Divide and conquer: Configuring submodels for valid and efficient analyses of complex simulation models

Individual-based modeling is considered an important tool in ecology and other disciplines. A major challenge of individual-based modeling is that it addresses complex systems that include a large number of entities, hierarchical levels, and processes. To represent these, individual-based models (IBMs) usually comprise a large number of submodels. These submodels might be complex by themselves and interact with each other in many ways, which in turn can affect the overall system behavior in ways that are not always easy to understand. As a result, both the validity and credibility of IBMs can be limited. We here demonstrate how a cascaded design of simulation experiments (cDOE) may support the validity and efficiency of the analysis of IBMs and other ecological simulation models. We take a systematic approach that adopts a divide-and-conquer strategy. In a preparatory phase, submodels and their parameters are configured in “subexperiments”. Consequently, the “top-level experiments” of the simulation model can assess the research questions in a more valid and efficient way. Our strategy thus supports the structural realism of individual-based models because both the behavior of their main components and the relationships between these components are explicitly addressed.