Abstract
Climate change is primarily detrimental to the agriculture sector and the influence of climate change is decreased by using appropriate adaptation strategies. Studies on climate change adaptation recognize the importance of specific area-based research for designing policies to respond to climate change. This study, therefore, was applied at the district level to examine farmers’ preference for climate change adaptation strategies and the factors determining their preference. The objective of this study is to identify and model factors that influence farmers’ preference of adaptation strategies to counter the impacts of climate change in the case of Dera District, North Shoa, Oromia, Ethiopia. Cross-sectional study design was used with the questionnaire being administered on a multistage sample of 460 households from selected kebeles in the district. Descriptive statistics, multinomial logit, and count regression analysis were used to analyze the collected data. The study revealed that the farmers perceived that temperature had been increasing and rainfall had been decreasing over the last 10 years. The results also indicated that planting trees was the most preferred and frequently applied adaptation strategy to climate change while changing planting dates was the least. The results from the multinomial logit, Poisson regression, and negative binomial analysis showed that age, source of information, household size, education level of household head, distance to output market, distance to input market, agroecological locations of the farm, tropical livestock unit, size of the farm, tenure, grade of the farm, distance of the farm, formal extension service, farmer-to-farmer extension, credit service, rainfall expectation, and temperature expectations were significant factors in determining the adaptation strategies preferred by the farmers.
Highlights
IntroductionClimate change is a long-term shift in the statistics of weather (including its averages) for a given place and time
Climate change is a long-term shift in the statistics of weather for a given place and time
Using Different Enterprises (UDV). e statistical tests of significance of individual coefficient of using different enterprises indicators are based on Wald Chi-square and P value of respective coefficients as shown in Appendix 1 Table 4. e result revealed that age of household head, source of information, household size, distance of output market, distance of input market, agroecological location of the farm, size of the farm, number of livestock, grade of the farm, distance of the farm, extension service, credit service, farmer-to-farmer extension, rainfall expectation, and temperature expectation were significant factors affecting using different enterprises as adaptation options to climate change at 5% level of significance. e Poisson regression analysis revealed the following result for using different enterprises as adaptation option
Summary
Climate change is a long-term shift in the statistics of weather (including its averages) for a given place and time. Agriculture places a heavy burden on the environment in the process of providing humanity with food and fiber, while climate is the primary determinant of agricultural productivity. Interest in this issue has motivated a substantial body of research on climate change, and agriculture over the past decade [3]. Poisson regression assumes a Poisson distribution, characterized by a substantial positive skewness with variance equal to mean. If the variance is larger than the mean, it induces deflated standard errors and inflated standardized normal values, resulting in increased Type I errors that make Poisson regression less adequate
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
