Article(id=1246833310186492877, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1246833307606995898, articleNumber=null, orderNo=null, doi=10.3969/j.issn.0253-4193.2019.08.008, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1534176000000, receivedDateStr=2018-08-14, revisedDate=1542902400000, revisedDateStr=2018-11-23, acceptedDate=null, acceptedDateStr=null, onlineDate=1775197826190, onlineDateStr=2026-04-03, pubDate=1566662400000, pubDateStr=2019-08-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1775197826190, onlineIssueDateStr=2026-04-03, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1775197826190, creator=13701087609, updateTime=1775197826190, updator=13701087609, issue=Issue{id=1246833307606995898, tenantId=1146029695717560320, journalId=1149651085930835976, year='2019', volume='41', issue='8', pageStart='1', pageEnd='140', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1775197825576, creator=13701087609, updateTime=1775200503343, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1246844539051332282, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1246833307606995898, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1246844539051332283, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1246833307606995898, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=85, endPage=96, ext={EN=ArticleExt(id=1246833310559785945, articleId=1246833310186492877, tenantId=1146029695717560320, journalId=1149651085930835976, language=EN, title=Spatial variability of parameter sensitivity in the ecosystem simulation of the Bohai Sea and Yellow Sea, columnId=1243954927383462170, journalTitle=Haiyang Xuebao, columnName=Marine Biology, runingTitle=null, highlight=null, articleAbstract=

As the development of marine ecosystem models, the number of biological parameters increases, which consequently causes determination of these parameters to become a bottleneck in ecosystem modeling. Intrinsic regional characteristics of the ecosystem require spatial variability of biological parameters. To explore spatial difference of key parameters and their sensitivity, a highly resolved physical-biological ecosystem model ROMS-CoSiNE of the Bohai Sea and Yellow Sea is established. Sensitivity analysis of thirteen biological parameters indicates that strong difference in sensitivity exist between the south center Yellow Sea, the Bohai Sea and it’s coastal areas as well. The most sensitive parameter in the Bohai Sea is the initial slope of P-I curve. The second and third are the half saturation constant for zooplankton grazing and the maximum specific growth rate of zooplankton. For the south Yellow Sea, the most sensitive parameters are the maximum specific growth rate of zooplankton, the death rate of phytoplankton and the initial slope of P-I curve. Based on sensitivity distribution and phytoplankton budget, it is concluded that the low transparency in the Bohai Sea and high transparency in the Yellow Sea are mainly responsible for spatial difference of sensitivity relative to the initial slope of P-I curve. Spatial difference of sensitivity relative to the maximum specific growth rate of zooplankton and the death rate of phytoplankton, is affected by phytoplankton amount difference between the Bohai Sea and the Yellow Sea, and related to high nonlinearity in the ecosystem.

, correspAuthors=Haiyan Zhang, authorNote=null, correspAuthorsNote=null, copyrightStatement=Haiyang Xuebao, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Chenyi Luo, Hongtao Nie, Haiyan Zhang), CN=ArticleExt(id=1246833313369968653, articleId=1246833310186492877, tenantId=1146029695717560320, journalId=1149651085930835976, language=CN, title=渤、黄海生态环境模拟的参数敏感度空间差异分析, columnId=1243954927517679901, journalTitle=海洋学报, columnName=海洋生物, runingTitle=null, highlight=null, articleAbstract=

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。

, correspAuthors=张海彦, authorNote=null, correspAuthorsNote=
*张海彦(1987—),女,讲师,研究方向为海洋生态动力学。E-mail:
, copyrightStatement=版权所有©《海洋学报》编辑部 2023, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=6Y2OUjKOhwYXU6TsnAqu2w==, magXml=JtE7EK3GSRjwMjP2iTUACg==, pdfUrl=null, pdf=v2eoQ5Yfouvydn8f/4jDAQ==, pdfFileSize=4241037, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=hlXNSnJ5pYr3B/Se8gYzHQ==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=XXaG/muaN5k4B3xpbbR6CA==, mapNumber=null, authorCompany=null, fund=null, authors=

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:

