Rapid alignment of functional trait variation with locality across the invaded range of Sahara mustard (Brassica tournefortii)

Abstract

Premise of Study
Mechanisms by which invasive species succeed across multiple novel environmental contexts are poorly understood. Functional traits show promise for identifying such mechanisms, yet we lack knowledge of which functional traits are critical for success and how they vary across invaded ranges and with environmental features. We evaluated the widespread recent invasion of Sahara mustard (Brassica tournefortii) in the southwestern United States to understand the extent of functional trait variation across the invaded range and how such variation is related to spatial and climatic gradients.

Methods
We used a common garden approach, growing two generations of plants in controlled conditions sourced from 10 locations across the invaded range. We measured variation within and among populations in phenological, morphological, and physiological traits, as well as performance.

Key Results
We found nine key traits that varied among populations. These traits were related to phenology and early growth strategies, such as the timing of germination and flowering, as well as relative allocation of biomass to reproduction and individual seed mass. Trait variation was related most strongly to variation in winter precipitation patterns across localities, though variations in temperature and latitude also had significant contributions.

Conclusions
Our results identify key functional traits of this invasive species that showed significant variation among introduced populations across a broad geographic and climatic range. Further, trait variation among populations was strongly related to key climatic variables, which suggests that population divergence in these traits may explain the successful colonization of Sahara mustard across its invaded US range.

Full text

1188 • American Journal of Botany 105(7): 1188–1197, 2018; http://www.wileyonlinelibrary.com/journal/AJB © 2018 Botanical Society of America
A major contemporary challenge in ecology is predicting when
and where introduced species will be successful (Kolar and Lodge,
2001). Unfortunately, specic adaptive traits characterizing a suc-
cessful invader oen do not hold for all invasive species (Sakai etal.,
2001). Trait- based ecology shows promise for identifying mecha-
nisms that drive the success of invasives and predicting future pat-
terns (Leishman etal., 2007; Tecco etal., 2010; van Kleunen etal.,
2010; Murphy etal., 2016) because a functional approach can reveal
the mechanisms underlying dierent phenological, morphological,
and physiological characteristics that inuence species’ responses
to the environment. A number of functional traits have been related
to invasive performance and colonization success. ese include
rapid germination and owering phenologies (Kimball etal., 2011;
Colautti and Barrett, 2013), increased allocation to photosynthetic
and reproductive structures (Leishman etal., 2007; Moroney etal.,
2013; Erskine- Ogden etal., 2016), water- use eciency matched to
site- specic environments (Tecco etal., 2010; van Kleunen et al.,
2010), and combinations of each (Kimball etal., 2014). at said,
many iconic invasives occupy a wide breadth of environments
(Colautti etal., 2009), so focusing on a subset of the invaded sys-
tem may not adequately represent important traits and processes.
We expect that three categories of functional traits that inuence
establishment, survival, growth, and reproduction will reveal mech-
anisms driving invasive success: phenological, morphological, and
Rapid alignment of functional trait variation with locality
across the invaded range of Sahara mustard (Brassica
tournefortii)
Daniel E. Winkler1,2,6 , Jennifer R. Gremer3, Kenneth J. Chapin4, Melanie Kao5, and Travis E. Huxman1
RESEARCH ARTICLE
Manuscript received 3 December 2017; revision accepted 27 April
2018.
1 Department of Ecology and Evolutionary Biology,University of
California, Irvine, California 92697, USA
2 U.S. Geological Survey,Southwest Biological Science Center,
Moab, Utah 84532, USA
3 Department of Evolution and Ecology,University of California,
Davis, California 95616, USA
4 Department of Neurobiology, Physiology, and
Behavior,University of California, Davis, California 95616, USA
5 Undergraduate Program in Public Health,University of
California, Irvine, California 92697, USA
6 Author for correspondence (e-mail: winklerde@gmail.com)
Citation: Winkler, D. E., J. R. Gremer, K. J. Chapin, M. Kao, and T.
E. Huxman. 2018. Rapid alignment of functional trait variation with
locality across the invaded range of Sahara mustard (Brassica tourne-
fortii). American Journal of Botany 105(7): 1188–1197.
doi:10.1002/ajb2.1126
PREMISE OF STUDY: Mechanisms by which invasive species succeed across multiple novel
environmental contexts are poorly understood. Functional traits show promise for identifying
such mechanisms, yet we lack knowledge of which functional traits are critical for success
and how they vary across invaded ranges and with environmental features. We evaluated
the widespread recent invasion of Sahara mustard (Brassica tournefortii) in the southwestern
United States to understand the extent of functional trait variation across the invaded range
and how such variation is related to spatial and climatic gradients.
METHODS: We used a common garden approach, growing two generations of plants in
controlled conditions sourced from 10 locations across the invaded range. We measured
variation within and among populations in phenological, morphological, and physiological
traits, as well as performance.
KEY RESULTS: We found nine key traits that varied among populations. These traits were
related to phenology and early growth strategies, such as the timing of germination and
owering, as well as relative allocation of biomass to reproduction and individual seed mass.
Trait variation was related most strongly to variation in winter precipitation patterns across
localities, though variations in temperature and latitude also had signicant contributions.
