Data intermediate assessment: Examining the suitability of a novel depletion model for use in a spiny lobster fishery

Abstract

The choice of assessment technique for a fishery with some, but not large amounts of data (intermediate data fishery), can be complex and depends on their suitability to the available data set(s) at an optimum resolution and appropriateness of model assumptions. Various “appropriate” techniques may have different output biases and understanding these is essential for robust fisheries management. We tested the suitability of an extended depletion model to assess a crustacean population using simulated data that replicated fishing patterns of a southern rock lobster (SRL) fishery in Western Australia. This simulation showed the model was appropriate for use and robust to assumptions including predetermined parameter choice and whether lobsters moulted during the fitted period. Although natural mortality was shown to have the biggest influence on model outputs (when compared to assumptions on moulting and fishing efficiency), its actual impact was minimal. When applied to the SRL resource off Western Australia, the model indicated that the stock has been heavily fished and reduced to almost 20 % of virgin levels. In recent years exploitation rates have declined due to external factors such as market access. This has resulted in a rapid increase in biomass, and model projections suggest that, with current catches, the biomass will return to 50 % of virgin levels within 10 years. Testing the modelling approach on a fishery with intermediate data provisions through simulation, has provided confidence in applying this technique to derive improved estimates for management.