Article published on Frontiers in Sustainable Food Systems
This article presents a methodological framework to co-design climate-smart farming systems with local stakeholders (farmers, scientists, NGOs) so that large-scale change can be achieved. This framework is based on the lessons learned during a research project conducted in Honduras and Colombia from 2015 to 2017. Seven phases are suggested to engage a process of co-conception of climate-smart farming systems that might enable implementation at scale:
- “Exploration of the initial situation,” which identifies local stakeholders potentially interested in being involved in the process, existing farming systems, and specific constraints to the implementation of climate-smart agriculture (CSA).
- “Co-definition of an innovation platform,” which defines the structure and the rules of functioning for a platform favoring the involvement of local stakeholders in the process.
- “Shared diagnosis,” which defines the main challenges to be solved by the innovation platform.
- “Identification and ex ante assessment of new farming systems,” which assess the potential performances of solutions prioritized by the members of the innovation platform under CSA pillars.
- “Experimentation,” which tests the prioritized solutions on-farm.
- “Assessment of the co-design process of climate-smart farming systems,” which validates the ability of the process to reach its initial objectives, particularly in terms of new farming systems but also in terms of capacity building
- “Definition of strategies for scaling up/out,” which addresses the scaling of the co-design process. For each phase, specific tools or methodologies are used: focus groups, social network analysis, theory of change, life-cycle assessment, and on-farm experiments. Each phase is illustrated with results obtained in Colombia or Honduras.
This work was funded by the FONTAGRO program (FTG/RF-14837-RG; Contract #80), Agropolis Foundation (Contract #1502-006), and as part of the CGIAR Research Program on Climate Change, Agriculture, and Food Security (CCAFS), which is carried out with support from the CGIAR Trust Fund and through bilateral funding agreements.
In 2014, the Global Alliance for Climate-Smart Agriculture (GACSA) was launched with the goal of helping 500 million farmers practice climate-smart agriculture (CSA) defined as “agriculture that sustainably increases productivity, enhances resilience (adaptation), reduces/removes GHGs (mitigation) where possible, and enhances achievement of national food security and development goals” (FAO, 2013). Despite the controversies around the meaning of the concept and its lack of theoretical background (Torquebiau et al., 2018), CSA provides the framework within which synergies among adaptation, mitigation, and improved food security for small-scale farmers can be identified, developed, and disseminated. Innovative agricultural systems are needed to find synergies among those three pillars.
Existing studies on the co-design of innovative agricultural systems focus on the development of methods for the design and assessment of farming systems at several levels (Le Gal et al., 2011; Meynard et al., 2012; Prost et al., 2016), from the plot or the herd to the farm or the territory. In such studies, new cropping and livestock systems, combining scientific knowledge with the empirical knowledge of local actors (e.g., men and women farmers, extension services) directly involved, are analyzed and tested. Such studies have shown that the design of innovative agricultural systems has to involve technical, social, and organizational changes and to be analyzed and implemented with stakeholders at multiple levels (Delmotte et al., 2016; Moraine et al., 2016). Participatory mechanisms such as multi-actor innovation platforms associated with exploration tools, such as modeling tools or on-farm experiments, are key in such processes to facilitate mediation and the development of a common language among partners (Dabire et al., 2016). Such multi-actor innovation platforms can be defined as networks intended to strengthen interactions between actors in order to facilitate change that enables innovation (Kilelu et al., 2013). These platforms are virtual, physical, or physico-virtual spaces to learn, jointly conceive, and transform different situations; they are generated by individuals with different origins, different backgrounds, and different interests (Pali and Swaans, 2013).
Thus, the ability of local actors to tackle climate change challenges and mitigate their effects will depend on their ability to innovate and to articulate links among stakeholders while undertaking actions at the local level.
Today, the literature is growing on participatory processes aiming to support climate change policy planning (Rannow et al., 2010; Vervoort et al., 2014; Schroth et al., 2015), with some processes explicitly aiming to promote CSA nationally or locally (Mwongera et al., 2016; Andrieu et al., 2017). However, not many methodological guides exist to co-design climate-smart farming systems with stakeholders.
The purpose of this article is to present a seven-phase methodology to allow family farmers to co-design and adopt CSA options to tackle climate change effects in an open innovation platform. This article is based on the lessons learned during a participatory research conducted in Honduras and Colombia and that was articulated to ongoing research projects in both sites. In these ongoing research projects, groups of farmers, NGOs and research scientists were already working together to sustainably improve their agricultural systems. The article synthetizes and highlight the complementarity between different individual studies conducted from 2015 to 2017 (Acosta-Alba et al., 2019; Howland et al., under review; Osorio-García et al., under review).
After a presentation of the broad methodology, we will show how for each phase, the main results obtained in Colombia and Honduras. We will then discuss the specificity of this process compared with other processes used to design innovative agricultural systems and methodological challenges we found when applying the methodology.
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