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Assessing consumer trends and illegal activity by monitoring the online wildlife trade
Biological Conservation 227 (2018) 219–225
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Assessing consumer trends and illegal activity by monitoring the online wildlife trade
T
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Yik-Hei Sunga,b, , Jonathan J. Fongc a
School of Biological Sciences, The University of Hong Kong, Hong Kong, China Croucher Institute for Environmental Sciences, Partner State Key Laboratory of Environmental and Biological Analysis, Department of Biology, Hong Kong Baptist University, Hong Kong, China c Science Unit, Lingnan University, Tuen Mun, Hong Kong, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: Anthropogenic Allee effect CITES Hybrid Internet Turtle
Wildlife ranks the fourth among illegally traded items. The insatiable market demand for wildlife products directly threatens plants, animals and their natural habitats. Identifying illegal trade and understanding consumer trends is important for the conservation of overexploited species. The internet and social media have emerged as popular platforms for wildlife trade, and surveying these marketplaces is an important tool for conservation. Due to their high demand and high value, we choose turtles as a case study to demonstrate the usefulness of monitoring the online trade. We collected data (species, number and price) on the sale of live turtles from a Hong Kong-based internet forum for 36 months (September 2013–August 2016) to assess the scale of the trade, identify potential illegal trade and investigate factors that influence prices. We recorded 14,360 individuals of 136 species, including 67 threatened species. Of the 77 species sold that are listed in CITES appendices, 36% were likely illegally traded as they had neither possession licenses under Hong Kong law nor CITES import records. Turtles with the highest prices tended to be critically endangered species, wild-caught or those with special morphological forms. Sale of hybrid turtles of 38 “species/varieties” occurred in 4% of all sale posts. Our survey of the online trade in Hong Kong discovered important trends of sale price and consumer preference, collected baseline data for enforcing trade regulations and highlighted likely illegal trade of turtles. We encourage similar studies for other highly traded wildlife to be incorporated into integrative approaches for conservation management.
1. Introduction Illegal wildlife trade, worth up to USD 7–23 billion a year, is one of the most lucrative crimes following trafficking of humans, arms and drugs (Nellemann et al., 2016). The major driver of the illegal wildlife trade market is the demand for food, pets, commodity goods and medicine (Broad et al., 2003; Rosser and Mainka, 2002). This unsustainable overexploitation for human use has been identified as the biggest driver of biodiversity decline (Maxwell et al., 2016), which can synergize to more serious problems of ecosystem malfunction (Nijman, 2010). Wildlife trade is regulated at both international and national levels. The Convention on the International Trade in Endangered Species (CITES) is the international agreement that regulates international trade of approximately 35,800 species of animals and plants, which are listed in one of the three Appendices (I, II and III) (CITES, 2017).
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Different appendices offer different levels of restriction: Appendix I covers globally threatened species affected by trade (e.g. elephants, tigers) and no commercial trade of these species across borders is allowed; Appendix II covers species that are not necessarily threatened by imminent extinction but whose trade is subjected to strict regulation and cross boarder commercial trade requires non-detriment finding and export permit; and Appendix III requires export permits from the listing countries or certificates of origin from the non-listing countries to export. Through national laws, signatory national authorities implement CITES through a system of permits during import and export. National laws controlling the domestic trade of species may strengthen regulation of CITES-listed species after import into a country. Laws and regulations may differ between countries and territories. For example, the practice of “one country, two systems” in mainland China and Hong Kong results in differences in implementation of CITES. In China, endangered species are designated (first class, second class) and protected
Corresponding author at: School of Biological Sciences, The University of Hong Kong, Hong Kong, China. E-mail address: [email protected] (Y.-H. Sung).
https://doi.org/10.1016/j.biocon.2018.09.025 Received 16 May 2018; Received in revised form 22 August 2018; Accepted 19 September 2018 0006-3207/ © 2018 Elsevier Ltd. All rights reserved.
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Dudgeon, 2006; Luiselli et al., 2016; Nijman, 2010). By monitoring a popular Hong Kong-based internet platform for 36 months (September 2013–August 2016), we are able to (1) characterize the online turtle trade (e.g. number of individuals and species, and conservation status of traded species), (2) identify probable illegal trade, (3) identify the factors influencing the sale price and (4) investigate the phenomenon of producing and selling hybrids. We discuss each of these topics in detail, as well as provide recommendations on how to incorporate and improve online surveys for regulating wildlife trade.
under Article 9 of the Wildlife Protection Law of the People's Republic of China. The list of first class and second class species overlaps, but is not identical to CITES appendices. Use of protected species in mainland China is limited to scientific research, domestication, exhibition and special purposes, with the regulating body differing between first class (State Council) and second class species (provincial government). In Hong Kong, a license issued by the government is required to possess wild-caught individuals of species listed on CITES Appendix I and II. Although laws are in place, ineffective implementation of international and national laws (e.g. insufficient border controls, corruption and insufficient domestic trade control) hampers the effectiveness of CITES (Challender et al., 2015). What results is illegal cross-border and domestic trade of CITES-listed species (Nijman, 2010; Nijman and Shepherd, 2007). The internet has emerged as an important platform for wildlife trade (Lavorgna, 2014). Previously, studies on wildlife trade were done by visiting physical markets (Cheung and Dudgeon, 2006; Nijman and Shepherd, 2007; Regueira and Bernard, 2012), but recent studies showed that the internet is increasingly being used for illegal trade of various wildlife, including birds (Alves et al., 2012), mammals (Harrison et al., 2016), and orchids (Hinsley et al., 2015). Given the obscurity of traders online, regulation of wildlife trade on internet platforms is fraught with difficulties (Bennett, 2011). Formulation of measures to halt online wildlife trade is in dire need (Shirey and Lamberti, 2011), which necessitates a comprehensive understanding on the scale of the market (Sajeva et al., 2013), especially for heavily traded and harvested groups of wildlife (Yeo et al., 2017). The demand and price of wildlife may increase with rarity associated with morphology (Lyons and Natusch, 2013), life-history traits (Hinsley et al., 2015), origin (Dutton et al., 2011), and conservation and trade regulation status (Courchamp et al., 2006). Consumers may prefer rare species and pay disproportionally high prices for them, leading to increased hunting efforts (Courchamp et al., 2006). What results is a positive feedback loop—consumers pay disproportionally high prices for rare species, making it worthwhile for a hunter to dedicate more time and effort to find the organism, in turn making the species rarer and more expensive (Courchamp et al., 2006). Understanding the factors influencing consumers' preference in wildlife trade can help to identify measures to reduce demand for and regulate the trade of species of conservation concern (Hinsley et al., 2015). Turtles provide a good case study for understanding the interplay between consumer preferences and the illegal online wildlife trade. There are four main reasons. First, turtles have low species richness (356 species) (Rhodin et al., 2017), making species identification easier compared to other groups [e.g., > 25,000 species of orchids (Chase et al., 2003) and > 3500 species of snakes (Uetz et al., 2017)] and allowing for a better characterization of the trade. Second, turtles are among the most imperiled groups of organisms—over 60% of all species meet the criteria for critically endangered, endangered or vulnerable of the IUCN Red List (Rhodin et al., 2017). Unsustainable harvest of turtles for traditional medicine, food and pets is the primary threat responsible for plummeting turtle populations (Buhlmann et al., 2009; Cheung and Dudgeon, 2006; van Dijk, 2000). Third, the volume and diversity of turtles traded are high (Cheung and Dudgeon, 2006; Nijman and Shepherd, 2014), due to the high value and ease of transport. For example, a juvenile golden coin turtle (Cuora trifasciata) that is approximately 500 g is hearty enough to survive long-distance travel, can be easily smuggled and fetch over USD 5000. Lastly, the turtle trade exemplifies an important issue that needs to be understood about wildlife trade—sale of hybrids. For turtles, hybrids are intentionally produced and sold in the trade, leading to complications of species identification for trade regulations and formulating conservation efforts (Dalton, 2003; Parham et al., 2001; Stuart and Parham, 2006). To demonstrate the usefulness of monitoring the online wildlife trade for conservation management, we study the online trade of turtles in Hong Kong, a major hub for international wildlife trade (Cheung and
