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19,393 results for “water”
SBC LTER: Reef: Bottom Temperature: Continuous water temperature, ongoing since 2000
Giant kelp forests and the organisms living within them are exposed to a variable environment where biotic and abiotic drivers may affect populations and biological processes on the scale of hours to decades. To examine temporal and spatial patterns of temperature in giant kelp forests, SBC has measured ambient water temperature at nine reef sites located along the mainland coast of the Santa Barbara Channel and at two sites on the north side Santa Cruz Island beginning in 2000. Two submersible temperature loggers, sampling every 30 minutes and offset from each other by 15 minutes, are deployed so that data is recorded every 15 minutes at each site. Temperature loggers were retrieved and replaced bi-annually with a new logger, typically in the early summer (June-July) and in early winter (January-March). These temperature loggers measure temperature in water within a range of -20°C to 30°C, and accuracy of ± 0.20°C at 25°C.
SBC LTER: Ocean: High resolution water temperature at Mohawk and Arroyo Quemado, ongoing since 2018
Ocean in-situ temperature data were collected at two nearshore locations: Mohawk and Arroyo Quemado. There are three sites at each of the locations: inshore, offshore, and east of reef. Temperature was recorded using hobo sensors at 1-meter interval along the water column, and the sampling interval is 2 minutes.
SBC LTER: Reference: Sea-surface water temperature, Santa Barbara Harbor, Santa Barbara, CA, USA, 1955 to present, ongoing
The SBC-LTER has access to data on seawater temperature collected at Santa Barbara Harbor, Santa Barbara, CA, USA through the Scripps Institution of Oceanography Manual Shore Stations program. The SIO Manual Shore Stations program provides data and information about this shore station. For further information, please visit the SIO Manual Shore Stations website at https://library.ucsd.edu/dc/object/bb07606686. Please note: manual shore station data is updated periodically, not continuously. Funding for the Shore Stations Program provided by the California Department of Parks and Recreation, Natural Resources Division, Award# C22820005. Contact shorestation@ucsd.edu if you have questions
SBC LTER: Ocean: Time-series: Mid-water SeaFET and CO2 system chemistry at Alegria (ALE), 2011-2014
Calibrated pH (Total scale, SeaFET sensor) data was collected from Alegria in the Santa Barbara Channel (site ID: ALE) along with in situ temperature and associated carbonate chemistry parameters. The SeaFET instrument is located about 4 meters from the surface, with other moored instruments. Associated carbonate chemistry parameters were calculated with the CO2calc programs from USGS, and include: partial pressure and fugosity of CO2, concentrations of bicarbonate, carbonate and hyrdroxide ion, Omega (saturation state) of calcite and aragonite. Data have been interpolated to a 20 minute time interval for compatibility with other SBC LTER moored instrument data. Data coverage is 2011-06-21 to 2014-01-07.The update of this dataset was terminated in 2019. All data from this site have been concatenated with the pH data from the other sites and merged into one data package: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sbc&identifier=6005
SBC LTER: pH time series: Water-sample pH and CO2 system chemistry, ongoing since 2011
Data are a time-series of pH and carbonate chemistry in manually-collected sea water samples from sixteen near-shore locations and 20 locations along the Santa Barbara Channel, California, USA, and intended to benchmark data from moored pH instruments. Data collection began in June 2011 and is ongoing. Time-series for pH sensors deployed in the field (e.g., SeaFET) are available elsewhere. Discrete seawater samples were collected by hand or using a Niskin bottle. In the laboratory, samples were analyzed for pH (total scale) and total alkalinity. Two parameters were used to calculate the full suite of carbonate chemistry parameters using the CO2calc algorithms. Program outputs are included for laboratory conditions as input, and adjusted for situ temperature. See Methods for more information, e.g., Lunden, et al. Data were collected by a consortium of research groups with the intent to leverage their collective assets and expertise. These groups (and sponsors) include Santa Barbara Coastal LTER (NSF), OMEGAS Project (NSF), Passow Lab (Calif. State Water Board), Hofmann Lab (NSF, CINMS, US NPS).
Stream Water Level and Temperature for Mainland Creeks on the Atlantic Coast of Virginia 2002-2009
This dataset includes stage (water level) and temperature for selected creeks along the Atlantic Coast of the Delmarva Peninsula, in Virginia. Pressure sensors were placed in the creeks (typically along the edge of Route 600 (Seaside Road), and corrected for barometric pressure changes in post-processing.
