The Macao Special Administrative Region is located in the southeastern coastal area of China. The region of Macao was narrow in the history, so land reclamation has become a main means of expanding its geographical scope. Exploring the significance of land reclamation for the planning and urban construction of the Macao region provides valuable references. (1) The Google Earth Engine (GEE) cloud processing platform is used in this study to calculate the modified normalized difference water index (MNDWI) based on Landsat data from 1986 to 2021; (2) the Jenks natural index classification method is used to extract the water body range, and the water body boundary as well as area at different periods is calculated combined with the neural network classification method in the environment for visualizing images (ENVI) software; (3) this study then combines the patch-generating land use simulation (PLUS) model to predict the future trend of shoreline changes in the study area in 2036. The result indicates that the MNDWI and neural net classification method lead to a high classification accuracy with both the overall accuracy (OA) and Kappa coefficient being higher than 87%. Land reclamation activities in Macao were gradually intense from 1986 to 2021, with social and economic conditions such as transportation being main influencing factors, which provides valuable references and inspiration for the regional planning of the Macao Special Administrative Region.

The biological pump, driven by phytoplankton production and death, plays a crucial role in the ocean’s sequestration of atmospheric CO₂. In particular, marginal seas with high primary productivity show a significant capacity for carbon fixation. Variations in phytoplankton biomass and community structure are key factors influencing the efficiency of the marine biological pump. The Taiwan Strait (TS) is a unique shallow conduit that connects the East China Sea (ECS) and the South China Sea (SCS), which are subject to seasonal monsoons and episodic events (e.g., typhoons and floods). Thus, its planktonic ecosystem is significantly influenced by physical processes such as strong ocean currents, coastal upwelling and river discharge, resulting in noticeable seasonal variability. In this study, we examined spatiotemporal patterns of phytoplankton biomass and community structure using phytoplankton-sourced biomarkers from suspended particles in surface waters across all four seasons from 2019 to 2020 in the TS. The findings highlight notable seasonal disparities in phytoplankton biomass, with spring and summer exhibiting significantly higher levels compared to autumn and winter. In order to determine phytoplankton ecosystem responses to various physical and biological processes on a seasonal scale, we used Empirical Orthogonal/Eigen Function (EOF) analysis to investigate the covarying spatiotemporal patterns of: marine-sourced biomarkers and terrestrial-sourced biomarkers in surface suspended particles, a biomass indicator (Chl a), water-mass indicators [sea surface temperature (SST), sea surface salinity (SSS), nutrients], and a hydrodynamic indicator [total suspended solids at surface/bottom water, (TSS_S and TSS_B)]. The results identified six physical-biological coupling modes that influence seasonal variations in marine phytoplankton ecosystems within the energetic strait system. Additionally, an in-depth understanding of the coupling between physical process and lipid biomarker signals from suspended particles in the contemporary marine environment can offer valuable insights for interpreting ancient sediment records of phytoplankton ecosystem evolution in the TS.

The characteristics of the terrain of a strait can lead to a “fine tube” effect that enhances a monsoon and thereby affects the physical, chemical, and biological processes of marine ecosystems. This effect is a highly dynamic and complex phenomenon involving interactions among atmospheric, oceanic, and terrestrial systems, as well as biogeochemical cycles and biological responses driven by it. However, current understanding has been focused mainly on the differences between monsoons, and there have been few studies concerned with the weakening or strengthening of monsoons. To explore the biogeochemical and phytoplankton responses during varying intensities of the northeast (NE) monsoon in the Taiwan Strait, high-resolution, across-front observations combined with FerryBox online data and satellite observations were conducted in this study during a strong, moderate, and weak NE monsoon. The spatiotemporal changes of nutrient concentrations and phytoplankton communities were regulated by the dynamics of ocean currents forced by NE winds. The weakening of the NE monsoon caused shrinkage of the coastal currents that led to a reduction of nutrient concentrations and an alteration of the distribution patterns of phytoplankton communities along cross-front sections. Specifically, there was a notable decrease in the proportions of dinoflagellates and cryptophytes in inshore regions and of prasinophytes in offshore areas. This study showed for the first time the dynamics of phytoplankton with changes of ocean currents during varying intensities of the NE monsoon in a strait system. The findings helped to elucidate the general spatial patterns of the phytoplankton community based on satellite-derived surface temperature and wind patterns and further enhanced the understanding of biogeochemical cycles in marine systems.

