Abstract

The Northeast Regional Ocean Council and the Mid-Atlantic Regional Council on the Ocean (MARCO) collaborated to fund the development of maps of marine life to support ocean planning and management. Researchers at several institutions who work collaboratively as the Marine-life Data and Analysis Team (MDAT) assembled a collection of new maps that represents one of the largest known efforts globally to assemble and disseminate spatial data for multiple species and taxa of marine life. As part of this effort, NOAA National Centers for Coastal Ocean Science developed the maps of marine bird relative density and distribution for the entire Atlantic coast. The methods used to produce the bird maps are published in a Bureau of Ocean Energy Management Office of Environmental Studies Program report.

Avian individual species products

The individual species maps represent the results of predictive modeling applied to data from the 21 April 2017 version of the United States Fish and Wildlife Service (USFWS) Northwest Atlantic Seabird Catalog and the Canadian Wildlife Service (Environment and Climate Change Canada) Eastern Canada Seabirds at Sea database. The modeling framework enabled predictions beginning 1-2km offshore and extending to the US EEZ boundary along the entire US Atlantic coast. As a result, model predictions are not available for nearshore (0-2km) areas, embayments, or estuaries, such as Long Island. See the full Technical Report for a table of surveys that were incorporated in the models, and a table of environmental covariates used in the modeling process.

Hatched areas indicate model predictions in an area of no survey effort and should be interpreted cautiously.

Avian Relative Abundance probabilty model results are the long-term average relative abundance of individuals per strip transect segment. Source data used to create the models are from 1978 through 2016. Model resolution is 2km x 2km grid cells, and models were generated with an original extent of approximately the entire US east coast EEZ. Model results in areas with hatched marking are predictions that occur in areas with no survey effort. It is important to recognize that the model predictions do not represent absolute abundance, rather they are indices of abundance. Avian relative abundance predictive maps may inform users in answering the question “relative to other areas, how many more of species X are there likely to be in this area?” Please refer to the full Technical Report for more details.

For seasonal models, seasons are defined as:

  • Winter: December 1 to February 28/29
  • Spring: March 1 to May 31
  • Summer: June 1 to August 31
  • Fall: September 1 to November 30

Characterizations of model uncertainty

90% Confidence Interval Range - From model fit bootstrap procedure. Measure of uncertainty in model predictions originating from observation error, model structural uncertainty, and variability in the occurrence and abundance of birds at a given location over time that is not captured by the long-term average.

Coefficient of Variation - From model fit bootstrap procedure. The CV is a measure of model uncertainty representing the standard deviation of predictions as a proportion of the mean prediction. The magnitude of the CV is less affected by the mean prediction than is the 90% confidence interval range, so it better reflects relative uncertainty across the study area and between models. Values greater than 1, i.e. where the standard error is greater than the density estimate, indicate substantial uncertainty. When high CVs occur where the density estimate is very low, as is often the case, there is little cause for concern. But when high CVs occur where the density estimate is high, it suggests the model cannot predict density well there.

More information

Citation

Any use of the data should be accompanied by the following citations:

Winship A.J., B.P. Kinlan, T.P. White, J.B. Leirness, and J. Christensen. 2018. Modeling At-Sea Density of Marine Birds to Support Atlantic Marine Renewable Energy Planning: Final Report. OCS Study BOEM 2018-010. Sterling, VA. 67 pp. Available online: https://coastalscience.noaa.gov/data_reports/modeling-at-sea-density-of-marine-birds-to-support-atlantic-marine-renewable-energy-planning-final-report/

Curtice C., Cleary J., Shumchenia E., Halpin P.N. 2018. Marine-life Data and Analysis Team (MDAT) technical report on the methods and development of marine-life data to support regional ocean planning and management. Prepared on behalf of the Marine-life Data and Analysis Team (MDAT). Accessed at: http://seamap.env.duke.edu/models/MDAT/MDAT-Technical-Report.pdf

Acknowledgements

NOAA National Centers for Coastal Ocean Science. This study was funded in part by the U.S. Department of the Interior, Bureau of Ocean Energy Management through Interagency Agreement M13PG00005 with the U.S. Department of Commerce, National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), National Centers for Coastal Ocean Science (NCCOS). This product represents results of predictive modelling applied to data from the 'Northwest Atlantic Seabird Catalog' database maintained by USFWS and the ‘Eastern Canada Seabirds at Sea’ database maintained by the Canadian Wildlife Service, Environment and Climate Change Canada. For more information, please contact Arliss Winship (NCCOS Biogeography Branch, arliss.winship@noaa.gov).