Abstract
Abstract
There has been extensive work on the predator–prey spatial game, with a focus on how prey spatially respond to predators and how predators respond spatially to the distribution of various prey. Central to this work is the distinction between actual risk of predation relative to landscape availability and determining what prey perceive as risky habitat and which areas predators perceive they might be successful relative to the amount of time they spend in these areas. Several models have been proposed to best quantify the predator–prey spatial game, with researchers are often focusing on where prey are at risk of encountering a predator, which is often treated as a representation of the landscape of fear. However, this viewpoint can oversimplify the predation process because it is difficult to integrate both predator and prey perspectives simultaneously. We leveraged two types of habitat selection functions (resource selection functions and latent selection difference functions) to create a multi‐perspective framework that simultaneously integrates data from both predator and prey, effectively capturing the predator–prey spatial game. The framework quantifies actual spatial risk (landscape perspective), spatial risk relative to prey use (prey perspective), resources where predators are particularly successful relative to their use (predator perspective), and the landscape of fear (predator resource selection). We applied this framework by relating neonatal white‐tailed deer (
Odocoileus virginianus
) kill site locations to GPS locations from bobcats (
Lynx rufus
), coyotes (
Canis latrans
), and female white‐tailed deer. Areas where fawns were at an elevated risk of predation relative to landscape availability were primarily driven by predator efficiency and sometimes by female deer selection of risky fawn habitats. We also found that female deer may be cognizant of increased risk of fawn predation in some habitats and may decrease their use of those risky areas accordingly. By considering these different perspectives of prey risk and predator success, these results shed light on the complexities that underlie predator–prey dynamics. Overall, our work highlights that predation risk can be assessed from several perspectives and that multiple habitat selection functions can generate a multi‐perspective assessment and provide a deeper understanding of the predator–prey spatial game.