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.