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25 results for “Western Sahara”
qdgc Western Sahara
<p>QDGC tables delivered in geopackage file<br> - - - - - - - - - - - - - - - - - - - - - -<br> QDGC represents a way of making (almost) equal area squares covering a specific area to represent specific qualities of the area covered. The squares themselves are based on the degree squares covering earth. Around the equator we have 360 longitudinal lines , and from the north to the south pole we have 180 latitudinal lines. Together this gives us 64800 segments or tiles covering earth.<br> <br> <br> <br> <br> Within each geopackage file you will find a number of tables with these names:<br> <br> <br> <br> <br> -tbl_qdgc_01<br> -tbl_qdgc_02<br> -tbl_qdgc_03<br> -tbl_qdgc_04<br> -tbl_qdgc_05<br> -etc<br> <br> <br> <br> <br> The attributes for each table are:<br> <br> <br> <br> <br> qdgc Unique Quarter Degree Grid Cell reference string<br> area_reference Country<br> level_qdgc QDGC level<br> cellsize degrees decimal degree for the longitudal and latitudal length of the cell<br> lon_center Longitude center of the cell<br> lat_center Latitudal center of the cell<br> area_km2 Calculated area for the cell<br> geom Geometry<br> <br> <br> <br> <br> Metadata<br> --------<br> Geodata GCS_WGS_1984<br> Datum: D_WGS_1984<br> Prime Meridian: 0<br> <br> <br> <br> <br> Areas are calculated with different versions of Albers Equal Area Conic using the PostGIS function st_area. For the African continent I have used Africa Albers Equal Area Conic which will look like this:<br> - st_area(st_transform(geom, 102022))/1000000)<br> <br> <br> <br> <br> Licensing<br> ---------<br> Creative Commons Attribution 4.0 International<br> <br> <br> <br> <br> Conditions<br> ----------<br> Delivered to the user as-is. No guarantees. If you find errors, please tell me and I will try to fix it. Suggestions for improvements can be addressed to the github repository: https://github.com/ragnvald/qdgc<br> <br> <br> <br> <br> Thankyou<br> --------<br> The work has over the years been supported and received advice and moral support from many organisations and stakeholders. Here are some of them:<br> - Tanzania Wildlife Research Institute<br> - Dept of Biology, NTNU, Norway<br> - Norwegian Environment Agency<br> - Eivin Røskaft, Steven Prager, Howard Frederick, Julian Blanc, Honori Maliti, Paul Ramsey<br> <br> <br> <br> <br> References<br> ----------<br> * http://en.wikipedia.org/wiki/QDGC<br> * http://www.mindland.com/wp/projects/quarter-degree-grid-cells/about-qdgc/<br> * http://en.wikipedia.org/wiki/Lambert_azimuthal_equal-area_projection<br> * http://www.safe.com<br> <br> <br> <br> <br> <br> <br> <br> <br> Ragnvald Larsen<br> Trondheim 23rd of January, 2021<br> <br> <br> <br> <br> ragnvald@mindland.com<br> www.mindland.com</p>
Infrastructure Climate Resilience Assessment Data Starter Kit for Western Sahara
<p> This starter data kit collects extracts from global, open datasets relating to climate hazards and infrastructure systems. </p> <p> These extracts are derived from global datasets which have been clipped to the national scale (or subnational, in cases where national boundaries have been split, generally to separate outlying islands or non-contiguous regions), using Natural Earth (2023) boundaries, and is not meant to express an opinion about borders, territory or sovereignty. </p> <p> Human-induced climate change is increasing the frequency and severity of climate and weather extremes. This is causing widespread, adverse impacts to societies, economies and infrastructures. Climate risk analysis is essential to inform policy decisions aimed at reducing risk. Yet, access to data is often a barrier, particularly in low and middle-income countries. Data are often scattered, hard to find, in formats that are difficult to use or requiring considerable technical