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The Korean Society of Phycology (한국조류학회(藻類))
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Spatiotemporal variations of phytoplankton functional groups and environmental drivers over the past two decades in the Bohai, Yellow and East China Sea

  • Muhsan Ali Kalhoro (Marine College, Shandong University) ;
  • Veeranjaneyulu Chinta (Ningbo Institute of Digital Twin, Eastern Institute of Technology) ;
  • Muhammad Tahir (School of Space Science and Technology, Shandong University) ;
  • Yujie Sheng (Marine College, Shandong University) ;
  • Chunli Liu (Marine College, Shandong University) ;
  • Zhiyuan He (Marine College, Shandong University) ;
  • Zhenlin Liang (Marine College, Shandong University) ;
  • Jun Song (Operational Oceanography Institution, Dalian Ocean University) ;
  • Tony Song (Ningbo Institute of Digital Twin, Eastern Institute of Technology)
  • Received : 2025.09.20
  • Accepted : 2025.11.30
  • Published : 2025.12.15
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Abstract

Phytoplankton, the primary producers of marine ecosystems, play a crucial role in sustaining primary production. This study investigates spatiotemporal variations in phytoplankton functional groups (PFGs) and their environmental drivers across the Bohai, Yellow, and East China Seas (BYECS) from 2003 to 2022. Sea surface temperature exhibited a significant warming trend (sea surface temperature [SST]; τ > 0.48, p < 0.01), increasing from 16.39℃ in 2011 to 17.98℃ in 2021, mean at 17.24 ± 0.39℃ and a breakpoint around 2009. Smaller phytoplankton, including prokaryotes (PROKAR, 27.86%; mean = 1.59 ± 0.96 mg m-3) and pico-phytoplankton (PICO, 28.99%; mean = 1.70 ± 0.95 mg m-3) showed strong negative correlations with SST (r = -0.64 and -0.69) and pronounced declines after 2015. Haptophytes and nanoplankton also decreased significantly (τ < -0.52, p < 0.001) with a breakpoint around 2011. In contrast, larger groups; diatoms (5.28%; mean = 0.41 ± 0.15 mg m-3) and micro-phytoplankton (MICRO, 8.44%; mean = 0.60 ± 0.19 mg m-3) were positively associated with SST (r = 0.38-0.49), indicating enhanced resilience under warming conditions. Total chlorophyll-a (TChl-a; 3.38 ± 3.74 mg m-3) declined significantly (τ < -0.57, p < 0.001) and showed a strong negative correlation with SST (r = -0.64), indicating reduced biomass after 2011. PICO and MICRO contributed 30-45% and 20-35% of TChl-a, respectively. Nutrients showed no significant long-term trends. Overall, findings reveal a warming-driven shift from small to larger phytoplankton groups, with decrease in TChl-a reflecting structural and productivity changes in the BYECS ecosystem. These findings are BYECS-specific and should be interpreted with caution due to uncertainties in remote-sensing PFG products and the potential influence of riverine inputs, stratification, and mixing.

Keywords

Acknowledgement

Present work is supported by the Shandong University, Marine College, Weihai (202367800206), and Ningbo Institute of Digital Twin present research is funded by corresponding author (Prof. Dr. Tony Song). Authors acknowledge the cooperation of Science and Technology Plan of Liaoning Province (2024JH2/102400061); Dalian Science and Technology Innovation Fund (2024JJ11PT007; Cai Yu); Dalian Science and Technology Program for Innovation Talents of Dalian (2022RJ06); Liaoning Province Education Department Scientific research platform construction project (LJ232410158056); Basic scientific research funds of Dalian Ocean University (2024JBPTZ001). We also acknowledge Dr. Cai Yu for his continues support throughout this study.

