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171 results for “Subregions”
FIGURE 6 in The first record of Ia io Thomas, 1902 (Mammalia: Chiroptera: Vespertilionidae) from the Sundaic Subregion, with a description of a new subspecies from peninsular Thailand
FIGURE 6. Principal component analysis based on 12 craniodental measurements of I. io peninsulata subsp. nov. and I. io io. Factor loading scores are in table 2.
FIGURES 9–10 in A review of Malipatilius (Hemiptera: Heteroptera: Rhyparochromidae), with a checklist of Lygaeoidea occurring in the Papuan Subregion
FIGURES 9–10. Male genitalia of Malipatilius horvathi Kondorosy & Schmidt, sp. nov., 9: pygophore; 10: paramere. FIGURES 11–16. Metepisternum of males of Malipatilius species: 11 M. forticornis, 12 M. horvathi, 13 M. microps, 14 M. bodisjuditae, 15 M. pilosus, 16 M. minutus
FIGURES 5–8 in A review of Malipatilius (Hemiptera: Heteroptera: Rhyparochromidae), with a checklist of Lygaeoidea occurring in the Papuan Subregion
FIGURES 5–8. Dorsal view of Malipatilius spp. 5 M. macrops Kondorosy & Schmidt, sp. nov.; 6 M. pilosus Kondorosy & Schmidt, sp. nov.; 7 M. minutus Kondorosy & Schmidt, sp. nov.; 8 M. szentivanyi Kondorosy & Schmidt, sp. nov.
FIGURES 1–4 in A review of Malipatilius (Hemiptera: Heteroptera: Rhyparochromidae), with a checklist of Lygaeoidea occurring in the Papuan Subregion
FIGURES 1–4. Dorsal view of Malipatilius spp. 1 M. horvathi Kondorosy & Schmidt, sp. nov.; 2 M. microps Kondorosy & Schmidt, sp. nov.; 3 M. bodisjuditae Kondorosy & Schmidt, sp. nov.; 4 M. batantensis Kondorosy & Schmidt, sp. nov.
Fig. 2 in Barcoding diatoms: evaluation of the V4 subregion on the 18S rRNA gene, including new primers and protocols
Fig. 2 Box-and-whisker plot of intraspecific and intrageneric (x-axis) genetic distances measured in uncorrected p-distances (y-axis). Thick black lines indicate median values, boxes represent upper and lower quartiles, whiskers indicate value ranges, circles represent outliers
Fig. 1 in Barcoding diatoms: evaluation of the V4 subregion on the 18S rRNA gene, including new primers and protocols
Fig. 1 Consensus secondary structure of the 18S locus (SSU rRNA gene) in diatoms (181 sequences), based on the Toxarium undulatum 18S secondary structure model as reference sequence. Upper-case letters indicate that nucleotides at corresponding positions are conserved in 98– 100% of sequences, lower-case letters indicate 90–98% conservation, dots 80–90% conservation, circles indicate greater than 20% variability.
Woody plant subregions of the Amazon forest
<ol> <li>The Amazon forest covers 7.5 million Km<sup>2</sup> in nine countries, hosts 25% of the global biodiversity and is a major contributor to the biogeochemical and climatic functioning of the Earth system. Despite its global importance, a regionalization of the Amazon tree flora is still lacking. Clear and data-driven delimitation of subregions is important for macroecological studies, to the identification of metacommunities, and is a requisite for conservation planning.</li> <li>We aimed at identifying and mapping plant species subregions and investigated their relationships with environmental, historical, and human correlates. We provide the first woody plant regionalization of the entire Amazon forest using a data-driven approach based on assemblage composition patterns.</li> <li>We compiled data on woody species composition from 301 assemblages based on species occurrences. We then used unconstrained ordination, interpolation and clustering techniques to identify and map discrete woody subregions. Hierarchical clustering analysis was conducted in order to investigate the relationships between the identified subregions. We used multinomial logistic regression model and deviance partitioning to investigate the influence of environmental, historical, and human factors on subregions distribution.</li> <li>We identified 13 woody subregions in the entire Amazon forest. The hierarchical subregion classification showed a broad Andean-Cratonic east-west division. Variation in subregions were explained jointly by human factors and spatial structure followed by environmental factors and spatial structure combined.</li> <li> <i>Synthesis.</i> Our woody plant subregions differed from WWF ecoregions and physiognomic-based maps, highlighting the importance of basing regionalizations on taxon-specific groups and confirming that vegetation maps should not be used as proxies to plant diversity subregions. Our findings also confirm the need for multiple and extensive protected areas in the Amazon forest. The relevance of current climate factors in our study alerts to a profound impact that climate change could have on the spatial organization of the Amazon flora. </li> </ol>
FIGURE 3 in A new species of Glischropus from the Indochinese Subregion (Mammalia: Chiroptera: Vespertilionidae)
FIGURE 3. Holotype of Glischropus bucephalus n. sp. (HNHM 2006.34.49.); (A) lateral view of left mandible (B) occlusal view of left upper and (C) right lower toothrows. Scale = 5 mm.
