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174 results for “Cape Region”
Data from: Pleistocene range dynamics in the eastern Greater Cape Floristic Region: a case study of the Little Karoo endemic Berkheya cuneata (Asteraceae)
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Data from: Are forest‐shrubland mosaics of the Cape Floristic Region an example of alternate stable states?
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Data from: Dated plant phylogenies resolve Neogene climate and landscape evolution in the Cape Floristic Region
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Biodiversity across the Greater Cape Floristic Region
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Evolutionary stability, landscape heterogeneity, and human land-usage shape population genetic connectivity in the Cape Floristic Region biodiversity hotspot
<p>As human-induced change eliminates natural habitats, it impacts genetic diversity and population connectivity for local biodiversity. The South African Cape Floristic Region (CFR) is the most diverse extratropical area for plant biodiversity, and much of its habitat is protected as a UNESCO World Heritage site. There has long been great interest in explaining the underlying factors driving this unique diversity, especially as much of the CFR is endangered by urbanization and other anthropogenic activity. Here, we use a population and landscape genetic analysis of SNP data from the CFR endemic plant <i>Leucadendron salignum</i> or "common sunshine conebush" as a model to address the evolutionary and environmental factors shaping the vast CFR diversity. We found that high population structure, along with relatively deeper and older genealogies, are characteristic of the southwestern CFR, whereas, low population structure and more recent lineage coalescence depicts the eastern CFR. Population network analyses show genetic connectivity is facilitated in areas of lower elevation and higher seasonal precipitation. These population genetic signatures corroborate CFR species-level patterns consistent with high Pleistocene biome stability and landscape heterogeneity in the southwest, but with coincident instability in the east. Finally, we also find evidence of human land-usage as a significant gene flow barrier, especially in severely-threatened lowlands where genetic connectivity has been historically the highest. These results help identify areas where conservation plans can prioritize protecting high genetic diversity threatened by contemporary human activities within this unique cultural UNESCO site.</p>
Figure 5 from: Thompson AC, Bazelet CS, Naskrecki P, Samways MJ (2017) Adapting the Dragonfly Biotic Index to a katydid (Tettigoniidae) rapid assessment technique: case study of a biodiversity hotspot, the Cape Floristic Region, South Africa. Journal of Orthoptera Research 26: 63-71. https://doi.org/10.3897/jor.26.14552
Figure 5 - Map of ecosystem threat statuses and the average KBI scores (i.e. KBI/Site) of each ecosystem.
Figure 3 from: Thompson AC, Bazelet CS, Naskrecki P, Samways MJ (2017) Adapting the Dragonfly Biotic Index to a katydid (Tettigoniidae) rapid assessment technique: case study of a biodiversity hotspot, the Cape Floristic Region, South Africa. Journal of Orthoptera Research 26: 63-71. https://doi.org/10.3897/jor.26.14552
Figure 3 - Distribution of South African and Cape Floristic Region katydid species among Tettigoniidae subfamilies.
Figure 2 from: Thompson AC, Bazelet CS, Naskrecki P, Samways MJ (2017) Adapting the Dragonfly Biotic Index to a katydid (Tettigoniidae) rapid assessment technique: case study of a biodiversity hotspot, the Cape Floristic Region, South Africa. Journal of Orthoptera Research 26: 63-71. https://doi.org/10.3897/jor.26.14552
Figure 2 - Composition of South African (A, C, E) and Cape Floristic Region (B, D, F) katydid assemblages as characterised by their distribution (A, B), mobility (C, D), and trophic level (E, F) relative to their IUCN threat status.
Figure 1 from: Thompson AC, Bazelet CS, Naskrecki P, Samways MJ (2017) Adapting the Dragonfly Biotic Index to a katydid (Tettigoniidae) rapid assessment technique: case study of a biodiversity hotspot, the Cape Floristic Region, South Africa. Journal of Orthoptera Research 26: 63-71. https://doi.org/10.3897/jor.26.14552
Figure 1 - Proportion of South African (A, C, E, G) and Cape Floristic Region (B, D, F, H) katydid assemblages as characterised by the KBI assessment criteria (Threat Status, Distribution, Trophic level and Mobility).
Figure 4 from: Thompson AC, Bazelet CS, Naskrecki P, Samways MJ (2017) Adapting the Dragonfly Biotic Index to a katydid (Tettigoniidae) rapid assessment technique: case study of a biodiversity hotspot, the Cape Floristic Region, South Africa. Journal of Orthoptera Research 26: 63-71. https://doi.org/10.3897/jor.26.14552
Figure 4 - Distribution of Katydid Biotic Index (KBI) among ecosystem threat statuses (mean ± s.e.).
