Tree Physiology 28, 529–536
© 2008 Heron Publishing—Victoria, Canada
Persisting soil drought reduces leaf specific conductivity in Scots pine
(Pinus sylvestris) and pubescent oak (Quercus pubescens)
FRANK J. STERCK,1,2 ROMAN ZWEIFEL,3 UTE SASS-KLAASSEN1 and QUMRUZZAMAN
CHOWDHURY1
1
Forest Ecology and Forest Management Group, Wageningen University, P.O. Box 47, 6700 AA Wageningen, The Netherlands
2
Corresponding author ([email protected])
3
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland
Received January 31, 2007; accepted July 6, 2007; published online February 1, 2008
Summary Leaf specific conductivity (LSC; the ratio of stem
conductivity (KP ) to leaf area (AL )), a measure of the hydraulic
capacity of the stem to supply leaves with water, varies with
soil water content. Empirical evidence for LSC responses to
drought is ambiguous, because previously published results
were subject to many confounding factors. We tested how LSC
of similar-sized trees of the same population, under similar climatic conditions, responds to persistently wet or dry soil. Scots
pine (Pinus sylvestris L.) and pubescent oak (Quercus pubescens Willd.) trees were compared between a dry site and a wet
site in the Valais, an inner alpine valley in Switzerland. Soil water strongly influenced AL and KP and the plant components affecting KP, such as conduit radius, conduit density and functional sapwood area. Trees at the dry site had lower LSC than
trees with the same stem diameter at the wet site. Low LSC in
trees at the dry site was associated with a smaller functional
sapwood area and narrower conduits, resulting in a stronger reduction in KP than in AL. These observations support the hypothesis that trees maintain a homeostatic water pressure gradient. An alternative hypothesis is that relatively high investments in leaves compared with sapwood contribute to carbon
gain over an entire season by enabling rapid whole-plant photosynthesis during periods of high water availability (e.g., in
spring, after rain events and during morning hours when leafto-air vapor pressure deficit is small). Dynamic data and a hydraulic plant growth model are needed to test how investments
in leaves versus sapwood and roots contribute to transpiration
and to maximizing carbon gain throughout entire growth seasons.
Keywords: Huber value, leaf area, soil water potential, stem
conductivity.
Introduction
Trees adjust the functional balance among organs and tissues responsible for water acquisition (fine roots), transport
(sapwood) and transpiration (leaves) (Cannell and Dewar
1994). Leaf specific conductivity (LSC; the ratio of stem conductivity to leaf area (KP /AL ); abbreviations and units are listed
in Table 1) is considered a measure of hydraulic capacity of the
stem to supply leaves with water (Tyree and Zimmermann
2002). According to physical principles, KP should increase
linearly with sapwood cross-sectional area, conduit density
within sapwood and the fourth power of the radius of the conduits. If conduit properties are constant, LSC scales directly
with the Huber value (H; sapwood area divided by leaf area
(AS /AL )).
Although modeling studies predict an increase in LSC or H
in response to drought (Whitehead et al. 1984, Magnani et al.
2002), few empirical studies have confirmed these predictions
(Mencuccini and Bonosi 2001, Cherubini et al. 2003) and
some have shown the reverse pattern (Panek 1996, Vander
Willigen and Pammenter 1998). These studies focused on the
effects of the vapor pressure deficit between leaves and air
(VPD), but the results may have been confounded by environmental, genotypic or size differences across sites. Most empirical studies showing that LSC or H increases with soil drying
have investigated effects of short-term drought pulses (Irvine
et al. 1998) or drainage pulses (Ewers et al. 2000), rather than
persistent soil drought. An exception is the study by Addington et al. 2006 which found that, in Pinus palustris Mill., H
was lower at the site with persistently drier soil, but this was
mainly explained by variation in tree size across sites. From
the cited studies, it can be concluded that the observed responses of LSC and H to drought are often confounded by
ontogenetic responses, genotypic variation, site dynamics, climate factors, short-term versus long-term structural responses
or interspecific differences.
