Methodological opportunities for mitigating climate change in complex food systems

Abstract

Unravelling current complex food systems is relevant for their adjustment and redesign under the current changing climate conditions. Redesign may be necessitated by migration of people and changes of locations of major agri-food production. The redesign should be conducted synchronously with that of systems entangled with the food system, such as the socio-economic and cultural system. For such synchronous redesign a common methodological approach with a common set of methods is required. In the current article we suggest a common set of methods, and discuss how these methods find their basis in vastly different science fields, ranging from soft matter, biology, urban socio-economics, ecology, to machine learning. We address the various ways such methods have been applied in relatively small parts of the food systems and how they can be applied to larger parts of current and future food systems. The set of methods facilitates to identify the level of structuredness and randomness in complex systems. It helps to better predict upcoming transitions in complex systems, according critical points, and sudden instabilities. It facilitates in extracting information from a system, before, during and after the time that one makes an intervention, which in turn will help to decide which interventions are best to maintain or change functions of a complex system.