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1,558 results for “Southern Africa”
The name of the game: Palaeoproteomics and radiocarbon dates further refine the presence and dispersal of caprines in Eastern and Southern Africa
<p><span>We report the first large-scale palaeoproteomics research on eastern and southern African zooarchaeological samples, thereby refining our understanding of early caprine (sheep and goat) pastoralism in Africa. Assessing caprine introductions is a complicated task because of their skeletal similarity to endemic wild bovid species and the sparse and fragmentary state of relevant archaeological remains. Palaeoproteomics has previously proved effective in clarifying species attributions in African zooarchaeological materials, but few comparative protein sequences of wild bovid species have been available. Using newly generated collagen type I sequences for wild species, as well as previously published sequences, we assess species attributions for elements originally identified as caprine or "unidentifiable bovid" from seventeen eastern and southern African sites that span seven millennia. We identified over 70% of the archaeological remains and the direct radiocarbon dating of domesticate specimens allows refinement of the chronology of caprine presence in both African regions. These results thus confirm earlier occurrences in eastern Africa and the systematic association of domesticated caprines with wild bovids at all archaeological sites. The combined biomolecular approach highlights repeatability and accuracy of the methods for conclusive contribution in species attribution of archaeological remains in dry African environments.</span></p>
Fig. 5 in The Smicronychini of southern Africa (Coleoptera, Curculionidae): Review of the tribe and description of 12 new species
Fig. 5 (opposite page). Penis of Smicronyx from southern Africa, in dorsal (left) and lateral (right) view. A. Sharpia madibai sp. nov., ♂, holotype (SAMC). B. Afrosmicronyx cycnii sp. nov., ♂, holotype (SAMC). C. Afrosmicronyx louwi sp. nov., ♂, holotype (SAMC). D. Afrosmicronyx marshalli sp. nov., ♂, holotype (SANC). E. Afrosmicronyx nebulosipennis sp. nov., ♂, holotype (BMNH). F. Smicronyx similis sp. nov., ♂, holotype (SANC). G. Smicronyx pseudocoecus sp. nov., ♂, holotype (SAMC). H. Smicronyx paucisquamis sp. nov., ♂, holotype (SAMC). I. Smicronyx fallax (Gyllenhal, 1836), ♂, neotype (NHRS). J. Smicronyx australis sp. nov., ♂, holotype (SAMC). K. Smicronyx pauperculus Wollaston, 1864, ♂, specimen from Tanzania. L. Smicronyx san sp. nov., ♂, holotype (SAMC), bred from Chironia baccifera L. M. Smicronyx drakensbergensis sp. nov., ♂, holotype (TMSA). N. Smicronyx zonatus Haran, 2018, ♂, paratype (CBGP), specimen from the Western Cape Province of the Republic of South Africa. O. Smicronyx lutulentus Dietz, 1894, ♂ (CBGP). P. Smicronyx namibicus Haran, 2018, ♂, holotype (MNHN), specimen from Tanzania. Scale bars: 100 μm.
Fig. 3 in The Smicronychini of southern Africa (Coleoptera, Curculionidae): Review of the tribe and description of 12 new species
Fig. 3. Head and prothorax in lateral view of species of Smicronyx from southern Africa (Part 1). A. Sharpia madibai sp. nov., ♂, holotype (SAMC). B. Afrosmicronyx cycnii sp. nov., ♂, holotype (SAMC). C. Afrosmicronyx louwi sp. nov., ♂, holotype (SAMC). D. Afrosmicronyx marshalli sp. nov., ♂, holotype (SANC). E. Afrosmicronyx nebulosipennis, sp. nov., ♂, holotype (BMNH). F. Smicronyx gracilipes sp. nov., ♀, holotype (SAMC). G. Smicronyx similis sp. nov., ♂, holotype (SANC). H. Smicronyx pseudocoecus sp. nov., ♂, holotype (SAMC). Scale bars: 0.5 mm.
