Participatory diagnosis and development of climate change adaptive capacity in the groundnut basin of Senegal: building a climate-smart village model
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Sanogo D, Ndour YB, Sall M, Toure K, Diop M, Camara AB, N'Diaye O, Thiam D. 2017. Participatory diagnosis and development of climate change adaptive capacity in the groundnut basin of Senegal: building a climate-smart village model. Agriculture & Food Security 6-13.
Permanent link to cite or share this item: http://hdl.handle.net/10568/81011
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. 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. In this study, participatory vulnerability analysis, planning adaptation capacity and participatory communication for development were implemented, putting people affected by the impacts of climate change (CC) at the center of the approach. Four interdependent groups of activities/domains, namely—local and institutional knowledge, use of climate information services, development of climate-smart technology and local development plans, were covered. It was emphasized, how all this taken together could create improved livelihoods for women, men and vulnerable groups. Results: The approach made it possible to involve local people in the decision-making process for the development of their adaptation capacity to CC. It also helped to set up an overall land management process by identifying and addressing environmental (sustainable resource management, ecosystem resilience) and socioeconomic (institutional organization, empowerment, poverty alleviation and food security) challenges. A monitoring survey revealed that farmers appreciate well this participatory approach compared to previous top-down approach in that the former allow them to own the process. Also determinant drivers of adoption of the technologies were identified. Conclusion: Scaling this community development model in sites with similar climatic and socioeconomic conditions could help in contributing toward achieving food security in rural areas at wider scale because of better enthusiasm and engagement from rural farmers to pursue solution to their cons
SubjectsCLIMATE-SMART TECHNOLOGIES AND PRACTICES; DATA AND TOOLS FOR ANALYSIS AND PLANNING; EDUCATION AND OUTREACH; SOCIAL LEARNING;
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