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RESEARCH ARTICLE
Contents Vol 60(12)

Modelling the possible effects of climate change on an Australian multi-fleet prawn fishery

M. C. Ives A C , J. P. Scandol B , S. S. Montgomery B and I. M. Suthers A
+ Author Affiliations
- Author Affiliations

A School of Biological, Earth and Environmental Sciences, The University of New South Wales, Sydney, NSW 2052, Australia.

B NSW Department of Primary Industries, PO Box 21, Cronulla, NSW 2230, Australia.

C Corresponding author. Email: matthew.ives@industry.nsw.gov.au

Marine and Freshwater Research 60(12) 1211-1222 https://doi.org/10.1071/MF07110
Submitted: 24 May 2007  Accepted: 25 March 2009   Published: 17 December 2009

Abstract

The relationship between fisheries and climate has been given renewed emphasis owing to increasing concern regarding anthropogenically induced climate change. This relationship is particularly important for estuarine fisheries, where there are documented correlations between river discharge and productivity. The commercial catch of school prawns (Metapenaeus macleayi) has been shown to be positively correlated with the rates of river discharge in northern New South Wales, Australia. In the present study, a simulation model was developed to analyse the dynamics of the stock for 10 years under alternative river discharge scenarios, and the effectiveness of a series of management strategies under these scenarios was examined. A size-based metapopulation model was developed that incorporated the dynamics of school prawn populations in three habitats being harvested by three different fishing methods. The model indicated that both the growth and movement of prawns were affected by the rates of river discharge, and that higher rates of river discharge usually generated increased commercial catches, but this outcome was not certain. It was concluded that the population does not appear to be overexploited and that none of the three alternative management strategies performed better within the model than the current spatio-temporal closures, even under a wide range of river discharge scenarios.

Additional keywords: Bayesian modelling, climate variability, management strategy evaluation, stock assessment.


Acknowledgements

We would like to acknowledge Will Macbeth, Mark Baird, Jason Everett, André Punt, Malcolm Haddon, Neil Loneragan and an anonymous reviewer for their valuable comments on this manuscript. This study was funded by the ARC Linkage Project APA(I) LP0453821 and the NSW Department of Primary Industries.


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