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6 results for “Watershed characteristics”
NSC01 Chemistry and physical characteristics of soils from Konza LTER watersheds with different fire and grazing treatments
Soil chemical and physical characteristics are quantified on selected LTER watersheds adjacent to LTER vegetation sampling plots. Sampling was initiated in 1982, and is repeated every five years. A subset of variables (e.g., pH, Bray extractable P, total C, exchangeable cations) is measured on all sample dates, while additional specific variables (e.g., bulk density, soil texture, CaCO3 content, trace metals, extractable inorganic N) are measured less frequently. Methods for C and N analysis have changed over time. C content of samples from 1982, 1987 and 1997 was derived from Walkley-Black measurements of % soil organic matter (OM) content, using a conversion factor of 1.72 (%C = %OM / 1.72). Soil C content of samples from 1992, 2002 and later were determined by dry combustion and gas chromatography (i.e., Carlo-Erba C/N analyzer). N content of samples prior to 1992 was based on Kjeldahl digeston. N content of samples from 1992 on were determined by dry combustion and gas chromatography (i.e., Carlo-Erba C/N analyzer). Additional details regarding sampling protocols and analytical methods are available in the Konza LTER Methods Manual.
Characteristics of the Marsh-Forest Boundary within Chesapeake Bay Region Coastal Watersheds
Sea level rise is leading to the rapid landward migration of marshes into coastal forests and other terrestrial ecosystems. Although complex biophysical interactions likely govern these ecosystem transitions, projections of sea level driven land conversion commonly rely on a simplified delineation of the marsh-upland boundary based on tidal datums alone. To determine the influence of biophysical drivers on the elevation of the marsh-forest transition, and their implication for land conversion, we examined almost 100,000 high-resolution marsh-forest boundary elevation points, determined independently from tidal datums, alongside 14 environmental variables in the Chesapeake Bay, the largest estuary in the United States.
LAGOS-US LOCUS v1.0: Data module of location, identifiers, and physical characteristics of lakes and their watersheds in the conterminous U.S.
This data package, LAGOS-US LOCUS v1.0, is one of the core data modules of the LAGOS-US platform that provides an extensible research-ready platform to study the 479,950 lakes and reservoirs larger than or equal to 1 ha in the conterminous US (48 states plus the District of Columbia). This data module contains information on the location, identifiers, and physical characteristics of lakes and their watersheds. The characteristics in this module include: variables that can be obtained from GIS data such as location and geometry; variables that can be derived using GIS processing such as lake watersheds and their geometry, lake glaciation history, and lake connectivity; and commonly used identifiers from GIS and other data products useful for linking with LAGOS-US. LOCUS is based on a snapshot of the high-resolution National Hydrography Dataset product available at the initiation of the project that provided the basis for locating, identifying, and characterizing the geometry of all lakes in LAGOS-US. The database design that supports the LAGOS-US research platform was created based on several important design features. Lakes are the fundamental unit of consideration, all lakes in the spatial extent must be represented (above a minimum size) and most information is connected to individual lakes. The design is modular, interoperable (the modules can be used with each other), and extensible (future database modules can be developed and used in the LAGOS-US research platform by others). Users are encouraged to use the other 2 core data modules that are part of the LAGOS-US platform: GEO (which includes geospatial ecological context at multiple spatial and temporal scales for lakes and their watersheds) and LIMNO (in situ lake surface-water physical, chemical, and biological measurements through time) that are each found in their own data packages.
Physical characteristics and GPS data for 21 permanent plots in Coweeta white pine watershed 1 from 2003 to 2004
A GPS receiver was used to acquire UTM coordinates and elevation for each plot center. Aspect and slope were also measured.
Biogeochemical and sediment characteristics of streambanks with and without preferential groundwater discharge in the Farmington River Watershed, CT, USA
Open the record for dataset details and reuse information.
LBA-ECO ND-01 Streamwater and Watershed Characteristics, Rondonia, Brazil: 1998-1999
This data set provides the results of (1) synoptic streamwater sampling and analyses from numerous sites across Rondonia and (2) corresponding watershed characteristics derived from remote sensing and historical/available data sources. Sixty streams, in both forested and non-forested sites, were sampled once during the dry season in August of 1998 and 49 of the same streams were sampled again during the wet season in January-February of 1999. Analyses included sodium (Na), calcium (Ca), magnesium (Mg), potassium (K), silica (Si), chloride (Cl), sulfate, pH, and acid neutralizing capacity. Watershed characteristics, including soil cation content, pH, watershed lithology, area, percent deforested, and urban watershed population density, were derived and calculated from digitized soil maps and available soil profile analyses, digitized topographic maps, land use mosaics from Landsat Thematic Mapper (TM) images, and Brazilian census data. The objective of the study was to determine the relative influence of watershed soil exchangeable cation content, rock type, deforestation, and urban population density on stream concentrations of base cations, dissolved silicon, chloride and sulfate in both the dry and wet seasons in a humid tropical region undergoing regional land use transformation. There are three comma-delimited data files with this data set.
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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.