Oxygen isotope signatures of transpired water vapor: the role of isotopic non-steady-state transpiration under natural conditions

Oxygen isotope signatures of transpired water vapor: the role ofisotopic non-steady-state transpiration under natural conditions

Maren Dubbert1, Matthias Cuntz2, Arndt Piayda2 and Christiane Werner1

1Agroecosystem Research, BAYCEER, University of Bayreuth, Universit€atsstraße 30, 95447 Bayreuth, Germany; 2UFZ – Computational Hydrosystems, Helmholtz Centre for Environmental

Research, Permoserstraße 15, 04318 Leipzig, Germany

Author for correspondence:Maren Dubbert

Tel: +49 921 552181Email: [email protected]

Received: 16 January 2014

Accepted: 6 May 2014

New Phytologist (2014) 203: 1242–1252doi: 10.1111/nph.12878

Key words: isotopic non-steady-statetranspiration, isotopic steady-statetranspiration, laser spectrometer, oxygenisotopes, plant transpiration,Quercus suber.

Summary

� The oxygen isotope signature of water is a powerful tracer of water movement from plants

to the global scale. However, little is known about the short-term variability of oxygen iso-

topes leaving the ecosystem via transpiration, as high-frequency measurements are lacking.� A laser spectrometer was coupled to a gas-exchange chamber directly estimating branch-

level fluxes in order to evaluate the short-term variability of the isotopic composition of

transpiration (dE) and to investigate the role of isotopic non-steady-state transpiration under

natural conditions in cork-oak trees (Quercus suber) during distinct Mediterranean seasons.� The measured d18O of transpiration (dE) deviated from isotopic steady state throughout

most of the day even when leaf water at the evaporating sites was near isotopic steady state.

High agreement was found between estimated and modeled dE values assuming non-steady-

state enrichment of leaf water.� Isoforcing, that is, the influence of the transpirational d18O flux on atmospheric values,

deviated from steady-state calculations but daily means were similar between steady state

and non-steady state. However, strong daytime isoforcing on the atmosphere implies that

short-term variations in dE are likely to have consequences for large-scale applications, for

example, partitioning of ecosystem fluxes or satellite-based applications.

Introduction

Oxygen isotope signatures (d18O) of water can provide importantinformation on the impact of distinct pathways of water from theecosystem to the global scale (Dongmann et al., 1974; Yakir &Sternberg, 2000; Williams et al., 2004). At the ecosystem level,for example, they can be used to partition net water fluxes intotheir constituent fluxes (Yakir & Sternberg, 2000). The largestwater output flux of an ecosystem is transpiration, associated withan isotopic composition (dE), that strongly influences the isotopicsignature of the local water cycle. dE is mostly assumed to be inisotopic steady state, that is, has the same composition as the sup-plying water, because an increase in the isotopic composition ofterrestrial water is not observed in the long term. In recent years,though, it has become clear that leaf water, which feeds transpira-tion, is isotopically not in steady state most of the time in many ofdifferent ecosystems (e.g. Dongmann et al., 1974; Cernusak et al.,2002). Consequently, dE should also deviate from isotopic steadystate. It was, however, difficult to determine dE in the past as mea-surements of water vapor isotopes were difficult to obtain usingcold-trap methods (Helliker & Ehleringer, 2002), delivering datawith low time resolution (Harwood et al., 1998). Alternatively, dEcan be estimated indirectly by modeling the isotopic signature ofleaf water at the evaporating sites of the leaves under the assump-tion of non-steady-state transpiration, that is, dE 6¼ d18O of

xylem/source water (ds; Dongmann et al., 1974). Thereafter dEcan be determined using the equation of Craig & Gordon (1965).Nevertheless, ecosystem partitioning studies still often assumedtranspiration to be in isotopic steady state, that is, the d18O oftranspiration is equal to the d18O of xylem water (ds; e.g. Yepezet al., 2003).

More information is available on isotopic non-steady-stateeffects on the oxygen isotope enrichment of leaf water itself (dl)and associated mechanistic processes at the leaf and canopy scales(Farquhar & Cernusak, 2005; Seibt et al., 2006; Cuntz et al.,2007; Lai et al., 2008; Xiao et al., 2012). By contrast, the diurnaldevelopment of dE and the relationship between non-steady-stateleaf water and the consequent non-steady-state effect of tran-spired vapor have gained little attention. The latter can, however,be estimated indirectly by measurements of ambient vapor isoto-pic composition inside the canopy (Xiao et al., 2010), whereasfield studies estimating the temporal development of dE directly,that is, by coupling gas-exchange systems to laser spectrometers,are still scarce (but see Haverd et al., 2011; Wang et al., 2012).The recent developments in laser spectroscopy now enable directmeasurements of the isotopic composition of atmospheric watervapor (da), and of evapotranspiration (dET), and its componentswith high temporal resolution in the field (on a scale of minutesto hours; Werner et al., 2012 and literature therein). Conse-quently, emerging studies using continuous high-frequency

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measurements of da combined with land surface models havegained new insights into fractionation processes occurring duringisotopic water vapor and carbon dioxide exchange (C18O16O;e.g. Xiao et al., 2010, 2012; Lee et al., 2012; Welp et al., 2012;Berkelhammer et al., 2013). In this context, it is important toquantify and disentangle the impact of isotopic non-steady-statetranspiration on ecosystem flux partitioning and atmosphericvapor under natural conditions.

