Previous Issue
Display Method:
Articles in press have been peer-reviewed and accepted, which are not yet assigned to volumes /issues, but are citable by Digital Object Identifier (DOI).
Display Method:
, Available online
Abstract
FullText HTML
PDF 13669KB
Abstract:
Coral reef ecological restoration is internationally recognized as a pivotal technology and essential approach to reverse the degradation trend of coral reefs, which requires selecting native coral species for restoration and matched artificial reefs based on local conditions. Taking the degraded coral reef area of Weizhou Island, Guangxi as the research object, this study systematically investigated the growth adaptability of hermatypic stony corals and their compatibility with artificial reefs through a 10-month monitoring program of artificial nursery cultivation and an 18-month transplantation experiment involving three types of concrete artificial reefs (trapezoidal, table-shaped, and truncated conical). The results showed that the 10-month survival rates of all four tested coral species exceeded 85%. Both Acropora muricata and Acropora hyacinthus achieved 100% survival. Acropora hyacinthus exhibited a higher growth rate of living tissue projection area during some periods, while Acropora muricata performed better comprehensively in terms of survival stability, three-dimensional morphology formation, and engineering application potential, and can be used as the core restoration species. Among the three types of artificial reefs, the 18-month survival rate of corals on the trapezoidal artificial reef reached 92%, which was significantly higher than that on the truncated conical reef (77%) and the table-shaped reef (60%). Under environmental stress, physiological indicators including effective quantum yield and net photosynthetic rate showed significant specific responses to reef shapes, with the trapezoidal artificial reef demonstrating superior resistance to high temperature and typhoon stress as well as stronger damage recovery capability. The coral reef ecological restoration model established in this study—featuring Acropora muricata as the main restoration species, cable tie binding as the fixation method, metal seedbeds as the cultivation carrier, and trapezoidal artificial reefs as the colonization substrate—provides a scientific basis and practical technical reference for coral reef ecological restoration in typhoon-prone subtropical marine areas of China.
Coral reef ecological restoration is internationally recognized as a pivotal technology and essential approach to reverse the degradation trend of coral reefs, which requires selecting native coral species for restoration and matched artificial reefs based on local conditions. Taking the degraded coral reef area of Weizhou Island, Guangxi as the research object, this study systematically investigated the growth adaptability of hermatypic stony corals and their compatibility with artificial reefs through a 10-month monitoring program of artificial nursery cultivation and an 18-month transplantation experiment involving three types of concrete artificial reefs (trapezoidal, table-shaped, and truncated conical). The results showed that the 10-month survival rates of all four tested coral species exceeded 85%. Both Acropora muricata and Acropora hyacinthus achieved 100% survival. Acropora hyacinthus exhibited a higher growth rate of living tissue projection area during some periods, while Acropora muricata performed better comprehensively in terms of survival stability, three-dimensional morphology formation, and engineering application potential, and can be used as the core restoration species. Among the three types of artificial reefs, the 18-month survival rate of corals on the trapezoidal artificial reef reached 92%, which was significantly higher than that on the truncated conical reef (77%) and the table-shaped reef (60%). Under environmental stress, physiological indicators including effective quantum yield and net photosynthetic rate showed significant specific responses to reef shapes, with the trapezoidal artificial reef demonstrating superior resistance to high temperature and typhoon stress as well as stronger damage recovery capability. The coral reef ecological restoration model established in this study—featuring Acropora muricata as the main restoration species, cable tie binding as the fixation method, metal seedbeds as the cultivation carrier, and trapezoidal artificial reefs as the colonization substrate—provides a scientific basis and practical technical reference for coral reef ecological restoration in typhoon-prone subtropical marine areas of China.
, Available online
Abstract:
The mantle tissue and its mucus of the hard clam Meretrix meretrix play a significant role in defending against pathogens. However, the potential links between the composition and function of their inherent microbiota and host immunity remains unclear. In this study, 16S rRNA gene high-throughput sequencing was used to compare the microbiota composition and potential functions between the mantle tissue (group M) and mantle mucus (group N) in health clams. Non-targeted metabolomics (UHPLC-Q-TOF/MS) was employed to analyze metabolite changes in the mantle mucus under Vibrio stress. Furthermore, spearman correlation analysis was applied to integrate the microbiota and metabolomics data, aiming to preliminarily explore potential associations between the microbiota and host immune metabolism. The results revealed significant niche differentiation between the mantle and mucus microbiota. The mantle microbiota exhibited higher richness and was dominated by the phylum Spirochaetota, while the mucus microbiota showed higher evenness, with Proteobacteria and Bacteroidota as the dominant phyla. The mucus was significantly enriched in taxa with polysaccharide-degrading or potential pathogenic capabilities, such as the genera vibrio, Tenacibaculum and Flavobacterium. Functional prediction indicated that the mucus microbiota was more active in immune- and energy-related pathways, like cysteine and methionine metabolism and oxidative phosphorylation. Metabolomic analysis under Vibrio stress showed significant alterations in various immune-related metabolites in the mucus, including succinate acid, propionate acid, and phenylalanine. Correlation analysis between microbiota and metabolites revealed close associations between resident microbes and host metabolites, such as a strong positive correlation between the genus Marinomonas and uracil, and a strong negative correlation between Flavobacterium and nitrate. Collectively, these findings suggest that the mantle-mucus complex functions as a dynamic interfacial microenvironment. Its specific microbial community structure may interact with host metabolism, providing immunological preparedness for the host to counteract pathogen invasion.
The mantle tissue and its mucus of the hard clam Meretrix meretrix play a significant role in defending against pathogens. However, the potential links between the composition and function of their inherent microbiota and host immunity remains unclear. In this study, 16S rRNA gene high-throughput sequencing was used to compare the microbiota composition and potential functions between the mantle tissue (group M) and mantle mucus (group N) in health clams. Non-targeted metabolomics (UHPLC-Q-TOF/MS) was employed to analyze metabolite changes in the mantle mucus under Vibrio stress. Furthermore, spearman correlation analysis was applied to integrate the microbiota and metabolomics data, aiming to preliminarily explore potential associations between the microbiota and host immune metabolism. The results revealed significant niche differentiation between the mantle and mucus microbiota. The mantle microbiota exhibited higher richness and was dominated by the phylum Spirochaetota, while the mucus microbiota showed higher evenness, with Proteobacteria and Bacteroidota as the dominant phyla. The mucus was significantly enriched in taxa with polysaccharide-degrading or potential pathogenic capabilities, such as the genera vibrio, Tenacibaculum and Flavobacterium. Functional prediction indicated that the mucus microbiota was more active in immune- and energy-related pathways, like cysteine and methionine metabolism and oxidative phosphorylation. Metabolomic analysis under Vibrio stress showed significant alterations in various immune-related metabolites in the mucus, including succinate acid, propionate acid, and phenylalanine. Correlation analysis between microbiota and metabolites revealed close associations between resident microbes and host metabolites, such as a strong positive correlation between the genus Marinomonas and uracil, and a strong negative correlation between Flavobacterium and nitrate. Collectively, these findings suggest that the mantle-mucus complex functions as a dynamic interfacial microenvironment. Its specific microbial community structure may interact with host metabolism, providing immunological preparedness for the host to counteract pathogen invasion.
, Available online
Abstract:
High-stability monitoring of air-sea CO2 partial pressure (pCO2) is fundamental for assessing air-sea CO2 fluxes across long temporal and broad spatial scales. Among the commonly used methods worldwide, the air-water equilibration technique and the membrane-based diffusion technique are widely applied for measuring pCO2. In this study, we conducted underway continuous observations in Yueqing Bay and a 50-hour fixed-point deployment near Bianmanyu Island using the LI-5405A (air-water equilibration method) and the CONTROS HydroC® CO2 sensor (membrane equilibration method). The performance characteristics and application scenarios of the two approaches were systematically compared. The average difference between the two methods was 0.76 ± 4.46 μatm during the entire observation period, but both approaches produced consistent temporal trends with strong correlation. These two approaches exhibited distinct advantages: the membrane equilibrium method features low power consumption and an integrated watertight design, making it suitable for long-term continuous monitoring in in-situ scenarios or where power supply and space are limited. The air-water equilibration method, featuring rapid response and high precision, is more applicable for high-resolution measurements in dynamic environments. We propose a synergistic observational framework combining baseline monitoring using the membrane equilibration technique with periodic calibration via the air-water equilibration method. This integrated approach enhances both temporal and spatial resolution of air-sea CO2 flux observations, thereby improving data reliability and providing robust technical support for nearshore carbon source-sink assessments.
