The settling velocity is an important physical parameter of coral sand. Because of the rod coral sand is obviously different from other shapes of coral sand, it is not suitable to apply the settling velocity formula of the existing coral sand for calculation. The rod coral sand was selected to study the settling velocity and its influencing factors for single particle settlement experiment in stagnant water in this study. By analyzing the effects of different equivalent particle sizes and shape coefficients on the settling velocity of rod coral sand, it is found that the settling velocity of rod coral sand is strongly correlated with the diameter of the volume-equivalent sphere and Corey shape coefficient. Based on the experimental data, an empirical formula suitable for calculating the settling velocity of rod coral sand is deduced, which enriches the theory of coastal sediment.

Optically stimulated luminescence (OSL) dating as a absolute dating method for sediments has been widely used in Quaternary studies. Improving the accuracy and precision of OSL dating has been a hot spot in academic research. However, for a long time, there have been numerous studies on equivalent dose measurement procedures and calculation methods, and relatively few studies on environmental dose rates. In this paper, we conducted OSL chronology study on marine sediment samples obtained from the Borehole ZBW in the southwestern of Hainan Province. The contents of uranium, thorium and potassium in the samples were measured by inductively coupled plasma mass spectrometry/optical emission spectrometry (ICP-MS/OES), neutron activation analysis (NAA) and γ-ray spectrometer, respectively. The results show that there are differences in the results measured by the three methods in some strata, and the reasons could be: (1) incomplete dissolution of U in heavy minerals during the ICP-MS/OES pretreatment process; (2) the ICP-MS/OES measurement results are the elemental contents of U, Th, and K, which include some non-radionuclide contents; (3) the small sample size used for NAA, which was subject to chance errors, and the dilution effect of non-radioactive material in the sample affects the measurement results; (4) there is an imbalance of uranium system in the sample. Combined with the sedimentary environment in the study area and the data measured by HPGe γ-ray spectrometer, the results show that the uranium imbalance originates from the autogenous uranium absorption phenomenon, and the effect on the environmental dose rate is about 11%.

Ocean fronts variations in strength are key to the terrestrial material transport and global material cycle. Ocean temperature fronts are formed between the branches of West Pacific Boundary Current and the coastal current during the winter and spring seasons in the eastern shelf of China. In order to investigate the multi-time scale variation and main controlling factors of temperature front over the Yellow Sea under the dual influence of winter storms and shelf circulation, we investigate the coupling of low-latitude driven circulation systems and high-latitude driven winter storms on frontal variability with the methods of signal decomposition and explainable deep learning on the decadal and weather scale. On the decadal scale, empirical orthogonal decomposition and ensemble empirical modal decomposition are used to relate temperature changes in the Yellow Sea to the strength of the Yellow Sea Warm Current. The results indicate that the spatial distribution of first sea surface temperature (SST) EOF mode has obvious characteristics of the Yellow Sea Warm Current-coastal current system; the time series of the first SST EOF mode correlates well with the Yellow Sea Warm Current intensity index and is modulated by the low frequency ENSO signal. On the weather scale, this paper trains CNN-LSTM models and uses interpretability metrics to conduct the research. The results show that, in windless or weak wind conditions, the strength of ocean front is maintained by the combination of pressure gradient forces resulted from sea surface height and Coriolis forces caused by flow field. However, in the storm conditions, influenced by Kelvin Wave propagation and shear front fragmentation, the flow field is responsible for the ocean front variation. The results of this study show that big data and machine learning methods are important means to establish connections between many ocean parameters and discover some unique physical ocean processes, which have broad application prospects.

To explore the source of platinum group elements (PGE) in cobalt-rich crusts, the samples from Caiwei Seamounts in western Pacific were chosen as the research object, for which XRD, ICP-OES and ICP-MS were used to analyze the mineral composition, major elements contents and PGE contents in cobalt-rich crusts. The results showed that, the main crystalline minerals were vernadites in cobalt-rich crusts, and the minor minerals included quartz, plagioclase, potassium feldspar and carbon fluoride apatite. Also many amorphous ferric minerals were contained in cobalt-rich crusts. In addition, Mn and Fe contents were the highest in cobalt-rich crusts, and PGE were enriched in cobalt-rich crusts. PGE contents were 142−1352 ng/g, and Pt contents were 114−1268 ng/g, in which Pt accounted for more than 80%. PGE contents in the old layers were higher than that in the new layers. And the phosphatization appeared in the old crust layers. Moreover, there was an obvious contrast in PGE of cobalt-rich crusts, Pd group (PPGE) contents were more than Ir group (IPGE). PGE diagrams showed the positive Pt anomalies and negative Pd anomalies. And Pt was enriched and Pd was poor in cobalt-rich crusts. Meanwhile, PGE in cobalt-rich crusts were probably derived from the reaction between seamount basalt and seawater during the oceanic shell erosion process. PGE had positive correlation with CaO, P₂O₅, Ba and Cu, so PGE were probably enriched in the phosphate phase. In addition, the growth profile of cobalt-rich crust was from top to bottom and from new to old, PGE contents increased gradually. Therefore, oxidative marine environment and high marine productivity had a positive impact on phosphatization, which further promoted the enrichment of PGE. This study provided a certain reference value for revealing the source of PGE in cobalt-rich crusts.

