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Biomass allocation is closely related to species traits, resources avail- ability and competitive abilities, and therefore it is often used to capture resource utilisation within plants. In this study, we searched for patterns in biomass alloca- tion between foliage and wood (stem plus branch), and how they changed with tree size (diameter), species identity and functional traits (leaf area and specific wood density). Using data on the aboveground biomass of 89 trees from six species in a Mistbelt forest (South Africa), we evaluated the leaf to wood mass ratio (LWR). The effects of tree size, species identity and specific traits on LWR were tested using Generalised Linear Models. Tree size (diameter) was the main driver of bio- mass allocation, with 44.43 % of variance explained. As expected, LWR declined significantly with increasing tree diameter. Leaf area (30.17% explained variance) and wood density (12.61% explained variance) also showed significant effects, after size effect was accounted for. Results also showed clear differences among species and between groups of species. Per unit of wood mass, more biomass is allocated to the foliage in the species with the larger leaf area. Inversely, less bio- mass is allocated to the foliage in species with higher wood density. Moreover, with increasing diameter, lower wood density species tended to allocate more biomass to foliage and less biomass to stems and branches. Overall, our results emphasise the influence of plant size and functional traits on biomass allocation, but showed that neither tree diameter and species identity nor leaf area and wood density are the only important variables.
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Ann. For. Res. 59(1): _-_ 2016 ANNALS OF FOREST RESEARCH
www.afrjournal.org
Patterns of biomass allocation between foliage and
woody structure: the effects of tree size and specific
functional traits
S. Mensah, R. Glèlè Kakaï, T. Seifert
Mensah, S., Glèlè Kakaï, R., Seifert, T., 2016. Patterns of biomass allocation be-
tween foliage and woody structure: the effects of tree size and specic functional
traits. Ann. For. Res. 59(1): _-_.
Abstract. Biomass allocation is closely related to species traits, resources avail-
ability and competitive abilities, and therefore it is often used to capture resource
utilisation within plants. In this study, we searched for patterns in biomass alloca-
tion between foliage and wood (stem plus branch), and how they changed with tree
size (diameter), species identity and functional traits (leaf area and specic wood
density). Using data on the aboveground biomass of 89 trees from six species in a
Mistbelt forest (South Africa), we evaluated the leaf to wood mass ratio (LWR).
The effects of tree size, species identity and specic traits on LWR were tested
using Generalised Linear Models. Tree size (diameter) was the main driver of bio-
mass allocation, with 44.43 % of variance explained. As expected, LWR declined
signicantly with increasing tree diameter. Leaf area (30.17% explained variance)
and wood density (12.61% explained variance) also showed signicant effects,
after size effect was accounted for. Results also showed clear differences among
species and between groups of species. Per unit of wood mass, more biomass is
allocated to the foliage in the species with the larger leaf area. Inversely, less bio-
mass is allocated to the foliage in species with higher wood density. Moreover, with
increasing diameter, lower wood density species tended to allocate more biomass
to foliage and less biomass to stems and branches. Overall, our results emphasise
the inuence of plant size and functional traits on biomass allocation, but showed
that neither tree diameter and species identity nor leaf area and wood density are
the only important variables.
Keywords aboveground biomass, leaf area, leaf to wood mass ratio, Mist-
belt forest, South Africa, partitioning, species identity, trunk diameter, wood
density.
Authors. Sylvanus Mensah (sylvanus.m89@gmail.com), Thomas Seifert - De-
partment of Forest and Wood Sciences, Stellenbosch University, South Africa;
Sylvanus Mensah, Romain Glèlè Kakaï - Laboratory of Biomathematics and
Forest Estimations.
Manuscript received October 11, 2015; revised February 08, 2016; accepted Feb-
ruary 12, 2016; online rst March 21, 2016.
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Ann. For. Res. 59(1): _-_, 2016 Research article
Introduction
Biomass production is a primary function of
forest ecosystems that is inuenced by an in-
terplay of processes: roots capture nutrients
from soil, stems and branches provide mechan-
ical support and conduct water with nutrients,
and leaves x carbon (Poorter et al. 2012). Be-
cause plants have to balance the allocation of
resources to roots, stem, branches and leaves
in a way to enable necessary physiological
activities for the functioning of these organs,
only plants that are successful in acquisition
of resources will maintain or achieve a regular
growth (Bloom et al. 1985, Shipley & Mezi-
ane 2002). The extent to which acquisition and
utilisation of resources vary among taxa would
dene the limit of plant biomass production
(Reich 2002). Therefore, understanding the
patterns of biomass partitioning within plants
is of high importance in the eld of tree phys-
iology and plant ecology, and also has many
applications for agriculture/forestry.
Biomass allocation has generally been used
to capture resource utilisation by plants in
empirical and simulation studies (e.g. Seifert
& Müller-Starck 2009, Pretzsch et al. 2012,
Rötzer et al. 2012, Tomlinson et al. 2014, Fre-
schet et al. 2015). According to the optimal
partitioning theory (OPT), plants should allo-
cate more biomass to organs that have limited
access to resources (Bloom et al. 1985). For
instance, in water- and nutrients-limited envi-
ronments, plants decrease the biomass alloca-
tion to foliage with increasing light availability
(Shipley & Meziane 2002, Poorter et al. 2012).
Similarly, in nutrient-limited soils, more bio-
mass would be allocated to roots to increase
use of water and nutrient resources (Deng et al.
2006, Poorter et al. 2012). Therefore, biomass
allocation among plant organs is driven by
above and belowground environmental condi-
tions (Müller et al. 2000, Freschet et al. 2015),
but plant size (Pino et al. 2002), ontogenic
trends (Poorter et al. 2012, Xie et al. 2012),
species competitive abilities (Ninkovic 2003,
Dybzinski et al. 2011), species identity and
functional traits (McCarthy et al. 2007, Poorter
et al. 2015) can also act as potential covariates
to dene the investment in support tissues.
