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41 results for “African Lakes”
Figure 2 in Phylogeny and biogeography of African Biomphalaria (Gastropoda: Planorbidae), with emphasis on endemic species of the great East African lakes
Figure 2. Plots of transitions (TS) and transversions (TV) for Biomphalaria relative to the percentage sequence divergence (p-distance). The sliding window analysis for noncoding sequences and codon position for protein coding sequences are given in the insets. A, TS/TV plot of the partial sequence of the mitochondrial 16S gene. Regions with the most variation are identified in the sliding window analysis and correspond to loop regions in the secondary structure. B, TS/TV plot of the total internal transcribed spacer I (ITS1) gene that indicates a possible saturation. The sliding window analysis (inset) illustrates that the variation is not distributed uniformly across the sequence. C, TS/TV plot of the partial sequence of cytochrome oxidase subunit I (COI; primer pair LCO/HCO). The codon position plot is given in the inset. D, TS/TV plot of the partial sequence of COI (primer pair ASMIT 1/2). The codon position plot is given in the inset.
Figure A1 in Phylogeny and biogeography of African Biomphalaria (Gastropoda: Planorbidae), with emphasis on endemic species of the great East African lakes
Figure A1. Cladograms resulting from maximum-likelihood (ML) and maximum-parsimony (MP) analyses of the combined matrix and parsimony analyses of single-gene cladograms. Bootstrap support is indicated at the nodes. A, Consensus cladogram inferred from weighted and unweighted 16S by MP. B, Cladogram inferred from internal transcribed spacer I (ITS1) by MP. C, Cladogram inferred from cytochrome oxidase subunit I (COI) by MP (primer pair LCO/HCO). D, Cladogram inferred from COI (primer pair ASMIT 1/2) by MP. E, Cladogram inferred from the combined data matrix by MP. F, Cladogram inferred from the combined data matrix by ML.
Figure 1 in Phylogeny and biogeography of African Biomphalaria (Gastropoda: Planorbidae), with emphasis on endemic species of the great East African lakes
Figure 1. Summary cladogram from DeJong et al. (2001) showing the relationships of the African Biomphalaria. Note the position of Biomphalaria stanleyi within Biomphalaria pfeifferi.
Agricultural land use and ensuing eutrophication both shape parasitic trematode communities in rural African lakes
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Biogeochemical data from the HIPE project in Lakes Edward and George (East African Rift)
<p>The geo-referenced and timestamped data-set consists of 7 files:</p> <ul> <li>“db_cruise_CTD” contains the CTD profiles obtained during the cruises</li> <li>“db_cruise_GHGs” contains CO2, CH4, N2O dissolved concentrations, chlorophyll-a concentrations, inorganic nutrients (NO3-, N2O-, NH4+, PO43-) and d13C-CH4 from the 4 cruises</li> <li>“db_monitoring” contains CO2, CH4, N2O dissolved concentrations, chlorophyll-a concentrations, and POC from the monitoring at two stations (January 2017 to December 2019)</li> <li>“db_uw” contains the continuous of CO2 and CH4 (plus EXO-II data) on 19/03/2019</li> <li>“meteo_Mweya” contains the meteorological data acquired from June 2016 to March 2019</li> <li>“db_monitoring_CTD” contains the CTD profiles from the deep station of the monitoring.</li> <li>“mooring” contains the temperature data from a mooring at a station 10 m deep (March 2019)</li> </ul> <p> </p> <p>Data were acquired in Lake Edward, Kazinga Channel and Lake George on four occasions (20/10-07/11/2016, 23/03-08/04/2017, 18/01-02/02/2018, 21/03-30/03/2019). From January 2017 to December 2019, a shallow station (3 m bottom depth) and a deeper station (22 m bottom depth) were regularly sampled, every 21 d in 2017 and 2018, and every 30 d in 2019. A mooring was deployed at a station at 10m bottom depth in Lake Edward (-0.2459°N 29.8635°E) equipped with RBR Solo temperature sensors at 6 depths from surface to 1m above the sediment (0.2, 1.0, 2.0, 5.0, 7.5 and 9.0 m depth) from 21/03/2019 (13:00 local time (LT)) to 23/03/2019 (13:50 LT)<em>.