Intensified acidification has emerged as an increasing threat to the health of global coastal ecosystems,and decreasing pH trends have been observed in Chinese coastal waters.However,the drivers in complex regions lik...Intensified acidification has emerged as an increasing threat to the health of global coastal ecosystems,and decreasing pH trends have been observed in Chinese coastal waters.However,the drivers in complex regions like Hangzhou Bay remain poorly understood due to the lack of high-resolution time-series data.Thus,utilizing two years of hourly data(2019−2020)from two buoy stations,this study analyzes the key variables driving pH variability and develops a highperformance support vector regression(SVR)model for pH estimation,which achieves a coefficient of determination(R2)of 0.72 on an independent testing dataset.This model was then used to reconstruct a continuous daily sea surface pH dataset,which reveals a clear seasonal pH cycle with minimums in summer and maximums in winter.This pattern arises from a complex interplay among multiple factors.River runoff is the dominant influence in summer,whereas temperature and biological activity primarily shape the pH patterns in other seasons.The pronounced pH variability and the strong,runoff-driven summer minimum highlight the region’s heightened vulnerability to episodic acidification.This work provides key insights into the drivers of sea surface pH in Hangzhou Bay,improving the understanding of the nearshore carbonate system and its ecological responses to global change in a complex estuarine environment.展开更多
The flux of dissolved inorganic nitrogen(DIN),predominantly nitrate(NO3-)and ammonium(NH4+),from land to coastal waters via rivers is commonly estimated simply by multiplying water flux with nitrogen conce...The flux of dissolved inorganic nitrogen(DIN),predominantly nitrate(NO3-)and ammonium(NH4+),from land to coastal waters via rivers is commonly estimated simply by multiplying water flux with nitrogen concentration.Understanding DIN fluxes in gated estuaries is critical as these systems often serve as hotspots for nutrient transformations,influencing coastal water quality and ecosystem health.However,the subsequent interactions involving NO3-and NH4+adsorption or desorption on suspended sediments are often overlooked.To better understand the impact of these interactions on the overall NO3-and NH4+sorption or desorption and subsequently,the mobility and transport to the coastal zone,we conducted a series of NO3-and NH4+adsorption and desorption experiments.These experiments involved varying suspended sediment concentrations,particle sizes,salinities,and sea-salt ions to assess their potential effects.Results indicate that desorption of NO3-and NH4+from suspended sediments is more prominent than adsorption,with NH4+desorption being particularly significant.Notably,at low suspended particle concentrations and high salinity,NH4+desorption from sediments increased markedly,which further amplified in polyhaline conditions.This effect could result from ion pairing between NH4+and seawater anions,along with competition from seawater cations for sediment cation exchange sites,enhancing NH4+diffusion from estuarine sediments,and the elevated NH4+release could promote DIN transport to nearshore waters,especially in gated estuaries where sediment resuspension occurs.Given the critical role of NH4+in estuarine nitrogen cycling,ignoring these dynamics could lead to underestimations of DIN transport in river-estuary systems.Therefore,incorporating sediment dynamics into DIN flux estimations is crucial for accurately assessing nitrogen transport in gated estuaries.展开更多
Oceanic dissolved oxygen(DO)in the ocean has an indispensable role on supporting biological respiration,maintaining ecological balance and promoting nutrient cycling.According to existing research,the total DO has dec...Oceanic dissolved oxygen(DO)in the ocean has an indispensable role on supporting biological respiration,maintaining ecological balance and promoting nutrient cycling.According to existing research,the total DO has declined by 2%of the total over the past 50 a,and the tropical Pacific Ocean occupied the largest oxygen minimum zone(OMZ)areas.However,the sparse observation data is limited to understanding the dynamic variation and trend of ocean using traditional interpolation methods.In this study,we applied different machine learning algorithms to fit regression models between measured DO,ocean reanalysis physical variables,and spatiotemporal variables.We demonstrate that extreme gradient boosting(XGBoost)model has the best performance,hereby reconstructing a four-dimensional DO dataset of the tropical Pacific Ocean from 1920 to 2023.The results reveal that XGBoost significantly improves the reconstruction performance in the tropical Pacific Ocean,with a 35.3%reduction in root mean-squared error and a 39.5%decrease in mean absolute error.Additionally,we compare the results with three Coupled Model Intercomparison Project Phase 6(CMIP6)models data to confirm the high accuracy of the 4-dimensional reconstruction.Overall,the OMZ mainly dominates the eastern tropical Pacific Ocean,with a slow expansion.This study used XGBoost to efficiently reconstructing 4-dimensional DO enhancing the understanding of the hypoxic expansion in the tropical Pacific Ocean and we foresee that this approach would be extended to reconstruct more ocean elements.展开更多
基金The National Natural Science Foundation of China under contract No.42576185the Zhejiang Provincial Natural Science Foundation of China under contract No.LD24D060002+1 种基金Funds for Special Projects of the Central Government in Guidance of Local Science and Technology Development under contract No.2025ZY01111the Project of Sanya Yazhou Bay Science and Technology City under contract No.SKJC-JYRC-2025-52.
