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68 results for “distributional boundary”
Data set: Variations in water economy traits in two Sphagnum species across their distribution boundaries
<p><em>Sphagnum</em> trait data collected (2016-2017) across a climatic gradient in Sweden. Trait data for both shoot and canopy traits. Data for <em>Sphagnum cuspidatum</em> and <em>Sphagnum lindbergii</em>. Also contains data on species occurrence records in Sweden and output from speceis distribution modelling. See published paper for more information.</p> <p>Files contain (i) processed data ("calculated_trait_data...cvs"), (ii) raw data ("Campbell_etal_clim_traits_...cvs"), (iii) their readme files, and (iv) R-scripts to run the analyses. Note that you need the files in the zip-file to run the analyses in the R-script. The zip-file contains all raw data (climate, traits, species occurences), MaxEnt output, and raster files from photogrammetry.</p> <p>More info in paper: <a href="https://doi.org/10.1002/ajb2.16347" target="_blank" rel="noopener">https://doi.org/10.1002/ajb2.16347</a></p>
Рис. 1. Карта района иссΛеΑований. 1 – граница зон раститеΛьности; 2 – граница поΑзон раститеΛьности; 3 – места сбора материаΛа; I – южная тайга; II – среΑняя тайга; III – северная тайга; IV – крайнесеверная тайга; V – ΛесотунΑра; VI – южная тунΑра; VII – северная тунΑра. Fig. 1. Map of the studied area. 1 – boundary of vegetation zones; 2 – boundary of vegetation subzones; 3 – collection points; I – southern taiga; II – middle taiga; III – northern taiga; IV – extremely northern taiga; V – forest tundra; VI – southern tundra; VII – northern tundra. in Fauna and landscape-zonal distribution of Orthoptera in the Komi Republic (Russia)
Рис. 1. Карта района иссΛеΑований. 1 – граница зон раститеΛьности; 2 – граница поΑзон раститеΛьности; 3 – места сбора материаΛа; I – южная тайга; II – среΑняя тайга; III – северная тайга; IV – крайнесеверная тайга; V – ΛесотунΑра; VI – южная тунΑра; VII – северная тунΑра. Fig. 1. Map of the studied area. 1 – boundary of vegetation zones; 2 – boundary of vegetation subzones; 3 – collection points; I – southern taiga; II – middle taiga; III – northern taiga; IV – extremely northern taiga; V – forest tundra; VI – southern tundra; VII – northern tundra.
Porosity distribution in sub-skin boundary area of the powderbed additively manufactured parts
<p>Repository contains measurement results of the experimental investigationn of the sub-skin porosity in additively manufactured parts. Specimens were manufactured using machine manufacturer's suggested process parameters. Four different machines (EOS M400, TRUMPF TruPrint 1000, SLM 280 and DMG MORI LASERTEC 30 2nd gen.) and four different powder materials (mararging steel 1.2709, aluminum alloy AlSi10Mg, Titanium grade 5 and stainless steel 1.4404) are covered. Influences of the relative orientation of the hatch and boundary scanning tracks was investigated. Efficiency of the mitigation strategy againts sub-skin porosity issues through distance variation between hatch and boundary tracks was evaluated.</p> <p>Please refer to README.MD (or .PDF) for more detailed information about this dataset.</p>
Fig. 1 in INSUFFICIENT COLD RESISTANCE AND THE EASTERN BOUNDARY OF THE DISTRIBUTION RANGE OF ANT LASIUS FULIGINOSUS (HYMENOPTERA: FORMICIDAE)
Fig. 1. Supercooling points (SCP) distributions of the Lasius fuliginosus from 3 nests from the environs of the Novosibirsk. In the right upper corner of the picture there is a number of the nest.
