The establishment of effective proxies for the differentiation of sedimentary facies in the tide-dominated river mouth is fundamental to the delineation of stratigraphy and the study of paleoenvironments. Geochemical signatures of the acetic acid (HAc) extractive phases of alkaline earth metals, such as Sr, Ba, and Ca, are closely related to sedimentary environments and thus provide a novel method for discriminating the sedimentary facies of river mouth. In this study, 50 surface water and surface sediment samples were obtained from different geomorphological units of the Jiulong River mouth, i.e., river channel, distributary channel, delta front, delta front slope, prodelta, and shallow marine area, and the salinity of the water, the grain size, and the Sr, Ba, and Ca contents and Sr/Ba molar ratio (Sr/Ba) in HAc leachates of the sediments were determined. Contents of alkaline earth metals in HAc leachates of surface sediments from the Changjiang (Yangtze) River coast were also collated. The goals of this study were to reveal the spatial distribution of alkaline earth metals in the Jiulong River mouth, define their depositional mechanisms, and search for effective geochemical proxies for identification of the various sedimentary facies in the fluvial to marine transition zone. The results revealed several land-to-sea gradients. The Ba content decreased rapidly from the distributary channel to the sea, and the Sr and Ca contents and Sr/Ba increased gradually with the increase in salinity. Salinity, marine biomass, and sedimentary dynamic processes, were speculated to be the main reasons for the differences in their spatial distributions. There were significant differences in Ba, Sr, Ca, and Sr/Ba between the river channel and the distributary channel, in Ca and Ba between the distributary channel and the delta front (slope), and in Sr, Ca, and Sr/Ba between the delta front (slope) and the prodelta–shallow marine region. The Sr–Ba scatterplot showed that the sediments of the river channel and alluvial plain were located as a high Ba and low Sr element-defined end-member, whereas samples of the prodelta and shallow marine formed a high Sr and low Ba end-member. These can be used as characteristic end-members indicating terrestrial facies and marine facies, respectively. The sediments of the delta plain, tidal river, distributary channel, delta front, and delta front slope are located between these two end-member regions of the scatterplot, and this region of the diagram can be used to identify land–sea transitional sedimentary facies.

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 lanternfishes are mesopelagic fish that are highly productive as common bycatch of deep-sea shrimp trawlers, but they are often neglected or discarded. Despite being one of the dominant lanternfish species in the Arabian Sea, little is known about the life history of Diaphus thiollierei and its role in marine ecosystems. In this study, 103 D. thiollierei were collected in the Arabian Sea during October-November 2020 to study population growth based on sagittal otolith daily ages; and 10 fish collected during April–May 2021 were subjected to otolith microchemistry analysis to reconstruct the vertical migration in their life history using LA-ICP-MS technique. The standard length–dry weight (SL-DW) relationships for D. thiollierei revealed both negative allometric growth and a significant difference between the sexes. Using daily growth annuli counts on the sagittal section of otoliths, the von Bertalanffy growth equation for D. thiollierei was determined. The pattern of four elemental ratios (Sr to Ca, Mg to Ca, Li to Ca, and Ba to Ca) in sagittal otolith suggested that, in general, D. thiollierei descended continually after hatching until the post-larval (PL) stage when they reached a depth of approximately 200 m. Subsequently, from the PL stage to the post-metamorphosis Ⅱ (PM Ⅱ) stage, D. thiollierei likely further sank from 200 m to a depth of approximately 300 m, and then in the daytime they were at a depth of approximately 300–800 m to take refuge from predators. This pilot study explored to unravel the vertical migration during life history in D. thiollierei from sagittal otoliths, whereas further investigation on otolith is needed to better delineate the population ecology in detail, and thus to provide basic information for the exploitation of the lanternfish resource and the understanding of their ecological roles.