In this study, we explored LSC responses to persistent soil
drought by comparing tree populations that experience different soil water availabilities (wet site versus dry site). By looking at the same tree population, we consider only phenotypic
responses to soil drought and exclude strong microclimatic
(e.g., VPD) effects. We analyzed how morphological plant
components contribute to the overall drought response in LSC
(Figure 1). We predicted that KP decreases in response to increasing soil drought because of a smaller AS and smaller conduit sizes (R) (Figure 1A; cf. Eilmann et al. 2006). Although
530
STERCK, ZWEIFEL, SASS-KLAASSEN AND CHOWDHURY
Table 1. Symbols and abbreviations used in the Equations. For statistical analyses and representation in figures and tables, other units may
be used. The entire sapwood was considered conductive in Scots pine
(Pinus sylvestris), but only the outer annual growth ring of the sapwood was considered conductive in pubescent oak (Quercus pubescens).
Code Description
Units
AL
AS
AEW
ALW
Dstem
D
DEW
DLW
KP
KPEW
KPLW
R
REW
RLW
LSC
DS
Total leaf area
Functional sapwood cross-sectional area
AS in earlywood
AS in latewood
Stem diameter 50 cm above stem base
Conduit density
D in early wood sapwood
D in late wood sapwood
Potential stem conductivity
KP of earlywood
KP of latewood
Hydraulic conduit radius
R in the earlywood
R in the latewood
Leaf specific conductivity (KP /AL)
Drought-induced stress
H
η
ρw
k
ψ
gs
h
Huber value (AS /AL)
Viscosity of water at 20 °C
Density of water at 20 °C
Sapwood permeability
Pressure
Stomatal conductance
Length from roots to leaves
m2
m2
m2
m2
m
m– 2
m– 2
m– 2
kg m MPa – 1 s – 1
kg m MPa – 1 s – 1
kg m MPa – 1 s– 1
m
m
m
kg m –1 MPa – 1 s – 1
0 for wet site;
1 for dry site
–
Pa s
kg m – 3
kg m MPa – 1 s – 1
MPa
mol m – 2 s – 1
m
the smaller conduit size may be compensated by a higher conduit density (D), the fourth power contribution of R to KP, according to Hagen-Poiseuille principles, will result in a net decrease in KP. Total AL, the other main component of LSC (Figure 1B), is predicted to decrease in response to soil drying because of previous-year limitations in resource acquisition and
bud formation (Zweifel et al. 2006). Specifically, we tested
two alternative hypotheses by comparing Scots pine (Pinus
sylvestris L.) and pubescent oak (Quercus pubescens Willd.)
trees growing on dry slopes with trees growing along irrigation
channels on the same slope in the Valais: (1) LSC increases as
soil dries because of a greater effect on AL than on KP (Figure
1B); and (2) LSC decreases as soil dries because of a greater
effect on KP than on AL.
Materials and methods
Study site
The study was carried out on a south-facing slope in the Valais,
Salgesch, Switzerland (46°19′27″ N, 7°34′40″ E) in the summer of 2005. The area receives about 600 mm annual precipitation, distributed throughout the year (Zweifel et al. 2005).
Mean monthly temperature varies from –1 °C in January to
Figure 1. A conceptual model of relationships among plant traits. Single-headed arrows denote direct effects, and double-headed arrows
denote correlations. (A) Effects of drought-induced stress (DS) on
functional sapwood area (AS), conduit radius (R) and conduit density
(D), and in turn, the contributions of these components to potential
stem conductivity (KP ). (B) Effects of DS on total leaf area (AL) and
KP and, in turn, of the contributions of AL and KP to leaf specific conductivity (LSC). Signs adjacent to arrows indicate the expected relationships.
19 °C in July. The soil is 10–30 cm deep and classified as a
rendzic leptosol on solid rock limestone (Rigling et al. 2002).
