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

Authors :
Cao, Mengmeng
Li, Xuyan
Cui, Tingwei
Pan, Xinliang
Li, Yan
Chen, Yanlong
Wang, Ning
Xiao, Yanfang
Song, Xingai
Xu, Yuzhu
A, Runa
Mu, Bing
Qing, Song
Liu, Rongjie
Zhao, Wenjing
Bao, Yuhai
Zhang, Jie
Wei, Lan
Source :
International Journal of Digital Earth. Jan2023, Vol. 16 Issue 1, p3772-3793. 22p.
Publication Year :
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 < 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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17538947
Volume :
16
Issue :
1
Database :
Academic Search Index
Journal :
International Journal of Digital Earth
Publication Type :
Academic Journal
Accession number :
173778994
Full Text :
https://doi.org/10.1080/17538947.2023.2257658