Development Of Criteria For Simplifying Ecological Risk Models

Tropical seagrass habitats of the Great Barrier Reef are influenced by a complex suite of parameters. Recently there has been particular interest in the impact of land-derived runoff to the long-term viability of tropical seagrass habitats. Seagrass ecosystems are highly variable and poorly understood. A decision support tool that copes sufficiently with knowledge gaps and uncertainty was required to support the management of this complex stochastic system. We chose to develop a quantitative Bayesian Network (BN) as the risk management decision support tool for tropical seagrass. The objective of the decision support tool was to improve understanding of the current state of the seagrass ecosystem at risk, the impact of multiple threats to seagrass, and/or the impact of multiple management choices on seagrass health. A Bayesian Network was preferred for decision support tool development because BNs can summarize small-scale, unpredictable, and unmanageable processes via probabilistic expressions which can be updated as new information comes to hand. The capacity of BNs to summarize system processes encourages analytic focus to be directed toward the most critical factors.