Article(id=1212062513764626843, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1212062510887342132, articleNumber=null, orderNo=null, doi=10.12284/hyxb2023120, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1678982400000, receivedDateStr=2023-03-17, revisedDate=1682179200000, revisedDateStr=2023-04-23, acceptedDate=null, acceptedDateStr=null, onlineDate=1766907822314, onlineDateStr=2025-12-28, pubDate=1696003200000, pubDateStr=2023-09-30, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1766907822314, onlineIssueDateStr=2025-12-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1766907822314, creator=13701087609, updateTime=1766907822314, updator=13701087609, issue=Issue{id=1212062510887342132, tenantId=1146029695717560320, journalId=1149651085930835976, year='2023', volume='45', issue='9', pageStart='1', pageEnd='188', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1766907821628, creator=13701087609, updateTime=1766924706207, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1212133329994904375, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1212062510887342132, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1212133329994904376, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1212062510887342132, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=105, endPage=118, ext={EN=ArticleExt(id=1212062514033062308, articleId=1212062513764626843, tenantId=1146029695717560320, journalId=1149651085930835976, language=EN, title=Energy flow characteristics of the food web in the northern waters of Jiangsu Province based on LIM-MCMC model, columnId=1194652705852465724, journalTitle=Haiyang Xuebao, columnName=Article, runingTitle=null, highlight=null, articleAbstract=

Study on the structure and energy flow of food webs is important for maintaining the stability of structure and function of marine ecosystems, which will contribute to the in-depth understanding of the complex processes of marine ecosystems. Based on the seasonal bottom trawl survey data in the northern waters of Jiangsu Province from 2019−2021, a linear inverse models using a Monte Carlo method coupled with Markov chain model combined with ecological network analysis (ENA) were used to explore the status of the ecosystem and energy flow characteristics of the food web in this area. The results showed that there were 299 energy flow paths in the ecosystem, which showed a typical pyramid structure. In addition, the energy consumed by respiration and the energy flowing into the detritus of each functional group remains synchronized. Compared with other sea areas, connectance (C) and system omnivory index (SOI) were 0.40 and 0.22, respectively, which were at relatively high levels, indicating that organisms from different trophic levels in this ecosystem were closely connected. It has a relatively complex food web structure, which can resist external disturbance. Total primary production/total respiration (TPP/TR) and Finn’s cycling index (FCI) were 1.05 and 5.76%, respectively, indicating that the ecosystem was relatively mature and used energy efficiently. In addition, constraint efficiency (CE), extent of development (AC), synergism index (b/c) and dominance indirect effects (i/d) also indicated high potential for development and regeneration. This study will provide a theoretical basis for the restoration and sustainable utilization of fishery resources in the northern waters of Jiangsu Povince, and provide a scientific basis for the implementation of Ecosystem-based fishery management in this area.

, correspAuthors=Ying Xue, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright © 2023 Pratacultural Science. All rights reserved., 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=Hu Zhang, Pengcheng Li, Haisheng Hu, Ying Xue, Jianmei Yuan, Chengkai Ben, Chaowen Zhu, Yueyue Xiao, Kaiwei Zu), CN=ArticleExt(id=1212062515127775699, articleId=1212062513764626843, tenantId=1146029695717560320, journalId=1149651085930835976, language=CN, title=基于LIM-MCMC模型研究江苏近海北部海域食物网能量流动特征, columnId=1149698756456657529, journalTitle=海洋学报, columnName=论文, runingTitle=null, highlight=null, articleAbstract=

食物网结构特征和能量流动的研究,对于维持海洋生态系统结构和功能的稳定具有重要意义,有助于深入理解海洋生态系统的复杂过程。本研究基于2019−2021年在江苏近海北部海域开展的季节性渔业资源底拖网调查数据,通过构建基于蒙特卡罗马尔科夫链算法的逆线性模型(Linear Inverse Models using a Monte Carlo Method Coupled with Markov Chain, LIM-MCMC),结合生态网络分析(Ecological Network Analysis,ENA)的方法,分析了该海域生态系统状态和食物网能量流动特征,旨在为江苏近海北部海域食物网营养动力学研究提供参考依据。结果表明,该海域生态系统共包含299条能量流动路径,能量流动分布整体呈典型的金字塔结构,各功能群呼吸消耗和流入有机碎屑的能量保持同步性。通过与其他海域比较发现,江苏近海北部海域生态系统的连接指数(Connectance,C)和系统杂食指数(System Omnivory Index,SOI)分别为0.40和0.22,处于较高水平,表明该生态系统不同营养级间的营养联系较为紧密,食物网结构相对复杂,能够在较大程度上抵御外界扰动。总初级生产力/总呼吸(Total Primary Production/Total Respiration,TPP/TR)和Finn’s循环指数(Finn’s Cycling Index,FCI)分别为1.05和5.76%,表明该生态系统对能量利用效率较高。此外,约束效率(Constraint Efficiency,CE)、发展程度(Extent of Development,AC)、协同效应指数(Synergism Index,b/c)和主导间接效应(Dominance Indirect Effects,i/d)也表明该生态系统具有较高的系统发展程度、再生潜力和系统发展空间。本研究将有助于为江苏近海北部海域生态系统的修复和渔业资源的可持续利用提供理论基础,为实施基于生态系统的渔业管理提供科学依据。

, correspAuthors=薛莹, authorNote=null, correspAuthorsNote=
*薛莹,男,教授,主要从事渔业资源生物学、渔业生态学等领域的研究。E-mail:
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张虎(1980-),男,江苏省新沂市人,正高级工程师,从事海洋生态与渔业资源研究。E-mail:

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张虎(1980-),男,江苏省新沂市人,正高级工程师,从事海洋生态与渔业资源研究。E-mail:

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张虎(1980-),男,江苏省新沂市人,正高级工程师,从事海洋生态与渔业资源研究。E-mail:

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• Benthic survey stations; + nekton, zooplankton and phytoplankton survey stations

, figureFileSmall=RITRBWeNOUpaU/2c1FO/OA==, figureFileBig=8AZ9iv1yMDFR2RIh0Wx5rg==, tableContent=null), ArticleFig(id=1215325222090232802, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=CN, label=图1, caption=江苏近海北部海域采样站位分布

•为底栖生物调查站位;+为游泳生物、浮游动物和浮游植物调查站位

, figureFileSmall=RITRBWeNOUpaU/2c1FO/OA==, figureFileBig=8AZ9iv1yMDFR2RIh0Wx5rg==, tableContent=null), ArticleFig(id=1215325222182507495, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=EN, label=Fig. 2, caption=Energy flow characteristics of food webs in northern sea areas of Jiangsu Province

G1−G26 represents 26 functional groups; blue for respiration, gray for CO2, tomato colour for I trophic level, orange colour for II −III trophic level, red trophic level for III− IV trophic level, yellow for IV−Ⅴ trophic level; the magnitude of circle represents the energy flow value;→ indicates the direction of energy flow

, figureFileSmall=WpckQrPUnbONdFwrPbDUMQ==, figureFileBig=dtWVqVBke1D8bNEPI0OboA==, tableContent=null), ArticleFig(id=1215325222262199275, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=CN, label=图2, caption=江苏近海北部海域食物网能量流动特征

G1−G26表示26个功能群;蓝色表示呼吸,灰色表示CO2,番茄色表示第I营养级,橘黄色表示第II −III营养级,红色表示第III− IV营养级,黄色表示第 IV−Ⅴ营养级;圆圈大小表示能量流动值;→表示能量流入方向

