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.
411
datasets available to search
ShareScore release 0.7.1
Dataset results
411 results for “spatial variation”
Figure 1 in Spatial and temporal variations of fish communities in the longitudinal gradient of the Mono River (Benin and Togo: West Africa)
Figure 1. – Study area (A) with sampling sites (B). Black bar, Nangbéto dam; Gray bar, future Adjarala dam; Ac, Atchinédji; Ad, Adjarala; Ak, Akodéseva; Al, Albarkazé; At, Atakè; Co, Codjohoué; Dj, Djonnougui; Ds, Djossouhoué; Ma, Mayoudji; To, Togodo.
Figure 4 in Spatial and temporal variations of fish communities in the longitudinal gradient of the Mono River (Benin and Togo: West Africa)
Figure 4. – Spatial variations (average and standard deviation) in the Shannon-Wiener diversity and Pielou equitability indices. Site order follows the upstream-downstream gradient.
FIGURE 3 in Spatial and temporal variation of the diet of the flag tetra Hyphessobrycon heterorhabdus (Characiformes: Characidae) in streams of the Eastern Amazon
FIGURE 3 | Ordination of the diet of Hyphessobrycon heterorhabdus between hydrological periods in eight streams of a protected area in the Eastern Amazon, Brazil.
FIGURE 1 in Spatial and temporal variation of the diet of the flag tetra Hyphessobrycon heterorhabdus (Characiformes: Characidae) in streams of the Eastern Amazon
FIGURE 1 | Streams sampled during the dry period of 2010 and the flood period of 2011 in the Caxiuanã National Forest, Eastern Amazon, State of Pará, Brazil.
Fig. 2 in Spatial variation of summer microphytoplankton and zooplankton communities related to environmental parameters in the coastal area of Djerba Island (Tunisia, Eastern Mediterranean) Abstract
Fig. 2: Spatial variations of physical-chemical parameters: temperature, salinity, pH, Dissolved Oxygen and/ Depth Transparency along the western and eastern coasts of Djerba Island.
Fig. 4 in Spatial variation of dung beetle assemblages associated with forest structure in remnants of southern Brazilian Atlantic Forest
Fig. 4. Redundancy analysis ordination for dung beetle abundance (a) and biomass (b) constrained by environmental variables. Triplot with explanatory variables, species and samples: sp. 1: Bdelyrus braziliensis; sp. 2: Canthidium aff. trinodosum; sp. 3: Canthon luctuosus; sp. 4: Canthon rutilans cyanescens; sp. 5: Canthonella aff. instriata; sp. 6: Coprophanaeus dardanus; sp. 7: Coprophanaeus saphirinus; sp. 8: Deltochilum brasiliense; sp. 9: Deltochilum furcatum; sp. 10: Deltochilum morbillosum; sp. 11: Deltochilum multicolor; sp. 12: Deltochilum rubripenne; sp. 13: Dichotomius sericeus; sp. 14: Dichotomius quadrinodosus; sp. 15: Dichotomius sp.; sp. 16: Eurysternus cyanescens; sp. 17: Eurysternus parallelus; sp. 18: Paracanthon aff. rosinae; sp. 19: Phanaeus splendidulus; sp. 20: Uroxys sp. 1; sp. 21: Uroxys sp. 2; A: basal area of first tree; B: height of first tree; C: top diameter of first tree; D: distance to first tree; E: basal area of first shrub; F: height of first shrub; G: top diameter of first shrub; H: distance to first shrub; I: land slope; J:altitude; K: leaf litter cover; L:green cover; M: exposed soil; N: height of leaf litter; O: canopy cover; 1–25: ANH sampling points; 26–50: ITA sampling points; 51–75: PER sampling points; 76–100: RAT sampling points.
Fig. 3 in Spatial variation of dung beetle assemblages associated with forest structure in remnants of southern Brazilian Atlantic Forest
Fig. 3. Multivariate Regression Tree (MRT) analysis of the dung beetle abundance (a) and biomass with environmental variables as predictor variables. Environmental variables: A, basal area of trees; I, land slope; J, altitude; N, height of leaf litter; O, canopy cover. Species names are abbreviated and can be found in legend of Fig. 4 and in Appendix C. Bar charts at the terminal leaves of the regression tree represent species abundance means. The order of bars in each bar chart are the same and follows the sequence of names showed at left.