Coral reef substrate classification plays a crucial role in marine resource development and marine ecological protection. At present, deep learning semantic segmentation methods are widely used in the field of remote sensing image classification, but less research has been conducted in substrate classification. Due to the high cost of pixel-by-pixel labeling in the fully supervised deep learning-based method, it is not suitable for large-scale and high-frequency substrate classification work. The semi-supervised deep learning-based method can effectively use the labeled labels to generate pseudo-labels for unlabeled data, thus effectively reducing the labor cost, however, the performance of the existing semi-supervised method is vulnerable to the interference of pseudo-label noise. To address the above problems, this paper proposes a semi-supervised substrate classification method based on soft and hard collaborative decision making. First, a high quality Pseudo tag is generated using joint decision making of multiple models; then, a loss function (Collaboration Choice of decision Confidence Loss function, 3CLoss) is proposed to take into account the confidence of Pseudo tag pixels and guide the model for training; finally, a soft and hard collaborative decision making approach is used to obtain accurate substrate classification results. The accuracy of this paper was evaluated on the shallow benthic habitat atlas datasets of Buck Island Reef in the northern part of St. Croix, U.S. Virgin Islands, and Pearl and Hermes Atolls, about 400 km southeast of Midway Island, Hawaiian Islands, and the experimental results show that the accuracy of the proposed method is comparable to that of the fully supervised learning method, and 3.08% higher than that of the mainstream semantic segmentation methods on average, which can effectively serve the coral reef substrate survey.

Acanthaster planci, one of the predators of reef-building corals, has attracted much attention for its catastrophic damage to coral reef ecosystems. However, the spatial and temporal distribution characteristics of A. planci are still unclear in the coral reef ecosystem of the South China Sea. In this study, using environmental DNA and real-time quantitative PCR techniques, we analyzed the concentration variation of the mitochondrial cytochrome-c-oxidase subunits I (COTS-mtCOI) fragment of A. planci in the surface seawater of the Xisha Islands in September 2020, April 2021 and January 2022, and the correlations between the concentration variation with environmental factors such as seawater temperature, salinity, pH, chlorophyll content, nutrients content and other environmental factors. The results showed that COTS-mtCOI fragment concentration in the Xisha Islands varied from 0 copies/m³ to 4.13×10⁷ copies/m³ during 2020−2022, and there were always higher concentrations in the Yongle Atoll. For Huaguang Reef, Jinqing Islands, Lingyang Reef, Quanfu Island and Zhaoshu Island, the average concentration of COTS-mtCOI fragment in September 2020 was significantly (p<0.05) higher than those in April 2021 and January 2022. In addition, COTS-mtCOI fragment concentration was significantly (p<0.05) positively correlated with surface seawater temperature. These results suggest that the population of A. planci is widely distributed in the seawater of Xisha Islands, and higher density of A. planci could appear in Yongle Atoll. Moreover, ocean warming may accelerate the outbreak of A. planci. This study is helpful to understand the population distribution characteristics of A. planci in the coral reef ecosystems of the South China Sea, and can provide a theoretical basis for the early warning and forecast of the A. planci outbreak.

Diurnal observation is necessary for grasping the variability of carbonate system in coastal waters and sea-air CO₂ exchange process and is helpful to reduce the uncertainty of assessments for carbon source/sink. Surface carbonate system and related parameters were obtained during twice 24 hours fixed sampling and observation conducted in April and August 2018 in the Yingluo Bay-Anpu Harbor, located in the northeastern Beibu Gulf. In this paper, we analyzed the hourly variations of partial pressure of CO₂ in surface sea water (pCO₂) and discussed the corresponding environment factors controlling pCO₂ in both seasons. The pCO₂ values ranged from 530−628 μatm in spring to 427−748 μatm in summer, with the average sea-air CO₂ flux in spring and summer for (1.7±0.8) mmol/(m²·d) and (1.2±0.8) mmol/(m²·d), respectively. The study area acted as a weak CO₂ source during both seasons. The hourly changes of pCO₂ in spring were more significantly affected by temperature effects than in summer. During summertime, pCO₂ had more sensibly response to tidal action, enhanced biological production and respiration with inflow of coastal freshwater such as rivers and submarine groundwater discharge. Water warming dominated the formation of high pCO₂ in spring. The enhanced biological production during the physical mixing of saline and fresh water played a role in the drawdown of surface dissolved inorganic carbon (DIC) and the mangroves and salt marshes ecosystems along the bay had a certain contribution to the addition of DIC on the freshwater end-member in summer. The variations of the ratio of DIC concentration and total alkalinity (TA) in the water masses could imply the overall distribution pattern adjacent to the Yingluo Bay-Anpu Harbor that high values exists in the bay and lower values exists in offshore water.

