Characterizing and forecasting fish recruitment in a changing world

Abstract

Recruitment, the entry of young fish into a stock, is an important process in population dynamics models, which form the basis for many stock assessments. As such, recruitment has been a focus of research among fishery scientists for over a hundred years. Recruitment is often assumed to be a function of the spawning biomass of a stock. However, quantifying this relationship is challenging. The first chapter of this thesis examines the prevalence of a detectable influence of spawning biomass on recruitment for the stocks included in the RAM Legacy Stock Assessment database. We found most stocks (57%) did not have a detectable relationship between spawning biomass and recruitment over the observed ranges of spawning biomass. Environmental factors appear to play a larger role in recruitment variation. Furthermore, many of the stocks we examined had evidence of a regime shift (46%). Our results highlight the need to develop effective methods to model and forecast large variations in recruitment over time. The second chapter of this thesis evaluates the forecast performance of six methods on groundfish recruitment. The methods varied in the level of parameterization and operational use. We found that forecast performance depends on the time period, the performance metric, and the characteristics of the time series. Our results indicate an advantage in using non-parametric forecast methods, especially for mid-term projections.