Doctoral Degrees (Rural resource management)
Permanent URI for this collectionhttps://hdl.handle.net/10413/13241
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Browsing Doctoral Degrees (Rural resource management) by Subject "Indigenous knowledge systems."
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Item The role of indigenous knowledge systems in seasonal prediction and adaptation to climate change and variability amongst smallholder farmers in Bikita, Zimbabwe.(2018) Mafongoya, Owen.; Mafongoya, Paramu L.; Mudhara, Maxwell.Climate change and variability have serious threats on rainfed agriculture in Zimbabwe. Poor and vulnerable smallholder farmers are facing serious food insecurity. Vulnerability to droughts is worsened by poverty, limited financial capital and access to technology. These factors limit their ability to cope, adapt and build resilience to climate change shocks and stresses. Local farmers’ adaptive potential, planning and preparedness are affected because of absence of adequate seasonal forecasting information. Smallholder farmers usually get forecasting information from indigenous knowledge indicators and scientific forecasts. Due to limited technology, they rely more on indigenous indicators. This study scrutinized local farmer vulnerability and the subsequent indigenous adaptation strategies used in coping with climate change risks and hazards. In using indigenous knowledge in coping and adaptation, the study interrogated the role of social capital and local institutions in reducing their vulnerability to disasters. The role of social capital and local institutions was scrutinized in the context local farmer indigenous knowledge and adaptation. Data in this study was collected using Focus Group Discussions, key informant interviews and structured questionnaires. The collected data was discussed based on the Sustainable Livelihoods Framework. Results revealed majority of smallholder farmers, particularly women, are vulnerable to droughts and diseases. Their adaptive potential is constrained by their limited access weather and seasonal information. Seasonal forecasting information helps them in planning and making decisions which reduces vulnerability to climate change risks and hazards. Despite the presence of multiple indigenous indicators for seasonal forecasting, seasonal information still remains problematic for local farmers. Unreliability of some of the indigenous indicators and other factors such as modern science, christianity, western education and scientific seasonal forecasting are negatively affecting the use indigenous indicators in seasonal forecasting. On another level of adaptation, using social capital and local institutions is critical. Some farmers’ failure in reviving indigenous based social capital is crippling their potential of self-help adaptation strategies. Furthermore, some intervening local institutions are not premising their adaptation strategies much on indigenous strategies. In areas where local farmers invest in social capital and local institutions include indigenous knowledge systems, vulnerability is reduced. It can be concluded that use of indigenous knowledge systems is critical for sustainable adaptation of rural poor and vulnerable smallholder farmers. It can be recommended that the government needs to encourage and incorporate indigenous knowledge into adaptation plans and actions, and integrate indigenous knowledge into scientific seasonal forecasting and adaptation strategies. Integrating local knowledge and scientific strategies would reduce vulnerability and increase local farmer resilience and adaptive capacity against climate change shocks and stresses.