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84 results for “Distributional Shift”
Data from: Trait-dependent distributional shifts in fruiting of common British fungi
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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
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Data from: Climate-driven range shifts explain the distribution of extant gene pools and predict future loss of unique lineages in a marine brown alga
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Data from: Range-wide distribution of genetic diversity in the North American tree Juglans cinerea: a product of range shifts, not ecological marginality or recent population decline
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Data from: Evidence of large-scale range shift in the distribution of a Palaearctic migrant in Africa
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Concurrent shifts in wintering distribution and phenology in migratory swans
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The role of dispersal limitation and reforestation in shaping the distributional shift of a forest herb under climate change
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Data from: Model-based inference for estimating shifts in species distribution, area occupied and centre of gravity
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Ecological niche modelling to project past, current and future distributional shift of black ebony tree (Diospyros melanoxylon Roxb.) in India
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Supplementary material 1 from: Schertler A, Rabitsch W, Moser D, Wessely J, Essl F (2020) The potential current distribution of the coypu (Myocastor coypus) in Europe and climate change induced shifts in the near future. NeoBiota 58: 129-160. https://doi.org/10.3897/neobiota.58.33118
Supplementary materials
Data from: Individual shifts toward safety explain age-related foraging distribution in a gregarious shorebird
Although age-related spatial segregation is ubiquitous, the underlying mechanisms are poorly understood. Here, we aim to elucidate the processes behind a previously established age-related foraging distribution of red knots (Calidris canutus canutus) in their main wintering area in West Africa (Banc d'Arguin, Mauritania). Based on 10 years of observations of 1232 uniquely color-ringed individuals of 1 to 18+ years old, we examined whether the observed age-related foraging distribution resulted from 1) spatial differences in mortality or 2) age-related shifts in habitat use. Using multistate capture–recapture modeling, we showed that with age foraging red knots moved away from the shoreline, that is, to areas with fewer surprise attacks by raptors. Considering uncertainties in the subjective gradient in predation danger with increasing distance from shore (as assessed from correlations between vigilance and distance from shore in foraging birds), we applied 2 different danger zone boundaries, at 40 m and 500 m from shore. Between years, red knots had a much higher chance to move from the dangerous nearshore area to the "safe" area beyond (71–78% and 26% for 40-m and 500-m danger zone boundary, respectively), than vice versa (4% and 14%). For neither danger zone boundary value did we find differences in annual mortality for individuals using either dangerous or safe zone, so the move away from the shore with age is attributed to individual careers rather than differential mortality. We argue that longitudinal studies like ours will reveal that ontogenetic shifts in habitat use are more common than so far acknowledged.
distribution shift dataset for Java
<p>This is a dataset for studying distribution shift under programming language.</p>
Projected shifts in deadwood bryophytes in Sweden, data used for species distribution modelling and for climate and forest scenario analysis
<p>Climate change and habitat loss are main threats to forest biodiversity. We fitted ensembles of single species distribution models for 23 deadwood-living bryophyte species in Sweden, based on species records from the Swedish Lifewatch website. This data set comprises the species and environmental data used for species distribution modelling, and coefficients of the fitted single species distribution models (GLM, Poisson point-process, MaxEnt).</p> <p>Based on the fitted species distribution models, we conducted simulations of future species distributions given realistic climate and forest projection scenarios at the national scale of Sweden. The data used for the scenario analysis are stored here.</p>
Evaluation of the parenchymal distribution of renal steatosis using chemical shift-magnetic resonance imaging in chronic kidney disease
<p><strong>Supplementary Table.</strong> The results of normality and variance homogeneity assumptions<strong>.</strong></p>
Data from: Individual shifts toward safety explain age-related foraging distribution in a gregarious shorebird
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Projected shifts in deadwood bryophytes in Sweden, data used for species distribution modelling and for climate and forest scenario analysis
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Data from: Differential responses of sexual and asexual <em>Aphis gossypii</em> lineages to climate change: shifts in distribution, phenology, and host-plant interactions
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Data from: Climate‐driven shifts in the distribution of koala browse species from the Last Interglacial to the near future
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Data from: Evaluating distributional shifts in home range estimates
A variety of methods are commonly used to quantify animal home ranges using location data acquired with telemetry. High-volume location data from global positioning system (GPS) technology provide researchers the opportunity to identify various intensities of use within home ranges, typically quantified through utilization distributions (UDs). However, the wide range of variability evident within UDs constructed with modern home range estimators is often overlooked or ignored during home range comparisons, and challenges may arise when summarizing distributional shifts among multiple UDs. We describe an approach to gain additional insight into home range changes by comparing UDs across isopleths and summarizing comparisons into meaningful results. To demonstrate the efficacy of this approach, we used GPS location data from 16 bighorn sheep (Ovis canadensis) to identify distributional changes before and after habitat alterations, and we discuss advantages in its application when comparing home range size, overlap, and joint-space use. We found a consistent increase in bighorn sheep home range size when measured across home range levels, but that home range overlap and similarity values decreased when examined at increasing core levels. Our results highlight the benefit of conducting multiscale assessments when comparing distributions, and we encourage researchers to expand comparative home range analyses to gain a more comprehensive evaluation of distributional changes and to evaluate comparisons across home range levels.
AnoShift: A distribution shift benchmark for unsupervised anomaly detection
<p>Analyzing the distribution shift of data is a growing research direction in nowadays Machine Learning (ML), leading to emerging new benchmarks that focus on providing a suitable scenario for studying the generalization properties of ML models. The existing benchmarks are focused on supervised learning, and to the best of our knowledge, there is none for unsupervised learning. Therefore, we introduce an unsupervised anomaly detection benchmark with data that shifts over time, built over Kyoto-2006+, a traffic dataset for network intrusion detection. This type of data meets the premise of shifting the input distribution: it covers a large time span (10 years), with naturally occurring changes over time (eg users modifying their behavior patterns, and software updates). We first highlight the non-stationary nature of the data, using a basic per-feature analysis, t-SNE, and an Optimal Transport approach for measuring the overall distribution distances between years. Next, we propose AnoShift, a protocol splitting the data in IID, NEAR, and FAR testing splits. We validate the performance degradation over time with diverse models, ranging from classical approaches to deep learning. Finally, we show that by acknowledging the distribution shift problem and properly addressing it, the performance can be improved compared to the classical training which assumes independent and identically distributed data (on average, by up to 3% for our approach).</p>
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.