The aim of the study was to strengthen the capacities of the farmers in a participatory process to adapt to climate change. It was assumed that an innovation platform could support generation and exchange of knowledge on climate change, exchange and identification and implementation of options for adaptation tailored to local needs by the participating farmers

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.

This chapter reports on the different functions fulfilled by existing mechanisms for supporting collective innovation in the agricultural and agrifood sectors in the countries of the Global South in order to identify the potential contributions the research community can make to strengthen them. The authors show that a variety of mechanisms are needed to create enabling conditions for innovation and to provide a step-by-step support to innovation communities, according to their capacities and learning needs.

The evidence base on agri-food systems is growing exponentially. The CoSAI-commissioned study, Mining the Gaps, applied artificial intelligence to mine more than 1.2 million publications for data, creating a clearer picture of what research has been conducted on small-scale farming and post-production systems from 2000 to the present, and where evidence gaps exist.

A range of approaches and financial instruments have been used to stimulate and support innovation in agriculture and resolve interlocking constraints for uptake at scale. These include innovation platforms, results-based payments, value chain approaches, grants and prizes, incubators, participatory work with farmer networks, and many more.

Innovation for sustainable agricultural intensification (SAI) is challenging. Changing agricultural systems at scale normally means working with partners at different levels to make changes in policies and social institutions, along with technical practices. This study extracts lessons for practitioners and investors in innovation in SAI, based on concrete examples, to guide future investment.

A huge increase in investment in innovation for agricultural systems is critical to meet the Sustainable Development Goals and Paris Climate Agreement. Most of this increase needs to come from reorienting existing funding for innovation. However, understanding whether an investment will fully promote environmentally sustainable and equitable agri-food systems can be difficult.

Finance is a key lever for turning agriculture from a potential source of environmental harm and social inequity to a driver of conservation and social inclusiveness. Private and public sector funding for farmers to combat climate change and protect and restore nature (‘Paying for Nature’) is rapidly increasing. Yet this new funding may not reach its aims without drastically improving farm-level reward mechanisms.