Identification of vocal individuality in male cuckoos using different analytical techniques

Li, Y, Xia, C, Lloyd, H, Li, D and Zhang, Y (2017) Identification of vocal individuality in male cuckoos using different analytical techniques. Avian Research, 8 (1). ISSN 2053-7166

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Abstract

© 2017 The Author(s). Background: Individuality in vocalizations may provide an effective tool for surveying populations of the Common Cuckoo (Cuculus canorus) but there remains few data on which technique to use to identify individuality. In this research, we compared the within- and between-individual variation in cuckoo calls using two different analytical methods, and discuss the feasibility of using call individuality to count male cuckoos within a population. Methods: We recorded vocalization from 13 males, and measured 15 spectro-temporal variables for each call. The majority of these call variables (n=12) have greater variation between individuals than within individual. We first calculated the similarity (Pearson's R) for each paired calls in order to find a threshold that could distinguish calls emitted from the same or different males, and then counted the number of males based on this distinction. Second, we used the more widely accepted technique of discriminant function analysis (DFA) to identify individual male cuckoos, and compared the correct rate of classifying individuals between the two analytical methods. Results: Similarity of paired calls from the same male was significantly higher than from different males. Under a relatively broad threshold interval, we achieved a high ( > 90%) correct rate to distinguish calls and an accurate estimate of male numbers. Based on banded males (n=3), we found the similarity of paired calls from different days was lower when compared with paired calls from the same day, but this change did not obscure individual identification, as similarity values of paired calls from different days were still larger than the threshold used to distinguish calls from the same or different males. DFA also yielded a high rate (91.9%) of correct classification of individuals. Conclusions: Our study suggests that identifying individual vocalizations can form the basis of an appropriate survey method for counting male cuckoos within a population, provided the performance of different analytical techniques are compared.