Coral community dynamics and disturbances : a modelling approach for Caribbean coral reefs

Abstract

The capacity of reefs to recover after disturbance is fundamental to prediction of their stability. This is particularly relevant now, following the global decline of reefs during the last decades. A discrete, spatially explicit model (probabilistic cellular automaton) was developed to simulate a Caribbean coral community. Community complexity was generated from behaviour of fundamental units of corals, the polyps. Regarding background disturbance, area disturbed and patch size were investigated; both were equally important in driving coral community structure and diversity. A powerlaw model was developed to predict natural disturbances, and implemented in later testing of system dynamics. Corals were assigned differential susceptibilities to background disturbances. Results assessed against field data showed that most modelled species had realistic colony size frequency distributions (though 20% had insufficient comparison data). Following model development, recovery from single impacts (simulated warming events) was tested. Model responses indicate importance of local setting to community resilience. Individual susceptibility of species was mediated by life history strategy investment. Application of a warming sequence of predicted anomalies for this century was then introduced. Community composition changed betwee1 0-40 years from predominantly persistent, large, slow growing species to small, fecund, fast growing species. After 40 years a phase shift occurred in which algae dominated the community. It is concluded that the future may herald declines in the main Caribbean reef-building species, in ways that match several previous but largely untested speculations. This model indicates that there will be serious implications to reefs, including their numerous commercially important species. The model includes all known major life history attributes of the corals, based on real data. Structural properties of the model were tested for stability and computational efficiency. Disturbances of several types were investigated; natural background disturbance, and warming events, both as single and repeated incidents to assess recovery dynamics in the light of ongoing, intensifying climate-mediated global changes