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- Abstract：Coral reefs are among the most important ecosystems in the ocean, and achieving fine-scale geomorphic classification is essential for ecological conservation and resource management. However, the complexity, diversity, and stratified nature of reef geomorphic structures, together with heterogeneity arising from variations in water depth, continue to challenge conventional classification approaches. To address these limitations, this study introduces FCRS-Mamba, a fine-scale coral reef geomorphic classification model designed around an omnidirectional selective scanning strategy. The model incorporates an eight-direction Omnidirectional Selective Scan Module (OSSM) as its central component to effectively extract spatial features from high-resolution reef remote sensing imagery across multiple directions. Classification experiments were conducted on Antelope Reef and North Reef using imagery from the Beijing-3A (BJ-3A) and GF-2 satellites. FCRS-Mamba achieved an mIoU of 81.49% for fifteen geomorphic categories on Antelope Reef and 77.43% for nine categories on North Reef. Compared with existing approaches, it improved the average mIoU by 7.24% and 10.95% on Antelope Reef and North Reef, respectively. With its high classification accuracy, the model provides reliable data for coral reef ecological monitoring and marine resource management, thereby supporting ecological restoration planning, protected area delineation, and the advancement of sustainable marine ecosystem development.Keywords：coral reef;geomorphic classification;remote sensing;state space model (SSM);semantic segmentation1|0|0
Updated：2026-08-17 - Abstract：The Japan Sea is a semi-enclosed marginal sea characterized by complex hydrodynamics and prominent seasonal variability in oceanic fronts and currents. While physical dynamics are known to influence marine ecosystems, the specific spatiotemporal dependence of chlorophyll a (Chl a) on frontal activities and other environmental factors in this region remains quantitatively under-explored. This study utilized satellite-derived sea surface temperature (SST) and Chl-a data to detect fronts using the gradient method and investigated their relationships using empirical orthogonal function (EOF) and correlation analyses. The results revealed distinct seasonal patterns, with the subpolar frontal zone exhibiting a phase reversal in frontal activity compared to the coastal shelf zone. A significant positive correlation between frontal probability (FP) and Chl a was identified in the central and southern basins (35°N–40°N), indicating that frontal dynamics are a primary driver of phytoplankton growth in this region, likely through nutrient supply via vertical circulation. In contrast, wind forcing and surface currents were identified as the dominant factors regulating Chl-a variability in the northern and coastal regions. Furthermore, these regional dynamics were found to be significantly modulated by the North Pacific index on interannual scales. These findings provide a comprehensive quantitative assessment of the physical-biological coupling in the Japan Sea, highlighting the spatially varying roles of fronts and atmospheric forcing in sustaining marine productivity.Keywords：frontal activity;seasonal variability;chlorophyll a;Japan Sea;wind1|0|0Updated：2026-08-13
- Abstract：Cyanobacterial blooms and aquatic vegetation exhibit similar spectral characteristics, which limits the discriminative capability of traditional spectral index-based methods. Moreover, existing deep learning models still suffer from omission and misclassification errors in fragmented boundary regions. This study proposes a semantic segmentation network, termed global-local multi-scale feature extraction network (GLMFENet), which is designed to jointly exploit global and local multi-scale features. Based on an encoder-decoder architecture, GLMFENet incorporates a global feature extraction module to model long-range semantic dependencies, together with a spatial attention-guided local multi-scale feature extraction module to enhance fine-grained discriminability. By synergistically integrating global contextual information with local structural features, the proposed network enables accurate differentiation between cyanobacterial blooms and aquatic vegetation. A dataset comprising 467 Sentinel-2 MSI images collected from multiple lakes across China was established for model training and validation. GLMFENet achieved a mean IoU (mIoU) of 84.6%, a mean F1-score of 91.3%, and a Kappa coefficient of 86.4% on the test set, outperforming widely adopted deep learning models such as DeepLabV3+, SegFormer, and Swin-UNet. The proposed method improves the mIoU by 10.7–19.6 percentage points compared with traditional spectral index-based methods, leading to more accurate and reliable extraction of cyanobacterial blooms and aquatic vegetation.Keywords：cyanobacterial bloom;aquatic vegetation;remote sensing;deep learning1|1|0Updated：2026-08-13
