Phase synchronization between culture and climate forcing

Over the history of humankind cultural innovations have helped improve survival and adaptation to environmental stress. This has led to an overall increase in human population size, which in turn further contributed to cumulative cultural learning. During the Anthropocene, or arguably even earlier, this positive socio-demographic feedback has caused a strong decline in important resources, that - coupled with projected future transgression of planetary boundaries - may potentially reverse the long-term trend in population growth. Here we present a simple consumer/resource model that captures the coupled dynamics of stochastic cultural learning and transmission, population growth, and resource depletion in a changing environment. The idealized stochastic mathematical model simulates boom/bust cycles between low-population subsistence, high density resource exploitation and subsequent population decline. For slow resource recovery timescales and in the absence of climate forcing, the model predicts a longterm global population collapse. Including a simplified periodic climate forcing, we find that cultural innovation and population growth can couple with the climatic forcing via nonlinear phase-synchronization. We discuss the relevance of this finding in the context of cultural innovation, the anthropological record and longterm future resilience of our own predatory species.

Methods
This dataset contains the Matlab code used to solve the ordinary differential equations (ODE) (1-3) of the paper "Phase synchronization between culture and climate forcing" in Proceedings of the Royal Society, B. The prognostic equation describe the dynamics of population density, resources/carrying capacity and culture, respectively.

The Matlab code represents an Euler discretization of the stochastic ODEs and a Weibull-distributed noise distribution is assumed for the cultural innovation term. All images in the paper can be reproduced - at least in a statistical sense - by changing the parameters in the code by the parameters indicated in the figure caption of the manuscript.