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Plant Physiol. (1999) 120: 1165-1174
Observations of Hydrogen and Oxygen Isotopes in Leaf Water
Confirm the Craig-Gordon Model under Wide-Ranging Environmental
Conditions1
John S. Roden2, * and
James R. Ehleringer
Stable Isotope Ratio Facility for Environmental Research,
Department of Biology, University of Utah, Salt Lake City, Utah
84112
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ABSTRACT |
The
Craig-Gordon evaporative enrichment model of the hydrogen ( D) and
oxygen ( 18O) isotopes of water was tested in a
controlled-environment gas exchange cuvette over a wide range (400
D and 40 18O) of leaf waters. (Throughout this
paper we use the term "leaf water" to describe the site of
evaporation, which should not be confused with "bulk leaf water" a
term used exclusively for uncorrected measurements obtained from whole
leaf water extractions.) Regardless of how the isotopic
composition of leaf water was achieved (i.e. by changes in source
water, atmospheric vapor D or 18O, vapor pressure
gradients, or combinations of all three), a modified version of the
Craig-Gordon model was shown to be sound in its ability to predict the
D and 18O values of water at the site of evaporation.
The isotopic composition of atmospheric vapor was shown to have
profound effects on the D and 18O of leaf water and
its influence was dependent on vapor pressure gradients. These results
have implications for conditions in which the isotopic composition of
atmospheric vapor is not in equilibrium with source water, such as
experimental systems that grow plants under isotopically enriched water
regimes. The assumptions of steady state were also tested and found not
to be a major limitation for the utilization of the leaf water model
under relatively stable environmental conditions. After a major
perturbation in the D and 18O of atmospheric vapor,
the leaf reached steady state in approximately 2 h, depending on
vapor pressure gradients. Following a step change in source water, the
leaf achieved steady state in 24 h, with the vast majority of
changes occurring in the first 3 h. Therefore, the Craig-Gordon
model is a useful tool for understanding the environmental factors that
influence the hydrogen and oxygen isotopic composition of leaf water as
well as the organic matter derived from leaf water.
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INTRODUCTION |
The stable isotopes of hydrogen ( D) and oxygen
( 18O) in meteoric water vary in both space and
time. When incorporated into the organic matter of plant tissues,
analyses of these isotopes can provide valuable environmental
information regarding patterns of plant water use (Dawson, 1993 ) and
climatic variation (Schiegl, 1974 ; Gray and Thompson, 1976 ; Epstein and
Krishnamurthy, 1990 ). One of the first steps in understanding how the
stable isotopes of water are incorporated into plant organic matter is
to model how leaf water is altered as a result of transpiration (Roden et al., 1999 ). (Throughout this paper we use the term "leaf
water" to describe the site of evaporation, which should not be
confused with "bulk leaf water" a term used exclusively for
uncorrected measurements obtained from whole leaf water
extractions.)
A freely evaporating surface tends to enrich leaf water in heavy
isotopes, since the lighter isotopes of hydrogen and oxygen in water
vapor escape from liquid surfaces more readily that the isotopically
heavy water molecules. Craig and Gordon (1965) were the first to model
this isotopic-fractionation effect for evaporation from large bodies of
water. Flanagan et al. (1991b) modified the Craig-Gordon model
to include the effects of a turbulent boundary layer on the kinetic
fractionation factors that were appropriate for molecular diffusion
only. In some cases the Craig-Gordon model predicts a greater isotopic
enrichment than was actually observed in bulk leaf water (Allison et
al., 1985 ; Leaney et al., 1985 ; Flanagan and Ehleringer, 1991 ; Flanagan
et al., 1991a ; Wang and Yakir, 1995 ). Since the value of leaf
water at the site of carbohydrate metabolism is an essential component
of models predicting the hydrogen and oxygen isotopic composition of
plant organic matter, carefully controlled experiments are needed to
determine how sound these leaf water models are under different
environmental conditions. This is particularly critical when plants are
grown experimentally under conditions in which the source water and
atmospheric water vapor are not in isotopic equilibrium with each
other.
Important environmental parameters included in all leaf water models
are the vapor pressure and isotopic composition of the air near the
leaf and the isotopic composition of the source water supplying the
leaf. The parameters involving atmospheric vapor are often not measured
rigorously in growth experiments and are assumed to have limited
effects on plant isotopic composition. However, White et al. (1994)
demonstrated that the isotopic composition of atmospheric vapor plays
an important role in the isotopic composition of cellulose (presumably
through its effect on leaf water), and asserted that studies that
ignore the influence of atmospheric vapor are potentially flawed.