2. Materials & methods 2.1. Study platform Due to the possibility of cross-posting on different platforms and manpower constraints, we monitored a single wildlife trading platform in Hong Kong. To identify the most active platform, we compared the number of posts selling turtles as pets on three internet platforms for three months. Two of these platforms were forums (one selling all animals and the other specializing on turtles) and one platform was a group on social media (specializing on turtles). The forum specializing on turtles had the highest number of posts, so we focused on this forum. On the forum, members connect and discuss a variety of topics about turtles, including husbandry and trade. The forum is accessible to the public, but only members can post. Due to ethical considerations, we do not disclose the specifics of the forum (name, site address) following the practices of similar studies (Hinsley et al., 2016; Sajeva et al., 2013). 2.2. Sampling We collected data (date of post, species identity, number of individuals sold and price) from all posts that live turtles were sold between September 2013 and August 2016. Species identity was based on the scientific or common name listed in the post. For hybrids, the identity of the parental species was also based on scientific or common name. Photos could not be used for validation of species identity because not all posts included pictures. It is possible that posts (mistakenly or purposefully) misidentified species, but a preliminary crosscheck of a subset of posts did not find any misidentifications. It is possible for members to use multiple user names, but we were unable to account for this in our data collection. Data from September 2013 to December 2015 were collected at a single time as an archive of past posts, while data from January 2016 to August 2016 were collected biweekly. We standardized species names by following the taxonomy in Rhodin et al. (2017). To ensure consistency and minimize overestimates, we enacted two rules when collecting data. First, we assumed one turtle for sale if the number of individuals was not listed. Second, to avoid repeatedly recording the sale of the same individual or batch of turtles, we excluded posts by a member selling the same species in the same month. We identified potential illegal trade in two ways. First, we compared forum data to official import records into Hong Kong between 2007 and 2016 in the CITES trade database (CITES, 2017), following the CITES listings as of August 2016 (CoP16). These import records were retrieved in March 2018 to avoid missing records because of delay in data submission to CITES. Although our online surveys began in 2013, we included older import records to be conservative in identifying illegal trade, as turtles are long-lived animals that can be sold several years after import. Species being sold in Hong Kong but absent from CITES import records were regarded as likely being imported to Hong Kong illegally. Second, under a law in Hong Kong, Protection of Endangered Species of Animals and Plants Ordinance (CAP.586), a possession license is required for the possession and sale of all live turtles included in CITES Appendix I, and wild-caught individuals in Appendix II. We obtained a species list for which possession licenses had been issued by the enforcement authority (Agriculture, Fisheries and Conservation 220
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Department, Hong Kong Government) in September 2017. All Appendix I and wild Appendix II listed species sold on the forum and absent from possession license list were regarded as being traded illegally. We also included the four native CITES-listed species in Hong Kong, which collection is prohibited in Hong Kong (Beal's-eyed turtle [Sacalia bealei], big-headed turtle [Platysternon megacephalum], golden coin turtle [C. trifasciata] and Reeve's terrapin [Mauremys reevesii]). 2.3. Analysis of price We used general linear mixed models to determine the factors influencing the (log-transformed) prices of turtles, using package lme4 in software R (Wood and Scheipl, 2013). In the analysis, we excluded posts without price and selected species with over 10 posts to avoid spurious price listing. For predictor variables in the full model, we included maximum carapace length (Bonin et al., 2006), IUCN status (Critically Endangered [CR], Endangered [EN], Vulnerable [VU], Near Threatened [NT], Least Concern [LC] and Not Evaluated [NE]) (IUCN, 2017), listing of CITIES (Appendix I, II, III and not listed) (CITES, 2017), source (captive bred, wild caught and not listed), morphological forms (normal [not specified] or special), number of individual of the species for sale (availability of the species), distribution range size (Buhlmann et al., 2009) and year. To determine the differences in turtle prices over time, we divided the data collected into three 12-month periods: 2013–2014 (September 2013–August 2014), 2014–2015 (September 2014–August 2015), and 2015–2016 (September 2015–August 2016). We included month and species as random factors to account for variations related to season and consumer preference for other species-specific characteristics (e.g. morphology) that could not be included in this study, respectively. We did not include age of turtles sold because this information was missing in most of the posts. We applied the dredge function in the MuMIn package in software R to identify the best subset of predictor variables and determine the best model based on Akaike's Information Criterion values (Barton, 2011; Burnham and Anderson, 2002). We regarded models for which the delta AIC values within two units of the best models to have similar support. We averaged the estimates from the best supporting models to calculate final estimates and standard errors for predictor variables. We used Chisquare statistics to test for the significant differences between categorical variables (Bolker et al., 2009); the reference categories used were critically endangered of IUCN status, Appendix I of CITES, captive bred turtles, normal morphological form and 2013–2014.
Fig. 1. Total number of species and IUCN Red list status of turtle species from different geographical regions sold on an internet forum between September 2013 and August 2016 in Hong Kong. Abbreviation: EN = endangered; VU = vulnerable; NT = near threatened; LC = least concern; NE = not evaluated and, DD = data deficient. Grey bars indicate the proportion of turtle species that are listed in threatened categories (CR, EN or VU).
the most expensive and were significantly more expensive than turtles listed as EN, NT and LC (Fig. 3). Wild-caught and individuals with special morphology were also significantly more expensive while prices of turtles were the lowest in 2013–2014. Over 4% (388) of total posts sold hybrids. Based on the self-identification of parental species by the seller, we recorded 38 different species combinations, of which 27 were offspring of pure species (F1) and 11 were offspring of hybrids (F2 or beyond). Seven hybrid individuals were more expensive than both parent species (Fig. 4). 4. Discussion In this study we use turtles as a case study to highlight the utility and importance of monitoring the online wildlife trade. From surveying a single online trading platform in Hong Kong, we collected baseline data to characterize the scale and scope of the turtle trade, identified likely illegal international trade and ascertained factors influencing sale price and consumer preference. We discuss each of these findings in detail, as well as provide recommendations on how to incorporate and improve online surveys for regulating wildlife trade of other taxa.