References

  1. Anderson, D. M., Cembella, A. D. & Hallegraeff, G. M. 2012. Progress in understanding harmful algal blooms: paradigm shifts and new technologies for research, monitoring, and management. Annu. Rev. Mar. Sci. 4:143–176. doi.org/10.1146/annurev-marine-120308-081121
  2. Anderson, D. M., Glibert, P. M. & Burkholder, J. M. 2002. Harmful algal blooms and eutrophication: nutrient sources, composition, and consequences. Estuaries 25:704–726. doi.org/10.1007/BF02804901
  3. Aubry, F. B., Cossarini, G., Acri, F., et al. 2012. Plankton communities in the northern Adriatic Sea: patterns and changes over the last 30 years. Estuar. Coast. Shelf Sci. 115:125–137. doi.org/10.1016/j.ecss.2012.03.011
  4. Bai, J. & Perron, P. 2003. Computation and analysis of multiple structural change models. J. Appl. Econ. 18:1–22. doi.org/10.1002/jae.659
  5. Bartlett, M. S. 1950. Tests of significance in factor analysis. Br. J. Stat. Psychol. 3:77–85.
  6. Behrenfeld, M. J., O'Malley, R. T., Siegel, D. A., et al. 2006. Climate-driven trends in contemporary ocean productivity. Nature 444:752–755. doi.org/10.1038/nature05317
  7. Belsley, D. A., Kuh, E. & Welsch, R. E. 1980. Regression diagnostics: identifying influential data and sources of collinearity. Wiley, New York, 300 pp.
  8. Benjamini, Y. & Hochberg, Y. 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Series B 57:289–300. doi.org/10.1111/j.2517-6161.1995.tb02031.x
  9. Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. 2015. Time series analysis: forecasting and control. 5th ed. John Wiley and Sons Inc., Hoboken, NJ, 712 pp.
  10. Brunsdon, C., Fotheringham, A.S. & Charlton, M. E. 1996. Geographically weighted regression: a method for exploring spatial nonstationarity. Geogr. Anal. 28:281–298. doi.org/10.1111/j.1538-4632.1996.tb00936.x
  11. Cattell, R. B. 1966. The Scree test for the number of factors. Multivar. Behav. Res. 1:245–276. doi.org/10.1207/s15327906mbr0102_10
  12. Chen, B., Xu, Z., Zhou, Q., et al. 2010. Long-term changes of phytoplankton community in Xiagu waters of Xiamen, China. Acta Oceanol. Sin. 29:104–114. doi.org/10.1007/s13131-010-0081-4
  13. Chen, C.-T. A. 2009. Chemical and physical fronts in the Bohai, Yellow and East China seas. J. Mar. Syst. 78:394–410. doi.org/10.1016/j.jmarsys.2008.11.016
  14. Chen, C.-T. A. & Wang, S.-L. 1999. Carbon, alkalinity and nutrient budgets on the East China Sea continental shelf. J. Geophys. Res. Oceans 104:20675–20686. doi.org/10.1029/1999jc900055
  15. Chinta, V., Kalhoro, M. A., Liang, Z., Tahir, M., Song, G. & Zhang, W. 2024. Decadal climate variability of chlorophyll-a in response to different oceanic factors in the Western Indian Ocean: the sea of Oman. Clim. Dyn. 62:8675–8690. doi.org/10.1007/s00382-024-07354-4
  16. Chinta, V., Kalhoro, M. A., Tahir, M., Liang, Z. & Song, T. 2025. Impact of tropical cyclone Tej on oceanic environment in the Arabian Peninsula. Front. Mar. Sci. 12:1575203. doi.org/10.3389/fmars.2025.1575203
  17. Cohen, J., Cohen, P., West, S. G. & Aiken, L. S. 2003. Applied multiple regression/correlation analysis for the behavioral sciences. 3rd ed. Lawrence Erlbaum Associate Publishers, Mahwah, NJ, 736 pp.
  18. Field, C. B., Behrenfeld, M. J., Randerson, J. T. & Falkowski, P. 1998. Primary production of the biosphere: integrating terrestrial and oceanic components. Science 281:237–240. doi.org/10.1126/science.281.5374.237
  19. Fotheringham, A. S., Brunsdon, C. & Charlton, M. E. 2002. Geographically weighted regression: the analysis of spatially varying relationships. Wiley, Chichester, 282 pp.
