Climate Change and Small-Scale Agriculture in the Eastern Cape Province: Investigating the Nexus of Awareness, Adaptation, and Food Security

Abstract

Climate change poses a significant threat to global agriculture, particularly for small-scale farmers who often lack the resources and knowledge to adapt. Without effective coping and adaptation strategies, agriculture in Africa is likely to suffer, leading to increased poverty and food insecurity. Adaptation to climate change is closely linked to farmers’ awareness of the issue, though the extent of this awareness in South Africa remains unclear due to conflicting previous studies. This study aimed to investigate the relationship between climate change awareness, adaptation strategies, and food security among small-scale farmers in the Eastern Cape Province, with the aim of understanding how farmers’ awareness of climate change influences their adaptation decisions and the subsequent impact on agricultural productivity and food security. The study used quantitative analysis to examine the relationship between climate change knowledge, adaptation, and food security. Multi-stage sampling was used to collect data from 200 small-scale farmers through semi-structured questionnaires. Logit regression and endogeneity switching regression were applied for data analysis. The study finds that small-scale farmers in the province are fully aware of climate change and have experienced its negative impacts, especially reduced farm returns (38%) and yields (36%), which threaten agricultural productivity, food security, and farmers’ economic viability. In response, farmers have adopted various strategies, including crop rotation (22%), using improved crop varieties (20%), changing planting dates (12%), and applying fertilizer or mulching (12%). Key factors influencing adaptation include age, access to climate information, education, market proximity, extension services, drought frequency, temperature and rainfall perceptions, radio ownership, farm income, size, and family size. The study shows that these adaptation strategies have improved agricultural yields and farm returns, positively contributing to food security in the area. Based on the study findings, this study recommends that governments and policymakers implement and provide targeted policy interventions, extension services, and educational programs that can enhance climate change knowledge among small-scale farmers.

1. Introduction

The agriculture sector plays a crucial role in many African economies, employing around 65–70% of the workforce, supporting 90% of household livelihoods, and accounting for about a quarter of the continent’s gross domestic product [1]. Growth in the agriculture sector is believed to be more effective at reducing poverty, which the continent is currently battling with, than growth in non-agricultural sectors [2]. However, growth in the agricultural sector is constrained by current climate change challenges due to its inextricability on climate conditions and its susceptibility to climate change impacts [3]. The agricultural production has been disturbed by the impact of climate change and variability in many parts of the world, with a special focus on smallholder farmers as they rely more on wildlife for survival [4,5,6]. Since agriculture in most African countries is predominantly small-scale and rain-fed, its susceptibility to climate variability and change is heightened [7,8,9]. The sector’s vulnerability in Africa is further heightened by the fact that small-scale and smallholder farmers largely lack access to the resources and technology required to manage and adapt to the impacts of climate change [10,11,12]. Climate change projections indicate the potential for significant changes in Africa’s climatic conditions, including the likelihood of increasingly warm and dry weather in the subtropics and increased rainfall in the tropics. Additionally, the projections suggest a high probability of substantial impacts across many regions of Africa [5,13,14,15]. Therefore, there is a need for effective coping and adaptation strategies to help farmers sustain their agricultural practices under changing climate conditions. Without effective coping and adaptation strategies, these impacts on small-scale farmers are likely to intensify [16,17,18], resulting in intensified poverty and food insecurity levels, particularly in the rural areas of the continent where farming is the primary livelihood [8].

Small-scale farming, in general, is specifically vulnerable to the devastating effects of climate change due to a lack of ability to cope with these changes [19]. Farming plays a major role in the contribution of food for rural households to be food secure, but this sector is very sensitive to climate change and farmers depend mostly on it. In a study conducted by Tomlinson and Rhiney [20], the literature suggests that most workers encounter major challenges associated with climate change, such as shortfalls in production and extremely hot weather conditions. The effects of climate change on small-scale farmers are more likely to grow if there are no suitable coping strategies [12].

Long-term weather climate change is considered a worldwide threat/risk that transcends geographical boundaries and is recognized as one of the most severe environmental dangers [7]. It continues to pose a significant risk to humanity, threatening global survival and safety. Its impacts are already being felt across various sectors and production environments globally. African countries worldwide are mostly affected by long-term weather variations as they bring unpredictable results that influence farming practices and produce negatively. These long-term weather variations are the main progressive encounters that many countries face [9]. Most small-scale farming communities are very susceptible to climate change as it decreases production and results in food insecurity [9]. Many underdeveloped countries suffer the consequences of climate change due to their lack of advanced technology to support their farming systems [16]. Farming systems directly support 600 million livelihoods in many parts of sub-Saharan Africa (SSA) and South Asia [20]. The agricultural sector is quickly mounting and contributes about 33% to its GDP in these areas; however, due to climate change occurrence, this might be influenced negatively, leading to a decrease in agricultural yields [20].

Many Southern Africa countries face high surface temperatures, dry conditions, and altered rainfall patterns, which have become prevalent and are projected to worsen [21,22]. The inability of South Africans to prepare for current and projected climate change, and its impacts, is heightened by its semi-arid and water-stressed nature [23]. Projected changes in climate and subsequent lack of water will aggravate current water strains [23,24], leading to adverse effects on water resources, agricultural production, food security, ecosystem services, and the South African economy [25]. Although smallholder farming does not contribute significantly to the GDP or the national economy, it has a great potential to reduce poverty and increase food security in many rural households [26]. In South Africa, over 200,000 smallholder farmers and about 2 million subsistence farmers participate in food production at the household level, addressing the serious issue of food security [26].

Long weather variations in climate pose a risk to the sustainability of many smallholder farming communities as they depend solely on nature for survival, especially in rural areas where farmers already face numerous challenges [27]. This situation necessitates a deeper understanding of climate change to develop impactful coping mitigations that address its effects on smallholder agriculture. This understanding is crucial for smallholder farmers, who often bear the brunt of local and global environmental changes [28]. The future climate-resilient development of smallholder farmers depends on their understanding of climate changes and their capacity to respond effectively through proper adaptation and mitigation.

Climate change represents a profound global crisis with far-reaching consequences for agriculture, ecosystems, and food security. Its impacts are particularly severe for small-scale farmers in vulnerable regions, such as sub-Saharan Africa, where communities often face limited resources and capacities to mitigate climate-related risks. This is especially true in South Africa’s Eastern Cape Province, a region that relies heavily on subsistence farming and remains one of the country’s poorest. Here, small-scale farmers are increasingly threatened by climate-related challenges, including erratic rainfall, prolonged droughts, rising temperatures, and shifting growing seasons. These environmental changes, compounded by widespread poverty, exacerbate the region’s food insecurity, creating a pressing need for effective adaptation strategies. This study contributes significantly to climate change and small-scale agriculture discourse by exploring the complex inter-relationship between climate change awareness, adaptation strategies, and food security in the Eastern Cape. While much of the existing literature has examined these components in isolation, climate change awareness, adaptation, and food security, there remains a notable gap in research that integrates these elements and investigates how they intersect and influence each other within smallholder farming. The focus of this study is to address the insufficient understanding of how smallholder farmers in developing regions, particularly in South Africa, perceive and respond to climate change and how these responses are intricately linked to their food security outcomes. While previous studies have documented the broader impacts of climate change on agriculture, there has been limited research on the specific adaptation strategies employed by small-scale farmers in the Eastern Cape. Furthermore, few studies have explored how these strategies, or the absence thereof, influence long-term food security. This gap is critical, given that small-scale agriculture is central to rural livelihoods in Southern Africa, and the ability of farmers to adapt to climate variability is a key determinant of their long-term resilience. Despite the centrality of agriculture to the region’s economy and food systems, smallholder farmers in the Eastern Cape face substantial barriers, ranging from a lack of financial resources and technological support to insufficient climate knowledge and access to adaptation tools. As a result, they are disproportionately vulnerable to climate-induced environmental changes exacerbated by global climate trends.

Additionally, this study contributes significantly to understanding climate change and small-scale agriculture by exploring the interconnectedness of climate change awareness, adaptation strategies, and food security in the Eastern Cape Province of South Africa. While the existing literature has explored these individual elements, climate change awareness, adaptation, and food security, there is a notable gap in integrated research examining how these factors inter-relate, especially within small-scale farming. This study addresses the critical concern of limited understanding regarding how smallholder farmers perceive and respond to climate change and how these responses influence their food security outcomes. Although there is a growing body of research on the impacts of climate change on agriculture, few studies have focused on the specific adaptation strategies employed by small-scale farmers in the Eastern Cape and how these strategies contribute to long-term food security. This research gap is particularly significant, as small-scale agriculture plays a foundational role in the livelihoods of rural communities in Southern Africa, particularly in the Eastern Cape. However, farmers in this region often face challenges such as limited resources, inadequate knowledge, and a lack of access to climate data, which hinder their ability to adapt effectively to climate variability. By focusing on the intersection of climate change awareness, adaptation practices, and food security, this study goes beyond examining the general effects of climate change on agriculture. It offers new insights into how farmers’ awareness of climate change influences their adoption of specific adaptive measures and, in turn, how these measures impact their long-term food security. This study also provides a localized perspective on the unique socio-economic and environmental conditions in the Eastern Cape, an area under-researched in the literature. This approach highlights the complexities of climate adaptation within a region marked by poverty, limited market access, and frequent climate shocks, all compounding farmers’ ability to adapt. Moreover, this study offers a holistic perspective that situates climate change adaptation and food security within the specific dynamics of the Eastern Cape, making it highly relevant to policymakers, practitioners, and development organizations working in similar rural contexts. The findings of this study have important policy implications for improving climate change adaptation programs and food security interventions aimed at smallholder farmers. Through its in-depth analysis, this research fills a critical gap in the literature, offering actionable recommendations for strengthening the resilience of small-scale farmers in the face of ongoing climate challenges.

This study examines the intersection of climate change awareness, adaptation practices, and food security. It offers a nuanced understanding of how awareness influences farmers’ adoption of adaptation measures and how they affect their ability to secure food. In contrast to studies that treat these factors in isolation, this research underscores the interconnectedness of climate change awareness, adaptation, and food security, illustrating their cumulative impact on farmers’ resilience. Additionally, by contextualizing these dynamics within the socio-economic and environmental realities of the Eastern Cape, this study offers a localized perspective that has been underexplored in the literature. This localized focus is essential for developing context-specific strategies to support smallholder farmers in the region better, helping them build resilience and improve food security in the face of climate change. This research fills a critical gap in understanding how smallholder farmers in the Eastern Cape perceive, adapt to, and are impacted by climate change, providing valuable insights that can inform the design of targeted interventions to enhance climate resilience and food security for vulnerable farming communities.