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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., articleTitle=null, refAbstract=null), Reference(id=1254506175039463467, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833310186492877, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=42, rfOrder=53, authorNames=null, journalName=null, refType=null, unstructuredReference=洪华生. 中国区域海洋学: 化学海洋学[M]. 北京: 海洋出版社, 2012., articleTitle=null, refAbstract=null), Reference(id=1254506175286927403, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833310186492877, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=42, rfOrder=54, authorNames=null, journalName=null, refType=null, unstructuredReference=Hong Huasheng. Regional Oceanography of China Seas: Chemical Oceanography[M]. Beijing: China Ocean Press, 2012., articleTitle=null, refAbstract=null)], funds=[Fund(id=1254506153057117063, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833310186492877, awardId=null, language=CN, fundingSource=国家重点研发计划(2017YFC1404403, 2016YFC1401602);国家自然科学基金(41806018)。, fundOrder=null, country=null)], companyList=[AuthorCompany(id=1254506133436162766, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833310186492877, xref=1, ext=[AuthorCompanyExt(id=1254506133457134287, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833310186492877, companyId=1254506133436162766, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 School of Marine Science and Technology, Tianjin University, Tianjin 300072, China), AuthorCompanyExt(id=1254506133482300114, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833310186492877, companyId=1254506133436162766, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 天津大学 海洋科学与技术学院,天津 300072)])], figs=[ArticleFig(id=1254506144358130499, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833310186492877, language=EN, label=Fig. 1, caption=Bathymetry of model domain, figureFileSmall=BM1X2ls+fC+D8Fi9FIALpg==, figureFileBig=/wO/vQsWEQ7vd4BQTSVw0A==, tableContent=null), ArticleFig(id=1254506144555262791, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833310186492877, language=CN, label=图1, caption=模型区域及水深分布, figureFileSmall=BM1X2ls+fC+D8Fi9FIALpg==, figureFileBig=/wO/vQsWEQ7vd4BQTSVw0A==, tableContent=null), ArticleFig(id=1254506144861446986, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833310186492877, language=EN, label=Fig. 2, caption=Schematic of CoSiNE biological model

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

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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

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Biological parameters

, figureFileSmall=null, figureFileBig=null, tableContent=
描述 参数 取值 单位 文献来源
S1最大生长率 gmaxs1 2 d–1 [23]
S2最大生长率 gmaxs2 2.5 d–1 [23]
Z1最大捕食率 beta1 1.6 d–1 [29]
Z2最大捕食率 beta2 0.65 d–1 [30]
Z1捕食半饱和常数(以氮计) akz1 0.5 mmol/m3 [23]
Z2捕食半饱和常数(以氮计) akz2 0.25 mmol/m3 [23]
光合作用有效短波辐射 PARfrac 0.46 [29]
S1 P–I曲线初始斜率 amaxs1 0.025 d–1·(W·m–2–1 [23]
S2 P–I曲线初始斜率 amaxs2 0.025 d–1·(W·m–2–1 [23]
S1铵盐抑制系数(以氮计) pis1 5.59 mmol/m3 [23]
S2铵盐抑制系数(以氮计) pis2 4 mmol/m3 [31]
S1 硝酸盐吸收半饱和常数(以氮计) akno3s1 1 mmol/m3 [32]
S2 硝酸盐吸收半饱和常数(以氮计) akno3s2 2 mmol/m3 [6]
S1 铵盐吸收半饱和常数(以氮计) aknh4s1 0.1 mmol/m3 [33]
S2 铵盐吸收半饱和常数(以氮计) aknh4s2 0.3 mmol/m3 [34]
S1 磷酸盐吸收半饱和常数(以氮计) akpo4s1 0.065 mmol/m3 [6]
S2 磷酸盐吸收半饱和常数(以氮计) akpo4s2 0.125 mmol/m3 [6]
S2 硅酸盐吸收半饱和常数(以氮计) aksio4s2 4.5 mmol/m3 [31]
海水光吸收系数 ak1 0.036 m–1 [29]
浮游植物光吸收系数 ak2 0.11 m–1·(mmol·m–3–1 [30]
Z2 死亡率 bgamma0 0.1 d–1 [34]
Z1 捕食效率 bgamma1 0.75 d–1 [35]
Z2 捕食效率 bgamma2 0.75 d–1 [35]
S1 死亡率 bgamma3 0.2 d–1 [31]
S2 死亡率 bgamma4 0.1 d–1 [36]
碎屑分解速率 bgamma5 0.03 d–1
浮游植物凝聚速率 bgamma6 0.005 d–1
硝化速率 bgamma7 0.25 d–1 [37]
小型碎屑沉降速率 wsd 15 m·d–1 [31]
含硅碎屑沉降速率 wsdsi 25 m·d–1 [38]
S2 沉降速率 wsp 1 m·d–1 [23]
浮游植物氮磷吸收比 n2p 16 mol(以N计)/mol(以P计)
), ArticleFig(id=1254506149319992172, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833310186492877, language=CN, label=表1, caption=

