Implications of taxonomic bias for human–carnivore conflict mitigation

The Integral Nature of Encounter Rate in Predicting Livestock Depredation Risk

Carnivore depredation of livestock is one of the primary drivers of human-carnivore conflict globally, threatening the well-being of livestock owners, and fueling large carnivore population declines. Interventions designed to reduce carnivore depredation typically center around predictions of depredation risk. However, these spatial risk models tend to be informed by data depicting the number of livestock attacked by carnivores. Importantly, such models omit key stages in the predation sequence which are required to predict predation risk, or in this case depredation risk. Applying the classic predation risk model defined by Lima and Dill demonstrates that depredation risk is dependent upon quantifying the rates at which carnivores encounter livestock before attacking. However, encounter rate is challenging to estimate, necessitating novel data collection systems. We developed and applied such a system to quantify carnivore-livestock encounters at livestock corrals (i.e., bomas) across a 9-month period in Central Kenya. Concurrently, we monitored the number of livestock attacked by carnivores at these bomas. We calculated carnivore-livestock encounter rates, attack rates, and depredation risk at the boma. We detected 1,383 instances in which carnivores encountered livestock at the bomas. However, we only recorded seven attacks. We found that the encounter rate and attack rate for spotted hyenas were almost six and three times higher than that for any other species, respectively. Consequently, spotted hyenas posed the greatest depredation risk for livestock at the boma. We argue that better understanding of carnivore-livestock encounter rates is necessary for effective prediction and mitigation of carnivore depredation of livestock.