Evaluating the Resilience and Sustainability of Local Agricultural Systems Embedded into the Global Food Supply Chain
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Evaluating the Resilience and Sustainability of Local Agricultural Systems Embedded into the Global Food Supply Chain

Abstract

This dissertation focuses on the sustainability and resilience of local agricultural systems integrated into the global food supply chain. In a resource-limited world, where water, soil health, and optimal growing temperatures are distributed unevenly and incongruously with global population distribution, a global supply chain has become the hallmark of modern food security. The high-intensity agriculture production in one locale allows far-off populations to increasingly access foreign land and water resources through food trade or resource appropriation to satisfy their local needs. Meanwhile, the food outlook will likely continue changing due to compounding climatic, political, and economic stressors. Amidst this, a deeper understanding of how agricultural systems have developed and sustained production amidst complex challenges – and how big data and remote sensing can be used to understand this relationship – is needed. In this dissertation work, I first examine the sustainability of agricultural transformations in México – a country that has rapidly modified and shifted domestic agricultural land and water resource consumption, especially to satisfy the demand of its northern neighbors since the North American Free Trade Agreement (NAFTA). In the first chapter, I use a biophysical crop water model to examine how market demands and international trade agreements have reshaped national crop production, the associated reliance on unsustainable freshwater resources, and virtual water flows out of México to the United States. The findings reveal that irrigated water plays an increasingly prominent role in export agriculture and that many non-traditional, export-oriented crops are grown in water-scarce Mexican municipalities relying on unsustainable irrigation practices, serving as a warning for the future of these food supplies. The second chapter explores a hotspot for Mexican agricultural transformation and – using machine learning of satellite imagery and a national dataset of communal land – delineates how export-oriented irrigation agriculture reconfigures local land use practices. The rapid expansion of berry greenhouses onto private and communal lands since NAFTA reveals the pressures a global food system impartially exerts on resources from communal and non-communal systems alike. The third and final chapter examines the agricultural resilience of Ukraine – a second critically important agricultural region – amidst war. Using unsupervised learning of satellite imagery and fixed linear regression analysis, this study maps the abandonment and recultivation of agriculture since 2011, with a marked increase in the early onset of abandonment since the war’s 2022 escalation. The regression analysis shows that war-related exposures are more positively associated with agricultural abandonment over the whole period, while annual precipitation plays an important role in abandonment since 2018. Of war-related exposures, the presence of Russian occupation is associated with larger increases in abandonment than conflict events. Combined, these studies contribute knowledge of how a globalized food system has transformed sub-national landscapes and the land and water resources they consume to support food security.

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