Smallholder farmers’ adaptation to climate change and determinants of their adaptation decisions in the Central Rift Valley of Ethiopia
© The Author(s) 2017
Received: 13 April 2016
Accepted: 21 February 2017
Published: 6 March 2017
The agricultural sector remains the main source of livelihoods for rural communities in Ethiopia, but faces the challenge of changing climate. This study investigated how smallholder farmers perceive climate change, what adaptation strategies they practice, and factors that influence their adaptation decisions. Both primary and secondary data were used for the study, and a multinomial logit model was employed to identify the factors that shape smallholder farmers’ adaptation strategies.
The results show that 90% of farmers have already perceived climate variability, and 85% made attempts to adapt using practices like crop diversification, planting date adjustment, soil and water conservation and management, increasing the intensity of input use, integrating crop with livestock, and tree planting. The econometric model indicated that education, family size, gender, age, livestock ownership, farming experience, frequency of contact with extension agents, farm size, access to market, access to climate information and income were the key factors determining farmers’ choice of adaptation practice.
In the Central Rift Valley of Ethiopia, climate change is a pressing problem, which is beyond the capacity of smallholders to respond to autonomously. Farmers’ capacity to choose effective adaptation options is influenced by household demography, as well as positively by farm size, income, access to markets, access to climate information and extension, and livestock production. This implies the need to support the indigenous adaptation strategies of the smallholder farmers with a wide range of institutional, policy, and technology support; some of it targeted on smaller, poorer or female-headed households. Moreover, creating opportunities for non-farm income sources is important as this helps farmers to engage in those activities that are less sensitive to climate change. Furthermore, providing climate change information, extension services, and creating access to markets are crucial.
KeywordsClimate change Adaptation Diversification Livelihoods Multinomial logit model Smallholder farmers
Scientific evidence indicates that the earth’s climate is rapidly changing, owing to increases in greenhouse gas emissions [1, 2]. The increased concentration of greenhouse gases has raised the average temperature and altered the amount and distribution of rainfall globally [3, 4]. For example, in Sub-Saharan Africa, warming is expected to be greater than the global average and in parts of the region, rainfall will decline . There is growing evidence that extreme events, such as droughts and floods, have been common incidences . These have affected smallholder farmers in developing countries who heavily depend on rainfed agriculture for their livelihoods [2, 6, 7]. In Africa, climate change has affected both the natural and social systems [7, 8]. Impacts of climate change are felt more severely in semi-arid and arid areas [7, 9, 10]. Limiting the damage due to climate change has become a challenge for the global community now. In this regard, climate change mitigation and adaptation are crucial . Adaptation can manage the impacts but cannot by itself solve the problem of climate change. Even with adaptation, there will be residual costs. Smallholder farmers, for instance, can switch to more adapted crop varieties, but they may have lower productivity . In developing countries, adaptation of the agricultural sector to the changing climate is important for ensuring livelihoods of the poor communities . Adaptation will require the involvement of multiple stakeholders, including policymakers, extension agents, NGOs, researchers, communities, and farmers. Climate change adaptation is mostly location-specific, and its effectiveness depends on local institutions and socioeconomic setting . A better understanding of how smallholder farmers perceive climate change and the adaptation strategies they practice is needed to make policies and design programs aimed at promoting successful adaptation in the agricultural sector. A combination of factors influences the farmers’ perception about climate variability and the decision to use the selected adaptation strategies [14, 15].
Farmers in developing nations are developing resilience to climate change-related risks like droughts and floods through practicing diverse adaptation strategies. In the West African Sahel, for instance, pastoralists have come up with strategies to cope with the erratic rainfall . In Ethiopia, diverse practices are used in both the highlands and lowlands [16, 17]. The agricultural sector in Ethiopia accounts for about 42% of national GDP, 90% of exports and 85% of employment , and is mainly rainfed. The history of drought in Ethiopia dates back to 250 BC, since then droughts have occurred in different parts of the country at different times . At present, the potential adverse effects of climate change on Ethiopia’s agricultural sector are major concerns. In the Central Rift Valley of Ethiopia, climate change and variability is manifest through frequent droughts and floods, erratic rainfall and fluctuating mean temperature . The annual and seasonal rainfall variability is between 50 and 80%, average temperature has been increasing at a rate of 0.37 °C every ten years, and the maximum daily temperature has increased by a cumulative 1.5 °C since 1900 . Smallholder farmers are highly dependent on rainfed agriculture which is very sensitive to climate variability and change. Changes in the distribution and amount of rainfall which have resulted in low precipitation and frequent drought have been affecting agriculture .
