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Fine root morphology is phylogenetically structured,but nitrogen is related to the plant economics spectrumin temperate treesOscar J. Valverde-Barrantes*,1, Kurt A. Smemo1,2 and Christopher B. Blackwood1
1Department of Biological Sciences, Kent State University, Kent, OH 44242, USA; and 2The Holden Arboretum, 9500Sperry Rd, Kirtland, OH 44094, USA
Summary
1. Plant functional traits have revealed trade-offs related to life-history adaptations, geographi-
cal distributions, and ecosystem processes. Fine roots are essential in plant resource acquisition
and play an important role in soil carbon cycling. Nonetheless, root trait variation is still
poorly quantified and rarely related to the rest of the plant.
2. We examined chemical and morphological traits of 34 temperate arbuscular mycorrhizal
tree species, representing three main angiosperm clades (super-orders asterid, magnoliid and
rosid). We tested to what extent fine root chemical and morphological traits were correlated
similarly to the leaf economical spectrum (LES) or were structured by ancestral affiliations
among species.
3. Root traits did not display the same trade-offs as leaves (e.g. specific root length was not cor-
related with root N, whereas specific leaf area was correlated with leaf N). Moreover, 75% of
below-ground traits were phylogenetically structured according to Pagel’s k and Abouheif’s
Cmean autocorrelation tests, as opposed to 28% of above-ground traits. Magnoliids showed
thicker, less branched roots than asterids or rosids, but rosid roots exhibited lower N and higher
non-acid-hydrolysable (e.g. lignin) content than other species. In contrast, leaf traits did not dif-
fer significantly among super-orders. At the whole-tree level, chemical traits such as nitrogen tis-
sue content and lignin content were correlated between above and below-ground organs.
4. The distribution of root traits in woody temperate trees was better explained by shared
ancestry than by the nutrient content and structural trade-offs expected by the LES hypothesis.
Root chemistry and morphology differed substantially among species belonging to different
super-orders, suggesting deep divergences in resource acquisition strategies among major
angiosperm groups. Although we found partial support for the idea of whole-plant integration
based on corresponding nitrogen content across all organs (i.e. a plant economics spectrum),
our study stresses phylogenetic affiliation as the primary driver of root trait distributions
among angiosperms, a pattern that could be easily overlooked based solely on above-ground
observations.
Key-words: angiosperm evolution, arbuscular mycorrhizal trees, fine root traits, phylogenetic
trait conservatism, plant economics spectrum, root nitrogen content, specific leaf area, specific
root length
Introduction
Plant functional traits can be defined as morphological,
physiological or phenological attributes that influence the
fitness of individuals in their ecosystems (Reich et al. 2003;
Violle et al. 2007). Comparisons of functional traits have
revealed important axes of variation across species that
reflect fundamental biophysical trade-offs (Reich et al.
2003; Westoby & Wright 2006). The best known example
is the ‘leaf economic spectrum’ (LES), which predicts a
tight correlation between physiological, chemical and mor-
phological traits in leaves, ranging from leaves with high
photosynthetic rates, specific leaf area (SLA) and nitrogen
(N) but short life span, to leaves with lower metabolic*Correspondence author. E-mails: [email protected]; os.valver
© 2014 The Authors. Functional Ecology © 2014 British Ecological Society
Functional Ecology 2015, 29, 796–807 doi: 10.1111/1365-2435.12384
activity and N content but higher tissue protection and
longer life span (Reich et al. 1998; Wright et al. 2005). Life
history and adaptations to environmental conditions are
often considered the main drivers of the LES (Ackerley &
Cornwell 2007; Engelbrecht et al. 2007; Kraft, Valencia &
Ackerly 2008). Phylogenetic relationships, in contrast, are
rarely mentioned as a factor explaining LES syndromes,
particularly among broadleaf species. Milla & Reich
(2011), for instance, found little effect of phylogenetic
structure on the distribution of leaf traits among 57 pairs
of vicariant species growing at different altitudes in a tem-
perate broadleaf forest. Instead, leaf trait syndromes clo-
sely followed thermal regimes, indicating that ecological
filtering was far more important than shared ancestry in
explaining leaf trait differences of related species (Ackerly
& Reich 1999; Reich et al. 2003; Whitman & Aarssen
2010; but see Peppe et al. 2011).
Fine roots (the 2–3 most distal links in a root system,
Hishi 2007) exhibit wide interspecific variation in morpho-
logical and chemical traits in temperate woody plants
(Guo et al. 2008; Comas & Eissenstat 2009; Holdaway
et al. 2011). It has been suggested that such trait diversity
might be driven by trade-offs associated with stress toler-
ance, nutrient uptake rates and life-history strategies
(Grime et al. 1997; Comas & Eissenstat 2004; McCormack
et al. 2012). Because leaves and fine roots are both short-
lived organs specialized for resource capture, it is often
assumed that root trait variation is driven by compromises
between carbon investment and resource capture, similar
to those expected from the LES hypothesis. For example,
fine roots must be highly metabolically active to intercept
and take up water and nutrients from soil, requiring
investment in N to maintain transport systems, enzyme
activity and mycorrhizal symbioses (Reich et al. 2008).
Thus, correlation between N content and root respiration
rate may reflect a relationship between root N and meta-
bolic activity similar to that described for foliar organs
(Reich, Walters & Ellsworth 1997). Among woody temper-
ate trees, species classified as fast growers have shown
higher specific root length (SRL) and smaller diameter,
higher root N concentration, faster P uptake and higher
respiration rates than congeneric species with slower
growth rates (Reich et al. 1998; Comas, Bouma & Eissen-
stat 2002; Comas & Eissenstat 2004). Thus, it is possible
that fine root functional traits reflect similar trade-offs to
those predicted by the LES hypothesis (Reich et al. 2003;
Craine 2005).
