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12,309 results for “America”
Baseline map of 137Cs inventories in reference soil sites at the continental scales of South America
<p>This dataset contains the baseline map of <sup>137</sup>Cs inventories in reference soil sites (Bq m<sup>-2</sup>, decay-corrected to 2020) estimated by Partial Least Square Regression (PLSR) with a spatial resolution of 2 km at the continental scale of South America, as well as the prediction uncertainties of the baseline map (coefficient of variation, %).<br> Details information regarding this dataset can be found in the original publication:<br> Mapping the spatial distribution of global <sup>137</sup>Cs fallout in soils of South America as a baseline for Earth Science studies, Earth-Science Reviews, Volume 214, 2021, 103542, ISSN 0012-8252, https://doi.org/10.1016/j.earscirev.2021.103542.</p>
Dataset for "Authorship concentration in health sciences journals from Latin America and the Caribbean"
<p>Authorship concentration indexes and other data for journals in the LILACS (Latin American and the Caribbean Literature on Health Sciences) bibliographic database, from 2015 to 2019 (FONTENELLE, 2022). These data are read and created by <a href="https://doi.org/10.5281/zenodo.6127497">analytic code in Zenodo</a>.</p> <ul> <li><em>authorship_concentration.csv</em> - dataset derived in Fontenelle (2022) from raw data exported from LILACS. This is the main file, and it's CC-BY because other researchers might have curated the raw data differently and thus derived different data. CSV file encoded with ASCII.</li> <li><em>authorship_concentration_datadictionary.csv</em> - data dictionary for the previous file. This file is actually CC0. CSV file encoded with ASCII.</li> <li><em>journals.csv</em> - dataset about the journals indexed in LILACS between 2015 and 2019. As a result of simply converting and filtering the original TITLE database, this is actually CC0 by the Pan American Health Organization (PAHO). CSV file encoded with UTF-8.</li> <li><em>journal_subjects.csv</em> - DeCS descriptors for the journals identified by the ISSN. CC0 by the Pan American Health Organization (PAHO), as above. CS file encoded with ASCII.</li> </ul>
European Investment Bank Projects in ACP, OCT, Africa, Asia, and Latin America (1957-2024)
<p>This dataset offers a comprehensive analysis of European Investment Bank (EIB) projects in Africa, the Caribbean, and the Pacific (ACP) regions, Overseas Countries and Territories (OCT), Asia, and Latin America, spanning from 1975 to 2023. The dataset includes information on 2,558 projects; each entry in the dataset includes key project details such as the project’s sector, date of signature, and financial commitments. All numbers are in 2015 euros.</p>
Supporting data for "Forest carbon uptake as influenced by snowpack and length of photosynthesis season in seasonally snow-covered forests of North America"
<p>This is a supporting dataset for the paper :</p> <div> <div>Yang, J. C., Bowling, D. R., Smith, K. R., Kunik, L., Raczka, B., Anderegg, W. R. L., Bahn, M., Blanken, P. D., Richardson, A. D., Burns, S. P., Bohrer, G., Desai, A. R., Arain, M. A., Staebler, R. M., Ouimette, A. P., Munger, J. W., and Litvak, M. E.: Forest carbon uptake as influenced by snowpack and length of photosynthesis season in seasonally snow-covered forests of North America, Agricultural and Forest Meteorology, 353, 110054, <a href="https://doi.org/10.1016/j.agrformet.2024.110054">https://doi.org/10.1016/j.agrformet.2024.110054</a>, 2024.</div> </div> <p>Descriptions and units for each column can be found in a dedicated page within the data file. Methods are decribed in the paper.</p>
A Quantitative Tomotectonic Plate Reconstruction of Western North America and the Eastern Pacific Basin
<p>The two plate model archives in this directory are linked to the paper (<em>Geochemistry, Geophysics, Geosystems</em>, in press):</p> <p>A Quantitative Tomotectonic Plate Reconstruction of Western North America and the Eastern Pacific Basin by Edward J. Clennett1, Karin Sigloch1, Mitchell G. Mihalynuk2, Maria Seton3, Martha A. Henderson2, Kasra Hosseini1,4, Afsaneh Mohammadzaheri1, Stephen T. Johnston5, and R. Dietmar Muller3</p> <p>1. Department of Earth Sciences, University of Oxford, South Parks Road, Oxford OX1 3AN, UK</p> <p>2. British Columbia Geological Survey, P.O. Box Stn Prov Govt, Victoria, BC, V8W 9N3, Canada</p> <p>3. EarthByte Group, School of Geosciences, The University of Sydney, NSW 2006, Australia</p> <p>4. The Alan Turing Institute, British Library, 96 Euston Road, London NW1 2DB, UK</p> <p>5. Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, AB T6G 2E3, Canada</p> <p>The zipped archive contains two plate models: <strong>Clennett_etal_2020_M2019.zip</strong> and <strong>Clennett_etal_2020_S2013.zip</strong>. The former is our model in the Müller et al. (2019) reference frame, and the latter is our model implemented into the Shephard et al. (2013) plate reconstruction. Both of these folders contain the same types of files: coastlines, plate boundaries, plate topologies, a rotation file and terrane shapefiles.</p> <p>To view the models, open GPlates (downloadable at: <a href="https://www.gplates.org">www.gplates.org</a>), click 'File' > 'Open Project', navigate to the folder containing the desired model, and then click on the file <strong>Clennett_etal_2020_G3_XXXX.gproj</strong>. This will simultaneously open all the files that comprise the model. A layers panel will appear, with the option to turn on/off certain files. The view can be changed by clicking on the globe, and the model can be run by clicking the play button in the animation bar, starting from 170Ma. Features can be inspected by clicking the 'choose feature' tab, selecting a feature, and clicking 'query feature'.