Abstract

A spatially explicit model of coral community dynamics has been developed, based around a cellular automaton, with additional processes impacting upon it such as recruitment and disturbance. It represents a homogeneous plot on a Caribbean fore-reef slope with 10 coral species. Complexity that arises from species behaviour is shown to be realistic, generated by simple, repeated actions of the base units (coral polyps). The spatial resolution used here is high, and allows detailed demographic dynamics to be examined. Input parameters were based on values extracted from the literature for all processes (except disturbance, which is examined here). Natural background disturbance processes were explored in order to understand their importance in structuring coral communities and populations. Initially two disturbance parameters were investigated: spatial extent (proportion of plot affected) and size of disturbed patches. Both were found to be equally important in driving coral community structure, and subsequent diversity. The latter also influenced coral population size structure by altering mortality regimes. A power law model was introduced to distribute the total area disturbed into patches; its parameters were tuned using emergent size structure of the coral Agaricia spp. Differential mortality for species was also included, based on colony size and tissue regeneration rates. Model performance was assessed by running simulations with different levels of background disturbance, and resulting population size structures of each species were compared to field observations. Seven species compared extremely well, while accuracy of a further two could not be quantified due to a lack of suitable field data. Only one species, Siderastrea siderea, had unrealistic population size structures, which is discussed with respect to the life history of this species. Applications of this model include predicting communities under changing disturbance regimes, and colonisation and recovery processes following acute disturbances.

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