Fig. 6 in The Smicronychini of southern Africa (Coleoptera, Curculionidae): Review of the tribe and description of 12 new species
Fig. 6. Habitus in natura, host plants and habitats of Smicronyx of southern Africa. A. S. fallax (Gyllenhal, 1863) on Cuscuta campestris Yunck, 1932. B. Cuscuta campestris. C. S. pseudocoecus sp. nov. on Cuscuta sp. D. Cuscuta nitida E. Mey ex Choisy, host of S. pseudocoecus sp. nov. and S. australis sp. nov. E. S. san sp. nov. on Chironia baccifera L. F. Sebaea Sol. ex R.Br. sp., host of S. san sp. nov. G. Orphium frutescens L. (E. Mey), host of S. san sp. nov. and surrounding fynbos vegetation. H. Chironia baccifera, host of S. san sp. nov. I. S. zonatus Haran, 2018, in copula. J. Orobanchaceae Vent., host of S. zonatus growing in a marshy environment at the base of Cyperaceae Juss.
Fig. 4 in The Smicronychini of southern Africa (Coleoptera, Curculionidae): Review of the tribe and description of 12 new species
Fig. 4. Head and prothorax in lateral view of species of Smicronyx from southern Africa (Part 2). A. Smicronyx paucisquamis sp. nov., ♂, holotype (SAMC). B. Smicronyx fallax (Gyllenhal, 1836), ♂, neotype (NHRS). C. Smicronyx australis sp. nov., ♂, holotype (SAMC). D. Smicronyx san sp. nov., ♂, bred from Chironia baccifera L., holotype (SAMC). E. Smicronyx drakensbergensis sp. nov., ♂, holotype (TMSA). F. Smicronyx lutulentus Dietz, 1894, ♂ (CBGP). Scale bars: 0.5 mm.
Fig. 1 in The Smicronychini of southern Africa (Coleoptera, Curculionidae): Review of the tribe and description of 12 new species
Fig. 1. Habitus of species of Smicronychini from southern Africa (Part 1). A. Sharpia madibai sp. nov., ♂, holotype (SAMC). B. Afrosmicronyx cycnii sp. nov., ♂, holotype (SAMC). C. Afrosmicronyx louwi sp. nov., ♂, holotype (SAMC). D. Afrosmicronyx marshalli sp. nov., ♂, holotype (SANC). E. Afrosmicronyx nebulosipennis sp. nov., ♂, holotype (BMNH). F. Smicronyx gracilipes sp. nov., ♀, holotype (SAMC). G. Smicronyx similis sp. nov., ♂, holotype (SANC). H. Smicronyx pseudocoecus sp. nov., ♂, holotype (SAMC). I. Smicronyx paucisquamis sp. nov., ♂, holotype (SAMC). J. Smicronyx fallax (Gyllenhal, 1836), ♂, neotype (NHRS). K. Smicronyx australis sp. nov., ♂, holotype (SAMC). L. Smicronyx pauperculus Wollaston, 1864, ♂, specimen from Tanzania. Scale bars: 1 mm.
Fatiando a Terra Data: Southern Africa - Ground-based gravity
<p>This is a public domain compilation of ground measurements of gravity from Southern Africa. The observations are the absolute gravity values in mGal. The horizontal datum is not specified and heights are referenced to "sea level", which we will interpret as the geoid (which realization is likely not relevant since the uncertainty in the height is probably larger than geoid model differences).</p> <p><strong>Note:</strong> This is a processed and formatted version of the source dataset below. It's meant for use in documentation and tutorials of the <a href="https://www.fatiando.org">Fatiando a Terra</a> project. Please <strong>cite the original authors</strong> when using this dataset.</p> <p><strong>Changes made: </strong>Keep only coordinates, absolute gravity, and the (sea-level) observation height. Remove some points below sea-level (a bit suspicious and are potentially flawed heights from shipborne measurements). Convert from a custom text format to compressed CSV.</p> <p><strong>Source: </strong><a href="https://www.ngdc.noaa.gov/mgg/gravity/">NOAA NCEI</a></p> <p><strong>Source license: </strong><a href="https://ngdc.noaa.gov/ngdcinfo/privacy.html">public domain</a></p> <p><strong>Repository:</strong> <a href="https://github.com/fatiando-data/southern-africa-gravity">https://github.com/fatiando-data/southern-africa-gravity </a></p>
Fatiando a Terra Data: Southern Africa - Topography and Bathymetry
