Primates, characterized by high degrees of fission-fusion dynamics, often use vocalizations to coordinate travel, locate and maintain contact with groupmates, recruit new party members, regulate spatial cohesion, and avoid extra-group conspecifics. In environments with limited visibility, individually distinct vocalizations may become increasingly important as they decrease listener uncertainty and allow individuals to differentially respond to caller identity. For this study, we examined the acoustic variation and individual distinctiveness of contact calls in woolly monkeys (Lagothrix lagotricha poeppigii) from the Tiputini Biodiversity Station in Amazonian Ecuador. Acoustic recordings of woolly monkey vocalizations were previously collected in June and July of 2019. Using the audio-visualization software RavenPro, we extracted and measured 1354 vocalizations encompassing three major categories: contact calls (73%), alarm calls (18%), and other vocalizations (9%). Chirps, a type of contact call, were the most prominent vocalization, recorded from most individuals. Of the 888 chirps identified, 205 could be accurately linked to an individual caller. Comparing the coefficients of variation within and between individuals for seven acoustic parameters, we found that inter-individual variation was high, and that these parameters could be used to confidently discriminate between callers. These findings were confirmed using a discriminant function analysis, where callers were classified with >50% accuracy. While the current study highlights that the variability found within contact calls allows for identity encoding, it remains unclear to what extent that information is used? To better understand the role individual recognition plays in primate communication, we aim to expand our analyses to more call types, as well as examine listener responses based on caller identity and social contexts. In all, this research opportunity has provided me with hands-on training in bioacoustic analysis, including the use of RavenPro and running statistical analyses in R, and I look forward to taking my research into the field in 2022.
Author: Nico Jaworski
Faculty Advisor: Kelsey Ellis, Anthropology
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