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396 results for “Surface water”
September 2003 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites
Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in September, 2003. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.
December 2003 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites
Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in December, 2003. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.
March 2004 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites
Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in March, 2004. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.
May 2004 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites
Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in May, 2004. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.
March 2002 surface water phytoplankton productivity for 10 Georgia Coastal Ecosystems LTER sampling sites
Water samples were collected by Niskin bottle or by hand from just beneath the surface during low tide surveys at or near 10 GCE-LTER sampling sites in March 2002. The incorporation of radiolabelled bicarbonate in response to varying levels of illumination was measured using a photosynthetron apparatus. Photosynthesis-irradiance (P-I) curves constructed from these measurements will be used in conjunction with algal biomass and PAR versus depth measurements to estimate instantaneous gross primary production in the water at each GCE sampling site. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.
Surface water DIC, total alkalinity, and pH for the September 2002 through December 2004 Georgia Coastal Ecosystems LTER oceanographic surveys
Surface water samples for total dissolved inorganic carbon (DIC), total alkalinity (TAlk), and pH were collected from the Altamaha River, Doboy Sound, Sapelo River and the Duplin River (anchor station near Marsh Landing) during the Georgia Coastal Ecosystems LTER oceanographic surveys from September 2002 through December 2004. DIC was measured using a custom automated DIC analyzer. Total alkalinity was determined by Gran titration. pH of surface water at stations was measured on board using a glass electrode. This study was part of the GCE oceanographic monitoring program, and will be repeated periodically.
Surface water DIC, total alkalinity, and pH for the March 2001 Georgia Coastal Ecosystems LTER oceanographic survey
Surface water samples for total dissolved inorganic carbon (DIC), total alkalinity (TAlk), and pH were collected from the Altamaha River, Doboy Sound, Sapelo River and the Duplin River (anchor station near Marsh Landing) during March 19-21, 2001. DIC was measured using a custom automated DIC analyzer. Total alkalinity was determined by Gran titration. pH of surface water at stations was measured on board using a glass electrode. This study was part of the GCE oceanographic monitoring program, and will be repeated periodically.
Surface water DIC, total alkalinity, and pH for the June 2001 Georgia Coastal Ecosystems LTER oceanographic survey
Surface water samples for total dissolved inorganic carbon (DIC), total alkalinity (TAlk), and pH were collected from the Altamaha River, Doboy Sound, Sapelo River and the Duplin River (anchor station near Marsh Landing) during June 26-28, 2001. DIC was measured using a custom automated DIC analyzer. Total alkalinity was determined by Gran titration. pH of surface water at stations was measured on board using a glass electrode. This study was part of the GCE oceanographic monitoring program, and will be repeated periodically.
Surface water DIC, total alkalinity, and pH for the October 2001 Georgia Coastal Ecosystems LTER oceanographic survey
Surface water samples for total dissolved inorganic carbon (DIC), total alkalinity (TAlk), and pH were collected from the Altamaha River, Doboy Sound, Sapelo River and the Duplin River (anchor station near Marsh Landing) during October 11-14, 2001. DIC was measured using a custom automated DIC analyzer. Total alkalinity was determined by Gran titration. pH of surface water at stations was measured on board using a glass electrode. This study was part of the GCE oceanographic monitoring program, and will be repeated periodically.
Surface water DIC, total alkalinity, and pH for the November 2001 Georgia Coastal Ecosystems LTER oceanographic survey
Surface water samples for total dissolved inorganic carbon (DIC), total alkalinity (TAlk), and pH were collected from the Altamaha River, Doboy Sound, Sapelo River and the Duplin River (anchor station near Marsh Landing) during November 26-29, 2001. DIC was measured using a custom automated DIC analyzer. Total alkalinity was determined by Gran titration. pH of surface water at stations was measured on board using a glass electrode. This study was part of the GCE oceanographic monitoring program, and will be repeated periodically.
June 2001 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites
Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in June, 2001. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.
October 2001 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites
Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in October, 2001. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.
November 2001 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites
Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in November, 2001. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.
March 2002 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites
Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in March, 2002. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.
September 2002 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites
Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in September, 2002. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.
