Multidimensional characteristics and distribution networks of illegal wildlife trade in the Yunnan-Guangxi region

The illegal wildlife trade poses a severe threat to the survival of endangered species and is a critical area of research in ecologically-centered green criminology. Domestic studies on this issue, however, remain underdeveloped. Focusing on the Yunnan-Guangxi region, this study systematically analyzes the multidimensional characteristics, spatiotemporal patterns, and distribution network structures of illegal wildlife trade using public case data from China Judgements Online from 2013 to 2023. The study employs a combination of mathematical statistics, spatial analysis, and social network analysis methods. The results show that: ①the crimes primarily involved mammals, birds, and reptiles, with elephants, rhesus monkeys, and tortoises as typical species; the main perpetrators were predominantly males aged 41~50, with low educational levels, mainly engaged in agricultural work. ②The number of offenses initially increased, peaking in 2019, and declined sharply after 2020 due to COVID-19 containment measures. Monthly analysis reveals that January and July were high-incidence periods, with a peak occurring in spring. ③Spatially, criminal activities were concentrated in border regions and provincial capitals, forming a dual-core pattern with significant clustering. ④Distribution networks are mainly provincial, while cross-provincial and international routes rely on border nodes to establish smuggling corridors with Vietnam and Myanmar, ultimately converging on the southeastern coast (Guangdong and Fujian). Different forms of criminal organizations, including organized, general, and unorganized groups, exhibit notable differences in distribution network structure, node functions, and trafficking routes. The study recommends combating illegal wildlife trade through strengthening border enforcement, monitoring key nodes, big data-driven management, and community participation.