PK˜½n;YFꋸk>¸k>refs.MYD ¢üÐ<ÿþ79Ludwig, 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; AUSTRALIAArticleFeb®Assessment 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:000243823900001ÕTrop 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.auEnglish ÷üÐ<ÿþ7<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:000243823900002ÈEuropean 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.itEnglish _üÐ<ÿþ7=Wickham, J. D. Riitters, K. H. Wade, T. G. Coan, M. Homer, C.2007?The effect of Appalachian mountaintop mining on interior forest179-187Landscape Ecology222«Appalachian mountains; coal mining; edge effects; forest loss; interior forest UNITED-STATES; LAND-USE; HABITAT FRAGMENTATION; NUTRIENT; SCALE; DYNAMICS; SERVICES; CLIMATEArticleFeb‡Southern 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:000243823900003€US 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.govEnglishcüÐ<ÿþ7CLopez-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 Ecology222èoak; 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; OAKArticleFeb‰Hard (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 ª 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:000243823900004ðINECOL 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.mxEnglishÜüÐ<ÿþ7Gagne, S. A. Fahrig, L.2007jEffect of landscape context on anuran communities in breeding ponds in the National Capital Region, Canada205-215Landscape Ecology222áland use; urbanization; agriculture; forest cover; Amphibian conservation; species richness; abundance SPECIES RICHNESS; LAND-USE; AMPHIBIANS; FRAGMENTATION; FROG; CONSEQUENCES; BIODIVERSITY; POPULATIONS; PREDATION; ABUNDANCEArticleFebäLand 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 ÜISI 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.comEnglishËüÐ<ÿþ7cGonzalez-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 Ù 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.eduEnglishüÐ<ÿþ7Galbraith, L. M. Burns, C. W.2007KLinking land-use, water body type and water quality in southern New Zealand231-241Landscape Ecology222Åwetlands; 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:000243823900007¡Univ 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.nzEnglishZüÐ<ÿþ7 =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 Ecology222àFinland; spatial forest planning; spatial objectives; stand neighborhood structure; suitable habitat PTEROMYS-VOLANS; WILDLIFE; EXTINCTION; OPTIMIZATION; CONSERVATION; BIODIVERSITY; CONSTRAINTS; LANDSCAPES; MOVEMENTS; OREGONArticleFebªSpatial 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.fiEnglish,üÐ<ÿþ7 Leyk, S. Zimmermann, N. E.2007OImproving land change detection based on uncertain survey maps using fuzzy sets257-272Landscape Ecology222Äpredictive 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:000243823900009âUniv 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–üÐ<ÿþ7 *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:000243823900010àUniv 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.orgEnglishæüÐ<ÿþ7Maheu-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:000243823900011³McGill 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.caEnglishcüÐ<ÿþ7'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 Ecology222þscaling; 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—üÙ<ÿþ7_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:000243619800001ÛUniv 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)üÙ<ÿþ7 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:000243619800002¾Technion 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 ZüÐ<ÿþ7Buyantuyev, A. Wu, J. G.2007<Effects of thematic resolution on landscape pattern analysis7-13Landscape Ecology221álandscape characterization; image classification; thematic resolution; landscape metrics; landscape pattern analysis SCALING RELATIONS; CHANGING SCALE; METRICS; INDEXES; FRAGMENTATION; AGGREGATION; SENSITIVITY; BEHAVIOR; AREAArticleJanéThe 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:000243619800003ÛArizona 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.eduEnglishüÐ<ÿþ7Gardner, R. H. Urban, D. L.2007/Neutral models for testing landscape hypotheses15-29Landscape Ecology221îneutral 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; VEGETATIONArticleJan–Neutral 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:000243619800004ûUniv 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.eduEnglishPüÐ<ÿþ7Bodin, O. Norberg, J.2007YA network approach for analyzing spatially structured populations in fragmented landscape31-44Landscape Ecology221ýlandscape fragmentation; compartments; graphs; network analysis; Madagascar; Lemur catta; spatial resilience; natural reserves HABITAT FRAGMENTATION; LEMUR-CATTA; CONNECTIVITY; METRICS; RESILIENCE; MADAGASCAR; DISPERSAL; PERSPECTIVE; THRESHOLDS; MAMMALSArticleJanËWe 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 ÊISI 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:000243619800005šStockholm Univ, Dept Syst Ecol, S-10691 Stockholm, Sweden. Bodin, O, Stockholm Univ, Dept Syst Ecol, S-10691 