Feature article

This study was conducted to explore the contribution of silicon dissolution from beach sediments to the dissolved silicon budget in the coastal waters. From March to September in 2017, six field surveying cruises were conducted in the Muping offshore area (Yantai, China), the southern North Yellow Sea. By investigating monthly distributions and the averaged values of dissolved inorganic nutrients, monthly accumulation of dissolved silicate anomaly (ΔSi, as defined with the difference between dissolved inorganic nitrogen and silicate concentrations)of 1.5 μmol·L^-1 was observed in this offshore area with weak circulation from May to August. Further combining laboratory incubation experiments, theoretical calculation and field data analyses, It was found that the permeable particles in beaches could be dissolved, leaching active silicate to seawater, and increasing the offshore silicate concentration by 0.7~2.0 μmol·L^-1 every month, roughly consistent with the monthly accumulation rate of field ΔSi. Extrapolating the beach silicate-leaching flux to the length of the coastline rounding the Yellow Sea, the previously reported imbalance in silicate budget in this coastal sea could roughly be bridged. This study indicated again that the dissolving of permeable particles might contribute significantly to coastal silicate budget.

Tidal flats are influenced by tides, experiencing periodic inundation and exposure, thus the inundation frequency reflects the elevation of tidal flats. This study utilizes time-series SAR satellite remote sensing data to conduct research on the remote sensing inversion method of tidal flat topography based on tidal level complementary cumulative distribution function. The key lies in proposing a new method for inundation frequency correction based on the weighting scale of remote sensing observation counts. And, based on the mathematical definition of inundation frequency, the functional relationship between inundation frequency and tidal flat elevation was explored, leading to the construction of a tidal flat topography inversion model based on the tidal level complementary cumulative distribution function. Then, the validation of the method was conducted in the Yueqing Bay. Based on the time-series Sentinel-1 satellite SAR remote sensing data, the tidal flat topographies for the periods 2019-2020 and 2021-2022 were successfully inverted. The accuracy assessment was conducted based on the corresponding period’s ICESat-2 satellite laser altimetry data. The root mean square errors (RMSE)of the tidal flat topographies for the periods 2019-2020 and 2021-2022 were 0.41 m and 0.51 m, respectively. Additionally, the RMSE of topography for the period of 2019-2020 using in-situ data was 0.48 m. The accuracy assessment suggest that the proposed method in this study can achieve high-precision tidal flat topography without field-measured topographic data. It is expected to be applicable to the monitoring of tidal flat topography in more regions.

Island ecosystems are characterized by resource specificity and ecosystem vulnerability, thus, the scientific assessment of the impact of land use change on the carbon sequestration and other ecosystem service functions of island ecosystems is of great significance to the sustainability management of islands. The Dongtou Islands in Zhejiang Province represents a typical island ecosystem that has undergone developmental utilization such as land reclamation and conservation-restoration initiatives like the Blue Bay Project. It serves as an ideal case study for establishing assessment methods of how land use changes affecting the carbon sequestration service function of island coastal ecosystems and others, and for exploring the effectiveness of management measures. In this study, a land classification model based on XGBoost algorithm was used to obtain land use classification data of the Dongtou Islands in 12 phases (3 years as a phase)from 1988 to 2023 (with accuracy of 91.52%). On this basis, the changes in carbon sequestration amounts of major ecosystems, including woodland, salt marshes, and tidal flats, in the Dongtou Islands were calculated. A coupling coordination degree model of “economic development-land use-carbon sequestration function” was constructed by combining the socio-economic statistical data, and the degree of coupling coordination between the economy and ecosystem of the Dongtou Islands for more than 30 years was explored. The study found that from 1988 to 2023, the total land area of the Dongtou Islands increased by 34.97% due to natural silt deposition and sea reclamation efforts. The cumulative total of ecosystem carbon sequestration amount and net carbon sequestration amount for the main ecosystems amounted to 49.45×10⁴ t and 46.13×10⁴ t, respectively, basically showing an oscillating upward trend. Carbon sequestration mainly resulted from woodland and coastal wetlands (including tidal flats and salt marshes), with cumulative carbon sequestration amount of 25.44×10⁴ t and 24.01×10⁴ t, respectively. The “economic development-land use-carbon sequestration function” coupling coordination degrees of the Dongtou Islands were in a coordinated state from 2006 to 2023. Overall, the coupling coordination degree is greatly affected by the land use changes. Ecological restoration projects can enhance the comprehensive evaluation index of the land use and carbon sequestration function system, and then improve the coupling coordination degree. This study can provide a scientific theories and data foundation for the socio-economic development and ecological environmental protection planning of the Dongtou Islands.

