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60 results for “Africa Assessment”
Figures 5-10 from: Heraty JM, Mbanyana N, Van Noort S (2020) A new species of Eucharissa Westwood (Eucharitidae) from South Africa, with an evaluation of the importance of pupae for assessing relationships in these ant parasitoids. Journal of Hymenoptera Research 79: 43-55. https://doi.org/10.3897/jhr.79.56042
Figures 5-10 Eucharissa insolita sp. nov. 5–8 male: 5 head and mesosoma in place in cocoon 6 adult in place in cocoon 7 exuvium of body and host ant remains 8 exuvium cap from face and antenna, anterior 9 planidial exuvium taken from last-instar larva 10 last instar larva, lateral. Abbreviations: dlp2, dorsolateral process; T, tergum.
Figures 1-4 from: Heraty JM, Mbanyana N, Van Noort S (2020) A new species of Eucharissa Westwood (Eucharitidae) from South Africa, with an evaluation of the importance of pupae for assessing relationships in these ant parasitoids. Journal of Hymenoptera Research 79: 43-55. https://doi.org/10.3897/jhr.79.56042
Figures 1-4 Eucharissa insolita sp. nov., male 1 head and mesosoma, anterior 2 habitus, lateral 3 lower face, frontal 4 habitus, dorsal.
Supplementary material 1 from: Bitani N, Shivambu TC, Shivambu N, Downs CT (2022) An impact assessment of alien invasive plants in South Africa generally dispersed by native avian species. NeoBiota 74: 189-207. https://doi.org/10.3897/neobiota.74.83342
Table S1
Supplementary material 2 from: Bitani N, Shivambu TC, Shivambu N, Downs CT (2022) An impact assessment of alien invasive plants in South Africa generally dispersed by native avian species. NeoBiota 74: 189-207. https://doi.org/10.3897/neobiota.74.83342
Table S2
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 1 in A floristic assessment of grassland diversity loss in South Africa
Figure 1. Location of the 18 study sites in the Grassland Biome of South Africa. Land-use transformation at localities: Agriculture, afforestation: 1, 2, 3; field margins: 4, 5, 6; abandoned fields: 7, 8, 9; urban, green space: 10, 11, 12; peri-urban: 13, 14, 15; mine rehabilitation: 16, 17, 18.
Use of Antiretroviral (ARV) Drug Levels in Dried Blood Spots (DBS) to Assess and Manage ART Adherence in South Africa
ClinicalTrials.gov study NCT04333498. IPD Sharing: NO. Countries: 2. Publications: 0.
An impact assessment of the SADC FTA on bilateral trade relations between South Africa and Zimbabwe
<p>The Journal paper uses the Gravity Model of International Trade to investigate the impact of the Southern African Development Comuunity (SADC) Free Trade Area (FTA) on trade between South Africa and Zimbabwe. The study found out that South Africa gained more in trade by 88.4% if the country used the SADC FTA than the 1964 Bilateral Trade Agreement which was between South Africa and Zimbabwe. In addition, there was trade diversion of 176% for Zimbabwe when trading in SADC FTA. Furthermore the paper showed that South Africa will in future trade more with countries such as the Seychelles and Angola whilst Zimbabwe will gain more in trade if it trades with South Africa. The paper recommends that there is need for Zimbabwe and South Africa to expand trade with SADC Countries in order to promote intra-regional trade.</p>
Human Challenge With Live-attenuated Rotavirus to Assess Next-generation Rotavirus Vaccines in Africa
ClinicalTrials.gov study NCT04658914. IPD Sharing: YES. Countries: 1. Publications: 0.
An impact assessment of the SADC FTA on bilateral trade relations between South Africa and Zimbabwe
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Distribution. Known only in NW Zimbabwe (Lutope-Ngolangola Gorge S of Zambezi Escarpment) and NE South Africa (Limpopo Province). Specific status ofsimilarly looking populations throughout the rest of southern Africa (Zambia, Malawi, Mozambique, Zimbabwe, and Botswana) has not been assessed, and additional sampling is needed. in Rhinolophidae
Distribution. Known only in NW Zimbabwe (Lutope-Ngolangola Gorge S of Zambezi Escarpment) and NE South Africa (Limpopo Province). Specific status ofsimilarly looking populations throughout the rest of southern Africa (Zambia, Malawi, Mozambique, Zimbabwe, and Botswana) has not been assessed, and additional sampling is needed.
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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.