Song structure, not high‐frequency song content, determines high‐frequency auditory sensitivity in nine species of New World sparrows (Passeriformes: Emberizidae)

Abstract

Summary1. The evolution of vocal signals can be constrained by a host of factors including habitat effects on sound propagation, morphology of sound-producing structures and phylogenetic relationships among species. Here, we asked whether auditory sensitivity over a broad range of frequencies correlates with the spectral content of conspecific vocalizations, or whether it is constrained by the overall structure of vocalizations, habitat effects on sound propagation or relatedness among species. 2. We studied nine New World sparrows (Passeriformes: Emberizidae) including three open-habitat species, three scrub-like habitat species and three forest species. For each habitat, one species had pure-trilled songs, another had tonal songs and another had complex songs with tones, trills and amplitude-modulated buzzes. 3. As predicted by the acoustic adaptation hypothesis, song spectral properties (specifically frequency and entropy) had the highest values in open-habitat species and the lowest values in forest species. 4. Based on our results from song analyses, and the sender-receiver matching hypothesis, we predicted that open-habitat species would be more sensitive to high-frequency sounds compared to forest species. Contrary to this prediction, habitat and high-frequency song content had little effect on audiogram shape. Song type, however, had a strong effect, with species that produce complex songs showing higher sensitivity to high-frequency sounds than all other species. 5. Our results suggest that the use of song frequency by receivers depends on song structure and not necessarily on song spectral content. Therefore, our current understanding of how signal-processing mechanisms should match signal properties appears to be too simple. When thinking about the evolution of signal-processing mechanisms, the multidimensionality of signals, and how the different dimensions can interact, should be considered.

Habitat-related differences in auditory processing of complex tones and vocal signal properties in four songbirds

“…Lohr et al (2003) found a similar pattern in these three species, although enhanced withinspecies discrimination was only evident at high signal-tonoise ratios. In addition, we have recently shown that auditory sensitivity to high-frequency sounds is better predicted by vocal complexity than by high-frequency vocal content in sparrows (Vélez et al 2015). Together, these results support the idea that auditory processing mechanisms are correlated with vocal performance.…”

“…Sex was determined using plumage patterns in nuthatches and house sparrows, and wing chord in titmice [males ≥80 mm (Lucas et al 1993)]. We took a tissue sample from an outer retrix of the white-crowned sparrows and used the protocol of Griffiths et al (1998) for genetic sexing (also see Vélez et al 2015). Only adults were tested.…”

Identifying ecological drivers of interspecific variation in song complexity in songbirds (Passeriformes, Passeri)

“…Other factors co‐vary with habitat type, so alternative hypotheses may explain the observed relationship of PC1 and open habitats. One potentially confounding factor is higher species richness in more complex habitats (Roth , Kroodsma ), which leads to greater background noise (Hart et al ), meaning that songs with fewer unique syllables are more easily recognized by conspecifics (Emlen , Singh and Price ). Higher species richness can also lead to increased acoustic competition between taxa, leading to a negative relationship with acoustic complexity and/or repertoire size (Naugler and Ratcliffe ).…”

“…Finally, for all recordings, we defined singing speed as the total number of syllables produced divided by song length. To reduce the dimensionality of the data, we performed a principal components (PC) analysis on the eight quantified elements of complexity (Gil and Slater , Lachlan et al , Vélez et al , Hill et al ). We retained the first two principal components axes (PC1 and PC2) which explained the majority of the variation in the data.…”

“…Beyond that, there is no standardized definition of complexity, and the definition varies among studies, but it generally involves the number of syllables, the pace at which the syllables are sung (sometimes referred to as ‘syllable rate’), and variation in the characteristics of the syllables themselves as quantified via spectral analysis (Baker ). Some characteristics are more commonly quantified than others – for example, the range in frequency (bandwidth) of a syllable, but studies are increasingly using more parameters to describe syllables, such as spectral complexity (Tchernichovski et al , Vélez et al , Hill et al ). Quantifying a greater range of parameters allows for a better measure of a syllable's complexity (Fig.…”