Using risk prediction models and species sensitivity maps for large-scale identification of infrastructure-related wildlife protection areas: The case of bird electrocution

Abstract

The use of systematic area-selection procedures to design protected areas can help optimize conservation actions. However, this process has rarely been used to identify high-risk mortality areas to protect wildlife from human impacts. Electrocution on power lines is one the most important human-related causes of bird mortality worldwide, especially for raptors. Identifying and correcting dangerous individual pylons can significantly reduce the number of electrocution victims, but applying this procedure at a large spatial scale is impractical. In this paper we describe a new selection process that allows for identification of high-risk mortality areas at large scales, combining spatial electrocution risk models with maps of species sensitivity to such an impact. We used the Valencia Region (eastern Spain) as our study system. The risk prediction map was built using bird electrocution records on 1 km ×1 km grids from 2000 to 2009 and the species sensitivity map was built using data on presence and use of four raptor species. The combination of both maps was compared to the distribution of Special Protected Areas and validated by local experts to identify prediction errors or gaps. The final proposal of high priority areas to protect birds from electrocution covered 16.3% of the Valencia Region. Our work supports the use of predictive models and sensitivity maps in the decision-making process to locate high priority infrastructure-related wildlife protection areas at a large scale