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Valentini G, Masuda N, Shaffer Z, Hanson JR, Sasaki T, Walker SI, Pavlic TP, Pratt SC. Division of labour promotes the spread of information in colony emigrations by the ant Temnothorax rugatulus. Proc Biol Sci 2020; 287:20192950. [PMID: 32228408 PMCID: PMC7209055 DOI: 10.1098/rspb.2019.2950] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 03/06/2020] [Indexed: 01/23/2023] Open
Abstract
The fitness of group-living animals often depends on how well members share information needed for collective decision-making. Theoretical studies have shown that collective choices can emerge in a homogeneous group of individuals following identical rules, but real animals show much evidence for heterogeneity in the degree and nature of their contribution to group decisions. In social insects, for example, the transmission and processing of information is influenced by a well-organized division of labour. Studies that accurately quantify how this behavioural heterogeneity affects the spread of information among group members are still lacking. In this paper, we look at nest choices during colony emigrations of the ant Temnothorax rugatulus and quantify the degree of behavioural heterogeneity of workers. Using clustering methods and network analysis, we identify and characterize four behavioural castes of workers-primary, secondary, passive and wandering-covering distinct roles in the spread of information during an emigration. This detailed characterization of the contribution of each worker can improve models of collective decision-making in this species and promises a deeper understanding of behavioural variation at the colony level.
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Affiliation(s)
- Gabriele Valentini
- School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287, USA
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
| | - Naoki Masuda
- Department of Mathematics, State University of New York, Buffalo, NY 14260, USA
- Computational and Data-Enabled Science and Engineering Program, University at Buffalo, State University of New York, Buffalo, NY 14260, USA
| | - Zachary Shaffer
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
| | - Jake R. Hanson
- School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287, USA
- Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ 85287, USA
| | - Takao Sasaki
- Odum School of Ecology, University of Georgia, Athens, GA 30602, USA
| | - Sara Imari Walker
- School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287, USA
- Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ 85287, USA
- ASU–SFI Center for Biosocial Complex Systems, Arizona State University, Tempe, AZ 85287, USA
| | - Theodore P. Pavlic
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
- Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ 85287, USA
- ASU–SFI Center for Biosocial Complex Systems, Arizona State University, Tempe, AZ 85287, USA
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ 85287, USA
- School of Sustainability, Arizona State University, Tempe, AZ 85287, USA
| | - Stephen C. Pratt
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
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Abstract
Evolutionary theory predicts that animals act to maximize their fitness when choosing among a set of options, such as what to eat or where to live. Making the best choice is challenging when options vary in multiple attributes, and animals have evolved a variety of heuristics to simplify the task. Many of these involve ranking or weighting attributes according to their importance. Because the importance of attributes can vary across time and place, animals might benefit by adjusting weights accordingly. Here, we show that colonies of the ant Temnothorax rugatulus use their experience during nest site selection to increase weights on more informative nest attributes. These ants choose their rock crevice nests on the basis of multiple features. After exposure to an environment where only one attribute differentiated options, colonies increased their reliance on this attribute relative to a second attribute. Although many species show experience-based changes in selectivity based on a single feature, this is the first evidence in animals for adaptive changes in the weighting of multiple attributes. These results show that animal collectives, like individuals, change decision-making strategies according to experience. We discuss how these colony-level changes might emerge from individual behaviour.
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Affiliation(s)
- Takao Sasaki
- School of Life Sciences and Center for Social Dynamics and Complexity, Arizona State University, , Tempe AZ 85287, USA
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