Annual patterns of green tides blooms in the coastal waters of Qinhunagdao from 2018 to 2020

IF 2.1 4区地球科学 Q2 MARINE & FRESHWATER BIOLOGY Journal of Sea Research Pub Date : 2023-12-01 DOI:10.1016/j.seares.2023.102461

Yan Li , Xiaojun Ma , Meijie Jiang , Wei Song , Hongbin Han

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Abstract

Green tide disasters have been occurring along the Qinhuangdao coastal area for several years since 2015. This study investigated the interannual changes of green tides in Qinhuangdao from 2018 to 2020 and found that the green algae biomass was significantly reduced in 2020. The peak biomass of the green tide in July was only 151.5 g m⁻³, which is significantly lower than 7789.4 g m⁻³ in July 2018 and 5873.9 g m⁻³ in July 2019. Further comparative analysis showed that the decrease in nutrients, reduction in the density of Ulva microscopic propagules, and low biomass of attached macroalgae on the seaweed beds along the Jinmenghaiwan bath coastal area were the main causes for the decrease in the scale of green tides in Qinhuangdao in 2020. This paper also summarizes the factors of green tide formation in Qinhuangdao and proposes relevant prevention and control suggestions for the local governments based on the previous research.

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2018 - 2020年秦皇岛沿海绿潮年化格局

自2015年以来，秦皇岛沿海地区已经发生了好几年的绿潮灾害。本研究调查了2018 - 2020年秦皇岛绿潮的年际变化，发现2020年绿藻生物量明显减少。7月绿潮的峰值生物量仅为151.5 g m−3，显著低于2018年7月的7789.4 g m−3和2019年7月的5873.9 g m−3。进一步的对比分析表明，2020年秦皇岛绿潮规模减小的主要原因是营养物减少、Ulva微观繁殖体密度降低以及金梦湾浴场海岸带海藻床上附着大型藻类生物量低。在前人研究的基础上，总结了秦皇岛绿潮形成的因素，并为地方政府提出了相关的防治建议。

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来源期刊

Journal of Sea Research 地学-海洋学

CiteScore

3.20

自引率

5.00%

发文量

审稿时长

6-12 weeks

期刊介绍： The Journal of Sea Research is an international and multidisciplinary periodical on marine research, with an emphasis on the functioning of marine ecosystems in coastal and shelf seas, including intertidal, estuarine and brackish environments. As several subdisciplines add to this aim, manuscripts are welcome from the fields of marine biology, marine chemistry, marine sedimentology and physical oceanography, provided they add to the understanding of ecosystem processes.