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131
datasets available to search
ShareScore release 0.9.0
Dataset results
131 results for “habitat prediction”
Data from: Crater lake habitat predicts morphological diversity in adaptive radiations of cichlid fishes
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Predicting habitat suitability for wild deer in relation to threatened ecological communities in south-eastern New South Wales, Australia
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Data from: Finer-scale habitat predicts nest survival in grassland birds more than management and landscape: a multi-scale perspective
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Data from: The importance of using topographic features to predict climate-resilient habitat for migratory forest landbirds: an example for the Rusty Blackbird, Olive-sided Flycatcher, and Canada Warbler
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Data from: Habitat niche breadth predicts invasiveness in solitary ascidians
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Data from: Predictive modelling of habitat selection by marine predators with respect to the abundance and depth distribution of pelagic prey
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Predicted impacts of climate change on wild and commercial berry habitats will have food security, conservation and agricultural implications
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Both real-time and long-term environmental data perform well in predicting shorebird distributions in managed habitat
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Remotely sensed forest understory density and nest predator occurrence interact to predict suitable breeding habitat and the occurrence of a resident boreal bird species
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Data from: Density-dependent habitat selection predicts fitness and abundance in a small lizard
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Is phylogeographic congruence predicted by historical habitat stability, or ecological co-associations?
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Data from: Carcass predictability but not domestic pet introduction affects functional response of scavenger assemblage in urbanised habitats
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Data from: Temporally dynamic habitat suitability predicts genetic relatedness among caribou
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Data from: Predicting species occurrences with habitat network models
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Data from: Use of opportunistic sightings and expert knowledge to predict and compare Whooping Crane stopover habitat
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A new model of forelimb ecomorphology for predicting the ancient habitats of fossil turtles
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Predictive multi-scale occupancy models at range-wide extents: effects of habitat and human disturbance on distributions of wetland birds
<p><span><i>Aim:</i> Predicting distributions is fundamental to ecology, yet hindered by spatially-restricted sampling, scale-dependent relationships, and detection error associated with field surveys. Predictive species distribution models (SDMs) are nonetheless vital for conservation of many species. We developed a framework for building predictive SDMs with multi-scale data, and used it to develop range-wide breeding-season SDMs for 14 marsh bird species of concern.</span></p> <p><span><i>Location: </i>USA.</span></p> <p><span><i>Methods: </i>We built SDMs using data from range-wide surveys conducted over 14 years, and habitat and disturbance covariates measured at multiple spatial scales. We built hierarchical occupancy models that included heterogeneity in detectability during sampling, and used Bayesian model selection to regulate model complexity (covariates and scales) based explicitly on spatial predictive abilities. We thus integrated model selection for optimizing out-of-sample prediction, range-wide sampling over broad conditions, multi-scale analyses and scale-optimization, and species-specific detectability for a suite of wide-ranging species. </span></p> <p><span><i>Results: </i>Distributions of marsh birds were affected by local wetland conditions, but also by agricultural, urban, and hydrologic disturbances operating from local scales (100 – 500 m) to the watershed level. Variables measuring human disturbances improved prediction for most species, and every species was affected by attributes at > 1 scale. Five species showed evidence for continental-scale range contraction during the study.</span></p> <p><span><i>Main conclusions: </i>We demonstrate how hierarchical occupancy models can be optimized for prediction across a species' range at the extent of a continent while also accounting for imperfect detection, and thus describe a generalizable approach that can be used for any species. We provide the first data-driven, empirical SDMs built at the range-wide extent for most of our 14 study species and demonstrate that previous studies focused on local distributions and the effects of fine-scale wetland vegetation missed important broad-scale drivers of occupancy for marsh birds. </span></p>
Data from: Future climate change is predicted to affect the microbiome and condition of habitat-forming kelp
Climate change is driving global declines of marine habitat-forming species through physiological effects and through changes to ecological interactions, with projected trajectories for oceanwarming and acidification likely to exacerbate such impacts in coming decades. Interactions between habitat-formers and their microbiomes are fundamental for host functioning and resilience, but how such relationships will change in future conditions is largely unknown. We investigated independent and interactive effects of warming and acidification on a large brown seaweed, the kelp Ecklonia radiata, and its associated microbiome in experimental mesocosms. Microbial communities were affected by warming and, during the first week, by acidification. During the second week, kelp developed disease-like symptoms previously observed in the field. The tissue of some kelp blistered, bleached and eventually degraded, particularly under the acidification treatments, affecting photosynthetic efficiency. Microbial communities differed between blistered and healthy kelp for all treatments, except for those under future conditions of warming and acidification, which after two weeks resembled assemblages associated with healthy hosts. This indicates that changes in the microbiome were not easily predictable as the severity of future climate scenarios increased. Future ocean conditions can change kelp microbiomes and may lead to host disease, with potentially cascading impacts on associated ecosystems.
Data from: Cats in the forest: predicting habitat adaptations from humerus morphometry in extant and fossil Felidae (Carnivora)
Mammalian carnivores are rarely incorporated in paleoenvironmental reconstructions, largely because of their rarity within the fossil record. However, multivariate statistical modeling can be successfully used to quantify specific anatomical features as environmental predictors. Here we explore morphological variability of the humerus in a closely related group of predators (Felidae) to investigate the relationship between morphometric descriptors and habitat categories. We analyze linear measurements of the humerus in three different morphometric combinations (log-transformed, size-free, and ratio), and explore four distinct ways of categorizing habitat adaptations. Open, Mixed, and Closed categories are defined according to criteria based on traditional descriptions of species, distributions, and biome occupancy. Extensive exploratory work is presented using linear discriminant analyses and several fossils are included to provide paleoecological reconstructions. We found no significant differences in the predictive power of distinct morphometric descriptors or habitat criteria, although sample splitting into small and large cat guilds greatly improves the stability of the models. Significant insights emerge for three long-canine cats: Smilodon populator, Paramachairodus orientalis, and Dinofelis sp. from Olduvai Gorge (East Africa). S. populator and P. orientalis are both predicted to have been closed-habitat adapted taxa. The false "sabertooth" Dinofelis sp. from Olduvai Gorge is predicted to be adapted to mixed habitat. The application of felid humerus ecomorphology to the carnivoran record of Olduvai Gorge shows that the older stratigraphic levels (Bed I, 1.99–1.79 Ma) included a broader range of environments than Beds II or V, where there is an abundance of cats adapted to open environments.
Data from: Ecological constraints coupled with deep-time habitat dynamics predict the latitudinal diversity gradient in reef fishes
We develop a spatially explicit model of diversification based on paleohabitat to explore the predictions of four major hypotheses potentially explaining the latitudinal diversity gradient (LDG), namely, the 'time-area', 'tropical niche conservatism', 'ecological limits' and 'evolutionary speed' hypotheses. We compare simulation outputs to observed diversity gradients in the global reef fish fauna. Our simulations show that these hypotheses are non-mutually exclusive and that their relative influence depends on the time scale considered. Indeed, simulations suggest that reef habitat dynamics produced the LDG during deep geological time, while ecological constraints shaped the modern LDG, with a strong influence of the reduction in the latitudinal extent of tropical reefs during the Neogene. Overall, this study illustrates how mechanistic models in ecology and evolution can provide a temporal and spatial understanding of the role of speciation, extinction and dispersal in generating contemporary biodiversity patterns.
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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.