- Abstract：Muddy tidal flats (hereafter referred to as mudflats) dominate China’s coastal tidal wetlands. A comprehensive assessment of their carbon stock characteristics is thus essential for refining the understanding of China’s marine carbon sink capacity. In this study, sediment core sampling was conducted to systematically analyze sedimentary organic carbon (SOC) content, grain-size parameters, clay mineral composition, and carbon stock characteristics of mudflat sediments from different bays in Zhejiang Province. The results indicate that muddy sediments predominate in all three studied bays. The semi-enclosed Yanpu Bay (YP Bay), with stable hydrodynamics and small-river input, has significantly higher SOC content (0.63%±0.04%) than the high-energy Hangzhou Bay (HZ Bay) (0.55%±0.07%, large-river input) and the open Aiwan Bay (AW Bay) (0.36%±0.07%, no river input). Within individual bays, hydrodynamic conditions varied little across tidal zones, and no statistically significant differences in SOC content were detected. Nevertheless, SOC levels were generally higher in the high-tidal zone than in the middle-tidal and low-tidal zones. Analyses of total organic carbon to total nitrogen ratios (C/N) and stable carbon isotopes (δ13C) suggest that SOC in all three bays originates from mixed marine and terrestrial sources. Terrestrial organic matter contributes more prominently in HZ Bay and AW Bay due to the influence of Changjiang (Yangtze) River runoff, whereas YP Bay is dominated by marine-derived organic matter. By integrating data from mudflats along the Chinese coast, this study further reveals that carbon stock ranges from 18.2 to 141.5 Mg C/ha, with a total carbon storage of approximately 51.9 Tg C. The SOC stock of mudflats exhibits a “high-medium-high” spatial distribution pattern from north to south, where climate, riverine transport, and sedimentary environments are likely the primary factors driving this variation.Keywords：mudflat;sedimentary organic carbon (SOC);SOC stock;hydrodynamic condition2|1|0Updated：2026-08-06
- Abstract：The chlorophyll-a (Chl-a) concentration is a core indicator for assessing the health of marine ecosystems. With single-photon-sensitive detection capability, satellite-borne lidar technology can penetrate the sea surface to obtain subsurface optical signals in polar nights, overcoming the constraints of passive remote sensing. In this study, the backward scattering coefficient of particulate matter (bbp) was inverted based on the lidar equation, and a trinomial fitting model was developed to convert bbp(532) to Chl a using the Biogeochemical-Argo (BGC-Argo) measured data in the Norwegian Sea. The retrieval accuracy was verified using corresponding BGC-Argo buoy measurements and Moderate Resolution Imaging Spectroradiometer (MODIS) water color data. Four Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) orbital photon counting lidar tracks data (2020–2024) of the Norwegian Sea were selected to retrieve the spatial and temporal distribution characteristics of the vertical Chl-a profile. Horizontally, high Chl-a concentration (up to >2 mg/m3 owing to warm-warm convergence) was observed at the eastern edge and in the central sea, followed by at turbid nearshore waters at low latitudes, and low concentrations (<0.5 mg/m3) were observed in the open sea. Vertically, significant stratification was observed in the depth range of 3–14 m. We verified the feasibility of ICESat-2 to invert the vertical profiles of Chl a under complex sea conditions at high latitudes, and filled the observation gap of passive remote sensing in polar nights.Keywords：Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) lidar;chlorophyll a;Norwegian Sea;backscattering coefficient1|2|0Updated：2026-08-06
