• The Journal of Fisheries Business Administration
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• v.25 no.1
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• pp.37-59
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• 1994

Many studies to cope with the present problems of Korean coastal and offshore fisheries has been performed, but these were done partly in necessities and general studies for Korean inshore and offshore fisheries are in early stage. Most of these studies adopted analytical way of approach for each fishery individually and they could not reflect the effect of correlated interaction among fisheries on the several common species/stocks, and thus optimal effort allocation was impossible. To consider general fisheries and optimal effort allocation among competing mixed species, a linear programming (LP) approach is applied in this study and introduced into 16 important inshore and offshore fisheries with 13 constraining species which were chosen by annual yield order. This study is not based on the biological interaction among species (i.e., prey - predator system) but the technological interaction between species and fishing efforts. For the application of LP model in these fisheries, the standardization of fishing efforts through different fishing gears could not be successful and a new way of effort standardization through CPUE for vessel tonnage was originated. Total standardized fishing effort on a particular species i, Ei, is computed as the linear summation of standardized fishing effort generated by each fishery j. That is, (equation omitted) where $f_{j}$ is the total vessel tonnage of fishery j and aij is the coefficients contributing to the standardized fishing effort per ton for species i taken in fishery j. The total fishing effort level on species i due to both directed fishing and by - catch can thus be accounted in the aij's. Optimal effort allocation among the j fisheries may be considered a minimizing problem (minimize $\Sigma$ $f_{j}$), subject to the constraints that standardized fishing effort levels on particular species are maintained at, above, and below certain predefined levels. Fishing effort goals for individual species can be based on various biological and/or economic criteria, i.e., fishing effort level generating maximum sustainable yield and/or maximum economic yield. But in this study the $F_{0.1}$ criteria which was accepted as an approximate level for $F_{mey}$ by Outland and Boerema's (1973) study. The findings of this study are, (1) LP model can be applied to the Korean inshore and offshore fisheries giobally. (2) Through a new way of combining multiple different fisheries' efforts for a particular species together generating standardized fishing effort, Schaefer curve could be applied to the complex system successfully. (3) The results of this study for total reduction scale were mostly the same as those of prior studies, but different much from the individual scales of reduction. This study showed the necessities for exploitation of more concrete parameters to put into consideration of profitability of fisheries and social factors, and this model can be modified according to the actual constraints. Also, considering the age structure of stocks, this model can be developed into better one for better fisheries management.ent.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.4
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• pp.359-364
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• 2001

This paper presents case studies on the multi-species fisheries in Korean waters, Multi-species fisheries were divided into two types, that is, multi-species by a single fishery and single species by multiple fisheries. For the case of single species by multiple fisheries, the small yellow croaker stock caught mainly by the Korean pair trawl fishery and the Korean stow net fishery was selected. This approach uses both standardized fishing efforts for the two fisheries by a general linear model and some data for the economic analysis, and then estimates maximum sustainable yield (MSY), maximum economic yield (MEY) and fishing efforts for MSY and MEY, An analysis of interaction aspects between pair trawl and stow net fisheries was carried out to predict the optimal level of fishing effort from the economic point of view, which gives the largest benefits to the two fisheries.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.2
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• pp.208-217
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• 2021

This study described the fishing characteristics of Pacific herring Clupea pallasii and examined the relationship between its catch and sea temperature in Korean waters from 1970 to 2019. Although the herring catch in Korean waters stayed below 1,000 tons per year from the mid-1970s to mid-1980s, the catch in the winters in the East Sea of Korea started to increase markedly after 1987-1988, when the sea surface temperature (SST) seemed to shift to a warmer regime. Since the mid-2000s, overall, herring was caught throughout the year in the East Sea and eastern South Sea of Korea, and its catch significantly increased by around 30,000 tons per year. The main fishing grounds of herring in the poor fishing years until the mid-1980s were possibly formed in the western offshore of Korea, and subsequently the fishing grounds were distributed in the eastern coast of Korea. While the standardized catch per unit effort (CPUE) for two main fisheries of herring catch was significantly correlated with the herring catch since the 2000s, there was a gradual decline since the 2010s. The herring catch in the East Sea had significant positive correlations with SSTs, but that in the West Sea had a significant negative correlation.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.44 no.3
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• pp.194-206
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• 2008

This study standardized catch per unit effort(CPUE) of the Korean longline fishery, which has been used to assess the status of stock as an index of abundance, for bigeye and yellowfin tunas in the Indian Ocean. The Generalized Linear Model(GLM) was used to analyze the fishery data, which were catch in number and effort data collected each month from 1971 to 2007 by $5\;{\times}\;5$ degree of latitude and longitude. Explanatory variables for the GLM analysis were year, month, fishing area, number of hooks between floats(HBF), and environment factors. The HBF was divided into three classes while the area was divided into eight subareas. Although sea surface temperature(SST) and southern oscillation index(SOI) were considered as environmental factors, only SST was used to build a model based on statistical significance. Standardized CPUE for yellowfin tuna showed a declining trend, while nominal CPUE for the species showed an increasing trend.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.55 no.2
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• pp.95-104
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• 2019

This study is aimed to take a stock assessment of blackthroat seaperch Doederleinia seaperch regarding the fishing effort of large-powered Danish Seine Fishery and Southwest Sea Danish Seine Fishery. For the assessment, the state-space model was implemented and the standardized catch per unit effort (CPUE) of large powered Danish Seine Fishery and Southwest Sea Danish Seine Fishery which is necessary for the model was estimated with generalized linear model (GLM). The model was adequate for stock assessment because its r-square value was 0.99 and root mean square error (RMSE) value was 0.003. According to the model with 95% confidence interval, maximum sustainable yield (MSY) of Blackthroat seaperch is from 2,634 to 6,765 ton and carrying capacity (K) is between 33,180 and 62,820. Also, the catchability coefficient (q) is between 2.14E-06 and 3.95E-06 and intrinsic growth rate (r) is between 0.31 and 0.72.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.54 no.2
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• pp.116-123
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• 2018

Pacific bluefin tuna (Thunnus orientalis) has been mostly caught by the Korean offshore large purse seine fishery in Korean waters. The annual catch of Pacific bluefin tuna caught by the offshore large purse seine fishery in Korean waters showed less than 1,000 mt until the 1990s except for 1997. The catch sharply increased to 2,401 mt in 2000 and recorded the highest of 2,601 mt in 2003, but the catch has generally decreased with a fluctuation thereafter. The main fishing ground of Pacific bluefin tuna of this fishery is formed around Jeju Island. However, it expanded to the Yellow Sea, the coastal of Busan, and the East Sea, which depends on the migration patterns of Pacific bluefin tuna by season. The CPUE standardization of Pacific bluefin tuna was conducted using Generalized Linear Model (GLM) to assess the proxy of the abundance index. The data used for the GLM were catch (weight), effort (number of hauls), catch ratio of Pacific bluefin tuna, moon phase by year, quarter and area. The standardized CPUE from 2004 to 2011, except for 2003 and 2010, showed a steady trend, and then increased until 2014. The CPUE in 2015 decreased, and in 2016 was higher than that in 2015. The result of GLM suggests that the effect of the catch ratio of Pacific bluefin tuna is the largest factor affecting the nominal CPUE.