Energy generation is shifting towards renewable sources, but how do these developments impact our environment? In their latest research, Megan Murgatroyd and colleagues develop a predictive model to guide where best to locate wind turbines to minimize collision risk for a large soaring raptor.

The sight of a wind farm is no longer strange to us. For some they might be seen as gentle giants, answers to our energy crisis. However, standing at 200m tall, with blades that can move at speeds of up to 180MPH, these turbines can pose a serious and deadly challenge to birds and bats that share the same airspace.

Globally, it seems that raptors are the group of birds most negatively impacted by wind energy. Indeed, the same pattern has emerged in South Africa, with raptors making up 36% of the carcasses found below turbines at operational wind farms. Large soaring raptors in particular are prone to collisions with wind turbines, and their relatively long lifespans and slow reproductive rates mean that even small increases in mortality can lead to accelerated population declines.

The most effective way to reduce the impact of wind turbines is to position them away from sensitive areas which are used regularly by raptors for flight activity. However, for this to be done effectively we need to first have a good understanding of how raptors use the landscape, and then have an applied and flexible tool which can be used to predict collision risk at proposed developments early in the planning phase.

In our new paper, we demonstrate the effectiveness of such a tool for the Verreaux’s eagle, a large soaring raptor found throughout much of the mountainous regions of sub-Saharan  Africa.

We attached GPS trackers to 15 adult Verreaux’s eagles and analysed how landscape features and ranging behaviour are associated with exposure to collision risk. We built a habitat use model, which identified the landscape features associated with eagle flight within the collision risk zone (i.e. the areas where eagles fly less than 200m above ground level – the height of a turbine). This model can now be used to predict collision risk in any area where the location of Verreaux’s eagle nests are known.

Our model classifies areas into high risk (no-go for wind energy development) and low risk (least likely to be used by eagles and suitable for development) based on the topography within a 12km radius of any eagle nest. Previously, high risk areas have been defined using simple circular buffers around the nest site and, although a 3km radius has been recommended, this had not been tested empirically.

There are potential costs associated with each method. For developers, both circular buffers and our model will exclude a certain amount of area from development which results in a financial cost. For eagle conservation, both methods might suggest somewhere is safe for turbines but is actually used by resident eagles. We measured the tradeoff between these costs for our model and for circular buffers by testing it on tracked eagles along a gradient of development exclusion areas, with the aim of minimising costs for both parties.

Our model shows that, rather than a circular buffer, developers can expect to have the no-go area reduced by 20 – 21% while still achieving the equivalent level of protection to resident eagles. And from the eagle conservation perspective, we showed that our model provided around 4 – 6% improvement in the level of protection provided to eagles when compared with a circular buffer of the same area.

By incorporating habitat use into predictive models, we show that a greater area of land can be made available for wind energy development without increased mortality risk to raptors.

This is a win-win situation, which can inform and expedite wind energy development in locations which minimize the likelihood of collisions for Verreaux’s eagle. It also provides a balance between the development of wind energy, which is needed to reduce greenhouse gasses, and the conservation of a threatened raptor species.

Our methods have already been applied to proposed wind energy developments in South Africa and we now hope to implement similar methods for other at-risk raptors.

Read the full article, A predictive model for improving placement of wind turbines to minimise collision risk potential for a large soaring raptor, in Journal of Applied Ecology