留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

渤、黄海生态环境模拟的参数敏感度空间差异分析

罗辰奕 聂红涛 张海彦

罗辰奕,聂红涛,张海彦. 渤、黄海生态环境模拟的参数敏感度空间差异分析[J]. 海洋学报,2019,41(8):85–96,doi:10.3969/j.issn.0253−4193.2019.08.008
引用本文: 罗辰奕,聂红涛,张海彦. 渤、黄海生态环境模拟的参数敏感度空间差异分析[J]. 海洋学报,2019,41(8):85–96,doi:10.3969/j.issn.0253−4193. 2019.08.008
Luo Chenyi,Nie Hongtao,Zhang Haiyan. Spatial variability of parameter sensitivity in the ecosystem simulation of the Bohai Sea and Yellow Sea[J]. Haiyang Xuebao,2019, 41(8):85–96,doi:10.3969/j.issn.0253−4193.2019.08.008
Citation: Luo Chenyi,Nie Hongtao,Zhang Haiyan. Spatial variability of parameter sensitivity in the ecosystem simulation of the Bohai Sea and Yellow Sea[J]. Haiyang Xuebao,2019, 41(8):85–96,doi:10.3969/j.issn.0253−4193. 2019.08.008

渤、黄海生态环境模拟的参数敏感度空间差异分析

doi: 10.3969/j.issn.0253-4193.2019.08.008
基金项目: 国家重点研发计划(2017YFC1404403, 2016YFC1401602);国家自然科学基金(41806018)。
详细信息
    作者简介:

    罗辰奕(1995—),女,湖北省武汉市人,研究方向为海洋生态动力学。E-mail: luocy@tju.edu.cn

    通讯作者:

    张海彦(1987—),女,讲师,研究方向为海洋生态动力学。E-mail: haiyan_zhang@tju.edu.cn

  • 中图分类号: X55

Spatial variability of parameter sensitivity in the ecosystem simulation of the Bohai Sea and Yellow Sea

  • 摘要: 随着海洋生态系统模型的发展,生态变量增多,众多生物过程参数量值的确定成为制约生态环境模拟的瓶颈问题,生态系统结构区域性要求模型中的生态参数具有区域差异。为探究不同海区的关键参数及参数敏感度的空间差异,本研究在渤、黄海建立了ROMS-CoSiNE物理–生物耦合的高分辨率生态系统模型,并对13种生态参数的敏感度空间分布进行分析。结果表明:南黄海中部与渤海及近岸海域的敏感度差异较大。渤海敏感度最大的参数为决定光合速率的浮游植物P-I曲线初始斜率,其次为浮游动物捕食半饱和常数和浮游动物最大捕食率。而南黄海中部敏感度最大的参数为浮游动物最大捕食率,其次为浮游植物死亡率和浮游植物P-I曲线初始斜率。结合敏感度分布及浮游植物生物量收支得出,渤海水体透明度较南黄海偏低、浮游植物生长光限制较强,是引起浮游植物P-I曲线初始斜率敏感度在渤海高于黄海的主要原因。浮游动物最大捕食率及浮游植物死亡率的敏感度空间差异,受渤、黄海浮游植物生物量差异的影响,与生态系统中的高度非线性特征有关。
  • 图  1  模型区域及水深分布

    Fig.  1  Bathymetry of model domain

    图  2  CoSiNE生态模型示意图

    S1. 小型浮游植物;S2.硅藻;Z1. 小型浮游动物;Z2. 中型浮游动物;Chl1.小型浮游植物对应的叶绿素;Chl2.大型浮游植物对应的叶绿素

    Fig.  2  Schematic of CoSiNE biological model

    S1. microphytoplankton; S2. diatom; Z1. microzooplankton; Z2. mesozooplankton; Chl1. chlorophyll corresponding to microphytoplankton; Chl2. chlorophyll corresponding to macroplankton

    图  3  模型模拟的2011年3月表层温度(a)、底层温度(b)、表层盐度(c)、底层盐度(d)及2013年6月表层温度(e)、底层温度(f)、表层盐度(g)、底层盐度(h)与现场观测的对比。颜色大面分布为模型结果,散点表示现场观测结果