CONCLUSIONS: Our results identify key functional traits of this invasive species that showed
signicant variation among introduced populations across a broad geographic and climatic
range. Further, trait variation among populations was strongly related to key climatic
variables, which suggests that population divergence in these traits may explain the
successful colonization of Sahara mustard across its invaded US range.
KEY WORDS Brassicaceae; Brassica tournefortii; common garden; desert; evolution;
functional traits; greenhouse; invasion; multiple generations; Sahara mustard.

July 2018, Volume 105 • Winkler etal.—Functional trait variation in Sahara mustard • 1189
physiological traits. Plasticity and rapid evolution of these traits in
novel environments likely facilitates expansion in invaded ranges
(Burton etal., 2010; Davidson etal., 2011).
Species invasions typically result from interacting features across
ecological, evolutionary, and organismal processes. As such, the
rapid alignment of phenological and morphological traits associ-
ated with favorable conditions for establishment (e.g., germination
timing, seed size) as well as the timing of reproduction are likely
necessary for most invasives to succeed (Muth and Pigliucci, 2006;
Wolkovich and Cleland, 2011; Novy etal., 2013; Nguyen etal., 2016).
Some invasive species have rapidly responded to invaded environ-
ments over short periods (e.g., <100 yr; Novy etal., 2012; Nguyen
etal., 2016). is has been shown to be true in invasive species in
desert systems worldwide (Chambers etal., 2007; Drenovsky etal.,
2012; Marushia et al., 2012; Merrill et al., 2012; Erskine- Ogden
etal., 2016). us, invaders in these systems may succeed only if
traits aecting tness are able to match local environments (e.g.,
rainfall variability and seasonal temperature covariance; Loik etal.,
2004). Such patterns would be consistent with strategies associated
with desert adaptation in ephemeral plants (e.g., Smith etal., 1997;
Huxman etal., 2013) and would suggest that invasive species exploit
trait relationships similar to those of native species that succeed in
these environments, but also that they likely employ enhanced per-
formance in several attributes that further success (e.g., Kimball
etal., 2014).
e range of Sahara mustard (Brassica tournefortii) is rapidly
expanding and negatively aecting natural ecosystems across the
southwestern United States (Barrows etal., 2009; VanTassel etal.,
2014). is invader has become increasingly common in arid and
semiarid regions throughout the Southwest since its putative in-
troduction in the 1920s (Sanders and Minnich, 2000). e species
has invaded ecosystems ranging from coastal Mediterranean in
California to hot desert localities from Arizona to Texas. Further,
Sahara mustard has several features that hint at its capacity to rap-
idly evolve. e species is a generalist and, as such, germinates un-
der a wide range of temperatures, light conditions, and soil depths
(anos etal., 1991; Jurado and Westoby, 1992; Chahuan etal., 2006;
Bangle etal., 2008). It is also highly fecund: the species is capable
of self- fertilization (i.e., facultative autogamy) and produces seeds
rapidly (~50 d from germination; Marushia et al., 2012) and in
high quantities (Trader et al., 2006) that can remain viable ≥1 yr
aer production. e species also exhibits some level of dormancy
(Adondakis and Venable, 2004; Chahuan etal., 2006), which may al-
low for buered population dynamics during unfavorable or unpre-
dictable conditions (Venable, 2007; Gremer etal., 2016). Individual
plants can produce >16,000 seeds annually that disperse via small
mammals, owing water, wind, and human transport (Trader etal.,
2006; Sánchez- Flores, 2007; Bangle etal., 2008; Berry etal., 2014).
Further, Sahara mustard’s ability to self- fertilize and its large dis-
tribution likely promote local adaptation and rapid range expansion
(Sakai etal., 2001) as well as establishment in new isolated localities
by single individuals. In other words, Sahara mustard has many of
the common traits associated with rapid population dynamics and
invasive success (Grime, 2006; Ordonez, 2010), but the functional
biology underlying its success, and how that varies across the in-
vaded range, is poorly understood. Previous modeling work sug-
gests that Sahara mustard might exist as a plastic, general- purpose
genotype (sensu Baker, 1965) such that the invaded range environ-
ment matches that of the native range (Li etal., 2015). However,
Sahara mustard occupies a large native range (Marushia et al.,
2012; Li etal., 2015) and likely exists as several genetically distinct
populations that have been separated by thousands of kilometers
and generations (Parker etal., 2003; Lawson Handley etal., 2011).
Further, it is most probable that Sahara mustard in the United States
is representative of only a small regional population from its native
range (i.e., Lombaert etal., 2010; Arnesen etal., 2017). Although a
few ecological studies have examined the species’ performance and
impacts in a few invaded areas (Barrows etal., 2009; Marushia etal.,
2010, 2012; VanTassel et al., 2014; Li etal., 2015), no research has
been conducted to determine how functional trait variation may
explain the success of this rapidly spreading invasive. us, Sahara
mustard is an ideal system to explore the functional biology under-
lying species invasions.
Our study aimed to identify key functional traits that explain
the success of Sahara mustard across a broad range of environments
in the southwestern United States. We tested for population diver-
gence in functional traits using multigenerational common garden
experiments, whereby we grew plants in common garden environ-
ments and matched plant traits to features associated with their
source environment locality. In doing so, we distinguished between
environmental, maternal, and ospring- level variation eects on
observed phenotypes. We predicted that phenological traits, par-
ticularly germination, would vary across populations with dierent
environmental cues (Wolkovich and Cleland, 2014). Specically, we
expected higher germination rates in populations from more xeric
sites because success of individuals at these sites would likely re-
quire that they take advantage of relatively rare, ephemeral rains.
