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28,952 results for “Distributed”
Fig. 5 in Distribution patterns of selected insect populations on their host plants - an ecological study
Fig. 5: Determination of the grade of aggregation (k) according to two independent methods (see text) and illustration of the relationship between k and xm: (a) greenflies (first method), (b) sap beetles (first method), (c) greenflies (second method), (d) sap beetles (second method).
Fig. 4 in Distribution patterns of selected insect populations on their host plants - an ecological study
Fig. 4: Mean values and standard deviations of the x/s2 ratios for a more detailed differentiation of m the animal distribution patterns. According to the results greenflies and sap beetles colonizing the upper parts of the nettle are distinguished by aggregated distribution patterns, whilst sap beetles residing on the lower parts of the nettle are characterized by a more regular distribution. Mealybugs tend to develop random distribution patterns.
Fig. 1 in Malacological mapping in Austria distribution of the Austrian spring snail Bythinella austriaca (v. F , 1857) in the federal state of Salzburg
Fig. 1: Geographical map of the federal state of Salzburg including all sample points with registered occurrence of the Austrian spring snail B. austriaca. Open circles mark sample locations published in literature, whereas filled circles represent sample points of own field investigations.
Figure 2. Summer core area delineation. The straight line with a in Demographic characteristics, seasonal range and habitat topography of Balkan chamois population in its southernmost limit of its distribution (Giona mountain, Greece)
Figure 2. Summer core area delineation. The straight line with a slope of –1 represents the random use of space within the population seasonal range. The curve that sags below the line of random use represents the clumped use of space. The summer core area can be defined at the point whose tangent has slope –1, e.g. 85%, that is, whose tangent is parallel to the line of random use. This is also the point of the curve that is furthest from the line of random use.
Figure 1 in Disjunct distribution of Szeptyckiella gen. nov. from New Caledonia and South China undermines the monophyly of Willowsiini (Collembola: Entomobryidae)
Figure 1. Szeptyckiella boulouparica sp. nov. (A) Habitus; (B) chaetae on Ant. IV; (C) Ant. III organ; (D) scales on Abd. III; (E) lateral bothriotrichum of Abd. III; (F) scales on manubrium. Scale bar: 0.5 mm, A; 10 µm, B–F.
Figure 4 in Disjunct distribution of Szeptyckiella gen. nov. from New Caledonia and South China undermines the monophyly of Willowsiini (Collembola: Entomobryidae)
Figure 4. Szeptyckiella sinelloides sp. nov. (A) Habitus; (B) base of Ant. (I) dorsal side; (C) mucro; (D) scales on head. Scale bar: 0.5 mm, A; 10 µm, B–D.
Figure 3 in Disjunct distribution of Szeptyckiella gen. nov. from New Caledonia and South China undermines the monophyly of Willowsiini (Collembola: Entomobryidae)
Figure 3. Szeptyckiella boulouparica sp. nov., abdominal chaetotaxy: (A) Abd. I–III; (B) Abd. IV; (C) Abd. V. Scale bar: 50 µm.
