Abstract
People living in the Congo basin forest have developed a variety of ways to use natural resources. Thus, the increase in conservation projects must be accompanied by efforts to clarify the livelihood-related conditions of local people. This paper provided a detailed in- vestigation of the utilization of natural resources by the Bongando people living in the great ape habitat of the Democratic Republic of the Congo (DRC). Specifically, the paper examined food acquisition and consumption based on direct observations and measurements, and also discussed the adequacy of food assessment approaches. Quantitative data on food acquisition and consumption at the study site showed that the amount of carbohydrates consumed was adequate; however, less animal protein was consumed by those living at the study site than by people living in great ape habitats in Africa. This suggests that availability of animal protein fluctuates, and that the Bongando people follow a dual village/forest lifestyle. Cassava leaves and other vegetables are also important protein sources. Data on the food preferences of the Bongando indicate that they strongly prefer cassava as their staple, and that they engage in sophisticated ways of cultivating leaves for consumption as food. The data also reflect the Bongando people's strong preference for wild animals, and the fact that some people avoid eating livestock. Food preferences are important factors in the success of conservation projects, as it is crucial to find ways for local people to maintain adequate caloric and protein intake that are acceptable to the people themselves and to the projects. Therefore, research based on a food assessment approach should occur in parallel with research based on direct observations. Quantitative food assessment is useful because it provides data for an entire year for a large-scale population. However, it is also necessary to conduct preliminary research to obtain basic infor- mation about a population and its use of natural resources. Research designs must be developed based on the analysis, screening, and correction of data by researchers with a deep knowledge about the local livelihoods to prevent human error.
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