Climate change adaptation Archives - Resilient Landscapes (RL)

Awareness and uptake gaps in climate variability adaptation and mitigation strategies among tree-crop, bee-product and fodder value chains: Eastern Province, Rwanda

Key messages

Around 50% of farmers adopt adaptation practices (resilient crops, agroforestry, soil and water management), but only ~10% use mitigation options such as renewable energy or energy-saving cookers.
Traders and processors show higher adoption rates for mitigation (~35% renewable energy, ~41% energy-saving measures), yet overall uptake among other value-chain actors remains below potential.
Farmers, buyers, processors, traders, and service providers have limited awareness and adoption of climate finance, as well as carbon credit opportunities, as mitigation measures.
Stakeholders are more aware of climate variability impacts than they are active in the utilization of adaptation or mitigation measures. Bridging this gap require=s inclusive finance, bundled incentives, and local capacity building.
Buyers, processors and traders lack a comprehensive understanding of climate change impacts and sustainable sourcing. This underscores the need for inclusive value-chain development and private-sector investment in climate-smart agriculture technologies.
Policymakers demonstrate relatively higher awareness and response capacity, while farmers, buyers, processors, and service providers require targeted capacity building to reach comparable levels.

Farmer information brief on the fodder value chain: Transformation of livelihoods and ecosystems through nature-based enterprises in Eastern Province, Rwanda

Key highlights

Planting improved fodder varieties (Napier, Brachiaria, Chloris gayana, fodder trees, legumes) can boost nutrition and milk yields.
Mixing grasses, trees and crop residues (maize, beans, rice straw) can provide year-round feed, especially in dry seasons.
Applying good management practices means proper land preparation, timely planting, manure use, regular weeding, and harvesting at the right stage.
Investing in improved fodder is important: one hectare can feed 15 dairy cows, raise milk output and deliver strong profits.
Climate resilience and livelihoods can be strengthened by reducing feed gaps, improving animal health, increasing manure for crops, creating jobs, and using tree-based systems to adapt to climate change.

Climate-Smart Practices for Sustainable Rice Farming: Impacts on Farm Technical Efficiency and Income in Pasuruan, East Java, Indonesia

The agricultural sector is a major source of greenhouse gas emissions and highly vulnerable to climate change. Climate-Smart Rice Cultivation (CSRC) offers a pathway to improve productivity, resilience, and reduce emissions in rice farming. This study evaluates CSRC’s impact on technical efficiency and income in Pasuruan District, East Java, under the ‘Rejoso Kita Phase 2’ project by World Agroforestry (ICRAF). A total of 249 rice farmers—168 CSRC adopters and 81 non-adopters—were surveyed using structured interviews. Stochastic frontier analysis and Propensity Score Matching (PSM) were applied to control for selection bias and estimate treatment effects. CSRC adopters statistically significant achieved higher technical efficiency (0.872) compared to non-CSRC (0.737). Although CSRC farmers achieved higher income (IDR 5,782,717) compared to non-CSRC (IDR 4,290,970), the difference was not statistically significant. Key determinants of adoption include age, experience, and land tenure; younger and more experienced farmers are more likely to adopt. These findings suggest that scaling CSRC can enhance resource-use efficiency and strengthen climate resilience, especially when supported through targeted outreach to younger farmers, capacity-building programs, and risk-mitigating incentives. Policy recommendations include promoting CSRC branding, strengthening value chains, and facilitating access to direct marketing channels to improve economic benefits over time.

Climate-smart agriculture and household food security: the case of smallholder farmers in semi-arid Tanzania

Smallholder farmers in the semi-arid districts of Kongwa and Chamwino, Tanzania, are increasingly vulnerable to food insecurity due to the escalating impacts of climate change. This study examined the association between climate-smart agriculture (CSA) adoption and food security using survey data from 380 households. The findings indicate that manure application, drought-tolerant seeds, and tree intercropping are the most widely adopted CSA practices, although the adoption rate declines as adoption intensity increases: approximately 25% of households adopt only one practice, while fewer than 5% implement six. CSA adoption was associated with higher dietary diversity (HDDS), improved food consumption scores (FCS), and lower household food insecurity access scores (HFIAS) and reduced coping strategies index (rCSI). CSA adoption was also associated with higher farm income, with greater adoption intensity amplifying both food security and income benefits. Household characteristics, including education, gender, off-farm income, asset ownership, and access to extension services, were linked to variations in adoption and outcomes. These findings highlight the potential of integrated CSA strategies to support food security and livelihoods. Policies promoting CSA intensification, addressing socio-economic barriers, strengthening extension services, and targeting gender disparities can enhance the effectiveness and inclusivity of CSA adoption in semi-arid Tanzania.

