Identification of Shark Species Composition and Proportion in the

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Identification of Shark Species Composition and Proportion in the Powered By Docstoc
					Identification of Shark Species Composition and
Proportion in the Hong Kong Shark Fin Market Based
on Molecular Genetics and Trade Records
 Joint Institute for Marine and Atmospheric Research, c/o National Research Institute of Far Seas Fisheries, 5-7-1 Orido-Shimizu,
Shizuoka 474-0022, Japan
†Guy Harvey Research Institute, Nova Southeastern University Oceanographic Center, 8000 North Ocean Drive, Dania Beach,
FL 33004, U.S.A.
‡Renewable Resources Assessment Group, Imperial College London, Royal School of Mines Building, Prince Consort Road,
London SW7 2AZ, United Kingdom

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 is particularly 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.

Key Words: DNA forensics, marketplace monitoring, marketplace sampling, seafood, wildlife
            o                  o             o                       o                                   o
Identificaci´ n de la Composici´ n y Proporci´ n de Especies de Tibur´ n en el Mercado de Aletas de Tibur´ n en
Hong Kong Con Base en Gen´tica Molecular y Registros Comerciales
Resumen: El floreciente y en gran parte no regulado comercio de aletas de tibur´ n representa una de las
m´ s serias amenazas para las poblaciones de tiburones en todo el mundo. En Hong Kong, el mayor mercado
                  o                                                                   ı
de aletas de tibur´ n en el mundo, los comerciantes clasifican a las aletas en categor´as con nombres en Chino
                                                 o                  ı                                    o
con base en el valor de mercado, pero la relaci´ n entre la categor´a de mercado y las especies de tibur´ n no
es clara, lo que limita la identificaci´ n de especies que son sujetas de mayor comercio. Para delinear estas

∗∗ Address
         correspondence to M. Shivji, email
Paper submitted September 4, 2004; revised manuscript April 12, 2005.

                                                                                            Conservation Biology Volume 20, No. 1, 201–211
                                                                                            C 2006 Society for Conservation Biology
                                                                                            DOI: 10.1111/j.1523-1739.2006.00247.x
202       Species in Shark Fin Trade                                                                                  Clarke et al.

                n                                                               u          ı
relaciones, dise˜ amos una estrategia para recolectar con comerciantes un n´ mero estad´sticamente suficiente
de aletas bajo condiciones de mercado de acceso limitado debido a la intensificaci´ n de las sensibilidades de
                                          o                                     o        o                 o
los comerciantes. Con base en informaci´ n de los comerciantes y en inspecci´ n morfol´ gica, hicimos hip´ tesis
sobre la correspondencia entre los nombres comerciales y los taxa de tiburones para aletas dentro de 11 cate-
    ı                                            o                 e                     o
gor´as comerciales comunes. Probamos las hip´ tesis utilizando t´cnicas de identificaci´ n de especies con base
en ADN para determinar la concordancia entre la categor´a de mercado y la especie. Solo 14 especies abar-
caron aproximadamente 40% del peso de las aletas a la venta. La proporci´ n de muestras que confirmaron la
    o                                                o                            ı
hip´ tesis de correspondencia, o concordancia, vari´ de 0.64 a 1 en las categor´as de mercado. Incorporamos
              o                                                                          a
la informaci´ n de concordancia y los registros de venta disponibles en modelos estoc´ sticos para estimar la
            o      u                       o
contribuci´ n, seg´ n el peso, de cada tax´ n al comercio de aletas. El peso de aletas a la venta fue dominado
por Prionace glauca, que comprendi´ 17% del total del mercado. Otros taxa, incluyendo a Isurus oxyrinchus,
Carcharhinus falciformis, C. obscurus, C. leucas, Sphyrna spp. y Alopias spp., comprendieron por lo menos entre
2 y 6% del comercio. Nuestro m´todo para monitoreo del mercado de productos de vida silvestre es partic-
ularmente aplicable a situaciones de escasez de datos cuantitativos obtenidos en el sitio de extracci´ n del
                        a         e                     a
recurso y cuando el an´ lisis gen´tico a gran escala est´ limitado por restricciones presupuestarias o de acceso
al mercado.

