Exploring the connection between emergent animal personality and fitness using a novel individual-based model and decision tree approach

The connection between reproductive fitness and animal personality is not fully understood. Using computer simulations and machine learning, we found high accuracy rules that predict which personalities are associated with fitness for two correlated measures of components of fitness applied a posteriori for classificatory purposes: fitness component (1) in terms of survival and short-term reproductive success, and fitness component (2) in terms of long term reproductive success which is indirectly related to survival of the parents. Animals are represented in the abstract as individuals with a genome that through time develops into certain characteristic behaviors and personalities. To the best of our knowledge, this is the first simulation study of its kind that extracts rules to investigate the link between personality and fitness. Clearly separated behaviors between fit and non-fit individuals emerged through the evolution of the population over time without top-down processing. Moreover, we did not employ a pre-defined fitness function, in order to minimize any possible biases toward a specific type of behavior. With respect to fitness component (1), we found that individuals with one of two extreme values of a personality trait (either bold or fearful) tend to be most fit, which agrees with empirical studies. With respect to fitness component (2), we found that when resources are low, fit individuals search for food whereas if food is abundant, they focus on reproduction, thereby suggesting the context dependence of fitness related behaviors. Once again, these results agree with empirical studies.