Jennifer N. Solomon

Estimating Illegal Resource Use at a Ugandan Park with the Randomized Response Technique

Illegal resource use is a major threat to conservation in protected areas throughout the world, yet accurately estimating the number of poachers has been difficult. People violating the law seldom identify themselves for fear of retribution; thus quantifying illegal resource use is constrained by methodological problems. We evaluate the effectiveness of the randomized response technique (RRT) with a population that is partially illiterate to assess the extent of illegal resource use at Kibale National Park, Uganda. RRT is unique in allowing respondents to disclose sensitive information because the interviewer can not ascertain an individuals true response to the incriminating question. We found estimates of six types of illegal resource use when measured by RRT were significantly higher than when measured by direct questioning. This method offers a potentially powerful tool for understanding conservation threats in the developing world.

Contrasting perceptions of ecosystem services of an African forest park

SUMMARY Traditionally, conservation programmes assume that local peoples’ support for parks depends on receiving material benefits from foreign exchange, tourism, development and employment. However, in the case of forest parks in Africa, where annual visitation can be small, local support may instead result from ecosystem services. Kibale National Park, a forest park in Uganda, demonstrates that people appreciate parks in ways that are seldom cited nor explored. Public perceptions of benefits accrued from Kibale were explored using two different sampling techniques: a community census and a geographic sample. In both surveys, over 50% of respondents perceived benefits provided by Kibale National Park, and over 90% of those who perceived benefits identified ecosystem services, whereas material benefits were cited less frequently. Multimodel selection on a suite of general linear models for the two different sampling methods provided a comparison of factors influencing perceptions of ecosystem services. Perceptions of Park benefits were influenced by geography, household and respondent characteristics, and perception of negative impacts from the Park. Perceived ecosystem benefits played an important role in the way the Park was

Fishing for a solution: can collaborative resource management reduce poverty and support conservation?

Protected area management in developing countries faces the challenges of building support for conservation among neighbouring residents and monitoring the social and ecological impacts of conservation programming. This study examined a collaborative resource management (CRM) programme at Kibale National Park (Uganda) that permits residents to fish inside the Park. Like other integrated conservation and development programmes, the goals are to help alleviate poverty and encourage support for conservation and conservation-related behaviours. The programmes impact was empirically analysed using an 81 item personal survey, with 94 CRM fishers and 91 comparison group respondents, and additional data from semi-structured interviews and document review. Fishers’ annual income was significantly greater (median = US

Active and Passive Bait-fishing by Black-Crowned Night Herons

376.02 yr −1 ) than that of the comparison group (median = US

Understanding the drivers of sensitive behavior using Poisson regression from quantitative randomized response technique data

196.19 yr −1 ; p p

Measuring and monitoring illegal use of natural resources.

Abstract Previous research reports bait-fishing in seven different species of ardeids. Our observations of Black-crowned Night Herons (Nycticorax nycticorax) on the island of Oahu, Hawaii, USA are the first to detail both passive and active bait-fishing in the same species. These observations provide support for the hypothesis that passive bait-fishing is a precursor to development of active bait-fishing methods in wading birds.

The Pigeon Paradox: Dependence of Global Conservation on Urban Nature

Understanding sensitive behaviors—those that are socially unacceptable or non-compliant with rules or regulations—is essential for creating effective interventions. Sensitive behaviors are challenging to study, because participants are unlikely to disclose sensitive behaviors for fear of retribution or due to social undesirability. Methods for studying sensitive behavior include randomized response techniques, which provide anonymity to interviewees who answer sensitive questions. A variation on this approach, the quantitative randomized response technique (QRRT), allows researchers to estimate the frequency or quantity of sensitive behaviors. However, to date no studies have used QRRT to identify potential drivers of non-compliant behavior because regression methodology has not been developed for the nonnegative count data produced by QRRT. We develop a Poisson regression methodology for QRRT data, based on maximum likelihood estimation computed via the expectation-maximization (EM) algorithm. The methodology can be implemented with relatively minor modification of existing software for generalized linear models. We derive the Fisher information matrix in this setting and use it to obtain the asymptotic variance-covariance matrix of the regression parameter estimates. Simulation results demonstrate the quality of the asymptotic approximations. The method is illustrated with a case study examining potential drivers of non-compliance with hunting regulations in Sierra Leone. The new methodology allows assessment of the importance of potential drivers of different quantities of non-compliant behavior, using a likelihood-based, information-theoretic approach. Free, open-source software is provided to support QRRT regression.