Understanding the manner in which communities develop over time is a central goal of Ecology. Traditionally, successional dynamics are investigated using either empirical or theoretical techniques but not both. Here I combine field data of post-disturbance community development with Markov analyses in order to broaden our understanding of the mechanisms driving observed differences in successional rate and trajectory.  I evaluate successional outcomes across variability in key factors that are known to have significant impacts on both population and community dynamics. These factors are: Propagule input, life history characteristics, size of initial disturbance and geographic location.  My analysis uses transition frequencies between community states to assess the prevailing mechanisms of species interaction (Facilitation, Inhibition or Tolerance) throughout the course of succession and then determine the extent to which these mechanisms contribute to the rate and outcome of succession.  Preliminary results suggest that the rocky intertidal of the California coast is an appropriate system in which these phenomena may be examined since calculated community transition frequencies of control (undisturbed) plots in the turfweed Endocladia muricata zone accurately predict independently observed species abundances.  This model will be used to compare simulated recovery trajectories across multiple geographic locations and intertidal taxa and can be manipulated to incorporate stochastic factors such as recruitment. This combination of empirical data and predictive modeling will provide a more complete understanding of the relative importance of the processes driving patterns of ecological succession, a process that is both fundamental and ubiquitous in nature.