Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

An evolutionary game theoretic model of rhino horn devaluation

Glynatsi, Nikoleta E., Knight, Vincent and Lee, Tamsin E. 2018. An evolutionary game theoretic model of rhino horn devaluation. Ecological Modelling 389 , pp. 33-40. 10.1016/j.ecolmodel.2018.10.003
Item availability restricted.

[img] PDF - Accepted Post-Print Version
Restricted to Repository staff only until 22 October 2019 due to copyright restrictions.

Download (633kB)

Abstract

Rhino populations are at a critical level due to the demand for rhino horn and the subsequent poaching. Wildlife managers attempt to secure rhinos with approaches to devalue the horn, the most common of which is dehorning. Game theory has been used to examine the interaction of poachers and wildlife managers where a manager can either ‘dehorn’ their rhinos or leave the horn attached and poachers may behave ‘selectively’ or ‘indiscriminately’. The approach described in this paper builds on this previous work and investigates the interactions between the poachers. We build an evolutionary game theoretic model and determine which strategy is preferred by a poacher in various different populations of poachers. The purpose of this work is to discover whether conditions which encourage the poachers to behave selectively exist, that is, they only kill those rhinos with full horns. The analytical results show that full devaluation of all rhinos will likely lead to indiscriminate poaching. In turn it shows that devaluing of rhinos can only be effective when implemented along with a strong disincentive framework. This paper aims to contribute to the necessary research required for informed discussion about the lively debate on legalising rhino horn trade.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Mathematics
Advanced Research Computing @ Cardiff (ARCCA)
Publisher: Elsevier
ISSN: 0304-3800
Date of First Compliant Deposit: 13 February 2019
Date of Acceptance: 8 October 2018
Last Modified: 23 Aug 2019 10:15
URI: http://orca.cf.ac.uk/id/eprint/116224

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics