A fundamental fact about mutualisms is that these mutually beneficial interactions often harbor cheaters that benefit from the use of resources and services without providing any positive feedback to other species. The role of cheaters in the evolutionary dynamics of mutualisms has long been recognized, yet their broader impacts at the community level, beyond species they directly interact with, is still poorly understood. Because mutualisms form networks often involving dozens of species, indirect effects generated by cheaters may cascade through the whole community, reshaping trait evolution. Here, we study how cheating interactions can influence coevolution in mutualistic networks. We combined a coevolutionary model, empirical data on animal-plant mutualistic networks and numerical simulations to show that high trait disparity emerges as a consequence of the negative effect of cheaters on victim fitness, which in turn fuels selection favoring victim traits that are increasingly different from the cheaters' traits. Intermediate levels of cheating interactions in a network can lead to the formation of groups of species phenotypically similar to each other and distinct from species in other groups, generating clustered trait patterns. The resulting clustered trait pattern, in turn, changes the pattern of interaction in simulated networks, fostering the formation of modules of interacting species and reducing nestedness. Our results indicate that directional selection imposed by cheaters on their victims counteracts selection for trait convergence imposed by mutualists, leading to the emergence of modules of phenotypically similar interacting species but phenotypically distinct from other modules. Based on these results, we suggest that cheaters might be a fundamental missing element for our understanding of how multispecies selection shapes the trait distribution and structure of mutualistic networks.

A fundamental fact about mutualisms is they are often explored by species that explore resources and services provided by individuals without providing any benefit. The role of these cheaters on the evolutionary dynamics of mutualisms has long been recognized, but cheaters may not only affect the species they explore. Because mutualisms form networks that often involve dozens to hundreds of species in a given site, indirect effects generated by cheaters may cascade through the network, reshaping trait evolution. Here, we study how harboring cheating interactions can influence coevolution in mutualistic networks. We combine a coevolutionary model, data on empirical networks of mutualisms, and numerical simulations to show that the higher frequency of cheating interactions can lead to the formation of groups of species phenotypically similar to each other but distinct from other groups of species, leading to higher trait disparity. The clustered trait patterns generated by cheaters, in turn, change the patterns of interaction in simulated networks, fostering the formation of modules of interacting species. Our results indicate that cheaters of mutualisms can contribute to generate phenotypic clusters in mutualisms, counteracting selection for convergence imposed by mutualistic patterns, and favoring the emergence of modules of interacting species.

is characterized by groups of species phenotypically similar to each other but distinct from other groups of species. Finally, the evolution of traits, driven by exploitation interactions, changes the organization of interactions in simulated networks, forming interaction modules. Our results indicate that lifestyles that explore mutualisms can contribute to the maintenance of the phenotypic disparity and to the formation of modules of interacting species.