Fine-scale collision risk mapping and validation with long-term mortality data reveal current and future wind energy development impact on sensitive species

© 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/bync/4.0/).

The ongoing demand for renewable energy has boosted the development of wind farms worldwide. Given the impact these facilities have on flying species, a spatially explicit assessment of collision risk in vulnerable species is needed to guide management actions and prioritise areas for installing these infrastructures. We used GPS-tracking data of 127 adult and 50 juvenile griffon vultures in peninsular Spain gathered between 2014 and 2022 to evaluate factors influencing vulnerability and exposure and predict collision risk. We validate the observed collision risk with recorded long-term mortality data (1999–2022) at regional and wind farm scales and evaluate the estimated impact of current and future turbine facilities. Our results showed that overall food availability increases vulnerability and exposure, whilst distance to nesting areas and the presence of conspecifics decreased both vulnerability and exposure in adults and juveniles, respectively. Our maps revealed that 19% and 10% of the Spanish peninsular area had a high collision risk for adults and juveniles, respectively. Importantly, the number of turbine casualties was positively related to collision risk at the regional and wind farm scale and ∼ 18 of the breeding population lies within high collision risk areas.Moreover, the areas with the highest risk of collision also have the highest number of turbines and largely overlap with areas suitable for developing new wind farms. Our study highlights the need to reduce collision risk mapping uncertainties by validating model outputs with actual mortality data. Moreover, it emphasises the urgent need for spatial planning of wind energy development, searching for safer alternatives for biodiversity. This approach undoubtedly serves as a tool to define “not go to” areas for installing new turbines for one of the most sensitive species.

This research was funded by Comunidad de Bardenas Reales de Navarra, Spanish Ministry of Economy and Competitiveness (MCIN/AEI/10.13039/501100011033) and EU/FEDER (grants PID2020-113808RA-I00, PID2019-109685GB-I00, RTI2018–099609-B-C22, CGL2012–32544, CGL2015–66966-C2–1-2-R and CGL2015–66966-C2–1-R2); Junta de Andalucía (RNM-1925 and P18-RT-1321); FEDER_2021.1524 and the Spanish Ministry of Science, Innovation and Universities and ERDF (RTI2018–099609-B-C21, TRASCAR); and Poctefa Interreg Project (EFA 089/15 Ecogyp). Part of this work was funded by Ecotone Telemetry (Poland). JMPG was supported by a Spanish Ministry of Science, Innovation and Universities postdoctoral contract (IJC-2019-038968). EA was supported by Generalitat Valenciana and European Social Fund (APOSTD/2021), and Spanish Ministry of Science, Innovation and Universities Contracts (FJC2021–047885-I).

Peer reviewed