Chinese black sleeper (Bostrychus sinensis) is a fish that lives both in seawater and freshwater, feeds on crustaceans, aquatic insects and occasionally shellfish. The existence of digestive enzyme in viscera to act on chitinous exoskeleton of the prey is of interest. In this study, a chitinase was purified to homogeneity using ammonium sulfate precipitation, DEAE-Sephacel ion exchange, Sephacryl S-200 HR and Superdex 200 gel filtration columns. The purified protein presents a molecular mass of 58 kDa as determined by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and results in a single band on native PAGE. According to peptide mass fingerprinting, two peptides containing a total of 20 amino acid residues, were 95% identical to a chitinase from yellow perch (Perca flavescens) and 100% identical to the chitinase from greater amberjack (Seriola dumerili). The purified chitinase showed optimum activity at pH 6.0, and was stable at acidic conditions and temperature below 55°C. The enzymatic activity was quite stable in the presence of NaCl, even at 1 mol/L . The chitinase was capable of degrading chitosan into low molecular mass chitooligosaccharides (COS) with sizes in a range of 200–700 Da, and the circular dichroism profile of the COS greatly differed from native chitosan. Full-length cDNA encoding the present chitinase was cloned and the transcript levels of chitinase in various tissues were determined by quantitative real-time PCR. The results showed that the transcript level of chitinase was highest in esophagus and hepatopancreas.

This study attempted to compare the performance of local polynomial interpolation, inverse distance weighted interpolation, and ordinary kriging in studying distribution patterns of swimming crabs. Cross-validation was used to select the optimum method to get distribution results, and kriging was used for making spatial variability analysis. Data were collected from 87 sampling stations in November of 2015 (autumn) and February (winter), May (spring) and August (summer) of 2016. Results indicate that swimming crabs widely distributed in autumn and summer: in the summer, they were more spatially independent, and resources in each sampling station varied a lot; in the winter and spring, the abundance of crabs was much lower, but the individual crab size was bigger, and they showed the patchy and more concentrative distribution pattern, which means they were more spatially dependent. Distribution patterns were in accordance with ecological migration features of swimming crabs, which were affected by the changing marine environment. This study could infer that it is applicable to study crab fishery or even other crustacean species using geostatistical analysis. It not only helps practitioners have a better understanding of how swimming crabs migrate from season to season, but also assists researchers in carrying out a more comprehensive assessment of the fishery. Therefore, it may facilitate advancing the implementation in the pilot quota management program of swimming crabs in northern Zhejiang fishing grounds.

To characterize environmental factors controlling decadal-scale variations in the buried flux of marine organic carbon (${\rm{BF}}_{\rm{C_m}} $) in the eastern shelf sea areas of China (ECSS), four well preserved sediment cores collected from the central Yellow Sea mud (CYSM) area, the Yellow Sea Coastal Current (YSCC) area and the Changjiang River Estuary (CRE) were investigated in this study. In the CYSM, variations in ${\rm{BF}}_{\rm{C_m}} $ were found to be dependent on variations in primary productivity and to exhibit a cyclical trend possibly related to fluctuations in the Pacific Decadal Oscillation (PDO) and the East Asian winter monsoon index (EAWM). In the YSCC, ${\rm{BF}}_{\rm{C_m}} $ likewise depends on primary productivity. Prior to the 1950s, variations in ${\rm{BF}}_{\rm{C_m}} $ were similar to that of the EAWM. After the 1950s, ${\rm{BF}}_{\rm{C_m}} $ increased rapidly and exhibited maximum values in the surface layer, consistent with an increase in primary productivity caused by the input of terrestrial nutrients associated with China’s economic development. In the CRE, variations in ${\rm{BF}}_{\rm{C_m}} $ were affected by several competing factors making it difficult to identify clear relationships between variations in ${\rm{BF}}_{\rm{C_m}} $ and primary productivity. In contrast, long-term variability in ${\rm{BF}}_{\rm{C_m}} $ is more similar to changes in the Changjiang River sediment load. Thus, it is speculated that the construction of dams along the Changjiang River may be the main cause of variations in ${\rm{BF}}_{\rm{C_m}} $ in this area. Given the disproportionate effects of human activities on marine environments and decadal variations in ${\rm{BF}}_{\rm{C_m}} $ in the ECSS, careful attention should be paid to regional differences in organic carbon preservation and environmental changes lest estimates of these values be made imprecise or inaccurate.

