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110 results for “Bird dispersal”
Seed dispersal by the cosmopolitan house sparrow widen the spectrum of unexpected endozoochory by granivore birds
<p>Presence of seeds from different plant species found in the droppings of the house sparrow (<em>Passer domesticus</em>) and their viability determined by the tetrazolium test.</p>
Changing bird migration patterns have potential to enhance dispersal of alien plants from urban centres
<p>In this version I have uploaded the revised code and a list of plant species following reviewer comments in the revision process for the MS.</p>
Fig. 3 in Seed dispersal effectiveness: A comparison of four bird species feeding on seeds of invasive Acacia cyclops in South Africa
Fig. 3. Geographic distribution (i.e. green colour) of the studied bird species in Southern Africa, namely, the frugivorous (a) Knysna turaco Tauraco corythaix, and (b) the red-winged starling Onychognathus morio, (c) the granivorous red-eyed dove Streptopelia semitorquata, and (d) the laughing dove S.senegalensis (SABAP 2 http://www.adu.org.za/ accessed 23 June 2015).
Fig. 2 in Seed dispersal effectiveness: A comparison of four bird species feeding on seeds of invasive Acacia cyclops in South Africa
Fig. 2. Seed dispersal effectiveness (i.e. a product of germination rates (quality) and average adult body mass as proxy for seed load (quantity) for different bird species that ingested seeds of Acacia cyclops: the frugivorous Knysna turaco Tauraco corythaix, and the red-winged starling Onychognathus morio, the granivorous red-eyed dove Streptopelia semitorquata, and the laughing dove S. senegalensis. Different letters above the bars show statistically significant difference. Error bars show standard error of mean.
Fig. 1 in Seed dispersal effectiveness: A comparison of four bird species feeding on seeds of invasive Acacia cyclops in South Africa
Fig. 1. Seed dispersal quality (i.e. mean germination rates % ± SE) for untreated (experimental control) and gut-passed Acacia cyclops seeds through different bird species:the frugivorous Knysna turaco Tauraco corythaix, and the red-winged starling Onychognathus morio, the granivorous red-eyed dove Streptopelia semitorquata, and the laughing dove S. senegalensis. Different letters above the bars show statistically significant difference. Error bars show standard error of mean.
Data from: Food availability modulates differences in parental effort between dispersing and philopatric birds
Dispersal entails costs and might have to be traded off against other life-history traits. Dispersing and philopatric individuals may thus exhibit alternative life-history strategies. Importantly, these differences could also partly be modulated by environmental variation. Our previous results in a patchy population of a small passerine, the collared flycatcher, suggest that, as breeding density, a proxy of habitat quality, decreases, dispersing individuals invest less in reproduction but maintain a stable oxidative balance, whereas philopatric individuals maintain a high reproductive investment at the expense of increased oxidative stress. In this study, we aimed at experimentally testing whether these observed differences between dispersing and philopatric individuals across a habitat quality gradient were due to food availability, a major component of habitat quality in this system. We provided additional food for the parents to use during the nestling rearing period and we measured subsequent parental reproductive effort (through provisioning rate, adult body mass, and plasmatic markers of oxidative balance) and reproductive output. Density-dependent differences between dispersing and philopatric parents in body mass and fledging success were observed in control nests but not in supplemented nests. However, density-dependent differences in oxidative state were not altered by the supplementation. Altogether, our results support our hypothesis that food availability is responsible for some of the density-dependent differences observed in our population between dispersing and philopatric individuals but other mechanisms are also at play. Our study further emphasizes the need to account for environmental variation when studying the association between dispersal and other traits.
Data from: Fine-scale genetic structure in a wild bird population: the role of limited dispersal and environmentally-based selection as causal factors
Individuals are typically not randomly distributed in space; consequently ecological and evolutionary theory depends heavily on understanding the spatial structure of populations. The central challenge of landscape genetics is therefore to link spatial heterogeneity of environments to population genetic structure. Here, we employ multivariate spatial analyses to identify environmentally induced genetic structures in a single breeding population of 1174 great tits Parus major genotyped at 4701 single-nucleotide polymorphism (SNP) loci. Despite the small spatial scale of the study relative to natal dispersal we found multiple axes of genetic structure. We built distance-based Moran's eigenvector maps to identify axes of pure spatial variation, which we used for spatial correction of regressions between SNPs and various external traits known to be related to fitness components (avian malaria infection risk, local density of conspecifics, oak tree density and altitude). We found clear evidence of fine-scale genetic structure, with 21, 7 and 9 significant SNPs respectively associated with infection risk by two species of avian malaria (Plasmodium circumflexum and P. relictum) and local conspecific density. Such fine-scale genetic structure relative to dispersal capabilities suggests ecological and evolutionary mechanisms maintain within-population genetic diversity in this population with the potential to drive micro-evolutionary change.
