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.
discriminant function analysis