From foraging trails to transport networks: how the quality-distance trade-off shapes network structure

Author:

Lecheval Valentin1ORCID,Larson Hannah2,Burns Dominic D. R.1ORCID,Ellis Samuel3ORCID,Powell Scott4ORCID,Donaldson-Matasci Matina C.2ORCID,Robinson Elva J. H.1ORCID

Affiliation:

1. Department of Biology, University of York, UK

2. Department of Biology, Harvey Mudd College, Claremont, CA, USA

3. Centre for Research in Animal Behaviour, University of Exeter, UK

4. Department of Biological Sciences, George Washington University, Washington, DC, USA

Abstract

Biological systems are typically dependent on transportation networks for the efficient distribution of resources and information. Revealing the decentralized mechanisms underlying the generative process of these networks is key in our global understanding of their functions and is of interest to design, manage and improve human transport systems. Ants are a particularly interesting taxon to address these issues because some species build multi-sink multi-source transport networks analogous to human ones. Here, by combining empirical field data and modelling at several scales of description, we show that pre-existing mechanisms of recruitment with positive feedback involved in foraging can account for the structure of complex ant transport networks. Specifically, we find that emergent group-level properties of these empirical networks, such as robustness, efficiency and cost, can arise from models built on simple individual-level behaviour addressing a quality-distance trade-off by the means of pheromone trails. Our work represents a first step in developing a theory for the generation of effective multi-source multi-sink transport networks based on combining exploration and positive reinforcement of best sources.

Funder

NERC

NSF

Publisher

The Royal Society

Subject

General Agricultural and Biological Sciences,General Environmental Science,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

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