This study aimed at (a) examining how the local community perceived the impacts of climate change, (b) identifying what adaptation practices they use, and (c) investigating the factors that determine their choice of adaptation strategies in the central rift valley of Ethiopia. The study area has climate-related risks such as water stress and increased incidences of pest and diseases .
Description of the study area
The study was done in Arsi Negelle district of West Arsi Zone, Oromia Regional State of Ethiopia (Fig. 1). The district is located at 250 km south of the national capital, Addis Ababa. Geographically, it is located between 7°17′N and 7°66′N, and between 38°43′E and 38°81′E. The temperature ranges between 10 and 25 °C, while annual rainfall varies between 500 and 1200 mm. The area has four distinct seasons including the dry season (December to February), the short rainy season (March to May), the main rainy season (June to August), and the autumn season (September to November) . Topographically, the district is slightly undulating especially in the highlands and almost flat in the lowlands. Some parts of the highlands in the district are still covered by natural forest, bush and shrub. There are three large inland Lakes—Abijata, Shalla and Langano—in the district. The district has relatively fair agricultural potential, which is reflected in the diversity of crop and livestock production for food and income generation . In comparison with other districts of the West Arsi Zone, Arsi Negele district has more severe extreme events such as recurrent drought. This study was conducted in three agro-ecological zones in the district that range between 1500 and 2800 m.a.s.l. The high altitude agro-ecological zone occupies the largest area followed by mid and low altitude agro-ecological zones, respectively.
Sampling design and sample size
This study employed a multi-staged sampling technique, where a combination of sampling techniques was used to select the Kebeles (the lowest level administrative units under the Federal Democratic Government of Ethiopia) and households. In the first stage, Arsi Negelle district was selected purposely from the districts of West Arsi Zone, because it is one of the most severely affected districts by extreme climate change-related risks and is characterized by three distinct agro-ecological zones, highland, midland and lowland .
Distribution of sampled households by the Kebele/village
Kebele name (and agro-ecology)
Total number of households
Number of sampled household heads
Male household heads (%)
Female household heads (%)
Meraro Hawilo (Highland)
Kersa IIala (Midland)
Mudi Arjo (Lowland)
Data sources and data collection methods
This study employed both qualitative and quantitative data collection methods as recommended by Neuman . The qualitative data at community level were collected through focus group discussions, key informant interviews, and observations. The focus group discussions for this study were held with separate groups of elders, youth and women in each Kebele comprising 6–10 individuals per group. The sessions were moderated by the researcher using a checklist including climate change parameters in the area, the resultant impact, farmers’ response, and what factors influenced farmers’ adaptation decisions. Similarly, key informant interviews were held with knowledgeable people from the community, including the agricultural staff, administrators from government offices, and NGOs. These were individuals who have access to information on weather forecasts, climate change impact, and constraints to adapting to climate change. In addition, data at the household level were collected through a household survey using structured questionnaires. Those were initially pretested to check their validity and appropriateness. For pretesting the questionnaire, nine households from non-sampled Kebeles were identified and interviewed prior to the actual interview of the target sample households. This allowed the restructuring of questions before intensive data collection. Based on the limitations identified in the pretest, the questionnaires were then amended and enriched for the actual interview. The sampling size for the households’ survey was determined using the rule N ≥ 50 + 8m  in order to assure that the econometric model could be estimated with sufficient degrees of freedom, where N = sample size, and m = number of explanatory variables. Consequently, a total of 200 sample households were selected and interviewed: 70 from Merarow Hawilo (high altitude Kebele), 53 from Kersa Elala (mid-altitude Kebele), and 77 Mudi Arjo (low altitude Kebele). The local language, Afan Oromo, was used for effective communication for the household survey, focus group discussions and key informant interviews. Research assistants fluent in Afan Oromo and with good knowledge of local traditions were recruited and trained before conducting the survey.
Descriptive data analysis
In this study, demographic and socioeconomic data were summarized and presented using descriptive statistics such as frequency, percentage, graphs, figures, and tables. Also t test and Chi-square tests were used in order to compare the difference among groups for different socioeconomic and demographic variables. This test is mainly employed to know whether the difference is statistically significant or not. For this analysis, both Microsoft Excel and STATA version 13 were used.
