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Two simple movement mechanisms for spatial division of labour in social insects


Richardson, Thomas; Stroeymeyt, Nathalie; Crespi, Alessandro; Keller, Laurent (2022), Two simple movement mechanisms for spatial division of labour in social insects, Dryad, Dataset,


Many animal species divide space into a patchwork of home ranges, yet there is little consensus on the mechanisms individuals use to maintain fidelity to particular locations. Theory suggests that animal movement could be based upon simple behavioural rules that use local information such as olfactory deposits, or global strategies, such as long-range biases toward landmarks. However, empirical studies have rarely attempted to distinguish between these mechanisms. Here, we perform individual tracking experiments on four species of social insects, and find that colonies consist of different groups of workers that inhabit separate but partially-overlapping spatial zones. Our trajectory analysis and simulations suggest that worker movement is consistent with two local mechanisms: one in which workers increase movement diffusivity outside their primary zone, and another in which workers modulate turning behaviour when approaching zone boundaries. Parallels with other organisms suggest that local mechanisms might represent a universal method for spatial partitioning in animal populations.


Individual trajectories collected by automated tracking using barcode tags. 

See the Methods section in the main paper, the Supporting Information and the Nature Reporting Summary for details on the tracking.

Usage notes

This repository contains the raw data for the publication:

Richardson, T.O., Stroeymeyt, N.S., Crespi, A., & Keller, L. "Two simple movement mechanisms for spatial division of labour in social insects". Nature Communications. In press.

Code for constructing the bipartite spatial networks, and for the simulations can be found in the following Zenodo repository:


FP7 People: Marie-Curie Actions, Award: 30114

ERC, Award: 802628

ERC, Award: 249375

ERC, Award: 741491