We expected that precipitation would best predict variation across
all three functional categories of traits (phenological, morpholog-
ical, and physiological) because Sahara mustard occupies water-
limited environments that vary in precipitation regime in its native
range, and variable precipitation is critical in the southwestern
United States. We also expected to see variation among popula-
tions in allocation of biomass to leaves, with increased allocation in
populations that experienced increasing aridity across the species
range, suggesting increased competition for resources with native
species. Last, we predicted that water- use eciency (WUE) and leaf
nitrogen investment would vary among populations, with more arid
sites having higher WUE and leaf N, similar to other desert invad-
ers (Huxman etal., 2013; Kimball etal., 2014). Further, we expected
that winter precipitation would be a strong driver of reproductive
allocation. Overall, we predicted that divergence in functional traits
would explain Sahara mustard’s current invaded range.
MATERIALS AND METHODS
Species natural history
Sahara mustard (Brassicaceae: Brassica tournefortii Gouan) is an
annual native to the Mediterranean basin and much of the Middle
East through to western India (Prain, 1898; anos et al., 1991;
Aldhebiani and Howladar, 2013). It is considered a weedy species in
agricultural elds in parts of its native range (Ahmed etal., 2015; El-
Saied etal., 2015) but also has traditional dietary uses and economic
value in regions where it is cultivated (Singh etal., 2015; Guarrera
and Savo, 2016). Sahara mustard is an invasive throughout much
of Australia (Chahuan etal., 2006), South Africa (McGeoch etal.,
2009), Chile (Teillier etal., 2014), and western North America (Li
etal., 2015). In North America, the rst documented occurrence

1190 • American Journal of Botany
of Sahara mustard comes from a herbarium sample collected
in the Coachella Valley, California, in 1927. It is thought to have
been introduced as a contaminant of date palm translocation into
the hemisphere (Sanders and Minnich, 2000) and remained rela-
tively unnoticed except in the Coachella and Imperial valleys of
California’s deserts, where it was observed to be locally established
(Musil, 1948; Robbins etal., 1951). Herbarium records track its
spread to coastal California in the late 1950s and to Tucson, Arizona,
and Sonora, Mexico, in the early 1970s. e species apparently saw
a population boom beginning in the 1980s when it spread rapidly
throughout the Southwest (Sanders and Minnich, 2000).
Field sampling and common garden design
In spring 2015, we collected seeds from 20 individual plants from
10 locations spanning a ~10° latitudinal and ~15° longitudinal
gradient across Sahara mustard’s invaded U.S. range (Fig.1 and
Table1). Sites ranged from coastal Mediterranean to hot desert eco-
systems. Desert ephemerals such as Sahara mustard require expo-
sure to summer temperatures to break dormancy and cue seeds for
germination (Clauss and Venable, 2000; Huang etal., 2016). us,
we stored eld seeds in paper envelopes in the greenhouses at the
University of California, Irvine (daily mean temperature range: 26–
32°C) during summer 2015, aer which we stored seeds at room
temperature (~20°C) in the laboratory before growth experiments.
Sahara mustard seeds can remain viable 4–5 yr aer collection when
stored in a dark cool place as we have done (Chauhan etal., 2006).
We grew eld- collected seeds for two generations to account for
the inuence of maternal environment. From each maternal line,
we randomly selected three seeds and sowed them into the top 1 cm
of soil (sensu Chauhan etal., 2006) in 11.4 L containers. We used a
custom mix of 85% unwashed sand, 10% perlite, and 5% cactus mix
(Scotts Miracle- Gro). We placed containers randomly on green-
house benches but grouped by sampling site to prevent fertilization
across sites. Sampling sites were spaced out ~3 m. We randomly
rotated sampling- site containers weekly to control for any small-
scale environmental variation in the greenhouse. Greenhouse
temperatures were kept above freezing and below 24°C, averaging
15–20°C for the duration of the experiment, via an automated cli-
mate control system (GEM Link; QCOM, Irvine, California, USA).
Soils were watered regularly to keep seeds moist and encourage
germination. We surveyed daily for germination and removed any
additional germinants aer the rst individual emerged, to prevent
competition for resources within each pot. It is possible that this in-
troduced bias toward earlier- germinating plants in our study. ese
rst germinants, however, likely represent a major portion of the
trait variation in established seedlings in the eld (e.g., ompson
etal., 2001; James etal., 2006). Plants were fertilized weekly aer in-
dividuals produced two true leaves (Peter’s 20- 20- 20 solution, Scotts
Miracle- Gro). Outcrossing rates are incredibly low in Sahara mus-
tard (<10%; Winkler, 2017) and plants were allowed to self- pollinate
or cross- pollinate within sites. We harvested seeds from this rst
common garden generation once seedpods had visibly ripened but
before pods burst. We weighed seed and sowed them as above. Only
individuals of this second generation were used in analyses, to avoid
FIGURE 1. Sampling sites across the invaded range of Sahara mustard (Brassica tournefortii). See Table1 for site characteristics.