The anaerobic oxidation of methane (AOM) is a pivotal component of elemental cycling within cold seep sediments. This process is usually performed by anaerobic methanotrophic archaea (ANME) and sulfate-reducing bacteria (SRB), which usually exist as symbionts. However, pure cultures of ANME have not yet been obtained, and their slow metabolism hinders further exploration and research into their metabolic characteristics and collaborative mechanisms. In this study, we utilized hybridization chain reaction-fluorescence in situ hybridization (HCR-FISH) technology and high-throughput 16S rRNA gene sequencing to investigate the composition and state of ANME communities at different depths of the sediments in the black microbial mat area of the South China Sea Formosa cold seep. The results showed that ANME-1 and ANME-2 were the dominant groups in the sampled Formosa cold seep sediments. Specifically, ANME-2 was found to form consortia with SRB, while no such associations were detected for ANME-1. This observation suggested that ANME-2 and SRB primarily engage in symbiotic AOM processes, highlighting potential differences in physiological roles and methane metabolism pathways between ANME-1 and ANME-2. Furthermore, in sediment samples of all layers, the diameters of ANME-2/SRB consortia were predominantly concentrated between 3-10 μm. Correlation analysis indicated a significant link between the distribution of consortium diameters and environmental factors such as sulfate concentration in the sediment, underscoring the impact of environmental factors on the growth of ANME/SRB consortia. Additionally, using HCR-FISH, we further discovered the presence of multiple consortium clusters in the Formosa cold seep sediment, characterized by orderly connected and uniform-sized consortium, implying possible connections or cooperative relationships among consortia. This study revealed the presence and distribution patterns of ANME groups and sizes of symbiotic microbial consortia in sediment samples from different depths of the Formosa cold seep, laying the foundation for further understanding methane metabolism mechanisms and ecological functions of different ANME groups in situ cold seep sediments.

Coastal estuaries are influenced by terrestrial inputs and usually act as sources of atmospheric carbon dioxide (CO₂), whereas mangrove ecosystems generally serve as sinks of atmospheric CO₂. Therefore, accurately measuring the CO₂ emissions at mangrove estuaries is of great significance for constructing regional and global carbon budgets. Dongzhai Harbor locates in the northeastern of Hainan Island, and connects to the Qiongzhou Strait outward, surrounding by 5 major small rivers. Mangroves are mainly distributed in the west and south of Dongzhai Harbor. This study conducted four field surveys in Dongzhaigang, the surrounding major rivers and the adjacent sea areas in December 2022 (dry season), December 2023 (dry season), May 2022 (wet season) and August 2023 (wet season) respectively. The results show that the surface water partial pressure of CO₂ (pCO₂) presents a decreasing trend from rivers to inner and outer harbor. Temperature, river-sea mixing, and biological respiration jointly affect the spatial distributions of pCO₂ in the dry and wet seasons. The CO₂ flux in wet season (8.8±8.2 mmol·m^-2·d^-1) is greater than that in dry season (3.4±3.6 mmol·m^-2·d^-1), and the annual CO₂ flux (6.1±6.3 mmol·m^-2·d^-1) is lower than that in other tropical mangrove estuaries around the world. This study estimates that the estuarine CO₂ emission could offset about 10.4%~21.9% of the carbon sequestration by plants in Dongzhai Harbor.

Using eddy-resolving numerical simulation data and historical hydrological observation data, this study investigates the sources, seasonal and interannual variability of two subsurface undercurrents under the Indonesian Throughflow—the Ombai Undercurrent located in the Ombai Strait and the Timor Undercurrent located in the Timor Channel. The results indicate that these two undercurrents exist at depths of approximately 200-800 m, which are a quasi-permanent undercurrent system. The formation of the Ombai Undercurrent is mainly related to the eastward extension of the South Java Undercurrent, while the water source of the Timor Undercurrent is more complex, mostly a mixture of the South Java Undercurrent and the Leeuwin Undercurrent. Both subsurface undercurrents exhibit significant seasonal and interannual variations, with a significant semiannual period at the seasonal scale, typically peaking during the Indian Ocean monsoon transition period (April, May, and October). Combining historical wind, satellite altimeters, and temperature and salinity observation data, it is found that the meridional pressure gradient in the subsurface layer related to local wind and their upwelling is the dominant factor leading to their seasonal changes. At the interannual scale, there is a period of 2-4 years for subsurface undercurrents, which is significantly correlated with the Indian Ocean dipole.