expertise. Nevertheless, there are global, open datasets which provide some information about climate hazards, society, infrastructure and the economy. This "data starter kit" aims to kickstart the process and act as a starting point for further model development and scenario analysis. </p> <p>Hazards:</p> <ul> <li>coastal and river flooding (Ward et al, 2020)</li> <li>extreme heat and drought (Russell et al 2023, derived from Lange et al, 2020)</li> <li>tropical cyclone wind speeds (Russell 2022, derived from Bloemendaal et al 2020 and Bloemendaal et al 2022)</li> </ul> <p>Exposure:</p> <ul> <li>population (Schiavina et al, 2023)</li> <li>built-up area (Pesaresi et al, 2023)</li> <li>roads (OpenStreetMap, 2023)</li> <li>railways (OpenStreetMap, 2023)</li> <li>power plants (Global Energy Observatory et al, 2018)</li> <li>power transmission lines (Arderne et al, 2020)</li> </ul> <p> The spatial intersection of hazard and exposure datasets is a first step to analyse vulnerability and risk to infrastructure and people. </p> <p> To learn more about related concepts, there is a free short course available through the Open University on <a href="https://www.open.edu/openlearncreate/course/view.php?id=11539">Infrastructure and Climate Resilience</a>. This <a href="https://opsis.eci.ox.ac.uk/courses/2-infra-for-resil/">overview of the course</a> has more details. </p> <p> These Python libraries may be a useful place to start analysis of the data in the packages produced by this workflow: </p> <ul> <li> <a href="https://github.com/tomalrussell/snkit"><code>snkit</code></a> helps clean network data </li> <li> <a href="https://github.com/nismod/snail"><code>nismod-snail</code></a> is designed to help implement infrastructure exposure, damage and risk calculations </li> </ul> <p> The <a href="https://github.com/nismod/open-gira"><code>open-gira</code></a> repository contains a larger workflow for global-scale open-data infrastructure risk and resilience analysis. </p> <p> For a more developed example, some of these datasets were key inputs to a regional climate risk assessment of current and future flooding risks to transport networks in East Africa, which has a related online visualisation tool at <a href="https://east-africa.infrastructureresilience.org/">https://east-africa.infrastructureresilience.org/</a> and is described in detail in Hickford et al (2023). </p> <p><strong>References</strong></p> <ul> <li> Arderne, Christopher, Nicolas, Claire, Zorn, Conrad, & Koks, Elco E. (2020). Data from: Predictive mapping of the global power system using open data [Dataset]. In Nature Scientific Data (1.1.1, Vol. 7, Number Article 19). Zenodo. DOI: <a href="https://doi.org/10.5281/zenodo.3628142">10.5281/zenodo.3628142</a> </li> <li> Bloemendaal, Nadia; de Moel, H. (Hans); Muis, S; Haigh, I.D. (Ivan); Aerts, J.C.J.H. (Jeroen) (2020): STORM tropical cyclone wind speed return periods. 4TU.ResearchData. [Dataset]. DOI: <a href="https://doi.org/10.4121/12705164.v3">10.4121/12705164.v3</a> </li> <li> Bloemendaal, Nadia; de Moel, Hans; Dullaart, Job; Haarsma, R.J. (Reindert); Haigh, I.D. (Ivan); Martinez, Andrew B.; et al. (2022): STORM climate change tropical cyclone wind speed return periods. 4TU.ResearchData. [Dataset]. DOI: <a href="https://doi.org/10.4121/14510817.v3">10.4121/14510817.v3</a> </li> <li> Global Energy Observatory, Google, KTH Royal Institute of Technology in Stockholm, Enipedia, World Resources Institute. (2018) Global Power Plant Database. Published on Resource Watch and Google Earth Engine; <a href="http://resourcewatch.org/">resourcewatch.org/</a> </li> <li> Hickford et al (2023) Decision support systems for resilient strategic transport networks in low-income countries – Final Report. Available online: <a