ISN2: Detecting and Interdicting Illicit Wildlife Trafficking Supply Chains

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This award promotes economic welfare and progress of interdisciplinary science, by studying how illegal wildlife supply chains react and respond to policy, law enforcement, and market interventions. Wildlife trafficking generates an estimated US$23 billion annually for the global criminal economy; it can undermine national security, decrease economic prosperity, and fuel social conflict both in the U.S. and abroad. This project builds fundamental insight about how different computational approaches aid methods for detecting network patterns in illicit wildlife supply chains and new understanding about how illicit wildlife supply chain organizations operate (even using legal networks at times). The study will inform resource allocation, monitoring and enforcement, and communication to facilitate effective interdiction activities to combat wildlife trafficking. Further, the award will benefit decisions about how, when, and where to intervene and disrupt illicit wildlife supply networks. The interdisciplinary approach creates new channels of communication between geography, supply chain management, operations research, conservation social science, and computer science. The project supports broad engagement of PhD students in interdisciplinary science, will diffuse results into research journals via publications, university education via business case studies, and conservation practice via engagement of practitioners. Using complementary lines of inquiry into the global problem of wildlife trafficking, the project develops a new, fundamental understanding of wildlife trafficking supply chains (WTSCs), including decision points, behavioral patterns of participants, dynamic linkages between component parts, and convergence with legal supply chains. The research will define, describe, and map key nodes and components of a specific supply chain using existing, team-collected data from an illicit WTSC, create qualitative framework models associated with decisions about WTSCs, develop methods to detect meaningful patterns of weakness and resilience in WTSCs, and create new quantitative WTSC interdiction models and solution approaches building on techniques for network design optimization, the multi-armed bandit, the orienteering problem and green security games. Our outcomes will be to measure operations in a real-world system, develop geospatial information science and computational models about system operations, refine and revise these models to predict resiliency, and test the scalability, performance of the models at tactical and strategic levels and convergence with other illicit supply chains. Results have potentially transformative implications for science and decision-making in broader society.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.