, figureFileSmall=WpckQrPUnbONdFwrPbDUMQ==, figureFileBig=dtWVqVBke1D8bNEPI0OboA==, tableContent=null), ArticleFig(id=1215325222350279663, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=EN, label=Fig. 3, caption=Energy flow of food webs in northern areas of Jiangsu Province (The number of energy flows see Fig. A1), figureFileSmall=JU4aYjgWaZO1iztxaT6rrg==, figureFileBig=R0zFYMgz0Fgik9t6Xt9QwQ==, tableContent=null), ArticleFig(id=1215325222417388531, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=CN, label=图3, caption=江苏近海北部海域食物网能量流动路径分析(能量流动编号见表A1), figureFileSmall=JU4aYjgWaZO1iztxaT6rrg==, figureFileBig=R0zFYMgz0Fgik9t6Xt9QwQ==, tableContent=null), ArticleFig(id=1215325222488691703, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=EN, label=Fig. 4, caption=Respiratory consumption and energy flow to detritus by functional groups of the food web in northern sea areas of Jiangsu Province, figureFileSmall=jidehqPQ1CJl14SGOg5SKA==, figureFileBig=LWvIN1lkjs/ZAlsV8GE38Q==, tableContent=null), ArticleFig(id=1215325222576772094, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=CN, label=图4, caption=江苏近海北部海域食物网各功能群呼吸消耗和流入碎屑的能流值, figureFileSmall=jidehqPQ1CJl14SGOg5SKA==, figureFileBig=LWvIN1lkjs/ZAlsV8GE38Q==, tableContent=null), ArticleFig(id=1215325222681628677, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=EN, label=Table 1, caption=

Ecological network analysis (ENA) indices

, figureFileSmall=null, figureFileBig=null, tableContent=
生态网络分析指数类型指数名称简称
基本指数生态系统总流量TST
总呼吸量TR
流向碎屑的能量TDET
系统杂食指数SOI
总初级生产量TPP
总初级生产力/总呼吸TPP/TR
总初级生产力/总生物量TPP/TB
连接数L
连接指数C
平均连接权重TST/L
平均隔间流通量TST/n
路径分析总系统循环流量TSTc
系统非循环总流量TSTs
Finn’s循环指数FCI
平均路径长度APL
网络不确定性平均相互信息AMI
统计不确定性HR
条件的不确定性DR
实现的不确定性RUR
网络约束HC
约束效率CE
系统发展和增长优势度A
开发能力DC
发展程度AC
环境分析同质化HP
协同效应指数b/c
主导间接效应i/d
营养和杂食性水平营养级TL
杂食指数OI
), ArticleFig(id=1215325222778097672, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=CN, label=表1, caption=

生态网络分析指数

, figureFileSmall=null, figureFileBig=null, tableContent=
生态网络分析指数类型指数名称简称
基本指数生态系统总流量TST
总呼吸量TR
流向碎屑的能量TDET
系统杂食指数SOI
总初级生产量TPP
总初级生产力/总呼吸TPP/TR
总初级生产力/总生物量TPP/TB
连接数L
连接指数C
平均连接权重TST/L
平均隔间流通量TST/n
路径分析总系统循环流量TSTc
系统非循环总流量TSTs
Finn’s循环指数FCI
平均路径长度APL
网络不确定性平均相互信息AMI
统计不确定性HR
条件的不确定性DR
实现的不确定性RUR
网络约束HC
约束效率CE
系统发展和增长优势度A
开发能力DC
发展程度AC
环境分析同质化HP
协同效应指数b/c
主导间接效应i/d
营养和杂食性水平营养级TL
杂食指数OI
), ArticleFig(id=1215325222912315403, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=EN, label=Table 2, caption=

Functional groups division and basic parameters of LIM-MCMC model in northern sea areas of Jiangsu Province

, figureFileSmall=null, figureFileBig=null, tableContent=
功能群生物量/(t·km−2·a−1生产量/生物量(P/B消耗量/生物量(Q/B排泄量/生物量(U/B呼吸量/生物量(R/B营养级杂食指数
注:“−”代表无数据。
G1 长蛇鲻0.0021.526.000.10~0.500.50~0.524.190.242
G2 星康吉鳗0.0024.607.600.10~0.500.50~0.524.080.259
G3 黄鮟鱇0.0011.16~1.261.40~3.800.10~0.500.50~0.524.310.136
G4 虾虎鱼科0.0991.594.700.10~0.500.52~0.553.390.156
G5 鲆鲽类0.0150.74~1.465.60~16.100.10~0.500.52~0.553.460.219
G6 石首鱼科0.1721.15~4.605.90~9.100.10~0.500.52~0.553.640.371
G7 鳀科0.0962.37~2.705.980.10~0.500.52~0.553.080.190
G8 其他底层鱼类0.0791.45~2.904.23~9.900.10~0.500.52~0.553.360.378
G9 其他中上层鱼类0.0230.46~2.373.10~18.700.10~0.500.52~0.553.250.376
G10 近底层鱼类0.0410.63~3.264.80~9.000.10~0.500.52~0.553.290.400
G11 蟹类0.6643.5012.000.10~0.500.55~0.752.900.460
G12 口虾蛄0.7261.34~8.007.43~30.000.10~0.500.52~0.553.200.386
G13 戴氏赤虾0.0063.90~5.6515.00~26.900.10~0.500.52~0.553.020.301
G14 细鳌虾0.0713.7524.900.10~0.500.55~0.752.660.245
G15 鹰爪虾0.0611.8413.000.10~0.500.55~0.752.990.154
G16 长臂虾科0.3727.6925.000.10~0.500.55~0.752.880.161
G17 其他虾类0.3818.00~8.8028.00~30.000.10~0.500.55~0.752.820.112
G18 头足类0.0242.00~4.507.00~17.000.10~0.500.52~0.553.610.466
G19 其他头足类0.0034.5917.550.10~0.500.52~0.553.450.198
G20 棘皮动物0.3651.20~4.503.58~16.700.10~0.500.55~0.752.520.301
G21 软体动物29.8696.0027.000.10~0.500.55~0.752.030.025
G22 底栖动物2.9441.57~5.008.60~20.000.10~0.500.55~0.752.030.151
G23 尖海龙0.0052.305.980.10~0.500.55~0.752.850.014
G24 浮游动物2.27125.00~40.00122.10~180.030.10~0.500.70~0.932.000.014
G25 浮游植物20.673106.520.05~0.500.05~0.301.000.000
G26有机碎屑51.9121.000.000
), ArticleFig(id=1215325223008784400, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=CN, label=表2, caption=

