Estimates of the abundance and habitat area for two species of burrowing shrimps in Yaquina Bay estuary, Oregon. This dataset is associated with the following publication: Dumbauld, B., L. McCoy, T. DeWitt , and J. Chapman. Estimating long-term trends in populations of two ecosystem engineering burrowing shrimps in Pacific Northwest (USA) estuaries. HYDROBIOLOGIA. Springer, New York, NY, USA, 848(5): 993-1013, (2021).

Using existing habitat datasets and natural-history traits, we created a Habitat Suitability Index (HSI) model in ArcGIS to determine the distribution of suitable habitat for harvested clams in Yaquina Bay. Existing habitat datasets were used to interpolate value estimates throughout the bay for the four input habitat variables used in the model (sediment % fines, bathymetry, salinity, and burrowing shrimp presence). Natural history traits (derived from literature) were then used to assign binary suitability values to each habitat variable for each species. The suitability sum of these variable layers then produced an overall HSI value of 0-4 (low-high). To validate this model, we used existing bivalve (presence/absence) data to calculate presence probabilities. Included in this dataset are these bivalve data, along with the habitat estimates and suitability values produced by our model. This dataset is associated with the following publication: Lewis, N., E. Fox, and T. DeWitt. Estimating the distribution of harvested estuarine bivalves with natural-history-based habitat suitability models... ESTUARINE, COASTAL AND SHELF SCIENCE. Elsevier Science Ltd, New York, NY, USA, 219: 453-472, (2019).

Using existing habitat datasets and natural-history traits, we created a Habitat Suitability Index (HSI) model in ArcGIS to determine the distribution of suitable habitat for harvested clams in Yaquina Bay. Existing habitat datasets were used to interpolate value estimates throughout the bay for the four input habitat variables used in the model (sediment % fines, bathymetry, salinity, and burrowing shrimp presence). Natural history traits (derived from literature) were then used to assign binary suitability values to each habitat variable for each species. The suitability sum of these variable layers then produced an overall HSI value of 0-4 (low-high). To validate this model, we used existing bivalve (presence/absence) data to calculate presence probabilities. Included in this dataset are these bivalve data, along with the habitat estimates and suitability values produced by our model. This dataset is associated with the following publication: Lewis, N., E. Fox, and T. DeWitt. Estimating the distribution of harvested estuarine bivalves with natural-history-based habitat suitability models... ESTUARINE, COASTAL AND SHELF SCIENCE. Elsevier Science Ltd, New York, NY, USA, 219: 453-472, (2019).

This data set contains Penaeid shrimp counts and measurements. Water parameter measurements such as salinity, dissolved oxygen, temperature, and turbidity were also measured. General habitat notes as well as vegetation type are also available.

These data represent oyster reefs in Georgia's coastal waterways, extending from Chatham County south to Glynn County. A pilot project for certain coastal regions was completed in 2013, with the remaining project areas finished in 2015. This mapping project was conducted under contract to the Georgia Department of Natural Resources with the goal of inventorying oyster reefs in Georgia's coastal waterways. Oyster reef extent polygons were created through heads-up digitization using 4-band, 6-inch resolution DMC digital aerial imagery as the source. This imagery was collected between November 2012 and February 2013. The minimum mapping unit is 5 square meters, though discretion was used to collect features smaller than this. Partners: Georgia Department of Natural Resources

These data represent benthic habitats in a coastal area near Green Bay, Wisconsin. The area extends approximately 91 kilometers between Suamico, Wisconsin, and Menominee, Michigan, and covers approximately 64 square kilometers. Benthic biota and substrates were classified using the Coastal and Marine Ecological Classification Standard (CMECS). The classification process involved object-based image segmentation of lidar bathymetry, cross-referencing geospatial data with the CMECS hierarchy, and expert interpretation. Biotic and substrate components were classified to the CMECS group or community level, with additional detail provided by co-occurring elements and modifiers. Mapping confidence was higher in areas with Digital Elevation Models (DEMs), as geomorphometric details from digital elevation models could often be directly linked to substrate types through professional geologic judgment. In areas lacking DEM coverage, object-based segmentation was not possible, leading to lower confidence and requiring manual interpretation of substrate and biotic data from available source and ancillary data. In some instances, with support from geologic judgment or imagery, CMECS Substrate Component classifications at DEM boundaries were linearly extrapolated across gaps in DEM coverage. The layers available within the data download include biotic, confidence, and substrate. Partners: Coastal States Organization

This dataset contains juvenile Dungeness crab (Cancer magister) abundance data and associated habitat data from three estuaries in Oregon (Tillamook, Yaquina, and Alsea bays). These data were collected by EPA surveys in 2010-2011. Additionally, this dataset includes areal data on National Wetlands Inventory (NWI) habitat classes within our study areas. This dataset is associated with the following publication: Lewis, N., D. Young, C. Folger, and T. DeWitt. Assessing the Relative Importance of Estuarine Nursery Habitats – a Dungeness Crab (Cancer magister) Case Study. Estuaries and Coasts. Estuarine Research Federation, Port Republic, MD, USA, s12237-020-00821-1, (2020).

Study compared densities of nekton, benthos, and seagrass among newly deposited dredged sediments and nearby and distant natural seagrass sites over a three year period. Recovery of seagrass and nekton communities from dredged material placement was predicted to take from 4-8 years.

Sampled marshes and ponds along two transects within the intermediate and brackish marsh zones of Breton Sound, Louisiana, from May 7-11, 2001. Sampling followed several planned releases of freshwater from the Caernarvon diversion structure during the winter of 2000 and spring of 2001 as part of a larger study to examine the ecological effect of pulsed freshwater releases on the ecosystem.