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0100 200 km
-119º W
-119º W
-110º W
-110º W
-36º N
CA1
-36º N
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AZ NM
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UT
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CA3
CA4
AZ1
AZ2
NM
TX
TABLE 1. Site codes, names, geographic locations, and elevation of Sahara
mustard sampling sites.
Code Location Latitude, longitude Elevation (m)
CA1 Nipomo 35.048, −120.512 128.22
CA4 In- Ko- Pah Park Road 32.647, −116.106 905.68
CA3 Coachella Valley Preserve 33.772, −116.304 24.64
CA2 Mojave National Preserve 34.803, −115.612 1193.11
NV Las Vegas 36.090, −115.233 726.88
UT Red Clis National
Conservation Area
37.225, −113.406 985.23
AZ2 Saguaro National Park 32.177, −110.739 962.64
AZ1 Dateland 32.801, −113.541 130.86
NM Mesquite 32.184, −106.678 1195.52
TX Fort Hancock 31.299, −105.832 1114.53

July 2018, Volume 105 • Winkler etal.—Functional trait variation in Sahara mustard • 1191
the inuence of maternal eects (Roach and Wul, 1987). In total,
we sowed 2000 eld- collected seeds from 115 maternal lines and
10 sampling sites. Not all seeds were viable, resulting in 1600 seeds
germinating from 87 maternal lines across the 10 sites.
Measurements
We measured phenological, morphological, and physiological
functional traits of the second ex situ generation. We chose traits
that have been shown to be important for invasives or that respond
strongly to environmental conditions typical of the desert biomes
invaded in North America (Leishman etal., 2007; Tecco etal., 2010;
Huxman etal., 2013; Kimball et al., 2014; Murphy et al., 2016).
Phenological traits included time to germination, leaf expansion,
and owering. We measured germination timing of each individual
as the days from seed sowing to germination. We tracked leaf phe-
nology daily during the rst month and every other day thereaer.
We recorded leaf expansion as the date of emergence for each of the
rst ve true leaves each individual produced. We recorded time to
owering as the number of days from germination to anthesis.
We measured several morphological traits, including
aboveground biomass components (including stem, leaf, and
reproductive- structure dry weights), relative growth rate, allocation
to leaf area, and allocation to reproduction. We randomly harvested
three plants from each locality biweekly starting 1 mo aer initial
germination and ending when seeds ripened. Harvesting lasted for
3 mo, or 6 harvesting sessions. We cut aboveground components
at the soil surface and sorted plant parts into leaves, stems, and re-
productive structures. Leaves were counted, weighed, and digitally
scanned using a Canon MF8200C printer (Canon, Tokyo, Japan)
and aLI- 3100C Area Meter (LI- COR, Lincoln, Nebraska, USA). We
calculated leaf area for the 25 largest leaves (or all leaves if <25 were
available) using ImageJ (Schneider et al., 2012). Any remaining
leaves were grouped for area measurements. We calculated mean
leaf area as the sum of the area of all leaves divided by the total
number of leaves. We then dried all plant components for 48h at
60°C to obtain dry weight. We estimated relative growth rates for
each population as the slope of linear regressions between log10
transformed aboveground biomass and time (sensu Angert etal.,
2007). Last, we calculated the percentage of biomass allocated to
reproductive structures (% repro) as the dry weight of reproductive
structures divided by the total aboveground biomass of each plant.
We also measured physiological traits, including water- use e-
ciency (WUE), leaf carbon (Cmass) and nitrogen (Nmass) content, and
relative water content of leaves. We collected leaf tissues prior to
owering and concurrent with the third harvest for isotopic anal-
ysis. Leaf 13C, Cmass, and Nmass were analyzed at the University of
California, Davis Stable Isotope Facility via an elemental analyzer
interfaced to a mass spectrometer (PDZ Europa, ANCA- GSL, and
PDZ Europa 20- 20; Secron, Cheshire, UK). We converted carbon
isotope ratios to discrimination values (Δ, per mil δ—a time-
integrated measure of water- use eciency; Dawson etal., 2002) by
the equation Δ = δa − δp / (1 + δp) × 0.0001, where δa is the car-
bon isotope ratio of atmospheric CO2 (assumed to be −8 δ) and δp
is the measured carbon isotope ratio of the leaf tissue (Farquhar
etal., 1989). Lower values of Δ indicate higher intrinsic WUE values
(Dawson etal., 2002).
We measured relative water content (RWC) of leaves at peak
productivity as a proxy for leaf turgor (Smart and Bingham, 1974).
We sampled three individuals from each site and used leaf punches
from the healthiest, fully emerged leaf from each plant. We obtained
fresh weights of leaf punches and then oated leaves in distilled wa-
ter in a Petri dish for 6 h in a dark room to allow for rehydration.
We obtained the assumed turgid weights and dried leaves for 24
h at 60°C to obtain dry weights. We used these data to calculate
RWC as wf − wd / wt − wd, where wf, wd, and wt are fresh weight, dry
weight, and turgid weight, respectively (Weatherley, 1950; González
and González- Vilar, 2001).
Environmental data
We used BioClim climate variables from each sampling site to test
for trait divergence and alignment with local environmental condi-
tions (Hijmans etal., 2005). ese climate variables represent annu al
and seasonal trends, as well as extremes in temperature and precip-
itation, which are oen useful in describing species distributions.
