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These data were compiled for investigating the relationship between acoustic backscattering by riverbeds composed of various riverbed substrates (bed sediment), and for developing and testing a probabilistic model for substrate classification based on high-frequency multibeam acoustic backscatter. The model is described in Buscombe et al. (2017). The data consist of various quantities on coincident grids, from various sites along the Colorado River in Grand Canyon, including water depth, bed roughness, the area (or footprint) of the acoustic beam, unfiltered and filtered backscatter magnitude, sediment classification (for each location, 1 of 5 sediment classes in a categorical scheme), and the probabilities for...
In December 2009, a workshop sponsored by the US Geological Survey and the US Environmental Protection Agency was held to identify on-going sea level rise (SLR) modeling efforts, data gaps, and information needs for management decisions about current and future mitigation and restoration efforts in Oregon estuaries. The workshop brought together 46 non-governmental organizations, federal scientists, state land managers, and SLR modelers and has inspired collaborations for data, knowledge, and technology exchange. A second SLR workshop was scheduled for February 1 and 2, 2011 in Newport, OR to continue to build upon the collaborative efforts established at the first workshop.
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This is a GIS data layer representing submerged aquatic vegetation (SAV) of the Barnegat Bay - Little Egg Harbor estuary, 2009, developed by classifying high resolution airborne digital camera imagery. Included are the submerged aquatic vegetation densities mapped into three classes throughout the study area and their respective area and perimeter for each polygon. The three classes of SAV are: 1) Dense (80% - 100% cover), 2) Moderate (40% - 80% cover), and 3) Sparse (10% - 40% cover). For full documentation, please refer to the technical report, 'Assessment of Seagrass Status in the Barnegat Bay - Little Egg Harbor Estuary System: 2003 and 2009 (Rutgers University, Lathrop and Haag, 2010), which is listed in the...
The “Sea‚ÄźLevel Affecting Marshes Model” (SLAMM) is a moderate resolution model used to predict the effects of sea level rise on marsh habitats (Craft et al. 2009). SLAMM has been used extensively on both the west coast (e.g., Glick et al., 2007) and east coast (e.g., Geselbracht et al., 2011) of the United States to evaluate potential changes in the distribution and extent of tidal marsh habitats. However, a limitation of the current version of SLAMM, (Version 6.2) is that it lacks the ability to model distribution changes in seagrass habitat resulting from sea level rise. Because of the ecological importance of SAV habitats, the US Environmental Protection Agency, US Geological Survey, and US Department of Agriculture...
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This dataset records Cladophora and associated submerged aquatic vegetation (SAV) biomass collected approximately monthly during the growing season starting in 2018 at stations located along the U.S. shoreline of Lakes Michigan, Huron, Erie, and Ontario. It also records a variety of supporting data collected at Cladophora measurement stations. These supporting data include: - seasonal time series of light, water currents, wave action, temperature, specific conductivity, turbidity, pH, phycocyanin, chlorophyll, and dissolved oxygen from moored sensors at a subset of stations; - measurements of Secchi disk depth and water chemistry; - water column profiles of temperature, specific conductivity, turbidity, pH, phycocyanin,...
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This dataset records Cladophora and associated submerged aquatic vegetation (SAV) biomass collected approximately monthly during the growing season of 2018 at stations located along the U.S. shoreline of Lakes Michigan, Huron, Erie, and Ontario. It also records a variety of supporting data collected at Cladophora measurement stations. These supporting data include: - seasonal time series of light, currents, wave action, temperature, specific conductivity, turbidity, pH, phycocyanin, chlorophyll, and dissolved oxygen from moored sensors at a subset of stations; - measurements of Secchi disk depth and water chemistry; - water column profiles of temperature, specific conductivity, turbidity, pH, phycocyanin, chlorophyll,...
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Seagrass habitats for the Gulf of Mexico. Seagrasses provide nursery areas, spawning and foraging habitats for fish, fowl, and reptiles.
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This projects primary goal was to provide data on biomass of potential seed resources located within shallow water coastal areas within fresh to saline coastal waters of the northern Gulf of Mexico. The data set provides biomass of seeds, by species or lowest practical taxon from 2013, 2014 and 2015 across 384 randomly selected sites located in shallow water coastal areas. The data were collected between June and September of each year. This data set can be merged with a dataset which reports submerged aquatic vegetation and environmental data collected at the same time (La Peyre et al. 2017; https://doi.org/10.5066/F7Z899WV). This project was co-funded by the Gulf Coast Prairie and the Gulf Coastal Plains and Ozarks...
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This projects primary goal was to provide data on biomass of potential seed resources located within shallow water coastal areas within fresh to saline coastal waters of the northern Gulf of Mexico. The data set provides biomass of seeds, by species or lowest practical taxon from 2013, 2014 and 2015 across 384 randomly selected sites located in shallow water coastal areas. The data were collected between June and September of each year. This data set can be merged with a dataset which reports submerged aquatic vegetation and environmental data collected at the same time (La Peyre et al. 2017; https://doi.org/10.5066/F7GH9G44). This project was co-funded by the South Central Climate Adaptation Science Center and...
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This dataset records Cladophora and associated submerged aquatic vegetation (SAV) biomass collected approximately monthly during the growing season of 2019 at stations located along the U.S. shoreline of Lakes Michigan, Huron, Erie, and Ontario. It also records a variety of supporting data collected at Cladophora measurement stations. These supporting data include: - seasonal time series of light, currents, wave action, temperature, specific conductivity, turbidity, pH, phycocyanin, chlorophyll, and dissolved oxygen from moored sensors at a subset of stations; - measurements of Secchi disk depth and water chemistry; - water column profiles of temperature, specific conductivity, turbidity, pH, phycocyanin, chlorophyll,...


    map background search result map search result map Submerged aquatic vegetation (SAV) CRSSA image classification of the Barnegat Bay - Little Egg Harbor estuary, New Jersey: 2009 Submerged Aquatic Vegetation - Gulf of Mexico Seed biomass from shallow coastal water areas from Texas through Alabama, 2013-2015 Seed biomass from shallow coastal water areas from Texas through Alabama, 2013-2015 Acoustic backscatter - Data and Python Code Cladophora biomass and supporting data collected in the Great Lakes, 2019 Cladophora biomass and supporting data collected in the Great Lakes, 2018 (ver. 1.1, September 2020) Cladophora biomass and supporting data collected in the Great Lakes Submerged aquatic vegetation (SAV) CRSSA image classification of the Barnegat Bay - Little Egg Harbor estuary, New Jersey: 2009 Acoustic backscatter - Data and Python Code Seed biomass from shallow coastal water areas from Texas through Alabama, 2013-2015 Seed biomass from shallow coastal water areas from Texas through Alabama, 2013-2015 Cladophora biomass and supporting data collected in the Great Lakes, 2018 (ver. 1.1, September 2020) Cladophora biomass and supporting data collected in the Great Lakes, 2019 Cladophora biomass and supporting data collected in the Great Lakes Submerged Aquatic Vegetation - Gulf of Mexico