Experimental evolution is a powerful method that has been instrumental for revealing core mechanisms of adaptation and coevolution. It has mostly been used in very simple settings of one or two species. Yet, it is now increasingly being employed in more complex community settings that include indirect effects, higher-order interactions, and multidimensional selection typical of natural communities. Here we synthesize the emerging field of experimental evolution in communities and show how community context reshapes selection and evolutionary trajectories, beyond what single-species or pairwise designs predict. We conducted a systematic literature survey targeting multi-species, multi-generation evolution, identifying 100 such studies with the number increasing recently. Despite this progress, most experiments are biased toward microbial systems and competitive interactions, leaving major gaps for predicting evolution in realistic communities. We discuss community ecology concepts in the light of experimental evolution, together with designs that address these concepts. We emphasize three main research areas: indirect and higher-order interactions that make selection multidimensional, eco-evolutionary feedbacks linking trait change to community dynamics, and genetic constraints that shape responses across interaction networks. We then discuss routes to increase ecological realism with field experiments and conclude by outlining key research fronts for experimental evolution in communities.
Montbel et al. (2026) studied this question.