3. Results We collected data from 9058 posts in the 36-month period. In these posts, 14,360 live turtles of 136 species were advertised for sale. The number of individuals and species sold fluctuated over time, but there was no obvious temporal pattern (Fig. A1). Among the species sold, 67 (49%) were listed in IUCN threatened categories (CR = 24; EN = 23; and VU = 20). Geographically, most traded species originated from Asia (46 species; 34%) and North America (35 species; 26%; Fig. 1). Species in IUCN threatened categories (CR, EN, VU) were most common from Asia (84.8% 39/46 species) and Africa (58.3%, 7/12 species). Among the 136 species recorded, 77 were listed in CITES Appendices (Appendix I = 9; Appendix II = 58; and Appendix III = 10; Fig. 2). Twenty-eight species were likely to be illegally traded since they were absent from CITES import records (2007–2016) and/or the Hong Kong possession license species list (Fig. 2; Table A1). The price of individual turtles ranged from USD 1–50,800 (HKD 8–400,000; HKD 1 = USD 0.127). The total value of the posts examined was USD 5,740,986. The best model (R2m = 0.29; R2c = 0.75) that explain price variation included the IUCN status (χ2 = 42.35; P < 0.001), source (χ2 = 72.28; P < 0.001), morphological form (χ2 = 971.29; P < 0.001) and year (χ2 = 263.27; P < 0.001; Table A2 and A3). Comparing the categories of IUCN status, CR turtles were
4.1. Characterization of online turtle trade Our 3-year study found that over ⅓ (136 of 356) of all turtle species were present, including 24 CR species, in the trade. The species diversity found online was comparable to the survey of physical stores in Hong Kong between 2000 and 2003, which recorded 155 species (Cheung and Dudgeon, 2006). In this study, disproportionally high percentages (> 75%) of the traded species originated from Asia and Africa were threatened species (Fig. 1). This corroborates a number of studies finding a significant scale of illegal wildlife trade in these regions (Natusch and Lyons, 2012; Nijman, 2010). For trade volume, we recorded 14,360 live turtles, which represents approximately 0.1% of the global CITES-listed reptile trade in the same time frame (average 11.4 million whole organism equivalents; Harfoot et al., 2018). We consider the relative value of this percentage large, as the CITES data represents global trade of all reptiles (including live specimens and skins), while our data merely represents live turtle trade from a single online platform from one city (Hong Kong). Another online wildlife trade study focusing on animals found that turtles and tortoises represented approximately 45% of all specimens identified (Hastie, 2018). These numbers highlight the immense scale of the turtle trade 221
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Fig. 2. Proportion of CITES-listed and non CITES-listed species (A), and proportion of illegally traded species (CITES-listed species without import records in the CITES trade database and/or records possession license species list under a law in Hong Kong (Protection of Endangered Species of Animals and Plants Ordinance [CAP.586])) (B) among turtle species sold on an internet forum between September 2013 and August 2016 in Hong Kong.
Fig. 3. Estimates in the generalized linear mixed models for price of turtles sold on a Hong Kong internet forum between September 2013 and August 2016. Abbreviations: CR = critically endangered; EN = endangered; VU = vulnerable; NT = near threatened; LC = least concern; NE = not evaluated and, DD = data deficient. Critically endangered, captive-bred, normal morphological form and 2013–2014 were set as reference categories and shown as 0.
CITES Appendix II-listed species sourced from captive stocks are exempt from the requirement of a possession license in Hong Kong. In our study, we found that several species sold on the forum were listed as wild-caught, but were absent from the Hong Kong possession license species list: African spurred tortoise (Centrochelys sulcata), eastern box turtle (Terrapene carolina), golden coin turtle (C. trifasciata), keeled box turtle (Cuora mouhotii) and Vietnamese pond turtle (Mauremys annamensis). As there are currently no reliable methods of differentiating the source of an individual, this presents an opportunity to falsely declare wild-caught individuals as captive-bred. This phenomenon has already been documented in the European Union (Auliya et al., 2016) and mainland China (Shi et al., 2007; Shi et al., 2008). So, are these individuals sold online wild-caught or captive-bred? Both situations present violation of Hong Kong law: if individuals are wild-caught, the owners are in violation of Hong Kong possession law, while if captivebred, the owner is fraudulently selling the turtle as wild-caught (likely for a higher price). In the second case, sellers may be persecuted in
(Nijman and Shepherd, 2014). 4.2. Use of online market surveys to reveal illegal trade Surveying online markets can provide an estimate of the illegal wildlife trade—36% (28 of 77) of CITES-listed turtle species sold on the internet were not listed in CITES import records or the Hong Kong species list of possession licenses, flagging them as being traded illegally. Of these potentially illegal species, 82% are classified with IUCN threatened status (CR, EN, VU), including a few range-restricted species distributed on islands, such as Ryukyu black-breasted leaf turtle (Geoemyda japonica), Palawan forest turtle (Siebenrockiella leytensis) and ploughshare tortoise (Astrochelys yniphora). Because of the high value, it is likely that these species are being sold as pets rather than food. Illegal harvesting and trade for the pet markets continue to pose threats to the remnant populations of these critically endangered species (Auliya et al., 2016). 222
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Nogueira-Filho, 2011). However, the consumer preference for wildcaught individuals may indemnify the effectiveness of this approach. This preference for wild products has also been reported for other wildlife products, such as bear bile (Dutton et al., 2011). Consumers, oftentimes the owners of turtle farms (Shi et al., 2007), may prefer wildcaught individuals due to perceived benefits of higher fertility, special morphological forms and unique genetic make-up. A prime example of the difference between wild-caught and captive-bred individuals can be seen with the golden coin turtle. Although a high number of captivebred turtles from China are produced (> 40,000 individuals in 2002) (Shi et al., 2008; Sigouin et al., 2016), the high price of wild-caught specimens recorded in this study (mean = USD 10,429) was 77% higher than other individuals (mean = USD 5903). The higher prices of rare and wild-caught turtles exemplify anthropogenic Allee effect—rarity increases the price of an item, the disproportionally high prices provide incentives for persistent harvesting of the already depleted wild populations (Courchamp et al., 2006). This positive-feedback loop is dangerous and if not addressed will contribute to the extinction of turtle species worldwide.
Fig. 4. Average prices of hybrid turtles and the respective parent species sold on an internet forum between September 2013 and August 2016 in Hong Kong. Hybrids with an average price higher than both parent species are indicated in red. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
4.4. Demand for special morphology Hong Kong under the Trade Descriptions Ordinance, CAP. 362, a local law enacted in 2013, which prohibits false trade description. The key for this problem is to develop methods to differentiate the source of an individual. Stable isotope analysis has been used to identify the source of frogs in the trade (Dittrich et al., 2017), and effort should be made to applying this technique to turtles and other wildlife products. The availability of CITES-listed turtles online shows that illegal trade is occurring in plain view, and is strong evidence that trade regulations in their current form are ineffective. The import of wildlife into Hong Kong is not well regulated, which accords with studies on the trade of other wildlife, such as shark fin (Shea and To, 2017) and snakes (Zhou and Jiang, 2004). With the blooming demand for wildlife and their products in China, Hong Kong's close proximity to China makes it an important transit point for international smuggling of wildlife into China. This is exemplified by regular seizure cases between Hong Kong and China (ADM Capital Foundation, 2015). Popular ports such as Hong Kong must find ways to broaden their arsenal to detect wildlife smuggling and enforce anti-smuggling laws, such as increasing inspections at ports (Phelps et al., 2010), use of scent detector dogs (Beebe et al., 2016) and use of conservation forensics to differentiate wild-caught individuals from captive-bred individuals (Natusch et al., 2017).
Turtles, pure species or hybrids, with special morphology were highly priced. Turtle keepers may prefer rare or strange forms, similar to the preference of “designer” green pythons (individuals that display abnormal color) (Lyons and Natusch, 2013). Most “designer” turtles recorded in this study were albino—the most expensive individual recorded in this study was an albino common snapping turtle (Chelydra serpentina) adult, which was offered for USD 50,800. Wild individuals or populations with special color forms may be targeted for producing “designer” turtles. Hybrid turtles represented a small proportion (4%) of the trade, yet some were highly priced. Hybrid turtles may be attractive to hobbyists because of the high variability and uniqueness of morphology, as “designer” turtles. Hybrids of the Indochinese box turtle (Cuora galbinifrons) and keeled box turtle (Cuora mouhoutii) were over nine times more expensive than the price of their parent species (Fig. 4). Production of hybrids (F2 or beyond) does not lead to elimination of turtles from the wild, however, increasing popularity of hybrid turtles in the market may render trade regulation more difficult. Under CITES, the trade of hybrids is regulated if either of the parents is listed in the Appendices and the more restrictive Appendix applies if parents are listed in different Appendices. It has been challenging for enforcement personnel to identify pure species (Natusch and Lyons, 2012), let alone hybrids. From our data, we recorded hybrids of generation F3 or beyond with four species listed—morphological species identification is extremely difficult for these individuals. Molecular approaches may be needed to identify hybrid individuals and their parent species for trade regulation (Fong and Chen, 2010; Stuart and Parham, 2006).
