ArticleJournal of the Royal Society, Interface2016
Variability in individual activity bursts improves ant foraging success.
Article in Journal of the Royal Society, Interface, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- Foraging ants as liquid brains: Movement heterogeneity shapes collective efficiency.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Preference and Toxicity of Sulfoxaflor, Flupyradifurone, and Triflumezopyrim Bait against the Fire AntInsects · 2024Article
- Spatiotemporal organization of ant foraging from a complex systems perspective.Scientific reports · 2024Article
- A Data-Driven Simulation of the Trophallactic Network and Intranidal Food Flow Dissemination in Ants.Animals : an open access journal from MDPI · 2022Article
- Movement, Encounter Rate, and Collective Behavior in Ant Colonies.Annals of the Entomological Society of America · 2021Article
- A Semi-Deterministic Random Walk with Resetting.Entropy (Basel, Switzerland) · 2021Article
- Occupancy patterns in superorganisms: a spin-glass approach to ant exploration.Royal Society open science · 2020Article
- Article
- Lévy flight movements prevent extinctions and maximize population abundances in fragile Lotka-Volterra systems.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
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Authors and funding
5 authors.
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Abstract
Using experimental and computational methods, we study the role of behavioural variability in activity bursts (or temporal activity patterns) for individual and collective regulation of foraging in A. senilis ants. First, foraging experiments were carried out under special conditions (low densities of ants and food and absence of external cues or stimuli) where individual-based strategies are most prevalent. By using marked individuals and recording all foraging trajectories, we were then able to precisely quantify behavioural variability among individuals. Our main conclusions are that (i) variability of ant trajectories (turning angles, speed, etc.) is low compared with variability of temporal activity profiles, and (ii) this variability seems to be driven by plasticity of individual behaviour through time, rather than the presence of fixed behavioural stereotypes or specialists within the group. The statistical measures obtained from these experimental foraging patterns are then used to build a general agent-based model (ABM) which includes the most relevant properties of ant foraging under natural conditions, including recruitment through pheromone communication. Using the ABM, we are able to provide computational evidence that the characteristics of individual variability observed in our experiments can provide a functional advantage (in terms of foraging success) to the group; thus, we propose the biological basis underpinning our observations. Altogether, our study reveals the potential utility of experiments under simplified (laboratory) conditions for understanding information-gathering in biological systems.
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