Collaborative Research: Coastal SEES (Track 1): Chesapeake Bay Sustainability: Implications of changing climate and shifting management objectives

合作研究：沿海 SEES（轨道 1）：切萨皮克湾可持续性：气候变化和管理目标转变的影响

• 批准号: 1325489
• 负责人: Roy Hoagland
• 金额: $ 1.5万
• 依托单位: College of William and Mary
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1325489&HistoricalAwards=false
• 关键词: Collaborative; Research; Coastal; SEES; Track

This project aims to develop an advanced modeling framework that integrates the physical, biogeochemical, and human components needed to simulate and select climate change adaptation strategies that will support a sustainable system. It merges a fine resolution hydrodynamic model with a broader-scale whole-ecosystem model that is capable of simulating socioeconomic interactions to characterize human-natural linkages in the system. The research specifically uses hypothetical alterations to the Chesapeake Bay designed to reduce storm surge to examine the impacts on estuarine dynamics, fisheries production, and potential flooding risks, with emphasis on feedbacks to the human system.The conceptual framework for the project is an examination of the physical, chemical, and biological consequences of an alteration of the estuarine system designed to reduce risks in the linked human system. The focus of the proposed work is simulation of the intervention?s impacts on fisheries production and potential flooding risks, both feedbacks to the human system. This work directly addresses the issue of risk mitigation through physical alterations of estuarine systems potentially confounding current efforts to sustain water quality and fisheries production. Informing the policy and management decisions will require this type of enhanced modeling tools and expanded understanding of system responses.This project brings together researchers with complementary strengths in the essential modeling efforts and the subsequent translation to policy guidance. The project will provide two senior graduate students training in interdisciplinary research on issues of sustainability, and it will provide course materials for other graduate students working in the Center for Coastal Resources Management at VIMS and the Coastal Policy Law Clinic at William & Mary. Because the project will be managed from the Center for Coastal Resources Management at VIMS, the products and insights developed will have a unique connection to the coastal management and policy communities in Chesapeake Bay. The results of this project will be incorporated into the formal guidance, the outreach education programs, and the online data provided to local and state government personnel by the Center, thus ensuring the direct translation of project products to management and policy. In addition, because these topics are currently of great interest to a wide variety of public and private entities, there are opportunities for outreach education sessions to increase the understanding of sustainability concepts, policy options, and management challenges across a wide spectrum of stakeholders including state legislators, NGO staffs, and private citizensThis project is supported under NSF's Coastal SEES (Science, Engineering and Education for Sustainability) program.

该项目旨在开发一个先进的建模框架，该框架集成了模拟和选择支持可持续系统的气候变化适应战略所需的物理，地球化学和人类成分。它将一个高分辨率的水动力学模型与一个更广泛的全生态系统模型相结合，该模型能够模拟社会经济相互作用，以描述系统中人类与自然的联系。该研究专门使用假设的改变切萨皮克湾，旨在减少风暴潮，以检查对河口动态，渔业生产和潜在的洪水风险的影响，重点是对人类系统的反馈。该项目的概念框架是检查物理，化学，和生物后果的改变河口系统的设计，以减少风险，在连接人类系统。拟议工作的重点是模拟干预？海洋生态系统对渔业生产的影响和潜在的洪水风险，都是对人类系统的反馈。这项工作直接解决了通过河口系统的物理改变来减轻风险的问题，这可能会混淆目前维持水质和渔业生产的努力。为政策和管理决策提供信息将需要这种类型的增强建模工具和对系统响应的扩展理解。该项目汇集了在基本建模工作和随后的政策指导翻译方面具有互补优势的研究人员。该项目将为两名高年级研究生提供关于可持续性问题的跨学科研究培训，并将为在VIMS海岸资源管理中心和William玛丽海岸政策法律诊所工作的其他研究生提供课程材料。 由于该项目将由VIMS的海岸资源管理中心管理，因此开发的产品和见解将与切萨皮克湾的海岸管理和政策社区有着独特的联系。该项目的成果将被纳入正式指导、外展教育计划以及中心提供给地方和州政府人员的在线数据，从而确保将项目产品直接转化为管理和政策。此外，由于这些主题目前对各种公共和私人实体都非常感兴趣，因此有机会举办外展教育会议，以增加包括州立法者，非政府组织工作人员和私人公民在内的广泛利益相关者对可持续性概念，政策选择和管理挑战的理解。（科学，工程和教育的可持续性）计划。