We evaluated 19 BioClim climate variables (BIO1–19; Hijmans
etal., 2005) at a 30 arc- second resolution (~1 km2) for inclusion in
our models. We tested all variables for pairwise correlation across
the study area using the Raster package in R to prevent overtting
(Hijmans and van Etten, 2012). We retained 7 of the 19 BioClim lay-
ers that had correlation coecients under |0.70| (Appendix S1; see
Supplemental Data with this article), four of which were related to
temperature and three to precipitation. When variables were highly
correlated, we retained those variables related most directly to our
hypotheses. For example, we retained those related to winter precip-
itation, because our study system exists as a winter ephemeral plant,
as well as variables that best captured the aridity gradient across
the species’ range. Temperature variables included isothermality
(tempiso; the mean monthly range divided by the annual range in
temperatures; BIO3), temperature seasonality (tempseasonality; stand-
ard deviation × 100; BIO4), and mean temperatures of the wettest
(tempwetqtr) and coldest (tempcoldqtr) quarters (BIO8–9). Precipitation
variables included precipitation during the wettest (precipwetmonth)
and driest (precipdrymonth) months (BIO13–14), and precipitation of
the coldest quarters (precipcoldqtr; BIO19).
Statistical analyses
We rst calculated summary statistics by population for key func-
tional traits associated with phenology, physiology, and morphol-
ogy (Appendix S2). We then used Pearson correlation coecients
to identify which traits best represented these functional trait cate-
gories and removed autocorrelated traits (r > |0.70|). Nine key func-
tional traits were retained for nal analyses. (Appendix S3). ese
functional traits were combined with the reduced set of geographic
and bioclimatic variables in subsequent analyses to understand var-
iation across localities.
We used nested analysis of variance (ANOVA) to examine po-
tential eects of site and maternal lineages as sources of variation
in functional traits. We included age of the plant as a covariate for
ANOVAs of non- phenology traits to account for potential time-
dependent ontogenetic eects associated with dierent harvests.
We log10 transformed measurements when needed to meet statis-
tical assumptions. We then used hierarchical partitioning if the
ANOVA showed signicant population dierences. Hierarchical
partitioning allowed us to examine the relative contribution of geo-
graphic and bioclimatic temperature and precipitation variables in
explaining variation in functional traits. Hierarchical partitioning
enables better estimation of the relative importance of each variable

1192 • American Journal of Botany
while also accounting for potential colinearity of explanatory varia-
bles (Chevan and Sutherland, 1991; Murray and Conner, 2009). For
each hierarchical partitioning analysis, we rst accounted for cor-
related error structures that arise from repeated measures (within
populations) and used linear mixed- eects models with each func-
tional trait as the response variable and maternal lineage nested
within population as random eects and related the residuals to ge-
ographic and bioclimatic variables using hierarchical partitioning.
We then performed randomization tests on each functional trait
(1000 iterations each using an r2 goodness- of- t measure) to assess
the signicance of each geographic and bioclimatic variable. We
computed Z- scores to determine the signicance of each explan-
atory variable. Last, we used linear regression to test relationships
between population means for each functional trait and the geo-
graphic and bioclimatic variables identied as signicant by rand-
omization tests (we report nonsignicant relationships in Appendix
S4). All statistical analyses were carried out in R version 3.3.2 (R
Core Team, 2014), and models were evaluated using the “eects”
package (Fox, 2003).
RESULTS
We found strong dierences among populations for all nine func-
tional traits (Table2), which suggests that trait divergence among
populations may play a role in inuencing plant performance across
the invaded range of Sahara mustard. is was evidenced most
strongly in phenological and morphological traits related to germi-
nation (days to germination: F8, 501 = 7.88, P < 0.001; seed weight:
F9, 119 = 3.70, P < 0.001) and early growth (days to rst leaf: F8 = 4.97,
P < 0.001; days to rst ower: F8 = 5.41, P < 0.001). ese traits var-
ied by 105%, 57%, 145%, and 99%, respectively, across the 10 local-
ities evaluated from the invaded range in North America. However,
populations also exhibited dierences in additional morphological
traits, including mean leaf area (F7, 113 = 3.49, P = 0.002) and propor-
tion of biomass allocation to reproduction (% repro; F8, 89 = 5.19, P <
0.001), which varied by 1143% and 1300%, respectively. Populations
also varied by 16%, 9%, and 121% for physiological traits related to
water stress and nutrient allocation—RWC (F8, 19 = 2.55, P = 0.045),
WUE (F7, 9 = 51.68, P < 0.001), and Nmass (F7, 9 = 19.87, P < 0.001).
Variation within populations was observed for each category of trait
variation (Table2). Signicant eects of maternal lineage were de-
tected for days to germination (F33, 501 = 5.92, P < 0.001), rst leaf
(F33, 489 = 4.97, P < 0.001), rst ower (F31, 332 = 2.12, P < 0.001), mean
leaf area (F27, 113 = 1.58, P = 0.05), WUE (F9, 9 = 84.16, P < 0.001), and
Nmass (F9, 9 = 11.63, P < 0.001).
