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425 results for “Forest fragment”

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zenodo32/100

Fig. 3 in Climate-driven variation in dispersal ability predicts responses to forest fragmentation in birds

Fig. 3 | Fragmentationsensitivityincreaseswithdispersallimitationinbird assemblages.a, Variationin fragmentationsensitivity anddispersalability plottedonaconsensusphylogenetictree.Eachbranchrepresentsagenus (n = 441), withdataattipsaveragedacrossfamilies (n = 115) forvisualiZation. Branchcoloursindicatedispersallimitation (leastdispersivespeciesin red); tipcoloursshowtheproportionoffragmentation-sensitivespeciesineach family (expandedanalysis;mostsensitivein yellow).b, Datapoints (coloured bylevelofhistoricaldisturbance) aremeansfor 31 studylandscapes.Foreach assemblage,fragmentationsensitivityisassignedtoforest-corespecies withhighforestdependency (Restrictedanalysis),andmeandispersal limitationisthenHWIaveragedacrossallspecies;nHWIislogarithmically scaled (log(1/HWI)) forvisualiZation.StatisticsarefromageneraliZedlinear modelwithquasi-binomialerrors;purplelineshowsmodelfit (R2 = 0.180); shadedregionshows 95% confidenceintervals.Boxplotsin b showthesame distributionswithmedianvalue,interquartilerangeandwhiskerstoextreme values (outliersaredatapoints>1.5× quartiles).Resultsfortheexpandedsample areshownin ExtendedData Fig. 4.

opennotspecifiedMay 2023View details →
zenodo32/100

Fig. 2 in Climate-driven variation in dispersal ability predicts responses to forest fragmentation in birds

Fig. 2 | Globalpatternsoflandscapedisturbanceanddispersallimitation. a, Thepresenceofnatural oranthropogenichistoricaldisturbancesrecorded ineachgridcell.Naturaldisturbancepressures (bright red) includemajorfires, stormsandglaciation;theseeventshavetypicallypersisted forlongerperiods oftimeandmaycausecompleteremovalofforestbiota.Anthropogenicforest loss (palered) representsmore recentdisturbancethatoftenalterscomposition oflocalassemblageswithoutcompleteeradication.b, VariationinnHWI averagedacross speciesoccurringineachgridcell,rangingfromlow (blue) to high (red) dispersallimitation.Dispersallimitationdataarecalculatedfrom measurementsof 10,562 birdspecies,logarithmicallyscaledforvisualiZation (log(1/HWI)).Yellowdotsshowstudylandscapes (21 from BIOFRAG;10 from additionalsampling).Gridcellsin a and b are 2.5 arcminutes. c,d, Hypothetical relationships:extinctionfilterspredictthatfragmentationsensitivityis negativelyassociatedwithhistoricaldisturbance (c), whiledispersal-related mechanismspredictthatfragmentationsensitivityispositivelyassociated with dispersallimitation (d).

opennotspecifiedMay 2023View details →
zenodo32/100

Fig. 1 in Climate-driven variation in dispersal ability predicts responses to forest fragmentation in birds

Fig. 1 | Hypothesespredictingthedistributionoffragmentation-sensitive species. Thetoppathway (a) illustrateshow ' extinctionfilters' linkedto historicaldisturbances (forexample, fireandanthropogenicforestloss) canbenon-random,removingspeciestraitsassociatedwithsensitivityto disturbanceandretainingmoreresilientsurvivors.Tropicalbirdcommunities thathavelargelyavoidedseverehistoricaldisturbancetheoreticallycontain morespecieswithdisturbance-sensitivetraits (suchaspoordispersaland ecologicalspecialiZation),accentuatingtheimpactsofforestfragmentation (b). Backgroundturnoverofspecies,shownin (b) butpresentinallpathways, israndomwithrespecttodisturbance-sensitivetraits.Adifferentmechanism involvestheevolutionofflightadaptationstocopewithseasonalfluctuations intemperatureandresources (including vegetation,insects,flowersand fruits).In birds, thepredominantadaptationtoseasonalityinvolvesincreased mobility (fromlocaldispersaltolong-distancemigration),sohighly seasonal communitieslackdispersal-limitedspecies,potentiallyincreasingtheir resiliencetoforestfragmentation (c) incomparisonwithclimaticallystable regions (b). Relativespeciesrichnessisshownbythenumberofbirdsilhouettes inthecommunity.

opennotspecifiedMay 2023View details →
zenodo32/100

ExtendedData Fig. 5 in Climate-driven variation in dispersal ability predicts responses to forest fragmentation in birds