White and Gedzelman (1984) have shown that the D of atmospheric
vapor can vary seasonally by as much as 70 at a single site and that
the assumption of isotopic equilibrium of atmospheric vapor with
surface water may not always be valid. It may be that the discrepancies
between the Craig-Gordon model and measured leaf water D and
18O values under field conditions are related
to variations in atmospheric vapor D and
18O that are unaccounted for. In addition,
experiments that study the incorporation of stable isotopes in plant
material by artificially enriching water sources can produce
nonequilibrium conditions in which large isotopic differences are
generated between the isotopic composition of the source water and that
of the atmospheric water vapor (Roden and Ehleringer, 1999 ).
While the Craig-Gordon model has strong theoretical support, it has not
been tested over an extended range of leaf waters under conditions of
isotopic nonequilibrium between source water and atmospheric vapor.
Thus, it is important to know how sensitive leaf water is to variations
in the isotopic composition of atmospheric vapor and whether models can
accurately predict leaf water enrichment under a variety of
environmental conditions.
Another important feature of all leaf water models is the assumption of
steady state. In natural systems this assumption is often violated due
to the continual diurnal variation in environmental parameters (Harwood
et al., 1998 ; Yakir, 1998 ). The time needed for a leaf to equilibrate
with its environment after a perturbation is of interest for modeling
efforts. The length of time to reach steady state could also be
affected by humidity, and thus it is important to understand the
significance of variation in vapor pressure gradients. In addition,
understanding how humidity affects the isotopic composition of leaf
water is important as a first step in clarifying some of the disparate
observations in the literature regarding humidity signals recorded in
plant cellulose. While some studies contend that humidity information
is recorded in the isotopic composition of plant cellulose (Edwards and
Fritz, 1986 ; Lipp et al., 1993 ), others find no evidence for a humidity signal (DeNiro and Cooper, 1989 ; White et al., 1994 ; Terwilliger and
DeNiro, 1995 ).
The objectives of this study were: (a) to determine if the leaf water
model is accurate at steady state over a wide range of leaf water
isotopic compositions and vapor pressure gradients and under conditions
in which the isotopic signatures of atmospheric vapor are substantially
different from source water signatures; and (b) to determine the
dynamic response of leaf water to step changes in both atmospheric
vapor and source water isotopic composition.
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MATERIALS AND METHODS |
Plant Material and Growth Conditions
Three-year-old saplings of two species, water birch (Betula
occidentalis Hook) and cottonwood (Populus angustifolia
James), were obtained from local nurseries. The saplings were grown
hydroponically in 190-L tanks (stock tanks, Rubbermaid, Wooster, OH)
with aquarium pumps and airstones providing oxygen to the roots as
described in detail previously (Roden and Ehleringer, 1999 ). The
initial tank water isotopic composition was derived from Salt Lake City municipal water ( D = 120 ;
18O = 15 ). Additions of
D2O and 10 atom % 18O
water (Europa Scientific, Crewe, UK) were mixed with Salt Lake City
water when the experiment called for a change in source water ( D = +87 ; 18O = +6 ).
Nutrients were supplied to the roots as one-tenth-strength Hoagland
solution. The plants were grown in a greenhouse set to 25°C and
ambient humidity (20%-60%). Plants were grown for 1 month in the
greenhouse under constant hydroponic conditions prior to any gas
exchange measurements. A second experiment utilized only cottonwood
saplings grown hydroponically in individual 10-L buckets under three
different source water 18O compositions
( 15 , 0 , and +15 ).
Gas Exchange Measurements
A steady-state gas exchange system described previously (Comstock
and Ehleringer, 1993 ) was utilized to measure water vapor and
CO2 exchange in mature leaves. The temperature,
humidity, light, and CO2 concentration within the
cuvette were controlled and measured. Boundary layer conductance to
water vapor in the cuvette was 2 mol m 2
s 1. Leaf temperatures ranged from 23°C to
26°C. Light levels were saturating (>1,500 µmol photons
m 2 s 1, 400-700 nm),
and the CO2 concentration was 360 µL
L 1. The leaf-to-air water vapor mole fraction
gradient ( ) was controlled by adjusting flow rates and temperature
of a dew point column for vapor input, and was maintained for the
entire 5- to 7-h experiment between 0.005 and 0.01 and between 0.018 and 0.025 (dimensionless, mole per mole) for the "low" and
"high" treatments, respectively. Total conductance to water
vapor differed between treatments for birch (low ; range 0.16 to
0.54 mol m 2 s 1, mean of
0.4 and high ; range 0.14 to 0.34 mol m 2
s 1, mean of 0.24) but not for cottonwood (low
, range 0.17 to 0.55 mol m 2
s 1, mean of 0.35 and high range 0.13 to
0.57 mol m 2 s 1, mean of
0.33).
