Modeling At-Sea Occurrence and Abundance of Marine Birds to Support Atlantic Marine Renewable Energy Planning: Phase 1 Report

Report

Title: Modeling At-Sea Occurrence and Abundance of Marine Birds to Support Atlantic Marine Renewable Energy Planning: Phase 1 Report
Publication Date:
May 01, 2016
Document Number: OCS Study BOEM 2016-039
Pages: 113
Publisher: U.S. Department of the Interior Bureau of Ocean Energy Management (BOEM)
Receptor:

Document Access

Website: External Link
Attachment: Access File
(13 MB)

Citation

Kinlan, B.; Winship, A.; White, T.; Christensen, J. (2016). Modeling At-Sea Occurrence and Abundance of Marine Birds to Support Atlantic Marine Renewable Energy Planning: Phase 1 Report. Report by US Department of Commerce (DOC) and National Oceanic and Atmospheric Administration (NOAA). pp 113.
Abstract: 

This report describes the first phase of a project aimed at producing maps of the spatial distributions of marine bird species in U.S. Atlantic Outer Continental Shelf (OCS) waters that can be used to inform marine spatial planning in the region. Visual sighting survey data from over three decades were analyzed to derive seasonal and annual maps of the spatial distributions of 40 marine bird species in U.S. Atlantic OCS waters from Florida to Maine. Spatial predictive modeling was applied to the survey data to account for spatial and temporal heterogeneity in survey effort, platform, and protocol. Model predictions are presented as seasonal and annual maps of the relative probability of occurrence and relative abundance of study species throughout the U.S. Atlantic OCS. The relative importance of different predictor variables is presented, indicating which variables most influenced the predicted distributions for each species in each season. While the primary objective of this study was not to determine the ecological drivers and mechanisms behind the spatial distributions of marine bird species in the study area, our model results may provide useful hypotheses for future studies aimed more at ecological inference.

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