The state of the art in stock assessment: where we are and where we are going

Abstract

Throughout the world´s major commercial fisheries the standard paradigm includes fitting a stock assessment model to the data and then applying some form of reference point or a range of reference points, usually a target exploitation rate, to calculate a point estimate of the annual allowable catch. Over the last decade the methods available to be used in these models have changed dramatically from those using only catch, catch-at-age and survey or CPUE data to methods that now use every source of data available in a totally integrated framework. The use of meta-analysis has provided formal statistical methods for incorporating information learned from other stocks. Modern methods make it possible to express uncertainty in all model outputs, but management agencies are only now learning to deal with explicit recognition of uncertainty and have lagged far behind the scientific capability to express uncertainty. While modern stock assessment models have grown increasingly complex and their development is limited to a priesthood of experts, I believe the future trend will be to base management decisions on simple rules that are more often data-based rather than model-based, while the complex models will serve primarily to evaluate the robustness of these decision rules.