scholarly journals Methane distribution, flux, and budget in the East China Sea and Yellow Sea

2015 ◽  
Vol 12 (9) ◽  
pp. 7017-7053 ◽  
Author(s):  
M.-S. Sun ◽  
G.-L. Zhang ◽  
X.-P. Cao ◽  
X.-Y. Mao ◽  
J. Li ◽  
...  
Keyword(s):  
East China Sea ◽  
Yellow Sea ◽  
The Yellow Sea ◽  
East China ◽  
Hangzhou Bay ◽  
The East China Sea ◽  
The Changjiang Estuary ◽  
China Sea ◽  
Ch4 Production ◽  
Ch4 Concentration

Abstract. We measured dissolved methane (CH4) concentrations, saturations, and fluxes from sea into air and from sediment into water during cruises in March, May, August, October, and December of 2011 in the East China Sea (ECS) and the Yellow Sea (YS). CH4 concentrations had obvious spatial and seasonal variability due to the complex effects of different water masses and other variables. Maximal CH4 concentration, sea–air and sediment–water fluxes all occurred during the summer. CH4 concentration decreased gradually from the coastal area to the open sea, and high levels of CH4 generally appeared near the Changjiang Estuary and outside the Hangzhou Bay. During early spring and winter, CH4 had a uniform distribution from the surface to the bottom, but CH4 concentration increased gradually with depth during other seasons. The subsurface CH4 maximum occurred at a depth of about 200 m during May, October, and December. The CH4 level at the bottom was generally higher than at the surface, and this was enhanced during summer due to hypoxia in the bottom waters. Changjiang-diluted water, the Kuroshio Current, and the Taiwan Warm Current Water affected the geographic distribution of CH4 in the ECS, and these water bodies contributed about 3.45, 2.97, 14.60 mol s−1 of CH4 during summer and 2.11, 8.58, 5.20 mol s−1 CH4 during winter, respectively. Sediment was also a significant source of dissolved CH4 in the ECS, and we estimated the average sediment–water CH4 flux of the ECS and YS as about 1.02 μmol m−2 d−1. We also used a box model to calculate the CH4 budget in the ECS. The results suggested that in situ CH4 production in the water column was the major source of CH4, and accounted for 0.21 μmol m−3 day−1 during summer and 0.11 μmol m−3 day−1 during winter. Air–sea exchange was the major sink of CH4 in the ECS. We estimated total CH4 emission from the ECS and YS as about 4.45 x 109 mol during 2011. Our results indicated that the ECS and YS were active areas for CH4 production and emission.

Distribution and influencing factors of dissolved manganese in the Yellow Sea and the East China Sea

2021 ◽  
pp. 104002
Author(s):  
Yuan Zhang ◽  
Lei Li ◽  
Jingling Ren ◽  
Huijun He ◽  
Ruifeng Zhang ◽  
...  
Keyword(s):  
Influencing Factors ◽  
East China Sea ◽  
Yellow Sea ◽  
The Yellow Sea ◽  
East China ◽  
The East China Sea ◽  
China Sea

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

2014 ◽  
Vol 11 (3) ◽  
pp. 779-806 ◽  
Author(s):  
J. Sun ◽  
X. Y. Gu ◽  
Y. Y. Feng ◽  
S. F. Jin ◽  
W. S. Jiang ◽  
...  
Keyword(s):  
Surface Layer ◽  
Environmental Factors ◽  
East China Sea ◽  
Correspondence Analysis ◽  
Yellow Sea ◽  
The Yellow Sea ◽  
East China ◽  
The East China Sea ◽  
China Sea ◽  
Living Coccolithophores

Abstract. This paper describes the distribution of living coccolithophores (LCs) in the Yellow Sea and the East China Sea in summer and winter, and its relationship with environmental factors by canonical correspondence analysis (CCA). We carried out a series of investigations on LCs 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 coccolithophore 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. 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 in 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. Abbreviations: LCs: Living Coccolithophores; CCA: canonical correspondence analysis; DCM: Deep Chlorophyll Maximum

The genetic divergence of Oratosquilla oratoria between the East China Sea and Yellow Sea: physical barrier and possible local adaptation

2017 ◽  
Vol 99 (3) ◽  
pp. 631-638
Author(s):  
Wenbin Zhu ◽  
Xinwei Du ◽  
Zhiqiang Han ◽  
Hanxiang Xu
Keyword(s):  
Local Adaptation ◽  
East China Sea ◽  
Yellow Sea ◽  
The Yellow Sea ◽  
Coi Gene ◽  
East China ◽  
The East China Sea ◽  
China Sea ◽  
Oratosquilla Oratoria ◽  
Genetic Break

In order to confirm the genetic relationship between the Yellow Sea and East China Sea populations of mantis shrimps Oratosquilla oratoria, fragments of mitochondrial DNA COI gene samples were analysed. A total of 212 individuals from nine localities in the East China Sea and Yellow Sea were collected and 108 haplotypes were detected. Neighbour-joining analysis revealed a complete genetic break between the Yellow Sea and East China Sea, which was consistent with the previous mtDNA 16S rRNA. Pleistocene isolation and the current physical barrier were responsible for the complete genetic break between the East China Sea and Yellow Sea. Furthermore, local adaptation in the COI gene may also be contributed to by the genetic differentiation between the populations of the Yellow Sea and East China. The different Ka/Ks ratios between the two clades may reflect different selection pressures and local adaptation on the fragment of COI gene.

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