A model for estimating mortality of Atlantic salmon,Salmo salar, between spawning events

Abstract

We developed a Bayesian hierarchical model to estimate annual mortality of repeat-spawning Atlantic salmon, Salmo salar, that distinguishes between mortality rates and the confounding effects of consecutive-year and alternate-year repeat-spawning strategies. The model provides annual estimates of two mortality rates: mortality in the first year (Z1), a time period during which salmon are primarily in freshwater (staging, spawning, and overwintering) followed by a brief period at sea, and mortality in the second year (Z2) when salmon are predominantly at sea. When fit to data for the LaHave River (Nova Scotia, Canada) salmon population, Z1 showed an increasing trend throughout the time series, whereas Z2 also increased but in a single, stepwise manner. Once a time series of mortality rates was separated from the other life-history parameters, we were able to demonstrate how they could be used for examining the influence of environmental conditions by comparing the estimated mortality rate time series with the North Atlantic Oscillation Index (NAOI). This comparison uncovered a statistically significant correlation between the NAOI and the survival in the second year after spawning that would not have been evident had the mortality estimation model not been developed.