    Fig.  3  Comparison of surface and bottom temperature and salinity between model results (colored map) and observations (dots) in March 2011 (a, b, c, d) and June 2013 (e, f, g, h)

    图  4  模型模拟的2012年6月(a)、8月(b),2013年6月(c)、7月(d)、8月(e)、9月(f)表层叶绿素与现场观测结果对比。颜色大面分布为模型结果,散点表示现场观测结果

    Fig.  4  Comparison of simulated (colored map) surface chlorophyll and observations (dots) in June 2012 (a), August 2012 (b), June 2013 (c), July 2013 (d), August 2013 (e), September 2013 (f)

    图  5  关于浮游植物P-I曲线初始斜率(H-ispi)、浮游动物最大捕食率(H-beta)、浮游动物捕食半饱和常数(H-akz)、浮游动物捕食效率(H-grzf)、浮游动物死亡率(H-mort)、浮游植物最大生长率(H-gmax)和浮游植物死亡率(H-death)的敏感度分布

    Fig.  5  Parameter sensitivity distribution of slope of P-I curve of phytoplankton (H-ispi), maximum grazing rate of zooplankton (H-beta), half saturation constant for zooplankton grazing (H-akz), grazing efficiency (H-grzf), specific mortality rate of zooplankton (H-mort), maximum specific growth rate (H-gmax), and death rate (H-death) of phytoplankton

    图  6  关于浮游植物P-I曲线初始斜率(H-ispi)、浮游动物最大捕食率(H-beta)、浮游植物死亡率(H-death)以及基础实验中B区和C区浮游植物生物量收支。BIO表示净的生物作用(PP-GRZ-MORT-AGG

    Fig.  6  Phytoplankton budget in B and C districts in baseline, initial slope of P-I curve of phytoplankton (H-ispi), maximum grazing rate of zooplankton (H-beta), death rate of phytoplankton (H-death) simulations. BIO represents net biological influence (PP-GRZ-MORT-AGG)

    表  1  生态模型参数取值

    Tab.  1  Biological parameters

    描述参数取值单位文献来源
    S1最大生长率gmaxs12d–1[23]
    S2最大生长率gmaxs22.5d–1[23]
    Z1最大捕食率beta11.6d–1[29]
    Z2最大捕食率beta20.65d–1[30]
    Z1捕食半饱和常数(以氮计)akz10.5mmol/m3[23]
    Z2捕食半饱和常数(以氮计)akz20.25mmol/m3[23]
    光合作用有效短波辐射PARfrac0.46[29]
    S1 P–I曲线初始斜率amaxs10.025d–1·(W·m–2–1[23]
    S2 P–I曲线初始斜率amaxs20.025d–1·(W·m–2–1[23]
    S1铵盐抑制系数(以氮计)pis15.59mmol/m3[23]
    S2铵盐抑制系数(以氮计)pis24mmol/m3[31]
    S1 硝酸盐吸收半饱和常数(以氮计)akno3s11mmol/m3[32]
    S2 硝酸盐吸收半饱和常数(以氮计)akno3s22mmol/m3[6]
    S1 铵盐吸收半饱和常数(以氮计)aknh4s10.1mmol/m3[33]
    S2 铵盐吸收半饱和常数(以氮计)aknh4s20.3mmol/m3[34]
    S1 磷酸盐吸收半饱和常数(以氮计)akpo4s10.065mmol/m3[6]
    S2 磷酸盐吸收半饱和常数(以氮计)akpo4s20.125mmol/m3[6]
    S2 硅酸盐吸收半饱和常数(以氮计)aksio4s24.5mmol/m3[31]
    海水光吸收系数ak10.036m–1[29]
    浮游植物光吸收系数ak20.11m–1·(mmol·m–3–1[30]
    Z2 死亡率bgamma00.1d–1[34]
    Z1 捕食效率bgamma10.75d–1[35]
    Z2 捕食效率bgamma20.75d–1[35]
    S1 死亡率bgamma30.2d–1[31]
    S2 死亡率bgamma40.1d–1[36]
    碎屑分解速率bgamma50.03d–1
    浮游植物凝聚速率bgamma60.005d–1
    硝化速率bgamma70.25d–1[37]
    小型碎屑沉降速率wsd15m·d–1[31]
    含硅碎屑沉降速率wsdsi25m·d–1[38]
    S2 沉降速率wsp1m·d–1[23]
    浮游植物氮磷吸收比n2p16mol(以N计)/mol(以P计)
    下载: 导出CSV

    表  2  浮游植物量对模型参数的敏感性

    Tab.  2  Sensitivity of model parameter to phytoplankton.

