This study aims to assess community awareness, perceived impacts and adaptation strategies to climate change in Liben Chukala District, Ethiopia, focusing on the vulnerabilities of subsistence-farming households and identifying measures to strengthen local resilience.
Data were collected from 167 households selected using a multi-stage sampling technique. Quantitative analyses, including descriptive and inferential statistics, were conducted using SPSS 22 to examine levels of awareness, perceived climate impacts, coping mechanisms and adoption of adaptation strategies.
Results indicated that 64.1% of farmers were aware of climate change, whereas 35.9% lacked a clear understanding. Over the past 30 years, erratic rainfall, rising temperatures and recurrent droughts have negatively affected crop and livestock productivity. Key impacts include drought (41.9%), pests and diseases (27.5%), poverty (20.4%), severe soil erosion (77.2%), forest loss (72.5%) and water scarcity (83.8%), with women and children identified as the most vulnerable. Farmers’ coping strategies – such as asset sales (25%), borrowing money (21.6%), meal reduction (11.4%), firewood/charcoal sales, seasonal migration and wage labor – help short-term survival but often increase long-term risk. Adaptation measures adopted include crop diversification (85.6%), drought-tolerant varieties (71.3%), soil and water conservation (79.6%), livestock management (47.9%) and agroforestry (48.5%), although adoption is limited by land and resource constraints.
This study provides comprehensive empirical evidence on climate change awareness, impacts and adaptation strategies at the district level in Ethiopia. The findings highlight the need for targeted interventions, including expanding irrigation infrastructure and improving access to credit and essential inputs, to enhance the resilience of smallholder farming communities.
1. Introduction
Climate refers to the long-term patterns of atmospheric conditions in a specific area, expressed through averages and extremes of weather elements (Allen and Breshears, 1998; Dixon et al., 2020; Suberi, 2022). Climate change, marked by shifts in these patterns, has emerged as a global concern due to its wide-ranging impacts on ecosystems, economies and human well-being.
In sub-Saharan Africa, climate change intensifies existing vulnerabilities, exacerbating poverty, food insecurity and hunger (von Braun, 2020; Mekonnen et al., 2021). Its impacts are particularly severe in developing countries, where populations depend heavily on climate-sensitive sectors such as agriculture. Among these, Ethiopia stands out as one of the most climate-vulnerable nations in Africa due to its reliance on rain-fed agriculture. Climate extremes – especially droughts and floods – have reduced agricultural productivity, contributing to food insecurity, poverty and population displacement. However, limited awareness among rural communities about climate change and its impacts continues to hinder effective adaptation.
Although scientific and local knowledge systems differ in framing climate change, both play crucial roles in shaping adaptive strategies (Nguyen et al., 2021; Demem, 2023). Public perceptions are often influenced by socio-cultural contexts rather than scientific evidence, potentially constraining climate action unless supported through education and awareness programs (Howe et al., 2019; Mekonnen et al., 2021). In rural Ethiopia, an insufficient understanding of climate dynamics weakens communities’ capacity to respond proactively to environmental challenges.
Empirical evidence across Ethiopia shows that rural households and pastoralists recognize changes in rainfall and temperature, though awareness varies by education level, access to extension services and agro-ecological zone (Gemeda et al., 2023). Many communities report decreased and erratic rainfall, delayed onset of rains, more frequent droughts and occasional floods – leading to reduced yields, livestock mortality, food insecurity and health risks. These perceptions generally align with meteorological data and national assessments (Teku, 2025). National and sectoral reports further estimate significant agricultural and GDP losses from climate extremes, projecting that poverty risks will escalate if adaptation remains inadequate.
Recent studies, including the Ethiopia Country Climate and Development Report, highlight increasing economic exposure and population vulnerability to droughts and floods (Food and Agriculture Organization of the United Nations, 2024; World Bank Group, 2024). Common adaptation measures include crop diversification, use of early-maturing varieties, soil and water conservation, small-scale irrigation, livelihood diversification (such as petty trade and migration) and rangeland management among pastoralists (Feyissa et al., 2025; Tamire et al., 2025; Teklay et al., 2025). However, adoption levels remain uneven due to financial constraints, insecure land tenure, limited access to technologies, inadequate information and institutional weaknesses. Ethiopia’s Nationally Determined Contributions and related national strategies acknowledge these barriers, emphasizing the need to strengthen extension services, early-warning systems, microfinance access and market linkages (Alhassan and Ahmad, 2025; United Nations Development Programme, 2025).
Against this backdrop, Liben Chukala District represents a microcosm of Ethiopia’s climate vulnerability. The district frequently experiences droughts, erratic rainfall and water scarcity that threaten agricultural productivity and rural livelihoods. Consequently, assessing farmers’ awareness, perceptions and adaptive responses to climate change is essential to inform context-specific adaptation strategies.
Community engagement is pivotal in studying climate change awareness and adaptation in Liben Chukala District because climate impacts are locally manifested and best understood by those directly affected. Engaging communities enables researchers to document local knowledge, perceptions and indigenous adaptation practices, ensuring that findings are contextually relevant and actionable (Lambebo et al., 2025). In Liben Chukala, where socioeconomic and agro-ecological conditions vary widely, residents possess valuable insights about long-term environmental changes, coping practices and traditional adaptation mechanisms (Haji and Bakuza, 2023). Their participation enhances the social relevance and empirical validity of research (Assefa, 2024) and fosters trust and ownership, thereby increasing the likelihood that proposed adaptation measures will be accepted and implemented at the grassroots level (Bedada et al., 2025).
This study has some limitations that should be acknowledged. First, it focuses on Liben Chukala District, which may limit the generalizability of findings to other regions with different agro-ecological contexts. Second, the cross-sectional design captures farmers’ awareness and adaptation strategies at a single point in time, preventing analysis of seasonal or long-term changes. Third, resource and time constraints limited the sample size and excluded complementary methods such as longitudinal tracking or crop yield measurement. Finally, the study primarily considers farmers’ perspectives without systematically incorporating those of policymakers or extension agents, which might have provided a broader institutional perspective.
Unlike previous studies conducted at regional or national scales, this research offers localized evidence from Liben Chukala District – a highly climate-vulnerable area with limited prior documentation. Its novelty lies in integrating assessments of farmers’ awareness, perceptions of climate risks and adaptation practices. By doing so, the study contributes new insights into the relationship between community awareness and adaptive behavior in rural Ethiopia.
2. Materials and methods
2.1 Theoretical framework
This study adopts an integrated theoretical framework that combines Protection Motivation Theory (PMT) and the Sustainable Livelihoods Framework (SLF) to explain how community awareness and perceived impacts of climate change influence local adaptation strategies in Liben Chukala District.
The PMT, originally proposed by Rogers (1975), posits that protective behavior results from two cognitive appraisal processes: threat appraisal – perceived severity and vulnerability – and coping appraisal – perceived response efficacy, self-efficacy and response cost. When individuals perceive a threat as severe and feel vulnerable, they are motivated to act, especially if they believe their response will be effective and manageable.
