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.

Impacts of distorted fishery statistical data on assessments of three surplus production models

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.

基于Stackelberg博弈的资源动态定价策略

针对计算密集型任务卸载时边缘云计算能力有限引起的公平性问题,提出一种基于Stackelberg(斯坦克伯格)博弈的资源动态定价策略.首先,分析边缘云系统资源剩余量和用户需求之间的实时关系,设计边缘云网络收益及用户成本函数.然后,通过验证用户之间非合作博弈纳什均衡点的存在性,获得基于完全状态信息下用户成本最低时的最优卸载策略.最后,采用双向迭代搜索算法求解边缘收益问题,获取经价格调整因子调节后的边缘云网络最优定价策略.仿真结果表明:所提算法当计算资源较少时能保证边缘云收益,并在保证用户公平性前提下提高用户服务质量.