Despite a growing body of research on farmers’ understanding and perceptions of climate change in Southern African countries, including studies from Maponya & Mpandeli [29], Elum et al. [30] and Tesfuhuney and Mbeletshie [31], there remains significant debate regarding the level of awareness and understanding among smallholder farmers. While some studies suggest that small-scale producers have a basic understanding of climate change, other research highlights a troubling lack of awareness. For instance, Diniso et al. [32] report that many South African farmers struggle to grasp the link between global warming and local climate change, with some referring to the phenomenon simply as “changing weather” [33]. This discrepancy in understanding is a critical issue, as the ability to effectively respond to climate risks depends on the depth of farmers’ knowledge. Smallholder farmers often face significant barriers, including limited access to accurate climate data and agricultural extension services, which hinder their adaptation capacity. This knowledge gap heightens their vulnerability to climate-induced shocks and undermines their long-term resilience, particularly in regions like the Eastern Cape, where small-scale agriculture is vital to rural livelihoods and food security. While studies have documented the broader impacts of climate change on agriculture in South Africa, particularly in the Eastern Cape, there remains a notable gap in research focused on the specific adaptation strategies employed by smallholder farmers in the region. Despite the widespread acknowledgment of climate change’s potential to disrupt farming, few studies have explored how these farmers respond to climate variability and how they affect long-term food security outcomes. To cope with climate change, many smallholder farmers in the Eastern Cape have adopted various adaptive strategies, such as crop diversification, staggered planting and harvesting, improved water management, and, in some cases, early weather warning systems [34,35,36,37]. These strategies have been shown to enhance resilience, enabling farmers to mitigate some of the adverse effects of climate change. Farmers who are proactive and able to implement these adaptive measures quickly are more likely to improve their crop yields and overall well-being, as they are better prepared for unexpected climatic events [38]. However, the effectiveness of these strategies is often limited by resource constraints and a lack of technical support, underscoring the need for targeted interventions to enhance farmers’ adaptive capacities and strengthen their resilience to climate change in the long term.

This study makes theoretical, empirical, practical, policy and decision-making, and methodological additions to the body of knowledge already available on climate change, small-scale agriculture, and food security. The theoretical contributions are predicated on investigating the relationship between climate change, agricultural practices, and food security results in the Eastern Cape Province and on improving knowledge of small-scale farmers’ awareness of and adaption methods to climate change. In addition to identifying regionally specific difficulties and potential for climate-resilient agriculture in the Eastern Cape Province, empirical contributions include primary data on the effects of climate change, adaption strategies, and small-scale farmers’ experiences with food security.

It is important to note that exposure to climate change varies geographically across spatial and temporal scales. This means that farmers within a specific region may experience climate change differently. Scientific data may fail to capture the varying climate trends experienced within the same hydroclimatic area [39,40]. This indicates that farmers within the same district can experience and observe different climate variations. The difference in the climate change experienced and observed directly influences individuals’ climate change perception and understanding, and hence, influences the adaptation decision. The first step towards effective climate change adaptation is recognizing that the climate has been and continues to change [41]. It is argued that individuals who are proactive in climate change adaptation began by perceiving and understanding that the local climate was changing [31]. This awareness is often achieved through firsthand experience of the effects and influence of changes in climate on their livelihoods rather than through hearsay, as people tend to dismiss any subject if its influence is not evident in their own lives [32]. This experience also increases curiosity to seek more information about observed climate change, leading to greater access to and use of climate information [33]. Against this background, this study aims to assess the impact of climate change awareness and access to climate information on small-scale farmers’ adoption of the available adaptation strategies for their agricultural yields and farm returns in the Eastern Cape.

2. Theoretical Framework

The Theory of Planned Behaviour (TPB) is a psychological framework used to understand human decision-making, focusing on three key factors: attitudes, subjective norms, and perceived behavioural control. These elements influence how individuals, including farmers, respond to challenges like climate change [42,43,44,45,46]. TPB has proven particularly useful in small-scale agriculture, where it helps explain how farmers adopt adaptive practices in response to climate variability. In the study ‘Climate Change and Small-Scale Agriculture in the Eastern Cape Province: Investigating the Nexus of Awareness, Adaptation, and Food Security’, TPB provides a lens to explore the interconnectedness of farmers’ climate change awareness, coping strategies, and food security outcomes [42]. The theory helps illuminate how farmers’ decisions are shaped by their attitudes toward climate change, social influences (e.g., peers, family, community leaders), and their perceived ability to implement adaptive measures, which can depend on access to resources and support. By understanding these psychological and social factors, the study reveals why some farmers are more proactive in adapting to climate change while others may be resistant or passive. TPB offers valuable insights into the psychological drivers behind adaptation decisions, guiding targeted interventions that can enhance resilience, improve food security, and support sustainable agricultural practices in the Eastern Cape.

Attitudes: Attitudes are pivotal in the Theory of Planned Behaviour (TPB), significantly influencing individuals’ intentions and actions. In the context of a study on climate change knowledge and coping strategies among small-scale farmers in the Eastern Cape Province, understanding farmers’ attitudes and awareness towards these strategies is crucial for evaluating their adaptive capacity. Farmers’ attitudes toward coping strategies are significantly influenced by their awareness of climate change impacts and their perceptions of the effectiveness and feasibility of these practices. This awareness shapes farmers’ perception of the urgency and necessity of adapting their methods. When farmers understand the challenges posed by climate variability, such as droughts or erratic rainfall, they are more likely to recognize the importance of implementing adaptive practices. If they believe these strategies will lead to improved yields and greater food security, they are more inclined to embrace them. This positive perception fosters a proactive approach, encouraging them to invest time and resources into learning and applying new methods. Farmers’ attitudes are shaped by their perceptions of strategy effectiveness, feasibility, and benefits, influenced by past experiences and socio-economic constraints [47]. Positive attitudes often stem from firsthand success stories, driving increased adoption rates, while negative attitudes can hinder experimentation and investment in new techniques. Conversely, if they doubt the effectiveness of these adaptations or perceive them as burdensome, their likelihood of adoption diminishes. Therefore, cultivating a positive attitude through education and awareness campaigns is essential, as it empowers farmers to embrace innovative strategies that mitigate the impacts of climate change, secure their food sources, and improve their overall well-being. However, Liu et al. [48] and Ullah et al. [49] demonstrated that these attitudes and beliefs adversely affect climate change initiatives. Conversely, Hasibuan et al. [50] and Mwaseba et al. [51] advised that recognizing climate change positively correlates with adopting mitigation strategies. The small-scale farmers’ attitude toward climate change is evident through their recognition of climate-related occurrences, indicating their belief in the occurrence and impact of climate change.

Additionally, social factors play a vital role in shaping these attitudes. Farmers often look to their peers and community leaders for guidance. When they see successful implementations of coping strategies within their networks, it reinforces their belief in the efficacy of these practices. Conversely, if they doubt the effectiveness of these adaptations or perceive them as overly complex or burdensome, their likelihood of adoption diminishes. Moreover, the role of accessible information cannot be overstated. Education and outreach initiatives that effectively communicate the tangible benefits of adaptation strategies can shift perceptions and enhance confidence in their utility. By cultivating a positive attitude through targeted awareness campaigns, stakeholders can empower farmers to embrace innovative strategies that mitigate the impacts of climate change, secure their food sources, and improve their overall well-being. Fostering supportive attitudes among farmers is essential for promoting sustainable agricultural practices that can withstand the challenges of a changing climate, thereby contributing to greater food security and resilience in rural communities. Subjective Norms: Subjective norms, referring to the influence of social networks and community expectations, play a critical role in shaping farmers’ intentions regarding climate adaptation practices [52,53,54]. Additionally, subjective norms reflect the social pressures and expectations from influential figures such as family members, peers, and agricultural extension advisors. These norms can provide awareness and essential social validation and reinforce the acceptability of particular strategies within the community, further influencing farmers’ decisions. In the study context, subjective norms influence farmers’ decisions to adopt coping strategies. These norms encapsulate the social pressures and expectations farmers perceive from various influential sources such as family members, neighbors, and agricultural extension agents. When influential figures within a community advocate for adaptive practices, such as sustainable farming techniques, it creates a collective momentum that encourages others or farmers to follow suit. This social pressure can enhance farmers’ willingness to adopt these strategies as they seek acceptance and support from their social circles. Suppose farmers observe and know that their peers or agricultural advisors endorse specific coping strategies. In that case, they are more inclined to adopt them. This endorsement acts as a form of social validation, reinforcing the perceived legitimacy and efficacy of the strategy within the community.

Furthermore, the power of social networks extends beyond mere encouragement; it can also provide valuable resources and information [55]. Farmers are more likely to experiment with new practices when they observe their neighbors successfully implementing them or receiving positive reinforcement from community leaders. This shared knowledge fosters a culture of adaptation, where farmers feel less isolated in their efforts and more supported in their choices. Conversely, if prevailing community norms discourage innovation or adaptation, individuals may hesitate to embrace new practices, fearing social ostracism or skepticism. Therefore, leveraging the influence of social norms is essential in promoting climate adaptation strategies. Initiatives that engage community leaders and utilize local networks can create an environment where adaptive practices are accepted and celebrated [55]. By fostering a collective commitment to resilience and sustainability, communities can empower farmers to make informed decisions that enhance their capacity to cope with climate variability, ultimately contributing to greater food security and community well-being. Perceived Behavioural Control: Perceived behavioural control refers to farmers’ beliefs regarding their ability to implement adaptation strategies successfully, and it plays a crucial role in shaping their willingness to act. Several factors influence this perception, including access to resources, information availability, and necessary skills development. When farmers have access to essential resources, such as funding, tools, and materials, they are more likely to feel equipped to adopt new agricultural practices. Furthermore, information dissemination through channels like radio broadcasts or agricultural extension services is vital; it informs farmers about the benefits of adaptive strategies and guides them in effectively implementing these practices [56,57]. Cultivating relevant skills through training and education also enhances farmers’ confidence in adapting. For instance, workshops on sustainable farming techniques or climate-smart agriculture can empower farmers with the knowledge and hands-on experience needed to implement new methods. When farmers perceive themselves as capable and supported in their efforts, they are significantly more inclined to embrace innovative practices that can mitigate the impacts of climate change [58,59]. Moreover, awareness of behavioural control encompasses farmers’ beliefs in their ability to implement these coping strategies successfully. This perception is crucial for understanding their intentions, as it determines whether farmers feel empowered to act. When farmers recognize they have the necessary resources, skills, and support, they are more inclined to adopt climate-resilient practices. Conversely, if they feel constrained by a lack of resources or knowledge, their motivation to act diminishes, leading to inaction in the face of pressing challenges.