href="https://transport-links.com/hvt-publications/final-report-decision-support-systems-for-resilient-strategic-transport-networks-in-low-income-countries">https://transport-links.com/hvt-publications/final-report-decision-support-systems-for-resilient-strategic-transport-networks-in-low-income-countries</a> </li> <li> Lange, S., Volkholz, J., Geiger, T., Zhao, F., Vega, I., Veldkamp, T., et al. (2020). Projecting exposure to extreme climate impact events across six event categories and three spatial scales. Earth's Future, 8, e2020EF001616. DOI: <a href="https://doi.org/10.1029/2020EF001616">10.1029/2020EF001616</a> </li> <li> Natural Earth (2023) Admin 0 Map Units, v5.1.1. [Dataset] Available online: <a href="https://www.naturalearthdata.com/downloads/10m-cultural-vectors/10m-admin-0-details/">www.naturalearthdata.com/downloads/10m-cultural-vectors/10m-admin-0-details</a> </li> <li> OpenStreetMap contributors, Russell T., Thomas F., nismod/datapkg contributors (2023) Road and Rail networks derived from OpenStreetMap. [Dataset] Available at <a href="https://global.infrastructureresilience.org">global.infrastructureresilience.org</a> </li> <li> Pesaresi M., Politis P. (2023): GHS-BUILT-S R2023A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030) European Commission, Joint Research Centre (JRC) PID: <a href="http://data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea">data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea</a>, doi:10.2905/9F06F36F-4B11-47EC-ABB0-4F8B7B1D72EA </li> <li> Russell, T., Nicholas, C., & Bernhofen, M. (2023). Annual probability of extreme heat and drought events, derived from Lange et al 2020 (Version 2) [Dataset]. Zenodo. DOI: <a href="https://doi.org/10.5281/zenodo.8147088">10.5281/zenodo.8147088</a> </li> <li> Schiavina M., Freire S., Carioli A., MacManus K. (2023): GHS-POP R2023A - GHS population grid multitemporal (1975-2030). European Commission, Joint Research Centre (JRC) PID: <a href="http://data.europa.eu/89h/2ff68a52-5b5b-4a22-8f40-c41da8332cfe">data.europa.eu/89h/2ff68a52-5b5b-4a22-8f40-c41da8332cfe</a>, doi:10.2905/2FF68A52-5B5B-4A22-8F40-C41DA8332CFE </li> <li> Ward, P.J., H.C. Winsemius, S. Kuzma, M.F.P. Bierkens, A. Bouwman, H. de Moel, A. Díaz Loaiza, et al. (2020) Aqueduct Floods Methodology. Technical Note. Washington, D.C.: World Resources Institute. Available online at: <a href="https://www.wri.org/publication/aqueduct-floods-methodology">www.wri.org/publication/aqueduct-floods-methodology</a>. </li> </ul>
Fig. 9 in Revision of deep-water species in Granulina (Gastropoda: Granulinidae) from Mauritania and Western Sahara
Fig. 9. Granulina sigridae sp. nov., Mauritania.A –I. Timiris coral mound chain, MSM16–3/GeoB14876. A –B. Paratype (SMF373040). A. Ventral view, height 2.9 mm, width 1.8 mm. B. Columellar folds. C–D. Holotype (SMF359034). C. Ventral view, height 3.1 mm, width 1.9 mm. D. Columellar folds. E– G. Paratype (SMF373040). E –F. Ventral and side views, height 3.2 mm, width 1.8 mm, tumidity 1.6 mm. G. Micro-sculpture above second columellar tooth, see arrow in E–F. H. Paratype (SMF373040), ventral view, height 3.0 mm, width 1.8 mm. I. Paratype (SMF373040), side view, height 3.1 mm, tumidity 1.6 mm. J–K. Tamxat Mounds, MSM16–3/GeoB14904, ventral view, height 2.8 mm, width 1.7 mm.
Fig. 7 in Revision of deep-water species in Granulina (Gastropoda: Granulinidae) from Mauritania and Western Sahara
Fig. 7. Granulina ronaldi sp. nov., Mauritania, off Banc d'Arguin, CANCAP/3.154. A–D. Holotype (SMF359026). A–B. Ventral and side views, height 2.9 mm, width 1.7 mm, tumidity 1.4 mm. C. Columellar folds. D. Micro-sculpture above second columellar fold, see arrow in C. E–F. Paratype (SMF359020), ventral and side views, height 2.5 mm, width 1.5 mm, tumidity 1.3 mm. G–H. Paratype (SMF359027), central and side views, height 2.5 mm, width 1.4 mm, tumidity 1.3 mm, callus line indicated by white dots. I–J. Paratype (SMF359029), ventral and side views, height 2.5 mm, width 1.5 mm, tumidity 1.2 mm.
