Abstract
Although wind power has proven to be a key component in the efforts of fighting climate change, their harmful effects on avian wildlife has raised increasingly prominent concerns. As the development of wind power is expected to continue at a faster pace, the potential increase in fatal bird collisions is immense. Large-bodied, soaring birds are known to be particularly at risk, for which the White-tailed Eagle (Haliaeetus albicilla) is quintessential.
In this study, the collision risk for white-tailed eagles were predicted and extrapolated to the entire landscape of central and northern Norway (i.e. mapping their landscape of risk). The predictions were based on satellite telemetry data, showing the wide-ranging movements patterns of 34 sub-adult individuals. Their total predicted collision risk across the landscape was found by combining the results of three predictive models, including their resource selection, their risk flight height (50 – 185 m), and a mathematical model centered on direct collision risk. Furthermore, the final predictive collision risk maps were used to assess the collision risk of existing wind farms within the study area. During their movements along the coast, white-tailed eagles are also prone to cumulative effects of several wind farms. Hence, the movement trajectories of each eagle were used to estimate the cumulative collision risk based on the risk levels of each intersected wind farm.
The resource selection revealed that white-tailed eagles were most likely to appear in sparsely vegetated, coastal lowlands. They also favored steep slopes, which aligns nicely with their exploitation of orographic uplift for soaring flight. The probability of flying at risk heights also increased in slopes, while the direct collision risk was more evenly distributed across the landscape. The total predicted collision risk based on all model results was notably higher in the steep coastal landscapes along the Norwegian fjords and declined rapidly with increasing topographic elevation. For the risk posed by each wind farm, the size had a considerable effect on total collision risk, which was expected. However, the findings also revealed that certain smaller wind farms were sited less effectively within preferable eagle habitats. In the cumulative collision risk assessment, the risk varied greatly between individuals, with certain individuals avoiding wind farms more effectively than others. Some individuals also avoided high risk wind farms more effectively, despite moving through the same number of wind farms in total.
Predictive collision risk modelling and cumulative risk assessments represents an advancement towards limiting the harmful effects of wind power. Facilitating the opportunity to analyze predicted collision risk over large areas can improve the effectiveness of strategic planning and site selection. Moreover, by assessing the collision risk in existing wind farms and their cumulative effects on whitetailed eagles, additional site-specific mitigation strategies can be implemented as needed. If not addressed properly, the ecological implications of wind power can be extensive. However, these methods and findings can improve the knowledge base related to birdlife protective practices and future wind power developments in general.