Thus, fostering a strong sense of perceived behavioural control is essential for promoting effective climate adaptation among farmers. By addressing barriers to resource access, enhancing information flow, and providing targeted training, stakeholders can empower farmers to adopt adaptive strategies confidently. This empowerment enhances individual resilience and strengthens agricultural communities’ capacity to respond to climate variability uncertainties, ultimately contributing to improved food security and sustainability. According to Wilson et al. [59], perceived control over behaviour is a crucial predictor of farmers’ inclination toward adopting agrarian practices. Through the extension, Perceived Behaviour Control directly influences farmers’ intentions and behaviour during the decision-making period.

In the context of this study, the Theory of Planned Behaviour (TPB) provides a comprehensive framework for understanding the intentions and behaviours of small-scale crop farmers as they adopt coping strategies for climate change. TPB posits that the behavioural intentions of these farmers are shaped by three key factors: attitudes, subjective norms, and perceived behavioural control. Farmers’ attitudes toward coping strategies are significantly influenced by their perceptions of the effectiveness and feasibility of these practices, playing a critical role in shaping their intentions to adopt them. For example, if farmers believe that specific strategies will lead to improved yields and greater food security, they are more likely to embrace those practices. Additionally, subjective norms reflect the social pressures and expectations from influential figures such as family members, peers, and agricultural extension advisors. These norms can provide essential social validation and reinforce the acceptability of particular strategies within the community, thereby influencing farmers’ decisions. Moreover, perceived behavioural control encompasses farmers’ beliefs in their ability to implement these coping strategies successfully. This perception is crucial for understanding their intentions, as it determines whether farmers feel empowered to act. When farmers recognize they have the necessary resources, skills, and support, they are more inclined to adopt climate-resilient practices.

By examining these psychological factors, this study aims to elucidate the underlying motivations that drive farmers’ decision-making processes. This insight will inform the development of targeted interventions and policies designed to support adopting climate-resilient agricultural practices, ultimately enhancing the resilience of farmers in the Eastern Cape Province against the challenges posed by climate change. By integrating these components, the TPB provides insights into how awareness of climate change and personal and social factors affect farmers’ decisions to adapt. This study highlights that increased awareness of climate impacts and effective communication about adaptation options can enhance farmers’ confidence and willingness to change their practices, thereby improving food security and resilience in the face of climate variability. By addressing attitudes, subjective norms, and perceived behavioural control, stakeholders can create tailored initiatives that resonate with farmers’ motivations and capabilities. Such concerted efforts and intentions are essential for fostering increased adoption of adaptive practices, ultimately bolstering farm productivity and fortifying the resilience of agricultural communities in the Eastern Cape Province in the face of climate change challenges. Figure 1 illustrates the application of the Theory of Planned Behaviour within the context of this study.

3. Methodology

3.1. Description of the Study

The Eastern Cape Province is home to many small-scale crop and livestock farmers who are particularly vulnerable to the impacts of climate change, including increased temperatures, altered precipitation patterns, and more frequent extreme weather events. These changes pose significant challenges to agricultural production in the region, largely dependent on rain-fed agriculture. The Eastern Cape’s main feature is its spectacular coastline bordering the Indian Ocean.

It covers an area of 168,966 km² and has a population of 6,996,976. It is the second-largest Province in South Africa by surface area and has the third-largest population [60,61,62]. The capital is Bhisho. Other major cities and towns include Port Elizabeth (Gqeberha), East London, Makhanda (previously known as Grahamstown), Mthatha (previously Umtata), Graaf Reinet, Cradock, and Port St Johns. The Eastern Cape is one of South Africa’s poorest provinces, incorporating large areas of South Africa’s former homelands. The Eastern Cape is divided into two metropolitan municipalities (Buffalo City Metropolitan Municipality and Nelson Mandela Bay Metropolitan Municipality) and six districts subdivided into 31 local municipalities.

The Province has good climatic conditions, which are favorable for agricultural activities. The climate is hot in summer, with an average of 26 degrees Celcius, and winter temperatures average 13 degrees Celcius. The average rainfall in summer is 1000 mm, and in winter, it is 400 mm. These climate conditions favor any agricultural activities, and as a result, the Province is known for its livestock production, vegetable and crop production, and citrus production. Most agricultural activities are dominated by smallholder farmers who practice for market and home consumption as this is their primary source of livelihood (Figure 2).

3.2. Sampling Procedure, Sample Size, and Data Collection

This study employed a cross-sectional research design based on a survey conducted in the Eastern Cape Province. A detailed sampling framework was developed to ensure a comprehensive representation of the study area, considering factors such as cropping patterns, agricultural activities, the proportion of cultivated land, and climate variations across different agroecological districts. These districts were deliberately selected to reflect various climate conditions and cropping systems. Data were collected using a multi-stratified random sampling method targeting small-scale crop farmers. Initially, three district municipalities (OR Tambo, Amatole, and Chris Hani) were selected based on the presence of active small-scale crop farmers and relevant climatic and agroecological factors. Subsequently, four wards were randomly chosen from each district. In the second phase, a stratified random sampling technique was applied, categorizing small-scale farmers into three strata: Stratum 1 for crop farmers, Stratum 2 for vegetable farmers, and Stratum 3 for livestock farmers. In the final phase, 67 farmers from each district were randomly interviewed, culminating in a total of 200 small-scale crop farmers participating in the data collection process.

A structured questionnaire was utilized to collect data from respondents via face-to-face interviews. To ensure its effectiveness, the questionnaire was pre-tested with 10% of the sample size in Ntselamanzi Location, which was not included in the final study. The pre-testing aimed primarily to identify and resolve any ambiguities in the wording of the questions, ensuring that respondents interpreted them as intended to minimize inaccuracies. Additionally, it assessed the clarity and comprehensibility of the questions, which is vital for preventing biased or incomplete responses caused by confusion. Finally, the pre-test evaluated the sequence of the questions to ensure a logical flow, facilitating smooth progression throughout the interview.

Additionally, pre-testing helps evaluate response options, estimate completion time, and assess cultural sensitivity, all contributing to the questionnaire’s effectiveness and relevance for diverse audiences. It also validates the constructs being measured, ensuring the reliability of the questionnaire and enhancing the validity of the research findings. Overall, pre-testing was conducted to ensure quality, reliability, and effectiveness, thereby improving the accuracy of the research outcomes. The questionnaire comprehensively addressed various aspects, including farm household demographics, agricultural practices, production costs, irrigation water usage, access to extension services, access to climate information and the channels used to gather it, perceptions of climate change and associated risks, responses to climate change, access to credit, farm and household assets, supplementary income sources, and barriers to implementing climate change responses. Special attention was given to capturing perceptions of extreme weather conditions and climate risks and understanding adaptation strategies in response to these extremes. Questions were designed to determine whether farmers had observed long-term climate changes over the past two decades. Overall, the findings reveal a perceived trend of erratic rainfall patterns and increasing temperatures in the study area.

3.3. Data Analysis

The collected data were coded and entered into Excel before being transferred to STATA 17 for analysis. Descriptive statistics were employed to outline the profiles of small-scale farmers, their perceived understanding of climate change, the challenges they encountered, and the adaptation strategies they adopted. Logit regression analysis was utilized to identify the factors influencing adopting these adaptation strategies among small-scale crop farmers. Additionally, endogeneity switching regression was applied to evaluate the effects of adaptation strategies on crop yield and farm returns, respectively.

3.3.1. Endogeneity Switching Regression (ESR)

This study employed the endogeneity switching regression model as an analytical tool to assess the impact of adaptation strategies to climate change on small-scale crop farmers in the Eastern Cape Province of South Africa. Endogeneity switching regression is a statistical method designed to address endogeneity in regression analysis. Endogeneity arises when independent variables are correlated with the error term in the regression model, resulting in biased and inconsistent parameter estimates. Various econometric models exist to evaluate the effects of climate change adaptation on crop yield. Common methods used in cross-sectional surveys include simple comparisons of means between adopters and non-adopters, ordinary least squares (OLS) regression treating adaptation as a binary variable, and propensity score matching. However, Di Falco and Veronesi [63] and Khanal et al. [64] pointed out that these methods assume adaptation is exogenously determined, despite evidence indicating its endogeneity. This oversight can lead to biased estimates and misinterpretation of findings, underscoring the necessity for more advanced approaches that consider the endogenous nature of adaptation decisions in agricultural contexts. Consequently, this study utilized endogeneity switching regression to accurately estimate the impact of climate change adaptation strategies on small-scale crop farmers in the area.

Endogeneity switching regression provides a significant advantage through its flexible model specification, allowing researchers to adaptively switch between different regression models based on whether specific variables are exogenous or endogenous, thus enhancing the accuracy of causal relationship estimates [65,66,67,68]. This approach directly addresses endogeneity concerns by incorporating instrumental variables or alternative methods to reduce the correlation between independent variables and the error term, which is essential for obtaining unbiased estimates. Additionally, endogeneity switching regression can achieve improved statistical efficiency when valid and exogenous instrumental variables are used, resulting in more precise parameter estimates compared to propensity score matching. The ability to dynamically adjust model specifications, directly address endogeneity, and enhance statistical efficiency highlights the robustness and effectiveness of endogeneity switching regression in empirical research. Consequently, this study favored endogeneity switching regression over propensity score matching due to its flexibility in model specification, its direct approach to addressing endogeneity issues, and its capacity to achieve greater statistical efficiency while avoiding the limitations inherent in propensity score matching. Although propensity score matching is simpler to implement and interpret, endogeneity switching regression offers a more rigorous methodology by adapting model specifications to accommodate the complexities of the data. Furthermore, while propensity score matching reduces selection bias and employs a non-parametric approach, endogeneity switching regression directly confronts endogeneity challenges and yields more statistically efficient parameter estimates, making it the preferred analytical framework for this study.

