Coevolution has been a fundamental topic in evolutionary biology for over 50 years, but the focus has been on pairwise coevolution which occurs only in specific natural systems. Diffuse coevolution, where many species create selective effects on each other, is hypothesized to be more common, but is difficult to detect and study because of the large number of interactions. Quantitative methods that would indicate the presence of diffuse coevolution largely rely on covariance of genetic or phenotypic data for one-to-many species relationships, but outcomes of community-scale evolutionary processes should be apparent in the structure of community-level ecological interactions. Our goal is to develop methods to identify community-level patterns that serve as a signature of diffuse coevolution to complement existing methods.
Results/Conclusions
To fill this gap, we have developed a mathematical model based on plant-herbivore systems with multiple species in each guild that includes the chemical profiles of plants and the diet breadth of the herbivores. This model allows us to control the diversity of chemicals in the system, the costs of their production or detoxification, and the strength of selection created by herbivory. The number of species is the system is not predetermined, but evolves in tandem with the chemical complexity.
With a single chemical, the model reproduces results of pairwise coevolution models, with escalation when costs are low, cycles when costs are high, and low plant and herbivore diversity. With many chemicals and low costs, both plants and herbivores escalate their overall chemical profile, creating populations where each individual has a large chemical or detoxification repertoire, and which maintain a species diversity lower than the chemical diversity. With many chemicals and high costs, individual chemicals show coevolutionary cycles, and each species has a lower chemical diversity.
Depending on the potential chemical diversity and costs, the patterns of association between plants and herbivores are obscured by lags in the evolutionary response of species created by mutation limitation and linkage between components of the chemical profile. In effect, these create an interaction between the "ghost of defenses past" with the "ghost of herbivory past." By understanding the model dynamics, we can derive a statistical approach based on community structure that identifies the signature of diffuse coevolution. We will calibrate this approach to our model output, and then apply to data for well-studied plant-herbivore systems.