An Examination of Wing Beat Frequency as a Species Signature for North American Birds At Risk from Wind Energy Development

Standard approaches for assessing risk to birds from, and evaluating mitigation effectiveness for, wind energy development utilize human observers. Reliance on human observers can be expensive, can pose risk to health and... [ view full abstract ]

Standard approaches for assessing risk to birds from, and evaluating mitigation effectiveness for, wind energy development utilize human observers. Reliance on human observers can be expensive, can pose risk to health and safety, or may simply be impractical. In order to determine if remote detection and identification of birds can address these shortcomings, we explored the use of wing beat frequency to classify birds to species within three geographical groups of North American birds potentially at risk from both offshore and land-based wind energy development. We wanted to determine the degree of specificity to which one could classify birds based on wing beat frequency alone. The first species group selected was from pelagic birds of the Pacific Outer Continental Shelf; the second group was from the Northeast Atlantic Outer Continental Shelf; and the third was from large land birds from the Intermountain West. To calculate wing beat frequencies we collected allometric information from published sources, measured wing areas from digital bird wing photographs, and worked to simplify a published wing beat frequency model. Because wing areas derived from digital photos were comparable to published values we were able to estimate wing beat frequencies for 53 North American species, most of which were previously unpublished. The wing beat frequencies that we modeled were comparable to the few published values available, which supported previously published modeling efforts. No single species exhibited a wing beat frequency mutually exclusive of all others within its geographical group, but species could be reliably classified into small subgroups based on wing beat frequency alone. Coupling wing beat frequency with additional information such as range, habitat preference, seasonality, expected frequency of occurrence, and possibly additional behavior, may enable classification of birds to species level, thus improving the assessment of risk and evaluation of mitigation actions at wind energy sites using remote sensing.