  20. Furuya, K., Hayashi, M., Yabushita, Y. & Ishikawa, A. 2003. Phytoplankton dynamics in the East China Sea in spring and summer as revealed by HPLC-derived pigment signatures. Deep Sea Res. II Top. Stud. Oceanogr. 50:4355–4367. doi.org/10.1016/S0967-0645(02)00460-5
  21. Furuya, K., Kurita, K. & Odate, T. 1996. Distribution of phytoplankton in the East China Sea in the winter of 1993, J. Oceanogr. 52:323–333. doi.org/10.1007/BF02235927
  22. Guo, S., Feng, Y., Wang, L., et al. 2014. Seasonal variation in the phytoplankton community of a continental-shelf sea: the East China Sea. Mar. Ecol. Prog. Ser. 516:103–126. doi.org/10.3354/meps10952
  23. Guo, S., Tian, W., Dai, M., Liu, Z. & Sun, J. 2011. Phytoplankton assemblages in the East China Sea in summer 2009. Adv. Mar. Sci. 29:474–486. doi.org/10.3969/j.issn.1671-6647.2011.04.007
  24. Guo, X. Y., Zhu, X.-H., Long, Y. & Huang, D. J. 2013. Spatial variations in the Kuroshio nutrient transport from the East China Sea to south of Japan. Biogeosciences 10:6403–6417. doi.org/10.5194/bg-10-6403-2013
  25. He, Q., Sun, J., Luan, Q. & Yu, Z. 2009. Phytoplankton in Changjiang estuary and adjacent waters in winter. Mar. Environ. Sci. 28:360–365.
  26. Hoegh-Guldberg, O., Jacob, D., Taylor, M., et al. 2018. Impacts of 1.5°C global warming on natural and human systems. Available from: https://unfccc.int/topics/science/workstreams/cooperation-with-the-ipcc/ipcc-special-reporton-global-warming-of 15-degc. Accessed Mar 12, 2020.
  27. Huang, R., Chen, J., Wang, L. & Lin, Z. 2012. Characteristics, processes, and causes of the spatio-temporal variabilities of the East Asian Monsoon system. Adv. Atmos. Sci. 29:910–942. doi.org/10.1007/s00376-012-2015-x
  28. Huang, T.-H., Chen, C.-T. A., Lee, J., et al. 2019. East China Sea increasingly gains limiting nutrient P from South China Sea. Sci. Rep. 9:5648. doi.org/10.1038/s41598-019-42020-4
  29. Hyndman, R. J. & Athanasopoulos, G. 2021. Forecasting: principles and practice. 3rd ed. OTexts, Melbourne, 442 pp.
  30. Jia, H.-B., Shao, J.-B., Hu, H.-Y., Wang, Y.-M., Wei, N. & Hu, X.-P. 2014. Changes and reason analysis of phytoplankton community structure in the Yangtze Estuary and adjacent sea before and after the impoundment of the Three Gorges Dam. Mar. Sci. Bull. 33:305–314. doi.org/10.11840/j.issn.1001-6392.2014.03.009
  31. Jiang, Z., Chen, J., Zhou, F., et al. 2015. Controlling factors of summer phytoplankton community in the Changjiang (Yangtze River) Estuary and adjacent East China Sea shelf. Cont. Shelf Res. 101:71–84. doi.org/10.1016/j.csr.2015.04.009
  32. Jolliffe, I. T. 2002. Principal component analysis. 2nd ed. Springer, New York, 488 pp.
  33. Jolliffe, I. T. & Cadima, J. 2016. Principal component analysis: a review and recent developments. Philos. Trans. A Math. Phys. Eng. Sci. 374:20150202. doi.org/10.1098/rsta.2015.0202
  34. Kaiser, H. F. 1974. An index of factorial simplicity. Psychometrika 39:31–36. doi.org/10.1007/BF02291575
  35. Kaiser, H. F. & Rice, J. 1974. Little Jiffy, Mark IV. Educ. Psychol. Meas. 34:111–117. doi.org/10.1177/001316447403400115
  36. Kalhoro, M. A., Chinta, V., de Mutsert, K., et al. 2024. Impact of tropical cyclone Biparjoy on oceanic parameters in the Arabian Sea. Mar. Pollut. Bull. 208:117046. doi.org/10.1016/j.marpolbul.2024.117046
  37. Kalhoro, M. A., Chinta, V., Tahir, M., et al. 2025a. Assessing chlorophyll-a variability and its relationship with decadal climate patterns in the Arabian Sea. J. Mar. Sci. Eng. 13:1170. doi.org/10.3390/jmse13061170
  38. Kalhoro, M. A., Chinta, V., Tahir, M., et al. 2025b. Machine learning-based prediction and forecasting of chlorophyll-a in the northern Indian Ocean using satellite data. Ecol. Inform. 92:103482. doi.org/10.1016/j.ecoinf.2025.103482
  39. Kalhoro, M. A., Ye, H., Liu, C., Zhu, L., Liang, Z. & Tang, D. 2025c. Impact of sea surface temperature fronts on the spatial distribution of jellyfish in the northern Arabian sea. Estuar. Coast. Shelf Sci. 312:109033. doi.org/10.1016/j.ecss.2024.109033
