Subtidal communities on hard substrates are characterized by high diversity, intense competition for space, small-scale turnover, and large-scale stability. This research project will develop a series of four models for subtidal communities, using a detailed, long-term data set from the Gulf of Maine. Model I is a linear Markov chain model describing the replacement of individuals within the community and using tools from stochastic process theory to characterize succession and convergence in the community and develop perturbation analysis to characterize the response to changes in transition probabilities. Model 2 is a nonlinear version of Model 1; it includes density-dependence in rates of transition and will incorporate new, maximum likelihood-based methods for parameter estimations. Model 3 is a stochastic cellular automaton, which embeds the framework of Models I and 2 in an explicit spatial setting. This model will be used to investigate the effects of spatial pattern in subtidal communities. Model 4 is also a cellular automaton, but is developed directly from measurements of the mechanisms (recruitment, growth, disturbance, and competition) that generate species transitions. This research will provide new methods for studying community dynamics in general, and an increased understanding of rocky subtidal communities.
