Northwest Fisheries Science Center

Display All Information

Document Type: Journal Article
Center: NWFSC
Document ID: 7467
Title: How variable is recruitment for marine fishes? A hierarchical model for testing life history theory
Author: James T. Thorson, Olaf Jensen, Elise Zipkin
Publication Year: 2014
Journal: Canadian Journal of Fisheries and Aquatic Sciences
Keywords: recruitment, stock-recruit curve, meta-analysis, autocorrelated recruitment, stock assessment, age at maturity, life history theory, hierarchical model, stock-recruit database,

 Recruitment often varies substantially even in the absence of changes in adult spawning biomass, and residual variability after accounting for stock-recruit relationship may have serial autocorrelation due to the environmental effects.  However, the likely magnitude of variability and autocorrelation in recruitment has not been formally estimated.  We therefore develop a hierarchical model for recruitment variability and autocorrelation, and apply it to data for 154 fish populations.  Results are similar when using either Ricker and Beverton-Holt stock-recruit models, and show an average log-standard deviation of 0.67 for recruitment and an average autocorrelation of 0.49.  Estimates differ substantially among taxonomic orders and stocks, and also support an hypothesized positive relationship between age at maturity and autocorrelation.  Results can be used as a Bayesian prior for recruitment variability in models for data-poor stocks, and to distinguish recruitment from other process errors in models for data-rich stocks.   Estimates can also be used in the design of future simulation model and management strategy evaluation, and in theoretical research regarding life history variation.

Theme: Recovery and rebuilding of marine and coastal species
Foci: Characterize the population biology of species, and develop and improve methods for predicting the status of populations.
Develop methods to use physiological, biological and behavioral information to predict population-level processes.