Evolution of what? A network approach for the detection of evolutionary forces

Martin Hilbert*, Poong Oh, Peter Monge

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

Structures of evolving populations are traditionally derived from traits of its members. An alternative approach uses network metrics to define groups that evolve jointly. This supposes that selection acts not only on who members are (i.e., traits) but also on to whom they are connected (i.e., interdependent relationships). This paper presents a method to meaningfully quantify differences in evolutionary forces over multiple levels of population taxonomies and tests almost 1000 multilevel partitions of 8 empirical networked populations evolving over time. It shows that multilevel network metrics as selection criteria identifies stronger evolutionary natural selection than trait based population taxonomies.

Original languageEnglish
Pages (from-to)38-46
Number of pages9
JournalSocial Networks
Volume47
DOIs
Publication statusPublished - Oct 1 2016
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2016 Elsevier B.V.

ASJC Scopus Subject Areas

  • Anthropology
  • Sociology and Political Science
  • General Social Sciences
  • General Psychology

Keywords

  • Natural selection
  • Network dynamics
  • Network evolution
  • Network partition
  • Network theory

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