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

Cite this dataset

Crouch, Nicholas M.A.; Mason-Gamer, Roberta J.; Crouch, Nicholas M. A.; Mason‐Gamer, Roberta J. (2019). Data from: Identifying ecological drivers of interspecific variation in song complexity in songbirds (Passeriformes, Passeri) [Dataset]. Dryad.


A diversity of selective pressures and stochastic processes have likely created substantial variation in song structure, creating difficulties in quantifying the influence of specific ecological factors. This problem is further compounded by differences in study taxa and methods of data analysis between studies. Large comparative studies offer the potential to mitigate some of these methodological difficulties by maximizing the power of statistical analyses and minimizing the probability of misidentifying the magnitude and direction of relationships between independent and dependent variables. In this study, we quantified song complexity for 367 species of globally distributed songbirds (Passeriformes, Passeri). We quantified eight individual acoustic variables that have previously been linked to audio complexity which we analyzed independently, and after applying multivariate statistics to the variables. We used Bayesian linear mixed effect models to test multiple hypotheses regarding song complexity: that it should be greater in open habitats, in migratory species, for sexually monomorphic species, at higher latitudes and altitudes, and that it should co‐vary with clutch size characteristics. Our results challenge perceptions of the effect of habitat structure on song complexity; for instance, counter to expectation, we found songs in closed environments to have reduced syllable diversity. Additionally, our results suggest song complexity may not be ubiquitously a means of communicating male quality, with no significant difference between recordings from monomorphic and dimorphic species. By estimating song complexity in multiple ways, and quantifying these over large taxonomic and spatial scales, we are able to gain a more nuanced understanding of how song complexity is potentially affected by a range of biotic and abiotic factors. Our results also suggest that caution is required when making generalized statements about the relative influence of different factors on song complexity; more densely‐sampled, group‐specific studies are necessary complements to this taxonomically broad analysis.

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