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19,324 results for “westerns”
A collection of fully-annotated soundscape recordings from the Western United States
<p>This collection contains 33 hour-long soundscape recordings, which have been annotated with 20,147 bounding box labels for 56 different bird species from the Western United States. The data were recorded in 2018 in the Sierra Nevada, California, USA. This collection has partially been featured as test data in the 2021 BirdCLEF competition and can primarily be used for training and evaluation of machine learning algorithms.</p> <p><strong>Data collection</strong></p> <p>Measuring the effects of forest management activities in the Sierra Nevada, California, USA can reveal a potential correlation with avian population density and diversity. For this dataset, passive acoustic surveys were conducted in the Lassen and Plumas National Forests in May-August 2018. Survey grid cells (4 km<sup>2</sup>) were randomly selected from a 6,000-km<sup>2</sup> area, and SWIFT recording units were deployed at locations conducive to sound propagation (e.g., ridges rather than gullies) within those cells. The sensitivity of the used microphones was -44 (+/-3) dB re 1 V/Pa. The microphone's frequency response was not measured, but is assumed to be flat (+/- 2 dB) in the frequency range 100 Hz to 7.5 kHz. The analog signal was amplified by 38 dB and digitized (16-bit resolution) using an analog-to-digital converter (ADC) with a clipping level of -/+ 0.9 V. Recording units recorded continuously 17:00 - 23:59, 0:00 - 10:00, one-hour files were stored as uncompressed WAVE sampled at 32 kHz and later converted to FLAC. Parts of this dataset have previously been used in the 2021 BirdCLEF competition.</p> <p><strong>Sampling and annotation protocol</strong></p> <p>We subsampled data for this collection by selecting locations that spanned the full elevational and latitudinal gradients of our study area (~840 – 1700 m asl and 39.41 – 40.71°N), and thus represent a broad range of plant communities. A single annotator boxed every bird call he could recognize, ignoring those that are too faint or unidentifiable. Raven Pro software was used to annotate the data. Provided labels contain full bird calls that are boxed in time and frequency. The annotator was allowed to combine multiple consecutive calls of one species into one bounding box label if pauses between calls were shorter than five seconds. We use eBird species codes as labels, following the 2021 eBird taxonomy (Clements list).</p> <p><strong>Files in this collection</strong></p> <p>Audio recordings can be accessed by downloading and extracting the “soundscape_data.zip” file. Soundscape recording filenames contain a sequential file ID, recording date and timestamp in PDT. As an example, the file “SNE_001_20180509_050002.flac” has sequential ID 001 and was recorded on May 9th 2018 at 05:00:02 PDT. Ground truth annotations are listed in “annotations.csv” where each line specifies the corresponding filename, start and end time in seconds, low and high frequency in Hertz and an eBird species code. These species codes can be assigned to scientific and common name of a species with the “species.csv” file. The approximate recording location with longitude and latitude can be found in the “recording_location.txt” file.</p> <p><strong>Acknowledgements </strong></p> <p>The collection and annotation of this dataset was funded by the U.S. Forest Service Region 5 and the California Department of Fish and Wildlife.</p>
Data from: Seasonal variation in wildlife roadkills in plantations and tropical rainforest in the Anamalai Hills, Western Ghats, India