Stockholm, Sweden. orjan@system.ecology.su.seEnglishˆüÐ<ÿþ7Grear, J. S. Burns, C. E.2007˜Evaluating effects of low quality habitats on regional population growth in Peromyscus leucopus: Insights from field-parameterized spatial matrix models45-60Landscape Ecology221ühabitat 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; SURVIVALArticleJan…Due 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‡üÐ<ÿþ7 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:000243619800007ÄUS 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.govEnglishüüÐ<ÿþ70Smithwick, 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 Ecology221ºlandscape; carbon; disturbance; fire; harvest; NECB; NPP; model PACIFIC-NORTHWEST; FIRE FREQUENCY; BOREAL FOREST; PRODUCTIVITY; DISTURBANCE; MODELS; SCALE; USA; SEQUESTRATION; ATMOSPHEREArticleJaníShort- 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 ÏISI 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.eduEnglish0üÐ<ÿþ7 "He, Z. B. Zhao, W. Z. Chang, X. L.2007›The modifiable areal unit problem of spatial heterogeneity of plant community in the transitional zone between oasis and desert using semivariance analysis95-104Landscape Ecology221“transitional zone between oasis and desert; spatial heterogeneity; the modifiable areal unit problem; scale effect; zoning effect LANDSCAPE ECOLOGYArticleJanŠThe 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 ÀISI 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:000243619800009ßChinese 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.cnEnglishHüÐ<ÿþ7!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; COEXISTENCEArticleJan¼Among 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:000243619800010¸Ben 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.ilEnglishšüÐ<ÿþ7"Guirado, M. Pino, J. Roda, F.2007ŒComparing 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.esEnglishTüÐ<ÿþ7#Weir, J. E. S. Corlett, R. T.2007WHow far do birds disperse seeds in the degraded tropical landscape of Hong Kong, China?131-140Landscape Ecology221úbulbuls; dispersal distance; frugivory; Garrulax; global warming; habitat fragmentation; landscape connectivity; pycnonotidae; seed shadows MONTANE FOREST; PATTERNS; TREE; FRAGMENTATION; CONSEQUENCES; MIGRATION; MOVEMENT; TRACKING; DISTANCE; BEHAVIORArticleJan½Information 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:000243619800012ÊUniv 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.hkEnglish¹üÐ<ÿþ7$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 Ecology221Òtimber 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:000243619800013³USDA, 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.usEnglishƒüÐ<ÿþ7%Verburg, P. H.2006=Simulating feedbacks in land use and land cover change models 1171-1183Landscape Ecology218áland 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:000242089300001ÍUniv 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 áüÐ<ÿþ7&$Chen, X. W. Barrows, C. W. Li, B. L.2006SPhase coupling and spatial synchrony of subpopulations of an endangered dune lizard 1185-1193Landscape Ecology218“Coachella 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 üÐ<ÿþ7'Bossuyt, B. Honnay, O.2006…Interactions between plant life span, seed dispersal capacity and fecundity determine metapopulation viability in a dynamic landscape 1195-1205Landscape Ecology218æclonality; 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.beEnglishJüÐ<ÿþ7(.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 Ecology218ðhabitat; logistic regression; multiscale analysis; nest site use; Nipponia nippon; geographic information system; reintroduction; scaling; semivariogram LANDSCAPE PATTERN-ANALYSIS; INVENTORY DATA; HABITAT; ECOLOGY; PRODUCTIVITY; BIRDS; PREYArticleNovÙThe 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.comEnglishüÐ<ÿþ7)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 Ecology218÷arid grasslands; desertification; drought; grazing; perennial grasses; transport processes SEMIDESERT GRASSLAND RANGE; CONSERVATION BIOLOGY; ECOLOGICAL RESEARCH; TRANSITION ZONE; UNITED-STATES; VEGETATION; PATTERNS; DESERTIFICATION; EROSION; SCALEArticleNovÈFactors 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:000242089300005´USDA 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.eduEnglish¹üÐ<ÿþ7*$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; COMMUNITIESArticleNovæDespite 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:000242089300006®Univ 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`üÐ<ÿþ7+Brook, B. W. Bowman, Dmjs2006ˆPostcards 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:000242089300007ËCharles 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¯üÐ<ÿþ7,-Pringle, H. J. R. Watson, I. W. Tinley, K. L.2006€Landscape 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; BALANCEArticleNovšRecent 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±üÐ<ÿþ7-5Schoennagel, 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; VARIABILITYArticleNov©A 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.eduEnglish8üÐ<ÿþ7.