Figure 4 from: Thompson AC, Bazelet CS, Naskrecki P, Samways MJ (2017) Adapting the Dragonfly Biotic Index to a katydid (Tettigoniidae) rapid assessment technique: case study of a biodiversity hotspot, the Cape Floristic Region, South Africa. Journal of Orthoptera Research 26: 63-71. https://doi.org/10.3897/jor.26.14552
Figure 4 - Distribution of Katydid Biotic Index (KBI) among ecosystem threat statuses (mean ± s.e.).
Figure 3 from: Thompson AC, Bazelet CS, Naskrecki P, Samways MJ (2017) Adapting the Dragonfly Biotic Index to a katydid (Tettigoniidae) rapid assessment technique: case study of a biodiversity hotspot, the Cape Floristic Region, South Africa. Journal of Orthoptera Research 26: 63-71. https://doi.org/10.3897/jor.26.14552
Figure 3 - Distribution of South African and Cape Floristic Region katydid species among Tettigoniidae subfamilies.
Figure 2 from: Thompson AC, Bazelet CS, Naskrecki P, Samways MJ (2017) Adapting the Dragonfly Biotic Index to a katydid (Tettigoniidae) rapid assessment technique: case study of a biodiversity hotspot, the Cape Floristic Region, South Africa. Journal of Orthoptera Research 26: 63-71. https://doi.org/10.3897/jor.26.14552
Figure 2 - Composition of South African (A, C, E) and Cape Floristic Region (B, D, F) katydid assemblages as characterised by their distribution (A, B), mobility (C, D), and trophic level (E, F) relative to their IUCN threat status.
Figure 1 from: Thompson AC, Bazelet CS, Naskrecki P, Samways MJ (2017) Adapting the Dragonfly Biotic Index to a katydid (Tettigoniidae) rapid assessment technique: case study of a biodiversity hotspot, the Cape Floristic Region, South Africa. Journal of Orthoptera Research 26: 63-71. https://doi.org/10.3897/jor.26.14552
Figure 1 - Proportion of South African (A, C, E, G) and Cape Floristic Region (B, D, F, H) katydid assemblages as characterised by the KBI assessment criteria (Threat Status, Distribution, Trophic level and Mobility).
Figure 5 from: Thompson AC, Bazelet CS, Naskrecki P, Samways MJ (2017) Adapting the Dragonfly Biotic Index to a katydid (Tettigoniidae) rapid assessment technique: case study of a biodiversity hotspot, the Cape Floristic Region, South Africa. Journal of Orthoptera Research 26: 63-71. https://doi.org/10.3897/jor.26.14552
Figure 5 - Map of ecosystem threat statuses and the average KBI scores (i.e. KBI/Site) of each ecosystem.
FIGURE 2 in Two new species of Oxalis (Oxalidaceae) from the Greater Cape Floristic Region
FIGURE 2. Geographic distribution of Oxalis carolina (circle) and O. filifoliolata (diamond).
Figure 8 from: Perissinotto R, Šípek P, Ball J (2014) Description of adult and third instar larva of Trichostetha curlei sp. n. (Coleoptera, Scarabaeidae, Cetoniinae) from the Cape region of South Africa. ZooKeys 428: 41-56. https://doi.org/10.3897/zookeys.428.7855
Figure 8 - Trichostetha bicolor feeding on flowers of Agathosma capensis (Rutaceae) at Saldanha Bay, September 2004 (Photo: L Clennell).
Figure 5 from: Perissinotto R, Šípek P, Ball J (2014) Description of adult and third instar larva of Trichostetha curlei sp. n. (Coleoptera, Scarabaeidae, Cetoniinae) from the Cape region of South Africa. ZooKeys 428: 41-56. https://doi.org/10.3897/zookeys.428.7855
Figure 5 - Trichostetha curlei sp. n., third instar larva. A Habitus of fully grown larva (length 41 mm) B cranium C epipharynx D Labio-maxillar complex and hypopharynx, dorsal aspect E labio-maxillar complex and hypopharynx, ventral aspect F metathoracic leg, lateral aspect H antenna (G dorsal aspect H ventral aspect). Scale bars: 1 mm (Photos: P Šípek).
Figure 4 from: Perissinotto R, Šípek P, Ball J (2014) Description of adult and third instar larva of Trichostetha curlei sp. n. (Coleoptera, Scarabaeidae, Cetoniinae) from the Cape region of South Africa. ZooKeys 428: 41-56. https://doi.org/10.3897/zookeys.428.7855
Figure 4 - Trichostetha curlei sp. n.: Male specimen in its natural habitat on the Elandsberg summit, November 2013 (Photo: JB Ball).
Figure 2 from: Perissinotto R, Šípek P, Ball J (2014) Description of adult and third instar larva of Trichostetha curlei sp. n. (Coleoptera, Scarabaeidae, Cetoniinae) from the Cape region of South Africa. ZooKeys 428: 41-56. https://doi.org/10.3897/zookeys.428.7855
Figure 2 - Trichostetha curlei sp. n.: Dorsal (A) and lateral (B) view of aedeagus (length 6.8 mm) (Photos: L Clennell).
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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.