Abalone stocks are vulnerable to localized depletion, followed by fishery collapse. In Australia, assessments of abalone fisheries have been written in all abalone-producing states. However, except in NSW (Worthington, 1998), the basis for those stock assessments is generally an anecdotal interpretation of un-standardized commercial catch-effort data and, sometimes, information on the size-composition of the catch. This information is often combined, in an informal way, with research data to give an impression of the status of the stocks. Performance indicators used do not tend to be biologically based. Most importantly, the sustainability of current catch levels is not known with any confidence. Meeting the guidelines from Environment Australia with regard to sustainability of fisheries will require a more formal assessment for such an important fishery.
The development of FRDC project 1999/116, to develop a National Abalone Model, is an attempt to answer the obvious need for a valid model. Currently, New South Wales is the only state where a stock assessment model is being used as the basis for fishery management decisions in an abalone fishery. In Tasmania, The inputs currently available to the model being developed include fishery-dependent catch-effort data, fishery-dependent length-frequency data, research length-frequency data, and estimates of biological parameters. The crucial data, missing from the inputs to the model, is a fishery-independent index of relative abundance. The survey techniques used in NSW and in Victoria have been found incapable of producing estimates with sufficient
precision under Tasmanian conditions. There is thus a need to develop an optimum combination of fishery independent indices of abundance that will have application in the full range of Tasmanian abalone habitats. In addition, Tasmania's raw catch-effort data must be standardized prior to its use in a formal assessment model because of the high variability in catch rates between divers, areas, season, and other factors.
Specifically this project will:
(1) better determine the relationship between catch-rate and abundance. This is needed for realistic standardisation of catch and effort statistics;
(2) improve our understanding of the differences between commercial size-composition data and the actual size composition of the legal size abalone left after fishing (selectivity v availability). Such data are a key ingredient of stock assessment models;
(3) assess the accuracy of diver logbook data. This will help ensure that the data requested via industry logbooks focuses on the most appropriate questions and will assist with appropriate standardisation.
The information gained will underpin the development of credible, realistic fisheries models for abalone, which will consequently improve the confidence with which abalone fisheries are managed. Increased confidence in fisheries management decisions will have measurable economic benefits.
