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We quantified the vigilance levels of elk (Cervus elaphus) preyed on by wolves (Canis lupus) in Yellowstone National Park, between January and May in 2005 and 2006, and used Akaike's information criterion to compare a set of 38 regression models for vigilance levels. These models combined up to 9 predictor variables of 3 types: characteristics of the prey group (herd size and composition), characteristics of the predator (wolf pack size, distance away, and the presence/absence of a kill), and characteristics of the local environment (distance to woodland edges, snow depth, and snow cover). The set of models spanned a range of complexity from simple univariate models to complex combinations with up to 3 variables of each type. Complex models incorporating the characteristics of the wolf pack, the structure of the elk herd, and the environmental conditions had higher information content than simple models. Although univariate models of vigilance detect significant relationships, they have low information content relative to multivariate models. These results show that elk assesses factors of several types when assessing risk and deciding how much time to allocate to vigilance. In particular, we found that all well-supported models of vigilance included several “prey” variables and several “predator” variables. This result highlights the need to consider information about predators when trying to explain variation in vigilance levels in prey.
Liley et al. (Thu,) studied this question.