  40. Kendall, M. G. 1975. Rank correlation methods. 4th ed. Charles Griffin, London, 260 pp.
  41. Kim, Y., Youn, S.-H., Oh, H. J., et al. 2020. Spatiotemporal variation in phytoplankton community driven by environmental factors in the northern East China Sea. Water 12:2695. doi.org/10.3390/w12102695
  42. Legendre, P. & Legendre, L. 2012. Numerical ecology. 3rd English ed. Elsevier, Amsterdam, 419 pp.
  43. Li, M., Xu, K., Watanabe, M. & Chen, Z. 2007. Long-term variations in dissolved silicate, nitrogen, and phosphorus flux from the Yangtze River into the East China Sea and impacts on estuarine ecosystem. Estuar. Coast. Shelf Sci. 71:3–12. doi.org/10.1016/j.ecss.2006.08.013
  44. Li, Q. P., Dong, Y. & Wang, Y. 2016. Phytoplankton dynamics driven by vertical nutrient fluxes during the spring inter-monsoon period in the northeastern south China sea. Biogeosciences 13:455–466. doi.org/10.5194/bg-13-455-2016
  45. Liu, C., Kang, J., Wang, G. & Sun, W. 2012. Monthly change of nutrients impact on phytoplankton in Kuroshio of East China Sea. Energy Procedia 16:1193–1198. doi.org/10.1016/j.egypro.2012.01.190
  46. Liu, C., Ma, N., Sun, M., et al. 2025. Impact of climate change on frequency and community structure of red tide events in the northern South China Sea. Clim. Dyn. 63:51. doi.org/10.1007/s00382-024-07552-0
  47. Liu, F. & Chen, C. 2012. Remote sensing study of the seasonal distribution of phytoplankton groups in the south China sea. In 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Institute of Electrical and Electronics Engineers, New York, pp. 2563–2566.
  48. Liu, S., Cui, Z., Zhao, Y. & Chen, N. 2022. Composition and spatial-temporal dynamics of phytoplankton community shaped by environmental selection and interactions in the Jiaozhou Bay. Water Res. 218:118488. doi.org/10.1016/j.watres.2022.118488
  49. Liu, X., Xiao, W., Landry, M. R., Chiang, K.-P., Wang, L. & Huang, B. 2016. Responses of phytoplankton communities to environmental variability in the East China Sea. Ecosystems 19:832–849. doi.org/10.1007/s10021-016-9970-5
  50. Lou, X. & Hu, C. 2014. Diurnal changes of a harmful algal bloom in the East China Sea: observations from GOCI. Remote Sens. Environ. 140:562–572. doi.org/10.1016/j.rse.2013.09.031
  51. Ma, S. 2018. Studies on responses of phytoplankton and community structure to ocean acidification. Ph.D. dissertation, Shanghai Ocean University, Shanghai, China (in Chinese).
  52. Mackey, M. D., Mackey, D. J., Higgins, H. W. & Wright, S. W. 1996. CHEMTAX: a program for estimating class abundances from chemical markers: application to HPLC measurements of phytoplankton. Mar. Ecol. Prog. Ser. 144:265–283.
