Simple representation of the dynamics of biomass error propagation for stock assessment models

Errors in estimates of current exploitable biomass from age-structured stock assessment models typically propagate over time as though they had been computed by using a very simple Kalman filter equation. This equation shows that persistent overestimates of biomass during stock declines are caused mainly by three factors: first-order autoregressive effects of past errors, hyperstability in relative abundance indices, and overestimates of current recruitment. Besides exposing these main causes of bias in biomass estimation, the equation can be used to develop very efficient closed-loop or management performance simulations and to provide timely biomass estimates in situations where it is not practical or economical to carry out full assessments every year.