A Markov-chain transition model (FORSUM) and Monte Carlo simulations were used to simulate the succession patterns and predict a long-term impact of flood on the forest structure and growth in the floodplain of the Upper Mississippi River and Illinois River. Model variables, probabilities, functions, and parameters were derived from the analysis of two comprehensive field surveys conducted in this floodplain. This modeling approach describes the establishment, growth, competition, and death of individual trees for modeled species on a 10,000-ha landscape with spatial resolution of 1 ha. The succession characteristics of each Monte Carlo simulation are summed up to describe forest development and dynamics on a landscape level. FORSUM simulated the impacts of flood intensity and frequency on species composition and dynamics in the Upper Mississippi River floodplain ecosystem. The model provides a useful tool for testing hypotheses about forest succession and enables ecologists and managers to evaluate the impacts of flood disturbances and ecosystem restoration on forest succession. The simulation results suggest that the Markov-chain Monte Carlo method is an efficient tool to help organize the existing data and knowledge of forest succession into a system of quantitative predictions for the Upper Mississippi River floodplain ecosystem. ?? 2009 Elsevier B.V.