Context-oriented model validation of individual-based models in ecology: A hierarchically structured approach to validate qualitative, compositional and quantitative characteristics

Validation constitutes a vital process in model development and application, as it ensures the applicability of a model for the intended purposes and trustworthy results within the range of model assumptions. Commonly, independent empirical data sets are statistically compared with the generated model results, which is an adequate approach for models which operate on a single hierarchical level, such as most equation-based models. Individual-based models (IBM) can operate on different organisational levels synchronously and have an inherent complex and variable interaction structure for many applications. Thus a plain comparison of data congruity on the result levels might leave too many questions unanswered. However, a more comprehensive assessment of model validity can require additional investigations which encompass also qualitative and structural relationships. Here we describe a hierarchically structured validation which is oriented towards the investigated context of the model and allows organising the validation process in close relation to the different hierarchical levels which are covered in the model. The context oriented organisation protocol for validation includes the following steps: (1) assessing the different model levels separately, then, (2) applying a set of different techniques such as visual inspection, statistical comparison, involvement of experts, aggregation of data on higher integration levels and experimental validation. The context oriented approach accounts for the specificity of individual-based models – i.e., the dynamic self-organisation of model outcomes from biologically underpinned individual interactions without an inherent determination of properties on higher hierarchical levels – and extends the potential of the validation process qualitatively, as it allows to assess complex structural and causal relations and multi-level feedback processes of the developed models.