Introduction
Different species in a shared habitat may be exposed to divergent
selective agents, but one selective force common to natural populations
across the globe is the diel cycling of environmental conditions at an
unvarying pace of 24 h as a result of the Earth´s rotation. The
prevalence of such selection pressure is evidenced by the evolution of
the circadian clock, an endogenous timekeeper, across the tree of life,
which allows for varied biological functions from the expression of
individual genes to physiology and behavior to be appropriately timed
relative to anticipated environmental oscillations (e.g., Yerushalmi and
Green 2009). Experimental disruptions of the clock by loss-of-function
mutations or by manipulations of the exogenous surroundings often reveal
deleterious consequences on fitness components. For example,Drosophila melanogaster had lower fitness in unnatural day
lengths than under 24-h cycles (Pittendrigh and Minis 1972); an
arrhythmic Synechococcus bacterial strain was outcompeted by the
wild type with a functional clock in cycling conditions (Woelfle et al.
2004), and in the common sunflower (Helianthus annuus ) an
interruption of natural solar tracking reduced biomass and the number of
pollinator visits (Atamian et al. 2016).
Circadian traits are measured in constant conditions where the clock can
”free-run” and where endogenous cycles often deviate from 24-h rhythms
maintained under naturally cycling settings. The free-running length of
one full cycle, the circadian period, is a key trait that is expected to
be closely related to fitness: the circadian resonance theory postulates
that peak fitness is achieved when the length of the endogenous
circadian period matches that of the exogenous environmental cycle
(Pittendrigh and Minis 1972). Consequently, 24-h circadian periods would
be expected to be advantageous in natural environments, whereas
deviations from 24 h in either direction would improve fitness in
unnatural diel cycles shorter or longer than 24 h. These tradeoffs might
arise from physiological costs associated with constantly re-entraining
the clock to an environmental cycle that is out of sync with the
endogenous circadian rhythm (Pittendrigh and Minis 1972). Evidence for
this hypothesis has been reported in studies on experimental mutant
genotypes of the plant model Arabidopsis thaliana and
cyanobacteria that express marked variation in circadian period (Dodd et
al. 2005, Ouyang et al. 1998, Woelfle et al. 2004; Rubin et al. 2017),
but results from resonance experiments are not always fully compatible
with the classical theory (e.g., Graf et al. 2011, Horn et al. 2019,
Woodley of Menie et al. 2019).
While experimental genotypes with induced mutations are useful in
dissecting the explicit molecular components of varied biological
functions, they are not representative of patterns of genetic diversity
that have arisen in natural environments. In the wild, various
evolutionary processes determine the partitioning of genetic variation
in quantitative traits among vs. within populations (Mackay et
al. 2009, Mitchell-Olds et al. 2007), and populations may become
genetically differentiated from each other as a consequence of
stochastic events such as random genetic drift (Palumbi 2003, Slatkin
1987) or systematic spatially varying natural selection (Loveless and
Hamrick 1984, Siol et al. 2010). Populations may also exhibit genetic
isolation by distance, in which physically proximate populations are
more similar than distant ones, if populations originate by chance from
a limited number of genetically related founders or migration is
restricted (McRae and Beier 2007, Slatkin 1987, Wright 1943).
Intraspecific genetic variation that tracks spatial heterogeneity in the
environment characterizes many plant traits related to fitness,
including timing of growth and reproduction (e.g., Méndez-Vigo et al.
2011) which have overlapping molecular genetic underpinnings with the
circadian clock (Brachi et al. 2010). For example, flowering time is
highly variable among natural genotypes of A . thalianasampled across the Iberian Peninsula, with lower-elevation origins
generally flowering earlier in common garden (Vidigal et al. 2017).
Circadian traits are no different from other quantitative traits when it
comes to substantial naturally occurring genetic variation: Michael et
al. (2003) documented a range of 6.5 h in circadian period in leaf
movement among 150 A . thaliana genotypes sampled across
the Northern Hemisphere and a latitudinal gradient spanning
~50°, while Rees et al. (2021) restricted their sampling
to Sweden and described a range of 4.4 h in delayed fluorescence among
191 genotypes sampled between 55° and 63° N. Since diel cycles are
uniformly 24 h in length across the globe, variation in circadian period
has predominantly been examined in relation to latitude that correlates
closely with photoperiod and its variability over the course of a year
(e.g., Hut et al. 2013). Yet, latitude alone explains only a minor
proportion (less than 8 %) of the observed genetic variation in
circadian period in A . thaliana (Michael et al. 2003, Rees
et al. 2021), and thus the environmental agents that help maintain
variation in the clock remain to a large extent unidentified (Salmela
and Weinig 2019). It is noteworthy that animals also exhibit significant
natural variability in circadian period which in locomotor activity of
insects varies by up to 8 h among mostly European populations ofPyrrhocoris apterus (Pivarciova et al. 2016) and inTribolium castaneum in Japan (Abe et al. 2021), with no evidence
for marked linear latitudinal trends.
Beside studies on diverse pools of A . thaliana accessions,
plant studies sampling multiple genotypes per geographic location (i.e.,
populations) have demonstrated that genetic variation in the clock
concurrently segregates among and within populations (Greenham et al.
2017, Leinonen et al. 2020, Salmela et al. 2016) in a manner that is
similar for instance to flowering time in natural populations ofA . thaliana on the Iberian Peninsula (Méndez-Vigo et al.
2013). For instance, in an annual Mimulus guttatus population
from southern Oregon, maternal seed families exhibited a genotypic range
of almost 4 h in circadian period (Greenham et al. 2017). Further, in a
population of B . stricta from southeastern Wyoming,
circadian period varied by 3.5 h among maternal families sampled within
a few hundred meters, with evidence for a positive correlation between
period length and first-year growth (Salmela et al. 2016). Together,
these patterns point to the role of fine-grained regional environmental
heterogeneity in shaping genetic variation in the circadian clock.
The contribution of environmental heterogeneity to the genetic diversity
of circadian rhythms can be uncovered by sampling multiple populations
across well-defined spatial gradients. Temperature conditions vary for
instance with elevation such that growing seasons begin later and at
longer day lengths at higher elevations, giving rise to genetic clines
in quantitative traits even within relatively narrow spatial scales
(e.g., Leinonen et al. 2020). Here, we sample plant populations
intensively within a limited latitudinal but an 800-m elevational
gradient in order to determine how quantitative genetic variation in
circadian period is partitioned among and within Rocky Mountain
populations of B . stricta , a short-lived and predominantly
self-fertilizing perennial relative of A . thaliana with a
wide North American distribution (Song et al. 2006). With the
utilization of circadian assays of leaf movement across these
populations and on over 3800 plants, we examine whether different
evolutionary factors including stochastic and selective forces are
associated with the spatial trends of variation in circadian period
within a region that is small compared to previous studies on natural
genotypes (e.g., Greenham et al. 2017, Michael et al. 2003, Rees et al.
2021) but that nonetheless comprises pronounced environmental
heterogeneity. Based on a preceding study that found significant among-
and within-population genetic diversity in circadian period in the same
region but with only four populations and a smaller elevational gradient
(Salmela et al. 2016), we hypothesize that (1) circadian period
will exhibit genetic variation among and within the 30 populations,(2) that the range of variation among population will be larger
than in Salmela et al. (2016) due to a greater range of environments
sampled, and that (3) if variation in the clock contributes to
adaptation to environmental heterogeneity, patterns of genetic variation
among and within populations will correlate with elevation and
associated local environmental variables.