Assessing the Fishery Resource Status of China’s Coastal Waters Using Surplus Production Models

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.

Fishery stock assessment of Kiddi shrimp (Parapenaeopsis stylifera) in the Northern Arabian Sea Coast of Pakistan by using surplus production models

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.

A stock assessment for Illex argentinus in Southwest Atlantic using an environmentally dependent surplus production model

The southern Patagonian stock（SPS） of Argentinian shortfin squid, Illex argentinus, is an economically important squid fishery in the Southwest Atlantic. Environmental conditions in the region play an important role in regulating the population dynamics of the I. argentinus population. This study develops an environmentally dependent surplus production（EDSP） model to evaluate the stock abundance of I. argentines during the period of 2000 to 2010. The environmental factors（favorable spawning habitat areas with sea surface temperature of 16–18°C） were assumed to be closely associated with carrying capacity（K） in the EDSP model. Deviance Information Criterion（DIC） values suggest that the estimated EDSP model with environmental factors fits the data better than a Schaefer surplus model without environmental factors under uniform and normal scenarios.The EDSP model estimated a maximum sustainable yield（MSY） from 351 600 t to 685 100 t and a biomass from 1 322 400 t to1 803 000 t. The fishing mortality coefficient of I. argentinus from 2000 to 2010 was smaller than the values of F（0.1） and F（MSY）. Furthermore, the time series biomass plot of I. argentinus from 2000 to 2010 shows that the biomass of I.argentinus and this fishery were in a good state and not presently experiencing overfishing. This study suggests that the environmental conditions of the habitat should be considered within squid stock assessment and management.

Application of the Moving Averaging Technique in Surplus Production Models

Surplus production models are the simplest analytical methods effective for fish stock assessment and fisheries management. In this paper, eight surplus production estimators(three estimation procedures) were tested on Schaefer and Fox type simulated data in three simulated fisheries(declining, well-managed, and restoring fisheries) at two white noise levels. Monte Carlo simulation was conducted to verify the utility of moving averaging(MA), which was an important technique for reducing the effect of noise in data in these models. The relative estimation error(REE) of maximum sustainable yield(MSY) was used as an indicator for the analysis, and one-way ANOVA was applied to test the significance of the REE calculated at four levels of MA. Simulation results suggested that increasing the value of MA could significantly improve the performance of the surplus production model(low REE) in all cases when the white noise level was low(coefficient of variation(CV) = 0.02). However, when the white noise level increased(CV= 0.25), adding the value of MA could still significantly enhance the performance of most models. Our results indicated that the best model performance occurred frequently when MA was equal to 3; however, some exceptions were observed when MA was higher.

Application of CEDA and ASPIC computer packages to the hairtail (Trichiurus japonicus) fishery in the East China Sea

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.

Evaluation of the fishery status for King Soldier Bream Argyrops spinifer in Pakistan using the software CEDA and ASPIC

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.

Maximum Sustainable Yield Estimates of Ladypees,Sillago sihama(Forsskl),Fishery in Pakistan Using the ASPIC and CEDA Packages

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.

Assessing recent gradual upsurge of marine captured Hilsa stock(Tenualosa ilisha)in Bangladesh

The anadromous Hilsa shad(Tenualosa ilisha)fishery is the prime single species fishery of Bangladesh that driven by open access system which was selected for this study.Key purpose of this study was to assess the MSY(Maximum Sustainable Yield)in order to review the effectivity of the ongoing management policy of this fishery.For this reason,time series maritime or downstream catch-effort data of the Bay of Bengal were assembled from the Department of Fisheries,Bangladesh.MSY,CPUE and other population parameters were estimated through Surplus Production Models(SPMs)using computer software packages of CEDA,ASPIC and TropFishR.Assessed biological reference points of MSY from the best fitted CEDA package was 282,100 t(R^(2)=0.822)for the normal assumptions of the Schaefer and Pella-Tomlinson models.MSY values from the ASPIC packages(324,100 t and 263,500 t;for Fox and Schaefer model)and Schaefer model from TropFishR(345,486t)were larger than the catch in 2017(278,948 t).The values of F ratio(F/FMSY)for all SPMs were found less than 1 and B ratio(B/BMSY)were greater than 1 that clearly indicate the gradual upsurge of the Hilsa stock.Based on the above findings of BRPs,it also proves the effectivity of the current“Hilsa fishery management action plan”by the authorities.

Catch per unit effort,maximum sustainable yield and exploitation of demersal fish of Omani artisanal fishery

Objective:To evaluate exploitation status of the stocks of demersal fishes in Omani artisanal fisheries.Methods:Time-series data between 2005 and 2014 on catches and effort represented by the number of fishing boats were used to estimate catch per unit effort and maximum sustainable yields applying Schaefer surplus production model.Regression analyses were made online using GraphPad software.Results:The study revealed that increasing the number of boats on the fishery caused a decrease of catch per unit effort of some species.Maximum sustainable yields and exploitation status were estimated for these species applying.Conclusions:Some demersal fish species were found to be caught in quantities exceeding maximum sustainable yields during some fishing seasons indicating overexploitation of their stocks.