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162 results for “continental scale”
Data from: the great tit HapMap project: a continental-scale analysis of genomic variation in a songbird
<p>A major aim of evolutionary biology is to understand why patterns of genomic diversity vary within taxa and space. Large-scale genomic studies of widespread species are useful for studying how environment and demography shape patterns of genomic divergence. Here, we describe one of the most geographically comprehensive surveys of genomic variation in a wild vertebrate to date; the great tit (<em>Parus major</em>) HapMap project. We screened <em>ca</em> 500,000 SNP markers across 647 individuals from 29 populations, spanning ~30 degrees of latitude and 40 degrees of longitude - almost the entire geographic range of the European subspecies. Genome-wide variation was consistent with a recent colonisation across Europe from a South-East European refugiam, with bottlenecks and reduced genetic diversity in island populations. Differentiation across the genome was highly heterogeneous, with clear "islands of differentiation", even among populations with very low levels of genome-wide differentiation. Low local recombination rates were a strong predictor of high local genomic differentiation (F<sub>ST</sub>), especially in island and peripheral mainland populations, suggesting that the interplay between genetic drift and recombination causes highly heterogeneous differentiation landscapes. We also detected genomic outlier regions that were confined to one or more peripheral great tit populations, probably as a result of recent directional selection at the species' range edges. Haplotype-based measures of selection were related to recombination rate, albeit less strongly, and highlighted population-specific sweeps that likely resulted from positive selection. Our study highlights how comprehensive screens of genomic variation in wild organisms can provide unique insights into spatio-temporal evolutionary dynamics.</p>
Termite trait data from: Continental-scale shifts in termite diversity and nesting and feeding strategies
<p>Typically, termites are treated as a single guild, which ignores important internal diversity, including diverse feeding and nesting traits. These termite traits are crucial for both ecosystem-level fluxes and trophic webs, with implications for vertebrate species. Despite their ecological importance, the large-scale distribution of termite feeding and nesting traits and the relationship with termite diversity is largely unknown. We investigated whether functional diversity, species richness, and feeding (wood, litter, grass, dung) and nesting trait (aboveground mound, belowground nest, inside tree or outside tree nest) distributions of termites were climatically control. To address this gap, we assembled a continental-scale database of termite traits and occurrence in Australia and modelled termite nesting and feeding traits in response to macroclimate. Functional richness and evenness increased primarily with temperature. Australia showed multiple hotspots of termite diversity with each hotspot showing a distinct guild composition. The large-scale distribution of nesting traits showed that aboveground nesting species were the most common nesting guild in the dry and wet tropics while belowground nesting dominated in seasonally cold arid environments, demonstrating a strong climatic control on nesting strategy. Given their large biomass and many interactions with other species, the macro-ecology of termite traits may be especially important in predicting shifts in other species' distributions at continental and global scales.</p>
Modeled data related to the article "Diffusive Wave Models for Operational Forecasting of Channel Routing at Continental Scale"
<p>The data holder contains modeled data on water level and discharge from some test cases.</p>
Continental-scale associations of Arabidopsis thaliana phyllosphere members with host genotype and drought
<p><strong><span>Plants are colonized by distinct pathogenic and commensal microbiomes across different regions of the globe, but the factors driving their geographic variation are largely unknown. Using 16S rDNA and shotgun sequencing, we characterized the associations of the <em>Arabidopsis thaliana</em> leaf microbiome with host genetics and climate variables from 267 populations in the species’ native range across Europe. Comparing the distribution of the 575 major bacterial amplicon variants (phylotypes), we discovered that microbiome composition in <em>A. thaliana</em> segregates along a latitudinal gradient. The latitudinal clines in microbiome composition are predicted by metrics of drought, but also by the spatial genetics of the host. To validate the relative effects of drought and host genotype we conducted a common garden field study, finding 10% of the core bacteria to be affected directly by drought, and 20% to be affected by host genetic associations with drought. These data provide a valuable resource for the plant microbiome field, with the identified associations suggesting that drought can directly and indirectly shape genetic variation in A. thaliana via the leaf microbiome.</span></strong></p>
Convergent genomic signatures of local adaptation across a continental-scale environmental gradient
<p><span>Convergent local adaptation offers a glimpse into the role of constraint and stochasticity in adaptive evolution, in particular the extent to which similar genetic mechanisms drive adaptation to common selective forces. Here, we investigated the genomics of local adaptation in two non-sister woodpeckers that are co-distributed across an entire continent and exhibit remarkably convergent patterns of geographic variation. We sequenced the genomes of 140 individuals of Downy (<em>Dryobates</em> <em>pubescens</em>) and Hairy (<em>D</em>. <em>villosus</em>) woodpeckers and employed a suite of genomic approaches to identify loci under selection. We showed evidence that convergent genes have been targeted by selection in response to shared environmental pressures, such as temperature and precipitation. Among candidates, we found multiple genes putatively linked to key phenotypic adaptations to climate, including differences in body size (e.g., <em>IGFPB</em>) and plumage (e.g., <em>MREG</em>). These results are consistent with genetic constraints limiting the pathways of adaptation to broad climatic gradients, even after genetic backgrounds diverge.</span></p>