ExtendedData Fig. 5 | Driversoffragmentationsensitivitywith Anthropogenicdisturbances.Resultsof Bayesianphylogeneticmixedeffect modelspredictingfragmentationsensitivityfor 1564 birdpopulations (n = 1034 species).Populations wereclassifiedasfragmentationsensitiveif they wereidentifiedas 'Forest-core' by BIOFRAG. Restrictedanalysisassigned fragmentationsensitivityonlyto 'Forestspecialists' (a); Expandedanalysis assignedfragmentationsensitivityto both 'Forestspecialist' and 'Forest associated' species (b; see Methods). Bayesianposteriordistributionisshown abovetheline;effectsiZeestimateswithcredibleintervals (CI) belowtheline (68%: thickerrorbars;95%:thinerrorbars).HigheffectsiZesindicateapositive associationwithfragmentationsensitivity;loweffect siZesindicateanegative association.Finchandhawksilhouettesindicatethatbothmodelswererunon acompletesample.Historicaldisturbanceisabinaryvariable (1/0) calculated usinganthropogenicdisturbance (forestloss) only.

opennotspecifiedMay 2023View details →
zenodo32/100

ExtendedData Fig. 1 in Climate-driven variation in dispersal ability predicts responses to forest fragmentation in birds

ExtendedData Fig. 1 | Correlationbetweendisturbanceandlatitude. Study landscapesexposedtohighlevelsofhistoricaldisturbance (n = 16 landscapes; red) tendtobefoundathigherlatitudesthanlandscapesexposedtolowerlevels ofhistoricaldisturbance (n = 15 landscapes;blue).Disturbancelevelisestimated fromglobalmapsof majorhistoricaldisturbance (forexamplefire,glaciation). Absolutelatitudeisthecentroidlatitudeof allsamplingpointsineachstudy landscape.Boxplotsshowthemedian, interquartilerangeandwhiskers extendingtoextremevalues.Statisticsshowresultsof two-sided Wilcoxon ranksum testindicatingthatdisturbanceandlatitudearecorrelated (without accountingforspatialauto-correlation).

opennotspecifiedMay 2023View details →
zenodo32/100

ExtendedData Fig. 4 in Climate-driven variation in dispersal ability predicts responses to forest fragmentation in birds

ExtendedData Fig. 4 | Correlationbetweenfragmentationsensitivityand dispersallimitationinbirds. Datapoints (colouredbylevelofhistorical disturbance) arecommunitymeanvaluesforavian assemblagesat 31 study landscapesmappedin Fig.1. Foreachassemblage,fragmentationsensitivity isassignedtospecieswith 'Forest-core' habitatpreferenceandeitherahigh or mediumforestdependency (Expandedanalysis).Meandispersallimitationis thenegative (thatisinverse) hand-wingindex (nHWI) averagedacross allspecies intheassemblage;nHWIislogarithmicallyscaled (log(1/HWI)) forvisualiZation. StatisticsarefromageneraliZedlinearmodelwithquasi-binomialerrors;purple lineshowsmodelfit (R2 = 0.270); shadedregionshows 95% confidenceintervals. Adjacentboxplotsshowthesamedistributionwithmedianvalue,interquartile range,andwhiskerstoextremevalues (outliersaredatapoints>1.5x quartiles).

opennotspecifiedMay 2023View details →
zenodo32/100

ExtendedData Fig. 3 in Climate-driven variation in dispersal ability predicts responses to forest fragmentation in birds

ExtendedData Fig. 3 | Correlationbetweenfragmentationsensitivityand latitudeinbirds. Datapoints (colouredbylevelofhistoricaldisturbance) are communitymeanvaluesforavianassemblagesat 31 studylandscapesmapped in Fig.1. Foreachassemblage,fragmentationsensitivityisassignedto (a) Forest-specialistspecieswith 'Forest-core' habitatpreference (Restrictedanalysis),and (b) Forest-associatedspecieswith ' Forest-core' habitatpreference (Expanded analysis).Absolutelatitudeistheabsolutecentroidlatitudeofallsampling pointsineachstudylandscape.StatisticsarefromgeneraliZedlinearmodels withquasi-binomialerrors;purplelineshowsmodelfit (Restrictedanalysis:R2 = 0.2559, Expandedanalysis:R2 = 0.3208); shadedregionshowsthe 95% confidence intervals.

opennotspecifiedMay 2023View details →
zenodo32/100

Fig. 5 in Climate-driven variation in dispersal ability predicts responses to forest fragmentation in birds

Fig. 5 | Predictorsofdispersallimitationinbirds. Resultsshownareoutputs ofphylogeneticgeneraliZedleast-squaresmodelspredictingdispersal limitation (nHWI) acrossallbirdspeciessampled,includinglong-distance migrants (swallowimage,dark bars;n = 1,034), onlyresidentspeciesandshort distance/partialmigrants (thrushimage,medium bars;n = 921) oronlyresident species (pittaimage, palebars;n = 858). Panelspresentthreesetsofmodels withincreasingcomplexity:aunivariatemodelwithsinglepredictor (a,d), and multivariatemodelswithtwo (b,e) andthree (c,f) predictors.Eachpredictoris calculatedatthespecieslevelbyaveragingacrosslandscapeswhere eachspecies ispresent.Disturbance (red) isthelocalbinarydisturbancescore,latitude (yellow) istheabsolutelatitudeof thelandscapecentroids andseasonality (blue) isthestandarddeviationof meanmonthlytemperaturevalues.a–c, Effect-siZeestimateswith 95% confidenceintervals;anegativeeffectindicates reduceddispersallimitation (thatis,increaseddispersalability).R2 and Akaike informationcriterion (AIC) valuesarecalculatedforfullsamplemodelsonly. d–f, Proportionof independentvariationexplainedbyeachmodelcovariate, calculatedusinghierarchicalpartitioning.