(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 Ecology218¾Desakota; 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:000242089300010ôEastern 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.eduEnglish_üÐ<ÿþ7/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; USLEArticleNovãSince 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.caEnglishÀüÐ<ÿþ70(Baker, M. E. Weller, D. E. Jordan, T. E.2006TImproved methods for quantifying potential nutrient interception by riparian buffers 1327-1345Landscape Ecology218èriparian 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:000242089300012ðUtah 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.eduEnglishèüÐ<ÿþ71FFullerton, A. H. Beechie, T. J. Baker, S. E. Hall, J. E. Barnas, K. A.2006‹Regional patterns of riparian characteristics in the interior Columbia River basin, Northwestern USA: applications for restoration planning 1347-1360Landscape Ecology218ßcoarse-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 êISI 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:000242089300013çNOAA 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.govEnglishüÐ<ÿþ72Rizkalla, 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; POPULATIONArticleNovÆSeveral 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:000242089300014ÂPurdue 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.eduEnglish üÐ<ÿþ73Pascual-Hortal, L. Saura, S.2006˜Comparison and development of new graph-based landscape connectivity indices: towards the priorization of habitat patches and corridors for conservation959-967Landscape Ecology217Øconnectivity; 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:000241010900001ñUniv 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.esEnglishZüÐ<ÿþ74tOkland, R. H. Bratli, H. Dramstad, W. E. Edvardsen, A. Engan, G. Fjellstad, W. Heegaard, E. Pedersen, O. Solstad, H.2006ŸScale-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:000241010900002¡Univ 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.noEnglishjüÐ<ÿþ753Schweiger, O. Dormann, C. F. Bailey, D. Frenzel, M.2006ŒOccurrence 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; BIODIVERSITYArticleOct’Distribution 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 À 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”üÐ<ÿþ76Wang, 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:000241010900004£SUNY 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.sgEnglishÌüÐ<ÿþ77VVan 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 Ecology217ÄEU 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:000241010900005êWL 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.nlEnglishnüÐ<ÿþ78-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; COMPLEXITYArticleOctíThe 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:000241010900006×E 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.eduEnglishÆüÐ<ÿþ79Koper, 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; ABUNDANCEArticleOctÞPrevious 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:000241010900007¦Univ Alberta, Dept Renewable Resources, Edmonton, AB T6G 2H1, Canada. Koper, N, Univ Manitoba, Inst Nat Resources, Winnipeg, MB R3T 2N2, Canada. koper@cc.umanitoba.caEnglishSüÐ<ÿþ7:#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 Ó 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:000241010900008ÃUniv 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.brEnglishVüÐ<ÿþ7;/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 Ecology217áconditional 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.orgEnglishüÐ<ÿþ7<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 ýISI 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!üÐ<ÿþ7=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; CONSERVATIONArticleOctäThe 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 ÄISI 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.beEnglish±üÐ<ÿþ7>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 Ecology217ÄBlakely'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:000241010900012þAustralian 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.auEnglishåüÐ<ÿþ7?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; DYNAMICSArticleOctçOver 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 Ý 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.seEnglish3üÐ<ÿþ7@-Pontius, R. G. Versluis, A. J. Malizia, N. R.2006BVisualizing certainty of extrapolations from models of land change 1151-1166Landscape Ecology217Ëaccuracy; 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.eduEnglishVüöÿÿÿ?ÉDGiovanni 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. üöÿÿÿ?Ê-Sara A. O. Cousins Helena Ohlson Ove Eriksson2007‚Effects of historical and present fragmentation on plant species diversity in semi-natural grasslands in Swedish rural landscapes 723-730Landscape Ecology225–Area-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. ºüöÿÿÿ?