Preferential information extraction from space-based passive microwave measurements enables accurate characterization of snow depth variability at continental scales
<p>This is a repository contains </p> <p>1)training data (x_data, y_data, snow_max) </p> <p>2) Developed Deep Learning model (snow_model.py)</p> <p>3) Training weights (*.hdf files)</p> <p>for publication " Preferential information extraction from space-based passive microwave measurements enables accurate characterization of snow depth variability at continental scales"</p> <p> </p>
Integrating animal tracking datasets at a continental scale for mapping wildlife habitat
<div><em>Aim:</em></div> <div> </div> <div>The increasing availability of animal tracking datasets collected across many sites provides new opportunities to move beyond local assessments to enable detailed and consistent habitat mapping at biogeographic scales. However, integrating wildlife datasets across large areas and study sites is challenging, as species' varying responses to different environmental contexts must be reconciled. Here, we compare approaches for large-area habitat mapping and assess available habitat for a recolonizing large carnivore, the Eurasian lynx (Lynx lynx).</div> <div> </div> <div> <em>Location: </em>Europe</div> <div> </div> <div><em>Methods:</em></div> <div> </div> <div>We use a continental-scale animal tracking database (450 individuals from 14 study sites) to systematically assess modeling approaches, comparing (1) global strategies that pool all data for training vs. building local, site-specific models and combining them, (2) different approaches for incorporating regional variation in habitat selection, and (3) different modeling algorithms, testing nonlinear mixed effects models as well as machine-learning algorithms.</div> <div> </div> <div><em>Results:</em></div> <div> </div> <div>Both global and local modeling strategies allowed building transferable habitat models with overall similar predictive performance. Model performance was the highest using flexible machine-learning algorithms and when incorporating variation in habitat selection as a function of environmental variation. Our best-performing model used a weighted combination of local, site-specific habitat models. Our habitat maps identified large areas of suitable, but currently unoccupied lynx habitat, with many of the most suitable unoccupied areas located in regions that could foster connectivity between currently isolated populations.</div> <div> </div> <div><em>Main conclusions:</em></div> <div> </div> <div>We demonstrate that global and local modeling strategies can achieve robust habitat models at the continental scale and that considering regional variation in habitat selection improves broad-scale habitat mapping. More generally, we highlight the promise of large wildlife tracking databases for large-area habitat mapping. Our maps provide the first high-resolution, yet continental assessment of lynx habitat across Europe, providing a consistent basis for conservation planning for restoring the species within its former range.</div>
Termite trait data from: Continental-scale shifts in termite diversity and nesting and feeding strategies
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Convergent genomic signatures of local adaptation across a continental-scale environmental gradient
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Climate more important than soils for predicting forest biomass at the continental scale
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Data from: Evidence of intraspecific adaptive variation in the American pika (Ochotona princeps) on a continental scale using a target enrichment and mitochondrial genome skimming approach
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Data from: The role of diversification in the continental scale community assembly of the American oaks (Quercus)
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Data from: the great tit HapMap project: a continental-scale analysis of genomic variation in a songbird
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Continental-scale shift in foraging habitat use by a highly nomadic species following Australia’s Black Summer megafires
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Data from: Mast seeding patterns are asynchronous at a continental scale
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Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat
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Continental-scale genomic analysis suggests shared post-admixture adaptation in the Americas - Z scores tables
<p><strong>Zscores20Pop. </strong>20pop dataset Z scores by SNP in the three ancestries (A. Africa B. Europe C. America).</p> <p><strong>Zscores1090Ind.</strong> 1090Ind dataset Z scores by SNP in the three ancestries (A. Africa B. Europe C. America).</p>
Data from: Use of simulation-based statistical models to complement bioclimatic models in predicting continental scale invasion risks
Invasive species represent one of the greatest risks to global biodiversity and economic productivity of agroecosystems. The development of certain novel crops—e.g., herbaceous perennial biomass crops—may create a risk of novel invasions by these crops. Therefore, potential benefits and risks need to be weighed in making decisions about their introduction and subsequent management. Ideally, such a weighing will be based on good estimates of invasion risks in realistic scenarios pertaining to actual landscapes of concern regarding invasion. Most previous large-scale analyses of invasion risk have used species distribution models and their established methods. Unfortunately, these approaches are unable to incorporate local scale biotic and spatial factors that influence invasion risk. Here we present a case study for how such factors can be efficiently incorporated in large-scale analyses of invasion risk, by extending simulation models with statistical modeling tools. By these means, we predict invasion risk at the scale of the entire United States for a major biomass crop, Miscanthus × giganteus. We then combine invasion risk predictions for this method with those from bioclimatic methods, producing a map of aggregated invasion risk that can offer more nuanced predictions of invasion risk than either approach alone. Lastly, we evaluate potential risks for invasive crops that differ in invasiveness traits, to examine how geographic patterns of invasion risk vary among invaders as a result of their particular constellation of traits.
