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Comparing local and regional density models for marine birds in the Gulf of Maine.


Authors

MEGAN C. FERGUSON1*, EVAN M. ADAMS1, MARY E. MCELROY1, IAIN J. STENHOUSE1, ANDREW T. GILBERT1, ARLISS J. WINSHIP2, & KATHRYN A. WILLIAMS1
1Biodiversity Research Institute, Portland, Maine 04103, United States (*megan.ferguson@briwildlife.org)
2CSS Inc., under contract to NOAA National Centers for Coastal and Ocean Science (NCCOS), Silver Spring, Maryland, 20910, United States

Citation

Ferguson, M. C., Adams, E. M., McElroy, M. E., Stenhouse, I. J., Gilbert, A. T., Winship, A. J., & Williams, K. A. (2026). Comparing local and regional density models for marine birds in the Gulf of Maine. Marine Ornithology, 54(2), 241-258.
http://doi.org/10.5038/2074-1235.54.2.1703

Received 10 October 2025, accepted 09 March 2026

Date Published: 2026/10/15
Date Online: 2026/09/20

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Key words: density models, digital aerial survey, marine birds, offshore wind, risk assessment, spatial cross-correlation, seabird

Abstract

The Gulf of Maine has extensive potential for floating offshore wind energy development. However, to assess potential impacts, substantial spatiotemporal gaps exist in offshore wildlife data from standardized observational surveys in the region. Such data can support distribution and density modeling to inform marine spatial planning. In an effort to reduce these gaps, we modeled seasonal marine bird densities based on data from four digital aerial surveys conducted in 2023-2024 across a 6,700 km2 area of the Gulf. We also compared these local models to existing regional density models for marine birds using spatial cross-correlation and center-of-gravity analyses to assess potential mismatches in predictions. Local and regional models were weakly spatially correlated for most taxon/season combinations (global spatial cross-correlation indices with negative exponential decay ranged from -0.21 to 0.23, mean = 0.07, median = 0.11), and local and regional centers of gravity did not consistently align (mean absolute difference = 11.7 km). We discuss several reasons for discrepancies between local and regional predictions of marine bird densities, including underlying differences in model structure and differences in spatiotemporal resolution of source data. Given the limitations of both models, we were unable to determine which model can best inform offshore planning and risk assessments. Further observational surveys are needed to refine models so they may be used reliably for management and conservation, particularly in winter, which is the least surveyed season in the Gulf. Future observational survey efforts should follow best available guidance for survey design to support effective consideration of marine birds in offshore planning and risk assessments.

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