Abstract
Demographic models of human cultural evolution have high explanatory potential but weak empirical support. Here we use a global dataset of rock art sites and climate and genetics-based estimates of ancient population densities to test a new model based on epidemiological principles. The model focuses on the process whereby a cultural innovation becomes endemic in a population. It predicts that this cannot occur unless population density exceeds a critical value. Analysis of the data, using a Bayesian statistical framework, shows that the model has stronger empirical support than a null model, where rock art detection rates and population density are independent, or a proportional model where detection is directly proportional to population density. Comparisons between results for different geographical areas and periods yield qualitatively similar results, supporting the robustness of the model. Re-analysis of the rock art data, using a second set of independent population estimates, yields similar results. We conclude that population density above a critical threshold is a necessary condition for the maintenance of rock art as a stable part of a population’s cultural repertoire. Methods similar to those described can be used to test the model for other classes of archaeological artifact and to compare it against other models.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
↵† Joint first authors
We have revised the text and title of the manuscript to clarify the significance of our model. In brief, we predict that a cultural innovation, such as rock art, can only become endemic in a population when population density exceeds a critical threshold. We also introduced a significant technical change in our analysis. In the papers included in our dataset the majority of radiocarbon dates were calibrated but some were not or did not report their calibration status. The previous version of our paper did not correct for this. In the new version we infer the calibration status of all radiocarbon dates and perform our own calibration of dates inferred to be uncalibrated. The change did not affect our qualitative findings but led to small changes in most of our numerical results. The tables and figures in the revised manuscript reflect these changes.