Daniel S. Caetano and Jeremy M. Beaulieu (Feb 2020)
Phylogenetic comparative analysis of cricket songs show strong autocorrelation of rates among sequence positions
“Comparative analyses of phenotypic sequences using phylogenetic trees”
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Cricket calls are a very common background soundtrack of evening hikes. In field crickets (genus Gryllus), the males relentlessly rub their wings producing the signature chirp sound. The temporal pattern of chirps, or the timing of sounds that comprise the overall cricket melody, varies among different species and is often used by taxonomists to identify and describe species. In this study, Drs. Daniel Caetano and Jeremy Beaulieu at the University of Arkansas combined a robust phylogeny depicting relationships among Gryllus crickets with a novel statistical approach to characterize the evolutionary dynamics of a cricket’s melody. For instance, does the variation among cricket melodies emerge as a consequence of independent evolution of species-specific chirps? Or has the variation among cricket songs evolved by changing neighboring blocks of linked chirps? The authors found strong evidence for correlated changes among neighboring regions of the songs observed within Gryllus. In other words, the diversity of cricket melodies was likely produced by coordinated evolutionary changes within specific chirp blocks. Another important finding was that the silence intervals between each block of chirps were differentiated as the most evolutionary labile attribute of the melodies. Taken together, these results confirm previous work which suggested that cricket melodies generally evolve through the expansion and contraction of both neighboring chirp and silence blocks.
Abstract
Phenotypic sequences are a type of multivariate trait organized structurally, such as teeth distributed along the dental arch, or temporally, such as the stages of an ontogenetic series. Unlike other multivariate traits, the elements of a phenotypic sequence are distributed along an ordered set, which allows for distinct evolutionary patterns between neighboring and distant positions. In fact, sequence traits share many characteristics with molecular sequences, although important distinctions pose challenges to current comparative methods. We implement an approach to estimate rates of trait evolution that explicitly incorporates the sequence organization of traits. We apply models to study the temporal pattern evolution of cricket calling songs. We test whether neighboring positions along a phenotypic sequence have correlated rates of evolution or if rate variation is independent of sequence position. Our results show that cricket song evolution is strongly autocorrelated and models perform well when used with sequence phenotypes even under small sample sizes. Our approach is flexible and can be applied to any multivariate trait with discrete units organized in a sequence-like structure.