DOI QR코드

DOI QR Code

A Comparative Analysis of Maximum Entropy and Analytical Models for Assessing Kapenta (Limnothrissa miodon) Stock in Lake Kariba

카리브호수 카펜타 자원량 추정을 위한 최대엔트피모델과 분석적 모델의 비교분석

  • Received : 2017.08.16
  • Accepted : 2017.12.05
  • Published : 2017.12.31

Abstract

A Maximum Entropy (ME) Model and an Analytical Model are analyzed in assessing Kapenta stock in Lake Kariba. The ME model estimates a Maximum Sustainable Yield (MSY) of 25,372 tons and a corresponding effort of 109,731 fishing nights suggesting overcapacity in the lake at current effort level. The model estimates a declining stock from 1988 to 2009. The Analytical Model estimates an Acceptable Biological Catch (ABC) annually and a corresponding fishing mortality (F) of 1.210/year which is higher than the prevailing fishing mortality of 0.927/year. The ME and Analytical Models estimate a similar biomass in the reference year 1982 confirming that both models are applicable to the stock. The ME model estimates annual biomass which has been gradually declining until less than one third of maximum biomass (156,047 tons) in 1988. It implies that the stock has been overexploited due to yieldings over the level of ABC compared to variations in annual catch, even if the recent prevailing catch levels were not up to the level of MSY. In comparison, the Analytical Model provides a more conservative value of ABC compared to the MSY value estimated by the ME model. Conservative management policies should be taken to reduce the aggregate amount of annual catch employing the total allowable catch system and effort reduction program.

카리브호수의 카펜타 자원량을 추정하기 위해 최대엔트로피(ME)모델과 분석적 모델이 적용된다. ME모델을 이용하여 25,372톤의 최대지속가능 어획량(MSY)과 MSY의 어획노력량인 109,731의 어획일수(fishing nights)를 추정하였는데, 이는 현재 어획노력량 수준이 과잉투자됨으로써 1988년 이후 2009년 현재까지 자원량을 감소시키는 요인인 것을 나타낸다. 분석적 모델은 매년의 생물학적 허용 어획량(ABC)과 연간 1.21의 어획사망계수(일반적 어획사망계수인 0.927 보다 큰)를 추정한다. 이 두 모델은 1982년 기준년도의 자원량 추정에 적용할 수 있는 유사한 자원량을 추정한다. ME모델에 의하면 1988년의 최대 자원량(156,047톤)에 대해 1/3수준이하 까지 점점 하락하는 결과를 추정하였는데, 이는 최근의 어획량이 MSY 수준 이하이지만 ABC수준보다 높게 나타나 남획된 것을 암시한다. 다시 말해서, 분석적 모델은 ME모델에서의 MSY보다 더 보수적인 ABC를 제공함으로써, 보수적인 어업관리정책(총허용어획량제도, 어획노력감소정책 등)을 적극적으로 고려해야함을 내포하고 있다.

Keywords

References

  1. Beverton, R. J. H. and S. Holt, On the Dynamics of Exploited Fish Populations, Chapman & Hall Fish and Fisheries Series, Vancouver, Canada, 1957.
  2. Brooks C., Introductory Econometrics for Finance, Cambridge university Press, 2002.
  3. Chifamba, P. C., Daily Rings on Otholiths as a Method for Ageing the Sardine Limnothrissa miodon in Lake Kariba. Trans. Zimbabwe Sci. Ass. 66, 1992.
  4. Cochrane, K. L., "The Influence of Food Availability, Breeding Seasons and Growth on Commercial Catches of Limnothrissa miodon (Boulenger) in Lake Kariba," J. Fish Biol. Vol. 24, 1984, pp. 623-635. https://doi.org/10.1111/j.1095-8649.1984.tb04833.x
  5. Golan, A, G. Judge, and D. Miller, A Maximum Entropy Econometrics, John Wiley and Sons. 1996b.
  6. Golan, A., G. Judge, and L. Karp, "A Maximum Entropy Approach to Estimation and Inference in Dynamic Models or Counting Fish in the Sea using Maximum Entropy," Journal of Economic Dynamics and Control, Vol. 20, 1996a, pp. 559-582. https://doi.org/10.1016/0165-1889(95)00864-0
  7. Hilborn, R. and C. J. Walters, "A General Model for Simulation of Stock and Fleet Dynamics in Spatially Heterogeneous Fisheries," Canadian Journal of Fisheries and Aquatic Sciences, Vol. 44, No. 7, 1987, pp. 1366-1369. https://doi.org/10.1139/f87-163
  8. http://www.uvm.edu/giee/AV/Spatial_Modeling_Book/4/node33.html
  9. Marshall B. E., "Growth and mortality of the Introduced Lake Tanganyika clupeid," Limnothrissa miodon, in Lake Kariba. J. Fish Biol. Vol. 31, 1987, pp. 603-615. https://doi.org/10.1111/j.1095-8649.1987.tb05265.x
  10. Pascoe S., A Bioeconomic Analysis of the UK Fisheries of the English Channel. PhD Thesis, University of Portsmouth, UK, 1998.
  11. Pyo, H. D., "A Comparative Analysis of Surplus Production Models and a Maximum Entropy Model for Estimating the Anchovy Stock in Korea," Jour. Fish. Mar. Sci. Edu. Vol. 18, No. 1, 2006, pp. 19-30.
  12. Quinn, T. D., and R. B. Deriso RB, Quantitative Fish Dynamics, Oxford University Press. New York, 1999, p. 542.
  13. Shannon, C. E., "A Mathematical Theory of Communication," Bell System Technical Journal, Vol. 27, 1948, pp. 379-423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
  14. Sun C. H., "Optimal Number of Fishing Vessels for Taiwan's Offshore Fisheries: A Comparison of Different Fleet Size Reduction Policies," Marine Resource Economics, Vol. 13, 1999, pp. 275-288.
  15. Theil, H., Applied Economic Forecasting, North-Holland. Amsterdam, 1966.
  16. Tresierra, A. and Z. Culquichicon, Fisheries Biology. Trujillo. Peru, 1993, p. 432.
  17. Vignaux, M., G. A. Vignaux, S. Lizamore, and D. Gresham, "Fine-scale Mapping of Fish Distribution From Commercial Catch and Effort Data Using Maximum Entropy Tomography," Canadian Journal of Fisheries and Aquatic Sciences, Vol. 55, No. 5, 1998, pp. 1220-1227. https://doi.org/10.1139/f97-297
  18. Xiao Y., "Subtleties In, And Practical Problems With, The Use of Production Models in Fish Stock Assessment," Fisheries Research, Vol. 33, 1997, pp. 17-36. https://doi.org/10.1016/S0165-7836(97)00065-9
  19. Zhang, C. I. and B. A. Megrey, "A revised Alverson and Carney Model for Estimating the Instantaneous Rate of Natural Mortality," Transactions of the American Fisheries Society, Vol. 135, 2006, pp. 620-633. https://doi.org/10.1577/T04-173.1
  20. Zhang, C. I. and B. A. Megrey, "A Simple Biomass-Based Length-Cohort Analysis for Estimating Biomass and Fishing Mortality," Transactions of the American Fisheries Society, Vol. 139, 2010, pp. 911-924. https://doi.org/10.1577/T09-041.1
  21. Zhang, C. I. and J. B. Lee. "Stock Assessment and Management Implications of Horse Mackerel (Trachurus japonicus) in Korean waters, based on the relationships between recruitment and the ocean environment," Progress in Oceanography, Vol. 49, 2001, pp. 513-537. https://doi.org/10.1016/S0079-6611(01)00038-6