4.3. Consumer preference for wild and rare turtles Consumer preference is a major driver of the wildlife market, and sale price may help us understand this preference. We found that the price of turtles increased with rarity associated with IUCN status. This phenomenon was also seen in the markets for orchids and snakes (Hinsley et al., 2015; Lyons and Natusch, 2013). Notably, the five most expensive turtle species were all critically endangered species belonging to the Asian box turtle genus Cuora: Zhou's box turtle (C. zhoui; mean = USD 38,461), Pan's box turtles (C. pani; mean = USD 20,940), yellow-headed box turtle (C. aurocapitata; mean = USD 19,872), McCord's box turtle (C. mccordi; mean = USD 16,667) and golden coin turtle (mean = USD 6418). This underscores the enormous demand of Asian box turtles in the pet market (Auliya et al., 2016). The legal wildlife trade has seen a shift from predominantly wildsourced to more captive-sourced products for most taxonomic groups, particularly in reptiles (Harfoot et al., 2018). Captive breeding has been successful for some endangered turtle species, such as the golden coin turtle (Shi et al., 2008; Sigouin et al., 2016). Captive-bred turtles have been suggested as a potential source to satisfy the demand in the turtle trade and relieve the pressure on wild populations (Nogueira and
4.5. Temporal trends in turtle prices We found that the price of turtles changed significantly over time, showing a peak in 2014–2015. Temporal changes in market prices are of conservation significance because it may suggest a change in supply and demand of turtles. For the supply side, increase in prices may reveal depleted wild populations (Harris et al., 2015) or reduced productivity in turtle farms. For the demand side, under the influence of the socioeconomic aspects of the trade, turtle hobbyists may have wanted to acquire more turtles. In addition, a shift in consumer preference, favoring more-expensive species/morphological forms, may have occurred (Lyons and Natusch, 2013). Such change in prices over relatively short period of time highlights the dynamic nature of turtle trade—we call for studies to collect longer-term data on prices, information on wild populations and consumer preferences, in order to refine our understanding of factors that influence the turtle trade. 223
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5. Conclusions
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The internet has emerged as a popular platform for wildlife trade, imposing additional challenges to wildlife trade regulation. We demonstrate that systematic surveys of online markets are important tools to understand consumer preference and reveal potential illegal trade. Continued monitoring has the potential to uncover other trends, such as shifts in consumer preference and market reactions to special events (e.g., new legislation, uplisting of species on endangered lists), and we see our study as a baseline data for these future comparisons. This in turn allows us to evaluate the effectiveness of wildlife trade regulation at both international and national levels. For turtles, we found that over a third of the trade species among the CITES-listed species being sold were likely traded, highlighting that the current interventions are ineffective at controlling the illegal trade of endangered turtles. We believe that similar online trade surveys of other wildlife should be done to enhance our understanding of the illegal wildlife trade markets and facilitate stronger trade enforcement. Surveys of the online wildlife trade are not a panacea, but rather another tool to aid conservation management. We believe an integrative approach (Sigouin et al., 2016), including systematic market surveys, enhanced regulation of trade and public education on the effect of trade on wild population for hobbyists, must be in place along the trade chain to halt the illegal and unsustainable wildlife trade before the highly sought-after species become extinct in the wild, for turtles as well as other prized wildlife taxa. Acknowledgements This work was supported by Ocean Park Conservation Foundation, Hong Kong. We would like to thank Agriculture, Fisheries and Conservation Department, Hong Kong Government for providing information on the trade. We are grateful to Ken Lee, Eric Ng, Franco Leung, Anthony Ki, Tom Li, Charlotte Chan, Fa Cheung, Lag Wan, Agnes Chan, Cherry Ho, Cecilia Wong for assistance with data collection. We thank Anthony Lau for his comments on the manuscript. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.biocon.2018.09.025. References ADM Capital Foundation, 2015. Wildlife crime: is Hong Kong doing enough? (available at). http://admcf.org/wp-content/uploads/2016/12/1-Resource-b-Wildlife-Crime-IsHong-Kong-Doing-Enough-Report-English-version-December-2015.pdf, Accessed date: 12 October 2017. Alves, R., Lima, J., Araujo, H., 2012. The live bird trade in Brazil and its conservation implications: an overview. Bird Conserv. Int. 23, 53–65. Auliya, M., Altherr, S., Ariano-Sanchez, D., Baard, E.H., Brown, C., Brown, R.M., Cantu, J.-C., Gentile, G., Gildenhuys, P., Henningheim, E., Hintzmann, J., Kanari, K., Krvavac, M., Lettink, M., Lippert, J., Luiselli, L., Nilson, G., Nguyen, T.Q., Nijman, V., Parham, J.F., Pasachnik, S.A., Pedrono, M., Rauhaus, A., Córdova, D.R., Sanchez, M.E., Schepp, U., van Schingen, M., Schneeweiss, N., Segniagbeto, G.H., Somaweera, R., Sy, E.Y., Türkozan, O., Vinke, S., Vinke, T., Vyas, R., Williamson, S., Ziegler, T., 2016. Trade in live reptiles, its impact on wild populations, and the role of the European market. Biol. Conserv. 204, 103–119. Barton, K., 2011. MuMIn: multi-model inference (R package version 1.0. 0, available at). http://CRAN.R-project.org/package/MuMIn/, Accessed date: 20 August 2016. Beebe, S.C., Howell, T.J., Bennett, P.C., 2016. Using scent detection dogs in conservation settings: a review of scientific literature regarding their selection. Front. Vet. Sci. 3, 96. Bennett, E.L., 2011. Another inconvenient truth: the failure of enforcement systems to save charismatic species. Oryx 45, 476–479. Bolker, B.M., Brooks, M.E., Clark, C.J., Geange, S.W., Poulsen, J.R., Stevens, M.H.H., White, J.-S.S., 2009. Generalized linear mixed models: a practical guide for ecology and evolution. Trends Ecol. Evol. 24, 127–135. Bonin, F., Devaux, B., Dupre, A., 2006. Turtles of the World, first edn. Johns Hopkins University Press, Baltimore, Maryland, USA. Broad, S., Mulliken, T., Roe, D., 2003. The nature and extent of legal and illegal trade in wildlife. In: Oldfield, S. (Ed.), The Trade in Wildlife: Regulation for Conservation.
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Stuart, B.L., Parham, J.F., 2006. Recent hybrid origin of three rare Chinese turtles. Conserv. Genet. 8, 169–175. Uetz, P., Hošek, J., Hallermann, J., 2017. The reptile database (available at). http://www. reptile-database.org, Accessed date: 5 November 2018. van Dijk, P.P., 2000. The status of turtles in Asia. In: van Dijk, P.P., Stuart, B.L., Rhodin, A.G.J. (Eds.), Asian Turtle Trade: Proceedings of a Workshop on Conservation and Trade of Freshwater Turtles and Tortoises in Asia. MTC Printing, Lunenburg, Massachusetts, USA, pp. 15–23. Wood, S., Scheipl, F., 2013. gamm4: generalized additive mixed models using mgcv and lme4 (available at). https://cran.r-project.org/web/packages/gamm4/index.html, Accessed date: 6 December 2017. Yeo, L.M., McCrea, R.S., Roberts, D.L., 2017. A novel application of mark-recapture to examine behaviour associated with the online trade in elephant ivory. PeerJ 5, e3048. Zhou, Z., Jiang, Z., 2004. International trade status and crisis for snake species in China. Conserv. Biol. 18, 1386–1394.
