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Abstract Sea surface salinity (SSS) is a master variable in oceanography and important to understand marine biogeochemical and physical processes. In the East China Sea (ECS), a random forest based regression ensemble model (RF) was developed to estimate the SSS with a spatial resolution of ∼1 km based on a large synchronous data set of in situ SSS observations, MODIS‐derived remote sensing reflectance (Rrs) and sea surface temperature (SST). The model showed the best performance when the Rrs(412), Rrs(488), Rrs(555), Rrs(667), SST and Julian day (JD) were used as inputs, with a root mean square error (RMSE) of 0.84, mean absolute error (MAE) of 0.31 and coefficient of determination (R2) of 0.81 for model training (N = 4,504), and a RMSE of 0.77, MAE of 0.30 and R2 of 0.86 for the model test (N = 1,153). The accuracy of the SSS model was examined using an independent data set during the period of 2020–2022 with a RMSE of 0.66 and MAE of 0.39 (N = 2,151). The interannual and seasonal signal of modeled SSS of the ECS, showed that important drivers of variability are the Changjiang discharge and the East‐Asian monsoon. Applications of the model to other Chinese marginal seas (Yellow and Bohai seas) showed good agreement in distribution patterns when compared with the estimated SSS from NASA Soil Moisture Active Passive. Once more empirical oceanographic data is made available, this robust model can be applied to other regions retraining the model with informed local data sets.

Abstract Background Heme proteins, such as hemoglobin, horseradish peroxidase and cytochrome P450 (CYP) enzyme, are highly versatile and have widespread applications in the fields of food, healthcare, medical and biological analysis. As a cofactor, heme availability plays a pivotal role in proper folding and function of heme proteins. However, the functional production of heme proteins is usually challenging mainly due to the insufficient supply of intracellular heme. Results Here, a versatile high-heme-producing Escherichia coli chassis was constructed for the efficient production of various high-value heme proteins. Initially, a heme-producing Komagataella phaffii strain was developed by reinforcing the C4 pathway-based heme synthetic route. Nevertheless, the analytical results revealed that most of the red compounds generated by the engineered K. phaffii strain were intermediates of heme synthesis which were unable to activate heme proteins. Subsequently, E. coli strain was selected as the host to develop heme-producing chassis. To fine-tune the C5 pathway-based heme synthetic route in E. coli, fifty-two recombinant strains harboring different combinations of heme synthesis genes were constructed. A high-heme-producing mutant Ec-M13 was obtained with negligible accumulation of intermediates. Then, the functional expression of three types of heme proteins including one dye-decolorizing peroxidase (Dyp), six oxygen-transport proteins (hemoglobin, myoglobin and leghemoglobin) and three CYP153A subfamily CYP enzymes was evaluated in Ec-M13. As expected, the assembly efficiencies of heme-bound Dyp and oxygen-transport proteins expressed in Ec-M13 were increased by 42.3–107.0% compared to those expressed in wild-type strain. The activities of Dyp and CYP enzymes were also significantly improved when expressed in Ec-M13. Finally, the whole-cell biocatalysts harboring three CYP enzymes were employed for nonanedioic acid production. High supply of intracellular heme could enhance the nonanedioic acid production by 1.8- to 6.5-fold. Conclusion High intracellular heme production was achieved in engineered E. coli without significant accumulation of heme synthesis intermediates. Functional expression of Dyp, hemoglobin, myoglobin, leghemoglobin and CYP enzymes was confirmed. Enhanced assembly efficiencies and activities of these heme proteins were observed. This work provides valuable guidance for constructing high-heme-producing cell factories. The developed mutant Ec-M13 could be employed as a versatile platform for the functional production of difficult-to-express heme proteins.