An extension of the LES hypothesis states that the
adoption of an ecological strategy reflected by leaf traits
should also structure trait variation for all other organs
to maximize competitive ability (Grime et al. 1997; Reich
2014). This hypothesized integration of functional traits
across plant organs has gained recent support. Freschet
et al. (2010), for example, showed strong integration
among tissue types (leaf, stem and root) across 40 species
of subarctic flora, including 16 woody species. Integration
among leaf and root functional traits has also been
found in several grass or herb-dominated communities
(Craine et al. 2002; Birouste et al. 2011; Kembel & Cahill
2011; but see Tjoelker et al. 2005). However, studies
focused on woody plants seem to show lower integration
between leaf and root traits than non-woody plants. For
instance, Fortunel, Fine & Baraloto (2012) reported poor
correlation between foliar and coarse root traits in tropi-
cal trees. Hobbie et al. (2010) also reported no corre-
spondence between leaf and root chemical traits for 11
European tree species. Similarly, Withington et al. (2006),
Espeleta, West & Donovan (2009) and McCormack et al.
(2012) found poor correspondence between morphologi-
cal root traits, root life span and leaf life span among
temperate tree species grown in common gardens, con-
tradicting the idea of strong below- and above-ground
trait integration.
One potential explanation for the lack of clear inte-
gration of traits among roots and leaves in woody
plants is suggested by previous studies, which show a
stronger trait phylogenetic conservatism in roots (Baylis
1975; St. John 1980; Comas & Eissenstat 2009; Chen
et al. 2013) than is typically found in foliar tissues
(Wright et al. 2004). It has been hypothesized that this
trait segregation among plant lineages arose from the
unique association between roots and mycorrhizal fungi
(Brundrett 2002). Symbiotic associations with arbuscular
mycorrhizal (AM) fungi represent the ancestral state and
the most common association in terrestrial plants, cur-
rently present in >75% of angiosperms (Brundrett 2009).
AM fungi depend completely on root cortical tissue for
carbon and energy acquisition. Thus, Baylis (1975) pro-
posed that thick, non-branched, slow-growing roots were
the ancestral root type in basal angiosperms because
they are optimal for AM fungal colonization, which was
essential for the success of ancestral angiosperm groups
with little ability to obtain nutrient on their own. Subse-
quent adaptation of more recent angiosperm groups to
drier and colder conditions may have selected finer,
more branched root systems, thereby facilitating soil
exploration and nutrient absorption with less symbiotic
aid (St. John 1980; Brundrett 2002; Comas et al. 2012).
Although Baylis’ hypothesis is frequently mentioned to
explain root trait variation among angiosperm species
(Pregitzer et al. 2002; Comas & Eissenstat 2009; Hold-
away et al. 2011), few studies have addressed the ques-
tion using comparative analyses (Chen et al. 2013; Kong
et al. 2014), and little is known about how phylogenetic
conservatism in root traits may correspond with their
foliar counterparts.
In this study, we examined above- and below-ground
traits of temperate tree species representing three major
phylogenetic groups of woody angiosperms. We sampled
trees forming AM symbioses, allowing us to control for
confounding morphological and chemical modifications
associated with the switch to alternative mycorrhizal
groups. Our objectives focused on two questions: (i) Are
fine root traits more phylogenetically conserved than
© 2014 The Authors. Functional Ecology © 2014 British Ecological Society, Functional Ecology, 29, 796–807
Phylogenetic structure of woody root traits 797
corresponding above-ground traits? (ii) Even if traits are
phylogenetically conserved, does the integration of fine
root traits follow similar trade-offs as those expected based
on the LES hypothesis? For the first question, we hypothe-
sized that root traits would be more similar among closely
related species (Hypothesis 1.1). We expected that basal
angiosperms (i.e. the magnoliid clade) would be divergent
chemically and morphologically from more recently
derived groups (asterid and rosid clades). Moreover, we
hypothesized that phylogeny would be a more important
factor explaining below-ground than above-ground trait
variation (Hypothesis 1.2). For the second question, we
compared two possible but not mutually exclusive hypoth-
eses explaining the coordination between root morphologi-
cal and chemical functional traits of woody angiosperms.
If fine root functional traits follow trade-offs similar to
those observed in foliar tissues (Hypothesis 2.1, LES
hypothesis), we would expect significant correlations
between root morphological and chemical traits. Finally, if
resource capture strategies are integrated at the whole-
plant level (Hypothesis 2.2, Freschet et al. 2010), species
should show a full integration of above- and below-ground
trait syndromes commonly associated with life-history
strategy (Reich et al. 1998, 2003). Therefore, root chemical
and morphological traits should be correlated with above-
ground traits across species.
Materials and methods
STUDY SITE AND SAMPLE COLLECT ION
We sampled a set of 34 woody angiosperm species, plus two gym-
nosperms used as an out-group, replicated in two separate living
tree collections (Table S1, Supporting information, Fig. 1): The
Holden Arboretum, Ohio (40°570N and 82°280W) and Boone
County Arboretum, Kentucky (38°570N and 84°430W). The Hol-
den Arboretum (c. 300 m elevation) receives an average of 116 cm
Fig. 1. Phylogenetic relationship and trait value distribution for 36 woody species grown in common gardens in the Midwestern USA.
The traits displayed are (A) specific root length (SRL) for first-order roots; (B) ratio of non-acid-hydrolysable to nitrogen contents (NAH:
N) ratio for first-order roots; (C) above-ground branch tissue density and (D) specific leaf area (SLA). Symbol size indicates relative trait
values for each species, with smaller symbols closer to the mean value; black symbols represent values above the mean and white symbols
are below the mean. Branch lengths were standardized to have the same length; open circles represent ancestral nodes; filled circles sam-
pled species. The gymnosperms Ginkgo biloba and Thuja occidentalis were used as out-group.
© 2014 The Authors. Functional Ecology © 2014 British Ecological Society, Functional Ecology, 29, 796–807
798 O. J. Valverde-Barrantes et al.
precipitation per year, with an average annual temperature of
8 °C. The soils at Holden were formerly under mixed mesophytic
and beech-maple forest on gently sloped (2–6% slope) fine-silty,
mixed, active, mesic Aeric Fragiaqualfs from the Platea series.
