Download leaf functional traits vary with the adult height of plant species in

Journal of
Plant Ecology
Volume 7, Number 1,
Pages 68–76
February 2014
doi:10.1093/jpe/rtt023
Advanced Access publication
15 May 2013
available online at
www.jpe.oxfordjournals.org
Leaf functional traits vary with the
adult height of plant species in
forest communities
Dongmei Jin1,2, Xuecui Cao1,2 and Keping Ma1,*
1
State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, 20
Nanxincun, Xiangshan, Beijing 100093, China
2
Graduate School of Chinese Academy of Sciences, 19 Yuquan Road, Beijing 100049, China
*Correspondence address. State Key Laboratory of Vegetation and Environmental Change, Institute of Botany,
Chinese Academy of Sciences, 20 Nanxincun, Xiangshan, Beijing 100093, China. Tel: +86-10-6283-6223;
Fax: +86-10-8259-9518; E-mail: [email protected]
Abstract
Aims
Within-community variation accounts for a remarkable proportion
of the variation in leaf functional traits. Plant height may be used to
explain within-community variances of leaf traits because different
microenvironments, especially light intensity, may occur at different heights. This study determines whether or not leaf nitrogen (N)
and phosphorus (P) contents as well as leaf mass per area (LMA)
are interspecifically correlated with the adult height of forest woody
species. We also discuss these relationships with respect to community structure and functions of the ecosystem.
Methods
A total of 136 dicotyledonous woody species from 6 natural forests
(3 evergreen and 3 deciduous ones) in East China (18°44′–45°25′N,
108°50′–128°05′E) were investigated. For each of the 157 species–site
combinations, 6 traits were measured: plant adult height relative to
the forest canopy (HR), leaf N and P contents per unit area (Narea and
Parea), N and P contents per unit dry mass (Nmass and Pmass) and LMA.
The total variances of each leaf trait across sites were partitioned in
a hierarchical manner. The relationships between leaf traits and HR
within forest communities were then analyzed using both standardized major axis regression and Felsenstein’s phylogenetic independent contrasts. Relationships between evergreen and deciduous forests
were compared by linear mixed models.
Important Findings
HR is a robust predictor of leaf Narea, Parea and LMA, explaining
36.7%, 39.4% and 12.0% of their total variations across forests,
respectively. Leaf Narea, Parea and LMA increased with HR in all of
the studied forests, with slopes that were steeper in evergreen forests
than in deciduous ones. Leaf Nmass and Pmass showed no significant
relationship with HR generally. The increase in leaf Narea, Parea and
LMA with HR across species is assumed to maximize community
photosynthesis and may favor species with larger HR.
Keywords: leaf traits, nitrogen, phosphorus, height, interspecific,
phylogeny
Received: 13 March 2012, Revised: 2 April 2013,
Accepted: 17 April 2013
Introduction
Nitrogen (N), phosphorus (P) and dry mass input in leaves are
essential for leaf structure, plant photosynthesis and growth.
Leaf N and P contents (both area and mass based) and leaf mass
per area (LMA) are some of the most important functional
traits in the leaf economic spectrum (Reich et al. 1997, 1999;
Wright et al. 2004). How these traits change with respect to the
environment has aroused significant research interest (Craine
et al. 2001; He et al. 2008; Ordonez et al. 2009; Reich and Oleksyn
2004; Wright et al. 2005a). Previous studies have found that
climate or soil factors explain only a minor aspect of the total
variation in leaf traits. Climate explains 18% of the variation
along the principal multivariate trait axis at the global scale
(Wright et al. 2005b), while climate and soil variables explain
11% of the total variation in leaf traits across Chinese grasslands
(He et al. 2010). Moreover, the mean variation among species
within a site is no less than the variation among sites that differ
markedly in climate or soil (He et al. 2010; Wright et al. 2005b).
