LAUSR

Abstract We consider the challenge in estimating the natural mortality, M , in a standard statistical fish stock assessment model based on time series of catch- and abundance-at-age data. Though anecdotal evidence and empirical experience lend support to the fact that this parameter may be difficult to estimate, the current literature lacks a theoretical justification. We first discuss the estimatability of a time-invariant M theoretically and present necessary conditions for a constant M to be identifiable. We then investigate the practical usefulness of this by estimating M from simulated data based on models fitted to 19 fish stocks. Using the same data sets, we next explore several model formulations of time varying M , with a pre-specified mean value. Cross validation is used to assess the prediction performance of the candidate models. Our results show that a time-invariant M can be estimated with reasonable precision for a few stocks with long time series and typically high values of the true M . For most stocks, however, the estimation uncertainty of M is very large. For time-varying M , we find that accounting for variability across age and time using a simple model significantly improves the performance compared to a time-invariant M . No significant improvement is obtained by using complex models, such as, those with time dependencies in variability around mean values of M .