Evolutionary rescue can maintain an oscillating community undergoing environmental change.

The persistence of ecological communities is challenged by widespread and rapid environmental change. In many cases, persistence may not be assured via physiological acclimation or migration and so species must adapt rapidly in situ. This process of evolutionary rescue (ER) occurs when genetic adaptation allows a population to recover from decline initiated by environmental change that would otherwise cause extirpation. Community evolutionary rescue (CER) occurs when one or more species undergo a rapid evolutionary response to environmental change, resulting in the recovery of the ancestral community. Here, we study the dynamics of CER within a three-species community coexisting by virtue of resource oscillations brought about by nonlinear interactions between two species competing for a live resource. We allowed gradual environmental change to affect the traits that determine the strength and symmetry of the interaction among species. By allowing the component species to evolve rapidly, we found that: (i) trait evolution can allow CER and ensure the community persists by preventing competitive exclusion during environmental change, (ii) CER brings about a change in the character of the oscillations (period, amplitude) governing coexistence before and after environmental change, and (iii) CER may depend on evolutionary change that occurs simultaneously with or subsequently to environmental change. We were able to show that a change in the character of community oscillations may be a signature that a community is undergoing ER. Our study extends the theory on ER to a world of nonlinear community dynamics where-despite high-frequency changes of population abundances-adaptive evolutionary trait change can be gradual and directional, and therefore contribute to community rescue. ER may happen in real, complex communities that fluctuate owing to a mix of external and internal forces. Experiments testing this theory are now required to validate our predictions.