Integrating machine learning to assess climate risks on reservoir’s inflow and hydropower generation across West African basins

This study presents a novel five-step ensemble machine learning approach to improve predictive accuracy in assessing climate change impacts on inflow patterns and hydropower generation across seven dam basins in West Africa. The methodology integrates precipitation and temperature using the multi-lag approach. An initial pool of fifteen machine learning models were evaluated, and top-performing models were selected for further refinement through iterative ensemble stacking and weak learner elimination. Historical analysis (1983–2014) utilized CHIRPS and CHIRTS datasets. Future projections employed twelve bias-adjusted CMIP6 models and their ensemble mean (EnsMean) under SSP1-2.6, SSP2-4.5, and SSP5-8.5 for the near (2036–2067) and far (2068–2099) futures. Results showed notable improvements in model accuracy and efficiency across layers, with R² and NSE exceeding 0.6 for all inflow simulations and for selected energy simulations (Bagre, Nangbeto, and Taabo). Projections indicated warming up to 4.5°C and spatially heterogeneous precipitation changes across basins and scenarios, with SSP5-8.5 projecting the most pronounced shifts. Inflow reductions are projected to reach up to 24% at Buyo and 13% at Nangbeto, while hydropower output may decline by up to 19% at Nangbeto and 58% at Taabo in the future. Conversely, Manantali and Taabo are projected to experience inflow increases, and Bagre may see energy gains of up to 42% under SSP5-8.5. These findings highlight heightened vulnerability, as well as contrasting opportunities across the region, underscoring the urgent need for adaptive management strategies, such as enhancing hydropower system resilience, diversifying energy portfolios, and integrating renewable sources to mitigate climate risks. Hydropower managers and policymakers must prioritize proactive measures to ensure energy security and sustainable resource management amid changing climatic conditions.

Field and laboratory manual for unsupported 210Pb analyses

This manual provides a general conceptual framework for collecting and analyzing radionuclides related to the ²¹⁰Pb dating method in mangrove ecosystems. The ²¹⁰Pb radionuclide dating method applies alpha and/or gamma spectrometry. This guide outlines procedures for field sample collection, laboratory analyses and data analyses relating to these approaches.

Field and laboratory manual for unsupported 210Pb analyses

Temporal and spatial variability in photosynthetic activity of Vitellaria paradoxa in agroforestry parklands of Burkina Faso

This study investigated the temporal and spatial variation in photosynthetic activity of Vitellaria paradoxa (shea tree) growing in agroforestry parklands across two contrasting climatic zones of Burkina Faso. Measurements of chlorophyll fluorescence, chlorophyll content, leaf temperature, stomatal conductance, and environmental variables were conducted from April to December 2023 to assess physiological responses to climatic variability. Significant differences were observed between the northern and southern Sudanian phytogeographical zones, particularly in chlorophyll content, energy dissipation mechanisms, and photosynthetic performance. Trees in the more humid southern Sudanian zone exhibited higher chlorophyll content and better photosynthetic efficiency than those in the drier northern zone. Leaf temperature was strongly influenced by ambient temperature, while vapor pressure deficit and photosynthetically active radiation affected stomatal conductance and energy dissipation processes. The results demonstrate that V. paradoxa possesses physiological mechanisms that enable adaptation to changing environmental conditions, including regulation of heat dissipation, chlorophyll utilization, and gas exchange. These findings improve understanding of the ecophysiological resilience of shea trees under climate change and provide insights for sustaining agroforestry parklands in the Sudano-Sahelian region.

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