- Abstract：The Qingshui River Basin is the largest tributary entering the Huanghe (Yellow) River within Ningxia of China, contributing about 49% of the sediment load from this section. In this basin, the suspended sediment concentration (SSC) exhibits a short-term variability with values rising by orders of magnitude within hours. This phenomenon is primarily driven by the precipitation-induced runoff, which induces the surface soil erosion, sediment transport and the local bed erosion. Such rapid fluctuations of SSC are difficult to be captured using manual sampling or satellite remote sensing methods. To address this issue, a classification-based inversion model was developed in this paper using the ground-based in-situ hyperspectral data from the Wangtuan station beside Qingshui River between March and September 2024, covering both normal and flood periods. At the beginning, we utilized the K-means clustering algorithm to classify these water spectral characteristics into three types. These water types exhibited different spectral characteristics in the position and number of their reflectance peaks. Subsequently we built empirical and machine learning models for each water type to retrieve SSC. By comparison to Global models, the classification-based inversion models substantially improved inversion performance: a linear empirical model performed the best for low SSC water type (R2=0.92), while support vector regression and random forest achieved an R2 of 0.92 under medium and high SSC conditions, respectively. Therefore, this study we conducted in this paper achieved a high inversion accuracy of SSC especially for medium and high SSC water types. Our results revealed that the ‘classify first, then model’ method is reliable for estimating SSC of high-sediment water bodies in the Qingshui River Basin, and enhances the feasibility of ground-based in-situ hyperspectral monitoring technology for refined Huanghe River watershed management.Keywords：Qingshui River Basin;Huanghe (Yellow) River;suspended sediment concentration (SSC);in-situ hyperspectral;K-means clustering;inversion model3|2|0Updated：2026-08-04
- Abstract：This study reports the discovery of Vittina lambda sp. nov., a new neritid species from Hainan Island, South China Sea, alongside three new records: Nerita antiquata, Clithon eudeli, and C. peguense. V. lambda sp. nov., distinguished by unique Λ-shaped shell color patterns and radular morphology (narrower central teeth, sharper marginal teeth), was historically misidentified within V. coromandeliana populations. Integrative taxonomy combining mitochondrial COI sequences (revealing>5% K2P divergence), Bayesian Poisson Tree Processes (bPTP) analysis, and morphology confirmed its cryptic status. For now, three new records are found in Guangdong, Guangxi, and Hainan only in China. Among them, Clithon eudeli was previously reported from its type locality in Vietnam only and has a unique and easily recognizable appearance in the genus Clithon. These findings highlight the South China Sea as a biodiversity hotspot and underscore the efficacy of molecular-morphological approaches in resolving complex neritid taxonomy.Keywords：Vittina lambda sp. nov.;cryptic species;COI barcoding;integrative taxonomy;marine gastropods5|3|0Updated：2026-08-04
- Abstract：High resolution satellite optical sensors provide detailed sea surface textures and wave patterns, offering significant potential for retrieving sea surface wave parameters. The Coastal Zone Imager (CZI) onboard China’s ocean color satellite Haiyang-1E (HY-1E) provides 20-m multispectral and 5-m panchromatic imagery with a 3-d revisit cycle. Its distinctive optical design, which separates transmission and reflection channels onto different focal planes, introduces specific along-track channel time lags. In this study, the viewing geometry and inter-channel time lags of the CZI sensor were systematically evaluated. A dedicated workflow for wave parameter retrieval was developed and its feasibility was validated using 4 in-situ measurements and 69 reanalysis matchups. There is a statistically linear relationship between CZI-derived and reanalysis wave direction (RMSE=20.50°, Bias=0.24°) and period (RMSE=1.68 s, Bias=0.10 s). The specific requirements and limitations of CZI for resolving the 180° directional ambiguity were analyzed in detail. Furthermore, the proposed method was applied to generate the original coastal regional wave products from HY-1E. The uncertainty in comparison with ERA5 products and the potential of wind speed estimation were additionally discussed. Overall, these findings demonstrate that the HY-1E CZI sensor can effectively retrieve sea surface wave parameters, providing a valuable data source for monitoring coastal and marine dynamical environments.Keywords：sea surface wave;optical remote sensing;Haiyang-1E (HY-1E) Coastal Zone Imager (CZI);wave parameter;time lag5|4|0Updated：2026-07-29