江苏近海北部海域功能群划分及LIM-MCMC模型的基本参数

, figureFileSmall=null, figureFileBig=null, tableContent=
功能群生物量/(t·km−2·a−1生产量/生物量(P/B消耗量/生物量(Q/B排泄量/生物量(U/B呼吸量/生物量(R/B营养级杂食指数
注:“−”代表无数据。
G1 长蛇鲻0.0021.526.000.10~0.500.50~0.524.190.242
G2 星康吉鳗0.0024.607.600.10~0.500.50~0.524.080.259
G3 黄鮟鱇0.0011.16~1.261.40~3.800.10~0.500.50~0.524.310.136
G4 虾虎鱼科0.0991.594.700.10~0.500.52~0.553.390.156
G5 鲆鲽类0.0150.74~1.465.60~16.100.10~0.500.52~0.553.460.219
G6 石首鱼科0.1721.15~4.605.90~9.100.10~0.500.52~0.553.640.371
G7 鳀科0.0962.37~2.705.980.10~0.500.52~0.553.080.190
G8 其他底层鱼类0.0791.45~2.904.23~9.900.10~0.500.52~0.553.360.378
G9 其他中上层鱼类0.0230.46~2.373.10~18.700.10~0.500.52~0.553.250.376
G10 近底层鱼类0.0410.63~3.264.80~9.000.10~0.500.52~0.553.290.400
G11 蟹类0.6643.5012.000.10~0.500.55~0.752.900.460
G12 口虾蛄0.7261.34~8.007.43~30.000.10~0.500.52~0.553.200.386
G13 戴氏赤虾0.0063.90~5.6515.00~26.900.10~0.500.52~0.553.020.301
G14 细鳌虾0.0713.7524.900.10~0.500.55~0.752.660.245
G15 鹰爪虾0.0611.8413.000.10~0.500.55~0.752.990.154
G16 长臂虾科0.3727.6925.000.10~0.500.55~0.752.880.161
G17 其他虾类0.3818.00~8.8028.00~30.000.10~0.500.55~0.752.820.112
G18 头足类0.0242.00~4.507.00~17.000.10~0.500.52~0.553.610.466
G19 其他头足类0.0034.5917.550.10~0.500.52~0.553.450.198
G20 棘皮动物0.3651.20~4.503.58~16.700.10~0.500.55~0.752.520.301
G21 软体动物29.8696.0027.000.10~0.500.55~0.752.030.025
G22 底栖动物2.9441.57~5.008.60~20.000.10~0.500.55~0.752.030.151
G23 尖海龙0.0052.305.980.10~0.500.55~0.752.850.014
G24 浮游动物2.27125.00~40.00122.10~180.030.10~0.500.70~0.932.000.014
G25 浮游植物20.673106.520.05~0.500.05~0.301.000.000
G26有机碎屑51.9121.000.000
), ArticleFig(id=1215325223147196441, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=EN, label=Table 3, caption=

The number and ratio of energy flow paths of each functional group in the food web in northern sea areas of Jiangsu Province

, figureFileSmall=null, figureFileBig=null, tableContent=
功能群能量流入
路径数
能量流出
路径数
占总能流路径
数比例/%
G1 长蛇鲻1667.36
G2 星康吉鳗1927.02
G3 黄鮟鱇1525.69
G4 虾虎鱼科16129.36
G5 鲆鲽类2179.36
G6 石首鱼科201210.70
G7 鳀科7126.35
G8 其他底层鱼类231011.04
G9 其他中上层鱼类1667.36
G10 近底层鱼类11127.69
G11 蟹类7157.36
G12 口虾蛄13118.03
G13 戴氏赤虾4115.02
G14 细鳌虾2166.02
G15 鹰爪虾996.02
G16 长臂虾科484.01
G17 其他虾类111910.03
G18 头足类13138.70
G19 其他头足类6115.69
G20 棘皮动物5136.02
G21 软体动物2217.69
G22 底栖动物5218.70
G23 尖海龙121.00
G24 浮游动物2259.03
G25 浮游植物1134.68
G26有机碎屑25710.70
), ArticleFig(id=1215325223256248351, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=CN, label=表3, caption=

江苏近海北部海域食物网各功能群能量流入、流出路径数及比例

, figureFileSmall=null, figureFileBig=null, tableContent=
功能群能量流入
路径数
能量流出
路径数
占总能流路径
数比例/%
G1 长蛇鲻1667.36
G2 星康吉鳗1927.02
G3 黄鮟鱇1525.69
G4 虾虎鱼科16129.36
G5 鲆鲽类2179.36
G6 石首鱼科201210.70
G7 鳀科7126.35
G8 其他底层鱼类231011.04
G9 其他中上层鱼类1667.36
G10 近底层鱼类11127.69
G11 蟹类7157.36
G12 口虾蛄13118.03
G13 戴氏赤虾4115.02
G14 细鳌虾2166.02
G15 鹰爪虾996.02
G16 长臂虾科484.01
G17 其他虾类111910.03
G18 头足类13138.70
G19 其他头足类6115.69
G20 棘皮动物5136.02
G21 软体动物2217.69
G22 底栖动物5218.70
G23 尖海龙121.00
G24 浮游动物2259.03
G25 浮游植物1134.68
G26有机碎屑25710.70
), ArticleFig(id=1215325223386271783, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=EN, label=Table 4, caption=

Ecological network analysis indices in northern sea areas of Jiangsu Province

, figureFileSmall=null, figureFileBig=null, tableContent=
生态网络分析指数类型指数名称
基本指数生态系统总流量(TST)6 345.21
总呼吸量(TR)1 613.32
流向碎屑的能量(TDET)749.55
系统杂食性指数(SOI)0.22
总初级生产量(TPP)1 695.90
总初级生产量/总呼吸(TPP/TR)1.05
总初级生产量/总生物量(TPP/TB)27.30
连接数(L)299
连接指数(C)0.40
平均连接权重(TST/L)21.22
平均隔间流通量(TST/n)326.22
路径分析总系统循环流量(TSTc)365.48
系统非循环总流量(TSTs)5 979.72
Finn’s循环指数%(FCI)5.76
平均路径长度(APL)2.26
网络不确定性平均相互信息(AMI)1.64
统计不确定性(HR3.14
条件的不确定性(DR1.50
实现的不确定性(RUR0.52
网络约束(HC88.16
约束效率(CE)0.71
系统发展和增长优势度(A)19 009.65
开发能力(DC)29 428.58
发展程度(AC)0.65
环境分析同质化(HP)1.80
协同效应指数(b/c)1.12
主导间接效应(i/d)6.09
), ArticleFig(id=1215325223470157868, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=CN, label=表4, caption=

江苏近海北部海域生态网络分析指数

, figureFileSmall=null, figureFileBig=null, tableContent=
生态网络分析指数类型指数名称
基本指数生态系统总流量(TST)6 345.21
总呼吸量(TR)1 613.32
流向碎屑的能量(TDET)749.55
系统杂食性指数(SOI)0.22
总初级生产量(TPP)1 695.90
总初级生产量/总呼吸(TPP/TR)1.05
总初级生产量/总生物量(TPP/TB)27.30
连接数(L)299
连接指数(C)0.40
平均连接权重(TST/L)21.22
平均隔间流通量(TST/n)326.22
路径分析总系统循环流量(TSTc)365.48
系统非循环总流量(TSTs)5 979.72
Finn’s循环指数%(FCI)5.76
平均路径长度(APL)2.26
网络不确定性平均相互信息(AMI)1.64
统计不确定性(HR3.14
条件的不确定性(DR1.50
实现的不确定性(RUR0.52
网络约束(HC88.16
约束效率(CE)0.71
系统发展和增长优势度(A)19 009.65
开发能力(DC)29 428.58
发展程度(AC)0.65
环境分析同质化(HP)1.80
协同效应指数(b/c)1.12
主导间接效应(i/d)6.09
), ArticleFig(id=1215325223637930029, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=EN, label=Table 5, caption=

Comparation of characteristic parameters between northern sea areas of Jiangsu Province and other marine ecosystems

, figureFileSmall=null, figureFileBig=null, tableContent=
研究区域TSTTPPTPP /TRCSOI
注:“−”代表相关研究没有计算该指数。
嵊泗人工鱼礁区[41]516017301.39
枸杞岛海藻场[42]28019116041.250.220.33
渤海[43]331615668.400.34
海州湾[4]479022027.090.430.20
黄河口[17]312613543.450.380.12
江苏近海北部海域(本研究)6345.2116961.050.400.22
), ArticleFig(id=1215325223755370547, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=CN, label=表5, caption=

江苏近海北部海域与其他海域生态系统特征参数的比较

, figureFileSmall=null, figureFileBig=null, tableContent=
研究区域TSTTPPTPP /TRCSOI
注:“−”代表相关研究没有计算该指数。
嵊泗人工鱼礁区[41]516017301.39
枸杞岛海藻场[42]28019116041.250.220.33
渤海[43]331615668.400.34
海州湾[4]479022027.090.430.20
黄河口[17]312613543.450.380.12
江苏近海北部海域(本研究)6345.2116961.050.400.22
), ArticleFig(id=1215325223864422456, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=EN, label=Table A1, caption=

