In an increasingly interconnected world, food trade systems are increasingly exposed to overlapping crises—including pandemics, geopolitical conflicts, and climate change. These disruptions reveal persistent vulnerabilities in global supply chains and demand a cross-scale understanding of food trade resilience. This dissertation applies the metacoupling framework—which integrates human–nature interactions within (intracoupling), between neighboring (pericoupling), and between distant (telecoupling) systems—to examine food trade dynamics under multiple crises across spatial and temporal scales.Chapter 2 presents a systematic review of 455 peer-reviewed studies and identifies major gaps in existing research. While most studies focus on national-scale trade or intracoupled systems, few consider spillover systems or interactions across multiple coupling types. Based on this gap, the chapter synthesizes fragmented resilience indicators into a unified assessment framework, structured around human- and nature-related drivers. Chapter 3 develops a multi-dimensional evaluation framework to assess food trade resilience before and after the COVID-19 pandemic. By disaggregating five indicators—Bonilla index, centrality, connectivity, trade disruptions, and supply chain diversity—into adjacent and distant trade components, the study reveals stark inequalities in resilience, particularly in low-income countries with limited diversification and infrastructure. Chapter 4 constructs a rapid assessment framework to estimate the impacts of the Russia–Ukraine war on winter cereals trade in 2022. Leveraging remote sensing-based cropland data, trade statistics, and network metrics, the study shows a sharp decline in trade connectivity and the emergence of new trade pathways, exposing the fragility of current supply chains in conflict-affected regions. Chapter 5 extends the analysis to the global wheat trade over three decades (1991–2022). Using a combination of network analysis, structural change modeling (SCM), and generalized additive models (GAM), the chapter quantifies long-term trends in trade resilience. The results show widening disparities across income groups, with distant trade growing in dominance and low-income countries remaining disproportionately vulnerable to both acute and chronic crises. Together, these chapters advance theoretical and empirical understanding of food trade resilience under multiple crises. By integrating metacoupling theory with remote sensing, network science, and quantitative modeling, this dissertation provides a cross-scale perspective on the evolving structure of global wheat trade and offers actionable insights for enhancing global food system resilience.
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