Can climate-smart macadamia agroforestry systems safeguard smallholder farmers against climate shocks in Malawi?

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Emmanuel Junior Zuza, William Banda, Yoseph Araya, Andrew Emmott, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9303871/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Smallholder farmer resilience to climate change is commonly assessed through discrete adaptation measures, overlooking the potential of integrated land use systems. Our study explores Climate-Smart Macadamia Agroforestry (CSMA) as a climate adaptation strategy in central Malawi. We examine farmer perceptions, existing climate challenges, and the feasibility of scaling up CSMA systems to enhance adaptive capacity. Moving beyond approaches that treat adaptation as isolated interventions, we identify two distinct pathways: system-integrated resilience among CSMA farmers, where multiple adaptive benefits are embedded within the land use system itself; and discrete strategy adoption among non-CSMA farmers, which typically requires costly, separate interventions. Moreover, our study reveals that CSMA inherently bundles ecosystem services, including temporal flexibility, income diversification, and carbon sequestration, that collectively strengthen adaptive capacity without additional investment, while monoculture systems remain comparatively vulnerable. By quantifying performance differences in yield stability and income resilience between the two groups, we identify strategic opportunities for mainstreaming agroforestry into climate adaptation and land use planning frameworks. Practically, the study also highlights targeted interventions including drought-tolerant varieties, integrated pest management, and post-harvest technologies that can enhance smallholder resilience not only in Malawi but across comparable farming systems in sub-Saharan Africa SSA) and globally. Smallholder resilience adaptation strategies Sub-Saharan Africa sustainable agriculture integrated land use systems mixed methods Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Climate change poses a fundamental threat to agricultural systems across Sub-Saharan Africa (SSA), with particularly severe consequences for countries where smallholder farming underpins both livelihoods and national economies (Morton, 2007 ; Zenda, 2024 ; Akram et al., 2025 ). Malawi exemplifies this vulnerability: approximately 80% of the population are smallholder farmers and depend on rainfed agriculture, which contributes nearly 30% to national GDP (Abidoye et al., 2025 ). Increasingly erratic rainfall, rising temperatures, and more frequent extreme weather events are disrupting traditional farming calendars, altering crop growth cycles, increasing evapotranspiration, and compressing already narrow planting windows (Likoya et al., 2023 ). These climatic pressures compound structural vulnerabilities, inadequate irrigation infrastructure, limited institutional support, and widespread poverty that severely constrain farmers’ adaptive capacity. Despite these challenges, smallholder farmers are not passive victims of climate change but active agents developing innovative responses to emerging risks. Studies have shown that successful climate adaptation in smallholder systems comes from integrating traditional knowledge with improved technologies, supported by appropriate policy frameworks and institutional arrangements (Simon & Leck, 2015 ; Taylor, 2016 ; Chemura et al., 2025 ). Among numerous adaptation strategies one common viable option is agroforestry systems. Agroforestry is a practice that integrates trees with annual crops and/or livestock. The practice offers multiple co-benefits, including improved soil health (Putra et al., 2025), enhanced water retention (Kaushal et al., 2021 ), diversified income streams (Castle et al., 2021 ), and reduced risk exposure through temporal and spatial production diversification (Matevski et al., 2024 ; Ndhlovu, 2025). In Malawi, various agroforestry practices have shown potential for addressing climate challenges while maintaining or improving productivity, though adoption rates remain variable across contexts and farming systems (Muzungwi et al., 2024). Within the range of agroforestry options available to Malawian smallholder farmers, macadamia-based systems (hereafter referred to as climate-smart macadamia agroforestry, CSMA), which involve intercropping annual crops such as maize, soybeans, groundnuts, common beans, potatoes, and pigeon peas and/or integration with livestock rearing have emerged as a particularly promising climate-smart alternative. Macadamia trees possess several characteristics well-suited to climate variability: deep root systems that access groundwater during dry periods (Carr, 2013 ), tolerance to temperature fluctuations (Huett, 2004 ), and productive lifespans extending several decades (Hardner et al., 2019 ). Additionally, macadamia nuts command premium prices in international markets, thereby providing smallholders with improved income stability (Rogiers et al., 2025 ). However, the implementation of CSMA particularly by smallholders faces considerable challenges that require careful examination. These include the significant upfront investment required for tree establishment (macadamia seedlings cost around USD $ 4), the extended gestation period before productive harvests begin, technical knowledge requirements, and potential trade-offs with immediate food security and income needs (Zuza et al., 2024 ; Baipai et al., 2025 ). Furthermore, individual farmers not affiliated with cooperatives face particular difficulties in accessing markets, securing inputs, and obtaining tree seedlings, suggesting that blended financial support mechanisms are needed to facilitate adoption (Zuza et al., 2024 ). As such, understanding how these factors interact with farmer decision-making and existing livelihood strategies is essential for designing appropriate support interventions. The central Malawi districts of Ntchisi and Dowa provide a helpful context for examining these dynamics. Both districts are characterised by mixed farming systems dominated by staple crop production, with farmers increasingly recognising the need for diversification to address climate risks. The presence of both CSMA adopters and non-adopters within the same agroecological zones enables comparative analysis of the factors influencing adoption decisions and outcomes. Our study therefore aims to contribute to the growing body of practice-oriented knowledge on agroforestry in SSA by evaluating the potential of CSMA to enhance smallholder resilience in central Malawi. Through a mixed-methods approach, our study addresses three central research questions: (1) What are the impacts of climate change on crop yields and the farming calendar? (2) What are the impacts of climate change on farmer incomes, crop marketing, and input costs? (3) What adaptation strategies are implemented to counter the impacts of climate change? The findings are intended to inform policy development, extension programme design, and future research priorities in support of climate-resilient agricultural development in Malawi and comparable contexts across the region. 2. Materials and methods 2.1. Description of the study area The study was conducted in Dowa and Ntchisi districts of Malawi’s central region (Fig. 1 a). These districts were purposively selected due to their agricultural importance, vulnerability to climate impacts, and their status in macadamia cultivation. Both districts are dominated by smallholder farming systems, with maize serving as the principal staple crop and coffee, groundnuts, soybeans, potatoes and green vegetables as cash crops (Chinseu et al., 2019 ). Additionally, these districts also represent the highest concentration of macadamia producers in central Malawi. Dowa district covers an area of 3,041 km², with altitudes ranging between 700–1,500 metres above sea level (m.a.s.l). The district is divided into seven Extension Planning Areas (EPAs), with macadamia production concentrated in the Nachisaka EPA (Fig. 1 b). EPAs are administrative units established to facilitate agricultural extension and development planning (Banda, 2025). Dowa experiences an annual temperature range of 10–32°C and receives 800–1,500 mm of rainfall annually, largely influenced by elevation (Zuza et al., 2024 ). Ntchisi district covers an area of 1,655 km², with altitudes ranging from 900 to over 2,000 m.a.s.l., creating diverse agroecological conditions across the landscape. For instance, Kalira EPA spans from hot, dry lowlands along the Rift Valley escarpment to cool, wet uplands on the Rift Valley ridge. Rainfall distribution varies among the EPAs as well, with Malomo receiving relatively lower precipitation (800–1200 mm) compared to Chikwatula and Kalira (1,200–1,500 mm). The district records an annual temperature range from approximately 8°C in the cold season to 35°C in the hot season (Jere et al., 2020 ). These varied yet generally favourable climatic and edaphic conditions support macadamia cultivation across all EPAs in the district. 2.2. Sampling and data collection A mixed methods approach (Tashakkori & Teddlie, 2010 ) involving a structured household questionnaire and focus group discussions (FGDs) was used to gain understanding of farmer perceptions and experiences regarding the impact of climate change on their livelihoods and agricultural production. Both instruments were developed drawing on the thematic priorities identified in Section 1 and were directly informed by the recommendations of Zuza et al. ( 2024 ), who called for empirical investigation into the impacts of CSMA on smallholder farmer resilience to climate change in Malawi. The FGDs were designed to elicit deeper contextual perspectives that structured questionnaires alone cannot readily capture. The study used a stratified random sampling approach (Iliyasu & Etikan, 2021 ), with EPA serving as the primary strata. Within each stratum, villages were randomly selected, followed by systematic random household sampling. This approach ensured geographical diversity while maintaining statistical representativeness. The structured questionnaire was administered to 119 farmers, both CSMA and non-CSMA adopters, across the two study districts in February 2025. In Dowa district, sampling was conducted in Nachisaka EPA, while in Ntchisi district, sampling covered Chikwatula, Kalira, Malomo, and Chipuka EPAs. The survey provided breadth and comparability, allowing patterns, relationships, and the prevalence of climate-related challenges and adaptation practices to be identified (Weyant, 2022). To complement the survey data, five FGDs one in each of the five mentioned EPAs each comprising ten members were conducted across the EPAs with both male and female farmers. FGDs were particularly valuable in generating nuanced insights into participants’ lived experiences, uncovering the social dynamics, shared perspectives, and gendered dimensions of climate-related challenges and adaptation practices. While FGD findings cannot be generalised to wider populations, they enriched the quantitative evidence by providing depth and contextual understanding of the factors that motivate, support, or constrain the adoption of climate-smart practices (Li et al., 2020 ). Together, the survey and FGDs produced a robust evidence base, combining generalisable quantitative patterns with detailed qualitative insights. We obtained favourable ethical approval for the study from both the Human Research Ethics Committee (HREC) of The Open University, United Kingdom and Highlands Macadamia Cooperative Union Limited (HIMACUL), Malawi. 2.3. Data analysis Quantitative data was analysed using Python programming language, with descriptive statistics generated for key variables. Cross-tabulations and correlation analyses were conducted to explore relationships between farmer characteristics, climate impacts, and adaptation strategies. Qualitative data from the FGDs was transcribed and examined using Bryman (2016) six phase reflexive approach to thematic analysis. This process enabled the systematic identification of recurrent themes and emerging issues. The rich narratives captured through the FGDs provided deeper contextual insights into the research questions, offering perspectives often overlooked in conventional adoption studies (Chinseu et al., 2018). The deductive (theory-driven) approach was applied during coding and interpretation, ensuring that analysis was grounded in participants’ accounts. 