By Megan McDaniels, Erin Buchholtz, Graham McCulloch, Anna Songhurst, and Amanda Stronza.
Read the full paper here.
Negative interactions between people and wildlife are a complex global challenge, and we can use information from different sources to understand and address them. In some regions of sub-Saharan Africa, endangered African savanna elephants consume the crops people are growing, which can lead to loss of food, livelihoods, and even death for both people and elephants. Because long-term measurements and monitoring of human-wildlife conflict and wildlife populations are often absent in rural areas, it is necessary to bring together multiple types of data to build a full picture of the underlying patterns, drivers, and potential solutions to conflict. Data types can include formal reports of conflict as well as discussions with community members whose experiences with wildlife form valuable local ecological knowledge.
In this study, we examined human-elephant conflict in the Western Panhandle of the Okavango Delta in Botswana. This region includes key elephant habitat as well as several subsistence farming communities. We used data from governmental records of human-elephant conflict from 2008 to 2016, interviews with local farmers in 2016 that included memories as far back as the 1990s, and surveys of elephant damage to farms in 2016. These different data sources revealed that incidents of human-elephant conflict and the elephant population have been increasing since the 1990s. Crop consumption and damage was the main form of conflict, and the amount of damage was most strongly linked with the size of the raiding elephant herd, rather than other factors such as the types of crops planted. The majority of conflict occurred in the mid to late rainy season when crops were ripening.
Not only did we gain detailed insight into the patterns and trends in human-elephant conflict in the Western Panhandle, but we also found that the different data types built on each other and were able to expand the scope of our study across time and space in ways that no single data source could have accomplished. Our approach is replicable in other rural areas experiencing human-wildlife conflict, and can be an important precursor to effective community-led conflict mitigation.