Testing the evolutionary driving forces on display signal complexity in an Asian agamid lizard

Abstract

Abstract Elucidating the factors behind the evolution of signal complexity is essential in understanding animal communication. Compared to vocal and color signals, dynamic display signals only start to attract attention recently. In this study, we tested the social complexity and background noise hypotheses on the evolution of dynamic display signal complexity. We collected displays videos from twelve populations across the distribution range of the Asian agamid lizard, Phrynocephalus przewalskii. Their various components (tail coil, tail lash, body turning, and limb flapping) were quantified. Furthermore, we measured the population density and sexual size dimorphism (SSD), as estimates of social complexity, and vegetation height, as estimate of background noise. Using linear mixed models, we tested associations between measurements of signal component variability (e.g. coefficient of variation of maximum speed Limb flapping), display (as a whole) complexity (e.g. Component change rate) and estimates of social complexity and background noise. Several significant associations were detected, including between CV of maximum speeds of body turning/limb flapping and SSD (negative), between component change rate and background noise (positive). Several other associations were sex-dependent and the trends were often opposite between the sexes. Our data are consistent with both social complexity and background noise hypotheses, and our research provides direct evidence on the level-specific links among display complexity, social complexity and background noise.