High-stability monitoring of air-sea CO2 partial pressure (pCO2) is fundamental for assessing air-sea CO2 fluxes across long temporal and broad spatial scales. Among the commonly used methods worldwide, the air-water equilibration technique and the membrane-based diffusion technique are widely applied for measuring pCO2. In this study, we conducted underway continuous observations in Yueqing Bay and a 50-hour fixed-point deployment near Bianmanyu Island using the LI-5405A (air-water equilibration method) and the CONTROS HydroC® CO2 sensor (membrane equilibration method). The performance characteristics and application scenarios of the two approaches were systematically compared. The average difference between the two methods was 0.76 ± 4.46 μatm during the entire observation period, but both approaches produced consistent temporal trends with strong correlation. These two approaches exhibited distinct advantages: the membrane equilibrium method features low power consumption and an integrated watertight design, making it suitable for long-term continuous monitoring in in-situ scenarios or where power supply and space are limited. The air-water equilibration method, featuring rapid response and high precision, is more applicable for high-resolution measurements in dynamic environments. We propose a synergistic observational framework combining baseline monitoring using the membrane equilibration technique with periodic calibration via the air-water equilibration method. This integrated approach enhances both temporal and spatial resolution of air-sea CO2 flux observations, thereby improving data reliability and providing robust technical support for nearshore carbon source-sink assessments.
, Available online
Abstract:
To overcome key challenges such as the tendency of seeds to drift with water currents during sowing and low seedling establishment rates, this study focused on eelgrass (Zostera marina), a dominant temperate seagrass species. The effects of two types of pelleting matrices—wood-based and mineral-based—and varying drying durations (0–12 min) on the physical and physiological properties of eelgrass seeds were systematically investigated. Following a preliminary screening of groups exhibiting germination potential, the impacts of these treatments on seed germination and seedling establishment were further evaluated. Results demonstrated that prolonged drying significantly enhanced both sinking acceleration and compressive strength of granulated seeds. Notably, seeds coated with the mineral-based matrix exhibited the highest sinking acceleration, reaching 3.2 times that of uncoated seeds, and displayed 3.1 times greater compressive strength than those in the wood-based matrix group. However, seed viability decreased progressively with increasing drying time: the uncoated and wood-based matrix groups maintained viability above 80% up to 8 min of drying, whereas the mineral-based group fell below this threshold after only 4 min. The wood-based matrix played a protective role in alleviating physiological stress induced by drying. Throughout the 0–12 min drying period, α-/β-amylase activities and total protein content in the wood-based matrix group remained comparable to those in the uncoated control group and were significantly higher than those in the mineral-based matrix group (P < 0.05). With respect to seedling establishment, the wood-based matrix treatment achieved rates of 39.0%–43.0% under drying durations of 0–4 min, which were statistically similar to the uncoated control (42.0%) and markedly higher than those observed in the mineral-based treatment (8%–12.5%). Correlation analysis revealed a highly significant positive association between seedling establishment rate and key physiological parameters, including enzyme activity and protein content. Furthermore, comprehensive benefit index analysis indicated that the wood-based matrix could achieve an optimal trade-off between physical suitability and physiological vitality when drying duration was restricted to 2–4 min. These findings suggest that using a wood-based pelleting matrix combined with a short drying duration (2–4 min) is a feasible and effective strategy for improving Z. marina seed handling and establishment in seagrass restoration practices.
To overcome key challenges such as the tendency of seeds to drift with water currents during sowing and low seedling establishment rates, this study focused on eelgrass (Zostera marina), a dominant temperate seagrass species. The effects of two types of pelleting matrices—wood-based and mineral-based—and varying drying durations (0–12 min) on the physical and physiological properties of eelgrass seeds were systematically investigated. Following a preliminary screening of groups exhibiting germination potential, the impacts of these treatments on seed germination and seedling establishment were further evaluated. Results demonstrated that prolonged drying significantly enhanced both sinking acceleration and compressive strength of granulated seeds. Notably, seeds coated with the mineral-based matrix exhibited the highest sinking acceleration, reaching 3.2 times that of uncoated seeds, and displayed 3.1 times greater compressive strength than those in the wood-based matrix group. However, seed viability decreased progressively with increasing drying time: the uncoated and wood-based matrix groups maintained viability above 80% up to 8 min of drying, whereas the mineral-based group fell below this threshold after only 4 min. The wood-based matrix played a protective role in alleviating physiological stress induced by drying. Throughout the 0–12 min drying period, α-/β-amylase activities and total protein content in the wood-based matrix group remained comparable to those in the uncoated control group and were significantly higher than those in the mineral-based matrix group (P < 0.05). With respect to seedling establishment, the wood-based matrix treatment achieved rates of 39.0%–43.0% under drying durations of 0–4 min, which were statistically similar to the uncoated control (42.0%) and markedly higher than those observed in the mineral-based treatment (8%–12.5%). Correlation analysis revealed a highly significant positive association between seedling establishment rate and key physiological parameters, including enzyme activity and protein content. Furthermore, comprehensive benefit index analysis indicated that the wood-based matrix could achieve an optimal trade-off between physical suitability and physiological vitality when drying duration was restricted to 2–4 min. These findings suggest that using a wood-based pelleting matrix combined with a short drying duration (2–4 min) is a feasible and effective strategy for improving Z. marina seed handling and establishment in seagrass restoration practices.
, Available online ,
doi: 10.12284/hyxb20260000
Abstract:
Artemia is important live bait in the cultivation of marine fish and crustacean seedlings, with more than 90% derived from wild Artemia resources. In order to study the effects of environmental changes and the unique aquaculture and harvest management on the morphometrical and genetic characteristics of Artemia in Yuncheng Salt Lake, Shanxi Province in the past 30 years, Artemia cysts collected in 1993 (YC-1993), 2019 (YC-2019) and 2023 (YC-2023) from Yuncheng Salt Lake were cultured and morphometrical measurements were conducted. Specific-locus amplified fragments sequencing (SLAF-seq) was used for population genetics analysis. The results showed that the YC-2023 group was extremely significantly larger than the YC-1993 group in terms of body length, abdominal length, ovary width, interocular distance, eye diameter, second antenna length, and peripheral claspers, while the cyst diameter of the YC-2023 group was significantly smaller than that of the YC-1993 group. The results of genetic analysis showed that the YC-2023 group had the lowest genetic diversity. The polymorphism information content (PIC) of three populations was between 0.252 and 0.305, showing moderate polymorphism (0.25<PIC<0.5). The Fst value of the genetic differentiation coefficient between the YC-2019 and YC-2023 populations is 0.087, indicating moderate genetic differentiation (0.05<Fst<0.15). However, the Fst value between the YC-1993 and the other two populations is 0.151, indicating a high degree of genetic differentiation (0.15<Fst<0.25). Phylogenetic tree, principal component analysis, the kinship heat map and Admixture analysis further revealed that although there was a certain degree of genetic differentiation among the three populations, their genetic information originated from the same original ancestor. The morphometrical traits and genetic variations of Yuncheng Artemia may result from genetic selection and genetic drift caused by the environmental changes that Yuncheng Salt Lake has undergone in recent years, and unique aquaculture and harvest management. This study will provide theoretical support for the conservation and utilization of Artemia germplasm resources in Yuncheng Salt Lake.