Palabras Clave: ADN forense, mariscos, monitor, muestreo, vida silvestre

Introduction                                                        fisheries (Camhi 1999) have contributed to growing con-
                                                                    cerns that the fin trade may be driving shark catches to
Advances in molecular biology over the past decade have             unsustainable levels. Policy responses to these concerns,
created a variety of powerful conservation tools, includ-           including the Food and Agriculture Organization’s Inter-
ing the ability to identify the species or population origin        national Plan of Action for Sharks (Food and Agriculture
of wildlife products, enabling new types of trade monito-           Organization 1998) and the listing of three shark species
ring and analysis. The often secretive nature of the wildlife       in the appendices of the Convention on International
trade and the prohibitively high cost of purchasing sam-            Trade in Endangered Species of Wild Fauna and Flora
ples, however, may constrain sample access and acqui-               (CITES), have been hampered by a lack of species-specific
sition and thus limit application of genetic technology.            catch and trade data for most fisheries (Clarke 2004a).
Under these circumstances, the appropriate choice of                Shark resource management based on an amalgam of
study objectives and the sampling design become criti-              species is suboptimal because it is likely to exaggerate the
cal aspects of any research program aimed at surveying              conservation concern for some species (e.g., sharks with
markets to monitor and quantify wildlife trade.                     high fecundities and low age of maturity) while poten-
   Many researchers have applied genetic techniques to              tially understating the vulnerability of less prolific shark
determine whether particular species, populations, or in-                                           e
                                                                    stocks (Smith et al. 1998; Cort´s 2002).
dividuals are present in wildlife trade (e.g., Malik et al.            Hong Kong is the world’s largest shark fin market, rep-
1997; Birstein et al. 1998; Hoelzel 2001; Dalebout et al.           resenting at least 50% of the global trade (Fong & Ander-
2002). These researchers, however, were concerned pri-              son 2002; Clarke 2004b). Previous studies of the Hong
marily with demonstrating that the proposed technique               Kong fin trade describe fin types with primarily English
is effective for forensic identification of individual mar-         common names for sharks (Parry-Jones 1996; Vannuccini
ketplace products and did not attempt to characterize               1999; Fong & Anderson 2000) and rely solely on traders’
the composition and proportion of species in the trade              knowledge of these English names, with no means of inde-
as a whole. Marketplace sampling and characterization               pendently verifying the actual species origin. Traders use
of wildlife products are particularly valuable when the             30–45 market categories of fins ( Yeung et al. 2000), but
sources of extraction (e.g., landing ports for fish or hunt-        the Chinese names of these categories do not correspond
ing camps for terrestrial mammals) are diffuse and lack             to the Chinese taxonomic names of shark species (Huang
standardized, species-specific records. In such cases mon-          1994). Instead Chinese market categories for shark fins
itoring of species parts in trade, particularly in large ware-      appear to be organized primarily by the quality of fin rays
houses at the center of global supply chains, may be the            produced and secondarily by distinguishing features of
most effective means of obtaining data necessary for off-           dried fins because often traders have never observed the
take assessment and management.                                     whole animal.
   Increasing awareness of the vulnerability of shark                  Our recent analysis of Hong Kong shark fin auction
species to exploitation (Camhi et al. 1998; Castro et al.           data produced minimum estimates of quantities (metric
1999) and a documented proliferation of finning (i.e., re-          tonnes [mt]) of shark fins traded in 11 market categories.
moval of fins and discarding of the carcass at sea) in some         We used statistical models to account for missing records

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Volume 20, No. 1, February 2006
Clarke et al.                                                                                      Species in Shark Fin Trade   203

and simulate a complete dataset (Clarke et al. 2004). The          lieved to be common in the fin trade, to ensure species
11 studied market categories comprised 46% of the auc-             specificity (i.e., absence of false positives).
tioned shark fins, with the remainder auctioned under                 Sequences and diagnostic validation data for the
other trade names or in unspecified categories. Over-              species-specific primers used in this study are avail-
all, 18% of the auctioned fins were labeled as ya jian,            able from the following sources: shortfin mako (Isu-
which on the basis of trader information and morpholog-            rus oxyrinchus), longfin mako (I. paucus), silky (Car-
ical examination were hypothesized to originate from the           charhinus falciformis), dusky (C. obscurus), and blue
blue shark (Prionace glauca). Several other categories             sharks in Shivji et al. (2002); common (Alopias vulpi-
hypothesized to derive from other coastal and pelagic              nus), bigeye (A. supercilious), and pelagic thresher (A.
sharks comprised 3–5% each of the estimated auctioned              pelagicus) sharks in Abercrombie (2004); tiger (Galeo-
fin quantity (Clarke et al. 2004). Although this study pro-        cerdo cuvier), bull (C. leucas), and spinner (C. brevip-
vides the first quantitative information on trade composi-         inna) sharks in Nielsen (2004); and scalloped (Sphyrna
tion by market category, its usefulness is limited because         lewini), smooth (S. zygaena), and great hammerhead (S.
Chinese market categories could not be related conclu-             mokarran) sharks in Abercrombie et al. (2005). The sand-
sively to shark taxa and thus extraction rates for individual      bar shark (C. plumbeus) primer sequence is in Pank et
species could not be assessed.                                     al. (2001; additional validation data from M. Henning &
   Here we investigated, using molecular genetic identi-           M.S.S., unpublished data).
fication, concordances between the most common Chi-                   All primers are highly reliable in their diagnostic ac-
nese market categories and species in the Hong Kong                curacy (above references), with the following caveats
shark fin market. These concordance results were de-               for two primers. The dusky primer cross-amplifies two
signed to be modeled in conjunction with estimates of              of its congeners, Galapagos shark (C. galapagensis) and
the traded weight of shark fins in each market category            oceanic whitetip shark (C. longimanus). Because fins of
(Clarke et al. 2004) to better understand the composition          the oceanic whitetip shark are unmistakably distinct in
and contribution by species to the fin trade. Another of           appearance (Castro 1993), however, we used the dusky
our objectives was to devise effective market sampling             primer to indirectly confirm morphological identification
strategies for animal parts under conditions fraught with          of these fins. The uncertainty introduced when using the
sampling constraints and to guide other applications of            dusky primer is thus limited to the inability to distinguish
molecular diagnostic methods to wildlife trade monitor-            fins from dusky and Galapagos sharks only. The bull shark
ing faced with similar access limitations.                         primer faintly cross-amplifies its congener, the Caribbean
                                                                   reef shark (C. perezi). Because cross-amplification of the
                                                                   Caribbean reef shark by the bull shark primer is ineffi-
                                                                   cient, however, consistently producing only a very faint
                                                                   amplicon, discrimination between these two species has
                                                                   not been problematic (Nielsen 2004). Nevertheless, a sec-
Genetic Identification
                                                                   ondary testing of all fins identified as originating from
The recent development of diagnostic DNA sequence                  bull shark with an extensively validated Caribbean reef
tests with species-specific PCR primers for sharks be-             shark primer (M. Henning & M.S.S., unpublished data)
lieved to be common in the shark fin trade has provided            confirmed identification of bull shark fins.
a new tool for studying this trade. Detailed methodolo-
gies for these diagnostic tests are provided in Pank et
al. (2001), Shivji et al. (2002), Chapman et al. (2003),
                                                                   Sampling Constraints in the Hong Kong Shark Fin Market
Abercrombie (2004), Nielsen (2004), and Abercrombie
et al. (2005), and are overviewed briefly here. The tech-          Approximately 50 retail or wholesale establishments in
nique relies on DNA sequence differences among shark               the dried seafood business district of Hong Kong (Sai Yin
species in the nuclear ribosomal DNA ITS2 locus for the            Pun) deal in shark fin products. Of this number, about
development of species-specific primers. Each primer is            16 wholesalers take turns hosting daily shark fin auctions
a short, synthetic, single-stranded piece of DNA designed          and at least an equal number import large quantities of
to recognize (anneal to) and PCR amplify only DNA from             fins and then export them to mainland China for process-
a single shark species (e.g., a primer designed for short-         ing without auctioning. Traders receive fins from at least
fin mako shark will amplify only DNA from fins of that             85 countries and territories (Clarke & Mosqueira 2002)
species), producing a species-specific DNA band (ampli-            in poorly sorted shipments; because of on-site space lim-
con). Each primer we used here was tested extensively              itations they immediately re-sort the fins into market cat-
against its target species from worldwide sources to en-           egories and promptly auction or sell them. Our sampling
sure its global diagnostic utility (i.e., absence of false nega-   opportunities were limited to these re-sorting periods be-
tives) and approximately 72 nontarget species, including           cause traders refused us access to the fins at other times.
very closely related species (congeners) and those be-             Limits on sampling during re-sorting periods arose from