Stomatal conductance to water vapor and leaf transpiration rates were
recorded throughout the experiment. Although not critical for
calculations of leaf water isotopic composition, carbon assimilation rates ranged from 10 to 25 µmol CO2
m 2 s 1 and intercellular
CO2 concentrations from 200 to 300 µL
L 1.
Experiment 1: Change in Input Vapor Isotopic Composition
At the start of the experiment, a sapling was transferred from the
190-L tank in the greenhouse to an 8-L bucket containing the same
source water as the tank (the bucket was actually filled with tank
water), brought to the gas exchange system, and a root aeration system
was installed. A leaf was placed into the gas exchange cuvette for
1 h to allow physiological adjustment to the cuvette environment
and the stomata to open fully. The input water vapor was manipulated by
altering the isotopic composition of the water reservoir that
humidified the air stream prior to the dew point column (the bubbler).
For the 1st h, input water vapor was set to a value close to the
ambient conditions in the greenhouse, then the water in the bubbler was
enriched by approximately 180 to 240 ( D) and/or 20 to 25
( 18O). Prior to the step change, both input
and output water vapor was collected in a 9-mm Pyrex tube fitted to an
ethanol/dry ice trapping system ( 78°C) connected to the air flow
tubing either just before (input vapor) or just after (output vapor)
the leaf cuvette. After the step change, output water vapor was sampled every 20 to 30 min for the first 2 h and less frequently
thereafter to determine the time required for the leaf to reach
isotopic steady state.
Experiment 2: Change in Water Source Isotopic Composition
In this experiment, the saplings were handled in the same initial
manner as described above, except instead of a step change in input
vapor isotopic composition, the water in the bucket was enriched from
120 to +120 in D and/or from 15 to +10 in 18O. Output water vapor was sampled (as above)
at progressively longer time intervals over a 30-h period to determine
the time required for the leaf to reach isotopic steady state after a
step change in source water isotopic composition. In addition to output vapor, source water was also sampled periodically.
Experiment 3: Dependence of Leaf Water on and Isotopic
Composition of Vapor
In this experiment, the saplings were handled in the same initial
way as in experiment 1, except dynamic changes in output vapor were not
tracked. The isotopic composition of the input water vapor was changed
by enriching the bubbler (as above), and the leaf was allowed to reach
steady state for a minimum of 5 h. The experiment did not end
unless the estimates of stomatal conductance, transpiration rate, and
did not systematically vary for at least 1 h. The leaves did
not show any midday depressions in stomatal conductance, and for the
most part had flat-line responses for the entire experimental period.
At the end of the experiment, the output water vapor, source water, and
leaf water were sampled. This experiment was performed on both species
with two source water treatments, both low and high (see above), as
well as four to five different input vapor isotopic compositions for a total of 32 experiments. The data from these experiments were also used
to test the ability of a leaf water model to predict the observed
variations in leaf water D generated by the imposed environmental
conditions.
Due to analysis problems with the 18O
measurements in the original experiments, a second round of experiments
was performed that varied 18O in source water
and the cuvette vapor to generate variation in leaf water
18O to test the leaf water model for
18O. This experiment used three source water
treatments ( 15 , 0 , and +15 18O),
with all other measurements similar to the steady-state experiment described above.
Isotope Sampling
Approximately 2 mL of water was sampled from the tank or buckets
for analysis of source water D and 18O. At
the end of each experiment, leaf material with the midvein removed was
placed into a glass vial, sealed with laboratory film, and placed into
a freezer ( 5°C) until the water could be extracted for isotopic
analysis. Leaf water was obtained by cryogenic extraction as described
by Ehleringer and Osmond (1989) . The sample was frozen in liquid
nitrogen ( 190°C) and once evacuated, the system was then isolated
from the vacuum pump and immersed in boiling water. The water from the
leaf was then collected in a tube immersed in liquid nitrogen until all
water was extracted.