Fig. 1 in Spatial variation of dung beetle assemblages associated with forest structure in remnants of southern Brazilian Atlantic Forest
Fig. 1. Map of the Atlantic Forest remnants where dung beetles were sampled during January and February 2012. Anhatomirim Environmental Protection Area in Governador Celso Ramos city; Permanent Protection Areas of Itapema city; Peri Lagoon Municipal Park in Florianópolis city; Permanent Protection Areas of Ratones in Florianópolis city.
Figure 2 in Temporal variation and spatial distribution of the pest insect Edessa meditabunda in cotton (Gossypium hirsutum) as an alternative host plant
Figure 2. Surface maps constructed based on Inverse Distance Weight (IDW) interpolation showing spatial distribution of nymphs in cotton between 70 (A), 77 (B), 84 (C), 91 (D) days after emergence (DAE) and Sum of all Evaluations (E). Low density is represented in green while red indicates high density of E. meditabunda.
SpatialCVGAE: Spatial Domain Identification via Consensus Clustering Integrated Variational Graph Autoencoder
Open the record for dataset details and reuse information.
Data from: Impact of spatial variation of a crucial prey, the molecricket, on hoopoe territory occupancy and reproduction
Direct benefits accrued from securing a territory of sufficient quality are important determinants of individual fitness and population persistence. Food supply is one of the main factors of animal territory quality, with spatial and temporal variation in prey availability largely dictating reproductive output and thus population dynamics. In a Swiss hoopoe population, molecrickets Gryllotalpa gryllotalpa, the most profitable prey locally, can constitute most of the food biomass delivered to chicks by parents. We first investigated the impact of molecricket prey on hoopoes' fitness-related traits by quantifying the spatial variation in the food allocation pattern of both male and female parents to chicks across the whole population range; and second, analysed the impact of this prey on current reproduction and, using a 11 yr dataset, on the temporal occupancy rate of each territory. We found considerable but spatially repeatable variation, over the years, of molecricket biomass in the diet provisioned to chicks. This spatial heterogeneity in chicks' diet composition was mirrored both in the history of territory occupancy (2002–2012) and in current reproductive success (2012). Territories with a greater biomass of molecrickets in chicks' diet produced more fledglings in better body condition. Yet, these effects on current reproduction were exclusively demonstrated for male parents, corroborating that paternal provisioning patterns play a predominant role in hoopoe reproductive success. This study demonstrates how a single, very profitable prey species might affect spatial variation in territory settlement and individual reproductive success in a regionally endangered bird species, with potential consequences for its population dynamics and persistence.
Data from: Spatial variation in Allee effects influences patterns of range expansion
Allee effects are thought to slow range expansion and contribute to stable range boundaries. Recent studies have shown Allee effects to vary spatiotemporally due to influences of environmental heterogeneity on population processes. Gradients in Allee effects might occur as a species' range approaches suboptimal conditions while expanding into new territory. Allee effects could exhibit patchiness if drivers of positive density dependence (e.g., mate finding rates) are influenced by habitat patchiness. However, theoretical studies have largely assumed Allee effects to be spatially constant. The goal of this study was to evaluate how spatiotemporal patterns of range expansion respond to spatial variations in Allee effects. We simulated spread in landscapes that differed in the spatial configuration and range of Allee thresholds. We compared spread with a constant Allee effect to spread in landscapes where the Allee threshold varied along a gradient or in a patchy fashion. Landscape configuration affected patterns of range expansion when Allee thresholds were near or exceeded the number of colonizing immigrants. In gradient landscapes, spread decelerated as the range edge approached higher Allee thresholds. In patchy landscapes, spread advanced quickly through areas with lower Allee thresholds and stalled in areas with higher Allee thresholds. Both focal and neighboring locations influencing spread. Spatial variation in Allee effects may be an underappreciated source of heterogeneity in patterns of range expansion. When Allee effects vary, spread estimates based on a spatially averaged Allee threshold may not accurately predict realized rates of spread. Our findings suggest that spread can occur despite generally high Allee thresholds if Allee thresholds are low in a subset of patches. This result has negative implications for controlling the spread of invasive species, but it also suggests range shifts by native species in response to climate change may be possible with even sparsely distributed refugia from Allee effects.
