Uncovering Cryptic Coevolution.

Abstract

AbstractStudies of coevolution in the wild have largely focused on reciprocally specialized species pairs with striking and exaggerated phenotypes. Textbook examples include interactions between toxic newts and their garter snake predators, long-tongued flies and the flowers they pollinate, and weevils with elongated rostra used to bore through the defensive pericarp of their host plants. Although these studies have laid a foundation for understanding coevolution in the wild, they have also contributed to the widespread impression that coevolution is a rare and quirky sideshow to the day-to-day grind of ecology and evolution. In this perspective, we argue that the focus of coevolution has been biased toward the obvious and ignored the cryptic. We have focused on the obvious-studies of reciprocally specialized species pairs with exaggerated phenotypes-mainly because we have lacked the statistical tools required to study coevolution in more generalized and phenotypically mundane systems. Building from well-established coevolutionary theory, we illustrate how model-based approaches can be used to remove this barrier and begin estimating the strength of coevolutionary selection indirectly using routinely collected data, thus uncovering cryptic coevolution in more typical communities. By allowing the distribution of coevolutionary selection to be estimated across genomes, phylogenies, and communities and over deep timescales, these novel approaches have the potential to revolutionize the way we study coevolution. As we develop a road map to these next-generation approaches, we highlight recent studies making notable progress in this direction.