Which types of quantitative foresight scenarios to frame the future of food systems? A review

The paper can be accessed on the website of the Agricultural Systems journal (open-access) :

Quantitative scenarios have become common tools to explore the evolution of agricultural and food systems and their necessary transition towards greater sustainability. Yet, despite the diversity in methods and questions explored, a notable gap remains in methodically categorizing such scenarios.

Through reviewing a broad range of studies, this paper aims to address this gap. It pursues two main objectives: (1) proposing a comprehensive typology classification of distinctive scenario types; (2) delving into the practical implications that diverse scenario designs bring to the forefront.

Based on a snowball sampling method, 36 quantitative food system scenario studies were included in the sample and reviewed. A coding process allowed to characterize each scenario based on a set of variables focused on the scenarios’ design process (e.g. purpose of the scenarios, number of scenarios tested, scale of analysis, consideration of production systems, sectors of interest, considered sustainability dimensions, etc.). Typology identification involved two iterative rounds of discussion among the authors, based on variables deemed pivotal for distinguishing scenario types.

The paper proposes four scenario types of quantitative food system scenarios, centered on the scenarios’ purpose and design process. Scenario types A and B are more normative as they seek to demonstrate the feasibility of a specific scenario or frame the conditions for its feasibility, differing in the number of scenarios tested (respectively one and many). Scenario types C and D are more exploratory as they aim to assess the consequences of different scenarios, differing in the number of scenario variables being explored (respectively one and many). Besides the proposed classification, the paper discusses important methodological considerations related to scenario design (e.g. the consideration of multiple sustainability dimensions, the adoption of participatory approaches, etc.).

This paper contributes to enhancing coherence across food system foresight studies and helps to ensure that quantitative scenarios are utilized effectively for their intended purposes, such as assessing the feasibility of achieving a goal or evaluating different options.