The remarkably limited explanatory power of molecular ecology
We undoubtedly live in the era of genomics, with a continuous development of increasingly sophisticated molecular genetic tools. Together with those molecular tools, the statistical inferences used to analyze such data are getting increasingly refined. It has now become standard in analyses of population genetic data to estimate migration rates, barriers to gene flow, detect loci under selection, and associations between genetic and ecological variation. However, few users of these methods realize that their explanatory power is in fact highly limited and many of the methods are prone to biases and errors. Using results from my own research, I will explain several of these pitfalls and show when certain types of inferences can lead to erroneous results. I will then provide suggestions for the proper use of these analyses. Above all, I will warn against any over-enthusiastic use of methods in cases for which they are not suited, which unfortunately includes the great majority of their applications.