- Abstract：Phytoplankton primary productivity (PP) is a key indicator of carbon fixation and ecosystem functioning in inland waters. Using high-resolution Sentinel-2 imagery, this study developed a regionalized Vertically Generalized Production Model (VGPM) optimized for highly turbid, shallow lakes to estimate modeled PP dynamics in Taihu Lake from 2019 to 2025. The multi-year mean daily PP in Taihu Lake ranged from 820.68 to 1 527.11 mg C/(m²·d), with a lake-wide average of ~1 232.28 mg C/(m²·d). Spatially, modeled PP decreased from the bays to the central basin and from west to east, with Zhushan and Meiliang bays maintaining the highest productivity (up to ~1 667.93 mg C/(m²·d)). At the same time, the eastern region dominated by aquatic vegetation showed lower values (<950 mg C/(m2·d)). Temporally, modeled PP exhibited a strong seasonal cycle, with higher values in summer and autumn and lower values in winter and spring, forming a bimodal pattern with peaks in May and September (>1 800 mg C/(m²·d)). Moderate water temperature and sufficient light availability promoted productivity, whereas turbidity (light attenuation) limited phytoplankton growth. By integrating corrections for phytoplankton vertical distribution, algal bloom classification, and the removal of aquatic vegetation signals, the model’s performance was greatly improved. The Google Earth Engine (GEE)-based workflow enabled efficient long-term modeled PP monitoring and provides a transferable framework for quantifying carbon cycling, guiding eutrophic lake restoration, and assessing climate responses.Keywords：Sentinel-2;Taihu Lake;primary productivity (PP);Vertically Generalized Production Model (VGPM) model3|4|0Updated：2026-07-29
- Abstract：The South China Sea (SCS), due to its unique geographical location and marine environment, harbors a diverse and representative coral reef ecosystem. This study examines the trophic structure of major marine organisms within the coral reef ecosystem of the southern SCS through stable isotope analysis (δ13C and δ15N). The analysis is based on field samples collected during the spring of 2023 and 2024. The δ13C values of consumers spanned from -21.72‰ to -3.26‰, and the δ15N values ranged from 2.42‰ to 10.97‰, which indicates a well-defined and continuous trophic spectrum. The trophic levels (TLs) of fish varied from 1.80 to 3.35, whereas those of invertebrates ranged from 1.08 to 2.76, suggesting a structured ecosystem in the study area. MixSIAR modeling revealed that macroalgae, plankton, and organic matter on coral surfaces (OMCs) were the predominant basal food sources, supporting five major trophic groups: carnivores, corallivores, planktivores, macroalgae-consuming herbivores and omnivores. Notably, several species that traditionally feed on coral, such as Chaetodon ornatissimus and Heniochus chrysostomus, demonstrated an increased reliance on algal resources, implying a possible change in feeding strategy. Additionally, the diet preference of Acanthaster planci showed a strong reliance on crustose coralline algae (CCA), with juveniles experiencing growth stagnation or adults suffering from long-term starvation being the predominant individuals. This highlights the importance of food-source monitoring for understanding the population dynamics of A. planci. This study provides basic data and novel perspectives for coral reef conservation and sustainable management in the coral reef ecosystems of the western Pacific Ocean.Keywords：coral reef;stable isotope;food source;trophic level (TL)4|5|0Updated：2026-07-29
- Abstract：The Chinese shrimp (Fenneropenaeus chinensis) is one of the most valuable cultured penaeid species. However, overfishing and inbreeding depression have caused marked declines in both wild stocks and aquaculture production. As the main edible portion, muscle tissue plays a decisive role in growth performance, one of the most critical economic traits in shrimp breeding. Myogenic differentiation factor D (MyoD) is a key positive regulator of myogenesis and skeletal muscle growth in vertebrates; however, knowledge of its role in crustacean muscle development remains limited. In this study, we identified and characterized the MyoD homolog from Chinese shrimp (FcMyoD) and investigated its potential function in muscle growth. The full-length FcMyoD cDNA is 1 484 bp in length and encodes a 210-amino-acid protein. Compared with MyoD from Litopenaeus vannamei (LvMyoD), FcMyoD harbors a frameshift mutation that truncates of the C-terminal region. In adult shrimp, FcMyoD expression was highest in muscle tissue, and muscle FcMyoD expression in large individuals was significantly higher than in small individuals. Following 36 d of continuous double-stranded RNA (dsRNA) targeting FcMyoD, the muscle growth rate in the dsRNA group was markedly lower than in the phosphate buffer saline (PBS) group. Histological analysis further revealed reduces muscle fiber diameter and narrower inter-fiber spaces in the dsRNA group. These results suggest that FcMyoD may act as a positive regulator of muscle formation and growth in Chinese shrimp. This study provides important information for the role of MyoD in crustacean myogenesis and muscle growth and a basic insight for future molecular breeding strategies to improve the growth traits in farmed shrimp.Keywords：shrimp;Fenneropenaeus chinensis;MyoD;myogenesis;muscle growth2|5|0Updated：2026-07-27
