Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song ...

• Main Authors: Allen, Jennifer, Garland, Ellen, Dunlop, Rebecca, Noad, Michael
• Format: Dataset
• Language: English
• Published: Dryad 2019
• Subjects: Syntax; vocal learning; song; network modelling; Megaptera novaeangliae; Humpback Whale
• Online Access: https://dx.doi.org/10.5061/dryad.2bvq83bkv; https://datadryad.org/stash/dataset/doi:10.5061/dryad.2bvq83bkv

Vocal communication systems have a set of rules that govern the arrangement of acoustic signals, broadly defined as ‘syntax’. However, there is a limited understanding of potentially shared or analogous rules across vocal displays in different taxa. Recent work on songbirds has investigated syntax using network-based modelling. This technique quantifies features such as connectivity (adjacent signals in a sequence) and recurring patterns. Here, we apply network-based modelling to the complex, hierarchically structured songs of humpback whales (Megaptera novaeangliae) from east Australia. Given the song’s annual evolving pattern and the cultural conformity of males within a population, network modelling captured the patterns of multiple song types over 13 consecutive years. Song arrangements in each year displayed clear “small-world” network structure, characterised by clusters of highly connected sounds. Transitions between these connected sounds further suggested a combination of both structural stability ...