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Many-eyes and sentinels in selfish and cooperative groups
Charlie Pilgrim1, Andrew M Bate1, Anna Sigalou2
1Department of Statistics, School of Mathematics, University of Leeds, Leeds LS2 9JT, United Kingdom.
Summary
Animals in groups use collective vigilance for predator detection. This study reveals that either a "many-eyes" or "sentinel" strategy is favored based on how vigilance costs change with environment type.
Area of Science:
- Behavioral Ecology
- Evolutionary Biology
- Game Theory
Background:
- Collective vigilance enhances predator detection in social animals.
- Two main strategies exist: many-eyes (low individual vigilance) and sentinel (high individual vigilance).
Purpose of the Study:
- To analytically model the adaptive problem of balancing predation and vigilance costs.
- To determine the conditions favoring many-eyes versus sentinel strategies.
Main Methods:
- Developed an analytical model with minimal assumptions.
- Investigated how cost scaling with vigilance level influences strategy preference.
- Considered both selfish and cooperative fitness optimization.
Main Results:
- Many-eyes strategies are favored when vigilance costs increase steeply at higher levels (convex costs, e.g., open fields).
- Sentinel strategies are favored when vigilance costs increase steeply at low levels then plateau (concave costs, e.g., vantage points).
- Strategy preference is independent of whether individuals optimize personal or group fitness.
Conclusions:
- The choice between many-eyes and sentinel strategies is an adaptive solution to vigilance costs.
- Environmental factors, specifically the shape of vigilance cost functions, dictate the optimal strategy.
- The model explains behavioral switching, edge effects, and turn-taking in collective vigilance.