Introduction
Aside from limits set by dispersal barriers, distribution range borders
are commonly assumed to be the result of the constraints imposed by the
ecological requirements of species (either biotic or abiotic), as
environmental gradients may change towards suboptimal conditions near
range edges (Hutchinson 1957; Brown 2002). All in all, the factors that
shape these distribution borders not due to dispersal barriers are
ultimately linked to local adaptation dynamics; simply put, a species
does not occur outside its distribution border because it is not adapted
to the environmental conditions beyond it (Kirkpatrick and Barton 1997;
Bridle and Vines 2007). However, the edge of a species’ range is
typically more abrupt than expected, given that environmental change
towards suboptimal conditions or niche boundaries is usually gradual
(Sexton et al. 2009). Moreover, all across their ranges species meet a
range of conditions that is much greater than the environmental change
that takes place at the edge of the range (Kirkpatrick and Barton 1997).
To understand these seemingly arbitrary boundaries to range expansion,
Haldane (1956) proposed gene ‘swamping’ as a center-border effect by
which gene flow from central to marginal habitats causes maladaptation
at the edges of the range, reducing population density and constraining
range expansion. This dynamic pattern would jeopardize adaptation at the
edge of the range even if the genetic variants that could promote range
expansion are present in the genetic pool of a species, because gene
swamping would hamper a rise in the frequencies of adaptive alleles at
range limits (Haldane 1956). However, this hypothesis has been subject
to continuous debate (Nosil and Crespi 2004; Sexton et al. 2011;
Polechová 2018).
Another possibility is that range limits arise because a species has
fully colonized the spatial projection of its ecological niche, in such
way that niche expansion must precede range enlargement (Hutchinson
1957). In such cases, since niche expansion implies adaptation to more
extreme conditions along one or more environmental gradients, this
process is limited by the magnitude of the additive genetic variance
associated with adaptation to these gradients (Lande and Shannon 2006).
Conversely, if habitat and/or environmental suitability remains high at
and beyond range boundaries, then dispersal constraints, gene swamping
and/or marginal demographic effects could be defining the location and
shape of distribution limits (Kirkpatrick and Barton 1997; Bridle and
Vines 2007; Charlesworth 2009; Peterson 2011, Duncan et al. 2015).
However, if the genetic variability required for range expansion is not
available in the genetic pool of a species, gene swamping cannot be
invoked to explain range limits (Polechova and Barton 2015, Polechova
2018). Evaluating these different hypotheses is thus crucial to
understand the adaptive causes underlying the formation and shaping of
range edges (Sexton et al. 2009; Lee-Yaw et al. 2018).
Landscape genomics approaches have boosted our understanding of how
environmental variables drive the genetic dynamics of local adaptation
(Hoban et al. 2016; Ahrens et al. 2018). These methods can be applied to
model (and predict) potential range boundaries by looking at the shifts
in allelic frequencies along environmental gradients (Eckert et al.
2008; Herrera and Bazaga 2008, Razgour et al. 2019). Thus, it is
possible to explore what loci govern the adaptability of a species, and
to model the suitability of certain genotypes to different habitats all
over a species’ range (i.e., environmental association analyses;
Rellstab et al. 2015; Whitlock and Lotterhos 2015). However, describing
correlations between genotypes and environmental gradients is only one
part of the challenge, because some loci could show strong but spurious
associations with environmental gradients due to population history
rather than natural selection. Thus, it is also paramount to identify
the loci underpinning local adaptation, since they make the fraction of
genetic variation that is relevant to explain an individual’s ability to
disperse to, and thrive in, new habitats (Dudaniec et al. 2018).
Identifying these combinations of loci under selection is a prerequisite
to understand the adaptive basis of the origin and maintenance of new
populations and, therefore, the genetic dynamics that shape range
boundaries (Hargreaves et al. 2014).
New populations of a species can be established either by 1) the arrival
of individuals carrying genetic adaptations to that new site, or 2) the
arrival of genetic variants that can recombine in situ to generate new
locally adapted genotypes (Barton and Etheridge 2018). Discerning
between these two possibilities is a hard challenge. In particular, the
last scenario is controversial because it assumes that an individual is
able to reproduce in a location to which it is not adapted. However, the
potential to produce new genetic combinations increases with dispersal
rate, by rising the probability that different (suboptimal) genotypes
eventually co-occur at the same new habitats (Barton and Etheridge 2018;
LaRue et al. 2018). Thus, study organisms with low dispersal rates
should reduce the confounding effects of dispersion, allowing us to
focus on local adaptation dynamics as responsible of expansion
constraints (Lee-Yaw et al. 2018).
In this study, we integrate genomic data into the distribution modelling
of a lacertid lizard species, the Large Psammodromus Psammodromus
algirus , whose phylogeographical and ecological differentiation is well
characterized (Carranza et al. 2006, Díaz et al. 2017, Llanos-Garrido et
al. 2019). This lizard is widespread across the Western Mediterranean
region, and its range encompasses contrasting environmental conditions,
extending from northern Africa in the south to southwest France in the
north, and from Portugal in the west to Tunisia in the east (Fig. 1A).
We used 21 loci putatively under selection (hereafter outliers;
Llanos-Garrido et al. 2019) to model distribution boundaries on the
basis of five closely located central populations that cover a
representative fraction of the environmental variation faced by P.
algirus across its entire distribution range. These outlier SNPs were
identified by two methods of outlier detection, one of them independent
of population coancestry (an extension of the Lewontin–Krakauer test;
Bonhomme et al. 2010) and the other one not (Bayescan v.2.1; Foll and
Gaggiotti 2008). To model the distribution of P. algirus from
these SNPs putatively under selection, we ran an environmental
association analysis (Rellstab et al. 2015) with allelic variants at
loci under selection as predictors, and we extrapolated, for all
possible allelic combinations at those loci, the geographical locations
with suitable environmental conditions. By doing so, we were able to
infer not only an ecological niche model of the whole distribution range
of the species, but also the genotypes that would potentially be adapted
to each geographical grid cell within it. We assumed a simple model
without center-border biases, and in which every genotype is able to
reach every geographic cell. Also, we only used the (adaptive) genetic
variation at those particular loci likely to be associated with
environmental conditions, in such way that we could know whether actual
range limits are linked to adaptability thresholds determined by the
amount of additive genetic variance available for selection. This
approach allowed us to test whether a species’ distribution range can be
explained by the genetic dynamics that shape local adaptation, without
invoking demographic processes such as gene swamping or increased
homozygosity near the edge of the range (Herrera and Bazaga 2008;
Polechová et al. 2009).
Specifically, we aimed to answer the following questions: 1) Is it
possible to infer an entire distribution range on the basis of a limited
number of outlier loci? 2) How important are limitations to dispersal in
defining a species’ range limits? 3) Are there fewer genotypes adapted
to marginal conditions than to core conditions? And 4) is there an
adaptability threshold, determined by the availability of genetic
variance under selection, that constrains the expansion of the range
beyond its actual boundaries?