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.

The forests of Central Africa constitute the continent’s largest continuous tract of forest, maintained in part by over 200 protected areas across six countries with varying levels of restriction and enforcement. Despite protection, these Central African forests are subject to a multitude of overlapping proximate and underlying drivers of deforestation and degradation, such as conversion to small-scale agriculture. This pilot study explored whether transboundary protected area complexes featuring mixed resource-use restriction categories are effective in reducing the predicted disturbance risk to intact forests attributed to small-scale agriculture. At two transboundary protected area complex sites in Central Africa, we used Google Earth Engine and a suite of earth observation (EO) data, including a dataset derived using a replicable, open-source methodology stemming from a regional collaboration, to predict the increased risk of deforestation and degradation of intact forests caused by small-scale agriculture. For each complex, we then statistically compared the predicted increased risk between protected and unprotected forests for a stratified random sample of 2 km sites (n = 4000). We found varied effectiveness of protected areas for reducing the predicted risk of deforestation and degradation to intact forests attributed to agriculture by both the site and category of protected areas within the complex. Our early results have implications for sustainable agriculture development, forest conservation, and protected areas management and provide a direction for future research into spatial planning. Spatial planning could optimize the configuration of protected area types within transboundary complexes to achieve both forest conservation and sustainable agricultural production outcomes.

Illegal activities pose challenges to the conservation of mountain gorillas (Gorilla beringei beringei) across the Virunga Landscape (VL). This paper investigates the relationship between household livelihood security (HLS) and the perceived prevalence of illegal activities across the VL. Results from a survey of 223 residents of areas adjacent to the VL in Uganda and Rwanda reveal varied links between human livelihoods and illegal activities threatening wildlife. For example, while poaching appears to be negatively associated with health and financial security among residents, it is positively associated with education security, indicating that education may be contributing to illegal activities threatening wildlife. Food security constraints were also found to be significantly associated with poaching. Finally, findings suggest that although HLS investments are essential in improving local community livelihoods, only food and financial security are the most effective means of reducing illegal activities in Virunga.

The forests of the Greater Mekong Subregion, consisting of Myanmar, Thailand, Cambodia, Laos and Vietnam, are under high pressure from economic development and exploitation of natural resources, including but not limited to land concession, smallholder plantations and commercial agriculture, agroforestry development, mining, and road infrastructure development. While these threats are well-known, the magnitude and dynamics of their individual and interacting effects on forest cover are not fully understood. This pilot study aims to apply existing, publicly available macro, micro, and socioeconomic data in addition to remote sensing forest cover data to explore economic determinants of deforestation in the Greater Mekong, using the case of the Central Annamites Landscape (CAL) ecoregion of Vietnam. A longitudinal panel was constructed for 2000-2017, containing 1,658 observations for 144 variables across 95 Tier 2 (district) administrative units in CAL from 2000-2017 for modeling macroeconomic and socioeconomic conditions against annual tree cover loss aggregated to the Tier 2 administrative unit. The first phase of the study used tiered spatial regression analysis to correlatively identify which commodities, economic development activities, and social conditions have historically had the greatest effect on forest cover by magnitude in CAL. Based on first phase results, we selected a subset of these determinants for scenario modelling to predict possible deforestation outcomes given certain economic scenarios. The results, among others, indicate that, when spatially collocated, high poverty rates and smaller scale agricultural land conversion are key immediate determinants of deforestation. This therefore provides evidence to support programs targeting rubber, acacia harvesting, artisanal mining, and land conversion for cash crop plantations. Education is also key immediate socioeconomic factor, as poverty rate is consistently associated with tree cover loss and increased educational attainment is consistently associated with reduced tree cover loss, at approximately 12 ha per percentage increase in secondary school graduation. On the macro level, economic growth in China and Vietnam are correlatively associated with tree cover loss, as are rising trade in Myanmar and Laos. This study provides a methodological contribution to the current academic literature identifying socioeconomic dimensions of deforestation through spatial econometric analysis and scenario modelling at the landscape level. For practitioner work, this pilot provides a model or tool for strategic planning of conservation interventions in light of economic conditions and factors.