Rangelands are pivotal for global carbon cycling, climate regulation, and rural livelihoods, yet they are increasingly threatened by overgrazing, land-use conversion, and climate variability. Carbon storage serves as a key ecological indicator, reflecting both ecosystem health and the capacity of rangelands to contribute to climate mitigation. This study assessed carbon storage and its economic value in the Borana rangelands of southern Ethiopia between 2010 and 2024. Four major carbon pools, aboveground biomass, belowground biomass, soil organic carbon, and dead organic matter, were assessed and mapped using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model. Results showed a total-carbon storage decline from 505.18 Mt C in 2010 to 503.93 Mt C in 2024, a net loss of 1.25 Mt C (0.25% of baseline stock). Spatial analysis revealed heterogeneous change patterns: intact bushlands and woodland retained the highest carbon densities, while heavily grazed and cultivated areas experienced substantial depletion. The associated economic valuation showed a Net Present Value loss of US$ 108.16 million over the 14-year period, with per-hectare economic value of carbon loss ranging between US$ 9,174 and 18,952. Although the magnitude of losses is relatively small compared to the total stock, the trend indicates a net release of carbon to the atmosphere, reducing the rangelands' potential to function as a carbon sink. From an ecological and management perspective, these losses serve as an early-warning signal of rangeland degradation. Continued depletion will compromise forage availability, livestock productivity, and ecosystem resilience. Implementing sustainable grazing management and integrating carbon finance and restoration initiatives could enhance local resilience, improve carbon retention, and support pastoral livelihoods, enabling Borana to transition toward a climate-resilient carbon sink, delivering ecological, economic, and social co-benefits while contributing to national and global climate objectives.

Climate variability poses major challenges to smallholder maize farmers in Ethiopia, affecting productivity, livelihoods, and food security. Comprehensive maize value-chain assessments could enhance farmers' climate-change resilience and promote more sustainable and adaptive production systems. This study assessed climate risks along the maize value chain, identified context-specific, best-bet climate-smart agriculture (CSA) practices, and examined adoption barriers among smallholder farmers in southern Ethiopia. We applied a mixed-methods approach, combining climate-trend analysis, household surveys, focus group discussions, and stakeholder consultations across Gofa, South Omo, Wolaita Zones, and Sidama Regional State. The study observed declining rainfall in South Omo during the Kiremt (mid-June to mid-September) and Belg (February to May) rainy seasons, and increased precipitation in Wolaita and Gofa in October to December. Farmers cited drought, erratic rainfall, heat stress, and fall armyworm as major risks affecting maize production, which disrupted sowing and fertilizer application, increased pest outbreaks and soil degradation, and lowered yields. In response, farmers adopted CSA practices to differing degrees, which notably improved maize varieties (68.4–89.5%), conservation agriculture (58.30–73.7%), integrated soil-fertility management (ISFM) (65.20–80.60%), and agroforestry (44.5–76.3%). The five key barriers to CSA adoption identified were input shortages, limited access to finance, lack of awareness, limited technical capacity, and lack of agro-advisory information. By providing a multi-level understanding of climate risks and CSA adaptation strategies and scaling tailored best-bet CSA practices across the maize value chain, these findings provide actionable insights for implementing climate-resilient policies and extension programs that enhance yields and build climate resilience across Ethiopia's maize value chain.

Rainfall variability presents a major challenge for climate-sensitive sectors in arid and semi-arid regions such as Djibouti, where livelihoods depend heavily on rain-fed systems. This study investigates the seasonal and interannual variability of rainfall and temperature in Djibouti during 1981–2024, focusing on spatial patterns and their relationships with large-scale ocean-atmosphere drivers-. Results confirm a bimodal rainfall regime with primary peaks during July-September (JAS) and secondary peaks during March-May (MAM), associated with the seasonal migration of the Intertropical Convergence Zone. The principal rainy season (JAS) contributes approximately 45.8

Policies in sub-Saharan Africa are constrained by a limited knowledge of climate change extremes and a focus on agricultural production rather than nutrition supply. Here we model the impacts of future extremes on national-level calorie and nutrient supply in Zambia for production and nutrition focused policy scenarios. We identify the specific cropland, yield and import increases required to achieve climate-resilient nutrition security and highlight policy options.

