Variability in humpback whale songs reveals how individuals can be distinctive when sharing a complex vocal display.

Individually distinctive acoustic signals in animal vocal communication are taxonomically widespread, however, the investigation of these signal types in marine mammals has focused only on a few species. Humpback whale songs are a stereotyped, hierarchically structured vocal display performed by males, and hence thought to be sexually selected. Within a population, whales conform to a common version of the song despite the song constantly evolving. While humpback songs have been studied extensively at the population level, individual level variation has been rarely described, with inconclusive results. Here, we quantified inter- and intra-individual variability at different levels in the song hierarchy using songs from 25 singers across two song types from the eastern Australian population song of 2002 (12 singers), and the revolutionary song introduced in 2003 (13 singers). Inter-individual variability was found heterogeneously across all hierarchical levels of the song structure. In addition, distinct and individually specific patterns of song production were consistently recorded across song levels, with clear structural differences between the two song types. These results suggest that within the constraints of song conformity, males can produce individually distinctive patterns that could function as an advertisement to females to convey individual qualities.

Song complexity is maintained during inter-population cultural transmission of humpback whale songs.

Among animal species, the songs of male humpback whales (Megaptera novaeangliae) are a rare example of social learning between entire populations. Understanding fine-scale similarity in song patterns and structural features will better clarify how accurately songs are learned during inter-population transmission. Here, six distinct song types (2009-2015) transmitted from the east Australian to New Caledonian populations were quantitatively analysed using fine-scale song features. Results found that New Caledonian whales learned each song type with high accuracy regardless of the pattern's complexity. However, there were rare instances of themes (stereotyped patterns of sound units) only sung by a single population. These occurred more often in progressively changing 'evolutionary' songs compared to rapidly changing 'revolutionary' songs. Our results suggest that populations do not need to reduce complexity to accurately learn song patterns. Populations may also incorporate changes and embellishments into songs in the form of themes which are suggested to be learnt as distinct segments. Maintaining complex song patterns with such accuracy suggests significant acoustic contact, supporting the hypothesis that song learning may occur on shared feeding grounds or migration routes. This study improves the understanding of inter-population mechanisms for large-scale cultural transmission in animals.

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

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, characterized by clusters of highly connected sounds. Transitions between these connected sounds further suggested a combination of both structural stability and variability. Small-world network structure within humpback songs may facilitate the characteristic and persistent vocal learning observed. Similar small-world structures and transition patterns are found in several birdsong displays, indicating common syntactic patterns among vocal learning in multiple taxa. Understanding the syntactic rules governing vocal displays in multiple, independently evolving lineages may indicate what rules or structural features are important to the evolution of complex communication, including human language.

Community through Culture: From Insects to Whales: How Social Learning and Culture Manifest across Diverse Animal Communities.

It has become increasingly clear that social learning and culture occur much more broadly, and in a wider variety of animal communities, than initially believed. Recent research has expanded the list to include insects, fishes, elephants, and cetaceans. Such diversity allows scientists to expand the scope of potential research questions, which can help form a more complete understanding of animal culture than any single species can provide on its own. It is crucial to understand how culture and social learning present in different communities, as well as what influences community structure and culture may have on one another, so that the results across these different studies may most effectively inform one another. This review presents an overview of social learning in species across a spectrum of community structures, providing the necessary infrastructure to allow a comparison of studies that will help move the field of animal culture forward.

Cultural revolutions reduce complexity in the songs of humpback whales.

Much evidence for non-human culture comes from vocally learned displays, such as the vocal dialects and song displays of birds and cetaceans. While many oscine birds use song complexity to assess male fitness, the role of complexity in humpback whale (Megaptera novaeangliae) song is uncertain owing to population-wide conformity to one song pattern. Although songs change gradually each year, the eastern Australian population also completely replaces their song every few years in cultural 'revolutions'. Revolutions involve learning large amounts of novel material introduced from the Western Australian population. We examined two measures of song structure, complexity and entropy, in the eastern Australian population over 13 consecutive years. These measures aimed to identify the role of complexity and information content in the vocal learning processes of humpback whales. Complexity was quantified at two hierarchical levels: the entire sequence of individual sound 'units' and the stereotyped arrangements of units which comprise a 'theme'. Complexity increased as songs evolved over time but decreased when revolutions occurred. No correlation between complexity and entropy estimates suggests that changes to complexity may represent embellishment to the song which could allow males to stand out amidst population-wide conformity. The consistent reduction in complexity during song revolutions suggests a potential limit to the social learning capacity of novel material in humpback whales.

Using self-organizing maps to classify humpback whale song units and quantify their similarity.

Classification of vocal signals can be undertaken using a wide variety of qualitative and quantitative techniques. Using east Australian humpback whale song from 2002 to 2014, a subset of vocal signals was acoustically measured and then classified using a Self-Organizing Map (SOM). The SOM created (1) an acoustic dictionary of units representing the song's repertoire, and (2) Cartesian distance measurements among all unit types (SOM nodes). Utilizing the SOM dictionary as a guide, additional song recordings from east Australia were rapidly (manually) transcribed. To assess the similarity in song sequences, the Cartesian distance output from the SOM was applied in Levenshtein distance similarity analyses as a weighting factor to better incorporate unit similarity in the calculation (previously a qualitative process). SOMs provide a more robust and repeatable means of categorizing acoustic signals along with a clear quantitative measurement of sound type similarity based on acoustic features. This method can be utilized for a wide variety of acoustic databases especially those containing very large datasets and can be applied across the vocalization research community to help address concerns surrounding inconsistency in manual classification.