast, Dunlin abundances at sites were related to availability of habitat at only a local scale during the wet winter (1999-2000). Regional habitat availability was of little importance in predicting Killdeer distributions, and Killdeer site use appeared unrelated to habitat distributions at both landscape and local scales. Results suggest prioritizing sites for conservation that are located in areas with high wetland coverage.://000235866400002  ISI Document Delivery No.: 019WC Times Cited: 0 Cited Reference Count: 56 Cited References: *SAS I INC, 1999, SAS SYST WIND VERS 8 BENNER PA, 1997, RIVER QUALITY DYNAMI, P23 BEST LB, 2001, J WILDLIFE MANAGE, V65, P442 BURNHAM KP, 2002, MODEL SELECTION MULT CALME S, 2000, J BIOGEOGR, V27, P725 CASTRO G, 1989, AUK, V106, P474 CLARKE SE, 1991, ENVIRON MANAGE, V15, P847 COHEN J, 1988, STAT POWER ANAL BEHA CONNORS PG, 1981, AUK, V98, P49 COWARDIN LM, 1979, CLASSIFICATION WETLA DAGGETT SG, 1998, WETLAND LAND USE CHA DUNNING JB, 1992, OIKOS, V65, P169 ELPHICK CS, 1998, THESIS U NEVADA RENO ELPHICK CS, 2003, AGR ECOSYST ENVIRON, V94, P17 EVANS PR, 1976, ARDEA, V64, P117 FAIRBAIRN SE, 2001, WETLANDS, V21, P41 FARMER AH, 1997, CONDOR, V99, P698 GOSSCUSTARD JD, 1977, J APPL ECOL, V14, P701 HAIG SM, 1998, CONSERV BIOL, V12, P749 HULSE D, 2002, WILLAMETTE RIVER BAS JACKSON BJS, 2000, BIRDS N AM, V517 JACKSON PL, 1993, ATLAS PACIFIC NW KERSTEN M, 1987, ARDEA, V75, P175 KOTLIAR NB, 1990, OIKOS, V59, P253 KOZAKIEWICZ M, 1995, MOSAIC LANDSCAPES EC, P136 LITTELL RC, 1996, SAS SYSTEM MIXED MOD LOVVORN JR, 1996, BIOL CONSERV, V77, P97 MILSOM TP, 1998, BIOL CONSERV, V84, P119 MILSOM TP, 2000, J APPL ECOL, V37, P706 MYERS JP, 1983, AM BIRDS, V37, P23 NAUGLE DE, 1999, LANDSCAPE ECOL, V14, P267 NAUGLE DE, 2000, J WILDLIFE MANAGE, V64, P253 ORMEROD SJ, 2000, J APPL ECOL, V37, P699 PYKE GH, 1983, ECOLOGY ANIMAL MOVEM, P7 RAMSEY FL, 1997, STAT SLEUTH COURSE M RIFFELL SK, 2003, LANDSCAPE ECOL, V18, P95 ROBINSON JA, 1997, INT WADER STUDIES, V9, P37 RODWAY MS, 2003, CAN J ZOOL, V81, P492 ROSENBERG DK, 1999, J WILDLIFE MANAGE, V63, P1028 ROSHIER DA, 2001, LANDSCAPE ECOL, V16, P547 ROSHIER DA, 2002, BIOL CONSERV, V106, P399 SANZENBACHER PM, 2002, CONDOR, V104, P271 SANZENBACHER PM, 2002, WATERBIRDS, V25, P16 SKAGEN SK, 1994, WILSON BULL, V106, P91 SZEKELY T, 1992, J ANIM ECOL, V61, P447 TAFT OW, 2003, WETLANDS, V23, P51 TAFT OW, 2004, ENVIRON MANAGE, V33, P749 TAFT OW, 2004, THESIS OREGON STATE TISCHENDORF L, 2000, LANDSCAPE ECOL, V15, P633 TWEDT DJ, 1998, AM MIDL NAT, V140, P140 WARNOCK N, 1995, WILSON BULL, V107, P131 WARNOCK ND, 1996, BIRDS N AM, V203 WARNOCK SE, 1995, AUK, V112, P920 WARNOCK SE, 1996, IBIS, V138, P160 WITH KA, 1994, LANDSCAPE ECOL, V9, P25 WU JG, 2002, LANDSCAPE ECOL, V17, P355 0921-2973 Landsc. Ecol.ISI:000235866400002USGS, Forest & Rangeland Ecosyst Sci Ctr, Corvallis, OR 97331 USA. Oregon State Univ, Dept Fisheries & Wildlife, Corvallis, OR 97331 USA. Taft, OW, USGS, Forest & Rangeland Ecosyst Sci Ctr, 3200 SW Jefferson Way, Corvallis, OR 97331 USA. oriane_taft@usgs.govEnglish|?4 'Takada, T. Miyamoto, A. Hasegawa, S. F.2010_Derivation of a yearly transition probability matrix for land-use dynamics and its applications561-572Landscape Ecology254ITransition matrices have often been used in landscape ecology and GIS studies of land-use to quantitatively estimate the rate of change. When transition matrices for different observation periods are compared, the observation intervals often differ because satellite images or photographs of the research site taken at constant time intervals may not be available. If the observation intervals differ, the transition probabilities cannot be compared without calculating a transition matrix with the normalized observation interval. For such calculation, several previous studies have utilized a linear algebra formula of the power root of matrices. However, three difficulties may arise when applying this formula to a practical dataset from photographs of a research site. We examined the first difficulty, namely that plural solutions could exist for a yearly transition matrix, which implies that there could be multiple scenarios for the same transition in land-use change. Using data for the Abukuma Mountains in Japan and the Selva el Ocote Biosphere Reserve in Mexico, we then looked at the second difficulty, in which we may obtain no positive Markovian matrix and only a matrix partially consisting of negative numbers. We propose a way to calibrate a matrix with some negative transition elements and to estimate the prediction error. Finally, we discuss the third difficulty that arises when a new land-use category appears at the end of the observation period and how to solve it. We developed a computer program to calculate and calibrate the yearly matrices and to estimate the prediction error.!://WOS:000275444100006Times Cited: 0 0921-2973WOS:00027544410000610.1007/s10980-009-9433-x?Kazuhiko Takeuchi Dong-Kun Lee1989RA framework for environmental management planning -A landscape-ecological approach53-63Landscape Ecology31environmental management planning, environmental resources, environmental data base, environmental indices, environmental modeling, process-oriented planning, landscape ecologyFramework, concepts, and methods of Environmental Management Planning (EMP) are discussed. A landscape- ecological approach was taken to integrate the environmental indices. EMP focuses on regional factors - natural, social, amenity related - and becomes more sensitive as the scale of study increases. The processes of EMP include a vertical aspect, dealing with pollution, conservation, and amenities, and a more general horizontal component which involves zoning and land use planning. Environmental impacts may be assessed by modeling exercises using all available data and considering all land use options. To keep up with the rapid change of environment and its perception, EMP should be process-oriented rather than purpose-oriented. The concepts of EMP were applied to the middle basin of the Tamagawa River and it was shown that multivariate analysis is useful for the regional subdivision and environmental modeling. 2<7 #Taki, H. Kevan, P. G. Ascher, J. S.20078Landscape effects of forest loss in a pollination system 1575-1587Landscape Ecology2210apiformes apoidea carolinian forest forested ecosystem fragmentation habitat loss spring ephemeral PLANT REPRODUCTIVE SUCCESS HABITAT FRAGMENTATION ERYTHRONIUM-AMERICANUM SEED SET POPULATION-SIZE DRY FOREST LYTHRUM-SALICARIA BEES HYMENOPTERA COSTA-RICA FRUIT-SETArticleDec+Forest loss has been invoked as a cause for changes in the reproductive success of animal-pollinated woodland plants, associated with changes in their pollinators. To analyze such effects, it is important to include all of the three key players: landscapes, pollinators and a plant. We investigated effects of forest loss on an insect-pollinated plant through landscapes in forested ecosystems to pollinator communities and plant populations. Then we questioned if abundance and species richness in pollinator communities decrease as forest loss increases, and this in turn leads to a decrease in reproductive output of an insect-pollinated plant. We made a study with 12 populations of the bee pollinated herb, Erythronium americanum, in a landscape characterized by scattered fragments of deciduous forest within intensively managed agricultural fields. We also sampled bees as the potential pollinators by pan traps. We quantified the study landscapes using the amount of forest cover and the length of forest edge within each of the six radii (250, 500, 750, 1,000, 1,250 and 1,500 m). Regression analyses showed that the abundance and species richness of all collected bees were positively related to only the forest cover at the radius of 750 m. We also found the positive relationships for the seed set of E. americanum when the forest cover at the same radius and abundance of all collected bees were used as the predictor variables. These results indicate that forest loss causes negative impacts on potential pollinator communities and seed sets of some woodland herbs.://000250632100015xISI Document Delivery No.: 227BL Times Cited: 0 Cited Reference Count: 66 Taki, Hisatomo Kevan, Peter G. Ascher, John S. 0921-2973 Landsc. Ecol.ISI:000250632100015tForestry & Forest Prod Res Inst, Dept Forest Entomol, Tsukuba, Ibaraki 305, Japan. Univ Guelph, Dept Environm Biol, Guelph, ON N1G 2W1, Canada. Amer Museum Nat Hist, Div Invertebrate Zool, New York, NY 10024 USA. Taki, H, Forestry & Forest Prod Res Inst, Dept Forest Entomol, 1 Matsunosato, Tsukuba, Ibaraki 305, Japan. pkevan@uoguelph.ca htaki@affrc.go.jp ascher@amnh.orgEnglish|?Talluto, M. V. Suding, K. N.2008sHistorical change in coastal sage scrub in southern California, USA in relation to fire frequency and air pollution803-815Landscape Ecology237sInvasions resulting in the transformation of one ecosystem to another are an increasingly widespread phenomenon. While it is clear that these conversions, particularly between grassland and shrubland systems, have severe consequences, it is often less clear which factors are associated with these conversions. We resampled plots from the 1930s (Weislander VTMs) to test whether two widely assumed factors, changes in fire frequency and nitrogen deposition, are associated with the conversion of coastal sage scrublands to exotic grasslands in southern California. Over the 76-year period, coastal sage scrub cover declined by 49%, being replaced predominantly by exotic grassland species. Grassland encroachment was positively correlated with increased fire frequency and, in areas with low fire frequencies, air pollution (percent fossil carbon as indicated by partial derivative C-14, likely correlated with nitrogen deposition). We conclude that increases in fire frequency and air pollution over the last several decades in southern California may have facilitated the conversion of coastal sage shrubland to exotic grassland systems.!://WOS:000258540300004Times Cited: 0 0921-2973WOS:00025854030000410.1007/s10980-008-9238-3S<7=-Tang, S. M. Franklin, J. F. Montgomery, D. R.1997;Forest harvest patterns and landscape disturbance processes349-363Landscape Ecology126GIS; simulation models; landscape pattern; debris flows; wind damage; forest harvesting; Washington State; USA MODEL; OREGON; COMMUNITIES; LANDSLIDES; EXPRESSION; DRAINAGE; EROSIONArticleDecA physically-based model of the topographic influence on debris flow initiation and a rule-based model for wind damage were used to assess the influence of forest clearcutting patterns (i.e., location, size, shape and distribution of cut units) on the potential for landscape disturbance by these processes in Charley Creek watershed, Washington State, USA. Simulated clearcutting patterns consisted of 7, 9 or 26 ha square or rectangular harvest units distributed in either an aggregated or dispersed pattern under three stream-buffering scenarios. The slope-stability model predicted that potentially unstable ground is concentrated along steep headwater streams and inner-gorge side-slopes. Areas susceptible to wind damage were determined from the combination of slope, aspect, elevation, soil drainage and primary tree species. Among the variables examined here, the location of harvest units constitutes the most important factor influencing the potential for shallow landsliding. In contrast, the location, size, and shape of clearcuts and the interactions among these three factors significantly influenced the potential for wind damage. Minimal correspondence between areas predicted to be potentially unstable and areas susceptible to wind damage implies that harvest patterns designed to mitigate the potential for shallow landsliding may not necessarily reduce the potential for wind damage. Our results demonstrate that: (1) the location of timber harvesting is more important than the geometry of harvest activity in influencing shallow landsliding; (2) forest harvest patterns strongly influence the potential for disturbance processes; and (3) a single cutting pattern will often fail to meet all landscape management goals.://000077684400001 !ISI Document Delivery No.: 150UR Times Cited: 11 Cited Reference Count: 85 Cited References: *AT T, 1991, S PLUS VERS 3 0 REL *CLALL RIV LANDSC, 1994, FIN REV DRAFT *ESRI, 1992, ARC VERS 6 1 2 *FEMAT, 1993, FOR EC MAN EC EC SOC *SAT, 1993, VIAB ASS MAN CONS SP *SPSFP, 1995, 5 CORT CONS *SYSTAT INC, 1992, SYSTAT VERS 5 0 WIND *WAC, 1990, FOR PRACT BOARD, CH222 *WFPB, 1993, WASHINGTON FOREST PR, M1 AHRENS DC, 1988, METEOROLOGY TODAY IN ALEXANDER RR, 1964, FOREST SCI, V10, P130 BABCOCK RS, 1994, WASHINGTON DIVISION, V80, P141 BOYCE JS, 1929, USDA TECHNICAL B, V104 CAINE N, 1980, GEOGR ANN A, V62, P23 CEDERHOLM CJ, 1974, FRIUW7404 U WASH FIS CISSEL J, 1990, COPE RES, V3, P8 COFFMAN DM, 1972, WATER RESOUR RES, V8, P1497 CONNELLY BA, 1992, THESIS U WASHINGTON COOPER WS, 1926, ECOLOGY, V7, P391 DETENBECK NE, 1992, ENVIRON MANAGE, V16, P33 DIETRICH WE, 1978, Z GEOMORPHOLOGIE S, V29, P191 DIETRICH WE, 1993, J GEOL, V101, P259 DIETRICH WE, 1995, HYDROL PROCESS, V9, P383 DYRNESS CT, 1969, PNW111 USDA FOR SERV FOSTER DR, 1992, J ECOL, V80, P79 FRANKLIN JF, 1987, LANDSCAPE ECOL, V1, P19 FRANKLIN JF, 1989, AM FOR, V95, P1 FRANKLIN JF, 1992, WATERSHED MANAGEMENT, P25 FRANKS RR, 1988, GENE DEV, V2, P1 FURNISS MJ, 1991, INFLUENCES FOREST RA, P297 GLOYNE RW, 1968, STRUCTURE WIND ITS R, P7 GRANT G, 1990, FORESTS WILD MANAGED, P35 GRATKOWSKI HJ, 1956, FOREST SCI, V2, P60 GUIE HD, 1921, AM FOR, V27, P379 GUSTAFSON EJ, 1996, J ENVIRON MANAGE, V46, P77 HALLOIN LJ, 1987, SOIL SURVEY CLALLAM HANSEN AJ, 1995, ECOL APPL, V5, P535 HEMSTROM M, 1990, COPE REPORT, V3, P8 HEMSTROM M, 1990, FORESTS WILD MANAGED, P27 HENDERSON JA, 1989, 00188 R6ECOLTP USDA HUPP CR, 1983, CASTANEA, V48, P89 IVERSON LR, 1988, LANDSCAPE ECOLOGY, V2, P45 JOHNSON KN, 1991, ALTERNATIVES MANAGEM JONES EW, 1945, NEW PHYTOL, V44, P130 JONES JA, 1996, WATER RESOUR RES, V32, P959 MEGAHAN WF, 1972, J FOREST, V70, P135 MEGAHAN WF, 1983, WATER RESOUR RES, V19, P811 MITCHELL SJ, 1995, FOREST CHRON, V71, P446 MONTGOMERY DR, 1993, WATER RESOUR RES, V29, P3925 MONTGOMERY DR, 1994, WATER RESOUR RES, V30, P1153 MONTGOMERY DR, 1994, WATER RESOUR RES, V30, P1925 MORISAWA ME, 1957, EOS T AM GEOPH U, V38, P86 ONEILL RV, 1992, LANDSCAPE ECOL, V7, P55 PHILLIPS EL, 1972, WASHINGTON CLIMATE T PICKETT STA, 1985, ECOLOGY NATURAL DIST, P371 PICKETT STA, 1989, OIKOS, V54, P129 RUTH RH, 1953, 7 USDA FOR SERV PAC RUTH RH, 1979, PNW88 USDA FOR SERV SAUER JD, 1962, J ECOL, V50, P275 SCHAETZL RJ, 1989, CAN J FOREST RES, V19, P1 SCHLICHTE K, 1991, AERIAL PHOTO INTERPR SCHROEDER WL, 1983, FOREST SCI, V29, P823 SELBY MJ, 1993, HILLSLOPE MAT PROCES SIDLE RC, 1985, AM GEOPHYSICAL UNION, V11 SILEN RC, 1955, TIMBERMAN, V56, P82 SOUSA WP, 1984, ANNU REV ECOL SYST, V15, P353 STATHERS RJ, 1994, 9401 BRIT COL MIN FO SWANSON FJ, 1975, GEOLOGY, V3, P393 SWANSON FJ, 1988, BIOSCIENCE, V38, P92 SWANSTON DN, 1971, FOREST LAND USES STR, P29 SWANSTON DN, 1976, GEOMORPHOLOGY ENG, P199 TANG SM, 1991, THESIS MICHIGAN STAT TANG SM, 1995, ENVIRON MANAGE, V19, P741 TANG SM, 1995, THESIS U WASHINGTON TURNER MG, 1987, LANDSCAPE HETEROGENE, P85 TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 TURNER MG, 1989, OIKOS, V55, P121 TURNER MG, 1994, LANDSCAPE ECOL, V9, P59 VEBLEN TT, 1994, J ECOL, V82, P125 WALLIN DO, 1994, ECOL APPL, V4, P569 WATT AS, 1947, J ECOL, V35, P1 WEBB LJ, 1958, AUST J BOT, V6, P220 WHITE PS, 1979, BOT REV, V45, P229 ZAR JH, 1984, BIOSTATISCAL ANAL ZIEMER RR, 1981, J HYDROL NZ, V20, P8 0921-2973 Landsc. Ecol.ISI:000077684400001Bethel Coll, Dept Biol Sci, St Paul, MN 55112 USA. Tang, SM, Bethel Coll, Dept Biol Sci, 3900 Bethel Dr, St Paul, MN 55112 USA. sm-tang@bethel.eduEnglish|7%Tang, W. Malanson, G. P. Entwisle, B.2009`Simulated village locations in Thailand: a multi-scale model including a neural network approach557-575Landscape Ecology244settlement models nonlinearity neural networks village niche thailand land-use change settlement formation niche construction cellular-automata rural settlement costa-rica dynamics patterns time complexityAprThe simulation of rural land use systems in general, and rural settlement dynamics in particular, has developed with synergies of theory and methods for decades. Three current issues are: linking spatial patterns and processes, representing hierarchical relations across scales, and considering nonlinearity to address complex non-stationary settlement dynamics. We present a hierarchical simulation model to investigate complex rural settlement dynamics in Nang Rong, Thailand. This simulation uses sub-models to allocate new villages at three spatial scales. Regional and sub-regional models, which involve a nonlinear space-time autoregressive model implemented in a neural network approach, determine the number of new villages to be established. A dynamic village niche model, establishing a pattern-process link, was designed to enable the allocation of villages into specific locations. Spatiotemporal variability in model performance indicates that the pattern of village location changes as a settlement frontier advances from rice-growing lowlands to higher elevations. Simulation experiments demonstrate that this simulation model can enhance our understanding of settlement development in Nang Rong and thus gain insight into complex land use systems in this area.://000263898100010-414XI Times Cited:0 Cited References Count:86 0921-2973ISI:000263898100010Tang, W Univ Illinois, Dept Geog, Urbana, IL 61801 USA Univ Illinois, Dept Geog, Urbana, IL 61801 USA Univ Iowa, Dept Geog, Iowa City, IA 52242 USA Univ N Carolina, Dept Sociol, Chapel Hill, NC 27599 USA Univ Illinois, Natl Ctr Supercomp Applicat, Urbana, IL 61801 USA Univ Iowa, Obermann Ctr Adv Studies, Iowa City, IA 52242 USA Univ N Carolina, Carolina Populat Ctr, Chapel Hill, NC 27599 USADoi 10.1007/S10980-009-9322-3EnglishJ<7(Taverna, K. Urban, D. L. McDonald, R. I.2005Modeling landscape vegetation pattern in response to historic land-use: a hypothesis-driven approach for the North Carolina Piedmont, USA689-702Landscape Ecology206CART; classification tree; generalized linear models; GLM; logistic regression; vegetation modeling NONPARAMETRIC APPROACH; PREDICTING VEGETATION; ECOLOGY; CLASSIFICATION; DISTRIBUTIONS; VARIABLES; TREESArticleSeprCurrent methods of vegetation analysis often assume species response to environmental gradients is homogeneously monotonic and unimodal. Such an approach can lead to unsatisfactory results, particularly when vegetation pattern is governed by compensatory relationships that yield similar outcomes for various environmental settings. In this paper we investigate the advantages of using classification tree models (CART) to test specific hypotheses of environmental variables effecting dominant vegetation pattern in the Piedmont. This method is free of distributional assumptions and is useful for data structures that contain non-linear relationships and higher-order interactions. We also compare the predictive accuracy of CART models with a parametric generalized linear model (GLM) to determine the relative strength of each predictive approach. For each method, hardwood and pine vegetation is modeled using explanatory topographic and edaphic variables selected based on historic reconstructions of patterns of land use. These include soil quality, potential soil moisture, topographic position, and slope angle. Predictive accuracy was assessed on independent validation data sets. The CART models produced the more accurate predictions, while also emphasizing alternative environmental settings for each vegetation type. For example, relic hardwood stands were found on steep slopes, highly plastic soils, or hydric bottomlands - alternatives not well captured by the homogeneous GLM. Our results illustrate the potential utility of this flexible modeling approach in capturing the heterogeneous patterns typical of many ecological datasets.://000233600700005 ISI Document Delivery No.: 988KS Times Cited: 1 Cited Reference Count: 41 Cited References: *NASIS, 2003, DIG SOIL SURV AR ATT ASHE WW, 1897, B N CAROLINA GEOLOGI, V6 BIO AMF, 1998, J VEG SCI, V9, P5 BRADY NC, 2002, NATURE PROPERTIES SO BRAUN EL, 1950, DECIDUOUS FORESTS E BREIMAN L, 1984, WADSWORTH STAT PROBA BROWN DG, 1994, J VEG SCI, V5, P641 CHAMBERS JM, 1992, STAT MODELS S WADSWO CHRISTENSEN NL, 1981, FOREST SUCCESSION CO, P230 COILE TS, 1948, B DUKE U SCH FORESTR, V13 DANIELS RB, 1999, TECHNICAL B N CAROLI, V314 DEATH G, 2000, ECOLOGY, V81, P3178 DRAPER D, 1995, J ROY STAT SOC B MET, V57, P45 FIELDING AH, 1997, ENVIRON CONSERV, V24, P38 FRANKLIN J, 1995, PROG PHYS GEOG, V19, P474 FRANKLIN J, 1998, J VEG SCI, V9, P733 GUISAN A, 2000, ECOL MODEL, V135, P147 HAND DJ, 1997, CONSTRUCTION ASSESSM HEALY RG, 1985, COMPETITION LAND AM HOSMER DW, 2000, APPL LOGISTIC REGRES KUTNER MH, 1996, APPL LINEAR STAT MOD LINNET K, 1986, CLIN CHEM, V32, P1341 MAUNZ SJ, 2002, THESIS U N CAROLINA MCDONALD RI, 2002, CASTANEA, V67, P84 MCNEMAR Q, 1947, PSYCHOMETRIKA, V12, P153 MOORE DM, 1991, ENVIRON MANAGE, V15, P59 MOORE ID, 1991, HYDROL PROCESS, V5, P3 MORISETTE JT, 1999, INT J REMOTE SENS, V20, P2703 OOSTING HJ, 1942, AM MIDL NAT, V28, P1 PARKER AJ, 1982, PHYSICAL GEOGR, V3, P160 PEET RK, 1980, VEROFF GEOBOT I ETH, V69, P14 PEET RK, 1992, PLANT SUCCESSION THE, P102 SCHNEIDER LC, 2001, AGR ECOSYST ENVIRON, V85, P83 TRIMBLE SW, 1974, MAN INDUCED SOIL ERO URBAN D, 2002, ECOSCIENCE, V9, P200 URBAN DL, 2002, ANAL ECOLOGICAL COMM, P221 VAYSSIERES MP, 2000, J VEG SCI, V11, P679 WEAR DN, 1998, ECOSYSTEMS, V1, P575 WHITE PS, 1996, E OLD GROWTH FORESTS, P178 WOLOCK DM, 1995, WATER RESOUR RES, V31, P1315 YEE TW, 1991, J VEG SCI, V2, P587 0921-2973 Landsc. Ecol.ISI:000233600700005 Univ N Carolina, Curriculum Ecol, Chapel Hill, NC 27599 USA. Duke Univ, Nicholas Sch Environm & Earth Sci, Durham, NC 27708 USA. Taverna, K, Virginia Dept Conservat & Recreat, Div Nat Heritage, 217 Governor St, Richmond, VA 23219 USA. kristin.taverna@dcr.virginia.govEnglish|? #Tavernia, Brian G. Reed, J. Michael2010sSpatial, temporal, and life history assumptions influence consistency of landscape effects on species distributions 1085-1097Landscape Ecology257Aug1Models describing relationships between landscape features and species distribution patterns often display inter-study inconsistencies. Identifying factors contributing to these inconsistencies is a vital step in clarifying the ecological importance of landscape features and synthesizing an effective knowledge base for use in conservation contexts. We examined the influence of several spatial, temporal, and life history assumptions on the outcomes of distribution versus landscape models (DLMs) relating wetland bird communities at 29 Massachusetts (USA) sites to independent urbanization, wetland, forest, and agricultural landscape gradients. We considered a bird specialization index as well as obligate and facultative species richness as response variables. Landscape gradients were quantified at 10 landscape extents (0-1000 m in 100 m increments) and three time periods (1971, 1985, 2005). Univariate models indicated that our specialization index showed: (1) the strongest response to landscape gradients at small extents (200 m); (2) a negative, threshold response to urbanization was superior to a linear fit; and (3) no evidence of time-lagged effects of landscape change. Interestingly, the form of our model (i.e. linear versus threshold) influenced the extent at which strongest effects were detected. Multivariate models relating the specialization index as well as obligate and facultative species richness to landscape gradients showed evidence of annual variability (i.e. composition, parameter estimates, and variability explained) that did not depend upon an organism's degree of specialization. Our results provide evidence that violations of common assumptions (e.g. selection of appropriate extent, lack of time-lagged effects, etc.) can impact the outcome of DLMs, which could lead to inter-study inconsistencies.!://WOS:000279592100008Times Cited: 0 0921-2973WOS:00027959210000810.1007/s10980-010-9482-1 <7Taylor, P. D. Merriam, G.1996:Habitat fragmentation and parasitism of a forest damselfly181-189Landscape Ecology113odonata; Calopteryx maculata; gregarine; heterogeneity; landscape structure CRICKETS GRYLLUS-VELETIS; PENNSYLVANICUS; ECTOPARASITES; FECUNDITY; PREDATOR; ODONATA; SCALESArticleJun9We compared populations of a forest damselfly - Calopteryx maculata - in two kinds of landscapes. In fragmented landscapes, forested foraging patches were separated from streams (where oviposition and mating occur) by up to 500 m of pasture. In non-fragmented landscapes, there was continuous forest cover adjacent to streams. The prevalence and intensity of midgut infections of a gregarine parasite were significantly lower in the fragmented landscapes than in the non-fragmented landscapes. We have shown elsewhere that in the fragmented landscapes, damselflies move over greater areas to forage than in the non-fragmented landscapes. We postulate that these movements lower the rate of encounter between damselflies and oocysts, thus lowering the prevalence and intensity of infection. The differences suggest that actual habitat fragmentation events would alter the relationship between host and parasite, but that populations of both species would persist after fragmentation. Prevalence of parasitism is related to age but we found no residual effects of size on parasitism.://A1996UX47800005 ISI Document Delivery No.: UX478 Times Cited: 8 Cited Reference Count: 31 Cited References: ABRO A, 1974, ZOOLOGICA SCRIPTA, V3, P111 ABRO A, 1976, ZOOLOGICA SCRIPTA, V5, P265 ABRO A, 1987, ODONATOLOGICA, V16, P119 ADDICOTT JF, 1987, OIKOS, V49, P340 ANHOLT BR, 1992, OIKOS, V65, P428 CHAMBERS JM, 1989, STAT MODELS S WADSWO CORBET PS, 1980, ANNU REV ENTOMOL, V25, P189 DUNNING JB, 1992, OIKOS, V65, P169 FORBES MRL, 1991, OECOLOGIA, V86, P335 FORBES MRL, 1991, OIKOS, V60, P336 FORSYTH A, 1987, BEHAV ECOL SOCIOBIOL, V21, P73 IVES AR, 1993, ECOLOGY, V74, P1929 JOHNSON C, 1962, AM MIDL NAT, V68, P242 JOHNSON C, 1973, ODONATOLOGICA, V2, P69 KAREIVA P, 1987, NATURE, V326, P388 KOTLIAR NB, 1990, OIKOS, V59, P253 KRUESS A, 1994, SCIENCE, V264, P1581 LORD JM, 1990, CONSERV BIOL, V4, P197 MARDEN JH, 1990, ANIM BEHAV, V39, P954 MCCULLAGH P, 1989, GENERALIZED LINEAR M MERRIAM HG, 1984, P 1 INT SEM METH LAN, P5 ROLAND J, 1993, OECOLOGIA, V93, P25 ROLAND J, 1995, POPULATION DYNAMICS, P195 SIEGEL JP, 1992, J MED ENTOMOL, V29, P968 TAYLOR PD, 1993, OIKOS, V68, P571 TAYLOR PD, 1995, OIKOS, V73, P43 WAAGE JK, 1972, ODONATOLOGICA, V1, P155 WEGNER J, 1990, BIOL CONSERV, V54, P263 WILKINSON L, 1990, SYSTAT SYSTEM STAT ZUK M, 1987, ECOL ENTOMOL, V12, P341 ZUK M, 1987, ECOL ENTOMOL, V12, P349 0921-2973 Landsc. Ecol.ISI:A1996UX47800005ACARLETON UNIV,OTTAWA CARLETON INST BIOL,OTTAWA,ON K1S 5B6,CANADA.English~?*Taylor, R. S. Oldland, J. M. Clarke, M. F.2008aEdge geometry influences patch-level habitat use by an edge specialist in south-eastern Australia377-389Landscape Ecology234We investigated patterns in habitat use by the noisy miner (Manorina melanocephala) along farmland-woodland edges of large patches of remnant vegetation (> 300 ha) in the highly fragmented box-ironbark woodlands and forests of central Victoria, Australia. Noisy miners exclude small birds from their territories, and are considered a significant threat to woodland bird communities in the study region. Seventeen different characteristics of edge habitat were recorded, together with the detection or non-detection of noisy miners along 129 500-m segments of patch edge. Habitat characteristics ranged from patch-level factors related to patch-edge geometry to site-level floristic factors. Backward (stepwise) logistic regression analyses were used to identify habitat characteristics that were associated with the occupancy of a site by noisy miners. After accounting for the effects of spatial autocorrelation on the occurrence of noisy miners along edges, we identified projections of remnant vegetation from the patch edge into the agricultural matrix (e.g., corners of patches, peninsulas of vegetation) and clumps of trees in the agricultural matrix within 100 m of the edge as significant predictors of the occupancy of edges by noisy miners. This relationship was also confirmed in two other geographically and floristically distinct habitats within Victoria. The use of edges with projections by noisy miners may confer advantages in interspecific territorial defence. In light of these results, we advocate revegetation strategies that attempt to enclose projections within 100 m of the edge, with fencing placed out to this new boundary, to reduce the likelihood of colonisation and domination of an edge by noisy miners. Our study highlights the need for greater consideration to be given to the patterns in habitat use by aggressive edge specialists, particularly in relation to patch-edge geometry and other human-induced components of landscapes."://WOS:000254250400002 Times Cited: 0WOS:000254250400002(10.1007/s10980-008-9196-9|ISSN 0921-2973ڽ7=Temperli, Christian Zell, Jürgen Bugmann, Harald Elkin, Ché2013jSensitivity of ecosystem goods and services projections of a forest landscape model to initialization data 1337-1352Landscape Ecology287Springer Netherlands[Climate change Forest inventory Landscape model Model initialization Simulation Uncertainty 2013/08/01+http://dx.doi.org/10.1007/s10980-013-9882-0 0921-2973Landscape Ecol10.1007/s10980-013-9882-0English 07 Termorshuizen, J. W. Opdam, P.2009TLandscape services as a bridge between landscape ecology and sustainable development 1037-1052Landscape Ecology248SpringerUniv, Wageningen Res Ctr, Landscape Ctr N. L. A. A. Wageningen Netherlands Res Ctr, Land Use Planning Grp N. L. A. A. Wageningen NetherlandsLandscape change Collaborative spatial planning Landscape functions Pattern-process relations Landscape value and valuation Ecosystem services Structure-function-value chain Interdisciplinary research Transdisciplinary research Sustainability scienceOctLandscape ecology is in a position to become the scientific basis for sustainable landscape development. When spatial planning policy is decentralised, local actors need to collaborate to decide on the changes that have to be made in the landscape to better accommodate their perceptions of value. This paper addresses two prerequisites that landscape ecological science has to meet for it to be effective in producing appropriate knowledge for such bottom-up landscape-development processes-it must include a valuation component, and it must be suitable for use in collaborative decision-making on a local scale. We argue that landscape ecological research needs to focus more on these issues and propose the concept of landscape services as a unifying common ground where scientists from various disciplines are encouraged to cooperate in producing a common knowledge base that can be integrated into multifunctional, actor-led landscape development. We elaborate this concept into a knowledge framework, the structure-function-value chain, and expand the current pattern-process paradigm in landscape ecology with value in this way. Subsequently, we analyse how the framework could be applied and facilitate interdisciplinary research that is applicable in transdisciplinary landscape-development processes.://000269913600005pISI Document Delivery No.: 495RV Times Cited: 3 Cited Reference Count: 100 Termorshuizen, Jolande W. Opdam, Paul 0921-2973 DORDRECHT2009 Landsc. Ecol.ISI:000269913600005Landscape ecologyTermorshuizen, JW, Univ Wageningen & Res Ctr, Landscape Ctr, POB 47, NL-6700 AA Wageningen, Netherlands. Jolande.Termorshuizen@wur.nl10.1007/s10980-008-9314-8Englishڽ7ATheobald, DavidM2013]A general model to quantify ecological integrity for landscape assessments and US application 1859-1874Landscape Ecology2810Springer NetherlandsZLandscape assessments Ecological integrity Land use Degree of human modification Fuzzy sum 2013/12/01+http://dx.doi.org/10.1007/s10980-013-9941-6 0921-2973Landscape Ecol10.1007/s10980-013-9941-6Englishz|? Theobald, David M.2010MEstimating natural landscape changes from 1992 to 2030 in the conterminous US999-1011Landscape Ecology257Aug_Quantifying landscape dynamics is a central goal of landscape ecology, and numerous metrics have been developed to measure the influence of human activities on natural landscapes. Composite scores that characterize human modifications to landscapes have gained widespread use. A parsimonious alternative is to estimate the proportion of a cover type (i.e. natural) within a spatial neighborhood to characterize both compositional and structural aspects of natural landscapes. Here I extend this approach into a multi-scale, integrated metric and apply it to national datasets on land cover, housing density, road existence, and highway traffic volume to measure the dynamics of natural landscapes in the conterminous US. Roughly one-third of the conterminous US (2.6 million km(2)) in 1992 was classified as human-dominated. By 2001 this expanded by 80,800 km(2), and forecasted residential growth by 2030 will potentially lead to an additional loss of up to 92,200 km(2). Wetland cover types were particularly affected. The natural landscapes metric developed here provides a simple, robust measure of landscape dynamics that has a direct physical interpretation related to proportion of natural habitat affected at a location, represents landscapes as a gradient of conditions rather predicated on patch/matrix definition, and measures the spatial context of natural areas.!://WOS:000279592100002Times Cited: 3 0921-2973WOS:00027959210000210.1007/s10980-010-9484-z 9<79MTheobald, D. M. Hobbs, N. T. Bearly, T. Zack, J. A. Shenk, T. Riebsame, W. E.2000tIncorporating biological information in local land-use decision making: designing a system for conservation planning35-45Landscape Ecology151Rcollaborative design conservation planning GIS land use LANDSCAPE WILDLIFE HABITATArticleJanHuman settlement is a formidable agent of change affecting fundamental ecological processes. Decisions governing these land-use changes occur almost exclusively at the local level and, as a result, they are made at many different locations and times. Consequently, it is difficult for ecologists to provide needed scientific support for these choices. We built an information system designed to support conservation decisions at local scales by offering data over the Internet. We collaborated with local stakeholders (e.g., developers, planners, politicians, land owners, environmental activists) to design the system. This collaboration produced several generalizations about effective design of information systems to support conservation. The most important of these is the idea that ecological data and analysis must be understood by those who will be affected by the decisions. Also, planning for conservation is a process that uses scientific data, but that ultimately depends on the expression of human values. A major challenge landscape ecologists face is to extend general landscape principles to provide specific scientific information needed for local land-use planning.://000083830400004 8ISI Document Delivery No.: 258GN Times Cited: 24 Cited Reference Count: 28 Cited References: *FOR EC MAN ASS TE, 1993, FOR EC MAN EC EC SOC *USDA, 1998, NAT RES INV *USFWS, 1983, 101ESM USFWS BEAN MJ, 1997, CONSERV BIOL, V11, P1 BOYCE MS, 1992, ANNU REV ECOL SYST, V23, P481 CORT CA, 1996, CONSERV BIOL, V10, P632 DOUGLAS I, 1994, CHANGES LAND USE LAN, P149 DUERKSON CJ, 1996, 470471 PAS AM PLANN HOBBS NT, 1994, SCOP SYSTEM CONSERVA HOLLING CS, 1997, CONSERV ECOL, V1, P1 KAHN A, 1966, KYKLOS, V19, P23 KARR JR, 1990, CONSERV BIOL, V4, P244 MEREDITH T, 1996, HUMAN ECOL REV, V3, P231 MURPHY DD, 1992, ECOL APPL, V2, P3 NOSS RF, 1997, SCI CONSERVATION PLA PECK S, 1998, PLANNING BIODIVERSIT PORTER D, 1997, MANAGING GROWTH AM C REJESKI D, 1993, ENV MODELING GIS, P318 RIEBSAME WE, 1996, MT RES DEV, V16, P395 ROCKWOOD P, 1995, LANDSCAPE URBAN PLAN, V31, P379 SCOTT JM, 1993, WILDLIFE MONOGR, V123, P41 SOULE ME, 1991, J AM PLANN ASSOC, V57, P313 STEINITZ C, 1996, BIODIVERSITY LANDSCA THEOBALD DM, 1997, LANDSCAPE URBAN PLAN, V39, P25 THEOBALD DM, 1998, GEOGRAPHICAL ENV MOD, V2, P57 VITOUSEK PM, 1997, SCIENCE, V277, P494 WEEKS P, 1997, CONSERV BIOL, V11, P236 WHITE D, 1997, CONS BIOL, V11, P1 0921-2973 Landsc. Ecol.ISI:000083830400004Colorado State Univ, Nat Resource Ecol Lab, Ft Collins, CO 80523 USA. Theobald, DM, Colorado State Univ, Nat Resource Ecol Lab, Ft Collins, CO 80523 USA.English~?!Thiele, J. Schuckert, U. Otte, A.2008YCultural landscapes of Germany are patch-corridor-matrix mosaics for an invasive megaforb453-465Landscape Ecology234Predicting the vulnerability of landscapes to both the initial colonisation and the subsequent spread of invasive species remains a major challenge. The aim of this study was to assess the relative importance of sub-patch level factors and landscape factors for the invasion of the megaforb Heracleum mantegazzianum. In particular, we tested which factors affect the presence in suitable habitat patches and the cover-percentage within invaded patches. For this purpose, we used standard (logistic) regression modelling techniques. The regression analyses were based on inventories of suitable habitat patches in 20 study areas (each 1 km(2)) in cultural landscapes of Germany. The cover percentage in invaded patches was independent from landscape factors, except for patch shape, and even unsatisfactorily explained by sub-patch level factors included in the analysis (R-2 = 0.19). In contrast, presence of H. mantegazzianum was affected by both local and landscape factors. Woody habitat structure decreased the occurrence probability, whereas vicinity to transport corridors (rivers, roads), high habitat connectivity, patch size and perimeter-area ratio of habitat patches had positive effects. The significance of corridors and habitat connectivity shows that dispersal of H. mantegazzianum through the landscape matrix is limited. We conclude that cultural landscapes of Germany function as patch-corridor-matrix mosaics for the spread of H. mantegazzianum. Our results highlight the importance of landscape structure and habitat configuration for invasive spread. Furthermore, this study shows that both local and landscape factors should be incorporated into spatially explicit models to predict spatiotemporal dynamics and equilibrium stages of plant invasions."://WOS:000254250400008 Times Cited: 0WOS:000254250400008(10.1007/s10980-008-9202-2|ISSN 0921-2973<7 Thogmartin, W. E. Knutson, M. G.2007gScaling local species-habitat relations to the larger landscape with a hierarchical spatial count model61-75Landscape Ecology2216abundance map; black-billed cuckoo; hierarchical model; information-theoretic model selection; multi-level model; red-headed woodpecker; spatial count model; wood thrush BREEDING-BIRD DISTRIBUTION; FOREST BIRDS; CERULEAN WARBLERS; GAP ANALYSIS; ABUNDANCE; CLIMATE; BIODIVERSITY; VEGETATION; OCCUPANCY; PATTERNSArticleJanMuch of what is known about avian species-habitat relations has been derived from studies of birds at local scales. It is entirely unclear whether the relations observed at these scales translate to the larger landscape in a predictable linear fashion. We derived habitat models and mapped predicted abundances for three forest bird species of eastern North America using bird counts, environmental variables, and hierarchical models applied at three spatial scales. Our purpose was to understand habitat associations at multiple spatial scales and create predictive abundance maps for purposes of conservation planning at a landscape scale given the constraint that the variables used in this exercise were derived from local-level studies. Our models indicated a substantial influence of landscape context for all species, many of which were counter to reported associations at finer spatial extents. We found land cover composition provided the greatest contribution to the relative explained variance in counts for all three species; spatial structure was second in importance. No single spatial scale dominated any model, indicating that these species are responding to factors at multiple spatial scales. For purposes of conservation planning, areas of predicted high abundance should be investigated to evaluate the conservation potential of the landscape in their general vicinity. In addition, the models and spatial patterns of abundance among species suggest locations where conservation actions may benefit more than one species.://000243619800007 K ISI Document Delivery No.: 127XO Times Cited: 0 Cited Reference Count: 50 Cited References: *US FISH WILDL SER, 2002, BIRDS CONS CONC *US NACBI COMM, 2000, N AM BIRD CONS IN BI BRENNAN JM, 2002, INTEGRATING LANDSCAP, P68 BROOKS SP, 1998, J COMPUT GRAPH STAT, V7, P434 BURNHAM KP, 2002, MODEL SELECTION MULT, P353 DEATH G, 2000, ECOLOGY, V81, P3178 DIAMOND DD, 2003, NAT AREA J, V23, P129 DONOVAN TM, 2002, ECOL APPL, V12, P364 GALE GA, 2001, J FIELD ORNITHOL, V72, P291 GALLI AE, 1976, AUK, V93, P356 GEISSLER PH, 1990, US FISH WILDL SERV B, V90, P54 GELMAN A, 1995, BAYESIAN DATA ANAL, P526 GIESE CLA, 2003, FOREST ECOL MANAG, V179, P523 GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 GUSTAFSON EJ, 2002, ECOL APPL, V12, P412 HOLLAND JD, 2004, BIOSCIENCE, V54, P227 HUGHES JM, 2001, BIRD N AM, V587, P24 KOENIG WD, 2001, ECOLOGY, V82, P2636 LEE M, 2002, OIKOS, V96, P110 LICHSTEIN JW, 2002, ECOL APPL, V12, P836 LINK WA, 2002, ECOLOGY, V83, P2832 LINK WA, 2002, J WILDLIFE MANAGE, V66, P277 LONG JS, 1997, REGRESSION MODELS CA, P297 MARTIN TE, 1981, AUK, V98, P715 MCKENNEY DW, 2002, PREDICTING SPECIES O, P377 MCNAB WH, 1994, WOWSA5 US FOR SERV NOON BR, 2003, BIOSCIENCE, V53, P1217 OCONNOR RJ, 2004, AUK, V121, P604 PEARLSTINE LG, 2002, J ENVIRON MANAGE, V66, P127 REMPEL RS, 2003, LANDSCAPE ECOL, V18, P741 RICH TD, 2004, PARTNERS FLIGHT N AM, P84 RIITTERS K, 2000, CONSERV ECOL, V4, P2756 ROSEBERRY JL, 1998, J WILDLIFE MANAGE, V62, P895 ROTH RR, 1996, BIRDS N AM, V246, P28 SAMPLE DW, 1997, MANAGING HABITAT GRA SARGENT RA, 2003, SOUTHEAST NAT, V2, P217 SCOTT JM, 1993, WILDLIFE MONOGR, P1 SCOTT JM, 2002, PREDICTING SPECIES O, P868 SEOANE J, 2004, ECOL MODEL, V171, P209 SMITH KG, 1987, J WILDLIFE MANAGE, V51, P459 SMITH KG, 2000, BIRDS N AM, V518, P28 SPIEGELHALTER DJ, 2002, J ROY STAT SOC B 4, V64, P583 SPIEGELHALTER DJ, 2003, WINBUGS VERSION 1 4 THOGMARTIN WE, 2004, ECOL APPL, V14, P1766 THOGMARTIN WE, 2006, CONDOR, V108, P25 THOMAS A, 2002, GEOBUGS USER MANUAL VENIER LA, 1999, J BIOGEOGR, V26, P315 VENIER LA, 2004, J BIOGEOGR, V31, P315 WIENS JA, 1981, ESTIMATING NUMBERS T, P513 WIENS JA, 1987, OIKOS, V48, P132 0921-2973 Landsc. Ecol.ISI:000243619800007US Geol Survey, Upper Midw Environm Sci Ctr, La Crosse, WI 54603 USA. Thogmartin, WE, US Geol Survey, Upper Midw Environm Sci Ctr, 2630 Fanta Reed Rd, La Crosse, WI 54603 USA. wthogmartin@usgs.govEnglishڽ7 Thomas, ShyamM Moloney, KirkA2013pHierarchical factors impacting the distribution of an invasive species: landscape context and propagule pressure81-93Landscape Ecology281Springer NetherlandsOInvasion Neighborhood Loosestrife Spatial pattern Surrounding land use Wetlands 2013/01/01+http://dx.doi.org/10.1007/s10980-012-9816-2 0921-2973Landscape Ecol10.1007/s10980-012-9816-2English<7Thompson, C. M. McGarigal, K.2002lThe influence of research scale on bald eagle habitat selection along the lower Hudson River, New York (USA)569-586Landscape Ecology176extent grain habitat selection Haliaeetus leucocephalus multi-scale scale threshold NEST SITE SELECTION RESOURCE SELECTION LANDSCAPE ECOLOGY AVAILABILITY DATA RESPONSES PATTERNS ARIZONA MODELSArticleOctAs the concepts of landscape ecology have been incorporated into other disciplines, the influence of spatial patterns on animal abundance and distribution has attracted considerable attention. However, there remains a significant gap in the application of landscape ecology theories and techniques to wildlife research. By combining landscape ecology techniques with traditional wildlife habitat analysis methods, we defined an 'organism-centered perspective' for breeding bald eagles (Haliaeetus leucocephalus) along the Hudson River, New York, USA. We intensively monitored four pairs of breeding eagles during the 1999 and 2000 breeding seasons, and collected detailed information on perch and forage locations. Our analysis focused on three critical habitat elements: available perch trees, access to foraging areas, and freedom from human disturbance. We hypothesized that eagle habitat selection relative to each of these elements would vary with the spatial scale of analysis, and that these scaling relationships would vary among habitat elements. We investigated two elements of spatial scale: grain and local extent. Grain was defined as the minimum mapping unit; local extent was defined by the size of an analysis window placed around each focal point. For each habitat element, we quantified habitat use over a range of spatial scales. Eagles displayed scale-dependent patterns of habitat use in relation to all habitat features, including multi-scale and threshold-like patterns. This information supports the existence of scale-dependant relationships in wildlife habitat use and allowed for a more accurate and biologically relevant evaluation of Hudson River breeding eagle habitat.://000179774900007 ISI Document Delivery No.: 624RN Times Cited: 13 Cited Reference Count: 62 Cited References: *USFWS, 1996, REG SIGN HAB HAB COM ADDICOTT JF, 1987, OIKOS, V49, P340 AEBISCHER NJ, 1993, ECOLOGY, V74, P1313 ALLDREDGE JR, 1986, J WILDLIFE MANAGE, V50, P157 ALLEN TFH, 1982, HIERARCHY PERSPECTIV ANDREW JM, 1982, J WILDLIFE MANAGE, V46, P383 ANTHONY RG, 1989, J WILDLIFE MANAGE, V53, P148 BAKER BW, 1995, J WILDLIFE MANAGE, V59, P752 BOWERMAN WW, 1993, THESIS U MICHIGAN AN BROWN BT, 1997, J RAPTOR RES, V31, P7 BUEHLER DA, 1991, J WILDLIFE MANAGE, V55, P282 BYERS CR, 1984, J WILDLIFE MANAGE, V48, P1050 CAIN SL, 1989, J RAPTOR RES, V23, P10 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FRASER JD, 1985, J WILDLIFE MANAGE, V49, P585 GARRETT MG, 1993, J WILDLIFE MANAGE, V57, P19 GERRARD JM, 1975, BLUE JAY, V33, P169 GIBBS JP, 1998, LANDSCAPE ECOL, V13, P263 GRUBB TG, 1991, J WILDLIFE MANAGE, V55, P500 GRUBB TG, 1995, WILSON BULL, V107, P258 HALL LS, 1999, J WILDLIFE MANAGE, V63, P451 HARDESTY JL, 1991, 8843 NAT FISH WILDL HUNT WG, 1992, ECOLOGY BALD EAGLES JACKMAN RE, 1993, N AM BIRD BANDER, V18, P98 KERKHOFF AJ, 2000, CONSERV ECOL, V4 KOLASA J, 1991, ECOLOGICAL HETEROGEN, P1 KOTLIAR NB, 1990, OIKOS, V59, P253 LAMBERSON RH, 1992, CONSERV BIOL, V6, P505 LEVIN SA, 1992, ECOLOGY, V73, P1943 LITVAITIS JA, 1996, RES MANAGEMENT TECHN, P254 LIVINGSTON SA, 1990, J WILDLIFE MANAGE, V54, P644 MCCLEAN SA, 1998, J WILDLIFE MANAGE, V62, P793 MCEWAN LC, 1979, J WILDLIFE MANAGE, V43, P585 MCGARIGAL K, 1991, WILDLIFE MONOGRAPHS, V115 MCGARIGAL K, 1995, PNW351 US FOR SERV N MCGARIGAL K, 2000, MULTIVARIATE STAT WI MORRIS DW, 1987, ECOLOGY, V68, P362 NEU CW, 1974, J WILDLIFE MANAGE, V38, P541 ORROCK JL, 2000, ECOL APPL, V10, P1356 OTIS DL, 1997, J WILDLIFE MANAGE, V61, P1016 OTIS DL, 1999, J WILDLIFE MANAGE, V63, P1039 PEARSON SM, 1997, WILDLIFE LANDSCAPE E, P215 PEERY MZ, 1999, J WILDLIFE MANAGE, V63, P36 SCHULZ TT, 1992, WILDLIFE SOC B, V20, P74 STALMASTER MV, 1978, J WILDLIFE MANAGE, V42, P506 STALMASTER MV, 1998, WILDLIFE MONOGRAPHS, V137 STEIDL RJ, 1996, ECOL APPL, V6, P482 THOMAS DL, 1990, J WILDLIFE MANAGE, V54, P322 THOMPSON C, 2000, STATUS MOVEMENTS BAL TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1991, QUANTITATIVE METHODS TURNER MG, 1997, WILDLIFE LANDSCAPE E, P215 TURNER MG, 2001, LANDSCAPE ECOLOGY TH URBAN DL, 1987, BIOSCIENCE, V37, P119 WATSON JA, 1986, DACW5783C0100 OR STA WIENS JA, 1976, ANNU REV ECOL SYST, V7, P81 WIENS JA, 1987, OIKOS, V48, P132 WIENS JA, 1989, FUNCT ECOL, V3, P385 WILLIAMS BK, 1981, USE MULTIVARIATE STA, P59 WITH KA, 1995, ECOLOGY, V76, P2446 WOOD PB, 1999, J RAPTOR RES, V33, P97 YOUNG JA, 1993, FINAL REPORTS TT POL 0921-2973 Landsc. Ecol.ISI:000179774900007Utah State Univ, Dept Fisheries & Wildlife, Logan, UT 84322 USA. Univ Massachusetts, Dept Nat Resource Conservat, Amherst, MA 01003 USA. Thompson, CM, Utah State Univ, Dept Fisheries & Wildlife, Logan, UT 84322 USA.English|?C Thompson, J. R. Spies, T. A.2010Factors associated with crown damage following recurring mixed-severity wildfires and post-fire management in southwestern Oregon775-789Landscape Ecology255Wildfires and post-fire logging and planting have a lasting influence on the quantity and arrangement of live and dead vegetation, which can, in turn, affect the behavior of future fires. In 2002, the Biscuit Fire re-burned 38,000 ha of mixed-conifer/evergreen hardwood forest in southwestern Oregon that had burned heterogeneously during the 1987 Silver Fire and then was subject, in part, to post-fire logging and planting. We measured vegetation cover and crown damage from at temporal sequence (1987, 2000, and 2002) of digital aerial photo-plots (plot size = 6.25 ha) within managed and unmanaged portions of the twice-burned landscape. We estimated the strength and nature of relationships between crown damage in the two fires while also accounting for the influence of several vegetation, topographic, weather, and management variables. On average, unmanaged plots within the reburn area had 58% of their live crown cover scorched or consumed by the Biscuit Fire (median = 64%). The level of re-burn crown damage was strongly related to the level of crown damage during the Silver Fire. Typically, the areas that burned severely in the Silver Fire succeeded to a mix of shrubs and tree regeneration (i.e. shrub-stratum vegetation), which then experienced high levels of Biscuit Fire damage. In contrast, the level of tree-stratum damage in the Biscuit Fire was largely independent of Silver Fire damage. Within plots that were salvage-logged then planted after the Silver Fire, on average 98% of the vegetation cover was damaged by the Biscuit Fire (median = 100%). Within the plots that experienced complete crown damage in the Silver Fire but were left unmanaged, on average 91% of the vegetation cover was damaged by the Biscuit Fire (median = 95%). Our findings suggest that in productive fire-prone landscapes, a post-fire mosaic of young regenerating vegetation can influence the pattern of crown damage in future wildfires.!://WOS:000276609800009Times Cited: 0 0921-2973WOS:00027660980000910.1007/s10980-010-9456-3|?Thompson, S. D. Gergel, S. E.2008Conservation implications of mapping rare ecosystems using high spatial resolution imagery: recommendations for heterogeneous and fragmented landscapes 1023-1037Landscape Ecology239Protection of rare ecosystems requires information on their abundance and spatial distribution, yet mapping rare ecosystems, particularly those which are fragmented, is a challenge. Use of high spatial resolution satellite imagery is increasing, in part because it may be well-suited for mapping fine-scale components of landscapes. We classified high spatial resolution QuickBird imagery of coastal British Columbia, Canada into late seral forest associations. With an emphasis on rare forest associations, we compared the classification accuracies resulting from contrasting accuracy assessment techniques. We also evaluated the impact of post-classification image smoothing on the quantity and configuration of rare forest associations mapped. Less common associations were generally classified with lower accuracies than more abundant associations, however, accuracies varied depending on the assessment technique used. In particular, ignoring the presence of fine-scale heterogeneity falsely lowered the estimates of map accuracy by approximately 20%. Smoothing, while generally increasing the accuracies of rare forest associations, had a large effect on their predicted spatial extent and configuration. Simply due to smoothing, areal estimates of rare associations differed by as much as 36%, the number of patches decreased by 73% on average, and mean patch size increased by up to 650%. Our findings indicate that routinely used post-classification and map assessment techniques can greatly impact the portrayal of rare and fragmented ecosystems. Further research is needed on the specific challenges of mapping and assessing the accuracy of rare ecosystems in fragmented and heterogeneous landscapes.!://WOS:000260283100003Times Cited: 0 0921-2973WOS:00026028310000310.1007/s10980-008-9263-2K|?c 6Thornton, Daniel H. Branch, Lyn C. Sunquist, Melvin E.2011~The influence of landscape, patch, and within-patch factors on species presence and abundance: a review of focal patch studies7-18Landscape Ecology261JanUnderstanding the influence of large and small-scale heterogeneity on species distribution and abundance is one of the major foci of landscape ecology research in fragmented environments. Although a large number of studies have addressed this issue individually, little effort has been made to synthesize the vast amount of literature published in the last decade. We reviewed 122 focal patch studies on 954 species published between 1998 and 2009 to determine the probability of species responding significantly to landscape, patch, and within-patch variables. We assessed the influence of taxonomic, life history, and methodological variables on probability of response to these 3 levels. Species in diverse taxa responded at high rates to factors at all three levels, suggesting that a multi-level approach is often necessary for understanding species response in patchy systems. Mammals responded at particularly high rates to landscape variables and therefore may benefit more than other taxa from landscape-level conservation efforts in fragmented environments. The probability of detecting a species response to landscape context, patch, and within-patch factors was influenced by a variety of methodological aspects of the studies such as type of landscape metric used, type of response variable, and sample size. Study design issues rarely are discussed by authors as reasons why a particular study did not find an effect of a variable, but should be given more consideration in future studies.!://WOS:000286004400002Times Cited: 1 0921-2973WOS:00028600440000210.1007/s10980-010-9549-z|?8"Tian, Li Chen, Jiquan Yu, Shi Xiao2014XCoupled dynamics of urban landscape pattern and socioeconomic drivers in Shenzhen, China715-727Landscape Ecology294AprThe effects of land use policy and socioeconomic changes on urban landscape dynamics have been increasingly investigated around the world, but our knowledge of the underlying processes of these effects is still inadequate for sustainably managing urban ecosystems. Thus, the main goal of this study was to understand: (1) the changes in urban landscape, population, and economic conditions over a 36-year period, and (2) the coupled dynamics of land use policy, landscape structure, major demographic features, and three kinds of industries in one of the most dazzling modern cities of China-the Shenzhen special economic zone (SEZ). The landscape expansion index was used to explore the developed-land expansion under different land use policies while structural equation modeling (SEM) was used to analyze the relationship among three variables (Land Cover Change or LCC, Economy, and Population). We found that the urban expansion during the four periods (1973-1979, 1979-1995, 1995-2003, and 2003-2009) was not always at the expense of urban vegetation cover. The importance of each socioeconomic driver during the four periods was not consistent over time, with policy shifts as the primary driver. Our SEM showed that Economy played a more important role than Population in driving LCC in the Shenzhen SEZ. Meanwhile, the secondary and tertiary industries had a stronger influence than the primary industry; and the floating population had a greater effect than the registered permanent population.!://WOS:000333533800013Times Cited: 1 0921-2973WOS:00033353380001310.1007/s10980-014-9995-0|?10Tian, Yu Wu, Jianguo Wang, Tianming Ge, Jianping2014~Climate change and landscape fragmentation jeopardize the population viability of the Siberian tiger (Panthera tigris altaica)621-637Landscape Ecology294AprThe Amur tiger, a flagship species of the boreal forest ecosystem in Russian Far East and northeastern China, has declined dramatically in population and geographic distribution due to human caused habitat fragmentation and poaching over the past century. The fate of this largest feline species will also be influenced by the worsening impacts of climate change. In this paper we assess the possible effects of climate change (three scenarios from the 2007 IPCC Report) on the Amur tiger by integrating species distribution modeling (SDM) and population viability analysis (PVA). We projected the potential and realized suitable habitat distributions to examine the impacts from anthropogenic factors, and evaluated the changes of suitable habitat and extinction risk for 100 years under climate change. The realized suitable habitat was projected to be more severely fragmented than the potential suitable habitat because of human-related factors. The potential suitable habitat would expand northward under all climate change scenarios considered. However, the tiger population would suffer the largest decline and highest extinction risk in the next 100 years under the worst climate change scenario (A1B) even though the size of potential habitat would be greatest. Under climate change, the tiger population could persist for the next century only if the size and quality of current habitat patches would remain intact. In addition, our study demonstrated that using SDM alone could grossly overestimate the geographic distribution of the Amur tiger, and that coupling SDM and PVA could provide important insights into conservation planning to mitigate the effects of climate change.!://WOS:000333533800006Times Cited: 0 0921-2973WOS:00033353380000610.1007/s10980-014-0009-z <7'Tikka, P. M. Hogmander, H. Koski, P. S.2001IRoad and railway verges serve as dispersal corridors for grassland plants659-666Landscape Ecology167binomial test dispersal ecological corridors grassland plants spatial order traffic route verges FRAGMENTED LANDSCAPES SEED DISPERSAL CONSERVATION ABUNDANCE MIGRATION PATTERNS MAMMALS FORESTS ECOLOGYArticleOctThe role of linear habitat strips as dispersal corridors is a disputed topic. Reports concerning their significance for animals have been contradictory, and the functions of corridors have been difficult to study in the case of sedentary organisms such as plants. Previous studies on dispersal of plants along corridors have concentrated on a single or a few species at a time. We developed a general method, a generalisation of the binomial test, for considering dispersal or spatial relations of a large group of species. Particularly, we studied the ability of grassland plants to spread along road and railway verges. Our data set consists of plant lists collected at study plots scattered irregularly along road and railway networks. The dispersal ability was assessed by testing whether the species composition at neighbouring sites - measured along roads and railways - reflects spatial dependence within each species. Our result showed that similar combinations of grassland species occurred at neighbouring sites more often than expected in a spatially independent case. We argue that management of verges and spatial autocorrelation of environmental factors were not responsible for the result and thereby we conclude that grassland plants use road and railway corridors for dispersal. This result is encouraging in regards to preservation of grassland plant populations. Although semi-natural and natural grasslands have become scarce, road and railway embankments may partly compensate for this loss, serving as substitute habitats and dispersal routes.://000172809400006 [ISI Document Delivery No.: 503QG Times Cited: 7 Cited Reference Count: 46 Cited References: 1991, TIENRAKENNUSTOIDEN Y 1996, PUBLIC ROADS ENV NAT 1996, VEGETATION ROAD AREA 1998, TIENRAKENNUSTOIDEN Y ARNOLD GW, 1991, NATURE CONSERVATION, V2, P273 BENGTSSONLINDSJ.S, 1991, ECOL B, V41, P388 BENNETT AF, 1990, LANDSCAPE ECOL, V4, P109 BROWN JH, 1995, ECOLOGY, V76, P2028 CUMMINGS JR, 1994, AM MIDL NAT, V132, P209 DOWNES SJ, 1997, CONSERV BIOL, V11, P718 EKSTAM U, 1997, GRASSLAND MANAGEMENT ERIKSSON A, 1995, ECOGRAPHY, V18, P310 ERNST WHO, 1998, ACTA BOT NEERL, V47, P131 FORNEY KA, 1989, CONSERV BIOL, V3, P45 FRITZ R, 1993, BIOL CONSERV, V64, P141 GILBERT F, 1998, P ROY SOC LOND B BIO, V265, P577 GRIME JP, 1988, COMP PLANT ECOLOGY F HAAS CA, 1995, CONSERV BIOL, V9, P845 HAMETAHTI L, 1998, RETKEILYKASVIO FIELD HOLYOAK M, 1996, J ANIM ECOL, V65, P640 INGLIS G, 1992, CONSERV BIOL, V6, P581 JENNERSTEN O, 1992, ECOLOGICAL PRINCIPLE, P394 LEGENDRE P, 1993, ECOLOGY, V74, P1659 LYNCH JF, 1995, NATURE CONSERVATION, V4, P34 MANN CC, 1995, SCIENCE, V270, P1428 MEFFE GK, 1994, PRINCIPLES CONSERVAT NICHOLLS AO, 1991, NATURE CONSERVATION, V2, P49 RASSI P, 2000, SUOMEN LAJIEN UHANAL ROSENBERG DK, 1998, CAN J ZOOL, V76, P117 SAUNDERS DA, 1991, NATURE CONSERVATION, V2 SCHMIDT W, 1989, VEGETATIO, V80, P147 SCOTT NE, 1982, WATSONIA, V14, P41 SCOTT NE, 1985, VEGETATIO, V62, P433 SEVOLA Y, 1997, TAPION TASKUKIRJA, P11 SIMBERLOFF D, 1992, CONSERV BIOL, V6, P493 STOTTELE T, 1994, THESIS U GOTTINGEN G STRYKSTRA RJ, 1997, ACTA BOT NEERL, V46, P387 SUOMINEN J, 1970, ANN BOT FENN, V7, P143 SUOMINEN J, 1974, LUONNON TUTKIJA, V78, P12 SUTCLIFFE OL, 1996, CONSERV BIOL, V10, P1359 TIKKA PM, 2000, APPL VEG SCI, V3, P25 VANDORP D, 1996, THESIS AGR U WAGENIN VANDORP D, 1997, LANDSCAPE ECOL, V12, P39 WILCOX DA, 1989, ENVIRON MANAGE, V13, P365 WILLSON MF, 1990, J VEG SCI, V1, P547 ZINK TA, 1995, RESTOR ECOL, V3, P304 0921-2973 Landsc. Ecol.ISI:000172809400006Univ Jyvaskyla, Dept Biol & Environm Sci, FIN-40351 Jyvaskyla, Finland. Tikka, PM, Univ Helsinki, Dept Limnol & Environm Protect, POB 62, FIN-00014 Helsinki, Finland.English<7k^Tinker, D. B. Resor, C. A. C. Beauvais, G. P. Kipfmueller, K. F. Fernandes, C. I. Baker, W. L.1998UWatershed analysis of forest fragmentation by clearcuts and roads in a Wyoming forest149-165Landscape Ecology133forest fragmentation landscape pattern clearcutting logging roads watershed analysis Bighorn National Forest disturbance lodgepole pine ECOSYSTEM MANAGEMENT LANDSCAPE STRUCTURE ROCKY-MOUNTAINS OLD-GROWTH HABITAT PERSPECTIVE VEGETATION PATTERNS OREGON ELKArticleJun!Remotely sensed data and a Geographic Information System were used to compare the effects of clearcutting and road-building on the landscape pattern of the Bighorn National Forest, in north-central Wyoming. Landscape patterns were quantified for each of 12 watersheds on a series of four maps that differed only in the degree of clearcutting and road density. We analyzed several landscape pattern metrics for the landscape as a whole and for the lodgepole pine and spruce/fir cover classes across these maps, and determined the relative effects of clearcutting and road building on the pattern of each watershed. At both the landscape- and cover class-scales, clearcutting and road building resulted in increased fragmentation as represented by a distinct suite of landscape structural changes. Patch core area and mean patch size decreased, and edge density and patch density increased as a result of clearcuts and roads. Clearcuts and roads simplified patch shapes at the landscape scale, but increased the complexity of lodgepole pine patches. Roads appeared to be a more significant agent of change than clearcuts, and roads which were more evenly distributed across a watershed had a greater effect on landscape pattern than did those which were densely clustered. Examining individual watersheds allows for the comparison of fragmentation among watersheds, as well as across the landscape as a whole. Similar studies of landscape structure in other National Forests and on other public lands may help to identify and prevent further fragmentation of these areas.://000079303300002 ISI Document Delivery No.: 179BH Times Cited: 27 Cited Reference Count: 53 Cited References: *ESRI INC, 1995, UND GIS ARC INFO MET *SPSS INC, 1995, SPSS WIND US GUID *USDA FOR SERV, 1993, NAT HIER FRAM EC UN ANDREN H, 1994, OIKOS, V71, P355 BAKER WL, 1992, LANDSCAPE ECOL, V7, P291 BAKER WL, 1994, LANDSCAPE STRUCTURE BEAUVAIS GP, UNPUB MAMMAL COMMUNI BISSONETTE JA, 1989, T N AM WILDL NAT RES, V54, P89 BURCHAM MG, 1993, EVALUATING ELK SECUR CHEN JQ, 1992, ECOL APPL, V2, P387 COATS RN, 1981, ENVIRON MANAGE, V5, P147 CROMPTON BJ, 1994, THESI U WYOMING LARA DESPAIN DG, 1973, ECOL MONOGR, V43, P329 DIXON WJ, 1990, BMDP STAT SOFTWARE M DOBKIN DS, 1994, CONSERVATION MANAGEM FAABORG J, 1995, ECOLOGY MANAGEMENT N, P357 FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 GATES JE, 1978, ECOLOGY, V59, P871 HARRIS LD, 1984, FRAGMENTED FOREST HEJL SJ, 1995, ECOLOGY MANAGEMENT N, P220 JACKSON JE, 1991, USERS GUIDE PRINCIPA JENSEN ME, 1996, WATER RESOUR BULL, V32, P203 KAUFMANN MR, 1994, RM246 USDA FOR SERV KELLER ME, 1992, CONDOR, V94, P55 LI H, 1993, LANDSCAPE ECOL, V8, P63 LOTSPEICH FB, 1980, WATER RESOUR BULL, V16, P581 LOVEJOY TE, 1986, CONSERVATION BIOL SC, P257 LYON LJ, 1980, J WILDLIFE MANAGE, V44, P352 LYON LJ, 1983, J FOREST, V81, P592 MAXWELL JR, 1995, NC176 USDA FOR SERV MCCLELLAN BN, 1988, J APPL ECOL, V25, P451 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MILLER JR, 1996, LANDSCAPE ECOL, V11, P115 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 MONTGOMERY DR, 1995, WATER RESOUR BULL, V31, P369 MORRISON PH, 1994, REMOTE SENSING GIS E, P77 MURCIA C, 1995, TRENDS ECOL EVOL, V10, P58 NOSS RF, 1993, WILD EARTH SPECIAL I, P10 NOSS RF, 1994, PRINCIPLES CONSERVAT, P237 OPDAM P, 1993, LANDSCAPE ECOLOGY ST, P147 REED RA, 1996, BIOL CONSERV, V75, P267 REED RA, 1996, CONSERV BIOL, V10, P1098 RIPPLE WJ, 1991, BIOL CONSERV, V57, P73 ROMME WH, 1989, BIOSCIENCE, V39, P695 RUGGIERO LF, 1994, RM254 USDA FOR SERV SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SHANDS WE, 1994, SILVICULTURE CRADLE, P3 SHINNEMAN DJ, 1996, THESIS U WYOMING LAR SPIES TA, 1994, ECOL APPL, V4, P555 SWANSON FJ, 1994, ECOSYSTEM MANAGEMENT, V2, P80 TEMPLE SA, 1986, WILDLIFE 2000 MODELI, P261 TOWNSEND FE, 1986, PHOTOGRAMM ENG REM S, V52, P213 VAILLANCOURT DA, 1995, THESIS U WYOMING LAR 0921-2973 Landsc. Ecol.ISI:000079303300002iUniv Wyoming, Dept Bot, Laramie, WY 82071 USA. Tinker, DB, Univ Wyoming, Dept Bot, Laramie, WY 82071 USA.Englishy<7h)Tinker, D. B. Romme, W. H. Despain, D. G.2003nHistoric range of variability in landscape structure in subalpine forests of the Greater Yellowstone Area, USA427-439Landscape Ecology184disturbance fire historic range of variability landscape structure lodgepole pine logging Yellowstone NATIONAL-PARK INFREQUENT DISTURBANCES ROCKY-MOUNTAINS FIRE FRAGMENTATION ROADS MANAGEMENT DYNAMICS ECOLOGY PATTERNArticle A measure of the historic range of variability (HRV) in landscape structure is essential for evaluating current landscape patterns of Rocky Mountain coniferous forests that have been subjected to intensive timber harvest. We used a geographic information system (GIS) and FRAGSTATS to calculate key landscape metrics on two -130,000-ha landscapes in the Greater Yellowstone Area, USA: one in Yellowstone National Park (YNP), which has been primarily shaped by natural fires, and a second in the adjacent Targhee National Forest (TNF), which has undergone intensive clearcutting for nearly 30 years. Digital maps of the current and historical landscape in YNP were developed from earlier stand age maps developed by Romme and Despain. Maps of the TNF landscape were adapted from United States Forest Service Resource Information System (RIS) data. Key landscape metrics were calculated at 20-yr intervals for YNP for the period from 1705-1995. These metrics were used to first evaluate the relative effects of small vs. large fire events on landscape structure and were then compared to similar metrics calculated for both pre- and post-harvest landscapes of the TNF. Large fires, such as those that burned in 1988, produced a structurally different landscape than did previous, smaller fires (1705-1985). The total number of patches of all types was higher after 1988 (694 vs. 340-404 before 1988), and mean patch size was reduced by almost half (186 ha vs. 319-379 ha). The amount of unburned forest was less following the 1988 fires (63% vs. 72-90% prior to 1988), yet the number of unburned patches increased by nearly an order of magnitude (230 vs. a maximum of 41 prior to 1988). Total core area and mean core area per patch decreased after 1988 relative to smaller fires (-73,700 ha vs. 87,000-110,000 ha, and 320 ha vs. 2,123 ha, respectively). Notably, only edge density was similar (17 m ha(-1) after 1988) to earlier landscapes (9.8-14.2 m ha(-1)). Three decades of timber harvesting dramatically altered landscape structure in the TNF. Total number of patches increased threefold (1,481 after harvest vs. 437 before harvest), and mean patch size decreased by -70% (91.3 ha vs. 309 ha). None of the post-harvest landscape metrics calculated for the TNF fell within the HRV as defined in YNP, even when the post-1988 landscape was considered. In contrast, pre- harvest TNF landscape metrics were all within, or very nearly within, the HRV for YNP. While reference conditions such as those identified by this study are useful for local and regional landscape evaluation and planning, additional research is necessary to understand the consequences of changes in landscape structure for population, community, ecosystem, and landscape function.://000185919200006 ISI Document Delivery No.: 732AT Times Cited: 8 Cited Reference Count: 41 Cited References: *ESRI, 1995, ARC INFO US MAN *US ARM CONSTR ENG, 1997, GRASS US MAN VERS 4 BAKER WL, 1992, LANDSCAPE ECOL, V7, P181 BAKER WL, 1992, LANDSCAPE ECOL, V7, P291 BAKER WL, 2000, FOREST FRAGMENTATION, P55 CISSEL JH, 1998, PNWGTR422 US FOR SER CISSEL JH, 1999, ECOL APPL, V9, P1217 FOSTER DR, 1998, ECOSYSTEMS, V1, P497 FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 HANSEN AJ, 1991, BIOSCIENCE, V41, P382 JOHNSON EA, 1992, FIRE VEGETATION DYNA KNIGH RL, 2000, FOREST FRAGMENTATION LANDRES PB, 1999, ECOL APPL, V9, P1179 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MILLER JR, 1996, LANDSCAPE ECOL, V11, P115 MILLSPAUGH SH, 2000, GEOLOGY, V28, P211 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 MORITZ MA, 1997, ECOL APPL, V7, P1252 NOSS RF, 1994, PRINCIPLES CONSERVAT, P237 REED RA, 1996, BIOL CONSERV, V75, P267 REED RA, 1996, CONSERV BIOL, V10, P1098 RENKIN RA, 1992, CAN J FOREST RES, V22, P37 ROMME WH, 1982, ECOL MONOGR, V52, P199 ROMME WH, 1989, BIOSCIENCE, V39, P695 ROMME WH, 1989, W WILDLANDS, V15, P10 ROMME WH, 1998, ECOSYSTEMS, V1, P524 ROMME WH, 2000, FOREST FRAGMENTATION, P377 SAUNDERS DA, 1991, CONSERV BIOL, V5, P18 SWANSON FJ, 1993, EASTSIDE FOREST ECOS, V2, P89 SWETNAM TW, 1999, ECOL APPL, V9, P1189 TINKER DB, 1998, LANDSCAPE ECOL, V13, P149 TINKER DB, 2000, FOREST FRAGMENTATION TURNER MG, 1993, LANDSCAPE ECOL, V8, P213 TURNER MG, 1994, LANDSCAPE ECOL, V9, P59 TURNER MG, 1995, BIOSCIENCE S TURNER MG, 1997, ECOL MONOGR, V67, P411 TURNER MG, 1998, ECOSYSTEMS, V1, P493 VEBLEN TT, 2000, FOREST FRAGMENTATION, P31 WALLIN DO, 1996, FOREST ECOL MANAG, V85, P291 WHITE PS, 1999, ECOLOGICAL STEWARDSH, P281 WILMER HB, 2000, EFFECTS FIRE LOGGING 0921-2973 Landsc. Ecol.ISI:000185919200006Univ Wisconsin, Dept Zool, Madison, WI 53706 USA. Univ Wyoming, Dept Bot, Laramie, WY 82071 USA. Ft Lewis Coll, Dept Biol, Durango, CO 81301 USA. Montana State Univ, Dept Biol, USGS, Bozeman, MT USA. Tinker, DB, Univ Wisconsin, Dept Zool, Madison, WI 53706 USA.English<7Tischendorf, L.2001@Can landscape indices predict ecological processes consistently?235-254Landscape Ecology163artificial vs. realistic landscapes dispersal landscape indices pattern-process relationships simulation model CARABID BEETLES COLEOPTERA HABITAT FRAGMENTATION PEROMYSCUS-LEUCOPUS MULTISCALE ANALYSIS SPATIAL PATTERN INSECT MOVEMENT BREEDING BIRDS RANDOM-WALK DISPERSAL CONNECTIVITYArticleAprThe ecological interpretation of landscape patterns is one of the major objectives in landscape ecology. Both landscape patterns and ecological processes need to be quantified before statistical relationships between these variables can be examined. Landscape indices provide quantitative information about landscape pattern. Response variables or process rates quantify the outcome of ecological processes (e.g., dispersal success for landscape connectivity or Morisita's index for the spatial distribution of individuals). While the principal potential of this approach has been demonstrated in several studies, the robustness of the statistical relationships against variations in landscape structure or against variations of the ecological process itself has never been explicitly investigated. This paper investigates the consistency of correlations between a set of landscape indices (calculated with Fragstats) and three response variables from a simulated dispersal process across heterogeneous landscapes (cell immigration, dispersal success and search time) against variation in three experimental treatments (control variables): habitat amount, habitat fragmentation and dispersal behavior. I found strong correlations between some landscape indices and all three response variables. However, 68% of the statistical relationships were highly inconsistent and sometimes ambiguous for different landscape structures and for differences in dispersal behavior. Correlations between one landscape index and one response variable could range from highly positive to highly negative when derived from different spatial patterns. I furthermore compared correlation coefficients obtained from artificially generated (neutral) landscape models with those obtained from Landsat TM images. Both landscape representations produced equally strong and weak statistical relationships between landscape indices and response variables. This result supports the use of neutral landscape models in theoretical analyses of pattern-process relationships.://000168194400004 qISI Document Delivery No.: 423TT Times Cited: 56 Cited Reference Count: 78 Cited References: *SAS I, 1990, SAS VERS 6 ANDREASSEN HP, 1996, J APPL ECOL, V33, P555 BAARS MA, 1979, OECOLOGIA, V44, P125 BAKER WL, 1992, LANDSCAPE ECOL, V7, P291 BAKOWSKI C, 1988, ACTA THERIOL, V33, P345 BONNET X, 1999, BIOL CONSERV, V89, P39 CAIN DH, 1997, LANDSCAPE ECOL, V12, P199 CHARRIER S, 1997, AGR ECOSYST ENVIRON, V61, P133 COLLINS RJ, 1997, LANDSCAPE ECOL, V12, P63 CULLINAN VI, 1992, LANDSCAPE ECOL, V7, P211 DOAK DF, 1992, THEOR POPUL BIOL, V41, P315 DUELLI P, 1990, BIOL CONSERV, V54, P193 FAHRIG L, 1995, BIOL CONSERV, V73, P177 FAHRIG L, 1997, J WILDLIFE MANAGE, V61, P603 FAHRIG L, 1998, ECOL MODEL, V105, P273 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FRAMPTON GK, 1995, BIOL CONSERV, V71, P347 GAINES MS, 1980, ANNU REV ECOL SYST, V11, P163 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GARDNER RH, 1991, QUANTITATIVE METHODS, P289 GARRABOU J, 1998, LANDSCAPE ECOL, V13, P225 GARRETT MG, 1988, J MAMMAL, V69, P236 GILES RH, 1999, ENVIRON MANAGE, V23, P477 GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HADDAD NM, 1999, AM NAT, V153, P215 HAEFNER JW, 1991, ECOL MODEL, V56, P221 HAMAZAKI T, 1996, LANDSCAPE ECOL, V11, P299 HANSSON L, 1991, BIOL J LINN SOC, V42, P89 HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HENEIN K, 1990, LANDSCAPE ECOL, V4, P157 HULSHOFF RM, 1995, LANDSCAPE ECOL, V10, P101 JAEGER JAG, 2000, LANDSCAPE ECOL, V15, P115 JOHANSEN A, 1994, PHYSICA D, V78, P186 KAREIVA PM, 1983, OECOLOGIA, V56, P234 KROHNE DT, 1984, AM MIDL NAT, V112, P146 KROHNE DT, 1987, HOLARCTIC ECOL, V10, P196 LAVOREL S, 1993, OIKOS, V67, P521 LEDUC A, 1994, LANDSCAPE ECOL, V9, P279 LI HB, 1994, ECOLOGY, V75, P2446 LIDICKER WZ, 1975, SMALL MAMMALS THEIR, P103 MADER HJ, 1984, BIOL CONSERV, V29, P81 MADER HJ, 1990, BIOL CONSERV, V54, P209 MATTER SF, 1996, OECOLOGIA, V105, P447 MAUREMOOTO JR, 1995, AGR ECOSYST ENVIRON, V52, P141 MCGARIGAL K, 1995, ECOL MONOGR, V65, P235 MCGARIGAL K, 1995, PNW351 US FOR SERV G MEISEL JE, 1998, LANDSCAPE ECOL, V13, P347 MERRIAM G, 1989, LANDSCAPE ECOLOGY, V2, P227 NIKORA VI, 1999, LANDSCAPE ECOL, V14, P17 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 PAN DY, 1999, LANDSCAPE ECOL, V14, P35 PLOTNICK RE, 1993, LANDSCAPE ECOL, V8, P201 POOLE KG, 1997, J WILDLIFE MANAGE, V61, P497 QI Y, 1996, LANDSCAPE ECOL, V11, P39 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 RIJNSDORP AD, 1980, OECOLOGIA BERLIN, V45, P274 ROSENBERG DK, 1997, BIOSCIENCE, V47, P677 RUCKELSHAUS M, 1997, CONSERV BIOL, V11, P1298 SAKAI HF, 1997, J WILDLIFE MANAGE, V61, P343 SCHIPPERS P, 1996, ECOGRAPHY, V19, P97 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SKINNER CN, 1995, LANDSCAPE ECOL, V10, P219 TISCHENDORF L, 2000, LANDSCAPE ECOL, V15, P633 TRANI MK, 1999, FOREST ECOL MANAG, V114, P459 TRAUB B, 1999, FORSTWISS CENTRALBL, V118, P39 TRZCINSKI MK, 1999, ECOL APPL, V9, P586 TURCHIN P, 1991, ENVIRON ENTOMOL, V20, P955 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER SJ, 1991, QUANTITATIVE METHODS, P17 WALLIN H, 1988, OECOLOGIA, V77, P39 WEGNER J, 1990, BIOL CONSERV, V54, P263 WIENS JA, 1985, OIKOS, V45, P412 WIENS JA, 1997, OIKOS, V78, P257 WITH KA, 1995, ECOLOGY, V76, P2446 WITH KA, 1997, OIKOS, V78, P151 WITH KA, 1997, OIKOS, V79, P219 0921-2973 Landsc. Ecol.ISI:000168194400004zCarleton Univ, Ottawa Carleton Inst Biol, Ottawa, ON K1S 5B6, Canada. Tischendorf, L, Busestr 76, D-28213 Bremen, Germany.English^<7(Tischendorf, L. Bender, D. J. Fahrig, L.2003cEvaluation of patch isolation metrics in mosaic landscapes for specialist vs. generalist dispersers41-50Landscape Ecology181dispersal behaviour habitat fragmentation habitat loss matrix structure patch isolation CARABID BEETLES COLEOPTERA METAPOPULATION PERSISTENCE HABITAT DESTRUCTION PEROMYSCUS-LEUCOPUS CONNECTIVITY POPULATION MOVEMENTS MODEL FRAGMENTATION CONSERVATIONArticleJan We examined the effects of matrix structure and movement responses of organisms on the relationships between 7 patch isolation metrics and patch immigration. Our analysis was based on simulating movement behaviour of two generic disperser types (specialist and generalist) across mosaic landscapes containing three landcover types: habitat, hospitable matrix and inhospitable matrix. Movement, mortality and boundary crossing probabilities of simulated individuals were linked to the landcover and boundary types in the landscapes. The results indicated that area-based isolation metrics generally predict patch immigration more reliably than distance-based isolation metrics. Relationships between patch isolation metrics and patch immigration varied between the two generic disperser types and were affected by matrix composition or matrix fragmentation. Patch immigration was always affected by matrix composition but not by matrix fragmentation. Our results do not encourage the generic use of patch isolation metrics as a substitute for patch immigration, in particular in metapopulation models where generic use may result in wrong projections of the survival probability of metapopulations. However, our examination of the factors affecting the predictive potential of patch isolation metrics should facilitate interpretation and comparison of existing patch isolation studies. Future patch isolation studies should include information about landscape structure and the dispersal distance and dispersal behaviour of the organism of interest.://000181767500003 k ISI Document Delivery No.: 659FW Times Cited: 18 Cited Reference Count: 56 Cited References: *SAS I, 1990, SAS VERS 6 ADLER FR, 1994, THEOR POPUL BIOL, V45, P41 ANDREASSEN HP, 1996, J APPL ECOL, V33, P555 BAARS MA, 1979, OECOLOGIA, V44, P125 BAKOWSKI C, 1988, ACTA THERIOL, V33, P345 BEAUDETTE PD, 1992, CAN J ZOOL, V70, P693 BONNET X, 1999, BIOL CONSERV, V89, P39 BOYCE M, 1996, Q REV BIOL, V71, P167 CHARRIER S, 1997, AGR ECOSYST ENVIRON, V61, P133 COLLINS RJ, 1997, LANDSCAPE ECOL, V12, P63 DUELLI P, 1990, BIOL CONSERV, V54, P193 FAHRIG L, 1995, BIOL CONSERV, V73, P177 FAHRIG L, 1997, J WILDLIFE MANAGE, V61, P603 FAHRIG L, 1998, ECOL MODEL, V105, P273 FRAMPTON GK, 1995, BIOL CONSERV, V71, P347 GAINES MS, 1980, ANNU REV ECOL SYST, V11, P163 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GARRETT MG, 1988, J MAMMAL, V69, P236 HADDAD NM, 1999, AM NAT, V153, P215 HAEFNER JW, 1991, ECOL MODEL, V56, P221 HAIG SM, 1998, CONSERV BIOL, V12, P749 HANSKI I, 1991, BIOL J LINN SOC, V42, P2 HANSKI I, 1994, BIOL CONSERV, V68, P167 HANSKI I, 1994, J ANIM ECOL, V63, P151 HANSSON L, 1991, BIOL J LINN SOC, V42, P89 HENEIN K, 1990, LANDSCAPE ECOL, V4, P157 HESS GR, 1996, AM NAT, V148, P226 JOHANSEN A, 1994, PHYSICA D, V78, P186 KROHNE DT, 1984, AM MIDL NAT, V112, P146 KROHNE DT, 1987, HOLARCTIC ECOL, V10, P196 LEVINS R, 1969, B ENTOMOL SOC AM, V15, P237 LIDICKER WZ, 1975, SMALL MAMMALS THEIR, P103 LINDENMAYER DB, 1995, ECOL APPL, V5, P164 LINDENMAYER DB, 1995, ECOL MODEL, V82, P161 LINDENMAYER DB, 1996, LANDSCAPE ECOL, V11, P79 MACARTHUR RH, 1967, THEORY ISLAND BIOGEO MADER HJ, 1984, BIOL CONSERV, V29, P81 MADER HJ, 1990, BIOL CONSERV, V54, P209 MATTER SF, 1996, OECOLOGIA, V105, P447 MAUREMOOTO JR, 1995, AGR ECOSYST ENVIRON, V52, P141 MERRIAM G, 1989, LANDSCAPE ECOLOGY, V2, P277 MOILANEN A, 1995, J ANIM ECOL, V64, P141 POOLE KG, 1997, J WILDLIFE MANAGE, V61, P497 RIJNSDORP AD, 1980, OECOLOGIA BERLIN, V45, P274 ROSENBERG DK, 1997, BIOSCIENCE, V47, P677 SAKAI HF, 1997, J WILDLIFE MANAGE, V61, P343 SCHIPPERS P, 1996, ECOGRAPHY, V19, P97 SWART J, 1996, ECOL MODEL, V93, P57 TISCHENDORF L, 2000, LANDSCAPE ECOL, V15, P633 TISCHENDORF L, 2001, LANDSCAPE ECOL, V16, P235 VERBOOM J, 1991, OIKOS, V61, P149 WALLIN H, 1988, OECOLOGIA, V77, P39 WEGNER J, 1990, BIOL CONSERV, V54, P263 WIENS JA, 1985, OIKOS, V45, P412 WITH KA, 1997, CONSERV BIOL, V11, P1069 WITH KA, 1997, OIKOS, V78, P151 0921-2973 Landsc. Ecol.ISI:000181767500003Carleton Univ, Ottawa Carleton Inst Biol, Ottawa, ON K1S 5B6, Canada. Fahrig, L, Carleton Univ, Ottawa Carleton Inst Biol, Ottawa, ON K1S 5B6, Canada. lfahrig@ccs.carleton.caEnglishJ<7 Tischendorf, L. Fahrig, L.2000-How should we measure landscape connectivity?633-641Landscape Ecology157HEDGEROW NETWORK LANDSCAPE CARABID BEETLES COLEOPTERA HABITAT FRAGMENTATION PEROMYSCUS-LEUCOPUS HETEROGENEOUS LANDSCAPES ABAX-PARALLELEPIPEDUS CONSERVATION BIOLOGY POPULATION-DYNAMICS SMALL MAMMALS DISPERSALArticleOctlThe methods for measuring landscape connectivity have never been compared or tested for their responses to habitat fragmentation. We simulated movement, mortality and boundary reactions across a wide range of landscape structures to analyze the response of landscape connectivity measures to habitat fragmentation. Landscape connectivity was measured as either dispersal success or search time, based on immigration into all habitat patches in the landscape. Both measures indicated higher connectivity in more fragmented landscapes, a potential for problematic conclusions for conservation plans. We introduce cell immigration as a new measure for landscape connectivity. Cell immigration is the rate of immigration into equal-sized habitat cells in the landscape. It includes both within- and between-patch movement, and shows a negative response to habitat fragmentation. This complies with intuition and existing theoretical work. This method for measuring connectivity is highly robust to reductions in sample size (i.e., number of habitat cells included in the estimate), and we hypothesize that it therefore should be amenable to use in empirical studies. The connectivity measures were weakly correlated to each other and are therefore generally not comparable. We also tested immigration into a single patch as an index of connectivity by comparing it to cell immigration over the landscape. This is essentially a comparison between patch-scale and landscape-scale measurement, and revealed some potential for patch immigration to predict connectivity at the landscape scale. However, this relationship depends on the size of the single patch, the dispersal characteristics of the species, and the amount of habitat in the landscape. We conclude that the response of connectivity measures to habitat fragmentation should be understood before deriving conclusions for conservation management.://000089421500004 ISI Document Delivery No.: 356AV Times Cited: 48 Cited Reference Count: 46 Cited References: *STATS INC, 1995, STATISTICA WIND COMP ANDREASSEN HP, 1996, J APPL ECOL, V33, P555 BAARS MA, 1979, OECOLOGIA, V44, P125 CHARRIER S, 1997, AGR ECOSYST ENVIRON, V61, P133 COLLINS RJ, 1997, LANDSCAPE ECOL, V12, P63 DEMERS MN, 1995, CONSERV BIOL, V9, P1159 DIFFENDORFER JE, 1995, ECOLOGY, V76, P827 DOAK DF, 1992, THEOR POPUL BIOL, V41, P315 FAHRIG L, 1997, J WILDLIFE MANAGE, V61, P603 FAHRIG L, 1998, ECOL MODEL, V105, P273 FRAMPTON GK, 1995, BIOL CONSERV, V71, P347 GAINES MS, 1980, ANNU REV ECOL SYST, V11, P163 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GOODWIN BJ, 1998, ECOLOGICAL SCALE THE, P193 GREEN DG, 1994, PACIFIC CONSERVATION, V1, P194 HANSSON L, 1991, BIOL J LINN SOC, V42, P89 HENEIN K, 1990, LANDSCAPE ECOL, V4, P157 HOLMQUIST JG, 1998, OIKOS, V81, P558 KEITT TH, 1997, CONSERV ECOL, V1 KROHNE DT, 1984, AM MIDL NAT, V112, P146 KROHNE DT, 1985, CAN J ZOOL, V63, P71 KROHNE DT, 1987, HOLARCTIC ECOL, V10, P196 LIDICKER WZ, 1975, SMALL MAMMALS THEIR, P103 MADER HJ, 1984, BIOL CONSERV, V29, P81 MADER HJ, 1990, BIOL CONSERV, V54, P209 MATTER SF, 1996, OECOLOGIA, V105, P447 MCGARIGAL K, 1995, 351 PNW US FOR SERV MERRIAM G, 1989, LANDSCAPE ECOLOGY, V2, P227 METZGER JP, 1997, ACTA OECOL, V18, P1 PETIT S, 1998, AGR ECOSYST ENVIRON, V69, P243 PETIT S, 1998, CR ACAD SCI III-VIE, V321, P55 PITHER J, 1998, OIKOS, V83, P166 POOLE KG, 1997, J WILDLIFE MANAGE, V61, P497 RIJNSDORP AD, 1980, OECOLOGIA BERLIN, V45, P274 RUCKELSHAUS M, 1997, CONSERV BIOL, V11, P1298 SAKAI HF, 1997, J WILDLIFE MANAGE, V61, P343 SCHIPPERS P, 1996, ECOGRAPHY, V19, P97 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 TAYLOR PD, 1993, OIKOS, V68, P571 TISCHENDORF L, IN PRESS OIKOS TISCHENDORF L, 1997, ECOL MODEL, V103, P33 WALLIN H, 1988, OECOLOGIA, V77, P39 WIENS JA, 1997, OIKOS, V78, P257 WITH KA, 1997, CONSERV BIOL, V11, P1069 WITH KA, 1997, OIKOS, V78, P151 WITH KA, 1997, OIKOS, V79, P219 0921-2973 Landsc. Ecol.ISI:000089421500004zCarleton Univ, Ottawa Carleton Inst Biol, Ottawa, ON K1S 5B6, Canada. Tischendorf, L, Busestr 76, D-28213 Bremen, Germany.EnglishK۽7 Toman, Eric2013lSustainability as more than a buzzword: distilling the concept and developing tangible assessment approaches573-575Landscape Ecology283Springer Netherlands 2013/03/01+http://dx.doi.org/10.1007/s10980-013-9851-7 0921-2973Landscape Ecol10.1007/s10980-013-9851-7Englishڽ7 Tomaselli, Valeria Dimopoulos, Panayotis Marangi, Carmela Kallimanis, AthanasiosS Adamo, Maria Tarantino, Cristina Panitsa, Maria Terzi, Massimo Veronico, Giuseppe Lovergine, Francesco Nagendra, Harini Lucas, Richard Mairota, Paola Mücher, CasparA Blonda, Palma2013zTranslating land cover/land use classifications to habitat taxonomies for landscape monitoring: a Mediterranean assessment905-930Landscape Ecology285Springer NetherlandscMapping Land cover Land use Habitat Earth observation Taxonomies Natura 2000 Classification schemes 2013/05/01+http://dx.doi.org/10.1007/s10980-013-9863-3 0921-2973Landscape Ecol10.1007/s10980-013-9863-3EnglishG<7/Toms, J. D. Hannon, S. J. Schmiegelow, F. K. A.2005Population dynamics of songbirds in the boreal mixedwood forests of Alberta, Canada: Estimating minimum and maximum extents of spatial population synchrony543-553Landscape Ecology205body mass; boreal birds; boreal mixedwood forest; passeriformes; population dynamics; sampling design; spatial autocorrelation; spatial scale; temporal variation; territory size BUTTERFLY POPULATION; AUTOCORRELATION; SCALE; BIRDS; PATTERN; SIZE; TERRITORIES; DISPERSAL; ECOLOGY; MODELSArticleJulfEcological phenomena vary over space and time and interpretation of these processes also varies depending on the measurement scale. As the spatial scale of observation increases and decreases, changes in population abundance will likely exhibit alternating patterns of asynchrony and synchrony. While the study of how and why population dynamics change with spatial scale of measurement is intrinsically interesting, most population ecologists seek to study mechanisms of population change on a discrete study area. Our study develops methods that population ecologists can use to determine spatially appropriate sampling designs, and demonstrates how such spatial scales can be determined for 25 species of songbirds using long-term data from the boreal mixedwood forest of Alberta, Canada. To determine minimum scales of synchrony in population dynamics, we calculated the average correlation of changes in population abundance over time across different numbers of fixed-radius point-count samples. We then used a randomization test to remove the effect of number of replicates from the determination of appropriate spatial scale. The maximum extent of synchrony was estimated as the distance where population dynamics were no longer correlated. Estimates of the minimum scale of synchrony differed between species, ranging from 3.1 to 18.6 ha. The maximum scale of synchrony was estimated to be greater than or equal to 8 km for 14 of the 25 species examined, and to be greater than or equal to 70 km for Tennessee Warbler (Vermivora peregrina). Maximum spatial extents were significantly correlated with body mass and territory size.://000232205600004 G ISI Document Delivery No.: 969AK Times Cited: 0 Cited Reference Count: 60 Cited References: ALLEN TFH, 1982, HIERARCHY PERSPECTIV BEARD KH, 1999, CONSERV BIOL, V13, P1108 BJORNSTAD ON, 2001, ENVIRON ECOL STAT, V8, P53 BOWMAN J, 2002, ECOLOGY, V83, P2049 BRISKIE JV, 1994, BIRDS N AM, V99 BROWN JH, 1995, ECOLOGY, V76, P2028 CARLILE DW, 1989, LANDSCAPE ECOLOGY, V2, P203 CIMPRICH DA, 2000, BIRDS N AM, V527 DAWSON WR, 1997, BIRDS N AM, V280 FALLS JB, 1994, BIRDS N AM, V128 GARDALI T, 2000, BIRDS N AM, V551 GHALAMBOR CK, 1999, BIRDS N AM, V459 GREIGSMITH P, 1952, ANN BOT, V16, P293 HALL GA, 1994, BIRDS N AM, V136 HANNON SJ, 1993, BIRDS BOREAL FOREST, P127 HEJL SJ, 2002, BIRDS N AM, V623 HEJL SJ, 2002, BIRDS N AM, V669 HOLLING CS, 1992, ECOL MONOGR, V62, P447 HUDON J, 1999, BIRDS N AM, V432 HUNT PD, 1998, BIRDS N AM, V376 JAMES RD, 1998, BIRDS N AM, V379 KERSHAW KA, 1957, ECOLOGY, V38, P291 KOENIG WD, 1998, CONSERV BIOL, V12, P612 KOENIG WD, 2001, ECOLOGY, V82, P2636 LICHSTEIN JW, 2002, ECOL MONOGR, V72, P445 LOWTHER PE, 1999, BIRDS N AM, V454 MACK DE, 2000, BIRDS N AM, V540 MCARDLE BH, 1990, J ANIM ECOL, V59, P439 MEAD R, 1974, BIOMETRICS, V30, P295 MIDDLETON ALA, 1998, BIRDS N AM, V334 MORRIS RF, 1958, ECOLOGY, V39, P487 MORSE DH, 1993, BIRDS N AM, V55 MOSKAT C, 2000, ACTA ZOOL ACAD SCI H, V46, P19 MOSKOFF W, 1996, BIRDS N AM, V214 PARADIS E, 1999, ECOL LETT, V2, P114 PARADIS E, 2000, ECOLOGY, V81, P2112 PITOCHELLI J, 1993, BIRDS N AM, V72 PITOCHELLI J, 1997, BIRDS N AM, V320 QI Y, 1996, LANDSCAPE ECOL, V11, P39 RANTA E, 1995, P ROY SOC LOND B BIO, V262, P113 RANTA E, 1999, TRENDS ECOL EVOL, V14, P400 RIMMER CC, 1998, BIRDS N AM, V350 ROLAND J, 1997, NATURE, V386, P710 SCHMIEGELOW FKA, 1997, ECOLOGY, V78, P1914 SCHMIEGELOW FKA, 1999, FOREST FRAGMENTATION, P201 SCHOENER TW, 1968, ECOLOGY, V49, P123 SHERRY TW, 1979, AUK, V96, P265 SHERRY TW, 1985, HABITAT SELECTION BI, P283 SHERRY TW, 1997, BIRDS N AM, V277 SMITH SM, 1993, BIRDS N AM, V39 STEEN H, 1996, ECOLOGY, V77, P2365 SUTCLIFFE OL, 1996, J ANIM ECOL, V65, P85 THOMAS CD, 1991, OECOLOGIA, V87, P577 TOMS JD, 2004, THESIS U ALBERTA EDM TURNER MG, 2001, LANDSCAPE ECOLOGY TH VANHORN MA, 1994, BIRDS N AM, V88 WALTERS EL, 2002, BIRDS N AM, V662 WIEGERT RG, 1962, ECOLOGY, V43, P125 WIENS JA, 1989, FUNCT ECOL, V3, P385 WYATT VE, 2002, BIRDS N AM, V692 0921-2973 Landsc. Ecol.ISI:000232205600004Univ Alberta, Dept Biol Sci, Edmonton, AB T6G 2E9, Canada. Univ Alberta, Dept Renewable Resources, Edmonton, AB T6G 2H1, Canada. Toms, JD, Univ Waterloo, Dept Stat & Actuarial Sci, 200 Univ Ave W, Waterloo, ON N2L 3G1, Canada. jdtoms@math.uwaterloo.caEnglish.? Toth, R. E.1988CTheory and Language in Landscape Analysis, Planning, and Evaluation193-201Landscape Ecology14_Landscape ecology, landscape structure, landscape analysis, landscape planning theory, Paradigm4A soft paradigm for landscape analysis is presented. This paradigm focuses on the analysis of function first, and then on structure. The objective is to determine which factors are operationally significant, how these factors bring about change, and how they define the spatial characteristics of landscapes.