Migration-tracking integrated phylogeography supports long-distance dispersal-driven divergence for a migratory bird species in the Japanese archipelago
<p>Previous phylogeographic studies of migratory bird species have not discriminated long-distance dispersal (LDD) from vicariant speciation in their diversification process. We conducted an integrative phylogeographic approach to test the LDD hypothesis, which predicts that a Japanese migratory bird subspecies diverged from a population in the coastal region of the East China Sea (CRECS) via LDD over the East China Sea (ECS). We used the Brown Shrike as a model species, and we conducted molecular phylogenetics, species distribution models (SDMs) and migration tracking. We assessed whether the LDD hypothesis is applicable to the divergence history of the Japanese subspecies of the Brown Shrike.</p> <p>The datasets include three zipped files, namely DataS1.zip, DataS2.zip, and DataS3.zip. See the READ ME (AOKI_et_al_2021_DATASET_README.txt) for how each of the folder and files contained in them can be used to reproduce our results.</p> <p>DataS1.zip inlcudes an xml file to conduct the BEAST analysis. Molecular data, which include nucleotide sequences obtained for cytochrome b (cytb), cytochrome oxidase c subunit I (COI), myoglobin intron-2 (MB) and transforming growth factor beta 2 intron-5 (TGFb2), have been all reposited to DDBJ international nucleotide sequence database, and accession numbers have been already given to them. Accession numbers are provided in the appendix attached to the main manuscript.</p> <p>DataS2.zip includes several data that are related to produce occurrence data of the Brown Shrike used in the analysis and an R code to reproduce the SDMs. Explanatory climatic variables are all available at WorldClim v.1.4 (Hijmans et al., 2005), which are processed in the R code.</p> <p>DataS3.zip includes migratory route analyses using light-level geolocator data are available as the original light-level data and R codes. Sensitivity analyses were also conducted in these analyses, but their codes and results are seperately provided here.</p>
ExtendedData Fig. 9 in Climate-driven variation in dispersal ability predicts responses to forest fragmentation in birds
ExtendedData Fig. 9 | Correlationbetweenseasonalityanddisturbance. At thelocallandscapelevel (a), seasonalityiscalculatedasthestandarddeviationof meanmonthlytemperaturevaluesthroughouttheyearatthelandscapecentroid (n = 31). Highdisturbancemeans 50% of thestudylandscapeareaoverlaps areasofhighnatural (forexamplestorms,glaciers,fires) orAnthropogenic (for exampleforestloss).Boxplotsshowmedian,interquartile range,andwhiskers toextremevalues (outliersaredatapoints>1.5x quartiles).Statisticsarefrom atwo-sided Wilcoxon test.Atthespecieslevel (b), communitymeanvalues (n = 31), arecalculatedusingspecies' distributionalseasonalityanddisturbance scores.Disturbanceiscalculatedastheproportionof thespeciesbreedingrange whichoverlapsareasofhighnatural (forexamplestorms,glaciers,fires) or anthropogenic (forexampleforestloss) disturbance.Seasonalityiscalculated asthestandarddeviationof meanmonthlytemperaturevaluesthroughoutthe year,averagedacrossallgridcellsinthespecies' breedingrange.Statisticsare fromalinearregressionwith Gaussianerrors;purplelineshowsmodelfit;shaded areais 95% confidenceintervals.
ExtendedData Fig. 8 in Climate-driven variation in dispersal ability predicts responses to forest fragmentation in birds
ExtendedData Fig. 8 | Relationshipbetweendispersallimitation (nHWI) anddiet. Datashownfor (a) 276 birdspeciessampledacross 18 temperate studylandscapes,and (b) 817 birdspeciessampledacross 13 tropicalstudy landscapes.Dietaryclasseswith <5 specieswereremovedfromtheanalysis.Diet classificationsarefrom Tobiasand Pigot110. F-statisticand P-valuearecalculated withatwo-way ANOVA.Boxplotsshowmedian,interquartile range,andwhiskers toextremevalues (outliersaredatapoints>1.5x quartiles).
