Living Laboratory: A Model for Co-creation and Sharing Knowledge and Skills in Building Resilient Food Systems

Experiences from Mosop Subcounty, Nandi County, Kenya

Abstract

Today’s unsustainable and inequitable food system demand attention from all stakeholders. Malnutrition is on the rise, the food systems activities are responsible for biodiversity loss, water depletion, and land degradation. The top-down agricultural development research and practices have been increasingly called into question. Living lab as both an approach and a platform for supporting agricultural research and extension advisory services could be applicable in a wide range of settings and diverse actors. The main aim of the study was to investigate whether climate change affects smallholder dairy production in Mosop. The author explores the potential of the living lab model for analyzing and building resilient and sustainable dairy production systems. The study employed case study method in Mosop Sub County. The study used key informant interviews and focus group discussions involving project implementers and beneficiaries for data collection. Mosop subcounty documents the promising climate adaptation strategies promoted by the program for climate smart livestock through the LL model. The findings indicated that climate change is taking place and is already affecting dairy production in Mosop. The adaptation strategies most effective in addressing impacts of climate change on dairy production include; feed conservation especially silage making; use of crop residues (maize stovers) and 24H feed fermentation. The findings also indicated that the principle of inclusiveness, transparence and realism according to the living labs models contributed to project outcomes. The livestock extension officers acknowledged that the social learning happening around the networks of pioneer adopters is an innovation mechanism in and rural advisory and agricultural extension. Both the farmer respondents and livestock officers, further agreed that, if supported and motivated this farmer to farmer horizontal learning is an effective model for scaling locally-led climate change adaptation in agrifood system and environmental landscape. The findings indicate the LL model allows the involvement of a diversity of actors; it allows experimentation in reality thus grounding it to co-creation. However, for LL to thrive, it requires an open mindset and reversal learning especially for the agricultural advisory service providers and researchers. This study recommends that there is a need for designing interventions towards resilient dairy production systems but most importantly, these should account for local contexts, priorities and preferences. This will enhance uptake and adoption, consequently enhancing resilience and sustainability.