Effects of Ecological Competition on Assessing Yellowfin tuna (Thunnus albacares) and Bigeye tuna (Thunnus obesus) Stocks in the Atlantic Ocean by Production Model with a Bayesian Approach

博士 === 國立臺灣大學 === 海洋研究所 === 102 === Yellowfin tuna (Thunnus albacares) and bigeye tuna (Thunnus obesus) stocks in the Atlantic Ocean are mainly distributed in the tropical waters. These two stocks spawn in the Gulf of Guinea during summer. When they are in their juvenile stage, these two stocks mix...

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Main Authors: Chia-Lung Shih, 石佳隴
Other Authors: 許建宗
Format: Others
Language:zh-TW
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/60857273690338923136
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spelling ndltd-TW-102NTU052790222016-03-09T04:24:05Z http://ndltd.ncl.edu.tw/handle/60857273690338923136 Effects of Ecological Competition on Assessing Yellowfin tuna (Thunnus albacares) and Bigeye tuna (Thunnus obesus) Stocks in the Atlantic Ocean by Production Model with a Bayesian Approach 生態競爭對用貝氏估計生產量模式評估大西洋黃鰭鮪與大目鮪資源的影響 Chia-Lung Shih 石佳隴 博士 國立臺灣大學 海洋研究所 102 Yellowfin tuna (Thunnus albacares) and bigeye tuna (Thunnus obesus) stocks in the Atlantic Ocean are mainly distributed in the tropical waters. These two stocks spawn in the Gulf of Guinea during summer. When they are in their juvenile stage, these two stocks mix in the surface waters. In addition, the stomach contents of these two stocks show dietary overlap. Thus, we hypothesized that these two stocks may show the effects of ecological competition on both. The objective of this study is to investigate the effects of ecological competition on assessing yellowfin tuna and bigeye tuna stocks by using the surplus production model with a Bayesian approach. In the analysis of Taiwanese longline fishery data, the results showed that there were two fishing types in the fishery. One fishing type was using lower number hooks of per basket (8-11 hooks), operating majorly in the higher latitude of waters (north of 15oN and south of 20oS), targeting on albacore and called as regular longline fishery. Another fishing type was using higher number hooks per basket (15-18 hooks), operating majorly in the lower latitude of waters (15oN-20oS), targeting on bigeye tuna and bycatching yellowfin tuna, and called as deep longline fishery. The standardized yellowfin tuna and bigeye tuna abundance indexes of this study showed extreme high CPUEs in 1994 and 1995, and highly temperal variation. In the sensitivity analysis of Bayesian approach, the results showed that unreasonable priors setting and questionable country fishery abundance indexes would result in bias of stock assessment. While input data included bigeye tuna abundance indexes of Taiwanese longline fihsery, the estimated parameters of production model showed a slight diference. In the analysis of the effects of competition on assessing yellowfin tuna and bigeye tuna stocks, the results showed that the competition exist in the two stocks. Yellowfin tuna stock could obviously decrease the biomass of bigeye tuna stock (w2=0.2304) and bigeye tuna stock would lightly decrease the biomass of yellowfin tuna stock (w1=0.0981). The estimated parameters of yellowfin tuna and bigeye tuna stocks estimated by the model with competition became smaller than these estimated by the single-species model, but the maximum sustainable yield (73,000 tons) of bigeye tuna estimated by the model with competition were smaller than that (maximum sustainable yield: 95,000 tons) estimated by the single-species model. Thus, we suggested that the total allowable catch of yellowfin tuna stock could be maintained at the current catch level (110,000 tons), whereas that of bigeye tuna stock should be decreased from 85,000 tons to 40,000 tons to avoid overexploiting this stock. 許建宗 2014 學位論文 ; thesis 115 zh-TW
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language zh-TW
format Others
