DOI QR코드

DOI QR Code

한국 동해 생태계의 잠재생산량 추정방법에 관한 비교 연구

A comparative study on the estimation methods for the potential yield in the Korean waters of the East Sea

  • 임정현 (부경대학교 해양생산시스템관리학부) ;
  • 서영일 (국립수산과학원 연근해자원과) ;
  • 장창익 (부경대학교 해양생산시스템관리학부)
  • LIM, Jung-Hyun (Department of Marine Production System Management, Pukyong National University) ;
  • SEO, Young-Il (Fisheries Resources Management Division, National Institute of Fisheries Science) ;
  • ZHANG, Chang-Ik (Department of Marine Production System Management, Pukyong National University)
  • 투고 : 2018.04.12
  • 심사 : 2018.05.09
  • 발행 : 2018.05.31

초록

Due to the decrease in coastal productivity and deterioration in the quality of ecosystem which result from the excessive overfishing of fisheries resources and the environmental pollution, fisheries resources in the Korean waters hit the dangerous level in respect of quantity and quality. In order to manage sustainable and effective fisheries resources, it is necessary to suggest the potential yield (PY) for clarifying available fisheries resources in the Korean waters. So far, however, there have been few studies on the estimation methods for PY in Korea. In addition, there have been no studies on the comparative analysis of the estimation methods and the substantial estimation methods for PY targeted for large marine ecosystem (LME) For the reasonable management of fisheries resources, it is necessary to conduct a comprehensive study on the estimation methods for the PY which combines population dynamics and ecosystem dynamics. To reflect the research need, this study conducts a comparative analysis of estimation methods for the PY in the Korean waters of the East Sea to understand the advantages and disadvantages of each method, and suggests the estimation method which considered both population dynamics and ecosystem dynamics to supplement shortcomings of each method. In this study, the maximum entropy (ME) model of the holistic production method (HPM) is considered to be the most reasonable estimation method due to the high reliability of the estimated parameters. The results of this study are expected to be used as significant basic data to provide indicators and reference points for sustainable and reasonable management of fisheries resources.

