Southwestern Kenya’s smallholder dairy farmers’ climate change perceptions, knowledge and adaptation
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Publication Date
2024-01Author
Odhiambo, Charles Okech
Wasike, Chrilukovian Bwire
Ogindo, Harun Okello
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Show full item recordAbstract/ Overview
Globally, climate change (CC) adaptation is critical as CC compounds smallholder dairy farmers’
challenges. Farmers’ CC perceptions and knowledge could influence their CC adaptations. This study
in Southwestern Kenya sought to establish smallholder dairy farmers’ CC perceptions and CC
knowledge level and their relationships to CC adaptations. Concurrent Fixed Mixed Methods was used
to collect data from 367 smallholder dairy farmers obtained by multi-stage sampling. Purposive
sampling was used to pick qualitative study respondents. Binary logistic regression and Framework
methods were used in data analysis. Meteorological data indicated an increase in both day and night
temperature (0.3oC) and mean annual rainfall (195 mm). Respondents perceived CC had high impact on
dairy cattle health (61.0%) and feed availability (42.2%), and moderate effect on labour requirements
(42.2%). Adaptation practices included mixed farming (96.5%), non-intensive production (95.1%), using
household labour (94.6%), reducing herd size to 2 (92.9%), establishing own fodder (92.4%), rearing
cross-bred cattle (87.7%), mainly of non-Friesian blood and their crosses (87.5), and maintaining an
increasing trend in milk income (68.4%). Perceptions of decreased night temperatures significantly
influenced mixed farming (Adjusted Odds=0.13; p=0.04) and rearing of non-Friesian breeds and their
crosses (Adjusted Odds=0.19; p=0.01). Perceptions of no change in night temperatures significantly
influenced rearing of non-Friesian breeds and their crosses (Adjusted Odds=0.08; p=0.02); and
perceptions that distribution of short rains got worse significantly influenced adoption of own fodder
(Adjusted Odds=0.02; p=0.01). Majority (61%) of respondents had above-average CC knowledge, with
the total score greatly influencing dairy herd size (Adjusted Odds=0.11; p=0.02). Governments should
invest in climate forecasting infrastructure and incorporate indigenous CC knowledge in CC adaption
plans, strategies and policies.