Optimal sampling for estimating the size structure and mean size of abalone caught in a new south wales fishery

The fishery for blacklip abalone, Haliotis rubra, is one of the most valuable in New South Wales, Australia. An important part of the stock assessment process for this fishery is to quantify temporal changes in mean size and size structure of abalone in the landed catch. Variation in abalone growth over small spatial scales in this fishery and differences in harvest strategy among different divers result in large variations in sizes of abalone landed. Monte Carlo simulations were used to investigate the influence of these sources of variation on estimates of mean size and size structure. Different sampling scenarios were considered from random sampling of all diver-days to a more realistic scheme where abalone were subsampled both within and among diver-days. For a given total number of abalone measured, error in estimated mean size and size structure declined asymptotically with increasing numbers of diver-days. By measuring at least 1,500 abalone from 100 diver-days, reliable estimates of size structure and mean size of abalone in the catch for the whole fishery were produced. This conclusion was robust with respect to the number of diver-days in the fishery. Estimated sampling intensity and probabilities of detecting differences based on simulated variances for the whole fishery are provided.