ICES Journal of Marine Science: Journal du Conseil Advance Access originally published online on March 28, 2009
ICES Journal of Marine Science: Journal du Conseil 2009 66(4):631-645; doi:10.1093/icesjms/fsp063
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A simulation strategy for fleet dynamics in Australia’s northern prawn fishery: effort allocation at two scales
1 CSIRO Mathematics and Information Sciences, PO Box 120, Cleveland, QLD 4163, Australia
2 CSIRO Marine and Atmospheric Research, PO Box 120, Cleveland, QLD 4163, Australia
3 School of Aquatic and Fishery Sciences, University of Washington, Box 355020, Seattle, WA 98195-5020, USA, and CSIRO Marine and Atmospheric Research, GPO Box 1538, Hobart, TAS 7001, Australia
Correspondence to W. N. Venables: tel: +61 7 3826 7251; fax: +61 7 3826 7304; e-mail: bill.venables{at}csiro.au.
Venables, W. N., Ellis, N., Punt, A. E., Dichmont, C. M., and Deng, R. A. 2009. A simulation strategy for fleet dynamics in Australia’s northern prawn fishery: effort allocation at two scales. – ICES Journal of Marine Science, 66: 631–645.We describe simple and effective methods for simulating the movement of a fishing fleet, the spatio-temporal allocation of effort, in the context of harvest policy evaluation. Vessel movements are simulated in a manner that can balance established seasonal fishing patterns with the influence of perceived local variations in abundance. In the longer term, the model adapts smoothly to changes in fleet size and price fluctuations in critical resources, such as fuel. Given an initial allocation of effort at a fine temporal (but coarse spatial) scale, as needed for projecting stock dynamics, a second phase assigns the effort at a finer spatial (but coarser temporal) scale for environmental impact assessment. The first phase is based on a discrete-state, time-inhomogeneous Markov chain, with transition probabilities following a multiple logistic model. Although the ideas are generic, the method has been developed for the specific case of Australia’s northern prawn fishery, which is used to motivate and describe the method. The approach, in a harvest policy evaluation context, is novel in that it uses economic projections (not surrogates) to reflect realistically the recent pressures many fishing industries are under to change their spatial fishing pattern in response to global fuel price fluctuations.
Keywords: fleet dynamics, fuel price, harvest strategy, Markov chain, northern prawn fishery, prawn, vessel movement
Received 10 June 2008; accepted 23 February 2009; advance access publication 28 March 2009.