When estimating the impact of adaptation strategies on agricultural productivity and farm returns, endogeneity can arise from issues such as omitted variable bias, reverse causality, and measurement error. The fundamental concept of endogeneity switching regression is to address these issues by switching between different regression models depending on the exogeneity or endogeneity of specific variables. This method facilitates a more robust and reliable estimation of the causal relationship between adaptation strategies and agricultural outcomes. The endogeneity switching regression was implemented in two stages. The first stage focused on the adoption of adaptation strategies and the resulting effects of adapting to climate change. Initially, we used the logit selection model to estimate the factors influencing small-scale crop farmers’ adoption of adaptation strategies, accounting for interactions among these factors. In the second stage, we assessed the impact of each outcome variable, crop yield and farm returns (measured in kilograms per hectare and ZAR per hectare, respectively), by splitting the endogenous model into two dimensions. This study employed least-squares regression with selectivity correction terms to analyze the relationship between climate change adaptation strategies and these outcomes.

3.3.2. Selection of Adaptation Strategies to Climate Change

The initial model addresses the selection process for climate change adaptation, represented by a binary variable. A logit regression was employed to estimate the farmers’ choices regarding adaptation strategies. This model is appropriate since the dependent variable is binary or dichotomous, indicating whether a farmer has adopted a specific adaptation strategy (1 for yes, 0 for no) or whether their agricultural yield has increased compared to the previous season (1 for yes, 0 for no). The model specification focuses on a latent variable denoted as A*, which captures the expected benefits of choosing to adapt versus not adapting [65,68]. The formulation of this latent variable is as follows:

$$A_i^{\ast }=Z_{i\alpha }+{\mathrm{ŋ}}_i with A^{\ast }\left\{\begin{array}{c}1 if A_i>0\\ 0 otherwise\end{array}\right.$$

(1)

In a farm household, I will adopt adaptation strategies ($A_i^{\ast }=1$) in response to long-term changes in mean temperature and rainfall if A* > 0; 0 otherwise. Here, Z represents an n × m matrix of explanatory variables, α is an m × 1 vector of model parameters to be estimated, and ŋ is an n × 1 vector of normally distributed random error terms with a mean of zero.

3.3.3. Impact Assessment of Adaptation Strategies to Climate Change Conditions

The second stage focuses on the outcome equation, where crop yield (measured in kilograms per hectare) and farm returns (measured in Rands, or ZAR, per hectare) are used to separate the endogenous model into two distinct components [69]. This process involves implementing separate commands or production functions to analyze the decision-making of small-scale crop farmers regarding adaptation versus non-adaptation to climate change. This study assumes that the variables representing these outcomes follow a linear relationship with the explanatory factors, enabling an assessment of how adopting adaptation strategies to climate change affects crop yields and net farm returns. This linear specification is expressed as follows:

$$Y_i=X_{i\alpha }+y_i\phi +{\epsilon }_i$$

(2)

In this context, $Y_i$ represents the vector of outcome variables, including crop yield and net farm returns.

$X_i$ is the vector of explanatory variables, which encompasses factors such as age, education, family size, farm characteristics (e.g., farm size, location, and machinery), and soil types, as well as institutional and financial variables (e.g., access to extension services, climate information, and credit).

Additionally, $y_i$ is a dummy variable indicating adopting adaptation strategies. At the same time, α and $\phi$ are the parameters to be estimated, and εi represents the error term.

3.3.4. Estimation and Identification

Given this study’s reliance on survey data and the non-random selection of adaptation strategies, it is crucial to adopt an approach that effectively addresses selection bias. Therefore, this research utilized an Endogenous Switching Regression (E.S.R.) model to reduce selection bias resulting from both observable and unobservable heterogeneity in the sample, following the methodology proposed by previous studies [69]. This model is implemented in two stages: first, the decision-making process regarding adaptation adoption is analyzed as described in the selection equations [Equations (1) and (2)]; second, separate equations are formulated to represent the outcomes for both adopters and non-adopters.

$${\mathrm{C}\mathrm{o}\mathrm{m}\mathrm{m}\mathrm{a}\mathrm{n}\mathrm{d} 1 \mathrm{t}\mathrm{o} \mathrm{A}\mathrm{d}\mathrm{a}\mathrm{p}\mathrm{t} y}_{1i}=X_{1i}\beta +{\epsilon }_{1i} if A_i=1$$

(3)

$$\mathrm{C}\mathrm{o}\mathrm{m}\mathrm{m}\mathrm{a}\mathrm{n}\mathrm{d} 2 \mathrm{t}\mathrm{o} \mathrm{N}\mathrm{o}\mathrm{t} \mathrm{t}\mathrm{o} \mathrm{a}\mathrm{d}\mathrm{a}\mathrm{p}\mathrm{t} y_{2i}=X_{2i}\beta +{\epsilon }_{2i} if A_i=0$$

(4)

In this model,$y_{1i}$ and $y_{2i}$ represent crop yield and farm returns for adopters and non-adopters, measured in kilograms per hectare and Rands (ZAR) per hectare, respectively.

$X_i$ encompasses a set of explanatory variables that include inputs, climate variables, socio-economic factors, institutional characteristics, and farm attributes. The error terms ${\epsilon }_{1i}$ and ${\epsilon }_{2i}$ are the error terms for adopters and non-adopters, respectively.

In the context of this switching regression model, selection bias emerges in the error terms ε and ŋ. If the explanatory factors do not fully account for unobserved variables, a correlation exists between the error terms in the production and selection equations, expressed as corr (ϵ, η) ≠ 0. The error terms ŋi, ${\epsilon }_{1i}$, and ${\epsilon }_{2i}$ follow a trivariate normal distribution with a mean of zero, and the covariance matrix is defined as follows:

$$Cov(\mathrm{ŋ}\mathrm{i}, {\epsilon }_1 \mathrm{a}\mathrm{n}\mathrm{d} {\epsilon }_2)=\left\{\begin{array}{c}{\delta }_{\mathrm{ŋ}}^2 {\delta }_{1\mathrm{ŋ}} {\delta }_{2\mathrm{ŋ}}\\ {\delta }_{1\mathrm{ŋ}} {\delta }_1^2 .\\ {\delta }_{2\mathrm{ŋ}} . {\delta }_2^2 \end{array}\mid \right.,$$

(5)

where the variance of the error terms in the selection equation and the two production equations are represented by ${\delta }_{ŋ}^2,$δ12, and ${\delta }_2^2$, respectively. The covariance between the error term of the selection equation (${ŋ}_i$) and the production regimes 1 (${\epsilon }_{1i}$) and 2 (${\epsilon }_{2i}$) is denoted as ${\delta }_{1ŋ}$ and ${\delta }_{2ŋ}$, respectively. The notation (.) indicates that the outcomes from production regimes 1 and 2 cannot be observed simultaneously for a given farmer, resulting in an absence of covariance. In the presence of selection bias, the expected values of the error terms for the two regime equations are not equal to zero.

$$E[{\epsilon }_{1i}\mid A_i=1]={\delta }_{1\mathrm{ŋ}}{\displaystyle \frac{\mathrm{\varnothing }(Z_{i\alpha })}{\Phi (Z_{i\alpha })}}={\delta }_{1\mathrm{ŋ}}{\lambda }_{1i,}$$

(6)

$$E[{\epsilon }_{2i}\mid A_i=0]={-\delta }_{2\mathrm{ŋ}}{\displaystyle \frac{\mathrm{\varnothing }(Z_{i\alpha })}{1-\Phi (Z_{i\alpha })}}={\delta }_{2\mathrm{ŋ}}{\lambda }_{2i,}$$

(7)

where $\varnothing$(.) represents the standard normal probability, and Φ (.) denotes the standard normal cumulative distribution. The terms ${\lambda }_{1i}$ and ${\lambda }_{2i}$ are interpreted as inverse Mills ratios [70] and are included in the righthand side of the production equations to account for any selection bias. The correlation coefficients between the error terms of the production and selection equations are also indicated.

$${\rho }_1={\displaystyle \frac{{\delta }_{1\mathrm{ŋ}}^2}{{\delta }_{\mathrm{ŋ}}{\delta }_1}}$$

(8)

$${\rho }_2={\displaystyle \frac{{\delta }_{2\mathrm{ŋ}}^2}{{\delta }_{\mathrm{ŋ}}2}}$$

(9)

The significance of the estimated covariances ${\rho }_{1ŋ}$ and ${\rho }_{2ŋ}$ indicates that the decisions to adopt adaptation strategies, crop yield, and farm returns are correlated, thereby rejecting the null hypothesis of sample selectivity bias. This underscores the value of the endogenous switching model. In this context, the complete information maximum likelihood estimate offers an efficient output for the Endogenous Switching Regression (ESR), allowing for simultaneous estimation of both the selection and production equations. This approach is superior to two-step estimators, which tend to be inefficient for calculating standard errors.