Light profiles in the water column of coastal bays of Virginia 2011-2024
Measurements of light extinction were made from a small boat at designated stations. Measurements were taken above the water (AIR), 10 cm below the surface (SURFACE) and at depths from 25 cm (D_025cm) to 250 cm (D_250cm) below the surface. All light measurements were made with a Licor 4-pi quantum Photosynthetically Active Radiation (PAR) sensor LI-193 and a LI-1000 or LI-250a light meter. All light units are in microEinsteins (moles of photons) Calculations of the extinction coefficient (Kd) should NOT include air measurements.
Audio and Water Movement Data for Oyster Reef and Mudflat Sites on the Coast of Virginia, 2018
Paired marine audio soundscape recordings with concurrent acoustic Doppler velocimeter (ADV) turbulence measurements at three intertidal sites: a natural oyster reef, a restored oyster reef, and a bare mudflat. The objective was to establish the link between oyster reef soundscapes and hydrodynamics, specifically the role that turbulence plays in generating near field pressure waves that may be used as physical cues by oyster larvae when initiating settlement behaviors. Data were collected at three different locations, with water turbulance measurements at rates up to 25Hz concurrent with audio recording.
Raw stable water isotope measurements in water vapour at 8 m a.s.l. on the port side of the ship, made in the austral summer of 2016/2017 during the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>This dataset includes the raw data of stable water vapour isotope (δ18O, δ2H, deuterium excess) and water vapour mixing ratio measurements at a height of approximately 8 meters above sea level taken in the Southern Ocean during the Antarctic Circumnavigation Expedition (ACE) from November 2016 to April 2017 using a Picarro laser spectrometer L2120 mounted on the port side of the ship. The spectrometer was operated throughout the whole expedition. This data has to be calibrated using the calibration runs and applying an appropriate calibration procedure following the IAEA guide lines.</p> <p>Two similar datasets also measuring stable water isotopes (SWIs) in water vapour were collected during the same expedition and can be distinguished from this dataset due to the height of the measurement collection (at 8 m a.s.l and 13.5 m a.s.l). The three ACE datasets of SWIs in water vapour are described and compared in Thurnherr et al. (2020).</p> <p><strong>Dataset contents</strong></p> <ul> <li>leg*/HBDS2190-yyyymmdd-hhmmssZ-DataLog_User.dat, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p><strong>Dataset license</strong></p> <p>This raw stable water isotope measurements dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full description can be found at https://creativecommons.org/licenses/by/4.0/</p> <p><strong>Dataset citation</strong></p> <p>Please cite this dataset as:<br> Kozachek, A. (2020). Raw stable water isotope measurements in water vapour at 8 m a.s.l. on the port side of the ship, made in the austral summer of 2016/2017 during the Antarctic Circumnavigation Expedition (ACE). (Version 1.0) [Data set]. Zenodo.</p>
Water restriction induces behavioral fight but impairs thermoregulation in a dry-skinned ectotherm
<p>Raw data of the article "Water restriction induces behavioral fight but impairs thermoregulation in a dry‐skinned ectotherm" by Rozen-Rechels D. et al., published in Oikos in 2020 (https://doi.org/10.1111/oik.06910). These data are freely available and are provided as csv files. Check the readme file for information on metadata.</p> <p>Data were formatted by David Rozen-Rechels and produced according to standards and protocols described in the companion paper.</p>
Carbon and water fluxes in a cork oak woodland in Central Portugal
<p>The Data set contains eddy covariance measurements of carbon and water fluxes and ancillary measurements observed at a cork oak woodland (<em>Quercus suber </em>L.) in central Portugal. The climate is Mediterranean, with mild, wet winters and hot, dry summers.</p> <p>Data are available in the file data.csv (UTF-8 encoding), the description of the variables and units are available in the file meta.csv (UTF-8 encoding).</p> <p>Further description of the site, methods and data processing can be viewed in the files metadata.pdf and metadata.csv</p> <p> </p>
Calibrated data of stable water isotope measurements in water vapour at 13.5 m a.s.l., made in the austral summer of 2016/2017 around the Southern Ocean during the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>This data set includes the calibrated data of stable water vapour isotope (δ<sup>18</sup>O, δ<sup>2</sup>H, deuterium excess) and water vapour mixing ratio measurements at approximately 13.5 m a.s.l. taken around the Southern Ocean during the Antarctic Circumnavigation Expedition (ACE) from November 2016 to April 2017 using a Picarro laser spectrometer L2130. The data provides continuous timelines of atmospheric water vapour properties in the marine boundary layer for studies of the atmospheric water cycle.</p> <p>The raw data from which this calibrated dataset originates has been published separately (Thurnherr and Aemisegger, 2019; DOI 10.5281/zenodo.3664177).</p> <p>Two other calibrated stable water isotope measurement datasets were also collected during ACE. They differ by the location of measurement on the ship: 8 m a.s.l on the starboard (DOI: 10.5281/zenodo.3739335) and port sides (DOI: 10.5281/zenodo.3739354).</p> <p><strong>Dataset contents</strong></p> <ul> <li>ACE_watervapour_isotopes_SWI13_1h.csv, data file, comma-separated values</li> <li>ACE_watervapour_isotopes_SWI13_5min.csv, data file, comma-separated values</li> <li>cal_runs_SWI13.csv, metadata, comma-separated values</li> <li>data_file_header.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p>NaN values denote missing values which occur because of e.g., maintenance, instrument calibration, large cavity variations.</p> <p><strong>Dataset license</strong></p> <p>This calibrated stable water isotope measurements in water vapour is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Calibrated data of stable water isotope measurements in water vapour at 8 m a.s.l. on the starboard side of the ship, made in the austral summer of 2016/2017 around the Southern Ocean during the Antarctic Circumnavigation Expedition.
