Suspended particulate matter (SPM) plays a key role in the “source-sink” deposition system, and internal isolated waves, a common dynamical phenomenon in the South China Sea, have been shown to be an important factor influencing the distribution of SPM and the deposition process. The study was carried out in September 2022 in the sea area from Luzon Strait to Dongsha Islands, using LISST-deep and CTD equipment for simultaneous observation to study the distribution of suspended particulate matter in terms of particle size and volume concentration. The satellite remote sensing data during the investigation period were used to delineate the influence range of internal isolated waves and to reveal the influence of internal isolated waves on the characterization changes of suspended particulate matter during transport from a kinetic point of view. It was found that: (1) the distribution of suspended particulate matter of smaller sizes (15−25 μm) was dominated in the amplitude depth interval (6−79 m) of the inner isolated wave, and the closer the depth of the trough of the inner isolated wave was, the higher the frequency of the occurrence of suspended particulate matter of smaller sizes. (2) The distribution of suspended particles spreads from the center of the inner isolated wave crest line to both sides, forming a low volume concentration zone (≤91 μL/L) in the center, and forming a high concentration zone (≥500 μL/L) on both sides of the crest line and the distal end of the propagation path of the inner isolated wave. In addition, the study further reveals that the internal isolated wave breaks down the aggregated suspended particles into smaller size and single composition particles through modification, and changes the volume concentration distribution of the suspended particles at different locations of the crest line, propagation path and amplitude depth through control, which provides an important theoretical basis for the understanding of the South China Sea source-sink deposition system.

Shoreline erosion prediction is one of the hot issues in coastal dynamic geomorphology research. Based on the long short term memory (LSTM), the data of shoreline, water depth, intertidal zone width , and wave and tidal current for ERA5 inversion clollected from 1985 to 2023 near Sheyang County of Jiangsu Province were used to construct a coastal erosion risk prediction model in this study. The prediction model could accurately predict the nonlinear/linear change trend of accelerated erosion, stable erosion or coastline sedimentation. The results showed that the increasing of wave and tidal currents was the main factor of coastal erosion in Sheyang area in recent 20 years under the condition of sand source reduction. Besides, an ideal experiment of coastal protection activities was conducted by using the prediction model, and the protection effects of coastal reinforcement, wave dissipation and weak current engineering were discussed. The results showed that the protection effect of coastal reinforcement is the best, and wave dissipation is better than weak current. The prediction model is reasonable, and has great application value and development potential.

The Chukchi Borderland served as the critical gateway for the inflow of Atlantic Water (AW, which is the most important heat storage layer in the Arctic Ocean) into the Canada Basin in the western Arctic Ocean. One of the key issues is how the AW and Pacific Winter Water (PWW) interacts in this complex topography region. The answer to this question will shed light on the important role of AW in the Arctic Ocean. In this study, based on the multi-sources’ quality controlled hydrographic data during 1999−2021, the variation of AW, PWW and the double-diffusive staircases in the Chukchi Borderland are studied in details. We identified three anomalous warm events of AW that occurred in year 2000, 2012 and 2018 with the maximum potential temperature over 1℃. The vertical averaged heat content between the PWW and AW shows a warming trend in the central and eastern region of the Chukchi Borderland. The major reason for this is the warming of PWW. The depth of PWW is more sensitive to the shifting of the Beaufort Gyre (BG) than that of the AW. The combined changes of PWW and AW lead to the variation of double-diffusive staircases, which show a regime shift from large to small thickness and to largely decayed in the Canada Basin. Our results suggest that the major mechanism for this transition is the cooling of AW along with the stronger stratification that restricts the vertical mixing for all.

