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Dataset results
8 results for “2010 - 2017”
Fish tag data remotely detected using whole stream antennas or hand held tag readers in the Kuparuk, Itkilik, and Sagavanirktok drainages near Toolik Field Station, Alaska, from 2010 to 2017
From 2009 to 2017, the FISHSCAPE Project (grant numbers 1719267, 1417754, and 0902153), based at Toolik Field Station, has monitored physical, chemical, and biological parameters within three watersheds: The Kuparuk (including Toolik Lake and Toolik outlet stream); The Sagavanirktok (primarily Oksrukuyik Creek, but also including sections of the Ailish and Atigun Rivers and the Galbraith Lakes); and The Itkillik (primarily the I-Minus outlet stream, a tributary that that feeds into the Itkilik River). Target species were primarily Arctic grayling and Lake trout, although Arctic char, Burbot, Dolly varden, round whitefish, and slimey sculpin were also captured. This file contains the detectioned fish tags using whole stream or hand-held antennas in the three watersheds. We had no field season in 2014 and thus did not deploy antennaes. Fish were tagged with Passive Integrated Transponder (PIT) tags which can be read with a whole stream antenna to track the migration of the fish, predominately Arctic grayling, throughout the systems. Fish tags detected with a handheld readers are designated in Site ID as "XXX_capture". For "capture" fish time is arbitraily set at '7:00:00'' of the day of capture and tagging because actual time was not recorded. The individual fish data (date, tag number, length, weight, species) associated with the tag can be found in the 2009-2017_FISHSCAPE_fish_tagging file.
LIDAR Derived Dune-Crest Elevation Values and Shrub Prediction Morphometrics for the Virginia Coast Reserve Barrier Islands: 2010 - 2017
This dataset includes LIDAR derived dune-crest elevation values for the VCR for 2010-2017. Dune-crest elevation values were sampled every 100 m from Smith to Cedar islands. The ArcGis Pro file includes the location of dune-crest transects. Additionally, this dataset includes island characteristics related to predicting shrub presence or absence for 2010, 2016, and 2017.
TOMCAT model data & IASI satellite data of O3, CO, H2O, CH4 and OH/derived OH for 2010 and 2017
<p>Monthly mean data of ozone (O3), carbon monoxide (CO), water vapour (H2O), methane (CH4) and the hydroxyl radical (OH) for 2010 and 2017.</p> <p>Model data is from the 3D chemical transport model TOMCAT (Chipperfield, 2006).</p> <p>Satellite observations are from the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp-A satellite and retrieved using schemes developed by the Rutherford Appleton Laboratory (RAL). The Ch4 is from RAL's CH4 retrieval scheme (Siddans et al. 2020) and the O3, CO and H2O retrievals are from the extended version of RAL’s Infrared and Microwave Sounding (IMS-extended) scheme (Pope et al. 2021). </p> <p>Full description of the data can be found in Pimlott et al. (2022) (preprint: https://doi.org/10.5194/acp-2022-79) which has now been accepted for publication in ACP. </p>
Text-fig. 3. Bivariate plots of the lower teeth (m3 – m2) of small to medium sized Miocene hyaenodonts from African localities. Data source: Pilgrim (1912, 1932), Colbert (1935), Savage (1965), Barry (1988), Morales et al. (1998a, 2003, 2007, 2008, 2010), Holroyd (1999), Morlo et al. (2007), Rasmussen et al. (2009), Borths et al. (2016), Borths and Seiffert (2017). in New Hyaenodonts (Ferae, Mammalia) From The Early Miocene Of Napak (Uganda), Koru (Kenya) And Grillental (Namibia)
Text-fig. 3. Bivariate plots of the lower teeth (m3 – m2) of small to medium sized Miocene hyaenodonts from African localities. Data source: Pilgrim (1912, 1932), Colbert (1935), Savage (1965), Barry (1988), Morales et al. (1998a, 2003, 2007, 2008, 2010), Holroyd (1999), Morlo et al. (2007), Rasmussen et al. (2009), Borths et al. (2016), Borths and Seiffert (2017).
