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Abstract
Animals can actively encode different types of identity information in learned communication signals, such as group membership or individual identity. The social environments in which animals interact may favor different types of information, but whether identity information conveyed in learned signals is resilient or responsive to social disruption over short evolutionary timescales is not well understood. We inferred the type of identity information that was most salient in vocal signals by combining computational tools, including supervised machine learning, with a conceptual framework of “hierarchical mapping”, or patterns of relative acoustic convergence across social scales. We used populations of a vocal learning species as a natural experiment to test whether the type of identity information emphasized in learned vocalizations changed in populations that experienced the social disruption of introduction into new parts of the world. We compared the social scales with the most salient identity information among native and introduced range monk parakeet (Myiopsitta monachus) calls recorded in Uruguay and the United States, respectively. We also evaluated whether the identity information emphasized in introduced range calls changed over time. To place our findings in an evolutionary context, we compared our results with another parrot species that exhibits well-established and distinctive regional vocal dialects that are consistent with signaling group identity. We found that native and introduced range monk parakeet calls both displayed the strongest convergence at the individual scale and minimal convergence within sites. We did not identify changes in the strength of acoustic convergence within sites over time in the introduced range calls. These results indicate that the individual identity information in learned vocalizations did not change over short evolutionary timescales in populations that experienced the social disruption of introduction. Our findings point to exciting new research directions about the resilience or responsiveness of communication systems over different evolutionary timescales.
DOI
https://doi.org/10.32942/osf.io/n79kc
Subjects
Behavior and Ethology, Ecology and Evolutionary Biology, Life Sciences
Keywords
Acoustic communication, Biological invader, Contact call, Hierarchical mapping, Identity signaling, Individual signature, Monk parakeet, Myiopsitta monachus, Social information, Supervised machine learning, Vocal learning
Dates
Published: 2022-09-23 13:08
Last Updated: 2023-07-08 14:29
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License
CC-BY Attribution-No Derivatives 4.0 International
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Data and Code Availability Statement:
We will make data publicly available upon manuscript acceptance to a peer-reviewed journal.
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