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ICES Journal of Marine Science: Journal du Conseil Advance Access originally published online on May 2, 2009
ICES Journal of Marine Science: Journal du Conseil 2009 66(5):928-934; doi:10.1093/icesjms/fsp112
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© 2009 International Council for the Exploration of the Sea. Published by Oxford Journals. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Efficient designs for sampling and subsampling in fisheries research based on ranked sets

You-Gan Wang1, Yimin Ye2 and David A. Milton3

1 CSIRO Mathematical and Information Sciences, CSIRO Long Pocket Laboratories, 120 Meiers Road, Indooroopilly, QLD 4068, Australia
2 CSIRO Marine and Atmospheric Research, PO Box 120, Cleveland, QLD 4163, Australia. Present address: Fishery Management and Conservation Service, FAO, Viale delle Terme di Caracalla, 00153 Rome, Italy
3 CSIRO Wealth from Oceans Flagship, Marine and Atmospheric Research, PO Box 120, Cleveland, QLD 4163, Australia

Correspondence to Y-G. Wang: tel: +61 7 3214 2816; fax: +61 7 3214 2855; e-mail: you-gan.wang{at}csiro.au.

Wang, Y-G., Ye, Y., and Milton, D. A. 2009. Efficient designs for sampling and subsampling in fisheries research based on ranked sets. – ICES Journal of Marine Science, 66: 928–934.

Sampling strategies are developed based on the idea of ranked set sampling (RSS) to increase efficiency and therefore to reduce the cost of sampling in fishery research. The RSS incorporates information on concomitant variables that are correlated with the variable of interest in the selection of samples. For example, estimating a monitoring survey abundance index would be more efficient if the sampling sites were selected based on the information from previous surveys or catch rates of the fishery. We use two practical fishery examples to demonstrate the approach: site selection for a fishery-independent monitoring survey in the Australian northern prawn fishery (NPF) and fish age prediction by simple linear regression modelling a short-lived tropical clupeoid. The relative efficiencies of the new designs were derived analytically and compared with the traditional simple random sampling (SRS). Optimal sampling schemes were measured by different optimality criteria. For the NPF monitoring survey, the efficiency in terms of variance or mean squared errors of the estimated mean abundance index ranged from 114 to 199% compared with the SRS. In the case of a fish ageing study for Tenualosa ilisha in Bangladesh, the efficiency of age prediction from fish body weight reached 140%.

Keywords: age determination, monitoring survey, ranked set sampling, sampling design, sampling efficiency

Received 26 November 2008; accepted 26 March 2009; advance access publication 2 May 2009.


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