In the context of smallholder farmers and pastoralists, PMT provides a robust theoretical lens for explaining behavioral adaptation to climate variability. Farmers with high awareness of climate change and strong perceptions of its negative effects are more likely to experience higher threat appraisal and, when supported by strong coping appraisal, are more inclined to adopt adaptive strategies such as water harvesting, crop diversification, agroforestry and improved soil management (Ologunde and Matthew, 2024; Kim and Noh, 2025).
Recent empirical research confirms that PMT variables – perceived severity, vulnerability, response efficacy and self-efficacy – are significant predictors of adaptation intention and behavioral response among smallholder farmers (Bagagnan et al., 2019). Studies in Ethiopia and other African contexts have demonstrated that PMT-based constructs effectively capture how perception and awareness shape adaptation behavior, supporting its application to climate-change research in developing countries (Ayal and Leal Filho, 2017; Regasa and Akirso, 2019).
The Sustainable Livelihoods Framework (DFID, 1999; Scoones, 2015) complements PMT by embedding individual motivation within the broader socio-economic and institutional environment. The SLF identifies five core livelihood capitals – human, social, natural, physical and financial – that determine people’s ability to respond to shocks, trends and seasonal stresses (Natarajan et al., 2022; Vercillo, 2016).
This framework is particularly relevant for climate-vulnerable rural communities, as it explains differences in households’ adaptive capacity and resilience (Hailu et al., 2024; Getnet et al., 2025). Even when individuals are motivated to adapt (as explained by PMT), their actions are constrained or enabled by the availability of livelihood assets, access to credit and markets and institutional support such as agricultural extension and climate-information services (Tesfamariam et al., 2024). Recent applications of the SLF in Ethiopia and other dryland regions underscore its utility for understanding how asset endowment and governance quality influence adaptation outcomes (Maru et al., 2021; Tofu et al., 2023).
2.2 Data sources and types
This study used both primary and secondary data. Primary data were gathered through household surveys, key informant interviews, focus group discussions and field observations. Secondary sources included government climate and agricultural reports, peer-reviewed literature and unpublished academic studies from local institutions.
2.3 Research design and approach
The convergent parallel mixed methods approach was employed in this study to obtain a comprehensive understanding of community awareness, perceived impacts and local adaptation strategies to climate change in Liben Chukala District, Ethiopia. This design was appropriate because it allowed the researcher to collect quantitative and qualitative data simultaneously, analyze them independently and then integrate the findings during interpretation. The quantitative component provided measurable evidence on the levels of awareness, perceived risks and adoption of adaptation practices among smallholder farmers, while the qualitative component captured deeper insights into local perceptions, motivations and contextual barriers influencing adaptation decisions. Moreover, the approach helped reconcile potential discrepancies between what farmers reported in surveys and what was revealed in interviews, focus group discussions and field observations. Overall, the convergent parallel design enabled a more holistic and nuanced understanding of climate change adaptation processes – an area shaped by both measurable socio-economic factors and complex socio-cultural perceptions.
2.4 Sample size and sampling technique
A multi-stage sampling technique was used to select representative households. First, Liben Chukala District was purposively selected for this study because it represents one of the areas in Ethiopia highly affected by climate variability and recurrent droughts. The district lies within the semi-arid agro-ecological zone of the East Shewa Zone, Oromia Region, where rainfall is erratic, unevenly distributed and highly variable both spatially and temporally. According to regional meteorological data (Gashaw et al., 2023), the district has experienced increasing temperature trends and declining rainfall over the past two decades. Furthermore, Liben Chukala is predominantly dependent on rain-fed agriculture and livestock rearing, making its population particularly vulnerable to the impacts of climate change. The district also exhibits diverse topographic and socio-economic conditions, which provide a useful microcosm for studying community awareness, perceived impacts and local adaptation strategies. Previous research (Gemeda et al., 2023; Teku, 2025; World Bank Group, 2024) highlights that such drought-prone highland and lowland interface areas are critical for understanding rural adaptive behavior in Ethiopia.
Then, two kebeles – Kongo and Dire Doti – were purposively selected to ensure the study captures diverse agro-climatic conditions and climate-related challenges within the district. These kebeles differ in rainfall patterns, soil types and exposure to hazards such as drought and erratic rainfall, which allows the study to reflect variations in farmers’ experiences, perceptions and adaptation strategies. Using Cochran’s (1979) formula at a 93% confidence level and 7% precision, a sample of 167 households was drawn proportionally from a total population of 1,655 households. Finally, respondents’ households were selected using a simple random sampling technique.
2.5 Data collection methods and tools
Data were collected through a mixed-methods approach combining semi-structured questionnaires, key informant interviews, focus group discussions and field observations. This approach was chosen because it enables triangulation of data sources, providing both quantitative breadth and qualitative depth. Semi-structured questionnaires (pre-tested on 10 households for clarity) allowed us to capture comparable, measurable data, while key informant interviews and focus group discussions – guided by structured checklists – offered rich contextual insights and helped validate household responses. Field observations further strengthened the analysis by documenting real-time practices and environmental conditions.
2.6 Data analysis
Descriptive statistics summarized respondents’ socio-demographic profiles, awareness levels and perceived climate change impacts. One-sample t-tests were used to assess the significance of variables such as family size, landholding, farming experience and tropical livestock units (TLU).
3. Results and discussions
3.1 Socio-Demographic characteristics of respondents
As depicted in Table 1, about 31.1% of the household heads are between 20 and 35 years of age, while those aged between 36 and 50 years account for 47.3%, those aged between 51 and 65 years account for 16.2% and those above 66 comprise about 5.4%. This implies that the majority of the respondents are adults and above average. According to Santrock (2011), age group categorization from 20 to 40 young, 41–60 adults and >60 are elders. In this regard, the age distribution of the respondents ranged from 25 to 65 years and the average age was 48 years. In terms of religious composition, 46.1% of the survey households are adherents of Orthodox Christianity, 28.7% are Protestant and 18.6% are Wakefata. As indicated in Table 1, most of the respondents are Orthodox Christianity, while a few are Muslim (6.6%) followers.
Age, religion and educational status of survey household heads (n = 167)
| Variable category | Frequency | % |
|---|---|---|
| Age category | ||
| Between 20 and 35 | 52 | 31.1 |
| Between 36 and 50 | 79 | 47.3 |
| Between 51 and 65 | 27 | 16.2 |
| Above 66 | 9 | 5.4 |
| Religion | ||
| Orthodox | 77 | 46.1 |
| Muslim | 11 | 6.6 |
| Protestant | 48 | 28.7 |
| Wakefata | 31 | 18.6 |
| Educational status | ||
| Illiterate | 76 | 45.5 |
| Read and write | 35 | 21.0 |
| Primary education completed | 31 | 18.6 |
| High school completed | 21 | 12.6 |
| Higher education completed | 4 | 2.4 |
| Variable category | Frequency | % |
|---|---|---|
| Age category | ||
| Between 20 and 35 | 52 | 31.1 |
| Between 36 and 50 | 79 | 47.3 |
| Between 51 and 65 | 27 | 16.2 |
| Above 66 | 9 | 5.4 |
| Religion | ||
| Orthodox | 77 | 46.1 |
| Muslim | 11 | 6.6 |
| Protestant | 48 | 28.7 |
| Wakefata | 31 | 18.6 |
| Educational status | ||
| Illiterate | 76 | 45.5 |
| Read and write | 35 | 21.0 |
| Primary education completed | 31 | 18.6 |
| High school completed | 21 | 12.6 |
| Higher education completed | 4 | 2.4 |
In terms of education status, 45.5% household respondents were illiterate (cannot read and write), 21% can read and write, 18.6% are complete primary school, 12.6% are completed high school and 2.4% are completed higher education (who have a diploma and level). This implies that the majority of respondent households are uneducated. However, it is theorized that farmers with higher levels of education are more likely to adapt better to climate change due to the fact that educated persons are associated with access to information on improved technologies, higher productivity and adaptation to climate change (Deressa et al., 2009). Illiteracy may aggravate the vulnerability of farm households and communities to climatic and other natural shocks and reduce their coping capacity.
