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This study supplements spatial panel econometrics techniques with qualitative GIS to analyse spatio-temporal changes in the distribution of integrated conservation–development projects relative to poaching activity and unauthorized resource use in Volcanoes National Park, Rwanda. Cluster and spatial regression analyses were performed on data from ranger monitoring containing > 35,000 combined observations of illegal activities in Volcanoes National Park, against tourism revenue sharing and conservation NGO funding data for 2006–2015. Results were enriched with qualitative GIS analysis from key informant interviews. We found a statistically significant negative linear effect of overall integrated conservation–development investments on unauthorized resource use in Volcanoes National Park. However, individually, funding from Rwanda's tourism revenue sharing policy did not have an effect in contrast to the significant negative effect of conservation NGO funding. In another contrast between NGO funding and tourism revenue sharing funding, spatial analysis revealed significant gaps in revenue sharing funding relative to the hotspots of illegal activities, but these gaps were not present for NGO funding. Insight from qualitative GIS analysis suggests that incongruity in prioritization by decision makers at least partly explains the differences between the effects of revenue sharing and conservation NGO investment. Although the overall results are encouraging for integrated conservation–development projects, we recommend increased spatial alignment of project funding with clusters of illegal activities, which can make investment decision-making more data-driven and projects more effective for conservation.

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L'Hoest's monkey's (Cercopithecus Ihoesti) are believed to be naturally infected with a simian immunodeficiency virus (SIV), termed SIVIho, but only a handful of isolates, all derived from captive animals from the Democratic Republic of Congo (DCR), have thus far been characterized. Here, we report the noninvasive detection and molecular characterization of SIVIho in a wild L'Hoest's monkey from the Nyungwe Forest in Rwanda. Screening four L'Hoest's monkey fecal samples collected opportunistically as part of a larger noninvasive survey of SIV prevalence in Nyungwe National Park we identified one to be vRNA positive. Reverse transcriptase polymerase chain reaction (RT-PCR) amplification of a subgenomic pol fragment (598 bp) identified a new SIVIho strain (RW30) that differed from previously reported SIVIho isolates in 17-22% of its nucleotide sequence. In a phylogenic tree of partial Pol protein sequences, RW30 fell well within the SIVIho radiation, but was not particularly closely related to any of the other strains. These results provide the first direct evidence that L'Hoewst's monkeys harbor SIVIho in the wild, that infection is prevalent in different areas of the species' habitat, and that geographically diverse SIVIho strains cluster in a single group according to their species of origin. L'Hoest's monkeys represent the third primate species for which the utility of noninvasive SIV testing has been documented.

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Research regarding tourism’s effect on the subjective well-being (SWB) of destination residents has provided important insight, but it generally has relied on indirect analyses and diverse measures. This study used livability theory and a novel contingent SWB method in which respondents directly reported anticipated SWB effects. This method is exploratory, but it provides greater confidence in causal relationships. Results from a general population survey in Oregon (USA) suggested the method functioned as intended. County-level population growth and visitor intensity predicted perceived current impacts of tourism. In turn, perceived impacts predicted change in SWB contingent on a vignette reflecting a 20% increase in tourists. Across all individuals and counties, average SWB changes were negative for the environment domain and positive for other domains. Practical implications are discussed, with the most positive SWB effects from tourism development expected to occur in counties with low visitor intensity, especially those with low population growth.