|77 Trabaud, L. Galtie, J. F.1996oEffects of fire frequency on plant communities and landscape pattern in the Massif des Aspres (southern France)215-224Landscape Ecology114fire landscape diversity aspres southern france quercus ilex quercus suber national-park forest history vegetation ecosystems minnesota diversityAug`Fire frequency can affect pattern and diversity in plant communities and landscapes. We had the opportunity to study changes due to recurring wildfires on the same sites over a period of 50 years in the ''Massif des Aspres'' (southern France). The study was carried out in areas occupied by Quercus suber and Q. ilex series. A comparison of historical and cartographical documents (vegetation maps covering a 50 year interval and an accurate map of major wildfires during this period) allowed us to determine the changes occurring over time with or without fire action. Plant communities were grouped into three main vegetation types: forests, treed shrublands and shrublands. The passage of three successive wildfires on the same site led to a decrease in forest areas and an increase in shrublands; however, shrublands were already present before the first fire of the period under consideration. Less frequent fire occurrence induced more complex heterogeneity and greater landscape diversity. In the study region as a whole, with or without fire action, a significant decrease in forest surfaces was recorded, whereas there was an increase of unforested communities such as treed shrublands and shrublands. In some parts of the Massif fires increased the homogeneity of the landscape, in other parts they created a greater heterogeneity and diversity of plant communities.://A1996VC12700004.Vc127 Times Cited:23 Cited References Count:34 0921-2973ISI:A1996VC12700004VTrabaud, L Cnrs,Ctr Ecol Fonct & Evolut,Route Mende,Bp 5051,F-34033 Montpellier,FranceEnglishڽ7 MTrainor, AnneM Walters, JeffreyR Morris, WilliamF Sexton, Joseph Moody, Aaron2013aEmpirical estimation of dispersal resistance surfaces: a case study with red-cockaded woodpeckers755-767Landscape Ecology284Springer NetherlandsCNatal dispersal Picoides borealis Prospecting Radio-telemetry LiDAR 2013/04/01+http://dx.doi.org/10.1007/s10980-013-9861-5 0921-2973Landscape Ecol10.1007/s10980-013-9861-5English <7g'Tran, L. T. O'Neill, R. V. Smith, E. R.2006[A generalized distance measure for integrating multiple environmental assessment indicators469-476Landscape Ecology214nenvironmental quality indicators; Euclidean distance; multivariate analysis MID-ATLANTIC REGION; VULNERABILITYArticleMayThe paper presents a new distance measure useful for integrated environmental assessments. It is a generalized weighted Euclidean distance whose weights are calculated based on the coefficients of determination among environmental quality indicators in the data set. The proposed distance allows all environmental quality indicators to be used directly without any reduction in dimension (e.g., as in principal component analysis). Hypothetical and case-study examples are given to illustrate the distance measure. Examples demonstrate that the proposed distance is suitable and valuable for integrating multiple indicators into a single index, a common task in integrated environmental assessment.://000237487700001 ISI Document Delivery No.: 041WR Times Cited: 0 Cited Reference Count: 13 Cited References: *USGS, 1982, 878S USGS BOUGHTON DA, 1999, ECOSYST HEALTH, V5, P312 JONES KB, 1997, EPA600R97130 OFF RES LEGENDRE P, 1998, NUMERICAL ECOLOGY LOCANTORE NW, 2004, ENVIRON MONIT ASSESS, V94, P249 MEYER CD, 2000, MATRIX ANAL APPL LIN ONEILL RV, 1997, BIOSCIENCE, V47, P513 SCHOTT JR, 1997, MATRIX ANAL STAT SMITH ER, 2003, EPA600R03082 TRAN LT, 2002, ENVIRON MANAGE, V29, P845 TRAN LT, 2003, ENVIRON MANAGE, V31, P822 TRAN LT, 2004, ENVIRON MONIT ASSESS, V94, P263 WICKHAM JD, 1999, ENVIRON MANAGE, V24, P553 0921-2973 Landsc. Ecol.ISI:000237487700001Florida Atlantic Univ, Dept Geosci, Boca Raton, FL 33431 USA. TN & Associates, Oak Ridge, TN USA. US EPA, Off Res & Dev, Nat Exposure Res Lab, Res Triangle Pk, NC 27711 USA. Tran, LT, Florida Atlantic Univ, Dept Geosci, 777 Glades Rd, Boca Raton, FL 33431 USA. ltran@fau.eduEnglish ~?q6Treml, E. A. Halpin, P. N. Urban, D. L. Pratson, L. F.2008fModeling population connectivity by ocean currents, a graph-theoretic approach for marine conservation19-36Landscape Ecology23The dispersal of individuals among marine populations is of great importance to meta-population dynamics, population persistence, and species expansion. Understanding this connectivity between distant populations is key to their effective conservation and management. For many marine species, population connectivity is determined largely by ocean currents transporting larvae and juveniles between distant patches of suitable habitat. Recent work has focused on the biophysics of marine larval dispersal and its importance to population dynamics, although few studies have evaluated the spatial and temporal patterns of this potential dispersal. Here, we show how an Eulerian advection-diffusion approach can be used to model the dispersal of coral larvae between reefs throughout the Tropical Pacific. We illustrate how this connectivity can be analyzed using graph theory-an effective approach for exploring patterns in spatial connections, as well as for determining the importance of each site and pathway to local and regional connectivity. Results indicate that the scale (average distance) of dispersal in the Pacific is on the order of 50-150 km, consistent with recent studies in the Caribbean (Cowen, et al. 2006). Patterns in the dispersal graphs highlight pathways for larval dispersal along major ocean currents and through island chains. A series of critical island,stepping stones' are discovered providing potential pathways across the equatorial currents and connecting distant island groups. Patterns in these dispersal graphs highlight possible pathways for species expansions, reveal connected upstream/downstream populations, and suggest areas that might be prioritized for marine conservation efforts."://WOS:000252922800003 Times Cited: 0WOS:000252922800003(10.1007/s10980-007-9138-y|ISSN 0921-2973]<7Tress, G. Tress, B. Fry, G.2005=Clarifying integrative research concepts in landscape ecology479-493Landscape Ecology204!disciplines; epistemology; integrative research; interdisciplinarity; multidisciplinarity; research evaluation; transdisciplinarity MULTIFUNCTIONAL LANDSCAPES; AGRICULTURAL LANDSCAPES; CULTURAL LANDSCAPE; INTERDISCIPLINARITY; CHALLENGES; FRAMEWORK; BARRIERS; LAND; DISCIPLINARY; MANAGEMENTReviewMay5Integrative research approaches are intensely discussed in landscape ecology, in academia and in research policy. However, confusion over the terminology hampers communication. Many current landscape ecological research projects have difficulties to agree on a common understanding of the core concepts associated with different forms of integrative research. This is also evidenced by the lack of discussion of integrative research concepts in published papers. This hinders integration in research projects and makes the comparison and evaluation of the outcomes of different research concepts impossible. This paper discusses and defines the meanings of interdisciplinary and transdisciplinary ( integrative) research approaches to ease discourse on their application in landscape ecological research. It reviews definitions of the concepts found in the research literature and develops definitions of integrative and associated research concepts (disciplinarity, multidisciplinarity, interdisciplinarity and transdisciplinarity) based on their degree of disciplinary integration and involvement of non-academics. Integrative concepts are viewed as a continuum rather than as fixed categories. The paper discusses the need to develop integrative theory and methods and argues that we should be more explicit when using integrative research concepts in project proposals, project work and publications. Finally, the paper reflects on the ongoing discussion in landscape ecology concerning whether it is developing from an integrative research field towards a discipline in its own right.://000233035100009 qISI Document Delivery No.: 980RE Times Cited: 2 Cited Reference Count: 109 Cited References: *BMBF, 1996, FORD OK KONZ AGR RAH *BMWV KK, 1999, KULT B, V3 *CERI, 1972, INT PROBL TEACH RES *EUR COMM, 2001, 6 EU ENV ACT PROGR 2 *EUR COMM, 2002, SCI SOC ACT PLAN *FORSKN, 1994, MENN LANDSK BIOD FOR *FORSKN, 2002, MENN LANDSK BIOD 199 *IALE, 1998, IALE B, V16 *MRIT, 1995, RES PERSP WHIT PAP N *NWO, 2002, PROT DEV DUTCH ARCH AKINBAMI JFK, 2003, J ENVIRON MANAGE, V69, P115 ALROE HF, 2002, AGR HUM VALUES, V19, P3 ANTROP M, 2001, LANDSCAPE URBAN PLAN, V55, P163 ANTROP M, 2003, DELTA SERIES, V2, P44 BASTIAN O, 2002, LANDSCAPE ECOL, V16, P757 BETTINGER P, 2001, LANDSCAPE URBAN PLAN, V56, P107 BIERTER W, 1975, P INT M HUM EC, P325 BRANDT J, 1999, DANISH J GEOGRAPHY, V1, P21 BRANDT J, 2000, LANDSCAPE ECOL, V15, P181 BUCHECKER M, 2003, LANDSCAPE URBAN PLAN, V64, P29 BUREL F, 1995, LANDSCAPE URBAN PLAN, V33, P327 BUREL F, 2003, LANDSCAPE ECOLOGY CO BURGI M, 2001, LAND USE POLICY, V18, P9 BURLEY J, 2001, FOREST POLICY ECON, V2, P79 BURLEY JB, 1995, LANDSCAPE URBAN PLAN, V33, P195 CAPRA A, 2002, J CULT HERIT, V3, P93 CLEMETSEN M, 2000, AGR ECOSYST ENVIRON, V77, P125 CONRAD J, 2002, J TRANSDISCIPLINARY, V1, P15 DASCHKEIT A, 2001, HDB UMWELTWISSENSCHA, V7, P3 DECAMPS H, 2000, LANDSCAPE URBAN PLAN, V47, P105 DECAMPS H, 2001, LANDSCAPE URBAN PLAN, V57, P169 DEFILA R, 1998, ZWISCHEN FACHERN DIN, P111 DICASTRI F, 1986, GEOJOURNAL, V13, P299 DUNCKER E, 2001, SCI TECHNOL HUM VAL, V26, P349 ELIASSON I, 2000, LANDSCAPE URBAN PLAN, V48, P31 EWAN J, 2004, LANDSCAPE URBAN PLAN, V68, P53 EWEL KC, 2001, ECOSYSTEMS, V4, P716 FIELD DR, 2003, SOC NATUR RESOUR, V16, P349 FOHRER N, 2002, PHYS CHEM EARTH, V27, P655 FRANK R, 1988, WORDS R BURCHEFIELDS, P91 FRY GLA, IN PRESS KEY TOPICS FRY GLA, 2001, LANDSCAPE URBAN PLAN, V57, P159 GIBBONS M, 1994, NEW PRODUCTION KNOWL HABERL H, 2001, LAND USE POLICY, V18, P1 HABERLI R, 2001, TRANSDICIPLINARITY J, P6 HADAC E, 1977, LANDSCAPE PLAN, V4, P333 HOBBS R, 1997, LANDSCAPE URBAN PLAN, V37, P1 HOBBS RJ, 2002, INTEGRATING LANDSCAP, P412 HOCHTL F, 2005, LANDSCAPE URBAN PLAN, V70, P85 HOLL A, 1999, LANDSCAPE URBAN PLAN, V46, P15 HOLLAENDER K, 2003, DELTA SERIES, V2, P91 HOSTETLER M, 1999, LANDSCAPE URBAN PLAN, V45, P15 JAEGER J, 1998, GAIA, V7, P10 JAKOBSEN CH, 2004, FOREST POLICY ECON, V6, P15 JANTSCH E, 1970, POLICY SCI, V1, P403 JANTSCH E, 1972, PROBLEMS TEACHING RE, P97 JOHNSON CW, 1995, LANDSCAPE URBAN PLAN, V32, P219 KARLQVIST A, 1999, POLICY SCI, V32, P379 KEMMIS S, 2000, HDB QUALITATIVE RES, P567 KINZIG AP, 2001, ECOSYSTEMS, V4, P709 KLEIN JT, 1990, INTERDISCIPLINARITY KLEIN JT, 2001, TRANSDISCIPLINARITY, P35 KLIJN J, 2000, LANDSCAPE ECOLOGY LA LATTUCA LR, 2001, CREATING INTERDISCIP LAVERY I, 1996, LANDSCAPE URBAN PLAN, V35, P181 MANDER U, 2004, LANDSCAPE URBAN PLAN, V67, P1 MERCER N, 2000, WORDS MINDS WE USE L MITTELSTRASS J, 1993, INTERDISCIPLINARY SC, V18, P153 MITTELSTRASS J, 1996, BASLER SCHRIFTEN EUR, V22 MORAN J, 2002, INTERDISCIPLINARITY MOSS MR, 2000, LANDSCAPE ECOL, V15, P303 NASSAUER JI, 1995, LANDSCAPE ECOL, V10, P229 NAVEH Z, 1978, ENV ED PRINCIPLES ME, P149 NAVEH Z, 1984, LANDSCAPE ECOLOGY TH NAVEH Z, 1991, LANDSCAPE ECOL, V5, P65 NAVEH Z, 1994, LANDSCAPE ECOLOGY TH NAVEH Z, 1995, LANDSCAPE URBAN PLAN, V32, P43 NAVEH Z, 2000, LANDSCAPE URBAN PLAN, V50, P7 NAVEH Z, 2001, LANDSCAPE URBAN PLAN, V57, P269 NICOLINI M, 2001, FORSCHUNGSPROGRAM KU, V11 OPDAM P, 2002, LANDSCAPE ECOLOGY, V16, P767 PALANG H, 2000, LANDSCAPE URBAN PLAN, V50, P1 PETERSEIL J, 2004, LAND USE POLICY, V21, P307 PICKETT STA, 2004, LANDSCAPE URBAN PLAN, V69, P369 POIANI KA, 1998, LANDSCAPE URBAN PLAN, V43, P143 ROWE JS, 1997, ECOLOGIST, V27, P147 SANTELMANN MV, 2004, LANDSCAPE ECOL, V19, P357 SCHANZ H, 1999, FORSTWISS CENTRALBL, V118, P368 SCHULTZ AM, 1977, INTERDISCIPLINARITY SPANNER D, 2001, J ACAD LIBR, V27, P352 TREES B, 2005, LANDSCAPE URBAN PLAN, V70, P177 TRESS B, 2001, LANDSCAPE URBAN PLAN, V57, P137 TRESS B, 2002, DEV PERSPECTIVES LAN, P25 TRESS B, 2003, DELTA SERIES, V2, P182 TRESS G, 2003, DELTA SERIES, V3 VANASSCHE K, 2003, DELTA SERIES, V2, P100 VANASSELT MBA, 2002, GLOBAL ENVIRON CHANG, V12, P167 VANMANSVELT JD, 1997, AGR ECOSYST ENVIRON, V63, P233 VOS W, 1999, LANDSCAPE URBAN PLAN, V46, P3 WEINGART P, 1987, INTERDISZIPLINARITAT, P159 WEINGART P, 1997, ETHIK SOZIALWISSENSC, V8, P521 WIENS JA, 1992, LANDSCAPE ECOL, V7, P149 WIENS JA, 1999, ISSUES LANDSCAPE ECO, P148 WINDER N, 2003, DELTA SERIES, V2, P74 WRIGHT RL, 1987, LANDSCAPE ECOL, V1, P107 WU JG, 2002, LANDSCAPE ECOL, V17, P355 YOUNG GL, 1974, ADV ECOL RES, V8, P1 ZONNENVELD IS, 1995, LAND ECOLOGY INTRO L ZONNEVELD IS, 1988, LANDSCAPE ECOLOGY MA, P3 0921-2973 Landsc. Ecol.ISI:000233035100009Univ Wageningen & Res Ctr, Dept Environm Sci, Land Use Planning Grp, NL-6703 BJ Wageningen, Netherlands. Alterra Green World Res, Landscape Ctr, NL-6700 AA Wageningen, Netherlands. Agr Univ Norway, Dept Landscape Planning, N-1432 As, Norway. Tress, G, Univ Wageningen & Res Ctr, Dept Environm Sci, Land Use Planning Grp, Gen Foulkeseweg 13, NL-6703 BJ Wageningen, Netherlands. tress@tress.ccEnglish? Truax, Barry Barrett, Gary20119Soundscape in a context of acoustic and landscape ecology 1201-1207Landscape Ecology269Springer NetherlandsEarth and Environmental SciencecSoundscape ecology is being proposed as a new synthesis that leverages two important fields of study: landscape ecology and acoustic ecology. These fields have had a rich history. Running “in parallel” for over three decades now, soundscape ecology has the potential to unite these two (among other) fields in ways that provide new perspectives on the acoustics of landscapes. Each of us was involved in the “birth” of these two fields. We each reflect here on the rich history of landscape ecology and acoustic ecology and provide some thoughts on the future of soundscape ecology as a new perspective.+http://dx.doi.org/10.1007/s10980-011-9644-9 0921-297310.1007/s10980-011-9644-9ڽ7 -Trueman, Mandy Hobbs, RichardJ Niel, Kimberly2013WInterdisciplinary historical vegetation mapping for ecological restoration in Galapagos519-532Landscape Ecology283Springer NetherlandsVOral history Aerial photography Mapping uncertainty Reference ecosystems Heterogeneity 2013/03/01+http://dx.doi.org/10.1007/s10980-013-9854-4 0921-2973Landscape Ecol10.1007/s10980-013-9854-4English^? ZTrumbo, Daryl Burgett, Amber Hopkins, Robert Biro, Elizabeth Chase, Jonathan Knouft, Jason2012eIntegrating local breeding pond, landcover, and climate factors in predicting amphibian distributions 1183-1196Landscape Ecology278Springer NetherlandsBiomedical and Life SciencesSpecies distributions are influenced by many processes operating over varying spatial scales. The development of species distribution models (SDMs), also known as ecological niche models, has afforded the opportunity to predict the distributions of diverse taxa across broad geographic areas and identify variables that are potentially important in regulating these distributions. However, the integration of site-specific habitat data with broad scale climate and landcover data has received limited attention in an SDM framework. We investigate whether SDMs developed with breeding pond, landcover, and climate variables can accurately predict the distributions of nine pond-breeding amphibians in eastern Missouri, USA. Additionally we investigate the relative influences of each environmental variable on the distribution predictions for each study species, and whether the most influential variables are shared among multiple taxa. Boosted regression tree (BRT) SDMs were developed for each species with 38 abiotic and biotic environmental variables, including data from the breeding ponds, surrounding landcover, and climate. To test the models, field surveys were performed in 2007 and 2008 at 103 ponds for nine amphibian species. BRT models developed with breeding pond, landcover, and climate data accurately predicted the occurrences of six of nine species across the study area. Furthermore, the presence of each species was best predicted by a unique combination of environmental variables. Results also suggest that landcover and climate factors may be more influential for species near the edge of their geographic ranges, while local breeding pond factors may be more important for species nearer to the center of their ranges.+http://dx.doi.org/10.1007/s10980-012-9770-z 0921-297310.1007/s10980-012-9770-z7}?-Tubelis, D. P. Lindenmayer, D. B. Cowling, A.2007Bird populations in native forest patches in south-eastern Australia: the roles of patch width, matrix type (age) and matrix use 1045-1058Landscape Ecology227Aug://000248381900007 0921-2973ISI:000248381900007|?:;Tucker, David Gage, Stuart H. Williamson, Ian Fuller, Susan2014PLinking ecological condition and the soundscape in fragmented Australian forests745-758Landscape Ecology294AprNatural landscapes are increasingly subjected to anthropogenic pressure and fragmentation resulting in reduced ecological condition. In this study we examined the relationship between ecological condition and the soundscape in fragmented forest remnants of south-east Queensland, Australia. The region is noted for its high biodiversity value and increased pressure associated with habitat fragmentation and urbanisation. Ten sites defined by a distinct open eucalypt forest community dominated by spotted gum (Corymbia citriodora ssp. variegata) were stratified based on patch size and patch connectivity. Each site underwent a series of detailed vegetation condition and landscape assessments, together with bird surveys and acoustic analysis using relative soundscape power. Univariate and multivariate analyses indicated that the measurement of relative soundscape power reflects ecological condition and bird species richness, and is dependent on the extent of landscape fragmentation. We conclude that acoustic monitoring technologies provide a cost effective tool for measuring ecological condition, especially in conjunction with established field observations and recordings.!://WOS:000333533800015Times Cited: 1 0921-2973WOS:00033353380001510.1007/s10980-014-0015-1 <7_FTucker, K. Rushton, S. P. Sanderson, R. A. Martin, E. B. Blaiklock, J.1997NModelling bird distributions - a combined GIS and Bayesian rule-based approach77-93Landscape Ecology122vbirds; Bayes theorem; species distribution; habitat suitability model LAND-COVER MAP; SATELLITE IMAGERY; GREAT-BRITAINArticleAprModels to predict the breeding distribution of three species of birds in north-east England are described. The models use readily available data from the ornithological literature on the habitat preferences and life-history characteristics of the birds, together with satellite (land cover) and physiographic data. These data are linked via Bayesian decision-rules, and model predictions calculated at the landscape scale using a raster-based Geographic Information System. Log-linear regressions of the predicted suitability of the landscape for the birds with observed sets of nest records were statistically significant for all three species. The robustness of the models to the effects of nonindependence of predictor (habitat) variables on Bayesian predictions was investigated using a perturbation method, which gave minor improvements to the accuracy of the predictions. The value of this modelling approach as a method of utilising published autoecological data to predict the landscape distribution of birds is discussed.://A1997XQ45000002 ISI Document Delivery No.: XQ450 Times Cited: 25 Cited Reference Count: 42 Cited References: AITKIN M, 1989, STAT MODELLING GLIM ASPINALL P, 1983, CLIN INFLUENCES DECI, V13, P295 ASPINALL R, 1991, COMPUTER MODELLING E, P325 ASPINALL R, 1993, PHOTOGRAMM ENG REM S, V59, P537 AVERY MI, 1990, NATURE, V344, P860 BIBBY C, 1995, IBIS, V137, P247 BIBBY CJ, 1992, BIRD CENSUS TECHNIQU BONHAMCARTER GF, 1988, PHOTOGRAMM ENG REM S, V54, P1585 BONHAMCARTER GF, 1991, GEOGRAPHICAL INFORMA, V2, P171 CHERRILL AJ, 1995, BIOL CONSERV, V71, P313 CODY ML, 1985, HABITAT SELECTION BI CRAMP S, 1977, HDB BIRDS EUROPE MID, V1 EVANS D, 1992, HIST NATURE CONSERVA EYRE MD, 1992, LAND USE CHANGE CAUS, P131 FULLER RJ, 1982, BIRD HABITATS BRITAI FULLER RM, 1994, PHOTOGRAMM ENG REM S, V60, P553 GUTZWILLER KJ, 1992, LANDSCAPE ECOL, V6, P293 HASLETT JR, 1990, TRENDS ECOL EVOL, V5, P214 LACK P, 1986, ATLAS WINTERING BIRD LEE PM, 1989, BAYESIAN STAT INTRO LODWICK GS, 1966, J CHRON DIS, V194, P485 LUSTED LB, 1968, INTRO MED DECISION M MARCHANT J, 1990, POPULATION TRENDS BR MASON CF, 1976, BIRD STUDY, V23, P33 MCCULLAGH P, 1983, GENERALIZED LINEAR M PERRINS CM, 1979, BRIT TITS PERRINS CM, 1983, AVIAN ECOLOGY PHILLIPS LD, 1973, BAYESIAN STAT SOCIAL RADCLIFFE DA, 1976, BIRD STUDY, V23, P63 RUSHTON SP, 1992, LAND USE CHANGE CAUS, P111 RUSHTON SP, 1994, J APPL ECOL, V31, P313 RUSHTON SP, 1995, J ENV PLANNING MANAG, V3, P35 SHARROCK JTR, 1976, ATLAS BREEDING BIRDS SITTERS H, 1988, TETRAD ATLAS BREEDIN STROUD DA, 1987, BIRDS BOGS FORESTRY STROUD DA, 1990, BIRD STUDY, V37, P177 USHER MB, 1986, WILDLIFE CONSERVATIO WEBB T, 1987, N AM ADJACENT OCEANS WESTERVELT JM, 1990, N8722 CERL ADP WIENS JA, 1989, ECOLOGY BIRD COMMUNI WIENS JA, 1995, IBIS, V137, P97 YEE TW, 1991, J VEG SCI, V2, P587 0921-2973 Landsc. Ecol.ISI:A1997XQ45000002gUNIV NEWCASTLE UPON TYNE,CTR LAND USE & WATER RESOURCES RES,NEWCASTLE TYNE NE1 7RU,TYNE & WEAR,ENGLAND.EnglishL|?T JTulbure, Mirela G. Wimberly, Michael C. Roy, David P. Henebry, Geoffrey M.2011|Spatial and temporal heterogeneity of agricultural fires in the central United States in relation to land cover and land use211-224Landscape Ecology262FebAgricultural burning is an important land use practice in the central U.S. but has received little attention in the literature, whereas most of the focus has been on wildfires in forested areas. Given the effects that agricultural burning can have on biodiversity and emissions of greenhouse gasses, there is a need to quantify the spatial and temporal patterns of fire in agricultural landscapes of the central U.S. Three years (2006-2008) of the MODIS 1 km daily active fire product generated from the MODIS Terra and Aqua satellite data were used. The 2007 Cropland Data Layer developed by the U.S. Department of Agriculture was used to examine fire distribution by land cover/land use (LCLU) type. Global ordinary least square (OLS) models and local geographically weighted regression (GWR) analyses were used to explore spatial variability in relationships between fire detection density and LCLU classes. The monthly total number of fire detections peaked in April and the density of fire detections (number of fires/km(2)/3 years) was generally higher in areas dominated by agriculture than areas dominated by forest. Fire seasonality varied among areas dominated by different types of agriculture and land use. The effects of LCLU classes on fire detection density varied spatially, with grassland being the primary correlate of fire detection density in eastern Kansas; whereas wheat cropping was important in central Kansas, northeast North Dakota, and northwest Minnesota.!://WOS:000286474900005Times Cited: 0 0921-2973WOS:00028647490000510.1007/s10980-010-9548-0>|? )Turlure, C. Schtickzelle, N. Baguette, M.2010BResource grain scales mobility and adult morphology in butterflies95-108Landscape Ecology251Relations between species mobility and life history traits and/or landscape and habitat features are of broad interest to ecologists and conservation biologists. Here we investigated the reliability of the relations between mobility and (1) resource grain and (2) morphological traits in butterflies. Results were used to assess the biological realism of morphological traits associated with flight as mobility proxies. We then investigated how biological, environmental and landscape variables affected these mobility proxies. We used a multi-species approach on two different sites. Morphological traits were measured on ca. 20 individuals per site, species and sex. Resource distribution was carefully monitored by investigating the spatial distribution and overlap of larval and adult feeding resources, together representing the resource grain. The spatial extent of individual station keeping movements was estimated from distances recorded between successive recaptures of individuals from mark-release-recapture experiments. Morphological traits seemed reliable proxies of mobility, as both variables were strongly correlated. Morphological variations were related to flight type and spatial dimension of nectar resource. The most striking point was the clear relation between the index of relative investment in mobility versus fecundity in females with the spatial dimension of adult feeding resource. Given the generally accepted relation between abdomen volume and female fecundity, this suggests that females might invest more in fecundity when nectar resources are widespread. Finally, we did not detected effects of landscape structure on mobility, which indicates that functional grain of resources is more likely to influence mobility and evolution of morphology in butterflies than landscape connectivity.!://WOS:000273479100008Times Cited: 0 0921-2973WOS:00027347910000810.1007/s10980-009-9403-3<7)Turner, D. P. Cohen, W. B. Kennedy, R. E.2000oAlternative spatial resolutions and estimation of carbon flux over a managed forest landscape in Western Oregon441-452Landscape Ecology155carbon forest landscape scale net ecosystem production net primary production Oregon spatial resolution CONTERMINOUS UNITED-STATES PACIFIC-NORTHWEST TERRESTRIAL ECOSYSTEMS SATELLITE DATA BOREAL FOREST PROCESS MODEL SCALE VEGETATION BIOMASS REFLECTANCEArticleJul` Spatially-distributed estimates of biologically-driven CO2 flux are of interest in relation to understanding the global carbon cycle. Global coverage by satellite sensors offers an opportunity to assess terrestrial carbon (C) flux using a variety of approaches and corresponding spatial resolutions. An important consideration in evaluating the approaches concerns the scale of the spatial heterogeneity in land cover over the domain being studied. In the Pacific Northwest region of the United States, forests are highly fragmented with respect to stand age class and hence C flux. In this study, the effects of spatial resolution on estimates of total annual net primary production (NPP) and net ecosystem production (NEP) for a 96 km(2) area in the central Cascades Mountains of western Oregon were examined. The scaling approach was a simple 'measure and multiply' algorithm. At the highest spatial resolution (25 m), a stand age map derived from Landsat Thematic Mapper imagery provided the area for each of six forest age classes. The products of area for each age class and its respective NPP or NEP were summed for the area wide estimates. In order to evaluate potential errors at coarser resolutions, the stand age map was resampled to grain sizes of 100, 250, 500 and 1000 m using a majority filter reclassification. Local variance in near-infrared (NIR) band digital number at successively coarser grain sizes was also examined to characterize the scale of the heterogeneity in the scene. For this managed forest landscape, proportional estimation error in land cover classification at the coarsest resolution varied from -1.0 to +0.6 depending on the initial representation and the spatial distribution of the age class. The overall accuracy of the 1000 m resolution map was 42% with respect to the 25 m map. Analysis of local variance in NIR digital number suggested a patch size on the order of 100-500 m on a side. Total estimated NPP was 12% lower and total estimated NEP was 4% lower at 1000 m compared to 25 m. Carbon flux estimates based on quantifying differences in total biomass stored on the landscape at two points in time might be affected more strongly by a coarse resolution analysis because the differences among classes in biomass are more extreme than the differences in C flux and because the additional steps in the flux algorithm would contribute to error propagation. Scaling exercises involving reclassification of fine scale imagery over a range of grain sizes may be a useful screening tool for stratifying regions of the terrestrial surface relative to optimizing the spatial resolution for C flux estimation purposes.://000088036700004 j ISI Document Delivery No.: 331UH Times Cited: 13 Cited Reference Count: 64 Cited References: *UN, 1997, KYOT PROT UN FRAM CO *VEMAP PART, 1995, CYCLES, V9, P407 ASELMANN I, 1989, J ATMOS CHEM, V8, P307 BORMANN FH, 1979, PATTERN PROCESS FORE BOTKIN DB, 1990, BIOGEOCHEMISTRY, V9, P161 BOUWMAN AF, 1995, J GEOPHYS RES-ATMOS, V100, P2785 CAO C, 1997, SCALE REMOTE SENSING, P57 CIESZEWSKI CJ, 1996, SPATIAL ACCURACY ASS, P649 COHEN WB, 1995, INT J REMOTE SENS, V16, P721 COHEN WB, 1996, BIOSCIENCE, V46, P836 COHEN WB, 1998, PHOTOGRAMM ENG REM S, V64, P293 CROPPER WP, 1984, CAN J FOREST RES, V14, P855 DAVIS FW, 1991, PHOTOGRAMM ENG REM S, V57, P689 FARAJALLA NS, 1995, HYDROL PROCESS, V9, P55 FRANKLIN JF, 1990, NATURAL VEGETATION O FRANKLIN JF, 1991, WILDLIFE VEGETATION, P71 GHOLZ HL, 1985, CAN J FOREST RES, V15, P400 GRIER CC, 1977, ECOL MONOGR, V47, P373 GRIER CC, 1989, PNWGTR222 USDA FOR S HARMON ME, 1990, SCIENCE, V247, P699 HAYNES R, 1995, GTRRM259 USDA FOR SE HUNT ER, 1996, GLOBAL BIOGEOCHEM CY, V10, P431 JUSTICE CO, 1985, INT J REMOTE SENS, V6, P1271 JUSTICE CO, 1998, IEEE T GEOSCI REMOTE, V36, P1228 KAUPPI PE, 1992, SCIENCE, V256, P70 LOVELAND TR, 1991, PHOTOGRAMM ENG REM S, V57, P1453 MCGUIRE AD, 1992, GLOBAL BIOGEOCHEM CY, V6, P101 MILNE BT, 1993, SOME MATH QUESTIONS, P109 MOODY A, 1994, PHOTOGRAMM ENG REM S, V60, P585 MOODY A, 1995, LANDSCAPE ECOL, V10, P363 MYNENI RB, 1994, REMOTE SENS ENVIRON, V49, P200 NELSON R, 1986, INT J REMOTE SENS, V7, P429 OLSON R, 1996, GLOBAL CHANGE NEWSLE, P13 PAXLENNEY M, 1997, REMOTE SENS ENVIRON, V61, P210 PHILLIPS DL, UNPUB ERROR ANAL LAR PIERCE LL, 1995, LANDSCAPE ECOL, V10, P239 POTTER CS, 1993, GLOBAL BIOGEOCHEM CY, V7, P811 POWELL DS, 1993, RM234 USDA FOR SERV PRICE JC, 1995, REMOTE SENS ENVIRON, V52, P55 PRINCE SD, 1995, J BIOGEOGR, V22, P815 REICH PB, 1999, IN PRESS REMOTE SENS RILEY RH, 1997, INT J REMOTE SENS, V18, P121 ROBINSON JM, 1989, CLIMATIC CHANGE, V14, P243 RUIMY A, 1994, J GEOPHYS RES, V99, P5263 RUNNING SR, 1999, IN PRESS REMOTE SENS SCHIMEL DS, 1995, BIOGENIC TRACE GASES, P358 SCHIMEL DS, 1995, GLOBAL CHANGE BIOL, V1, P77 SCHIMEL DS, 1995, REMOTE SENS ENVIRON, V51, P49 SCHROEDER PE, 1995, FOREST ECOL MANAG, V75, P87 SELLERS PJ, 1987, REMOTE SENS ENVIRON, V21, P143 SPRUGEL DG, 1985, ECOLOGY NATURAL DIST, P335 STEYAERT LT, 1997, J GEOPHYS RES-ATMOS, V102, P29581 STONE TA, 1994, PHOTOGRAMM ENG REM S, V60, P541 TOWNSHEND JRG, 1988, INT J REMOTE SENS, V9, P187 TURNER DP, 1995, ECOL APPL, V5, P421 TURNER DP, 1996, ECOL MODEL, V90, P53 TURNER J, 1975, CAN J FOREST RES, V5, P681 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 VANCLEVE K, 1991, LONG TERM ECOLOGICAL VOGT K, 1991, TREE PHYSIOL, V9, P69 WALLIN DO, 1996, FOREST ECOL MANAG, V85, P291 WARING RH, 1979, SCIENCE, V204, P1380 WHITE JD, 1994, J VEG SCI, V5, P687 WOODCOCK CE, 1987, REMOTE SENS ENVIRON, V21, P311 0921-2973 Landsc. Ecol.ISI:000088036700004Oregon State Univ, Dept Forest Sci, Corvallis, OR 97331 USA. Turner, DP, Oregon State Univ, Dept Forest Sci, Peavy Hall 154, Corvallis, OR 97331 USA.Englishڽ7/Turner, MonicaG Donato, DanielC Romme, WilliamH2013zConsequences of spatial heterogeneity for ecosystem services in changing forest landscapes: priorities for future research 1081-1097Landscape Ecology286Springer NetherlandsSustainability Resilience Greater Yellowstone ecosystem Pacific Northwest Climate change Pinus contorta Pseudotsuga menziesii Fire Bark beetles Land use 2013/07/01+http://dx.doi.org/10.1007/s10980-012-9741-4 0921-2973Landscape Ecol10.1007/s10980-012-9741-4EnglishA<7Turner, M. D. Hiernaux, P.2002kThe use of herders' accounts to map livestock activities across agropastoral landscapes in semi-arid Africa367-385Landscape Ecology175GIS grazing ecology indigenous knowledge land use livestock distributions Niger pastoralism piosphere Sahel spatial modeling SAHELIAN WEST-AFRICA DAILY GRAZING ORBITS NUTRIENT AVAILABILITY SPATIAL-DISTRIBUTION SPECIES COMPOSITION FORAGING MODELS BURKINA-FASO LAND-USE PATTERNS RANGELANDSArticleOctTImproved understandings of the agricultural and range ecologies of semi-arid Africa require better information on the spatiotemporal distribution of domestic livestock across agropastoral landscapes. An empirical GIS-based approach was developed for estimating distributions of herded livestock across three agropastoral territories ( around 100 km(2) each) over a two-year period. Algorithms developed from regression analyses of herd tracking data (with R(2)s greater than or equal to 0.67) are used to transform a more comprehensive but incomplete set of data generated from herders' accounts of their herds' grazing itineraries ( 400 herds following 6500 itineraries). The resulting characterization registers 40 000 days of livestock activities across 694 land units ( averaging 70 ha) over the study period. This study demonstrates that rural producers' knowledge of their daily extraction practices can be translated to fine-grained characterizations of extraction densities across mixed landscapes. The spatiotemporal distribution of livestock that is revealed by this approach diverges strongly from that predicted by commonly-used point-diffusion estimation procedures. Instead, the distribution reflects local patterns of land use, topography, vegetation, settlements, and water points. Grazing and nongrazing times spent in land units are not spatially correlated and the seasonality of grazing pressure is spatially variable. Therefore, the ecological impacts of livestock grazing are spatially variable at fine scales and there is a significant potential for livestock-mediated nutrient transfers across agropastoral landscapes. The georeferenced data produced by this approach not only will help evaluate the impact and sustainability of different management practices but also provides a strong empirical base for improved spatial modeling of herded livestock.://000179388800001 ISI Document Delivery No.: 617YP Times Cited: 11 Cited Reference Count: 82 Cited References: ABEL NOJ, 1989, LAND DEGRAD REAHB, V1, P1 ANDREW MH, 1988, TRENDS ECOL EVOL, V3, P336 BAILEY DW, 1996, J RANGE MANAGE, V49, P386 BASSETT TJ, 1986, GEOGR REV, V76, P233 BATIONO A, 1991, ALLEVIATING SOIL FER, P217 BEAUVILAIN A, 1977, ETUDES NIGERIENNES I, V42 BENOIT M, 1979, TRAVAUX DOCUMENTS OR, V101 BONFIGLIOLI AM, 1982, NGAYNAKA HERDING ACC BOUDET G, 1972, ADANSONIA 2, V12, P505 BOURN D, 1994, 37A OV DEV I PAST DE BREMAN H, 1978, P 1 INT RANG C AM SO, P592 CISSE AM, 1986, DYNAMIQUE STRATE HER COPPOLILLO PB, 2000, HUM ECOL, V28, P527 COUGHENOUR MB, 1991, J RANGE MANAGE, V44, P530 DEBOER WF, 1989, HUM ECOL, V17, P445 DELEEUW PN, 1993, RANGE ECOLOGY DISEQU, P136 DELEEUW PN, 1995, LIVESTOCK SUSTAINABL, P371 DEVRIES FWT, 1982, PRODUCTIVITE PATURAG DIARRA L, 1995, LIVESTOCK SUSTAINABL, P99 DUGUE P, 1997, SOIL FERTILITY MANAG, P369 DUGUE P, 1998, AGR DEV, V18, P99 DUNNING JB, 1995, ECOL APPL, V5, P3 DUPIRE M, 1970, RECHERCHES SCI HUMAI, V32 DYSONHUDSON R, 1980, ANN REV ANTHOPOLOGY, V9, P15 ELLIS J, 1994, BIOSCIENCE, V44, P340 FRATKIN E, 1994, AFRICAN PASTORALIST GADO B, 1980, ETUDES NIGERIENNES I, V45 GALATY JG, 1991, HERDERS WARRIORS TRA GALLAIS J, 1975, PAYSANS PASTEURS GOU GUERIN H, 1986, CAHIERS RECHERCHE DE, V9, P60 HANAN NP, 1991, J APPL ECOL, V28, P173 HARRIS FMA, 1998, AGR ECOSYST ENVIRON, V71, P201 HAYWOOD M, 1980, 3 ILCA HEASLEY L, 1996, SOC NATUR RESOUR, V9, P31 HIERNAUX P, 1996, J APPL ECOL, V33, P387 HIERNAUX P, 1996, RANGELANDS SUSTAINAB, A HIERNAUX P, 1997, SOIL FERTILITY MANAG, P339 HIERNAUX P, 1998, PLANT ECOL, V138, P191 HIERNAUX P, 1999, J ARID ENVIRON, V41, P231 HOBBS NT, 1996, J WILDLIFE MANAGE, V60, P695 HOPEN C, 1958, PASTORAL FULBE FAMIL KILLANGA S, 1989, AFRICAN SMALL RUMINA, P86 KOYATE O, 1987, MEMOIRE FIN ETUDES I KROGH L, 1997, J ARID ENVIRON, V35, P147 LAMPREY HF, 1983, TROPICAL SAVANNAS, P643 LANDAIS E, 1993, CAHIERS AGR, V2, P9 LANGE RT, 1983, T ROYAL SOC S AUSTR, V107, P137 MCCOWN RL, 1979, AGR SEMIARID ENV, P297 MCINTIRE J, 1992, CROP LIVESTOCK INTER MCNAUGHTON SJ, 1988, NATURE, V334, P343 MICHEL JF, 1999, REV ELEV MED VET PAY, V52, P25 MIDDLETON N, 1997, WORLD ATLAS DESERTIF MOULIN CH, 1993, PERFORMANCES ANIMALE NIAMIR M, 1987, GRAZING INTENSITY EC NIAMIRFULLER M, 1999, MANAGING MOBILITY AF PEDEN DG, 1987, J RANGE MANAGE, V40, P67 PICKUP G, 1994, J APPL ECOL, V31, P231 PICKUP G, 1997, J APPL ECOL, V34, P657 PIERI C, 1992, FERTILITY SOILS FUTU POWELL JM, 1987, AGR SYST, V25, P261 POWELL JM, 1995, LIVESTOCK SUSTAINABL POWELL JM, 1996, AGR SYST, V52, P143 QUILFEN JP, 1983, AGRON TROP, V38, P206 REID RS, 1995, ECOL APPL, V5, P978 SCHLEICH K, 1986, REV ELEV MED VET PAY, V39, P97 SCOONES I, 1989, 28B OV DEV I PAST DE SENFT RL, 1983, J RANGE MANAGE, V36, P553 SENFT RL, 1987, BIOSCIENCE, V37, P789 SENFT RL, 1989, ECOL MODEL, V46, P283 SHI X, 1998, UNPUB ALGORITHM COMP STENNING DJ, 1960, CULTURES SOC AFRICA, P139 TAUPIN JD, 1998, WATER RESOURCES VARI, P141 TOLSMA DJ, 1987, J APPL ECOL, V24, P991 TURNER MD, 1995, LIVESTOCK SUSTAINABL, P435 TURNER MD, 1998, J BIOGEOGR, V25, P669 TURNER MD, 1998, J BIOGEOGR, V25, P683 TURNER MD, 1999, HUM ECOL, V27, P267 TURNER MD, 1999, J ARID ENVIRON, V41, P277 VALENTIN C, 1985, SOIL EROSION CONSERV, P51 VALENZA J, 1981, REV ELEV MED VET PAY, V34, P83 VANKEULEN H, 1990, AGR ECOSYST ENVIRON, V32, P177 WEST LT, 1984, SOIL SURVEY ICRISAT 0921-2973 Landsc. Ecol.ISI:000179388800001Univ Wisconsin, Dept Geog, Madison, WI 53706 USA. Turner, MD, Univ Wisconsin, Dept Geog, 384 Sci Hall,550 Pk St, Madison, WI 53706 USA.English? Turner, M.G.1987WSpatial Simulation of Landscape Changes in Georgia: A Comparison of 3 Transition Models29-36Landscape Ecology11?Land use, Fractal dimension, Spatial model, Simulation, Georgia)Spatial simulation models were developed to predict temporal changes in land use patterns in a Piedmont county in Georgia (USA). Five land use categories were included: urban, cropland, abandoned cropland, pasture, and forest. Land use data were obtained from historical aerial photography and digitized into a matrix based on a 1 ha grid cell format. Three different types of spatial simulation were compared: (1) random simulations based solely on transition probabilities; (2) spatial simulations in which the four nearest neighbors (adjacent cells only) influence transitions; and (3) spatial simulations in which the eight nearest neighbors (adjacent and diagonal cells) influence transitions. Models and data were compared using the mean number and size of patches, fractal dimension of patches, and amount of edge between land uses. The random model simulated a highly fragmented landscape having numerous, small patches with relatively complex shapes. The two versions of the spatial model simulated cropland well, but simulated patches of forest and abandoned cropland were fewer, larger, and more simple than those in the real landscape. Several possible modifications of model structure are proposed. The modeling approach presented here is a potentially general one for simulating human-influenced landscapes.@? Turner, M.G.19903Spatial and temporal analysis of landscape patterns21-30Landscape Ecology41@GIS, spatial pattern analysis, scale, neutral model, disturbancevA variety of ecological questions now require the study of large regions and the understanding of spatial heterogeneity. Methods for spatial-temporal analyses are becoming increasingly important for ecological studies. A grid cell based spatial analysis program (SPAN) is described and results of landscape pattern analysis using SPAN are presentedd. Several ecological topics in which geographic information systems (GIS) can play an important role (landscape pattern analysis, neutral models of pattern and process, and extrapolation across spatial scales) are reviewed. To study the relationship between observed landscape patterns and ecological processes, a neutral model approach is recommended. For example, the expected pattern (i.e., neutral model) of the spread of disturbance across a landscape can be generated and then tested using actual landz scape data that are stored in a GE. Observed spatial or temporal patterns in ecological data may also be influenced by scale. Creating a spatial data base frequently requires integrating data at different scales. Spatial scale is shown to influence landscape pattern analyses, but extrapolation of data across spatial scales may be possible if the grain and extent of the data are specified. The continued development and testing of new methods for spatial-temporal analysis will contribute to a general understanding of landscape dynamics.<7_Turner, M. G. Barrett, G. W. Gardner, R. H. Iverson, L. R. Risser, P. G. Wiens, J. A. Wu, J. G.2007)In memoriam - Frank B. Golley (1930-2006)1-3Landscape Ecology221Biographical-ItemJan://000243619800001 |ISI Document Delivery No.: 127XO Times Cited: 0 Cited Reference Count: 1 Cited References: GOLLEY FB, PUBLICATION LIST 0921-2973 Landsc. Ecol.ISI:000243619800001Univ Wisconsin, Dept Zool, Madison, WI USA. Univ Georgia, Inst Ecol, Athens, GA 30602 USA. Univ Maryland, Ctr Environm Sci, Appalachian Lab, Frostburg, MD USA. USDA, Forest Serv, Deleware, OH USA. Oklahoma State Univ, Oklahoma City, OK USA. Nature Conservancy, Washington, DC USA. Arizona State Univ, Sch Life Sci, Tempe, AZ 85287 USA. Arizona State Univ, Global Inst Sustainabil, Tempe, AZ 85287 USA. Turner, MG, Univ Wisconsin, Dept Zool, Madison, WI USA. turnermg@wisc.eduEnglish?(Turner, M. G. Dale, V. H. Gardner, R. H.19898Predicting across scales: Theory development and testing245-252Landscape Ecology33/4Vlandscape ecology, spatial scale, temporal scale, grain, extent, extrapolation, models~Landscape ecologists deal with processes that occur at a variety of temporal and spatial scales. The ability to make predictions at more than one level of resolution requires identification of the processes of interest and parameters that affect this process at different scales, the development of rules to translate information across scales, and the ability to test these predictions at the relevant spatial and temporal scales. This paper synthesizes discussions from a workshop on ‘Predicting Across Scales: Theory Development and Testing’ that was held to discuss current research on scaling and to identify key research issues. ?>Turner, M. G. O'Neill, R. V. Gardner, R. H. Milne, B. T.1989FEffects of changing spatial scale on the analysis of landscape pattern153-162Landscape Ecology33/4mSpatial scale, Grain, Extent, Resolution, Landscape ecology, Diversity, dominance, Contagion, Spatial patternThe purpose of this study was to observe the effects of changing the grain (the first level of spatial resolution possible with a given data set) and extent (the total area of the study) of landscape data on observed spatial patterns and to identify some general rules for comparing measures obtained at different scales. Simple random maps, maps with contagion (i.e., clusters of the same land cover type), and actual landscape data from USGS land use (LUDA) data maps were used in the analyses. Landscape patterns were compared using indices measuring diversity (H), dominance (D) and contagion (C). Rare land cover types were lost as grain became coarser. This loss could be predicted analytically for random maps with two land cover types, and it was observed in actual landscapes as grain was increased experimentally. However, the rate of loss was influenced by the spatial pattern. Land cover types that were clumped disappeared slowly or were retained with increasing grain, whereas cover types that were dispersed were lost rapidly. The diversity index decreased linearly with increasing grain size, but dominance and contagion did not show a linear relationship. The indices D and C increased with increasing extent, but Hexhibited a variable response. The indices were sensitive to the number (m) of cover types observed in the data set and the fraction of the landscape occupied by each cover type (Pk); both m and Pk varied with grain and extent. Qualitative and quantitative changes in measurements across spatial scales will differ depending on how scale is defined. Characterizing the relationships between ecological measurements and the grain or extent of the data may make it possible to predict or correct for the loss of information with changes in spatial scale.<7i4Turner, M. G. Pearson, S. M. Bolstad, P. Wear, D. N.2003qEffects of land-cover change on spatial pattern of forest communities in the Southern Appalachian Mountains (USA)449-464Landscape Ecology185building density forest communities land-cover change land-use change landscape change southern appalachians spatial analysis CENTRAL NEW-ENGLAND ECOLOGICAL PRINCIPLES LANDSCAPE PATTERNS NATURE CONSERVANCY OLYMPIC PENINSULA WATER-QUALITY PATCH-SIZE BIODIVERSITY VEGETATION DYNAMICSArticleTUnderstanding the implications of past, present and future patterns of human land use for biodiversity and ecosystem function is increasingly important in landscape ecology. We examined effects of land-use change on four major forest communities of the Southern Appalachian Mountains (USA), and addressed two questions: (1) Are forest communities differentially susceptible to loss and fragmentation due to human land use? (2) Which forest communities are most likely to be affected by projected future land cover changes? In four study landscapes, maps of forest cover for four time periods (1950, 1970, 1990, and projections for 2030) were combined with maps of potential forest types to measure changes in the extent and spatial pattern of northern hardwoods, cove hardwoods, mixed hardwoods, and oak-pine. Overall, forest cover increased and forest fragmentation declined in all four study areas between 1950 and 1990. Among forest community types, cove hardwoods and oak-pine communities were most affected by land-cover change. Relative to its potential, cove hardwoods occupied only 30-40% of its potential area in two study landscapes in the 1950s, and oak-pine occupied similar to 50% of its potential area; cove hardwoods remained reduced in extent and number of patches in the 1990s. Changes in northern hardwoods, which are restricted to high elevations and occur in small patches, were minimal. Mixed hardwoods were the dominant and most highly connected forest community type, occupying between 47 and 70% of each study area. Projected land-cover changes suggest ongoing reforestation in less populated regions but declining forest cover in rapidly developing areas. Building density in forest habitats also increased during the study period and is projected to increase in the future; cove hardwoods and northern hardwoods may be particularly vulnerable. Although increases in forest cover will provide additional habitat for native species, increases in building density within forests may offset some of these gains. Species-rich cove hardwood communities are likely to be most vulnerable to future land-use change.://000185827200001 ISI Document Delivery No.: 730JG Times Cited: 10 Cited Reference Count: 77 Cited References: *SAMAB, 1996, 4 USDA FOR SERV SAMA ANTROP M, 2000, LANDSCAPE ECOL, V15, P257 ASKINS RA, 1990, CURRENT ORNITHOLOGY, V7, P1 BERNHARDSEN T, 1992, GEOGRAPHIC INFORMATI BOLGER DT, 1997, CONSERV BIOL, V11, P406 BOLSTAD PV, 1998, LANDSCAPE ECOL, V13, P271 BOUMA J, 1998, AGR ECOSYST ENVIRON, V67, P103 BRAUN EL, 1950, DECIDUOUS FORESTS E COOPERRIDER A, 1999, ECOLOGICAL STEWARDSH, P604 DALE VH, 1994, CONSERV BIOL, V8, P1027 DALE VH, 2000, ECOL APPL, V10, P639 DAY FP, 1974, ECOLOGY, V34, P329 DAY FP, 1988, FOREST HYDROLOGY ECO DETENBECK NE, 1993, LANDSCAPE ECOL, V8, P39 DUERKSEN CJ, 1997, 470471 AM PLAN ASS P DUFFY DC, 1992, CONSERV BIOL, V6, P196 DUPOUEY JL, 2002, ECOLOGY, V83, P2978 ELLER RD, 1982, MINERS MILLHANDS MOU FOSTER DR, 1992, J ECOL, V80, P753 FOSTER DR, 1998, ECOSYSTEMS, V1, P497 FOSTER DR, 1999, ECOL APPL, V9, P555 FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 FRANKLIN JF, 1993, ECOL APPL, V3, P202 FRIESEN LE, 1995, CONSERV BIOL, V9, P1408 FULLER TL, 1998, ECOSYSTEMS, V1, P76 HANSEN AJ, 1993, ECOL APPL, V3, P481 HANSEN AJ, 1995, ECOL APPL, V5, P555 HARDING JS, 1998, P NATL ACAD SCI USA, V95, P14843 HARRISON RL, 1997, J WILDLIFE MANAGE, V61, P112 HUNTER ML, 1991, BALANCING BRINK EXTI, P266 JOHNSON LB, 1997, FRESHWATER BIOL, V37, P209 JONGMAN RHG, 2002, LANDSCAPE URBAN PLAN, V58, P211 LEE RG, 1992, NEW PERSPECTIVES WAT, P499 LI H, 1993, LANDSCAPE ECOL, V8, P63 LILLESAND TM, 1994, REMOTE SENSING IMAGE LUCY WH, 1997, LANDSCAPE URBAN PLAN, V36, P259 MACDONALD D, 2000, J ENVIRON MANAGE, V59, P47 MATLACK GR, 1994, ECOLOGY, V75, P1491 MATLACK GR, 1997, J BIOGEOGR, V24, P297 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MCNAB WH, 1989, FOREST SCI, V35, P91 MILLER JN, 1997, LANDSCAPE ECOL, V12, P137 MITCHELL CE, 2002, ECOL APPL, V12, P1364 MOTZKIN G, 1996, ECOL MONOGR, V66, P345 NOSS RF, 1987, BIOL CONSERV, V41, P11 ODELL EA, 2001, CONSERV BIOL, V15, P1143 PEARSON SM, 1998, CASTANEA, V63, P382 PEARSON SM, 1999, ECOL APPL, V9, P1288 PHILLIPS DL, 1990, ECOLOGY, V71, P204 POIANI KA, 1998, LANDSCAPE URBAN PLAN, V43, P143 RADELOFF VC, 2000, SOC NATUR RESOUR, V13, P599 RADELOFF VC, 2001, FOREST SCI, V47, P229 REID WV, 2001, ENVIRONMENT, V43, P20 RICHARDS C, 1996, CAN J FISH AQUAT S1, V53, P295 RUTLEDGE D, 1995, THESIS U TENNESSEE K SCHNAIBERG J, 2002, ENVIRON MANAGE, V30, P24 SINCLAIR ARE, 1995, ECOL APPL, V5, P579 SKOLE DL, 1994, BIOSCIENCE, V44, P314 SORANNO PA, 1996, ECOL APPL, V6, P865 TUCKER K, 1997, LANDSCAPE ECOL, V12, P77 TURNER BL, 1994, AMBIO, V23, P91 TURNER MG, 1990, PHOTOGRAMM ENG REM S, V56, P379 TURNER MG, 1996, ECOL APPL, V6, P1150 TURNER MG, 1998, STATUS TRENDS OUR NA, V1, P37 VANDVIK V, 2002, PLANT ECOL, V162, P233 VOGEL WO, 1989, WILDLIFE SOC B, V17, P406 WALLIN DO, 1994, ECOL APPL, V4, P569 WEAR DN, 1993, NATURAL RESOURCE MOD, V7, P379 WEAR DN, 1996, ECOL APPL, V6, P1173 WEAR DN, 1998, ECOL APPL, V8, P619 WEAR DN, 1998, ECOSYSTEMS, V1, P575 WHITE D, 1997, CONSERV BIOL, V11, P349 WHITTAKER RH, 1952, ECOL MONOGR, V22, P1 WHITTAKER RH, 1956, ECOL MONOGR, V26, P1 WILLIAMS M, 1989, AM THEIR FORESTS HIS WOLF PR, 1983, ELEMENTS PHOTOGRAMME ZIPPERER WC, 2000, ECOL APPL, V10, P685 0921-2973 Landsc. Ecol.ISI:000185827200001Univ Wisconsin, Dept Zool, Madison, WI 53706 USA. Mars Hill Coll, Dept Biol, Mars Hill, NC 28754 USA. Univ Minnesota, Dept Forest Resources, St Paul, MN 55108 USA. US Forest Serv, USDA, Res Triangle Pk, NC 27709 USA. Turner, MG, Univ Wisconsin, Dept Zool, Madison, WI 53706 USA.English <7Turner, M. G. Romme, W. H.1994+Landscape dynamics in crown fire ecosystems59-77Landscape Ecology913CROWN FIRE; PATCH MOSAIC; FIRE MODELS; FIRE REGIMESReviewMarCrown fires create broad-scale patterns in vegetation by producing a patch mosaic of stand age classes, but the spread and behavior of crown fires also may be constrained by spatial patterns in terrain and fuels across the landscape. In this review, we address the implications of landscape heterogeneity for crown fire behavior and the ecological effects of crown fires over large areas. We suggest that fine-scale mechanisms of fire spread can be extrapolated to make broad-scale predictions of landscape pattern by coupling the knowledge obtained from mechanistic and empirical fire behavior models with spatially-explicit probabilistic models of fire spread. Climatic conditions exert a dominant control over crown fire behavior and spread, but topographic and physiographic features in the landscape and the spatial arrangement and types of fuels have a strong influence on fire spread, especially when burning conditions (e.g., fuel moisture and wind) are not extreme. General trends in crown fire regimes and stand age class distributions can be observed across continental, latitudinal, and elevational gradients. Crown fires are more frequent in regions having more frequent and/or severe droughts, and younger stands tend to dominate these landscapes. Landscapes dominated by crown fires appear to be nonequilibrium systems. This nonequilibrium condition presents a significant challenge to land managers, particularly when the implications of potential changes in the global climate are considered. Potential changes in the global climate may alter not only the frequency of crown fires but also their severity. Crown fires rarely consume the entire forest, and the spatial heterogeneity of burn severity patterns creates a wide range of local effects and is likely to influence plant reestablishment as well as many other ecological processes. Increased knowledge of ecological processes at regional scales and the effects of landscape pattern on fire dynamics should provide insight into our understanding of the behavior and consequences of crown fires.://A1994NC71800006 JISI Document Delivery No.: NC718 Times Cited: 131 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1994NC71800006CTURNER, MG, OAK RIDGE NATL LAB,DIV ENVIRONM SCI,OAK RIDGE,TN 37831.EnglishZ?7ITurner, M. G. Romme, W. H. Gardner, R. H. O'Neill, R. V. Kratz, T. K.1993ZA revised concept of landscape equilibrium: Disturbance and stability on scaled landscapes213-227Landscape Ecology83<disturbance, landscape equilibrium, landscape ecology, scale |7 DTurner, M. G. Romme, W. H. Gardner, R. H. Oneill, R. V. Kratz, T. K.1993[A Revised Concept of Landscape Equilibrium - Disturbance and Stability on Scaled Landscapes213-227Landscape Ecology839disturbance landscape equilibrium landscape ecology scaleSepTemporal and spatial scales of disturbance and recovery are often confounded in discussions of landscape equilibrium. We developed a broad framework for the description of landscapes that separates the spatial and temporal scales of disturbance and recovery and predicts the resultant dynamics of a landscape. Two key parameters representing time and space are used to describe potential disturbance dynamics. The temporal parameter, T, is the ratio of the disturbance interval (i.e., time between successive disturbance events) to the time required for a disturbed site to recover to a mature stage. The spatial parameter, S, is the ratio of the size of the disturbance to the size of the landscape. The use of ratios in both parameters permits the comparison of landscapes across a range of spatial and temporal scales. A simple simulation model was developed to explore the implications of various combinations of S and T. For any single simulation, disturbances of a fixed size are imposed at random locations on a gridded landscape at specified intervals. Disturbed sites recover deterministically through succession. Where disturbance interval is long relative to recovery time and a small proportion of the landscape is affected, the system is stable and exhibits low variance over time (e.g., northeastern hardwood forests). These are traditional ''equilibrium'' systems. Where disturbance interval is comparable to recovery interval and a large proportion of the landscape is affected, the system is stable but exhibits large variance (e.g., subalpine forests in Yellowstone Park). Where disturbance interval becomes much shorter than recovery time and a large proportion of the landscape is affected, the system may become unstable and shift into a different trajectory (e.g., arid ecosystems with altered fire regimes). This framework permits the prediction of disturbance conditions that lead to qualitatively different landscape dynamics and demonstrates the scale-dependent nature of concepts of landscape equilibrium.://A1993MB34000007.Mb340 Times Cited:129 Cited References Count:0 0921-2973ISI:A1993MB34000007JTurner, Mg Oak Ridge Natl Lab,Div Environm Sci,Pob 2008,Oak Ridge,Tn 37831English<7x4Turner, M. G. Romme, W. H. Reed, R. A. Tuskan, G. A.2003KPost-fire aspen seedling recruitment across the Yellowstone (USA) Landscape127-140Landscape Ecology182%fire ecology landscape ecology logistic regression Northern Rocky Mountains population dynamics Populus tremuloides spatial extrapolation spatial heterogeneity COMMUNITIES FOLLOWING FIRE NATIONAL-PARK POPULUS-TREMULOIDES CLIMATE-CHANGE EARLY SUCCESSION HABITAT USE FORESTS ELK DIVERSITY WINTERArticleLandscape patterns of quaking aspen (Populus tremuloides) seedling occurrence and abundance were studied after a rare recruitment event following the 1988 fires in Yellowstone National Park, Wyoming, USA. Belt transects (1 to 17 km in length, 4 m width) along 18 foot trails were surveyed for aspen seedlings on the subalpine plateau of the Park, along gradients of elevation and geologic substrate, during the summer of 1996. Aspen seedling presence and density were characterized as a function of elevation, geologic substrate, slope, aspect, vegetation/ cover type, presence of burned forest, and distance to nearest adult aspen stand. Presence of aspen seedlings was best predicted by the incidence of burned forest and proximity to adult aspen; aspen seedlings were only found in burned forest and were more likely to occur closer to adult aspen clones. When tested against independent data collected in 1997, the logistic regression model for aspen seedling presence performed well ( overall accuracy = 73%, Tau(p) = 0.41). When present, variation in aspen seedling density at local scales (less than or equal to 200 m) was largely explained by elevation, with higher densities observed at lower elevations. At broad scales (> 1 km), seedling density was a function of cover type, elevation, aspect, slope, and burn severity, with greater seedling density in more severely burned forested habitats on southerly, shallow slopes at lower elevations. Aspen seedling densities ranged from 0 to 46,000 seedlings/ha with a median density of 2,000/ha on sites where they occurred. Aspen seedlings were most abundant in the south central and southwest central regions of the park, approximately an order of magnitude less abundant in the southeast region, and nearly absent in the north central area. Establishment of new aspen stands on Yellowstone's subalpine plateau would represent a substantial change in the landscape. However, the long-term fate of these postfire aspen seedlings is not known.://000183770300003 ISI Document Delivery No.: 694JB Times Cited: 10 Cited Reference Count: 64 Cited References: *SAS I INC, 1989, SAS STAT US GUID VER *US GEOL SURV, 1972, GEOL MAP YELL NAT PA *USA CERL, 1993, GRASS 4 1 US REF MAN BAKER FS, 1925, USDA B, V1291 BAKER WL, 1997, ECOGRAPHY, V20, P155 BALLING RC, 1992, CLIMATIC CHANGE, V22, P35 BARNES BV, 1966, ECOLOGY, V47, P439 BARTLEIN PJ, 1997, CONSERV BIOL, V11, P782 BARTOS DL, 1981, J RANGE MANAGE, V34, P315 BARTOS DL, 1994, J RANGE MANAGE, V47, P79 BOUYCE MS, 1989, JACKSON ELK HERD INT BOYCE MS, 1988, P TALL TIMB FIR EC C, V17, P121 CHRISTENSEN NL, 1989, BIOSCIENCE, V39, P678 CRAWFORD HJ, 1998, INT J PSYCHOPHYSIOL, V30, P197 DALE VH, 2001, BIOSCIENCE, V51, P723 DEBYLE NV, 1985, ASPEN ECOLOGY MANAGE, P115 DEBYLE NV, 1985, ASPEN ECOLOGY MANAGE, P135 DESPAIN DG, 1991, YELLOWSTONE VEGETATI EINSPAHR DW, 1976, WO25 USDA FOR SERV ERIKSSON O, 1992, OIKOS, V63, P439 ERWIN EA, 2001, AM MIDL NAT, V145, P299 FOWELLS HA, 1965, USDA AGR HDB, V271 GRAHAM RL, 1990, BIOSCIENCE, V40, P575 HINDS TE, 1985, ASPEN ECOLOGY MANAGE, P87 HOBBS NT, 1984, J WILDLIFE MANAGE, V48, P551 HOUSTON DB, 1982, NO YELLOWSTONE ELK JELINSKI DE, 1992, AM J BOT, V79, P728 JONES JR, 1974, RM122 USDA FOR SERV KALCOUNIS MC, 1998, J WILDLIFE MANAGE, V62, P603 KALUZNY SP, 1998, S PLUS SPATIAL STATS KAY CE, 1990, THESIS UTAH STATE U KAY CE, 1993, NORTHWEST SCI, V67, P94 KAY CE, 1997, CAN FIELD NAT, V111, P607 KAY CE, 2000, J RANGE MANAGE, V53, P145 KREBILL RG, 1972, INT129 USDA FOR SERV LOOPE LL, 1973, QUATERNARY RES, V3, P425 LOOSE SS, 1995, J FIELD ORNITHOL, V66, P503 MA ZK, 1995, PHOTOGRAMM ENG REM S, V61, P435 MARTNER BE, 1986, WYOMING CLIMATE ATLA MCDONOUGH WT, 1985, ASPEN ECOLOGY MANAGE, P25 MOSS EH, 1938, BOT GAZ, V99, P529 MUEGGLER WF, 1982, INT294 USDA FOR SERV OLMSTED CE, 1979, N AM ELK ECOLOGY BEH, P89 PEARSON GA, 1914, PLANT WORLD, V17, P249 PEARSON SM, 1995, ECOL APPL, V5, P744 QUINN RO, 2001, SUSTAINING ASPEN W L, P369 RIPPLE WJ, 2000, BIOL CONSERV, V95, P361 RIPPLE WJ, 2001, WEST J APPL FOR, V16, P61 ROMME WH, 1982, ECOL MONOGR, V52, P199 ROMME WH, 1989, BIOSCIENCE, V39, P695 ROMME WH, 1991, CONSERV BIOL, V5, P373 ROMME WH, 1995, ECOLOGY, V76, P2097 ROMME WH, 1997, NAT AREA J, V17, P17 SCHIER GA, 1975, INT170 USDA FOR SERV SINGER FJ, 1998, WILDLIFE SOC B, V26, P375 STEVENS MT, 1999, MOL ECOL, V8, P1769 TREXLER JC, 1993, ECOLOGY, V74, P1629 TURNER MG, 1994, J VEG SCI, V5, P731 TURNER MG, 1997, ECOL MONOGR, V67, P411 TURNER MG, 1998, ECOSYSTEMS, V1, P511 TURNER MG, 1999, INT J WILDLAND FIRE, V9, P21 TUSKAN GA, 1996, CAN J FOREST RES, V26, P2088 WAGNER FH, 1993, HUMANS COMPONENTS EC, P257 WHITE CA, 1998, WILDLIFE SOC B, V26, P449 0921-2973 Landsc. Ecol.ISI:000183770300003Univ Wisconsin, Dept Zool, Madison, WI 53706 USA. Colorado State Univ, Dept Forest Sci, Ft Collins, CO 80523 USA. Oak Ridge Natl Lab, Div Environm Sci, Oak Ridge, TN 37831 USA. Turner, MG, Univ Wisconsin, Dept Zool, Madison, WI 53706 USA.English?bTurner, M.G. C.L. Ruscher1988-Changes in Landscape Patterns in Georgia, USA241-251Landscape Ecology14qLand use, Spatial patterns, Aerial photography, Fractal dimension, Edge, Diversity, Dominance, Contagion, GeorgiatThe objectives of this study were to determine how landscape patterns in Georgia, USA have changed through time and whether the spatial patterns varied by physiographic region. Historical aerial photography was used to analyze spatial patterns of land use from the 1930’s to the 1980's. Land use patterns were quantified by: (1) mean number and size of patches; (2) fractal dimension of patches; (3) amount of edge between land uses; and (4) indices of diversity, dominance, and contagion. Forest cover increased in aerial extent and in mean patch size. The mean size of agricultural patches increased in the coastal plain and decreased in the mountains and Piedmont. Edges between land uses decreased through time, indicating less dissection of the landscape. Fractal dimensions also decreased, indicating simpler patch shapes. Indices of diversity and dominance differed through time but not among regions; the contagion index differed among regions but not through time. A geographic trend of decreasing diversity and increasing dominance and contagion was observed from the mountains to the lower coastal plain. Landscape patterns exhibited the greatest changes in the Piedmont region. Overall, the Georgia landscape has become less fragmented and more connected during the past 50 years. Changing patterns in the landscape may have implications for many ecological processes and resources.|?"Tweel, Andrew W. Turner, R. Eugene2014_Contribution of tropical cyclones to the sediment budget for coastal wetlands in Louisiana, USA 1083-1094Landscape Ecology296JulThe storm surge from a single hurricane can deposit tens of millions of tons of sediment on coastal wetlands within 100 km of landfall, but the distribution and cumulative amount from hurricanes at a centurial timescale is unknown. Here we use a model calibrated by three storms to estimate the average deposition on the deteriorating Louisiana coast from 1851 to 2008. The total deposition on Louisiana coastal wetlands, exclusive of open water, averages 5.6 million tons of inorganic sediment per year, equivalent to 3.8 % of the modern annual Mississippi River sediment load. Seventy nine percent of this sediment is deposited in a 20 km strip along the Gulf of Mexico (7,400 km(2) wetlands) comprised primarily of salt marshes, and this distribution matches spatial and temporal patterns described in modern surficial deposits and sediment cores. We estimate that surge-induced deposition of sediment is attributable to at least 65 % of the inorganic content of the top 24 cm of soils in abandoned delta lobes, and 80 % in the chenier plain. While the most sedimentation from a given event results from the most intense storms, 78 % of the long-term hurricane sedimentation results from moderate storms (930-990 mb) that comprise 51 % of tropical cyclone events. Furthermore, we estimate that the 47 % of storms that make landfall with an internal barometric pressure above 990 mb account for only 7 % of the tropical cyclone sedimentation on wetlands.!://WOS:000338331600012Times Cited: 1 0921-2973WOS:00033833160001210.1007/s10980-014-0047-6?XFabiana Umetsu Renata Pardini2007Small mammals in a mosaic of forest remnants and anthropogenic habitats—evaluating matrix quality in an Atlantic forest landscape 517-530Landscape Ecology224Disturbed landscapes - Endemic species - Introduced species - Habitat association - Invading species - Forest fragmentation - Forest regeneration - Homogeneous tree plantations The matrix of altered habitats that surrounds remnants in human dominated landscapes has been considered homogeneous and inhospitable. Recent studies, however, have shown the crucial role of the matrix in maintaining diversity in fragmented landscapes, acting as a mosaic of units with varying permeability to different species. Inclusion of matrix quality parameters is especially urgent in managing fragmented landscapes in the tropics where agriculture frontiers are still expanding. Using standardized surveys in 23 sites in an Atlantic forest landscape, we evaluated matrix use by small mammals, the most diverse ecological group of mammals in the Neotropics, and tested the hypothesis that endemic species are the most affected by the conversion of original forest into anthropogenic habitats. By comparing species distribution among forest remnants and the predominant adjacent habitats (native vegetation in initial stages of regeneration, eucalyptus plantations, areas of agriculture and rural areas with buildings), we found a strong dissimilarity in small mammal assemblages between native vegetation (including initial stages) and anthropogenic habitats, with only two species being able to use all habitats. Endemic small mammals tended to occupy native vegetation, whereas invading species from other countries or open biomes tended to occupy areas of non-native vegetation. Our results highlight that future destruction of native vegetation will favor invading or generalist species which could dominate highly disturbed landscapes, and that some matrix habitats, such as regenerating native vegetation, should be managed to increase connectivity among populations of endemic species.  |7Umetsu, F. Pardini, R.2007Small mammals in a mosaic of forest remnants and anthropogenic habitats-evaluating matrix quality in an Atlantic forest landscape517-530Landscape Ecology224Bdisturbed landscapes endemic species introduced species habitat association invading species forest fragmentation forest regeneration homogeneous tree plantations tropical rain-forest fragmented landscapes southeastern brazil metapopulation dynamics species richness small rodents corridors disturbance abundance diversityAprThe matrix of altered habitats that surrounds remnants in human dominated landscapes has been considered homogeneous and inhospitable. Recent studies, however, have shown the crucial role of the matrix in maintaining diversity in fragmented landscapes, acting as a mosaic of units with varying permeability to different species. Inclusion of matrix quality parameters is especially urgent in managing fragmented landscapes in the tropics where agriculture frontiers are still expanding. Using standardized surveys in 23 sites in an Atlantic forest landscape, we evaluated matrix use by small mammals, the most diverse ecological group of mammals in the Neotropics, and tested the hypothesis that endemic species are the most affected by the conversion of original forest into anthropogenic habitats. By comparing species distribution among forest remnants and the predominant adjacent habitats (native vegetation in initial stages of regeneration, eucalyptus plantations, areas of agriculture and rural areas with buildings), we found a strong dissimilarity in small mammal assemblages between native vegetation (including initial stages) and anthropogenic habitats, with only two species being able to use all habitats. Endemic small mammals tended to occupy native vegetation, whereas invading species from other countries or open biomes tended to occupy areas of non-native vegetation. Our results highlight that future destruction of native vegetation will favor invading or generalist species which could dominate highly disturbed landscapes, and that some matrix habitats, such as regenerating native vegetation, should be managed to increase connectivity among populations of endemic species.://000245296600004-151NF Times Cited:6 Cited References Count:64 0921-2973ISI:000245296600004Pardini, R Univ Sao Paulo, Inst Biosci, Dept Zool, Rua Matao Travessa 14,101, BR-05508900 Sao Paulo, SP, Brazil Univ Sao Paulo, Inst Biosci, Dept Zool, BR-05508900 Sao Paulo, SP, BrazilDoi 10.1007/S10980-006-9041-YEnglish<7 7Urban, D. L. Miller, C. Halpin, P. N. Stephenson, N. L.2000EForest gradient response in Sierran landscapes: the physical template603-620Landscape Ecology157gap model gradient analysis landscape pattern sensitivity analysis Sierra Nevada spatial scale water balance CLIMATE-CHANGE SOIL-MOISTURE VEGETATION DISTRIBUTION MOUNTAINOUS TERRAIN POTENTIAL RESPONSE SOLAR-RADIATION COMPUTER-MODEL SURFACE FIRE EVAPOTRANSPIRATION SIMULATIONArticleOct~Vegetation pattern on landscapes is the manifestation of physical gradients, biotic response to these gradients, and disturbances. Here we focus on the physical template as it governs the distribution of mixed-conifer forests in California's Sierra Nevada. We extended a forest simulation model to examine montane environmental gradients, emphasizing factors affecting the water balance in these summer-dry landscapes. The model simulates the soil moisture regime in terms of the interaction of water supply and demand: supply depends on precipitation and water storage, while evapotranspirational demand varies with solar radiation and temperature. The forest cover itself can affect the water balance via canopy interception and evapotranspiration. We simulated Sierran forests as slope facets, defined as gridded stands of homogeneous topographic exposure, and verified simulated gradient response against sample quadrats distributed across Sequoia National Park. We then performed a modified sensitivity analysis of abiotic factors governing the physical gradient. Importantly, the model's sensitivity to temperature, precipitation, and soil depth varies considerably over the physical template, particularly relative to elevation. The physical drivers of the water balance have characteristic spatial scales that differ by orders of magnitude. Across large spatial extents, temperature and precipitation as defined by elevation primarily govern the location of the mixed conifer zone. If the analysis is constrained to elevations within the mixed-conifer zone, local topography comes into play as it influences drainage. Soil depth varies considerably at all measured scales, and is especially dominant at fine (within-stand) scales. Physical site variables can influence soil moisture deficit either by affecting water supply or water demand; these effects have qualitatively different implications for forest response. These results have clear implications about purely inferential approaches to gradient analysis, and bear strongly on our ability to use correlative approaches in assessing the potential responses of montane forests to anthropogenic climatic change.://000089421500002 ISI Document Delivery No.: 356AV Times Cited: 21 Cited Reference Count: 65 Cited References: ABER JD, 1992, OECOLOGIA, V92, P463 ANDERSON MA, 1995, SOIL SCI, V160, P415 ARKLEY RJ, 1981, SOIL SCI SOC AM J, V45, P423 BEERS TW, 1966, J FOREST, V64, P691 BONAN GB, 1989, ECOL MODEL, V45, P275 BONAN GB, 1992, J VEG SCI, V3, P495 BOTKIN DB, 1972, J ECOL, V60, P849 BOTKIN DB, 1993, FOREST DYNAMICS ECOL BURNS RM, 1990, AGR HDB USDA FOREST, V654 CLARK JS, 1999, ECOLOGY, V80, P1475 COSBY BJ, 1984, WATER RESOUR RES, V20, P682 DALY C, 1994, J APPL METEOROL, V33, P140 DELCOURT HR, 1983, QUATERNARY SCI REV, V1, P153 DINGMAN SL, 1994, PHYSICAL HYDROLOGY GARDNER RH, 1985, METHODS UNCERTAINTY GRABER DM, 1993, T P SER, V9, P17 HAEFNER JW, 1996, MODELING BIOL SYSTEM HALPIN PN, 1995, THESIS U VIRGINIA CH HARPER JL, 1977, POPULATION BIOL PLAN HELVEY JD, 1965, WATER RESOUR RES, V1, P193 HELVEY JD, 1971, P 3 INT S HYDR PROF, P103 JARVIS PG, 1983, PHYSL PLANT ECOLOGY, V4, P234 KOZAK A, 1969, FOREST CHRON, V45, P278 LASSEN LE, 1969, FPL124 USDA FOR SERV LEEMANS R, 1987, VEGETATIO, V69, P147 LEGENDRE P, 1989, VEGETATIO, V80, P107 LOEHLE C, 1996, ECOL MODEL, V90, P1 MELILLO JM, 1995, GLOBAL BIOGEOCHEM CY, V9, P407 MILLER C, 1999, CAN J FOREST RES, V29, P202 MILLER C, 1999, ECOL MODEL, V114, P113 MILLER C, 1999, ECOSYSTEMS, V2, P76 MINORE D, 1979, 87 USDA GTR PNW MOORE ID, 1990, HYDROLOGICAL PROCESS, V5, P3 MUELLER MJ, 1982, SELECTED CLIMATIC DA NIKOLOV NT, 1992, ECOL MODEL, V61, P149 PARTON WJ, 1987, SOIL SCI SOC AM J, V51, P1173 RUNNING SW, 1987, CAN J FOREST RES, V17, P472 RUNNING SW, 1988, ECOL MODEL, V42, P125 SELLERS WD, 1965, PHYSICAL CLIMATOLOGY SHUGART HH, 1984, THEORY FOREST DYNAMI SHUGART HH, 1992, ANNU REV ECOL SYST, V23, P15 SMITH T, 1989, VEGETATIO, V83, P49 SMITH TM, 1992, ADV ECOL RES, V22, P93 SOLOMON AM, 1986, OECOLOGIA, V68, P567 STEPHENSON NL, 1988, THESIS CORNELL U ITH STEPHENSON NL, 1990, AM NAT, V135, P649 STEPHENSON NL, 1993, P 4 C RES CAL NAT PA, P93 STEPHENSON NL, 1998, J BIOGEOGR, V25, P855 URBAN DL, UNPUB DEMOGRAPHIC PR URBAN DL, 1987, BIOSCIENCE, V37, P119 URBAN DL, 1991, FOREST ECOL MANAG, V42, P95 URBAN DL, 1992, PLANT SUCCESSION THE, P249 URBAN DL, 1993, CLIMATIC CHANGE, V23, P247 URBAN DL, 1999, DERIVED MODELS METAM, P70 VANKAT JL, 1982, MADRONO, V29, P200 WARING RH, 1982, CAN J FOREST RES, V12, P556 WARING RH, 1985, FOREST ECOSYSTEMS CO WATT AS, 1947, J ECOL, V35, P1 WEINSTEIN DA, 1992, LANDSCAPE BOUNDARIES, P379 WHITTAKER RH, 1967, AM J BOT, V54, P931 WIENS JA, 1989, FUNCT ECOL, V3, P385 WOLOCK DM, 1995, WATER RESOUR RES, V31, P1315 YEAKLEY JA, 1998, HYDROL EARTH SYST SC, V2, P41 ZIEMER RR, 1964, J GEOPHYS RES, V69, P615 ZINKE PJ, 1967, FOREST HYDROLOGY, P137 0921-2973 Landsc. Ecol.ISI:000089421500002zDuke Univ, Nicholas Sch Environm, Durham, NC 27708 USA. Urban, DL, Duke Univ, Nicholas Sch Environm, Durham, NC 27708 USA.EnglishB? @Uriarte, María Yackulic, Charles Lim, Yili Arce-Nazario, Javier2011VInfluence of land use on water quality in a tropical landscape: a multi-scale analysis 1151-1164Landscape Ecology268Springer NetherlandsEarth and Environmental ScienceThere is a pressing need to understand the consequences of human activities, such as land transformations, on watershed ecosystem services. This is a challenging task because different indicators of water quality and yield are expected to vary in their responsiveness to large versus local-scale heterogeneity in land use and land cover (LUC). Here we rely on water quality data collected between 1977 and 2000 from dozens of gauge stations in Puerto Rico together with precipitation data and land cover maps to (1) quantify impacts of spatial heterogeneity in LUC on several water quality indicators; (2) determine the spatial scale at which this heterogeneity influences water quality; and (3) examine how antecedent precipitation modulates these impacts. Our models explained 30–58% of observed variance in water quality metrics. Temporal variation in antecedent precipitation and changes in LUC between measurements periods rather than spatial variation in LUC accounted for the majority of variation in water quality. Urbanization and pasture development generally degraded water quality while agriculture and secondary forest re-growth had mixed impacts. The spatial scale over which LUC influenced water quality differed across indicators. Turbidity and dissolved oxygen (DO) responded to LUC in large-scale watersheds, in-stream nitrogen concentrations to LUC in riparian buffers of large watersheds, and fecal matter content and in-stream phosphorus concentration to LUC at the sub-watershed scale. Stream discharge modulated impacts of LUC on water quality for most of the metrics. Our findings highlight the importance of considering multiple spatial scales for understanding the impacts of human activities on watershed ecosystem services.+http://dx.doi.org/10.1007/s10980-011-9642-y 0921-297310.1007/s10980-011-9642-y?Uta, Steinhardt Martin, Volk2002xAn investigation of water and matter balance on the meso-landscape scale: A hierarchical approach for landscape research1-12Landscape Ecology171pGIS-coupled modeling - Hierarchy - Land use scenarios - Landscape planning - Landscape water balance - MesoscalezThe realization of strategies for sustainable land use assumes specificresearch concepts from the local to the global scale (micro-, meso- andmacroscale). Therefore, landscape ecological science has to provideinvestigation methods for all these different scales. By combiningtop-down and bottom-up approaches in addition tocoupled GIS-model applications and traditional methods, the investigation oflandscape ecological structures and processes seems to be possible. Thepresented studies show this approach on examples of two study areas in EasternGermany: A watershed of 400 km2 and an administrativedistrict of about 4000 km2. The scale-specificapplicability of several models and methods were tested for theseinvestigations, and the validation of the calculated results are presented. Animportant outcome of the project should be the prevention of conflicts betweenagriculture, water management and soil, and water and nature conservation;based onrecommendations for land use variants with decreased pollutant loading withinagricultural areas. The scale specific investigations can be considered as abase for establishing sustainable land use.*http://dx.doi.org/10.1023/A:1015215332242 10.1023/A:1015215332242 References AG Boden 1994. Bodenkundliche Kartieranleitung, Edition 1994. AG Boden, Hannover, Germany, 392 pp. Arnold J.G., Allen P.M. and Bernhardt G. 1993. A comprehensive surface-groundwater flow model. J. Hydrology 142: 47-69. BGR, Hannover Geol. Jahrb. Franko U. et al. 1997. Einfluß von Standort und Bewirtschaftung auf den N-Austrag aus Agrarökosystemen. UFZ-Bericht 10/97., Leipzig, Germany, 63 pp. Glugla G. and Fürtig G. 1997. Dokumentation zur Anwendung des Rechenprogramms ABIMO. Bundesanstalt für Gewässerkunde, Berlin, Germany, 30 pp. Grayson R.B., Moore I.D. and McMahon T.A. 1992. Physically based hydrologic modeling, 2. Is the concept realistic? Water Resources Research 26 19: 2659-2666. Haycock N.E. and Burt T.P. 1993. The sensitivity of rivers to nitrate leaching: The effecitiveness of near-stream land as a nutrient retention zone. In: Thomas D.S.G. and Allison R.J. (eds), Landscape Sensivity. Wiley, New York, NY, USA, pp. 261-272. Helming K. and Frielinghaus M. 1999. Skalenaspekte der Bodenerosion. In: Steinhardt U. and Volk M. (eds), Regionalisierung in der Landschaftsökologie. Teubner-Verlag, Stuttgart-Leipzig, Germany, pp. 221-232. Hickey R., Smith A. and Jankowski P. 1994. Slope length calculation from a DEM within ARC/INFO GRID. Comput. Environ. And Urban Systems 18: 365-380. Kiemstedt H., von Haaren C., Mönnecke M. and Ott S.Der Bundesminister für Umweltschutz und Reaktorsicherheit 1997. Landschaftsplanung-Inhalte und Verfahrensweisen. 39 S ORT. Klijn J.A. 1995. Hierarchical concepts in landscape ecology and its underlying disciplines, Report 100. Win and Starring Centre for Integrated Land, Soil and Water Research, Wageningen, The Netherlands, 144 pp. Krysanova V., Müller-Wohlfeil D.-L. and Becker A. 1998. Development and test of a spatial distributed hydrological/water quality model for mesoscale watersheds. Ecological Modelling 106: 261-289. Leser H. 1997. Landschaftsökologie. 