There is increasing pressure on wind energy facilities to manage or mitigate for wildlife collisions. However, little information exists regarding spatial and temporal variation in collision rates, meaning that mitigation is most often a blanket prescription. To address this knowledge gap, we evaluated variation among turbines and months in an aspect of collision risk—probability of entry by an eagle into a rotor-swept zone (hereafter, “probability of entry”). We examined 10,222 eagle flight paths identified and recorded by an automated bird monitoring system at a wind energy facility in Wyoming, USA. Probabilities of entry per turbine–month combination were 4.03 times greater in some months than others, ranging 0.15 to 0.62. The overall probability of entry for the riskiest turbine (i.e., the one with the greatest probability of entry) was 2.39 times greater than the least-risky turbine. Our methodology describes large variation across turbines and months in the probability of entry. If subsequently combined with information on other sources of variation (i.e., weather, topography), this approach can identify risky versus safe situations for eagles under which cost of management, curtailment prescriptions, and collision risk can be simultaneously minimized.

中文翻译：

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老鹰以每个涡轮机不同的速率进入风力涡轮机的转子扫掠区

风能设施在管理或减轻野生动物碰撞方面的压力越来越大。然而，关于碰撞率的空间和时间变化的信息很少，这意味着缓解通常是一揽子处方。为了解决这一知识差距，我们在碰撞风险方面评估了涡轮机和月份之间的变化——老鹰进入旋翼后掠区的可能性（以下称为“进入的可能性”）。我们在美国怀俄明州的一家风能设施中检查了由自动鸟类监测系统识别和记录的 10,222 条鹰飞行路径。在某些月份中，每个涡轮机月组合的进入概率是其他月份的 4.03 倍，范围为 0.15 至 0.62。风险最高的涡轮机（即进入概率最大的涡轮机）进入的总概率为 2。比风险最低的涡轮机高 39 倍。我们的方法描述了进入概率在涡轮机和月份之间的巨大变化。如果随后结合其他变化源（即天气、地形）的信息，这种方法可以识别鹰的风险与安全情况，在这种情况下，管理成本、缩减处方和碰撞风险可以同时最小化。