Turtle Conservancy, Lunenburg, Massachusetts, USA. Rosser, A.M., Mainka, S.A., 2002. Overexploitation and species extinctions. Conserv. Biol. 16, 584–586. Sajeva, M., Augugliaro, C., Smith, M.J., Oddo, E., 2013. Regulating internet trade in CITES species. Conserv. Biol. 27, 429–430. Shea, K.H., To, A.W.L., 2017. From boat to bowl: patterns and dynamics of shark fin trade in Hong Kong ― implications for monitoring and management. Mar. Policy 81, 330–339. Shi, H.T., Parham, J.F., Lau, M., Chen, T.H., 2007. Farming endangered turtles to extinction in China. Conserv. Biol. 21, 5–6. Shi, H., Parham, J.F., Zhiyong, F., Meiling, H., Feng, Y., 2008. Evidence for the massive scale of turtle farming in China. Oryx 42, 147–150. Shirey, P.D., Lamberti, G.A., 2011. Regulate trade in rare plants. Nature 469, 457–465. Sigouin, A., Pinedo-Vasquez, M., Nasi, R., Poole, C., Horne, B., Lee, T.M., Durant, S., 2016. Priorities for the trade of less charismatic freshwater turtle and tortoise species. J. Appl. Ecol. 54, 345–350.
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Contents lists available at ScienceDirect
Biological Conservation journal homepage: www.elsevier.com/locate/biocon
Assessing consumer trends and illegal activity by monitoring the online wildlife trade
T
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Yik-Hei Sunga,b, , Jonathan J. Fongc a
School of Biological Sciences, The University of Hong Kong, Hong Kong, China Croucher Institute for Environmental Sciences, Partner State Key Laboratory of Environmental and Biological Analysis, Department of Biology, Hong Kong Baptist University, Hong Kong, China c Science Unit, Lingnan University, Tuen Mun, Hong Kong, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: Anthropogenic Allee effect CITES Hybrid Internet Turtle
Wildlife ranks the fourth among illegally traded items. The insatiable market demand for wildlife products directly threatens plants, animals and their natural habitats. Identifying illegal trade and understanding consumer trends is important for the conservation of overexploited species. The internet and social media have emerged as popular platforms for wildlife trade, and surveying these marketplaces is an important tool for conservation. Due to their high demand and high value, we choose turtles as a case study to demonstrate the usefulness of monitoring the online trade. We collected data (species, number and price) on the sale of live turtles from a Hong Kong-based internet forum for 36 months (September 2013–August 2016) to assess the scale of the trade, identify potential illegal trade and investigate factors that influence prices. We recorded 14,360 individuals of 136 species, including 67 threatened species. Of the 77 species sold that are listed in CITES appendices, 36% were likely illegally traded as they had neither possession licenses under Hong Kong law nor CITES import records. Turtles with the highest prices tended to be critically endangered species, wild-caught or those with special morphological forms. Sale of hybrid turtles of 38 “species/varieties” occurred in 4% of all sale posts. Our survey of the online trade in Hong Kong discovered important trends of sale price and consumer preference, collected baseline data for enforcing trade regulations and highlighted likely illegal trade of turtles. We encourage similar studies for other highly traded wildlife to be incorporated into integrative approaches for conservation management.
1. Introduction Illegal wildlife trade, worth up to USD 7–23 billion a year, is one of the most lucrative crimes following trafficking of humans, arms and drugs (Nellemann et al., 2016). The major driver of the illegal wildlife trade market is the demand for food, pets, commodity goods and medicine (Broad et al., 2003; Rosser and Mainka, 2002). This unsustainable overexploitation for human use has been identified as the biggest driver of biodiversity decline (Maxwell et al., 2016), which can synergize to more serious problems of ecosystem malfunction (Nijman, 2010). Wildlife trade is regulated at both international and national levels. The Convention on the International Trade in Endangered Species (CITES) is the international agreement that regulates international trade of approximately 35,800 species of animals and plants, which are listed in one of the three Appendices (I, II and III) (CITES, 2017).
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Different appendices offer different levels of restriction: Appendix I covers globally threatened species affected by trade (e.g. elephants, tigers) and no commercial trade of these species across borders is allowed; Appendix II covers species that are not necessarily threatened by imminent extinction but whose trade is subjected to strict regulation and cross boarder commercial trade requires non-detriment finding and export permit; and Appendix III requires export permits from the listing countries or certificates of origin from the non-listing countries to export. Through national laws, signatory national authorities implement CITES through a system of permits during import and export. National laws controlling the domestic trade of species may strengthen regulation of CITES-listed species after import into a country. Laws and regulations may differ between countries and territories. For example, the practice of “one country, two systems” in mainland China and Hong Kong results in differences in implementation of CITES. In China, endangered species are designated (first class, second class) and protected
Corresponding author at: School of Biological Sciences, The University of Hong Kong, Hong Kong, China. E-mail address: [email protected] (Y.-H. Sung).
https://doi.org/10.1016/j.biocon.2018.09.025 Received 16 May 2018; Received in revised form 22 August 2018; Accepted 19 September 2018 0006-3207/ © 2018 Elsevier Ltd. All rights reserved.
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Dudgeon, 2006; Luiselli et al., 2016; Nijman, 2010). By monitoring a popular Hong Kong-based internet platform for 36 months (September 2013–August 2016), we are able to (1) characterize the online turtle trade (e.g. number of individuals and species, and conservation status of traded species), (2) identify probable illegal trade, (3) identify the factors influencing the sale price and (4) investigate the phenomenon of producing and selling hybrids. We discuss each of these topics in detail, as well as provide recommendations on how to incorporate and improve online surveys for regulating wildlife trade.