<p>This dataset contains animal roadkill data (2011-13) from the Valparai Plateau and Anamalai Tiger Reserve, Western Ghats, India. Occurrence records were gathered in the field by researchers of the <a href="https://www.ncf-india.org">Nature Conservation Foundation, India</a>. The dataset corresponds to the following publication:</p> <p>Jeganathan, P., Mudappa, D., Kumar, M. A., and Raman, T. R. S. 2018. <a href="https://doi.org/10.18520/cs/v114/i03/619-626">Seasonal variation in wildlife roadkills in plantations and tropical rainforest in the Anamalai Hills, Western Ghats, India</a>. <em>Current Science</em> 114(3): 619-626. DOI: 10.18520/cs/v114/i03/619-626</p> <p>CONTACT #1<br> 1. Name: P. Jeganathan<br> 2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br> 3. Work Phone: +91 821 2515601<br> 4. Email address: jegan@ncf-india.org<br> 5. ORCID: https://orcid.org/0000-0002-0238-0655</p> <p>CONTACT #2<br> 1. Name: Divya Mudappa<br> 2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br> 3. Work Phone: +91 821 2515601<br> 4. Email address: divya@ncf-india.org<br> 5. ORCID: https://orcid.org/0000-0001-9708-4826</p> <p>CONTACT #3<br> 1. Name: M. Ananda Kumar<br> 2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br> 3. Work Phone: +91 821 2515601<br> 4. Email address: anand@ncf-india.org<br> 5. ORCID: https://orcid.org/0000-0001-7094-1314</p> <p>CONTACT #4<br> 1. Name: T. R. Shankar Raman<br> 2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br> 3. Work Phone: +91 821 2515601<br> 4. Email address: trsr@ncf-india.org<br> 5. ORCID: https://orcid.org/0000-0002-1347-3953</p> <p><strong>Keywords: </strong>tropical rainforest, plantations, Anamalai Hills, animal roadkill, linear infrastructure intrusions, highways, road ecology, animal-vehicle collisions </p> <p><strong>Geographic Coverage:</strong><br> 1. Location/Study Area: Valparai Plateau, Tamil Nadu, India; Anamalai Tiger Reserve, Tamil Nadu, India<br> 2. GPS coordinates: Valparai Plateau (10°15'- 10°22'N, 76°52' - 76°59'E); Anamalai Tiger Reserve (10°12' - 10°35'N, 76°49' - 77°24'E)</p> <p><strong>Temporal Coverage:</strong><br> 1. Begins: 2011-06-01 (Year, Month, Day)<br> 2. Ends: 2013-05-31 (Year, Month, Day)</p> <p><strong>Methods:</strong></p> <p>Methods involved repeated surveys along the road routes searching for roadkills and habitat sampling as described in <a href="https://doi.org/10.18520/cs/v114/i03/619-626">Jeganathan et al. (2018),<em> Current Science</em> 114(3): 619-626</a>, DOI: 10.18520/cs/v114/i03/619-626</p> <p><strong>Files included:</strong></p> <p>Besides this 00_README.txt file, the dataset includes the following six files as explained below:<br> 1) 01_habitat_length.csv -- details of road routes surveyed as line transects<br> 2) 02_sampling_events.csv -- details of individual line transect sample surveys along road routes<br> 3) 03_roadkill_data_final.csv -- roadkill occurrence data from sample surveys along road routes<br> 4) 04_canopy_and_habitat.csv -- canopy and habitat readings along road routes (transects) surveyed<br> 5) 05_roadkill_transects_all.kml -- KML file containing geographic tracks of 11 road routes surveyed as roadkill transects<br> 6) 06_road_transects_map.jpg -- Map of surveyed routes corresponding to Figure 1 in Jeganathan et al. (2018)</p> <p><strong>01_habitat_length.csv</strong><br> transect: name of road route surveyed as a line transect<br> route_description: description of road route<br> tlength_km: transect length along road in kilometres (km)<br> tlength_m: transect length along road in metres (m)<br> forest: extent of the road in metres (m) with forest on both sides<br> forest_tea: extent of the road in metres (m) with forest on one side, tea on the other<br> coffee_forest: extent of the road in metres (m) with forest on one side, coffee plantation on the other<br> tea: extent of the road in metres (m) with tea plantation on both sides<br> coffee: extent of the road in metres (m) with coffee plantation on both sides<br> eucalyptus: extent of the road in metres (m) with eucalyptus plantation on both sides<br> eucalyptus_tea: extent of the road in metres (m) with eucalyptus on one side, tea plantation on the other</p> <p><strong>02_sampling_events.csv</strong><br> season: monsoon (June to December 2011) or summer (March to June 2012 prior to the onset of 2012 monsoon)<br> transect: name of road route surveyed as a line transect<br> transect: name of road route surveyed as a line transect<br> tcode: unique code for each individual survey of a road route (transect) coevered on a specific date<br> eventDate: date of road survey<br> tlength: transect length along road in kilometres (km)</p> <p><strong>03_roadkilldata_final.csv</strong><br> sno: serial number of observation<br> season: monsoon (June to December 2011) or summer (March to June 2012 prior to the onset of 2012 monsoon)<br> transect: name of road route surveyed as a line transect<br> tcode: unique code for each individual survey of a road route (transect) coevered on a specific date<br> eventDate: date of road survey<br> fielddate: date of road survey as initially noted (for two surveys completed over two successive days, the initial date was recorded as eventDate for 2011-06-17 = 2011-06-16 and eventDate for 2011-07-06 = 2011-07-05<br> tlength: transect length along road in kilometres (km)<br> verbatimIdentification: original identification of roadkilled taxon<br> vernacularName: common name of taxon<br> scientificName: scientific name of taxon for corresponding taxonomic level of identification<br> taxonRank: rank of taxon indicating for corresponding taxonomic level of identification<br> taxonRemarks: category of taxon as noted for analysis<br> verbatimCoordinateSystem: coordinate system used for initial data collection<br> verbatimSRS: SRS of the location data collected (EPSG:32643/WGS84)<br> georeferenceRemarks: note indicating locations were converted from UTM (zone 43 N) to latitude longitude using QGIS software<br> verbatimLongitude: UTM longitude (Easting) as originally recorded<br> verbatimLatitude: UTM latitude (Northing) as originally recorded<br> decimalLongitude: longitude in decimal degree East<br> decimalLatitude: latitude in decimal degrees North<br> habitat: habitat on either side of the road (forest - forest on both sides; forest_tea - forest on one side, tea on the other; human - human settlements; coffee - coffee plantation on both sides; coffee_forest - coffee on one side, forest on the other; eucalyptus - eucalyptus plantation on both sides; eucalyptus_tea - eucalyptus on one side, tea on the other; tea - tea plantation)<br> individualCount: number of individuals recorded as roadkill (0 if no roadkills in that survey)<br> occurrenceStatus: indicated as 'present' for roadkills, or 'absent' if no roadkills recorded<br> occurrenceRemarks: notes and remarks if any</p> <p><strong>04_canopy_and_habitat.csv</strong><br> transect: name of road route surveyed as a line transect<br> verbatimroute: route name as originally noted<br> sno: serial number<br> canopycover: 0 if tree canopy absent, 1 if tree canopy present above point of observation<br> canopyoverlap: horizontal overlap of tree canopy above point of observation ranked as 0 - no canopy above; 1 canopy present but barely touching or overrlapping; 2 - canopy overlapping with sky still visible through leaves; 3 - canopy overlaps overhead densely with sky scarcely visible<br> verticaloverlap: vertical gap between canopy or branches of trees above point of observation ranked as 0 - very wide; 1 - barely touching, 2 - significant vertical overlap, 3 - substantial and dense vertical overlap<br> habcode: two letter alphabetical code with each letter indicating habitat on one side of the road at the point of observation with f - forest, t - tea, c - coffee, e - eucalyptus, v - village or human habitation, m - dam or reservoir<br> habno: numeric category for habitat on either side coded as 1 for monocultures (ee, tt); 2 for mixed forest and plantation (ef, ft, etc.); 3 for forest (ff), and 4 for coffee plantation (cc)<br> longitude: longitude in decimal degrees east<br> latitude: latitude in decimal degrees north</p> <p><strong>05_roadkill_transects_all.kml</strong><br> This KML file contains all 11 road routes surveyed as roadkill transects.</p> <p><strong>06_road_transects_map.jpg</strong><br> This map illustrating the surveyed road routes corresponds to Figure 1 in <a href="https://doi.org/10.18520/cs/v114/i03/619-626">Jeganathan et al. (2018), <em>Current Science</em> 114(3): 619-626</a>, DOI: 10.18520/cs/v114/i03/619-626</p>
Dataset for the ``Fast atmospheric response to a cold oceanic mesoscale patch in the north-western tropical Atlantic" publication