Econometric data analysis
In this study, the determinants of farmers’ adaptation decisions to climate change were analyzed using a multinomial logit (MNL) . In this study, the method was used to analyze the choices the farmers make regarding crop- and livestock-based adaptation strategies and what factors determine those choices. The MNL model was used based on the previous literature on determinants of farmers’ adaptation to climate change [14, 30]. This model suits such type of analysis as it permits the analysis of decisions across more than two categories, allowing the determination of choice probabilities for different categories [31, 32]. However, the model requires that households are associated with only their most preferred option from a given set of adaptation strategies. Unbiased and consistent parameter estimates using this model need to assume independence of irrelevant alternatives that requires that the probability of using a certain adaptation method by a given household is independent from the probability of choosing another adaptation method. We are aware that collecting and using only the most preferred adaptation option for each household risks under-emphasizing the known importance to smallholder farmers of using multiple adaptation strategies , but the approach has allowed a high level of specification of the relations between adaptation strategies and underlying socioeconomic variables.
The model is specified as follows.
Variable description and hypothesis for the impact of the independent variables on dependent variables
Dummy, 1 = male, 0 = female
Total annual income
Access to market
Dummy, 1 = yes, 0 = no
Access to climate information
Dummy, 1 = yes, 0 = no
Access to extension
Dummy, 1 = yes, 0 = no
Continuous, Tropical livestock unit (TLU)
Marginal effect of marginal probabilities is the function of probabilities and measures the expected change in probabilities where particular adaptation choice is being made by a unit change of the independent variable from the mean .
Results and discussion
Smallholder farmers’ perceptions of climate change
Primary sources of information about climate change and its impacts
Climate change information sources
From radio broadcasting
From other farmers
Impact of climate change on smallholder farming
Climate change adaptation strategies by smallholder farmers
Primary adaptation strategies to climate change and the proportion of respondents that practiced them
Number of households
Percent of households
Change in planting date
Intensive use of agricultural inputs
Crop and livestock integration
Soil and water conservation
No adaptation strategy used
The results in Table 4 show that the most important practice farmers used to reduce the impacts of climate change particularly in the lowland, was to change crop planting dates and crop varieties. In case of extreme drought, the farmers migrated to the highland areas for some time. Currently, storage of crop residues (maize straw) as an emergency feed in dry periods is a common practice. In addition, maintenance of grain reserves, crop diversification, and using early maturing crop varieties were some of the adaptation mechanisms. Similarly, in the highlands, smallholder farmers used various adaptation strategies to climate change. Here, crops like barley, peas and beans were performing poorly and some farmers had already reduced the portion of land allocated for such crops. In some cases, farmers had already stopped their production. On the other hand, majority of the farmers opted to grow other crops like teff and maize, which used to be typical midland agro-ecology crops. Nevertheless, the productivity of these new crops was reported to be low. In addition, cultivation of drought tolerant crops such as Enset (Ensete ventricosum) as a source of both food and livestock feed was becoming popular.
Farmers’ primary constraints to adapting to the changing climate
List of constraints
Total number of respondents
Respondents in %
Lack of climate forecasting information
Poor potential for irrigation
Lack of contact with extension personnel
Shortage of farm land
Shortage of labor for implement adaptation
Exposure or access to mass media
Shortage of necessary farm inputs
Low level of education
Shortage of money
The results in Table 4 show that although diverse climate change adaptation strategies exist in the area, the farmers were not practicing them to their full potential due to constraints. The major constraint was the low level of education. About 17% of the respondents reported a low level of education as the major constraint to adaptation to climate change (Table 5). This was followed by shortage of labor, lack of access to information through mass media, shortage of farm implements, and financial constraints, respectively. Lack of sufficient money hindered farmers from getting the necessary agricultural inputs. Also the farmers did not have sufficient family labor and were not able to employ laborers. Shortage of farmland has been associated with the limited capacity of farmer to intensify their agricultural production. Although irrigation has been practiced in the area for vegetable production, its extent is still limited and also does not apply to field crops. This is associated with the inability of farmers to use both surface and ground water due to limited technological and financial capacity. In this regard, farmers who used underground water for irrigation for vegetable production mentioned that they dug shallow wells of about 5–10 m deep. But they mentioned that underground water tables were receding progressively and they needed to dig deeper beyond 15 m, which needed specialized equipment and technology beyond their reach.
