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4,462 results for “South America”
FIGURE 6 in Revision of the genus Corythalia C.L. Koch, 1850, part 1: Diagnosis and new species from South America (Araneae: Salticidae: Salticinae: Euophryini)
FIGURE 6. Corythalia latipes, specimens from Bahia, Brazil. A–B Male neotype, left palp (A ventral view; B retrolateral view). C–E Female F-1, epigyne (C ventral view; D vulva, dorsal view; E schematic course of internal duct system).
FIGURE 5 in Revision of the genus Corythalia C.L. Koch, 1850, part 1: Diagnosis and new species from South America (Araneae: Salticidae: Salticinae: Euophryini)
FIGURE 5. Corythalia latipes, colour illustration of male holotype, dorsal view. Reproduced from C.L. Koch (1846, fig. 1269).
FIGURE 5 in Acanthemblemaria aceroi, a new species of tube blenny from the Caribbean coast of South America with notes on Acanthemblemaria johnsoni (Teleostei Chaenopsidae)
FIGURE 5. CT-scans of Acanthemblemaria johnsoni, SIO 06-274. A) Lateral view of entire specimen; B) Lateral view of head; C) Dorsal view of head; D) Isolated palatine bone.
Data from: The Magellanic Province and its fish fauna (South America): several provinces or one?
Aim: We assessed the validity of the division of the Magellanic Province into the four provinces as proposed by Briggs and Bowen (2012): Southern Chile, Tierra del Fuego, Southern Argentina and Falkland (Malvinas) Islands. We aimed to 1) present an up to date list of the fishes from the region known as "Magellanic Province", 2) analyze the specific richness of fishes in the Atlantic and Pacific sectors and their degree of endemism, 3) evaluate statistically the validity of the three Provinces proposed for the Atlantic sector Location: Southern tip of the American continent at latitudes higher than 40ºS in the Atlantic as well as in the Pacific Oceans. Methods: The list of fishes was prepared by consulting more than 140 sources, many related to observations resulting from research cruises, although two ichthyological collections and two ichthyological websites were also used. The South American species with distributions extending outside of the area corresponding to the Magellanic Province, and all cosmopolitan species, were excluded of endemism analyses. For analyzing fish distributions in the Atlantic sector, the data employed are from eight research cruises carried out from 1978 to 2006 from 37º to 59º South. A total of 523 fishing trawls have been analyzed, grouped into cell of 1º x 1º cells. The species composition of each cell was evaluated by multivariate analysis (nonmetric multidimensional scaling, cluster, and similarity analyses). Results: The percentage of endemism in each sector (Atlantic 2.87% and Pacific 2.87%) is smaller than the endemism common to both sectors (9.2%). The total of endemic species in the Province is 14.94%, which is bigger than the 10% indicated as the lower limit for defining a biogeographic province suggested by Briggs (1974). In addition, multivariate analyses does not show differences in the species composition, neither between Falkland (Malvinas) Islands and "Southern Argentina" nor between the latter and Tierra del Fuego. Main conclusions: The ichthyological data indicate only one biogeographic province in the region not four as previously posited.
Data from: Strangers in a strange land: Ecological dissimilarity to metatherian carnivores may partly explain early colonization of South America by Cyonasua-group procyonids
It was once thought that the endemic carnivorous mammals of South America, the metatherian sparassodonts, were driven extinct by North American carnivores through competitive exclusion. However, sparassodonts went extinct before most groups of carnivorans entered South America; only the endemic Cyonasua-group procyonids (Cyonasua and Chapalmalania), which immigrated to South America nearly four million years earlier than other carnivorans, significantly overlapped with sparassodonts in time. In this study, we examine the functional morphology of the dentition of Cyonasua and Chapalmalania through quantitative analysis to determine the dietary habits of these taxa and the degree to which they may have ecologically overlapped sparassodonts and large predatory Neogene didelphimorphians. We find Cyonasua and Chapalmalania to be more carnivorous than extant procyonids other than Bassariscus, in agreement with previous studies, but more omnivorous than most other carnivorans and all meat-eating South American metatherians, including sparassodonts. The extreme ecological dissimilarity between Cyonasua-group procyonids and members of the endemic South American predator guild may explain why procyonids were able to successfully establish themselves in South America several million years earlier than most other northern mammals (including all other carnivorans): they moved into a previously unoccupied ecological niche (large omnivore) and avoided direct competition with incumbent native species, a situation similar to that documented in historical cases of biological invasion. The omnivorous diets and climbing/swimming abilities of procyonids may have increased their chances for a successful over-water dispersal relative to other carnivorans, further favoring their successful establishment in South America.