<p>The dataset presented here contains the files needed to produce the results presented in the publication "Fast atmospheric response to a SST mesoscale cold patch in the north-western subtropical Atlantic" submitted to the <em>Journal of Geophysical Research: Atmospheres</em>. The scripts that read and produce these files are publicly available at <a href="https://github.com/ClauClouds/SST-impact/">https://github.com/ClauClouds/SST-impact/</a> and can also be found in this repository (code_python.zip). This Zenodo data repository includes the following datasets:</p> <ul> <li> <p>Radiosonde data from 2-3 February 2020 (Stephan et al., 2021)</p> </li> <li> <p>Doppler lidar, and ARTHUS Raman lidar variables data from 2-3 February 2020,</p> </li> <li> <p>GOES-East (Geostationary Operational Environmental Satellite - East) Binary Cloud Mask (BCM) and Cloud Optical Depth (COD) products, provided at 2 km grid spacing every 10 minutes. They come from the GOES-R Advanced Baseline Imager (ABI) (Schmit et al., 2017), available at <a href="https://www.ncei.noaa.gov/products/satellite/goes-r-series.Data">https://www.ncei.noaa.gov/products/satellite/goes-r-series.Data</a> and they are provided for the 2-3 February 2020.</p> </li> <li> <p>Multi-scale Ultra-high Resolution (MUR) product (JPL MUR MEaSUREs Project, 2015,183 (Chin et al., 2017)) averaged between the 2nd and 3rdfor the 2nd of February 2020. The MUR product is an analysis product provided on a daily basis that combines different satellite (infrared at high and medium resolutions and microwave products) and in-situ data (Chin et al., 2017).</p> </li> <li> <p>W-band radar data post-processed for the purposes of the publication. The original W-band radar data used are publicly accessible at <a href="https://howto.eurec4a.eu/merian_cloudradar.html">https://howto.eurec4a.eu/merian_cloudradar.html</a> and can be downloaded via <a href="https://eurec4a.aeris-data.fr/">AERIS data portal</a>. See more details and specific DOI below.</p> </li> </ul> <p>The present dataset is structured as follows:</p> <ul> <li> <p>diurnal_cycle_removed_vars: files containing the time series of the variables without noise and diurnal cycle (filenames with extended dates 20200202 and 20200203)</p> </li> <li> <p>diurnal_cycle: files containing the diurnal cycle of each variable used in the publication</p> </li> <li> <p>binned_sst_vars: files containing variables binned in terms of SST, used to derive the plots in the paper.</p> </li> <li> <p>satellite_data: a folder containing all satellite data used in the publication</p> </li> </ul> <p>Additional data used in the publication, that are processed via the scripts contained in the link mentioned above, are available online at the following urls:</p> <ul> <li> <p>cloud radar observations can be directly obtained from the public dataset identifiable via DOI: <a href="https://doi.org/10.25326/235">https://doi.org/10.25326/235</a> (Acquistapace et al., 2022)</p> </li> <li> <p>ASCAT wind field data and corresponding MUR SST data are available from the NASA JPL PODAAC platform (<a href="https://podaac.jpl.nasa.gov/">https://podaac.jpl.nasa.gov/</a>)</p> </li> <li> <p>hourly ERA5 (Hersbach et al., 2020) gridded fields (available at https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-pressure-levels?tab=form, last accessed March 2022) of the following variables: SST, water vapor mixing ratio, air temperature, and horizontal wind components. </p> </li> </ul> <p><br> </p> <p>References;</p> <p>Acquistapace et al., 2022, ESSD, <a href="https://doi.org/10.25326/235">https://doi.org/10.25326/235</a>.</p> <p>Schmit, T. et al., 2017, QJRMS, <a href="https://doi.org/10.1175/BAMS-D-15-00230.1">https://doi.org/10.1175/BAMS-D-15-00230.1</a></p> <p>Hersbach et al., 2020, QJRMS, <a href="https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/qj.3803">https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/qj.3803</a></p> <p>Stephan et al., 2021, ESSD, <a href="https://doi.org/10.5194/essd-13-491-2021">https://doi.org/10.5194/essd-13-491-2021</a></p> <p>Chin, T. M. et al., (2017), RS, <a href="https://doi.org/10.1016/j.rse.2017.07.029">https://doi.org/10.1016/j.rse.2017.07.029</a></p>
Bottom water acidification and warming on the western Eurasian Arctic shelves: Dynamical downscaling projections. Data archive.
