Embedding stock assessment within an integrated hierarchical Bayesian life cycle modelling framework: an application to Atlantic salmon in the Northeast Atlantic

Abstract

We developed a hierarchical Bayesian integrated life cycle model for Atlantic salmon that improves on the stock assessment approach currently used by ICES and provides some interesting insights about the population dynamics of a stock assemblage. The model is applied to the salmon stocks in eastern Scotland. It assimilates a 40-year (1971–2010) time-series of data compiled by ICES, including the catches in the distant water fisheries at Faroes and West Greenland and estimates of returning fish abundance. Our model offers major improvements in terms of statistical methodology for A. salmon stock assessment. Uncertainty about inferences is readily quantified in the form of Bayesian posterior distributions for parameters and abundance at all life stages, and the model could be adapted to provide projections based on the uncertainty derived from the estimation phase. The approach offers flexibility to improve the ecological realism of the model. It allows the introduction of density dependence in the egg-to-smolt transition, which is not considered in the current ICES assessment method. The results show that this modifies the inferences on the temporal dynamics of the post-smolt marine survival. In particular, the overall decrease in the marine survival between 1971 and 2010 and the sharp decline around 1988–1990 are dampened when density dependence is considered. The return rates of smolts as two-sea-winter (2SW) fish has declined in a higher proportion than return rates as one-sea-winter (1SW) fish. Our results indicate that this can be explained either by an increase in the proportion maturing as 1SW fish or by an increase in the mortality rate at sea of 2SW fish, but the data used in our analyses do not allow the likelihood of these two hypotheses to be gauged.

Evidence for spatial coherence in time trends of marine life history traits of Atlantic salmon in the North Atlantic

“…As explained by Massiot‐Granier et al. (), higher egg‐to‐smolt survivals are logically balanced by lower estimates of post‐smolt survivals (Figure S2.2). But because the egg deposition varies over the time series, introducing density dependence in freshwater results in temporal variations in the egg‐to‐smolt survivals (Figure S2.1).…”

“…To separate the variability in the natural and fishing mortality during the freshwater and marine phase and in the proportion of fish that mature as 1SW, we use the framework described in ICES () and Massiot‐Granier et al. ().…”

“…To date, the PFA models used for formulating catch advice at ICES (,b) rely on a coarsely constructed stock–recruitment dynamic, defined as the productivity parameter between the eggs (measure of the spawning stock) and abundance at the PFA stage (recruitment). Statistical inferences on the time series of productivity parameters are susceptible to time‐series bias because the dynamic link between PFA and subsequent egg depositions is not represented (Massiot‐Granier et al., ; Su & Peterman, ). The lack of flexibility in the modelling framework also restricts the integration of the large amount of available data and knowledge of demographic and population dynamics.…”

“…We extend the framework developed by Massiot‐Granier et al. () for one SU to include the dynamics of all SUs in NA and SE within a single unified hierarchical Bayesian life cycle approach with populations following a similar life history process (Buckland, Newman, Fernández, Thomas, & Harwood, ; Buckland, Newman, Thomas, & Koesters, ; Clark, ; Parent & Rivot, ; Rivot, Prévost, Parent, & Baglinière, ). The new framework allows for modelling covariations among all SUs and for partitioning the effects of fisheries from the effects of environmental factors at a hierarchy of spatial scales, including at the level of the North Atlantic, of each CSG, and for each SU within a CSG.…”

Spatial synchrony in the response of a long range migratory species (Salmo salar) to climate change in the North Atlantic Ocean

“…Because of data limitations, the model structure forces all temporal variations in survival to occur between the smolt migration and the prefishery stage. Indeed, as already discussed by Massiot-Granier et al (2014) and Olmos et al (2019), the data currently available do not allow partitioning out the temporal variations of the marine mortality that occur at different periods of the marine phase.…”