3.3.5. The Treatment Effect of Adaptation Strategies

This study evaluates the impact of adaptation practices on productivity using an endogenous regression model, treating adapters as the treatment group ($A_i$ = 1), and estimating their counterfactual outcomes. The observed results for both adapters and non-adapters are detailed below:

$$\mathrm{A}\mathrm{d}\mathrm{a}\mathrm{p}\mathrm{t}\mathrm{e}\mathrm{r} E[y_{1i}\mid A_i=1]=X_{1i}{\beta }_1+{\delta }_{1\mathrm{ŋ}}{\lambda }_{1i,}$$

(10)

$$\mathrm{N}\mathrm{o}\mathrm{n}\text{-}\mathrm{a}\mathrm{d}\mathrm{a}\mathrm{p}\mathrm{t}\mathrm{e}\mathrm{r} E[y_{2i}\mid A_i=0]=X_{2i}{\beta }_2+{\delta }_{2\mathrm{ŋ}}{\lambda }_{2i,}$$

(11)

Similarly, the equation for the counterfactual yield and farm returns for both adapters and non-adapters is presented as follows:

$$\mathrm{A}\mathrm{d}\mathrm{a}\mathrm{p}\mathrm{t}\mathrm{e}\mathrm{r} \mathrm{c}\mathrm{o}\mathrm{u}\mathrm{n}\mathrm{t}\mathrm{e}\mathrm{r} \mathrm{f}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{u}\mathrm{a}\mathrm{l} E[y_{2i}\mid A_i=0]=X_{1i}{\beta }_2+{\delta }_{2\mathrm{ŋ}}{\lambda }_{1i,}$$

(12)

$$\mathrm{N}\mathrm{o}\mathrm{n}\text{-}\mathrm{a}\mathrm{d}\mathrm{a}\mathrm{p}\mathrm{t}\mathrm{e}\mathrm{r} \mathrm{c}\mathrm{o}\mathrm{u}\mathrm{n}\mathrm{t}\mathrm{e}\mathrm{r} \mathrm{f}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{u}\mathrm{a}\mathrm{l} E[y\mid A_i=0]=X_{2i}{\beta }_1+{\delta }_{1\mathrm{ŋ}}{\lambda }_{2i,}$$

(13)

Next, the average treatment effect on crop yield and farm returns for this group is calculated as follows:

$$\begin{gathered} \mathrm{A}\mathrm{T}\mathrm{T}=E[y_{1i}\mid A_i=1]-E[y_{2i}\mid A_i=1] \\ =X_{1i}{(\beta }_1-{\beta }_2)+({\delta }_{1\mathrm{ŋ}}{-{\delta }_{2\mathrm{ŋ}})\lambda }_{1i,} \end{gathered}$$

The estimated effect of adaptation on crop yield and farm returns for non-adopters (untreated) is:

$$\begin{gathered} \mathrm{A}\mathrm{T}\mathrm{U}=E[y_{1i}\mid A_i=0]-E[y_{2i}\mid A_i=0] \\ =X_{2i}{(\beta }_1-{\beta }_2)+({\delta }_{1\mathrm{ŋ}}{-{\delta }_{2\mathrm{ŋ}})\lambda }_{2i,} \end{gathered}$$

(14)

where ATT represents the average treatment effect for the treated group (adapters), while ATU refers to the average treatment effect for the untreated group (non-adapters). For the validity of the Endogenous Switching Regression (ESR) model, an exclusion restriction is required that is correlated with adaptation but does not directly influence the productivity of small-scale crop farmers. Consequently, this study employs a set of variables as selection instruments, specifically climate information and distance to market. These variables are considered instrumental because they are significant factors affecting the decision to adapt to climate change, as noted by various researchers. However, these variables do not directly determine farmers’ productivity or income levels. To empirically assess the validity of these instruments in the ESR model, the initial test involves using a logit model to analyze the adoption of adaptation strategies, incorporating both the instruments and other relevant variables. The analysis confirms that these instruments are indeed robust predictors of adaptation.

A distortion test is conducted to determine whether the instruments have a significant impact on production and return processes. This analysis indirectly assesses whether the instruments are correlated with unobservable factors. The results confirm that the instruments do not collectively exert a statistically significant influence on productivity and farm returns for non-adapters.

Several studies have yet to differentiate between adaptations motivated by climate considerations and those driven by other livelihood pressures. Identifying the most effective adaptations for mitigating the impacts of climate change remains essential [71]. Through surveys, common adaptation strategies in the study area were identified, including improved crop varieties, crop rotation, irrigation, crop diversification/mulching, soil and water conservation practices, application of organic fertilizers/mulching, planting drought-resistant crops, and adjusting planting dates. The selection equation employed a binary indicator as the dependent variable to indicate whether farmers utilized any of these adaptation strategies, while the outcome equation focused on yield per hectare and farm returns per hectare.

4. Findings and Discussion

4.1. Demographic Characteristics of Farmers

The demographic characteristics of smallholder farmers are crucial for understanding their profiles and backgrounds.

Table 1. Demographic characteristics of smallholder farmers.

Demographic Characteristics	Frequency	Percentage
Sex: Female	136	68
Access to extension services: 5 visits per month	128	64
Farm organization membership	132	66
Occupation: Farmer	140	70
Access to credit: yes	88	44
Source of income: grant and farming	128	64
Access to climate change information	144	72
Variable	Mean	Standard Deviation
Age	43.42	14.28
Family size	5.67
A year spent in school	11.43	9.25
Farm size (Ha)	2.85
Distance to market input/output (Km)	11.34	9.15
Household month income (ZAR)	4869.43	28.76

below presents the demographic data of the farmers involved in this study. The results indicate that women comprise the majority of the farming population, at 68%. This is not surprising, given that many men in the province migrate to urban areas for employment in the non-agricultural sector. These findings align with Nyang’au et al. [72] and Mdoda et al. [62] who suggest men have left to pursue quicker-paying jobs in cities, partly due to reduced landholding resulting from the land distribution framework. The average age of farmers in this study is 43 years, suggesting that most smallholder farmers are middle-aged and possess the physical stamina needed for agricultural work. This observation is consistent with the findings of Okello et al. [73] and Mdoda et al. [67], which indicate that the majority of smallholder farming in Africa is carried out by energetic middle-aged individuals who are willing to take risks for potentially high returns and are inclined to adopt technology to boost productivity and profits. This demographic benefits the study, as these farmers are familiar with innovative technologies that mitigate climate change and enhance productivity. Most farmers have completed secondary education, averaging 11 years of schooling. This level of education indicates literacy, which is vital for farmers as it aids in interpreting climate information, accessing resources, and employing innovative farming techniques. These findings are in line with those of Mdoda et al. [67], Amir et al. [74], Mutunga et al. [75], and Mujuru et al. [61], who emphasize that extending years of schooling is essential for enhancing farmers’ knowledge and skills. The average household size is six people, which is a proxy for family labor. This larger family size is beneficial, providing essential labor for farming activities. A large family enables farmers to rely on relatives for labor, increasing productivity and reducing transaction costs. The average monthly income, which includes social security and farm earnings, is ZAR 4869.43, an important figure for supporting farm operations and covering household expenses.

The average farm size in this study was 3 hectares, indicating that farming is primarily practiced on a small scale. This finding aligns with Mdoda et al. [60], who noted that agriculture in the Eastern Cape Province is predominantly small-scale. Among the smallholder farmers surveyed, 64% reported receiving extension services, with visits occurring five times a month. These services are vital, as they provide training on production and climate change adaptation, disseminate new agricultural techniques, and share important information about climate change and market trends. Additionally, 66% of farmers are members of farm organizations, which play a significant role in enhancing their knowledge about climate change and adaptation through training sessions held twice every two months. These organizations serve as platforms for farmers to exchange valuable information regarding climate issues, innovations, new crop varieties, and other relevant topics, ultimately strengthening their resilience. As full-time farmers, they are on-site daily, enabling them to stay informed about ongoing developments and the impacts of climate change, which enhances their understanding of the importance of adaptation. Consequently, farmers primarily rely on grants and farm returns for their income. While some farmers have access to credit, many do not, compelling them to depend on their household monthly income to sustain their farming operations. This aligns with the findings of Mdoda [5] and Mujuru et al. [61], who reported that most smallholder farmers in the Eastern Cape struggle to access credit due to high interest rates, relying instead on social grants and farm income for their livelihood. Distance poses another challenge for smallholder farmers, as many are in remote areas. On average, they must travel 11 km to access input and output markets or visit the Department of Agriculture, which results in high transaction costs. Nevertheless, farmers have access to climate change information, which is crucial for raising awareness and implementing adaptation measures among smallholder farmers in this study.

4.2. Smallholder Farmers’ Awareness of Climate Variability and Change in the Study Area

This section starts by checking whether smallholder farmers knew about the climate change phenomenon. The results indicating that 78% of smallholder farmers are aware of climate change are significant, suggesting that many recognize its impact on their livelihoods, which is crucial for adaptation and resilience strategies. However, while this awareness is a positive step, the 22% who are unaware represent a critical group to enhance their resilience to climate impacts. Figure 3 shows the farmers’ awareness level.

This section is essential for farmers, as it provides vital information about climate change and variability, enabling them to understand which adaptation strategies are necessary to mitigate these changes. Farmers informed about climate change are more likely to take prompt action and adopt effective adaptation measures. Smallholder farmers have reported experiencing significant changes in both rainfall and temperature. They have observed declining rainfall patterns, negatively affecting their agricultural productivity. These findings align with the research of Makamane et al. [76] and Nyang’au et al. [72], which indicate a substantial decrease in rainfall over the years, leading to detrimental impacts on agriculture. Farmers believe rainfall levels were more favorable in previous years and note that the rain now arrives much later in the season, disrupting the traditional plowing schedule. Additionally, the duration of the rainfall season has shortened, making it difficult for many farmers to plan effectively for their planting activities. The unpredictable nature of rainfall, combined with the reduced season length, complicates their farming efforts. Figure 4 illustrates the changes in rainfall patterns as experienced by smallholder farmers.

Conversely, smallholder farmers have also observed changes in temperature over the years. This study revealed that farmers have experienced an increase in temperatures by 78% compared to previous years, as illustrated in Figure 5. These findings are consistent with Mdoda [77], who reported similar trends among smallholder farmers in the Eastern Cape. Farmers further indicated that these temperature changes have had a detrimental effect on their agricultural practices.

The results presented in Figure 5 illustrate the prevalence of various natural disasters and extreme weather events in the study area. In the surveyed region, extreme weather events are distributed unevenly, with prolonged droughts being the most common, occurring at a rate of 42%. Droughts, characterized by significantly below-average precipitation, severely impact agriculture, water supplies, and ecosystems. These findings are consistent with those of Madamombe et al. [78] and Mdoda [5], who identified drought as the most frequent extreme weather event adversely affecting agricultural productivity. Strong winds follow closely behind, accounting for 20% of occurrences. These winds can damage structures, trees, and power lines, particularly in storm-prone areas of the Eastern Cape Province. Floods, although less common at 16%, still pose a significant risk, inundating land and causing harm to property and infrastructure and sometimes resulting in loss of life, especially in regions susceptible to heavy rainfall or near rivers and coastlines. Tornadoes, which make up 10% of occurrences, present a considerable threat with their powerful rotating columns of air that can cause widespread destruction. Additionally, hot seasons account for 12% of events, resulting in prolonged periods of unusually high temperatures that exacerbate drought conditions and increase the risk of heatwaves, dehydration, and wildfires—particularly affecting vulnerable populations with limited access to cooling resources. These findings highlight the diverse range of extreme weather events and the urgent need for comprehensive strategies to mitigate their impacts and enhance community resilience, especially among smallholder crop farmers.

