Using tide gauge observation, satellite altimeter data, and the result of 10 CMIP6 Earth System Models with good simulation performance, the long-term trend of sea level change in China, and predicts the range of sea level rise in the future are analyzed in this study. The results show that: (1) from 1960 to 2021, the sea level in China’s coastal areas showed an accelerated rising trend, with a rise rate of 2.5 mm/a and an acceleration of 0.06 mm/a². From 1993 to 2021, the rise rate was 4.0 mm/a, higher than the global rate of 3.3 mm/a in the same period. (2) From 1980 to 2021, the sea level rise rates of the Bohai Sea and the Yellow Sea, the East China Sea and the South China Sea were 3.5 mm/a, 3.3 mm/a and 3.6 mm/a, respectively. The sea level rise rates of the Bohai Sea and the Yellow Sea, the South China Sea were relatively fast, while the sea level rise rates of East China Sea was slow. The coastal sea level rose slowly from 1960s to 1970s, and accelerated after 1980s in the Bohai Sea and the Yellow Sea. (3) Under the medium (SSP2-4.5) and high (SSP5-8.5) scenarios, China’s offshore sea level will rise by 0.22 m (0.19−0.28 m) and 0.24 m (0.21−0.33 m) respectively in 2050, and will rise by 0.59 m (0.47−0.80 m) and 0.83 m (0.64−1.09 m) respectively in 2100. (4) During 2021−2040, the median value of sea level rise predicted by statistics is close to the predicted value under the low, medium and high scenarios of the numerical model. During 2041−2060, the predicted values of the low, medium and high scenarios of the numerical model are between the middle and high values of the statistical prediction. During 2081−2100, the high value of sea level rise predicted by statistics is close to that predicted by the medium scenario of the numerical model, the absolute deviation is 0.017 m, and the relative deviation is 3.4%. (5) Under the high scenario, the existing once-in-a-century extreme high sea level in 2100 will become less than 10 year return period, in which more than 50% of the stations will become less than 2 year return period, the defense capacity of coastal protection works and other infrastructure will be reduced, and the risk of flood and other disaster events in complex coastal cities will increase.

Early diagenesis in marginal sea sediments is an important process that affects carbon cycling and burial. Early diagenetic processes and influencing factors, however, remains poorly constrained. Dissolved inorganic carbon (DIC), dissolved inorganic nitrogen (DIN), Fe²⁺, Mn²⁺, sulfate and other parameters in sediment porewaters of five short cores collected in August 2018 from the Changjiang River Estuary and East China Sea inner-shelf were analyzed. In combination with grain size composition, specific surface area, organic carbon concentrations and stable carbon isotopic composition in surface sediments and bottom water parameters, the early diagenetic processes and influencing factors in sediments under different sedimentary regimes were studied. Concentrations of DIC and ${{\rm {NH}}_4^+} $ in sediment porewaters in the mud area gradually increase with depth, and relatively high production fluxes of DIC and ${{\rm {NH}}_4^+} $ (4.03 mmol/(m²·d) and 0.57 mmol/(m²·d), respectively) and consumption fluxes of ${{\rm {SO}}_4^{2-}} $ (−4.56 mmol/(m²·d)) are observed at the center of the mud area, while in the sandy area, there are no obvious variations of these solutes, and the fluxes are lower compared with those in muddy sediments. According to the vertical distributions of these solutes in the sediment porewaters, the sediment disturbance depth in the mud area varies at 20−40 cm, and gradually decreases from the Changjiang River Estuary mud area to the Zhe-Min coast mud area, whereas in the sandy area, no sediment disturbance is found. The thickness of sediment disturbed layer is positively correlated with solute fluxes (e.g., DIC and ${{\rm {NH}}_4^+} $) in sediment porewaters, indicating that the physical reworking of sediments is an important factor affecting the remineralization of sedimentary organic carbon in the mud area. In general, the main decomposition pathway of the sedimentary organic carbon in the disturbed layer of the mud area is iron/manganese reduction, and below the disturbed layer the main pathway is the sulfate reduction, while in the sandy area, the main degradation pathway is aerobic respiration. This study enriches the understanding of the impact of sedimentary dynamic processes on early diagenesis in the Changjiang River Estuary and adjacent sea areas, and contributes to better understand the cycling and burial of organic carbon in the large-river estuary and adjacent sea areas.

Coccolithophores can produce particulate organic carbon (POC) via photosynthesis and synthesize particulate inorganic carbon (PIC) via calcification; they also make an important contribution to marine carbon cycle. Some studies have reported that ocean acidification generally increases POC content and decreases PIC content of coccolithophores, however, most of the studies show these results under nutrient replete conditions, and a few studies focus on the combined effects of nutrient limitation and ocean acidification on coccolithophores. In this study, we investigated the physiological responses of the coccolithophore Emiliania huxleyi to ocean acidification under dissolved inorganic phosphorus (DIP) limitation. Our data show that ocean acidification and DIP limitation act synergistically to reduce growth rate, relative photosynthetic electron transport rate and light use efficiency of photosynthetic system II of E. huxleyi. Dissolved inorganic phosphorus limitation dominantly increases cellular POC content and offsets the negative effect of ocean acidification on cellular PIC content and the ratio of PIC : POC. Our results suggest that DIP limitation changed the response trends of POC and PIC contents to ocean acidification, which indicates that the contributions of coccolithophores to marine carbon cycle are different in these ocean areas with different DIP concentrations.

Multiple studies have confirmed the long-term property modification of water columns from the bottom to the sea surface at the Southern Ocean and pointed out that it is closely related to the changes of large-scale external forcing. However, the higher frequency interannual variability of the water masses and its causes are still poorly understood, including the winter water (WW), which is the most vulnerable to external forcing near the sea surface. Based on repeated hydrographic observations along 110°E in Januaries 2011 to 2020 and meteorological reanalysis datasets, this study estimated interannual variability of the WW layer in the seasonal ice zone (SIZ) and its possible causes over ten years. Results show that WW properties have significant temporal and spatial variability in this region. A significant positive correlation between the WW core temperature anomaly and the previous-year Antarctic Oscillation (AAO) index anomaly (R = 0.69) and a negative correlation between the AAO index and the turning latitude of the local zonal wind component (R = −0.61), indicate that a larger (smaller) AAO index corresponds to a southward (northward) shift of the divergence zone, and the increase (decrease) of the WW core temperature in the SIZ. A negative correspondence between the local net precipitation anomaly and the WW core salinity anomaly indicates the negative net precipitation anomaly (less freshwater transport to the ocean) after 2016 contributes to an increase in the WW core salinity anomaly. Meanwhile, the local eddy kinetic energy anomaly is negatively correlated with the WW thickness anomaly (R = −0.70), which supports the idea that the enhancement (decrease) in the intensity of persistent cyclonic eddies in this region may strengthen (weaken) the upward pumping to shoal the depth of the circumpolar deep water, and further affect the WW thickness. This study contributes to an in-depth understanding of the specific response of water columns in the Southern Ocean to the high-frequency variability of external forcing.

Traditional species distribution models rarely incorporate interspecific relationships into the modeling framework, which hinders their predictions of habitat distributions. In recent years, joint species distribution models (JSDMs) have drawn increasing attentions, but their practical applications remain rare in the marine realm. In this study, we used the HMSC (hierarchical modelling of species communities) method to study their relationships between 17 demersal fish species and environmental factors and the interspecific correlation. The model was built on the basis of bottom trawling data collected in the coastal waters of Shandong in summer, 2017, including the environmental data of water depth, bottom water temperature and bottom water salinity. Five variants of HMSC models were developed with respect to the linear or nonlinear relationships between species and the environmental variables and the exists of random effects, and WAIC and other indicators as well as cross-validation were used to evaluate the performances of fitting and prediction of these models. The results showed that the optimal model was the one incorporating nonlinear relationships and random effects (Model 5). The nonlinear models were generally superior to the linear models, and including the interspecific relationships in the model could improve model fitting performances. Temperature was the main factor influencing the distribution of demersal fishes in the coastal waters of Shandong, accounting for 51.4% of the mean explained variance, followed by water depth and random effects, which accounted for 35.7% and 12.8% explained variance, respectively. There were significant linear positive correlations between most demersal fishes and water depth, and significant nonlinear relationships with water temperature. There were significant interspecific correlations among the demersal fishes, which could be roughly divided into three groups according to the sign of the correlations, indicating that the interspecies relationships played an important role in shaping species distributions. This study suggested that the abiotic factors and biotic factors should be integrated in species distribution modeling, and our results might provide a guideline for the prediction of habitat distribution of fishery resources.

Colanic acid is one of the vital exopolysaccharides in biofilms, yet the effect of marine bacterial colanic acid on the settlement of invertebrates is still rarely covered. In this study, eight strains of marine bacteria isolated from natural biofilms were identified and the phylogenetic analysis was carried out, the colanic acid content and inducing ability of biofilms were also determined. Before that, the biofilm formation capacity and the extracellular products of the screened bacteria were detected. It was found that β-polysaccharide had a significant positive correlation with the settlement rate of Mytilus coruscus plantigrades (p < 0.05). The quantitative results of colanic acid content showed that among the five Gram-negative bacteria which could produce colanic acid, Shewanella marisflavi had the highest colanic acid yield of 1076.43 μg/mL, and three Gram-positive bacteria could not generate it. The results of plantigrade settlement induced by different biofilms showed that the inducing activity of marine bacterial biofilms on the settlement rate of M. coruscus was positively correlated with the content of colanic acid (p < 0.05). These findings prove that the Gram-negative bacteria with colanic acid can positively regulate the settlement of M. coruscus plantigrades, while the Gram-positive bacteria without colanic acid have no inducing activity. This study provides further insights to figure out the interaction between the chemical cues of biofilms and marine molluscs.

