Accounting for structural uncertainty to facilitate precautionary fishery management: illustration with Namibian orange roughy

Abstract

FAO guidelines for the implementation of a precautionary approach to fishery management have been applied in developing and developed fisheries using a variety of stock-assessment methods that apply simulation modeling and several different methods to account for uncertainty in model parameters. Several recent works, however, point out that uncertainty in the structural formulation of stock-assessment models, e.g., in the form of the stock-recruit relationship and assumptions about catchability and stock structure, must also be taken into account because model-based advice can be much more sensitive to structural uncertainty than to parameter uncertainty. Although it is highly desirable to account for both types of uncertainty, the fisheries literature has devoted attention mostly to the former and relatively little to developing formal probabilistic methods to account for structural uncertainties. This paper argues for a more formal empirical basis for dealing with structural uncertainties in providing precautionary management advice. Some guidelines for applying a Bayesian stock-assessment approach to deal with structural uncertainty are reformulated and illustrated with an application of Bayesian importance sampling to the stock assessment of Namibian orange roughy (Hoplostethus atlanticus).