Many previous studies have emphasised
the inuence of plant size on biomass alloca-
tion (Bonser & Aarssen 2009, Poorter & Sack
2012, Xie et al. 2012), regardless of whether
root to shoot ratio, or its inverse shoot to root
ratio is used (Wilson 1988, Reich 2002, Moka-
ny et al. 2006). The use of root to shoot ratio
has the advantage of taking into account the
whole plant, however, it condenses the total
aboveground biomass into one compartment
and therefore limits the investigation on the
different organs (e.g. stem, branch, leaves)
(Poorter et al. 2012). Whether the generalisa-
tion about plant size inuence on biomass al-
location also applies for aboveground organs
alone, has received much less attention so far
(Körner 1994, Poorter et al. 2015). In particu-
lar, as stem, branches and leaves have different
physiological activities (Pearcy et al. 2005),
analysing the patterns of biomass allocation
between aboveground organs can produce ad-
ditional information. Accurate quantication
of wood (i.e. stem plus branch) and foliage
biomass would allow for understanding such
patterns, the extent to which they vary among
species, groups of species, and according to
specic traits.
Species groups, distinguished phylogenet-
ically, morphologically or physiologically,
are important because species from different
groups may have different specialized strate-
gies to optimize uptake of resources. Depend-
ing on plant traits, species are often grouped
into woody or herbaceous species, angio-
sperms or gymnosperms, coniferous or broad-
leaved, deciduous or evergreen. Specic traits
such as wood density, leaf area and maximum
height could show strong inuence on the al-
location patterns (Mokany et al. 2006, Reich
2002). For instance, wood density is a good
predictor of individual tree diameter incre-
ments (Wright et al. 2010), and correlates con-
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Mensah et al. Patterns of biomass allocation between foliage and woody structure...
sistently with the biomass increment (Finegan
et al. 2015). Besides wood density, specic leaf
area is known to be related with the intensity
of plant respiration and photosynthesis (Ivetić
et al. 2014, Weraduwage et al. 2015), and thus
plant growth. In the infancy of its growth, a
plant would tend to allocate more resources to
leaves so that to allow maximum interception
of light and favour xation of large amounts
of C from atmosphere. As a result, leaf area
would co-determine, through the rate of pho-
tosynthesis and respiration, the relative growth
rate of the plant (Tomlinson et al. 2014).
In this study, we evaluated the biomass allo-
cation to wood (stem plus branch) and foliage
using our available data on the aboveground
biomass of 89 trees from six species in a Mist-
belt forest (South Africa). We expected that
tree size, species identity and functional traits
would inuence the biomass allocation, but we
did not know their relative importance.
We rst examined the between-species vari-
ation in the biomass allocation using the leaf
to wood mass ratio (LWR). Because biomass
allocation is size dependent, we assessed si-
multaneously the effects of tree size (diameter
at breast height, dbh) and species identity on
LWR. We further accounted for the effect of
tree size, and tested whether the biomass al-
location in the aboveground compartment was
inuenced by species traits such as, individual
leaf area and wood density. Finally, we com-
pared the trend lines of LWR and dbh scaling
relationship between groups of species. We
tested the hypotheses that (i) LWR decreases
with increasing tree diameter, but (ii) the effect
of tree size works differently according to the
species group. Specically, we suspected that
(iii) the slope of the trend line of LWR-dbh
in the group of species with higher leaf area,
would be larger than in the one of species with
smaller leaf area.
Materials and Methods
Study area and species
The study area is located in Limpopo Mistbelt
Forests, in South Africa (Mucina & Rutherford
2006). The study was specically carried out
in Woodbush-De Hoek State Forest (approx-
imately 23°50’S, 29°59’E), near Tzaneen,
in the North Eastern Transvaal (Geldenhuys
2002). The altitude in the area varies between
1050 to 1650 m above mean sea level. The an-
nual precipitation ranges from 600 and 1800
mm. The vegetation in the Woodbush-De
Hoek State Forest is dominated by tree spe-
cies such as Xymalos monospora (Harv.) Baill.
ex Warb, Podocarpus latifolius (Thunb.) R.
Br. ex Mirb., Combretum kraussii Hochst.,
Syzygium gerrardii Burtt Davy, Cryptocarya
transvaalensis Burtt Davy in the canopy lay-
er, and by small trees and shrubs like Oxyan-
thus speciosus DC., Peddiea africana Hook.,
Oricia bachmannii (Engl.) I. Verd., Kraussia
oribunda Harv. in the understorey vegetation.
On the basis of leaf area, specic wood densi-
ty and the relative dominance in the forest, six
species were considered for this study. They
were Celtis africana Burm. f. (Cannabaceae),
Combretum kraussii (Combretaceae), Croton
sylvaticus Hochst. (Euphorbiaceae), Syzygi-
um gerrardii (Myrtaceae), Trichilia dregeana
Sond. (Meliaceae) and Xymalos monospora
(Monimiaceae). C. africana, C. kraussii and
C. sylvaticus are deciduous trees while S. ger-
rardii, T. dregeana and X. monospora are all
evergreen species.
Sampling design and laboratory analysis
Data on aboveground biomass was obtained
from tree and branch sampling, individual tree
measurement, and laboratory processing from
December 2014 to May 2015. Fourteen to
fteen individual trees were selected per spe-
cies across a wide range of diameter at breast
height. In total, 89 individual trees were con-
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Ann. For. Res. 59(1): _-_, 2016 Research article
sidered.