Data from: Where do wintering cormorants come from? Long-term changes in the geographical origin of a migratory bird on a continental scale
1. Populations of migratory birds often mix to a considerable extent in their wintering areas. Knowledge about the composition of wintering populations is highly relevant in relation to management, not least for species, such as the great cormorant Phalacrocorax carbo sinensis, prone to conflicts with human interests. However, few studies have been able to estimate long-term changes in winter population composition. 2. We use 30 years of ringing and recovery data (1983-2013) from all major breeding populations of cormorants in continental Europe (except the Black Sea region) to estimate partitioning probabilities (i.e. the probabilities of moving to specific wintering areas) using a Bayesian capture-mark-recovery model. Combining these results with information on breeding numbers and reproductive output in a population model, we estimate the size and composition of wintering populations in Europe and North Africa. 3. Partitioning probabilities showed some variation over time, but were similar for first-winter and older birds. Cormorants from the western part of the breeding range tended to winter progressively further west over time. This may be a density-dependent response to the recent growth of more easterly breeding populations. 4. All wintering populations grew rapidly over the study period, and their composition showed pronounced changes. All wintering populations were composed of birds from many different breeding populations, but the proportion of cormorants of more easterly origin increased markedly over time in most wintering areas. 5. Policy implications. Cormorant wintering populations in Europe consist of mixtures of birds of different breeding origin, and these mixtures are highly variable over time. This reduces the chances of successfully limiting conflicts in a specific wintering area through e.g. regulation of breeding numbers in one breeding area. The dynamic nature of cormorant winter populations means that conflicts are best addressed when and where the conflict occurs, or on the scale of the entire continental population. It is unlikely that the latter will be cost-effective and politically realistic.09-Jan-2018
Data from: Continental-scale patterns reveal potential for warming-induced shifts in cattle diet
In North America, it has been shown that cattle in warmer, drier grasslands have lower quality diets than those cattle grazing cooler, wetter grasslands, which suggests warming will increase nutritional stress and reduce weight gain. Yet, little is known about how the plant species that comprise cattle diets change across these gradients and whether these shifts in dietary quality coincide with shifts in dietary composition, i.e. the relative abundance of different plant species consumed by cattle. To quantify geographic patterns in dietary composition, we analyzed the dietary composition and dietary quality of unsupplemented cattle from 289 sites across the central US by sequence-based analyses of plant DNA isolated from cattle fecal samples. Overall, assuming that the percentage of reads for a species in a sample corresponds to the percentage of protein derived from the species, only 45% of the protein intake for cattle was derived from grasses. Within the Great Plains, northern cattle relied more on grasses than southern cattle, which derived a greater proportion of their protein from herbaceous and woody eudicots. Eastern cattle were also more likely to consume a unique assemblage of plant species than western cattle. High dietary protein was not strongly tied to consumption of any specific plant species, which suggests that efforts to promote individual plant species may not easily remedy protein deficiencies. A few plant species were consistently associated with lower quality diets. For example, the diets of cattle with high amounts of Elymus or Hesperostipa were more likely to have lower crude protein concentrations than diets with less of these grasses. Overall, our analyses suggest that climatic warming will increase the reliance of cattle on eudicots as protein concentrations of grasses decline. Monitoring cattle diet with this DNA-based sequencing approach can be an effective tool for quantifying cattle diet to better increase animal performance and guide mitigation strategies to changing climates.
ScienceDex guides
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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.