The Perception of and Adaptation to Climate Change among Cocoa Farm Households in Ondo State, Nigeria
The study was conducted to examine the perception of and adaptation to climate change among cocoa farmers in Ondo State, Nigeria. Also, determinants of farmers’ level of perception and adaptation to change in climatic conditions were examined. Simple random sampling technique was used to select 200 farmers but after removing cases of incomplete or non-response, the final sample size came to 160 cocoa farmers. Descriptive statistics were used to analyse the farmers’ socio-economics characteristics while Heckman’s two-step procedure was used to identify the determinants of respondents’ perception and adaptation to climate change. The results revealed that the cocoa farmers’ population was ageing and cocoa production in the study area was dominated by men. The household size ranged between 1 and 20 persons while the mean was 8 persons. The majority of the farmers solely made use of hired labour. The average farm size was 7 hectares while 83.75 percent of cocoa farmers had no access to credit. Most of the respondents perceived climate change in the study area. In order to adapt to climate change, 10 different types of adaptation strategies were used by 83.75% of the farmers while 16.25% did nothing. 7 variables (age, education, farming experience, household size, farm size, access to extension services, and distance to farm input purchasing market) significantly determined whether or not cocoa farmers perceive climate change while again another 7 independent variables (age, education, farming experience, farm size, access to extension services, access to credit and training on climate change) significantly determined whether or not they would adapt to it. The study therefore, recommends that credit should be made available to the farmers and an effective extension service system should be put in place.
This work is licensed under Creative Commons Attribution 3.0 License.
Academic Journal of Interdisciplinary Studies ISSN 2281 3993(Print) ISSN 2281-4612(Online)
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