A cross-species framework to identify vocal learning abilities in mammals

Abstract

Vocal production learning (VPL) is the experience-driven ability to produce novel vocal signals through imitation or modification of existing vocalizations. A parallel strand of research investigates acoustic allometry, namely how information about body size is conveyed by acoustic signals. Recently, we proposed that deviation from acoustic allometry principles as a result of sexual selection may have been an intermediate step towards the evolution of vocal learning abilities in mammals. Adopting a more hypothesis-neutral stance, here we perform phylogenetic regressions and other analyses further testing a potential link between VPL and being an allometric outlier. We find that multiple species belonging to VPL clades deviate from allometric scaling but in the opposite direction to that expected from size exaggeration mechanisms. In other words, our correlational approach finds an association between VPL and being an allometric outlier. However, the direction of this association, contra our original hypothesis, may indicate that VPL did not necessarily emerge via sexual selection for size exaggeration: VPL clades show higher vocalization frequencies than expected. In addition, our approach allows us to identify species with potential for VPL abilities: we hypothesize that those outliers from acoustic allometry lying above the regression line may be VPL species. Our results may help better understand the cross-species diversity, variability and aetiology of VPL, which among other things is a key underpinning of speech in our species. This article is part of the theme issue ‘Voice modulation: from origin and mechanism to social impact (Part II)’.

Vocal tract allometry in a mammalian vocal learner

“…Taken together, these suggestions will provide a more precise and detailed picture of the harbour seal's vocal anatomy. Observed species-specific vocalisations are determined by both the species' vocal anatomy and their capacity for vocal learning (Garcia & Ravignani 2020;Ravignani & Garcia 2021). The vocal anatomy generates vocal predispositions by imposing biomechanical constraints, whereas neural processes determine the degree of control species have over their vocal organs (Garcia & Manser, 2020).…”

“…Unfortunately, the relative contribution of both sound production mechanisms is unclear. Here, we test a hypothesis trying to segregate anatomical vs. learning mechanisms (Garcia & Ravignani, 2020;Ravignani & Garcia 2021). As shown here, by testing for allometric relationships between body size and vocal tract structures, one can start to disentangle the respective contributions of vocal anatomy and vocal motor control in shaping acoustic signals.…”

“…Recent cross-species work indeed showed that, given a cross-species regression between sounds produced and body size, outlier species seem to cluster either on one side of the linethose with anatomical adaptations or on the otherthe vocal learners. This led to a morphology vs. learning hypothesis (Garcia & Ravignani, 2020;Ravignani & Garcia, 2021): dishonest signals in mammals may arise either from anatomical adaptations or vocal learning capacities. This prediction has the potential to identify new vocal learners or species with unexpected vocal tract morphology.…”

“…PGLS regressions between frequency parameters (frequency range in the left panel, maximum frequency in the right panel) and body mass across 164 mammalian species. All variables are log-transformed and the figure is adapted from Ravignani and Garcia (2021). The dotted lines represent a threshold at 2,5 standard deviations from the main regression lines used to define outliers.…”

Voice modulation: from origin and mechanism to social impact

“…Ravignani & Garcia [19] (critical topics (i) and (iii)) ask whether such deviations can be predicted by the vocal learning abilities of the species. Using a comparative phylogenetic and acoustic analysis approach, their unexpected results show that multiple species belonging to clades showing vocal production learning do indeed deviate from allometric scaling, but in the opposite direction to that expected from size exaggeration mechanisms.…”