CAREER: Decoding seascape-scale vegetation patterns on coral reefs to understand ecosystem health: Integrating research and education from organismal to planetary scales

世界各地的珊瑚礁正受到一系列人为压力的日益威胁。气候变化被认为是威胁珊瑚礁的一个关键的全球压力源，但生态系统管理者提高珊瑚礁复原力的唯一已被证实的杠杆是减轻当地和区域的压力源，如捕鱼压力。然而，一个棘手的问题仍然存在，那就是如何衡量捕捞对生态系统的影响，特别是在发生捕捞的大空间(例如，10米)和时间(多年)尺度上。这样做的一个有希望的方法是使用在全球珊瑚礁上发现的大规模植被模式，称为“光环”，以远程观察捕鱼压力何时、何地以及在多大程度上影响群落结构和功能。该计划将实验室和现场实验与尖端卫星成像技术和计算机科学方法相结合，使我们在理解物种水平的相互作用如何在空间和时间上扩大规模以塑造世界各地的珊瑚礁海景方面取得了飞跃。通过利用这些方法，协同教育计划：1)将科学和艺术(即壁画和卫星图像)结合起来，教育和启发夏威夷的学生和公众关于珊瑚礁生态的知识；2)在夏威夷人数较少的少数族裔高中培养研究生的技术能力；3)使这些拥有科学交流技能的学生能够与不同的受众交流。通过利用这一研究计划和它将涉及的尖端技术，调查员为长期教学和指导活动奠定了坚实的基础，重点是提高STEM的能力-具有夏威夷和其他太平洋岛民背景的代表不足的少数民族。破译珊瑚礁光环可以告诉我们捕鱼对珊瑚礁生态系统健康的影响，为珊瑚礁生态系统管理者和保护实践者提供了宝贵的知识，因为由于人类压力因素，珊瑚礁继续快速变化。该项目将实验室和现场实验与尖端卫星成像技术和计算机科学方法相结合，以解决以下目标：1)确定在珊瑚礁周围形成“光环”的机制，以及2)在全球范围内检验由这些机制产生的预测。这个项目使用跨学科的方法--横跨生态学、海洋学、地理空间科学和计算机科学--来解决这些目标。该计划有三个科学目标：1)确定哪些物种相互作用机制和环境因素导致珊瑚礁晕圈及其相对重要性；2)这些机制是否在全球范围内是一致的，还是在地理上不同；以及3)晕圈是否因此可用作珊瑚礁生态系统健康方面的指标。在这个过程中，这项研究加深了我们对远程观测工具(卫星和无人机图像；相机陷阱)如何与计算机科学(机器学习)和生态学方法(机械实验)相结合，以产生原本不可能产生的紧急见解的理解。该项目由生物海洋学计划、既定的激励竞争研究计划(EPSCoR)和海洋教育计划联合资助。该奖项反映了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。

Coral reefs worldwide are under increasing threat from a range of human-induced stressors. Climate change is understood to be a key global stressor threatening reefs, but the only proven levers for ecosystem managers to increase reef resilience is to mitigate local and regional stressors such as fishing pressure. A vexing question persists, however, which is how to measure the effects of fishing on ecosystems, particularly over the large spatial (e.g., 10s of meters) and temporal (multi-year) scales over which fishing occurs. One promising approach to doing so is using the large-scale vegetation patterns found on coral reefs globally, called “halos”, to remotely observe when, where, and to what extent fishing pressure is affecting community structure and function. This program combines lab- and field-based experiments with cutting-edge satellite imaging technology and computer science approaches to provide a leap forward in our understanding of how species-level interactions can scale up in space and time to shape coral reef seascapes around the world. By drawing on these approaches, the synergistic education program: 1) integrates science and art (i.e., murals and satellite imagery) to educate and inspire Hawai‘i’s students and general public about coral reef ecology; 2) builds technological capacity in Hawai‘i’s underrepresented minority high school to graduate students, and 3) empowers these students with science communication skills to communicate with diverse audiences. By leveraging this research program and the cutting-edge technologies it will involve, the investigator establishes a strong foundation for long-term teaching and mentoring activities focused on increasing capacity within STEM-underrepresented minorities with Hawaiian and other Pacific Islander backgrounds. Decoding what coral reef halos can tell us about the effects of fishing on reef ecosystem health provides valuable knowledge to reef ecosystem managers and conservation practitioners as reefs continue to rapidly change due to human stressors. This project combines lab- and field-based experiments with cutting-edge satellite imaging technology and computer science approaches to address the goals of: 1) determining the mechanisms that create the “halos” that form around coral patch reefs, and 2) testing the predictions arising from these mechanisms in a global arena. This project uses a transdisciplinary approach – spanning ecology, oceanography, geospatial science, and computer science – to address these goals. This program has three scientific objectives: to determine 1) which species interaction mechanisms and environmental factors cause reef halos and what their relative importance is; 2) whether these mechanisms are globally consistent or vary geographically; and 3) whether halos can therefore be used as an indicator of aspects of coral reef ecosystem health. In the process, this research advances our understanding of how remote observation tools (satellite and drone imagery; camera traps) can be integrated with computer science (machine learning) and ecological approaches (mechanistic experiments) to generate emergent insights that would not otherwise be possible.This project is jointly funded by the Biological Oceanography Program, the Established Program to Stimulate Competitive Research (EPSCoR), and Ocean Education Programs.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.