Abstract
Offshore wind facilities during both construction and operation may impact bird populations directly through mortality from collisions and indirectly through displacement that affects population fitness. We present data on population size, conservation importance, and ecological traits of bird species found in the vicinity of the Atlantic Outer Continental Shelf and a method of ranking their relative sensitivity to the impacts of collision and displacement. Based on both our literature synthesis and the collision sensitivity rank, avoidance behavior and flight height appear to be key factors that influence vulnerability to collision. More data are needed for both of these behavioral traits. The collision sensitivity rank identified that populations of gulls, phalaropes, cormorants, and jaegers are of particularly high concern on the Atlantic Outer Continental Shelf. Available literature and the displacement sensitivity rank both suggest that avoidance of wind facilities and habitat flexibility appear to be key behavioral traits causing potential loss of population fitness through displacement. The displacement sensitivity rank identified that populations of sea ducks, loons, and some alcid species are most vulnerable. The impacts of displacement on populations will be less immediate and less obvious than those of mortality from collision; therefore, we hope that the approach developed here for the Bureau of Ocean Energy Management will help prioritize monitoring programs of vulnerable species before, during, and after construction and assist with informing siting decisions for offshore wind facilities. It would be possible to refine this model to fit specific needs by focusing on certain species or locations. Our research also uncovered data gaps and conflicting data among sources for most of the metrics we analyzed in our study. Specifically, more data are urgently needed on species-specific flight altitude and species-specific avoidance behavior, and we recommend that studies conducted by the Bureau of Ocean Energy Management target these two areas of knowledge gaps using standardized and cross-study comparable methodologies. Given the data gaps and associated levels of uncertainty present within the available data, our results should be interpreted while considering the levels of variation and uncertainty present within currently available data.