Profiling unauthorized natural resource users for better targeting of conservation interventions

Unauthorized use of natural resources is a key threat to many protected areas. Approaches to reducing this threat include law enforcement and integrated conservation and development (ICD) projects, but for such ICDs to be targeted effectively, it is important to understand who is illegally using which natural resources and why. The nature of unauthorized behavior makes it difficult to ascertain this information through direct questioning. Bwindi Impenetrable National Park, Uganda, has many ICD projects, including authorizing some local people to use certain nontimber forest resources from the park. However, despite over 25 years of ICD, unauthorized resource use continues. We used household surveys, indirect questioning (unmatched count technique), and focus group discussions to generate profiles of authorized and unauthorized resource users and to explore motivations for unauthorized activity. Overall, unauthorized resource use was most common among people from poor households who lived closest to the park boundary and farthest from roads and trading centers. Other motivations for unauthorized resource use included crop raiding by wild animals, inequity of revenue sharing, and lack of employment, factors that created resentment among the poorest communities. In some communities, benefits obtained from ICD were reported to be the greatest deterrents against unauthorized activity, although law enforcement ranked highest overall. Despite the sensitive nature of exploring unauthorized resource use, management‐relevant insights into the profiles and motivations of unauthorized resource users can be gained from a combination of survey techniques, as adopted here. To reduce unauthorized activity at Bwindi, we suggest ICD benefit the poorest people living in remote areas and near the park boundary by providing affordable alternative sources of forest products and addressing crop raiding. To prevent resentment from driving further unauthorized activity, ICDs should be managed transparently and equitably

A Novel Approach to Assessing the Prevalence and Drivers of Illegal Bushmeat Hunting in the Serengeti

Assessing anthropogenic effects on biological diversity, identifying drivers of human behavior, and motivating behavioral change are at the core of effective conservation. Yet knowledge of people's behaviors is often limited because the true extent of natural resource exploitation is difficult to ascertain, particularly if it is illegal. To obtain estimates of rule-breaking behavior, a technique has been developed with which to ask sensitive questions. We used this technique, unmatched-count technique (UCT), to provide estimates of bushmeat poaching, to determine motivation and seasonal and spatial distribution of poaching, and to characterize poaching households in the Serengeti. We also assessed the potential for survey biases on the basis of respondent perceptions of understanding, anonymity, and discomfort. Eighteen percent of households admitted to being involved in hunting. Illegal bushmeat hunting was more likely in households with seasonal or full-time employment, lower household size, and longer household residence in the village. The majority of respondents found the UCT questions easy to understand and were comfortable answering them. Our results suggest poaching remains widespread in the Serengeti and current alternative sources of income may not be sufficiently attractive to compete with the opportunities provided by hunting. We demonstrate that the UCT is well suited to investigating noncompliance in conservation because it reduces evasive responses, resulting in more accurate estimates, and is technically simple to apply. We suggest that the UCT could be more widely used, with the trade-off being the increased complexity of data analyses and requirement for large sample sizes

Advances in estimation by the item sum technique using auxiliary information in complex surveys

To collect sensitive data, survey statisticians have designed many strategies to reduce nonresponse rates and social desirability response bias. In recent years, the item count technique (ICT) has gained considerable popularity and credibility as an alternative mode of indirect questioning survey, and several variants of this technique have been proposed as new needs and challenges arise. The item sum technique (IST), which was introduced by Chaudhuri and Christofides (2013) and Trappmann et al. (2014), is one such variant, used to estimate the mean of a sensitive quantitative variable. In this approach, sampled units are asked to respond to a two-list of items containing a sensitive question related to the study variable and various innocuous, nonsensitive, questions. To the best of our knowledge, very few theoretical and applied papers have addressed the IST. In this article, therefore, we present certain methodological advances as a contribution to appraising the use of the IST in real-world surveys. In particular, we employ a generic sampling design to examine the problem of how to improve the estimates of the sensitive mean when auxiliary information on the population under study is available and is used at the design and estimation stages. A Horvitz-Thompson type estimator and a calibration type estimator are proposed and their efficiency is evaluated by means of an extensive simulation study. Using simulation experiments, we show that estimates obtained by the IST are nearly equivalent to those obtained using “true data” and that in general they outperform the estimates provided by a competitive randomized response method. Moreover, the variance estimation may be considered satisfactory. These results open up new perspectives for academics, researchers and survey practitioners, and could justify the use of the IST as a valid alternative to traditional direct questioning survey modes.Ministerio de Economía y Competitividad of SpainMinisterio de Educacion, Cultura y Deporteproject PRIN-SURWE