An elementary study of impacts of error structure on the estimation of fish natural mortality coefficient using cohort analysis (CA) model

Pope's (1972)cohort analysis model can be used to estimate fish natural mortality coefficient (M) when series abundance and catch data are available. Errors in both the model and data are usually neglected in usual calculations, regardless of whether it is realistic. This paper discusses the M estimation using Pope's cohort analysis model, and a generalized linear model (GzLM) is used to explore the effect on the estimated results of three error structures (normal, lognormal and gamma). Monte Carlo simulation analyses show that when white noises (coefficient of variation, CV) in the data are less than about 10%, the estimated values of M are mostly reliable. The estimation quality of M using Pope's model can be influenced by the assumption about the error structure in the estimation, and that lognormal distribution is appropriate for the Pope's model. Two species of long-lived with low M and short-lived with high M were generated, and the simulation analysis indicates that the method performs better for short-lived species with high M1. We then applied this method to the data of the Yellow Sea anchovy (Engraulis japonicus) under the three error structures. The results obtained from lognormal GzLM distribution are more viable than other distributions, and the estimated values of M are viable for young ages, for their more accurate observed data, than that of older ages.