FIGURE 2 in A new species of Glischropus from the Indochinese Subregion (Mammalia: Chiroptera: Vespertilionidae)
FIGURE 2. Lateral view of skulls of (A) Glischropus bucephalus n. sp. (holotype, HNHM 2006.34.49., from Cambodia) (B) G. tylopus (holotype, BM(NH) 70.2.10.2, from Borneo) (C) G. javanus (holotype, RMNH 15323, from Java). Scale = 5 mm.
FIGURE 1 in A new species of Glischropus from the Indochinese Subregion (Mammalia: Chiroptera: Vespertilionidae)
FIGURE 1. Portrait of a living specimen of Glischropus bucephalus n. sp. (paratype, HNHM 2006.34.37., from Cambodia).
FIGURE 4 in A new species of Glischropus from the Indochinese Subregion (Mammalia: Chiroptera: Vespertilionidae)
FIGURE 4. Frontal view of left upper incisors of (A) Glischropus bucephalus n. sp. (holotype, HNHM 2006.34.49., from Cambodia) (B) G. tylopus (BM(NH) 10.4.5.68, from Borneo). Scale = 1 mm.
Checklist of cryptbiont assemblages in coral reef of two subregions of the Great Caribbean Sea using ARMS
<p><strong>*Corresponding autor: </strong>edlinguerra@gmail.com</p> <p>This checklist contains systematic information of specimens of the cryptobiont assemblages identified by experts of each Phyla and is a complementary material of the research “The use of ARMS to evaluate taxonomic diversity and spatial distribution cryptobiont assemblages of coral reefs in two subregions of the great Caribbean Sea”. The checklist contains 367 morphotypes, 246 species, 86 genera, two subfamily, 26 family, seven class and nine Phyla. For the present research, animals of the appropriate species and quality were selected and the minimum number required to obtain scientifically valid results, as well as anesthetized and deposited in National Collections: Colección Regional de Crustáceos de la Península de Yucatán (SEMARNAT number: YUC-CC-255-11), Colección Regional de Moluscos de la Península de Yucatán (SEMARNAT number: YUC. -INV-240-01-11), Colección Regional de Equinodermos de la Península de Yucatán (SEMARNAT number: DGVS-CC-307-18), Colección Regional de Ascidias de la Península de Yucatán (SEMARNAT number: DGVS-CC-306-18), Colección Regional de Briozoos de la Península de Yucatán (SEMARNAT number: DGVS-CC-308-18), Colección Regional de Cnidarios de la Península de Yucatán (SEMARMAT number: YUC-CC-254-11), Colección Regional de Policládidos de la Península de Yucatán (105 Collection CONABIO) and Colección Nacional del Phyla Porifera “Gerardo Green” of the Universidad Nacional Autónoma de México, Sisal, Mexico (UMDI-Sisal) and within accordance with scientific collection permits: PPF/DGOPA: 295/17, 300/17, 294/17, 293/17, PPF/DGOPA-076/19 issued by Mexico’s State Secretaria de Agricultura, Ganaderia, Desarrollo Rural, Pesca y Alimentación (SAGARPA).</p> <p><strong>CC-BY-NC-N</strong></p>
Scenario Data: Annual Demand and Supply per Subregion (NUTS3 regions)
<p>4 scenarios:</p> <p>DE, GA, DEE, DEG</p> <p>Regions included: NUTS3</p> <p>Scenario years: 2030, 2035, 2040, 2045, 2050</p> <p>Energetic scope: Electricity, hydrogen demand and supply per sector/subsector/application/technology</p> <p>Units: annual volumes in TWh, installed capacities in GW.</p>
Scenario Data: Annual Demand and Supply per Subregion (NSWPH regions)
<p>4 scenarios:</p> <p>DE, GA, DEE, DEG</p> <p>Regions included: BEXX, DEXX etc.</p> <p>Scenario years: 2030, 2035, 2040, 2045, 2050</p> <p>Energetic scope: Electricity, hydrogen demand and supply per sector/subsector/application/technology</p> <p>Units: annual volumes in TWh, installed capacities in GW.</p>
Functional Anatomical Examination of Axillary Sentinel Lymph Node Drainage in the Axillary Subregions in Early Breast Cancer
ClinicalTrials.gov study NCT01804309. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Subregion specific dynamics of striatal dopamine
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The flow of axonal information among hippocampal subregions: 2. Patterned stimulation sharpens routing of information transmission
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Woody plant subregions of the Amazon forest
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Immigration of Sogatella furcifera from the Greater Mekong Subregion into northern China revealed by 2b-RAD sequencing
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FIGURES 8–9 in Review of unreported shorefly genera of the tribe Scatellini from the New Zealand subregion (Diptera: Ephydridae) with description of three new species
FIGURES 8–9. Tennants Lake, the type locality of Haloscatella balioptera.
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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.