Small-scale fisheries (SSF) are essential to global food security and livelihoods, yet their assessment is often limited by incomplete or uncertain fisheries-dependent data. Traditional indicators such as catch-per-unit-effort (CPUE) can be unreliable, especially for sedentary species, due to mismatches between the scale of fishing effort assessment and the spatial dynamics of target populations. This study evaluates the potential of georeferenced fisheries-dependent data (GFFD) to predict catch per dive (CPD) and improve CPUE estimation in the Tasmanian commercial abalone fishery, focusing on Blacklip abalone (Haliotis rubra).
Fisher-reported CPD estimates collected between January 2023 and October 2024, were matched to georeferenced effort data obtained using GPS and depth loggers and validated against daily weighed landings. Kernel density estimates (75% isopleths) were used to calculate dive metrics including duration, area covered, swim rate, and depth. The current approach for allocating CPD assigns a portion of the daily catch to individual dives based on their duration as a proportion of the total daily dive time. This method assumes that catch is proportional to effort. Comparison of effort measures within this approach indicated that dive duration was a more reliable predictor of CPD than area. To further improve predictive accuracy, a Generalised Additive Model (GAM) was developed using a broader suite of dive metrics. The final model, informed by automated selection, enhanced predictive performance of CPD and identified swim rate, depth, and the effort-based allocated catch value as key predictors.
The findings demonstrate that fishers can provide reliable catch estimates, and that GFFD-derived metrics can accurately predict CPD for Blacklip abalone. Aligning catch data with the spatial scale of effort improves assessments of fishing impact, particularly for sedentary species like H. rubra. Identifying key behavioural metrics also offers insights into how fishing practices might shift in response to ecological or economic changes. Given the central role of CPUE in Tasmania’s abalone harvest strategy, these findings enhance the robustness and defensibility of management decisions. Although developed for the Tasmanian context, this approach shows promise for improving CPUE accuracy in other SSFs globally with comparable spatiotemporal fishing practices.