The D of water samples from the tanks, leaves, and output vapor were
obtained by reducing the H in 2 µL of H2O to
H2 using 100 mg of a Zn catalyst in a 500°C
oven (modification of Coleman et al., 1982 ). The
18O values of the water samples were obtained
by a modified micro-equilibration technique in which 20 to 60 µL of
water was sealed in a 9-mm Pyrex tube with approximately 240 µL of
CO2 in a 25°C water bath for over 7 d. In
this method the CO2 is extracted cryogenically
using liquid nitrogen and dry-ice/ethanol traps (Ehleringer and Osmond, 1989 ). Because of the small volume of CO2 in the
micro-equilibration technique, an external "cold-finger" was used
to increase the amount of CO2 input into the mass
spectrometer. Both the H2 and CO2 were analyzed on an isotope ratio mass
spectrometer (MAT Delta S, Finnigan, San Jose, CA) with a precision of
±1 for D and ±0.2 for 18O.
Leaf Water Model
Throughout this paper we will be using the conventional
"delta" notation, which expresses the isotopic composition of a
material relative to that of a standard on a per mil deviation basis:
|
(1)
|
where is the isotope ratio and R is the molar ratio
of heavy to light isotopes. The standard for both hydrogen and oxygen is Standard Mean Ocean Water (SMOW).
A general model for the evaporative enrichment of a free water surface
for both D and 18O was developed by Craig
and Gordon (1965) . The model includes both an equilibrium isotope
effect resulting from the phase change from liquid to vapor and a
kinetic isotope effect caused by different rate of diffusion of the
heavy and light isotopes of water vapor in air. The Craig-Gordon model
was expanded by Flanagan et al. (1991b) to include leaf boundary
layers (see also Farquhar et al., 1989 ):
|
(2)
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where the subscripts a, wl, and wx refer to bulk air, leaf water,
and xylem water, respectively, and e is the vapor pressure (subscripts
a, s, and i refer to bulk air, leaf surface, and intercellular air
spaces, respectively). (Leaf surface vapor pressures were determined
from the equations of Ball [1987]. The fractionation factors differ
depending on whether hydrogen or oxygen isotopes are being modeled, but
the same general model applies to both species.) * is the
liquid-vapor equilibrium fractionation factor and varies with
temperature according to the equations of Majoube (1971) for both H/D
and 16O/18O,
k is the kinetic fractionation associated with
diffusion in air (H/D = 1.025 and
16O/18O = 1.0285), and
kb is the kinetic fractionation associated
with diffusion through the boundary layer and is calculated by raising k to the 2/3 power (H/D = 1.017 and
16O/18O = 1.0189).
Other studies (Buhay et al., 1996 ; Wang et al., 1998 ) have
accounted for boundary layer effects by modifying the kinetic fractionation for different species from leaf aerodynamic and morphological properties.
The Craig-Gordon model contains a number of assumptions that may not be
strictly valid for leaves, causing potential discrepancies between the
model and bulk leaf water D and 18O
measurements. For leaves the assumption of: (a) isotopic steady state
(b) constant water volume, and (c) isotopic homogeneity may not always
be valid (Yakir, 1998 ). Significant spatial heterogeneity in D and
18O of water within a leaf has been observed,
because all parts are not equally exposed to evaporation (Yakir et al.,
1989 ; Luo and Sternberg, 1992 ). Some of this heterogeneity may be
caused by compartmentation (vein and mesophyll tissues), patchy
stomatal conductances (Mott, 1995 ), contrasting effects of diffusion of isotopically enriched water from the evaporating surfaces into the leaf
tissues against the convective flux of source water from the xylem
(Péclet effect, Farquhar and Lloyd, 1993 ), or all of the above.
In addition, some researchers have found that leaf morphological and
physiological characteristics can enhance predictions of the isotopic
composition of leaf water (Buhay et al., 1996 ; Wang et al., 1998 ). Due
to the many potentially interacting effects described above, we chose
to bundle them all into empirical equations (Flanagan, 1993 ) that are
used to correct bulk leaf water measurements for comparisons with
predictions of the Craig-Gordon model:
|
(3)
|
|
(4)
|
where l is the proportion of
the bulk leaf water subjected to evaporative enrichment, the subscripts
bulk and wx refer to bulk leaf water and xylem water, respectively, and
wl refers to the values of D and 18O from
Equation 2 above. An electronic spreadsheet version of the model
is available at (ftp://ecophys.biology.utah.edu/treering/).
 |
RESULTS |
To compare the curves during step changes in either source water
or input water vapor isotopic composition, the data were normalized
such that the relative change in output vapor at steady state was set
to 100%. For both D and 18O, leaves
reached isotopic steady state in 5 to 6 h (Figs.