Energy flow paths of food webs and their symbolic meanings in northern sea areas of Jiangsu Province and other marine ecosystems

, figureFileSmall=null, figureFileBig=null, tableContent=
序号能量流动路径 序号能量流动路径 序号能量流动路径 序号能量流动路径 序号能量流动路径
注:G1. 长蛇鲻;G2. 星康吉鳗;G3. 黄鮟鱇;G4. 虾虎鱼科;G5. 鲆鲽类;G6. 石首鱼科;G7. 鳀科;G8. 其他底层鱼类;G9. 其他中上层鱼类;G10. 近底层鱼类;G11. 蟹类;G12. 口虾蛄; G13. 戴氏赤虾;G14. 细鳌虾;G15. 鹰爪虾;G16. 长臂虾科;G17. 其他虾类;G18. 头足类;G19. 其他头足类;G20. 棘皮动物;G21. 软体动物;G22. 底栖动物;G23. 尖海龙;G24. 浮游动物;G25. 浮游植物;G26. 有机碎屑;RES. 呼吸。
x1G1→G1 x61G8→G10 x121G14→G4 x181G18→G17 x241G22→G12
x2G1→G2x62G8→G26x122G14→G5x182G18→G18x242G22→G13
x3G1→G8x63G8→RESx123G14→G6x183G18→G26x243G22→G15
x4G1→G9x64G9→G5x124G14→G7x184G18→RESx244G22→G16
x5G1→G26x65G9→G8x125G14→G8x185G19→G2x245G22→G17
x6G1→RESx66G9→G10x126G14→G9x186G19→G4x246G22→G18
x7G2→G26x67G9→G18x127G14→G10x187G19→G6x247G22→G19
x8G2→RESx68G9→G26x128G14→G12x188G19→G8x248G22→G20
x9G3→G26x69G9→RESx129G14→G15x189G19→G9x249G22→G26
x10G3→RESx70G10→G1x130G14→G17x190G19→G12x250G22→RES
x11G4→G1x71G10→G2x131G14→G18x191G19→G15x251G23→G26
x12G4→G2x72G10→G4x132G14→G19x192G19→G16x252G23→RES
x13G4→G3x73G10→G5x133G14→G26x193G19→G18x253G24→G1
x14G4→G4x74G10→G6x134G14→RESx194G19→G26x254G24→G3
x15G4→G5x75G10→G8x135G15→G1x195G19→RESx255G24→G4
x16G4→G6x76G10→G9x136G15→G2x196G20→G1x256G24→G5
x17G4→G8x77G10→G10x137G15→G3x197G20→G2x257G24→G6
x18G4→G9x78G10→G12x138G15→G5x198G20→G4x258G24→G7
x19G4→G11x79G10→G18x139G15→G6x199G20→G5x259G24→G8
x20G4→G12x80G10→G26x140G15→G7x200G20→G6x260G24→G9
x21G4→G26x81G10→RESx141G15→G8x201G20→G8x261G24→G10
x22G4→RES x82G11→G2 x142G15→G26 x202G20→G9 x262G24→G11
x23G5→G3x83G11→G3x143G15→RESx203G20→G12x263G24→G12
x24G5→G5x84G11→G4x144G16→G2x204G20→G13x264G24→G13
x25G5→G6x85G11→G5x145G16→G4x205G20→G17x265G24→G14
x26G5→G8x86G11→G6x146G16→G5x206G20→G20x266G24→G15
x27G5→G9x87G11→G8x147G16→G6x207G20→G26x267G24→G16
x28G5→G26x88G11→G9x148G16→G8x208G20→RESx268G24→G17
x29G5→RESx89G11→G11x149G16→G18x209G21→G1x269G24→G18
x30G6→G1x90G11→G12x150G16→G26x210G21→G2x270G24→G19
x31G6→G2x91G11→G15x151G16→RESx211G21→G3x271G24→G20
x32G6→G3x92G11→G17x152G17→G1x212G21→G4x272G24→G21
x33G6→G5x93G11→G19x153G17→G2x213G21→G5x273G24→G22
x34G6→G6x94G11→G22x154G17→G3x214G21→G6x274G24→G23
x35G6→G8x95G11→G26x155G17→G4x215G21→G7x275G24→G24
x36G6→G11x96G11→RESx156G17→G5x216G21→G8x276G24→G26
x37G6→G12x97G12→G2x157G17→G6x217G21→G9x277G24→RES
x38G6→G15x98G12→G4x158G17→G7x218G21→G10x278G25→G3
x39G6→G18x99G12→G5x159G17→G8x219G21→G11x279G25→G4
x40G6→G26x100G12→G6x160G17→G9x220G21→G12x280G25→G5
x41G6→RESx101G12→G8x161G17→G10x221G21→G13x281G25→G8
x42G7→G1x102G12→G12x162G17→G11x222G21→G15x282G25→G9
x43G7→G2x103G12→G17x163G17→G12x223G21→G16x283G25→G14
x44G7→G3x104G12→G18x164G17→G15x224G21→G17x284G25→G17
x45G7→G4x105G12→G19x165G17→G17x225G21→G18x285G25→G20
x46G7→G5x106G12→G26x166G17→G18x226G21→G20x286G25→G21
x47G7→G6x107G12→RESx167G17→G19x227G21→G22x287G25→G22
x48G7→G8x108G13→G1x168G17→G22x228G21→G26x288G25→G24
x49G7→G9x109G13→G2x169G17→G26x229G21→RESx289G25→G26
x50G7→G10x110G13→G3x170G17→RESx230G22→G1x290G25→RES
x51G7→G18x111G13→G4x171G18→G1x231G22→G2x291G26→G1
x52G7→G26x112G13→G5x172G18→G2x232G22→G3x292G26→G2
x53G7→RESx113G13→G6x173G18→G3x233G22→G4x293G26→G3
x54G8→G1x114G13→G7x174G18→G5x234G22→G5x294G26→G4
x55G8→G2x115G13→G8x175G18→G6x235G22→G6x295G26→G5
x56G8→G3x116G13→G10x176G18→G8x236G22→G7x296G26→G5
x57G8→G5x117G13→G26x177G18→G9x237G22→G8x297G26→G8
x58G8→G6 x118G13→RES x178G18→G10 x238G22→G9 x298G26→G17
x59G8→G8x119G14→G1x179G18→G12x239G22→G10x299CO2→G25
x60G8→G9x120G14→G2x180G18→G15x240G22→G11
), ArticleFig(id=1215325223977668666, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062513764626843, language=CN, label=表A1, caption=

