To determine if water-sediment regulation has affected macrobenthic community structure in the Huanghe River Estuary, China, macrobenthic samples were collected following regulation events from 2012 to 2016. We identify seven phyla and 138 macrobenthic species from within samples throughout the survey area, over time. Species richness and abundance in 2012 were significantly higher than in 2016. Biomass did not differ significantly during 2012–2016. Dominant species were mostly small polychaetes, with mollusks, arthropods, and echinoderms all being relatively rare. In 2016, dominant species were small polychaetes. MDS reveals macrobenthic communities at all surveyed distances from the estuary to have become the same community structure over time. Shannon-Wiener diversity and Margalef richness indexes trended down over time. CCA reveals the most dominant sediment-dwelling species to prefer lower dissolved oxygen, sulfides, and pH, and sediments with high D₅₀ and low clay content. We speculate that water-sediment regulation has affected seabed communities, particularly Region A in our survey area.

microRNAs (miRNA) families play a critical role in plant growth, development, and responses to abiotic stress. In this study, we characterized Up-miR-843 and its targets genes in Ulva prolifera responses to nitrogen depravation and heat stress. The data demonstrated that 184 target genes of Up-miR-843 could be successfully validated. N deficiency not heat stress stimulus induced increase in abundance of the Up-miR-843 while exhibited reverse expression of target genes, including cyclin A3 and cyclin L, which were strictly required for cell cycle progression. In addition, U. prolifera with highly expression of Up-miR-843 showed improved biomass, and photosynthesis compared with that under normal growth conditions. Thus, the N deprivation and heat responsive miRNAs might be a possible member mediating the expression of these target genes, which further regulated the growth of U. prolifera.

As one of the top four commercially important species in China, yellow croaker (Larimichthys polyactis) with two geographic subpopulations, has undergone profound changes during the last several decades. It is widely comprehended that understanding its population dynamics is critically important for sustainable management of this valuable fishery in China. The only two existing population dynamics models assessed the population of yellow croaker using short time-series data, without considering geographical variations. In this study, Bayesian models with and without hierarchical subpopulation structure were developed to explore the spatial heterogeneity of the population dynamics of yellow croaker from 1968 to 2015. Alternative hypotheses were constructed to test potential temporal patterns in yellow croaker’s population dynamics. Substantial variations in population dynamics characteristics among space and time were found through this study. The population growth rate was revealed to increase since the late 1980s, and the catchability increased more than twice from 1981 to 2015. The East China Sea’s subpopulation witnesses faster growth, but suffers from higher fishing pressure than that in the Bohai Sea and Yellow Sea. The global population and two subpopulations all have high risks of overfishing and being overfished according to the MSY-based reference points in recent years. More conservative management strategies with subpopulation considerations are imperative for the fishery management of yellow croaker in China. The methodology developed in this study could also be applied to the stock assessment and fishery management of other species, especially for those species with large spatial heterogeneity data.

Rapid changes on nutrient supply and CO₂ concentration that occurred in the northern South China Sea (SCS) during the Early Oligocene, provides an ideal natural laboratory, allowing us to peer into the coccolithophores’ physiology in the geological records. In this study, we established a new nannofossil assemblage index, termed as E* ratio, which is calculated by the relative abundance of eutrophic taxa and meso-oligotrophic taxa (${E^*}=\frac{e}{{e + c}}\times100$, where e is eutrophic taxa, and c is meso-oligotrophic taxa). Eutrophic taxa include small Reticulofenestra, Reticulofenestra lockeri group, Reticulofenestra bisecta group and Coccolithus pelagicus group, while meso-oligotrophic taxa include Cyclicargolithus spp. The E* ratio is well correlated with nutrient proxy during the Early Oligocene, while with different covarying patterns under the higher and lower CO₂ condition. By comparing the assemblage changes to the published data, we suggest that coccolithophores may change the way they use carbon source and nutrient with the decline of CO₂. Furthermore, this implies a possible initiation of the carbon concentrating mechanism.

Rapid and accurate identification of Vibrio species has been problematic because phenotypic characteristics are variable within species and biochemical identification requires two or more days to complete. Matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) has become a powerful tool for rapidly distinguishing between related bacterial species. However, its accuracy depends on the number of strains in a database. In the current study, we extend and apply the Vibrio database based on MALDI-TOF MS. A total of 74 strains of Vibrio representing 28 species were identified and included in new database. A phylogenetic tree based on rpoB sequence and dendrograms were constructed. We analyzed 30 clinical Vibrio of three species to evaluate the new database and carried out PCA dendrogram analyses for differences of strains. We created a new database that offered fast and accurate Vibrio identification. MSP and PCA dendrogram analyses provided technical support to track sources and incidences of Vibrio infection. In addition, the discovery of characteristic and differential peaks is useful for the future identification of Vibrio. This represents a powerful tool for the rapid and accurate classification and identification of Vibrio and closely related species.

A method of measuring the tritium in seawater based on electrolytic enrichment and ultra-low background liquid scintillation counting techniques was established. The different factors influencing the detection limit were studied, including the counting time, the electrolytic volume of the seawater samples, the selection of background water, scintillation solution and their ratio. After optimizing the parameters and electrolyzing 350 mL volume of samples, the detection limit of the method was as low as 0.10 Bq/L. In order to test the optimization of system for this method, of the 84 seawater samples collected from the Arctic Ocean we measured, 92% were above the detection limit (the activity of this samples ranged from 0.10 Bq/L to 1.44 Bq/L with an average of (0.30±0.24) Bq/L). In future research, if we need to accurately measure the tritium activity in samples, the volume of the electrolytic samples will be increased to further reduce the minimum detectable activity.