3. Results 3.1. Farmer characteristics Our study comprised of 48 CSMA and 71 non-CSMA farmers (Table 1 ). Male respondents constituted 58% of the overall sample, with a higher proportion among CSMA farmers (64.6%) than non-macadamia farmers (53.5%), though this difference was not statistically significant using an independent t-test ( P = 0.23). The most striking demographic distinction was age. CSMA farmers were significantly older than their non-CSMA farmers ( P ≤ 0.001), a 14.8-year differential that reflects macadamia’s local characterization as a “retirement crop.” However, this term does not imply post career cultivation but rather captures the reality that macadamia adoption requires substantial upfront capital for land and seedlings, coupled with tolerance for delayed returns during the tree’s lengthy maturation period. Our FDGs confirmed that older farmers, having accumulated productive assets and secured land tenure over decades, were better positioned to absorb these costs, whereas younger farmers face binding constraints in land access and credit availability. Table 1 Demographic characteristics of CSMA and non-CSMA farming households Variable Non-CSMA farmers % CSMA farmers % Total % t-test Gender Male 53.5 64.6 58 0.23 Female 46.5 35.4 42 Education attainment Partial primary school 39.4 43.8 41 Completed primary school 21.1 16.7 19.3 Partial secondary school 18.3 20.8 19.3 0.946 Completed secondary school 19.7 16.7 18.5 Attended tertiary education 1.4 2.1 1.7 Mean of household age Mean 39.6 54.4 45.5 Std. err. 1.5 1.8 1.3 0.000 Std. dev. 12.6 12.6 14.5 3.2. Education attainment Education is often a key factor shaping farmers’ ability to adopt new practices and technologies. We, however, found that formal educational attainment was uniformly low across both adopters and non-adopters of CSMA, suggesting that schooling levels were not a distinguishing factor in adoption decisions within this population. The majority of respondents (60.5%) had not progressed beyond primary education, while tertiary education was extremely rare (≤ 2.1%). Most farmers therefore relied far more on experiential learning than on formal schooling to guide their farming decisions. As one farmer explained: I left school after standard 5 (primary school) because my family needed help with farming. Most of my knowledge about agriculture comes from practical experience rather than formal education. Another farmer emphasised the intergenerational transmission of knowledge: You know what, farming is all about experience and how long you have been practicing. My farming knowledge has been passed from generation to generation, so I did not go to school, I was busy taking care of the fields.” At the same time, farmers’ narratives reveal that access to extension services plays a critical role in supplementing limited formal education. Several respondents reported a noticeable decline in public extension support over time, particularly for macadamia relative to staple crops and as such impacting their practices and yields. One farmer reflected: Most of my farming knowledge comes from observing parents, neighbours, attending field days and farmer field schools. Back in the early 2000s, when I was diversifying to macadamia, alangizi (extension workers) from the EPA visited us weekly, providing training on good production practices. Today, that support has largely disappeared; extension officers now focus on other important crops, and only HIMACUL continues to offer us advice on macadamia nut production. Another added: As of late there has been a decline in our contact with alangizi. This is especially true for macadamia farming. Other crops like maize, soybeans and groundnuts are well supported but not this one. This makes it difficult for us to know what to do when we have issues, especially on pests and disease management and soil nutritional management. 3.3. Impacts of climate change on crop yields Our findings reveal that climate change has negative impacts on agricultural productivity, with substantial and differentiated effects documented across farming systems. The analysis shows notable disparities in climate vulnerability between crop types, with non-CSMA farmers experiencing significantly greater yield reductions (70%) compared to CSMA farmers (56%) over the preceding five-year period (see Table 2 ). Although the difference is not statistically significant through the use of Chi square test ( P = 0.266), the trend suggests comparatively greater climate resilience within CSMA systems than in conventional monoculture systems. Table 2 Impact of climate change on crop yields among CSMA and non-CSMA farmers Variable Non-CSMA farmers % CSMA % Total % P-value Significantly decreased 70.4 56.3 64.7 0.266 Slightly decreased 26.8 33.3 29.4 No change 1.4 2.1 1.7 Slightly increased 1.4 4.2 2.5 Significantly increased 0 4.2 1.7 These quantitative findings are reinforced by qualitative evidence that explains the mechanisms driving productivity changes. Non-CSMA farmers particularly emphasised the disruption of traditional seasonal patterns, especially rainfall variability: “We’ve experienced increasingly unpredictable rainfall patterns over the past five years. When I started farming 30 years ago, we could reliably predict when to plant our crops each growing season which was always in October, but now the rains come late or stop unexpectedly. Last season, my maize yield was half what I harvested five years ago.” Such reasons reflect heightened climate uncertainty, including delayed onset of rains, early cessation, and erratic distribution, all of which undermine planning, crop establishment, and yield stability in monocropping systems. In contrast, CSMA farmers described tangible protective benefits associated with macadamia-based agroforestry systems. Tree cover was perceived as moderating microclimatic extremes and reducing physical crop damage during extreme weather events: The climate has really changed over the years. We used to get reliable Chiperoni rains during the dry seasons here, but now they hardly come. I tell you, without underplanting these macadamia trees with maize, soybeans, and groundnuts, I would be in serious trouble. During the past years of cyclones Idai and Kenneth, I watched my neighbours lose their entire maize crop to those terrible winds and floods, but my fields stayed protected. The trees shielded and protected the annual crops - breaking the wind and stopping the water from washing everything away. That’s when I truly understood the power of growing macadamia alongside other crops. This testimony highlights key resilience mechanisms associated with CSMA systems, including windbreak effects, reduced soil erosion, improved water retention, and structural protection during storms. At the same time, both farmer groups reported emerging climate-related challenges, particularly shifts in pest dynamics: We’ve observed new pest patterns over the past three seasons. The stink bugs in macadamia and soybeans that previously appeared only briefly now persist throughout much of the growing season, requiring additional management interventions, increasing our production costs, and in cases where we have failed to manage them causing heavy losses on crops, especially macadamia nuts. Another farmer reported: You know there is this new pest “Kapuchi” (Fall armyworm) this one is trouble. Once it is in your maize you are done. I don’t know where it came from but it’s a big challenge. We have been experimenting on local remedies such as the use of fish soup, application of sand, and neem tree extracts combined with constant monitoring but its tough. 3.4. Impacts of climate change on the seasonal farming calendar Beyond yield reductions, climate change has disrupted fundamental farming operations across multiple dimensions in the study area. Traditional planting and harvesting calendars have been particularly affected, with all of the respondents (100%) reporting severe disruptions to seasonal timing. During FDGs, farmers frequently mentioned the difficulty in planning agricultural activities, with one farmer noting: Previously, we knew exactly when to prepare our fields and when to sow the seeds. Now, we’re constantly adjusting our schedules based on weather patterns that seem to change every season. These temporal disruptions were worsened by resource-related challenges. Water availability (droughts) has become increasingly problematic, with most respondents reporting moderate to severe impacts (Fig. 2 ). Simultaneously, pest occurrence has intensified, creating additional pressure on already vulnerable crops. These combined stressors have created a cascade of challenges that collectively contribute to the reported declines in crop yields, establishing a concerning pattern of multi-dimensional agricultural vulnerability across the study areas. In addition, declining yields and income makes it even more difficult over time for farmers to make the transitions needed to invest in CSMA. However, at production system level 70% non-CSMA farmers reported severe impacts on planting and harvesting times, while about 45% experienced significant yield reductions. In contrast, CSMA farmers reported fewer severe impacts across all dimensions, suggesting that integrating macadamia into farming systems may buffer against climate-related shocks. 3.5. Impacts of climate change on farmer incomes Climate change has generated substantial economic challenges among the study households, with income reductions representing a widespread phenomenon affecting both macadamia and non-macadamia producers. Analysis of income changes over the past three years reveals that the majority of farmers have experienced significant financial hardship, with 59.2% of non-CSMA farmers and 54.2% of CSMA farmers reporting that their incomes have markedly decreased (Fig. 3 ). An additional 23.9% of non-CSMA farmers and 31.3% of CSMA farmers experienced slight income reductions, bringing the total proportion of farmers facing income declines to over 80% across both groups. However, despite experiencing similar proportions of income decline, CSMA farmers reported greater economic resilience through diversified income streams and extended harvest periods. CSMA farmers highlighted how agroforestry systems provided crucial economic flexibility during vulnerable periods. The extended harvesting calendar emerged as a particularly important resilience mechanism, with farmers emphasising how multiple harvest periods throughout the season provided income when other crops failed. As one CSMA farmer explained: With macadamia, I can harvest three times per season. This is crucial during the lean period in January when Christmas expenses are done, school fees are due, and our maize stores are finished. I use some nuts for food and sell the rest for income to buy more food and pay school fees. Yes, my income has declined, but I’m still better off than farmers without macadamia trees. This statement shows how CSMA addresses both food and nutritional security and cash flow challenges that are particularly acute during the lean season in Malawi. The ability to harvest throughout the year provides macadamia farmers with financial flexibility that monoculture farmers lack, enabling them to meet seasonal expenses like school fees and food purchases when annual crop reserves are depleted. 3.6. Impacts of climate change on crop marketing Climate change has created significant barriers to market participation for smallholder farmers across both of the study areas. The survey findings reveal that reduced crop quality stands as the predominant challenge, affecting 38.4% of all respondents. Farmers described how increasingly variable weather conditions have compromised product standards. A farmer reported: Droughts and late seasonal rains have significantly affected both groundnut quantity and quality. For groundnuts droughts result in rosette (a disease in groundnuts) and make them easily affected by chuku (aflatoxins). Similarly, late seasonal rains during groundnut harvesting and drying encourages moisture, which results in fungal contamination and high levels of aflatoxin. As a result, the majority of the groundnut cannot be sold to international markets due to higher levels of aflatoxins. Another farmer echoed: The maize we’ve harvested recently doesn’t store as well due to inconsistent maturation caused by erratic rainfall. This forces us to either consume it quickly or sell at reduced prices, leaving us vulnerable to food shortages later in the season. Market dynamics have also shifted due to climate-induced scarcity, with 28.8% of respondents reporting increased competition. This has created a paradoxical situation where overall supply decreases while individual farmers face greater difficulty securing buyers. Transportation infrastructure vulnerabilities have emerged as another significant constraint, with 11.8% of respondents citing extreme weather events as disrupting market access routes. However, 17.5% of respondents reported no discernible impact on market access, suggesting some variation in resilience factors across the surveyed population. This merits further investigation to identify potential adaptive practices that could be more broadly applied. 3.7. Farming input cost escalation due to climate change The survey results reveal a strong perception that climate change has contributed to rising agricultural input costs, with 67.5% of respondents affirming this connection. Several farmers provided specific mechanisms through which climate change has increased production expenses. The economic implications extend beyond direct input costs to include risk management expenses. Farmers reported investing in contingency supplies, including backup seeds, additional pesticides, and emergency fertilisers to protect them against climate uncertainties, further straining household budgets already under pressure from reduced yields and market volatility. A farmer explained: We now need to apply fertiliser multiple times due to heavy rains washing away nutrients. Seeds that previously performed well now fail under current conditions, forcing us to purchase more expensive climate-adapted varieties. The unpredictability means we must invest in contingency supplies, significantly increasing our production costs. While 25.2% of respondents did not perceive a climate-related cost increase and 7.4% remained uncertain, the predominant consensus supports a strong connection between changing climate conditions and heightened production expenses. 