江苏近海北部海域食物网能量流动路径及其符号含义

, figureFileSmall=null, figureFileBig=null, tableContent=
序号能量流动路径 序号能量流动路径 序号能量流动路径 序号能量流动路径 序号能量流动路径
注:G1. 长蛇鲻;G2. 星康吉鳗;G3. 黄鮟鱇;G4. 虾虎鱼科;G5. 鲆鲽类;G6. 石首鱼科;G7. 鳀科;G8. 其他底层鱼类;G9. 其他中上层鱼类;G10. 近底层鱼类;G11. 蟹类;G12. 口虾蛄; G13. 戴氏赤虾;G14. 细鳌虾;G15. 鹰爪虾;G16. 长臂虾科;G17. 其他虾类;G18. 头足类;G19. 其他头足类;G20. 棘皮动物;G21. 软体动物;G22. 底栖动物;G23. 尖海龙;G24. 浮游动物;G25. 浮游植物;G26. 有机碎屑;RES. 呼吸。
x1G1→G1 x61G8→G10 x121G14→G4 x181G18→G17 x241G22→G12
x2G1→G2x62G8→G26x122G14→G5x182G18→G18x242G22→G13
x3G1→G8x63G8→RESx123G14→G6x183G18→G26x243G22→G15
x4G1→G9x64G9→G5x124G14→G7x184G18→RESx244G22→G16
x5G1→G26x65G9→G8x125G14→G8x185G19→G2x245G22→G17
x6G1→RESx66G9→G10x126G14→G9x186G19→G4x246G22→G18
x7G2→G26x67G9→G18x127G14→G10x187G19→G6x247G22→G19
x8G2→RESx68G9→G26x128G14→G12x188G19→G8x248G22→G20
x9G3→G26x69G9→RESx129G14→G15x189G19→G9x249G22→G26
x10G3→RESx70G10→G1x130G14→G17x190G19→G12x250G22→RES
x11G4→G1x71G10→G2x131G14→G18x191G19→G15x251G23→G26
x12G4→G2x72G10→G4x132G14→G19x192G19→G16x252G23→RES
x13G4→G3x73G10→G5x133G14→G26x193G19→G18x253G24→G1
x14G4→G4x74G10→G6x134G14→RESx194G19→G26x254G24→G3
x15G4→G5x75G10→G8x135G15→G1x195G19→RESx255G24→G4
x16G4→G6x76G10→G9x136G15→G2x196G20→G1x256G24→G5
x17G4→G8x77G10→G10x137G15→G3x197G20→G2x257G24→G6
x18G4→G9x78G10→G12x138G15→G5x198G20→G4x258G24→G7
x19G4→G11x79G10→G18x139G15→G6x199G20→G5x259G24→G8
x20G4→G12x80G10→G26x140G15→G7x200G20→G6x260G24→G9
x21G4→G26x81G10→RESx141G15→G8x201G20→G8x261G24→G10
x22G4→RES x82G11→G2 x142G15→G26 x202G20→G9 x262G24→G11
x23G5→G3x83G11→G3x143G15→RESx203G20→G12x263G24→G12
x24G5→G5x84G11→G4x144G16→G2x204G20→G13x264G24→G13
x25G5→G6x85G11→G5x145G16→G4x205G20→G17x265G24→G14
x26G5→G8x86G11→G6x146G16→G5x206G20→G20x266G24→G15
x27G5→G9x87G11→G8x147G16→G6x207G20→G26x267G24→G16
x28G5→G26x88G11→G9x148G16→G8x208G20→RESx268G24→G17
x29G5→RESx89G11→G11x149G16→G18x209G21→G1x269G24→G18
x30G6→G1x90G11→G12x150G16→G26x210G21→G2x270G24→G19
x31G6→G2x91G11→G15x151G16→RESx211G21→G3x271G24→G20
x32G6→G3x92G11→G17x152G17→G1x212G21→G4x272G24→G21
x33G6→G5x93G11→G19x153G17→G2x213G21→G5x273G24→G22
x34G6→G6x94G11→G22x154G17→G3x214G21→G6x274G24→G23
x35G6→G8x95G11→G26x155G17→G4x215G21→G7x275G24→G24
x36G6→G11x96G11→RESx156G17→G5x216G21→G8x276G24→G26
x37G6→G12x97G12→G2x157G17→G6x217G21→G9x277G24→RES
x38G6→G15x98G12→G4x158G17→G7x218G21→G10x278G25→G3
x39G6→G18x99G12→G5x159G17→G8x219G21→G11x279G25→G4
x40G6→G26x100G12→G6x160G17→G9x220G21→G12x280G25→G5
x41G6→RESx101G12→G8x161G17→G10x221G21→G13x281G25→G8
x42G7→G1x102G12→G12x162G17→G11x222G21→G15x282G25→G9
x43G7→G2x103G12→G17x163G17→G12x223G21→G16x283G25→G14
x44G7→G3x104G12→G18x164G17→G15x224G21→G17x284G25→G17
x45G7→G4x105G12→G19x165G17→G17x225G21→G18x285G25→G20
x46G7→G5x106G12→G26x166G17→G18x226G21→G20x286G25→G21
x47G7→G6x107G12→RESx167G17→G19x227G21→G22x287G25→G22
x48G7→G8x108G13→G1x168G17→G22x228G21→G26x288G25→G24
x49G7→G9x109G13→G2x169G17→G26x229G21→RESx289G25→G26
x50G7→G10x110G13→G3x170G17→RESx230G22→G1x290G25→RES
x51G7→G18x111G13→G4x171G18→G1x231G22→G2x291G26→G1
x52G7→G26x112G13→G5x172G18→G2x232G22→G3x292G26→G2
x53G7→RESx113G13→G6x173G18→G3x233G22→G4x293G26→G3
x54G8→G1x114G13→G7x174G18→G5x234G22→G5x294G26→G4
x55G8→G2x115G13→G8x175G18→G6x235G22→G6x295G26→G5
x56G8→G3x116G13→G10x176G18→G8x236G22→G7x296G26→G5
x57G8→G5x117G13→G26x177G18→G9x237G22→G8x297G26→G8
x58G8→G6 x118G13→RES x178G18→G10 x238G22→G9 x298G26→G17
x59G8→G8x119G14→G1x179G18→G12x239G22→G10x299CO2→G25
x60G8→G9x120G14→G2x180G18→G15x240G22→G11
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基于LIM-MCMC模型研究江苏近海北部海域食物网能量流动特征
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张虎 1 , 李鹏程 2 , 胡海生 1 , 薛莹 2, * , 袁健美 1 , 贲成恺 1 , 祝超文 1 , 肖悦悦 1 , 祖凯伟 1
海洋学报 | 论文 2023,45(9): 105-118
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海洋学报 | 论文 2023, 45(9): 105-118
基于LIM-MCMC模型研究江苏近海北部海域食物网能量流动特征
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张虎1 , 李鹏程2, 胡海生1, 薛莹2, * , 袁健美1, 贲成恺1, 祝超文1, 肖悦悦1, 祖凯伟1
作者信息
  • 1 江苏省海洋水产研究所, 江苏 南通 226007
  • 2 中国海洋大学 水产学院, 山东 青岛 266003
  • 张虎(1980-),男,江苏省新沂市人,正高级工程师,从事海洋生态与渔业资源研究。E-mail:

通讯作者:

*薛莹,男,教授,主要从事渔业资源生物学、渔业生态学等领域的研究。E-mail:
Energy flow characteristics of the food web in the northern waters of Jiangsu Province based on LIM-MCMC model
Hu Zhang1 , Pengcheng Li2, Haisheng Hu1, Ying Xue2, * , Jianmei Yuan1, Chengkai Ben1, Chaowen Zhu1, Yueyue Xiao1, Kaiwei Zu1
Affiliations
  • 1Jiangsu Marine Fisheries Research Institute, Nantong 226007, China
  • 2Fisheries College, Ocean University of China, Qingdao 266003, China
出版时间: 2023-09-30 doi: 10.12284/hyxb2023120
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食物网结构特征和能量流动的研究,对于维持海洋生态系统结构和功能的稳定具有重要意义,有助于深入理解海洋生态系统的复杂过程。本研究基于2019−2021年在江苏近海北部海域开展的季节性渔业资源底拖网调查数据,通过构建基于蒙特卡罗马尔科夫链算法的逆线性模型(Linear Inverse Models using a Monte Carlo Method Coupled with Markov Chain, LIM-MCMC),结合生态网络分析(Ecological Network Analysis,ENA)的方法,分析了该海域生态系统状态和食物网能量流动特征,旨在为江苏近海北部海域食物网营养动力学研究提供参考依据。结果表明,该海域生态系统共包含299条能量流动路径,能量流动分布整体呈典型的金字塔结构,各功能群呼吸消耗和流入有机碎屑的能量保持同步性。通过与其他海域比较发现,江苏近海北部海域生态系统的连接指数(Connectance,C)和系统杂食指数(System Omnivory Index,SOI)分别为0.40和0.22,处于较高水平,表明该生态系统不同营养级间的营养联系较为紧密,食物网结构相对复杂,能够在较大程度上抵御外界扰动。总初级生产力/总呼吸(Total Primary Production/Total Respiration,TPP/TR)和Finn’s循环指数(Finn’s Cycling Index,FCI)分别为1.05和5.76%,表明该生态系统对能量利用效率较高。此外,约束效率(Constraint Efficiency,CE)、发展程度(Extent of Development,AC)、协同效应指数(Synergism Index,b/c)和主导间接效应(Dominance Indirect Effects,i/d)也表明该生态系统具有较高的系统发展程度、再生潜力和系统发展空间。本研究将有助于为江苏近海北部海域生态系统的修复和渔业资源的可持续利用提供理论基础,为实施基于生态系统的渔业管理提供科学依据。

