

While global attention has been focused on the COVID-19 pandemic, rapid climatic change and biodiversity loss threaten further ‘crises’ or ‘breakdowns’ in which social–ecological dynamics undermine established human and natural systems (IPBES, 2019 Masson-Delmotte et al., 2018). We outline convergent and efficient functional descriptions of social and ecological systems that can be used to develop such models, data resources that can support them, and possible ‘high-level’ processes that they can represent.Ī free Plain Language Summary can be found within the Supporting Information of this article While no models are able to predict exact outcomes in complex social–ecological systems, we suggest that one new approach with substantial promise is hybrid modelling that uses existing model architectures to isolate and understand key processes, revealing risks and associated uncertainties of crises emerging.


However, models that operate over large geographical extents often rely on assumptions such as economic equilibrium and optimisation in social–economic systems, and mean-field or trend-based behaviour in ecological systems, which limit the simulation of crisis dynamics. Computational modelling is a key tool in understanding these processes and their effects on system resilience.
