Combining information from commercial catches and research surveys to estimate recruitment: a comparison of methods

Abstract

Three basic methods for estimating year-class strength given several research surveys or commercial catch indices of recruitment are described. Two are regression methods - calibration regression and predictive regression. The third method is factor analysis, in which the covariance between the indices is modelled as a function of the relationship to the underlying true, but unobservable, recruitment. All three of the methods estimate recruitment as an inverse variance weighted average of the estimates from each of the index series. Tests indicate that factor analysis and calibration with shrinkage perform best overall. Calibration can be quite sensitive to missing data, however, and may break down if the most recent year's recruitment is far from the mean of the absolute abundance series. Under these conditions, factor analysis performs better in simulation trials. -from Authors