Ship-borne infrared radiometric measurements conducted during the Chinese National Arctic Research Expedition (CHINARE) in 2008, 2010, 2012, 2014, 2016 and 2017 were used for in situ validation studies of the Moderate Resolution Imaging Spectroradiometer (MODIS) sea ice surface temperature (IST) product. Observations of sea ice were made using a KT19.85 radiometer mounted on the Chinese icebreaker Xuelong between July and September over six years. The MODIS-derived ISTs from the satellites, Terra and Aqua, both show close correspondence with ISTs derived from radiometer spot measurements averaged over areas of 4 km×4 km, spanning the temperature range of 262–280 K with a ±1.7 K (Aqua) and ±1.6 K (Terra) variation. The consistency of the results over each year indicates that MODIS provides a suitable platform for remotely deriving surface temperature data when the sky is clear. Investigation into factors that cause the MODIS IST bias (defined as the difference between MODIS and KT19.85 ISTs) shows that large positive bias is caused by increased coverage of leads and melt ponds, while large negative bias mostly arises from undetected clouds. Thin vapor fog forming over Arctic sea ice may explain the cold bias when cloud cover is below 20%.

In order to apply satellite data to guiding navigation in the Arctic more effectively, the sea ice concentrations (SIC) derived from passive microwave (PM) products were compared with ship-based visual observations (OBS) collected during the Chinese National Arctic Research Expeditions (CHINARE). A total of 3 667 observations were collected in the Arctic summers of 2010, 2012, 2014, 2016, and 2018. PM SIC were derived from the NASA-Team (NT), Bootstrap (BT) and Climate Data Record (CDR) algorithms based on the SSMIS sensor, as well as the BT, enhanced NASA-Team (NT2) and ARTIST Sea Ice (ASI) algorithms based on AMSR-E/AMSR-2 sensors. The daily arithmetic average of PM SIC values and the daily weighted average of OBS SIC values were used for the comparisons. The correlation coefficients (CC), biases and root mean square deviations (RMSD) between PM SIC and OBS SIC were compared in terms of the overall trend, and under mild/normal/severe ice conditions. Using the OBS data, the influences of floe size and ice thickness on the SIC retrieval of different PM products were evaluated by calculating the daily weighted average of floe size code and ice thickness. Our results show that CC values range from 0.89 (AMSR-E/AMSR-2 NT2) to 0.95 (SSMIS NT), biases range from −3.96% (SSMIS NT) to 12.05% (AMSR-E/AMSR-2 NT2), and RMSD values range from 10.81% (SSMIS NT) to 20.15% (AMSR-E/AMSR-2 NT2). Floe size has a significant influence on the SIC retrievals of the PM products, and most of the PM products tend to underestimate SIC under smaller floe size conditions and overestimate SIC under larger floe size conditions. Ice thickness thicker than 30 cm does not have a significant influence on the SIC retrieval of PM products. Overall, the best (worst) agreement occurs between OBS SIC and SSMIS NT (AMSR-E/AMSR-2 NT2) SIC in the Arctic summer.

The stable isotopic composition (δ¹³C and δ¹⁵N) and carbon/nitrogen ratio (C/N) of particulate organic matter (POM) in the Chukchi and East Siberian shelves from July to September, 2016 were measured to evaluate the spatial variability and origin of POM. The δ¹³C_POC values were in the range of −29.5‰ to −17.5‰ with an average of −25.9‰±2.0‰, and the δ¹⁵N_PN values ranged from 3.9‰ to 13.1‰ with an average of 8.0‰±1.6‰. The C/N ratios in the East Siberian shelf were generally higher than those in the Chukchi shelf, while the δ¹³C and δ¹⁵N values were just the opposite. Abnormally low C/N ratios (<4), low δ¹³C_POC (almost −28‰) and high δ¹⁵N_PN (>10‰) values were observed in the Wrangel Island polynya, which was attributed to the early bloom of small phytoplankton. The contributions of terrestrial POM, bloom-produced POM and non-bloom marine POM were estimated using a three end-member mixing model. The spatial distribution of terrestrial POM showed a high fraction in the East Siberian shelf and decreased eastward, indicating the influence of Russian rivers. The distribution of non-bloom marine POM showed a high fraction in the Chukchi shelf with the highest fraction occurring in the Bering Strait and decreased westward, suggesting the stimulation of biological production by the Pacific inflow in the Chukchi shelf. The fractions of bloom-produced POM were highest in the winter polynya and gradually decreased toward the periphery. A negative relationship between the bloom-produced POM and the sea ice meltwater inventory was observed, indicating that the net sea ice loss promotes early bloom in the polynya. Given the high fraction of bloom-produced POM, the early bloom of phytoplankton in the polynyas may play an important role on marine production and POM export in the Arctic shelves.

Under-ice ambient noise in the Arctic Ocean is studied using the data recorded by autonomous hydrophones at the long-term ice station during the 9th Chinese National Arctic Research Expedition. Time-frequency analysis of two 7-s-long ice-induced noise samples shows that both ice collision and ice breaking noise have many outliers in the time-domain (impulsive characteristic) and abundant frequency components in the frequency-domain. Ice collision noise lasts for several seconds while the duration of ice breaking noise is much shorter (i.e., less than tens of milliseconds). Gaussian distribution and symmetric alpha stable (sαs) distribution are used in this paper to fit the impulsive under-ice noise. The sαs distribution can achieve better performance as it can track the heavy tails of impulsive noise while Gaussian distribution fails. This paper also analyzes the meteorological variables during the under-ice noise observation experiment and deduces that the impulsive ambient noise was caused by the combined force of high wind speed and increasing atmosphere temperature on the ice canopy. The Pearson correlation coefficients between long-term power spectral density variations of under-ice ambient noise and meteorological variables are also studied in this paper.