Because the studied species were protected
in South Africa, they were measured and sam-
pled without damaging them. Thus, the diame-
ter was measured on the standing stem at every
2 meters interval up to the crown base, by a
professional tree climber. The larger branches
(basal diameter >15 cm) were treated as stem
section and thus measured at the thick and thin
diameter ends. The distance from the thick and
thin points was also measured. On the small-
er branches (basal diameter <15 cm), only the
branch basal diameter was measured. In ad-
dition, samples of wood cores were collected
at breast height and crown base levels using
increment corer, for further determination
of wood density. To limit the damages to the
tree, two to four branches were sampled at dif-
ferent height levels for each tree, and packed
into paper bags for estimation of dry mass of
branch wood and foliage. The wood density
was obtained by using the water-displacement
method and by oven-drying the core samples
to equilibrium weight (at 105°C until 48 to 72
drying hours). The branch wood and foliage
samples were also oven-dried at 105°C until
their constant weight (Seifert & Seifert 2014).
Aboveground biomass data and specific traits
The dry mass of branch foliage was used to
estimate for each species, the foliage biomass
equations at branch level as a function of
branch basal diameter (Mensah et al. unpub-
lished). Based on these specic foliage bio-
mass equations and the branch basal diameter
measured on standing trees, the foliage bio-
mass was up-scaled from the branch level to
the tree level. The same method was applied
for the branch wood to determine the total dry
mass of wood in smaller branches at tree lev-
el. In addition, the volume of larger branches
and standing stems was calculated by applying
Smalian’s formula (van Laar and Akça 2007),
and the average wood density was thus used
to calculate the wood biomass for the stem
and larger branches. The total aboveground
wood mass of each individual tree was then
obtained by adding the biomass of stem and
larger branches to the total dry mass of wood
in smaller branches (Table 1).
The plant traits used in this study were wood
density (g/cm3) and individual leaf area (cm2).
Wood density was obtained from laboratory
analyses. Because wood cores were taken from
two levels on each standing tree, the averaged
wood density was used. The information on
leaf area of these species was obtained from
TRY database on biological traits (Kattge et al.
2011) and using the Trees of Southern Africa
(Coates-Palgrave 2002). In case multiples val-
ues were available for a species, the average
value was used. C. africana, C. kraussii, S.
gerrardii and X. monospora have leaves with
smaller area, whereas C. sylvaticus and T. dre-
geana have leaves with relatively greater area
(Table 1).
Data analysis
We evaluated the biomass allocation to wood
and foliage by calculating for each individu-
al tree, the foliage mass to wood mass ratio
(LWR), i.e. the biomass allocated to foliage
per unit of wood mass. To assess the effect of
species identity, we tested for the difference of
LWR among study species through a one-way
analysis of variance applied to the log-trans-
formed data. The normal distribution was
checked using Shapiro Wilk statistic. Species
were post-hoc compared by performing the
Student-Newman-Keuls test. Next, we tested
whether the size dependency hypothesis of bi-
omass allocation applies for wood and foliage
components, and whether there were differ-
ences among species. We used a Generalised
Linear Model (GLM) to estimate simultane-
ously, the effects of tree size (i.e., dbh) and
species identity. As the distribution of LWR
was positively skewed, we tted the GLM
with Gamma family and “log” link. GLMs
were also used to examine the relative effects
of specic traits (wood density and leaf area)
on LWR. To do so, we controlled the variation
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Mensah et al. Patterns of biomass allocation between foliage and woody structure...
Species No. trees DBH (cm) Wood density
(g/cm3)
Aboveground
biomass (kg) Leaf phenology
C. africanaa,d 15 2.80-94.50 0.30-0.65 4.93-8871.97 Deciduous
C. kraussiia,d 16 1.50-91.00 0.51-0.66 0.26-4590.19 Deciduous
C. sylvaticusb,c 14 4.80-64.00 0.38-0.50 4.17-5127.94 Deciduous
S. gerrardiia,d 15 0.70-92.50 0.51-0.65 0.17-3423.33 Evergreen
T. dregeanab,c 14 2.80-62.00 0.35-0.55 0.82-2357.97 Evergreen
X. monosporaa,c 15 2.00-54.50 0.39-0.54 2.61-3816.50 Evergreen
of LWR due to tree size by using the residu-
als of LWR-DBH model as response variable,
and each specic trait as explanatory variable.
Finally, we grouped the species and compared
the trend lines of LWR-dbh scaling relation-
ship between groups of species. We used the
specic functional traits as a grouping factor,
thus distinguishing (1) between species with
larger and smaller leaf area, and (2) between
species with higher and lower wood density.
After grouping, we found that the range for
tree diameter was greater in the group of high
wood density species (0.7- 94.5 cm). There-
fore, we excluded the largest trees from the set
of study species to have approximatively the
same range of tree diameter within each group,
and to fairly compare the trends in LWR-DBH
scaling relationship.
Results
Effects of tree diameter and species identity
on biomass partitioning patterns
Within study species, the biomass allocated to
foliage per unit of wood mass (LWR) ranged
from 0.0038 to 0.0225 for C. africana, 0.0071
to 0.0704 for C. kraussii, 0.0200 to 0.0916
for C. sylvaticus, 0.0073 to 0.1443 for S. ger-
rardii, 0.0113 to 0.0485 for T. dregeana and
0.0053 to 0.0503 for X. monospora (Figure
1). There were signicant differences between
species (F = 13.4; P < 0.001). On average, C.
sylvaticus and T. dregeana showed the highest
values of LWR, followed by C. kraussii and S.
gerrardii, while C. africana and X. monospora
had the same and lowest values (Figure 1).
Tree diameter and species identity showed
signicant effects (P < 0.001) on the biomass
allocation patterns, with 77.96 % of the total
variance being explained (Table 2). Tree diam-
eter alone explained 44.44 % of the variance of
LWR for all species (P < 0.001). The effect of
tree size was shown by a signicant decrease
in LWR with increasing tree diameter (Figure
2a), regardless of the species. Results from
GLM also showed species’ signicant effects
Traits of study species and sampled trees
Table 1
Note. a - species with smaller leaf area, b - species with larger leaf area, c - species with lower wood density, d - species
with higher wood density.
