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Figure 16 in A revision of the egg-eating snakes of the genus Dasypeltis Wagler (Squamata: Colubridae: Colubrinae) in north-eastern Africa and south-western Arabia, with descriptions of three new species
Figure 16. Vicinity of Hargeisa, Somaliland—habitat of Dasypeltis taylori sp. nov. (Photo: T. Mazuch)
Figure 9 in A revision of the egg-eating snakes of the genus Dasypeltis Wagler (Squamata: Colubridae: Colubrinae) in north-eastern Africa and south-western Arabia, with descriptions of three new species
Figure 9. Dasypeltis bazi. Dorsal (A) and ventral (B) views of a male (ZMB 1861) from 'Upper Egypt'. (Photos: F. Tillack)
Figure 1 in A revision of the egg-eating snakes of the genus Dasypeltis Wagler (Squamata: Colubridae: Colubrinae) in north-eastern Africa and south-western Arabia, with descriptions of three new species
Figure 1. Tail length (mm) relative to snout-vent length (mm) in males and females of Dasypeltis atra, D. scabra, D. confusa, D. medici, D. fasciata and D. abyssina in north-eastern Africa.
Figure 13 in A revision of the egg-eating snakes of the genus Dasypeltis Wagler (Squamata: Colubridae: Colubrinae) in north-eastern Africa and south-western Arabia, with descriptions of three new species
Figure 13. Dasypeltis taylori sp. nov. Body and head views of the holotype (BM 1949.2.2.2) from Haud, Somaliland. (Photos: Natural History Museum, London)
Figure 8 in A revision of the egg-eating snakes of the genus Dasypeltis Wagler (Squamata: Colubridae: Colubrinae) in north-eastern Africa and south-western Arabia, with descriptions of three new species
Figure 8. Dasypeltis bazi. Dorsal (left), lateral (middle) and ventral (right) views of the head of the largest known female (BM 97.10.28.575) from Fayoum, Egypt. (Photo: Natural History Museum, London)
Figure 12 in A revision of the egg-eating snakes of the genus Dasypeltis Wagler (Squamata: Colubridae: Colubrinae) in north-eastern Africa and south-western Arabia, with descriptions of three new species
Figure 12. Dasypeltis cf. bazi. Dorsal view of the anterior part of the body of a specimen (ZFMK 38415) from Erkowit, Sudan. (Photo: W. Böhme)
Figure 7. Dasypeltis bazi. A in A revision of the egg-eating snakes of the genus Dasypeltis Wagler (Squamata: Colubridae: Colubrinae) in north-eastern Africa and south-western Arabia, with descriptions of three new species
Figure 7. Dasypeltis bazi. A: Dorsal and lateral views of the largest known female (BM 97.10.28.575) from Fayoum, Egypt (Photo: M.F. Bates); B: Ventral view of the same specimen (Photo: Natural History Museum, London).
Figure 11 in A revision of the egg-eating snakes of the genus Dasypeltis Wagler (Squamata: Colubridae: Colubrinae) in north-eastern Africa and south-western Arabia, with descriptions of three new species
Figure 11. Dorsal views of Dasypeltis loveridgei comb. nov. ['6N' colour pattern of Gans 1959; specimen also has 6 supralabials on either side of head, with 2nd and 3rd in contact with orbital] (female, ZMB 33670a, top) from Otjimbingwe, Namibia, and Dasypeltis bazi (male, ZMB 1861, below) from 'Upper Egypt' showing the general similarity in colour pattern. (Photo: M.F. Bates)
Figure 4 in A revision of the egg-eating snakes of the genus Dasypeltis Wagler (Squamata: Colubridae: Colubrinae) in north-eastern Africa and south-western Arabia, with descriptions of three new species
Figure 4. Dasypeltis confusa. ['5L' colour pattern of Gans 1959] A: Bisu (Kigezi), Uganda. (BM 1951.1.3.69, Photo: M.F. Bates); B: Kacheliba, Kenya (NMK 489, Photo: P. Malonza); C: Mumias, Kenya (CAS 141784, Photo: J. Vindum); D: Lake Kivu, Rwanda (ZMB 77441, Photo: F. Tillack).
Figure 10 in A revision of the egg-eating snakes of the genus Dasypeltis Wagler (Squamata: Colubridae: Colubrinae) in north-eastern Africa and south-western Arabia, with descriptions of three new species
Figure 10. Dasypeltis bazi. Dorsal (left), lateral (middle) and ventral (right) views of the head of a male (ZMB 1861) from 'Upper Egypt'. (Photos: F. Tillack)
Figure 3 in A revision of the egg-eating snakes of the genus Dasypeltis Wagler (Squamata: Colubridae: Colubrinae) in north-eastern Africa and south-western Arabia, with descriptions of three new species
Figure 3. Geographical distribution of the genus Dasypeltis in north-eastern Africa and south-western Arabia.