3.8. Climate change adaptation mechanisms Adaptive capacity reflects farmers’ inherent ability to respond to, adjust to, and recover from climate-induced challenges through the implementation of appropriate coping mechanisms. Our results reveal distinct adoption patterns between macadamia and non-macadamia farmers, highlighting differential adaptive approaches across crop types (Fig. 4 ). The findings show that CSMA farmers concentrate on changing planting dates (68% adoption), while non-macadamia farmers exhibit more diversified strategy portfolios with higher uptake of soil conservation practices (68.5%), improved irrigation (61.5%), agroforestry (56.4%), and crop diversification (64.7%). Drought-resistant varieties show balanced adoption across both systems (44.6% macadamia vs. 55.4% non-macadamia). A farmer reported: You know rainfall has become unreliable, so I’ve adapted by using hybrid maize varieties from the farm input subsidy programme. These varieties can withstand short dry spells during the season and still produce good yields A macadamia farmer highlighted: “Over my 60 years, planting used to be predictable. We always planted in mid-October, and we could even plant a week earlier knowing the rains would arrive the following week. Today, this certainty no longer exists. I must adjust planting dates each season based on rainfall patterns. In some years, we have planted as late as Christmas.” These contrasting patterns largely reflect inherent characteristics of CSMA production systems rather than differential adaptive capacity. CSMA inherently incorporates many practices that non-macadamia farmers implement as discrete adaptation strategies. Basin construction for water harvesting, permanent ground cover maintenance, and intercropping with annual crops provide integrated soil conservation and diversification benefits within macadamia orchards. Since these measures are embedded within the production system, macadamia farmers are less likely to identify them as separate “adaptation strategies” and instead emphasise accessible temporal adjustments like planting-date modifications of their annual crops. This suggests that while both farming systems demonstrate adaptive capacity, they express it through fundamentally different approaches, macadamia farmers through system-integrated practices and temporal flexibility, and non-macadamia farmers through explicit implementation of multiple discrete strategies. 4. Discussion 4.1. Impacts of climate change on crop yields and the farming calendar Climate change reduces crop yields through both direct effects on crop growth and the ways farmers respond to the shocks they experience. Our study shows that vulnerability varies between macadamia and non-macadamia farming systems, with important implications for adaptation. Although both groups of farmers reported substantial yield declines, the 14%-point difference between non-macadamia (70%) and macadamia farmers (56%) experiencing severe decreases highlights differences in resilience. We argue that CSMA systems provide a degree of buffering that monoculture systems often lack. The buffering role of CSMA was particularly visible during extreme weather climatic events, including the years Malawi experienced severe droughts and tropical cyclones such as Kenneth (2019) and Idai (2021). CSMA systems provided multiple layers of protection: they reduced the force of winds, limited physical damage to the annual crops and infrastructure, stabilised soils, and moderated rainfall impacts through canopy interception and litter accumulation, which together diminished runoff, erosion, and flooding. These farmer observations are corroborated by controlled studies indicating that agroforestry windbreaks can reduce wind speeds by 17–67% and surface runoff by 30–50% (Cleugh, 1998 ; Mume & Workalemahu, 2021 ; Baker et al., 2025 ). As the frequency and severity of extreme weather events intensify under climate change, such ecosystem-based protections are valuable for climate adaptation. This contrasts with monocultural systems, which remain highly vulnerable and often experience catastrophic yield losses under comparable shocks (Mkondiwa et al., 2025 ). Beyond yield reductions, climate change has also disrupted fundamental farming operations by undermining the reliability of traditional planting and harvesting calendars. This reflects a broader global pattern where altered rainfall onset, shortened growing seasons, and unpredictable dry spells are forcing farmers to abandon established scheduling practices. This finding is consistent with studies in SSA, where climatic variability has increasingly led to shorter and more unpredictable planting windows, affecting crop planning and productivity (Chikowo et al., 2014 ; Fiwa et al., 2014 ; Moyo et al., 2017 ). The shortening of the growing season poses particular challenges for smallholder farmers reliant on rainfed agriculture, as it compresses the time available for crop establishment and development, potentially reducing yields. Furthermore, studies in East Africa show that changing rainfall patterns have delayed sowing dates and increased uncertainty in maize-based systems (Adhikari et al., 2015 ; Apraku et al., 2021 ; Palmer et al., 2023 ). Similar disruptions are reported in South Asia, where erratic monsoon onset has forced rice farmers to alter planting windows, often with negative yield consequences (Junaid et al., 2021 ; Habib-ur-Rahman et al., 2022 ). Evidence from Latin America also highlights how temperature shifts and irregular precipitation are reducing the effectiveness of traditional agricultural calendars, undermining the reliability of indigenous knowledge systems (Tovar et al., 2022 ; van Leeuwen et al., 2024 ). These findings reinforce our results by demonstrating that the erosion of seasonal predictability is not unique to our study area but is emerging as a global challenge for smallholder agriculture. These challenges are further complicated by resource pressures and the intensification of insect pests. Water availability has become increasingly problematic, with most respondents reporting moderate to severe impacts. At the same time, pest occurrence has intensified, creating additional stress on already vulnerable crops. Farmers highlighted, for example, how stink bugs that attack soybeans and macadamia, once seasonal, are now present throughout the growing period, requiring greater effort and cost to manage. The observed change in the presence of pests from occasional to present throughout the season challenges the effectiveness of traditional pest management practices, suggesting a migration to integrated pest management systems that embrace the role of climate change on crop production. This aligns with evidence that climate change is altering insect life cycles by extending reproductive periods and delaying dormancy (Skendžić et al., 2021 ; Subedi et al., 2023 ). The effects of shifting rainfall, reduced water availability, and pest intensification create a cascade of challenges that together contribute to yield declines, establishing a pattern of multi-dimensional agricultural vulnerability across the study area. 4.2. Impacts of climate change on farmer incomes, crop marketing, and input costs Climate change affects farmers’ livelihoods through direct impacts on agricultural productivity and cascade effects that amplify economic losses. Climate variability puts production of annual crops at risk, with over 80% of farming households in our study experiencing income declines. Farmers relying solely on annual crops are particularly vulnerable to these climate shocks, facing huge income reductions. We found that having access to diversified income streams through CSMA helps resolve some of these economic vulnerabilities while also directly impacting household resilience. The economic impacts manifest differently across farming systems, with CSMA farmers being more resilient compared to non-macadamia farmers. This may be due to the nature of macadamia as a specialty crop with a focus on market and export orientation. Consequently, farmers cultivating macadamia benefit from export markets and high revenues. This economic positioning allows farmers to make meaningful investments in climate shock buffering strategies better than subsistence farmers (Barrett, 2010 ). It is also important to note that the specialty nature of macadamia has attracted particular attention from institutional and policy support, making it one of the government’s strategic export crops and benefiting from deliberate efforts to promote its cultivation. Additionally, CSMA provides valuable ecosystem services that generate extra economic benefits unavailable to non-macadamia farmers. Mature macadamia trees sequester about 20 kg of carbon dioxide annually, creating potential carbon credit income per tree each year in emerging carbon markets (Paembonan et al., 2021 ). In contrast, non-CSMA farmers lack access to these carbon revenue streams and are more vulnerable to input price shocks due to greater reliance on external fertilizers and pest control measures. This demonstrates that agroforestry systems can reduce income volatility by 20–40% during extreme weather events compared to monoculture systems and provide ecosystem service benefits valued at USD $ 500–1,500 per hectare annually (Price, 1995 ; Kay et al., 2019 ; Bhattarai et al., 2025 ). Our survey results show that farmers practicing CSMA are less likely to experience complete income loss during climate shocks. These farmers are better able to maintain cash flow through multiple macadamia harvests, especially during the lean season harvests. Macadamia trees also enhance soil water retention through leaf litter and root systems, reducing water stress and fertiliser quantities for the intercropped annuals (Simba et al., 2023 ; Xu et al., 2025 ). Evidence further shows that agroforestry systems deliver multiple adaptation benefits, including risk reduction through diversification (Kittur et al., 2024 ) and microclimate regulation (Shekmohammed et al., 2021 ). However, non-macadamia farmers face heightened economic risks from single harvests and higher production costs (fertilisers and pesticides), making them particularly vulnerable to weather-related losses and input price fluctuations, often resorting to borrowing or selling assets to meet basic needs. This comparative advantage demonstrates CSMA’s capacity to provide both food and nutritional security alongside cash flow stability while generating ecosystem service income streams. Climate extremes create cascading economic impacts where drought leads to crop failure, especially among non-macadamia farmers, necessitating complete replanting which represents a double loss similar to flood damage. CSMA farmers benefit from tree-based stability that maintains some income even when annual crops fail. Moreover, non-macadamia farmers invest heavily in contingency supplies, including backup seeds, additional pesticides, and emergency fertilisers to safeguard against climate uncertainties, typically adding USD $ 100–150 per hectare in risk management costs. Conversely, CSMA farmers leverage ecosystem services such as natural pest control and soil fertility enhancement to reduce contingency input needs, spending 40% less on risk management compared to monoculture systems. Complex market dynamics create additional economic pressures, with reduced crop quality affecting 38.4% of respondents. The impact of climate change on crop quality and the associated marketing decisions is complex and dynamic (Morton, 2007 ). It mainly depends on which types of climate stresses affect crops and how these stresses interact with post-harvest handling practices. Farmers described how increasingly variable weather conditions compromise product standards, particularly regarding aflatoxin contamination in groundnuts and maize caused by moisture fluctuations during harvesting and drying. Aflatoxin contamination poses risks that extend beyond economic losses, representing a critical public health challenge. As potent carcinogens, aflatoxins are associated with liver damage and immune suppression, particularly when exposure occurs through chronic dietary intake (Wu, 2015 ; Mgandu et al., 2024 ). Severe contamination events have also been linked to acute health impacts, including fatalities. A major outbreak in Kenya in 2004 caused over 125 human deaths and hundreds of hospitalisations due to contaminated maize (Probst et al., 2004 ). More recently, in 2024, Zambia experienced an outbreak in which 400 dogs died, prompting authorities to launch a national public health crisis response. These incidents highlight both the immediacy and severity of aflatoxin risks across different contexts. Beyond acute outbreaks, aflatoxin contamination compromises the safety of domestic food supplies and disqualifies agricultural products from international markets (Hejazi, 2025 ). With increasing warming projected under climate change, the frequency and severity of aflatoxin contamination is expected to intensify, especially in the tropical and sub-tropical regions (Casu et al., 2025; Kharod et al., 2025 ). Evidence from Central Malawi already highlights how these trends may exacerbate public health risks while threatening livelihoods and nutrition security (Warnatzsch et al., 2020 ). 