Bayesian fitting of probabilistic maturation reaction norms to population-level data

Abstract

Probabilistic maturation reaction norms (PMRNs) are an important tool for studying fisheries-induced evolution and environmental effects on life history. To date there has been no way to fit a PMRN to population-level fisheries data; instead individual-level data must be used. This limits the stocks and time periods that can be studied.We introduce a Bayesian method for fitting PMRNs to population-level data. The method is verified against both an existing result and simulated data, and applied to historical Barents Sea cod data which combines observations of population-level variation in age, size and maturity status from Russia and Norway.The method shows a clear and rapid trend towards greater probability of maturation at smaller lengths in the Barents Sea cod.The new model fitting algorithm allows us to study historic changes in life history despite the lack of individual-level data seen in much long term data. Access to more data will aid the study of evolutionary hypotheses in a wide range of organisms.