ExtendedData Fig. 7 in Climate-driven variation in dispersal ability predicts responses to forest fragmentation in birds
ExtendedData Fig. 7 | Predictorsofdispersallimitationinbirds. Results shownareoutputsof phylogeneticleastsquaresmodelpredictingdispersal limitation (nHWI) acrossallbirdspeciessampled,includinglong-distance migrants (swallowimage,dark bars;n = 1034); onlyresidentspeciesandshort distance/partialmigrants (thrushimage,medium bars;n = 921); orresident speciesonly (pittaimage,palebars;n = 858). Panelspresentthreesetsofmodels withincreasingcomplexity:aunivariatemodelwithsinglepredictor (a,d), and multivariatemodelswithtwo (b,e) andthree (c,f) predictors.Eachpredictor iscalculatedatthespecieslevelbyaveragingacross landscapeswhereeach speciesispresent.Disturbance (red) iscalculatedastheproportionofspecies breedingrangewhichoverlapsareasofhigh natural (e.g. storms,glaciers,fires) oranthropogenic (e.g. forestloss) disturbance.Absolutelatitude (yellow) is calculatedasthecentroidlatitudeof thespeciesbreedingrange.Seasonality (blue) iscalculatedasthestandarddeviationof meanmonthlytemperature valuesthroughouttheyear,averagedacrossallgridcellsinthebreedingrange. a–c, EffectsiZeestimatesaregivenwith 95% confidenceintervals;anegative effectindicatesreduceddispersallimitation (thatisincreased dispersalability). R2 and AICvaluesarecalculatedforfullsamplemodelsonly.d–f, Proportion of independentvariationexplainedbyeachmodelcovariate,calculatedusing hierarchicalpartitioning.
ExtendedData Fig. 6 in Climate-driven variation in dispersal ability predicts responses to forest fragmentation in birds
ExtendedData Fig. 6 | Driversoffragmentationsensitivitywithnatural disturbances. Resultsof Bayesianphylogeneticmixedeffectmodelspredicting fragmentationsensitivityfor 1564 birdpopulations (n = 1034 species). Populationswereclassifiedasfragmentationsensitiveiftheywereidentifiedas 'Forest-core' by BIOFRAG. Restrictedanalysisassignedfragmentationsensitivity onlyto 'Forestspecialists' (a); Expandedanalysisassignedfragmentation sensitivitytoboth ' Forestspecialist' and ' Forestassociated' species (b; see Methods).Bayesianposteriordistributionisshownabovetheline;effectsiZe estimateswithcredibleintervals (CI) belowtheline (68%: thickerrorbars; 95%: thinerrorbars).HigheffectsiZesindicateapositiveassociationwith fragmentationsensitivity;loweffectsiZesindicateanegativeassociation. Finchandhawksilhouettesindicatethatbothmodelswererunonacomplete sample. Historicaldisturbanceisabinaryvariable (1/0) calculatedusingnatural disturbance (forexamplefires,storms & glaciation) layersonly.
ExtendedData Fig. 2 in Climate-driven variation in dispersal ability predicts responses to forest fragmentation in birds
ExtendedData Fig. 2 | Thelatitudinalgradientinaveragedispersallimitation ofbirdassemblages.Datapoints (colouredbylevelofhistoricaldisturbance) showthecommunitymeanvaluesforavianassemblagessampledat 31 study landscapesmappedin Fig.1. Theoverallgradientisnotexplainedbylandscape disturbancehistory.Absolutelatitudeisthecentroidlatitudeofallsampling pointsineachstudylandscape.Mean dispersallimitationisthenegative (thatis inverse) hand-wingindex (nHWI) averagedacrossallspeciesintheassemblage; nHWIislogarithmicallyscaled (log(1/HWI)) forvisualiZation.Statisticsarefroma linearmodelwith Gaussianerrors;purplelineshowsmodelfit (R2 = 0.44); shaded regionshowsthestandarderrorof theregressioncoefficient.
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.
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).
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.
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.
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).
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).
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.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.