4.3. Adaptation strategies implemented to counter the impacts of climate change Adaptation to climate change is critical for maintaining productivity and safeguarding rural livelihoods, especially as rising climate risks threaten global food security. Our findings shows that both CSMA and non-macadamia farmers in central Malawi demonstrate adaptive capacity, but in different ways. CSMA farmers focus on temporal strategies, especially shifting of annual crop planting dates, while non-macadamia farmers rely on diversified adaptation strategies such as crop diversification, soil conservation, improved irrigation, and recently adopting agroforestry. Interestingly, drought-tolerant seeds were adopted by around 45% of farmers in both groups, reflecting a common strategy to buffer against climate risks. This pattern aligns with broader evidence that smallholder farmers enhance resilience by diversifying crops, conserving soil moisture, and adopting stress-tolerant varieties such as drought tolerant and early maturing varieties to enhance resilience (Holden & Fisher, 2015 ; Katengeza et al., 2019 ). This concentration-diversification dichotomy provides important insights into how adaptive capacity is expressed across different agricultural systems and challenges conventional assumptions about optimal adaptation pathways. The nature of these differences becomes more evident when examining CSMA as a system of adaptation. However, the contrasting patterns do not necessarily reflect lower adaptive capacity among CSMA farmers; rather, they arise because many adaptive practices are already embedded within macadamia-based systems. CSMA farmers argue that this system of production inherently bundles adaptation practices. For example, basic construction around the macadamia trees, leaf litter fall and interplanting with annuals simultaneously provides permanent soil cover, which helps in building soil organic matter and in turn soil health, conserves soil moisture, and diversifies production. Additionally, legumes such as groundnuts, pigeon peas and soybeans help to improve the soil fertility through biological nitrogen fixation that is used by the macadamia trees and the subsequent crop in the following season. In contrast, non-macadamia farmers must create equivalent benefits through discrete investments. This indicates that CSMA enhances climate resilience through system architecture rather than discrete interventions. These interpretations are in agreement with Lunn-Rockliffe et al. (2025), who reported that combining methods allows farmers to expand the synergy between regenerative agricultural practices, thereby increasing farm productivity in the face of intersecting challenges such as climate change, soil degradation, and pests and diseases. Additionally, research on adaptation perception confirms that farmers often fail to recognise the benefits of integrated systems as discrete adaptation measures (Gemtou et al., 2024 ; Kabato et al., 2025 ). This explains why CSMA farmers may not identify embedded practices as separate adaptation strategies, even though they significantly strengthen resilience. Our findings, therefore, suggest that promoting agroforestry practices can extend resilience beyond CSMA farmers. Integrating trees into farming systems, whether for smallholder or large commercial farms, for shade, soil conservation, or diversified harvests, offers a practical pathway to enhance adaptive capacity. 5. Conclusion Our study demonstrates that climate-smart macadamia agroforestry can strengthen smallholder resilience to climate change in central Malawi and globally. By reconfiguring farm structure rather than introducing a single adaptive practice, CSMA integrates diversification, ecological regulation and temporal flexibility within the production system itself. In doing so, it shifts adaptation from reactive coping toward structurally integrated resilience. Compared with conventional monocultures, CSMA systems are associated with more stable production outcomes and broader livelihood buffering, supported by ecosystem services delivered through tree-crop integration. The contrast between concentration and diversification pathways highlights that resilience is not solely a function of the number of strategies adopted, but of how risk management is organised within the farming system. Agroforestry, in this context, operates as a platform for cumulative adaptation. However, the transition to tree-based systems remains constrained by a climate vulnerability trap: declining yields and rising costs reduce the capacity of the most exposed households to invest in long-gestation crops. Without targeted support, adaptation may remain inaccessible to those who would benefit most. Embedding CSMA within national adaptation frameworks will therefore require coordinated policy, finance and market interventions, including risk sharing mechanisms during establishment phases, climate-smart credit, carbon incentives, strengthened extension systems and inclusive value-chain integration. These findings position agroforestry as a structural pathway toward climate-resilient rural development. Its broader contribution to adaptation and food security will depend on enabling institutional architectures capable of supporting equitable system transformation under accelerating climate change. We therefore argue that supporting CSMA and related agroforestry approaches should be prioritised in agricultural policy, in Malawi but also for farming communities globally. In addition, strengthening knowledge exchange through peer-learning mechanisms such as farm walks, field days, and farmer field schools can accelerate adoption and ensure that both younger and older farmers benefit from these practices. Declarations Declaration of generative AI and AI-assisted technologies in the manuscript preparation process During the preparation of this work the author(s) did not use any generative AI and AI-assisted technologies. Data and code The datasets will be made available upon request from the corresponding author. The statistical analysis code, and supplementary materials, are publicly accessible through the Climate-Impacts repository. Funding declarations This research was supported by The Open University through the Open Societal Challenges initiative. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The views expressed in this publication are those of the authors and do not necessarily reflect the official position of The Open University. Competing interests The authors declare no competing interests. Ethical approval The Human Research Ethics Committee (HREC) of The Open University, United Kingdom, provided ethical approval for this study. CRediT authorship contribution statement Conceptualisation: EZ, AE, YA, NE; Methodology: EZ, YA, AE, WB; Writing – Original draft: EZ, WB; Writing – review & editing: YA, AE, NE, TE, MC, JH: Data analysis: EZ, MC, WB; Visualisations: WB, EZ, MC; Funding acquisition: AE, NE, TE; Project supervision: EZ, AE, WB, NE, TE, JH. References Abidoye B, Aladysheva A, Haitz N, Montresor G, Nyekanyeka T, Orlic E, Prowse M. Supporting farmers dealing with climate change: The impact of Participatory Integrated Climate Services for Agriculture (PICSA) on smallholder lead farmers in Malawi. 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Agronomy. 2024;14(2):308. https://doi.org/10.3390/agronomy14020308 . Zenda M. A systematic literature review on the impact of climate change on the livelihoods of smallholder farmers in South Africa. Heliyon. 2024;10(18). https://doi.org/10.1016/j.heliyon.2024.e38162 . Zuza EJ, Maseyk K, Bhagwat SA, Rawes W, Araya YN. Climate suitability predictions for the cultivation of macadamia ( Macadamia integrifolia ) in Malawi using climate change scenarios. PLoS ONE. 2021;16(9):e0257007. https://doi.org/10.1371/journal.pone.0257007 . Zuza EJ, Muhammed AO, Emmott A, Brandenburg RL, Araya YN. (2024). Macadamia Nuts as a Supplement. Nut Consum its Usefulness Mod World, 85. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9303871","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":621312071,"identity":"30ceea85-2e60-4abb-aa55-eedc8123b8e6","order_by":0,"name":"Emmanuel Junior Zuza","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYBADGQhVARdIIKiFB0KdIVkLYxsRWvjFTid+Lmyz4WHgP2P84ee8e/IGB5gffmBsS8OpRXJ27mbpmW1pQFvOGBj2bis23HCAzViCsS0HpxaD27kbpHnbDvMwMPYYJPBuS2DccIDBDOjCCpxa7G/nbv7N2/afh4GZx+Dg3zkJ9hsOsH/Dq8VAOncb0JYDPAxsPIbNvA0JiRsO8IBswe0widu526x5ziXzsPGwFTPLHEtInnmYp1gi4Rxu7/MDvX+bp8xOjp//8OaPb2oSbPuOt2/88KEsGacWOGCDs5gZiInIUTAKRsEoGAX4AAAvoErhJaSmqwAAAABJRU5ErkJggg==","orcid":"","institution":"Royal Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Emmanuel","middleName":"Junior","lastName":"Zuza","suffix":""},{"id":621312072,"identity":"83994161-9f27-4094-86bc-b25b8aba244a","order_by":1,"name":"William Banda","email":"","orcid":"","institution":"Harper Adams University","correspondingAuthor":false,"prefix":"","firstName":"William","middleName":"","lastName":"Banda","suffix":""},{"id":621312073,"identity":"00d3dca6-f094-4892-a3a0-bf5a5d958d60","order_by":2,"name":"Yoseph Araya","email":"","orcid":"","institution":"The Open University","correspondingAuthor":false,"prefix":"","firstName":"Yoseph","middleName":"","lastName":"Araya","suffix":""},{"id":621312074,"identity":"a834661f-fe55-4a68-8a78-9919d53103ea","order_by":3,"name":"Andrew Emmott","email":"","orcid":"","institution":"Neno Macadamia Trust","correspondingAuthor":false,"prefix":"","firstName":"Andrew","middleName":"","lastName":"Emmott","suffix":""},{"id":621312075,"identity":"df97ff74-53bb-4ce0-a72f-a179ed413bfd","order_by":4,"name":"Nick Emmott","email":"","orcid":"","institution":"Neno Macadamia Trust","correspondingAuthor":false,"prefix":"","firstName":"Nick","middleName":"","lastName":"Emmott","suffix":""},{"id":621312076,"identity":"72a7ff2d-6b51-435b-b003-f543703e73b2","order_by":5,"name":"Tim Emmott","email":"","orcid":"","institution":"Neno Macadamia Trust","correspondingAuthor":false,"prefix":"","firstName":"Tim","middleName":"","lastName":"Emmott","suffix":""},{"id":621312077,"identity":"2e53010d-e4ba-4375-9ed6-c344c8a9f734","order_by":6,"name":"Moses Chitete","email":"","orcid":"","institution":"Lilongwe University of Agriculture and Natural Resources","correspondingAuthor":false,"prefix":"","firstName":"Moses","middleName":"","lastName":"Chitete","suffix":""},{"id":621312078,"identity":"a6a49273-6ca3-4d32-bb92-8d26195f199e","order_by":7,"name":"Jonathan Hanson","email":"","orcid":"","institution":"Queen's University Belfast","correspondingAuthor":false,"prefix":"","firstName":"Jonathan","middleName":"","lastName":"Hanson","suffix":""}],"badges":[],"createdAt":"2026-04-02 13:38:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9303871/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9303871/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106960309,"identity":"e5ad2e16-f935-4ecb-a90c-b26aad4423db","added_by":"auto","created_at":"2026-04-15 09:20:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":501586,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Topographic variation across Malawi; (b) Study EPAs (red), within Ntchisi (green) and Dowa (orange) Districts.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-9303871/v1/f9987964121b6e684ece60de.png"},{"id":106960522,"identity":"2ee71d36-8a81-410b-9b77-5be65fafbc1a","added_by":"auto","created_at":"2026-04-15 09:21:37","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":145511,"visible":true,"origin":"","legend":"\u003cp\u003eImpacts of climate change on farming among CSMA and non-CSMA farmers (multiple responses).\u003c/p\u003e","description":"","filename":"Figure2V1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9303871/v1/691859a4067342d5ae88852f.jpg"},{"id":106960214,"identity":"3101b872-eaf1-41b1-b616-f3c6bee897e6","added_by":"auto","created_at":"2026-04-15 09:19:24","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1107353,"visible":true,"origin":"","legend":"\u003cp\u003eImpacts of climate change on farmer incomes among CSMA and non-CSMA farmers.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-9303871/v1/1150ab623f3df9d2ff97c011.png"},{"id":106960405,"identity":"28165745-1329-46e9-9482-75e9610b2ac4","added_by":"auto","created_at":"2026-04-15 09:20:53","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":60484,"visible":true,"origin":"","legend":"\u003cp\u003eClimate change adaptation strategies implemented among CSMA and non-CSMA farmers.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-9303871/v1/18fc46b70c2ec8e815e3d80f.png"},{"id":106963180,"identity":"e8f7d5a1-bd71-4ce6-b317-7f93182bd5a8","added_by":"auto","created_at":"2026-04-15 09:42:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3040248,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9303871/v1/2c64bee4-bd7c-4c58-9298-6c063d9608d4.pdf"},{"id":106812537,"identity":"b6013eed-6e49-4cd0-bcc3-81df57c15fd8","added_by":"auto","created_at":"2026-04-13 16:32:51","extension":"png","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1834004,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.png","url":"https://assets-eu.researchsquare.com/files/rs-9303871/v1/cd9db94b791003bdaba8b970.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Can climate-smart macadamia agroforestry systems safeguard smallholder farmers against climate shocks in Malawi?","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eClimate change poses a fundamental threat to agricultural systems across Sub-Saharan Africa (SSA), with particularly severe consequences for countries where smallholder farming underpins both livelihoods and national economies (Morton, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Zenda, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Akram et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Malawi exemplifies this vulnerability: approximately 80% of the population are smallholder farmers and depend on rainfed agriculture, which contributes nearly 30% to national GDP (Abidoye et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Increasingly erratic rainfall, rising temperatures, and more frequent extreme weather events are disrupting traditional farming calendars, altering crop growth cycles, increasing evapotranspiration, and compressing already narrow planting windows (Likoya et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These climatic pressures compound structural vulnerabilities, inadequate irrigation infrastructure, limited institutional support, and widespread poverty that severely constrain farmers\u0026rsquo; adaptive capacity.\u003c/p\u003e \u003cp\u003eDespite these challenges, smallholder farmers are not passive victims of climate change but active agents developing innovative responses to emerging risks. Studies have shown that successful climate adaptation in smallholder systems comes from integrating traditional knowledge with improved technologies, supported by appropriate policy frameworks and institutional arrangements (Simon \u0026amp; Leck, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Taylor, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Chemura et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Among numerous adaptation strategies one common viable option is agroforestry systems.