Volume 39 Issue 8
Aug.  2020
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Dongyan Han, Chongliang Zhang, Ying Xue, Binduo Xu, Yiping Ren, Yong Chen. Impacts of sample size for stomach content analysis on the estimation of ecosystem indices[J]. Acta Oceanologica Sinica, 2020, 39(8): 53-61. doi: 10.1007/s13131-020-1633-x
Citation: Dongyan Han, Chongliang Zhang, Ying Xue, Binduo Xu, Yiping Ren, Yong Chen. Impacts of sample size for stomach content analysis on the estimation of ecosystem indices[J]. Acta Oceanologica Sinica, 2020, 39(8): 53-61. doi: 10.1007/s13131-020-1633-x

Impacts of sample size for stomach content analysis on the estimation of ecosystem indices

doi: 10.1007/s13131-020-1633-x
Funds:  The National Natural Science Foundation of China under contract No. 31772852; the Fundamental Research Funds for the Central Universities under contract No. 201612004.
More Information
  • Corresponding author: E-mail: renyip@ouc.edu.cn
  • Received Date: 2019-12-12
  • Accepted Date: 2020-04-08
  • Available Online: 2020-12-28
  • Publish Date: 2020-08-25
  • This study used Ecopath model of the Jiaozhou Bay as an example to evaluate the effect of stomach sample size of three fish species on the projection of this model. The derived ecosystem indices were classified into three categories: (1) direct indices, like the trophic level of species, influenced by stomach sample size directly; (2) indirect indices, like ecology efficiency (EE) of invertebrates, influenced by the multiple prey-predator relationships; and (3) systemic indices, like total system throughout (TST), describing the status of the whole ecosystem. The influences of different stomach sample sizes on these indices were evaluated. The results suggest that systemic indices of the ecosystem model were robust to stomach sample sizes, whereas specific indices related to species were indicated to be with low accuracy and precision when stomach samples were insufficient. The indices became more uncertain when the stomach sample sizes varied for more species. This study enhances the understanding of how the quality of diet composition data influences ecosystem modeling outputs. The results can also guide the design of stomach content analysis for developing ecosystem models.
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