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Identifying agricultural disaster risk zones for future climate actions

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  • Nkongho Ayuketang Arreyndip

Abstract

Identifying agricultural disaster risk regions before the occurrence of climate-related disasters is critical for early mitigation planning. This paper aims to identify these regions based on data from the Food and Agriculture Organization of the United Nations (FAO), the bilateral and multilateral trade network data of the World Integrated Trade Solution(WITS) and the agent-based economic model Acclimate. By applying a uniform forcing across agricultural sectors of some breadbasket regions (US, EU and China), when single and simultaneous extreme weather events occur, such as the 2018 European heatwave, production and consumption value losses and gains are calculated at regional and global levels. Comparing the FAO data sets, WITS, and Acclimate’s production value losses, the results show a strong dependence of agricultural production losses on a region’s output and connectivity level in the global supply and trade network. While India, Brazil, Russia, Canada, Australia, and Iran are highly vulnerable, the imposition of export restrictions to compensate for demand shortfalls makes Sub-Saharan Africa the most vulnerable region, as it is heavily dependent on agricultural imports. In addition, simultaneous extreme weather events can exacerbate the loss of value of agricultural production relative to single extreme weather events. Agricultural practices to increase production such as smart farming, increased investment in plantation agriculture, and diversification of trading partners can help mitigate future food security risks in Sub-Saharan Africa and other agricultural import-dependent regions.

Suggested Citation

  • Nkongho Ayuketang Arreyndip, 2021. "Identifying agricultural disaster risk zones for future climate actions," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-16, December.
  • Handle: RePEc:plo:pone00:0260430
    DOI: 10.1371/journal.pone.0260430
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    References listed on IDEAS

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