The modern fishery stock assessment could be conducted by various models, such as Stock Synthesis model with high data requirement and complicated model structure, and the basic surplus production model, which fails to incorporate individual growth, maturity, and fishery selectivity, etc. In this study, the Just Another Bayesian Biomass Assessment (JABBA) Select which is relatively balanced between complex and simple models, was used to conduct stock assessment for yellowfin tuna (Thunnus albacares) in the Atlantic Ocean. Its population dynamics was evaluated, considering the influence of selectivity patterns and different catch per unit effort (CPUE) indices on the stock assessment results. The model with three joint longline standardized CPUE indices and logistic selectivity pattern performed well, without significant retrospective pattern. The results indicated that the stock is not overfished and not subject to overfishing in 2018. Sensitivity analyses indicated that stock assessment results are robust to natural mortality but sensitive to steepness of the stock-recruitment relationship and fishing selectivity. High steepness was revealed to be more appropriate for this stock, while the fishing selectivity has greater influence to the assessment results than life history parameters. Overall, JABBA-Select is suitable for the stock assessment of Atlantic yellowfin tuna with different selectivity patterns, and the assumptions of natural mortality and selectivity pattern should be improved to reduce uncertainties.

Swordtip squid (Uroteuthis edulis) is one of the important economical fishing target species in the East China Sea. Uroteuthis edulis is characterized by rapid growth, extensive migration, and long spawning period and sensitive to surrounding environment. In order to assess its stock status, it is necessary to explore its spawning season, growth patterns of different populations and their relationship with the environment in advance. In this paper, based on the samples of U. edulis collected in the East China Sea from September 2017 to March 2018, we explored the relationships between daily growth of statolith microstructure and environmental variables by gradient forest method and generalized additive model. The spawning season of U. edulis was found to be nearly one year, and two dominant season groups were found: the spring group with the peak period of April and the summer group with the peak period of August. Water temperature in the depth of 25 m (Temp_25), sea surface temperature (SST) and zonal velocity were the key environmental variables for the daily growth of April-spawning group. The most suitable environmental conditions for the growth of April-spawning group were water temperature (24−27°C) and velocity (0.1−0.3 m/s). SST, Temp_25 and mixed layer depth were the key environment variables for the daily growth of August-spawning group. The most suitable environmental conditions for the growth of August-spawning group were water temperature (21−28°C) and water depth (0−50 m). Key environmental variables of different groups suggested that early growth was significantly affected by seasonal changes of water temperature, current velocity and prey abundance. This study explored the relationships between early growth and environmental variables and provided the scientific guidance for the management and conservation of U. edulis.

Dinitrogen (N₂) fixed by a group of prokaryotes (diazotrophs) is the dominant process adding bioavailable nitrogen into the ocean. Although it has been intensively studied how N₂ fixation is controlled by resources (bottom-up factors), it is unclear whether the grazing (top-down control) effectively impacts growth and distribution of different diazotroph groups. In this study, we evaluate this question by conducting log-log regression of diazotroph biomass onto corresponding N₂ fixation rates in the global ocean. The slope of the regression for Trichodesmium is ~0.8, indicating that a small portion of the increase in N₂ fixation does not accumulate as its biomass. This leads to a conclusion that Trichodesmium is under a substantial top-down control, although bottom-up control still dominates. We also analyze the residuals of the regression in the North Atlantic, concluding that free trichomes of Trichodesmium are subject to stronger top-down control than its colonies. The weak correlation between the biomass and N₂ fixation of unicellular cyanobacterial diazotrophs indicates that the degree of top-down control on this type of diazotrophs varies greatly. The analyses obtain unrealistic results for diatom-diazotroph assemblages due to complicated nitrogen sources of these symbioses. Our study reveals the variability of top-down control among different diazotroph groups across time and space, suggesting its importance in improving our understandings of ecology of diazotrophs and predictions of N₂ fixation in biogeochemical models. Measurements of size-specific N₂ fixation rates and growth rates of different diazotroph groups can be useful to more reliably analyze the top-down control on these key organisms in the global ocean.

