Determinants of agroforestry technologies’ adoption for climate change adaptation in Muooni watershed, Machakos County, Kenya
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Date
2016-11
Authors
Mawuli, Asempah
Journal Title
Journal ISSN
Volume Title
Publisher
Kenyatta University
Abstract
Agroforestry presents opportunities for adaptation to the impacts of climate change
and variability in food security and livelihood development systems. According to
Intergovernmental Panel on Climate Change, Kenya is experiencing climate change
and projections suggest that there would be more extreme weather conditions by the
year 2030 and beyond. This would worsen the food insecurity and poverty situation
currently observed in arid and semi-arid districts such as Machakos County. Though
farmers in Muooni Watershed of Machakos County are practicing agroforestry for
livelihood diversification and climate change adaptation, full scale production is yet
to be achieved. This study sought to assess the determinants of agroforestry
technologies' adoption for climate change adaptation by smallholder farmers in
Muooni watershed of Machakos County, Kenya with the following specific
objectives: (1) to determine the agroforestry based climate change adaptation
technologies used by smallholder farmers in Muooni watershed; (2) to evaluate the
level of adoption of agroforestry based climate change adaptation technologies; (3) to
evaluate factors influencing the adoption of agroforestry based climate change
adaptation technologies and (4) to evaluate the opportunities and barriers in the
adoption of agroforestry based climate change adaptation technologies by smallholder
farmers in Muooni watershed. The study employed transects and cross-sectional
surveys where observational guide and questionnaires were used respectively in
surveying the catchment. Descriptive statistics was used to determine the agroforestry
technologies employed in the watershed while adoption formula and probit model
were used to evaluate the level of adoption and the factors influencing the adoption
respectively. Strengths, Weaknesses, Opportunities and Threat analysis were
conducted to establish the challenges and opportunities in adoption of agroforestry
technologies in the watershed. The study revealed 14. agroforestry based climate
change adaptation technologies in the watershed. It was established that, there is
difference in means of level of adoption between male (mean=42.4451,
SD=17.80319) and female agroforestry farmers (mean=41.2202, SD=18.29936) in
the study. However, independent-sample t-test showed no statistically significant
difference in the level of adoption of agroforestry based climate change adaptation
technologies by male and females agroforestry farmers in Muooni watershed as
hypothesised (t= 0.339, df= 98, p=0.735). Through probit regression analysis, it was
found that age, membership in cooperative group and monthly income were
statistically significant at probability level of 1% (p < .01), while sex, education,
farming experience, family size and access to training were statistically significant at
probability level of 5% (p < .05) . The overall result of the probit model shows a
significant difference at 5% level of probability. Through Strengths, Weaknesses,
Opportunities and Threat matrix analysis and Quantitative Strategy Planning Matrix
analysis, it was evident that the challenges in the watershed can be averted if the
available opportunities are harnessed. The study recommends introduction of other
agroforestry technologies to farmers and improvement in government and
institutional support systems focusing on factors that influence adoption of
agroforestry technologies. Finally, the watershed managers must prioritise activities
and interventions in the watershed in order to maximize the opportunities for climate
change adaptation through agroforestry in the watershed.
Description
A Thesis Submitted in Partial Fulfilment of the Requirements for the award of the Degree of Master of Science (Integrated Watershed Management) in the School of Pure and Applied
Sciences, Kenyatta University. November, 2016