Collecting the Strategies to Stabilize the Livelihood of Small-Scale Farmers and Training Common Strategies Considering Sustainability and Vulnerability in Drought Conditions

Document Type : Research Paper

Authors

1 Khuzestan Agricultural Sciences and Natural Resources University

2 Department of Agricultural Management and Development, University of Tehran

Abstract

This research conducted with the overall object of collecting the Strategies to Stabilize the Livelihood of Small-Scale Farmers in Drought Conditions in Kurdistan Province. Based on the results of the research, the most important strengths and weaknesses of stabilizing livelihood in drought conditions were "good infrastructure, diversification of production and development of complementary and non-farm activities in the province" and "reduction of economic and productive power of agricultural families due to repeated drought" in order. Also, the most paramount opportunities and threats in this field were "development and promotion of drought insurance in the country (cattle, pasture, and crops)" and"lack of organizational structure to monitor the effects of climate change on rural livelihoods." After determining appropriate strategies using quantitative matrix management (QSPM) the attractiveness of each of the strategies identified that the most important strategies were"diversification of sources of livelihood and non-farm activities associated with the greenhouse farming using the right infrastructure in the province" and"collecting the proper plans of capacity-creating in agricultural communities to cope with risks through clustering of rural knowledge and development of the infrastructure needed to maintain livelihood". According to results the establishment of strategic space in Agricultural Organization was the strategy shift, withdrawal or reduction, development, and diversification, in order. Moreover, decision tree analysis showed that two variables, stability, and vulnerability could make agricultural strategies separated from each other with a prediction accuracy of 69.7%.

Keywords


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