There is a significant disconnection between the richness of data and the effectiveness of decision-making in current marine observation practices. This study argues that the root cause lies in the “ontological” bias and “methodological” mismatch in the logic that guides observation design. We first examine the “uniformity assumption” that views the ocean as a spatially homogeneous and temporally gradual system. Based on the “land-sea heterogeneity isomorphism” framework, we demonstrate that the ocean is essentially a heterogeneous landscape dominated by key dynamic processes, characterized by “resource-rich areas”, “risk-concentrated areas”, and “pulsatile events” that drive their changes. These local, transient, and nonlinear threshold processes often dominate the function and evolution of coastal and estuarine ecosystems. Traditional “mission-oriented” or “undifferentiated census” observations, which ignore this essence, lead to systematic omissions of core processes and key risk signals. Based on this, we propose a fundamental shift in the marine science observation paradigm: from “routine observation-driven alone” to “a combination of routine observation and scientific questions/management goal-driven”. We construct a logical framework of “scientific questions/management goals-key processes-observation requirements”, and systematically expound on three methodological breakthroughs to address the “fluid medium” characteristics of the ocean: building a “dynamic adaptive perception network” to replace fixed grids, establishing “full-chain process analysis” to replace isolated hypothesis testing, and achieving an intelligent closed loop of “real-time assimilation and predictive decision-making”. This study aims to provide a comprehensive theoretical pathway from ontological cognition to methodological practice to build the next generation of “precise, efficient, and applicable” marine science observation systems.

The global ocean is currently facing a severe challenge of “cryptic ecosystem degradation”, characterized by subtle but progressive declines in ecosystem integrity. Conventional water quality monitoring often indicates regulatory “compliance”, while underlying processes such as food web disruption, loss of keystone species, and functional degradation of ecosystems continue largely undetected. This management paradox arises from traditional assessment paradigms that emphasize physicochemical conditions while overlooking biological structure and ecosystem functionality. This study proposes a target-driven framework for marine ecosystem health assessment, aiming to facilitate a paradigm shift in environmental management from “comprehensive census” approaches to “precision-based diagnostic” strategies. Departing from fixed indicator frameworks, the proposed system introduces a “three-level funnel” generation logic: (i) identification of core ecological issues based on specific management objectives, (ii) selection of key biological components and associated indicators, and (iii) design of an optimal spatiotemporal observation strategy. Guided by the principles of usability, effectiveness and adequacy, the framework is supported by an integrated “space-air-sea-intelligence” technological network and enables the transformation of observational data into actionable decision-making knowledge through an intelligent diagnostic engine. Case studies demonstrate that the framework can dynamically generate customized assessment schemes tailored to diverse management objectives, including “overall health assessment, ” “aquaculture carrying capacity evaluation”, and “disaster early warning”. Among these, the classical triad-based Index of Biotic Integrity (Z/F/B-IBI), encompassing “zooplankton-fish-benthos” represents the optimal scheme generated by the framework for achieving “regional-scale ecosystem health assessment”. Overall, the proposed system aims to maximize management efficiency while minimizing observational costs, thereby providing a dynamically adaptable, “precision medicine-like” solution for ecosystem-based marine management.

Health assessments of marine ecosystems rely heavily on the real-time diagnosis of biological status and functions. However, the “cognitive lag” of traditional biological observation (i.e., the long period from sample collection to species identification and data output, which makes it difficult to reflect rapid changes in the ecosystem promptly) has become the core bottleneck for the operational application of health assessment. This article systematically analyzes the historical roots and contemporary predicaments of this bottleneck, pointing out that it stems from “technological path dependence”, “verification logic paradox”, and “observation network absence”. To break through this predicament, this article proposes a new biological observation paradigm that will enable the shift from “lagging evidence collection to real-time diagnosis”. This paradigm includes three core dimensions: at the cognitive level, it will survey the “complete species set”, track the “functional fingerprints”, and identify key ecological function signals; at the technical level, it will construct a “real-time perception-quality control verification” collaborative technical system, integrate cutting-edge measures such as environmental DNA, in situ imaging, and intelligent acoustics, and innovatively iterate the verification mode; at the network level, through the development of modular intelligent biological sensing modules, it will embed biological sensing capabilities in the global observation network in an “plug-and-play” manner, achieving automated and continuous perception of biological signals. This paradigm shift aims to upgrade biological observations to a forward-looking information infrastructure that supports real-time health diagnoses and early warnings regarding marine ecosystems.