Sediment core samples were collected from 17 stations in the middle and eastern Chukchi Sea during the sixth Chinese National Arctic Research Expedition (CHINARE-Arctic) in summer 2014. The samples were analyzed for composition, abundance, biomass, vertical distribution, size spectra, and ecological indexes of meiofauna. A total of 14 meiofauna taxa were detected, and the free-living marine nematodes comprised the most dominant taxon, accounting for 97.21% of the average abundance. The abundance and biomass of meiofauna were within ranges of (218.12±85.83)–(7 239.38±1 557.15) ind./(10 cm²) and (130.28±52.17)–(3 309.56±1 751.80) μg/(10 cm²), with average values of (2 391.90±1 966.19) ind./(10 cm²) and (1 549.73±2 042.85) μg/(10 cm²) (according to dry weight) respectively. Furthermore, 91.26% of the individuals were distributed in the top layer of 0–5 cm of surface sediment, and 90.84% had sizes of 32–250 μm. Group diversity index of meiofauna in the survey area was low, and the variation of abundance was the main difference in meiofauna communities among all stations. Abundance and biomass of meiofauna were not significantly correlated with environmental factors except concentration of nutrient Si in bottom seawater. Abundance of meiofauna in shallow water of marginal seas in the Pacific sector of the Arctic Ocean is likely at a same level and higher than that in most of China sea areas, suggesting that the shallow water of the summer Chukchi Sea is a continental shelf area with rich resources of meiofauna. The Chukchi Sea is important for studying the ecosystem of the Arctic Ocean and environmental responses. However, studies on meiofauna in the Chukchi Sea are still not enough, and in the future, natural and human disturbances may increase due to global warming, the Arctic channel opening, and other factors. Thus, more studies on meiofauna should be required, in order to know more about how the Arctic benthic community would alter.

Living coccolithophores (LCs) are regarded as a group of calcifiers and play important roles in global carbon cycle. This study used microscopic observations of LCs in the western Pacific Ocean to investigate their community structure and biodiversity, especially to test whether local physical traits (mesoscale eddies) could explain their biogeographic distributions during autumn of 2017. The coccolithophore calcite inventory based on carbon-volume transformation was estimated in this study. A total of 28 taxa of coccospheres and 19 types of coccoliths were identified from 161 samples. Gephyrocapsa oceanica was the most predominant species in all the coccolithophore community, followed by Florisphaera profunda, Emiliania huxleyi, Umbilicosphaera sibogae, Gladiolithus flabellatus and Umbellosphaera tenuis. The abundance of coccospheres and coccoliths ranged from 0 to 26.8×10³ cells/L and from 0 to 138.5×10³ coccoliths/L, averaged at 4.2×10³ cells/L and 10.9×10³ coccoliths/L, respectively. This study indicated that coccolithophore community in the survey area can be clustered into four groups. Three ecological niches of coccolithophores were characterized by their vertical profiles and multivariate statistical analysis. Coccolithophore abundance and species composition were remarkably different among warm-eddy region, G. oceanica dominated warm-eddy region, while F. profunda dominated warm-eddy and none-eddy region. The average values of estimated particulate inorganic carbon, particulate organic carbon were 0.197 μg/L and 0.140 μg/L, respectively. The current field study widened the dataset of coccolithophores in western Pacific Ocean.

An ensemble optimal interpolation (EnOI) data assimilation method is applied in the BCC_CSM1.1 to investigate the impact of ocean data assimilations on seasonal forecasts in an idealized twin experiment framework. Pseudo-observations of sea surface temperature (SST), sea surface height (SSH), sea surface salinity (SSS), temperature and salinity (T/S) profiles were first generated in a free model run. Then, a series of sensitivity tests initialized with predefined bias were conducted for a one-year period; this involved a free run (CTR) and seven assimilation runs. These tests allowed us to check the analysis field accuracy against the “truth”. As expected, data assimilation improved all investigated quantities; the joint assimilation of all variables gave more improved results than assimilating them separately. One-year predictions initialized from the seven runs and CTR were then conducted and compared. The forecasts initialized from joint assimilation of surface data produced comparable SST root mean square errors to that from assimilation of T/S profiles, but the assimilation of T/S profiles is crucial to reduce subsurface deficiencies. The ocean surface currents in the tropics were better predicted when initial conditions produced by assimilating T/S profiles, while surface data assimilation became more important at higher latitudes, particularly near the western boundary currents. The predictions of ocean heat content and mixed layer depth are significantly improved initialized from the joint assimilation of all the variables. Finally, a central Pacific El Niño was well predicted from the joint assimilation of surface data, indicating the importance of joint assimilation of SST, SSH, and SSS for ENSO predictions.

The methane bubble plume attracts interest because it offers direct evidence of seafloor gas leakage and plays an indirect role in the exploration and identification of natural gas hydrate. In this study, based on established plume models and their migration sections, three amplitude-class attributes were extracted from three formations for the migration sections of five plumes, and the correlation between the gas content and seismic attribute was obtained. As the gas content increases, the amplitude attribute correspondingly increases, and the linear correlation is relatively good. Moreover, correlation coefficients between gas content and amplitude attributes are close to 1.0. By using linear fitting, the relation model between the gas content of the plume and the seismic attribute was obtained. The relation model was subsequently used to invert the gas content from a real data-bearing plume. Comparison of the gas content section of the plume with the attribute section and real seismic section reveals common distribution characteristics, namely, the color of the section in the lower right corner is dark. If the amplitude value is large in the seismic section of the real plume, the amplitude attribute value is also large in the corresponding attribute section, and the inverted value of the gas content is also large (because gas content and amplitude are linearly correlated), which indicates that the plume bubbles of the section in the lower right corner is intensively distributed. Finally, the obtained gas content section of the plume can reflect the distribution of the plume bubble content more simply and intuitively, from which the distribution law of seafloor bubbles can be deduced, and this lays a foundation for the further estimation of the gas content of the plume and hydrate reserves.

