A regional nuclear conflict would compromise global food security

Abstract

A limited nuclear war between India and Pakistan could ignite fires large enough to emit more than 5 Tg of soot into the stratosphere. Climate model simulations have shown severe resulting climate perturbations with declines in global mean temperature by 1.8 °C and precipitation by 8%, for at least 5 y. Here we evaluate impacts for the global food system. Six harmonized state-of-the-art crop models show that global caloric production from maize, wheat, rice, and soybean falls by 13 (±1)%, 11 (±8)%, 3 (±5)%, and 17 (±2)% over 5 y. Total single-year losses of 12 (±4)% quadruple the largest observed historical anomaly and exceed impacts caused by historic droughts and volcanic eruptions. Colder temperatures drive losses more than changes in precipitation and solar radiation, leading to strongest impacts in temperate regions poleward of 30°N, including the United States, Europe, and China for 10 to 15 y. Integrated food trade network analyses show that domestic reserves and global trade can largely buffer the production anomaly in the first year. Persistent multiyear losses, however, would constrain domestic food availability and propagate to the Global South, especially to food-insecure countries. By year 5, maize and wheat availability would decrease by 13% globally and by more than 20% in 71 countries with a cumulative population of 1.3 billion people. In view of increasing instability in South Asia, this study shows that a regional conflict using <1% of the worldwide nuclear arsenal could have adverse consequences for global food security unmatched in modern history.

Keywords: India–Pakistan conflict; cold temperature yield response; food system shock; global gridded crop model intercomparison (GGCMI); multiple breadbasket failure.

Fig. 1.

Nuclear conflict-induced global climate perturbations. Changes in (A) 2-m air temperature (°C), (B) precipitation (%), and (C) surface incoming shortwave and (D) longwave solar radiation (%) are shown across 15 postconflict years for two climate simulation sets (climate forcing 1 and 2), with three ensemble members each (runs a–c). Changes are shown as absolute (temperature) and relative (all other variables) differences between control and perturbed global mean values, calculated over the global land area. The average year 1 to 5 change is highlighted on top of the shaded boxes.

Fig. 2.

Postconflict change of global staple crop production. Conflict-related impacts on global caloric production of maize, wheat, rice, soybean, and their total are shown for combined (red), rainfed (gray), and irrigated (blue) production. Changes are shown for the crop model ensemble mean (colored bars; the SD is indicated by horizontal lines) for the postconflict year with largest “combined” declines per crop (respective year is shown on top of the bar). All data are averaged across climate simulation sets. Black bars centered on the zero line illustrate the SD of unperturbed historical variability (1981 to 2009). Circled percentages highlight the 5-y postconflict average change. “Total” refers to the cumulated caloric production of the four crops, and percentage numbers in parentheses and the circle sizes indicate the respective fraction of current total global cereal production (including soybean). The bar width for total is increased to emphasize main results.

Fig. 3.

Spatial and temporal patterns of maize impacts. (A) Relative maize yield changes (%) are shown as 5-y postconflict averages across the crop and climate model ensemble. (B–K) Time-series Insets illustrate aggregated changes in maize production (%) at (B) the global level and (C–K) nine world regions, for the participating crop models (line type), and two climate simulation sets (line color; climate forcing 1 [gray] and climate forcing 2 [yellow]), respectively. Mean years 1 to 5 production changes are highlighted on top of the shaded boxes. The contribution of each world region to global maize production is indicated in the bottom-right corner of the regional Insets. Grid cells (0.5°) with $<$10 ha maize harvested area are masked from the map (white) and hatching indicates cells in which not all crop models agree on the sign of simulated yield change. India and Pakistan are excluded.

Fig. 4.

Latitudinal profile of crop yield changes and cropland extent. Current cropland extent of the staple crops (A) maize, (B) wheat, (C) rice, and (D) soybean is shown across latitude bands as fractions of the crop-specific global extent (top x axis). Relative changes (5-y postconflict average) in crop yields are shown as latitude averages, based on rainfed crop simulations in all grid cells, unconstrained by current cropland areas (bottom x axis). The overlaps of gray and tan indicate areas with potentially adverse effects on current crop production. Yield data are presented as climate and crop model averages.

Fig. 5.

Maize yield and production sensitivity to individually perturbed climate drivers. Changes in simulated maize yield (%) for climate input variables perturbed one at a time: (A) air temperature, (B) precipitation, and (C) surface incoming shortwave solar radiation, filled in with control AgMERRA climate. (D) The combined perturbation has all four drivers perturbed collectively. Percentage numbers at the top of each plot indicate the respective global caloric production change. This sensitivity study is performed for climate model simulation CF1_a and by the crop models EPIC-BOKU, GEPIC, LPJmL, pDSSAT, and PEPIC. Data are shown as the mean across crop models, post conflict years 1 to 5, 29 y of historical climatology, and rainfed and irrigated systems. India and Pakistan are excluded.

Fig. 6.

Initial and postconflict food reserves and domestic use. For maize and wheat combined, stocks-to-use ratios (%)—food reserves relative to domestic use—are shown at the country level for (A) current conditions (2006 to 2008 average), (C) the postconflict year 1, and (E) postconflict year 4. B, D, and F show maize and wheat domestic use, as (B) absolute preconflict kilocalories per capita and (D and F) relative postconflict changes (%) for (D) year 1 and (F) year 4, which is the year with largest declines (SI Appendix, Figs. S12 and S13). The trade network analysis evaluates national caloric crop production changes averaged across crop and climate models, but individually for each crop (without substitution between crops). India and Pakistan are excluded.