Under the stresses of climate change and anthropogenic activities, marine ecosystems are undergoing unprecedented changes. Accurately assessing the ecological quality status of marine ecosystems and their spatiotemporal variation characteristics is an urgent scientific challenge. Within marine ecological quality assessment frameworks, macrobenthos serve as critical evaluation criteria due to their distinctive physiological and ecological traits. However, current assessment indicators based on macrobenthic communities are numerous yet singular, lacking a comprehensive integrated evaluation system. To address this gap, the present study proposes a multi-dimensional, multi-indicator evaluation framework constructed from an ecological perspective that integrates both community structure and function. This framework comprises three primary categories and nine secondary indices: (1) biotic indices (M-AMBI and BENTIX index); (2) community structure (Shannon-Wiener diversity index, species richness, taxonomic composition, abundance, and biomass); and (3) functional attributes and stability (functional diversity and stability). Weight assignments were allocated according to indicator importance to calculate the macrobenthic community ecological quality index (MCEQI) for benthic ecological status assessment. Application of MCEQI to analyze the macrobenthic community ecological status in Jiaozhou Bay demonstrated that this index exhibits higher accuracy than single-indicator approaches, providing a more comprehensive reflection of community ecological quality.

The health status assessment of marine benthic ecosystems, as an important basis for maintaining the ecological balance of the oceans, relies on the long-term dynamic monitoring of benthic communities. In this study, we systematically reviewed the history and current applications of ecological assessment indices developed based on benthic organisms, including the perspectives of future fields in marine ecosystem health assessment. Traditional biological indices—including biodiversity indices (Shannon-Wiener index, Pielou index, etc.), functional group analyses (feeding evenness index), and indices (AMBI, M-AMBI, BENTIX index, etc.) based on the proportion of pollution-tolerant/sensitive species have advanced ecosystem health assessment by quantifying the responses of community structure to environmental stressors and facilitating the shift from qualitative to quantitative assessments. Nevertheless, traditional methods are limited by cumbersome procedures for morphological characterization, the limitations of single indicators, and regional differences in applicability. In recent years, environmental DNA (eDNA) technology has made up for the shortcomings of traditional methods by rapidly obtaining biodiversity information through high-throughput sequencing, and has derived novel indices such as gAMBI, which validates its complementarity with morphological methods. Integration of Artificial Intelligence (AI) techniques such as machine learning algorithms (Random Forests, Convolutional Neural Networks, and so on) with statistical analysis has improved the ability of ecosystem assessment models to resolve nonlinear relationships and multiple stressors. Meanwhile, automatic and intelligent image recognition technology offers the possibility of accurate and rapid identification of macrofauna and their monitoring. Future research shall integrate multidimensional data and interdisciplinary techniques to construct a more universal and dynamically responsive assessment system to cope with the potential impacts of global climate change and human activities on marine ecosystems.

Marine microorganisms, characterized by their immense biomass, rapid environmental response, and crucial ecological functions, serve as sensitive indicators for assessing the health of marine ecosystems. This article provides a systematic review of recent advances in marine ecological monitoring and health assessment based on microbial communities. First, we discussed the key characteristics of marine microorganisms as bioindicators, such as their high sensitivity to environmental stress and their functional redundancy in maintaining ecosystem processes. Case studies are presented to highlight the successful use of microbial monitoring to address climate change, pollution events, and ecological disasters. Next, we reviewed the evolution of marine microbial monitoring technologies, spanning from traditional cultivation methods to modern techniques such as high-throughput sequencing and Raman spectroscopy. We also compared the advantages and limitations of these approaches in practical applications. Finally, in response to challenges such as insufficient data standardization and the lack of quantitative assessment metrics, we proposed a systematic framework for future development. This framework emphasizes the need for end-to-end standardization from sampling to data analysis, the creation of intelligent diagnostic models that integrate multi-dimensional “Raman spectroscopy-genetic-environmental” information with the establishment of a national-scale specialized monitoring network. This review aims to provide theoretical supports and technical pathways for the development of a next-generation, high-resolution, real-time microbial-based marine ecological health assessment system.

