Reproduction cost reduces demographic stochasticity and enhances inter-individual compatibility.

A population׳s survival depends on its ability to adapt to constraints impinging upon it. As such, adaptation is at the heart of an increasing number of theoretical models. In this paper, we propose a bottom-up evolutionary model to explore the relationship between individual evolutionary dynamics and population-level survival. To do so, we extend a well-established model of gene network evolution by introducing a cost for reproduction. As a result population sizes fluctuate and populations can even go extinct. We find that if a population survives a small and critical number of generations, it will reach a quasi-stationary state which ensures long-term survival. In a constant environment, individual adaptation occurs in response to changes in a populations genetic composition. We show that genetic compatibility increases over generations as a by-product of selection for robustness, thus preventing extinction. We also demonstrate that the number of reproductive opportunities per individual, initial population size, and mutation rates all influence population survival. Finally, mixing different populations reveals that individual properties of gene networks co-evolve with the genetic composition of the population in order to maximize an individuals reproductive success.