1 and 2).
For plants exposed to high , the leaves reached equilibrium in as
little as 2 h, with 50% of the changes occurring within 30 to 60 min. Plants exposed to low took longer to reach steady state (3-5
h) as well as half maximum (1-2 h). There was no apparent difference
in the amount of time to reach steady state between D and
18O, although there is not enough replication
(n = 2) to determine fine scale differences. Birch
leaves may take longer to reach equilibrium that poplar leaves, but,
again, the differences were generally minor.

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| Figure 1.
Time course of the relative change in output vapor
D after a step change in input vapor D (time 0) for leaves of
birch or poplar exposed to high or low . Values are means ± SE (n = 2). A missing error bar implies
that a sample was lost (n = 1) unless the data are
near 0% or 100%, in which case the error bars are often within the
symbol. If a symbol is missing then both samples were lost due to
technical difficulties.
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| Figure 2.
Time course of the relative change in output vapor
18O after a step change in input vapor
18O (time 0) for leaves of birch or poplar exposed to
high or low . Values are means ± SE
(n = 2). A missing error bar implies that a sample
was lost (n = 1) unless the data are near 0% or
100%, in which case the error bars are often within the symbol. If a
symbol is missing then both samples were lost due to technical
difficulties.
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When there was an abrupt change in source water to the roots the output
vapor changed little over the 1st h, then changed
rapidly by 3 h, and exhibited gradual changes thereafter (Fig.
3). The leaf reached steady state by
24 h and somewhat earlier for birch than cottonwood. Both plants
were exposed to moderate (0.01-0.018) and had stable conductances
to water vapor (0.4-0.6 mol m 2
s 1) and transpiration rates (5-7 mmol
m 2 s 1) during the
daytime periods.

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| Figure 3.
Time course of the relative change in output vapor
D and 18O after a step change in source water D
and 18O (time 0) for leaves of birch and poplar.
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Various combinations of the isotopic composition of source water and
input vapor produced leaves with a range of 400 in leaf water D.
For a given source water and , both species produced linear
relationships between cuvette water vapor D and leaf water D
(Fig. 4). The cuvette water vapor (the
output vapor) isotopic composition is a combination of both the input
vapor and transpiration and is analogous to atmospheric vapor in
natural systems. The leaf not only undergoes evaporative enrichment
with its environment but also isotopic vapor exchange. The degree to
which the isotopic composition of the cuvette water vapor affected leaf
water was dependent on (Fig. 4).

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| Figure 4.
Relationship between the isotopic composition of
cuvette water vapor (output vapor) and the isotopic composition of leaf
water for birch and poplar leaves exposed to high and low and grown
in source water of either 122 or 87 D.
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At low (high humidity) there is a greater probability for the water
vapor in the cuvette to exchange with the leaf, causing the differences
in the observed slopes between high and low . The intersection of
the high and low lines occurred when the cuvette water vapor D
was close to the source water D. If there is no gradient in D
between atmospheric vapor and source water, then becomes
irrelevant, as it relates to isotopic vapor exchange and the leaf water
isotopic signature reflects evaporative enrichment only. The reason the
cuvette water vapor D at the intersection of the high and low lines is not exactly equal to the source water D value is that will still affect evaporative enrichment even if isotopic gradients for
vapor exchange are minimized.
Using the detailed environmental and physiological measurements derived
from the steady-state gas exchange experiments, the leaf water isotopic
composition was predicted from the leaf water model (Eq. 2). These
predictions were then compared with the measured leaf water D
values. Clearly, the model does a good job of predicting leaf water
D over a wide range of leaf water values (400 ) and only deviated
from the 1:1 line at highly enriched values (Fig. 5). These leaf waters were generated by
extremely diverse means, including both depleted and enriched source
waters, high and low , and highly depleted and enriched cuvette
water vapor input. The Craig-Gordon model handled these disparate
environmental conditions and produced plausible leaf water predictions.

