TY - JOUR
T1 - Indigenous knowledge and science-based predictors reliability and its implication for climate adaptation in Ghana
AU - Ankrah, Daniel Adu
AU - Kwapong, Nana Afranaa
AU - Boateng, Seth Dankyi
N1 - Publisher Copyright:
© 2021 African Journal of Science, Technology, Innovation and Development.
PY - 2022
Y1 - 2022
N2 - The study examined the reliability of indigenous knowledge and science-based predictors of climate and how this influences smallholder farmers’ practices and adaptations in Ghana’s three regions (Northern, Western and Volta regions). Two districts were selected in each region: Builsa South and Zabzugu in Northern Region, Swefi Wiaso and Jomoro in Western Region, and Agotime-Ziope and Ketu North in Volta Region. The study employed purposive sampling involving 240 respondents. The findings show indigenous predictors of climate include the emergence of migratory birds, the direction of cloud formation, sun intensity, frog croaks and sprouting of new leaves on Emire, Shea, Tarmeranda and Baobab trees. An indigenous knowledge reliability index of 0.72 relative to 0.88 for science-based predictors was obtained, implying that both indigenous knowledge and science-based predictors are reliable indicators for forecasting weather. Indigenous knowledge and science-based predictors influence adaptation strategies through the cultivation of indigenous varieties, early or late planting, diversification of crops cultivated and the use of improved crop and drought-tolerant varieties. Governments in sub-Saharan Africa can consider tasking meteorological stations to harness indigenous and science-based predictors in daily forecasts towards adaptation and mitigation strategies.
AB - The study examined the reliability of indigenous knowledge and science-based predictors of climate and how this influences smallholder farmers’ practices and adaptations in Ghana’s three regions (Northern, Western and Volta regions). Two districts were selected in each region: Builsa South and Zabzugu in Northern Region, Swefi Wiaso and Jomoro in Western Region, and Agotime-Ziope and Ketu North in Volta Region. The study employed purposive sampling involving 240 respondents. The findings show indigenous predictors of climate include the emergence of migratory birds, the direction of cloud formation, sun intensity, frog croaks and sprouting of new leaves on Emire, Shea, Tarmeranda and Baobab trees. An indigenous knowledge reliability index of 0.72 relative to 0.88 for science-based predictors was obtained, implying that both indigenous knowledge and science-based predictors are reliable indicators for forecasting weather. Indigenous knowledge and science-based predictors influence adaptation strategies through the cultivation of indigenous varieties, early or late planting, diversification of crops cultivated and the use of improved crop and drought-tolerant varieties. Governments in sub-Saharan Africa can consider tasking meteorological stations to harness indigenous and science-based predictors in daily forecasts towards adaptation and mitigation strategies.
KW - climate change
KW - climate variability
KW - indigenous knowledge
KW - science-based predictors
KW - smallholder farmers
UR - http://www.scopus.com/inward/record.url?scp=85109811452&partnerID=8YFLogxK
U2 - 10.1080/20421338.2021.1923394
DO - 10.1080/20421338.2021.1923394
M3 - Article
AN - SCOPUS:85109811452
SN - 2042-1338
VL - 14
SP - 1007
EP - 1019
JO - African Journal of Science, Technology, Innovation and Development
JF - African Journal of Science, Technology, Innovation and Development
IS - 4
ER -