Delay-difference models are intermediate between simple surplus-production models and complicated age-structured models. Such intermediate models are more efficient and require less data than age-structured models. In...Delay-difference models are intermediate between simple surplus-production models and complicated age-structured models. Such intermediate models are more efficient and require less data than age-structured models. In this study, a delay-differ- ence model was applied to fit catch and catch per unit effort （CPUE） data （1975-2011） of the southern Atlantic albacore （Thunnus alalunga） stock. The proposed delay-difference model captures annual fluctuations in predicted CPUE data better than Fox model. In a Monte Carlo simulation, white noises （CVs） were superimposed on the observed CPUE data at four levels. Relative estimate error was then calculated to compare the estimated results with the true values of parameters a and fl in Ricker stock-recruitment model and the catchability coefficient q. a is more sensitive to CV than fl and q. We also calculated an 80% percentile confidence interval of the maximum sustainable yield （MSY, 21756 t to 23408 t; median 22490 t） with the delay-difference model. The yield of the southern Atlantic albacore stock in 2011 was 24122t, and the estimated ratios of catch against MSY for the past seven years were approxi- mately 1.0. We suggest that care should be taken to protect the albacore fishery in the southern Atlantic Ocean. The proposed de- lay-difference model provides a good fit to the data of southern Atlantic albacore stock and may be a useful choice for the assessment of regional albacore stock.展开更多
A continuous time delay-difference model(CTDDM) has been established that considers continuous time delays of biological processes.The southern Atlantic albacore(Thunnus alalunga) stock is the one of the commercially ...A continuous time delay-difference model(CTDDM) has been established that considers continuous time delays of biological processes.The southern Atlantic albacore(Thunnus alalunga) stock is the one of the commercially important tuna population in the marine world.The age structured production model(ASPM) and the surplus production model(SPM) have already been used to assess the albacore stock.However,the ASPM requires detailed biological information and the SPM lacks the biological realism.In this study,we focus on applying a CTDDM to the southern Atlantic albacore(T.alalunga) species,which provides an alternative method to assess this fishery.It is the first time that CTDDM has been provided for assessing the Atlantic albacore(T.alalunga) fishery.CTDDM obtained the 80%confidence interval of MSY(maximum sustainable yield) of(21 510 t,23 118 t).The catch in 2011(24 100 t) is higher than the MSY values and the relative fishing mortality ratio(F_(2011)/F_(MSY)) is higher than 1.0.The results of CTDDM were analyzed to verify the proposed methodology and provide reference information for the sustainable management of the southern Atlantic albacore stock.The CTDDM treats the recruitment,the growth,and the mortality rates as all varying continuously over time and fills gaps between ASPM and SPM in this stock assessment.展开更多
基金supported by the Fundamental Research Funds for the Central Universities of China (Grant No. 201022001)
文摘Delay-difference models are intermediate between simple surplus-production models and complicated age-structured models. Such intermediate models are more efficient and require less data than age-structured models. In this study, a delay-differ- ence model was applied to fit catch and catch per unit effort （CPUE） data （1975-2011） of the southern Atlantic albacore （Thunnus alalunga） stock. The proposed delay-difference model captures annual fluctuations in predicted CPUE data better than Fox model. In a Monte Carlo simulation, white noises （CVs） were superimposed on the observed CPUE data at four levels. Relative estimate error was then calculated to compare the estimated results with the true values of parameters a and fl in Ricker stock-recruitment model and the catchability coefficient q. a is more sensitive to CV than fl and q. We also calculated an 80% percentile confidence interval of the maximum sustainable yield （MSY, 21756 t to 23408 t; median 22490 t） with the delay-difference model. The yield of the southern Atlantic albacore stock in 2011 was 24122t, and the estimated ratios of catch against MSY for the past seven years were approxi- mately 1.0. We suggest that care should be taken to protect the albacore fishery in the southern Atlantic Ocean. The proposed de- lay-difference model provides a good fit to the data of southern Atlantic albacore stock and may be a useful choice for the assessment of regional albacore stock.
基金Supported by the Special Fund of Chinese Central Government for Basic Scientific Research Operations in Commonweal Research Institutes(No.201022001)
文摘A continuous time delay-difference model(CTDDM) has been established that considers continuous time delays of biological processes.The southern Atlantic albacore(Thunnus alalunga) stock is the one of the commercially important tuna population in the marine world.The age structured production model(ASPM) and the surplus production model(SPM) have already been used to assess the albacore stock.However,the ASPM requires detailed biological information and the SPM lacks the biological realism.In this study,we focus on applying a CTDDM to the southern Atlantic albacore(T.alalunga) species,which provides an alternative method to assess this fishery.It is the first time that CTDDM has been provided for assessing the Atlantic albacore(T.alalunga) fishery.CTDDM obtained the 80%confidence interval of MSY(maximum sustainable yield) of(21 510 t,23 118 t).The catch in 2011(24 100 t) is higher than the MSY values and the relative fishing mortality ratio(F_(2011)/F_(MSY)) is higher than 1.0.The results of CTDDM were analyzed to verify the proposed methodology and provide reference information for the sustainable management of the southern Atlantic albacore stock.The CTDDM treats the recruitment,the growth,and the mortality rates as all varying continuously over time and fills gaps between ASPM and SPM in this stock assessment.
