Individual identification on the basis of the songs of the Asian Stubtail (Urosphena squameiceps)

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.