The main tree species are pubescent oak (Quercus pubescens)
and Scots pine (Pinus sylvestris), henceforth referred to as oak
and pine. To test our hypotheses we compared trees on a dry
slope (dry site) with trees along an irrigation channel on the
same slope (wet site), on the assumption that the sites differed
only in soil water availability.
Field experiment
We selected 10 trees of each species (stem diameter 3–18 cm;
measured 50 cm above the stem base) from the dry site, and
another 10 trees of each species growing within 2 m of an irrigation channel (wet site). Selected trees were a minimum of
50 m from each other to reduce pseudo-replication effects. The
40 trees occurred at a maximum distance of 500 m from one
another, and were selected within a narrow altitudinal range
(950–1000 m) to avoid confounding effects of climate.
The following variables were measured in the field: stem diameter at 50 cm aboveground (Dstem); tree and lowest branch
heights; crown radius in eight directions; and the number of
apices of leaf-bearing shoots. For each tree, two cores were
taken 50 cm above the stem base, with an increment corer
(Suunto, Finland), and prepared for dendrochronological and
wood anatomical analyses. To improve the contrast between
cell lumen and cell walls, the core samples were soaked in
10% NaOH, air dried, and the surface rubbed with chalk to fill
the conduit lumens. Ring width, earlywood width and late-
TREE PHYSIOLOGY VOLUME 28, 2008
DROUGHT AND LEAF SPECIFIC CONDUCTIVITY
wood width were measured over the whole radius with the
LINTAB system and Time Series Analysis and Presentation
software (TSAP, Rinntech, Heidelberg, Germany). Heartwood and sapwood were demarcated on the cores; a 1:1 (v/v)
mix of sulfuric acid:sodium nitrate (50%) was applied to improve the contrast for pine (Cummins 1972). Conduit radius
was measured for early- and latewood in 5 randomly selected
conduits in the earlywood and 5 in the latewood of each of the
last seven consecutive rings, using UTHSCSA Image Tool
software v.3.0 (http://ddsdx.uthscsa.edu/dig/itdesc.html). The
same software was used to measure conduit density.
Five randomly selected branches were harvested per tree.
The apices of these branches were counted. Leaves were harvested and dried, and leaf dry mass determined. The product of
leaf mass and the ratio of number of apices in the whole tree to
number of apices in the five branches gave an estimate of total
leaf mass. We also measured leaf area of 50 leaves, and calculated specific leaf area (leaf area:leaf mass ratio) to predict AL
from the product of total leaf mass and specific leaf area.
Hydraulic parameter calculations
For each tree, the functional balance between water transport
in the stem and transpiration of water through the leaf surface
area was expressed by H and LSC. In this study, we defined AS
as the actual sapwood area for Scots pine (Èermák et al. 1992)
and the outermost ring area for pubescent oak (Hinckley et al.
1979, Bréda and Granier 1996, Tognetti et al. 1998, Nardini
and Pitt 1999, Barbaroux and Bréda 2002, Domec and Gartner
2002, Cherubini et al. 2003, Zweifel et al. 2006 ). We calculated KP from the potential conductivity in earlywood (KPEW)
and latewood (KPLW):
K P = K PEW + K PLW
(1)
We calculated KPEW and KPLW from the hydraulic conduit radius (REW or RLW, respectively), conduit density (DEW or DLW,
respectively) and sapwood area (AEW or ALW, respectively),
with the Hagen-Poiseuille equation. The hydraulic conduit radius R was calculated for early- and latewood separately as:
1
⎛1 n ⎞4
R = ⎜ ∑ ri4 ⎟
⎝ n i =1 ⎠
(2)
531
where ri is the ith conduit of n (n = 70) measured conduits in
the earlywood (REW) and latewood (RLW). Parameters AEW and
ALW refer to the areas of the sapwood (in early and latewood,
respectively) in pine, and of the outer ring in oak (cf. Table 1).
