Surplus-production models are widely used in fish stock assessment and fisheries management due to their simplicity and lower data demands than age-structured models such as Virtual Population Analysis. The CEDA (catc...Surplus-production models are widely used in fish stock assessment and fisheries management due to their simplicity and lower data demands than age-structured models such as Virtual Population Analysis. The CEDA (catch-effort data analysis) and ASPIC (a surplus-production model incorporating covariates) computer packages are data-fitting or parameter estimation tools that have been developed to analyze catch-and-effort data using non-equilibrium surplus production models. We applied CEDA and ASPIC to the hairtail (Trichiurus japonicus) fishery in the East China Sea. Both packages produced robust results and yielded similar estimates. In CEDA, the Schaefer surplus production model with log-normal error assumption produced results close to those of ASPIC. CEDA is sensitive to the choice of initial proportion, while ASPIC is not. However, CEDA produced higher R 2 values than ASPIC.展开更多
The catch and effort data analysis（CEDA） and ASPIC（a stock assessment production model incorporating covariates） computer software packages were used to estimate the maximum sustainable yield（MSY） from the catch...The catch and effort data analysis（CEDA） and ASPIC（a stock assessment production model incorporating covariates） computer software packages were used to estimate the maximum sustainable yield（MSY） from the catch and effort data of Greater lizardfish Saurida tumbil fishery of Pakistan from 1986 to 2009. In CEDA three surplus production models of Fox, Schaefer and Pella-Tomlinson were used. Here initial proportion（IP） of 0.5 was used because the starting catch was roughly 50% of the maximum catch. With IP = 0.5, the estimated MSY from Fox model were 20.59 mt and 38.16 mt for normal and log-normal error assumptions, while the MSY from Schaefer and Pella-Tomlinson were 60.40, 60.40 and 60.40 mt, for normal, log-normal and gamma error assumptions respectively. The MSY values from Schaefer and Pella-Tomlinson models of three error assumptions were the same. The R2 values from those three models were above 0.6. When IP = 0.5, the MSY values estimated from ASPIC from Fox were 132 mt, and from logistic model were 69.4 mt, with R2 value above 0.8. Therefore we suggest the MSY of S. tumbil fishery from Pakistan to be 60–70 mt, which is higher than the latest catch, thus we would recommend that the fishing efforts for this fishery may be kept at the current level.展开更多
Catch and effort data were analyzed to estimate the maximum sustainable yield （MSY） of King Soldier Bream, Argyrops spinifer （Forsskal, 1775, Family： Sparidae）, and to evaluate the present status of the fish stoc...Catch and effort data were analyzed to estimate the maximum sustainable yield （MSY） of King Soldier Bream, Argyrops spinifer （Forsskal, 1775, Family： Sparidae）, and to evaluate the present status of the fish stocks exploited in Pakistani waters. The catch and effort data for the 25-years period 1985-2009 were analyzed using two computer software packages, CEDA （catch and effort data analysis） and ASPIC （a surplus production model incorporating covariates）. The maximum catch of 3 458 t was observed in 1988 and the minimum catch of 1 324 t in 2005, while the average annual catch ofA. spinifer over the 25 years was 2 500 t. The surplus production models of Fox, Schaefer, and Pella Tomlinson under three error assumptions of normal, log-normal and gamma are in the CEDA package and the two surplus models of Fox and logistic are in the ASPIC package. In CEDA, the MSY was estimated by applying the initial proportion （IP） of 0.8, because the starting catch was approximately 80% of the maximum catch. Except for gamma, because gamma showed maximization failures, the estimated results of MSY using CEDA with the Fox surplus production model and two error assumptions, were 1 692.08 t （R^2=0.572） and 1 694.09 t （R^2=0.606）, respectively, and from the Schaefer and the Pella Tomlinson models with two error assumptions were 2 390.95 t （R^2=0.563）, and 2 380.06 t （R^2=0.605）, respectively. The MSY estimated by the Fox model was conservatively compared to the Schaefer and Pella Tomlinson models. The MSY values from Schaefer and Pella Tomlinson models were the same. The computed values of MSY using the ASPIC computer software program with the two surplus production models of Fox and logistic were 1 498 t （R^2=0.917）, and 2 488 t （R^2=0.897） respectively. The estimated values of MSY using CEDA were about 1 700-2 400 t and the values from ASPIC were 1 500-2 500 t. The estimates output by the CEDA and the ASPIC packages indicate that the stock is overfished, and needs some effective management to reduce the fishing effort of the species in Pakistani waters.展开更多
