CAMEO: Multiscale modeling of Hawaii's coral reef communities

CAMEO：夏威夷珊瑚礁群落的多尺度建模

• 批准号: 1041673
• 负责人: Megan Donahue
• 金额: $ 36.45万
• 依托单位: University of Hawaii
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-15 至 2014-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1041673&HistoricalAwards=false
• 关键词: CAMEO; Multiscale; modeling; Hawaii; coral

A key challenge in the effective management of marine ecosystems is translating from small scale studies of distribution and dynamics to the regional scale of management action. In many marine ecosystems, including the Hawaiian Archipelago, there are extensive survey data of nearshore communities from multiple investigators, representing a huge investment of resources. Often, these data are underutilized and remain of limited use to managers. In the Hawaiian Archipelago, at least seven separate entities are engaged in surveys of coral reef communities, with varying degrees of coordination. The synthesis of these data requires integrated modeling approaches at multiple scales. This study builds on an existing database and extends two existing models: the Coral Recovery Model (CRM) of stochastic coral recovery after disturbance and the COMBO model of the synergistic impacts of increasing acidification and temperature on coral reefs. Extending from this prior work is the application of two innovative modeling approaches (scale transition theory and fundamental niche modeling) to predict coral community composition and dynamics at the regional scale. Fundamental niche modeling uses multiple data fitting approaches (regression, machine learning, etc) to describe the relationship between species and their environments, using a split dataset for training and validation. This approach can generate a predictive and validated spatially continuous model of species distribution from discrete data points. The scale transition modeling will use the completed database of species distributions as the landscape on which species interactions occur. These interactions are described by a local model, here, based on recruitment, growth, and mortality from the Coral Recovery Model. In scale transition theory, the local model plus landscape information on the distribution and co-distribution of organisms and their environments predicts how a species assemblage responds (locally and regionally) to changes in biotic and abiotic factors on the landscape.This project will generate four products relevant to ecosystem-based management of the Hawaiian Archipelago, resulting in significant impacts beyond the research community: (1) A Hawaiian Archipelago-wide GIS database of coral distribution, benthic community data, fish surveys, and other data gathered by CRAMP, NPS (National Park Service), various divisions in NOAA, the Hawaii Division of Aquatic Resources, and other sources into a single GIS database; (2) Validated, predictive, and spatially continuous maps of coral species distribution throughout the Archipelago; (3) A validated Coral Recovery Model for coral reef mitigation in the Main Hawaiian Islands; (4) Prediction of coral community response to climate change throughout the Hawaiian Archipelago, based on known and predicted coral distributions and the COMBO model.

有效管理海洋生态系统的一个关键挑战是从对分布和动态的小规模研究转变为区域规模的管理行动。在包括夏威夷群岛在内的许多海洋生态系统中，有来自多个调查人员的广泛的近岸社区调查数据，代表着巨大的资源投入。通常，这些数据没有得到充分利用，对管理人员的使用仍然有限。在夏威夷群岛，至少有七个独立的实体以不同程度的协调从事珊瑚礁群落的调查。这些数据的综合需要在多个尺度上集成建模方法。本研究在现有数据库的基础上，扩展了现有的两个模型：干扰后珊瑚随机恢复的珊瑚恢复模型（CRM）和酸化和温度增加对珊瑚礁协同影响的COMBO模型。在此基础上，应用两种创新的建模方法（尺度过渡理论和基本生态位模型）在区域尺度上预测珊瑚群落组成和动态。基础生态位建模使用多种数据拟合方法（回归，机器学习等）来描述物种与其环境之间的关系，使用分裂数据集进行训练和验证。该方法可以从离散的数据点生成预测和验证的物种分布空间连续模型。尺度转换模型将使用已完成的物种分布数据库作为物种相互作用发生的景观。这些相互作用是由一个本地模型描述的，在这里，基于珊瑚恢复模型的招募、生长和死亡率。在尺度转换理论中，局部模型加上生物及其环境分布和共分布的景观信息，预测物种组合如何（局部和区域）响应景观上生物和非生物因素的变化。该项目将产生与夏威夷群岛基于生态系统的管理相关的四个产品，产生重大影响，超出研究界：(1)夏威夷群岛范围内的珊瑚分布、底栖生物群落数据、鱼类调查和其他数据的GIS数据库，这些数据由CRAMP、NPS（国家公园管理局）、NOAA的各个部门、夏威夷水生资源部门和其他来源收集到一个单一的GIS数据库；(2)整个群岛珊瑚物种分布的验证、预测和空间连续地图；(3)夏威夷主要岛屿珊瑚礁缓解的经过验证的珊瑚恢复模型；(4)基于已知和预测珊瑚分布和COMBO模型的夏威夷群岛珊瑚群落对气候变化的响应预测。