K PEW =
π
4
ρw AEW DEW REW
8n
(3)
K PLW =
π
4
ρw ALW DLW RLW
8n
(4)
where η is viscosity of water (1.002 × 10 – 3 Pa s at 20 °C) and
ρw is density of water (998.2 kg m – 3 at 20 °C). Although the
calculations of KP, KPEW and KPLW overestimate actual sapwood conductivity, they serve as precise comparative measures of stem conductivity within species (Steppe and Lemeur
2007).
Results
Although pine trees had a smaller AS at the dry site than at the
wet site, they had more, and consequently, narrower rings in
the sapwood (Figure 2). Thus, pines at the dry site seemed to
compensate for slow radial stem growth by delayed conversion of sapwood into heartwood. In oaks, AS was assumed to
be equivalent to the outer ring, which was larger in trees at the
wet site than at the dry site.
Although H decreased with stem size, it hardly differed between the sites (Figure 3). Leaf specific conductivity in oak
was only a tenth that in pine. As shown in Figure 3, LSC did
not change with stem diameter in pine, but declined with stem
diameter in oak (Figure 3). Except for the smallest oaks, LSC
was lower at the dry site than at the wet site in both species.
Path-analysis showed that the negative effect of AL on LSC
was compensated by the positive effect of KP (see path-coefficients: –0.90 versus 1.08 in oak (Figure 4A), and –1.32 versus
1.46 in pine (Figure 4B)), and that a stronger decline in KP than
in AL at the dry site accounted for the site response in LSC (see
Figure 4: –0.77 versus –0.33 in oak, and –0.64 versus –0.17 in
pine; also see Figures 3E–H). Although AS was smaller in
trees at the dry site than at the wet site, particularly in pine, the
difference was insufficient to account for the observed site
Figure 2. Comparison of (A) total number of
rings in the sapwood and (B) mean ring area
with stem diameter 50 cm above stem base
(Dstem) for Pinus sylvestris trees at the dry (䊊)
and wet (䊉) sites in the Valais, Switzerland.
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532
STERCK, ZWEIFEL, SASS-KLAASSEN AND CHOWDHURY
Figure 3. Effects of site (drought-induced
stress; DS) on functional relationships in trees
differing in stem diameter Dstem (n = 10) in
Quercus pubescens and Pinus sylvestris trees
at the dry (䊊) and wet (䊉) sites. (A, B) Huber
value (H), (C, D) leaf specific conductivity
(LSC), (E, F) total leaf area (AL) and (G, H)
potential conductivity (KP ). If regression analysis indicated significant interaction effects of
(DS × Dstem ), regressions are shown for each
site separately. Otherwise, ANCOVA was performed to distinguish between the effects of
DS and Dstem (see Table 1 for parameter codes,
and Table 2 for statistics).
variation in LSC (see Figure 2). The site effects on REW and
DEW mirrored one another (see opposite signs of path-coefficients in Figure 5), because smaller conduits allow for higher
densities. In turn, however, REW had a much greater effect on
KP than did DEW, because KP increased with REW to the 4th
power (cf. Equation 3). Because of the small values of RLW and
ALW, the latewood contributions to LSC were less than the
early wood contributions in both species. Taken together, these
results indicate that the combined effects of drought on KP,
which were mediated by AS and R, and the rather weak effect
on AS resulted in lower LSC at the dry site than at the wet site
for both species.
