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84 results for “Distributional Shift”
Data from: Climate change-driven shifts in C3 and C4 grass distributions and leaf traits could lead to changes in community-level flammability
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Data for: Using distribution models to identify range shifts of four Acroneuria Pictet, 1841 (Plecoptera: Perlidae) species in the Midwest USA
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Data from: Subtle shift in groundfish depth distribution within the impact range of seismic surveying along a continental slope
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Data from: Shifts in mutation bias promote mutators by altering the distribution of fitness effects
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Directional selection shifts trait distributions of planted species in dryland restoration
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Projected shifts in 21st century sardine distribution and catch in the California Current
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Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals
Aim: Our aim involved developing a method to analyze spatiotemporal distributions of Arctic marine mammals (AMMs) using heterogeneous open source data, such as scientific papers and open repositories. Another aim was to quantitatively estimate the effects of environmental covariates on AMMs' distributions and to analyze whether their distributions have shifted along with environmental changes. Location: Arctic shelf area. The Kara Sea. Methods: Our literature search focused on survey data regarding polar bears (Ursus maritimus), Atlantic walruses (Odobenus rosmarus rosmarus) and ringed seals (Phoca hispida). We mapped the data on a grid and built a hierarchical Poisson point process model to analyze species' densities. The heterogeneous data lacked information on survey intensity and we could model only the relative density of each species. We explained relative densities with environmental covariates and random effects reflecting excess spatiotemporal variation and the unknown, varying sampling effort. The relative density of polar bears was explained also by the relative density of seals. Results: The most important covariates explaining AMMs' relative densities were ice concentration and distance to the coast, and regarding polar bears, also the relative density of seals. The results suggest that due to the decrease in the average ice concentration, the relative densities of polar bears and walruses slightly decreased or stayed constant during the 17-yearlong study period, whereas seals shifted their distribution from the Eastern to the Western Kara Sea. Main conclusions: Point process modelling is a robust methodology to estimate distributions from heterogeneous observations, providing spatially explicit information about ecosystems and thus serves advances for conservation efforts in the Arctic. In a simple trophic system, a distribution model of a top predator benefits from utilizing prey species' distributions compared to a solely environmental model. The decreasing ice cover seems to have led to changes in AMMs' distributions in the marginal Arctic region.
Data from: Tests of species-specific models reveal the importance of drought in postglacial range shifts of a Mediterranean-climate tree: insights from integrative distributional, demographic and coalescent modelling and ABC model selection
Past climate change has caused shifts in species distributions and undoubtedly impacted patterns of genetic variation, but the biological processes mediating responses to climate change, and their genetic signatures, are often poorly understood. We test six species-specific biologically informed hypotheses about such processes in canyon live oak (Quercus chrysolepis) from the California Floristic Province. These hypotheses encompass the potential roles of climatic niche, niche multidimensionality, physiological trade-offs in functional traits, and local-scale factors (microsites and local adaptation within ecoregions) in structuring genetic variation. Specifically, we use ecological niche models (ENMs) to construct temporally dynamic landscapes where the processes invoked by each hypothesis are reflected by differences in local habitat suitabilities. These landscapes are used to simulate expected patterns of genetic variation under each model and evaluate the fit of empirical data from 13 microsatellite loci genotyped in 226 individuals from across the species range. Using approximate Bayesian computation (ABC), we obtain very strong support for two statistically indistinguishable models: a trade-off model in which growth rate and drought tolerance drive habitat suitability and genetic structure, and a model based on the climatic niche estimated from a generic ENM, in which the variables found to make the most important contribution to the ENM have strong conceptual links to drought stress. The two most probable models for explaining the patterns of genetic variation thus share a common component, highlighting the potential importance of seasonal drought in driving historical range shifts in a temperate tree from a Mediterranean climate where summer drought is common.
