Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
425
datasets available to search
ShareScore release 0.9.0
Dataset results
425 results for “Forest fragment”
Figure 3 in Nest-site microhabitat association of red-billed leiothrix in subtropical fragmented forest in central China: evidence for a reverse edge effect on nest predation risk?
Figure 3. Nonmetric multidimensional scaling (NMS) ordination of 237 sample units of microhabitat characteristics in the forest, and the joint plot of NMS scores with important microhabitat variables (r2> 0.2). The first and third axes represent 30% and 46% of the total variation, respectively.
Figure 4 in Nest-site microhabitat association of red-billed leiothrix in subtropical fragmented forest in central China: evidence for a reverse edge effect on nest predation risk?
Figure 4. Nonmetric multidimensional scaling (NMS) ordination of 134 sample units of microhabitat characteristics in the scrub-grassland, and the joint plot of NMS scores with important microhabitat variables (r2> 0.2). The first and second axes represent 78% and 15% of the total variation, respectively.
Figure 1 in Nest-site microhabitat association of red-billed leiothrix in subtropical fragmented forest in central China: evidence for a reverse edge effect on nest predation risk?
Figure 1. Study areas and vegetation types for nest-site selection of the red-billed leiothrix in Daweishan Nature Reserve (DSNR; 28°20′54″–28°28′47″N, 114°01′51″–114°12′52″E), Hunan Province, China.
Figure 4 in The social wasps (Hymenoptera: Vespidae: Polistinae) of a fragment of Atlantic Forest in southern Bahia, Brazil
Figure 4. (A, B) Accumulation and rarefaction curves for the wasps collected employing the three methodologies.
Figure 6 in The social wasps (Hymenoptera: Vespidae: Polistinae) of a fragment of Atlantic Forest in southern Bahia, Brazil
Figure 6. (A, B) Accumulation and rarefaction curves for the wasps collected in the three fragments.
Figure 2 in Orchid bees (Hymenoptera, Apidae, Euglossini) are seasonal in Seasonal Semideciduous Forest fragments, southern Brazil
Figure 2. Orchid bee phenology in Seasonal Semideciduous Forest fragments, Euglossa fimbriata.
Fig. 2 in Seasonal Activity of Carabidae (Coleoptera) in Forest Fragments and Crops in São Paulo, Brazil
Fig. 2. Seasonal activity of dominant species of Carabidae in three areas of São Paulo, Brazil. NTS = no-tillage system, CTS = conventional tillage system. Solid line = soybean/corn crops; dashed line = forest fragment.
Fig. 1 in Seasonal Activity of Carabidae (Coleoptera) in Forest Fragments and Crops in São Paulo, Brazil
Fig. 1. Seasonal activity of dominant species of Carabidae in three areas of São Paulo, Brazil. NTS = no-tillage system, CTS = conventional tillage system. Solid line = soybean/corn crops; dashed line = forest fragment.
FIGURE 3 in An updated checklist of bryophytes for the state of Paraíba, a Brazilian hotspot: new records and biological spectrum in a Seasonally Dry Tropical Forest fragment
FIGURE 3. Representation of life forms in terms of bryophyte species richness in thee studied seasonally dry tropical forest fragment in the Northeast Region of Brazil.
FIGURE 2 in An updated checklist of bryophytes for the state of Paraíba, a Brazilian hotspot: new records and biological spectrum in a Seasonally Dry Tropical Forest fragment
FIGURE 2. Results for the Weighted Pair-Group Method with Arithmetic mean (WPGMA) based on the Sørensen similarity index for all species at sites listed by Germano et al. (2016) and the studied seasonally dry tropical forest fragment (SDTF). Cophenetic Correlation Coefficient (CCC) = 0.83. The areas are named following Germano et al. (2016) with P = point/sampled area.
Population structure and genetic variation of fragmented mountain birch forests in Iceland
<p>Data avilability for the manuscript JOH-2022-096.R2 accepted for application</p>
Fig. 2 in Variation in diet of frugivorous bats in fragments of Brazil's Atlantic Forest associated with vegetation density
Fig. 2.—Carbon and nitrogen isotopic ratios for each bat population presented as mean and standard deviation. Each panel represents one species–season pairing: Al-H is Artibeus lituratus in the Humid season; Cp-H is Carollia perspicillata in the Humid season; Cp-S is C. perspicillata in the super-humid season; Sl-S is Sturnira lilium in the super-humid season. Fragments and population designations correspond to fragments in Brazil's Atlantic Forest in Fig. 1. Shades correspond to fragment where the sample was collected ordered by area. Darker greens are largest fragments; darkest purple are smallest fragments.
Fig. 1 in Variation in diet of frugivorous bats in fragments of Brazil's Atlantic Forest associated with vegetation density
Fig. 1.—Map of study sites situated in Brazil's Atlantic Forest, Rio de Janeiro State, Brazil. Sites in Reserva Ecologica de Guapiacu ("REGUA") and fragments (F) adjacent to this area are indicated as points. Thirteen areas were sampled and allocated as REGUA, REGUA2, REGUA3 for those sampled in the reserve (considered repeated efforts sampling in the same fragment), and 10 fragments designated as F1 through F10. This figure was constructed using ESRI base maps and existing maps available through Instituto Brasileiro de Geografia (IBGE) (SOS Mata Atlântica (2009) (www.sosma.org). Used under commons licence). Figure is adapted from Teixeira (2019).
Figure 1 in Natural regeneration in Atlantic Forest Fragments: using ants (Hymenoptera: Formicidae) for monitoring a conservation unit
Figure 1. Botujuru Private Natural Heritage Preserve location and the respective collecting sites.
FIGURE 1 in Earthworm communities in long-term no-tillage systems and secondary forest fragments in Paraná, Southern Brazil
FIGURE 1. Location of the municipalities of the sampling sites in Paraná, Brazil. Light grey = Faxinal (FX), Black = Mauá da Serra (MS), Dark grey = Palmeira (PL)
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.
ScienceDex guides
Understand access before you commit
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.