  53. Mann, H. B. 1945. Nonparametric tests against trend. Econometrica 13:245–259. doi.org/10.2307/1907187
  54. McClain, C. R. 2009. A decade of satellite ocean color observations. Annu. Rev. Mar. Sci. 1:19-42. doi.org/10.1146/annurev.marine.010908.163650
  55. Meng, Q., Li, P., Zhai, F. & Gu, Y. 2020. The vertical mixing induced by winds and tides over the Yellow Sea in summer: a numerical study in 2012. Ocean Dyn. 70:847–861. doi.org/10.1007/s10236-020-01368-2
  56. Moore, S. K., Trainer, V. L., Mantua, N. J., et al. 2008. Impacts of climate variability and future climate change on harmful algal blooms and human health. Environ. Health 7(Suppl. 2):S4. doi.org/10.1186/1476-069X-7-S2-S4
  57. Najjar, R. G., Pyke, C. R., Adams, M. B., et al. 2010. Potential climate-change impacts on the Chesapeake Bay. Estuar. Coast. Shelf Sci. 86:1–20. doi.org/10.1016/j.ecss.2009.09.026
  58. Ndah, A. B., Dagar, L., Becek, K. & Odihi, J. O. 2019. Spatio-temporal dynamics of phytoplankton functional groups in the South China Sea and their relative contributions to marine primary production. Reg. Stud. Mar. Sci. 29:100598. doi.org/10.1016/j.rsma.2019.100598
  59. Nick, F. M., Vieli, A., Andersen, M. L., et al. 2013. Future sea-level rise from Greenland's main outlet glaciers in a warming climate. Nature 497:235–238. doi.org/10.1038/nature12068
  60. Noman, M. A., Sun, J., Gang, Q., et al. 2019. Factors regulating the phytoplankton and tintinnid microzooplankton communities in the East China Sea. Cont. Shelf Res. 181:14–24. doi.org/10.1016/j.csr.2019.05.007
  61. O'Brien, R. M. 2007. A caution regarding rules of thumb for variance inflation factors. Qual. Quant. 41:673–690. doi.org/10.1007/s11135-006-9018-6
  62. O'Reilly, J. E., Maritorena, S., Siegel, D. A., et al. 2000. Ocean color chlorophyll a algorithms for SeaWiFS, OC2 and OC4: Version 4. In Hooker, S. B. & Firestone, E. R. (Eds.) NASA, SeaWiFS Postlaunch Technical Report Series. Vol. 11. SeaWiFS Postlaunch Calibration and Validation Analyses. NASA Goddard Space Flight Center, Greenbelt, MD, pp. 9–23.
  63. Pan, X., Mannino, A., Marshall, H. G., Filippino, K. C. & Mulholland, M. R. 2011. Remote sensing of phytoplankton community composition along the northeast coast of the United States. Remote Sens. Environ. 115:3731–3747. doi.org/10.1016/j.rse.2011.09.011
  64. Park, M. O., Kang, S. W., Lee, C. I., Choi, T. S. & Lantoine, F. 2008. Structure of the phytoplanktonic communities in Jeju Strait and northern East China Sea and dinoflagellate blooms in spring 2004: analysis of photosynthetic pigments. Sea 13:27–41.
  65. Pearson, K. 1895. Note on regression and inheritance in the case of two parents. Proc. R. Soc. Lond. 58:240–242.
  66. Polovina, J. J., Howell, E. A. & Abecassis, M. 2008. Ocean's least productive waters are expanding. Geophys. Res. Lett. 35:L03618. doi.org/10.1029/2007GL031745
  67. Prais, S. J. & Winsten, C. B. 1954. Trend estimators and serial correlation. Biometrika (Cowles Commission Discussion Paper 383).
  68. Qi, Y., Chen, J., Wang, Z., et al. 2004. Some observations on harmful algal bloom (HAB) events along the coast of Guangdong, southern China in 1998. Hydrobiologia 512:209–214. doi.org/10.1023/B:HYDR.0000020329.06666.8c
  69. Schaffer, G., Leth, O., Ulloa, O., et al. 2000. Warming and circulation change in the eastern South Pacific Ocean. Geophys. Res. Lett. 27:1247–1250. doi.org.10.1029/1999GL010952
  70. Sekerci, Y. & Ozarslan, R. 2020. Oxygen-plankton model under the effect of global warming with nonsingular fractional order. Chaos Solitons Fractals 132:109532. doi.org/10.1016/j.chaos.2019.109532
  71. Sen, P. K. 1968. Estimates of the regression coefficient based on Kendall's tau. J. Am. Stat. Assoc. 63:1379–1389. doi.org/10.1080/01621459.1968.10480934
  72. Song, S. 2010. Phytoplankton functional groups in the Yellow Sea and the East China Sea. Ph.D. dissertation, Chinese Academy of Sciences, Beijing, China (in Chinese).
