Heterogeneous Activity Causes a Nonlinear Increase in the Group Energy Use of Ant Workers Isolated from Their Social Environment
Increasing evidence has shown that the energy use of ant colonies increases sublinearly with colony size so that large colonies consume less per capita energy than small colonies. It has been postulated that social environment (e.g., in the presence of queen and brood) is critical for the sublinear group energetics, and a few studies of ant workers isolated from queens and brood observed linear relationships between group energetics and size. In this paper, we hypothesize that the sublinear energetics arise from the heterogeneity of activity in ant groups, that is, large groups have relatively more inactive members than small groups. We further hypothesize that the energy use of ant worker groups that are allowed to move freely increases more slowly than the group size even if they are isolated from queen and brood. Previous studies only provided indirect evidence for these hypotheses due to technical difficulties. In this study, we applied the automated behavioral monitoring and respirometry simultaneously on isolated worker groups for long time periods, and analyzed the image with the state‐of‐the‐art algorithms. Our results show that when activity was not confined, large groups had lower per capita energy use, a lower percentage of active members, and lower average walking speed than small groups; while locomotion was confined, however, the per capita energy use was a constant regardless of the group size. The quantitative analysis shows a direct link between variation in group energy use and the activity level of ant workers when isolated from queen and brood.
N. Ferral et al., "Heterogeneous Activity Causes a Nonlinear Increase in the Group Energy Use of Ant Workers Isolated from Queen and Brood," Insect Science, vol. 25, no. 3, pp. 487 - 498, Institute of Zoology, Chinese Academy of Sciences, Jun 2018.
The definitive version is available at https://doi.org/10.1111/1744-7917.12433
Intelligent Systems Center
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01 Jun 2018