Although several bioclimatic variables were important predic-
tors of trait variation, no single variable was most important across
all traits. Precipwetmonth explained four of the nine tested traits—pri-
marily phenological features (i.e., germination time advanced, and
number of days to rst leaf increased with increasing precipita-
tion) and morphological features (i.e., individual seed weight and
TABLE 2. Nested ANOVA results testing for eects of population, maternal lineage, and individual plant age on functional traits in Sahara mustard. Traits include
phenological measurements of the number of days to germinate (days to germ), leaf phenology (rst leaf), days to the rst ower (rst ower), individual seed weight
(seed wt; mg), mean leaf area (mm2), the percent of carbon allocated to reproductive structures (% repro), relative water content (RWC), water- use eciency (WUE; ∆),
and leaf nitrogen content (Nmass; μg). Signicant P values are in bold.
Trait
Population Maternal line Plant age Error
df SS F P df SS F P df SS F P df SS
Days to germ 8.00 12.61 7.88 <0.001 33.00 34.26 5.19 <0.001 – – – – 501.00 100.19
First leaf 8.00 10.15 4.97 <0.001 33.00 37.52 4.46 <0.001 – – – – 489.00 124.79
First ower 8.00 907.00 5.41 <0.001 31.00 1378.70 2.12 <0.001 – – – – 332.00 6958.30
Seed wt 9.00 0.72 3.70 <0.001 9.00 0.25 1.29 0.25 1.00 0.60 27.74 <0.001 119.00 2.59
Mean leaf area 7.00 7.60 3.48 <0.001 27.00 13.34 1.59 0.05 1.00 20.47 65.67 <0.001 113.00 35.31
% repro 8.00 0.13 5.20 <0.001 26.00 0.12 1.57 0.06 1.00 0.24 80.00 <0.001 89.00 0.27
RWC 8.00 3.30 2.55 0.05 15.00 2.87 1.18 0.36 1.00 0.10 0.60 0.45 19.00 3.07
WUE 7.00 0.01 51.68 <0.001 9.00 0.03 84.16 <0.001 1.00 0.00 59.11 <0.001 9.00 0.00
Nmass 7.00 1.14 19.87 <0.001 9.00 0.85 11.63 <0.001 1.00 0.33 40.05 <0.001 9.00 0.07
TABLE 3. Hierarchical partitioning results showing percentage of variance explained by individual geographic and bioclimatic variables. Asterisks indicate which
variables explained a signicant amount of variance based on randomization tests for hierarchical partitioning with an upper 95% condence limit (Z ≥ 1.65; statistical
results reported in Appendix S5). Traits include phenological measurements of the number of days to germinate (days to germ), leaf phenology (rst leaf), days to the
rst ower (rst ower), individual seed weight (seed wt; mg), mean leaf area (mm2), the percent of carbon allocated to reproductive structures (% repro), relative water
content (RWC), water- use eciency (WUE; ∆), and leaf nitrogen content (Nmass; μg).
Trait Latitude Long Elevation Tempseasonality Precipwetmonth Precipdrymonth Precipcoldqtr
Days to germ 11.93 10.10 12.27 11.73 22.33* 15.24* 16.39*
First leaf 9.07 10.65 38.70* 11.34 16.55* 6.17 7.52
First ower 12.57 11.71* 7.77 36.93* 10.90 9.30 10.81
Seed wt 5.81 10.87 20.82* 4.82 26.07* 21.12* 10.48
Mean leaf area 23.82* 9.89 21.67* 13.63 17.06 8.44 5.49
% repro 17.55 9.29 7.17 7.07 27.02* 15.38 16.53
RWC 4.13 12.26 41.85 6.99 12.80 5.78 16.19
WUE 12.72 17.41 26.09 12.03 17.98 7.46 6.30
Nmass 17.63 24.80 2.96 27.81* 11.29 10.03 5.48

July 2018, Volume 105 • Winkler etal.—Functional trait variation in Sahara mustard • 1193
allocation to reproduction decreased with increasing precipitation;
Table3 and Appendix S5). Elevation was also clearly important, ex-
plaining ~40% of the variation in timing of rst leaf and RWC (a
phenological and a physiological trait, respectively). In both cases,
elevation likely correlates with additional environmental variables
that drive leaf phenology and potential cellular water decit as
indicated by RWC (a physiological trait that increased with ele-
vation, tracking typical increases in precipitation with elevation).
Temp sea sonality also explained a substantial proportion of variation,
but only for timing of the rst ower (phenology; Table 3). For
physiological traits, the only bioclimatic variable that explained
variation was temperature seasonality, which had a positive rela-
tionship with leaf nitrogen content. All other geographic and biocli-
matic variables explained <30% of the variation in functional traits.
