DISES: Drivers of Ecosystem-based Adaptation to extreme events in mangrove-reef social-ecological systems

该项目的重点是社会和环境过程和相互作用，这些过程和相互作用影响了依赖红树林-珊瑚礁的沿海社区对热带气旋的基于生态系统的适应的有效性。在过去的十年中，EbA已经成为一种适应方法，其重点是恢复，管理和保护等战略，以帮助减少极端事件的影响。若干研究表明，红树林和珊瑚礁可大大减少热带气旋期间洪水对人员和财产造成的损害，同时还提供宝贵的资源，如灾后重建所需的木材和燃料。这些生态系统反过来又受到气旋影响以及使用和管理这些生态系统的社区的影响。换句话说，EbA是一个内在动态的社会生态系统（SES），在生态系统、依赖和管理它们的人和社区以及飓风等外部冲击之间具有强烈的反馈。通过结合社会，生态和工程方法的综合方法，该项目的见解将为全球易受气旋影响的社区的EbA战略设计提供信息。调查人员正在培训研究生进行跨学科的沿海科学，其成果正在加强研究沿海问题的本科生的课程。正在通过讲习班、政策简报和在线地图向斐济和波多黎各的资源和灾害风险管理人员提供研究成果。该项目正在促进对红树林-珊瑚礁社会-生态系统中基于生态系统的适应如何应对斐济和波多黎各脆弱社区的气旋影响的理解。两国都是自然资源丰富的小岛屿国家，经常遭受飓风，但有不同的环境治理体系。使用SES框架，该项目正在确定红树林珊瑚礁SES和极端事件的相互作用如何塑造现有和新兴的EbA行动和结果。该项目采取了一种融合的方法，将自然资源管理，生态学和工程学相结合，以评估影响EbA实施和有效性的社会和环境驱动因素。该研究包括：社会科学方法，以确定EbA行动的社会经济和治理驱动因素;遥感方法，以检测生态变化的驱动因素;一个基于代理的模型，以描述社会进程和与环境的相互作用如何影响EbA行动，以及;沿海洪水损害模型，以量化不同情景下的防洪效益的红树林和珊瑚礁生态系统的范围和条件。从这些方法的输出将开发预测的社会和生态后果的EbA在不同的情况下，未来的气旋事件和红树林珊瑚礁管理策略。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。

This project focuses on social and environmental processes and interactions that shape the effectiveness of Ecosystem-based Adaptation (EbA) to tropical cyclones in mangrove-reef-dependent coastal communities. EbA has emerged over the past decade as an adaptation approach that focuses on strategies such as restoration, management, and conservation to help reduce the impacts of extreme events. Several studies show that mangrove forests and coral reefs can significantly reduce flood damage to people and property during tropical cyclone events, while also providing valuable resources such as timber for reconstruction and fuel in their aftermath. These ecosystems are, in turn, affected by cyclone impacts and the communities that use and manage them. In other words, EbA are an inherently dynamic Social-Ecological System (SES) with strong feedbacks between the ecosystems, the people and communities depending upon and managing them, and external shocks like cyclones. With an integrated approach that combines social, ecological, and engineering methods, the insights from this project will inform the design of EbA strategies for cyclone-prone communities worldwide. The investigators are training graduate students to conduct interdisciplinary coastal science and results are enhancing curricula for undergraduate students studying coastal issues. Research outcomes are being made available to resource and disaster risk managers in Fiji and Puerto Rico through workshops, policy briefs and online maps. This project is advancing understanding of how Ecosystem-based Adaptation (EbA) in mangrove-reef Social-Ecological Systems (SES) respond to cyclone impacts among vulnerable communities in Fiji and Puerto Rico. Both are natural resource-rich small island states frequently experiencing cyclones, yet have different environmental governance systems. Using an SES framework, this project is identifying how interactions in a mangrove-coral reef SES and extreme events shape existing and emerging EbA actions and outcomes. The project takes a convergent approach, combining natural resource management, ecology, and engineering to assess the social and environmental drivers that shape the implementation and effectiveness of EbA. The study incorporates: social-science methods to identify socio-economic and governance drivers of EbA actions; remote sensing methods to detect drivers of ecological change; an agent-based model to describe how social processes and interactions with the environment influence EbA actions, and; a coastal flood damage model to quantify the flood protection benefits derived under different scenarios of mangrove and reef ecosystem extent and condition. Outputs from these methods will develop predictions of the social and ecological outcomes of EbA under different scenarios of future cyclone events and mangrove-reef management strategies. Results will inform future EbA efforts on similar coastlines worldwide.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.