Moreover, direct estimates of dE provide the novel opportunityto validate and improve common modeling, for example theCraig and Gordon equation to model isotopes of soil evaporation(Craig & Gordon, 1965; Good et al., 2012; Dubbert et al., 2013;Hu et al., 2014), and resolve the role of non-steady-state transpi-ration under natural conditions on a diurnal basis at high resolu-tion (Simonin et al., 2013). At present, hardly anything is knownabout the impact of environmental factors or differences betweenplant functional groups on: temporal variations of dE on a diur-nal time-scale; the proportion of non-steady-state transpirationunder natural conditions; and the isoforcing of non-steady-statetranspiration on the atmosphere. This knowledge is crucial, as dEis widely used to partition ecosystem fluxes (Yakir & Sternberg,2000) or in water balance modeling from regional to global scales(e.g. Farquhar & Lloyd, 1993; Jasechko et al., 2013; Schlesinger& Jasechko, 2014).

To fill this gap, a novel approach was used, combining a cus-tom-built flow-through gas-exchange branch chamber with a cav-ity ring-down spectrometer (CRDS). We present here, to ourknowledge, the first data set on daytime cycles of direct estimatesof dE in key environmental periods: spring, summer drought,and the beginning of autumn. In particular, we compare directwith indirect estimates of the isotopic composition of transpiredwater vapor (dE) of cork-oak (Quercus suber L.) trees. Further-more, we quantify the role of non-steady-state transpiration anddetermine the driving factors for the deviation of dE from the iso-topic composition of source water ds, that is, isotopic steady state,as well as the isoforcing of isotopic non-steady-state transpirationon the atmosphere.

Materials and Methods

Isotopic compositions are reported here as ratios R between theconcentrations of rare and common isotopes, and expressed ind-notation, that is, relative to Vienna Standard Mean OceanWater (V-SMOW; Gonfiantini, 1978): d = R/RV-SMOW� 1, orin D-notation, that is, relative to source water Rs: D = R/Rs� 1.The latter facilitates a comparison between different ecosystems.A list of all abbreviations is given in Table 1.

Study site

Measurements were conducted between June and November2011 in an open cork-oak woodland in central Portugal(39°8017.84″N, 8°2003.76″W; Herdade de Machoqueira doGrou). The trees are widely spaced (209 individuals ha�1) with aleaf area index of 1.1 and a mean maximum height of 10 m. Thesite is characterized by a Mediterranean climate with wet winters

and springs and hot, dry summers. The mean annual temperatureis c. 15.9°C and the mean annual precipitation is 680 mm (last30-yr average; Instituto de Meteorologia, Lisbon, Portugal). Forfurther information, see Dubbert et al. (2013).

Environmental variables

Air temperature and relative humidity (RH; CS-215 Tempera-ture and Relative Humidity Probe; Campbell Scientific, Logan,UT, USA) were stored as 30-min averages in a datalogger(Cr10x, CR1000; Campbell Scientific). Volumetric soil watercontent (hs; 10hs; Decagon, Pullman, WA, USA) at 5 and 60 cmdepth was measured and 60-min averages were stored in a data-logger (CR1000; Campbell Scientific; four sensors per depth).Leaf temperature was recorded simultaneously with gas-exchange

Table 1 Symbols and descriptions used in this study

Symbol Description

ak Kinetic fractionation factora+ Equilibrium fractionation factord18O Oxygen stable isotope signature (&)d Oxygen stable isotope signature, shortened version (&)D Deviation of a given isotopic signature from source water℘ P�eclet numberh Volumetric soil water content (m3m�3)C The molar water concentration (mol m�3)D/Di Differences in molecular diffusivity (D) between the major

and the minor isotopologsE Plant transpiration (mmol m�2 s�1)ET Evapotranspiration (mmol m�2 s�1)f1,2 Factors for estimating Rl

fem Factor for estimating Rm

gtw Total conductance for water vaporh Relative humidity normalized to leaf temperature (%)I Isoforcing (mol m�2 s�1&)Leff Effective length of water movement in the leaf mesophyll (m)n Exponent relating D/Di to apparent kinetic fractionationRH Relative air humidity (%)R Isotope ratio of (18O)/(16O)T Temperature (°C)u Flow rate (mol(air) s�1)Vm Leaf water volume (mol(H2O) m�2)w Mole fraction (mol(H2O) mol(air)�1)

