Measuring the strength of environment–recruitment relationships: the importance of including predictor screening within cross-validations

Abstract

Abstract There has recently been considerable interest in establishing relationships between environmental variables and annual recruitment to fish stocks. Such relationships have the potential to reduce the uncertainty in the assessment of the stocks. When many environmental variables are considered, it is easy to draw conclusions that exaggerate the ability to predict recruitment. One technique to protect against this is cross-validation. This technique has usually been incorrectly applied, in that it has not included predictor screening (the selection from a large set of potential predictors of a smaller set to use in prediction). A simulation experiment is used to show that this omission can cause chance correlations to be wrongly identified as useful, and the reliability of useful predictors to be overestimated. It also shows that the mistaken use of chance correlations to predict recruitment can be worse than the use of the default predictor (the mean of previous recruitments), and that our ability to measure the reliability of recruitment predictors is typically poor.