LIM-MCMC模型  /  生态网络分析  /  能量流动  /  生态系统特征  /  食物网

Study on the structure and energy flow of food webs is important for maintaining the stability of structure and function of marine ecosystems, which will contribute to the in-depth understanding of the complex processes of marine ecosystems. Based on the seasonal bottom trawl survey data in the northern waters of Jiangsu Province from 2019−2021, a linear inverse models using a Monte Carlo method coupled with Markov chain model combined with ecological network analysis (ENA) were used to explore the status of the ecosystem and energy flow characteristics of the food web in this area. The results showed that there were 299 energy flow paths in the ecosystem, which showed a typical pyramid structure. In addition, the energy consumed by respiration and the energy flowing into the detritus of each functional group remains synchronized. Compared with other sea areas, connectance (C) and system omnivory index (SOI) were 0.40 and 0.22, respectively, which were at relatively high levels, indicating that organisms from different trophic levels in this ecosystem were closely connected. It has a relatively complex food web structure, which can resist external disturbance. Total primary production/total respiration (TPP/TR) and Finn’s cycling index (FCI) were 1.05 and 5.76%, respectively, indicating that the ecosystem was relatively mature and used energy efficiently. In addition, constraint efficiency (CE), extent of development (AC), synergism index (b/c) and dominance indirect effects (i/d) also indicated high potential for development and regeneration. This study will provide a theoretical basis for the restoration and sustainable utilization of fishery resources in the northern waters of Jiangsu Povince, and provide a scientific basis for the implementation of Ecosystem-based fishery management in this area.

