A framework to model shrimp (Pandalus borealis) stock dynamics and to quantify the risk associated with alternative management options, using Bayesian methods

A new integrated Bayesian framework for making quantitative assessments, predictions, and risk analyses of shrimp (Pandalus borealis) stock development is constructed. A biomass dynamic model, based on the logistic function but including an explicit term for cod predation, suggests that the quantity of shrimp consumed by cod could equal that taken by the fishery. The model proved superior to an alternative model in its ability to estimate parameters central to the assessment; the alternative model subsumed cod predation as part of an overall population growth effect without a time trend. Two series of shrimp biomass indices, catch, cod biomass estimates, cod consumption estimates, and prior distributions of model parameters provided information to the models. Process and observation errors were incorporated simultaneously using a state-space modelling framework. A Bayesian approach was used to construct posterior probability distributions of model parameters and derived variables relevant for management advice, including quantification of future risk of transgressing reference points in relation to alternative management options.