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| Figure 5.
Relationship between the D of modeled and
measured leaf water. Variations in leaf water were generated in a gas
exchange cuvette through altering input vapor D, source water
D, and vapor pressure deficits and flow rates. The line represents a
1:1 relationship.
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The leaf water model accurately predicted measured leaf water
18O over a range of nearly 40 (Fig.
6). In this experiment, we used only
cottonwood. The species-specific parameters in the leaf water model
(stomatal conductance and transpiration rate) are only used to estimate
the water vapor at the leaf surface (Ball, 1987 ; Roden et al., 1999 ),
and sensitivity analysis has shown that their effects on leaf
water isotopic composition are limited. Although Wang et al. (1998)
have observed substantial differences between species, the similar
morphology and physiology of birch and cottonwood leaves, as well as
the lack of observed species effects when modeling leaf water D,
indicated that a single species (cottonwood) test for
18O was sufficient.

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| Figure 6.
Relationship between the 18O of
modeled and measured leaf water. Variations in leaf water were
generated in a gas exchange cuvette through altering input vapor
18O, source water 18O, and vapor pressure
deficits and flow rates. The line represents a 1:1 relationship.
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DISCUSSION |
Despite a variety of approaches to alter the isotopic composition
of leaf water (i.e. changing the , the source water D and
18O, or the atmospheric vapor D and
18O), the Craig and Gordon (1965) evaporative
enrichment model as modified by Flanagan et al. (1991b) did an
excellent job in predicting leaf water isotopic composition over a wide
range (400 in D and 40 in 18O) of
values (Figs. 5 and 6). Some previous studies have found that the
Craig-Gordon model predicted a higher degree of heavy isotopic
enrichment than observed in bulk leaf water measurements (Allison et
al., 1985 ; Leaney et al., 1985 ; Flanagan and Ehleringer, 1991 ; Flanagan
et al., 1991a ; Wang and Yakir, 1995 ). Although the results of
this study also showed a similar trend between modeled and measured
bulk leaf water values, the generality of the model is still clearly
evident over the range of leaf waters that far exceeds natural
conditions (Figs. 5 and 6).
Although some researchers have attributed the difference between
observed and modeled leaf water to the inclusion of unfractionated vein
water in the bulk leaf water isotopic composition (Allison et al.,
1985 ; Leaney et al., 1985 ; Walker et al., 1989 ), the results presented
in this study were corrected (Eqs. 3 and 4) for this effect. The
unfractionated pool of water has been estimated to be from 13% to 30%
of the total water volume (Allison et al., 1985 ; Leaney et al., 1985 ;
Walker et al., 1989 ; Flanagan et al., 1991b ). Since the major
vein was cut out of the leaf just prior to sampling, a smaller fraction
(10%) produced the best fit between observed and measured values in
this study. Alternatively, some researchers have attributed
discrepancies between observed and modeled leaf water to high
transpiration rates (Flanagan et al., 1991b ). Transpiration
rates could potentially shift the balance between the back diffusion of
heavy isotopes from the sites of evaporation and the bulk flow of
source water into the leaf (Farquhar and Lloyd, 1993 ). However, there
was no relationship between transpiration rate and differences between
modeled and measure leaf water isotopic composition in our data (Fig.
7), although the transpiration rates were
much lower than reported in Flanagan et al. (1991b) .

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| Figure 7.
Difference between modeled and measured leaf water
D as a function of leaf transpiration rate or the difference between
source water D and cuvette vapor D. , Plants grown in enriched
source water (87 D); , plants grown in depleted source water
( 122 D).
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Modeling bulk leaf water is more problematic than modeling leaf water
at the site of evaporation. The Craig-Gordon model contains a number of
assumptions that may not be strictly valid for whole leaves, such as
isotopic steady state, constant water volume, and isotopic homogeneity
(Flanagan, 1993 ; Yakir, 1998 ). Many of the bulk leaf water corrections
in the literature require detailed anatomical, morphological, and
physiological information for each species (Buhay et al., 1996 ; Wang et
al., 1998 ; Yakir, 1998 ). In addition, the Péclet correction
(Farquhar and Lloyd, 1993 ), in which the effects of diffusion of
isotopically enriched water from the evaporating surfaces into the leaf
tissues opposes the convective flux of source water from the xylem,
requires knowledge of the leaf transpiration rate and the effective
mixing pathlength. In practice, the effective mixing length is
calculated from the discrepancies between the Craig-Gordon model and
the measured bulk leaf water along with gas exchange measurements of
leaf transpiration. The proportion of bulk leaf water subjected to
evaporative enrichment ( l) in
Equations 3 and 4 is an empirical value that incorporates all of the
factors that influence bulk leaf water isotopic heterogeneity for the
species tested. Mechanistic models of the D and
18O values of bulk leaf water may still be
unable to account for all of the potential influences on leaf
heterogeneity (e.g. patchy stomatal conductance).