Thus, seeking the drivers of trait variation across species
coexisting within a community must be performed to allow
prediction of possible changes in the community structure and
functions of the ecosystem under climate change (Diaz and
Cabido 1997; Lavorel and Garnier 2002).
© The Author 2013. Published by Oxford University Press on behalf of the Institute of Botany, Chinese Academy of Sciences and the Botanical Society of China.
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Jin et al. | Vertical patterns of leaf traits in forests69
Plant height is a potential driver of leaf trait variation within
a community. According to the Beer–Lambert law, light intensity from the canopy of a forest may decrease exponentially
with increasing accumulative leaf area index (LAI) down
through the forest (Lüttge 2008). For example, in mature
temperate or tropical forests, only 1%–2% of the light shed
on the forest canopy can reach the forest floor (Molles 2008).
Air temperature and relative air humidity also vary with plant
height in a community (Lüttge 2008). As a result, plant height
largely determines the microenvironments of leaves and
regulates various leaf morphological and physiological traits
(Anten and Hirose 2003; Bassow and Bazzaz 1998; Woodruff
et al. 2008). In particular, area-based leaf N content and photosynthetic capacity have been observed to increase with
plant height and ambient light intensity among intraspecific
individuals (Ellsworth and Reich 1993; Winner et al. 2004).
Area-based leaf N and P contents as well as LMA have been
observed to increase across species from the under- and midstories of tropical rain forests up to their canopy (Bigelow
1993; Cavaleri et al. 2010). However, given the differences in
species compositions and canopy structures in subtropical or
temperate forests from tropical forests, knowledge about the
interspecific patterns of leaf trait–height relationships in subtropical or temperate forests is limited. Moreover, whether or
not differences exist between the patterns of evergreen and
deciduous forests is also unclear.
In this study, the leaf trait–height relationships within six
natural forests in East China were investigated. The studied
forests represent a full spectrum of typical forests ranging
from a tropical rain forest to a mixed deciduous–coniferous
forest across latitude in East China. Five leaf traits were measured: LMA, leaf N and P contents per unit area (Narea and
Parea) as well as leaf N and P contents per unit dry mass (Nmass
and Pmass). The adult height of each species was divided by
the canopy height of the local community to determine the
relative height of species in a community (HR) for comparison among forest communities. This study aims to investigate
(i) the extent to which HR within a forest explains the total
variance of each leaf trait, (ii) the changes in leaf N and P
contents as well as LMA as HR increases across species within
a community and (iii) possible differences in the patterns of
leaf N and P contents with respect to HR across different forest
communities.
Materials and Methods
Site description
The six forests investigated in this study are natural old-growth
forests located in preserved areas. The forests, from south to
north (from 18°44′ to 45°25′N), are Jianfengling, Dinghushan,
Gutianshan, Baotianman, Changbaishan and Maoershan
(see Table 1 for details). These forests differed considerably
in terms of mean annual temperature (from 2.8 to 20.9°C)
and mean annual precipitation (from 724 to 2652 mm). Their
canopy heights varied from 13 m in Gutianshan to 41 m in
Maoershan. The Jianfengling, Dinghushan and Gutianshan
forests were evergreen forests, whereas the Baotianman,
Changbaishan and Maoershan forests were deciduous ones.
Field sampling
Field sampling was conducted from mid-July to mid-August
in 2007 and 2008. We sampled abundant woody species, all
dicotyledonous, from continuous forests. Care was taken
to avoid dramatic changes in terrain. Based on former field
investigations for each site (Hao et al. 2008; Li 1994; Ye et al.
2008; Zhu et al. 2008), the sampled species contributed 60%–
80% of the coverage of the local forest communities. A total
of 136 species (including 105 tree species and 31 shrub species) from 85 genera and 44 families were collected. For each
of the 157 species–site combinations, 3 adult individuals were
sampled. Samples were collected from sunlit tree crowns
using a pole tree pruner with the aid of tree climbing when
necessary. At least 20 healthy and fully expanded leaves/leaflets from at least 3 twigs were collected (leaves from the current and previous years were included for evergreen species).