<p>This archive includes one .mat file (MATLAB format) containing all the data and interpolated SINMOD model used for skill assessment and bias correction, and several NetCDF files containing the SINMOD SRES A1B projections (bias corrected where possible) for the bottom water in the pan-Arctic model domain for years 2001-2099 inclusive. Temporal resolution is biweekly and spatial resolution is 20km (see grid info in NetCDF files).</p>
Wood density for 26 plant species collected from Northern Western Ghats
<p>This dataset contains wood density estimates for species collected from Sindhudurg district of Maharashtra. The data was collected for baseline data generation for the Sahyadri Restoration Program as part of CEROS Lab at Nature Conservation Foundation. The fieldwork was carried out in Feb-Mar 2024.</p> <p>Wood cores were collected using Increment Borer (Haglof 12inch, 3 thread, 5.15mm)</p> <p>Usage notes:</p> <p>readme_wood_density.txt contains the information for each columns and the values calculated</p> <p>Wood Density Maharashtra.csv contains the dataset</p> <p><strong>ACKNOWLEDGEMENTS:</strong></p> <p>I would like to thank GCPL CSR (Godrej Consumers Products) for funding this data collection as part of the Sahyadri Restoration project and S.P.K College Sawantwadi for providing the necessary lab support. Special thanks to Dr. Deelip Bharmal (Principal S.P.K College) and Dr. G.S Margaj (Professor Zoology Dept) for help with the lab analysis.</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>
Farmers' fields network of oilseed rape intercropped with service plant in Western Switzerland.
<p>These data are associated with the publication of Bousselin et al. (2024) in which the experiment and the protocols are explained into details.</p> <p><span>Bousselin, X., Lorin, M., Valantin-Morison, M. </span><em>et al.</em><span> Determinants of oilseed rape-service plant intercropping performance variability across a farmers’ fields network in Western Switzerland. </span><em>Agron. Sustain. Dev.</em><span> </span><strong>44</strong><span>, 40 (2024). https://doi.org/10.1007/s13593-024-00972-6</span></p>
Data for Identifying Robust Decarbonization Pathways for the Western U.S. Electric Power System under Deep Climate Uncertainty
<p>Data from the paper "Identifying Robust Decarbonization Pathways for the Western U.S. Electric Power System under Deep Climate Uncertainty"</p>
Stress regimes in the Himalaya-Karakoram-Tibet, the western part of India-Eurasia collision: stress field implications based on focal mechanism solution data
<p>This dataset contains valuable information on earthquake events, including their location, magnitude, depth, and focal mechanism solutions. This README file provides detailed explanations of each header in the dataset, as well as information about the files included in the repository.<br><br><em>"Stress regimes in the Himalaya-Karakoram-Tibet, the western part of India-Eurasia collision: stress field implications based on focal mechanism solution data"</em> <strong>(Under Review)</strong><br> </p>
CLDF dataset derived from Bodt's "Lexical Cognates in Western Kho-Bwa" from 2019
<p>Cite the source of the dataset as:</p> <blockquote> <p>Bodt, Timotheus Adrianus and List, Johann-Mattis (2019): Testing the predictive strength of the comparative method: An ongoing experiment on unattested words in Western Kho-Bwa languages. Papers in Historical Phonology 4.1: 22-44.</p> </blockquote>
Ground Vertical and east Velocities for the Western Gulf of Corinth, Greece, combining InSAR and GPS
<p><strong>Data group</strong> :<br> Ground Vertical and East Velocities for the Western Gulf of Corinth combining InSAR and GPS, for the period 2002-2010</p> <p><strong>Data identifiers</strong> : </p> <ol> <li>Best constrained 951 vertical and east PS-SBAS velocities for pixels of 200m</li> <li>Best constrained 4391 vertical and east PS-SBAS velocities for pixels of 200m</li> </ol> <p><strong>Version</strong> : 1.0</p> <p><strong>Coordinate Reference System</strong>: Geographic WGS84, EPSG:4326</p> <p><strong>Citation</strong>: Elias & Briole, 2018, Ground deformations in the Corinth rift, Greece, investigated through the means of SAR multi-temporal interferometry<br> </p>
