Quantitative Investigation of Wildlife Trafficking Supply Chains: A Review

Conservation tools: the next generation of engineering–biology collaborations

“…If these communities cannot rely on tourism, they may focus on wildlife trafficking, as those species are prevalent near them [ 89 ]. A review of wildlife tracking [ 90 ] focusing on operations and supply chain management recognized four challenges that limit preventative measures: the difficulties of understanding the true scale of illegal wildlife trade from available data; the breadth of the issue—trafficked animals are used for food, status symbols, traditional medicine, exotic pets and more (this requires the policy remedy to be multifaceted), and sometimes illegal wildlife trade operates in countries with corrupt governments or limited infrastructures for law enforcement and monitoring; illegal wildlife traders are geared towards undetectable operations, especially from financial institutions; and illegal wildlife trade is considered less serious than other trafficking, i.e. human, drugs and weapons.…”

“…There are several suggested ways to apply research in supply chain operations toward combating illegal wildlife trade [ 90 ]. These include: bolstering data through CT such as satellite data, acoustic monitoring, eDNA, news scraping and finding online markets; strengthening data detection and prediction through network analysis and understanding data bias; modelling the problem as a network interdiction problem to see how to disrupt the supply chain network; more effective resource management and reducing corruption.…”

“…If these communities cannot rely on tourism, they may focus on wildlife trafficking, as those species are prevalent near them [89]. A review of wildlife tracking [90] focusing on operations and supply chain management recognized four challenges that limit preventative measures:…”

Advancing interdisciplinary science for disrupting wildlife trafficking networks

“…Machine learning can help fill in data gaps by using available data to build models for predicting likely linkages and routes that have not been detected yet. Many quantitative methods are available for dealing with limited and difficult to process data, which is helpful in this interdisciplinary context ( 31 ). Techniques in reinforcement learning have become popular in the Operations Research literature in recent years and present a powerful opportunity to apply optimization methods to areas that have traditionally suffered from a lack of quality data ( 32 ).…”

“…Quantitative approaches that can advance understanding of the contours of WTN vulnerability from the perspective of both offenders and defenders include bilevel optimization and network design models, among others ( 33 ). Operations research models offer insight into more effective resource allocation for tactical and operational actions, sourcing practices to reduce the laundering of illicitly obtained products, and data-based decision-making for interdiction ( 31 ). Bilevel optimization models, for example, could help incorporate a range of domain-specific characteristics about WTNs and address both offender and defender objectives instead of single-focused analysis.…”