| Literature DB >> 28062112 |
Carmen Silva1, João Alexandre Cabral1, Samantha Jane Hughes2, Mário Santos3.
Abstract
Worldwide ecological impact assessments of wind farms have gathered relevant information on bat activity patterns. Since conventional bat study methods require intensive field work, the prediction of bat activity might prove useful by anticipating activity patterns and estimating attractiveness concomitant with the wind farm location. A novel framework was developed, based on the stochastic dynamic methodology (StDM) principles, to predict bat activity on mountain ridges with wind farms. We illustrate the framework application using regional data from North Portugal by merging information from several environmental monitoring programmes associated with diverse wind energy facilities that enable integrating the multifactorial influences of meteorological conditions, land cover and geographical variables on bat activity patterns. Output from this innovative methodology can anticipate episodes of exceptional bat activity, which, if correlated with collision probability, can be used to guide wind farm management strategy such as halting wind turbines during hazardous periods. If properly calibrated with regional gradients of environmental variables from mountain ridges with windfarms, the proposed methodology can be used as a complementary tool in environmental impact assessments and ecological monitoring, using predicted bat activity to assist decision making concerning the future location of wind farms and the implementation of effective mitigation measures.Keywords: Acoustic monitoring; Bat activity patterns; Ecological modelling; Environmental risk assessment; Stochastic Dynamic Methodology (StDM); Wind farms
Year: 2017 PMID: 28062112 DOI: 10.1016/j.scitotenv.2016.12.135
Source DB: PubMed Journal: Sci Total Environ ISSN: 0048-9697 Impact factor: 7.963