Artemia is important live bait in the cultivation of marine fish and crustacean seedlings, with more than 90% derived from wild Artemia resources. In order to study the effects of environmental changes and the unique aquaculture and harvest management on the morphometrical and genetic characteristics of Artemia in Yuncheng Salt Lake, Shanxi Province in the past 30 years, Artemia cysts collected in 1993 (YC-1993), 2019 (YC-2019) and 2023 (YC-2023) from Yuncheng Salt Lake were cultured and morphometrical measurements were conducted. Specific-locus amplified fragments sequencing (SLAF-seq) was used for population genetics analysis. The results showed that the YC-2023 group was extremely significantly larger than the YC-1993 group in terms of body length, abdominal length, ovary width, interocular distance, eye diameter, second antenna length, and peripheral claspers, while the cyst diameter of the YC-2023 group was significantly smaller than that of the YC-1993 group. The results of genetic analysis showed that the YC-2023 group had the lowest genetic diversity. The polymorphism information content (PIC) of three populations was between 0.252 and 0.305, showing moderate polymorphism (0.25<PIC<0.5). The Fst value of the genetic differentiation coefficient between the YC-2019 and YC-2023 populations is 0.087, indicating moderate genetic differentiation (0.05<Fst<0.15). However, the Fst value between the YC-1993 and the other two populations is 0.151, indicating a high degree of genetic differentiation (0.15<Fst<0.25). Phylogenetic tree, principal component analysis, the kinship heat map and Admixture analysis further revealed that although there was a certain degree of genetic differentiation among the three populations, their genetic information originated from the same original ancestor. The morphometrical traits and genetic variations of Yuncheng Artemia may result from genetic selection and genetic drift caused by the environmental changes that Yuncheng Salt Lake has undergone in recent years, and unique aquaculture and harvest management. This study will provide theoretical support for the conservation and utilization of Artemia germplasm resources in Yuncheng Salt Lake.
, Available online
Abstract:
This study examines the mechanism of the unexpected absence of bottom hypoxia in the lower Pearl River Estuary during summer 2023 through integrated analysis of hydrological, biogeochemical and physical drivers. The Pear River discharge during 2023 summer was only 51% of the historical average summer average. This led to a 45% reduction in riverine nutrient fluxes and a sharp decline in marine-sourced organic carbon production. Persistent northeasterly downwelling-favorable winds during the 15 days preceding sampling weakened stratification (stratification factor of 0.074 ± 0.20 during 2023 cruise versus 0.14 ± 0.17, 0.38 ± 0.50 and 0.18 ± 0.20 during other three cruises of 2015, 2017 and 2018 when hypoxia occurred) enhanced vertical mixing and oxygen replenishment in the bottom water. The reduced river discharge also shortened the water residence time in the estuary to 1.8 days, compared to 3.1 days under average summer discharge conditions, thereby limiting the oxygen-depleting effect of organic matter degradation. The synergistic effect of these factors led to the absence of bottom-water hypoxia in the Pearl River Estuary in summer 2023. This study reveals the important regulating role of extreme hydro-meteorological conditions in the formation of estuarine hypoxia.
This study examines the mechanism of the unexpected absence of bottom hypoxia in the lower Pearl River Estuary during summer 2023 through integrated analysis of hydrological, biogeochemical and physical drivers. The Pear River discharge during 2023 summer was only 51% of the historical average summer average. This led to a 45% reduction in riverine nutrient fluxes and a sharp decline in marine-sourced organic carbon production. Persistent northeasterly downwelling-favorable winds during the 15 days preceding sampling weakened stratification (stratification factor of 0.074 ± 0.20 during 2023 cruise versus 0.14 ± 0.17, 0.38 ± 0.50 and 0.18 ± 0.20 during other three cruises of 2015, 2017 and 2018 when hypoxia occurred) enhanced vertical mixing and oxygen replenishment in the bottom water. The reduced river discharge also shortened the water residence time in the estuary to 1.8 days, compared to 3.1 days under average summer discharge conditions, thereby limiting the oxygen-depleting effect of organic matter degradation. The synergistic effect of these factors led to the absence of bottom-water hypoxia in the Pearl River Estuary in summer 2023. This study reveals the important regulating role of extreme hydro-meteorological conditions in the formation of estuarine hypoxia.
, Available online
Abstract:
The Miaodao Archipelago in Shandong Province are rich in seaweed resources and hold great potential for nearshore marine carbon sinks. However, fundamental data and research related to the seaweed beds in this region remain scarce, which astricts the calculation and evaluation to carbon sink of seaweed beds. Therefore, this study aimed to complement the gap in baseline information regarding seaweed beds in the Miaodao Archipelago. In this study, 10 residential islands of Miaodao archipelago in Shandong Province were selected and the distribution of seaweed fields in the subtidal zone was investigated and sampled by scuba diving. Seaweed resource information in the seaweed beds, including the distribution and area of seaweed beds, species composition, biomass, dominant species, and community diversity, was identified and counted, and then combined with the environmental context, the community structure characteristics of the seaweed beds in the 10 islands were clustered. A total of 34 species of macroalgae were collected, belonging to 21 families and 25 genera. Among them were 18 species of red algae (11 families, 15 genera), 4 species of green algae (2 families, 2 genera), and 12 species of brown algae (8 families, 8 genera). The dominant macroalgal species in the region included Saccharina japonica, Undaria pinnatifida, Sargassum muticum, Gelidium amansii, Chondrus nipponicus, Ulva lactuca, Dictyopteris divaricata, Sargassum pallidum, and Desmarestia viridis. The results of statistical analysis revealed that Tuoji Island and Xiaoqin Island had relatively high biomass density. Nouth Changshan Island exhibited the highest species richness, followed by Miao Island and South Huangcheng Island. South Huangcheng Island had the highest diversity index, with Nouth Changshan Island and Tuoji Island ranking next, and also showed the highest evenness index among the surveyed sites. Cluster analysis results indicated significant differences in community structure between the five southern islands (South Changshan Island, North Changshan Island, Miao Island, Daheishan Island, Xiaoheishan Island) and the five northern islands (Tuoji Island, Daqin Island, Xiaoqin Island, South Huangcheng Island, North Huangcheng Island), mainly due to geographic variation. This study helps complement the gap in baseline information regarding seaweed beds in Shandong Province, thus providing essential data for the carbon sink evaluation and theoretical support for development of nearshore blue carbon sink of seaweed beds in Shandong Province.
The Miaodao Archipelago in Shandong Province are rich in seaweed resources and hold great potential for nearshore marine carbon sinks. However, fundamental data and research related to the seaweed beds in this region remain scarce, which astricts the calculation and evaluation to carbon sink of seaweed beds. Therefore, this study aimed to complement the gap in baseline information regarding seaweed beds in the Miaodao Archipelago. In this study, 10 residential islands of Miaodao archipelago in Shandong Province were selected and the distribution of seaweed fields in the subtidal zone was investigated and sampled by scuba diving. Seaweed resource information in the seaweed beds, including the distribution and area of seaweed beds, species composition, biomass, dominant species, and community diversity, was identified and counted, and then combined with the environmental context, the community structure characteristics of the seaweed beds in the 10 islands were clustered. A total of 34 species of macroalgae were collected, belonging to 21 families and 25 genera. Among them were 18 species of red algae (11 families, 15 genera), 4 species of green algae (2 families, 2 genera), and 12 species of brown algae (8 families, 8 genera). The dominant macroalgal species in the region included Saccharina japonica, Undaria pinnatifida, Sargassum muticum, Gelidium amansii, Chondrus nipponicus, Ulva lactuca, Dictyopteris divaricata, Sargassum pallidum, and Desmarestia viridis. The results of statistical analysis revealed that Tuoji Island and Xiaoqin Island had relatively high biomass density. Nouth Changshan Island exhibited the highest species richness, followed by Miao Island and South Huangcheng Island. South Huangcheng Island had the highest diversity index, with Nouth Changshan Island and Tuoji Island ranking next, and also showed the highest evenness index among the surveyed sites. Cluster analysis results indicated significant differences in community structure between the five southern islands (South Changshan Island, North Changshan Island, Miao Island, Daheishan Island, Xiaoheishan Island) and the five northern islands (Tuoji Island, Daqin Island, Xiaoqin Island, South Huangcheng Island, North Huangcheng Island), mainly due to geographic variation. This study helps complement the gap in baseline information regarding seaweed beds in Shandong Province, thus providing essential data for the carbon sink evaluation and theoretical support for development of nearshore blue carbon sink of seaweed beds in Shandong Province.
