DS01 - Gestion sobre des ressources et adaptation au changement climatique

Pangolins going extinct (PANGO-GO): Tracing the local-to-global trade of the most trafficked mammals on Earth with evolutionary-based toolkits – PANGO-GO

Submission summary

The illegal wildlife trade has become a global threat to tropical biodiversity and as such, to the millions of people who depend on it. Recently, the scale of wildlife trade has moved from local to global notably through the growing demand from local urban centers and Chinese Traditional Medicine (CTM) markets. Pangolins, a group of Afro-Asian ant-eating mammals, have recently emerged as the most trafficked mammals on Earth, being literally “eaten to extinction”. Because they are subject to a drastic change in the magnitude of their trade involving local-to-global networks, pangolins have been highlighted as the flagship species of the bushmeat crisis currently operating in the tropics. So far, the pangolin trade has suffered from poor traceability because of (i) the various forms under which pangolins are traded, from smoked carcasses to scale powder, and (ii) the lack of knowledge on their diversification patterns.

In PANGO-GO, we propose an integrative evolutionary framework combining cutting-edge genomics and 3D morphometrics approaches with modeling of local trade networks, from which innovative tools will be derived to implement an efficient tracing of pangolins. Our approach is expected to answer the growing societal demand for mitigating the pangolin trade. It should also supersede the caveats of traditional survey techniques based on visual identification and interviews of commodity chain stakeholders, generally failing to identify the species and their geographic origins. First, we will establish the diversification patterns of pangolins across Africa and Asia through high-throughput sequencing of mitogenomes and hundreds of nuclear loci, positing that phylogenetic / phylogeographic patterns will constitute an appropriate framework to extract the best molecular and morphological markers for tracing the pangolin trade at the global scale (i.e. across and between continents). Second, we will focus on the Gabonese market, a hub of the pangolin trade recently affected by the demand from the CTM market, to trace the dynamics of local networks through an approach integrating genotyping and market modelling. We will explore the relative contributions of three traditional-to-emerging genotyping techniques (gene capture, RAD- and microsatellite genotyping) to the geographical tracing of pangolins seized on the Gabonese markets. To identify temporal trends and the main societal factors (including the Chinese demand) acting on the local market, we will model the Gabonese trade dynamics in relation to pangolins’ biological traits, environmental factors and the characteristics of bushmeat actors, through a combination of previous and planned surveys of major markets spanning a 15-year period and involving two focal partners. Third, we will deliver a series of evolutionary-based, turnkey toolkits capable of tracing the nature of the pangolin trade whatever its scales and conditions, including SNP chips, molecular and morphological online identification tools, and tracing protocols adapted to Chinese seizures and degrade DNA.

The major scientific challenge of PANGO-GO is to rely on fundamental science to design innovative, implementable toolkits for wildlife trade monitoring and to bolster wildlife forensic capacity in Africa and Asia. Through our collaboration with focal partners in Gabon and China together with the implication of local bushmeat stakeholders, we expect to deliver efficient and accessible tools for tracing the pangolin trade across its various scales, to support international law enforcement and to raise conservation awareness along the bushmeat commodity chain that will eventually prevent pangolins from going extinct.

Project coordinator




EDB Evolution et diversité biologique
UMR - 7207 MNHN - CR2P

Help of the ANR 630,188 euros
Beginning and duration of the scientific project: December 2017 - 48 Months

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