Wild meat trade over the last 45 years in the Peruvian Amazon

The trade in wild meat is an important economic component of rural people's livelihoods, but it has been perceived to be among the main causes of the decline of wildlife species. Recently, the COVID-19 pandemic has brought to light an additional concern of wildlife markets as a major human-health challenge. We analyzed data from the largest longitudinal monitoring (1973-2018) of the most important urban wild-meat markets in Iquitos, Peru, to examine the trends in and impacts of these markets on people's livelihoods. Over the last 45 years, wild meat sales increased at a rate of 6.4 t/year (SD 2.17), paralleling urban population growth. Wild meat sales were highest in 2018 (442 t), contributing US$2.6 million (0.76%) to the regional gross domestic product. Five species of ungulates and rodents accounted for 88.5% of the amount of biomass traded. Vulnerable and Endangered species represented 7.0% and 0.4% of individuals sold, respectively. Despite growth in sales, the contribution of wild meat to overall urban diet was constant: 1-2%/year of total meat consumed. This result was due to greater availability and higher consumption of cheaper meats (e.g., in 2018, poultry was 45.8% cheaper and was the most consumed meat) coupled with the lack of economic incentives to harvest wild meat species in rural areas. Most wild meat was sold salted or smoked, reducing the likelihood of foodborne diseases. Community-based wildlife management plans and the continued trade bans on primates and threatened taxa may avoid biodiversity loss. Considering the recent COVID-19 pandemic, future management plans should include potential viral hosts and regulation and enforcement of hygiene practices in wild-meat markets.

Understanding complex drivers of wildlife crime to design effective conservation interventions

In conservation understanding the drivers of behavior and developing robust interventions to promote behavioral change is challenging and requires a multifaceted approach. This is particularly true for efforts to address illegal wildlife use, where pervasive-and sometimes simplistic-narratives often obscure complex realities. We used an indirect questioning approach, the unmatched count technique, to investigate the drivers and prevalence of wildlife crime in communities surrounding 2 national parks in Uganda and combined scenario interviews and a choice experiment to predict the performance of potential interventions designed to tackle these crimes. Although poverty is often assumed to be a key driver of wildlife crime, we found that better-off households and those subject to human-wildlife conflict and those that do not receive any benefits from the parks' tourism revenue sharing were more likely to be involved in certain types of wildlife crime, especially illegal hunting. The interventions predicted to have the greatest impact on reducing local participation in wildlife crime were those that directly addressed the drivers including, mitigating damage caused by wildlife and generating financial benefits for park-adjacent households. Our triangulated approach provided insights into complex and hard-to-access behaviors and highlighted the importance of going beyond single-driver narratives.

Audience segmentation to improve targeting of conservation interventions for hunters

Audience segmentation could help improve the effectiveness of conservation interventions. Marketers use audience segmentation to define the target audience of a campaign. The technique involves subdividing a general population into groups that share similar profiles, such as sociodemographic or behavioral characteristics. Interventions are then designed to target the group or groups of interest. We explored the potential of audience segmentation for use in defining conservation target groups with a case study of hunters in Liberia. Using 2 data sets describing households (n = 476) and hunters (n = 205), we applied a clustering method in which infinite binomial mixture models group hunters and households according to livelihood and behavior variables and a simple method to define target groups based on hunting impact (hunting households and high-impact hunters). Clusters of hunters and households differed in their experiences with confiscation of catch at roadblocks and participation in livelihood-support programs, indicating that these interventions operate unevenly across subsets of the population. By contrast, the simple method masked these insights because profiles of hunting households and high-impact hunters were similar to those of the general population. Clustering results could be used to guide the development of livelihood and regulatory interventions. For example, a commonly promoted agricultural activity, cocoa farming, was practiced by only 2% (out of 87) of the largest hunter cluster of nonlocal gun hunters but was prevalent among local trappers, suggesting that assistance aimed at cocoa farmers is less appropriate for the former group. Our results support the use of audience segmentation across multiple variables to improve targeted intervention designs in conservation.

Detecting deterrence from patrol data

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.

Hunting for common ground between wildlife governance and commons scholarship

Wildlife hunting is essential to livelihoods and food security in many parts of the world, yet present rates of extraction may threaten ecosystems and human communities. Thus, governing sustainable wildlife use is a major social dilemma and conservation challenge. Commons scholarship is well positioned to contribute theoretical insights and analytic tools to better understand the interface of social and ecological dimensions of wildlife governance, yet the intersection of wildlife studies and commons scholarship is not well studied. We reviewed existing wildlife-hunting scholarship, drawing on a database of 1,410 references, to examine the current overlap with commons scholarship through multiple methods, including social network analysis and deductive coding. We found that a very small proportion of wildlife scholarship incorporated commons theories and frameworks. The social network of wildlife scholarship was densely interconnected with several major publication clusters, whereas the wildlife commons scholarship was sparse and isolated. Despite the overarching gap between wildlife and commons scholarship, a few scholars are studying wildlife commons. The small body of scholarship that bridges these disconnected literatures provides valuable insights into the understudied relational dimensions of wildlife and other overlapping common-pool resources. We suggest increased engagement among wildlife and commons scholars and practitioners to improve the state of knowledge and practice of wildlife governance across regions, particularly for bushmeat hunting in the tropics, which is presently understudied through a common-pool resource lens. Our case study of the Republic of Congo showed how the historical context and interrelationships between hunting and forest rights are essential to understanding the current state of wildlife governance and potential for future interventions. A better understanding of the interconnections between wildlife and overlapping common-pool resource systems may be key to understanding present wildlife governance challenges and advancing the common-pool resource research agenda.

A spatial approach to combatting wildlife crime

Poaching can have devastating impacts on animal and plant numbers, and in many countries has reached crisis levels, with illegal hunters employing increasingly sophisticated techniques. We used data from an 8-year study in Savé Valley Conservancy, Zimbabwe, to show how geographic profiling-a mathematical technique originally developed in criminology and recently applied to animal foraging and epidemiology-can be adapted for use in investigations of wildlife crime. The data set contained information on over 10,000 incidents of illegal hunting and the deaths of 6,454 wild animals. We used a subset of data for which the illegal hunters' identities were known. Our model identified the illegal hunters' home villages based on the spatial locations of the hunting incidences (e.g., snares). Identification of the villages was improved by manipulating the probability surface inside the conservancy to reflect the fact that although the illegal hunters mostly live outside the conservancy, the majority of hunting occurs inside the conservancy (in criminology terms, commuter crime). These results combined with rigorous simulations showed for the first time how geographic profiling can be combined with GIS data and applied to situations with more complex spatial patterns, for example, where landscape heterogeneity means some parts of the study area are less likely to be used (e.g., aquatic areas for terrestrial animals) or where landscape permeability differs (e.g., forest bats tend not to fly over open areas). More broadly, these results show how geographic profiling can be used to target antipoaching interventions more effectively and more efficiently and to develop management strategies and conservation plans in a range of conservation scenarios.