The trouble with isolation by distance

Patrick G. Meirmans

Molecular Ecology · 2012 · 645 citations · 45 references

Concepts

TL;DR

Isolation by distance causes geographically close individuals to be genetically more similar, yet most statistical tests assume a non‑spatial Island model. The author argues that spatial autocorrelation from IBD biases standard tests and urges that analyses account for spatial dependence or adopt spatially explicit null models. Simulations were used to demonstrate the bias in tests of hierarchical population structure and selection detection. The simulations revealed that IBD generates many false positives in both test categories.

Abstract

Abstract The genetic population structure of many species is characterised by a pattern of isolation by distance (IBD): due to limited dispersal, individuals that are geographically close tend to be genetically more similar than individuals that are far apart. Despite the ubiquity of IBD in nature, many commonly used statistical tests are based on a null model that is completely non‐spatial, the Island model. Here, I argue that patterns of spatial autocorrelation deriving from IBD present a problem for such tests as it can severely bias their outcome. I use simulated data to illustrate this problem for two widely used types of tests: tests of hierarchical population structure and the detection of loci under selection. My results show that for both types of tests the presence of IBD can indeed lead to a large number of false positives. I therefore argue that all analyses in a study should take the spatial dependence in the data into account, unless it can be shown that there is no spatial autocorrelation in the allele frequency distribution that is under investigation. Thus, it is urgent to develop additional statistical approaches that are based on a spatially explicit null model instead of the non‐spatial Island model.

References

45