                                                                                              Conservation Biology
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204        Species in Shark Fin Trade                                                                                                Clarke et al.

the patchy nature of the shipments (i.e., during each sam-                 Sampling Program Design
pling episode fins tended to be clustered in a few market
categories from a particular source country) and the need                  We selected 11 market categories for study because they
to minimize sampling time to avoid delaying re-sorting op-                 were common in the trade and because we had diagnos-
erations. Furthermore, random sampling of the complete                     tic PCR primers for the species we hypothesized to be
range of fins on hand was not feasible because of the                      present in each category. Concordances between Chi-
logistics of moving large sacks in cramped warehouses.                     nese market names and taxa (Table 1) were hypothe-
Given these restrictions, and based on the results of initial              sized based on information from traders and were com-
enquiries at more than 30 trading houses, instead of ran-                  pared with published information on morphologies of
dom sampling we tested samples of particular shark fin                     fins and whole sharks (Fisheries Agency of Japan 1999;
market categories across as wide a range of traders and                    Vannuccini 1999; Yeung et al. 2000; Froese & Pauly 2002).
source countries as possible.                                              We avoided market categories representing mixed fin

Table 1. A priori hypothesized matches (x→x ) between traders’ market categories and shark taxa for fins targeted in the sampling.

                                                                                                                             Number of
                          Hypothesized                                                                                    samples required
Market                 predominant shark                                                              Assigned
category               taxa within market                         Taxonomic                           a priori           CV p =          CV p =
(x)∗                      category (x )                           uncertainty                        value of p           0.1             0.05

Ya jian              blue (Prionace              visually distinct; low probability of                  0.95                6               22
                        glauca)                    mixing with other species
Qing lian            shortfin mako               some traders mentioned infrequent                      0.80               25             100
                        (Isurus                    mixing with the less abundant
                        oxyrinchus)                longfin mako (I. paucus)
Wu yang              silky (Carcharhinus         observed presence of silvertip shark                   0.70               43             172
                        falciformis)               fins (C. albimarginatus); potential
                                                   for mixing with other carcharhinids
                                                   especially Galapagos shark (C.
Hai hu               dusky (C. obscurus)         visually similar to bai qing and ruan                  0.90               12               45
                                                   sha but high value of these fins
                                                   causes traders to sort them
Bai qing             sandbar (C.                 visually similar to hai hu and ruan sha                0.90               12               45
                       plumbeus)                   but high value of these fins causes
                                                   traders to sort them accurately
Ruan sha             tiger (Galeocerdo           visually similar to hai hu and bai qing                0.90               12               45
                        cuvier)                    but high value of these fins causes
                                                   traders to sort them accurately
Chun chi             smooth and                  traders state this category contains all               0.60               67             267
                       scalloped                   hammerheads (Sphyrna and
                       hammerhead                  Eusphyra spp., 7 species in total)
                       (Sphyrna                    other than great (S. mokarran);
                       zygaena and S.              hammerhead species not listed as
                       lewini)                     predominant taxa are believed to be
                                                   considerably less abundant
Gu pian              great hammerhead            high value suggests sorting is accurate                0.85               18               71
                       (S. mokarran)               but category may inadvertently
                                                   contain other light-colored
                                                   hammerheads (Sphyrna spp.)
Wu gu                thresher (Alopias           some traders mentioned infrequent                      0.90               12               45
                       spp., 3 species)            mixing with longfin mako (I.
Sha qing             bull (C. leucas)            some traders mentioned infrequent                      0.80               25             100
                                                   mixing with another unknown shark,
                                                   possibly pigeye (C. amboinensis)
Liu qiu              oceanic whitetip (C.        visually distinct; low probability of                  0.95                6              22
                       longimanus)                 mixing with other species
∗ Trade names are romanized under the Pinyin (Putonghua) system. Chinese characters (complex form) are given to facilitate translation

