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<p>Food systems face multi-dimensional pressures and require integrated assessments of environmental, social, health and economic dimensions to inform their transformation. Although economic equilibrium models and integrated assessment models have been instrumental in this context, future decision-making requires more diverse and inclusive participatory processes. Here we evaluate the ability of current models to represent food systems and identify challenges and opportunities regarding key aspects of their transformative change, including socio-political dynamics and human–nature feedbacks, links between global and local scales, robustness under uncertainty, as well as evolving stakeholder demands. Our analysis underscores the need to rethink how models are designed and used for a more effective integration into decision-making processes.</p>

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Complexity and uncertainty in future food system transformation modelling

  • 期刊论文

  • 发表日期：

    2025年11月10日

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  • Enayat A. Moallemi,
  • Adam C. Castonguay,
  • Daniel Mason-D’Croz,
  • Rohan Nelson,
  • Wolfgang Britz,
  • Cameron Allen,
  • Michalis Hadjikakou,
  • Michael Battaglia,
  • Brett A. Bryan,
  • Costanza Conti,
  • Raymundo Marcos-Martinez,
  • Stefan Frank,
  • Duy Nong,
  • Sibel Eker,
  • Saman Razavi,
  • Javier Navarro-Garcia,
  • Lei Gao

摘要

Food systems face multi-dimensional pressures and require integrated assessments of environmental, social, health and economic dimensions to inform their transformation. Although economic equilibrium models and integrated assessment models have been instrumental in this context, future decision-making requires more diverse and inclusive participatory processes. Here we evaluate the ability of current models to represent food systems and identify challenges and opportunities regarding key aspects of their transformative change, including socio-political dynamics and human–nature feedbacks, links between global and local scales, robustness under uncertainty, as well as evolving stakeholder demands. Our analysis underscores the need to rethink how models are designed and used for a more effective integration into decision-making processes.