The three system CGIAR research programs on Integrated Systems for the Humid Tropics, Dryland Systems and Aquatic Agricultural Systems have included “capacity to innovate” as an intermediate development outcome in their respective theories of change. The wording of the intermediate development outcome is “increased systems capacity to innovate and contribute to improved livelihoods of low-income agricultural communities.” This note captures the CGIAR's collective thinking about this intermediate development outcome from a systems perspective to clarify it and inspire other programs.
This paper describes the learning selection approach to enabling innovation that capitalizes on the complexity of social systems at different scales of analysis. The first part of the paper describes the approach and how it can be used to guide the early stages of setting up a “grassroots” innovation process. The second part of the paper looks at how the learn selection model can be used “top-down” to guide research investments to trigger large-scale systemic change.
This paper (Part I) present a case study of work conducted by the International Centre for Tropical Agriculture (CIAT) to adapt network mapping techniques to a rural and developing country context. It reports on work in Colombia to develop a prototype network diagnosis tool for use by service providers who work to strengthen small rural groups. It is complemented by a further paper in this issue by Louise Clark (Part II) which presents work to develop a network diagnosis tool for stakeholders involved in agricultural supply chains in Bolivia.
There have been repeated calls for a ‘new professionalism’ for carrying out agricultural research for development since the 1990s. At the centre of these calls is a recognition that for agricultural research to support the capacities required to face global patterns of change and their implications on rural livelihoods, requires a more systemic, learning focused and reflexive practice that bridges epistemologies and methodologies.
Numerous innovation platforms have been implemented to encourage the adoption of agricultural innovations and stakeholder interactions within a value chain. Yet little research has been undertaken on the design and implementation of innovation platforms focussing on issues other than market access and aiming to encourage agro-ecological intensification.
La co-conception de systèmes agricoles innovants est une piste prometteuse pour répondre au défi de l’innovation, notamment pour les exploitations agricoles familiales africaines confrontées à de multiples changements. Mais il faut penser à la place et aux rôles tenus par de multiples acteurs (agriculteurs, conseillers, chercheurs) pour produire les changements souhaités par toutes les parties, et donc réfléchir à la question du partenariat dans le processus.
This methodological framework is based on Life Cycle Assessment (LCA) and multi-criteria assessment methods. It integrates CSA-related issues through the definition of Principles, Criteria and Indicators, and involves farmers in the assessment of the effects of CSA practices. To reflect the complexity of farming systems, the method proposes a dual level of analysis: the farm and the main cash crop/livestock production system. After creating a typology of the farming systems, the initial situation is compared to the situation after the introduction of a CSA practice.
Climate-smart agriculture (CSA) is an approach to help agricultural systems worldwide, concurrently addressing three challenge areas: increased adaptation to climate change, mitigation of climate change, and ensuring global food security – through innovative policies, practices, and financing. It involves a set of objectives and multiple transformative transitions for which there are newly identified knowledge gaps. We address these questions raised by CSA within three areas: conceptualization, implementation, and implications for policy and decision-makers.