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Bats are the second most speciose order of mammals and are under significant threat throughout the world. Survey and monitoring of bats for conservation are severely hampered by the lack of a reliable and user-friendly method of identifying bats from their echolocation calls. We recorded and described time-expanded echolocation calls from 23 bat species in the National Park of Dadia-Lefkimi-Soufli, Greece. We compared the performance of quadratic and linear discriminant function analysis (DFA) of calls as a means of identifying species. Quadratic rather than linear DFA has been used by several researchers because of the violation of the method's basic assumption (homogeneity of variance-covariance matrices). However, when linear DFA was applied for the classification of recorded species in this study, correct classification rate was identical to the quadratic functions (82.4%) and linear models did not misclassify bats to the species with the greatest dispersion, the main problem caused by violation of the homogeneity assumption. The advantage of linear DFA is that it provides discriminant function coefficients. The linear combination of these coefficients and parameters from calls from unidentified bats can be used for species identification without access to the original data sets, an option not provided by quadratic analysis. When separate models were developed for Myotis species and for FM/QCF species, correct classification rates increased to 84.8% and 93.4%, respectively. DF coefficients thus provide a reliable identification tool, but intraspecific geographic variation must be taken into account.
Several recent impact studies reveal that in some localities industrial wind farms are associated with high numbers of bat fatalities. In Europe, most published studies have been conducted in the northwest, while bat diversity generally is much higher in the south of the continent. Here we provide evidence from a post-construction monitoring study conducted in north-eastern Greece between August 2009 and July 2010. Overall, 88 turbines from nine wind farms were intensively searched, and 181 dead and two injured bats were found in their proximity. The most frequently killed species were Nyctalus leisleri (n - 56), Pipistrellus pipistrellus/ P. pygmaeus (53), P. nathusii (35), Hypsugo savii (23) and N. noctula (10). Fatality rates were high from June to September. Most killed bats were adult males. Observed differences in the temporal pattern of fatalities among species may be associated with differences in their behaviour and distribution. Sex segregation with males at higher elevation, where the wind farms were located, and/or absence of females from such areas during summer may be the reason behind the higher male mortality rates. Bat fatalities were unequally distributed among wind farms and turbines. Four turbines (5%) accounted for 27% and 13 turbines (15%) for 51% of the fatalities. The most frequently killed species exhibited different spatial patterns of fatality, presumably because some turbines were located closer to roosts and/or commuting corridors. Fatalities were positively correlated with tower height but not with rotor size. To reduce bat fatalities, we recommend an increase in the cut-in speed of turbines responsible for fatalities from sunset to sunrise.
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