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Dataset results
277 results for “regional scale”
Data from: Soil fungal communities of grasslands are environmentally structured at a regional scale in the Alps
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Data from: Small beetle, large-scale drivers: how regional and landscape factors affect outbreaks of the European spruce bark beetle
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Data from: Decrease in diversity and changes in community composition of arbuscular mycorrhizal fungi in roots of apple trees with increasing orchard management intensity across a regional scale
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Data from: Regional climate and local-scale biotic acceptance explain native-exotic diversity relationships in Australian annual plant communities
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Data from: Local and regional scale habitat heterogeneity contribute to genetic adaptation in a commercially important marine mollusc (Haliotis rubra) from southeastern Australia
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Data from: Multi-scale model of regional population decline in little brown bats due to white-nose syndrome
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Data from: Phenotype-environment mismatch in metapopulations - implications for the maintenance of maladaptation at the regional scale
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Data from: Variation in the ecstatic display call of the Gentoo Penguin (Pygoscelis papua) across regional geographic scales
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Tree growth response to drought partially explains regional-scale growth and mortality patterns in Iberian forests
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Data from: Species richness-productivity relationships of tropical terrestrial ferns at regional and local scales
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Data from: Tree diversity across multiple scales and environmental heterogeneity promote ecosystem multifunctionality in a large temperate forest region
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Simulation data used for publication "Dilatory and downward development of 3-meter scale irregularities in the Funnel-like region of Equatorial Plasma Bubble" by Tulasi Ram et al.
<p>The dataset includes two-dimensional simulation output used in the paper.</p> <p>"altitude_eq.dat" and "zonal.dat" contains grid information.</p> <p>"read_n_2D_0.5mV.pro" and "read_n_2D_2mV.pro" are IDL files to read the dataset, with detailed description of each data.</p> <p>The original three-dimensional simulation output is too large to publish at the repository. Author (TY) is willing to share the original data.</p>
Patch-level facilitation fosters high-Andean plant diversity at regional scales
<p>Survey of the alpine vegetation in seven mountains of the Patagonian Andes from January to March of 2017 and 2018. On each mountain, we established one study site at each of three elevations (1600, 1800 and 2000 m). Accordingly, we sampled a total of 21 alpine plant communities (i.e., seven mountains x three elevations) dominated by cushion plants. At each community, 50 individual cushion plants were haphazardly selected within an area of approx. 0.5 ha, pairing each cushion with an adjacent non-cushion or open area 50 cm away in a random direction. In order to sample a similar surface in the surrounding open area, a wire hoop was shaped to match the size of the sampled cushion that was then placed on the ground. The number and identity of all plant species were recorded at both cushion and open area plots. Given that cushion plants are roughly elliptical, microsites were defined as elliptical plots, and thus, the longer and shorter axes of each cushion were measured as an approximate estimation of its area. In total, we sampled 2100 plots (1050 cushion plants and 1050 open area plots).</p>
Data from: Habitat loss and thermal tolerances influence the sensitivity of resident bird populations to winter weather at regional scales
<p>1. Climate change and habitat loss pose the greatest contemporary threats to biodiversity, but their impacts on populations largely vary across species. These differential responses could be caused by complex interactions between landscape and climate change and species-specific sensitivities.</p> <p>2. Understanding the factors that determine which species are most vulnerable to the synergistic effects of climate change and habitat loss is a high conservation priority. Here, we ask (a) whether and to what extent land cover moderates the impacts of winter weather on population dynamics of wintering birds, and (b) what role species' physiology might play in modifying their responses to changing weather conditions.</p> <p>3. To address these questions, we used thousands of observations collected by citizen scientists participating in Project FeederWatch to build dynamic occupancy models for 14 species of wintering birds.</p> <p>4. Populations of wintering birds were more dynamic, having higher rates of local extinction and colonization, in more forested landscapes during extreme cold – presumably enabling them to better track resources. However, urban areas appeared to provide refuge for some species, as demonstrated by increased local colonization during the harshest winter weather. Lastly, we found that species-specific differences in thermal tolerances strongly influenced occupancy dynamics such that species that are less cold-tolerant were more likely to go locally extinct at colder sites and during colder periods throughout winter.</p> <p>5. Together, our results suggest species that are less cold-tolerant and populations occupying less forested landscapes are most vulnerable to extreme winter weather. 11-Jun-2020</p>