Subscript Description

a Atmospheric airC Craig and Gordon steady-state prediction at the evaporating

sites (&)e Evaporating siteh Relative humidityi Stomatal cavityin Chamber airl Leafm Liquid mesophyll waterout Background airp PrecipitationR(t) Isotope ratio of leaf water at the evaporating sites at time t (&)R(t+dt) Isotope ratio of leaf water at the evaporating sites at time

t plus a time step t + dt (&)s Source water; i.e. xylem water

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measurements (see ‘CRDS-based measurements’ below). RH cor-rected to leaf temperature h and leaf vapor pressure deficit VPD(Pa) were calculated from RH and leaf and air temperatures.

CRDS-based measurements

Fluxes and the isotopic composition of cork-oak transpirationwere measured using a CRDS (L2120-i; Picarro, Santa Clara,CA, USA) in combination with custom-built branch chambersin an open gas exchange system (n = 3 per treatment; Fig. 1). Atransparent cylindrical acrylic chamber with a total volume of2.5 l was coated with an FEP foil (4PTFE, Stuhr, Germany) toavoid isotopic fractionation. The background air inlet port andthe sampling air outlet port were located at opposite sides ofthe chamber. The background air was sampled above crownheight and buffered with a 200-l volume. The flow through thechamber was adjusted between 1 and 2.5 l min�1. The CRDSwas calibrated three times a day using a standard delivery mod-ule and vaporizer (Picarro) with two laboratory standards thatwere regularly calibrated against V-SMOW and standard lightantarctic precipitation (SLAP) (IAEA, Vienna, Austria). Mea-surement precision was < 0.2&. The concentration dependenceof the instrument was determined according to the procedure ofSchmidt et al. (2010; Supporting Information Fig. S1, TableS1). H2O mole fractions (ppmv) of the CRDS were calibratedbefore each measurement campaign in the laboratory using adew-point generator (Walz, Effeltrich, Germany). During fieldmeasurements the precision of the instrument was regularlycross-checked using an equally calibrated infrared gas analyzer(Li840; Li-Cor Biosciences, Lincoln, NE, USA). The precisionof the CRDS was < 100 ppmv throughout the measurementperiod; blank measurements of the chamber were obtained anddid not reveal differences connected with air passing the cham-ber (Fig. S2). Background air and sampling air were measuredalternately until stable values were reached and a 5-min intervalaverage was recorded for calculation of transpiration (E) and dE(see Fig. S2). The observed increase in air temperature in the

chamber above ambient was c. 2°C after 5 min and stable there-after. Fluxes of E as well as total leaf conductance (gtw) were cal-culated based on Von Caemmerer & Farquhar (1981). Gasexchange was not measured during the night, because transpira-tion ceases almost completely and calculations of fluxes are veryerror prone. Therefore nighttime values of transpiration andconductance needed for modeling nighttime dE and de weretaken from published data for a comparable Mediterranean oaksystem (Dawson et al., 2007). Isotope signatures of transpiredvapor were calculated by mass balance:

dE ¼ uoutwoutdout � u inw indinuoutwout � u inw in

¼ woutdout � w indinwout � win

� w inwoutðdout � dinÞwout � w in

Eqn 1

(u, the flow rate (mol(air) s�1); w, the mole fraction (mol(H2O)mol(air)�1); d, the isotope ratio of the incoming (‘in’) and outgo-ing (‘out’) air streams of the chamber.) Flow rates are measuredwith humid air so that conservation of dry air givesuin(1� win) = uout(1� wout), and it follows the second line ofEqn 1. This is equivalent to the equation given by Simonin et al.(2013), therein cited as Evans and von Caemmerer (pers. obs.).The second term in Eqn 1 corrects for the increased air flow in thechamber as a result of the addition of water by transpiration E.

Measurement of the isotopic composition of xylem and leafwater

Xylem samples of terminal branches (n = 4) were collected atnoon. Leaf samples (n = 2–4) were collected at 12 time-pointsthroughout the measurement campaign. Xylem and leaf waterwas extracted on a custom-built vacuum line by cryogenic distil-lation. Samples were heated at c. 95°C for 90 min under vacuumof 0.04–0.08 mbar and vapor was trapped in liquid N2-cooledwater traps. Samples were stored in sealed glass vials at 4°C untilanalysis. Water d18O was analyzed after headspace equilibration

Fig. 1 Schematic overview and pictures ofthe experimental set-up for measuring leaftranspiration, its isotopic composition andmicrometeorological parameters within thechamber in the field.