Sediment oxygen consumption (SOC) is an important parameter of marine sediments and an important characterization parameter of the rate of organic carbon mineralization in seafloor sediments, and the study of SOC can help us to understand the carbon cycling process in the whole ocean. As one of the most important and active sites for organic carbon mineralization and burial, marginal seas have received widespread attention and research around the world, but there is still a lack of relevant attention to the Chinese marginal sea region with typical seasonal variations of the marine environment, especially the Yellow Sea and Bohai Sea. In this paper, the intact core incubation was used to study the SOC in the Yellow Sea and Bohai Sea in April, July and October 2022, and the results showed that the rates of SOC ranged from 7.11 mmol/(m²·d) to 17.33 mmol/(m²·d). There was no significant difference between the SOC of the Yellow Sea and the Bohai Sea in spring (ANOVA, p > 0.05), and the SOC of the Yellow Sea was lower than Bohai Sea in summer (ANOVA, p < 0.01) and autumn (ANOVA, p < 0.01); the SOC of the Yellow Sea was the largest in spring and the smallest in summer, and there was no significant difference between the SOC of the Bohai Sea in summer and autumn, which were significantly higher than that of spring (ANOVA, p < 0.05). Temperature and sediment Chl a concentration were the influencing factors. Meanwhile, the SOC was used to assess the rate of benthic organic carbon mineralization. When compared with the primary productivity, the results indicated that the contribution of benthic organic carbon mineralization to primary productivity in the Bohai Sea ranged from 42.8% to 74.5%, which was one of the key links in the carbon cycle of the Bohai Sea, while the benthic organic carbon mineralization in Yellow Sea plays a less significant role in the carbon cycle of the Yellow Sea carbon cycle than Bohai Sea. This paper systematically studied the SOC in the Yellow Sea and Bohai Sea and its spatial and temporal distribution characteristics, exploring the contribution of organic carbon mineralization to primary productivity in the Yellow Sea and Bohai Sea, which provided theoretical support for the understanding of organic carbon mineralization and burial in the Yellow Sea and Bohai Sea.

Sea surface temperature (SST) is one of the most important physical variables of the ocean, which provides the basic information of the climate system. Accurately SST forecasting system has a comprehensive and essential application. In recent years, AI-based SST forecasting methods have become popular and shown great potential. Based on the convolutional long and short-term memory neural network (ConvLSTM), this paper studies the influence of multi-scale input fields on SST prediction in the northern South China Sea. Multi-dimensional ensemble empirical mode decomposition method (MEEMD) is used to decompose the average daily SST into the spatial eigenmodes of differentiated scales. Input different combinations of eigenmodes into ConvLSTM for training and prediction experiments. Results show that when using all four SST eigenmodes, the RMSE of the predicted SST in 1−7 days is 0.4−0.8℃, decrease 0.2−1.2℃ compared with the original SST alone; the MAPE is 1%−6%, decrease 0.5%−10%; the spatial correlation coefficient is 99.5%−96.5%, improve 0.5%−3.5%. Moreover, the randomized experiments also further proved the method has a high universality. The prediction model based on deep learning needs to select the appropriate training data in order to further improve its prediction accuracy. This paper preliminarily explores the integration of artificial intelligence methods and physical concepts in SST prediction, which can provide some reference for future research.