Codes and datasets associated with the paper "Day-ahead Wind Power Predictions at Regional Scales: Post-processing Operational Weather Forecasts with a Hybrid Neural Network"
<p>The jupyter notebooks and datasets associated with the EEM20 forecasts are available here. More details will be provided shortly. </p> <p>Please check the EEM20 website (<a href="https://eem20.eu/forecasting-competition/">https://eem20.eu/forecasting-competition/</a>) for the details of the forecasting competition. </p>
Drivers of amphibian population dynamics and asynchrony at local and regional scales
<ol> <li>Identifying the drivers of population fluctuations in spatially distinct populations remains a significant challenge for ecologists. Whereas regional climatic factors may generate population synchrony (i.e., the Moran effect), local factors including the level of density-dependence may reduce the level of synchrony. Although divergences in the scaling of population synchrony and spatial environmental variation have been observed, the regulatory factors that underlie such mismatches are poorly understood.</li> <li>Few previous studies have investigated how density-dependent processes and population-specific responses to weather variation influence spatial synchrony at both local and regional scales. We addressed this issue in a pond-breeding amphibian, the great crested newt (<i>Triturus cristatus</i>). We used capture-recapture data collected through long-term surveys in five <i>T. cristatus</i> populations in Western Europe.</li> <li>In all populations – and subpopulations within metapopulations – population size, annual survival and recruitment fluctuated over time. Likewise, there was considerable variation in these demographic rates between populations and within metapopulations. These fluctuations and variations appear to be context-dependent and more related to site-specific characteristics than local or regional climatic drivers. We found a low level of demographic synchrony at both local and regional levels. Weather has weak and spatially variable effects on survival, recruitment and population growth rate. In contrast, density-dependence was a common phenomenon (at least for population growth) in almost all populations and subpopulations.</li> <li>Our findings support the idea that the Moran effect is low in species where the population dynamics more closely depends on local factors (e.g. population density and habitat characteristics) than on large-scale environmental fluctuation (e.g. regional climatic variation). Such responses may have far-reaching consequences for the long-term viability of spatially structured populations and their ability to response to large-scale climatic anomalies.</li> </ol>
Figure 6 from: Mattsson BJ, Toth W, Penker M, Kieninger P, Vacik H (2020) Drivers and value tradeoffs of regional-scale adaptation in rural landscapes of central Europe. Research Ideas and Outcomes 6: e53608. https://doi.org/10.3897/rio.6.e53608
Figure 6 Gantt chart showing tasks (T), milestones (M), and deliverables (D) as well as involvement of human resources according to the time plan – T, M and D are described in the text.
Figure 4 from: Mattsson BJ, Toth W, Penker M, Kieninger P, Vacik H (2020) Drivers and value tradeoffs of regional-scale adaptation in rural landscapes of central Europe. Research Ideas and Outcomes 6: e53608. https://doi.org/10.3897/rio.6.e53608
Figure 4 Example classifications of tradeoffs from the perspective of regional stewardship programs: Distributed: each ecosystem service category is 20-30% (exclusive); Emphasized: ≥ 1 category is 30-50% (exclusive); Dominant: one categories is >50%.
Figure 2 from: Mattsson BJ, Toth W, Penker M, Kieninger P, Vacik H (2020) Drivers and value tradeoffs of regional-scale adaptation in rural landscapes of central Europe. Research Ideas and Outcomes 6: e53608. https://doi.org/10.3897/rio.6.e53608
Figure 2 Two hypotheses regarding drivers of adaptation, illustrated by simulated effects of individual drivers on an adaptation index (see below Tasks 1.1, 1.2, 3.2 in the Work Plan). Categories of drivers distinguished by symbols: diamond (u) = science; square (■) = culture; circle (●) = climate; triangle (▲) = cross-border; and × = regional program capacity. Whiskers represent 95% Bayesian credibility intervals; open symbols illustrate significant positive effects. Cx = communication.
Figure 3 from: Mattsson BJ, Toth W, Penker M, Kieninger P, Vacik H (2020) Drivers and value tradeoffs of regional-scale adaptation in rural landscapes of central Europe. Research Ideas and Outcomes 6: e53608. https://doi.org/10.3897/rio.6.e53608
Figure 3 Two hypotheses regarding drivers of adaptation, illustrated by simulated values representing absence (A) or presence (B) of interactions between effects on an adaptation index (see below Tasks 1.1, 1.2, 3.2 in Work Plan). Simulated effects include progress toward adaptation by countries of focal regions and by neighbors of these regions. Categories of progress toward adaptation defined as 'more advanced' (at or above median index value) or 'less advanced' (below median index value). Whiskers represent 95% Bayesian credibility intervals; non-overlapping whiskers illustrate statistically significant contrasts.
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.