This study provides a comprehensive assessment of climate characteristics, variability, and their impacts on maize production in Southern Ethiopia, integrating historical observations with future climate projections. Using advanced statistical analyses, including Mann-Kendall trend tests and Rotated Empirical Orthogonal Functions (REOF), we identify significant warming trends in both minimum and maximum temperatures across all seasons, alongside spatially heterogeneous rainfall variability strongly influenced by ocean-atmosphere interactions such as ENSO and the Indian Ocean Dipole. Our analysis reveals that maize yields in key agricultural zones, Sidama, South Omo, and Wolayita are highly sensitive to seasonal rainfall and temperature fluctuations, particularly during critical phenological stages. Future climate projections under SSP1 and SSP5 scenarios indicate decreasing rainfall during the main maize growing season (MAM) coupled with rising temperatures, exacerbating water stress and threatening crop productivity. Conversely, increased rainfall during the short rains (SON) may offer opportunities but also pose risks from waterlogging and pest outbreaks. These findings underscore the urgent need for climate-smart agricultural strategies, including drought-resistant varieties, adjusted planting calendars, and enhanced water management, to safeguard food security and rural livelihoods amid evolving climate risks in Southern Ethiopia. This is designed as a logical progression from foundational context to applied agricultural implications. An integrated climate–agriculture assessment for South Ethiopia, synthesizing long-term observations, advanced statistical diagnostics, and state-of-the-art climate model projections to unravel past trends, key variability drivers, and future risks. The first section (Fig. 1) maps the region’s geographic setting, elevation, soils, and agroecological zones; factors that dictate crop suitability and shape vulnerability to climate extremes. Baseline climatologies of rainfall (Fig. 2) and minimum/maximum temperature (Fig. 3, supported by Fig. 3a) capture seasonal cycles and spatial gradients, forming essential references for detecting anomalies. Trend analyses (Fig. 4–5, supported by Fig. 4a, 5a–5d) uncover significant spatial–temporal changes in rainfall, temperature, and sea surface temperature (SST) between 1981–2024, including season-specific precipitation declines or increases and pervasive warming in both minimum and maximum temperatures. These shifts have direct implications for heat stress, evapotranspiration rates, and the potential redefinition of agroecological zones. Rotated Empirical Orthogonal Function (REOF) analysis (Fig. 6 and 8, supported by Fig. 8a–8c) isolates dominant rainfall variability modes, linked to large-scale ocean–atmosphere phenomena. Correlation and composite diagnostics (Fig. 7, supported by Fig. 7a–7c) emphasize the seasonal influence of SST anomalies, El Niño-Southern Oscillation (ENSO), and the Indian Ocean Dipole (IOD), clarifying connection pathways that govern rainfall variability. The climate–agriculture coupling (Fig. 9) demonstrates measurable impacts of seasonal rainfall anomalies on maize yield, production, and harvested area, highlighting farmers’ adaptive strategies under water stress. Multi-model ensemble analyses (Fig. 10–11; see also supplementary Figs. 10a–10c, 11a–11c) under two Shared Socioeconomic Pathways: SSP1 (Sustainability) and SSP5 (Fossil-Fueled Development), elucidate model uncertainties and indicate projected shifts in rainfall regimes and enhanced warming, thereby informing targeted adaptation strategies. Collectively, these findings advance scientific understanding of climate–agriculture interactions, enhance seasonal forecasting capability, and provide evidence-based guidance for policymakers, extension services, and climate-resilient agricultural investment in one of East Africa’s most climate-sensitive regions. Distinct seasonal and spatial climate variability in Southern Ethiopia strongly influences maize production dynamics. Rainfall variability is closely linked to global ocean-atmosphere drivers such as ENSO, Indian Ocean Dipole, and Atlantic SST anomalies. Maize yields are highly sensitive to seasonal rainfall and temperature changes, with critical growth stages most vulnerable to climate fluctuations. Future projections indicate reduced rainfall during the main growing season (MAM) and increased temperatures, posing significant risks to maize productivity. Adaptation strategies including drought-resistant crops, adjusted planting schedules, and improved water management are essential to enhance resilience and food security.

