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Phytoplankton species composition of four ecological provinces in Yellow Sea, China

Authors :
Haijiao Liu
Xiaoqian Li
Xiaoyun Leng
Jun Sun
Yuanyuan Feng
Source :
Journal of Ocean University of China. 16:1115-1125
Publication Year :
2017
Publisher :
Springer Science and Business Media LLC, 2017.

Abstract

The ecological province based on phytoplankton species composition is important to understanding the interplay between environmental parameters and phytoplankton species composition. The aim of this study was to establish phytoplankton species composition ecological pattern thus elucidate the relationship between environmental factors and the phytoplankton species composition in the ecological provinces. Phytoplankton samples were collected from 31 stations in Yellow Sea (121.00°–125.00°E, 32.00°–39.22°N) in November 2014. The samples were enumerated and identified with the Utermohl method under an optical inverted microscope-AE2000 with magnifications of 200 × or 400 ×. In the present study, a total of 141 taxa belonging to 60 genera of 4 phyla of phytoplankton were identified, among them 101 species of 45 genera were Bacillariophyta, 36 species of 11 genera were Dinophyta, 3 species of 3 genera were Chrysophyta and 1 species of 1 genera was Chlorophyta. The study area was divided into 4 ecological provinces according to an unsupervised cluster algorithm applied to the phytoplankton biomass. A T-S (Temperature-Salinity) scatter diagram depicted with data of water temperature and salinity defined by environmental provinces matched well with the ecological provinces. The results of Canonical Correspondence Analysis (CCA) indicated that the phytoplankton species composition was mainly correlated with temperature, salinity and silicate concentration in the studied area. A method of establishing ecological provinces is useful to further understanding the environmental effects on the marine phytoplankton species composition and the consequent marine biogeochemistry.

Details

ISSN :
19935021 and 16725182
Volume :
16
Database :
OpenAIRE
Journal :
Journal of Ocean University of China
Accession number :
edsair.doi...........56da85b9ab04071ff4903c804d003f49
Full Text :
https://doi.org/10.1007/s11802-017-3270-3