Determinants of farmers’ choices of adaptation strategies to climate change
Parameter estimates of multinomial logit model for climate change adaptation decision
Changing input use intensity
Change planting date
Integrating crop with livestock
Soil and water conservation
Access to market
Access to climate information
Access to extension
No adaptation option
Number of observation
Prob > χ 2
Pseudo R square
Marginal effect due to independent variables
Changing input use intensity
Change planting date
Integrating crop with livestock
Soil and water conservation
Access to market
Access to climate information
Access to extension
The results in Table 6 show that being a male-headed household increased the likelihood of tree planting, integrating crops with livestock, and soil and water conservation as adaptation strategies at 5 and 1% significance levels compared to the base category. Specifically, the results show that being a male-headed household increased the probability of tree planting by 31%, crop livestock integration by 8%, and soil and water conservation by 12% as climate change adaptation strategies (Table 7). As hypothesized, male-headed households had better opportunities to practice adaptation measures than the female-headed households. This finding is similar to a study by Deressa et al.  done in another part of Ethiopia that analyzed farmer’s choices of climate change adaptation methods, which showed that male-headed households could be more likely to have access to technologies and climate change information than female-headed households. As a result, they were in a better position to practice diverse adaptation strategies than the female-headed ones .
The age of the household head had positively impacted the decision to practice some of the adaptation strategies and negatively in the case of others (Table 6). In this regard, age is positively related with the decision to intensify agricultural inputs. This means that as the age of the household head increases by a year, the probability of the households practicing agricultural intensification increases by 9%. However, the household head is not highly related with the probability of the household adapting to climate change by tree planting. This means that as the age of the household head increases by one year, the probability of the household planting trees will increase by 2.2% (Table 7). According to the findings, a unit increase in age of the household head resulted in a 9% increase in the probability of practicing soil and water conservation, whereas it resulted in a 12% increase in the practice of changing crop varieties as a climate change adaptation strategy.
The result in Table 6 shows that education has a positive effect on farmers’ adaptation strategies and hence, it significantly increases adaptation options with a 1% probability level. The marginal effect in Table 7 shows that a unit increase in number of years of education could increase by 2% of the likelihood of adopting crop diversification, 1.4% change in planting date, 3.1% tree planting and 2% integrating crop with livestock production as adaptation measures. This is because educated farmers are expected to adopt new technologies based on their awareness of the potential benefits from the proposed climate change adaptation measures .
Family size has a significant and positive effect on climate change adaptation, increasing the probability (p < 0.01) of planting food and fodder trees, integrating crop with livestock, and soil and water conservation measures (Table 6). The marginal effect result in Table 7 shows that a unit increase in productive family members increases the likelihood of adopting the aforementioned adaptation strategies by 1.3, 2.35 and 4%, respectively. According to Kurukulasuriya and Mendelsohn  and Gbetibouo , the probable reason is that larger family size and a larger number of productive household members increase agricultural production because it is associated with labor-intensive agricultural practices. Thus, household size has a significant association with some of the adaptation categories.
The result in Table 6 show that farming experience has a positive effect on some climate change adaptation strategies. It helped to stimulate response to the negative effects of climate change on agriculture. This is because more experienced farmers are assumed to have better knowledge about weather information and its implication on agricultural practices.
Farm size has a positive and significant association with most of the adaptation strategies. That is, as the size of farmland increases, the probability of planting different fodder trees and integrating crop with livestock production increases. Farm size has therefore positively and significantly increased the likelihood of adaptation to climate change . Furthermore, large farm sizes provide an opportunity for diversification of their crop and livestock enterprises, and it can help to distribute risks associated with unpredictable weather.
The results in Table 6 show that income of households has a positive and significant effect on changing farm input use intensity, integrating crops with livestock, and water conservation practices at a 10% level of significance. The marginal effect result in Table 7 shows that a unit increase in household income can increase the likelihood of use of necessary farm inputs and soil and water conservation practices by 0.8%. This finding is consistent with a study by Negash  which found that income has a positive relation with soil conservation measures, changes in planting date and use of crop diversification.
Access to input and output markets has a positive and significant effect on farmer input intensity and crop diversification at 10% significance level (Table 6). Easy access to input and output market increases the likelihood of changing input use intensity and crop diversification by 2.6% (Table 7). Market access could help farmers to buy fertilizer, pesticides, and improved crop varieties.