, Available online
Abstract:
Taking the Caofeidian seagrass bed—the largest existing seagrass bed in China—as the research object, this study adopted a combined method of remote sensing interpretation, field investigation, and model analysis to carry out research on the quantitative zoning of density and the formation mechanism of spatial heterogeneity of the Caofeidian seagrass bed. Through the interpretation of high-resolution satellite remote sensing images and combined with on-site field verification, the quantitative data of three core zoning types under the spatial pattern of “dense in the north and sparse in the south” of the Caofeidian seagrass bed were obtained, namely the dense area (with an area of 7.31 km2, accounting for 18.34%), the moderately dense area (with an area of 10.36 km2, accounting for 26.00%), and the sparse area (with an area of 22.18 km2, accounting for 55.66%). On the whole, it shows the characteristics of patchy mosaic distribution. Based on 10 environmental data items (including illumination, ammonium, and sediment density) obtained from field investigations, an MLP-ANN (Multilayer Perceptron-Artificial Neural Network) model was used for analysis, and it was found that the internal friction angle of sediment (contribution: 18%), water temperature (contribution: 15%), and sediment phosphate (contribution: 15%) were the core driving factors affecting the density zoning of the seagrass bed, with a cumulative influence accounting for 48%. The research results indicated that the density zoning of the Caofeidian seagrass bed is formed by thejoint effect of natural dynamic factors and human activities: in the southern region, strong tidal currents cause sediment scouring, and superimposed on the impacts of engineering activities such as oilfield exploration and channel dredging, as well as land-based pollution, forming the degradation chain of “sediment disturbance - nutrient imbalance”; the northern region is far from these disturbance sources, and through ecological restoration, the sediment conditions have been optimized, thus providing support for the formation of the medium-to-high density seagrass bed areas. This study fills the gaps in the quantitative research on the density zoning of the Caofeidian seagrass bed and the research on its formation mechanism, and provides a scientific basis and technical paradigm for the scientific assessment and effective restoration of seagrass beds in the Bohai Bay.
Taking the Caofeidian seagrass bed—the largest existing seagrass bed in China—as the research object, this study adopted a combined method of remote sensing interpretation, field investigation, and model analysis to carry out research on the quantitative zoning of density and the formation mechanism of spatial heterogeneity of the Caofeidian seagrass bed. Through the interpretation of high-resolution satellite remote sensing images and combined with on-site field verification, the quantitative data of three core zoning types under the spatial pattern of “dense in the north and sparse in the south” of the Caofeidian seagrass bed were obtained, namely the dense area (with an area of 7.31 km2, accounting for 18.34%), the moderately dense area (with an area of 10.36 km2, accounting for 26.00%), and the sparse area (with an area of 22.18 km2, accounting for 55.66%). On the whole, it shows the characteristics of patchy mosaic distribution. Based on 10 environmental data items (including illumination, ammonium, and sediment density) obtained from field investigations, an MLP-ANN (Multilayer Perceptron-Artificial Neural Network) model was used for analysis, and it was found that the internal friction angle of sediment (contribution: 18%), water temperature (contribution: 15%), and sediment phosphate (contribution: 15%) were the core driving factors affecting the density zoning of the seagrass bed, with a cumulative influence accounting for 48%. The research results indicated that the density zoning of the Caofeidian seagrass bed is formed by thejoint effect of natural dynamic factors and human activities: in the southern region, strong tidal currents cause sediment scouring, and superimposed on the impacts of engineering activities such as oilfield exploration and channel dredging, as well as land-based pollution, forming the degradation chain of “sediment disturbance - nutrient imbalance”; the northern region is far from these disturbance sources, and through ecological restoration, the sediment conditions have been optimized, thus providing support for the formation of the medium-to-high density seagrass bed areas. This study fills the gaps in the quantitative research on the density zoning of the Caofeidian seagrass bed and the research on its formation mechanism, and provides a scientific basis and technical paradigm for the scientific assessment and effective restoration of seagrass beds in the Bohai Bay.
, Available online
Abstract:
Toxic algal species pose significant threats to ecological environmental safety and human health. Azadinium dexteroporum, one of the main producers of azaspiracid toxins, remains poorly studied in China, and its distribution in Chinese coastal waters is still unclear. In this study, environmental DNA (eDNA) methods were used to obtain occurrence records of A. dexteroporum in Chinese coastal areas. Using the 2050s and 2100s as future projection periods, the Maximum Entropy (MaxEnt)model was applied to simulate the potential suitable habitats of this species under current and three future climate scenarios (SSP126, SSP245, and SSP585). The results indicated that nitrate concentration, silicate concentration, and sea surface temperature were the primary environmental factors influencing the distribution of A. dexteroporum. Under current conditions, the suitable habitat area was estimated to be 63.71 × 104 km2, mainly concentrated in the northern South China Sea. With climate change, the potential suitable area of A. dexteroporum is projected to shrink, decreasing to 5.58×104 km2～32.21×104 km2 by the 2100s. The spatial distribution pattern of suitable habitats shows an overall “southward contraction and northward expansion” trend: the extensive suitable areas in the South China Sea are expected to disappear, while new suitable areas may emerge in the Yellow and Bohai Seas. The centroid of suitable habitats is projected to shift up to 1,439 km, migrating from the northern South China Sea to north of the Yangtze River estuary. These findings provide important scientific insights for the ecological risk monitoring, forecasting, and management of harmful dinoflagellates.
Toxic algal species pose significant threats to ecological environmental safety and human health. Azadinium dexteroporum, one of the main producers of azaspiracid toxins, remains poorly studied in China, and its distribution in Chinese coastal waters is still unclear. In this study, environmental DNA (eDNA) methods were used to obtain occurrence records of A. dexteroporum in Chinese coastal areas. Using the 2050s and 2100s as future projection periods, the Maximum Entropy (MaxEnt)model was applied to simulate the potential suitable habitats of this species under current and three future climate scenarios (SSP126, SSP245, and SSP585). The results indicated that nitrate concentration, silicate concentration, and sea surface temperature were the primary environmental factors influencing the distribution of A. dexteroporum. Under current conditions, the suitable habitat area was estimated to be 63.71 × 104 km2, mainly concentrated in the northern South China Sea. With climate change, the potential suitable area of A. dexteroporum is projected to shrink, decreasing to 5.58×104 km2～32.21×104 km2 by the 2100s. The spatial distribution pattern of suitable habitats shows an overall “southward contraction and northward expansion” trend: the extensive suitable areas in the South China Sea are expected to disappear, while new suitable areas may emerge in the Yellow and Bohai Seas. The centroid of suitable habitats is projected to shift up to 1,439 km, migrating from the northern South China Sea to north of the Yangtze River estuary. These findings provide important scientific insights for the ecological risk monitoring, forecasting, and management of harmful dinoflagellates.
, Available online ,
doi: 10.12284/hyxb2025006
Abstract:
Studying the occurrence and dynamics of microplastics on coastal beaches is crucial for the integrated management of coastal zones and the assessment of ecological risks. Previous research has highlighted that physical processes play a pivotal role in influencing the occurrences of microplastic on coastal beaches. However, the impact of extreme meteorological events such as typhoons on the distribution of microplastic pollution has yet to be explored. This study conducted field fixed-plot experiments on the coastal beaches of Xiamen City before and after Typhoon "Haikui" to analyze the variations in the abundance, composition, and diversity of microplastic on beaches. The results showed that the abundance of microplastics on the beaches in Xiamen City before Typhoon Haikui was (251.5 ± 27.9) n/kg, and this value significantly decreased to (127.0 ± 18.8) n/kg post-typhoon. Before and after the typhoon, the composition of microplastics on the beaches showed distinct variations, with the abundance of microplastics of different shapes and sizes responding differently to the typhoon. In particular, the abundance of smaller particles (<500 μm) significantly decreased, while the proportion of fibrous particles increased. Moreover, the typhoon event led to a general decrease in the Shannon-Wiener diversity index, while an increase in the Pielou’s evenness index. The impact of typhoons on the distribution of microplastics on beaches arises from the complex coupling of multiple dynamic physical processes in extreme weather, and it is also closely related to factors such as the location and substrate conditions of the coasts. To achieve simulation and prediction of the dynamics of microplastic pollution during typhoon processes, systematic and comprehensive research on the relevant mechanisms is still required in the future.
