Identifying agricultural disaster risk zones for future climate actions

China are simultaneously forced. For China, the Chinese economy suffers the highest produc- tion value losses when the US and China are simultaneously forced while its highest produc- tion value rise comes when the EU and the US are simultaneously forced. Globally (World), the global economy suffers the highest production value drop when the US alone is forced while the highest rise in production value comes when the EU and China are simultaneously forced. In this same table (Table 2), we equally see that the EU economy suffers the highest con- sumption value losses when all three regions are simultaneously 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 economy suffers the highest con- sumption value losses when all three regions are simultaneously shocked by the extreme weather event while the highest consumption value rise in this region is experienced when the EU alone is forced. For China, the Chinese economy suffers the highest consumption value losses when the US and China are simultaneously forced while its highest consumption value rise comes when the EU and the US are simultaneously forced. Globally (World), the global economy suffers the highest consumption value drop when all three regions are simulta- neously forced while the highest rise in consumption value comes when the EU and China are simultaneously forced. In Fig 5, a share of the median agricultural production and consumption value losses when

aggregated over all concurrent extreme weather scenarios is presented. Fig 5(a) is the produc- tion value losses while Fig 5(b) is the corresponding consumption value losses. Details of the global effects of the each concurrent forcing scenario is presented in Fig 7 in S1 File. From Eqs (1) and (2), negative values(red) implies a rise in production/consumption value while positive values (blue) imply a drop in production/consumption value. Here, we see that there is a global drop in production value and a global rise in consumption value during these extreme weather events. A drop in production value will lead to losses at the level of the farmers. In other not to directly bear the losses by the farmers, these losses will be transferred to consumers in the form of higher prices (price shocks). This figure equally shows India, Brazil, China, Canada, Russia, Iran will suffer the most production value losses during concurrent extreme weather events while Brazil, India, Russia, Canada Australia, Iran, South Africa Japan, Indonesia, Argentina will generally experience price shocks. In Fig 6, a comparative analysis of the impacts of the various forcing scenarios on the mean agricultural production Fig 6(a) and consumption values losses Fig 6(b) to test the strength of the various forcing is performed. Here, we see that concurrent extreme weather events in all three breadbasket regions will lead to the highest agricultural consumption value losses and production value gains while the least repercussion is felt when China alone is shocked.

Table 3. Average production value and consumption value losses in all economic sectors for all forcing scenarios. A comparative analysis is done over the key agricul- tural regions. Values are in Billion USD. Parameters Key regions EU US CHN EU-US EU-CHN US-CHN ALL Production value losses EU28 270176.73 24853.214 6707.73 213966.16 124159.72 -130923.8 211502.13 USA -24515.68 157130.23 -288.755 153347.24 -39316.55 239482.13 362005.71 CHN -45947.04 -33253.76 8520.98 -128955.66 111829.99 337713.99 180484.5 World 122660.61 148226.155 12407.3 74851.45 -377620.54 -61217.25 104810.96 Consumption value losses EU28 125557.66 21795.25 5337.77 115114.34 81388.23 -7837.3 160424.93 USA -11219.46 64237.42 -102.64 60825.45 -6528.27 114750.36 195370.45 CHN -13924.12 -15753.06 2734.23 -63012.83 26089.3 154549.6 105844.62 World 99748.86 96257.19 12418.95 83229.71 -85313.04 198638.41 381174.07 https://doi.org/10.1371/journal.pone.0260430.t003 PLOS ONE Identifying agricultural disaster risk zones for future climate actions PLOS ONE | https://doi.org/10.1371/journal.pone.0260430 December 2, 2021 10 / 16