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.

Maximum sustainable yield of Greater lizardfish Saurida tumbil fishery in Pakistan using the CEDA and ASPIC packages

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.

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.

基于CEDA和ASPIC软件的南大西洋长鳍金枪鱼渔业资源评估研究

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。

基于贝叶斯方法的南大西洋长鳍金枪鱼渔业的风险评估与管理

使用ASPIC与CEDA软件对南大西洋长鳍金枪鱼的产量和标准化的CPUE数据进行分析,得到了环境容量K、可捕系数q和内禀增长率r的点估计。以此作为3个参数的先验信息,应用MCMC算法计算3个参数的后验概率分布。根据种群参数的后验概率,设定不同的捕捞策略,对该群体进行风险评估。结果表明,1985—2005年南大西洋长鳍金枪鱼经历了轻度的过度捕捞,2005年之后开始恢复,目前这个群体的资源状态较好,仍需加强管理使其可持续发展。建议产量控制在27 970t以内,捕捞死亡率控制在0.15左右。

Separation of closely spaced modes by combining complex envelope displacement analysis with method of generating intrinsic mode functions through filtering algorithm based on wavelet packet decomposition

One of the important issues in the system identification and the spectrum analysis is the frequency resolution, i.e., the capability of distinguishing between two or more closely spaced frequency components. In the modal identification by the empirical mode decomposition （EMD） method, because of the separating capability of the method, it is still a challenge to consistently and reliably identify the parameters of structures of which modes are not well separated. A new method is introduced to generate the intrin- sic mode functions （IMFs） through the filtering algorithm based on the wavelet packet decomposition （GIFWPD）. In this paper, it is demonstrated that the CIFWPD method alone has a good capability of separating close modes, even under the severe condition beyond the critical frequency ratio limit which makes it impossible to separate two closely spaced harmonics by the EMD method. However, the GIFWPD-only based method is impelled to use a very fine sampling frequency with consequent prohibitive computational costs. Therefore, in order to decrease the computational load by reducing the amount of samples and improve the effectiveness of separation by increasing the frequency ratio, the present paper uses a combination of the complex envelope displacement analysis （CEDA） and the GIFWPD method. For the validation, two examples from the previous works are taken to show the results obtained by the GIFWPD-only based method and by combining the CEDA with the GIFWPD method.

Value and Development Countermeasures for Modern Agriculture in Suzhou

With advance of urbanization and industrialization, modern agricultural development in Chinas economic developed areas (CEDAs) is greatly restricted by traditional concept. To speed up the development of modern agriculture in CEDAs, this paper takes Suzhou City as an example from theories supporting modern agricultural development. It demonstrates agriculture in CEDAs plays an important role in adjusting supply of agricultural and sideline products, reserving rural labor employment, protecting ecological environment, increasing farmers income, and passing on agricultural culture. It contends that CEDAs should take reserving basic farmland as prerequisite; take adequate supply of primary agricultural products, protection of living environment, maintenance of agricultural landscape, and inheritance of farming culture as objectives; establish perfect modern agricultural system through firmly setting up modern agricultural value concept; increase local public finance input; increase agricultural functional value from technical and management levels, to realize increase of farmers income, promote sustainable development of agriculture, promote integrated urban and rural development, as well as harmonious development of human and nature.

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.

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.