</em></p> <p> </p> <p>Solar radiation, ultraviolet radiation, wind speed (cup anemometer), wind direction (wind vane), rain (mechanical rain collector), air temperature, barometric pressure data were acquired with a Davis Instruments weather station (Vantage Pro2 fitted with standard manufacturer sensors) in Mweya on top of a building of the Uganda Wildlife Authority, 4m above ground (-0.190384°N 29.899103°E) . Data were measured every 5 seconds, averaged and logged every 10 minutes.</p> <p>During the March 2019 cruise, continuous measurements (1 min interval) of partial pressure of CO<sub>2</sub> (pCO<sub>2</sub>) and of partial pressure of CH<sub>4</sub> (pCH<sub>4</sub>) were made with an equilibrator designed for turbid waters consisting of a tube filled with glass marbles (Frankignoulle et al. 2001) coupled to a Los Gatos Research off-axis integrated cavity output spectroscopy analyzer (Ultraportable Greenhouse Gas Analyzer with extended range for CH<sub>4</sub>). In parallel water temperature, specific conductivity, pH, dissolved oxygen saturation level (%O<sub>2</sub>), turbidity, chlorophyll-<em>a</em> (Chl-<em>a</em>), and fluorescent dissolved organic matter (FDOM) were measured with an YSI EXO-II multi-parameter probe, position with a Garmin geographical position system (Map 60S) portable probe, and depth with a Humminbird Helix 5 echo-sounder. Surface water was pumped to the equilibrator and the multi-parameter probe (on deck) with a 12V-powered water pump (LVM105) attached to the side of the boat at a fixed depth of about 0.5 m depth.</p> <p>Discrete sampling was done from the side of the boat with a 5.0 L Niskin bottle (General Oceanics). During the first cruise, vertical profiles of water temperature, specific conductivity, pH, %O<sub>2</sub> and Chl-<em>a</em> were measured with a Hydrolab DS5 multi-parameter probe, while during the other three cruises and also during the monitoring, turbidity and FDOM were measured additionally with a YSI EXO-II multi-parameter probe. Both multi-parameter probes were calibrated according to manufacturer’s specifications, in air for %O<sub>2</sub> and with standard solutions for other variables: commercial pH buffers (4.00, 7.00, 10.00), a 1000 µS cm<sup>-1</sup> standard for conductivity. pCO<sub>2</sub> was measured directly after water sampling with a Li-Cor Li-840 infra-red gas analyser (IRGA) based on the headspace technique with 4 polypropylene 60 ml syringes (Borges et al. 2015). The Li-Cor 840 IRGA was calibrated before and after each cruise with ultrapure N<sub>2</sub> and a suite of gas standards (Air Liquide Belgium) with CO<sub>2</sub> mixing ratios of 388, 813, 3788 and 8300 ppm. The overall precision of pCO<sub>2</sub> measurements was ±2.0%.</p> <p>Samples for CH<sub>4</sub> and N<sub>2</sub>O were collected from the Niskin bottle with a silicone tube in 60 ml borosilicate serum bottles (Wheaton), poisoned with 200 µL of a saturated solution of HgCl<sub>2</sub> and sealed with a butyl stopper and crimped with an aluminium cap. Measurements were made with the headspace technique (Weiss 1981) and a gas chromatograph (GC) (SRI 8610C) with a flame ionisation detector for CH<sub>4</sub> and electron capture detector for N<sub>2</sub>O calibrated with CO<sub>2</sub>:CH<sub>4</sub>:N<sub>2</sub>O:N<sub>2</sub> gas mixtures (Air Liquide Belgium) with mixing ratios of 1, 10 and 30 ppm for CH<sub>4</sub>, 404, 1018, 3961 ppm for CO<sub>2</sub>, and 0.2, 2.0 and 6.0 ppm for N<sub>2</sub>O. The precision of measurement based on duplicate samples was ±3.9% for CH<sub>4</sub> and ±3.2% for N<sub>2</sub>O.