between Pinyin and other forms of Chinese romanization.

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Volume 20, No. 1, February 2006
Clarke et al.                                                                                     Species in Shark Fin Trade   205

lots such as those simply sorted by size because of low              Individual warehouses were sampled between Novem-
value.                                                            ber 2000 and February 2002. At each establishment,
   Given the highly sensitive nature of the fin trade and the     traders were shown a list of desired fin types (in Chinese
accompanying logistical constraints to market sampling,           characters) and asked to allow free-of-charge sampling of
and to reduce the uncertainty in downstream estimation            small pieces of tissue from the edges of dried fins. Sam-
of the proportion of fins in the trade by individual species,     ples were clipped with clean metal pincers or scissors,
we developed an explicit sampling strategy. By determin-          and laboratory genetic analyses avoided using cut edges
ing the sampling effort required to estimate concordances         when extracting DNA in case of cross-sample contamina-
within a given confidence interval for each market cate-          tion introduced at the point of cutting. In the majority
gory, we minimized sampling bias toward the most eas-             of visits, not all fin types could be sampled because of
ily sampled categories (i.e., most common or least valu-          limited stocks. In addition, some traders were reluctant
able products). Simultaneously, we prioritized sampling           to allow sampling of high-value fins for fear of product
of those categories hypothesized to contain a mixture             damage. Many traders did not understand the rationale
of look-alike species’ fins over those expected to con-           for replicate sampling within a category and this led to
tain distinct products from a single species. Determining         sample sizes of n = 1 during many visits. We used the
sample sizes necessary per category in the absence of ex-         information-theoretic evenness measure of Brillouin for
isting information requires setting an a priori probability,      nonrandom samples (Zar 1999) to assess the diversity of
p, that the hypothesized match between market category            samples collected in each market category by trader and
and taxonomic identity would hold for a given tested fin.         geographic source region. Higher values for this statistic
In setting the a priori p we assumed that market cate-            indicate that the samples were spread more evenly among
gories containing morphologically distinctive fins most           the various trader or source regions.
likely derived from a single species and would thus have
high p values (i.e., near 1). We correspondingly reduced
the p values for other categories according to the de-
gree of taxonomic uncertainty as determined from trader
information and preliminary market reconnaissance
                                                                  Implementation of the Sampling Design
(Table 1).
   The required number of samples, n, was determined              We obtained records of 29% of all auctions held during an
based on the binomial model (sensu Zar 1999), with the            18-month period (October 1999–March 2001), including
formula                                                           numerous records from all major trading houses. Details
                                                                  of the auction records and methodology for using existing
                               q                                  records to simulate a complete set of records for the 18-
                       n=              ,
                            (CV p )2 p                            month period are described in Clarke et al. (2004).
                                                                     A total of 596 fin samples from the 11 target market cat-
where p is the proportion correctly identified, q is the          egories was collected. The number of collected samples
proportion incorrectly identified, and CV p is the coeffi-        exceeded the target number for CVp = 0.10 for each mar-
cient of variation in p, as given by CVp = sp /p, where s p       ket category, and for three categories ( ya jian, wu gu, and
is the standard deviation of p. Using this formula, and the       liu qiu) the number of collected samples also exceeded
a priori p values, the requisite number of samples for two        the target number for CVp = 0.05 (Tables 1 & 2).
CV levels for p (CVp = 0.05 and 0.10) was calculated for             Our ability to assess (1) the fidelity of nomenclature
each market category (Table 1).                                   across the trading community and (2) the traders’ ability
   The sampling program aimed to estimate, based on ge-           to consistently classify fins imported from different parts
netic analysis, the a posteriori probability p that a fin iden-   of the world into coherent categories was determined
tified by a trader as market category x is taxon x with a         by the distribution of samples among different trading
low CV for p (CVp < 0.10). The 11 market categories we            houses and source ocean basins or regions. The distri-
analyzed genetically were modeled earlier with Markov             bution by trader was skewed such that 372 of the 596
chain Monte Carlo methods to determine the percentage             samples (62%) were obtained from just two traders. This
by weight of auctioned fins in each category on an annual         is a reflection of the sharp decline in trade-community co-
basis (Clarke et al. 2004). We extended this model based          operation following a shark conservation campaign con-
on the results of the concordance testing such that in each       ducted in Hong Kong in March 2001. Because many of the
model iteration the stochastically determined weight of           traders were unable to be precise about the geographic
fins in each market category was multiplied by a stochas-         origin of the fins, we used general categories to assess
tic estimate of p, generated from data on the number of           the distribution of samples across ocean basins or areas.
samples tested and the number of samples verifying the            The two heavily sampled traders specialized in imports
hypothesized match for each category. This allowed us to          from South America, and this is reflected in the fact that
determine the proportion of fins in the trade by species.         264 of 596 samples (44%) were said to have originated in

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206        Species in Shark Fin Trade                                                                                                 Clarke et al.

