Shifting drivers and predictable corridors of an illegal wildlife trade network

Illegal wildlife trade is a major driver of biodiversity loss but the lack of understanding of mechanisms sustaining criminal networks hampers law enforcement. We integrated three decades of confiscation data, criminological modeling, and spatial network analysis to dissect the illegal parrot trade in Mexico, a global hotspot of parrot diversity and endemism. Our interdisciplinary approach revealed that the wildlife trade is the leading threat, elevating their extinction risk. Trade is shifting from poverty-driven to population density-linked patterns. Circuit theory-based landscape modeling identified critical trade routes from biodiverse habitats to urban centers, providing actionable targets for law enforcement. Our study demonstrates the effectiveness of combining criminological methods with landscape science to identify specific trafficking routes, a transferable framework for generating actionable intelligence. Crucially, because illicit wildlife networks frequently converge with broader organized crime, this spatial framework provides a powerful proxy for exposing the shared logistical corridors of global illicit markets.