The biological pump, driven by phytoplankton production and death, plays a crucial role in the ocean’s sequestration of atmospheric CO₂. In particular, marginal seas with high primary productivity show a significant capacity for carbon fixation. Variations in phytoplankton biomass and community structure are key factors influencing the efficiency of the marine biological pump. The Taiwan Strait (TS) is a unique shallow conduit that connects the East China Sea (ECS) and the South China Sea (SCS), which are subject to seasonal monsoons and episodic events (e.g., typhoons and floods). Thus, its planktonic ecosystem is significantly influenced by physical processes such as strong ocean currents, coastal upwelling and river discharge, resulting in noticeable seasonal variability. In this study, we examined spatiotemporal patterns of phytoplankton biomass and community structure using phytoplankton-sourced biomarkers from suspended particles in surface waters across all four seasons from 2019 to 2020 in the TS. The findings highlight notable seasonal disparities in phytoplankton biomass, with spring and summer exhibiting significantly higher levels compared to autumn and winter. In order to determine phytoplankton ecosystem responses to various physical and biological processes on a seasonal scale, we used Empirical Orthogonal/Eigen Function (EOF) analysis to investigate the covarying spatiotemporal patterns of: marine-sourced biomarkers and terrestrial-sourced biomarkers in surface suspended particles, a biomass indicator (Chl a), water-mass indicators [sea surface temperature (SST), sea surface salinity (SSS), nutrients], and a hydrodynamic indicator [total suspended solids at surface/bottom water, (TSS_S and TSS_B)]. The results identified six physical-biological coupling modes that influence seasonal variations in marine phytoplankton ecosystems within the energetic strait system. Additionally, an in-depth understanding of the coupling between physical process and lipid biomarker signals from suspended particles in the contemporary marine environment can offer valuable insights for interpreting ancient sediment records of phytoplankton ecosystem evolution in the TS.

The characteristics of the terrain of a strait can lead to a “fine tube” effect that enhances a monsoon and thereby affects the physical, chemical, and biological processes of marine ecosystems. This effect is a highly dynamic and complex phenomenon involving interactions among atmospheric, oceanic, and terrestrial systems, as well as biogeochemical cycles and biological responses driven by it. However, current understanding has been focused mainly on the differences between monsoons, and there have been few studies concerned with the weakening or strengthening of monsoons. To explore the biogeochemical and phytoplankton responses during varying intensities of the northeast (NE) monsoon in the Taiwan Strait, high-resolution, across-front observations combined with FerryBox online data and satellite observations were conducted in this study during a strong, moderate, and weak NE monsoon. The spatiotemporal changes of nutrient concentrations and phytoplankton communities were regulated by the dynamics of ocean currents forced by NE winds. The weakening of the NE monsoon caused shrinkage of the coastal currents that led to a reduction of nutrient concentrations and an alteration of the distribution patterns of phytoplankton communities along cross-front sections. Specifically, there was a notable decrease in the proportions of dinoflagellates and cryptophytes in inshore regions and of prasinophytes in offshore areas. This study showed for the first time the dynamics of phytoplankton with changes of ocean currents during varying intensities of the NE monsoon in a strait system. The findings helped to elucidate the general spatial patterns of the phytoplankton community based on satellite-derived surface temperature and wind patterns and further enhanced the understanding of biogeochemical cycles in marine systems.

As the most important component of marine siliceous organisms, diatoms are vital primary producers of the ocean that are often used as indicators of paleoenvironmental change. To understand the response of sedimental diatoms to regional environmental changes and the factors affecting the distribution of sedimental diatoms in the Taiwan Strait, this study quantified and classified the diatoms found in surface sediments collected during four surveys from 2019 to 2020. Overall, 118 diatom taxa and 44 genera were identified with total diatom abundance of 8–27 353 valves/g. Four diatom assemblages representing different environments were identified. Among them, assemblage Ⅰ represented a coastal environment, assemblage Ⅱ comprised warm water species of a coastal environment, Assemblage Ⅲ represented a coastal environment affected markedly by exorheism, Assemblage Ⅳ represented a group with lowest diatom abundance. Seasonal variation in total diatom abundance was controlled by seven environmental factors: depth, sea surface salinity, mean grain size, silicate, nitrite, nitrate, and phosphate. Spatiotemporal variation in each of the diatom assemblages was substantial and strongly affected by various currents, upwelling, and low-salinity water. Specifically, it was found that the succession of diatom assemblages reflects change in the range of influence of local warm currents.

