Neighbor density-dependent facilitation promotes coexistence and internal oscillation

The ability of species to form diverse communities is not fully understood. Species are known to interact in various ways with their neighborhood. Despite this, common models of species coexistence assume that per capita interactions are constant and competitive, even as the environment changes. In this study, we investigate how neighbor density-dependent variation in the strength and sign of species interactions changes species and community dynamics. We show that by including these sources of variation, predictions of ecological dynamics are significantly improved compared to outcomes of typical models that hold interaction strengths constant. We compared how well models based on different functions of neighbor density and identity did in describing population trajectories (i.e., persistence over time) and community dynamics (i.e., temporal stability, synchrony and degree of oscillation) in simulated two-species communities and a real diverse annual plant system. In our simulated communities, we found the highest level of coexistence between species pairs when species interactions varied from competitive to facilitative according to neighbor density (i.e., following a sigmoid function). Introducing within-guild facilitation through a nonlinear bounded function allowed populations, both simulated and empirical, to avoid extinction or runaway growth. In fact, nonlinear bounded functions (i.e., exponential and sigmoid functions) predicted population trends over time within the range of abundances observed over the last 10 years. With the sigmoid function, the simulated communities of two species displayed a higher probability of synchrony and oscillation than other functional forms. These simulated communities did not always show temporal stability but were predicted to coexist. Overall, varying species interactions lead to realistic ecological trajectories and community dynamics when bounded by asymptotes based on neighbor density. These findings are important for advancing our understanding of how diverse communities are sustained and for operationalizing ecological theory in the study of the real world.