Over the past two decades, numerous countries have actively participated in the International Argo Program, working toward the global “OneArgo” goal. China’s Argo program has deployed over 500 autonomous profiling floats in the Indo-Pacific, with 55 Beidou (BD) floats, equipped with the Beidou satellite communication system, currently operational. During the operation of the BD float network, we found that in addition to the limitation of floats battery, the loss may also be caused by communication loss due to the floats escaping from the Beidou-2’s short message coverage. In this study, float trajectories are simulated using velocity fields from an eddy-resolved resolution Estimating the Circulation and Climate of the Ocean, Phase Ⅱ (ECCO2) model and a Lagrangian particle tracking model programmed to represent the vertical motions of profiling floats. The simulations can help to explore both the representativeness and the predictability of profiling float displacements. By deploying a large number of synthetic floats in the Lagrangian particle tracking system, we construct probability density functions (PDFs) of the simulated-float trajectory among key oceans, for example, a joint region of East Indian−South China Sea−Northwest Pacific Ocean (5°–40°N, 70°–140°E), which is generally similar to the location of the present BD float network. These statistics can help to estimate the chance of floats drifting into shallow seas (such as the East China Sea) and out of the coverage of the Beidou satellite communication. With this knowledge changes to the future China’s Argo observing system could be made.

Under global climate change, water flow and related nutrient biogeochemistry in the Arctic are changing at an unprecedented rate, and potentially affect nutrient cycling in the Arctic Ocean. However, nutrient fluxes via submarine groundwater discharge (SGD) are potentially important yet poorly understood in the Arctic. Here we quantified that nutrient fluxes through radium-derived SGD were three orders of magnitude higher than those from the local river and constituted 25%−96% of the total nutrient inputs into the Kongsfjorden. These large groundwater nutrient fluxes with high NIN/DIP molar ratio (average 99) may change the biomass and community structure of phytoplankton. Meanwhile, combining other SGD study cases around the Arctic region, SGD rates tend to increase over the past three decades, possibly on account of the effects of global warming. The SGD-derived nutrient may cause the increase of net primary productivity in the Arctic Ocean. The results will provide important basic data for land-ocean interactions in the typical fjord of the Arctic under the influence of global warming.

Forecasting of ocean currents is critical for both marine meteorological research and ocean engineering and construction. Timely and accurate forecasting of coastal current velocities offers a scientific foundation and decision support for multiple practices such as search and rescue, disaster avoidance and remediation, and offshore construction. This research established a framework to generate short-term surface current forecasts based on ensemble machine learning trained on high frequency radar observation. Results indicate that an ensemble algorithm that used random forests to filter forecasting features by weighting them, and then used the AdaBoost method to forecast can significantly reduce the model training time, while ensuring the model forecasting effectiveness, with great economic benefits. Model accuracy is a function of surface current variability and the forecasting horizon. In order to improve the forecasting capability and accuracy of the model, the model structure of the ensemble algorithm was optimized, and the random forest algorithm was used to dynamically select model features. The results show that the error variation of the optimized surface current forecasting model has a more regular error variation, and the importance of the features varies with the forecasting time-step. At ten-step ahead forecasting horizon the model reported root mean square error, mean absolute error, and correlation coefficient by 2.84 cm/s, 2.02 cm/s, and 0.96, respectively. The model error is affected by factors such as topography, boundaries, and geometric accuracy of the observation system. This paper demonstrates the potential of ensemble-based machine learning algorithm to improve forecasting of ocean currents.

To understand the temporal and spatial variations in nutrient dynamics, as well as the potential cross-shelf transport of nutrients between the East China Sea (ECS) shelf and the northwestern Pacific Ocean, six field observations covering the ECS were conducted in spring, summer, and autumn in 2011 and 2013. Nutrient dynamics in the ECS and nutrient exchange between shelf water and the open ocean were examined. High concentrations of dissolved inorganic nutrients were detected in the nearshore surface layer and offshore bottom layer in different seasons, and the concentrations of dissolved inorganic nutrients in surface seawater were lower in summer and autumn than in spring. The concentrations of dissolved organic nutrients in Kuroshio surface water were slightly lower in summer than in spring, but the concentrations in Kuroshio subsurface water were slightly higher in summer than in spring. There were abundant nutrient reservoirs in the euphotic zone of the ECS, which explained the high primary productivity. The evaluation of cross-shelf transport indicated that nutrients from shelf water were transported out across the 200 m isobath through the surface layer with the density (σ) less than 23.0 kg/m³ in spring. The flux of dissolved inorganic nitrogen transported from the ECS shelf to the Northwest Pacific Ocean in spring was equivalent to 21% of the atmospheric nitrogen deposition in the Northwest Pacific Ocean. In summer, the onshore flux in the surface and bottom layers accounted for 80% of the total flux, and the transportation of nutrients along the surface layer to the continental shelf contributed to the nutrient storage and primary productivity of the euphotic zone in the ECS shelf in summer.