Based on the presented data on rainfall, extreme weather events, and temperature changes, this study concludes that smallholder farmers in the area are acutely aware of, and have perceived shifts in, the climate over the years. These farmers contend that climate change has adversely affected their agricultural yields, diminishing farm returns. This aligns with the findings of Belay et al. [42] and Nyang’au et al. [72], who reported that climate change has led to decreased agricultural productivity, further compromising food availability and farm income. Such changes are among the most significant challenges faced by farmers and the province as a whole. Farmers have also reported increased pests and diseases, further complicating their agricultural efforts. They have also noted that the hot seasons and elevated temperatures have resulted in crop failures due to excessive heat. These findings are illustrated in Figure 6 below.

4.3. Effect of Climate Change in the Study Area

Smallholder farmers in this study are fully aware of climate variability and change. Based on their experiences, it is evident that climate change and variability have negatively impacted smallholder farmers in this study. Smallholder crop farmers have argued that climate change has reduced their agricultural produce, which has lessened their farm returns. These results agree with Belay et al. [42] and Nyang’au et al. [72] in that they show climate change has decreased agricultural productivity, reducing food availability and farm returns. These are the most noticeable changes that have hampered farmers and the province.

Reduced farm returns are critical to smallholder farmers and the broader agricultural economy. This reduction in farm returns limits farmers’ abilities to produce sufficient food for their families and communities, exacerbating food insecurity, especially where smallholder agriculture is prevalent. Additionally, smallholder farmers play a vital role in local economies, and decreased returns lead to diminished spending within their communities, negatively affecting local businesses and overall economic health. Persistent low returns can push farmers deeper into poverty, hindering their ability to invest in better practices, education, or healthcare. The study results revealed that climate change leads to agricultural yield variability, with declines in crop production caused by increased temperatures and shifting precipitation patterns, posing a substantial threat to food security for farmers who depend on consistent yields for their livelihoods. Climate change also facilitates the emergence of new pests and diseases, further challenging farmers who may need access to necessary pest management resources. Crop failure due to climate change is a pressing concern that poses significant threats to food security, farmer livelihoods, and agricultural sustainability. As climate patterns shift, smallholder farmers and agricultural systems face increasing challenges that can lead to reduced yields or complete crop loss. These results are shown in Figure 7 below.

4.4. Channels for Climate Information for Smallholder Crop Farmers

Smallholder crop farmers in the study area know climate change and its impacts. The findings indicate that these farmers receive climate information, enhancing their knowledge and understanding of necessary adaptations. The information they obtain primarily comes from weather forecasts. Figure 8 below illustrates the main channels smallholder crop farmers access climate information. These channels reflect the various methods by which farmers acquire critical climate insights essential for informed decision-making in their agricultural practices. Extension agents play a crucial role at the forefront, accounting for 40% of the information dissemination efforts by providing tailored guidance and resources through direct interactions and workshops. This channel has significantly aided farmers in understanding and responding to climate-related challenges, though its impact is limited due to various factors. Following closely is farmer-to-farmer knowledge sharing, which represents 24% and highlights the importance of peer exchanges in facilitating learning and adaptation to climate variability. Additionally, traditional media channels such as radio and television, comprising 14%, continue to be vital sources of climate information, offering timely updates, weather forecasts, and educational content that remains accessible even in remote rural areas.

Traditional radio remains the most widely used and relevant channel for many farmers due to its low resource requirements and the rural locations of their farms [79]. As mobile phone usage increases, particularly in developing regions, mobile technology now accounts for 12% of information dissemination. This technology provides platforms for delivering weather forecasts, agronomic advice, and market prices directly to farmers via text messages, voice calls, or smartphone applications. Additionally, research institutions and non-governmental organizations contribute 10% to disseminating climate information through studies, resource development, and training programs, which enhance farmers’ understanding of climate-related issues and promote climate-smart agricultural practices. By integrating these diverse channels, a comprehensive approach is created for delivering essential climate information, ultimately strengthening the resilience and livelihoods of smallholder farmers in the face of climate change challenges.

4.5. Adopted Coping Strategies by Smallholder Crop Farmers to Mitigate Climate Change Impact in the Study Area

Figure 9 presents the coping strategies employed by smallholder crop farmers in the study area, offering a detailed overview of the agricultural methods they use to tackle the challenges posed by climate change and enhance their resilience. One prominent strategy is the adoption of improved crop varieties, which account for 20% of practices. This approach helps increase productivity and adaptability to changing climatic conditions through drought tolerance and disease resistance. Additionally, adjusting planting schedules, representing 12% of strategies, has emerged as a vital tactic. This allows farmers to optimize growing conditions in response to altered climate patterns, thus reducing risks and maximizing yields. This adaptation has become particularly important as rainfall patterns have shifted, affecting farm preparation timelines [5,76].

Crop rotation, which accounts for 22% of the methods used, stands out as a fundamental practice for sustainable farming. It promotes soil health, pest control, and nutrient retention over time, making it particularly suitable for smallholder farmers due to its ease of implementation, requiring minimal knowledge and investment [62]. In addition to crop rotation, other strategies include planting drought-resistant varieties (10%), furrow irrigation (6%), applying organic fertilizers and mulching (12%), implementing soil and water conservation practices (8%), and engaging in crop diversification or intercropping (10%). Each approach offers distinct advantages, such as improved water efficiency, enhanced soil fertility, erosion control, and risk diversification. Collectively, these practices provide a comprehensive toolkit for strengthening agricultural resilience, optimizing resource use, and mitigating the effects of climate variability [47,72,80]. By adopting a tailored combination of these strategies that align with local conditions, farmers can effectively manage the challenges posed by climate change while sustaining and even improving agricultural productivity and sustainability for the future.

4.6. Determinants of Factors Influencing the Uptake of Coping Strategies by Smallholder Crop-Farmers

The logit regression model was employed to assess the factors influencing farmers’ decisions to adopt strategies for mitigating climate change, with the results summarized in

Table 2. Logit regression of factors influencing smallholder crop farmers’ uptake of coping strategies.

Explanatory Variables	Coef.	Std Error	Marginal Effect
Age	−0.0187 **	0.0092	0.042
Access to climatic information	1.4533 ***	0.2180	0.035
Years spent in school	1.3672 ***	0.2258	0.051
Knowledge about coping strategies	0.5786 ***	0.1275	0.019
Distance to the nearest market	−0.6091 **	0.3122	0.018
Access to agricultural extension services	0.4862 **	0.1417	0.062
Frequency of drought in 10 years	1.4183 ***	0.2072	0.029
Crop failure history (production shock experience)	0.7892 ***	0.2521	0.045
Perception of increase in temperature	2.3694 **	0.5641	0.052
Perecption of decrease in rainfall	−3.6851 ***	0.6621	0.039
Radio	0.3876 **	0.1982	0.041
Farm income	0.3276 **	0.1563	0.032
Family size	0.1919 **	0.0548	0.047
Farm size	−0.4655 ***	0.1268	0.038
Cons.	−0.4531 ***	0.1951	0.142
Observers = 200	R-square = 0.721	LR Chi-Square (16) = 127.21 Prob > Chi-Square = 0.000	Log-likelihood = −392.6929

Note: ** and *** represent significance levels at 5% and 1%, respectively.

. The analysis revealed significant insights into the determinants driving these decisions. The R-square value of 0.721 indicates that the variables included in the model account for approximately 72.1% of the variability in farmers’ adaptation choices. Additionally, the L.R. Chi-Square test yielded a value of 127.21 with a p-value of 0.000, suggesting that the model significantly differs from a null model, reinforcing its validity and reliability. The negative log-likelihood value of −392.6929 suggests a good fit of the model to the data, as it reflects the logarithm of the likelihood function evaluated at the estimated coefficients, with lower values indicating a better fit. These findings underscore the robustness of the regression model in identifying and elucidating the factors influencing farmers’ decisions to adapt to climate change. Such insights are invaluable for informing policy development and intervention strategies to enhance climate resilience within agricultural communities.

The coefficient for farmer’s age was negative and statistically significant at the 5% level, indicating a detrimental relationship between age and adopting adaptation strategies. Specifically, the negative coefficient reveals that as a farmer’s age increases by one year, their agricultural yields decline by approximately 0.0187 units, reflecting a reduced capacity to adapt. Older farmers tend to have lower adoption rates of new strategies than their younger counterparts, primarily due to their risk-averse nature and a diminished drive to improve yields. Additionally, they often have less physical strength to manage farm tasks effectively. This finding highlights a significant vulnerability among aging farmers in adapting to the evolving agricultural landscape. The marginal effect of 0.04 units further illustrates that agricultural yields decrease by about 0.042 units yearly as farmers age, irrespective of other factors. These results align with findings from Gebre et al. [81] and Jamshidi et al. [82], which indicate that older farmers are less likely to adopt adaptation strategies compared to younger farmers, who are more proactive in minimizing the impacts of climate change and enhancing productivity to improve their farm returns. Furthermore, farmers with higher levels of education generally exhibit greater awareness of climate change and agricultural innovations, making them more inclined to adopt new technologies and methods to tackle climate-related challenges.

Access to climatic information exhibited a positive coefficient and was statistically significant at the 1% level. This indicates that each additional channel through which farmers access climate data increases agricultural yields, enhancing their adaptive capacity by 1.4533 units. The positive relationship between access to climatic information reveals a critical insight: improved access significantly boosts agricultural productivity. This highlights the essential role of timely and accurate weather forecasts, climate projections, and related information in enabling farmers to make informed decisions about crop selection, optimal planting times, and risk management strategies. The marginal effect of 0.035 further emphasizes this importance, suggesting that each unit of enhanced access to climatic information increases by 0.035 units in agricultural productivity while controlling for other variables. These findings align with the research by Dhakal et al. [83] and Zakari et al. [84], which indicate that access to climate information improves farmers’ understanding of weather patterns and alerts them to potential changes, as well as informs them about recommended mitigation strategies to address climate change challenges.

