North Carolina State University, Department of Marine, Earth and Atmospheric Sciences, Center for Marine Sciences and Technology, Morehead City, North Carolina, United States of America.
North Carolina Coastal Reserve and National Estuarine Research Reserve, Beaufort, North Carolina, United States of America.
PLoS One. 2019 Jan 25;14(1):e0210936. doi: 10.1371/journal.pone.0210936. eCollection 2019.
Geospatial habitat suitability index (HSI) models have emerged as powerful tools that integrate pertinent spatial information to guide habitat restoration efforts, but have rarely accounted for spatial variation in ecosystem service provision. In this study, we utilized satellite-derived chlorophyll a concentrations for Pamlico Sound, North Carolina, USA in conjunction with data on water flow velocities and dissolved oxygen concentrations to identify potential restoration locations that would maximize the oyster reef-associated ecosystem service of water filtration. We integrated these novel factors associated with oyster water filtration ecosystem services within an existing, 'Metapopulation Persistence' focused GIS-based, HSI model containing biophysical (e.g., salinity, oyster larval connectivity) and logistical (e.g., distance to nearest restoration material stockpile site) factors to identify suitable locations for oyster restoration that maximize long-term persistence of restored oyster populations and water filtration ecosystem service provision. Furthermore, we compared the 'Water Filtration' optimized HSI with the HSI optimized for 'Metapopulation Persistence,' as well as a hybrid model that optimized for both water filtration and metapopulation persistence. Optimal restoration locations (i.e., locations corresponding to the top 1% of suitability scores) were identified that were consistent among the three HSI scenarios (i.e., "win-win" locations), as well as optimal locations unique to a given HSI scenario (i.e., "tradeoff" locations). The modeling framework utilized in this study can provide guidance to restoration practitioners to maximize the cost-efficiency and ecosystem services value of habitat restoration efforts. Furthermore, the functional relationships between oyster water filtration and chlorophyll a concentrations, water flow velocities, and dissolved oxygen applied in this study can guide field- and lab-testing of hypotheses related to optimal conditions for oyster reef restoration to maximize water quality enhancement benefits.
地理空间栖息地适宜性指数 (HSI) 模型已成为一种强大的工具，可整合相关空间信息，指导栖息地恢复工作，但很少考虑生态系统服务提供的空间变化。在这项研究中，我们利用美国北卡罗来纳州帕姆利科湾的卫星衍生叶绿素 a 浓度数据，结合水流速度和溶解氧浓度数据，确定潜在的恢复地点，以最大限度地提高牡蛎礁相关的水过滤生态系统服务。我们将这些与牡蛎水过滤生态系统服务相关的新因素与现有的基于 GIS 的“复种群生存”重点 HSI 模型相结合，该模型包含生物物理因素（例如盐度、牡蛎幼虫连通性）和物流因素（例如距离最近的恢复材料储存点），以确定适合牡蛎恢复的地点，最大限度地提高恢复后的牡蛎种群和水过滤生态系统服务的长期持久性。此外，我们比较了“水过滤”优化的 HSI 与优化“复种群生存”的 HSI，以及同时优化水过滤和复种群生存的混合模型。确定了最佳恢复地点（即适合度得分最高的前 1%的地点），这些地点在三种 HSI 情景中是一致的（即“双赢”地点），以及在特定 HSI 情景中特有的最佳地点（即“权衡”地点）。本研究中使用的建模框架可以为恢复实践人员提供指导，以最大限度地提高栖息地恢复工作的成本效益和生态系统服务价值。此外，本研究中应用的牡蛎水过滤与叶绿素 a 浓度、水流速度和溶解氧之间的功能关系可以指导与牡蛎礁恢复的最佳条件相关的假设的现场和实验室测试，以最大限度地提高水质改善效益。
