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148 results for “foothills”
Fig. 7 in Xiphocentronidae (Trichoptera: Psychomyioidea) from the Andean foothills: first species of Machairocentron and Xiphocentron described in the Peruvian Amazon
Fig. 7. Xiphocentron matsigenka sp. nov., holotype, male genitalia (MUSM-ENT-0320566). A. Lateral view, with detail of paraproct. B. Dorsal view. C. Ventral view. D. Phallus, dorsal and lateral views, respectively. E. Phallus in full length, dorsal view.
Fig. 6 in Xiphocentronidae (Trichoptera: Psychomyioidea) from the Andean foothills: first species of Machairocentron and Xiphocentron described in the Peruvian Amazon
Fig. 6. Xiphocentron harakbut sp. nov.,holotype, male genitalia (MUSM-ENT-0320564). A. Lateral view, with detail of paraproct. B. Dorsal view. C. Ventral view. D. Phallus, dorsal and lateral views, respectively. E. Left inferior appendage, photograph, lateroventral view.
Daily landscape-level snow cover percent data from (Rich, et al 2013) TLFS, IMVT, and SDOT sitse, in the northern foothills of the Brooks Range, Alaska,spring 2011 to 2014.
Daily landscape-level snow cover percent data from Toolik Lake Field Station (TFS), Imnavait (IMVT), and the Sagavanirktok River DOT site (SDOT), in the northern foothills of the Brooks Range, Alaska. Data collected from May to early June 2011 to 2014.
Morphometric trait measurements of Arctic char in foothill lakes of arctic Alaska
<p class="CxSpFirst">Polymorphism facilitates coexistence of divergent morphs (e.g., phenotypes) of the same species by minimizing intraspecific competition, especially when resources are limiting. Arctic char <i>(Salvelinus sp</i>.) are a Holarctic fish often forming morphologically, and sometimes genetically, divergent morphs. In this study, we assessed the morphological and genetic diversity and divergence of 263 individuals from seven populations of arctic char with varying length-frequency distributions across two distinct groups of lakes in northern Alaska. Despite close geographic proximity, each lake group occurs on landscapes with different glacial ages and surface water connectivity, and thus were likely colonized by fishes at different times. Across lakes, a continuum of physical (e.g., lake area, maximum depth) and biological characteristics (e.g., primary productivity, fish density) exists, likely contributing to characteristics of present-day char populations. Although some lakes exhibit bimodal size distributions, using model-based clustering of morphometric traits corrected for allometry, we did not detect morphological differences within and across char populations. Genomic analyses using 15,934 SNPs obtained from genotyping-by-sequencing demonstrated differences among lake groups related to historical biogeography, but within lake groups and within individual lakes, genetic differentiation was not related to total body length. We used PERMANOVA to identify environmental and biological factors related to observed char size structure. Significant predictors included water transparency (i.e., a primary productivity proxy), char density (fish·ha<sup>-1</sup>), and lake group. Larger char occurred in lakes with greater primary production and lower char densities, suggesting less intraspecific competition and resource limitation. Thus, char populations in more productive and connected lakes may prove more stable to environmental changes, relative to food-limited and closed lakes, if lake productivity increases concomitantly. Our findings provide some of the first descriptions of genomic characteristics of char populations in arctic Alaska, and offer important consideration for the persistence of these populations for subsistence and conservation.</p>
Рис. 2. ЧисΛенность кабанов в разΛичные гоΔы на 10 км маршрута in The ecology and distribution of wild boars (Sus scrofa Linnaeus, 1758) in the foothills of the Martakert Region of the Republic of Artsakh
Рис. 2. ЧисΛенность кабанов в разΛичные гоΔы на 10 км маршрута
Рис. 1. Карта района иссΛеΔований: 1 — Тонашен; 2 — Варнкатаг; 3 — Магавуз in The ecology and distribution of wild boars (Sus scrofa Linnaeus, 1758) in the foothills of the Martakert Region of the Republic of Artsakh
Рис. 1. Карта района иссΛеΔований: 1 — Тонашен; 2 — Варнкатаг; 3 — Магавуз
Fig. 2 in The ecology and distribution of wild boars (Sus scrofa Linnaeus, 1758) in the foothills of the Martakert Region of the Republic of Artsakh
Fig. 2. The number of wild boars in different years in 10 km route
Fig. 1 in Beetle communities (Insecta: Coleoptera) of Beech Forests at the Foothills of the Volcanic Carpathians, Ukraine
Fig. 1. Map showing the locations of the traps in the Kamianytsia forestry, Ukraine.