Figure 1 Distribution of leaf to wood mass ratio
among studied species; CA - C. africana,
CK - C. kraussii, CS - C. sylvaticus, SG
- S. gerrardii, TD - T. dregeana, XM - X.
monospora. Species with the same letter
are not signicantly different at p = 0.05
(Student-Newman-Keuls test).
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Ann. For. Res. 59(1): _-_, 2016 Research article
on the leaf to wood mass ratio (P < 0.001, Ta-
ble 2), and a large variability of species-spe-
cic slopes. For a given tree diameter, C.
sylvaticus, T. dregeana, C. kraussii and S. ger-
rardii showed slopes of 1.27±0.14, 1.13±0.14,
0.81±0.14 and 0.53±0.14 respectively, higher
than the one in C. africana, which was consid-
ered as the baseline (Table 2). X. monospora
was ranked last, and had a slope that did not
differ signicantly from the one in the baseline
(P = 0.320).
Effects of leaf area and wood density on
biomass partitioning patterns
Leaf area and specic wood density explained
30.17 % and 12.61 % respectively, of the var-
iance of the leaf to wood mass ratio, after the
effect of tree diameter was accounted for. The
leaf to wood mass ratio increased signicant-
ly (P < 0.001) with increasing leaf area (Table
2; Figure 2b). Contrary to the leaf area, wood
density showed a negative effect on the leaf to
wood mass ratio (Table 2; Figure 2c). Figure
3 showed a signicant decline in LWR with
increasing tree diameter for all species groups
(scaling coefcient < 0, Figures 3a-b). Howev-
er, the biomass allocated to foliage per unit of
wood mass decreased more steeply in higher
wood density species (slope = -5.10-4) than in
lower wood density species (slope = -4.10-4,
Figure 3b). Accordingly, species with higher
wood density had slightly lower LWR than
species with lower wood density. In contrast, a
more remarkable differentiation was noted be-
tween species with larger leaf area and species
with smaller leaf area (Figures 3b): those with
larger leaf area had greater slope and intercept,
and therefore greater biomass allocated to foli-
age per unit of wood biomass.
Discussion
Our results showed that tree size (diameter)
has a strong effect on the aboveground biomass
partitioning patterns, as also revealed in other
studies (Xie et al. 2012, Poorter et al. 2015).
More specically, LWR declined substantially
with increasing tree diameter, regardless of the
species. This means that as trees get larger, the
production of foliage biomass per unit of wood
mass tends to decrease. This outcome accords
with other studies that reported for larger trees,
an increasing relative contribution of stem and
branches with a proportional decrease in the
fraction of foliage (e.g. Pajtik et al. 2011, Luo
et al. 2014). This is also consistent with the fact
that an increase in wood biomass occurs often
at the expense of foliage biomass (Helmisaari
Estimate SE t P (>|t|) Deviance P (>Chi) Pseudo R
square (%)
Intercept -3.092 0.164 -18.896 <0.001
77.96
Log (DBH) -0.525 0.041 -12.769 <0.001 24.79 <0.001
Species 18.70 <0.001
C. kraussii 0.813 0.139 5.866 <0.001
C. sylvaticus 1.273 0.143 8.893 <0.001
S. gerrardii 0.533 0.141 3.777 <0.001
T. dregeana 1.126 0.143 7.866 <0.001
X. monospora 0.141 0.141 1.001 0.320
Intercept 1.387 0.403 3.444 <0.001 12.61
Wood density -2.672 0.767 -3.482 <0.001 4.11 <0.001
Intercept -0.464 0.093 -4.972 <0.001 30.17
Leaf area 0.011 0.002 6.131 <0.001 9.96 <0.001
Output of GLMs describing the effects of tree diameter, species identity, wood density and leaf
area on leaf to wood mass ratio
Table 2
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Mensah et al. Patterns of biomass allocation between foliage and woody structure...
et al. 2002). Such a reduced production of foli-
age biomass is in part a result of the declining
production of branch foliage when branches
get older (King 1997). This is intrinsically
linked with increasing amount of heartwood
in stems and branches with increasing age and
in line with the ndings that sapwood area is
highly correlated with total foliage biomass
according to the pipe model theory (Shinoza-
ki et al. 1964a,b, Marchand 1984, Morataya et
al. 1999). The higher LWR in younger trees
indicates that more carbohydrate resources
would have been allocated to foliage to under-
take photosynthetic activities and allow rapid
vertical growth. In natural environments (e.g.
natural forests), it is remarkable that resource
partitioning among plant organs at early devel-
opment stages is part of plant’s strategy built
as a response of competition for light. But as
plant size increases, more resources are allo-
cated for stem growth (height and diameter)
to enable plants to compete with conspecic
and heterospecic neighbours. In the mean-
time, additional resources are invested for root
growth and for below ground mechanical safe-
ty (Poorter et al. 2015). Therefore, increasing
tree size would result in different mechanical
architectures that enable plants to differen-
tially access the resources in the below and
aboveground compartments (Fourcaud et al.
2008). While our results support the hypothe-
sis of size-related allocation patterns, the var-
iance explained by tree diameter leaves much
part of variation to be attributed to species-spe-
cic differences (Weiner 2004, McCarthy et al.
2007, Poorter et al. 2015), and / or environ-
mental effects (McCarthy & Enquist 2007, Re-
ich et al. 2014).
The signicant effect of species identity on
the biomass partitioning patterns stresses the
plasticity of different species in acquiring re-
sources and adjusting biomass allocation. In-
deed, different species are expected to obtain
resources in various ways because of the in-
Figure 2 Individual effects of (a) tree size (DBH), (b) leaf area and (c) wood density on leaf
to wood mass ratio. The regression coefcients (estimates) and values of pseudo
R-square are given in Table 2.
