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严重的威胁。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行之有效的杠杆是减轻当地和区域的压力源，如捕鱼压力。然而，一个令人烦恼的问题仍然存在，即如何衡量捕鱼对生态系统的影响，特别是在大的空间范围内（例如，10米）和时间（多年）尺度上捕鱼发生。一个很有希望的办法是利用全球珊瑚礁上的大规模植被模式，即“晕圈”，远程观察捕捞压力何时、何地以及在多大程度上影响到群落结构和功能。该计划将实验室和实地实验与尖端的卫星成像技术和计算机科学方法相结合，为我们理解物种水平的相互作用如何在空间和时间上扩大以塑造世界各地的珊瑚礁海景提供了飞跃。 通过借鉴这些方法，协同教育计划：1）整合科学和艺术（即，（2）在夏威夷的少数民族高中为研究生建立技术能力，（3）赋予这些学生与不同受众沟通的科学沟通技能。通过利用这项研究计划和它将涉及的尖端技术，研究人员建立了长期教学和辅导活动的坚实基础，重点是提高具有夏威夷和其他太平洋岛民背景的STEM代表性不足的少数民族的能力。解码珊瑚礁晕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从业者提供了宝贵的知识，因为珊瑚礁由于人类的压力而继续迅速变化。该项目将实验室和实地实验与尖端卫星成像技术和计算机科学方法相结合，以实现以下目标：1）确定在珊瑚礁周围形成“晕圈”的机制，2）在全球竞技场测试这些机制产生的预测。该项目使用跨学科的方法-跨越生态学，海洋学，地理空间科学和计算机科学-来实现这些目标。该计划有三个科学目标：确定（1）哪些物种相互作用机制和环境因素导致珊瑚礁晕及其相对重要性;（2）这些机制是否在全球范围内一致或在地理上有所不同;以及（3）晕是否因此可以用作珊瑚礁生态系统健康方面的指标。在这个过程中，这项研究推进了我们对远程观测工具如何（卫星和无人机图像;相机陷阱）可以与计算机科学相结合（机器学习）和生态方法该项目由生物海洋学计划，刺激竞争性研究的既定计划（EPSCoR），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。

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.