Figure 9 from: Hammond HEJ, García-Tejero S, Pohl GR, Langor DW, Spence JR (2021) Spatial and temporal variation of epigaeic beetle assemblages (Coleoptera, Carabidae, Staphylinidae) in aspen-dominated mixedwood forests across north-central Alberta. In: Spence J, Casale A, Assmann T, Liebherr JК, Penev L (Eds) Systematic Zoology and Biodiversity Science: A tribute to Terry Erwin (1940-2020). ZooKeys 1044: 951-991. https://doi.org/10.3897/zookeys.1044.65776
Figure 9 Boxplots of beta-diversity of epigaeic beetle assemblages in aspen-dominated mixedwood forests at the Lac la Biche location, 1992–93 ACarabidae and BStaphylinidae. Beta diversity was calculated within locations, within stands, and within lines for mature and old stands. Significant differences between stand age classes are indicated by asterisks above the boxplots (* p < 0.05, ** p < 0.01, *** p < 0.001)
Figure 8 from: Hammond HEJ, García-Tejero S, Pohl GR, Langor DW, Spence JR (2021) Spatial and temporal variation of epigaeic beetle assemblages (Coleoptera, Carabidae, Staphylinidae) in aspen-dominated mixedwood forests across north-central Alberta. In: Spence J, Casale A, Assmann T, Liebherr JК, Penev L (Eds) Systematic Zoology and Biodiversity Science: A tribute to Terry Erwin (1940-2020). ZooKeys 1044: 951-991. https://doi.org/10.3897/zookeys.1044.65776
Figure 8 Redundancy analysis (RDA) of epigaeic beetle assemblages in aspen-dominated mixedwood forests at the Lac la Biche location, 1992–93 ACarabidaeBStaphylinidae. Each symbol represents the catch from a single pitfall trap pooled over two years.
Figure 7 from: Hammond HEJ, García-Tejero S, Pohl GR, Langor DW, Spence JR (2021) Spatial and temporal variation of epigaeic beetle assemblages (Coleoptera, Carabidae, Staphylinidae) in aspen-dominated mixedwood forests across north-central Alberta. In: Spence J, Casale A, Assmann T, Liebherr JК, Penev L (Eds) Systematic Zoology and Biodiversity Science: A tribute to Terry Erwin (1940-2020). ZooKeys 1044: 951-991. https://doi.org/10.3897/zookeys.1044.65776
Figure 7 Adjusted percentage of variance of assemblage composition in the regional dataset explained at each spatial scale – between locations, between lines in the same location and between traps in the same line ACarabidaeBStaphylinidae.
Figure 6 from: Hammond HEJ, García-Tejero S, Pohl GR, Langor DW, Spence JR (2021) Spatial and temporal variation of epigaeic beetle assemblages (Coleoptera, Carabidae, Staphylinidae) in aspen-dominated mixedwood forests across north-central Alberta. In: Spence J, Casale A, Assmann T, Liebherr JК, Penev L (Eds) Systematic Zoology and Biodiversity Science: A tribute to Terry Erwin (1940-2020). ZooKeys 1044: 951-991. https://doi.org/10.3897/zookeys.1044.65776
Figure 6 Boxplots of epigaeic beetle assemblage beta-diversity within regions, within locations and within lines for Boreal Forest (BF) and Foothills (FH) Natural Regions ACarabidaeBStaphylinidae. Significant differences between Natural Regions are indicated by asterisks above the boxplots (** p < 0.01, *** p < 0.001).
