Does increased model complexity improve description of phosphorus dynamics in a large treatment wetland?

Abstract

As the structure of ecological models grows more complex, it becomes increasingly important to identify the appropriate level of complexity for reliable process description and prediction. Here, a suite of mechanistic biogeochemical models with different levels of complexity for representing phosphorus cycling processes was developed and tested against observations from a large treatment wetland. The study site was the 147-ha Cell 4 of Stormwater Treatment Area 1 West, which was designed to help protect the greater Everglades, FL, USA, from nutrient over-enrichment. Six biogeochemical models of differing complexity were coupled with a pre-calibrated two-dimensional hydrodynamic model of Cell 4 and tested against field data. We provide guidance for evaluating a set of models with varying level of complexity using key model attributes that influence the suitability of a model or a set of models. Considerations of model accuracy, complexity, and explanatory depth are combined into a single indicator of model effectiveness. Results revealed that the most complex model structure may not necessarily be the most effective in simulating the dynamics of total phosphorus (TP) concentrations in the wetland. The rate of improvement in the model performance decreased as model complexity increased. Although the most complex model reproduced the field observations best, the marginal improvement in model performance compared to simpler models was outweighed by the higher costs of increased complexity. Highly detailed representations of system structures may not be useful to simulate TP dynamics in treatment wetlands if comprehensive data sets are not available to constrain each pathway. It is crucial for model developers and users to evaluate model structures of differing complexity to identify the appropriate level of complexity for given data and questions of interest.