Real-time anti-poaching tags could help prevent imminent species extinctions

Paul O’Donoghue, Christian Rutz

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)


At an estimated $7–10 billion annually, the global trade in illegal wildlife parts is
comparable in economic value to human trafficking, and the smuggling of weapons and drugs (Wasser et al. 2008; Wyler & Sheikh 2013). Basic economic principles of supply and demand ensure that, as target species become ever rarer, their market value continues to rise, gradually pushing them towards extinction (Courchamp et al. 2006; Nowell 2012a). One particular problem is that anti-poaching rangers often arrive too late at crime scenes to arrest criminals, making poaching a low-risk and high-gains enterprise (Wyler & Sheikh 2013). Here, we identify an opportunity to address this fundamental problem – we propose that cutting-edge tracking technology could be harnessed to implement effective ‘real-time poaching-alert systems’. Animals would be fitted with miniature electronic devices (‘biologgers’) that can detect a poaching event, establish its exact location, and relay data remotely to ground teams. Such systems should considerably increase the chances of successful interception, and thereby, escalate the actual and perceived risks of poaching, establishing a powerful new deterrent. In combination with other mitigation strategies (reviewed below), this innovative approach could lead to a much-needed breakthrough in the increasingly desperate fight against wildlife crime.

Original languageEnglish
Pages (from-to)5-10
Number of pages6
JournalJournal of Applied Ecology
Issue number1
Early online date24 Jul 2015
Publication statusPublished - Feb 2016


  • Anti-poaching measures
  • Biologging
  • Elephant
  • Environmental education
  • Illegal trade
  • Ivory
  • Poaching
  • Rhino
  • Tiger
  • Wildlife crime


Dive into the research topics of 'Real-time anti-poaching tags could help prevent imminent species extinctions'. Together they form a unique fingerprint.

Cite this