Fig. 4 in Beetle communities (Insecta: Coleoptera) of Beech Forests at the Foothills of the Volcanic Carpathians, Ukraine
Fig. 4. Species accumulation curve.
Fig. 2 in Beetle communities (Insecta: Coleoptera) of Beech Forests at the Foothills of the Volcanic Carpathians, Ukraine
Fig. 2. Scheme and general view of the window combined trap (polytrap).
Fig. 3 in Beetle communities (Insecta: Coleoptera) of Beech Forests at the Foothills of the Volcanic Carpathians, Ukraine
Fig. 3. General view of research plots.
Morphometric trait measurements of Arctic char in foothill lakes of arctic Alaska
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Wind River Experimental Forest site, station Washington Region 4, East Olympic Cascades Foothills, study of Palmer Drought Severity Index in units of dimensionless on a monthly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Wind River Experimental Forest (WIN) contains Palmer Drought Severity Index measurements in dimensionless units and were aggregated to a monthly timescale.
Wind River Experimental Forest site, station Washington Region 4, East Olympic Cascades Foothills, study of Palmer Drought Severity Index in units of dimensionless on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Wind River Experimental Forest (WIN) contains Palmer Drought Severity Index measurements in dimensionless units and were aggregated to a yearly timescale.
FIGURE 5 in A new species of Litoria (Amphibia: Anura: Hylidae) from the foothills of the Foja Mountains, Papua Province, Indonesia
FIGURE 5. Map of New Guinea showing the known distribution of Litoria gasconi sp. nov. and Litoria multiplica.
FIGURE 4 in A new species of Litoria (Amphibia: Anura: Hylidae) from the foothills of the Foja Mountains, Papua Province, Indonesia
FIGURE 4. Primary foothill rainforest around Marina Valen Village, Papua Province Indonesia, type locality of Litoria gasconi sp. nov.
FIGURE 1 in A new species of Litoria (Amphibia: Anura: Hylidae) from the foothills of the Foja Mountains, Papua Province, Indonesia
FIGURE 1. Dorsal (A) and ventral (B) views of holotype MZB Amph. 15839 of Litoria gasconi sp. nov. (scale = 10 mm), (C) lateral view of head of holotype MZB Amph. 15839 (scale = 5 mm), (D) paratype MZB amph 12036 (SJR 9805) in life showing bilobed dermal fold below vent and orange thigh and axillary colourations.
FIGURE 2 in A new species of Litoria (Amphibia: Anura: Hylidae) from the foothills of the Foja Mountains, Papua Province, Indonesia
FIGURE 2. Paratopotype of Litoria gasconi sp. nov. MZB Amph. 15840 (SJR 6019) (top) photographed in life at night, note distinct dermal folds on posterior edge of forearm, and Litoria multiplica (bottom) Tualapa, Southern Highlands Province, Papua New Guinea, in life, note black ventral patches and blue groin and thighs. All photographs by S. J. Richards.
FIGURE 6 in A new species of glassfrog, genus Hyalinobatrachium (Anura: Centrolenidae), from the Caribbean foothills of Costa Rica
FIGURE 6. Bayesian phylogram showing phylogenetic relationships of Hyalinobatrachium dianae and other Central American species of Hyalinobatrachium for which sequences were available. Bayesian posterior probability values (>0.9) are shown above the branches.
FIGURE 7 in A new species of glassfrog, genus Hyalinobatrachium (Anura: Centrolenidae), from the Caribbean foothills of Costa Rica
FIGURE 7. Audiospectrograms of two advertisement calls from the male holotype of Hyalinobtrachium dianae.
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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.