Are ranger patrols effective in reducing poaching‐related threats within protected areas?

Moore, J. F.; Mulindahabi, Felix; Masozera, Michel; Nichols, James D.; Hines, James E.; Turikunkiko, Ezechiel; Oli, Madan K.

doi:10.1111/1365-2664.12965

Cited by 75 publications

(97 citation statements)

References 50 publications

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“…Among the few studies for which it was possible to calculate δ , we found 1 instance where it was much higher (Moore et al. ), so we assessed the impact of higher values in the sensitivity analysis.…”

Section: Methodsmentioning

confidence: 99%

“…We set appropriate values of effort by estimating δ in a real data set (Hötte et al 2016) and adjusting E in the model to obtain a matching value of δ (0.06) (Supporting Information). Among the few studies for which it was possible to calculate δ, we found 1 instance where it was much higher (Moore et al 2018), so we assessed the impact of higher values in the sensitivity analysis.…”

Section: Modelmentioning

confidence: 99%

“…Various alternative approaches have been used, including indirect inference from levels of local bushmeat consumption (Hodgkinson 2009), hunter interviews (Gandiwa 2011;St. John et al 2015), and correlations between observed incidences of poaching and patrol effort (e.g., Leader-Williams et al 1990;Steinmetz et al 2014;Moore et al 2018). Unfortunately, each approach has limitations.…”

Section: Introductionmentioning

confidence: 99%

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Detecting deterrence from patrol data

Dobson

Milner‐Gulland

Beale

et al. 2018

Conservation Biology

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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.

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Section: Methodsmentioning

confidence: 99%

Section: Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Detecting deterrence from patrol data

Dobson

Milner‐Gulland

Beale

et al. 2018

Conservation Biology

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“…As such, this framework is well suited to study spatiotemporal interactions between wildlife and poachers. However, few studies account for the imperfect detection in the occupancy of poachers (Critchlow et al 2015, Moore et al 2018. Such a flexible parameterization can therefore assess the dynamics of species interactions simultaneously with species occupancy and detection (Fidino et al 2018).…”

Section: Introductionmentioning

confidence: 99%

“…Using repeated surveys of detections and non-detections of poaching-related threats, such as snares, and of wildlife collected at several spatial units, one can estimate the temporal variation in the detection and occupancy probabilities of poachers in a given site conditional on the occurrence of wildlife with which they interact. One recent study assessed levels of illegal wildlife killing in a national park in Rwanda by fitting an occupancy model on detection/non-detection of poaching signs directly (Moore et al 2018). However, few studies account for the imperfect detection in the occupancy of poachers (Critchlow et al 2015, Moore et al 2018.…”

Section: Introductionmentioning

confidence: 99%

Inferring wildlife poaching in southeast Asia with multispecies dynamic occupancy models

Marescot

Lyet

Singh³

et al. 2019

Ecography

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Determining the 'space race' between co-occurring species is crucial to understand the effects of interspecific interactions on the extinction risk of species threatened by poachers and predators. Dynamic two-species occupancy models provide a flexible framework to decompose complex species interaction patterns, while accounting for imperfect detection. These models can describe poachers-wildlife interactions, as they allow estimating occupancy, extinction and colonisation probabilities of wildlife conditional on the occurrence of poachers and vice versa. We applied our model to a case study on wildlife poaching in the eastern plains of Cambodia. We used co-occurrence data extracted from the database of the SMART partnership to study the distribution dynamics between poachers and six ungulate species pooled together into the tiger prey guild. We used four years of survey data reporting the locations of snares and of presence signs of the ungulates recorded by rangers during their monthly multi-patrolling sessions. Our results showed that a substantial proportion of the sites occupied by ungulate species went extinct over the years of the study while the proportion of sites colonised by poachers increased. We also showed, for the first time, that spatiotemporal heterogeneity in the patrolling effort explains a great deal of the variation in the detection of poachers and ungulates. Our approach provides practitioners with a flexible and robust tool to assess conservation status of species and extinction risk of wildlife populations. It can assist managers in better evaluating, learning and adapting the patrolling strategies of rangers.

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What is the evidence that counter‐wildlife crime interventions are effective for conserving African, Asian and Latin American wildlife directly threatened by exploitation? A systematic map protocol

Rytwinski

Öckerman

Taylor

et al. 2021

Ecol Sol and Evidence

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Human activities are driving a global biodiversity crisis. In response, a broad range of conservation actions have been implemented. With finite resources available, and a rapidly narrowing window, the scientific and policy communities have acknowledged the need to better understand the effectiveness of interventions for conserving threatened species. Given the recent emphasis on the use of counter wildlife crime interventions (i.e. those that directly protect wildlife from illegal harvest, detect and sanction rule‐breakers, and interdict and control illegal wildlife commodities), there is a clear need to summarize the available evidence on biological and threat reduction outcomes of such actions to help make evidence‐informed management and funding decisions. Here, we present a protocol for a systematic map that will collate the existing body of literature addressing the effectiveness of counter‐wildlife crime interventions for protecting targeted species. Our focus will be on select species or species groups directly threatened by exploitation (i.e. illegal harming whether by harvest as a resource or for control/persecution) and native to Africa, Asia and Latin America, which are regions that have experienced significant wildlife populations declines. The systematic map will aim to capture available evidence found in commercially published and grey literature. We will search for the literature using four publication databases, Google Scholar, 36 specialist websites and databases and sources identified through a call for evidence among relevant networks. Eligibility screening will be conducted at two stages: (1) title and abstract and (2) full text. Relevant information from included papers will be extracted and entered into a searchable, coded database (MS‐Excel). Narrative synthesis and descriptive statistics will describe the key characteristics of the relevant evidence base (e.g. geographic location, species, interventions, direct threats, outcomes and study designs). Using visual heat maps, we will identify key knowledge gaps warranting further research and clusters of evidence that could serve as topics for future systematic reviews. The resulting map will guide further exploration on evaluating the effectiveness of counter‐wildlife crime interventions, and aid in building an evidence base that supports both management and funding decisions to ensure efficient use of limited resources and maximal conservation benefits.

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Are ranger patrols effective in reducing poaching‐related threats within protected areas?

Cited by 75 publications

References 50 publications

Detecting deterrence from patrol data

Detecting deterrence from patrol data

Inferring wildlife poaching in southeast Asia with multispecies dynamic occupancy models

What is the evidence that counter‐wildlife crime interventions are effective for conserving African, Asian and Latin American wildlife directly threatened by exploitation? A systematic map protocol

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