A stochastic model for seagrass (Zostera muelleri) in Port Phillip Bay, Victoria, Australia

Recently, there have been attempts to identify a set of key environmental indicators for Victoria’s marine and coastal environments. The recommendation that seagrass density and abundance be used as indicators requires that the effects on seagrass resulting from changes in the physical environment be predictable. This paper presents a stochastic population model for Zostera muelleri in Port Phillip Bay, Victoria. Building the model identified a number of issues that relate to constructing models for modular organisms. Of particular importance are the assumptions made when devising demographic structure and modelling complex population ecology in data poor environments. The project has provided a preliminary framework for the evaluation of potential environmental indicators and the monitoring programs developed for them. Using the probability of falling below a range of population densities, we were able to specify a background risk against which impacts may be measured. In this case, there was a 50% chance that the population density would fall below 230 individuals per m2 at least once in the next 20 years. Simulations representing the impacts of turbidity plumes are presented.