Ë/Valerie J. Debuse Judith King Alan P. N. House2007ŽEffect 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. FüÐ<ÿþ7“3Rustigian, 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 ÕISI 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:000181767500005üOregon 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÷üÐ<ÿþ7”3Jordan, F. Baldi, A. Orci, K. M. Racz, I. Varga, Z.2003¥Characterizing the importance of habitat patches and corridors in maintaining the landscape connectivity of a Pholidoptera transsylvanica (Orthoptera) metapopulation83-92Landscape Ecology181»connectivity 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.huEnglishVüÐ<ÿþ7•Belanger, L. Grenier, M.2002_Agriculture intensification and forest fragmentation in the St. Lawrence valley, Quebec, Canada495-507Landscape Ecology176 human population satelite imagery HAUT-SAINT-LAURENT HABITAT FRAGMENTATION NEW-ENGLAND LANDSCAPE BIRDS DYNAMICS DEFORESTATION PERCEPTIONS ASSEMBLAGES VEGETATIONArticleOct„Quantifying 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:000179774900001éEnvironm 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 GüÐ<ÿþ7– Matthysen, E.2002`Boundary effects on dispersal between habitat patches by forest birds (Parus major, P-caeruleus)509-515Landscape Ecology176±Belgium 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 ãISI 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:000179774900002‡Univ Instelling Antwerp, Dept Biol, B-2610 Wilrijk, Belgium. Matthysen, E, Univ Instelling Antwerp, Dept Biol, B-2610 Wilrijk, Belgium.EnglisháüÐ<ÿþ7—Cousins, S. A. O. Eriksson, O.2002qThe influence of management history and habitat on plant species richness in a rural hemiboreal landscape, Sweden517-529Landscape Ecology176Ðalpha 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:000179774900003ÝStockholm 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.EnglishÆüÐ<ÿþ7˜&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.English€üÐ<ÿþ7™%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 Ecology176åfire 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 CALIFORNIAArticleOct»Topography, 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.EnglishËüÐ<ÿþ7š#He, F. L. LaFrankie, J. V. Song, B.2002SScale dependence of tree abundance and richness in a tropical rain forest, Malaysia559-568Landscape Ecology176Édiversity mapping grain size Malaysia spatial variation tropical rain forest JANZEN-CONNELL MODEL SPATIAL SCALE PLANT-COMMUNITIES SPECIES RICHNESS DIVERSITY ECOLOGY PATTERNS DENSITY VEGETATION DYNAMICSArticleOctþAbundance 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.EnglishüÐ<ÿþ7›Thompson, C. M. McGarigal, K.2002lThe influence of research scale on bald eagle habitat selection along the lower Hudson River, New York (USA)569-586Landscape Ecology176Àextent grain habitat selection Haliaeetus leucocephalus multi-scale scale threshold NEST SITE SELECTION RESOURCE SELECTION LANDSCAPE ECOLOGY AVAILABILITY DATA RESPONSES PATTERNS ARIZONA MODELSArticleOct£As 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:000179774900007×Utah 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.English­üÐ<ÿþ7œ%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 AUSTRALIAArticleOctêHuman-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 Š 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:000179774900008ÑUniv 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.EnglishþüÐ<ÿþ7 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-FORESTSReviewNov©Humans 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:000179746400001¦US 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.EnglishsüÐ<ÿþ7žCFuhlendorf, 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.eduEnglishÐüÐ<ÿþ7O2Ernoult, 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:000240500100001œUniv 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.frEnglish6üÐ<ÿþ7P(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:000240500100002ÏUniv 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 üÐ<ÿþ7QCaplat, P. Lepart, J. Marty, P.2006“Landscape 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:000240500100003ÀCNRS, 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.frEnglishuüÐ<ÿþ7R!Ko, D. W. He, H. S. Larsen, D. R.2006KSimulating private land ownership fragmentation in the Missouri Ozarks, USA671-686Landscape Ecology215úForest 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:000240500100004¬Univ 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.eduEnglishÕüÐ<ÿþ7SRanius, T. Kindvall, O.2006xExtinction risk of wood-living model species in forest landscapes as related to forest history and conservation strategy687-698Landscape Ecology215êcoarse 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; REQUIREMENTSArticleJulÉDead 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 øISI 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:000240500100005ãSwedish 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 ÔüÐ<ÿþ7T5Heinl, 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; VEGETATIONArticleJuløA 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.deEnglishÃüÐ<ÿþ7U,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; AREAArticleJulÇHabitat 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.eduEnglish9üÐ<ÿþ7V0Zhu, 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 