Spatial and temporal variability in somatic growth in fisheries stock assessment models: evaluating the consequences of misspecification

Distinct types of fish species experience variation in somatic growth rates over their life span; however, growth has historically been assumed to be invariant across time and space in integrated analysis-based stock assessment. A few previous studies have reported biased and imprecise assessment model outcomes when variability in somatic growth was ignored. In this study, we used a simulation-estimation framework to expand previous analyses and to examine the consequences of ignoring or incorporating spatial and temporal (year- and cohort-specific) variability in somatic growth in stock assessment models. The study included three life history types: small pelagic (e.g. sardine), gadids (e.g. cod), and long-lived (e.g. rockfish). In general, ignoring any type of variability in somatic growth led to biased and imprecise estimates of stock spawning biomass and management quantities. Unequal distribution of fishing mortality across space had large impacts on the performance of estimation models as well Conversely, accounting for somatic growth variability, either by including an environmental index, estimating annual deviates, or implementing a spatially explicit model, produced unbiased and precise results. This study shows that somatic growth variability might produce large effects in stock assessments when ignored and provides pertinent information for stock assessment best practice guidelines.

Automated summary

Ignoring variability in fish species somatic growth rates can lead to biased and imprecise estimates in stock assessment models, while incorporating this variability can produce unbiased and precise results. Unequal distribution of fishing mortality across space significantly impacts estimation model performance.