    实验名称描述浮游植物量变化率敏感度敏感程度
    H-ispi浮游植物P-I曲线初始斜率74.95%149.9%±0.88+++
    H-beta浮游动物的最大捕食率–52.91%–105.81%±0.06– – –
    H-akz浮游动物捕食半饱和常数46.42%92.84%±0.21++
    H-mort浮游动物死亡率40.07%80.14%±0.44++
    H-grzf浮游动物捕食效率–36.41%–72.81%±0.07– –
    H-gmax浮游植物最大生长率24.93%49.85%±0.25++
    H-death浮游植物死亡率–24.39%–48.77%±0.09– –
    H-wsd沉降速率–5.85%–11.7%±0.04
    H-n2p浮游植物生长所需氮磷比–2.77%5.54%±0.05+
    H-kpo4浮游植物生长磷酸盐半饱和常数–2.34%–4.68%±0.03
    H-agg浮游植物凝结速率–2.11%–4.21%±0.02
    H-kon3浮游植物生长硝酸盐半饱和常数–0.56%–1.11%±0.03
    H-nitr硝化速率0.46%0.92%±0.03+
    下载: 导出CSV

    表  3  B区和C区的敏感度

    Tab.  3  Parameter sensitivity in District B and C

    实验名称B区C区
    敏感度敏感度排序敏感度敏感度排序
    H-ispi150.74%146.36%3
    H-beta–98.50%3–64.57%1
    H-akz123.57%236.59%5
    H-grzf–66.17%5–37.16%4
    H-mort92.24%45.24%7
    H-gmax55.01%622.15%6
    H-death–40.80%7–55.78%2
    H-wsd–18.06%81.66%10
    H-n2p0.24%132.28%8
    H-kpo40.65%110.36%13
    H-agg–1.79%10–1.63%11
    H-kno3–3.06%90.44%12
    H-nitr0.45%121.7%9
    下载: 导出CSV

    表  4  关于浮游植物P-I曲线初始斜率(H-ispi)、浮游动物最大捕食率(H-beta)、浮游植物死亡率(H-death)实验中B区和C区浮游植物源汇项相对于基础实验的变化率

    Tab.  4  Change rates of phytoplankton source/sink terms in cases initial slope of P-I curve of phytoplankton (H-ispi), maximum grazing rate of zooplankton (H-beta), death rate of phytoplankton (H-death) relative to baseline in B and C districts

    实验H-ispiH-betaH-death
    B区C区B区C区B区C区
    PP84.15%27.22%–39.73%–14.07%–15.01%–15.09%
    GRZ82.58%31.09%–28.19%7.83%–29.20%–31.76%
    MORT84.45%24.50%–59.39%–35.26%14.14%3.33%
    AGG219.87%60.86%–73.95%–38.22%–23.02%–39.90%
    BIO939.95%140.44%–116.27%–76.00%–30.67%74.04%
    ADV103.11%71.48%–78.85%–95.56%–35.68%–1.32%
    DIFF8.85%92.53%–0.54%–110.61%7.13%11.79%
    下载: 导出CSV
  • [1] Denman K L. Modelling planktonic ecosystems: parameterizing complexity[J]. Progress in Oceanography, 2003, 57(3/4): 429−452.
    [2] Losa S N, Kivman G A, Ryabchenko V A. Weak constraint parameter estimation for a simple ocean ecosystem model: what can we learn about the model and data?[J]. Journal of Marine Systems, 2004, 45(1/2): 1−20.
    [3] Mateus M D, Franz G. Sensitivity analysis in a complex marine ecological model[J]. Water, 2015, 7(5): 2060−2081.
    [4] Kishi M J, Nakata K, Ishikawa K. Sensitivity analysis of a coastal marine ecosystem[J]. Journal of the Oceanographical Society of Japan, 1981, 37(3): 120−134. doi: 10.1007/BF02308096
    [5] 高会旺, 孙文心, 翟雪梅. 水层生态系统动力学模式参数的敏感性分析[J]. 青岛海洋大学学报, 1999, 29(3): 398−404.

