Individual foraging specialization and success change with experience in a virtual predator-prey system

This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.

Add a Comment

You must log in to post a comment.


Comments

There are no comments or no comments have been made public for this article.

Downloads

Download Preprint

Supplementary Files
Authors

Maxime Fraser Franco , Francesca Francesca Santostefano, Julien G. A. Martin, Clint D. Kelly , Pierre-Olivier Montiglio

Abstract

The capacity of predators to match their tactic to their prey and to optimize their skills at implementing a given tactic are expected to drive the outcome of predator-prey interactions. Hence, successive interactions of predators with their prey may result in increased flexibility in tactic use or in individual foraging specialization. Yet, there are limited empirical assessments showing links between past experience, foraging specialization, and hunting success at the individual level, due to the challenges of monitoring direct interactions in the wild. Here, we used a virtual predator-prey system (the game Dead by Daylight) to investigate how individual predator foraging specialization and success developed across repeated interactions with their prey. We found that 68% of predators became either increasingly specialized by always moving at a fast pace, or flexible by transitioning between slow and fast speeds. The predators’ strategies were partially matched to their prey’s speed, suggesting that changes in hunting behaviour were driven by repeated encounters with their prey. Flexible and specialist foragers achieved similar success overall. Hence, our findings suggest that experience may promote behavioural diversification in predator-prey systems.

DOI

https://doi.org/10.32942/X27H0Z

Subjects

Behavior and Ethology, Biodiversity, Ecology and Evolutionary Biology

Keywords

foraging behaviour, reciprocal behavioural plasticity, learning, Antipredator behaviour, virtual ecology, Dead by Daylight

Dates

Published: 2024-11-27 11:09

License

CC-BY Attribution-NonCommercial 4.0 International

Additional Metadata

Language:
English

Conflict of interest statement:
The authors declare no conflict of interest

Data and Code Availability Statement:
The data and code is freely available on this GitHub repository : https://github.com/quantitative-ecologist/experience-hunting-tactics