smsR : A seasonal assessment model for exploited stocks

We present a seasonal stock assessment model, which allows the user to initiate a stochastic age‐based model inside the R programming language. The model is currently the official stock assessment model for five small pelagic stocks in the North Sea. The seasonality component enables within year changes in weight, natural mortality and recruitment, which is commonly missing from existing methods. We show through simulation analysis that including seasonality can lead to lower bias in stocks with strong interannual dynamics. We provide a variety of useful functions and applications that let the user perform diagnostics and evaluate the goodness‐of‐fit of the model. The software contains functions used for catch forecasting and management strategy evaluation. The stock assessment model is written in Template Model Builder (TMB), which enables rapid parameter estimation and the potential to estimate parameters as random effects. Practical implication . The model offers a tool for consistent and transparent stock assessments for populations with strong seasonal dynamics.