</p> <p>Samples for the stable isotope composition of CH<sub>4</sub> (δ<sup>13</sup>C-CH<sub>4</sub>) were collected and preserved as described above for the CH<sub>4</sub> concentration. The δ<sup>13</sup>C-CH<sub>4</sub> was determined with a custom developed interface, whereby a 20 ml He headspace was first created, and CH<sub>4</sub> was flushed out through a double-hole needle, non-CH<sub>4</sub> volatile organic compounds were trapped in liquid N<sub>2</sub>, CO<sub>2</sub> was removed with a soda lime trap, H<sub>2</sub>O was removed with a magnesium perchlorate trap, and the CH<sub>4</sub> was quantitatively oxidized to CO<sub>2</sub> in an online combustion column similar to that of an elemental analyzer. The resulting CO<sub>2</sub> was subsequently pre-concentrated by immersion of a stainless steel loop in liquid N<sub>2</sub>, passed through a micropacked GC column (Restek HayeSep Q, 2m length, 0.75mm internal diameter), and finally measured on a Thermo DeltaV Advantage isotope ratio mass spectrometer (IRMS). Calibration was performed with CO<sub>2</sub> generated from certified reference standards (IAEA-CO-1 or NBS-19, and LSVEC) and injected in the line after the CO<sub>2</sub> trap. Reproducibility of measurement based on duplicate injections of samples was typically better than ±0.5 ‰.</p> <p>Water was filtered on Whatman glass fibre filters (GF/F grade, 0.7 µm porosity) for particulate organic carbon (POC) and Chl-<em>a</em> (47 mm diameter). Filters for POC were stored dry and filters for Chl-<em>a</em> were stored frozen at -20°C. Filters for POC analysis were decarbonated with HCl fumes for 4h and dried before encapsulation into silver cups; POC concentration was analysed on an EA-IRMS (Thermo FlashHT with DeltaV Advantage), with a reproducibility better than ±5%. Data were calibrated with certified (IAEA-600: caffeine) and in-house standards (leucine and muscle tissue of Pacific tuna) that were previously calibrated versus certified standards. The Chl-<em>a</em> samples were analysed by HPLC according to Descy et al. (2005), with a reproducibility of ±0.5% and a detection limit of 0.01 µg L<sup>-1</sup>.</p> <p>The water filtered through GF/F Whatman glass fibre filters was collected and further filtered through polyethersulfone syringe encapsulated filters (0.2 µm porosity) for nitrate (NO<sub>3</sub><sup>-</sup>), nitrite (NO<sub>2</sub><sup>-</sup>) and ammonium (NH<sub>4</sub><sup>+</sup>) and were stored frozen (-20°C) in 50 mL polypropylene vials. NO<sub>3</sub><sup>-</sup> and NO<sub>2</sub><sup>-</sup> were determined with the sulfanilamide colorimetric with the vanadium reduction method (APHA, 1998), and NH<sub>4</sub><sup>+</sup> with the dichloroisocyanurate-salicylate-nitroprussiate colorimetric method (SCA, 1981). Detection limits were 0.3, 0.01, and 0.15 µmol L<sup>-1</sup> for NH<sub>4</sub><sup>+</sup>, NO<sub>2</sub><sup>-</sup> and NO<sub>3</sub><sup>-</sup>, respectively. Precisions were ±0.02 µmol L<sup>-1</sup>, ±0.02 µmol L<sup>-1</sup>, and ±0.1 µmol L<sup>-1</sup> for NH<sub>4</sub><sup>+</sup>, NO<sub>2</sub><sup>-</sup> and NO<sub>3</sub><sup>-</sup>, respectively.</p> <p> </p> <p>References</p> <p> </p> <p>APHA, 1998. Standard methods for the examination of water and wastewater, American Public Health Association.</p> <p>Borges, A. V., Darchambeau, F., Teodoru, C. R., Marwick, T. R., Tamooh, F., Geeraert, N., Omengo, F. O., Guérin, F., Lambert, T., Morana, C., Okuku, E., and Bouillon, S.: Globally significant greenhouse gas emissions from African inland waters, Nature Geosci., 8, 637-642, doi:10.1038/NGEO2486, 2015.</p> <p>Descy, J.-P., Hardy, M.-A., Sténuite, S., Pirlot, S., Leporcq, B., Kimirei, I., Sekadende, B., Mwaitega, S. R., and Sinyenza, D., 2005. Phytoplankton pigments and community composition in Lake Tanganyika. Freshw. Biol., 50, 668-684.</p> <p>Frankignoulle, M., Borges, A., Biondo R., 2001. A new design of equilibrator to monitor carbon dioxide in highly dynamic and turbid environments. Water Res., 35, 1344-1347.</p> <p>Standing committee of Analysts: Ammonia in waters. Methods for the examination of waters and associated materials. 16 pp., 1981.</p> <p>Weiss, R.F., 1981. Determinations of carbon dioxide and methane by dual catalyst flame ionization chromatography and nitrous oxide by electron capture chromatography. J. Chromatogr. Sci., 19, 611-616.</p>
