Numerical simulation of pelagic ecosystem's seasonal variation in the central East China Sea

CHEN Jian-zhong; GE Jian-zhong; BELLERBY Richard

doi:10.3969/j.issn.1000-5641.2019.06.015

Issue 6

Dec. 2019

Turn off MathJax

Article Contents

Article Navigation > Journal of East China Normal University (Natural Sciences) > 2019 > (6): 153-168

CHEN Jian-zhong, GE Jian-zhong, BELLERBY Richard. Numerical simulation of pelagic ecosystem's seasonal variation in the central East China Sea[J]. Journal of East China Normal University (Natural Sciences), 2019, (6): 153-168. doi: 10.3969/j.issn.1000-5641.2019.06.015

Citation:

CHEN Jian-zhong, GE Jian-zhong, BELLERBY Richard. Numerical simulation of pelagic ecosystem's seasonal variation in the central East China Sea[J]. Journal of East China Normal University (Natural Sciences), 2019, (6): 153-168. doi: 10.3969/j.issn.1000-5641.2019.06.015

Citation:

PDF( 3435 KB)

Numerical simulation of pelagic ecosystem's seasonal variation in the central East China Sea

doi: 10.3969/j.issn.1000-5641.2019.06.015

1.
State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200241, China
2.
Norwegian Institute for Water Research, Bergen N-5006, Norway

Received Date: 2018-09-06
Publish Date: 2019-11-25

Abstract

Abstract

The 1D physics-ecological system model GOTM-FABM-ERSEM is used to simulate the seasonal variation in pelagic ecosystem components in the central East China Sea. The interaction between physical and bio-chemical components is well characterized. The biophysical drivers of seasonality are light, temperature, vertical stratification, and nutrient concentrations as well as their respective rates of supply. There are two blooming periods for phytoplankton:these are April and October. In summer, the seawater temperature is the highest and stratification is the strongest, with high nutrient concentrations found below the thermocline; these concentrations reach a maximum in September with phytoplankton biomass reaching a maximum of 5.3 mg C·m^-3 in the subsurface layer (about 20 m depth) and periodic growth promoted by tidal mixing. The temporal variability of zooplankton and bacteria is tightly coupled with that of phytoplankton, but with a 3 d lag in spring blooming; hence, the zooplankton and bacteria reach maximum concentrations after the spring phytoplankton bloom. Bacterial biomass in the upper layer is controlled by phytoplankton standing stock and temperatures during the summer.
- East China Sea,
- marine modelling,
- pelagic ecosystems,
- seasonal variability

FullText(HTML)

References(37)

