Instantaneous Rates Tagging Models Allowing for Delayed Mixing of Newly Tagged Cohorts: Benefits from Partial Year Tabulation of Recaptures

Instantaneous rates tagging models can be used to estimate natural mortality and fishing mortality rates from multi-year tagging studies in which cohorts of tagged animals are released at the start of each year.  The models can include additional parameters to account for a delay in mixing of newly tagged animals with previously tagged animals.  One such model allows for the newly tagged population to become fully mixed in less than one year (the Hoenig et al. model). Here a new model, referred to as the partial-year tabulation model for delayed mixing (delayed pyt model), is proposed in which the year is divided into parts and tag returns are tabulated by parts of the year rather than a full year.  This is beneficial when there is delayed mixing because it achieves greater precision and provides estimates of the instantaneous rate of fishing mortality in the first year, which cannot be estimated when tag returns are tabulated by full year.  It also allows the flexibility of getting estimates after only part of the year has passed rather than waiting for the full year to pass.  The new model can be used at little or no extra cost.  The superiority of the delayed pyt model over the Hoenig et al. model is demonstrated through Monte Carlo simulation.