4th edn. UTB, Ulmer, Stuttgart, Germany. Neef E. 1967. Die theoretischen Grundlagen der Landschaftslehre. g. In: Dover J.W. and Bunce R.G.H. (eds), Key concepts in Landscape Ecology. IALE, Preston, UK, pp. 405-410. Riitters K.H. and Wickham J.D. 1997. A Landscape Atlas of the Chesapeak Bay Watershed. Environmental Research Center, Norris, TN, USA, 29 pp. Röder M. 1998. Erfassung und Bewertung anthropogen bedingter Änderungen des Landschaftswasserhaushaltes-dargestellt an Beispielen der Westlausitz. TU, Dresden, Germany. Sächsische Landesanstalt für Landwirtschaft 1996. Erosion 2D/3D. Ein Computermodell zur Simulation der Bodenerosion durch Wasser. Sächsische Landesanstalt für Landwirtschaft, Dresden, Germany. Sauerborn P. 1994. Die Erosivität der Niederschläge in Deutschland-Ein Beitrag zur quantitativen Prognose der Bodenerosion durchWasser in Mitteleuropa. In: Bonner Bodenkundliche Abhandlungen 13. Schwertmann U., Vogl W. and Kainz M. 1990. Bodenerosion durch Wasser. 2nd edn. Ulmer, Stuttgart, Germany, 64 pp. Srinivasan R. and Arnold J.G. 1993. Basin scale water quiality modelling using GIS. In: Proceedings, Applications of Advanced Inform. Technologies for Managem. Of Nat. Res., June 17-19, Spokane, WA, USA, pp. 475-484. Statistisches Bundesamt 1996. CORINE Land Cover-Daten zur Bodenbedeckung., Wiesbaden, Germany. Steinhardt U. 1999. Quantifying landscape ecological processes on the landscape scale (Abs.). In: Proceedings of the 5th World Congress of the IALE: Landscpe Ecology-The science and the action, Vol. II. Snowmass Village, CO, USA. Steinhardt U. and Volk M. 2000. Von der Makropore zum Flußeinzugsgebiet-Hierarchische Ansätze zum Verständnis des landschaftlichen Wasser-und Stoffhaushalt. Petermanns Geogr. Mitt. 144: 80-91. Volk M. 1999. Interactions between landscape balance and land use in the Dessau region, eastern Germany. A hierarchical approach. In: Hlavinkova P. and Munzar J. (eds), Regional Prosperity and Sustainability. Proceedings of the 3rd Moravian Geographical Conference CONGEO99., Austerlitz, pp. 201-209. Volk M. and Steinhardt U. 1998. Integration unterschiedlich erhobener Datenebenen in GIS für landschaftsökologische Bewertungen im mitteldeutschen Raum. Photogrammetrie-Fernerkundung-GIS 6/98: 349-362. Volk M. and Bannholzer M. 1999. Auswirkungen von Landnutzungsänderungen auf den Gebietswasserhaushalt: Anwendungsmöglichkeiten des Modells ABIMO für regionale Szenarien. Geoökodynamik 20 3: 193-210. Wishmeier W.H. and Smith D.D. 1978. Predicting Rainfall Erosion Losses-A Guide to Conservation Planning. Agriculture Handbook No. 537. U.S. Department of Agriculture, Washington, DC, USA. cDepartment of Applied Landscape Ecology, Center of Environmental Research, D-04301 Leipzig, Germany-}?7Vacher, Kerri A. Killingbeck, Keith T. August, Peter V.2007bIs the relative abundance of nonnative species an integrated measure of anthropogenic disturbance?821-835Landscape Ecology226Jul&://BIOSIS:PREV200700463285 0921-2973BIOSIS:PREV200700463285l? /Vačkář, David Chobot, Karel Orlitová, Erika2012pSpatial relationship between human population density, land use intensity and biodiversity in the Czech Republic 1279-1290Landscape Ecology279Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9779-3 0921-297310.1007/s10980-012-9779-3|? 7Valbuena, D. Verburg, P. H. Bregt, A. K. Ligtenberg, A.2010DAn agent-based approach to model land-use change at a regional scale185-199Landscape Ecology252Land-use/cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. A common approach to analyse and simulate LUCC as the result of individual decisions is agent-based modelling (ABM). However, ABM is often applied to simulate processes at local scales, while its application in regional studies is limited. This paper describes first a conceptual framework for ABM to analyse and explore regional LUCC processes. Second, the conceptual framework is represented by combining different concepts including agent typologies, farm trajectories and probabilistic decision-making processes. Finally, the framework is illustrated through a case study in the Netherlands, where processes of farm cessation, farm expansion and farm diversification are shaping the structure of the landscape. The framework is a generic, straightforward approach to analyse and explore regional LUCC with an explicit link to empirical approaches for parameterization of ABM.!://WOS:000274437100003Times Cited: 1 0921-2973WOS:00027443710000310.1007/s10980-009-9380-6#?ZValdo, Kuusemets Ülo, Mander20022Nutrient flows and management of a small watershed59-68Landscape Ecology170[Buffer zones - Constructed wetlands - Nitrogen and phosphorus runoff - Watershed management Nutrient leaching from agricultural areas is one of the main concerns of watershed management. The paper examines nitrogen and phosphorus leaching from different parts of small agricultural watershed (378 ha) that was divided into 6 subcatchments. The calculations of nutrient outflow are based on the detailed measurement at the time of intensive agricultural activities during 5 years (1987–1991). The results show that nutrient leaching can vary very much even in such a small catchment area. The retention of nitrogen and phosphorus took place in the storage lake: 3,900 and 2.2 kg ha−1 year−1, respectively. At the same time, in the small subcatchment with high shallow groundwater outflow value, the nitrogen and phosphorus outflow was 233 and 0.90 kg ha−1 year−1, respectively. The most effective mitigation method is establishing buffer zones on the banks of the stream. A buffer zone of 460 m length would remove 2,200 to 2,640 kg N and 12 to 15 kg P a year, a constructed wetland on the stream would remove 1,660 to 2,760 kg N and 3 to 4.5 kg P a year. The detailed study gives good opportunity to estimate most critical areas where application of mitigation methods is most needed and ecologically and economically effective. *http://dx.doi.org/10.1023/A:1015281727132 I10.1023/A:1015281727132 Valdo Kuusemets Email: valdo@ut.ee Phone: +37 27 375 819 Fax: +37 27 375825 References APHA 1981. Standard methods for the Examination of Water and WasteWater. 15th edition. American Public Health Organization, Washington, USA. Arheimer B. and Wittgren H.B. 1994. Modelling the effects of wetlands on regional nitrogen transport. Ambio 23(6): 378-386. Bastian O. and Schreiber K.-F. (eds) 1999. Analyse und ökologische Bewertung der Landschaft. 2., neubearbeitete Auflage. Spektrum Akademischer Verlag Heidelberg, Berlin, Germany. Behrendt H., Lademann L., Pagenkopf W.-G., and Pöthig R. 1996. Vulnerable areas of phosphorus leaching-detection by GIS-analysis and measurements of phosphorus sorption capacity. Water Sci. Technol. 33(4-5): 175-181. Blackwell M.S.A., Hogan D.V., and Maltby E. 1999. The use of conventionally and alternatively located buffer zones for the removal of nitrate from diffuse agricultural run-off. Water Sci. Technol. 39(12): 157-164. Collinge S.K. 1996. Ecological consequences of habitat fragmentation: Implications for landscape architecture and planning. Landsc. Urb. Plan. 36: 59-77. Fleischer S. and Stibe L. 1991. Drainage basin management-reducing river transported nitrogen. Verhandlungen Internationale Vereinigung für Theoretische und Angewandte Limnologie 24: 1753-1755. Forman R.T.T. and Gordon M. 1986. Landscape Ecology. John Wiley, New York, NY, USA. Haycock N.E. and Muscutt A.D. 1995. Landscape management strategies for the control of diffuse pollution. Landsc. Urb. Plan. 31(1-3): 313-321. Jensen J.J. and Skop E. 1998. Alternative strategies for reducing nitrogen loading. Environ. Pollut. 102(S1): 741-748. Kuusemets V. and Mander Ñ. 1999. Ecotechnological measures to control nutrient losses from catchments. Water Sci. Technol. 40(10): 195-202. Lowrance R., Todd R., Fail J., Hendrickson O., Leonard R., and Asmussen L. 1984. Riparian forests as nutrient filters in agricultural watersheds. Bioscience 34(6): 374-377. Mander Ñ., Kull A., and Kuusemets V. 2000. Nutrien flows and land use change in a rural catchment: a modelling approach. Landsc. Ecol. 15: 187-1999. Mander Ñ. and Järvet, A. 1998. Buffering Role of Small Reservoirs in Agricultural Catchments. Internl. Rev. Hydrobiol. 83: 639-646. Mander Ñ., Kull A., Tamm V., Kuusemetes V., and Karjus R. 1998. Impact of climatic fluctuations and land use change on runoff and nutrient losses in rural landscapes. Landsc. Urb. Plann. 41: 229-238. Mander Ñ., Kuusemets V., and Ivask M. 1995. Nutrient dynamics of riparian ecotones: A case study from the Porijõgi River catchment, Estonia. Landsc. Urb. Plann. 31: 333-348. Mander Ñ., Kuusemets V., Järvet A., Häberli K., Nõges T., Tuvikene A., and Mauring T. 1997. Ecological engineering for wastewater control in agricultural catchment areas: Three case studies from Estonia. In: Etnier C. and Guterstam B. (eds), Ecological Engineering for Wastewater Treatment, CRC/Lewis, New York, NY, USA, pp. 263-286. Mander Ñ. and Mauring T. 1994. Nitrogen and phosphorus retention in natural ecosystems. In: Ryszkowski L. and Balazy S. (eds), Functional Appraisal of Agricultural Landscape in Europe, Research Center for Agricultural and Forest Environment, Polish Academy of Sciences, Poznan, Poland, pp. 77-94. Mander Ñ. and Mauring T. 1997. Constructed wetlands for waste-water treatment in Estonia. Water Sci. Technol. 35(5): 323-330. Peterjohn W.W. and Correll D.L. 1984. Nutrient dynamics in an agricultural watershed: observations on the role of a riparian forest. Ecology 65(5): 1466-1475. Petersen R.C., Petersen L.B.-M., and Lacoursiére J. 1992. A building-block Model of Stream Restoration. In: Boon P.J., Calow P., and Petts G.E. (eds), River Conservation and Management, John Wiley and Sons Ltd., New York, NY, USA, pp. 293-309. Pinay G. and Decamps H. 1988. The role of riparian woods in regulating nitrogen fluxes between the alluvial aquifer and surface water: A conceptual model. Regul. Riv. Res.Manag. 2: 507-516. Pionke H.B., Gburek W.J., and Sharpley N. 2000. Critical source area controls on water quality in an agricultural watershed located in the Chesapeake Basin. Ecol. Engineer. 14(4): 325-335. Sharpley A., Chapra S., Wedepohl R., Sims J., Daniel T., and Reddy K. 1994. Managing agricultural phosphorus for protection of surface waters-Issues and options. J. Environ. Quality 23(3): 437-451. Straškraba M. 1996. Ecotechnological methods for managing nonpoint source pollution in watersheds, lakes and reservoirs. Water Sci. Technol. 33(4-5): 73-80. }Valdo Kuusemets1 and Ülo Mander1 (1) Institute of Geography, University of Tartu, 46 Vanemuise St., 51014 Tartu, Estonia |?$ RValeix, M. Loveridge, A. J. Davidson, Z. Madzikanda, H. Fritz, H. Macdonald, D. W.2010How key habitat features influence large terrestrial carnivore movements: waterholes and African lions in a semi-arid savanna of north-western Zimbabwe337-351Landscape Ecology2538Within a landscape where prey has an aggregated distribution, predators can take advantage of the spatial autocorrelation of prey density and intensify their search effort in areas of high prey density by using area-restricted search behaviour. In African arid and semi-arid savannas, large herbivores tend to aggregate around scarce water sources. We tested the hypothesis that water sources are a key determinant of habitat selection and movement patterns of large free-ranging predators in such savannas, using the example of the African lion. We used data from 19 GPS radio-collared lions in Hwange National Park, Zimbabwe. Maps of lions' trajectories showed that waterholes are key loci on the lions' route-maps. Compositional analyses revealed that lions significantly selected for areas located within 2 km of a waterhole. In addition, analysis of lions' night paths showed that when lions are close to a waterhole (< 2 km), they move at lower speed, cover shorter distances per night (both path length and net displacement) and follow a more tortuous path (higher turning angle, lower straightness index and higher fractal dimension) than when they are further from a waterhole. Hence, our results strongly suggest that lions adopt area-restricted searching in the vicinity of waterholes, and reduce their search effort to minimize the time spent far from a waterhole. They provide an illustration of how key habitat features that determine the dispersion of prey (e.g. waterholes in this study) have an influence on the spatial ecology and movement patterns of terrestrial predators.!://WOS:000275122600002Times Cited: 0 0921-2973WOS:00027512260000210.1007/s10980-009-9425-xڽ7.DVallecillo, Sara Hermoso, Virgilio Possingham, HughP Brotons, Lluís2013fConservation planning in a fire-prone Mediterranean region: threats and opportunities for bird species 1517-1528Landscape Ecology288Springer Netherlands_Wildfires Land-cover changes Priority areas Fire impact Bird assemblage Marxan Spatial planning 2013/10/01+http://dx.doi.org/10.1007/s10980-013-9904-y 0921-2973Landscape Ecol10.1007/s10980-013-9904-yEnglish|?,Vallet, J. Daniel, H. Beaujouan, V. Roze, F.2008uPlant species response to urbanization: comparison of isolated woodland patches in two cities of North-Western France 1205-1217Landscape Ecology2310The effect of urbanization on species distribution has been extensively documented, but a main challenge in urban ecology is to better understand the factors causing different distributions among species in response to urbanization. Hence, this paper aims to compare the effects of urbanization on woodland plant assemblages in two cities and to describe species responses by using several indicators. The study was carried out in the cities of Angers and Rennes (North-Western France) where 11 isolated woodlands were surveyed along an urban-rural gradient in each city. Abundance data of spontaneous species were collected from 220 quadrats. The effect of land cover (within a 500 m buffer around each woodland) on species assemblages was investigated by Canonical Correspondence Analysis. Buildings and pavement areas were the most significant predictors of species composition, and the effect of location in Angers or Rennes appeared on the second axis. More than 60% of the most frequent plant species were indicator of urban or rural location and their preferences were similar in the two cities. These lists of urban and rural indicator species were compared with Ellenberg's indicator values and two other indicators specific to forest environment. The species which grow preferentially in urban woodlands are species which are already known to be associated with recent forests rather than ancient forests; with hedgerows rather than woodlands. The opposite pattern was observed concerning rural species. Moreover, urban indicator species have higher optima for soil pH and soil nitrogen content than rural indicator species. Different characteristics and history of forest habitat-continuity of the forest land cover, linearity of the habitat, change in adjacent land cover and land use-could select the same species, and the responses of the latter might involve different preferences concerning soil alkalinity and nutrient status.!://WOS:000261790600006Times Cited: 0 0921-2973WOS:00026179060000610.1007/s10980-008-9293-9 <7 Van Berkel, D. B. Verburg, P. H.2012Combining exploratory scenarios and participatory backcasting: using an agent-based model in participatory policy design for a multi-functional landscape641-658Landscape Ecology275multifunctional landscape agent-based models backcasting forecasting ecosystem services rural development landscape evolution land-use rural-development stakeholders futures lessons visualization perceptions strategies multiscale dynamicsMayWhile the merits of local participatory policy design are widely recognised, limited use is made of model-based scenario results to inform such stakeholder involvement. In this paper we present the findings of a study using an agent based model to help stakeholders consider, discuss and incorporate spatial and temporal processes in a backcasting exercise for rural development. The study is carried out in the Dutch region called the Achterhoek. Region-specific scenarios were constructed based on interviews with local experts. The scenarios are simulated in an agent based model incorporating rural residents and farmer characteristics, the environment and different policy interventions for realistic projection of landscape evolution. Results of the model simulations were presented to stakeholders representing different rural sectors at a workshop. The results indicate that illustration of the spatial configuration of landscape changes is appreciated by stakeholders. Testing stakeholders' solutions by way of model simulations revealed that the effectiveness of local interventions is strongly related to exogenous processes such as market competition and endogenous processes like local willingness to engage in multifunctional activities. The integration of multi-agent modelling and participatory backcasting is effective as it offers a possibility to initiate discussion between experts and stakeholders bringing together different expertise.://000303056100003-929JC Times Cited:0 Cited References Count:62 0921-2973Landscape EcolISI:000303056100003}Van Berkel, DB Vrije Univ Amsterdam, Inst Environm Studies IVM, Boelelaan 1087, NL-1081 HV Amsterdam, Netherlands Vrije Univ Amsterdam, Inst Environm Studies IVM, Boelelaan 1087, NL-1081 HV Amsterdam, Netherlands Vrije Univ Amsterdam, Inst Environm Studies IVM, NL-1081 HV Amsterdam, Netherlands Vrije Univ Amsterdam, Amsterdam Global Change Inst, NL-1081 HV Amsterdam, NetherlandsDOI 10.1007/s10980-012-9730-7English?Vvan Daalen,J.C. H.H. Shugart1989uOUTENIQUA - A computer model to simulate succession in the mixed evergreen forests of the southern Cape, South Africa255-267Landscape Ecology24VSouth Africa, mixed evergreen forests, succession, simulation model, landscape ecologyA succession model for mixed evergreen forests of the southern Cape, South Africa, called OUTENIQUA, was developed based on one for subtropical rain forest in New South Wales, Australia. The model simulates the regeneration, growth and mortality on a 0.04 ha plot using an individual-tree based modeling approach to forest succession. The OUTENIQUA model was tested on its ability to simulate species dynamics of the forest stand used for its development, as well as on independent data from a neighboring stand and not used for the model derivation. The model is used as a research tool to summarize published and unpublished knowledge on the southern Cape forests and to highlight aspects where knowledge is insufficient. The development of the model represents a test of an individual-tree gap model as a simulation tool for use in management and directing research in subtropical and tropical forests.<77VVan der Lee, G. E. M. Van der Molen, D. T. Van den Boogaard, H. F. P. Van der Klis, H.2006vUncertainty analysis of a spatial habitat suitability model and implications for ecological management of water bodies 1019-1032Landscape Ecology217EU Bird and Habitat Directive; HSI-model; Lake IJsselmeer; Monte Carlo simulation; pondweed; The Netherlands; uncertainty analysis; water management CONFIDENCE-INTERVALS; INDEX MODELS; RELIABILITYArticleOct+Habitat suitability index (HSI) models have been generally accepted in ecological management as a means to predict effects of pressures and restoration measures on habitats and populations. HSI-models estimate habitat suitability from relevant habitat variables. Because outcomes of HSI-studies may have significant consequences, it is crucial to have insight into the uncertainties of the predictions. In this study a method for uncertainty analysis, using Monte Carlo simulations, was developed and applied for a HSI-model of pondweed (Potamogeton pectinatus) in Lake IJsselmeer, The Netherlands. Uncertainties in both habitat model functions and in input data were considered. The magnitude of the uncertainties in model functions were estimated by a panel of experts, and the uncertainty was highest at intermediate values of the suitability index (0.4-0.6). Uncertainty in the predicted habitat suitability is spatially correlated with variations in environmental habitat variables such as water quality and substrate. The estimated uncertainty may be considered acceptable for the purposes of water management, namely directing ecological rehabilitation and conservation activities. However, the uncertainties may be too high to meet the accuracy requirements of legislation such as the EU Bird and Habitat directive.://000241010900005 mISI Document Delivery No.: 091FA Times Cited: 0 Cited Reference Count: 34 Cited References: *EUR COMM, 2000, MAN NAT 2000 SIT PRO *US FISH WILDL SER, 1980, HAB EV PROC HEP, P101 *US FISH WILDL SER, 1981, STAND DEV HAB SUIT I BENDER LC, 1996, WILDLIFE SOC B, V24, P347 BEUTEL TS, 1999, ECOGRAPHY, V22, P219 BLOCK WM, 1994, WILDLIFE SOC B, V22, P549 BROOKS RP, 1997, WILDLIFE SOC B, V25, P163 BURGMAN MA, 2001, ECOL APPL, V11, P70 CAROLL C, 1999, CONSERV BIOL, V13, P1344 COOKE RM, 1991, EXPERTS UNCERTAINITY DETTMERS R, 2002, J WILDLIFE MANAGE, V66, P417 DUEL H, 1996, ECOHYDRAULICS 2000, P619 FRIJTERS M, 1999, EXMR9800X GORE JA, 1996, REGUL RIVER, V12, P459 GUISAN A, 2000, ECOL MODEL, V135, P147 HAMMERSLEY JM, 1979, MONTE CARLO METHODS HURLEY JF, 1986, MODELING HABITAT REL, P151 JANS L, 1997, 97045X RIZA LAANE WEM, 1996, 96049X TNO BSA LEWIS PAW, 1989, SIMULATION METHODOLO, V1 MADDOCK I, 1999, FRESHWATER BIOL, V41, P373 NOORDHUIS R, 2001, AQUAT BOT, V72, P349 PARASIEWICZ P, 1996, REGUL RIVER, V12, P575 RAILSBACK SF, 2003, ECOL APPL, V13, P1580 ROLOFF GJ, 1999, WILDLIFE SOC B, V27, P973 ROTHLEY KD, 2001, J WILDLIFE MANAGE, V65, P953 RYKIEL EJ, 1996, ECOL MODEL, V90, P229 VANDERLEE GEM, 2000, KWALITEIT HEP INSTRU VANDERLEE GEM, 2003, ACHTERGRONDOCUMENT A VANDIJK PM, 1999, SUPPLY SEDIMENT RIVE VANEERDEN MR, 1997, VAN ZEE TOT LAND, V64 VANHORNE B, 1991, FISH WILDLIFE RES, P8 WHITTINGHAM MJ, 2003, ECOGRAPHY, V26, P521 WILLIAMS JG, 1996, T AM FISH SOC, V125, P458 0921-2973 Landsc. Ecol.ISI:000241010900005WL Delft Hydraul, NL-2600 MH Delft, Netherlands. Inst Inland Water Management & Waste Water Treatm, NL-8200 AA Lelystad, Netherlands. Van der Klis, H, WL Delft Hydraul, POB 177, NL-2600 MH Delft, Netherlands. Hanneke.vdKlis@wldelft.nlEnglish?"van der Meulen, F. J. V. Witter. 1991>Impact of climatic change on coastal dune landscapes of Europe5-6Landscape Ecology61/2?;7van der Meulenl,F. J.V. Witter W. Ritchie S.M. Arens1991#Precepts, approaches and strategies7-13Landscape Ecology61/2NClimate change, sand dunes, coastal dynamics, coastal defence, dune management[?+van der Zee, Dick 19909The complex relationship between landscape and recreation225-236Landscape Ecology44jlandscape, recreation, land evaluation, impact, spatial behaviour, scenic quality, airphoto interpretationbThe relation between landscape and recreation is very complex. There are various, interrelated approaches to analyze this relation, such as land evaluation, impact analysis, spatial behaviour analysis, and assessment of the scenic quality of the landscape or landscape evaluation. In many.of these approaches airphoto interpretation can be a useful tool.L|?8Van Dessel, W. Van Rompaey, A. Poelmans, L. Szilassi, P.2008cPredicting land cover changes and their impact on the sediment influx in the Lake Balaton catchment645-656Landscape Ecology236The land cover pattern in the Lake Balaton catchment (Hungary) has been changing since decollectivization in the 1990s. These land cover changes significantly impact the landscape connectivity, controlling the influx of sediments into the lake. A comparison of high resolution land cover maps from 1981, 2000 and 2005 showed a significant extensification of the agriculture with land cover conversions from arable land and vineyards to grassland and forest. For each land unit transition probabilities were assessed using logistic regression techniques to evaluate to which extent land cover changes are controlled by physical or socio-economic parameters. A stochastic land cover allocation algorithm was applied to generate future land cover patterns. The landscape connectivity for each of the simulated land cover patterns was assessed by means of a distributed routing algorithm. The simulations suggest that further land abandonment in the upslope parts of the catchment will cause a non-linear reduction of average soil erosion rates. The changes, however, have a relatively low impact on the sediment volume entering the lake because of the land unit's poor connectivity with permanent river channels. The major contributors to the lakes sediment load are the vineyards near the lakeshore. They are likely to be maintained because of their touristic value. A significant reduction of the total sediment input in the lake can be expected only if soil conservation measures in the vineyards near the shorelines are undertaken.!://WOS:000257210900002Times Cited: 0 0921-2973WOS:00025721090000210.1007/s10980-008-9227-6|? OVan Dessel, W. Van Rompaey, A. Poelmans, L. Szilassi, P. Jordan, G. Csillag, G.2009zPredicting land cover changes and their impact on the sediment influx in the Lake Balaton catchment (vol 23, pg 645, 2008)987-987Landscape Ecology247Aug://000268430900011^Van Dessel, Wim Van Rompaey, Anton Poelmans, Lien Szilassi, Peter Jordan, Gyozo Csillag, Gabor 0921-2973ISI:00026843090001110.1007/s10980-009-9382-4-}?Van Doorn, A. M. Bakker, M. M.2007The destination of arable land in a marginal agricultural landscape in South Portugal: an exploration of land use change determinants 1073-1087Landscape Ecology227Aug://000248381900009 0921-2973ISI:000248381900009<7T.van Horssen, P. W. Schot, P. P. Barendregt, A.19999A GIS-based plant prediction model for wetland ecosystems253-265Landscape Ecology143ecological modeling geostatistics logistic regression uncertainty propagation GROUNDWATER CONTAMINATION PROBABILISTIC ASSESSMENT NITROGEN AVAILABILITY NETHERLANDS VEGETATION CONSERVATION REGRESSION GRADIENT SYSTEMS AREASArticleJunAn existing non-spatial model for the prediction of response of wetland plant species on ecological factors has been transformed into a GIS-based prediction model which produces spatial output at the landscape scale. The input, spatial patterns of the ecological factors, were constructed with geostatistical spatial interpolation (kriging). With this GIS-based model the spatial patterns of presence and absence of 78 wetland plant species are predicted for an area with wetlands in the Netherlands of approximately 500 square kilometers. The GIS-based model has been validated, and the estimated uncertainty of the input has been propagated through the model. At the species level the output shows spatially coherent and non-random patterns. The validation is affected by the propagation of input errors through the model. The number of valid predictions declines approximately 10-20% when 95% confidence intervals are used in the validation. This study shows that it is feasible to use a geostatistical interpolation method to construct spatial patterns of ecological factors on a landscape scale and to use these patterns as input for a GIS-based prediction model. The added uncertainty on the input values however, affects the number of valid predictions of the model.://000081041200003 ISI Document Delivery No.: 209HB Times Cited: 8 Cited Reference Count: 54 Cited References: *EPA, 1991, MT3D MOD 3 DIM TRANS *MIN AGR NAT MAN F, 1990, NAT POL PLAN NETH ANDERSON MP, 1992, APPL GOUNDWATER MODE APPELO CAJ, 1993, GEOCHEMISTRY GROUNDW AUSTIN MP, 1994, J VEG SCI, V5, P215 BARENDREGT A, 1989, HYDROECOLOGISCH MODE BARENDREGT A, 1991, HYDROECOLOGISCH MODE BARENDREGT A, 1993, LANDSCAPE ECOLOGY ST, P79 BARENDREGT A, 1993, THESIS FACULTEIT RUI BARENDREGT A, 1995, BIOL CONSERV, V72, P393 BELLEHUMEUR C, 1997, PLANT ECOL, V130, P89 BURROUGH PA, 1998, PRINCIPLES GEOGRAPHI DEMARS H, 1996, THESIS FACULTEIT RUI DEMARS H, 1997, HYDROL PROCESSES, V11, P353 DEUTSCH CV, 1992, GSLIB GEOSTATISTICAL EVERTS FH, 1991, VEGETATIT ONTWIKKELI GREMMEN NJM, 1990, J ENVIRON MANAGE, V31, P143 GROSS KL, 1995, J ECOL, V83, P357 HAINESYOUNG R, 1993, LANDSCAPE ECOLOGY GE HASTIE TJ, 1990, GENERALIZED ADDITIVE HEUVELINK GBM, 1993, THESIS FACULTEIT RUI ISAAKS EH, 1989, INTRO APPL GEOSTATIS ISTOK JD, 1996, GROUND WATER, V34, P1050 JOHNSON LB, 1990, LANDSCAPE ECOL, V4, P31 JONGMAN RHG, 1995, DATA ANAL COMMUNITY KING AW, 1990, QUANTITATIVE METHODS, P479 LATOUR JB, 1993, SCI TOTAL ENVIRON S, P1513 MEYERS DE, 1982, MATH GEOL, V14, P629 OLFF H, 1995, LANDSCHAP, V5, P69 PEBESMA EJ, 1997, J HYDROL, V200, P364 PEREIRA JMC, 1991, PHOTOGRAMM ENG REM S, V57, P1475 RAUTMAN CA, 1996, GROUND WATER, V34, P899 RIPLEY BD, 1987, STOCHASTIC SIMULATIO ROBERTSON GP, 1988, ECOLOGY, V69, P1517 ROSSI RE, 1992, ECOL MONOGR, V62, P277 RUNHAAR J, 1996, BIOL CONSERV, V76, P269 SCHOT PP, 1988, AGR WATER MANAGE, V14, P459 SCHOT PP, 1989, GRONDWATERSYSTEMEN G SCHOT PP, 1991, THESIS FACULTEIT RUI TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 VANBRUSSEL J, 1997, LANDSCHAP, V14, P19 VANDENBERG WJ, 1985, VEGETATIE OOSTELIJK VANDERIJT CWCJ, 1996, J VEG SCI, V7, P505 VENTERINK HO, 1997, ECOL MODEL, V101, P347 VERHOEVEN JTA, 1992, GEOBOTANY, V18 VILLARD MA, 1996, ECOLOGY, V77, P59 VOS CC, 1993, LANDSCAPE ECOLOGY ST WASSEN M, 1990, THESIS FACULTEIT RUI WASSEN MJ, 1990, LANDSCAPE ECOL, V5, P21 WASSEN MJ, 1992, LANDSCHAP, V9, P83 WASSEN MJ, 1996, VEGETATIO, V124, P191 WASSEN MJ, 1996, VEGETATIO, V126, P5 WITMER MCH, 1989, THESIS FACULTEIT RUI WITTE JPM, 1992, WETLAND ECOLOGY MANA, V2, P69 0921-2973 Landsc. Ecol.ISI:000081041200003Univ Utrecht, Netherlands Ctr Geoecol Res Modelling & Quantitat, Dept Environm Studies, NL-3508 TC Utrecht, Netherlands. van Horssen, PW, Univ Utrecht, Netherlands Ctr Geoecol Res Modelling & Quantitat, Dept Environm Studies, POB 80-115, NL-3508 TC Utrecht, Netherlands.English%<7!van Langevelde, F. Jaarsma, C. F.2004?Using traffic flow theory to model traffic mortality in mammals895-907Landscape Ecology198mitigation; road ecology; traffic flow theory; traffic mortality; two-patch population model BADGER MELES-MELES; VEHICLE COLLISIONS; ROAD KILLS; POPULATIONS; DISPERSAL; MANAGEMENT; DEERArticleTraffic has a considerable effect on population and community dynamics through the disruption and fragmentation of habitat and traffic mortality. This paper deals with a systematic way to acquire knowledge about the probabilities of successful road crossing by mammals and what characteristics affect this traversability. We derive a model from traffic flow theory to estimate traffic mortality in mammals related to relevant road, traffic and species characteristics. The probability of successful road crossing is determined by the pavement width of the road, traffic volume, traversing speed of the mammals and their body length. We include the traversability model in a simple two-patch population model to explore the effects of these road, traffic and species characteristics on population dynamics. Analysis of the models show that, for our parameter ranges, traffic volume and traversing speed have the largest effect on traffic mortality. The population size is especially negatively affected when roads have to be crossed during the daily movements. These predictions could be useful to determine the expected effectiveness of mitigating measures relative to the current situation. Mitigating measures might alter the road and traffic characteristics. The effects of these changes on traffic mortality and population dynamics could be analysed by calculating the number of traffic victims before and after the mitigating measures.://000226268600007 JISI Document Delivery No.: 886YI Times Cited: 4 Cited Reference Count: 38 Cited References: *OECD, 1986, EC DES LOW TRAFF ROA ADAMS LW, 1983, J APPL ECOL, V20, P403 AMARASEKARE P, 1998, THEOR POPUL BIOL, V53, P44 ANDREWS A, 1990, AUSTR ZOOLOGIST, V26, P130 BAERWALD JE, 1976, TRNASPORTATION ENG H BOTMA H, 1986, 1091 TRB NAT RES COU, P126 BRUINDERINK GWTAG, 1996, CONSERV BIOL, V10, P1059 CLARKE GP, 1998, BIOL CONSERV, V86, P117 CLEVENGER AP, 2003, BIOL CONSERV, V109, P15 DAVIES JM, 1987, J ZOOL, V211, P525 DREW DR, 1968, TRAFFIC FLOW THEORY EDELSTEINKESHET L, 1988, MATH MODELS BIOL FORMAN RTT, 1998, ANNU REV ECOL SYST, V29, P207 GARRETT LC, 1999, J SAFETY RES, V30, P219 HAIGHT FA, 1963, MATH THEORIES TRAFFI HAIGHT FA, 1966, HDB POISSON DISTRIBU HARDERS J, 1968, STRASSENBAU STRASSEN HELS T, 2001, BIOL CONSERV, V99, P331 HUIJSER MP, 2000, BIOL CONSERV, V95, P111 HUNT J, 1993, TRAFFIC ENG CONTROL, V11, P526 JAARSMA CF, 1997, P 6 INT S ENV C RIGH, P383 JACKSON SD, 1998, P INT C WILDL EC TRA, P17 KELLER V, 1997, HABITAT FRAGMENTATIO, P70 LANGE R, 1994, ZOOGDIEREN W EUROPA LANKESTER K, 1991, J APPL ECOL, V28, P561 LEUTZBACH W, 1988, INTRO THEORY TRAFFIC MADER HJ, 1984, BIOL CONSERV, V29, P81 MUNGUIRA ML, 1992, J APPL ECOL, V29, P316 OXLEY DJ, 1974, J APPL ECOL, V11, P51 PETERS RH, 1983, ECOLOGICAL IMPLICATI PUTMAN RJ, 1997, J ENVIRON MANAGE, V51, P43 ROMIN LA, 1996, WILDLIFE SOC B, V24, P276 SINGH AP, 2000, 7 INT S ENV RIGHTS O SPELLERBERG IF, 1998, GLOBAL ECOL BIOGEOGR, V7, P317 TROMBULAK SC, 2000, CONSERV BIOL, V14, P18 VANBOHEMEN HD, 1998, ECOL ENG, V11, P199 VANLANGEVELDE F, 1997, HABITAT FRAGMENTATIO, P171 VERMEULEN HJW, 1994, BIOL CONSERV, V69, P339 0921-2973 Landsc. Ecol.ISI:000226268600007pUniv Wageningen & Res Ctr, Dept Environm Sci, Resource Ecol Grp, NL-6708 PD Wageningen, Netherlands. Univ Wageningen & Res Ctr, Dept Environm Sci, Land Use Planning Grp, NL-6703 BJ Wageningen, Netherlands. van Langevelde, F, Univ Wageningen & Res Ctr, Dept Environm Sci, Resource Ecol Grp, Bornsesteeg 69, NL-6708 PD Wageningen, Netherlands. frank.vanlangevelde@wur.nlEnglisho<7(;van Langevelde, F. Schotman, A. Claassen, F. Sparenburg, G.20008Competing land use in the reserve site selection problem243-256Landscape Ecology153allocation model conservation planning habitat fragmentation reserve site selection spatial optimization stepping stones HABITAT FRAGMENTATION SMALL WOODS LANDSCAPE PATTERNS EUROPAEA OPTIMIZATION NETWORKS SUCCESS FOREST BIRDSArticleAprThe objective of this paper is to present an approach that addresses competing land uses in the reserve site selection problem. This approach is implemented in a spatial optimization model for conservation planning in human-dominated landscapes: MENTOR. This model allocates new sites as stepping stones between existing sites. We illustrated the model by a case with competition for space between wildlife habitat and agriculture as it occurs in the Netherlands. We focused on deciduous forests with the European nuthatch Sitta europaea as an umbrella species for forest birds. Suitability maps for deciduous forests and for agriculture were applied as input for the allocation model. Effects on the landscape pattern, nuthatch populations, bird species richness and dairy farming were described. We can conclude that the application of MENTOR leads to an effective reserve network in De Leijen concerning the suitability of the land for dairy farming. The results show a doubling of the average proportion of occupied habitat, an increase in colonization probability of patches, a decrease in extinction probability of local populations, and an increase in bird species richness per patch. Whereas it results in a relatively small reduction in land currently used by agriculture.://000085293300006 ISI Document Delivery No.: 283UB Times Cited: 12 Cited Reference Count: 43 Cited References: 1993, NATUURBELEIDSPLAN NO *CBS, 1984, NED BOSST, V1 *CPB, 1992, SCANNING FUTURE LONG ANDREN H, 1994, OIKOS, V71, P355 ARTHUR JL, 1997, ENVIRON ECOL STAT, V4, P153 BEDWARD M, 1992, BIOL CONSERV, V62, P115 BELLAMY PE, 1996, J APPL ECOL, V33, P249 BELLAMY PE, 1998, OECOLOGIA, V115, P127 COOK EA, 1994, LANDSCAPE PLANNING E CSUTI B, 1997, BIOL CONSERV, V80, P83 ENOKSSON B, 1995, LANDSCAPE ECOL, V10, P267 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY HANSKI I, 1996, AM NAT, V147, P527 HINSLEY SA, 1998, GLOBAL ECOL BIOGEOGR, V7, P125 HOF J, 1997, ECOL APPL, V7, P1160 HUININK HTM, 1993, 492 IKC AT KALKHOVEN JTR, 1995, 193 IBN KUIJSTERS R, 1989, LANDBOUW RUIMTEMAAT KUIJSTERS R, 1990, LANDBOUW KLEINSCHALI LI H, 1993, LANDSCAPE ECOL, V8, P63 LINDENMAYER DB, 1996, LANDSCAPE ECOL, V11, P79 MARGULES CR, 1988, BIOL CONSERV, V43, P63 MARTINEZFALERO E, 1995, QUANTITATIVE TECHNIQ, P237 MATTHYSEN E, 1996, ECOGRAPHY, V19, P67 MURPHY JJ, 1992, DRUG AGING, V2, P1 NANTEL P, 1998, BIOL CONSERV, V84, P223 NEVO A, 1996, ECOL MODEL, V91, P271 NILSSON SG, 1976, ORNIS SCAND, V7, P179 NOSS RF, 1997, SCI CONSERVATION PLA OPDAM P, 1993, IALE STUDIES LANDSCA, V1, P145 OPDAM P, 1994, IBIS, V137, S139 POST F, 1990, VOGELS MIDDEN BRABAN, P34 QUINN JF, 1988, CONS BIOL, V2, P293 SAATY TL, 1980, ANAL HIERARCHICAL PR SAUNDERS DA, 1991, BIOL CONSERV, V1, P18 SCHUTZ PR, 1990, AANLEG BEHEER BOS BE SIMBERLOFF D, 1998, BIOL CONSERV, V83, P245 VANBUUREN M, 1993, IALE STUDIES LANDSCA, V1, P219 VANDESANDE A, 1988, LEYEN NATUURWAARDEN VANDORP D, 1987, LANDSCAPE ECOLOGY, V1, P59 VANLANGEVELDE F, 1999, THESIS AGR U WAGENIN VERBOOM J, 1991, OIKOS, V61, P149 VERBOOM J, 1993, IALE STUDIES LANDSCA, V1, P172 0921-2973 Landsc. Ecol.ISI:000085293300006Wageningen Univ Agr, Dept Environm Sci, Land Use Planning Grp, NL-6703 BJ Wageningen, Netherlands. Inst Forestry & Nat Res, Dept Landscape Ecol, NL-6700 AA Wageningen, Netherlands. Agr Univ Wageningen, Dept Math, Operat Res Grp, NL-6703 HA Wageningen, Netherlands. van Langevelde, F, Agr Univ Wageningen, Dept Environm Sci, Trop Nat Conservat & Ecol Vertebrates Grp, Bornsesteeg 69, NL-6708 PD Wageningen, Netherlands.EnglishD<7"Van Oost, K. Govers, G. Desmet, P.2000]Evaluating the effects of changes in landscape structure on soil erosion by water and tillage577-589Landscape Ecology156field boundary land use soil erosion tillage WATEM AGRICULTURAL LAND SEDIMENT FLOW REDISTRIBUTION SIMULATION DEPOSITION CATCHMENTS PATTERNS RATESArticleAugLandscape structure, or the spatial organization of different land units, has an impact on erosion and sedimentation on agricultural land. However, current erosion models emphasize the temporal, and less the spatial, variability of relevant parameters so that the effects of changes in landscape structure have hitherto not been studied in detail. Therefore, a spatially distributed water and tillage erosion model that allows the incorporation of landscape structure is presented. The model is applied to three study sites in the Belgian Loam Belt where significant changes in landscape structure occurred over the last fifty years. Erosion rates were shown to change by up to 28% however, with decreases as well as increases occurring. These could be explained by the interaction of changes in land use with changes in the position of field boundaries. Thus, landscape structure is an important control when the effect of environmental change on erosion risk is to be assessed.://000088037200007 ISI Document Delivery No.: 331UN Times Cited: 47 Cited Reference Count: 43 Cited References: BAUDRY J, 1988, MUNSTERSCHE GEOGRAPH, V29, P23 BOLLINNE A, 1985, SOIL EROSION CONSERV DEPUYDT F, 1969, ACTA GEOGR LOVANIENS, V7, P141 DEROO APJ, 1995, LISEM LIMBURG SOIL E DESMET PJJ, 1995, CATENA, V25, P389 DESMET PJJ, 1996, J SOIL WATER CONSERV, V51, P427 DESMET PJJ, 1997, CATENA, V29, P283 DESMET PJJ, 1997, THESIS U LEUVEN DESMET PJJ, 1999, GEOGRAPHIC INFORMATI FAVISMORTLOCK D, 1995, CATENA, V25, P365 FLANAGAN DC, 1995, 10 NSERL USDAARS FOSTER GR, 1975, PRESENT PROSPECTIVE FOSTER GR, 1982, HYDROLOGIC MODELING GOVERS G, 1988, GEOMORPHOLOGY, V1, P343 GOVERS G, 1993, FARM LAND EROSION TE GOVERS G, 1994, EUR J SOIL SCI, V45, P469 GOVERS G, 1996, EARTH SURF PROC LAND, V21, P929 GRAYSON RB, 1992, WATER RESOUR RES, V26, P2659 LAL R, 1991, SOIL MANAGEMENT SUST LINDSTROM MJ, 1992, SOIL TILL RES, V24, P243 LUDWIG B, 1995, CATENA, V25, P227 MCCOOL DK, 1989, T ASAE, V32, P1571 MERRIAM G, 1990, CHANGING LANDSCAPES, P121 MEYER LD, 1995, T ASAE, V38, P809 MITAS L, 1998, WATER RESOUR RES, V34, P505 MOORE ID, 1986, T ASAE, V29, P1624 MORGAN RPC, 1998, EARTH SURF PROC LAND, V23, P527 NICKS AD, 1994, IAHS PUBLICATION, V224 PAPENDICK RI, 1977, J SOIL WATER CONSERV, V32, P49 PIMENTEL D, 1995, SCIENCE, V267, P1117 QUINE TA, 1994, IAHS PUBLICATION, V224 QUINE TA, 1997, EARTH SURF PROC LAND, V22, P799 RENARD KG, 1993, PREDICTING SOIL EROS SLATTERY MC, 1997, EARTH SURF PROC LAND, V22, P705 STEEGEN A, IN PRESS GEOMORPHOLO STONE JR, 1985, SOIL SCI SOC AM J, V49, P987 TAKKEN I, SPATIAL EVALUATION P, V37, P431 VALENTIN C, 1998, NATO ASI SERIES, V55 VANDAELE K, 1995, CATENA, V25, P213 VERITY GE, 1990, CAN J SOIL SCI, V70, P471 WATSON DA, 1986, T ASAE, V29, P98 WILLIAMS J, 1996, J SOIL WATER CONSERV, V51, P381 WISCHMEIER WH, 1978, USDA AGR HDB, V537, P58 0921-2973 Landsc. Ecol.ISI:000088037200007Katholieke Univ Leuven, Lab Expt Geomorphol, B-3000 Louvain, Belgium. Van Oost, K, Katholieke Univ Leuven, Lab Expt Geomorphol, B-3000 Louvain, Belgium.English3~?Van Sickle, J. Johnson, C. B.2008?Parametric distance weighting of landscape influence on streams427-438Landscape Ecology234We present a parametric model for estimating the areas within watersheds whose land use best predicts indicators of stream ecological condition. We regress a stream response variable on the distance-weighted proportion of watershed area that has a specific land use, such as agriculture. Distance weighting functions model the declining influence of landscape elements as a function of their flowpath distances, first to the stream channel (to-stream distance), and then down the channel to the location at which stream condition was sampled (in-stream distance). Model parameters specify different distance scales over which to-stream and in-stream influences decline. As an example, we predict an index of biotic integrity (IBI) for the fish communities in 50 small streams of the Willamette Basin of Oregon, USA, from distance-weighted proportions of agricultural or urban land use in their watersheds. The weighting functions of best-fitting models (R-2 = 0.57) represent landscape influence on IBI as extending upstream tens of kilometers along the stream channel network, while declining nearly to zero beyond a distance of 30 m from the channel. Our example shows how parametric distance weighting can identify the distance scales, and hence the approximate areas within watersheds, for which land use is most strongly associated with a stream response variable. In addition, distance-weighting parameters offer a simple and direct language for comparing the scales of landscape influence on streams across different land uses and stream ecosystem components."://WOS:000254250400006 Times Cited: 0WOS:000254250400006(10.1007/s10980-008-9200-4|ISSN 0921-2973 i|?R@Vanacker, Veerle Bellin, Nicolas Molina, Armando Kubik, Peter W.2014^Erosion regulation as a function of human disturbances to vegetation cover: a conceptual model293-309Landscape Ecology292Feb Human-induced land cover changes are causing important effects on the ecological services rendered by mountain ecosystems, and the number of case-studies of the impact of humans on soil erosion and sediment yield has mounted rapidly. In this paper, we present a conceptual model that allows evaluating overall changes in erosion regulation after human disturbances. The basic idea behind this model is that soil erosion mechanisms are independent of human impact, but that the frequency-magnitude distributions of erosion rates change as a response to human disturbances. Pre-disturbance (or natural) erosion rates are derived from in situ produced 10 Be concentrations in river sediment, while post-disturbance (or modern) erosion rates are derived from sedimentation rates in small catchments. In its simplicity, the model uses vegetation cover change as a proxy of human disturbance. The erosion regulation model is here applied in two mountainous regions with different vegetation dynamics, climatic and geological settings: the Austro Ecuatoriano, and the Spanish Betic Cordillera. Natural erosion benchmarks are necessary to assess human-induced changes in erosion rates. While the Spanish Betic Cordillera is commonly characterized as a degraded landscape, there is no significant difference between modern catchment-wide erosion and long-term denudation rates. The opposite is true for the Austro Ecuatoriano where the share of natural erosion in the total modern erosion rate is minimal for most disturbed sites. When pooling pre- and post-disturbance erosion data from both regions, the data suggest that the human acceleration of erosion is related to vegetation disturbances. The empirical regression model predicts human acceleration of erosion, here defined as the ratio of post-disturbance to pre- disturbance (or natural benchmark) erosion rate, as an exponential function of vegetation disturbance. This suggests that the sensitivity to human-accelerated erosion would be ecosystem dependent, and related to the potential vegetation cover disturbances as a result of human impact. It may therefore be expected that the potential for erosion regulation is larger in well-vegetated ecosystem where strong differences may exist in vegetation cover between human disturbed and undisturbed or restored sites.!://WOS:000331935100009Times Cited: 3 0921-2973WOS:00033193510000910.1007/s10980-013-9956-zc<79Vanacker, V. Govers, G. Barros, S. Poesen, J. Deckers, J.2003The effect of short-term socio-economic and demographic change on landuse dynamics and its corresponding geomorphic response with relation to water erosion in a tropical mountainous catchment, Ecuador1-15Landscape Ecology181aerial image analysis Andes Cuenca geomorphic response land use change suspended sediment concentration water erosion SEDIMENT YIELD ANDES PATTERNS STORAGE BASINArticleJanThe analysis of aerial photographs over a 33-year period (1962-1995) shows that land use in the study catchment is highly dynamic as a response to the land reform programs of the 1960s and 1970s and a strong population increase. The secondary forest is increasingly replaced by grassland while old grasslands are now used as cultivated land. Despite the increased pressure on the land, the upward movement of agricultural activity and the concurrent deforestation, the overall forest cover did not decline. The deforestation in the uplands is compensated for by a regeneration of secondary forest on abandoned rangelands and afforestation with Eucalyptus trees in the low-lying areas. The land use changes resulted in a strong decrease of the areas subject to intense soil degradation: afforestation with Eucalyptus trees on degraded lands was successful in controlling soil erosion in the lower parts of the catchment. The relationship between land use and sediment load in the river system is not straightforward. Statistical analysis of a time series of suspended sediment concentrations, which were measured at the outlet of three distinctive sub-catchments for a six-year period (1994-2000), revealed that the geomorphic response of the river system is not only dependent on the land use and the area affected by water erosion, but also on the spatial connectivity between sediment producing areas and the river network.://000181767500001 ISI Document Delivery No.: 659FW Times Cited: 6 Cited Reference Count: 31 Cited References: *DIR GEN EST CENS, 1960, PRIM CENS POBL EC 19 *EMPR MUN TEL AG P, 2000, INF ANN DAT MET HIDR *INEC, 1990, CENS POBL VIV 1990 *INECEL, 1982, PROYECT HIDR PAUT MA *INT I AER SURV EA, 1999, ILWIS 2 2 WIND INT L *WORLD BANK, 2000, WORLD DEV IND BLENCH R, 1999, RETHINKING NATURAL R BOYD C, 2000, NATURAL RESOURCE PER, V63, P1 COMMANDER S, 1986, WORLD DEV, V14, P79 DEKONING GHJ, 1998, AGR ECOSYST ENVIRON, V70, P231 DENONI G, 1989, CAHIER ORSTOM PEDOLO, V24, P183 DENONI G, 1993, CAHIER ORSTOM PEDOLO, V28, P254 EVANS JK, 2000, J SOIL WATER CONSERV, V55, P264 GONDARD P, 1988, LAND USE POLICY, V5, P341 HARDEN CP, 1993, PHYSICAL GEOGR, V14, P254 HARDEN CP, 1996, MT RES DEV, V16, P274 HESS CG, 1990, MT RES DEV, V10, P333 JERVES L, 1999, INFORME BATIMETRIA, V34 MORRIS A, 1997, MT RES DEV, V17, P31 POESEN JW, 1996, J SOIL WATER CONSERV, V51, P386 STEEGEN A, 2000, GEOMORPHOLOGY, V33, P25 TIFFEN M, 1994, MORE PEOPLE LESS ERO TRIMBLE SW, 1999, SCIENCE, V285, P1244 TURNER BL, 1993, POPULATION GROWTH AG VANACKER V, 2000, REV GEOGRAPHIE ALINE, V3, P65 VANOOST K, 2000, LANDSCAPE ECOL, V15, P577 VANROMPAEY AJJ, 2001, EARTH SURF PROC LAND, V26, P1221 VOS R, 1988, TRANSFORMACIONES AGR, P134 WALLING DE, 1999, HYDROBIOLOGIA, V410, P223 WHITE S, 1991, MT RES DEV, V11, P37 WUNDER S, 1996, MT RES DEV, V16, P367 0921-2973 Landsc. Ecol.ISI:000181767500001mFund Sci Res Flanders FWO, Brussels, Belgium. Katholieke Univ Leuven, Lab Expt Geomorphol, Louvain, Belgium. Empresa Publ Municipal Telecomun Agua Potable & A, Direcc Gest Ambiental, Cuenca, Ecuador. Katholieke Univ Leuven, Inst Land & Water Management, Louvain, Belgium. Vanacker, V, Fund Sci Res Flanders FWO, Brussels, Belgium. veerle.vanacker@geo.kuleuven.ac.beEnglish\<70Vanapeldoorn, R. C. Celada, C. Nieuwenhuizen, W.1994iDistribution and dynamics of the red squirrel (Sciurus vulgaris l) in a landscape with fragmented habitat227-235Landscape Ecology93ZRED SQUIRREL (SCIURUS-VULGARIS L); SPATIAL DYNAMICS; HABITAT FRAGMENTATION; METAPOPULATIONArticleSepIn a four year study data on the presence of red squirrel were collected in an agricultural landscape by counting dreys in 49 woods ranging from 0.5 to 14 ha, and differing in quality of habitat and isolation. Logit regression analysis showed that the area per woodlot covered with conifers is a good predictor of squirrel presence for each year and during the whole period, but the significance of the regression decreases with time. During the study the number of woods occupied by red squirrel increased, and smaller woods and those without conifers also became inhabited. This trend is in accordance with the positive effect of time in regression analyses on the presence of the species and on the colonization of woods, and it suggests an increase of squirrel numbers in the area. Addition of several isolation variables in the regression analyses showed significant effects in different years, and the effect of isolation was independent of time. In the first two years the area of habitat around a woodlot, the distance to the nearest woodlot larger than 30 ha, and the density of possible movement corridors have significant effects on the presence of red squirrel. In the last two years, with presumably a high number of squirrels, the (short) distance to the nearest woodlot and also the area of habitat around woods have significant effects. It is concluded that the spatial dynamics of the population can be understood as the outcome of individual spatial behaviour, rather than as the result of metapopulation processes.://A1994PL16600005 IISI Document Delivery No.: PL166 Times Cited: 23 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1994PL16600005lVANAPELDOORN, RC, DLO,IBN,INST FORESTRY & NAT RES,DEPT LANDSCAPE ECOL,POB 23,6700 AA WAGENINGEN,NETHERLANDS.English |7s 0Vanapeldoorn, R. C. Celada, C. Nieuwenhuizen, W.1994iDistribution and Dynamics of the Red Squirrel (Sciurus-Vulgaris L) in a Landscape with Fragmented Habitat227-235Landscape Ecology93Wred squirrel (sciurus-vulgaris l) spatial dynamics habitat fragmentation metapopulationSepIn a four year study data on the presence of red squirrel were collected in an agricultural landscape by counting dreys in 49 woods ranging from 0.5 to 14 ha, and differing in quality of habitat and isolation. Logit regression analysis showed that the area per woodlot covered with conifers is a good predictor of squirrel presence for each year and during the whole period, but the significance of the regression decreases with time. During the study the number of woods occupied by red squirrel increased, and smaller woods and those without conifers also became inhabited. This trend is in accordance with the positive effect of time in regression analyses on the presence of the species and on the colonization of woods, and it suggests an increase of squirrel numbers in the area. Addition of several isolation variables in the regression analyses showed significant effects in different years, and the effect of isolation was independent of time. In the first two years the area of habitat around a woodlot, the distance to the nearest woodlot larger than 30 ha, and the density of possible movement corridors have significant effects on the presence of red squirrel. In the last two years, with presumably a high number of squirrels, the (short) distance to the nearest woodlot and also the area of habitat around woods have significant effects. It is concluded that the spatial dynamics of the population can be understood as the outcome of individual spatial behaviour, rather than as the result of metapopulation processes.://A1994PL16600005-Pl166 Times Cited:30 Cited References Count:0 0921-2973ISI:A1994PL16600005jVanapeldoorn, Rc Dlo,Ibn,Inst Forestry & Nat Res,Dept Landscape Ecol,Pob 23,6700 Aa Wageningen,NetherlandsEnglish|?0 *Vandermeer, J. Perfecto, I. Schellhorn, N.2010XPropagating sinks, ephemeral sources and percolating mosaics: conservation in landscapes509-518Landscape Ecology254pWe present a framework that uses both sources and sinks as elements in the construction of a landscape matrix. We propose that the matrix be conceived as a collection of temporary habitats, some of which are sources, others of which are sinks, that form a landscape mosaic. The key element in this framing is that the sources are ephemeral and the sinks are propagating. A mean field approach is used to modify the classic metapopulation model, taking this new framework into account. Additionally a spatially explicit approach reveals different scaling rules for the percolation probability and the propagating probability.!://WOS:000275444100002Times Cited: 0 0921-2973WOS:00027544410000210.1007/s10980-010-9449-2<7f/vanDorp, D. Schippers, P. vanGroenendael, J. M.1997vMigration rates of grassland plants along corridors in fragmented landscapes assessed with a cellular automation model39-50Landscape Ecology121useed dispersal; migration; corridor; restoration; grassland plants; fragmentation SEED DISPERSAL; VEGETATION; ECOLOGYArticleFebZ This study investigated the efficacy of linear landscape elements in fragmented landscapes as corridors for perennial grassland species with short-range seed dispersal. Corridors are assumed to be essential for the persistence of metapopulations in fragmented landscapes, but it is unclear to what extent linear landscape elements such as ditch banks and road verges can function as corridors for those species. The principal factors that determine the rate of migration through corridors include the width and habitat quality of patches within a corridor (expressed as the population growth rate lambda) and the dispersal capacity of plants (expressed as the slope a of the relationship between seed number and log-distance), A cellular automation model was used to simulate the effects of the principal factors on the rate of migration, Simulations with different levels of the principal factors showed highly significant and positive main effects of dispersal capacity, habitat quality and width of corridors on the migration rate. Significant interactions existed between dispersal capacity x width and dispersal capacity x habitat quality (p < 0.0001), indicating that the effects of width and habitat quality depended on the dispersal capacity. In narrow corridors most of the dispersed seeds were deposited outside the corridor, which significantly reduced migration rates, especially for species with long-range dispersal (alpha = -0.4). In wide corridors (up to 20 m), seed losses were much smaller and migration rates approximated those of continuous habitats. The contribution of the few long-range seeds to the rate of migration was significant when habitat quality was high (population growth rates up to 2.5). However, in all simulations migration rates were very low, i.e. < 5 m/yr. It is concluded that linear landscape elements are not effective corridors in fragmented landscapes for plants with short-range seed dispersal, because migration rates are low (< 5 m/yr), landscape elements vary in the percentage of high quality patches, and refugia and suitable habitat patches are frequently several kilometres apart, making a cohesive infrastructure of corridors for plants elusive. It is argued that the best way to conserve endangered plant species that encounter dispersal barriers is to harvest seeds from nearby source populations and introduce them as suitable habitats.://A1997XQ44800005 {ISI Document Delivery No.: XQ448 Times Cited: 30 Cited Reference Count: 34 Cited References: BULLOCK SH, 1977, ECOLOGY, V58, P681 BUNCE RHG, 1990, SPECIES DISPERSAL AG CZARAN T, 1992, TRENDS ECOL EVOL, V7, P38 FAHRIG L, 1991, QUANTITATIVE METHODS, P417 FALK DA, 1992, CONSERVATION BIOL TH, P397 GILPIN M, 1991, METAPOPULATION DYNAM HERBEN T, 1991, OIKOS, V60, P215 HOWE HF, 1982, ANNU REV ECOL SYST, V13, P201 JANZEN DH, 1984, AM NAT, V123, P338 LEISHMAN MR, 1992, AUST J BOT, V40, P599 MCCLANAHAN TR, 1986, ECOL MODEL, V32, P301 MCEVOY PB, 1987, ECOLOGY, V68, P2006 MELMAN TCP, 1988, CONNECTIVITY LANDSCA, V29, P157 MERRIAM G, 1984, METHODOLOGY LANDSCAP, V1, P5 NIPVANDERVOORT J, 1979, J BIOGEOGR, V6, P301 OUBORG NJ, 1993, THESIS UTRECHT U PRIMACK RB, 1992, CONSERV BIOL, V6, P513 RABINOWITZ D, 1991, AM J BOT, V68, P596 SAUNDERS D, 1991, ROLE CORRIDORS SCHMIDT W, 1989, VEGETATIO, V80, P147 SILVERTOWN J, 1992, J ECOL, V80, P527 SKOGLUND SJ, 1990, CAN J BOT, V68, P754 SYKORA KV, 1993, PLANTENGEMEENSCHAPPE, V59 VANDORP D, 1996, IN PRESS CANADIAN J VANDORP D, 1996, THESIS WAGENINGEN AG VANGROENENDAEL J, 1988, TRENDS ECOL EVOL, V3, P264 VANGROENENDAEL JM, 1990, NATUURONTWIKKELING L, V1, P67 VANSTRIEN AJ, 1989, J APPL ECOL, V26, P989 VERKAAR HJ, 1983, NEW PHYTOL, V95, P335 VERKAAR HJ, 1990, SPECIES DISPERSAL AG, P82 VERMEULEN HJW, 1994, BIOL CONSERV, V69, P339 VOS CC, 1993, LANDSCAPE ECOLOGY ST, P1 WERNER PA, 1975, CAN J BOT, V53, P810 WILLSON MF, 1992, SEEDS ECOLOGY REGENE, P61 0921-2973 Landsc. Ecol.ISI:A1997XQ44800005UAGR UNIV WAGENINGEN,DEPT TERR ECOL & NAT CONSERVAT,NL-6708 PD WAGENINGEN,NETHERLANDS.English|7l Vanhees, W. W. S.19942A Fractal Model of Vegetation Complexity in Alaska271-278Landscape Ecology94$alaska complexity fractal vegetationDecGA methodology using fractals to measure vegetation complexity in three regions of Alaska is presented. Subjective, binomial (0 = simple, 1 = complex) classifications of the complexity of mapped vegetation polygon patterns within continuous forest inventory plots measured in the regions were made by interpreters of aerial photographs. The fractal dimensions of the vegetation patterns within the plots then were estimated. Subsequently, the subjective classifications of the photo-interpreted plots were regressed against fractal dimension by using logistic regression. Assessment of interobserver agreement among the aerial photo interpreters, by using estimated unweighted Kappa coefficients, indicated substantial classification agreement among observers. Examination of general versus regional applicability of the logistic models provided strong support for applicability of a single model to all three regions. The logistic model provides numerical identification of the division between simple and complex patterns. Possible applications beyond the needs of the study are discussed.://A1994PX89500004,Px895 Times Cited:6 Cited References Count:0 0921-2973ISI:A1994PX89500004fVanhees, Wws Us Forest Serv,Pacific Nw Res Stn,Forestry Sci Lab,3301 C St,Suite 200,Anchorage,Ak 99503English? GVannier, Clémence Vasseur, Chloé Hubert-Moy, Laurence Baudry, Jacques20119Multiscale ecological assessment of remote sensing images 1053-1069Landscape Ecology268Springer NetherlandsEarth and Environmental ScienceIn landscape ecology, the importance of map extent and resolution on the value of landscape indices is widely discussed, but the information content of the map, mostly derived from remote sensing images, is not. In this study, we sought (1) to understand the influence of changes in maps’ spatial and spectral resolution of agricultural landscape elements, taking hedgerow networks as a case study, and (2) to explore how predictions of species distribution might be affected by maps’ resolutions, taking two carabid species as a case study. To do so, we compared maps from different remote sensors, derived two landscape characterization variables from the maps related to patterns known to drive ecological processes, and analyzed their predictive power on biological data distribution to assess the information content of these maps. The results show that (1) the use of several methods, including landscape metrics, was useful to assess map validity; (2) the spatial resolution of satellite images is not the only important factor; changes in spectral resolution significantly alter maps; (3) the relevant definition of “hedgerow” to construct functional maps is species and process specific; thus the different maps are not either good or bad, but rather provide complementary information; (4) the more a species responds to network structure and over small areas, the less the different maps can be substitutable one to another.+http://dx.doi.org/10.1007/s10980-011-9626-y 0921-297310.1007/s10980-011-9626-y <7 (Vasques, G. M. Grunwald, S. Myers, D. B.2012pAssociations between soil carbon and ecological landscape variables at escalating spatial scales in Florida, USA355-367Landscape Ecology273soil carbon scale variogram spatial variation spatial autocorrelation land-use change organic-carbon terrain attributes matter everglades grassland framework nitrogen ireland issuesMarThe spatial distribution of soil carbon (C) is controlled by ecological processes that evolve and interact over a range of spatial scales across the landscape. The relationships between hydrologic and biotic processes and soil C patterns and spatial behavior are still poorly understood. Our objectives were to (i) identify the appropriate spatial scale to observe soil total C (TC) in a subtropical landscape with pronounced hydrologic and biotic variation, and (ii) investigate the spatial behavior and relationships between TC and ecological landscape variables which aggregate various hydrologic and biotic processes. The study was conducted in Florida, USA, characterized by extreme hydrologic (poorly to excessively drained soils), and vegetation/land use gradients ranging from natural uplands and wetlands to intensively managed forest, agricultural, and urban systems. We used semivariogram and landscape indices to compare the spatial dependence structures of TC and 19 ecological landscape variables, identifying similarities and establishing pattern-process relationships. Soil, hydrologic, and biotic ecological variables mirrored the spatial behavior of TC at fine (few kilometers), and coarse (hundreds of kilometers) spatial scales. Specifically, soil available water capacity resembled the spatial dependence structure of TC at escalating scales, supporting a multi-scale soil hydrology-soil C process-pattern relationship in Florida. Our findings suggest two appropriate scales to observe TC, one at a short range (autocorrelation range of 5.6 km), representing local soil-landscape variation, and another at a longer range (119 km), accounting for regional variation. Moreover, our results provide further guidance to measure ecological variables influencing C dynamics.://000300087500004-889QE Times Cited:0 Cited References Count:45 0921-2973Landscape EcolISI:000300087500004xGrunwald, S Univ Florida, Soil & Water Sci Dept, 2169 McCarty Hall,POB 110290, Gainesville, FL 32611 USA Univ Florida, Soil & Water Sci Dept, 2169 McCarty Hall,POB 110290, Gainesville, FL 32611 USA Univ Florida, Soil & Water Sci Dept, Gainesville, FL 32611 USA Brazilian Agr Res Corp, Natl Ctr Soil Res, BR-22460000 Rio De Janeiro, RJ, Brazil ARS, USDA, Columbia, MO 65211 USADOI 10.1007/s10980-011-9702-3English<7qVega-Garcia, C. Chuvieco, E.2006Applying local measures of spatial heterogeneity to Landsat-TM images for predicting wildfire occurrence in mediterranean landscapes595-605Landscape Ecology214forest fire; Landsat; landscape pattern; Mediterranean landscape; remote sensing; Spain; wildfire occurrence CLASSIFICATION; PATTERNArticleMayIn mountainous Mediterranean regions, land abandonment processes in past decades are hypothesized to trigger secondary vegetal succession and homogenization, which in recent years has increased the size of burned areas. We conducted an analysis of temporal changes in landscape vegetal spatial pattern over a 15-year period (1984-1998) in a rural area of 672.3 km(2) in Eastern Spain to investigate the relationship between local landscape heterogeneity and wildfire occurrence. Heterogeneity was analyzed from textural metrics derived from non-classified remote sensing data at several periods, and was related to wildfire history in the study area. Several neural network models found significant relationships between local spatial pattern and future fire occurrence. In this study, sensitivity analysis of the texture variables suggested that fire occurrence, estimated as probability of burning in the near future, increased where local homogeneity was higher.://000237487700011 ISI Document Delivery No.: 041WR Times Cited: 0 Cited Reference Count: 45 Cited References: *ICONA, 1990, CLAV FOT ID MOD COMB *NEUR, 2000, NEUR COMPL SOL NEUR *PCI INC, 1997, US PCI SOFTW *SAS I INC, 1999, SAS ONL DOC VERS 8 ALBINI FA, 1976, INT30 USDA FOR SERV ATZBERGER C, 2004, REMOTE SENS ENVIRON, V93, P53 BENAKIVA M, 1985, DISCRETE CHOICE ANAL BRIDLE JS, 1990, NATO ASI SERIES F, V68 CHAVEZ PS, 1996, PHOTOGRAMM ENG REM S, V62, P1025 CONNERS RW, 1980, IEEE T PATTERN PAMI, V2 COX DR, 1989, ANAL BINARY DATA DELCASTILLO JR, 2000, DEFENSA CONTRA INCEN DUGUY B, 1998, THESIS I AGR MED ZAR FAHLMAN SE, 1988, NEUR, V2 FARINA A, 1998, PRINCIPLES METHODS L FORMAN RTT, 1986, LANDSCAPE ECOLOGY GIMENO RR, 1994, CATALOGO FLORISTICO HARALICK RM, 1973, IEEE T SMC, V3, P610 HARALICK RM, 1979, P IEEE, V67, P786 HEPNER GF, 1990, PHOTOGRAMM ENG REM S, V56, P469 HOSMER DW, 1989, APPL LOGISTIC REGRES KOZA JR, 1993, GENETIC PROGRAMMING LLORET F, 2002, LANDSCAPE ECOL, V17, P745 MADDALA GS, 1988, INTRO ECONOMETRICS MAGNUSSEN S, 2000, SILVA FENN, V34, P351 MOREIRA F, 2001, LANDSCAPE ECOL, V16, P557 MUNOZ RV, 2000, DEFENSA CONTRA INCEN MYNENI RB, 1995, IEEE T GEOSCI REMOTE, V33, P481 NELSON RF, 2000, BIOSCIENCE, V50, P419 ONEILL RV, 1996, LANDSCAPE ECOL, V11, P169 PRENTICE RL, 1986, BIOMETRIKA, V73, P1 RIANO D, 2002, CAN J FOREST RES, V32, P1301 RIANO D, 2003, IEEE T GEOSCI REMO 1, V41, P1056 RIVASMARTINEZ S, 1987, MEMORIA MAPA SERIE V ROMEROCALCERRAD.R, 2002, FOREST FIRE RES WILD ROMEROCALCERRADA R, 2004, LANDSCAPE URBAN PLAN, V66, P217 SHUPE SM, 2004, REMOTE SENS ENVIRON, V93, P131 TEILLET PM, 1982, CAN J REMOTE SENS, V8, P84 TERRADAS J, 1996, ECOLOGIA FOC, P209 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 VASCONCELOS MJP, 2001, PHOTOGRAMMETRIC ENG, V67, P73 VEGAGARCIA C, 1995, INT J WILDLAND FIRE, V5, P101 VEGAGARCIA C, 1996, AI APPLICATIONS, V10, P9 VEGAGARCIA C, 2003, THESIS U ALCALA MADR VIEDMA O, 1998, P 3 INT C FOR FIR RE, V2, P1593 0921-2973 Landsc. Ecol.ISI:000237487700011Univ Lleida, Afr & Forest Engn Dept, Lleida 25198, Spain. Univ Alcala De Henares, Dept Geog, Alcala De Henares 28801, Spain. Vega-Garcia, C, Univ Lleida, Afr & Forest Engn Dept, Avda Alcalde Rovira Roure 191, Lleida 25198, Spain. cvega@eagrof.udl.esEnglish #<7 BVeran, S. Kleiner, K. J. Choquet, R. Collazo, J. A. Nichols, J. D.2012CModeling habitat dynamics accounting for possible misclassification943-956Landscape Ecology277habitat dynamics land cover habitat misclassification accuracy hidden markov chain multi-event model capture-recapture models spatial autocorrelation accuracy assessment landscape ecology pattern fragmentation transitions region errorAugLand cover data are widely used in ecology as land cover change is a major component of changes affecting ecological systems. Landscape change estimates are characterized by classification errors. Researchers have used error matrices to adjust estimates of areal extent, but estimation of land cover change is more difficult and more challenging, with error in classification being confused with change. We modeled land cover dynamics for a discrete set of habitat states. The approach accounts for state uncertainty to produce unbiased estimates of habitat transition probabilities using ground information to inform error rates. We consider the case when true and observed habitat states are available for the same geographic unit (pixel) and when true and observed states are obtained at one level of resolution, but transition probabilities estimated at a different level of resolution (aggregations of pixels). Simulation results showed a strong bias when estimating transition probabilities if misclassification was not accounted for. Scaling-up does not necessarily decrease the bias and can even increase it. Analyses of land cover data in the Southeast region of the USA showed that land change patterns appeared distorted if misclassification was not accounted for: rate of habitat turnover was artificially increased and habitat composition appeared more homogeneous. Not properly accounting for land cover misclassification can produce misleading inferences about habitat state and dynamics and also misleading predictions about species distributions based on habitat. Our models that explicitly account for state uncertainty should be useful in obtaining more accurate inferences about change from data that include errors.://000306068200002-969PP Times Cited:0 Cited References Count:39 0921-2973Landscape EcolISI:000306068200002Veran, S USGS Patuxent Wildlife Res Ctr, 12100 Beech Forest Rd, Laurel, MD 20708 USA USGS Patuxent Wildlife Res Ctr, 12100 Beech Forest Rd, Laurel, MD 20708 USA USGS Patuxent Wildlife Res Ctr, Laurel, MD 20708 USA N Carolina State Univ, Dept Zool, Raleigh, NC 27695 USA N Carolina State Univ, US Geol Survey, N Carolina Cooperat Fish & Wildlife Res Unit, Raleigh, NC 27695 USA Sch Forestry & Wildlife Sci, Auburn, AL 36849 USA CNRS, UMR 5175, Ctr Ecol Fonct & Evolut, F-34293 Montpellier 5, FranceDOI 10.1007/s10980-012-9746-zEnglish<7\7Verbeylen, G. De Bruyn, L. Adriaensen, F. Matthysen, E.2003lDoes matrix resistance influence Red squirrel (Sciurus vulgaris L. 1758) distribution in an urban landscape?791-805Landscape Ecology188red squirrel cost distance effective distance GIS landscape resistance patch isolation patch quality patch size HETEROGENEOUS LANDSCAPES HABITAT FRAGMENTATION POPULATION-DENSITY CONNECTIVITY DYNAMICS MODEL DISPERSAL METAPOPULATION CONSERVATION OCCUPANCYArticleMIn determining isolation effects in fragmented populations, the landscape matrix is not often considered. Usually simple distance measures are used to quantify degree of isolation. We tested the effect of the matrix on the presence of red squirrels in 354 wooded patches in the Brussels Region, by comparing several isolation measures. These were 1) distance to the nearest source patch, 2) the Hanski-measure (a combination of distance to and size of all possible sources), 3) effective distances calculated from different least cost models using the ArcView grid extension 'Cost Distance' (a combination of distance and resistance of the landscape, with different resistances for different landscape types) and 4) some combinations of the Hanski-measure and the effective distances. Size and quality of the target patches were always included in the tests of the predictive power of different isolation measures on squirrel presence/absence. All variables examined (patch size, quality and isolation) significantly influenced squirrel presence. Models using the effective distances gave the best results. Models including the Hanski-measure improved significantly when Euclidean distance was replaced by effective distance, showing that parameterisation of matrix resistance added significant additional explanatory power when modelling squirrel presence.://000188716100005 ISI Document Delivery No.: 770HA Times Cited: 15 Cited Reference Count: 54 Cited References: *SAS I, 1989, SAS STAT US GUID VER, V1 *SAS I, 1989, SAS STAT US GUID VER, V2 ADRIAENSEN F, 2003, LANDSCAPE URBAN PLAN, V996, P1 AK A, 1995, THESIS U UTRECHT UTR AKAIKE H, 1974, IEEE T AUTOMATIC CON, V19, P716 ANDREN H, 1994, OIKOS, V71, P355 ASFERG T, 1997, SAUGETIERKUNDLICHE I, V21 BELISLE M, 2001, CONSERV ECOL, V5 BERGGREN A, 2001, J ANIM ECOL, V70, P663 BUNN AG, 2000, J ENVIRON MANAGE, V59, P265 CELADA C, 1994, BIOL CONSERV, V69, P177 CHARDON JP, 2003, LANDSCAPE ECOL, V18, P561 DELIN AE, 1999, LANDSCAPE ECOL, V14, P67 DUNNING JB, 1995, ECOL APPL, V5, P3 FERRERAS P, 2001, BIOL CONSERV, V100, P125 GONZALES EK, 2000, THESIS U GUELPH GUEL GRAHAM CH, 2001, CONSERV BIOL, V15, P1789 HALPIN PN, 2000, P 20 ANN ESRI US C J HANSKI I, 1994, J ANIM ECOL, V63, P151 HARMS WB, 1989, CHANGING LANDSCAPES, P73 HARRISON S, 1999, ECOGRAPHY, V22, P225 HASTINGS A, 1996, BIOL CONSERV, V78, P143 JOHNSON AR, 1992, LANDSCAPE ECOL, V7, P63 KAREIVA PM, 1983, OECOLOGIA, V57, P322 MATTHYSEN E, 1999, OECOLOGIA, V119, P501 MICHELS E, 2001, MOL ECOL, V10, P1929 MOILANEN A, 2002, ECOLOGY, V83, P1131 NAGELKERKE NJD, 1991, BIOMETRIKA, V78, P691 PICKETT STA, 2001, ANNU REV ECOL SYST, V32, P127 QUINBY P, 1999, OPPORTUNITIES WILDLI RICKETTS TH, 2001, AM NAT, V158, P87 RODRIGUEZ A, 1999, J APPL ECOL, V36, P649 SCHIPPERS P, 1996, ECOGRAPHY, V19, P97 SINGLETON PJ, 2000, I90 SNOQUALMIE PASS SUKOPP H, 1990, URBAN ECOLOGY PLANTS TAYLOR PD, 1993, OIKOS, V68, P571 TISCHENDORF L, 1997, ECOL MODEL, V103, P33 TISCHENDORF L, 2000, OIKOS, V90, P7 TITTENSOR AM, 1970, NOTES MAMMAL SOC, P528 TSCHARNTKE T, 2002, ECOL RES, V17, P229 VANAPELDOORN RC, 1994, LANDSCAPE ECOL, V9, P227 VERBEYLEN G, 2003, ECOGRAPHY, V26, P118 VILLALBA S, 1998, KEY CONCEPTS LANDSCA, P205 VOS CC, 2001, AM NAT, V157, P24 VOS CC, 2001, HEREDITY 5, V86, P598 WALKER R, 1997, P 1997 ESRI EUR US C WAUTERS L, 1992, J ZOOL, V227, P71 WAUTERS L, 1994, OIKOS, V69, P140 WAUTERS LA, 1988, J ZOOL, V214, P179 WAUTERS LA, 1990, MAMMALIA, V54, P377 WAUTERS LA, 1997, CONSERVATION RED SQU, P79 WHITCOMB RF, 1981, FOREST ISLAND DYNAMI, P125 XU JP, 1995, INT J GEOGR INF SYST, V9, P153 ZAMMIT AE, 1999, PROPOSAL IDENTIFYING 0921-2973 Landsc. Ecol.ISI:0001887161000052Univ Antwerp UIA, Dept Biol, Lab Anim Ecol, B-2610 Wilrijk, Belgium. Inst Nat Conservat, B-1070 Brussels, Belgium. Univ Antwerp, RUCA, Dept Biol, Evolutionary Biol Grp, B-2020 Antwerp, Belgium. Verbeylen, G, Inst Forestry Game Management, B-9500 Geraardsbergen, Belgium. goedele.verbeylen@lin.vlaanderen.beEnglish?'B. Verboom R. van Apeldoorn1990IEffects of habitat fragmentation on the red squirrel, Sciurus vulgaris L.171-176Landscape Ecology42/3IThe effects of woodlot size and isolation, in relation to habitat fragmentation, on the distribution of the red squirrel were studied. In The Netherlands, 50 woodlots (0.55 - 13.78 ha) were surveyed in an agricultural landscape for the presence of red squirrel. In 26 woodlots squirrel dreys (nests) were found. Logit regression analysis showed that woodlot size and the area per woodlot covered with coniferous trees were the best predictors of squirrel presence. Addition of isolation variables by means of a stepwise forward regression method showed significant effects of the distance to a large, permanently inhabited wood and the amount of surrounding wood. No effect was found for the distance to the nearest woodlot (> 0.5 ha). The model could be further improved by adding a measure of the amount of hedgerows surrounding a woodlot. <7aVerboom, B. Huitema, H.1997The importance of linear landscape elements for the pipistrelle Pipistrellus pipistrellus and the serotine bat Eptesicus serotinus117-125Landscape Ecology122bats; hedgerows; linear landscape elements; orientation; Pipistrellus; Eptesicus FEEDING ECOLOGY; VESPERTILIONIDAE; CHIROPTERA; PREGNANCY; LACTATION; BEHAVIOR; FLIGHT; BIRDS; DIETArticleAprMThe relation between two species of bats, the pipistrelle (Pipistrellus pipistrellus (Schreber, 1774)) and the serotine (Eptesicus serotinus (Schreber, 1774)) and linear landscape elements such as hedgerows, tree lines and tree lanes was studied in an agricultural area in The Netherlands. The pipistrelle was observed almost entirely close to landscape elements, while serotines more frequently crossed fields and meadows. Serotine activity in these open areas was, however, negatively related to the distance to a landscape element and to windspeed. On a landscape scale the results indicate a more than proportional positive relation between the density of serotine bats and the density of linear landscape elements, whereas this relation was only proportional in the case of the pipistrelle. It is argued, that landscapes with a high density of linear elements have a surplus value for serotine bats. Three possible functions of linear elements for bats (orientation clues, foraging habitat and shelter from wind and/or predators) are discussed. Any of these may explain the results of this study.://A1997XQ45000004 ISI Document Delivery No.: XQ450 Times Cited: 27 Cited Reference Count: 33 Cited References: BATEMAN GC, 1974, J MAMMAL, V55, P45 BELL WJ, 1991, SEARCHING BEHAV BEHA FORMAN RTT, 1984, ENVIRON MANAGE, V8, P495 GETZ LL, 1978, J MAMMAL, V59, P208 HELMER W, 1983, LUTRA, V26, P1 HENDERSON MT, 1985, BIOL CONSERV, V31, P95 HOARE LR, 1991, J ZOOL, V225, P665 KALKO EKV, 1993, BEHAV ECOL SOCIOBIOL, V33, P415 KAPTEYN K, 1990, 1081 AGR U WAG NAT C KARG J, 1985, ARCH NATURSCHUTZ LAN, V25, P247 LABEE AH, 1983, LUTRA, V26, P12 LEWIS T, 1969, J APPL ECOL, V6, P443 LEWIS T, 1969, J APPL ECOL, V6, P453 LEWIS T, 1970, ANN APPL BIOL, V66, P477 LIMPENS HJG, 1989, LUTRA, V32, P1 LIMPENS HJG, 1991, MYOTIS, V29, P63 MILLER LA, 1981, J COMP PHYSIOL, V142, P67 MUELLER H, 1957, SCIENCE, V126, P307 NEUWEILER G, 1988, ANIMAL SONAR PROCESS, P535 NEUWEILER G, 1990, PHYSIOL REV, V70, P615 OPDAM P, 1985, BIOL CONSERV, V34, P333 RACEY PA, 1985, J ANIM ECOL, V54, P205 RIEGER I, 1990, MITT NATURF GES SCHA, V35, P37 ROBINSON MF, 1993, J ZOOL, V231, P239 SPEAKMAN JR, 1991, MAMMAL REV, V21, P123 STONES RC, 1969, J MAMMAL, V50, P157 SULLIVAN CM, 1993, J ZOOL, V231, P656 SWIFT SM, 1985, J ANIM ECOL, V54, P217 TAYLOR LR, 1974, J ANIM ECOL, V43, P225 VANDORP D, 1987, LANDSCAPE ECOLOGY, V1, P59 VERBOOM B, 1990, LANDSCAPE ECOL, V4, P171 WEGNER JF, 1979, J APPL ECOL, V16, P349 WILLIAMS TC, 1966, ANIM BEHAV, V14, P486 0921-2973 Landsc. Ecol.ISI:A1997XQ45000004MVerboom, B, INST FORESTRY & NAT RES,POB 23,NL-6700 AA WAGENINGEN,NETHERLANDS.English|? _Verboom, Jana Schippers, Peter Cormont, Anouk Sterk, Marjolein Vos, Claire C. Opdam, Paul F. M.2010Population dynamics under increasing environmental variability: implications of climate change for ecological network design criteria 1289-1298Landscape Ecology258OctThere is growing evidence that climate change causes an increase in variation in conditions for plant and animal populations. This increase in variation, e.g. amplified inter-annual variability in temperature and rainfall has population dynamical consequences because it raises the variation in vital demographic rates (survival, reproduction) in these populations. In turn, this amplified environmental variability enlarges population extinction risk. This paper demonstrates that currently used nature conservation policies, principles, and generic and specific design criteria have to be adapted to these new insights. A simulation shows that an increase in variation in vital demographic rates can be compensated for by increasing patch size. A small, short-lived bird species like a warbler that is highly sensitive to environmental fluctuations needs more area for compensation than a large, long-lived bird species like a Bittern. We explore the conservation problems that would arise if patches or reserve sizes would need to be increased, e.g. doubled, in order to compensate for increase in environmental variability. This issue has serious consequences for nature policy when targets are not met, and asks for new design criteria.!://WOS:000281725700012YTimes Cited: 2 10th International Congress of Ecology Aug 16-21, 2009 Brisbane, AUSTRALIA 0921-2973WOS:00028172570001210.1007/s10980-010-9497-7ڽ7=Verburg, PeterH Asselen, Sanneke Zanden, EmmaH Stehfest, Elke2013TThe representation of landscapes in global scale assessments of environmental change 1067-1080Landscape Ecology286Springer NetherlandsTLandscape Global Spatial structure Integrated assessment Ecosystem services Land use 2013/07/01+http://dx.doi.org/10.1007/s10980-012-9745-0 0921-2973Landscape Ecol10.1007/s10980-012-9745-0English<7%Verburg, P. H.2006=Simulating feedbacks in land use and land cover change models 1171-1183Landscape Ecology218land use and land cover change; model; feedback; complex systems HOUSEHOLD DECISION-MAKING; AGENT-BASED MODEL; TEMPORAL COMPLEXITY; MULTISCALE ANALYSIS; LANDCOVER CHANGE; DRIVING FORCES; SPATIAL MODELS; SYSTEMS; FUTURE; LEVELArticleNov%In spite of the many advances in land use and land cover change modelling over the past decade many challenges remain. One of these challenges relates to the explicit treatment of feedback mechanisms in descriptive models of the land use system. This paper argues for model-based analysis to explore the role of feedback mechanisms as determinants of land use dynamics and system evolution. Different types of feedbacks in the land use system are discussed addressing interactions over scales of analysis, feedbacks between impacts and driving forces of land use change and feedbacks between agents and land units. The inclusion of feedbacks in land use models will require new methods for model parameterization and calibration, but will ultimately increase our understanding of land use system dynamics.://000242089300001 ISI Document Delivery No.: 106GP Times Cited: 0 Cited Reference Count: 94 Cited References: *EEA, 1999, ENV EUR UN TURN CENT *GLP, 2005, 53IHDP IGBP ADGER WN, 2000, PROG HUM GEOG, V24, P347 AGARWAL C, 2001, REV ASSESSMENT LAND BAKER WL, 1999, SPATIAL MODELING FOR, P333 BERGER T, 2001, AGR ECON, V25, P245 BOLLIGER J, 2005, ECOL COMPLEX, V2, P107 BONABEAU E, 2002, P NATL ACAD SCI U S3, V99, P7280 BOSSEL H, 1999, INDICATORS SUSTAINAB BOUSQUET F, 2004, ECOL MODEL, V176, P313 BRAIMOH AK, 2004, EARTH INTERACT, V8, P1 BRIASSOULIS H, 2000, WEB BOOK REGIONAL SC BROWN DG, 2005, INT J GEOGR INF SCI, V19, P153 BROWN DG, 2005, J GEOGRAPHICAL SYSTE, V7, P25 BURGI M, 2004, LANDSCAPE ECOL, V19, P857 BYRNE D, 1998, COMPLEXITY THEORY SO CARVALHO G, 2004, ENV DEV SUSTAIN, V6, P163 CASTELLA JC, 2005, AGR SYST, V86, P312 CASTELLA JC, 2005, ECOLOGY SOC, V10, P27 COSTANZA R, 2003, FUTURES, V35, P651 COUCLELIS H, 2001, GEOGRAPHIC INFORM SY, P33 COUCLELIS H, 2005, ENVIRON PLANN A, V37, P1353 DEADMAN P, 2004, ENVIRON PLANN B, V31, P693 DENIJS TCM, 2004, J ENVIRON MANAGE, V72, P35 EVANS TP, 2001, ECOL MODEL, V143, P95 EVANS TP, 2004, J ENVIRON MANAGE, V72, P57 FISCHER G, 2001, AGR ECOSYST ENVIRON, V85, P163 FOLEY JA, 2003, FRONT ECOL ENVIRON, V1, P38 FOLEY JA, 2005, SCIENCE, V309, P570 GEIST HJ, 2002, BIOSCIENCE, V52, P143 GEIST HJ, 2004, BIOSCIENCE, V54, P817 GEOGHEGAN J, 1998, PEOPLE PIXELS LINKIN, P51 GREENE WH, 2000, ECONOMETRIC ANAL GRIFFITH DA, 2005, ANN ASSOC AM GEOGR, V95, P740 GRIMM V, 1999, ECOL MODEL, V115, P129 GUISAN A, 2000, ECOL MODEL, V135, P147 GUTMAN G, 2004, LAND CHANGE SCI OBSE HEISTERMANN M, 2006, AGR ECOSYST ENVIRON, V114, P141 HEUVELINK GBM, 1993, INT J GEOGR INF SYST, V7, P231 HIETEL E, 2004, LANDSCAPE ECOL, V19, P473 HOLLING CS, 1996, RIGHTS NATURE ECOLOG, P57 HOLLING CS, 2001, ECOSYSTEMS, V4, P390 HOSHINO S, 2001, LAND USE POLICY, V18, P75 LAMBIN EF, 2000, 48 IGBP LAMBIN EF, 2003, ANNU REV ENV RESOUR, V28, P205 LEVIN SA, 1998, ECOSYSTEMS, V1, P431 LIGTENBERG A, 2004, J ENVIRON MANAGE, V72, P43 LOW B, 1999, ECOL ECON, V31, P227 MANSON SM, 2001, GEOFORUM, V32, P405 MANSON SM, 2005, AGR ECOSYST ENVIRON, V111, P47 MEIJL HV, 2006, AGR ECOSYST ENVIRON, V114, P21 MILNE BT, 1998, ECOSYSTEMS, V1, P449 MUNROE DK, 2002, AGR ECON, V27, P355 NELSON GC, 2001, LAND ECON, V77, P187 NEPSTAD D, 2001, FOREST ECOL MANAG, V154, P395 ORESKES N, 1994, SCIENCE, V263, P641 OSULLIVAN D, 2000, ENVIRON PLANN A, V32, P1409 OSULLIVAN D, 2004, T I BRIT GEOGR, V29, P282 OVERMARS KP, 2005, INT J GEOGR INF SCI, V19, P125 OVERMARS KP, 2006, AGR SYST, V89, P435 PAN WKY, 2005, GLOBAL PLANET CHANGE, V47, P232 PARKER DC, 2003, ANN ASSOC AM GEOGR, V93, P314 PARKER DC, 2004, AGR ECOSYST ENVIRON, V101, P233 PIJANOWSKI BC, 2002, COMPUTERS ENV URBAN, V26, P553 POLSKY C, 2004, ANN ASSOC AM GEOGR, V94, P549 PONTIUS RG, 2004, ECOL MODEL, V179, P445 REIDSMA P, 2006, AGR ECOSYST ENVIRON, V114, P86 RINDFUSS RR, 2003, PEOPLE ENV APPROACHE, P1 RINDFUSS RR, 2004, P NATL ACAD SCI USA, V101, P13976 ROUCHIER J, 2001, J ECON DYN CONTROL, V25, P527 RUDEL TK, 2005, TROPICAL FORESTS REG SCHMIT C, 2006, ENVIRON SCI POLICY, V9, P174 SCHOORL JM, 2004, CATENA, V57, P35 SCOONES I, 1999, ANNU REV ANTHROPOL, V28, P479 STEPHENNE N, 2001, AGR ECOSYST ENVIRON, V85, P145 TURNER BL, 1995, 35 IGBP TURNER BL, 1997, ECUMENE, V4, P196 TURNER BL, 2004, LAND CHANGE SCI OBSE, P431 VANNOORDWIJK M, 2002, ECOL MODEL, V149, P113 VELDKAMP A, 2001, AGR ECOSYST ENVIRON, V85, P1 VERBURG PH, 1999, ECOL MODEL, V116, P45 VERBURG PH, 2000, ECOSYSTEMS, V3, P369 VERBURG PH, 2002, ENVIRON MANAGE, V30, P391 VERBURG PH, 2004, GEOJOURNAL, V61, P309 VERBURG PH, 2004, GEOPH MONOG SERIES, V153, P217 VERBURG PH, 2004, LANDSCAPE ECOL, V19, P77 VOINOV A, 1999, ENVIRON MODELL SOFTW, V14, P473 WALSH SJ, 1999, PHOTOGRAMM ENG REM S, V65, P97 WALSH SJ, 2001, AGR ECOSYST ENVIRON, V85, P47 WEAR DN, 1998, ECOSYSTEMS, V1, P575 WHITE R, 2000, COMPUTERS ENV URBAN, V24, P383 WU JG, 2002, ECOL MODEL, V153, P1 WU JG, 2004, LANDSCAPE ECOL, V19, P125 ZALIDIS GC, 2004, J ENVIRON MANAGE, V70, P315 0921-2973 Landsc. Ecol.ISI:000242089300001Univ Wageningen & Res Ctr, Dept Environm Sci, NL-6700 AA Wageningen, Netherlands. Verburg, PH, Univ Wageningen & Res Ctr, Dept Environm Sci, POB 37, NL-6700 AA Wageningen, Netherlands. Peter.Verburg@wur.nlEnglish S<7 FVerburg, P. H. Koomen, E. Hilferink, M. Perez-Soba, M. Lesschen, J. P.2012eAn assessment of the impact of climate adaptation measures to reduce flood risk on ecosystem services473-486Landscape Ecology274climate change adaptation integrated spatial modelling land use ecosystem services flood risk soil protection land-use change use change scenarios cover change europe dynamics future consequences areas model landscapesAprMeasures of climate change adaptation often involve modification of land use and land use planning practices. Such changes in land use affect the provision of various ecosystem goods and services. Therefore, it is likely that adaptation measures may result in synergies and trade-offs between a range of ecosystems goods and services. An integrative land use modelling approach is presented to assess such impacts for the European Union. A reference scenario accounts for current trends in global drivers and includes a number of important policy developments that correspond to on-going changes in European policies. The reference scenario is compared to a policy scenario in which a range of measures is implemented to regulate flood risk and protect soils under conditions of climate change. The impacts of the simulated land use dynamics are assessed for four key indicators of ecosystem service provision: flood risk, carbon sequestration, habitat connectivity and biodiversity. The results indicate a large spatial variation in the consequences of the adaptation measures on the provisioning of ecosystem services. Synergies are frequently observed at the location of the measures itself, whereas trade-offs are found at other locations. Reducing land use intensity in specific parts of the catchment may lead to increased pressure in other regions, resulting in trade-offs. Consequently, when aggregating the results to larger spatial scales the positive and negative impacts may be off-set, indicating the need for detailed spatial assessments. The modelled results indicate that for a careful planning and evaluation of adaptation measures it is needed to consider the trade-offs accounting for the negative effects of a measure at locations distant from the actual measure. Integrated land use modelling can help land use planning in such complex trade-off evaluation by providing evidence on synergies and trade-offs between ecosystem services, different policy fields and societal demands.://000302346900002-919RS Times Cited:0 Cited References Count:49 0921-2973Landscape EcolISI:000302346900002Verburg, PH Vrije Univ Amsterdam, Inst Environm Studies, De Boelelaan 1087, NL-1081 HV Amsterdam, Netherlands Vrije Univ Amsterdam, Inst Environm Studies, De Boelelaan 1087, NL-1081 HV Amsterdam, Netherlands Vrije Univ Amsterdam, Inst Environm Studies, NL-1081 HV Amsterdam, Netherlands Vrije Univ Amsterdam, Fac Econ, NL-1081 HV Amsterdam, Netherlands Vrije Univ Amsterdam, Business Adm, NL-1081 HV Amsterdam, Netherlands ObjectVis BV, NL-1081 HV Amsterdam, Netherlands Alterra, NL-6700 AA Wageningen, NetherlandsDOI 10.1007/s10980-012-9715-6English|? Verburg, P. H. Overmars, K. P.2009Combining top-down and bottom-up dynamics in land use modeling: exploring the future of abandoned farmlands in Europe with the Dyna-CLUE model 1167-1181Landscape Ecology249$Land use change is the result of interactions between processes operating at different scales. Simulation models at regional to global scales are often incapable of including locally determined processes of land use change. This paper introduces a modeling approach that integrates demand-driven changes in land area with locally determined conversion processes. The model is illustrated with an application for European land use. Interactions between changing demands for agricultural land and vegetation processes leading to the re-growth of (semi-) natural vegetation on abandoned farmland are explicitly addressed. Succession of natural vegetation is simulated based on the spatial variation in biophysical and management related conditions, while the dynamics of the agricultural area are determined by a global multi-sector model. The results allow an exploration of the future dynamics of European land use and landscapes. The model approach is similarly suitable for other regions and processes where large scale processes interact with local dynamics.!://WOS:000270739000003Times Cited: 1 0921-2973WOS:00027073900000310.1007/s10980-009-9355-7|? ZVerburg, P. H. van Berkel, D. B. van Doorn, A. M. van Eupen, M. van den Heiligenberg, Harm2010UTrajectories of land use change in Europe: a model-based exploration of rural futures217-232Landscape Ecology252WLand use change is characterized by a high diversity of change trajectories depending on the local conditions, regional context and external influences. Policy intervention aims to counteract the negative consequences of these changes and provide incentives for positive developments. Region typologies are a common tool to cluster regions with similar characteristics and possibly similar policy needs. This paper provides a typology of land use change in Europe at a high spatial resolution based on a series of different scenarios of land use change for the period 2000-2030. A series of simulation models ranging from the global to the landscape level are used to translate scenario conditions in terms of demographic, economic and policy change into changes in European land use pattern. A typology developed based on these simulation results identifies the main trajectories of change across Europe: agricultural abandonment, agricultural expansion and urbanization. The results are combined with common typologies of landscape and rurality. The findings indicate that the typologies based on current landscape and ruralities are poor indicators of the land use dynamics simulated for the regions. It is advocated that typologies based on (simulated) future dynamics of land change are more appropriate to identify regions with potentially similar policy needs.!://WOS:000274437100005Times Cited: 0 0921-2973WOS:00027443710000510.1007/s10980-009-9347-7b<7Verburg, P. H. Veldkamp, A.2004ZProjecting land use transitions at forest fringes in the Philippines at two spatial scales77-98Landscape Ecology191deforestation; land use planning; land use change; modeling; protected areas; Philippines; spatial indices TROPICAL DEFORESTATION; INFORMATION-SYSTEM; SATELLITE DATA; COVER CHANGE; PATTERNS; MODEL; POLICIES; LANDSCAPES; SCENARIOS; MARKETSArticleThis paper presents two applications of a spatially explicit model of land use change at two spatial scales: a nation-wide application for the Philippines at relatively coarse resolution and an application with high spatial resolution for one island of the Philippines: Sibuyan island, Romblon province. The model is based on integrated analysis of socio-economic and biophysical factors that determine the allocation of land use change in combination with the simulation of the temporal dynamics (path-dependence and reversibility of changes), spatial policies and land requirements. Different scenarios of near-future developments in land use pattern are simulated illustrating the effects of implementing spatial policies. Results from the coarse scale model with national extent mainly serve to identify the overall pattern of land use change and 'hot zones' of deforestation. The detailed application provides more insight in the pattern of land use change and its consequences for ecological processes. The use of the results for environmental assessments is illustrated by calculating spatial indices to assess the impact of land use change on forest fragmentation. It is concluded that spatially explicit modeling of land use change yields important information for environmental management and land use planning. The applications illustrate that the scale of analysis is an important determinant of the model configuration, the interpretation of the results and the potential use by stakeholders. There is no single, optimal, scale for land use change assessments. Each scale enables different types of analysis and assessment: applications at multiple scales therefore give complementary information needed for environmental management.://000189394100006 ISI Document Delivery No.: 780RA Times Cited: 7 Cited Reference Count: 56 Cited References: *USGS, 1996, GTOPO30 GLOB DIG EL ANGELSEN A, 1999, WORLD BANK RES OBSER, V14, P73 BAKER WL, 1992, LANDSCAPE ECOL, V7, P291 CHOMITZ KM, 1996, WORLD BANK ECON REV, V10, P487 COSTANZA R, 1998, ENVIRON MANAGE, V22, P183 COXHEAD I, 2000, WORLD DEV, V28, P111 COXHEAD I, 2001, LAND ECON, V77, P250 COXHEAD I, 2002, ENVIRON DEV ECON 2, V7, P341 DEFRIES RS, 2000, INT J REMOTE SENS, V21, P1389 DOBSON JE, 2000, PHOTOGRAMM ENG REM S, V66, P849 GARDNER RH, 1998, ECOLOGICAL SCALE THE, P17 GARRITY DP, 1993, SUSTAINABLE AGR ENV, P549 GEIST HJ, 2002, BIOSCIENCE, V52, P143 GEOGHEGAN J, 2001, AGR ECOSYST ENVIRON, V85, P25 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HARGROVE WW, 2000, ECOL MODEL, V135, P243 HE HS, 2000, LANDSCAPE ECOL, V15, P591 HE HS, 2002, INT J GEOGR INF SCI, V16, P93 KELLY PF, 1998, ENVIRON URBAN, V10, P35 LAMBIN EF, 1997, PROG PHYS GEOG, V21, P375 LAMBIN EF, 2001, GLOBAL ENVIRON CHANG, V11, P261 LIU DS, 1993, FOREST ECOL MANAG, V57, P1 MCMORROW J, 2001, GLOBAL ENVIRON CHANG, V11, P217 MENON S, 2000, CONSERV BIOL, V15, P501 MLADENOFF DJ, 1999, SPATIAL MODELING FOR MLADENOFF DJ, 2002, APACK 2 22 USERSS GU NELSON GC, 1997, AM J AGR ECON, V79, P80 NELSON GC, 2001, LAND ECON, V77, P187 OJIMA DS, 1994, BIOSCIENCE, V44, P300 ONEILL RV, 1991, LANDSCAPE ECOL, V5, P137 PETERSON GD, 2002, ECOSYSTEMS, V5, P329 PORTELA R, 2001, ECOL MODEL, V143, P115 RAMBALDI G, 2000, ESSENTIALS PROTECTED, V7 RAMBALDI G, 2000, PLA NOTES, V39, P19 RIITTERS K, 2000, CONSERV ECOL, V4 RIPPLE WJ, 1991, BIOL CONSERV, V57, P73 SCHOORL JM, 2001, AGR ECOSYST ENVIRON, V85, P281 SHIVELY GE, 2001, LAND ECON, V77, P268 SWETS JA, 1986, SCIENCE JUN, P1285 TISCHENDORF L, 2001, LANDSCAPE ECOL, V16, P235 TUCKER CJ, 2000, INT J REMOTE SENS, V21, P1461 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 VANDENTOP GM, 1998, SOCIAL DYNAMICS DEFO VANROMPAEY AJJ, 2002, EARTH SURF PROC LAND, V27, P481 VELASCO E, 2000, SOCIOECONOMIC CULTUR VELDKAMP A, 1996, ECOL MODEL, V91, P231 VELDKAMP A, 2001, AGR ECOSYST ENVIRON, V85, P1 VERBURG PH, 1999, ECOL MODEL, V116, P45 VERBURG PH, 2002, ENVIRON MANAGE, V30, P391 VERBURG PH, 2003, IN PRESS GEOJOURNAL VERBURG PH, 2003, LAND USE NATURE CONS WALPOLE P, 1999, DECLINE PHILIPPINES WEAR DN, 1998, ECOL APPL, V8, P619 WHITE D, 1997, CONSERV BIOL, V11, P349 WOLLENBERG E, 2000, LANDSCAPE URBAN PLAN, V47, P65 WU JG, 2002, LANDSCAPE ECOL, V17, P761 0921-2973 Landsc. Ecol.ISI:000189394100006Univ Wageningen & Res Ctr, Lab Soil Sci & Geol, NL-6700 AA Wageningen, Netherlands. Verburg, PH, Univ Wageningen & Res Ctr, Lab Soil Sci & Geol, POB 37, NL-6700 AA Wageningen, Netherlands. peter.verburg@wur.nlEnglishM? Vergara, Pablo2011bMatrix-dependent corridor effectiveness and the abundance of forest birds in fragmented landscapes 1085-1096Landscape Ecology268Springer NetherlandsEarth and Environmental Science Corridor function for wildlife movement constitutes an important and desirable ecological characteristic of linear landscape structures. Changes in the matrix conditions, however, may result in substantial changes in the mechanisms responsible for the use of corridors by animals. I developed a model that describes the influence of matrix quality on the effectiveness of corridors for wildlife movement and the abundance of animals in the corridors. The model predicts that corridor effectiveness is maximized at intermediate matrix quality levels, while the abundance in the corridor increases asymptotically with matrix quality. I tested predictions of this model by comparing the expected and observed relative abundance of forest bird species in two landscape types of southern Chile. In nine out of 12 cases the model correctly predicted the relative abundance of forest birds. Riparian forest strips were expected to be effective functioning as corridors for five out of six studied species, although corridor effectiveness for each species varied between landscape types. A reasonable strategy to improve connectivity is to maintain (or to increase, if necessary) the matrix quality at a level such that corridors can function efficiently as both drift fences and movement conduits.