Ethiopian pastoralist communities are facing a recurrent drought crisis that significantly affects the availability of water and pasture resources for communities dependent on livestock. The increasing intensity, duration and frequency of droughts in the pastoral community in Ethiopia have drawn the attention of multiple stakeholders and increased stakeholder debates on the role of early warning systems (EWSs) for anticipatory action to build climate resilience in the pastoral community. The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT), in collaboration with various partners, has developed an interactive web-based digital EWS to provide near real-time information on water and pasture conditions in pastoral and agro-pastoral regions of Ethiopia. In this study, a stakeholder analysis was conducted to identify key stakeholders, understand stakeholder needs, and facilitate collaboration towards sustaining the EWS. The stakeholder analysis revealed the roles and information needs of key actors engaged in livestock water and pasture monitoring and early warning systems aimed at improving the pastoral communities’ resilience. The analysis showed a pressing need for access to real-time information on water and pasture availability and seasonal climate forecasts by local communities for effective and optimal resources management. Local and national governments need similar data for evidence-based decision-making in resource allocation and policy development. International and non-governmental organizations (INGOs) require the same information for efficient humanitarian responses and targeted development interventions. The private sector seeks insights into market dynamics to better align production strategies with community needs. An EWS serves as a vital tool for development partners, facilitating improved planning, coordination, and impact assessment. It also emphasizes the importance of proactive collaboration among stakeholders, including local communities, government bodies, INGOs, and academic and research institutions. Enhanced communication strategies, such as partnerships with local media, are essential for timely information dissemination. Ultimately, sustained collaboration and adaptive strategies are crucial for optimizing the impact of an EWS towards improving the livelihoods and resilience of pastoral communities amid climate variability.

Transforming our food systems will require changing our innovation systems, in which organisations on agricultural research and innovation can play a crucial role. Key success factors for change can be organised into three dimensions: designing and managing transformative innovations, culture and structures of innovation organisations, and their engagement with the wider innovation ecosystem. Failures are crucial elements of innovation processes. Rapidly testing, sharing, building on, and learning from successful, and failed, innovations are key. This connects to the paradigm ‘Open Innovation 2.0’, which is widely applied in the private sector but not yet applied and evaluated for research and innovation organisations in the public sector or tertiary education. Four key principles emerge, namely big-picture action-oriented thinking, entrepreneurial organisational culture, close attention to partnerships and contexts, and diverse investment portfolios, with different levels of risk. These also imply—and require—the upstream transformation of funding and incentive systems.

There is a large and growing literature on the potential use of policy instruments for stimulating the adoption of Climate-Smart Agriculture (CSA) practices amongst smallholders. The objective of this article is to review and understand how the array of potential policy incentives can serve as mechanisms for enhancing adoption and upscaling of potential CSA practices by small-scale farmers in low-income countries. The review follows a matrix approach capturing where specific CSA practices (rows) are supported by typical policy instruments (columns) for enhancing widespread adoption. We first identify six key CSA practices, namely water management, soil and nutrient management, crop tolerance to stress, agroforestry and intercropping, crop rotation and mixed systems, and pest and disease management. Then we discuss the impact of those typical policy instruments, namely market prices, taxes and subsidies, land rights, rural finance, training and information, and certification and labeling. The review finds that most studies on this subject have a rather narrow focus on functional properties of a specific policy instrument and a particular CSA practice, thereby ignoring substitution, complementary or conditional effects between policy measures and CSA practices. Consequently, previous studies identify few incentives, particularly effective on their own. Wider perspectives on impact pathways point to the importance of sequencing and scaling for enhancing farmers' CSA adoption. We therefore advocate for more integrated approaches that also consider indirect effects of policy instruments on CSA adoption and pursue their systematic anchoring through successful policies that enhance widespread adoption.

The severity of the climate challenge requires a change in the climate response, from an incremental to a more far-reaching and radical transformative one. There is also a need to avoid maladaptation whereby responses to climate risk inadvertently reinforce vulnerability, exposure and risk for some sections of society. Innovative technological interventions are critical but enabling social, institutional and governance factors are the actual drivers of the transformative process. Bringing about this transformation requires inter- and transdisciplinary approaches, and the embracing of social equity. In this Perspective, we unpack what this means for agricultural research and, based on our collective experience, we map out a research agenda that weaves different research components into a holistic and transformative one. We do not offer best practice, but rather reflections on how agricultural research can more readily contribute to transformative adaptation, along with the personal and practical challenges of designing and implementing such an agenda.

