Models for tagging data that allow for incomplete mixing of newly tagged animals

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Abstract
The Brownie models for tagging data allow one to estimate age- and year-specific total survival rates as well as tag recovery rate parameters. The latter can provide estimates of exploitation rates if the tag reporting, tag shedding, and tag-induced mortality rates can be estimated. A limitation of the models is that they do not allow for newly tagged animals to have different survival rates than previously tagged animals because of lack of complete mixing. We develop a model that allows for the animals to be incompletely mixed, or not fully recruited, into the population during the entire year in which they are tagged. There is a penalty in terms of precision associated with the use of this model. To increase the precision, we also developed a model for which it is assumed that animals become fully mixed (recruited) after a portion of the year has elapsed. Sometimes, animals must be tagged after the fishing season has begun. In this case, newly tagged animals experience fishing and natural mortality for only a fraction of the year. The partial-year non-mixing model can be modified to account for this situation.

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