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Ann. For. Res. 59(1): _-_, 2016 Research article
terspecic variation in architectural branching
and phenotypic plasticity (Poorter et al. 2006,
Fourcaud et al. 2008, Lambers et al. 2006,
Jarčuška & Barna 2011), and in functional
traits (Xie et al. 2012, Freschet et al. 2015).
For instance, when analysing the individual
effect of each species, we found the highest
slopes for C. sylvaticus and T. dregeana. From
a biological perspective, this result means that,
for a given value of trunk diameter, C. sylvati-
cus and T. dregeana would exhibit higher foli-
age biomass per unit of wood mass, compared
to C. africana, C. kraussii S. gerrardii and X.
monospora. From a functional perspective,
the relatively greater foliage biomass allocat-
ed in C. sylvaticus and T. dregeana is likely
the result of the effects of functional traits that
might be strongly involved in the construction
of conductive tissues and the growth of plant.
Our results support the inuence of plant
functional traits, such as specic wood density
and individual leaf area, on biomass alloca-
tion. Leaf area showed positive effects on the
biomass allocated to foliage per unit of wood
mass. Accordingly, species with larger aver-
age leaf area exhibited higher LWR than those
with smaller leaf area. The leaf area seems to
be a good explanatory variable of biomass al-
location patterns because it denes not only
the extent of interception of radiant energy,
but also the absorption of CO2, and facilitates
the transfer of water between foliage and at-
mosphere (Margolis et al. 1995, Leuchner et
al. 2012, Priesack et al. 2012, Weraduwage et
al. 2015). Our results reinforce the importance
of leaf traits for plant performance (Poorter &
Bongers 2006). Specically, larger leaves have
greater potential for light interception and pho-
tosynthetic production. If the effect of leaf area
can also explain the between-species variation
of allocation patterns, then species leaf area
should play an important role in determining
the capacity of plant to capture aboveground
resources (Freschet et al. 2015), and also a cru-
cial role in plant competition.
Leaf to wood mass ratio decreased with in-
creasing wood density. The latter has proved
to be a good indicator of the aboveground
biomass in many studies (Chave et al. 2014,
Wright et al. 2010, Finegan et al. 2015), even
though the relation between tree biomass and
wood density is not always consistent (Stegen
et al. 2009). Pajtik et al. (2011) found signif-
icant differences in whole tree biomass be-
tween beech, oak and pine species in Slovakia,
and related this outcome to a probable effect
of wood density. The here-reported inuence
of wood density could be explained by the
fact that low wood density would allow for a
faster tree growth (King et al. 2006, Wright et
al. 2010), and when tree grows faster, more re-
sources are allocated to the organ responsible
for photosynthetic activities, thus stimulating
the production of foliage. The faster growth in
lower wood density tree is typical for pioneer
Figure 3 Regression lines tting the distribution of
leaf to wood mass ratio as a function of
tree diameter (DBH; cm) in (a) higher and
lower wood density (WD) species, and in
(b) smaller and larger leaf area (LA) spe-
cies.
9
Mensah et al. Patterns of biomass allocation between foliage and woody structure...
tree species and enables them to ll forest can-
opy gaps quickly. On the contrary, in higher
wood density species, the conductive tissues
are most expensive to construct (Suzuki 1999),
thus slowing tree growth. Furthermore, it was
found that LWR declined with increasing tree
size for both higher and lower wood density
species, consistently with what is expected
from the size dependency hypothesis. How-
ever, the fact that LWR declines more steeply
in higher wood density species than in lower
wood density species indicates that the latter
allocates more biomass to foliage and less
biomass to stem and branches. This outcome
suggests that additional resources have prob-
ably been allocated to foliage to maximize
photosynthetic activities in low wood density
species.
All being considered, it is worth mentioning
that co-existing species show quite different
patterns of aboveground allocation and dif-
ferent correlations with structural traits. This
may serve as proof that competition in the
Mistbelt forests is interacting with tree struc-
ture and morphology. However, it must be tak-
en into account that the competition in these
multi-species forests is complex and that trees
might change their competitive abilities during
their lifetime as shown in similarly structured
Afrotemperate forests (Seifert et al. 2014).
Conclusions
Tree size was the major inuencing variable
on biomass allocation between leaves and
wood and, species identity (i.e. difference in
the species per se) showed clearly differentia-
ble patterns, as response to varying plant func-
tional traits such as leaf area and wood densi-
ty. Therefore, our study underlines the role of
plant size and functional traits in the plasticity
of adjustment in biomass allocation, but more
importantly, it highlights that neither tree di-
ameter and species identity nor leaf area and
wood density are the only important variables
to consider if we are to catch the total varia-
bility in the biomass allocation patterns. While
recent studies put forward the importance of
above and belowground resources available,
accounting for the role of plant functional
traits that could capture the leaf and wood eco-
nomics spectra, would provide deeper insights
into the mechanisms behind resource utilisa-
tion and biomass allocation.
Acknowledgements
This research was partly supported by the
SHARE Intra-ACP project and the National
Research Foundation of South Africa through
the project Catchman Letaba in the RTF fund-
ing scheme of DST. Special thanks go to the
colleagues Otto Pienaar and Andrew Perkins
who provided help during the data collection.
We also acknowledge the anonymous referees
for their signicant contribution.