\u003c/p\u003e \u003cp\u003eAgroforestry is a practice that integrates trees with annual crops and/or livestock. The practice offers multiple co-benefits, including improved soil health (Putra et al., 2025), enhanced water retention (Kaushal et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), diversified income streams (Castle et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and reduced risk exposure through temporal and spatial production diversification (Matevski et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ndhlovu, 2025). In Malawi, various agroforestry practices have shown potential for addressing climate challenges while maintaining or improving productivity, though adoption rates remain variable across contexts and farming systems (Muzungwi et al., 2024).\u003c/p\u003e \u003cp\u003eWithin the range of agroforestry options available to Malawian smallholder farmers, macadamia-based systems (hereafter referred to as climate-smart macadamia agroforestry, CSMA), which involve intercropping annual crops such as maize, soybeans, groundnuts, common beans, potatoes, and pigeon peas and/or integration with livestock rearing have emerged as a particularly promising climate-smart alternative. Macadamia trees possess several characteristics well-suited to climate variability: deep root systems that access groundwater during dry periods (Carr, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), tolerance to temperature fluctuations (Huett, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), and productive lifespans extending several decades (Hardner et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Additionally, macadamia nuts command premium prices in international markets, thereby providing smallholders with improved income stability (Rogiers et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, the implementation of CSMA particularly by smallholders faces considerable challenges that require careful examination. These include the significant upfront investment required for tree establishment (macadamia seedlings cost around USD \u003cspan\u003e$\u003c/span\u003e 4), the extended gestation period before productive harvests begin, technical knowledge requirements, and potential trade-offs with immediate food security and income needs (Zuza et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Baipai et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Furthermore, individual farmers not affiliated with cooperatives face particular difficulties in accessing markets, securing inputs, and obtaining tree seedlings, suggesting that blended financial support mechanisms are needed to facilitate adoption (Zuza et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). As such, understanding how these factors interact with farmer decision-making and existing livelihood strategies is essential for designing appropriate support interventions.\u003c/p\u003e \u003cp\u003eThe central Malawi districts of Ntchisi and Dowa provide a helpful context for examining these dynamics. Both districts are characterised by mixed farming systems dominated by staple crop production, with farmers increasingly recognising the need for diversification to address climate risks. The presence of both CSMA adopters and non-adopters within the same agroecological zones enables comparative analysis of the factors influencing adoption decisions and outcomes. Our study therefore aims to contribute to the growing body of practice-oriented knowledge on agroforestry in SSA by evaluating the potential of CSMA to enhance smallholder resilience in central Malawi. Through a mixed-methods approach, our study addresses three central research questions: (1) What are the impacts of climate change on crop yields and the farming calendar? (2) What are the impacts of climate change on farmer incomes, crop marketing, and input costs? (3) What adaptation strategies are implemented to counter the impacts of climate change? The findings are intended to inform policy development, extension programme design, and future research priorities in support of climate-resilient agricultural development in Malawi and comparable contexts across the region.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Description of the study area\u003c/h2\u003e \u003cp\u003eThe study was conducted in Dowa and Ntchisi districts of Malawi\u0026rsquo;s central region (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). These districts were purposively selected due to their agricultural importance, vulnerability to climate impacts, and their status in macadamia cultivation. Both districts are dominated by smallholder farming systems, with maize serving as the principal staple crop and coffee, groundnuts, soybeans, potatoes and green vegetables as cash crops (Chinseu et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Additionally, these districts also represent the highest concentration of macadamia producers in central Malawi.\u003c/p\u003e \u003cp\u003eDowa district covers an area of 3,041 km\u0026sup2;, with altitudes ranging between 700\u0026ndash;1,500 metres above sea level (m.a.s.l). The district is divided into seven Extension Planning Areas (EPAs), with macadamia production concentrated in the Nachisaka EPA (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). EPAs are administrative units established to facilitate agricultural extension and development planning (Banda, 2025). Dowa experiences an annual temperature range of 10\u0026ndash;32\u0026deg;C and receives 800\u0026ndash;1,500 mm of rainfall annually, largely influenced by elevation (Zuza et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNtchisi district covers an area of 1,655 km\u0026sup2;, with altitudes ranging from 900 to over 2,000 m.a.s.l., creating diverse agroecological conditions across the landscape. For instance, Kalira EPA spans from hot, dry lowlands along the Rift Valley escarpment to cool, wet uplands on the Rift Valley ridge. Rainfall distribution varies among the EPAs as well, with Malomo receiving relatively lower precipitation (800\u0026ndash;1200 mm) compared to Chikwatula and Kalira (1,200\u0026ndash;1,500 mm). The district records an annual temperature range from approximately 8\u0026deg;C in the cold season to 35\u0026deg;C in the hot season (Jere et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These varied yet generally favourable climatic and edaphic conditions support macadamia cultivation across all EPAs in the district.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Sampling and data collection\u003c/h2\u003e \u003cp\u003eA mixed methods approach (Tashakkori \u0026amp; Teddlie, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) involving a structured household questionnaire and focus group discussions (FGDs) was used to gain understanding of farmer perceptions and experiences regarding the impact of climate change on their livelihoods and agricultural production. Both instruments were developed drawing on the thematic priorities identified in Section 1 and were directly informed by the recommendations of Zuza et al. (\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), who called for empirical investigation into the impacts of CSMA on smallholder farmer resilience to climate change in Malawi. The FGDs were designed to elicit deeper contextual perspectives that structured questionnaires alone cannot readily capture.\u003c/p\u003e \u003cp\u003eThe study used a stratified random sampling approach (Iliyasu \u0026amp; Etikan, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), with EPA serving as the primary strata. Within each stratum, villages were randomly selected, followed by systematic random household sampling. This approach ensured geographical diversity while maintaining statistical representativeness. The structured questionnaire was administered to 119 farmers, both CSMA and non-CSMA adopters, across the two study districts in February 2025. In Dowa district, sampling was conducted in Nachisaka EPA, while in Ntchisi district, sampling covered Chikwatula, Kalira, Malomo, and Chipuka EPAs. The survey provided breadth and comparability, allowing patterns, relationships, and the prevalence of climate-related challenges and adaptation practices to be identified (Weyant, 2022).\u003c/p\u003e \u003cp\u003eTo complement the survey data, five FGDs one in each of the five mentioned EPAs each comprising ten members were conducted across the EPAs with both male and female farmers. FGDs were particularly valuable in generating nuanced insights into participants\u0026rsquo; lived experiences, uncovering the social dynamics, shared perspectives, and gendered dimensions of climate-related challenges and adaptation practices. While FGD findings cannot be generalised to wider populations, they enriched the quantitative evidence by providing depth and contextual understanding of the factors that motivate, support, or constrain the adoption of climate-smart practices (Li et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Together, the survey and FGDs produced a robust evidence base, combining generalisable quantitative patterns with detailed qualitative insights. We obtained favourable ethical approval for the study from both the Human Research Ethics Committee (HREC) of The Open University, United Kingdom and Highlands Macadamia Cooperative Union Limited (HIMACUL), Malawi.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Data analysis\u003c/h2\u003e \u003cp\u003eQuantitative data was analysed using Python programming language, with descriptive statistics generated for key variables. Cross-tabulations and correlation analyses were conducted to explore relationships between farmer characteristics, climate impacts, and adaptation strategies. Qualitative data from the FGDs was transcribed and examined using Bryman (2016) six phase reflexive approach to thematic analysis. This process enabled the systematic identification of recurrent themes and emerging issues. The rich narratives captured through the FGDs provided deeper contextual insights into the research questions, offering perspectives often overlooked in conventional adoption studies (Chinseu et al., 2018). The deductive (theory-driven) approach was applied during coding and interpretation, ensuring that analysis was grounded in participants\u0026rsquo; accounts.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Farmer characteristics\u003c/h2\u003e \u003cp\u003eOur study comprised of 48 CSMA and 71 non-CSMA farmers (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Male respondents constituted 58% of the overall sample, with a higher proportion among CSMA farmers (64.6%) than non-macadamia farmers (53.5%), though this difference was not statistically significant using an independent \u003cem\u003et-test\u003c/em\u003e (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.23).\u003c/p\u003e \u003cp\u003eThe most striking demographic distinction was age. CSMA farmers were significantly older than their non-CSMA farmers (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.001), a 14.8-year differential that reflects macadamia\u0026rsquo;s local characterization as a \u003cem\u003e\u0026ldquo;retirement crop.\u0026rdquo;\u003c/em\u003e However, this term does not imply post career cultivation but rather captures the reality that macadamia adoption requires substantial upfront capital for land and seedlings, coupled with tolerance for delayed returns during the tree\u0026rsquo;s lengthy maturation period. Our FDGs confirmed that older farmers, having accumulated productive assets and secured land tenure over decades, were better positioned to absorb these costs, whereas younger farmers face binding constraints in land access and credit availability.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic characteristics of CSMA and non-CSMA farming households\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNon-CSMA farmers %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCSMA farmers %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003et-test\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eEducation attainment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePartial primary school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCompleted primary school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePartial secondary school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.946\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCompleted secondary school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAttended tertiary education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMean of household age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eStd. err.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eStd. dev.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Education attainment\u003c/h2\u003e \u003cp\u003eEducation is often a key factor shaping farmers\u0026rsquo; ability to adopt new practices and technologies. We, however, found that formal educational attainment was uniformly low across both adopters and non-adopters of CSMA, suggesting that schooling levels were not a distinguishing factor in adoption decisions within this population. The majority of respondents (60.5%) had not progressed beyond primary education, while tertiary education was extremely rare (\u0026le;\u0026thinsp;2.1%). Most farmers therefore relied far more on experiential learning than on formal schooling to guide their farming decisions. As one farmer explained:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eI left school after standard 5 (primary school) because my family needed help with farming. Most of my knowledge about agriculture comes from practical experience rather than formal education.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eAnother farmer emphasised the intergenerational transmission of knowledge:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eYou know what, farming is all about experience and how long you have been practicing. My farming knowledge has been passed from generation to generation, so I did not go to school, I was busy taking care of the fields.