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In response to the sustainability issues that agriculture faces in advanced economies, agroecology has gained increasing relevance in scientific, political, and social debates. This has promoted discussion about transitions to agroecology, which represents a significant advancement. Accordingly, it has become a growing field of research. We reviewed the literature on and in support of farm transitions to agroecology in advanced economies in order to identify key research challenges and suggest innovative research paths. Our findings can be summarized as follows: (1) Research that supports exploration and definition of desired futures, whether based on future-oriented modeling or expert-based foresight approaches, should more explicitly include the farm level. It should stimulate the creativity and design ability of farmers and other stakeholders, and also address issues of representation and power among them. (2) Research that creates awareness and assesses farms before, during or after transition requires more holistic and dynamic assessment frameworks. These frameworks need to be more flexible to adapt to the diversity of global and local challenges. Their assessment should explicitly include uncertainty due to the feedback loops and emergent properties of transitions. (3) Research that analyzes and supports farms during transition should focus more on the dynamics of change processes by valuing what happens on the farms. Research should especially give more credence to on-farm experiments conducted by farmers and develop new tools and methods (e.g., for strategic monitoring) to support these transitions. This is the first review of scientific studies of farm transitions to agroecology. Overall, the review indicates that these transitions challenge the system boundaries, temporal horizons, and sustainability dimensions that agricultural researchers usually consider. In this context, farm transitions to agroecology require changes in the current organization and funding of research in order to encourage longer term and more adaptive configurations.

International audience; AbstractThe Companion Modeling approach aims to stimulate learning and sharing of perceptions among several actors through the co-construction and use of a model, while the Integrated Assessment of Agricultural Systems aims to assess a large set of performances of current and alternative systems. Our research question was: to what extent does the joint use of these two methods foster sustainability thinking? We show how the co-design of evolving agriculture scenarios and the use of Integrated Assessment of Agricultural Systems methods guided the implementation of a Companion Modeling process applied to the Valensole Plateau, southeastern France. An initial phase, based on a preliminary diagnosis, aimed to collectively formulate the issues to be addressed, and to engage the actors in a collective dynamic. The second phase consisted of leading actors in the co-construction of a simulation model to represent the agricultural system to be evaluated using economic, social, and environmental indicators at different scales. In the final phase, the current situation and the co-designed scenario were collectively analyzed. The scenario was conceived as a “worst case”, embedded with drivers such as input costs and climate change. Opposing adaptation strategies were envisioned by farmers and other actors. Results show how debates between participants adaptively shaped the model. Scenario simulations highlighted better environmental performance at the expense of economic performance. The differences between farms led to discussions on technical management. Overall, the process stimulated collective reflection among the actors and created a learning experience with the sharing of perceptions and knowledge about the agricultural system. The model was considered relevant by the participants, who expressed interest in continuing its exploration. Our approach, which used a unique combination of Integrated Assessment of Agricultural Systems and scenario development with Companion Modeling, could be adapted to other areas and issues, although tool transfer remains an open question.