Indigenous knowledge and science-based predictors reliability and its implication for climate adaptation in Ghana

Abstract

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.

Keywords:

• indigenous knowledge
• climate variability
• climate change
• smallholder farmers
• science-based predictors

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 Science-based predictors are based on the use of the process of enquiry involving scientific data in the prediction of climatic factors. The scientific data are based on information emanating from the Ghana Meteorological Agency (GMet) and Esoko. These predictors include information on temperature, rainfall, windspeed/direction, sunshine duration and cloud cover. Esoko is a private entity that transmits daily weather and market information to farmers. See Section 2.

2 Esoko is a private entity that collects and collates climatic information specific to geographical locations via daily text and voice messages to farmers.

3 NVivo is a qualitative data analysis software package used to organize and analyze qualitative data that include unstructured text, audio, images and video.