Many-Eyes and Sentinels in Selfish and Cooperative Groups

TL;DR

This paper presents a unified analytical framework explaining when animals adopt many-eyes or sentinel vigilance strategies based on how vigilance costs scale with effort, applicable to both selfish and cooperative groups.

Contribution

It introduces a minimal-assumption model showing that many-eyes and sentinel strategies are solutions to the same problem, determined by cost functions and applicable to different social contexts.

Findings

Strategies depend on cost function shape: convex costs favor many-eyes, concave costs favor sentinels.

Both selfish and cooperative behaviors follow the same strategic principles.

Model explains behavioral switching and edge effects in vigilance.

Abstract

Collective vigilance describes how animals in groups benefit from the predator detection efforts of others. Empirical observations typically find either a many-eyes strategy with all (or many) group members maintaining a low level of individual vigilance, or a sentinel strategy with one (or a few) individuals maintaining a high level of individual vigilance while others do not. With a general analytical treatment that makes minimal assumptions, we show that these two strategies are alternate solutions to the same adaptive problem of balancing the costs of predation and vigilance. Which strategy is preferred depends on how costs scale with the level of individual vigilance: many-eyes strategies are preferred where costs of vigilance rise gently at low levels but become steeper at higher levels (convex; e.g. an open field); sentinel strategies are preferred where costs of vigilance rise steeply at low levels and then flatten out (concave; e.g. environments with vantage points). This same dichotomy emerges whether individuals act selfishly to optimise their own fitness or cooperatively to optimise group fitness. The model is extended to explain discrete behavioural switching between strategies and differential levels of vigilance such as edge effects.