Table 2. Shark fin samples collected and their distribution within each market category by trader and geographic source (ocean basin/region)
of fins.

                                                                                                     Source ocean basins
Trader’s                                                        Traders           Evenness          or regions represented         Evenness
market                Hypothesized            Samples         represented        for traders        (of 8 total, excluding        for sources
category              species match         collected (n)     (of 21 total)     (Brillouin J)a          unidentified)b           (Brillouin J)a

Ya jian         P. glauca                         37               11                0.81                       5                     0.77
Qing lian       I. oxyrinchus                     69               11                0.68                       6                     0.82
Wu yang         C. falciformis                   110               13                0.71                       5                     0.58
Hai hu          C. obscurus                       34                7                0.52                       4                     0.43
Bai qing        C. plumbeus                       40                9                0.64                       3                     0.69
Ruan sha        G. cuvier                         26                6                0.63                       3                     0.48
Chun chi        S. zygaena or S. lewini           94               13                0.68                       7                     0.60
Gu pian         S. mokarran                       35                8                0.70                       4                     0.29
Wu gu           Alopias spp.                      75                9                0.69                       6                     0.81
Sha qing        C. leucas                         53               10                0.74                       5                     0.64
Liu qiu         C. longimanus                     23                9                0.76                       3                     0.76
a Theevenness statistics (Brillouin J) (Zar 1999) represent only the equity of the distribution of samples among traders or sources that were
sampled and are not a function of the total possible number of sampled traders or sources.
b Geographic sources of fins cited by the traders providing samples were grouped into eight categories as follows: South America (Brazil,

Ecuador); Eastern Atlantic/West Africa (Spain, Togo); Southeast Asia (Australia, Indonesia, Philippines); Indian Ocean (India, Sri Lanka,
Maldives, Bangladesh); Southern Africa (South Africa, Angola); Central America (Gulf of Mexico, Costa Rica); South Pacific (Fiji); Middle East
(may include fins from unspecified African countries).

South America. Nevertheless, one of the heavily sampled                    a posteriori values of p, the proportion of samples vali-
traders also received shipments of fins from other loca-                   dating the hypothesized match, ranged from 0.64 for sha
tions, and these other locations contributed 50% of the                    qing to 1.00 for liu qiu (Table 3). Calculation of a poste-
samples from this trader.                                                  riori estimates of the coefficient of variation of p (CV p )
   Evenness of sampling diversity, based on the Brillouin                  suggested that for the majority of market categories the
J statistic, across traders ranged from 0.52 to 0.81 (Ta-                  sample size was sufficient to provide a robust estimate
ble 2). The lowest value resulted for the category hai hu                  of the a posteriori value of p because all values of CV p
(n = 34), for which 56% of the samples were collected                      were <0.11 (Table 3). The results from further testing of
from one trader, with another 29% from a second trader.                    samples that did not verify the hypothesized match are
The remaining samples were distributed among five other                    given in Table 4.
traders. Evenness of sampling diversity across geographic                     The results for some market categories, which were eas-
source regions ranged from 0.29 to 0.82 (Table 2), with                    ily distinguished from most other types of fins because
the lowest value for category gu pian (n = 35), for which                  of size, shape, or color, conformed closely to hypothe-
89% of the samples were collected from one source re-                      sized identities. For example, none of the liu qiu fins
gion, with the remaining samples distributed among three                   was from any shark other than oceanic whitetip, and the
other regions or an unidentified source.                                   only ya jian that was not a blue shark fin was from a
                                                                           bigeye thresher shark, which is similar in fin dimensions.
                                                                           Gu pian fins, recognizable because of their light color
Species Identification of Samples
                                                                           and large size, mainly derived from great hammerheads
All samples (n = 596) were initially tested with the                       as expected, and four of the five gu pian fins deriving
species-specific primer representing the hypothesized                      from other species were from the morphologically simi-
taxonomic match (Table 1). Complete sample amplifica-                      lar, though smaller, scalloped hammerhead.
tion failure (i.e., failure of the positive control amplicon                  Some market categories validated the hypothesized
to appear [Pank et al. 2001; Shivji et al. 2002]) occurred                 species matches at higher probabilities (i.e., were less
in <4% of the samples. If each amplifiable sample failed                   diverse) than expected. We expected that a posteriori val-
to amplify with its hypothesized species primer (a q fin),                 ues of p for chun chi, smooth or scalloped hammerhead
it was consecutively tested in a multiplex PCR format (de-                 (n = 94), concordance would be relatively low because
tailed in Shivji et al. [2002]) against primers for each of                of the potential presence of other hammerhead species
the 16 species we addressed (i.e., all the species listed                  (e.g., S. tudes, S. corona, S. media, and Eusphyra blochii)
in Table 1 plus longfin mako and spinner) until a match                    for which primers have not yet been developed, in the
was found (a q i sample) or until all the primers had been                 chun chi category. However, except for two samples iden-
tried without achieving identification (a q u sample). The                 tified as deriving from the great hammerhead, one sample

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Clarke et al.                                                                                                     Species in Shark Fin Trade    207

Table 3. Results of genetic analysis of shark fin samples by market category.

