Up to 1 billion birds die annually in the U.S. from window collisions; most of these casualties represent migratory native species. Because this major mortality source likely contributes to the decline of the North American avifauna, mitigation tools are needed that accurately predict real‐time collision risk, allowing hazards to be minimized before fatalities occur. We assessed the potential use of weather surveillance radar, an emerging tool increasingly used to study and to predict bird migration, as an early warning system to reduce numbers of bird‐window collisions. Based on bird‐window collision monitoring in Oklahoma, USA, we show that radar‐derived migration variables are associated with nightly numbers of collisions. Across the entire night, numbers of collisions increased with higher migration traffic rate (i.e. numbers of birds crossing a fixed line perpendicular to migration direction), and migration variables for specific periods within the night were also related to nightly collisions.
Aircraft collisions with birds span the entire history of human aviation, including fatal collisions during some of the first powered human flights. Much effort has been expended to reduce such collisions, but increased knowledge about bird movements and species occurrence could dramatically improve decision support and proactive measures to reduce them. Migratory movements of birds pose a unique, often overlooked, threat to aviation that is particularly difficult for individual airports to monitor and predict the occurrence of birds vary extensively in space and time at the local scales of airport responses. We use two publicly available datasets, radar data from the US NEXRAD network characterizing migration movements and eBird data collected by citizen scientists to map bird movements and species composition with low human effort expenditures but high temporal and spatial resolution relative to other large‐scale bird survey methods. As a test case, we compare results from weather radar distributions and eBird species composition with detailed bird strike records from three major New York airports. We show that weather radar‐based estimates of migration intensity can accurately predict the probability of bird strikes, with 80% of the variation in bird strikes across the year explained by the average amount of migratory movements captured on weather radar. We also show that eBird‐based estimates of species occurrence can, using species’ body mass and flocking propensity, accurately predict when most damaging strikes occur.
- Award ID(s):
- 1927743
- NSF-PAR ID:
- 10449861
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Journal of Applied Ecology
- Volume:
- 58
- Issue:
- 10
- ISSN:
- 0021-8901
- Page Range / eLocation ID:
- p. 2029-2039
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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