Abstract Onshore wind farm development may impact vulnerable large eagles at both individual and population levels and requires appropriate assessment under the EU Bird and Habitat Directives. The present conservation policy (e.g. fixed safety zones around nest sites) improves species conservation but may not prevent habitat loss or reduce collision risk in the best possible way because this policy may not consider habitat-specific effects on eagle behaviour. Here, we develop a method for estimating habitat use and flying time distribution within Golden Eagle (Aquila chrysaetos) home ranges. Location data retrieved with GPS-transmitters (Global Positioning system) in Finland indicated that these large raptors used vast areas (mean 297 km2, 95% Minimum Convex Polygon), reaching up to 14 km, but not uniformly around their nests. The best resource selection function models (cross-validation performance 83%) revealed that flying Golden Eagles preferred the vicinity of their nests, steep slopes, and old forests in their home range. They avoided human settlements and neighboring territories. GPS data indicated short flying times per day (mean 2.2 h) and about 30% of the flying time within collision risk heights (50–200 m). Together with information on habitat selection, flying times can be used for predicting airspace use of birds and in assessing the collision risk at particular wind farm locations. Thus, our method can be applied in planning wind farm locations that enable a safer co-existence of large territorial birds and wind power plants in the same landscape.

中文翻译：

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模拟金雕栖息地选择和其家庭范围内的飞行活动，以实现更安全的风电场规划

摘要 陆上风电场开发可能会在个体和种群层面影响脆弱的大鹰，需要根据欧盟鸟类和栖息地指令进行适当评估。目前的保护政策（例如在巢址周围固定安全区）改善了物种保护，但可能无法以最佳方式防止栖息地丧失或减少碰撞风险，因为该政策可能没有考虑栖息地特定对鹰行为的影响。在这里，我们开发了一种估计金鹰（Aquila chrysaetos）家庭范围内栖息地使用和飞行时间分布的方法。在芬兰使用 GPS 发射器（全球定位系统）检索到的位置数据表明，这些大型猛禽使用了广阔的区域（平均 297 平方公里，95% 最小凸多边形），可达 14 公里，但它们的巢穴周围并不均匀。最佳资源选择函数模型（交叉验证性能 83%）显示，飞翔的金鹰更喜欢栖息地附近的巢穴、陡坡和古老的森林。他们避开人类住区和邻近地区。GPS 数据表明每天的飞行时间很短（平均 2.2 小时），大约 30% 的飞行时间在碰撞风险高度（50-200 m）内。结合栖息地选择信息，飞行时间可用于预测鸟类的空域使用和评估特定风电场位置的碰撞风险。因此，我们的方法可以应用于规划风电场位置，使大型领土鸟类和风力发电厂在同一景观中更安全地共存。