Evaluation of sampling designs for different fishery groups in the Yangtze River estuary, China

Abstract

Fishery-independent surveys serve as an important data source for research, assessment and management of fishery resources. It is important to carry out some comparative studies on sampling designs so as to get the optimal design. In this study, we used computer simulations to evaluate the performance of five sampling designs to assess population densities of various fishery groups (total fishery species, fishes, shrimps and crabs) in the Yangtze River estuary (YRE), China. The survey designs were simple random sampling, systematic sampling and stratified sampling with three allocation schemes. We found that optimal sampling designs were different depending on the target fishery groups. In general, systematic sampling had higher precision and accuracy for estimating population density compared to simple random sampling and stratified sampling. However, systematic sampling led to the underestimation of population density, where large fluctuations in error rate were observed with increasing sample size during certain seasons. Stratified sampling performed by proportional allocation of sampling efforts or equal allocation of sampling efforts schemes was slightly worse than systematic sampling. However, stratified sampling did not result in overestimation or underestimation of the mean population density. In stratified sampling designs, relative error decreased with increasing sample size. Stratified sampling with optimal criterion of sampling cost did not accurately estimate the population density, and had variable relative error and relative bias, indicating that the accuracy of this method could be increased by identifying reasonable allocation of samples among strata. These results can improve designs of fishery-independent surveys in the YRE, and future simulation studies on sampling design can be further studied to strengthen the management for fishery resources.