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

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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.