\u0026rdquo;\u003c/em\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eAt the same time, farmers\u0026rsquo; narratives reveal that access to extension services plays a critical role in supplementing limited formal education. Several respondents reported a noticeable decline in public extension support over time, particularly for macadamia relative to staple crops and as such impacting their practices and yields. One farmer reflected:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eMost of my farming knowledge comes from observing parents, neighbours, attending field days and farmer field schools. Back in the early 2000s, when I was diversifying to macadamia, alangizi (extension workers) from the EPA visited us weekly, providing training on good production practices. Today, that support has largely disappeared; extension officers now focus on other important crops, and only HIMACUL continues to offer us advice on macadamia nut production.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eAnother added:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAs of late there has been a decline in our contact with alangizi. This is especially true for macadamia farming. Other crops like maize, soybeans and groundnuts are well supported but not this one. This makes it difficult for us to know what to do when we have issues, especially on pests and disease management and soil nutritional management.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Impacts of climate change on crop yields\u003c/h2\u003e \u003cp\u003eOur findings reveal that climate change has negative impacts on agricultural productivity, with substantial and differentiated effects documented across farming systems. The analysis shows notable disparities in climate vulnerability between crop types, with non-CSMA farmers experiencing significantly greater yield reductions (70%) compared to CSMA farmers (56%) over the preceding five-year period (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Although the difference is not statistically significant through the use of Chi square test (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.266), the trend suggests comparatively greater climate resilience within CSMA systems than in conventional monoculture systems.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eImpact of climate change on crop yields among CSMA and non-CSMA farmers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-CSMA farmers %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCSMA %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSignificantly decreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.266\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSlightly decreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo change\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSlightly increased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSignificantly increased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eThese quantitative findings are reinforced by qualitative evidence that explains the mechanisms driving productivity changes. Non-CSMA farmers particularly emphasised the disruption of traditional seasonal patterns, especially rainfall variability:\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003cem\u003e\u0026ldquo;We\u0026rsquo;ve experienced increasingly unpredictable rainfall patterns over the past five years. When I started farming 30 years ago, we could reliably predict when to plant our crops each growing season which was always in October, but now the rains come late or stop unexpectedly. Last season, my maize yield was half what I harvested five years ago.\u0026rdquo;\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eSuch reasons reflect heightened climate uncertainty, including delayed onset of rains, early cessation, and erratic distribution, all of which undermine planning, crop establishment, and yield stability in monocropping systems.\u003c/p\u003e \u003cp\u003eIn contrast, CSMA farmers described tangible protective benefits associated with macadamia-based agroforestry systems. Tree cover was perceived as moderating microclimatic extremes and reducing physical crop damage during extreme weather events:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe climate has really changed over the years. We used to get reliable Chiperoni rains during the dry seasons here, but now they hardly come. I tell you, without underplanting these macadamia trees with maize, soybeans, and groundnuts, I would be in serious trouble. During the past years of cyclones Idai and Kenneth, I watched my neighbours lose their entire maize crop to those terrible winds and floods, but my fields stayed protected. The trees shielded and protected the annual crops - breaking the wind and stopping the water from washing everything away. That\u0026rsquo;s when I truly understood the power of growing macadamia alongside other crops.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThis testimony highlights key resilience mechanisms associated with CSMA systems, including windbreak effects, reduced soil erosion, improved water retention, and structural protection during storms. At the same time, both farmer groups reported emerging climate-related challenges, particularly shifts in pest dynamics:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eWe\u0026rsquo;ve observed new pest patterns over the past three seasons. The stink bugs in macadamia and soybeans that previously appeared only briefly now persist throughout much of the growing season, requiring additional management interventions, increasing our production costs, and in cases where we have failed to manage them causing heavy losses on crops, especially macadamia nuts.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eAnother farmer reported:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eYou know there is this new pest \u0026ldquo;Kapuchi\u0026rdquo; (Fall armyworm) this one is trouble. Once it is in your maize you are done. I don\u0026rsquo;t know where it came from but it\u0026rsquo;s a big challenge. We have been experimenting on local remedies such as the use of fish soup, application of sand, and neem tree extracts combined with constant monitoring but its tough.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Impacts of climate change on the seasonal farming calendar\u003c/h2\u003e \u003cp\u003eBeyond yield reductions, climate change has disrupted fundamental farming operations across multiple dimensions in the study area. Traditional planting and harvesting calendars have been particularly affected, with all of the respondents (100%) reporting severe disruptions to seasonal timing. During FDGs, farmers frequently mentioned the difficulty in planning agricultural activities, with one farmer noting:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003ePreviously, we knew exactly when to prepare our fields and when to sow the seeds. Now, we\u0026rsquo;re constantly adjusting our schedules based on weather patterns that seem to change every season.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThese temporal disruptions were worsened by resource-related challenges. Water availability (droughts) has become increasingly problematic, with most respondents reporting moderate to severe impacts (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Simultaneously, pest occurrence has intensified, creating additional pressure on already vulnerable crops. These combined stressors have created a cascade of challenges that collectively contribute to the reported declines in crop yields, establishing a concerning pattern of multi-dimensional agricultural vulnerability across the study areas. In addition, declining yields and income makes it even more difficult over time for farmers to make the transitions needed to invest in CSMA.\u003c/p\u003e \u003cp\u003eHowever, at production system level 70% non-CSMA farmers reported severe impacts on planting and harvesting times, while about 45% experienced significant yield reductions. In contrast, CSMA farmers reported fewer severe impacts across all dimensions, suggesting that integrating macadamia into farming systems may buffer against climate-related shocks.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Impacts of climate change on farmer incomes\u003c/h2\u003e \u003cp\u003eClimate change has generated substantial economic challenges among the study households, with income reductions representing a widespread phenomenon affecting both macadamia and non-macadamia producers. Analysis of income changes over the past three years reveals that the majority of farmers have experienced significant financial hardship, with 59.2% of non-CSMA farmers and 54.2% of CSMA farmers reporting that their incomes have markedly decreased (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). An additional 23.9% of non-CSMA farmers and 31.3% of CSMA farmers experienced slight income reductions, bringing the total proportion of farmers facing income declines to over 80% across both groups.\u003c/p\u003e \u003cp\u003eHowever, despite experiencing similar proportions of income decline, CSMA farmers reported greater economic resilience through diversified income streams and extended harvest periods. CSMA farmers highlighted how agroforestry systems provided crucial economic flexibility during vulnerable periods. The extended harvesting calendar emerged as a particularly important resilience mechanism, with farmers emphasising how multiple harvest periods throughout the season provided income when other crops failed. As one CSMA farmer explained:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eWith macadamia, I can harvest three times per season. This is crucial during the lean period in January when Christmas expenses are done, school fees are due, and our maize stores are finished. I use some nuts for food and sell the rest for income to buy more food and pay school fees. Yes, my income has declined, but I\u0026rsquo;m still better off than farmers without macadamia trees.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThis statement shows how CSMA addresses both food and nutritional security and cash flow challenges that are particularly acute during the lean season in Malawi. The ability to harvest throughout the year provides macadamia farmers with financial flexibility that monoculture farmers lack, enabling them to meet seasonal expenses like school fees and food purchases when annual crop reserves are depleted.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.6. Impacts of climate change on crop marketing\u003c/h2\u003e \u003cp\u003eClimate change has created significant barriers to market participation for smallholder farmers across both of the study areas. The survey findings reveal that reduced crop quality stands as the predominant challenge, affecting 38.4% of all respondents. Farmers described how increasingly variable weather conditions have compromised product standards. A farmer reported:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eDroughts and late seasonal rains have significantly affected both groundnut quantity and quality. For groundnuts droughts result in rosette (a disease in groundnuts) and make them easily affected by chuku (aflatoxins). Similarly, late seasonal rains during groundnut harvesting and drying encourages moisture, which results in fungal contamination and high levels of aflatoxin. As a result, the majority of the groundnut cannot be sold to international markets due to higher levels of aflatoxins.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eAnother farmer echoed:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe maize we\u0026rsquo;ve harvested recently doesn\u0026rsquo;t store as well due to inconsistent maturation caused by erratic rainfall. This forces us to either consume it quickly or sell at reduced prices, leaving us vulnerable to food shortages later in the season.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eMarket dynamics have also shifted due to climate-induced scarcity, with 28.8% of respondents reporting increased competition. This has created a paradoxical situation where overall supply decreases while individual farmers face greater difficulty securing buyers. Transportation infrastructure vulnerabilities have emerged as another significant constraint, with 11.8% of respondents citing extreme weather events as disrupting market access routes. However, 17.5% of respondents reported no discernible impact on market access, suggesting some variation in resilience factors across the surveyed population. This merits further investigation to identify potential adaptive practices that could be more broadly applied.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.7. Farming input cost escalation due to climate change\u003c/h2\u003e \u003cp\u003eThe survey results reveal a strong perception that climate change has contributed to rising agricultural input costs, with 67.5% of respondents affirming this connection. Several farmers provided specific mechanisms through which climate change has increased production expenses. The economic implications extend beyond direct input costs to include risk management expenses. Farmers reported investing in contingency supplies, including backup seeds, additional pesticides, and emergency fertilisers to protect them against climate uncertainties, further straining household budgets already under pressure from reduced yields and market volatility. A farmer explained:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eWe now need to apply fertiliser multiple times due to heavy rains washing away nutrients. Seeds that previously performed well now fail under current conditions, forcing us to purchase more expensive climate-adapted varieties. The unpredictability means we must invest in contingency supplies, significantly increasing our production costs.