[Sampling design optimization based on estimation accuracy and survey cost for fishery-independent surveys]

Optimization of sampling design can reduce survey cost, ensure the accuracy of survey data, and get the maximum benefit of survey design. In this study, survey voyage was added into sampling survey design optimization as the evaluation index to quantify the survey cost. Computer simulation and resampling technique were used to simulate the survey plan. Simulation annealing algorithm was used to find the survey design with the shortest voyage. Based on the survey data collected from the bottom trawl survey conducted in the Haizhou Bay and its adjacent waters in spring and autumn from 2013 to 2015, Kriging interpolation was used to simulate the relative abundance distribution of Conger myriaster, Enedrias fangi, and Hexagrammos otakii in the bay in two seasons as their 'true' values. Resampling was conducted using stratified random sampling with different sample sizes for simulation study, and the abundance indices of each target species were estimated based on the simulated data. The relative bias (RB) was used to evaluate the accuracy of estimation of abundance index. The average survey cost and probability of budget overshoot (P) were used to measure the cost of survey. Integrated evaluation index (IEI) was developed to measure the survey cost and estimation accuracy comprehensively. The results showed RB values of all target species decreased with sample size. Different target species had different RB values with the same sample size. The optimal numbers of station determined by different evaluation indices were different. The optimal sample size determined by RB was relatively high, while the cost exceeded the budget of survey. The optimal sample size determined by probability of exceeding survey budget was relatively low but the accuracy and precision of estimation was low. IEI balanced the survey cost and estimation accuracy, and the optimal sample size defined by IEI was at intermediate level. The sampling design considering survey cost and route planning could not only determine the optimal sample size, but also record the potential station location, the survey sequence and the corresponding survey cost of simulations. According to the actual cost budget, the desired survey design with low cost and low RB of estimation from simulations could be chosen for fishery-independent surveys.