GeoVectors-South-America-location (v0.1)
<p><strong>Description</strong></p> <p>The GeoVectors corpus is a comprehensive large-scale linked open corpus of OpenStreetMap (https://www.openstreetmap.org/) entity embeddings that provides latent representations of over 980 million entities. The GeoVectors capture the semantic and geographic similarities of OpenStreetMap entities and make them directly accessible to machine learning applications. The "-tags" datasets provide embeddings that capture the semantic similarities of OpenStreetMap entities. The "-location" datasets provide the geographic similarities.</p> <p><strong>Contents</strong></p> <p>This dataset was derived from an OpenStreetMap snapshot that was taken on November 10, 2020 (© OpenStreetMap contributors).</p> <p>We provide the GeoVectors in region-specific subsets. This subset contains location-embeddings for the region "South-America" including the following countries:</p> <ul> <li>Argentina</li> <li>Bolivia</li> <li>Brazil</li> <li>Chile</li> <li>Colombia</li> <li>Ecuador</li> <li>Paraguay</li> <li>Peru</li> <li>Suriname</li> <li>Uruguay</li> <li>Venezuela</li> </ul> <p><strong>File format</strong></p> <p>The embeddings are provided in the tab-separated values (tsv) format. Each row contains the embedding of a single OpenStreetMap entity. The first column contains the OpenStreetMap type and the second column contains the OpenStreetMap id of the respective entity. The type can either be node (n), way (w), or relation (r). The remaining columns represent the dimensions of the embedding space. (See also header.tsv)</p> <p><strong>Further information:</strong></p> <p>For further information, please visit <a href="http://geovectors.l3s.uni-hannover.de">http://geovectors.l3s.uni-hannover.de</a></p> <p><strong>Funding</strong>:</p> <p>This work was partially funded by DFG, German Research Foundation (“WorldKG", DE 2299/2-1), the Federal Ministry of Education and Research (BMBF), Germany (“Simple-ML", 01IS18054), the Federal Ministry for Economic Affairs and Energy (BMWi), Germany (“d-E-mand", 01ME19009B), and the European Commission (EU H2020, “smashHit", grant-ID 871477).</p>
GeoVectors-South-America-tags (v1.0)
<p><strong>Description</strong></p> <p>The GeoVectors corpus is a comprehensive large-scale linked open corpus of OpenStreetMap (https://www.openstreetmap.org/) entity embeddings that provides latent representations of over 980 million entities. The GeoVectors capture the semantic and geographic similarities of OpenStreetMap entities and make them directly accessible to machine learning applications. The "-tags" datasets provide embeddings that capture the semantic similarities of OpenStreetMap entities. The "-location" datasets provide the geographic similarities.</p> <p><strong>Contents</strong></p> <p>This dataset was derived from an OpenStreetMap snapshot that was taken on November 10, 2020 (© OpenStreetMap contributors).</p> <p>We provide the GeoVectors in region-specific subsets. This subset contains tag-embeddings for the region "South-America" including the following countries:</p> <ul> <li>Argentina</li> <li>Bolivia</li> <li>Brazil</li> <li>Chile</li> <li>Colombia</li> <li>Ecuador</li> <li>Paraguay</li> <li>Peru</li> <li>Suriname</li> <li>Uruguay</li> <li>Venezuela</li> </ul> <p><strong>File format</strong></p> <p>The embeddings are provided in the tab-separated values (tsv) format. Each row contains the embedding of a single OpenStreetMap entity. The first column contains the OpenStreetMap type and the second column contains the OpenStreetMap id of the respective entity. The type can either be node (n), way (w), or relation (r). The remaining columns represent the dimensions of the embedding space. (See also header.tsv)</p> <p><strong>Further information:</strong></p> <p>For further information, please visit <a href="http://geovectors.l3s.uni-hannover.de">http://geovectors.l3s.uni-hannover.de</a></p> <p><strong>Funding</strong>:</p> <p>This work was partially funded by DFG, German Research Foundation (“WorldKG", DE 2299/2-1), the Federal Ministry of Education and Research (BMBF), Germany (“Simple-ML", 01IS18054), the Federal Ministry for Economic Affairs and Energy (BMWi), Germany (“d-E-mand", 01ME19009B), and the European Commission (EU H2020, “smashHit", grant-ID 871477).</p>
FIGURE 51. Male genitalia, ventral view. A in A revision of the bee genus Augochlora Smith (Hymenoptera; Apoidea) in Southern South America
FIGURE 51. Male genitalia, ventral view. A) Augochlora daphnis Smith, B) Augochlora perimelas Cockerell, C) Augochlora scabrata sp. nov., D) Augochlora braziliensis Vachal, E) Augochlora cydippe (Schrottky), F) Augochlora nausicaa (Schrottky), G) Augochlora esox Vachal, H) Augochlora atlantica sp. nov., I) Augochlora laevicarinata sp. nov., J) Augochlora phoemonoe (Schrottky), K) Augochlora mendax sp. nov., L) Augochlora iphigenia Holmberg. Scale bar: 0.5 mm, all at same scale.
