A meta‐analysis of isolation by distance: relic or reference standard for landscape genetics?

Abstract

Isolation by distance (IBD) has been a common measure of genetic structure among populations and is based on Euclidean distances among populations. Whereas IBD does not incorporate geographic complexity (e.g. dispersal barriers, corridors) that may better predict genetic structure, a new approach (landscape genetics) joins landscape ecology with population genetics to better model genetic structure. Should IBD be set aside or should it persist as the most simple model in landscape genetics? We evaluated the status of IBD by collecting and analyzing results of 240 IBD data sets among diverse taxa and study systems. IBD typically represented a low proportion of variance in genetic structure (mean r 2 00.22) in part because many studies included relatively few populations (mean 011). The number of populations studied (N) was asymptotically related to IBD significance; a study with 9 populations has only 50% probability of significance, while one with!23 populations will have 90% probability of significance. Surprisingly, ectothermic animals were significantly (p00.0018) more likely to have significant IBD than endotherms, which suggests a metabolic basis underlying gene flow rates. We also observed marginally significant effects on IBD significance for a) taxa in general and b) dispersal modes within actively-dispersing endotherms. Other factors analyzed (genetic markers, genetic distances, habitats, active or passive dispersal, plant growth form) did not significantly affect IBD, likely related to typical N. For multiple reasons we conclude that IBD should continue as the simplest reference standard against which all other, more complex models should be compared in landscape genetics research.

Isolation-by-distance in landscapes: considerations for landscape genetics

“…Ever since Wright (1943) described isolation-by-distance (IBD), patterns of spatial genetic structure have been extensively studied in population genetic simulation models (Epperson, 2003;Epperson et al, 2010) and in natural populations (Crispo and Hendry, 2005;Jenkins et al, 2010;Storfer et al, 2010). In most of these studies, migration probability is a function of geographic straight-line distance.…”

“…In general, the variation in estimates of pairwise genetic distances explained by these effective distances is compared with that explained by geographic distances alone (that is, IBD). The latter is regarded as the most simple landscape genetic pattern that would be obtained even if there were no landscape effects and migration was thus only constrained by distance between demes (Spear et al, 2005;Balkenhol et al, 2009;Jenkins et al, 2010). This notion may have originated from spatially explicit simulation studies of IBD patterns, in which demes or individuals are usually placed in regular lattices throughout homogeneous spaces (Guillot et al, 2009;Epperson et al, 2010).…”

“…Most landscape genetic studies measure the level of IBD by quantifying the linear correlation between genetic (for example, F ST ) and geographic distances from all deme pairs in a data set (Crispo and Hendry, 2005;Balkenhol et al, 2009;Jenkins et al, 2010). However, to highlight dispersal barriers due to landscape elements, several authors have recently argued that landscape genetic analyses should be restricted to only those pairs of demes between which direct gene flow is possible (Angelone et al, 2011;Keller et al, 2013).…”

“…For various habitat configurations and maximum migration distances (MMD), we examined the development of IBD patterns, determined whether these patterns could best be described as case-I or case-IV F ST -distance relationships and at what interdeme distance the highest F ST -distance correlation was measured. In contrast to other population genetic simulation studies that have focussed on IBD patterns from a theoretical point of view (Epperson, 2003;Epperson et al, 2010), we specifically designed a simulation model that accommodated current landscape genetic practice (Balkenhol et al, 2009;Jenkins et al, 2010;Storfer et al, 2010), so that our findings can easily be integrated into future landscape genetic studies. For instance, we do not assess IBD patterns with Moran's I correlograms, as often done in population genetics (Epperson, 2003), but use linear correlations between F ST and geographic distance instead, as is done in landscape genetics (Jenkins et al, 2010).…”

“…However, to highlight dispersal barriers due to landscape elements, several authors have recently argued that landscape genetic analyses should be restricted to only those pairs of demes between which direct gene flow is possible (Angelone et al, 2011;Keller et al, 2013). As most landscape genetic studies make use of historical gene flow measures (for example, F ST ; Jenkins et al, 2010;Storfer et al, 2010), gene flow is not only measured between deme pairs that are within each other's maximum migration distance, but also between demes beyond this distance that experience indirect gene flow (over several generations) via intermediate demes. However, the inhibiting or facilitating effect on movement of certain landscape elements can only be detected between those demes that potentially exchange migrants (that is, deme pairs separated by a distance lower than the maximum migration distance).…”