Initial investigation of generic management procedures for data-poor fisheries

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2010

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University of Cape Town

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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.
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