Individual plant height, which is the vertical distance from
the ground level to the top of a plant, was measured using a
laser rangefinder (ProStaff 550, Nikon, Japan) and a clinometer (Cornelissen et al. 2003). The relative height of a species
in the local community was calculated from the average plant
height of three individuals divided by the maximum height
sampled (as canopy height in Table 1) in the same community.
Table 1: location, climatic traits and forest attributes of the six forests studied in East China Site
Location
Elevation (m) MAT (°C) MAP (mm) Climate zone
Jianfengling
Canopy height (m) Vegetation type
18°44′N, 108°50′E
1000
19.7
2652
Tropic
18
Rainforest
Dinghushan
23°10′N, 112°32′E
250
20.9
1985
Subtropic
22
Evergreen forest
Gutianshan
29°15′N, 118°07′E
580
14.2
1860
Subtropic
13
Evergreen forest
Baotianman
33°29′N, 111°55′E
1400
10.0
919
Warm temperate 15
Deciduous forest
Changbaishan 42°23′N, 128°05′E
800
4.6
752
Temperate
27
Mixed deciduous–coniferous forest
Maoershan
480
2.8
724
Temperate
41
Deciduous forest
45°25′N, 127°40′E
Climate data were collected from Chinese terrestrial ecological information with a resolution of 1 × 1 km from 1971 to 2000 (Yu et al. 2004).
Abbreviations: MAP = mean annual precipitation, MAT = mean annual temperature.
70
Laboratory measurements
Petioles or rachises were removed from each sample and
leaf blades were scanned to measure the projected leaf
area (WinFOLIA software, Regent, Canada) on the same
day that leaf samples were collected. After oven drying for
at least 48 h at 65°C to a constant weight, the leaf dry mass
of the samples was weighed to the nearest milligram. LMA
was calculated as the leaf dry mass divided by the projected
leaf area. Finely ground dry leaf powder was digested with
H2SO4–H2O2 for analysis. Leaf Nmass was measured following
the Kjeldahl method (Kjeltec 2200, FOSS, Sweden), while
leaf Pmass was determined followed the molybdenum blue
spectrophotometric procedure (UV-2550 spectrophotometer,
Shimadzu, Japan) (Kuo 1996). Narea was calculated as Nmass ×
LMA, and Parea was calculated as Pmass × LMA. Data of the leaf
traits for each species–site combination were also averaged
from three individuals.
Data analysis
Hierarchical (nested) variance components analysis was
applied for each leaf trait to quantify the relative importance
of factors in explaining the trait variances. These factors
were forest type (evergreen/deciduous forests), site within
forest type and species’ relative height within site (Fig. 1).
Type I sums of squares were converted to percentages at
each level.
Standardized major axis (SMA) regression was applied
(Warton et al. 2012) to estimate the best fit line for each leaf
trait against HR for each site (data were log10 transformed
before analysis). SMAs were tested among sites to determine
whether or not they shared a common slope by post hoc multiple comparisons. Whether or not these slopes are equal to
Journal of Plant Ecology
one, which implies an isometric relationship between the leaf
traits and HR, was also determined. Moreover, linear mixed
models were applied using setting site as the random factor to
determine general patterns of Narea and Parea in relation to HR
for both evergreen and deciduous forests.
Phylogenetic independent contrasts (PICs) (Felsenstein
1985) were used to determine whether or not the leaf trait–
HR relationships evaluated by SMA regression persist when
phylogeny is considered. When the PIC algorithm was
applied, the original N measurements of a trait (which were
often dependent on phylogeny as they represent mean values
for hierarchically related species) were transformed into N − 1
contrasts between pairs of related taxa or (estimated) ancestral nodes in the phylogeny. The contrasts of the traits were
phylogenetically independent and could be used in correlation or regression analysis.