Tropical cyclone (TC)-induced coastal flooding can lead to severe hazards in low-lying lands and is expected to be exacerbated by sea level rise and TC climatology changes related to the warming climate. Since the dense population in Xiamen Bay, Fujian, China, it is highly valuable in understanding coastal flooding of it, but little studies involved this topic. In this study, we establish a high-resolution numerical model covering all coastal low-lying land in Xiamen Bay based on FVCOM. This model is then used to assess the flood risk in Xiamen Bay under TCs with 10-, 100-, and 1000-year pressures by applying a multi-tracks blend method. The results show that 126 km2 of low-lying area can be flooded periodically by astronomical tides; and 388, 504, and 598 km2 of low-lying area can be flooded under TCs with 10-, 100-, and 1000-year pressures, accompanied by increased average flood depths of 2.3, 2.8, and 3.4 m, respectively. By 2100 under SSP5-8.5, the well-protected Xiamen Island becomes impacted by TCs with 10-year pressure, and flood areas under TCs with 100-year pressure are estimated to be nearly equivalent to that under TCs with 1000-year pressure at the current climate. The most increased exposure area by climate change are artificial surfaces and agricultural areas, showing the potential higher flood disasters in future.

The riverine nutrient inputs to the ocean reflects land-use changes and can affect the health of coastal environments over time, especially for a highly-anthropogenically influenced river-estuary-shelf system. To investigate the impact of riverine inputs on the Changjiang Estuary ecosystem at a multi-decadal time scale where long-term observations are limited, we built a three-dimensional physics-biogeochemistry-coupled model system based on the Finite-Volume Community Ocean Model (FVCOM) and the European Regional Shelf Ecosystem Model (ERSEM). Our model successfully simulated the temporal and spatial nutrient variabilities in the river-estuary-shelf con7tinuum from 1960 to 2018. The results showed increasing trends of nitrate and phosphate and fluctuating silicate variability, thereby leading to rising nitrogen (N) to phosphorus (P) ratios and decreasing silicon (Si) to N and P ratios. Such changes in the stoichiometric relationship of nutrient species also alter the community structure of the primary producers in estuaries. Our model showed a general increase of diatoms over the 59 years, corresponding to decreased proportions of micro-phytoplankton and pico- phytoplankton. With different backgrounds of light and nutrient limitations in the river and inner shelf, our model suggests that the trend of the diatom proportion in the light-limited river mouth is more associated with silicate variability, with decreased diatom proportions occurring in the 2000s. Our model relates the hydroclimate, nutrient load, and biogeochemical cycling, reproducing estuarine ecosystem variability and clarifying issues such as the causality of the ecosystem interactions.

Phytoplankton, the dominant marine primary producers, are considered highly sensitive indicators of ecosystem conditions and changes. The East China Sea (ECS) includes a variety of oceanic and coastal domains that collectively challenge our understanding of phytoplankton dynamics and controls. This study evaluates the seasonal and interannual variability of phytoplankton in the ECS and the underlying environmental determinants based on 22-year satellite chlorophyll (Chl-a) data and concurrent environmental variables. A seasonal spring bloom was found in the ECS, classically driven by increased stratification, which is associated with increases in sea surface temperature (SST), photosynthetically available radiation (PAR), net heat flux (NHF), and reduced wind mixing. The most significant Chl-a interannual variability was present in a triangular area surrounded by three SST fronts in the southern ECS during springtime. Anomalously high Chl-a (~30% increase) occurred with increased SST and NHF and enhanced wind mixing during negative Pacific Decadal Oscillation (PDO) and El Niño–Southern Oscillation (ENSO) modes. This seems to be contrary to the stratification control model, which fits the seasonal spring bloom observed in this region. More front activities during the negative PDO and ENSO could be associated with Chl-a increase in this triangular area. Contrary to this mixing control scenario, a significant Chl-a increase (~36% increase) also developed during the positive PDO and ENSO modes after 2014 under conditions of higher SST, NHF, and weaker wind mixing following the stratification control scenario. This study used biologically relevant objective regionalization of a heterogeneous area to elucidate phytoplankton bloom dynamics and controls. Our analyses highlight the triangular area in the ECS for its region-specific linkages between Chl-a and multiple climate-sensitive environmental drivers, as well as the potential structural and functional variability in this region.

