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.

The prokaryotic microbial communities in the sediments play crucial roles in the ecological functions of mangrove ecosystems. Therefore, the environmental factors that affect the structures of these prokaryotic microbial communities could indirectly participate in the regulation of mangrove functions, which is of great value for mangrove studies. The particle size (PS) of soils is recently demonstrated as a key environmental factor for shaping the microbial communities; however, this hypothesis has rarely been tested for mangrove environments. A case study of three tropical mangroves from Sanya, China was performed in this work to assess the influence of PS on the prokaryotic microbial community structures of bacteria, archaea, diazotrophs, and denitrifiers in the sediments. Results showed the variability in the spatial scale and the stability in the temporal scale for the prokaryotic communities, indicating that the tropical mangrove sediments could be a versatile but stable environment. Among the collected environmental factors, PS, salinity, and humidity had the greatest impacts, and PS mostly affected the structures of these prokaryotic communities based on its highest R² values of canonical correspondence analysis, Mental test, and linear fitting (p≤0.05). Furthermore, PS was positively correlated with the diversity and abundance of diazotrophic communities and negatively correlated with the abundances of methanogenic communities including Methanobacteriaceae, Methanospirillaceae, Methanoregulaceae, and Methanosaetaceae. Former studies show the increasing trend of PS caused by the rise of sea level and the intensification of human activities. Therefore, our findings indicate that PS could be a potential intermediate that links climate change and human activities with the possible ecological function migration of mangroves; meanwhile, the increase of PS could in turn release the stress of these environmental changes by increasing the abundance and diversity of the diazotrophic community and decreasing the abundances of methanogens.

A thorough understanding of the biogeochemical cycling of trace metals in the ocean is crucial because of the important role these elements play in regulating metabolism in marine biotas and thus, the climate. However, a precise and accurate analysis of trace metals in seawater is difficult because they are present at extremely low concentrations in a high salt matrix. In this study, we report an analytical method for the preconcentration and separation of six trace metals, Fe, Ni, Cu, Zn, Cd and Pb, in seawater using a seaFAST automatic solid-phase extraction device, analysis by a triple quadrupole collision/reaction technique with inductively coupled plasma mass spectrometry (ICP-MS), and quantification by the isotope dilution technique. A small volume (10 mL) of seawater sample was mixed with a multi-element isotope spike and subjected to seaFAST procedures. The preconcentrate solution was then analyzed using the optimized collision/reaction cell mode of ICP-MS, with NH₃ gas for Fe and Cd with a flow rate of 0.22 mL/min and He for Ni, Cu, Zn and Pb with a flow rate of 4.0 mL/min. The procedure blanks were 130 pmol/L, 3.0 pmol/L, 6.8 pmol/L, 37 pmol/L, 0.29 pmol/L and 0.42 pmol/L, for Fe, Ni, Cu, Zn, Cd and Pb, respectively. The method was validated using five reference materials (SLRs-6, SLEW-3, CASS-6, NASS-7 and GEOTRACE-GSC), and our results were consistent with the consensus values. The method was further validated by measuring full-water-column seawater samples from the subtropical Northwest Pacific Ocean, and our results demonstrated good oceanic consistency.

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.

Submesoscale processes in marginal seas usually have complex generating mechanisms, highly dependent on the local background flow and forcing. This numerical study investigates the spatial and seasonal differences of submesoscale activities in the upper ocean of the South China Sea (SCS) and the different dynamical regimes for sub-regions. The spatial and seasonal variations of vertical vorticity, horizontal convergence, lateral buoyancy gradient, and strain rate are analyzed to compare the submesoscale phenomenon within four sub-regions, the northern region near the Luzon Strait (R1), the middle ocean basin (R2), the western SCS (R3), and the southern SCS (R4). The results suggest that the SCS submesoscale processes are highly heterogeneous in space, with different seasonalities in each sub-region. The submesoscale activities in the northern sub-regions (R1, R2) are active in winter but weak in summer, while there appears an almost seasonal anti-phase in the western region (R3) compared to R1 and R2. Interestingly, no clear seasonality of submesoscale features is shown in the southern region (R4). Further analysis of Ertel potential vorticity reveals different generating mechanisms of submesoscale processes in different sub-regions. Correlation analyses also show the vertical extent of vertical velocity and the role of monsoon in generating submesoscale activities in the upper ocean of sub-regions. All these results suggest that the sub-regions have different regimes for submesoscale processes, e.g., Kuroshio intrusion (R1), monsoon modulation (R2), frontal effects (R3), topography wakes (R4).

Submesoscale activity in the upper ocean has received intense studies through simulations and observations in the last decade, but in the eddy-active South China Sea (SCS) the fine-scale dynamical processes of submesoscale behaviors and their potential impacts have not been well understood. This study focuses on the elongated filaments of an eddy field in the northern SCS and investigates submesoscale-enhanced vertical motions and the underlying mechanism using satellite-derived observations and a high-resolution (~500 m) simulation. The satellite images show that the elongated highly productive stripes with a typical lateral scale of ~25 km and associated filaments are frequently observed at the periphery of mesoscale eddies. The diagnostic results based on the 500 m-resolution realistic simulation indicate that these submesoscale filaments are characterized by cross-filament vertical secondary circulations with an increased vertical velocity reaching O(100 m/d) due to submesoscale instabilities. The vertical advections of secondary circulations drive a restratified vertical buoyancy flux along filament zones and induce a vertical heat flux up to 110 W/m². This result implies a significant submesoscale-enhanced vertical exchange between the ocean surface and interior in the filaments. Frontogenesis that acts to sharpen the lateral buoyancy gradients is detected to be conducive to driving submesoscale instabilities and enhancing secondary circulations through increasing the filament baroclinicity. The further analysis indicates that the filament frontogenesis detected in this study is not only derived from mesoscale straining of the eddy, but also effectively induced by the subsequent submesoscale straining due to ageostrophic convergence. In this context, these submesoscale filaments and associated frontogenetic processes can provide a potential interpretation for the vertical nutrient supply for phytoplankton growth in the high-productive stripes within the mesoscale eddy, as well as enhanced vertical heat transport.

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.

In this study, a moored array optimization tool (MAOT) was developed and applied to the South China Sea (SCS) with a focus on three-dimensional temperature and salinity observations. Application of the MAOT involves two steps: (1) deriving a set of optimal arrays that are independent of each other for different variables at different depths based on an empirical orthogonal function method, and (2) consolidating these arrays using a K-center clustering algorithm. Compared with the assumed initial array consisting of 17 mooring sites located on a 3°×3° horizontal grid, the consolidated array improved the observing ability for three-dimensional temperature and salinity in the SCS with optimization efficiencies of 19.03% and 21.38%, respectively. Experiments with an increased number of moored sites showed that the most cost-effective option is a total of 20 moorings, improving the observing ability with optimization efficiencies up to 26.54% for temperature and 27.25% for salinity. The design of an objective array relies on the ocean phenomenon of interest and its spatial and temporal scales. In this study, we focus on basin-scale variations in temperature and salinity in the SCS, and thus our consolidated array may not well resolve mesoscale processes. The MAOT can be extended to include other variables and multi-scale variability and can be applied to other regions.

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.