References
Bloom A.J., Chapin F.S., Mooney H.A., 1985. Resource
limitation in plants—an economic analogy. Annual Re-
view of Ecology and Systematics 16(1): 363-392. DOI:
10.1146/annurev.es.16. 110185.002051
Bonser S.P., Aarssen L.W., 2009. Interpreting reproduc-
tive allometry individual strategies of allocation explain
size-dependent reproduction in plant populations. Per-
spectives in Plant Ecology, Evolution and Systematics
11(1): 31-40. DOI: 10.1016/j.ppees. 2008.10.003
Chave J., Réjou-Méchain M., Búrquez A., Chidumayo E.,
Colgan M.S., Delitti W.B.C., Duque A., Eid T., Fearn-
side P.M., Goodman R.C., Henry M., Martínez-Yrízar
A., Mugasha W.A., Muller-Landau H.C., Mencuccini
M., Nelson B.W., Ngomanda A., Nogueira E.M., Or-
tiz-Malavassi E., Pélissier R., Ploton P., Ryan C.M.,
Saldarriaga J.G., Vieilledent G., 2014. Improved allo-
metric models to estimate the aboveground biomass of
tropical trees. Global Change Biology 20 (10): 3177-
3190. DOI: 10.1111/gcb.12629
Coates-Palgrave M., 2002. Keith Coates-Palgrave Trees of
Southern Africa, edn 3, imp. 4 Random House Struik,
Cape Town, 1212 p.
Deng J.M., Wang G.X., Morris E.C., Wei X.P., Li D.X.,
Chen B.M., Zhao C.M., Liu J.,Wang Y., 2006. Plant
mass–density relationship along a moisture gradient
in north-west China. Journal of Ecology 94: 953-958.
10
Ann. For. Res. 59(1): _-_, 2016 Research article
DOI: 10.1111/j.1365-2745.2006.01141.x
Dybzinski R., Farrior C., Wolf A., Reich P.B., Pacala
S.W., 2011. Evolutionarily stable strategy of carbon
allocation to foliage, wood, and ne roots in trees
competing for light and nitrogen: an analytically trac-
table, individual-based model and quantitative compar-
isons to data. American Naturalist 177: 153-166. DOI:
10.1086/657992
Finegan B., Peña-Claros M., de Oliveira A., Ascarrunz N.,
Bret-Harte M.S., Carreño-Rocabado G., Casanoves F.,
Díaz S., Eguiguren Velepucha P., Fernandez F., Licona
J.C., Lorenzo L., Salgado Negret B., Vaz M., Poorter
L., 2015. Does functional trait diversity predict above-
ground biomass and productivity of tropical forests?
Testing three alternative hypotheses. Journal of Ecolo-
gy 103: 191-201. DOI: 10.1111/1365-2745.12346
Fourcaud T., Zhang X., Stokes A., Lambers H., Körner
C., 2008. Plant growth modelling and applications: the
increasing importance of plant architecture in growth
models. Annals of Botany 101: 1053-1063. DOI:
10.1093/aob/mcn050
Freschet G.T., Kichenin E., Wardle A.D., 2015. Explaining
within-community variation in plant biomass alloca-
tion: a balance between organ biomass and morphology
above vs below ground? Journal of Vegetation Science
26: 431-440. DOI: 10.1111/jvs.12259
Geldenhuys C.J., 2002. Tropical secondary forest manage-
ment in Africa: Reality and perspectives. South Africa
Country Paper.
Helmisaari H.S., Makkonen K., Kellomaki S., Valtonen
E., Malkonen E., 2002. Below- and above-ground bio-
mass, production and nitrogen use in Scots pine stands
in eastern Finland. Forest Ecology and Management
165: 317-326. DOI: /10.1016/S0378-1127(01) 00648-X
Ivetić V., Stjepanović St., Devetaković J., Stanković D.,
Škorić M., 2014. Relationships between leaf traits and
morphological attributes in one-year bareroot Fraxinus
angustifolia Vahl. seedlings. Annals of Forest Research
57(2): 197-203. DOI: 10.15287/afr.2014.214
Jarčuška B., Barna M., 2011. Plasticity in above-ground
biomass allocation in Fagus sylvatica L. saplings in re-
sponse to light availability. Annals of Forest Research
54(2): 151-160.
Kattge J., Diaz S., Lavorel S., Prentice C., Leadley P.,
Bonisch G. et al., 2011. TRY - a global database of plant
traits. Global Change Biology 17: 2905-2935. DOI:
10.1111/j.1365-2486.2011.02451.x
King D.A., 1997. Branch growth and biomass allocation
in Abies amabilis saplings in contrasting light environ-
ments. Tree Physiology 17: 251-258. DOI: 10.1093/
treephys/17.4.251
King D.A., Davies S.J., Tan S., Noor N.S., 2006. The role
of wood density and stem support costs in the growth
and mortality of tropical trees. Journal of Ecology 94:
670-680. DOI: 10.1111/j.1365-2745.2006.01112.x
Körner C., 1994. Biomass fractionation in plants: a recon-
sideration of denitions based on plant functions. In:
Roy J., Garnier E., (eds.), A whole plant perspective
on carbon–nitrogen interactions. Academic Publishing,
The Hague, the Netherlands, pp. 173-185.
Lambers H., Shane M.W., Cramer M.D., Pearse S.J.,
Veneklaas E.J., 2006. Root structure and functioning
for efcient acquisition of phosphorus: matching mor-
phological and physiological traits. Annals of Botany
98: 693-713. DOI: 10.1093/aob/mcl114
Leuchner M., Hertel C., Rötzer T., Seifert T., Weigt R.,
Werner H., Menzel A., 2012. Solar radiation as a
driver for growth and competition in forest stands.
