ALTAA: analysis of long-term activity patterns in ant colonies

Collective behaviours are a fascinating study area due to the emergent properties that can only arise in groups of interacting individuals. However, their quantitative study is often impaired by technical difficulties, creating either low-quality and sparse data, or impractical data amounts, particularly when capturing large groups over long periods of time. Common challenges arise from recording group members with as little obscuring of each other as possible, as well as in generating manageable data amounts with as high as possible information content. We here provide a multi-component system that allows to record, analyze and simulate the long-term spatiotemporal activity patterns of insect collectives, especially ant colonies. Our Ant Observing System, ALTAA, comprises a flat nest design to prevent occlusion of individuals, a recording system running on a low-power single-board-computer, and a set of computer programs performing quantitative analyses to guide the formation and validation of rules underlying the observed collective patterns. Our system is scalable in that it allows parallel, continuous observation of a high number of colonies using low memory space, with colony maintenance requirements (e.g. feeding, nest humidity) being achieved at lowest possible disturbance by the experimenter. We showcase the potential of the system in a study using the black garden ant, Lasius niger, where we analyze the spatiotemporal effects of different group size (1, 6, 10 ants), brood (larvae) presence or absence, as well as of different nest geometries, over a period of one week. We show that the ants motion activity has a weak periodicity in the range of 20 to 120 minutes promoted by larval presence, and that ants are spatially attracted to their larvae, the water source and the walls. We also find that the presence of nestmates lowers an individual ants motion activity. Observed data are compared to simulations of the temporal activity of the ants. ALTAA provides a powerful toolkit to quantify and interpret spatial and temporal collective activity patterns in (social) insects over extended periods.