Predicting Prey Population Dynamics from Kill Rate, Predation Rate and Predator-Prey Ratios in three Wolf-Ungulate Systems

Scientific Disciplines
Biological Sciences - Terrestrial
Keywords
Yellowstone national park
yellowstone
University of Montana
wildlife management
gray wolf
Banff
Isle Royale
kill rate
predatorprey ratios
population dynamics
prey population
predation rate
prey population dynamics
Authors
Years
Volumes
Volume 18, No. 1-4

Predicting prey population dynamics from kill 
Rate, predation rate and predator-prey ratios in 
Three wolf-ungulate systems
Mark Hebblewhite*, Wildlife Biology Program, University of Montana, Missoula, MT, 59812
John Vucetich, School of Forest Resources and Environmental Science, Michigan Technological 
University, Houghton, MI 49931.
Doug Smith, Yellowstone Center for Resources, Wolf Project, PO Box 168, Yellowstone National 
Park,WY82190, USA;
Rolf O. Peterson, School of Forest Resources and Environmental Science, Michigan Technological 
University, Houghton, MI 49931.
Predation rate (PR), kill rate and predator-prey ratio’s are all thought to be fundamental 
statistics for understanding and managing predation. However, relatively little is known 
about how these statistics explain prey population dynamics. We assess these relationships 
across three systems where wolf–prey dynamics have been observed for 41 years (Isle 
Royale), 19 years (Banff) and 12 years (Yellowstone). Theoretical simulations indicate 
that kill rate can be related to PR in a variety of diverse ways that depend on the nature of 
predator–prey dynamics. These simulations also suggested that the ratio of predator to-prey 
is a good predictor of prey growth rate. The empirical relationships indicate that PR is not 
well predicted by kill rate, but is better predicted by the ratio of predator-to-prey. Kill rate 
is also a poor predictor of prey growth rate. However, PR and predator-prey ratio’s each 
explained significant portions of variation in prey growth rate for two of the three study 
sites. Our analyses offer two general insights. First, it remains difficult to judge whether to 
be more impressed by the similarities or differences among these 3 study areas. Second, our 
work suggests that kill rate and PR are similarly important for understanding why predation 
is such a complex process. We conclude with a review of potential management applications 
of predator-prey ratio’s and the assumptions required to understanding prey population 
dynamics.