</p> <p>The files that comprise the model are described below:</p> <p>1. <strong>Clennett_etal_2020_Coastlines.gpml</strong>: Coastlines used in the reconstruction. The coastlines of western North America and Mexico were edited from the global model to account for later terrane accretions. </p> <p>2. <strong>Clennett_etal_2020_NAm_bounds.gpml</strong>: File containing the new plate boundaries digitised in this study.</p> <p>3. <strong>Clennett_etal_2020_Plates.gpml</strong>: File containing the edited plate boundaries of the global model, as well as our new continuously-closing plate topologies.</p> <p>4. <strong>Clennett_etal_2020_Rotations.rot</strong>: This is the rotation file that contains the relative motions between plates, terranes and plate boundaries for western North America and the eastern Pacific basin. The first column specifies the plate ID, the second column the timestep, the third, fourth and fifth columns are the latitude, longitude and angle of the stage rotations, and the sixth column is the plate that the feature moves relative to. Most lines are accompanied with a comment describing the rotation.</p> <p>5. <strong>Clennett_etal_2020_Terranes.gpml</strong>: This file contains all the terranes shown in the model. We further divided these into superterranes, so that each can be coloured accordingly for better visualisation purposes: a. Angayucham.gpml b. Farallon.gpml c. Guerrero.gpml d. Insular.gpml e. Intermontane.gpml f. Kula.gpml g. North_America.gpml h. Western_Jurassic.gpml</p> <p>6. <strong>Movie</strong> <strong>S1</strong>. Movie showing plate evolution at 1 million-year intervals, embedded within the Muller et al. (2019) global model. Blue boundaries are subduction zones, red boundaries are mid-ocean ridges, green boundaries are transform faults, and pink boundaries are other unspecified boundaries. Plates are not labelled but can be identified from figures 5-10.</p> <p>7. <strong>Movie S2</strong>. Movie showing plate evolution at 1 million-year intervals, embedded within the Shephard et al. (2013) global model. Blue boundaries are subduction zones, red boundaries are mid-ocean ridges, green boundaries are transform faults, and pink boundaries are other unspecified boundaries. Plates are not labelled but can be identified from figures 5-10.</p> <p> </p> <p>The agegrids and spreading rate grids associated with this model can be accessed at: <a href="https://repo.gplates.org/webdav/PlateModel_Age_SR_Grids/Clennett_etal_2020_G3/" target="_blank" rel="noopener">https://repo.gplates.org/webdav/PlateModel_Age_SR_Grids/Clennett_etal_2020_G3/</a></p>
Supporting Online Data for 'Timber trade in the United States of America 1870 to 2017. A socio-metabolic analysis'
<p>This data file (.xlsx) contains all data used to create tables and figures of the study "Timber trade in the United States of America 1870 to 2017. A socio-metabolic analysis". Main article is available under: https://doi.org/10.1080/01615440.2024.2316039</p>
Final model for "Automated Large-Scale Full Seismic Waveform Inversion for North America and the North Atlantic" by Krischer et al. (2018)
<p>The HDF5 file contains the final model of the paper "Automated Large-Scale Full Seismic Waveform Inversion for North America and the North Atlantic" by Krischer et al. (2018), soon to be published in the Journal of Geophysical Research - Solid Earth.</p> <p>The "coordinates_0", "coordinates_1", and "coordinates_2" data sets are the coordinates along each dimension, here colatitude in degree, longitude in degree, and radius in meter, respectively. The regularly sampled data is available in five 3D-arrays in the "data" group: "vp", "vsv", "vsh", "rho", and "Q". Velocities are defined at 1 Hertz and are given in km/s, the density in kg/m^3. Q is Q_mu.</p> <p>The coordinates have to be rotated to yield true spherical Earth coordinates. They have to be rotated around on axis vector of 0.766044443118978/0.6427876096865393/0.0 in cartesian x/y/z coordinates by -30.0 degrees. Conversion of spherical to cartesian coordinates happens with the standard convention:</p> <p>x = r sin(theta) cos(phi)<br> y = r sin(theta) sin(phi)<br> z = r cos(theta)</p>
Supplementary Material for "Formal methods in dependable systems engineering: a survey of professionals from Europe and North America"
<p>This report contains supplemental material for <a href="https://link.springer.com/article/10.1007%2Fs10664-020-09836-5">this paper</a>, including a detailed analysis of responses to certain questions, further visualizations of the collected data, details on our analysis of related work, and a copy of the whole questionnaire. This material was shared for the period of peer review and has been significantly updated, extended, and included in <a href="https://link.springer.com/article/10.1007%2Fs10664-020-09836-5">this journal publication</a>.</p>
Regional model results (combined) for the six transition potentials (one for Africa, Australia, Asia, Europe, North America, and South America)
<p>Results for the six regional models showing areas of high potential to transition from tree cover to tree cover loss to areas of low potential to transition.</p>
Teleseismic P-wave Tomography Beneath the Pantanal, Paraná and Chaco-Paraná Basins, SE South America: Delimiting Lithospheric Blocks of the SW Gondwana Assemblage.
