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Using network analysis to identify indicator species and reduce collision fatalities at wind farms
Biological Conservation ( IF 4.9 ) Pub Date : 2018-08-01 , DOI: 10.1016/j.biocon.2018.06.003
Esther Sebastián-González , Juan Manuel Pérez-García , Martina Carrete , José Antonio Donázar , José Antonio Sánchez-Zapata

Abstract The adverse effects of wind farms on wildlife, mainly the mortality of flying animals at turbines, should be carefully studied to reconcile renewable energy production and biodiversity conservation. The growing consensus about the aggregated pattern of this mortality at particular turbines suggests that the identification of high-mortality turbines can decisively aid in the implementation of effective management actions. Here, taking advantage of a long-term monitoring program of animal mortality at wind farms (10,017 fatalities of 170 bird and bat species between 1993 and 2016) in two Spanish regions, we demonstrate the utility of network analysis in identifying species indicative of high-risk turbines whose stoppage could significantly reduce the mortality of other species. Our protocol can be easily applied to any region with available data on animal mortality to help managers reduce the negative impacts of wind farms.

中文翻译:

使用网络分析来识别指示物种并减少风电场的碰撞死亡人数

摘要 风电场对野生动物的不利影响,主要是涡轮机飞行动物的死亡,应仔细研究,以协调可再生能源生产和生物多样性保护。关于特定涡轮机这种死亡率的总体模式的日益共识表明,识别高死亡率涡轮机可以决定性地帮助实施有效的管理行动。在这里,利用西班牙两个地区风电场动物死亡率的长期监测计划(1993 年至 2016 年间 170 种鸟类和蝙蝠物种死亡 10,017 次),我们展示了网络分析在识别高危物种方面的效用。风险涡轮机的停机可以显着降低其他物种的死亡率。
更新日期:2018-08-01
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