Characterizing China's Illegal Trade in Avifauna on Social Media

ABSTRACT The illegal wildlife trade poses a growing threat to species conservation worldwide. Although international bird trading has received considerable attention, the scale and dynamics of regional markets remain poorly understood, especially regarding illegal activities. Using social media data, we characterized China's online illicit trade in avifauna and explored its conservation implications. We identified 178 avian species advertised for illegal sale online. Most species (96.1%) were native to China and protected under national law: Forty‐two species (23.6%) were listed as State Key Protected Wild Animals, and 129 species (72.5%) were categorized as State Protected Terrestrial Wild Animals with Important Ecological, Scientific, and Social Values. About 20% of traded species were included in CITES Appendices, and 10 species (5.6%) were globally threatened (CR = 1; EN = 2; and VU = 7) according to the IUCN Red List. The number of online posts per species ranged from 1 to 421 (median = 15.5), with over half exceeding 10 posts. Trait analyses indicated that traded species occupied a wide range of ecological niches. Logistic regression indicated that passerine trade status (traded vs. non‐traded) was correlated with body mass and distributional range size, while negative binomial regression revealed that trade intensity (postcount) was related to national protection status. Our findings reveal extensive, diverse illegal bird trading on Chinese social media and highlight the need for coordinated action between governments and social media platforms to combat wildlife cybercrime.

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Publication Details

Journal
Integrative Conservation
Published
2025-11-25
DOI
https://doi.org/10.1002/inc3.70053
Primary Topic
Wildlife Conservation and Criminology Analyses
Type
article
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article

Characterizing China's Illegal Trade in Avifauna on Social Media

Aiwu Jiang, Jiaping Xu, Luke Gibson
Integrative Conservation
Wildlife Conservation and Criminology Analyses
article

Characterizing China's Illegal Trade in Avifauna on Social Media

Aiwu Jiang, Jiaping Xu, Luke Gibson
article en

Abstract

ABSTRACT The illegal wildlife trade poses a growing threat to species conservation worldwide. Although international bird trading has received considerable attention, the scale and dynamics of regional markets remain poorly understood, especially regarding illegal activities. Using social media data, we characterized China's online illicit trade in avifauna and explored its conservation implications. We identified 178 avian species advertised for illegal sale online. Most species (96.1%) were native to China and protected under national law: Forty‐two species (23.6%) were listed as State Key Protected Wild Animals, and 129 species (72.5%) were categorized as State Protected Terrestrial Wild Animals with Important Ecological, Scientific, and Social Values. About 20% of traded species were included in CITES Appendices, and 10 species (5.6%) were globally threatened (CR = 1; EN = 2; and VU = 7) according to the IUCN Red List. The number of online posts per species ranged from 1 to 421 (median = 15.5), with over half exceeding 10 posts. Trait analyses indicated that traded species occupied a wide range of ecological niches. Logistic regression indicated that passerine trade status (traded vs. non‐traded) was correlated with body mass and distributional range size, while negative binomial regression revealed that trade intensity (postcount) was related to national protection status. Our findings reveal extensive, diverse illegal bird trading on Chinese social media and highlight the need for coordinated action between governments and social media platforms to combat wildlife cybercrime.

Integrative ConservationVol. 4(4)
Guangxi University (CN), Southern University of Science and Technology (CN)
Openalex Percentile: Top 65%
Wildlife Conservation and Criminology Analyses
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Characterizing China's Illegal Trade in Avifauna on Social Media — Aiwu Jiang, Jiaping Xu, et al. · Integrative Conservation (2025) | TGRS Research Map | TGRS