- Abstract：This study surveyed the Xiaoheishan Island artificial reef area in China’s Bohai Sea (deployed in 2014) through year-round ecological surveys conducted in 2023. Using environmental DNA metabarcoding technology, we systematically studied the ecological restoration effects and underlying mechanisms of the artificial reef area. The results revealed 91 genetically identified fish species in the artificial reef area, compared to 87 species in the control area, indicating that artificial reefs play a positive role in restoring biodiversity. Principal Component Analysis demonstrated significant seasonal and spatial differences in biological distribution between the artificial reef and control areas (P<0.05). Specifically, the artificial reef area is dominated by small demersal rock-associated fishes such as Gobiidae, Scorpaeniformes, Lateolabrax japonicus, and Hexagrammos otakii; in contrast, the control area features predominantly pelagic and soft-bottom species including Liza haematocheila, Engraulis japonicus, Mugil cephalus, Paralichthys olivaceus, and Scomberomorus niphonius. By Canonical Correspondence Analysis, we propose that seasonal migration driven by water temperature and species’ life-history strategies promote habitat partitioning between the artificial reef and control areas, which in turn influences the distribution of dissolved oxygen and NH
- Abstract：Raphidiopsis raciborskii is recognized as a highly invasive cyanobacterium, with increasing reports of its prevalence. Pesticides and heavy metals represent two significant categories of pollutants contributing to water contamination. To investigate the invasion characteristics of cyanobacteria in polluted waters, chlorophyll fluorescence kinetics revealed that high-concentration exposure reduced key fluorescence transient points—O (initial), J and I (intermediate), and P (peak)—compared to the control, whereas the P level was elevated under low-concentration exposure. Fv/Fo and PIABS values rose notably with low cadmium (Cd) exposure but declined with high Cd and high-concentration co-exposure. Values were lower in high-concentration co-exposure than low single Cd exposure, yet higher than high-concentration single Cd exposure. Photosynthetic parameters exhibited an increase at low Cd concentrations but demonstrated a notable decrease at high Cd and combined Cd exposure. Low concentration combined exposure significantly enhanced superoxide dismutase (SOD) and catalase (CAT) activities, with no significant change observed in malondialdehyde (MDA) content. In contrast, high concentration combined exposure resulted in decreased SOD and CAT activities, a significant increase in MDA content, and reduced glutathione (GSH) levels across the exposure groups. Microstructural and ultrastructural alterations indicate oxidative stress. Transcriptome analysis revealed that high co-exposure down-regulated key photosynthetic genes, and the presence of glyphosate (Gly) mitigated Cd toxicity during co-exposure. These findings contribute to a deeper understanding of the adaptive mechanisms of invasive cyanobacteria to pesticides and heavy metals, providing theoretical support for the management of invasive cyanobacterial species.Keywords：Raphidiopsis raciborskii;glyphosate;cadmium;compound pollution;chlorophyll fluorescence;transcriptome sequencing;oxidative stress5|4|0Updated：2026-07-27