Precipwetmont h explained a percentage of variance for the highest
number of functional traits, including days to germination, timing
of the rst leaf, seed weight, and percentage of biomass allocated to
reproductive structures (% repro). All of these are functional traits
related to issues associated with aligning biological activity to con-
ditions during germination and early stages of growth. Longitude
explained a portion of variation in timing to rst ower, reecting
typical phenology patterns from the coastal to interior sites associ-
ated with growing- season constraints arising from aridity. Similarly,
variance in mean leaf area was explained by latitude. Finally, a per-
centage of variation in individual seed weights was explained by
precipdr ymonth, likely indicating a shi to investing in heavier seeds
that could survive hot summers in relatively dry environments.
e number of days to germination decreased with increasing
winter precipitation (precipw etmonth; r2 = 0.49, P = 0.03; Fig.2). Time
to rst leaf increased with longitude (r2 = 0.50, P = 0.05), again likely
following typical phenology patterns moving inland. Time to rst
leaf also increased with increasing winter precipitation (precipwetmonth;
r2 = 0.56, P = 0.03). Similar to hierarchical partitioning results, indi-
vidual seed weights decreased with increasing winter precipitation
and precipitation during the driest months (precipwetmonth; r2= 0.62,
P = 0.01; precipdrymonth; r2 = 0.52, P = 0.03). is trend was also ob-
served with percentage of biomass allocated to reproductive struc-
tures (% repro), which decreased with increasing winter precipitation
(precipwetmo nth; r2 = 0.80, P < 0.01; Fig. 2). Finally, the lowest RWC
(i.e., highest cellular water decit, although marginally signicant;
r2 =0.43, P = 0.06) was observed at the lowest elevations in desert
sites. Concurrently, the highest water- use eciency was observed at
these low- elevation sites (r2 = 0.68, P = 0.01) and followed precipdrymonth
(marginally signicant r2 = 0.47, P = 0.06; Fig.2), indicative of adapt-
ing to water stress.
DISCUSSION
Invasive populations may encounter unique selective pressures and
limitations across their ranges, including dierences in abiotic con-
ditions such as drought, temperature, and seasonality. Identifying
which plant traits have contributed to and may predispose invasives
to spread into novel environments allows us to better understand
the mechanisms driving invasion, predict future patterns, and pro-
vide targets for management (Funk etal., 2008). e results of the
present study demonstrate signicant variation in key functional
traits in Sahara mustard in a common garden environment, which
suggests that this species has responded to variable selection pres-
sures with dierent phenological, physiological, and morphological
strategies across a broad range of environmental conditions in the
southwestern United States. Further, we quantied the relative con-
tributions of geographic and bioclimatic factors in explaining var-
iation in observed phenotypes, showing that functional strategies
of Sahara mustard corresponded with local variation in seasonally
available precipitation. e shis in phenological, morphological,
and physiological traits observed among populations of Sahara
mustard are likely to have facilitated its successful invasion across
the region. is variation reects altered water- use eciency to
tolerate drought stress, adjustment in the timing of key biological
events within the context of aridity, and investment in reproduc-
tion to ensure future success. ese patterns are consistent with the
generalized strategies of desert adaptation used by ephemeral plants
(e.g., Smith etal., 1997; Huxman etal., 2013). is suggests that
Sahara mustard likely exploits trait relationships similar to those of
native species that are successful in these environments, but also
that it likely employs enhanced performance in several attributes
that further contribute to success (e.g., Kimball etal., 2014).
While the ecological and evolutionary patterns in arid systems
like those occupied by Sahara mustard are similar overall, regional
environmental contexts vary considerably, particularly in rainfall
variability and seasonal temperature covariance (Loik etal., 2004).
Functional trait approaches that relate species performance to en-
vironmental variation have proven useful for determining eects of
contemporary climate change (e.g., Kimball etal., 2010) and can be
powerful in elucidating the mechanisms that promote the success of
invasive species (Colautti and Barrett, 2013; Funk, 2013; Wolkovich
etal., 2013; Winkler etal., 2016; Gilbert et al., 2017). However, a
grand challenge in ecology and evolutionary biology is understand-
ing how invasive species respond to and leverage environmental
variation during establishment. is challenge is made more urgent
by the need to forecast ecological and evolutionary dynamics in the
face of climate change and future invasions.
Sahara mustard has colonized multiple ecoregions of North
America in <100 yr and appears well poised to continue to dom-
inate arid environments and expand its range. Part of this success
has been attributed to the ability of some invasives to self- fertilize
(Schemske, 1984; Barrett etal., 2008; Marushia etal., 2012; Pannell,
2015). Our results identify shiing phenologies, investment in
leaves and reproductive structures, and water- use eciencies to
match environmental drivers as critical for establishment and sur-
vival in the invaded range. Sahara mustard responded to decreas-
ing winter precipitation (precipwetmonth) by increasing allocation to
reproductive structures, thereby ensuring that seeds could tolerate
drought stress in the driest sites. Together, these reproductive and
functional traits likely allow Sahara mustard to overcome recruit-
ment barriers that challenge species in novel environments (Weber
and Schmid, 1998).
We found that Sahara mustard exhibits substantial population
variation in germination and growth related to local, seasonal
precipitation. In doing so, this species may be able to synchronize
its growth to local conditions, which would not only increase its
reproductive success, but also increase its competitiveness with
native species (Powell etal., 2011; Wolkovich and Cleland, 2011).
us, the level of trait divergence observed in our common gardens
is consistent with local adaptation, given the unlikely alternatives
that many distinct Sahara mustard genotypes invaded (Lawson
Handley et al., 2011; Colautti and Barrett, 2013; Oduor et al.,
2016; but see Genton etal., 2005; Oduor etal., 2015) or that ge-
netic dri serendipitously resulted in environmental correlations.