Dissolved oxygen (DO) is fundamental to maintaining the balance and stability of marine ecosystems. Under the combined influence of climate warming and intensified human activities, hypoxia in coastal waters worldwide is increasing in severity and spatial extent, making deoxygenation a major threat to coastal ecosystem health. As a typical semi-enclosed sea, the Bohai Sea is subject to multiple environmental pressures, including ocean warming, eutrophication, and rapid socio-economic development. In recent years, varying degrees of hypoxia have been reported across multiple subregions of the Bohai Sea, with hypoxic centers primarily located northeast of the Yellow River estuary and southeast of Qinhuangdao (occurring ≥3 times). This study reviews domestic and international research on hypoxia in the Bohai Sea, characterizes the spatial distribution patterns of summer hypoxia over the past two decades, and summarizes the dominant controlling processes. It further outlines the long-term development trends and their influencing factors in the Bohai Sea and proposes key directions for future research on hypoxia in the region. The study aims to provide a scientific basis and decision-making support for ecological health assessment and marine resource management in the region.

Changes in the seasonal cycle of phytoplankton are important indicators of coastal ecosystem responses to climate change and human activities. Based on historical observations from Jiaozhou Bay in 2005, 2010, 2015, and 2020, this study examined long-term variations in the seasonal cycle of phytoplankton biomass and their environmental drivers. The results showed that the seasonal distribution pattern of phytoplankton biomass in Jiaozhou Bay changed markedly during 2005~2020, shifting from a bimodal pattern with winter and summer peaks to a predominantly unimodal pattern with a summer-autumn peak. Winter peak values of net-collected phytoplankton abundance and chlorophyll a concentration decreased substantially, from 103.62×10⁶ cells/m³ and 15.29 μg/L in 2005 to 12.81×10⁶ cells/m³ and 1.13 μg/L in 2020, respectively. Community structure analysis indicated that diatoms consistently dominated the phytoplankton assemblage and that variation in diatom abundance was the primary driver of the observed shift in the seasonal cycle of phytoplankton biomass. In contrast, dinoflagellate abundance declined markedly after peaking in 2010. Correlation analyses suggested that increasing winter water temperature and decreasing phosphate concentration were the main factors underlying the attenuation and eventual disappearance of the winter phytoplankton biomass peak. These findings reveal the long-term evolution of phytoplankton seasonal structure in Jiaozhou Bay under the combined influence of climate change and nutrient adjustment, and offer scientific support for coastal ecosystem management.

As primary producers, phytoplankton constitute a vital component of marine ecosystems, and their community structure largely determines the stability of these ecosystems. Previous studies on phytoplankton community structure in Laizhou Bay have relied primarily on short-term observations or data from one or two sampling cruises. There remains a scarcity of multi-year continuous survey data, and the temporal evolution of phytoplankton community structure has rarely been systematically analyzed. Based on survey data from 2016 to 2023 summer in Laizhou Bay, we investigated the interannual variations of phytoplankton and conducted correlation analyses between phytoplankton communities and environmental factors. Results show that a total of 106 species from 3 phyla were identified over the 8-year period, predominantly diatoms, followed by dinoflagellates. Significant interannual variations in species composition were observed, and the lowest diversity (48 species) occurred in 2019 and the highest (68 species) in 2020. Phytoplankton cell abundance ranged from 39.1×10⁴ cells/m³ to 2 687.3×10⁴ cells/m³, peaked in 2017 and reached the minimum levels in 2021. In the planar distribution, the phytoplankton cell abundance, the nearshore waters of estuaries such as the Yellow River estuary and Xiaoqing River estuary are higher than that of the central part of the bay. Dominant species included Pseudo-nitzschia pungens, Chaetoceros curvisetus, Skeletonema costatum, and Cerataulina pelagica. Correlation analysis revealed that nitrate-nitrogen was the primary environmental factor on phytoplankton abundance. The overall upward trend in the interannual variations of diversity index (H'), richness index (d), and evenness index (J') indicate that phytoplankton community structure tended to improve. This study contributed to clarifying the evolutionary trend and influencing factors of phytoplankton in Laizhou Bay, and provided a scientific foundation for decision-making in marine ecological environment protection of the bay area.

