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Updated: Aug 27, 2025

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
Published on: February 15, 2017
Fuzzy clustering as a tool to differentiate between discrete and graded call types
Dana A Cusano1, Michael J Noad1, Rebecca A Dunlop1
1Cetacean Ecology and Acoustics Laboratory, School of Veterinary Science, University of Queensland, Gatton, Queensland 4343, Australia danacusano@gmail.com, mnoad@uq.edu.au, r.dunlop@uq.edu.au.
Abstract:
Animals may communicate potential information to conspecifics using stereotyped "discrete" calls and variable "graded" calls. However, animal vocal research often centers on identifying the number of call types in a repertoire rather than quantifying the amount of gradation. Here, fuzzy clustering was applied to the social call repertoire of a species with a complex communication system, the humpback whale (Megaptera novaeangliae). Of 26 call types, 6 were classified as discrete, 7 as graded, and 13 as intermediate. These results indicate that humpback whales have a graded call repertoire, and fuzzy clustering may be a useful approach to investigate this variability.
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