Deep water in the South China Sea is renewed by the cold and dense Luzon Strait overflow. However, from where and how the deep water upwells is poorly understood yet. Based on the Hybrid Coordinate Ocean Model reanalysis data, vertical velocity is derived to answer these questions. Domain-integrated vertical velocity is of two maxima, one in the shallow water and the other at depth, and separated by a layer of minimum at the bottom of the thermocline. Further analysis shows that this two-segmented vertical transport is attributed to the vertical compensation of subsurface water to the excessive outflow of shallow water and upward push of the dense Luzon Strait overflow, respectively. In the abyssal basin, the vertical transport increases upward from zero at the depth of 3 500–4 000 m and reaches a maximum of 1.5×10⁶ m³/s at about 1 500 m. Deep water upwells mainly from the northeastern and southwestern ends of the abyssal basin and off the continental slopes. To explain the upward velocity arising from slope breaks, a possible mechanism is proposed that an onshore velocity component can be derived from the deep western boundary current above steep slopes under bottom friction.

This study aims to investigate variability of the deep South China Sea (SCS) circulation using the Hybrid Coordinate Ocean Model (HYCOM) global reanalysis product. The results reveal that annual cycle is a dominant component in the deep SCS circulation. Meanwhile, the boundary circulation strength is the weakest in January and peaks between June and September. The eastern and southern boundary currents strengthen/weaken one to three months earlier than that in the western and northern boundaries. Vector Empirical Orthogonal Functions (VEOF) analysis results reveal that semiannual and intraseasonal fluctuations are significant components, of which the spatial patterns are mainly confined in the northern and western boundary areas as well as the southwestern sub-basin. Wavelet analysis results show the strength of significant fluctuation varies year to year. Trend analysis results indicate a decadal weakening in the deep SCS circulation. An anomalous anticyclonic circulation, 50–70 km apart from the slope break, tends to weaken the cyclonic boundary circulation in the western and northern boundaries as well as the southwestern sub-basin. This trend is similar to the observed decadal weakening in the North Atlantic deep circulation. Thus, the findings of this study reveal that the variation of the deep SCS circulation has a remarkable response to the climate change. The mechanisms responsible for the variation are worth pursuing if more observations are available.

The mesopelagic communities are important for food web and carbon pump in ocean, but the large-scale studies of them are still limited until now because of the difficulties on sampling and analyzing of mesopelagic organisms. Mesopelagic organisms, especially micronekton, can form acoustic deep scattering layers (DSLs) and DSLs are widely observed. To explore the spatial patterns of DSLs and their possible influencing factors, the DSLs during daytime (10:00–14:00) were investigated in the subtropical northwestern Pacific Ocean (13°–23.5°N, 153°–163°E) using a shipboard acoustic Doppler current profiler at 38 kHz. The study area was divided into three parts using k-means cluster analysis: the northern part (NP, 22°–24°N), the central part (CP, 17°–22°N), and the southern part (SP, 12°–17°N). The characteristics of DSLs varied widely with latitudinal gradient. Deepest core DSLs (523.5 m±17.4 m), largest nautical area scattering coefficient (NASC) (130.8 m²/n mile²±41.0 m²/n mile²), and most concentrated DSLs (mesopelagic organisms gathering level, 6.7%±0.7%) were observed in NP. The proportion of migration was also stronger in NP (39.7%) than those in other parts (18.6% in CP and 21.5% in SP) for mesopelagic organisms. The latitudinal variation of DSLs was probably caused by changes in oxygen concentration and light intensity of mesopelagic zones. A positive relationship between NASC and primary productivity was identified. A four-months lag was seemed to exist. This study provides the first basin-scale baselines information of mesopelagic communities in the northwest Pacific with acoustic approach. Further researches are suggested to gain understandings of seasonal and annual variations of DSLs in the region.

Complex perturbations in the profile and the sparsity of samples often limit the validity of rapid environmental assessment (REA) in the South China Sea (SCS). In this paper, the remote sensing data were used to estimate sound speed profile (SSP) with the self-organizing map (SOM) method in the SCS. First, the consistency of the empirical orthogonal functions was examined by using k-means clustering. The clustering results indicated that SSPs in the SCS have a similar perturbation nature, which means the inverted grid could be expanded to the entire SCS to deal with the problem of sparsity of the samples without statistical improbability. Second, a machine learning method was proposed that took advantage of the topological structure of SOM to significantly improve their accuracy. Validation revealed promising results, with a mean reconstruction error of 1.26 m/s, which is 1.16 m/s smaller than the traditional single empirical orthogonal function regression (sEOF-r) method. By violating the constraints of linear inversion, the topological structure of the SOM method showed a smaller error and better robustness in the SSP estimation. The improvements to enhance the accuracy and robustness of REA in the SCS were offered. These results suggested a potential utilization of REA in the SCS based on satellite data and provided a new approach for SSP estimation derived from sea surface data.

