Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
11
datasets available to search
ShareScore release 0.9.0
Dataset results
11 results for “Occupancy Density”
Data from: Nine-banded Armadillo (Dasypus novemcinctus) occupancy and density across an urban to rural gradient
<p>The nine-banded Armadillo (<em>Dasypus novemcinctus</em>) is the only species of Armadillo in the United States and alters ecosystems by excavating extensive burrows used by many other wildlife species. Relatively little is known about its habitat use or population densities, particularly in developed areas, which may be key to facilitating its range expansion. We evaluated Armadillo occupancy and density in relation to anthropogenic and landcover variables in the Ozark Mountains of Arkansas along an urban to rural gradient. Armadillo detection probability was best predicted by temperature (positively) and precipitation (negatively). Contrary to expectations, occupancy probability of Armadillos was best predicted by slope (negatively) and elevation (positively) rather than any landcover or anthropogenic variables. Armadillo density varied considerably between sites (ranging from a mean of 4.88 – 46.20 Armadillos per km<sup>2</sup>) but was not associated with any environmental or anthropogenic variables.</p>
Data from: Kirtland's warbler occupancy and plantation density
<p>Early studies into the habitat preferences of the Kirtland's warbler (KW; <em>Setophaga kirtlandii</em>) suggested that these birds exhibited a preference for areas with high jack pine stem densities; therefore, jack pine plantations established as part of the KW recovery and conservation programs have been planted using a 1.5 x 1.8 m spacing (3,588 trees ha<sup>-1</sup>). In contrast, traditional pine plantations in the Lake States established for roundwood production are typically planted on a 2.1 x 2.4 m spacing that equates to 1,922 trees ha<sup>-1</sup>. Over more than 40 years, tree spacing in KW habitat plantations has gone largely unchanged, and until very recently there has never been an attempt to verify that these tighter spacings actually provide better KW habitat than would a traditional forestry spacing. We used a retrospective approach to assess the impacts of tree density on KW occupancy and observed an unexpected negative relationship between realized plantation density and maximum occupancy by KW singing males. This finding should be interpreted with caution due to the limited nature of this study; however, a lack of a positive relationship is entirely plausible given the narrow range of densities encountered in plantations, as well as the fact that uniform spacing of plantations should allow for the achievement of optimal jack pine cover at lower densities than would be required in a natural-origin stand.</p>
Data from: Kirtland's warbler occupancy and plantation density
Open the record for dataset details and reuse information.
Data from: Nine-banded Armadillo (Dasypus novemcinctus) occupancy and density across an urban to rural gradient
Open the record for dataset details and reuse information.
Data from: Examining the occupancy-density relationship for a low-density carnivore
1. The challenges associated with monitoring low-density carnivores across large landscapes have limited the ability to implement and evaluate conservation and management strategies for such species. Non-invasive sampling techniques and advanced statistical approaches have alleviated some of these challenges and can even allow for spatially explicit estimates of density, one of the most valuable wildlife monitoring tools. 2. For some species, individual identification comes at no cost when unique attributes (e.g. pelage patterns) can be discerned with remote cameras, while other species require viable genetic material and expensive lab processing for individual assignment. Prohibitive costs may still force monitoring efforts to use species distribution or occupancy as a surrogate for density, which may not be appropriate under many conditions. 3. Here, we used a large-scale monitoring study of fisher Pekania pennanti to evaluate the effectiveness of occupancy as an approximation to density, particularly for informing harvest management decisions. We combined remote cameras with baited hair snares during 2013–2015 to sample across a 70 096 km2 region of western New York, USA. We fit occupancy and Royle-Nichols models to species detection–non-detection data collected by cameras, and spatial capture-recapture models to individual encounter data obtained by genotyped hair samples. Variation in the state variables within 15-km2 grid cells was modeled as a function of landscape attributes known to influence fisher distribution. 4. We found a close relationship between grid-cell estimates of fisher state variables from the models using detection–non-detection data and those from the spatial capture-recapture model, likely due to informative spatial covariates across a large landscape extent and a grid-cell resolution that worked well with the movement ecology of the species. Fisher occupancy and density were both positively associated with the proportion of coniferous-mixed forest and negatively associated with road density. As a result, spatially-explicit management recommendations for fisher were similar across models, though relative variation was dampened for the detection–non-detection data. 5. Synthesis and applications. Our work provides empirical evidence that models using detection-non-detection data can make similar inferences regarding relative spatial variation of the focal population to models using more expensive individual encounters when the selected spatial grain approximates or is marginally smaller than home range size. When occupancy alone is chosen as a cost-effective state variable for monitoring, simulation and sensitivity analyses should be used to understand how inferences from detection–non-detection data will be affected by aspects of study design and species ecology.
Figure 2 in Density, occupancy and detectability of tortoise species (Chelonoidis spp.) in the Atlantic Forest: implications for conservation and management
Figure 2. Relationship between the probability of detection of Chelonoidis denticulatus (A) and Chelonoidis carbonarius (B) with the accumulated rainfall of the day before sampling (previous rainfall) in the Vale Natural Reserve, Brazil.
Figure 1 in Density, occupancy and detectability of tortoise species (Chelonoidis spp.) in the Atlantic Forest: implications for conservation and management
Figure 1. Location of the Vale Natural Reserve, municipality of Linhares, Espírito Santo, south-eastern Brazil, showing the location of the linear transects and the types of vegetation present in the Reserve.
Figure 3 in Density, occupancy and detectability of tortoise species (Chelonoidis spp.) in the Atlantic Forest: implications for conservation and management
Figure 3. Relationship between the probability of occupancy of Chelonoidis denticulatus (A) and Chelonoidis carbonarius (B) with the distance from the water resource, and relationship between the probability of occupancy of Chelonoidis denticulatus and the percentage of forest cover (C) in the Vale Natural Reserve, Brazil.
Data from: Examining the occupancy-density relationship for a low-density carnivore
Open the record for dataset details and reuse information.
Density dependence influences competition and hybridization at an invasion front - occupancy and istope data
<p>Occupancy data and stable isotope data associated with the publication ' Density dependence influences competition and hybridization at an invasion front' in <em>Diversity and Distributions.</em></p>
Impacts of free-ranging yaks on habitat occupancy and population density of a high-mountain endangered pheasant species
<p>This dataset include all raw data for reproducing all of the analyses in this paper.</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.