Phylogenetic analysis and alignment of behavioral sequences by direct optimization

We propose a new approach to consider behavioral data in phylogenetic analyses. We show that behavior can be described as sequences of repeated units, and that these behavioral sequences can be analyzed under direct optimization in a way similar to molecular data. This approach provides repeatable hypotheses of homology for behavior when traditional criteria result in multiple alternatives or do not allow to propose any. We exemplify this approach by analyzing the calling songs of the North American Gryllus species under direct optimization. We first use two alternative coding schemes to describe the temporal patterns of the songs as sequences of repeated simple behaviors. We submit these behavioral data to phylogenetic analysis under direct optimization, first as separate analyses, and second in combination with molecular data and additional acoustic characters. The results show that the coding option that consists of discretizing the silent parts of the songs: (1) allows description of the songs in a more precise way; (2) discriminates further the songs between species; and (3) enhances the phylogenetic content of the behavioral sequences. Our study demonstrates that behavioral sequences can be transformed so that they can be used in genuine phylogenetic analysis, in isolation or combined with other data sets. We discuss how this approach may provide phylogenetic signal where none or little is usually available, and the applications to the study of the evolution of behavioral evolution.