Use of Bayesian analysis with individual‐based modeling to project outcomes of coral restoration

Various approaches to coral restoration have been developed to help increase rate of reef recovery from perturbations, among the most common of which is coral transplantation. Success is often evaluated based on short‐term observations that capture only the initial phase of space colonization by coral transplants. Here, an individual‐based model is developed to quantify uncertainty in future trajectories in experimental plots given past observations. Empirical data were used to estimate probabilistic growth, survival, and fission rates of Acropora pulchra and A. intermedia (order Scleractinia) in a sandy reef flat (Bolinao, Philippines). Simulations were initialized with different densities (25 or 50 transplants per species per 16 m 2 ) to forecast possible coral cover trajectories over a 5‐year period. Given current conditions, there is risk of local extinction which is higher in low‐density plots for both species, and higher for A. intermedia compared to A. pulchra regardless of density. While total coral cover is projected to increase, species composition in the future is more likely to be highly uneven. The model was used to quantify effect on recovery rate of protection from pulse anthropogenic disturbances, given different initial transplantation densities. When monitoring data are limited in time, stochastic models may be used to assess whether the restoration trajectory is heading toward the desired state and at what rate, and foresee system response to various adaptive interventions.