linear inverse models using a Monte Carlo method coupled with Markov chain  /  ecological network analysis  /  energy flows  /  ecosystem characteristics  /  food web
张虎, 李鹏程, 胡海生, 薛莹, 袁健美, 贲成恺, 祝超文, 肖悦悦, 祖凯伟. 基于LIM-MCMC模型研究江苏近海北部海域食物网能量流动特征. 海洋学报, 2023 , 45 (9) : 105 -118 . DOI: 10.12284/hyxb2023120
Hu Zhang, Pengcheng Li, Haisheng Hu, Ying Xue, Jianmei Yuan, Chengkai Ben, Chaowen Zhu, Yueyue Xiao, Kaiwei Zu. Energy flow characteristics of the food web in the northern waters of Jiangsu Province based on LIM-MCMC model[J]. Haiyang Xuebao, 2023 , 45 (9) : 105 -118 . DOI: 10.12284/hyxb2023120
江苏近海北部海域位于海州湾与苏北浅滩交接地带,是南黄海西部典型的开放式海域。由于陆源径流输入大量有机质和营养盐,该海域饵料生物资源丰富,生态环境独特,适宜鱼、虾、蟹、贝、藻的繁衍和栖息,是多种渔业生物重要的产卵场、索饵场和栖息地[1-2]。近年来,由于过度捕捞、气候变化等多重压力的影响[3],造成海洋生态环境恶化、渔业资源日益衰退及群落结构变化等生态问题[4-5]。因此,加强对江苏近海北部海域生态系统的保护和修复,将有助于实现海洋生态系统的健康可持续发展。
食物网结构和功能的研究,对于量化物种间相互作用及维持海洋生态系统的稳定性具有重要意义,有助于理解海洋生态系统的复杂过程[6]。营养动力学模型的不断发展,为海洋食物网结构和功能的研究提供了有效方法。其中,逆线性模型(Linear Inverse Model, LIM)是基于营养动力学原理构建的生态系统能量流动模型[7],其最早出现在地球物理科学领域,直到20世纪80年代末被应用于食物网的能量流动研究中[8]。另外,结合蒙特卡罗马尔可夫链(Markov Chain Monte Carlo, MCMC)方法,通过提供生态系统中能量流动的概率分布,可以有效避免低估食物网规模和复杂性等问题[910],并在很大程度上考虑了数据及模型的不确定性。目前,基于蒙特卡罗马尔科夫链算法的逆线性模型(Linear Inverse Models using a Monte Carlo Method Coupled with Markov Chain,LIM-MCMC)已成功应用于全球多个水域的食物网研究中[11-12]。该模型优点在于其包含能量平衡和不平衡方程,通过参数限制计算能量流动值,并将采样误差等不确定性因素考虑在内[13],为食物网的营养动力学研究提供一种有效方法。
本研究基于2019−2021年在江苏近海北部海域开展的季节性渔业资源底拖网调查数据,通过构建LIM-MCMC模型,结合生态网络分析(Ecological Network Analysis,ENA)的方法,分析了该海域的生态系统状态和食物网能量流动特征,旨在为江苏近海北部海域食物网营养动力学的深入研究提供参考依据,为实施基于生态系统的渔业管理提供理论支撑。
样品采自2019−2021年在江苏近海北部海域进行的季节性渔业资源与栖息环境综合调查,主要调查内容包括游泳生物、底栖生物、浮游动物和浮游植物。调查范围在34.00°~35.50°N,119.00°~121.00°E之间的海域,站位设计采用定点设站的方法,且各航次调查站位保持一致(图1)。调查船为长32.6 m,宽6.3 m,主机功率184 kW的单拖渔船,拖速为2.5 kn左右,每站平均拖网时间约为1 h。调查网具采用网型125.32 m × 59.1 m(36.0 m)网口周长×网身全长(浮子纲长),网口宽度12 m,囊网网目20 mm,全长59 m的有翼单囊拖网及浅水I、III型网等组成。
LIM-MCMC模型是在物种间质量平衡关系的基础上,遵循营养动力学原理[7],并结合蒙特卡罗马尔科夫(MCMC)算法构建的生态系统能量流动模型。该模型通过一系列生态关联的功能群,定义生态系统各组分,所有功能群基本覆盖该生态系统能量流动全过程。模型基于生态系统内部处于稳定状态的假设,没有迁移等因素带来生物量的变化,各功能群能量输入与输出保持平衡[14],即能量平衡遵循:生产量(Q)= 产出(P)+ 排泄(U)+ 呼吸(R)。模型根据各功能群相关生物学和捕捞数据,建立质量平衡方程和约束能量流动值的不平衡方程,通过参数限制计算实验无法获取的能量输入与输出值[9],从而对生态系统的营养结构和能量流动进行评价。
LIM-MCMC模型由质量平衡方程和不平衡方程组成[15]
平衡方程:
$ {\boldsymbol{E}}_{(m\;\times\; n)} \cdot x = {\boldsymbol{F}}\text{,} $
不平衡方程:
$ {\boldsymbol{G}}_{(c\;\times \;n)} \cdot x \geqslant h\text{,} $
式中,Em × nGc × n表示能量流动路径系数矩阵;m代表各功能群的质量平衡以及通过实验测得的已知能量流动路径数据;c表示加入模型的不等式数;n为能量流动路径数量(x1, x2, ···, xn);F表示等式值的矩阵(m × 1);h表示不等式的值(c × 1)。
本研究基于优势种并综合考虑摄食习性、栖息环境等功能属性的相似性,将该海域生物群落定义为26个功能群,既包括优势种和主要渔业种类,也包括摄食和生态习性相似的物种,以及有机碎屑、浮游植物、浮游动物、底栖动物、棘皮动物和软体动物等各营养级生物。
除有机碎屑外,各功能群包含生产量/生物量(P/B)、摄食量/生物量(Q/B)、排泄量/生物量(U/B)和呼吸量/生物量(R/B)4个生物属性参数,分别表示单位生物量的生产量、摄食量、排泄量和呼吸量。有关能量流动的限制参数主要参考邻近海域的历史文献[4, 16-25],并通过各功能群的P/BQ/BU/BR/B等参数的最大值和最小值范围,对能量流动值加以限制。此外,对2019−2021年调查数据按照拖速(2 kn)和作业时间(1 h)进行标准化处理,根据扫海面积法估算生物量,并按照摄食矩阵对功能群进行划分。其中摄食矩阵主要依据调查海域鱼类样品的胃含物分析,并结合相关参考文献进行构建[20, 26-28]。生物量和能量流动均以湿重形式表示,单位均为t/(km2·a)。
模型调试通过R(3.5.2版)中的 “Lim”和 “LimSolve”[29-30]包实现。模型中存在多条能量流动路径难以被量化(m < n),且数据输入存在固有的不确定性。因此,可能出现限制条件相互矛盾造成模型未找到特定的解决方案。通过检查各功能群的限制条件,并逐一添加进行调试,直至模型成功运行。此时,至少存在一组解,满足质量平衡和不平衡方程[31],即食物网能量流动达到平衡。为降低模型误差,重复运行100次,通过结合MCMC算法对所有可能的结果进行取样求解并计算平均值,其平均值即为每条路径的能量流动值。
生态网络分析(ENA)方法是分析生态系统相互作用关系、辨识系统内在和整体属性的一种有效分析方法[32],已被证明在描述生态系统功能等方面是非常有效的[33]。主要包括:基本指数、路径分析、网络不确定性、系统发展和增长、环境分析以及营养和杂食性水平几个方面(表1)。上述各指数均通过NetMatCalc软件计算[34]
本研究选择ENA中的基本指数反映生态系统总体特征。在这一类别中考虑一些基本生态系统属性,分别从能量流出和流入角度考虑各功能群的流通量。其中,生态系统总流量(Total System Throughput, TST)是生态系统中所有能流量的总和,用来衡量生态系统的规模和增长状况;总初级生产力/总呼吸(Total Primary Production/Total Respiration, TPP/TR)是表征生态系统成熟度的一个重要指标[35],TPP/TR越接近于1.00,表明生态系统越成熟;连接指数(Connectance, C)和系统杂食指数(System Omnivory Index, SOI)均是衡量生态系统内部联系的复杂程度[36]。此外,还包括总初级生产量(Total Primary Production, TPP)、总呼吸量(Total Respiratory Flows, TR)、流向碎屑的能量(Total Flows into Detritus, TDET)、连接数(Number of Links, L)、平均连接权重(Average Link Weight, TST/L)和平均隔间流通量(Average Compartment Throughflow, TST/n)等指标。
从路径分析、网络不确定性、系统发展和增长以及环境分析选择5个指标反映食物网的不确定性和发展差异,包括:Finn’s循环指数(Finn’s Cycling Index, FCI)、约束效率(Constraint Efficiency, CE)、发展程度(Extent of Development, AC)、协同效应指数(Synergism Index, b/c)和主导间接效应(Dominance Indirect Effects, i/d)。其中,FCI是衡量生态系统中能量再循环利用的比例[37];CE是内在网络约束对最大网络不确定性的贡献程度[38];AC衡量了生态系统的发展[34]和再生潜力[39],以及b/c和i/d等指标[40]
基于LIM-MCMC模型构建的江苏近海北部海域生态系统的食物网能量流动特征如图2所示。由模型结果(表2)可知,浮游植物和有机碎屑处于第I营养级,其生物量分别为20.673 t/(km2·a)和51.912 t/(km2·a),占食物网总生物量的65.46%;浮游动物为第II 营养级,尖海龙(Syngnathus acus)、底栖动物、软体动物、棘皮动物、细鳌虾(Leptochela gracilis)、鹰爪虾(Trachypenaeus curvirostris)、长臂虾科,其他虾类和蟹类位于第II 和III营养级之间;戴氏赤虾(Metapenaeopsis dalei)、口虾蛄(Oratosquilla oratoria)、近底层鱼类、其他中上层鱼类、其他底层鱼类、鳀科、石首鱼科、鲆鲽类和虾虎鱼科位于第III和 IV营养级之间;顶级捕食者,如长蛇鲻(Saurida elongata)、星康吉鳗(Conger myriaster)和黄鮟鱇(Lophius litulon),位于第 IV营养级以上。杂食指数高于0.35的功能群有石首鱼科、其他底层鱼类、其他中上层鱼类、近底层鱼类、蟹类、口虾蛄和大型头足类,多为III和 IV的中高营养级,而低营养级和顶级捕食者的杂食指数相对较小(表2)。