Experimental data to the publication "Genetic-optimised aperiodic code for distributed optical fibre sensors"
<p>The source data underlying Figs. 3-5 and Supplementary Figs. 6, 8-14 are provided as a Source Data file.</p>
Data from: Contemporary and future distributions of cobia, Rachycentron canadum
<p><b>Aim:</b> Climate change has influenced the distribution and phenology of marine species, globally. However, knowledge of the impacts of climate change are lacking for many species that support valuable recreational fisheries. Cobia (<i>Rachycentron canadum</i>) are the target of an important recreational fishery along the U.S. east coast that is currently the subject of a management controversy regarding allocation and stock structure. Further, the current and probable future distributions of this migratory species are unclear, further complicating decision-making. The objectives of this study are to better define the contemporary distribution of cobia along the U.S. east coast and to project potential shifts in distribution and phenology under future climate change scenarios.</p> <p><b>Location:</b> Chesapeake Bay and the U.S. east coast.</p> <p><b>Methods:</b> We developed a depth-integrated habitat suitability model using archival tagging data from cobia that were caught and tagged in Chesapeake Bay during summer months and coupled those data with high-resolution ocean models to project the contemporary and future distributions of cobia along U.S. east coast.</p> <p><b>Results:</b> During the winter months, suitable cobia habitat currently occurs in offshore waters off North Carolina and further south, whereas during the summer months, suitable habitat occurs in waters from Florida to southern New England. In warmer years, the availability of suitable habitat increases in northern latitudes. Under continued climate change over the next 40-80 years, suitable habitat is projected to shift northward and decrease over the shelf.</p> <p><b>Main conclusions:</b> Habitat distributions suggest cobia overwinter offshore and could inhabit waters further north during warmer months, into state jurisdictions that do not have strict management regulations for cobia. When waters are warmer, distributions are projected to shift poleward and seasonal migrations may begin earlier. These results can inform resource allocation discussions between fishery managers and resource users.</p>
Bioclimatic data for species distribution modelling in the Amazon Basin
<p>In this dataset, bioclimatic data regarding the Amazon Basin, in the near of the cities of Manaus and Manacapuru are available. There are 11 environmental data variables, referring to temperature, atmospheric pressure, concentration of pollutants and aerosols, such as carbon monoxide, ozone, carbon dioxide, among others. These were collected by the G-159 Gulfstream aircraft during its two periods of operation (IOP1 and IOP2), available in the GOAmazon (Green Ocean Amazon) project's data repository. A spatial interpolation methodology (linear barycentric interpolation) was applied to each variable, in order to obtain a larger area of data. The species occurrence data were collected from the repositories of the ICMBio (Instituto Chico Mendes de Conservação da Biodiversidade) Portal da Biodiversidade and GBIF (Global Biodiversity Information Facility), referring to the same date and location of the environmental data. <br> </p>
New fault slip distribution for the 2010 Mw 7.2 El Mayor Cucapah earthquake based on realistic 3D finite element inversions of coseismic displacements using space geodetic data
<p>The .csv files included in this repository contain the data used in the numerical model as input, while the .txt file is the output (slip on a regular grid of points on the fault planes from the joint inversion of the geodetic datasets.</p>
Data and scripts for the analysis of fruit flies' species distributions in Reunion island
<p>Data and scripts supporting the analyses of the joint species distributions of eight Tephritids species in La Réunion island.</p>
FIG. 9. — Distribution des stigmates d in Des exploitations intensives d'huîtres pendant l'Antiquité et le Moyen Âge sur le littoral atlantique français: l'exemple de Beauvoir-sur-Mer (Vendée)
FIG. 9. — Distribution des stigmates d'ouverture d'huîtres observés sur les huîtres de Beauvoir-sur-Mer. Abréviation: N, nombre de valves étudiées (C. Dupont, CNRS).
FIG. 18 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 18. — Ventral view of the skull of Molossus pretiosus Miller, 1902. Note the crest between the occipital and the basisphenoid pits. Scale bar: 1 mm.
FIG. 13 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 13. — Molossus molossus (Pallas, 1766) skull: A, dorsal view; B, frontal view; C, ventral view; D, posterior view; E, lateral view. Scale bar: 1 mm.
FIG. 14 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 14. — Molossus molossus (Pallas, 1766). Photo courtesy of Dr Marco A. R. Mello (https://marcoarmello.wordpress.com).
FIG. 12 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 12. — Geographic range of Molossus rufus (E. Geoffroy, 1805) in Brasil. The numbers represent the localities described in Appendix 1.
FIG. 10 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 10. — Molossus rufus (E. Geoffroy, 1805). Photo courtesy of Dr Marco A. R. Mello (https://marcoarmello.wordpress.com).
FIG. 11 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 11. — Skull of Molossus rufus E. Geoffroy, 1805: A, dorsal view; B, posterior view; C, lateral view; D, frontal view. Scale bar: 1 mm.
FIG. 2 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 2. — Variable characters in skull morphology within Molossus E. Geoffroy, 1805 (Pallas, 1766): A, B, lateral views; C, D, ventral views; E, F, posterior view; H, G, frontal view. Numbers represents characters described in the text: 1, skull robustness; 2, sagittal crest; 3, basioccipital pits; 4, projection of the canines; 5, lambdoidal crest and occipital complex; 6, mastoid process; 7, rostrum shape; 8, infraorbital foramen; 9, upper incisors; 10, nasal process. Not to scale.
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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.