Fig. 6 in Revision of deep-water species in Granulina (Gastropoda: Granulinidae) from Mauritania and Western Sahara
Fig. 6. Granulina reginae sp. nov., Mauritania. A –D. Timiris Mound Complex. A –C. Holotype, POS346/ GeoB11587 (SMF359019). A–B. Ventral view, height 2.2 mm, width 1.4 mm, C. Micro-sculpture above second fold, see arrow in B. D. Paratype, POS346/GeoB11588 (SMF359021), ventral view, height 2.0 mm, tumidity 1.2 mm. E–J. Paratypes (SMF359025), off Banc d'Arguin, MSM16–3/GeoB14799. E–F. Ventral and side view, height 2.1 mm, width 1.3 mm, tumidity 1.1 mm. G. Micro-sculpture above second fold, see arrows in E, H. H. Columellar folds. I–J. Ventral and side view, height 2.2 mm, width 1.4 mm, tumidity 1.1 mm.
Fig. 5 in Revision of deep-water species in Granulina (Gastropoda: Granulinidae) from Mauritania and Western Sahara
Fig. 5. Location map of the new species in Granulina Jousseaume, 1888 off Mauritania and Western Sahara. White circles show all investigated stations; colour symbols show locations of shells from new species. Granulina reginae sp. nov. is presented by yellow squares, G. sigridae sp. nov. as red diamonds, G. sandrae sp. nov. as blue triangles, and G. ronaldi sp. nov. as green circles. Bathymetric data from GEBCO; contours 500 m
Fig. 4 in Revision of deep-water species in Granulina (Gastropoda: Granulinidae) from Mauritania and Western Sahara
Fig. 4. Ganulina aff. crassa, off Nouakchott, Mauritania. A–D. M44/133–KG615. E–F. M60/77–KG960. A–B. Ventral and side view, height 1.8 mm, width 1.2 mm, tumidity 1.0 mm. C. Micro-sculpture above second columellar fold, see arrow in D. D. Columellar folds and labial denticles. E. Ventral view, height 2.0 mm, width 1.3 mm. F. Ventral view, height 2.0 mm, width 1.3 mm.
Fig. 3 in Revision of deep-water species in Granulina (Gastropoda: Granulinidae) from Mauritania and Western Sahara
Fig. 3. Granulina crassa Smriglio, Gubbioli & Mariottini, 2000, Western Sahara, off Cap Blanc, M44/235–KG649. A–D. Ventral and side views, height 2.1 mm, width 1.3 mm, tumidity 1.0 mm. C. Columellar folds. D. Micro–sculpture above second columellar fold, see arrow in C. E–F. Ventral and side views, height 2.1 mm, width 1.3 mm, tumidity 1.0 mm. G–H. Views and dimensions as E–F. I – J. Views and dimensions as E–F.
Fig. 8 in Revision of deep-water species in Granulina (Gastropoda: Granulinidae) from Mauritania and Western Sahara
Fig. 8. Granulina sandrae sp. nov., Mauritania. – A –F. Off Cap Timiris, CANCAP/3.154. A –B. Holotype (SMF359030), ventral view, height 3.5 mm, width 2.2 mm, micro-sculpture above second columellar tooth, see arrow in A. C. Paratype (SMF359031), side view with thickened lip, height 3.2 mm, tumidity 1.8 mm. D–F. Paratype (SMF359031). D, F. Ventral and side views, height 3.2 mm, width 2.1 mm, tumidity 1.8 mm. E. Columellar view with teeth. – G–J. Southern Banc d'Arguin, MSM16–3/ GeoB14847. G–I. Paratype (SMF359033). G. Ventral view height 3.6 mm, width 2.5 mm. H. Microsculpture above second columellar fold, see arrow in I. I. Columellar folds. J. Paratype (SMF359033), side view with thickened lip, height 3.4 mm, tumidity 2.0 mm.
Fig. 1 in Revision of deep-water species in Granulina (Gastropoda: Granulinidae) from Mauritania and Western Sahara
Fig. 1. Location map of the known species of Granulina Jousseaume, 1888 found off Mauritania and Western Sahara. All investigated stations are shown by white circles; specimens of Granulina were only found at locations indicated by colour symbols. Granulina cerea Smriglio, Gubbioli & Mariottini, 2000 is presented as yellow squares, G. crassa Smriglio, Gubbioli & Mariottini, 2000 as red diamonds, G. crystallina Smriglio, Gubbioli & Mariottini, 2000 as blue triangles and G. nofronii Smriglio, Gubbioli & Mariottini, 2000 as green circles. Bathymetric data from GEBCO, contours at 500 m intervals.