Tracking and understanding the historical variations in phytoplankton community composition in Sanggou Bay hold significant implications for eutrophication management, environmental quality regulation in aquaculture waters, and provides basic materials and scientific basis for carrying capacity. Based on previous investigations of phytoplankton in Sanggou Bay, we summerized four decades of historical data to analyze the long-term variation trends in community structure and identify the key drivers on the current state. Results show that chlorophyll a (chl a) in surface water increased from inner to outer bay in spring but decreased in autumn and winter, showing notable compositional shifts. Nano-phytoplankton dominated chl a in spring (53%) and summer (71%), while micro-phytoplankton prevailed in autumn (52%) and winter (71%). A total of 57 phytoplankton species (including varieties and forms) from 33 genera were identified, mainly diatoms (40 species) and dinoflagellates (14 species), and diatoms remained the dominant group. Cell abundance of phytoplankton was the highest in summer (276×10³ cells/L) and lowest in winter (6.4×10³ cells/L). Species diversity indices had no significant seasonal variation. Over the past four decades, chl a dynamics in Sanggou Bay exhibited two distinct phases: a peak in the 1990s followed by a decline after the 2000s due to the shifts in aquaculture practices, stabilizing post-2000 until 2024. Prolonged large-scale raft aquaculture resulted in the decreases in the number of phytoplankton and diatom species and a notable transition toward smaller-sized diatom dominance. The type and density of culture species and culture modes may be the key factors on the community structure and seasonal variation of phytoplankton.

To investigate the occurrence characteristics and ecological risks of microplastics in zooplankton communities of Jiaozhou Bay, a seasonal survey was conducted in February, May, August, and November that quantified the abundance and characteristics of microplastics within zooplankton. The results showed that the microplastics abundance within individual zooplankton over the four months was 0.30, 0.20, 0.21, and 0.20 items/individual, respectively. The community-level microplastic abundance was 0.19, 5.61, 7.36, and 0.52 items/m³, respectively. The microplastic abundance within zooplankton communities in May and August was significantly higher than that in February and November. The average storage of microplastics by zooplankton communities in Jiaozhou Bay over the four months was 3.19×10¹⁰ items, with the highest value observed in August. Fibers were the predominant shape of microplastics in zooplankton, accounting for 89% of the total, with no significant differences observed among months. Most microplastics were smaller than 500 μm, with an average length of (491±454) μm; microplastics detected in August exhibited significantly greater lengths (P<0.05). The predominant chemical compositions were polyester fibers and cellophane, accounting for 37% and 19% of the total, respectively, with no significant differences observed among months. The mean values of the microplastic pollution load index (PLI) and polymer hazard index (PHI) for zooplankton in Jiaozhou Bay over four months were 3.49±2.94 and 4.33±1.31, respectively, both corresponding to the lowest risk category(PLI<10, PHI<10). The mean bioaccumulation factor (BAF) was 55.59±56.84, indicating no significant bioaccumulation potential of microplastics in zooplankton communities (BAF<1000). Temperature, suspended particulate matter concentration, and chlorophyll a concentration were identified as the primary factors influencing the risk assessment outcomes.

