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303 results for “habitat preference”

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zenodo36/100

Figure 4 in Assessments of environmental variables affecting the spatiotemporal distribution and habitat preferences of living Ostracoda (Crustacea) species in the Enez Lagoon Complex (Enez-Evros Delta, Turkey)

Figure 4. Salinity tolerance diagram of Ostracoda determined in the Enez lagoons.

opencc-by-4.0Dec 2018View details →
zenodo36/100

Figure 5 in Seasonal distribution and habitat use preference of Barking deer (Muntiacus vaginalis) in Murree-Kotli Sattian-Kahuta National Park, Punjab Pakistan

Figure 5. Slopes of occupied locations of Barking deer habitat.

opencc-by-4.0Dec 2022View details →
zenodo36/100

Figure 1 in Seasonal distribution and habitat use preference of Barking deer (Muntiacus vaginalis) in Murree-Kotli Sattian-Kahuta National Park, Punjab Pakistan

Figure 1. Distribution of Barking deer in study area.

opencc-by-4.0Dec 2022View details →
zenodo36/100

Figure 7 in Seasonal distribution and habitat use preference of Barking deer (Muntiacus vaginalis) in Murree-Kotli Sattian-Kahuta National Park, Punjab Pakistan

Figure 7. Aspects of occupied locations of Barking Deer in study area.

opencc-by-4.0Dec 2022View details →
zenodo36/100

Figure 3 in Seasonal distribution and habitat use preference of Barking deer (Muntiacus vaginalis) in Murree-Kotli Sattian-Kahuta National Park, Punjab Pakistan

Figure 3. Plant species recorded in summer from habitat of Barking deer.

opencc-by-4.0Dec 2022View details →
zenodo36/100

Figure 6 in Seasonal distribution and habitat use preference of Barking deer (Muntiacus vaginalis) in Murree-Kotli Sattian-Kahuta National Park, Punjab Pakistan

Figure 6. Coarse topography / habitat characteristics at occupied locations of Barking deer.

opencc-by-4.0Dec 2022View details →
zenodo36/100

Figure 4 in Seasonal distribution and habitat use preference of Barking deer (Muntiacus vaginalis) in Murree-Kotli Sattian-Kahuta National Park, Punjab Pakistan

Figure 4. Plant species recorded in winter from habitat of Barking deer.

opencc-by-4.0Dec 2022View details →
zenodo36/100

Fig. 8 in Ground beetles (Coleoptera: Carabidae) from the region of Cape Emine (Central Bulgarian Black sea coast). Part I. Taxonomic and zoogeographic structure, life forms, habitat and humidity preferences

Fig. 8. Ecological groups of carabids in terms of humidity (number of specimens).

opencc-by-4.0Jan 2015View details →
zenodo36/100

Fig. 6 in Ground beetles (Coleoptera: Carabidae) from the region of Cape Emine (Central Bulgarian Black sea coast). Part I. Taxonomic and zoogeographic structure, life forms, habitat and humidity preferences

Fig. 6. Proportions of the species according to the type of preferred habitat.

opencc-by-4.0Jan 2015View details →
zenodo36/100

Fig. 7 in Ground beetles (Coleoptera: Carabidae) from the region of Cape Emine (Central Bulgarian Black sea coast). Part I. Taxonomic and zoogeographic structure, life forms, habitat and humidity preferences

Fig. 7. Ecological groups of carabids in terms of humidity (number of species).

opencc-by-4.0Jan 2015View details →
zenodo36/100

Fig. 5 in Ground beetles (Coleoptera: Carabidae) from the region of Cape Emine (Central Bulgarian Black sea coast). Part I. Taxonomic and zoogeographic structure, life forms, habitat and humidity preferences

Fig. 5. Proportions of the species according to their habitat preferendum.

opencc-by-4.0Jan 2015View details →
zenodo36/100

Fig. 3 in Ground beetles (Coleoptera: Carabidae) from the region of Cape Emine (Central Bulgarian Black sea coast). Part I. Taxonomic and zoogeographic structure, life forms, habitat and humidity preferences

Fig. 3. Proportions of the carabid species by zoogeographical complexes.

opencc-by-4.0Jan 2015View details →
zenodo36/100

Fig. 2 in Ground beetles (Coleoptera: Carabidae) from the region of Cape Emine (Central Bulgarian Black sea coast). Part I. Taxonomic and zoogeographic structure, life forms, habitat and humidity preferences

Fig. 2. Proportions of the species among the tribes.

opencc-by-4.0Jan 2015View details →
zenodo36/100

Fig. 1 in Ground beetles (Coleoptera: Carabidae) from the region of Cape Emine (Central Bulgarian Black sea coast). Part I. Taxonomic and zoogeographic structure, life forms, habitat and humidity preferences

Fig. 1. Proportions of the species among the tribes.

