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

Authors :
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
Source :
International Journal of Digital Earth, Vol 16, Iss 1, Pp 3772-3793 (2023)
Publication Year :
2023
Publisher :
Taylor & Francis Group, 2023.

Abstract

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 (R2 = 0.87, p

Details

Language :
English
ISSN :
17538947 and 17538955
Volume :
16
Issue :
1
Database :
Directory of Open Access Journals
Journal :
International Journal of Digital Earth
Publication Type :
Academic Journal
Accession number :
edsdoj.f462f83f3416462f8b7e5260dd0e9af4
Document Type :
article
Full Text :
https://doi.org/10.1080/17538947.2023.2257658