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NCCOS Assessment: Modeling At-Sea Density of Marine Birds to Support Atlantic Marine Renewable Energy Planning from 1978-2016 (NCEI Accession 0176682)

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.

About this Dataset

Updated: 2024-02-22
Metadata Last Updated: 2025-11-19T16:05:31.306Z
Date Created: N/A
Data Provided by:
Dataset Owner: N/A

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Title NCCOS Assessment: Modeling At-Sea Density of Marine Birds to Support Atlantic Marine Renewable Energy Planning from 1978-2016 (NCEI Accession 0176682)
Description 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.
Modified 2025-11-19T16:05:31.306Z
Publisher Name N/A
Contact N/A
Keywords 0176682 , BIRDS , model output , NOAA National Centers for Coastal Ocean Science , NOAA National Centers for Coastal Ocean Science , Gulf of Maine , Mid-Atlantic Bight , North Atlantic Ocean , oceanography , DOC/NOAA/NOS/NCCOS > National Centers for Coastal Ocean Science, National Ocean Service, NOAA, U.S. Department of Commerce , BOEM Project: Integrative Statistical Modeling And Predictive Mapping Of Seabird Distribution And Abundance On The Atlantic Outer Continental Shelf , NCCOS Project: Modeling and mapping marine bird distributions on the U.S. Atlantic Outer Continental Shelf to support offshore renewable energy planning , EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > ANIMALS/VERTEBRATES > BIRDS , Marine Spatial Ecology > Ecological and Biogeographic Assessments , Derived Data Product , Geospatial , Model , Models/Analysis > Data Analysis > Environmental Modeling , Relative Density , Continent > North America > Canada , Continent > North America > United States Of America > Connecticut , Continent > North America > United States Of America > Delaware , Continent > North America > United States Of America > Florida , Continent > North America > United States Of America > Georgia , Continent > North America > United States Of America > Maine , Continent > North America > United States Of America > Maryland , Continent > North America > United States Of America > Massachusetts , Continent > North America > United States Of America > New Hampshire , Continent > North America > United States Of America > New Jersey , Continent > North America > United States Of America > New York , Continent > North America > United States Of America > North Carolina , Continent > North America > United States Of America > Rhode Island , Continent > North America > United States Of America > South Carolina , Continent > North America > United States Of America > Virginia , OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC OCEAN , OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC OCEAN > GULF OF MAINE , Ocean > Atlantic Ocean , Region > Atlantic Ocean , Region > International , U.S. States and Territories > Connecticut , U.S. States and Territories > Delaware , U.S. States and Territories > Florida , U.S. States and Territories > Georgia , U.S. States and Territories > Maine , U.S. States and Territories > Maryland , U.S. States and Territories > Massachusetts , U.S. States and Territories > New Hampshire , U.S. States and Territories > New Jersey , U.S. States and Territories > New York , U.S. States and Territories > North Carolina , U.S. States and Territories > Rhode Island , U.S. States and Territories > South Carolina , U.S. States and Territories > Virginia , Atlantic Ocean , Continental Shelf , South Atlantic Bight , Earth Science Services > Models > Dynamic Vegetation/Ecosystem Models , RM4YYU , environment , oceans , biota
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