Identifying agricultural disaster risk zones for future climate actions

Next, a comparative study to investigate the strength of each forcing scenario on the agri- cultural and economic production and consumption value is carried out. In Table 2, the aver- age production value and consumption value losses in the agricultural sectors for all forcing scenarios (EU, US, CHN, EU-US, EU-CHN, US-CHN, and EU-US-CHN (ALL)) are pre- sented. A comparative analysis is done over the key agricultural regions and the World. Values are in Billion USD. Here, we see that the EU agricultural sector suffers the highest production value losses when the EU is individually shocked by the extreme weather event while the high- est production value rise in this region is experienced when all three regions are simulta- neously forced. For the US, the US agricultural sector suffers the highest production value losses when the US is individually shocked by the extreme weather event while the highest pro- duction value rise in this region is experienced when the EU and China (EU-CHN) are simul- taneously forced. For China, the Chinese agricultural sector suffers the highest production value losses when the US and China are simultaneously forced while its highest production value rise comes when the EU and the US are simultaneously forced. Globally (World), the agricultural production value rises in all forcing scenarios with the greatest rise seen when all three regions are simultaneously forced. In this same table (Table 2), we see that the EU agricultural sector suffers the highest con-

sumption value losses when the EU is individually shocked by the extreme weather event while the highest consumption value rise in this region is experienced when the US and China are simultaneously forced. For the US, the US agricultural sector suffers the highest consumption value losses when the US and China are simultaneously shocked by the extreme weather event while the highest consumption value rise in this region is experienced when the EU and China are simultaneously forced. For China, the Chinese agricultural sector suffers the highest con- sumption value losses when the US and China are simultaneously forced while its highest con- sumption value rise comes when the EU and the US are simultaneously forced. Globally (World), the agricultural consumption value drops in all forcing scenarios with the greatest drop seen when all three regions are simultaneously forced. In Table 3, the cascading average production value and consumption value losses in all eco- nomic sectors for all forcing scenarios (EU, US, CHN, EU-US, EU-CHN, US-CHN, and EU-US-CHN (ALL)) are equally presented. A comparative analysis is done over the key agri- cultural regions and the World. Values are in Billion USD. Here, we see that the EU economy suffers the highest production value losses when the EU is individually shocked by the extreme weather event while the highest production value rise in this region is experienced when the US and China are simultaneously forced. For the US, the US economy suffers the highest pro-

duction value losses when all three regions are simultaneously forced by the extreme weather event while the highest production value rise in this region is experienced when the EU and Table 2. Average production value and consumption value losses in the agricultural sectors for all forcing scenarios. A comparative analysis is done over the key agri- cultural regions. Values are in Billion USD. Parameters Key regions EU US CHN EU-US EU-CHN US-CHN ALL Production value losses EU28 57237.3 -31000.2 -2807.45 -3243.69 -108907.88 -245458.79 -172373.58 USA -24972.65 54086.47 -2021.31 42978.49 -119000.99 3864.0 -33448.95 CHN -49072.59 -44116.58 456.63 -142373.9 -81471.75 14405.99 -101610.68 World -128416.55 -103252.57 -14997.73 -358013.30 -976266.56 -936079.85 -1222640.33 Consumption value losses EU28 47466.83 -3715.05 36.8 35800.91 40156.09 -21421.66 36247.22 USA -4566.21 36355.54 -147.0 40152.94 -8811.98 50901.5 46592.79 CHN -9125.91 -6919.30 2046.11 -10925.74 78680.59 103044.01 93661.27 World 22841.38 26242.94 1812.67 53737.89 86180.55 89814.065 126860.13 https://doi.org/10.1371/journal.pone.0260430.t002 PLOS ONE Identifying agricultural disaster risk zones for future climate actions PLOS ONE | https://doi.org/10.1371/journal.pone.0260430 December 2, 2021 9 / 16