Prioritization of adaptation options is complex. This study presents a multi-dimensional framework to evaluate how to allocate resources among competing alternatives. The main objectives of the study were to identify the prioritized climate-smart agricultural practices adopted among smallholder farmers in different value chains across sub-Saharan Africa (SSA) and to assess the economic feasibility of the practices using Cost-Benefit Analysis (CBA) to develop a portfolio of viable and cost-effective options. This study focused on selected five SSA countries and selected value chains. 153 smallholder farmers and stakeholders were interviewed. The Climate Smart Agriculture Prioritization Framework was applied for the assessment of economically viable adaptation options. The prioritization was based on standard ranks on the ability of the practice to improve productivity, increase resilience, and mitigation. Spearman's rank-order correlation was used to assess the independence of the ranks. A CBA was conducted as the final step. Smallholder farmers in the study areas prioritized the adoption of improved seed, good agricultural practices, and conservation agriculture practices. In the sweet potato value chain in Kenya, good agricultural practices was viable with an NPV of US$ 28,044, an IRR of 328%, and a one-year payback period. This is in comparison to the improved seed varieties (US$ 8,738, 111%, and two years payback period) respectively. In Nigeria, the most viable option was the improved seed in the potato value chain and good agricultural practices in the rice value chain. In Malawi, Ethiopia, and Zambia, the most viable practices were improved seed, and conservation agriculture in the soybean, faba beans, and peanut value chains respectively. The NPV was highly sensitive to changes in the discount rate, moderately to price, yield, and practice lifecycle, and least to changes in annual labour costs. The results elaborate on the most feasible adaptation practices that enable smallholder farmers to increase productivity and be economically efficient. The use of the CSA-PF consecutively with the CBA tool allows for the proper identification of best-bet CSA options.

A majority of smallholder farmers in sub-Saharan Africa (SSA) countries depend to a large extent on agriculture for food security and income. Efforts aimed at improving farm-related profitability are therefore important to improving livelihoods among smallholder farmers. In Ghana, for example, smallholder farmers that depend on agriculture face serious risks especially those related to climate change and variability and soil degradation. Notwithstanding these dangers, evidence of the published literature on how best to tackle these challenges is limited. Over the recent decades, however, there has been advancement by programs channelling resources into Climate-Smart Agricultural (CSA) practices to improving smallholder livelihoods and food security. The interest in advancing investment in CSA practices is a key pathway that has the potential to significantly reduce the negative effect of climate change and variability risks on smallholder farmers livelihoods. Investing in CSA practices is also a key pathway to improving farm yield per unit area. Consequently, smallholder farmers are adopting and implementing CSA practices. Despite that, a gap still exists on the profitability of undertaking such an investment, as this is key in determining the sustainability of CSA practices. On this basis, the present study undertook a detailed cost-benefit analysis (CBA) of seven CSA practices identified with smallholder farmers in the coastal savannah agro-ecological zone of Ghana. A total of 48 smallholder farmers that had adopted these practices were studied. Three CBA indicators namely the net present value (NPV), internal rate of return (IRR) and payback period (PP) were assessed for each of the seven CSA practices. The results showed that out of the seven CSA practices examined, six of them were profitably suitable for adoption and scaling up from the perspective of smallholder farmers as well as the public perspective. The finding from this study, therefore, fill the current information gap in the literature on the costs and benefits of adopting CSA practices on household livelihoods in Ghana. Such a finding is critical to the promotion and scaling up the adoption of CSA practices by smallholder farmers and serve as a basis of formulating appropriate guidelines and policies for supporting CSA practices.

