GRIP: Global Reef Impact Projections

该项目旨在将英国、美国和澳大利亚的科学家聚集在一起，建立一套用于预测和预测全球珊瑚礁压力的原型操作工具，并提供长期合作伙伴关系，为珊瑚礁管理者提供决策支持的逐步改变。温水珊瑚是大型的个体生物群落，珊瑚虫是光合作用的单细胞生物（虫黄藻）的宿主。虫黄藻和珊瑚虫的共生关系是互惠互利的，虫黄藻为珊瑚虫提供氧气和营养，珊瑚虫提供物理保护并提供呼吸产生的二氧化碳。当受到压力时，虫黄藻死亡或离开水螅体，反过来又给水螅体施加压力，可能导致珊瑚死亡（Baird和Marshall， 2002）。虫黄藻对高温非常敏感，虽然不同的虫黄藻具有不同的温度阈值（Hume等人，2015），但事实证明，一种被称为温度加热周的简单指标是识别珊瑚何时可能漂白的一种非常有效的方法（Skirving等人，2019）。20多年来，珊瑚礁观察利用遥感，建模和现场数据来观察，预测和提醒其用户全球珊瑚礁威胁。大约有1000名资源管理人员、科学家、民选官员、教育工作者和公众订阅了珊瑚礁观察的自动卫星珊瑚白化警报系统。珊瑚礁观察基于DHW的警报允许珊瑚礁管理者通过指导他们何时应该进行现场温度测量来确定他们的珊瑚礁是否面临迫在眉睫的威胁，检查漂白的初步证据，然后保护食草动物种群，从而减轻极端温度的一些更糟糕的影响，保护水质，限制危险地区的开发和娱乐用途（https://www.coris.noaa.gov/activities/reef_managers_guide/welcome.html）.Coral珊瑚礁观察组织由世界领先的遥感科学家、生物学家和生态学家组成。他们最先进的工具是为了利用这些专业知识而建立的。随着用户需求变得越来越复杂，以及基线因气候变化而发生变化，有必要超越直接观察到的范围。该项目建立了一种新的伙伴关系，将气候和海岸建模的专业知识和方法纳入珊瑚礁观察工具包。这一伙伴关系将共同生成并验证一套大型的简化的沿海模型模拟，涵盖全球整个热带海洋。这些模式模拟不仅将提供半动态缩尺或未来预测，而且还将利用最先进的大气再分析，及时推回并补充卫星观测的地下信息。这一伙伴关系将共同开发基于这些数据的珊瑚礁应力产品，但这将建立在NOAA珊瑚礁观察在开发和分发这些工具的结果方面20多年的经验基础上。最后，本项目将确定将这些新工具转化为直接交付到管理人员和决策者手中的业务生产产出的最佳途径。

This project seeks to bring together UK, US and Australian scientists to establish a set of proto-operational tools for predicting and projecting stress on global coral reefs, and deliver a long-term partnership to provide coral reef managers with a step-change in decision-making support.Warm water corals are large colonies of individual organisms, coral polyps, which act as hosts to photosynthesising unicellular organisms known as zooxanthellae. The zooxanthellae and polyp symbiosis are mutually beneficial, with the zooxanthellae providing the polyp with oxygen and nutrients, and the polyps providing physical protection and supplying carbon dioxide from respiration. When stressed, zooxanthellae die or leave the polyp, in turn stressing the polyp, potentially leading to the coral's mortality (Baird and Marshall, 2002). Zooxanthellae are very sensitive to high temperatures, and while different zooxanthellae have different temperature thresholds (Hume et al., 2015), a simple metric known as Degree Heating Weeks has proved to be a very effective way of identifying when corals are likely to bleach (Skirving et al., 2019).For more than 20 years, Coral Reef Watch has utilized remote sensing, modelling and in-situ data to observe, predict and alert its users to coral reef threats worldwide. ~1,000 resource managers, scientists, elected officials, educators, and the public subscribe to Coral Reef Watch's automated satellite coral bleaching alert system. Coral Reef Watch's DHW based alerts allow reef managers to mitigate some of the worse effects of temperature extremes by guiding when they should be making in situ temperature measurements to identify if their reefs are under imminent threat, checking for initial evidence of bleaching, then protecting herbivore populations, protecting water quality and restricting development and recreational use of at-risk areas (https://www.coris.noaa.gov/activities/reef_managers_guide/welcome.html).Coral Reef Watch is made up of a world leading team of remote sensing scientists, biologists and ecologists. Their state-of-the-art tools have been built to take advantage of these expertise. As user requirements become increasingly sophisticated, and baselines shift in response to climate change, there is a need to move beyond what can be directly observed. This project builds a new partnership to bring climate and coastal modelling expertise and approaches into the Coral Reef Watch toolkit.This partnership will collaboratively generate and verify a large set of reduced-complexity coastal model simulations spanning the entirety of the global tropical oceans. These model simulations will provide not only semi-dynamical downscaling or future projections, but also, using state-of-the art atmospheric reanalyses, push back in time and supplement satellite observations with subsurface information. Working together this partnership will develop coral reef stress products based on this data, but will do so by building on the more than 20 years of experience NOAA Coral Reef Watch have in developing and distributing the results from such tools. Finally, this project will identify the optimal pathway for transition these new tools into operationally produced outputs delivered directly into the hands of managers and decision makers.