Boone County Arboretum (c. 300 m elevation) receives 105–112 cm precipitation annually, with an average temperature of
11 °C. The site is located mostly on gently sloped fine-silty Aquic
Fragiudalfs in the Rossmoyne series, which, prior to clearing and
conversion to agriculture, was covered with deciduous hardwood
forest species typical of the oak-hickory region.
Our sampling design aimed to have a comparative representa-
tion of three main angiosperm lineages (i.e. magnoliids, asterids
and rosids) for temperate trees species forming only AM associa-
tions (Brundrett, Murase & Kendrick 1990; Wang & Qiu 2006).
Life-history description, phylogenetic relationships and details of
tree assembling are detailed in the Table S1. Above- and below-
ground samples were collected during mid-summer (July–August)
of 2010 and 2011. Samples from each species were taken from four
healthy adult trees (two individuals from each site) relatively iso-
lated from other woody plants. Root samples were obtained by
extracting two large soil cores (10 cm diameter 9 15 cm deep
PVC pipes) within 2 m of the main stem of each individual tree,
avoiding large (>5 cm diameter) roots. Samples were placed in air-
tight bags and stored at 4 °C. Additionally, roots exposed and left
in the soil were traced to the main stem and a small segment
(c. 10 cm long) that included 3–4 most distal root orders was
extracted, preserved in 45/5/50 water–acetic acid–formalin mixture
and used as a reference. In the laboratory, roots were separated
from soil by soaking in water for 12 h, gently washing with deion-
ized water and then comparing washed roots to the reference sam-
ple before further analysis.
Above-ground tissue was collected from the same individuals
that roots were taken from. The most distal branch sections that
included fully expanded sunlit leaves and first-year shoots were
cut at the junction with the basal branch. Leaves and twigs (long
shoots of first-year growth tissue with leaves still attached to the
stem) were detached from older branches immediately after collec-
tion. Leaves, twigs and branches were sealed individually in air-
tight polyethylene bags and maintained at 4 °C until fresh weight
and area could be measured (usually within 2 days; Wilson,
Thompson & Hodgson 1999). Leaf vouchers of each species were
collected and deposited in the Kent State University Herbarium
(accession numbers KS65950–KS65980).
MORPHOLOGICAL , ARCHITECTURAL AND CHEMICAL
TRA ITS
For root morphological analyses, we used five randomly selected
5- to 10-cm-long root systems comprised of the three most distal
root orders, which has been considered the portion of root sys-
tems analogous to leaf tissues (Xia, Guo & Pregitzer 2010). Root
systems were labelled according to Strahler’s stream ordering sys-
tem with the most distal roots labelled as the first order (Fitter
et al. 1991). Root image analysis of entire root systems was per-
formed using WINRHIZO software (Instrument Regent, Qu�ebec
City, QC, Canada) following Valverde-Barrantes et al. (2013) to
quantify specific root tip abundance (tips g�1 DRM), fractal
dimension and average link length (cm). Additional root systems
from each tree were dissected into three orders until c. 2 g of fresh
weight tissue was obtained from each root order. Roots from each
order (kept hydrated during dissection) were scanned, dried for
24–48 h at 65 °C and weighed. Image analysis and mass values
from each root order were combined to estimate average diameter,
SRL (m g�1 dry root mass, DRM), specific root surface area
(SRA, cm2 g�1 DRM) and root tissue density (RTD,
g DRM cm�3) for each root order from each sampled tree. For
chemical analysis, a subsample of each root set that was separated
by order was ground using a GenoGrinder (Spex SamplePrep,
Metuchen, NJ, USA) at 500 rpm for 1 min. Samples with exces-
sive fibrous material were frozen with liquid nitrogen and
ground manually with a mortar and pestle. All samples were
oven-dried again at 65 °C for 24–48 h. Proximate tissue compo-
sition was analysed in duplicates with a series of extractions as
described by Ryan, Melillo & Ricca (1990). Briefly, polar and
non-polar extractives were removed by consecutive extractions
with methanol and dichloromethane, respectively. The residue
from the polar/non-polar extractions was then separated into
acid-hydrolysable (AH; representing crystalline carbon polymers
like cellulose) and non-acid-hydrolysable (NAH; representing lig-
nin-like amorphous polymers) compounds using a two-stage
sequence of sulphuric acid digestions (Cusack et al. 2009).
Finally, all fractions were corrected for ash content after inciner-
ation of the NAH fraction at 500 °C for 4 h. Total %C and %
N were determined on duplicate 0�2–0�5 mg dried tissue samples
using an elemental analyser (Costech Analytical Model 4010,
Valencia, CA, USA).
For leaf area estimates, a minimum of five fully expanded leaves
including petioles were scanned on a flatbed scanner (Cornelissen
et al. 2003). Leaf dry matter content and SLA (cm2 g�1) were esti-
mated following Wilson, Thompson & Hodgson (1999). Leaf thick-
ness was estimated in situ measuring 10 freshly collected leaves
from each individual sampled at The Holden Arboretum. Each leaf
was measured at three points (tip, medium and base points, in the
middle of three randomly chosen leaflets in the case of compound
leaves) with an electronic thickness gauge (Eagle Technology,
Mequon, WI, USA, precision 0�01 mm) avoiding major veins or
irregular areas. Twigs and branches (including bark) were cut into
3–5 segments 2–5 cm long and scanned together, weighed, dried at
80 °C for 3 days and reweighed (Swenson and Enquist 2008). Den-
sity values for twigs and branches were calculated using volume
estimates from WinRhizo software. Additionally, we determined
fresh area per g for twigs (specific twig area, STwigA) and branches
(specific branch area, SBranchA) to have a common measured vari-
able for all tissues (analogous to SRA for roots and SLA for
leaves). Chemical analysis of above-ground tissues followed the
same procedure applied to root material.
DATA ANALYS IS
Testing for trait divergence among phylogenetic groups(Hypothesis 1.1)
We focused our analysis on differences between phylogenetic
groups at the super-order level. Firstly, we performed a linear
mixed-model ANOVA for each measured trait at the individual
level, using the REML criterion for model optimization (Bates,
Meechler & Bolker 2013). Fixed factors included super-order
(magnoliid, asterid, and rosid), site (Holden or Boone County
Arboretum), and tissue position (root order for below-ground
traits, and leaf, twig or branch for above-ground traits). Species
nested in clades was designated a random factor to account for
the non-independence of individuals of the same species. A post
hoc Tukey HSD test was performed to determine significant dif-
ferences among super-order groups. We also tested for differences
among super-orders in a multivariate context. Briefly, we created
chemical and morphological matrices for each root order and
above-ground tissue type. Then we performed a phylogenetic
principal component analysis (pPCA, Revell 2009) to find major
axes of trait variation in each tissue type. Finally, we tested for
differences among super-orders at the multivariate level by per-
forming a redundancy analysis on the first two pPCA axis of
each matrix (RDA, ter Braak 1986), using as factor matrix a cat-
egorical vector describing species at the super-order level (Jom-
bart et al. 2010).
© 2014 The Authors. Functional Ecology © 2014 British Ecological Society, Functional Ecology, 29, 796–807
Phylogenetic structure of woody root traits 799
Comparing phylogenetic conservatism between above-and below-ground traits (Hypothesis 1.2)
We tested the hypothesis of higher phylogenetic conservatism in
root traits compared with other organs by performing Abouheif’s
Cmean autocorrelation and Pagel’s k tests. Abouheif’s Cmean
analyses the autocorrelation of traits due to species topological
positions in the tree without including branch length in the calcu-
lations (Abouheif 1999; Thuiller et al. 2011). Pagel’s k coefficient
reflects the phylogenetic dependence of observed trait data with
respect to a pure Brownian model of evolution (Pagel 1999).
Both indices are therefore the most appropriate for phylogenetic
trees with standardized branch lengths (M€unkem€uller et al.
2012). Significance was estimated by comparing observed phylo-
genetic signal values to 999 permutations shuffling values at the
tips of the tree. Values significantly higher than zero indicate that
a trait is more similar among closely related taxa than expected
at random (phylogenetic signal sensu Jombart & Dray 2010).
To test whether below-ground trait variation is more often
structured by phylogeny than above-ground traits, we calculated
the difference between the number of traits showing significant A-
bouheif’s Cmean or Pagel’s k values and tested the significance
using permutation analysis assuming that equal number of traits
significantly structured by phylogeny but randomly distributed
among organs.
Correlations between morphology and chemistry withinplant tissues (Hypothesis 2.1)
We tested the LES hypothesis by calculating Pearson’s correla-
tions between species mean SRL and root C : N, and between
SLA and leaf C : N. Correlations were also calculated using phy-
logenetically independent contrasts to account for phylogenetic
non-independence of species (Felsenstein 1985). We also used a
coinertia analysis to test for trait correlations in an explicitly mul-
tivariate context. Coinertia analysis was performed on the infor-
mative morphological and chemical pPCA axes selected for
Hypothesis 1.1. This procedure finds a new set of ordination axes
that maximizes the coinertia, or sum of squared covariances,
between two data matrices, without being constrained by colinear-
ity or numbers of variables in the data matrices (Dray, Chessel &
Thioulouse 2003). We tested whether the observed coinertia value
was higher than expected by chance by performing a Monte Carlo
simulation test using 999 random permutations of the rows in
each matrix (Dol�edec & Chessel 1994).
Axes of variation integrating above- and below-groundtraits (Hypothesis 2.2)
To test for integrated variation in leaf and root traits, we first cal-
culated Pearson’s correlations, with and without phylogenetically
independent contrasts, between SRL and SLA and between root
and leaf C : N. Finally, we determined the coinertia between
above- and below-ground traits. pPCA axes included in the analy-
sis were projected in a multivariate ordination to look for domi-
nant axes of variation. To test the robustness of the correlation
among trait axes, we repeated the coinertia analysis comparing
above- and below-ground matrices before and after accounting for
phylogenetic effects using PIC scores as corrected values of all
pPCA axes (Baraloto et al. 2010).
All statistical analyses were performed in the R 2.12 statistical
platform (R Development Core Team, 2012) using the packages
lme4 (Bates, Meechler & Bolker 2013), picante (Kembel et al.
2010), ape (Paradis, Claude & Strimmer 2004), phytools (Revell
2012), adephylo (Jombart & Dray 2010), ade4 (Dray & Dufour
2004) and vegan (Oksanen et al. 2008). Trait variables were
log-transformed when necessary before statistical analysis to
account for heteroscedasticity and non-normal distribution of
residual error.
Results
TEST ING FOR TRA IT D IVERGENCE AMONG
PHYLOGENET IC GROUPS (HYPOTHESIS 1 .1 )
Similar above- and below-ground traits (e.g. per cent N)
showed similar ranges of variation among species
(Table S2). For the univariate linear mixed-model ANO-
VAs, the factors that significantly affected traits varied
among tissues (Table S3). Differences across tissues (root
orders or twigs vs. leaves) were the most important fac-
tor for most measured traits. Super-order was a signifi-
cant factor explaining most below-ground but not above-
ground trait variation, even after controlling for site and
root order, indicating a strong phylogenetic effect on
below-ground trait variation (Fig. 1, Hypothesis 1.1). Site
differences seemed to influence root chemical traits such
as polar and non-polar compounds and nitrogen content,
with Boone samples showing higher root N and polar
compound concentration but lower non-polar content
than Holden samples (Table S3). Above-ground, polar,
non-polar and AH content was also affected by site. In
a few cases, we detected an interaction between site and
super-order (Table S3). However, the interaction did not
alter the overall trait patterns observed among super-
orders.
