Literature DB >> 16909673

Identification of shark species composition and proportion in the Hong Kong shark fin market based on molecular genetics and trade records.

Shelley C Clarke1, Jennifer E Magnussen, Debra L Abercrombie, Murdoch K McAllister, Mahmood S Shivji.   

Abstract

The burgeoning and largely unregulated trade in shark fins represents one of the most serious threats to shark populations worldwide. In Hong Kong, the world's largest shark fin market, fins are classified by traders into Chinese-name categories on the basis of market value, but the relationship between market category and shark species is unclear preventing identification of species that are the most heavily traded. To delineate these relationships, we designed a sampling strategy for collecting statistically sufficient numbers of fins from traders and categories under conditions of limited market access because of heightened trader sensitivities. Based on information from traders and morphological inspection, we hypothesized matches between market names and shark taxa for fins within 11 common trade categories. These hypotheses were tested using DNA-based species identification techniques to determine the concordance between market category and species. Only 14 species made up approximately 40% of the auctioned fin weight. The proportion of samples confirming the hypothesized match, or concordance, varied from 0.64 to 1 across the market categories. We incorporated the concordance information and available market auction records for these categories into stochastic models to estimate the contribution of each taxon by weight to the fin trade. Auctioned fin weight was dominated by the blue shark (Prionace glauca), which was 17% of the overall market. Other taxa, including the shortfin mako (Isurus oxyrinchus), silky (Carcharhinus falciformis), sandbar (C. obscurus), bull (C. leucas), hammerhead (Sphyrna spp.), and thresher (Alopias spp.), were at least 2-6% of the trade. Our approach to marketplace monitoring of wildlife products isparticularly applicable to situations in which quantitative data at the source of resource extraction are sparse and large-scale genetic testing is limited by budgetary or other market access constraints.

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Year:  2006        PMID: 16909673     DOI: 10.1111/j.1523-1739.2005.00247.x

Source DB:  PubMed          Journal:  Conserv Biol        ISSN: 0888-8892            Impact factor:   6.560


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