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.
4
datasets available to search
ShareScore release 0.9.0
Dataset results
4 results for “habitat amount hypothesis”
Data from: Experimental evidence does not support the Habitat Amount Hypothesis
For a half century, habitat configuration – the arrangement of habitat patches within a landscape – has been central to theories of landscape ecology, population dynamics, and community assembly, in addition to conservation strategies. A recent hypothesis advanced by Fahrig (2013) would, if supported, greatly diminish the relevance of habitat configuration as a predictor of diversity. The Habitat Amount Hypothesis posits that the sample area effect overrides patch size and patch isolation effects of habitat fragmentation on species richness. It predicts that the amount of habitat in a local landscape, regardless of configuration, is the main landscape-level determinant of species richness. If habitat amount is indeed the major, landscape-level driver of species richness, the slopes of the species–area relationship (SAR) for otherwise similar fragmented and unfragmented landscapes should be indistinguishable. We tested the Habitat Amount Hypothesis with data from two replicated and controlled habitat fragmentation experiments that disentangle the effects of habitat amount and configuration. One experiment provided time-series data on plant species richness and the other on micro-arthropod species richness. We found that, relative to less fragmented habitats, the SARs for fragmented habitats have significantly higher slopes and that the magnitude of the difference in slopes increased over time. Relatively more species were lost in smaller areas when fragments were more isolated. In both experiments, the proportion of species lost due to increased habitat fragmentation was nearly identical to the proportion lost due to reduced habitat amount. Our results provide a direct and experimentally derived refutation of the Habitat Amount Hypothesis, supporting the long-held view that in addition to area, patch isolation and configuration are important determinants of species richness. Differences in species richness between fragmented and non-fragmented habitats increase over time, demonstrating that long-term studies are needed to understand the effects of fragmentation, above and beyond the amount of habitat lost.
Data from: Experimental evidence does not support the Habitat Amount Hypothesis
Open the record for dataset details and reuse information.
Data from: Habitat amount hypothesis and passive sampling explain mammal species composition in Amazonian river islands
Open the record for dataset details and reuse information.
Support for the habitat amount hypothesis from a global synthesis of species density studies
Open the record for dataset details and reuse information.
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.