Data Supporting The role of dopant segregation on the oxygen vacancy distribution and oxygen diffusion in CeO2 grain boundaries
<p>Data supporting the article "The role of dopant segregation on the oxygen vacancy distribution and oxygen diffusion in CeO<sub>2</sub> grain boundaries, accepted for publication in the Journal of Physics: Energy (<a href="https://doi.org/10.1088/2515-7655/ab28b5">doi.org/10.1088/2515-7655/ab28b5</a>). Data includes inputs for molecular dynamics simulations using the DL_POLY classic code.Simulations can be rerun from the inputs provide. </p> <p>Input data required for the generation of the grain boundary structures is included and uses the METADISE code. </p>
Text-fig. 1. Palaeogeographical scheme (distribution of land and sea basins) in part of Eurasia at the beginning of the Late Cretaceous (modified from Spicer et al. 2008). The green leaf symbol indicates the site of the Arman Flora. Asterisks indicate the Okhotsk-Chukotka volcanogenic belt. Dashdotted line indicates the boundary between the Siberian- Canadian and Euro-Sinian palaeofloristic regions (modified from Vakhrameev 1991). in On The Likely Palaeoelevation Of The Turonian - Coniacian Arman Flora Site (North-Eastern Asia)
Text-fig. 1. Palaeogeographical scheme (distribution of land and sea basins) in part of Eurasia at the beginning of the Late Cretaceous (modified from Spicer et al. 2008). The green leaf symbol indicates the site of the Arman Flora. Asterisks indicate the Okhotsk-Chukotka volcanogenic belt. Dashdotted line indicates the boundary between the Siberian- Canadian and Euro-Sinian palaeofloristic regions (modified from Vakhrameev 1991).
Data for "A snapshot of the long term evolution of a distributed tectonic plate boundary" submitted to Science Advances
<p>This compressed folder contains data presented in Figures of the following paper: "<strong>A snapshot of the long term evolution of a distributed tectonic plate boundary</strong>" by M. Dalaison, R. Jolivet, L. Le Pourhiet; submitted to <em>Science Advances</em> in February 2023</p> <p>Please open the README.txt file for details about the folder's content</p>
Mars Watershed boundary data for "Global Spatial Distribution of Hack's Law Exponent on Mars Consistent with Early Arid Climate "
<p>This is the watershed boundary data for Mars (along with Hack's Law exponent) as described in Luo et al. "Global Spatial Distribution of Hack’s Law Exponent on Mars Consistent with Early Arid Climate" accepted for publication in Geophysical Research Letters on 3/10/2023.</p> <p>The attributes are as follows:</p> <p>Id, gridcode = ID of basin</p> <p>Shape_Length = perimeter of the basin</p> <p>Shape_area = area of the basin</p> <p>geoArea = geodesic area of the basin</p> <p>geoLength = geodesic perimeter of the basin</p> <p>areaR = geoArea / Shape_area</p> <p>LengthR = geoLength / Shape_Length</p> <p>n_exponent = Hack’s Law Exponent (h in L = k A^h)</p> <p>n_coefficient = Hack’s Law exponent (k in L = k A^h)</p> <p>n_r2 = r^2 of the nonlinear fit (optimize.curve_fit function in SciPy)</p>
Data and code from: You shall not pass, the Pacific oxygen minimum zone creates a boundary to shortfin mako shark distribution in the Eastern North Pacific Ocean
Open the record for dataset details and reuse information.
Effects of surface fluxes on the moist potential vorticity distribution in the tropical cyclone boundary layer
<p>Hourly model outputs (t=150-240 hrs) from five axisymmetric simulations of tropical cyclones are provided as follows :</p> <ol> <li>cm1_test40_ver2 (referred to as CONTROL in the manuscript)</li> <li>cm1_test41_ver2 (referred to as H2.0 in the manuscript)</li> <li>cm1_test42_ver2 (referred to as H0.5 in the manuscript)</li> <li>cm1_test43_ver2 (referred to as M2.0 in the manuscript)</li> <li>cm1_test44_ver2 (referred to as M0.5 in the manuscript)</li> </ol> <p>Model outputs from the 3D simulation are interpolated to cylindrical coordinates and saved individually for each variable in binary format, and these are provided for t=150-240 hrs as follows:</p> <ol> <li>cm1_test13_ver2 (referred to as 3D-TC in the manuscript)</li> </ol> <p>Jupyter notebooks are also provided to read and analyze processed outputs from the datasets described above and plot the figures included in the manuscript. The datasets used in "<em>figure_05.ipynb</em>", "<em>figure_06.ipynb</em>", and "<em>figure_07.ipynb</em>" are large and can be made available by the authors upon request.</p>
Data from: Modelling species distribution at the boundaries of the Earth's climate
Open the record for dataset details and reuse information.
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.