The Macao Special Administrative Region is located in the southeastern coastal area of China. The region of Macao was narrow in the history, so land reclamation has become a main means of expanding its geographical scope. Exploring the significance of land reclamation for the planning and urban construction of the Macao region provides valuable references. (1) The Google Earth Engine (GEE) cloud processing platform is used in this study to calculate the modified normalized difference water index (MNDWI) based on Landsat data from 1986 to 2021; (2) the Jenks natural index classification method is used to extract the water body range, and the water body boundary as well as area at different periods is calculated combined with the neural network classification method in the environment for visualizing images (ENVI) software; (3) this study then combines the patch-generating land use simulation (PLUS) model to predict the future trend of shoreline changes in the study area in 2036. The result indicates that the MNDWI and neural net classification method lead to a high classification accuracy with both the overall accuracy (OA) and Kappa coefficient being higher than 87%. Land reclamation activities in Macao were gradually intense from 1986 to 2021, with social and economic conditions such as transportation being main influencing factors, which provides valuable references and inspiration for the regional planning of the Macao Special Administrative Region.

Forecasting of ocean currents is critical for both marine meteorological research and ocean engineering and construction. Timely and accurate forecasting of coastal current velocities offers a scientific foundation and decision support for multiple practices such as search and rescue, disaster avoidance and remediation, and offshore construction. This research established a framework to generate short-term surface current forecasts based on ensemble machine learning trained on high frequency radar observation. Results indicate that an ensemble algorithm that used random forests to filter forecasting features by weighting them, and then used the AdaBoost method to forecast can significantly reduce the model training time, while ensuring the model forecasting effectiveness, with great economic benefits. Model accuracy is a function of surface current variability and the forecasting horizon. In order to improve the forecasting capability and accuracy of the model, the model structure of the ensemble algorithm was optimized, and the random forest algorithm was used to dynamically select model features. The results show that the error variation of the optimized surface current forecasting model has a more regular error variation, and the importance of the features varies with the forecasting time-step. At ten-step ahead forecasting horizon the model reported root mean square error, mean absolute error, and correlation coefficient by 2.84 cm/s, 2.02 cm/s, and 0.96, respectively. The model error is affected by factors such as topography, boundaries, and geometric accuracy of the observation system. This paper demonstrates the potential of ensemble-based machine learning algorithm to improve forecasting of ocean currents.

The element iron limitation is one of the crucial factors contributing to high nutrient low chlorophyll in the Southern Ocean (SO). Mixed layer dynamics regulate the availability of iron to phytoplankton. In this paper, we investigate the influence of surface iron supplementation triggered by the mixed layer depth (MLD) variation on chlorophyll-a (Chl-a) concentration in the SO on seasonal and interannual timescales. This analysis is based on the Biogeochemical Southern Ocean State Estimate for the period from 2013 to 2021. We provide a comprehensive and systematic mapping of the regions within the SO, where Chl-a is affected by iron input related to MLD deepening. The relationship between the MLD and the Chl-a varies with the latitude on the seasonal time scale. Both the MLD and sea ice melting affect the distribution of Chl-a. On the interannual scale, iron supply due to MLD deepening occurs primarily north of 60°S. Horizontal advection-induced entrainment enhances the surface iron input during the austral summer, which favors Chl-a increase. In addition to the MLD, the melting of sea ice and cooling of the sea surface can also alter iron input and subsequently affect Chl-a distribution in the austral summer. During the austral winter, entrainment can boost iron stocks, stimulating a subsequent spring increase of Chl-a in the SO. Furthermore, sea surface temperature declines during the austral winter, promoting an increased iron supply and creating favorable conditions for the subsequent spring Chl-a increase in the SO.

The marine hydrological process is still unclear due to scarce observations. Based on stable water isotopes in surface seawater along the 33rd Chinese National Antarctic Science Expedition from November 2016 to April 2017, this study explored the hydrological processes in the Pacific, Indian and Southern oceans. The results show that the Northwest Pacific (0°–26°N) is a region with strong evaporation (the δ¹⁸O-δD slope is 6.58), while the southern Indian Ocean is a region with strong precipitation (the δ¹⁸O-δD slope is 9.57). The influence of continental runoff and water mass mixing reduces the correlation between δ¹⁸O and salinity in the eastern Indian Ocean. The characteristics of the isotopes and hydrological parameters indicate that the Agulhas Front and sub-Tropical Convergence do not merge in the Antarctic–Indian Ocean region. The freezing of sea ice near the Antarctic continent decreases the δ¹⁸O and δD by 0.40‰ and 7.0‰, respectively, compared with those near 67°S. This study is helpful for understanding marine hydrological processes and promoting the understanding and research of the nature of ocean responses in the context of climate change.

