Model-derived causal explanations are inherently constrained by hidden assumptions and context

Models are widely used for investigating cause-effect relationships in complex systems. Within the CauSES project we were interesting in how computational models are used to make causal claims. However, often different models yield diverging causal claims about specific phenomena. Therefore, critical reflection is needed on causal insights derived from modeling.

Fig. 1
Fig. 1 from the associated publication: Overview of entities taken into account in the 15 models analyzed. They are grouped into cod, sprat, herring and other species populations, the environment (represented by different factors), and fishers. Box sizes and grey numbers show the number of models in which the entity was included (out of 15 models in total). The additional boxes within larger ones show the separation of cod, sprat or herring populations into age groups, size groups or life stage groups, and the separation of fishers into multiple fleets.

As an example, we here compare ecological models dealing with the dynamics and collapse of cod in the Baltic Sea. The models addressed different specific questions, but also vary widely in system conceptualization and complexity. With each model, certain ecological factors and mechanisms were analyzed in detail, while others were included but remained unchanged, or were excluded.

Model-based causal analyses of the same system are thus inherently constrained by diverse implicit assumptions about possible determinants of causation. In developing recommendations for human action, awareness is needed of this strong context dependence of causal claims, which is often not entirely clear. Model comparisons can be supplemented by integrating findings from multiple models and confronting models with multiple observed patterns.

The paper “Model-derived causal explanations are inherently constrained by hidden assumptions and context: The example of Baltic cod dynamics” is published at Environmental Modeling and Software

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