It is likely that there will continue to be a substantial increase in the number of wind turbines as we aim to meet global energy demands through renewable sources. However, these structures can have adverse impacts on airborne wildlife, such as posing a potential collision risk with the turbine structure. A range of methods and technologies have been applied to the collection of bird flight parameters, such as height and speed, to improve the estimation of potential collision compared with traditional visual methods, but these are currently not applied in a consistent and systematic way. To this end, a systematic literature search was conducted to (1) examine the methods and technologies that can be used to provide bird flight data to assess the impact of wind energy developments and (2) provide an updated framework to guide how they might be most usefully applied within the impact assessment process. Four empirical measurement methods were found that improve the estimation of bird flight parameters: radar, telemetry, ornithodolite and LiDAR. These empirical sensor-based tools were typically more often applied in academic peer-reviewed papers than in report-based environmental statements. Where sensor-based tools have been used in the report-based literature, their inconsistent application has resulted in an uncertain regulatory environment for practitioners. Our framework directly incorporates sensor-based methods, together with their limitations and data requirements, from pre-deployment of infrastructure to post-consent monitoring of impacts. This revised approach will help improve the accuracy of estimation of bird flight parameters for ornithological assessment of wind energy. Sensor-based tools may not be the most cost-effective. However, a precedent has been set for wind energy development consent refusal based on ornithological impact assessment, and therefore the cost of collecting accurate and reliable flight data may be balanced favourably against the cost of development consent refusal.

中文翻译：

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量化与风能开发相关的鸟类空域使用的方法

随着我们的目标是通过可再生能源满足全球能源需求，风力涡轮机的数量可能会继续大幅增加。然而，这些结构会对空中的野生动物产生不利影响，例如与涡轮机结构构成潜在的碰撞风险。与传统的视觉方法相比，一系列方法和技术已应用于鸟类飞行参数的收集，例如高度和速度，以提高对潜在碰撞的估计，但目前还没有以一致和系统的方式应用这些方法和技术。为此，进行了系统的文献检索，以 (1) 研究可用于提供鸟类飞行数据以评估风能发展的影响的方法和技术，以及 (2) 提供更新的框架以指导如何最有效地应用它们影响评估过程。发现四种经验测量方法可以改善鸟类飞行参数的估计：雷达、遥测、鸟瞰仪和激光雷达。这些基于经验传感器的工具通常更常用于学术同行评审论文，而不是基于报告的环境声明。在基于报告的文献中使用了基于传感器的工具时，其不一致的应用导致从业者的监管环境不确定。我们的框架直接结合了基于传感器的方法，以及它们的局限性和数据要求，从基础设施的预部署到影响的同意后监测。这种修订后的方法将有助于提高鸟类飞行参数估计的准确性，用于风能鸟类评估。基于传感器的工具可能不是最具成本效益的。然而，基于鸟类学影响评估拒绝风能开发许可的先例已经建立，因此收集准确可靠的飞行数据的成本可以有利地与开发许可的拒绝成本相平衡。基于传感器的工具可能不是最具成本效益的。然而，基于鸟类学影响评估拒绝风能开发许可的先例已经建立，因此收集准确可靠的飞行数据的成本可以有利地与开发许可的拒绝成本相平衡。基于传感器的工具可能不是最具成本效益的。然而，基于鸟类学影响评估拒绝风能开发许可的先例已经建立，因此收集准确可靠的飞行数据的成本可以有利地与开发许可的拒绝成本相平衡。