1194 • American Journal of Botany
at said, plasticity may also explain part of the trait variation
we observed. Nonetheless, our results suggest a genetic compo-
nent to the variation in functional traits in Sahara mustard, which
likely contributes to the continued success of the populations we
sampled. Given these populations’ variability across their range,
the ability to rapidly adapt to new environments may enable the
species to spread into additional semiarid or pulse- driven systems
(Drenovsky etal., 2012).
Phenotypic plasticity is oen important for successful establish-
ment of invasives early in the invasion process (Sexton etal., 2002;
Richards etal., 2006; Funk, 2008; Davidson etal., 2011; Castillo
et al., 2014). Plasticity can promote local adaptation by enabling
populations to persist in novel environments, in which they experi-
ence new selection pressures and potentially lose plasticity through
time (Parker etal., 2003; Franks etal., 2007; Ghalambor etal., 2007;
Crispo, 2008). While we cannot fully distinguish between xed
FIGURE 2. Linear regressions of functional traits and geographic and bioclimatic variables identied as signicant in hierarchical partitioning analy-
ses and with signicant linear regressions (r2 and P values are reported in each panel). Circle colors match those of each population in Figure1. Graphs
illustrate relationships between (A) days to germination and precipitation during the wettest month, (B) days to rst leaf and longitude, (C) days to rst
leaf and precipitation during the wettest month, (D) individual seed weight and precipitation during the wettest month, (E) individual seed weight
and precipitation during the driest month, (F) percentage of biomass allocated to reproductive structures and precipitation during the wettest month,
(G) relative water content (RWC) and elevation, (H) water- use eciency (WUE) and elevation, and (I) WUE and precipitation during the driest month.

July 2018, Volume 105 • Winkler etal.—Functional trait variation in Sahara mustard • 1195
and plastic variation in traits from our data, we did address pos-
sible maternal and ontogenetic eects on trait variation and have
evidence for population dierentiation in traits in a common gar-
den environment. It is likely that Sahara mustard also exhibits plas-
ticity, given its large range that contains many similar environments
(Tecco etal., 2010; Drenovsky etal., 2012). Future work to quantify
the relative contributions of xed and plastic variation in traits in
response to precipitation, temperature, and geographic position
would be productive for understanding the mechanisms driving in-
traspecic variation in traits. is would also elucidate the microev-
olutionary dynamics associated with the successful invasion of this
species and would be valuable to pursue using a reciprocal garden
design in both native and invaded ranges (Moloney etal., 2009).
An open question is how these processes interact to inuence plant
behavior, encompassing the complex system of multiple traits, and
how plasticity, population divergence, and ontogenetic dynamics
are combined across the range.
Overall, our results demonstrate that this species exhibits func-
tional trait variations across populations that correspond to envi-
ronmental variability across thousands of kilometers in its invaded
range. We have thus shown that linking life- history strategies, func-
tional traits, and responses to environmental variation can assist
in producing a mechanistically based predictive framework for
ecologists to understand the behavior of invasive species in space
and time (Huxman etal., 2013). Although many invasions arise
as a result of accidental introductions (Lehan etal., 2013), range
expansions of already established invasives may occur under fu-
ture climate scenarios (Novy etal., 2012; Nguyen etal., 2016), and
Sahara mustard seems poised for such an expansion. Sahara mus-
tard’s range of functional strategies across multiple environments,
coupled with self- compatibility and high production of propagules,
make it a strong contender for continued invasion under future sce-
narios (DeFalco etal., 2003; Nguyen etal., 2016).
ACKNOWLEDGEMENTS
is research was supported by the Tubb Canyon Desert
Conservancy, the Robert Lee Graduate Student Research Grant
through the Joshua Tree National Park Association, the Howie
Wier Memorial Conservation Grant through the Anza- Borrego
Foundation, the Forrest Shreve Student Research Fund through the
Ecological Society of America, the Mildred E. Mathias Graduate
Student Research Grant through the UC Natural Reserve System, the
Mayhew Graduate Research Award through the Boyd Deep Canyon
Desert Research Center, a Graduate Assistance in Areas of National
Need Research Grant (GAANN), UCI’s Department of Ecology &
Evolutionary Biology, the Ayala School of Biological Sciences, the
UCI Data Science Initiative at the University of California, Irvine,
and the Victor and Virginia Voth Family Trust. Additional funding
(to M.K.) was provided by UCI’s Summer Undergraduate Research
Program (UCI SURP). Plant material was collected under National
Park Service permit MOJA- 2015- SCI- 0021. Field, laboratory, and
greenhouse work was made possible with the help of A. Choi, A.
Collins, C. Bell, A. Dang, A, Desai, J. Dong, G. Ferguson, P. Holm, D.
Hughson, A. Kaiser, H. Kooner, A. Kearns, M. Li, K. Lund, K. Phan,
K. Rabbani, T. Scott, L. Smith, R. Staehle, C. Vagnier, S. Weller, and W.
Yang. anks to the Huxman and Gremer lab members and Center
for Environmental Biology sta for feedback on the manuscript, and
to three anonymous reviewers for their helpful comments.
DATA ACCESSIBLITY
Data have been archived through gshare under https://doi.
org/10.6084/m9.gshare.6175808.
SUPPORTING INFORMATION
Additional Supporting Information may be found online in the
supporting information tab for this article.
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