  73. Song, S., Li, Z., Li, C. & Yu, Z. 2017. The response of spring phytoplankton assemblage to diluted water and upwelling in the eutrophic Changjiang (Yangtze River) Estuary. Acta Oceanol. Sin. 36:101–110. doi.org/10.1007/s13131-017-1094-z
  74. Spearman, C. 1904. The proof and measurement of association between two things. Am. J. Psychol. 15:72–101. 
  75. Student. 1908. The probable error of a mean. Biometrika 6:1–25. doi.org/10.2307/2331554
  76. Su, J. L. & Yuan, Y. L. 2005. Coastal hydrology in China. Ocean Press, Beijing, 367 pp (in Chinese).
  77. Sun, D., Huan, Y., Qiu, Z., Hu, C., Wang, S. & He, Y. 2017. Remote-sensing estimation of phytoplankton size classes from GOCI satellite measurements in Bohai Sea and Yellow Sea. J. Geophys. Res. Oceans 122:8309–8325. doi.org/10.1002/2017JC013099
  78. Sun, J. 2011. Marine phytoplankton and biological carbon sink. Acta Ecol. Sin. 31:5372–5378.
  79. Sun, Y., Youn, S.-H., Kim, Y., et al. 2022. Interannual variation in phytoplankton community driven by environmental factors in the northern east China Sea. Front. Mar. Sci. 9:769497. doi.org/10.3389/fmars.2022.769497
  80. Torrisi, M. & Dell'Uomo, A. 2006. Biological monitoring of some Apennine rivers (central Italy) using the diatom-based Eutrophication/Pollution Index (EPI-D) compared to other European diatom indices. Diatom Res. 21:159–174. doi.org/10.1080/0269249X.2006.9705657
  81. Van-Meerssche, E. & Pinckney, J. L. 2017. The influence of salinity in the domoic acid effect on estuarine phytoplankton communities. Harmful Algae 69:65–74. doi.org/10.1016/j.hal.2017.10.003
  82. Wang, D., Huang, B., Liu, X., Liu, G. & Wang, H. 2014. Seasonal variations of phytoplankton phosphorus stress in the Yellow Sea Cold Water Mass. Acta Oceanol. Sin. 33:124–135. doi.org/10.1007/s13131-014-0547-x
  83. Wang, G., Cao, W., Wang, G. & Zhou, W. 2013. Phytoplankton size class derived from phytoplankton absorption and chlorophyll-a concentrations in the northern South China Sea. Chin. J. Oceanol. Limnol. 31:750–761. doi.org/10.1007/s00343-013-2291-z
  84. Wang, J., Yu, Z., Wei, Q. & Yao, Q. 2019. Long-term nutrient variations in the Bohai Sea over the past 40 years. J. Geophys. Res. Oceans 124:703–722. doi.org/10.1029/2018JC014765
  85. Wang, S., Ishizaka, J., Hirawake, T., et al. 2015. Remote estimation of phytoplankton size fractions using the spectral shape of light absorption. Opt. Express 23:10301–10318. doi.org/10.1364/OE.23.010301
  86. Wei, Q., Yao, Q., Wang, B., Wang, H. & Yu, Z. 2015. Long-term variation of nutrients in the southern Yellow Sea. Cont. Shelf Res. 111:184–196. doi.org/10.1016/j.csr.2015.08.003
  87. Worsfold, M., Good, S., Atkinson, C. & Embury, O. 2024. Presenting a long-term, reprocessed dataset of global sea surface temperature produced using the OSTIA system. Remote Sens. 16:3358. doi.org/10.3390/rs16183358
  88. Wu, J.-T. & Kow, L.-T. 2002. Applicability of a generic index for diatom assemblages to monitor pollution in the tropical River Tsanwun, Taiwan. J. Appl. Phycol. 14:63–69. doi.org/10.1023/A:1015277013102
  89. Xi, H., Losa, S. N., Mangin, A., et al. 2020. Global retrieval of phytoplankton functional types based on empirical orthogonal functions using CMEMS GlobColour merged products and further extension to OLCI data. Remote Sens. Environ. 240:111704. doi.org/10.1016/j.rse.2020.111704
  90. Xi, H., Losa, S. N., Mangin, A., et al. 2021. Global chlorophyll a concentrations of phytoplankton functional types with detailed uncertainty assessment using multisensor ocean color and sea surface temperature satellite products. J. Geophys. Res. Oceans 126:e2020JC017127. doi.org/10.1029/2020JC017127