Discussion
Growth
Trees at the dry site produced fewer leaves and less wood than
trees at the wet site, as indicated by the smaller AL, narrower
annual growth rings and smaller AS. Lower productivity at the
dry site than at the wet site was expected, because foliage of
trees on a dry site is characterized by limited stomatal conductance (gs ), lower carbon gain, which reduces shoot and leaf
production, and lower cell turgor, which reduces radial wood
growth (Tyree 2003, Gallé 2006, Zweifel et al. 2006, 2007). In
a study with Pinus palustris, such drought-driven limitations
TREE PHYSIOLOGY VOLUME 28, 2008
DROUGHT AND LEAF SPECIFIC CONDUCTIVITY
533
Table 2. Summary of regression analysis of the effects of stem diameter (Dstem ) and drought-induced stress (DS) on the Huber value (H;
sapwood area:leaf area (AS /A L )), specific leaf conductivity (LSC),
and underlying morphological components in Quercus pubescens and
Pinus sylvestris trees. For Q. pubescens, the interaction effect of Dstem
× DS was significant, and the model was run for individuals from each
site separately. Log-log transformed values were used in the regression model: log10(LSC) = a + blog10(Dstem ) + cDS + d(log10(Dstem) ×
DS), where DS is a dummy variable (wet site = 0, dry site = 1). Effects
of Dstem and DS are shown by b and c values. Intercept value a is not
shown. Significance of the coefficient is indicated as: *, P < 0.05; **,
P < 0.01; ***, P < 0.001; nr, not relevant for single factor regressions
on Dstem; and ns, not significant (P > 0.05).
Dstem effect = b
DS effect = c
Quercus pubescens
H wet
H dry
LSC wet
LSC dry
KP
AL
AS
REW
DEW
–0.56 *
–1.30 ***
–
–1.44 ***
ns
1.27 ***
0.36 *
ns
ns
nr
nr
nr
nr
–0.53 ***
–0.18 ***
–0.38 ***
–0.10 ***
0.16 ***
Pinus sylvestris
H
LSC
KP
AL
AS
REW
DEW
–0.37 **
–
1.43 ***
1.80 ***
1.44 ***
ns
ns
–
–0.48 ***
–0.64 ***
–0.16 **
–0.18 ***
–0.17 ***
0.17 ***
Figure 4. Path-analysis. Effects of site (drought-induced stress, DS)
and stem diameter (Dstem) on total leaf area (AL ) and potential stem
conductivity (KP) and, in turn, the contributions of AL and KP to leaf
specific conductivity (LSC) in (A) Quercus pubescens and (B) Pinus
sylvestris. Path-coefficients (standardized regression coefficients)
along single-headed arrows refer to direct effects, and correlation coefficients along double-headed arrows refer to correlations. Significance of effects and correlations are indicated as: **, P < 0.01; and
***, P < 0.001.
in production were not observed, because AS was similar
across sites and AL was larger at the dry site (Addington et al.
2006). Possibly, the higher annual precipitation in that study
area compared with our site (1310 versus 600 mm) reduced the
severity of soil drought. The low productivity of our study
trees at the dry site suggests that the soil drought was more severe.
Wood anatomy
Soil water strongly influenced AL and KP and the wood characteristics affecting KP. As expected, pines and oaks had considerably narrower conduits in both early- and latewood and
higher conduit densities at the dry site. This accords with the
idea that cell expansion rate and cell size are controlled by
turgor pressure (Hsiao and Avecedo 1974, Steppe et al. 2006),
and that cell expansion rate and ultimate cell size decrease
with decreasing water availability (Sass and Eckstein 1995,
Villar-Salvador et al. 1997, Zweifel et al. 2006). Dendrochronological studies have demonstrated that time series of
conduit size correlate positively with corresponding precipitation (e.g., Sass and Eckstein 1995). However, Eilmann et al.
(2006) reported that latewood conduit size decreased with increasing precipitation in trees at our study site. This may have
Figure 5. Path-analysis. Effects of site (drought-induced stress, DS)
on functional sapwood area (AS), conduit radius (R) and conduit density (D) and, in turn, the contributions of these components to potential stem conductivity (KP) in (A) Quercus pubescens and (B) Pinus
sylvestris. Path-coefficients (standardized regression coefficients)
along single-headed arrows refer to direct effects, and correlation coefficients along double-headed arrows refer to correlations. The relationships are shown for the earlywood traits (AS, R and D), because
the latewood contributions to leaf specific conductivity were less in
both species. Significance of effects and correlations are indicated as:
*, P < 0.05; and ***, P < 0.001.