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for 24 h at 20°C on an Isoprime IRMS (Elementar, Hanau,Germany) coupled via open split to a lgas auto sampler (Elemen-tar). Within every batch of 44 samples, three replicates of threedifferent laboratory standards were analyzed for d18O calibrationversus V-SMOW. Laboratory standards were regularly calibratedagainst V-SMOW, SLAP, and Greenland icesheet precipitation(GISP) water standards (IAEA). Analytical precision was< 0.1&.

Calculation of isotopic signatures

The isotopic ratio of transpiration RE is linked to the isotopicratios of water at the evaporating sites Re and ambient vapour Ra(Craig & Gordon, 1965; Farquhar & Lloyd, 1993):

RE ¼ 1

akaþð1� hÞ ðRe � aþhRaÞ Eqn 2

(ak and a+, the kinetic and equilibrium fractionation factors(> 1), respectively; h, the relative humidity corrected for leaf tem-perature.) The Craig and Gordon steady state requires that theisotopic composition of vapor departing from the leaf must bethe same as the isotopic composition of incoming water, that is,RE = Rs, which leads to:

RC ¼ akaþð1� hÞRs þ aþhRa Eqn 3

(RC, the isotopic composition of leaf water at the evaporating sitein steady state.) Subtracting Eqn 3 from Eqn 2 gives:

Re � RC ¼ akaþð1� hÞðRE � RsÞ Eqn 4

which leads to a linear relationship in D-notation between theisotopic composition of evaporation RE or expressed as deviationfrom source values as DE and the deviation from steady state ofthe isotopic composition at the evaporating sites De:

DE ¼ De � DC

akaþð1� hÞ Eqn 5

(DC, the deviation of leaf water at the evaporating site in steadystate from source water.) 1� h in the denominator emphasizesthe fact that, if humidity approaches saturation, the pure waterflux E diminishes and in this case the isoflux term EDE, conse-quently DE approaches infinity; because

EDE ¼ gtwwi

akaþðDe � DCÞ Eqn 6

(gtw, the total conductance for water vapor from the stomatal cav-ity to the point of observation; wi, the humidity in the stomatalcavity, that is, vapor saturation at leaf temperature expressed asmole fraction (mol(H2O) mol(air)�1).) The flux from the vegeta-tion to the atmosphere in d-terms is not simply an isotope fluxEdE but rather the isoforcing IE (Cuntz et al., 2003; Lee et al.,2009):

IE ¼ E

waðdE � daÞ Eqn 7

(wa, the atmospheric humidity in mole fraction (mol(H2O) mol(air)�1).

The non-steady-state isotopic composition of leaf water Rl canbe written in an iterative form, if leaf water volume Vm (mol(H2O) m�2) is constant (Dongmann et al., 1974; Cuntz et al.,2007):

RIðt þ dt Þ ¼ f1RC þ ðRIðt Þ � f1RCÞe�gtwwi

akaþVm f2

dtEqn 8

where Rl at a time t + dt is calculated from Rl at an earlier time twith constant environmental conditions during the time step dt.The factors f1 and f2 depend on the water pool of interest. To cal-culate the isotopic composition of total mesophyll water Rm, thatis, Rl� Rm, the factors are f1 = f2 = fem, with

fem ¼ 1� e�}m

}mwith the Peclet number}m ¼ ELeff

CDEqn 9

where C = 106/18 = 55.6 9 103 mol m�3 is the molar water con-centration, D (m2 s�1) is the tracer diffusivity in liquid water andLeff (m) is the effective length of water movement in the leafmesophyll. To calculate the isotopic composition at the evaporat-ing sites Re, that is, Rl� Re, the factors are f1 = 1, f2 = fem. We fol-low Cuntz et al. (2007), who argued that f1 = f2 = 1 is sufficientin this case.

Notably, isotope signatures of leaf water at the evaporating sitein the non-steady state can be modeled independently fromobservations of RE and can then be used to predict RE and,inversely, observations of RE can be used to predict Rl at the evap-orating site.

Statistical analysis

Linear relationships were tested between measured and modeledestimates of dE, and between DE and (De� DC) or (De� DC)/(1� h) separately for days in spring, summer and autumn. Statis-tical analyses were carried out with STATISTICA 6.0 (StatSoft Inc.,Tulsa, OK, USA).

Results and Discussion

The laser spectrometer coupled to gas-exchange chambersenabled highly time-resolved estimates of dE in the field (Fig. 1).To evaluate how changes in environmental factors impact tempo-ral variations of dE on a diurnal time-scale, measurements wereconducted in three distinct climatic periods: (1) a moist, warmspring (11.4% mean soil moisture hs) with high transpirationrates (maximum 0.49 mmol m�2 s�1); (2) a dry, warm summer(4.5% hs), with reduced leaf conductance; and (3) a wet, coldautumn with maximum transpiration rate dropping to0.18 mmol m�2 s�1 (Fig. 2).