From the total household heads included in the sampling, 27 (16.2%) were female-headed and 140 (83.8%) were male-headed households (Figure 1). This implies that most of the households in the study area are male. This indicates that male-headed households are more likely to take up climate change adaptation methods because men may have access to information, land and the ability to use various management and farming practices than women (Nhemachena and Hassan, 2007).
The chart shows a comparison of male and female data using two measures: frequency and percentage. In the frequency section, the male value is 140 and the female value is 27. In the percentage section, the male value is 83.8 percent and the female value is 16.2 percent. The chart presents both measures side by side to compare the distribution between the two groups.Sex of household heads
Source: Authors’ own work
The chart shows a comparison of male and female data using two measures: frequency and percentage. In the frequency section, the male value is 140 and the female value is 27. In the percentage section, the male value is 83.8 percent and the female value is 16.2 percent. The chart presents both measures side by side to compare the distribution between the two groups.Sex of household heads
Source: Authors’ own work
As indicated in Table 2 below, about 86.2% of the respondents had no credit access, while 13.8% had credit access. Only a few households have the opportunity to get credit. However, as a focus group discussion participant noted, the availability of credit empowers farmers to buy inputs such as fertilizer, improved crop varieties and irrigation facilities. In both the study kebeles, farm income is very limited and only 22.8% of the total sample households responded that they are engaged in off-farm activities to supplement their family income, while 77.2% have no off-farm income (Table 2). According to the focus group discussion, a few farmers are engaged in petty trade, daily labor, handicraft production and beekeeping. However, it is regularly believed that the implementation of a new adaptation strategy requires sufficient financial well-being (Destaw and Fenta, 2021).
Credit access, off-farm income and type of agriculture practiced by survey household heads (n = 167)
| Variable category | Frequency | % |
|---|---|---|
| Credit access | ||
| Yes | 23 | 13.8 |
| No | 144 | 86.2 |
| Off–farm income | ||
| Yes | 38 | 22.8 |
| No | 129 | 77.2 |
| Type of agriculture practiced | ||
| Rain fed | 97 | 58.1 |
| Irrigation | 9 | 5.4 |
| Both | 61 | 36.5 |
| Variable category | Frequency | % |
|---|---|---|
| Credit access | ||
| Yes | 23 | 13.8 |
| No | 144 | 86.2 |
| Off–farm income | ||
| Yes | 38 | 22.8 |
| No | 129 | 77.2 |
| Type of agriculture practiced | ||
| Rain fed | 97 | 58.1 |
| Irrigation | 9 | 5.4 |
| Both | 61 | 36.5 |
Higher-income farmers may be less risk-averse and have more access to information and a longer-term planning horizon. 5.4% of respondent households practiced irrigation farming, 58.1% had practiced rain-fed agriculture and 36.5% had practiced both irrigation and rain-fed agriculture. Some farmers (nearest to the average) practiced both irrigation and rain-fed agriculture to cope with the adverse effects of climate change in the study area. The focus group discussion participant also stated that even though most of the lakes, springs and ponds were dried, the interest of farmers and attention of the government for irrigation farming is higher today than 30 years ago.
The overall average landholding size was 3.6886 hectares, which is above the national average landholding of 1.02 hectares. The respondents’ livestock holding mean, measured in TLU, was 2.8057 (Table 3). As participants in the focus group discussion noted, landholding size and livestock holding were the most important factors for differences in agricultural production and wealth status, and this is important in using diversified adaptation mechanisms.
Results of one-sample t-test for family size, landholding size, farming experience and TLU of survey household heads (n = 167)
| Variable | Mean | SD | t-test | p-value |
|---|---|---|---|---|
| Family size | 5.4192 | 3.12072 | 22.441 | 0.000 |
| Landholding size | 3.6886 | 2.74636 | 17.357 | 0.000 |
| Farming experience | 25.1317 | 14.08774 | 23.054 | 0.000 |
| TLU | 2.8057 | 1.88331 | 19.252 | 0.000 |
| Variable | Mean | SD | t-test | p-value |
|---|---|---|---|---|
| Family size | 5.4192 | 3.12072 | 22.441 | 0.000 |
| Landholding size | 3.6886 | 2.74636 | 17.357 | 0.000 |
| Farming experience | 25.1317 | 14.08774 | 23.054 | 0.000 |
| 2.8057 | 1.88331 | 19.252 | 0.000 |
As indicated in Table 3, the farming experience mean for respondent farmers was 25.1317 years. Experience in farming increases the likelihood of uptake of adaptations to climate change because more experienced farmers have better knowledge of the coping mechanism (Darge et al., 2023). The family size mean of respondent farmers is 5.4192 (Table 3). As participants in the focus group discussion stated, households with large families are more likely to adapt to climate change because large family size is normally associated with a higher labor endowment, which would enable a household to accomplish various agricultural tasks.
3.2 Farmers’ awareness toward climate change
As shown in Figure 2, 64.1% of the respondents reported having heard about climate change, while 35.9% indicated that they had not heard of it. This suggests that the level of understanding was somewhat limited. Interviews with district extension officers suggested that farmers tend to associate climate change with local terms such as “weather changes,” “drought” or spiritual explanations like God’s punishment, rather than the scientific concept of “climate change.” During the FGDs, farmers identified irregular rainfall and prolonged droughts as indicators of climate change, reflecting a practical, experience-based understanding.
The bar chart presents responses to the question Have you heard about climate change this yet? using two measures. The frequency section shows 107 responses for yes and 60 responses for no. The percentage section shows 64.1 percent for yes and 35.9 percent for no. The chart compares awareness levels by showing both counts and percentages side by side.Respondents’ awareness about climate change
Source: Authors’ own work
The bar chart presents responses to the question Have you heard about climate change this yet? using two measures. The frequency section shows 107 responses for yes and 60 responses for no. The percentage section shows 64.1 percent for yes and 35.9 percent for no. The chart compares awareness levels by showing both counts and percentages side by side.Respondents’ awareness about climate change
Source: Authors’ own work
Regarding sources of climate information, radio was the primary medium for 41.3% of respondents (Table 4), followed by government extension services (38.3%). This reliance on traditional media and extension networks underscores the limited penetration of digital platforms and literacy barriers in rural Ethiopia. It also reflects the relative success of agricultural extension programs in disseminating climate-related information, though gaps remain in frequency, accuracy and localization of messages. Consistent with Abukari et al. (2021), the finding emphasizes the need to strengthen rural communication infrastructures and integrate local languages and indigenous knowledge into dissemination efforts.