Uribe-Rivera et al 2017 DataSet: High resolution bioclimatic layers for southwest of South America for three recent past periods (1970, 1990 and 2010)
<p>These files were generated as part of the article "Dispersal and extrapolation on the accuracy of temporal predictions from distribution models for the Darwin’s frog" (Uribe-Rivera et al. 2017; accepted in Ecological Applications)</p> <p>We used point data of meteorological stations between 34°-48°S and 70°-75°W, to generate new climatic surfaces for three recent past periods (1970; 1990; 2010). Meteorological data encompassed 293 weather stations, and were extracted from three databases: Dirección Meteorológica de Chile (DMC); Dirección General de Aguas de Chile (DGA); and the FAOClim-NET Agroclimatic database management system (FAO 2001), recording monthly records of mean daily minimum temperature, mean daily maximum temperature and total rainfall for 5-year periods (1965-1969 for 1970 climatic conditions; 1985-1989 for 1990 climatic conditions; and 2005-2009 for 2010 climatic conditions). For each period monthly mean values of each climatic variable were interpolated to generate surfaces using Anusplin v.4.4 (Hutchinson and Xu 2006), which applies the same algorithm used to derive the WorldClim bioclimatic surfaces (Hijmans et al. 2005). Interpolations were fitted following Pliscoff et al. (2014) at a ~1x1 Km resolution, with elevation as an independent variable using the GTOPO30 global digital elevation model (USGS, 1996). Because some weather stations do not have information for every month, we used the option of non-data of Anusplin. The quality of interpolations of climatic data was assessed calculating the Pearson correlation coefficient at the cell level between the monthly climatic values from the CRU-TS v3.10.01 Historic Climate Database for GIS (Climatic Research Unit - Time Series, 2012), and the monthly climatic values from the new climatic layers. Finally, surfaces of 19 bioclimatic variables were generated using the dismo package in R (Hijmans et al. 2014).</p> <p>All bioclimatic layers were uploaded in a single compressed ZIP file. Individual layers can be found inside it as georeferenced ASCII raster files, and nominated primarily by time period, and secundarily by the number of bioclimatic layer, following the worldclim nomenclature (http://www.worldclim.org/bioclim).</p>
Personality, space use, network, and tick infestation data from a field study of sleepy lizards, 2010 and 2014 - 2017
Open the record for dataset details and reuse information.
Carbon Pools across CONUS using the MaxEnt Model, 2005, 2010, 2015, 2016, and 2017
This dataset provides annual estimates of six carbon pools, including forest aboveground live biomass, belowground biomass, aboveground dead biomass, belowground dead biomass, litter, and soil organic matter, across the conterminous United States (CONUS) for 2005, 2010, 2015, 2016, and 2017. Carbon stocks were estimated using a modified MaxEnt model. Measurements of pixel-specific site conditions from remote sensing data were combined with field inventory data from the U.S. Forest Service Forest Inventory and Analysis (FIA). Remote sensing data inputs included Thematic Mapper on Landsat 5, Operational Land Imager on Landsat 8, Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua, microwave radar measurements from Phased Array type L-band Synthetic Aperture Radar (PALSAR) on Advanced Land Observation Satellite (ALOS) and PALSAR-2 ALOS-2, airborne imagery from National Agriculture Imagery Program (NAIP), and the digital elevation model from the Shuttle Radar Topography Mission (SRTM). Data from satellite and airborne sources were co-registered on a common 100 m (1 ha) grid.
Dataset related to article: "Psychosocial Cardiological Schedule-Revised (PCS-R) in a Cardiac Rehabilitation Unit: Reflections Upon Data Collection (2010–2017) and New Challenges"
<p><strong>Introduction: </strong>The Psychosocial Cardiological Schedule (PCS) was developed as a screening tool for patients undergoing cardiac rehabilitation (CR) to detect clinically relevant psychosocial/cognitive problems requiring psychological assessment/intervention. Filled out by a trained nurse, it classifies patients according to their need or not for a psychological interview and intervention provided by the psychologist (PCS-Yes vs. PCS-No).</p> <p><strong>Aims: </strong>The main aim was to compare PCS data collected, respectively, in 2010 and 2017, regarding patients' socio-demographic characteristics, clinical variables, and the inclusion criteria for psychological counseling. Subsequently, the original Italian PCS was revised and an English version of the schedule was provided [PCS-Revised (PCS-R)].</p> <p><strong>Results: </strong>28 patients (aged 53.5 + 12.6 years, M = 20) of the 87 recruited in 2010 vs. 35 (aged 64.9 + 12.7 years, M = 28) of the 83 recruited in 2017 met the criteria for PCS-Yes: age < 55 years, social problems (living alone, no social support), manifest psychological/behavioral problems, suspected neuropsychological disorders, low prescription adherence, inadequate disease awareness. Comparing the two samples (2010 vs. 2017), clinical variables were similar, and the need for a psychological interview did not differ substantially (32.2 vs. 42.2%), but age increased significantly (PCS-Yes: 53.5 ± 12.6 vs. 64.9 ± 12.7 years, <em>p</em> = 0.001; PCS-No: 68.3 ± 8.0 vs. 75.0 ± 7.7 years, <em>p</em> = 0.0001). A significant increase was observed in the recommendation for neuropsychological assessment (3.6 vs. 25.7%, <em>p</em> = 0.02) to confirm eventual cognitive deficits. These results, the clinical experience, and the recent evidences from literature led to the PCS-R, incorporating a psychosocial screening, a psychological/neuropsychological deeper assessment, and a recommendation for a specific intervention to be carried out either during rehabilitation or in outpatient services.</p> <p><strong>Conclusion: </strong>The data comparison highlight changes in the cardiac population, which is aging and more frequently requires neuropsychological assessment. The PCS-R could be considered in clinical practice as a useful screening tool to implement a timely coordinated interdisciplinary intervention, comprehensive of specific and tailored psychotherapeutic techniques.</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.