Submarine earthquake is one of the most major factors causing deep-water international submarine cables damage. Understanding the process of submarine cables damage and the mechanism of submarine cables damage caused by turbidity currents after earthquake are of great significance to the security maintenance of international submarine communications. Combined with the lastest research result of global seabed topography and using professional international submarine cables engineering software Makaiplan, the process of plenty of submarine cables damage after Grand Banks Earthquake and Hengchun Earthquake were studied, then the relationship between the pattern of submarine cable damage and the developing process of turbidity currents after earthquake was found, and the mechanism of submarine cables damage caused by turbidity currents after earthquake was summarized. Study result shows that submarine cables break points are located intentively in submarine canyons and trenches. The movement speed of turbidity currents in submarine canyon and submarine trench, which caused submarine cable damage, can reach several ten kilometers to several hundred kilometres per hour. Terrestrial rivers and continental shelf undersea river channels provide materials transportation for the development of turbidity currents. Submarine canyons and trenchs are the pathes of turbidity currents movement then damage plenty of submarine cables. The turbidity currents that developed from upper continental slope in passive continental margin after earthquake can damage submarine cables laid on continental slope, continental rise and abyssal plain. This kind of turbidity currents achieves maximum speed on continental slope, then self-accelerate on abyssal plain. Multiple turbidity currents can develop at different positions of continental slope at the same time in active continental margin, then strike submarine cables which laid on canyons and trenches for multiple times. This kind of turbidity currents achieves maximum speed and self-accelerates in submarine trenches. There are several earthquake-resistance measures: submarine cable routes trying to avoid crossing submarine canyons and trenches which connected to terrestrial rivers or continental shelf channels; using shallow water type submarine cable which has outer armor protection when crossing inevitably; laying submarine cables suspended slightly on the bottom of canyons or trenches with Uraduct protection on them; changing the cross-section shape of submarine cable.

Artificial intelligence in oceanography has demonstrated a great potential with the explosive growth of ocean observation data and numerical model products. This article first reviews the history of ocean big data development, and then introduces in detail the current status of artificial intelligence in oceanography applications including identifying ocean phenomenon, forecasting ocean variables and phenomenon, estimating dynamic parameters, correcting forecast errors, and solving dynamic equations. Specifically, this article elaborates the research on the intelligent identification of ocean eddies, internal waves and sea ice, the intelligent prediction of sea surface temperatures, El Ni?o-Southern Oscillation, storm surges, waves and currents, the intelligent estimation of ocean turbulence parameterization for numerical models, and the intelligent correction of waves and current forecast errors. In addition, it discusses the recent progress of applying physical mechanism fusion and Fourier neural operator for solving ocean dynamic equations. This article is based on the current status of artificial intelligence in oceanography and aims to provide a comprehensive demonstration of the advantages and potential of applying artificial intelligence methods in the field of oceanography. With the two emerging research hotspots: digital twin oceans and artificial intelligence large models, the future development direction of artificial intelligence provides enlightenment and reference for interested scientists and researchers.

Waves are one of the most important phenomena in the ocean. The accurate and quick updated wave forecasting is of crucial significance for ensuring marine activities safety. The development of wave forecast is presented, including the traditional statistical wave forecasting methods, numerical wave prediction models, and the rapidly developing artificial intelligence (AI) wave forecasting methods. Currently, AI wave forecast models have been demonstrated unique advantages in terms of computational efficiency and adaptive forecasting accuracy, and they are gradually being applied in practical wave forecasting operations, transitioning from the research stage. However, they also have limitations, including limited forecasting elements, underestimation of extreme wave conditions, and weak forecasting generalization ability. Based on the characteristics of AI wave prediction, key scientific and technological issues that need to be addressed in current AI wave forecasting are proposed. These include efficient utilization of observational data, incorporation of prior physical knowledge, and enhancement of AI model safety and generalization ability.

Histopathological indexes can be used to assess health of organism, but their application faces challenges such as low efficiency, high cost and strong subjectivity. Introducing artificial intelligence (AI) technology into histopathological analysis of biological tissues can leverage its high-throughput image analysis capabilities, overcoming the limitations in assessing and monitoring marine organism health. Based on our review on health assessment indicators of marine organisms, the application of AI in image analysis, and the use of AI for histopathological image processing, a deep learning-based histopathological image analysis approach was proposed using gill tissues of marine mussels as representative. Through a series of processes such as training, validation, and prediction of histopathology images, it was determined that the Res-UNet deep learning model can efficiently and accurately quantify histopathological damage in mussels’ gills. An automated, high-throughput, and less subjective workflow based on deep learning was finally established, offering new ideas and techniques for marine organism health assessment and marine monitoring.

