Structural stability determines evolutionary stability in mutualistic model ecosystems

Understanding the factors that influence the persistence and stability of complex ecological networks is a central focus of ecological research. Recent research into these factors has predominantly attempted to unveil the ecological processes and structural constraints that influence network stability. Comparatively little attention has been given to the consequences of evolutionary events, despite the fact that the interplay between ecology and evolution has been recognised as fundamental to understand the formation of ecological communities and predict their reaction to change. In light of current environmental challenges, there is a compelling need for a quantitative framework to predict biodiversity loss under environmental perturbations while accounting for evolutionary processes. We extend existing mutualistic population dynamical models by incorporating evolutionary adaptation events to address this critical gap. We relate ecological aspects of mutualistic community stability to the stability of persistent evolutionary pathways. Our findings highlight the significance of the structural stability of ecological systems in predicting biodiversity loss under both evolutionary and environmental changes, particularly in relation to species-level selection. Notably, our simulations reveal that the evolution of mutualistic networks tends to increase a network-dependent parameter termed critical competition, which places systems in a regime in which mutualistic interactions enhance structural stability and, consequently, biodiversity. This research emphasizes the pivotal role of natural selection in shaping ecological networks, steering them towards reduced effective competition below a critical threshold where mutualistic interactions foster stability. The outcomes of our study contribute to the development of a predictive framework for eco-evolutionary dynamics, offering insights into the interplay between ecological and evolutionary processes in the face of environmental change.