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海州湾底层鱼类物种多样性与生物量的关系

万勇慧 刘淑德 张崇良 纪毓鹏 徐宾铎 薛莹

万勇慧,刘淑德,张崇良,等. 海州湾底层鱼类物种多样性与生物量的关系[J]. 海洋学报,2023,45(9):82–90 doi: 10.12284/hyxb2023134
引用本文: 万勇慧,刘淑德,张崇良,等. 海州湾底层鱼类物种多样性与生物量的关系[J]. 海洋学报,2023,45(9):82–90 doi: 10.12284/hyxb2023134
Wan Yonghui,Liu Shude,Zhang Chongliang, et al. Relationship between species diversity and biomass of demersal fish in Haizhou Bay[J]. Haiyang Xuebao,2023, 45(9):82–90 doi: 10.12284/hyxb2023134
Citation: Wan Yonghui,Liu Shude,Zhang Chongliang, et al. Relationship between species diversity and biomass of demersal fish in Haizhou Bay[J]. Haiyang Xuebao,2023, 45(9):82–90 doi: 10.12284/hyxb2023134

海州湾底层鱼类物种多样性与生物量的关系

doi: 10.12284/hyxb2023134
基金项目: 国家重点研发计划重点专项(2022YFD2401301)。
详细信息
    作者简介:

    万勇慧(2000-),女,山东省滨州市人,主要从事鱼类种群动力学研究。E-mail:wanyonghui0@126.com

    通讯作者:

    张崇良,男,副教授,主要从事渔业资源评估与生态系统模拟。E-mail: zhangclg@ouc.edu.cn

  • 中图分类号: P714+.5;S932.4

Relationship between species diversity and biomass of demersal fish in Haizhou Bay

  • 摘要: 随着生物多样性的丧失,全球许多海洋生态系统的功能发生了显著变化。为了解生物多样性和生态系统功能之间的关系,科学的海洋生态保护与管理显得尤为重要。本研究根据2013−2022年春季在海州湾及其邻近海域进行的底拖网调查数据,基于结构方程模型(SEM)探究了底栖鱼类群落中环境因素、生物多样性(物种丰富度与均匀度)和生态系统功能指标(以总生物量表示)之间的关系。结果表明:物种丰富度和生物量之间存在显著的正相关,而均匀度和生物量存在显著的负相关。环境因素中盐度对物种丰富度和生物量均有显著的影响,而对于温度来说,夏季与冬季的温度比年平均温度对生物量的影响更强烈。本研究表明,生态位互补效应和选择效应这两种机制可能同时对维持海州湾底层鱼类群落中的生物多样性−生物量关系发挥了作用,此外这种关系还依赖于它们所生存的环境和栖息条件。
  • 图  1  海州湾及其邻近海域渔业资源底拖网调查站位

    Fig.  1  Sampling stations of the fishery resource surveys in the Haizhou Bay and its adjacent waters

    图  2  结构方程模型图示

    Fig.  2  Illustration of structural equation models

    图  3  2013−2022年底层鱼类生物量的变化趋势(a)和物种丰富度、均匀度的变化趋势(b)

    Fig.  3  Trends in demersal fish biomass (a) and species richness and evenness (b) from 2013 to 2022

    图  4  年均温度初始模型图示(a)和优化模型结果图示(b)

    红色线表示显著的正影响路径,蓝色线表示显著的负影响路径,虚线表示影响不显著的路径

    Fig.  4  Illustration of annual mean temperature model (a) and optimization model results (b)

    Red lines indicate significant positive effects paths, blue lines indicate significant negative effects paths, and dashed lines indicate insignificant paths

    图  5  季节温度模型结果图示

    红色线表示显著的正影响路径,蓝色线表示显著的负影响路径,灰色虚线表示影响不显著路径,红色虚线表示有正影响的显著缺失路径

    Fig.  5  Illustration of the results of seasonal temperature model

    Red lines indicate significant positive effects paths, blue lines indicate significant negative effects paths, gray dashed lines indicate insignificant paths, and red dashed lines indicate significant missing paths with positive effects

    图  6  最优模型结果图示

    红色线表示显著的正影响路径,蓝色线表示显著的负影响路径

    Fig.  6  Illustration of the optimal model results

    Red lines indicate significant positive effects paths, blue lines indicate significant negative impact paths

    表  1  各模型参数对比

    Tab.  1  Comparison of parameters of each model

    指标初始模型年均温度模型季节温度模型最优模型
    模型设置包含全部路径去掉不显著路径加入夏季与冬季温度变量去掉不显著路径,加入显著缺失路径
    显著缺失路径均匀度和win2.SST
    Fisher’s C1.76113.62631.09915.591
    p0.7800.1910.4110.621
    AIC49.845.673.151.6
    BIC123.794.9137.8107.1
    R20.340.350.410.39
    下载: 导出CSV
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出版历程
  • 收稿日期:  2023-02-24
  • 修回日期:  2023-06-26
  • 网络出版日期:  2023-09-06
  • 刊出日期:  2023-09-30

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