In recent decades, harmful algal blooms (HABs), particularly red tide events caused by dinoflagellates, have occurred frequently in China’s coastal waters, threatening marine ecological security, economic and social development, and human health. Considering the diversity and abundance of dinoflagellate cysts in sediments from 267 stations in China’s four major seas during 2014-2018, this study integrated historical HAB records and literature on the distribution and abundance of vegetative cells in water bodies. By applying the typical red tide risk assessment method, risk maps for red tide outbreaks of 26 target dinoflagellate species in China’s seas were compiled, and the assessment results were interpreted and discussed. The target dinoflagellates exhibited varying degrees of red tide risk values. Among them, 11 species (Scrippsiella acuminata, Scrippsiella donghaiensis, Gonyaulax spinifera, Alexandrium catenella, Levanderina fissa, Pseudocochlodinium profundisulcus, Alexandrium pacificum, Alexandrium minutum, Gonyaulax polygramma, Akashiwo sanguinea,and Prorocentrum donghaiense) showed high-risk characteristics at certain monitoring stations, whereas 21 species displayed moderately high-risk characteristics. Additionally, the risk values of different dinoflagellates varied across China’s four major seas and presented distinct regional features. For example, the red tide risk values of Pr. donghaiense and Ps. profundisulcus in the East and South China Seas, respectively, were significantly higher than those in other sea areas. Correlation analysis showed that 37 pairs and 5 pairs of dinoflagellate species showed significantly positive and negative correlations in their risk values, respectively, reflecting certain synergistic or competitive relationships in their ecological niches. This study provides a scientific basis for preventing and controlling red tides in China’s coastal waters, and a reference for similar studies in other marine areas worldwide, and for the prediction and forecasting of red tides.

It is essential for ecosystem-based fisheries management to investigate the spatiotemporal distribution characteristics and environmental driving mechanisms of the key zooplankton species (Acetes chinensis) during its total allowable catch project period. We applied DBSCAN (density-based spatial clustering of application with noise) algorithm to process summer 2021 Beidou VMS (vessel monitoring system) data to extract information of the fishing locations associated with A. chinensis catches. We then combined these locations with remotely sensed marine environmental data and investigated the distribution patterns and key environmental drivers of A. chinensis habitats in the Haizhou Bay during summer in MaxEnt model using geographic detector method. Results indicate that suitable habitats for A. chinensis were concentrated in mainly three regions: 120°01′~120°17′E and 34°43′~34°47′N; 119°48′~119°58′E and 34°34′~34°42′N; and 119°58′~120°12′E and 34°25′~34°33′N. Although A. chinensis is a small, planktonic shrimp, its spatiotemporal distribution was not solely determined by surface residual currents, and the dominant factors influencing its distribution varied in different fishing periods. In the entire fishing season, the water depth, phytoplankton abundance, sea surface temperature, and sea surface salinity emerged as critical drivers of the habitat distribution. The optimal conditions in Haizhou Bay were determined as: water depth of 3.5~11.0 m, phytoplankton abundance of 9.5~17.0 mmol/m³ or 27.5~30.0 mmol/m³, sea surface temperature of 24.2~25.5 ℃, and sea surface salinity of 21.0‰~23.6‰. During the peak catch period, surface residual currents became an additional important factor on the distribution of the shrimp habitats. Future research shall focus on developing a comprehensive observation indicator system for this key species and conducting further assessments to ensure the sustainable production of A. chinensis resources.

The Yellow Sea Cold Water Mass (YSCWM), acting as a distinct physical barrier, forms a stable, low-temperature, high-salinity environment; however, the mechanisms by which it influences the distribution patterns of benthic microeukaryotes and the associated environmental drivers remain poorly understood. In this study, we systematically characterized microeukaryotic communities in sediment samples collected from two stations in the Bohai Sea and fifteen stations located within and surrounding the YSCWM, using environmental DNA (eDNA) sequencing with the 18S rDNA gene as the molecular marker. The results show that Dinoflagellata constituted the dominant taxonomic group both within and outside the YSCWM; however, the microeukaryotic community structures of the two regions differed significantly (ANOSIM: R=0.576 3, P=0.001). Compared with regions outside the YSCWM, communities within the YSCWM exhibited lower species richness (median: 1 529 vs. 1 672) but displayed a more complex co-occurrence network structure (4 062 vs. 3 138 edges), suggesting greater potential ecosystem stability. Deterministic processes, particularly heterogeneous selection, predominantly govern community assembly, in which water depth exerts a stronger influence on communities outside the OYSCWM communities, whereas temperature and median sediment grain size play more critical roles in shaping communities within the YSCWM. These findings demonstrate that the YSCWM plays a critical role in structuring sedimentary microeukaryote communities and highlights environmental DNA (eDNA) technology as an effective approach for elucidating marine microbial biogeographic patterns and evaluating ecosystem structure.