under Article 9 of the Wildlife Protection Law of the People's Republic of China. The list of first class and second class species overlaps, but is not identical to CITES appendices. Use of protected species in mainland China is limited to scientific research, domestication, exhibition and special purposes, with the regulating body differing between first class (State Council) and second class species (provincial government). In Hong Kong, a license issued by the government is required to possess wild-caught individuals of species listed on CITES Appendix I and II. Although laws are in place, ineffective implementation of international and national laws (e.g. insufficient border controls, corruption and insufficient domestic trade control) hampers the effectiveness of CITES (Challender et al., 2015). What results is illegal cross-border and domestic trade of CITES-listed species (Nijman, 2010; Nijman and Shepherd, 2007). The internet has emerged as an important platform for wildlife trade (Lavorgna, 2014). Previously, studies on wildlife trade were done by visiting physical markets (Cheung and Dudgeon, 2006; Nijman and Shepherd, 2007; Regueira and Bernard, 2012), but recent studies showed that the internet is increasingly being used for illegal trade of various wildlife, including birds (Alves et al., 2012), mammals (Harrison et al., 2016), and orchids (Hinsley et al., 2015). Given the obscurity of traders online, regulation of wildlife trade on internet platforms is fraught with difficulties (Bennett, 2011). Formulation of measures to halt online wildlife trade is in dire need (Shirey and Lamberti, 2011), which necessitates a comprehensive understanding on the scale of the market (Sajeva et al., 2013), especially for heavily traded and harvested groups of wildlife (Yeo et al., 2017). The demand and price of wildlife may increase with rarity associated with morphology (Lyons and Natusch, 2013), life-history traits (Hinsley et al., 2015), origin (Dutton et al., 2011), and conservation and trade regulation status (Courchamp et al., 2006). Consumers may prefer rare species and pay disproportionally high prices for them, leading to increased hunting efforts (Courchamp et al., 2006). What results is a positive feedback loop—consumers pay disproportionally high prices for rare species, making it worthwhile for a hunter to dedicate more time and effort to find the organism, in turn making the species rarer and more expensive (Courchamp et al., 2006). Understanding the factors influencing consumers' preference in wildlife trade can help to identify measures to reduce demand for and regulate the trade of species of conservation concern (Hinsley et al., 2015). Turtles provide a good case study for understanding the interplay between consumer preferences and the illegal online wildlife trade. There are four main reasons. First, turtles have low species richness (356 species) (Rhodin et al., 2017), making species identification easier compared to other groups [e.g., > 25,000 species of orchids (Chase et al., 2003) and > 3500 species of snakes (Uetz et al., 2017)] and allowing for a better characterization of the trade. Second, turtles are among the most imperiled groups of organisms—over 60% of all species meet the criteria for critically endangered, endangered or vulnerable of the IUCN Red List (Rhodin et al., 2017). Unsustainable harvest of turtles for traditional medicine, food and pets is the primary threat responsible for plummeting turtle populations (Buhlmann et al., 2009; Cheung and Dudgeon, 2006; van Dijk, 2000). Third, the volume and diversity of turtles traded are high (Cheung and Dudgeon, 2006; Nijman and Shepherd, 2014), due to the high value and ease of transport. For example, a juvenile golden coin turtle (Cuora trifasciata) that is approximately 500 g is hearty enough to survive long-distance travel, can be easily smuggled and fetch over USD 5000. Lastly, the turtle trade exemplifies an important issue that needs to be understood about wildlife trade—sale of hybrids. For turtles, hybrids are intentionally produced and sold in the trade, leading to complications of species identification for trade regulations and formulating conservation efforts (Dalton, 2003; Parham et al., 2001; Stuart and Parham, 2006). To demonstrate the usefulness of monitoring the online wildlife trade for conservation management, we study the online trade of turtles in Hong Kong, a major hub for international wildlife trade (Cheung and
2. Materials & methods 2.1. Study platform Due to the possibility of cross-posting on different platforms and manpower constraints, we monitored a single wildlife trading platform in Hong Kong. To identify the most active platform, we compared the number of posts selling turtles as pets on three internet platforms for three months. Two of these platforms were forums (one selling all animals and the other specializing on turtles) and one platform was a group on social media (specializing on turtles). The forum specializing on turtles had the highest number of posts, so we focused on this forum. On the forum, members connect and discuss a variety of topics about turtles, including husbandry and trade. The forum is accessible to the public, but only members can post. Due to ethical considerations, we do not disclose the specifics of the forum (name, site address) following the practices of similar studies (Hinsley et al., 2016; Sajeva et al., 2013). 2.2. Sampling We collected data (date of post, species identity, number of individuals sold and price) from all posts that live turtles were sold between September 2013 and August 2016. Species identity was based on the scientific or common name listed in the post. For hybrids, the identity of the parental species was also based on scientific or common name. Photos could not be used for validation of species identity because not all posts included pictures. It is possible that posts (mistakenly or purposefully) misidentified species, but a preliminary crosscheck of a subset of posts did not find any misidentifications. It is possible for members to use multiple user names, but we were unable to account for this in our data collection. Data from September 2013 to December 2015 were collected at a single time as an archive of past posts, while data from January 2016 to August 2016 were collected biweekly. We standardized species names by following the taxonomy in Rhodin et al. (2017). To ensure consistency and minimize overestimates, we enacted two rules when collecting data. First, we assumed one turtle for sale if the number of individuals was not listed. Second, to avoid repeatedly recording the sale of the same individual or batch of turtles, we excluded posts by a member selling the same species in the same month. We identified potential illegal trade in two ways. First, we compared forum data to official import records into Hong Kong between 2007 and 2016 in the CITES trade database (CITES, 2017), following the CITES listings as of August 2016 (CoP16). These import records were retrieved in March 2018 to avoid missing records because of delay in data submission to CITES. Although our online surveys began in 2013, we included older import records to be conservative in identifying illegal trade, as turtles are long-lived animals that can be sold several years after import. Species being sold in Hong Kong but absent from CITES import records were regarded as likely being imported to Hong Kong illegally. Second, under a law in Hong Kong, Protection of Endangered Species of Animals and Plants Ordinance (CAP.586), a possession license is required for the possession and sale of all live turtles included in CITES Appendix I, and wild-caught individuals in Appendix II. We obtained a species list for which possession licenses had been issued by the enforcement authority (Agriculture, Fisheries and Conservation 220
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Department, Hong Kong Government) in September 2017. All Appendix I and wild Appendix II listed species sold on the forum and absent from possession license list were regarded as being traded illegally. We also included the four native CITES-listed species in Hong Kong, which collection is prohibited in Hong Kong (Beal's-eyed turtle [Sacalia bealei], big-headed turtle [Platysternon megacephalum], golden coin turtle [C. trifasciata] and Reeve's terrapin [Mauremys reevesii]). 2.3. Analysis of price We used general linear mixed models to determine the factors influencing the (log-transformed) prices of turtles, using package lme4 in software R (Wood and Scheipl, 2013). In the analysis, we excluded posts without price and selected species with over 10 posts to avoid spurious price listing. For predictor variables in the full model, we included maximum carapace length (Bonin et al., 2006), IUCN status (Critically Endangered [CR], Endangered [EN], Vulnerable [VU], Near Threatened [NT], Least Concern [LC] and Not Evaluated [NE]) (IUCN, 2017), listing of CITIES (Appendix I, II, III and not listed) (CITES, 2017), source (captive bred, wild caught and not listed), morphological forms (normal [not specified] or special), number of individual of the species for sale (availability of the species), distribution range size (Buhlmann et al., 2009) and year. To determine the differences in turtle prices over time, we divided the data collected into three 12-month periods: 2013–2014 (September 2013–August 2014), 2014–2015 (September 2014–August 2015), and 2015–2016 (September 2015–August 2016). We included month and species as random factors to account for variations related to season and consumer preference for other species-specific characteristics (e.g. morphology) that could not be included in this study, respectively. We did not include age of turtles sold because this information was missing in most of the posts. We applied the dredge function in the MuMIn package in software R to identify the best subset of predictor variables and determine the best model based on Akaike's Information Criterion values (Barton, 2011; Burnham and Anderson, 2002). We regarded models for which the delta AIC values within two units of the best models to have similar support. We averaged the estimates from the best supporting models to calculate final estimates and standard errors for predictor variables. We used Chisquare statistics to test for the significant differences between categorical variables (Bolker et al., 2009); the reference categories used were critically endangered of IUCN status, Appendix I of CITES, captive bred turtles, normal morphological form and 2013–2014.
Fig. 1. Total number of species and IUCN Red list status of turtle species from different geographical regions sold on an internet forum between September 2013 and August 2016 in Hong Kong. Abbreviation: EN = endangered; VU = vulnerable; NT = near threatened; LC = least concern; NE = not evaluated and, DD = data deficient. Grey bars indicate the proportion of turtle species that are listed in threatened categories (CR, EN or VU).
the most expensive and were significantly more expensive than turtles listed as EN, NT and LC (Fig. 3). Wild-caught and individuals with special morphology were also significantly more expensive while prices of turtles were the lowest in 2013–2014. Over 4% (388) of total posts sold hybrids. Based on the self-identification of parental species by the seller, we recorded 38 different species combinations, of which 27 were offspring of pure species (F1) and 11 were offspring of hybrids (F2 or beyond). Seven hybrid individuals were more expensive than both parent species (Fig. 4). 4. Discussion In this study we use turtles as a case study to highlight the utility and importance of monitoring the online wildlife trade. From surveying a single online trading platform in Hong Kong, we collected baseline data to characterize the scale and scope of the turtle trade, identified likely illegal international trade and ascertained factors influencing sale price and consumer preference. We discuss each of these findings in detail, as well as provide recommendations on how to incorporate and improve online surveys for regulating wildlife trade of other taxa.
