Buchholtz, E., Fitzgerald, L., Songhurst, A., McCulloch, G. and Stronza, A., 2020. Experts and elephants: local ecological knowledge predicts landscape use for a species involved in human-wildlife conflict. Ecology and Society, 25(4). doi.org/10.5751/ES-11979-250426
Abstract
Local ecological knowledge (LEK) has been increasingly invoked in biodiversity monitoring and conservation efforts. Although methods involving LEK have become more widespread in ecology, it remains an undervalued source of information in understanding the ecology of wildlife in the context of human-wildlife conflict. People who regularly interact with wildlife, and often with notable consequences, as is the case with human-wildlife conflict, will likely build up ecological knowledge of that species. We gathered LEK on the landscape use of the African elephant (Loxodonta Africana) in a region where its range overlaps with human land use and results in conflict, the western Okavango Panhandle of Botswana. We interviewed community-defined local experts and used participatory ranking activities to gather information on landscape use of elephants. The scores from the rankings were then incorporated with environmental data following resource selection function methods common in ecology. The resulting LEK-based model had high predictive ability for elephant locations when modeled at a local scale (25 km, Spearman's rho = 0.98, P < 0.0001). We also calculated resource selection models using elephant telemetry data combined with the same environmental data as the LEK models. These models showed a complementary pattern, with better predictive ability at the regional scale (Spearman's rho = 0.98, P < 0.0001) than at the local scale (rho = 0.92, P < 0.0031). In addition to being used for the resource selection functions, each method provided different kinds of information on elephant landscape use. Our results support the use of LEK as a tool for understanding local patterns of wildlife landscape use in the context of human-wildlife conflict, where the knowledge can be used to complement other data across scales and the use of which can itself contribute to better conservation outcomes.