Robust encoding of acoustic identity in alpaca hums - a basis for individual recognition

Abstract

Individual recognition is an important element of social interactions among animals. While the presence of individually distinct vocalisations (providing a basis for individual recognition) has been widely tested across species, information about which components of a call encode this information is lacking. We investigated whether female alpaca (Vicugna pacos) vocalisations, particularly their hums, encode information about individual identity and explored which parameters contribute to this encoding. We recorded vocalisations from 9 adult female alpaca and extracted both spectro-temporal features (frequencies and duration) and mel-frequency cepstral coefficients (MFCC). Random forest analyses revealed clear individual differences in both datasets, with the spectro-temporal features allowing for slightly more accurate classification than MFCC (71% and 66.5% accuracy for spectro-temporal features and MFCC, respectively). These robust acoustic identities have the potential to provide a basis for individual recognition in alpaca, which could have important flow on effects for alpaca communication, as it allows receivers to modulate their response to the callers identity. Alpaca, as herd-living and vocal animals, provide an excellent model system for better understanding the mechanisms, causes and consequences of recognition and inter-individual communication.