Exploratory assessment of historical recruitment patterns using relative abundance and catch data

Abstract

Historical apparent recruitment rates can be estimated from time series of relative abundance and catch data using a simple difference equation in conjunction with assumed catchability coefficient and natural survival rate. Simple smoothing and optimal linear state estimation procedures can remove much of the variance in such estimates due to measurement error in relative abundance. The apparent patterns can be helpful to reveal important recruitment changes prior to availability of data for more complex stock assessments, provide checks on recruitments estimated by more complex assessment procedures, and provide warnings about biases in other assessment procedures that might result from using the relative abundance data for model tuning.