Bird strikes at commercial airports explained by citizen science and weather radar data
Bird strikes at commercial airports explained by citizen science and weather radar data
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DOI：
10.1111/1365-2664.13971
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发表时间：
2021-08-18
影响因子：
5.7
通讯作者：
Farnsworth, Andrew
中科院分区：
文献类型：
--
作者：
Nilsson, Cecilia;La Sorte, Frank A.;Farnsworth, Andrew
飞机与鸟类的碰撞跨越了人类航空的整个历史，包括在一些最早的动力人类飞行中发生的致命碰撞。已经花费了大量的努力来减少这种碰撞，但增加对鸟类运动和物种发生的了解可以极大地改善决策支持和主动减少碰撞的措施。鸟类的迁徙活动对航空构成了一种独特的、往往被忽视的威胁，对于各个机场来说，监测和预测鸟类的发生尤其困难，在机场反应的地方尺度上，在空间和时间上差异很大。我们使用两个公开可用的数据集，来自美国NEXRAD网络的描述迁徙运动的雷达数据和公民科学家收集的eBird数据来绘制鸟类运动和物种组成的地图，与其他大规模鸟类调查方法相比，这种方法具有较低的人力成本和较高的时间和空间分辨率。作为测试案例，我们将天气雷达分布和eBird物种组成的结果与纽约三个主要机场的详细鸟击记录进行了比较。我们表明，基于天气雷达的迁徙强度估计可以准确地预测鸟类撞击的可能性，全年鸟类撞击的变化有80%是由天气雷达捕捉到的平均迁徙运动量来解释的。我们还表明，基于eBird的物种发生估计可以利用物种的体重和成群倾向，准确地预测最具破坏性的打击发生的时间。合成与应用。通过更好地了解不同鸟类发生的时间和地点，世界各地的机场可以以更高的时间和空间分辨率预测碰撞风险的季节性时段；这种预测包括预测何时可能发生最严重和最具破坏性的袭击。我们的结果突出了将数据集与鸟类运动和分布数据联合起来，以开发更好的、更分类和生态上调整的袭击发生可能性和袭击严重程度的模型的力量。
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.