<p>This is a topography and bathymetry grid with a resolution of 1 arc-minute over Southern Africa. The grid was generated by cropping the ETOPO1 global topography grid. The heights are referenced to the mean sea level.</p> <p><strong>Note:</strong> This is a processed and formatted version of the source dataset below. It's meant for use in documentation and tutorials of the <a href="https://www.fatiando.org">Fatiando a Terra</a> project. Please <strong>cite the original authors</strong> when using this dataset.</p> <p><strong>Changes made:</strong> Data were cropped to a region that covers only the Southern Africa. Coordinates have been renamed to <em>longitude</em> and <em>latitude</em>. The dataset has been renamed to <em>topography</em>. The metadata of the dataset have been improved following CF-conventions. <strong> </strong></p> <p><strong>Source: </strong>ETOPO1 <a href="https://doi.org/10.7289/V5C8276M">https://doi.org/10.7289/V5C8276M</a></p> <p><strong>Source license: </strong><a href="https://ngdc.noaa.gov/mgg/global/dem_faq.html#sec-2.4">public domain</a></p> <p><strong>Repository: </strong><a href="https://github.com/fatiando-data/southern-africa-topography">https://github.com/fatiando-data/southern-africa-topography</a></p>
Fatiando a Terra Data: Bushveld, Southern Africa - Observed and preprocessed gravity
<p>This dataset contains ground gravity observations over the area that comprises the Bushveld Igenous Complex in Southern Africa, including preprocessed gravity fields such as the <em>gravity disturbance</em> and the <em>bouguer gravity disturbance</em> (topography-free gravity disturbance). In addition, the dataset contains the heights of the observation points referenced on the WGS84 reference ellipsoid and over the mean sea-level (what can be considered to be the geoid). This dataset was built upon a portion of the Southern Africa gravity compilation available through <a href="https://www.ngdc.noaa.gov/mgg/gravity/">NOAA NCEI</a>.<br> <br> <strong>Note:</strong> This is a processed and formatted version of the source dataset below. It's meant for use in documentation and tutorials of the <a href="https://www.fatiando.org">Fatiando a Terra</a> project. Please <strong>cite the original authors</strong> when using this dataset.<br> <br> <strong>Changes made: </strong></p> <ul> <li>The original data were cropped to a region bounded by 25 and 32 degrees on longitude and -27 and -23 degrees on latitude.</li> <li>Geometric observation heights were obtained by adding geoid heights to the original observation heights referenced on the mean sea-level. The geoid heights on each observation point were obtained by interpolation of the geoid available in doi: <a href="https://doi.org/10.5281/zenodo.5882205">10.5281/zenodo.5882205</a>.</li> <li>Gravity disturbances were computed by removing the normal gravity of the WGS84 ellipsoid computed through <a href="https://www.fatiando.org/boule">Boule</a>.</li> <li>Bouguer gravity disturbances were computed by forward modelling the topography using <a href="https://www.fatiando.org/harmonica">Harmonica</a> starting from the topography grid provided in doi: <a href="https://doi.org/10.5281/zenodo.6481379">10.5281/zenodo.6481379</a> and using densities of 2670 kg/m³ above the ellipsoid and 1040 - 2670 kg/m³ below the ellipsoid.</li> </ul> <p><strong>Source: </strong><a href="https://www.ngdc.noaa.gov/mgg/gravity/">NOAA NCEI</a> (gravity) and <a href="https://doi.org/10.7289/V5C8276M">ETOPO1</a> (topography)</p> <p><strong>Source license: </strong><a href="https://ngdc.noaa.gov/ngdcinfo/privacy.html">public domain</a> (gravity) and <a href="https://ngdc.noaa.gov/mgg/global/dem_faq.html#sec-2.4">public domain</a> (topography)</p> <p><strong>Repository</strong>: <a href="https://github.com/fatiando-data/bushveld-gravity">https://github.com/fatiando-data/bushveld-gravity</a></p>
Text-fig. 1. Relief map of Africa to show the location of the Cheringoma Plateau at the southern extremity of the African Rift System. in Stratigraphy, Chronology And Palaeontology Of The Tertiary Rocks Of The Cheringoma Plateau, Mozambique
Text-fig. 1. Relief map of Africa to show the location of the Cheringoma Plateau at the southern extremity of the African Rift System.