+http://dx.doi.org/10.1007/s10980-011-9641-z 0921-297310.1007/s10980-011-9641-zڽ7 JVergara, PabloM Pérez-Hernández, ChristianG Hahn, IngoJ Jiménez, JaimeE2013^Matrix composition and corridor function for austral thrushes in a fragmented temperate forest121-133Landscape Ecology281Springer Netherlands-Corridors Drift fence Edge-following behavior 2013/01/01+http://dx.doi.org/10.1007/s10980-012-9821-5 0921-2973Landscape Ecol10.1007/s10980-012-9821-5English[|7Vergara, P. M. Armesto, J. J.2009^Responses of Chilean forest birds to anthropogenic habitat fragmentation across spatial scales25-38Landscape Ecology241birds cross-scale effects forest fragmentation habitat use habitat specialists chile agricultural landscape temperate forests pine plantations understory birds avian diversity maulino forest chiloe island rain-forest abundance communitiesJanAlthough it is recognized that anthropogenic forest fragmentation affects habitat use by organisms across multiple spatial scales, there is uncertainty about these effects. We used a hierarchical sampling design spanning three spatial scales of habitat variability (landscape > patch > within-patch) and generalized mixed-effect models to assess the scale-dependent responses of bird species to fragmentation in temperate forests of southern Chile. The abundances of nine of 20 bird species were affected by interactions across spatial scales. These interactions resulted in a limited effect of within-patch habitat structure on the abundance of birds in landscapes with low forest cover, suggesting that suitable local habitats, such as sites with dense understory cover or large trees, are underutilized or remain unused in highly fragmented landscapes. Habitat specialists and cavity-nesters, such as tree-trunk foragers and tapaculos, were most likely to exhibit interactions across spatial scales. Because providing additional sites with dense understory vegetation or large habitat trees does not compensate the negative effect of the loss of forest area on bird species, conservation strategies should ensure the retention of native forest patches in the mixed-use landscapes.://000262506000003-395EI Times Cited:0 Cited References Count:52 0921-2973ISI:000262506000003Vergara, PM Univ Santiago Chile, Dept Ingn Geog, Av Lib B, Santiago 3363, Chile Univ Santiago Chile, Dept Ingn Geog, Santiago 3363, Chile Pontificia Univ Catolica Chile, Dept Ecol, Ctr Adv Studies Ecol & Biodivers, Santiago, Chile Univ Chile, IEB, Santiago, ChileDoi 10.1007/S10980-008-9275-YEnglish&}?Vergara, P. M. Marquet, P. A.2007On the seasonal effect of landscape structure on a bird species: the thorn-tailed rayadito in a relict forest in northern Chile 1059-1071Landscape Ecology227Aug://000248381900008 0921-2973ISI:000248381900008!<7=FVerheyen, K. Fastenaekels, I. Vellend, M. De Keersmaeker, L. Hermy, M.2006iLandscape factors and regional differences in recovery rates of herb layer richness in Flanders (Belgium) 1109-1118Landscape Ecology217 connectivity; dispersal spectrum; forest age; forest type; fragmentation; habitat configuration; historical connectivity; IFM measure EASTERN NORTH-AMERICA; PLANT-COMMUNITIES; FORESTS; MIGRATION; DISPERSAL; DISTANCE; RESTORATION; DIVERSITY; ENDOZOOCHORY; CONSERVATIONArticleOctThe recovery of understory plants in recent forests is critical for evaluating the overall capacity of landscapes to maintain plant biodiversity. Here we used a large data set of vegetation plots from the Flemish Forest Inventory in combination with maps of forest history and soil-based Potential Natural Vegetation to evaluate regional differences in the rate of recovery of understory plant diversity in three regions of Flanders, Belgium. We expressed the degree of recovery in recent forests using the species richness of ancient forests as a reference point, and found strong differences among regions in the average level of recovery. These differences appeared to be due to regional variation in average patch connectivity and age (ultimately stemming from differences in land use history) and - to a lesser extent - environmental conditions. We also found an increase in the proportional representation of vertebrate dispersed species and species with short-distance dispersal with increasing levels of recovery. Our results highlight the potential drivers of inter-regional variation in the process of recovery of plant diversity during restoration, and they emphasize the importance of historical and spatial context in the recovery process.://000241010900011 ISI Document Delivery No.: 091FA Times Cited: 0 Cited Reference Count: 37 Cited References: BAKKER JP, 1999, TRENDS ECOL EVOL, V14, P63 BELLEMARE J, 2002, J BIOGEOGR, V29, P1401 BIESBROUCK B, 2001, 0001 VLINA NAT PLANT BROWN AG, 1997, GLOBAL ECOL BIOGEOGR, V6, P169 BRUNET J, 1998, J ECOL, V86, P429 BULLOCK JM, 2003, ECOGRAPHY, V26, P692 CHAO A, 2005, ECOL LETT, V8, P148 COUVREUR M, 2005, ECOGRAPHY, V28, P37 DEKEERSMAEKER L, 2001, C9706 VLINA DOBSON AP, 1997, SCIENCE, V277, P515 FLINN KM, 2005, FRONT ECOL ENVIRON, V3, P243 GRAAE BJ, 2000, J VEG SCI, V11, P881 HANSKI I, 1994, J ANIM ECOL, V63, P151 HEINKEN T, 2001, HERCYNIA, V34, P237 HERMY M, 1999, BIOL CONSERV, V91, P9 HONNAY O, 2002, BIODIVERS CONSERV, V11, P213 JACQUEMYN H, 2001, J VEG SCI, V12, P635 JACQUEMYN H, 2003, RESTOR ECOL, V11, P417 KOLB A, 2004, CONSERV BIOL, V19, P929 LINDBORG R, 2004, ECOLOGY, V85, P1840 MATLACK GR, 1994, ECOLOGY, V75, P1491 MOILANEN A, 2002, ECOLOGY, V83, P1131 MYERS JA, 2004, OECOLOGIA, V139, P35 PAKEMAN RJ, 2002, FUNCT ECOL, V16, P296 PETERKEN GF, 1996, NATURAL WOODLAND ECO PETIT S, 2004, LANDSCAPE ECOL, V19, P463 SEVENANT M, 2002, ECODISTRICTEN RUIMTE STIEPERAERE H, 1980, DUMORTIERA, V22, P1 TACK G, 1993, BOSSEN VLAANDEREN HI TAKAHASHI K, 2004, J ECOL, V92, P778 VANDERWALL SB, 1992, ECOLOGY, V73, P614 VANRUREMONDE RHAC, 1991, J VEG SCI, V2, P377 VELLEND M, 2003, ECOLOGY, V84, P1067 VELLEND M, 2003, ECOLOGY, V84, P1158 VERHEYEN K, 2003, BASIC APPL ECOL, V4, P537 VERHEYEN K, 2003, J ECOL, V91, P563 WATERINCKX M, 2001, BOSINVENTARIS VLAAMS 0921-2973 Landsc. Ecol.ISI:000241010900011Univ Ghent, Lab Forestry, B-9090 Melle Gontrode, Belgium. Univ Louvain, Lab Forest Nat & Landscape Res, B-3000 Louvain, Belgium. Univ British Columbia, Dept Bot, Vancouver, BC V6T 1Z4, Canada. Univ British Columbia, Dept Zool, Vancouver, BC V6T 1Z4, Canada. Univ British Columbia, Biodivers Res Ctr, Vancouver, BC V6T 1Z4, Canada. Inst Forestry & Game Management, B-9500 Geraardsbergen, Belgium. Verheyen, K, Univ Ghent, Lab Forestry, Geraardsbergsesteenweg 267, B-9090 Melle Gontrode, Belgium. kris.verheyen@ugent.beEnglishL?BP. Vestergaard1991iMorphology and vegetation of a dune system in SE Denmark in relation to climate change and sea level rise77-87Landscape Ecology61/22Sea level rise, dunes, lowland Denmark, psammosere_Recordings by the Danish Meteorological Institute show, that the mean temperature of Denmark has remained fairly constant and the mean precipitation in winter has increased very slightly during the last c. 100 years, and that the relative sea level rise in Danish waters amounted to between + 9 cm and -3 cm during the same period of time. For the W Baltic area a doubling of CO2-level in the atmosphere is predicted to cause an increase in mean temperature by 3-4C, an increase in length of growing season by c. 55 days, an increase in aridity, and a sea level rise of between 25 and 165 cm. Based on recent observations of morphology, soil and vegetation of a W Baltic dune system, possible effects of these changes upon vegetational composition, phytogeography, nutrient economy, stability, and ground water level of coastal dunes are discussed.e|?3 <Veysey, Jessica S. Mattfeldt, Sandra D. Babbitt, Kimberly J.2011Comparative influence of isolation, landscape, and wetland characteristics on egg-mass abundance of two pool-breeding amphibian species661-672Landscape Ecology265MayThe distribution and abundance of species are shaped by local and landscape processes, but the dominant processes may differ with scale and increasing human disturbance. We investigated population responses of two pool-breeding amphibian species to differences in local and landscape characteristics in suburbanizing, southeastern New Hampshire, USA. In 2003 and 2004, we sampled 49 vernal pools for spotted salamander (Ambystoma maculatum) and wood frog (Lithobates sylvaticus) egg masses. Using egg masses as a proxy for breeding-female population size, we examined the relative influence of five land-use and three isolation variables at two scales (300 and 1000 m) and five wetland variables on egg-mass abundance. For both species, road density at the landscape scale (1000 m) and hydroperiod most strongly predicted egg-mass abundance, with abundance decreasing as roads became denser and hydroperiods shortened. Wetland isolation was also an important predictor, with abundance greatest at more isolated pools, suggesting that both species concentrate at isolated pools when alternative breeding sites are scarce. Surprisingly, no 300-m parameters were strongly associated with salamander egg-mass abundance, whereas several landscape parameters were. In suburbanizing areas, it is at least as important to consider landscape-scale road density as to consider hydroperiod when designing conservation plans for these species. Furthermore, both isolated and clustered pools provide these species important habitat and may require protection. Finally, the conceptual framework for spotted-salamander management must be expanded so that spatial configuration at the landscape scale becomes a regular, integrated component of conservation planning for this species.!://WOS:000291485100005Times Cited: 0 0921-2973WOS:00029148510000510.1007/s10980-011-9590-6_<7/Vezina, K. Bonn, F. Van, C. P.2006pAgricultural land-use patterns and soil erosion vulnerability of watershed units in Vietnam's northern highlands 1311-1325Landscape Ecology218atropical environment; watershed; erosion dynamics; scaling in space and time; GIS GIS; RISK; USLEArticleNovSince the mid eighties, agricultural development and increased population growth in Vietnam's northern highlands have modified land use patterns and thus, increased the runoff process and soil degradation induced by water erosion. In the last decade, Vietnamese literature has focused on the computation of soil losses over large areas. Most of these spatial and quantitative soil erosion studies do not consider the impact of agricultural land use diversity (spatial heterogeneity), particularly at the watershed scale, and the annual variability of seasonal landscape factors on soil erosion vulnerability and hence, landscape dynamics. We present an integrated approach combining field measurements and observations, GIS and modeling to determine the spatial and temporal dynamics of soil erosion vulnerability according to watershed units and hence, the impact of physical environment components and agricultural land use patterns on landscape evolution. Tables and graphics showing the cropping systems, the periods within a year, and the watershed units that are most vulnerable are presented. The double cultivation cycles for paddy rice fields not only imply two periods of land preparation and establishment that expose the soil surface to raindrop impacts, but also increased soil management practices that decrease the soil's resistance to detachment. Despite the low levels of soil management practices for the shifting cultivation system, the near absence of soil conservation practices clearly increases their vulnerability. Hence, rainfed cropping systems, mainly soya and cassava, cultivated on sloping lands (hills and mountains) where soil erosion vulnerability is the highest represent the watershed units which are the most prone to soil loss.://000242089300011 ISI Document Delivery No.: 106GP Times Cited: 0 Cited Reference Count: 35 Cited References: *FAO, 1998, TOPS CHAR SUST LAND, P71 BOGGS G, 2001, LAND DEGRAD DEV, V12, P417 BONN F, 1998, SECHERESSE, V19, P185 CARSON MA, 1972, HILLSLOPE FORM PROCE COHEN MJ, 2005, GEODERMA, V124, P235 DIJK AIJ, 2001, J HYDROL, V247, P239 ELWELL HA, 1995, SOIL EROSION CONSERV, P71 ELWELL HA, 1995, SOIL EROSION CONSERV, P71 HUDSON N, 1971, SOIL CONSERVATION JAIN MK, 2000, HYDROLOG SCI J, V45, P771 JAIN SK, 2001, WATER RESOUR MANAG, V15, P41 KALPAGE FSC, 1974, TROPICAL SOILS CLASS LETRONG T, 2001, CREATING PROTECTED A, P55 MATI BM, 1995, TROP AGR, V72, P18 MILLWARD AA, 1999, CATENA, V38, P109 MITASOVA H, 1996, INT J GEOGR INF SYST, V10, P629 MITASOVA H, 1998, MULTIDIMENSIONAL SOI MORGAN RPC, 1995, SOIL EROSION CONSERV MULENGERA MK, 1999, TROP AGR, V76, P17 NGUYEN QM, 1990, OBSERVATION SOIL ERO NGUYEN QM, 1992, REG SEM ENV GEOL NOV, P105 RENARD KG, 1994, J HYDROL, V157, P287 RENARD KG, 1997, AGR HDB USDA, V703, P404 ROOSE E, 1999, B PEDOLOGIQUE FAO STONE RP, 2000, UNIVERSAL SOIL LOSS THAI P, 2001, VIETNAM SOIL SCI, V15, P161 TRAN K, 1999, LAND ENV REPORT ACTU, P21 TURKELBOOM F, 1997, CATENA, V29, P29 VAESEN K, 2001, FIELD CROP RES, V69, P13 VINH CL, 2000, VIETNAM NATL U J SCI, V11, P142 WALL GJ, 2002, RUSLEFAC REVISED UNI, P53 WILLIAMS CN, 1970, CLIMATE SOIL CROP PR WISCHMEIER WH, 1981, S AGR HDB USDA, V537, P58 WU JG, 2002, LANDSCAPE ECOL, V17, P355 ZINGERLI C, 2002, CONTESTING POLICIES, P14 0921-2973 Landsc. Ecol.ISI:000242089300011OUniv Sherbrooke, Remote Sensing Applicat & Res Ctr, CARTEL, Sherbrooke, PQ J1K 2R1, Canada. Vietnamese Acad Sci & Technol, Inst Geol, Ctr Remote Sensing & Geomat, VTGEO, Hanoi, Vietnam. Vezina, K, Univ Sherbrooke, Remote Sensing Applicat & Res Ctr, CARTEL, 2500 Univ Blvd, Sherbrooke, PQ J1K 2R1, Canada. karine.r.vezina@usherbrooke.caEnglish|?8Viaud, V. Monod, H. Lavigne, C. Angevin, F. Adamczyk, K.2008RSpatial sensitivity of maize gene-flow to landscape pattern: a simulation approach 1067-1079Landscape Ecology239Pollen dispersal is a critical process defining connectivity among plant populations. In the context of genetically modified (GM) crops in conventional agricultural systems, strategies based on spatial separation are promoted to reduce functional connectivity between GM and non-GM crop fields. Field experiments as well as simulation studies have stressed the dependence of maize gene flow on distances between source and receptor fields and on their spatial configuration. However, the influence of whole landscape patterns is still poorly understood. Spatially explicit models, such as MAPOD-maize, are thus useful tools to address this question. In this paper we developed a methodological approach to investigate the sensitivity of cross-pollination rates among GM and non-GM maize in a landscape simulated with MAPOD-maize. The influence of landscape pattern on model output was studied at the landscape and field scales, including interactions with other model inputs such as cultivar characteristics and wind conditions. At the landscape scale, maize configuration (proportion of and spatial arrangement in a given field pattern) was shown to be an important factor influencing cross-pollination rate between GM and non-GM maize whereas the effect of the field pattern itself was lower. At the field scale, distance to the nearest GM maize field was confirmed as a predominant factor explaining cross-pollination rate. The metrics describing the pattern of GM maize in the area surrounding selected non-GM maize fields appeared as pertinent complementary variables. In contrast, field geometry and field pattern resulted in little additional information at this scale.!://WOS:000260283100006Times Cited: 0 0921-2973WOS:00026028310000610.1007/s10980-008-9264-1@|? Viedma, O.2008{The influence of topography and fire in controlling landscape composition and structure in Sierra de Gredos (Central Spain)657-672Landscape Ecology236Mediterranean landscapes are dynamic systems that undergo temporal changes in composition and structure in response to disturbances, such as fire. Neither landscape patterns nor driving factors that affect them are evenly distributed in space. Accordingly, disturbances and biophysical factors interact in space through time. The aim of this paper is to assess the relative influence of topography and fire on the landscape patterns of a large forested area located in Sierra de Gredos (Central Spain) through time. A series of Landsat MSS images from 1975 to 1990, and a digital elevation model (DEM) were used to map fires, assess topographical complexity and evaluate changes in landscape composition and structure. Functional regions across the entire landscape were identified using different classification criteria (i.e., percentage burned area and topographic properties) to model topographic and fire impacts at regional scales. A canonical variance partition method, with a time series split-plot design, quantified the relative influence and co-variation of topography and fire on land cover patterns through time. Main results indicated that analyzing portions of the landscape under similar environmental conditions and fire histories, the effects of different fire regimes on the spatio-temporal dynamics of main land covers can be highlighted. However, the impact of fire on landscape patterns was high variable among regions due to the different regeneration abilities of main land covers, the topographic constraints and the fire histories of each region. Hence, broad patterns of fire related variance and co-variation with topography emerged across the entire area due to the different conditions of each landscape portion in which this large Mediterranean landscape was divided.!://WOS:000257210900003Times Cited: 0 0921-2973WOS:00025721090000310.1007/s10980-008-9228-5|?/Vieira, Renee Finn, John T. Bradley, Bethany A.2014How does the landscape context of occurrence data influence models of invasion risk? A comparison of independent datasets in Massachusetts, USA 1601-1612Landscape Ecology299NovThe spatial distribution of non-native, invasive plants on the landscape is strongly influenced by human action. People introduce non-native species to new landscapes and regions (propagule pressure) as well as increase ecosystem invasibility through disturbance of native ecosystems. However, the relative importance of different landscape drivers of invasion may vary with landscape context (i.e., the types and amounts of surrounding land cover and land use). If so, data collected in one context may not be appropriate for predicting invasion risk across a broader landscape. To test whether independent occurrence datasets suggest similar landscape drivers of invasion, we compared landscape models based on data compiled by the Invasive Plant Atlas of New England (IPANE), which are contributed opportunistically by trained citizen scientists, to models based on Forest Stewardship plans (FSPs), which are located in privately owned and relatively undisturbed forests. We evaluated 16 landscape variables related to propagule pressure and/or disturbance for significant predictors of invasive plant presence based on presence/absence and count regression models. Presence and richness of invasive plants within FSPs was most influenced by proportion of open land and proximity to residential areas, which are both sources of propagules in forest interiors. In contrast, IPANE invasive plant presence and richness for the same area was influenced by distance to roads and streams. These results suggest that landscape drivers of invasion vary considerably depending on landscape context, and the choice of occurrence dataset will strongly influence model results.!://WOS:000343648700011Times Cited: 0 0921-2973WOS:00034364870001110.1007/s10980-014-0080-54|?; Vila, Montserrat Ibanez, Ines2011 Plant invasions in the landscape461-472Landscape Ecology264Apr<Biological invasions and changes in land-use are two components of global change affecting biodiversity worldwide. There is overriding evidence that invasions can dramatically change the landscape and that particular land-use types facilitate invasions. Still, these issues have not formally percolated into risk analysis of biological invasions, and only recently has the influence of the surrounding landscape on invasive species spread started to be considered. In this paper we review the literature on the influence of the surrounding landscape on the local level of plant invasions (i.e., abundance and richness of alien plants in plant communities). Our review confirms that there are more alien plant species and they are more abundant at fragment edges than in the interior of fragments. The decline on the level of invasion towards the interior of fragments is sharp. To a lesser extent, there is higher invasion in small isolated fragments than in large connected patches. However, despite their relevance, the influence of connectivity and shape of the fragments have been scarcely explored. Besides the fact that a site has more invaders if surrounded by a human-dominated landscape than by a natural one, the past history and the configuration of that landscape are also important. Invasion within land-uses is often associated with the historical legacy of changes in land-use, indicating that current land-uses might represent an invasion credit to future invasions. Accurate accounts of the invasion process and effective conservation programs will depend on such considerations.!://WOS:000288807300002Times Cited: 0 0921-2973WOS:00028880730000210.1007/s10980-011-9585-3? GVillanueva-Rivera, Luis Pijanowski, Bryan Doucette, Jarrod Pekin, Burak20116A primer of acoustic analysis for landscape ecologists 1233-1246Landscape Ecology269Springer NetherlandsEarth and Environmental ScienceIn this paper we present an introduction to the physical characteristics of sound, basic recording principles as well as several ways to analyze digital sound files using spectrogram analysis. This paper is designed to be a “primer” which we hope will encourage landscape ecologists to study soundscapes. This primer uses data from a long-term study that are analyzed using common software tools. The paper presents these analyses as exercises. Spectrogram analyses are presented here introducing indices familiar to ecologists (e.g., Shannon’s diversity, evenness, dominance) and GIS experts (patch analysis). A supplemental online tutorial provides detailed instructions with step by step directions for these exercises. We discuss specific terms when working with digital sound analysis, comment on the state of the art in acoustic analysis and present recommendations for future research.+http://dx.doi.org/10.1007/s10980-011-9636-9 0921-297310.1007/s10980-011-9636-9? 7Vinatier, Fabrice Gosme, Marie Valantin-Morison, Muriel2012A tool for testing integrated pest management strategies on a tritrophic system involving pollen beetle, its parasitoid and oilseed rape at the landscape scale 1421-1433Landscape Ecology2710Springer NetherlandsBiomedical and Life Sciences*The intensification of agriculture has led to a loss of biodiversity and subsequently to a decrease in ecosystem services, including regulation of pests by natural enemies. Biological regulation of pests is a complex process affected by both landscape configuration and agricultural practices. Although modeling tools are needed to design innovative integrated pest management strategies that consider tritrophic interactions at the landscape scale, landscape models that consider agricultural practices as levers to enhance biological regulation are lacking. To begin filling this gap, we developed a grid-based lattice model called Mosaic-Pest that simulates the spatio-temporal dynamics of Meligethes aeneus , a major pest of oilseed rape, and its parasitoid, Tersilochus heterocerus through a landscape that changes through time according to agricultural practices. The following agricultural practices were assumed to influence the tritrophic system and were included in the model: crop allocation in time and space, ploughing, and trap crop planting. To test the effect of agricultural practices on biological regulation across landscape configurations, we used a complete factorial design with the variables described below and ran long-term simulations using Mosaic-Pest. The model showed that crop rotation and the use of trap crop greatly affected pollen beetle densities and parasitism rates while ploughing had only a small effect. The use of Mosaic-Pest as a tool to select the combination of agricultural practices that best limit the pest population is discussed.+http://dx.doi.org/10.1007/s10980-012-9795-3 0921-297310.1007/s10980-012-9795-3ڽ7 7Vinatier, Fabrice Gosme, Marie Valantin-Morison, Muriel2013Explaining host–parasitoid interactions at the landscape scale: a new approach for calibration and sensitivity analysis of complex spatio-temporal models217-231Landscape Ecology282Springer NetherlandsOTritrophic model Sensitivity analyses Inverse modeling Co-inertia Morris method 2013/02/01+http://dx.doi.org/10.1007/s10980-012-9822-4 0921-2973Landscape Ecol10.1007/s10980-012-9822-4English <7<Vogt, P. Riitters, K. H. Estreguil, C. Kozak, J. Wade, T. G.2007<Mapping spatial patterns with morphological image processing171-177Landscape Ecology222{morphological image processing; spatial pattern; forest fragmentation UNITED-STATES; FOREST FRAGMENTATION; LANDSCAPE; SCALEArticleFebhWe use morphological image processing for classifying spatial patterns at the pixel level on binary land-cover maps. Land-cover pattern is classified as 'perforated,' 'edge,' 'patch,' and 'core' with higher spatial precision and thematic accuracy compared to a previous approach based on image convolution, while retaining the capability to label these features at the pixel level for any scale of observation. The implementation of morphological image processing is explained and then demonstrated, with comparisons to results from image convolution, for a forest map of the Val Grande National Park in North Italy.://000243823900002 ISI Document Delivery No.: 130UG Times Cited: 0 Cited Reference Count: 21 Cited References: *HEINZ CTR HJ HEIN, 2002, STAT NAT EC MEAS LAN *MONTR PROC LIAIS, 2000, MONTR PROC YEAR 2000 *USDA FOR SERV, 2004, FS766 USDA FOR SERV BOGAERT J, 2004, ENVIRON MANAGE, V33, P62 CIVCO DL, 2002, PHOTOGRAMM ENG REM S, V68, P1083 ESTREGUIL CM, 2004, 21078EN EUR FORMAN RTT, 1995, LAND MOSAICS FORMAN RTT, 1995, LANDSCAPE ECOL, V10, P133 HEILMAN GE, 2002, BIOSCIENCE, V52, P411 LI HB, 2004, LANDSCAPE ECOL, V19, P389 MATHERON G, 1967, ELEMENTS THEORIE MIL METZGER JP, 1996, LANDSCAPE ECOL, V11, P65 METZGER JP, 1997, ACTA OECOL, V18, P1 MUSICK HB, 1991, QUANTITATIVE METHODS NEEL MC, 2004, LANDSCAPE ECOL, V19, P435 RIITTERS K, 2000, CONSERV ECOL, V4 RIITTERS KH, 2002, ECOSYSTEMS, V5, P815 RIITTERS KH, 2004, ENVIRON MONIT ASSESS, V91, P257 SOILLE P, 2003, MORPHOLOGICAL IMAGE TURNER MG, 2001, LANDSCAPE ECOLOGY TH ZIPPERER WC, 1993, LANDSCAPE ECOL, V8, P177 0921-2973 Landsc. Ecol.ISI:000243823900002European Commiss, DG Joint Res Ctr, IES, Land Management & Nat Hazards Unit LMNH, I-21020 Ispra, VA, Italy. US Forest Serv, So Res Stn, Res Triangle Pk, NC 27709 USA. Jagiellonian Univ, Inst Geog & Spatial Management, PL-30387 Krakow, Poland. US EPA, Div Environm Sci, Res Triangle Pk, NC 27711 USA. Vogt, P, European Commiss, DG Joint Res Ctr, IES, Land Management & Nat Hazards Unit LMNH, TP 261,Via E Fermi 1, I-21020 Ispra, VA, Italy. peter.vogt@jrc.itEnglishH|?von Haaren, Christina Albert, Christian Barkmann, Jan de Groot, Rudolf S. Spangenberg, Joachim H. Schroeter-Schlaack, Christoph Hansjuergens, Bernd2014From explanation to application: introducing a practice-oriented ecosystem services evaluation (PRESET) model adapted to the context of landscape planning and management 1335-1346Landscape Ecology298OctOThe development and use of the conceptual framework of ecosystem services (ES) has been very successful in supporting the broad diffusion and application of ES within science and policy communities. However, most of the currently proposed interpretations of the framework neither correlate to environmental planning nor to decision-making contexts at the local and regional scale, which is a potential reason for the slow adoption and practice of the ES conceptual framework. This paper proposes a practice-oriented ES evaluation (PRESET) model specifically adapted to the requirements of local and regional planning and decision-making contexts, and discusses its potential benefits and implications for practice. Through the usage of PRESET we suggest making a distinction between 'offered ES', 'utilized ES', 'human input', and 'ES benefits' as relevant information for decision-making. Furthermore, we consider it important to link these decision-support categories to different value dimensions relevant in planning and management practice. PRESET provides guidance to inject the ES concept into planning, but needs to be implemented together with concrete assessment methods, indicators and data. The planning strategic benefits of using PRESET include its reference to existing legislative objectives, avoiding the risk that monetized ES values might dominate decision-making, clarification of human contributions, and easier identification of land use conflicts and synergies. Examples are given for offered and utilized ES, as well as for respective evaluation approaches and instruments of implementation.!://WOS:000342078600006Times Cited: 2 0921-2973WOS:00034207860000610.1007/s10980-014-0084-1|?_von Wehrden, Henrik Abson, David J. Beckmann, Michael Cord, Anna F. Klotz, Stefan Seppelt, Ralf2014~Realigning the land-sharing/land-sparing debate to match conservation needs: considering diversity scales and land-use history941-948Landscape Ecology296JuloThe "land sharing versus land sparing" concept provides a framework for comparing potential land use patterns in terms of trade-offs between biodiversity conservation and agricultural yields at a landscape scale. Here, we raise two additional aspects to be considered in the sparing/sharing debate, supported by a review of available literature. First, beta and gamma (instead of alpha) diversity measures capture landscape scale variance in biodiversity in response to land use changes and should be considered for the long-term management of agricultural landscapes. Moreover, beta and gamma diversity may better account for comparisons of biodiversity between spared and shared land use options. Second, land use history has a pronounced influence on the complexity and variance in agricultural habitat niches at a landscape scale, which in turn may determine the relevance of sparing or sharing land use options. Appropriate and comparable biodiversity metrics and the recognition of landscape history are two vital preconditions in aligning biological conservation goals with maximized yields within the sparing/sharing framework.!://WOS:000338331600002Times Cited: 0 0921-2973WOS:00033833160000210.1007/s10980-014-0038-72|76 Vos, C. C. Stumpel, A. H. P.1996zComparison of habitat-isolation parameters in relation to fragmented distribution patterns in the tree frog (Hyla arborea)203-214Landscape Ecology114habitat fragmentation isolation amphibians landscape planning agricultural landscape communities metapopulations extinction dynamics forest birds modelAugThe distribution pattern of the tree frog (Hyla arborea) in an intensively used agricultural landscape in Zealand Flanders, was analyzed for effects of habitat fragmentation. The logistic regression models showed that the chance that a pond (potential reproduction site) was occupied by tree frogs depended on three isolation factors. The density of ponds within 750 m of the occupied pond was higher compared to ponds that remained unoccupied during the survey period. Additionally both the density of shrubs as well as the density of high herbs, two terrestrial habitat factors, was higher within 1000 m of occupied ponds. The explanatory value of two different types of isolation measures was compared with logistic regression analysis. It is discussed that 'Concentric isolation measures', which take size and distance of potential habitat patches in all directions into account, are expected to give a better description of isolation than the more often used 'distance from the nearest habitat patch'.://A1996VC12700003.Vc127 Times Cited:20 Cited References Count:42 0921-2973ISI:A1996VC12700003LVos, Cc Inst Forestry & Nat Res,Postbus 23,Nl-6700 Aa Wageningen,NetherlandsEnglish |? 5Vos, Claire C. van der Hoek, Dirk C. J. Vonk, Marijke2010DSpatial planning of a climate adaptation zone for wetland ecosystems 1465-1477Landscape Ecology2510DecpHere we present a spatial planning approach for the implementation of adaptation measures to climate change in conservation planning for ecological networks. We analyse the wetland ecosystems of the Dutch National Ecological Network for locations where the effectiveness of the network might be weakened because of climate change. We first identify potential dispersal bottlenecks where connectivity might be insufficient to facilitate range expansions. We then identify habitat patches that might have a too low carrying capacity for populations to cope with additional population fluctuations caused by weather extremes. Finally, we describe the spatial planning steps that were followed to determine the best locations for adaptation measures. An essential part of our adaptation strategy is to concentrate adaptation measures in a 'climate adaptation zone'. Concentrating adaptation measures is a cost-effective planning strategy, rendering the largest benefit per area unit. Measures are taken where abiotic conditions are optimal and measures to enhance the spatial cohesion of the network are taken close to existing areas, thus creating the highest possible connectivity with the lowest area demands. Another benefit of a climate adaptation zone is that it provides a spatial protection zone where activities that will have a negative impact on ecosystem functioning might be avoided or mitigated. The following adaptation measures are proposed within the climate adaptation zone: (1) link habitat networks to enable species to disperse from present to future suitable climate zones, (2) enlarge the carrying capacity by either enlarging the size of natural areas or by improving habitat quality to shorten population recovery after disturbances, (3) increase the heterogeneity of natural areas, preferably by stimulating natural landscape-forming processes, to avoid large synchronised extinctions after extreme weather events. The presented approach can be generalised to develop climate adaptation zones for other ecosystem types inside or outside Europe, where habitat fragmentation is a limiting factor in biodiversity responses to climate change.!://WOS:000283371000001Times Cited: 0 0921-2973WOS:00028337100000110.1007/s10980-010-9535-5<7Wagner, H. H. Edwards, P. J.2001nQuantifying habitat specificity to assess the contribution of a patch to species richness at a landscape scale121-131Landscape Ecology162conservation value habitat specificity landscape structure land-use rarity scaling species richness PLANT DIVERSITY BIODIVERSITYArticleFebAssessing and predicting the species richness of a complex landscape remains a problem because there is no simple scaling function of species richness in a heterogeneous environment. Furthermore, the potential value of an area for biodiversity conservation may depend on which, rather than how many, species the area contains. This paper shows how we can objectively evaluate the contribution of an area, e.g., a habitat patch, to larger-scale plant species richness, e.g., a landscape composed of patches of several habitat types, and how we can test hypotheses that attempt to explain this contribution. We quantified the concept of habitat specificity to assess the proportion of each observed plant population that is concentrated within a given spatial element. A case study of a biodiversity-monitoring program in the Swiss Canton of Aargau showed that the relative contribution of the three main types of land use to the overall species richness differed strongly between higher taxa (vascular plants and molluscs). However, the type of data, i.e., presence-absence or abundance, was not important. Resampling of the plant data suggested that stratification provided an unbiased estimate of relative specificity, whereas unstratified sampling caused bias even for large samples. In a second case study of vascular plants in an agricultural landscape in central Switzerland, we tested whether the type, size or shape of a landscape element can predict its contribution to the species richness of the landscape. Habitat types that were less frequently disturbed contributed more per m(2) to landscape species richness than more frequently disturbed ones. Contrary to expectation, patch size was negatively correlated to specificity per m(2) for arable fields, whereas patch shape appeared to be unrelated to the specificity per m(2) both for arable fields and for meadows. The specificity approach provides a solution to the problem of scaling species richness and is ideally suited for testing hypotheses on the effect of landscape structure on landscape species richness. Specificity scores can easily be combined with measures of other aspects of rarity to assess the contribution of a spatial element to conservation goals formulated at regional, national or global level.://000167936500004 TISI Document Delivery No.: 419EN Times Cited: 21 Cited Reference Count: 22 Cited References: BUNGE J, 1993, J AM STAT ASSOC, V88, P364 COLWELL RK, 1994, PHILOS T ROY SOC B, V345, P101 DAVIS JC, 1986, STAT DATA ANAL GEOLO DUELLI P, 1992, VERH GES OEKOLOGIE B, V21, P379 DUELLI P, 1997, AGR ECOSYST ENVIRON, V62, P81 DUFRENE M, 1997, ECOL MONOGR, V67, P345 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FORMAN RTT, 1995, LAND MOSAICS ECOLOGY GASTON KJ, 1994, RARITY GASTON KJ, 1996, BIODIVERSITY BIOL NU, P77 GRIFFITH DA, 1982, ANN ASSOC AM GEOGR, V72, P332 MACARTHUR RH, 1976, THEORY ISLAND BIOGEO PALMER MW, 1994, AM NAT, V144, P717 PALMER MW, 1995, NAT AREA J, V15, P124 RABINOWITZ D, 1981, BIOL ASPECTS RARE PL, P205 RICKETTS TH, 1999, BIOSCIENCE, V49, P369 STOHLGREN TJ, 1997, ENVIRON MONIT ASSESS, V48, P25 STOHLGREN TJ, 1997, LANDSCAPE ECOL, V12, P155 SUTER W, 1998, GAIA, V7, P174 WAGNER HH, UNPUB ENV ECOLOGICAL WAGNER HH, 2000, LANDSCAPE ECOL, V15, P219 WILLIAMS PH, 1999, CONSERVATION CHANGIN, P221 0921-2973 Landsc. Ecol.ISI:000167936500004Swiss Fed Inst Forest Snow & Landscape Res, Nat & Landscape Conservat Unit, CH-8903 Birmensdorf, Switzerland. Wagner, HH, Colorado State Univ, Dept Biol, Ft Collins, CO 80523 USA.English<7`BWagner, H. H. Werth, S. Kalwij, J. M. Bolli, J. C. Scheidegger, C.2006YModelling forest recolonization by an epiphytic lichen using a landscape genetic approach849-865Landscape Ecology216cellular automaton; disturbance; epiphytes; forest dynamics; genetic structure; Lobaria pulmonaria; population genetics LOBARIA-PULMONARIA; HABITAT FRAGMENTATION; DISPERSAL; POPULATION; CONNECTIVITY; CONSERVATION; DIVERSITY; DIASPORES; ECOLOGY; BIOLOGYArticleAugThe process of recolonization after disturbance is crucial for the persistence and dynamics of patch-tracking metapopulations. We developed a model to compare the spatial distribution and spatial genetic structure of the epiphytic lichen Lobaria pulmonaria within the perimeter of two reconstructed 19th century disturbances with a nearby reference area without stand-level disturbance. Population genetic data suggested that after stand-replacing disturbance, each plot was colonized by one or a few genotypes only, which subsequently spread clonally within a local neighborhood. The model (cellular automaton) aimed at testing the validity of this interpretation and at assessing the relative importance of local dispersal of clonal propagules vs. long-distance dispersal of clonal and/or sexual diaspores. A reasonable model fit was reached for the empirical data on host tree distribution, lichen distribution, and tree- and plot-level genotype diversity of the lichen in the reference area. Although model calibration suggested a predominance of local dispersal of clonal propagules, a substantial contribution of immigration of non-local genotypes by long-distance dispersal was needed to reach the observed levels of genotype diversity. The model could not fully explain the high degree of clonality after stand-replacing disturbance, suggesting that the dispersal process itself may not be stationary but depend on the ecological conditions related to disturbance.://000239484200006 7 ISI Document Delivery No.: 069YA Times Cited: 2 Cited Reference Count: 57 Cited References: ANTOINE ME, 2004, BRYOLOGIST, V107, P163 BAILEY RH, 1976, LICHENOLOGY PROGR PR, P215 BAILEY RH, 1979, LICHENOLOGIST, V11, P105 BEERLI P, 1999, GENETICS, V152, P763 BROOKS CP, 2003, OIKOS, V102, P433 CAIN ML, 2000, AM J BOT, V87, P1217 CLARK JS, 1998, AM NAT, V152, P204 CLOBERT J, 2001, DISPERSAL DENISON WC, 2003, MYCOLOGIA, V95, P513 FORTIN MJ, 2003, OIKOS, V102, P203 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GONZALEZASTORGA JG, 2004, ANN BOT-LONDON, V94, P545 GOODWIN BJ, 2003, LANDSCAPE ECOL, V18, P687 HARRISON S, 1999, ECOGRAPHY, V22, P225 HOLDEREGGER R, IN PRESS LANDSCAPE E, V21, P797 IHAKA R, 1996, J COMPUTATIONAL GRAP, V5, P299 JORDAN WP, 1970, BRYOLOGIST, V73, P669 KALWIJ JM, 2005, ECOL APPL, V15, P2015 KALWIJ JM, 2005, THESIS U BERN BERN KEYMER JE, 2000, AM NAT, V156, P478 KOT M, 1996, ECOLOGY, V77, P2027 LERTZMAN K, 1998, ECOLOGICAL SCALE THE, P339 MERRIAM G, 1984, 1 INT SEM METH LANDS OUBORG NJ, 1999, J ECOL, V87, P551 OZINGA WA, 2005, OIKOS, V108, P555 PARKER M, 2002, BIOL CONSERV, V105, P217 PECK SL, 2004, TRENDS ECOL EVOL, V19, P530 RAY C, 2001, BIOL CONSERV, V100, P3 RICHARDS CM, 1999, EVOLUTION, V53, P63 RIKKINEN J, 2002, SCIENCE, V297, P357 ROSE F, 1976, LICHENOLOGY PROGR PR, P279 ROSE F, 1992, BRYOPHYTES LICHENS C, P211 SCHEIDEGGER C, 1995, LICHENOLOGIST, V27, P361 SCHEIDEGGER C, 1998, LOBARION LICHENS IND, P33 SCHEIDEGGER C, 2002, MONITORING LICHENS M, P163 SCHUTZ JP, 2002, FORESTRY, V75, P329 SNALL T, 2005, OIKOS, V109, P209 SORK VL, 2006, LANDSCAPE ECOL, V21, P821 SUNDBERG B, 1997, OECOLOGIA, V109, P10 TACKENBERG O, 2003, ECOL MONOGR, V73, P173 TAYLOR PD, 1993, OIKOS, V68, P571 TISCHENDORF L, 2000, LANDSCAPE ECOL, V15, P633 TRAPNELL DW, 2005, MOL ECOL, V14, P75 VILLA F, 2004, LANDSCAPE SIMULATION, P77 VITTOZ P, 1998, THESIS U LAUSANNE LA WAGNER HH, 2005, ECOLOGY, V86, P1975 WAGNER HH, 2005, GENETICS, V169, P1739 WALSER JC, 2001, MOL ECOL, V10, P2129 WALSER JC, 2003, FUNGAL GENET BIOL, V40, P72 WALSER JC, 2004, AM J BOT, V91, P1273 WALSER JC, 2004, HEREDITY, V93, P322 WERTH S, IN PRESS MOL ECOL WERTH S, 2005, THESIS U BERN BERN WIENS JA, 1993, OIKOS, V66, P369 WITH KA, 1997, CONSERV BIOL, V11, P1069 WITH KA, 1999, ECOLOGY, V80, P1340 YOSHIMURA I, 1971, J HATTORI BOT LAB, V34, P231 0921-2973 Landsc. Ecol.ISI:000239484200006WSL Swiss Fed Res Inst, CH-8903 Birmensdorf, Switzerland. Wagner, HH, WSL Swiss Fed Res Inst, CH-8903 Birmensdorf, Switzerland. helene.wagner@wsl.chEnglish <7&$Wagner, H. H. Wildi, O. Ewald, K. C.2000TAdditive partitioning of plant species diversity in an agricultural mosaic landscape219-227Landscape Ecology153<heterogeneity landscape scale species diversity BIODIVERSITYArticleAprIn this paper, we quantify the effects of habitat variability and habitat heterogeneity based on the partitioning of landscape species diversity into additive components and link them to patch-specific diversity. The approach is illustrated with a case study from central Switzerland, where we recorded the presence of vascular plant species in a stratified random sample of 1'280 quadrats of 1 m(2) within a total area of 0.23 km(2). We derived components of within- and between-community diversity at four scale levels (quadrat, patch, habitat type, and landscape) for three diversity measures (species richness, Shannon index, and Simpson diversity). The model implies that what we measure as within-community diversity at a higher scale level is the combined effect of heterogeneity at various lower levels. The results suggest that the proportions of the individual diversity components depend on the habitat type and on the chosen diversity aspect. One habitat type may be more diverse than another at patch level, but less diverse at the level of habitat type. Landscape composition apparently is a key factor for explaining landscape species richness, but affects evenness only little. Before we can test the effect of landscape structure on landscape species richness, several problems will have to be solved. These include the incorporation of neighbourhood effects, the unbiased estimation of species richness components, and the quantification of the contribution of a landscape element to landscape species richness.://000085293300004 ISI Document Delivery No.: 283UB Times Cited: 57 Cited Reference Count: 18 Cited References: ALLAN JD, 1975, OECOLOGIA, V18, P359 ALLEN TFH, 1982, HIERARCHY PERSPECTIV BEGON M, 1996, ECOLOGY COLWELL RK, 1994, PHILOS T ROY SOC B, V345, P101 DUELLI P, 1992, VERH GES OEKOLOGIE B, V21, P379 DUELLI P, 1997, AGR ECOSYST ENVIRON, V62, P81 DUELLI P, 1998, BIODIVERS CONSERV, V7, P297 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY GASTON KJ, 1996, BIODIVERSITY BIOL NU, P1 LANDE R, 1996, OIKOS, V76, P5 MACARTHUR RH, 1965, BIOL REV, V40, P510 MACARTHUR RH, 1976, THEORY ISLAND BIOGEO MAGURRAN AE, 1988, ECOLOGICAL DIVERSITY ONEILL RV, 1986, HIERARCHICAL CONCEPT ONEILL RV, 1991, ECOL STUD, V86, P85 PEET RK, 1974, ANNU REV ECOL SYST, V5, P285 WHITTAKER RH, 1977, EVOL BIOL, V10, P1 ZONNEVELD IS, 1995, J VEG SCI, V5, P441 0921-2973 Landsc. Ecol.ISI:000085293300004Swiss Fed Inst Forest Snow & Landscape Res, CH-8903 Birmensdorf, Switzerland. Swiss Fed Inst Technol, Geobot Inst, CH-8092 Zurich, Switzerland. Wagner, HH, Swiss Fed Inst Forest Snow & Landscape Res, CH-8903 Birmensdorf, Switzerland.English<7$Waldhardt, R. Simmering, D. Otte, A.2004IEstimation and prediction of plant species richness in a mosaic landscape211-226Landscape Ecology192tagricultural mosaic landscape; land-use change; land-use pattern; land-use scenario; habitat patter; mosaic concept; vascular plant species richness; binomial distribution; probability calculation; species area relation; Erda; Germany AGRICULTURAL LANDSCAPES; ECOLOGICAL PROCESSES; GRAZING MANAGEMENT; BIODIVERSITY; DIVERSITY; HABITAT; COMMUNITY; SCALE; AREA; CONSERVATIONArticle.Traditional agricultural mosaic landscapes are likely to undergo dramatic changes through either intensification or abandonment of land use. Both developmental trends may negatively affect the vascular plant species richness of such landscapes. Therefore, sustainable land-use systems need to be developed to maintain and re-establish species richness at various spatial scales. To evaluate the sustainability of specific land-use systems, we need approaches for the effective assessment of the present species richness and models that can predict the effects on species richness as realistically as possible. In this context, we present a methodology to estimate and predict vascular plant species richness at the local and the regional scale. In our approach, the major determinants of vascular plant species richness within the study area are taken into consideration: These are according to Duelli's mosaic concept the number of habitat types and of habitat patches within area units. Furthermore, it is based on the relative frequencies of species within habitat types. Our approach comprises six steps: (i) the determination of present habitat patterns within an observation area, (ii) the creation of a land-use scenario with simulated habitat patterns, (iii) the determination of species frequencies within habitat types of this area, (iv) a grouping of habitat-specific species, (v) the estimation of the probabilities for all species (or habitat specialists) to occur, either in stepwise, exponentially enlarged landscape tracts (local scale), or in the entire observation area (regional scale), and (vi) the validation of the estimated species numbers. The approach will be exemplified using data from the municipal district of Erda, Lahn-Dill Highlands, Germany. The current species numbers to be expected on the basis of probability calculations were compared with those recorded on the basis of extensive field work. This comparison shows that, on the basis of our simple calculations, the current local plant species richness can be predicted well, with a slight underestimation.://000220452500008 ISI Document Delivery No.: 806SB Times Cited: 11 Cited Reference Count: 89 Cited References: *FAO, 1998, WORLD REF BAS SOIL R AUSTRHEIM G, 1999, PLANT ECOL, V145, P59 BALDOCK D, 1996, FARMING MARGINGS BOUMA J, 1998, AGR ECOSYST ENVIRON, V67, P103 BUREL F, IN PRESS DIFFERENTIA CASE TJ, 1987, AM SCI, V75, P402 CHYTRY M, 2002, J VEG SCI, V13, P79 COUSINS SAO, 2001, ECOGRAPHY, V24, P461 CSECSERITS A, 2001, APPL VEG SCI, V4, P63 DAUBER J, 2003, AGR ECOSYST ENVIRON, V98, P321 DUELLI P, 1992, VERH GES OEKOLOGIE B, V21, P379 DUELLI P, 1997, AGR ECOSYST ENVIRON, V62, P81 DUELLI P, 1998, BIODIVERS CONSERV, V7, P297 DUNNING JB, 1992, OIKOS, V65, P169 ELLENBERG H, 1992, SCRIPTA GEOBOT, V18, P9 FLEISHMAN E, 2000, ECOL APPL, V10, P569 FOSTER BL, 2000, PLANT ECOL, V146, P1 FREEMARK KE, 2001, BIOL CONSERV, V101, P337 GRIFFITHS GH, 2000, INT J REMOTE SENS, V21, P2685 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HAINESYOUNG R, 1996, PROG PHYS GEOG, V20, P418 HANSEN AJ, 1992, ECOLOGY STUDIES, V92 HARRIS LD, 1984, FRAGMENTED FOREST IS HARRIS LD, 1988, CONSERV BIOL, V2, P330 HAY GJ, 2001, LANDSCAPE ECOL, V16, P471 HOFFMANN J, 2001, ECOL STU AN, V147, P325 HULSHOFF RM, 1995, LANDSCAPE ECOL, V10, P101 HUPPE J, 1990, REINHOLD TUXEN GESEL, V2, P61 JOHNSON MP, 1974, J BIOGEOGR, V1, P149 JONSEN ID, 1997, LANDSCAPE ECOL, V12, P185 KOCHY M, 1997, NORD J BOT, V17, P215 KOHL M, 1978, GIESSENER GEOGRAPHIS, V45 KORNECK D, 1996, SCHRIFTENREIHE VEGET, V28, P21 LAWESSON JE, 1998, FOREST ECOL MANAG, V106, P235 LECOEUR D, 2002, AGR ECOSYST ENVIRON, V89, P23 LEVIN SA, 2000, ECOSYSTEMS, V3, P498 LUCZAJ L, 1997, FOLIA GEOBOT PHYTOTX, V32, P343 LUOTO M, 2000, PLANT ECOL, V149, P157 LUOTO M, 2002, LANDSCAPE ECOL, V17, P195 MA MH, 2002, AGR ECOSYST ENVIRON, V89, P137 MACARTHUR RH, 1963, EVOLUTION, V17, P373 MACARTHUR RH, 2001, THEORY ISLAND BIOGEO MACDONALD D, 2000, J ENVIRON MANAGE, V59, P47 MARSHALL EJR, 2002, AGR ECOSYST ENVIRON, V89, P5 MATSON PA, 1997, SCIENCE, V277, P504 MAUDSLEY M, 1999, P IALE C BRIST UK MCCRACKEN DI, 2000, QUANTITATIVE APPROAC, P97 MCDONALD AW, 2001, APPL VEG SCI, V4, P167 MOLLER D, 1999, J RURAL ENG DEV, V40, P197 MOLLER D, 2002, BER LANDWIRTSCH, V80, P393 NORDERHAUG A, 2000, LANDSCAPE ECOL, V15, P201 NOSS RF, 1990, CONSERV BIOL, V4, P355 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 OPDAM P, 2003, LANDSCAPE ECOL, V18, P113 PARODY JM, 2001, GLOBAL ECOL BIOGEOGR, V10, P305 PARTEL M, 1999, ECOGRAPHY, V22, P153 PYSEK P, 2002, GLOBAL ECOL BIOGEOGR, V11, P279 ROSENZWEIG ML, 1995, SPECIES DIVERSITY SP SAHLEN G, 2001, BIODIVERS CONSERV, V10, P673 SALA OE, 2000, SCIENCE, V287, P1770 SHAFER CL, 1990, ISLAND THEORY CONSER SIMMERING D, 2001, PECKIANA, V1, P79 SIMMERING D, 2001, TUEXENIA, V21, P51 SMITH RS, 1994, J APPL ECOL, V31, P13 SODERSTROM B, 2001, BIODIVERS CONSERV, V10, P1839 STEFFANDEWENTER I, 2003, ECOLOGY, V83, P1421 STERNBERG M, 2000, J APPL ECOL, V37, P224 STOHLGREN TJ, 1997, ECOL APPL, V7, P1064 STOHLGREN TJ, 1997, ENVIRON MONIT ASSESS, V48, P25 STOHLGREN TJ, 1997, LANDSCAPE ECOL, V12, P155 THIES C, 1999, SCIENCE, V285, P893 TISCHENDORF L, 2001, LANDSCAPE ECOL, V16, P235 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 VONARX G, 2002, B GEOBOT I ETH, V68, P3 VOS CC, 2002, APPL LANDSCAPE ECOLO WAGNER HH, 2001, LANDSCAPE ECOL, V16, P121 WALDHARDT R, 1999, Z KULTURTECHNIK LAND, V40, P246 WALDHARDT R, 2000, AGRARSPECTRUM, V31, P121 WALDHARDT R, 2003, AGR ECOSYST ENVIRON, V98, P393 WALDHARDT R, 2003, NOVA ACTA LEOPOLDINA, V87, P237 WALDREP GC, 2000, PRESERVATION, V52, P10 WEIBULL AC, 2003, BIODIVERS CONSERV, V12, P1335 WHITTAKER RJ, 2001, J BIOGEOGR, V28, P453 WIENS JA, 1993, OIKOS, V66, P369 WIENS JA, 2002, APPL LANDSCAPE ECOLO WILSON WL, 2003, AGR ECOSYST ENVIRON, V94, P249 WISSKIRCHEN R, 1998, STANDARDLISTE FARN B WOLTERS V, 1999, J RURAL ENG DEVERSIT, V40, P253 WRBKA T, 1999, HETEROGENEITY LANDSC 0921-2973 Landsc. Ecol.ISI:000220452500008QUniv Giessen, IFZ, Inst Landscape Ecol & Resources Management, Div Landscape Ecol & Landscape Planning, D-35392 Giessen, Germany. Waldhardt, R, Univ Giessen, IFZ, Inst Landscape Ecol & Resources Management, Div Landscape Ecol & Landscape Planning, Heinrich Buff Ring 26-32, D-35392 Giessen, Germany. rainer.waldhardt@agrar.uni-giessen.deEnglish? Wali, Mohan2012:Restoring ecosystems: a history, and some human dimensions 1075-1077Landscape Ecology277Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9742-3 0921-297310.1007/s10980-012-9742-3;<7|)Walker, R. S. Novaro, A. J. Branch, L. C.2003Effects of patch attributes, barriers, and distance between patches on the distribution of a rock-dwelling rodent (Lagidium viscacia)187-194Landscape Ecology182Argentina barriers Chinchillidae habitat quality isolation Lagidium matrix metapopulation mountain vizcacha Patagonia patch size METAPOPULATION DYNAMICS FRAGMENTED POPULATIONS LANDSCAPE STRUCTURE HABITAT ABUNDANCE QUALITY CONNECTIVITY DISPERSAL MOLINA DIETArticleWe tested whether size of habitat patches and distance between patches are sufficient to predict the distribution of the mountain vizcacha Lagidium viscacia a large, rock-dwelling rodent of the Patagonian steppe Argentina, or whether information on other patch and landscape characteristics also is required. A logistic regression model including the distance between rock crevices and depth of crevices, distance between a patch and the nearest occupied patch, and whether or not there was a river separating it from the nearest occupied patch was a better predictor of patch occupancy by mountain vizcachas than was a model based only on patch size and distance between patches. Our results indicate that a simple metapopulation analysis based on size of habitat patches and distance between patches may not provide an accurate representation of regional population dynamics if patches vary in habitat quality independently of patch size and features in the matrix alter connectivity.://000183770300007 ISI Document Delivery No.: 694JB Times Cited: 4 Cited Reference Count: 38 Cited References: *SPSS INC, 1999, SPSS BAS 10 0 APPL G ARNOLD GW, 1995, LANDSCAPE ECOL, V10, P65 FLEISHMAN E, 2002, CONSERV BIOL, V16, P706 GALENDE GI, 1998, IHERINGIA Z, V84, P3 GALENDE GI, 1998, MAZTOZOOLOGIA NEOTRO, V5, P123 HANSKI I, 1994, J ANIM ECOL, V63, P151 HANSKI I, 1995, OIKOS, V72, P21 HILL JK, 1996, J ANIM ECOL, V65, P725 HOKIT DG, 1999, ECOL APPL, V9, P124 HOKIT DG, 2001, CONSERV BIOL, V15, P1102 HOSMER DW, 1989, APPL LOGISTIC REGRES JIMENEZ JE, 1995, VIDA SILVESTRE NEOTR, V4, P89 JONSEN ID, 2001, OECOLOGIA, V127, P287 KEYGHOBADI N, 1999, MOL ECOL, V8, P1481 KINDVALL O, 1996, ECOLOGY, V77, P207 KING PS, 1987, EVOLUTION, V41, P401 LEON RJC, 1998, ECOLOGIA AUSTRAL, V8, P125 MAZEROLLE MJ, 1999, ECOSCIENCE, V6, P117 MICOL T, 1994, J ANIM ECOL, V63, P851 MOILANEN A, 1998, AM NAT, V152, P530 MOILANEN A, 1998, ECOLOGY, V79, P2503 NAGELKERKE NJD, 1991, BIOMETRIKA, V78, P691 PEARSON OP, 1948, J MAMMAL, V29, P345 PETIT S, 1998, CR ACAD SCI III-VIE, V321, P55 PUIG S, 1998, Z SAUGETIERKD, V63, P228 REDFORD K, 1992, MAMMALS NEOTROPICS S, V2 RICKETTS TH, 2001, AM NAT, V158, P87 ROBERTS DW, 1986, VEGETATIO, V66, P123 ROLAND J, 2000, ECOLOGY, V81, P1642 SINCLAIR ARE, 1982, CAN J ZOOL, V60, P889 SJOGRENGULVE P, 1996, METAPOPULATIONS WILD, P111 STITH BM, 1996, METAPOPULATIONS WILD, P187 VANAPELDOORN RC, 1994, LANDSCAPE ECOL, V9, P227 VOS CC, 2001, HEREDITY 5, V86, P598 WALKER RS, 2000, Z SAUGETIERKD, V65, P293 WALKER RS, 2001, THESIS U FLORIDA GAI WIENS JA, 1997, METAPOPULATION BIOL, P43 WILCOX BA, 1980, CONSERVATION BIOL EV, P95 0921-2973 Landsc. Ecol.ISI:000183770300007Univ Florida, Dept Wildlife Ecol & Conservat, Gainesville, FL 32611 USA. Wildlife Conservat Soc, Neuquen Appl Ecol Ctr, RA-8371 Neuquen, Argentina. Walker, RS, Univ Florida, Dept Wildlife Ecol & Conservat, Gainesville, FL 32611 USA.EnglishF<7)Walker, R. S. Novaro, A. J. Branch, L. C.2007Functional connectivity defined through cost-distance and genetic analyses: a case study for the rock-dwelling mountain vizcacha (Lagidium viscacia) in Patagonia, Argentina 1303-1314Landscape Ecology229landscape connectivity; microsatellites; non-invasive sampling; South America LANDSCAPE CONNECTIVITY; POPULATION-STRUCTURE; MICROSATELLITE LOCI; F-STATISTICS; HABITAT; FLOW; DIFFERENTIATION; ECOLOGY; DISPERSAL; MOVEMENTArticleNovLandscape connectivity can have profound consequences for distribution and persistence of populations and metapopulations. Evaluating functional connectivity of a landscape for a species requires a measure of dispersal rates through landscape elements at a spatial scale sufficient to encompass movement capabilities of individuals over the entire landscape. We evaluated functional connectivity for a rock-dwelling mammal, the mountain vizcacha (Lagidium viscacia), in northern Patagonia. Because of the strict association of mountain vizcachas with rocks, we hypothesized that connectivity for this species would be influenced by geology. We used molecular genetic estimates of gene flow to test spatially explicit models of connectivity created with GIS cost-distance analysis of landscape resistance to movement. We analyzed the spatial arrangement of cliffs with join counts and local k-function analyses. We did not capture and genotype individuals, but sampled at the population level through non-invasive collection of feces of mountain vizcachas. The model of landscape connectivity for mountain vizcachas based on geology was corroborated by the pattern of genetic structure, supporting the hypothesis that functional connectivity for mountain vizcachas is influenced by geology, particularly by the distribution of appropriate volcanic rocks. Analysis of spatial arrangement of cliffs indicated that occupied cliffs are clustered and confirmed that rivers act as barriers to dispersal for mountain vizcachas. Our methods could be used, within certain constraints, to study functional landscape connectivity in other organisms, and may be particularly useful for cryptic or endangered species, or those that are difficult or expensive to capture.://000250207500004 Cited Reference Count: 49 Cited References: ADRIAENSEN F, 2003, LANDSCAPE URBAN PLAN, V64, P233 BELISLE M, 2005, ECOLOGY, V86, P1988 BROQUET T, 2004, MOL ECOL, V13, P3601 BROQUET T, 2006, LANDSCAPE ECOL, V21, P877 CHEN DM, 1998, POINT PATTERN ANAL CLIFF AD, 1973, SPATIAL AUTOCORRELAT COULON A, 2004, MOL ECOL, V13, P2841 DEON R, 2002, CONSERV ECOL, V6 EASTMAN JR, 1989, P AUTOCARTO, V9, P288 ERNEST HB, 2000, MOL ECOL, V9, P433 FERRERAS P, 2001, BIOL CONSERV, V100, P125 FLAGSTAD O, 1999, MOL ECOL, V8, P879 GAGGIOTTI OE, 1999, MOL ECOL, V8, P1513 GETIS A, 1987, ECOLOGY, V68, P473 GOODMAN SJ, 1997, MOL ECOL, V6, P881 GOUDET J, 2000, FSTAT PROGRAM ESTIMA GRAHAM CH, 2001, CONSERV BIOL, V15, P1789 HARTL DL, 1997, PRINCIPLES POPULATIO HOECK HN, 1982, Z TIERPSYCHOL, V59, P177 JONSEN ID, 2001, OECOLOGIA, V127, P287 KEYGHOBADI N, 1999, MOL ECOL, V8, P1481 KNAAPEN JP, 1992, LANDSCAPE URBAN PLAN, V23, P1 LEON RJC, 1998, ECOLOGIA AUSTRAL, V8, P125 MANEL S, 2003, TRENDS ECOL EVOL, V18, P189 MARES MA, 1987, CURRENT MAMMALOGY, V1, P307 MERRIAM G, 1995, LANDSCAPE APPROACHES, P64 MICHELS E, 2001, MOL ECOL, V10, P1929 MILLER M, 1997, TOOLS POPULATION GEN MOILANEN A, 2002, ECOLOGY, V83, P1131 PITHER J, 1998, OIKOS, V83, P166 POPE LC, 1996, MOL ECOL, V5, P629 RAYMOND M, 1995, EVOLUTION, V49, P1280 RAYMOND M, 1995, J HERED, V86, P248 RICE WR, 1989, EVOLUTION, V43, P223 ROLAND J, 2000, ECOLOGY, V81, P1642 ROSEN MA, 2001, EXERGY INT J, V1, P3 ROUSSET F, 1997, GENETICS, V145, P1219 SLATKIN M, 1995, GENETICS, V139, P457 SUTCLIFFE OL, 2003, LANDSCAPE URBAN PLAN, V63, P15 TABERLET P, 1999, TRENDS ECOL EVOL, V14, P323 TAYLOR PD, 1993, OIKOS, V68, P571 TISCHENDORF L, 2000, OIKOS, V90, P7 VERBEYLEN G, 2003, LANDSCAPE ECOL, V18, P791 VIGNIERI SN, 2005, MOL ECOL, V14, P1925 VOS CC, 2001, HEREDITY 5, V86, P598 WALKER RS, 2000, MOL ECOL, V9, P1672 WALKER RS, 2000, Z SAUGETIERKD, V65, P293 WALKER RS, 2003, LANDSCAPE ECOLOGY, V18, P185 WEIR BS, 1984, EVOLUTION, V38, P1358 0921-2973 Landsc. Ecol.ISI:000250207500004[Ctr Ecol Aplicada Neuquen, Wildlife Conservat Soc, RA-8371 Neuquen, Argentina. Univ Florida, Dept Wildlife Ecol & Conservat, Gainesville, FL 32611 USA. Ctr Ecol Aplicada Neuquen, Consejo Natl Invest Cient & Tecn, RA-8371 Neuquen, Argentina. Walker, RS, Ctr Ecol Aplicada Neuquen, Wildlife Conservat Soc, RA-8371 Neuquen, Argentina. swalker@wcs.orgEnglish<7!Wallace, L. L. Crosthwaite, K. A.2005;The effect of fire spatial scale on Bison grazing intensity337-349Landscape Ecology203Bison; fire; grazing intensity; landscape heterogeneity; overmatching TALLGRASS PRAIRIE; FORAGING BEHAVIOR; HETEROGENEITY; PATTERNS; CATTLE; VEGETATION; GRASSLAND; LANDSCAPE; DIVERSITY; NUTRIENTArticleAprTo determine whether fire spatial and temporal scales affect foraging behavior and grazing intensity by Bison (Bison bison), we burned three different patch sizes (225, 900, and 3600 m 2) across an otherwise homogeneous grassland landscape. We then monitored grazing intensity for the succeeding 14 months. During the first 5 months after the burn (August-January), the Bison grazing intensity pattern was affected by whether a plot was burned and only marginally affected by plot size. During the next 5 months (January-June), grazing intensity was unaffected by plot size, but was greatest in the unburned 225 and 3600-m(2) plots. The final 4 months (June-October), grazing intensity was unaffected by treatments other than being higher in the unburned 3600-m(2) Plots. By the final sampling date, biomass was significantly greater in the burned plots and grazing intensity appeared to be responding to the amount of biomass present and the total amount of N present. The pattern displayed within the first 5 months after the burn is congruent with the expectations of optimal foraging theory with overmatching in the smallest plot size of 225 m(2) (BioScience 37 (1987) 789-799). The next two sampling periods displayed a matching aggregate response relative to biomass availability (Oecologia 100 (1999) 107-117) and total nitrogen mass (g m(-2)). The temporal shift that we found in Bison response to burn patch size is, to our knowledge, the first such examination of both spatial and temporal responses by Bison to landscape heterogeneity. We now have quantitative evidence of how native herbivores can alter their foraging responses to changes in landscape structure over time.://000231824400009 ISI Document Delivery No.: 963RU Times Cited: 0 Cited Reference Count: 59 Cited References: *SAS I INC, 1998, SAS STAT US GUID REL ADAMS DE, 1985, AM MIDL NAT, V113, P170 BELOVSKY GE, 1984, AM NAT, V124, P97 BIONDINI ME, 1989, VEGETATIO, V85, P21 BRIGGS JM, 1995, AM J BOT, V82, P1024 CHARNOV EL, 1976, AM NAT, V110, P141 CID MS, 1998, J RANGE MANAGE, V51, P644 COLLINS SL, 1987, ECOLOGY, V68, P1243 COLLINS SL, 1998, GRASSLAND DYNAMICS L, P140 COLLINS SL, 1998, SCIENCE, V280, P745 COPPEDGE BR, 1998, J RANGE MANAGE, V51, P258 ENGLE DM, 2000, J VEG SCI, V11, P135 FUHLENDORF SD, 2001, BIOSCIENCE, V51, P625 GRUNBAUM D, 1998, AM NAT, V151, P97 HAMILTON RG, 1996, T N AM WILDL NAT RES, P208 HARTNETT DC, 1996, J RANGE MANAGE, V49, P413 HAYES DC, 1985, J RANGE MANAGE, V38, P406 HECKATHORN SA, 1996, FUNCT ECOL, V10, P396 HOWE HF, 1995, ECOLOGY, V76, P1917 HUTCHINGS MR, 2001, ECOLOGY, V82, P1138 JARAMILLO VJ, 1992, J APPL ECOL, V29, P9 JIANG Z, 1993, EVOL ECOL, V7, P488 KAUTZ JE, 1978, P 1 INT RANG C, V1, P438 KIE JG, 1999, J MAMMAL, V80, P1114 KNAPP AK, 1999, BIOSCIENCE, V49, P39 KOLASA J, 1991, ECOLOGICAL HETEROGEN, P1 LARSON L, 1989, P 11 N AM PRAIR C, P243 LEPS J, 2000, MULTIVARIATE ANALA S MCINTYRE NE, 1999, LANDSCAPE ECOL, V14, P437 MCNAUGHTON SJ, 1979, AM NAT, V113, P691 MEAGHER MM, 1973, NATL PARK SERVICE SC, V1, P161 MORGAN RA, 1997, ECOLOGY, V78, P1087 ONEILL RV, 1988, LANDSCAPE ECOL, V2, P63 PASTOR J, 1997, J MAMMAL, V78, P1040 PEDEN DG, 1976, AM MIDL NAT, V96, P225 PICONE LI, 2003, J RANGE MANAGE, V56, P291 REDMANN RE, 1993, AM MIDL NAT, V130, P262 ROBERTSON GP, 1991, EXPLOITATION ENV HET, P237 ROTENBERRY JT, 1998, ECOLOGY, V79, P1160 RUTLEY BD, 2001, J RANGE MANAGE, V54, P218 SENFT RL, 1984, P W SECT AM SOC ANIM, V35, P192 SENFT RL, 1987, BIOSCIENCE, V37, P789 STADDON JFR, 1983, ADAPTIVE BEHAV LEARN STEINAUER EM, 1994, THESIS U OKLAHOMA NO STEINAUER EM, 1995, ECOLOGY, V76, P1195 STEUTER AA, 1995, ECOL APPL, V5, P756 SVEJCAR T, 1989, J RANGE MANAGE, V42, P11 TERBRAAK CJF, 1998, CANOCO REFERENCE MAN TURNER MG, 1994, ECOL APPL, V4, P472 TURNER MG, 1997, ECOL MONOGR, V67, P411 VANVUREN D, 1984, J RANGE MANAGE, V37, P260 VERDU JR, 2000, BIODIVERS CONSERV, V9, P1707 WALLACE LL, 1993, FUNCT ECOL, V7, P326 WALLACE LL, 1995, LANDSCAPE ECOL, V10, P75 WALLISDEVRIES MF, 1994, OECOLOGIA, V100, P107 WALLISDEVRIES MF, 1999, OECOLOGIA, V121, P355 WESSMAN CA, 1997, ECOL APPL, V7, P493 WILLMS W, 1980, J APPL ECOL, V17, P69 WILLMS W, 1981, J RANGE MANAGE, V34, P267 0921-2973 Landsc. Ecol.ISI:000231824400009Univ Oklahoma, Dept Bot & Microbiol, Norman, OK 73019 USA. Wallace, LL, Univ Oklahoma, Dept Bot & Microbiol, 770 Van Vleet Oval,Room 135, Norman, OK 73019 USA. lwallace@ou.eduEnglish|7_ AWallace, L. L. Turner, M. G. Romme, W. H. Oneill, R. V. Wu, Y. G.1995PScale of Heterogeneity of Forage Production and Winter Foraging by Elk and Bison75-83Landscape Ecology102^yellowstone national park foraging ecology foraging hierarchy snow landscape ecology ungulatesAprThe relationship between fine-scale spatial patterns of forage abundance and the feeding patterns of large ungulates is not well known. We compared these patterns for areas grazed in winter by elk and bison in a sagebrush-grassland landscape in northern Yellowstone National Park. At a fine scale, the spatial distribution of mapped feeding stations in 30 m x 30 m sites was found to be random where there were no large patches devoid of vegetation. In areas similar to the mapped sites, the underlying spatial distribution pattern of biomass was also determined to be random. At a broad scale, forage biomass differed among communities across the northern range but forage quality did not. These results suggest that ungulates are feeding randomly within forage patches (fine scale) but may select feeding sites based upon forage abundance at broader, landscape scales. Contrary to what has been suggested in other systems, ungulates were not 'overmatching' at finer scales.://A1995QX34400002-Qx344 Times Cited:38 Cited References Count:0 0921-2973ISI:A1995QX34400002>Wallace, Ll Univ Oklahoma,Dept Bot & Microbiol,Norman,Ok 73019EnglishA<7IWallin, D. O. Elliott, C. C. H. Shugart, H. H. Tucker, C. J. Wilhelmi, F.1992FSatellite remote-sensing of breeding habitat for an African weaverbird87-99Landscape Ecology72IREMOTE SENSING; AVHRR; BREEDING HABITAT; HABITAT SUITABILITY; EAST AFRICAArticleJulData derived from the Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA series of operational, polar orbiting, meteorological satellites have previously been shown to be quite useful for monitoring vegetation dynamics at scales ranging from regional (10(4) km2) to global. In this report, we demonstrate that these same data can be used to monitor potential breeding habitat for a highly mobile, granivorous African weaver-bird, the red-billed quelea (Quelea quelea). This species is often considered to be an agricultural pest, affecting cereal production throughout sub-Saharan Africa. The temporal resolution and very large (continental) spatial coverage provided by these data can provide a unique context within which to examine species distribution and abundance patterns.://A1992JF61500002 IISI Document Delivery No.: JF615 Times Cited: 14 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1992JF61500002PWALLIN, DO, OREGON STATE UNIV,DEPT FOREST SCI,PEAVY HALL 154,CORVALLIS,OR 97331.English <7 5Walpole, A. A. Bowman, J. Murray, D. L. Wilson, P. J.2012TFunctional connectivity of lynx at their southern range periphery in Ontario, Canada761-773Landscape Ecology275landscape resistance range periphery canada lynx lynx canadensis circuit theory occupancy functional connectivity habitat winter habitat selection northern maine conservation corridors population-dynamics closure assumption landscape canadensis ecology forest carnivoresMayPeripheral populations are often small and isolated compared to those in the range core, in part due to the patchy distribution of suitable habitats at range margins. It follows that peripheral populations typically occur at lower densities and are more susceptible to extinction, but their persistence may be facilitated through connectivity with core areas. Relationships between connectivity and the distribution of animal populations have not yet been fully evaluated, especially for large carnivores having extensive spatial needs and specialized habitat requirements. Using observations of snow tracks, we modeled occurrence of Canada lynx (Lynx canadensis) in relation to landscape characteristics along their southern range periphery in Ontario, Canada; we sought to assess functional connectivity of lynx habitat along the southern margins of the range. As observed in other studies, young coniferous forests had the highest probability of lynx occurrence, likely due to their association with snowshoe hares (Lepus americanus). We used the occurrence model to parameterize a resistance surface and then circuit theory to predict functional connectivity along the southern periphery of lynx distribution. Lynx typically travelled through landscapes with higher connectivity than random paths, implying that lynx habitat requirements in their southern range likely extend beyond habitat composition, and that conservation efforts should seek to preserve metapopulation dynamics through functional connectivity of suitable habitat across larger spatial scales.://000303056100011-929JC Times Cited:0 Cited References Count:51 0921-2973Landscape EcolISI:000303056100011 Walpole, AA Ontario Minist Nat Resources, Wildlife Res & Dev Sect, DNA Bldg,2140 E Bank Dr, Peterborough, ON K9J 7B8, Canada Ontario Minist Nat Resources, Wildlife Res & Dev Sect, DNA Bldg,2140 E Bank Dr, Peterborough, ON K9J 7B8, Canada Ontario Minist Nat Resources, Wildlife Res & Dev Sect, Peterborough, ON K9J 7B8, Canada Trent Univ, Dept Biol, Peterborough, ON K9J 7B8, Canada Trent Univ, Forens Sci Program, Peterborough, ON K9J 7B8, Canada Trent Univ, Nat Resources DNA Profiling & Forens Ctr, Dept Biol, Peterborough, ON K9J 7B8, CanadaDOI 10.1007/s10980-012-9728-1English|? $Walsh, Christopher J. Webb, J. Angus2014tSpatial weighting of land use and temporal weighting of antecedent discharge improves prediction of stream condition 1171-1185Landscape Ecology297Aug,Land management to protect streams requires knowing which parts of the landscape most strongly influence stream condition. Understanding how flow through landscapes and along streams affects such land-use impacts requires knowing the period of antecedent discharge that most strongly influences condition. Both considerations require determination of optimal weighting schemes for predictors of stream condition. We calculated forest cover weighted by flow-path distance to 572 urban, peri-urban, and rural sites-in the Melbourne, Australia, region-sampled for macroinvertebrates, and antecedent discharge weighted by time preceding each of 1,723 samples. Using mixed linear models that accounted for spatial dependence, we aimed to determine the weighting curve shape and length that best predicted macroinvertebrate assemblage composition. The best model was a function of mean annual discharge, weighted forest cover, weighted imperviousness, weighted antecedent discharge, and their interactions. Optimal weightings were exponential-half-decay distance 35 m overland (plausible range 26-50 m), and 1.0 km in-stream (0.75-1.3 km) for forest cover-, and linear over a parts per thousand yen4 year for antecedent discharge. Model plausibility was more affected by weighting distance than the shape of the weighting function. Regardless of weighting curve shape, riparian forest effects on macroinvertebrate assemblages are strongest within 10(1)-10(2) m from the stream, and 10(3) m upstream. Although exponential weightings are only marginally more plausible, they are the most realistic representation of physical processes. While our conclusions should not be interpreted as recommendations for buffer widths, they provide valuable insight into the scales of influence in the region and could be used to inform management decisions.!://WOS:000339831300007Times Cited: 0 0921-2973WOS:00033983130000710.1007/s10980-014-0050-y |? Walter, W. David VerCauteren, Kurt C. Campa, Henry, III Clark, William R. Fischer, Justin W. Hygnstrom, Scott E. Mathews, Nancy E. Nielsen, Clayton K. Schauber, Eric M. Van Deelen, Timothy R. Winterstein, Scott R.2009oRegional assessment on influence of landscape configuration and connectivity on range size of white-tailed deer 1405-1420Landscape Ecology2410|Variation in the size of home range of white-tailed deer (Odocoileus virginianus) has broad implications for managing populations, agricultural damage, and disease spread and transmission. Size of home range of deer also varies seasonally because plant phenology dictates the vegetation types that are used as foraging or resting sites. Knowledge of the landscape configuration and connectivity that contributes to variation in size of home range of deer for the region is needed to fully understand differences and similarities of deer ecology throughout the Midwest. We developed a research team from four Midwestern states to investigate how size of home range of deer in agro-forested landscapes is influenced by variations in landscape characteristics that provide essential habitat components. We found that for resident female deer, annual size of home range in Illinois (mean = 0.99 km(2)), Michigan (mean = 1.34 km(2)), Nebraska (mean = 1.20 km(2)), and Wisconsin (mean = 1.47 km(2)) did not differ across the region (F (3,175) = 0.42, P = 0.737), but differences between agricultural growing and nongrowing periods were apparent. Variables influencing size of home range included: distance to forests, roads, and urban development from the centroid of deer home range, and percent of crop as well as four landscape pattern indices (contrast-weighted edge density, mean nearest neighbor, area-weighted mean shape index, and patch size coefficient of variation). We also identified differences in model selection for four landscapes created hierarchically to reflect levels of landscape connectivity determined from perceived ability of deer to traverse the landscape. Connectivity of selected forested regions within agro-forested ecosystems across the Midwest plays a greater role in understanding the size of home ranges than traditional definitions of deer habitat conditions and landscape configuration.