Access to climate information is an important variable that affects adaptation options. The results in Table 6 show that as expected, access to climate information had impacted adaptation to climate change. That is, a farmer who had better access to weather information (i.e., seasonal or mid-term forecasting) made better informed adaptation decision. Smallholder farmers who had access to weather information had a higher probability of implementing climate change adaptation strategies such as late and early planting, use of early maturing crops, planting food and fodder trees, and soil and water conservation measures at 1% level of significance. Being well informed about rainfall and temperature variability increased the likelihood of shifting planting date adjustments by 39% (Table 7). These findings are similar to the findings from various studies [15, 37, 39, 42, 46].
The result in Table 6 indicates that access to extension is positively and significantly related with adaptation options. As expected by the researchers, access to extension services increases the probability of adopting different adaptation practices. Having access to extension packages increased the likelihood of implementing soil and water conservation by 35.4%, tree planting by 5%, crop diversification by 18.55% and changing planting date by 19.3% (Table 7). In this regard, the result from the descriptive statistics shows that about 94% of the households had the opportunity to use crop and livestock extension packages. According to Nhemachena , better access to crop and livestock extension services has a strong and positive impact on climate adaptation strategies.
Livestock and crop production are the main economic activities in the area. The result in Table 6 indicated that livestock production has a positive association with the adoption of climate change adaptation strategies such as adjustment of planting season, integrating crops with livestock rearing and soil and water conservation practices at 5% level of significance. A number of studies have shown that livestock ownership has a positive association with the adaptation measures aforementioned [42, 48, 49]. However, the number of livestock is found to be negatively related with crop diversification, planting date adjustment and other agronomic activities .
The results show that the majority of the farmers have perceived changes in rainfall and experienced the effects of a changing climate over a period of two decades. That is, extended dry periods and declining precipitation are more frequent across the agro-ecologies in the district. As a result, both livestock and crop production by smallholder farmers have already been adversely affected. The farmers are trying to adapt through the use of improved agricultural practices like increasing on-farm tree planting, soil and water conservation, adjustment of planting dates, crop diversification, improved crop varieties, and use of agricultural inputs like fertilizers and pesticides. Farmers’ capacity to choose effective adaptation options is influenced by household demography, as well as positively by farm size, income, access to markets, access to climate information and extension, and livestock production. This implies the need to support the indigenous adaptation strategies of the smallholder farmers with a wide range of institutional, policy, and technology support, some of it targeted on smaller, poorer or female-headed households. In this case the role of government and NGOs is imperative. As the rainy seasons are recently becoming more and more unpredictable and uncertain, depending on rainfed agriculture in the area is less unlikely and hence policy driven actions to provide irrigation facilities based on both ground and surface water are vital. Moreover, creating opportunities for non-farm income sources is important as this helps them to engage in those activities that are less sensitive to climate change. Furthermore, providing climate change information, extension services, and creating access to markets are crucial. Therefore, including these activities in the existing formal extension channels of the Ministry of Agriculture and other line ministries will be useful to farmers.
gross domestic product
meters above sea level
AB designed the data collection tools, undertook fieldwork and most of the analysis, and developed the manuscript. JR contributed in developing the data collection tools, survey design and writing of the manuscript. TW and JM contributed to the research design, analysis, reviewed and made editorial comments on the draft manuscript. All the authors read and approved the final manuscript.
The authors are grateful for the financial support from the Department for International Development (DfID) under the Climate Impact Research Capacity and Leadership Enhancement (CIRCLE) programme for this study. They are also grateful to the International Livestock Research Institute (ILRI), for hosting the CIRCLE Fellow, within the CGIAR Research Program for Climate Change, Agriculture and Food Security (CCAFS). In addition to that the authors would like to acknowledge Wondo Genet College of Forestry and Natural Resource, Hawassa University for the necessary support during the field work.
The authors declare they have no competing interests.
Consent for publication
The authors obtained permission from all participants in Arsi Negelle district, to publish their data.
Ethical approval and consent to participate
Consent to participate was received from everyone interviewed in Arsi Negelle district, Ethiopia. A research committee from Ethiopia’s Hawassa University and the International Livestock Research Institute (ILRI) was informed of the study.
This project was funded by Department for International Development (DfID) and the Climate Impact Research Capacity and Leadership Enhancement (CIRCLE) programme.
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