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

Area of Science:

• Bioacoustics
• Animal Communication
• Computational Biology

Background:

• Quantifying variation in animal vocalizations is crucial for understanding evolution and behavior.
• Humpback whale songs are complex, hierarchical, and culturally evolving signals.
• Measuring song variation across different scales presents a significant analytical challenge.

Purpose of the Study:

• To develop a novel method for quantifying song similarity in humpback whales at multiple hierarchical levels.
• To create a robust metric that accounts for the complex structure of whale songs.
• To enable a more accurate assessment of vocal variation for evolutionary and conservation studies.

Main Methods:

• Developed a weighted similarity calculation to integrate information across different hierarchical levels of whale song.
• Applied measurements of sound units to bridge information gaps between lower and upper song structures.
• Quantified song similarity at multiple scales, from individual sound units to population-level variation.

Main Results:

• The proposed weighted method provides a more realistic and robust representation of song similarity.
• The approach successfully quantifies variation at multiple scales within the hierarchical song structure.
• Demonstrated the effectiveness of the method in capturing complex patterns of cultural evolution in whale songs.

Conclusions:

• The new method offers a powerful tool for analyzing hierarchically structured signals in bioacoustics.
• This quantification of song similarity aids in understanding cultural transmission and evolution in humpback whales.
• The approach has significant implications for the conservation management of endangered whale populations and can be applied to other species.