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NCCOS Assessment: Predictive Mapping of Seabirds, Pinnipeds and Cetaceans off the Pacific Coast of Washington from 1995-07-21 to 2015-12-08 (NCEI Accession 0148762)
This data collection comprises seasonal distribution maps and model outputs of selected seabird, pinniped and cetacean species off the Pacific coast of Washington. The maps were developed by predicting relative density using associative models linking at-sea species observations with environmental covariates. Seabird, pinniped and cetacean observations were compiled from federal, state and NGO monitoring programs with data between 1995 and 2014. Environmental covariates were processed from long-term archival satellite, oceanographic and hydrographic databases. Selected species include: Marbled Murrelet (Brachyramphus marmoratus), Rhinoceros Auklet (Cerorhinca monocerata), Tufted Puffin (Fratercula cirrhata), Common Murre (Uria aalge), Black-footed Albatross (Phoebastria nigripes), Northern Fulmar (Fulmarus glacialis), Pink-footed Shearwater (Puffinus creatopus), Sooty Shearwater (Puffinus griseus), Steller sea lion (Eumetopias jubatus), harbor seal (Phoca vitulina), humpback whale (Megaptera novaeangliae), gray whale (Eschrichtius robustus), harbor porpoise (Phocoena phocoena) and Dall’s porpoise (Phocoenoides dalli). Summer season (April to October) predictions were developed for all species. In addition, winter season (November to March) predictions were developed for Rhinoceros Auklet, Common Murre and Black-footed Albatross. The collection includes multiple geospatial model outputs for each species and season combination. Data are grouped into seabird, pinniped and cetacean datasets, and each dataset includes its own data documentation record.
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NCCOS Mapping: Merged Bathymetry Data in the Channel Islands National Marine Sanctuary for Benthic Habitat Mapping from 1998 to 2022 (NCEI Accession 0304093)
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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.
Modeled prevalence of seabirds and relative abundance of cetaceans in the Northwest Atlantic Ocean from 1980-04-01 to 1988-10-01 (NCEI Accession 0130025)
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This data set is a compilation of modeled seabird prevalence predictions for a selection of species including Razorbill (Alca torda), Greater Shearwater (Puffinus gravis), Wilson’s Storm-petrel (Oceanites oceanicus), Northern Gannet (Morus bassanus), and all auks (Alcidae), and relative abundance of cetaceans including humpback whale (megaptera novaeangliae), right whale (Eubalaena glacialis), sei whale (Balaenoptera borealis), and fin whale (Balaenoptera musculus). These data were generated to improve the Stellwagen Bank National Marine Sanctuary management plan review and coastal zone management decisions in the Gulf of Maine and surrounding area. These geospatial data sets are part of a large compilation of data provided in the referenced NCCOS (2006) technical memorandum.
NCCOS Assessment: Modeling At-Sea Density of Marine Birds to Support Atlantic Marine Renewable Energy Planning from 1978-2016 (NCEI Accession 0176682)
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This dataset provides seasonal spatial rasters of median predicted long-term (1978-2016) relative density of 47 marine bird species throughout the US Atlantic Outer Continental Shelf (OCS) and adjacent waters at a 2-km spatial resolution. Three indications of the uncertainty associated with the model predictions are also provided: 1) seasonal spatial layers indicating areas with no survey effort, 2) seasonal spatial rasters of the precision of predicted relative density of each species characterized as its coefficient of variation (CV), and 3) seasonal spatial rasters of the precision of predicted relative density of each species characterized as its 90% confidence interval. Predicted relative density should always be considered in conjunction with these three indications of uncertainty. Suggested symbology class breaks and labels for mapping predicted relative density and its CV are also included. Finally, this dataset also includes spatial rasters of environmental predictor variables that were used in the predictive modeling.
NCCOS Assessment: U.S. West Coast Cross-Shelf Habitat Suitability Modeling of Deep-Sea Corals and Sponges, 2016-10-01 to 2020-09-30 (NCEI Accession 0276883)
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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.
NCCOS Assessment: Southeastern U.S. Predictive Modeling of Deep-Sea Corals and Hardbottom Habitats, 2016-10-01 to 2021-09-30 (NCEI Accession 0282806)
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This data collection contains geospatial data from models predicting the spatial distributions of deep-sea corals (DSCs) and hardbottom habitats offshore of the southeastern U.S. It includes a database (.csv text file) containing records of occurrence (presence-absence) for DSCs with associated measures of sampling effort and bottom type from 20 datasets comprised of data from visual field surveys conducted with underwater vehicles. It also includes raster datasets at 100 x 100 m spatial resolution depicting the median and coefficient variation of the predicted occurrence (occupancy probability) for 24 taxa of DSCs (23 genera, 1 family) and hardbottom habitats. Additional raster datasets depict the median and coefficient of variation of the predicted genus richness for the 23 genera of DSCs. The data collection also includes raster datasets at 100 x 100 m spatial resolution depicting each of the 62 spatial environmental predictors considered for fitting the models. For more information, see Poti et al. (2022). The project to compile this model took place between 2016 and 2021, however the model input data range from 2001-2018 and the model output covers the same timeframe.
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