Studying the occurrence and dynamics of microplastics on coastal beaches is crucial for the integrated management of coastal zones and the assessment of ecological risks. Previous research has highlighted that physical processes play a pivotal role in influencing the occurrences of microplastic on coastal beaches. However, the impact of extreme meteorological events such as typhoons on the distribution of microplastic pollution has yet to be explored. This study conducted field fixed-plot experiments on the coastal beaches of Xiamen City before and after Typhoon "Haikui" to analyze the variations in the abundance, composition, and diversity of microplastic on beaches. The results showed that the abundance of microplastics on the beaches in Xiamen City before Typhoon Haikui was (251.5 ± 27.9) n/kg, and this value significantly decreased to (127.0 ± 18.8) n/kg post-typhoon. Before and after the typhoon, the composition of microplastics on the beaches showed distinct variations, with the abundance of microplastics of different shapes and sizes responding differently to the typhoon. In particular, the abundance of smaller particles (<500 μm) significantly decreased, while the proportion of fibrous particles increased. Moreover, the typhoon event led to a general decrease in the Shannon-Wiener diversity index, while an increase in the Pielou’s evenness index. The impact of typhoons on the distribution of microplastics on beaches arises from the complex coupling of multiple dynamic physical processes in extreme weather, and it is also closely related to factors such as the location and substrate conditions of the coasts. To achieve simulation and prediction of the dynamics of microplastic pollution during typhoon processes, systematic and comprehensive research on the relevant mechanisms is still required in the future.
, Available online
Abstract:
This study focuses on the physical process of a sea fog event during Typhoon Lekima in the Northern Yellow Sea by using observation data, reanalysis data and backward trajectory model. The analysis indicates that the typhoon circulation was the decisive factor determining whether fog formed offshore and developed inland. The warm and humid southerlies from the south Yellow Sea condensed into fog on the colder sea surface besides the typhoon center, which not only provided sufficient moisture for the formation and development of the sea fog but also formed a significant inversion layer over the fog area with the downdraft in the center of the typhoon. The "stable up and turbulent down" structure in the atmospheric boundary layer improved the development of sea fog on the coast and inland area. However, the horizontal wind steering and the strengthening wind speed behind the typhoon strengthened the wind shear in the atmospheric boundary layer, resulting in the enhanced turbulent mixing and the decrease of the stability in the bottom atmospheric boundary layer, which was the main cause of the fog dissipation.
This study focuses on the physical process of a sea fog event during Typhoon Lekima in the Northern Yellow Sea by using observation data, reanalysis data and backward trajectory model. The analysis indicates that the typhoon circulation was the decisive factor determining whether fog formed offshore and developed inland. The warm and humid southerlies from the south Yellow Sea condensed into fog on the colder sea surface besides the typhoon center, which not only provided sufficient moisture for the formation and development of the sea fog but also formed a significant inversion layer over the fog area with the downdraft in the center of the typhoon. The "stable up and turbulent down" structure in the atmospheric boundary layer improved the development of sea fog on the coast and inland area. However, the horizontal wind steering and the strengthening wind speed behind the typhoon strengthened the wind shear in the atmospheric boundary layer, resulting in the enhanced turbulent mixing and the decrease of the stability in the bottom atmospheric boundary layer, which was the main cause of the fog dissipation.
, Available online
Abstract:
The possibility of the Indonesian submarine wreck on 20 April 2021 was analyzed based on satellite remote sensing observation and numerical simulation. The results indicate that large-amplitude oceanic internal waves, estimated to be approximately 50 m using satellite images, originate from the Lombok Strait. They are widely distributed to the north of the Bali Island and are suggested to cause an abrupt sinking of the Indonesian submarine.
The possibility of the Indonesian submarine wreck on 20 April 2021 was analyzed based on satellite remote sensing observation and numerical simulation. The results indicate that large-amplitude oceanic internal waves, estimated to be approximately 50 m using satellite images, originate from the Lombok Strait. They are widely distributed to the north of the Bali Island and are suggested to cause an abrupt sinking of the Indonesian submarine.
, Available online
Abstract:
Abstract：The potential fish production was controlled largely by ocean primary production (OPP) and there were a lot of research findings of estimating fish production by using OPP in China. The relationships between the biomass of fishery stock and OPP were often complicated by the varieties of trophic control in the ecosystem. In this paper, we examined the relationship between biomass of chub mackerel (Scomber japonicus) and net primary production (NPP) and discussed mechanism of trophic control in the ecosystem of chub mackerel fishing ground in south East China Sea by using catch and effort data from the large purse sense of China fishery and NPP derived from remote sensing. The results showed there was a significant non-linear relationship between NPP and standardized CPUE (Catch Per Unit Effort) (P<0.05) instead of the linear trend. The non-linear relationship could be described by a reversed parabolic curve, which meant the biomass of chub mackerel increased with NPP and then decreased when the NPP exceeded a point. The results implied there were other trophic controls in addition to bottom-up control occurred in the ecosystem in south East China Sea. We speculated the change of abundance of the key species at intermediate trophic levels or/and interspecific competitions contribute to the relationship.
Abstract：The potential fish production was controlled largely by ocean primary production (OPP) and there were a lot of research findings of estimating fish production by using OPP in China. The relationships between the biomass of fishery stock and OPP were often complicated by the varieties of trophic control in the ecosystem. In this paper, we examined the relationship between biomass of chub mackerel (Scomber japonicus) and net primary production (NPP) and discussed mechanism of trophic control in the ecosystem of chub mackerel fishing ground in south East China Sea by using catch and effort data from the large purse sense of China fishery and NPP derived from remote sensing. The results showed there was a significant non-linear relationship between NPP and standardized CPUE (Catch Per Unit Effort) (P<0.05) instead of the linear trend. The non-linear relationship could be described by a reversed parabolic curve, which meant the biomass of chub mackerel increased with NPP and then decreased when the NPP exceeded a point. The results implied there were other trophic controls in addition to bottom-up control occurred in the ecosystem in south East China Sea. We speculated the change of abundance of the key species at intermediate trophic levels or/and interspecific competitions contribute to the relationship.
Display Method:
2026, 48(2): 1-10.
doi: 10.12284/hyxb20260020
Abstract:
In 2025, China’s manned submersible, the Jiaolong, successfully completed its first manned deep-sea dive in the ice-covered waters of the Arctic, marking a pivotal first step in advancing China’s deep-sea exploration from ‘full ocean depth’ to ‘all ocean regions’. The expedition faced numerous challenges, including extremely low temperatures, shifting sea ice, geomagnetic anomalies and intricate underwater acoustic conditions. We made systematic adaptations to the Jiaolong submersible, achieving key technological breakthroughs in deployment and recovery, under-ice ascent guidance, and ice-zone navigation and positioning. This paper outlines the core challenges of manned deep-sea operations in polar environments. It focuses on the submersible’s tailored modification plan and the key technologies implemented during the world’s first coordinated dual-submersible mission in polar waters. This paper aim to provide technical references and engineering paradigms for China’s future routine polar deep-sea exploration, habitat studies and resource surveys.
In 2025, China’s manned submersible, the Jiaolong, successfully completed its first manned deep-sea dive in the ice-covered waters of the Arctic, marking a pivotal first step in advancing China’s deep-sea exploration from ‘full ocean depth’ to ‘all ocean regions’. The expedition faced numerous challenges, including extremely low temperatures, shifting sea ice, geomagnetic anomalies and intricate underwater acoustic conditions. We made systematic adaptations to the Jiaolong submersible, achieving key technological breakthroughs in deployment and recovery, under-ice ascent guidance, and ice-zone navigation and positioning. This paper outlines the core challenges of manned deep-sea operations in polar environments. It focuses on the submersible’s tailored modification plan and the key technologies implemented during the world’s first coordinated dual-submersible mission in polar waters. This paper aim to provide technical references and engineering paradigms for China’s future routine polar deep-sea exploration, habitat studies and resource surveys.
2026, 48(2): 79-94.
doi: 10.12284/hyxb20260010
Abstract:
High-quality underwater optical images are crucial for tasks such as digital twins of seabed scenes, benthic habitat protection, seabed mineral resource detection, and understanding unknown underwater phenomena. However, due to factors such as complex aquatic environments and lighting conditions, underwater optical images suffer from degradation issues including color distortion, blurred details, and low contrast. Existing underwater image enhancement methods often focus on optimizing enhancement algorithms themselves, lacking systematic analytical mechanisms for tracing, classifying, and grading different types of degradation. To address this, considering the complexity and heterogeneity of underwater optical imaging environments, this paper proposes an image quality enhancement strategy that takes degradation types into account. First, a degradation-type-aware network is constructed to identify underwater hazy and blurred images, achieving an accuracy of 97%, and also demonstrating a high distinguishing capability for illumination degradation types. Second, for the identified underwater hazy images, an adaptive color correction method is designed based on the statistical distribution of color bias values in real underwater images, effectively restoring color attenuation in varying degrees. Finally, a block indexing strategy is introduced to obtain more precise background light estimates, further addressing the hazy blur issue in underwater images in conjunction with the underwater dark channel prior. Experimental results on various real underwater image datasets, including UIEB and RUIE, indicate that compared to representative underwater image enhancement methods, the PSNR and SSIM metrics are improved by 22.17% and 4.5%, respectively.
