The devil is in the detail:quantifying vocal variation in a complex, multi-levelled, and rapidly evolving display

• Published in: The Journal of the Acoustical Society of America
• Main Authors: Garland, Ellen C., Rendell, Luke, Lilley, Matthew S., Poole, M. Michael, Allen, Jenny, Noad, Michael J.
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2017
• Subjects: Song; Sequence; Cultural evolution; Levenshtein distance; Humpback whale; Humpback Whale; Megaptera novaeangliae
• Online Access: https://risweb.st-andrews.ac.uk/portal/en/researchoutput/the-devil-is-in-the-detail(a9e88d20-91b4-4694-9ba0-f18f890d79bd).html; https://doi.org/10.1121/1.4991320; https://research-repository.st-andrews.ac.uk/bitstream/10023/12641/1/PDF_for_reviewer.pdf; http://asa.scitation.org/doi/suppl/10.1121/1.4991320

Identifying and quantifying variation in vocalizations is fundamental to advancing our understanding of processes such as speciation, sexual selection, and cultural evolution. The song of the humpback whale ( Megaptera novaeangliae ) presents an extreme example of complexity and cultural evolution. It is a long, hierarchically structured vocal display that undergoes constant evolutionary change. Obtaining robust metrics to quantify song variation at multiple scales (from a sound through to population variation across the seascape) is a substantial challenge. Here, we present a method to quantify song similarity at multiple levels within the hierarchy. To incorporate the complexity of these multiple levels, the calculation of similarity is weighted by measurements of sound units (lower levels within the display) to bridge the gap in information between upper and lower levels. Results demonstrate that the inclusion of weighting provides a more realistic and robust representation of song similarity at multiple levels within the display. Our method permits robust quantification of cultural patterns and processes that will also contribute to the conservation management of endangered humpback whale populations, and is applicable to any hierarchically structured signal sequence.