The l value of 10% used in this
study produced excellent fits between modeled and measured observations
over an extended range of leaf water D and
18O values for both species (Figs. 5 and 6).
This implies that if l is
determined for a species using detailed micro-environmental and gas
exchange information, as well as the isotopic composition of bulk leaf
water, then it may be used to correct bulk leaf water observations over
a wide range of values. However, the utilization of the Craig-Gordon
model in studies of the isotopic composition of plant organic matter
(e.g. tree rings, Roden and Ehleringer, 1999 ), as well as
studies of global and canopy CO2 exchange of O with the atmosphere (Farquhar and Lloyd,
1993 ; Flanagan et al., 1994 ), is not dependent on the various
corrections for bulk leaf water heterogeneity. For these studies what
is important is the D and 18O values in the
chloroplast, where carbohydrate metabolism and CO2 exchange take place. The proximity of
chloroplasts to the air-water interface suggests that chloroplast water
should be very close to that predicted by the Craig-Gordon model, as
shown by Flanagan et al. (1994 , but see also contrasting results from Yakir et al., 1993 ).
There was a slight trend for the difference between modeled and
measured leaf water isotopic composition to be related to the magnitude
of the difference between source water and cuvette vapor D (for the
enriched source water treatment only [Fig. 7]). Sensitivity analysis
of the leaf water model indicates (Roden et al., 1999 ) that as
the difference between source water D and atmospheric vapor D
increases, any errors in humidity measurements will magnify errors in
model prediction. In addition, at high humidities, any errors in
atmospheric vapor D measurements will also magnify errors in the
prediction of leaf water D. Thus, although the model is effective in
handling even large differences between source water and atmospheric
vapor D (as high as 300 in this study), extreme care must be
taken when estimating environmental parameters for use in the leaf
water model. However, these concepts are less likely to apply to
differences observed in field studies, since the differences between
the isotopic composition of local water sources and atmospheric vapor
are not as large as those generated in these experiments.
These results have implications for conditions in which the isotopic
composition of atmospheric vapor is not in equilibrium with source
water, such as experimental systems that grow plants under isotopically
enriched water regimes (Roden and Ehleringer, 1999 ) and natural
systems in which trees are exposed to seasonably variable atmospheric
water vapor but tap water sources that are less variable than meteoric
input (ground water).
There was excellent agreement between modeled and measured leaf water
18O evident over the entire leaf water range
(approximately 40 , Fig. 6). There did not appear to be any
relationship between transpiration rate and discrepancies between
modeled and measure leaf water 18O values, nor
was there a relationship between the magnitude of source water and
cuvette vapor 18O differences (data not
shown). Some of the differences between modeled and observed oxygen
isotope ratios in leaf water from the earliest studies relate to the
noninclusion of boundary layer effects in the Craig-Gordon model
(Flanagan et al., 1991b ). Boundary layer effects are
quantitatively more important for oxygen than for hydrogen because the
relative magnitudes of the kinetic and equilibrium fractionation
factors differ between the two species (Flanagan, 1993 ).
Following a change in the isotopic composition of vapor in the cuvette,
approximately 2 to 5 h was required for the leaf to reach isotopic
steady state depending on . A number of other studies (Farris and
Strain, 1978 ; Yakir et al., 1993 ) have also found that 2 h are
required to reach steady state. Flanagan et al. (1991b) found
that common bean leaves required approximately 1 h to reach
isotopic steady state when exposed to an increase in irradiance.
Flanagan et al. (1991b) used dry air as an input to create very
high ; the resulting high transpiration rates may explain some of
the differences in the response dynamics, since lower tend to
extend the equilibration time (Figs. 1 and 2).