The number of years spent in school had a positive coefficient and was statistically significant at the 1% level. This indicates that each additional year of education increases the likelihood of enhanced agricultural yields as farmers improve their knowledge and adaptive capacity by 1.3672 units. The positive correlation between years of education and agricultural productivity underscores a vital connection: more educated farmers tend to achieve higher yields. This improvement may stem from their greater ability to adopt modern farming techniques, understand market trends, and effectively access information resources. The marginal effect of 0.051 reinforces this relationship, indicating that each additional year of education significantly increases 0.051 units in agricultural productivity, holding all other variables constant. These findings align with research by Dhakal et al. [83], Ali and Erenstein [85], Jamshidi et al. [82], and Mdoda [77], which highlight the crucial role of education in enhancing farmers’ knowledge of innovative practices and adaptation strategies to climate change, ultimately aimed at boosting agricultural productivity.

Knowledge of coping strategies exhibited a positive coefficient and was statistically significant at the 1% level. This indicates that a 1% increase in farmers’ knowledge of these strategies leads to a corresponding rise in agricultural yields, with an improvement in adaptive capacity of 0.5786 units. The positive coefficient associated with knowledge of coping strategies reveals a crucial insight: farmers well-versed in adaptation techniques typically achieve higher agricultural outputs. This highlights the importance of equipping farmers with the necessary skills and resources to address climate variability, pest infestations, and other agricultural demands. The marginal effect of 0.019 further reinforces this point, suggesting that each additional enhancement in proficiency regarding coping strategies results in a noteworthy increase of 0.019 units in agricultural productivity while controlling for other variables.

The distance to the nearest market displayed a negative coefficient and was statistically significant at the 5% level. This indicates that for every additional kilometer a farmer must travel to access markets, agricultural yields decrease, with a corresponding decline in adaptive capacity of 0.6091 units. This negative coefficient highlights a crucial insight into agricultural dynamics: proximity to markets significantly influences yields. The findings emphasize the importance of market access in shaping farmers’ productivity. Specifically, agricultural yields tend to decline as the distance to the nearest market increases. Although the coefficient is negative, its impact is relatively small, as reflected by a marginal effect of 0.018. This suggests that each additional kilometer from the market results in an approximate decrease of 0.018 units in agricultural yields while controlling for other variables. This implies that farmers closer to markets may enjoy lower transportation costs, better product pricing, and improved access to inputs and information. In contrast, those situated further away may encounter logistical challenges, increased post-harvest losses, and limited market opportunities, which can adversely affect their productivity and profitability [83].

Access to agricultural extension services exhibited a positive coefficient and was statistically significant at the 5% level. This is expected, as extension services serve as intermediaries between research institutions and farmers. The findings indicate that a one-unit increase in farm visits and a 1% increase in access to extension services correlates with increased agricultural yields, enhancing farmers’ adaptive capacity by 0.4862 units. The positive coefficient suggests that greater access to agricultural extension services is linked to improved agricultural yields. These services are vital in disseminating technical knowledge, providing training and advisory support, and facilitating farmers’ adoption of new technologies. The marginal effect of 0.062 indicates that each additional unit of access to agricultural extension services results in a 0.062-unit increase in farm yields while controlling for other factors. These results align with Atube et al.‘s [86] findings, which state that access to agricultural extension services significantly boosts small-scale farmers’ likelihood of adopting climate change adaptation measures. This is due to farmers gaining exposure to up-to-date information and acquiring technical skills through these services, enhancing their readiness to adapt.

Farm income displayed a positive coefficient and was statistically significant at the 5% level. This indicates that a unit increase in farm income by ZAR 1 results in a rise in agricultural yields, enhancing farmers’ adaptive capacity by 0.3276 units. The positive coefficient suggests that higher farm income increases agricultural yields. Farmers with greater financial resources will likely have improved access to inputs, technologies, and services that boost productivity. The marginal effect of 0.032 indicates that for each unit increase in farm income, agricultural yields rise by approximately 0.032 units while controlling for all other factors.

Family size exhibited a positive coefficient and was statistically significant at the 5% level. This indicates that increasing one additional family member contributes to higher agricultural yields, enhancing farmers’ adaptive capacity by 0.1919 units. The positive coefficient suggests that larger family sizes correlate with increased agricultural productivity. This may be due to the availability of family labor for farm activities, enabling farmers to cultivate larger areas and achieve greater productivity. The marginal effect of 0.047 implies that each additional family member results in a 0.047-unit increase in agricultural yields while controlling for other factors. These findings align with the research of Kabubo-Mariara and Mulwa [87] and Ndamani and Watanabe [88], which indicate that larger family sizes facilitate adaptation to climate change by providing more available labor compared to smaller families.

The drought frequency over the past decade showed a positive coefficient and was statistically significant at the 1% level. This indicates that having faced drought conditions in the last ten years has improved farmers’ understanding of climate change and influenced their adaptation decisions. Specifically, a 1% increase in drought frequency correlates with an enhancement of 1.4183 units in agricultural yields due to increased knowledge and adaptive capacity. This strong relationship highlights that repeated exposure to drought amplifies farmers’ awareness of climate-related risks and emphasizes the need for adaptive strategies. Experiencing drought raises their perception of vulnerability and encourages a proactive stance in managing these challenges. As farmers become more aware of the immediate impacts of water scarcity on their livelihoods, they are more likely to adopt crop diversification, irrigation, organic fertilizer application, and adjust planting dates to boost their resilience. The marginal effect of 0.029 further illustrates this importance, indicating that each additional unit of drought frequency contributes to an increase of 0.029 units in agricultural productivity while controlling for other factors. These findings align with the work of Asrat and Siman [18].

Crop failure (experience of production shocks) was associated with a positive coefficient and was statistically significant at the 1% level. This indicates that a 1% increase in crop failure experienced by farmers leads to an improvement of 0.7892 units in agricultural yields, as it enhances their knowledge and adaptive capacity. Farmers who have faced crop failures are more likely to adopt coping strategies, highlighting the significant role of personal experience in agricultural decision-making. When confronted with the devastating impacts of crop failure, farmers become acutely aware of the risks tied to their farming practices and the unpredictability of climate conditions. These past failures are vital learning opportunities, prompting them to seek and implement adaptive strategies, such as investing in drought-resistant crops or adopting irrigation techniques. This proactive behaviour demonstrates how firsthand experiences shape their understanding of potential threats and motivate them to strengthen their resilience against future uncertainties. Therefore, recognizing the importance of crop failure history in shaping farmers’ coping strategies underscores the need for policies and programs that leverage these experiential insights to foster adaptive agricultural practices. The marginal effect of 0.045 further emphasizes this point, indicating that each additional unit of crop failure experience correlates with an increase of 0.045 units in agricultural productivity while controlling for other variables. Prior research suggests that an individual’s inclination to take proactive measures in response to natural hazards increases with the severity of the damage they have experienced [17,89].

The perception of rising temperatures had a positive coefficient and was statistically significant at the 5% level. This indicates that a unit increase in the perception of temperature rises enhances the likelihood of farmers adapting to climate change, increasing 2.3694 units in agricultural yields. This strong correlation suggests that perceived risks serve as a significant motivator for farmers to modify their practices in response to climate change. When farmers acknowledge the effects of rising temperatures on their crops and overall agricultural viability, they are more inclined to take proactive measures to mitigate these impacts. This could include selecting heat-resistant crop varieties, adjusting planting schedules, or implementing water-efficient irrigation methods. Increased awareness of the challenges posed by rising temperatures influences their immediate agricultural decisions and fosters a long-term commitment to resilience and sustainability. Consequently, the substantial impact of temperature perception on adaptation strategies highlights the importance of effective communication and education regarding climate change, empowering farmers to make informed choices that protect their livelihoods in a progressively challenging environment. The marginal effect of 0.052 further emphasizes this point, indicating that each additional unit of perceived temperature increase corresponds to an approximate rise of 0.052 units in agricultural productivity while controlling for other variables. These findings align with Ceci et al. [90], who assert that awareness of climate variations, particularly in relation to historical trends, is essential in shaping adaptation strategies and positively influencing the livelihoods of households.

The perception of decreased rainfall had a negative coefficient and was statistically significant at the 1% level. This indicates that a 1% increase in the perception of declining rainfall reduces agricultural yields, as farmers’ adaptive capacity decreases by 3.6851 units. This strong negative correlation suggests that when farmers observe a drop in rainfall, it may foster feelings of hopelessness or resignation, ultimately discouraging proactive adaptive behaviours. Rather than actively seeking solutions to mitigate the impacts of reduced water availability, these farmers may become resigned to their circumstances, viewing their situation as beyond their control. This mindset can hinder their willingness to explore alternative farming practices, thereby increasing their vulnerability to climate change. The perception of diminishing rainfall reduces motivation to adapt and perpetuates a cycle of inaction that could jeopardize their long-term livelihoods. Understanding this psychological barrier is crucial for developing effective interventions that promote resilience among farmers confronting the harsh realities of climate variability, emphasizing the need for support systems that inspire hope and empower adaptation to changing environmental conditions. Although the coefficient is negative, the magnitude of this effect is relatively small yet significant, as demonstrated by the marginal effect of 0.039. This suggests that for each unit increase in the perception of decreasing rainfall patterns, agricultural yields decline by approximately 0.039 units, holding all other variables constant. These findings are consistent with the work of Asrat and Simane [18].

Radio ownership had a positive coefficient and was statistically significant at the 5% level. This indicates that a 1% increase in farmers owning radios enhances their agricultural yields by improving their knowledge and adaptive capacity by 0.3876 units. Radio ownership significantly contributes to farmers’ adoption of coping strategies, highlighting the essential role of media in raising awareness about climate-related challenges and potential adaptive measures. Radio broadcasts empower farmers to make informed decisions regarding their agricultural practices by providing timely and relevant information. For example, farmers can learn about innovative techniques, market trends, and weather forecasts to better anticipate and respond to adverse conditions. Additionally, radio is an accessible platform for disseminating knowledge, particularly in rural areas where literacy levels may vary and access to other information sources may be limited. The influence of radio ownership on the uptake of coping strategies underscores its importance as an educational resource. It demonstrates how effective communication can cultivate a culture of resilience among farmers. Therefore, leveraging radio as a medium for information dissemination is crucial for equipping farmers with the tools they need to navigate the uncertainties posed by climate change, ultimately enhancing their adaptive capacity and sustainability. The marginal effect of 0.041 further emphasizes this significance, indicating that each additional unit of radio ownership results in a commendable increase of 0.041 units in agricultural productivity, holding all other variables constant. This finding aligns with the research of Adeboa and Anang [14] and Thinda et al. [13], who suggest that access to information through media channels like radio facilitates the adoption of coping strategies, ultimately leading to improved agricultural yields.

