7
mitigation. They identify a significant skew in the available peer-reviewed literature
towards maize-based systems, productivity outcomes and on-farm trials. This suggest that anyone interested in creating evidence-based programmes and plans will
find many gaps in the scientific knowledge. A complementary quantitative approach
towards assessing the multidimensionality of agricultural technologies can be found
in Kimaro et al. Here, the authors collect agronomic data on the performance of
technologies across the three pillars of CSA (productivity, resilience and mitigation)
in three agroforestry systems of Tanzania (shelterbelt, intercropping and border
plantings of fuelwood and food crops). Their findings highlight the perspective and
flexibility needed to understand whether a technology is climate-smart or not.
Performance assessments, however, only provide part of the evidence. Manda et al.
design and pilot a participatory framework to evaluate practices against farmerselected criteria of productivity and resilience. This qualitative approach can help
fill gaps in knowledge-which other chapters of the book have pointed towards-while
being farmer-centric. Mwungu et al. present an analysis of barriers to the adoption
of a technology. Specifically, the authors investigate drivers behind the adoption of
improved varieties in rural, post-conflict Uganda. They find that household size and
information networks influence adoption, with results pointing towards both general and context-specific rules on the adoption of CSA technologies. For example,
while household size is typically positively correlated with adoption, trust in information networks may be increasingly important in some contexts, such as postconflict zones. Davies et al. analyse how culture and spirituality can affect the
adoption of technologies. The introduction of culture as a determinant of adoption
is unique in most discussions of technologies in general and of CSA in particular.
This concern may be acutely pertinent for technologies aimed at addressing climate
risks, given that weather—good or bad—is often viewed as a manifestation of
divine intervention. Together, the chapters presented in this section of the book provide insights into the social considerations and scientific approaches that inform the
adoption of CSA.
Because technologies are only part of the food system, the fourth set of chapters
explores how value chains contribute to the climate-resilience of smallholder farmers and how climate risks to these value chains can be reduced. Barzola et al. focus
on farmers and test the hypothesis that farmer entrepreneurship—the innovative use
of agricultural resources to create opportunities for value creation—as well as
engagement in the value chain facilitates the adoption of CSA technologies. The
study found that farm size influences entrepreneurial innovativeness in a surprising
way—with smaller farms more likely than larger ones to engage in all forms of
innovation. Actors seeking to promote innovation, including the adoption of technology, might therefore consider investing in programmes that help farmers to
develop a more entrepreneurial outlook. Hammond et al. further explore farmer participation and climate resilience. The authors use an innovative survey tool, the
Rural Household Multi-Indicator Survey, to investigate how participation in Shea
value chain activities benefit poor farmers. Shea trees serve as a buffer against
desertification, accumulate carbon in the landscape and protect soil and water
resources, while processing activities (more specifically, shea butter production)
1 An Introduction to the Climate-Smart Agriculture Papers
mitigation. They identify a significant skew in the available peer-reviewed literature
towards maize-based systems, productivity outcomes and on-farm trials. This suggest that anyone interested in creating evidence-based programmes and plans will
find many gaps in the scientific knowledge. A complementary quantitative approach
towards assessing the multidimensionality of agricultural technologies can be found
in Kimaro et al. Here, the authors collect agronomic data on the performance of
technologies across the three pillars of CSA (productivity, resilience and mitigation)
in three agroforestry systems of Tanzania (shelterbelt, intercropping and border
plantings of fuelwood and food crops). Their findings highlight the perspective and
flexibility needed to understand whether a technology is climate-smart or not.
Performance assessments, however, only provide part of the evidence. Manda et al.
design and pilot a participatory framework to evaluate practices against farmerselected criteria of productivity and resilience. This qualitative approach can help
fill gaps in knowledge-which other chapters of the book have pointed towards-while
being farmer-centric. Mwungu et al. present an analysis of barriers to the adoption
of a technology. Specifically, the authors investigate drivers behind the adoption of
improved varieties in rural, post-conflict Uganda. They find that household size and
information networks influence adoption, with results pointing towards both general and context-specific rules on the adoption of CSA technologies. For example,
while household size is typically positively correlated with adoption, trust in information networks may be increasingly important in some contexts, such as postconflict zones. Davies et al. analyse how culture and spirituality can affect the
adoption of technologies. The introduction of culture as a determinant of adoption
is unique in most discussions of technologies in general and of CSA in particular.
This concern may be acutely pertinent for technologies aimed at addressing climate
risks, given that weather—good or bad—is often viewed as a manifestation of
divine intervention. Together, the chapters presented in this section of the book provide insights into the social considerations and scientific approaches that inform the
adoption of CSA.
Because technologies are only part of the food system, the fourth set of chapters
explores how value chains contribute to the climate-resilience of smallholder farmers and how climate risks to these value chains can be reduced. Barzola et al. focus
on farmers and test the hypothesis that farmer entrepreneurship—the innovative use
of agricultural resources to create opportunities for value creation—as well as
engagement in the value chain facilitates the adoption of CSA technologies. The
study found that farm size influences entrepreneurial innovativeness in a surprising
way—with smaller farms more likely than larger ones to engage in all forms of
innovation. Actors seeking to promote innovation, including the adoption of technology, might therefore consider investing in programmes that help farmers to
develop a more entrepreneurial outlook. Hammond et al. further explore farmer participation and climate resilience. The authors use an innovative survey tool, the
Rural Household Multi-Indicator Survey, to investigate how participation in Shea
value chain activities benefit poor farmers. Shea trees serve as a buffer against
desertification, accumulate carbon in the landscape and protect soil and water
resources, while processing activities (more specifically, shea butter production)
1 An Introduction to the Climate-Smart Agriculture Papers