A high resolution hydrodynamic-biogeochemical-oyster-filtration model predicts that the presence of oysters (Crassostrea virginica) can improve, or reduce, water quality depending upon oyster abundance and location

IF 2.6 3区 环境科学与生态学 Q2 ECOLOGY Ecological Modelling Pub Date : 2024-08-28 DOI:10.1016/j.ecolmodel.2024.110833
R.K. Gawde , E.W. North , R.R. Hood , W. Long , H. Wang , M.J. Wilberg
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Abstract

The eastern oyster (Crassostrea virginica) provides numerous ecosystem services such as building reef habitat, clarifying the water by filtering seston, and reducing excess nitrogen when their biodeposits are denitrified. Some of these ecosystem services have been extensively studied using two-dimensional and three-dimensional (3D) models. Yet, the relationship between oyster abundance, their filtration and biodeposition rates, and associated water quality metrics has not been estimated with high-resolution models that include biodeposit resuspension as well as simulation of 3D processes in the sub-tributaries where oysters are abundant. To undertake these estimates, a 3D Regional Ocean Modeling System (ROMS) framework, comprised of a coupled hydrodynamic-water quality model with an oyster filtration and biodeposition sub-model, was implemented over a fine-resolution model grid (120–150 m) of the Choptank River on the eastern shore of Chesapeake Bay, U.S.A. After validation with data from 20 cruises between May and September 2010, the model was used to predict seven variables associated with water quality in simulations with zero, recent, and 50x recent abundances of oysters. Results indicated that improvement in the seven water quality variables differed in response to the abundance of oysters and between regions in the Choptank River. In line with expectations, the water quality metrics improved with increasing oyster abundance in the shallow and retentive sub-tributaries of Broad and Harris Creeks. In contrast, in the deeper and more flushed mainstem of the Choptank River, some water quality metrics deteriorated when recent abundances of oysters were added to the model compared to the simulation with zero oysters and the same metrics improved when oyster abundances were increased by 50x. Overall, model results indicated that the many complex physical and biogeochemical processes that influence the effect of oysters on water quality resulted in differing responses to oysters across different systems. In addition, this study introduces a high-resolution, predictive tool that could be used to estimate the number of oysters needed to meet water quality thresholds in specific systems in support of ecosystem management.

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高分辨率水动力-生物地球化学-牡蛎-过滤模型预测,牡蛎(Crassostrea virginica)的存在可改善或降低水质,具体取决于牡蛎的丰度和位置
东部牡蛎(Crassostrea virginica)提供了许多生态系统服务,如建造珊瑚礁生境、通过过滤沉积物澄清水质,以及在其生物沉积物脱氮时减少过量的氮。其中一些生态系统服务已通过二维和三维(3D)模型进行了广泛研究。然而,对于牡蛎丰度、牡蛎过滤和生物沉积率以及相关水质指标之间的关系,还没有使用高分辨率模型进行估算,这些模型包括生物沉积物再悬浮以及牡蛎丰度所在支流的三维过程模拟。为了进行这些估算,在美国切萨皮克湾东岸 Choptank 河的精细分辨率模型网格(120-150 米)上实施了三维区域海洋建模系统(ROMS)框架,该框架由水力-水质耦合模型和牡蛎过滤与生物沉积子模型组成。在利用 2010 年 5 月至 9 月期间 20 次巡航的数据进行验证后,该模型被用于预测与水质相关的七个变量,模拟牡蛎丰度为零、最近丰度和最近丰度 50 倍的情况。结果表明,七个水质变量的改善程度随牡蛎丰度和乔普坦克河不同区域而不同。与预期一致的是,在布罗德溪和哈里斯溪的浅水和潴留性子支流,水质指标随着牡蛎数量的增加而改善。相反,在较深且水流较急的乔普坦克河干流,与牡蛎丰度为零的模拟相比,当牡蛎丰度增加到模型中时,一些水质指标会恶化,而当牡蛎丰度增加 50 倍时,同样的指标会得到改善。总体而言,模型结果表明,影响牡蛎对水质影响的许多复杂物理和生物地球化学过程导致不同系统对牡蛎的反应不同。此外,这项研究还引入了一种高分辨率的预测工具,可用于估算特定系统中达到水质阈值所需的牡蛎数量,以支持生态系统管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Ecological Modelling
Ecological Modelling 环境科学-生态学
CiteScore
5.60
自引率
6.50%
发文量
259
审稿时长
69 days
期刊介绍: The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources. Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide. We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory. This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions. These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems. The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications. The journal also supports the activities of the [International Society of Ecological Modelling (ISEM)](http://www.isemna.org/).
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