Farmers’ source of information about climate change (n = 167)
| Sources of information | Frequency | % |
|---|---|---|
| Radio | 69 | 41.3 |
| Television | 8 | 4.8 |
| Government organization (extension workers) | 64 | 38.3 |
| Other sources | 26 | 15.6 |
| Sources of information | Frequency | % |
|---|---|---|
| Radio | 69 | 41.3 |
| Television | 8 | 4.8 |
| Government organization (extension workers) | 64 | 38.3 |
| Other sources | 26 | 15.6 |
Farmers’ perceptions of climate change were largely experiential, derived from observable changes in rainfall and temperature rather than from formal scientific understanding. As shown in Table 5, 73.7% reported erratic rainfall patterns, and 65.3% linked climate change to increasing drought frequency. This experiential awareness suggests that local perception aligns closely with meteorological records showing long-term rainfall variability and warming trends in Oromia. However, such perception-based awareness may limit understanding of broader climatic drivers or long-term projections, thereby constraining proactive adaptation. Thus, combining indigenous observation with scientific climate literacy through participatory training would enhance adaptive capacity.
Knowledge of respondents on the local indicators of climate change (n = 167)
| Local indicator | Responses | Frequency | % |
|---|---|---|---|
| fluctuations in daily temperature | Yes | 91 | 54.5 |
| No | 76 | 45.5 | |
| heavier precipitation and flooding | Yes | 79 | 47.3 |
| No | 88 | 52.7 | |
| Erratic rainfall pattern and amount | Yes | 123 | 73.7 |
| No | 44 | 26.3 | |
| Increasing in droughty condition | Yes | 109 | 65.3 |
| No | 58 | 34.7 | |
| Other indicators | Yes | 64 | 38.3 |
| No | 103 | 61.7 |
| Local indicator | Responses | Frequency | % |
|---|---|---|---|
| fluctuations in daily temperature | Yes | 91 | 54.5 |
| No | 76 | 45.5 | |
| heavier precipitation and flooding | Yes | 79 | 47.3 |
| No | 88 | 52.7 | |
| Erratic rainfall pattern and amount | Yes | 123 | 73.7 |
| No | 44 | 26.3 | |
| Increasing in droughty condition | Yes | 109 | 65.3 |
| No | 58 | 34.7 | |
| Other indicators | Yes | 64 | 38.3 |
| No | 103 | 61.7 |
3.3 Impacts of climate change
3.3.1 Effects on livelihoods.
Climate change has had a profound impact on livelihoods in the study area. A large majority of households reported experiencing significant climate-related changes over the past 30 years, particularly in the form of erratic rainfall, prolonged droughts and increasing temperatures. These changes have led to declining crop and livestock productivity, frequent droughts, pest outbreaks and reduced agricultural yields, contributing to food insecurity and poverty.
Recurrent drought was perceived as the most pressing impact, cited by 41.9% of respondents (Table 6). Drought has direct implications for both crop and livestock productivity through reduced soil moisture, seed germination failure and pasture scarcity – findings consistent with Amanuel et al. (2019) and Belay et al. (2024). Yet, beyond confirmation, these results highlight structural vulnerabilities such as dependence on rain-fed systems and insufficient water-harvesting infrastructure. Increasing drought frequency has compounded food insecurity, illustrating the intersection between climatic shocks and socioeconomic fragility.
Impacts of climate change on farmers’ livelihoods (n = 167)
| Impacts of climate change | Frequency | % |
|---|---|---|
| Expose to pests and disease | 46 | 27.5 |
| Drought | 70 | 41.9 |
| Famine and poverty | 34 | 20.4 |
| Another impact of climate change in the area | 17 | 10.2 |
| Impacts of climate change | Frequency | % |
|---|---|---|
| Expose to pests and disease | 46 | 27.5 |
| Drought | 70 | 41.9 |
| Famine and poverty | 34 | 20.4 |
| Another impact of climate change in the area | 17 | 10.2 |
Approximately 27.5% of respondents identified a rise in livestock and crop diseases, while 20.4% associated climate change with increased poverty and hunger. These perceptions signal indirect but compounding effects of climate variability – where higher temperatures and humidity shift foster pests and pathogens, aggravating livelihood losses. The spread of livestock diseases such as anthrax and blackleg and crop pests such as Striga and aphids aligns with earlier studies (Bedada et al., 2018) but also points to emerging biosecurity challenges that current extension systems may not be adequately addressing.
3.3.2 Decline in crop and livestock productivity.
Crop productivity: The result of Table 7 indicates a notable decline in crop yields, particularly for teff and sorghum, which respondents attribute primarily to erratic rainfall and recurrent droughts. At the same time, 34.7% of respondents recalled high productivity levels three decades ago; only 12.6% report similarly high yields today, despite the adoption of improved varieties and fertilizer use. This suggests that technological interventions, though beneficial, have not fully compensated for the adverse effects of changing climatic conditions. Focus group discussions, particularly with Development Agents (DAs), confirmed that improved crop varieties have contributed to yield increases for some crops, highlighting the role of adaptive strategies. Nevertheless, the majority of respondents – 46.1% and 41.3% reporting medium and poor productivity, respectively – perceive current yields as suboptimal, underscoring the persistent vulnerability of local agriculture to climate variability.
Impact of climate change on crop production (n = 167)
| Performance of crop productivity over time | Frequency | % | |
|---|---|---|---|
| Crop productivity 30 years ago | High | 58 | 34.7 |
| Medium | 80 | 47.9 | |
| Low | 29 | 17.4 | |
| Crop productivity at current (in 2023) | High | 21 | 12.6 |
| Medium | 77 | 46.1 | |
| Low | 69 | 41.3 | |
| Performance of crop productivity over time | Frequency | % | |
|---|---|---|---|
| Crop productivity 30 years ago | High | 58 | 34.7 |
| Medium | 80 | 47.9 | |
| Low | 29 | 17.4 | |
| Crop productivity at current (in 2023) | High | 21 | 12.6 |
| Medium | 77 | 46.1 | |
| Low | 69 | 41.3 | |
These findings align with previous studies indicating that climate change exerts both direct and indirect effects on crop production (Demem, 2023; Solomon et al., 2021; Chimdo, 2022; Ginbo, 2022; Araro et al., 2020). Changes in temperature and rainfall patterns have been shown to disrupt crop growth cycles, reduce soil moisture availability and exacerbate water stress, ultimately lowering yields of both rain-fed and irrigated crops (Mammo, 2022). The observed discrepancies between technological interventions and actual yield outcomes suggest that adaptation measures, while important, may be insufficient without complementary strategies such as improved water management, climate-resilient cropping systems and local capacity building to buffer against increasingly erratic weather patterns.