%://BIOSIS:PREV201000014114Times Cited: 0 0921-2973BIOSIS:PREV201000014114:10.1007/s10980-009-9374-4}?Walters, Steven2007lModeling scale-dependent landscape pattern, dispersal, and connectivity from the perspective of the organism867-881Landscape Ecology226Jul&://BIOSIS:PREV200700463288 0921-2973BIOSIS:PREV200700463288,<7m8Wamelink, G. W. W. ter Braak, C. J. F. van Dobben, H. F.2003eChanges in large-scale patterns of plant biodiversity predicted from environmental economic scenarios513-527Landscape Ecology185the Netherlands Biodiversity deposition groundwater level model nitrogen economic scenario analysis soil ELLENBERG INDICATOR VALUES SPECIES RICHNESS FIELD-MEASUREMENTS VEGETATION CHANGE REGIONAL-SCALE COASTAL DUNES MODEL NETHERLANDS MANAGEMENT DIVERSITYArticleIn the industrialized world large sums of money are spent on measures to preserve biodiversity by improving environmental quality. This creates a need to evaluate the effectiveness of such measures. In response we developed a model, NTM, that links plant biodiversity to abiotic variables that are under human control. These variables are: vegetation management, and the soil variables groundwater level, pH and nitrogen availability. We used species richness and the criteria of the Red Lists, i.e., the rarity and decline per species as measure for potential changes in biodiversity. NTM uses a statistical approach, and models potential plant biodiversity based on the above criteria as a non-linear function of the three soil variables. The regression model is calibrated on a data set consisting of 33,706 vegetation releves. Because field data of vegetation combined with measurements of soil variables are insufficiently available, we used the average of Ellenberg's indicator values of the species in each releve as a proxy. NTM was subjected to both validation and uncertainty analysis. The validation was carried out by comparison with an independent data set. The uncertainty analysis showed that uncertainty in absolute biodiversity values is large, but that comparative scenario studies can be carried out with an acceptable uncertainty. As an example we show the evaluation of the impact of three European economic scenarios on potential plant biodiversity in the Netherlands. Although there were differences per vegetation type and per region, potential plant biodiversity had a tendency to increase, with the highest increase for the scenario with the highest reduction in atmospheric deposition of nitrogen and acidity.://000185827200005 ISI Document Delivery No.: 730JG Times Cited: 1 Cited Reference Count: 55 Cited References: *CENTR PLANB, 1996, 89 CENTR PLANB *GENST 5 COMM, 1993, GENST 5 REL 3 REF MA *RIVM, 1997, NVK 97 *VANDOBBEN HF, UNPUB QUANTIFICATION ALI MM, 2000, J ARID ENVIRON, V45, P215 ANGELSTAM PK, 1998, J VEG SCI, V9, P593 BAKKER JP, 1989, THESIS U GRONINGEN G BERDOWSKI JJM, 1991, 114102 RIVM CATTO N, 2002, CAN GEOGR-GEOGR CAN, V46, P17 DEVRIES W, 1989, WATER AIR SOIL POLL, V48, P349 DIEKMANN M, 1998, J ECOL, V86, P269 DUPRE C, 2002, J ECOL, V90, P796 EILERS PHC, 1996, STAT SCI, V11, P89 ELLENBERG H, 1982, VEGETATION MITTELEUR ELLENBERG H, 1991, SCRIPTA GEOBOTANICA, V18, P9 ERTSEN ACD, 1998, PLANT ECOL, V135, P113 FOPPEN RPB, 2001, BRIDGING GAPS FRAGME GEERTSEMA W, 2002, THESIS ALTERRA GOEDHART PW, 1996, GENSTAT 5 GLW DLO PR GRIFFITHS GH, 2000, INT J REMOTE SENS, V21, P2685 HASTIE T, 1990, GEN ADDITIVE MODELS HAWKES JC, 1997, J APPL ECOL, V34, P375 HECTOR A, 1999, SCIENCE, V286, P1123 HERTOG AJ, 1992, GEAUTOMATISEERDE BEP HILL MO, 1997, J VEG SCI, V8, P579 HILL MO, 2000, J APPL ECOL, V37, P3 HUSTON MA, 1994, BIOL DIVERSITY COEXI JANSEN MJW, 2000, FORESIGHT PRECAUTION KOOIJMAN AM, 1998, J ECOL, V86, P511 KROS J, 1995, 95 SCDLO KROS J, 2002, ALTERRA SCI CONTRIBU, V7 LARSSON TB, 2001, ECOLOGICAL B, V50 LATOUR JB, 1993, TNO COMM HYDROL RES, V47, P53 LOREAU M, 1998, P NATL ACAD SCI USA, V95, P5632 MACE G, 1994, SPECIES, V21, P13 NAEEM S, 1996, OIKOS, V76, P259 NOHR H, 1997, BIODIVERS CONSERV, V6, P545 NOSS RF, 2001, CONSERV BIOL, V15, P578 OOMES MJM, 1996, J APPL ECOL, V33, P576 PASTOORS MJH, 1993, 714305004 RIVM POLLOCK MM, 1998, ECOLOGY, V79, P94 SCHAFFERS AP, 2000, J VEG SCI, V11, P225 SCHAMINEE JHJ, 1989, LEVENDE NATUUR, V90, P204 SCHOUWENBERG EPA, 2000, 001 ALT TERBRAAK CJF, 1994, J VEG SCI, V5, P361 THOMPSON K, 1993, PHYTOCOENOLOGIA, V23, P277 VANDERMAAREL E, 1993, PHYTOCOENOLOGIA, V23, P343 VANEK R, 2000, ECOL ENG, V16, P127 VANOENE H, 1999, ECOL APPL, V9, P920 VANWIRDUM G, 1990, THESIS MAASTRICHT WAMELINK GWW, 1996, 233 IBNDLO WAMELINK GWW, 2000, 045 ALT WAMELINK GWW, 2002, J VEG SCI, V13, P269 WISHEU IC, 1996, OIKOS, V76, P253 WOHLGEMUTH T, 1998, BIODIVERS CONSERV, V7, P159 0921-2973 Landsc. Ecol.ISI:000185827200005pAlterra, NL-6700 AA Wageningen, Netherlands. Wamelink, GWW, Alterra, POB 47, NL-6700 AA Wageningen, Netherlands.English<7d/Wang, G. X. Guo, X. Y. Shen, Y. P. Cheng, G. D.2003hEvolving landscapes in the headwaters area of the Yellow River (China) and their ecological implications363-375Landscape Ecology184Ulandscape evolution landscape pattern source area of the Yellow River transfer matrixArticleMThe relationship and feedback between landscape pattern, function and process serve to describe the behavior of a regional landscape. Based on landscape function characteristics such as biological productivity, soil nutrient content, vegetative cover, etc., a quantitative method and digital model for analyzing evolving landscape functionality in the headwaters area of the Yellow River in the People's Republic of China were devised. Through the analysis of three-phase remote sensing data from 1975, 1985 and 1995 and based upon the well-defined characteristics of this region's evolving landscape over the past 30 years, the attendant ecology of the different functional landscape ecotypes was investigated. Between 1975 and 1995 the area of AC&S (alpine cold meadow and steppe) in the source area of the Yellow River has decreased by 27.25%, ACSW (alpine cold swamp meadow) has decreased by 27.04%, ALP (alpine steppe) by 38.18% and lakes by 9.78%. The grass biomass production decreased by 752.37 Gg, of which AC&S meadows accounted for 83.8% of these losses. The overall stock capacity of the headwaters area of the Yellow River decreased by 518.36 thousand sheep units. Soil nutrients showed a similar pattern, soil nutrient loss was greater from 1985-1995 than from 1975-1985. Changes in the overall ecological functionality of the area were not simply a result of a summation of the changes associated with individual evolving landscapes, but rather an integration of positive and negative influences. Landscape evolution occurs in two main directions: degradation and strengthening (expanding and improving). An understanding of the direction, force and integration of parameters influencing landscape evolution as it impacts the attending ecosystems can allow one to foresee how the landscape of the Yellow River source area will evolve in the coming years.://000185919200002 ISI Document Delivery No.: 732AT Times Cited: 1 Cited Reference Count: 29 Cited References: *CHIN AC SCI I GEO, 1990, ATL QINGH TIB PLAT BECKER A, 1997, 43 IGBP BURKE VJ, 2000, LANDSCAPE ECOL, V15, P1 CHEN Q, 1998, PRATACULTURAL SCI, V7, P44 CHENG G, 1997, INFLUENCES CLIMATIC CHENG G, 1998, J ADV EARTH SCI S, V13, P24 FARINA A, 1998, PRINCIPLES METHODS L FLERCHINGER GN, 1991, AGR FOREST METEOROL, V56, P227 FORMAN RTT, 1995, LANDSCAPE ECOL, V10, P133 FU B, 1994, LAND DEGRAD REHABIL, V5, P33 FU B, 1999, J ENVIRON SCI, V11, P136 JI Z, 1996, J GLACIOL GEOCRYOL S, V18, P274 KANG X, 1996, J GLACIOL GEOCRYOL S, V18, P281 LI X, 2000, ACTA ECOLOGICA SINIC, V20, P1113 LIU Y, 1996, ECOENVIRONMENT SUSTA MCGARIGAL K, 1994, FRAGSTATS SPATIAL AN PENG M, 1987, MEMOIRS I PLATEAU BI, V17, P71 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 TIAN G, 1995, REMOTE SENSING DYNAM TURNER MG, 1991, QUANTITATIVE METHODS WANG B, 2000, J GLACIOLOGY GEOCRYO, V22, P200 WANG S, 1998, J ADV EARTH SCI S, V13, P65 WU B, 1998, CHINESE SCI BULL, V43, P2437 XI J, 1997, WATER RESOURCES YELL XIAO D, 1997, ACTA ECOLOGICA SINIC, V17, P453 XIAO D, 1998, J APPL ECOL, V9, P217 XIAO D, 1999, PROGGR LANDSCAPE ECO, P8 YANG C, 1997, STOPPED FLOWING EVEN, P1 ZHAO L, 1996, ANN REPORT COMPREHEN, P70 0921-2973 Landsc. Ecol.ISI:000185919200002LChinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, State Key Lab Frozen Soil Engn, Lanzhou 730000, Peoples R China. Lanzhou Univ, Coll Resource & Environm, Lanzhou 730000, Peoples R China. Wang, GX, Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, State Key Lab Frozen Soil Engn, Lanzhou 730000, Peoples R China.English O<7'Wang, G. X. Yao, J. H. Luo, L. Qian, L.2004_Soil C and N content under evolving landscapes in an arid inland river basin of northwest China621-629Landscape Ecology196garid region; landscape evolution; soil organic C and N contents; deposition and losses; impacts ECOLOGYArticleAugThe state of a landscape is primarily reflected by its soil nutrients and organic matter status, which in turn are related to the type, size and number of landscape elements or patches. Evolving landscape patterns inevitably cause an evolution in ecosystem functionality. In particular, in arid regions, gained, lost and existing soil N and C pools have important ecological implications. The impacts of evolving landscapes in the middle reaches of the Heihe River basin of northwest China on soil organic C and N losses were assessed by both quantitative and computer modelling methods. In the period 1987-1997, patch transitions of the region's evolving landscapes have been predominantly characterized by a farmland expansion of 1.5 . 10(3) km(2), and the desertification of 15.12% of existing farmlands into desert. As the result of such changes, alpine steppe and piedmont warm and desert steppe decreased by 43.9% and 2.72% respectively, whereas, plain swamp meadow and gobi and sandy desert increased by 13.2% and 10.77%, respectively. Consequently, soil organic matter and N contents decreased significantly in most landscape patches. In the study region, over these ten years, net soil organic C and N losses reached 5.30 Gg and 0.51 Gg, respectively, a pattern repeated over the entire arid inland region of northwest China, due to similar hydrological resources and patterns of regional development. Large soil C and N losses caused by landscape changes will inevitably result in significant new environmental problems.://000224100600004 ~ISI Document Delivery No.: 857FC Times Cited: 0 Cited Reference Count: 17 Cited References: *NANJ AGR U, 1992, METH AN AGR CHEM PAR BOJIE F, 1999, J ENVIRON SCI, V11, P136 FARINA A, 1998, PRINCIPLES METHODS L FORMAN RTT, 1995, LANDSCAPE ECOL, V10, P133 GENXU W, 1999, J NATURAL RESOURCES, V14, P109 GENXU W, 2002, GEOGRAPHIC SCI, V22, P527 JINGYUN F, 1996, CARBON POOL TERRESTR, P95 LI X, 2000, ACTA ECOLOGICA SINIC, V20, P1113 LING L, 2001, ACTA ECOLOGICA SIICA, V21, P1217 LONGHENG C, 2000, SOIL HEXI CORRIDOR C MCGARIGAL K, 1994, FRAGSTATS SPATIAL AN PICKETT STA, 1995, SCIENCE, V269, P331 RITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 VINCENT J, 2000, LANDSCAPE ECOLOGY, V15, P1 XIAO D, 1997, ACTA ECOLOGICA SINIC, V17, P453 XIAO D, 1999, PROGGR LANDSCAPE ECO, P8 ZILI F, 2001, J NATURAL RESOURCES, V16, P22 0921-2973 Landsc. Ecol.ISI:0002241006000042Lanzhou Univ, MOE Lab Western Chinas Environm Syst, Lanzhou 730000, Peoples R China. Lanzhou Univ, Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, Lanzhou 730000, Peoples R China. Wang, GX, Lanzhou Univ, MOE Lab Western Chinas Environm Syst, Lanzhou 730000, Peoples R China. gxwang@ns.lzb.ac.cnEnglish|?MWang, Hong-Bing Li, Hong Ming, Hong-Bo Hu, Yong-Hong Chen, Jia-Kuan Zhao, Bin2014xPast land use decisions and socioeconomic factors influence urban greenbelt development: a case study of Shanghai, China 1759-1770Landscape Ecology2910Dec Although the designation of greenbelts around cities has been a common practice for several decades, some greenbelts have not been successfully protected from development. To explore the forces driving the construction of greenbelts, this paper examines how past land use and land cover decisions and current socioeconomic factors have affected the development of the artificial greenbelt zone in China's Shanghai metropolitan area. Using aerial photographs from 1994, 2005, and 2010, we find that the area of afforested greenbelt was generally related to past land use/cover decisions. Compared with cropland and grassland, factory, village, and urban land use/cover types showed higher resistance to transitioning to forest during the study period. Moreover, the Mantel test showed little spatial autocorrelation between protected land and geodetic coordinates. Principal coordinates of neighbour matrices analysis showed that socioeconomic and urban contextual variables explained 9 % of the variation in protected land, whereas the spatial variables explained 24 %. Population migration towards the city's suburban fringes negatively affected the greenbelt area, while district-level finance revenue was a positive factor and town/sub-district-level gross domestic product was a negative factor, depending on the investment sources for greenbelt construction. Furthermore, distance to the sub-centre and distance to a subway station had positive influences. Understanding these driving forces can help improve greenbelt planning and management.!://WOS:000346920900010Times Cited: 0 0921-2973WOS:00034692090001010.1007/s10980-014-0104-1p<78Wang, H. Q. Hall, C. A. S. Cornell, J. D. Hall, M. H. P.2002Spatial dependence and the relationship of soil organic carbon and soil moisture in the Luquillo Experimental Forest, Puerto Rico671-684Landscape Ecology178elevation gradient Luquillo Experimental Forest (LEF) spatial correlation spatial variability topography LARGE LAND AREAS GEOSTATISTICAL ANALYSIS OPTIMAL INTERPOLATION CHEMICAL-PROPERTIES TROPICAL FOREST ECOSYSTEM WATERSHEDS DYNAMICS MATTER DISTURBANCEArticleDecWe used geo-spatial statistical techniques to examine the spatial variation and relationship of soil organic carbon (SOC) and soil moisture (SM) in the Luquillo Experimental Forest (LEF), Puerto Rico, in order to test the hypothesis that mountainous terrain introduces spatial autocorrelation and crosscorrelation in ecosystem and soil properties. Soil samples (n = 100) were collected from the LEF in the summer of 1998 and analyzed for SOC, SM, and bulk density (BD). A global positioning system was used to georeference the location of each sampling site. At each site, elevation, slope and aspect were recorded. We calculated the isotropic and anisotropic semi-variograms of soil and topographic properties, as well as the cross-variograms between SOC and SM, and between SOC and elevation. Then we used four models (random, linear, spherical and wave/hole) to test the semi-variances of SOC, SM, BD, elevation, slope and aspect for spatial dependence. Our results indicate that all the studied properties except slope angle exhibit spatial dependence within the scale of sampling (200 - 1000 m sampling interval). The spatially structured variance (the variance due to the location of sampling sites) accounted for a large proportion of the sample variance for elevation (99%), BD (90%), SOC (68%), aspect (56%) and SM (44%). The ranges of spatial dependence ( the distances within which parameters are spatially dependent) for aspect, SOC, elevation, SM, and BD were 9810 m, 3070 m, 1120 m, 930 m and 430 m, respectively. Cross correlograms indicate that SOC varies closely with elevation and SM depending on the distances between samples. The correlation can shift from positive to negative as the separation distance increases. Larger ranges of spatial dependence of SOC, aspect and elevation indicate that the distribution of SOC in the LEF is determined by a combination of biotic (e.g., litterfall) and abiotic factors (e.g., microclimate and topographic features) related to elevation and aspect. This demonstrates the importance of both elevation and topographic gradients in controlling climate, vegetation distribution and soil properties as well as the associated biogeochemical processes in the LEF.://000181767400001 ISI Document Delivery No.: 659FV Times Cited: 5 Cited Reference Count: 46 Cited References: *GAMM DES, 1998, GS PLUS GEOST ENV SC BASNET K, 1993, TROP ECOL, V34, P51 BIRKELAND PW, 1974, PEDOLOGY WEATHERING BLACK CA, 1965, METHODS SOIL ANAL 2 BROWN S, 1983, SO44 USDA BURGESS TM, 1980, J SOIL SCI, V31, P315 BURGESS TM, 1980, J SOIL SCI, V31, P333 CAHN MD, 1994, SOIL SCI SOC AM J, V58, P1240 DAVIDOFF B, 1988, SOIL SCI, V145, P1 DETWILER RP, 1986, BIOGEOCHEMISTRY, V2, P67 GARCIAMARTINO AR, 1996, CARIBB J SCI, V32, P413 GARCIAMONTIEL DC, 1994, FOREST ECOL MANAG, V63, P57 GRIFFITH DA, 1999, CASEBOOK SPATIAL STA HALL CAS, 1992, WATER AIR SOIL POLL, V64, P385 HOLDRIDGE LR, 1967, LIFE ZONE ECOLOGY ISAAKS EH, 1989, INTRO APPL GEOSTATIS KERN JS, 1997, SOIL PROCESSES CARBO, P29 LECLERC G, 2000, QUANTIFYING SUSTAINA, P223 LUGO AE, 1993, PLANT SOIL, V149, P27 MCDOWELL WH, 1992, BIOGEOCHEMISTRY, V18, P53 PARTON WJ, 1987, SOIL SCI SOC AM J, V51, P1173 PARTON WJ, 1988, BIOGEOCHEMISTRY, V5, P109 PASTOR J, 1998, ECOL APPL, V8, P411 ROBERTSON GP, 1987, ECOLOGY, V68, P744 ROBERTSON GP, 1997, ECOL APPL, V7, P158 ROSSI RE, 1992, ECOL MONOGR, V62, P277 ROUHANI S, 1996, GEOSTATISTICS ENV GE SANCHEZ MJ, 1997, IITFRN1 USDA FOR SER SANFORD RL, 1991, BIOTROPICA, V23, P364 SCATENA FN, 1995, GEOMORPHOLOGY, V13, P199 SCATENA FN, 1996, BIOTROPICA A, V28, P424 SCHLESINGER WH, 1996, ECOLOGY, V77, P364 SILVER WL, 1994, PLANT SOIL, V164, P29 SILVER WL, 1999, BIOGEOCHEMISTRY, V44, P301 SMITH JL, 1994, SOIL BIOL BIOCHEM, V26, P1151 TABOR JA, 1984, SOIL SCI SOC AM J, V48, P602 THOMPSON GR, 1993, MODERN PHYSICAL GEOL TRANGMAR BB, 1985, ADV AGRON, V38, P45 TRANGMAR BB, 1987, SOIL SCI SOC AM J, V51, P668 WANG H, 2002, IN PRESS ECOLOGICAL, V147, P105 WEAVER PL, 1987, BIOTROPICA, V19, P17 WEAVER PL, 1990, BIOTROPICA, V22, P69 WEBSTER R, 1985, ADV SOIL SCI, V3, P1 YOST RS, 1982, SOIL SCI SOC AM J, V46, P1028 YOST RS, 1982, SOIL SCI SOC AM J, V46, P1033 ZIMMERMAN JK, 1996, BIOTROPICA A, V28, P414 0921-2973 Landsc. Ecol.ISI:000181767400001SUNY Coll Environm Sci & Forestry, Syst Ecol Lab, Syracuse, NY 13210 USA. Wang, HQ, SUNY Coll Environm Sci & Forestry, Syst Ecol Lab, Syracuse, NY 13210 USA. hqwang@mailbox.syr.eduEnglishڽ7 %Wang, Jun Brown, DanielG Chen, Jiquan2013dDrivers of the dynamics in net primary productivity across ecological zones on the Mongolian Plateau725-739Landscape Ecology284Springer NetherlandsqGrassland ecosystem Net primary productivity Drivers Spatial panel data models Ecological zones Mongolian Plateau 2013/04/01+http://dx.doi.org/10.1007/s10980-013-9865-1 0921-2973Landscape Ecol10.1007/s10980-013-9865-1Englishڽ7 LWang, Lixin Okin, GregoryS D’Odorico, Paolo Caylor, KellyK Macko, StephenA2013]Ecosystem-scale spatial heterogeneity of stable isotopes of soil nitrogen in African savannas685-698Landscape Ecology284Springer NetherlandsdC3 plants C4 plants Geostatistics Isotope Kalahari Savannas Soil δ15N Soil nitrogen Stable isotopes 2013/04/01+http://dx.doi.org/10.1007/s10980-012-9776-6 0921-2973Landscape Ecol10.1007/s10980-012-9776-6English|? Wang, W. W. Pataki, D. E.2010ISpatial patterns of plant isotope tracers in the Los Angeles urban region35-52Landscape Ecology251Plant-environment interactions are difficult to study in urban areas, in part due to the confounding factors that affect physiology, including alterations to atmospheric composition and climate. We wished to determine whether the spatial distribution of urban plant isotope and chemical tracers could be used to distinguish among the many environmental factors that may influence plant physiological processes. We extensively sampled winter annual plants in the region in and surrounding Los Angeles, USA, and analyzed plant material for stable carbon, nitrogen and oxygen isotopes as well as carbon and nitrogen content; and radiocarbon composition. We then overlay maps of the spatial distribution of pollutant, climatic, geographic, and population variables to determine if there were significant relationships. Multiple regression analysis indicated that the radiocarbon content of winter annual plants was strongly related to ozone and carbon monoxide concentrations. Nitrogen isotopes and leaf nitrogen content were related to atmospheric NO2 and ozone concentrations. Oxygen isotope ratios were correlated with atmospheric vapor pressure deficit and ozone concentrations. These relationships suggest that plant processes are influenced by anthropogenic N uptake and ozone damage in this region. For stable carbon isotopes, spatial variability was correlated with temperature and the distribution of pollutants and point sources, but the functional relationships were less clear. While further studies are needed to confirm the mechanisms, these results highlight the potential for mapping of plant isotopes as a tool for studying complex plant-environment interactions in urban landscapes.!://WOS:000273479100004Times Cited: 0 0921-2973WOS:00027347910000410.1007/s10980-009-9401-5|? Wang, Xianli Cumming, Steve G.2010mConfiguration dynamics of boreal forest landscapes under recent fire and harvesting regimes in western Canada 1419-1432Landscape Ecology259NovHarvesting and forest fire change the spatial configurations of forest habitat. We used multivariate statistical models to evaluate the individual and cumulative effects of these two disturbances on habitat configuration in managed boreal forest landscapes in western Canada. We evaluated three aspects of configuration (core area, inter-patch distance and shape) using indices normalized for total habitat abundance. The two disturbances types had different effects on the three configuration metrics in terms of both the magnitude and direction of change. We found that the magnitudes of harvesting effects were larger than for fire. The direction of change was the same for core area and shape, but opposite for inter-patch distance which decreased slightly after fire. The combined effects of the two disturbances are distinct from the effects of either disturbance alone, and the effects are not always additive or compensatory for all metrics. Pre-treatment configuration was a significant covariate in all models, and total habitat abundance was significant in 4/9 models, but these were often not the most important covariates. In the cumulative disturbance model, covariates for the number or size of cut-blocks were significant.!://WOS:000281981000009Times Cited: 1 0921-2973WOS:00028198100000910.1007/s10980-010-9517-7;|?8 Wang, Xianli Cumming, Steven G.20119Measuring landscape configuration with normalized metrics723-736Landscape Ecology265May(Natural and anthropogenic disturbances on natural landscapes reduce the abundance and alter the spatial arrangement of certain habitat types. Measuring and modeling such alterations, and their biological effects, remains challenging in part because many widely used configuration metrics are correlated with habitat amount. In this paper, we consider the sources of such correlation, and distinguish process or sample-based correlation from functional correlation that may be an artifact of the metrics themselves. Process correlation is not necessarily a serious problem for statistical inference, but functional correlation would be. We propose that functional correlation may be reduced by normalizing metrics by habitat abundance. We illustrate with normalized versions of total core area, mean nearest neighbor distance, and mean shape index, and show informally that the standard versions of these metrics should exhibit functional correlation. We evaluate the normalized metrics on samples of harvested and undisturbed forested landscapes, and on simulated landscapes generated with varying degrees of spatial autocorrelation. Normalization markedly reduced correlations with habitat abundance on natural landscapes, but not on simulated landscapes. The reasons for this appear to be a combination of differing variances in metric values within levels of habitat abundance, and of the precise form of the relationships between habitat abundance and the un-normalized metrics. In all cases, the normalization changes the ordering of landscapes by metric values across levels of habitat abundance. In consequence, normalized and standard metrics cannot both be accurate measures of configuration. We conclude that statistical modeling of ecological response data is needed to finally determine the merits of the normalizations.!://WOS:000291485100010Times Cited: 1 0921-2973WOS:00029148510001010.1007/s10980-011-9601-7 1|7Wang, X. L. Cumming, S. G.2009\Modeling configuration dynamics of harvested forest landscapes in the Canadian boreal plains229-241Landscape Ecology242harvesting forest fragmentation landscape configuration landscape pattern metrics landscape dynamics boreal forest pattern-analysis breeding birds regional-scale fragmentation habitat disturbance mixedwood alberta cover managementFebHabitat configuration has important implications for the persistence of faunal and floral populations at a variety of spatial scales. Forest harvesting alters habitat configurations. However, measuring and predicting such alterations remains challenging, in part because previously developed metrics of habitat configuration are often not statistically independent of habitat amount. Thus, their ability to measure independent effects of habitat configurations and habitat amount on ecosystem components such as wildlife populations has been limited. Here, we evaluate habitat configuration based on newly developed metrics that are independent of habitat amount but do not depend on regression residuals of abundance and configuration relationships on any population of landscapes. We use these new metrics to measure and predict changes in habitat configuration following forest harvesting in the boreal forest of Alberta, Canada. Our findings clearly demonstrate changes in habitat configuration resulting from forest harvesting can be predicted precisely with information about initial habitat patch structure and harvesting patterns. Because forest harvesting has significant implications for habitat configuration, accurately predicting these changes is critical for determining if forest harvesting strategies are sustainable for ecosystem components and processes. This study provides a set of novel, robust metrics for tracking landscape-scale changes in habitat configuration in harvested boreal forests.://000262828900007-399WB Times Cited:0 Cited References Count:41 0921-2973ISI:000262828900007Wang, Xl Univ Alberta, Dept Renewable Resources, 751 Gen Serv Bldg, Edmonton, AB T6G 2H1, Canada Univ Alberta, Dept Renewable Resources, Edmonton, AB T6G 2H1, Canada Univ Laval, Dept Sci Bois & Foret, Fac Foresterie & Geomat, Quebec City, PQ G1V 0A6, CanadaDoi 10.1007/S10980-008-9301-0English<76Wang, Y. C. Larsen, C. P. S.2006~Do coarse resolution US presettlement land survey records adequately represent the spatial pattern of individual tree species? 1003-1017Landscape Ecology217forest landscape; geostatistics; GLO survey; interpolation; Minnesota; presettlement vegetation; scale; spatial resolution NORTHERN WISCONSIN; LANDSCAPE ECOLOGY; BARAGA COUNTY; FIRE REGIMES; FOREST TYPES; NEW-ENGLAND; VEGETATION; SCALE; CLASSIFICATION; DISTURBANCEArticleOctMPresettlement land survey records (PLSRs) are a valuable and unique source of information for the reconstruction of presettlement forest patterns. The purpose of this study was to determine whether coarsely resolved PLSRs are adequate to characterize the spatial patterns of individual tree species over large areas. The General Land Office Survey records of the PLSRs of Minnesota were used and species selected in the analysis were based on their abundances and degrees of clustering. A geostatistical procedure was developed to analyze observations of bearing-tree point-locations, at progressively coarser resolutions from 1 x 1 mile to 24 x 24 miles, to create spatially continuous probability surfaces of species occurrences across the landscape. Statistical and visual analyses of the geostatistical predictions indicated that coarsely resolved PLSRs, as coarse as 24 x 24 miles, can adequately represent the spatial pattern of individual species over large areas. Mean errors in predictions increased as more coarsely resolved data were used, primarily in response to the decreased abundance of a species and minorly in response to the degree of spatial clustering of a species. The results indicate that coarsely resolved township-level data of 6 x 6 miles can be used for presettlement vegetation reconstruction of large areas of several counties.://000241010900004 HISI Document Delivery No.: 091FA Times Cited: 0 Cited Reference Count: 45 Cited References: *ESRI INC, 1996, US AV *ESRI INC, 2001, US ARCGIS GEOST AN *SPSS INC, 1999, SPSS BAS 10 0 WIND U ALMENDINGER J, 1997, 56 MINN DEP NAT RES BAILEY RG, 1995, DESCRIPTION ECOREGIO BARRETT LR, 1995, AM MIDL NAT, V134, P264 BATEK MJ, 1999, J BIOGEOGR, V26, P397 BOLLIGER J, 2004, RESTOR ECOL, V12, P124 BONHAMCARTER GF, 1994, GEOGRAPHIC INFORM SY BROWN DG, 1998, INT J GEOGR INF SCI, V12, P105 BROWN DG, 1998, PLANT ECOL, V134, P97 BURROUGH PA, 1996, GEOGRAPHIC OBJECTS I, P3 CLARK PJ, 1954, ECOLOGY, V35, P445 COGBILL CV, 2002, J BIOGEOGR, V29, P1279 COWELL CM, 1995, ANN ASSOC AM GEOGR, V85, P65 DELCOURT HR, 1996, LANDSCAPE ECOL, V11, P363 DYER JM, 2001, CAN J FOREST RES, V31, P1708 FENSHAM RJ, 1997, J BIOGEOGR, V24, P827 FOSTER DR, 1992, J ECOL, V80, P753 HE HS, 2000, J BIOGEOGR, V27, P1031 HEINSELMAN ML, 1973, QUATERNARY RES, V3, P329 HERSHEY RR, 2000, QUANTIFYING SPATIAL, P119 ISAAKES EH, 1989, APPL GEOSTATISTICS JACKSON SM, 2000, CAN J FOREST RES, V30, P605 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 LIEGEL C, 1982, SCI ARTS LETT, V70, P13 LORIMER CG, 1977, ECOLOGY, V58, P139 MACLEAN AL, 2002, P S FIR FUEL TREATM MANIES KL, 2000, LANDSCAPE ECOL, V15, P741 MANIES KL, 2001, CAN J FOREST RES, V17, P1719 MARSCHNER FJ, 1974, ORIGINAL VEGETATION OWENS KE, 2001, THESIS MICHIGAN TU QI Y, 1996, LANDSCAPE ECOL, V11, P39 ROSSI RE, 1992, ECOL MONOGR, V62, P277 SCHULTE LA, 2001, J FOREST, V99, P5 SCHULTE LA, 2002, CAN J FOREST RES, V32, P1616 SCHULTE LA, 2005, ECOLOGY, V86, P431 SICCAMA TG, 1971, AM MIDL NAT, V85, P153 SNETSINGNER S, 2000, LAND COVER CHANGE GR TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 WANG YC, 2004, THESIS U BUFFALO WANG YC, 2005, PROG PHYS GEOG, V29, P568 WHITNEY GG, 1996, COASTAL WILDERNESS F WU JG, 2002, LANDSCAPE ECOL, V17, P355 WU JG, 2004, LANDSCAPE ECOL, V19, P125 0921-2973 Landsc. Ecol.ISI:000241010900004SUNY Buffalo, Univ Buffalo, Dept Geog, Buffalo, NY 14261 USA. Wang, YC, Natl Univ Singapore, Dept Geog, 1 Arts Link, Singapore 117570, Singapore. geowyc@nus.edu.sgEnglish|?2Wang, Y. H. Yang, K. C. Bridgman, C. L. Lin, L. K.2008PHabitat suitability modelling to correlate gene flow with landscape connectivity989-1000Landscape Ecology238Landscape connectivity is important in designing corridor and reserve networks. Combining genetic distances among individuals with least-cost path (LCP) modelling helps to correlate indirect measures of gene flow with landscape connectivity. Applicability of LCP modelling, however, is reduced if knowledge on dispersal pathways or routes is lacking. Therefore, we integrated habitat suitability modelling into LCP analysis to avoid the subjectivity common in LCP analyses lacking knowledge on dispersal pathways or routes. We used presence-only data and ecological niche factor analysis to model habitat suitability for the spiny rat, Niviventer coninga, in a fragmented landscape of western Taiwan. We adapted the resultant habitat suitability map for incorporation into LCP analyses. Slightly increased Mantel correlations indicated that a class-weighted suitability map better explained genetic distances among individuals than did geographical distances. The integration of habitat suitability modelling into LCP analysis can thus generate information on distribution of suitable habitats, on potential routes of dispersal, for placement of corridors, and evaluate landscape connectivity.!://WOS:000259481900009Times Cited: 0 0921-2973WOS:00025948190000910.1007/s10980-008-9262-3 |7Ward, D. P. Kutt, A. S.2009Rangeland biodiversity assessment using fine scale on-ground survey, time series of remotely sensed ground cover and climate data: an Australian savanna case study495-507Landscape Ecology244species diversity rangelands disturbance ecological indicators condition spider assemblages northern australia grazing gradients vegetation cover land-use trends patterns rainfall fire heterogeneityAprSavanna rangelands are undergoing rapid environmental change and the need to monitor and manage landscape health is becoming increasingly an imperative of government agencies and research organizations. Remotely sensed ecological indicators of disturbance offer a potential approach, particularly in the context of issues of scale required to assess and monitor extensive rangeland areas. The objective of this research is to analyse the potential of spatially explicit ecological indicators of disturbance to explain the spatial variability in species diversity and abundance (including introduced flora species) in rangelands. For two mapped rangeland ecosystem types in northern Australia, regression analysis was used to explore the relationships between species diversity and abundance, and remotely sensed ground cover time series statistics, foliage projective cover, and a precipitation deficit index. It was assumed that the ecosystem types used had been mapped to represent uniform vegetation units and consequently predictors of environmental heterogeneity were not used in the regression analysis. It was found that the predictor variables performed well in explaining the variation in species diversity and abundance for the more open, homogenous and less topographically complex basalt ecosystem type and less effectively for the more structurally complex, more wooded and less disturbed metamorphic ecosystem type. The results indicate that, for mapped ecosystem types with low heterogeneity and topographic complexity, ground cover temporal mean and variance are potentially useful indicators of disturbance to species diversity and abundance, provided the local spatial variability in the climate signal is accounted for.://000263898100005-414XI Times Cited:1 Cited References Count:64 0921-2973ISI:000263898100005Ward, Dp Griffith Univ, Australian Rivers Inst, Nathan, Qld 4111, Australia Griffith Univ, Australian Rivers Inst, Nathan, Qld 4111, Australia CSIRO Sustainable Ecosyst Rangelands & Savannas, Davies Lab, Aitkenvale, Qld 4814, AustraliaDoi 10.1007/S10980-009-9324-1English ?+J. V. Ward Florian, Malard Klement, Tockner2002ULandscape ecology: a framework for integrating pattern and process in river corridors35-45Landscape Ecology170Biodiversity hierarchy - Connectivity - Disturbance - Expansion/contraction cycle - Flood plains - Island dynamics - Restoration - River corridors - Riverine landscapesInvestigations of European floodplain rivers demonstrate how landscape ecology can provide an effective framework to integrate pattern and process in river corridors, to examine environmental dynamics and interactive pathways between landscape elements, and to develop viable strategies for river conservation. The highly complex and dynamic nature of intact river corridors is particularly amenable to a landscape ecology perspective. Analysis of spatial patterns has provided considerable insight into environmental heterogeneity across river corridors and is an essential prelude to examining dynamic interactions. For example, data from aerial photographs, digitized maps and year-round field measurements in a glacial flood plain, enabled us to distinguish six channel types, based on the correspondence between connectivity and physicochemical attributes. Spatial data were also used to analyze longitudinal changes in landscape elements along the course of a morphologically-intact riverine corridor, providing insight into the structural complexity that must have characterized many Alpine rivers in the pristine state. Landscape indices were employed to investigate seasonal dynamics in a glacial flood plain of the Swiss Alps which exhibits a predictable expansion/contraction cycle, with corresponding shifts in flow paths (surface and subsurface) and water sources (snowmelt, englacial, subglacial, alluvial aquifer, hillslope aquifer). Surface connectivity exhibited an unexpected biphasic relationship with total channel length, whereas riverscape diversity progressively increased along the entire range of channel length. Reconstituting the functional integrity that characterizes intact river corridors should perhaps be the major goal of river conservation initiatives. Although understanding functional processes at the landscape scale is essential in this regard, few data are available. In the Alluvial Zone National Park on the Austrian Danube, three phases of hydrological connectivity were identified (disconnection, seepage connection and surface connection) that corresponded to the predominance of three functional processes (biotic interactions, primary production and particulate transport) within the river corridor. *http://dx.doi.org/10.1023/A:1015277626224 10.1023/A:1015277626224 Klement Tockner Email: tockner@eawag.ch Phone: 41-1-823 5315 References Amoros C. and Petts G.E. (eds) 1993. Hydrosystemes Fluviaux. Masson, Paris, France. Arscott D.B., Tockner K. and Ward J.V. 2000. Aquatic habitat structure and diversity along the corridor of an Alpine floodplain river (The Fiume Tagliamento). Archiv für Hydrobiologie 149: 679-704. Decamps H. 1984. Towards a landscape ecology of river valleys. In: J.H. Cooley and F.B. Golley (eds), Trends in Ecological Research for the 1980s, Plenum, New York, NY, USA, pp. 163-178. Edwards P.J., Kollmann J., Gurnell A.M., Petts G.E., Tockner K. and Ward J.V. 1999. A conceptual model of vegetation dynamics on gravel bars of a large Alpine river. Wetlands Ecol. Manag. 7: 141-153. Forman R.T.T. and Godron M. 1981. Patches and structural components for a landscape ecology. BioSci. 31: 733-740. Gustafson E.J. 1998. Quantifying landscape spatial patterns: What is the state of the art? Ecosyst. 1: 143-156. Gurnell A.M., Petts G.E., Hannah D.M., Smith B.P.G., Edwards P.J., Kollmann J., Ward J.V. and Tockner K. 2001. Riparian vegetation and island formation along the gravel-bed Fiume Tagliamento, Italy. Earth Surface Processes and Landforms 26: 31-62. Johnson W.C. 1994. Woodland expansion in the Platte River, Nebraska, Patterns and causes. Ecol. Monogr. 64: 45-84. Klein B. and Tockner K. 2000. Biodiversity in springbrooks of a glacial flood plain (Val Roseg, Switzerland). Verhandlungen der Internationalen Vereinigung für Theoretische und Angewandte Limnologie 27: 704-711. Kollmann J., Vieli M., Edwards P.J., Tockner K. and Ward J.V. 1999. Interactions between vegetation development and island formation in the Alpine river Tagliamento. Appl. Veget. Sci. 2: 25-36. Malard F., Tockner K. and Ward J.V. 1999. Shifting dominance of subcatchment water sources and flow paths in a glacial floodplain, Val Roseg, Switzerland. Arct. Antarct. Alp. Res. 31: 135-150. Malard F., Tockner K. and Ward J.V. 2000. Physico-chemical heterogeneity in a glacial riverscape. Landsc. Ecol. 15: 679-695. Osterkamp W.R. 1998. Processes of fluvial island formation, with examples from Plum Creek, Colorado and Snake River, Idaho. Wetlands 18: 530-545. Petts G.E., Moller H. and Roux A.L. (eds) 1989. Historical changes of Large Alluvial Rivers, Western Europe, Wiley, Chichester, UK. Schiemer F., Baumgartner C. and Tockner K. 1999. Restoration of floodplain rivers: 'The Danube Restoration Project'. Regul. Riv. Res. Manag. 15: 231-244. Schumm S.A. 1985. Patterns of alluvial rivers. Ann. Rev. Earth Planet. Sci. 13: 5-27. Stanford J.A., Ward J.V., Liss W.J., Frissell C.A., Williams R.N., Lichatowich J.A. and Coutant C.C. 1996. A general protocol for restoration of regulated rivers. Regul. Riv. Res. Manag. 12: 391-413. Tockner K., Malard F., Burgherr P., Robinson C.T., Uehlinger U., Zah R. and Ward J.V. 1997. Physico-chemical characterization of channel types in a glacial floodplain ecosystem (Val Roseg, Switzerland). Archiv für Hydrobiologie 140: 433-463. Tockner K., Schiemer F. and Ward J.V. 1998. Conservation by restoration: The management concept for a river-floodplain system on the Danube River, Austria. Aquat. Conserv. 8: 71-86. Tockner K., Pennetzdorfer D., Reiner N., Schiemer F. and Ward J.V. 1999. Hydrological connectivity and the exchange of organic matter and nutrients in a dynamic river-floodplain system (Danube, Austria). Freshwater Biol. 41: 521-535. Tockner K., Ward J.V., Arscott D.B., Edwards P.J., Kollmann J., Gurnell A.M., Petts G.E. andMaiolini B. The Tagliamento River: A model ecosystem for Alpine gravel-bed rivers. In: H. Plachter and M. Reich (eds), Ecology and Conservation of Gravel Bed Rivers and Alluvial Floodplains in the Alps. Springer, Berlin, Germany (in press). Tockner K., Malard F. and Ward J.V. 2000. An extension of the flood pulse concept. Hydrol. Proc. 14, 2861-2883. Turner M.G. and Gardner R.H. 1991. Quantitative methods in landscape ecology: An introduction. In: M.G. Turner and R.H. Gardner (eds), Quantitative methods in landscape ecology, Springer Verlag, New York, NY, USA, pp. 3-14. Ward J.V. 1997. An expansive perspective of riverine landscapes: Pattern and process across scales. GAIA 6: 52-60. Ward J.V. 1998. Riverine landscapes: Biodiversity patterns, disturbance regimes, and aquatic conservation. Biol. Conserv. 83: 269-278. Ward J.V., Malard F., Tockner K. and Uehlinger U. 1999a. Influence of ground water on surface water conditions in a glacial flood plain of the Swiss Alps. Hydrol. Process. 13: 277-293. Ward J.V., Tockner K., Edwards P.J., Kollmann J., Bretschko G., Gurnell A.M., Petts G.E. and Rossaro B. 1999b. A reference river system for the Alps: The Fiume Tagliamento. Regul. Riv. Res. Manag. 15: 63-75. Ward J.V., Tockner K. and Schiemer F. 1999c. Biodiversity of floodplain river ecosystems: Ecotones and connectivity. Regul. Riv. Res. Manag. 15: 125-139. Ward J.V., Tockner K., Edwards P.J., Kollmann J., Bretschko G., Gurnell A.M., Petts G.E. and Rossaro B. 2000. Potential role of island dynamics in river ecosystems. Verhandlungen der Internationalen Vereinigung für Theoretische und Angewandte Limnologie 27: 2582-2585. Wiens J.A. 1995. Landscape mosaics and ecological theory. In: L. Hansson, L. Fahrig and G. Merriam (eds), Mosaic Landscapes and Ecological Processes, Chapman & Hall, London, UK, pp. 1-26. J. V. Ward1, Florian Malard2 and Klement Tockner1 (1) Department of Limnology, EAWAG/ETH, Überlandstrasse 133, 8600 Dübendorf, Switzerland (2) Present address: UMR CNRS 5023, Université Claude Bernard, Lyon 1, 69622 Villeurbanne Cedex, France <7"Ward, J. V. Malard, F. Tockner, K.2001ULandscape ecology: a framework for integrating pattern and process in river corridors35-45Landscape Ecology17 Supplement 1biodiversity hierarchy connectivity disturbance ezpansion/contraction cycle flood plains island dynamics restoration river corridors riverine landscapes FIUME-TAGLIAMENTO GLACIAL FLOODPLAIN ISLAND FORMATION RESTORATION DANUBE SYSTEM CONSERVATION CONNECTIVITY BIODIVERSITY SWITZERLANDArticleInvestigations of European floodplain rivers demonstrate how landscape ecology can provide an effective framework to integrate pattern and process in river corridors, to examine environmental dynamics and interactive pathways between landscape elements, and to develop viable strategies for river conservation. The highly complex and dynamic nature of intact river corridors is particularly amenable to a landscape ecology perspective. Analysis of spatial patterns has provided considerable insight into environmental heterogeneity across river corridors and is an essential prelude to examining dynamic interactions. For example, data from aerial photographs, digitized maps and year-round field measurements in a glacial flood plain, enabled us to distinguish six channel types, based on the correspondence between connectivity and physicochemical attributes. Spatial data were also used to analyze longitudinal changes in landscape elements along the course of a morphologically-intact riverine corridor, providing insight into the structural complexity that must have characterized many Alpine rivers in the pristine state. Landscape indices were employed to investigate seasonal dynamics in a glacial flood plain of the Swiss Alps which exhibits a predictable expansion/contraction cycle, with corresponding shifts in flow paths (surface and subsurface) and water sources (snowmelt, englacial, subglacial, alluvial aquifer, hillslope aquifer). Surface connectivity exhibited an unexpected biphasic relationship with total channel length, whereas riverscape diversity progressively increased along the entire range of channel length. Reconstituting the functional integrity that characterizes intact river corridors should perhaps be the major goal of river conservation initiatives. Although understanding functional processes at the landscape scale is essential in this regard, few data are available. In the Alluvial Zone National Park on the Austrian Danube, three phases of hydrological connectivity were identified (disconnection, seepage connection and surface connection) that corresponded to the predominance of three functional processes (biotic interactions, primary production and particulate transport) within the river corridor.://000176041000004 ISI Document Delivery No.: 559TG Times Cited: 15 Cited Reference Count: 30 Cited References: AMOROS C, 1993, HYDROSYSTEMES FLUVIA ARSCOTT DB, 2000, ARCH HYDROBIOL, V149, P679 DECAMPS H, 1984, TRENDS ECOLOGICAL RE, P163 EDWARDS PJ, 1999, WETLANDS ECOLOGY MAN, V7, P141 FORMAN RTT, 1981, BIOSCIENCE, V31, P733 GURNELL AM, 2001, EARTH SURF PROC LAND, V26, P31 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 JOHNSON WC, 1994, ECOL MONOGR, V64, P45 KLEIN B, 2000, VERHANDLUNGEN INT VE, V27, P704 KOLLMANN J, 1999, APPL VEG SCI, V2, P25 MALARD F, 1999, ARCT ANTARCT ALP RES, V31, P135 MALARD F, 2000, LANDSCAPE ECOL, V15, P679 OSTERKAMP WR, 1998, WETLANDS, V18, P530 PETTS GE, 1989, HIST CHANGES LARGE A SCHIEMER F, 1999, REGUL RIVER, V15, P231 SCHUMM SA, 1985, ANNU REV EARTH PL SC, V13, P5 STANFORD JA, 1996, REGUL RIVER, V12, P391 TOCKNER K, IN PRESS ECOLOGY CON TOCKNER K, 1997, ARCH HYDROBIOL, V140, P433 TOCKNER K, 1998, AQUAT CONSERV, V8, P71 TOCKNER K, 1999, FRESHWATER BIOL, V41, P521 TOCKNER K, 2000, HYDROL PROCESS, V14, P2861 TURNER MG, 1991, QUANTITATIVE METHODS, P3 WARD JV, 1997, GAIA, V6, P52 WARD JV, 1998, BIOL CONSERV, V83, P269 WARD JV, 1999, HYDROL PROCESS, V13, P277 WARD JV, 1999, REGUL RIVER, V15, P125 WARD JV, 1999, REGUL RIVER, V15, P63 WARD JV, 2000, VERHANDLUNGEN INT VE, V27, P2582 WIENS JA, 1995, MOSAIC LANDSCAPES EC, P1 Suppl. 1 0921-2973 Landsc. Ecol.ISI:000176041000004ETH, EAWAG, Dept Limnol, CH-8600 Dubendorf, Switzerland. Tockner, K, ETH, EAWAG, Dept Limnol, Uberlandstr 133, CH-8600 Dubendorf, Switzerland. tockner@eawag.chEnglish|7Warman, L. Moles, A. T.2009Alternative stable states in Australia's Wet Tropics: a theoretical framework for the field data and a field-case for the theory1-13Landscape Ecology241resilience bistability rainforest sclerophyll fire positive feedbacks management north-eastern australia dominated woodland savanna rain-forest contractions kakadu-national-park northeastern queensland climate-change positive feedbacks african savanna regime shifts humid tropicsJanLThe vegetation of the Wet Tropics bioregion of Far North Queensland is a complex system whose components (mainly tropical rainforests and fire-prone forests and woodlands) have mostly been studied independently from each other. We suggest that many characteristics of the vegetation are consistent with those of a complex, dynamic, spatially heterogeneous system which exhibits alternative stable states. We propose these states are driven and maintained by the interaction of vegetation-specific positive feedback loops with the regions' environmental parameters (such as topography, steep humidity gradients and seasonality) and result in the rainforest/fire-prone vegetation mosaic that characterises the area. Given the regions' magnitude, biodiversity and complexity, we propose the Wet Tropics as an important new example and a good testing ground for alternative stable state and resilience theories in large heterogeneous natural systems. At the same time, thinking in terms of alternative stable states and resilience creates a new context for understanding the regions' biological dynamics.://000262506000001-395EI Times Cited:0 Cited References Count:73 0921-2973ISI:000262506000001Warman, L Univ New S Wales, Evolut & Ecol Res Ctr, Sch Biol Earth & Environm Sci, Sydney, NSW 2052, Australia Victoria Univ Wellington, Sch Biol Sci, Wellington, New ZealandDoi 10.1007/S10980-008-9285-9EnglishA?<(L. Wartena J.H. van Boxel D. Veenhuysen1991KMacroclimate, microclimate and dune formation along the West European coast15-27Landscape Ecology51/2kClimate, microclimate, energy balance, dunes, dune formation, wind, temperature, precipitation, evaporationExtremely important to the climate in any region are the radiation balance and the exchange processes of heat, water vapour and momentum. Most climatological parameters (e.g. temperature, humidity, wind speed, cloudiness and precipitation) are the direct or indirect result of the radiation balance and these exchange processes. The weather of the West European coast from Tarifa (Spain) to Skagen (Denmark) is especially suitable for the formation of dunes. Often a wind is blowing, varying widely in force and direction. The conditions are optimal for the formation of high and wide dune complexes, given a large supply of sand by the sea. The annual precipitation surplus is considerable for most of this coast. This favours the establishment of vegetation, and thereby it enhances dune formation. The short distance to the land-sea border causes strong gradients in several climatological parameters. These gradients lead to mesoscale effects, such as land-sea breezes and coastal fronts. The varying vegetation cover and the presence of slopes in all directions induce a strongly varying microclimate. However, this microclimate is not unique to the coastal dunes. Unique is the interaction with the wide range of ambient weather, which is inherent to the coast. It is not possible to be conclusive about the effects of climatic change on coastal dunes because climate models are not yet able to predict the changes adequately and because these models supply information on the expected mean climate, but not on the actual weather.?*Wartena,L. J. H. van Boxel D. Veenhuysen. 1991KMacroclimate, microclimate and dune formation along the West European coast15-27Landscape Ecology61/2fclimATE,microclimate,energy balance, dunes,dune formation, wind, temperature,precipitation,evaporationڽ7 KWassen, MartinJ Boer, HugoJ Fleischer, Katrin Rebel, KarinT Dekker, StefanC2013MVegetation-mediated feedback in water, carbon, nitrogen and phosphorus cycles599-614Landscape Ecology284Springer NetherlandsjCarbon Nitrogen Phosphorus Nutrients Stomata Global climate change Plants Water Ecosystem Feedbacks Scales 2013/04/01+http://dx.doi.org/10.1007/s10980-012-9843-z 0921-2973Landscape Ecol10.1007/s10980-012-9843-zEnglish?/?Martin J. Wassen Aat Barendregt Paul P. Schot Boudewijn Beltman1990wDependency of local mesotrophic fens on a regional groundwater flow system in a poldered river plain in the Netherlands21-38Landscape Ecology51Scalcium-saturation, fens, groundwater flow system, hydrology, restoration, zonationThe effect of regional, subregional and local groundwater flow systems on mesotrophic fen ecosystems was studied in the polders of the Vecht River plain that borders the Pleistocene ice-pushed moraine of Het Gooi. Variation in the vegetation and in the habitat factors (groundwater and peat soil) of fens depends whether or not the fens are connected to the outflow of the regional groundwater system. Changes in the regional groundwater flow system, caused by changes in the water management of the polders, are probably responsible for the deterioration of mesotrophic fens. Drastic measures will have to be taken to restore the hydrology on a regional scale if the mesotrophic fens are to be saved from extinction. Hydrological research that integrates the results of regional and local studies is essential if the ecology of fen ecosystems is to be understood.W|? NWasserman, Tzeidle N. Cushman, Samuel A. Schwartz, Michael K. Wallin, David O.2010cSpatial scaling and multi-model inference in landscape genetics: Martes americana in northern Idaho 1601-1612Landscape Ecology2510DecIndividual-based analyses relating landscape structure to genetic distances across complex landscapes enable rigorous evaluation of multiple alternative hypotheses linking landscape structure to gene flow. We utilize two extensions to increase the rigor of the individual-based causal modeling approach to inferring relationships between landscape patterns and gene flow processes. First, we add a univariate scaling analysis to ensure that each landscape variable is represented in the functional form that represents the optimal scale of its association with gene flow. Second, we use a two-step form of the causal modeling approach to integrate model selection with null hypothesis testing in individual-based landscape genetic analysis. This series of causal modeling indicated that gene flow in American marten in northern Idaho was primarily related to elevation, and that alternative hypotheses involving isolation by distance, geographical barriers, effects of canopy closure, roads, tree size class and an empirical habitat model were not supported. Gene flow in the Northern Idaho American marten population is therefore driven by a gradient of landscape resistance that is a function of elevation, with minimum resistance to gene flow at 1500 m.!://WOS:000283371000011Times Cited: 1 0921-2973WOS:00028337100001110.1007/s10980-010-9525-7 <7 KWasserman, T. N. Cushman, S. A. Shirk, A. S. Landguth, E. L. Littell, J. S.2012Simulating the effects of climate change on population connectivity of American marten (Martes americana) in the northern Rocky Mountains, USA211-225Landscape Ecology272habitat fragmentation gene flow climate change american marten martes americana connectivity landscape genetics landscape genetics united-states inbreeding depression species distributions wild populations extinction dispersal inference habitat forestsFeb8We utilize empirically derived estimates of landscape resistance to assess current landscape connectivity of American marten (Martes americana) in the northern Rocky Mountains, USA, and project how a warming climate may affect landscape resistance and population connectivity in the future. We evaluate the influences of five potential future temperature scenarios involving different degrees of warming. We use resistant kernel dispersal models to assess population connectivity based on full occupancy of suitable habitat in each of these hypothetical future resistance layers. We use the CDPOP model to simulate gene exchange among individual martens in each of these hypothetical future climates. We evaluate: (1) changes in the extent, connectivity and pattern of marten habitat, (2) changes in allelic richness and expected heterozygosity, and (3) changes in the range of significant positive genetic correlation within the northern Idaho marten population under each future scenario. We found that even moderate warming scenarios resulted in very large reductions in population connectivity. Calculation of genetic correlograms for each scenario indicates that climate driven changes in landscape connectivity results in decreasing range of genetic correlation, indicating more isolated and smaller genetic neighborhoods. These, in turn, resulted in substantial loss of allelic richness and reductions in expected heterozygosity. In the U. S. northern Rocky Mountains, climate change may extensively fragment marten populations to a degree that strongly reduces genetic diversity. Our results demonstrate that for species, such as the American marten, whose population connectivity is highly tied to climatic gradients, expected climate change can result in profound changes in the extent, pattern, connectivity and gene flow of populations.://0003000887000069Sp. Iss. SI 889QQ Times Cited:2 Cited References Count:43 0921-2973Landscape EcolISI:000300088700006Cushman, SA US Forest Serv, Rocky Mt Res Stn, 2500 S Pine Knoll Dr, Flagstaff, AZ 86001 USA US Forest Serv, Rocky Mt Res Stn, 2500 S Pine Knoll Dr, Flagstaff, AZ 86001 USA US Forest Serv, Rocky Mt Res Stn, Flagstaff, AZ 86001 USA No Arizona Univ, Sch Forestry, Flagstaff, AZ 86001 USA Univ Washington, Climate Impacts Grp, Ctr Earth Syst Sci, Seattle, WA 98195 USA Univ Montana, Div Biol Sci, Missoula, MT 59812 USADOI 10.1007/s10980-011-9653-8English|? Watling, J. I. Orrock, J. L.2010kMeasuring edge contrast using biotic criteria helps define edge effects on the density of an invasive plant69-78Landscape Ecology251Habitat edges can alter population dynamics, influence community structure, determine the success of conservation efforts, and facilitate the spread of invasive species. Despite recognition that edges influence the nature and strength of ecological interactions, edges are generally characterized using abiotic measures that likely capture habitat quality for only the focal taxa, and ignore the potential for biotic interactions to explain edge effects. Here we describe the association between edges and the density of an invasive shrub, Lonicera maackii, and infer the functional role of edges by using multiple criteria to weight edge contrast. We define edge contrast using both an abiotic criterion in which contrast is weighted by differences in light availability, and a biotic criterion in which edge contrast is weighted by the association between edges and the abundance of the American Robin (Turdus migratorius), an important avian seed disperser. Biotically defining edge contrast significantly improved model fit in all cases, demonstrating that the large-scale distribution of an invasive shrub is best predicted using both abiotic and biotic edge characterization. More generally, our work suggests that weighting edge contrast using key biological interactions in addition to abiotic criteria may be a promising way to understand the multiple pathways by which edges influence the distribution and abundance of organisms.!://WOS:000273479100006Times Cited: 0 0921-2973WOS:00027347910000610.1007/s10980-009-9416-y|?AWatson, Simon J. Watson, David M. Luck, Gary W. Spooner, Peter G.2014xEffects of landscape composition and connectivity on the distribution of an endangered parrot in agricultural landscapes 1249-1259Landscape Ecology297AugeThe extent and connectivity of individual habitat types strongly affects the distribution and abundance of organisms. However, little is known of how the level of connectivity and the interactions between different habitat types influences the distribution of species. Here, we used the geographically restricted and endangered regent parrot Polytelis anthopeplus monarchoides as a case study to examine the importance of composition and connectivity between different elements in 39 complex landscape mosaics (each 10 km radius). We compiled a database of 674 regent parrot nesting records, regional vegetation maps and measures of multipath connectivity between core vegetation types under different scenarios of resistance to movement provided by landscape elements. The occurrence of regent parrot nests was strongly affected by landscape composition, being positively related to the extent Eucalyptus camaldulensis riverine forest, but negatively related to the extent of semi-arid woodlands dominated by Eucalyptus largiflorens. Connectivity between E. camaldulensis forest (principal nesting habitat) and mallee (preferred feeding habitat) was a strong predictor of nest locations. Our study shows that the suitability of fragmented agricultural landscapes for supporting species can be greatly affected by connectivity and interactions between preferred and non-preferred habitats. For species that require complementary habitats such as the regent parrot, conservation management activities may be ineffective if they simply focus on a single core habitat type or the impacts of human land uses without regard to the interrelationships among landscape elements. While increasing the amount of primary preferred habitat should remain a cornerstone goal, increasing the extent and improving connectivity with alternative landscape elements also should be priority management objectives.!://WOS:000339831300013Times Cited: 0 0921-2973WOS:00033983130001310.1007/s10980-014-0065-4 $|? dWatts, Kevin Eycott, Amy E. Handley, Phillip Ray, Duncan Humphrey, Jonathan W. Quine, Christopher P.2010Targeting and evaluating biodiversity conservation action within fragmented landscapes: an approach based on generic focal species and least-cost networks 1305-1318Landscape Ecology259NoviThe focus of biodiversity conservation is shifting to larger spatial scales in response to habitat fragmentation and the need to integrate multiple landscape objectives. Conservation strategies increasingly incorporate measures to combat fragmentation such as ecological networks. These are often based on assessment of landscape structure but such approaches fail to capitalise on the potential offered by more ecologically robust assessments of landscape function and connectivity. In this paper, we describe a modelling approach to identifying functional habitat networks and demonstrate its application to a fragmented landscape where policy initiatives seek to improve conditions for woodland biodiversity including increasing woodland cover. Functional habitat networks were defined by identifying suitable habitat and by modelling connectivity using least-cost approaches to account for matrix permeability. Generic focal species (GFS) profiles were developed, in consultation with stakeholders, to represent species with high and moderate sensitivity to fragmentation. We demonstrated how this form of analysis can be used to aid the spatial targeting of conservation actions. This 'targeted' action scenario was tested for effectiveness against comparable scenarios, which were based on random and clumped actions within the same landscape. We tested effectiveness using structural metrics, network-based metrics and a published functional connectivity indicator. Targeting actions within networks resulted in the highest mean woodland area and highest connectivity indicator value. Our approach provides an assessment of landscape function by recognising the importance of the landscape matrix. It provides a framework for the targeting and evaluation of alternative conservation options, offering a pragmatic, ecologically-robust solution to a current need in applied landscape ecology.!://WOS:000281981000001Times Cited: 1 0921-2973WOS:00028198100000110.1007/s10980-010-9507-9h? 4Weaver, Jennifer Conway, Tenley Fortin, Marie-Josée2012gAn invasive species’ relationship with environmental variables changes across multiple spatial scales 1351-1362Landscape Ecology279Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9786-4 0921-297310.1007/s10980-012-9786-4<7Weaver, K. Perera, A. H.2004YModelling land cover transitions: A solution to the problem of spatial dependence in data273-289Landscape Ecology193fragmentation; regions; stochastic; spatial bias; vegetation transition CELLULAR-AUTOMATON MODEL; VEGETATION DYNAMICS; LANDSCAPE PATTERN; BOREAL FOREST; DISTURBANCE; COMPETITION; SIMULATION; SUCCESSION; DISPERSAL; ENVIRONMENTSArticleRaster-based spatial land cover transition models (LCTMs) are widely used in landscape ecology. However, many LCTMs do not account for spatial dependence of the input data, which may artificially fragment the output spatial configuration. We demonstrate the consequences of ignoring spatial dependence, thus assigning probabilities randomly in space, using a simple LCTM. We ran the model from four different initial conditions with distinct spatial configurations and results indicated that, after 20 simulation steps, all of them converged towards the spatial configuration of the random data set. From an ecological perspective this is a serious problem because ecological data often exhibit distinct spatial configuration related to ecological processes. As a solution, we propose an approach (region approach) that accounts for spatial dependence of LCTM input data. Underlying spatial dependence was used to apply spatial bias to probability assignment within the model. As a case study we applied a region approach to a Vegetation Transition Model (VTM); a semi-Markovian model that simulates forest succession. The VTM was applied to approximately 500,000 ha of boreal forest in Ontario, at 1 ha pixel resolution. When the stochastic transition algorithms were applied without accounting for spatial dependence, spatial configuration of the output data became progressively more fragmented. When the VTM was applied using the region approach to account for spatial dependence output fragmentation was reduced. Accounting for spatial dependence in transition models will create more reliable output for analyzing spatial patterns and relating those patterns to ecological processes.://000221878900004 K ISI Document Delivery No.: 827DL Times Cited: 1 Cited Reference Count: 61 Cited References: *ESRI, 1998, ARCINFO WIND VERS 7 *NRC, 2000, CAN DIG EL DAT STAND *OMNR, 1977, READ REF ONT LAND IN *TEX A M U TAES, 2001, BLACKL GRASS 2 0 ACEVEDO MF, 1996, ECOL MODEL, V87, P267 ADDICOTT JF, 1987, OIKOS, V49, P340 ANSELIN L, 1996, SPATIAL ANAL PERSPEC, P111 BAKER WL, 1989, LANDSCAPE ECOL, V2, P111 BAKER WL, 1992, LANDSCAPE ECOL, V7, P291 BALDWIN DJB, 2001, 150 ONT FOR RES I ON BALZTER H, 1998, ECOL MODEL, V107, P113 BARRINGER TH, 1981, P 15 INT S REM SENS, P125 BELL EJ, 1977, SOCIOECONOMIC PLANNI, V11, P13 BONAN GB, 1989, ANNU REV ECOL SYST, V20, P1 BROWN DG, 2000, J ENVIRON MANAGE, V59, P247 CLIFF AD, 1973, SPATIAL AUTOCORRELAT DEUTSCHMAN DH, 1993, PATCH DYNAMICS, P184 DING YM, 1992, COMPUT ENVIRON URBAN, V16, P3 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FOX JC, 2000, FOREST ECOL MANAG, V154, P261 FRELICH LE, 1999, ECOSYSTEMS, V2, P151 GARDNER RH, 1999, LANDSCAPE ECOLOGICAL, P280 GREEN DG, 1989, VEGETATIO, V82, P139 GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HARVEY BD, 1995, CAN J FOREST RES, V25, P1658 HE HS, 1999, ECOLOGY, V80, P81 HE HS, 2000, LANDSCAPE ECOL, V15, P591 HUNSAKER CT, 2001, SPATIAL UNCERTAINTY JENERETTE GD, 2001, LANDSCAPE ECOL, V16, P611 LEVIN SA, 1976, ANNU REV ECOL SYST, V7, P287 LI H, 1997, SCALE REMOTE SENSING, P211 LI HB, 1994, ECOLOGY, V75, P2446 MATSINOS YG, 2002, ECOL MODEL, V149, P71 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MOLOFSKY J, 2001, P ROY SOC LOND B BIO, V268, P273 MOORE AD, 1990, J ENVIRON MANAGE, V30, P111 MORAN PAP, 1950, BIOMETRIKA, V37, P17 MULLER MR, 1994, LANDSCAPE ECOL, V9, P151 ONEILL RV, 1996, LANDSCAPE ECOL, V11, P169 PERERA AH, 1997, 146 ONT FOR RES I FO PERERA AH, 2003, 152 ONT FOR RES I ON PRACH K, 1993, OIKOS, V66, P343 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 ROSSI RE, 1992, ECOL MONOGR, V62, P277 ROWE JS, 1972, PUBLICATION CANADIAN, V1300 SILVERTOWN J, 1992, J ECOL, V80, P527 SIRAKOULIS GC, 2000, ECOL MODEL, V133, P209 SKLAR FH, 1991, QUANTITATIVE METHODS, P239 STOCKS CE, 2000, GEOGRAPHICAL ENV MOD, V4, P219 SVENNING JC, 2002, PLANT ECOL, V160, P169 TRUDELL A, 1996, FOREST RESOURCE INVE TURNER MG, 1987, LANDSCAPE ECOL, V1, P29 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 WEAVER K, 2002, THESIS U TORONTO DEP WIENS JA, 1976, ANNU REV ECOL SYST, V7, P81 WISSEL C, 1992, ECOL MODEL, V63, P29 WOLFRAM S, 1984, NATURE, V311, P419 WOLOCK DM, 1995, WATER RESOUR RES, V31, P1315 YEMSHANOV D, 2002, ECOL MODEL, V150, P189 0921-2973 Landsc. Ecol.ISI:000221878900004-Ontario Minist Nat Resources, Ontario Forest Res Inst, Forest Landscape Ecol Program, Sault Ste Marie, ON P6A 2E5, Canada. Perera, AH, Ontario Minist Nat Resources, Ontario Forest Res Inst, Forest Landscape Ecol Program, 1235 Queen St E, Sault Ste Marie, ON P6A 2E5, Canada. ajith.perera@mnr.gov.on.caEnglishT<7#Weir, J. E. S. Corlett, R. T.2007WHow far do birds disperse seeds in the degraded tropical landscape of Hong Kong, China?131-140Landscape Ecology221bulbuls; dispersal distance; frugivory; Garrulax; global warming; habitat fragmentation; landscape connectivity; pycnonotidae; seed shadows MONTANE FOREST; PATTERNS; TREE; FRAGMENTATION; CONSEQUENCES; MIGRATION; MOVEMENT; TRACKING; DISTANCE; BEHAVIORArticleJanInformation on seed dispersal distances is critical for understanding plant species persistence in habitat fragments and vegetation recovery when disturbance is reduced. In the degraded upland landscape of Hong Kong (22 degrees N), the bulbuls Pycnonotus sinensis and P. jocosus are responsible for a large proportion of seed movements. Dispersal distances were estimated from gut passage times (GPTs) and movement patterns determined by radio-telemetry. Estimates were also made for the hwamei, Garrulax canorus. Seven adult P. sinensis and four adult G. canorus were tracked in winter, and six juvenile P. sinensis, three juvenile P. jocosus and two juvenile G. canorus in summer. GPTs were 5-122 min in the bulbuls and 18-61 min in the hwamei. Most 10min movements were < 100 m for the bulbuls and < 50 m for the hwamei, but the largest were > 1300 m for both bulbuls and 940 m for the hwamei. Displacement-time graphs generally levelled off rapidly, with median displacements < 60 m after an hour, except with summer juvenile bulbuls. Median displacements during median gut passage times for seeds from single-seeded fruits were 40, 116 and 131 m, respectively, for winter adult P. sinensis and summer juvenile P. sinensis and P. jocosus. Maximum observed displacements during the maximum measured GPTs were > 1 km for all bulbuls. Estimated dispersal distances were shorter for hwameis. The radio-telemetry results were supplemented by 49 h of visual observations, during which 1,510 bird movements across open areas were observed, 64% by P. sinensis, 13% by P. jocosus, and 0.5% by G. canorus. The bulbuls, therefore, connect habitat fragments in upland Hong Kong for plants with fruits within their maximum gape width.://000243619800012 ISI Document Delivery No.: 127XO Times Cited: 0 Cited Reference Count: 42 Cited References: AU AYY, 2006, PLANT ECOL CORLETT RT, 1996, J TROP ECOL 6, V12, P819 CORLETT RT, 1998, FORKTAIL, V13, P23 CORLETT RT, 2002, SEED DISPERSAL FRUGI, P451 DUDGEON D, 2004, ECOLOGY BIODIVERSITY FUKUI A, 2003, ORNITHOLOGICAL SCI, V2, P41 FUKUI AW, 1995, RES POPUL ECOL, V37, P211 GODOY JA, 2001, MOL ECOL, V10, P2275 GRAHAM CH, 1995, BIOTROPICA, V27, P479 HEWITT N, 2002, J BIOGEOGR, V29, P337 HIGGINS SI, 2003, OIKOS, V101, P354 HOLBROOK KM, 2000, OECOLOGIA, V125, P249 HOUGHTON J, 2005, REP PROG PHYS, V68, P1343 HOWE HF, 2004, BIOSCIENCE, V54, P651 ISLER ML, 1999, TANAGERS NATURAL HIS IZHAKI I, 1992, CONDOR, V94, P912 JOHST K, 2002, OIKOS, V98, P263 KEITH S, 1992, BIRDS AFRICA, V4, P279 KO IWP, 1999, THESIS U HONG KONG H LEUNG YK, 2004, HONG KONG METEOROL S, V14, P21 LEVEN MR, 2000, THESIS U HONG KONG H LEVEY DJ, 2000, ECOLOGY, V81, P267 LEVIN SA, 2003, ANNU REV ECOL EVOL S, V34, P575 LEVINE JM, 2003, ANNU REV ECOL EVOL S, V34, P549 MAHLI Y, 2004, PHILOS T R SOC LON B, V359, P311 MANDONDALGER I, 2004, J TROP ECOL 6, V20, P635 NATHAN R, 2000, TRENDS ECOL EVOL, V15, P278 PEARSON RG, 2005, BIOL CONSERV, V123, P389 PEH KSH, 2002, RAFFLES B ZOOL, V50, P251 PIZO MA, 2004, ORNITOL NEOTROP S, V15, P117 RABINOWITZ AR, 1991, J ZOOL, V223, P281 RAYNER JMV, 1985, DICT BIRDS, P224 SCHABACKER J, 2000, ECOTROPICA, V6, P157 SO SNH, 1999, THESIS U HONG KONG H SUN C, 1997, OECOLOGIA, V112, P94 WANG BC, 2002, TRENDS ECOL EVOL, V17, P379 WANG H, 2001, MAMM BIOL, V66, P251 WEHNCKE EV, 2003, J ECOL, V91, P677 WESTCOTT DA, 2000, OECOLOGIA, V122, P249 WILLIAMS TC, 2001, AUK, V118, P389 YUMOTO T, 1999, ECOL RES, V14, P179 ZHUANG XY, 1997, J TROP ECOL 6, V13, P857 0921-2973 Landsc. Ecol.ISI:000243619800012Univ Hong Kong, Dept Ecol & Biodivers, Hong Kong, Hong Kong, Peoples R China. Corlett, RT, Univ Hong Kong, Dept Ecol & Biodivers, Pokfulam Rd, Hong Kong, Hong Kong, Peoples R China. Corlett@hkucc.hku.hkEnglishz|?*Weisberg, P. J. Ko, D. Py, C. Bauer, J. M.2008_Modeling fire and landform influences on the distribution of old-growth pinyon-juniper woodland931-943Landscape Ecology238<Expansion of Pinus and Juniperus species into shrub steppe in semi-arid regions of the western United States has been widely documented and attributed in part to fire exclusion. If decreased fire frequency has been an important cause of woodland expansion, one would expect to find age structures dominated by younger trees on more fire-prone sites, with old-growth pinyon-juniper woodland limited to sites with lower fire risk. We compared current old-growth distribution with spatial models for fire risk in a 19-km(2) watershed in central Nevada, USA. Multiple GIS models were developed to represent fire susceptibility, according to abiotic factors representing fuels and topographic barriers to fire spread. We also developed cellular automata models to generate fire susceptibility surfaces that additionally account for neighborhood effects. Rule-based GIS models failed to predict old-growth distribution better than random models. Cellular automata models incorporating spatial heterogeneity of site productivity predicted old-growth distribution better than random models but with low accuracy, ranging from 58% agreement at the single-pixel (0.09-ha) scale to 80% agreement for 20-pixel neighborhoods. The best statistical model for predicting old-growth occurrence included the negative effect of topographic convergence index (local wetness), and the positive effects of solar insolation and proximity to rock outcrops. Results support the hypothesis that old-growth woodlands in the Great Basin are more likely to occur on sites with low fire risk. However, weak relationships suggest that old-growth woodlands have not been confined to fire-safe sites. Conservation efforts should consider the landscape context of old-growth woodlands across a broad landscape, with an emphasis on conserving landscape variability in tree age structure.!://WOS:000259481900005Times Cited: 0 0921-2973WOS:00025948190000510.1007/s10980-008-9249-0<7\+Weishampel, J. F. Knox, R. G. Levine, E. R.1999hSoil saturation effects on forest dynamics: scaling across a southern boreal/northern hardwood landscape121-135Landscape Ecology142aggregation biomass drainage class GIS soil maps succession model waterlogging CO2-INDUCED CLIMATE CHANGE NORTHERN FORESTS BOREAL FORESTS GLOBAL CHANGE GAP MODELS SIMULATION ECOSYSTEMS MOISTURE MULTIFREQUENCY TEMPERATUREArticleAprPatch modeling can be used to scale-up processes to portray landscape-level dynamics. Via direct extrapolation, a heterogeneous landscape is divided into its constituent patches; dynamics are simulated on each representative patch and are weighted and aggregated to formulate the higher level response. Further extrapolation may be attained by coarsening the resolution of or lumping environmental data (e.g., climatic, edaphic, hydrologic, topographic) used to delimit a patch. Forest patterns at the southern boreal/northern hardwood transition zone are often defined by soil heterogeneity, determined primarily by the extent and duration of soil saturation. To determine how landscape-level dynamics predicted from direct extrapolation compare when coarsening soil parameters, we simulated forest dynamics for soil series representing a range of drainage classes from east-central Maine. Responses were aggregated according to the distribution of soil associations comprising a 600 ha area based on local- (1.12,000), county- (1:120,000) and state- (1:250,000) scale soil maps. At the patch level, simulated aboveground biomass accumulated more slowly in poorer draining soils. Different soil series yielded different communities comprised of species with various tolerances for soil saturation. When aggregated, removal of waterlogging caused a 20-60% increase in biomass accumulation during the first 50 years of simulation. However, this early successional increase and the maximum level of biomass accumulation over a 200 year period varied by as much as 40% depending on the geospatial data. This marked discrepancy suggests caution when extrapolating with forest patch models by coarsening parameters and demonstrates how rules used to rescale environmental data need to be evaluated for consistency.://000079802500003 ISI Document Delivery No.: 187RV Times Cited: 1 Cited Reference Count: 57 Cited References: *SOIL SURV DIV STA, 1993, USDA HDB, V18 *USDA NRCS, 1996, 42 USDA NRCS NAT SOI *USDA SCS, 1971, HDB SOIL SURV INV FI *USDA SCS, 1990, SOIL SURV INT SEL LA *USDA SCS, 1993, MISC PUB USDA NAT RE, V1492 BIDLAKE WR, 1992, SOIL SCI SOC AM J, V56, P1904 BONAN GB, 1989, ANNU REV ECOL SYST, V20, P1 BONAN GB, 1993, CLIMATIC CHANGE, V24, P281 BOTKIN DB, 1977, 6834 IBM RC BOTKIN DB, 1989, POTENTIAL EFFECTS GL BOTKIN DB, 1992, CLIMATIC CHANGE, V20, P87 BOTKIN DB, 1992, CONSEQUENCES GREENHO, P277 BOTKIN DB, 1993, FOREST DYNAMICS ECOL BRISTOW KL, 1986, AGR FOREST METEOROL, V36, P193 BUGMANN H, 1995, CLIMATIC CHANGE, V29, P251 BUGMANN HKM, 1995, J BIOGEOGR, V22, P477 FIFER S, 1998, FOREST ECOSYSTEM DYN GLEBOV FZ, 1992, SYSTEMS ANAL GLOBAL, P241 GOODMAN V, 1963, SOIL SURVEY PENOBSCO GOWARD SN, 1994, REMOTE SENS ENVIRON, V47, P107 GRIGAL DF, 1994, BIOGEOCHEMISTRY, V27, P171 JOHNSON AR, 1996, GIS ENV MODELING PRO, P451 KIMMINS JP, 1996, SOIL SCI SOC AM J, V60, P1643 KING AW, 1991, QUANTITATIVE METHODS, P479 KIRKBY MJ, 1996, J SOIL WATER CONSERV, V51, P391 KNOX RG, 1997, IEEE COMPUT SCI ENG, V4, P52 LEVINE ER, 1993, ECOL MODEL, V65, P199 LEVINE ER, 1994, REMOTE SENS ENVIRON, V47, P231 LEVINE ER, 1997, J GEOPHYS RES-ATMOS, V102, P29407 LOEHLE C, 1996, ECOL MODEL, V90, P1 MALANSON GP, 1993, CLIMATIC CHANGE, V23, P95 MALANSON GP, 1993, RIPARIAN LANDSCAPES MARTIN P, 1992, AUST J BOT, V40, P717 ONEILL RV, 1988, SCALES GLOBAL CHANGE, P29 PASTOR J, 1985, ORNLTM9519 PASTOR J, 1986, BIOGEOCHEMISTRY, V2, P3 PASTOR J, 1988, NATURE, V334, P55 PASTOR J, 1992, SYSTEMS ANAL GLOBAL, P216 PEARLSTINE L, 1985, ECOL MODEL, V29, P283 PHIPPS RL, 1979, ECOL MODEL, V7, P257 PRICE DT, 1993, WORLD RESOUR REV, V5, P15 RANSON KJ, 1994, IEEE T GEOSCI REMOTE, V32, P388 RANSON KJ, 1994, REMOTE SENS ENVIRON, V47, P142 RASTETTER EB, 1992, ECOL APPL, V2, P55 ROURKE RV, 1978, 203 USDA SCS U MAIN SHAO GF, 1994, FOREST ECOL MANAG, V70, P169 SHUGART HH, 1992, ANNU REV ECOL SYST, V23, P15 SHUGART HH, 1996, CLIMATIC CHANGE, V34, P131 SHUGART HH, 1996, GLOBAL CHANGE TERRES, P117 SOLOMON AM, 1986, OECOLOGIA, V68, P567 SOLOMON AM, 1992, SYSTEMS ANAL GLOBAL, P291 URBAN DL, 1990, VERSATILE MODEL SIMU URBAN DL, 1991, FOREST ECOL MANAG, V42, P95 VANDERHEIJDE PKM, 1988, SCALES GLOBAL CHANGE, P195 VERRY ES, 1987, NO FORESTED WETLANDS, P163 VOMPERSKY SE, 1997, NO FORESTED WETLANDS, P189 WEISHAMPEL JF, 1997, USE REMOTE SENSING M, P109 0921-2973 Landsc. Ecol.ISI:000079802500003yUniv Cent Florida, Dept Biol, Orlando, FL 32816 USA. Weishampel, JF, Univ Cent Florida, Dept Biol, Orlando, FL 32816 USA.English]<73Wellnitz, T. A. Poff, N. L. Cosyleon, G. Steury, B.2001zCurrent velocity and spatial scale as determinants of the distribution and abundance of two rheophilic herbivorous insects111-120Landscape Ecology162Agapetus body morphology current velocity Epeorus grazers hydrodynamics mobility spatial scale streams ALGAL COLONIZATION STREAM COMMUNITY MOUNTAIN STREAM PATCH DYNAMICS ECOLOGY CLASSIFICATION COMPETITION PATTERNS BEHAVIOR GRAZERSArticleFebOrganisms frequently show marked preferences for specific environmental conditions, but these preferences may change with landscape scale. Patterns of distribution or abundance measured at different scales may reveal something about an organism's perception of the environment. To test this hypothesis, we measured densities of two herbivorous aquatic insects that differed in body morphology and mobility in relation to current velocity measured at different scales in the upper Colorado River (Colorado, USA). Streambed densities of the caddisfly larva Agapetus boulderensis (high hydrodynamic profile, low mobility) and mayfly nymph Epeorus sp. (low hydrodynamic profile, high mobility) were assessed at 3 spatial scales: whole riffles, individual cobbles within riffles, and point locations on cobbles. Riffles were several meters in extent, cobbles measured 10-30 cm in size, and the local scale was within a few centimeters of individual larvae (themselves ca. 0.5-1.0 cm in size). We also quantified the abundance of periphytic food for these herbivores at the cobble and riffle scales. Agapetus favored slow current (< 30 cm s(-1)) across all scales. Epeorus, by contrast, favored fast current (60-80 cm s(-1)) at the local and riffle scale, but not at the cobble scale. Only Agapetus showed a significant relationship to current at the cobble scale, with greatest larval densities occurring at velocities near 30 cm s(-1). We had predicted an inverse correlation between grazer density and periphytic abundance; however, this occurred only for Agapetus, and then only at the cobble scale. These data suggest that organisms respond to environmental gradients at different spatial scales and that the processes driving these responses may change with scale, e.g., shifting from individual habitat selection at local and cobble scales to population responses at the riffle scale. This study also highlights the importance of using the appropriate scale of measurement to accurately assess the relationship between organisms and environmental gradients across scale.://000167936500003 zISI Document Delivery No.: 419EN Times Cited: 18 Cited Reference Count: 40 Cited References: ALLAN JD, 1982, ECOLOGY, V63, P1444 ALLAN JD, 1995, STREAM ECOLOGY STRUC ALLEN TFH, 1988, HIERARCHY PERSPECTIV ARENS W, 1989, ARCH HYDROBIOL S, V83, P253 BENKE AC, 1984, ECOLOGY AQUATIC INSE, P289 COOPER SD, 1998, AUST J ECOL, V23, P27 DAVIS JA, 1989, FRESHWATER BIOL, V21, P271 ERICKSEN CH, 1996, AQUATIC INSECTS N AM, P29 FRUTIGER A, 1998, J N AM BENTHOL SOC, V17, P104 GHOSH M, 1991, AQUAT BOT, V40, P37 GORDON ND, 1992, STREAM HYDROLOGY INT HART DD, 1987, OECOLOGIA, V73, P41 HART DD, 1992, OECOLOGIA, V91, P220 HART DD, 1996, LIMNOL OCEANOGR, V41, P297 HART DD, 1999, IN PRESS ANN REV ECO HYNES HBN, 1970, ECOLOGY RUNNING WATE KOHLER SL, 1992, ECOL MONOGR, V62, P165 KOLASA J, 1991, ECOLOGICAL HETEROGEN, P1 LAMBERTI GA, 1984, ECOLOGY AQUATIC INSE, P164 LEVIN SA, 1992, ECOLOGY, V73, P1943 LIMA SL, 1996, TRENDS ECOL EVOL, V11, P131 MCAULIFFE JR, 1984, OIKOS, V42, P327 MCINTIRE CD, 1966, HYDROBIOLOGIA, V27, P559 MENGE BA, 1990, TRENDS ECOL EVOL, V5, P52 MERRITT RW, 1996, INTRO AQUATIC INSECT NEWBURY RW, 1984, ECOLOGY AQUATIC INSE, P323 PALMER TM, 1995, OECOLOGIA, V104, P476 POFF NL, 1990, J N AMER BENTHOL SOC, V9, P303 POFF NL, 1992, OIKOS, V65, P465 POFF NL, 1995, OIKOS, V71, P179 PRINGLE CM, 1988, J N AM BENTHOL SOC, V7, P503 RADER RB, 1997, CAN J FISH AQUAT SCI, V54, P1211 STATZER B, 1982, OECOLOGIA BERL, V53, P290 STATZNER B, 1988, J N AM BENTHOL SOC, V7, P307 STRONG DR, 1984, INSECTS PLANTS TOWNSEND CR, 1989, J N AM BENTHOL SOC, V8, P36 VOGELS S, 1994, LIFE MOVING FLUIDS WALLACE BJ, 1996, INTRO AQUATIC INSECT, P44 WELLNITZ TA, 1998, FRESHWATER BIOL, V39, P135 WIENS JA, 1989, FUNCT ECOL, V3, P385 0921-2973 Landsc. Ecol.ISI:000167936500003Colorado State Univ, Dept Biol, Ft Collins, CO 80523 USA. Wellnitz, TA, Colorado State Univ, Dept Biol, Ft Collins, CO 80523 USA.EnglishU<7 GWells, M. L. O'Leary, J. F. Franklin, J. Michaelsen, J. McKinsey, D. E.2004eVariations in a regional fire regime related to vegetation type in San Diego County, California (USA)139-152Landscape Ecology192GIS-coupled modeling; landscape-scale vegetation change; regional fire regime; similarity index; Southern California vegetation; spatial variability; transition matrices; vegetation classification SOUTHERN-CALIFORNIA; FREQUENCY; SUPPRESSION; IMPACTS; MODELSArticle?This study considers variations in a regional fire regime that are related to vegetation structure. Using a Geographic Information System, the vegetation of San Diego County, Southern coastal California USA is divided into six generalized classes based on dominant plant form and include: herbaceous, sage scrub, chaparral, hardwood forest, conifer forest and desert. Mapped fire occurrences for the 20th century are then overlain to produce records of stand age, fire frequency and transitional stability for each of the vegetation classes. A `Manhattan' similarity index is used to compare and group transition matrices for the six classes of vegetation. This analysis groups herbaceous, hardwood and conifer forests in one group, sage scrub and chaparral in a second, and desert in a third. In general, sage scrub and chaparral have burned more frequently than other vegetation types during the course of the 20(th) century. Temporal trends suggest that the rate of burning in shrub-dominated vegetation is either stable (chaparral) or increasing (sage scrub), while the rate of burning in both hardwood and conifer forest is declining. This is consistent with a pattern of increased fire ignitions along the relatively low elevation urban-wildland interface, and an increase in the efficiency of fire suppression in high elevation forests.://000220452500003 aISI Document Delivery No.: 806SB Times Cited: 5 Cited Reference Count: 45 Cited References: *NAT WILDF COORD G, 1981, S389 BOIS INT FIR CT ANDREWS PL, 1986, INT194 USDA FOR SERV BAKER WL, 1989, ECOLOGY, V70, P23 BAKER WL, 1992, ECOLOGY, V73, P1879 BEAUCHAMP RM, 1986, FLORA SAN DIEGO COUN BYRNE R, 1977, P S ENV CONS FIR FUE DAVIS FW, 1995, MADRONO, V42, P40 DODGE JM, 1975, THESIS U CALIFORNIA HANES TL, 1988, CALIFORNIA NATIVE PL, V9, P417 HANSEN AJ, 2000, LANDSCAPE ECOL, V15, P505 HEINSELMAN ML, 1973, QUATERNARY RES, V3, P329 HICKMAN JC, 1993, JEPSON MANUAL HIGHER JOHNSON EA, 1985, CAN J FOREST RES, V15, P214 JOHNSON EA, 1991, ECOLOGY, V72, P194 JOHNSON EA, 1992, FIRE VEGETATION DYNA JOHNSON EA, 1994, ADV ECOL RES, V25, P239 KEELEY JE, 1982, P S DYN MAN MED TYP, P431 KEELEY JE, 1995, BIBLIO FIRE ECOLOGY, V1 KEELEY JE, 1995, BIBLIO FIRE ECOLOGY, V2 KEELEY JE, 1999, SCIENCE, V284, P1829 KEELEY JE, 2000, N AM TERRESTRIAL VEG, P203 KEELEY JE, 2001, CONSERV BIOL, V15, P1536 KEELEY JE, 2002, J BIOGEOGR, V29, P303 KRAUSMANN WJ, 1981, THESIS SAN DIEGO STA LEFKOVITCH LP, 1984, AM NAT, V123, P484 MCBRIDE JR, 1983, TREE RING B, V43, P51 MENSING SA, 1999, QUATERNARY RES, V51, P295 MILLER C, 2000, LANDSCAPE ECOLOGY, V15, P373 MINNICH RA, 1983, SCIENCE, V219, P1287 MINNICH RA, 1989, NATURAL HIST MUSEUM, V34, P37 MINNICH RA, 1995, BRUSHFIRES CALIFORNI, P21 MINNICH RA, 2001, CONSERV BIOL, V15, P1549 MOONEY HA, 1988, CALIFORNIA NATIVE PL, V9, P471 MORITZ MA, 1997, ECOL APPL, V7, P1252 MORITZ MA, 2003, ECOLOGY, V84, P351 NOYMEIR I, 1977, VEGETATIO, V33, P79 PYNE SJ, 1982, FIRE AM REED WJ, 1998, FOREST SCI, V44, P465 REED WJ, 1998, J AGR BIOL ENVIR ST, V3, P430 ROTHERMEL RC, 1972, INT115 USDA FOR SERV ROTHERMEL RC, 1973, J FOREST, V71, P640 ROTHERMEL RC, 1983, INT143 USDA FOR SERV TIMBROOK J, 1982, J CALIFORNIA GREAT B, V4, P163 WELLS ML, 1993, P GIS LIS, V2, P786 WELLS ML, 1995, BISW S FIR ISS SOL U, P193 0921-2973 Landsc. Ecol.ISI:000220452500003VSan Diego State Univ, Dept Geog, San Diego, CA 92182 USA. Tijuana River Natl Estuarine Res Reserve, Imperial Beach, CA 91932 USA. San Diego State Univ, Dept Biol, San Diego, CA 92182 USA. Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USA. Wells, ML, San Diego State Univ, Dept Geog, San Diego, CA 92182 USA. mwells@parks.ca.govEnglish?5Walter E. Westman Laurence L. Strong Bruce A. Wilcox1989KTropical deforestation and species endangerment: the role of remote sensing97-109Landscape Ecology32gtropical deforestation, biodiversity, remote sensing, Uganda, Queensland, rainforests, change detectionInitial results of a pilot study to link remotely-sensed information on tropical forest loss to field-based information on species endangerment are reported here. LANDSAT multispectral scanner (MSS) imagery from 1973 and 1988 were used to estimate net forest removal (29% of forest area), regrowth (7% of forest area, including possible artifactual errors), and forest edges in Mabira Forest in southeastern Uganda during the 15-year period. Of the forest remaining, the percentage that was heavily disturbed increased from 18% to 42%. This change in forest density was observable with the MSS imagery. The total forest edge-to-area ratio (including edges interior to the forest boundary) increased by 29% over the period. Although four distinct types of closed tropical forest, based on structure or dominance, could be recognized on the ground, the types could not be distinguished by differences in spectral reflectance in the four MSS bands. Closed tropical forest could be readily distinguished from exotic conifer plantations, banana plantations, and other non-forest vegetation types. Field measurements in Mabira and other Ugandan rain forests, and in rain forest isolates on the Atherton Tableland of North Queensland, are being made to relate changes in forest fragmentation to resulting changes in species abundance, structural form of the forests, and morphological diversity of target populations. Possible applications of conservation biology theory and modeling to these data are briefly discussed.F<7gDWestphal, M. I. Field, S. A. Tyre, A. J. Paton, D. Possingham, H. P.2003bEffects of landscape pattern on bird species distribution in the Mt. Lofty Ranges, South Australia413-426Landscape Ecology184Akaike Information Criterion Australian birds fragmentation landscape metrics logistic regression receiver operating characteristic SUPERB FAIRY-WREN SPATIAL AUTOCORRELATION HABITAT FRAGMENTATION BREEDING BIRDS FOREST ABUNDANCE COMMUNITIES WOODLANDS EXTINCTION THRESHOLDArticleYWe assessed how well landscape metrics at 2, 5, and 10 km scales could explain the distribution of woodland bird species in the Mount Lofty Ranges, South Australia. We considered 31 species that have isolated or partially isolated populations in the region and used the Akaike Information Criterion to select a set of candidate logistic regression models. The 2 km distance was the most appropriate scale for a plurality of the species. While the total amount of area of native vegetation around a site was the most important determining factor, the effect of landscape configuration was also important for many species. Most species responded positively to area-independent fragmentation, but the responses to mean patch isolation and mean patch shape were more variable. Considering a set of candidate models for which there is reasonable support (Akaike weights > 0.10), 12 species responded negatively to landscapes with highly linear and isolated patches. No clear patterns emerged in terms of taxonomy or functional group as to how species respond to landscape configuration. Most of the species had models with relatively good discrimination (12 species had ROC values > 0.70), indicating that landscape pattern alone can explain their distributions reasonably well. For six species there were no models that had strong weight of evidence, based on the AIC and ROC criteria. This analysis shows the utility of the Akaike Information Criterion approach to model selection in landscape ecology. Our results indicate that landscape planners in the Mount Lofty Ranges must consider the spatial configuration of vegetation.://000185919200005 ISI Document Delivery No.: 732AT Times Cited: 10 Cited Reference Count: 54 Cited References: ANDERSON DR, 2000, J WILDLIFE MANAGE, V64, P912 ANDREN H, 1994, OIKOS, V71, P355 BAJEMA RA, 2001, AM MIDL NAT, V145, P288 BERRY ME, 1998, SOUTHWEST NAT, V43, P453 BRYAN B, 2000, STRATEGIC REVEGETATI BURNHAM KP, 1998, MODEL SELECTION INFE BURNHAM KP, 2001, WILDLIFE RES, V28, P111 ELITH J, 2000, QUANTITATIVE METHODS, P39 ELKIE P, 1999, PATCH ANAL USERS MAN ESTADES CF, 1999, ECOL APPL, V9, P573 FAHRIG L, 1997, J WILDLIFE MANAGE, V61, P603 FAHRIG L, 1998, ECOL MODEL, V105, P273 FAHRIG L, 2002, ECOL APPL, V12, P346 FIELDING AH, 1997, ENVIRON CONSERV, V24, P38 FORD HA, 2001, BIOL CONSERV, V97, P71 FORTIN MJ, 1993, DESIGN ANAL ECOLOGIC FRANKLIN DC, 1999, EMU 1, V99, P15 GARNETT ST, 2000, ACTION PLAN AUSTR BI GREY MJ, 1997, WILDLIFE RES, V24, P631 GREY MJ, 1998, PAC CONS BIOL, V4, P55 HOBBS RJ, 2001, CONSERV BIOL, V15, P1522 HOWE RW, 1984, ECOLOGY, V65, P1585 HOWELL CA, 2000, LANDSCAPE ECOL, V15, P547 JANSEN A, 2001, BIOL CONSERV, V100, P173 JANSSON G, 1999, LANDSCAPE ECOL, V14, P283 KIRKPATRICK S, 1983, SCIENCE, V220, P671 KOENIG WD, 1998, ECOGRAPHY, V21, P423 KOENIG WD, 1999, TRENDS ECOL EVOL, V14, P22 LEGENDRE L, 1983, NUMERICAL ECOLOGY LEGENDRE P, 1993, ECOLOGY, V74, P1659 LOYN RH, 2001, BIOL CONSERV, V97, P361 MAZEROLLE MJ, 1999, ECOSCIENCE, V6, P117 MCDONNELL M, 2002, MATH METHODS SPATIAL MCGARIGAL K, 1995, ECOL MONOGR, V65, P235 METROPOLIS N, 1953, J CHEM PHYS, V21, P1087 MEYER JS, 1998, WILDLIFE MONOGR, V139, P1 MORTBERG U, 2000, LANDSCAPE URBAN PLAN, V50, P215 NEAVE HM, 1996, FOREST ECOL MANAG, V85, P197 NIAS RC, 1984, EMU, V84, P178 NIAS RC, 1986, EMU, V86, P139 PATON DC, 1994, S AUSTR ORNITHOLOGIS, V31, P151 PEARCE J, 2000, ECOL MODEL, V133, P225 POSSINGHAM H, 2001, B COMMUNITY BIODIVER, P15 POSSINGHAM HP, 2000, MATH METHODS IDENTIF PULLIAM HR, 1988, AM NAT, V132, P652 PULLIAM HR, 1996, POPULATION DYNAMICS ROSENBERG KV, 1999, CONSERV BIOL, V13, P568 SAAB V, 1999, ECOL APPL, V9, P135 SAUNDERS DA, 1977, EMU, V77, P180 SCHMIEGELOW FKA, 2002, ECOL APPL, V12, P375 TRZCINSKI MK, 1999, ECOL APPL, V9, P586 TURNER MG, 2001, LANDSCAPE ECOLOGY TH TYRE AJ, UNPUB ECOLOGICAL APP VILLARD MA, 1999, CONSERV BIOL, V13, P774 0921-2973 Landsc. Ecol.ISI:000185919200005Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA. Univ Queensland, Dept Zool & Entomol, St Lucia, Qld 4072, Australia. Univ Queensland, Dept Math, St Lucia, Qld 4067, Australia. Univ Adelaide, Dept Appl & Mol Ecol, Adelaide, SA 5005, Australia. Univ Adelaide, Dept Environm Biol, Adelaide, SA 5005, Australia. Westphal, MI, Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA.English =<7 $Weyland, F. Baudry, J. Ghersa, C. M.2012rA fuzzy logic method to assess the relationship between landscape patterns and bird richness of the Rolling Pampas869-885Landscape Ecology276agroecosystem biodiversity fuzzy logic pampas region argentina land-use agricultural intensification clustering approach species richness pampean region biodiversity argentina management diversity scaleJul?The loss of biodiversity in productive ecosystems is a global concern of the last decades. The Rolling Pampas of Argentina is an intensively cropped region that underwent important land use and landscape change, with different impacts on biodiversity of both plants and animals. Land use type and habitat complexity are hypothesized to be the most important factors determining species richness in agro-ecosystems. But it is not easy to define these attributes in an unambiguous fashion, or determine their interactions at different spatial scales. A fuzzy logic approach allows overcoming some of these problems by using linguistic variables and logic rules to relate them and formulate hypothesis. We constructed fuzzy logic models to study how bird species richness in the Rolling Pampas is related to land use and habitat complexity, and how these variables interact at two spatial scales. Results showed that at the local scale, landscape complexity is the most important factor determining species numbers; trees and bodies of water are the most influential complexities. The effect of local scale landscape attributes was modified depending on the context at broader scales, so that agricultural sites were enriched when surrounded by more favorable landscapes. There was a high dispersion in the predicted/observed value relationship, indicating that landscape factors interact in more complex ways than those captured by the models we used. We suggest that the fuzzy logic approach is suitable for working with biological systems, and we discuss the advantages and disadvantages of its use.://000305218000007-958DZ Times Cited:0 Cited References Count:72 0921-2973Landscape EcolISI:000305218000007Weyland, F Univ Buenos Aires, IFEVA CONICET, Dept Recursos Nat & Ambiente, Fac Agron, Av San Martin 4453,C1417DSE, Buenos Aires, DF, Argentina Univ Buenos Aires, IFEVA CONICET, Dept Recursos Nat & Ambiente, Fac Agron, Av San Martin 4453,C1417DSE, Buenos Aires, DF, Argentina Univ Buenos Aires, IFEVA CONICET, Dept Recursos Nat & Ambiente, Fac Agron, Buenos Aires, DF, Argentina INRA, SAD Paysage, F-35042 Rennes, FranceDOI 10.1007/s10980-012-9735-2English <7(Wheater, C. P. Cullen, W. R. Bell, J. R.2000NSpider communities as tools in monitoring reclaimed limestone quarry landforms401-406Landscape Ecology155kindicators invertebrates reclamation restoration MANAGEMENT VEGETATION DERBYSHIRE GRASSLAND BEETLE FAUNA UKArticleJul;Spider communities are sensitive to a wide range of environmental factors and are potential ecological indicators which may be effective in the assessment and monitoring of restored ecosystems. One restoration technique of disused limestone quarry faces, landform replication, attempts to create landforms and ecosystems similar to those found on natural dalesides. Vegetation surveys indicate that communities developing on landform replications are more closely allied to natural dalesides than are those of naturally recolonised disused quarries. Assessment of the spider communities of three landform replication sites, a natural limestone daleside and seven naturally recolonised disused limestone quarries, using DECORANA and TWINSPAN, produced differing patterns of sites than those observed through the assessment of the vegetation communities. DECORANA assessment based on vascular plant species composition highlights the similarities between daleside and reclaimed site communities. The sensitivity of spider communities to vegetation structure and extent of bare ground highlights differences between sites and provides evidence of important differences in vegetation community development particularly in relation to cover and structure. Implications for the assessment of reclamation and restoration techniques are discussed.://000088036700001 ISI Document Delivery No.: 331UH Times Cited: 6 Cited Reference Count: 26 Cited References: ASSELIN A, 1988, CONNECTIVITY LANDSCA, P85 BELL JR, 1998, STRUCTURE SPIDER COM, P253 CULLEN WR, 1998, BIOL CONSERV, V84, P25 DOBEL HG, 1990, ENVIRON ENTOMOL, V19, P1356 DUFFEY E, 1975, P 6 INT C AR AMST, P52 GAGEN P, 1993, Z GEOMORPHOLOGIE S, V87, P163 GIBSON CWD, 1992, ECOGRAPHY, V15, P166 GIBSON CWD, 1992, J APPL ECOL, V29, P132 HILL MO, 1979, DECORANA FORTRAN PRO HILL MO, 1979, TWINSPAN FORTRAN PRO HOPKINS PJ, 1984, J APPL ECOL, V21, P935 JONESWALTERS L, 1988, 32 EFU MADER HJ, 1988, MUNTERSCHE GEOGRAPHI, V29, P97 MAELFAIT JP, 1989, COMPT REND S INV BEL, P437 MALLOCH AJC, 1988, VESPAN 2 MORRIS MG, 1992, LANDSCAPE ECOLOGY BR, P66 RUSHTON SP, 1987, B BR ARACHNOL SOC, V7, P165 RUSHTON SP, 1988, BIOL CONSERV, V46, P169 RUSHTON SP, 1989, J APPL ECOL, V26, P489 RUSHTON SP, 1992, J BIOGEOGR, V19, P99 SIEPEL H, 1989, COMPT REND S INV BEL, P443 SPEIGHT MCD, 1986, P 3 EUR C ENT AMST, P485 UETZ GW, 1991, HABITAT STRUCTURE PH, P325 WEBB NR, 1984, J APPL ECOL, V21, P921 WHEATER CP, 1997, RESTOR ECOL, V5, P77 WISE DH, 1993, SPIDERS ECOLOGICAL W 0921-2973 Landsc. Ecol.ISI:000088036700001Manchester Metropolitan Univ, Dept Geog & Environm Sci, Manchester M1 5GD, Lancs, England. Wheater, CP, Manchester Metropolitan Univ, Dept Geog & Environm Sci, Chester St, Manchester M1 5GD, Lancs, England.English '<7White, M. A. Mladenoff, D. J.1994OOld-growth forest landscape transitions from pre-European settlement to present191-205Landscape Ecology93ACER-SACCHARUM; DISTURBANCE; GEOGRAPHIC INFORMATION SYSTEMS (GIS); HEMLOCK HARDWOOD; OLD-GROWTH FOREST; SPATIAL PATTERN; SUCCESSION; TSUGA-CANADENSIS; WISCONSIN; WESTERN GREAT LAKESArticleSepWe conducted a multi-temporal spatial analysis of forest cover for a 9600 ha landscape in northern Wisconsin, U.S.A., using data from pre-European settlement (1860s), post-settlement (1931), and current (1989) periods. Using GIS we have shown forest landscape changes and trajectories that have been generally described in aggregate for the norther Great Lake States region. We created the pre-European settlement map from the witness tree data of the original federal General Land Office survey notes. The 1931 cover was produced from the Wisconsin Land Economic Inventory, and the 1989 cover map was based on color infrared photography. We used GIS to analyze 1) land area occupied by different forest types at different dates, 2) temporal transitions between dates and their driving proceses, and 3) successional trajectories with landforms and spatial associations of forest types. Over the 120 year period, forest cover has changed from a landscape dominated by old-growth hemlock (Tsuga canadensis) and hardwood forests (Acer saccharum, Betula alleghaniensis) to largely second-growth hardwoods and conifers. The former dominant hemlock is largely eliminated from the landscape. From 1860 to 1931, large-scale disturbances associated with logging were the dominant processes on the landscape. Early successional forest types covered much of the landscape by the 1930s. From 1931 to 1989, succession was the dominant process driving forest transitions as forest types succeeded to a diverse group of upland hardwood and conifer forest types. If successional trajectories continue, a more homogeneous landscape may develop comprised of both a northern hardwood type dominated by sugar maple, and a boreal conifer/hardwood forest.://A1994PL16600003 IISI Document Delivery No.: PL166 Times Cited: 63 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1994PL16600003AWHITE, MA, UNIV MINNESOTA,NAT RESOURCES RES INST,DULUTH,MN 55811.English <7]FWickham, J. D. Jones, K. B. Riitters, K. H. Wade, T. G. O'Neill, R. V.1999bTransitions in forest fragmentation: implications for restoration opportunities at regional scales137-145Landscape Ecology142WGIS hierarchy land-cover percolation theory scale threshold SPATIAL SCALES ECOTONES USAArticleApr]Where the potential natural vegetation is continuous forest (e.g., eastern US), a region can be divided into smaller units (e.g., counties, watersheds), and a graph of the proportion of forest in the largest patch versus the proportion in anthropogenic cover can be used as an index of forest fragmentation. If forests are not fragmented beyond that converted to anthropogenic cover, there would be only one patch in the unit and its proportional size would equal 1 minus the percentage of anthropogenic cover. For a set of 130 watersheds in the mid-Atlantic region, there was a transition in forest fragmentation between 15 and 20% anthropogenic cover. The potential for mitigating fragmentation by connecting two or more disjunct forest patches was low when percent anthropogenic cover was law, highest at moderate proportions of anthropogenic cover, and again low as the proportion of anthropogenic cover increased toward 100%. This fragmentation index could be used to prioritize locations for restoration by targeting watersheds where there would be the greatest increase in the size of the largest forest patch.://000079802500004 ,ISI Document Delivery No.: 187RV Times Cited: 17 Cited Reference Count: 26 Cited References: EHRLICH PR, 1977, ECOSCIENCE POPULATIO GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GARDNER RH, 1991, QUANTITATIVE METHODS, P289 HEALY RG, 1981, MARKET RURAL LAND TR HOLLING CS, 1973, ANNUAL REV ECOLOGY S, V4, P1 HUNSAKER CT, 1995, BIOSCIENCE, V45, P193 KING RJ, 1989, AUST SYST BOT, V2, P1 KUCHLER AW, 1964, AM GEOGRAPHICAL SOC, V36 LOEHLE C, 1996, LANDSCAPE ECOL, V11, P225 LYNCH JF, 1984, BIOL CONSERV, V28, P287 MCDONNELL JJ, 1993, HUMANS COMPONENTS EC MILNE BT, 1996, ECOLOGY, V77, P805 NOSS RF, 1993, SAVING NATURES LEGAC ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 ONEILL RV, 1989, LANDSCAPE ECOL, V3, P193 PLOTNICK RE, 1993, LECT MATH LIFE SCI P, V23, P129 STAUFFER D, 1985, INTRO PERCOLATION TH TURNER MG, 1993, LANDSCAPE ECOL, V8, P213 VOGELMANN JE, 1995, CONSERV BIOL, V9, P439 VOGELMANN JE, 1998, PHOTOGRAMM ENG REM S, V64, P45 WESSMAN CA, 1992, ANNU REV ECOL SYST, V23, P175 WESTMAN WE, 1977, SCIENCE, V197, P960 WHITTAKER RH, 1975, COMMUNITIES ECOSYSTE WICKHAM JD, 1997, ENVIRON MANAGE, V21, P247 WICKHAM JD, 1997, PHOTOGRAMM ENG REM S, V63, P397 WILCOVE DS, 1986, CONSERVATION BIOL SC, P234 0921-2973 Landsc. Ecol.ISI:000079802500004US EPA, Natl Exposure Res Lab, Res Triangle Pk, NC 27711 USA. Wickham, JD, US EPA, Natl Exposure Res Lab, MD-56, Res Triangle Pk, NC 27711 USA.English<7Wickham, J. D. Norton, D. J.1994(Mapping and analyzing landscape patterns7-23Landscape Ecology912LANDSCAPE PATTERN; LAND COVER; CLASSIFICATION; GISArticleMarLandscapes were mapped as clusters of 2 or 3 land cover** types, based on their pattern within the clusters and tendency for a single type to dominate. These landscapes, called Landscape Pattern Types (LPTs), were combined with other earth surface feature data in a Geographic Information System (GIS) to test their utility as analysis units. Road segment density increased significantly as residential and urbanized land cover components increased from absent, to present as patch, to present as matrix (i.e., the dominant land cover type). Stream segment density was significantly lower in LPTs with an urbanized or residential matrix than in LPTs with either a forest or agriculture matrix, suggesting an inverse relationship between stream network density and the prevalence of human development other than agriculture in the landscape. The ratio of average forest patch size to total forest in the LPT unit decreased as agriculture replaced forest, then increased as residential and urban components dominated. Wetland fractal dimension increased as agriculture and residential land cover components of LPTs increased. Comparison of LPT and LUDA land cover area statistics in ecoregions suggested that land cover data alone does not provide information as to its spatial arrangement.://A1994NC71800002 IISI Document Delivery No.: NC718 Times Cited: 20 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1994NC71800002JWICKHAM, JD, DESERT RES INST,CTR BIOL SCI,7010 DANDINI BLVD,RENO,NV 89512.English '<7*Wickham, J. D. O'Neill, R. V. Jones, K. B.2000&A geography of ecosystem vulnerability495-504Landscape Ecology156\GIS land-cover change population modeling roads LAND-USE INTERPOLATION ECOLOGY QUALITY COVERArticleAugLand-cover change and the subsequent potential loss of natural resources due to conversion to anthropogenic use is regarded as one of the more pervasive environmental threats. Population and road data were used to generate interpolated surfaces of land demand across a large region, the mid-Atlantic states of Pennsylvania, Delaware, Maryland, Virginia, and West Virginia. The land demand surfaces were evaluated against land-cover change, as estimated using temporal decline in Normalized Difference Vegetation Index (NDVI). In general, the interpolated surfaces exhibited a plateau along the eastern seaboard that sank to a valley in the center of the study area, and then rose again to a plateau in the west that was of overall lower height than the plateau on the eastern seaboard. The spatial pattern of land-cover change showed the same general pattern as the interpolated surfaces of land demand. Correlations were significant regardless of variations used to generate the interpolated surfaces. The results suggest that human activity is the principal agent of land-cover change at regional scales in this region, and that natural resources that change as land cover changes (e.g., water, habitat) are exposed to a gradient of vulnerability that increases from west to east.://000088037200001 `ISI Document Delivery No.: 331UN Times Cited: 9 Cited Reference Count: 33 Cited References: *ENV SYST RES I, 1992, GRID COMM REF FUNCT *US EPA, 1993, USEPA600R93135 OFF R BARKLEY DL, 1996, LAND ECON, V72, P336 BEAULAC MN, 1982, WATER RESOUR BULL, V18, P1013 BERRY BJL, 1990, GLOBAL EC RESOURCE U BOCKSTAEL NE, 1996, AM J AGR ECON, V78, P1168 CARROTHERS GAP, 1956, J AM I PLANNERS, V22, P94 CLARK C, 1951, J ROYAL STATISTICA A, V114, P490 FRANKE R, 1982, COMPUT MATH APPL, V8, P273 FRINK CR, 1991, J ENVIRON QUAL, V20, P717 FUNG T, 1988, PHOTOGRAMMETRIC ENG, V54, P1449 JENSEN JR, 1981, AM CARTOGRAPHER, V8, P127 JERNIGAN RW, 1986, PRIMER KRIGING JONES KB, 1997, 600R97130 USEPA OFF KHORRAM S, 1999, MONOGRAPH AM SOC PHO LANCASTER P, 1986, CURVE SURFACE FITTIN MARKHAM BL, 1987, REMOTE SENS ENVIRON, V22, P39 MITAS L, 1988, COMPUT MATH APPL, V16, P983 ONEILL RV, 1997, BIOSCIENCE, V47, P513 RIEBSAME WE, 1994, BIOSCIENCE, V44, P350 RIITTERS KH, 1997, BIOL CONSERV, V81, P191 SCHOTT JR, 1988, REMOTE SENS ENVIRON, V26, P1 SHEPPARD E, 1990, CAPITALIST SPACE EC SHI YJ, 1997, LAND ECON, V73, P90 SINGH A, 1989, INT J REMOTE SENS, V10, P989 TUCKER CJ, 1979, REMOTE SENS ENVIRON, V8, P127 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 WATSON DF, 1985, GEO-PROCESSING, V2, P315 WATSON DF, 1992, CONTOURING GUIDE DIS WEAR DN, 1998, ECOL APPL, V8, P619 WICKHAM JD, IN PRESS FOREST FRAG WICKHAM JD, 1999, ENVIRON MANAGE, V24, P553 WILCOVE DS, 1986, SCI SCARCITY DIVERSI, P237 0921-2973 Landsc. Ecol.ISI:000088037200001aUS EPA, Res Triangle Pk, NC 27711 USA. Wickham, JD, US EPA, MD-56, Res Triangle Pk, NC 27711 USA.English <75*Wickham, J. D. O'Neill, R. V. Jones, K. B.2000-Forest fragmentation as an economic indicator171-179Landscape Ecology152economic geography geographic information systems (GIS) land-cover change land use modeling LAND-COVER INTERPOLATION MULTIPLE ECOLOGY SCALESArticleFebVDespite concern over the ecological consequences of conversion of land from natural cover to anthropogenic uses, there are few studies that show a quantitative relationship between fragmentation and economic factors. For the southside economic region of Virginia, we generated a surface (map) of urbanization pressure by interpolation of population from a ring of cities surrounding the region. The interpolated map showed a geographic gradient of urbanization pressure or demand for land that increased from northwest to southeast. Estimates of forest fragmentation were moderately correlated with the geographic gradient of urbanization pressure. The fragmentation-urbanization relationship was corroborated by examining land-cover change against the urbanization map. The geographic gradient in land-cover change was strongly correlated with the urbanization pressure gradient. The correspondence between geographic gradients in land-cover change and urbanization pressure suggests that forest fragmentation will occur at a greater rate in the eastern portion of the southside economic region in the future.://000084522700008 FISI Document Delivery No.: 270EP Times Cited: 15 Cited Reference Count: 37 Cited References: *ENV SYST RES I, 1992, GRID COMM REF FUNCT *US EPA, 1993, EPA600R93135 OFF RES BARKLEY DL, 1996, LAND ECON, V72, P336 BERRY BJL, 1990, GLOBAL EC RESOURCE U BOCKSTAEL NE, 1996, AM J AGR ECON, V78, P1168 CARROTHERS GAP, 1956, J AM I PLANNERS, V22, P94 CLARK C, 1951, J ROYAL STATISTICA A, V114, P490 CRESSIE N, 1991, STAT SPATIAL DATA FONSECA JW, 1990, VIRGINIA GEOGRAPHER, V22, P1 FUNG T, 1988, PHOTOGRAMMETRIC ENG, V54, P1449 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 JENSEN JR, 1981, AM CARTOGRAPHER, V8, P127 JONES KB, 1997, EPA600R97130 OFF RES LAGRO JA, 1992, LANDSCAPE ECOL, V7, P275 LANCASTER P, 1986, CURVE SURFACE FITTIN MARKHAM BL, 1987, REMOTE SENS ENVIRON, V22, P39 MEENTEMEYER V, 1987, ECOL STUD, V64, P15 MITAS L, 1988, COMPUT MATH APPL, V16, P983 OPDAM P, 1991, LANDSCAPE ECOL, V5, P93 OPENSHAW S, 1977, ENVIRON PLANN A, V9, P169 PLOTNICK RE, 1993, LECT MATH LIFE SCI P, V23, P129 RIITTERS KH, 1997, BIOL CONSERV, V81, P191 ROBINSON WS, 1950, AM SOCIOL REV, V15, P351 SCHOTT JR, 1988, REMOTE SENS ENVIRON, V26, P1 SHEPPARD E, 1990, CAPITALIST SPACE EC SHI YJ, 1997, LAND ECON, V73, P90 SINGH A, 1989, INT J REMOTE SENS, V10, P989 TUCKER CJ, 1979, REMOTE SENS ENVIRON, V8, P127 TURNER MG, 1990, PHOTOGRAMM ENG REM S, V56, P379 TURNER MG, 1996, ECOL APPL, V6, P1150 VOGELMANN JE, 1998, PHOTOGRAMM ENG REM S, V64, P45 WATSON DF, 1985, GEO-PROCESSING, V2, P315 WEAR DN, 1998, ECOL APPL, V8, P619 WICKHAM JD, 1997, ENVIRON MANAGE, V21, P247 WICKHAM JD, 1999, LANDSCAPE ECOL, V14, P137 WILCOVE DS, 1986, SCI SCARCITY DIVERSI, P237 0921-2973 Landsc. Ecol.ISI:000084522700008aUS EPA, Res Triangle Pk, NC 27711 USA. Wickham, JD, US EPA, MD-56, Res Triangle Pk, NC 27711 USA.English _<7=Wickham, J. D. Riitters, K. H. Wade, T. G. Coan, M. Homer, C.2007?The effect of Appalachian mountaintop mining on interior forest179-187Landscape Ecology222Appalachian mountains; coal mining; edge effects; forest loss; interior forest UNITED-STATES; LAND-USE; HABITAT FRAGMENTATION; NUTRIENT; SCALE; DYNAMICS; SERVICES; CLIMATEArticleFebSouthern Appalachian forests are predominantly interior because they are spatially extensive with little disturbance imposed by other uses of the land. Appalachian mountaintop mining increased substantially during the 1990s, posing a threat to the interior character of the forest. We used spatial convolution to identify interior forest at multiple scales on circa 1992 and 2001 land-cover maps of the Southern Appalachians. Our analyses show that interior forest loss was 1.75-5.0 times greater than the direct forest loss attributable to mountaintop mining. Mountaintop mining in the southern Appalachians has reduced forest interior area more extensively than the reduction that would be expected based on changes in overall forest area alone. The loss of Southern Appalachian interior forest is of global significance because of the worldwide rarity of large expanses of temperate deciduous forest.://000243823900003 yISI Document Delivery No.: 130UG Times Cited: 0 Cited Reference Count: 34 Cited References: *SAMAB, 1996, 5 SAMAB USDA FOR SER *US EPA, 2005, PUBL EPA BEAULAC MN, 1982, WATER RESOUR BULL, V18, P1013 BURNS SLS, 2005, THESIS W VIRGINIA U COSTANZA R, 1997, NATURE, V387, P253 FAHRIG L, 2002, ECOL APPL, V12, P346 FOSTER DR, 1998, ECOSYSTEMS, V1, P96 FOX J, 1999, ORGAN ENVIRON, V12, P163 FRINK CR, 1991, J ENVIRON QUAL, V20, P717 FRY J, 2005, LAND COVER CHANGE DE, P105 HARPER KA, 2005, CONSERV BIOL, V19, P768 HAYDEN BP, 1998, PHILOS T ROY SOC B, V353, P5 HINKLE CR, 1993, BIODIVERSITY SE US U HOMER C, 2004, PHOTOGRAMM ENG REM S, V70, P829 JONES KB, 2001, LANDSCAPE ECOL, V16, P301 LAURANCE WF, 2002, CONSERV BIOL, V16, P605 MARSHALL CH, 2004, MON WEATHER REV, V132, P28 ONEILL RV, 2000, BIOSCIENCE, V50, P333 PICKERING J, 2003, WILDERNESS EARTHS LA PIELKE RA, 2002, PHILOS T ROY SOC A, V360, P1705 RAMAHARITRA T, 2006, TROP RESOURCE B, V25, P32 RIITTERS K, 2000, CONSERV ECOL, V4 RIITTERS KH, 2002, ECOSYSTEMS, V5, P815 RIITTERS KH, 2003, J FOREST, V101, P18 ROBINSON SK, 1995, SCIENCE, V267, P1987 SCOTT JM, 1998, ANN MO BOT GARD, V85, P34 SKOLE D, 1993, SCIENCE, V260, P1905 SLONECKER ET, 2001, REMOTE SENS REV, V20, P293 SZWILSKI TB, 2001, INT J SURF MINING RE, V15, P73 VOGELMANN JE, 2001, PHOTOGRAMM ENG REM S, V67, P650 WEAKLAND CA, 2005, AUK, V122, P497 WEATHERS KC, 2001, CONSERV BIOL, V15, P1506 WESTMAN WE, 1977, SCIENCE, V197, P960 WICKHAM JD, 2005, LANDSCAPE ECOL, V20, P791 0921-2973 Landsc. Ecol.ISI:000243823900003US EPA, Natl Exposure Res Lab, Res Triangle Pk, NC 27711 USA. US Forest Serv, So Forest Res Stn, Res Triangle Pk, NC 27709 USA. US Geol Survey, Sci Applicat Int Corp, EROS Data Ctr, Sioux Falls, SD 57198 USA. Wickham, JD, US EPA, Natl Exposure Res Lab, E243-05, Res Triangle Pk, NC 27711 USA. wickham.james@epa.gov kriitters@fs.fed.us wade.timothy@epa.gov coan@usgs.gov homer@usgs.govEnglishs?Z7J. D. Wickham K. H. Riitters T. G. Wade J. W. Coulston2007:Temporal change in forest fragmentation at multiple scales481-489Landscape Ecology224fConservation - Cumulative impact - Forest loss - Land-cover change - Land-use planning - Pine Barrens Previous studies of temporal changes in fragmentation have focused almost exclusively on patch and edge statistics, which might not detect changes in the spatial scale at which forest occurs in or dominates the landscape. We used temporal land-cover data for the Chesapeake Bay region and the state of New Jersey to compare patch-based and area–density scaling measures of fragmentation for detecting changes in the spatial scale of forest that may result from forest loss. For the patch-based analysis, we examined changes in the cumulative distribution of patch sizes. For area–density scaling, we used moving windows to examine changes in dominant forest. We defined dominant forest as a forest parcel (pixel) surrounded by a neighborhood in which forest occupied the majority of pixels. We used >50% and ≥60% as thresholds to define majority. Moving window sizes ranged from 2.25 to 5,314.41 hectares (ha). Patch size cumulative distributions changed very little over time, providing no indication that forest loss was changing the spatial scale of forest. Area–density scaling showed that dominant forest was sensitive to forest loss, and the sensitivity increased nonlinearly as the spatial scale increased. The ratio of dominant forest loss to forest loss increased nonlinearly from 1.4 to 1.8 at the smallest spatial scale to 8.3 to 11.5 at the largest spatial scale. The nonlinear relationship between dominant forest loss and forest loss in these regions suggests that continued forest loss will cause abrupt transitions in the scale at which forest dominates the landscape. In comparison to the Chesapeake Bay region, dominant forest loss in New Jersey was less sensitive to forest loss, which may be attributable the protected status of the New Jersey Pine Barrens. |?4Wickham, J. D. Riitters, K. H. Wade, T. G. Homer, C.2008:Temporal change in fragmentation of continental US forests891-898Landscape Ecology238mChanges in forest ecosystem function and condition arise from changes in forest fragmentation. Previous studies estimated forest fragmentation for the continental United States (US). In this study, new temporal land-cover data from the National Land Cover Database (NLCD) were used to estimate changes in forest fragmentation at multiple scales for the continental US. Early and late dates for the land-cover change data were ca. 1992 and ca. 2001. Forest density was used as a multi-scale index of fragmentation by measuring the proportion of forest in neighborhoods ranging in size from 2.25 to 5314.41 ha. The multi-scale forest density maps were classified using thresholds of 40% (patch), 60% (dominant), and 90% (interior) to analyze temporal change of fragmentation. The loss of dominant and interior forest showed distinct scale effects, whereas loss of patch forest was much less scale-dependent. Dominant forest loss doubled from the smallest to the largest spatial scale, while interior forest loss increased by approximately 80% from the smallest to the second largest spatial scale, then decreased somewhat. At the largest spatial scale, losses of dominant and interior forest were 5 and 10%, respectively, of their ca. 1992 amounts. In contrast, patch forest loss increased by only 25% from the smallest to largest spatial scale. These results indicate that continental US forests were sensitive to forest loss because of their already fragmented state. Forest loss would have had to occur in an unlikely spatial pattern in order to avoid the proportionately greater impact on dominant and interior forest at larger spatial scales.!://WOS:000259481900002Times Cited: 0 0921-2973WOS:00025948190000210.1007/s10980-008-9258-z <77Wickham, J. D. Riitters, K. H. Wade, T. G. Jones, K. B.2005}Evaluating the relative roles of ecological regions and land-cover composition for guiding establishment of nutrient criteria791-798Landscape Ecology207Clean Water Act (CWA); eutrophication; nitrogen; phosphorus; scale; variance component analysis CONTERMINOUS UNITED-STATES; STREAMS; NITROGEN; PHOSPHORUS; WATERSHEDS; ECOREGIONS; EXPORTArticleNovThe continuing degradation of United States surface waters by excessive nutrient loads has motivated the establishment of nutrient criteria for streams, lakes, and estuaries as a means to protect aquatic resources. Nutrient criteria have been established based on ecoregional differences, recognizing that geographic variation in climate, topography, geology, and land use require use of different criteria values for different regions of the continental United States. Several studies have demonstrated that land-cover composition also strongly influences nutrient concentrations and yields. We examined the relative importance of ecoregions and watershed land-cover composition in explaining variability in nitrogen (N) and phosphorus (P) concentrations by re-analyzing the National Eutrophication Survey (NES) data reported by Omernik (1977). The variance of N concentrations among land-cover composition classes within ecoregions was six times larger than the variance among ecoregions. For P concentrations, land-cover composition within ecoregions accounted for three times more variance than ecoregions themselves. Variance across ecoregions was only weakly significant after accounting for variance in land-cover composition within ecoregions. The results suggest that the relationship between land-cover composition and nutrient concentrations in aquatic systems should also be used to help guide establishment of nutrient criteria.://000233036300002 ISI Document Delivery No.: 980RQ Times Cited: 2 Cited Reference Count: 24 Cited References: *US EPA, 1998, 822R98002 US EPA OFF *US EPA, 2000, 822B00104 US EPA OFF ALEXANDER RB, 2000, NATURE, V403, P758 BAILEY RG, 1995, MISCELLANEOUS PUBLIC, V1391 BEAULAC MN, 1982, WATER RESOUR BULL, V18, P1013 CARPENTER SR, 1998, ECOL APPL, V8, P559 DILLON PJ, 1975, WATER RES, V9, P135 DODDS WK, 2000, J N AM BENTHOL SOC, V19, P186 DODDS WK, 2002, CAN J FISH AQUAT SCI, V59, P865 FISHER TR, 1998, WATER AIR SOIL POLL, V105, P387 FRINK CR, 1991, J ENVIRON QUAL, V20, P717 GRIFFITH GE, 1999, J SOIL WATER CONSERV, V54, P666 HALLOWAY JM, 1998, NATURE, V395, P785 JONES KB, 2001, LANDSCAPE ECOL, V16, P301 LEWIS WM, 2002, BIOGEOCHEMISTRY, V57, P375 OMERNIK JM, 1977, EPA ECOLOGICAL RES S OMERNIK JM, 1987, ANN ASSOC AM GEOGR, V77, P118 PANUSKA JC, 1995, 38 WISC DEP NAT RES PETERSON BJ, 2001, SCIENCE, V292, P80 ROHM CM, 2002, J AM WATER RESOUR AS, V38, P213 SATTERTHWAITE FE, 1946, BIOMETRICS B, V2, P110 SEARLE SR, 1992, VARIANCE COMPONENTS SMITH RA, 2003, ENVIRON SCI TECHNOL, V37, P3039 WICKHAM JD, 2003, LANDSCAPE ECOL, V18, P193 0921-2973 Landsc. Ecol.ISI:000233036300002US EPA, Natl Exposure Res Lab, Res Triangle Pk, NC 27711 USA. US Forest Serv, So Res Stn, Res Triangle Pk, NC 27709 USA. US EPA, Natl Exposure Res Lab, Las Vegas, NV 89119 USA. Wickham, JD, US EPA, Natl Exposure Res Lab, E243 05, Res Triangle Pk, NC 27711 USA. wickham.james@epa.govEnglish|?/ 4Wickham, James D. Wade, Timothy G. Riitters, Kurt H.2011FAn environmental assessment of United States drinking water watersheds605-616Landscape Ecology265MayThere is an emerging recognition that natural lands and their conservation are important elements of a sustainable drinking water infrastructure. We conducted a national, watershed-level environmental assessment of 5,265 drinking water watersheds using data on land cover, hydrography and conservation status. Approximately 78% of the conterminous United States lies within a drinking water watershed. The typical drinking water watershed had a high percentage of natural vegetation ((x) over tilde = 77%) but a low percentage of it was set aside for conservation ((x) over tilde = 3%). Median percentage values for urban and agriculture were 5 and 8%, respectively. Between ca. 1992 and ca. 2001, approximately 23% of the drinking water watersheds lost at least 1% of their natural vegetation, and approximately 9% of the watersheds had at least a 1% increase in the amount of urban land. Loss of natural vegetation was common in nearly all areas of the country, but also concentrated in the Ohio River and Southeast hydrologic regions. Urbanization was concentrated in the eastern United States, primarily in the Mid-Atlantic and Southeast hydrologic regions.!://WOS:000291485100001Times Cited: 1 0921-2973WOS:00029148510000110.1007/s10980-011-9591-5U<7}mWickham, J. D. Wade, T. G. Riitters, K. H. O'Neill, R. V. Smith, J. H. Smith, E. R. Jones, K. B. Neale, A. C.20036Upstream-to-downstream changes in nutrient export risk195-208Landscape Ecology182Chesapeake Bay in-stream nutrient decay modeling nitrogen phosphorus pollution watersheds PREDICTING NUTRIENT PHOSPHORUS EXPORT NITROGEN BUDGET COASTAL-PLAIN UNITED-STATES LAND-COVER WATERSHEDS RIVER DENITRIFICATION ECOSYSTEMArticleNutrient export coefficients are estimates of the mass of nitrogen (N) or phosphorus (P) normalized by area and time (e.g., kg/ha/yr). They have been estimated most often for watersheds ranging in size from 10(2) to 10(4) hectares, and have been recommended as measurements to inform management decisions. At this scale, watersheds are often nested upstream and downstream components of larger drainage basins, suggesting nutrient export coefficients will change from one subwatershed to the next. Nutrient export can be modeled as risk where lack of monitoring data prevents empirical estimation. We modeled N and P export risk for subwatersheds of larger drainage basins, and examined spatial changes in risk from upstream to downstream watersheds. Spatial (subwatershed) changes in N and P risk were a function of in-stream decay, subwatershed land-cover composition, and subwatershed streamlength. Risk tended to increase in a downstream direction under low rates of in-stream decay, whereas high rates of in-stream decay often reduced risk to zero (0) toward downstream subwatersheds. On average, increases in the modeled rate of in-stream decay reduced risk by 0.44 for N and 0.39 for P. Interactions between in-stream decay, land-cover composition and streamlength produced dramatic changes in risk across subwatersheds in some cases. Comparison of the null cases of no in-stream decay and homogeneously forested subwatersheds with extant conditions indicated that complete forest cover produced greater reductions in nutrient export risk than a high in-stream decay rate, especially for P. High rates of in-stream decay and complete forest cover produced approximately equivalent reductions in N export risk for downstream subwatersheds.://000183770300008  ISI Document Delivery No.: 694JB Times Cited: 2 Cited Reference Count: 48 Cited References: *USDA NAT RES CONS, 2001, FED STAND DEL HYDR U ALEXANDER RB, 2000, NATURE, V403, P758 ALEXANDER RB, 2001, SPRING M MAY 29 JUN ARNOLD CL, 1996, J AM PLANN ASSOC, V62, P244 BARTELL SM, 1992, ECOLOGICAL RISK ESTI BEAULAC MN, 1982, WATER RESOUR BULL, V18, P1013 BURNS DA, 1998, BIOGEOCHEMISTRY, V40, P73 CLESCERI NL, 1986, WATER RESOUR BULL, V22, P983 DELWICHE LD, 1983, WATER RESOURCES B, V19, P951 DEWALD T, 1985, STORET REACH RETRIEV DILLON PJ, 1975, WATER RES, V9, P135 DONIGIAN AS, 1994, 15796 CBPTRS FISHER TR, 1998, WATER AIR SOIL POLL, V105, P387 FRINK CR, 1991, J ENVIRON QUAL, V20, P717 GARDNER RH, IN PRESS ROLE MODELS GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GRAHAM RL, 1991, ECOL APPL, V1, P196 HARTIGAN JP, 1983, J ENVIRON ENG-ASCE, V109, P1259 HESSION WC, 1996, WATER RESOUR BULL, V32, P1039 HILL AR, 1979, NATURE, V281, P291 HILL AR, 1981, CAN GEOGR, V25, P225 JONES KB, 2001, LANDSCAPE ECOL, V16, P301 JORDAN TE, 1997, J ENVIRON QUAL, V26, P836 LEOPOLD LB, 1953, 252 US GEOL SURV LINKER LC, 1996, WATER ENV TECHNOL, V8, P48 LOVELAND TR, 1996, GAP ANAL LANDSCAPE A, P75 LOWRANCE RR, 1985, ECOLOGY, V66, P287 LUCEY KJ, 1993, J ENVIRON QUAL, V22, P38 OMERNIK JM, 1977, EPA600377105 ENV RES ONEILL RV, 1982, ENVIRON TOXICOL CHEM, V1, P167 PETERSON BJ, 2001, SCIENCE, V292, P80 PRESTON EM, 1988, ENVIRON MANAGE, V12, P656 PRESTON SD, 1999, 994054 USGS WAT RES RAST W, 1983, J ENV ENG, V109, P503 RECKHOW KH, 1980, EPA440580011 RENARD KG, 1997, AGR HDB USDA, V703 REYNOLDS JF, 1999, INTEGRATING HYDROLOG, P273 RICHARDS C, 1998, RISK ASSESSMENT LOGI, P255 RISSER PG, 1984, SPECIAL PUBLICATION, V2 SEABER PR, 1987, HYDROLOGIC UNIT MAPS SJODIN AL, 1997, BIOGEOCHEMISTRY, V39, P327 SMITH RA, 1997, WATER RESOUR RES, V33, P2781 SUTER GW, 1993, ECOLOGICAL RISK ASSE VOGELMANN JE, 2001, PHOTOGRAMM ENG REM S, V67, P650 WICKHAM JD, 1999, LANDSCAPE ECOL, V14, P137 WICKHAM JD, 2000, J AM WATER RESOUR AS, V36, P1417 WICKHAM JD, 2002, COMPUT ELECTRON AGR, V37, P15 WICKHAM JD, 2002, ECOL APPL, V12, P93 0921-2973 Landsc. Ecol.ISI:0001837703000081US EPA, Natl Exposure Res Lab, Res Triangle Pk, NC 27711 USA. US Forest Serv, Forestry Sci Lab, Res Triangle Pk, NC 27709 USA. ONeill Inc, Oak Ridge, TN 37831 USA. US EPA, Natl Exposure Res Lab, Las Vegas, NV 89119 USA. Wickham, JD, US EPA, Natl Exposure Res Lab, MD 243-05, Res Triangle Pk, NC 27711 USA.Englishڽ7 Wiens, JohnA2013AIs landscape sustainability a useful concept in a changing world? 1047-1052Landscape Ecology286Springer NetherlandseClimate change Ecosystem services Land use change Landscape structure Scale Sustainability Thresholds 2013/07/01+http://dx.doi.org/10.1007/s10980-012-9801-9 0921-2973Landscape Ecol10.1007/s10980-012-9801-9Englisho<7 Wiens, J. A.1992!What is landscape ecology, really149-150Landscape Ecology73Editorial MaterialSep://A1992JW40100001 IISI Document Delivery No.: JW401 Times Cited: 30 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1992JW40100001=WIENS, JA, COLORADO STATE UNIV,DEPT BIOL,FT COLLINS,CO 80523.English;<7Z Wiens, J. A.1999-Landscape ecology: the science and the action103-103Landscape Ecology142Editorial MaterialApr://000079802500001 HISI Document Delivery No.: 187RV Times Cited: 0 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:000079802500001English\~?m Wiens, J. A.2008GAllerton Park 1983: the beginnings of a paradigm for landscape ecology?125-128Landscape Ecology23TIn 1983, a group of incipient landscape ecologists met to discuss the nature and future directions for landscape ecology. The themes emerging from this conference-movement of materials, organisms, and energy through a landscape; the genesis of landscape patterns; the effects of landscape structure on the spread of disturbances; and the potential contributions of landscape ecology to resource management-established a foundation for the development of landscape ecology in North America over the following decades. I discuss these contributions in the light of where landscape ecology is today."://WOS:000252636100001 Times Cited: 0WOS:000252636100001(10.1007/s10980-008-9195-x|ISSN 0921-2973 207 Wiens, J. A.2009>Landscape ecology as a foundation for sustainable conservation 1053-1065Landscape Ecology248SpringerXPrbo Conservat Sci, Petaluma C. A. U. S. A. Nature Conservancy, Arlington V. A. U. S. A.OConservation Cynomys ludovicianus Land use Landscape context Prairie dogs ScaleOct Landscape ecology and conservation share a common focus on places, but they differ in their perspectives about what is important about those places, and the integration of landscape ecology into conservation is far from complete. I consider four ways in which landscape ecology can contribute to conservation. First, protected areas that are established for conservation are not stand-alone isolates. They exist in the context of broader landscape mosaics, which may encourage or discourage movements of individuals into and out of an area. Second, the landscape surroundings of a preserve may contain threats to the biodiversity within the preserve, many of them consequences of human activities. In combination, these relationships with the surroundings may make the "effective area" of a preserve different from that shown on a map. Third, the scale of an administrative area or of management action may not coincide with the scales of populations, disturbances, or ecological processes, creating challenges to both landscape ecology and conservation. Finally, landscapes encompass people and their activities; sustainability of conservation requires consideration of the tradeoffs between human uses and the biodiversity values of a landscape. I illustrate these four themes with a case study of the management of prairie dogs (Cynomys ludovicianus) in the Great Plains of North America, where the tensions between conservation and human land uses are particularly high. Ecologists and conservationists consider prairie dogs as keystone species in these grassland ecosystems and primary targets for conservation, but many private landowners regard them as varmints that consume valuable livestock forage and degrade rangeland condition. Effective conservation of functioning grasslands must include prairie dogs, and this in turn requires that the issues be addressed in terms of the biological, social, and cultural features of entire landscapes. Important as they are, areas protected for conservation cannot by themselves stem the tide of global biodiversity loss. The perspective must be broadened to include the landscapes where people live and work, recognizing the dynamic nature of landscapes and the factors driving land-use change. Landscape ecologists must work together to overcome the cultural differences between their disciplines, and between academic science and conservation practice and management. It can, and must, be done.://000269913600006XISI Document Delivery No.: 495RV Times Cited: 2 Cited Reference Count: 55 Wiens, John A. 0921-2973 DORDRECHT2009 Landsc. Ecol.ISI:000269913600006Landscape ecologyZWiens, JA, PRBO Conservat Sci, 3820 Cypress Dr 11, Petaluma, CA 94954 USA. jwiens@prbo.org10.1007/s10980-008-9284-xEnglish?Wiens, J.A. B.T. Milne1989^Scaling of 'landscape' in landscape ecology, or, landscape ecology from a beetle's perspective87-96Landscape Ecology32<landscape, fractals, grassland, pattern and process, scalingResearch performed on microlandscapes embodies the essence of landscape ecology by focusing on the ecological consequences of the mosaic structure of different landscape elements. As an illustration, observations and simulations were used to test whether the fractal structure of grassland microlandscapes affected the movement patterns of tenebrionid beeetles in natural environments. The significant tendency of beetles to avoid 1 m^2 cells with fractal dimensions of 1.85 to 1.89 (indicating the area-filling tendency of bare ground) demonstrated the role of landscape structure as a modifier of beetle movements or diffusion in heterogeneous landscapes. Experiments in microlandscapes may accelerate the development of quantitative conceptual frameworks applicable to landscapes at all scales. <7 Wiersma, Y. F.2007YThe effect of target extent on the location of optimal protected areas networks in Canada 1477-1487Landscape Ecology2210ecoregions ecozones protected areas representative networks redundancy reserve location scaling spatial scale CAPE FLORISTIC REGION INSULAR BIOGEOGRAPHY LANDSCAPE ECOLOGY RESERVE SELECTION SOUTH-AFRICA CONSERVATION MAMMALS PARKS IRREPLACEABILITY DISTRIBUTIONSArticleDecVarious jurisdictions in Canada are currently undertaking, or have recently completed, planning exercises as part of implementation and expansion of representative reserve networks (networks of provincial parks, national parks, ecological reserves, etc.). These exercises have resulted in recommendations to governments about which areas of land should be set aside as protected areas, and different levels of government have been involved in the process of land acquisition. In some cases, planning exercises have included implementation of new protected areas to complement existing reserve networks. Many of these exercises have applied principles such as complementarity, using heuristic algorithms that are well-described in the literature. These planning exercises may be conducted within politically or ecologically bounded target regions of varying extents. Here, I develop candidate locations for representative reserve areas for disturbance-sensitive mammals across Canada. I use ecologically bounded regions (within the national boundaries of Canada) at three different levels of spatial hierarchy: mammal provinces, ecozones, and ecoregions. I show that the extent of the target region has an effect on the minimum number of protected areas required to achieve representation; a larger region requires fewer protected areas than the sum of the protected areas required to represent its component regions at a lower level of spatial hierarchy. The results illustrate that selection of sites for inclusion in a reserve network is highly scale-dependent, and different spatial extents in the target regions may introduce inefficiencies or redundancies in selecting representative protected areas.://000250632100007]ISI Document Delivery No.: 227BL Times Cited: 0 Cited Reference Count: 45 Wiersma, Yolanda F. 0921-2973 Landsc. Ecol.ISI:000250632100007Mem Univ Newfoundland, Dept Biol, St John, NF A1B 3X9, Canada. Univ Guelph, Dept Integrat Biol, Guelph, ON N1G 2W1, Canada. Wiersma, YF, Mem Univ Newfoundland, Dept Biol, St John, NF A1B 3X9, Canada. ywiersma@mun.caEnglish<7)Wiersma, Y. F. Nudds, T. D. Rivard, D. H.2004Models to distinguish effects of landscape patterns and human population pressures associated with species loss in Canadian national parks773-786Landscape Ecology197biogeography; extirpations; GIS; human population; land cover; land use; landscape thresholds; mammals; minimum reserve area; protected areas INSULAR BIOGEOGRAPHY; FAUNAL COLLAPSE; PROTECTED AREAS; GAME RESERVES; HUMAN DENSITY; HABITAT LOSS; EXTINCTION; MAMMALS; CORRIDORS; RICHNESSArticle,It is widely accepted that large protected areas are required to effectively conserve historical species composition. However, recent analyses of mammal species loss in Canadian and African national parks contradict earlier conclusions that extent of local extinctions (i.e., extirpations) is strongly inversely related to park size, suggesting that park size alone is inadequate to predict reserve designs that may sustain biodiversity. To plan protected areas that will meet conservation goals, reserve-design models that incorporate other landscape-scale factors in addition to reserve area are needed; potential factors include the types and intensity of land use and habitat change, together with land cover types, in and around parks. Additionally, human population size around parks, and visitor density in parks may affect species loss. We quantified land use, land cover, and human population in and around 24 Canadian national parks to model effects of human disturbance and changes in natural habitats on known mammal extirpations. Multiple regression models were compared using the Akaike Information Criterion (AIC(c)). The most parsimonious model (AIC(c) weighting w(i) = 0.5391) emphasized effective habitat area in and around parks and not visitor numbers nor human population size around parks. Our model suggests that parks with as little as 3140 km(2) of effective habitat area inside may be large enough to conserve historical mammal species composition if they are also surrounded by at least 18 000 km(2) of effective habitat within 50 km of park boundaries.://000226384000006 w ISI Document Delivery No.: 888OL Times Cited: 1 Cited Reference Count: 63 Cited References: 1994, PARKS CANADA GUIDING 1998, STATE PARKS 1997 REP *GEOM INT, 1996, PUK NAT PARK EC CONS ADAMS IT, 1992, UNPUB FEASIBILITY ST ANDERSON DR, 2001, J WILDLIFE MANAGE, V65, P373 APLET GH, 1999, PRACTICAL APPROACHES, P71 ATAURI JA, 2001, LANDSCAPE ECOL, V16, P147 BANFIELD AWF, 1974, MAMMALS CANADA BEDNARCZUK E, 2003, THESIS U GUELPH GUEL BEIER P, 1998, CONSERV BIOL, V12, P1241 BRASHARES JS, 2001, P ROY SOC LOND B BIO, V268, P2473 BURKEY TV, 1995, BIOL CONSERV, V71, P107 BURNHAM KP, 1998, MODEL SELECTION INFE COLE DN, 1987, P NAT WILD RES C ISS, P135 COPPEDGE BR, 2001, ECOL APPL, V11, P47 DIAMOND JM, 1975, BIOL CONSERV, V7, P129 FAHRIG L, 1997, J WILDLIFE MANAGE, V61, P603 FORMAN RTT, 2003, ROAD ECOLOGY SCI SOL FOSTER DR, 2002, J BIOGEOGR, V29, P1337 GLENN SM, 1989, J BIOGEOGR, V16, P261 GRIGORIEW P, 1985, 4 U WAT GU WD, 2002, LANDSCAPE ECOL, V17, P699 GURD DB, 1999, J BIOGEOGR, V26, P973 GURD DB, 2001, CONSERV BIOL, V15, P1355 HARCOURT AH, 2001, BIODIVERS CONSERV, V10, P1011 HOBSON KA, 2002, CONSERV BIOL, V16, P1530 HUMPHREYS WF, 1982, J BIOGEOGR, V9, P391 HUNT PD, 1998, CONSERV BIOL, V12, P1377 JALKOTZY MG, 1997, EFFECTS LINEAR DEV W KEITT TH, 1997, CONSERV ECOL, V1 LANDRY M, 2001, G WRIGHT FORUM, V18, P13 MACARTHUR RH, 1967, THEORY ISLAND BIOGEO MALANSON GP, 1999, DIVERS DISTRIB, V5, P27 MANN CC, 1995, SCIENCE, V270, P1428 MCGARIGAL K, 1995, PNWGTR351 US FOR SER MILLER JN, 1997, LANDSCAPE ECOL, V12, P137 MURPHY EC, 1998, J WILDLIFE MANAGE, V62, P1359 NAVEH Z, 1984, LANDSCAPE ECOLOGY TH NEWMARK WD, 1995, CONSERV BIOL, V9, P512 NEWMARK WD, 1996, CONSERV BIOL, V10, P1549 NEYNIFLE M, 2000, CONSERV BIOL, V14, P893 NOSS RF, 1986, ENVIRON MANAGE, V10, P299 PARKS SA, 2002, CONSERV BIOL, V16, P800 RANTA P, 1998, BIODIVERS CONSERV, V7, P385 RIVARD DH, 2000, CONSERV BIOL, V14, P1099 SCHREIBER RK, 1977, AM MIDL NAT, V97, P504 SIMBERLOFF D, 1987, CONSERV BIOL, V1, P63 SIMBERLOFF D, 1992, CONSERV BIOL, V6, P493 SKIBICKI AJ, 1995, 6 U WAT DEP CAN HER SOULE ME, 1979, BIOL CONSERV, V15, P259 TURNER MG, 2001, LANDSCAPE ECOLOGY TH VASARHELYI C, 2001, P ANN M PARKS RES FO, P267 VIRGOS E, 2001, J BIOGEOGR, V28, P381 WAGNER HH, 2001, LANDSCAPE ECOL, V16, P121 WALTON M, 1998, LINKING PROTECTED AR, P552 WHITE GC, 2001, MODELING NATURAL RES, P35 WICKHAM JD, 2000, LANDSCAPE ECOL, V15, P495 WIERSMA YF, 2001, J BIOGEOGR, V28, P447 WITH KA, 1997, OIKOS, V78, P151 WITH KA, 2001, BIOL CONSERV, V100, P75 WOODROFFE R, 1998, SCIENCE, V280, P2126 ZAR JH, 1999, BIOSTATISTICAL ANAL ZORN P, 2001, CONSERV BIOL, V15, P353 0921-2973 Landsc. Ecol.ISI:000226384000006Univ Guelph, Dept Zool, Guelph, ON N1G 2W1, Canada. Dept Canadian Heritage, Hull, PQ K1A 0M5, Canada. Wiersma, YF, Univ Guelph, Dept Zool, Guelph, ON N1G 2W1, Canada. ywiersma@uoguelph.caEnglishڽ7 0Wilkinson, ElliotB Branch, LynC Miller, DeborahL2013RFunctional habitat connectivity for beach mice depends on perceived predation risk547-558Landscape Ecology283Springer NetherlandsFunctional connectivity Predation risk Beach mice Gap crossing Landscape restoration Fragmentation Animal movement Santa Rosa Island Florida 2013/03/01+http://dx.doi.org/10.1007/s10980-013-9858-0 0921-2973Landscape Ecol10.1007/s10980-013-9858-0English<7 -Williams, D. M. Quinn, A. C. D. Porter, W. F.2012]Landscape effects on scales of movement by white-tailed deer in an agricultural-forest matrix45-57Landscape Ecology271first-passage time gps collars landscape structure scales of movement seasonality white-tailed deer animal movement 1st-passage time parturition dispersal mortality behavior pattern ranges search modelsJan]Understanding how organisms respond to landscape heterogeneity is foundational to landscape ecology. We characterized seasonal scales of movement of white-tailed deer (Odocoileus viginianus) in an agricultural-forest matrix using first-passage time analysis (FPT) for 62 GPS-collared individuals. We investigated whether those scales were driven by demographic or landscape features. We found FPT for each individual across all seasons was typically dominated by a peak in variance of FPT/area at scales (radii) from 425 to 1,675 m. These peaks occurred at scales consistent with seasonal space use. We observed additional lower magnitude peaks at larger scales (3,000-6,000 m) and small scales (25-150 m). Peaks at larger scales were associated with seasonal migrations and dispersal events. Small scale peaks may represent resting or foraging behavior. Female movements were organized at smaller scales than males in the spring/summer season. Models relating landscape features to movement scales suggest that deer perceive and move within the landscape differently as the roles of dominant land-cover types shift seasonally. During winter, configuration (interspersion/juxtaposition) of land-cover types is more important to deer than during spring/summer and fall. During spring/summer and fall, movement behavior may be dictated by reproductive and harvest activities.://000298228300004-864HI Times Cited:0 Cited References Count:40 0921-2973Landscape EcolISI:000298228300004Williams, DM Michigan State Univ, Dept Fisheries & Wildlife, E Lansing, MI 48824 USA Michigan State Univ, Dept Fisheries & Wildlife, E Lansing, MI 48824 USA Michigan State Univ, Dept Fisheries & Wildlife, E Lansing, MI 48824 USADOI 10.1007/s10980-011-9664-5English,ڽ7 Williams, MarkA Baker, WilliamL2013Variability of historical forest structure and fire across ponderosa pine landscapes of the Coconino Plateau and south rim of Grand Canyon National Park, Arizona, USA297-310Landscape Ecology282Springer NetherlandsGeneral Land Office survey Forest reconstruction Mixed-severity fire Piñon–juniper woodlands Topography Tree density Basal area Fire severity 2013/02/01+http://dx.doi.org/10.1007/s10980-012-9835-z 0921-2973Landscape Ecol10.1007/s10980-012-9835-zEnglishj|7S Wilson, J. B. King, W. M. G.1995DHuman-Mediated Vegetation Switches as Processes in Landscape Ecology191-196Landscape Ecology104`switch boundary ecotone landscape mowing trampling human effects positive feedback garden designAugSwitches are processes in which there is positive feedback between vegetation and environment. Landscape features can be created and modified by switches. The concept has previously been used with physical factors and non-human animals as the switch mediator, i.e. the factor which the vegetation modifies and which in turn affects the vegetation. Here, the switch concept is extended to include some types of human behaviour as possible switch mediators. With this extension, the switch concept can explain the impact on the landscape of some types of human behaviour. Examples are given of the behaviour of mower drivers, mowing up to a boundary which they create and/or maintain, and of walkers trampling tracks which they create and/or maintain. Other possibilities are discussed briefly. It is concluded that the concept of a human-mediated switch can unify the study of human behaviour, vegetation processes and landscape ecology.://A1995RP98800001,Rp988 Times Cited:8 Cited References Count:0 0921-2973ISI:A1995RP988000019Wilson, Jb Univ Otago,Dept Bot,Pob 56,Dunedin,New ZealandEnglish w|7.Wilson, T. L. Johnson, E. J. Bissonette, J. A.2009nRelative importance of habitat area and isolation for bird occurrence patterns in a naturally patchy landscape351-360Landscape Ecology243breeding bird fragmentation metapopulation dynamics sagebrush obligate mountain meadow utah USA forest fragmentation connectivity populations movement ecologyMarThere is debate among ecologists about whether total habitat area or patch arrangement contributes most to population and/or community responses to fragmented or patchy landscapes. We tested the relative effects of patch area and isolation for predicting bird occurrence in a naturally patchy landscape in the Bear River Mountains of Northern Utah, USA. We selected focal patches (mountain meadows) ranging in elevation from 1,920 to 2,860 m and in size from 0.6 to 182 ha. Breeding birds were sampled in each focal meadow during the summers of 2003 and 2004 using variable-distance point transects. Logistic regression and likelihood-based model selection were used to determine the relationship between likelihood of occurrence of three bird species (Brewer's sparrow, vesper sparrow, and white-crowned sparrow) and area, isolation, and proximity metrics. We used model weights and model-averaged confidence intervals to assess the importance of each predictor variable. Plots of area versus isolation were used to evaluate complex relationships between the variables. We found that meadow area was the most important variable for explaining occurrence for two species, and that isolation was the most important for the other. We also found that the absolute distance was more appropriate for evaluating isolation responses than was the species-specific proximity metric. Our findings add clarity to the debate between ecologists regarding the relative importance of area and isolation in species responses to patchy landscapes.://000263419500005-408EY Times Cited:0 Cited References Count:34 0921-2973ISI:000263419500005YWilson, TL Utah State Univ, Coll Nat Resources, Dept Wildland Resources, 5230 Old Main Hill, Logan, UT 84322 USA Utah State Univ, Coll Nat Resources, Dept Wildland Resources, Logan, UT 84322 USA Area Ecol Program, Bend, OR 97702 USA Utah State Univ, Coll Nat Resources, US Geol Survey, Utah Cooperat Fish & Wildlife Res Unit, Logan, UT 84322 USADoi 10.1007/S10980-008-9309-5English+? Wimberly, Michael2012MLyme disease: a quintessential connection between ecosystems and human Health 1383-1384Landscape Ecology279Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9768-6 0921-297310.1007/s10980-012-9768-6 <7Wimberly, M. C.2006cSpecies dynamics in disturbed landscapes: When does a shifting habitat mosaic enhance connectivity?35-46Landscape Ecology211(connectivity; critical behavior; disturbance; extinction; fragmentation; patch dynamics; percolation; threshold GAP-CROSSING DECISIONS; EXTINCTION THRESHOLDS; FRACTAL LANDSCAPES; METAPOPULATION PERSISTENCE; SUCCESSIONAL LANDSCAPES; WESTERN OREGON; FRAGMENTATION; FIRE; DEFORESTATION; CONSEQUENCESArticleJanAlthough landscape ecology emphasizes the effects of spatial pattern on ecological processes, most neutral models of species-habitat relationships have treated habitat as a static constraint. Do the working hypotheses derived from these models extend to real landscapes where disturbances create a shifting mosaic? A spatial landscape simulator incorporating vegetation dynamics and a metapopulation model was used to compare species in static and dynamic landscapes with identical habitat amounts and spatial patterns. The main drivers of vegetation dynamics were stand-replacing disturbances, followed by gradual change from early-successional to old-growth habitats. Species dynamics were based on a simple occupancy model, with dispersal simulated as a random walk. As the proportion of available habitat (p) decreased from 1.0, species occupancy generally declined more rapidly and reached extinction at higher habitat levels in dynamic than in static landscapes. However, habitat occupancy was sometimes actually higher in dynamic landscapes than in static landscapes with similar habitat amounts and patterns. This effect was most pronounced at intermediate amounts of habitat (p = 0.3-0.6) for mobile species that had high colonization rates, but were unable to cross non-habitat patches. Differences between static and dynamic landscapes were contingent upon the initial metapopulation size and the shapes of disturbances and the resulting habitat patterns. Overall, the results demonstrate that dispersal-limited species exhibit more pronounced critical behavior in dynamic landscapes than is predicted by simple neutral models based on static landscapes. Thus, caution should be exercised in extending generalizations derived from static landscape models to disturbance-driven landscape mosaics.://000235887300004 ISI Document Delivery No.: 020DD Times Cited: 0 Cited Reference Count: 39 Cited References: AKCAKAYA HR, 2004, CONSERV BIOL, V18, P526 BAKKER VJ, 2004, CONSERV BIOL, V18, P689 BASCOMPTE J, 1996, J ANIM ECOL, V65, P465 BOUGHTON D, 2002, CONSERV ECOL, V6 BOYCHUK D, 1997, ECOL MODEL, V95, P145 BROOKS TM, 1999, CONSERV BIOL, V13, P1140 COWLISHAW G, 1999, CONSERV BIOL, V13, P1183 DESROCHERS A, 1997, CONSERV BIOL, V11, P1204 FAHRIG L, 1991, QUANTITATIVE METHODS, P417 FAHRIG L, 1998, ECOL MODEL, V105, P273 FAHRIG L, 2002, ECOL APPL, V12, P346 FLATHER CH, 2002, AM NAT, V159, P40 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GARDNER RH, 1991, ECOTONES ROLE LANDSC, P76 GLENN EM, 2004, J WILDLIFE MANAGE, V68, P33 GU WD, 2002, LANDSCAPE ECOL, V17, P699 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 HANSKI I, 1999, OIKOS, V87, P209 HEYERDAHL EK, 2001, ECOLOGY, V82, P660 HILL MF, 1999, ECOL LETT, V2, P121 JOHNSON MP, 2000, OIKOS, V88, P67 JOHST K, 2002, OIKOS, V98, P263 KEITT TH, 1997, CONSERV ECOL, V1 KEYMER JE, 2000, AM NAT, V156, P478 MATLACK GR, 2004, J ECOL, V92, P1025 MOLONEY KA, 1996, ECOLOGY, V77, P375 PICKETT STA, 1985, ECOLOGY NATURAL DIST RICHARDS WH, 2002, CONSERV BIOL, V16, P1409 SCHUMAKER NH, 2004, ECOL APPL, V14, P381 TILMAN D, 1994, NATURE, V371, P65 VANWAGNER CE, 1978, CANADIAN J FOREST RE, V8, P220 WATT AS, 1947, J ECOL, V35, P1 WIMBERLY MC, 2001, ECOLOGY, V82, P1443 WIMBERLY MC, 2002, CAN J FOREST RES, V32, P1316 WIMBERLY MC, 2004, ECOL MODEL, V180, P41 WITH KA, 1999, CONSERV BIOL, V13, P314 WITH KA, 1999, LANDSCAPE ECOL, V14, P73 WU JG, 1994, ECOL MONOGR, V64, P447 WU JG, 1995, Q REV BIOL, V70, P439 0921-2973 Landsc. Ecol.ISI:000235887300004Univ Georgia, Warnell Sch Forest Resources, Athens, GA 30602 USA. Wimberly, MC, Univ Georgia, Warnell Sch Forest Resources, Athens, GA 30602 USA. wimberly@forestry.uga.eduEnglishr<7Wimberly, M. C. Ohmann, J. L.2004{A multi-scale assessment of human and environmental constraints on forest land cover change on the Oregon (USA) coast range631-646Landscape Ecology196Rdisturbance; environmental heterogeneity; forest fragmentation; forest management; habitat loss; human impacts; land ownership; watersheds PRE-EUROPEAN SETTLEMENT; WISCONSIN PINE-BARRENS; COARSE WOODY DEBRIS; LANDSCAPE STRUCTURE; HABITAT DESTRUCTION; PACIFIC-NORTHWEST; GRADIENT ANALYSIS; SPATIAL-ANALYSIS; EXTINCTION DEBT; WESTERN OREGONArticleAugHuman modification of forest habitats is a major component of global environmental change. Even areas that remain predominantly forested may be changed considerably by human alteration of historical disturbance regimes. To better understand human influences on the abundance and pattern of forest habitats, we studied forest land cover change from 1936 to 1996 in a 25 000 km(2) landscape in the Oregon ( USA) Coast Range. We integrated historical forest survey data and maps from 1936 with satellite imagery and GIS data from 1996 to quantify changes in major forest cover types. Change in the total area of closed-canopy forests was relatively minor, decreasing from 68% of the landscape in 1936 to 65% in 1996. In contrast, large-conifer forests decreased from 42% in 1936 to 17% in 1996, whereas small-conifer forests increased from 21% of the landscape in 1936 to 39% in 1996. Linear regression models were used to predict changes in the proportion of large conifer forest as a function of socioeconomic and environmental variables at scales of subbasins ( mean size = 1964 km(2), n = 13), watersheds (mean size = 302 km(2), n = 83), and subwatersheds (mean size = 18 km(2), n = 1325). The proportion of land in private ownership was the strongest predictor at all three spatial scales ( partial R-2 values 0.57 - 0.76). The amounts of variation explained by other independent variables were comparatively minor. Results corroborate the hypothesis that differing management regimes on private and public ownerships have led to different pathways of landscape change. Furthermore, these distinctive trajectories are consistent over a broad domain of spatial scales.://000224100600005 U ISI Document Delivery No.: 857FC Times Cited: 6 Cited Reference Count: 57 Cited References: *INS CORP, 2001, SPLUS 6 US GUID ADDICOTT JF, 1987, OIKOS, V49, P340 ANDERSON MJ, 1999, J STAT COMPUT SIM, V62, P271 ANDREWS HJ, 1940, MISCELLANEOUS PUBLIC, V389 AXELSSON AL, 2002, LANDSCAPE ECOL, V17, P403 BLACK AE, 2003, ECOL APPL, V13, P51 COHEN WB, 2002, ECOSYSTEMS, V5, P122 CROW TR, 1999, LANDSCAPE ECOL, V14, P449 DALY C, 1994, J APPL METEOROL, V33, P140 DRAPEAU P, 2000, ECOL MONOGR, V70, P423 FRANKLIN JF, 1973, GTRPNW8 USDA FOR SER HALL FG, 1991, ECOLOGY, V72, P628 HALPERN CB, 1995, ECOL APPL, V5, P913 HARGIS CD, 1999, J APPL ECOL, V36, P157 HARMON ME, 1986, ADV ECOL RES, V15, P133 IMPARA PC, 1997, SPATIAL TEMPORAL PAT KENNEDY RSH, FOREST ECOLOGY MANAG KLINE JD, 2001, ECOSYSTEMS, V4, P3 LEGENDRE P, 1993, ECOLOGY, V74, P1659 LOEHLE C, 1996, ECOL APPL, V6, P784 LOMOLINO MV, 2000, ECOLOGY, V81, P1517 MANLY BF, 1991, RANDOMIZATION MONTE MARTIN KJ, 2002, FOREST SCI, V48, P255 MATLACK GR, 1994, ECOLOGY, V75, P1491 MCCOMB WC, 2002, FOREST SCI, V48, P203 MCGARIGAL K, 1995, ECOL MONOGR, V65, P235 MLADENOFF DJ, 1993, ECOL APPL, V3, P294 NAGAIKE T, 1999, LANDSCAPE URBAN PLAN, V43, P209 NETER J, 1989, APPL LINEAR REGRESSI OHMANN JL, 1998, ECOL MONOGR, V68, P151 OHMANN JL, 2002, CAN J FOREST RES, V32, P725 OLSON DH, 2001, WILDLIFE HABITAT REL, P187 PINDER JE, 1999, AM MIDL NAT, V142, P213 RADELOFF VC, 1999, CAN J FOREST RES, V29, P1649 RADELOFF VC, 2000, ECOL APPL, V10, P233 RADELOFF VC, 2001, FOREST SCI, V47, P229 RIPPLE WJ, 2000, BIOL CONSERV, V93, P127 ROBBINS WG, 1997, LANDSCAPES PROMISE O SPIES TA, 1988, ECOLOGY, V69, P1689 SPIES TA, 1994, ECOL APPL, V4, P555 SPIES TA, 2002, INTEGRATING LANDSCAP, P179 STANFIELD BJ, 2002, LANDSCAPE ECOL, V17, P685 TILMAN D, 1994, NATURE, V371, P65 TURNER MG, 1988, LANDSCAPE ECOL, V1, P241 TURNER MG, 1996, ECOL APPL, V6, P1150 VERBURG PH, 2000, ECOSYSTEMS, V3, P369 VITOUSEK PM, 1994, ECOLOGY, V75, P1861 VOGELMANN JE, 1995, CONSERV BIOL, V9, P439 WEAR DN, 1996, ECOL APPL, V6, P1173 WEAR DN, 1998, ECOSYSTEMS, V1, P575 WEAR DN, 1999, FOREST ECOL MANAG, V118, P107 WHITE MA, 1994, LANDSCAPE ECOL, V9, P191 WIENS JA, 1989, FUNCT ECOL, V3, P385 WIMBERLY MC, 2000, CONSERV BIOL, V14, P167 WIMBERLY MC, 2001, ECOLOGY, V82, P1443 WIMBERLY MC, 2002, CAN J FOREST RES, V32, P1316 WITH KA, 1995, ECOLOGY, V76, P2446 0921-2973 Landsc. Ecol.ISI:000224100600005Univ Georgia, Warnell Sch Forest Resources, Athens, GA 30602 USA. US Forest Serv, USDA, Pacific NW Res Stn, Corvallis, OR 97331 USA. Wimberly, MC, Univ Georgia, Warnell Sch Forest Resources, Athens, GA 30602 USA. wim-berly@smokey.forestry.uga.eduEnglish|? NWinn, N. Williamson, C. E. Abbitt, R. Rose, K. Renwick, W. Henry, M. Saros, J.2009[Modeling dissolved organic carbon in subalpine and alpine lakes with GIS and remote sensing807-816Landscape Ecology246JulFCurrent global trends in lake dissolved organic carbon (DOC) concentrations suggest a need for tools to more broadly measure and predict variation in DOC at regional landscape scales. This is particularly true for more remote subalpine and alpine regions where access is difficult and the minimal levels of anthropogenic watershed disturbance allow these systems to serve as valuable reference sites for long-term climate change. Here geographic information system (GIS) and remote sensing tools are used to develop simple predictive models that define relationships between watershed variables known to influence lake DOC concentrations and lake water color in the Absaroka-Beartooth Wilderness in Montana and Wyoming, USA. Variables examined include watershed area, topography, and vegetation cover. The resulting GIS model predicts DOC concentrations at the lake watershed scale with a high degree of accuracy (R (2) = 0.92; P a parts per thousand currency sign 0.001) by including two variables: vegetation coverage (representing sites of organic carbon fixation) and areas of low slope (0-5%) within the watershed (wetland sites of DOC production). Importantly, this latter variable includes not only surficially visible wetlands, but "cryptic" subsurface wetlands. Modeling with Advanced Land Imager satellite remote sensing data provided a weaker relationship with water color and DOC concentrations (R (2) = 0.725; P a parts per thousand currency sign 0.001). Model extrapolation is limited by small sample sizes but these models show promise in predicting lake DOC in subalpine and alpine regions.://000268248100008fWinn, Neil Williamson, Craig E. Abbitt, Robbyn Rose, Kevin Renwick, William Henry, Mary Saros, Jasmine 0921-2973ISI:00026824810000810.1007/s10980-009-9359-3<7 With, K. A.1994IUsing fractal analysis to assess how species perceive landscape structure25-36Landscape Ecology91cFRACTAL DIMENSION; GRASSLAND; GRASSHOPPERS; LANDSCAPE PERCEPTION; MICROLANDSCAPE; MOVEMENT PATTERNSArticleMarTo develop a species-centered definition of 'landscapes,' I suggest using a fractal analysis of movement patterns to identify the scales at which organisms are interacting with the patch structure of the landscape. Significant differences in the fractal dimensions of movement patterns of two species indicate that the species may be interacting with the patch structure at different scales. Fractal analysis therefore permits comparisons of 'landscape perceptions' of different species within the same environment. I tested the utility of this fractal application by analyzing the movement patterns of three species of acridid grasshoppers (Orthoptera) in a grassland mosaic. The largest species moved up to 6 times faster than the two smaller species, and species exhibited different responses to microlandscape structure within 25-m2 plots. Further, the largest species exhibited different responses to microlandscape structure in two pastures subjected to different intensities of cattle grazing. This species thus is able to integrate information on landscape structure at broad spatial scales. Fractal analysis of movement patterns revealed that the two small species had significantly more tortuous patterns than the larger species, which suggests that these species are interacting with patch structure at a finer scale of resolution than the large species. Fractal analysis can be used to identify the perceptive resolution of a species; that is, the spatial grain and extent at which they are able to perceive and respond to heterogeneity. Analysis of movement patterns across a range of spatial scale may reveal shifts in fractal dimension that reflect transitions in how species respond to the patch structure of the landscape at different scales.://A1994NC71800003 IISI Document Delivery No.: NC718 Times Cited: 91 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1994NC71800003AWITH, KA, OAK RIDGE NATL LAB,DIV ENVIRONM SCI,OAK RIDGE,TN 37831.English<7sWith, K. A. King, A. W.1999ODispersal success on fractal landscapes: a consequence of lacunarity thresholds73-82Landscape Ecology141dispersal critical thresholds habitat fragmentation fractals lacunarity analysis neutral landscape models percolation theory HABITAT FRAGMENTATION CONNECTIVITY ECOLOGY MODELS BIRDS HETEROGENEITY CONSERVATION ENVIRONMENTS EXTINCTION MAMMALSArticleFebHabitat fragmentation is expected to disrupt dispersal, and thus we explored how patch metrics of landscape structure, such as percolation thresholds used to define landscape connectivity, corresponded with dispersal success on neutral landscapes. We simulated dispersal as either a purely random process (random direction and random step lengths) or as an area-limited random walk (random direction, but movement limited to an adjacent cell at each dispersal step) and quantified dispersal success for 1000 individuals on random and fractal landscape maps across a range of habitat abundance and fragmentation. Dispersal success increased with the number of cells a disperser could search (m), but poor dispersers (m < 5) searching via area-limited dispersal on fractal landscapes were more successful at locating suitable habitat than random dispersers on either random or fractal landscapes. Dispersal success was enhanced on fractal landscapes relative to random ones because of the greater spatial contagion of habitat. Dispersal success decreased proportionate to habitat loss for poor dispersers (In = 1) on random landscapes, but exhibited an abrupt threshold at low levels of habitat abundance (p < 0.1) for area-limited dispersers (m ( 10) on fractal landscapes. Conventional metrics of patch structure, including percolation, did not exhibit threshold behavior in the region of the dispersal threshold. A lacunarity analysis of the gap structure of landscape patterns, however, revealed a strong threshold in the variability of gap sizes at low levels of habitat abundance (p < 0.1) in fractal landscapes, the same region in which abrupt declines in dispersal success were observed. The interpatch distances or gaps across which dispersers must move in search of suitable habitat should influence dispersal success, and our results suggest that there is a critical gap-size structure to fractal landscapes that interferes with the ability of dispersers to locate suitable habitat when habitat is rare. We suggest that the gap structure of landscapes is a more important determinant of dispersal than patch structure, although both are ultimately required to predict the ecological consequences of habitat fragmentation.://000079005100006 AISI Document Delivery No.: 173XM Times Cited: 64 Cited Reference Count: 39 Cited References: ALLAIN C, 1991, PHYS REV A, V44, P3552 ANDREN H, 1994, OIKOS, V71, P355 DOAK DF, 1992, THEOR POPUL BIOL, V41, P315 FAHRIG L, 1985, ECOLOGY, V66, P1762 FAHRIG L, 1988, THEOR POPUL BIOL, V34, P194 FAHRIG L, 1997, J WILDLIFE MANAGE, V61, P603 GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GARDNER RH, 1989, LANDSCAPE ECOL, V3, P217 GARDNER RH, 1991, QUANTITATIVE METHODS, P289 GARDNER RH, 1993, HUMANS COMPONENTS EC, P208 GARDNER RH, 1998, IN PRESS LANDSCAPE E GREENWOOD PJ, 1980, ANIM BEHAV, V28, P1140 GREENWOOD PJ, 1982, ANNU REV ECOL SYST, V13, P1 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 HANSSON L, 1991, BIOL J LINN SOC, V42, P89 KAREIVA P, 1990, PHILOS T ROY SOC B, V330, P175 LANDE R, 1987, AM NAT, V130, P624 MANDELBROT BB, 1983, FRACTAL GEOMETRY NAT ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 ONEILL RV, 1988, LANDSCAPE ECOL, V2, P63 OPDAM P, 1990, SPECIES DISPERSAL AG, P3 PEARSON SM, 1996, BIODIVERSITY MANAGED, P77 PICKETT STA, 1995, SCIENCE, V269, P331 PLOTNICK RE, 1993, LANDSCAPE ECOL, V8, P201 PLOTNICK RE, 1993, LECT MATH LIFE SCI P, V23, P207 PLOTNICK RE, 1996, PHYS REV E B, V53, P5461 SAUPE D, 1988, SCI FRACTAL IMAGES, P71 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 TAYLOR PD, 1993, OIKOS, V68, P571 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1991, QUANTITATIVE METHODS WALSH PD, 1996, J THEOR BIOL, V183, P351 WIENS JA, 1993, OIKOS, V66, P369 WIENS JA, 1997, OIKOS, V78, P257 WITH KA, IN PRESS CONSERVATIO WITH KA, 1995, ECOLOGY, V76, P2446 WITH KA, 1997, CONSERV BIOL, V11, P1069 WITH KA, 1997, OIKOS, V78, P151 WITH KA, 1997, OIKOS, V79, P219 0921-2973 Landsc. Ecol.ISI:000079005100006Bowling Green State Univ, Dept Biol Sci, Bowling Green, OH 43403 USA. With, KA, Bowling Green State Univ, Dept Biol Sci, Bowling Green, OH 43403 USA.English|? "With, Kimberly A. Pavuk, Daniel M.2011[Habitat area trumps fragmentation effects on arthropods in an experimental landscape system 1035-1048Landscape Ecology267AugThe effects of habitat area and fragmentation are confounded in many studies. Since a reduction in habitat area alone reduces patch size and increases patch isolation, many studies reporting fragmentation effects may really be documenting habitat-area effects. We designed an experimental landscape system in the field, founded on fractal neutral landscape models, to study arthropod community responses to clover habitat in which we adjusted the level of fragmentation independently of habitat area. Overall, habitat area had a greater and more consistent effect on morphospecies richness than fragmentation. Morphospecies richness doubled between 10 and 80% habitat, with the greatest increase occurring up to 40% habitat. Fragmentation had a more subtle and transient effect, exhibiting an interaction at intermediate levels of habitat only at the start of the study or in the early-season (June) survey. In these early surveys, morphospecies richness was higher in clumped 40-50% landscapes but higher in fragmented landscapes at 60-80% habitat. Rare or uncommon species are expected to be most sensitive to fragmentation effects, and we found a significant interaction with fragmentation at intermediate levels of habitat for these types of morphospecies in early surveys. Although the effects of fragmentation are expected to amplify at higher trophic levels, all trophic levels exhibited a significant fragmentation effect at intermediate levels of habitat in these early surveys. Predators/parasitoids were more sensitive to habitat area than herbivores, however. Thus, our results confirm that habitat area is more important than fragmentation for predicting arthropod community responses, at least in this agricultural system.!://WOS:000292705900011Times Cited: 0 0921-2973WOS:00029270590001110.1007/s10980-011-9627-x0<7&With, K. A. Schrott, G. R. King, A. W.2006]The implications of metalandscape connectivity for population viabilityin migratory songbirds157-167Landscape Ecology2124birds; demographic model; habitat loss and fragmentation; immigration; landscape dynamics; neutral landscape models; source-sink dynamics HABITAT-SPECIFIC DEMOGRAPHY; NEOTROPICAL MIGRANT BIRDS; LANDSCAPE CONNECTIVITY; REPRODUCTIVE SUCCESS; NESTING SUCCESS; WOOD THRUSHES; SINKS; DYNAMICS; DISPERSAL; SURVIVALArticleFebLandscape connectivity is considered important for species persistence, but linkages among landscape populations (metalandscape connectivity) may be necessary to ensure the long-term viability of some migratory songbirds at a broader regional scale. Because of regional source-sink dynamics, these species can maintain steady populations within extensively fragmented landscapes (landscape sinks) owing to high levels of immigration from source landscapes. We undertook a modeling study to identify the conditions under which immigration, an index of metalandscape connectivity, could rescue declining populations of songbirds in heavily disturbed landscapes. In general, low to moderate levels of immigration (m = 0-20%) were sufficient to rescue species with low edge-sensitivity in landscapes where < 70% habitat had been destroyed. At the other extreme, moderate to high levels of immigration (m = 11-40%) were usually required to rescue highly edge-sensitive species in these same landscapes. Very high levels of immigration (m > 40%) were required to rescue highly edge-sensitive species in extensively fragmented landscapes that had lost > 50% habitat, or when any landscape lost >= 50% habitat gradually over a period of 100 or more years (r = 0.5% habitat lost/year). Paradoxically higher levels of immigration were thus necessary to offset population declines when habitat was lost gradually than when it was lost quickly, where population response lagged behind landscape change. This implies that the importance of metalandscape connectivity for population viability may not be fully appreciated in landscapes undergoing rapid rates of change. Natural immigration rates for migratory songbirds match the very high levels (> 40%) we found necessary to sustain populations in heavily disturbed landscapes, which underscores the importance of metalandscape connectivity for the continued persistence of many migratory songbirds in the face of widespread habitat loss and fragmentation.://000235866400001 (ISI Document Delivery No.: 019WC Times Cited: 0 Cited Reference Count: 45 Cited References: ANDERS AD, 1997, CONSERV BIOL, V11, P698 BRAWN JD, 1996, ECOLOGY, V77, P3 DONOVAN TM, 1995, CONSERV BIOL, V9, P1380 DONOVAN TM, 1995, CONSERV BIOL, V9, P1396 DONOVAN TM, 1997, ECOLOGY, V78, P2064 FAUTH PT, 2000, AUK, V117, P194 FAUTH PT, 2000, LANDSCAPE ECOL, V15, P621 FAUTH PT, 2001, CONSERV BIOL, V15, P523 FLASPOHLER DJ, 2001, ECOL APPL, V11, P32 FLATHER CH, 1996, ECOLOGY, V77, P28 FREEMARK K, 2002, APPL LANDSCAPE ECOLO, P58 GARDNER RH, 1999, LANDSCAPE ECOLOGICAL, P280 GREENWOOD PJ, 1980, ANIM BEHAV, V28, P1140 HANSKI I, 1999, METAPOPULATION ECOLO HOLMES RT, 1996, J ANIM ECOL, V65, P183 HOOVER JP, 1995, AUK, V112, P146 IMS RA, 1995, MOSAIC LANDSCAPES EC, P85 IMS RA, 1997, METAPOPULATION BIOL, P247 KARR JR, 1990, AM NAT, V136, P277 MOILANEN A, 2002, ECOLOGY, V83, P1131 MOREIRA F, 2001, LANDSCAPE ECOL, V16, P175 MORTON ML, 1991, ORNIS SCAND, V22, P98 MURPHY MT, 2001, ECOLOGY, V82, P1304 NOSS RF, 1991, LANDSCAPE LINKAGES B, P23 ORELL M, 1999, J EVOLUTION BIOL, V12, P283 PLISSNER JH, 1996, ANIM BEHAV 6, V51, P1307 PORNELUZI PA, 1999, CONSERV BIOL, V13, P1151 PULLIAM HR, 1988, AM NAT, V132, P652 PULLIAM HR, 1991, AM NAT S, V137, P50 RICKLEFS RE, 1992, ECOLOGY CONSERVATION, P537 ROBINSON SK, 1995, SCIENCE, V267, P1987 ROTH RR, 1993, AUK, V110, P37 SCHROTT GR, 2005, ECOL APPL, V15, P493 SPIES TA, 1994, ECOL APPL, V4, P555 STENNING MJ, 1988, J ANIM ECOL, V57, P307 TAYLOR PD, 1993, OIKOS, V68, P571 TISCHENDORF L, 2000, OIKOS, V90, P7 TRINE CL, 1998, CONSERV BIOL, V12, P576 WEBSTER MS, 2002, TRENDS ECOL EVOL, V17, P76 WIENS JA, 2002, APPL LANDSCAPE ECOLO, P3 WITH KA, 1997, CONSERV BIOL, V11, P1069 WITH KA, 1997, OIKOS, V78, P151 WITH KA, 2001, BIOL CONSERV, V100, P75 WITH KA, 2002, APPL LANDSCAPE ECOLO, P105 WITH KA, 2004, ECOLOGY GENETICS EVO, P23 0921-2973 Landsc. Ecol.ISI:000235866400001Kansas State Univ, Div Biol, Manhattan, KS 66506 USA. Oak Ridge Natl Lab, Div Environm Sci, Oak Ridge, TN 37831 USA. With, KA, Kansas State Univ, Div Biol, Ackert Hall, Manhattan, KS 66506 USA. kwith@ksu.eduEnglish |7Withey, J. C. Marzluff, J. M.2009gMulti-scale use of lands providing anthropogenic resources by American Crows in an urbanizing landscape281-293Landscape Ecology242resource use utilization distribution urban ecology spatial autocorrelation habitat selection american crow corvus brachyrhynchos washington state exurban development nest predators seattle region conservation songbirds dynamics ecology consequences campgrounds communitiesFebThe conversion of forests and farmlands to human settlements has negative impacts on many native species, but also provides resources that some species are able to exploit. American Crows (Corvus brachyrhynchos), one such exploiter, create concern due to their impact as nest predators, disease hosts, and cultural harbingers of evil. We used various measures of crow abundance and resource use to determine crows' response to features of anthropogenic landscapes in the Puget Sound region of the United States. We examined land cover and land use composition at three spatial scales: study sites (up to 208 ha), crow home ranges within sites (18.1 ha), and local land cover (400 m(2)). At the study site and within-site scales crow abundance was strongly correlated with land cover providing anthropogenic resources. In particular, crows were associated with the amount of 'maintained forest' cover, and were more likely to use grass and shrub cover than forest or bare soil cover. Although crows did not show a generalized response to an edge variable, they exhibited greater use of patchy habitat created by human settlements than of native forests. Radio-tagged territorial adults used resources within their home ranges relatively evenly, suggesting resource selection had occurred at a larger spatial scale. The land conversion pattern of new suburban and exurban settlements creates the mix of impervious surfaces and maintained vegetation that crows use, and in our study area crow populations are expected to continue to increase.://000262828900011-399WB Times Cited:0 Cited References Count:57 0921-2973ISI:000262828900011Withey, JC Lewis & Clark Coll, Dept Biol, 0615 SW Palatine Hill Rd, Portland, OR 97219 USA Univ Washington, Coll Forest Resources, Seattle, WA 98195 USADoi 10.1007/S10980-008-9305-9English<74Wolfert, H. P. Hommel, Pwfm Prins, A. H. Stam, M. H.2001mThe formation of natural levees as a disturbance process significant to the conservation of riverine pastures47-57Landscape Ecology17 supplement 1disturbance meandering natural levee overbank deposition riverine grassland river rehabilitation River Dinkel The Netherlands RHONE RIVER SUCCESSION VEGETATION FLOODPLAIN CANADAArticleDisturbances and patch dynamics are inherent to many ecosystems of the world, especially in the riparian zone. This paper describes the influence of natural levee overbank deposition on riverine grasslands along the meandering River Dinkel (The Netherlands). Here, the rare vegetation type Diantho-Amerietum, characterised by Dianthus deltoides, Thymus pulegioides, Pimpinella saxifraga and Galium verum, has been identified as important to nature conservation. Diantho-Armerietum shows a strong preference for dry, nutrient poor, sandy and relatively young soils, with an elevation approximately 30-50 cm above bankfull discharge level, corresponding to a flooding frequency of 2-3 times per year. The lower zones are strongly influenced by nutrient-rich water, whereas the higher zones are vulnerable to soil acidification. In the intermediate zone, soil development may be reset due to the supply of calcium, adsorbed to recently deposited levee sands. Since deposition rates will decrease with increasing levee heights, new levees are regularly needed to stop the decline of this floriferous vegetation type. The formation of new natural levees is favoured by the occurrence of meander cutoffs, causing a cyclic succession of landforms along the river. Therefore a conservation strategy for this vegetation type needs to aim at the rehabilitation of the natural levee disturbance process, in conjunction with encouraging the meandering of the river.://000176041000005 TISI Document Delivery No.: 559TG Times Cited: 0 Cited Reference Count: 33 Cited References: *PROV OV, 1993, BEH BEH RES DINK TUS BORNETTE G, 1994, VEGETATIO, V110, P171 BOS F, 1981, 110 LANDB VAKGR VEG BRAVARD JP, 1986, OIKOS, V47, P92 BRIERLEY GJ, 1997, SEDIMENT GEOL, V114, P1 BROCK TCM, 1987, ARCH HYDROBIOL BEIH, V27, P57 BURRIGTER E, 1980, ABHANDLUNGEN LANDESM, V42, P4 CAZANACLI D, 1998, GEOMORPHOLOGY, V25, P43 FINCK P, 1998, SCHRIFTENREIHE LANDS, V56 GONGGRIJP GP, 1976, DINKELDAL RAPPORT HOMMEL PWF, 1990, 23 DLO STAR CENTR HOMMEL PWF, 1994, 304 DLO STAR CENTR JOHNSON WC, 1976, ECOL MONOGR, V46, P59 JUNK WJ, 1989, CANADIAN SPECIAL PUB, V106, P110 KONDOLF GM, 2000, RESTOR ECOL, V8, P48 KRAUSCH HD, 1968, MITTEILUNGEN FLORIST, V13, P71 LEOPOLD LB, 1964, FLUVIAL PROCESSES GE MAKASKE A, 1998, NETHERLANDS GEOGRAPH, V249 MEINARDI CR, 1998, STROMINGEN, V4, P27 MIALL AD, 1996, GEOLOGY FLUVIAL DEPO NANSON GC, 1977, J BIOGEOGR, V4, P229 PARKER G, 1976, P S INL WAT NAV FLOO, P1248 PECK S, 1998, PLANNING BIODIVERSIT PICKET STA, 1985, ECOLOGY NATURAL DIST PLACHTER H, 1998, SCHRIFTENREIHE LANDS, V56 POTT R, 1991, ABHANDLUNGEN WESTFAL, V53, P1 REINECK HE, 1980, DEPOSITIONAL SEDIMEN RULKENS T, 1983, RELATIE TUSSEN VEGET SCHAMINEE JHJ, 1996, VEGETATIE NEDERLAND, V3 SCHUMM SA, 1988, SCALES GLOBAL CHANGE, P225 TURNER MG, 1987, LANDSCAPE HETEROGENE VANDERHAMMEN T, 1971, MEDEDELINGEN RIJKS G, V22, P147 VERDONSCHOT PFM, 1993, 4 DLO I BOS NAT Suppl. 