• Title/Summary/Keyword: Jack mackerel fishery

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A Study on Fisheries Management of Ecosystem-Based TAC using a Linear Programming (선형계획법을 이용한 생태계 기반 TAC 어업관리에 관한 연구)

  • Seo, Young-Il;Cheon, Seong-Hoon;Kim, Do-Hoon
    • The Journal of Fisheries Business Administration
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    • v.45 no.2
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    • pp.61-72
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    • 2014
  • This study aimed to empirically investigate the applicability of ecosystem-based TAC (Total Allowable Catch) fisheries management targeting the large purse seine fishery where multi-species are regulated by TAC. Using a linear programming, the optimal fishing effort and the catch amount by species which maximize fishing profits were analyzed under the constraint condition of catch limits by species. Analytical results showed that an application of TAC on only chub mackerel would have negative impacts on fish stocks such as hairtail and jack mackerel by increasing the level of fishing effort to achieve its allocated catch limit. However, under the constraint condition of catch limits of all species, it was shown that optimal catches of all species were achieved within their catch limits. It implies the importance of ecosystem-based management considering biological and technical interactions of species those were excluded in the traditional single species fisheries management.

Effects of Hook and Bait Types on Bigeye Tuna Catch Rates in the Tuna Longline Fishery (다랑어 연승어업에서 눈다랑어 어획률에 미치는 낚시 및 미끼의 효과)

  • Kim, Soon-Song;Moon, Dae-Yeon;An, Doo-Hae;Hwang, Seon-Jae;Kim, Yeong-Seung;Bigelow, Keith;Curran, Daniel
    • Korean Journal of Ichthyology
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    • v.20 no.2
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    • pp.105-111
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    • 2008
  • A pelagic tuna longline research cruise in the eastern and central Pacific Ocean from September to October of 2006 was conducted to compare catch rates with the use of different hook type and bait combinations. Traditional tuna hooks (J 4) and three circle hook types (C15, C16, C18), along with five bait types (chub mackerel (CM), jack mackerel (JM), milkfish (MF), sardine (SD), and squid (SQ)) and hook number as a proxy for hook depth were evaluated for their effect on bigeye tuna catch rates (fish per 1,000 hooks) using Generalized Linear Models (GLMs). Results from 28 sets indicated significant differences in bigeye catch rates between individual longline sets and hook number. The GLM explained 33% of the deviance in bigeye catch rates with these two factors. An alternative model formulation included bait type which had a small effect (explaining 2.7% of the deviance) on catch rates. Hook type had a negligible and non-significant effect in the GLMs. These results indicate that all of the hooks and baits tested are equally effective at catching bigeye tuna and that hook number (depth) was the paramount operational factor in explaining bigeye tuna catch rates.