Livestock production: The result indicates a marked decline in livestock productivity, reflecting the multifaceted impacts of climate change on livestock systems. Key challenges include reduced feed availability, limited water accessibility, compromised animal health and decreased growth and reproductive performance, all of which contribute to reductions in herd size and overall productivity (Mekuyie and Mulu, 2021; Habte et al., 2022). As Figure 3 illustrates, while 52.7% of respondents reported higher livestock numbers 30 years ago, only 9% perceive improvements in 2023, largely attributable to adaptive measures such as silage production and water harvesting. Despite these interventions, nearly half of respondents (49.1%) reported low current livestock productivity, highlighting persistent vulnerabilities linked to feed scarcity, disease outbreaks and water stress.
The grouped bar chart compares percentage levels at two time points: before 30 years ago and at the current time in 2023. For the earlier period, the values are 52.7 percent for high level, 35.9 percent for medium level, and 11.4 percent for low level. For the current time, the values are 9 percent for high level, 41.9 percent for medium level, and 49.1 percent for low level. The chart shows how the distribution across the three levels changes over time.Impact of climate change on livestock production
Source: Authors’ own work
The grouped bar chart compares percentage levels at two time points: before 30 years ago and at the current time in 2023. For the earlier period, the values are 52.7 percent for high level, 35.9 percent for medium level, and 11.4 percent for low level. For the current time, the values are 9 percent for high level, 41.9 percent for medium level, and 49.1 percent for low level. The chart shows how the distribution across the three levels changes over time.Impact of climate change on livestock production
Source: Authors’ own work
These findings corroborate previous studies demonstrating that climate change exerts both direct and indirect pressures on livestock production (Sintayehu et al., 2023; Mengistu et al., 2025; Habte et al., 2022; Mekuyie and Mulu, 2021). The decline in livestock performance suggests that adaptation strategies, while beneficial, remain insufficient to offset the compounded effects of environmental stressors. This underscores the need for integrated approaches, including improved forage management, climate-resilient animal husbandry practices and strengthened veterinary and water infrastructure, to sustain livestock productivity under increasingly erratic climatic conditions.
3.3.3 Impacts on natural resources and the environment.
Land degradation and soil erosion: Land degradation and soil erosion remain pressing challenges for farmers in Leban Chukala, driven by a combination of intensive farming practices, erratic rainfall and increased wind activity. According to Table 8, 77.2% of respondents identified soil erosion and land degradation as serious current issues, with the most severe effects observed near riverbanks and hillsides, where topsoil loss is pronounced. While 18.6% of respondents reported improvements attributed to soil and water conservation measures, these interventions appear insufficient to fully counteract the accelerating degradation. The findings underscore the cumulative impact of both/anthropogenic and climatic factors, with floods and heavy rainfall events exacerbating soil loss and, consequently, reducing crop productivity. These results are consistent with previous studies demonstrating that flooding and poor land management are significant drivers of land degradation and declining agricultural yields (Bedada et al., 2018; Maru and Makambi, 2024).
Impacts of climate change on natural resources and environment (n = 167)
| Natural resources and environmental impact | Rate of impact | Frequency | % |
|---|---|---|---|
| Change in Forest cover | Increased | 32 | 19.2 |
| Decreased | 121 | 72.5 | |
| No change | 14 | 8.4 | |
| Land degradation and soil erosion over time | Increased | 129 | 77.2 |
| Decreased | 31 | 18.6 | |
| No change | 7 | 4.2 | |
| Water availability | Increased | 27 | 16.2 |
| Decreased | 140 | 83.8 | |
| No change | 0 | 0 |
| Natural resources and environmental impact | Rate of impact | Frequency | % |
|---|---|---|---|
| Change in Forest cover | Increased | 32 | 19.2 |
| Decreased | 121 | 72.5 | |
| No change | 14 | 8.4 | |
| Land degradation and soil erosion over time | Increased | 129 | 77.2 |
| Decreased | 31 | 18.6 | |
| No change | 7 | 4.2 | |
| Water availability | Increased | 27 | 16.2 |
| Decreased | 140 | 83.8 | |
| No change | 0 | 0 |
The evidence suggests that without strengthened and context-specific soil conservation strategies, including terracing, reforestation and integrated watershed management, land degradation will continue to undermine agricultural sustainability in the region. Moreover, the persistent tension between the need for intensive cultivation to meet food demands and the imperative to maintain soil health highlights a critical challenge for local agricultural adaptation planning.
Forest cover: The finding reveals a significant decline in forest cover over the past three decades, with 72.5% of households reporting reductions, primarily because of deforestation for fuelwood, agricultural expansion and other human activities. This long-term deforestation trend highlights the persistent pressure on local forest resources and its potential consequences for biodiversity, soil conservation and local climate regulation. Conversely, 19.2% of respondents noted recent increases in forest cover, largely attributed to targeted reforestation and restoration initiatives such as the Green Legacy campaign. While these efforts demonstrate the potential for community- and government-led interventions to reverse forest loss, the relatively low proportion of households observing gains indicates that restoration has yet to offset the historical deforestation significantly. These findings align with previous studies documenting both the drivers of forest decline and the emerging impacts of afforestation programs (Mekonnen et al., 2021; Getachew et al., 2025), underscoring the need for sustained, scalable and locally adapted forest management strategies to achieve long-term ecological resilience.
Water availability: A striking 83.8% of respondents (Table 8) reported that water shortages have intensified over the past three decades, with none indicating that water availability has remained constant. This trend reflects the growing vulnerability of local communities to climate variability, particularly recurrent droughts and erratic rainfall patterns, which reduce surface and groundwater availability. The pervasive nature of water scarcity underscores its cascading impacts on agricultural production, livestock health and household livelihoods, reinforcing the interdependence between water security and overall rural resilience. These findings are consistent with broader studies linking climate change to decreased water access and heightened drought frequency (Cherinet, 2017; Solomon et al., 2021), highlighting the urgent need for integrated water management strategies, including rainwater harvesting, small-scale irrigation and watershed restoration, to mitigate long-term water stress in the region.
3.3.4 Impacts on social groups.
The findings indicate that climate change disproportionately impacts vulnerable social groups, highlighting the social dimensions of environmental stress. As shown in Figure 4, nearly half of the respondents (48%) identified women as the most affected, followed by children (41%). Women’s heightened vulnerability is largely because of their central role in household labor, including the collection of water and fuel, which becomes increasingly burdensome under conditions of resource scarcity. Children, on the other hand, are more susceptible to climate-related health risks, including malnutrition and waterborne diseases. Focus group discussions and key informant interviews further revealed that the poor, landless and marginalized populations are particularly at risk, lacking both the resources and adaptive capacity to cope with climate-induced shocks. These observations align with previous research on social vulnerability, emphasizing that climate impacts are not only environmental but also deeply socio-economic (Markkanen and Anger-Kraavi, 2019). The evidence underscores the need for targeted interventions that enhance adaptive capacity, including gender-sensitive programs, social protection measures and community-based resilience strategies, to ensure that the most vulnerable groups are not left disproportionately exposed to climate risks.
