Data for Exploring the future of land use and food security: A new set of global scenarios

Input and output data of the quantitative assessment of the Agrimonde-Terra scenarios. Simulations have been conducted with the GlobAgri-AgT model. The aim of the Agrimonde-Terra foresight was to build global scenarios linking land use and food security, with special attention to overlooked aspects such as nutrition and health, in order to help explore what could be the future of the global food system. In this article, we seek to highlight how the resulting set of scenarios contributes to the debate on land use and food security and enlarges the range of possible futures of the global food system. We highlight four main contributions. Combining a scenario building method based on morphological analysis and quantitative simulations with a tractable and simple biomass balance model, the proposed approach improves transparency and coherence between scenarios’ narratives and quantitative assessment. Agrimonde-Terra scenarios comprise a wide range of alternative diets, with contrasted underlying nutritional and health issues, which accompany contrasted urbanization and rural transformation processes, both dimensions that are lacking in other sets of global scenarios. Agrimonde-Terra scenarios share some similarities with existing sets of global scenarios, notably the SSPs, but are most often less optimistic as regards agricultural land expansion up to 2050. Agrimonde-Terra scenarios enlarge the scope of possible futures by proposing two pathways uncommon in other sets of global scenarios. The first one invites future studies to re-open the debate on the possible reconnection, within supranational regional blocs, of the food industry to regional production. The second one calls for considering that a ‘perfect storm’, induced by climate change and an ecological crisis combined with social and economic crises, is still possible. Both scenarios should clearly be part of the debate as the current context of the COVID-19 pandemic shows.