Landscape Ecology

, Volume 29, Issue 5, pp 891–903 | Cite as

A modelling approach to infer the effects of wind farms on landscape connectivity for bats

  • Federica Roscioni
  • Hugo Rebelo
  • Danilo Russo
  • Maria Laura Carranza
  • Mirko Di Febbraro
  • Anna Loy
Research article

Abstract

Little is known about the potentially disrupting effects of wind farms on the habitat connectivity of flying vertebrates at the landscape scale. We developed a regional-scale model to assess the wind farm impact on bat migration and commuting routes. The model was implemented for the bat Nyctalus leisleri in a region of central Italy currently undergoing considerable wind farm development. A Species Distribution Model (SDM) for N. leisleri was generated using the MaxEnt algorithm based on 47 presence records (reduced to 19 after the autocorrelation procedure) and 10 environmental variables derived from topographic and land cover maps. We used the SDM to create a map of connectivity using the software UNICOR to identify potential commuting corridors (PCCs). The incidence of each wind farm on bat flight corridors was assessed by overlaying the existing (380) and planned (195) turbine locations onto the PCCs. The SDM was statistically robust (AUC > 0.8). Most of the corridors were concentrated in the western part of the region, which hosts the largest suitable areas for the species; most of the existing (54 %) and planned (72 %) wind farms interfered with important corridors connecting the western and the eastern parts of the region. Our results provide key information on the impact of the wind farm industry on biodiversity on a regional scale. The novel approach adopted, based on SDM and connectivity analysis, could be easily extended to other flying vertebrates and landscapes and constitutes a promising planning tool necessary for harmonizing the development of renewable energy infrastructures with issues of biodiversity conservation.

Keywords

Connectivity analysis Nyctalus leisleri Renewable energy impact Species distribution models Wind farms 

Supplementary material

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Federica Roscioni
    • 1
  • Hugo Rebelo
    • 2
    • 3
  • Danilo Russo
    • 3
    • 4
  • Maria Laura Carranza
    • 1
  • Mirko Di Febbraro
    • 1
  • Anna Loy
    • 1
  1. 1.EnvixLab, Dipartimento Bioscienze e TerritorioUniversità del MolisePescheItaly
  2. 2.Centro de Investigação em Biodiversidade e Recursos Genéticos da Universidade do PortoInstituto de Ciências Agrárias de VairãoVairãoPortugal
  3. 3.School of Biological SciencesUniversity of BristolBristolUK
  4. 4.Wildlife Research Unit, Laboratorio di Ecologia Applicata, Sezione di Biologia e Protezione dei Sistemi Agrari e Forestali, Dipartimento di AgrariaUniversità degli Studi di Napoli Federico IIPorticiItaly

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