We evaluated the effect of various error sources in fishery harvest/effort data on the maximum sustainable yield （MSY） and corresponding fishing effort （EMsv） using Monte Carlo simulation analyses. A high coeffici...We evaluated the effect of various error sources in fishery harvest/effort data on the maximum sustainable yield （MSY） and corresponding fishing effort （EMsv） using Monte Carlo simulation analyses. A high coefficient of variation （CV） of the catch and effort values biased the estimates of MSY and EMsv. Thus, the state of the fisheries resource and its exploitation was overestimated. We compared the effect using three surplus production models, Hilborn-Waters （H-W）, Schnute, and Prager models. The estimates generated using the H-W model were significantly affected by the CV. The Schnute model was least affected by errors in the underlying data. The CVof the catch data had a greater impact on the assessment than the CV of the fishing effort. Similarly, the changes in CV had a greater impact on the estimated maximum sustainable yield （MSY） than on the corresponding estimate of fishing effort （EMsY）. We discuss the likely effect of these biases on management efforts and provide suggestions for the improvement of fishery evaluations.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
Case-Based Reasoning （CBR） is an AI approach and been applied to many areas. However, one area - geography - has not been investigated systematically and thus has been identified as the focus for this study. This pa...Case-Based Reasoning （CBR） is an AI approach and been applied to many areas. However, one area - geography - has not been investigated systematically and thus has been identified as the focus for this study. This paper intends to further extend current CBR to a geographic CBR （Geo-CBR）. First, the concept of Geo-CBR is proposed. Second, a representation model for geographic cases has been established based on the Tesseral model and on a further extension in spatio-temporal dimensions for geographic cases. Third, a reasoning model for Geo-CBR is developed by considering the spatio-temporat characteristics and the uncertain and limited information of geographic cases. Finally, the Geo-CBR model is applied to forecasting the production of ocean fisheries to demonstrate the applicability of the developed Geo-CBR in solving problems in the real world. According to the experimental results, Geo-CBR is an effective and easy-to-implement approach for predicting geographic cases quantitatively.展开更多
Pakistani marine waters are under an open access regime. Due to poor management and policy implications, blind fishing is continued which may result in ecological as well as economic losses. Thus, it is of utmost impo...Pakistani marine waters are under an open access regime. Due to poor management and policy implications, blind fishing is continued which may result in ecological as well as economic losses. Thus, it is of utmost importance to estimate fishery resources before harvesting. In this study, catch and effort data, 1996-2009, of Kiddi shrimp Parapenaeopsis stylifera fishery from Pakistani marine waters was analyzed by using specialized fishery software in order to know fishery stock status of this commercially important shrimp. Maximum, minimum and average capture production ofP. stylifera was observed as 15 912 metric tons （mr） （1997）, 9 438 mt （2009） and 11 667 mt/a. Two stock assessment tools viz. CEDA （catch and effort data analysis） and ASPIC （a stock production model incorporating covariates） were used to compute MSY （maximum sustainable yield） of this organism. In CEDA, three surplus production models, Fox, Schaefer and Pella-Tomlinson, along with three error assumptions, log, log normal and gamma, were used. For initial proportion （IP） 0.8, the Fox model computed MSY as 6 858 nat （CV=0.204, R^2=0.709） and 7 384 mt （CV=0.149, R^2=0.72） for log and log normal error assumption respectively. Here, gamma error produced minimization failure. Estimated MSY by using Schaefer and Pella-Tomlinson models remained the same for log, log normal and gamma error assumptions i.e. 7 083 mt, 8 209 mt and 7 242 mt correspondingly. The Schafer results showed highest goodness of fit R2 （0.712） values. ASPIC computed MSY, CV, R2, FMsv and BMsv parameters for the Fox model as 7 219 nat, 0.142, 0.872, 0.111 and 65 280, while for the Logistic model the computed values remained 7 720 mt, 0.148, 0.868, 0.107 and 72 110 correspondingly. Results obtained have shown that P. stylifera has been overexploited. Immediate steps are needed to conserve this fishery resource for the future and research on other species of commercial importance is urgently needed.展开更多
基金Supported by the National Natural Science Foundation for Young Scientists of China (No. 40801225)the Natural Science Foundation of Zhejiang Province (No. Y3090038)
文摘We evaluated the effect of various error sources in fishery harvest/effort data on the maximum sustainable yield （MSY） and corresponding fishing effort （EMsv） using Monte Carlo simulation analyses. A high coefficient of variation （CV） of the catch and effort values biased the estimates of MSY and EMsv. Thus, the state of the fisheries resource and its exploitation was overestimated. We compared the effect using three surplus production models, Hilborn-Waters （H-W）, Schnute, and Prager models. The estimates generated using the H-W model were significantly affected by the CV. The Schnute model was least affected by errors in the underlying data. The CVof the catch data had a greater impact on the assessment than the CV of the fishing effort. Similarly, the changes in CV had a greater impact on the estimated maximum sustainable yield （MSY） than on the corresponding estimate of fishing effort （EMsY）. We discuss the likely effect of these biases on management efforts and provide suggestions for the improvement of fishery evaluations.