There could also be species differences, since the turnover time for
leaf water depends on the ratio of leaf water to the transpiration
rate. On the other hand, birch, poplar, and common bean leaves all have
fairly thin leaves and relatively high transpiration rates, so turnover
rates may not be the critical factor. Longer time periods would be
required to reach steady state for thick, schlerophylous leaves, plants
in very humid environments, or leaves with low stomatal conductance.
However, it should also be noted that the step change in these
experiments was fairly drastic (output vapor changed by as much as
270 in D and 15 in 18O over the 5- to
7-h experiment), and in natural systems, perturbations in the
environment would be far less drastic and more gradual.
Leaves may actually be very close to isotopic steady state in the field
even though the environmental conditions are not constant, so the
steady-state assumptions of the leaf water model may not invalidate its
use in natural systems. A recent study by Harwood et al. (1998) showed
that leaves of Piper aduncum were not at isotopic steady
state while vapor pressure deficits were changing and isotopic steady
state was achieved for only 2 h around midday. However, isotopic
steady state was achieved for a time, and sampling protocols should
consider the best time of day to collect leaves so as to avoid changing
environmental conditions.
After a change in source water isotopic composition, approximately
3 h was required for the majority of changes in leaf water to show
up in the output vapor and approximately 24 h was required to be
assured of complete equilibration for the small trees used in these
experiments (Fig. 3). Using typical transpiration rates (5 mmol
m 2 s 1), specific leaf
area, and relative water content of a poplar leaf, turnover of the
entire leaf water volume should have occurred in as little as 15 min.
The amount of time it takes for a leaf to come into equilibration with
a step change in the isotopic composition of source water depends on
the capacitance of the system (especially stem water storage capacity)
and on the mixing rate within the leaf (apoplastic to symplastic water
exchange). In natural systems the isotopic composition of source water
can change, but seldom is this change rapid or to as large an extent as
in these experiments (240 in D and 25 in
18O). These results are more applicable to
experimental systems in which stable isotopes of water are used as
tracers. A spike in either 2H or
18O could be detected within 24 h, depending
on the water flux rates through the plant.
The degree of isotopic enrichment in a leaf is not only dependent on
evaporation, but also on the difference between the isotopic composition of the water supplying the leaf and that of the atmospheric water vapor. In general, the isotopic composition of vapor in the air
is related to the isotopic composition of meteoric waters for that
region, making it difficult to study atmospheric vapor effects in the
field. The advantage of a gas exchange system is that artificial
differences between the isotopic composition of source water and
atmospheric vapor can be imposed and effects on leaf water studied
while other factors such as are controlled. The differences in
slope between the high and low (Fig. 4) demonstrate that the heavy
isotopes in atmospheric vapor influence leaf water isotopic composition
depending on the gradients that drive vapor flux. There is often the
perception that vapor moves in one direction only (out of the leaf),
but our data support the concept of a bidirectional isotopic flux until
isotopic equilibrium is reached.
In conclusion, the models describing evaporative enrichment developed
by Craig and Gordon (1965) and modified by Flanagan et al.
(1991b) are sound in their ability to predict both hydrogen and
oxygen isotopic composition over a wide range of leaf waters. As such,
these equations are a useful tool to determine the environmental factors that may influence leaf water and, ultimately, plant organic matter isotopic composition. It is clear from the present study that
when making estimates of leaf water isotopic composition in natural or
artificial environments, careful measurements of atmospheric humidity
and the isotope ratios of that vapor are needed. The model assumption
of isotopic steady state is probably achieved under relatively stable
environmental conditions and should not be a deterrent for using the
model in field situations.
 |
FOOTNOTES |
1
This study was supported by the National Science
Foundation (grant no. IBN 95-08671).
2
Present address: Department of Biology, Southern
Oregon University, Ashland, OR 97520-5071.
*
Corresponding author; e-mail rodenj{at}sou.edu; fax 541-552-6412.
Received January 4, 1999;
accepted May 10, 1999.
 |
ABBREVIATIONS |
Abbreviations:
D, stable hydrogen isotope ratio.
18O, stable oxygen isotope ratio.
, leaf-to-air water
vapor mole fraction gradient.
 |
ACKNOWLEDGMENTS |
The authors thank Craig Cook and Mike Lott (Stable Isotope Ratio
Facility for Environmental Research) for isotope analysis and valuable
discussion, Sue Phillips and Brent Helliker for assistance with the gas
exchange system, and Jonathan Comstock and Larry Flanagan for valuable
discussions.
 |
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