FOREcasting Scenario Food Risks and Environment

Context and challenges

Prospective scenarios show that a shift in diets, in particular towards a more plant-based diet coupled with a significant reduction in animal products, will be necessary to alleviate these multiple risks. This evolution will have repercussions on agricultural areas (grasslands, biodiversity, etc.) and on the practices of farmers and livestock breeders (agro-ecological practices, conversion of livestock breeders to agriculture, or even abandonment of agriculture).

Numerous studies have explored the future impacts of AFS on socio-ecosystems at different spatial scales, via scenarios (Afterres2050, TYFA). However, they do not make reference to multi-risks and do not take into account cascade effects or interactions between risks, particularly as these scenarios amplify the uncertainties as the targeted time horizon moves further away from the initial state.

Goals

The FORESAFE project – which falls within the scope of Axis 1 of the metaprogram, “Establish connections between different types of risk” – has two interconnected objectives. The first (O1) is to assess the future risks associated with changing diets, using a multi-risk (i.e. systemic) approach. For this, a comparative study of three prospective scenarios (Afterres2050, TYFA, Couesnon 2050) will be conducted to identify the variables mobilized and the risks taken into account. This assessment cannot be made without first building up a (retrospective) knowledge base of the multiple risks associated with livestock farming (as well as with agriculture and diet) and their interactions (in particular a cascade effect). The analysis will focus on “climate risk” and “biodiversity risk”, taking into account changes in land use and occupancy (justification in the “synergy with projects already funded” section). The second objective (O2) will focus on exploring avenues for spatially explicit modeling (and model nesting) for the three scenarios at a fine spatial scale. The challenge is to identify existing climate/pollinator/pest and land-use models, to list needs in terms of input data, and to develop a conceptual model showing linkages and/or obstacles (spatial scale, time step, raster/vector, etc.).

INRAE structures

Partenaires hors INRAE