Successful mating of spatially-explicit demography and genetics in a new simulation modeling framework: Individual-based, spatial eco-evolutionary models at last

Background/Question/Methods

Simulation models are essential for understanding how environmental drivers, including landscape change, shape population genetic structure and persistence probabilities.  The emerging field of eco-evolutionary modeling is beginning to develop such analyses by linking individual-based demographic and genetic processes together within spatially-explicit simulation frameworks.  However, the few existing tools in this class are actually either population genetics simulators that have been augmented with simple demographic models, or population viability simulators with simplified genetic parameters.  To have practical value, eco-evolutionary models will have to acquire much more demographic and genetic sophistication.

Results/Conclusions

Here, we introduce a new simulation framework called HexSim that seamlessly connects a mature demographic model to a flexible genetics toolkit.  HexSim can be used to develop eco-evolutionary population models for a wide variety of life histories, ranging in complexity from theoretically simple to realistic and detailed.  We showcase two sets of spatially-explicit scenarios: theoretical population genetic dynamics, and complex eco-evolutionary models with management strategies.  We demonstrate how this new modeling framework can be a powerful tool for landscape geneticists, conservation biologists, evolutionary biologists, teachers, and others.