该海域生态系统共包含299条能量流动路径,能量流动分布整体呈典型的金字塔结构。依据能量流动值的大小,将其划分为4组(图3)包括:a. 0.00~1.00 t/(km2·a);b. 1.00~10.00 t/(km2·a);c. 10.00~100.00 t/(km2·a);d. >100.00 t/(km2·a)。a组包括227条能量流动路径,占总路径的75.92%。其能量流动主要发生在低营养级功能群,在生态系统中具有重要地位(图3a)。b组主要由初级消费者向高营养级传递,有35条能量流动路径,占11.71%。其中口虾蛄→口虾蛄、头足类→呼吸消耗(RES)、底栖动物→近底层鱼类、近底层鱼类→呼吸消耗(RES)、浮游动物→软体动物、口虾蛄→有机碎屑和其他虾类→口虾蛄具有较高的能量流动,分别为7.74 t/(km2·a)、7.07 t/(km2·a)、6.44 t/(km2·a)、6.41 t/(km2·a)、6.40 t/(km2·a)、6.32 t/(km2·a)和6.26 t/(km2·a)(图3b)。c组能量流动共14条能量流动路径,占总路径的4.68%,在能量的传递过程中能量多数通过呼吸消耗或流入有机碎屑。主要能量流动路径包括:浮游植物→鲆鲽类、其他中上层鱼类→呼吸消耗(RES)、其他虾类→有机碎屑、浮游植物→有机碎屑、其他中上层鱼类→有机碎屑和浮游植物→呼吸消耗(RES),分别为98.68 t/(km2·a)、98.25 t/(km2·a)、86.10 t/(km2·a)、82.58 t/(km2·a)、82.50 t/(km2·a)和81.75 t/(km2·a)(图3c)。该生态系统中能量流动值超过100.00 t/(km2·a)的能流路径有23条,占7.69%。其中各功能群之间在其他虾类→呼吸消耗(RES)能量最高,为278.32 t/(km2·a),其次为浮游植物→底栖动物、浮游植物→浮游动物和浮游植物→棘皮动物的能量,分别为246.39 t/(km2·a)、245.45 t/(km2·a)和224.51 t/(km2·a),在生态系统能量传递中具有重要作用(图3d)。
江苏近海北部海域食物网各功能群能量流入和流出路径数如表3所示,其中石首鱼科、其他底层鱼类、其他虾类和有机碎屑功能群的能流路径相对较为复杂,占食物网总能流路径数的比例分别为10.70%、11.04%、10.03%和10.70%。而浮游动物、软体动物、星康吉鳗和黄鮟鱇等功能群,其能量流入或流出的路径数目较少(表3)。
在食物网能量流动中,共有25个功能群具有呼吸能量消耗,合计为1 613.32 t/(km2·a)(图4a)。其中,其他虾类、浮游动物和底栖动物等低营养级功能群中具有较高的呼吸能量消耗,分别为278.32 t/(km2·a)、201.53 t/(km2·a)和186.54 t/(km2·a)。对高营养级功能群而言,通过呼吸消耗排出生态系统的能量均较少,如长蛇鲻、星康吉鳗、黄鮟鱇和虾虎鱼科等功能群,呼吸消耗的能量仅为0.001 t/(km2·a)、0.005 t/(km2·a)、0.001 t/(km2·a)和0.009 t/(km2·a),在生态系统呼吸消耗的能量中占极小比例。在25个流入有机碎屑功能群的能量流动中(图4b),其他底层鱼类流入有机碎屑功能群的能量最高,为137.09 t/(km2·a)。其次为鲆鲽类和石首鱼科,分别为110.42 t/(km2·a)和103.65 t/(km2·a)。其他营养级较低的功能群,如浮游植物、棘皮动物和浮游动物等也具有较高的能量流入有机碎屑。
江苏近海北部海域生态系统的生态网络分析(ENA)如表4所示。结果表明,该海域生态系统的总流量(TST)为6 345.21 t/(km2·a),其中总呼吸量(TR)为1 613.32 t/(km2·a),流向碎屑的能量(TDET)为749.55 t/(km2·a),分别占总流量的25.43%和11.81%。生态系统的总初级生产量(TPP)为1 695.90 t/(km2·a),总初级生产量与总生物量比(TPP/TB)为27.30,总初级生产量与总呼吸的比(TPP/TR)为1.05。路径分析指数表明,该生态系统中的系统总循环流量(TSTc)为365.48 t/(km2·a),非循环总流量(TSTs)为5 979.72 t/(km2·a),系统总循环流量占比为5.76%,即Finn’s循环指数(FCI)为5.76。此外,还包括约束效率(CE)、发展程度(AC)、协同效应指数(b/c)和主导间接效应(i/d)等其他生态网络分析(ENA)结果,具体见表4
表5所示,与其他海域相比,江苏近海北部海域生态系统的系统总流量(TST)为6345.21 t/(km2·a),显著高于嵊泗人工鱼礁区、渤海、海州湾和黄河口,但明显低于枸杞岛海藻场。该海域总初级生产量/总呼吸(TPP/TR)低于其他多数海域。此外,江苏近海北部海域生态系统的连接指数(C)和系统杂食指数(SOI)分别为0.40和0.22,连接指数(C)相比上述其他海域生态系统处于较高水平,而系统杂食指数(SOI)处于中等水平(表5)。
本研究通过构建LIM-MCMC模型,结合生态网络分析(ENA),研究了江苏近海北部海域食物网的能量流动特征和生态系统状态。研究发现,该生态系统整体能流分布由低营养级向高营养级逐渐减少,呈典型的能量金字塔结构[5]。能量流动较高的功能群属于浮游植物、有机碎屑、浮游动物、尖海龙、底栖生物、软体动物和棘皮动物等低营养级生物。该生态系统的能量供应主要来源于浮游植物和有机碎屑,其中68.28%来源于浮游植物,31.72%来源于有机碎屑。浮游植物作为主要初级生产者,为生态系统提供主要的能量供应,而有机碎屑作为另一个主要的能量来源,在生态系统中形成碎屑食物链。
同时,本研究结果与前人研究一致 [12, 14],均表明碎屑功能群作为重要的能量来源为其他物种提供能量,且浮游动物在功能群之间的能量流动中起到重要传递作用。而浮游动物、尖海龙、底栖生物、软体动物和棘皮动物作为消费者,在能量由低营养级到高营养级流动的过程中发挥关键作用,其能量流入发生变化会通过上行控制作用直接影响整个食物网的能量传递,从而决定高营养级生物的规模[5]。此外,星康吉鳗和黄鮟鱇作为食物网中的顶级捕食者,其能量流出路径数较少,仅包括流入有机碎屑和呼吸消耗两条路径,且能流值极低,其生物量和数量的变化可能通过下行控制作用对低营养级生物产生营养级联效应,以维持食物网的相对稳定。
食物网作为一个有机的统一整体,各营养级生物在其中发挥着重要作用,共同维持海域生态系统的稳定,特别是对低营养级和顶级捕食者而言,其能量流动会通过营养级联效应对整个食物网的结构和功能产生影响。本研究发现,江苏近海北部海域中高营养级生物的能量流入和流出路径数均相对较高,且能量流动值较低,表现为弱相互作用[5]。在受到外界环境或人为因素的扰动时,生态系统能够通过调整其能量流动路径的流入和流出值,维持能量的收支平衡,对于维持生态系统的稳定性具有重要调节作用[44]。同时,通过与其他生态系统比较发现,江苏近海北部海域生态系统的初级生产量/总呼吸 (TPP/TR)接近1.00,表明该生态系统处于相对成熟状态[19],只有较少能量进入生态系统再循环过程[35],与Finn’s循环指数(FCI)[37]表现一致。此外,江苏近海北部海域生态系统的连接指数(C)和系统杂食指数(SOI)处于较高水平,表明不同营养级生物之间的营养联系较为紧密,食物网结构复杂度较高[36],能够在较大程度上抵御外界扰动的影响。而在生态系统的不确定性和发展差异方面,约束效率(CE)、发展程度(AC)、协同效应指数(b/c)和主导间接效应(i/d)表明,该生态系统具有较高的系统发展程度、再生潜力和发展空间[34, 37-40]
综上所述,该海域未来应进一步加强对低营养级消费者的保护,从而保障初级生产者的能量能够有效的向高营养级传递。特别是在未来气候变化情景下,部分地区低营养级的生物量有可能会发生强烈改变[45]。因此,开展低营养级消费者的保护,将有利于缓解气候变化对该海域生态系统的影响。此外,对于顶级捕食者,应评估其维持食物网稳定性的最小生物量或数量,并将其纳入控制可捕量的因素之中,这是权衡其经济价值和生态功能价值的有效方法。
LIM-MCMC模型作为量化食物网能流特征的有效方法,虽然考虑了数据及模型的不确定性[13],但是影响模型输出的因素还有很多,例如:功能群划分的方法以及功能群的数目等[46-47],这将对LIM-MCMC模型的输出结果以及后续的生态网络分析(ENA)产生较大影响。因此,今后在LIM-MCMC模型构建过程中,应考虑选择合适的功能群划分方法以及功能群数目,将有助于提高模型输出结果的可靠性,以便更加准确地反映该海域生态系统状态和食物网能量流动特征,为实施基于生态系统的渔业管理和渔业资源的可持续利用提供数据支撑。
  • 2022年度江苏省农业生态保护与资源利用专项—渔业生态与资源监测(2022-SJ-061-01);2021年度江苏省农业生态保护与资源利用专项—渔业生态与资源监测(2021-SJ-110-02)。
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2023年第45卷第9期
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doi: 10.12284/hyxb2023120
  • 接收时间:2023-03-17
  • 首发时间:2025-12-28
  • 出版时间:2023-09-30
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  • 收稿日期:2023-03-17
  • 修回日期:2023-04-23
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2022年度江苏省农业生态保护与资源利用专项—渔业生态与资源监测(2022-SJ-061-01);2021年度江苏省农业生态保护与资源利用专项—渔业生态与资源监测(2021-SJ-110-02)。
作者信息
    1 江苏省海洋水产研究所, 江苏 南通 226007
    2 中国海洋大学 水产学院, 山东 青岛 266003

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*薛莹,男,教授,主要从事渔业资源生物学、渔业生态学等领域的研究。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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