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9 results for “resource selection function”
Data from: Under cover: The nuanced influence of functional properties of cover on resource selection by pygmy rabbits (Brachylagus idahoensis)
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A Functional Response in Resource Selection Links Multi-Scale Responses of a Large Carnivore to Human Mortality Risk
<p>This repository contains code and data to reproduce results from the manuscript 'A Functional Response in Resource Selection Links Multi-Scale Responses of a Large Carnivore to Human Mortality Risk'. </p>
Ruffed Grouse Resource Selection Function and Survival Datasets
<p>For overwintering species, individuals' ability to find refugia from inclement weather and predators likely confers strong fitness benefits. How animals use their environment can be mediated by their personality (e.g., risk-taking), but does personality mediate how overwintering species select refugia? Snow cover is a dynamic winter characteristic that can influence crypsis or provide below-the-snow refugia. We explored how wintering ruffed grouse (<i>Bonasa umbellus</i>) selected snow roosting sites, a behavior that reduces stress and cold exposure. We linked selection for ~700 roosts with survival of 42 grouse, and showed that grouse generally selected deeper snow and warmer areas. Grouse found in shallow snow were less likely to survive winter. However, individuals with personalities for selecting deep snow improved their survival, suggesting that demographic consequences of selecting winter refugia are mediated by differences in personality<i>.</i> Our study provides a crucial, and seldom addressed, link between personality in resource selection and resulting demographic consequences.</p>
Data from: Revisiting the functional response in habitat selection for large herbivores: a matter of spatial variation in resource distribution?
Most habitats are distributed heterogeneously in space, forcing animals to move according to both habitat characteristics and their needs for energy and safety. Animal space use should therefore vary according to habitat characteristics, a process known as the "functional response" in habitat selection. This response has often been tested vis-à-vis the proportion of a habitat category within areas available to individuals. Measuring sought-after resources in landscape where they are continuously distributed is a challenge and we posit here that both the mean availability of a resource and its spatial variation should be measured. Accordingly, we tested for a functional response in habitat selection according to these two descriptors of the resource available for a mountain herbivore. We hypothesized that selection should decrease with mean value of resources available and increase with its spatial variation. Based on GPS data from 50 chamois females and data on the actual foodscape (i.e. distribution of edible-only biomass in the landscape), we estimated individual selection ratio (during summer months) for biomass at the home range level, comparing edible biomass in individual home ranges and the mean and standard deviation of edible biomass in their available range. Chamois being a group-living species, available accessible ranges were shared by several individuals that formed socio-spatial groups (clusters) in the population. As expected, selection ratios increased with the standard deviation of edible resources in each cluster, but unlike our prediction, was unrelated to its mean. Selection of areas richer in resources hence did not fade away when more resources were available on average, a result that may be explained by the need for this capital breeder species to accumulate fat-reserve at a high rate during summer months. Low spatial variation could limit the selection of chamois, which highlights the importance of resource distribution in the process of habitat selection.
Resource selection functions based on hierarchical generalized additive models provide new insights into individual animal variation and species distributions
<p>Habitat selection studies are designed to generate predictions of species distributions or inference regarding general habitat associations and individual variation in habitat use. Such studies frequently involve either individually indexed locations gathered across limited spatial extents and analyzed using resource selection functions (RSF), or spatially extensive locational data without individual resolution typically analyzed using species distribution models. Both analytical methodologies have certain desirable features, but analyses that combine individual- and population-level inference with flexible non-linear functions may provide improved predictions while accounting for individual variation. Here, we describe how RSFs can be fit using hierarchical generalized additive models (HGAMs) using widely available software, providing a means to explore individual variation in habitat associations and to generate species distribution maps. We used GPS tracking data from Golden Eagles (Aquila chrysaetos) from across eastern North America with four environmental predictors to generate monthly distribution models. We considered three model structures that assumed different amounts of individual variation in the functional relationship between predictors and habitat use and used k-fold cross-validation to compare model performance. Models accounting for individual variability in shape and smoothness of functional responses performed best. Eagles exhibited the least amount of individual variation in response to land cover variables during winter months, with most individuals more closely adhering to the population-level trend. During summer months, eagles exhibited more substantial individual variation in shape and smoothness of the functional relationships, suggesting some need to account for individual variation in eagle habitat use for both inferential and predictive purposes, during this time of year. Because they allow users to blend flexible functions with random effects structures and are well-supported by a variety of software platforms, we believe that HGAMs provide a useful addition to the suite of analyses used for modeling habitat associations or predicting species distributions.</p>
Data from: Revisiting the functional response in habitat selection for large herbivores: a matter of spatial variation in resource distribution?
Open the record for dataset details and reuse information.
Resource selection functions based on hierarchical generalized additive models provide new insights into individual animal variation and species distributions
Open the record for dataset details and reuse information.
Ruffed Grouse Resource Selection Function and Survival Datasets
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Winter-run Chinook salmon resource selection function 2020
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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)
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.