The pie chart shows the percentage distribution of social groups that are more affected. Women account for 48 percent, children account for 41 percent, and men account for 11 percent.Impact of climate change on social groups
Source: Authors’ own work
The pie chart shows the percentage distribution of social groups that are more affected. Women account for 48 percent, children account for 41 percent, and men account for 11 percent.Impact of climate change on social groups
Source: Authors’ own work
3.4 Farmers’ coping and adaptation strategies to climate change
Farmers in Leban Chukala use a range of local and institutional strategies to adapt to climate change, yet their adaptive capacity remains constrained by limited infrastructure, technological resources and financial support. As Figure 5 illustrates, perceptions regarding responsibility for climate adaptation are varied: approximately 21% of respondents see it as primarily the role of governmental organizations, 12.6% attribute it to non-governmental organizations (NGOs) and 29.3% consider local communities themselves responsible. Notably, the majority – 37.1% – recognize that effective adaptation requires coordinated efforts among government bodies, NGOs and local communities. This finding underscores the importance of collaborative governance and multi-stakeholder approaches in addressing climate risks, as isolated interventions are unlikely to achieve sustainable outcomes. It also highlights a gap in institutional support and community engagement, suggesting that enhancing access to climate-resilient technologies, extension services and participatory planning mechanisms is critical to strengthening local adaptive capacity and ensuring that adaptation strategies are both context-specific and equitable.
The bar chart shows responses to the question Who is responsible to adaptation practice? using frequency and percentage measures. Government organisation shows a frequency of 35 and a percentage of 21 percent. Non-government organisation shows a frequency of 21 and a percentage of 12.6 percent. Local community shows a frequency of 49 and a percentage of 29.3 percent. Collaboration of three shows a frequency of 62 and a percentage of 37.1 percent. The chart displays paired bars for each group to present both values side by side.Responsible bodies to adaptation practice of climate change
Source: Authors’ own work
The bar chart shows responses to the question Who is responsible to adaptation practice? using frequency and percentage measures. Government organisation shows a frequency of 35 and a percentage of 21 percent. Non-government organisation shows a frequency of 21 and a percentage of 12.6 percent. Local community shows a frequency of 49 and a percentage of 29.3 percent. Collaboration of three shows a frequency of 62 and a percentage of 37.1 percent. The chart displays paired bars for each group to present both values side by side.Responsible bodies to adaptation practice of climate change
Source: Authors’ own work
3.4.1 Coping mechanisms.
Selling assets: In the study area of Leban Chukala, the strategy of selling assets emerges as the predominant and initial response to climate shocks, with 25.1% of respondents (Table 9) reporting the sale of livestock or eucalyptus poles during droughts. This common approach underscores how households draw on tangible assets as a buffer against climate-induced losses. However, interpreting this as a “strategy” demands greater nuance: asset sales in such contexts can operate simultaneously as adaptation and distress coping, carrying both short-term relief and longer-term risks (Berhanu et al., 2024; Admassie and Abebaw, 2021). In the Leban Chukala case, the constraint of market access and buyer selectivity is especially salient (Mekuyie and Mulu, 2021). When farmers must sell in distressed conditions, or when buyers are scarce or exploitative, asset sales can trigger a downward spiral of asset depletion with little return, thereby reducing future resilience (Deressa et al., 2009). This aligns with findings from recent studies that classify asset-selling primarily as a coping rather than a sustainable adaptation response, particularly when undertaken reactively during crisis periods rather than as part of a planned resilience strategy (Bryan et al., 2024).
Farmers’ coping practices to climate change in the study area (n= 167)
| Coping mechanism | Frequency | % |
|---|---|---|
| Selling fire wood and charcoal | 22 | 13.2 |
| Look for daily work | 28 | 16.8 |
| Reduce meal size and frequency | 19 | 11.4 |
| Seasonal migration | 14 | 8.4 |
| Sell assets | 42 | 25 |
| Borrowing money | 36 | 21.6 |
| Other coping mechanisms | 6 | 3.6 |
| Total | 167 | 100 |
| Coping mechanism | Frequency | % |
|---|---|---|
| Selling fire wood and charcoal | 22 | 13.2 |
| Look for daily work | 28 | 16.8 |
| Reduce meal size and frequency | 19 | 11.4 |
| Seasonal migration | 14 | 8.4 |
| Sell assets | 42 | 25 |
| Borrowing money | 36 | 21.6 |
| Other coping mechanisms | 6 | 3.6 |
| Total | 167 | 100 |
Selling firewood and charcoal: In the study area, 13.2% of households (Table 9) reported that they cover their own consumption needs by selling firewood and charcoal to semi-urban and urban markets. This adaptation behavior reflects a short-term survival strategy in the face of climate stress and income shortfalls. However, the relative prominence of this strategy highlights key risks and trade-offs. On one hand, the sale of firewood and charcoal provides immediate cash and sustains household consumption – an important buffer when crop yields, livestock productivity and other livelihood sources are under pressure (Hirpha et al., 2021; Deressa et al., 2009). On the other hand, this strategy may exacerbate environmental degradation, particularly deforestation, soil erosion and the loss of ecosystem services (Amare and Simane, 2018). Studies in Ethiopia have shown that even the adoption of improved cookstoves only partially mitigates the problem, as biomass fuel extraction remains high and continues to contribute to forest loss and land degradation (Amare and Simane, 2018; Mekonnen et al., 2021). From a policy perspective, this suggests that adaptation support should address more than just immediate coping – it must also incentivize sustainable energy alternatives, strengthen community-based forest management and help households transition away from ecosystem-degrading income sources (Food and Agriculture Organization of the United Nations, 2024).
Reducing meal size and frequency: According to respondents’ interviews, 11.4% of households (Table 9), particularly adults, reported reducing meal size and frequency during periods of food shortages to lower household expenses. This finding is consistent with Tsegaye et al. (2018), who noted that food rationing is a common short-term coping strategy among rural households facing climatic stress. However, such a response is largely erosive rather than adaptive, as it undermines nutritional status and immunity, thereby increasing susceptibility to diseases such as malaria (Abate, 2021; Mekonnen et al., 2021). Studies show that repeated meal reduction reflects chronic food insecurity and weak adaptive capacity, ultimately compromising household health and productivity (Food and Agriculture Organization of the United Nations, 2024; Hassen et al., 2021).
Seasonal migration: About 8.4% of households (Table 9), mainly involving youth, reported temporary migration for income during harsh periods. Typically, the youngest household members migrate for 3–5 months and return once some income is secured. This aligns with findings by Mekuyie and Mulu (2021) and Narita et al. (2022), who note that seasonal migration is a common livelihood adjustment to climate and economic shocks in rural Ethiopia. However, such migration often represents reactive coping rather than proactive adaptation, as it provides short-term income but may disrupt family labor, education and social ties, while offering limited resilience to recurring shocks (Yaro et al., 2020; Food and Agriculture Organization of the United Nations, 2024).
Seeking daily labor: About 16.8% of households (Table 9) reported relying on labor migration, particularly when farm yields decline. This finding aligns with Deressa et al. (2009) and Mekuyie and Mulu (2021), who note that migration is a widespread income diversification strategy among smallholders facing climate and market shocks. However, while labor migration provides short-term income stability, it often reflects a reactive coping mechanism rather than sustainable adaptation, as it may deplete local labor, reduce agricultural productivity and strain family cohesion (Narita et al. (2022).