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534
STERCK, ZWEIFEL, SASS-KLAASSEN AND CHOWDHURY
resulted from limited cambial activity at the dry site in the
summer, a delayed response to earlier conditions or multiple
confounding factors (see Cherubini et al. 2003). In our study,
the persistent soil drought resulted in narrower latewood conduits, as expected in response to a likely drought-driven decline in turgor in trees at the dry site (Villar-Salvador et al.
1997, Zweifel et al. 2005).
Potential stem conductivity
We calculated KP based on theoretical principles, as expressed
by the Hagen-Poiseuille equation (see Equations 2–4). We assumed that the conductive cross-sectional area equaled the total sapwood area for pine (e.g., Whitehead et al. 1984) and the
area of the last ring for oak (cf. Bréda and Granier 1996). The
higher conductivity for pine than for oak agrees with ecophysiological information for trees from the same site
(Zweifel et al. 2007). The potential conductivity may have
been underestimated for oak, because the early wood in some
older rings may have contributed to sap flow (Poyatos et al.
2007a), which was unaccounted for in our calculations. For
both species, potential conductivity, may have been higher
than actual conductivity because it takes no account of end
wall resistances (Sperry et al. 2005) and vulnerability to cavitation (Maherali et al. 2004). Some field studies derive conductivity from measurements of sap flow and microclimate
(Zweifel et al. 2005), but cannot relate the conductance to actual functional sapwood area. When KP is quantified for xylem
sections exposed to controlled water pressure gradients in the
laboratory (Cavender-Bares and Holbrook 2001), assumptions
about the conductive xylem area are needed to predict conductance for trees under field conditions. It may be reasonable to
assume that the entire xylem cross-sectional area contributes
to water transport in beech (Fagus sylvatica L.) and oak
(Quercus robur L.) seedlings (Steppe et al. 2006). In studies of
beech and oak seedlings, the actual conductivities match the
theoretical prediction, i.e., assuming the entire xylem cross
section contributes to stem conductivity multiplied by a species-specific factor with a value of less than 1.0 (Steppe and
Lemeur 2007). This finding suggests that the potential conductivity, as calculated from the Hagen-Poiseuille equation,
can be used for comparative studies within species (cf. Sperry
et al. 2005).
Leaf specific conductivity
For both pines and oaks, LSC was lower at the dry site than at
the wet site. Magnani et al. (2002) predicted the reverse pattern, but cautioned that the empirical evidence for this prediction was based on studies with large trees exposed to drought
pulses for only a few years (e.g., Irvine et al. 1998), or to short
irrigation pulses (e.g., Ewers et al. 2000). The observed increase in LSC in response to drought pulses reflects a sharp increase in leaf production and AL, but little change in wood production and AS. For trees growing under persistent dry conditions, we found the reverse pattern: a decline in LSC, indicating that trees favor allocation to leaves over allocation to radial
growth, which accords with many empirical studies compar-
ing trees along drought gradients (Panek 1996, Vander Willigen and Pammenter 1998), but not all (Mencuccini and Bonosi
2001). Addington et al. (2006) found a lower H in Pinus
palustris in response to persistent soil drought; however, after
controlling for differences in tree height between dry and wet
sites, they concluded that the site effect on H was negligible.
Thus, their findings for P. palustris are in agreement with the
drought responses of H that we observed in P. sylvestris and, at
least partially, with those we observed in Quercus pubescens.
The large difference in LSC between trees at our dry and wet
sites thus confirms that conduit properties significantly contributed to the observed drought responses in LSC, particularly in pine.