The Canada Basin is the largest basin in the Arctic Ocean. Its unique physical features have the highest concentration of nutrients being found in the subsurface layer, referred to as the subsurface nutrient maximum layer (SNM). Under climate change in the Arctic, the SNM is an essential material base for primary productivity. However, long-term trends of nutrient variations and dominant factors related to nutrient levels in the SNM are still unclear. In this study, we analyzed the SNM variations and main influencing factors of the Canada Basin based on the Global Ocean Data Analysis Project Version 2 between 1990 and 2015 and the Chinese Arctic Research Expedition between 2010 and 2016. We found that the nutrient concentrations in the SNM were relatively stable for decades [average concentrations of nitrate, phosphate, and silicate were (13.6 ± 2.4) μmol/L, (1.8 ± 0.2) μmol/L, and (31.5 ± 5.7) μmol/L, respectively]. Nutrient reservoirs were dominated by physical processes. Inflow and outflow water of the SNM contributed about 60.4% and −50.2% to the nutrient stocks, respectively, while particle deposition and remineralization in the Canada Basin contributed approximately one-third to the nutrient stocks. Nitrogen fixation and denitrification in the Canada Basin had no substantial impact on nutrient stocks. The overall stabilization of the SNM over the past few decades implied that the SNM would not substantially affect short term primary productivity. Understanding the long-term trends and dominant factors of reservoirs in the SNM will provide useful insights into the changing Canada Basin ecosystem.

Ny-Ålesund, located in Arctic Svalbard, is one of the most sensitive areas on Earth to global warming. In recent years, accelerated glacier ablation has become remarkable in Ny-Ålesund. Glacial meltwaters discharge a substantial quantity of materials to the ocean, affecting downstream ecosystems and adjacent oceans. In August 2015, various water samples were taken near Ny-Ålesund, including ice marginal meltwater, proglacial meltwater, supraglacial meltwater, englacial meltwater, and groundwater. Trace metals (Al, Cr, Mn, Fe, Co, Cu, Zn, Cd, and Pb), major ions, alkalinity, pH, dissolved oxygen, water temperature and electric conductivity were also measured. Major ions were mainly controlled by chemical weathering intensity and reaction types, while trace metals were influenced by both chemical weathering and physicochemical control upon their mobility. Indeed, we found that Brøggerbreen was dominated by carbonate weathering via carbonation of carbonate, while Austre Lovénbreen and Pedersenbreen were dominated by sulfide oxidation coupled with carbonate dissolution with a doubled silicate weathering. The higher enrichment of trace metals in supraglacial meltwater compared to ice marginal and proglacial meltwater suggested anthropogenic pollution from atmospheric deposition. In ice marginal and proglacial meltwater, principal component analysis indicated that trace metals like Cr, Al, Co, Mn and Cd were correlated to chemical weathering. This implies that under accelerated glacier retreat, glacier-derived chemical components are subjected to future changes in weathering types and intensity.

The biogeochemical processes of marine sediments are influenced by bioturbation and organic carbon decomposition, which is crucial for understanding global element cycles and climate change. Two sediment cores were acquired in 2017 from abyssal basins in the central-eastern tropical Pacific to determine the bioturbation and organic carbon degradation processes. The radioactivity concentrations of ²¹⁰Pb and ²²⁶Ra in the sediment cores were measured, indicating the presence of significant excess ²¹⁰Pb (²¹⁰Pb_ex) signals in the sediment cores. Besides, a manganese nodule was discovered in one core, which had a substantial influence on the distribution of ²¹⁰Pb_ex. With the exception of this anomalous finding, the bioturbation coefficients in the remaining core were estimated to be 10.6 cm²/a using a steady-state diffusion model, greater than most of the deep-sea sediments from the equatorial eastern Pacific. By using a bio-diffusion model, we further calculated the degradation rates of organic carbon (8.02 ka⁻¹), which is also higher than other areas of the Pacific. Our findings displayed the presence of a biologically active benthic ecosystem in the central-eastern tropical Pacific.