Atmospheric_river_land_hydrology_western_US_HUC8_datasets
<p>Dataset for the manuscript entitled "Impact of Atmospheric Rivers on Surface Hydrological Processes in Western U.S. Watersheds".</p> <p> </p> <p>It includes daily meteorological and surface hydrological data from western U.S. WRF simulation. Data is aggregated to 8-digit Hydrological Unit (HUC8) watersheds.</p> <p> </p> <p>To use this dataset, please cite the following two publications:</p> <p> </p> <p>Chen, X., Leung, L. R., Gao, Y., Liu, Y., Wigmosta, M., & Richmond, M. (2018). Predictability of extreme precipitation in western U.S. watersheds based on atmospheric river occurrence, intensity, and duration. <em>Geophysical Research Letters</em>, 45, 11,693–11,701. <a href="https://doi.org/10.1029/2018GL079831">https://doi.org/10.1029/2018GL079831</a></p> <p> </p> <p>Chen, X., Leung, L. R., Wigmosta, M., & Richmond, M. (2019). Impact of Atmospheric Rivers on Surface Hydrological Processes in Western U.S. Watersheds. <em>Journal of Geophysical Research: Atmospheres</em>, <a href="http://doi.org/10.1029/2019JD03468">https://doi.org/10.1029/2019JD03468</a></p>
Prediction Experiment for Western Kho-Bwa language data: dataset
<p><strong>Prediction Experiment on Western Kho-Bwa languages</strong></p> <p><em>Timotheus A. Bodt (SOAS, London) and Johann-Mattis List (Max Planck Institute, Jena)</em></p> <p>This database includes all the sound files and the transcriptions of the prediction experiment for Western Kho-Bwa. This experiment was registered as:</p> <p>Bodt, Timotheus A., Nathan W. Hill and Johann-Mattis List. 2018. <em>Prediction experiment for missing words in Kho-Bwa language data. </em>Open Science Framework Preregistrations October 5. <a href="https://osf.io/evcbp/">https://osf.io/evcbp/</a> </p> <p>The data and code can be found on:</p> <p>Timotheus A. Bodt, Nathan W. Hill, & Johann-Mattis List. (2018, October 8). Prediction experiment for missing words in Kho-Bwa language data (Version v1.0.1). Zenodo. <a href="http://doi.org/10.5281/zenodo.1451176">http://doi.org/10.5281/zenodo.1451176</a></p> <p>A paper explaining the experiment is under review:</p> <p>Bodt, Timotheus A. and Johann-Mattis List. 2019 (under review). Testing the predictive force of the comparative method: An ongoing experiment on unattested words in Western Kho-Bwa languages. <em>Papers in Historical Phonology</em> Volume 1: 1–21.</p> <p>The results of the experiment will be presented at the International Conference on Historical Linguistics 24: 01-Jul-2019 - 05-Jul-2019, Canberra, Australia.</p> <p>The uncut sound files, cut sound files, original field notes and preliminary transcriptions have been saved as:</p> <p>Bodt, Timotheus Adrianus. (2019). <em>'Retrodiction' experiment Western Kho-Bwa languages: data [Data set]</em>. Zenodo. <a href="http://doi.org/10.5281/zenodo.2529727">http://doi.org/10.5281/zenodo.2529727</a></p> <p><strong>How to use these files?</strong></p> <ul> <li>Download the zip folder soundfiles_prediction_experiment.zip</li> <li>Extract the files in a separate folder</li> <li>Search for the required sound file(s)</li> </ul> <p>Searching sound files can best be done using the English CONCEPTS from the predictions_results.csv file. For example, searching for BACK will give all the sound files that contain the English gloss ‘back’ (including ‘backwards’, ‘back’ as body part, turn ‘back’ etc.).</p> <p>Another option is the select all the sound files of a given linguistic variety / doculect by searching for the original sound file number.</p> <p>I would advise against using a certain attested form in the predictions_results.csv file and search for that (e.g. p a ŋ + b u ‘chest’), because the cut sound files have been saved without spaces and morpheme breaks and because the actual transcriptions of the sound files may have changed after analysis, but were not updated in the name of the cut sound files.</p> <p>If you cannot find a certain sound file, then it may simply not have been recorded or not cut from the main sound file. If you are really interested, please mail me at <a href="mailto:timintibet@hotmail.com">timintibet@hotmail.com</a> and I will attempt to find it or record it.</p>
The topographic signature of ecosystem climate sensitivities in the western U.S.