1 0921-2973 Landsc. Ecol.ISI:000176041000005Univ Wageningen & Res Ctr, NL-6700 AA Wageningen, Netherlands. Free Univ Amsterdam, Fac Earth Sci, NL-1081 HV Amsterdam, Netherlands. Wolfert, HP, Univ Wageningen & Res Ctr, POB 47, NL-6700 AA Wageningen, Netherlands. h.p.wolfert@alterra.wag-ur.nlEnglish#?Z7H. P. Wolfert P. W. F. M. Hommel A. H. Prins M. H. Stam2002mThe formation of natural levees as a disturbance process significant to the conservation of riverine pastures47-57Landscape Ecology170Disturbance - Meandering - Natural levee - Overbank deposition - Riverine grassland - River rehabilitation - River Dinkel - The NetherlandsDisturbances and patch dynamics are inherent to many ecosystems of the world, especially in the riparian zone. This paper describes the influence of natural levee overbank deposition on riverine grasslands along the meandering River Dinkel (The Netherlands). Here, the rare vegetation type Diantho-Armerietum, characterised by Dianthus deltoides, Thymus pulegioides, Pimpinella saxifraga and Galium verum, has been identified as important to nature conservation. Diantho-Armerietum shows a strong preference for dry, nutrient poor, sandy and relatively young soils, with an elevation approximately 30–50 cm above bankfull discharge level, corresponding to a flooding frequency of 2–3 times per year. The lower zones are strongly influenced by nutrient-rich water, whereas the higher zones are vulnerable to soil acidification. In the intermediate zone, soil development may be reset due to the supply of calcium, adsorbed to recently deposited levee sands. Since deposition rates will decrease with increasing levee heights, new levees are regularly needed to stop the decline of this floriferous vegetation type. The formation of new natural levees is favoured by the occurrence of meander cutoffs, causing a cyclic succession of landforms along the river. Therefore a conservation strategy for this vegetation type needs to aim at the rehabilitation of the natural levee disturbance process, in conjunction with encouraging the meandering of the river.*http://dx.doi.org/10.1023/A:1015229710294 10.1023/A:1015229710294 H. P. Wolfert Email: h.p.wolfert@alterra.wag-ur.nl Phone: +31 317 474398 Fax: +31 317 419000 References Bornette G., Amoros C., Castella C. and Beffy J.L. 1994. Succession and vegetation in the aquatic vegetation of two former Rhône River channels. Vegetatio 110: 171-184. Bos F. and Hagman F. 1981. Droge graslanden: Een vergelijkend vegetatiekundig en oecologisch onderzoek van vegetaties met Dianthus deltiodes en van verwante droge, zandige graslanden. Rapport 110, Vakgroep Vegetatiekunde, Plantenoecologie en Onkruidkunde, Landbouwhogeschool, Wageningen, The Netherlands. Bravard J-P., Amoros C. and Pautou G. 1986. Impact of engineering works on the successions of communities in a fluvial system. Oikos 47: 92-111. Brierley G.J., Ferguson R.J. and Woolfe K.J. 1997. What is a fluvial levee? Sed. Geol. 114: 1-9. Brock Th.C.M., Van der Velde G. and Van de Steeg H.M. 1987. The effects of extreme water level fluctuations on the wetland vegetation of a nymphaeid-dominated oxbow lake in The Netherlands. Archiv für Hydrobiologie, Beiheft 27: 57-73. Burrigter E., Pott R., Raus T. and Wittig R. 1980. Die Hudelandschaft 'Borkerner Paradies' im Emstal bei Meppen. Abhandlungen aus dem Landesmuseum für Naturkunde zu Münster in Westfalen 42, 4, Westfälische Vereinsdruckerei, Münster, Germany. Cazanacli D. and Smith N.D. 1998. A study of morphology and texture of natural levees-Cumberland Marshes, Saskatchewan, Canada. Geomorphology 25: 43-55. FAO 1985. FAO/Unesco Soil Map of the World 1:5,000,000: Revised legend. World Soil Resources Report, Food and Agricultural Organisation of the United Nations, Rome, Italy. Finck P., Klein M., Riecken U. and Schröder E. (eds.) 1998. Schutz und Förderung dynamischer Prozesse in der Landschaft. Schriftenreihe für Landschaftspflege und Naturschutz 56, Bundesamt für Naturschutz, Bonn-Bad Godesberg, Germany. Gonggrijp G.P. 1976. Het Dinkeldal. Rapport, Rijksinstituut voor Natuurbeheer, Leersum, The Netherlands. Hommel P.W.F.M., Dirkx G.H.P., Prins A.H., Wolfert H.P. and Vrielink J.G. 1994. Natuurbehoud en natuurontwikkeling langs Bloemenbeek en Boven-Dinkel: Gevolgen van ingrepen in de waterhuishouding van het Dinkelsysteem voor enkele karakteristieke vegetatietypen. Rapport 304, DLO-Staring Centrum, Wageningen, The Netherlands. Hommel P.W.F.M., Leeters E.E.J.M. and Vrielink J.G. 1990. Vegetation changes in the Speulderbos (The Netherlands) during the period 1958-1988. Report 23, DLO-Staring Centrum, Wageningen, The Netherlands. Johnson W.C., Burgess R.L. and Keammerer W.R. 1976. Forest overstory vegetation and environment on the Missouri River floodplain in North Dakota. Ecol. Monogr. 46: 59-84. Junk J.W., Bailey P.B. and Sparks R.E. 1989. The flood pulse concept in river floodplain systems. Can. J. Fish. Aquat. Sci. 106: 110-127. Kondolf G.M. 2000. Some suggested guidelines for geomorphic aspects of anadromous salmonid habitat restoration proposals. Restor. Ecol. 8: 48-56. Krausch H.-D. 1968. Die Sandtrockenrasen (Sedo-Scleranthetea) in Brandenburg. In: Mitteilungen der Floristisch-soziologischen Arbeitsgemeinschaft N.F. 13, Floristisch-soziologischen Arbeitsgemeinschaft, Todenmann über Rinteln, pp. 71-100. Leopold L.B., Wolman M.B. and Miller J.P. 1964. Fluvial Processes in Geomorphology. Freeman, San Francisco, USA. Makaske A. 1998. Anastomosing rivers: Forms, processes and sediments. Netherlands Geographical Studies 249, Koninklijk Nederlands Aardrijkskundig Genootschap / Faculteit Ruimtelijke Wetenschappen, Universiteit Utrecht, Utrecht, The Netherlands. Meinardi C.R., Schotten C.G.J., De Vries J.J. 1998. Grondwateraanvulling en oppervlakkige afstroming in Nederland: Langjaarlijkse gemiddelden voor de zand-en leemgebieden. Stromingen 4: 27-41. Miall A.D. 1996. The Geology of Fluvial Deposits: Sedimentary Facies, Basin Analysis and Petroleum Geology. Springer, Berlin, Germany. Nanson G.C. and Beach H.F. 1977. Forest succession and sedimentation on a meandering river floodplain, northeast British Columbia, Canada. J. Biogeogr. 4: 229-251. Parker G. and Andres D. 1976. Detrimental effects of river channelization. In: Proceedings of the 3rd Annual Symposium, Fort Collins, Waterways, Harbors and Coastal Engineering Division, American Society of Civil Engineers, pp. 1248-1266. Peck S. 1998. Planning for Biodiversity: Issues and Examples. Island Press, Washington DC, USA. Picket S.T.A. and White P.S. (eds) 1985. The Ecology of Natural Disturbance and Patch Dynamics. Academic Press, Orlando. Plachter H. 1998. Die Auen alpinerWildflüsse alsModelle störungsgeprägter ökologischer Systeme. 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Rapport, Vakgroep Vegetatiekunde, Plantenoecologie en Onkruidkunde, Landbouwhogeschool, Wageningen, The Netherlands. Schaminée J.H.J., Stortelder A.H.F. and Weeda E.J. 1996. De vegetatie van Nederland-3. Graslanden, zomen en droge heiden. Opulus Press, Uppsala, Sweden. Schumm S.A. 1988. Variability of the Fluvial System in Space and Time. In Rosswall T., Woodmansee R.G. and Risser P.G. (eds), Scales and Global Change, John Wiley & Sons, Chichester, UK, pp. 225-250. Turner M.G. (ed.) 1987. Landscape Heterogeneity and Disturbance. Springer-Verlag, New York, NY, USA. Van der Hammen T. and Bakker J.A. 1971. Former vegetation, landscape and man in the Dinkel valley. In: Van der Hammen T. and Wijmstra T.A. (eds), Upper Quarternary of the Dinkel valley, pp. 147-158. Mededelingen, nieuwe serie 22, Rijks Geologische Dienst, Haarlem, The Netherlands. Verdonschot P.F.M., Schot J.A. and Scheffers M.R. 1993. Potentiële ecologische ontwikkelingen in het aquatisch deel van het Dinkelsysteem: Onderdeel van het NBP-project Ecologisch onderzoek Dinkelsysteem. Rapport 4, DLO-Instituut voor Bos-en Natuuronderzoek, Wageningen, The Netherlands. H. P. Wolfert1 , P. W. F. M. Hommel1, A. H. Prins1 and M. H. Stam2 (1) Alterra, Wageningen University and Research Centre, P.O. Box 47, 6700 AA Wageningen, The Netherlands (2) Faculty of Earth Sciences, Free University, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands <7Wolter, P. T. White, M. A.2002aRecent forest cover type transitions and landscape structural changes in northeast Minnesota, USA133-155Landscape Ecology172change detection forest classification forest dynamics forest fragmentation landsat landscape indices landscape pattern THEMATIC MAPPER DATA VEGETATION INDEXES SPATIAL PATTERN OLD-GROWTH DAMAGE EDGE SUCCESSION MANAGEMENT IMAGERY STATESArticleZLandsat TM satellite data covering an approximate 5-year interval (1990-1995) were used to quantify spatial pattern and transition rates between forest ecological states for a 2.76 million ha region in northeast Minnesota. Changes in forest cover were stratified by Ecological Subsection, management status, and by ownership categories using a 1995 digital ownership layer. Approximately 4.2% of the 1990 mature forested area was converted to early successional types by 1995. Of this 4.2%, private lands accounted for 33%, federal lands 31%, county lands 20% and state lands 16%. Notable conversion percentages by cover type category were spruce-fir (-5.3%), aspen-birch (-4.7%), jack pine (-4.6%) and black spruce (-3.0%). Transition rates were also adjusted to fit ten-year time intervals. Shannon-Weaver Eveness and edge density of cover types increased over the study period as relative contagion and interior forest area decreased. These trends suggest both smaller patches and a more even distribution of cover types. Area of upland conifers, lowland conifers and lowland hardwoods decreased while the area of mature upland hardwoods increased in most patch size classes except the > 500 ha class which showed a substantial decrease in area. The area of early successional types increased in most patch size classes. Non-industrial private forestland had the lowest proportion of interior forest of all ownership categories - decreasing by 13.5% in five years. Smaller average cut-unit sizes and uncoordinated forest management is the likely cause since cutting rates between private and public forestland were similar.://000177049100003 ISI Document Delivery No.: 577ET Times Cited: 9 Cited Reference Count: 47 Cited References: *ERDAS INC, 1997, ERDAS FIELD GUID VER *MI DEP NAT RES, 1995, COOP STAND ASS FIELD *MI DEP NAT RES, 1998, GAP STEW DAT *MN FOR RES COUNC, 1999, LT0799 MINN FOR RES *USDA FOR SERV FOR, 1992, REP BLU RIBB PAN FOR AHLGREN CE, 1957, ECOLOGY, V38, P622 ANDERSON CE, 2002, UNPUB NATURAL AREAS CZAPLEWSKI RL, 1999, J FOREST, V97, P44 EDER JJ, 1989, J FOREST, V87, P50 FRANKLIN JF, 1987, LANDSCAPE ECOLOGY, V1, P5 FRELICH LE, 1995, ECOSCIENCE, V2, P148 FRELICH LE, 2000, UNPUB ECOLOGICAL FIR GUSTAFSON EJ, 1994, LANDSCAPE ECOL, V9, P237 GUSTAFSON EJ, 1996, FOREST ECOL MANAG, V87, P27 GUSTAFSON EJ, 1996, J ENVIRON MANAGE, V46, P77 HALL FG, 1991, ECOLOGY, V72, P628 HANSKI IK, 1996, AUK, V113, P578 HEINSELMAN ML, 1973, QUATERNARY RES, V3, P329 HEINSELMAN ML, 1996, BOUNDARY WATERS WILD HUNTER ML, 1990, WILDLIFE FORESTS FOR JAAKKO, 1994, FINAL GENERIC ENV IM JOHNSON EA, 1987, CAN J BOT, V65, P853 KOUKI J, 1997, CAN J FOREST RES, V27, P1765 LI H, 1993, LANDSCAPE ECOL, V8, P63 LI H, 1993, LANDSCAPE ECOLOGY, V3, P155 LI HB, 1994, ECOLOGY, V75, P2446 LOGAN TL, 1979, 7 ANN REM SENS EARTH, V7, P163 MCGARIGAL K, 1995, GTR351 USDA FOR SERV MLADENOFF DJ, 1993, ECOL APPL, V3, P294 MLADENOFF DJ, 1997, LANDSCAPE ECOL, V12, P379 MLADENOFF DJ, 1999, APACK 2 11 SOFTWARE OLSSON H, 1994, REMOTE SENS ENVIRON, V50, P221 PASTOR J, 1990, LANDSCAPE ECOL, V4, P55 PASTOR J, 1992, SYSTEMS ANAL GLOBAL, P216 PASTOR J, 1993, LECT MATH LIFE SCI, V23, P5 PRICE JC, 1987, REMOTE SENS ENVIRON, V21, P15 ROLAND J, 1995, ENVIRON ENTOMOL, V24, P1175 SACHS DL, 1998, CAN J FOREST RES, V28, P23 SPIES TA, 1994, ECOL APPL, V4, P555 TEMPLE SA, 1998, J FOREST, V96, P22 TURNER MG, 1996, ECOL APPL, V6, P1150 VOGELMANN JE, 1988, REMOTE SENS ENVIRON, V24, P227 VOGELMANN JE, 1989, REMOTE SENS ENVIRON, V30, P217 VOGELMANN JE, 1990, INT J REMOTE SENS, V11, P2281 WALLIN DO, 1994, ECOL APPL, V4, P569 WHITE MA, 1994, LANDSCAPE ECOL, V9, P191 WOLTER PT, 1995, PHOTOGRAMM ENG REM S, V61, P1129 0921-2973 Landsc. Ecol.ISI:000177049100003Univ Minnesota, Nat Resources Res Inst, Ctr Water & Environm, Duluth, MN 55811 USA. Wolter, PT, Univ Wisconsin, 2420 Nicolet Dr, Green Bay, WI 54311 USA.EnglishK<7l.Wondzell, S. M. Cunningham, G. L. Bachelet, D.1996}Relationships between landforms, geomorphic processes, and plant communities on a watershed in the northern Chihuahuan Desert351-362Landscape Ecology116erosion; deposition; limiting resources; runoff; water availability; ecotones; grazing; grassland; shrubland; desertification SOUTHERN NEW-MEXICO; SONORAN DESERT; VEGETATION PATTERNS; MESQUITE DUNELANDS; FORMER GRASSLANDS; MOJAVE DESERT; SOIL; DESERTIFICATION; GRADIENTS; SOUTHWESTArticleDec5 The close correlation of plant communities to landforms and geomorphic surfaces resulted from differences in the redistribution of water and organic matter between landforms in the northern Chihuahuan Desert. Biotic processes are limited by water and nitrogen, and the interactions between landforms, geomorphic processes, soils, and plant communities control the redistribution of these limiting resources within internally drained catchments, Geomorphic processes are regulated by the geologic structure and gross topographic relief of internally drained catchments over geological time scales, Land forming processes can be viewed as static at time scales of 10's to 100's of years, with individual landforms regulating geomorphic processes, namely erosion and deposition resulting from the horizontal redistribution of water within the catchment, The vegetation composition is a critical feedback, reinforcing the erosional or depositional geomorphic processes that dominate each landform. The Jornada Long-Term Ecological Research site may be one of the simplest cases in which to decipher the relationship between landforms, geomorphic processes and plant communities. However, these geomorphic processes are common to all internally drained catchments throughout the Basin and Range Province, and result in the development of characteristic landforms and associated vegetation communities, Although the patterns may be modified by differences in parent material, watershed size, and land use history-erosional, depositional, and transportational landforms can still be identified. The sharpness of ecotones between plant communities on individual landforms is related to the degree to which landforms are linked through the flow of water and sediment. Sharp ecotones occurred at the transition from depositional to erosional landforms where little material was transferred and steep environmental gradients are maintained, Gradual ecotones occurred at the transition from erosional to depositional landforms where large quantities of material were transferred leading to the development of a gradual environmental gradient. The relationships between geomorphic processes and vegetation communities that we describe have important implications for understanding the desertification of grasslands throughout semi-arid regions of North America. Disturbances such as grazing and climate change alter the composition of plant communities, thereby affecting the feedbacks to geomorphic processes, eventually changing drainage patterns and the spatial patterns of plant communities supported within the landscape.://A1996VY82900005 X ISI Document Delivery No.: VY829 Times Cited: 21 Cited Reference Count: 56 Cited References: BAHRE CJ, 1993, J BIOGEOGR, V20, P489 BLACKWELDER E, 1931, J GEOL, V20, P442 BOWERS MA, 1986, OIKOS, V46, P284 BOWERS MA, 1988, VEGETATIO, V74, P107 BUFFINGTON LC, 1965, ECOL MONOGR, V35, P139 BULL WB, 1991, GEOMORPHIC RESPONSES BURKE IC, 1989, VEGETATIO, V84, P77 CORNELIUS JM, 1991, J VEG SCI, V2, P59 CORNET AF, 1988, ECOL STUD, V92 CRAWFORD CS, 1982, ENVIRON CONSERV, V9, P181 FENNEMAN NM, 1931, PHYSIOGRAPHY W US GARCIAMOYA E, 1970, ECOLOGY, V51, P81 GARDNER JL, 1951, ECOL MONOGR, V21, P379 GIBBENS RP, 1983, J RANGE MANAGE, V36, P145 GIBBENS RP, 1988, J RANGE MANAGE, V41, P186 GIBBENS RP, 1992, J RANGE MANAGE, V45, P585 GILE LH, 1979, DESERT PROJECT SOILS GILE LH, 1981, GUIDEBOOK DESERT PRO, V39 GRIFFITHS D, 1901, B USDA BUR PLANT IND, V4 GRIFFITHS D, 1910, B USDA BUREA PLANT I, V177 GROVER HD, 1990, CLIMATIC CHANGE, V17, P305 HALVORSON WL, 1974, ECOLOGY, V55, P173 HASTINGS JR, 1965, CHANGINE MILE HAWLEY JW, 1975, NEW MEXICO GEOLOGICA, P139 HENNESSY JT, 1983, J RANGE MANAGE, V36, P370 HUNT CB, 1966, PLANT ECOLOGY DEATH LEOPOLD A, 1924, J FOREST, V22, P1 LUDWIG JA, 1987, ECOLOGY, V68, P448 LUDWIG JA, 1989, J ARID ENVIRON, V16, P35 LUDWIG JA, 1994, PACIFIC CONSERVATION, V1, P209 LUDWIG JA, 1995, LANDSCAPE ECOL, V10, P51 MABBUTT JA, 1987, J ARID ENVIRON, V12, P41 MACMAHON JA, 1981, US IBP SYNTHESIS SER, V11 MCAULIFFE JR, 1994, ECOL MONOGR, V64, P111 MONTANA C, 1990, J VEG SCI, V1, P669 NASH MHH, 1985, NUMERICAL CLASSIFICA NEILSON RP, 1986, SCIENCE, V232, P27 NOYMEIR I, 1973, ANNU REV ECOL SYST, V4, P25 OLSVIGWHITTAKER L, 1983, VEGETATIO, V54, P153 ORDONEZ E, 1936, AAPG BULL, V20, P1277 PARKER KC, 1991, J BIOGEOGR, V18, P151 PETERSON FF, 1981, NEVADA AGR EXPT STAT, V28 PICKUP G, 1985, AUSTR RANGELAND J, V7, P114 SCHLESINGER WH, 1984, BOT GAZ, V145, P116 SCHLESINGER WH, 1989, SOIL SCI SOC AM J, V53, P1567 SCHLESINGER WH, 1990, SCIENCE, V247, P1043 STEIN R, 1979, AM MIDL NAT, V102, P28 STRAIN WS, 1966, TEXAS MEMORIAL MUSEU, V10 SZAREK SR, 1979, J ARID ENVIRON, V2, P187 WHITE LP, 1971, J ECOL, V59, P615 WIERENGA PJ, 1987, J ARID ENVIRON, V13, P53 WONDZELL S, 1995, J VEG SCI, V6, P377 WONDZELL SM, 1987, STRATEGIES CLASSIFIC, P15 WONDZELL SM, 1990, J VEG SCI, V1, P403 YAIR A, 1980, OECOLOGIA, V47, P83 YORK JC, 1969, ARID LANDS PERSPECTI, P157 0921-2973 Landsc. Ecol.ISI:A1996VY82900005BWondzell, SM, NEW MEXICO STATE UNIV,DEPT BIOL,LAS CRUCES,NM 88003.English <7 Wood, S. W. Bowman, D. M. J. S.2012zAlternative stable states and the role of fire-vegetation-soil feedbacks in the temperate wilderness of southwest Tasmania13-28Landscape Ecology271alternative stable states fire forest positive feedbacks aerial photography phosphorus west tasmania rain-forest holocene vegetation bathurst harbor organic soils landscape australia savanna ecosystems boundariesJanGTwo ecological models have been put forward to explain the dynamics of fire-promoting and fire-sensitive vegetation in southwest Tasmania: the alternative stable states model of Jackson (in Proc Ecol Soc Aust 3:9-16, 1968) and the sharpening switch model of Mount (in Search 10:180-186, 1979). Assessing the efficacy of these models requires high resolution spatio-temporal data on whether vegetation patterns are stable or dynamic across landscapes. We analysed ortho-rectified sequences of aerial photography and satellite imagery from 1948, 1988 and 2010 to detect decadal scale changes in forest and non-forest vegetation cover in southwest Tasmania. There was negligible change from forest to non-forest (< 0.05%) and only a modest change from non-forest to forest over the study period. Forest cover increased by 4.1% between 1948 and 1988, apparently due to the recovery of forest vegetation following stand-replacing fire prior to 1948. Forest cover increased by 0.8% between 1988 and 2010, reflecting the limited ability of forest to invade treeless areas. The two models include interactions between vegetation, fire and soil, which we investigated by analysing the chemical (phosphorus, nitrogen) and physical properties (clay, silt) of 128 soil samples collected across 34 forest-non-forest boundaries. Phosphorus in the upper horizon was typically lower in non-forest vegetation compared to forest vegetation, which is consistent with proposed fire-vegetation-soil feedbacks. Mineral horizons were dominated by sand, with low levels of clay under all vegetation types. Available field evidence lends support to the Jackson (1968) alternative stable states model as the most suitable model of vegetation dynamics on nutrient poor substrates in southwest Tasmania although modifications of the timeframes for transitions toward rainforest are required.://000298228300002-864HI Times Cited:1 Cited References Count:65 0921-2973Landscape EcolISI:000298228300002Wood, SW Univ Tasmania, Sch Plant Sci, Private Bag 55, Hobart, Tas 7001, Australia Univ Tasmania, Sch Plant Sci, Private Bag 55, Hobart, Tas 7001, Australia Univ Tasmania, Sch Plant Sci, Hobart, Tas 7001, AustraliaDOI 10.1007/s10980-011-9677-0Englishv? B R.L. Wright1987iIntegration in land research for Third World development planning: An applied aspect of landscape ecology107-117Landscape Ecology12=development, planning, agriculture, models, interdisciplinary<In the practical application of landscape ecology to development planning it is essential that there be interdisciplinary collaboration. Three ways of developing this collaboration are discussed. These are (1) use of environmental concepts which directs specialists to focus on landscape interrelationships; (2) geomorphic differentiation to provide a common framework for analysis and (3) a unified methodology based on mathematical modelling, hypothesis testing, and application of statistical theory. Broader implications to policy and administration are also examined.<7 Wu, J.2007-Past, present and future of landscape ecology 1433-1435Landscape Ecology2210Editorial MaterialDec://000250632100001TISI Document Delivery No.: 227BL Times Cited: 0 Cited Reference Count: 6 Wu, Jianguo 0921-2973 Landsc. Ecol.ISI:000250632100001Arizona State Univ, Sch Life Sci, Tempe, AZ 85287 USA. Arizona State Univ, Global Inst Sustainabil, Tempe, AZ 85287 USA. Wu, J, Arizona State Univ, Sch Life Sci, Tempe, AZ 85287 USA. Jingle.Wu@asu.eduEnglish|? Wu, Jianguo2010SLandscape of culture and culture of landscape: does landscape ecology need culture? 1147-1150Landscape Ecology258Oct!://WOS:000281725700001Times Cited: 2 0921-2973WOS:00028172570000110.1007/s10980-010-9524-8? Wu, Jianguo2011:Improving the writing of research papers: IMRAD and beyond 1345-1349Landscape Ecology2610Springer NetherlandsEarth and Environmental Science+http://dx.doi.org/10.1007/s10980-011-9674-3 0921-297310.1007/s10980-011-9674-3ڽ7 Wu, Jianguo2013kKey concepts and research topics in landscape ecology revisited: 30 years after the Allerton Park workshop1-11Landscape Ecology281Springer NetherlandsSLandscape ecology Core questions Key topics Future direction Allerton Park workshop 2013/01/01+http://dx.doi.org/10.1007/s10980-012-9836-y 0921-2973Landscape Ecol10.1007/s10980-012-9836-yEnglishڽ7 Wu, Jianguo2013`Landscape sustainability science: ecosystem services and human well-being in changing landscapes999-1023Landscape Ecology286Springer NetherlandsSustainability Landscape sustainability science Landscape sustainability spectrum Ecosystem services Human well-being Key research questions and approaches 2013/07/01+http://dx.doi.org/10.1007/s10980-013-9894-9 0921-2973Landscape Ecol10.1007/s10980-013-9894-9English.<7  Wu, J. G.2004JEffects of changing scale on landscape pattern analysis: scaling relations125-138Landscape Ecology192landscape metrics; pattern analysis; scale effects; scaling; scalograms; grain; extent SPATIAL-RESOLUTION; ECOLOGY; AGGREGATION; METRICS; MODELS; SENSITIVITY; INDEXES; REGION; ISSUESArticleXLandscape pattern is spatially correlated and scale-dependent. Thus, understanding landscape structure and functioning requires multiscale information, and scaling functions are the most precise and concise way of quantifying multiscale characteristics explicitly. The major objective of this study was to explore if there are any scaling relations for landscape pattern when it is measured over a range of scales (grain size and extent). The results showed that the responses of landscape metrics to changing scale fell into two categories when computed at the class level (i.e., for individual land cover types): simple scaling functions and unpredictable behavior. Similarly, three categories were found at the landscape level, with the third being staircase pattern, in a previous study when all land cover types were combined together. In general, scaling relations were more variable at the class level than at the landscape level, and more consistent and predictable with changing grain size than with changing extent at both levels. Considering that the landscapes under study were quite diverse in terms of both composition and configuration, these results seem robust. This study highlights the need for multiscale analysis in order to adequately characterize and monitor landscape heterogeneity, and provides insights into the scaling of landscape patterns.://000220452500002 H ISI Document Delivery No.: 806SB Times Cited: 42 Cited Reference Count: 71 Cited References: ALLEN RFH, 1984, RM110 USDA FOR SERV ALLEN TFH, 1982, HIERARCHY PERSPECTIV AMRHEIN CG, 1995, ENVIRON PLANN A, V27, P105 ARBIA G, 1996, GEOGRAPHICAL SYSTEMS, V3, P123 BENSON BJ, 1995, LANDSCAPE ECOL, V10, P113 BIAN L, 1993, PROF GEOGR, V45, P1 BIAN L, 1999, PHOTOGRAMM ENG REM S, V65, P73 BRADSHAW GA, 1992, J ECOL, V80, P205 BROWN JH, 2000, SCALING BIOL BURROUGH PA, 1995, DATA ANAL COMMUNITY, P213 COSTANZA R, 1989, ECOLOGICAL MODELLING, V47, P199 COSTANZA R, 1994, LANDSCAPE ECOL, V9, P47 DALE MRT, 1999, SPATIAL PATTERN ANAL DUNGAN JL, 2002, ECOGRAPHY, V25, P626 FORTIN MJ, 1999, LANDSCAPE ECOLOGICAL, P253 FROHN RC, 1998, REMOTE SENSING LANDS GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GOOVAERTS P, 1997, GEOSTATISTICS NATURA GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HARGIS CD, 1998, LANDSCAPE ECOL, V13, P167 HAY GJ, 2001, LANDSCAPE ECOL, V16, P471 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 JENSEN HJ, 1998, SELF ORG CRITICALITY JUSTICE CO, 1989, INT J REMOTE SENS, V10, P1539 KEELING MJ, 1997, PHILOS T ROY SOC B, V352, P1589 KING AW, 1991, LANDSCAPE ECOL, V5, P239 LAM NSN, 1992, PROF GEOGR, V44, P88 LEVIN SA, 1992, ECOLOGY, V73, P1943 LUCK M, 2002, LANDSCAPE ECOL, V17, P327 MACARTHUR RH, 1972, GEOGRAPHICAL ECOLOGY MARCEAU DJ, 1999, CANADIAN J REMOTE SE, V25, P347 MCGARIGAL K, 1995, PNWGTR351 PAC NW RES MEENTEMEYER V, 1987, LANDSCAPE HETEROGENE, P15 MEENTEMEYER V, 1989, LANDSCAPE ECOLOGY, V3, P163 MEISEL JE, 1998, LANDSCAPE ECOL, V13, P347 MILNE BT, 1991, ECOLOGICAL HETEROGEN, P69 MILNE BT, 1992, AM NAT, V139, P32 MILNE BT, 1997, WILDLIFE LANDSCAPE E, P32 MOELLERING H, 1972, GEOGR ANAL, V4, P34 MOODY A, 1994, PHOTOGRAMM ENG REM S, V60, P585 ONEILL RV, 1979, SYSTEMS ANAL ECOSYST, P59 ONEILL RV, 1986, HIERARCHICAL CONCEPT ONEILL RV, 1991, ECOLOGICAL HETEROGEN, P85 ONEILL RV, 1996, LANDSCAPE ECOL, V11, P169 OPENSHAW S, 1984, MODIFIABLE AREAL UNI PLATT T, 1975, ANNU REV ECOL SYST, V6, P189 PLOTNICK RE, 1993, LANDSCAPE ECOL, V8, P201 PLOTNICK RE, 2001, PALEOBIOLOGY, V27, P126 QI Y, 1996, LANDSCAPE ECOL, V11, P39 REYNOLDS JF, 1999, INTEGRATING HYDROLOG, P273 ROBINSON WS, 1950, AM SOCIOL REV, V15, P351 ROSSI RE, 1992, ECOL MONOGR, V62, P277 SAURA S, 2001, PHOTOGRAMM ENG REM S, V67, P1027 SCHNEIDER DC, 2001, BIOSCIENCE, V51, P545 SCHNEIDER DC, 2001, SCALING RELATIONS EX, P113 TOBLER WR, 1970, EC GEOGRAPHY S, V46, P234 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 TURNER MG, 2001, LANDSCAPE ECOLOGY TH TURNER SJ, 1991, QUANTITATIVE METHODS, P17 URBAN DL, 1987, BIOSCIENCE, V37, P119 WICKHAM JD, 1995, INT J REMOTE SENS, V16, P3585 WIENS JA, 1989, FUNCT ECOL, V3, P385 WOODCOCK C, 1992, INT J REMOTE SENS, V13, P3167 WRIGLEY N, 1996, SPATIAL ANAL MODELLI, P23 WU J, 1999, CANADIAN J REMOTE SE, V25, P367 WU J, 2000, GEOGRAPHICAL INFORMA, V6, P6 WU J, 2003, LANDSCAPE ECOLOGY, V17, P761 WU J, 2004, SCALING UNCERTAINTY WU JG, 1994, ECOL MONOGR, V64, P447 WU JG, 1995, Q REV BIOL, V70, P439 WU JG, 2002, LANDSCAPE ECOL, V17, P355 0921-2973 Landsc. Ecol.ISI:000220452500002Arizona State Univ, Sch Life Sci, Fac Ecol Evolut & Environm Sci, LEML, Tempe, AZ 85287 USA. Wu, JG, Arizona State Univ, Sch Life Sci, Fac Ecol Evolut & Environm Sci, LEML, Tempe, AZ 85287 USA. Jingle.Wu@asu.eduEnglish^<7~ Wu, J. G.2006CLandscape ecology, cross-disciplinarity, and sustainability science1-4Landscape Ecology211Editorial MaterialJan://000235887300001 ISI Document Delivery No.: 020DD Times Cited: 1 Cited Reference Count: 18 Cited References: *NAT RES COUNC, 1999, OUR COMM JOURN TRANS BASTIAN O, 2001, LANDSCAPE ECOL, V16, P757 CLARK WC, 2003, P NATL ACAD SCI USA, V100, P8059 KATES RW, 2001, SCIENCE, V292, P641 NAVEH Z, 1994, LANDSCAPE ECOLOGY TH PICKETT STA, 1994, ECOLOGICAL UNDERSTAN POTSCHIN M, 2005, LANDSCAPE URBAN PLAN REITAN PH, 2005, SUSTAINABILITY SCI P, V1, P77 RINDFUSS RR, 2005, P NAT ACAD SCI, V101, P13976 TRESS G, 2005, LANDSCAPE ECOL, V20, P479 TROLL C, 1939, Z GESELLSCHAFT ERDKU, P241 TROLL C, 1971, GEOFORUM, V8, P43 TURNER MG, 2001, LANDSCAPE ECOLOGY TH TURNER MG, 2005, ANNU REV ECOL EVOL S, V36, P319 WIENS JA, 1999, ISSUES LANDSCAPE ECO, P148 WU J, 2006, IN PRESS KEY TOPICS WU J, 2006, SCALING UNCERTAINTY WU JG, 2002, LANDSCAPE ECOL, V17, P355 0921-2973 Landsc. Ecol.ISI:000235887300001Arizona State Univ, Sch Life Sci, Tempe, AZ 85287 USA. Arizona State Univ, Global Inst Sustainabil, Tempe, AZ 85287 USA. Wu, JG, Arizona State Univ, Sch Life Sci, Tempe, AZ 85287 USA. Jingle.Wu@asu.eduEnglish|? Wu, J. G.2010>Urban sustainability: an inevitable goal of landscape research1-4Landscape Ecology251!://WOS:000273479100001Times Cited: 0 0921-2973WOS:00027347910000110.1007/s10980-009-9444-7<7Wu, J. G. Hobbs, R.2002SKey issues and research priorities in landscape ecology: An idiosyncratic synthesis355-365Landscape Ecology174Qkey issues landscape ecology research priorities and challenges PSEUDOREPLICATIONArticleLandscape ecology has made tremendous progress in recent decades, but as a rapidly developing discipline it is faced with new problems and challenges. To identify the key issues and research priorities in landscape ecology, a special session entitled "Top 10 List for Landscape Ecology in the 21st Century" was organized at the 16th Annual Symposium of the US Regional Association of International Association of Landscape Ecology, held at Arizona State University (Tempe, Arizona, USA) during April 25-29, 2001. A group of leading landscape ecologists were invited to present their views. This paper is intended to be a synthesis, but not necessarily a consensus, of the special session. We have organized the diverse and wide-ranging perspectives into six general key issues and 10 priority research topics. The key issues are: (1) interdisciplinarity or transdisciplinarity, (2) integration between basic research and applications, (3) Conceptual and theoretical development, (4) education and training, (5) international scholarly communication and collaborations, and (6) outreach and communication with the public and decision makers. The top 10 research topics are: (1) ecological flows in landscape mosaics, (2) causes, processes, and consequences of land use and land cover change, (3) nonlinear dynamics and landscape complexity, (4) scaling, (5) methodological development, (6) relating landscape metrics to ecological processes, (7) integrating humans and their activities into landscape ecology, (8) optimization of landscape pattern, (9) landscape sustainability, and (10) data acquisition and accuracy assessment. We emphasize that, although this synthesis was based on the presentations at the "Top 10 List" session, it is not a document that has been agreed upon by each and every participant. Rather, we believe that it is reflective of the broad-scale vision of the collective as to where landscape ecology is now and where it may be going in future.://000178391000005 ISI Document Delivery No.: 600LF Times Cited: 62 Cited Reference Count: 37 Cited References: ARONSON J, 1996, RESTOR ECOL, V4, P377 BARRETT GW, 1999, LANDSCAPE ECOLOGY SM BISSONETTE JA, 1997, WILDLIFE LANDSCAPE E DALE VH, 2001, APPL ECOLOGICAL PRIN FARINA A, 1998, PRINCIPLES METHODS L FARINA A, 2000, LANDSCAPE ECOLOGY AC FORMAN RTT, 1995, LAND MOSAICS ECOLOGY GOLLEY FB, 1991, LANDSCAPE URBAN PLAN, V21, P3 HAINESYOUNG R, 1993, LANDSCAPE ECOLOGY GI HANSSON L, 1995, MOSAIC LANDSCAPES EC HARGROVE WW, 1992, LANDSCAPE ECOL, V6, P251 KLOPATEK JM, 1999, LANDSCAPE ECOLOGICAL KUHN TS, 1970, STRUCTURE SCI REVOLU KUHN TS, 1983, NY TIMES NEW YO 0313 LEVIN SA, 1999, FRAGILE DOMINION COM LUDWIG J, 1997, LANDSCAPE ECOLOGY FU MACARTHUR RH, 1967, THEORY ISLAND BIOGEO MLADENOFF DJ, 1999, SPATIAL MODELING FOR MOSS M, 1999, ISSUES LANDSCAPE ECO, P138 NASSAUER JI, 1997, PLACING NATURE CULTU NAVEH Z, 1988, LANDSCAPE ECOLOGY MA, P23 NAVEH Z, 1994, LANDSCAPE ECOLOGY TH NAVEH Z, 2000, LANDSCAPE URBAN PLAN, V50, P7 OKSANEN L, 2001, OIKOS, V94, P27 ONEILL RV, 1999, ISSUES LANDSCAPE ECO, P1 PICKETT STA, 1994, ECOLOGICAL UNDERSTAN PUTNAM SH, 1986, ADV URBAN SYSTEMS MO, P91 RISSER PG, 1984, ILLINOIS NATURAL HIS, V2 SANDERSON J, 2000, LANDSCAPE ECOLOGY TO TROLL C, 1939, Z GESELLSCHAFT ERDKU, P241 TURNER MG, 2001, LANDSCAPE ECOLOGY TH WATT AS, 1947, J ECOL, V35, P1 WIENS JA, 1999, ISSUES LANDSCAPE ECO WIENS JA, 1999, ISSUES LANDSCAPE ECO, P148 WU J, 1999, CANADIAN J REMOTE SE, V25, P367 WU J, 2000, LANDSCAPE ECOLOGY PA ZONNEVELD IS, 1995, LAND ECOLOGY 0921-2973 Landsc. Ecol.ISI:000178391000005Arizona State Univ, Dept Plant Biol, Tempe, AZ 85287 USA. Murdoch Univ, Sch Environm Sci, Murdoch, WA 6150, Australia. Wu, JG, Arizona State Univ, Dept Plant Biol, Tempe, AZ 85287 USA.English<7/Wu, J. G. Shen, W. J. Sun, W. Z. Tueller, P. T.2002HEmpirical patterns of the effects of changing scale on landscape metrics761-782Landscape Ecology178anisotropy extent grain landscape metric scalograms landscape pattern analysis scale effect SPATIAL-RESOLUTION ECOLOGY SENSITIVITY DYNAMICS INDEXESArticleDec#While ecologists are well aware that spatial heterogeneity is scale-dependent, a general understanding of scaling relationships of spatial pattern is still lacking. One way to improve this understanding is to systematically examine how pattern indices change with scale in real landscapes of different kinds. This study, therefore, was designed to investigate how a suite of commonly used landscape metrics respond to changing grain size, extent, and the direction of analysis (or sampling) using several different landscapes in North America. Our results showed that the responses of the 19 landscape metrics fell into three general categories: Type I metrics showed predictable responses with changing scale, and their scaling relations could be represented by simple scaling equations (linear, power-law, or logarithmic functions); Type II metrics exhibited staircase-like responses that were less predictable; and Type III metrics behaved erratically in response to changing scale, suggesting no consistent scaling relations. In general, the effect of changing grain size was more predictable than that of changing extent. Type I metrics represent those landscape features that can be readily and accurately extrapolated or interpolated across spatial scales, whereas Type II and III metrics represent those that require more explicit consideration of idiosyncratic details for successful scaling. To adequately quantify spatial heterogeneity, the metric-scalograms (the response curves of metrics to changing scale), instead of single-scale measures, seem necessary.://000181767400007 ISI Document Delivery No.: 659FV Times Cited: 33 Cited Reference Count: 46 Cited References: ATKINSON PM, 1993, INT J REMOTE SENS, V14, P1005 BENSON BJ, 1995, LANDSCAPE ECOL, V10, P113 BIAN L, 1999, PHOTOGRAMM ENG REM S, V65, P73 BUCKLEY RC, 1985, J BIOGEOGR, V12, P527 DALE MRT, 1983, SPATIAL PATTERN ANAL FROHN RC, 1998, REMOTE SENSING LANDS GARDNER RH, 1987, LANDSCAPE ECOL, V1, P19 GARDNER RH, 1998, ECOLOGICAL SCALE THE, P17 GREIGSMITH P, 1983, QUANTITATIVE PLANT E HE F, 1994, ENV ECOLOGICAL STAT, V1, P265 JELINSKI DE, 1996, LANDSCAPE ECOL, V11, P129 JENERETTE GD, 2002, LANDSCAPE ECOLOGY, V16, P611 JUSTICE CO, 1989, INT J REMOTE SENS, V10, P1539 LAVOREL S, 1993, OIKOS, V67, P521 LEDUC A, 1994, LANDSCAPE ECOL, V9, P279 LEVIN SA, 1992, ECOLOGY, V73, P1943 LI HB, 1993, LANDSCAPE ECOL, V8, P155 LI HB, 1994, ECOLOGY, V75, P2446 LUCK M, 2002, IN PRESS LANDSCAPE E, V17, P327 MACARTHUR RH, 1967, THEORY ISLAND BIOGEO MARCEAU DJ, 1994, REMOTE SENS ENVIRON, V49, P93 MARCEAU DJ, 1999, CANADIAN J REMOTE SE, V25, P347 MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MEENTEMEYER V, 1987, LANDSCAPE HETEROGENE, P15 MOODY A, 1995, LANDSCAPE ECOL, V10, P363 ONEILL RV, 1988, LANDSCAPE ECOL, V1, P153 ONEILL RV, 1991, ECOLOGICAL HETEROGEN, P85 ONEILL RV, 1996, LANDSCAPE ECOL, V11, P169 OPENSHAW S, 1984, MODIFIABLE AREAL UNI QI Y, 1996, LANDSCAPE ECOL, V11, P39 RIITTERS KH, 1995, LANDSCAPE ECOL, V10, P23 RIITTERS KH, 1996, LANDSCAPE ECOL, V11, P197 SAURA S, 2001, PHOTOGRAMM ENG REM S, V67, P1027 TURNER MG, 1989, ANNU REV ECOL SYST, V20, P171 TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 TURNER MG, 2001, LANDSCAPE ECOLOGY TH WICKHAM JD, 1995, INT J REMOTE SENS, V16, P3585 WIENS JA, 1989, FUNCT ECOL, V3, P385 WILLIAMSON M, 1988, ANAL BIOGEOGRAPHY, P91 WOODCOCK CE, 1987, REMOTE SENS ENVIRON, V21, P311 WU J, 1995, ENCY ENV BIOL, P371 WU J, 1999, CANADIAN J REMOTE SE, V25, P367 WU J, 2000, GEOGRAPHICAL INFORMA, V6, P6 WU JG, 1991, B MATH BIOL, V53, P911 WU JG, 1994, ECOL MONOGR, V64, P447 WU JG, 1995, Q REV BIOL, V70, P439 0921-2973 Landsc. Ecol.ISI:000181767400007EArizona State Univ, Dept Plant Biol, Tempe, AZ 85287 USA. Chinese Acad Sci, S China Inst Bot, Guangzhou 510650, Peoples R China. Water Serv Dept City Phoenix, Phoenix, AZ 85003 USA. Univ Nevada, Dept Environm & Resource Sci, Reno, NV 89512 USA. Wu, JG, Arizona State Univ, Dept Plant Biol, Tempe, AZ 85287 USA. jingle@asu.eduEnglish|?N +Wu, Xiaolan Murray, Alan T. Xiao, Ningchuan2011cA multiobjective evolutionary algorithm for optimizing spatial contiguity in reserve network design425-437Landscape Ecology263Mar]Landscape fragmentation is a well-recognized threat to the long-term survivability of many plant and animal species. As a complex concept, fragmentation has multiple spatial and functional components, of which spatial contiguity is of great importance. A contiguous landscape provides physical condition and increases the opportunities for species dispersal and migration. However, in real planning situations, contiguity is either too expensive to achieve or impractical because of barriers of urban landscapes. As such, the traditional yes/no function of contiguity has been extended into a notion of relative contiguity which has the value range between zero and one. Relative contiguity measures levels of interconnectivity of landscapes based on graph theory and spatial interaction. It takes into account both inner-reserve relationship (i.e. reserve sizes) and inter-reserve spatial proximity. This paper presents a multiobjective evolutionary algorithm approach to maximizing relative contiguity in reserve network design. This approach obtains solutions that maximize the measure of relative contiguity, minimize the total acquisition area, and satisfy constraints on the coverage of individual species. Application results show the developed algorithm has significant advantages in optimizing relative contiguity and generating a variety of alternative solutions.!://WOS:000288808100010Times Cited: 0 0921-2973WOS:00028880810001010.1007/s10980-011-9571-9#|?Q Wulf, Monika Rujner, Hendrik2011~A GIS-based method for the reconstruction of the late eighteenth century forest vegetation in the Prignitz region (NE Germany)153-168Landscape Ecology262FebOur goal was to reconstruct the late eighteenth century forest vegetation of the Prignitz region (NE Germany) at a scale of 1:50,000. We also wanted to relate the historical forest vegetation to the actual and potential natural vegetation. For these purposes, we selected 15 woody species and transferred relevant data found in historical records from various sources together with the recent localities of (very) old individuals belonging to these woody species into ArcView GIS. Following multi-step data processing including the generation of a point density layer using a moving window with kernel estimation and derivation of vegetation units applying Boolean algebra rules together with information on site conditions, we derived 17 forest communities corresponding to the potential natural vegetation. We were able to reconstruct the historical forest vegetation for 90% of the forest area ca. 1780. Only two of the 17 forest communities covered large parts of the forested area. The oak forest with Agrostis capillaris covered about 44% of the total forest area, and alder forests on fenland made up about 37%. Oak-hornbeam forests with Stellaria holostea comprised slightly less than 6% of the forest area, while all other forest communities comprised less than 1%. The historical forest vegetation is more similar to the potential forest vegetation and quite different from the actual forest vegetation because coniferous tree species currently cover approximately two-thirds of the actual forest area. The most beneficial result of this study is the map of high-resolution historical vegetation units that may serve as the basis for various further studies, e.g., modelling long-term changes in biodiversity at the landscape scale.!://WOS:000286474900001Times Cited: 1 0921-2973WOS:00028647490000110.1007/s10980-010-9555-1D|? Wulf, M. Sommer, M. Schmidt, R.2010|Forest cover changes in the Prignitz region (NE Germany) between 1790 and 1960 in relation to soils and other driving forces299-313Landscape Ecology252Decadal to centennial land-cover changes are important drivers of many environmental issues, including biodiversity, biogeochemical cycles and, especially, the global carbon balance. In general, changes are well documented over only a few decades. Studies of land-cover changes and its drivers over centuries are rare. Therefore, the main objectives of this study are (1) to trace the development of the actual pattern of forest-open land over 170 years, and (2) to associate land-cover classes with site conditions (soils) as well as with other driving forces during three periods (1790-1838, 1838-1870, and 1870-1960). For these purposes, we used a combined approach of GIS-techniques and historical reconstructions from archives. The shifts of percentages for established forests, afforestation, clearings and open land on different soils were checked using a chi square test. From the archives, we obtained information on demographic, political/institutional and economic/technological factors, which are assumed to be drivers for past land-cover changes. Percentages of most land-cover classes hardly differed between the periods. However, established forests remained mainly on sandy soils and, to a large extend, afforestation was realised on sandy soils. Clearings reached high percentages on fluvial sands and organic sediments in the early period. A complex of demographic, political/institutional and economic/technological factors also had a considerable impact on land use/cover change in the Prignitz region. Thus, in addition to the strong association of land-cover classes with soils, our study demonstrated that other driving forces, i.e. political and economic factors, played an important role in the full understanding of land use from the past to the present.!://WOS:000274437100010Times Cited: 0 0921-2973WOS:00027443710001010.1007/s10980-009-9411-3<73Xiao, X. Y. Gertner, G. Wang, G. X. Anderson, A. B.2005LOptimal sampling scheme for estimation landscape mapping of vegetation cover375-387Landscape Ecology204 geostatistics; global estimation; local estimation; sampling design; soil erosion; uncertainty REMOTE-SENSING INVESTIGATIONS; SOIL LOSS EQUATION; REGIONALIZED VARIABLES; UNCERTAINTY ASSESSMENT; SPATIAL-RESOLUTION; LOCAL ESTIMATION; DESIGN; SIZE; EFFICIENCY; PROGRAMArticleMay/An optimization of a sampling design alms at decreasing costs Without losing necessary spatial information and desired precision for estimation and mapping of vegetation cover. This study concentrates on investigating optimal solutions for sampling design, considering both plot and sample size in terms of cost and variance estimated for global estimation and local landscape mapping of overall vegetation cover used in the management of soil erosion. A geostatistical method was developed based on regionalized variable theory and compared to a classical random sampling method for a case study in which optimal sampling was designed for estimating and mapping vegetation cover. Cost is introduced into the sampling design in terms of measurement time. This method has made it possible to seek optimal solutions for determining plot and sample sizes given a desired precision and allowable Survey cost budget for both local and global estimation. The results show that the geostatistical method is more cost-efficient than the classical designs because it accounts for spatial dependence of variables in the sampling design. Moreover, plot size affects kriging standard error of the local estimate more significantly than sample size, while sample size has more effect on precision of the global estimate than does plot size.://000233035100002 ISI Document Delivery No.: 980RE Times Cited: 2 Cited Reference Count: 30 Cited References: ARVANITIS LG, 1967, HILGARDIA, V38, P133 ARVANITIS LG, 1991, C OPT DES FOR EXP SU, P107 ATKINSON PM, 1991, INT J REMOTE SENS, V12, P559 ATKINSON PM, 1997, PHOTOGRAMM ENG REM S, V63, P1345 BURGESS TM, 1981, J SOIL SCI, V32, P643 COCHRAN WG, 1977, SAMPLING TECHNIQUES CURRAN PJ, 1986, REMOTE SENS ENVIRON, V20, P31 CURRAN PJ, 1988, REMOTE SENS ENVIRON, V24, P493 DIERSING VE, 1992, ENVIRON MANAGE, V16, P405 GOOVAERTS P, 1997, GEOSTATISTICS NATURA HENDRICKS WA, 1956, MATH THEORY SAMPLING JOURNEL AG, 1978, MINING GEOSTATISTICS MCBRATNEY AB, 1981, COMPUT GEOSCI, V7, P331 MCBRATNEY AB, 1981, COMPUT GEOSCI, V7, P335 MCBRATNEY AB, 1983, SOIL SCI, V135, P177 MCGWIRE K, 1993, INT J REMOTE SENS, V14, P2137 MESAVAGE C, 1956, J FOREST, V54, P569 OLEA RA, 1984, J INT ASS MATH GEOL, V16, P369 OREGAN WG, 1966, FOREST SCI, V12, P406 RENARD KG, 1997, USDA AGR HDB, V703, P1 SINGH D, 1986, THEORY ANAL SAMPLE S TAZIK DJ, 1992, N9203 CONSTR ENG RE THOMPSON S, 1992, WILEY SERIES PROBABI WANG GX, 2001, CATENA, V46, P1 WANG GX, 2001, ISPRS J PHOTOGRAMM, V56, P65 WANG GX, 2001, PHOTOGRAMM ENG REM S, V67, P575 WARREN SD, 1990, PHOTOGRAMM ENG REM S, V56, P333 WEBSTER R, 1989, REMOTE SENS ENVIRON, V29, P67 WIEGERT RG, 1962, ECOLOGY, V43, P125 YFANTIS EA, 1987, MATH GEOL, V19, P183 0921-2973 Landsc. Ecol.ISI:000233035100002Univ Illinois, Urbana, IL 61801 USA. Army Corps Engineers, CERL, Champaign, IL USA. Gertner, G, Univ Illinois, W503 Turner Hall,1102 S Goodwin Ave, Urbana, IL 61801 USA. gertner@uiuc.eduEnglish8<7.(Xie, Y. C. Yu, M. Bai, Y. F. Xing, X. R.2006bEcological analysis of an emerging urban landscape pattern-desakota: a case study in Suzhou, China 1297-1309Landscape Ecology218Desakota; landscape ecology; tempo-spatial transition; the lower Yangtze River Delta LAND-COVER CHANGES; RURAL INTERACTION; IMAGERY; TRANSFORMATION; SYSTEM; AGENDA; CITIES; MEXICO; FORM; USAArticleNov+Recent scholarly efforts to investigate the conventional wisdom of urban transition and conceptualize the distinct patterns of urbanization emerging in China, simply referred to as "desakota", have not yielded any conclusive validation. The possible existence of "desakota" is significant for landscape ecology and regional science research in that it challenges long cherished Western notions concerning the separation of urban processes from rural processes and the spatial uniqueness of the respective landscapes. This paper examines physical evidence of desakota from land use changes and tempo-spatial dynamics of desakota development in the lower Yangtze River Delta-one of the most populous and rapidly growing economic regions in China. The paper uses satellite data in 1990, 1995 and 2000 to spectrally disaggregate such rural landscape patterns as urban construction expanding from existing commercial and industrial centers, rural non-agricultural construction, special large infrastructure construction, and crop cultivation. The paper inspects one transect (60 km long and 12 km wide) cutting across Suzhou City in south and Changshu City in north. The transect is divided into four segments to investigate quantitative changes of land types between the two cities over time. The paper applies landscape ecological metrics to analyze tempo-spatial patterns of desakota changes in terms of counts, densities, shapes, compositions, spatial relationships and diversities. The paper concludes: (1) desakota occurred in Suzhou area before 1990 and witnessed two phases of development, dramatic expansion between 1990 and 1995 and consolidation during 19952000; (2) desakota dynamics show distinct spatial patterns, new growth of large and specialized urban districts dominant in the vicinity of large cities (Suzhou) and incremental expansion of existing urban places in small cities and rural areas; and (3) landscape metrics are very informative in discerning dynamics and patterns of land use and land cover changes and different metrics vary in descriptive power and sensitivity.://000242089300010  ISI Document Delivery No.: 106GP Times Cited: 0 Cited Reference Count: 71 Cited References: *US CLIM CHANG SCI, 2003, STRAT PLAN US CLIM C *WORLD BANK, 2001, CHIN AIR LAND WAT EN ALONSO W, 1971, IND LOCATION REGIONA, P3 BAKER WL, 1992, LANDSCAPE ECOL, V7, P291 BOUTET JC, 2003, LANDSCAPE ECOL, V18, P553 COLLINS JB, 1994, REMOTE SENS ENVIRON, V50, P267 DAVIS K, 1968, CITY NEWLY DEV COUNT, P5 DORNER B, 2002, LANDSCAPE ECOL, V17, P729 DOUGLASS M, 1998, THIRD WORLD PLAN REV, V20, P1 FANG C, 2002, DESIGN STUDY SHENZHE FISCHER G, 1998, IR98047 INT I APPL S FRIEDMANN J, 1975, URBAN TRANSITION COM FRIEDMANN J, 1996, ENVIRON URBAN, V8, P129 FUNG T, 1990, IEEE T GEOSCI REMOTE, V28, P681 GARDNER RH, 1991, QUANTITATIVE METHODS, P289 GINSBERG NB, 1998, URBAN DEV ASIA RETRO, P3 GINSBURG NB, 1991, EXTENDED METROPOLIS GORDON S, 1980, REMOTE SENS ENVIRON, V9, P189 HAUSER PM, 1965, STUD URBANIZATION, P503 HESSBURG PF, 1999, ECOL APPL, V9, P1232 KIRKBY R, 2000, URBAN LAND REFORM CH LAMPARD E, 1955, EC DEV CULTURAL CHAN, V3, P81 LEE ES, 1966, DEMOGRAPHY, V3, P47 LI HB, 2004, LANDSCAPE ECOL, V19, P389 LIEBERTHAL K, 1995, GOVERNING CHINA REVO LIN C, 1997, RED CAPITALISM S CHI LIN C, 2001, URBAN STUD, V38, P383 LIN GCS, 2001, PROF GEOGR, V53, P56 LIPTON M, 1984, J DEV STUD, V20, P139 LIU J, 2002, SCI CHINA SER D, V46, P373 LIU JY, 2002, J GEOGRAPHICAL SCI, V12, P275 LOGAN J, 2002, NEW CHINESE CITY LUCK M, 2002, LANDSCAPE ECOL, V17, P327 MA LJC, 2002, ENVIRON PLANN A, V34, P1545 MARTON A, 2000, CHINAS SPATIAL EC DE MCGARIGAL K, 1995, PNWGTR351 USDA FOR S MCGEE TG, 1989, URBANIZATION ASIA SP, P93 MCGEE TG, 1991, EXTENDED METROPOLIS, P3 MERA K, 1973, EC DEV CULTURAL CHAN, V21, P309 NAUGHTON B, 1999, PARADOX CHINAS POST OI JC, 1999, RURAL CHINA TAKES OF PANNELL CW, 1991, EXTENDED METROPOLIS, P113 PANNELL CW, 2002, ENVIRON PLANN A, V34, P1571 PETERSEN W, 1975, POPULATION PILON PG, 1988, PHOTOGRAMMETRIC ENG, V54, P1709 POTTER RB, 1995, CITIES, V12, P67 QUARMBY NA, 1989, INT J REMOTE SENS, V10, P953 RUIZLUNA A, 2003, LANDSCAPE ECOL, V18, P159 SETO KC, 2005, LANDSCAPE ECOL, V20, P871 SWENSON JJ, 2000, LANDSCAPE ECOL, V15, P713 TACOLI C, 1998, ENVIRON URBAN, V10, P147 TANG W, 2000, CHINAS REGIONS POLIT, P275 TIMBERLAKE M, 1985, URBANIZATION WORLD E TURNER BL, 1989, GLOBAL CHANGE OUR CO, P90 TURNER BL, 1991, INT SOC SCI J, V43, P669 TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 TURNER MG, 2001, LANDSCAPE ECOLOGY TH VEECK G, 1991, EXTENDED METROPOLIS, P157 VELAZQUEZ A, 2003, GLOBAL ENVIRON CHANG, V13, P175 VOLLER J, 1998, CONSERVATION BIOL PR WANG F, 1993, IEEE T GEOSCI REMOTE, V31, P136 WEBER M, 1958, CITY FREE PRESS GLEN WEI YHD, 2002, ENVIRON PLANN A, V34, P1725 WU JG, 2004, LANDSCAPE ECOL, V19, P125 XIE Y, 2003, ASIAN GEOGR, V22, P119 XIE YC, 2005, GLOBAL ENVIRON CHANG, V15, P238 YAO S, 1992, URBAN AGGLOMERATIONS YEH AGO, 1997, INT PLANNING STUDIES, V2, P193 YEUNG YM, 1998, URBAN DEV ASIA RETRO, P283 ZHOU YX, 1991, EXTENDED METROPOLIS, P89 ZHOU YX, 2000, URBAN GEOGR, V21, P205 0921-2973 Landsc. Ecol.ISI:000242089300010Eastern Michigan Univ, Dept Geog & Geol, Ypsilanti, MI 48197 USA. Chinese Acad Sci, Inst Bot, Lab Quantitat Vegetat Ecol, Beijing 100093, Peoples R China. Xie, YC, Eastern Michigan Univ, Dept Geog & Geol, Ypsilanti, MI 48197 USA. yxie@emich.eduEnglishy|? DXu, Chonggang Guneralp, Burak Gertner, George Z. Scheller, Robert M.2010|Elasticity and loop analyses: tools for understanding forest landscape response to climatic change in spatial dynamic models855-871Landscape Ecology256JulSpatially explicit dynamic forest landscape models have been important tools to study large-scale forest landscape response under global climatic change. However, the quantification of relative importance of different transition pathways among different forest types to forest landscape dynamics stands as a significant challenge. In this study, we propose a novel approach of elasticity and loop analyses to identify important transition pathways contributing to forest landscape dynamics. The elasticity analysis calculates the elasticity to measure the importance of one-directional transitions (transition from one forest type directly to another forest type); while the loop analysis is employed to measure the importance of different circular transition pathways (transition from one forest type through other forest types back to itself). We apply the proposed approach to a spatially explicit dynamic model, LANDIS-II, in a study of forest landscape response to climatic change in the Boundary Waters Canoe Area (BWCA) incorporating the uncertainties in climatic change predictions. Our results not only corroborate the findings of the previous studies on the most likely future forest compositions under simulated climatic variability, but also, through the novel application of the elasticity and loop analyses concepts, provide a quantitative assessment of the specific mechanisms leading to particular forest compositions, some of which might remain undetected with conventional model evaluation methods. By quantifying the importance of specific processes (transitions among forest types) to forest composition dynamics, the proposed approach can be a valuable tool for a more quantitative understanding of the relationship between processes and landscape composition/patterns.!://WOS:000278526000004Times Cited: 0 0921-2973WOS:00027852600000410.1007/s10980-010-9464-34}?CXu, Chi Liu, Maosong Zhang, Cheng An, Shuqing Yu, Wen Chen, Jing M.2007]The spatiotemporal dynamics of rapid urban growth in the Nanjing metropolitan region of China925-937Landscape Ecology226Jul&://BIOSIS:PREV200700463292 0921-2973BIOSIS:PREV200700463292 j<7 8Xu, C. Liu, M. S. Hong, C. Chi, T. An, S. Q. Yang, X. J.2012Temporal variation of characteristic scales in urban landscapes: an insight into the evolving internal structures of China's two largest cities 1063-1074Landscape Ecology277characteristic scale domain urban structure remote sensing urbanization wavelet analysis nanjing metropolitan region land-use change wavelet analysis spatiotemporal dynamics gradient analysis urbanization patterns ecology growth USAAugUrbanization has induced profound landscape changes. While the spatiotemporal patterns of urban landscapes have been extensively studied, the manner by which the internal structures of already urbanized areas change remains little understood. Characteristic scales are an important measure of landscape structure, and they represent the typical spatial extents of landscape elements in hierarchies. In this study, we quantified temporal variations of the characteristic scales in the central urban landscapes of Beijing and Shanghai over an 18 year period. Using transect data from Landsat images, characteristic scales were identified through wavelet analysis and then classified into several discrete domains using the k-means clustering method. These characteristic scale domains appeared to correspond with the typical extents of the blocks and block clusters in the study areas. Results showed that the number of the characteristic scale domains changed within a small range of 3-5 while the mean values of the characteristic scales within the domains showed substantial temporal variation. Larger characteristic scales were more variable than smaller ones in both cities. Distinguishing relative change rates of building forms, land use and street layout of urban landscapes allowed us to interpret these differences. The street layout of urban landscapes usually reacts slowly to the force of change, acting as the skeleton of the urban landscape. As a result, block sizes can remain relatively stable and corresponding characteristic scales present inheritance features. Land use and building forms are more susceptible to changes. Block clusters with flexible extents could result in significant variation of characteristic scales.://000306068200010-969PP Times Cited:0 Cited References Count:62 0921-2973Landscape EcolISI:000306068200010Liu, MS Nanjing Univ, Sch Life Sci, 22 Hankou Rd, Nanjing 210093, Jiangsu, Peoples R China Nanjing Univ, Sch Life Sci, 22 Hankou Rd, Nanjing 210093, Jiangsu, Peoples R China Nanjing Univ, Sch Life Sci, Nanjing 210093, Jiangsu, Peoples R ChinaDOI 10.1007/s10980-012-9764-xEnglish ?{+Gal Yaacobi Yaron Ziv Michael L. Rosenzweig2007tEffects of interactive scale-dependent variables on beetle diversity patterns in a semi-arid agricultural landscape 687-703Landscape Ecology225Carabidae - Fragmentation - GIS - Habitat variability - Landscape heterogeneity - Patch size - Path analysis - Remote sensing - Species diversity - Tenebrionidae Understanding species-diversity patterns in heterogeneous landscapes invites comprehensive research on how scale-dependent processes interact across scales. We used two common beetle families (Tenebrionidae, detrivores; Carabidae, predators) to conduct such a study in the heterogeneous semi-arid landscape of the Southern Judean Lowland (SJL) of Israel, currently undergoing intensive fragmentation. Beetles were censused in 25 different-sized patches (500–40,000 m2). We used Fisher’s α and non-parametric extrapolators to estimate species diversity from 11,125 individuals belonging to 56 species. Patch characteristics (plant species diversity and cover, soil cover and degree of stoniness) were measured by field transects. Spatial variables (patch size, shape, physiognomy and connectivity) and landscape characteristics were analyzed by GIS and remote-sensing applications. Both patch-scale and landscape-scale variables affected beetle species diversity. Path-analysis models showed that landscape-scale variables had the strongest effect on carabid diversity in all patches. The tenebrionids responded differently: both patch-scale and landscape-scale variables affected species diversity in small patches, while mainly patch-scale variables affected species diversity in large patches. Most of the paths affected species diversity both directly and indirectly, combining the effects of both patch-scale and landscape-scale variables. These results match the biology of the two beetle families: Tenebrionidae, the less mobile and more site-attached family, responded to the environment in a fine-grained manner, while the highly dispersed Carabidae responded to the environment in a coarse-grained manner. We suggest that understanding abiotic and biotic variable interactions across scales has important consequences for our knowledge of community structure and species diversity patterns at large spatial scales. ڽ7>@Yang, Jiuyan Cushman, SamuelA Yang, Jie Yang, Mingbo Bao, Tiejun2013`Effects of climatic gradients on genetic differentiation of Caragana on the Ordos Plateau, China 1729-1741Landscape Ecology289Springer NetherlandsJCaragana Landscape genetics Adaptive radiation Gene flow Climate gradients 2013/11/01+http://dx.doi.org/10.1007/s10980-013-9913-x 0921-2973Landscape Ecol10.1007/s10980-013-9913-xEnglish)|?K LYang, Jian Dilts, Thomas E. Condon, Lea A. Turner, P. Lee Weisberg, Peter J.2011Longitudinal- and transverse-scale environmental influences on riparian vegetation across multiple levels of ecological organization381-395Landscape Ecology263MarRiparian vegetation is distinct from adjacent upland terrestrial vegetation and its distribution is affected by various environmental controls operating at the longitudinal scale (along the river) or transverse scale (perpendicular to the river). Although several studies have shown how the relative importance of transverse or longitudinal influences varies with the scale of observation, few have examined how the influences of the two scales vary with the level of ecological organization. We modeled vegetation-environment relationships at three hierarchically nested levels of ecological organization: species, plant community, and vegetation type. Our hierarchically structured analyses differentiated the spatial extent of riparian zones from adjacent upland vegetation, the distribution of plant community types within the riparian zone, and the distribution of plant species within community types. Longitudinal gradients associated with climate and elevation exerted stronger effects at the species level than at the community level. Transverse gradients related to lateral surface water flux and groundwater availability distinguished riparian and upland vegetation types, although longitudinal gradients of variation better predicted species composition within either riparian or upland communities. We concur with other studies of riparian landscape ecology that the relative predictive power of environmental controls for modeling patterns of biodiversity is confounded with the spatial extent of the study area and sampling scheme. A hierarchical approach to spatial modeling of vegetation-environment relationships will yield substantial insights on riparian landscape patterns.!://WOS:000288808100007Times Cited: 0 0921-2973WOS:00028880810000710.1007/s10980-010-9565-z<7)EYao, J. Peters, D. P. C. Havstad, K. M. Gibbens, R. P. Herrick, J. E.2006SMulti-scale factors and long-term responses of Chihuahuan Desert grasses to drought 1217-1231Landscape Ecology218arid grasslands; desertification; drought; grazing; perennial grasses; transport processes SEMIDESERT GRASSLAND RANGE; CONSERVATION BIOLOGY; ECOLOGICAL RESEARCH; TRANSITION ZONE; UNITED-STATES; VEGETATION; PATTERNS; DESERTIFICATION; EROSION; SCALEArticleNovFactors with variation at broad (e.g., climate) and fine scales (e.g., soil texture) that influence local processes at the plant scale (e.g., competition) have often been used to infer controls on spatial patterns and temporal trends in vegetation. However, these factors can be insufficient to explain spatial and temporal variation in grass cover for and and semiarid grasslands during an extreme drought that promotes woody plant encroachment. Transport of materials among patches may also be important to this variation. We used long-term cover data (19152001) combined with recently collected field data and spatial databases from a site in the northern Chihuahuan Desert to assess temporal trends in cover and the relative importance of factors at three scales (plant. patch, landscape unit) in explaining spatial variation in grass cover. We examined cover of five important grass species from two topographic positions before, during, and after the extreme drought of the 1950s. Our results show that dynamics before, during, and after the drought varied by species rather than by topographic position. Different factors were related to cover of each species in each time period. Factors at the landscape unit scale (rainfall, stocking rate) were related to grass cover in the pre- and post-drought periods whereas only the plant-scale factor of soil texture was significantly related to cover of two upland species during the drought. Patch-scale factors associated with the redistribution of water (microtopography) were important for different species in the pre- and post-drought period. Another patch-scale factor, distance from historic shrub populations, was important to the persistence of the dominant grass in uplands (Bouteloua eriopoda) through time. Our results suggest the importance of local processes during the drought, and transport processes before and after the drought with different relationships for different species. Disentangling the relative importance of factors at different spatial scales to spatial patterns and long-term trends in grass cover can provide new insights into the key processes driving these historic patterns, and can be used to improve forecasts of vegetation change in and and semiarid areas.://000242089300005 < ISI Document Delivery No.: 106GP Times Cited: 0 Cited Reference Count: 61 Cited References: ABRAHAMSON WG, 2003, ECOLOGY, V84, P2476 ANDERSON JE, 2001, ECOL MONOGR, V71, P531 ARCHER S, 1994, ECOLOGICAL IMPLICATI, P13 ARNOLD GW, 1978, ETHOLOGY FREE RANGIN BAILEY DW, 1996, J RANGE MANAGE, V49, P386 BIONDINI ME, 1998, ECOL APPL, V8, P469 BRESHEARS DD, 2003, EARTH SURF PROC LAND, V28, P1189 BROWN BJ, 1989, OIKOS, V54, P189 BUFFINGTON LC, 1965, ECOL MONOGR, V35, P139 CHEVAN A, 1991, AM STAT, V45, P90 CONLEY W, 1992, COENOSES, V7, P55 FOSTER DR, 1998, ECOSYSTEMS, V1, P497 FREDRICKSON E, 1998, J ARID ENVIRON, V39, P191 GEE GW, 1986, METHODS SOIL ANAL, V1, P383 GIBBENS RP, IN PRESS 1950S DROUG GIBBENS RP, 1983, J RANGE MANAGE, V36, P145 GIBBENS RP, 1987, J RANGE MANAGE, V40, P136 GIBBENS RP, 1988, J RANGE MANAGE, V41, P186 GIBBENS RP, 2005, J ARID ENVIRON, V61, P651 GROSS BD, 2004, THESIS NEW MEXICO ST HENNESSY JT, 1983, J RANGE MANAGE, V36, P723 HERBEL CH, 1972, ECOLOGY, V53, P1084 HEYERDAHL EK, 2001, ECOLOGY, V82, P660 HOBBIE JE, 2003, BIOSCIENCE, V53, P21 HOCHSTRASSER T, 2002, J ARID ENVIRON, V51, P55 HOCHSTRASSER T, 2004, J VEG SCI, V15, P615 HUMPHREY RR, 1958, BOT REV, V24, P193 KIE JG, 2002, ECOLOGY, V83, P530 LUDWIG JA, 1997, LANDSCAPE ECOLOGY FU LUDWIG JA, 2005, ECOLOGY, V86, P288 MACK RN, 2000, ECOL APPL, V10, P689 MACNALLY R, 2000, BIODIVERS CONSERV, V9, P655 MACNALLY R, 2002, BIODIVERS CONSERV, V11, P1397 MCAULIFFE JR, 1994, ECOL MONOGR, V64, P111 MCEUEN AB, 2004, ECOLOGY, V85, P507 MONGER HC, 2002, ENCY SOIL SCI, P84 NASH MS, 1999, ECOL APPL, V9, P814 NELSON EW, 1934, USDA TECHNICAL B, V409 OKIN GS, 2001, J GEOPHYS RES-ATMOS, V106, P9673 PARSHALL T, 2003, ECOLOGY, V84, P736 PETERS DPC, IN PRESS BIOSCIENCE PETERS DPC, 2004, P NATL ACAD SCI USA, V101, P15130 PETERS DPC, 2004, WEED TECHNOL S, V18, P1221 PETERS DPC, 2006, STRUCTURE FUNCTION C POWERS JS, 1999, LANDSCAPE ECOL, V14, P105 REYNOLDS JF, 1999, ECOL MONOGR, V69, P69 SAXTON KE, 1986, SOIL SCI SOC AM J, V50, P1031 SCHLESINGER WH, 1990, SCIENCE, V247, P1043 SENFT RL, 1987, BIOSCIENCE, V37, P789 STEFFEN W, 2002, CHALLENGES CHANGING TEASCHNER TB, 2001, INFLUENCE SOIL DEPTH TONGWAY DJ, 2001, BANDED VEGETATION PA TURNER MG, 2003, BIOSCIENCE, V53, P46 VANDEKOPPEL J, 2002, AM NAT, V159, P209 WAINWRIGHT JA, 2002, J ARID ENVIRON, V51, P219 WALSH CJ, 2004, HEIR PART PACKAGE VE WHITTAKER RH, 1975, COMMUNITIES ECOSYSTE WITH KA, 2002, CONSERV BIOL, V16, P1192 WONDZELL SM, 1990, J VEG SCI, V1, P403 WOODHOUSE CA, 1998, B AM METEOROL SOC, V79, P2693 WRIGHT RG, 1976, SW NAT, V21, P259 0921-2973 Landsc. Ecol.ISI:000242089300005USDA ARS, Jornada Expt Range, Las Cruces, NM 88003 USA. Peters, DPC, USDA ARS, Jornada Expt Range, 2995 Knox St,MSC 3JER,NMSU,Box 30003, Las Cruces, NM 88003 USA. debpeter@nmsu.eduEnglish|?& Yates, A. G. Bailey, R. C.2010[Improving the description of human activities potentially affecting rural stream ecosystems371-382Landscape Ecology253eStressor (or human activity) gradients that quantify variation in the magnitude and type of human activity among sites are an important and widely applicable tool for aquatic monitoring and assessment. These gradients are typically determined from regional land cover data. We predicted that their performance could be improved by incorporating less generalized depictions of human activities. Using data from 479 rural, headwater basins we calculated four human activity gradients (HAGs) that differed in the level of detail (coarse, fine) and spatial explicitness (aspatial, spatial) used to describe human activity. Results demonstrated that the addition of fine detailed information was valuable as it resulted in a HAG that captured subtle differences in the extent of human activity among study units. In comparison, the addition of spatially explicit data added little novel information to the HAG. Analysis of fish and benthic macroinvertebrate samples from 160 of the 479 basins indicated that the addition of fine detailed and spatially explicit information significantly increased the ability of the HAG to predict variation in aquatic assemblages. We concluded that HAGs can better meet the requirements of monitoring and assessment programs if detailed and spatially explicit descriptions of human activity are used along with more typically available land cover data.!://WOS:000275122600004Times Cited: 1 0921-2973WOS:00027512260000410.1007/s10980-009-9413-1ڽ7 *Ye, Xinping Skidmore, AndrewK Wang, Tiejun2013eWithin-patch habitat quality determines the resilience of specialist species in fragmented landscapes135-147Landscape Ecology281Springer NetherlandsvHabitat fragmentation Habitat heterogeneity Habitat quality Species specialisation Agent-based model Dynamic landscape 2013/01/01+http://dx.doi.org/10.1007/s10980-012-9826-0 0921-2973Landscape Ecol10.1007/s10980-012-9826-0English?y?Yeakley, J. A. R. A. Moen D. D. Breshears M. K. Nungesser1994jResponse of North American ecosystem models to multi-annual periodicities in temperature and precipitation249-260Landscape Ecology94{model comparison, climate cycles, grassland, forest, gap models, STEPPE, LINKAGES, time series analysis, frequency analysis |7j <Yeakley, J. A. Moen, R. A. Breshears, D. D. Nungesser, M. K.1994iResponse of North-American Ecosystem Models to Multiannual Periodicities in Temperature and Precipitation249-260Landscape Ecology94rclimate cycles forest ecology grassland ecology gap models steppe linkages time series analysis frequency analysisDecEcosystem models typically use input temperature and precipitation data generated stochastically from weather station means and variances. Although the weather station data are based on measurements taken over a few decades, model simulations are usually on the order of centuries. Consequently, observed periodicities in temperature and precipitation at the continental scale that have been correlated with large-scale forcings, such as ocean-atmosphere dynamics and lunar and sunspot cycles, are ignored. We investigated how these natural climatic fluctuations affect aboveground biomass in ecosystem models by incorporating some of the more pronounced continental-scale cycles in temperature (4, 11, 80, 180 year periods) and precipitation (11 and 19 year periods) into models of three North American forests (using LINKAGES) and one North American grassland (using STEPPE). Even without inclusion of periodicities in climate, long-term dynamics of these models were characterized by internal frequencies resulting from vegetation birth, growth and death processes. Our results indicate that long-term temperature cycles result in significantly lower predictions of forest biomass than observed in the control case for a forest on a biome transition (northern hardwoods/boreal forest). Lower-frequency, higher-amplitude temprature oscillation caused amplification of forest biomass response in forests containing hardwood species. Shortgrass prairie and boreal ecosystems, dominated by species with broad stress tolerance ranges, were relatively insensitive to climatic oscillations. Our results suggest periodicities in climate should be incorporated within long-term simulations of ecosystems with strong internal frequencies, particularly for systems on biome transitions.://A1994PX89500002,Px895 Times Cited:2 Cited References Count:0 0921-2973ISI:A1994PX89500002GLos Alamos Natl Lab,Environm Sci Grp,Mail Stop J495,Los Alamos,Nm 87545English<7Young, C. H. Jarvis, P. J.2001LMeasuring urban habitat fragmentation: an example from the Black Country, UK643-658Landscape Ecology167connectivity contiguity fragmentation habitat quality land-use landscape urban habitats West Midlands LANDSCAPE CONNECTIVITY INFORMATION-SYSTEMS CONSERVATION GREENWAYS DISPERSAL STRATEGY ECOLOGY SCALEArticleOct7The processes of urbanisation have left a fragmented mosaic of habitat patches of varying size, shape and character with the result that from location to location the number and quality of contacts between patches varies considerably. Traditional measurements of this habitat fragmentation, and its converse, connectivity, have rarely looked at the landscape as a whole but instead have simplified it to specific landscape subsets, or else have looked at area-to-area relationships through generalising the landscape into homogeneous pixels or grids. In this paper the character of the whole landscape is examined at scales appropriate to the spatial variability of the urban environment. Using a direct measurement of patch-to-patch contact all contacts between all patches are examined and the relationship between all contiguous and connecting habitats is quantified. This is further refined to look at connections between patches of different quality, a measure that highlights the adverse effects of urbanisation as a whole on landscape connections between quality habitats.://000172809400005 ISI Document Delivery No.: 503QG Times Cited: 3 Cited Reference Count: 41 Cited References: *NAT CONS COUNC, 1990, HDB PHAS 1 HAB SURV AHERN J, 1995, LANDSCAPE URBAN PLAN, V33, P131 ANDREN H, 1994, OIKOS, V71, P355 BARKER GMA, 1997, 256 ENGL NAT BEIER P, 1998, CONSERV BIOL, V12, P1241 COLLINGE SK, 1996, LANDSCAPE URBAN PLAN, V36, P59 DAWSON D, 1994, 94 ENGL NAT DAWSON KJ, 1995, LANDSCAPE URBAN PLAN, V33, P27 DOAK DF, 1992, THEOR POPUL BIOL, V41, P315 FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FORMAN RTT, 1995, LANDSCAPE ECOL, V10, P133 GILBERT OL, 1989, ECOLOGY URBAN HABITA GOODE DA, 1989, J APPL ECOL, V26, P859 HARDY PB, 1997, URBAN NATURE MAGAZIN, V3, P6 JAEGER JAG, 2000, LANDSCAPE ECOL, V15, P115 JANSSENS P, 1988, CONNECTIVITY LANDSCA, P43 JOHNSON CW, 1995, LANDSCAPE URBAN PLAN, V32, P219 JOHNSON LB, 1990, LANDSCAPE ECOL, V4, P31 KNIGHT TW, 1996, ECOLOGY, V77, P1756 KOVAR P, 1995, LANDSCAPE URBAN PLAN, V32, P137 KOZOVA M, 1986, EKOL CSSR, V5, P187 LINEHAN J, 1995, LANDSCAPE URBAN PLAN, V33, P179 MCDONNELL MJ, 1988, CONNECTIVITY LANDSCA, P17 METZGER JP, 1997, ACTA OECOL, V18, P1 MOILANEN A, 1998, ECOLOGY, V79, P2503 PITHER J, 1998, OIKOS, V83, P166 REBELE F, 1994, GLOBAL ECOL BIOGEOGR, V4, P173 RIITTERS KH, 1997, BIOL CONSERV, V81, P191 SCHILLER A, 1997, URBAN ECOL, V1, P103 SCHIPPERS P, 1996, ECOGRAPHY, V19, P97 SCHUMAKER NH, 1996, ECOLOGY, V77, P1210 SISINNI SM, 1993, URBAN PLANNING, V25, P95 SUKOPP H, 1980, GARTEN LANDSCHAFT, V7, P565 SZACKI J, 1994, MEMORABILIA ZOOLOGIC, V49, P49 THOMAS CD, 1995, ECOLOGY CONSERVATION, P46 TURNER MG, 1990, LANDSCAPE ECOL, V4, P21 VEITCH N, 1995, BIOL CONSERV, V72, P91 WILCOVE DS, 1986, CONSERVATION BIOL SC, P237 WITH KA, 1997, OIKOS, V78, P151 WITTIG R, 1983, BIOL CONSERV, V26, P57 YOUNG CH, IN PRESS ENV MANAG 0921-2973 Landsc. Ecol.ISI:000172809400005Wolverhampton Univ, Sch Appl Sci, Wolverhampton WV1 1DJ, W Midlands, England. Young, CH, Wolverhampton Univ, Sch Appl Sci, Wulfruna St, Wolverhampton WV1 1DJ, W Midlands, England.Englishڽ7 -Zaitsev, AndreiS Straalen, NicoM Berg, MattyP2013WLandscape geological age explains large scale spatial trends in oribatid mite diversity285-296Landscape Ecology282Springer NetherlandsxOribatida Acari Geological age Soil fauna diversity Spatial distribution Landscape Mite Forest vegetation type Soil type 2013/02/01+http://dx.doi.org/10.1007/s10980-012-9834-0 0921-2973Landscape Ecol10.1007/s10980-012-9834-0English~?p Zajac, R. N.20087Challenges in marine, soft-sediment benthoscape ecology7-18Landscape Ecology23In this paper I address three sets of challenges that face ecologists who are studying soft-sediment benthic landscapes (or benthoscapes). These include (a) development of technology and analytical approaches for sea floor mapping and quantifying benthoscape structure, (b) development of benthoscape ecology theory that integrates ideas from terrestrial and other marine systems, but focuses on the unique aspects of these environments, and (c) making empirical headway. Coordinated efforts in all three areas are needed to make progress in understanding soft-sediment systems, which arguably comprise the largest set of landscapes on the earth. In particular, much more work is needed in relating biotic patterns to the actual spatial structural aspects of soft-sediment benthoscapes."://WOS:000252922800002 Times Cited: 0WOS:000252922800002(10.1007/s10980-007-9140-4|ISSN 0921-2973? =Zald, Harold Spies, Thomas Huso, Manuela Gatziolis, Demetrios2012Climatic, landform, microtopographic, and overstory canopy controls of tree invasion in a subalpine meadow landscape, Oregon Cascades, USA 1197-1212Landscape Ecology278Springer NetherlandsBiomedical and Life SciencesTree invasions have been documented throughout Northern Hemisphere high elevation meadows, as well as globally in many grass and forb-dominated ecosystems. Tree invasions are often associated with large-scale changes in climate or disturbance regimes, but are fundamentally driven by regeneration processes influenced by interactions between climatic, topographic, and biotic factors at multiple spatial scales. The purpose of this research was to quantify spatiotemporal patterns of meadow invasion; and how climate, larger landforms, topography, and overstory trees have interactively influenced tree invasion. We combined airborne Light Detection and Ranging (LiDAR) characterizations of landforms, topography, and overstory vegetation with historical climate, field measurements of snow depth, tree abundance, and tree ages to reconstruct spatial and temporal patterns of tree invasion over five decades in a subalpine meadow complex in the Oregon Cascade Range, USA. Proportion of meadow occupied by trees increased from 8 % in 1950 to 35 % in 2007. Larger landforms, topography, and tree canopies interactively mediated regional climatic controls of tree invasion by modifying depth and persistence of snow pack, while tree canopies also influenced seed source availability. Landscape context played an important role mediating snow depth and tree invasion; on glacial landforms tree invasion was negatively associated with spring snowfall, but on debris flows tree invasion was not associated with snow fall. The importance of snow, uncertain climate change impacts on snow, and mediation of snow by interacting and context dependent factors in complex mountain terrain poses substantial hurdles for understanding how these ecotones may respond to future climate conditions.