In the autumn of 2022, a red tide species Eucampia zodiacus bloomed in the nearshore water of Rushan, northern Yellow Sea, lasting for more than 40 days. This nearshore area is the main aquaculture domains for oyster Crassostrea gigas in China, and the important bait for oysters is phytoplankton. It has been shown that there are large seasonal variations of phytoplankton in this area, but there are fewer studies related to phytoplankton feeding by oysters, especially the effect of red tide outbreaks on their feeding selectivity. By analyzing the phytoplankton in water samples and oyster stomach contents, two complete blooming and recession periods of red tide were identified, with the second one having the longest duration (about 18 days) and the highest abundance (2.23×10⁶ cells/L). At the peak of the red tide, the algae abundance in the stomach contents of oysters (2.11×10⁴ cells/ind.) was significantly higher than that during the recession period of the red tide (1.44×10³ cells/ind.). During the blooming period of E. zodiacus, oysters tended to randomly feed on this dominant species, and preferred to feed on 5 diatom genera such as Nitzschia and Coscinodiscus, etc., during the recession period of the red tide, the oyster's feeding selectivity index decreased for most of phytoplankton species, preferring only Pleurosigma sp. and shifting to avoid its previously preferred genera Navicula and Paralia sulcata. The study indicated that the oyster may have limited control over the outbreaks of the E. zodiacus because it is not a preferred bait for oysters, and the oysters’ feeding selectivity changed significantly before and after the outbreaks of E. zodiacus, which suggests that its outbreaks may have affected the subsequent feeding behavior of oysters.

Marine ecosystem health is under severe pressure. Therefore, scientific and effective evaluation indicators for its assessment and early warning are urgently required. Plankton is a sensitive indicator of ecosystem changes and is critical in the marine food web, supporting important ecosystem services such as carbon sequestration and fishery production. Based on survey data of Jiaozhou Bay from 2003 to 2013, this study screened two types of zooplankton functional group indicators closely related to environmental changes: the dry weight biomass of traditional forage zooplankton (large crustaceans, large copepods, and small copepods), and the dry weight biomass proportion of gelatinous zooplankton (jellyfish, chaetognaths, and tunicates). These indicators represent the productivity level and stability of the functional group structure, respectively. According to the range and thresholds of the historical data, a graded evaluation standard was established. By constructing a two-dimensional coordinate plane based on zooplankton functional group indicators, according to the graded evaluation standard, the historical health status of the ecosystems in Jiaozhou Bay was classified into ecosystems with benign and risky development. These were further subdivided into seven types of health status, namely, rich-product, healthy-sustainable, benign-development, gelatinous-development, gelatinization, high-risk, and resource-scarce. This study provides a typical case using zooplankton functional groups as assessment indicators to establish an assessment system for offshore ecosystem health.

To investigate the characteristics of the macrobenthic community and its benthic ecological quality in Geligang, a typical intertidal flat in northern Liaodong Bay, 12 stations (including non-harvesting areas, Mactra veneriformis harvesting areas, and Solen grandis harvesting areas) were deployed in the area in June 2024, and macrobenthic fauna and environmental factors were surveyed. Results show that (1) a total of 35 species of macrobenthos were identified, mainly Crustacea (14 species), Mollusca (10 species), and Polychaeta (9 species), of which five species dominated, including Potamocorbula laevis and M. veneriformis; and the community mean abundance and biomass are 163.67 ind./m² and 284.47 g/m² respectively. (2) The cluster analysis and non-metric multidimensional scaling (NMDS) showed that the community similarity between non-harvesting area and M. veneriformis harvesting area was high, while that in the S. grandis harvesting area sits as a separate unit. (3) The Abundance-Biomass Curve (ABC) shows that the macrobenthic community structure in the intertidal flat was stable. The Mantel’s test showed that chlorophyll a and water temperature were important factors on the changes in local macrobenthic community. (4) The benthic ecological quality assessment based on AMBI and M-AMBI indices showed that only a few sites (e.g., No.3) were in moderate or severe disturbance status, and the overall benthic habitat quality was in good condition. The M-AMBI index was better adapted than the single index under the disturbance of mechanized harvesting. This study revealed the benthic ecological status in the intertidal flat, provided a scientific basis for balancing shellfish resource development and habitat protection, and suggested to prioritize the use of the M-AMBI index for long-term monitoring and management assessment.