Climate change adaptation strategies provide a cushion for smallholder farmers, especially in sub-Saharan Africa against the risks posed by climate hazards such as droughts and floods. However, the decision-making process in climate adaptation is complex. To better understand the dynamics of the process, we strive to answer this question: what are the potential trade-offs and synergies related to decision-making and implementation of climate adaptation strategies among smallholder farmers in sub-Saharan Africa region? A systematic literature review methodology was used through the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement with the four-stage inclusion/exclusion criteria to identify the literature from selected databases (Scopus and Google Scholar). The climate adaptation strategies are organized into five broad categories (crop management, risk management, soil/land management, water management, and livestock management strategies). Evidence suggests that potential trade-offs may arise concerning added costs, additional labor requirements, and competition among objectives or available resources. The synergies, on the other hand, arise from implementing two or more adaptation strategies concurrently in respect of increased productivity, resilience, yield stability, sustainability, and environmental protection. Trade-offs and synergies may also differ among the various adaptation strategies with minimum/zero tillage, comparatively, presenting more trade-offs. The development and promotion of low-cost adaptation strategies and complementary climate adaptation options that minimize the trade-offs and maximize the synergies are suggested. Skills and knowledge on proper implementation of climate change adaptation strategies are encouraged, especially at the local farm level.

Analysis of farmer risk perceptions is usually limited to production risks, with risk perception as a function of likelihood and severity. Such an approach is limited in the context of the many risks and other important risk attributes. Our analysis of the risk perceptions of farmers extends beyond production risks, severity of the risks, and their likelihoods. We first characterize agricultural risks and identify their main sources and consequences. We then analyze risk perceptions as a hierarchical construct using partial least squares path modelling. We determine the most important risks and risk attributes in the perceptions of farmers, and test for differences in the perceptions between men and women. Results show that severity and ability to prevent a risk are most important in forming risk perceptions. Second, probabilities (ability to prevent) tend to matter more to men (women) for some risks; lastly, low crop yields and fluctuating input prices have greater total effects on the overall risk perception. Our results provide an impetus for risk analysis in agriculture to consider risk attributes that cause affective reactions such as severity and perceived ability to prevent the risks, the need for input price stabilization, and redress of the rampart yield gaps in small-scale agriculture.

This report provides a summary/sythesis of key research outputs and messages gathered from the four year BMZ-funded project on Scaling up soil carbon enhancement interventions for food security and climate across complex landscapes in Kenya and Ethiopia.

Abstract Climate change adaptation strategies provide a cushion for smallholder farmers, especially in sub-Saharan Africa against the risks posed by climate hazards such as droughts and floods. However, the decision-making process in climate adaptation is complex. To better understand the dynamics of the process, we strive to answer this question: what are the potential trade-offs and synergies related to decision-making and implementation of climate adaptation strategies among smallholder farmers in sub-Saharan Africa region? A systematic literature review methodology was used through the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement with the four-stage inclusion/exclusion criteria to identify the literature from selected databases (Scopus and Google Scholar). The climate adaptation strategies are organized into five broad categories (crop management, risk management, soil/land management, water management, and livestock management strategies). Evidence suggests that potential trade-offs may arise concerning added costs, additional labor requirements, and competition among objectives or available resources. The synergies, on the other hand, arise from implementing two or more adaptation strategies concurrently in respect of increased productivity, resilience, yield stability, sustainability, and environmental protection. Trade-offs and synergies may also differ among the various adaptation strategies with minimum/zero tillage, comparatively, presenting more trade-offs. The development and promotion of low-cost adaptation strategies and complementary climate adaptation options that minimize the trade-offs and maximize the synergies are suggested. Skills and knowledge on proper implementation of climate change adaptation strategies are encouraged, especially at the local farm level.

Declining soil fertility is one of the major causes of food insecurity and high levels of poverty, both of which tend to hamper economic development in sub-Saharan Africa (SSA). To improve soil fertility, the implementation of soil organic carbon (SOC) enhancement technologies has become crucial to slowing land degradation, through increasing SOC, which is the basis of soil fertility. Using data from 381 households from Azuga-Suba and Yesir watersheds in Ethiopia, this study explores the extent of the adoption of technologies that enhance SOC. Soil organic carbon enhancing technologies include the use of manure, fertilizer, and crop residue management. The Probit model was used to assess what constrains the adoption of these technologies. The results indicate that fertilizer is the most adopted technology having over 90% adoption in both watersheds. Manure at 28% and 56% adoption while crop residue management at 37% and 26% adoption in Azuga-Suba and Yesir respectively. Technology adoption is highly constrained by lack of education, access to extension services, and access to credit services. Institutions and local farmer groups influence these constraints through training, provision of information, offering incentives, and credit services. Large plots hinder the use of manure and fertilizer due to the bulky nature of manure and the high costs of fertilizers. Insecurity in land tenure limits the adoption of manure and residue management. Perception of soil erosion and soil fertility tends to constrain the adoption of SOC technologies, as farmers are afraid that all improvements through soil amendment will be diminished through soil erosion. At the same time, farmers do not perceive the importance of SOC enhancing technologies in plots that were fertile. These results imply that strengthening institutions that enhance farmers' knowledge and provide credit as well as strengthening social protection schemes and farmer groups is crucial in promoting the adoption of these technologies.

