
Abstract Live animal smuggling presents a suite of conservation and biosecurity concerns, including the introduction of invasive species and diseases. Yet, understanding why certain species are smuggled over others, and predicting which species will be smuggled, remains relatively unexplored. Here, we compared the live reptile species illegally smuggled to Australia (75 species) to the legal trade of live reptile species in the United States. Almost all smuggled species were found in the legal US pet market (74 species), and we observed an average time lag of 5.6 years between a species first appearing in the United States and its subsequent detection in Australia. Using a Bayesian regression model, species popularity in the United States, and internationally, were positively associated with smuggling probability to Australia. Our findings give insight to the drivers of illegal wildlife trade and our predictive modelling approach provides a framework for anticipating future trends in wildlife smuggling.
PO1-I-002, Supplementary Information, environment assessment, QH301 Biology, Natural Environment Research Council (NERC), General. Including nature conservation, geographical distribution, alien species, QH1-199.5, wildlife trade, invasive species, QH301, NE/S011641/1, trafficking, Biosecurity, IPBES, Other, illegal wildlife trade, pet trade, Alien Invasive Species Assessment AIS, Chapter 5, biosecurity, biodiversity
PO1-I-002, Supplementary Information, environment assessment, QH301 Biology, Natural Environment Research Council (NERC), General. Including nature conservation, geographical distribution, alien species, QH1-199.5, wildlife trade, invasive species, QH301, NE/S011641/1, trafficking, Biosecurity, IPBES, Other, illegal wildlife trade, pet trade, Alien Invasive Species Assessment AIS, Chapter 5, biosecurity, biodiversity
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 26 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
