Locally adaptive aggregation of organisms under death risk in rock-paper-scissors models

TL;DR

This study uses stochastic simulations of a spatial rock-paper-scissors model to show that locally adaptive aggregation based on environmental danger levels can enhance biodiversity and reduce death risk, depending on the aggregation threshold and sensory perception.

Contribution

It introduces a novel adaptive aggregation strategy based on local danger detection in spatial rock-paper-scissors models, demonstrating its effects on biodiversity and spatial organization.

Findings

Aggregation benefits when danger threshold is below 30% opponent density.

Perception of longer distances improves aggregation effectiveness.

Adaptive aggregation promotes biodiversity even with limited organism mobility.

Abstract

We run stochastic simulations of the spatial version of the rock-paper-scissors game, considering that individuals use sensory abilities to scan the environment to detect the presence of enemies. If the local dangerousness level is above a tolerable threshold, individuals aggregate instead of moving randomly on the lattice. We study the impact of the locally adaptive aggregation on the organisms' spatial organisation by measuring the characteristic length scale of the spatial domains occupied by organisms of a single species. Our results reveal that aggregation is beneficial if triggered when the local density of opponents does not exceed $30\%$; otherwise, the behavioural strategy may harm individuals by increasing the average death risk. We show that if organisms can perceive further distances, they can accurately scan and interpret the signals from the neighbourhood, maximising the effects of the locally adaptive aggregation on the death risk. Finally, we show that the locally adaptive aggregation behaviour promotes biodiversity independently of the organism's mobility. The coexistence probability rises if organisms join conspecifics, even in the presence of a small number of enemies. We verify that our conclusions hold for more complex systems by simulating the generalised rock-paper-scissors models with five and seven species. Our discoveries may be helpful to ecologists in understanding systems where organisms' self-defence behaviour adapts to local environmental cues.