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Integrating ecosystem services considerations within a GIS-based habitat suitability index for oyster restoration

机译:将生态系统服务考虑因素纳入基于GIS的生境适应性指数以进行牡蛎恢复

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摘要

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.
机译:地理空间栖息地适应性指数(HSI)模型已成为一种强大的工具,可以整合相关的空间信息以指导栖息地恢复工作,但很少考虑生态系统服务提供中的空间变化。在这项研究中,我们利用美国北卡罗来纳州帕米利科桑德的卫星衍生叶绿素a浓度,结合水流速度和溶解氧浓度的数据,确定了可能使牡蛎礁相关的生态系统水过滤服务最大化的潜在修复位置。 。我们将这些与牡蛎滤水生态系统服务相关的新颖因素整合到了现有的,以“种群持续性”为重点的基于GIS的HSI模型中,该模型包含生物物理(如盐度,牡蛎幼虫的连通性)和后勤性(如到最近的恢复材料储存地点的距离) )确定合适的牡蛎恢复地点的因素,这些因素可以使恢复的牡蛎种群和水过滤生态系统服务提供的长期持久性最大化。此外,我们将优化了“水过滤”的HSI与针对“种群持久化”进行了优化的HSI,以及针对水过滤和元种群持久化进行了优化的混合模型。确定了三个HSI方案(即“双赢”位置)之间一致的最佳修复位置(即,与适应性得分最高的1%相对应的位置)以及给定HSI方案所独有的最佳位置(即“权衡”位置)。本研究中使用的建模框架可以为恢复从业人员提供指导,以最大程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,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用于本研究,可指导与牡蛎礁恢复最佳条件有关的假设的现场和实验室测试,以最大程度地提高水质。

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