                                                                                            Samples confirmed
                                                                                                                         A posteriori estimateb
Trader’s               Hypothesized genetic           Samples        Samples with             as matching the
market category        identification                  tested       control failuresa       hypothesized species          p         CV p        sp

Ya jian                P. glauca                          37                   1                     35                 0.97       0.028       0.027
Qing lian              I. oxyrinchus                      69                   2                     57                 0.85       0.051       0.044
Wu yang                C. falciformis                    110                   2                     86                 0.80       0.049       0.039
Hai hu                 C. obscurus                        34                   0                     29                 0.85       0.071       0.061
Bai qing               C. plumbeus                        40                   6                     25                 0.74       0.103       0.076
Ruan sha               G. cuvier                          26                   1                     21                 0.84       0.087       0.073
Chun chi               S. zygaena or S. lewini            94                   1                     89                 0.96       0.022       0.021
Gu pian                S. mokarran                        35                   0                     30                 0.86       0.069       0.059
Wu gu                  Alopias spp.                       75                   7                     50                 0.74       0.073       0.054
Sha qing               C. leucas                          53                   3                     32                 0.64       0.106       0.068
Liu qiu                C. longimanus                      23                   0                     23                 1.00         0           0
Total                                                    596                  23                    477
a Samples
        with control failures are those for which no positive control amplification could be obtained after several trials.
b The
   proportion of samples validating the hypothesized match is the a posteriori p value (equal to the number of matching samples per
number of samples tested minus control failures).

identified as pelagic thresher, and one sample that did not                     two sampling events from two different traders is less
amplify with any primer, only scalloped and smooth ham-                         easily explained.
merhead fins were present.                                                         Most of the remaining trade categories contained a
   The other category that was less species-diverse than                        higher diversity of species than expected. The mixing
expected was wu yang (n = 110). Amplification with the                          of longfin mako fins with threshers in the wu gu cate-
silky shark species-specific primer was observed in 80%                         gory (22% of fins) and with shortfin makos in the qing
of the successfully tested samples. Most of the remain-                         lian category (9% of fins) was extensive. Of the q i sam-
ing amplifiable fins were identified as scalloped hammer-                       ples in the wu gu and qing lian categories, 88% and 75%,
heads (n = 6) or shortfin makos (n = 4). Only one each of                       respectively, were longfin mako fins. All the high-value
three other Carcharhinus congeners were present (Table                          carcharhinid fins (i.e., hai hu, bai qing, and ruan sha)
4), suggesting that these are most likely present in only                       contained other carcharhinid species and several uniden-
small numbers in the wu yang category. The presence                             tifiable fins that did not amplify with any existing primer.
of several shortfin makos in this category may be due to                        The market category with the lowest a posteriori value of
sampling error because some of the traders call shortfin                        p was sha qing, which was originally expected to show
makos wu yang (         , i.e., same romanization but differ-                   a strong concordance with the bull shark. Of the 50 sha
ent Chinese characters). Identification of six scalloped                        qing samples successfully tested, 17 could not be iden-
hammerheads in the wu yang samples collected during                             tified and may have derived from the morphologically

Table 4. Summary of shark fin samples not confirming the hypothesized match in each market category.

Market category                   q u samplesa                 q i samplesb                               Identity of q i samplesc

Ya jian                                 0                            1                     bigeye thresher (1)
Qing lian                               2                            8                     longfin mako (6), bigeye thresher (1),
                                                                                              scalloped hammerhead (1)
Wu yang                                 9                           13                     scalloped hammerhead (6), shortfin mako (4),
                                                                                              sandbar (1), dusky or Galapagos (1), spinner (1)
Hai hu                                  4                            1                     silky (1)
Bai qing                                8                            1                     dusky or Galapagos (1)
Ruan sha                                3                            1                     bull (1)
Chun chi                                1                            3                     great hammerhead (2), pelagic thresher (1)
Gu pian                                 1                            4                     scalloped hammerhead (4)
Wu gu                                   1                           17                     longfin mako (15), shortfin mako (1), blue (1)
Sha qing                               17                            1                     tiger (1)
Liu qiu                                 0                            0                     not available
Totals                                 46                           50
a Samples  that did not amplify with any species-specific primer.
b Samples  that were found to amplify with another species-specific primer.
c True species identity and number of samples corresponding to each species for q samples.