In the following we quantify the deviation of dE from xylemwater ds, validate a commonly used modeling approach and





analyze the relationship between the occurrence of isotopic non-steady state at the leaf level and the extent of depletion of dE.Finally, we quantify the isoforcing of isotopic non-steady-statetranspiration on atmospheric d18O.

Isotopic non-steady-state transpiration under naturalconditions and comparison with modeled dE

Observed plant transpirational isotope signatures (dE) neverreached xylem values (i.e. steady-state, ds) during the daytime onany day and varied between �26.1& and �6.2& (Fig. 3). Con-sequently, the deviation of dE from ds (DE) varied strongly withina day and was generally most negative in the morning. dE mainlyincreased throughout the day toward the end of the light period(Fig. 3). During the dark period, dE could not be measuredbecause of high methodological uncertainties for very low noctur-nal flux rates (E). However, modeled dE values (Eqns 2 and 8)indicate that the negative dE values during the day are counterbal-anced during the night (Fig. 3). The diurnal development of dEthus differs from the dome-shaped pattern of oxygen isotope sig-natures of leaf mesophyll water (dm), with the highest enrichmentcorresponding to peak temperature and low h in the afternoonand the lowest dm around sunrise (Fig. 4; see also Lai et al., 2006,2008; Yepez et al., 2007). The peak dm enrichment shifted tolater afternoon/evening hours with increasing day length andhigher temperatures. Notably, modeled and observed dm fit verywell (dm,obs = 0.96 9 dm,model + 0.33; R2 = 0.91; P < 0.001;Fig. 4).

In general, measured plant transpirational isotope signatures(dE) ranged between xylem water ds (�3.4 to �4.7&) and ambi-ent vapor da (�19.9 to �30.2&; Fig. 3). If da can be assumed to

be in equilibrium with precipitation during a rain event and frac-tionation associated with condensation is c. �10& at 20°C(Majoube, 1971), the da values observed correspond to isotopesignatures of precipitation dp of c. �10& (but note the shifts tovery negative da on 11 June and 18 and 20 September). Indeed,observed dp varied between �7 and �10& at this site (M. Dub-bert et al., unpublished). Somewhat higher values in xylem (ds)indicate that ds and hence soil water isotopes were not in fullequilibrium with dp, which is mainly caused by the relatively hotand dry environment leading to strong evaporative enrichmentand isotopic gradients within the top 20 cm of the soil profile of> 10& within a few days after a rain event (Dubbert et al.,2013). Moreover, atmospheric vapor is transported toward thesite from north to north-east (mainly continental air masses) andis thus not expected to be in isotopic equilibrium with localxylem water on each day.

Variations in dE can be caused by changes in abiotic or bioticconditions, that is, RH or stomatal conductance, and areexpected to persist until sufficient time has passed under constantenvironmental or physiological conditions to allow for dE toapproach ds. Most isotope models assume that the leaf consists ofa single water pool supplying the transpiration stream (bulk leafwater, Vm; Eqn 8; Dongmann et al., 1974; Farquhar & Cernu-sak, 2005) and leaf water residence time can be calculated as Vm

divided by the one-way flux of water out of the leaf (gtwwi; Eqn8). This leads to mean leaf water residence times of 4.6� 2.3,5.4� 1.9 and 3.6� 1.6 h in spring, summer and autumn,respectively, indicating that in our case the residence time of thewater supporting the transpirational flux is always much longerthan periods during which environmental or physiological condi-tions remain constant (Figs 2, 3; Simonin et al., 2013). However,

(a) (b) (c)

(d) (e) (f)

(g) (h) (i)Fig. 2 Environmental conditions andecophysiological parameters observed withthe chamber set-up forQuercus suber in latespring (a–c), late summer (d–f) and autumn(g–i; date format: day.month.year): relativehumidity corrected to leaf temperature(h (%); black lines), leaf temperature(°C; dashed gray lines), transpiration rate(E (mmol m�2 s�1); n = 3; mean� SE; greencircles), and total leaf conductance(gtw (mmol m�2 s�1); black circles).



