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

该项目侧重于影响依赖红树林珊瑚礁的沿海社区基于生态系统的适应热带气旋有效性的社会和环境进程及相互作用。EBA在过去十年中作为一种适应方法出现，侧重于恢复、管理和保护等战略，以帮助减少极端事件的影响。几项研究表明，红树林和珊瑚礁可以大大减少热带气旋期间洪水对人和财产造成的损失，同时还可以提供宝贵的资源，如重建所需的木材和灾后燃料。这些生态系统反过来又受到气旋影响以及使用和管理它们的社区的影响。换句话说，EBA是一个内在的动态社会生态系统(SES)，在生态系统、依赖和管理生态系统的人和社区与气旋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飓风影响的社区设计EBA战略提供参考。研究人员正在培训研究生进行跨学科的沿海科学研究，结果是加强了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。该项目正在增进对红树林-珊瑚礁社会生态系统基于生态系统的适应(EBA)如何应对斐济和波多黎各脆弱社区的气旋影响的理解。这两个国家都是自然资源丰富的小岛国，经常遭遇龙卷风，但环境治理制度不同。利用SES框架，该项目正在确定红树林-珊瑚礁SES和极端事件之间的相互作用如何影响现有的和新出现的EBA行动和结果。该项目采取一种融合的方法，将自然资源管理、生态学和工程学结合起来，评估影响EBA实施和有效性的社会和环境驱动因素。这项研究包括：确定环境影响评估行动的社会经济和治理驱动因素的社会科学方法；检测生态变化驱动因素的遥感方法；描述社会进程和与环境的互动如何影响环境影响评估行动的基于主体的模型；以及量化红树林和珊瑚礁生态系统范围和条件的不同情景下的防洪效益的沿海洪水破坏模型。这些方法的结果将对EBA在未来气旋事件和红树林-珊瑚礁管理战略的不同情景下的社会和生态结果进行预测。结果将为EBA未来在世界范围内类似海岸线上的努力提供信息。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.