3. Results We collected data from 9058 posts in the 36-month period. In these posts, 14,360 live turtles of 136 species were advertised for sale. The number of individuals and species sold fluctuated over time, but there was no obvious temporal pattern (Fig. A1). Among the species sold, 67 (49%) were listed in IUCN threatened categories (CR = 24; EN = 23; and VU = 20). Geographically, most traded species originated from Asia (46 species; 34%) and North America (35 species; 26%; Fig. 1). Species in IUCN threatened categories (CR, EN, VU) were most common from Asia (84.8% 39/46 species) and Africa (58.3%, 7/12 species). Among the 136 species recorded, 77 were listed in CITES Appendices (Appendix I = 9; Appendix II = 58; and Appendix III = 10; Fig. 2). Twenty-eight species were likely to be illegally traded since they were absent from CITES import records (2007–2016) and/or the Hong Kong possession license species list (Fig. 2; Table A1). The price of individual turtles ranged from USD 1–50,800 (HKD 8–400,000; HKD 1 = USD 0.127). The total value of the posts examined was USD 5,740,986. The best model (R2m = 0.29; R2c = 0.75) that explain price variation included the IUCN status (χ2 = 42.35; P < 0.001), source (χ2 = 72.28; P < 0.001), morphological form (χ2 = 971.29; P < 0.001) and year (χ2 = 263.27; P < 0.001; Table A2 and A3). Comparing the categories of IUCN status, CR turtles were
4.1. Characterization of online turtle trade Our 3-year study found that over ⅓ (136 of 356) of all turtle species were present, including 24 CR species, in the trade. The species diversity found online was comparable to the survey of physical stores in Hong Kong between 2000 and 2003, which recorded 155 species (Cheung and Dudgeon, 2006). In this study, disproportionally high percentages (> 75%) of the traded species originated from Asia and Africa were threatened species (Fig. 1). This corroborates a number of studies finding a significant scale of illegal wildlife trade in these regions (Natusch and Lyons, 2012; Nijman, 2010). For trade volume, we recorded 14,360 live turtles, which represents approximately 0.1% of the global CITES-listed reptile trade in the same time frame (average 11.4 million whole organism equivalents; Harfoot et al., 2018). We consider the relative value of this percentage large, as the CITES data represents global trade of all reptiles (including live specimens and skins), while our data merely represents live turtle trade from a single online platform from one city (Hong Kong). Another online wildlife trade study focusing on animals found that turtles and tortoises represented approximately 45% of all specimens identified (Hastie, 2018). These numbers highlight the immense scale of the turtle trade 221
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Fig. 2. Proportion of CITES-listed and non CITES-listed species (A), and proportion of illegally traded species (CITES-listed species without import records in the CITES trade database and/or records possession license species list under a law in Hong Kong (Protection of Endangered Species of Animals and Plants Ordinance [CAP.586])) (B) among turtle species sold on an internet forum between September 2013 and August 2016 in Hong Kong.
Fig. 3. Estimates in the generalized linear mixed models for price of turtles sold on a Hong Kong internet forum between September 2013 and August 2016. Abbreviations: CR = critically endangered; EN = endangered; VU = vulnerable; NT = near threatened; LC = least concern; NE = not evaluated and, DD = data deficient. Critically endangered, captive-bred, normal morphological form and 2013–2014 were set as reference categories and shown as 0.
CITES Appendix II-listed species sourced from captive stocks are exempt from the requirement of a possession license in Hong Kong. In our study, we found that several species sold on the forum were listed as wild-caught, but were absent from the Hong Kong possession license species list: African spurred tortoise (Centrochelys sulcata), eastern box turtle (Terrapene carolina), golden coin turtle (C. trifasciata), keeled box turtle (Cuora mouhotii) and Vietnamese pond turtle (Mauremys annamensis). As there are currently no reliable methods of differentiating the source of an individual, this presents an opportunity to falsely declare wild-caught individuals as captive-bred. This phenomenon has already been documented in the European Union (Auliya et al., 2016) and mainland China (Shi et al., 2007; Shi et al., 2008). So, are these individuals sold online wild-caught or captive-bred? Both situations present violation of Hong Kong law: if individuals are wild-caught, the owners are in violation of Hong Kong possession law, while if captivebred, the owner is fraudulently selling the turtle as wild-caught (likely for a higher price). In the second case, sellers may be persecuted in
(Nijman and Shepherd, 2014). 4.2. Use of online market surveys to reveal illegal trade Surveying online markets can provide an estimate of the illegal wildlife trade—36% (28 of 77) of CITES-listed turtle species sold on the internet were not listed in CITES import records or the Hong Kong species list of possession licenses, flagging them as being traded illegally. Of these potentially illegal species, 82% are classified with IUCN threatened status (CR, EN, VU), including a few range-restricted species distributed on islands, such as Ryukyu black-breasted leaf turtle (Geoemyda japonica), Palawan forest turtle (Siebenrockiella leytensis) and ploughshare tortoise (Astrochelys yniphora). Because of the high value, it is likely that these species are being sold as pets rather than food. Illegal harvesting and trade for the pet markets continue to pose threats to the remnant populations of these critically endangered species (Auliya et al., 2016). 222
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Nogueira-Filho, 2011). However, the consumer preference for wildcaught individuals may indemnify the effectiveness of this approach. This preference for wild products has also been reported for other wildlife products, such as bear bile (Dutton et al., 2011). Consumers, oftentimes the owners of turtle farms (Shi et al., 2007), may prefer wildcaught individuals due to perceived benefits of higher fertility, special morphological forms and unique genetic make-up. A prime example of the difference between wild-caught and captive-bred individuals can be seen with the golden coin turtle. Although a high number of captivebred turtles from China are produced (> 40,000 individuals in 2002) (Shi et al., 2008; Sigouin et al., 2016), the high price of wild-caught specimens recorded in this study (mean = USD 10,429) was 77% higher than other individuals (mean = USD 5903). The higher prices of rare and wild-caught turtles exemplify anthropogenic Allee effect—rarity increases the price of an item, the disproportionally high prices provide incentives for persistent harvesting of the already depleted wild populations (Courchamp et al., 2006). This positive-feedback loop is dangerous and if not addressed will contribute to the extinction of turtle species worldwide.
Fig. 4. Average prices of hybrid turtles and the respective parent species sold on an internet forum between September 2013 and August 2016 in Hong Kong. Hybrids with an average price higher than both parent species are indicated in red. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
4.4. Demand for special morphology Hong Kong under the Trade Descriptions Ordinance, CAP. 362, a local law enacted in 2013, which prohibits false trade description. The key for this problem is to develop methods to differentiate the source of an individual. Stable isotope analysis has been used to identify the source of frogs in the trade (Dittrich et al., 2017), and effort should be made to applying this technique to turtles and other wildlife products. The availability of CITES-listed turtles online shows that illegal trade is occurring in plain view, and is strong evidence that trade regulations in their current form are ineffective. The import of wildlife into Hong Kong is not well regulated, which accords with studies on the trade of other wildlife, such as shark fin (Shea and To, 2017) and snakes (Zhou and Jiang, 2004). With the blooming demand for wildlife and their products in China, Hong Kong's close proximity to China makes it an important transit point for international smuggling of wildlife into China. This is exemplified by regular seizure cases between Hong Kong and China (ADM Capital Foundation, 2015). Popular ports such as Hong Kong must find ways to broaden their arsenal to detect wildlife smuggling and enforce anti-smuggling laws, such as increasing inspections at ports (Phelps et al., 2010), use of scent detector dogs (Beebe et al., 2016) and use of conservation forensics to differentiate wild-caught individuals from captive-bred individuals (Natusch et al., 2017).
