This data collection contains geospatial data from models predicting the spatial distributions of deep-sea corals and sponges offshore of the continental U.S. West Coast to 1200 m depth. It includes raster datasets at 200 x 200 m spatial resolution depicting the mean of the predicted relative habitat suitability, the coefficient of variation of the predicted relative habitat suitability, the classified mean relative habitat suitability, and the ‘robust high’ habitat suitability prediction for each of 31 taxa of deep-sea corals and 15 taxa of sponges and raster datasets at 200 x 200 m spatial resolution depicting the number of taxa of deep-sea corals associated with hard substrate that have ‘high’ habitat suitability or ‘robust high’ habitat suitability at each grid cell. The data collection also includes raster datasets at 200 x 200 m spatial resolution depicting each of the 66 spatial environmental predictor variables considered for fitting the models.

This dataset uses rugosity measurements collected during the California Seafloor Mapping Project (CSMP) as a proxy to classify benthic habitat as either Hard or Soft. While originally developed for MPA planning and MLPA implementation, this dataset provides a comprehensive estimate of benthic habitat for California waters. Two versions of this data are available:Statewide mosaic raster of all data resampled at 10m (shown here). Vector format for visualization and analysis. Substrate classifications are binned into depth ranges and 1 degree latitude/longitude grids.

We created merged bathymetry surfaces segmented in GeoTiff format by resolution and depth within the Channel Islands National Marine Sanctuary (CINMS) from more than 20 multibeam mapping surveys. These bathymetry data were collected between 1998 and 2022 by National Oceanic and Atmospheric Administration (NOAA), United States Geological Survey (USGS), Monterey Bay Aquarium Research Institute (MBARI) California State University, Monterey Bay (CSUMB) and Ocean Exploration Trust (OET). Bathymetry data collected by institutions outside of NOAA are reference to overlapping NOAA hydrographic surveys using an average depth difference correction. The merged bathymetric surface resolutions varied by depth from 2x2m in <40m, 4x4m in 36 to 80 m, 8x8m in 72 to 160m, 16x16m in 144 to 320m and to 24x24m in >300m. They can be used to create high-resolution, nearly continuous coverage benthic habitat maps within the CINMS.

This data collection contains outputs from spatial predictive models of habitat suitability for the black coral Leiopathes glaberrima in the U.S. Gulf of Mexico. The models were derived from records of Leiopathes glaberrima occurrence and environmental and oceanographic variables describing conditions that may influence the distribution of deep-sea corals, including measures of depth, steepness, and complexity of the seafloor, composition of sediments on the seafloor, and ocean productivity.