生态模型参数取值

, figureFileSmall=null, figureFileBig=null, tableContent=
描述 参数 取值 单位 文献来源
S1最大生长率 gmaxs1 2 d–1 [23]
S2最大生长率 gmaxs2 2.5 d–1 [23]
Z1最大捕食率 beta1 1.6 d–1 [29]
Z2最大捕食率 beta2 0.65 d–1 [30]
Z1捕食半饱和常数(以氮计) akz1 0.5 mmol/m3 [23]
Z2捕食半饱和常数(以氮计) akz2 0.25 mmol/m3 [23]
光合作用有效短波辐射 PARfrac 0.46 [29]
S1 P–I曲线初始斜率 amaxs1 0.025 d–1·(W·m–2–1 [23]
S2 P–I曲线初始斜率 amaxs2 0.025 d–1·(W·m–2–1 [23]
S1铵盐抑制系数(以氮计) pis1 5.59 mmol/m3 [23]
S2铵盐抑制系数(以氮计) pis2 4 mmol/m3 [31]
S1 硝酸盐吸收半饱和常数(以氮计) akno3s1 1 mmol/m3 [32]
S2 硝酸盐吸收半饱和常数(以氮计) akno3s2 2 mmol/m3 [6]
S1 铵盐吸收半饱和常数(以氮计) aknh4s1 0.1 mmol/m3 [33]
S2 铵盐吸收半饱和常数(以氮计) aknh4s2 0.3 mmol/m3 [34]
S1 磷酸盐吸收半饱和常数(以氮计) akpo4s1 0.065 mmol/m3 [6]
S2 磷酸盐吸收半饱和常数(以氮计) akpo4s2 0.125 mmol/m3 [6]
S2 硅酸盐吸收半饱和常数(以氮计) aksio4s2 4.5 mmol/m3 [31]
海水光吸收系数 ak1 0.036 m–1 [29]
浮游植物光吸收系数 ak2 0.11 m–1·(mmol·m–3–1 [30]
Z2 死亡率 bgamma0 0.1 d–1 [34]
Z1 捕食效率 bgamma1 0.75 d–1 [35]
Z2 捕食效率 bgamma2 0.75 d–1 [35]
S1 死亡率 bgamma3 0.2 d–1 [31]
S2 死亡率 bgamma4 0.1 d–1 [36]
碎屑分解速率 bgamma5 0.03 d–1
浮游植物凝聚速率 bgamma6 0.005 d–1
硝化速率 bgamma7 0.25 d–1 [37]
小型碎屑沉降速率 wsd 15 m·d–1 [31]
含硅碎屑沉降速率 wsdsi 25 m·d–1 [38]
S2 沉降速率 wsp 1 m·d–1 [23]
浮游植物氮磷吸收比 n2p 16 mol(以N计)/mol(以P计)
), ArticleFig(id=1254506151157097330, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833310186492877, language=EN, label=Table 2, caption=

Sensitivity of model parameter to phytoplankton.

, figureFileSmall=null, figureFileBig=null, tableContent=
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 +
), ArticleFig(id=1254506151459087222, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833310186492877, language=CN, label=表2, caption=

浮游植物量对模型参数的敏感性

, figureFileSmall=null, figureFileBig=null, tableContent=
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 +
), ArticleFig(id=1254506151891100536, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833310186492877, language=EN, label=Table 3, caption=

Parameter sensitivity in District B and C

, figureFileSmall=null, figureFileBig=null, tableContent=
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-ispi 150.74% 1 46.36% 3
H-beta –98.50% 3 –64.57% 1
H-akz 123.57% 2 36.59% 5
H-grzf –66.17% 5 –37.16% 4
H-mort 92.24% 4 5.24% 7
H-gmax 55.01% 6 22.15% 6
H-death –40.80% 7 –55.78% 2
H-wsd –18.06% 8 1.66% 10
H-n2p 0.24% 13 2.28% 8
H-kpo4 0.65% 11 0.36% 13
H-agg –1.79% 10 –1.63% 11
H-kno3 –3.06% 9 0.44% 12
H-nitr 0.45% 12 1.7% 9
), ArticleFig(id=1254506152100815741, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833310186492877, language=CN, label=表3, caption=

B区和C区的敏感度

, figureFileSmall=null, figureFileBig=null, tableContent=
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-ispi 150.74% 1 46.36% 3
H-beta –98.50% 3 –64.57% 1
H-akz 123.57% 2 36.59% 5
H-grzf –66.17% 5 –37.16% 4
H-mort 92.24% 4 5.24% 7
H-gmax 55.01% 6 22.15% 6
H-death –40.80% 7 –55.78% 2
H-wsd –18.06% 8 1.66% 10
H-n2p 0.24% 13 2.28% 8
H-kpo4 0.65% 11 0.36% 13
H-agg –1.79% 10 –1.63% 11
H-kno3 –3.06% 9 0.44% 12
H-nitr 0.45% 12 1.7% 9
), ArticleFig(id=1254506152373445504, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833310186492877, language=EN, label=Table 4, caption=

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

, figureFileSmall=null, figureFileBig=null, tableContent=
实验 H-ispi H-beta H-death
B区 C区 B区 C区 B区 C区
PP 84.15% 27.22% –39.73% –14.07% –15.01% –15.09%
GRZ 82.58% 31.09% –28.19% 7.83% –29.20% –31.76%
MORT 84.45% 24.50% –59.39% –35.26% 14.14% 3.33%
AGG 219.87% 60.86% –73.95% –38.22% –23.02% –39.90%
BIO 939.95% 140.44% –116.27% –76.00% –30.67% 74.04%
ADV 103.11% 71.48% –78.85% –95.56% –35.68% –1.32%
DIFF 8.85% 92.53% –0.54% –110.61% 7.13% 11.79%
), ArticleFig(id=1254506152708989827, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833310186492877, language=CN, label=表4, caption=