- Abstract：Among diverse Artemia strains, Xizang Artemia exhibits higher baseline HUFA content, containing a rich eicosapentaenoic acid (EPA) and a minor amount of docosahexaenoic acid (DHA). Nevertheless, the content of DHA in Xizang Artemia remains insufficient for marine aquatic organisms, particularly marine fish. Moreover, the enrichment efficiency and metabolism of highly unsaturated fatty acid (HUFA) in Xizang Artemia are not yet fully elucidated. This research investigated the survival and HUFA metabolic rates of Artemia tibetiana during the enrichment process with DHA-rich emulsified fish oil and in the subsequent 6, 12, 24, 48, and 72 h starvation at 14, 19, and 24 °C, in comparison with Artemia franciscana. The findings indicated that A. tibetiana achieved the highest DHA content of 9.78 mg/g dry weight (DW) after 36-h enrichment, whereas A. franciscana reached its peak DHA content of 31.40 mg/g DW after 24-h enrichment. After 72-h starvation, the DHA content in both species declined rapidly, with a metabolic rate exceeding 70%. Both species exhibited relatively lower metabolic rates for EPA and arachidonic acid (ARA), less than 50% and 38% respectively. After 72-h starvation, the DHA metabolic rates of A. tibetiana were significantly lower than those of A. franciscana at the three temperatures (P<0.05), demonstrating species-specific characteristics. Two-factor analysis of variance revealed that the metabolic rates of ARA, EPA, and DHA increased significantly with the increased starvation temperature and the prolonged starvation time (P<0.001). In conclusion, the starting enrichment time and enrichment duration should be determined according to the Artemia species/strains in order to guarantee the enrichment efficiency. Additionally, the remaining HUFA-enriched Artemia should be stored at a lower temperature to minimize the metabolic consumption of HUFA and ensure a higher survival rate. This study offers a reference for studying the HUFA metabolic pattern of Artemia and provides guidance for the application of Artemia enrichment and the preservation of HUFA-enriched Artemia in hatcheries.Keywords：Artemia tibetiana;enrichment;starvation;highly unsaturated fatty acid (HUFA) metabolism5|4|0Updated：2026-07-20
- Abstract：River-estuary continua are hotspots for nitrogen transformations; however, whether N2O and N2 transformations vary in parallel in response to environmental variations along these continua remains poorly understood. This study compared spatial variations and environmental controls of excess N2O (ΔN2O) and excess N2 (ΔN2) concentrations along an urban river-estuary continuum, combining multi-season measurements with metagenomic analysis of nitrogen-cycling functional genes. Both ΔN2O (-0.61–188.78 nmol/L) and ΔN2 (-127.38–155.66 μmol/L) peaked in the river-estuary transition zone, coinciding with high nutrient inputs and potentially prolonged water residence time. However, we found a clear decoupling between these two gases, evidenced by their insignificant correlation and spatially offset peaks. Machine learning analysis indicated their divergent environmental drivers; nitrate was more important for ΔN2O, while temperature and dissolved organic carbon (DOC) were more critical for ΔN2. DOC was positively correlated with the genetic potential ratio of N2 production to fixation, and temperature was negatively linked to the genetic potential for N2O production relative to reduction. Furthermore, upon entering the estuary, ΔN2 concentrations declined more sharply than ΔN2O, leading to widespread N2 undersaturation (i.e., ΔN2<0). This undersaturation is consistent with reduced denitrification, reflected by decreased denitrifier abundance due to high salinity and sulfide levels, alongside persistent N2 fixation. The slower decrease in ΔN2O is consistent with reduced N2O consumption and elevated ammonia-oxidizing archaea to ammonia-oxidizing bacteria ratio. Our findings highlight distinct biogeochemical controls on N2O and N2 dynamics, providing insights for improving nitrogen removal and mitigating N2O emissions in aquatic ecosystems.Keywords：greenhouse gas;river-estuary continuum;metagenomics;nitrogen fixation;nitrogen removal7|4|0Updated：2026-07-20
- Abstract：Particulate organic carbon (POC) is critical to the coastal carbon cycle of the Yellow Sea (YS), a typical marginal sea, but its interannual-to-multiyear variability and driving mechanisms remain unclear due to the limitations of traditional linear or single-factor analyses. To address this gap, we employed model-derived surface POC data from 2003 to 2023 and wavelet coherence analysis to investigate POC variability and regulating mechanisms at multi-scales in the YS. The dominant spatiotemporal mode of surface POC exhibits pronounced seasonality, a consistent coastal-offshore gradient (higher in coastal waters), and a spring maximum, which is regulated by the seasonal alternation controlled by coastal production or input and offshore stratification or ventilation. Wavelet analysis reveals distinct subregional differences in driving mechanisms of POC variability at interannual-to-multiyear scales. Colored dissolved organic matter (CDOM) is the optimal single driver in most subregions, while sea