Rapid evolution of prehistoric dogs from wolves by natural and sexual selection emerges from an agent-based model

Wolves are among the earliest animals to be domesticated. However, the mechanism by which ancient wolves were domesticated into modern dogs is unknown. The prevailing domestication hypotheses are that humans selectively bred the wolves that were more docile. However, a competing hypothesis states that wolves which were less hostile towards humans would essentially domesticate themselves by naturally selecting for tamer wolves, since that would allow for easier access to food from human settlements. A major critique of the latter hypothesis is whether evolution by this natural selective pathway could have occurred in a sufficiently short time span. Simulating the process would help demonstrate if such an objection is sufficient to dismiss this hypothesis. Thus, we constructed an agent-based model of evolution of a single trait, a measure of human tolerance, in canines to test the merit of the time constraint objection. We tested scenarios both with and without mate preference to provide ..., This dataset is entirely the result of synthetic, in-silico experiments. It was collected by running the provided Python code. Additional documentation is provided in this GitHub repository: david-elzinga/dog_evolution, , # Rapid Evolution of Prehistoric Dogs from Wolves by Natural and Sexual Selection Emerges from an Agent-Based Model

Here, we provide the necessary .py files to recreate the results found in the above-entitled manuscript. If you desire to load the data provided, it's recommended you use pandas 2.0.3 and python 3.10.13. 

Nearly all .py files will require you have evolutuion_system.py file in the base directory. This .py file enacts the ABM as described in the manuscript. All other .py files should be placed in the same base directory. 

You should construct a data folder and a figures folder in the base directory. In the data folder create an efast, prcc, and a monotonicity subfolder. These exists so you do not have to re-run the efast, prcc, or monotonicity simulations. In the figures folder create subfolders for default_distributions, distributions, efast, monotonicity, prcc, validation, and verification. Any figures generated will be produced in the corresponding figures sub-folder. ...