Fishing activity was captured across 53,852 one Hectare hex grid cells across Tasmania. A total of 113,164 diving hours were recorded across 125,536 individual fishing events (Table 1). Between 2012 and 2016, the Tasmanian Geo-Fishery Dependent Data (GFDD) program captured between 85 % and 90 % of the fishing effort across the entire fishery. Four spatial Indicators obtained from the GFDD - linear swim rate (Lm/hr), area search rate (Ha/hr), catch landed per Hectare (KgLa/Ha), and drops per day offer significant promise as new performance measures in addition to classic catch and effort based CPUE indicators (Chapter 6). Catch landed per unit area (KgLa/Ha) and Maximum linear extent of the dive displayed consistent and interpretable trends that parallel trends in CPUE, and the relationship with CPUE appeared to be global in nature. Linear swim rate as Lm/Hr appeared to have a local rather than global relationship with CPUE (Kg/Hr), highlighting the importance of underlying assumptions when determining TRPs and LRPs for these new spatial indicators. The GFDD through the linear swim rate indicator was able to detect a change in intensity of selective fishing practices (i.e. fisher diving patterns) in the Perkins Bay greenlip fishery. This finding is an important demonstration of the capacity of GFDD to identify change in fishing behaviour that has a spatial signature. The primary impediment to utilising these indicators in Harvest Strategies or ad hoc decision processes (for states with data available) is the limited time-series from which to develop meaningful Limit and Target reference Points (LRP and TRP).

This project has achieved the first significant quantitively description of spatially structured, spatially discrete hand-harvest fisheries across Tasmania, New South Wales and Victoria. Serial depletion is often presented as a theoretical explanation for the demise of fisheries, but that concept is rarely supported with empirical data. Chapter 10 demonstrated that the Tasmanian abalone fishery was comprised of several hundred discrete reef systems across the Tasmanian coastline, and that catch was largely proportional to area. While there were several outlier reefs, this relationship between reef area and reef production hints at some underlying base productivity. Strong relationships between catch and effort are routinely observed, but this is the first demonstration that such a relationship also exists for catch and area.

The proportion of fishable reef utilised each year and the degree of overlap between successive years was previously unknown, and researchers and management relied on industry participants to provide input on long-term changes. However results obtained from diver overlap analyses suggest that asking fishers their opinion on whether the global fishable reef is changing is an unfair question, as there is relatively little overlap in where fishers work, and particularly in large fisheries with many divers, any one diver may only fish a small fraction of the total area. Analytical tools developed in this project enable researchers to exploit the GFDD datasets and provide a precise measure of the extent of reef used in any one year. This project demonstrated that the area of reef fished in anyone year may be only half the known productive fishing grounds. This should not be interpreted as potential for expansion, but rather highlights the process of cycling through fishing grounds, enabling some reefs to escape fishing in some years.

There has been considerable attention given in Victoria and New South Wales to develop a predictive tool utilising previous history to determine future catch. While this is a potentially exciting application of the GFDD data, there appears to be considerable spatial and temporal dynamic in predictability of catch. The Geographic Weighted Regression analyses (Chapter 8) were very useful in identifying local areas of temporal persistence, and/or areas where catch is highly variable mong years. These types of analyses may have greater utility in understanding how productivity of exploited reef systems change through time in a backward-looking investigation than in any future predictive capacity. The challenge with using spatial linear modelling of whole of year spatial fishing patterns to predict catch in future years is that TACC decisions are often made prior to completion of the fishing year. There would need to be a clear demonstration that partial years data provided the same overall pattern as the full year data, and that is likely to be dependent on how much quota was left to catch at the time of the analyses.

Several analytical tools were developed to examine fleet behaviour and diver movement patterns, local variability in harvest levels and spatial structure of the reef systems being exploited. Separating normal fleet patterns driven by fisher preference, effects of inter-annual variation in exploitable biomass, and long-term changes in stock levels will require a much longer time series than currently available. Short term shifts in fleet movements and temporal variability in structure of fishing may be easily confused with normal cycling of fishing grounds. There is considerable impatience to utilise Geo-referenced fishery-dependent data in decision making processes and Harvest Strategies, despite no defensible mechanism to develop reference points from the short time series available. Similarly, the proportion of the known fishable reef area utilised each year and the degree of overlap among subsequent years are likely to be enormously informative for understanding one of the key unknown questions in abalone fisheries – is the footprint of the fishery and/or density changing through time. The capacity to identify areas of high persistence of commercially productive stocks will also improve our ability to understand and monitor key drivers of productivity and local regions critical to achieving the TACC.

Project has facilitated the collection of geo-referenced fishery dependent data across Tasmania, New South Wales and Victoria. A companion project was also run in the South Australian Central Zone abalone fishery where use of the Tasmanian GPS and Depth data loggers was made mandatory in 2013. The success of GFDD in improving the confidence in determining stock status ultimately relies on the high level of data coverage achieved, particularly in Tasmania. While the KUD derived spatial indicators may be useful with lower levels of coverage, the grid derived indicators will be of little use without high levels of data coverage as they rely on capturing activities of the entire fleet across a fishing year. In particular the Index of Persistence developed in Chapter 9 is not viable without a high level of data coverage. If spatial indicators are to be considered as part of annual assessments of fishery status there must be a commitment to ongoing collection of the data to generate a time-series that is useful, and that there is some certainty of these data streams being available for assessment into the future.