Birds colliding with wind turbines are seen as one of the key environmental issues associated with wind farms. Before
these wind farms are built, we use models to predict how many birds might collide so that we can ensure they are built in
places where they do not pose an unacceptable risk to bird populations. However, the data that are used for these models
are often very limited, meaning that estimates of the number of collisions likely to occur can be quite imprecise. We have
collected high-resolution tracking data from lesser black-backed gulls in the north west of England. These data give
detailed 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 the
distribution of birds within these wind farms and also to help predict collision risk at individual turbines, which is affected by
both the height and speed at which birds fly (data which can be obtained from the tracked birds). This information will allow
us to show, for the first time, how the risk of birds colliding with turbines varies across the wind farms. This will enable us to
make recommendations about key areas to direct efforts for recording collisions and also where measures to prevent or
reduce collisions are likely to be most effective.

By recording bird distributions and relating behaviour to environmental conditions, we will be able to start to understand
how collision risk varies in relation to changing conditions. This will enable us to use predicted wind conditions to make
short-term forecasts about when and where birds are most likely to collide with turbines. This has the potential to help
reduce collisions by allowing companies to identify when any individual turbine is likely to pose a high risk to birds, enabling
them to better target measures to reduce collisions.

Potential Impact:
Marine Renewable Energy Industry & Environmental Consultancies

The European offshore wind industry is growing rapidly and expected to be worth in the region of £9.2 Billion a year by 2030. Across the EU, there is a target to reduce carbon emissions by 40% of 1990 levels by 2030 and offshore wind is likely to play a key role in this. However, at present, collision represents a key challenge to regulators as part of the consenting process. The number of birds predicted to collide with turbines is usually assessed prior to the construction of a wind farm using a collision risk model. However, these models make a number of simplistic assumptions about bird behaviour and movements within a wind farm. As a consequence, pre-construction assessments of collision risk may be unrealistic and, potentially over-estimated. With the expansion of the offshore wind sector, collision risk estimates are reaching a level where they may have significant population level impacts with the consequence that projects are refused planning consent. By utilising tracking data to develop a collision risk model, we will be able to analyse how birds behave and move offshore in much more detail than is allowed for using existing models. The results from our model will help developers and their consultants to understand how realistic outputs from existing collision risk models are.

Mitigation and monitoring within an offshore wind farm can be time-consuming and economically costly. By producing a spatial model of collision risk within an offshore wind farm, we will enable developers to target specific areas for mitigation measures. These could be pre-construction measures, for example raising turbine hub height, or post-construction measures, such as deploying deterrent devices. The relative costs and benefits of different strategies could be modeled. Monitoring collisions offshore can be very challenging and involves expensive equipment. By identifying where collision risk is likely to be greatest, our models will be able to help consultant employed by developers to develop cost-effective monitoring programmes.

Whilst our model is developed with the offshore wind industry in mind, the principles are likely to be applicable to other marine renewable energy industries as well.

Government Regulators and Statutory Nature Conservation Bodies

It is important that SNCBs are able to give advice to governmental regulators based on the best available scientific evidence. At present there are concerns that the simplistic assumptions made by existing collision risk models may result in unrealistic estimates of collision risk. This poses a significant consenting risk for offshore wind farms and, may, make it harder to achieve targets to increase the use of renewable energy and reduce greenhouse gas emissions. By making use of tracking data within a collision risk model, it will be possible to improve the evidence base with which collision risk is assessed, helping to ensure that consenting decisions are based on the best available evidence.