کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8060707 | 1520472 | 2018 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A preliminary study on ABC estimation approach for ecosystem-based TAC management
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موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
اقیانوس شناسی
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چکیده انگلیسی
Korea's acceptable biological catch (ABC) for total allowable catch (TAC) management has been estimated by a five-tier system that relies on population-based stock assessment models according to available ecological information for pelagic or demersal species. To overcome the limitations of the current ABC estimation system based on population dynamic models, this study attempted to integrate the ecosystem-based fisheries assessment (EBFA) approach into Korea's current ABC estimation system, and has developed an ABC estimation approach for ecosystem-based TAC management. To estimate an ecosystem-based ABC, ABC estimated by the current ABC estimation system was adjusted depending on the species risk index (SRI) that was derived from risk analysis of EBFA. During the process, the SRI-F relationship which generalizes the relationship between SRI and fishing mortality (F) was devised, and was used to estimate an ecosystem-based ABC. Also, the SRI projection as a function of the F scenario was conducted to estimate the regression coefficient of a relationship of SRI and F. We demonstrated an ecosystem-based ABC estimation by applying it to the chub mackerel, one of the TAC species in Korea's large purse seine fishery. As a result, the F at ABC (0.39/year) was adjusted as 0.365/year, while ABC (180,000â¯mt) was reduced to 170,393â¯mt. We found that this approach can be used to conservatively estimate the TAC in an ecosystem-based context for quota-managed fisheries.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ocean & Coastal Management - Volume 157, 1 May 2018, Pages 9-22
Journal: Ocean & Coastal Management - Volume 157, 1 May 2018, Pages 9-22
نویسندگان
Hee Joong Kang, Young Il Seo, Chang Ik Zhang,