Modeling at-sea density of marine birds to support renewable energy planning on the Pacific outer continental shelf of the contiguous United States
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Abstract
This report describes the at-sea spatial distributions of marine birds in Pacific OCS waters off the contiguous U.S. (Figure 1.1) to inform marine spatial planning in the region. The goal was to estimate long-term average spatial distributions for marine bird species using all available science-quality transect survey data and numerous bathymetric, oceanographic, and atmospheric predictor variables. We developed seasonal habitat-based spatial models of the at-sea distribution for 33 individual species and 13 taxonomic groups of marine birds throughout the study region. A statistical modeling framework was used to estimate numerical relationships between bird sighting data (i.e., standardized counts) and a range of temporal (e.g., Pacific Decadal Oscillation [PDO] index), spatially static (e.g., depth), and spatially dynamic (e.g., sea surface chlorophyll-a concentration) environmental variables. The estimated relationships were then used to predict spatially explicit long-term average density (individuals per km2) throughout the study area for each species/group in each of four seasons. Bird sighting data came from multiple scientific survey programs and consisted of at-sea counts of birds collected between 1980 and 2017 using boat-based and fixed-wing aerial transect survey methods. Spatial environmental variables were derived from remote sensing satellite data and an ocean dynamics model.
Study Area
Publication type | Report |
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Publication Subtype | Federal Government Series |
Title | Modeling at-sea density of marine birds to support renewable energy planning on the Pacific outer continental shelf of the contiguous United States |
Series title | OCS Study |
Series number | BOEM 2021-014 |
Year Published | 2021 |
Language | English |
Publisher | Bureau of Ocean Energy Management |
Contributing office(s) | Western Ecological Research Center |
Description | xix, 385 p. |
Country | United States |
State | California, Oregon, Washington |
Other Geospatial | Pacific Coast |
Google Analytic Metrics | Metrics page |