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8 results for “multi-species occupancy models”
Assessing patterns and risk to Chilean freshwater fish distributions using multi-species occupancy models
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Multi-species occupancy modeling provides novel insights into amphibian metacommunity structure and wetland restoration
<p>A fundamental goal of community ecology is to understand species-habitat relationships and how they shape metacommunity structure. Recent advances in occupancy modeling enable habitat relationships to be assessed for both common and rare species within metacommunities using multi-species occupancy models (MSOM). These models account for imperfect species detection and offer considerable advantages over other analytical tools commonly used for community analyses under the elements of metacommunity structure (EMS) framework. Here, we demonstrate that MSOM can be used to infer habitat relationships and test metacommunity theory, using amphibians. Repeated frog surveys were undertaken at 55 wetland sites in eastern Australia. We detected 11 frog species from three families (Limnodynastidae, Myobatrachidae and Pelodryadidae). The rarest species was detected at only one site whereas the most common species was detected at 42 sites (naïve occupancy rate: 0.02 – 0.76). Two models were assessed representing two competing hypotheses; the best-supported model included the covariates distance to the nearest site (connectivity), wetland area, presence of the non-native eastern mosquitofish (<i>Gambusia holbrooki</i>), proportion cover of emergent vegetation, an interaction term between Gambusia and emergent vegetation cover, and the proportion canopy cover over a site. Hydroperiod played no detectable role in metacommunity structure. We found species-habitat relationships that fit with current metacommunity theory – occupancy increased with wetland area and connectivity. There was a strong negative relationship between occupancy and the presence of predatory Gambusia, and a positive interaction between Gambusia and emergent vegetation. The presence of canopy cover strongly increased occupancy for several tree frog species, highlighting the importance of terrestrial habitat for amphibian community structure. We demonstrated how responses by amphibians to environmental covariates at the species level can be linked to occupancy patterns at the metacommunity scale. Our results have clear management implications – wetland restoration projects for amphibians and likely other taxa should maximize wetland area and connectivity, establish partial canopy cover, and eradicate Gambusia or provide aquatic vegetation to mitigate the impact of this non-native fish. We strongly advocate the use of MSOM to elucidate the habitat drivers behind animal occupancy patterns and to derive unbiased occupancy estimates for monitoring programmes.</p>
Multi-species occupancy model for estimating the probability of detecting amphibian species in Hungary
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Multi-species occupancy modeling provides novel insights into amphibian metacommunity structure and wetland restoration
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Data from: Modelling misclassification in multi-species acoustic data when estimating occupancy and relative activity
<p>1. Surveying wildlife communities provides data for informing conservation and management decisions that affect multiple species. Autonomous recording units (ARUs) can efficiently gather community data for a variety of taxa, but generally require software algorithms to classify each recorded call to a species. Species classification errors are possible during this process and result in both false negative and false positive detections. Available approaches for analysing ARU data do not model the species classification probabilities, meaning erroneous detections are attributed to an omnibus source instead of the presence of another species. Additionally, counts of call recordings for each species are often summarized to binary detection data for analyses. Expanding statistical models to capture these nuances of ARU data would allow for improved inferences about occupancy and relative activity. 2. Motivated by bat acoustic surveys, we developed a model to analyse counts of call recordings from multiple species simultaneously while accounting for species classification errors. Our model expands on previously developed false positive occupancy models to better describe acoustic data. We used simulations to compare our model to other false positive occupancy models for an example scenario with ARU data from two species. We also analyse acoustic data for eight bat species in Montana using our model. 3. In simulations, single-species models resulted in biased estimates of occupancy and relative activity because they failed to associate false positives with the presence of the second species. Models analysing binary observations ignored available information on relative activity and led to less precise estimates. Applying our model to bat acoustic data from Montana allowed for species-specific estimates of occupancy and relative activity. This analysis illustrates the flexibility in our model framework while also highlighting the assumptions and data requirements for implementation. Specifically, additional information on the species classification probabilities is needed and we discuss considerations for reliably estimating these parameters. 4. Directly modelling the species classification probabilities allows for improved ecological inferences for both occupancy and relative activity using community ARU data. Our statistical framework helps address the challenges posed by acoustic data, allowing ecologists to better utilize this technology to monitor wildlife communities.</p>
Data from: Modelling misclassification in multi-species acoustic data when estimating occupancy and relative activity
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Multi-species occupancy models as robust estimators of community richness
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Data from: Dynamic multi-species occupancy models reveal individualistic habitat preferences in a high-altitude grassland bird community
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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.