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we can expect that leaf water residence times differ stronglybetween different plant functional groups (Kahmen et al., 2009;Simonin et al., 2013), for example, between crop plants anddrought-adapted species with high stomatal control such asQ. suber. Indeed, comparing modeled dE with theoretical leaf

water residence times obtained by increasing (by twofold) orreducing (to ½ and ¼) the observed leaf water residence time(Fig. 5), it becomes clear that the observed pattern of strongdepletion of dE relative to ds during the day cannot equally beexpected in ecosystems dominated by species with small leaf

(a) (b) (c)

(d) (e) (f)

(g) (h) (i)

Fig. 3 Measurements in spring (a–c), summer(d–f) and autumn (g–i; date format:day.month.year) forQuercus suber of theoxygen isotope signatures of transpiredvapor (dE; black circles; n = 3; meanvalues� SE) and modeled dE considering anon-steady state with varying observed leafwater volume, Vm and kinetic fractionationfactor for oxygen, ak between 1.018 and1.0265 (gray uncertainty band). The darkgray uncertainty band indicates modeled dEwith ak = 1.018 and varying leaf temperaturefrom observed values to +6°C. The solid redline is modeled dE with leaf water volume Vm

kept constant (mean of the observed range)and ak = 1.018. Gray squares show measuredoxygen isotope signatures of ambient air andwhite triangles are oxygen isotope signaturesof xylem (n = 3; mean values� SE). Pleasenote different scales for positive and negativevalues.

(a) (b)

Fig. 4 Diurnal cycles of modeled andmeasured oxygen isotope signatures of leafmesophyll water forQuercus suber (dm; a)and modeled versus measured dm (b) on 4June (circles; black line), 6 June (up-triangles;black dotted line), 10 June (squares; blackdashed line) and 11 November 2011 (down-triangles; gray line).





water residence times as a result of either low stomatal control orlow leaf water contents (see, for example, the differences in leafwater residence time and depletion of dE from isotopic steadystate between citrus spp. and tobacco (Nicotiana tabacum)observed by Simonin et al. (2013)).

Moreover, as a consequence of its influence on leaf water resi-dence time (see Eqn 2), the leaf water content (Vm) represents animportant model input parameter. However, measuring Vm ofleaves from remote field sites is not straightforward, and it istherefore often assumed to be stable (e.g. Yepez et al., 2003).Here, Vm of cork-oak leaves was measured once in each season(spring, summer and autumn) during the morning and after-noon, and ranged between 8.4 and 12.8 mol m�2. Comparingthe use of measured changes in Vm with the assumption of a fixedmean value (Fig. 3, upper border of gray areas and solid red lines,respectively) shows that either the measured range of Vm is notlarge enough to strongly influence dE predictions or modeling dEis not sensitive with regard to changes in Vm. Accordingly,Cernusak et al. (2002, 2003) found considerable variations in Vm

in lupin (Lupinus angustifolius) and blue gum (Eucalyptusglobulus) and still found no significant impact on the predictionof dE (see also Cuntz et al., 2007).

In general, we found a good agreement between measured andmodeled dE values, both when modeling the isotopic enrichmentof leaf water at the evaporating sites of the leaves under theassumption of non-steady-state transpiration (de), and also whencalculating the depletion of dE compared with isotopic signaturesof xylem water (ds) using the Craig and Gordon equation (Fig. 3;Eqns 2 and 8). However, changes in the kinetic fractionation fac-tor in the model, that is, from morning to evening or betweendays, strongly altered the predicted dE (Fig. 3d–f). Kinetic frac-tionation describes the effect of differences in molecular diffusiv-ity (D) between the major and the minor isotopologs (D/Di). Itcan be expressed as ak = (D/Di)

n, where n equals 0 under fullyturbulent conditions, 2/3 for diffusion through the leaf laminarboundary layer and 1 for fully molecular diffusion (Farquhar &Lloyd, 1993). Lee et al. (2009) suggested that apparent ak differsbetween scales (i.e. leaf versus canopy). At the leaf scale, akshould always be close to the molecular value (1.028; Merlivat,1978) as stomatal resistance is usually much greater than bound-ary layer resistance. By contrast, at the canopy scale ak can vary

much more substantially: Lee et al. (2009) found canopy ak val-ues between 1.012 and 1.031. In chamber applications, akshould likewise be a weighted average between boundary layer,stomatal and aerodynamic resistances as a result of the ventilationof the chamber. Boundary layer resistance in gas exchange cham-bers is often determined using heat plates or similar methods(Brenner & Jarvis, 1995). However, this determines the com-bined boundary and aerodynamic resistance and we argue thatthe boundary layer resistance determined from heat measure-ments cannot be used directly for weighting boundary layer frac-tionation in total ak. Boundary layer and aerodynamic resistancesdepend on wind speed, and thus, using the formulations of thetwo resistances at the canopy scale and with wind speeds of 1–2.5 m s�1 in the chamber (i.e. the range of ventilation within thechamber resulting from the orientation of the van relative to theleaves), ak was estimated to range between 1.018 and 1.0265.Notably, overall very good fits between measured and modeleddE and dm values were found with ak = 1.018 (dE,obs = 0.829 dE,model� 2.9; R2 = 0.68; P < 0.001; Fig. 3), although our resultssuggest that ak was larger in summer (Fig. 3d–f).

