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http://ir.gzu.ac.zw:8080/xmlui/handle/123456789/777
Title: | Using Indigenous Knowledge Systems in Seasonal Prediction and Adapting to Climate Change Impacts in Bikita District in Zimbabwe |
Authors: | Mafongoya, Owen Mafongoya, Paramu Leslie Mudhara, Maxwell |
Keywords: | Indigenous indicators Forecasting Adaptation Decision-making |
Issue Date: | Apr-2021 |
Publisher: | Sage |
Series/Report no.: | Vol. 21;Issue 1 |
Abstract: | The use of indigenous knowledge systems (IKS) in seasonal forecasting and adaptation to devastating vagaries of climate change has gained attention in academic discourses. The debates opened contrasting views with the first overromanticizing IKS’ potential, while the other arguing that it has many setbacks. In this study, we interrogated IKS’ roles in seasonal forecasting and chances of informing adaptation among poorly resourced smallholder farmers in ward 24, Bikita. Using focus group discussions, in-depth interviews, and key informant interviews, we identified diverse indigenous indicators and interrogated how they subsequently inform adaptation. We noted that IKS is important in providing seasonal forecasting information, which is critical in making decisions in planning, designing cropping calendars, offering early warnings, as well informing preparedness against disasters. However, we also noted that IKS is under threat from Western education, Christianity, scientific seasonal forecasting (SSF), and climate change. These factors are challenging and reducing IKS’ reliability and hence increasing its susceptibility to disappearance. We concluded that IKS can be resuscitated if included in science education and policy frameworks. We recommended governments to formulate policy frameworks, that allow it to work well with SSF in reducing poorly resourced smallholder farmers’ vulnerability to climate change disasters. |
URI: | http://ir.gzu.ac.zw:8080/xmlui/handle/123456789/777 |
Appears in Collections: | Staff Articles |
Files in This Item:
File | Description | Size | Format | |
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Using Indigenous Knowledge Systems in Seasonal Prediction and Adapting to Climate Change Impacts in Bikita.pdf | 561.87 kB | Adobe PDF | View/Open |
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