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhile 25.2% of respondents did not perceive a climate-related cost increase and 7.4% remained uncertain, the predominant consensus supports a strong connection between changing climate conditions and heightened production expenses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.8. Climate change adaptation mechanisms\u003c/h2\u003e \u003cp\u003eAdaptive capacity reflects farmers\u0026rsquo; inherent ability to respond to, adjust to, and recover from climate-induced challenges through the implementation of appropriate coping mechanisms. Our results reveal distinct adoption patterns between macadamia and non-macadamia farmers, highlighting differential adaptive approaches across crop types (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The findings show that CSMA farmers concentrate on changing planting dates (68% adoption), while non-macadamia farmers exhibit more diversified strategy portfolios with higher uptake of soil conservation practices (68.5%), improved irrigation (61.5%), agroforestry (56.4%), and crop diversification (64.7%). Drought-resistant varieties show balanced adoption across both systems (44.6% macadamia vs. 55.4% non-macadamia). A farmer reported:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eYou know rainfall has become unreliable, so I\u0026rsquo;ve adapted by using hybrid maize varieties from the farm input subsidy programme. These varieties can withstand short dry spells during the season and still produce good yields\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eA macadamia farmer highlighted:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003e\u0026ldquo;Over my 60 years, planting used to be predictable. We always planted in mid-October, and we could even plant a week earlier knowing the rains would arrive the following week. Today, this certainty no longer exists. I must adjust planting dates each season based on rainfall patterns. In some years, we have planted as late as Christmas.\u0026rdquo;\u003c/em\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThese contrasting patterns largely reflect inherent characteristics of CSMA production systems rather than differential adaptive capacity. CSMA inherently incorporates many practices that non-macadamia farmers implement as discrete adaptation strategies. Basin construction for water harvesting, permanent ground cover maintenance, and intercropping with annual crops provide integrated soil conservation and diversification benefits within macadamia orchards. Since these measures are embedded within the production system, macadamia farmers are less likely to identify them as separate \u0026ldquo;adaptation strategies\u0026rdquo; and instead emphasise accessible temporal adjustments like planting-date modifications of their annual crops. This suggests that while both farming systems demonstrate adaptive capacity, they express it through fundamentally different approaches, macadamia farmers through system-integrated practices and temporal flexibility, and non-macadamia farmers through explicit implementation of multiple discrete strategies.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Impacts of climate change on crop yields and the farming calendar\u003c/h2\u003e \u003cp\u003eClimate change reduces crop yields through both direct effects on crop growth and the ways farmers respond to the shocks they experience. Our study shows that vulnerability varies between macadamia and non-macadamia farming systems, with important implications for adaptation. Although both groups of farmers reported substantial yield declines, the 14%-point difference between non-macadamia (70%) and macadamia farmers (56%) experiencing severe decreases highlights differences in resilience. We argue that CSMA systems provide a degree of buffering that monoculture systems often lack.\u003c/p\u003e \u003cp\u003eThe buffering role of CSMA was particularly visible during extreme weather climatic events, including the years Malawi experienced severe droughts and tropical cyclones such as Kenneth (2019) and Idai (2021). CSMA systems provided multiple layers of protection: they reduced the force of winds, limited physical damage to the annual crops and infrastructure, stabilised soils, and moderated rainfall impacts through canopy interception and litter accumulation, which together diminished runoff, erosion, and flooding. These farmer observations are corroborated by controlled studies indicating that agroforestry windbreaks can reduce wind speeds by 17\u0026ndash;67% and surface runoff by 30\u0026ndash;50% (Cleugh, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Mume \u0026amp; Workalemahu, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Baker et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). As the frequency and severity of extreme weather events intensify under climate change, such ecosystem-based protections are valuable for climate adaptation. This contrasts with monocultural systems, which remain highly vulnerable and often experience catastrophic yield losses under comparable shocks (Mkondiwa et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBeyond yield reductions, climate change has also disrupted fundamental farming operations by undermining the reliability of traditional planting and harvesting calendars. This reflects a broader global pattern where altered rainfall onset, shortened growing seasons, and unpredictable dry spells are forcing farmers to abandon established scheduling practices. This finding is consistent with studies in SSA, where climatic variability has increasingly led to shorter and more unpredictable planting windows, affecting crop planning and productivity (Chikowo et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Fiwa et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Moyo et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The shortening of the growing season poses particular challenges for smallholder farmers reliant on rainfed agriculture, as it compresses the time available for crop establishment and development, potentially reducing yields. Furthermore, studies in East Africa show that changing rainfall patterns have delayed sowing dates and increased uncertainty in maize-based systems (Adhikari et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Apraku et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Palmer et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Similar disruptions are reported in South Asia, where erratic monsoon onset has forced rice farmers to alter planting windows, often with negative yield consequences (Junaid et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Habib-ur-Rahman et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Evidence from Latin America also highlights how temperature shifts and irregular precipitation are reducing the effectiveness of traditional agricultural calendars, undermining the reliability of indigenous knowledge systems (Tovar et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; van Leeuwen et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These findings reinforce our results by demonstrating that the erosion of seasonal predictability is not unique to our study area but is emerging as a global challenge for smallholder agriculture.\u003c/p\u003e \u003cp\u003eThese challenges are further complicated by resource pressures and the intensification of insect pests. Water availability has become increasingly problematic, with most respondents reporting moderate to severe impacts. At the same time, pest occurrence has intensified, creating additional stress on already vulnerable crops. Farmers highlighted, for example, how stink bugs that attack soybeans and macadamia, once seasonal, are now present throughout the growing period, requiring greater effort and cost to manage. The observed change in the presence of pests from occasional to present throughout the season challenges the effectiveness of traditional pest management practices, suggesting a migration to integrated pest management systems that embrace the role of climate change on crop production. This aligns with evidence that climate change is altering insect life cycles by extending reproductive periods and delaying dormancy (Skendžić et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Subedi et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The effects of shifting rainfall, reduced water availability, and pest intensification create a cascade of challenges that together contribute to yield declines, establishing a pattern of multi-dimensional agricultural vulnerability across the study area.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Impacts of climate change on farmer incomes, crop marketing, and input costs\u003c/h2\u003e \u003cp\u003eClimate change affects farmers\u0026rsquo; livelihoods through direct impacts on agricultural productivity and cascade effects that amplify economic losses. Climate variability puts production of annual crops at risk, with over 80% of farming households in our study experiencing income declines. Farmers relying solely on annual crops are particularly vulnerable to these climate shocks, facing huge income reductions. We found that having access to diversified income streams through CSMA helps resolve some of these economic vulnerabilities while also directly impacting household resilience.\u003c/p\u003e \u003cp\u003eThe economic impacts manifest differently across farming systems, with CSMA farmers being more resilient compared to non-macadamia farmers. This may be due to the nature of macadamia as a specialty crop with a focus on market and export orientation. Consequently, farmers cultivating macadamia benefit from export markets and high revenues. This economic positioning allows farmers to make meaningful investments in climate shock buffering strategies better than subsistence farmers (Barrett, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). It is also important to note that the specialty nature of macadamia has attracted particular attention from institutional and policy support, making it one of the government\u0026rsquo;s strategic export crops and benefiting from deliberate efforts to promote its cultivation.\u003c/p\u003e \u003cp\u003eAdditionally, CSMA provides valuable ecosystem services that generate extra economic benefits unavailable to non-macadamia farmers. Mature macadamia trees sequester about 20 kg of carbon dioxide annually, creating potential carbon credit income per tree each year in emerging carbon markets (Paembonan et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In contrast, non-CSMA farmers lack access to these carbon revenue streams and are more vulnerable to input price shocks due to greater reliance on external fertilizers and pest control measures. This demonstrates that agroforestry systems can reduce income volatility by 20\u0026ndash;40% during extreme weather events compared to monoculture systems and provide ecosystem service benefits valued at USD \u003cspan\u003e$\u003c/span\u003e500\u0026ndash;1,500 per hectare annually (Price, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Kay et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Bhattarai et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur survey results show that farmers practicing CSMA are less likely to experience complete income loss during climate shocks. These farmers are better able to maintain cash flow through multiple macadamia harvests, especially during the lean season harvests. Macadamia trees also enhance soil water retention through leaf litter and root systems, reducing water stress and fertiliser quantities for the intercropped annuals (Simba et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Xu et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Evidence further shows that agroforestry systems deliver multiple adaptation benefits, including risk reduction through diversification (Kittur et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and microclimate regulation (Shekmohammed et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, non-macadamia farmers face heightened economic risks from single harvests and higher production costs (fertilisers and pesticides), making them particularly vulnerable to weather-related losses and input price fluctuations, often resorting to borrowing or selling assets to meet basic needs. This comparative advantage demonstrates CSMA\u0026rsquo;s capacity to provide both food and nutritional security alongside cash flow stability while generating ecosystem service income streams.\u003c/p\u003e \u003cp\u003eClimate extremes create cascading economic impacts where drought leads to crop failure, especially among non-macadamia farmers, necessitating complete replanting which represents a double loss similar to flood damage. CSMA farmers benefit from tree-based stability that maintains some income even when annual crops fail. Moreover, non-macadamia farmers invest heavily in contingency supplies, including backup seeds, additional pesticides, and emergency fertilisers to safeguard against climate uncertainties, typically adding USD\u003cspan\u003e$\u003c/span\u003e100\u0026ndash;150 per hectare in risk management costs. Conversely, CSMA farmers leverage ecosystem services such as natural pest control and soil fertility enhancement to reduce contingency input needs, spending 40% less on risk management compared to monoculture systems.\u003c/p\u003e \u003cp\u003eComplex market dynamics create additional economic pressures, with reduced crop quality affecting 38.4% of respondents. The impact of climate change on crop quality and the associated marketing decisions is complex and dynamic (Morton, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). It mainly depends on which types of climate stresses affect crops and how these stresses interact with post-harvest handling practices. Farmers described how increasingly variable weather conditions compromise product standards, particularly regarding aflatoxin contamination in groundnuts and maize caused by moisture fluctuations during harvesting and drying.