Effects of integrated conservation–development projects on unauthorized resource use in Volcanoes National Park, Rwanda: a mixed-methods spatio-temporal approach

Bernhard, K., Smith, T.ORCID logo, Sabuhoro, E., Nyandwi, E. & Munanura, I. E. (2020). Effects of integrated conservation–development projects on unauthorized resource use in Volcanoes National Park, Rwanda: a mixed-methods spatio-temporal approach. Oryx, https://doi.org/10.1017/S0030605319000735
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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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