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Title: Prevalence of endangered shark trophies in automated detection of the online wildlife trade
Direct exploitation, which includes the trade of wild animals for their parts, is a major driver of extinction. Digital communication tools, particularly the internet, have facilitated the trade in endangered species. Here, we automatically collected data to analyze online sales of threatened animals across 148 English-text online mar- ketplaces. We created a tool that searched for online sales of 13,267 animal species at risk of global extinction, as classified by the International Union for Conservation of Nature (IUCN), as well as 706 animal species on Ap- pendix I of the Convention for International Trade in Endangered Species (CITES), for which international commercial trade is prohibited. Examining a period of 15 weeks in 2018, we identified 10,699 unique listings selling body parts or eggs of threatened species, of which 4131 contained a full species name (common or sci- entific). These 4131 results were then filtered by keywords and, finally, manually vetted, which yielded 546 sale listings for 83 species. Of these 546 listings, 61 % advertised shark trophies (mainly jaws), 73 % of which were taken from species listed as endangered or critically endangered. Just four websites hosted >95 % of listings. We identified 18 species for sale that are included on CITES Appendix I. We also identified 13 species for which the IUCN had not identified intentional use as a threat. This work expands current understanding about the dealing of endangered and potentially illegal species online, specifies taxa threatened by online trade, and highlights emerging opportunities and persistent challenges to preventing the trafficking of threatened species.  more » « less
Award ID(s):
2146351 2146312
PAR ID:
10580013
Author(s) / Creator(s):
; ; ; ; ;
Publisher / Repository:
Elsevier sciencedirect
Date Published:
Journal Name:
Biological Conservation
Volume:
304
Issue:
C
ISSN:
0006-3207
Page Range / eLocation ID:
110992
Subject(s) / Keyword(s):
Endangered species Machine-learning Online Sharks Threatened Trade Wildlife
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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