Based on multi-platform observed data, an unexpected response of a warm mesoscale eddy to bypassed typhoon Megi in the South China Sea in 2010 was observed and investigated. During the passage of typhoon Megi, the SLA maximum of the warm eddy increased from 30 to 36 cm, the radius increased from 78 to 116 km, the eddy kinetic energy increased from 166 to 303 m²/s², and the amplitude increased from 3 to 9 cm. On the right side of the typhoon, the thermocline water at Argo station on the edge of the warm eddy sank by 20 to 40 m. Diagnosis of the wind stress curl alone indicates that the warm eddy should be weaken and the thermocline should be raised, which are inconsistent with the observation results. Diagnosis based on the reanalysis sea surface velocity indicates that during the passage of typhoon Megi, the water diverges below the typhoon path, while the water converges on the right side of the path in the warm eddy region, and the SLA maximum as well as the amplitude of warm eddy are positively correlated with the convergence intensity. Estimation based on the reanalysis sea surface velocity also indicates that the water at Argo station will sink 29 m. Both the warm eddy characteristics and the thermocline depression are consistent with the observation. The case study shows that the response of mesoscale eddy on the edge of typhoon influence to typhoon is constrained not only by wind stress curl but also by the oceanic background conditions, and further attentions are required to explore the corresponding response and mechanism of upper ocean to typhoon.

Combined with the Holland wind fields and the ERA5 wind fields, the mixed wind fields was set up by introducing a weight coefficient varying with the radius of wind speed, and a typhoon wave model in Zhejiang sea area was established using MIKE21 SW. Then, the Holland, the ERA5 and the mixed wind fields were used as the input wind fields to simulate the wind speed and the significant wave height during No.1918 typhoon Mitag, respectively. The verification shows that the simulated results obtained using the Holland wind fields and the ERA5 wind fields cannot agree accurately with the observed data, while the mixed wind fields proposed in this study can improve the simulation accuracy. In order to study whether the above conclusion is universal in Zhejiang sea area, five typical typhoons that have the most serious impact on Zhejiang sea area in the recent 5 years were selected for typhoon wave numerical simulations and the error statistical analysis. The results indicate the wind speed around the typhoon center is relatively good using the Holland wind fields and the average relative errors of the maximum wind speed are 8.62%-10.19%, but the average relative errors of the wind speed below 10 m/s is relatively bigger, reaching 29.76%-44.29%. However, the wind speed around the typhoon center using the ERA5 wind fields is smaller than the observed data, and the average relative errors of the maximum wind speed are 17.64%-25.77%, but the average relative errors of wind speed below 10 m/s are smaller than that using the Holland wind fields, which are 19.64%-32.00%. During the five typhoon processes, the average values of the average relative errors of the significant wave height driven by Holland, the ERA5 and the mixed wind fields are 29.92%, 25.62% and 22.82%, respectively. Correspondingly, the average root mean square errors are 0.46 m, 0.42 m and 0.39 m and the consistency indexes are 0.94, 0.95 and 0.96. The above results shows that the mixed wind fields proposed in this study is universal in Zhejiang sea area and can improve the simulation accuracy of typhoon waves.

Based on Global Navigation Satellite System (GNSS) dynamic precision point positioning technology (PPP), the influence factors of precipitable water vapor (PWV) detection over the ocean were studied. The sampling interval, satellite masking angle, PPP solution method (fixed solution or floating point solution), and the influence of Beidou satellite system combination on ocean PWV retrieval were mainly analyzed. In the marine observation environment, the results show that the accuracy of PWV inversion is the highest when the sampling interval is 30 s. When the number of available satellites is small, the accuracy of PWV inversion is better when the satellite masking angle is set to 5°-10°, and the accuracy decreases gradually with the increase of the satellite masking angle. Whether the PPP solution is fixed or not, it has little effect on the accuracy of PWV inversion. On the basis of GPS/GLONASS system combination, adding Beidou observation value will improve the redundancy of observation and improve the accuracy of PWV inversion.