Phylogeny topologies of coexisting species in each community were constructed by online Phylomatic (http://phylodiversity.net/phylomatic/) based on an APG III-derived mega
tree [Phylomatic tree R20120829 (plants)] and resolved to a
dichotomy with reference to Flora of China (http://www.efloras.org). Phylogenetic branch lengths were calibrated using
the BLADJ algorithm in Phylocom 4.2 (Webb et al. 2008) with
estimated molecular and known fossil ages (Wikström et al.
2001).
Statistical analysis was performed in the free software R,
version 2.15.1 (R Development Core Team 2009) with R
packages. SMA regressions were computed using package
‘smatr’(Warton et al. 2012), linear mixed models were applied
using package ‘nlme’ and PICs of each trait and through origin
correlations were computed with packages ‘picante’(Kembel
et al. 2010) and ‘PHYLOGR’(Diaz-Uriarte and Garland 2010).
Figure 1: hierarchical variance components of five leaf traits. Type I sums of squares were converted to percentages at each level. Narea/Parea:
leaf N/P content per unit area; Nmass/Pmass: leaf N/P content per unit dry mass; LMA: leaf dry mass per unit area. Data of the leaf traits were log10
transformed before analysis.
Jin et al. | Vertical patterns of leaf traits in forests71
Results
Leaf N and P contents, as well as LMA, were compared
among sites and the total variances of each trait across sites
were partitioned in a hierarchical manner. The evergreen
forests (Jianfengling, Dinghushan and Gutianshan) had
lower leaf Nmass and Pmass but higher LMA than the deciduous
ones (Baotianman, Changbaishan and Maoershan) (Table 2,
P < 0.05). The forest type is the major determinant for Nmass,
Pmass and LMA, explaining 38.2% of the total variance of
Nmass, 64.9% of Pmass and 50.9% of LMA (Fig. 1). Variations
in Narea and Parea across sites and between evergreen and
deciduous forests were moderate. Total variances of Narea
and Parea were explained mostly by HR within sites, which
explained 36.7% of the variance of Narea and 39.4% of the
variance of Parea. HR within sites also explained 12.0% of the
total variance of LMA (P < 0.001) but only 2% of Nmass and
1% of Pmass.
SMA regression and PICs were employed to determine the
relationships between the leaf traits and HR within each forest. Positive correlations between leaf Narea and HR as well
as between Parea and HR within the six forests were supported by SMA regressions (P < 0.05, only the relationship
of Narea–HR in Jianfengling was significant at P < 0.1; Table 3).
The observed pattern was generally confirmed by correlations (forced through the origin) using PIC (Table 4). The
positive correlation between LMA and HR was supported by
both SMA and PIC in Dinghushan, Changbaishan and Maoe­
rshan (P < 0.001), weakly supported by SMA in Jianfengling
and Baotianman (P < 0.1) and weakly supported by PIC in
Gutianshan (P < 0.05; Tables 3 and 4). Neither leaf Nmass nor
Pmass was generally correlated with HR, except for Nmass in
Changbaishan and Maoershan as well as Pmass in Baotianman,
which showed positive correlations with HR upon application
of PIC (P < 0.05).
To determine whether or not Narea, Parea and LMA increase
with HR in an isometric manner, we compared their SMA
slopes with the slope of one, after the data were log10
transformed. The SMA slopes of leaf Narea, Parea and LMA
against HR were generally <1 (Table 3). In the three deciduous
forests, the values varied from 0.21 to 0.51, all of which are
significantly <1 (P < 0.01). The SMA slopes in the evergreen
forests varied from 0.58 to 1.13, significantly <1.0 for Narea in
Jianfengling and Gutianshan (P < 0.05) and for Parea and LMA
in Gutianshan (P < 0.01). The linear mixed models confirmed
that for a certain increase in HR, Narea and Parea increase
faster in the evergreen forests (with slopes of 0.44 and 0.42,
respectively) compared with those in the deciduous forests
(with slopes of 0.26 for both Narea and Parea; Fig. 2). According
to the fitted lines, as HR increases from 14.1% to 100% in
the evergreen forests, leaf Narea increases from 775 to 1837 mg
m−2 and Parea increases from 32.4 to 73.8 mg m−2. In the
deciduous forests, as HR increases from 2.9% to 100%, leaf
Narea increases from 946 to 1576 mg m−2 and Parea increases
from 38.1 to 96.3 mg m−2 (Fig. 2).