Figure 2. Dasypeltis medici. A in A revision of the egg-eating snakes of the genus Dasypeltis Wagler (Squamata: Colubridae: Colubrinae) in north-eastern Africa and south-western Arabia, with descriptions of three new species
Figure 2. Dasypeltis medici. A: Vicinity of Dar-es-Salaam, Tanzania (Photo: W.R. Branch); B: Juvenile from East Usambara Mountains, Tanzania (Photo: W.R. Branch); C: Watamu, Kenya (Photo: S. Spawls); D: Tanga, Tanzania (Photo: S. Spawls); E & F: Diani Beach, Kenya (Photos: F. Finke). [A & B are colour pattern '8' ('medici'), C & D are pattern '3' ('lamuensis', mostly unmarked), and E & F—same individual—are intermediate (weakly marked).]
Figure 6 in A revision of the egg-eating snakes of the genus Dasypeltis Wagler (Squamata: Colubridae: Colubrinae) in north-eastern Africa and south-western Arabia, with descriptions of three new species
Figure 6. Dasypeltis scabra. Close-up dorsal view (in alcohol) of MNHN 7227 (paralectotype of Rachiodon abyssinus, see p. 39) from the White Nile River (possibly near Khartoum, Sudan) showing a '5N' pattern (see Gans 1959) consisting of dark oval saddles and dark dorso-ventrally elongated lateral bars, with paler centres. (Photo: M.F. Bates)
Figure 5 in A revision of the egg-eating snakes of the genus Dasypeltis Wagler (Squamata: Colubridae: Colubrinae) in north-eastern Africa and south-western Arabia, with descriptions of three new species
Figure 5. Dasypeltis scabra. ['5N' colour pattern of Gans 1959] A: Dodoma, Tanzania (Photo: W.R. Branch); B: Masiko ya Tembo, Tanzania (Photo: W.R. Branch), C: Wajir, Kenya (Photo: S. Spawls); D: Juvenile from Loita Hills, Kenya (Photo: T. Mazuch); E: Gilgil, Kenya (Photo: S. Spawls); F: MSNM 974, Magadi, Somalia (Photo: Museo Civico di Storia Naturale, Milan); G: Awash National Park, Ethiopia (Photo: S. Spawls); H: Awash National Park, Ethiopia (Photo: S. Spawls).
Μονή Θάρρι Moni Thari, Rodos. Church from the north east.
<p>Μονή Θάρρι Moni Thari, Ρόδος Rodos. Church from the north east.</p>
WRF output. Resolution: 12 km. Domain: Eastern North America
<p>Derived products from WRF simulations at 12 km resolution. LBC: ERA-Interim. Output every 10-min. Output level: 3rd model level </p> <p>Details given in: Pryor S.C. et al. (2018): Inter-annual variability of wind climates and wind turbine annual energy production. Manuscript published in Wind Energy Science.</p> <p>5 netcdf files;</p> <p>Pryoretal_WES2018_part1.nc contains information shown in Figure 3. Included variables; lat, lng, medianWSHH, CI(medianWSHH), vectors of data in WT grid cells and in grid cells without WT.</p> <p>Pryoretal_WES2018_part2.nc contains information shown in Figure 4. Included variables; Weibull distribution fits by wind speed bin and year, and FFT of output from TX, IA, and NY.</p> <p>Pryoretal_WES2018_part3.nc contains information shown in Figure 5. Included variables; lat, lng, 50th and 90th percentile WI, AEP and difference, vectors of data in WT grid cells and in grid cells without WT.</p> <p>Pryoretal_WES2018_part4.nc contains information shown in Figure 6.Included variables; lat, lng, 50th and 90th percentile AEP and difference, vectors of data in WT grid cells and in grid cells without WT.</p> <p>Pryoretal_WES2018_part5.nc contains information shown in Figure 7. Included variables; lat, lng, time of minimum, time of maximum.</p> <p> </p>
Climatic dissimilarity data for North America at 1 km resolution.