Minneapolis-St. Paul Metro Area Lakes Surface Water Quality Characteristics
Urban lakes are heavily impacted by human activities and climate variability, and they provide many ecosystem services to residents. The MSP LTER program is studying long term changes in urban lake water quality, ecology and management as part of our long term studies of urban environments. The goal of this dataset is to understand how land-use change, management, and climate have impacted urban lake biogeochemistry over time. This dataset includes parameters characterizing the long term (> 5 years) surface water quality and chemistry of 294 lakes and ponds in the Minneapolis-Saint Paul Seven County Metropolitan Area, Minnesota, USA. The dataset draws from data publicly available through the Minnesota Pollution Control Agency and data provided by individual agencies, park districts and cities. The dataset is distinct from other lake datasets because it is curated to only report a single value per lake x date x parameter, minimizing the amount of data manipulation needed before use in statistical analyses. All data come from the top two meters of the water column. In the case of multiple spatial measurements on a single lake or multiple agencies sampling the same lake on the same day, chemistry data were averaged to generate a single value. For Secchi data, the deepest reported observation on a given lake x date was used. Parameters: total phosphorus, total nitrogen, total Kjeldahl nitrogen, nitrate, nitrite, nitrate + nitrite (NOx), ammonium, chlorophyll a (corrected and not corrected for pheophytin), specific conductivity, chloride, and Secchi depth. These waterbodies are identified by their DNR Division of Water (DOW) number with minor alterations for subbasin identification. This dataset does not comprehensively represent all lentic waterbodies that have substantial water quality data in the metro area, and some included waterbodies may be considered wetlands according to state classifications. The data brought together in this database has undergone QAQC by the
Water surface occurrence and recurrence from the article "Amazon's 2023 Drought: Sentinel-1 Reveals Extreme Rio Negro River Contraction"
<p>This data package contains the 10 m spatial resolution occurrence and recurrence water surface masks from the article "Amazon's 2023 Drought: Sentinel-1 Reveals Extreme Rio Negro River Contraction" . These maps have been produced with Sentinel-1 images (10 m) and a Deep Learning method for image segmentation called U-net, methods and data are fully described in the article. Water surface occurrence is computed for the period 2022-2023 and indicates the percentage of time that a pixel is classified as water (100%: always water, 0%: never water, and values between 0 and 100 indicate seasonality). Water surface recurrence is computed for the period 2022-2023 and indicates the number of times that a pixel was classified as a water surface, i.e., 35 indicates that the pixel was classified 35 times as a water surface during the 2022-2023 period. The total size of the dataset is 158 Mo and is distributed in two Geotiffs, one for the water surface occurence and one for the water surface. When using this dataset, please cite the original article <a href="https://doi.org/10.3390/rs16061056">https://doi.org/10.3390/rs16061056</a></p>
Redistribution of the map of the water surfaces of the Flemish Region (status 2024)
<p>This is a redistribution of the dataset '<a href="https://www.vlaanderen.be/datavindplaats/catalogus/watervlakken-versie-2024" target="_blank" rel="noopener">Watervlakken - versie 2024</a>’ (Water surfaces - edition 2024), originally published by the Research Institute for Nature and Forest (INBO) and distributed by 'Informatie Vlaanderen' under a CC-BY compatible license. More specifically, this Zenodo record redistributes the GeoPackage file from the original data source, in order to support reproducible, analytical workflows on Flemish Natura 2000 habitats and regionally important biotopes.</p> <p>The digital map of standing water surfaces (edition 2024) is a georeferenced digital file of standing surface waters in Flanders (northern Belgium). The file contains 93 201 polygons with an area between 1.45 m² and 2.47 km² and can be considered as the most complete and accurate representation of lentic water bodies presently available for the Flemish territory. The map is based on topographic map layers, orthophoto images, the Digital Terrain Model of Flanders version II, results of a water prediction model and, to a lesser extent, field observations. It can be used for a wide range of applications in research, policy preparation and policy implementation, management planning and evaluation that consider the distribution and characteristics of stagnant water bodies. The map is also relevant internationally, including updates for the National Wetland Inventories (Ramsar). Furthermore, its unique reference to each object will considerably facilitate related data management.</p> <p>For this new edition of Watervlakken (2024), the orthophoto images of 2021, 2022 and 2023 and the digital terrain model of Flanders have been used. This edition also uses the results of an AI prediction model for water developed by VITO. Data from various Regional Landscapes, ad hoc user reports and field observations have been used to digitise additional polygons, make shape corrections or remove filled ponds from the map layer. For a number of water surfaces, new data on the Flemish type according to the European Water Framework Directive (WFD type), water depth and connectivity have been added to the attribute table.</p> <p>The data source is produced, owned and administered by the Research Institute for Nature and Forest (INBO, Department of Environment of the Flemish government).</p>
The Water-ice Feature in Near-infrared Disk-scattered Light around HD 142527: Micron-sized Icy Grains Lifted up to the Disk Surface?
<p>This is a reproduction package for the paper "The Water-ice Feature in Near-infrared Disk-scattered Light around HD 142527: Micron-sized Icy Grains Lifted up to the Disk Surface?" by Tazaki et al. (2021). In this repository, you will find the data files used to make figures in the paper. Source codes and scripts are included as well.</p>
The Surface Water Chemistry (SWatCh) database
<p>This is the dataset presented in the following manuscript: The Surface Water Chemistry (SWatCh) database: A standardized global database of water chemistry to facilitate large-sample hydrological research, which is currently under review at Earth System Science Data.</p> <p>Openly accessible global scale surface water chemistry datasets are urgently needed to detect widespread trends and problems, to help identify their possible solutions, and determine critical spatial data gaps where more monitoring is required. Existing datasets are limited in availability, sample size/sampling frequency, and geographic scope. These limitations inhibit the answering of emerging transboundary water chemistry questions, for example, the detection and understanding of delayed recovery from freshwater acidification. Here, we begin to address these limitations by compiling the global surface water chemistry (SWatCh) database. We collect, clean, standardize, and aggregate open access data provided by six national and international agencies to compile a database containing information on sites, methods, and samples, and a GIS shapefile of site locations. We remove poor quality data (for example, values flagged as “suspect” or “rejected”), standardize variable naming conventions and units, and perform other data cleaning steps required for statistical analysis. The database contains water chemistry data for streams, rivers, canals, ponds, lakes, and reservoirs across seven continents, 24 variables, 33,722 sites, and over 5 million samples collected between 1960 and 2022. Similar to prior research, we identify critical spatial data gaps on the African and Asian continents, highlighting the need for more data collection and sharing initiatives in these areas, especially considering freshwater ecosystems in these environs are predicted to be among the most heavily impacted by climate change. We identify the main challenges associated with compiling global databases – limited data availability, dissimilar sample collection and analysis methodology, and reporting ambiguity – and provide recommended solutions. By addressing these challenges and consolidating data from various sources into one standardized, openly available, high quality, and trans-boundary database, SWatCh allows users to conduct powerful and robust statistical analyses of global surface water chemistry.</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.