Data from: Shaping species with ephemeral boundaries: the distribution and genetic structure of the desert tortoise (Gopherus morafkai) in the Sonoran Desert region
Aim: We examine the role biogeographical features played in the evolution of Morafka's desert tortoise (Gopherus morafkai) and test the hypothesis that G. morafkai maintains genetically distinct lineages associated with different Sonoran Desert biomes. Increased knowledge of the past and present distribution of the Sonoran Desert region's biota provides insight into the forces that drive and maintain its biodiversity. Location: Sonoran Desert biogeographical region; Sonora and Sinaloa, Mexico and Arizona, USA. Methods: We examined wild tortoises from Mexico (n = 155) and Arizona (n = 78), spanning their known distribution. We used mtDNA sequences to reconstruct matrilineal relationships and 25 microsatellite (STR) loci for Bayesian analyses of gene flow. We performed clinal analyses on both mtDNA and STR loci to determine the position and amount of introgression where lineages co-occur. We used GIS to assess the association of genetic structuring with ecological features. We used these data in a hypothesis-driven approach to assess different models of how genetic diversity is maintained and distributed in G. morafkai. Results: Gopherus morafkai was found to comprise genetically and geographically distinct 'Sonoran' and 'Sinaloan' lineages. Both lineages occurred in a relatively narrow zone of overlap in Sinaloan thornscrub, where it transitions into Sonoran desertscrub. Limited introgression occurred at the contact zone. The best-fit model suggests that these lineages diverged in parapatry where the distribution of genotypes is environment-dependent and introgression is inhibited by exogenous selection. Main conclusions: The historically shifting ecotone between tropical deciduous forest and Sonoran desertscrub appears to be a boundary that fostered divergence between parapatric lineages of tortoises. The sharp genetic cline between the two lineages suggests that periods of isolation in temporary refugia due to Pleistocene climatic cycling influenced divergence. Despite incomplete reproductive isolation, the Sonoran and Sinaloan lineages of G. morafkai are on separate evolutionary trajectories.
Figure 15 in Species boundaries, geographic distribution and evolutionary history of the Western Palaearctic freshwater mussels Unio (Bivalvia: Unionidae)
Figure 15. Coalescence-based species tree generated in BEAST. The x-axis scale is in millions of years. Bars indicate 95% high probability density intervals. Asterisks (*) in the tree indicate posterior probabilities pp> 0.9.
Figure 9 in Species boundaries, geographic distribution and evolutionary history of the Western Palaearctic freshwater mussels Unio (Bivalvia: Unionidae)
Figure 9. Differing shell shapes of Unio elongatulus. A, Po di Tolle River, Italy. B, Lake Candia, Italy. C, Venice, Italy. D, Lake Cestella, Italy. E, Lake Bačinska, Croatia. F, G, Mirna River, Croatia. H, Zrmanja River, Croatia. I, Lake Scutari, Albania. Scale bar 2 cm.
Figure 6 in Species boundaries, geographic distribution and evolutionary history of the Western Palaearctic freshwater mussels Unio (Bivalvia: Unionidae)
Figure 6. Differing shell shapes of Unio tigridis. A, Lake Kinneret, Israel. B, Tersakan River, Southwest Turkey.
Figure 7 in Species boundaries, geographic distribution and evolutionary history of the Western Palaearctic freshwater mussels Unio (Bivalvia: Unionidae)
Figure 7. Differing shell shapes of Unio mancus. A, Stabiacciu River, Corsica. B, Liscia River, Sardinia. C, Cedrino River, Corsica. D, River at Banyoles Lake, Spain. E, F, Araxisi River, Sardinia. Scale bar 2 cm.
Figure 4 in Species boundaries, geographic distribution and evolutionary history of the Western Palaearctic freshwater mussels Unio (Bivalvia: Unionidae)
Figure 4. Differing shell shapes of Unio foucauldianus. A, Loukos River. B, Oum Er Rbia River. C, Molouya River. D, Mda River. E, Martil River. F, Beth River (Sebou). G, Loukos River. Scale bar 2 cm.
Figure 3 in Species boundaries, geographic distribution and evolutionary history of the Western Palaearctic freshwater mussels Unio (Bivalvia: Unionidae)
Figure 3. Differing shell shapes of Unio tumidus. A, Franconian Saale, a tributary of the Main River (Rhine), Germany. B, Fulda River (Weser), Germany. C, Okna River (Danube), Slovakia. D, Danube River, Slovakia. E, Ferma Lake (Rhine), Germany. F, Thames River, UK. G, Fulda River (Weser), Germany. H, Rhine River, Germany. I, Horloff River (Rhine), Germany. Scale bar 2 cm.
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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.