Similarities among phylogenetic groups varied depend-
ing on the traits compared, as shown by the RDA ordina-
tion plots (Fig. 2). As expected from Baylis’ observations,
the morphology of magnoliid roots was significantly differ-
ent from asterid or rosid species (RDA analysis P < 0�005for first-order roots, Fig. 2a). Magnoliid roots were thicker
and less branched when compared with most root systems
of more derived angiosperm taxa. However, this observa-
tion did not hold for chemical traits. In this case, magno-
liid and asterid roots were on average different than rosid
roots (RDA analysis P < 0�005 for first-order roots,
Fig. 2c). Rosid species exhibited consistently lower N con-
tent and higher NAH : N ratio than other angiosperms
(Fig. 1, Table S3). A similar test for foliar traits showed
no significant differences among super-orders for either
morphological or chemical traits (P = 0�11 and 0�09,respectively, Fig. 2b,d).
COMPARING PHYLOGENET IC CONSERVAT ISM
BETWEEN ABOVE- AND BELOW-GROUND TRA ITS
(HYPOTHES IS 1 .2 )
The importance of phylogeny explaining trait variation
between above- and below-ground structures was con-
firmed by the phylogenetic signal analysis (Hypothesis
1.2). Both Abouheif’s and Pagel’s phylogenetic signal
tests were consistent with the conserved nature of root
© 2014 The Authors. Functional Ecology © 2014 British Ecological Society, Functional Ecology, 29, 796–807
800 O. J. Valverde-Barrantes et al.
traits across phylogenetic super-orders (72% and 56% of
the root traits studied showed significant phylogenetic
signal according to Abouheif’s Cmean and Pagel’s k,respectively, Table S4). The proportion of above-ground
traits with significant phylogenetic signal was lower
(28% and 33% of traits were significant according to
Abouheif’s Cmean and Pagel’s k, respectively). This lower
frequency of phylogenetic structure was significantly
different according to a permutation test (P = 0�0001 for
both Abouheif’s Cmean and Pagel’s k tests, Tables 1
and S4).
CORRELAT ION BETWEEN CHEMICAL AND
MORPHOLOGICAL TRA ITS WITH IN T ISSUES
(HYPOTHES IS 2 .1 )
The hypothesis that roots display a correlation between
chemical and morphological traits similar to that expected
from the LES hypothesis was not supported (Hypothesis
2.1). Increases in SRL, for instance, were not related to
C : N values (r = 0�24, P = 0�15, Fig. 3a), even though we
found the expected negative relationship in leaves for the
same species (r = �0�74, P < 0�005, Fig. 3b). At the multi-
variate level, we found a weak correlation between root
chemical and morphological pPCA trait axes (coinertia r
ranging from 0�17 to 0�34, Tables 2 and S5). Moreover,
coinertia values decreased after phylogenetic correction
(36% on average, Table 2), suggesting that part of the cor-
relation was explained by coupled root morphological and
chemical trait evolution. Similarly, twigs and branches
showed low coinertia between morphology and chemical
pPCA trait axes, which also decreased after phylogenetic
correction (Table 2). In contrast, leaf trait matrices showed
higher coinertia values (r = 0�40, P = 0�001) with no effects
of phylogeny on the relationship (Table 2).
CORRELAT IONS BETWEEN MORPHOLOGY AND
CHEMISTRY WITH IN PLANT T ISSUES (HYPOTHESIS 2 . 1 )
Specific root length was not related to SLA (r = �0�01,P = 0�97, Fig. 4a). However, the C : N ratio between
leaves and roots was closely related (r = 0�67, P < 0�001,
Table 1. Comparison of the level of phylogenetic structuring of 39
below-ground and 36 above-ground tissue traits measured in 34
species of angiosperms. Percentage of traits showing significant
phylogenetic signal (Abouheif’s Cmean index) in leaves, twigs and
branches and three orders of fine roots (N = 12 traits per tissue),
as well as the entire root system (all below-ground estimations
additionally included specific root tip abundance, fractal dimen-
sion and link length). Individual trait analyses shown in Tables S2
and S3
Trait Abouhief Cmean Pagel k
Leaf 25�00 33�33Twig 23�08 33�33Branch 36�36 33�33All above-ground 27�78 33�33First-order root 75�00 58�33Second-order root 66�67 50�00Third-order root 63�64 50�00All below-ground 71�79 56�41
Asterid
Magnoliid
Rosid Asterid
Magnoliid
Rosid
pPCA1 (98·4%)
Super-order F = 13·3, P < 0·001
(a)
Asterid Magnoliid Rosid
Asterid Magnoliid Rosid
pPCA1 (77·09%)
(b)
Asterid Magnoliid Rosid
Asterid Magnoliid Rosid
Super-order F = 12·2, P < 0·001
pPCA1 (44·28%)
pPC
A2
(22·
16%
)
(d)
Super-order F = 1·7, P = 0·09
Asterid Magnoliid
Rosid
Asterid Magnoliid
Rosid
pPCA1 (82·9%)
pPC
A2
(16·
2%)
Super-order F = 2·3, P = 0·11
(c)
LeavesFirst-order roots
pPC
A2
(1·3
%)
Mor
phol
ogy
pPC
A2
(9·8
4%)
Che
mis
try
Fig 2. Ordination of first-order fine root
and leaf morphological and chemical func-
tional traits. For all panels, axis values rep-
resent the first two phylogenetic principal
component analysis (pPCA) axes, and the
amount of variation explained by each axis
(horizontal axis representing the pPCA axis
that explained the largest amount of varia-
tion). Labels represent the centroid values
for each super-order (magnoliids, asterids
and rosids). P-values were obtained from
redundancy analysis (RDA) testing differ-
ences in traits among super-orders. pPCA
loadings for traits are shown in Table S4.
