Introduction:
Understanding the processes shaping phenotypic diversification in nature
is a central objective of ecology and evolutionary biology (Schluter
2000, Bolnick et al. 2011). The effects of phenotypic variation
in foundation species can be far-reaching, influencing everything from
species interactions to the evolution of complex communities (Whithamet al. 2020). Trait variation within widespread species can be
extensive due to historic demographic processes and spatially and
temporally heterogeneous landscapes exerting different selection
pressures across their range (Whitlock 2008). Over time, subpopulations
can become genetically and phenotypically differentiated due to neutral
processes, such as drift, gene flow, and mutation, as well as the
adaptive process of natural selection (Wright 1931; Spitze 1993;
Holsinger & Weir 2009; Leinonen et al. 2013). The relative
importance of these stochastic versus selective forces is still debated
but is crucial for understanding the probability and rate of phenotypic
divergence in the past and future (O’Hara 2005; Hangartner et al.2012; Leinonen et al. 2013). Forest ecosystems provide evidence
of significant genetic differences, a high degree of local adaptation,
and ecological consequences for associated species and communities
(Savolainen et al. 2007; O’Neill et al. 2008; Leimuet al. 2008; Hereford 2009), including species of Populus(Whitham et al. 2006; Grady et al. 2011; Grady et
al. 2013; Evans et al. 2016; Fischer et al. 2017; Cooperet al. 2019). Understanding the processes underlying genetic and
phenotypic divergence in these species, especially in relation to past
and future adaptation to climatic variation, is essential both for
selecting current stock for restoration and forecasting the potential
for further adaptation in response to climate change (Grady et
al. 2015; Evans et al. 2016).
One way to test whether natural selection is the mechanism responsible
for generating phenotypic differences among populations is to compare
QST, the variation in quantitative traits, to
FST, the variation in neutral genes (Wright 1951; Lande
1992; Spitze 1993). QST is the quantitative genetic
analog to FST and measures the proportion of additive
genetic variance in a trait attributed to among-population differences.
If QST exceeds the neutral expectation of
FST, there is evidence that directional selection is
responsible for population-level phenotypic differentiation. If
QST ≈ FST, the null model that
population differences are due to genetic drift alone cannot be
rejected. Finally, if QST is lower than
FST, this suggests uniform or stabilizing selection
acting to constrain among-population divergence (Spitze 1993).
QST-FST comparisons have been primarily
used to detect selection and evaluate the degree of local adaptation
among populations, but have increasingly been used as a management and
conservation tool (Leinonen et al . 2013). For example,
QST has been used to designate populations as separate
conservation units (Leinonen et al. 2008), to assess the adaptive
potential of invasive species, measure the rates of evolution in
different environments, and look at the constraints on adaptation due to
increased habitat fragmentation (Leinonen et al. 2013). The surge
in both experimental and theoretical studies comparing molecular and
quantitative genetic variation has revealed a major role of natural
selection in shaping intraspecific variation in quantitative traits
(McKay & Latta 2002; Leinonen et al. 2008; Leinonen et
al. 2013), with approximately 70% of all studies showing
QST > FST (Leinonenet al. 2008). QST studies are often used as an
exploratory analysis to first see the selective patterns across a suite
of traits, and then target those traits with the highest levels of
differentiation to examine their genetics and responses to selection
more closely (Leinonen et al. 2008; Whitlock 2008).
The pattern of phenotypic variation in tree species along climate
gradients often appears consistent with local adaptation in response to
selection by climatic conditions. For example, phenological traits are
closely linked to temperature and photoperiod, and show strong
latitudinal clines in multiple tree species (Howe et al. 2003;
Savoleinen et al. 2007; Evans et al. 2016; Cooper et
al. 2019). Within Populus , growth and phenology traits differ
among genotypes (Frewen et al. 2000; Howe et al. 2000;
Fischer et al. 2017; Davis et al . 2020), with evidence of
variation and adaptive differences among populations (Grady et
al. 2011; Evans et al. 2014; McKown et al. 2014; Cooperet al. 2019). In Populus fremontii specifically, there are
large population differences in phenology expressed in common garden
experiments at both the cold and hot edge of the species’ tolerance
(Cooper et al . 2019), as well as clear correspondence between a
population’s source climate and its mortality and productivity in cold
vs. hot conditions (Grady et al. 2011, 2013, 2015). Population
structure in P. fremontii has also been attributed to differences
in spring and winter precipitation, which can affect flowering
phenology, and therefore gene flow, across its range (Cushman et
al . 2014; Ikeda et al. 2017). However, to definitively show that
phenotypic variation among populations is due to divergent selection by
their home climate, we need approaches that integrate molecular and
phenotypic assessments in common garden environments.