In: Matyssek R., Schnyder H., Ernst D., Munch J-C.,
Oßwald W., Pretzsch H., (eds.), Growth and defence in
plants: resource allocation at multiple scales. Ecological
Studies 220, Springer, pp. 175-191. DOI: 10.1007/978-
3-642-30645-7_8
Luo Y., Zhang X., Wang X., Ren Y., 2014. Dissecting Vari-
ation in Biomass Conversion Factors across China’s
Forests: Implications for Biomass and Carbon Account-
ing. PLoS ONE 9(4): e94777. DOI: 10.1371/journal.
pone.0094777
Marchand P.J., 1984. Sapwood area as an estimator of foli-
age biomass and projected leaf area for Abies balsamea
and Picea rubens. Canadian Journal of Forest Research
14(1): 85-87. DOI: 10.1139/x84-016
Margolis H., Oren R., Whitehead D., Kaufmann M.R.,
1995. Leaf area dynamics of conifer forests. In: Smith
W.K., Hinckley T.M., (eds.), Ecophysiology of conifer-
ous forests. Academic Press, San Diego, pp. 255-308.
DOI: 10.1016/B978-0-08-092593-6.50012-8
McCarthy M.C., Enquist B.J., 2007. Consistency be-
tween an allometric approach and optimal partitioning
theory in global patterns of plant biomass allocation.
Functional Ecology 21: 713-720. DOI: 10.1111/j.1365-
2435.2007.01276.x
McCarthy M.C., Enquist B.J., Kerkhoff A.J., 2007. Organ
partitioning and distribution across the seed plants: as-
sessing the relative importance of phylogeny and func-
tion. International Journal of Plant Sciences 168: 751-
761. DOI: 10.1086/513491
Mokany K., Raison R.J., Prokushkin A.S., 2006. Critical
analysis of root: shoot ratios in terrestrial biomes. Glob-
al Change Biology 12: 84-96. DOI: /10.1111/j.1365-
2486.2005.001043.x
Morataya R., Galloway G., Berninger F., Kanninen M.,
1999. Foliage biomass - sapwood (area and volume)
relationships of Tectona grandis L.F. and Gmelina ar-
borea Roxb.: silvicultural implications. Forest Ecology
and Management 113 (2-3): 231-239. DOI: 10.1016/
S0378-1127(98)00429-0
Mucina L., Rutherford M.C., 2006. The vegetation of
South Africa, Lesotho and Swaziland. Strelitzia 19,
South African National Biodiversity Institute, Pretoria,
807 p.
Müller I., Schmid B., Weiner J., 2000. The effect of nu-
trient availability on biomass allocation patterns in
27 species of herbaceous plants. Perspectives in Plant
Ecology, Evolution and Systematics 3(2): 115-127.
DOI: 10.1078/1433-8319-00007
11
Mensah et al. Patterns of biomass allocation between foliage and woody structure...
Ninkovic V., 2003. Volatile communication between bar-
ley plants affects biomass allocation. Journal of Ex-
perimental Botany 54: 1931-1939. DOI: 10.1093/jxb/
erg192
Pajtik J., Konopka B., Lukac M., 2011. Individual biomass
factors for beech, oak and pine in Slovakia: a compara-
tive study in young naturally regenerated stands. Trees
25: 277-288. DOI: 10.1007/ s00468-010-0504-z
Pearcy R.W., Muraoka H., Valladares F., 2005. Crown
architecture in sun and shade environments: assessing
function and trade-offs with a three-dimensional sim-
ulation model. New Phytologist 166: 791-800. DOI:
10.1111/j.1469-8137.2005.01328.x
Pino J., Sans F.X., Masalles R.M., 2002. Size-dependent
reproductive pattern and short-term reproductive cost in
Rumex obtusifolius L. Acta Oecologica 23(5): 321-328.
DOI: 10.1016/S1146-609X(02)01161-X
Poorter H., Jagodzinski A. M., Ruiz-Peinado R., Kuyah
S., Luo Y., Oleksyn J., Usoltsev V. A., Buckley T. N.,
Reich P. B., Sack L., 2015. How does biomass distri-
bution change with size and differ among species? An
analysis for 1200 plant species from ve continents.
New Phytologist 208: 736-749. doi:10.1111/nph.13571.
DOI: 10.1111/ nph.13571
Poorter H., Sack L., 2012. Pitfalls and possibilities
in the analysis of biomass allocation patterns in
plants. Frontiers in plant science 3:259. doi:10.3389/
fpls.2012.00259. DOI: 10.3389/ fpls.2012.00259
Poorter H., Niklas K.J., Reich P.B., Oleksyn J., Poot P.,
Mommer L., 2012. Biomass allocation to leaves, stems
and roots: meta-analyses of interspecic variation and
environmental control. New Phytologist 193: 30-50.
DOI: 10.1111/j.1469-8137.2011.03952.x
Poorter L., Bongers F., 2006. Leaf traits are good
predictors of plant performance across 53
rain forest species. Ecology 87: 1733-1743.
DOI: 10.1890/0012-9658(2006)87[1733:LTAGPO]2.0.
CO;2
Poorter L., Bongers L., Bongers F., 2006. Architec-
ture of 54 moist forest tree species: traits, trade-
offs, and functional groups. Ecology 87: 1289-1301.
DOI: 10.1890/0012-9658(2006)87[1289:AOMTST]
2.0.CO;2
Pretzsch H., Dieler J., Seifert T., Rötzer T., 2012. Cli-
mate effects on productivity and resource use ef-
ciency of Norway spruce (Picea abies [L.] Karst.) and
European beech (Fagus sylvatica [L.]) in stands with
different spatial mixing patterns. Trees 26:1343-1360.
DOI: 10.1007/s00468-012-0710-y
Priesack E., Gayler S., Rötzer T., Seifert T., 2012. Mech-
anistic modelling of soil-plant-atmosphere systems.