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

, figureFileSmall=null, figureFileBig=null, tableContent=
实验 H-ispi H-beta H-death
B区 C区 B区 C区 B区 C区
PP 84.15% 27.22% –39.73% –14.07% –15.01% –15.09%
GRZ 82.58% 31.09% –28.19% 7.83% –29.20% –31.76%
MORT 84.45% 24.50% –59.39% –35.26% 14.14% 3.33%
AGG 219.87% 60.86% –73.95% –38.22% –23.02% –39.90%
BIO 939.95% 140.44% –116.27% –76.00% –30.67% 74.04%
ADV 103.11% 71.48% –78.85% –95.56% –35.68% –1.32%
DIFF 8.85% 92.53% –0.54% –110.61% 7.13% 11.79%
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渤、黄海生态环境模拟的参数敏感度空间差异分析
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罗辰奕 1 , 聂红涛 1 , 张海彦 1, *
海洋学报 | 海洋生物 2019,41(8): 85-96
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海洋学报 | 海洋生物 2019, 41(8): 85-96
渤、黄海生态环境模拟的参数敏感度空间差异分析
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罗辰奕1 , 聂红涛1, 张海彦1, *
作者信息
  • 1 天津大学 海洋科学与技术学院,天津 300072
  • 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:

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:
Spatial variability of parameter sensitivity in the ecosystem simulation of the Bohai Sea and Yellow Sea
Chenyi Luo1 , Hongtao Nie1, Haiyan Zhang1, *
Affiliations
  • 1 School of Marine Science and Technology, Tianjin University, Tianjin 300072, China
出版时间: 2019-08-25 doi: 10.3969/j.issn.0253-4193.2019.08.008
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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。

生态系统模型  /  参数敏感度  /  空间差异  /  渤海  /  黄海

As the development of marine ecosystem models, the number of biological parameters increases, which consequently causes determination of these parameters to become a bottleneck in ecosystem modeling. Intrinsic regional characteristics of the ecosystem require spatial variability of biological parameters. To explore spatial difference of key parameters and their sensitivity, a highly resolved physical-biological ecosystem model ROMS-CoSiNE of the Bohai Sea and Yellow Sea is established. Sensitivity analysis of thirteen biological parameters indicates that strong difference in sensitivity exist between the south center Yellow Sea, the Bohai Sea and it’s coastal areas as well. The most sensitive parameter in the Bohai Sea is the initial slope of P-I curve. The second and third are the half saturation constant for zooplankton grazing and the maximum specific growth rate of zooplankton. For the south Yellow Sea, the most sensitive parameters are the maximum specific growth rate of zooplankton, the death rate of phytoplankton and the initial slope of P-I curve. Based on sensitivity distribution and phytoplankton budget, it is concluded that the low transparency in the Bohai Sea and high transparency in the Yellow Sea are mainly responsible for spatial difference of sensitivity relative to the initial slope of P-I curve. Spatial difference of sensitivity relative to the maximum specific growth rate of zooplankton and the death rate of phytoplankton, is affected by phytoplankton amount difference between the Bohai Sea and the Yellow Sea, and related to high nonlinearity in the ecosystem.

