We analyzed the songs of the Asian Stubtail (Urosphena squameiceps),a migratory passerine that breeds in northeast Asia.The possibility of individual identification of this species by songs was examined in a population in northern China during the breeding season of 2010.Individuality was determined using discriminant function analysis,artificial neural networks and spectrographic cross-correlation.Our results show that,the rate of correct classification is satisfactory in this species,regardless of methods.From an applied perspective,spectrographic cross-correlation is most suitable.Besides its maximum rate of correct classification (89.4％),it does not require measurements of spectrograms,which is a necessity other methods and may introduce artificial errors.We hope that our result of individual identification on the basis of acoustic signals may open up a new research venue for this species.