In: Matyssek R., Schnyder H., Ernst D., Munch J-C.,
Oßwald W., Pretzsch H., (eds.), Growth and defence in
plants: resource allocation at multiple scales. Ecological
Studies 220, Springer, pp. 335-353. DOI: 10.1007/978-
3-642-30645-7_15
Reich P.B., 2002. Root–shoot relations: optimality in
acclimation and adaptation or the ‘’Emperor’s New
Clothes’’? In: Waisel Y., Eshel A., Kafka U., (eds.),
Plant roots: the hidden half. Marcel Dekker, Basel, Swit-
zerland, pp. 205-220. DOI: 10.1201/9780203909423.
ch12
Reich P.B., Luo Y., Bradford J.B., Poorter H., Perry C.H.,
Oleksyn J., 2014. Temperature drives global patterns
in forest biomass allocation in leaves, stems and roots.
Proceedings of the National Academy of Sciences, USA
111: 13721-13726. DOI: 10.1073/ pnas.1216053111
Rötzer T., Seifert T., Gayler S., Priesack E., Pretzsch H.,
2012. Effects of stress and defence allocation defence
on tree growth: simulation results at the tree and stand
level. In: Matyssek R, Schnyder H, Ernst D, Munch
J-C, Oßwald W, Pretzsch H (eds) Growth and Defence
in Plants: Resource Allocation at Multiple Scales. Eco-
logical Studies 220, Springer. 401-432.
Seifert T., Seifert S., 2014. Modelling and simulation of
tree biomass. In Seifert T., (ed.), Bioenergy from Wood.
Springer Netherlands, Dordrecht, pp. 43-65. DOI:
10.1007/978-94-007-7448-3_3
Seifert T., Seifert S., Seydack A., Durheim G., von Gad-
ow K., 2014. Competition effects in an afrotemperate
forest. Forest Ecosystems 1:13. DOI: 10.1186/s40663-
014-0013-4
Seifert T., Müller-Starck G., 2009. Impacts of fructica-
tion on biomass production and correlated genetic ef-
fects in Norway spruce (Picea abies L. [Karst.]). Euro-
pean Journal of Forest Research 128(2): 155-169. DOI:
10.1007/s10342-008-0219-5
Shinozaki K., Yoda K., Hozumi K., Kira T., 1964a. A
quantitative analysis of plant form-the pipe model the-
ory: I. Basic analyses. Japanese Journal of Ecology 14:
97-105.
Shinozaki K., Yoda K., Hozumi K, Kira T., 1964b. A quan-
titative analysis of plant form-the pipe model theory: II.
Further evidence of the theory and its application in for-
est ecology. Japanese Journal of Ecology 14: 133-139.
Shipley B., Meziane D., 2002. The balanced-growth hy-
pothesis and the allometry of leaf and root biomass
allocation. Functional Ecology 16: 326-331. DOI:
10.1046/j.1365-2435.2002.00626.x
Stegen J.C., Swenson N.G., Valencia R., Enquist B.J.,
Thompson J., 2009. Above-ground forest biomass is not
consistently related to wood density in tropical forests.
Global Ecology and Biogeography 18: 617-625. DOI:
10.1111/j.1466-8238.2009.00471.x
Suzuki E., 1999. Diversity in specic gravity and wa-
ter content of wood among Bornean tropical rain-
forest trees. Ecological Research 14: 211-224. DOI:
10.1046/j.1440-1703.1999.143301.x
Tomlinson K.W., Poorter L., Bongers F., Borghetti F., Ja-
cobs L., van Langevelde F., 2014. Relative growth rate
variation of evergreen and deciduous savanna tree spe-
cies is driven by different traits. Annals of botany 114
(2): 315-324. DOI: 10.1093/aob/mcu107
van Laar A., Akça A., 2007. Forest mensuration. Springer
Netherlands, Dordrecht, 383 p. DOI: 10.1007/978-1-
4020-5991-9
12
Ann. For. Res. 59(1): _-_, 2016 Research article
Weiner J., 2004. Allocation, plasticity and allometry in
plants. Perspectives in Plant Ecology, Evolution and
Systematics 6: 207-215. DOI: 10.1078/1433-8319-
00083
Weraduwage S.M., Chen J., Anozie F.C., Morales A.,
Weise S.E., Sharkey T.D., 2015. The relationship be-
tween leaf area growth and biomass accumulation in
Arabidopsis thaliana. Frontiers in Plant Science 6:167.
DOI: 10.3389/fpls.2015.00167
Wilson J.B., 1988. A review of evidence on the control of
shoot: root ratio, in relation to models. Annals of Bota-
ny 61: 433-449.
Wright S.J., Kitajima K., Kraft N.J.B., Reich P.B., Wright
I.J., Bunker D.E., Condit R., Dalling J.W., Davies S.J.,
Díaz S., Engelbrecht B.M.J., Harms K.E., Hubbell S.P.,
Marks C.O., Ruiz-Jaen M.C., Salvador C.M., Zanne
A.E., 2010., Functional traits and the growth–mortality
trade-off in tropical trees. Ecology 91: 3664-3674. DOI:
10.1890/09-2335.1
Xie J., Tang L., Wang Z., Xu G., Li Y., 2012. Distinguish-
ing the biomass allocation variance resulting from on-
togenetic drift or acclimation to soil texture. PLoS ONE
7(7): e41502. DOI: 10.1371/ journal.pone.0041502
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This chapter describes the spatial and temporal variability of biologically important wavebands of solar radiation as crucial drivers for growth and competition in forest ecosystems. Fundamental differences between beech and spruce in the penetration of radiation are mainly due to the different morphological crown habit. Thus, the dense upper beech canopy absorbs most of the incoming radiation in the very top layer, while more radiation can penetrate into the spruce canopy. In addition to the habit, reflectance properties play important roles for the spectral composition. Spruce exhibits higher levels of the blue/red ratio throughout the canopy. Only a small number of sunflecks can be observed in the shade crown of both species. A model scenario shows the level of light enhancement and the alteration of the spectral composition in a clearing. Phenological phases such as leaf unfolding and leaf fall can be estimated well by the red/far red ratio.