    Gao Huiwang, Sun Wenxin, Zhai Xuemei. Sensitive analysis of the parameters of a pelagic ecosystem dynamic model[J]. Journal of Ocean University of Qingdao, 1999, 29(3): 398−404.
    [6] 赵亮. 渤海浮游植物生态动力学模型研究[D]. 青岛: 青岛海洋大学, 2002.

    Zhao Liang. A modeling study of the phytoplankton dynamic in the Bohai Sea[D]. Qingdao: Ocean University of China, 2002.
    [7] Kuroda H, Kishi M J. A data assimilation technique applied to estimate parameters for the NEMURO marine ecosystem model[J]. Ecological Modelling, 2004, 172(1): 69−85. doi: 10.1016/j.ecolmodel.2003.08.015
    [8] Ji X L, Liu G M, Gao S, et al. Parameter sensitivity study of the biogeochemical model in the China coastal seas[J]. Acta Oceanologica Sinica, 2015, 34(12): 51−60. doi: 10.1007/s13131-015-0762-0
    [9] Losa S N, Vézina A, Wright D, et al. 3D ecosystem modelling in the North Atlantic: relative impacts of physical and biological parameterizations[J]. Journal of Marine Systems, 2006, 61(3/4): 230−245.
    [10] Fennel K, Losch M, Schröter J, et al. Testing a marine ecosystem model: sensitivity analysis and parameter optimization[J]. Journal of Marine Systems, 2001, 28(1/2): 45−63.
    [11] 王春晖. 海洋生态系统动力学模型伴随同化研究及应用[D]. 青岛: 中国海洋大学, 2013.

    Wang Chunhui. Numerical study and application of a marine ecosystem dynamical model with adjoint assimilation method[D]. Qingdao: Ocean University of China, 2013.
    [12] 俞光耀, 吴增茂, 张志南, 等. 胶州湾北部水层生态动力学模型与模拟Ⅰ. 胶州湾北部水层生态动力学模型[J]. 青岛海洋大学学报, 1999, 29(3): 421−428.

    Yu Guangyao, Wu Zengmao, Zhang Zhinan, et al. A pelagic ecosystem model and simulation of the northern part of Jiaozhou Bay Ⅰ. Introduction to pelagic ecosystem model[J]. Journal of Ocean University of Qingdao, 1999, 29(3): 421−428.
    [13] 吴增茂, 俞光耀, 张志南, 等. 胶州湾北部水层生态动力学模型与模拟Ⅱ. 胶州湾北部水层生态动力学的模拟研究[J]. 青岛海洋大学学报, 1999, 29(3): 429−435.

    Wu Zengmao, Yu Guangyao, Zhang Zhinan, et al. A pelagic ecosystem model and simulation of the northern part of Jiaozhou Bay Ⅱ. A simulation study on the pelagic ecosystem Seasonal variations[J]. Journal of Ocean University of Qingdao, 1999, 29(3): 429−435.
    [14] Zhu Hai, Cui Maochang. Coupled physical-ecological modelling of the central part of Jiaozhou Bay Ⅰ. Physical modelling[J]. Chinese Journal of Oceanology and Limnology, 2000, 18(4): 309−314. doi: 10.1007/BF02876077
    [15] Cui Maochang, Zhu Hai. Coupled physical-ecological modelling in the central part of Jiaozhou Bay Ⅱ. Coupled with an ecological model[J]. Chinese Journal of Oceanology and Limnology, 2001, 19(1): 21−28. doi: 10.1007/BF02842785
    [16] 魏皓, 赵亮, 于志刚, 等. 渤海浮游植物生物量时空变化初析[J]. 青岛海洋大学学报, 2003, 33(2): 173−179. doi: 10.3969/j.issn.1672-5174.2003.02.002

