NSF Convergence Accelerator Track E: Combining high-resolution climate simulations with ocean biogeochemistry, fisheries and decision-making models to improve sustainable fisheries

NSF 融合加速器轨道 E：将高分辨率气候模拟与海洋生物地球化学、渔业和决策模型相结合，以改善可持续渔业

• 批准号: 2137684
• 负责人: Zhe Zhang
• 金额: $ 74.95万
• 依托单位: Texas A&M University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2137684&HistoricalAwards=false
• 关键词: NSF; Convergence; Accelerator; Track; Combining

NSF Convergence Accelerator Track E: Combining high-resolution climate simulations with ocean biogeochemistry, fisheries and decision-making models to improve sustainable fisheries.Fish and shellfish populations are a vital source of protein for many of the world’s people, and several of the largest are found along the eastern boundaries of the Pacific and Atlantic Oceans, where cold, deep water moves towards the surface, bringing nutrients that support both production by plants (phytoplankton) and the fish populations that feed on them. To ensure sustainability, fish and shellfish managers need information not only on the number of animals available at any given time, but also on potential future numbers, so that they can plan for such things as the number of fishing boats required or the size of seafood processing plants. Forecasting what will occur in such eastern boundary areas is difficult, however, because local winds rapidly change conditions. Adverse climate impacts, such as rising ocean temperatures and increasing acidity, are already affecting many coastal fishing-dependent communities, and such longer-term changes also have to be considered. The project aims to develop a decision support system, which uses the latest ocean models incorporating marine physics, chemistry and biology, to assist fish and shellfish managers in making their decisions. This is important as there are many stakeholders involved in harvesting fish and shellfish, who may have potentially conflicting interests. To this end, the research is aimed at integrating the outputs from the ocean models with a web-based decision support system that will help fisheries managers and industry make informed decisions to ensure that both the industry and its associated food production are sustainable. The investigators will work directly with the stakeholders to develop tools that are specifically able to meet their needs. The initial focus of the work is the California Current system along the U.S. west coast from California to Washington, which supports a local seafood industry valued annually at about $12 billion, with additional billions from catches landed by foreign boats in the U.S. If successful, the new tools should be extendable to other similar regions of the global ocean, thus increasing the value of the research. The project will provide training for students, including those from under-represented groups, in the use of the latest ocean models, as well as development opportunities for young faculty members at the participating institutions.Climate change-driven adverse ocean impacts are already affecting many rural, coastal, fishing-dependent communities, and these adverse impacts will likely accelerate for the foreseeable future. Forecasting potential changes in eastern boundary upwelling systems has benefitted recently from improvements in the resolution of global Earth system models, so that the latest eddy-resolving models at 10 km ocean resolution have greatly reduced systematic errors relative to observations. This project aims to use these advancements to improve forecasts of the fisheries potential of the California Current Ecosystem and improve decision making by managers and other stakeholders. The project will couple the output from such a high-resolution model simulation with the Marine Biogeochemistry Library and Fisheries Size and Functional Type models, thus incorporating physics, chemistry and biology with climate variability. The results will be integrated with a prototype, web-based decision support system, that uses mathematical decision analysis capabilities, to assist fisheries managers to model the complex, climate-related decision problems on which fisheries production depends. This is vital to ensure that the region can continue to support a sustainable fishery in the long term and the communities that depend on fishing for a living. In Phase 1, the project will develop a prototype of this linked decision system. The project will also develop a well-networked multidisciplinary team of modelers, social scientists, fisheries managers, economists, and industry and community stakeholders to advance convergence science and develop avenues for more sustainable fisheries under a changing climate. This team is essential for developing tools that are directly applicable to the needs of fishery stakeholders and will be fostered by meaningful communication between all groups throughout the project period. If successful, the model suite and decision support system should be extendable to other similar regions of the global ocean. Students and post-doctoral researchers, the next generation of scientists, will be trained in decision analysis and to use the most current high-resolution models. Furthermore, the project will provide valuable professional development opportunities for early career female Co-PIs involved in the program.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Convergence Accelerator Track E：将高分辨率气候模拟与海洋地球化学、渔业和决策模型相结合，以改善可持续渔业。鱼类和贝类种群是世界上许多人的重要蛋白质来源，其中几个最大的鱼类和贝类种群位于太平洋和大西洋东部边界的沿着，那里的冷水和深水流向表面，为植物（浮游植物）和以其为食的鱼类带来营养。为了确保可持续性，鱼类和贝类管理人员不仅需要任何特定时间可获得的动物数量的信息，而且还需要未来潜在数量的信息，以便他们可以计划所需的渔船数量或海鲜加工厂的规模。然而，预测东部边界地区将发生什么是困难的，因为当地的风迅速改变条件。 海洋温度上升和酸度增加等不利气候影响已经影响到许多沿海渔业依赖社区，而且还必须考虑这些长期变化。该项目旨在开发一个决策支持系统，该系统使用最新的海洋模型，结合海洋物理学、化学和生物学，以协助鱼类和贝类管理人员作出决定。这一点很重要，因为有许多利益相关者参与捕捞鱼类和贝类，他们可能有潜在的利益冲突。为此，研究的目的是将海洋模型的产出与基于网络的决策支持系统相结合，帮助渔业管理人员和行业做出明智的决定，以确保行业及其相关的粮食生产是可持续的。调查人员将直接与利益相关者合作，开发专门能够满足他们需求的工具。这项工作的最初重点是美国西海岸从加州到华盛顿的加州海流系统，该系统支持当地每年价值约120亿美元的海鲜产业，另外还有数十亿美元来自外国船只在美国登陆的渔获。该项目将为学生，包括代表性不足群体的学生提供使用最新海洋模型的培训，并为参与机构的年轻教员提供发展机会，气候变化造成的不利海洋影响已经影响到许多农村、沿海和依赖渔业的社区，在可预见的未来，这些不利影响可能会加速。预测东部边界上升流系统的潜在变化最近受益于全球地球系统模型分辨率的提高，因此，最新的10公里海洋分辨率的涡旋分辨模型大大减少了相对于观测的系统误差。该项目旨在利用这些进展来改善对加州当前生态系统渔业潜力的预测，并改善管理人员和其他利益相关者的决策。该项目将把这种高分辨率模型模拟的结果与海洋生物地球化学库和渔业规模和功能类型模型结合起来，从而将物理、化学和生物学与气候变异性结合起来。研究结果将与一个原型、基于网络的决策支持系统相结合，该系统利用数学决策分析能力，协助渔业管理人员对渔业生产所依赖的复杂的、与气候有关的决策问题进行建模。这对于确保该地区能够继续长期支持可持续渔业以及以渔业为生的社区至关重要。在第一阶段，该项目将开发这种关联决策系统的原型。该项目还将建立一个由建模人员、社会科学家、渔业管理人员、经济学家以及行业和社区利益攸关方组成的网络化多学科团队，以推进融合科学，并为气候变化下的更可持续渔业开发途径。该团队对于开发直接适用于渔业利益相关者需求的工具至关重要，并将通过整个项目期间所有团体之间的有意义的沟通得到促进。如果成功的话，模型套件和决策支持系统应该可以扩展到全球海洋的其他类似区域。学生和博士后研究人员，下一代科学家，将接受决策分析培训，并使用最新的高分辨率模型。此外，该项目将为参与该项目的早期职业女性共同首席信息官提供宝贵的专业发展机会。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。