A multi‐stock, length‐based assessment model for New Zealand rock lobster (Jasus Edwardsii)

We describe a multi‐stock, length‐based Bayesian assessment model for New Zealand spiny lobster (Jasus edwardsii) fisheries. This model allows simultaneous modelling of two or more stocks with a mixture of common and stock‐specific parameters: recruitment is always stock‐specific, but any other parameter can be specified as either common or stock‐specific. Common parameters are estimated from a wider base than they would be in a single‐stock model. The model's time step is flexible and can be changed during the period being modelled to accommodate better data quality in recent data. Other options include the capacity to estimate movements among stocks, allow density‐dependent growth, and choose among likelihood functions for the various data sets, between finite and instantaneous fishing dynamics and between two forms of selectivity curve.