GDL-DS: A Benchmark for Geometric Deep Learning under Distribution Shifts
<p>The following contains the datasets described in the paper: GDL-DS: A Benchmark for Geometric Deep Learning under Distribution Shifts, and the associated code can be found at https://github.com/Graph-COM/GDL_DS.</p>
GDL-DS: A Benchmark for Geometric Deep Learning under Distribution Shifts (Dataset 2)
<p>The following contains the datasets described in the paper: <strong>GDL-DS: A Benchmark for Geometric Deep Learning under Distribution Shifts</strong>, and the associated code can be found at <a href="https://github.com/Graph-COM/GDL_DS">https://github.com/Graph-COM/GDL_DS</a>. </p>
Ecological niche modelling to project past, current and future distributional shift of black ebony tree (Diospyros melanoxylon Roxb.) in India
<p>The present study utilized an ensemble modelling approach to predict the distribution of <em>D. melanoxylon</em> under present, past (Last Glacial Maximum, ~22,000 cal yr BP, Middle Holocene ~6000 cal yr BP) and future climate change scenarios (RCP 2.6 and 8.5 for 2050s and 2070s). The annual mean temperature, mean temperature of the wettest quarter and annual precipitations were the most critical parameters that chiefly influence the distribution of <em>D. melanoxylon</em>. The ensemble model rendered high accuracy with AUC=0.93, TSS=0.74, and Kappa=0.71. Past projections of <em>D. melanoxylon</em> indicated a widespread distribution during the Last Glacial Maximum and Middle Holocene suggesting its adaptability to semi-dry as well as warm and humid climates, respectively. The presence of fossil pollen evidence of <em>D. melanoxylon</em> in the suitable habitats derived through past projections in this study complements the model results and marks occurrences of the species during the Last Glacial Maximum and Middle Holocene. By 2050s and 2070s (RCP 8.5), there would be a decline in the distribution by only 0.4% (13622 km2) and 0.2% (6842 km2) of the extremely habitat suitable, respectively. The main factor leading to reduced habitat suitability is the anticipated rise in temperature and variations in seasonal precipitation patterns. Our findings, help in identifying the parts of the country which would be severely affected by future climate change scenarios and plan conservation strategies for this commercially important species to facilitate its growth in suitable habitats which are likely to sustain under future climatic conditions.</p>
Distribution. Endemic to Fennoscandia, specifically to the Scandinavian Peninsula (Norway and N & W Sweden), N Finland, and Kola Peninsula (NW Russia); S border fluctuates ¢.200 km, shifting S during cyclic peaks. in Cricetidae
Distribution. Endemic to Fennoscandia, specifically to the Scandinavian Peninsula (Norway and N & W Sweden), N Finland, and Kola Peninsula (NW Russia); S border fluctuates ¢.200 km, shifting S during cyclic peaks.
Concurrent shifts in wintering distribution and phenology in migratory swans
<p>Range shifts and phenological change are two processes by which organisms respond to environmental warming. Understanding the mechanisms that drive these changes is key for optimal conservation and management. Here we study both processes in the migratory Bewick's swan (<i>Cygnus columbianus bewickii</i>) using different methods, analysing nearly 50 years of resighting data (1970-2017). In this period the wintering area of the Bewick's swans shifted eastwards ("short-stopping") at a rate of >12.5 km y<sup>-1</sup>, thereby shortening individual migration distance on average by 353 km. Concurrently, the time spent at the wintering grounds has reduced ("short-staying") by ~38 days since 1989. We show that individuals are consistent in their migratory timing in winter, indicating that the frequency of individuals with different migratory schedules has changed over time (a generational shift). In contrast, for short-stopping we found evidence for both individual plasticity (individuals decrease their migration distances over their lifetime) and generational shift. Additional analysis of swan resightings with temperature data showed that, throughout the winter, Bewick's swans frequent areas where air temperatures are <i>c.</i> 5.5˚C. These areas have also shifted eastwards over time, hinting that climate warming is a contributing factor behind the observed changes in the swans' distribution. The occurrence of winter short-stopping and short-staying suggests that this species is to some extent able to adjust to climate warming, but benefits or repercussions at other times of the annual cycle need to be assessed. Furthermore, these phenomena could lead to changes in abundance in certain areas, with resulting monitoring and conservation implications. Understanding the processes and driving mechanisms behind population changes therefore is important for population management, both locally and across the species range.</p>
Data from: Model-based inference for estimating shifts in species distribution, area occupied and centre of gravity
Changing climate is already impacting the spatial distribution of many taxa, including bees, plants, birds, butterflies and fishes. A common goal is to detect range shifts in response to climate change, including changes in the centre of the population's distribution (the centre of gravity, COG), population boundaries and area occupied. Conventional estimators, such as the abundance-weighted average (AWA) estimator for COG, confound range shifts with changes in the spatial distribution of available survey data and may be biased when the distribution of survey data shifts over time. AWA also does not estimate the standard error of COG in individual years and cannot incorporate data from multiple survey designs. To explicitly account for changes in the spatial distribution of survey effort, we propose an alternative species distribution function (SDF) estimator. The SDF approach involves calculating distribution metrics, including COG, population boundary and area occupied, directly from the predicted species distribution or density function. We illustrate the SDF approach using a spatiotemporal model that is available as an r package. Using simulated data, we confirm that the SDF substantially decreases bias in COG estimates relative to the AWA estimator. We then illustrate the method by analysing data from two data sets spanning 1977–2013 for 18 marine fishes along the U.S. West Coast. In our case study, the SDF estimator shows significant northward shifts for six of 18 species (with southward shifts for only 2), where two species (darkblotched and greenstriped rockfishes) have both a northward shift and a decreased area occupied. Pelagic species (e.g. Pacific hake and spiny dogfish) have more variable distribution than bottom-associated species. We also find substantial differences between AWA and SDF estimates of COG that are likely caused by shifts in sampling distribution (which affect the AWA but not the SDF estimator). We caution that common estimators for range shift can yield inappropriate inference whenever sampling designs have shifted over time. We conclude by suggesting further improvements in model-based approaches to analysing climate impacts, including methods addressing the impact of local and regional temperature changes on species distribution.
