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 mode..., 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., , # Data from: Phase synchronization between culture and climate forcing

The main data provided with this submission includes the code used to generate the key figures in \"**Phase synchronization between culture and climate forcing, Proceedings of the Royal Society, B, 2024\"**

## Code/Software

This Matlab code performs numerical integrations of the stochastic ordinary differential equations (1)-(3) in **Phase synchronization between culture and climate forcing**, Proceedings of the Royal Society B, 2024 and generates the main figures. We use an Euler discretization of these equations (code lines 67, 69, 74) and apply a Weibull-distributed stochastic forcing with distribution parameters 1 and 0.1 (code line 74). Since there is no random seed for the stochastic term, every call of this code will generate a different sequence of random numbers and slightly different overall trajectories.

For kappa>0 (code lines 143 and below), the model equations turn into a non-autonomous (extern...