ORCID

Abstract

Male humpback whales produce hierarchically structured songs, primarily during the breeding season. These songsgradually change over the course of the breeding season, and are generally population specific. However, instances havebeen recorded of more rapid song changes where the song of a population can be replaced by the song of an adjacentpopulation. The mechanisms that drive these changes are not currently understood, and difficulties in tracking individualwhales over long migratory routes mean field studies to understand these mechanisms are not feasible. In order to helpunderstand the mechanisms that drive these song changes, we present here a spatially explicit agent-based model inspiredby methods used in computer music research. We model the migratory patterns of humpback whales, a simple songlearning and production method coupled with sound transmission loss, and how often singing occurs during thesemigratory cycles. This model is then extended to include learning biases that may be responsible for driving changes in thesong, such as a bias towards novel song, production errors, and the coupling of novel song bias and production errors.While none of the methods showed population song replacement, our model shows that shared feeding grounds whereconspecifics are able to mix provide key opportunities for cultural transmission, and that production errors facilitatedgradually changing songs. Our results point towards other learning biases being necessary in order for population songreplacement to occur.

Publication Date

2018-03-11

Publication Title

Music & Science

Volume

1

ISSN

2059-2043

Deposit Date

2024-06-04

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