On average, HR explained 26%, 37% and 22% of the
variances of Narea, Parea and LMA, respectively, within the
evergreen forests and explained 69%, 68% and 54% of the
variances of Narea, Parea and LMA, respectively, within the
deciduous forests (Table 3). When considering leaf Narea,
Parea and LMA simultaneously, their first principal components correlated closely with HR in the six investigated forests
(P < 0.01) with coefficients varying from 0.42 in Jianfengling
to 0.92 in Maoershan (Fig. 3 and Table 5).
Discussion
Plant height is a primary driver of leaf Narea and
Parea but not of Nmass or Pmass
Uncertainties regarding the response of leaf functional traits
to climate are largely due to dramatic variances within the
sites (He et al. 2006; Wright et al. 2004). By partitioning leaf
trait variances across six natural forests, we found that HR
within the sites explained a large component of the total
variance of Narea (36.7%) and Parea (39.4%) than did the
sum of those explained by forest type, climate or soil factors
among sites. Although the LMA across forests is largely
determined by forest type, HR is probably a primary driver
of LMA within forests, which was also revealed in a Costa
Rican tropical rain forest (Cavaleri et al. 2010). Nevertheless,
leaf Nmass and Pmass were largely determined at the site
level and found to be generally independent of HR. Thus,
Table 2: mean values of five leaf traits [leaf N and P contents per unit area (Narea, Parea), leaf N and P content per unit dry mass (Nmass,
Pmass) and LMA] of the species sampled in the six forests in East China Site
n
Narea (mg m−2)
Parea (mg m−2)
Nmass (mg g−1)
Pmass (mg g−1)
LMA (g m−2)
Jianfengling
38
1597.5 a (19.3)
60.8 bc (22.3)
19.6 b (25.9)
0.76 cd (36.6)
Dinghushan
20
1240.7 bc (38.9)
62.3 bc (33.3)
15.8 bc (25.9)
0.82 c (25.9)
78.5 b (31.6)
Gutianshan
41
1413.5 ab (25.2)
50.7 c (29.1)
14.8 c (29.2)
0.53 d (30.0)
103.7 a (36.2)
Baotianman
18
1131.1 bc (39.3)
58.2 bc (38.8)
26.6 a (27.9)
1.37 b (30.1)
44.5 c (42.8)
Changbaishan
15
1259.0 bc (30.8)
82.5 a (35.9)
26.5 a (18.1)
1.71 a (15.4)
47.8 c (28.1)
Maoershan
25
1073.9 c (33.9)
73.2 ab (31.3)
24.0 a (18.6)
1.66 a (20.5)
44.6 c (26.6)
84.8 ab (23.3)
Coefficients of variance (%) are given in parenthesis. Forests sharing the same letter were not significantly different at the P < 0.05 level, as
determined by Tukey’s multiple comparisons method. n = number of the species sampled.
72
Journal of Plant Ecology
incorporation of HR in the model predicting plant functional
traits from climate or soil factors will greatly enhance the
reliability of the modeling of traits such as leaf Narea, Parea
and LMA.
The pattern of leaf traits with respect to plant
adult height within a forest
A pattern in which interspecific leaf Narea, Parea and LMA
increased dramatically but leaf Nmass and Pmass did not vary significantly with HR was observed within forests from tropical
to temperate zones and within evergreen and deciduous forests in this study. This result is in accordance with patterns
observed in terms of leaf N traits, P traits and LMA across species in a tropical rain forest (Bigelow 1993; Cavaleri et al. 2010)
and along the canopy height of sugar maple (Acer saccharum)
in a deciduous forest (Ellsworth and Reich 1993). Two reasons
may explain this pattern. First, sunny leaves from the canopy
of a forest often develop palisade tissues with more cell layers and have larger LMA than leaves in the shade and thus
contain more N and P per unit leaf area (Aranda et al. 2004).