Data from: Genomic islands of speciation separate cichlid ecomorphs in an East African crater lake
The genomic causes and effects of divergent ecological selection during speciation are still poorly understood. Here we report the discovery and detailed characterization of early-stage adaptive divergence of two cichlid fish ecomorphs in a small (700 meters in diameter) isolated crater lake in Tanzania. The ecomorphs differ in depth preference, male breeding color, body shape, diet, and trophic morphology. With whole-genome sequences of 146 fish, we identified 98 clearly demarcated genomic "islands" of high differentiation and demonstrated the association of genotypes across these islands with divergent mate preferences. The islands contain candidate adaptive genes enriched for functions in sensory perception (including rhodopsin and other twilight-vision–associated genes), hormone signaling, and morphogenesis. Our study suggests mechanisms and genomic regions that may play a role in the closely related mega-radiation of Lake Malawi.
Distribution. SE Senegal, extreme SW Mali, Guinea-Bissau, Guinea, NW Sierra Leone, Liberia, Ivory Coast, S Burkina Faso, Ghana, Togo, Benin, extreme S Niger, W & C Nigeria, N Cameroon, S Chad, Central African Republic, S & E Sudan, N DR Congo, lowland parts of W Ethiopia, Uganda (not extreme S), NW Kenya (Lake Turkana region). in Bovidae
Distribution. SE Senegal, extreme SW Mali, Guinea-Bissau, Guinea, NW Sierra Leone, Liberia, Ivory Coast, S Burkina Faso, Ghana, Togo, Benin, extreme S Niger, W & C Nigeria, N Cameroon, S Chad, Central African Republic, S & E Sudan, N DR Congo, lowland parts of W Ethiopia, Uganda (not extreme S), NW Kenya (Lake Turkana region).
Data-set of CO2, CH4, N2O dissolved concentrations and ancillary data in surface waters of 24 African lakes.
<p>Geo-referenced and timestamped data-set of water temperature, Specific conductivity (SpCond), oxygen saturation level (%O<sub>2</sub>), dissolved methane (CH<sub>4</sub>) concentration, dissolved nitrous oxide (N<sub>2</sub>O) concentration, partial pressure of carbon dioxide (pCO<sub>2</sub>), carbon stable isotope composition of dissolved inorganic carbon (δ<sup>13</sup>C-DIC), dissolved organic carbon (DOC) concentration, chlorophyll-a (Chl-a) concentration, cyanobacteria abundance (CHEMTAX), nitrate (NO<sub>3</sub><sup>-</sup>) and ammonia concentration (NH<sub>4</sub><sup>+</sup>), coloured dissolved organic matter slope ratio (CDOM SR) in surface waters of African 24 lakes (Victoria, Tanganyika, Albert, Kivu, Edward, Mai Ndombe, Tumba, George, Kamohonjo, Alaotra, Ndalaga, Nyamusingere, Kyamwinga, Mbita, Lukulu, Yandja, Mbalukira, Nkugute, Nyamunuka, Kitagata, Mrambi, Kyashanduka, Katinda, Lac Vert).</p>
Distribution. SE Senegal, extreme SW Mali, Guinea-Bissau, Guinea, NW Sierra Leone, Liberia, Ivory Coast, S Burkina Faso, Ghana, Togo, Benin, extreme S Niger, W & C Nigeria, N Cameroon, S Chad, Central African Republic, S & E Sudan, N DR Congo, lowland parts of W Ethiopia, Uganda (not extreme S), NW Kenya (Lake Turkana region). in Bovidae
Distribution. SE Senegal, extreme SW Mali, Guinea-Bissau, Guinea, NW Sierra Leone, Liberia, Ivory Coast, S Burkina Faso, Ghana, Togo, Benin, extreme S Niger, W & C Nigeria, N Cameroon, S Chad, Central African Republic, S & E Sudan, N DR Congo, lowland parts of W Ethiopia, Uganda (not extreme S), NW Kenya (Lake Turkana region).