ecosystem model  /  parameter sensitivity  /  spatial variability  /  Bohai Sea  /  Yellow Sea
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. 海洋学报, 2019 , 41 (8) : 85 -96 . DOI: 10.3969/j.issn.0253-4193.2019.08.008
Chenyi Luo, Hongtao Nie, Haiyan Zhang. 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
近年来,海洋生态系统模型逐渐成为研究复杂海洋生态环境的重要手段。然而,随着生态系统模型发展的逐渐复杂化,模型中生态参数增多且量值难以确定,逐渐成为限制其模拟能力的瓶颈[1-2]。因此,确定影响模型结果的关键生态参数,可为模型调试及参数优化提供方向。在过去的几十年里,以浮游植物生物量变化对参数变化的响应进行的敏感性分析被广泛应用,是一种确定模型关键参数的有效手段[3]。Kishi等[4]通过在日本美川湾建立的生态模型得出模型中光合作用速率和浮游动植物的自然死亡率十分重要。高会旺等[5]在渤海建立了NPZD模型并提出浮游植物最大生长率、海水消光系数、浮游动物对浮游植物最大捕食率、捕食效率和碎屑的再矿化率是影响渤海水层生态系统年循环的主要因子。赵亮[6]在渤海建立浮游植物生态动力学模型,基于敏感性分析实验提出浮游植物最大生长率、浮游植物基础呼吸率、浮游植物死亡率、浮游动物捕食率、水底碎屑矿化率等参数比较敏感。Kuroda和Kishi[7]基于蒙特卡洛算法和主成分分析在北太平洋生态模型约80个模型参数中选出了8个影响最大的参数,包括0℃时的浮游植物光合作用速率、浮游动物死亡率、浮游植物死亡率和浮游动物捕食速率以及浮游植物吸收硝酸盐半饱和常数等几种。Ji等[8]在中国近海及邻近北太平洋建立一个研究碳循环的模型并指出浮游动物吸收速率、浮游动物最大生长率(20℃时)以及浮游动物基础代谢率是模型中的敏感参数。以上研究表明,不同海域生态模型的关键生态参数存在差异,即不同海域需要关注的关键生态参数有所不同。这是由于不同海区的生态系统结构不同,生态参数具有空间变化[2, 9]。而目前的生态系统模型,参数值大多来自文献或实验室实验结果且一般在整个海区取一个常数,关于生态参数区域性的研究较少[10-11]。因此,了解关键参数的空间分布及区域特征,可为日后实现生态参数取值的空间变化奠定基础。
渤海和黄海是我国重要的半封闭陆架海,沿海地区人口和工业生产高度集中,具有陆源输入量大、海水交换差、初级生产力高等特点,是历年来的研究热点,海洋生态系统模型逐步发展并走向环境管理应用[5, 6, 12-21]。但以往研究中,并未考虑关键生态参数的空间差异。因此,本课题组在渤海、黄海建立并校验高分辨生态动力学模型,本文应用该模型对生态参数进行敏感性分析,探究影响浮游植物生物量的关键生态参数的空间分布,并通过收支计算定量地分析这些关键生态参数的敏感度出现空间差异的原因,为后续生态模型参数优化提供参考。
本文使用温度、盐度、叶绿素等现场观测数据对模型进行校验。校验数据包括2011年3月和2013年6月航次观测的温度和盐度,2012年6月、8月及2013年6月、7月、8月和9月航次观测的叶绿素数据。
本次研究使用的水动力模型为三维斜压原始方程模式ROMS[22](Regional Ocean Modelling System)。模型研究的区域为29.85°~41.18°N,117.27°~127.36°E,覆盖全部渤海、黄海及邻近东海区域(图1)。模型水平分辨率为(1/24)°×(1/24)°,垂向分为30层,采用Mello-Yamada 2.5阶湍流闭合方案。耦合的生态模式是CoSiNE[23](The Carbon, Silicate and Nitrogen Ecosystem),包含两种浮游植物(小型浮游植物S1、硅藻S2)、两种浮游植物对应的叶绿素(小型浮游植物对应的叶绿素Chl1、大型浮游植物对应的叶绿素Chl2)、两种大小的浮游动物(小型浮游动物Z1、中型浮游动物Z2)、含氮碎屑、含硅碎屑、硝酸盐、铵盐、硅酸盐、磷酸盐、溶解无机碳、海水总碱度和溶解氧,模型示意图如图2所示。这些变量都受对流、扩散等物理过程影响。
模型中温度、盐度、无机氮、无机磷、无机硅和溶解氧的初始场数据为来自WOA13 V2(World Ocean Atlas 2013 V2)。叶绿素初始条件来自NEMO-PISCES全球模型结果(http://marine.copernicus.eu/services-portfolio/)。大气强迫数据来自ERA-Interim再分析资料[24],包括风应力、热通量、太阳辐射以及淡水通量等。开边界温盐、流速和水位数据来自HYCOM(Hybrid Coordinate Ocean Model, https://hycom.org/)全球再分析结果。开边界处的潮汐数据由OTPS的INDIAN Ocean(中国海&印度尼西亚2016)模型计算所得,包括M2、S2、K2、N2、K1、O1、Q1及P1等8个分潮的潮位和潮流数据。营养盐、叶绿素和溶解氧的开边界条件来自NEMO-PISCES全球模型月均结果。模型涵盖长江、钱塘江、淮河、黄河、海河、辽河、滦河、鸭绿江和汉江,其中长江的径流量数据来自大通站的观测结果,营养盐数据来自Global-News Model每月的数据[25]。其他河流的径流量和营养盐数据来自文献[26-28]。生态模式参数取值如表1所示,后续敏感性分析实验均以该取值为调整基础。模型从2006年1月1日开始运行至2013年12月31日,一共运行8年,考虑到模型的稳定时间,本文将分析2009年以后模型的结果。
