Recovering phylogenetic signal from frog mating calls

Abstract

Few studies have tried to analyse the phylogenetic information contained in frog mating calls. While some of those studies suggest that sexual selection deletes any phylogenetic signal, others indicate that frog calls do retain phylogenetic informative characters. Discordant results can be the outcome of disparate rates of character evolution and evolutionary plasticity of call characters in different groups of frogs, but also the result of applying different coding methods. No study to date has compared the relative performance of different coding methods in detecting phylogenetic signal in calls, hampering thus potential consilience between previous results. In this study, we analyse the strength of phylogenetic signal in 10 mating call characters of 11 related species of frogs belonging to three genera of Andean and Amazonian frogs (Anura: Terrarana: Strabomantidae). We use six quantitative characters (number of notes per call, note length, call length, number of pulses per note, fundamental frequency and dominant frequency) and four qualitative ones (presence/absence of: pseudopulses, frequency modulation in notes, amplitude modulation in notes and amplitude modulation in pulses). We code quantitative characters using four different coding and scaling methods: (i) gap-coding, (ii) fixed-scale, (iii) step-matrix gap-weighting with between-characters scaling, and (iv) step-matrix gap-weighting with between-states scaling. All four coding methods indicate that frog calls contain phylogenetic information. These results suggest that divergent selection on frog mating calls may not always be strong enough to eliminate phylogenetic signal. However, coding methods strongly affect the amount of recoverable information. Step-matrix gap-weighting with between-characters scaling and gap-coding are suggested as the best methods available for coding quantitative characters of frog calls. Also, our results indicate that the arbitrariness in selecting character states and the method for scaling transitions weights, rather than the number of character states, is what potentially biases phylogenetic analyses with quantitative characters.