Is it possible to acoustically identify individuals within a population?

Abstract

Acoustically identifying individuals may be a helpful technique when it is necessary to monitor animal populations over space and time. Previous studies have largely focused on the theoretical exploitation of vocal individuality or have looked at a small number of individuals. Here, we examined whether vocal individuality can be used to track the movement of individuals within a population (in this case when the number of individuals is greater than 100) and unknown beforehand. As a model species, we used the Corncrake (Crex crex)—a highly secretive bird whose calls are characterized by an individual- specific feature: pulse-to-pulse duration (PPD). When we performed classical discriminant function analyses on PPD, we correctly identified a high percentage of individuals ([98 %), even when sample size was larger than 100. However, a comparison of PPD similarity within and between individuals showed that, while birds can be correctly discriminated, unambiguous identification is impossible when the number of individuals is unknown beforehand. Therefore, we were only able to assess the probability that two calls belonged to the same individual. The results of this study show that acoustic identification in the Corncrake, and probably in other animal species, is mainly useful in detecting general behavioral patterns within populations. For instance, we discovered that more than 50 % of males change territories during the breeding season, probably to find females. Physical marking methods seem to be more reliable to tracking specific individuals. However, those methods usually consider limited numbers of individuals. Therefore, generalizing results to the population scale can also be misleading.