Using surplus production model packages of ASPIC(a stock-production model incorporating covariates) and CEDA(Catch effort data analysis),we analyzed the catch and effort data of Sillago sihama fishery in Pakistan.ASPI...Using surplus production model packages of ASPIC(a stock-production model incorporating covariates) and CEDA(Catch effort data analysis),we analyzed the catch and effort data of Sillago sihama fishery in Pakistan.ASPIC estimates the pa-rameters of MSY(maximum sustainable yield),Fmsy(fishing mortality),q(catchability coefficient),K(carrying capacity or unexploited biomass) and B1/K(maximum sustainable yield over initial biomass).The estimated non-bootstrapped value of MSY based on logistic was 598 t and that based on the Fox model was 415 t,which showed that the Fox model estimation was more conservative than that with the logistic model.The R2 with the logistic model(0.702) is larger than that with the Fox model(0.541),which indicates a better fit.The coefficient of variation(cv) of the estimated MSY was about 0.3,except for a larger value 88.87 and a smaller value of 0.173.In contrast to the ASPIC results,the R2 with the Fox model(0.651-0.692) was larger than that with the Schaefer model(0.435-0.567),indicating a better fit.The key parameters of CEDA are:MSY,K,q,and r(intrinsic growth),and the three error assumptions in using the models are normal,log normal and gamma.Parameter estimates from the Schaefer and Pella-Tomlinson models were similar.The MSY estimations from the above two models were 398 t,549 t and 398 t for normal,log-normal and gamma error distributions,re-spectively.The MSY estimates from the Fox model were 381 t,366 t and 366 t for the above three error assumptions,respectively.The Fox model estimates were smaller than those for the Schaefer and the Pella-Tomlinson models.In the light of the MSY estimations of 415 t from ASPIC for the Fox model and 381 t from CEDA for the Fox model,MSY for S.sihama is about 400 t.As the catch in 2003 was 401 t,we would suggest the fishery should be kept at the current level.Production models used here depend on the assumption that CPUE(catch per unit effort) data used in the study can reliably quantify temporal variability in population abundance,hence the mod-eling results would be wrong if such an assumption is not met.Because the reliability of this CPUE data in indexing fish population abundance is unknown,we should be cautious with the interpretation and use of the derived population and management parameters.展开更多
汽车行业的智能化、网联化是大势所趋。随着整车电子架构的快速演变,已经开始由原本的分布式ECUs控制策略转变为功能更加强大、更加趋于集中式管理的域控制器控制策略。这也就意味着软件在整车中的占比将进一步提高,软件质量问题变得更...汽车行业的智能化、网联化是大势所趋。随着整车电子架构的快速演变,已经开始由原本的分布式ECUs控制策略转变为功能更加强大、更加趋于集中式管理的域控制器控制策略。这也就意味着软件在整车中的占比将进一步提高,软件质量问题变得更为凸显。无论是AS P I CE还是汽车功能安全ISO 26262、G B/T 34590都对系统/软件开发过程提出了要求。其中,配置管理就是非常重要的一个环节。展开更多
剩余产量模型是最简单和应用最广泛的渔业资源评估模型之一。CEDA(catch-effort data analysis)和ASPIC(a surplus-production model incorporating covariates)是使用非平衡剩余产量模型对渔业产量和捕捞努力量数据进行分析的计算机软...剩余产量模型是最简单和应用最广泛的渔业资源评估模型之一。CEDA(catch-effort data analysis)和ASPIC(a surplus-production model incorporating covariates)是使用非平衡剩余产量模型对渔业产量和捕捞努力量数据进行分析的计算机软件。根据中国台湾延绳钓渔业的单位捕捞努力量渔获量(CPUE)数据,利用CDEA和ASPIC软件对南大西洋长鳍金枪鱼(Thunnus alalunga)渔业进行研究。结果显示,CEDA中使用对数正态误差假设的Fox模型产生了最大的R2值以及最接近ASPIC分析结果的种群参数值,但是CEDA得到的R2值低于ASPIC。CEDA对不同初始B1/K值的反应比ASPIC敏感。ASPIC中Logistic产量模型对不同初始B1/K值的反应比Fox模型更加灵敏。CEDA和ASPIC得出的最大可持续产量基本一致。展开更多
Surplus production models(SPMs)are among the simplest and most widely used fishery stock assessment models.The catch-effort data analysis(CEDA)and a surplus production model incorporating covariates(ASPIC)are software...Surplus production models(SPMs)are among the simplest and most widely used fishery stock assessment models.The catch-effort data analysis(CEDA)and a surplus production model incorporating covariates(ASPIC)are softwares for analyzing fishery catch and fishing effort data using nonequilibrium SPMs.In China Fishery Statistical Yearbook,annual fishery production and fishing effort data of the Yellow Sea,Bohai Sea,East China Sea,and South China Sea have been published from 1979 till present.Using its catch and fishing effort data from 1980 to 2018,we apply the CEDA and ASPIC to evaluate fishery resources in Chinese coastal waters.The results show that the total maximum sustainable yield(MSY)estimate of the four China seas is 10.05-10.83 million tons,approximately equal to the marine fishery catch(10.44 million tons)reported in 2018.It can be concluded that China’s coastal fishery resources are currently fully exploited and must be protected with a precautionary approach.Both softwares produced similar results;however,the CEDA had a much higher R2 value(above 0.9)than ASPIC(about 0.2),indicating that CEDA can better fit the data and therefore is more suitable for analyzing the fishery resources in the coastal waters of China.展开更多
基金Supported by the Special Research Fund of Ocean University of China(No. 201022001)
文摘Surplus-production models are widely used in fish stock assessment and fisheries management due to their simplicity and lower data demands than age-structured models such as Virtual Population Analysis. The CEDA (catch-effort data analysis) and ASPIC (a surplus-production model incorporating covariates) computer packages are data-fitting or parameter estimation tools that have been developed to analyze catch-and-effort data using non-equilibrium surplus production models. We applied CEDA and ASPIC to the hairtail (Trichiurus japonicus) fishery in the East China Sea. Both packages produced robust results and yielded similar estimates. In CEDA, the Schaefer surplus production model with log-normal error assumption produced results close to those of ASPIC. CEDA is sensitive to the choice of initial proportion, while ASPIC is not. However, CEDA produced higher R 2 values than ASPIC.