<p>The raster data layers contained in this archive represent climatic dissimilarity as the distance in multivariate climate space (represented by the 1st and 2nd axes of a principal components analysis based on 11 bioclimatic variables) between current (1981-2010) and future (either 2041-2070 ("2055") or 2071-2100 ("2085")) time periods. Ensemble data are based on mean projections from 15 CMIP5 models (CanESM2, ACCESS1.0, IPSL-CM5A-MR, MIROC5, MPI-ESM-LR, CCSM4, HadGEM2-ES, CNRM-CM5, CSIRO Mk 3.6, GFDL-CM3, INM-CM4, MRI-CGCM3, MIROC-ESM, CESM1-CAM5, GISS-E2R) that were chosen to represent all major clusters of similar AOGCMs. Projections from 8 of these 15 GCMs were also used to generate dissimilarity values based on individual GCM projections. Input bioclimatic data was developed by statistical downscaling using the ClimateNA software developed by T. Wang. Additional description of the data can be found at https://adaptwest.databasin.org/pages/climatic-dissimilarity.</p>
Spatial patterns of uncertainty in climate exposure metrics for North America at 1km resolution
<p>The data provided below represents the degree of uncertainty or variation between 8 individual general circulation models (GCM) for three metrics commonly used to assess the intensity of exposure to climate change. The three exposure metrics (forward and backward <a href="https://adaptwest.databasin.org/pages/adaptwest-velocitywna">climatic velocity</a> and <a href="https://adaptwest.databasin.org/pages/climatic-dissimilarity">local climatic dissimilarity</a>) were calculated based on the first two principal components (PC) scores derived from <a href="https://adaptwest.databasin.org/pages/climatic-dissimilarity">11 different climate variables</a>. Frameworks and heuristics supporting climate adaptation for conservation often rely on projections of climate change or climate exposure. However, projections of climate change vary among alternative GCM outputs, different emissions scenarios, and different future time periods. The potential for these model predictions to vary geographically presents a source of uncertainty in assigning climate-informed conservation strategies to landscapes. Regions with high agreement among predictions could be more confidently assigned a climate-informed strategy, whereas regions with less agreement among predictions may require a more cautious approach. More information on the data can be found at https://adaptwest.databasin.org/pages/uncertainty-climate-metrics.</p>
WRF-Chem output. Resolution: 24 km. Domain: Eastern North America
<p>Derived products from WRF-Chem simulations at 24 km resolution.</p> <p>Details given in: Crippa P. et al. (2019): Sensitivity of simulated aerosol properties over eastern North America to WRF-Chem parameterizations. Manuscript published in the Journal of Geophysical Research.</p> <p>14 netcdf files:</p> <p>Crippaetal_JGR2019_AOD.nc contains monthly mean AOD cloud screened for each ensemble member.</p> <p>Crippaetal_JGR2019_net_radiation.nc contains monthly mean surface net radiation for each ensemble member.</p> <p>Crippaetal_JGR2019_NO3_fine.nc contains monthly mean NO3 in the fine aerosol mode for each ensemble member.</p> <p>Crippaetal_JGR2019_SO4_fine.nc contains monthly mean SO4 in the fine aerosol mode for each ensemble member.</p> <p>Crippaetal_JGR2019_PM25_daily.nc contains daily PM<sub>2.5 </sub>concentrations for each ensemble member.</p> <p>Crippaetal_JGR2019_O3_daily.nc contains daily mean surface ozone concentrations in the fine aerosol mode for each ensemble member.</p> <p>Crippaetal_JGR2019_PBLH.nc contains monthly mean planetary boundary layer height for each ensemble member regridded on the MERRA-2 resolution</p> <p>Crippaetal_JGR2019_T2.nc contains monthly mean surface temperature at 2m for each ensemble member regridded on the MERRA-2 resolution</p> <p>Crippaetal_JGR2019_QPBL.nc contains monthly mean specific humidity in the PBL for each ensemble member regridded on the MERRA-2 resolution</p> <p>Crippaetal_JGR2019_PPT.nc contains monthly total precipitation for each ensemble member regridded on the MERRA-2 resolution</p> <p>Crippaetal_JGR2019_lat_WRF-Chem.nc contains the latitude coordinates of the WRF-Chem grid</p> <p>Crippaetal_JGR2019_lon_WRF-Chem.nc contains the longitude coordinates of the WRF-Chem grid</p> <p>Crippaetal_JGR2019_lat_MERRA2.nc contains the latitude coordinates of the MERRA2 grid</p> <p>Crippaetal_JGR2019_on_MERRA2.nc contains the longitude coordinates of the MERRA2 grid</p>
Historical PM2.5 dataset across North America
<p>This dataset is the estimated long-term (1981-2016) concentrations of ambient fine particulate matter across North America, which combines information from chemical transport modeling, satellite remote sensing, and ground-based monitoring. The estimates included information from updated historical emissions inventories and meteorological data, fine resolution satellite-based estimates of PM<sub>2.5</sub>, and ground-based measurements of PM<sub>2.5</sub>, PM<sub>10</sub> and total suspended particles (TSP) measurements.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.