High-quality underwater optical images are crucial for tasks such as digital twins of seabed scenes, benthic habitat protection, seabed mineral resource detection, and understanding unknown underwater phenomena. However, due to factors such as complex aquatic environments and lighting conditions, underwater optical images suffer from degradation issues including color distortion, blurred details, and low contrast. Existing underwater image enhancement methods often focus on optimizing enhancement algorithms themselves, lacking systematic analytical mechanisms for tracing, classifying, and grading different types of degradation. To address this, considering the complexity and heterogeneity of underwater optical imaging environments, this paper proposes an image quality enhancement strategy that takes degradation types into account. First, a degradation-type-aware network is constructed to identify underwater hazy and blurred images, achieving an accuracy of 97%, and also demonstrating a high distinguishing capability for illumination degradation types. Second, for the identified underwater hazy images, an adaptive color correction method is designed based on the statistical distribution of color bias values in real underwater images, effectively restoring color attenuation in varying degrees. Finally, a block indexing strategy is introduced to obtain more precise background light estimates, further addressing the hazy blur issue in underwater images in conjunction with the underwater dark channel prior. Experimental results on various real underwater image datasets, including UIEB and RUIE, indicate that compared to representative underwater image enhancement methods, the PSNR and SSIM metrics are improved by 22.17% and 4.5%, respectively.
2026, 48(2): 11-28.
doi: 10.12284/hyxb20260002
Abstract:
Infragravity waves (with periods of 25−250 s) are critical components of nearshore hydrodynamic processes and have significant influence on coastal geomorphological evolution and engineering safety. Based on the conservation equations of mass, momentum, and energy, this paper systematically reviews the latest research progress on the generation mechanisms and evolution characteristics of infragravity waves. Regarding generation mechanisms, the review elaborates on four primary mechanisms: bound long waves, moving breakpoint forcing, bore merging, and wind gusts. Particular attention is given to the theoretical development from the classical equilibrium solution to non-equilibrium solutions for bound long waves, along with the recently proposed unified Green’s function approach. In terms of propagation and evolution, the phase variation and energy transfer, nonlinear shoaling, nearshore dissipation, and shoreline reflection of infragravity waves on sloping beaches are introduced. Then, the amplification of infragravity waves over offshore raised topographies and coral reefs is also examined. The article further points out the inherent randomness present during the evolution of infragravity waves. Finally, future research directions are outlined, providing a theoretical reference for further study and application in terms of infragravity waves.
Infragravity waves (with periods of 25−250 s) are critical components of nearshore hydrodynamic processes and have significant influence on coastal geomorphological evolution and engineering safety. Based on the conservation equations of mass, momentum, and energy, this paper systematically reviews the latest research progress on the generation mechanisms and evolution characteristics of infragravity waves. Regarding generation mechanisms, the review elaborates on four primary mechanisms: bound long waves, moving breakpoint forcing, bore merging, and wind gusts. Particular attention is given to the theoretical development from the classical equilibrium solution to non-equilibrium solutions for bound long waves, along with the recently proposed unified Green’s function approach. In terms of propagation and evolution, the phase variation and energy transfer, nonlinear shoaling, nearshore dissipation, and shoreline reflection of infragravity waves on sloping beaches are introduced. Then, the amplification of infragravity waves over offshore raised topographies and coral reefs is also examined. The article further points out the inherent randomness present during the evolution of infragravity waves. Finally, future research directions are outlined, providing a theoretical reference for further study and application in terms of infragravity waves.
2026, 48(2): 29-39.
doi: 10.12284/hyxb20260008
Abstract:
Based on the observations of 3 wave buoys deployed in Liaodong Bay in winter of 2023−2025 and wave numerical model, this paper analyzes the characteristics of waves during freezing winter of Bohai Sea. According to the statistic results, the mean significant wave heights (mean significant wave periods) observed by 2 buoys in the center of Bohai Sea are about 1 m (4−5 s). Observations from the located buoy in Liaodong Bay indicate that waves are great affected by sea ice. When the buoy locates in a freezing region, the observed mean significant wave heights (mean significant periods) are 0.2 m (9 s), indicating a 54% reduction (98% increase) compared to the measurements without sea ice. The existence of sea ice may also lead the peak wave direction differ from the dominant wind direction. On the perspective of numeric modeling, the error of simulated wave heights can be reduced by 33% via adding ice-wave terms compared to the model without ice terms. By comparing two wind input terms (Komen and ST6), this paper finds that the simulations match the observations well and the error is comparable. Based on observations of buoys, the results rich the acknowledgements of people in the wave features in Bohai Sea during the freezing winter.
Based on the observations of 3 wave buoys deployed in Liaodong Bay in winter of 2023−2025 and wave numerical model, this paper analyzes the characteristics of waves during freezing winter of Bohai Sea. According to the statistic results, the mean significant wave heights (mean significant wave periods) observed by 2 buoys in the center of Bohai Sea are about 1 m (4−5 s). Observations from the located buoy in Liaodong Bay indicate that waves are great affected by sea ice. When the buoy locates in a freezing region, the observed mean significant wave heights (mean significant periods) are 0.2 m (9 s), indicating a 54% reduction (98% increase) compared to the measurements without sea ice. The existence of sea ice may also lead the peak wave direction differ from the dominant wind direction. On the perspective of numeric modeling, the error of simulated wave heights can be reduced by 33% via adding ice-wave terms compared to the model without ice terms. By comparing two wind input terms (Komen and ST6), this paper finds that the simulations match the observations well and the error is comparable. Based on observations of buoys, the results rich the acknowledgements of people in the wave features in Bohai Sea during the freezing winter.
2026, 48(2): 40-57.
doi: 10.12284/hyxb20260016
Abstract:
Shallow-buried gas hydrates are distributed along the continental slope margin of the northern South China Sea. These hydrates are characterized by shallow burial depths and thin overburden layers, rendering them sensitive to changes in seabed temperature and pressure and prone to dissociation. Focusing on internal solitary waves, internal tides, and seasonal bottom-water temperature variations in the northern South China Sea, this study employs a one-dimensional heat conduction model to simulate their effects on shallow subsurface hydrate dissociation and conducts a parameter sensitivity analysis. Results indicate that temperature-pressure perturbations induced by a single internal solitary wave propagate less than a few centimeters into the sediments, falling short of reaching the top of the Hydrate Occurrence Zone (HOZ) located approximately 0.078 m below the seabed, and are thus unlikely to trigger dissociation. In contrast, an internal-tide-induced temperature increase of 1.72℃ lasting 18 hours transfers heat to the HOZ top within 60 d, potentially leading to the dissociation of approximately 4 cm of hydrate. Seasonal bottom-water warming with an amplitude of 1.76℃ persisting for five months drives the dissociation front downward continuously over one year, resulting in a cumulative dissociation thickness of up to 14 cm. This significant impact demonstrates that the effect of sustained warming is substantially stronger than that of transient perturbations. Furthermore, parameter sensitivity analysis reveals that temperature amplitude and effective thermal diffusivity jointly control the propagation depth of thermal perturbations and the dissociation rate. The initial distribution characteristics of hydrates also significantly influence the dissociation process; specifically, the geothermal gradient, methane flux, and permeability determine the positions of the HOZ upper and lower boundaries, whereas porosity regulates the initial saturation and dissociation sensitivity. This study provides a critical basis for evaluating and predicting the stability of shallow subsurface hydrates and the associated risks of methane release.
