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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
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
Authors. Sylvanus Mensah (, 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.
Ann. For. Res. 59(1): _-_, 2016 Research article
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-
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-
Ann. For. Res. 59(1): _-_, 2016 Research article
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
Mensah et al. Patterns of biomass allocation between foliage and woody structure...
Species No. trees DBH (cm) Wood density
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.
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).
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.
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
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
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.
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-
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
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).
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.
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.
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Understanding the determinants of tree biomass allocation patterns among organs is crucial for both predicting the rate and potential of forest carbon sinks and guiding future multifunctional forest management. However, it is still not clear how the site conditions (e.g., elevation) and stand structure (e.g., tree dominance, stand density) affect the biomass allocation of single trees in forests. This study was implemented in the Liupan Mountains of the Loess Plateau of Northwest China by collecting the related information of biomass data of 110 sample trees with different dominance and influencing factors within 23 sample plots of larch plantations set up along the elevation gradient. Based on these data, the response tendency and functions of biomass allocation of single trees to individual influencing factors of site conditions and forest structure were analyzed. Moreover, the results illustrated that the ratio between root biomass and aboveground biomass decreased significantly with rising stand age and tree density, but increased significantly with rising elevation, and there was no significant relationship with the dominance of individual trees. The results of this study revealed the importance of considering the influencing factors of site conditions and stand structure when developing dynamic models of tree biomass allocation. The results and research methods used in this study provide useful tools for quantifying the biomass allocation and carbon storage partitioning in the study area and other similar regions.
Biomass of seedlings at different developing stages of growth is important information for studying the response of species to site conditions. The objectives of this study was to explore the distribution characteristics of AGB (above-ground biomass) and BGB (below-ground biomass) of Abies georgei var. smithii seedlings of different ages, and investigate the effects of topography (slope aspect, altitude), plant community characteristics (crown density, species diversity, etc.), and soil properties (soil physical and chemical properties) on the biomass and its allocation. Seedlings in five age classes (1–2, 3–4, 5–6, 7–8, and 9–10 years old) were collected by full excavation from 6 elevations (3800 m, 3900 m, 4000 m, 4100 m, 4200 m, 4300 m) on the north and south slopes of Sejila Mountain in Tibet. 15 seedlings of each age class were investigated at one altitude. The individual effects of seedling age (SA) and the interaction effects of SA, slope aspect (SL), and elevation (EG), namely, SL×EG, SL×SA, EG×SA, and SL×EG×SA, had significant effects on the AGB of the seedlings (p<0.05), whereas BGB was only significantly affected by SA (p<0.001). The AGB and BGB of the seedlings showed a binomial growth trend with the increase in seedling age, and had an allometric relationship at different elevations, α (allometric exponential) varied from 0.913 to 1.046 in the northern slope, and from 1.004 to 1.268 in the southern slope. The biomass of seedlings on the northern slope was remarkably affected by stand factors, with a contribution rate of 47.8%, whereas that on the southern slope was considerably affected by soil factors with a contribution rate of 53.2%. The results showed that age was the most important factor affecting seedling biomass. The allometric pattern of seedling biomass was relatively stable, but in a high-altitude habitat, A. georgei var. smithii seedlings increased the input of BGB. Understanding seedling biomass allocation and its influencing factors is useful for evaluating plants’ ability to acquire resources and survival strategies for adaptation to the environment in Tibet Plateau.
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Lianas are abundant and diverse in tropical forests and impact forest dynamics. They occupy part of the canopy, forming a layer of leaves overtopping tree crowns. Yet, their interaction with trees has been mainly studied from the ground. With the emergence of drone-based sensing, very high-resolution data may be obtained on liana distribution above canopies. Here, we assessed the relationship between common liana ground measurements and drone-determined liana leaf coverage over tree crowns, tested if this relationship is mediated by liana functional composition, and compared the signature of liana patches and tree crowns in our drone images. Using drone platforms, we acquired very high resolution RGB and multispectral images and LiDAR data over two 9-ha permanent plots located in northern Republic of Congo and delineated liana leaf coverage and individual tree crowns from these data. During a concomitant ground survey, we focused on 275 trees infested or not by lianas, for which we measured all lianas ≥ 1 cm in diameter climbing on them (n = 615) and estimated their crown occupancy index (COI). We additionally measured or recorded the wood density and climbing mechanisms of most liana taxa. Contrary to recent findings, we found significant relationships between most ground-derived metrics and the top-of-view liana leaf coverage over tree crowns. Tree crown infestation by lianas was primarily explained by the load of liana climbing on them, and negatively impacted by tree height. Liana leaf coverage over individual tree crowns was best predicted by liana basal area and negatively mediated by liana wood density, with a higher leaf area to diameter ratio for light-wooded lianas. COI scores were concordant with drone assessments, but two thirds differed from those obtained from drone measurements. Finally, liana patches had a higher light reflectance and variance of spectral responses than tree crowns in all studied spectra. However, the large overlap between them challenges the autodetection of liana patches in canopies. Overall, we illustrate that the joint use of ground and drone-based data deepen our understanding of liana-infestation pathways and of their functional and spectral diversity. We expect drone data to soon transform the field of liana ecology.