    Wei Hao, Zhao Liang, Yu Zhigang, et al. Variation of the phytoplankton biomass in the Bohai Sea[J]. Journal of Ocean University of Qingdao, 2003, 33(2): 173−179. doi: 10.3969/j.issn.1672-5174.2003.02.002
    [17] Wei Hao, Sun Jun, Moll A, et al. Phytoplankton dynamics in the Bohai Sea—observations and modelling[J]. Journal of Marine Systems, 2004, 44(3/4): 233−251.
    [18] Zhao Liang, Wei Hao. The influence of physical factors on the variation of phytoplankton and nutrients in the Bohai Sea[J]. Journal of Oceanography, 2005, 61(2): 335−342. doi: 10.1007/s10872-005-0044-0
    [19] 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. doi: 10.3969/j.issn.1009-6094.2006.04.016

    Xia Jie, Gao Huiwang. Simulation on seasonal cycle vertical structure of plankton ecosystem in eastern area of South Yellow Sea[J]. Journal of Safety and Environment, 2006, 6(4): 59−65. doi: 10.3969/j.issn.1009-6094.2006.04.016
    [20] 刘浩, 尹宝树. 渤海生态动力过程的模型研究Ⅰ. 模型描述[J]. 海洋学报, 2006, 28(6): 21−31. doi: 10.3321/j.issn:0253-4193.2006.06.004

    Liu Hao, Yin Baoshu. Model study on Bohai ecosystem Ⅰ. Model description and primary productivity[J]. Haiyang Xuebao, 2006, 28(6): 21−31. doi: 10.3321/j.issn:0253-4193.2006.06.004
    [21] 刘浩, 潘伟然. 营养盐负荷对浮游植物水华影响的模型研究[J]. 水科学进展, 2008, 19(3): 345−351. doi: 10.3321/j.issn:1001-6791.2008.03.007

    Liu Hao, Pan Weiran. Model for study on Impact of external nutrient sources on the Algalbloom[J]. Advances in Water Science, 2008, 19(3): 345−351. doi: 10.3321/j.issn:1001-6791.2008.03.007
    [22] Shchepetkin A F, McWilliams J C. The regional oceanic modeling system (ROMS): a split-explicit, free-surface, topography-following-coordinate oceanic model[J]. Ocean Modelling, 2005, 9(4): 347−404. doi: 10.1016/j.ocemod.2004.08.002
    [23] Chai F, Dugdale R C, Peng T H, et al. One-dimensional ecosystem model of the equatorial Pacific upwelling system. Part Ⅰ: model development and silicon and nitrogen cycle[J]. Deep–Sea Research Part Ⅱ: Topical Studies in Oceanography, 2002, 49(13/14): 2713−2745.
    [24] 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.v137.656
    [25] Wang Jianing, Yan Weijin, Chen Nengwang, et al. Modeled long-term changes of DIN:DIP ratio in the Changjiang River in relation to Chl-α and DO concentrations in adjacent estuary[J]. Estuarine, Coastal and Shelf Science, 2015, 166: 153−160. doi: 10.1016/j.ecss.2014.11.028
    [26] Zhang Jing. Nutrient elements in large Chinese estuaries[J]. Continental Shelf Research, 1996, 16(8): 1023−1045. doi: 10.1016/0278-4343(95)00055-0
    [27] Liu S M, Hong G H, Zhang J, et al. Nutrient budgets for large Chinese estuaries[J]. Biogeosciences, 2009, 6(10): 2245−2263. doi: 10.5194/bg-6-2245-2009
    [28] Tong Yindong, Zhao Yue, Zhen Gengchong, et al. Nutrient loads flowing into coastal waters from the main rivers of China (2006–2012)[J]. Scientific Reports, 2015, 5: 16678. doi: 10.1038/srep16678
    [29] Zielinski O, Llinás O, Oschlies A, et al. Underwater light field and its effect on a one-dimensional ecosystem model at station ESTOC, north of the Canary Islands[J]. Deep–Sea Research Part Ⅱ: Topical Studies in Oceanography, 2002, 49(17): 3529−3542. doi: 10.1016/S0967-0645(02)00096-6
    [30] Evans G T, Parslow J S. A model of annual plankton cycles[J]. Biological Oceanography, 1985, 3(3): 327−347.
    [31] Zhou Feng, Chai Fei, Huang Daji, et al. Investigation of hypoxia off the Changjiang Estuary using a coupled model of ROMS-CoSiNE[J]. Progress in Oceanography, 2017, 159: 237−254. doi: 10.1016/j.pocean.2017.10.008
    [32] Fujii M, Chai Fei. Modeling carbon and silicon cycling in the equatorial Pacific[J]. Deep–Sea Research Part Ⅱ: Topical Studies in Oceanography, 2007, 54(5/7): 496−520.
    [33] Fujii M, Boss E, Chai F. The value of adding optics to ecosystem models: a case study[J]. Biogeosciences Discussions, 2007, 4(3): 1585−1631. doi: 10.5194/bgd-4-1585-2007
    [34] Kishi M J, Kashiwai M, Ware D M, et al. NEMURO—a lower trophic level model for the North Pacific marine ecosystem[J]. Ecological Modelling, 2007, 202(1/2): 12−25.
    [35] Popova E E, Lozano C J, Srokosz M A, et al. Coupled 3D physical and biological modelling of the mesoscale variability observed in North-East Atlantic in spring 1997: biological processes[J]. Deep–Sea Research Part Ⅰ: Oceanographic Research Papers, 2002, 49(10): 1741−1768. doi: 10.1016/S0967-0637(02)00091-2
    [36] Ji Rubao, Davis C, Chen Changsheng, et al. Influence of local and external processes on the annual nitrogen cycle and primary productivity on Georges Bank: a 3-D biological–physical modeling study[J]. Journal of Marine Systems, 2008, 73(1/2): 31−47.
    [37] Kawamiya M, Kishi M J, Suginohara N. An ecosystem model for the North Pacific embedded in a general circulation model: Part Ⅰ: Model description and characteristics of spatial distributions of biological variables[J]. Journal of Marine Systems, 2000, 25(2): 129−157. doi: 10.1016/S0924-7963(00)00012-9
    [38] Lima I D, Doney S C. A three-dimensional, multinutrient, and size-structured ecosystem model for the North Atlantic[J]. Global Biogeochemical Cycles, 2004, 18(3): GB3019.
    [39] 官文江, 何贤强, 潘德炉, 等. 渤、黄、东海海洋初级生产力的遥感估算[J]. 水产学报, 2005, 29(3): 367−372.

