Scaling Climate Smart Agriculture in East Africa: Experiences and Lessons

Abstract

Climate-smart agriculture (CSA) responds in order to sustain agriculture under a changing environment, and is a major priority in the development sphere. However, to achieve impact at scale, CSA innovations must address agricultural systems’ context-specific and multi-dimensional nature and be purveyed through feasible scaling processes. Unfortunately, knowledge on the scaling of CSA innovations under smallholder farming systems and in the context of developing countries remains scant. Understanding scaling processes is essential to the design of a sustainable scaling strategy. This study aimed to draw lessons on scaling from 25 cases of scaling CSA, and related projects in Ethiopia, Kenya, Uganda, and Tanzania implemented by public institutions, local and international research organisations, Non-Govermental Orginsations(NGOs), and community-based organisations. Generally, scaling follows a linear pathway comprising technology testing and scaling. Most cases promoted technologies and models geared towards climate change adaptation in crop-based value chains, and only a few cases incorporated mitigation measures. Efforts to engage the private sector involved building business models as a potential scaling pathway. The cases were very strong on capacity building and institutionalisation from local, national, and even regional levels. However, four critical areas of concern about the sustainability of scaling emerged from the study: (i) There is little understanding and capture of the dynamics of smallholder farming systems in scaling strategies; (ii) climate data, projections, and impact models are rarely applied to support the decision of scaling; (iii) considerations for the biophysical and spatial-temporal impacts and trade-offs analysis in scaling is minimal and just starting to emerge; and (iv) there are still challenges effecting systemic change to enable sustainable scaling. In response to these concerns, we propose investment in understanding and considering the dynamics of the smallholder farming system and how it affects adoption, and subsequently scaling. Programme design should incorporate climate change scenarios. Scaling programmes can maximise synergies and leverage resources by adopting a robust partnerships model. Furthermore, understanding the spatio-temporal impact of scaling CSA on ecological functioning deserves more attention. Lastly, scaling takes time, which needs to be factored into the design of programmes.

Unlocking the economic potential of Hyphaene species known as mikoche in Tanzania

“…Furthermore, as climate change continues to affect Tanzania, Hyphaene trees can be integrated into Climate-Smart Agriculture (CSA) programs. The CSA is a farming approach that aims to sustain and increase agricultural productivity in a changing environment (Kirina et al, 2022). Hyphaene plants are well-adapted to arid and semi-arid environments, making them suitable crops for areas with limited water and other resources (Fick & Hijmans, 2017), such as fertilisers and pesticides.…”

Restoring Soil Cover and Plant Communities with Arbuscular Mycorrhizal Fungi as an Essential Component of DSS for Environmental Safety Management in Post-Industrial Landscapes

“…However, at the same time, the activity of mining and chemical enterprises is a determining factor of technogenesis, which significantly complicates the ecological situation in local areas with changes in landforms and hydrological and biogeochemical 2 of 22 regimes caused by the accumulation of significant waste on the ground. As a result, there are various environmental problems, primarily related to the pollution of numerous natural components of the environment-soil, water and vegetation-thus, the deteriorating health of the local population [1][2][3][4]. One of the industrial basins that has undergone intensive exploitation is the Pre-Carpathian sulfur-bearing basin.…”

Changes and Variability in rainfall onset, cessation and length of rainy season in the IGAD region of Eastern Africa

“…These smallholder farmers depend on the rain-fed farming of food crops such as maize, wheat, sorghum, rice, potatoes, bananas, cassava, beans, vegetables or cash crops such as sugar cane, tea, cotton, coffee among others (Kirina et al, 2022). The accumulated daily, monthly and seasonal rainfall amount, timing, distribution and intensity constitute important factor beside other agricultural inputs whether consumable inputs such as labour, soil type, fertilizers, insecticides or capital inputs such as mechanical and technology used to maximize yields of grains, seeds and nuts, vegetables and fruits been consumed or Pro table cash crops for Small-Scale Farms (Lobell & Burke, 2009).…”

“…The current increase in mean state of extreme events such as drought over east Africa (Haile et al, 2020), attributed historically to rains failure due to delayed onset, early withdrawal and reduced rainfall intensity (Camberlin et al, 2009), prolonged dry spells (Gitau et al, 2013), current and projected warming in temperatures (Ongoma et al, 2018). In addition, the projected rise in East Africa population and water demands and resources for Climate-smart agriculture (Kirina et al, 2022) are a major threat to regional food security and hence sustainable development. The situation could be accelerated by anticipated impacts of change and variability in climate on agricultural planning activities such as crop selection, land clearing pattern, seed planting and crop harvesting (Otieno et al, 2022).…”

“…Food crop farmers in Nasarawa State in Nigeria and many regions in Africa reported of having limited information on planting and harvesting dates, types of crops and seeds suitable when there is shifts in onset and cessation dates, rainy season become longer or shorter under current and future climate conditions (Yashim et al, 2020). These situations could force farmers to rely on assumptions and mere guess work considered local indigenous agricultural knowledge or farming by experience as a scaling strategy for climate-smart agriculture (Kirina et al, 2022). There is a need for su ciently, reliable and timely spatial and temporal information on the mean state, changes and variability in onset and cessation dates, length of rainy season patterns.…”