Estuarine plume frontal zones typically form a vertical two-layer structure with low-salinity and a high-temperature plume during the summertime. However, two field surveys in the Changjiang River Estuary and its adjacent shelf waters identified a significant surface cold-water zone (CWZ) formation in the summers of 2014 and 2015. The sea surface temperature of the CWZ was 4°C lower than the multi-year summer average. Satellite images showed that the CWZ mainly appeared in the Yangtze Shoal during the periods of July 1–17, 2014, and July 3–19, 2015. A three-dimensional physical-biogeochemical coupled model was used to explore the formation mechanism of the CWZ. Our investigation revealed that an uncharacteristic northerly wind during the southerly monsoon resulted in a significant onshore retreat of the plume front. Vertical tidal mixing is stronger than the decreased stratification in the former plume-covered region, which resulted in the formation of the CWZ. This process was accompanied by relatively lower net heat flux, which also promoted CWZ formation. The formation of CWZ had a strong ecological impact; enhanced vertical mixing transported nutrients from the lower layer to the surface column, relaxing the CWZ’s phosphate limitation. CWZ formation also increased the depth of the mixed layer and turbidity level in the water column, forming a temporary light limitation in the center. At the margin of the CWZ, it formed a patch with a high concentration of chlorophyll a. The underwater light was sufficient once the plume was restored and the CWZ was stratified again, and the phytoplankton grew rapidly in the center of the CWZ.

Corals rely on a symbiotic relationship with algae (zooxanthellae), which reside in the host tissue and play a critical role for host metabolism through photosynthesis, respiration, carbon translocation, and calcification. These processes affect coral reefs on different scales from cellular to organismal and ecosystem levels. A process-based dynamic model was developed and coupled with a one-dimensional (1-D) biogeochemical model to describe coral photosynthesis, respiration, and carbon translocation at the cellular level, calcification and ion transport in different coral polyp components (i.e., coelenteron, calcifying fluid) at the organismal level; and the exchange of material between corals and the ambient seawater at the ecosystem level. Major processes controlling the carbon budget in internal symbiosis were identified. For the symbiont, photosynthesis is the primary carbon source and translocation to the host is the major sink. For the host, most of the carbon translocated from the symbiont is lost through mucus leakage. In the host dissolved inorganic carbon (DIC) pool, most of the carbon is obtained from the surrounding seawater through uptake; photosynthesis and calcification are the major sinks of DIC. Based on a series of scenario studies, the model produced increase of photosynthesis rate with decline of calcification rate under higher air pCO2 and associated carbonate chemistry variabilities in different polyp components. The model results support the hypothesis that elevated pCO2 stimulates photosynthesis, resulting in a reduced supply of DIC to calcification. Such coupled models allow the exploration of process-based mechanisms, complementing laboratory and field studies.

Seaweed aquaculture produces enormous economic and ecological service benefits, making significant contributions to achieving global Sustainable Development Goals (SDGs). However, large-scale development of seaweed aquaculture and the unreasonable use of aquaculture rafts may trigger green tide, bringing negative ecological, social, and economic impacts. Therefore, it is vital to monitor the seaweed aquaculture industry accurately. Here, we mapped 10-m-resolution seaweed aquaculture along the Jiangsu coast of China based on active and passive remote sensing (Sentinel-1/2) and Random Forest using Google Earth Engine. The results demonstrate satisfactory model performance and data accuracy. The square seaweed aquaculture in the Lianyungang Offshore (Mode-I) has gradually expanded to the deep sea since 2016, with a maximum area of 194.06 km2 in 2018. Between 2021 and 2022, the area of the strip-shaped seaweed aquaculture in Subei radiation shoals (Mode-II) was considerably reduced, with most of the reduced land lying on the east side of the Dafeng Elk National Nature Reserve. In general, the area of the seaweed aquaculture in the prohibited breeding area was reduced from 20.32 km2 to 3.13 km2, and the area of the seaweed aquaculture in the restricted breeding area was reduced from 149.71 km2 to 33.15 km2. Results show that under the policy restriction, the scale of unsustainable seaweed aquaculture along the Jiangsu coast has been greatly reduced within seven years. This study can provide an efficient approach for the medium-scale extraction of seaweed aquaculture and provide decision support for the sustainable development of marine aquaculture.

The Krone–Partheniades (K-P) framework has been used for decades to quantify and analyze the sediment exchange at a water–bed interface. Measuring the erosion and deposition parameters that are part of this framework requires time-consuming field observations. Additionally, the erosion parameters are measured independently of deposition parameters, while in reality they are coupled. In numerical models applying the K-P framework these parameters are often assumed to be constant in time and mutually independent. In this study, we develop a relatively simple methodology to determine the erosion and deposition parameters, using conventional near-bed observations of bed level, sediment concentration and flow velocity. This methodology is subsequently applied to tripod observations collected in the Changjiang estuary, China, to compute continuous time-varying erosion and settling parameters. We propose a diagram to visualize the interdependency and accuracy of erosion and deposition parameters, which is the input for K-P framework models requiring this interdependency.

