Monitoring and forecasting avian collision risk at an operational offshore wind farm

鸟类与风力涡轮机相撞被视为与风力发电场相关的关键环境问题之一。在这些风力发电场建成之前，我们使用模型来预测有多少鸟类可能相撞，这样我们就可以确保它们建在不会对鸟类种群构成不可接受的风险的地方。然而，用于这些模型的数据往往非常有限，这意味着对可能发生的碰撞次数的估计可能相当不精确。我们从英格兰西北部较小的黑背鸥那里收集了高分辨率的跟踪数据。这些数据提供了鸟类如何在景观中移动的详细信息，包括在运营的海上风电场内和周围。我们将使用跟踪数据来模拟运营的风电场内的碰撞风险。这些数据将用于显示这些风电场内鸟类的分布，并帮助预测单个涡轮机的碰撞风险，这受到鸟类飞行的高度和速度的影响（可以从跟踪的鸟类中获得数据）。这些信息将使我们能够第一次展示鸟类与涡轮机相撞的风险在各个风电场之间的差异。这将使我们能够就关键领域提出建议，指导记录碰撞的努力，以及预防或减少碰撞的措施可能最有效的地方。通过记录鸟类分布和将行为与环境条件联系起来，我们将能够开始了解碰撞风险如何随着不断变化的条件而变化。这将使我们能够利用预测的风力条件来做出短期预测，了解鸟类何时何地最有可能与涡轮机相撞。这有可能帮助减少碰撞，使公司能够识别任何单个涡轮机何时可能对鸟类构成高风险，使他们能够更好地采取措施减少碰撞。

Birds colliding with wind turbines are seen as one of the key environmental issues associated with wind farms. Beforethese wind farms are built, we use models to predict how many birds might collide so that we can ensure they are built inplaces where they do not pose an unacceptable risk to bird populations. However, the data that are used for these modelsare often very limited, meaning that estimates of the number of collisions likely to occur can be quite imprecise. We havecollected high-resolution tracking data from lesser black-backed gulls in the north west of England. These data givedetailed information about how birds move around the landscape, including in and around operational offshore wind farms.We will use tracking data to model collision risk within operational wind farms. These data will be used to show thedistribution of birds within these wind farms and also to help predict collision risk at individual turbines, which is affected byboth the height and speed at which birds fly (data which can be obtained from the tracked birds). This information will allowus to show, for the first time, how the risk of birds colliding with turbines varies across the wind farms. This will enable us tomake recommendations about key areas to direct efforts for recording collisions and also where measures to prevent orreduce collisions are likely to be most effective.By recording bird distributions and relating behaviour to environmental conditions, we will be able to start to understandhow collision risk varies in relation to changing conditions. This will enable us to use predicted wind conditions to makeshort-term forecasts about when and where birds are most likely to collide with turbines. This has the potential to helpreduce collisions by allowing companies to identify when any individual turbine is likely to pose a high risk to birds, enablingthem to better target measures to reduce collisions.