The expansion of wind energy poses challenges to policy- and decision-makers to address conflicts with wildlife. Conflicts are associated with impacts of existing and planned projects on wildlife, and associated difficulties of prediction where impacts are subject to considerable uncertainty. Many post-construction studies have demonstrated adverse effects on individuals of various bird and bat species. These effects may come in the form of collision-induced mortality or behavioral or physiological changes reducing the fitness of individuals exposed to wind energy facilities. Upscaling these individual effects to population impacts provides information on the true value of interest from a conservation point of view. This paper identifies methodological issues associated when moving from individual effects to population impacts in the context of wind energy. Distinct methodological approaches to predict population impacts are described using published case studies. The various choices of study design and metrics available to detect significant changes at the population level are further assessed based on these. Ways to derive impact thresholds relevant for decision-making are discussed in detail. Robust monitoring schemes and sophisticated modelling techniques may inevitably be unable to describe the whole complexity of wind and wildlife interactions and the natural variability of animal populations. Still, they will provide an improved understanding of the response of wildlife to wind energy and better-informed policies to support risk-based decision-making. Policies that support the use of adaptive management will promote assessments at the population level. Providing information to adequately balance the development of wind energy with the persistence of wildlife populations.
- Wildlife management
- Population impacts
- Impact thresholds
May, R., Masden, E. A., Bennet, F., & Perron, M. (2019). Considerations for upscaling individual effects of wind energy development towards population-level impacts on wildlife. Journal of Environmental Management, 230, 84-93. https://doi.org/10.1016/j.jenvman.2018.09.062