Simulation modelling in landscape genetics: on the need to go further

With the emergence of landscape genetics, the basic assumptions and predictions of classical population genetic theories are being re‐evaluated to account for more complex spatial and temporal dynamics. Within the last decade, there has been an exponential increase in such landscape genetic studies ( Holderegger & Wagner 2006 ; Storfer et al. 2010 ), and both methodology and underlying concepts of the field are under rapid and constant development. A number of major innovations and a high level of originality are required to fully merge existing population genetic theory with landscape ecology and to develop novel statistical approaches for measuring and predicting genetic patterns. The importance of simulation studies for this specific research has been emphasized in a number of recent articles (e.g., Balkenhol et al. 2009a ; Epperson et al. 2010 ). Indeed, many of the major questions in landscape genetics require the development and application of sophisticated simulation tools to explore gene flow, genetic drift, mutation and natural selection in landscapes with a wide range of spatial and temporal complexities. In this issue, Jaquiéry et al. (2011) provide an excellent example of such a simulation study for landscape genetics. Using a metapopulation simulation design and a novel ‘scale of phenomena’ approach, Jaquiéry et al. (2011) demonstrate the utility and limitations of genetic distances for inferring landscape effects on effective dispersal.