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description 博士 === 國立臺灣大學 === 海洋研究所 === 102 === Yellowfin tuna (Thunnus albacares) and bigeye tuna (Thunnus obesus) stocks in the Atlantic Ocean are mainly distributed in the tropical waters. These two stocks spawn in the Gulf of Guinea during summer. When they are in their juvenile stage, these two stocks mix in the surface waters. In addition, the stomach contents of these two stocks show dietary overlap. Thus, we hypothesized that these two stocks may show the effects of ecological competition on both. The objective of this study is to investigate the effects of ecological competition on assessing yellowfin tuna and bigeye tuna stocks by using the surplus production model with a Bayesian approach. In the analysis of Taiwanese longline fishery data, the results showed that there were two fishing types in the fishery. One fishing type was using lower number hooks of per basket (8-11 hooks), operating majorly in the higher latitude of waters (north of 15oN and south of 20oS), targeting on albacore and called as regular longline fishery. Another fishing type was using higher number hooks per basket (15-18 hooks), operating majorly in the lower latitude of waters (15oN-20oS), targeting on bigeye tuna and bycatching yellowfin tuna, and called as deep longline fishery. The standardized yellowfin tuna and bigeye tuna abundance indexes of this study showed extreme high CPUEs in 1994 and 1995, and highly temperal variation. In the sensitivity analysis of Bayesian approach, the results showed that unreasonable priors setting and questionable country fishery abundance indexes would result in bias of stock assessment. While input data included bigeye tuna abundance indexes of Taiwanese longline fihsery, the estimated parameters of production model showed a slight diference. In the analysis of the effects of competition on assessing yellowfin tuna and bigeye tuna stocks, the results showed that the competition exist in the two stocks. Yellowfin tuna stock could obviously decrease the biomass of bigeye tuna stock (w2=0.2304) and bigeye tuna stock would lightly decrease the biomass of yellowfin tuna stock (w1=0.0981). The estimated parameters of yellowfin tuna and bigeye tuna stocks estimated by the model with competition became smaller than these estimated by the single-species model, but the maximum sustainable yield (73,000 tons) of bigeye tuna estimated by the model with competition were smaller than that (maximum sustainable yield: 95,000 tons) estimated by the single-species model. Thus, we suggested that the total allowable catch of yellowfin tuna stock could be maintained at the current catch level (110,000 tons), whereas that of bigeye tuna stock should be decreased from 85,000 tons to 40,000 tons to avoid overexploiting this stock.
author2 許建宗
author_facet 許建宗
Chia-Lung Shih
石佳隴
author Chia-Lung Shih
石佳隴
spellingShingle Chia-Lung Shih
石佳隴
Effects of Ecological Competition on Assessing Yellowfin tuna (Thunnus albacares) and Bigeye tuna (Thunnus obesus) Stocks in the Atlantic Ocean by Production Model with a Bayesian Approach
author_sort Chia-Lung Shih
title Effects of Ecological Competition on Assessing Yellowfin tuna (Thunnus albacares) and Bigeye tuna (Thunnus obesus) Stocks in the Atlantic Ocean by Production Model with a Bayesian Approach
title_short Effects of Ecological Competition on Assessing Yellowfin tuna (Thunnus albacares) and Bigeye tuna (Thunnus obesus) Stocks in the Atlantic Ocean by Production Model with a Bayesian Approach
title_full Effects of Ecological Competition on Assessing Yellowfin tuna (Thunnus albacares) and Bigeye tuna (Thunnus obesus) Stocks in the Atlantic Ocean by Production Model with a Bayesian Approach
title_fullStr Effects of Ecological Competition on Assessing Yellowfin tuna (Thunnus albacares) and Bigeye tuna (Thunnus obesus) Stocks in the Atlantic Ocean by Production Model with a Bayesian Approach
title_full_unstemmed Effects of Ecological Competition on Assessing Yellowfin tuna (Thunnus albacares) and Bigeye tuna (Thunnus obesus) Stocks in the Atlantic Ocean by Production Model with a Bayesian Approach
title_sort effects of ecological competition on assessing yellowfin tuna (thunnus albacares) and bigeye tuna (thunnus obesus) stocks in the atlantic ocean by production model with a bayesian approach
publishDate 2014
url http://ndltd.ncl.edu.tw/handle/60857273690338923136
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