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8,119 results for “species distribution”
FIGURE 3 in The genus Obrium Dejean, 1821 (Coleoptera: Cerambycidae: Cerambycinae Obriini) in Argentina: new species, distributions and host plant
FIGURE 3. Geographic distributions of the species of Obrium in Argentina: O. bifasciatum (white squares); O. cicatricosum (white circles); O. mimicum sp. n. (black star); O. trilobatum sp. n. (black triangles); O. trifasciatum (black circles).
FIGURE 4 in The genus Obrium Dejean, 1821 (Coleoptera: Cerambycidae: Cerambycinae Obriini) in Argentina: new species, distributions and host plant
FIGURE 4. Geographic distributions of the species of Obrium in Argentina: O. multifarium (black squares); O. vicinum (white circles).
FIGURE 1 in The genus Obrium Dejean, 1821 (Coleoptera: Cerambycidae: Cerambycinae Obriini) in Argentina: new species, distributions and host plant
FIGURE 1. General aspect of the species of Obrium in Argentina: a. Obrium bifasciatum; b. Obrium cicatricosum; c. Obrium mimicum sp. n. Scale bar = 5mm.
Provisioning forest and conservation science with European tree species distribution models under climate change
<p>Estimating shifts in the current range of forest tree species is crucial for formulating adaptive management strategies such as assisted migration. Ecological niche models have been the most widely used tools to estimate the potential climatic suitability of species worldwide. The reliability of such estimations depends on the model algorithm and the input data such as climate and species occurrence. We developed a dataset of the potential distribution of seven ecologically and economically important tree species of Europe in terms of their climatic suitability with an ensemble approach while accounting for uncertainty due to model algorithms. The distribution models shall be the basis for follow-up studies in forest and conservation science.</p>
FIGURE 6 in Two new species of Pristimantis (Anura: Craugastoridae) with notes on the distribution of the genus in northeastern Colombia
FIGURE 6. Illustration of the morphological characteristics of palmar surface, the foot and the head (lateral and dorsal view): A. Pristimantis ardilae sp. nov. B. Pristimantis bowara sp. nov. Scale bar = 5 mm.
Distribution. Extent of this species' dis tribution is not yet known; recorded with certainty in Morocco, Senegal, Saudi Ara bia, and Yemen. It is thought to be con tinuously distributed from Mauritania and Senegal E to South Sudan, Ethiopia, and Eritrea. However, boundary between this species and the morphologically identical H. coffer is not known. in Family Hipposideridae (Old World Leaf-nosed Bats)
Distribution. Extent of this species' dis tribution is not yet known; recorded with certainty in Morocco, Senegal, Saudi Ara bia, and Yemen. It is thought to be con tinuously distributed from Mauritania and Senegal E to South Sudan, Ethiopia, and Eritrea. However, boundary between this species and the morphologically identical H. coffer is not known.
Distribution. Widely in S Africa, but N & W boundaries are not yet known; known to occur in S DR Congo, W Angola, Zambia, Malawi, Mozambique, Namibia, N Botswana, Zimbabwe, South Africa, and Swaziland. A species morphologically identical to Ä caffer occurs widely in East Africa but whether this refers to H. caffer or H. tephrus has not yet been established. in Hipposideridae
Distribution. Widely in S Africa, but N & W boundaries are not yet known; known to occur in S DR Congo, W Angola, Zambia, Malawi, Mozambique, Namibia, N Botswana, Zimbabwe, South Africa, and Swaziland. A species morphologically identical to Ä caffer occurs widely in East Africa but whether this refers to H. caffer or H. tephrus has not yet been established.
Distribution. Known with certainty only from Chiang Mai Province, NW Thailand, although it is probably the species that occurs in NW, W & SE Thailand, including Tarutao I; specimens from Cambodia, found to be intermediate in size between Dobson's Horseshoe Bat (. yunanensis) and Pearson's Horseshoe Bat (. pearsonii), are also tentatively included in this species. in Rhinolophidae
Distribution. Known with certainty only from Chiang Mai Province, NW Thailand, although it is probably the species that occurs in NW, W & SE Thailand, including Tarutao I; specimens from Cambodia, found to be intermediate in size between Dobson's Horseshoe Bat (. yunanensis) and Pearson's Horseshoe Bat (. pearsonii), are also tentatively included in this species.
Subspecies and Distribution. R.f. frantisi Soisook et al, 2015 - known only from a few localities in N, SW & S Borneo. R.f. thailandicus Soisook & Bates, 2015 — known only from type locality in SW Thailand. Genetic data suggest that the species may also occur in Vietnam, but this requires more research. in Rhinolophidae
Subspecies and Distribution. R.f. frantisi Soisook et al, 2015 - known only from a few localities in N, SW & S Borneo. R.f. thailandicus Soisook & Bates, 2015 — known only from type locality in SW Thailand. Genetic data suggest that the species may also occur in Vietnam, but this requires more research.
