Contribution to unravel variability in bowhead whale songs and better understand its ecological significance

Since the first studies on bowhead whale singing behaviour, song variations have been consistently reported. However, there has been little discussion regarding variability in bowhead whale singing display and its ecological significance. Unlike the better studied humpback whales, bowhead whales do not appear to share songs at population level, but several studies have reported song sharing within clusters of animals. Over the winter season 2013-2014, in an unstudied wintering ground off Northeast Greenland, 13 song groups sharing similar hierarchical structure and units were identified. Unit types were assessed through multidimensional maps, showing well separated clusters corresponding to manually labelled units, and revealing the presence of unit subtypes. Units presented contrasting levels of variability over their acoustic parameters, suggesting that bowhead whales keep consistency in some units while using a continuum in values of frequency, duration and modulation parameters for other unit types. Those findings emphasise the need to account for variability in song analysis to better understand the behavioural ecology of this endangered species. Additionally, shifting from song toward units or phrase-based analysis, as it has been suggested for humpback whales, offers the opportunity to identify and track similarities in songs over temporal and geographical scales relevant to population monitoring.

Automated summary

Studies have shown that bowhead whales exhibit variability in their singing behavior, with some song groups sharing similar hierarchical structure and units. Unlike humpback whales, bowhead whales do not share songs at a population level, but instead exhibit song sharing within clusters of animals in specific areas. This variability in singing behavior highlights the importance of considering variability in song analysis to better understand the behavioral ecology of this endangered species. Additionally, shifting focus towards units or phrase-based analysis may help in identifying and tracking similarities in songs over different scales for population monitoring.