A numerical wave flume with fully nonlinear free surface boundary conditions is adopted to investigate the temporal characteristics of extreme waves in the presence of wind at various speeds. Incident wave trains are numerically generated by a piston-type wave maker, and the wind-excited pressure is introduced into dynamic boundary conditions using a pressure distribution over steep crests, as defined by Jeffreys’ sheltering mechanism. A boundary value problem is solved by a higher-order boundary element method (HOBEM) and a mixed Eulerian-Lagrangian time marching scheme. The proposed model is validated through comparison with published experimental data from a focused wave group. The influence of wind on extreme wave properties, including maximum extreme wave crest, focal position shift, and spectrum evolution, is also studied. To consider the effects of the wind-driven currents on a wave evolution, the simulations assume a uniform current over varying water depth. The results show that wind causes weak increases in the extreme wave crest, and makes the nonlinear energy transfer non-reversible in the focusing and defocusing processes. The numerical results also provide a comparison to demonstrate the shifts at focal points, considering the combined effects of the winds and the wind-driven currents.

In ocean bathymetry, the instantaneous depth measured by survey ships or by unmanned surface vehicles (USVs) cannot be directly taken as the chart depth because of the effect of waves and the tide. A novel ocean bathymetry technology is proposed based on the USV, the aim is to evaluate the potential of the USV using a real-time kinematic (RTK) and a single beam echo sounder for ocean bathymetry. First, using the RTK height of the USV with centimeter-level precision, the height of the sea level is obtained by excluding wave information using a low pass filter. Second, the datum distance between the reference ellipsoid and the chart depth is obtained by a novel method using tide tables and the height of the sea level from the USV. Previous work has usually achieved this using long-term tidal observation from traditional investigations. Finally, the chart depth is calculated using the transformation between the instantaneous depth of the USV measurement and the datum of the chart depth. Experiments were performed around the Wuzhizhou Island in Hainan Province using the unmanned surface bathymetry vehicle to validate the proposed technology. The successful results indicate the potential of the bathymetry technology based on the USV.

The Fram Strait (FS) is the primary region of sea ice export from the Arctic Ocean and thus plays an important role in regulating the amount of sea ice and fresh water entering the North Atlantic seas. A 5 a (2011–2015) sea ice thickness record retrieved from CryoSat-2 observations is used to derive a sea ice volume flux via the FS. Over this period, a mean winter accumulative volume flux (WAVF) based on sea ice drift data derived from passive-microwave measurements, which are provided by the National Snow and Ice Data Center (NSIDC) and the Institut Francais de Recherche pour d’Exploitation de la Mer (IFREMER), amounts to 1 029 km³ (NSIDC) and 1 463 km³ (IFREMER), respectively. For this period, a mean monthly volume flux (area flux) difference between the estimates derived from the NSIDC and IFREMER drift data is –62 km³ per month (–18×10⁶ km² per month). Analysis reveals that this negative bias is mainly attributable to faster IFREMER drift speeds in comparison with slower NSIDC drift data. NSIDC-based sea ice volume flux estimates are compared with the results from the University of Bremen (UB), and the two products agree relatively well with a mean monthly bias of (5.7±45.9) km³ per month for the period from January 2011 to August 2013. IFREMER-based volume flux is also in good agreement with previous results of the 1990s. Compared with P1 (1990/1991–1993/1994) and P2 (2003/2004–2007/2008), the WAVF estimates indicate a decline of more than 600 km³ in P3 (2011/2012–2014/2015). Over the three periods, the variability and the decline in the sea ice volume flux are mainly attributable to sea ice motion changes, and second to sea ice thickness changes, and the least to sea ice concentration variations.

In some studies, the researchers pretreated and measured organic carbon, nitrogen and their isotopes (δ¹³C and δ¹⁵N) of marine sediment together, to save costs and resources of analysis. However, the procedure of acidification to remove inorganic carbon for analysing δ¹³C can affect the values of nitrogen and δ¹⁵N, and the biases vary a lot depending on the CaCO₃ contents of sediments. In this study, the biases of total nitrogen (TN) and δ¹⁵N values arising from acidified sediments were compared between the CaCO₃-poor (1%–16%) and CaCO₃-rich (20%–40%) samples. TN and δ¹⁵N values were altered during acid treatment (without centrifugation) that possibly led to N-containing compounds volatilization. For CaCO₃-poor samples, acidification led to a range of 0%–40% TN losses and 0‰–2‰ shift in δ¹⁵N values; and 10%–60% TN losses and 1‰–14‰ shift in δ¹⁵N values for CaCO₃-rich samples. The biases from most samples exceeded the precision of the instrument (0.002% for TN and 0.08‰ for δ¹⁵N), and high biases could mislead our judgment for the environmental implication of the data. Thus, avoiding co-analysis of organic carbon, nitrogen and their isotopes (δ¹³C and δ¹⁵N) in sediments, even for CaCO₃-poor marine sediments, is necessary.

