Abstract

Using data from wild Atlantic salmon Salmo salar returning to spawn in seven Scottish rivers, we developed a model of fecundity based on individual body size and key developmental traits. We used a novel approach to model selection which maximises predictive accuracy for application to target river stocks to select the best from a suite of Bayesian hierarchical models. This approach aims to ensure the optimal model within the candidate set includes covariates that best predict out-of-sample data to estimate fecundity in areas where no direct observations are available. In addition to body size, the final model included the developmental characteristics of age at smolting and years spent at sea. Using two independent long-term monitoring datasets, the consequences of ignoring these characteristics was revealed by comparing predictions from the best model with models that omitted them.

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