Background: Up to now, efforts to help local communities out of the food-insecurity trap were guided by researcher (or other actors)-led decisions on technologies to be implemented by the communities. This approach has proved inefficient because of low adoption of the so-called improved technologies. This paper describes the strategic approaches to the development of a climate-smart village (CSV) model in the groundnut basin of Senegal.

This paper describes the strategic approaches to the development of a climate-smart village (CSV) model in the groundnut basin of Senegal. A CSV model is a participatory integrated approach using climate information, improved context-based technologies/practices aiming at reaching improved productivity (food and nutrition security), climate resilient people and ecosystem and climate mitigation.

Recently, a new approach to extension and climate information services, namely Participatory Integrated Climate Services for Agriculture (PICSA) has been developed. PICSA makes use of historical climate records, participatory decision-making tools and forecasts to help farmers identify and better plan livelihood options that are suited to local climate features and farmers’ own circumstances.

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.