Utilizing the molecular biomarkers of organic matter in marine sediments from the Antarctic Peninsula (D1-7) and adjacent waters of the South Orkney Islands (D5-6), the ecological relationships implicit in the reconstructed variations of planktonic productivity and population structure are examined in relation to the Biological Pump (BP)/Microbial Carbon Pump (MCP), as well as the efficiency of marine carbon sinks and storage. Over the past century, a series of molecular biomarkers in sediment cores has exhibited significant changes, reflecting substantial spatiotemporal evolution in upper ocean planktonic productivity/community structure and sedimentary carbon reservoirs. These changes are indeed linked to global climate variability. The research findings are as follows: (1) Based on the characteristics of molecular composition and chromatographic peak patterns of biomarker compounds, as well as parameters such as Main Peak Carbon (MH), Light Hydrocarbons/Heavy Hydrocarbons (L/H), Bacterial-Algal Ratio (nC₁₅ + nC₁₇ + nC₁₉), Large Phytoplankton Ratio (nC₂₁ + nC₂₃ + nC₂₅), and carbon preference index (CPI), it is evident that the primary source of sedimentary carbon is marine-derived organic carbon. Marine organisms serve as natural carbon sinks for carbon fixation and storage. (2) The sediments from the D5-6 region exhibit high organic matter enrichment, primarily influenced by factors such as higher surface water productivity, higher sedimentation rates (average of 0.19 cm/a), shallower water depths (385 m), and a reducing sedimentary environment (average Pr/Ph value of 0.95). These conditions favor the transport of Particulate Organic Carbon (POC) from the ocean surface to the deep sea via the Biological Pump (BP) process, facilitating rapid burial and storage. In contrast, sediments from the D1-7 region, characterized by greater water depths (1 100 m) and lower sedimentation rates (0.07 cm/a, experience degradation of carbonaceous compounds during sedimentation processes and subsequent oxidative degradation in an oxic environment (average Pr/Ph value of 1.22). Both processes are unfavorable for carbon sequestration in sediments. However, the control factor determining carbon preservation in sediments may predominantly be sedimentation rate. (3) Over the past century, the total abundance of zooplankton, primary productivity of phytoplankton, and biomass of diatoms and dinoflagellates in the waters near the Antarctic Peninsula and the South Orkney Islands have shown an increasing trend, while the biomass and proportion of coccolithophores have decreased (particularly evident near the Antarctic Peninsula). This indicates a declining trend in the effectiveness of the calcium carbonate pump while the silica pump dominated by diatoms is strengthening. The relative strengths of these two processes largely determine the structure and efficiency of the biological pump, as well as the proportion of organic and inorganic carbon transported to marine sediments. (4) The trends in molecular biomarker variations in the two sediment cores show certain comparability overall, with distinct stages. Following interdecadal shifts (since 1972), the waters near the South Orkney Islands experienced a significant increase in zooplankton abundance from a depth of 5-6 cm beginning in 1982. Particularly, during the periods of 1997 and 2012, zooplankton abundance witnessed a dramatic increase, indicating rapid changes in planktonic community structure under the backdrop of global warming. Variations in both decreased primary productivity of phytoplankton and increased zooplankton abundance contribute to significant uncertainties in the changes in the strength of the biological pump (enhancement/weakening). (5) In contrast, over the past century, the productivity of phytoplankton/diatoms and dinoflagellates in the waters near the Antarctic Peninsula has gradually increased, while microbial productivity/ancient archaeal biomass has decreased. This suggests a weakening of microbial carbon sequestration intensity, indicating a decrease in the efficiency of the microbial carbon pump (MCP). This underscores the crucial role of global warming in the fluctuations of phytoplankton productivity/biomass in marine waters. The biomass and composition characteristics of planktonic communities directly affect the transport of organic carbon in the upper water column and the efficiency of carbon sequestration in the MCP. As the largest carbon sink in the global ocean, the carbon sequestration capacity of the Antarctic may be diminishing.

To clarify the composition and distribution characteristics of macrobenthic communities in Yantai Changdao Island marine ranch and evaluate the impact of marine ranching on these macrobenthos, sampling stations were set up inside and outside the marine ranch in October 2022. Surveys of macrobenthic animals and the characteristics of macrobenthic communities were analyzed. A total of 88 species of macrobenthic animals were collected and identified during this voyage. Although the number of species in the pasture and control area was similar, the dominant groups differed. In the pasture, 70 species were identified, with mollusks being the dominant group; whereas, in the control area, 69 species were identified, with annelids as the dominant group. Eight dominant species were found, including 3 mollusk species in the pasture and 6 species in the control area, comprising 2 mollusk species, 1 echinoderm species, and 3 annelid species. The average abundance and biomass of macrobenthic animals in the pasture were significantly higher than those in the control area. However, Margalef species richness index (d), Pielou evenness index (J'), and Shannon Wiener diversity index (H') values showed little difference between the pasture and the outside. The results of Cluster analysis (CLUSTER) and non-metric multidimensional scaling (NMDS) analysis indicated that relatively low similarity among each station inside and outside the marine ranch. The AMBI and m-AMBI analyses revealed that the overall pollution disturbance in the studied water area was relatively small, indicating good benthic ecological health. Combined with historical data, the analysis revealed a significant increase in species abundance and biomass of macrobenthic communities in the surveyed area. These results suggest that the development of marine pastures has a certain degree of impact on the growth and development of macrobenthic communities.

