Variability in the spatial and temporal distribution of the saucer scallop, Amusium balloti, in Shark Bay-management implications
Faculty of Computing, Health and Science
School of Engineering / Natural Resources Modelling and Simulation Research Group
The present paper is the first description using geostatistical modelling of recruitment (0+) and residual (1+) scallop variability from an annual survey in a semi-tropical embayment. Geostatistical modelling provides a useful tool to explore and interpret distribution patterns and can provide information to determine potential behaviour of fishers. It may also aid in determining the time it will take from the beginning of the season to reach a catch-rate threshold, which is the management strategy implemented in the Shark Bay scallop fishery since 2004. High variability in recruit abundance and spatial distribution was observed among years, whereas patterns of residual abundance and distribution were less variable because of the fishing patterns of both the scallop and prawn fleets. Comparisons of commercial catch patterns indicated that high survey-abundance areas correlate with higher catches, validating that survey results are a good tool for fishers to utilise to target their fishing practices to optimise and maximise catch efficiencies. The study highlighted the inherent annual variability of scallop recruitment abundance and distribution that are primarily considered to be environmentally driven. However, both recruits and residual scallops contribute to the whole catch, so retaining residual scallops from year to year is important.
not open access