Genetic surfing creates fitness costs at the range edge (reviewed by Angert, Bontrager, & Ågren, 2020) in two ways. First, at least in one dimensional simulations, surfing causes genetic diversity to decline over space away from the population centre (Hallatschek & Nelson, 2008). Second, deleterious mutations can surf on the wave of advance to reach high frequencies over a large range (Peischl, Dupanloup, Kirkpatrick, & Excoffier, 2013; Travis et al., 2007) – a phenomenon known as expansion load (Peischl & Excoffier, 2015). These costs make the success of invasive species seem even more paradoxical (Estoup et al., 2016). However, a number of solutions have been proposed to the cost of range expansion. First, long range dispersal can ameliorate the loss of genetic diversity through surfing under some conditions (Paulose & Hallatschek, 2020). Second, the spatial sorting of dispersal traits that results from superior dispersers finding mates more often at the range edge (Shine, Brown, & Phillips, 2011) can rescue populations from expansion load (Peischl & Gilbert, 2020).

Genetic Surfing can also create geographic clines in allele frequency in the direction of range expansion (Klopfstein et al., 2006), clusters of low genetic diversity, and sweeps of random loci in different regions of the metapopulation (Hallatschek, Hersen, Ramanathan, & Nelson, 2007). These allele frequency patterns may be falsely interpreted as a footprint of selection (Excoffier & Ray, 2008).

Thus, when using genomic data to detect post-introduction adaptation in an invasive species known to have undergone a population bottleneck, modelling approaches should be used to rule out potentially confounding demographic and spatial effects (e.g. , Currat et al., 2006). Moreover, Peischl and Excoffier’s (2015) model of expansion load provides clear expectations in terms of the expected shape of the site frequency spectrum at the range front. Invasive species are therefore ideal systems in which to validate or reject these expectations.