数字农科院2.0

Enhanced Carbon Sequestration Potential Following Sediment Dredging in River Ecosystems: Insights into CO2 Fluxes, Phytoplankton, and Carbon Fixation Pathway Responses

文献类型： 外文期刊

作者： Hao, Zhuo;Chen, Shibo;Zhang, Qingwen;Liu, Bing;Chen, Shanghong

作者机构：

关键词： CO2 flux;carbonfixation pathway;carbon sequestration potential;phytoplankton

期刊名称： ENVIRONMENTAL SCIENCE & TECHNOLOGY

ISSN： 0013-936X

年卷期： 2025 年

页码：

收录情况： SCIE（2025版） ; ; EI（2025版）

摘要： River systems play crucial roles in the global carbon balance; however, the environmental consequences of sediment dredging on carbon dioxide (CO2) emissions and carbon sequestration potential remain poorly understood. This study presents the first systematic investigation linking sediment dredging to long-term carbon sequestration dynamics in river ecosystems, addressing critical uncertainties in anthropogenic impacts on aquatic carbon balance. Over a three-year period, dredging significantly altered CO2 flux (fCO(2)) and dissolved CO2 partial pressure (pCO(2)), with pronounced seasonal variability driven by dissolved organic carbon as a key predictor. Microbial community composition shifted from Cyanobacteria to Gammaproteobacteria and Flavobacteria dominance, accompanied by enhanced Calvin cycle enzyme gene expression and suppression of alternative carbon fixation pathways. While phytoplankton biomass, particularly Cyanobacteria, declined sharply during dredging, carbon sequestration potential exceeded predredging levels within three years of monitoring, indicating strong resilience in riverine carbon storage capacity. Our findings indicate that (1) dredging-induced community restructuring enhances chemoautotrophic carbon fixation through modified expression of rTCA cycle components and Calvin cycle optimization, (2) phytoplankton carbon biomass and chlorophyll a emerge as primary drivers of postdredging carbon sequestration pathways, and (3) gross primary production peaks at 960.8 mg C m(-2) d(-1) through synergistic phytoplankton interactions. These mechanistic discoveries, which quantify relationships between microbial taxa, metabolic gene expression, and carbon fluxes, establish new insights for predicting ecosystem responses to anthropogenic disturbances in river ecosystems.

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