Summer and winter living coccolithophores in the Yellow Sea and the East China Sea

Abstract

Abstract. To date, very little information on living coccolithophores species composition and distribution, especially the vertical profile has been reported around the world. This paper tries to fill this gap by descripting on living coccolithophores (LCs) distribution in the Yellow Sea and the East China Sea in summer and winter time in detail, and its relationship among enviromental factors by canonical correspondence analysis (CCA). We carried out the investigations on LC distribution in the Yellow Sea and the East China Sea in July and December 2011. 210 samples from different depths were collected from 44 stations in summer and 217 samples were collected from 45 stations in winter. Totally 20 taxa belonging to coccolithophyceae were identified using a polarized microscope at the 1000 × magnification. The dominant species of the two seasons were Gephyrocapsa oceanica, Emiliania huxleyi, Helicosphaera carteri, and Algirosphaera robusta. In summer the abundance of cells and coccoliths ranged 0 ~ 176.40 cells mL−1, and 0 ~ 2144.98 coccoliths mL−1, with the average values of 8.45 cells mL−1, and 265.42 coccoliths mL−1, respectively. And in winter the abundance of cells and coccoliths ranged 0 ~ 71.66 cells mL−1, and 0 ~ 4698.99 coccoliths mL−1, with the average values of 13.91 cells mL−1 and 872.56 coccoliths mL−1 respectively. In summer the LCs in surface layer were mainly observed on the coastal belt and southern part of the survey area. The highest abundance was found at the bloom station. In winter the LCs in surface layer had high value in the continental shelf area of section P. The comparison among section A, section F, section P and section E indicated lower species diversity and less abundance in the Yellow Sea than those of the East China Sea in both seasons. Temperature and the nitrate concentration may be the major environmental factors controlling the distribution and species composition of LCs in the studying area based on CCA.