Data from: Evidence of large-scale range shift in the distribution of a Palaearctic migrant in Africa
Aim: Long-distance Palaearctic migrant birds are declining at a faster rate than short-distance migrant or resident species. This is often attributed to changes on their non-breeding grounds and along their migratory routes. The European Honey-buzzard (Pernis apivorus) is a scarce migrant in southern Africa that is declining globally. This study assessed the distribution and abundance of honey-buzzards in southern Africa over the past four decades and compared it to trends in the East African population to examine possible drivers of population expansion in southern Africa. Location Southern and East Africa Methods European Honey-buzzard reporting data were collected from a variety of sources including citizen science databases (1983-2017). In addition, records of all other southern African vagrants (including ten other regularly occurring species) were gathered to account for changes in birdwatching effort in the sub-region. To assess the effect of forest loss on honey-buzzard abundance, rolling correlations were performed using forest cover in East Africa and number of honey-buzzard records in both sub-regions. Results European Honey-buzzard records in southern Africa have increased over five times more than other regularly occurring vagrant species and almost 40 times more than honey-buzzard in Tanzania, where the population has remained stable. Loss of forested area in East Africa was correlated with an increase in European Honey-buzzard records in southern Africa. Main conclusions We suggest that the European Honey-buzzard shift in wintering range may be driven by a decline in suitable habitat further north in Africa amongst other possible reasons. This effect may have been amplified by an increase in appropriate habitat across southern Africa brought about by anthropogenic changes to vegetation such as increased tree cover in urban areas. This study further highlights the importance of using African distributional data banks to understand the effects of global change on Palaearctic migrant bird species.
Climatic niche shifts in 815 introduced plant species affect their predicted distributions: Data and scripts
<p class="CxSpFirst"><u>Aim:</u> Introduced species often occupy different climates in their introduced than their native range, but to what degree do such 'climatic niche shifts' interfere with our ability to predict invasions? Answering this question is crucial if we are to understand the threat invasive species pose to human and natural systems, especially given the ever increasing use of species distribution models as tools for invasive species risk assessment and management. Here we investigated how strongly climatic niche shifts interfered with the transferability of native- and introduced-range species distribution models.</p> <p class="CxSpMiddle"><u>Location:</u> Our dataset consisted of ~14 million occurrences distributed worldwide.</p> <p class="CxSpMiddle"><u>Time Period:</u> Occurrence data were collected from online repositories dating from ca. 1600 with the vast majority being from the 20<sup>th</sup> century. Climatic data represent means between 1970–2000.</p> <p class="CxSpMiddle"><u>Major Taxa Studied:</u> Our database represented 815 terrestrial plant species.</p> <p class="CxSpMiddle"><u>Methods:</u> We used ordination to identify climatic niche shifts as species moved between continents. Next, we trained separate MAXENT models using native- or introduced-range occurrences, and projected those models into each species' introduced range. We compared the ordination and MAXENT models to determine whether niche shifts were associated with errors in MAXENT predictions.</p> <p class="CxSpMiddle"><u>Results:</u> Models trained on native-range occurrences poorly predicted introduced-range occurrences, and transferability was lowest in species with large climatic niche shifts. Directional shifts in species' predicted geographic distributions mirrored their niche dynamics. This is concerning because native-range data are often used to predict introduced-range distributions.</p> <p><u>Main Conclusions: </u>Our results highlight the importance of considering niche shifts when modeling the potential geographic distributions of introduced species, and cast doubt on the assumption that the climatic niche of a species can be transferred between native and invasive ranges.</p>
Shifting and Distribution of Foot Pressure Among Obese Subjects
ClinicalTrials.gov study NCT03441763. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Persistent natural acidification drives major distribution shifts in marine benthic ecosystems
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Climatic niche shifts in 815 introduced plant species affect their predicted distributions: Data and scripts
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Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals
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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)
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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.