+http://dx.doi.org/10.1007/s10980-012-9774-8 0921-297310.1007/s10980-012-9774-8 <7@Zampella, R. A. Lathrop, R. G.1997gLandscape changes in Atlantic white cedar (Chamaecyparis thyoides) wetlands of the New Jersey Pinelands397-408Landscape Ecology126^Atlantic white cedar wetlands; Chamaecyparis thyoides; disturbance; succession; Pinelands PINEArticleDec1Assessing the long-term sustainability of Atlantic white cedar (Chamaecyparis thyoides) wetlands in the New Jersey Pinelands is an important management concern. We used aerial photography dating from 1930 through 1991 and recent satellite imagery to quantify successional trends in these wetlands within the 1,473 km(2) Mullica River basin. Over the 61-yr period the composition of individual cedar patches in the study area changed in response to varying disturbance regimes but total cedar cover remained relatively stable. The dominant transitions were conversion of cedar to shrub cover and succession from shrub to cedar. Cedar harvesting, which was the dominant disturbance, was most intense during the early part of the study period. A decline in successful regeneration of more recent cedar cuts may be related to an increase in the Pinelands deer herd. Other major disturbances included wildfires and flooding. Most flooding was associated with beaver activity. Although the long-term effects of changing disturbance regimes are unknown, our results suggest a positive outlook for sustainability of Atlantic white cedar wetlands within the Mullica River basin. important management considerations that can affect cedar sustainability include effective post-harvest management of cut swamps and restoration of cedar in shrub or emergent dominated areas that historically contained cedar. Because hardwood conversion of undisturbed cedar patches was not a major transition, cedar harvesting to rejuvenate stands does not seem necessary to maintain Atlantic white cedar wetlands.://000077684400004 ISI Document Delivery No.: 150UR Times Cited: 4 Cited Reference Count: 22 Cited References: *PIN COMM, 1980, NEW JERS PIN COMPR M APPLEGATE JE, 1979, PINE BARRENS ECOSYST, P25 COLLINS BR, 1988, PROTECTING NEW JERSE CRAIG LJ, 1993, NEW YORK STATE MUSEU, V487 EHRENFELD JG, 1991, J APPL ECOL, V28, P467 FORMAN RTT, 1979, PINE BARRENS ECOSYST FORMAN RTT, 1981, B TORREY BOT CLUB, V108, P34 GLENNLEWIN DC, 1992, PLANT SUCCESSION THE, P11 LADERMAN AD, 1989, 85 US FISH WILDL SER LITTLE S, 1950, YALE U SCH FORESTRY, V56, P1 LITTLE S, 1951, B TORREY BOTANICAL C, V78, P153 LITTLE S, 1964, P ANN TALL TIMB FIR, V3, P34 LITTLE S, 1965, US FOR SERV RES NOTE, V33, P1 LITTLE S, 1979, PINE BARRENS ECOSYST, P297 MCCORMICK J, 1979, PINE BARRENS ECOSYST, P229 REINERT HK, 1988, COPEIA, P964 ROMAN CT, 1990, WETLAND ECOLOGY MANA, P163 SPRUGEL DG, 1985, ECOLOGY NATURAL DIST, P335 WANDLESS I, 1981, J CLIN HOSP PHARM, V6, P51 ZAMPELLA RA, 1987, ATLANTIC WHITE CEDAR, P295 ZAMPELLA RA, 1988, PROTECTING NEW JERSE, P214 ZAMPELLA RA, 1992, B TORREY BOT CLUB, V119, P253 0921-2973 Landsc. Ecol.ISI:000077684400004nPinelands Commiss, New Lisbon, NJ 08064 USA. Zampella, RA, Pinelands Commiss, POB 7, New Lisbon, NJ 08064 USA.English|?IiZeller, Katherine A. McGarigal, Kevin Beier, Paul Cushman, Samuel A. Vickers, T. Winston Boyce, Walter M.2014Sensitivity of landscape resistance estimates based on point selection functions to scale and behavioral state: pumas as a case study541-557Landscape Ecology293MarEstimating landscape resistance to animal movement is the foundation for connectivity modeling, and resource selection functions based on point data are commonly used to empirically estimate resistance. In this study, we used GPS data points acquired at 5-min intervals from radiocollared pumas in southern California to model context-dependent point selection functions. We used mixed-effects conditional logistic regression models that incorporate a paired used/available design to examine the sensitivity of point selection functions to the scale of available habitat and to the behavioral state of individual animals. We compared parameter estimates, model performance, and resistance estimates across 37 scales of available habitat, from 250 to 10,000 m, and two behavioral states, resource use and movement. Point selection functions and resistance estimates were sensitive to the chosen scale of the analysis. Multiple characteristic scales were found across our predictor variables, indicating that pumas in the study area are responding at different scales to different landscape features and that multi-scale models may be more appropriate. Additionally, point selection functions and resistance estimates were sensitive to behavioral state; specifically, pumas engaged in resource use behavior had an opposite selection response to some land cover types than pumas engaged in movement behavior. We recommend examining a continuum of scales and behavioral states when using point selection functions to estimate resistance.!://WOS:000331935500015Times Cited: 2 0921-2973WOS:00033193550001510.1007/s10980-014-9991-4 <7 +Zeller, K. A. McGarigal, K. Whiteley, A. R.20125Estimating landscape resistance to movement: a review777-797Landscape Ecology276connectivity cost/friction surface landscape permeability corridors resistant kernel landscape pattern wildlife american black bears gene flow expert opinion population-structure habitat linkages martes-americana connectivity distance models dispersalJul>Resistance surfaces are often used to fill gaps in our knowledge surrounding animal movement and are frequently the basis for modeling connectivity associated with conservation initiatives. However, the methods for quantifying resistance surfaces are varied and there is no general consensus on the appropriate choice of environmental data or analytical approaches. We provide a comprehensive review of the literature on this topic to highlight methods used and identify knowledge gaps. Our review includes 96 papers that parameterized resistance surfaces (sometimes using multiple approaches) for a variety of taxa. Data types used included expert opinion (n = 76), detection (n = 23), relocation (n = 8), pathway (n = 2), and genetic (n = 28). We organized the papers into three main analytical approaches; one-stage expert opinion, one-stage empirical, and two-stage empirical, each of which was represented by 43, 22, and 36 papers, respectively. We further organized the empirical approaches into five main resource selection functions; point (n = 16), matrix (n = 38), home range (n = 3), step (n = 1), and pathway (n = 1). We found a general lack of justification for choice of environmental variables and their thematic and spatial representation, a heavy reliance on expert opinion and detection data, and a tendency to confound movement behavior and resource use. Future research needs include comparative analyses on the choice of environmental variables and their spatial and thematic scales, and on the various biological data types used to estimate resistance. Comparative analyses amongst analytical processes is also needed, as well as transparency in reporting on uncertainty in parameter estimates and sensitivity of final resistance surfaces, especially if the resistance surfaces are to be used for conservation and planning purposes.://000305218000001-958DZ Times Cited:0 Cited References Count:86 0921-2973Landscape EcolISI:000305218000001Zeller, KA Univ Massachusetts, Dept Environm Conservat, Amherst, MA 01003 USA Univ Massachusetts, Dept Environm Conservat, Amherst, MA 01003 USA Univ Massachusetts, Dept Environm Conservat, Amherst, MA 01003 USA Panthera, New York, NY 10018 USADOI 10.1007/s10980-012-9737-0English<7"Zhang, M. H. Geng, S. Ustin, S. L.1998rQuantifying the agricultural landscape and assessing spatio-temporal patterns of precipitation and groundwater use37-53Landscape Ecology131|groundwater crops soils quantitative indices spatial patterns temporal variation Geographic Information System INDEXES SCALEArticleFebQuantitative agricultural landscape indices are useful to describe functional relationships among climatic conditions, groundwater dynamics, soil properties and agricultural land use for mathematical models. We applied methods of regression statistics, variance component estimation and a Geographical Information System (GIS) to construct indices describing crops and soils and to establish functional relationships among these variables. This paper describes the development of indices and the partitioning of the spatial and temporal variation in groundwater models using the data from Tulare County, California, which was selected as the study area. Indices of ground surface elevation, total crop water demand, soil water infiltration rate, and soil production index explain 91% of the variation in average spring groundwater level. After relating spatial patterns of groundwater use to indices of crop and soil properties, we found that mean groundwater use is positively related to total crop water demand and soil water infiltration rate while the variation in groundwater use was negatively correlated with the crop water demand and soil water infiltration rate and positively related to soil water holding capacity. The spatial variation in groundwater use was largely influenced by crops and soil types while the temporal variation was not. We also found that groundwater use increased exponentially with decreasing annual precipitation for most townships. Based on these associations, groundwater use in each township can be forecast from relative precipitation under current methods of agricultural production. Although groundwater table depth is strongly affected by topography, the statistically significant indices observed in the model clearly show that agricultural land use influences groundwater table depth. These simple relationships can be used by agronomists to make water management decisions and to design alternative cropping systems to sustain agricultural production during periods of surface water shortages.://000077256700004 ISI Document Delivery No.: 143LG Times Cited: 4 Cited Reference Count: 30 Cited References: 1970, US GEOLOGICAL SURVEY *AGR COMM OFF, 1990, AGR ANN REP *CA DEP WAT RES, 1991, CAL CONT DROUGHT 198 *ESRI, 1990, ARCINFO GIS PROD *U CAL COOP EXT, 1990, CROP EV LEAFL *U MINN WAT RES CT, 1983, GROUNDW RECH RAT MIN ALMEKINDERS CJM, 1995, NETH J AGR SCI, V43, P127 ANDERSSON L, 1991, LANDSCAPE ECOL, V5, P107 BARRINGER JL, 1987, INT GEOGR INF SYST S, V3, P73 BOONE RL, 1983, WATER RESOURCES CTR COSTANZA R, 1986, ESTUARINE VARIABILIT, P387 CURTIS L, 1988, WATER RESOURCES TULA DRAPER NR, 1981, APPL REGRESSION ANAL FRENZEL SA, 1985, GROUND WATER, V23, P220 GLEICK PH, 1991, SOCIETAL ENV COSTS C GUSTAFSON EJ, 1992, LANDSCAPE ECOL, V7, P101 HOWITT R, 1991, CALIF AGR, V45, P6 HULSHOFF RM, 1995, LANDSCAPE ECOL, V10, P101 LEVIN SA, 1992, ECOLOGY, V73, P1943 MEDLEY KE, 1995, LANDSCAPE ECOL, V10, P161 MYERS RH, 1987, CLASSICAL MODERN REG, P317 ONEILL RV, 1988, LANDSCAPE ECOLOGY, V1, P143 PIERCE LL, 1995, LANDSCAPE ECOL, V10, P239 RIITTERS KH, 1995, LANDSCAPE ECOLOGY, V10, P232 RISSER PG, 1987, LANDSCAPE HETEROGENE, P3 ROE HB, 1950, MOISTURE REQUIREMENT ROUSSEEUW PJ, 1987, ROBUST REGRESSION OU RYSZKOWSKI L, 1987, LANDSCAPE ECOL, V1, P85 SCHMIDT KD, 1987, J IRRIG DRAIN E-ASCE, V113, P16 TAN YR, 1990, T AM SOC AGR ENG, V33, P1147 0921-2973 Landsc. Ecol.ISI:000077256700004Univ Calif Davis, Dept Land Air & Water Resources, Davis, CA 95616 USA. Zhang, MH, Zeneca Ag Prod, Western Res Ctr, 1200 S 47th St, Richmond, CA 94804 USA.Englishڽ7 Zhang, Na Li, Harbin2013Sensitivity and effectiveness and of landscape metric scalograms in determining the characteristic scale of a hierarchically structured landscape343-363Landscape Ecology282Springer NetherlandsHierarchically structured neutral landscape Xilin River Basin of Inner Mongolia FRAGSTATS Class-level metric Scale issues Scale effect Multi-scale pattern Scaling 2013/02/01+http://dx.doi.org/10.1007/s10980-012-9837-x 0921-2973Landscape Ecol10.1007/s10980-012-9837-xEnglishc<7'Zhang, N. Yu, Z. L. Yu, G. R. Wu, J. G.2007rScaling up ecosystem productivity from patch to landscape: a case study of Changbai Mountain Nature Reserve, China303-315Landscape Ecology222scaling; extrapolation; ecosystem modeling; biogeochemical cycles; landscape pattern; net primary productivity; Changbai Mountain Nature Reserve NET PRIMARY PRODUCTIVITY; MODELING APPROACH; GENERAL-MODEL; SIMULATION; GRASSLAND; DYNAMICS; ECOLOGY; BALANCEArticleFebFScaling up ecosystem processes from plots to landscapes is essential for understanding landscape structure and functioning as well as for assessing ecological impacts of land use and climate change. This study illustrates an upscaling approach to studying the spatiotemporal pattern of ecosystem processes in the Changbai Mountain Nature Reserve in northeastern China by integrating simulation modeling, GIS, remote sensing data, and field-based observations. The ecosystem model incorporated processes of energy transfer, plant physiology, carbon dynamics, and water cycling. Using a direct extrapolation scheme, the patch-level ecosystem model was scaled up to quantify the landscape-level pattern of primary productivity and the carbon source-sink relationship. The simulated net primary productivity (NPP) for the entire landscape, consisting of several ecosystem types, was 0.680 kg C m(-2) yr(-1). The most widely distributed ecosystem type in this region was the mixed broad-leaved and Korean pine (Pinus koraiensis) forest, which had the highest NPP (1.084 kg C m(-2) yr(-1)). The total annual NPP for all ecosystem types combined was estimated to be 1.332 Mt C yr(-1). These results suggest that the Changbai Mountain landscape as a whole was a carbon sink, with a net carbon sequestration rate of about 0.884 Mt C yr(-1) for the study period. The simulated NPP agreed reasonably well with available field measurements at a number of locations within the study landscape. Our study provides new insight into the relationship between landscape pattern and ecosystem processes, and useful information for improving management practices in the Changbai Mountain Nature Reserve, which is one of the most important forested landscapes in China. Several research needs are discussed to further refine the modeling approach and reduce prediction uncertainties.://000243823900012 ISI Document Delivery No.: 130UG Times Cited: 0 Cited Reference Count: 41 Cited References: ABER JD, 1999, INTEGRATING HYDROLOG, P335 BAND LE, 1991, ECOL MODEL, V56, P171 BURKE IC, 1990, LANDSCAPE ECOL, V4, P45 CHEN BR, 1984, FOREST ECOSYSTEM STU, P19 CHEN CG, 1989, MANUAL BIOMASS MAIN CHEN JM, 1999, ECOL MODEL, V124, P99 COUGHLAN JC, 1997, LANDSCAPE ECOL, V12, P119 DAI Y, 2004, AM METEOROL SOC, V6, P2281 GE JP, 1990, J NE FOR U, V18, P26 HONG BG, 2006, LANDSCAPE ECOL, V21, P195 JIN CJ, 1995, ACTA ECOLOGICA SI SB, V15, P86 JIN CJ, 2000, CHIN J APPL ECOL, V11, P19 KENNEDY RE, 2006, LANDSCAPE ECOL, V21, P213 KING AW, 1991, QUANTITATIVE METHODS, P479 LAW BE, 2006, SCALING UNCERTAINTY, P167 LI H, 2006, SCALING UNCERTAINITY, P45 LIU J, 1997, REMOTE SENS ENVIRON, V62, P158 LIU J, 1999, J GEOPHYS RES-ATMOS, V104, P27735 MLADENOFF DJ, 1999, SPATIAL MODELING FOR NORMAN JM, 1982, BIOMETEOROLOGY INTEG, P65 PARTON WJ, 1987, SOIL SCI SOC AM J, V51, P1173 PEI TP, 1981, FOREST ECOSYSTEM STU, V2, P189 RUNNING SW, 1988, ECOL MODEL, V42, P125 RUNNING SW, 1993, SCALING PHYSL PROCES, P141 SUN R, 2004, CAN J REMOTE SENS, V30, P731 TURNER MG, 2001, LANDSCAPE ECOLOGY TH TURNER MG, 2006, IN PRESS KEY TOPICS WARING RH, 1998, FOREST ECOSYSTEMS AN WU J, 1999, CANADIAN J REMOTE SE, V25, P367 WU J, 2006, SCALING UNCERTAINITY WU J, 2006, SCALING UNCERTAINITY, P17 WU JG, 1994, ECOL MONOGR, V64, P447 WU JG, 1995, Q REV BIOL, V70, P439 WU JG, 1997, ECOL MODEL, V101, P325 WU JG, 2002, LANDSCAPE ECOL, V17, P355 XING SP, 1988, FORESTS JILIN PROVIN YAN XD, 1995, ACTA ECOL SIN SB, V15, P86 ZHANG N, 2003, ACTA PHYTOECOL SIN, V27, P325 ZHANG N, 2003, CHIN J APPL ECOL, V14, P643 ZHANG N, 2003, CHINESE J APPL ECOLO, V14, P659 ZHANG N, 2003, J GEOGR SCI, V13, P139 0921-2973 Landsc. Ecol.ISI:000243823900012)Grad Univ Chinese Acad Med, Coll Resources & Environm, Beijing 100049, Peoples R China. Natl Nat Sci Fdn China, Beijing 100085, Peoples R China. Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China. Beijing Normal Univ, Sch Life Sci, Beijing 100875, Peoples R China. Arizona State Univ, Sch Life Sci, Tempe, AZ 85287 USA. Arizona State Univ, Global Inst Sustainabil, Tempe, AZ 85287 USA. Zhang, N, Grad Univ Chinese Acad Med, Coll Resources & Environm, 19A Yu Quan Rd, Beijing 100049, Peoples R China. zhangna@gucas.ac.cnEnglish <7 -Zhang, Q. B. Li, Z. S. Liu, P. X. Xiao, S. C.2012gOn the vulnerability of oasis forest to changing environmental conditions: perspectives from tree rings343-353Landscape Ecology273dendrochronology ecohydrology habitat heterogeneity heihe river multi-directional change spatial habitat streamflow river basin water-depth china ecohydrology disturbance reconstructions variability streamflow climate recordMarIn water-limited regions, oases are important localities for maintaining ecological biodiversity and supporting social and economic development. For oases situated by the side of rivers, variability of streamflow is often considered as a dominant factor influencing the vulnerability of oases forest, whereas other factors receive much less attention. Here we argue that ecological and hydrological processes creating spatial habitat heterogeneity and particularly the change of habitat structure through time are critical aspects when assessing vulnerability of oasis forest. This is demonstrated by dendroecological studies of a dynamic landscape in Ejina Oasis in the lower reach of Heihe River, the second largest inland river in China. Our results show that radial growth of euphrates poplar trees in Ejina Oasis did not follow the variation of streamflow coming from the middle reach, and the poplar tree-ring growth did not change in the same way from one site to the other. An index of multi-directional change (MDCi) is defined from tree-ring data to describe the change in spatial habitats through time. We propose that the decreasing trend of MDCi indices since the 1950s is related to persistently increasing human activities, whereas high-frequency variability in MDCi indices is related to frequent and strong local disturbances such as windstorms as well as human activities that directly cause changes in streamflow. The results obtained from this study have potentially broad implications for identifying dryland ecosystems that are at risk or susceptible to change, and for making spatially explicit decisions for rational utilization of water resources.://000300087500003-889QE Times Cited:0 Cited References Count:33 0921-2973Landscape EcolISI:000300087500003Zhang, QB Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, 20 Nanxincun, Beijing 100093, Peoples R China Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, 20 Nanxincun, Beijing 100093, Peoples R China Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China NW Normal Univ, Dept Geog, Lanzhou 730070, Peoples R China Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, Lanzhou 730000, Peoples R ChinaDOI 10.1007/s10980-011-9685-0English <7 ^Zhang, T. Soranno, P. A. Cheruvelil, K. S. Kramer, D. B. Bremigan, M. T. Ligmann-Zielinska, A.2012xEvaluating the effects of upstream lakes and wetlands on lake phosphorus concentrations using a spatially-explicit model 1015-1030Landscape Ecology277'lake phosphorus concentration spatially-explicit modeling wetland upstream lake flow-path distance-attenuation effect agricultural drainage water source pollution models minneapolis st-paul land-use change nutrient retention metropolitan-area riparian buffers united-states waste-water landscapeAugLake phosphorus concentrations are strongly influenced by the surrounding landscape that generates phosphorus loads and water inflow to lakes, and the physical characteristics of the lake that determine the fate of these inputs. In addition, the presence, connectivity, and configuration of upstream lakes and wetlands likely affect downstream lake phosphorus concentrations. These freshwater landscape features have only sometimes been incorporated into phosphorus loading models, perhaps because of the need for spatially-explicit approaches that account for their location and hydrologic configuration. In this paper, we developed a lake phosphorus concentration model that includes three modules to estimate phosphorus loading, water inflow, and phosphorus retention, respectively. In modeling phosphorus loading and water inflow, we used a spatially-explicit approach to address their export at sources and their attenuation along flow-paths. We used 161 headwater lakes for model calibration and 28 headwater lakes for model validation. Using the calibrated model, we examined the effects of upstream lakes and wetlands on downstream lake phosphorus concentrations. To examine the effects of upstream lakes, we compared the output of the calibrated model for three additional datasets (208 lakes in total) that contained increasing area of upstream lakes. To examine the effect of upstream wetlands, we used the calibrated model to compare flow-path cell series that contained wetlands and those that did not. In addition, we simulated catchments in which all wetlands were converted to forest and recalculated downstream lake phosphorus concentrations. We found that upstream lakes decreased the phosphorus concentrations in downstream lakes; and, counter-intuitively, we found that wetlands increased phosphorus concentrations in most downstream lakes. The latter result was due to the fact that although wetlands reduced phosphorus loads to downstream lakes, they also reduced water inflow to downstream lakes and thus increased the phosphorus concentration of inflows to lakes. Our results suggest that when modeling lake phosphorus concentrations, freshwater features of the landscape and their spatial arrangement should be taken into account.://000306068200007-969PP Times Cited:0 Cited References Count:72 0921-2973Landscape EcolISI:0003060682000071Zhang, T Univ Florida, Dept Biol, 220 Bartram Hall,POB 118525, Gainesville, FL 32611 USA Univ Florida, Dept Biol, 220 Bartram Hall,POB 118525, Gainesville, FL 32611 USA Univ Florida, Dept Biol, Gainesville, FL 32611 USA Michigan State Univ, Dept Fisheries & Wildlife, E Lansing, MI 48824 USA Michigan State Univ, Lyman Briggs Coll, Dept Fisheries & Wildlife, E Lansing, MI 48825 USA Michigan State Univ, Dept Fisheries & Wildlife, James Madison Coll, E Lansing, MI 48824 USA Michigan State Univ, Dept Geog, Environm Sci & Policy Program, E Lansing, MI 48824 USADOI 10.1007/s10980-012-9762-zEnglishM|? FZhao, Tingting Bergen, Kathleen M. Brown, Daniel G. Shugart, Herman H.2009jScale dependence in quantification of land-cover and biomass change over Siberian boreal forest landscapes 1299-1313Landscape Ecology2410We investigated the influence of remote sensing spatial resolution on estimates of characteristic land-cover change (LCC) and LCC-related above-ground biomass change (Delta biomass) in three study sites representative of the East Siberian boreal forest. Data included LCC estimated using an existing Landsat-derived land-cover dataset for 1990 and 2000, and above-ground standing biomass stocks simulated by the FAREAST forest succession model and applied on a pixel basis. At the base 60 m resolution, several landscape pattern metrics were derived to describe the characteristic LCC types. LCC data were progressively degraded to 240, 480, and 960 m. LCC proportions and Delta biomass were derived at each of the coarser resolutions and scale dependences of LCC and Delta biomass were analyzed. Compared to the base 60 m resolution, the Logged LCC type was highly scale dependent and was consistently underestimated at coarser resolutions. The Burned type was under- or over-estimated depending strongly on its patch size. Estimated at the base 60 m resolution, modeled biomass increased in two sites (i.e., 3.0 and 6.4 Mg C ha(-1) for the Tomsk and Krasnoyarsk sites, respectively) and declined slightly in one site (i.e., -0.5 Mg C ha(-1) for the Irkutsk site) between the two dates. At the degraded resolutions, the estimated Delta biomass increased to 3.3 and 7.0 Mg C ha(-1) for the Tomsk and Krasnoyarsk sites, while it declined to -0.8 Mg C ha(-1) for the Irkutsk site. Results indicate that LCC and Delta biomass values may be progressively amplified in either direction as resolution is degraded, depending on the mean patch size (MPS) of disturbances, and that the error of LCC and Delta biomass estimates also increases at coarser resolutions.%://BIOSIS:PREV201000014106Times Cited: 0 0921-2973BIOSIS:PREV201000014106:10.1007/s10980-009-9379-z? QZhao, Tingting Brown, Daniel Fang, Hongliang Theobald, David Liu, Ting Zhang, Tao2012\Vegetation productivity consequences of human settlement growth in the eastern United States 1149-1165Landscape Ecology278Springer NetherlandsBiomedical and Life Sciences|In this study, we investigated the impact of human settlement growth on vegetation carbon uptake in the eastern United States between 1992/1993 and 2001. Human settlement growth was measured by changes in the density of housing units. Vegetation carbon uptake was estimated with gross primary production (GPP) based on the light-use efficiency approach applied to satellite imagery. Annual GPP was found to increase by approximately 140 g C m −2 on average for the entire study area in 2001 compared to 1992/1993, accompanied by region-wide increases in downward shortwave radiation and minimum daily temperature. Changes in GPP, however, varied significantly by different types of settlement growth. Exurbanized areas, where the rural settlement (less than 0.025 units per acre) converted to exurbs (0.025–0.6 units per acre), were associated with approximately 157 g C m −2 increase in GPP due to high vegetation proportions. Suburbanization, the conversion from exurban settlement to suburbs (0.6–4 units per acre), was related with a decline of GPP by 152 g C m −2 due to progressive development of built-up land cover. Results help to understand the potential of carbon mitigation in the human-dominated landscapes using vegetation as a natural store of carbon dioxide. This in turn has implications for the low-carbon development planning along the gradient of human settlement densities.+http://dx.doi.org/10.1007/s10980-012-9766-8 0921-297310.1007/s10980-012-9766-8 ~|78Zharikov, Y. Elner, R. W. Shepherd, P. C. F. Lank, D. B.2009kInterplay between physical and predator landscapes affects transferability of shorebird distribution models129-144Landscape Ecology241auc calibration distribution model dunlin intertidal landscape non-breeding shorebird transferability species distribution models british-columbia calidris-mauri semipalmated sandpipers western sandpiper intertidal flat habitat estuary invertebrates abundanceJanCoastal landscapes with extensive intertidal mudflats provide non-breeding habitat for Arctic shorebirds. Few attempts have been made to develop and test landscape-level models predicting the intertidal distribution of these birds. We modelled the distribution of a Holarctic species, Dunlin (Calidris alpina), at a hemispherically important non-breeding site, the Fraser River Delta, British Columbia, Canada, in seasons with different predator landscapes. We trained the models during a season when nocturnal predators were common and tested temporal transferability of the models on independent datasets when nocturnal predators were absent. Snowy Owls (Nyctea scandiaca) influenced Dunlin distribution and thus model transferability. After accounting for their presence, models displayed good to excellent discrimination, i.e. prediction of the instantaneous and cumulative (over low tide period) probability of mudflat use by Dunlin, in fore- and backcasting applications. Model calibration was good or else, where over-prediction was observed, the reason for the bias was identified. The distribution models may predict mudflat use by Dunlin and possibly related species given relevant data describing the intertidal landscape. The models are amenable to GIS application, describe the amount of use per hectare of the intertidal zone and can be used to determine and visualise relative and absolute suitability of intertidal areas.://000262506000011-395EI Times Cited:0 Cited References Count:40 0921-2973ISI:000262506000011QZharikov, Y Pacific Rim Natl Pk Reserve, POB 280, Ucluelet, BC V0R 3A0, Canada Simon Fraser Univ, Dept Biol Sci, Ctr Wildlife Ecol, Burnaby, BC V5A 1S6, Canada Environm Canada, Canadian Wildlife Serv, Delta, BC V4K 3N2, Canada Western & No Serv Ctr, Vancouver, BC V6B 6B4, Canada Pacific Rim Natl Pk Reserve, Ucluelet, BC V0R 3A0, CanadaDoi 10.1007/S10980-008-9291-YEnglish <7-Zharikov, Y. Lank, D. Huettmann, F. Cooke, F.2007tInterpreting habitat distribution models of an elusive species, the marbled murrelets: a response to Burger and Page 1283-1289Landscape Ecology229brachyramphus marmoratus; distribution modelling; habitat management; logistic regression; marbled murrelets; old-growth forest RESOURCE SELECTION FUNCTIONS; MULTIPLE SPATIAL SCALES; LANDSCAPE; SUCCESS; FRAGMENTATION; ACCURACY; PATTERNS; BEHAVIOR; ECOLOGY; COASTALArticleNovBurger and Page (this volume) evaluated our models of habitat preferences and breeding success of a threatened seabird, the marbled murrelet (Brachyramphus marmoratus), based on the largest available set of confirmed nest-sites found in coastal old-growth forest of the Pacific North-West. We believe our study documented novel and unexpected patterns of landscape-level distribution of marbled murrelets in both heavily logged and relatively intact old-growth landscapes and provided insights into how these patterns influence their reproduction, and, eventually, management. Considering the importance of the issue and to ensure appropriate and responsible use of the information we welcome discussion, detailed scrutiny and evaluation of our original results. Burger and Page claim to have identified flaws with model interpretation, data quality, statistical approaches, presentation and interpretation of our results that would invalidate our conclusions. We respond that most of their critique is irrelevant and/or misdirected with respect to our study and the interpretation of GIS data models, and that valid aspects of their claims do not critically affect our conclusions.://000250207500002 GCited Reference Count: 23 Cited References: BETTS MG, 2006, ECOL APPL, V16, P1076 BOYCE MS, 2002, ECOL MODEL, V157, P281 BURGER AE, 2007, LANDSC ECOL GIBSON LA, 2004, J APPL ECOL, V41, P213 HUETTMANN F, 2006, LANDSCAPE ECOL, V21, P1089 JOHNSON CJ, 2004, J APPL ECOL, V41, P238 JOHNSON CJ, 2004, LANDSCAPE ECOL, V19, P869 MAO JS, 2005, J WILDLIFE MANAGE, V69, P1691 MCPHERSON JM, 2004, J APPL ECOL, V41, P811 MCPHERSON JM, 2007, ECOGRAPHY, V30, P135 MEYER CB, 2002, CONSERV BIOL, V16, P755 MEYER CB, 2002, LANDSCAPE ECOL, V17, P95 PEARCE J, 2000, ECOL MODEL, V133, P225 PEERY AZ, 2004, CONDOR, V106, P344 PIDGEON AM, 2003, ECOL APPL, V13, P530 REESE GC, 2005, ECOL APPL, V15, P554 SEOANE J, 2004, ECOL MODEL, V175, P137 TRANQUILLA LM, 2005, J FIELD ORNITHOL, V76, P357 VAUGHAN IP, 2005, J APPL ECOL, V42, P720 VISSCHER DR, 2006, ECOGRAPHY, V29, P458 WHITTINGHAM MJ, 2006, J ANIM ECOL, V75, P1182 ZHARIKOV Y, 2006, LANDSCAPE ECOL, V21, P107 ZHARIKOV Y, 2007, J APPL ECOL, V44, P748 0921-2973 Landsc. Ecol.ISI:000250207500002Pacific Rim Natl Pk, Ucluelet, BC V0R 3A0, Canada. Simon Fraser Univ, Dept Biol Sci, Ctr Wildlife Ecol, Burnaby, BC V5A 1S6, Canada. Univ Alaska Fairbanks, Inst Arctic Biol, Dept Biol & Wildlife, Fairbanks, AK 99775 USA. Larkins Cottage, Castle Rising PE31 6AB, Norfolk, England. Zharikov, Y, Pacific Rim Natl Pk, 2185 Ocean Terrace,POB 280, Ucluelet, BC V0R 3A0, Canada. yuri.zharikov@pc.gc.caEnglishc?Yuri Zharikov David B. Lank Falk Huettmann Russell W. Bradley Nadine Parker Peggy P.-W. Yen Laura A. Mcfarlane-Tranquilla Fred Cooke2007Habitat selection and breeding success in a forest-nesting Alcid, the marbled murrelet, in two landscapes with different degrees of forest fragmentation 791Landscape Ecology225Erratum<7tZharikov, Y. Lank, D. B. Huettmann, F. Bradley, R. W. Parker, N. Yen, P. P. W. McFarlane-Tranquilla, L. A. Cooke, F.2006Habitat selection and breeding success in a forest-nesting Alcid, the marbled murrelet, in two landscapes with different degrees of forest fragmentation107-120Landscape Ecology211conservation; edge effect; Euclidean distance; GIS; landscape ecology; old-growth forest; radio-telemetry BRITISH-COLUMBIA; POPULATION; PATTERNS; ECOLOGY; OREGON; GROWTH; ISLAND; ASSOCIATIONS; VEGETATION; BEHAVIORArticleJanWe studied habitat selection and breeding success in marked populations of a protected seabird (family Alcidae), the marbled murrelet (Brachyramphus marmoratus), in a relatively intact and a heavily logged old-growth forest landscape in south-western Canada. Murrelets used old-growth fragments either proportionately to their size frequency distribution (intact) or they tended to nest in disproportionately smaller fragments (logged). Multiple regression modelling showed that murrelet distribution could be explained by proximity of nests to landscape features producing biotic and abiotic edge effects. Streams, steeper slopes and lower elevations were selected in both landscapes, probably due to good nesting habitat conditions and easier access to nest sites. In the logged landscape, the murrelets nested closer to recent clearcuts than would be expected. Proximity to the ocean was favoured in the intact area. The models of habitat selection had satisfactory discriminatory ability in both landscapes. Breeding success (probability of nest survival to the middle of the chick rearing period), inferred from nest attendance patterns by radio-tagged parents, was modelled in the logged landscape. Survivorship was greater in areas with recent clearcuts and lower in areas with much regrowth, i.e. it was positively correlated with recent habitat fragmentation. We conclude that marbled murrelets can successfully breed in old-growth forests fragmented by logging.://000235887300009 ISI Document Delivery No.: 020DD Times Cited: 0 Cited Reference Count: 59 Cited References: *MWALP, 2004, MARBL MURR BRACH MAR BASTIAN O, 2001, LANDSCAPE ECOL, V16, P757 BOYCE MS, 2002, ECOL MODEL, V157, P281 BRADLEY RW, 2002, CONDOR, V104, P178 BRADLEY RW, 2002, THESIS S FRASER U BRADLEY RW, 2004, J WILDLIFE MANAGE, V68, P318 BROOKS TM, 1999, CONSERV BIOL, V13, P1140 BURGER AE, 2001, J WILDLIFE MANAGE, V65, P696 BURGER AE, 2004, J FIELD ORNITHOL, V75, P53 BURNHAM KP, 2002, MODEL SELECTION MULT CAM E, 2003, CONSERV BIOL, V17, P1118 CARTER HR, 1987, WILSON BULL, V99, P289 CHEN JQ, 1995, ECOL APPL, V5, P74 CHOULAKIAN V, 1994, CAN J STAT, V22, P125 CLARK PJ, 1954, ECOLOGY, V35, P445 CONNER LM, 2001, RADIO TELEMETRY ANIM EBERHARDT LL, 2003, J WILDLIFE MANAGE, V67, P241 FIELDING AH, 1995, CONSERV BIOL, V9, P1466 FIELDING AH, 1997, ENVIRON CONSERV, V24, P38 FRIESEN L, 1999, CONSERV BIOL, V13, P338 GARMAN SL, 1999, FOREST FRAGMENTATION, P61 GEOGRATIS, 2002, NATURAL RESOURCES CA GEORGE TL, 2001, RESTOR ECOL, V9, P272 GREEN RE, 1997, J ZOOL 1, V243, P81 HARTMAN LH, 1997, J WILDLIFE MANAGE, V61, P377 HENSKE EJ, 2001, WILDLIFE SOC B, V29, P52 HIPFNER JM, 2002, AUK, V119, P827 HOSMER DW, 2000, APPL LOGISTIC REGRES HULL CL, 2001, AUK, V118, P1036 JOHNSON JB, 2004, TRENDS ECOL EVOL, V19, P101 JONES J, 2001, AUK, V118, P557 JONSSON BG, 1997, CAN J BOT, V75, P744 KELSON JD, 1995, NW NATURALIST, V76, P90 KOKKO H, 2004, J ANIM ECOL, V73, P367 LILLESAND TM, 2004, REMOTE SENSING IMAGE MANLEY IA, 1999, THESIS S FRASER U MARZLUFF JM, 1999, FOREST FRAGMENTATION, P155 MEYER CB, 2002, CONSERV BIOL, V16, P755 MEYER CB, 2002, LANDSCAPE ECOL, V17, P95 MIZUNO K, 1998, ARCTIC ALPINE RES, V30, P340 NELSON SK, 1995, ECOLOGY CONSERVATION, P89 NELSON SK, 1997, BIRDS N AM NETTLESHIP DN, 1985, ATLANTIC ALCIDAE EVO NIELSEN SE, 2004, FOREST ECOL MANAG, V199, P67 PARENDES LA, 2000, CONSERV BIOL, V14, P64 PARISH R, 2004, OECOLOGIA, V141, P562 PECK JE, 2001, NORTHWEST SCI, V75, P99 PEERY AZ, 2004, CONDOR, V106, P344 PENNYCUICK CJ, 1987, J EXP BIOL, V128, P335 PIDGEON AM, 2003, ECOL APPL, V13, P530 RALPH CJ, 1995, ECOLOGY CONSERVATION, P2 RAPHAEL MG, 2002, STUDIES AVIAN BIOL, V25, P221 RIPPLE WJ, 2003, NW NATURALIST, V84, P80 RODWAY MS, 2000, J FIELD ORNITHOL, V71, P415 SAAB VA, 2001, CONDOR, V103, P491 SINGER SW, 1991, CONDOR, V93, P330 VERMEER K, 1979, ARDEA, V67, P22 WATERHOUSE FL, 2004, TR029 MIN FOR WHITWORTH DL, 1997, COLON WATERBIRD, V20, P525 0921-2973 Landsc. Ecol.ISI:000235887300009Simon Fraser Univ, Dept Biol Sci, Ctr Wildlife Ecol, Burnaby, BC V5A 1S6, Canada. Univ Queensland, Sch Integrat Biol, Brisbane, Qld 4072, Australia. Univ Alaska Fairbanks, Inst Arctic Biol, Dept Biol & Wildlife, Fairbanks, AK 99775 USA. PRBO Conservat Sci, Stinson Beach, CA 94970 USA. Larkins Cottage, Castle Rising PE31 6AB, Norfolk, England. Zharikov, Y, Simon Fraser Univ, Dept Biol Sci, Ctr Wildlife Ecol, Burnaby, BC V5A 1S6, Canada. yzharikov@zen.uq.edu.auEnglishm|7tZharikov, Y. Lank, D. B. Huettmann, F. Bradley, R. W. Parker, N. Yen, P. P. W. Mcfarlane-Tranquilla, L. A. Cooke, F.2007Habitat selection and breeding success in a forest-nesting Alcid, the marbled murrelet, in two landscapes with different degrees of forest fragmentation (vol 21, pg 107, 2007)791-791Landscape Ecology225May://000246111800012,162TG Times Cited:0 Cited References Count:1 0921-2973ISI:000246111800012gZharikov, Y Univ Queensland, Sch Integrat Biol, Brisbane, Qld 4072, Australia Univ Queensland, Sch Integrat Biol, Brisbane, Qld 4072, Australia Simon Fraser Univ, Dept Sci Biol, Ctr Wildlife Ecol, Burnaby, BC V5A 1S6, Canada Univ Alaska Fairbanks, Dept Biol & Wildlife, Inst Arctic Biol, Fairbanks, AK 99775 USA PRBO Conservat Sci, Stinson Beach, CA 94970 USADoi 10.1007/S10980-007-9084-8English?+Zheng, Daolan Hunt, E.R. Running, Steven W.1996`Comparison of available soil water capacity estimated from topograph and soil series information3-14Landscape ecology111X|7? $Zheng, D. Hunt, E. R. Running, S. W.1996vComparison of available soil water capacity estimated from topography and soil series information (vol 11, pg 3, 1996)U1-U2Landscape Ecology113Jun://A1996UX47800006,Ux478 Times Cited:0 Cited References Count:1 0921-2973ISI:A1996UX47800006Englishs|?&Zheng, D. L. Heath, L. S. Ducey, M. J.2008TModeling grain-size dependent bias in estimating forest area: a regional application 1119-1132Landscape Ecology239BA better understanding of scaling-up effects on estimating important landscape characteristics (e.g. forest percentage) is critical for improving ecological applications over large areas. This study illustrated effects of changing grain sizes on regional forest estimates in Minnesota, Wisconsin, and Michigan of the USA using 30-m land-cover maps (1992 and 2001) produced by the National Land Cover Datasets. The maps were aggregated to two broad cover types (forest vs. non-forest) and scaled up to 1-km and 10-km resolutions. Empirical models were established from county-level observations using regression analysis to estimate scaling effects on area estimation. Forest percentages observed at 30-m and 1-km land-cover maps were highly correlated. This intrinsic relationship was tested spatially, temporally, and was shown to be invariant. Our models provide a practical way to calibrate forest percentages observed from coarse-resolution land-cover data. The models predicted mean scaling effects of 7.0 and 12.0% (in absolute value with standard deviations of 2.2 and 5.3%) on regional forest cover estimation (ranging from 2.3 and 2.5% to 11.1 and 23.7% at the county level) with standard errors of model estimation 3.1 and 7.1% between 30 m and 1 km, and 30 m and 10 km, respectively, within a 95% confidence interval. Our models improved accuracy of forest cover estimates (in terms of percent) by 63% (at 1-km resolution) and 57% (at 10-km resolution) at the county level relative to those without model adjustment and by 87 and 84% at the regional level in 2001. The model improved 1992 and 2001 regional forest estimation in terms of area for 1-km maps by 15,141 and 7,412 km(2) (after area weighting of all counties) respectively, compared to the corresponding estimates without calibration using 30 m-based regional forest areas as reference.!://WOS:000260283100010Times Cited: 0 0921-2973WOS:00026028310001010.1007/s10980-008-9272-1|7@ 'Zheng, D. L. Hunt, E. R. Running, S. W.1996aComparison of available soil water capacity estimated from topography and soil series information3-14Landscape Ecology111+ecosystem simulation satellite data textureFebWe present a simple and generalized method to predict Available Soil Water Capacity (ASWC-TOP) for a given area using a topographic index, defined as In(alpha/tan beta), where alpha is the upslope area draining past a certain point per unit width of slope, and beta is the local surface slope angle. The estimated results (ASWC-TOP) were then compared with the available soil water capacity calculated from soil series information provided by Soil Conservation Service, U.S. Department of Agriculture (ASWC-SCS). The model implementation was tested with three study cases: the Seeley-Swan valley, Montana, with pixel resolutions of 100 m and 1 km, respectively; and the state of Montana, U.S.A., with a pixel resolution of 1 km. A linear relationship exists between ASWC-SCS and In(alpha/tan beta). standard errors between ASWC-TOP and ASWC-SCS were about 4.4 cm in the Seeley-Swan valley and 5.5 cm in the state. The number of pixels with absolute residuals less than or equal to 4 cm between ASWC-TOP and ASWC-SCS accounted for 68.2, 64.4, and 51.9% for the valley 100 m, valley 1 km, and the state respectively. Some of the mismatches between ASWC-TOP and ASWC-SCS may indicate an improvement using this method compared to existing data because the topographic method reflects the higher spatial variation of the inputs. The increasing availability of digital elevation data, at various resolutions, may provide an alternative to soil series for estimating ASWC. The accuracy of ASWC-TOP depends on estimation of mean and maximum ASWC for a study area.://A1996UN74400001.Un744 Times Cited:17 Cited References Count:32 0921-2973ISI:A1996UN74400001+Univ Montana,Sch Forestry,Missoula,Mt 59812English|7 %Zheng, D. L. Wallin, D. O. Hao, Z. Q.1997sRates and patterns of landscape change between 1972 and 1988 in the Changbai Mountain area of China and North Korea241-254Landscape Ecology124satellite remote sensing landscape change change detection forest fragmentation forest management disturbance forest landscape vegetation change carbon storage rain-forests oregon biota conservation conversion america brazilAugMSatellite imagery was used to quantify rates and patterns of landscape change between 1972 and 1988 in the Changbai Mountain Reserve and its adjacent areas in the People's Republic of China and North Korea. The 190,000 ha Reserve was established as an International Biosphere Reserve by The United Nations Educational, Scientific and Cultural Organization (UNESCO) in 1979. It is the most important natural landscape remaining in China's temperate/boreal climate. The images used in this research cover a total area of 967,847 ha, about three-fourths of which is in China. Imagery from 1972 and 1988 was classified into 2 broad cover types (forest and non-forest). Overall, forests covered 84.4% of the study area in 1972 and 74.5% in 1988. Changes in forest cover within the Reserve were minimal. The loss of forest cover outside the Reserve appears to be strongly associated with timber harvesting at lower elevations. Landscape patterns in 1988 were more complex, more irregular, and more fragmented than in 1972. This is one of the few studies to assess landscape changes across two countries. The rates and patterns of forest-cover loss were different in China and North Korea. In North Korea, extensive cutting appears to have occurred prior to 1972 and this has continued through 1988 while in China, most cutting appears to have occurred since 1972.://A1997XV63300004.Xv633 Times Cited:46 Cited References Count:57 0921-2973ISI:A1997XV63300004EZheng, DL Oregon State Univ, Dept Forest Sci, Corvallis, or 97331 USAEnglish|?,Zheng, Zhenmin Fu, Bojie Hu, Haitang Sun, Ge2014qA method to identify the variable ecosystem services relationship across time: a case study on Yanhe Basin, China 1689-1696Landscape Ecology2910DecEcosystem services are increasingly recognized as the foundations of a well-functioning society. Large-scale ecological restoration projects have been implemented around China with the goal of restoring and sustaining ecosystem services, especially in vulnerable semi-arid regions where soil and water resources are most stressed due to historic human activities. The relationships among ecosystem services are often driven by land-use changes. It is necessary to develop an applicable method to explore the relationships between ecosystem services and driving factors over time. We selected the Yanhe Basin on China's Loess Plateau as the study area, which has experienced a large-scale Grain for Green Project (GGP), and quantified four ecosystem services (soil conservation, water retention, water yield, and crop production). The results of this study show that different trends have occurred for ecosystem services during 2000-2008. We found potential tradeoffs between soil conservation and water yield. Synergies may exist among water retention and soil conservation/water yield. Two types of preconditions were pointed out in the analysis process to define the potential relationships among ecosystem service variables. The correspondence analysis was used to explore its intrinsic linkage and its variations among ecosystemservices, land uses, and spatial locations. It suggests that the intensities of the ecosystem services provided by most of land uses and the internal proportion of regulating service to provision service in a sub-basin has been changed by GGP, but the relative spatial patterns of ecosystem services are still being maintained in entire basin scale from 1980 to 2008.!://WOS:000346920900005Times Cited: 2 0921-2973WOS:00034692090000510.1007/s10980-014-0088-xU?yZhou, G. Liebhold, A. M.1995YForecasting the spatial dynamics of gypsy moth outbreaks using cellular transition models177-189Landscape Ecology103$Markov chain, cellular automata, GIS|7] Zhou, G. F. Liebhold, A. M.1995YForecasting the Spatial Dynamics of Gypsy-Moth Outbreaks Using Cellular Transition Models177-189Landscape Ecology103Imarkov chain cellular automata lymantria dispar lepidoptera, lymantriidaeJun1A series of cellular transition probability models that predict the spatial dynamics of gypsy moth (Lymantria dispar L.) defoliation were developed. The models consisted of four classes: Simple Markov chains, Rook's and Queen's move neighborhood models, and distance weighted neighborhood models. Historical maps of gypsy moth defoliation across Massachusetts from 1961 to 1991 were digitized into a binary raster matrix and used to estimate transition probabilities. Results indicated that the distance weighted neighborhood model performed better then the other neighborhood models and the simple Markov chain. Incorporation of interpolated counts of overwintering egg mass counts taken throughout the state and incorporation of historical defoliation frequencies increased the performance of the transition models.://A1995RF27500005-Rf275 Times Cited:16 Cited References Count:0 0921-2973ISI:A1995RF275000055Us Forest Serv,Ne Forest Expt Stn,Morgantown,Wv 26505Englishn? Zhou, Weiqi Cadenasso, M.2012Effects of patch characteristics and within patch heterogeneity on the accuracy of urban land cover estimates from visual interpretation 1291-1305Landscape Ecology279Springer NetherlandsBiomedical and Life Sciences+http://dx.doi.org/10.1007/s10980-012-9780-x 0921-297310.1007/s10980-012-9780-x|?2 AZhou, Weiqi Huang, Ganlin Pickett, Steward T. A. Cadenasso, M. L.2011Y90 years of forest cover change in an urbanizing watershed: spatial and temporal dynamics645-659Landscape Ecology265MayNLandscape structure in the Eastern US experienced great changes in the last century with the expansion of forest cover into abandoned agricultural land and the clearing of secondary forest cover for urban development. In this paper, the spatial and temporal patterns of forest cover from 1914 to 2004 in the Gwynns Falls watershed in Baltimore, Maryland were quantified from historic maps and aerial photographs. Using a database of forest patches from six times-1914, 1938, 1957, 1971, 1999, and 2004-we found that forest cover changed, both temporally and spatially. While total forest area remained essentially constant, turnover in forest cover was very substantial. Less than 20% of initial forest cover remained unchanged. Forest cover became increasingly fragmented as the number, size, shape, and spatial distribution of forest patches within the watershed changed greatly. Forest patch change was also analyzed within 3-km distance bands extending from the urban core to the more suburban end of the watershed. This analysis showed that, over time, the location of high rates of forest cover change shifted from urban to suburban bands which coincides with the spatial shift of urbanization. Forest cover tended to be more stable in and near the urban center, whereas forest cover changed more in areas where urbanization was still in process. These results may have critical implications for the ecological functioning of forest patches and underscore the need to integrate multi-temporal data layers to investigate the spatial pattern of forest cover and the temporal variations of that spatial pattern.!://WOS:000291485100004Times Cited: 0 0921-2973WOS:00029148510000410.1007/s10980-011-9589-zU|?a:Zhou, Weiqi Qian, Yuguo Li, Xiaoma Li, Weifeng Han, Lijian2014Relationships between land cover and the surface urban heat island: seasonal variability and effects of spatial and thematic resolution of land cover data on predicting land surface temperatures153-167Landscape Ecology291JanWe investigated the seasonal variability of the relationships between land surface temperature (LST) and land use/land cover (LULC) variables, and how the spatial and thematic resolutions of LULC variables affect these relationships. We derived LST data from Landsat-7 Enhanced Thematic Mapper (ETM+) images acquired from four different seasons. We used three LULC datasets: (1) 0.6 m resolution land cover data; (2) 30 m resolution land cover data (NLCD 2001); and (3) 30 m resolution Normalized Difference Vegetation Index data derived from the same ETM+ images (though from different bands) used for LST calculation. We developed ten models to evaluate effects of spatial and thematic resolution of LULC data on the observed relationships between LST and LULC variables for each season. We found that the directions of the effects of LULC variables on predicting LST were consistent across seasons, but the magnitude of effects, varied by season, providing the strongest predictive capacity during summer and the weakest during winter. Percent of imperviousness was the best predictor on LST with relatively consistent explanatory power across seasons, which alone explained approximately 50 % of the total variation in LST in winter, and up to 77.9 % for summer. Vegetation related variables, particularly tree canopy, were good predictor of LST during summer and fall. Vegetation, particularly tree canopy, can significantly reduce LST. The spatial resolution of LULC data appeared not to substantially affect relationships between LST and LULC variables. In contrast, increasing thematic resolution generally enhanced the explanatory power of LULC on LST, but not to a substantial degree.!://WOS:000330827600012Times Cited: 6 0921-2973WOS:00033082760001210.1007/s10980-013-9950-5 |? (Zhou, W. Q. Schwarz, K. Cadenasso, M. L.2010tMapping urban landscape heterogeneity: agreement between visual interpretation and digital classification approaches53-67Landscape Ecology251Visual interpretation of remotely sensed imagery has long been used for landscape pattern analysis. Few studies, however, have investigated human variation in estimates of within-patch composition for classification of those patches, particularly in urban settings. This paper compares the agreement of two approaches-visual interpretation and object-based-to estimate the proportion cover of landscape features within delineated patches, and investigates the spatial patterns of patches with large disagreement between the two approaches. The two approaches were compared for the Gwynns Falls watershed, Maryland, USA. Three methods were used to assess agreement: a traditional error matrix based procedure and two fuzzy methods, a plus-one modification of the traditional procedure, and a fuzzy set theory method. We found that while visual interpretation does not work effectively when patches contain a mix of different types of features, accuracy increases with patches that are either dominated by a specific feature, or do not contain a specific feature. The overall accuracies of estimates by visual interpretation also vary by features, ranging from 63.3% for pavement to 93.8% for bare soil. Patches with large disagreement between the two approaches cluster spatially at locations where the urban landscape is more structurally complex, suggesting the accuracy of visual interpretation may be affected by patch shape complexity, and the spatial configuration of the landscape features within the patches. These results provide important insights into the accuracy of thematic maps based on visual interpretation, not only for ecologists and managers who are using the maps, but also for those who produce the maps.!://WOS:000273479100005Times Cited: 0 0921-2973WOS:00027347910000510.1007/s10980-009-9427-8}?2Zhu, L. Sun, O. J. Sang, W. G. Li, Z. Y. Ma, K. P.2007bPredicting the spatial distribution of an invasive plant species (Eupatorium adenophorum) in China 1143-1154Landscape Ecology228Oct://000248941900003 0921-2973ISI:0002489419000039<7V0Zhu, M. Xu, J. G. Jiang, N. Li, J. L. Fan, Y. M.2006uImpacts of road corridors on urban landscape pattern: a gradient analysis with changing grain size in Shanghai, China723-734Landscape Ecology215fragmentation; gradient analysis; grain size; land use; landscape pattern; patch density; road corridors; urbanization LAND-USE CHANGE; ECOLOGICAL-SYSTEMS; ROCKY-MOUNTAINS; FRAGMENTATION; TRANSFORMATION; ECOSYSTEM; ARIZONA; INDEXES; CANADA; GROWTHArticleJulUrbanization is one of the most important driving forces for land use and land cover change. Quantifying urban landscape pattern and its change is fundamental for monitoring and assessing ecological and socioeconomic consequences of urbanization. As the largest city in the country, Shanghai is now the fastest growing city in China. Using land use data set of 2002 and combining gradient analysis with landscape metrics, we analyzed landscape pattern of Shanghai with increasing grain size to study the impacts of road corridors on urban landscape pattern. Landscape metrics were computed along a 51 x 9 km(2) transect cutting across Shanghai with a moving window. The results showed that the urban landscape pattern of Shanghai was greatly changed when road corridors were merged with urban patches and the variation of patch density would alter when grain size changed. As a linear land use type, road corridors exhibited a different spatial signature comparing with other land use types and distinctive behavior with increasing grain size. Merging road and urban patches resulted in a sharp reduction in patch density, mainly caused by segmentation of roads corridors. The results suggested that grain size around 7.5 m might be optimal for urban landscape analysis. Landscape patch density is significantly correlated with road percent coverage and the most important effect of road corridors in urban landscape is increased habitat fragmentation.://000240500100008 ISI Document Delivery No.: 083ZE Times Cited: 0 Cited Reference Count: 43 Cited References: *SHANGH MUN STAT B, 2003, SHANGH STAT YB 2003 *UN POP DIV, 2000, WORLD URB PROSP 1999 *UN POP FUND, 1991, POP RES ENV CRIT CHA BAKER LA, 2001, ECOSYSTEMS, V4, P582 BREUSTE J, 1998, URBAN ECOLOGY CHENG HQ, 2003, LANDSCAPE URBAN PLAN, V62, P199 FORMAN RTT, 1986, LANDSCAPE ECOLOGY FORMAN RTT, 1995, LAND MOSAICS ECOLOGY FORMAN RTT, 1997, LANDSCAPE URBAN PLAN, V37, P129 FORMAN RTT, 1998, ANNU REV ECOL SYST, V29, P207 GAUBATZ P, 1999, URBAN STUD, V36, P1495 GODRON M, 1983, DISTURBANCE ECOSYSTE, P12 GRUBLER A, 1994, CHANGES LAND USE LAN, P287 GUSTAFSON EJ, 1998, ECOSYSTEMS, V1, P143 HAN SS, 2000, URBAN STUD, V37, P2091 HANSEN MJ, 2001, REMOTE SENS ENVIRON, V77, P50 JAEGER JAG, 2000, LANDSCAPE ECOL, V15, P115 KALNAY E, 2003, NATURE, V423, P528 LAMBIN EF, 1999, LAND USE LAND COVER LAMBIN EF, 2001, GLOBAL ENVIRON CHANG, V11, P261 LI HB, 2004, LANDSCAPE ECOL, V19, P389 LOUCKS OL, 1994, ECOLOGICAL CITY, P49 LUCK M, 2002, LANDSCAPE ECOL, V17, P327 MCDONNELL MJ, 1997, URBAN ECOSYSTEMS, V1, P21 MCGARIGAL K, 2002, SPATIAL PATTERN ANAL MCINTYRE NE, 2001, URBAN ECOSYST, V4, P5 MILLER JR, 1996, LANDSCAPE ECOL, V11, P115 PAN DY, 1999, LANDSCAPE ECOL, V14, P35 PARK RE, 1925, CITY PAULEIT S, 2000, LANDSCAPE URBAN PLAN, V52, P1 PICKETT STA, 2001, ANNU REV ECOL SYST, V32, P127 REDMAN CL, 1999, ECOSYSTEMS, V2, P296 REED RA, 1996, CONSERV BIOL, V10, P1098 SAURA S, 2004, LANDSCAPE ECOL, V19, P197 SUKOPP H, 1998, URBAN ECOL, P3 TURNER BL, 1995, LAND USE LAND COVER TURNER MG, 1989, LANDSCAPE ECOLOGY, V3, P153 WENG QH, 2002, J ENVIRON MANAGE, V64, P273 WHITTAKER RH, 1975, COMMUNITIES ECOSYSTE WU J, 2000, LANDSCAPE ECOLOGY PA WU JG, 2002, ECOL MODEL, V153, P7 WU JG, 2004, LANDSCAPE ECOL, V19, P125 YANG XJ, 2003, INT J GEOGR INF SCI, V17, P463 0921-2973 Landsc. Ecol.ISI:0002405001000088Nanjing Univ, Dept Biol, Nanjing 210093, Peoples R China. Nanjing Univ, Dept Urban & Resources Sci, Nanjing 210093, Peoples R China. Chinese Acad Sci, Nanjing Inst Geog & Limnol, Nanjing 210008, Peoples R China. Li, JL, Nanjing Univ, Dept Biol, 22 Hankou Rd, Nanjing 210093, Peoples R China. jianlongli@gmail.comEnglish%ڽ7 Zimbres, Barbara Furtado, MarianaM Jácomo, AnahT A. Silveira, Leandro Sollmann, Rahel Tôrres, NatáliaM Machado, RicardoB Marinho-Filho, Jader2013eThe impact of habitat fragmentation on the ecology of xenarthrans (Mammalia) in the Brazilian Cerrado259-269Landscape Ecology282Springer NetherlandsYActivity pattern Ecological sensitivity Habitat fragmentation Landscape ecology Xenarthra 2013/02/01+http://dx.doi.org/10.1007/s10980-012-9832-2 0921-2973Landscape Ecol10.1007/s10980-012-9832-2EnglishT|? QZimmerman, Jess K. Comita, Liza S. Thompson, Jill Uriarte, Maria Brokaw, Nicholas2010~Patch dynamics and community metastability of a subtropical forest: compound effects of natural disturbance and human land use 1099-1111Landscape Ecology257AugWhere large disturbances do not cause landscape-wide mortality and successional change, forested ecosystems should exhibit landscape metastability (landscape equilibrium) at a scale equal to the dominant patch size of disturbance and recovery within the landscape. We investigated this in a 16-ha contiguous plot of subtropical wet forest in Puerto Rico, the Luquillo Forest Dynamics Plot (LFDP), which experienced two major hurricanes during the 15-year study and has a land use history (logging and agriculture 40 or more years hence) that differs in intensity between two areas of the plot. Using he LFDP as our "landscape," we studied the spatial pattern of community change through time (3-5 year intervals) by calculating community dissimilarity between tree censuses for two size classes of trees (1 to < 10 cm DBH and a parts per thousand yen10 cm DBH) in quadrats ranging in size from 0.010-1 ha and for the entire landscape, i.e., plot or land use type. The point at which the decline in community dissimilarity with quadrat size showed maximum curvature identified the dominant patch size (i.e., point of metastability). For canopy trees a parts per thousand yen10 cm dbh, there was no evidence that the community experienced landscape-wide successional changes in either land use type, and we found a consistent patch size of community change around 0.1 ha (range 0.091-0.107). For the understory tree and shrub community (1 to < 10 cm dbh) there was some evidence of landscape-wide community changes over time in response to hurricane damage, apparently driven by interactions with the dominant canopy species, whose composition varied with land use intensity, and their species-specific susceptibility to hurricane damage.!://WOS:000279592100009Times Cited: 0 0921-2973WOS:00027959210000910.1007/s10980-010-9486-x|?PZiolkowska, Elzbieta Ostapowicz, Katarzyna Radeloff, Volker C. Kuemmerle, Tobias2014dEffects of different matrix representations and connectivity measures on habitat network assessments 1551-1570Landscape Ecology299NovEAssessing landscape connectivity is important to understand the ecology of landscapes and to evaluate alternative conservation strategies. The question is though, how to quantify connectivity appropriately, especially when the information available about the suitability of the matrix surrounding habitat is limited. Our goal here was to investigate the effects of matrix representation on assessments of the connectivity among habitat patches and of the relative importance of individual patches for the connectivity within a habitat network. We evaluated a set of 50 9 50 km 2 test areas in the Carpathian Mountains and considered three different matrix representations (binary, categorical and continuous) using two types of connections among habitat patches (shortest lines and least-cost paths). We compared connections, and the importance of patches, based on (1) isolation, (2) incidence-functional, and (3) graph measures. Our results showed that matrix representation can greatly affect assessments of connections (i.e., connection length, effective distance, and spatial location), but not patch prioritization. Although patch importance was not much affected by matrix representation, it was influenced by the connectivity measure and its parameterization. We found the biggest differences in the case of the integral index of connectivity and equally weighted patches, but no consistent pattern in response to changing dispersal distance. Connectivity assessments in more fragmented landscapes were more sensitive to the selection of matrix representation. Although we recommend using continuous matrix representation whenever possible, our results indicated that simpler matrix representations can be also used as a proxy to delineate those patches that are important for overall connectivity, but not to identify connections among habitat patches.!://WOS:000343648700008Times Cited: 0 0921-2973WOS:00034364870000810.1007/s10980-014-0075-23<7Zipperer, W. C.1993:Deforestation patterns and their effects on forest patches177-184Landscape Ecology83:DEFORESTATION; FRAGMENTATION; FOREST EDGE; FOREST INTERIORArticleSephFive identifiable patterns of deforestation are recognized - internal, indentation, cropping, fragmentation, and removal - and each has a distinct effect on habitat quality of forest patches in the eastern United States. By overlaying land use maps from 1973 and 1981 for three counties in the State of Maryland (Prince Georges, Anne Arundel, and Wicomico), changes in the interior core area and edge length of individual patches were measured. Forest interior declined by 23.8 km2 in Anne Arundel, 16.3 kM2 in Prince Georges, and 8.4 kM2 in Wicomico. Within Anne Arundel and Prince Georges Counties, deforestation increased edge length by 52.1 km and 31.2 km, respectively, whereas, within Wicomico, it decreased edge length by 8.7 km. Differences among counties resulted from current land use patterns, percentage of forest cover, and the dominant deforestation pattern.://A1993MB34000004 IISI Document Delivery No.: MB340 Times Cited: 29 Cited Reference Count: 0 0921-2973 Landsc. Ecol.ISI:A1993MB34000004HZIPPERER, WC, SUNY,CESF SYRACUSE,US FOREST SERV,NEFES,SYRACUSE,NY 13210.EnglishI<7 Zmyslony, J. Gagnon, D.2000[Path analysis of spatial predictors of front-yard landscape in an anthropogenic environment357-371Landscape Ecology154landscape replication Mantel tests mimicry neighbour interactions residential landscape street section urban vegetation URBAN FOREST COMMUNITIES VEGETATIONArticleMay,Contagious spatial patterns were shown to exist in the landscape of front-yards in street sections of Hochelaga-Maisonneuve, Montreal. Neighbour mimicry was hypothesized as the mechanism behind this pattern (Zmyslony and Gagnon 1998). To assess the role of spatial environmental factors in structuring this pattern, we carried out a path analysis on the front-yard landscape with five spatial factors: relative distance, street side, width, depth and type of front-yard. We removed all non-significant factors from our model with simple Mantel tests and untangled the common spatial component from the relationship between spatial factors and front-yard landscape with partial Mantel tests. We then used path analysis to evaluate the relative importance of all significant spatial factors in structuring front-yard landscape and to determine the r(2) (% of landscape variation explained by spatial factors). Results showed that (1) among all spatial environmental factors, distance (proximity) remained the best predictor of front-yard vegetation - distance alone explained an average of 20% of the landscape variation of a street section, (2) depth, width and type of front-yard also structured the front-yard landscape independently of distance, (3) front-yard landscape expresses greater similarity within the same side of a street section, and (4) in two street sections of Hochelaga-Maisonneuve, spatial factors predicted over 40% of the landscape variation. This suggests (1) that landscape contagion exists also in highly humanized environments and (2) that the mimicry phenomenon was induced not only by proximity, but also by similar environmental conditions in same side street sections and whole street sections. Finally, we suggest that street sections are a very useful and appropriate unit of analysis of urban ecosystems.://000086006700005 ISI Document Delivery No.: 296DA Times Cited: 3 Cited Reference Count: 36 Cited References: BURGESS EW, 1925, GROWTH CITY INTRO RE, P47 CALDWELL LK, 1990, LANDSCAPE ECOL, V5, P3 COOPER CC, 1975, EASTER HILL VILLAGE DANSEREAU P, 1984, LIVRO HOMENAGEM ORLA, V1, P87 DECHARDIN HT, 1954, PHENOMENE HUMAIN DORNEY JR, 1984, URBAN ECOL, V8, P69 EVEILLARD C, 1991, THESIS U MONTREAL GOWER JC, 1986, J CLASSIF, V3, P5 JIM CY, 1993, LANDSCAPE URBAN PLAN, V23, P119 LEDUC A, 1992, J VEG SCI, V3, P69 LEGENDRE L, 1984, COLLECTION ECOLOGIE, V13 LEGENDRE P, 1985, R PACKAGE MULTIVARIA LEGENDRE P, 1989, VEGETATIO, V80, P107 MANTEL N, 1967, CANCER RES, V27, P209 MILLER RG, 1966, SIMULTANEOUS STAT IN MONGEAU P, 1988, REGLES STRATEGIES EX NANTEL P, 1992, ECOLOGY, V73, P99 NAVEH Z, 1990, CULTURAL ASPECTS LAN NAVEH Z, 1995, LANDSCAPE URBAN PLAN, V32, P43 PIELOU EC, 1984, INTERPRETATION ECOLO PLANTE S, 1986, HOCHELAGA MAISONEUVE RICHARDS NA, 1984, URBAN ECOL, V8, P99 ROUTABOULE D, 1995, PAYSAGE INTERIEUR EX ROWNTREE RA, 1988, LANDSCAPE URBAN PLAN, V15, P1 SANDERS RA, 1984, URBAN ECOL, V8, P13 SANDERS RA, 1984, URBAN ECOL, V8, P91 SKOLIMOWSKI H, 1984, ECOPHILOSOPHY DESIGN SMOUSE PE, 1986, SYST ZOOL, V35, P627 SOKAL RR, 1981, BIOMETRY WHITNEY GG, 1980, J APPL ECOL, V17, P431 ZMYSLONY J, 1997, THESIS U QUEBEC MONT ZMYSLONY J, 1998, LANDSCAPE URBAN PLAN, V40, P295 ZONNEVELD IS, 1982, PERSPECTIVES LANDSCA, P9 ZONNEVELD IS, 1989, LANDSCAPE ECOLOGY, V3, P67 ZUBE EH, 1982, LANDSCAPE PLANN, V9, P1 ZUBE EH, 1987, LANDSCAPE ECOLOGY, V1, P37 0921-2973 Landsc. Ecol.ISI:000086006700005Univ Quebec, Grp Rech Ecol Forestiere, Montreal, PQ H3C 3P8, Canada. Gagnon, D, Univ Quebec, Grp Rech Ecol Forestiere, CP 8888,Succ Ctr Ville, Montreal, PQ H3C 3P8, Canada.English|?2Zoffoli, M. L. Kandus, P. Madanes, N. Calvo, D. H.2008Seasonal and interannual analysis of wetlands in South America using NOAA-AVHRR NDVI time series: the case of the Parana Delta Region833-848Landscape Ecology237*The use of NOAA-AVHRR NDVI time series from July 1981 to December 2000 was evaluated for the assessment of the functioning of a wetland macrosystem, the Parana River Delta. The spatial resolution of the dataset was 8 by 8 km. Spatial and temporal variations in NDVI pattern were analyzed and evidences for El Nino/South Oscillation events identified. We studied five wetland units (WUs) classified on the basis of landscape pattern and dominant hydrologic regime. Spearman rank correlations were performed among the NDVI time series of the different WUs. NDVI time series were correlated with water level in the Parana River and with records of local rainfall. In order to obtain a synthetic model of NDVI patterns, the autocorrelation functions (ACF) were estimated for each of the WUs. Results indicated that monthly mean NDVI values for all WUs showed a similar annual seasonal pattern, suggesting a control from the plant annual cycle on the NDVI signal. Besides, two general NDVI patterns were identified. The first pattern is represented by WUs under fluvial hydrologic regime. This is subjected to a significative interannual variability associated mainly to ENSO events. The second pattern corresponds to WUs with a very regular NDVI patterns. It includes wetlands which water input corresponds to tides or to rainfall. The ENSO had no significant influence on this pattern. This study suggests that NOAA-AVHRR NDVI long time series might provide valuable information about functioning of the large scale fluvial wetlands like those associated with South America basins.!://WOS:000258540300006Times Cited: 0 0921-2973WOS:00025854030000610.1007/s10980-008-9240-9,<7Zollner, P. A.2000kComparing the landscape level perceptual abilities of forest sciurids in fragmented agricultural landscapes523-533Landscape Ecology156Mchipmunks (Tamias striatus) connectivity dispersal fox squirrel (Sciurus niger) gray squirrel (Sciurus carolinensis) habitat isolation inter-patch movements perceptual range WHITE-FOOTED MICE SMALL MAMMALS HABITAT FRAGMENTATION RED SQUIRREL POPULATION-DYNAMICS BEHAVIORAL ECOLOGY TAMIAS-STRIATUS GREY SQUIRREL CORRIDOR USE VULGARIS LArticleAugPerceptual range is the maximum distance from which an animal can perceive the presence of remote landscape elements such as patches of habitat. Such perceptual abilities are of interest because they influence the probability that an animal will successfully disperse to a new patch in a landscape. Furthermore, understanding how perceptual range differs between species may help to explain differential species sensitivity to patch isolation. The objective of this research was to assess the perceptual range of eastern chipmunks (Tamias striatus), gray squirrels (Sciurus carolinensis), and fox squirrels (Sciurus niger) in fragmented agricultural landscapes. Animals were captured in remote woodlots and translocated to unfamiliar agricultural fields. There they were released at different distances from a woodlot and their movements towards or away from the woodlot were used to assess their ability to perceive forested habitat. Observed perceptual ranges of approximately 120 m for chipmunks, 300 m for gray squirrels, and 400 m for fox squirrels, suggest that differences in landscape-level perceptual abilities may influence the occurrence of these species in isolated habitat patches.://000088037200003 i ISI Document Delivery No.: 331UN Times Cited: 42 Cited Reference Count: 75 Cited References: ALLEN DL, 1943, DEP CONS GAME DIV PU, V100, P1 ANDREASSEN HP, 1998, ACTA THERIOL, V43, P371 ANDREN H, 1994, OIKOS, V71, P355 BATSCHELET E, 1981, CIRCULAR STAT BIOL BAUMGARTNER LL, 1940, J WILDLIFE MANAGE, V4, P479 BENDEL PR, 1994, AM MIDL NAT, V132, P227 BENNETT AF, 1994, BIOL CONSERV, V68, P155 BOONSTRA R, 1986, CAN J ZOOL, V64, P1034 BOWERS MA, 1993, ETHOLOGY, V94, P72 BOWERS MA, 1993, OIKOS, V66, P229 CRIST TO, 1995, J ANIM ECOL, V64, P733 DIFFENDORFER JE, 1995, ECOLOGY, V76, P827 FAHRIG L, 1988, APPL MATH COMPUT, V27, P53 FIRLE S, 1998, ECOLOGY, V79, P2113 FITZGIBBON CD, 1993, J APPL ECOL, V30, P736 FORSYTH DJ, 1973, AM MIDL NAT, V90, P107 GILLIS EA, 1998, CAN J ZOOL, V76, P791 GOODWIN BJ, 1999, OIKOS, V84, P160 GUSTAFSON EJ, 1990, AM MIDL NAT, V123, P186 GUSTAFSON EJ, 1996, ECOLOGY, V77, P94 HADDAD NM, 1999, AM NAT, V153, P215 HENDERSON MT, 1985, BIOL CONSERV, V31, P95 HENEIN K, 1998, OIKOS, V81, P168 HUNGERFORD KE, 1941, J WILDLIFE MANAGE, V5, P458 IMS RA, 1995, MOSAIC LANDSCAPES EC, P85 KEY GE, 1996, CAN J ZOOL, V74, P733 KOPROWSKI JL, 1994, MAMMALIAN SPECIES, V479, P1 KOPROWSKI JL, 1994, MAMMALIAN SPECIES, V480, P1 LARSEN KW, 1994, ECOLOGY, V75, P214 LAURANCE WF, 1990, J MAMMAL, V71, P641 LAURANCE WF, 1995, LANDSCAPE APPROACHES, P46 LIDICKER WZ, 1996, METAPOPULATIONS WILD, P85 LIMA SL, 1986, ANIM BEHAV, V34, P536 LIMA SL, 1996, TRENDS ECOL EVOL, V11, P131 LIMA SL, 1998, ADV STUD BEHAV, V27, P215 LIU JG, 1995, CONSERV BIOL, V9, P62 MCADAM AG, 1998, ANIM BEHAV 1, V55, P109 NIXON CM, 1978, ILLINOIS NATURAL HIS, V105 NIXON CM, 1986, CAN J ZOOL, V64, P512 NUNES S, 1996, J MAMMAL, V77, P807 NUPP TE, UNPUB LANDSCAPE LEVE NUPP TE, 1998, J MAMMAL, V79, P1234 OXLEY DJ, 1974, J APPL ECOL, V11, P51 PETTERSSON B, 1985, BIOL CONSERV, V32, P335 PITHER J, 1998, OIKOS, V83, P166 PULLIAM HR, 1992, ECOL APPL, V2, P165 RAIL JF, 1997, CONDOR, V99, P976 ROITBERG BD, 1997, OIKOS, V80, P234 ROSENBLATT DL, UNPUB LANDSCAPE ECOL ROSENBLATT DL, 1999, AM MIDL NAT, V141, P115 ROSENBLATT DL, 1999, THESIS U ILLINOIS UR RUSHTON SP, 1997, J APPL ECOL, V34, P1137 SEIDEL DR, 1961, J MAMMAL, V42, P256 SHEPERD BF, 1995, CAN J ZOOL, V73, P2098 SMITH CC, 1972, ECOLOGY, V53, P82 SNYDER DP, 1982, MAMM SPECIES, V168, P1 STEELE MA, 1992, AM MIDL NAT, V128, P156 SWIHARD RK, 1998, SPECIAL PUBLICATION, V6, P1 TAYLOR PD, 1993, OIKOS, V68, P571 TURCHIN P, 1998, QUANTITATIVE ANAL MO TURNER MG, 1993, ECOL MODEL, V69, P163 VANAPELDOORN RC, 1994, LANDSCAPE ECOL, V9, P227 VANVUREN D, 1998, BEHAV ECOLOGY CONSER, P369 VERBOOM B, 1990, LANDSCAPE ECOL, V4, P171 WAUTERS L, 1994, OIKOS, V69, P140 WEGNER JF, 1979, J APPL ECOL, V16, P349 WIENS JA, 1997, OIKOS, V78, P257 WITH KA, 1994, LANDSCAPE ECOL, V9, P25 WITH KA, 1995, ECOLOGY, V76, P2446 WITH KA, 1996, ECOL MODEL, V93, P125 YOEMANS SR, 1995, ANIM BEHAV, V49, P977 ZOLLNER PA, 1997, OIKOS, V80, P51 ZOLLNER PA, 1999, ANIM BEHAV 3, V58, P489 ZOLLNER PA, 1999, ECOLOGY, V80, P1019 ZOLLNER PA, 1999, OIKOS, V84, P164 0921-2973 Landsc. Ecol.ISI:000088037200003Indiana State Univ, Dept Life Sci, Terre Haute, IN 47809 USA. Zollner, PA, US Forest Serv, USDA, N Cent Res Stn, 5985 Highway K, Rhinelander, WI 54501 USA.English ?Isaak S. Zonneveld1989PThe land unit - A fundamental concept in landscape ecology, and its applications67-86Landscape Ecology32clandscape survey, land unit concept, land unit mapping, land unit systems, landscape classificationS The land unit, as an expression of landscape as a system, is a fundamental concept in landscape ecology. It is an ecologically homogeneous tract of land at the scale at issue. It provides a basis for studying topologic as well as chorologic landscape ecology relationships. A land unit survey aims at mapping such land units. This is done by simultaneously using characteristics of the most obvious (mappable) land attributes: landform, soil and vegetation (including human alteration of these three). The land unit is the basis of the map legend but may be expressed via these three land attributes. The more dynamic land attributes, such as certain animal populations and water fluxes, are less suitable as diagnostic criteria, but often link units by characteristic information/energy fluxes. The land unit survey is related to a further development of the widely accepted physiographic soil survey (see Edelman 1950). Important aspects include: by means of a systems approach, the various land data can be integrated more appropriately; geomorphology, vegetation and soil science support each other during all stages (photo-interpretation, field survey, data processing, final classification); the time and costs are considerably less compared with the execution of separate surveys; the result is directly suitable as a basis for land evaluation; the results can be expressed in separate soil, vegetation, land use and landform maps, or even single value maps. A land unit survey is therefore: a method for efficient survey of land attributes, such as soils, vegetation, landform, expressed in either separate or combined maps; a means of stimulating integration among separate land attribute sciences; an efficient basis for land evaluation. For multidisciplinary projects with applied ecologic aims (e.g., land management), it is therefore the most appropriate survey approach. Within the land unit approach there is considerable freedom in the way in which the various land attribute data are ‘integrated’. It is essential, however, that: during the photo-interpretation stage, the contributions of the various specialists are brought together to prepare a preliminary (land unit) photo-interpretation map; the fieldwork data are collected at exactly the same sample point, preferably by a team of specialists in which soil, vegetation and geomorphology are represented; the final map is prepared in close cooperation of all contributing disciplines, based on photo interpretation and field data; the final map approach may vary from one fully-integrated land unit map to various monothematic maps.?Nw-Xiaoming Zou Corinna Theiss Burton V. Barnes1992Pattern of Kirtland’s warbler occurrence in relation to the landscape structure of its summer habitat in northern Lower Michigan221-231Landscape Ecology64|Landscape ecology, landscape ecosystems, landscape structure, Kirtland’s warbler, endangered species, jack pine-oak forestStudies of the endangered Kirtland’s warbler in relation to landscape ecosystems were conducted from 1986- 1988 on a large wildfire-burn surrounding Mack Lake in southeastern Oscoda County, Michigan. A landscape ecosystem approach was used to distinguish low- and high-elevation segments of the landscape, as well as 11 local ecosystem types. The ecosystems were distinguished by physiography, microclimate, soil, and vegetation. The early occurrence of the warblers was strongly related to landscape structure, i.e., to the broad low- and high-elevation areas and the local ecosystem types within them. Territories of male warblers were observed in 5 of the 11 ecosystems. The five ecosystem types where warblers were observed were characterized by (1) a physiography of level or rolling terrain; (2) soil series of Grayling, Graycalm, Montcalm, or Rubicon; (3) uplands with relatively warm temperature during the breeding season; (4) vegetation dominated by low sweet blueberry, bearberry, wintergreen, northern pin oak, blue stem grasses, and hair cap moss; and (5) canopy of relatively tall, dense, and patchy jack pine and oak. Landscape structure appears to be an important factor affecting the occurrence of the warbler in its summer habitat in northern Lower Michigan. <7 #Zozaya, E. L. Brotons, L. Saura, S.2012Recent fire history and connectivity patterns determine bird species distribution dynamics in landscapes dominated by land abandonment171-184Landscape Ecology2728colonisation dynamics connectivity fire history habitat configuration land-use changes land abandonment open-habitat bird species potential dispersal flux eastern iberian peninsula mediterranean landscapes habitat availability breeding dispersal spatial-patterns catalonia ne forest spain biodiversity vegetationFebMediterranean landscapes are suffering two opposing forces leading to large-scale changes in species distribution: land abandonment of less productive areas and an increase in wildfire impact. Here, we test the hypothesis that fires occurred in recent decades drive the pattern of expansion of early-successional, open-habitat bird species by aiding in the process of colonisation of newly burnt areas. The study was carried out in Catalonia (NE Spain). We selected 44 burnt sites occurring between 2000 and 2005 to model colonisation patterns under different assumptions of potential colonisers' sources and evaluated the colonisation estimates with empirical data on six bird species especially collected for this purpose. We first defined three landscape scenarios serving as surrogates of potential colonisers' sources: open-habitats created by fire, shrublands and farmlands. Then, we used a parameter derived from a functional connectivity metric to estimate species colonization dynamics on the selected sites by each particular scenario. Finally, we evaluated our colonisation estimates with the species occurrence in the studied locations by using generalized linear mixed models. The occurrence of the focal species on the newly burnt sites was significantly related to the connectivity patterns described by both the recent fire history and the other open-habitat types generated by a different type of disturbance. We suggest that land use changes in recent decades have produced a shift in the relative importance of habitats acting as reservoirs for open-habitat bird species dynamics in Mediterranean areas. Before the middle of the twentieth century species' reservoirs were probably constituted by relatively static open habitats (grassland and farmland), whereas afterwards they likely consist of a shifting mosaic of habitat patches where fire plays a key role as connectivity provider and largely contributes to the maintenance of species persistence.://0003000887000039Sp. Iss. SI 889QQ Times Cited:1 Cited References Count:65 0921-2973Landscape EcolISI:000300088700003Zozaya, EL Ctr Tecnol Forestal Catalunya, Ctra St Llorenc de Morunys Port Comte Km 2, Solsona 25280, Spain Ctr Tecnol Forestal Catalunya, Ctra St Llorenc de Morunys Port Comte Km 2, Solsona 25280, Spain Ctr Tecnol Forestal Catalunya, Solsona 25280, Spain Museu Ciencies Nat Ciutadella, Inst Catala Ornitol, Barcelona 08003, Spain Univ Politecn Madrid, ETSI Montes, E-28040 Madrid, SpainDOI 10.1007/s10980-011-9695-yEnglish'?B Ervin H. Zube19870Perceived land use patterns and landscape values37-45Landscape Ecology118land use pattern, perception, information, human ecology+Land use patterns and land form are important sources of information that contribute to the formation of landscape perceptions and values. This paper discusses three concepts of human-landscape relationships: the human as an agent of biological and physical impacts on the landscape; the human as a static receiver and processor of information from the landscape; and the human as an active participant in the landscape-thinking, feeling and acting - a transactional concept. A model of the transactional concept and of human perception and response is presented along with a conjectural example of human-landscape transactions. Three empirical research projects are presented to illustrate varying relationships between and among humans and landscapes. Variations in human experiences, needs and desires, personal utility functions for the use of the landscape, and socio-cultural contexts are suggested as mediating variables on perceived values and human responses. The importance of landscape values information to planning and management activities is discussed.|? Zurita, G. A. Bellocq, M. I.2010Spatial patterns of bird community similarity: bird responses to landscape composition and configuration in the Atlantic forest147-158Landscape Ecology2513Studies dealing with community similarity are necessary to understand large scale ecological processes causing biodiversity loss and to improve landscape and regional planning. Here, we study landscape variables influencing patterns of community similarity in fragmented and continuous forest landscapes in the Atlantic forest of South America, isolating the effects of forest loss, fragmentation and patterns of land use. Using a grid design, we surveyed birds in 41 square cells of 100 km(2) using the point count method. We used multivariate, regression analyses and lagged predictor autoregressive models to examine the relative influence of landscape variables on community similarity. Forest cover was the primary variable explaining patterns of bird community similarity. Similarity showed a sudden decline between 20 and 40% of forest cover. Patterns of land use had a second order effect; native bird communities were less affected by forest loss in landscapes dominated by tree plantations (the most suitable habitat for native species) than in landscapes dominated by annual crops or cattle pastures. The effects of fragmentation were inconclusive. The trade-off between local extinctions and the invasion of extra-regional species using recently created habitats is probably the mechanism generating the observed patterns of community similarity. Limiting forest loss to 30-40% of the landscape cover and improving the suitability of human-modified habitats will contribute to maintain the structure and composition of the native forest bird community in the Atlantic forest.!://WOS:000273479100012Times Cited: 0 0921-2973WOS:00027347910001210.1007/s10980-009-9410-4ڽ7 FZurlini, Giovanni Petrosillo, Irene Jones, K. Bruce Zaccarelli, Nicola2013pHighlighting order and disorder in social–ecological landscapes to foster adaptive capacity and sustainability 1161-1173Landscape Ecology286Springer NetherlandsYSpectral entropy Order and disorder Adaptive capacity Sustainability NDVI-related indices 2013/07/01+http://dx.doi.org/10.1007/s10980-012-9763-y 0921-2973Landscape Ecol10.1007/s10980-012-9763-yEnglishV?DGiovanni Zurlini Kurt H. Riitters Nicola Zaccarelli Irene Petrosillo2007LPatterns of disturbance at multiple scales in real and simulated landscapes 705-721Landscape Ecology225EDisturbance pattern - Neutral model - Moving window - Land use change<We describe a framework to characterize and interpret the spatial patterns of disturbances at multiple scales in socio-ecological systems. Domains of scale are defined in pattern metric space and mapped in geographic space, which can help to understand how anthropogenic disturbances might impact biodiversity through habitat modification. The approach identifies typical disturbance 'profiles' based on the similarity of trajectories in a pattern metric space over a range of spatial scales. When different profiles are coherent in pattern metric space, they describe a regional spatial pattern. The divergence of a profile indicates a scale-dependent transition to a local spatial pattern, which can be examined for correspondence to different regions of geographic space. We illustrate the conceptual model with simulated maps and real disturbance maps from satellite imagery in south Italy. The results suggest that management of disturbances in the study region depend less on local drivers of disturbance and more on broader-scale drivers within the socio-ecological framework. 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