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A study on the forecasting biomass according to the changes in fishing intensity in the Korean waters of the East Sea

한국 동해 생태계의 어획강도 변화에 따른 자원량 예측 연구

  • 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)
  • 임정현 (부경대학교 해양생산시스템관리학부) ;
  • 서영일 (국립수산과학원 연근해자원과) ;
  • 장창익 (부경대학교 해양생산시스템관리학부)
  • Received : 2018.06.08
  • Accepted : 2018.07.12
  • Published : 2018.08.31

Abstract

Overfishing capacity has become a global issue due to over-exploitation of fisheries resources, which result from excessive fishing intensity since the 1980s. In the case of Korea, the fishing effort has been quantified and used as an quantified index of fishing intensity. Fisheries resources of coastal fisheries in the Korean waters of the East Sea tend to decrease productivity due to deterioration in the quality of ecosystem, which result from the excessive overfishing activities according to the development of fishing gear and engine performance of vessels. In order to manage sustainable and reasonable fisheries resources, it is important to understand the fluctuation of biomass and predict the future biomass. Therefore, in this study, we forecasted biomass in the Korean waters of the East Sea for the next two decades (2017~2036) according to the changes in fishing intensity using four fishing effort scenarios; $f_{current}$, $f_{PY}$, $0.5{\times}f_{current}$ and $1.5{\times}f_{current}$. For forecasting biomass in the Korean waters of the East Sea, parameters such as exploitable carrying capacity (ECC), intrinsic rate of natural increase (r) and catchability (q) estimated by maximum entropy (ME) model was utilized and logistic function was used. In addition, coefficient of variation (CV) by the Jackknife re-sampling method was used for estimation of coefficient of variation about exploitable carrying capacity ($CV_{ECC}$). As a result, future biomass can be fluctuated below the $B_{PY}$ level when the current level of fishing effort in 2016 maintains. The results of this study are expected to be utilized as useful data to suggest direction of establishment of fisheries resources management plan for sustainable use of fisheries resources in the future.

Keywords

References

  1. FAO Statistics. FAO Fisheries & Aquaculture - Statistics (http://www.fao.org/fishery/statistics/collections/en).
  2. FAO (Food and Agriculture Organization of the United Nations). 1996. Precautionary approach to fisheries. FAO Fisheries technical paper 350(2), 210.
  3. Kim JH and Lee KN. 2008. The analysis of fishing efforts and catch in Korea. The Journal of Fisheries Business Administration. 39(1), 163-194.
  4. KOSIS (Korean Statistical Information Service). Statistical database - Agriculture, forestry and fishery; Fishery. http://www.kosis.kr. Accessed in 2017.
  5. Lim JH. 2018. A comparative study on the estimation methods for the potential yield in the Korean waters of the East Sea. Ph.D. Thesis, Pukyong National University, Korea, 114.
  6. NIFS (National Institute of Fisheries and Science). 2016. Study on the estimation of fishing power according to the development of fishing vessels and gears. 114.
  7. Nishida T, Kitakado T, Iwasaki K and Itoh K. 2014. Kobe I (Kobe plot)+Kobe II (risk assessment) software (New version 3, 2014) - User's manual. IOTC-2014-WPTT16-53 Rev_2, 35.
  8. 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)
  9. Lim JH, Seo YI and Zhang CI. 2018. A comparative study on the estimation methods for the potential yield in the Korean waters of the East Sea. J Korean Soc Fish Ocean Technol, 54(2), 124-137. (DOI: 10.3796/KSFOT.2018.54.2.124)
  10. NIFS (National Institute of Fisheries and Science). 2017. Study on the estimation of exploitable carrying capacity and potential yield. 259.
  11. 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