Abstract Sea level rise (SLR) and subsidence are expected to increase the risk of flooding and reliance on flood defenses for cities built on deltas. Here, we combine reliability analysis with hydrodynamic modeling to quantify the effect of projected relative SLR on dike failures and flood hazards for Shanghai, one of the most exposed delta cities. We find that flood inundation is likely to occur in low‐lying and poorly protected periurban/rural areas of the city even under the present‐day sea level. However, without adaptation measures, the risk increases by a factor of 3–160 across the densely populated floodplain under projected SLR to 2100. Impacts of frequent flood events are predicted to be more affected by SLR than those with longer return periods. Our results imply that including reliability‐based dike failures in flood simulations enables more credible flood risk assessment for global delta cities where conventional methods have assumed either overtopping only or complete failure.

Total alkalinity (AT) is an important variable in the regulation of the seawater carbonate chemistry system, determining the capacity to buffer changes in pH. In the coastal oceans, carbonate system dynamics are controlled by numerous processes such as land-derived inputs, biological activity, and coastal water dynamics, and seasonal alkalinity variations can play an important role in the regional carbon cycle. However, our understanding of these variations on the East China Sea (ECS) shelf remains poor due to limited observations. In order to estimate and investigate the seasonal variability of AT on the ECS shelf, an artificial neural network (ANN) model was developed using five cruise datasets from 2008 to 2018. The model used temperature, salinity, and dissolved oxygen to estimate AT with a root-mean-square error (RMSE) of ∼7 umol kg–1, and was applied to calculate AT for eight cruises during 2013–2016. In addition, monthly water column AT for the period 2000–2016 was obtained using temperature, salinity, and dissolved oxygen from the Changjiang Biology Finite-Volume Coastal Ocean Model (FVCOM) Data. Spatial distributions, seasonal cycles and correlations of surface AT indicated that the seasonal fluctuation of the Changjiang River discharge is the major factor affecting seasonal variation of surface AT on the ECS shelf. The largest seasonal fluctuations of surface AT were found on the inner shelf near the Changjiang Estuary, which is under the influence of the Changjiang River discharge.

Sediment suspension and transport driven by waves and currents play a significant role in both the ecological and physical environments of large lakes. Lake Michigan has faced a rapidly increasing water level associated with intensified wind waves in the past decade. To investigate the spatiotemporal characteristics of suspended sediment concentration (SSC) and associated coastal sediment budgets in southern Lake Michigan, a 30‐year (1991–2020) hindcast was performed using a coupled wave‐current‐ sediment model (SWAN‐FVCOM‐CSTMS). We found that in southern Lake Michigan, the basin‐wide mean SSC increased, and the coastal sediment loss accelerated dramatically, corresponding with intensified waves, currents and lake water level rises over the past decade. The basin‐wide mean SSC, coastal sediment loss, wave height, wind speed, current speed, and water level in southern Lake Michigan are highly correlated. Spatially, the results reveal decreases in coastal SSC and sediment loss in the western portion of the southern basin, while the eastern sectors show an increase in both metrics. This reflects a clear shift in the wave climate and hydrodynamic environment. The alterations in long‐term coastal sediment budgets imply that considerable shoreline transformations are being influenced by modifications in the wave climate. Understanding the spatiotemporal characteristics of SSC and coastal sediment budgets is crucial for strategic water resource management and coastal infrastructure planning. [ABSTRACT FROM AUTHOR]

