Wheat trade tends to happen between countries with contrasting extreme weather stress and synchronous yield variation

Countries with more different extreme weather stress and synchronous yield tend to be trade partners, indicating a vulnerability in global food security, according to a statistical and machine learning analysis of international wheat trade networks. Extreme weather poses a major challenge to global food security by causing sharp drops in crop yield and supply. International crop trade can potentially alleviate such challenge by reallocating crop commodities. However, the influence of extreme weather stress and synchronous crop yield anomalies on trade linkages among countries remains unexplored. Here we use the international wheat trade network, develop two network-based covariates (i.e., difference in extreme weather stress and short-term synchrony of yield fluctuations between countries), and test specialized statistical and machine-learning methods. We find that countries with larger differences in extreme weather stress and synchronous yield variations tend to be trade partners and with higher trade volumes, even after controlling for factors conventionally implemented in international trade models (e.g., production level and trade agreement). These findings highlight the need to improve the current international trade network by considering the patterns of extreme weather stress and yield synchrony among countries.

Automated summary

Countries with greater differences in extreme weather stress and synchronous crop yield variations tend to become trade partners, highlighting the vulnerability of global food security.