<p>It has been suggested that hillslope topography can promote the persistence of hydrologic refugia, sites where ecosystem net primary productivity (NPP) is relatively insensitive to climate variation. However, the mechanisms that promote the persistence of these locations and their spatial distributions are poorly resolved. We quantified the response of ecosystem NPP to variability in the annual climatic water balance for 30 years across the western U.S. The slope of this pixel-specific linear regression represents ecosystem-climate sensitivity and provides a means to identify ecosystems that are buffered from droughts. Environmental conditions produced by hillslope convergence reduced ecosystem sensitivity to climate fluctuations across the entirety of the western U.S. We observed the greatest topographic effect in semi-arid climates, while vulnerability to drought was maximized in flat, arid landscapes. In aggregate, spatial patterns of ecosystem sensitivity can be implemented for regional planning to maximize conservation in landscapes that are more resistant to perturbations.</p>
Morphological traits of selected rock outcrop amphibians in the lateritic plateaus of the northern Western Ghats, India
<p>This project contains morphological trait data compiled for a study investigating the responses of rock outcrop amphibians to land-use change in the lateritic plateaus of the northern Western Ghats, at the community-level and at species-level.</p> <div> <div> <p>Species Coverage: <em>Euphlyctis jaladhara, Hoplobatrachus tigerinus, Minervarya cepfi, Minervarya gomantaki, Minervarya sahyadris, Sphaerotheca dobsonii, Microhyla nilphamariensis, Hydrophylax bahuvistara, Polypedates maculatus.</em></p> <p>Data was compiled by V. Jithin from literature, and Saunak Pal from Natural History Collections at the Bombay Natural History Society (2023).</p> </div> </div>
CLDF dataset derived from Dhakal et al.'s "South-Western Tibetic" from 2024
<p>Cite the source of the dataset as:</p> <blockquote> <p>Dhakal, D. N., List, J.-M., Roberts, S. G.(2024) A Phylogenetic Study of South-Western Tibetic. Journal of Language Evolution. https://doi.org/10.1093/jole/lzae008</p> </blockquote>
Emissions for individual housing in the Western Balkans
<p>Emissions for individual housing in the Western Balkans<br>-----------------------------------------------------------------<br>Version: Open data version 1<br>Date: 2024-10-09<br>Spatial reference system: ETRS89 / ETRS-LAEA (EPSG:3035)<br>Grid resolution: 500x500 m<br>DOI: 10.5281/zenodo.13906810</p> <p>Files<br>-------------------<br>emission_sector-C2_wb6_500m_2019_NOx.tif Gridded emissions for NOx<br>emission_sector-C2_wb6_500m_2019_PM10.tif Gridded emissions for PM10<br>emission_sector-C2_wb6_500m_2019_PM25.tif Gridded emissions for PM2.5<br>emission_sector-C2_wb6_500m_2019_SOx.tif Gridded emissions for SOx<br>readme.txt This readme-file</p> <p>Sector<br>-------------------<br>SNAP: 020200<br>GNFR: C2 (residential stationary combustion)<br>NFR: 1.A.4.b.i (Residential plants)</p> <p>Substances<br>-------------------<br>NOx: Nitrogen oxides as NO2<br>PM10: Particulate matter up to 10 µm size<br>PM2.5: Particulate matter up to 2.5 µm size<br>SOx: Sulphuric oxides (as SO2)</p> <p><br>Years<br>-------------------<br>2019</p> <p><br>Units<br>-------------------<br>ton/year</p> <p>Fileformat<br>-------------------<br>geotiff</p>
Mammal occurrence records (2024) in the Valparai Plateau and Anamalai Tiger Reserve, Western Ghats, India
<p>This dataset contains Mammal occurrence records (November 2023 - October 2024) in the Valparai Plateau and Anamalai Tiger Reserve, Western Ghats, India. It includes a few occurrence records from other parts of southern India. Occurrence records were gathered in the field by researchers of the Nature Conservation Foundation, India, using a mobile data collection application (EpiCollect5). Suggested citation is:<br>Nature Conservation Foundation (2024). Mammal occurrence records (2024) in the Valparai Plateau and Anamalai Tiger Reserve, Western Ghats, India. Nature Conservation Foundation, India. Dataset, Zenodo. DOI: 10.5281/zenodo.13910696<br> <br><strong>CONTACT #1</strong><br>1. Name: T. R. Shankar Raman <br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: trsr@ncf-india.org <br>5. ORCID: https://orcid.org/0000-0002-1347-3953</p> <p><strong>CONTACT #2</strong><br>1. Name: Divya Mudappa <br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: divya@ncf-india.org <br>5. ORCID: https://orcid.org/0000-0001-9708-4826</p> <p><strong>Keywords: </strong>tropical rainforest, plantations, Anamalai Hills, Western Ghats, animal distribution, mammals </p> <p><br><strong>Geographic Coverage:</strong><br>1. Location/Study Area: Valparai Plateau, Tamil Nadu, India; Anamalai Tiger Reserve, Tamil Nadu, India<br>2. GPS coordinates: Valparai Plateau (10°15'- 10°22'N, 76°52' - 76°59'E); Anamalai Tiger Reserve (10°12' - 10°35'N, 76°49' - 77°24'E)</p> <p><strong>Temporal Coverage:</strong><br>1. Begins: 2023-11-01 (Year, Month, Day)<br>2. Ends: 2024-10-01 (Year, Month, Day)</p> <p>Besides the 00_readMe.txt file containing this information, the dataset includes 23 images (photographs) and two comma-delimited text (csv) files as explained below:<br><strong>1) 01_anamalai-mammals-2024.csv </strong>-- This file has the main mammal occurrence data with relevant and renamed columns derived from the original downloaded csv file from the EpiCollect5 application website.</p> <p><strong>2) 02_nameMatch.csv</strong> -- This file matches the vernacular name as originally recorded with the correct common name and scientific name</p> <p>+23 image files (with ".jpg" file extension)</p> <p><strong>FILES INCLUDED IN DATASET</strong></p> <p><strong>01_anamalai-mammals-2024.csv</strong><br>This file has the main mammal occurrence data with relevant and renamed columns derived from the original downloaded csv file from the EpiCollect5 application website.<br>ec5_uuid: Unique ID for each observation<br>created_at: Automatic time stamp of date and time when record was created on the mobile app<br>uploaded_at: Automatic time stamp of date and time when record was uploaded using the mobile app<br>recordedBy: Name of observer<br>title: Title assigned to each record (composite of date, species, and type of observation)<br>lat_gps: Latitude in decimal degrees N<br>long_gps: Longitude in decimal degrees E<br>accuracy_gps: Horizontal accuracy of GPS location in metres<br>UTM_Northing_gps: Latitude in UTM<br>UTM_Easting_gps: Longitude in UTM<br>UTM_Zone_gps: UTM Zone<br>eventDate: Date in ISO format (yyyy-mm-dd)<br>verbatimEventDate: Date in format originally recorded (dd/mm/yyyy)<br>eventTime: Time of observation<br>vernacularName: Species common name as initially recorded<br>individualCount: Number of individuals observed<br>occurrenceRemarks: type of observation<br>habitat: Habitat type<br>photo: Filename of photo if available (NA otherwise)<br>eventRemarks: Notes or remarks about the observation</p> <p><strong>02_nameMatch.csv</strong><br>This file matches the name as originally recorded with the correct common name and scientific name.<br>vernacularName: Common or English name as initially recorded <br>scientificName: Scientific name of the species</p> <p>+23 image files (.jpg extension)</p>
Miocene construction of the High Andes recorded by exhumation of the Frontal Cordillera, La Ramada Massif of western Argentina (32°S) (Supporting Information)
<p>Supporting datasets for Howlett et al., "Miocene construction of the High Andes recorded by exhumation of the Frontal Cordillera, La Ramada Massif of western Argentina (32°S)" in <em>TECTONICS.</em></p>
Wildfire and climate teleconnection data in the Western Mediterranean Basin
<p>This dataset contains the data used to conduct all analyses of the manuscript entitled "<strong>Spatio-temporal domains of wildfire-prone teleconnection patterns in the Western Mediterranean Basin</strong>". Submitted to Geophysical Research Letters.</p> <p>File <em>fire_data.csv</em> contains monthly gridded data of total burned area (BA), number of fire ignitions (N) and the 95th percentile of fire size (S) at 0.5 degree spatial resolution. The spatial extent covers Portugal, Spain, Southern France, Corsica and Sardina. Original data sources have been acknowledged in the manuscript file.</p> <p>File <em>teleconnections.csv</em> contains monthly data of the the North Atlantic Oscillation (NAO), the East Atlantic (EA), the Atlantic Multidecadal Oscillation (AMO), the El Niño Southern Oscillation (ENSO), the Mediterranean Oscillation (MOI), the Pacific Decadal Oscillation (PDO), the Scandinavian pattern (SCAND) and the Western Mediterranean oscillation (WeMOi). Original data sources have been acknowledged in the manuscript file.</p>
ScienceDex guides
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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.