Fig. 2. Granulina Jousseaume, 1888 from Mauritania. A–D in Revision of deep-water species in Granulina (Gastropoda: Granulinidae) from Mauritania and Western Sahara
Fig. 2. Granulina Jousseaume, 1888 from Mauritania. A–D. Granulina cerea Smriglio, Gubbioli & Mariottini, 2000, off Banc d'Arguin, CANCAP/3.120. A–B. Shell. A. Ventral view, height 2.8 mm, width 1.7 mm. B. Micro-sculpture above second columellar fold, see arrow in A. C–D. Shell, ventral view and side view, height 2.6 mm, width 1.6 mm, tumidity 1.3 mm. E. Granulina crystallina Smriglio, Gubbioli & Mariottini, 2000, off Nouakchott, M44/193–KG626, ventral view, height 3.1 mm, width 2.0 mm. F–G. Granulina nofronii Smriglio, Gubbioli & Mariottini, 2000, MSM16–3/GeoB14714. F. Ventral view, height 2.3 mm, width 1.4 mm. G. Ventral view, height 2.5 mm, width 1.6 mm
Amphibians and Reptiles of Morocco and Western Sahara
Website dedicated to the dissemination of current knowledge on natural history, ecology, distribution, systematics and conservation of amphibians and reptiles of Morocco and Western Sahara. <p></p>http://www.moroccoherps.com/
Subspecies and Distribution. R.c.cystopsThomas,1903—NAfricafromMoroccotoNileValleyinEgypt,Sudan,andNSouthSudan,alsoinSahelregioninEMali,BurkinaFaso,Niger,andNChad. R. c. arabium Thomas, 1913 — extreme SW Syria, Levant, W Arabia S to Yemen and SE to W Oman (including Socotra I) and Horn of Africa (S Eritrea, Ethiopia, Djibouti, and N Somalia). Also, in S Western Sahara, Mauritania, and Senegal but probably a separate not yet described species there. in Rhinopomatidae
Subspecies and Distribution. R.c.cystopsThomas,1903—NAfricafromMoroccotoNileValleyinEgypt,Sudan,andNSouthSudan,alsoinSahelregioninEMali,BurkinaFaso,Niger,andNChad. R. c. arabium Thomas, 1913 — extreme SW Syria, Levant, W Arabia S to Yemen and SE to W Oman (including Socotra I) and Horn of Africa (S Eritrea, Ethiopia, Djibouti, and N Somalia). Also, in S Western Sahara, Mauritania, and Senegal but probably a separate not yet described species there.
Subspecies and Distribution. A.l.lerviaPallas,1777—Morocco,NA.l.,andNTunisia. A.l.angusiRothschild,1921—NWNiger(Air&TermitMassifs). A.l.blaineiRothschild,1913—SELybia,NEChad,andNW&NESudan(probablynowrestrictedtoRedSeahills). A.l.fassiniLepri,1930—NWLibya,extremeSTunisia. A.l.ornatus1.GeoffroySaint-Hilaire,1827—SE&SWEgypt. A. l. sahariensis Rothschild, 1913 — S Morocco, Western Sahara, NW Mauritania, S A.l ria, extreme S Libya, NE Mali, SE Niger, and NW Chad. Introduced, free-ranging populations occur in S Spain, the Canary Is, USA (California, New Mexico, and Texas), and NE Mexico. Subspecies of free-ranging introduced populations are unknown because they originate from zoo animals of uncertain origin or from hybrids. Most introduced populations are probably from subspecies lervia, derived from European zoos. The Aoudad has become a widespread invasive species. in Bovidae
Subspecies and Distribution. A.l.lerviaPallas,1777—Morocco,NA.l.,andNTunisia. A.l.angusiRothschild,1921—NWNiger(Air&TermitMassifs). A.l.blaineiRothschild,1913—SELybia,NEChad,andNW&NESudan(probablynowrestrictedtoRedSeahills). A.l.fassiniLepri,1930—NWLibya,extremeSTunisia. A.l.ornatus1.GeoffroySaint-Hilaire,1827—SE&SWEgypt. A. l. sahariensis Rothschild, 1913 — S Morocco, Western Sahara, NW Mauritania, S A.l ria, extreme S Libya, NE Mali, SE Niger, and NW Chad. Introduced, free-ranging populations occur in S Spain, the Canary Is, USA (California, New Mexico, and Texas), and NE Mexico. Subspecies of free-ranging introduced populations are unknown because they originate from zoo animals of uncertain origin or from hybrids. Most introduced populations are probably from subspecies lervia, derived from European zoos. The Aoudad has become a widespread invasive species.
