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.