Estimation of natural mortality using statistical analysis of fisheries catch-at-age data

This study utilized the fisheries catch-at-age data combined with the auxiliary information of effort data to calculate natural mortality rate (M), and the other population parameters such as catchability and recruitment. The method used in the paper was the standard statistical catch-at-age (SCA) model. Monte Carlo simulation data were used to test this method under four fishery scenarios (good contrast, one-way trip, recovery and status quo). This study showed that the quality of the annual recruitment greatly affected the estimated Ms. When the white noises (CVs) of recruitments reached 10% the estimated Ms were biased, even when the CVs of catch-at-age and effort data were low. CVs in catch-at-age and effort data were also important factors to affect the estimated M, and the results of the simulation analysis of three CV scenarios (CV in both of the catch-at-age and effort with the same level, CV in the catch-at-age (CVC) was half of CV in the effort (CVE) and CVE was half of CVC) indicated that CVC made more effects than CVE on the quality of the estimated M. Among the four fisheries, the one-way trip fishery outperformed the other three, since it obtained the lowest relative estimate error (REE) values of the estimated M for all the scenarios, while the recovery fishery had the worst performance. When M varied through ages, von-Bertalanffy growth function (VBGF) was introduced into the SCA model to estimate the age-dependent M, and the one-way trip and good contrast fisheries obtained more viable estimated Ms than the recovery and status quo fisheries. The method was also applied to the published data of North Atlantic albacore (Thunnus alalunga), and the estimated M was 0.186 year−1, which was lower than previously assumed (0.3 year−1) and may be viable in view of the high fishing effort imposed on the species.