\u003c/p\u003e \u003cp\u003eAflatoxin contamination poses risks that extend beyond economic losses, representing a critical public health challenge. As potent carcinogens, aflatoxins are associated with liver damage and immune suppression, particularly when exposure occurs through chronic dietary intake (Wu, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Mgandu et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Severe contamination events have also been linked to acute health impacts, including fatalities. A major outbreak in Kenya in 2004 caused over 125 human deaths and hundreds of hospitalisations due to contaminated maize (Probst et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). More recently, in 2024, Zambia experienced an outbreak in which 400 dogs died, prompting authorities to launch a national public health crisis response. These incidents highlight both the immediacy and severity of aflatoxin risks across different contexts.\u003c/p\u003e \u003cp\u003eBeyond acute outbreaks, aflatoxin contamination compromises the safety of domestic food supplies and disqualifies agricultural products from international markets (Hejazi, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). With increasing warming projected under climate change, the frequency and severity of aflatoxin contamination is expected to intensify, especially in the tropical and sub-tropical regions (Casu et al., 2025; Kharod et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Evidence from Central Malawi already highlights how these trends may exacerbate public health risks while threatening livelihoods and nutrition security (Warnatzsch et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Adaptation strategies implemented to counter the impacts of climate change\u003c/h2\u003e \u003cp\u003eAdaptation to climate change is critical for maintaining productivity and safeguarding rural livelihoods, especially as rising climate risks threaten global food security. Our findings shows that both CSMA and non-macadamia farmers in central Malawi demonstrate adaptive capacity, but in different ways. CSMA farmers focus on temporal strategies, especially shifting of annual crop planting dates, while non-macadamia farmers rely on diversified adaptation strategies such as crop diversification, soil conservation, improved irrigation, and recently adopting agroforestry. Interestingly, drought-tolerant seeds were adopted by around 45% of farmers in both groups, reflecting a common strategy to buffer against climate risks. This pattern aligns with broader evidence that smallholder farmers enhance resilience by diversifying crops, conserving soil moisture, and adopting stress-tolerant varieties such as drought tolerant and early maturing varieties to enhance resilience (Holden \u0026amp; Fisher, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Katengeza et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This concentration-diversification dichotomy provides important insights into how adaptive capacity is expressed across different agricultural systems and challenges conventional assumptions about optimal adaptation pathways.\u003c/p\u003e \u003cp\u003eThe nature of these differences becomes more evident when examining CSMA as a system of adaptation. However, the contrasting patterns do not necessarily reflect lower adaptive capacity among CSMA farmers; rather, they arise because many adaptive practices are already embedded within macadamia-based systems. CSMA farmers argue that this system of production inherently bundles adaptation practices. For example, basic construction around the macadamia trees, leaf litter fall and interplanting with annuals simultaneously provides permanent soil cover, which helps in building soil organic matter and in turn soil health, conserves soil moisture, and diversifies production. Additionally, legumes such as groundnuts, pigeon peas and soybeans help to improve the soil fertility through biological nitrogen fixation that is used by the macadamia trees and the subsequent crop in the following season. In contrast, non-macadamia farmers must create equivalent benefits through discrete investments. This indicates that CSMA enhances climate resilience through system architecture rather than discrete interventions.\u003c/p\u003e \u003cp\u003eThese interpretations are in agreement with Lunn-Rockliffe et al. (2025), who reported that combining methods allows farmers to expand the synergy between regenerative agricultural practices, thereby increasing farm productivity in the face of intersecting challenges such as climate change, soil degradation, and pests and diseases. Additionally, research on adaptation perception confirms that farmers often fail to recognise the benefits of integrated systems as discrete adaptation measures (Gemtou et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Kabato et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This explains why CSMA farmers may not identify embedded practices as separate adaptation strategies, even though they significantly strengthen resilience. Our findings, therefore, suggest that promoting agroforestry practices can extend resilience beyond CSMA farmers. Integrating trees into farming systems, whether for smallholder or large commercial farms, for shade, soil conservation, or diversified harvests, offers a practical pathway to enhance adaptive capacity.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eOur study demonstrates that climate-smart macadamia agroforestry can strengthen smallholder resilience to climate change in central Malawi and globally. By reconfiguring farm structure rather than introducing a single adaptive practice, CSMA integrates diversification, ecological regulation and temporal flexibility within the production system itself. In doing so, it shifts adaptation from reactive coping toward structurally integrated resilience.\u003c/p\u003e \u003cp\u003eCompared with conventional monocultures, CSMA systems are associated with more stable production outcomes and broader livelihood buffering, supported by ecosystem services delivered through tree-crop integration. The contrast between concentration and diversification pathways highlights that resilience is not solely a function of the number of strategies adopted, but of how risk management is organised within the farming system. Agroforestry, in this context, operates as a platform for cumulative adaptation.\u003c/p\u003e \u003cp\u003eHowever, the transition to tree-based systems remains constrained by a climate vulnerability trap: declining yields and rising costs reduce the capacity of the most exposed households to invest in long-gestation crops. Without targeted support, adaptation may remain inaccessible to those who would benefit most. Embedding CSMA within national adaptation frameworks will therefore require coordinated policy, finance and market interventions, including risk sharing mechanisms during establishment phases, climate-smart credit, carbon incentives, strengthened extension systems and inclusive value-chain integration.\u003c/p\u003e \u003cp\u003eThese findings position agroforestry as a structural pathway toward climate-resilient rural development. Its broader contribution to adaptation and food security will depend on enabling institutional architectures capable of supporting equitable system transformation under accelerating climate change. We therefore argue that supporting CSMA and related agroforestry approaches should be prioritised in agricultural policy, in Malawi but also for farming communities globally. In addition, strengthening knowledge exchange through peer-learning mechanisms such as farm walks, field days, and farmer field schools can accelerate adoption and ensure that both younger and older farmers benefit from these practices.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclaration of generative AI and AI-assisted technologies in the manuscript preparation process\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the preparation of this work the author(s) did not use any generative AI and AI-assisted technologies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData and code \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets will be made available upon request from the corresponding author. \u0026nbsp;The statistical analysis code, and supplementary materials, are publicly accessible through the Climate-Impacts repository.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by The Open University through the Open Societal Challenges initiative. \u0026nbsp;The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The views expressed in this publication are those of the authors and do not necessarily reflect the official position of The Open University.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Human Research Ethics Committee (HREC) of The Open University, United Kingdom, provided ethical approval for this study. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRediT authorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualisation: EZ, AE, YA, NE; Methodology: EZ, YA, AE, WB; Writing \u0026ndash; Original draft: EZ, WB; Writing \u0026ndash; review \u0026amp; editing: YA, AE, NE, TE, MC, JH: Data analysis: EZ, MC, WB; Visualisations: WB, EZ, MC; Funding acquisition: AE, NE, TE; Project supervision: EZ, AE, WB, NE, TE, JH.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbidoye B, Aladysheva A, Haitz N, Montresor G, Nyekanyeka T, Orlic E, Prowse M. 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Climate suitability predictions for the cultivation of macadamia (\u003cem\u003eMacadamia integrifolia\u003c/em\u003e) in Malawi using climate change scenarios. PLoS ONE. 2021;16(9):e0257007. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0257007\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0257007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZuza EJ, Muhammed AO, Emmott A, Brandenburg RL, Araya YN. (2024). Macadamia Nuts as a Supplement. Nut Consum its Usefulness Mod World, 85.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Smallholder resilience, adaptation strategies, Sub-Saharan Africa, sustainable agriculture, integrated land use systems, mixed methods","lastPublishedDoi":"10.21203/rs.3.rs-9303871/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9303871/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSmallholder farmer resilience to climate change is commonly assessed through discrete adaptation measures, overlooking the potential of integrated land use systems. Our study explores Climate-Smart Macadamia Agroforestry (CSMA) as a climate adaptation strategy in central Malawi. We examine farmer perceptions, existing climate challenges, and the feasibility of scaling up CSMA systems to enhance adaptive capacity. Moving beyond approaches that treat adaptation as isolated interventions, we identify two distinct pathways: system-integrated resilience among CSMA farmers, where multiple adaptive benefits are embedded within the land use system itself; and discrete strategy adoption among non-CSMA farmers, which typically requires costly, separate interventions. Moreover, our study reveals that CSMA inherently bundles ecosystem services, including temporal flexibility, income diversification, and carbon sequestration, that collectively strengthen adaptive capacity without additional investment, while monoculture systems remain comparatively vulnerable. By quantifying performance differences in yield stability and income resilience between the two groups, we identify strategic opportunities for mainstreaming agroforestry into climate adaptation and land use planning frameworks. Practically, the study also highlights targeted interventions including drought-tolerant varieties, integrated pest management, and post-harvest technologies that can enhance smallholder resilience not only in Malawi but across comparable farming systems in sub-Saharan Africa SSA) and globally.\u003c/p\u003e","manuscriptTitle":"Can climate-smart macadamia agroforestry systems safeguard smallholder farmers against climate shocks in Malawi?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-13 16:32:46","doi":"10.21203/rs.3.rs-9303871/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4d30e71d-3cbd-4ddc-bec6-cffd3a1999b9","owner":[],"postedDate":"April 13th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-18T12:22:30+00:00","index":84,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-17T07:53:49+00:00","index":83,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-13T20:59:53+00:00","index":82,"fulltext":""},{"type":"reviewerAgreed","content":"238270648358149567014601712279908392102","date":"2026-05-11T06:19:17+00:00","index":81,"fulltext":""},{"type":"reviewerAgreed","content":"227389197465688281547089998109652310051","date":"2026-05-09T14:03:34+00:00","index":80,"fulltext":""},{"type":"reviewerAgreed","content":"137268387601573109780348588677387196807","date":"2026-05-06T12:14:46+00:00","index":79,"fulltext":""},{"type":"reviewerAgreed","content":"70783519743926084110660642347469704867","date":"2026-05-06T10:40:49+00:00","index":78,"fulltext":""},{"type":"reviewerAgreed","content":"36969215484829450865736571030099158437","date":"2026-05-06T08:59:00+00:00","index":76,"fulltext":""},{"type":"reviewerAgreed","content":"322319665134626445413806107352259351050","date":"2026-05-05T16:19:42+00:00","index":74,"fulltext":""},{"type":"reviewerAgreed","content":"153658136755783228147263249400874671854","date":"2026-05-04T11:35:13+00:00","index":73,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-13T16:32:47+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-13 16:32:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9303871","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9303871","identity":"rs-9303871","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}