Table 3: SMA regressions of three leaf traits [leaf N and P contents per unit area (Narea, Parea) and LMA] against the relative height of
species (HR) in six communities Site
n
Slope (CI)
Intercept
R2
P
38
0.72 (0.53, 0.99) a
1.89
0.08
0.079
P1
Narea ~ HR
Jianfengling
0.045
Dinghushan
20
0.80 (0.55, 1.16) a
1.79
0.41
0.002
0.230
Gutianshan
41
0.70 (0.53, 0.92) a
1.94
0.28
0.000
0.011
<0.001
Baotianman
18
0.47 (0.31, 0.70) ab
2.35
0.38
0.006
Changbaishan
15
0.40 (0.34, 0.48) b
2.46
0.91
0.000
0.000
Maoershan
25
0.27 (0.22, 0.33) c
2.69
0.78
0.000
0.000
Parea ~ HR
Jianfengling
38
0.82 (0.60, 1.11) a
0.30
0.13
0.028
0.193
Dinghushan
20
0.58 (0.44, 0.76) ab
0.86
0.69
0.000
0.000
Gutianshan
41
0.84 (0.64, 1.10) a
0.24
0.28
0.000
0.204
Baotianman
18
0.49 (0.34, 0.69) b
1.04
0.55
0.001
0.000
Changbaishan
15
0.43 (0.32, 0.59) b
1.22
0.72
0.000
0.000
Maoershan
25
0.25 (0.20, 0.31) c
1.55
0.76
0.000
0.000
LMA ~ HR
Jianfengling
38
0.80 (0.58, 1.10) ab
0.47
0.09
0.062
0.162
Dinghushan
20
0.58 (0.41, 0.81) b
0.96
0.51
0.000
0.003
Gutianshan
41
1.13 (0.83, 1.53) a
0.05
0.07
0.108
0.451
Baotianman
18
0.51 (0.32, 0.81) bc
0.88
0.19
0.070
0.005
Changbaishan
15
0.36 (0.26, 0.50) c
1.10
0.70
0.000
0.000
Maoershan
25
0.21 (0.17, 0.26) d
1.39
0.73
0.000
0.000
The relationships between Nmass, Pmass and HR were non-significant in all cases and, thus, dropped. Abbreviations for the leaf traits are as defined
in Table 2. CI = 95% confidence interval. Slopes sharing the same letter were not significantly different at the P < 0.05 level between sites, as
determined using post hoc multiple comparison. P = P-value for SMA regressions; P1 = probability that the slope is equal to 1. Data were log10
transformed before analysis. Slopes with P < 0.05 are shown in bold.
Table 4: coefficients of correlations (forced through the origin) between PICs of five leaf traits and the relative height of species (HR)
within six forest communities Site
n
Narea–HR
Parea–HR
LMA–HR
Nmass–HR
−0.06
0.25
0.16
0.14
−0.01
Jianfengling
37
0.05
0.45**
0.09
Dinghushan
19
0.67**
0.89***
0.77***
Pmass–HR
Gutianshan
40
0.55***
0.48**
0.33*
−0.04
Baotianman
17
0.39
0.62**
0.08
0.31
0.49*
Changbaishan
14
0.94***
0.83***
0.91***
0.55*
0.37
Maoershan
24
0.81***
0.83***
0.74***
0.42*
0.34
Abbreviations for the leaf traits are as defined in Table 2. Data of the traits were log10 transformed before analysis. Correlation coefficients with
P < 0.05 are shown in bold.
*P < 0.05, **P < 0.01, ***P < 0.001.