© 2014 The Authors. Functional Ecology © 2014 British Ecological Society, Functional Ecology, 29, 796–807
Phylogenetic structure of woody root traits 801
Fig. 4b). Displaying all informative pPCA axes in multi-
variate space revealed two orthogonal axes between mor-
phological and chemical functional traits (Hypothesis 2.2,
Fig. 5). The first axis of variation seemed highly associated
with root and leaf N content, with leaf morphology (SLA)
as the only morphological trait aligned with the N axis. In
contrast, other morphological traits aligned across a sec-
ond axis, depicting a weak coordination between root and
stem morphological traits, but still largely independent
from the N axis. Moreover, trait correlations were influ-
enced by relatedness among species. Coinertia values
between above- and below-ground traits decreased from
r = 0�38 (P = 0�001) to 0�14 (P = 0�04) after the incorpora-
tion of phylogenetic contrasts to the pPCA axes, suggest-
ing that about c. 20% of the covariation in chemical and
morphological traits can be explained by the co-evolution
between above- and below-ground resource acquisition
organs (Fig. 5).
C : Nroot1
10 20 30 40
SRL r
oot1
(m g
–1)
0
20
40
60
80
100
120
r = –0·24, P = 0·15PIC r = –0·06, P = 0·7
(a)
C : Nleaf
10 20 30 40
SLA
(cm
2 g–1
)
0
200
400
600
800
1000
AsteridsRosidsMagnoliidsGymnosperms
(b) r = –0·74, P < 0·0001PIC r = –0·81, P < 0·0001
Fig. 3. Correlation between morphological and chemical traits for
leaves and first-order roots. (a) Specific root length (SRL) and
C : N in first-order roots; and (b) specific leaf area (SLA) and
C : N in leaves. Coefficients correspond with uncorrected Pear-
son’s correlation (r) and phylogenetic independent contrast corre-
lation values (PIC r).
Table 2. Coinertia coefficients comparing the coordination
between morphological and chemical traits within different organs
of 34 woody angiosperm species grown in common gardens in the
Midwestern USA. Coinertia coefficients represent the sum of
squared variances between matrices representing morphological
and chemical traits for each organ before (Uncorrected) and after
phylogenetic correction (Phylo-corrected)
Uncorrected Phylo-corrected
Coinertia P-value Coinertia P-value
Leaf 0�40 0�001 0�40 0�001Twig 0�18 0�01 0�05 0�20Branch 0�04 0�63 0�02 0�53All above-ground 0�29 0�005 0�24 0�003First-order root 0�17 0�03 0�04 0�67Second-order root 0�32 0�001 0�23 0�03Third-order root 0�34 0�001 0�26 0�001All below-ground 0�22 0�009 0�14 0�04
C : Nleaf
10 20 30 40
C :
Nro
ot1
10
20
30
40
AsteridsRosidsMagnoliidsGymnosperms
(b) r = 0·67, P < 0·0001PIC r = 0·56, P < 0·0001
SLA (cm2 g–1)
200 400 600 800 1000
SR
L roo
t1 (m
g–1
)
0
20
40
60
80
100
120(a) r = –0·01, P = 0·97
PIC r = 0·02, P = 0·9
Fig. 4. Comparison of leaves and first-order roots. (a) Morpho-
logical traits specific root length (SRL) and specific leaf area
(SLA); (b) C : N ratio for leaves and first-order roots. Correlation
coefficients correspond with uncorrected Pearson’s correlation (r)
and phylogenetic independent contrast correlation values (PIC r).
© 2014 The Authors. Functional Ecology © 2014 British Ecological Society, Functional Ecology, 29, 796–807
802 O. J. Valverde-Barrantes et al.
Discussion
EVOLUT IONARY FORCES EXPLA IN ING ROOT TRA IT
SYNDROMES
Our results support Baylis’ original hypothesis of a consis-
tent difference between root morphologies of basal and
more derived angiosperms (Baylis 1975), which is also con-
sistent with data reported elsewhere (Holdaway et al.
2011; Chen et al. 2013; Gu et al. 2014; Kong et al. 2014).
However, to our knowledge, this is the first time that, in
addition to root morphology, root chemical make-up (par-
ticularly root NAH : N ratio) has been reported to be
structured by phylogenetic history within angiosperm lin-
eages. Moreover, the significant interaction between phylo-
genetic clade and root orders suggests that the degree of
trait differentiation from distal to basal roots is also phylo-
genetically structured. Therefore, the evolutionary process
shaping functional traits in tree roots affects not only
individual root links but also the integration of root orders
at the entire root system level.
To explain hypothesized phylogenetic patterns in root
morphologies, Baylis (1975) suggested mycorrhizal depen-
dency as an important factor promoting morphological
conservatism among angiosperm root systems. This view is
consistent with theoretical evolutionary models indicating
high stability and phylogenetic conservatism in mycorrhi-
zal associations due to the complex genetic signalling
between microbial symbionts and plant roots (Kiers & van
der Heijden 2006; Markmann & Parniske 2008; Davison
et al. 2011; Kiers et al. 2011). Recent empirical studies
have also related root morphology, particularly root diam-
eter and cortex area, to the level of mycorrhizal coloniza-
tion in woody plants (Guo et al. 2008; Gu et al. 2014;
Kong et al. 2014). However, it is important to highlight
that this trend between root diameter and mycorrhizal
dependency could be limited to AM associations. Ectomy-
corrhizal associations, for instance, do not depend as heav-
ily on cortical cells for habitat because ectomycorrhizal
species create their own mantle around the root tip, thus
being less influenced by interspecific variation in root
diameter for colonization and development (Kong et al.
2014).
