ICES Journal of Marine Science: Journal du Conseil Advance Access originally published online on November 13, 2006
ICES Journal of Marine Science: Journal du Conseil 2007 64(1):97-109; doi:10.1093/icesjms/fsl013
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Optimizing a stratified sampling design when faced with multiple objectives
1 Quantitative Ecology and Resource Management Program, University of Washington, Box 352182, Seattle, WA 98195, USA
2 School of Aquatic and Fisheries Sciences, University of Washington, PO Box 355020, Seattle, WA 98195, USA
3 National Marine Fisheries Service, Alaska Fisheries Science Center, 7600 Sand Point Way NE, Seattle, WA 98115, USA
Correspondence to T. J. Miller: Present address: Large Pelagics Research Center, Zoology Department, University of New Hampshire, Durham, NH 03824, USA. tel: +1 603 862 2897; fax: +1 603 862 2888; e-mail: tim.miller{at}unh.edu
Miller, T. J., Skalski, J. R., and Ianelli, J. N. 2007. Optimizing a stratifield sampling design when faced with multiple objectives – ICES Journal of Marine Science, 64, 97–109.For many stratified sampling designs, the data collected are used by multiple parties with different estimation objectives. Quantitative methods to determine allocation of sampling effort to different strata to satisfy the often disparate estimation objectives are lacking. Analytical results for the sampling fractions and sample sizes for primary units within each stratum of a stratified (multi-stage) sampling design that are optimal with respect to a weighted sum of relative variances for the estimation objectives are presented. Further, an approach for assessing gains or losses for each estimation objective by changing allocation of sample sizes to each stratum is provided. As an illustration, the analytical results are applied to determine optimal observer sampling fractions (coverage rates) for the North Pacific Groundfish Observer Programme (NPGOP), for which the multiple objectives are assumed to be bycatch (seabird, marine mammal, and non-targeted fish species) and total catch, and catch-at-length and -age of targeted fish species. Simultaneously optimizing a criterion that defines the strata of the NPGOP sampling design is also considered. When observer coverage rates are allowed to be gear-specific for the NPGOP design, the optimized objective function is between 10% and 28% less than the value corresponding to current sampling for annual data (2000–2003) and 12% less when optimized over all years combined.
Keywords: multi-parameter, North Pacific, observer coverage, optimal sampling, stratified sampling
Received 27 February 2006; accepted 13 September 2006; advance access publication 13 November 2006.
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