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131 results for “habitat prediction”
Clinging performance on natural substrates predicts habitat use in anoles and geckos
<p>1. For arboreal lizards, the ability to cling or adhere to the substrate is critical for locomotion during prey capture, predator escape, thermoregulation, and social interactions. Thus, selection on traits related to clinging is likely strong. </p> <p>2. Correlations between morphology, performance, and habitat use have been documented in arboreal lizards, providing a framework for using functional traits to predict habitat use in the field.</p> <p>3. We tested the hypothesis that clinging performance predicts habitat use in an actively assembling community of introduced lizards in Hawaiʻi comprised of anoles (<i>Anolis carolinensis, A. sagrei</i>) and day geckos (<i>Phelsuma laticauda</i>).</p> <p>4. We measured morphological traits (toepad area and lamellae number) and tested clinging performance on two artificial and eight natural substrates in the lab. We measured habitat use in 10 m x 10 m outdoor enclosures where habitat availability was controlled and the lizard species assemblage was manipulated to reflect all species combinations. The enclosure experiment generated more than 9,000 habitat use observations from 360 lizards.</p> <p>5. Morphological traits that predict performance in <i>Anolis </i>were not predictive in <i>Phelsuma</i>, indicating that direct measures of performance are necessary for comparisons between the genera.</p> <p>6. Measuring clinging performance on multiple substrates provided key insights into patterns of habitat use. While all three species performed best on an artificial smooth substrate (acrylic), performance on natural substrates predicted which texture (rough vs. smooth) was most often used by each species. </p> <p>7. Performance predicted perch height use: species with the greatest clinging performance (<i>A. carolinensis </i>and <i>P. laticauda</i>) across substrates perched twice as high as <i>A. sagrei</i>.</p> <p>8. We did not observe habitat shifts in the height or texture of perches used by any species in response to experimental manipulation of the lizard species assemblage.</p> <p>9. Our results highlight the inextricable link between ecology, morphology, and performance, the importance of measuring functional traits in ecologically-relevant ways, and the potential for resource partitioning to be influenced by differences in the ability to attach to different substrates. </p>
Data from: Ecological constraints coupled with deep-time habitat dynamics predict the latitudinal diversity gradient in reef fishes
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Predictive multi-scale occupancy models at range-wide extents: effects of habitat and human disturbance on distributions of wetland birds
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Clinging performance on natural substrates predicts habitat use in anoles and geckos
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Data from: Predicting the non-linear collapse of plant-frugivore networks due to habitat loss
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Predicting hedgehog mortality risks on British roads using habitat suitability modelling
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Data from: Future climate change is predicted to affect the microbiome and condition of habitat-forming kelp
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Data from: Cats in the forest: predicting habitat adaptations from humerus morphometry in extant and fossil Felidae (Carnivora)
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Data from: Structural habitat predicts functional dispersal habitat of a large carnivore: how leopards change spots
Natal dispersal promotes inter-population linkage, and is key to spatial distribution of populations. Degradation of suitable landscape structures beyond the specific threshold of an individual's ability to disperse can therefore lead to disruption of functional landscape connectivity and impact metapopulation function. Because it ignores behavioral responses of individuals, structural connectivity is easier to assess than functional connectivity and is often used as a surrogate for landscape connectivity modeling. However using structural resource selection models as surrogate for modeling functional connectivity through dispersal could be erroneous. We tested how well a second-order resource selection function (RSF) models (structural connectivity), based on GPS telemetry data from resident adult leopard (Panthera pardus L.), could predict subadult habitat use during dispersal (functional connectivity). We created eight non-exclusive subsets of the subadult data based on differing definitions of dispersal to assess the predictive ability of our adult-based RSF model extrapolated over a broader landscape. Dispersing leopards used habitats in accordance with adult selection patterns, regardless of the definition of dispersal considered. We demonstrate that, for a wide-ranging apex carnivore, functional connectivity through natal dispersal corresponds to structural connectivity as modeled by a second-order RSF. Mapping of the adult-based habitat classes provides direct visualization of the potential linkages between populations, without the need to model paths between a priori starting and destination points. The use of such landscape scale RSFs may provide insight into predicting suitable dispersal habitat peninsulas in human-dominated landscapes where mitigation of human–wildlife conflict should be focused. We recommend the use of second-order RSFs for landscape conservation planning and propose a similar approach to the conservation of other wide-ranging large carnivore species where landscape-scale resource selection data already exist.
The dataset of predicting the potential habitat suitability of Saussurea species in China under future climate change using the optimized Maximum Entropy (MaxEnt) model
<p><strong>Description:</strong></p> <p>This dataset accompanies the study on the Saussurea species, renowned for its biodiversity and medicinal significance in high-elevation regions, which faces endangerment due to climate change and human activities. Despite its importance, conservation research on Saussurea has been limited. To address this gap, the study employed the optimized MaxEnt model to simulate Saussurea's habitat suitability and analyze key environmental factors influencing its distribution.</p> <p>The dataset includes:</p> <ol> <li><strong>Model and Parameter Optimization Code</strong>: The code used for optimizing the MaxEnt model parameters, ensuring reproducibility of the habitat suitability models.</li> <li><strong>Saussurea Distribution Points</strong>: Georeferenced points indicating the observed locations of Saussurea species.</li> <li><strong>Current Environmental Variables</strong>: Data on key environmental factors influencing Saussurea distribution, such as Elevation, Isothermality (Bio3), and Temperature Annual Range (Bio7).</li> <li><strong>Future Environmental Variables: </strong>Data on key environmental factors influencing Saussurea distribution under SSP126, SSP245, SSP370 and SSP585 in 2020-2100s.</li> </ol>
Data from: Structural habitat predicts functional dispersal habitat of a large carnivore: how leopards change spots
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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.