opencc-by-4.0Jan 2015View details →
zenodo36/100

Figure 1 in Roost characteristics and habitat preferences of Indian flying fox (Pteropus giganteus) in urban areas of Lahore, Pakistan

Figure 1. GIS-based map of Jinnah garden showing roosts of Indian flying fox populations.

opencc-by-4.0Dec 2015View details →
zenodo36/100

FIG. 1 in Habitat preferences of Papilio alexanor Esper, [1800]: implications for habitat management in the Italian Maritime Alps

FIG. 1. — Papilio alexanor Esper,[1800].Photograph:Davide Piccoli.

opencc-zeroMar 2015View details →
zenodo36/100

Fig. 1 in The habitat preference of dung beetle species associated with elephant dung of the Malay Peninsula

Fig. 1. Map of all the localities where dung beetle sampling was carried out.

opencc-by-4.0May 2019View details →
zenodo36/100

Fig. 1 in Diel flight activity and habitat preference of dung beetles (Coleoptera: Scarabaeidae) in Peninsular Malaysia

Fig. 1. Location of the pitfall traps (black circle) in the study site.

opencc-by-4.0Dec 2014View details →
dryad36/100

Data from: Community-level canopy reflectance in grazed grasslands is linked to the habitat preferences of individual plant species

<p class="MsoNormal">Spectral remote sensing provides tools for biological monitoring and can be used to characterize habitat quality in grasslands. These data have been used to study the relationships between plant community composition and remotely sensed canopy reflectance in grazed grasslands. The study area is located on the island of Öland, Sweden, and the data were collected in grazed grasslands that represent a succession from previously arable fields to old semi-natural pastures. All included grassland sites have been assigned to three different classes of grassland age, defined by the grazing continuity in years: <span>young (5–14 years), intermediate-aged (15–49 years), and old (&gt;50 years).</span></p> <p class="MsoNormal">The plant community data consist of presences/absences for 100 vascular plant species in 104 (4 m × 4 m) sample plots positioned in open grassland vegetation. Information on species' habitat preferences is included and has been used to explain the associations between plant species' occurrences and the variation in community-level canopy reflectance.</p> <p class="MsoNormal">The remote sensing data consist of 317 hyperspectral bands in the wavelength regions 414–1322 nm, 1496–1797 nm, and 2050–2351 nm, and show the mean reflectance in each spectral band for the 104 sample plots. The main gradient in the hyperspectral data is characterized by contrasting reflectance values between bands located in the NIR spectra and bands located in the red, blue, and SWIR spectra.</p> <p class="MsoNormal">Grassland canopy reflectance was able to explain variation in the occurrences of individual plant species, particularly those with distinct habitat preferences. Species' habitat preferences indicated that vegetation reflectance in the red, blue, SWIR, and NIR spectra was linked to the plant-availability of mineral nitrogen. In contrast, species' phosphorus preferences showed stronger associations with reflectance in the green and red-edge spectra.</p>

opencc-zeroMay 2023View details →
dryad36/100

Habitat preferences and functional traits drive longevity in Himalayan high-mountain plants

<p>Plant lifespan has important evolutionary, physiological, and ecological implications related to population persistence, community stability, and resilience to ongoing environmental change impacts. Although biologists have long been puzzled over the extraordinary variation in plant lifespan and its causes, our understanding of interspecific variability in plant lifespan and the key internal and external factors influencing longevity remains limited. Here, we demonstrate the concurrent impacts of environmental, morphological, physiological, and anatomical constraints on interspecific variation in longevity among &gt;300 vascular dicot plant species naturally occurring at an elevation gradient (2800-6150 m) in the western Himalayas. First, we show that plant longevity (ranging from 1 to 100 years) is largely related to species' habitat preferences. Ecologically stressful habitats such as alpine and subnival host long-lived species, while productive ruderal and wetland habitats contain a higher proportion of shorter-lived species. Second, longevity is influenced by growth form with monocarpic forbs having the shortest lifespan and woody shrubs having the highest. Small-statured cushion plants with compact canopies and deep roots, most found on cold and infertile alpine and subnival soils, had a higher chance of achieving longevity. Third, plant traits reflecting plant adaptations to stress and disturbance affect interspecific differences in plant longevity. We show that longevity and growth are negatively correlated. Slow-growing species are those that have a higher chance of reaching a high age. Finally, higher longevity was associated with high leaf carbon and phosphorus, low root phosphorus and nitrogen, and with large bark-xylem ratio. Our findings suggest that plant longevity in high elevation is intricately determined by a combination of habitat preferences and growth form, as well as the plant growth rate and physiological processes.</p>

opencc-zeroMay 2023View details →

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Allen Brain Atlas

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Last verified 2026-04-30Open record

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DANDI Archive for NWB datasets

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Last verified 2026-04-30Open record

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.

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Last verified 2026-04-29Open record

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.

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neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record