Borrowing money: About 21.6% of households (Table 9) reported borrowing from relatives or financial institutions during crises, consistent with Schultz (2012), who identified informal credit as a key risk-sharing mechanism in rural economies. While such borrowing provides immediate liquidity and helps smooth consumption during shocks, it often reflects limited formal financial inclusion and can lead to indebtedness when repayment capacity is low (Hirpha et al., 2021). Thus, access to affordable and reliable rural finance remains crucial for transforming borrowing from a short-term coping response into a sustainable adaptation mechanism (World Bank Group, 2024).
Other strategies: About 3.6% of households (Table 9) reported engaging in mutual aid practices, such as lending grain or purchasing food on credit to be repaid after harvest. This aligns with findings by Endris et al. (2020), who note that social networks and informal credit systems play a vital role in cushioning rural households against shocks. However, while such reciprocal arrangements strengthen community solidarity and short-term food security, they remain limited in scale and sustainability, especially when covariate shocks affect entire communities simultaneously (Hirpha et al., 2021; Food and Agriculture Organization of the United Nations, 2024). Strengthening these traditional systems through formalized community-based risk-sharing mechanisms could enhance resilience in the long term.
3.4.2 Farmers’ adaptation strategies to climate change.
Farmers in Leban Chukala use diverse adaptation strategies to mitigate the impacts of climate change, reflecting both local innovation and alignment with national and global adaptation priorities (Alemayehu et al., 2022). Most households have adopted at least one strategy, highlighting the pervasive awareness of climate risks and the need to safeguard livelihoods (Hirpha et al., 2021). However, the effectiveness of these strategies varies, with socio-economic constraints, land scarcity and labor availability shaping adoption and outcomes.
Crop diversification: Practiced by 85.6% of respondents, crop diversification remains the dominant strategy to reduce climatic risk (Table 10). By planting multiple varieties and rotating crops based on rainfall and land conditions, households reduce the likelihood of total crop failure (Dixon et al., 2020). Yet, 14.4% of farmers still cultivate a single crop, indicating that limited land and capital can prevent optimal risk spreading. While crop diversification supports food security and income stability, its success depends on access to diverse seeds and extension services, which may be unevenly distributed across households (Kim and Noh, 2025).
Farmers’ adaptation strategies to climate change in the study area (n = 167)
| Adaptation strategy | Farmers’ response | Frequency | % |
|---|---|---|---|
| Crop diversification | Yes | 143 | 85.6 |
| No | 24 | 14.4 | |
| I didn’t know | – | – | |
| Growing of drought-resistant and early maturing crop varieties | Yes | 119 | 71.3 |
| No | 41 | 24.6 | |
| I didn’t know | 7 | 4.2 | |
| Water harvesting and small-scale irrigation | Yes | 28 | 16.8 |
| No | 139 | 83.2 | |
| I didn’t know | – | – | |
| Soil and water conservation | Yes | 133 | 79.6 |
| No | 34 | 20.4 | |
| I didn’t know | – | – | |
| Livestock management | Yes | 80 | 47.9 |
| No | 87 | 52.1 | |
| I didn’t know | – | – | |
| Tree planting and agro-forestry practices | Yes | 81 | 48.5 |
| No | 77 | 46.1 | |
| I didn’t know | 9 | 5.4 | |
| Diversification of income sources | Yes | 45 | 26.9 |
| No | 122 | 73.1 | |
| I didn’t know | – | – |
| Adaptation strategy | Farmers’ response | Frequency | % |
|---|---|---|---|
| Crop diversification | Yes | 143 | 85.6 |
| No | 24 | 14.4 | |
| I didn’t know | – | – | |
| Growing of drought-resistant and early maturing crop varieties | Yes | 119 | 71.3 |
| No | 41 | 24.6 | |
| I didn’t know | 7 | 4.2 | |
| Water harvesting and small-scale irrigation | Yes | 28 | 16.8 |
| No | 139 | 83.2 | |
| I didn’t know | – | – | |
| Soil and water conservation | Yes | 133 | 79.6 |
| No | 34 | 20.4 | |
| I didn’t know | – | – | |
| Livestock management | Yes | 80 | 47.9 |
| No | 87 | 52.1 | |
| I didn’t know | – | – | |
| Tree planting and agro-forestry practices | Yes | 81 | 48.5 |
| No | 77 | 46.1 | |
| I didn’t know | 9 | 5.4 | |
| Diversification of income sources | Yes | 45 | 26.9 |
| No | 122 | 73.1 | |
| I didn’t know | – | – |
Drought-resistant and early-maturing crops: About 71.3% of farmers (Table 10) grow crops such as sorghum, maize and haricot beans to cope with erratic rainfall (Mustafa, 2023; Kenea and Mebratu, 2020; Belay et al., 2024). These varieties enhance resilience by shortening growing cycles and maintaining yield under moisture stress. However, adoption is often constrained by limited seed availability and knowledge gaps and reliance on these varieties may reduce crop diversity, potentially increasing vulnerability to pests or market shocks.
Water harvesting and small-scale irrigation: Practiced by 16.8% (Table 10), primarily near water sources, these interventions improve dry-season production and buffer households against rainfall variability (Amare and Simane, 2018; Marie et al., 2020). Nevertheless, adoption remains low due to technical, financial and labor constraints, suggesting that scaling up irrigation requires institutional support, infrastructure investment and training.
Soil and water conservation: About 79.6% of farmers (Table 10) engage in terracing, stone bunds and related measures to reduce soil erosion and retain moisture. While such practices enhance land productivity and long-term resilience, 20.4% of households do not implement them due to labor shortages, particularly among elderly or sick households. This indicates that conservation measures, although effective, are labor-intensive and may disproportionately favor households with available working-age members (Teshome et al., 2022).
Livestock management: Approximately 47.9% have shifted to more resilient livestock types, reduced herd size, or adopted feed-saving strategies such as cut-and-carry (Table 10). This allows households to maintain income and nutrition during crop failures (Solomon et al., 2021; Magesa et al., 2023). Yet, feed shortages, market fluctuations and competition for grazing land limit the long-term sustainability of livestock-based adaptation.
Tree planting and agroforestry: Nearly 48.5% of farmers (Table 10) engage in reforestation and agroforestry, planting multipurpose trees such as Acacia albida and Eucalyptus saligna for soil conservation, shade and income from charcoal. Adoption is constrained by land scarcity and limited access to seedlings, and 46.1% do not practice tree planting, while 5.4% are unaware of its benefits (Jhariya et al., 2019; Quandt et al., 2023). While agroforestry contributes to both climate mitigation and adaptation, its effectiveness depends on land tenure security and integration with existing farming systems.
Income diversification: About 43.3% of households (Table 10) engage in off-farm activities such as petty trade, wage labor, or services to reduce dependence on climate-sensitive agriculture (Amare and Simane, 2018; Marie et al., 2020). While diversification spreads risk, it may also reduce labor availability for agriculture and reflect a reactive coping strategy rather than a structural transformation of livelihoods.
Overall, while farmers in Leban Chukala exhibit impressive adaptive behavior, these strategies are often constrained by socio-economic, infrastructural and environmental factors. Adoption is highest for low-cost, labor-intensive, or knowledge-based strategies (crop diversification and soil conservation), whereas capital-intensive interventions (irrigation, agroforestry and livestock upgrading) show lower uptake. This suggests that supporting climate adaptation requires holistic interventions that combine access to resources, training, financial services and market linkages, alongside policies that address land scarcity and labor limitations.