Seasonal variations and distributions of dissolved carbohydrate concentrations at the İzmir Bay were investigated with salinity, chlorophyll a (Chl a), and dissolved organic carbon (DOC) levels to understand their relationships. Samples were collected from surface, subsurface and bottom depths at seven stations. DOC concentrations ranged from 32.2 to 244.2 μmol/L, and in general, DOC levels increased from winter to summer, then slightly decreased in autumn. Monosaccharide (MCHO), polysaccharide (PCHO) and total dissolved carbohydrate (TDCHO) levels were found between 0.7–8.3, 0.7–19.5, and 2.6–24.6 μmol/L. DOC, MCHO, PCHO and TDCHO levels were found higher in middle-inner bays, under the influence of anthropogenic inputs, compared to outer bay. Seasonal changes of MCHO/DOC, PCHO/DOC and TDCHO/DOC ratios were statistically significant (p<0.05) and the ratios showed decrease trends from winter to summer-autumn seasons. Distributions of TDCHO/DOC ratios at wide ranges (2.5%–42.3%) indicated the presence of newly forming and degrading fractions of DOM. According to results of factor analysis, Chl a, MCHO and TDCHO were explained in the same factor groups. In conclusion, the results showed that dissolved carbohydrate levels in the İzmir Bay might be influenced by biological processes and terrestrial/anthropogenic inputs.

In 2013, the 29th Chinese National Antarctic Research Expedition (CHINARE) prospected the Prydz Bay on the Antarctic continental shelf, and the Chinese R/V Xuelong icebreaker sampled all of the examined locations. The nature of Antarctic fish diversity in the high-latitude Prydz Bay is virtually unknown, and the accuracy of relevant estimates has not been established. Thus, it is necessary to evaluate this diversity and propose protective measures. In total, ninety-nine specimens were collected from various locations. To overcome uncertainties associated with identifying species based on morphology, DNA barcoding (COI gene) was employed to reconstruct phylogenetic relationships with delimited references from NCBI. Twenty-two species representing six families were unambiguously identified from a neighbor-joining (NJ) tree and barcoding gaps. With the morphological identification, thirteen species were identified correctly, five species were identified correctly at the genus level, and four species were identified at the close sister species level. Notothenioid dominance was not evident in the Prydz Bay, in contrast to other published studies. The low species diversity and catch biomass during this CHINARE were severely constrained by limited fishing methods and localized sites, which led to biased underestimation. Our analyses indicate that DNA barcoding is an effective tool for the identification of fish species in the Prydz Bay. The identification and distribution of Antarctic fish should be an integral component of understanding Antarctic fish biodiversity and biogeography, and large-scale studies are necessary for the further taxonomic identification of Antarctic fish.

Natural mortality rate (M) is one of the essential parameters in fishery stock assessment, however, the estimation of M is commonly rough and the changes of M due to natural and anthropogenic impacts have long been ignored. The simplification of M estimation and the influence of M variations on the assessment and management of fisheries stocks have been less well understood. This study evaluated the impacts of the changes in natural mortality of Spanish mackerel (Scomberomorus niphonius) on their management strategies with data-limited methods. We tested the performances of a variety of management procedures (MPs) with the variations of M in mackerel stock using diverse estimation methods. The results of management strategies evaluation showed that four management procedures DCAC, SPMSY, curE75 and minlenLopt1 were more robust to the changes of M than others; however, their performance were substantially influenced by the significant decrease of M from the 1970s to 2017. Relative population biomass (measure as the probability of B>0.5B_MSY) increased significantly with the decrease of M, whereas the possibility of overfishing showed remarkable variations across MPs. The decrease of M had minor effects on the long-term yield of curE75 and minlenLopt1, and reduced the fluctuation of yield (measure as the probability of AAVY<15%) for DCAC, SPMSY. In general, the different methods for M estimation showed minor effects on the performance of MPs, whereas the temporal changes of M showed substantial influences. Considering the fishery status of Spanish mackerel in China, we recommended that curE75 has the best trade-off between fishery resources exploitation and conservation, and we also proposed the potentials and issues in their implementations.

We developed an approach that integrates generalized additive model (GAM) and neural network model (NNM) for projecting the distribution of Argentine shortfin squid (Illex argentinus). The data for this paper was based on commercial fishery data and relevant remote sensing environmental data including sea surface temperature (SST), sea surface height (SSH) and chlorophyll a (Chl a) from January to June during 2003 to 2011. The GAM was used to identify the significant oceanographic variables and establish their relationships with the fishery catch per unit effort (CPUE). The NNM with the GAM identified significant variables as input vectors was used for predicting spatial distribution of CPUE. The GAM was found to explain 53.8% variances for CPUE. The spatial variables (longitude and latitude) and environmental variables (SST, SSH and Chl a) were significant. The CPUE had nonlinear relationship with SST and SSH but a linear relationship with Chl a. The NNM was found to be effective and robust in the projection with low mean square errors (MSE) and average relative variances (ARV). The integrated approach can predict the spatial distribution and explain the migration pattern of Illex argentinus in the Southwest Atlantic Ocean.

The genetic basis for bivalves’ adaptation and evolution is not well understood. Even few studies have focused on the mechanism of molluscan molecular evolution between the coastal intertidal zone and deep-sea environment. In our studies, we first conducted the transcritpome assembly of Modiolus modiolus mussels living in coastal intertidal zones. Also, we conducted transcriptome comparison analyses between M. modiolus and Bathymodiolus platifrons living in hydrothermal vents and cold methane/sulfide-hydrocarbon seeps. De novo assemblies of the clean reads yielded a total of 182 476 and 156 261 transcripts with N50 values of 1 769 and 1 545 in M. modiolus and B. platifrons. A total of 27 868 and 23 588 unigenes were identified, which also displayed the similar GO representation patterns. Among the 10 245 pairs of putative orthologs, we identified 26 protein-coding genes under strong positive selection (Ka/Ks>1) and 12 genes showing moderate positive selection (0.5<Ka/Ks<1). Most of those genes are predicted to be involved in stress resistance. Overall, our study first provides the transcriptomic database for M. modiolus. Transcriptome comparison illustrates the genome evolution between M. modiolus and B. platifrons, and provides an important foundation for future studies on these two species.