Figure 4 from: Hammond HEJ, García-Tejero S, Pohl GR, Langor DW, Spence JR (2021) Spatial and temporal variation of epigaeic beetle assemblages (Coleoptera, Carabidae, Staphylinidae) in aspen-dominated mixedwood forests across north-central Alberta. In: Spence J, Casale A, Assmann T, Liebherr JК, Penev L (Eds) Systematic Zoology and Biodiversity Science: A tribute to Terry Erwin (1940-2020). ZooKeys 1044: 951-991. https://doi.org/10.3897/zookeys.1044.65776
Figure 4 Principal components analysis of epigaeic beetle assemblages in aspen-dominated mixedwood forests in north-central Alberta, 1992–93 ACarabidaeBStaphylinidae. Each symbol represents the catch from a single pitfall trap averaged over two years. Black symbols represent the Lower Foothills Natural Region; open symbols represent the Central Mixedwood Subregion, light grey symbols represent the Dry Mixedwood Subregion and the dark grey symbols represent the Lower Boreal Highlands Subregion of the Boreal Forest Natural Region. Ellipses represent the standard deviation around the centroid of points in each group and dashed polygons represent the final nodes of the multivariate regression tree (MRT) model. The inset shows the major MRT nodes grouping lines based on assemblage structure.
Figure 5 from: Hammond HEJ, García-Tejero S, Pohl GR, Langor DW, Spence JR (2021) Spatial and temporal variation of epigaeic beetle assemblages (Coleoptera, Carabidae, Staphylinidae) in aspen-dominated mixedwood forests across north-central Alberta. In: Spence J, Casale A, Assmann T, Liebherr JК, Penev L (Eds) Systematic Zoology and Biodiversity Science: A tribute to Terry Erwin (1940-2020). ZooKeys 1044: 951-991. https://doi.org/10.3897/zookeys.1044.65776
Figure 5 Redundancy analysis of epigaeic beetle assemblages in aspen-dominated mixedwood forests in Alberta, 1992–93 ACarabidaeBStaphylinidae. Each symbol represents the catch from a single pitfall trap averaged over two years. Open symbols represent the Foothills Natural Region; the black symbols represent the Central Mixedwood Subregion, grey squares represent the Dry Mixedwood Subregion and the grey diamonds represent the Lower Boreal Highlands Subregion of the Boreal Forest Natural Region. Ellipses represent the standard deviation around the centroid of points in each group.
Supplementary material 1 from: Hammond HEJ, García-Tejero S, Pohl GR, Langor DW, Spence JR (2021) Spatial and temporal variation of epigaeic beetle assemblages (Coleoptera, Carabidae, Staphylinidae) in aspen-dominated mixedwood forests across north-central Alberta. In: Spence J, Casale A, Assmann T, Liebherr JК, Penev L (Eds) Systematic Zoology and Biodiversity Science: A tribute to Terry Erwin (1940-2020). ZooKeys 1044: 951-991. https://doi.org/10.3897/zookeys.1044.65776
Supplementary tables
Figure 3 from: Hammond HEJ, García-Tejero S, Pohl GR, Langor DW, Spence JR (2021) Spatial and temporal variation of epigaeic beetle assemblages (Coleoptera, Carabidae, Staphylinidae) in aspen-dominated mixedwood forests across north-central Alberta. In: Spence J, Casale A, Assmann T, Liebherr JК, Penev L (Eds) Systematic Zoology and Biodiversity Science: A tribute to Terry Erwin (1940-2020). ZooKeys 1044: 951-991. https://doi.org/10.3897/zookeys.1044.65776
Figure 3 Coverage based rarefaction estimates of species richness and diversity of epigaeic beetles at each location in aspen-dominated mixedwood forests of north-central Alberta, 1992–93. Locations are distributed across four Natural Subregions (SR) and two Natural Regions (NR) ACarabidae (97.2% coverage) BStaphylinidae (97.6% coverage). Bars represent species richness (± 95% CI) and points represent the exponential of the Shannon diversity index (± 95% CI). For locations where there was significant interannual variation, the results for species richness are placed at the bottom of each bar, and results for diversity are placed in square brackets [] and are indicated above the point for that location.
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.