摘要Intensified acidification has emerged as an increasing threat to the health of global coastal ecosystems,and decreasing pH trends have been observed in Chinese coastal waters.However,the drivers in complex regions like Hangzhou Bay remain poorly understood due to the lack of high-resolution time-series data.Thus,utilizing two years of hourly data(2019−2020)from two buoy stations,this study analyzes the key variables driving pH variability and develops a highperformance support vector regression(SVR)model for pH estimation,which achieves a coefficient of determination(R2)of 0.72 on an independent testing dataset.This model was then used to reconstruct a continuous daily sea surface pH dataset,which reveals a clear seasonal pH cycle with minimums in summer and maximums in winter.This pattern arises from a complex interplay among multiple factors.River runoff is the dominant influence in summer,whereas temperature and biological activity primarily shape the pH patterns in other seasons.The pronounced pH variability and the strong,runoff-driven summer minimum highlight the region’s heightened vulnerability to episodic acidification.This work provides key insights into the drivers of sea surface pH in Hangzhou Bay,improving the understanding of the nearshore carbonate system and its ecological responses to global change in a complex estuarine environment.
基金Supported by the Tianjin Key R&D Program(No.21YFSNSN00220)。
摘要The flux of dissolved inorganic nitrogen(DIN),predominantly nitrate(NO3-)and ammonium(NH4+),from land to coastal waters via rivers is commonly estimated simply by multiplying water flux with nitrogen concentration.Understanding DIN fluxes in gated estuaries is critical as these systems often serve as hotspots for nutrient transformations,influencing coastal water quality and ecosystem health.However,the subsequent interactions involving NO3-and NH4+adsorption or desorption on suspended sediments are often overlooked.To better understand the impact of these interactions on the overall NO3-and NH4+sorption or desorption and subsequently,the mobility and transport to the coastal zone,we conducted a series of NO3-and NH4+adsorption and desorption experiments.These experiments involved varying suspended sediment concentrations,particle sizes,salinities,and sea-salt ions to assess their potential effects.Results indicate that desorption of NO3-and NH4+from suspended sediments is more prominent than adsorption,with NH4+desorption being particularly significant.Notably,at low suspended particle concentrations and high salinity,NH4+desorption from sediments increased markedly,which further amplified in polyhaline conditions.This effect could result from ion pairing between NH4+and seawater anions,along with competition from seawater cations for sediment cation exchange sites,enhancing NH4+diffusion from estuarine sediments,and the elevated NH4+release could promote DIN transport to nearshore waters,especially in gated estuaries where sediment resuspension occurs.Given the critical role of NH4+in estuarine nitrogen cycling,ignoring these dynamics could lead to underestimations of DIN transport in river-estuary systems.Therefore,incorporating sediment dynamics into DIN flux estimations is crucial for accurately assessing nitrogen transport in gated estuaries.
基金The National Natural Science Foundation of China under contract Nos T2421002, 623B2071,and 42125601the National Key R&D Program of China under contract No. 2023YFF0805300
摘要Oceanic dissolved oxygen(DO)in the ocean has an indispensable role on supporting biological respiration,maintaining ecological balance and promoting nutrient cycling.According to existing research,the total DO has declined by 2%of the total over the past 50 a,and the tropical Pacific Ocean occupied the largest oxygen minimum zone(OMZ)areas.However,the sparse observation data is limited to understanding the dynamic variation and trend of ocean using traditional interpolation methods.In this study,we applied different machine learning algorithms to fit regression models between measured DO,ocean reanalysis physical variables,and spatiotemporal variables.We demonstrate that extreme gradient boosting(XGBoost)model has the best performance,hereby reconstructing a four-dimensional DO dataset of the tropical Pacific Ocean from 1920 to 2023.The results reveal that XGBoost significantly improves the reconstruction performance in the tropical Pacific Ocean,with a 35.3%reduction in root mean-squared error and a 39.5%decrease in mean absolute error.Additionally,we compare the results with three Coupled Model Intercomparison Project Phase 6(CMIP6)models data to confirm the high accuracy of the 4-dimensional reconstruction.Overall,the OMZ mainly dominates the eastern tropical Pacific Ocean,with a slow expansion.This study used XGBoost to efficiently reconstructing 4-dimensional DO enhancing the understanding of the hypoxic expansion in the tropical Pacific Ocean and we foresee that this approach would be extended to reconstruct more ocean elements.