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. 2021 Oct 30:39:107531.
doi: 10.1016/j.dib.2021.107531. eCollection 2021 Dec.

Dataset of seized wildlife and their intended uses

Affiliations

Dataset of seized wildlife and their intended uses

Oliver C Stringham et al. Data Brief. .

Abstract

The illegal wildlife trade (IWT) threatens conservation and biosecurity efforts. The Internet has greatly facilitated the trade of wildlife, and researchers have increasingly examined the Internet to uncover illegal trade. However, most efforts to locate illegal trade on the Internet are targeted to one or few taxa or products. Large-scale efforts to find illegal wildlife on the Internet (e-commerce, social media, dark web) may be facilitated by a systematic compilation of illegally traded wildlife taxa and their uses. Here, we provide such a dataset. We used seizure records from three global wildlife trade databases to compile the identity of seized taxa along with their intended usage (i.e., use-type). Our dataset includes c. 4.9k distinct taxa representing c. 3.3k species and contains c. 11k taxa-use combinations from 110 unique use-types. Further, we acquired over 45k common names for seized taxa from over 100 languages. Our dataset can be used to conduct large-scale broad searches of the Internet to find illegally traded wildlife. Further, our dataset can be filtered for more targeted searches of specific taxa or derived products.

Keywords: CITES; Dark web; Illegal wildlife trade; Internet; LEMIS; Social media; Wildlife products; Wildlife seizures.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig 1
Fig. 1
Diversity of wildlife taxa illegally traded as reported in the databases of CITES, LEMIS and TRAFFIC. Widths of bars correspond to the number of taxa in each taxonomic group. The leftmost column displays the taxonomic kingdom, the middle column displays the phylum, and right column displays the order. Taxonomic orders with less than 10 taxa are not displayed.
Fig 2
Fig. 2
The number of use-type designations per taxa. There were 139 taxa (c. 3%) with 10 or more use-types.
Fig 3
Fig. 3
Use-taxa combinations at the family taxonomic level. The top 10 families (by number of use-taxa combinations) and the four main categories are displayed. Line thickness represents the number of unique taxa within each family that belong to a corresponding use-type main category (e.g., number of taxa in Orchidaceae that were seized as ‘live’; n = 325).

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