To understand the impact of rainfall on the functional group characteristics of macrobenthic communities in the shellfish farming area of Xiaoqing River estuary in Laizhou Bay, Bohai Sea, survey data of rainfall were collected in July (pre-rainfall) and August (post-rainfall) 2019 and analyzed. By integrating Shannon-Wiener niche breadth, Pianka niche overlap, and canonical correspondence analysis (CCA), the variation in dominant microbenthic species and their environmental drivers were examined. Results are as follows. (1) Eight dominant species were identified, of which Moerella iridescens and Nephthys oligobranchia were consistently dominant in the two months. (2) Significant shifts in life-form and feeding functional groups were observed: July was dominated by endobenthic-planktivores (mean density 265 ind./m², 71%), while August shifted to carnivores (mean density 103 ind./m², 58%), with the GS/GSB ratio increasing from 0 to 2/3. (3) Dominant species exhibited marked niche breadth variation (0.494~2.945), featuring coexistence of broad-niche species (e.g., Nephthys oligobranchia) and narrow-niche specialists (e.g., Potamocorbula laevis), with weak interspecific competition (60% of species pairs showed a narrow niche overlap value (<0.3). (4) CCA revealed that the salinity (32.7% explained variance, P<0.01) was the primary driver of functional group succession (GS/GSB ratio) and niche differentiation. The stenohaline bivalve Potamocorbula laevis (optimal salinity 22~34) served as a bioindicator for salinity thresholds. This study shows that rainfall-induced environmental changes (salinity, dissolved oxygen, pH, chlorophyll a) critically drive functional group succession and niche partitioning in macrobenthos, providing a scientific basis for conservation and sustainable utilization of benthic resources in the Xiaoqing River estuary.

The Yellow River Estuary as a vital ecological bridge linking freshwater and marine ecosystems, with its ecological health significantly impacted by the Yellow River water and sediment regulation project. To assess the environmental ecological quality of the estuary during this regulation period, data on macrobenthos and bottom water environmental factors were collected on three occasions throughout the 2023 water and sediment regulation phase. Four indices—AMBI, M-AMBI, BOPA, and Shannon-Wiener diversity—were employed to gauge the ecological status of the estuary. To reconcile the discrepancies in evaluation standards among these biological indices, an endeavor was made to establish a comprehensive biological index (CBI) using the entropy weight method. This approach aimed to unify the evaluation criteria across the four indices. Furthermore, the Nemerow Comprehensive Water Quality Evaluation Index (P) was introduced to validate the results. The survey revealed a total of 133 macrobenthos species belonging to five taxa, with polychaetes and mollusks emerging as the dominant groups. Notable shifts were observed in the macrobenthos community structure across the three periods: before, during, and after the water and sediment regulation. During the regulation period, the benthic ecological quality of the Yellow River Estuary was generally classified as “moderate” or “mildly polluted”. Pollution levels intensified at stations nearer to the estuary, indicating poorer ecological quality in these areas. The CBI exhibited a strong correlation with bottom water environmental factors and aligned well with the findings of the comprehensive water quality evaluation index. The evaluation grades for the ecological status at each monitoring station were distinctly stratified, demonstrating that the CBI method, constructed using the entropy weight method for various biological indices, is a viable tool for assessing the environmental ecological quality of the Yellow River Estuary. These research findings offer fresh perspectives for evaluating the environmental ecological quality of this crucial estuary.

