Stakeholders from academic, political, and social spheres encourage the development of more sustainable forms of agriculture. Given its scale and scope, the sustainability transition is a challenge to the entire agricultural sector. The main question is, how to support the transition process? In this article, we explore how agricultural science can address the sustainability transition of farming systems to understand and support transition processes. We discuss the potential for articulating three research approaches: comprehensive analysis, co-design, and simulation modeling. Comprehensive analysis of the sustainability transition provides perspectives on the interplay between resources, resource management, and related performances of farming systems on the one hand and technical, economic, and sociocultural dimensions of change on the other. Co-design of the sustainability transition stimulates local-scale transition experiments in the real world and identification of alternatives for change. Simulation modeling explores future-oriented scenarios of management at multiple levels and assesses their impacts. We illustrate the articulation of research approaches with two examples of research applied to agricultural water management and autonomy in crop-livestock systems. The resulting conceptual framework is the first one developed to organize research to understand and support the sustainability transition of farming systems.

Viewing the landscape as a spatialized social-ecological system allows identification of specific management challenges: integration of multiple views, multiple levels of organization, complex spatial-temporal patterns and uncertainties. Multi-criteria assessments (MCAs), which allow the comparison of alternative actions when multiple interests collide, are considered adequate to support landscape management. However, there is no consensus about how they should be applied and can integrate both multiple views and spatial dimension. We conducted an extensive quantitative and qualitative literature review targeting MCAs with a participatory and spatial approach. Our results suggest that (1) for sustainability assessments, participatory and spatial approaches endorse different rationales and hybrid methods are not so common; (2) within those methods, only scenario-selection methods (as opposed to design methods) can integrate spatially-explicit, spatially-implicit, place-specific, and overall values; and (3) current applications, which aggregate values ignoring their spatial and social distribution, do not coincide with the nature of landscape-management challenges. In addition, they give little importance to the structuration of information and to collective deliberation. We conclude that, in the absence of a good match between spatiality and participation, MCAs should, for now, be handled as insightful but distorted tools to explore and structure landscape-level management problems.

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Water imbalances are an environmental, social, and economic problem in many agricultural watersheds, including those in temperate climates. Structural changes are recommended because crisis management, through water restrictions, is not sustainable. However, the content of these changes is debated, especially because their impacts concern different sectors and stakeholders and are uncertain. MAELIA is an integrated assessment and modeling platform, which combines a multi-agent model with a geographic information system; it represents fine-scale interactions among water, water management, and agricultural systems, accounting for daily irrigation decisions on each field and effects of the corresponding water withdrawals on water flows. In this article, for the first time, we investigated the effectiveness of some of the most popular strategies aimed at solving water imbalances considering environmental, water management, and agricultural indicators calculated with MAELIA. The alternatives we assessed were (i) reducing the irrigated area, (ii) assisting irrigation with decision-support tools, (iii) implementing crop rotations, and (iv) merging water storage into large reservoirs. Simulations were run for the 2001-2013 period on a casestudy area, the downstream Aveyron watershed. We show that, in this area, the decision-support tool and crop-rotation alternatives drastically decreased irrigation withdrawals and required fewer restrictions and flow-support releases. However, those two alternatives had different impacts on the environment and farming systems: decision-support tools cost almost nothing for farming systems and improved environmental indicators slightly, while crop rotations had greater potential for long-term environmental preservation but degraded local and farm economies in the current context. The uniqueness of this study comes from using a fine-scale mechanistic model to assess, in an integrated way, the impacts of politically debated water management strategies that were previously only assessed in terms of potential withdrawal reduction.

Indicators are widely used in sustainability assessments. They serve both a descriptive function (i.e.., assessing a situation or effects of potential changes) and a normative function (i.e., allowing the expression of value judgments). These functions are usually considered when identifying and using indicators. However, processes such as formalization, estimation, and customization are needed to produce tangible indicators. These processes and their influence on sustainability assessments are studied less often. We focus on spatial aggregation, a specific type of customization commonly used for landscape-scale and regional assessments. Using a database with 146 indicator profiles for water management, we investigated reasons for spatial aggregation choices, i.e. whether indicators based on spatially-explicit data are aggregated while under development or are provided to users in a disaggregated form. Although the literature assigns a descriptive function to spatial aggregation, our database shows that reasons underlying aggregation choices are more diverse.These reasons include highlighting differences, fitting to the scale of a process, fitting to criteria, recognizing a lack of knowledge, expressing social rationality, contextualizing information, and allowing different interpretations of the same indicator. Some of these reasons reflect the choice to expand or reduce the range of potential uses of an indicator, and therefore the potential for different viewpoints to confront each other. Hence, normative claims combine with descriptive claims when aggregating indicators, and even more so when customizing them. In general, the form of indicators merits more attention in the practice and theory of sustainability assessments. Highlights• Indicators are viewed as objects to describe and debate a situation.• Indicators result from different information processes that are sometimes "hidden".• The process of spatial aggregation is investigated.• Spatial aggregation choices provide a degree of leeway in interpreting indicators.• Choices illustrate tension between the need for consistency and that for diversity.

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