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162 results for “continental scale”
Data from: Patterns and correlates of claims for brown bear damage on a continental scale
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Long distance migration is a major factor driving local adaptation at continental scale in a Pacific Salmon
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Data from: Pleistocene and ecological effects on continental-scale genetic differentiation in the bobcat (Lynx rufus)
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Data from: Where do wintering cormorants come from? Long-term changes in the geographical origin of a migratory bird on a continental scale
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Data from: Continental-scale patterns of pathogen prevalence: a case study on the corncrake
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The role of extreme rain events in driving tree growth across a continental-scale climatic range in Australia
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Data from: Demographic and spatiotemporal patterns of avian influenza infection at the continental scale, and in relation to annual life cycle of a migratory host
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Data from: Use of simulation-based statistical models to complement bioclimatic models in predicting continental scale invasion risks
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Data from: Citizen science reveals unexpected continental-scale evolutionary change in a model organism
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Local versus broad scale environmental drivers of continental beta diversity patterns in subterranean spider communities across Europe
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Data from: High gene flow on a continental scale in the polyandrous Kentish Plover Charadrius alexandrinus
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Data from: A continental scale trophic cascade from wolves through coyotes to foxes
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Continental-scale patterns of extracellular enzyme activity in the subsoil: an overlooked reservoir of microbial activity
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Anuran accents: Continental-scale citizen science data reveal spatial and temporal patterns of call variability
<p>Data and code associated with the 2020 publication in Ecology and Evolution (doi:10.1002/ece3.6833).</p>
Climatic and Vegetational Drivers of Insect Beta Diversity at the Continental Scale
<p>Aim</p> <p>We construct a framework for mapping pattern and drivers of insect diversity at the continental scale, and use it to test whether and which environmental gradients drive insect beta diversity.</p> <p>Location</p> <p>Global; North and Central America; Western Europe</p> <p>Time period</p> <p>21st century</p> <p>Major taxa studied</p> <p>Insects</p> <p>Methods</p> <p>An informatics system was developed to integrate terrestrial data on insects with environmental parameters. We mined repositories of data for distribution, climatic data was retrieved (WorldClim), and vegetation parameters inferred from remote sensing analysis (MODIS Vegetation Continuous Fields). Beta diversity between sites was calculated and then modelled with two methods, Mantel test with Multiple Regression and Generalized Dissimilarity Modelling.</p> <p>Results</p> <p>Geographic distance was usually the main driver of insect beta diversity. Independent of geographic distance, bioclimate variables explained more variance in dissimilarity than vegetation variables, although the particular variables found to be significant were more consistent in the latter, particularly, tree cover. Tree cover gradients drove compositional dissimilarity at denser coverages, in both continental case studies. For climate, gradients in temperature parameters were significant in driving beta diversity more so than gradients in precipitation parameters.</p> <p>Main conclusions</p> <p>Although environmental gradients drive insect beta diversity independently of geography, the relative contribution of different climatic and vegetational parameters is not expected to be consistent in different study systems. With further incorporation of additional temporal information and variables, this approach will enable development of a predictive framework for conserving insect biodiversity at the global-scale.</p> <p> </p>
Data from: Patterns of size variation in bees at a continental scale: does Bergmann's rule apply?
Body size latitudinal clines have been widley explained by the Bergmann's rule in homeothermic vertebrates. However, there is no general consensus in poikilotherms organisms in particular in insects that represent the large majority of wildlife. Among them, bees are a highly diverse pollinators group with high economic and ecological value. Nevertheless, no comprehensive studies of species assemblages at a phylogenetically larger scale have been carried out even if they could identify the traits and the ecological conditions that generate different patterns of latitudinal size variation. We aimed to test Bergmann's rule for wild bees by assessing relationships between body size and latitude at continental and community levels. We tested our hypotheses for bees showing different life history traits (i.e. sociality and nesting behaviour). We used 142,008 distribution records of 615 bee species at 50 km x 50 km (CGRS) grids across the West Palearctic. We then applied Generalized Least Squares fitted linear model (GLS) to assess the relationship between latitude and mean body size of bees, taking into account spatial autocorrelation. For all bee species grouped, mean body size increased with higher latitudes, and so followed Bergmann's rule. However, considering bee genera separately, four genera were consistent with Bergmann's rule, while three showed a converse trend, and three showed no significant cline. All life history traits used here (i.e. solitary, social and parasitic behaviour; ground and stem nesting behaviour) displayed a Bergmann's cline. In general there is a main trend for larger bees in colder habitats, which is likely to be related to their thermoregulatory abilities and partial endothermy, even if a "season length effect" (i.e. shorter foraging season) is a potential driver of the converse Bergmann's cline particularly in bumblebees.
FIGURE 4 in Towards identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 2. Checklists and keys to six archaeococcoid families
FIGURE 4. Neomargarodes trabuti Marchal, adult female, developed from Morrison (1928: 79, Fig. 28).
Figure 4 from: Kissling WD, Seijmonsbergen AC, Foppen RPB, Bouten W (2017) eEcoLiDAR, eScience infrastructure for ecological applications of LiDAR point clouds: reconstructing the 3D ecosystem structure for animals at regional to continental scales. Research Ideas and Outcomes 3: e14939. https://doi.org/10.3897/rio.3.e14939
Figure 4 - Time table for the eEcoLiDAR project (assuming a start in March 2017). The work plan covers tasks for the NLeSC engineers, the proposed PhD student, and two associated Postdoc projects.
Figure 3 from: Kissling WD, Seijmonsbergen AC, Foppen RPB, Bouten W (2017) eEcoLiDAR, eScience infrastructure for ecological applications of LiDAR point clouds: reconstructing the 3D ecosystem structure for animals at regional to continental scales. Research Ideas and Outcomes 3: e14939. https://doi.org/10.3897/rio.3.e14939
Figure 3 - Example of identifying trees in a forest from LiDAR data. Illustrated is a small plot of poplar trees in Flevoland, The Netherlands, for which tree crowns and tree tops have been calculated.
Figure 2 from: Kissling WD, Seijmonsbergen AC, Foppen RPB, Bouten W (2017) eEcoLiDAR, eScience infrastructure for ecological applications of LiDAR point clouds: reconstructing the 3D ecosystem structure for animals at regional to continental scales. Research Ideas and Outcomes 3: e14939. https://doi.org/10.3897/rio.3.e14939
Figure 2 - Generic workflow for object-based image analysis (OBIA) of LiDAR point clouds and proposed ecological applications. A workbench (blue) will be developed to handle the data storage, data exploration, and interactive OBIA of the massive LiDAR point clouds. Combined with datasets of bird distributions, climate, and other remote sensing layers (orange), the LiDAR data will be applied to several ecological case studies, e.g. by using species distribution modelling of birds and insect pollinators (green).
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.