Prey should hide more randomly when a predator attacks more persistently.

Area of Science:

• Behavioral Ecology
• Game Theory
• Predator-Prey Dynamics

Background:

• Prey animals face a critical decision when detected by predators: prioritize being difficult to locate or being difficult to capture if found.
• Previous models often simplified this dilemma, typically considering only a single pursuit event.

Purpose of the Study:

• To develop and analyze a mathematical model of predator-prey interactions in a repeated pursuit scenario.
• To investigate how the probability of repeated pursuit influences optimal evasion strategies for prey.

Main Methods:

• Modeled the predator-prey interaction as a zero-sum repeated game.
• The payoff was defined as the predator's probability of eventual capture.
• Analyzed the impact of repeated pursuit opportunities, linked to environmental factors like topography.

Main Results:

• A more random hiding strategy is advantageous for prey when the likelihood of repeated pursuit is high.
• This contrasts with single-pursuit models where random hiding is preferred under limited predator attention.
• The findings generalize search game theory to repeated game contexts.

Conclusions:

• The optimal prey strategy is context-dependent, shifting with the number of potential pursuit encounters.
• Environmental factors influencing pursuit repetition (e.g., topography) significantly impact evasion tactics.
• The model's predictions align with observed animal escape behaviors.