Constant-selection evolutionary dynamics on weighted networks

Author:

Bhaumik Jnanajyoti1ORCID,Masuda Naoki123ORCID

Affiliation:

1. Department of Mathematics, State University of New York at Buffalo , Buffalo, NY 14260-2900, USA

2. Institute for Artificial Intelligence and Data Science, State University of New York at Buffalo , Buffalo, NY 14260-5030, USA

3. Center for Computational Social Science, Kobe University , Kobe 657-8501, Japan

Abstract

The population structure often impacts evolutionary dynamics. In constant-selection evolutionary dynamics between two types, amplifiers of selection are networks that promote the fitter mutant to take over the entire population, and suppressors of selection do the opposite. It has been shown that most undirected and unweighted networks are amplifiers of selection under a common updating rule and initial condition. Here, we extensively investigate how edge weights influence selection on undirected networks. We show that random edge weights make small networks less amplifying than the corresponding unweighted networks in a majority of cases and also make them suppressors of selection (i.e. less amplifying than the complete graph, or equivalently, the Moran process) in many cases. Qualitatively, the same result holds true for larger empirical networks. These results suggest that amplifiers of selection are not as common for weighted networks as for unweighted counterparts.

Funder

Moonshot Research and Development Program

Japan Society for the Promotion of Science

National Science Foundation

Publisher

The Royal Society

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