A global analysis of song frequency in passerines provides no support for the acoustic adaptation hypothesis but suggests a role for sexual selection

Mikula, Peter; Vâlcu, Mihai; Brumm, Henrik; Bulla, Martin; Forstmeier, Wolfgang; Petrusková, Tereza; Kempenaers, Bart; Albrecht, Tomáš

doi:10.1111/ele.13662

Cited by 75 publications

(76 citation statements)

References 103 publications

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“…(a) Variation in response to the acoustic environment Animals modify the intensity, frequency, duration and repetition of their signals to compensate for variation in acoustic conditions in their environment (see [13][14][15][16]). If these adjustments involve immediate audio-vocal feedback [17][18][19] rather than memorized information from previous experience, they would not be classed as learned changes, based on the definition of learning applied herein.…”

Section: Non-learned Inputs Into Vocal Variationmentioning

confidence: 99%

The multi-dimensional nature of vocal learning

Vernes

Kriengwatana

Beeck

et al. 2021

Phil. Trans. R. Soc. B

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How learning affects vocalizations is a key question in the study of animal communication and human language. Parallel efforts in birds and humans have taught us much about how vocal learning works on a behavioural and neurobiological level. Subsequent efforts have revealed a variety of cases among mammals in which experience also has a major influence on vocal repertoires. Janik and Slater ( Anim. Behav. 60 , 1–11. ( doi:10.1006/anbe.2000.1410 )) introduced the distinction between vocal usage and production learning, providing a general framework to categorize how different types of learning influence vocalizations. This idea was built on by Petkov and Jarvis ( Front. Evol. Neurosci. 4 , 12. ( doi:10.3389/fnevo.2012.00012 )) to emphasize a more continuous distribution between limited and more complex vocal production learners. Yet, with more studies providing empirical data, the limits of the initial frameworks become apparent. We build on these frameworks to refine the categorization of vocal learning in light of advances made since their publication and widespread agreement that vocal learning is not a binary trait. We propose a novel classification system, based on the definitions by Janik and Slater, that deconstructs vocal learning into key dimensions to aid in understanding the mechanisms involved in this complex behaviour. We consider how vocalizations can change without learning, and a usage learning framework that considers context specificity and timing. We identify dimensions of vocal production learning, including the copying of auditory models (convergence/divergence on model sounds, accuracy of copying), the degree of change (type and breadth of learning) and timing (when learning takes place, the length of time it takes and how long it is retained). We consider grey areas of classification and current mechanistic understanding of these behaviours. Our framework identifies research needs and will help to inform neurobiological and evolutionary studies endeavouring to uncover the multi-dimensional nature of vocal learning. This article is part of the theme issue ‘Vocal learning in animals and humans’.

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Section: Non-learned Inputs Into Vocal Variationmentioning

confidence: 99%

The multi-dimensional nature of vocal learning

Vernes

Kriengwatana

Beeck

et al. 2021

Phil. Trans. R. Soc. B

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“…by propagating further or resisting noise better) than unlearned calls or songs (cf. [131]). Evidence of rapid changes in songs in response to urban noise [132,133] are consistent with this hypothesis.…”

Section: Discussionmentioning

confidence: 99%

The many functions of vocal learning

Carouso-Peck

Goldstein

Fitch

2021

Phil. Trans. R. Soc. B

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The capacity to learn novel vocalizations has evolved convergently in a wide range of species. Courtship songs of male birds or whales are often treated as prototypical examples, implying a sexually selected context for the evolution of this ability. However, functions of learned vocalizations in different species are far more diverse than courtship, spanning a range of socio-positive contexts from individual identification, social cohesion, or advertising pair bonds, as well as agonistic contexts such as territorial defence, deceptive alarm calling or luring prey. Here, we survey the diverse usages and proposed functions of learned novel signals, to build a framework for considering the evolution of vocal learning capacities that extends beyond sexual selection. For each function that can be identified for learned signals, we provide examples of species using unlearned signals to accomplish the same goals. We use such comparisons to generate hypotheses concerning when vocal learning is adaptive, given a particular suite of socio-ecological traits. Finally, we identify areas of uncertainty where improved understanding would allow us to better test these hypotheses. Considering the broad range of potential functions of vocal learning will yield a richer appreciation of its evolution than a narrow focus on a few prototypical species. This article is part of the theme issue ‘Vocal learning in animals and humans’.

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“…Evidence for acoustic adaptation across animals is mixed, with many studies demonstrating lower mass-corrected vocal frequencies for species inhabiting dense vegetation compared with more open environments (Ryan and Brenowitz 1985, Boncoraglio and Saino 2007, Derryberry 2009, Ey and Fischer 2009, Kirschel et al 2009, and others showing limited evidence of habitat effects on acoustic signals (Daniel and Blumstein 1998, Jain and Balakrishnan 2011, Mason and Burns 2015, Tietze et al 2015, Graham et al 2016, Mikula et al 2020. Implicit to most acoustic adaptation studies is the idea that a dense signaling environment Fig.…”

Section: Ecological and Sexual Selection On Vocal Frequencymentioning

confidence: 99%

Testing the strength and direction of selection on vocal frequency using metabolic scaling theory

Francis

Wilkins

2021

Ecosphere

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A major challenge for studies assessing drivers of phenotypic divergence is the statistical comparison of taxa with unique, often unknown, evolutionary histories, and for which there are no clear expected trait values. Because many traits are fundamentally constrained by energy availability, we suggest that trait values predicted by scaling theories such as the metabolic theory of ecology (MTE) can provide baseline expectations. Here, we introduce a metabolic scaling-based approach to test theory involving the direction and magnitude of ecological and sexual selection, using vocal frequency as an example target of selection. First, we demonstrate that MTE predicts the relationship between the natural log of body size and natural log of vocal frequency across 795 bird species, controlling for phylogeny. Family-wide deviations in slope and intercepts from MTE estimates reveal taxa with potentially important differences in physiology or natural history. Further, species-level frequency deviations from MTE expectations are predicted by factors related to ecological and sexual selection and, in some cases, provide evidence that differs from current understanding of the direction of selection and identity of ecological selective agents. For example, our approach lends additional support to the findings from many cross-habitat studies that suggest that dense vegetation selects for lower frequency signals. However, our analysis also suggests that birds in non-forested environments vocalize at frequencies higher than expected based on MTE, prompting intriguing questions about the selective forces in non-forest environments that may act on vocal frequency. Additionally, vocal frequency deviates more strongly from MTE expectations among species with smaller repertoires and those with low levels of sexual dichromatism, complicating the use of these common sexual selection surrogates. Broad application of our metabolic scaling approach might provide an important complementary approach to understanding how selection shapes phenotypic evolution by offering a common baseline across studies and taxa and providing the basis to explore evolutionary trade-offs within and among multicomponent and multimodal traits.

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A global analysis of song frequency in passerines provides no support for the acoustic adaptation hypothesis but suggests a role for sexual selection

Cited by 75 publications

References 103 publications

The multi-dimensional nature of vocal learning

The multi-dimensional nature of vocal learning

The many functions of vocal learning

Testing the strength and direction of selection on vocal frequency using metabolic scaling theory

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