The virtual ocean platform constructed by digital twin technology can further realize the 3D visualization and analysis of seabed environmental monitoring data. Based on the long-term in-situ monitoring data of the deep seabed, this paper uses Unity3D technology to build a virtual marine environment with multi-model fusion, and initially establishes a digital twin system for marine engineering geological environment; combines MATLAB and ArcGIS data analysis technology to realize intelligent monitoring, data analysis, human-computer interaction and auxiliary decision-making; the study further constructs a virtual environment particle system to conduct a 3D visualization and analysis of the near-bottom suspended sediment concentration elevation event in the northern part of the South China Sea. The results show that there are large spatial and temporal differences in suspended matter concentration, particle number and aggregation degree in the virtual environmental particle system. In particular, when the suspended matter concentration is maintained at a high level, particles are found to collide and overlap with each other, and the denser microclusters are derived in space. When the suspended matter concentration rises further to the peak, the number of microclusters increases and occupies most of the volume of space, forming a highly aggregated suspended matter aggregate with a wider coverage of suspended particles. This paper is based on image analysis techniques and compares the visualization results with real seafloor cameras with relative errors in the range of 0.16%–2.80%, which is highly feasible.

To understand the characteristics of autophagy induced by virus infection in microalgae Emiliania huxleyi, we used diverse techniques including transmission electron microscopy, fluorescence microscopy, immunolabeling and biochemical methodologies to investigate the role of autophagy in the interaction between E. huxleyi BOF92 and its specific virus EhV99B1. The results showed that virus infection induced autophagy and vacuolar acidification in host cells, concomitant with up-regulation of autophagy-related genes such as atg1, atg5, atg8 and atg12 (p < 0.01) and Vps34 protein involved in the induction and nucleation of autophagosomes (p < 0.01). The expression level of autophagy marker protein p62 was significantly down-regulated (p < 0.05) during viral infection, indicating enhanced autophagic flux and activated autophagy. The expressions levels of negative regulatory factors such as phosphatidylinositol (PI3K), phosphorylated protein kinase B (p-Akt) and phosphorylated target of rapamycin protein (p-TOR) were significantly decreased in the late stage of viral infection (p < 0.01). Moreover, the level of reactive oxygen species (ROS) increased dramatically (p < 0.01), accompanied by a significant reduction in mitochondrial membrane potential (MMP) and ATP levels (p < 0.01) during viral infection. In conclusion, EhV99B1 infection induces ROS production and mitochondrial membrane damage in host cells, and initiates autophagy by regulating the PI3K/Akt/TOR signal pathway. Therefore, autophagy, as a unique form of programmed cell death, is of great significance to the individual survival and population dynamics of phytoplankton respond to environmental and biological stress.

As one of the vegetation types with the highest carbon storage in tropical regions, the area of mangrove forest shows a trend of fragmentation and reduction. The spatial distribution and dynamic information of mangrove biomass are crucial to the estimation of greenhouse gas flux and carbon storage, as well as policy formulation and implementation. However, both optical data and SAR data commonly used for biomass estimation have signal saturation phenomenon, and traditional estimation algorithms for mangrove biomass estimation have high data requirements and relatively low estimation accuracy. In order to solve this problem, this study compared the accuracy of four gradient enhanced decision tree algorithms for estimating aboveground biomass (AGB) of invasive mangrove species Sonneria apetala used UAV-LiDAR data, and discussed the importance of variables in the modeling process. The results indicate that: (1) XGBR had a high fitting ability for the estimation of mangrove AGB, reaching R² = 0.833 8, RMSE = 1.55 Mg/hm². (2) The predicted AGB in the study area ranged from 73.10 Mg/hm² to 190.00 Mg/hm², with an average of 109.10 Mg/hm². (3) LiDAR index describing canopy height characteristics is an important variable for estimating mangrove AGB. Conclusion: This study proved the feasibility of UAV-LiDAR data and XGBR model for estimating the AGB of mangrove forests, in order to provide data support for the blue carbon research of mangrove ecosystems.

Two single-scene SAR images observed by Radarsat-2 and Sentinel-1A were decomposed to obtain a pair of SAR sub-aperture images at different azimuth-angles, respectively. Doppler centroid anomaly method was used to invert the sea surface current of two sub-aperture images with different azimuth angles. The current field was obtained by vector synthesis. The inversion results were verified by the HYCOM model data with spatio-temporal matching. The results show that the root mean square (RMS) of the current velocity between the synthesized result by two sub-aperture images of Radarsat-2 and the HYCOM model data is 0.09 m/s, and the correlation coefficient is 0.64. The RMS of current direction is 10.49° and the correlation coefficient is 0.78 of this group data. As for the results of the Sentinel-1A image, the RMS of the current velocity is 0.06 m/s, and the correlation coefficient is 0.82. The RMS of the current direction is 2.85°, and the correlation coefficient is 0.86. It can be seen that the two-dimensional ocean currents field can be effectively inverted based on the two sub-aperture SAR images that decomposed from single-scene SAR image. The inversion accuracy is related to the relative direction of the radar’s looking direction and the real current vector. The inversion accuracy of the sea surface current field can be higher when the relative angle is small.