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Variability in phytoplankton biomass and effects of sea surface temperature based on satellite data from the Yellow Sea, China

A time series of satellite data on Chlorophyll-a concentration (Chl-a) that used ocean color was studied to determine mechanisms of phytoplankton variation in recent decade in the Yellow Sea, China during 2003–2015. The variability patterns on seasonal and inter-annual oscillation periods were confi...

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Autores principales: Liu, Chunli, Sun, Qiwei, Xing, Qianguo, Wang, Sufen, Tang, Danling, Zhu, Donghe, Xing, Xiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6684081/
https://www.ncbi.nlm.nih.gov/pubmed/31386653
http://dx.doi.org/10.1371/journal.pone.0220058
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author Liu, Chunli
Sun, Qiwei
Xing, Qianguo
Wang, Sufen
Tang, Danling
Zhu, Donghe
Xing, Xiang
author_facet Liu, Chunli
Sun, Qiwei
Xing, Qianguo
Wang, Sufen
Tang, Danling
Zhu, Donghe
Xing, Xiang
author_sort Liu, Chunli
collection PubMed
description A time series of satellite data on Chlorophyll-a concentration (Chl-a) that used ocean color was studied to determine mechanisms of phytoplankton variation in recent decade in the Yellow Sea, China during 2003–2015. The variability patterns on seasonal and inter-annual oscillation periods were confirmed using the Empirical Orthogonal Function (EOF), and Morlet wavelet transform analyses, respectively. The first EOF mode for Chl-a was dominated by obvious spring and fall blooms in a spatial pattern that was related to the strong mixing of the water masses from the Yellow Sea Cold Warm Mass (YSCWM) and the Yellow Sea Warm Current (YSWC) in winter. The second EOF mode for Chl-a showed an opposite spatial pattern between the northern and southern regions. The temporal coefficient showed differences in the timing of blooms. On an inter-annual scale, Chl-a indicated variation at periods of 2–4 years during 2003–2015. Chl-a showed a significantly negative correlation with the sea surface temperature (r = -0.21, p<0.01), with time lags of 4 months (Chl-a ahead). Chl-a was coupled with El Niño Southern Oscillation (ENSO) events, with a positive correlation (r = 0.46, p<0.01) at a lag of 3–5 months (ENSO ahead). The present study demonstrated that the variation in phytoplankton biomass was controlled primarily by water mass seasonally, and it was influenced by ENSO events on an inter-annual scale.
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spelling pubmed-66840812019-08-15 Variability in phytoplankton biomass and effects of sea surface temperature based on satellite data from the Yellow Sea, China Liu, Chunli Sun, Qiwei Xing, Qianguo Wang, Sufen Tang, Danling Zhu, Donghe Xing, Xiang PLoS One Research Article A time series of satellite data on Chlorophyll-a concentration (Chl-a) that used ocean color was studied to determine mechanisms of phytoplankton variation in recent decade in the Yellow Sea, China during 2003–2015. The variability patterns on seasonal and inter-annual oscillation periods were confirmed using the Empirical Orthogonal Function (EOF), and Morlet wavelet transform analyses, respectively. The first EOF mode for Chl-a was dominated by obvious spring and fall blooms in a spatial pattern that was related to the strong mixing of the water masses from the Yellow Sea Cold Warm Mass (YSCWM) and the Yellow Sea Warm Current (YSWC) in winter. The second EOF mode for Chl-a showed an opposite spatial pattern between the northern and southern regions. The temporal coefficient showed differences in the timing of blooms. On an inter-annual scale, Chl-a indicated variation at periods of 2–4 years during 2003–2015. Chl-a showed a significantly negative correlation with the sea surface temperature (r = -0.21, p<0.01), with time lags of 4 months (Chl-a ahead). Chl-a was coupled with El Niño Southern Oscillation (ENSO) events, with a positive correlation (r = 0.46, p<0.01) at a lag of 3–5 months (ENSO ahead). The present study demonstrated that the variation in phytoplankton biomass was controlled primarily by water mass seasonally, and it was influenced by ENSO events on an inter-annual scale. Public Library of Science 2019-08-06 /pmc/articles/PMC6684081/ /pubmed/31386653 http://dx.doi.org/10.1371/journal.pone.0220058 Text en © 2019 Liu et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Liu, Chunli
Sun, Qiwei
Xing, Qianguo
Wang, Sufen
Tang, Danling
Zhu, Donghe
Xing, Xiang
Variability in phytoplankton biomass and effects of sea surface temperature based on satellite data from the Yellow Sea, China
title Variability in phytoplankton biomass and effects of sea surface temperature based on satellite data from the Yellow Sea, China
title_full Variability in phytoplankton biomass and effects of sea surface temperature based on satellite data from the Yellow Sea, China
title_fullStr Variability in phytoplankton biomass and effects of sea surface temperature based on satellite data from the Yellow Sea, China
title_full_unstemmed Variability in phytoplankton biomass and effects of sea surface temperature based on satellite data from the Yellow Sea, China
title_short Variability in phytoplankton biomass and effects of sea surface temperature based on satellite data from the Yellow Sea, China
title_sort variability in phytoplankton biomass and effects of sea surface temperature based on satellite data from the yellow sea, china
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6684081/
https://www.ncbi.nlm.nih.gov/pubmed/31386653
http://dx.doi.org/10.1371/journal.pone.0220058
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