Korean Journal of Fisheries and Aquatic Sciences (한국수산과학회지)

The Korean Society of Fisheries and Aquatic Science (한국수산과학회)
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Standardization of Catch per Unit Effort (CPUE) for Yellow Croaker (Larimichthys polyactis) in the East China Sea

동중국해 참조기자원에 대한 단위노력당어획량(CPUE)의 표준화

  • Lee, Dong-Woo (National Fisheries Research and Development Institute) ;
  • Lee, Jae-Bong (National Fisheries Research and Development Institute) ;
  • Kim, Yeong-Hye (National Fisheries Research and Development Institute) ;
  • Jung, Suk-Geun (National Fisheries Research and Development Institute)
  • Published : 2008.10.31
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Abstract

Yellow croaker (Larimichthys polyactis) is a major target species of large pair trawl fishery in the East China Sea. To standardize catch per unit effort (CPUE) of yellow croaker for the large pair trawl fishery, generalized linear model (GLM) was applied to evaluate and eliminate the influence of the explanatory factors (year, month, horse power and gross tonnage of vessel) on daily catches per boat collected and compiled by National Fisheries Research and Development Institute (NFRDI) from 1990 to 2007 at the fishery auction places of Busan, Masan and Incheon in Korea. Results of GLM showed that all of the factors significantly influenced on CPUE, explaining 36% of the total deviance. The standardized CPUE indicated that the abundance of yellow croaker in 2000's was 1.7 times higher than the CPUE in 1990's.

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References

  1. Butterworth, D.S. 1996. A possible alternative approach for generalized linear model analysis of tuna CPUE data. ICCAT Col. Vol. Sci. Pap., 45, 123-124
  2. Cooke, J.G. and K. Lankester. 1996. Consideration of statistical models for catch-effort indices for use in tuning VPAs. ICCAT Col. Vol. Sci. Pap. 45, 125-131
  3. Dobson, A.J. 1990. An introduction to generalized linear models. Chapman and Hall. London, 1-174
  4. Garcia-Rodriguez, M. 2003. Characterization and stan- dardization of a red shrimp, Aristeus antennatus (Risso, 1816), fishery off the Alicante gulf (SE Spain). Sci. Mar., 67(1), 63-74
  5. Gavaris, S. 1980. Use of a multiplicative model to estimate catch rate and effort from commercial data. Can. J. Fish. Aquat. Sci., 37, 2272-2275 https://doi.org/10.1139/f80-273
  6. Gudmundsdottir, A. and A. Nicolajsen. 2003. Standardized CPUE indices for Shrimp (Pandalus borealis) in Division 3M (Flemish Cap) 1993-2003, Serial No. N4932 NAFO SCR Doc. 03/90
  7. Hwang, B.N. and B.Q. Hong. 1985. On the Seasonal Distribution, Movement and Abundance of Hairtail, Trichiurus lepturus Linne, in the East China Sea and Yellow Sea, Bull. Nat'l. Fish. Res. Dev. Inst. Korea, No. 36, 13-22
  8. Hilborn, R. and C.J. Walters. 1992. Quantitative fisheries stock assessment: choice, dynamics and uncertainty. Chapman and Hall, New York
  9. Ihaka, R. and R. Gentleman. 1996. R: a language for data analysis and graphics. J. Comput. Graphic. Stat., 5, 299-314 https://doi.org/10.2307/1390807
  10. Kang, J.S. 2003. The United Nation convention on the law of the sea and fishery relations between Korea, Japan and China. Marine Policy, 27, 111-124 https://doi.org/10.1016/S0308-597X(02)00084-2
  11. Mario, S., P. Sartor and P. Belcari. 2003. Analysis of the factors affecting crustacean trawl fishery catch rates in the northern Tyrrhenian Sea (western Mediterranean). Fisheries Reserach, 65, 271-284 https://doi.org/10.1016/j.fishres.2003.09.019
  12. Maunder, M.N. 2001. A general framework for integrating the standardization of catch per unit of effort into stock assessment models. Can. J. Fish. Aquat. Sci., 58, 795-803 https://doi.org/10.1139/cjfas-58-4-795
  13. Maunder, M.N. and A.E. Punt. 2004. Standardizing catch and effort data: a review of recent approaches, Fisheries Research, 70, 141-159 https://doi.org/10.1016/j.fishres.2004.08.002
  14. Park, B.S. and M.K. Lee. 2005. The analysis of fishery buy-back programs of offshore fisheries concerning fishery production. Jour. Fish. Mar. Sci. Edu., 17(1), 115-131
  15. Park, J.Y. and J.H. Choi. 2000. Evaluation and future tasks of the Korea-China fisheries agreement. The Journal of Fisheries Business Administration, Korea, 31(2), 67-91
  16. Quinn II, T.J. and R.B. Deriso. 1999. Quantitative Fish Dynamics. Oxford University Press, New York
  17. R Development Core Team. 2004. R: A language and environment for statistical computing. Retrieved from http://www.R-project.org on June 17
  18. Robson, D.S. 1966. Estimation of the relative fishing power of individual ships. Research Bulletin, International Commission for the Northwest Atlantic Fisheries, 3, 5-14
  19. Shono, H. 2008. Application of statistical modeling and data mining method to the fish stock analyses. Bull. Fish. Res. Agen., No. 22, 1-85
  20. Yang, S.K. and K.D. Cho. 1982. The relationship between oceanographic condition and fishing ground distri- bution of Yellow croaker in the East China Sea and the Yellow sea. Bull. Korean Fish. Soc., 15, 26-34
  21. Yeon, I.J. and C.S. Park. 1991. Changes in distributional area on the stock fluctuation of yellow croaker, Pseudosciaena polyactis Bleeker, Bull. Nat'l. Fish. Res. Dev. Inst. Korea, No. 45, 85-100

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