Given the advances in satellite altimetry and multibeam bathymetry, benthic terrain classification based on digital bathymetric models (DBMs) has been widely used for the mapping of benthic topographies. For instance, cobalt-rich crusts (CRCs) are important mineral resources found on seamounts and guyots in the western Pacific Ocean. Thick, plate-like CRCs are known to form on the summit and slopes of seamounts at the 1 000–3 000 m depth, while the relationship between seamount topography and spatial distribution of CRCs remains unclear. The benthic terrain classification of seamounts can solve this problem, thereby, facilitating the rapid exploration of seamount CRCs. Our study used an EM122 multibeam echosounder to retrieve high-resolution bathymetry data in the CRCs contract license area of China, i.e., the Jiaxie Guyots in 2015 and 2016. Based on the DBM construted by bathymetirc data, broad- and fine-scale bathymetric position indices were utilized for quantitative classification of the terrain units of the Jiaxie Guyots on multiple scales. The classification revealed four first-order terrain units (e.g., flat, crest, slope, and depression) and eleven second-order terrain units (e.g., local crests, depressions on crests, gentle slopes, crests on slopes, and local depressions, etc.). Furthermore, the classification of the terrain and geological analysis indicated that the Weijia Guyot has a large flat summit, with local crests at the southern summit, whereas most of the guyot flanks were covered by gentle slopes. “Radial” mountain ridges have developed on the eastern side, while large-scale gravitational landslides have developed on the western and southern flanks. Additionally, landslide masses can be observed at the bottom of these slopes. The coverage of local crests on the seamount is ~1 000 km², and the local crests on the peak and flanks of the guyots may be the areas where thick and continuous plate-like CRCs are likely to occur.

Frontal upwelling is an important phenomenon in summer in the Yellow Sea (YS) and plays an essential role in the distribution of nutrients and biological species. In this paper, a three-dimensional hydrodynamic model is applied to investigate the characteristics and influencing factors of frontal upwelling in the YS. The results show that the strength and distribution of frontal upwelling are largely dependent on the topography and bottom temperature fronts. The frontal upwelling in the YS is stronger and narrower near the eastern coast than near the western coast due to the steeper shelf slope. Moreover, external forcings, such as the meridional wind speed and air temperature in summer and the air temperature in the preceding winter and spring, have certain influences on the strength of frontal upwelling. An increase in air temperature in the previous winter and spring weakens the frontal upwelling in summer; in contrast, an increase in air temperature in summer strengthens the frontal upwelling. When the southerly wind in summer increases, the upwelling intensifies in the western YS and weakens in the eastern YS. The air temperature influences the strength of upwelling by changing the baroclinicity in the frontal region. Furthermore, the meridional wind speed in summer affects frontal upwelling via Ekman pumping.

Oceanic noise is the background interference in sonar performance prediction and evaluation at high sea states. Statistics of underwater ambient noise during Typhoons Soulik and Nida were analyzed on the basis of experimental measurements conducted in a deep area of the Philippine Sea and the South China Sea. Generated linear regression, frequency correlation matrix (FCM), Burr distribution and Gumbel distribution were described for the analysis of correlation with environmental parameters including wind speed (WS), significant wave height (SWH), and the inter-frequency relationship and probability density function of noise levels (NLs). When the typhoons were quite close to the receivers, the increment of NLs exceeded 10 dB. Whilst ambient noise was completely dominated by wind agitation, NLs were proportional to the cubic and quintic functions of WS and SWH, respectively. The fitted results between NLs and oceanic parameters were different for “before typhoon” and “after typhoon”. The fitted slopes of linear regression showed a linear relationship with the logarithm of frequency. The average observed typhoon-generated NLs were 5 dB lower than the Wenz curve at the same wind force due to the insufficiently developed sea state or the delay between NLs and WS. The cross-correlation coefficient of FCM, which can be utilized in the identification of noise sources in different bands, exceeded 0.8 at frequencies higher than 250 Hz. Furthermore, standard deviation increased with frequency. The kurtosis was equal to 3 at >400 Hz approximately. The characteristics of NLs showed good agreement with the results of FCM.