    Guan Wenjiang, He Xianqiang, Pan Delu, et al. Estimation of ocean primary production by remote sensing in Bohai Sea, Yellow Sea and East China Sea[J]. Journal of Fisheries of China, 2005, 29(3): 367−372.
    [40] 朱兰部, 赵保仁. 渤、黄、东海透明度的分布与变化[J]. 海洋湖沼通报, 1991(3): 1−11.

    Zhu Lanbu, Zhao Baoren. Distributions and variations of the transparency in the Bohai Sea, Yellow Sea and East China Sea[J]. Transactions of Oceanology and Limnology, 1991(3): 1−11.
    [41] 高会旺, 杨华, 张英娟, 等. 渤海初级生产力的若干理化影响因子初步分析[J]. 青岛海洋大学学报, 2001, 31(4): 487−494. doi: 10.3969/j.issn.1672-5174.2001.04.004

    Gao Huiwang, Yang Hua, Zhang Yingjuan, et al. A preliminary study on factors affecting the primary production in the Bohai Sea[J]. Journal of Ocean University of Qingdao, 2001, 31(4): 487−494. doi: 10.3969/j.issn.1672-5174.2001.04.004
    [42] 洪华生. 中国区域海洋学: 化学海洋学[M]. 北京: 海洋出版社, 2012.

    Hong Huasheng. Regional Oceanography of China Seas: Chemical Oceanography[M]. Beijing: China Ocean Press, 2012.
  • 加载中
图(6) / 表(4)
计量
  • 文章访问数:  427
  • HTML全文浏览量:  25
  • PDF下载量:  203
  • 被引次数: 0
出版历程
  • 收稿日期:  2018-08-14
  • 修回日期:  2018-11-23
  • 网络出版日期:  2021-04-21
  • 刊出日期:  2019-08-25

目录

    /

    返回文章
    返回