期刊
JOURNAL OF APPLIED ECOLOGY
卷 58, 期 10, 页码 2029-2039出版社
WILEY
DOI: 10.1111/1365-2664.13971
关键词
bird migration; bird strikes; citizen science; eBird; flight safety; weather surveillance radar; wildlife management
资金
- National Science Foundation [DBI-1661329, ICER-1927743, IIS-1633206, NSF 1927743]
- Horizon 2020 Framework Programme [844360]
- Edward W. Rose Postdoctoral Fellowship
- Academy of Finland [aka 326315]
- Schweizerischer Nationalfonds zur Forderung der Wissenschaftlichen Forschung [SNF 31BD30_184120]
- Belgian Federal Science Policy Office [BelSPO BR/185/A1/GloBAM-BE]
- Leon Levy Foundation
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek [NWO E10008]
The study demonstrates that using radar data and eBird data can accurately predict bird strike events. The research also found that the probability of aircraft collisions with birds is related to the amount of migration captured by weather radar, and the most damaging strikes may occur when bird species are more abundant.
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. Synthesis and applications. By better understanding when and where different bird species occur, airports across the world can predict seasonal periods of collision risks with greater temporal and spatial resolution; such predictions include potential to predict when the most severe and damaging strikes may occur. Our results highlight the power of federating datasets with bird movement and distribution data for developing better and more taxonomically and ecologically tuned models of likelihood of strikes occurring and severity of strikes.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据