Massive floating macroalgal blooms in the ocean have had an array of ecological consequences; thus, tracking their drifting pattern and predicting their biomass are important for their effective management. However, a high-resolution ecological dynamics model is lacking. In this study, a physical–ecological model, Floating Macroalgal Growth and Drift Model (FMGDM v1.0), was developed to determine the dynamic growth and drift pattern of floating macroalgal, based on the tracking, replication and extinction of Lagrangian particles. The position, velocity, quantity and represented biomass of particles are updated synchronously between the tracking module and the ecological module. The former is driven by ocean flows and sea surface wind, while the latter is controlled by the temperature, salinity, and irradiation. Based on the hydrodynamic models of the Finite-Volume Community Ocean Model and parameterized using a culture experiment of Ulva prolifera, which caused the largest bloom worldwide of the green tide in the Yellow Sea, China, this model was applied to simulate the green tides around the Yellow Sea in 2014 and 2015. The simulation result, distribution and biomass of green tides, was validated using remote sensing observation data and reasonably modeled the entire process of green tide bloom and its extinction from early spring to late summer. Given the prescribed spatial initialization from remote sensing observation, the model could provide accurate short-term (7–8 d) predictions of the spatial and temporal developments of the green tide. With the support of the hydrodynamic model and biological data of macroalgae, this model can forecast floating macroalgae blooms in other regions. [ABSTRACT FROM AUTHOR]

While our understanding of pH dynamics has strongly progressed for open ocean regions, for marginal seas such as the East China Sea (ECS) progress has been constrained by limited observations and complex interactions between biological, physical, and chemical processes. Seawater pH is a very valuable oceanographic variable but not always measured using high quality instrumentation and according to standard practices. In order to predict water column total scale pH (pHT) and enhance our understanding of the seasonal variability of pHT on the ECS shelf, an artificial neural network (ANN) model was developed using 11 cruise datasets from 2013 to 2017 with coincident observations of pHT, temperature (T), salinity (S), dissolved oxygen (DO), nitrate (N), phosphate (P) and silicate (Si) together with sampling position and time. The reliability of the ANN model was evaluated using independent observations from 3 cruises in 2018, and showed a root mean square error accuracy of 0.04. A weight analysis of the ANN model variables suggested that DO, S, T were the most important predictor variables. Monthly water column pHT for the period 2000-2016 was retrieved using T, S, DO, N, P, and Si from the Changjiang Biology Finite-Volume Coastal Ocean Model (FVCOM). [ABSTRACT FROM AUTHOR]

The increasing vulnerability of coastal mega-cities to storm surge inundation means both infrastructure and populations are subject to significant threat. Planning for further urban development should include consideration of the changing circumstances in coastal cities to ensure a sustainable future. A sustainable urban plan relies on well preparedness and prediction of future climate change and multiple natural hazards. In light of these needs for urban planning, this paper develops a general method to simulate typhoon generated storm surge at the meso-scale (1-100 km in length). Meso-scale simulation provides a general approach that could be implemented to fulfil the purpose of planning, and has relatively low requirements for computation time and data, while still providing reasonable accuracy. The case study of Shanghai was chosen to implement this method. The meso-scale simulated results of two historical typhoons not only provides a realistic result at the city level, but is also suitable for implementing a large amount of simulations for future scenario studies. The method is generally applicable to all coastal cities around the world to examine the effect of future climate change on typhoon generated storm surge, even where historical observed data are inadequate or not available. [ABSTRACT FROM AUTHOR]

Over the past decade, three phases of the Deep Waterway Project (DWP) have been carried out to deepen the shipping channel of the Changjiang Estuary, where a significant sandbar previously dominated. This project has produced significant hydrodynamic and morphological changes within the North Passage of the Changjiang Estuary. High-resolution and continuous seasonal bathymétrie data from 1998 to 2008 provide good insight into sedimentation processes. These data reveal several significant characteristics: (1) During phase I, strong erosion occurred around the upper region, and the entrance, middle, and lower regions are under moderate deposition. The groin-blocked region had strong depositions. (2) The main-channel region shifted to erosion-dominant conditions during phase II. Erosion also occurred in the northern areas of the upper and middle regions. The entrance and southern areas of the upper and middle regions experienced deposition. (3) During phase III, the entrance region reached sedimentation equilibrium, and the northern area of the lower region experienced strong erosion. The southern areas of the middle and lower regions were under deposition. Domain-nesting DelftSD-flow model is applied to understand the mechanisms of the observed morphology and its changes induced by three phases of the DWP, which reveals that hydrodynamics intensify within the main-channel regions and decrease in the groin-blocked regions. These results are consistent with sedimentation patterns found. The simulations also show that dikes effectively keep the high suspended sediment concentration waters of Jiuduansha Shoal from entering the North Passage. [ABSTRACT FROM AUTHOR]