本文对模型进行初步校验之后,选取浮游植物P-I曲线初始斜率、浮游动物最大捕食率、浮游动物捕食半饱和常数、浮游动物捕食效率、浮游动物死亡率、浮游植物最大生长率、浮游植物死亡率、沉降速率、浮游植物生长所需氮磷比、浮游植物生长磷酸盐半饱和常数、浮游植物凝结速率、浮游植物生长硝酸盐半饱和常数以及硝化速率等涉及浮游植物生长和死亡、浮游动物捕食和死亡、硝化过程等主要生物过程的13种参数,并将各参数值增大50%进行敏感性实验。其中由于浮游动物捕食效率的最大值为1,所以在调整时将该参数调整至上限,即增大33%进行试验。本文将总浮游植物量(包括小型浮游植物和硅藻)作为评价模型生态参数敏感度的指标。评价生态参数敏感度的公式如下[8]
${S_{c,x}} = \frac{{{C_x} - {C_{x + \% }}}}{{{C_x}}}\bigg/\frac{{{{X}} - {{{X}}_{ + \% }}}}{{{X}}},$
式中,Sc, x 为敏感度,下标x代表各个参数,X为基础实验中参数值,X +%为参数增加50%(33%)以后的值;Cx 为基础实验全年积分浮游植物生物量,Cx+% 为参数调整之后的全年积分浮游植物生物量。
图3给出了温度及盐度的模拟结果和现场观测的对比。在2011年春季(3月),模型模拟的表底温度及盐度分布一致,垂向混合较为均匀,济州岛东北侧的表底层均呈现表征黄海暖流的高温、高盐水,均与观测相符。在2013年夏季(6月),海表温度显著高于春季,底层黄海冷水团形成。与春季相比,渤海、黄海夏季盐度有所降低。此外,长江冲淡水在向东扩展。总体上,模型可以较好地捕捉到温度和盐度的时空分布,且分别与观测存在较高的相关性 (相关系数分别为0.93和0.80)。
本研究将表层叶绿素作为模型生态场校验的变量。模型结果及现场观测(图4)均显示,河口及近岸海域叶绿素浓度较高。在时间分布上,7月和8月叶绿素浓度较高。模型得到的叶绿素浓度略低于观测结果,但分布趋势与观测一致,特别体现了黄海潮汐锋区及长江冲淡水影响范围内的高叶绿素分布,这与中国生态系统研究多年来基于观测对黄海和东海叶绿素分布的理解是完全一致的,将在另文中仔细分析其动力过程。总体上,基础实验中建立的生态动力学模型基本可以模拟出表层叶绿素的时空分布特征。
表2给出了水体积分的浮游植物现存量关于不同参数在整个模型区域的平均敏感度。根据敏感度绝对值大小,可将参数划分为+++/– – –(特别敏感,|敏感度|≥100%),++/––(较为敏感,20%≤|敏感度|<100%)和+/–(一般敏感,|敏感度|<20%)3类。在实验的13种参数中,浮游植物量对浮游植物P-I曲线初始斜率敏感度最高。浮游植物P-I曲线初始斜率增大50%后,浮游植物量增加了约75%,敏感度可达150%左右。其次,与浮游动物捕食相关的参数及浮游动物死亡率对浮游植物量也有显著影响。其中,浮游动物最大捕食率及浮游动物捕食半饱和常数增大50%,浮游植物量减少了约50%,对应的敏感度分别为–105.81%和92.84%。浮游植物量对浮游动物的死亡率及其捕食效率的变化也较为敏感,敏感度均大于70%。与浮游动物相关参数相比,浮游植物最大生长率及死亡率升高引起的浮游植物量变化则相对较小,分别为24.93%和–24.39%,对应敏感度为49.85%和–48.77%,也较为敏感。此外,浮游植物生长对碎屑及浮游植物沉降速率、硝化速率等以及与营养盐相关的浮游植物对硝酸盐、磷酸盐等吸收的半饱和浓度的敏感度偏低(敏感度<12%)。
总体上,敏感度较大的参数包括与浮游植物生长光限制相关的浮游植物P-I曲线初始斜率、与浮游动物量相关的浮游动物捕食率、死亡率等以及与浮游植物自身有关的生长率、死亡率三类。与前人研究相比,高会旺等[5]在渤海建立模型并得出浮游植物最大生长率、海水消光系数、浮游动物对浮游植物最大捕食率、捕食效率和碎屑的再矿化率较为敏感,随后赵亮[6]也在渤海建立了一个浮游植物生态动力学模型,提出浮游植物最大生长率、浮游植物基础呼吸率、浮游植物死亡率、浮游动物捕食率、水底碎屑矿化率等参数比较敏感,Ji等[8]在中国近海及邻近太平洋的研究中认为模型敏感参数为浮游动物吸收速率、浮游动物基础代谢速率及浮游动物最大生长率(20℃时)等。虽然由于模型配置以及研究海区区别,敏感参数存在一定差异,但是模型的主要关键参数均为与浮游植物及浮游动物生长和死亡直接相关的生态参数。