基金The Special Research Fund of Ocean University of China under contract No.201022001
文摘The catch and effort data analysis（CEDA） and ASPIC（a stock assessment production model incorporating covariates） computer software packages were used to estimate the maximum sustainable yield（MSY） from the catch and effort data of Greater lizardfish Saurida tumbil fishery of Pakistan from 1986 to 2009. In CEDA three surplus production models of Fox, Schaefer and Pella-Tomlinson were used. Here initial proportion（IP） of 0.5 was used because the starting catch was roughly 50% of the maximum catch. With IP = 0.5, the estimated MSY from Fox model were 20.59 mt and 38.16 mt for normal and log-normal error assumptions, while the MSY from Schaefer and Pella-Tomlinson were 60.40, 60.40 and 60.40 mt, for normal, log-normal and gamma error assumptions respectively. The MSY values from Schaefer and Pella-Tomlinson models of three error assumptions were the same. The R2 values from those three models were above 0.6. When IP = 0.5, the MSY values estimated from ASPIC from Fox were 132 mt, and from logistic model were 69.4 mt, with R2 value above 0.8. Therefore we suggest the MSY of S. tumbil fishery from Pakistan to be 60–70 mt, which is higher than the latest catch, thus we would recommend that the fishing efforts for this fishery may be kept at the current level.
基金Supported by the Special Research Fund of Ocean University of China(No.201022001)
文摘Catch and effort data were analyzed to estimate the maximum sustainable yield （MSY） of King Soldier Bream, Argyrops spinifer （Forsskal, 1775, Family： Sparidae）, and to evaluate the present status of the fish stocks exploited in Pakistani waters. The catch and effort data for the 25-years period 1985-2009 were analyzed using two computer software packages, CEDA （catch and effort data analysis） and ASPIC （a surplus production model incorporating covariates）. The maximum catch of 3 458 t was observed in 1988 and the minimum catch of 1 324 t in 2005, while the average annual catch ofA. spinifer over the 25 years was 2 500 t. The surplus production models of Fox, Schaefer, and Pella Tomlinson under three error assumptions of normal, log-normal and gamma are in the CEDA package and the two surplus models of Fox and logistic are in the ASPIC package. In CEDA, the MSY was estimated by applying the initial proportion （IP） of 0.8, because the starting catch was approximately 80% of the maximum catch. Except for gamma, because gamma showed maximization failures, the estimated results of MSY using CEDA with the Fox surplus production model and two error assumptions, were 1 692.08 t （R^2=0.572） and 1 694.09 t （R^2=0.606）, respectively, and from the Schaefer and the Pella Tomlinson models with two error assumptions were 2 390.95 t （R^2=0.563）, and 2 380.06 t （R^2=0.605）, respectively. The MSY estimated by the Fox model was conservatively compared to the Schaefer and Pella Tomlinson models. The MSY values from Schaefer and Pella Tomlinson models were the same. The computed values of MSY using the ASPIC computer software program with the two surplus production models of Fox and logistic were 1 498 t （R^2=0.917）, and 2 488 t （R^2=0.897） respectively. The estimated values of MSY using CEDA were about 1 700-2 400 t and the values from ASPIC were 1 500-2 500 t. The estimates output by the CEDA and the ASPIC packages indicate that the stock is overfished, and needs some effective management to reduce the fishing effort of the species in Pakistani waters.
