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BY-NC-ND 4.0 license Open Access Published by De Gruyter Open Access October 20, 2017

Integration of indigenous and scientific knowledge in climate adaptation in KwaZulu- Natal, South Africa

  • Myuri Basdew , Obert Jiri EMAIL logo and Paramu L Mafongoya

Abstract

Indigenous knowledge has for generations assisted rural subsistence farming communities adapt to climate change and make daily decisions regarding agriculture. This study was conducted in the rural community of Swayimane, uMshwathi Municipality, KwaZulu-Natal, South Africa. The main objective of the research was to determine the indigenous indicators used by rural farmers, identify the means through which seasonal climate information is disseminated and assess the strengths and weaknesses of indigenous and scientific knowledge. The other objective of the research was to evaluate the integration of indigenous and scientific weather forecasting. The research used 100 questionnaires which were administered to the subsistence farmers of the community. Focus group discussions and key informant interviews were conducted with small groups of individuals. Results showed that majority of the indigenous indicators related to rainfall and seasonal predictions. Also, seasonal scientific climate information was mainly disseminated via television and radio. Local farmers highlighted that indigenous knowledge was essential in predicting seasonal changes and rainfall and scientific knowledge was not trusted. Indigenous knowledge is transmitted by oral tradition, from generation to generation and mainly among the elderly, and, thinly, to the younger generation. Scientific information was thought to be too technical and difficult to comprehend. It can be concluded that subsistence farmers were open to the integration of scientific and indigenous weather forecasting. They highlighted that it would improve decision making concerning their agricultural activities.

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Received: 2017-3-13
Accepted: 2017-7-20
Published Online: 2017-10-20
Published in Print: 2017-10-26

© 2017

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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