Macroalgae are important components of the coral reef. They are part of the benthic community that play roles in productivity and framework build-up. Their interactions with other benthos, particularly hard corals are also of interest due to the widespread recognition that a phase shift has occurred, and is still occurring in coral reefs. That is, the abundance of hermatypic corals decreases, as large fleshy macroalgae increase. Thus, it is important to understand the mechanisms of this phase shift as they pose a big impact on reefs. This phenomenon can be approached by elucidating the dynamics of the macroalgal community, as well as their competitive interactions with corals. An ABM model will attempt to capture these dynamics using information obtained from both comprehensive literature mining and field work.

The agent-based simulation modeling approach is appropriate for depicting the dynamics of benthic macroalgae because it can incorporate space and local interactions that have been shown to be important. This approach has also been successfully applied to forest simulation modeling, e.g., the SORTIE forest model ( (Deutschman et al. 1997) ) and the U.S. Department of Agriculture Forest Vegetation Simulator.

This model would represent macroalgae – whether as species or as functional group – such that their growth pattern would be captured. Figure 1 illustrates the simple growth pattern of a filamentous alga using its modular units as building blocks. Collado-Vides et al. (1997) have simulated the clonal growth of Bostrychia radicans, a species associated with mangrove roots, using architectural growth rules and Lindenmayer systems.

Fig. 1. Simple model of the growth pattern of a filamentous algae where the repeating module is a single cell represented by a single line.

These individual level characteristics of morphology, growth, mortality and competitive ability of different macroalgal groups would be programmed as affected by extrinsic factors like herbivory, nutrients and light. Then from the interaction of the organisms, the population and community-level dynamics of biomass, cover, and diversity would be observed. 

These higher order dynamics could then feedback on the extrinsic factors (Figure 2).

Figure 2. A preliminary concept of what the model will attempt to capture.

A Java2-based prototype of the agents as described above will be made available in this page.

References

Collado-Vides, L., G. Gómez-Alcaraz, G. Rivas-Lechuga, and V. Gómez-Gutierrez. 1997. Simulation of the clonal growth of Bostrychia radicans (Ceramiales-Rhodophyta) using Lindenmayer systems. BioSystems 42:19-27.

Deutschman, D. H., S. A. Levin, C. Devine, and L. A. Buttel. 1997. Scaling from trees to forests: analysis of a complex simulation model. Science Online.