Distribution. North Africa, Horn of Africa, and W Middle East, including Morocco, Algeria, Tunisia, Libya, Egypt, Western Sahara, Mauritania, Senegal, Mali, Niger, Chad, Sudan, Eritrea, Ethiopia, Somalia, NE Nigeria, Sinai Peninsula, Israel, and WJordan; it probably occurs in the West Bank, extreme N Burkina Faso, and Djibouti. in Dipodidae
Distribution. North Africa, Horn of Africa, and W Middle East, including Morocco, Algeria, Tunisia, Libya, Egypt, Western Sahara, Mauritania, Senegal, Mali, Niger, Chad, Sudan, Eritrea, Ethiopia, Somalia, NE Nigeria, Sinai Peninsula, Israel, and WJordan; it probably occurs in the West Bank, extreme N Burkina Faso, and Djibouti.
Subspecies and Distribution. J. j. jaculus Linnaeus, 1758 — Morocco, Algeria, Tunisia, Libya, Egypt, Western Sahara, Mauritania, N Senegal, Mali, Niger, NE Nigeria, Chad, and Sudan. J Jschlueter: Nehring, 1901 — NE Egypt (N Sinai Peninsula), Gaza Strip, and Israel; it probably occurs in adjacent extreme WJordan in Dipodidae
Subspecies and Distribution. J. j. jaculus Linnaeus, 1758 — Morocco, Algeria, Tunisia, Libya, Egypt, Western Sahara, Mauritania, N Senegal, Mali, Niger, NE Nigeria, Chad, and Sudan. J Jschlueter: Nehring, 1901 — NE Egypt (N Sinai Peninsula), Gaza Strip, and Israel; it probably occurs in adjacent extreme WJordan
Distribution. Mediterranean, scattered in islands in Aegean and Ionian seas and coasts of Greece and W Turkey, NE Morocco, and NW Algeria; E Atlantic Ocean at Desertas Is (Madeira Is group) and Ras Nouadhibou (= Cabo Blanco/Cap Blanc Peninsula) on the border between Western Sahara and Mauritania; occasionally recorded in Canary Is, Mauritania (Banc d'Arguin), Tunisia (La Gallite), Libya (Cyrenaic coast), and the Adriatic coast in Croatia. in Phocidae
Distribution. Mediterranean, scattered in islands in Aegean and Ionian seas and coasts of Greece and W Turkey, NE Morocco, and NW Algeria; E Atlantic Ocean at Desertas Is (Madeira Is group) and Ras Nouadhibou (= Cabo Blanco/Cap Blanc Peninsula) on the border between Western Sahara and Mauritania; occasionally recorded in Canary Is, Mauritania (Banc d'Arguin), Tunisia (La Gallite), Libya (Cyrenaic coast), and the Adriatic coast in Croatia.
Distribution. Near-shore waters of tropical and subtropical West Africa, from the Western Sahara to S Angola. in Delphinidae
Distribution. Near-shore waters of tropical and subtropical West Africa, from the Western Sahara to S Angola.
