The conservation of endangered species can benefit from a clear understanding of the quantity and distribution of their main foods. The population of mountain gorillas (Gorilla beringei beringei) living in the Virunga Massif of Rwanda, Uganda, and Democratic Republic of Congo has doubled in size since the 1980s, due to success in conservation efforts in and around their habitat. However, this increase in population size along with pressures on gorilla habitat raises concerns about spatial-temporal changes in the gorillas' food plants. This study modelled the abundance and distribution of gorilla food species in the Virunga Massif. A total of 1050 vegetation recordings were collected on five plant species that are known to be frequently consumed by gorillas in one region of the Virungas, the Karisoke area. Two types of datasets collected along vegetation zones were combined: one with plant abundance expressed with Braun-Blanquet scores; and the other with abundance expressed as biomass. Moreover, ecological characteristics of locations where these species occur were extracted from satellite imagery. Analysis of variance and linear regression models were used to examine relationships between food species abundances and predictor variables. Subsequently, maps for the food species were created using boosted regression trees (BRTs). The abundance of species differed across vegetation zones, and the differences were statistically significant among vegetation zones with enough species observations. The accuracy of the BRTs indicated greater than random predictions (AUC > 0.65). This study shows the suitable areas for these gorilla food species and relevant ecological variables determining their distribution. The results provide insights into habitat occupancy by mountain gorillas, and help to design a baseline for monitoring changes in the abundance of gorilla food species under changing climate and anthropogenic pressure.
IntroductionCommunities living adjacent to protected areas in Africa are characterized by high poverty rates and their well-being often depends on park resources. This often results in forest degradation and decline in wildlife populations, for example due to illegal hunting for bush meat. To counter this challenge in Rwanda, a tourism revenue sharing program was initiated in 2005, with 5% (doubled to 10% in 2017) of the park gate fees invested in community development projects. We evaluated the effectiveness of this tourism revenue sharing from 2005 to 2017, targeting communities adjacent to Nyungwe National Park located in south-western Rwanda.MethodsWe used questionnaires addressed to members of community associations and local government in 24 sectors around Nyungwe National Park. Additionally, data on illegal resource use and socio-economic status of the surrounding communities were obtained to quantitatively triangulate and draw insights from communities’perceptions. Using spatial analyses and spatial regression, we mapped trends in illegal activities relative to socio-economic characteristics.Results and discussionBoth the qualitative and quantitative results indicate that the tourism revenue sharing program has not fully succeeded in improving community well-being around Nyungwe National Park. The tourism revenue sharing can consider targeting areas that demonstrate more need and reassessing prioritization of interventions supported by the program to achieve both poverty reduction around Nyungwe National Park and improved conservation outcomes in this protected area.
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