Parametric estimation and comparison of age-reading error matrices across species, stocks, and calcified structures

Stock assessments are often based on age-structured data obtained by interpreting calcified structures. Due to readability and human error, the observed age may be wrong. We propose a parametric model for age-reading error matrices, which is more realistic and robust than the commonly used empirical matrices. The parameters have meaningful interpretations, allowing for direct comparison of age-reading properties. We compare different species (Atlantic mackerel ( Scomber scombrus) and herring ( Clupea harengus)), stocks (North Sea autumn-spawning vs. Norwegian spring-spawning herring), and calcified structures (otoliths vs. scales). Three out of four data sets had an asymmetry tendency towards reading higher ages than the true age. The estimated probability of reading the wrong age was lower for scales than for otoliths. The true age is often unknown and assumed to be the modal age. We assess the systematic bias due to this assumption. Finally, when including age-reading error in stock assessment, the dominating age classes were estimated to be larger and spawning stock biomass lower. Our study contributes with methods and insight for including age-reading error in stock assessment.