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Cited by 461

The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.

Summarizing the Evidence on the International Trade in Illegal Wildlife

Open access
Rosen, Gail Emilia, Smith, Katherine F.·2010·EcoHealth

Abstract

The global trade in illegal wildlife is a multi-billion dollar industry that threatens biodiversity and acts as a potential avenue for invasive species and disease spread. Despite the broad-sweeping implications of illegal wildlife sales, scientists have yet to describe the scope and scale of the trade. Here, we provide the most thorough and current description of the illegal wildlife trade using 12 years of seizure records compiled by TRAFFIC, the wildlife trade monitoring network. These records comprise 967 seizures including massive quantities of ivory, tiger skins, live reptiles, and other endangered wildlife and wildlife products. Most seizures originate in Southeast Asia, a recently identified hotspot for future emerging infectious diseases. To date, regulation and enforcement have been insufficient to effectively control the global trade in illegal wildlife at national and international scales. Effective control will require a multi-pronged approach including community-scale education and empowering local people to value wildlife, coordinated international regulation, and a greater allocation of national resources to on-the-ground enforcement.

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Metadata

Authors
Rosen, G. E., & Smith, K. F.
Venue
EcoHealth
Published
2010-06-04
Volume
7
Issue
1
Pages
24-32
ISSN
  • 1612-9202 (ISSN-L)
  • 1612-9210
OpenAlex
W2036480343
Cited by
461
References
25
FWCI
8.12
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Summarizing the Evidence on the International Trade in Illegal Wildlife. https://app.cochat.ai/papers/10.1007/s10393-010-0317-y
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Rosen, G. E., & Smith, K. F. (2010). Summarizing the Evidence on the International Trade in Illegal Wildlife. EcoHealth. https://doi.org/10.1007/s10393-010-0317-y

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.