Soybeans play a crucial role in global food security and international agricultural trade. As the world’s largest consumer and trader of soybeans, China faces significant external dependence on supply and concentration of import sources. In light of increasing uncertainties in the international political and economic landscape, risks within China’s soybean supply chain have become increasingly prominent, highlighting the need to explore the global soybean supply potential and optimize import strategies. In response to national food security strategic requirements and anticipated changes in global production capacity, the Global Agro-Ecological Zone (GAEZ) model and the multi-objective nonlinear programming model are used in this paper to estimate the potential of soybean yield increase globally. From dual perspectives of risk minimization and cost minimization, diversified soybean import schemes for China are proposed across three scopes: neighboring countries, countries along the Belt and Road Initiative (BRI), and globally. The results indicate that in the long term, the center of gravity for global soybean production capacity remains in the Americas; these areas, along with Europe and Africa, are key regions for China to expand its soybean import sources in the future. If all countries’ soybean production potentials are fully explored, China can achieve sufficient soybean supply by relying on neighboring countries as well as those countries participating in the BRI. Specifically, it is estimated that during the 2020s (2011–2040), the potential soybean production in the United States, Brazil, and Argentina could reach more than 290 million tons, 140 million tons, and 130 million tons, respectively, under scenarios of both yield increase and cultivated land expansion. Neighboring countries such as India and Russia also show significant potential, with India’s production potentially increasing by 42.8 million tons and Russia’s by 10.4 million tons. The results suggest that China can achieve a more balanced and secure import strategy by leveraging the production capabilities of countries in the Americas, Europe, and Africa while also fostering closer economic and agricultural cooperation with neighboring nations and BRI countries. Based on these findings, policy recommendations aimed at stabilizing and ensuring China’s soybean supply are discussed.

Amid mounting global food risks, the expansion of BRICS—an important multilateral platform for emerging markets and developing economies—has reshaped agricultural trade relations within BRICS, carrying profound implications for food security and sustainable agricultural development. This study aims to analyze the evolution of BRICS agricultural product trade networks to deliver empirical insights for coordinated agricultural governance among BRICS members. We adopt a social network analysis (SNA) and the quadratic assignment procedure (QAP) to examine BRICS agricultural product trade network characteristics and identify its driving factors. The results reveal that agricultural product trade within BRICS expanded markedly after BRICS enlargement, accompanied by declines in network density and reciprocity. Furthermore, nodes in this agricultural trade network show growing functional differentiation: Brazil serves as the core supply hub, China the primary demand hub, and Russia a vital connecting node. Community analysis indicates that the network has not evolved into closed geographic blocs; instead, cross-regional linkages give rise to a polycentric hierarchical structure. QAP estimates show that agricultural supply capacity dominated network configurations before enlargement, while food-security pressure and institutional distance exerted more pronounced impacts afterward. These findings provide empirical evidence and policy references for BRICS members to deepen agricultural trade cooperation, stabilize cross-border agricultural supply chains, and collectively safeguard food security.

Introduction: Driven by the dual forces of global climate change and sea-level rise, storm surge disasters have emerged as a primary external shock constraining the sustainable development of coastal socio-economic systems. Methods: Different from previous studies that mainly focus on average effects, this study uses panel data from 11 coastal provinces and municipalities in China from 2011 to 2023 and employs Tobit models, two-part models, panel threshold models, and fuzzy-set qualitative comparative analysis to examine the nonlinear characteristics and configurational pathways of direct economic losses from storm surges. Results: The results show that storm hazard intensity and coastal economic exposure are positively associated with direct economic losses from storm surges, whereas regional adaptive capacity shows a loss-mitigation effect. Direct economic losses exhibit evident nonlinear characteristics, and the loss-amplifying effect of storm hazard intensity increases once it exceeds the estimated thresholds. Low direct economic losses cannot be explained by any single necessary condition, but are associated with different combinations of conditions, mainly including Defense Strategy-Driven Pathway and Comprehensive Resilience-Driven Pathway. Discussion: These findings are of great significance for improving coastal disaster risk governance systems and enhancing differentiated disaster prevention and mitigation capacities.

Systemic risk in the global staple food trade network has become a critical threat to global food security amid escalating geopolitical frictions and frequent extreme weather events. This study constructs directed weighted trade networks for wheat, rice, maize and soybean covering 196 economies, and applies a cascading failure model to compare cross-crop structural vulnerability. Simulation results reveal stark heterogeneous risk profiles: a shock originating from a top rice exporter in India spreads across two cascading rounds and impacts 25.5% of total network nodes, while a parallel shock from a top soybean exporter in Brazil triggers nine propagation rounds affecting 86.2% of nodes; by comparison, equivalent shocks to wheat and maize networks only affect 22.4% and 24.5% of nodes respectively. Under identical targeted attack conditions, rice and soybean networks suffer sharp connectivity deterioration after removing a small number of core exporter nodes, while wheat and maize networks retain relatively higher residual connectivity under the same attack intensity, reflecting that crop trade systems with higher supply concentration exhibit greater systemic vulnerability. This work adopts a single-year static network framework; future research will extend to multi-year dynamic network tracking and incorporate adaptive supply-chain feedback mechanisms. Despite this boundary, the study fills the research gap in cross-crop systemic risk comparison, providing robust empirical evidence for differentiated global food supply-chain resilience governance.