References

[1]	沈国英, 黄凌风.海洋生态学[M]. 2版.北京:科学出版社, 2002.
[2]	姜加虎, 王苏民.长江流域水资源、灾害及水环境状况初步分析[J].第四纪研究, 2004, 24(5):512-517. http://d.old.wanfangdata.com.cn/Periodical/dsjyj200405006
[3]	白涛, 杨德周, 尹宝树.夏季长江口外海区域上升流现象的数值研究[J].海洋科学, 2009, 33(11):65-72. http://d.old.wanfangdata.com.cn/Periodical/hykx200911013
[4]	董书航.东海营养盐分布特征及跨陆架交换研究[D].山东青岛: 中国海洋大学, 2015.
[5]	孙百晔.长江口及邻近海域浮游植物生长的光照效应研究[D].山东青岛: 中国海洋大学, 2008.
[6]	文斐, 孙晓霞, 郑珊, 等. 2011年春、夏季黄、东海叶绿素a和初级生产力的时空变化特征[J].海洋与湖沼, 2012, 43(3):438-444. http://d.old.wanfangdata.com.cn/Periodical/hyyhz201203009
[7]	朱建荣, 肖成猷, 沈焕庭.夏季长江冲淡水扩展的数值模拟[J].海洋学报:中文版, 1998, 20(5):13-22. http://d.old.wanfangdata.com.cn/Periodical/hyxb201301004
[8]	葛建忠, 胡克林, 丁平兴.风暴潮集成预报可视化系统设计和应用[J].华东师范大学学报(自然科学版), 2007(4):20-25. http://xblk.ecnu.edu.cn/CN/abstract/abstract23735.shtml
[9]	杨德周, 许灵静, 尹宝树, 等.黑潮跨陆架入侵东海年际变化的数值模拟[J].海洋与湖沼, 2017(6):1318-1327. http://d.old.wanfangdata.com.cn/Periodical/hyyhz201706019
[10]	杨雪飞.基于GOCI和数值模拟的东海近岸悬浮泥沙浓度逐时变化研究[D].上海: 中国科学院研究生院(上海技术物理研究所), 2016.
[11]	孙科.东海典型赤潮藻种群动态的数值模拟[D].山东青岛: 中国科学院研究生院(海洋研究所), 2013.
[12]	闫庆.长江口外锋区浮游植物生物量及其影响因子的观测与数值模拟[D].上海: 上海海洋大学, 2016.
[13]	贾守伟.长江冲淡水对长江口附近海域生态环境影响的数值研究[D].山东青岛: 中国海洋大学, 2014.
[14]	BLACKFORD J C, BURKILL P H. Planktonic community structure and carbon cycling in the Arabian Sea as a result of monsoonal forcing:The application of a generic model[J]. Journal of Marine Systems, 2002, 36(3):239-267. http://cn.bing.com/academic/profile?id=9b1ae43e1927b34ccdfe6ef4283016b2&encoded=0&v=paper_preview&mkt=zh-cn
[15]	VICHI M, PINARDI N, ZAVATARELLI M, et al. One-dimensional ecosystem model tests in the Po prodelta area[J]. Environmental Modelling & Software, 1998, 13(5):471-4812. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=cdf34bfcb280334df78985d5bc740aae
[16]	ALLEN J I, BLACKFORD J C, RADFORD P J. An 1-D vertically resolved modelling study of the ecosystem dynamics of the middle and southern Adriatic Sea[J]. Journal of Marine Systems, 1998, 18(1/2/3):265-286. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=1ea1263006f79968a2f436767e5de45f
[17]	PAN S, SHI J, GAO H, et al. Contributions of physical and biogeochemical processes to phytoplankton biomass enhancement in the surface and subsurface layers during the passage of Typhoon Damrey[J]. Journal of Geophysical Research:Biogeosciences, 2017, 122(1):212-229. doi: 10.1002/2016JG003331
[18]	夏洁, 高会旺.南黄海东部海域浮游生态系统要素季节变化的模拟研究[J].安全与环境学报, 2006, 6(4):59-65. http://d.old.wanfangdata.com.cn/Periodical/aqyhjxb200604016
[19]	BURCHARD H, BOLDING K, VILLARREAL M R. GOTM, a general ocean turbulence model: Theory, implementation and test cases[R]. Space Applications Institute, 1999.
[20]	BUTENSCHÖN M, CLARK J, ALDRIDGE J N, et al. ERSEM 15.06:Ageneric model for marine biogeochemistry and the ecosystem dynamics of the lower trophic levels[J]. Geoscientific Model Development, 2016, 9(4):1293-1339. doi: 10.5194/gmd-9-1293-2016
[21]	BRUGGEMAN J, BOLDING K. A general framework for aquatic biogeochemical models[J]. Environmental Modelling & Software, 2014, 61(C):249-265. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=87277483317550e8add0d3bd399caa03
[22]	MELLOR G L, YAMADA T. Development of a turbulent closure model for geophysical fluid problems[J]. Reviews of Geophysics & Space Physics, 1982, 20(4):851-875. http://cn.bing.com/academic/profile?id=740f4b2810f3ed6343bbf2067caf8c94&encoded=0&v=paper_preview&mkt=zh-cn
[23]	翁学传, 王从敏.台湾暖流水的研究[J].海洋科学, 1985, 9(1):7-10. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=Y1070801
[24]	张文静.长江冲淡水扩展区域低盐水团的数值模拟及动力机制分析[D].山东青岛: 中国海洋大学, 2010.
[25]	暨卫东.中国近海海洋图集.海洋化学[M].北京:海洋出版社, 2012.
[26]	GEJZ, DING P X, CHEN C S, et al. An integrated East China Sea-Changjiang Estuary model system with aim atresolving multi-scale regional-shelf-estuarine dynamics[J]. Ocean Dynamics, 2013, 63(8):881-900. doi: 10.1007/s10236-013-0631-3
[27]	DEE D P, UPPALA S M, SIMMONS A J, et al. The ERA-Interim reanalysis:Configuration and performance of the data assimilation system[J]. Quarterly Journal of the Royal Meteorological Society, 2011, 137(656):553-597. doi: 10.1002/qj.828
[28]	LOCARNINI R A, MISHONOV A V, ANTONOV J I, et al. World Ocean Atlas 2005 Volume 1: Temperature[R]. NOAA Atlas NESDIS, 2006.
[29]	ANTONOV J, SEIDOV D, BOYER T, et al. World Ocean Atlas 2009, Volume 2: Salinity[R]. Ocean Climate Laboratory, National Oceanographic Data Center, 2010.
[30]	BOYER T P, ANTONOV J I, BARANOVA O, et al. World ocean database 2013[J]. Data Science Journal, 2013, 90(49):153-173. http://d.old.wanfangdata.com.cn/NSTLQK/NSTL_QKJJ0233616396/
[31]	BROTAS V, GRANT M, CHUPRIN A, et al. In-situ databases and comparison of ESA Ocean Colour Climate Change Initiative (OC-CCI) products with precursor data, towards an integrated approach for ocean colour validation and climate studies[C]//EGU General Assembly, 2014.
[32]	ERM A, ARST H, TREI T, et al. Optical and biological properties of Lake Ülemiste, a water reservoir of the city of Tallinn I:Water transparency and optically active substances in the water[J]. Lakes & Reservoirs Research & Management, 2010, 6(1):63-74.
[33]	REINART A, ARST H, ERM A, et al. Optical and biological properties of Lake Ülemiste, a water reservoir of the city of Tallinn Ⅱ:Light climate in Lake Ülemiste[J]. Lakes & Reservoirs Research & Management, 2010, 6(1):75-84.
[34]	安琰.东海PN断面及邻近海域温盐及化学要素月季变化特征研究[D].上海: 上海师范大学, 2009.
[35]	李晓慧, 刘镇盛.长江口及邻近海域浮游动物生物量分布及季节变化[J].海洋学研究, 2017(4):94-101. http://d.old.wanfangdata.com.cn/Periodical/dhhy201704010
[36]	杨位迪, 郑连明, 李伟巍, 等.长江口邻近海域夏季大中型浮游动物物种多样性、年际变化及其影响因素[J].厦门大学学报(自然科学版), 2018(4):517-525. http://d.old.wanfangdata.com.cn/Periodical/xmdxxb201804012
[37]	李云.长江口及其邻近海域浮游异养细菌、寡营养细菌、光合细菌的分离鉴定、分布规律及与生态环境因子关系[D].上海: 华东师范大学, 2005.