Distribution. Five disjunct regions: Guinean and Sahelian savannas in W Africa (Guinea and Liberia E to Niger and Nigeria); White Nile valley (Sudan, South Sudan, and NE DR Congo); around Lake Victoria (Uganda, Kenya, and Tanzania); a narrow strip along the E African coast between Mombasa and Dar es Salaam; and SW shore of Lake Tanganyika in NE Zambia, based on a reidentification in 2010 of two specimens in the London Natural History Museum collected in 1920. in Molossidae
Distribution. Five disjunct regions: Guinean and Sahelian savannas in W Africa (Guinea and Liberia E to Niger and Nigeria); White Nile valley (Sudan, South Sudan, and NE DR Congo); around Lake Victoria (Uganda, Kenya, and Tanzania); a narrow strip along the E African coast between Mombasa and Dar es Salaam; and SW shore of Lake Tanganyika in NE Zambia, based on a reidentification in 2010 of two specimens in the London Natural History Museum collected in 1920.
Bangassou near Lake Maboké (near Mongoumba), Central African Republic. Based on proodont incisors, considered to be part of the M. sorella species group, from which it can be distinguished based on its reddish-brown dorsal coloration and blackish, slightly pointed ears. Monotypic. Distribution. Known from just three locali-ties in S Central African Republic. in Muridae
Bangassou near Lake Maboké (near Mongoumba), Central African Republic. Based on proodont incisors, considered to be part of the M. sorella species group, from which it can be distinguished based on its reddish-brown dorsal coloration and blackish, slightly pointed ears. Monotypic. Distribution. Known from just three locali-ties in S Central African Republic.
On following pages: 473. Senegal Striped Grass Mouse (Lemniscomys linulus); 474. Mittendorf's Striped Grass Mouse (Lemniscomys mittendorfi); 475. Hoogstraal's Striped Grass Mouse (Lemniscomys hoogstraali), 476. Buffoon Striped Grass Mouse (Lemniscomys macculus); 477. Griselda Striped Grass Mouse (Lemniscomys griselda); 478. Single-striped Grass Mouse (Lemniscomys rosalia); 479. Rosevear's Striped Grass Mouse (Lemniscomys roseveari); 480. West African Rufous-nosed Rat (Oenomys ornatus); 481. Common Rufous-nosed Rat (Oenomys hypoxanthus); 482. East African Groove-toothed Swamp Rat (Pelomys fallax); 483. Hopkins's Groove-toothed Swamp Rat (Pelomys hopkinsi); 484. Lake Victoria Groove-toothed Swamp Rat (Pelomys isseli); 485. Angolan Groove-toothed Swamp Rat (Pelomys campanae); 486. Least Groove-toothed Swamp Rat (Pelomys minor); 487. Target Rat (Stochomys longicaudatus); 488. Kemp's Thicket Rat (Thamnomys kempi); 489. Hatt's Thicket Rat (Thamnomys majon; 490. Schouteden's Thicket Rat (Thamnomys schoutedeni); 491. Thomas's Thicket Rat (Thamnomys venustus); 492. Namaqua Rock Rat (Micaelamys namaquensis); 493. Grant's Rock Rat (Micaelamys granti); 494. Mesic Four-striped Grass Rat (Rhabdomys dilectus); 495. West-Central South African Fourstriped Grass Rat (Rhabdomys bechuanae); 496. KwaZulu Natal Four-striped Grass Rat (Rhabdomys chakae); 497. Karoo Four-striped Grass Rat (Rhabdomys intermedius); 498. Xeric Four-striped Grass Rat (Rhabdomys pumilio), 499. Loring's Thallomys (Thallomys loringi); 500. Black-tailed Thallomys (Thallomys nigricauda); 501. Sundevall's Thallomys (Thallomys paedulcus); 502. Shortridge's Thallomys (Thallomys shortridgei). in Muridae