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208       Species in Shark Fin Trade                                                                                                    Clarke et al.

similar pigeye shark (C. amboinensis) for which no pri-                     in the sampling design whenever possible. For example,
mer is yet available.                                                       we acknowledge that traders’ market categories are based
                                                                            on fin value, which may have little connection with scien-
Market Composition by Trade Category                                        tific taxonomy. This issue was addressed for the categories
                                                                            of interest through an a priori formulation of p (hypoth-
Hong Kong auction records typically contained 19 major
                                                                            esized market category-taxon concordance), which was
market categories describing auction lots. These 19 cate-
                                                                            used to calculate the necessary number of samples.
gories in conjunction with alternative names for the same
                                                                               Our ability to obtain the requisite number and distri-
fin types, names for rare fin types, and combinations of
                                                                            bution of samples across traders and geographic source
names applied to mixed lots resulted in nearly 100 total
                                                                            regions was a key factor. Access constraints directed sam-
market categories. The stochastic model of auctioned fin
                                                                            pling toward testing concordances between market cat-
quantities, extended to incorporate genetic information,
                                                                            egories and shark taxa, rather than random sampling of
provided taxa-specific estimates of the composition, by
                                                                            the trade as a whole. Target sample sizes were achieved
weight, of the shark fin trade and confirmed that blue
                                                                            (Table 3) by following the concordance testing frame-
sharks comprised by far the largest distinct proportion
                                                                            work developed, and reasonable sample distribution was
(17.3% by weight) of fins auctioned in the Hong Kong
                                                                            obtained including 6–13 of the 21 traders and three to
market (Table 5).
                                                                            seven of the eight geographic source regions, depending
                                                                            on market category. Overall, given the covert nature of
                                                                            the trade and the sensitivities generated by ongoing con-
Discussion                                                                  servation campaigns, the implementation of the sampling
                                                                            program was highly successful.
Evaluation of the Sampling Program
Our ability to draw sound conclusions regarding the                         Trader Sorting and Labeling
species composition of the shark fin trade based on our
results is a function of the robustness of the sampling de-                 A large volume of fins (54% by weight) traded in unstud-
sign, the extent of category-specific sorting and labeling                  ied, and often nonspecific, categories (Clarke et al. 2004)
by Hong Kong traders, and the species-diversity scope                       could not be characterized. This shortcoming could not
of the diagnostic primer library. Each factor is discussed                  be overcome but was accounted for by limiting the study
individually and then integrated in the context of each                     to common and relatively distinct types of fins. These un-
studied market category in the following sections.                          studied categories may contain additional fins of studied
                                                                            taxa, particularly when fin size is small, and the low value
Sampling Design                                                             does not warrant careful sorting; therefore, taxa-specific
                                                                            estimates from this study should be considered as mini-
Studies involving sampling of traded wildlife products can                  mum proportions in trade.
gain an even greater understanding of the trade if mer-                        Another difficulty presented by the trade labeling sys-
chant records can be accessed and understood. Shortcom-                     tem was the existence of cases where several taxa are con-
ings of such records should then be explicitly addressed                    tained in one market category (e.g., wu gu category used

Table 5. Means and 95% probability intervals for estimated proportion of the Hong Kong shark fin trade composed of each taxa.a

                         Proportion of trade by market category b                                          Proportions of trade by taxa c
Market category        mean       lower 95% P.I.   upper 95% P.I.           Tested taxon/taxa        mean      lower 95% P.I.     upper 95% P.I.

Ya jian                18.2            16.6             20.0            P. glauca                    17.3           15.5               19.1
Qing lian               3.2             2.8              3.6            I. oxyrinchus                 2.7            2.3                3.1
Wu yang                 4.4             4.0              4.9            C. falciformis                3.5            3.1                4.0
Hai hu                  1.7             1.5              2.0            C. obscurus                   1.4            1.2                1.7
Bai qing                3.3             2.8              3.8            C. plumbeus                   2.4            1.9                2.8
Ruan sha                0.16            0.10             0.23           G. cuvier                     0.13           0.08               0.19
Chun chi                4.7             4.2              5.2            S. zygaena or S. lewini       4.4            3.9                4.9
Gu pian                 1.8             1.5              2.1            S. mokarran                   1.5            1.2                1.8
Wu gu                   3.2             2.8              3.6            Alopias spp.                  2.3            2.0                2.7
Sha qing                3.5             3.0              4.0            C. leucas                     2.2            1.8                2.6
Liu qiu                 1.9             1.6              2.1            C. longimanus                 1.8            1.6                2.1
a The possible presence of additional fins of these taxa within the 54% of the trade that could not be characterized implies that the estimates

below are minimums.
b Proportions by market category (and probability intervals, P.I.) are taken from model results presented in Clarke et al. (2004).
c Proportions by taxon/taxa were derived for this study by extending the model to adjust the market category for taxonomy (see text).