Shallow-buried gas hydrates are distributed along the continental slope margin of the northern South China Sea. These hydrates are characterized by shallow burial depths and thin overburden layers, rendering them sensitive to changes in seabed temperature and pressure and prone to dissociation. Focusing on internal solitary waves, internal tides, and seasonal bottom-water temperature variations in the northern South China Sea, this study employs a one-dimensional heat conduction model to simulate their effects on shallow subsurface hydrate dissociation and conducts a parameter sensitivity analysis. Results indicate that temperature-pressure perturbations induced by a single internal solitary wave propagate less than a few centimeters into the sediments, falling short of reaching the top of the Hydrate Occurrence Zone (HOZ) located approximately 0.078 m below the seabed, and are thus unlikely to trigger dissociation. In contrast, an internal-tide-induced temperature increase of 1.72℃ lasting 18 hours transfers heat to the HOZ top within 60 d, potentially leading to the dissociation of approximately 4 cm of hydrate. Seasonal bottom-water warming with an amplitude of 1.76℃ persisting for five months drives the dissociation front downward continuously over one year, resulting in a cumulative dissociation thickness of up to 14 cm. This significant impact demonstrates that the effect of sustained warming is substantially stronger than that of transient perturbations. Furthermore, parameter sensitivity analysis reveals that temperature amplitude and effective thermal diffusivity jointly control the propagation depth of thermal perturbations and the dissociation rate. The initial distribution characteristics of hydrates also significantly influence the dissociation process; specifically, the geothermal gradient, methane flux, and permeability determine the positions of the HOZ upper and lower boundaries, whereas porosity regulates the initial saturation and dissociation sensitivity. This study provides a critical basis for evaluating and predicting the stability of shallow subsurface hydrates and the associated risks of methane release.
2026, 48(2): 58-69.
doi: 10.12284/hyxb20260004
Abstract:
To investigate the differences in wave attenuation characteristics among rigid, flexible, and rigid-flexible composite vegetation under regular waves, a series of physical model tests were conducted in a laboratory flume. The wave attenuation effects of these three vegetation types were quantitatively analyzed, and the relationships between the drag coefficient (CD) and Reynolds number (Re), Keulegan-Carpenter number (KC), and Ursell number (Ur) were determined. Results show that all three configurations induce a progressive along-flume reduction in wave height. Increasing incident wave period or vegetation submergence ratio consistently weakens wave dissipation for all vegetation types. The response to wave height differs by configuration: dissipation by rigid vegetation increases markedly and continuously with wave height, whereas flexible vegetation exhibits a nonlinear behavior, strengthening at first and then weakening as wave height further increases. The rigid-flexible combined configuration integrates these advantages and also shows enhanced dissipation with increasing wave height. Moreover, CD for the three vegetation types can be represented using a unified theoretical expression; the primary distinction among configurations is the value of the influence factor γ, which accounts for the effect of vegetation swaying on wave-height attenuation. Statistically significant dependencies of CD on Re, KC, and Ur are observed and can be parameterized by a unified empirical formulation. These results provide a theoretical basis and design reference for optimizing vegetation configurations in coastal ecological protection and restoration engineering.
To investigate the differences in wave attenuation characteristics among rigid, flexible, and rigid-flexible composite vegetation under regular waves, a series of physical model tests were conducted in a laboratory flume. The wave attenuation effects of these three vegetation types were quantitatively analyzed, and the relationships between the drag coefficient (CD) and Reynolds number (Re), Keulegan-Carpenter number (KC), and Ursell number (Ur) were determined. Results show that all three configurations induce a progressive along-flume reduction in wave height. Increasing incident wave period or vegetation submergence ratio consistently weakens wave dissipation for all vegetation types. The response to wave height differs by configuration: dissipation by rigid vegetation increases markedly and continuously with wave height, whereas flexible vegetation exhibits a nonlinear behavior, strengthening at first and then weakening as wave height further increases. The rigid-flexible combined configuration integrates these advantages and also shows enhanced dissipation with increasing wave height. Moreover, CD for the three vegetation types can be represented using a unified theoretical expression; the primary distinction among configurations is the value of the influence factor γ, which accounts for the effect of vegetation swaying on wave-height attenuation. Statistically significant dependencies of CD on Re, KC, and Ur are observed and can be parameterized by a unified empirical formulation. These results provide a theoretical basis and design reference for optimizing vegetation configurations in coastal ecological protection and restoration engineering.
2026, 48(2): 70-78.
doi: 10.12284/hyxb20260014
Abstract:
Settling velocity is a key parameter in the dynamic characteristics of fine-grained cohesive sediments, holding significant importance for understanding the movement patterns of fine sediments and predicting the evolution of scour and fill in port channels. Due to their small particle size, large specific surface area, and tendency for flocculation between particles, the settling velocity of fine-grained cohesive sediments is influenced by multiple factors, with salinity and sediment concentration exerting particularly significant effects. Using in situ sediment samples collected from the Jiaxing Port channel, 42 sets of hydrostatic settling velocity tests were conducted in a sedimentation tank. These tests covered a salinity range of 0–15‰ and a sediment concentration range of 1–20 kg/m3, examining the combined effects of varying salinity and sediment concentration. The results indicate that when salinity is below 7–9‰, settling velocity increases gradually with rising salinity; beyond this range, settling velocity gradually decreased and stabilised with further salinity increases. For sediment concentrations below 8–10 kg/m3, velocity increased with concentration; above this threshold, velocity progressively decreased. Furthermore, compared to the influence of individual factors, salinity and sediment concentration exhibit synergistic effects, with their combined impact exerting a greater influence on sedimentation velocity. A comparative analysis was conducted on the effects of salinity and sediment concentration on sedimentation velocity under varying conditions. A formula for the hydrostatic sedimentation velocity of fine-grained sediments under different salinity and sediment concentration conditions was established through fitting, and validated against previous research findings. These results may provide relevant reference for studies on sediment transport patterns within the Jiaxing Port channel.
Settling velocity is a key parameter in the dynamic characteristics of fine-grained cohesive sediments, holding significant importance for understanding the movement patterns of fine sediments and predicting the evolution of scour and fill in port channels. Due to their small particle size, large specific surface area, and tendency for flocculation between particles, the settling velocity of fine-grained cohesive sediments is influenced by multiple factors, with salinity and sediment concentration exerting particularly significant effects. Using in situ sediment samples collected from the Jiaxing Port channel, 42 sets of hydrostatic settling velocity tests were conducted in a sedimentation tank. These tests covered a salinity range of 0–15‰ and a sediment concentration range of 1–20 kg/m3, examining the combined effects of varying salinity and sediment concentration. The results indicate that when salinity is below 7–9‰, settling velocity increases gradually with rising salinity; beyond this range, settling velocity gradually decreased and stabilised with further salinity increases. For sediment concentrations below 8–10 kg/m3, velocity increased with concentration; above this threshold, velocity progressively decreased. Furthermore, compared to the influence of individual factors, salinity and sediment concentration exhibit synergistic effects, with their combined impact exerting a greater influence on sedimentation velocity. A comparative analysis was conducted on the effects of salinity and sediment concentration on sedimentation velocity under varying conditions. A formula for the hydrostatic sedimentation velocity of fine-grained sediments under different salinity and sediment concentration conditions was established through fitting, and validated against previous research findings. These results may provide relevant reference for studies on sediment transport patterns within the Jiaxing Port channel.
2026, 48(2): 95-113.
doi: 10.12284/hyxb20260018
Abstract:
Constructing continuous spatiotemporal sequences of sea ice is a prerequisite for achieving more accurate, timely, and high-resolution sea ice predictions in the Bohai Sea. To address the inherent limitations of visible light and passive microwave data in sea ice monitoring, this paper proposes a technical approach based on multi-source synergy and super-resolution fusion. First, the DT-ASI algorithm is optimized and local tie points for the Bohai Sea are established to obtain time-series AMSR data at 6.25 km resolution. Subsequently, a sub-pixel convolutional neural network (Pixel Shuffle) is employed for super-resolution reconstruction, identifying the multi-stage Pixel Shuffle strategy as optimal. This approach reduces the mean absolute error by 8.79% and increases the correlation coefficient by 0.19. By integrating the super-resolution AMSR results with MODIS data, a highly continuous spatiotemporal sequence at 1 km resolution from 2002 to 2025 is constructed, with ice coverage during the ice season rising from less than 28.31% to over 95.86%. The dataset reveals preliminary trends of sea ice area reduction, a shortened ice season, and enhanced interannual variability over the past decade. During the 2024–2025 ice season, the Bohai Sea exhibited a distinctive cyclic pattern of “developing-almost completely melting-redeveloping”. This study, through a synergistic and fusion-based approach, overcomes the limitations of single data sources and provides a spatiotemporally continuous data foundation for refined sea ice monitoring and prediction in the Bohai Sea.
