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Retention probability of trawl codend for silver croaker (Argyrosomus argentatus)

트롤 끝자루에 대한 보구치(Argyrosomus argentatus)의 망목 선택성

KIM, Pyungkwan;PARK, Chang-Doo;LEE, Chun-Woo;KIM, Hyung-seok
김병관;박창두;이춘우;김형석

  • Received : 2019.01.23
  • Accepted : 2019.02.21
  • Published : 2019.02.28

Abstract

The annual production of silver croaker (Argyrosomus argentatus) in Korean towed fishing gears has been increased in recent five years. In 2017, the annual production of silver croaker in metric ton was increased 99.2% compared to 2013. However, the research for silver croaker has been focused on ecology in Korea. There has not been enough research in terms of fishing gears. Therefore, the research for retention probability for towed gears was conducted on covered codend method from June, 2016 to July, 2018. During the experiments, the total catch of silver croaker was 1,563. The geometry of the experimental trawl gear was controlled by trawl monitoring system; net height was 3.3 m, distance of trawldoors was 59.8 m and distance of wing net was 17.3 m. The selection curve for silver croaker was estimated by a logit model. The analysis was applied with the confidence interval to reduce uncertainty of the estimation. The $l_{50}$ was 13.87 cm and its selection range was 2.71 cm. P-value was estimated at 0.99. The mesh size for silver croaker in towed gears needs to be adjusted by considering its minimum maturity length, stakeholder's interests and fisheries regulations.

Keywords

Retention probability;Confidence interval;Maximum likelihood method

References

  1. Ahn SH and Han DH. 2012. Understanding of statistics, Biz press, Seoul, Korea, 200-222.
  2. Alverson DL, Freeberg MH, Pope JG and Murawski SA. 1996. A global assessment of fisheries bycatch and discards. FAO Fisheries technical paper 339, Rome, FAO. 233.
  3. Korean Statistical Information Service. 2013-2017. Fishery production statistics. Retrieved from http://kosis.kr/statHtml/statHtml.do?orgId=101&tblId=DT_1EW0005&conn_path=I3, Accessed Jan 2019.
  4. Fryer RJ. 1991. A model of between-haul variation in selectivity. ICES J Mar Sci 48(3), 281-290. (DOI:10.1093/icesjms/48.3.281) https://doi.org/10.1093/icesjms/48.3.281
  5. Harada M and Tokai T. 2007. Size selectivity of escape holes in conger tube traps for inshore hagfish Eptatretus burgeri and white-spotted conger Conger myriaster in Tokyo Bay. Fish Sci 73(3), 477-488. (DOI:10.1111/j.1444-2906.2007.01360.x) https://doi.org/10.1111/j.1444-2906.2007.01360.x
  6. Koh EH, An YS, Baeck GW and Jang CS. 2014. Feeding habitats of white croaker, Pennahia argentata in the coastal waters off Sejon island, Korea. Bull. Korean Fish Tech Soc 50(2), 139-146. (DOI:10.3796/KSFT.2014.50.2.139) https://doi.org/10.3796/KSFT.2014.50.2.139
  7. Millar R. 1993. Incorporation of between-haul variation using bootstrapping and nonparametric estimation of selection curves. Fish Bull 91(3), 564-572.
  8. NFRDI (National Fisheries Research and Development Institute). 2004. Commercial fishes of the coastal & offshore waters in Korea. Nati. Fish Res Dev Inst, Busan, Korea.
  9. Wienbeck H, Herrmann B, Moderhak W and Stepputtis D. 2011. Effect of netting direction and number of meshes around on size selection in the codend for Baltic cod (Gadus morhua). Fisheries Research 109(1), 80-88. (DOI:10.1016/j.fishres.2011.01.019) https://doi.org/10.1016/j.fishres.2011.01.019
  10. Wileman DA et. al. 1996. Manual of methods of measuring the selectivity of towed fishing gears. ICES Cooperative Research report 215, International council for the exploration of the sea, Copenhagen, Denmark. 16-56.

Acknowledgement

Supported by : 국립수산과학원