The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Abstract

Humpback whale (Megaptera novaeangliae) songs are a striking example of\ncultural transmission in non-humans (Garland et al., 2011). During the migration\nand mating season of this species, males produce complex, stereotyped sound\nsequences defined as ‘songs’(Payne & McVay, 1971). Within a population,\nmales conform to a common yet slowly evolving song. Change can also occur\nmore rapidly when a completely new song is adopted by the entire population in\na relatively short time (termed ‘revolution’) (Noad, Cato, Bryden, Jenner, &\nJenner, 2000). These phenomena can only occur if the whales are learning song\nfrom each other. While it is possible to record the shared song within a\npopulation and how this evolves in time, the individual mechanisms and\nlearning strategies behind the cultural transmission of song remain unknown.\nFurthermore, it is not clear how populations maintain conformity in songs that\nchange over variable timescales (evolution vs. revolution). This paper presents a\nspatially explicit multi-agent model designed to investigate humpback whale\nsong learning and transmission

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