<p>Tomographic data set for different depths (CSV-files with Longitude, Latitude anda Velocity Perturbation in percentage), Interpreted limit of the São Francisco Paleocontinent and the Abstract for the paper "Teleseismic P-wave Tomography Beneath the Pantanal, Paraná and Chaco-Paraná Basins, SE South America: Delimiting Lithospheric Blocks of the SW Gondwana Assemblage." submitted to Journal of Geophysical Research: Solid Earth.</p>
National Checklists 2017: South America Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>List of species from South America inferred from individual country lists that were derived from effechecka and modified geonames polygons
National Checklists 2017: North America Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>List of species from North America inferred from individual country lists that were derived from effechecka and modified geonames polygons
National Checklists 2019: South America Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details.<p></p>List of species from South America inferred from individual country lists that were derived from effechecka and modified geonames polygons
National Checklists 2019: North America Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details.<p></p>List of species from North America inferred from individual country lists that were derived from effechecka and modified geonames polygons
National Checklists 2019: North America Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details.<p></p>List of species from North America inferred from individual country lists that were derived from effechecka and modified geonames polygons
National Checklists 2019: South America Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details.<p></p>List of species from South America inferred from individual country lists that were derived from effechecka and modified geonames polygons
DATASETS and OUTCOMES - Assessment of intrinsic aquifer vulnerability at continental scale through a critical application of the DRASTIC method: the case of South America
<p>A robust and comprehensive assessment of intrinsic aquifer vulnerability at continental scale map may represent an essential initial step towards a more sustainable land-use and water management.</p> <p>This repository contains the outcomes of an intrinsic aquifer vulnerability assessment of South America, performed by the DRASTIC method. The assets included in this repository are mainly raster maps (.tif, .geotif), created and georeferenced in QGIS (v3.16). Coordinate reference system (CRS) of the dataset is WGS84.</p> <p>Technical specifications of all graphical outcomes are stored in a dedicated file (README.txt).</p>
Potential tree species distributions from the Last Glacial Maximum in North America
<p>Modern tree distributions modeled under current climate and predicted to past climate.</p> <p>Values of '2' represent presence.</p> <p>The column mark is current presence, while _20000 is 20 ka, _14000 is 14 ka, _13000 is 13 ka, etc.</p> <p>For quick download, the .dbf for each species can be joined to the shapefile (us_can_ecosub). Alternatively, download and use the zipped folder of shapefiles (glac_shapes)..</p>
Population dynamics shifts by Climate Change: High resolution future mid-century trends for South America.
<p>Köppen - Geiger scripts and resulting datasets for the publication entitled "Population dynamics shifts by Climate Change: High resolution future mid-century trends for South America." This scripts can be adapted to any geographic scale and region. Works with climate change scenarios.</p> <p>Original publication: <a href="https://doi.org/10.1016/j.gloplacha.2023.104155">https://doi.org/10.1016/j.gloplacha.2023.104155</a></p> <p>Dataset description</p> <p><strong>Scripts.rar</strong>: R Scripts used in this publication, as well they are reproducible</p> <p><strong>Readme_Köppen.txt</strong>: README file that explain the requisites and data formatting to run the scripts</p> <p><strong>Output datasets.zip</strong>: Output GIS datasets of this publication. Coordinate system GCS WGS 1984</p> <p> </p>
Phytoplankton list of taxa and cell biovolume from a subtropical coastal lagoon, South America
<p>We share information about the phytoplankton community from a subtropical coastal lagoon, Laguna de Rocha, a Biosphere Reserve, located in Uruguay, South America (34°37'60" S, 54°18'0" W). The lagoon is ~ 72 km2 with a mean depth of 0.5 m, and is characterized by a strong South-North salinity gradient that reflects its intermittent connection to the Atlantic Ocean (in the South). The lagoon has been subject to eutrophication in the last several decades. The dataset presented here belongs to the publication of Bonilla et al., 2005 (doi.org/10.1007/BF02696017). We present the complete list of phytoplankton taxa identified in a survey (1996-2000) for two sites, South and North, locations described in figure 1 (Bonilla et al., 2005). We also presented the cellular linear measurements and the cell biovolume of the most representative taxa. We believe these data are useful for the scientific community interested in phytoplankton dynamics, diversity and calculation of biomass (biovolume).</p>
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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.