Stringham Oliver C, Moncayo Stephanie, Thomas Eilish, Heinrich Sarah, Toomes Adam, Maher Jacob, Hill Katherine G W, Mitchell Lewis, Ross Joshua V, Shepherd Chris R, Cassey Phillip
Invasion Science & Wildlife Ecology Lab, University of Adelaide, SA 5005, Australia.
School of Mathematical Sciences, University of Adelaide, SA 5005, Australia.
Data Brief. 2021 Oct 30;39:107531. doi: 10.1016/j.dib.2021.107531. eCollection 2021 Dec.
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.
非法野生动物贸易(IWT)威胁着保护和生物安全工作。互联网极大地促进了野生动物贸易,研究人员也越来越多地通过互联网来揭露非法贸易。然而,大多数在互联网上查找非法贸易的工作都针对一种或少数几种分类群或产品。通过系统汇编非法交易的野生动物分类群及其用途,可能有助于在互联网(电子商务、社交媒体、暗网)上大规模查找非法野生动物。在此,我们提供这样一个数据集。我们使用了来自三个全球野生动物贸易数据库的查获记录,来汇编被查获分类群的身份及其预期用途(即使用类型)。我们的数据集包括约4900个不同的分类群,代表约3300个物种,包含来自110种独特使用类型的约11000个分类群 - 用途组合。此外,我们从100多种语言中获取了超过45000个被查获分类群的通用名称。我们的数据集可用于在互联网上进行大规模广泛搜索,以查找非法交易的野生动物。此外,我们的数据集可以进行筛选,以便对特定分类群或衍生产品进行更有针对性的搜索。