키워드

참고문헌

  1. Alias M. 2003. Trophic Model of the Coastal Fisheries Ecosystem of the West Coast of Penisular Malaysia. WorldFish Center Conference Proceedings 67, 313-332.
  2. Alverson DL, Longhurst AR and Gulland JA. 1970. How much food from the sea? Science 168, 503-505. (DOI: 10.1126/science.168.3930.503)
  3. Beddington JR and Kirkwood GP. 2005. The estimation of potential yield and stock status using life-history parameters. Phil Trans R Soc B 360, 163-170. (DOI: 10.1098/rstb.2004.1582)
  4. Christensen V and Pauly D. 1992. ECOPATH II a software for balancing steady ecosystem models and calculating network characteristics. Ecological Modeling 61, 169-185. (DOI: 10.1016/0304-3800(92)90016-8)
  5. Christensen V and Waters CJ. 2004. Ecopath with Ecosim: methods, capabilities and limitations. Ecological Modeling 172, 109-139. (DOI: 10.1016/j.ecolmodel.2003.09.003)
  6. Coll M, Palomera I and Tudela S. 2009a. Decadal changes in a NW Mediterranean Sea food web in relation to fishing exploitation. Ecological Modeling 220, 2088-2102. (DOI: 10.1016/j.ecolmodel.2009.04.049)
  7. Coll M, Santojanni A, Palomera I and Arneri E. 2009b. Food-web changes in the Adriatic Sea over the last three decades. Marine Ecology Progress Series 381, 17-37. (DOI: 10.3354/meps07944)
  8. Fox WW Jr. 1974. An overview of production modeling. Working document submitted to the workshop on population dynamics of Tuna, sponsored by the International Commission for the Conservation of Atlantic Tunas, and held at Nantes, France, WTPD- Nantes/74/13, 143-156.
  9. Golan A, Judge G and Karp L. 1996. A maximum entropy approach to estimation and inference in dynamic models or counting fish in the sea with maximum entropy. Journal of Economic Dynamics and Control 20, 559-582. (DOI: 10.1016/0165-1889(95)00864-0)
  10. Gulland JA. 1971. The fish resources of the ocean. Fishing News Book, West By fleet, 1-255.
  11. Jang SH, Ryu HS and Lee JH. 2011. Stock assessment and management implications of the Korean aucha perch (Coreoperca herzi) in freshwater: (2) Estimation of potential yield assessment and stock of Coreoperca herzi in the mid-upper system of the Seomjin River. Korean. J. Limnol. 44(2), 172-177.
  12. Kim HA. 2016. A study on the estimation of potential yield for Korean west coast fisheries. Master's thesis, Pukyong National University, Korea, 1-134.
  13. Kim S and Kang S. 1999. Recent development in the concept and research direction for carrying capacity of marine ecosystem. J. Korean Soc Fish Res 2, 101-110.
  14. KOSIS (Korean Statistical Information Service). Statistical database -Agriculture, Forestry and Fishery; Fishery. http://www.kosis.kr. Accessed in 2017.
  15. Lee JB, Shin YJ, Lee JH, Choi YM, Lee DW and Cha HK. 2012. Estimation of potential fishery yield for Corbicula japonica in the Seomjin River, Korea. Korean J Malacol 28(2), 91-99. https://doi.org/10.9710/kjm.2012.28.2.091
  16. Lee MW. 2014. Ecosystem-base stock assessment and fisheries management in the west coast of Korea. Doctoral dissertation, Pukyong National University, Korea, 1-130.
  17. Lee SW, Lee HS, Yoo JC, Je JG, Levings C and Paek WK. 2002. Factors affecting the conservation and distribution of migratory waterbirds in the southern tidal flats of Ganghwa Island, Korea. Kor. J. Env. Eco. 16(1), 34-45.
  18. Lassalle G, Gascuel D, Loch FL, Lobry J, Pierce GJ, Ridoux V, Santos MB, Spitz J and Niquil N. 2012. An ecosystem approach for the assessment of fisheries impacts on marine top predators: the Bay of Biscay case study. ICES Journal of Marine Science 69(6), 925-938. (DOI: 10.1093/icesjms/fss049)
  19. Libralato S, Coll M, Tudela S, Palomera I and Pranovi F. 2008. Novel index for quantification of ecosystem effects of fishing as removal of secondary production. Marine Ecology Progress Series 355, 107-129. (DOI: 10.3354/meps07224)
  20. Lim JH. 2018. A Comparative Study on the Estimation Methods for the Potential Yield in the Korean Waters of the East Sea. Doctoral dissertation, Pukyong National University, Korea, 114.
  21. Mackinson S and Daskalov G. 2007. An Ecosystem Model of the North Sea to Support an Ecosystem Approach to Fisheries Management: Description and Parameterisation. Sci. Ser. Tech Rep., Cefas Lowestoft 142, 196.
  22. Mustafa MG. 2003. Trophic model of the coastal ecosystem in the waters of Bangladesh, Bay of Bengal. WorldFish Center Conference Proceedings 67, 263-280.
  23. NIFS (National Institute of Fisheries and Science). 2016. Study on the Estimation of Fishing Power according to the Development of Fishing Vessels and Gears. 1-114.
  24. NIFS (National Institute of Fisheries and Science). 2016. Fishing trend and stock assessment of major species in the Korean waters. 1-205.
  25. Prager MH. 1992a. ASPIC: A surplus-production model incorporating covariates. ICCAT Collected Volume of Scientific Papers 28, 218-229.
  26. Prager MH. 1992b. Recent Developments in Extending the ASPIC Production Model. ICCAT Working Document SCRS/92/127, 1-10.
  27. Prager MH. 2005. User's Manual for ASPIC: A Stock-Production Model Incorporating Covariates (ver. 5) and Auxiliary Program. National Marine Fisheries Service Beaufort Laboratory Document BL-2004-01, 1-27.
  28. Ryther JH. 1969. Photosynthesis and fish production in the sea. Science, 166, 72-76. (DOI:10.1126/science.166.3901.72)
  29. Seo YI, Hwang KS, Cha HK, Oh TY, Jo HS, Kim BY, Ryu KJ and Lee YW. 2017. Change of relative fishing power index from technological development in the offshore large powered purse seine fishery. J Korean Soc Fish Technol. 53(1), 12-18. (DOI: 10.3796/KSFT.2017.53.1.012)
  30. Shin YJ. 2009. A method for estimating potential fishery yield in coastal waters. Master's thesis, Pukyong National University, Korea, 1-53.
  31. Tamura T and Fujise Y. 2002. Geographical and seasonal changes of the prey species of minke whale in the Northwestern Pacific. ICES Journal of Marine Science, 59: 516-528. (DOI: 10.1006/jmsc.2002.1199)
  32. Theil H. 1966. Applied Economic Forecasting. Chicago, Rand McNally.
  33. Trites AW, Livingston PA, Mackinson S, Vasconcellos MC, Springer AM and Pauly D. 1999. Ecosystem change and the decline of marine mammals in the Eastern Bering Sea: testing the ecosystem shift and commercial whaling hypotheses. Fisheries Centre Research Reports, 7, 1-100.
  34. Tukey JW. 1958. Bias and confidence in not quite large samples. The Annals of Mathematical Statistics 29, 614-623. https://doi.org/10.1214/aoms/1177706647