Mangroves are a crucial ecological barrier for coastal zones, and sensitive areas to climate change and human activities, where benthic fauna responds directly to the sedimentary environment because of their intimate contact and relatively fixed settlement habitats. In-situ observations and sample collections were carried out at 7 stations in the mangrove area off the Chaoshan coastal zone, in April 2021, for further analysis of the sedimentary environment, meiofaunal communities, and eco-environment quality evaluation. A total of 15 meiofauna groups were identified. Free-living marine nematodes were the most dominant group, accounting for 90.32% of the total abundance of meiofauna; while polychaetes were the first in biomass (58.44%). The average abundance of meiofauna was slightly higher than that of the other mangrove forests. The spatial pattern of the meiofaunal abundance exhibited a similar distribution trend to that of the abundance of nematodes and the content of chlorophyll a (Chl a), phaeophorbide, organic carbon, and heavy metals (Cd, Zn, Cu, Cr, and Hg): all the parameters showed the highest values in the northern of the Lianyang River, and decreased towards the south and north. Meiofaunal communities in different patches shared a high similarity of 70%, and the best explanation factor for the differences in the meiofauna community was the content of heavy metal Pb. The abundance ratio of marine nematodes to copepods (N/C), the possible ecological risk index, and the sediment quality grading all indicated a poor environmental state in the area investigated.

Oil and plastic pollutants are a serious threat to marine ecosystems and have even been found in the Ross Sea of the Southern Ocean. In order to obtain low-temperature alkane degrading bacteria and plastic-degrading bacteria in the region, a total of twelve sediment samples were collected in the Ross Sea area for enrichment and isolation of alkane-degrading bacteria at low-temperature, and the diversity analyses of the tetradecane-enriched communities showed that the most dominant genera were Pseudomonas, Alcanivorax, Marinomonas, Pseudoalteromonas. The polyethylene terephthalate(PET)and polyethylene(PE)was further validated using the dominant alkane-degrading bacteria. Scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (ATR-FTIR) demonstrated that the four pure cultures of Pseudomonas pelagia R1-05-CR3, Pseudomonas taeanensis A11-04-CA4, Halomonas titanicae A11-02-7C2 and Rhodococcus cerastii R1-05-7C3 could degrade PE effectively. The results of UPLC-MS and SEM confirmed the PET degradation by isolates of R. cerastii R1-05-7C3, Microbacterium maritypicum RA1-00-CA1, and H. titanicae A11-02-7C2. In conclusion, this study reports the diversity of the tetradecane-enriched consortia at low-temperature and plastic degrading bacteria in the offshore sediments of the Ross Sea in the Southern Ocean, which play a selfpurifying role in in-situ environmental contamination, and also provided strain resources for the biodegradation of hydrocarbon and plastic contaminants at low temperature.

Cage aquaculture is one of the most important types of marine aquaculture. Different types of cages have varying shapes in remote sensing images, and the background is complex. Previous methods for cage extraction have not been able to fully simulate human visual behavior and efficiently utilize spectral information. To address these issues, we propose a Spectral Loopy Attention U-Net (SLA-UNet) network model for cage aquaculture information extraction. The model utilizes the Random Forest (RF) algorithm based on the Estimation of Scale Parameter (ESP) to remove redundant spectral information after band operations. It also incorporates a human-like attention mechanism to enhance the important feature channels that affect cage information extraction. Additionally, edge completion is performed to supplement the loss information, achieving high-precision extraction of cage aquaculture information. We selected Zhanjiang City, Guangdong Province and Lingao County, as the study areas. Comparisons were made with the extraction results of the Canny algorithm, Otsu algorithm, PCA_Kmeans algorithm, RF algorithm based on ESP, and the U-Net model. The extraction accuracy of the SLA-UNet model for nearshore cages is 98.3%, and the average extraction accuracy for deep-sea cages is 98.9%, validating the effectiveness of the SLA-UNet model in cage aquaculture recognition.