STANDARDIZING CPUE OF ALBACORE TUNA (Thunnus alalunga Bonnaterre, 1788) ON TUNA LONGLINE FISHERY IN EASTERN INDIAN OCEAN

F. Rochman, B. Setyadji, A. Wujdi
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引用次数: 6

Abstract

Albacore (Thunnus alalunga) is the third dominant catch of Indonesian tuna longline fishery operating in the eastern Indian Ocean. The percentage production of albacore catch was reaching up 6% of the total catch of tuna groups in Indonesia. Thi study aims to examine a relative abundance indices using standardized catch per unit of effort (CPUE) of longliner based on albacore tuna. This information will give a valuable input and information to support stock assessment particularly in the regional basis. In this study, we use Generalized Linear Model (GLM) with Tweedie distribution to standardize the CPUE and to estimate relative abundance indices based on the Indonesian longline dataset time series. Data were collected from January 2006 to October 2015 (106 trip observer and 8.989 fishing days) by conducting direct onboard observation on tuna longline vessels operating in the Indian Ocean. The result show that year, area,hooks between floats, year*season, year*area and year* hooks between floats significantly influenced the nominal CPUE of albacore. The highest value of Standardized CPUE appeared in 2014 and probably related to the large number of foreign fishing vessels with a high capacity (over 60 GT) targeting frozen tuna including albacore. In 2015, standardized CPUE value was sharply decreased due to the ban of foreign vessels in Indonesia.
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关于印度洋东部金枪鱼延绳钓的标准化研究(Thunnus alalunga Bonnatere,1788)
长鳍金枪鱼(Thunnus alalunga)是印度尼西亚东印度洋延绳钓金枪鱼渔业的第三大主要渔获物。长鳍金枪鱼的渔获量占印度尼西亚金枪鱼总渔获量的比例达到6%。本研究旨在利用长鳍金枪鱼的标准化单位努力捕获量(CPUE)来检验相对丰度指数。这些资料将提供宝贵的投入和资料,以支持特别是在区域基础上的种群评估。本研究基于印尼延绳钓数据时间序列,采用具有Tweedie分布的广义线性模型(Generalized Linear Model, GLM)对CPUE进行标准化,并估算相对丰度指数。数据收集时间为2006年1月至2015年10月(106个行程观察员和8.989个渔日),通过对印度洋金枪鱼延绳钓渔船进行直接船上观测。结果表明,年、面积、鱼竿间钩、年*季节、年*面积和鱼竿间钩对长鳍金枪鱼的名义CPUE有显著影响。标准化CPUE最大值出现在2014年,可能与大量高容量(60 GT以上)的外国渔船捕捞包括长鳍金枪鱼在内的冷冻金枪鱼有关。2015年,由于印尼禁止外国船只进入,标准化CPUE值急剧下降。
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