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Combating Rhino Horn Trafficking: The Need to Disrupt Criminal Networks

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  • Timothy C Haas
  • Sam M Ferreira

Abstract

The onslaught on the World’s wildlife continues despite numerous initiatives aimed at curbing it. We build a model that integrates rhino horn trade with rhino population dynamics in order to evaluate the impact of various management policies on rhino sustainability. In our model, an agent-based sub-model of horn trade from the poaching event up through a purchase of rhino horn in Asia impacts rhino abundance. A data-validated, individual-based sub-model of the rhino population of South Africa provides these abundance values. We evaluate policies that consist of different combinations of legal trade initiatives, demand reduction marketing campaigns, increased anti-poaching measures within protected areas, and transnational policing initiatives aimed at disrupting those criminal syndicates engaged in horn trafficking. Simulation runs of our model over the next 35 years produces a sustainable rhino population under only one management policy. This policy includes both a transnational policing effort aimed at dismantling those criminal networks engaged in rhino horn trafficking—coupled with increases in legal economic opportunities for people living next to protected areas where rhinos live. This multi-faceted approach should be the focus of the international debate on strategies to combat the current slaughter of rhino rather than the binary debate about whether rhino horn trade should be legalized. This approach to the evaluation of wildlife management policies may be useful to apply to other species threatened by wildlife trafficking.

Suggested Citation

  • Timothy C Haas & Sam M Ferreira, 2016. "Combating Rhino Horn Trafficking: The Need to Disrupt Criminal Networks," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-26, November.
  • Handle: RePEc:plo:pone00:0167040
    DOI: 10.1371/journal.pone.0167040
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    References listed on IDEAS

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    Cited by:

    1. Timothy Haas, 2020. "Developing political-ecological theory: The need for many-task computing," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-26, November.
    2. Annamaria Ficara & Francesco Curreri & Giacomo Fiumara & Pasquale De Meo & Antonio Liotta, 2022. "Covert Network Construction, Disruption, and Resilience: A Survey," Mathematics, MDPI, vol. 10(16), pages 1-43, August.
    3. Neil, Emily & Madsen, Jens Koed & Carrella, Ernesto & Payette, Nicolas & Bailey, Richard, 2020. "Agent-based modelling as a tool for elephant poaching mitigation," Ecological Modelling, Elsevier, vol. 427(C).
    4. Chen, Frederick & ’t Sas-Rolfes, Michael, 2021. "Theoretical analysis of a simple permit system for selling synthetic wildlife goods," Ecological Economics, Elsevier, vol. 180(C).
    5. Rubino, Elena C. & Pienaar, Elizabeth F. & Soto, José R., 2018. "Structuring Legal Trade in Rhino Horn to Incentivize the Participation of South African Private Landowners," Ecological Economics, Elsevier, vol. 154(C), pages 306-316.
    6. Siqing Shan & Xijie Ju & Yigang Wei & Xin Wen, 2022. "Concerned or Apathetic? Using Social Media Platform (Twitter) to Gauge the Public Awareness about Wildlife Conservation: A Case Study of the Illegal Rhino Trade," IJERPH, MDPI, vol. 19(11), pages 1-21, June.
    7. Chen, Frederick, 2017. "The Economics of Synthetic Rhino Horns," Ecological Economics, Elsevier, vol. 141(C), pages 180-189.

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