Understanding inter-reach variation in brown trout (Salmo trutta) mortality rates using a hierarchical Bayesian state-space model

Successful management and protection of wild animal populations relies on good understanding of their life cycles. Because population dynamics depends on intricate interactions of biological and ecological processes at various scales, new approaches are needed that account for the variability of demographic processes and associated parameters in a hierarchy of spatial scales. A hierarchical Bayesian model for the resident brown trout (Salmo trutta) life cycle was built to assess the relative influence of local and general determinants of mortality. The model was fitted to an extensive data set collected in 40 river reaches, combining abundance and environmental data (hydraulics, water temperature). Density-dependent mortality of juveniles increased at low water temperatures and decreased with shelter availability. High water temperature increased densitydependent mortality in adults. The model could help to predict monthly juvenile and adult mortality under scenarios of global warming and changes in shelter availability due to habitat degradation or restoration.