The sustainable land management program (SLMP) of Ethiopia aims to improve livelihoods and create resilient communities and landscape to climate change. Soil organic carbon (SOC) sequestration is one of the key cobenefits of the SLMP. The objective of this study was to estimate the spatial dynamics of SOC in 2010 and 2018 (before and after SLMP) and identify the SOC sequestration hotspots at landscape scale in four selected SLMP watersheds in the Ethiopian highlands. The specific objectives were to: 1) comparatively evaluate SOC sequestration estimation model building strategies using either a single watershed, a combined dataset from all watersheds, and leave-one-watershed-out using Random Forest (RF) model; 2) map SOC stock of 2010 and 2018 to estimate amount of SOC sequestration and potential; 3) evaluate the impacts of SLM practices on SOC in four SLMP watersheds. A total of 397 auger composite samples from the topsoil (0?20 cm depth) were collected in 2010, and the same number of samples were collected from the same locations in 2018. We used simple statistics to assess the SOC change between the two periods, and machine learning models to predict SOC stock spatially. The study showed that statistically significant variation (P < 0.05) of SOC was observed between the two years in two watersheds (Gafera and Adi Tsegora) whereas the differences were not significant in the other two watersheds (Yesir and Azugashuba). Comparative analysis of model-setups shows that a combined dataset from all the four watersheds to train and test RF outperform the other two strategies (a single watershed alone and a leaveone-watershed-out to train and test RF) during the testing dataset. Thus, this approach was used to predict SOC stock before (2010) and after (2018) land management interventions and to derive the SOC sequestration maps. We estimated the sequestrated, achievable and target level of SOC stock spatially in the four watersheds. We assessed the impact of SLM practices, specifically bunds, terraces, biological and various forms of tillage practices on SOC using partial dependency algorithms of prediction models. No tillage (NT) increased SOC in all watersheds. The combination of physical and biological interventions (?bunds + vegetations? or ?terraces + vegetations?) resulted in the highest SOC stock, followed by the biological intervention. The achievable SOC stock analysis showed that further SOC stock sequestration of up to 13.7 Mg C ha?1 may be possible in the Adi Tsegora, 15.8 Mg C ha-1 in Gafera, 33.2 Mg C ha-1 in Azuga suba and 34.7 Mg C ha-1 in Yesir watersheds.

The last two decades have seen a rise of interest in the adoption and diffusion of agricultural technologies aimed at improving the sustainability of agricultural lands among smallholder farmers in developing countries. This papers set out to understand factors that influence the adoption of technologies that enhance soil carbon sequestration among smallholder farmers, using secondary data recorded in the World Overview of Conservation Approaches and Technologies (WOCAT) database from 45 to 50 smallholders' farmers in selected places in Kenya and Ethiopia respectively. A Probit model was used to analyse whether socio-economic, institutional, off-farm income, technical know-how, farmers' perceptions, and land use characteristics influences the adoption of technologies that enhance soil carbon sequestration. The results show that smallholder farmers that positively perceived net benefits of the soil carbon enhancing technologies were more likely to adopt such technologies that enhance soil carbon sequestration in both countries. Access to off-farm income and land ownership with title deeds were also found to be positively associated with adoption. Off-farm income positively influences adoption among farmer with a moderate income (100-500US$ per year) but not the rich (>500US$) farmers. Moderate to high level of skills and technical know-how required for implementing and maintaining a technology on the farm had a negative influence on adoption. This shows that interventions, aimed at addressing specific factors such as inadequate skills and knowledge, change in perception among farmers, and off-farm income are likely to have the greatest impact in decisions relating to the adoption of the soil carbon enhancing practices among farmers in East Africa.