基金supported by the special research fund ofthe Ocean University of China(201022001)the Chinese Scholarship Council(CSC)
文摘Using surplus production model packages of ASPIC(a stock-production model incorporating covariates) and CEDA(Catch effort data analysis),we analyzed the catch and effort data of Sillago sihama fishery in Pakistan.ASPIC estimates the pa-rameters of MSY(maximum sustainable yield),Fmsy(fishing mortality),q(catchability coefficient),K(carrying capacity or unexploited biomass) and B1/K(maximum sustainable yield over initial biomass).The estimated non-bootstrapped value of MSY based on logistic was 598 t and that based on the Fox model was 415 t,which showed that the Fox model estimation was more conservative than that with the logistic model.The R2 with the logistic model(0.702) is larger than that with the Fox model(0.541),which indicates a better fit.The coefficient of variation(cv) of the estimated MSY was about 0.3,except for a larger value 88.87 and a smaller value of 0.173.In contrast to the ASPIC results,the R2 with the Fox model(0.651-0.692) was larger than that with the Schaefer model(0.435-0.567),indicating a better fit.The key parameters of CEDA are:MSY,K,q,and r(intrinsic growth),and the three error assumptions in using the models are normal,log normal and gamma.Parameter estimates from the Schaefer and Pella-Tomlinson models were similar.The MSY estimations from the above two models were 398 t,549 t and 398 t for normal,log-normal and gamma error distributions,re-spectively.The MSY estimates from the Fox model were 381 t,366 t and 366 t for the above three error assumptions,respectively.The Fox model estimates were smaller than those for the Schaefer and the Pella-Tomlinson models.In the light of the MSY estimations of 415 t from ASPIC for the Fox model and 381 t from CEDA for the Fox model,MSY for S.sihama is about 400 t.As the catch in 2003 was 401 t,we would suggest the fishery should be kept at the current level.Production models used here depend on the assumption that CPUE(catch per unit effort) data used in the study can reliably quantify temporal variability in population abundance,hence the mod-eling results would be wrong if such an assumption is not met.Because the reliability of this CPUE data in indexing fish population abundance is unknown,we should be cautious with the interpretation and use of the derived population and management parameters.
文摘汽车行业的智能化、网联化是大势所趋。随着整车电子架构的快速演变,已经开始由原本的分布式ECUs控制策略转变为功能更加强大、更加趋于集中式管理的域控制器控制策略。这也就意味着软件在整车中的占比将进一步提高,软件质量问题变得更为凸显。无论是AS P I CE还是汽车功能安全ISO 26262、G B/T 34590都对系统/软件开发过程提出了要求。其中,配置管理就是非常重要的一个环节。
文摘剩余产量模型是最简单和应用最广泛的渔业资源评估模型之一。CEDA(catch-effort data analysis)和ASPIC(a surplus-production model incorporating covariates)是使用非平衡剩余产量模型对渔业产量和捕捞努力量数据进行分析的计算机软件。根据中国台湾延绳钓渔业的单位捕捞努力量渔获量(CPUE)数据,利用CDEA和ASPIC软件对南大西洋长鳍金枪鱼(Thunnus alalunga)渔业进行研究。结果显示,CEDA中使用对数正态误差假设的Fox模型产生了最大的R2值以及最接近ASPIC分析结果的种群参数值,但是CEDA得到的R2值低于ASPIC。CEDA对不同初始B1/K值的反应比ASPIC敏感。ASPIC中Logistic产量模型对不同初始B1/K值的反应比Fox模型更加灵敏。CEDA和ASPIC得出的最大可持续产量基本一致。
基金This study is supported by the project from the Food and Agriculture Organization of the United Nations(FAO)(No.GF.FIRFD.RA20403020400).
文摘Surplus production models(SPMs)are among the simplest and most widely used fishery stock assessment models.The catch-effort data analysis(CEDA)and a surplus production model incorporating covariates(ASPIC)are softwares for analyzing fishery catch and fishing effort data using nonequilibrium SPMs.In China Fishery Statistical Yearbook,annual fishery production and fishing effort data of the Yellow Sea,Bohai Sea,East China Sea,and South China Sea have been published from 1979 till present.Using its catch and fishing effort data from 1980 to 2018,we apply the CEDA and ASPIC to evaluate fishery resources in Chinese coastal waters.The results show that the total maximum sustainable yield(MSY)estimate of the four China seas is 10.05-10.83 million tons,approximately equal to the marine fishery catch(10.44 million tons)reported in 2018.It can be concluded that China’s coastal fishery resources are currently fully exploited and must be protected with a precautionary approach.Both softwares produced similar results;however,the CEDA had a much higher R2 value(above 0.9)than ASPIC(about 0.2),indicating that CEDA can better fit the data and therefore is more suitable for analyzing the fishery resources in the coastal waters of China.