FIGURE 50. Male genitalia, ventral view. A in A revision of the bee genus Augochlora Smith (Hymenoptera; Apoidea) in Southern South America
FIGURE 50. Male genitalia, ventral view. A) Augochlora genalis sp. nov., B) Augochlora foxiana Cockerell, C) Augochlora francisca Schrottky, D) Augochlora mulleri Cockerell, E) Augochlora seitzi Cockerell, F) Augochlora pyrgo (Schrottky), G) Augochlora thusnelda (Schrottky), H) Augochlora caerulior Cockerell, I) Augochlora hestia sp. nov. Scale bar: 0.5 mm, all at same scale.
FIGURE 47 in A revision of the bee genus Augochlora Smith (Hymenoptera; Apoidea) in Southern South America
FIGURE 47. Male of Augochlora iphigenia Holmberg. A) habitus, B) dorsal view of metasoma, C) frontal view of head, D) dorsal view of mesosoma. Scale bar: 1.0 mm, all at same scale.
FIGURE 48 in A revision of the bee genus Augochlora Smith (Hymenoptera; Apoidea) in Southern South America
FIGURE 48. Female of Augochlora mendax sp. nov. A) habitus, B) frontal view of head, C) dorsal view of mesosoma, D) dorsal view of metasoma. Scale bar: 1.0 mm, all at same scale.
FIGURE 45 in A revision of the bee genus Augochlora Smith (Hymenoptera; Apoidea) in Southern South America
FIGURE 45. Male of Augochlora thusnelda (Schrottky). A) habitus, B) frontal view of head, C) dorsal view of mesosoma, D) dorsal view of metasoma. Scale bar: 1.0 mm, all at same scale.
FIGURE 43 in A revision of the bee genus Augochlora Smith (Hymenoptera; Apoidea) in Southern South America
FIGURE 43. Male of Augochlora seitzi Cockerell. A) habitus, B) frontal view of head, C) dorsal view of mesosoma, D) dorsal view of metasoma. Scale bar: 1.0 mm, all at same scale.
FIGURE 46 in A revision of the bee genus Augochlora Smith (Hymenoptera; Apoidea) in Southern South America
FIGURE 46. Female of Augochlora iphigenia Holmberg. A) habitus, B) dorsal view of metasoma, C) frontal view of head, D) dorsal view of mesosoma. Scale bar: 1.0 mm, all at same scale.
FIGURE 44 in A revision of the bee genus Augochlora Smith (Hymenoptera; Apoidea) in Southern South America
FIGURE 44. Female of Augochlora thusnelda (Schrottky). A) habitus, B) frontal view of head, C) dorsal view of mesosoma, D) dorsal view of metasoma. Scale bar: 1.0 mm, all at same scale.
FIGURE 42 in A revision of the bee genus Augochlora Smith (Hymenoptera; Apoidea) in Southern South America
FIGURE 42. Female of Augochlora seitzi Cockerell. A) habitus, B) frontal view of head, C) dorsal view of mesosoma, D) dorsal view of metasoma. Scale bar: 1.0 mm, all at same scale.
FIGURE 49 in A revision of the bee genus Augochlora Smith (Hymenoptera; Apoidea) in Southern South America
FIGURE 49. Male of Augochlora mendax sp. nov. A) habitus, B) frontal view of head, C) dorsal view of mesosoma, D) dorsal view of metasoma. Scale bar: 1.0 mm, all at same scale.
FIGURE 39 in A revision of the bee genus Augochlora Smith (Hymenoptera; Apoidea) in Southern South America
FIGURE 39. Male of Augochlora pyrgo (Schrottky). A) habitus, B) frontal view of head, C) dorsal view of mesosoma, D) dorsal view of metasoma. Scale bar: 1.0 mm, all at same scale.
FIGURE 41 in A revision of the bee genus Augochlora Smith (Hymenoptera; Apoidea) in Southern South America
FIGURE 41. Male of Augochlora scabrata sp. nov. A) habitus, B) frontal view of head, C) dorsal view of mesosoma, D) dorsal view of metasoma. Scale bar: 1.0 mm, all at same scale.
FIGURE 38 in A revision of the bee genus Augochlora Smith (Hymenoptera; Apoidea) in Southern South America
FIGURE 38. Female of Augochlora pyrgo (Schrottky). A) habitus, B) frontal view of head, C) dorsal view of mesosoma, D) dorsal view of metasoma. Scale bar: 1.0 mm, all at same 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.