Jin et al. | Vertical patterns of leaf traits in forests73
Figure 3: the first principal component of Narea, Parea and LMA relative to the height of species within each community. Standardized
major axes are shown (P < 0.01). Data were log10 transformed before
analysis.
Table 5: Pearson correlation of the first principal component of
Narea, Parea and LMA to HR
Site
n
r
Jianfengling
38
0.42
0.009
Dinghushan
20
0.81
<0.001
Gutianshan
41
0.48
0.001
Baotianman
18
0.65
0.004
Changbaishan
15
0.91
<0.001
Maoershan
25
0.92
<0.001
P
Abbreviations for the leaf traits are as defined in Table 2. Correlation
coefficients (r) with P < 0.05 are shown in bold. Data of the traits
were log10 transformed before analysis.
Figure 2: leaf N (a) and P (b) content per unit area against species’
relative height within community for both evergreen and deciduous
forests. All coefficients are significant at P < 0.001. Each point in the
figure is a species–site combination. The evergreen forests included
99 species–site combinations from Jianfengling, Dinghushan and
Gutianshan, whereas the deciduous forests included 58 species–site
combinations from Baotianman, Changbaishan and Maoershan.
Second, as LMA increases with HR within a forest, Nmass and
Pmass show no trend of decrease, which may be expected from
the strong negative correlations between Nmass, Pmass and LMA
within forests in this study and across sites at the global scale
(Wright et al. 2004). In this study, trees with larger HR may
show advantages in N and P absorption such that they can
maintain Nmass and Pmass levels with a larger LMA.
The increase in leaf Narea and Parea with HR within a
community may help maximize the photosynthetic capacity
of the whole community. As leaf Narea and Parea increase with
HR, Narea and Parea respond simultaneously to light distribution
within a community, which decreases from the community
canopy to the community floor with increasing accumulative
leaf area (Ellsworth and Reich 1993; Hirose and Werger 1987).
Moreover, area-based photosynthetic capacity increases
remarkably with leaf Narea across species (Bassow and Bazzaz
1997) as well as light intensity within species in a forest
(Ellsworth and Reich 1993). Allocating N and P nutrients in
accordance with light availability within a forest is assumed to
maximize the carbon gain per unit leaf area and enhance the
photosynthetic capacity of the entire community. The theory
that it is optimal for a plant to allocate photosynthetic needed
resources in line with light availability to maximize its carbon
gain (Hirose and Werger 1987) may apply to the cross-species
level within a forest community.
The enhancement in leaf Narea, Parea and LMA was observed
to slow down gradually with increasing HR. This observation
74
could be attributed to the increase in light intensity with HR
until the saturation point of leaf photosynthesis is achieved.
At this point, increases in Narea or Parea no longer enhance leaf
photosynthesis. The leaf carbon gain per unit area may also
be limited by increasing leaf water stress due to gravity and
hydrological path length resistance (Koch et al. 2004).
Comparison of leaf trait–HR relationships among
forests
This study showed that the slopes were steeper in the evergreen forests compared with deciduous ones as leaf Narea, Parea
and LMA increased with HR, indicating that leaf Narea, Parea
and LMA decrease with faster rates from the forest canopy to
understory in the former than in the later. This result indicates
that light attenuates more quickly when passed through a
vertical profile of the evergreen forests, which could be attributed to the larger LAI in these forests. For example, an original mountain rainforest at Jianfengling (Li et al. 1992) and a
mature, natural broad-leaved forest at Dinghushan (Ren and
Peng 1997) have LAI values of 16.7 and 17.0, respectively,
whereas the maximum LAI values of a mixed coniferous and
broad-leaved forest at Changbaishan (Guan et al. 2007) and a
broad-leaved forest at Maoershan (Zhu et al. 2010) are ~6.0
and 9.0, respectively.
The correlations between LMA, Narea and Parea with HR were
closer in the deciduous forests than in the evergreen forests,
possible reasons for which include forest phenology, canopy structure and the topography of the forest community.