The newly discovered East Longjing-2 hydrothermal field (ELHF-2) is located on the Dragon Horn oceanic core complex of the ultraslow-spreading Southwest Indian Ridge, approximately 12 km from the ridge axis. This study measured the chemical compositions of pyrite from ELHF-2 using a laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) to investigate the genesis of the field. Three generations of pyrite were classified, and found that: Py1 and Py2, rich in V, Mn, U, and Se, occur in altered basalt debris and the silica alteration matrix, respectively. Py3 was mainly intergrown with chalcopyrite in quartz veins and had higher Cu, In, Ag, Sb, and Au contents than Py1 and Py2. Some elements, such as Au, Se, and Pb, are likely presented as direct substitution with Fe²⁺ in pyrite, while Cu, Zn, Co, Ni, and Ag probably occur both as direct substitution with Fe and as distributed micro- to nanoparticle-sized sulfides. Meanwhile, the occurrence of V, Mn, and U is likely presented as oxide inclusions. Trace element geochemistry suggested that the pyrite was formed under high-temperature conditions, and the ore forming elements were likely derived from ultramafic rocks. In addition, Py1 and Py2 were formed under higher water/rock ratio and higher temperature conditions, with more seawater involvement compared with Py3. The formation of ELHF-2 was probably driven by exothermic serpentinization reactions with an additional magmatic heat. This study shows that high-temperature hydrothermal circulation driven by magmatic activity can be developed on distal rift flank areas of magma-starved ultraslow-spreading ridges.

An internal gravity wave model was employed to simulate the generation of internal solitary waves (ISWs) over a sill by tidal flows. A westward shoaling pycnocline parameterization scheme derived from a three-parameter model was adopted, and then 14 numerical experiments were designed to investigate the influence of the pycnocline thickness, density difference across the pycnocline, westward shoaling isopycnal slope angle and pycnocline depth on the ISWs. When the pycnocline thickness on both sides of the sill increases, the total barotropic kinetic energy, total baroclinic energy and ratio of baroclinic kinetic energy (KE) to available potential energy (APE) decrease, whilst the depth of isopycnal undergoing maximum displacement and ratio of baroclinic energy to barotropic energy increase. When the density difference on both sides of the sill decreases synchronously, the total barotropic kinetic energy, ratio of baroclinic energy to barotropic energy and total baroclinic energy decrease, whilst the depth of isopycnal undergoing maximum displacement increases. When the westward shoaling isopycnal slope angle increases, the total baroclinic energy increases whilst the depth of turning point almost remains unchanged. When the depth of westward shoaling pycnocline on both sides of the sill reduces, the ratio of baroclinic energy to barotropic energy and total baroclinic energy decrease, whilst the total barotropic kinetic energy and ratio of KE to APE increase. When one of the above four different influencing factors was increased by 10% while the other factors keep unchanged, the amplitude of the leading soliton in ISW Packet A was decreased by 2.80%, 7.47%, 3.21% and 6.42% respectively. The density difference across the pycnocline and the pycnocline depth are the two most important factors in affecting the characteristics and energetics of ISWs.

Long term in situ atmospheric observation of the landfast ice nearby Zhongshan Station in the Prydz Bay was performed from April to November 2016. The in situ observation, including the conventional meteorological elements and turbulent flux, enabled this study to evaluate the sea ice surface energy budget process. Using in situ observations, three different reanalysis datasets from the European Centre for Medium-Range Weather Forecasts Interim Re-analysis (ERA-Interim), National Centers for Environmental Prediction Reanalysis2 (NCEP R2), and Japanese 55-year Reanalysis (JRA55), and the Los Alamos sea ice model, CICE, output for surface fluxes were evaluated. The observed sensible heat flux (SH) and net longwave radiation showed seasonal variation with increasing temperature. Air temperature rose from the middle of October as the solar elevation angle increased. The ice surface lost more energy by outgoing longwave radiation as temperature increased, while the shortwave radiation showed obvious increases from the middle of October. The oceanic heat flux demonstrated seasonal variation and decreased with time, where the average values were 21 W/m² and 11 W/m², before and after August, respectively. The comparisons with in situ observations show that, SH and LE (latent heat flux) of JRA55 dataset had the smallest bias and mean absolute error (MAE), and those of NCEP R2 data show the largest differences. The ERA-Interim dataset had the highest spatial resolution, but performance was modest with bias and MAE between JRA55 and NCEP R2 compare with in situ observation. The CICE results (SH and LE) were consistent with the observed data but did not demonstrate the amplitude of inner seasonal variation. The comparison revealed better shortwave and longwave radiation stimulation based on the ERA-Interim forcing in CICE than the radiation of ERA-Interim. The average sea ice temperature decreased in June and July and increased after September, which was similar to the temperature measured by buoys, with a bias and MAE of 0.9°C and 1.0°C, respectively.