Aquaculture, as the fastest-growing food production sector in the world, is becoming an increasingly nonnegligible source of greenhouse gas emissions. Despite this, there has been limited research on nitrous oxide (N₂O) emission from marine aquaculture in China, where more marine aquaculture occurs than anywhere else, globally. We estimated N₂O emissions (E) from marine mariculture of 10 fish and 6 crustacean species in China from 2003 to 2022 using production data from the China Fishery Statistical Yearbook (2004–2023), and data for feed conversion rates and types from the literature. From 2003, marine aquaculture production, the annual N₂O emissions (E_A), and the annual N₂O emissions per unit of aquaculture area (EI_A) trend upward. The E_A of fish culture was lower than that of crustaceans, but the EI_A of fish culture was generally higher. Sea bass (0.308 Tg/a, in terms of N) and white shrimp (0.945 Tg/a, in terms of N) had the highest average E_A among fish and crustacean cultures, respectively. The highest average E_A from fish and crustacean were both Guangdong Province (fish: 0.248 Tg, crustacean: 0.547 Tg), and the highest sea area were both the South China Sea (fish: 0.316 Tg, crustacean: 1.082 Tg); the highest average EI_A for fish and crustacean were Tianjin City [35.40 t/(hm²·a)] and Guangxi Zhuang Autonomous Region [19.83 t/(hm²·a)], respectively, and the highest sea areas were both the South China Sea (fish: 0.316 Tg, crustacean: 1.082 Tg). These analyses provide baseline data for a greenhouse gas emissions inventory for China, based on an interpretation of them, we provide recommendations for reducing N₂O emissions in marine fish and crustacean culture.

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.

Under global climate change, water flow and related nutrient biogeochemistry in the Arctic are changing at an unprecedented rate, and potentially affect nutrient cycling in the Arctic Ocean. However, nutrient fluxes via submarine groundwater discharge (SGD) are potentially important yet poorly understood in the Arctic. Here we quantified that nutrient fluxes through radium-derived SGD were three orders of magnitude higher than those from the local river and constituted 25%−96% of the total nutrient inputs into the Kongsfjorden. These large groundwater nutrient fluxes with high NIN/DIP molar ratio (average 99) may change the biomass and community structure of phytoplankton. Meanwhile, combining other SGD study cases around the Arctic region, SGD rates tend to increase over the past three decades, possibly on account of the effects of global warming. The SGD-derived nutrient may cause the increase of net primary productivity in the Arctic Ocean. The results will provide important basic data for land-ocean interactions in the typical fjord of the Arctic under the influence of global warming.

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.

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.

Understanding the dynamics of phytoplankton communities in coastal zones is crucial for the management and conservation of coastal ecosystems. Previous research indicated that the phytoplankton community structure and dominant taxa in the Bohai Sea (BHS) have exhibited significant shifts from the 1990s to the early 2010s in response to environmental changes, especially the change in nutrient structure. This study comprehensively investigated the variations in net-collected phytoplankton (>76 μm) community structure, diversity, and environmental factors in the BHS during the late summers of 2011−2020, aiming to understand the recent trend in phytoplankton community structure and to explore the interactions between the communities and the environment. During the study period, the nutrient status in the BHS was characterized by a decrease in dissolved inorganic nitrogen (DIN) concentration, an increase in dissolved inorganic phosphorus (DIP) concentration, and a return of the nitrogen-to-phosphorus (N/P) molar ratio (hereinafter referred to as N/P ratio) to the Redfield ratio since 2016. The eutrophication index (EI) in the BHS remained stable and was generally at a low level (<1). The Dia/Dino index fluctuated but did not show an obvious trend. Overall, the eutrophication, the imbalance in nutrient ratio, and the shift in phytoplankton community structure did not continue during the study period. The increased abundance of phytoplankton was strongly associated with elevated concentrations of DIN, as well as higher N/P and nitrogen-to-silicon (N/Si) ratios, whereas the greater diversity was strongly linked to higher concentrations of DIP. Diatoms and dinoflagellates showed significant differences in their interactions with the environment, and their relative dominance was related to water column depth and stratification intensity; their impacts on the phytoplankton community diversity were also significantly different. The variations of certain dominant species, i.e., Skeletonema costatum, Paralia sulcata, and Tripos longipes, exhibited strong links to the changes in nutrient structure in the BHS. The findings of this study contribute to understanding the regional environmental changes and provide insights into the adaptive strategies of coastal ecosystems in response to environmental shifts and fluctuations.

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.