Turtles, pure species or hybrids, with special morphology were highly priced. Turtle keepers may prefer rare or strange forms, similar to the preference of “designer” green pythons (individuals that display abnormal color) (Lyons and Natusch, 2013). Most “designer” turtles recorded in this study were albino—the most expensive individual recorded in this study was an albino common snapping turtle (Chelydra serpentina) adult, which was offered for USD 50,800. Wild individuals or populations with special color forms may be targeted for producing “designer” turtles. Hybrid turtles represented a small proportion (4%) of the trade, yet some were highly priced. Hybrid turtles may be attractive to hobbyists because of the high variability and uniqueness of morphology, as “designer” turtles. Hybrids of the Indochinese box turtle (Cuora galbinifrons) and keeled box turtle (Cuora mouhoutii) were over nine times more expensive than the price of their parent species (Fig. 4). Production of hybrids (F2 or beyond) does not lead to elimination of turtles from the wild, however, increasing popularity of hybrid turtles in the market may render trade regulation more difficult. Under CITES, the trade of hybrids is regulated if either of the parents is listed in the Appendices and the more restrictive Appendix applies if parents are listed in different Appendices. It has been challenging for enforcement personnel to identify pure species (Natusch and Lyons, 2012), let alone hybrids. From our data, we recorded hybrids of generation F3 or beyond with four species listed—morphological species identification is extremely difficult for these individuals. Molecular approaches may be needed to identify hybrid individuals and their parent species for trade regulation (Fong and Chen, 2010; Stuart and Parham, 2006).
4.3. Consumer preference for wild and rare turtles Consumer preference is a major driver of the wildlife market, and sale price may help us understand this preference. We found that the price of turtles increased with rarity associated with IUCN status. This phenomenon was also seen in the markets for orchids and snakes (Hinsley et al., 2015; Lyons and Natusch, 2013). Notably, the five most expensive turtle species were all critically endangered species belonging to the Asian box turtle genus Cuora: Zhou's box turtle (C. zhoui; mean = USD 38,461), Pan's box turtles (C. pani; mean = USD 20,940), yellow-headed box turtle (C. aurocapitata; mean = USD 19,872), McCord's box turtle (C. mccordi; mean = USD 16,667) and golden coin turtle (mean = USD 6418). This underscores the enormous demand of Asian box turtles in the pet market (Auliya et al., 2016). The legal wildlife trade has seen a shift from predominantly wildsourced to more captive-sourced products for most taxonomic groups, particularly in reptiles (Harfoot et al., 2018). Captive breeding has been successful for some endangered turtle species, such as the golden coin turtle (Shi et al., 2008; Sigouin et al., 2016). Captive-bred turtles have been suggested as a potential source to satisfy the demand in the turtle trade and relieve the pressure on wild populations (Nogueira and
4.5. Temporal trends in turtle prices We found that the price of turtles changed significantly over time, showing a peak in 2014–2015. Temporal changes in market prices are of conservation significance because it may suggest a change in supply and demand of turtles. For the supply side, increase in prices may reveal depleted wild populations (Harris et al., 2015) or reduced productivity in turtle farms. For the demand side, under the influence of the socioeconomic aspects of the trade, turtle hobbyists may have wanted to acquire more turtles. In addition, a shift in consumer preference, favoring more-expensive species/morphological forms, may have occurred (Lyons and Natusch, 2013). Such change in prices over relatively short period of time highlights the dynamic nature of turtle trade—we call for studies to collect longer-term data on prices, information on wild populations and consumer preferences, in order to refine our understanding of factors that influence the turtle trade. 223
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5. Conclusions
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The internet has emerged as a popular platform for wildlife trade, imposing additional challenges to wildlife trade regulation. We demonstrate that systematic surveys of online markets are important tools to understand consumer preference and reveal potential illegal trade. Continued monitoring has the potential to uncover other trends, such as shifts in consumer preference and market reactions to special events (e.g., new legislation, uplisting of species on endangered lists), and we see our study as a baseline data for these future comparisons. This in turn allows us to evaluate the effectiveness of wildlife trade regulation at both international and national levels. For turtles, we found that over a third of the trade species among the CITES-listed species being sold were likely traded, highlighting that the current interventions are ineffective at controlling the illegal trade of endangered turtles. We believe that similar online trade surveys of other wildlife should be done to enhance our understanding of the illegal wildlife trade markets and facilitate stronger trade enforcement. Surveys of the online wildlife trade are not a panacea, but rather another tool to aid conservation management. We believe an integrative approach (Sigouin et al., 2016), including systematic market surveys, enhanced regulation of trade and public education on the effect of trade on wild population for hobbyists, must be in place along the trade chain to halt the illegal and unsustainable wildlife trade before the highly sought-after species become extinct in the wild, for turtles as well as other prized wildlife taxa. Acknowledgements This work was supported by Ocean Park Conservation Foundation, Hong Kong. We would like to thank Agriculture, Fisheries and Conservation Department, Hong Kong Government for providing information on the trade. We are grateful to Ken Lee, Eric Ng, Franco Leung, Anthony Ki, Tom Li, Charlotte Chan, Fa Cheung, Lag Wan, Agnes Chan, Cherry Ho, Cecilia Wong for assistance with data collection. We thank Anthony Lau for his comments on the manuscript. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.biocon.2018.09.025. References ADM Capital Foundation, 2015. Wildlife crime: is Hong Kong doing enough? (available at). http://admcf.org/wp-content/uploads/2016/12/1-Resource-b-Wildlife-Crime-IsHong-Kong-Doing-Enough-Report-English-version-December-2015.pdf, Accessed date: 12 October 2017. Alves, R., Lima, J., Araujo, H., 2012. The live bird trade in Brazil and its conservation implications: an overview. Bird Conserv. Int. 23, 53–65. Auliya, M., Altherr, S., Ariano-Sanchez, D., Baard, E.H., Brown, C., Brown, R.M., Cantu, J.-C., Gentile, G., Gildenhuys, P., Henningheim, E., Hintzmann, J., Kanari, K., Krvavac, M., Lettink, M., Lippert, J., Luiselli, L., Nilson, G., Nguyen, T.Q., Nijman, V., Parham, J.F., Pasachnik, S.A., Pedrono, M., Rauhaus, A., Córdova, D.R., Sanchez, M.E., Schepp, U., van Schingen, M., Schneeweiss, N., Segniagbeto, G.H., Somaweera, R., Sy, E.Y., Türkozan, O., Vinke, S., Vinke, T., Vyas, R., Williamson, S., Ziegler, T., 2016. Trade in live reptiles, its impact on wild populations, and the role of the European market. Biol. Conserv. 204, 103–119. Barton, K., 2011. MuMIn: multi-model inference (R package version 1.0. 0, available at). http://CRAN.R-project.org/package/MuMIn/, Accessed date: 20 August 2016. Beebe, S.C., Howell, T.J., Bennett, P.C., 2016. Using scent detection dogs in conservation settings: a review of scientific literature regarding their selection. Front. Vet. Sci. 3, 96. Bennett, E.L., 2011. Another inconvenient truth: the failure of enforcement systems to save charismatic species. Oryx 45, 476–479. Bolker, B.M., Brooks, M.E., Clark, C.J., Geange, S.W., Poulsen, J.R., Stevens, M.H.H., White, J.-S.S., 2009. Generalized linear mixed models: a practical guide for ecology and evolution. Trends Ecol. Evol. 24, 127–135. Bonin, F., Devaux, B., Dupre, A., 2006. Turtles of the World, first edn. Johns Hopkins University Press, Baltimore, Maryland, USA. Broad, S., Mulliken, T., Roe, D., 2003. The nature and extent of legal and illegal trade in wildlife. In: Oldfield, S. (Ed.), The Trade in Wildlife: Regulation for Conservation.
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