<p><strong>Dataset abstract</strong></p> <p>This data set includes the calibrated data of stable water vapour isotope (δ18O, δ2H, deuterium excess) and water vapour mixing ratio measurements at approximately 8 m a.s.l. on the starboard of the ship, taken around the Southern Ocean during the Antarctic Circumnavigation Expedition (ACE) from February to March 2017 using a Picarro laser spectrometers L2130-i. The data provide continuous timelines of atmospheric water vapour properties in the marine boundary layer for studies of the atmospheric water cycle.</p> <p>The raw data from which this calibrated dataset originates has been published separately (Kozachek, 2020; DOI 10.5281/zenodo.3667535).</p> <p>Two other calibrated stable water isotope measurement datasets were also collected during ACE. They differ by the location of measurement on the ship: 8 m a.s.l on the port side (DOI: 10.5281/zenodo.3739354) and 13.5 m a.s.l (DOI 10.5281/zenodo.3250790).</p> <p><strong>Dataset contents</strong></p> <ul> <li>ACE_watervapour_isotopes_SWI8-sb_1h.csv, data file, comma-separated values</li> <li>ACE_watervapour_isotopes_SWI8-sb_5min.csv, data file, comma-separated values</li> <li>cal_runs_SWI8-sb.csv, metadata, comma-separated values</li> <li>cal_flag_times_SWI8-sb.csv, metadata, comma-separated values</li> <li>data_file_header.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p>NaN values denote missing values which occur because of e.g., maintenance, instrument calibration, large cavity variations.</p> <p><strong>Dataset license</strong></p> <p>This calibrated stable water isotope measurements in water vapour is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
A Spatially Variable Time Series of Sea Level Change Due to Artificial Water Impoundment
<p>This database contains a series of gravitational, rotational, and deformational (GRD) "fingerprints"—the spatial response of sea level—corresponding to redistribution of water mass because of impoundment of water in artificial reservoirs, as reported in Hawley <em>et al</em>. (2020). Fingerprints for the GRanD database (Lehner <em>et al</em>.; 2011) are for individual years, noted in the file name.</p> <p>Three additional files come from the dataset provided by Zarfl <em>et al</em>. (2015), as described in Hawley <em>et al.</em> (2020). "Const" includes the fingerprint for all reservoirs under construction in their database; "Plan" includes the fingerprint for all reservoirs in the planning phase. "Zarfl" includes the fingerprint for all reservoirs in "Const," with 15 years of seepage, as well as all reservoirs for "Plan" with 5 years of seepage, as described in Hawley <em>et al</em>. (2020).</p> <p>Each fingerprint has 525,825 points, which fill out a global grid of 513 x 1025 [lat x lon] points. Each node in latitude and longitude is evenly spaced. The first point represents the northernmost point at 0 [deg] longitude, and increase first to the east, then to the south.</p>
Mask at 300 m of water-body locations more than 5, 15 and 20 km distant from land
<p>Locations of water-body locations remote from land: This dataset is a latitude-longitude grid indicating the locations of water-body locations more distant from land than 5, 15 and 20 km. It is derived from Carrea et al., 2016, which in turn was derived from the ESA Climate Change Initiative for Land Cover Water Bodies product released in October 2014. 3 = distance greater than 20 km; >=2 = distance greater than 15 km; >=1 = distance greater than 5 km. Paper describing underlying distance-to-land dataset: Carrea, L., Embury, O., Merchant, C.J. (2016) Datasets related to inland water for limnology and remote sensing applications: distance-to-land, distance-to-water, water-body identifier and lake-centre co-ordinates. Geoscience Data Journal, 2(2). pp. 83-97. doi: https://doi.org/10.1002/gdj3.32. This work done within the project: ESA Climate Change Initiative Lakes, by University of Reading, UK. </p> <p> 'geospatial_lat_min': -90.0,\<br> 'geospatial_lat_max': 90.0,\<br> 'geospatial_lon_min': -180.0,\<br> 'geospatial_lon_max': 180.0,\<br> 'geospatial_lat_units': 'degrees_north',\<br> 'geospatial_lat_resolution': 0.0027777778,\<br> 'geospatial_lon_units': 'degrees_east',\<br> 'geospatial_lon_resolution': 0.0027777778,\<br> 'spatial_resolution': '300m'</p>