Although LMA of both shade-tolerant and light-demanding
species increases with light intensity, shade-tolerant species tend to have higher LMAs than light-demanding species under the same light intensity in evergreen forests (Lusk
and Warton 2007). A homogeneous canopy composed of leaf
inlays in a mature broad-leaved deciduous forest is similar
to a closed-canopy system. This type of canopy system may
be better described by the Beer–Lambert law than the multilayer canopy in tropical rain forests and the wavy forest
Journal of Plant Ecology
canopy composed of round, thick tree crowns in evergreen
forests. Evergreen forests in South China often have rugged
landforms and steep slopes caused by long-term weathering,
e.g. the average slope in Gutianshan is as steep as 37.5° (Mi
2009). On the same slope, soil N and P availability as well as
the maximum tree height tend to increase from upper-slope
to foot-slope positions (Maltez-Mouro et al. 2005; Tateno
and Takeda 2003). This topography-mediated complexity
in soil fertility and canopy height may weaken the parallelism between HR and leaf traits. As such, for HR to accurately
reflect the microenvironment of plant species in a community, the forest community must feature a closed canopy
and a flat ground. In other case, it is better to define HR in a
smaller scale to avoid the complexity aroused by the canopy
structure and topography.
A hypothetical model
The present study proposes a simple hypothetical model of
HR and its ecological effects (Fig. 4). Within a forest community, taller trees with higher light availability tend to allocate
more N, P and biomass per unit leaf area, and they often
have higher area-based photosynthesis than the shorter trees.
Simultaneously, the more carbohydrates these trees produce,
the more N and P nutrients are exchanged with their symbiotic fungi (Chapin et al. 2011). Thus, taller trees in a community may gain higher growth rates and competitive abilities
before leaf water availability becomes a major limitation.
This hypothetical model can help explain some phenomena.
For example, understory trees within a forest gap that feature enhanced HR in a micro-community also show increased
growth rates and may have a better chance to become overstory trees. As well, species with larger statures in a grassland community often become more dominant in N addition
experiments than in blank controls (Bai et al. 2010; Yang et al.
2011). This positive feedback is inferred to be the key driver
for height-related competition among species and the formation of the hierarchical structure of a forest community.
Figure 4: a hypothetical model showing the positive feedback of relative height of a plant through ambient light intensity, nutrient acquisition
and photosynthesis in a community, as well as its likely causes and effects.
Jin et al. | Vertical patterns of leaf traits in forests75
Conclusions
In this study, area- and mass-based leaf N and P contents,
LMA and the adult height of species were measured relative
to the community canopy of common woody species within
six natural forests from tropical to temperate zones in East
China. The findings revealed the importance of the adult
height of species in determining leaf functional traits. HR is
a robust predictor for leaf Narea, Parea and LMA within a community, especially in deciduous forests. The incorporation
of the adult height of species may help predict the possible
changes in interspecific leaf functional traits under future climate change. Increases in leaf Narea and Parea with HR tend
to allocate N and P nutrients across species according to the
light availability within a community. This characteristic may
maximize the carbon gain of the whole community and favor
species with larger HR in competition.
Funding
China National Natural Science Foundation (30710103907)
for the China—Germany Cooperation Project.
Acknowledgements
We would like to thank Drs Jinsheng He, Shucun Sun, Kechang Niu,
Jihong Huang, Xiaojuan Liu, Lin Zhang and the anonymous reviewers
for their valuable suggestions on this manuscript. We would also like
to thank the staff at the Jianfengling, Baotianman and Maoershan stations of the Chinese Forest Ecosystem Network, the Dinghushan and
Changbaishan stations of the Chinese Ecosystem Research Network
and the Gutianshan research station for their assistance during field
sampling. We are grateful to Lin Zhang, Jinlong Zhang and Jia Ding for
their field assistance and to Bin Chen for help in species identification.
Conflict of interest statement. None declared.
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