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Volume 20, No. 1, February 2006
Clarke et al.                                                                                      Species in Shark Fin Trade   209

for all three thresher species) and cases where many mar-         a 100% concordance with their hypothesized market
ket categories may be used for one taxon (e.g., the longfin       match. Given the ease of morphological identification of
mako found within several categories). Those cases that           these fins by traders, the best estimate of oceanic whitetip
were detected early in the study were addressed through           sharks’ contribution to the trade (1.8% [1.6–2.1%]) is
careful definition of target categories and sampling re-          likely more accurate than other species because these
quests to traders (e.g., clarifying whether the fin was           fins are less likely to be inadvertently sorted into other
sometimes called by another name).                                categories.
                                                                     The three hammerhead species (scalloped, smooth,
Scope of the Primer Library                                       and great) collectively formed a significant proportion of
                                                                  the trade (approximately 5.9%). The occurrence of some
Although diagnostic primers for each shark species in the
                                                                  scalloped hammerhead fins in the gu pian (great hammer-
shark fin trade (i.e., at least 50 species) are desirable, this
                                                                  head) category most likely resulted from the fact that both
is a large and ongoing task. In the interim, especially in
                                                                  scalloped and great hammerhead fins are similarly light
light of considerable concerns about the status of several
                                                                  in color. Inadvertent introduction of large, light-colored
populations, shark resource management requires cur-
                                                                  scalloped hammerhead fins into the gu pian category and
rent information on the fin trade to assess questions of
                                                                  small, light-colored great hammerhead fins into the chun
sustainable use, and it is therefore necessary to pursue
                                                                  chi category (Table 4) thus affects the traded weight es-
trade studies despite the current taxonomically incom-
                                                                  timates for the various species of hammerheads in both
plete primer library.
                                                                     The least reliable results were those for the dusky shark,
Estimates of Species Proportions in Trade
                                                                  which was estimated to contribute approximately 1.4%
Combining results of the genetic analyses with the                (1.2–1.7%) of the fins in the Hong Kong market. Although
stochastic modeling of trade records allowed the contri-          already low, this figure most likely overestimates this
bution of individual species to the trade to be determined.       species’ proportion in trade because the dusky primer
Shortfin mako fins showed an 85% concordance with the             used does not distinguish between dusky and Galapagos
market category qing lian, which equates to a trade pro-          sharks.
portion for that species of approximately 2.7% (probabil-            Our results indicate that between 34% and 45% (95%
ity interval 2.3–3.1%). The actual percentage is likely to        probability interval), and possibly more ( because of pres-
be somewhat higher, given the presence of shortfin mako           ence in unstudied categories), of the Hong Kong shark fin
fins in the wu yang (silky shark) trade category.                 auction trade is composed of only 14 species (i.e., nine
   The wu gu category contained mostly fins from the              mostly single-species trade categories plus scalloped and
three thresher species (74%), resulting in these species          smooth hammerheads and the three species of thresh-
collectively accounting for approximately 2.3% (2.0–              ers). This finding may reflect the relative abundance of
2.7%) of the shark-fin trade. The actual proportion in trade      these species in global fisheries, preferential demand for
is also likely to be slightly higher given the discovery of       their fins in this market, or a combination of these and
thresher fins, albeit at low frequency, in other categories       other factors. Our results indicate that blue sharks form a
(e.g., ya jian, qing lian, and chun chi) (Table 4). The           particularly large component of the market, a finding con-
longfin mako presented a key nomenclatural issue that             sistent with and potentially resulting from the fact that
affected both the wu gu (thresher) and qing lian (short-          blue sharks form a large proportion of the shark bycatch
fin mako) categories. Discussions with traders suggested          in pelagic longline fisheries targeting tuna and swordfish
that a minority of traders sort longfin mako fins into a          (Nakano & Seki 2003). Although this species is one of
separate category (qing hua); most either combine them                                                        e
                                                                  the most productive shark species (Cort´s 2002), further
with shortfin mako or thresher fins due to similarity of          analyses are needed to determine whether the current
appearance and market value.                                      demand exerted by the shark fin trade on this species is
   Tiger sharks, assumed by traders and authors of pre-           sustainable. Other species comprise approximately 0.1 to
vious studies to be hai hu (Chinese for ocean tiger),             4.4% each of the total trade volume, and, given the range
were instead highly concordant with the ruan sha cate-                                                                e
                                                                  in biological productivity of these species (Cort´s 2002),
gory, which comprised only 0.08 to 0.19% of the trade.            it is expected that some will be better able to withstand
Commonly traded carcharhinid sharks included the blue             the growing demands of the fin trade than others.
(17.3% [15.5%–19.1%]), silky (3.5% [3.1–4.0%]), sandbar
(2.4% [1.9–2.8%]), and bull (2.2% [1.8–2.6%]) sharks. The
                                                                  Present and Future Shark Fin Trade Characterization
presence of fins from these carcharhinid species in other
market categories was noted (Table 4) and would tend to           Available information does not provide a definitive an-
increase these estimates.                                         swer to the question of whether auction records are rep-
   Oceanic whitetip sharks, although circuitously identi-         resentative of the entire global trade. However, the Hong
fied in the genetic testing, are highly distinct and showed       Kong market serves both Hong Kong and mainland China

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                                                                                              Volume 20, No. 1, February 2006
210       Species in Shark Fin Trade                                                                                         Clarke et al.

(Clarke 2004a), and thus includes both high-end and             S. J. Joung and Y. Y. Liao, generously contributed their ex-
budget-conscious consumers with a wide spectrum of              pertise to the study. We thank E. J. Milner-Gulland, M. V.
tastes. Furthermore, Hong Kong auctions represent 20%           Ashley, and two anonymous reviewers for comments on
of all Hong Kong imports (Clarke et al. 2004), and Hong         previous versions of this manuscript.
Kong is thought to handle more than 50% of the global
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                                                                                                                 Volume 20, No. 1, February 2006