Calibration and evaluation of individual-based models using Approximate Bayesian Computation

It is often desirable to compare models to see whether all component modules are necessary. Here, we used ABC model selection to compare the full model with a simplified version which removed the earthworm's movement and much of the energy budget. We are able to show that inclusion of the energy budget is necessary for a good fit to the data. We show how our methodology can inform future modelling cycles, and briefly discuss how more advanced versions of ABC may be applicable to IBMs. We conclude that ABC has the potential to represent uncertainty in model structure, parameters and predictions, and to embed the often complex process of optimising an IBM's structure and parameters within an established statistical framework, thereby making the process more transparent and objective.