Another critical issue is the correct estimation of leaf tempera-ture. Temperature measurements were obtained from the surfaceof a single leaf in this study, but the increase in leaf temperatureabove air temperature can be inhomogeneous in branch bags, inparticular at high radiation, as leaves may shade each other (Mott& Peak, 2011). Variations in temperature influence modeled dEindirectly as they are used to calculate the equilibrium fraction-ation factor and to normalize h to leaf temperature values. There-fore, we tested the sensitivity of modeled dE to temperature byassuming a maximum deviation from observed leaf temperatureduring the daytime of 6°C (without incoming radiation duringthe night, temperatures should be homogeneous). Clearly, varia-tions in temperature can have an influence on modeled dE in cer-tain situations: a strong influence of temperature changes onmodeled dE could be observed during wet conditions in autumnin the early morning (Fig. 3, dark gray areas). During all otherdays, modeled dE was, however, not very sensitive to temperatureand the uncertainty does not compromise our findings regardingthe strong deviation of dE from isotopic steady state. Anotheraspect is the increase in air temperature inside the closed cham-ber, which was comparatively small here (Pape et al., 2009; on

(a) (b) (c)

Fig. 5 Modeled oxygen isotope signatures oftranspiration and observed oxygen isotopesignatures of the xylem ofQuercus suber

(gray solid line; n = 3; mean values) on 4 June(a), 18 September (b) and 11 November (c;date format: day.month.year). Red linesindicate modeled dE with the observed leafwater (lw) residence time (see Fig. 2), blackdotted and solid lines are dE with ½ and ¼ ofthe observed leaf water residence time,respectively, and black dashed lines are dEwith twice the observed leaf water residencetime.



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average 2°C). We did not measure the difference between the leafsurface temperatures of leaves inside and outside the chamber,but could not detect an increase in leaf temperature withinapprox. 10 min while the chamber was closed. Thus, the increasein temperature resulting from the chamber application could beassumed to have little impact on measured dE.

Relationship between De� DC and DE and impact on atmo-spheric vapor

Deviations from isotopic steady state at the leaf level, De� DC,and those of transpired vapor, DE, have not been considered sepa-rately in the past. However, transpiration (E) is a two-way flux,with E/(1� h) of water vapor diffusing out of the stomata and Eh/(1� h) of vapor diffusing into the leaf (Farquhar & Cernusak,2005), and likewise the isotopic composition of transpiration alsohas two parts. Denoting DE as in Eqn 5 reveals that DE is not sim-ply a mirror of De� DC but that the non-steady-state effect of leafwater at the evaporating sites is amplified by the factor 1/(1� h)for DE. The deviation of the leaf water isotopic composition at theevaporating sites from isotopic steady state (De� DC) was wellcorrelated with DE in autumn (and to a lesser degree in spring)when h was high (Fig. 6a,c) and thus the denominator in Eqn 4 issmall. However, during spring and also autumn, the non-steady-state effect of leaf water at the evaporating sites is amplified by upto 15& for DE. During dry and hot days in summer, no correla-tion between De� DC and DE could be found at all, although thevariability of De� DC was not small (between �4.1 and �8.8&;Fig. 6b). By contrast, (De� DC)/(1� h) was well correlated withDE and near to the 1 : 1 line also during summer (Fig. 6d–f).These results suggest that dE can strongly deviate from ds, evenwhen De� DC is small (Fig. 6). To date, the relationship betweenthe non-steady-state effects of leaf water and of transpired vapor

has gained little attention. However, comparing the De� DC andDE obtained here with those obtained in previous studies seems tosupport our findings (e.g. Lai et al., 2006; Yepez et al., 2007).Notably, the deviations of observed versus modeled DE from the1 : 1 line are not caused by the exclusion of the term a+ak, whichhas a very small overall effect on DE even in summer where diurnaltemperature fluctuations were high (Fig. 6d–f).

Oxygen isotope signatures of transpiration are used in applica-tions differing in spatial (plant to global) and temporal (minuteto annual) scales and it is thus crucial to assess where large errorscan be expected by assuming steady-state transpiration at largerscales. Accordingly, isoforcing of transpiration on the atmosphere(IE; Lee et al., 2009) was estimated assuming transpiration to bein steady state versus non-steady state (Fig. 7). Notably, isoforc-ing of the transpirational flux on atmospheric vapor is mostlypositive here, as, despite its depletion relative to xylem values, dEis enriched relative to ambient vapor. IE was large during daytimein spring and summer (up to 1.05 mol m�2 s�1&), when fluxeswere high. Looking at daytime values only, IE assuming steady-state transpiration was significantly higher than that assumingnon-steady-state dE on all days during spring and summer butnot during autumn, when the transpiration flux was small(Figs 2,7g–i). This implies that assuming plant transpiration tobe in a steady state can have a large impact for applications thatassess relatively short time intervals (e.g. partitioning studies:Williams et al., 2004; Yakir & Sternberg, 2000; Yepez et al.,2003; Zhang et al., 2011; Hu et al., 2014). Dubbert et al. (2013)found in a Mediterranean grassland community that assuming Eto be in isotopic steady state can lead to offsets of up to 70% inthe estimation of the fraction of transpiration in total evapotrans-piration. Moreover, on larger spatial scales, disregarding diurnalvariation may still be affected if sampling only takes place duringdaytime, for example, satellite-based water isotope assessments

