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70 results for “habitat isolation”
Data from: Isolated trees support lower bird taxonomic richness than trees within habitat patches but similar functional diversity
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Data from: Isolation by time and habitat and coexistence of distinct host races of the common cuckoo
Isolation by time occurs when different populations of a single species reproduce at different times and thereby reduce the probability of interbreeding, potentially causing divergent adaptation to timing of reproduction, eventually resulting in ecological species separated by timing of reproduction. We analyzed extensive data on timing of reproduction by different host races of the common cuckoo Cuculus canorus that is an obligate brood parasite laying eggs in the nests of many different species of passerine birds. Because different hosts breed at different times, specific host races of cuckoos have adapted to specific hosts by laying eggs when nests of these hosts are available, and such divergence may be further exaggerated by differences in timing of breeding among host races with similar habitat requirements. Host species accounted for a quarter of the variance in timing of breeding by the cuckoo. Common cuckoos reproduced at a similar, but narrower subset of dates as did possible hosts, showing that only a fraction of hosts with specific breeding dates were parasitized. Common cuckoo eggs laid in the 'right' kind of nests, phenotypically matching the eggs of the host, were laid later during the season than cuckoo eggs laid in the 'wrong' kind of nests where the eggs did not mimic those of the host. Pairs of sympatric cuckoo host races differed more in timing of breeding than pairs of allopatric host races, and pairs of cuckoo host races with similar breeding habitat differed more in breeding date than pairs of cuckoo host races with dissimilar habitat, as expected from reproductive character displacement. These findings are consistent with cuckoo host races being isolated by timing of breeding and habitat.
Data from: Competition-driven build-up of habitat isolation and selection favouring dispersal modification in a young avian hybrid zone
Competition-driven evolution of habitat isolation is an important mechanism of ecological speciation but empirical support for this process is often indirect. We examined how an on-going displacement of pied flycatchers from their preferred breeding habitat by collared flycatchers in a young secondary contact zone is associated with (a) access to an important food resource (caterpillar larvae), (b) immigration of pied flycatchers in relation to habitat quality, and (c) the risk of hybridization in relation to habitat quality. Over the past 12 years, the estimated access to caterpillar larvae biomass in the habitat surrounding the nests of pied flycatchers has decreased by a fifth due to shifted establishment possibilities, especially for immigrants. However, breeding in the high quality habitat has become associated with such a high risk of hybridization for pied flycatchers that overall selection currently favors pied flycatchers that were forced to immigrate into the poorer habitats (despite lower access to preferred food items). Our results show that competition-driven habitat segregation can lead to fast habitat isolation, which per se caused an opportunity for selection to act in favor of future "voluntarily" altered immigration patterns and possibly strengthened habitat isolation through reinforcement.
Data from: Habitat amount, not patch size and isolation, drives species richness of macro‐moth communities in countryside landscapes
Aim: Our aim is to test whether species richness patterns are best explained by the effect of the total amount of habitat within the landscape, or instead by a combination of patch size and patch isolation effects. To this end, we jointly contrast the habitat amount hypothesis and countryside biogeography with patch size and isolation concepts from island biogeography. Location: Three multi-habitat landscapes in Peneda-Gerês National Park, NW Portugal. Taxon: Macro-moths (Lepidoptera). Methods: Light-trapping using a semi-nested design at 84 fixed sites which were each repeatedly sampled six times. Results: Autocovariate models show that sampling sites with a higher number of forest and meadow macro-moth species (alpha diversity) were surrounded by a higher amount of forest and meadow habitat, respectively within a 160 and 320 m radius (scale of effect). These top-ranked models, containing only habitat amount as a significant variable, had lower AIC than models (only) containing patch size and/or isolation. Complementary to this, the countryside species-area relationship (SAR) model outperforms the classic SAR model, so that the effective area of habitat explains landscape species richness (gamma diversity) across spatial scales (beta diversity) better than the classic SAR. Specifically, we show that forest macro-moths have a higher spatial turnover than meadow macro-moths and that, on average, there are more species in forest than in meadow habitat. Main conclusions: The habitat amount hypothesis predicts alpha species richness in multi-habitat landscapes better than do patch size and isolation while the countryside SAR predicts beta and gamma diversity better than the classic SAR. We suggest that evidence is mounting to revise the application of the classical approaches of island biogeography and metapopulation theory to conservation biogeography.
Data from: Habitat amount, not patch size and isolation, drives species richness of macro‐moth communities in countryside landscapes
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Data from: Isolation by time and habitat and coexistence of distinct host races of the common cuckoo
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Data from: Competition-driven build-up of habitat isolation and selection favouring dispersal modification in a young avian hybrid zone
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Data from: The biggest losers: habitat isolation deconstructs complex food webs from top to bottom
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Coyote Creek Isolated Pool Habitat Data
<p>Data collected in 2015/2016 In Coyote Creek (Santa Clara County). Part of a larger ongoing research project. Uploaded for use in a class project for Reproducible and Collaborative Data Science, part of the Data Science for the 21st Century program.</p>
Genomic diversity of Escherichia isolates from diverse habitats
GEO Series GSE39667. Escherichia coli; Escherichia coli O157:H7 str. EDL933; Escherichia albertii; Escherichia sp. TW09254; Escherichia sp. TW09266; Escherichia sp. TW09276; Escherichia sp. TW09308; Escherichia sp. TW14263; Shigella flexneri 2a str. 2457T; Escherichia coli CFT073; Escherichia coli 042; Escherichia coli str. K-12 substr. MG1655; Escherichia sp. TW09231; Escherichia sp. TW11588; Escherichia sp. TW11966; Escherichia sp. TW14265; Escherichia sp. TW14267; Escherichia sp. Z205; Escherichia coli O157:H7 str. Sakai; Escherichia albertii TW07627; Escherichia sp. TW11930; Escherichia sp. TW14264; Escherichia sp. TW14266; Escherichia coli O127:H6 str. E2348/69; Escherichia sp. RL325/96; Escherichia sp. TW14182. 50 samples. Type: Genome variation profiling by array.
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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.