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

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...

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Bibliographic Details
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: AIP Publishing 2017
Subjects:
Online Access:https://espace.library.uq.edu.au/view/UQ:717634
Description
Summary: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, the authors 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. This 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.