The role of selection by past climatic conditions in shaping
intraspecific variation in foundation species is especially important to
quantify in the American Southwest, where the effects of climate change
are pronounced (Garfin et al. 2013, Williams et al. 2020).
Fremont cottonwood is especially sensitive to drought and high
temperature, as is evidenced by stand-level mortality at the Bill
Williams National Wildlife Refuge on the lower Colorado River (Fig. 1).
Mortality in these trees is associated with the megadrought that
Williams et al. (2020) identify as being the second worst drought
in the past 1200 years in the American Southwest. Recent studies by
Hultine et al. (2020a) and Blasini et al. (2020) suggest
that these trees are at the edge of their thermal tolerance where water
is essential for evaporative cooling. Thus, current climatic gradients
will be exacerbated by ongoing climate change, leading to new selection
pressures on functional traits that may be locally adapted to a narrower
range of environmental conditions.
In this study, we use trait data from three experimental common gardens
spanning the climatic range of P. fremontii to quantify
phenotypic divergence (QST) and compare it to neutral
genetic divergence (FST). Common gardens are necessary
to ensure that among-population variance components reflect genetic
differences and are not inflated by environmental effects (Leinonenet al. 2013). Reciprocal experimental gardens can indicate
whether populations are locally adapted to their current environments,
reveal traits that vary across environmental gradients as a result of
phenotypic plasticity (Kawecki & Ebert 2004; Franks et al.2014), and quantify the intensity of selection across space (Whitlock
2008). Our use of multiple common gardens adds to the
QST literature by examining how population-level trait
differentiation is expressed across environmental gradients. Plastic
responses to environmental stress or release from stress may mask or
amplify genetically determined trait differences that have emerged as a
result of divergent selection (Oke et al. 2015). Therefore, it is
important to assess phenotypes in multiple growing conditions in order
to demonstrate how the environment can modify the degree to which we can
detect evidence of selection.
The three gardens used in this study contain cloned cuttings from 16
populations of P. fremontii collected throughout Arizona. Both
the collection and garden sites span an elevational gradient of almost
2000 m, consistent with the species’ range and including a difference of
12°C mean annual temperature and > 500 mm in mean annual
precipitation. The benefit of these experimental gardens is enhanced by
the development of genomic data based on the identification of 1000s of
single nucleotide polymorphisms (SNPs) in the Fremont cottonwood genome.
These data can provide improved estimates of FST, owing
to their greater coverage of the genome and potentially lower mutation
rate than microsatellites, which have been routinely used to estimate
FST. SNPs are an ideal type of marker for quantifying
molecular divergence because mutation rates and the effects of drift on
SNP variation are considered to be more similar to loci that control
quantitative traits (Edelaar & Bjorklund 2011). Thus, the only
difference between quantitative trait loci driving QSTand the loci used in FST estimates should be that only
the latter conform to neutral molecular evolution (Leinonen et
al. 2013).
In order to address whether natural selection by climatic conditions is
an agent of phenotypic diversification across the range of Fremont
cottonwood, we evaluated three hypotheses: 1) Genetic variation in
multiple tree traits (phenology, specific leaf area, height, and trunk
diameter) will be evident among populations and genotypes in each of the
three common gardens, although the magnitude of the genetic component
may vary across environments and among traits. 2) QSTvalues will be significantly higher than the neutral expectation of
FST, suggesting divergent selection has outweighed drift
in shaping trait differences. Again, this drift-selection balance may
vary among traits, and our ability to detect selection on these traits
may vary across common gardens. 3) Mean population phenotypes will show
strong associations with their climate of origin, especially for the
most differentiated traits (those with high QST). This
pattern is expected when phenotypic differentiation is strongly shaped
by selection due to climate.