Farm size exhibited a negative coefficient and was statistically significant at the 1% level. This indicates that an increase of 1 hectare in farm size is associated with a decrease in agricultural yields, reducing farmers’ adaptive capacity by 0.4655 units. The negative coefficient for farm size suggests that larger farms tend to yield lower agricultural outputs. These findings challenge conventional assumptions and point to possible inefficiencies or resource constraints linked to larger-scale farming operations. The marginal effect of −0.038 indicates that agricultural yields decrease by approximately 0.038 units for each additional hectare while holding other variables constant. These results contradict the findings of Ali and Erenstein [85], Sigigaba et al. [91], and Kabubo-Mariara and Mulwa [87], who identified a positive relationship between farm size and technology adoption, particularly in the context of adaptation strategies aimed at enhancing agricultural productivity. However, they align with the conclusions of Asrat and Simane [18] and Zakari et al. [84], which indicate that smaller farm sizes negatively impact the willingness of small-scale farmers to adopt adaptation strategies.

4.7. Impact of Adopting Coping Strategies on Farm Returns of Smallholder Crop Farmers

The impact of adaptation strategies on small-scale crop farmers was analyzed using Average Treatment Effects and Average Treatment on the Treated with endogenous treatment effects. The estimates for ATE and ATT were derived after fitting the model to account for these endogenous factors. The findings are summarized in

Table 3. ATE and ATT of adaptation strategies on crop yield and farm income severity.

Agricultural Yields	ATE		ATT
	Mean	SD	Mean	SD
Crop yields (Kg/ha)	8.379	5.311 **	9.625	6.153 **
Farm income (ZAR/ha)	1893	0.423 **	2652	0.578 **

Note: ** p < 0.05, respectively.

. These results provide compelling evidence regarding the effects of adopted adaptation strategies on small-scale crop farmers, particularly crop yields and farm income. Specifically, the Average Treatment Effect (A.T.E.) indicates a mean increase of 8.379 Kg per hectare in crop yields. This suggests that, on average, farmers who implement adaptation strategies experience a significant improvement in crop yields compared to those who do not adopt such measures.

Additionally, the Average Treatment Effect on the Treated (ATT) indicates an even greater mean increase of 9.625 Kg per hectare in crop yields for farmers who actively adopt adaptation strategies. This suggests that these strategies are particularly beneficial for those who implement them. This finding aligns with the research of Adego et al. [65] and Bedeke et al. [92], demonstrating that farmers who adopt adaptation strategies achieve higher crop yields than those who do not. Regarding farm income, the ATE shows a mean increase of ZAR 1893 per hectare, reflecting a significant improvement in income for farmers who implement these strategies compared to non-adopters. In contrast, the ATT reveals a much higher mean increase of ZAR 2652 per hectare among farmers who adopt adaptation strategies, highlighting the substantial impact of these strategies on enhancing income for those who implement them. This finding is consistent with Dhakal et al. [83], who indicates that adaptation decisions made by farmers in response to climate change lead to higher crop revenues for small-scale farmers than those who do not adapt.

These results highlight the importance of adopting adaptation strategies in improving smallholder farmers’ crop yields and farm income. The higher mean values for the ATE and ATT, regarding crop yields and income, indicate that implementing adaptation strategies leads to significant improvements, particularly for those actively engaging with these strategies. However, the observed differences between the ATE and ATT suggest that, while adaptation strategies have a positive overall impact, their effectiveness may vary among small-scale farmers. Factors contributing to this variation include the strategies implemented, the specific conditions of individual farms, farmers’ experience, the degree of implementation, and adherence to the strategies. Thus, these findings emphasize the need to promote and support effective adaptation strategies among small-scale farmers to enhance their resilience and economic sustainability.

4.8. Significant Implications for Food Security from the Adopted Coping Strategies by Smallholder Crop Farmers to Mitigate Climate Change

The coping strategies adopted by smallholder crop farmers to mitigate climate change have significant implications for food security. These strategies, such as improved crop variety, diversifying crops, crop rotation, and implementing irrigation techniques, enhance resilience and stabilize yields despite climate variability. Farmers can ensure consistent food availability and access for their communities by improving agricultural productivity and reducing losses to enhance utilization and stability. Ultimately, these adaptive measures support farmers’ livelihoods and contribute to broader food security goals in the face of climate challenges.

4.8.1. Enhanced Agricultural Productivity

Adopting improved crop varieties (20%) and crop rotation (22%), among other innovative strategies, reflects a proactive and adaptive approach by smallholder farmers to enhance agricultural productivity amidst the pressing challenges of climate change. By selecting crop varieties that are more resilient to drought and pests, farmers can significantly bolster their yields, which is essential for ensuring a stable food supply. Additionally, crop rotation fosters soil health by preventing nutrient depletion, managing pest populations, and reducing the risk of crop failure, thereby contributing to consistent production levels. This dual strategy increases the quantity of food available and enhances its nutritional quality, making it a cornerstone of food security. As farmers navigate the complexities of a changing climate, these practices become increasingly vital; higher agricultural productivity directly translates to greater food availability and accessibility for communities, ultimately supporting broader economic stability and reducing vulnerability to food shortages. Fostering such adaptive agricultural practices is critical for sustaining food security amid ongoing environmental uncertainties and the growing population in the world.

4.8.2. Enhancing Resilience Through Adaptation Strategies and Support Systems

The awareness of climate variability among farmers is vital for implementing effective adaptation strategies to enhance resilience and productivity. With appropriate training and resources, farmers can adopt climate-smart agricultural practices that better equip them to navigate changing conditions. Improved access to climate information and support from extension agents empowers farmers to make informed decisions, thereby contributing to improved food security. Moreover, the various channels through which farmers receive this critical information underscore the necessity of robust communication and support systems. Strengthening these channels, especially extension services and peer-to-peer networks, facilitates the timely dissemination of vital knowledge. Building resilience within farming communities also necessitates supportive policies at regional and national levels to address climate change challenges. Investments in infrastructure, sustainable agricultural practices, and social safety nets are essential to bolster the capacity of smallholder farmers to cope with climate-related risks, ensuring long-term food security and community stability.

4.8.3. Resilience and Sustainable Practices to Climate Change

Farmers’ strategies, including altering planting schedules and utilizing drought-resistant varieties, significantly enhance their resilience against climate variability and related shocks. By adapting to changing weather patterns, these farmers can ensure consistent food production, which is crucial for food security. Moreover, their commitment to sustainable practices, such as applying organic fertilizers and soil conservation techniques, accounting for 20% of their strategies, promotes long-term agricultural health and environmental sustainability. These sustainable methods not only help maintain soil fertility and prevent degradation, but also secure the viability of future food production. Together, these adaptive and sustainable approaches form a robust framework that safeguards current agricultural outputs and ensures resilience against ongoing and future climate challenges, thereby reinforcing the foundation of food security in their communities.

4.8.4. Economic Impacts and Health Risks of Climate Change on Smallholder Farmers

The decline in agricultural productivity due to climate change has severe economic implications for smallholder farmers, reducing farm income and negatively impacting their livelihoods. Lower farm returns diminish purchasing power, making it increasingly challenging for families to access adequate food, exacerbating poverty and food insecurity, especially among vulnerable populations. Furthermore, climate change contributes to the rising prevalence of pests and diseases, further threatening crop yields and food quality. This not only jeopardizes food availability but also diminishes the nutritional value of the produce, increasing the risk of health complications and malnutrition within farming communities. Collectively, these factors underscore the urgent need for targeted interventions to bolster the resilience of smallholder farmers and ensure food security in the face of ongoing climate challenges.

4.8.5. Economic Returns from Adaptation

The significant increases in crop yields and farm income, averaging 8.379 units in yields and 1893 units in income, underscore the profound impact of adopting adaptation strategies on both food production and the economic viability of farming. These enhancements reflect improved agricultural outputs and demonstrate that when farmers successfully implement adaptive practices, they can achieve greater financial stability. Such economic returns are crucial, as they incentivize further investment in sustainable agricultural methods, creating a positive feedback circle that bolsters productivity and resilience. Farmers are better positioned to continue implementing environmentally sound practices by securing their economic future and reinforcing food security for their communities. This symbiotic relationship between economic returns and sustainable practices is essential for fostering a resilient agricultural system capable of navigating the complexities of a changing climate while ensuring an adequate food supply for future generations.

5. Conclusions and Recommendation

This study profiles smallholder farmers in the Eastern Cape, highlighting the role of demographics, climate change awareness, and adaptation strategies on their ability to cope with climate challenges. The majority of farmers are middle-aged (average age 43), predominantly female (68%), and well-educated (average of 11 years of schooling). They are aware of climate change, especially its impacts on rainfall, temperatures, and extreme weather events like droughts. Most farmers adopt adaptive strategies such as crop rotation and drought-resistant crops but face challenges like limited access to credit, remote locations, and fluctuating yields due to climate variability. Climate change already negatively impacts agricultural productivity, threatening food security and livelihoods. Farm income, family size, and personal experience with climate shocks affect farmers’ adaptive capacity. Those with higher incomes and larger families are better equipped to adapt, while direct experience with climate events motivates proactive strategies. However, perceived declines in rainfall create psychological barriers to adaptation. In conclusion, while smallholder farmers in the Eastern Cape are resilient and adopt strategies to maintain food security, they need more support to manage climate risks and improve agricultural productivity effectively. Smallholder farmers in the Eastern Cape are resilient but need more support to fully adapt to climate change. Key recommendations include improving access to credit, providing subsidies for drought-resistant seeds and irrigation, and expanding extension services. Gender-sensitive policies and addressing psychological barriers, such as concerns over declining rainfall, are also important. Investments in rural infrastructure, climate information via mobile and radio, and community-based training will help farmers adapt. Supporting farmer cooperatives and engaging youth are crucial for the region’s long-term sustainability and economic stability.