opennotspecifiedMay 2023View details →
zenodo32/100

Fig. 4 in Climate-driven variation in dispersal ability predicts responses to forest fragmentation in birds

Fig. 4 | Dispersallimitation (nHWI) explainsvariationinfragmentation sensitivity.Resultsof Bayesianphylogeneticmixed-effect modelspredicting fragmentationsensitivityforall 1,564 birdpopulations (n = 1,034 species). Populationswereclassifiedasfragmentationsensitiveiftheywereidentifiedas 'Forest-core' by BIOFRAG. Restrictedanalysisassignedfragmentationsensitivity onlyto 'Forestspecialists' (a); Expandedanalysisassignedfragmentation sensitivitytoboth ' Forestspecialist' and ' Forestassociated' species (b; see Methods).Bayesianposteriordistributionisshownabovetheline;effect-siZe estimateswithcredibleintervals (CI) arebelowtheline (thickerrorbars,68%; thinerrorbars,95%).HigheffectsiZesindicateapositiveassociationwith fragmentationsensitivity;loweffectsiZesindicateanegativeassociation. Historicaldisturbanceisabinaryvariable (1/0) calculatedusingalldisturbance layers (forestloss,glaciation,stormsandfires).

opennotspecifiedMay 2023View details →
dryad32/100

The joint effects of forest habitat area and fragmentation on Dung beetles

<p>Habitat loss and habitat fragmentation usually occur together, at the same time and place.  However, while there is consensus that habitat loss is the preeminent threat to biodiversity, the effects of fragmentation are contentious.  Some argue that habitat fragmentation is not bad for biodiversity, and even that it is good.  Generally, the studies that find no harm or positive outcomes of fragmentation invariably assume that it is independent of habitat loss.  However, dissociating the effects of habitat fragmentation from habitat loss is questionable because the two are essentially coupled.  Accordingly, we evaluated how forest area and fragmentation (via edge effects) influenced dung beetles<em> per se</em>, and through their effects on the abundance of mammals, using structural equation modeling (SEM).  Dung beetles are very sensitive to forest habitat loss and fragmentation, and to changes in the abundance of mammals on which they depend for dung.  Our study area was in the Tana River, Kenya, where forest fragments are depauperated of mammals except for two endemic species of monkeys.  We mapped 12 forests, counted the resident monkeys, and sampled 113,955 beetles from 288 plots.  Most of the 87 species of beetles found were small tunnellers.  After implementing a fully latent Structural Regression SEM, the optimal model explained a significant 26% of the variance in abundance, and 89% of diversity.  The main drivers of beetle abundance were positive, direct, effects of forest area and number of monkeys, and negative edge effects.  The main drivers of diversity were the direct effects of the beetle abundance, indirect effects of forest area and abundance of mammals, and indirect negative edge effects.  Thus forest area, fragmentation (via edge effects), and the number of monkeys jointly influenced the abundance and diversity of the beetles directly and indirectly.</p>

opencc-zeroAug 2023View details →
dryad32/100

Data from: Edge effects and beta diversity in ground and canopy beetle communities of fragmented subtropical forest

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publicFeb 2019View details →
dryad32/100

Data from: The effect of habitat fragmentation on the genetic structure of a top predator: loss of diversity and high differentiation among remnant populations of Atlantic Forest jaguars (Panthera onca)

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publicAug 2010View details →
dryad32/100

Data from: Trait-associated loss of frugivores in fragmented forest does not affect seed removal rates

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publicSep 2017View details →
dryad32/100

Data from: Deforestation and forest fragmentation in South Ecuador since the 1970s - losing a hotspot of biodiversity

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publicJul 2016View details →
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Data from: Corridors restore animal-mediated pollination in fragmented tropical forest landscapes

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publicJan 2016View details →
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Data from: Does long distance pollen dispersal preclude inbreeding in tropical trees? Fragmentation genetics of Dysoxylum malabaricum in an agro-forest landscape

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publicSep 2012View details →
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Data from: Small montane cloud forest fragments are important for conserving tree diversity in the Ecuadorian Andes

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publicJan 2018View details →
dryad32/100

Data from: Forest fragments modulate the provision of multiple ecosystem services

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publicFeb 2015View details →
dryad32/100

Data from: History of the fragmentation of the African rain forest in the Dahomey Gap: insight from the demographic history of Terminalia superba

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publicDec 2017View details →
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Data from: Brewing trouble: coffee invasion in relation to edges and forest structure in tropical rainforest fragments of the Western Ghats, India

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publicOct 2014View details →

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International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

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Last verified 2026-04-29Open record