INFEWS/T1: Impacts of Deglobalization on the Sustainability of Regional Food, Energy, Water Systems

在过去的50年里，通过国际贸易、移民和技术创新实现的全球化为美国经济创造了大量财富。然而，伴随这些收益而来的是制造业部门的失业、社会财富不平等加剧以及国外的环境影响。相反的社会和政治趋势揭示了去全球化的潜力，即，削弱了美国与全球市场的融合。该项目的目标是研究去全球化对区域粮食-能源-水系统的可持续性以及少数粮食-能源-水系统生产者和消费者的福祉的潜在影响。我们开发了一个新的综合建模框架，该框架考虑了个人土地使用和管理决策，区域对土地，能源和水资源的需求，以及水质和温室气体排放的影响。我们将该模型应用于五个州的五大湖地区：伊利诺伊州，印第安纳州，密歇根州，俄亥俄州和威斯康星州和评估不同的未来去全球化的情况和政策的影响区域FEWS的可持续性和社会福祉。当地和区域利益相关者通过参与式建模方法参与整个研究过程，以指导模型规范，开发未来情景，并确定可持续性指标。研究结果用于指导与决策者和其他利益攸关方讨论潜在的五大湖区域未来。建模框架建立在一个动态随机一般均衡模型，该模型考虑了关键资源存量的时间演变和个人的行为动态。该模型量化了未来不确定的环境，经济或政策条件的变化在国家和全球范围内对区域生产的粮食和能源服务，使用土地，水和能源资源，并依赖于农民，土地利用和流域异质性的影响。我们占这些地方的异质性使用个人农民的行为和空间明确的土地数据从莫米河流域。通过建立一个动态的随机集成建模框架，也考虑到个人的决策和空间的土地利用-流域异质性，本研究的区域FEWS集成建模的进步。该研究小组还设计了一种新的可持续发展评估方法，该方法建立在动态区域食品，能源，水系统建模框架的独特功能的基础上，以确定在一系列不确定条件下实现理想结果的政策。与利益相关者的参与式建模方法提高了模型的有效性，并在如何创建，传播和应用于区域FEWS管理的科学知识方面产生了创新，具体应用于五大湖地区。

Increased globalization through international trade, migration, and technological innovation has generated substantial wealth in the U.S. economy over the past 50 years. These gains , however, have been accompanied by job losses in the manufacturing sector, growing wealth inequality in society and environmental impacts abroad. Counter social and political trends reveal a potential for deglobalization, i.e., diminished integration of the U.S. with global markets. The goal of this project is to examine the potential effects of deglobalization on the sustainability of regional food-energy-water systems (FEWS) and well-being of FEW producers and consumers. We develop a new integrated modeling framework that accounts for individual land use and management decisions, regional demands for land, energy and water resources, and water quality and greenhouse gas emissions impacts. We apply the model to a five-state Great Lakes region: Illinois, Indiana, Michigan, Ohio, and Wisconsin and evaluate the implications of varying future deglobalization scenarios and policies for regional FEWS sustainability and societal well-being. Local and regional stakeholders are engaged throughout the research process via a participatory modeling approach to guide model specification, develop future scenarios, and identify sustainability metrics. The research results are used to guide discussion of potential Great Lakes regional futures with policymakers and other stakeholders. The modeling framework builds from a Dynamic Stochastic General Equilibrium model that accounts for both the time evolution of key resource stocks and the behavioral dynamics of individuals. The model quantifies the effects of uncertain future changes in environmental, economic, or policy conditions at national and global scales on the regional production of food and energy services that use land, water, and energy resources and that depend on farmer, land use, and watershed heterogeneity. We account for these local heterogeneities using individual farmer behavioral and spatially explicit land data from the Maumee River basin. By creating a dynamic stochastic integrated modeling framework that also accounts for individual decision making and spatial land use-watershed heterogeneity, this research advances the integrated modeling of regional FEWS. The research team also devises a novel approach to sustainability assessment that builds on the unique features of the Dynamic Regional Food, Energy, Water Systems modeling framework to identify policies that are robust in achieving desirable outcomes under a range of uncertainty conditions. The participatory modeling approach with stakeholders improves model validity and generates innovations in how scientific knowledge is created, disseminated, and applied to the management of regional FEWS with specific application to the Great Lakes region.