Another recent hypothesis is that root trait diversity in
angiosperms appeared as an adaptation to the emergence
of colder and drier climate during the Late Cretaceous
(Fletcher et al. 2008; Comas et al. 2012). According to this
hypothesis, more modern angiosperm lineages, as well as
several gymnosperms, increased lignification and reduced
xylem vessel size as they expanded into more xeric and
colder areas, becoming dominant in areas constrained by
water availability (Pittermann et al. 2012). It is thus possi-
ble that concomitant increases in SRL and tissue lignifica-
tion and decreases in diameter were a consequence of
selection for more efficient root systems in drier and colder
environments than the wet tropical sites where angio-
sperms possibly originated (Feild & Arens 2007; Feild,
Chatelet & Brodribb 2009). This view also suggests that
Coinertia axis 1 (30·9%)–1·5 –1·0 –0·5 0·0 0·5 1·0 1·5
Coi
nert
ia a
xis 2
(6·2
%)
–1·0
–0·8
–0·6
–0·4
–0·2
0·0
0·2
0·4
0·6
SLA
Twig D
STwigA
Branch D
SBranchALeaf N
Twig N
Branch N
Branch AH
SRL1
SRL2
SRL3
RTD3Root N1
Root N2Root N3
Above-ground chemical traitsBelow-ground chemical traitsAbove-ground morphological traitsBelow-ground morphological traits
Coinertia = 0·38, P < 0·0001
Phylo-coinertia = 0·14, P = 0·04
Fig. 5. Coinertia ordination of above-ground and below-ground chemical and morphological functional traits of leaves, twigs, branches
and three orders of roots. Traits shown are informative pPCA axes, and names represent the individual trait with the highest loading value
for that pPCA axis (see Table S4). Coinertia and phylo-coinertia r values represent the level of coinertia between above- and below-
ground matrices before and after performing phylogenetic contrast on pPCA axis. Both coinertia tests were significant (P = 0�0001 and
0�04 for coinertia and phylo-coinertia, respectively). For the morphological traits, SRL = specific root length for root orders 1, 2 and 3;
RTD3 = root tissue density for third-order roots; SLA = specific leaf area; SBranchA = specific branch area; STwigA = specific twig area;
D_Branch = branch diameter; and D_Twig = twig diameter. For chemical traits, N represents tissue nitrogen for each tissue;
Branch_AH = branch acid-hydrolysable content.
© 2014 The Authors. Functional Ecology © 2014 British Ecological Society, Functional Ecology, 29, 796–807
Phylogenetic structure of woody root traits 803
increases in root surface area and tissue lignification were
important adaptations to cope with low N availability,
slow decomposition rates and rough climatic conditions
common to temperate forests (Ostonen et al. 2007).
Highly branched and finer structure of roots is typically
associated with ectomycorrhizal or ericoid mycorrhizal
roots (Brundrett 2002), which developed within the rosids
and asterids, respectively. However, our data demonstrate
the presence of these root trait syndromes in AM plants,
the ancestral mycorrhizal relationship, within these lin-
eages. This supports the view that these root trait syn-
dromes were acquired by AM plants before the switch to
new fungal partners. Furthermore, fossil records indicate
that basal rosid families (i.e. Altingiaceae, Cercidiphylla-
ceae and Hamamelidaceae) have been historically distrib-
uted in temperate or high-altitude tropical forests (Wolfe
1997; Zhou, Crepet & Nixon 2001; Qi et al. 2012). Because
these basal rosid families are highly dominated by AM
associations (Wang & Qiu 2006), root traits such as
reduced diameter, high lignification and reduced link
length were likely acquired by an ancestor as a set of adap-
tations to colonize temperate areas (Wang et al. 2009).
Further analysis of root chemistry, morphology and physi-
ology in species from divergent evolutionary clades across
latitudinal gradients may help to elucidate the evolutionary
steps associated with the acquisition of root trait syn-
dromes (Guo et al. 2008), adaptive advantages under dif-
ferent ecological constraints (Gu et al. 2014) and
evolutionary processes leading to alternative mycorrhizal
partnerships.
TRA IT INTEGRAT ION AND EVOLUT ION IN ANGIOSPERM
ROOTS
Strong correlations among leaf functional traits such as
SLA and N content have been consistent across species
differing in growth form and biome distribution (Reich,
Walters & Ellsworth 1997; Wright et al. 2005). This strik-
ing global pattern suggests fundamental biophysical trade-
offs between the maximization of carbon fixation and the
minimization in water losses that limit the possible pheno-
typic combinations in foliar traits that can be successful
under natural selection (Boyce et al. 2009; Beerling &
Franks 2010; Donovan et al. 2011). A recent review by
Cornwell et al. (2014) also showed substantial variation in
leaf traits among closely related species, whereas consis-
tency between phylogeny and leaf trait values was limited
to a few highly specialized families adapted to extreme
environments. Thus, leaf traits in angiosperms seem less
constrained by ancestry and more influenced by environ-
mental conditions and life-history strategies.
Because LES has such significant influence on the under-
standing of functional trait variation (Wright et al. 2004;
McGill et al. 2006), the spectrum separating ‘fast-’ and
‘slow-growing’ species has been repeatedly applied to func-
tional trait variation in other organs, particularly fine roots
(Tjoelker et al. 2005; Kembel & Cahill 2011). Our results,
however, do not support this assumed similarity between
roots and leaves. We did not find significant correlations
between root chemical and morphological traits, suggest-
ing that morphological and chemical traits are decoupled
at the root system level. In fact, we found some species
with root trait combinations that seem contradictory to
patterns expected from the LES. For instance, some rosid
species with high SRL showed relatively high C : N ratio,
whereas magnoliids, which showed the lowest SRL, had
relatively lower C : N (Fig. 3). From the same individual
trees, we did find the expected correlations among leaf
traits, implying that the below-ground results are not an
artefact of biased sampling or lack of trait variation across
species.
In agreement with other studies involving woody plants
(Ishida et al. 2008; Baraloto et al. 2010; Fortunel, Fine &
Baraloto 2012; Chen et al. 2013), we found limited sup-
port for the idea that all tree organs are coordinated in a
whole-plant resource use strategy. The decoupling of root
chemical and morphological traits suggests that roots dis-
play a broader array of possible trait combinations than
foliar tissues for maximizing functional gains and mini-
mizing construction and maintenance costs (Donovan
et al. 2011; i.e. broader ‘phenotypic space’ sensu Pigliucci
2007). As explained above, the acquisition of functional
trait syndromes in fine roots arose independently among
plant lineages as adaptations to improve soil exploration,
deal with contrasting climatic limitations and different
mycorrhizal communities. As roots are exposed to a more
complex abiotic and biotic environment than leaves, and
the possibilities to maximize function seem broader than
those of foliar tissues, it is possible that species with simi-
lar leaf traits could present significantly different root sys-
tems.
