Evolution of what?

A Network Approach for the Detection of Evolutionary Forces
Hilbert, M., Oh, P., & Monge, P. (2016). Evolution of what? A network approach for the detection of evolutionary forces. Social Networks, 47, 38–46.

Highlights:

  • Evolutionary analysis usually focuses on traits, such as the beak length of Darwin’s finches
  • However, evolution acts on both who subjects are and whom they are connected with
  • We analyze the effects of network metrics on traditional evolutionary equations
  • We derive a formula to compare evolutionary forces for trait and network metrics
  • Network metrics identify stronger evolutionary natural selection than trait partitions

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 1,000 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.

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