Identification of individual Eastern Screech-Owls Megascops asio via vocalization analysis

Abstract

To more easily and non-invasively monitor urban Eastern Screech-Owl populations, we developed a method of distinguishing individual owls using their calls. A set of seven variables derived from recordings of ‘bounce’ calls taken from 10 known (either free-ranging birds recorded at a single site on a single night or identifiable captive owls) owls was tested using a model-based clustering analysis (Mclust) as a method of discriminating individual owls. The cluster analysis correctly classified these calls with 98% accuracy. A second set of calls from nine owls was used to further test the method and correctly classified 84% of the calls using the same variables. Four owls were recorded repeatedly from 2008 to 2010 to determine the extent to which calls changed over time; the cluster analysis correctly assigned 89% of the calls to the correct owl regardless of the year the recordings were made. Based on these results, we are confident that the Mclust analysis can be used to reliably and safely estimate abundance and survival of Eastern Screech-Owls within the time frame of a few years and of population sizes < 15 owls.