FIGURE 2 in Southern Africa's Great Escarpment as an amphitheater of climate-driven diversification and a buffer against future climate change in bats
FIGURE 2 Distributions (left), maximum likelihood (ML) phylogenetic trees (middle), principal component analysis (PCA) ordination plots from cranial measurements, photographs or drawings of the baculum and sonograms of echolocation calls (right) of selected groups of paramontane southern African bats having ranges categorized as arid (red symbols), Mediterranean (turquoise symbols), temperate-montane (blue), savanna-montane (orange), and tropical rain forest (green; see Table S1 for classification): horseshoe bats (Rhinolophus) of the R. capensis (a), R. darlingi (b), R. ferrumequinum (c), R. fumigatus (d) groups, wing-gland bats (Family Cistugidae, genus Cistugo (e), and long-eared serotine bats of the genus Laephotis (f)). Distribution maps were based on IUCN Redlist maps (open polygons), correctly identified vouchers from molecular studies (colored symbols; this study; GenBank; Curran et al., 2022; Demos et al., 2019; Dool et al., 2016; Taylor et al., 2018) and skulls measured in this study (crosses). In a few cases (see legends), GBIF records were indicated for the Angolan range of species. Gray shading indicates elevations over 1200 m a.s.l. Phylogenetic trees are shown for sub-clades (i.e., excluding outgroups) of three separate ML analyses undertaken with IQTREE of Rhinolophus, Cistugo, and Laephotis (Figures S2–S4). Values above nodes (in bold) represent median dates obtained for corresponding nodes from separate BEAST analyses in Figures S5–S7 (see text for details). Node support values for ML trees, obtained by the IQTREE program, are given below the nodes for SH-like approximate likelihood ratio tests (SH-aLRT), aBayes posterior probabilities, and ultra-fast bootstrap values (UFBS) respectively (see text for details). Tip labels marked in bold represent new sequences from this study. Underlined tip labels represent two instances of mtDNA introgression where morphologically distinct taxa from different biomes have near-identical cyt-b sequences. Species ranges of echolocation call peak frequencies were obtained from the literature for Rhinolophidae (Adams & Kwiecinski, 2018; Curran et al., 2022; Jacobs et al., 2013; Jacobs et al., 2017; Laverty & Berger, 2020; Monadjem et al., 2020; Mutumi et al., 2016; Odendaal & Jacobs, 2011; Odendaal et al., 2014; Schoeman & Jacobs, 2008), Cistugo (Monadjem et al., 2020; Schoeman & Jacobs, 2003, 2008), and long-eared Laephotis (Adams & Kwiecinski, 2018; Jacobs et al., 2005; Monadjem et al., 2020; Pierce et al., 2011). Bacula photographs and drawings were obtained from this study as well as Benda and Vallo (2012), Taylor et al. (2018), Curran et al. (2022). Abbreviation of South African province names: EC, Eastern Cape; FS, Free State; GP, Gauteng; KZN, KwaZulu-Natal; LP, Limpopo; MP, Mpumalanga; NC, Northern Cape; WC, Western Cape. Map lines delineate study areas and do not necessarily depict accepted national boundaries.
FIGURE 1 in Southern Africa's Great Escarpment as an amphitheater of climate-driven diversification and a buffer against future climate change in bats
FIGURE 1 Maps of southern, central, and eastern Africa showing (a) topographical features referred to in this study (see text for details), and (b) the extent of minimum monthly temperatures (bioclim6) <0°C from present and past (last glacial maximum [LGM]) models (from Worldclim; https://www.worldclim.com/; see Methods for more details). Gray or darker shading in both maps indicates mountains>1200 m in elevation. In (a), the acronym HEAN stands for the Highlands and Escarpments of Angola and Namibia (Mendelsohn et al., 2023); SEAMA stands for the South-East African Montane Archipelago (Bayliss et al., 2024); LMEE stands for the Limpopo–Mpumalanga– Eswatini Escarpment (Clark et al., 2022). The map in (b) shows distribution points of horseshoe bats, Rhinolophus (crosses), wing-gland bats, Cistugo (open triangles) and long-eared bats, Laephotis (open squares) based on morphological and molecular results from this study and from published a GenBank cyt-b sequences. In (b), minimum monthly temperatures <0°C indicated for the present (blue) and LGM (red), approximating the extent of frost (and hence temperate grasslands) currently and during the LGM (idea from Brain, 1985). Map lines delineate study areas and do not necessarily depict accepted national boundaries.