Subspecies and Distribution. R. c. cognatus K Andersen, 1906 - Andaman Is (South Andaman). R. c. famulus K. Andersen, 1918 - Andaman Is (North, Point, Interview, Baratang, and Narcondam). The species is not known from the Nicobar Is, despite a number of sources listing it from them. in Rhinolophidae
Subspecies and Distribution. R. c. cognatus K Andersen, 1906 - Andaman Is (South Andaman). R. c. famulus K. Andersen, 1918 - Andaman Is (North, Point, Interview, Baratang, and Narcondam). The species is not known from the Nicobar Is, despite a number of sources listing it from them.
FIGURES 18–26. Distribution maps for Metallactus hamifer species-group. M in Revision of the Metallactus hamifer species-group (Coleoptera: Chrysomelidae: Cryptocephalinae)
FIGURES 18–26. Distribution maps for Metallactus hamifer species-group. M. abditus (18); M. agonista (19); M. albivittis (20); M. albopictus (21); M. bivitticollis (22); M. chamorroi (23); M. crassicollis (24); M. dicaprioi (25); M. hamifer (26). Grey squares: localities reported in a generic way.
FIGURE5. Maximum likelihood tree based on the Kimura 2-parameter model of the COI sequences from the Siphamia species with P. kauderni as the outgroup. Tree shown here has the highest log likelihood following 10 000 replications. The percentage of trees in which the associated taxa clustered together is shown next to the branches, branch lengths are measured in the number of substitutions per site and all positions containing gaps and missing data have been eliminated. in Redescription and distributional range extension of the Speckled Siphonfish, Siphamia guttulata (Pisces: Apogonidae)
FIGURE5. Maximum likelihood tree based on the Kimura 2-parameter model of the COI sequences from the Siphamia species with P. kauderni as the outgroup. Tree shown here has the highest log likelihood following 10 000 replications. The percentage of trees in which the associated taxa clustered together is shown next to the branches, branch lengths are measured in the number of substitutions per site and all positions containing gaps and missing data have been eliminated.
FIGURE4.Map of selected records of Siphamia species recorded in Queensland and Papua New Guinea waters in 2003–2005, including the type locality of Siphamia guttulata. Some symbols represent more than one specimen. in Redescription and distributional range extension of the Speckled Siphonfish, Siphamia guttulata (Pisces: Apogonidae)
FIGURE4.Map of selected records of Siphamia species recorded in Queensland and Papua New Guinea waters in 2003–2005, including the type locality of Siphamia guttulata. Some symbols represent more than one specimen.
FIGURES 46–54 in Hidden gems in museum cabinets: new species and new distributional records of Scolytodes (Coleoptera: Scolytinae)
FIGURES 46–54. Dorsal, lateral and front view of the female holotype of Scolytodes capillus (46, 49, 52), S. rufus (47, 50, 53), and S. johnsoni (48, 51, 54).
FIGURES 10–18 in Hidden gems in museum cabinets: new species and new distributional records of Scolytodes (Coleoptera: Scolytinae)
FIGURES 10–18. Dorsal, lateral and front view of the holotype of male Scolytodes potens (10, 13, 16), female S. minimus (11, 14, 17), and female S. setosicauda (12, 15, 18).
FIGURES 55–63 in Hidden gems in museum cabinets: new species and new distributional records of Scolytodes (Coleoptera: Scolytinae)
FIGURES 55–63. Dorsal, lateral and front view of the holotype of Scolytodes longipilus (55, 58, 61), female S. prolatus (56, 59, 62), and female S. bicarinatus (57, 60, 63).
FIGURES 13–14 in Review of the genus Bubaces (Hemiptera: Heteroptera: Rhyparochromidae Lethaeini) with descriptions of three new species, new distributional records, and key to species
FIGURES 13–14. Metathoracic scent gland peritreme of Bubaces occidentalis sp. nov. 13, male. 14, female. FIGURES 15–22. Parameres of Bubaces spp. 15–16, B. castaneus Distant. 17–18, B. gloriosus sp. nov. 19–20, B. occidentalis sp. nov. 21–22, B. rostralis sp. nov.
FIGURES 1–7 in Review of the genus Bubaces (Hemiptera: Heteroptera: Rhyparochromidae Lethaeini) with descriptions of three new species, new distributional records, and key to species
FIGURES 1–7. Dorsal view of Bubaces spp. 1, B. castaneus Distant (female). 2, B. convergens Brailovsky (male). 3, B. enatus Brailovsky (female). 4, B. gloriosus sp. nov. (female). 5, B. occidentalis sp. nov. (male). 6, B. rostralis sp. nov. (male). 7, B. uhleri (Distant) (male).