Subspecies and Distribution. L. ¢c. capensis Linnaeus, 1758 — Western Cape Province (South Africa). L.c.aegyptiusDesmarest,1822—Egypt,Sudan,Palestine. L.c.aquiloThomas&Wroughton,1907—SMozambique. L. c. arabicus Hemprich & Ehrenberg, 1832 — Middle East, Arabian Peninsula, Iran, SW Pakistan (Baluchistan), and SW Afghanistan. . ¢. atlanticus de Winton, 1898 — Morocco. ¢. carpi Lundholm, 1955 — NW Namibia. granti Thomas & Schwann, 1904 — Northern Cape Province (South Africa). MDDnop hawker: Thomas, 1901 — W Sudan, Eritrea. isabellinus Cretzschmar, 1826 — Egypt, Sudan, Eritrea. Ean mediterraneus Wagner, 1841 — Sardinia. schlumberger: Remy Saint-Loup, 1894 — NE Morocco. sinaiticus Hemprich & Ehrenberg, 1832 — Egypt, Iraq. S whitakeri Thomas, 1902 — Libya, Niger and Algeria. The Cape Hare occurs in the Mediterranean I of Sardinia and in isolated populations scattered throughout most of the Arabian Peninsula and the Middle East and E to W Himalayas. This species has an extensive range in Africa which is separated in two distinct regions. First, in Egypt, Sudan, South Sudan, Eritrea, Ethiopia, Uganda, Kenya, and Tanzania, and throughout most of the dry savanna regions of C, W & N Africa, including parts of the Sahara Desert. Second, in savanna and semi-desert regions of Namibia, Botswana, S Zimbabwe, SW Mozambique, South Africa, Swaziland, and Lesotho. in Leporidae
Subspecies and Distribution. L. ¢c. capensis Linnaeus, 1758 — Western Cape Province (South Africa). L.c.aegyptiusDesmarest,1822—Egypt,Sudan,Palestine. L.c.aquiloThomas&Wroughton,1907—SMozambique. L. c. arabicus Hemprich & Ehrenberg, 1832 — Middle East, Arabian Peninsula, Iran, SW Pakistan (Baluchistan), and SW Afghanistan. . ¢. atlanticus de Winton, 1898 — Morocco. ¢. carpi Lundholm, 1955 — NW Namibia. granti Thomas & Schwann, 1904 — Northern Cape Province (South Africa). MDDnop hawker: Thomas, 1901 — W Sudan, Eritrea. isabellinus Cretzschmar, 1826 — Egypt, Sudan, Eritrea. Ean mediterraneus Wagner, 1841 — Sardinia. schlumberger: Remy Saint-Loup, 1894 — NE Morocco. sinaiticus Hemprich & Ehrenberg, 1832 — Egypt, Iraq. S whitakeri Thomas, 1902 — Libya, Niger and Algeria. The Cape Hare occurs in the Mediterranean I of Sardinia and in isolated populations scattered throughout most of the Arabian Peninsula and the Middle East and E to W Himalayas. This species has an extensive range in Africa which is separated in two distinct regions. First, in Egypt, Sudan, South Sudan, Eritrea, Ethiopia, Uganda, Kenya, and Tanzania, and throughout most of the dry savanna regions of C, W & N Africa, including parts of the Sahara Desert. Second, in savanna and semi-desert regions of Namibia, Botswana, S Zimbabwe, SW Mozambique, South Africa, Swaziland, and Lesotho.
Subspecies and Distribution. L.v.victoriaeThomas,1893—Tanzania. L.v.angolensisThomas,1904—Angola. L.v.senegalensisRochebrune,1883—Senegal,TheGambia. L. v. whyte: Thomas, 1894 — Malawi. The African Savanna Hare is present from the Atlantic coast of NW Africa (Western Sahara S to Guinea), E across the Sahel to Sudan and the extreme W Ethiopia, S through E Africa (E DR Congo, Uganda, W Kenya, Rwanda, Burundi, and Tanzania) to most of Angola, Zambia, Malawi, NE Namibia, Botswana, Zimbabwe, Mozambique, E South Africa, Swaziland, and Lesotho; a small isolated population exists near Beni Abbas in the Sahara Desert in W Algeria. in Leporidae
Subspecies and Distribution. L.v.victoriaeThomas,1893—Tanzania. L.v.angolensisThomas,1904—Angola. L.v.senegalensisRochebrune,1883—Senegal,TheGambia. L. v. whyte: Thomas, 1894 — Malawi. The African Savanna Hare is present from the Atlantic coast of NW Africa (Western Sahara S to Guinea), E across the Sahel to Sudan and the extreme W Ethiopia, S through E Africa (E DR Congo, Uganda, W Kenya, Rwanda, Burundi, and Tanzania) to most of Angola, Zambia, Malawi, NE Namibia, Botswana, Zimbabwe, Mozambique, E South Africa, Swaziland, and Lesotho; a small isolated population exists near Beni Abbas in the Sahara Desert in W Algeria.
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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.