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Journal of Oceanology and Limnology

, Volume 36, Issue 3, pp 973–980 | Cite as

The impact of spatial autocorrelation on CPUE standardization between two different fisheries

  • Luoliang Xu (许骆良)
  • Xinjun Chen (陈新军)
  • Wenjiang Guan (官文江)
  • Siquan Tian (田思泉)
  • Yong Chen (陈勇)
Article
  • 35 Downloads

Abstract

Catch per unit of effort (CPUE) data can display spatial autocorrelation. However, most of the CPUE standardization methods developed so far assumes independency of observations for the dependent variable, which is often invalid. In this study, we collected data of two fisheries, squid jigging fishery and mackerel trawl fishery. We used standard generalized linear model (GLM) and spatial GLMs to compare the impact of spatial autocorrelation on CPUE standardization for different fisheries. We found that spatial- GLMs perform better than standard-GLM for both fisheries. The overestimation of precision of CPUE estimates was observed in both fisheries. Moran’s I was used to quantify the level of autocorrelation for the two fisheries. The results show that autocorrelation in mackerel trawl fishery was much stronger than that in squid jigging fishery. According to the results of this paper, we highly recommend to account for spatial autocorrelation when using GLM to standardize CPUE data derived from commercial fisheries.

Keyword

spatial autocorrelation catch per unit effort (CPUE) standardization squid jigging fishery mackerel trawl fishery 

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Notes

Acknowledgement

We thank Chinese Oversea Fishery Association (COFA) and NOAA for providing data. We are grateful of CHANG Yongbo in College of Marine Sciences Shanghai Ocean University who has spent much time working in a mackerel trawl vessel and provides the information about the fishery. We also thank the Chinese Distant-water Squid Jigging Technical Group for providing fishery data and information.

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Copyright information

© Chinese Society for Oceanology and Limnology, Science Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Luoliang Xu (许骆良)
    • 1
    • 2
    • 3
  • Xinjun Chen (陈新军)
    • 1
    • 2
    • 3
  • Wenjiang Guan (官文江)
    • 1
    • 2
    • 3
  • Siquan Tian (田思泉)
    • 1
    • 2
    • 3
  • Yong Chen (陈勇)
    • 4
    • 1
  1. 1.College of Marine SciencesShanghai Ocean UniversityShanghaiChina
  2. 2.Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources (Shanghai Ocean University)Ministry of EducationShanghaiChina
  3. 3.National Engineering Research Center for oceanic FisheriesShanghai Ocean UniversityShanghaiChina
  4. 4.School of Marine SciencesUniversity of MaineOronoUSA

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