On following pages: 473. Senegal Striped Grass Mouse (Lemniscomys linulus); 474. Mittendorf's Striped Grass Mouse (Lemniscomys mittendorfi); 475. Hoogstraal's Striped Grass Mouse (Lemniscomys hoogstraali), 476. Buffoon Striped Grass Mouse (Lemniscomys macculus); 477. Griselda Striped Grass Mouse (Lemniscomys griselda); 478. Single-striped Grass Mouse (Lemniscomys rosalia); 479. Rosevear's Striped Grass Mouse (Lemniscomys roseveari); 480. West African Rufous-nosed Rat (Oenomys ornatus); 481. Common Rufous-nosed Rat (Oenomys hypoxanthus); 482. East African Groove-toothed Swamp Rat (Pelomys fallax); 483. Hopkins's Groove-toothed Swamp Rat (Pelomys hopkinsi); 484. Lake Victoria Groove-toothed Swamp Rat (Pelomys isseli); 485. Angolan Groove-toothed Swamp Rat (Pelomys campanae); 486. Least Groove-toothed Swamp Rat (Pelomys minor); 487. Target Rat (Stochomys longicaudatus); 488. Kemp's Thicket Rat (Thamnomys kempi); 489. Hatt's Thicket Rat (Thamnomys majon; 490. Schouteden's Thicket Rat (Thamnomys schoutedeni); 491. Thomas's Thicket Rat (Thamnomys venustus); 492. Namaqua Rock Rat (Micaelamys namaquensis); 493. Grant's Rock Rat (Micaelamys granti); 494. Mesic Four-striped Grass Rat (Rhabdomys dilectus); 495. West-Central South African Fourstriped Grass Rat (Rhabdomys bechuanae); 496. KwaZulu Natal Four-striped Grass Rat (Rhabdomys chakae); 497. Karoo Four-striped Grass Rat (Rhabdomys intermedius); 498. Xeric Four-striped Grass Rat (Rhabdomys pumilio), 499. Loring's Thallomys (Thallomys loringi); 500. Black-tailed Thallomys (Thallomys nigricauda); 501. Sundevall's Thallomys (Thallomys paedulcus); 502. Shortridge's Thallomys (Thallomys shortridgei).
On following pages: 61. Giffard's Gerbil (Gerbilliscus giffardi); 62. Northern Savanna Gerbil (Gerbilliscus kempii); 63. Fringe-tailed Gerbil (Gerbilliscus robustus); 64. Phillips's Gerbil (Gerbilliscus phillipsi); 65. Black-tailed Gerbil (Gerbilliscus nigricaudus); 66. Southern Savanna Gerbil (Gerbilliscus validus); 67. Bushveld Gerbil (Gerbilliscus leucogaster); 68. East African Gerbil (Gerbilliscus vicinus); 69. Boehm's Gerbil (Gerbilliscus boehmi); 70. Gorongoza Gerbil (Gerbilliscus inclusus); 71. Setzer's Hairy-footed Gerbil (Gerbilliscus setzeri); 72. Dune Hairy-footed Gerbil (Gerbilliscus tytonis); 73. Brush-tailed Hairy-footed Gerbil (Gerbilliscus vallinus); 74. Paeba Hairyfooted Gerbil (Gerbilliscus paeba); 75. Highveld Gerbil (Gerbilliscus brantsii); 76. Cape Gerbil (Gerbilliscus afen; 77. Robbins's Tateril (Taterillus arenarius); 78. Senegal Tateril (Taterillus pygargus); 79. Petter's Tateril (Taterillus petteri); 80. Tranier's Tateril (Taterillus tranieri); 81. Gracile Tateril (Taterillus gracilis); 82. Congo Tateril (Taterillus congicus); 83. Lake Chad Tateril (Taterillus lacustris); 84. Emin's Tateril (Taterillus emini); 85. Cape Short-tailed Gerbil (Desmodillus auricularis). in Muridae
On following pages: 61. Giffard's Gerbil (Gerbilliscus giffardi); 62. Northern Savanna Gerbil (Gerbilliscus kempii); 63. Fringe-tailed Gerbil (Gerbilliscus robustus); 64. Phillips's Gerbil (Gerbilliscus phillipsi); 65. Black-tailed Gerbil (Gerbilliscus nigricaudus); 66. Southern Savanna Gerbil (Gerbilliscus validus); 67. Bushveld Gerbil (Gerbilliscus leucogaster); 68. East African Gerbil (Gerbilliscus vicinus); 69. Boehm's Gerbil (Gerbilliscus boehmi); 70. Gorongoza Gerbil (Gerbilliscus inclusus); 71. Setzer's Hairy-footed Gerbil (Gerbilliscus setzeri); 72. Dune Hairy-footed Gerbil (Gerbilliscus tytonis); 73. Brush-tailed Hairy-footed Gerbil (Gerbilliscus vallinus); 74. Paeba Hairyfooted Gerbil (Gerbilliscus paeba); 75. Highveld Gerbil (Gerbilliscus brantsii); 76. Cape Gerbil (Gerbilliscus afen; 77. Robbins's Tateril (Taterillus arenarius); 78. Senegal Tateril (Taterillus pygargus); 79. Petter's Tateril (Taterillus petteri); 80. Tranier's Tateril (Taterillus tranieri); 81. Gracile Tateril (Taterillus gracilis); 82. Congo Tateril (Taterillus congicus); 83. Lake Chad Tateril (Taterillus lacustris); 84. Emin's Tateril (Taterillus emini); 85. Cape Short-tailed Gerbil (Desmodillus auricularis).