In previous studies, drought-driven increases in LSC or H
were usually related to higher VPD during periods of drought,
and these effects were discussed in the context of the hydraulic
model presented by Whitehead et al. (1984) (e.g., Poyatos et
al. 2007b). Here we use the same model to discuss the effect of
persisting soil drought on hydraulic architecture:
AL
c k ⎛ Δψ ⎞
=
⎜
⎟
AS gs VPD ⎝ h ⎠
(5)
where the constant c combines several variables that are
weakly temperature dependent (Whitehead et al. 1984), Δψ/h
is the pressure gradient (Δψ) measured over length (h) from
roots to leaves, gsVPD is the transpiration demand and k is the
permeability of the sapwood. Sapwood permeability may be
related to conduit radius (R) and conduit density (D) according
to the Hagen Poiseuille equation as:
k ∝ DR4
(6)
By dividing Equation 5 by k, we get an equation for the expected response of LSC:
c ⎛ Δψ ⎞
1
∝
⎜
⎟
LSC gs VPD ⎝ h ⎠
(7)
Although we distinguished between early- and latewood conductivities in our calculations, the general relationship is well
described by Equation 7, which predicts that LSC increases
with VPD and gs VPD. Such responses would contribute to
homeostatic regulation of Δψ. Whitehead et al. (1984) suggested that H will be lower at a warmer and drier site than at a
cooler and wetter site. The prediction that H and LSC
(ASKP /AL ) are higher at the drier site assumes that k is similar
across sites. However, site comparisons indicate that this is not
the case for pines and oaks (cf. Eilmann et al. 2006). Permeability was lower for early- and latewood at the dry site, a difference that was at least partially compensated for the lower gs
and gsVPD, assuming only minor differences in VPD between
sites. This response in k limits the change in H in response to
drought, which hardly differed between sites in either study
species. Moreover, it may largely account for the reduction in
LSC in response to drought. From this perspective, our results
TREE PHYSIOLOGY VOLUME 28, 2008
DROUGHT AND LEAF SPECIFIC CONDUCTIVITY
agree with the hydraulic model and suggest that a combined
response in physiology (i.e., gs ) and plant structure (LSC and
its components) contribute to acclimation of hydraulic architecture to soil drought (Martinez-Vilalta et al. 2004, Zweifel et
al. 2006).
This line of reasoning assumes constant conditions at the
dry and wet sites. Drought, however, varies at many time
scales including days, seasons and successive years (e.g.,
Zweifel et al. 2005, 2007). At these time scales, stomata close
during dry periods (Zweifel et al. 2006), limiting carbon gain
(Tyree 2003), implying that trees fix carbon mainly during wet
periods when AL is the main limitation on carbon gain. Accordingly, we may expect that trees in arid areas, such as the
Valais, favor carbon allocation to leaves rather than to radial
growth, because a large AL is highly advantageous during wet
periods. Furthermore, from a physiological perspective, low
turgor in the cambium will reduce radial growth in arid areas
(Steppe et al. 2006), whereas growth limitations due to low
turgor are less severe during spring leaf expansion (Zweifel et
al. 2006). The severe drought at our dry site may therefore
limit wood production rather than leaf production. The resultant high resistances to water flow in trees at the dry site may
be compensated, at least partially, by an ability to maintain sap
flow at lower leaf water potentials (Zweifel et al. 2007). However, during severe drought, such as during the 2003 summer,
sap flow may fall to zero, resulting in massive leaf loss and
persistent low water flow (Zweifel et al. 2007), especially in
oak.
In conclusion, pines and oaks had a lower LSC at the dry site
than at the wet site because of smaller AS, narrower conduits
and a greater reduction in KP than in AL. The resultant low hydraulic capacity during dry weather may be compensated for
by lower leaf water potentials, lower vulnerability to xylem
cavitation and greater resource allocation to fine roots, but
these features were not analyzed. We speculate that relatively
high investments in leaves contributed to carbon gain over a
whole season by enabling high rates of whole-plant photosynthesis during the wetter periods (e.g., in spring, after incidental
rains and during morning hours). Dynamic data and a hydraulic plant growth model are needed to test how investments in
leaves versus sapwood and roots (cf. Magnani et al. 2002,
Addington et al. 2006) contribute to transpiration and to maximizing carbon gain throughout entire growth seasons.
Acknowledgments
We thank Simone de Brock for assisting with field work and Nathan
Phillips for helpful comments. The wood anatomical research was
funded by the Netherlands Organization of Scientific Research
(NWO/AWL MEERVOUD 836.05.030).
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