Spatial and Temporal Simulation of Human Evolution. Methods, Frameworks and Applications

Title:Spatial and Temporal Simulation of Human Evolution. Methods, Frameworks and Applications

Volume: 15 Issue: 4

Author(s): Macarena Benguigui and Miguel Arenas

Affiliation:

Keywords: Demographic models, Human evolution, Human landscape genetics, Molecular evolution, Range expansion, Spatially explicit simulation.

Abstract: Analyses of human evolution are fundamental to understand the current gradients of human diversity. In this concern, genetic samples collected from current populations together with archaeological data are the most important resources to study human evolution. However, they are often insufficient to properly evaluate a variety of evolutionary scenarios, leading to continuous debates and discussions. A commonly applied strategy consists of the use of computer simulations based on, as realistic as possible, evolutionary models, to evaluate alternative evolutionary scenarios through statistical correlations with the real data. Computer simulations can also be applied to estimate evolutionary parameters or to study the role of each parameter on the evolutionary process. Here we review the mainly used methods and evolutionary frameworks to perform realistic spatially explicit computer simulations of human evolution. Although we focus on human evolution, most of the methods and software we describe can also be used to study other species. We also describe the importance of considering spatially explicit models to better mimic human evolutionary scenarios based on a variety of phenomena such as range expansions, range shifts, range contractions, sex-biased dispersal, long-distance dispersal or admixtures of populations. We finally discuss future implementations to improve current spatially explicit simulations and their derived applications in human evolution.

Cite this article as:

Benguigui Macarena and Arenas Miguel, Spatial and Temporal Simulation of Human Evolution. Methods, Frameworks and Applications, Current Genomics 2014; 15 (4) . https://dx.doi.org/10.2174/1389202915666140506223639