A new method for determining the foot point of the continental slope (FOS) was proposed for the delineation of the continental shelf in a complex geological context. This method calculated the location of the foot of slope based on the mean gradient of water depth and optimized it by combining the contrary evidence and the principles of convexity, segmentation and continuity. Using the southern continental margin of Mozambique as the study area, the method was applied to extract the most critical basis—FOS for continental shelf delineation using high-precision multibeam topographic data measured in 2021, and the result was confirmed by comparison with those extracted by the Geocap software which is used by the United Nations Commission on the Limits of the Continental shelf, proving the effectiveness and accuracy of this method.

Erythrobacteraceae is widely distributed in marine environments and can synthesize various pigments such as carotenoids. Carotenoids have photoprotective and antioxidant abilities, and they can play a crucial role in the adaptation of Erythrobacteraceae to marine ecosystems. In this study, we obtained the genomes of 107 marine Erythrobacteriaceae strains, analyzed the distribution characteristics of carotenoid biosynthesis genes including crtEBIGYZW in their genomes, constructed phylogenetic trees based on the amino acid sequences of the carotenoid biosynthesis genes, and elucidated the presence and distribution of carotenoid biosynthesis genes in Erythrobacteriaceae from deep-sea and shallow-sea sources. The results suggested that all of marine Erythrobacteriaceae strains contained the crtEIGZ genes, 98.1% of strains contained the crtBY genes, and 43.9% of them contained the crtW gene, which differed among strains but no any specificities found among the deep-sea or shallow-sea sources. Additionally, in the comparison of the phylogenetic topology, it was found that the crtBYZW genes were vertically transferred from their ancestor, while the crtEIG genes were mainly horizontal gene transferred. Our study aids in the understanding of the carotenoid biosynthesis gene evolution in the family Erythrobacteriaceae and also serves as a scientific basis for the study of carotenoid synthesis pathways and genes in other marine bacteria, enables a thorough understanding of marine carotenoid-synthesizing strains.

The waters surrounding South Georgia Island are one of the highest primary productivity regions in the Southern Ocean with enormous carbon sequestration potential. However, the strength of the biological pump efficiency in this area is still uncertain due to the lack of continuous upper ocean observation data.In this study, the hydrological and biogeochemical parameters obtained from the Biogeochemical Argo (BGC-Argo) floats deployed in the South Georgia Island vicinity during the period of 2017-2020 were utilized to investigate the impacts of physical processes on biogeochemical processes and to estimate the carbon export flux in the Antarctic summer. Results indicated that both upstream (northeast of the Antarctic Peninsula) and downstream (Georgia Basin) regions of South Georgia Island exhibited strong seasonal characteristics in Chl-a, with the latter area having a 4-month sustained period of phytoplankton bloom, suggesting a stable and continuous supply of iron. Using the temporal variability of the seasonal particulate organic carbon (POC) export, the summer POC export fluxes of the upstream and downstream regions were estimated to be 7.12±3.90 mmol·m^-2·d^-1 and 45.29±5.40 mmol·m^-2·d^-1, respectively, indicating that the difference might be due to enhanced downward export of organic carbon after the deepening of the mixed layer. The study found that the region maintained a high biological pump efficiency, contrary to the previous conclusion that the Georgia Basin had “high productivity low export efficiency”, which might have been caused by the limited “real-time” representation of the entire seasonal characteristics during ship-based surveys. BGC-Argo provides high spatiotemporal resolution of multi-parameter observation data, and this study demonstrates that it can more accurately quantify and evaluate marine biogeochemical processes and carbon sequestration potential.

Near-inertial waves (NIWs) play an important role in the response of ocean to typhoon. Their frequency varies with the depth and is the main factor in determining the propagation rate of near-inertial energy to the ocean interior. Based on the observation data from mooring, the factors affecting the blue-shift frequency of NIWs excited by typhoon were investigated in northwestern South China Sea. By analyzing the vorticity effect and Doppler effect caused by background currents, this study suggests that the Doppler effect of background currents was the main factor in the blue-shift frequency of NIWs. As depth increased, inertial wave frequencies increased. Quantitative calculations further demonstrated that within the upper 200 meters, the Doppler effect of the background currents was negative, approaching zero in depth around 200 meters. However, in the depth range of 230 to 400 meters, the Doppler effect became positive. This depth range exhibited the maximum strength of the background currents, with their direction aligned with the propagation direction of inertial waves. Consequently, the positive Doppler shift induced by the background currents was most pronounced. The results of this study are important for improving the understanding of the ocean response to typhoons, especially the propagation of near-inertial waves in areas with complex background current structure (e.g., the western boundary current region).