3.5 Institutional perspectives on climate change adaptation
Insights from agricultural extension agents and local administrators in Liben Chukala District revealed that institutional structures play a decisive role in shaping community awareness, perceptions and adaptive responses to climate change. Institutions act as the key link between scientific knowledge, government policy and local practices, determining how effectively farmers can respond to environmental stressors (Agrawal, 2008; Moser and Ekström, 2010).
Extension officers in the district emphasized that increasing community awareness of climate change has been a major focus of institutional interventions. They noted that most awareness activities are conducted through farmer training centers, village meetings and demonstration plots. These efforts are aimed at improving farmers’ understanding of changing rainfall patterns, recurrent droughts and declining soil fertility. Similar institutional initiatives have been reported in other parts of Ethiopia, where agricultural extension services serve as vital channels for knowledge dissemination and capacity building (Asrat and Simane, 2018; Belay et al., 2017). However, the officers also acknowledged several challenges, including limited financial resources, high staff turnover and inadequate access to up-to-date climate information, all of which reduce the continuity and effectiveness of awareness programs. These institutional limitations align with observations by Deressa et al. (2009); Gebrehiwot and van der Veen (2013), who found that resource constraints within extension systems significantly hinder adaptive learning among rural households.
In discussing local adaptation strategies, extension agents and administrators identified a range of measures promoted or facilitated through institutional support. These include soil and water conservation, reforestation, use of drought-tolerant crop varieties, crop diversification and the adoption of improved irrigation practices. Such activities are often implemented under programs like the Productive Safety Net Program and the Sustainable Land Management Program, which integrate climate resilience objectives into rural livelihoods (Bryan et al., 2024). Extension officers described how they mobilize community labor and provide technical advice for land rehabilitation and water harvesting structures. They emphasized that local institutions not only provide knowledge but also serve as platforms for collective action – facilitating collaboration among farmers, DAs and administrative bodies. This aligns with the findings of Tessema and Simane (2021), who stress that institutions enhance adaptive capacity by fostering social learning and cooperative problem-solving.
Nevertheless, both groups of informants highlighted persistent institutional challenges. The majority of adaptation initiatives remain project-driven, dependent on external donor funding and lack mechanisms for sustainability once funding ends. Moreover, extension services often operate reactively in response to climatic shocks rather than proactively through early warning and preventive systems. These institutional weaknesses mirror observations from other Ethiopian districts (Ewalo and Vedeld, 2023), where the limited integration of scientific climate information and the exclusion of indigenous knowledge constrain local adaptation efforts.
Extension agents also underscored the importance of incorporating indigenous knowledge into formal adaptation planning. They noted that farmers often rely on traditional ecological indicators – such as changes in animal behavior or local vegetation patterns – to anticipate rainfall. However, institutional programs have yet to fully integrate these indigenous forecasting systems into their extension approaches. As Antwi-Agyei et al. (2014); Simane and Zaitchik (2014) argue, blending local and scientific knowledge can improve the cultural relevance and effectiveness of adaptation strategies at the grassroots level.
In summary, institutional perspectives from Liben Chukala District underscore that while local government structures and extension systems have made significant progress in raising awareness and supporting adaptation, their efforts are constrained by financial limitations, weak inter-sectoral coordination and limited incorporation of local knowledge. Enhancing institutional capacity, ensuring continuity of adaptation programs and creating stronger linkages between scientific information and community practices are crucial steps toward building resilient and informed rural livelihoods in the face of climate change.
3.6 Research process flowchart
Figure 6 presents the overall research process flowchart, illustrating the sequential steps followed in this study.
The flowchart presents the stages of a research process in a top-to-bottom sequence. The process begins with identifying the research problem, reviewing literature, and formulating research objectives. It then moves to designing the methodology, which includes selecting the study area, determining sample size and sampling technique, and developing data collection methods. The next stage is data collection through surveys, interviews, and field observation. The flowchart then shows interpretation of results, covering community awareness, perceived climate change impacts, and local adaptation strategies. The final stage shows drawing conclusions and recommendations.Research process flowchart
Source: Authors’ own work
The flowchart presents the stages of a research process in a top-to-bottom sequence. The process begins with identifying the research problem, reviewing literature, and formulating research objectives. It then moves to designing the methodology, which includes selecting the study area, determining sample size and sampling technique, and developing data collection methods. The next stage is data collection through surveys, interviews, and field observation. The flowchart then shows interpretation of results, covering community awareness, perceived climate change impacts, and local adaptation strategies. The final stage shows drawing conclusions and recommendations.Research process flowchart
Source: Authors’ own work
4. Conclusion and recommendation
4.1 Conclusion
This study provides robust evidence of the multi-dimensional impacts of climate change on smallholder farming systems in the Leban Chukala District. Rising temperatures and increasingly erratic rainfall have disrupted livelihoods by lowering crop productivity, stressing livestock and degrading natural resources. Although most farmers recognize that the climate is changing, their understanding remains limited and is often framed in natural or spiritual terms. The consequences are severe: reduced agricultural output, more frequent pest and disease outbreaks, recurrent droughts and food shortages and a heightened risk of poverty – especially among vulnerable groups such as women and children.
The findings supply district-level evidence to design targeted adaptation policies, early-warning systems and gender-sensitive support programs. The results highlight successful, locally driven practices that can be scaled up and inform community training initiatives. The study identifies critical entry points – such as subsidized climate-smart inputs and information dissemination – for reducing vulnerability and strengthening food security. Theoretically, the research advances understanding of how farmers’ perceptions interact with observable climatic changes to shape adaptive behavior in semi-arid, smallholder contexts. Empirically, it offers detailed, household-level data from Ethiopia that can inform comparative studies and refine models of climate-change adaptation in similar agro-ecological zones.
4.2 Recommendations
Based on the findings, the following recommendations are made:
Local extension services should offer training that clarifies the science behind climate change and its practical implications, enabling farmers to adapt agricultural practices effectively.
Given the lack of irrigation facilities, especially for those unable to afford them, government bodies, particularly the district agricultural office, should facilitate access to irrigation tools such as water pumps to improve farmers’ capacity for adaptation.
Development institutions should improve the accessibility of credit facilities, enabling farmers to purchase productive technologies and essential agricultural inputs to diversify livelihoods.
The study highlights challenges such as limited access to seeds, fertilizers, moisture management practices and weather data. Research institutions should tackle these issues, while extension services must be adapted to meet farmers’ needs and local climate conditions.
Future research should evaluate the effects of climate change on farmers’ income and household wealth. It should also explore innovative adaptation technologies for long-term agricultural sustainability and identify effective strategies to guide future policy decisions.
Acknowledgements
The authors would like to offer a premier thanks to the households, key informants and focus group discussants who generously provided the essential data and information for this study.
Author contribution statement
Tafese Shole, Conceptualization, Study design, Data collection, Formal analysis, Data interpretation, Original draft – Writing and Reviewing. Asaye Ayele, Data analysis, Data interpretation, Manuscript writing. Tale Geddafa, Data analysis, Data interpretation, Manuscript writing.