FIGURE 3 in Southern Africa's Great Escarpment as an amphitheater of climate-driven diversification and a buffer against future climate change in bats
FIGURE 3 Map of southern, central, and eastern Africa showing major geographic features (as in Figure 1a) but with biogeographical barriers elucidated by this study indicated as red dashed lines, labelled as (i) to (vii) (see Discussion), and taxa specific to different ranges indicated according to the predominant biomes (green = tropical; red = arid, turquoise = Mediterranean, blue = temperate, orange = savanna). Note that only one savanna lineage is here indicated for ease of visualization. Map lines delineate study areas and do not necessarily depict accepted national boundaries.
TA B L E 1 Summary of model fit, based on the area under the curve (AUC) of the receiver operating characteristic (ROC) for training data, and the most important bioclimatic variables in past, present, and future (2070) Maxent models of 13 bat species included in this study. in Southern Africa's Great Escarpment as an amphitheater of climate-driven diversification and a buffer against future climate change in bats
TA B L E 1 Summary of model fit, based on the area under the curve (AUC) of the receiver operating characteristic (ROC) for training data, and the most important bioclimatic variables in past, present, and future (2070) Maxent models of 13 bat species included in this study.
FIGURE 4 in Southern Africa's Great Escarpment as an amphitheater of climate-driven diversification and a buffer against future climate change in bats
FIGURE 4 Maps of south-central Africa showing the distribution of Köppen–Geiger climate zones for the present (a) and projected future (2070) (b), as well as past (last glacial maximum: left panel), present (right panel), and projected future (2070; right panel) Maxent distribution models for five species groups of bats; Rhinolophus capensis group (c–e: green = R. swinnyi; blue = R. rhodesiae; orange = R. simulator; turquoise = R. capensis; red = R. denti); R. darlingi group (f–h: blue = R. cervenyi; orange = R. darlingi; red = R. damarensis), R. ferruquinum group, in part (i–k: blue = R. acrotis), Laephotis spp (l–n: blue = L. cf. botswanae; orange = L. angolensis), Cistugo spp (o–q: blue = C. lesueuri; red = C. seabrae). Details of Maxent models given in text. Ranges of species above indicated by colors corresponding to biomes recognized in this study (Tables S1 and S2) as follows: blue or green = temperate; orange = savanna; turquoise = Mediterranean; red = arid. Map lines delineate study areas and do not necessarily depict accepted national boundaries.
Figure 6 in New records of alien and potentially invasive grass (Poaceae) species for southern Africa
Figure 6. Jarava plumosa global distribution map, with country- or regional-level shading, taken and modified from POWO (2020).
Figure 2 in New records of alien and potentially invasive grass (Poaceae) species for southern Africa
Figure 2. Agrostis capillaris global distribution map, with country- or regional-level shading, taken and modified from POWO (2020).
Figure 5 in New records of alien and potentially invasive grass (Poaceae) species for southern Africa
Figure 5. Jarava plumosa; A, whole plant; B, inflorescence close-up; C, floret. Image A of R.J. Soreng et al. ZA-30 (US), B and C of R.J. Soreng et al. ZA-30 (PRE).
Figure 4 in New records of alien and potentially invasive grass (Poaceae) species for southern Africa
Figure 4. Festuca rubra global distribution map, with country- or regional-level shading, taken and modified from POWO (2020).
Figure 3 in New records of alien and potentially invasive grass (Poaceae) species for southern Africa
Figure 3. Festuca rubra; A, whole plant; B, lateral-tending rhizome covered in cataphylls; C, leaf sheath and junction with blade of a tiller showing strigose hairs; D, spikelet; E, base of palea with lemma removed to reveal the ovary and stamens; F, close-up of glabrous ovary apex. Images A and B of S.P. Sylvester et al. 3455 (US), C–F of S.P. Sylvester et al. 3455 (PRE).
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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)
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DANDI Archive for NWB datasets
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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.