Evolution of cooperation in deme-structured populations on graphs
- 1. Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland and SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
Description
Understanding how cooperation can evolve in populations despite its cost to individual cooperators is an important challenge. Models of spatially structured populations with one individual per node of a graph have shown that cooperation, modeled via the prisoner's dilemma, can be favored by natural selection. These results depend on microscopic update rules, which determine how birth, death, and migration on the graph are coupled. Recently, we developed coarse-grained models of spatially structured populations on graphs, where each node comprises a well-mixed deme, and where migration is independent from division and death, thus bypassing the need for update rules. Here, we study the evolution of cooperation in these models in the rare-migration regime, within the prisoner's dilemma. We find that cooperation is not favored by natural selection in these coarse-grained models on graphs where overall deme fitness does not directly impact migration from a deme. This is due to a separation of scales, whereby cooperation occurs at a local level within demes, while spatial structure matters between demes.
Files
10.1103_PhysRevE.109.024307.pdf
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Additional details
Identifiers
- DOI
- 10.1103/PhysRevE.109.024307;
- arXiv
- arXiv:2309.09876;
- Crossref Funder ID
- 10.13039/501100000781; 10.13039/501100007601;
Publishing Information
- Journal Title
- Physical Review E
- Journal Volume
- 109
- Journal Issue
- 2
- Journal Page Range
- 15 pgs.
- ISSN
- 1089-3787
INIS
- Country of Publication
- United States
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- Subject category
- S97: MATHEMATICAL METHODS AND COMPUTING; S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
- Descriptors DEI
- COOPERATION; DEATH; DIAGRAMS; DYNAMICAL SYSTEMS; EVOLUTION; GAME THEORY; GRAPH THEORY; LIMIT CYCLE; MATHEMATICAL MODELS; MIGRATION; NETWORK ANALYSIS; POPULATIONS; STATISTICAL MECHANICS; TIME-SERIES ANALYSIS
- Descriptors DEC
- ATTRACTORS; INFORMATION; MATHEMATICS; MECHANICS; STATISTICS
Optional Information
- Contract/Grant/Project number
- 851173
- Notes
- Present address: Department of Biosystems Science and Engineering (D-BSSE), ETH Zurich, CH-4058 Basel, Switzerland.; Contact Email: anne-florence.bitbol@epfl.ch; Record automatically processed
- Funding organization
- European Research Council; Horizon 2020