A predictive model for improving placement of wind turbines to minimise collision risk potential for a large soaring raptor

Abstract

With the rapid growth of wind energy developments world‐wide, it is critical that the negative impacts on wildlife are considered and mitigated. This includes minimising the number of large soaring raptors, which are killed when they collide with wind turbines. To reduce the likelihood of raptor collisions, turbines should be placed at locations which are least used by sensitive species. For resident or breeding species, this is often delineated crudely through the use of circular buffers centred on nest sites, which assume uniform habitat use around a nest site. Using GPS tracking data together with a digital elevation model we build and cross‐validate a simple generalisable model, to classify the spatial likelihood of wind turbine collisions for resident adult Verreaux's eagles in any landscape where there are known nests. We apply our methods to operational developments in South Africa to validate the model and demonstrate its ability in predicting actual collision mortalities. Our collision risk potential (CRP) model included the variables distance to nest, distance to conspecific nest, slope, distance to slope and elevation. Using our model, rather than a circular buffer, resulted in c. 4%–5% improvement in eagle protection while excluding development from the same amount (but not shape) of area. For an equal level of eagle protection, our model can make c. 20%–21% more area available for wind energy development compared to a circular buffer. Exploring collisions at operational wind farms in South Africa we show that our CRP model correctly predicted 79% of known collisions, while circular buffers (5.2 km radius) only captured 50% of collisions. Synthesis and applications. We show that by using predictive models to account for habitat use instead of simple buffers around a nest, a greater area of land can be made available for wind energy development without increased mortality risk to raptors. Our predictive model can be used to provide robust guidance on wind turbine placement in South Africa in a way which minimises the conflict between a vulnerable raptor species and the development of renewable energy.

Flight Altitudes of Raptors in Southern Africa Highlight Vulnerability of Threatened Species to Wind Turbines

“…Indeed, we are aware of a single study that we can use to quantitatively check our results. In South Africa, Murgatroyd et al (2021) used GPS tracking to demonstrate that Verreaux's Eagles (Aquila verreauxii) fly at turbine height (defined as ≤200 m) 68 ± 4% of the time. This is consistent with the data from GRIN, in which Verreaux's Eagles were seen flying at or below turbine height 73% of the time.…”

A predictive flight-altitude model for avoiding future conflicts between an emblematic raptor and wind energy development in the Swiss Alps

“…Processing a large amount of data is challenging and computationally expensive. Often data are heavily subsampled not only to reduce autocorrelation problems but also to meet computational capacities of classical statistical approaches [24,33]. On the other hand, more recent techniques that require large datasets, like machine learning algorithms and, especially, artificial neural networks, can capture complex nonlinear relationships present in the data.…”

“…In order to make use of all information included in the data and also develop a method that easily scales to potentially very large datasets, we used a deep feedforward neural network to model the probability of a bearded vulture flying within a given altitude range at a given location. Considering the still ongoing trend of increasing heights of newly constructed, modern wind turbines, we decided for a threshold of 200 m (hereafter referred to as critical altitude), below which the flight of a bird is deemed to be at potential risk of collision with the rotor blades (see also [33,34]). The flight altitude was converted to a binary response with 1 being a location within the critical altitude range and 0 otherwise.…”

“…To prevent detrimental impacts of the turbine operation on endangered species, wildlife managers and wind energy companies need adequate planning tools to minimize the deployment of wind facilities in areas where major conflicts with biodiversity preservation will occur. Different approaches have been used as planning tools to mitigate the risks encountered by flying vertebrates, spanning from mere delineations of buffer areas around sensitive locations [29–31], through the compilation of distribution areas of sensitive species [28,29,32], to more complex methods that account for fine-grained habitat use and/or flight behaviour of potentially impacted bat and bird species [13,33–37]. The first approach is fairly imprecise.…”

Commentary: the Past, Present, and Future of the Global Raptor Impact Network

“…GRIN will include analytical tools that specifically inform conservation assessments and direct conservation action. For example, flight altitude is an important determinant of collision risk with wind turbines (Khosravifard et al 2020, Murgatroyd et al 2021. Data recorded via the GRIN mobile app can therefore be used to inform the potential collision risk with wind turbines.…”