surface temperature (SST) dominates in the Southern Yellow Sea Cold Water Mass (SYSCWM). Specific optimal multi-factor combinations include CDOM+sea surface wind speed (SSW) in the Northern Yellow Sea Cold Water Mass (NYSCWM), chlorophyll a (Chl a)+Photosynthetically Available Radiation (PAR)+partial pressure of carbon dioxide (pCO2) in the SYSCWM, CDOM+Chl a+suspended matter (SPM) in the Jiangsu Shoal (JSS) and CDOM+sea surface salinity (SSS) in the Changjiang River estuary (CRE). These findings clarify the subregional heterogeneity of POC variability and its driving mechanisms in the YS at interannual-to-multiyear scales, and provide a robust scientific basis for accurate regional carbon budget assessments and the optimization of marine numerical models.Keywords：Yellow Sea;particulate organic carbon (POC);wavelet analysis;spatiotemporal variability;interannual-to-multiyear6|5|0Updated：2026-07-20
- Abstract：The Zonag Lake basin is situated in the hinterlands of the Qinghai-Xizang Plateau (QXP) and serves as a renowned calving ground for Tibetan antelopes. Zonag Lake is also a typical large inland lake on the QXP. Over the past three decades, the lake areas within the Zonag Lake basin have generally shown an expanding trend. However, different lakes therein have exhibited varying trend over time. Between 1988 and 1995, Zonag Lake, Kusai Lake, Haidingnor Lake, and Salt Lake all experienced shrinkage. After the 2011 breach of Zonag Lake, it continued to shrink, the downstream lakes, such as Kusai Lake, Haidingnor Lake, and Salt Lake consistently expanded. After the 2019 implementation of the Salt Lake drainage project, the water levels began to decline in 2020. The Zonag Lake basin has experienced an average annual precipitation of 308.5 mm over the past six decades, with a general upward trend in rainfall amounting to an average increase rate of 15.1%. The overall temperature within the basin has also been increasing, with a warming rate of 0.35 °C/10 a. This trend has become notably more pronounced since the beginning of the 21st century. Collectively, surface runoff (41.5%±2.3%) and lake precipitation (27.0%±1.5%) accounted for most of the total lake inflow, thus identifying atmospheric precipitation as the primary driver of lake expansion in the Zonag Lake basin. The meltwater from glaciers and permafrost was the secondary contributor, responsible for 24.0%±1.3% of the inflow.Keywords：Zonag Lake area;expansion;precipitation;temperature6|4|0Updated：2026-07-15
- Abstract：Taihu Lake is one of the most severely eutrophic large lakes worldwide, characterized by a complex ecosystem where algal blooms and aquatic vegetation coexist, and it serves as a critical regional water source. Identifying the channels through which algal blooms invade vegetated areas and understanding their underlying mechanisms is essential for effective lake management. In this study, multi-source remote-sensing data were used to extract the spatial patterns of algal bloom frequency and aquatic vegetation over the past 22 years. We detected the major encroachment routes of algal blooms into vegetated zones and revealed the long-term interaction mechanisms between algae and vegetation. Algal blooms were persistently concentrated in the western and northern bays, exhibiting an overall fluctuating upward trend. Aquatic vegetation was mainly distributed in four eastern bays, remained relatively stable before 2015, declined markedly in 2016 due to dredging and shoreline modifications, and then gradually recovered. A stable negative response relationship was observed between algal blooms and aquatic vegetation, jointly regulated by seasonal climate and nutrient structure. High temperatures and intense precipitation in summer facilitated bloom expansion, whereas low temperatures in winter favored vegetation recovery. Meanwhile, lower TN to TP ratios suppressed vegetation growth and enhanced bloom encroachment during summer. Three primary channels of algal bloom encroachment into vegetated areas were identified: the northern shoreline of Gonghu Bay, the surroundings of Dongshan Island, and the southern marginal zone. Among them, the water intake in northern Gonghu Bay represents the most vulnerable zone requiring priority control. Although bloom risk is relatively low for the central and southern water intakes, maintaining the existing hydrodynamic regime and vegetation structure remains essential to prevent vegetation degradation, and enhanced monitoring is needed to identify in situ bloom occurrences within vegetated regions.Keywords：algal bloom;aquatic vegetation;Taihu Lake;remote sensing6|4|0Updated：2026-07-15