Satellite derived bathymetric using multispectral imagery is an effective means to obtain shallow water depth information. However, its validity is limited to optical shallow water areas, but presents a “pseudo-shallow sea” distortion phenomenon in deep water areas. Therefore, accurately identifying the valid region of satellite derived bathymetry (SDB) data is crucial for its wide application. Based on high-spatial resolution remote sensing image, a data-driven method for evaluating the validity of SDB based on analysis of the differences in the statistical distribution of radiance in deep/shallow water regions is proposed in this paper. This method uses the local standard deviation of the radiance information of satellite images as a feature, optimizes the statistical characteristics of the optical deep water area based on the K-S test method, and uses the hypothesis test method to identify the SDB corresponding to the deep water invalid area. The experimental results in Ganquan Island region show that the method can effectively identify the invalid SDB associated with the optical deep water area by dividing the boundary between optical shallow and deep water area. After removing the invalid data, the mean absolute error (MAE) of SDB in the optical shallow region is 1.01, and the root mean square error (RMSE) is 1.52. The experimental results show that the proposed method can accurately identify the optical shallow region of SDB result, which benefits the interpretation and application of SDB results.

Using the tropical cyclone (TC) best track data from the Shanghai Typhoon Research Institute of the China Meteorological Administration (CMA-STI) and the monthly mean reanalysis data of NCEP/NCAR, the interannual variability of the basin-scale large-scale environmental steering flow and the tropical cyclone activity in the western North Pacific (WNP) during peak season from July to September from 1979−2016 are investigated. The results show that: (1) There are two typical modes of summer large-scale environmental steering flow in the WNP at the inter-annual scale. The first typical mode is a dipole circulation with a meridional distribution, which is closely related to the eastern ENSO and the sea-air coupling mode in the WNP region. (2) The TC activity (generation location, tracks, intensity and duration) differs significantly between the two typical interannual mode anomaly years of the large-scale environment steering flow, but the differences have distinctly different characteristics for the two typical inter-annual modes. (3) The spatial distribution of TC generation location shows significant differences from north to south between the years of the first typical interannual mode anomalies of large-scale environment steering flow; the TC tracks, especially the northwestward and westward prevailing tracks, also have significant differences, and their average duration and intensity also show their corresponding significant differences. In the second major interannual mode anomaly years, the TC generation locations show significant east-west distribution especially in the southeast quadrant, and the differences in TC tracks are mainly in the northwestward and offshore steering prevailing tracks, and their mean durations and intensities also show significant differences.

Yellowfin tuna (Thunnus albacares) is one of the most important fishes with great global economic and ecological value, and its conservation and management have received much concerns. The stock status of yellowfin tuna in the Indian Ocean based on the age-structured assessment program model is evaluated in this study, focusing on the uncertainties of its life history characteristics on the stock assessment results. The results show that the resources of yellowfin tuna in the Indian Ocean remained relatively stable from 1960 to 1985 and then declined gradually, while the fishing mortality coefficient F increased rapidly after 2010. This stock in 2020 may be overfished, since the estimated F₂₀₂₀ was greater than F_MSY (F that could attain maximum sustainable yield MSY), while spawning stock biomass, SSB₂₀₂₀ was less than SSB_MSY. Sensitivity analysis was also conducted to evaluate the uncertainties of stock assessment. Two important life history characteristics, natural mortality M and steepness of spawning-stock relationship h, were analyzed for their influence on the estimates of F, SSB and biological reference points. When h was set to 0.7, 0.8, and 0.9, SSB_MSY and SSB₀ (the unfished SSB) reduced by about 255 300 t and 340 400 t; and F₂₀₂₀/F_MSY gradually decreased (from 2.88 to 2.21 and 1.73). When the M was set to M₁ (0.963, 0.663, 0.548, 0.493, 0.463, 0.446) and M₂ (1.068, 0.735, 0.608, 0.547, 0.514, 0.495) respectively, the larger M₂ leads to lower SSB and F₂₀₂₀/F_MSY. In summary, the conservation and management of Indian Ocean yellowfin tuna should be tightened in the future to achieve long-term sustainable development of this fishery. The life history characteristics of yellowfin tuna should be fully understood, especially M and h estimation should be improved, to provide more accurate information for stock assessment and fisheries management for Indian Ocean yellowfin tuna.