Decoding alarm signal propagation of seed-harvester ants using automated movement tracking and supervised machine learning.

ABSTRACT: Alarm signal propagation through ant colonies provides an empirically tractable context for analysing information flow through a natural system, with useful insights for network dynamics in other social animals. Here, we develop a methodological approach to track alarm spread within a group of harvester ants, Pogonomyrmex californicus. We initially alarmed three ants and tracked subsequent signal transmission through the colony. Because there was no actual standing threat, the false alarm allowed us to assess amplification and adaptive damping of the collective alarm response. We trained a random forest regression model to quantify alarm behaviour of individual workers from multiple movement features. Our approach translates subjective categorical alarm scores into a reliable, conti

SUBMITTER: Guo X 

PROVIDER: S-EPMC8790334 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature