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.

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.

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.

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.

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.

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.

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.

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.

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.

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.