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Key Message Strychnos spinosa growth was less responsive than its fruit production, to tree size, protection status and climate; its fruit production increased with tree size, and more so on protected sites. Abstract Abiotic and biotic mechanisms (e.g. climate, human perturbations) are presumed to shape tree growth and reproductive performances. Using the wild fruit tree Strychnos spinosa Lam., as a case study in Benin, we tested whether (and how) tree growth and fruit production were influenced by protection status (non-protected vs. protected sites), climatic zones (Sudanian vs. Sudano-Guinean zones) and size classes (tree diameter < 15 cm; 15–20 cm and > 20 cm). We also tested which climatic variables were important in predicting tree growth/fruit production. Tree growth was only influenced by size class, with higher growth rate in smaller than bigger size classes. Unlike tree growth, fruit production varied significantly with climate and protection status (higher fruit production in Sudano-Guinean than in sudanian zone, and on protected sites than non-protected sites). Fruit production also increased with tree size, and more so on protected sites than non-protected sites. The effect of protection status on fruit production also varied with climatic zones, with protected trees having more fruits than non-protected trees in Sudano-Guinean zone, while both protected and non-protected trees showed similar fruit production in the Sudanian zone. There was a trade-off mechanism between fruit production and growth, which was more pronounced on protected sites. Our study showed that both climate and protection status were considerably important for fruit production, in significant positive (resp. negative) effects of temperature and relative humidity, via mediation by tree size in protected (resp. non-protected) sites. These underlying drivers should be taken into account when predicting scenario for fruit yield under future climate.
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Aims The fractal dimension and fractal abundance are important root architecture characteristics that can reflect the changes in the morphology of root systems in response to habitats. However, there are few studies on the root architecture of inland salt marsh plants from the perspective of fractal geometry. Methods The study was run on three sites representing a gradient of flooding intensity and salinity: (i) high-flooding and low-salinity area, (ii) intermediate-flooding and intermediate-salinity area, and (iii) low-flooding and high-salinity area. Saussurea salsa was the research object, and the responses of root geometric morphology traits and fractal structure to heterogeneous habitats were studied in the Sugan Lake wetland. Results The results showed that there was a significant negative correlation (p < 0.01) between the fractal dimension and fractal abundance of Saussurea salsa in different habitats. Moreover, the rate of fractal abundance increase was greater than the rate of fractal dimension decrease from the high-flooding, low-salinity area to the low-flooding, high-salinity area. Conclusions With the gradient of environment change, Saussurea salsa tended to form a root architecture with a high fractal dimension and low fractal abundance in the high-flooding, low-salinity area, whereas a root architecture with a low fractal dimension and high fractal abundance tended to form in the low-flooding, high-salinity area. The roots of Saussurea salsa showed fewer branches and were more inclined to show an increase in root expansion capacity in the low-flooding, high-salinity area.
Mangroves are recognised as an important carbon sequester and therefore demand accurate biomass and carbon stock estimations. This study aimed to develop additive biomass models for Heritiera fomes, the most dominant tree species of the Sundarbans Reserved Forest in Bangladesh. Using a non-destructive method, 219 small branches (diameter < 7 cm) were harvested from 97 individual trees to develop biomass models for leaves and smaller branches. The biomass of bigger branches (diameter > 7 cm) and stem was calculated from the volume and mean wood density value after debarking while the biomass of all other components was derived from the determined fresh to oven dry weight conversion ratio. Finally, the biomass of one individual tree was calculated by adding the biomass of trimmed and untrimmed leaves, small and large branches, foliage and stem. An independent data set was used to validate the best-fit model. A component-wise (leaves, branches, bark and stem) biomass model was developed by recovering subsequent cross-component correlations which were then aggregated using the weighted Gaussian maximum likelihood estimation method. Among the components model, D (diameter at breast height) alone performed best for leaves and branches while the product of D and H (total tree height) proved the better results for stem and bark. Our best-fit model (Biomass = 0.0389D2.3773 H0.4178 + 0.0492D2.3027 + 0.0112D1.1144 H1.4572 + 0.0306D1.8507) showed the highest model efficiency with the lowest AIC, RMSE%, MAE, and MPE values. The efficiency of our non-destructive model has shown that it is as effective as other widely used pan-tropical models. Our built models can therefore be used for accurate estimation of biomass and carbon stock in H. fomes of the Sundarbans Reserved Forest, Bangladesh.
To test the applicability of the pipe model theory to actual tree form, the frequency distribution of the thickness of woody organs in a tree was examined in 10 different species. The frequency f(D) of a certain diameter class D proved to have a definite pattern of distribution in the root, branch and trunk respectively, with only a little difference between the species. The obtained f(D)〜D curves showed that a root system could well be approximated by the assemblage of many pipes of unit thickness, a trunk by a few cones piled up one upon another, and a branch system by a geometric model intermediate between the two. The results were well consistent with the pipe model theory of tree form. As an application of the theory in forest ecology, a new method for estimating the amounts of leaves or branches of trees and stands was also proposed, based on the direct proportionality found between those amounts and the cross-sectional area of the trunk at the height just below the lowest living branch.
This chapter examines the dynamics of coniferous forest leaf area at different spatial and temporal scales by considering the hypotheses related to the control of leaf area development, ranging from simple allometric relations with tree size to more complex mechanistic models that consider the movement of water and nutrients to tree canopies, and secondly, various aspects of leaf area dynamics at varying spatial and temporal scales. Leaf area represents the surface area available for the interception of energy, the absorption of carbon dioxide, and the diffusion of water from the leaf to the atmosphere and is an important concept used in the estimation of the species' biological properties. The leaf area that can be supported by a tree is determined by the equilibrium between the ability of the stem and roots to supply water and nutrients to the foliage and the amount of photosynthetic active radiation intercepted by the crown. The total leaf surface area is generally from 2.0 to 3.14 times that of projected leaf area for conifers. The hydraulic model based on Darcy's law takes into account many of the physical characteristics of the hydraulic pathway between the stem and the foliage. For an individual tree, the volume flow rate of water (q) through a tree stem of length (l) is related to the cross-sectional sap-wood area (As), the water potential difference (ΔΨ), the saturated permeability of the sapwood (k), and the viscosity (ζ) of the water such that.
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.