Water
<p>Urban Atlas based data subset, where every element with CODE 50000 was extracted as a water element with the next information:</p> <p>gid integer area numeric perimeter numeric geom geometry(polygon,3035) albedo real emissivity real transmissivity real vegetation_shadow real run_off_coefficient real building_shadow smallint</p> <p>This data is an input for local effects calculation.</p>
DataSet of "No renal dysfunction or salt and water retention in acute mountain sickness at 4,559 m among young resting males after passive ascent"
<p><strong>Abstract</strong></p> <p><strong>Purpose</strong>: This study examined the role and function of the kidney at high altitude in relation to fluid balance and the development of acute mountain sickness (AMS), avoiding confounders that have contributed to conflicting results in previous studies.</p> <p><strong>Methods</strong>: We examined 18 healthy male volunteers (18 - 40 years) not acclimatized to high altitude while on a controlled diet and resting recumbently for 24 h at Lausanne (altitude: 560 m) followed by a period of 44 hours after reaching the Regina Margherita hut (4,559 m) by helicopter.</p> <p><strong>Results</strong>: AMS scores peaked after 20 h at 4,559 m. AMS was defined as functional Lake Louise score <span class="math-tex">\({\ge}\)</span> 2.There were no significant differences between 10 subjects with and 8 subjects without AMS for urinary flow, fluid balance and weight change. Sodium excretion rate was lower in those with AMS after 24 h at altitude. Microalbuminuria increased at altitude but not differently between the groups. Creatinine clearance was not affected by altitude or AMS, while sinistrin and PAH clearances decreased slightly, more markedly in those without AMS. Plasma concentrations of epinephrine, norepinephrine, atrial natriuretic factor and vasopressin increased while renin activity, angiotensin and aldosterone decreased at altitude. Hormones levels did not differ between those with and without AMS.</p> <p><strong>Conclusions</strong>: 1) Renal function is not affected by hypoxia at 4,559 m in resting subjects except for minor microalbuminuria, 2) high altitude diuresis does not occur and 3) AMS is not associated with salt and water retention or renal dysfunction.</p>
Water vapor isotope data from Pallas-Yllastunturi National Park, Finland (Winter 2017-18)
<p>Calibrated water vapor isotope and mixing ratio data from Pallas-Yllastunturi National Park, Finland.</p> <p>Site Name: Sammaltunturi Station, Finland (Finnish Meteorological Institute) <br> Site Location: 67.973°N; 24.116°E <br> Site Elevation: 565 m above sea level <br> Instrumentation: Picarro L2130-i Isotope and Gas Concentration Analyser<br> Parameters: δ<sup>18</sup>O water vapor, δ<sup>2</sup>H water vapor, deuterium (d)-excess water vapor, mixing ratio (5-minute averages)<br> Date/Time start: 20/12/2017 05:45 EET<br> Date/Time end: 31/03/2018 23:55 EET</p>
Background data: Untangling the effects of multiple human stressors and their impacts on fish assemblages in European running waters
<p>This dataset presents some backkground data from the EFI+ database. Related work addresses human stressors and their impacts on fish assemblages at pan-European scale by analysing single and multiple stressors and their interactions. Based on an extensive dataset with 3105 fish sampling sites, patterns of stressors, their combination and nature of interactions, i.e. synergistic, antagonistic and additive were investigated. </p> <p>Data were derived within the EU-project "Improvement and Spatial extension of the European Fish Index (EFI+)". EFI+, an EU FP6 research project from 2007-2009 was designed to gain new knowledge and to further develop and improve new biological assessment methods to meet needs of the Water Framework Directive (WFD). </p> <p>Background data are available for boxplots and barplots shown in the related research article in STOTEN.</p>
GRWSE-global river water surface elevation from sentinel-3
<p>This dataset includes time series of Water Surface Elevation (WSE) of large rivers at over 3000 virtual stations. The WSE time series were created using Sentinel-3A and Sentinel-3B altimetry data. </p>
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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.