Unprecedent green macroalgae bloom:mechanism and implication to disaster prediction and prevention  

作　　者：Mengmeng Cao Xuyan Li Tingwei Cui Xinliang Pan Yan Li Yanlong Chen Ning Wang Yanfang Xiao Xingai Song Yuzhu Xu Runa A Bing Mu Song Qing Rongjie Liu Wenjing Zhao Yuhai Bao Jie Zhang Lan Wei 

机构地区：[1]College of Geographical Science,Inner Mongolia Normal University,Hohhot,People’s Republic of China [2]School of Atmospheric Sciences,Sun Yat-Sen University&Key Laboratory of Tropical Atmosphere-Ocean System,Ministry of Education&Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai),Zhuhai,People’s Republic of China [3]Ministry of Natural Resources,First Institute of Oceanography,Qingdao,People’s Republic of China [4]National Marine Environmental Monitoring Center,Dalian,People’s Republic of China [5]North China Sea Marine Forecasting Center of State Oceanic Administration,Qingdao,People’s Republic of China [6]Ministry of Natural Resources,National Satellite Ocean Application Service,Beijing,People’s Republic of China [7]Ocean University of China,Qingdao,People’s Republic of China [8]Ministry of Ecology and Environment,South China Institute of Environmental Science,Guangzhou,People’s Republic of China

出　　处：《International Journal of Digital Earth》2023年第1期3772-3793,共22页国际数字地球学报（英文）

基　　金：supported in part by the National Natural Science Foundation of China[grant number 42088101];in part by the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)[grant number SML2021SP313];in part by the China-Korea Joint Ocean Research Center,China[grant number PI-2022-1];in part by the Fundamental Research Funds for the Central Universities,Sun Yat-sen University[grant number 23xkjc019].

摘　　要：Green macroalgae bloom(GMB),with the dominant species of Ulva prolifera,has regularly occurred since 2007 along the China coast.Although disaster prevention and control achieved favorable results in 2020,the satellite-observed GMB annual maximum coverage(AMC)rebounded sharply in 2021 to an unprecedented level.The reasons for this rebound and the significant interannual variability over past 15 years are still open questions.Here,by using long-term time-series(2007-2022)optical and Synthetic Aperture Radar satellite observations(1000+scenes),meteorological data and water quality statistics,the mechanism analysis was performed by exploring effects from natural factors and human activities.Two key determinants for AMC are successfully identified from numerous potential factors which are the macroalgae distribution in a key area(the Subei Shoal)during a critical period(from April to May 20)and the nutrient availability.Furthermore,by using these two parameters,a novel model for AMC prediction(R^(2)=0.87,p<0.01)is proposed and independently validated,which can reasonably explain the significant interannual variability(2014-2021)and agree well with the latest observation in 2022(percentage difference 12%).Finally,suggestions are proposed for future disaster prevention and alleviation.This work may aid future bloom prediction and management measure optimization.

关 键 词：green macroalgae annual maximum coverage(AMC) the Yellow Sea Porphyra mariculture extreme weather water quality 

分 类 号：P73[天文地球—海洋科学]