Incorporating Uncertainty into Fishery Models

Bayesian Analysis of Stock Survival and Recovery of Spring and Summer Chinook of the Snake River Basin

Richard B. Deriso

doi: https://doi.org/10.47886/9781888569315.ch9

Abstract.—Spring and summer chinook salmon Oncorhynchus tshawytscha populations of the Snake River basin provide the setting for an application of Bayesian analysis to derive risks of population survival and recovery for these endangered populations. The Bayesian approach is appealing because it provides a theoretical framework within which uncertainty about population dynamics is directly translated into measures of probability of achieving various population abundance targets, given certain types of actions in the future. Uncertainty about parameters governing the population dynamics is based on an application of the Bayes Theorem to the likelihood of observations about past recruitment, as viewed in the context of a generalized Ricker spawner and recruitment model. Uncertainty about future dynamics is based on simulations of population abundance over the next 100 years, and they contain both model parameter uncertainty and annual stochastic elements affecting survival. Results show substantial reductions in mortality rate (on the order of 0.5–0.7 per year, as compared with rates in recent years) are required in order for the populations to meet recovery and survival standards set for the next 48– 100 years. The level of mortality reduction needed to achieve these standards can assist in guiding potential hydropower system management options.