Recent declines in Eastern Tasmania (Tarbath & Gardner, 2012) and Tiparra Reef in South Australia (Chick & Mayfield, 2012) suggest a potential for changes in productivity. Further challenges to successfully managing abalone include periods of poor recruitment in some areas, rising Australian east coast temperatures, the Victorian virus outbreak, toxic blooms in Tasmania, and mortality events in Tasmania.

All these challenges to current management indicate the need for more detailed and rapidly reactive and defensible management of Australian abalone stocks.

The management strategy evaluation (MSE) framework from FRDC 2007/020 “Biological Performance Indicators for abalone fisheries”, focussed on the utility of classical performance measures. However, the Multi-Criterion-Decision-Analysis Harvest Strategy (MCDA-HS) being developed in Tasmania will integrate classic fishery Performance Measures (PMs) with new Spatial PMs, and include local complexity in growth (the latter are important for the TAC/LML debate). Now GPS data loggers have become compulsory within the Tasmanian fishery (2006/029 – “Using GPS technology to improve fishery-dependent data collection in abalone fisheries”), the need to test these new empirical harvest strategies, that include spatial PMs, is becoming urgent. The MSE framework, therefore needs modification to successfully simulate the new spatial performance measures and then test the performance of the novel harvest strategies. South Australia introduced a non-spatial MCDA-HS without testing and an array of unintended consequences is becoming apparent. To retain confidence in the application of formal harvest strategies with associated decision rules testing the harvest strategies as they are developed remains important.

Novel harvest Strategies need to be tested to determine by how much they improve the setting of TACs and associated LMLs. There is a recognized need to interact with FRDC 2011/201: “Implementing a spatial assessment and decision process to improve fishery management outcomes using geo-referenced diver data” so both projects can benefit from each other.