Extracting a time-varying climate-driven growth index from otoliths for use in stock assessment models

Abstract

Understanding the characteristics of individual growth is a critical component of population assessment. Most fisheries stock assessments assume constant values for each life history parameter, despite growing evidence that growth is variable at individual, temporal, and spatial scales. Otoliths contain important information pertaining to age and growth, among other things, and otolith increment data correlate with climate indices on a decadal scale. We expand on this concept to include individual- and year-level variation, and develop a nonlinear mixed-effects model to analyze otolith increment data. We then fit the model to otolith increment data for splitnose rockfish, and simulation-test the ability to precisely estimate year effects without bias. Generally, given a sample size of at least 50 otoliths, the model performs well at estimating year effects. With this method, species-specific indices of growth can be extracted from otolith increment data, and potentially be used in stock assessments to detect the effects of climate change on fish growth.