Computational Model Library

Effective population size and cultural evolution (version 1.0.0)

The model was designed to investigate (1) to what extent the effective population size of a cultural trait departs from the cultural equivalent N under non-ideal conditions, and (2) how the differences between Shennan’s (2001) and Henrich’s (2004) model assumptions influence the effect of demography on the rate of change in the mean skill level of a cultural trait. The model was programmed and run in NetLogo 5.1. The source code may need to be modified to run in later versions of NetLogo.

The model shows how natural selection and cultural selection affect the effective population size of a cultural trait, in many cases causing it to depart not only from census population size but also from the number of potential (and even actual) teachers in the population. Although Shennan (2001) is correct that the positive nonlinear effect of N on equilibrium mean fitness is explained by the fact that the relative strength of drift is a function of N, N does not “represent” Ne under non-ideal conditions. The results of this model show that the two are not equivalent under the conditions of Shennan’s model due to the fact that natural selection and directly biased oblique cultural transmission both drive down Ne.

The observation that increasing the probability of learning from the most skilled member of one’s subset of potential teachers increases Ne under Shennan’s model conditions but decreases Ne under Henrich’s model conditions reflects the fact that Shennan’s and Henrich’s models showcase different demographic effects. The effect of N on the rate of change in mean skill level in Henrich’s model is driven by the absolute number of oblique learners who attempt to copy the most skilled member of the parental generation.

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Release Notes

This is Version 1.0. It was programmed during the spring of 2015 and the results were published in the fall of 2016.

Download Version 1.0.0
Version Submitter First published Last modified Status
1.0.0 Luke Premo Tue May 17 21:30:57 2016 Tue May 17 21:30:57 2016 Published

Discussion

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