By the same authors

From the same journal

From the same journal

Detecting deterrence from patrol data

Research output: Contribution to journalArticle

Full text download(s)

Published copy (DOI)

Author(s)

Department/unit(s)

Publication details

JournalConservation Biology
DateAccepted/In press - 15 Sep 2018
DateE-pub ahead of print - 20 Sep 2018
DatePublished (current) - 1 Jun 2019
Issue number3
Volume33
Number of pages11
Pages (from-to)665-675
Early online date20/09/18
Original languageEnglish

Abstract

The threat posed to protected areas by the illegal killing of wildlife is countered principally by ranger patrols that aim to detect and deter potential offenders. Deterring poaching is a fundamental conservation objective, but its achievement is difficult to identify, especially when the prime source of information comes in the form of the patrols’ own records, which inevitably contain biases. The most common metric of deterrence is a plot of illegal activities detected per unit of patrol effort (CPUE) against patrol effort (CPUE-E). We devised a simple, mechanistic model of law breaking and law enforcement in which we simulated deterrence alongside exogenous changes in the frequency of offences under different temporal patterns of enforcement effort. The CPUE-E plots were not reliable indicators of deterrence. However, plots of change in CPUE over change in effort (ΔCPUE-ΔE) reliably identified deterrence, regardless of the temporal distribution of effort or any exogenous change in illegal activity levels as long as the time lag between patrol effort and subsequent behavioral change among offenders was approximately known. The ΔCPUE-ΔE plots offered a robust, simple metric for monitoring patrol effectiveness; were no more conceptually complicated than the basic CPUE-E plots; and required no specialist knowledge or software to produce. Our findings demonstrate the need to account for temporal autocorrelation in patrol data and to consider appropriate (and poaching-activity-specific) intervals for aggregation. They also reveal important gaps in understanding of deterrence in this context, especially the mechanisms by which it occurs. In practical applications, we recommend the use of ΔCPUE-ΔE plots in preference to other basic metrics and advise that deterrence should be suspected only if there is a clear negative slope. Distinct types of illegal activity should not be grouped together for analysis, especially if the signs of their occurrence have different persistence times in the environment.

Bibliographical note

© 2018 The Authors.

    Research areas

  • bushmeat, conservation, law enforcement, poaching, protected areas, wild meat

Discover related content

Find related publications, people, projects, datasets and more using interactive charts.

View graph of relations