Comparison of local ecological knowledge versus camera trapping to establish terrestrial wildlife baselines in community hunting territories within the Yangambi landscape in the Democratic Republic of Congo




Wildlife surveys, community occupancy, Africa, Local Knowledge, Camera traps, tropical forests


Baseline population data are fundamental to the development of wildlife management plans and are usually generated based on field surveys using sampling tools such as camera traps (CT). However, this method can be costly and ineffective with rare species or in wildlife-depleted areas. An alternative is to complement baseline wildlife population data with Local Ecological Knowledge (LEK)-based methods. We compared LEK and CT surveys in terms of their capacity to assess the status of terrestrial mammal species (richness, abundance, distribution) in the Yangambi landscape of the Democratic Republic of Congo. This region is heavily hunted and wildlife population densities are low. Species not captured by CT included naturally rare and endangered species that were instead recorded by interviewed hunters. LEK and CT abundance metrics were positively related for all species. For all medium- and large-sized species, the number of positive sites from LEK outnumbered the number of positive sites from the CT survey, indicating that hunters detected species over larger areas. Overall, our comparison suggests that LEK and CT methods can be used interchangeably to provide reliable information on relative abundance. Nevertheless, LEK appears as a more cost- effective alternative to camera trapping, particularly for hunted and depleted tropical forests.


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How to Cite

van Vliet, N., Rovero, F., Muhindo, J., Nyumu, J., Mbangale, E., Nziavake, S., Cerutti, P., Nasi, R., & Quintero, S. (2023). Comparison of local ecological knowledge versus camera trapping to establish terrestrial wildlife baselines in community hunting territories within the Yangambi landscape in the Democratic Republic of Congo. Ethnobiology and Conservation, 12.



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