Ecology215÷fragmentation; 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; GROWTHArticleJul¬Urbanization 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 ‘üÐ<ÿþ7WKou, X. J. Baker, W. L.2006LA landscape model quantifies error in reconstructing fire history from scars735-745Landscape Ecology215€error 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 žISI 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:000240500100009çUniv 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.eduEnglisháüÐ<ÿþ7XPDickson, 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 Ecology215çfire risk; lightning; ponderosa pine; topographic roughness; weights of evidence; wildland fire UNITED-STATES; LANDSCAPE STRUCTURE; AMERICAN SOUTHWEST; FOREST ECOSYSTEMS; WILDFIRE; MANAGEMENT; MOUNTAINS; REGIMES; ROADS; RESTORATIONArticleJulÐIn 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.eduEnglishïüÐ<ÿþ7Y=Frimpong, E. A. Ross-Davis, A. L. Lee, J. G. Broussard, S. R.2006ŠBiophysical 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.eduEnglishºüÐ<ÿþ7Z.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.eduEnglishWüØ<ÿþ7[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:000239484200001¤WSL 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¬üÐ<ÿþ7\$Holderegger, R. Kamm, U. Gugerli, F.2006KAdaptive vs. neutral genetic diversity: implications for landscape genetics797-807Landscape Ecology216êadaptive 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.chEnglishÿüÐ<ÿþ7] 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 ALBAArticleAug‡Landscape 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 ½ 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:000239484200003ŽDalhousie Univ, Dept Biol, Halifax, NS B2H 4J1, Canada. Latta, RG, Dalhousie Univ, Dept Biol, Halifax, NS B2H 4J1, Canada. Robert.Latta@Dal.caEnglish>üÐ<ÿþ7^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-POPULATIONSArticleAugâGenetic 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.eduEnglishüÐ<ÿþ7_Pannell, J. R. Dorken, M. E.2006ƒColonisation as a common denominator in plant metapopulations and range expansions: effects on genetic diversity and sexual systems837-848Landscape Ecology216£androdioecy; 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; DIFFERENTIATIONArticleAugÉColonisation 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 ¹ 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:000239484200005¡Univ 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.ukEnglishÚüÐ<ÿþ7`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 Ecology216ücellular automaton; disturbance; epiphytes; forest dynamics; genetic structure; Lobaria pulmonaria; population genetics LOBARIA-PULMONARIA; HABITAT FRAGMENTATION; DISPERSAL; POPULATION; CONNECTIVITY; CONSERVATION; DIVERSITY; DIASPORES; ECOLOGY; BIOLOGYArticleAugÀThe 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:000239484200006”WSL Swiss Fed Res Inst, CH-8903 Birmensdorf, Switzerland. Wagner, HH, WSL Swiss Fed Res Inst, CH-8903 Birmensdorf, Switzerland. helene.wagner@wsl.chEnglishªüÐ<ÿþ7a)Antolin, M. F. Savage, L. T. Eisen, R. J.2006bLandscape features influence genetic structure of black-tailed prairie dogs (Cynomys ludovicianus)867-875Landscape Ecology216Ðdisease; 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:000239484200007üColorado 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.eduEnglish7üÐ<ÿþ7b6Broquet, 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; MARKERSArticleAugìEmpirical 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.chEnglishüÐ<ÿþ7cFHolzhauer, 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 Ecology216¼genetic 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:000239484200009ÒUniv 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.deEnglishýüÐ<ÿþ7d+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 Ecology216Œbottlenecks; 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; MIGRATIONArticleAugÿSpatial 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:000239484200010âUniv 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.eduEnglishôüÐ<ÿþ7eDrew, C. A. Eggleston, D. B.2006`Currents, landscape structure, and recruitment success along a passive-active dispersal gradient917-931Landscape Ecology216ícellular 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 Ì 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:000239484200011ôN 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.eduEnglishFüÐ<ÿþ7f5Brown, K. Hansen, A. J. Keane, R. E. Graumlich, L. J.2006PComplex interactions shaping aspen dynamics in the Greater Yellowstone Ecosystem933-951Landscape Ecology216¼aspen; 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 ÈISI 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 üÐ<ÿþ7g'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; VULNERABILITYArticleMayºThe 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 ×üÐ<ÿþ7hPasher, J. King, D. J.2006GLandscape fragmentation and ice storm damage in eastern ontario forests477-483Landscape Ecology214ºdamage; 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 