Intensive agriculture has led to several drawbacks such as biodiversity loss, climate change, erosion, and pollution of air and water. A potential solution is to implement management practices that increase the level of provision of ecosystem services such as soil fertility and biological regulation. There is a lot of literature on the principles of agroecology. However, there is a gap of knowledge between agroecological principles and practical applications. Therefore, we review here agroecological and management sciences to identify two facts that explain the lack of practical applications: (1) the occurrence of high uncertainties about relations between agricultural practices, ecological processes, and ecosystem services, and (2) the site-specific character of agroecological practices required to deliver expected ecosystem services. We also show that an adaptive-management approach, focusing on planning and monitoring, can serve as a framework for developing and implementing learning tools tailored for biodiversity-based agriculture. Among the current learning tools developed by researchers, we identify two main types of emergent support tools likely to help design diversified farming systems and landscapes: (1) knowledge bases containing scientific supports and experiential knowledge and (2) model-based games. These tools have to be coupled with well-tailored field or management indicators that allow monitoring effects of practices on biodiversity and ecosystem services. Finally, we propose a research agenda that requires bringing together contributions from agricultural, ecological, management, and knowledge management sciences, and asserts that researchers have to take the position of “integration and implementation sciences.”

Paradoxically, the number of crop–livestock farms is declining across Europe, despite the fact that crop-livestock farms are theoretically optimal to improve the sustainability of agriculture. To solve this issue, crop–livestock integration may be organized beyond the farm level. For instance, local groups of farmers can negotiate land-use allocation patterns and exchange materials such as manure, grain, and straw. Development of such a collective agricultural system raises questions, rarely documented in the literature, about how to integrate crops and livestock among farms, and the consequences, impacts, and conditions of integrating them. Here, we review the different forms of crop–livestock integration beyond the farm level, their potential benefits, and the features of decision support systems (DSS) needed for the integration process. We identify three forms of crop–livestock integration beyond the farm level: local coexistence, complementarity, and synergy, each with increasingly stronger temporal, spatial, and organizational coordination among farms. We claim that the forms of integration implemented define the nature, area, and spatial configuration of crops, grasslands, and animals in farms and landscapes. In turn, these configurations influence the provision of ecosystem services. For instance, we show that the synergy form of integration promotes soil fertility, erosion control, and field-level biological regulation services through organizational coordination among farmers and spatiotemporal integration between crops, grasslands, and animals. We found that social benefits of the synergy form of integration include collective empowerment of farmers. We claim that design of the complementarity and synergy forms of crop–livestock integration can best be supported by collective participatory workshops involving farmers, agricultural consultants, and researchers. In these workshops, spatialized simulation modeling of crop–livestock integration among farms is the basis for achieving the upscaling process involved in integrating beyond the farm level. Facilitators of these workshops have to pay attention to the consequences on governance and equity issues within farmers groups.

Facing contemporary environmental crisis implies fostering agroecological innovations that take into account local ecological regulations and rely on multiple stakeholders' innovation capacities. This paper draws on two fields of literature that remain unconnected so far: participatory approaches and design sciences. It proposes an analysis grid to support a reflexive analysis of cases of implementation of three participatory design methods: ComMod (Companion Modelling for concerted management of natural resources), Forage Rummy (simulation-based board game for designing farming systems) and KCP (collective design workshops to foster innovation). This analysis highlights key features of the methods in view of agroecological innovation challenges, focusing on knowledge management and organisation for exploration.

Diversification of cropping systems has been proposed as a major mechanism to move towards sustainable cropping systems. To date, a diversification option that has received little attention is introduction of ley pastures into cropping systems, but the use of ley pastures is challenged by most future-oriented scenarios aiming to feed the world sustainably. In these scenarios, ruminant livestock feed only on permanent pastures, while cropping systems focus completely on production of crop-based human food. Diversification of cropping systems with ley pastures is thus compromised by knowledge gaps and future-oriented policy options. Here, we review ecosystem services provided by introducing ley pastures into cropping systems to increase sustainability of agriculture, discuss types of ley pastures and their management liable to promote these services, and raise future challenges related to introducing ley pastures into cropping systems. We conclude that (1) ley pastures provide a large set of input (soil conservation, nutrient provision and recycling, soil water retention, biological control of pests) and output (water purification, climate regulation, habitat provision for biodiversity conservation, forage production) ecosystem services of primary importance to cropping systems and society, respectively, as long as their spatial and temporal insertion within cropping systems is well-managed; otherwise, disservices may be produced. (2) To benefit from ecosystem services provided by ley pastures in cropping systems while limiting their disservices, it appears necessary to define a safe operating space for ley pastures in cropping systems. Moving towards this space requires changing plant breeding programs towards multiservice ley pastures, producing knowledge about emerging ways of introducing ley pastures into cropping systems (e.g., living mulch, green manure) and better quantifying the bundles of ecosystem services provided by ley pastures in cropping systems.

Agricultural production is unstable as a result of complex, dynamic and interrelated factors such as climate, markets and public policy that are beyond farmers’ control. Farmers must therefore develop new farming systems incorporating innovations in objectives, organization and practices adapted to changing production contexts. As a consequence, agronomists have expanded the “farming system design” field of research. A variety of quantitative and qualitative design approaches have been developed to support the analysis of current farming systems and the design and evaluation of alternatives. A comprehensive literature assessment is lacking for this emerging field of agricultural science. Here we review 41 farming system design approaches using computer models. Our main findings are the following: (1) the reviewed literature do not make reference to the theoretical approaches from the field of design science. (2) Two categories of farming system approaches can be distinguished: optimisation approaches, and participatory and simulation-based approaches. These two categories are connected to two of the main design science theories. (3) For optimisation approaches, farming system design is mainly seen as a problem-solving process. Emphasis is placed on the computational exploration of the solution space by a problem-solving algorithm. (4) For participatory and simulation-based approaches, conceptualization of the design problem is central to the farming system design process. The subsequent exploration of the solution space relies on the creativity of humans. (5) Optimisation approaches, and participatory and simulation-based approaches are oriented towards the development of exploitative rather than exploratory innovations. Exploitative innovations involve the exploitation of available knowledge while exploration innovations build on knowledge created in the course of the design process.