A performance comparison of stock density estimation of Larimichthys polyactis in the East China Sea using different models based on bottom trawl survey

Estimation of average catch per unit effort (CPUE) which is a relative index to measure fish abundance is important foundational work for stock assessment and fishery management. Based on the data of Larimichthys polyactis collected from the bottom trawl survey conducted in the East China Sea from 2004 to 2006, we calculated the average stock density of L.polyactis by arithmetic mean estimator (AM), resampling mean estimator (RM), lognormal distribution mean estimator (LM),-distribution mean estimator (DM) and Finney-Sichel mean estimator (FM), and evaluated the superiority (or inferiority) and robustness of different estimators. Results indicate that the mean estimators based on lognormal distribution were bigger than the last two estimators, and the-distribution mean estimator was the biggest one, while the last two estimators were much closer. The paired-sample t test reveals that the-distribution mean estimator was bigger than the other four estimators (P0.05); meanwhile, there was no difference among theother four estimators (P0.05). The coefficient variation (CV) of the-distribution mean estimator and the resampling mean estimator were less than the other three estimators. It is concluded that-distribution mean estimator was the best estimation method with good applicability and robustness.