在空间分布上,生态参数敏感度存在显著差异(图5)。13种参数的敏感性试验中,浮游植物P-I曲线初始斜率引起的敏感度的空间差异最大(标准偏差0.88)。该参数在渤海及黄海30 m以浅的区域水体积分浮游植物量的敏感度可达100%,而在黄海中部敏感度则相对较小,小于50%,其中甚至在海州湾外侧敏感度出现负值(约–30%)。类似的,浮游植物量对浮游动物死亡率、最大捕食率、捕食半饱和常数和捕食效率的敏感度均在黄海中部较小,且该区与其他区域敏感度情况存在较大差异。其中浮游动物的死亡率升高,摄取的浮游植物减少,但黄海中部的浮游植物没有增加反而减少,这一现象也体现了生态系统的非线性性和复杂性,浮游植物量受多种因素调控。此外,对比调整浮游植物最大生长率与调整浮游植物P-I曲线初始斜率之后的敏感度空间分布图可以看到两者空间分布特点较为相似,前者同样在渤海及黄海近岸区域存在较大值,其中长江口、苏北浅滩、渤海沿岸及中部浅滩的敏感度达到90%以上,而在黄海中部敏感度较低,甚至出现负值,只是整体上前者敏感度不如后者大。这一结果也体现了光在渤海、黄海海区对于浮游植物生长的重要性。对于浮游植物死亡率增大实验,大部分区域的敏感度为负值,而在渤海辽东浅滩周围洼地、南黄海沿岸区域的敏感度为正值,且达到50%以上,表明浮游植物量显著增加,浮游植物生长增多。对于不是十分敏感的参数如碎屑及浮游植物沉降速率、硝化速率等以及与营养盐相关的浮游植物对磷酸盐等吸收的半饱和浓度等参数,也呈现出空间差异特征,这些参数敏感度均较低,这里不再进行详细描述。
为量化敏感度的区域差异,及定量诊断物理及生物过程对敏感度区域差异的影响,本文选取了两个代表性区域,渤海(B区)及黄海中部区域(C区)(图1),并给出了两个区的参数敏感度(表3)。B区和C区敏感度较大的参数存在差异,B区最敏感的3个参数为浮游植物P-I曲线初始斜率、浮游动物捕食半饱和常数和浮游动物最大捕食率。而C区则为浮游动物捕食率、浮游植物死亡率和浮游植物P-I曲线初始斜率。此外,B区中大部分参数的敏感度要显著高于C区,如B区中浮游植物P-I曲线初始斜率敏感度为150%,而C区敏感度只有46%,不到B区敏感度值的1/3。C区中仅3个参数的敏感度略大于B区,如对于浮游植物死亡率,C区敏感度为–55.78%,大于B区的–40.80%。
为探究浮游植物现存量对生态参数敏感度出现空间差异的原因,本文选取敏感度较大且区域差异也较大的3个参数—浮游植物P-I曲线初始斜率、浮游动物最大捕食速率及浮游植物死亡率,计算这些参数实验中B区和C区浮游植物生物量收支情况。模型中描述浮游植物变化的公式如下[23]
$\frac{{\partial S}}{{\partial t}} = ADV + DIFF + PP - GRZ - MORT - AGG,$
式中,S表示浮游植物,ADV为对流项影响,DIFF为扩散项影响,PP为初级生产项,GRZ代表浮游动物捕食项,MORT是浮游植物死亡项,AGG为浮游植物聚集成碎屑项。
从浮游植物量的年收支(图6)可以看出,净初级生产项、死亡项和浮游动物捕食项为浮游植物量最主要的源汇项。总体上C区的浮游植物初级生产高于B区,即南黄海水体积分的初级生产力高于渤海,这与官文江等[39]通过卫星遥感数据反演得到的初级生产力分布趋势一致。此外,由于浮游植物生长、死亡以及被捕食等存在显著的季节循环过程,生物过程导致的净浮游植物变化量远远小于各个生物源汇项大小。此外,可以看到物理输运过程在B区表现为浮游植物的汇,在C区为源项,但其量值远远小于各生物源汇项。
在H-ispi实验中,增大浮游植物P-I曲线初始斜率意味着提高了光合作用过程对光的转化效率,也即减弱了光对浮游植物生长的限制。相对于基础试验,调整参数以后B区PP项增大了84.15%,C区增大了27.22%(表4)。两个区域的初级生产均出现明显增加,且B区较C区相对增加更多,与B区敏感度较大相对应。这一结果表明虽然近海普遍存在光限制,但是B区的浮游植物光限制程度要高于C区。这与渤海透明度低于南黄海透明度,且渤海水体光衰减较强以及渤海区海水透明度在很大程度上决定了初级生产力的变化趋势的认识相符[40-41]。同时,也与模型得到的渤海营养盐浓度总体高于南黄海相对应,即C区的营养盐限制要高于B区,与文献[42]结果一致。因此当整个海域光限制程度降低时,B区浮游植物增长更加显著。受初级生产力的影响,B区GRZ项、MORT项及AGG项的变化也均大于C区。总的来说,浮游植物生长光限制的强弱程度是浮游植物量对浮游植物P-I曲线初始斜率的敏感度存在空间差异的重要原因。这也说明模型中不同水体类型(不同海水透明度)的参数化过程将是影响初级生产力模拟的重要原因,合理按区域给出与光相关影响浮游植物生长的参数十分重要。
在H-beta实验中,浮游动物最大捕食率的增大将直接引起系统浮游植物量的减少,进而对其他过程造成影响。由于B区和C区的浮游植物生物量不同,及生态过程中存在高度非线性,B区和C区初级生产项的降低幅度并不相同(表4),B区降低39.73%(由1.30×104 mmol/m2降低至0.79×104 mmol/m2),C区降低14.07%(由4.34×104 mmol/m2降低至3.72×104 mmol/m2)。这一变化差异也直接影响了两个区域GRZ项的变化,对于B区,由于H-beta实验的PP项已减少至比原基础实验GRZ项(0.84×104 mmol/m2)还少,而从生态系统结构上讲,GRZ项的量须小于PP项,因此B区的GRZ项在H-beta实验中势必减小;对于C区,尽管该区域PP项也出现了下降,但由于下降幅度较小且浮游动物捕食率增大了50%,最终C区的GRZ项略有增大(7.83%)。总的来说,B区和C区GRZ项的变化受两个区域初级生产项的变化影响,主要是由高度非线性的生态过程决定的。此外,对应浮游植物初级生产的减少,B区和C区的浮游植物死亡量以及聚集成碎屑的量均出现了明显的降低,且B区降低幅度更低。相应地,B区的敏感度大于C区。综上所述,增大捕食率对初级生产较低的渤海影响较大,这与生态系统的高度非线性有关。
