Summary
This paper examines the treatment of complexity and uncertainty in computational models used to project future food system transformations. Drawing on a large international author team with modelling expertise, the work appears to analyse how existing integrated assessment models and food systems models represent key uncertainties and complex interactions, and likely identifies methodological gaps or recommendations for more robust scenario development. As suggested by the title and journal scope, the paper addresses a critical gap in how model-based evidence on food system futures is constructed and communicated.
UK applicability
UK food system policy relies increasingly on modelled projections of transformation scenarios (e.g. net zero, land use, trade). This analysis of model limitations and uncertainty treatment will be directly applicable to how UK policymakers should interpret and act upon modelling evidence in food and agricultural strategy.
Key measures
Model structure, uncertainty characterisation, scenario assumptions, complexity representation in food system transformation models
Outcomes reported
The study examined how modelling approaches represent complexity and uncertainty when projecting future food system transformations. The paper likely assessed the methodological frameworks, assumptions and limitations of integrated assessment models used to evaluate food system scenarios.
Topic tags
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