High-resolution future climate data for species distribution models in Europe
<p><strong>Description</strong></p> <p>This dataset contains a set of 13 climatological variables (<code>Variable</code>, <code>VariableName</code>) at a spatial resolution of 1x1km for Europe (nx = 13147, ny = 6071) for historical (<code>ClimatePeriod</code>) and future climate conditions. These variables are a subset of the so-called bioclimatic variables that are often part of global gridded datasets (e.g. <a href="https://worldclim.org/data/bioclim.html">WorldClim</a>, <a href="http://chelsa-climate.org/bioclim/">CHELSA</a>) that have been specifically developed for species distribution modelling and ecological applications.</p> <p>The climatological data correspond to 35-year (<code>Startyear_Endyear</code> = <code>1971_2005</code>) and 30-year (<code>Startyear_Endyear</code> = <code>2041_2070</code>) mean values representing respectively historical and future climate conditions. To account for the future climate conditions, three possible emission scenarios of greenhouse gases as defined by the <a href="https://www.ipcc.ch/">Intergovernmental Panel on Climate Change (IPCC)</a> are used (<code>ClimatePeriod</code> = <code>rcp26</code>, <code>rcp45</code>, <code>rcp85</code>).</p> <p>The complete set of variables (var[1-13]) for which historical and future climate data layers are produced are given below.</p> <p>The source data for the climate layers were assembled from the <a href="https://cordex.org/data-access/">EURO-CORDEX archive</a> (Kotlarski et al., 2014). More specifically, we have used the regional climate model simulations for Europe at a spatial resolution of 12.5x12.5km on which a three-step statistical downscaling approach has been applied:</p> <ol> <li><strong>Processing</strong> (averaging, totals, …) of all available time series of the EURO-CORDEX model experiments (<code>ClimatePeriod</code> = evaluation, historical, rcp) for the climatological variables.</li> <li><strong>Interpolation</strong> of the data layers from the 12.5x12.5km EURO-CORDEX grid to a 1x1km spatial <a href="http://chelsa-climate.org/">CHELSA</a> (Karger et al., 2017) reference grid (see files <code>lat_1km.csv</code> and <code>lon_1km.csv</code>).</li> <li><strong>Calculate differences</strong> between the 1x1km-interpolated variables (<code>Variable</code> = only for var[1-9]) from the evaluation model experiments (or <code>ClimatePeriod</code>) and the corresponding reference bioclimatic CHELSA variables. In order to account for possible biases present in the EURO-CORDEX climate models, these differences (or biases) are then subtracted from the respective 1x1-km-interpolated variables for the historical and rcp model experiments (<code>ClimatePeriod</code>).</li> </ol> <p>The dimensions of the 1x1km grid (excl. the first row and column):</p> <ul> <li>y-dimension = number of columns = 6071</li> <li>x-dimension = number of rows = 13147</li> </ul> <p>The longitudes and latitudes of respectively the southwest and northeast corner of the grid are:</p> <ul> <li>longitude -44.592; latitude 21.991 (southwest corner)</li> <li>longitude 64.967; latitude 72.583 (northeast corner)</li> </ul> <p>The climatological variables are used as input data for the species distribution modelling of Invasive Alien Species for the <a href="https://osf.io/7dpgr/">Tracking Invasive Alien Species (TrIAS)</a> project.</p> <p><strong>Variables</strong></p> <ul> <li><strong>Variable</strong> (VariableName): Unit</li> <li><strong>var1</strong> (AnnualMeanTemperature): °C</li> <li><strong>var2</strong> (AnnualAmountPrecipitation): mm year<sup>-1</sup></li> <li><strong>var3</strong> (AnnualVariationPrecipitation): coefficient of variation</li> <li><strong>var4</strong> (AnnualVariationTemperature): stdev</li> <li><strong>var5</strong> (MaximumTemperatureWarmestMonth): °C</li> <li><strong>var6</strong> (MinimumTemperatureColdestMonth): °C</li> <li><strong>var7</strong> (TemperatureAnnualRange): °C</li> <li><strong>var8</strong> (PrecipitationWettestMonth): mm</li> <li><strong>var9</strong> (PrecipitationDriestMonth): mm</li> <li><strong>var10</strong> (30yrMeanAnnualCumulatedGDDAbove5degreesC): °C days</li> <li><strong>var11</strong> (AnnualMeanPotentialEvapotranspiration): mm day<sup>-1</sup></li> <li><strong>var12</strong> (AnnualMeanSolarRadiation): W m<sup>-2</sup></li> <li><strong>var13</strong> (AnnualVariationSolarRadiation): stdev</li> </ul> <p><strong>Files</strong></p> <ul> <li><strong>varX_VariableName_ClimatePeriod_Startyear_Endyear.csv</strong>: climatological data layers for the 13 variables listed above</li> <li><strong>lon_1km.csv</strong>: longitudes for the 1x1km grid</li> <li><strong>lat_1km.csv</strong>: latitudes for the 1x1km grid</li> </ul>
FIGURES 41–46. Platydracus juang 41 in New distributional records of Staphylinina in Taiwan, including a new species of Miobdelus Sharp (Coleoptera: Staphylinidae: Staphylininae: Staphylinini)
FIGURES 41–46. Platydracus juang 41. Aedeagus in ventral view; 42. Aedeagus in lateral view; 43. Sternite 9, male; 44. Sternite 8, male; 45. Tergite 10, male; 46. Tergite 10, female. Scale bar: 0.5 mm
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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.