在H-death实验中,浮游植物死亡率增大50%之后,B区与C区的生态过程源项(PP项)降低幅度基本相同(分别为15.01%和15.09%,表4),B区PP项由1.30×104 mmol/m2降低至1.11×104 mmol/m2,C区PP由4.34×104 mmol/m2降低至3.69×104 mmol/m2,与前两个实验中两个区域PP项的变化趋势有所差异。而对于生物过程的汇项(GRZ项,MORT项,AGG项),C区的GRZ项和AGG项两项(–31.76%,–39.90%)比B区(29.20%,–23.02%)均相对于基础实验减少得更多,而且虽然两个区域的MORT项相对于基础实验都有增加,但是C区(3.33%)的增加的幅度小于B区(14.14%),整体看来B区生物汇项(由1.28×104 mmol/m2降低至1.09×104 mmol/m2,–14.68%)的变化幅度大于C区(由4.39×104 mmol/m2降低至3.77×104 mmol/m2, –14.10%)。对于整个生物过程,也即BIO项,基于表4可以看到两个海区的变化率相反。经计算两个区域生态过程源汇项的改变对BIO项的影响,B区源项改变 $\left( {\displaystyle\frac{{\Delta PP}}{{BI{O_{\rm {Baseline}}}}}} \right)$ BIO变化的影响为–737.03%,汇项改变 $\left( {\displaystyle\frac{{\Delta (GRZ + MORT + AGG)}}{{BI{O_{\rm {Baseline}}}}}} \right)$ BIO变化的影响约为706.37%;C区源项改变对BIO变化的影响为1 398%,汇项改变对BIO变化的影响约为1 323.95%。可以看出B区、C区均是由源项主导了BIO的变化,也即BIO应该呈现下降的趋势。然而,由于B区BIO项在数值上为正值而C区是负值,所以在计算变化率时C区由于负负得正得出与B区符号相反的变化率。不仅如此,基于图6也可以看到H-death实验中C区的BIO项相对于基础实验出现了下降,且变化幅度大于B区,从而引起两个区域的敏感度出现差异。总的来说,这一结果的出现主要受两个区域的生态源项也即初级生产项的影响,体现了生态过程的非线性特征。
本文在渤海、黄海建立ROMS-CoSiNE高分辨率生态系统模型,并利用观测数据对物理和生态要素模拟进行校验。在此基础上,对13种生态参数敏感度进行计算。整体上,影响渤海、黄海区域关键生态参数为浮游植物P-I曲线初始斜率、浮游动物最大捕食率、浮游动物捕食半饱和常数、浮游动物捕食效率、浮游动物死亡率和浮游植物最大生长率。生态参数敏感度存在显著空间差异,主要表现为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。
通过对浮游植物P-I曲线初始斜率、浮游动物最大捕食率以及浮游植物死亡率实验中浮游植物量收支的估算及分析得出,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到渤海、黄海浮游植物生物量的影响,与生态系统的高度非线性特征有关。
文中对关键生态参数及参数敏感度空间差异的认识,将为下一步选择优化参数提供方向。同时,可为近海生态模型参数分海区取值提供参考,如根据水体类型给出与浮游植物生长相关的水体光限制因子等。
  • 国家重点研发计划(2017YFC1404403, 2016YFC1401602);国家自然科学基金(41806018)。
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2019年第41卷第8期
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doi: 10.3969/j.issn.0253-4193.2019.08.008
  • 接收时间:2018-08-14
  • 首发时间:2026-04-03
  • 出版时间:2019-08-25
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  • 收稿日期:2018-08-14
  • 修回日期:2018-11-23
基金
国家重点研发计划(2017YFC1404403, 2016YFC1401602);国家自然科学基金(41806018)。
作者信息
    1 天津大学 海洋科学与技术学院,天津 300072

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*张海彦(1987—),女,讲师,研究方向为海洋生态动力学。E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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