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Biodiversity and Conservation

, Volume 22, Issue 8, pp 1821–1835 | Cite as

Regional-scale modelling of the cumulative impact of wind farms on bats

  • F. Roscioni
  • D. RussoEmail author
  • M. Di Febbraro
  • L. Frate
  • M. L. Carranza
  • A. Loy
Original Paper

Abstract

Wind farms are steadily growing across Europe, with potentially detrimental effects on wildlife. Indeed, cumulative impacts in addition to local effects should be considered when planning wind farm development at a regional scale, and mapping the potential risk to bats at this scale would help in the large-scale planning of wind turbines and focus field surveys on vulnerable areas. Although modelling offers a powerful approach to tackle this goal, its application has been thus far neglected. We developed a simple regional-scale analysis in an area of central Italy (Molise region) that is undergoing considerable wind farm development. We implemented species distribution models (SDMs) for two bat species vulnerable to wind farm impact, Nyctalus leisleri and Pipistrellus pipistrellus. We developed risk maps by overlaying SDMs for the two species with turbine locations, assessed the alteration of the landscape patterns of foraging habitat patches determined by the wind turbines, and identified highly vulnerable areas where wind farm construction would be particularly risky. SDMs were statistically robust (AUC ≥0.8 for both species) and revealed that 41 % of the region offers suitable foraging habitat for both species. These areas host over 50 % of the existing or planned wind farms, with 21 % of the turbines located within 150 m of forest edges, suggesting an increase in fatality risk. The alterations in suitable foraging patches consisted of a 7.7 % increase in the number of patches, a 10.7 % increase in the shape index, and a 8.1 % decrease in the mean patch area. The region’s western portion, which is most suitable to both species, requires careful consideration with regard to future wind farm planning.

Keywords

Chiroptera Energy Habitat alteration Maxent Risk assessment Species distribution models 

Abbreviations

AI

Aggregation index

AUC

Area under the receiver operating characteristic curve

AWMSI

Area weighted mean shape index

CA

Class area

CLC

Corine land cover

FFT

Fast fourier transformation

LPA

Landscape pattern analyses

LPI

Largest patch index

MPS

Mean patch size

NP

Number of patches

SDM

Species distribution models

Notes

Acknowledgments

We thank the Molise regional administration for providing the maps of wind turbine locations and Inergia SpA which in 2010 partly funded FR. Thanks also go to Damiano Preatoni and an anonymous reviewer for their valuable comments on a previous ms version.

Supplementary material

10531_2013_515_MOESM1_ESM.docx (214 kb)
Supplementary material 1 (DOCX 214 kb)

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • F. Roscioni
    • 1
  • D. Russo
    • 2
    • 3
    Email author
  • M. Di Febbraro
    • 1
  • L. Frate
    • 1
  • M. L. Carranza
    • 1
  • A. Loy
    • 1
  1. 1.EnvixLab, Dipartimento Bioscienze e TerritorioUniversità del MolisePescheItaly
  2. 2.Laboratorio di Ecologia Applicata, Dipartimento di AgrariaUniversità degli Studi di Napoli Federico IIPorticiItaly
  3. 3.School of Biological SciencesUniversity of BristolBristolUK

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