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Weather and Climate Extremes
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Weather and Climate Extremes
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Determinants of farmers' perceptions of climate variability, mitigation, and adaptation strategies in the central highlands of Kenya

Authors: Franklin S. Mairura; Collins M. Musafiri; Milka N. Kiboi; Joseph M. Macharia; Onesmus K. Ng'etich; Chris A. Shisanya; Jeremiah M. Okeyo; +3 Authors

Determinants of farmers' perceptions of climate variability, mitigation, and adaptation strategies in the central highlands of Kenya

Abstract

Climate variability in recent decades has intensified in the SSA region, which makes it imperative to explore adequate adaptation and mitigation strategies to offset its current and future adverse impacts. Farmers' perception of climate variability can significantly influence their coping, mitigation, and adaptation potential. This study assessed farmers' perceptions of indicators and consequences of climate variability and explored factors influencing their perception of climate variability and adoption of climate coping strategies. A cross-sectional survey design was used to sample 300 farmers in the Central Highlands of Kenya. Binary logistic regression models were used to determine factors that influenced the perception of climate variability, adaptation, and mitigation strategies based on three predictor sets, including socioeconomic, institutional, and environmental dimensions. Three climate adaptation and mitigation strategy groups adopted by farmers, including crop adjustment, nutrient management, and soil and water management practices, were subjected to binary logistic regression models. The core determinants of farmers' perception of climate variability included tropical livestock unit (TLU, p = 0.008), access to agricultural training (p = 0.022), change in agricultural production (p = 0.005), change in forest cover (p = 0.014), soil fertility status (p = 0.039), and perceptions of soil erosion (p = 0.001). Most farmers reported changes in all climatic indicators during the decade preceding the survey, including increasing temperature (80%), reduced precipitation (78%), and declining season lengths (76%). There were significant relationships between climate variability perceptions and coping strategies, with the soil and water management set showing stronger links with climate perceptions compared to crop adjustment and nutrient management strategies. Critical mitigation and adaptation strategies to cope with climate variability implemented by farmers included the use of fertilizer and manure in combination (71%), terracing (66%), and crop rotation (60%). Farmers' perceptions significantly determined the adoption of climate-smart agriculture technologies, and environmental determinants strongly influenced climate variability coping strategies. Therefore, while formulating climate sustainability-related policies, farmers' perceptions should be considered.

Country
Kenya
Keywords

Climate-smart agriculture, 333, Adaptation potential, Meteorology. Climatology, Greenhouse gas emissions, QC851-999, Climate variability

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    48
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
48
Top 1%
Top 10%
Top 1%
gold