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FRDC Project 2017-026 Using Spatial Fishery-Dependent data to Determine Stock Status

Australian abalone fisheries primarily use catch per unit effort (Kg/Hr) to set TACC. In some jurisdictions this is supplemented by realtively sparse fishery-dependent size and density data. In the Tasmanian abalone fishery TACCs are determined in a relative context i.e. catch rate is better or worse than previous years. Stable catch rates however may not indicate stable biomass and/or stable density. Catch rates are frequently criticised because the effort required to catch a quantity of catch may be influenced by density but also by density-independent factors such as conditions at the time of fishing, experience, and the ability of fishers to adjust their fishing strategy to maintain catch rates (diver behaviour driven hyper-stability). Central to the challenge of using catch rate data to determine change in stock status is accounting for these extraneous factors when using change in catch rate as a proxy for change in density.

Increasingly, there is a requirement to provide a 'stock status' determination in addition to the annual TACC determination, that defines either changes in the overall biomass, fishing mortality, or proxies for either. This has led to considerably conflict among researchers, managers and industry, largely due to the uncertainty around how best to derive a meaningful overall stock status indicator to meet the requirements, for example, of the Status of Australian Fish Stocks (SAFS) reporting process. These higher-level reporting processes are an important demonstration of sustainable management of Australian fisheries, but only if stock status determinations are accurate and robust to scrutiny. There is an urgent need to review common assumptions, methods and interpretations of CPUE as a primary indicator, and to determine whether inclusion of spatial fishery data could provide an improved 'global' indicator of stock status.

Principally, we need an alternative conceptual model to the traditional Dynamic Pool model, to facilitate interpretation of fishery-dependent data.

FRDC Project 2019-118 Simulation Testing of Australia's Abalone Harvest Strategies

All Australian abalone harvest strategies use empirical approaches, heavily supported by CPUE based indicators, that reflect tensions between producing harvest strategies that work at both larger management scales and that attempt to account for local scale population dynamics. All harvest strategies apply a weight-of-evidence approach that is generally not clearly codified. However, the different harvest strategies lead to very disparate ways of setting catches, with some adjusting catch based on relative performance of indicators, while others assume a direct relationship between CPUE and sustainable catch. These contrasting approaches have developed despite managing essentially the same group of species caught with the same fishi9ng methods and from similar reef environments. This project will therefore test each of the presently used harvest strategies to draw out their strengths and weaknesses in a common platform.

Only the Tasmanian harvest strategies and earlier harvest strategies used in the Victorian Western Zone have been simulation tested to date. The MSE models used in each case, due to funding and time constraints, have been developed in a way that means that portability across jurisdiction is time consuming and costly. As such, this project will address the need to write MSE code that will be usable for the future and in other jurisdictions. It will then test this code on two abalone stocks, one blacklip and one greenlip, to assist in this need for code generality. The final product will be freely available on a version control site such as GitHub with detailed guides on how it is best used.