ESR 32:223-235 (2017)  -  DOI:

Monitoring internet trade to inform species conservation actions

Valentina Vaglica1, Maurizio Sajeva1, H. Noel McGough1, Dylan Hutchison2, Claudio Russo3, Andrew D. Gordon3,4, Aro Vonjy Ramarosandratana5, Wolfgang Stuppy6, Matthew J. Smith7,8,*

1Dipartimento di Scienze e Tecnologie Biologiche, Chimiche e Farmaceutiche, Via Archirafi 18, Palermo 90123, Italy
2University of Washington, Seattle, WA 98195, USA
3Microsoft Research, Cambridge CB1 2FB, UK
4School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK
5Department of Plant Biology and Ecology, University of Antananarivo, PO Box 906, Antananarivo 101, Madagascar
6Royal Botanic Gardens, Kew, Wakehurst, Ardingly RH17 6TN, UK
7Microsoft Services, Reading RG6 1WG, UK
8Royal Botanic Gardens Kew, Richmond, Surrey TW9 3AE, UK
*Corresponding author:

ABSTRACT: Specimens, parts and products of threatened species are commonly traded on the internet. This could threaten the survival of some wild populations. We outline 2 methods to monitor internet sales of species to assess potential threats and inform conservation actions. Our first method combines systematic monitoring of online offers of plants for sale with expert consultation. Our second method utilises a computational model, trained to expert-classified records using probabilistic inference, to predict unknown properties of the traded taxa. We used these methods to monitor internet trade in 5 genera of succulent plant species endemic to Madagascar, some of which have recently been listed for trade regulation under the Convention on International Trade in Endangered Species (CITES). This revealed potential threats to wild populations: for instance, almost all species recorded were of high conservation concern, yet most offers for live plants were of apparently wild-collected specimens (85%). Our model predicted with 89% accuracy whether the plants were classified as propagated or wild collected by an expert, although accuracy dropped for data collected in the following summer. Our results highlight potential threats by internet trade to the survival of some CITES and non-CITES listed plant species from Madagascar. These should be addressed by further conservation actions and policy. More generally, our results reveal how standardised internet surveys can provide information on levels of trade in wild-collected threatened species that could impact on natural populations, and can provide data that can be incorporated into models to facilitate future monitoring and enforcement.

KEY WORDS: Adenia · Commiphora · Operculicarya · Uncarina · Machine learning · Infer.NET · Naive Bayes classifier

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Cite this article as: Vaglica V, Sajeva M, McGough HN, Hutchison D and others (2017) Monitoring internet trade to inform species conservation actions. Endang Species Res 32:223-235.

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