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Case-Based Reasoning （CBR） is an AI approach and been applied to many areas. However, one area - geography - has not been investigated systematically and thus has been identified as the focus for this study. This paper intends to further extend current CBR to a geographic CBR （Geo-CBR）. First, the concept of Geo-CBR is proposed. Second, a representation model for geographic cases has been established based on the Tesseral model and on a further extension in spatio-temporal dimensions for geographic cases. Third, a reasoning model for Geo-CBR is developed by considering the spatio-temporat characteristics and the uncertain and limited information of geographic cases. Finally, the Geo-CBR model is applied to forecasting the production of ocean fisheries to demonstrate the applicability of the developed Geo-CBR in solving problems in the real world. According to the experimental results, Geo-CBR is an effective and easy-to-implement approach for predicting geographic cases quantitatively.
基金Supported by the Earmarked Fund for Modern Agro-Industry Technology Research System of Chinathe Special Research Fund of Ocean University of China(No.201022001)
文摘Pakistani marine waters are under an open access regime. Due to poor management and policy implications, blind fishing is continued which may result in ecological as well as economic losses. Thus, it is of utmost importance to estimate fishery resources before harvesting. In this study, catch and effort data, 1996-2009, of Kiddi shrimp Parapenaeopsis stylifera fishery from Pakistani marine waters was analyzed by using specialized fishery software in order to know fishery stock status of this commercially important shrimp. Maximum, minimum and average capture production ofP. stylifera was observed as 15 912 metric tons （mr） （1997）, 9 438 mt （2009） and 11 667 mt/a. Two stock assessment tools viz. CEDA （catch and effort data analysis） and ASPIC （a stock production model incorporating covariates） were used to compute MSY （maximum sustainable yield） of this organism. In CEDA, three surplus production models, Fox, Schaefer and Pella-Tomlinson, along with three error assumptions, log, log normal and gamma, were used. For initial proportion （IP） 0.8, the Fox model computed MSY as 6 858 nat （CV=0.204, R^2=0.709） and 7 384 mt （CV=0.149, R^2=0.72） for log and log normal error assumption respectively. Here, gamma error produced minimization failure. Estimated MSY by using Schaefer and Pella-Tomlinson models remained the same for log, log normal and gamma error assumptions i.e. 7 083 mt, 8 209 mt and 7 242 mt correspondingly. The Schafer results showed highest goodness of fit R2 （0.712） values. ASPIC computed MSY, CV, R2, FMsv and BMsv parameters for the Fox model as 7 219 nat, 0.142, 0.872, 0.111 and 65 280, while for the Logistic model the computed values remained 7 720 mt, 0.148, 0.868, 0.107 and 72 110 correspondingly. Results obtained have shown that P. stylifera has been overexploited. Immediate steps are needed to conserve this fishery resource for the future and research on other species of commercial importance is urgently needed.