To elucidate recent changes in nutrient structure and potential phosphorus limitation in China’s coastal seas, this study analyzed the spatial distribution and interannual variability of dissolved inorganic nitrogen (DIN), phosphate (PO₄^3-), and their molar ratio (N/P) in surface waters of the central Bohai Sea, Yellow Sea, East China Sea, and the Changjiang River Estuary, using cruise data from National Natural Science Foundation of China shared surveys, and compared these with historical observations. The results indicate that in 2015 and 2017, most areas of the central Bohai Sea and Yellow Sea exhibited elevated N/P ratios, generally exceeding the Redfield ratio (16 : 1), reflecting pronounced nutrient imbalance and a tendency toward phosphorus limitation. In most years, the East China Sea also exhibited elevated N/P ratios; however, lower values were observed in parts of the outer shelf and in regions influenced by Kuroshio intrusion, suggesting possible nitrogen limitation in these areas. The Changjiang River Estuary maintained persistently high N/P ratios (>64 : 1), indicating stronger phosphorus limitation compared with other regions. Comparison with historical data revealed that N/P ratios in the central Bohai and Yellow Seas exhibited a long-term pattern of “initial increase followed by decline”, with peak values occurring around 2008 and 2005, respectively, suggesting that both seas have remained in a persistently high N/P state. Overall, nutrient imbalance is widespread in China’s coastal seas, although pronounced interregional and intraregional differences exist, reflecting the combined influence of land-based inputs and regional oceanographic processes. These findings provide a scientific basis for understanding the evolution of nutrient structure and the associated risk of nutrient limitation in China’s coastal seas.

The simulation and prediction of dynamic changes in zooplankton community play a critical role in evaluating the health of bay ecosystems. There remains significant uncertainty in the quantitative prediction of dynamic changes within zooplankton community using classical plankton ecosystem dynamics models. Jiaozhou Bay was used as a representative bay in China’s coastal regions facing multiple pressures from human activities and climate change. Utilizing long-term observation data on zooplankton abundance and environmental factors in Jiaozhou Bay such as temperature, salinity, nutrients, and chlorophyll a concentration from 1997 to 2010, we developed a technical and methodological system for predicting zooplankton abundance in Jiaozhou Bay by applying Empirical Dynamic Modeling approach. Our model achieved an effective prediction with a coefficient of determination (R²) of 0.64, root mean square error (RMSE) of 108.6 and a relative error of 42.5%. After analyzing 15 380 937 potential combinations, we pinpointed temperature and silicate as critical factors influencing the change of zooplankton abundance in Jiaozhou Bay. A deeper look into the research data suggested that the change of zooplankton abundance in Jiaozhou Bay from 1997 to 2010 was a result of interaction between bottom-up control and top-down control in the food web. The quantitative prediction method for changes in zooplankton abundance and the causal identification of driving factors developed in this study exhibited spatial transferability, highlighting their substantial potential as a foundational approach for the future health assessment model of coastal bay ecosystems in China.

The Tianjin coastal zone is an important ecological security barrier for the Beijing-Tianjin-Hebei urban agglomeration. To scientifically assess the evolution of its ecological health, an ecological health evaluation system was constructed for the coastal zone based on the Driving forces-Pressure-State-Impact-Response (DPSIR) model, and environmental monitoring or census data covering 2018~2023, in which 30 indicators were applied. The Analytic Hierarchy Process (AHP) and Entropy Weight Method were used to determine the weight of each indicator, and the health level of the coastal zone was comprehensively evaluated. In addition, the degree of coupling coordination among the sub-systems of DPSIR was ascertained, and the reliability of outcome was determined through a weight sensitivity experiment. Results show that the ecological health level of the coastal zone showed a fluctuating upward trend in general, and the health grade was increased from “relatively unhealthy” to “moderately healthy”. All the sub-systems were in moderately coordinated state, indicating that the health condition of the coastal zone of Tianjin has been improving year by year under the policy of promotion by the government. The region has initially formed a “green growth” model for the marine economy. However, a certain lag existed in ecosystem restoration relative to countermeasures, posing potential ecological disaster risks. The weight sensitivity analysis showed that the evaluation system constructed in this study has high robustness and can objectively reflect the evolution of the ecological health of the coastal zone in Tianjin, providing a scientific basis for refined governance in the coastal zone of Tianjin.