An evaluation of the Brownie tag-recapture model using simulation-estimation procedures, with application to British Columbia sablefish (Anoplopoma fimbria)

The Brownie tag-recapture model analyses multi-year tag recovery data to derive estimates of natural and fishing mortality that can be used to estimate population abundance. However, it makes several assumptions about the behaviour of tagged fish, tagging-induced mortality, tag retention, emigration, tag reporting, and timing of the fishery. I evaluate performance of the Brownie model when individual assumptions are violated, using Monte Carlo simulations over a suite of scenarios with known “true” parameter values chosen to mimic British Columbia sablefish (Anoplopoma fimbria). Bias and precision are quantified by comparing parameter estimates with their known “true” values and by the spread in estimates from 500 Monte Carlo trials, respectively. Assumptions about uniform mixing, timing of the fishery, and emigration had the greatest effects on bias of estimates of fishing mortality and abundance. Combining fishery-independent survey CPUE data with tag recovery data did not substantially improve bias or precision of parameter estimates