Initial investigation of generic management procedures for data-poor fisheries

Abstract

The vast majority of fish stocks in South Africa are not managed quantitatively as there is not sufficient data (such as an index of abundance) on which to base a resource assessment. In addition, these stocks are relatively “low-value”, which renders dedicated scientific management too costly, and a generic approach is therefore required. The aim of this work is to design and test some very simple “off-the-shelf” management procedures (MPs) that can be applied to groups of data-poor fisheries that share some key characteristics in terms of demographic parameters. For this initial investigation, a selection of empirical MPs is simulation tested on a wide range of operating models (OMs) representing the underlying dynamics of the resource in order to ascertain how well the different MPs perform. While the data-rich MPs perform somewhat better than the data-poor ones, as would be expected, it seems that the very simple data-poor MPs are surprisingly robust to a wide range of uncertainty for key parameters and could well be candidates to manage the South African data-poor stocks, ensuring perhaps not optimum, but at least relatively stable sustainable future catches.