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65 results for “Dispersal ability”
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.
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.
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).
Data from: Rapid evolution of dispersal ability makes biological invasions faster and more variable
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Data from: Homogenization of dispersal ability across bird species in response to landscape change
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The different fates of two Asian horseshoe crab species with different dispersal abilities
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Data from: Offspring dispersal ability covaries with nest-site choice
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Data from: Evidence for high dispersal ability and mito-nuclear discordance in the small brown planthopper, Laodelphax striatellus
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Dispersal ability and its consequences for population genetic differentiation and diversification
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Data from: Climate oscillations, glacial refugia, and dispersal ability: factors influencing the genetic structure of the least salmonfly, Pteronarcella badia (Plecoptera), in Western North America
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Data from: Selfing ability and dispersal are positively related, but not affected by range position, across multiple species of southern African Asteraceae
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Data from: Dispersal ability and habitat requirements determine landscape-level genetic patterns in desert aquatic insects
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Data from: Of niche differentiation, dispersal ability and historical legacies: what drives woody community assembly in recent Mediterranean forests?
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Data from: Movement propensity and ability correlate with ecological specialisation in European land snails: comparative analysis of a dispersal syndrome
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Data from: Multi-scale effects of habitat structure and landscape context on a vertebrate with limited dispersal ability (the brown-throated sloth, Bradypus variegatus)
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Data from: Incomplete datasets obscure associations between traits affecting dispersal ability and geographic range size of reef fishes in the Tropical Eastern Pacific
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Data from: Phylogeography of Petrolisthes armatus, an invasive species with low dispersal ability
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Data from: Dispersal propensity, but not flight performance, explains variation in dispersal ability
Enhanced dispersal ability may lead to accelerated range expansion and increased rates of population establishment, thereby affecting population genetic structure and evolutionary potential. Morphological, behavioural and physiological traits that characterize dispersive individuals from residents are poorly understood for many invertebrate systems, especially in non-polymorphic pterygote species. Here we examined phenotypic differences between dispersal-prone and philopatric individuals from repeated mark-release-recapture (MRR) experiments using an invasive agricultural pest, Ceratitis capitata. Comprehensive morphometric assessment and subsequent minimal adequate modelling using an information theoretic approach identified thorax mass : body mass ratio as a key predictor of disperser flies under semi-natural conditions. Performance differences in flight ability were then examined under controlled laboratory conditions to assess whether greater thorax mass : body mass ratio was associated with enhanced flight ability. The larger thorax : body mass ratio was associated with measurable differences in mean flight duration, most predominantly in males, and also by their willingness to disperse, scored as the number and duration of voluntary flights. No other measures of whole-animal flight performance (e.g. mean and peak vertical force, total or maximum flight duration) differed. Variation in voluntary behaviour may result in significant alterations of movement behaviour and realized dispersal in nature. This phenomenon may help explain intraspecific variation in the dispersal ability of insects.
Data from: Elevated temperatures translate into reduced dispersal abilities in a natural population of an aquatic insect
1. Rising global temperatures force many species to shift their distribution ranges. However, whether or not (and how fast) such range shifts occur depends on species' dispersal capacities. In most ecological studies, dispersal-related traits (such as the wing size or wing loading in insects) are treated as fixed, species-specific characteristics, ignoring the important role of phenotypic plasticity during insect development. 2. We tested the hypothesis that dispersal-related traits themselves vary in dependence of ambient environmental conditions (temperature regimes, discharge patterns and biotic interactions during individual development). 3. We collected data over 8 years from a natural population of the crane fly Tipula maxima in central Germany. Using linear mixed-effect models, we analysed how phenotypic traits, phenological characteristics and population densities are affected by environmental conditions during the preceding 3, 6 and 12 months. 4. We found a moderate (5.6%) increase in wing length per 1°C increase of mean annual temperatures during the previous year. At the same time, body weight increased by as much as 17.8% in females and 26.9% in males per 1°C, likely driven by increased habitat productivity, which resulted in a 16.4% (female) and 19.3% (male) increased wing loading. We further found a shorter, more synchronized emergence period (i.e., a narrower time frame for dispersal) with increasing temperatures. 5. Altogether, our results suggest that dispersal abilities of T. maxima were negatively affected by elevated temperatures, and we discuss how similar patterns might affect the persistence of populations of other aquatic insects, especially stenoecious taxa with narrow distribution ranges. Our study calls for integration of information on temperature-induced phenotypic plasticity of dispersal-related traits into models forecasting range shifts in the face of climate change. Furthermore, the patterns reported here are likely to affect metapopulation dynamics of aquatic insects under climate change conditions and may contribute to the ongoing decline of insect biomass and diversity.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.
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.