Data from: Genomic islands of speciation separate cichlid ecomorphs in an East African crater lake
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Data from: Adaptive phenotypic plasticity contributes to divergence between lake and river populations of an East African cichlid fish
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Data from: Adaptive divergence between lake and stream populations of an East African cichlid fish
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Fig. 2. a in Revision of the African cichlid fish genus <em><em>Ctenochromis</em></em> (Teleostei, Cichliformes), including a description of the new genus <em>Shuja</em> from Lake Tanganyika and the new species <em><em>Ctenochromis</em></em> <em>scatebra</em> from northern Tanzania
Fig. 2. a. Ruvu River where specimens of Ctenochromis pectoralis Pfeffer, 1893 were collected. b. Chemka Springs where specimens of C. scatebra Genner, Ngatunga & Turner sp. nov. were collected.
Figure 2. Sinanodonta woodiana from Algeria, Oubeira Lake. A in First record of the occurrence of the Chinese pond mussel Sinanodonta woodiana (Lea, 1834) (Bivalvia: Unionidae) in African freshwaters: Oubeira Lake, Algeria
Figure 2. Sinanodonta woodiana from Algeria, Oubeira Lake. A: live specimens of S. woodiana collected from Oubeira sediment; B: general view of soft body (a: gills; b: foot; c: mantle); C: external view of the shell; D: internal view of the shell; E: details of umbonal sculptures. Photos: BensaâdBendjedid L.
Linked collectors and determiners for: Revision of the African cichlid fish genus Ctenochromis (Teleostei, Cichliformes), including a description of the new genus Shuja from Lake Tanganyika and the new species Ctenochromis scatebra from northern Tanzania.
Natural history specimen data linked to collectors and determiners held within, "Revision of the African cichlid fish genus Ctenochromis (Teleostei, Cichliformes), including a description of the new genus Shuja from Lake Tanganyika and the new species Ctenochromis scatebra from northern Tanzania". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/02a5d778-d054-4731-b306-6906c0f9a425">https://bionomia.net/dataset/02a5d778-d054-4731-b306-6906c0f9a425</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/02a5d778-d054-4731-b306-6906c0f9a425">https://gbif.org/dataset/02a5d778-d054-4731-b306-6906c0f9a425</a>. Formatted as a Frictionless Data package.
Epigenetic Divergence during Early Stages of Speciation in an African Crater Lake Cichlid Fish
GEO Series GSE174120. Astatotilapia calliptera. 66 samples. Type: Expression profiling by high throughput sequencing; Methylation profiling by high throughput sequencing.
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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
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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
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