However, this does not mean that organs are completely
independent from each other. The low but significant cor-
relation between morphological traits of roots and
branches may indicate common selective forces (e.g. simi-
lar thermal and hydraulic stresses experienced by roots
and stems), which could lead to the integration of a similar
set of functional traits. The fact that some traits, such as
tissue density, are structured phylogenetically in both roots
and stems (Swenson & Enquist 2007; Mart�ınez-Cabrera
et al. 2009; Poorter et al. 2010), could also indicate that
the ontological process involved in the construction of
these tissues is shared. However, the fundamentally differ-
ent functions of fine roots and stems, and the additional
anatomical adaptations associated with mycorrhizal com-
munities in fine roots, may limit the extent to which these
tissues can be coordinated.
In contrast, the strong correlation in N content across
plant tissues highlights the possibility of a coordinated
trait axis representing ecological strategies in plants. Nitro-
gen levels in plant tissues are usually associated with pro-
tein content, respiration and overall metabolic activity
(Evans & Seemann 1989; Lambers, Robinson & Ribas-
Carbo 2005). A previous metaanalysis by Reich et al.
© 2014 The Authors. Functional Ecology © 2014 British Ecological Society, Functional Ecology, 29, 796–807
804 O. J. Valverde-Barrantes et al.
(2008) proposed a common relationship between N con-
tent and respiration rates for all plant organs. In grasses
and forbs, the full integration of fine root and leaf N con-
tent is well-established (Craine et al. 2002; Tjoelker et al.
2005), but relatively few studies have evaluated similar
integrations in woody plants (Reich et al. 1998; Wright &
Westoby 1999; Laughlin et al. 2010). Our results support
the hypothesis that N content reflects inherent physiologi-
cal and life-history trade-offs across ecological guilds that
are consistent across the entire plant (Wright et al. 2004),
and not strongly structured by phylogenetic background
(Reich et al. 2008). Future studies linking root N content
with physiology and particularly nutrient acquisition rates
in woody plants are an important follow-up to this study.
In summary, this work highlights the relevance that phy-
logenetic patterns may have in the understanding of fine
root trait patterns at the interspecific level (Mueller et al.
2010; Kembel & Cahill 2011). However, it is important to
note that we have a relatively small sample of temperate
woody angiosperms that do not provide a complete picture
of angiosperm root evolution. Expanding this study to
include subtropical and tropical species and under-repre-
sented phylogenetic groups could help to elucidate the
scope of our conclusions (Donaghue 2008). Moreover, this
study was intentionally designed to minimize the influence
of environmental factors on root traits. Soil conditions can
influence the link between above- and below-ground func-
tional traits at the community level (Zangaro et al. 2007;
Holdaway et al. 2011), and both foliar and root traits in
trees have been reported to vary independently as a way to
adapt to variations in nutrient availability (Comas & Eis-
senstat 2004; Espeleta, West & Donovan 2009; Freschet
et al. 2013). Nonetheless, considering that root trait varia-
tions due to plasticity are small compared to observed var-
iation across species (Chen et al. 2013; Valverde-Barrantes
et al. 2013), we argue that the patterns found in this are
key to understanding root trait variation within and across
woody plant communities. Such information could be use-
ful in our current understanding below-ground ecological
processes and also assessing the ecological role of fine
roots over geological time-scales (Donaghue 2008; Crisp
et al. 2009; Pittermann et al. 2012).
Acknowledgements
The authors would like to thank Scott Kelsey, Amber Horning, Suhana
Chattopadhyay, Eugene Ryee, Kristine Nissel, Benjamin Villareal, Haren
Bonepudi, Josh Lucas, Mariana Romero, Jean Carlo Valverde, Mike Fulp
and Carlynn Fulp for their assistance in the field and processing samples.
Special thanks to Ethan Johnson from The Holden Arboretum and Kristo-
pher Stone and Josh Selm from Boone County Arboretum for their advice in
selecting tree individuals, and to Charlotte Hewins from The Holden Arbo-
retum for sample processing help. We also thank Andrea Case, Jean Burns
and Kevin Mueller for commenting on earlier drafts of the manuscript. This
study was supported by grants from the U.S. National Science Foundation
(DEB-0918240, DEB-0918878) and Department of Energy (DE-SC000433),
start-up funds provided Kent State University, an Art and Margaret Herrick
Research Grant, a David and Susan Jarzen Scholarship, The Holden Arbo-
retum Trust and The Corning Institute for Education and Research. No con-
flicts of interest were declared upon the publication of this manuscript.
Data accessibility
Data used in this manuscript are deposited in the online data repository
Dryad doi: 10.5061/dryad.53mc6.
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Received 18 April 2014; accepted 23 October 2014
Handling Editor: Natalia Norden
Supporting Information
Additional Supporting information may be found in the online
version of this article:
Table S1. Life-history traits of 36 temperate tree species used for
the description of above- and below-ground traits in this study.
Table S2. Summary description of morphological and chemical
traits for three root orders, leaves, twigs and branches of all 36
species studied.
Table S3. Analysis of variance comparing phylogenetic groups
(Super-order) and tissue differences for all traits measured in 34
angiosperm tree species in two different common gardens.
Table S4. Phylogenetic signal values for functional traits in 34
woody angiosperm species.
Table S5. Loadings for phylogenetic principal component analysis
(pPCA) on morphological or chemical traits for three orders of
roots, leaves, twigs and branches of 34 species of woody angio-
sperms.
© 2014 The Authors. Functional Ecology © 2014 British Ecological Society, Functional Ecology, 29, 796–807
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