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.

Finding ways of increasing animal production with low external inputs and without compromising reproductive performances is a key issue of livestock systems sustainability. One way is to take advantage of the diversity and interactions among components within livestock systems. Among studies that investigate the influence of differences in animals' individual abilities in a herd, few focus on combinations of cow breeds with contrasting features in dairy cattle herds. This study aimed to analyse the performances and management of such multi-breed dairy cattle herds. These herds were composed of two types of dairy breeds: 'specialist' (Holstein) and 'generalist' (e.g. Montbeliarde, Simmental, etc.). Based on recorded milk data in southern French region, we performed ANOVA: (i) to compare the performances of dairy herds according to breed-type composition: multi-breed, single specialist breed or single generalist breed and (ii) to test the difference of milk performances of specialist and generalist breed cows (n = 10 682) per multi-breed dairy herd within a sample of 22 farms. The sampled farmers were also interviewed to characterise herd management through multivariate analysis. Multi-breed dairy herds had a better trade-off among milk yield, milk fat and protein contents, herd reproduction and concentrate-conversion efficiency than single-breed herds. Conversely, they did not offer advantages in terms of milk prices and udder health. Compared to specialist dairy herds, they produce less milk with the same concentrate-conversion efficiency but have better reproductive performances. Compared to generalist dairy herds, they produce more milk with better concentrate-conversion efficiency but have worse reproductive performances. Within herds, specialist and generalist breed cows significantly differed in milk performances, showing their complementarity. The former produced more milk for a longer lactation length while the latter produced milk with higher protein and fat contents and had a slightly longer lactation rank. Our results also focus on the farmers' management of multi-breed dairy herds underlying herd performances. Three strategies of management were identified and structured along two main axes. The first differentiates farmers according to their animal-selection practices in relation with their objectives of production: adapting animal to produce milk with low-feeding inputs v. focussing on milk yield trait to intensify milk production. The second refers to the purpose farmers give to multi-breed dairy herds: milk v. milk/meat production. These initial insights on the performances and management of multi-breed dairy herds contribute to better understanding the functioning of ruminant livestock systems based on individual variability.

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In agroecological approaches, autonomy emerges as a central concept. It is also meaningful for farmers, for whom implementing the agroecological transition of livestock farming systems (LFS) requires greater autonomy with respect to inputs and the dominant socioeconomic and technical regime. How does this concept of autonomy encompass the complexity of the agroecological transition? This chapter provides an answer through an overview of the various approaches used to analyse the autonomy of LFS, as well as a conceptual framework that can serve to comprehensively examine it. Three approaches to LFSs' autonomy are presented, based on whether they are focused on the flows of material between system components, on the functioning and management of the system, or on the socioeconomic organisation and the values underpinning it. Each of these addresses autonomy in its biotechnical or decisional dimension, as well as in terms of three analysis components: embeddedness, dependency, and footprint. The conceptual M.-A. Magne (