Constructing continuous spatiotemporal sequences of sea ice is a prerequisite for achieving more accurate, timely, and high-resolution sea ice predictions in the Bohai Sea. To address the inherent limitations of visible light and passive microwave data in sea ice monitoring, this paper proposes a technical approach based on multi-source synergy and super-resolution fusion. First, the DT-ASI algorithm is optimized and local tie points for the Bohai Sea are established to obtain time-series AMSR data at 6.25 km resolution. Subsequently, a sub-pixel convolutional neural network (Pixel Shuffle) is employed for super-resolution reconstruction, identifying the multi-stage Pixel Shuffle strategy as optimal. This approach reduces the mean absolute error by 8.79% and increases the correlation coefficient by 0.19. By integrating the super-resolution AMSR results with MODIS data, a highly continuous spatiotemporal sequence at 1 km resolution from 2002 to 2025 is constructed, with ice coverage during the ice season rising from less than 28.31% to over 95.86%. The dataset reveals preliminary trends of sea ice area reduction, a shortened ice season, and enhanced interannual variability over the past decade. During the 2024–2025 ice season, the Bohai Sea exhibited a distinctive cyclic pattern of “developing-almost completely melting-redeveloping”. This study, through a synergistic and fusion-based approach, overcomes the limitations of single data sources and provides a spatiotemporally continuous data foundation for refined sea ice monitoring and prediction in the Bohai Sea.
2026, 48(2): 114-130.
doi: 10.12284/hyxb20260012
Abstract:
The Arctic is a climate-sensitive region where Arctic Amplification is influenced by aerosol radiative forcing. Aerosol Optical Depth (AOD) as key parameter characterizing the extinction properties of atmospheric aerosols, plays a critical role in understanding the influence of aerosols on environmental and climate systems. Satellite remote sensing provides an important means of deriving AOD at global and regional scales, but existing satellite products still suffer from substantial data gaps due to retrieval limitations and the complex Arctic surface environment. The Bayesian Maximum Entropy (BME) method is commonly used for AOD data fusion, yet the traditional BME approach, which employs least squares to model covariance, struggles to effectively handle the complexity and non-stationarity of high-dimensional parameter spaces. Based on AOD products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging Spectro Radiometer (MISR), this study introduces a Particle Swarm Optimization (PSO) algorithm with global search capability to improve the covariance modeling process, resulting in a PSO-BME fusion algorithm that enhances the stability and accuracy of data integration. The results demonstrate that the PSO-BME method effectively integrates MODIS and MISR AOD data and successfully fills data gaps. In regions covered by both sources, the fused AOD achieves an RMSE of 0.055, an EE of 78%, an MAE of 0.04, and a correlation coefficient of 0.7, while maintaining acceptable accuracy in unobserved areas. The annual spatial coverage increased from 15.45% (MODIS) and 1.45% (MISR) to 32.7%. Spatiotemporal distribution analysis shows that the fusion product significantly improves spatial continuity and more accurately reflects overall AOD variations. Furthermore, the spatiotemporal evolution patterns reveal that aerosol distribution in the Arctic is influenced by both local meteorological conditions and cross-border transport of pollutants from mid- and low-latitudes.
The Arctic is a climate-sensitive region where Arctic Amplification is influenced by aerosol radiative forcing. Aerosol Optical Depth (AOD) as key parameter characterizing the extinction properties of atmospheric aerosols, plays a critical role in understanding the influence of aerosols on environmental and climate systems. Satellite remote sensing provides an important means of deriving AOD at global and regional scales, but existing satellite products still suffer from substantial data gaps due to retrieval limitations and the complex Arctic surface environment. The Bayesian Maximum Entropy (BME) method is commonly used for AOD data fusion, yet the traditional BME approach, which employs least squares to model covariance, struggles to effectively handle the complexity and non-stationarity of high-dimensional parameter spaces. Based on AOD products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging Spectro Radiometer (MISR), this study introduces a Particle Swarm Optimization (PSO) algorithm with global search capability to improve the covariance modeling process, resulting in a PSO-BME fusion algorithm that enhances the stability and accuracy of data integration. The results demonstrate that the PSO-BME method effectively integrates MODIS and MISR AOD data and successfully fills data gaps. In regions covered by both sources, the fused AOD achieves an RMSE of 0.055, an EE of 78%, an MAE of 0.04, and a correlation coefficient of 0.7, while maintaining acceptable accuracy in unobserved areas. The annual spatial coverage increased from 15.45% (MODIS) and 1.45% (MISR) to 32.7%. Spatiotemporal distribution analysis shows that the fusion product significantly improves spatial continuity and more accurately reflects overall AOD variations. Furthermore, the spatiotemporal evolution patterns reveal that aerosol distribution in the Arctic is influenced by both local meteorological conditions and cross-border transport of pollutants from mid- and low-latitudes.
2026, 48(2): 131-143.
doi: 10.12284/hyxb20260006
Abstract:
This study is based on sea surface temperature (SST) data from MODIS and AMSR2 satellite observations. Three machine learning models—backpropagation neural network (BPNN), random forest (RF), and convolutional neural network (CNN)—were constructed to conduct research on SST data fusion technology. In terms of model input design, two differentiated schemes are proposed: the basic scheme includes only latitude, longitude, and raw SST data, while the enhanced scheme introduces a time parameter, resulting in six fusion schemes—BP_without_time, BP_with_time, RF_without_time, RF_with_time, CNN_without_time, and CNN_with_time. Experimental test results show that among the three machine learning models, CNN demonstrates the most outstanding performance, while the RF model performs relatively weakly. In comparative tests of the three models, the enhanced schemes incorporating time parameters significantly outperform the basic schemes without time parameters. Validation results based on 2023–2024 buoy measurement data indicate that the accuracy of the fused SST data is slightly lower than that of AMSR2_SST, but shows a significant improvement compared to MODIS_SST. The monthly coverage of the fused data has been significantly improved compared to the original data. The minimum coverage for 2023–2024 increased from 19.79% of MODIS and 32.10% of AMSR2 to over 49.56%. Additionally, the high-resolution fused results can capture more detailed temperature distribution characteristics, providing richer spatial details compared to the 10 km resolution AMSR2 data.
This study is based on sea surface temperature (SST) data from MODIS and AMSR2 satellite observations. Three machine learning models—backpropagation neural network (BPNN), random forest (RF), and convolutional neural network (CNN)—were constructed to conduct research on SST data fusion technology. In terms of model input design, two differentiated schemes are proposed: the basic scheme includes only latitude, longitude, and raw SST data, while the enhanced scheme introduces a time parameter, resulting in six fusion schemes—BP_without_time, BP_with_time, RF_without_time, RF_with_time, CNN_without_time, and CNN_with_time. Experimental test results show that among the three machine learning models, CNN demonstrates the most outstanding performance, while the RF model performs relatively weakly. In comparative tests of the three models, the enhanced schemes incorporating time parameters significantly outperform the basic schemes without time parameters. Validation results based on 2023–2024 buoy measurement data indicate that the accuracy of the fused SST data is slightly lower than that of AMSR2_SST, but shows a significant improvement compared to MODIS_SST. The monthly coverage of the fused data has been significantly improved compared to the original data. The minimum coverage for 2023–2024 increased from 19.79% of MODIS and 32.10% of AMSR2 to over 49.56%. Additionally, the high-resolution fused results can capture more detailed temperature distribution characteristics, providing richer spatial details compared to the 10 km resolution AMSR2 data.
Most DownloadedMORE>
- Increased influences of the SST along the Kuroshio in previous winter on the summer precipitation in northeastern China
- The satellite remotely-sensed analysis of the temporal and spatial variability of chlorophyll a concentration in the northern South China Sea
- Observation of the seasonal evolution of DO, chlorophyll a maximum phenomena and nutrient accumulating in the southern Huanghai (Yellow) Sea Cold Water Mass area
- Quantitative research on earthquake-generated tsunami hazards based on the numerical simulations in Bohai Sea
Email alert
RSS