Collaborative Research: A hydrological seesaw and its effect on alkalinity dynamics in estuaries along a climate gradient
合作研究:水文跷跷板及其对气候梯度河口碱度动态的影响
基本信息
- 批准号:2319435
- 负责人:
- 金额:$ 21.36万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-09-01 至 2026-08-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
The main goal of this project is to learn how changes in freshwater conditions in shallow estuaries affect how much alkalinity, or acid-neutralizing capacity, the sediments produce or consume. It is hypothesized that a reduction in freshwater runoff will reduce alkalinity production in sediments via respirational processes that do not require oxygen; and during extreme drought, reduced compounds, for example reduced sulfur, produced from the above processes can be oxidized and generates acids. This project will examine three estuaries along the northwestern Gulf of Mexico with different amounts of freshwater inputs. One of the estuaries that experiences large freshwater runoff changes will be studied in more detail. The objective is to unravel the connection between these changes and the buildup and breakdown of reduced sulfur in the sediments. Additionally, the impact of these processes on the alkalinity of the water column will be assessed. This study will measure water column alkalinity changes and benthic fluxes, examine sedimentary record for historical changes, and conduct modeling to tie field measurements together. Researchers from both Texas A&M University-Corpus Christi (TAMU-CC) and Texas A&M University at Galveston (TAMUG) will work on this project. The team includes two early career scientists. Two graduate students, one from each campus, will use this project to develop their research. Results from this project will be used in classroom instructions as well as outreach activities. These activities include expanding the curriculum for an ongoing NSF National Research Traineeship program at TAMU-CC as well as developing a teaching module for Sea Camp at TAMUG, the latter serves elementary school students. It is known that electron acceptors other than dissolved oxygen can be used by microbes to respire organic carbon in nearshore sediments when the latter is absent. As a results, reduced sulfur is produced and preserved along with organic carbon preservation. However, the rate of this preservation is not constant and is subject to the amounts of nutrients and terrestrial organic carbon that rivers deliver. The results of this study will shed light on the role of hydrological conditions in nearshore alkalinity production and consumption. The findings will also be applied to other coastal regions in the face of decline in freshwater runoff. In addition, the model developed in this project can be used in a wide variety of applications in coastal research and management.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
该项目的主要目标是了解浅水河口淡水条件的变化如何影响沉积物产生或消耗多少碱度或酸中和能力。据推测,淡水径流的减少将通过不需要氧气的呼吸过程减少沉积物中的碱度产生;在极端干旱期间,上述过程产生的还原化合物,例如还原的硫,可以被氧化并产生酸。该项目将研究墨西哥湾西北部的三个河口,这些河口有不同数量的淡水输入。其中一个经历了淡水径流变化较大的河口将被更详细地研究。其目的是揭示这些变化与沉积物中还原硫的积累和分解之间的联系。此外,还将评估这些过程对水柱碱度的影响。这项研究将测量水柱碱度变化和海底通量,检查沉积记录的历史变化,并进行模拟,将现场测量结果联系在一起。来自德克萨斯农工大学科珀斯克里斯蒂分校(TAMU-CC)和德克萨斯农工大学加尔维斯顿分校(TAMUG)的研究人员将致力于这一项目。该团队包括两名职业生涯早期的科学家。两名研究生,每个校区一名,将利用这个项目来开展他们的研究。该项目的成果将用于课堂教学和外联活动。这些活动包括扩展TAMU-CC正在进行的NSF国家研究培训方案的课程,以及为TAMUG的海营开发一个教学模块,后者为小学生服务。已知,当近岸沉积物中没有溶解氧时,微生物可以利用电子受体而不是溶解氧来呼吸有机碳。其结果是,还原硫的生成和保存与有机碳保存一起进行。然而,这种保存的速度并不是恒定的,取决于河流输送的营养物质和陆地有机碳的数量。这项研究的结果将阐明水文条件在近岸碱度生产和消费中的作用。在淡水径流减少的情况下,这一发现也将适用于其他沿海地区。此外,在这个项目中开发的模型可以在海岸研究和管理的广泛应用中使用。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(0)
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Jiabi Du其他文献
Intermittent estuaries deserve global attention as vulnerable and vital ecosystems
间歇性河口作为脆弱而重要的生态系统,值得全球关注。
- DOI:
10.1038/s43247-025-02428-5 - 发表时间:
2025-06-06 - 期刊:
- 影响因子:8.900
- 作者:
Danial Khojasteh;Shivanesh Rao;Sarah McSweeney;Raimundo Ibaceta;Robert J. Nicholls;Jon French;William Glamore;John L. Largier;Janine Adams;Michael G. Hughes;Michael Barry;Hannah E. Power;Jiabi Du;Tobias A. Tucker;Rodrigo Cienfuegos;Patricio A. Catalan;David Hanslow - 通讯作者:
David Hanslow
A Machine‐Learning‐Based Model for Water Quality in Coastal Waters, Taking Dissolved Oxygen and Hypoxia in Chesapeake Bay as an Example
基于机器学习的沿海水域水质模型——以切萨皮克湾溶解氧和缺氧为例
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:5.4
- 作者:
Xin;Jian Shen;Jiabi Du - 通讯作者:
Jiabi Du
An analytical phytoplankton model and its application in the tidal freshwater James River
浮游植物分析模型及其在潮汐淡水詹姆斯河中的应用
- DOI:
- 发表时间:
2019 - 期刊:
- 影响因子:0
- 作者:
Zhengui Wang;Harry Wang;Jian Shen;Fei Ye;Yinglong J. Zhang;F. Chai;Zhuo Liu;Jiabi Du - 通讯作者:
Jiabi Du
Chlorophyll-a in Chesapeake Bay based on VIIRS satellite data: Spatiotemporal variability and prediction with machine learning
基于 VIIRS 卫星数据的切萨皮克湾叶绿素-a:时空变化和机器学习预测
- DOI:
- 发表时间:
2022 - 期刊:
- 影响因子:3.2
- 作者:
Xin Yu;Jian Shen;G. Zheng;Jiabi Du - 通讯作者:
Jiabi Du
An inverse approach to estimate bacterial loading into an estuary by using field observations and residence time.
通过现场观察和停留时间来估计进入河口的细菌负荷的逆向方法。
- DOI:
10.1016/j.marenvres.2021.105263 - 发表时间:
2021 - 期刊:
- 影响因子:3.3
- 作者:
Xin Yu;Jian Shen;Jiabi Du - 通讯作者:
Jiabi Du
Jiabi Du的其他文献
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