A METHOD FOR SIMPLIFYING LARGE ECOSYSTEM MODELS

Abstract Simplifying large ecosystem models is essential if we are to understand the underlying causes of observed behaviors. However, such understanding is often employed to achieve simplification. This paper introduces two model simplification methods that can be applied without requiring intimate prior knowledge of the system. Their utility is measured by the resulting values of given model diagnostics relative to those of the large model. The first method is a simple automated procedure for nondimensionalizing large ecosystem models, which identifies and eliminates terms that have little effect on model diagnostics. Some of its limitations are then addressed by the rate elimination method, which measures the relative importance of model terms using least‐squares regression. The methods are applied to a model of the nitrogen cycle in Port Phillip Bay, Victoria, Australia. The rate elimination method provided more insights into the causal relationships built into the model than the nondimensionalizing method. It also allowed the reduction of the model's dimension. Thus it is a useful first step in model simplification.