The Canada Basin is the largest basin in the Arctic Ocean. Its unique physical features have the highest concentration of nutrients being found in the subsurface layer, referred to as the subsurface nutrient maximum layer (SNM). Under climate change in the Arctic, the SNM is an essential material base for primary productivity. However, long-term trends of nutrient variations and dominant factors related to nutrient levels in the SNM are still unclear. In this study, we analyzed the SNM variations and main influencing factors of the Canada Basin based on the Global Ocean Data Analysis Project Version 2 between 1990 and 2015 and the Chinese Arctic Research Expedition between 2010 and 2016. We found that the nutrient concentrations in the SNM were relatively stable for decades [average concentrations of nitrate, phosphate, and silicate were (13.6 ± 2.4) μmol/L, (1.8 ± 0.2) μmol/L, and (31.5 ± 5.7) μmol/L, respectively]. Nutrient reservoirs were dominated by physical processes. Inflow and outflow water of the SNM contributed about 60.4% and −50.2% to the nutrient stocks, respectively, while particle deposition and remineralization in the Canada Basin contributed approximately one-third to the nutrient stocks. Nitrogen fixation and denitrification in the Canada Basin had no substantial impact on nutrient stocks. The overall stabilization of the SNM over the past few decades implied that the SNM would not substantially affect short term primary productivity. Understanding the long-term trends and dominant factors of reservoirs in the SNM will provide useful insights into the changing Canada Basin ecosystem.

To understand the temporal and spatial variations in nutrient dynamics, as well as the potential cross-shelf transport of nutrients between the East China Sea (ECS) shelf and the northwestern Pacific Ocean, six field observations covering the ECS were conducted in spring, summer, and autumn in 2011 and 2013. Nutrient dynamics in the ECS and nutrient exchange between shelf water and the open ocean were examined. High concentrations of dissolved inorganic nutrients were detected in the nearshore surface layer and offshore bottom layer in different seasons, and the concentrations of dissolved inorganic nutrients in surface seawater were lower in summer and autumn than in spring. The concentrations of dissolved organic nutrients in Kuroshio surface water were slightly lower in summer than in spring, but the concentrations in Kuroshio subsurface water were slightly higher in summer than in spring. There were abundant nutrient reservoirs in the euphotic zone of the ECS, which explained the high primary productivity. The evaluation of cross-shelf transport indicated that nutrients from shelf water were transported out across the 200 m isobath through the surface layer with the density (σ) less than 23.0 kg/m³ in spring. The flux of dissolved inorganic nitrogen transported from the ECS shelf to the Northwest Pacific Ocean in spring was equivalent to 21% of the atmospheric nitrogen deposition in the Northwest Pacific Ocean. In summer, the onshore flux in the surface and bottom layers accounted for 80% of the total flux, and the transportation of nutrients along the surface layer to the continental shelf contributed to the nutrient storage and primary productivity of the euphotic zone in the ECS shelf in summer.

Global carbon cycle has received extensive attention, among which the river-estuary system is one of the important links connecting the carbon cycle between land and ocean. In this paper, the distribution and control factors of particulate organic carbon (POC) were studied by using the data of organic carbon contents and its carbon isotopic composition (δ¹³C) in the mainstream and estuary of Passur River in the Sundarbans area, combined with the hydrological and biological data measured by CTD. The results show that POC content ranged from 0.263 mg/L to 9.292 mg/L, and the POC content in the river section (averaged 4.129 mg/L) was significantly higher than that in the estuary area (averaged 0.858 mg/L). Two distinct stages of POC transport from land to sea in the Sundarbans area were identified. The first stage occurred in the river section, where POC distribution was mainly controlled by the dynamic process of runoff and the organic carbon was mainly terrestrial source. The second stage occurred during estuarine mixing, where the POC distribution was mainly controlled by the mixing process of seawater and freshwater. The source of POC was predominantly marine and exhibiting vertical differences. The surface and middle layers were primarily influenced by marine sources, while the bottom layer was jointly controlled by terrestrial and marine sources of organic carbon. These findings are of great significance for understanding the carbon cycle in such a large mangrove ecosystem like the Sundarbans mangrove.