- Abstract：Coastal and estuarine wetlands support high biodiversity and provide essential ecosystem services. As flagship blue-carbon ecosystems, mangroves and adjacent tidal flats store disproportionate carbon, making robust biodiversity monitoring foundational to blue-carbon conservation and management. However, the challenges associated with conventional fish surveys limit effective management. In this study, environmental DNA (eDNA) metabarcoding and centipede sampling were conducted at four stations within the Zhanjiang Gaoqiao mangrove-mudflat system to compare their performance in assessing community composition, co-occurrence structure, and network stability. Using both methods, 102 species (80 genera, 46 families) were identified. PERMANOVA and PCoA analyses indicated that species composition differed significantly between methods (P0.01), while the mean detection rates did not differ (P0.05). Species accumulation and rarefaction-extrapolation curves showed that sampling sufficiency had nearly reached saturation for both methods. In the co-occurrence networks, the key species were Glossogobius giuris in the centipede net network and Periophthalmus modestus in the eDNA network. The eDNA network was substantially larger, comprising 188 significant pairs compared to 16 in the centipede net network. Habitat weighting of key species differed by method: the eDNA dataset was more enriched in benthopelagic and pelagic-neritic guilds and had higher weights in estuary/brackish, coastal/nearshore, and freshwater categories. In contrast, the centipede net dataset was more demersal, targeting sandy/muddy bottoms and mangrove habitats. Stability analyses revealed higher robustness, lower vulnerability, and greater positive and negative cohesion for the eDNA network (P0.001), indicating stronger signals of coordination and turnover. Overall, eDNA metabarcoding and centipede net sampling provided complementary insights into species composition, network structure, and stability, offering a more comprehensive understanding of fish diversity. These results establish a blue-carbon-relevant biodiversity baseline for a typical estuarine mangrove district and support integrated molecular-conventional monitoring to guide habitat protection and restoration across mangroves and tidal flats.Keywords：environmental DNA (eDNA);centipede net sampling;mudflat;fish diversity;ecological network;community stability6|3|0Updated：2026-07-13
- Abstract：A 12-week experimental study was conducted to explore the influence of temperature and eyestalk ablation on the spawning rate and ovarian development of mud crab Scylla paramamosain. The study comprised four experimental treatments: 25 °C (coded 25), 25 °C with eyestalk ablation (25EA), 30 °C (30), and 30 °C with eyestalk ablation (30EA). Results indicate that neither temperature nor eyestalk ablation significantly influenced the survival rate, HSI, or GSI (P>0.05). Nevertheless, eyestalk ablation significantly enhanced the spawning rate and oocyte diameter, with the 30EA group showing the greatest increase (P<0.05). Hormonal analysis of the hemolymph showed that eyestalk ablation significantly decreased gonad-inhibiting hormone (GIH) levels while elevating gonad-stimulating hormone (GTH) levels (P<0.05). Under 30 °C with eyestalk ablation, significant elevations in triglyceride (TG) levels were observed in the hemolymph, ovary, and hepatopancreas (P<0.05). Furthermore, eyestalk ablation significantly elevated vitellogenin (VTG) contents in both hepatopancreas and hemolymph. Besides, eyestalk ablation induced a significant upregulation of lipid synthesis (fas, 6pgd) and lipid transport (fatp 4) genes in the hepatopancreas (P<0.05). Similarly, elevated temperature significantly induced the upregulation of lipid synthesis (fas, 6pgd), lipid catabolism (hsl, aco), and lipid transport (fatp 4, fabp 3) genes in the ovary (P<0.05). Additionally, eyestalk ablation considerably enhanced the expression of fatp 4 in the ovary (P<0.05). Therefore, eyestalk ablation enhanced lipid accumulation in the ovary by reducing GIH levels, leading to increased oocyte diameter and ultimately enhancing the spawning rate of the crabs. In conclusion, eyestalk ablation significantly improved the spawning rate of S. paramamosain under temperatures of 25–30 °C. These findings provide theoretical support for optimizing artificial breeding strategies and improving seed production efficiency in mud crab aquaculture.Keywords：temperature;eyestalk ablation;ovarian development;spawning;mud crab6|4|0Updated：2026-07-09
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