  91. Xu, L., Hong, H.-S., Wang, H.-L. & Chen, W.-Q. 2001. The biogeochemistry of photosynthetic pigments in Jiulong River Estuary and Xiamen Bay. Chin. J. Oceanol. Limnol. 19:164–171. doi.org/10.1007/BF02863042
  92. Xu, Q., Sukigara, C., Goes, J. I., et al. 2019. Interannual changes in summer phytoplankton community composition in relation to water mass variability in the East China Sea. J. Oceanogr. 75:61–79. doi.org/10.1007/s10872-018-0484-y
  93. Xu, S., Song, J., Li, X., et al. 2010. Changes in nitrogen and phosphorus and their effects on phytoplankton in the Bohai Sea. Chin. J. Oceanol. Limnol. 28:945–952. doi.org/10.1007/s00343-010-0005-3
  94. Yang, F., Wei, Q., Chen, H. & Yao, Q. 2018. Long-term variations and influence factors of nutrients in the western North Yellow Sea, China. Mar. Pollut. Bull. 135:1026–1034. doi.org/10.1016/j.marpolbul.2018.08.034
  95. Yoon, S. C., Youn, S. H., Whang, J. D., Seo, Y. S. & Yoon, Y. Y. 2015. Long-term variation in ocean environmental conditions of the Northern East China Sea. J. Korean Soc. Mar. Environ. Energy 18:189–206. doi.org/10.7846/jkosmee.2015.18.3.189
  96. Yoon, Y. H., Park, J. S., Soh, H. Y. & Hwang, D.-J. 2003. Spatial distribution of phytoplankton community and red tide of dinoflagellate, Prorocentrum donghaience in the East China Sea during early summer. Korean J. Environ. Biol. 21:132–141.
  97. Yu, P., Guo, T., Zhu, Y., et al. 2017. Concentration and size distribution of amines in marine atmospheric particles over Yellow Sea, East China Sea and Northwest Pacific Ocean. Period. Ocean Univ. China 47:19–26.
  98. Zeebe, R. E. 2012. History of seawater carbonate chemistry, atmospheric CO2, and ocean acidification. Annu. Rev. Earth Planet. Sci. 40:141–165. doi.org/10.1146/annurev-earth-042711-105521
  99. Zhang, J., Liu, S. M., Ren, J. L., Wu, Y. & Zhang, G. L. 2007. Nutrient gradients from the eutrophic Changjiang (Yangtze River) Estuary to the oligotrophic Kuroshio waters and re-evaluation of budgets for the East China Sea Shelf. Prog. Oceanogr. 74:449–478. doi.org/10.1016/j.pocean.2007.04.019
  100. Zhang, Q., Weng, X. & Yang, Y. 1996. Analysis of water masses in the south Yellow Sea in spring. Oceanol. Limnol. Sin. 27:421–428.
  101. Zhang, Z., Qiao, F., Guo, J. & Gao, B. 2018. Seasonal changes and driving forces of inflow and outflow through the Bohai Strait. Cont. Shelf Res. 154:1–8. doi.org/10.1016/j.csr.2017.12.012
  102. Zhao, L., Zhao, Y., Dong, Y., et al. 2018. Influence of the northern Yellow Sea Cold Water Mass on picoplankton distribution around the Zhangzi Island, northern Yellow Sea. Acta Oceanol. Sin. 37:96–106. doi.org/10.1007/s13131-018-1149-9
  103. Zhao, R., Sun, J. & Bai, J. 2010. Phytoplankton assemblages in Yangtze River Estuary and its adjacent water in autumn 2006. Mar. Sci. 34:32–39.
  104. Zhao, Y., Yu, R.-C., Kong, F.-Z., et al. 2019. Features of phytoplankton communities and their controlling factors in the Yellow Sea and the East China Sea in summer time. Oceanol. Limnol. Sin. 50:838–850. doi.org/10.11693/hyhz20181100268
  105. Zhou, M.-J., Shen, Z.-L. & Yu, R.-C. 2008. Responses of a coastal phytoplankton community to increased nutrient input from the Changjiang (Yangtze) River. Cont. Shelf Res. 28:1483–1489. doi.org/10.1016/j.csr.2007.02.009
  106. Zhou, Q. 2014. Studies on community structure and biodiversity of phytoplankton in eastern marginal seas of China and Beibu Gulf. Ph.D. dissertation, Xiamen University, Xiamen, China (in Chinese).