scholarly journals Stimulation of Heterotrophic and Autotrophic Metabolism in the Mixing Zone of the Kuroshio Current and Northern South China Sea: Implications for Export Production

2019 ◽  
Vol 124 (9) ◽  
pp. 2645-2661 ◽  
Author(s):  
Yibin Huang ◽  
Edward Laws ◽  
Bingzhang Chen ◽  
Bangqin Huang
2021 ◽  
Vol 9 (5) ◽  
pp. 1104
Author(s):  
Ping Sun ◽  
Silu Zhang ◽  
Ying Wang ◽  
Bangqin Huang

Kuroshio Current intrusion (KCI) has significant impacts on the oceanographic conditions and ecological processes of the Pacific-Asian marginal seas. Little is known to which extent and how, specifically, the microzooplankton community can be influenced through the intrusion. Here, we focused on ciliates that often dominated the microzooplankton community and investigated their communities using high-throughput sequencing of 18S rRNA gene transcripts in the northern South China Sea (NSCS), where the Kuroshio Current (KC) intrudes frequently. We first applied an isopycnal mixing model to assess the fractional contribution of the KC to the NSCS. The ciliate community presented a provincial distribution pattern corresponding to more and less Kuroshio-influenced stations. Structural equation modeling revealed a significant impact of the KCI on the community, while environmental variables had a marginal impact. KCI-sensitive OTUs were taxonomically diverse but mainly belonged to classes Spirotrichea and Phyllopharyngea, suggesting the existence of core ciliates responding to the KCI. KCI-sensitive OTUs were grouped into two network modules that showed contrasting abundance behavior with the KC fraction gradient, reflecting differential niches (i.e., winner and loser) in the ciliate community during the Kuroshio intrusion scenarios. Our study showed that the Kuroshio intrusion, rather than environmental control, was particularly detrimental to the oligotrophic microzooplankton community.


2013 ◽  
Vol 10 (10) ◽  
pp. 6419-6432 ◽  
Author(s):  
C. Du ◽  
Z. Liu ◽  
M. Dai ◽  
S.-J. Kao ◽  
Z. Cao ◽  
...  

Abstract. Based on four cruises covering a seasonal cycle in 2009–2011, we examined the impact of the Kuroshio intrusion, featured by extremely oligotrophic waters, on the nutrient inventory in the central northern South China Sea (NSCS). The nutrient inventory in the upper 100 m of the water column in the study area ranged from ∼200 to ∼290 mmol m−2 for N + N (nitrate plus nitrite), from ∼13 to ∼24 mmol m−2 for soluble reactive phosphate and from ∼210 to ∼430 mmol m−2 for silicic acid. The nutrient inventory showed a clear seasonal pattern with the highest value appearing in summer, while the N + N inventory in spring and winter had a reduction of ∼13 and ∼30%, respectively, relative to that in summer. To quantify the extent of the Kuroshio intrusion, an isopycnal mixing model was adopted to derive the proportional contribution of water masses from the SCS proper and the Kuroshio along individual isopycnal surfaces. The derived mixing ratio along the isopycnal plane was then employed to predict the genuine gradients of nutrients under the assumption of no biogeochemical alteration. These predicted nutrient concentrations, denoted as Nm, are solely determined by water mass mixing. Results showed that the nutrient inventory in the upper 100 m of the NSCS was overall negatively correlated to the Kuroshio water fraction, suggesting that the Kuroshio intrusion significantly influenced the nutrient distribution in the SCS and its seasonal variation. The difference between the observed nutrient concentrations and their corresponding Nm allowed us to further quantify the nutrient removal/addition associated with the biogeochemical processes on top of the water mass mixing. We revealed that the nutrients in the upper 100 m of the water column had a net consumption in both winter and spring but a net addition in fall.


2021 ◽  
Vol 562 ◽  
pp. 110093
Author(s):  
Shuhuan Du ◽  
Rong Xiang ◽  
Jianguo Liu ◽  
Hongqiang Yan ◽  
Longbin Sha ◽  
...  

2006 ◽  
Vol 21 (4) ◽  
pp. 377-385 ◽  
Author(s):  
Hui Jiang ◽  
Svante Björck ◽  
Lihua Ran ◽  
Yue Huang ◽  
Jiayin Li

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