æISI 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:000237487700002ÞCarleton 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.caEnglish>üÐ<ÿþ7i4Ecke, F. Christensen, P. Sandstrom, P. Hornfeldt, B.2006eIdentification of landscape elements related to local declines of a boreal grey-sided vole population485-497Landscape Ecology214€1-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 SWEDENArticleMay¤Several 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.seEnglish1üÐ<ÿþ7jHeino, 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; GASTROPODSArticleMay“Biotic 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‘üÐ<ÿþ7k;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 Ecology214Ôage 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 ËISI 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.caEnglishOüÐ<ÿþ7l Chapa-Vargas, L. Robinson, S. K.2006…Nesting 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; DISTURBANCEArticleMayÓMeasuring 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.mxEnglishwüÐ<ÿþ7m3Schumacher, S. Reineking, B. Sibold, J. Bugmann, H.2006TModeling the impact of climate and vegetation on fire regimes in mountain landscapes539-554Landscape Ecology214üclimate 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 å 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§üÐ<ÿþ7n$Couteron, P. Barbier, N. Gautier, D.2006oTextural ordination based on fourier spectral decomposition: A method to analyze and compare landscape patterns555-567Landscape Ecology214ýCameroon; 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^üÐ<ÿþ7o'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:000237487700009úColorado 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.eduEnglishüÐ<ÿþ7pAOvalle, C. Del Pozo, A. Casado, M. A. Acosta, B. de Miguel, J. M.2006ƒConsequences 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 ÐISI 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:000237487700010øUniv 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.clEnglishüÐ<ÿþ7qVega-Garcia, C. Chuvieco, E.2006„Applying local measures of spatial heterogeneity to Landsat-TM images for predicting wildfire occurrence in mediterranean landscapes595-605Landscape Ecology214„forest fire; Landsat; landscape pattern; Mediterranean landscape; remote sensing; Spain; wildfire occurrence CLASSIFICATION; PATTERNArticleMayÅIn 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:000237487700011ùUniv 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.esEnglishyüÐ<ÿþ7rBrandt, J. S. Townsend, P. A.2006cLand use - land cover conversion, regeneration and degradation in the high elevation Bolivian Andes607-623Landscape Ecology214ôclassification; desertification; remote sensing; South America; spectral mixture analysis (SMA) MULTIPLE SPATIAL SCALES; LANDSCAPE INFLUENCES; BIOTIC INTEGRITY; PUNA ECOSYSTEMS; VEGETATION; CLASSIFICATION; ALTIPLANO; STREAMS; ACCURACY; AMAZONIAArticleMayÃRegional 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.eduEnglishnüÙ<ÿþ7sPedroli, 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:000236968500001úAlterra 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.nlEnglishnüÐ<ÿþ7tSwaffield, 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 ô 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:000236968500002ÏLincoln 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–üÐ<ÿþ7u+Pinto-Correia, T. Gustavsson, R. Pirnat, J.2006ˆBridging 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; FUTUREArticleApråEuropean 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.ptEnglishéüÐ<ÿþ7vLPalang, 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 ASPECTSArticleApr©Interactions 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.eeEnglishùüÐ<ÿþ7w"Bastian, O. Kronert, R. Lipsky, Z.2006[Landscape diagnosis on different space and time scales - a challenge for landscape planning359-374Landscape Ecology213‹evaluation; 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 Ø 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.deEnglishLüÐ<ÿþ7x&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 Ecology213Šculture; 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:000236968500006ëAlterra 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 üÐ<ÿþ7y*Groom, G. Mucher, C. A. Ihse, M. Wrbka, T.2006WRemote sensing in landscape ecology: experiences and perspectives in a European context391-408Landscape Ecology213Âclassification; 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:000236968500007©Natl 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.dkEnglishØüÐ<ÿþ7zZJongman, 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 Ecology213¿clustering; 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 ³ISI 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:000236968500008¸Univ 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.nlEnglish süÐ<ÿþ7{)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~üÐ<ÿþ7|aRiksen, M. Ketner-Oostra, R. van Turnhout, C. Nijssen, M. Goossens, D. Jungerius, P. D. Spaan, W.2006‘Will 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 vegetatio