(a) (b) (c)

(d) (e) (f)

Fig. 6 Spring (a, d), summer (b, e) andautumn (c, f) deviations inQuercus suber ofthe oxygen isotope signature of transpiredvapor from that of xylem water (DE (&))against the deviation of leaf water isotopiccomposition at the evaporating sites fromisotopic steady state (De�DC (&); a–c), andagainst De�DC (e, leaf water at theevaporating sites in the non-steady state; C,leaf water at steady state; h, relativehumidity) amplified by 1/(1� h) (d–f). Theblack lines indicate significant linearregressions and dashed black lines the 95%confident bands. The 1 : 1 line is indicated inblack; coefficients of determination R² andsignificance level P are shown inside theplots.





looking at the atmospheric boundary layer (Lee et al., 2012).Consequently, recent studies investigated the influence of (isoto-pic non-steady-state) E on canopy–air exchange of oxygen iso-topes of H2O and CO2 (Xiao et al., 2010; Berkelhammer et al.,2013) or on water vapor deuterium excess (Welp et al., 2012)using continuous observations of da and including a non-steady-state formulation for leaf water enrichment in a land surfacemodel (SiLSM). Interestingly, in soybean (Glycine max), Xiaoet al. (2010) found that the isotopic non-steady state of transpira-tion has a greater impact on leaf water enrichment than the P�ecleteffect. However, Xiao et al. (2012) also suggested that the isoto-pic steady-state assumption determines plant C18O16O exchangequite well during the daytime.

Notably, modeling dE with a broad range of leaf water resi-dence times (Fig. 5) indicates that the effect of consideringtranspiration to be in an isotopic steady state will be stronglydependent on plant functional type. Therefore, a survey of spe-cies from distinct functional groups with different leaf morpho-logical and structural traits, leaf water residence times andtranspiration rates may enable a thorough characterization of therole of non-steady-state transpiration. It would be particularlyinteresting to investigate how different plant functional groupsdiffer in the diurnal development of dE with regard to environ-mental stresses such as drought (Lai et al., 2008; Simonin et al.,2013).

In the long run, deviations from isotopic steady state must becompensated for, as accumulation of heavy water can only occurover short time-scales, that is, hours or in extreme cases days.Consequently, for whole-day mean IE, the deviation during thedaytime was compensated during the night by larger IE whentranspiration was considered to be in an isotopic non-steady state.Only on two out of nine measurement days was 24-h mean iso-forcing significantly smaller when transpiration was considered tobe in a non-steady state compared with a steady state (Fig. 7). Itwould thus be interesting to determine the maximum timeperiod for which IE can deviate from the steady-state prediction.

In conclusion, we found strong deviations from isotopic steadystate in plant transpiration during the daytime, which should beconsidered carefully when using dE to trace the impact of fluxesof the water or carbon cycle.

Acknowledgements

Funding was provided by the DFG (WATERFLUX Project:WE 2681/6-1; CU 173/2-1) and DAAD. We thank the Herdadeda Machoqueira and Joao S. Pereira for the use of the field site aswell as logistical support and Alexandra Correia and Babsi Teich-ner for help in the field and laboratory. Finally, we thank threeanonymous reviewers for their helpful comments on this manu-script.

(a) (b) (c)

(d) (e) (f)

(g) (h) (i) Fig. 7 Isoforcing of transpiration ofQuercus

suber on the atmosphere (IE; mol m�2 s�1&)for each measurement day during June (a–c),September (d–f) and November (g–i)assuming isotopic steady state (ss; black solidlines) or non-steady state (nss; red dashedlines). Nighttime transpiration rates andconductances were taken from Dawson et al.

(2007). 24-h means� SE are given for eachmeasurement day (date format:day.month.year); errors were calculated frombootstrap re-sampling.



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Supporting Information

Additional supporting information may be found in the onlineversion of this article.

Fig. S1 Concentration dependences of the cavity ring-down spec-trometer at six different oxygen and deuterium isotopicsignatures.

Fig. S2 H2O (ppm), d18O and dD (&) observed with the cavityring-down spectrometer of ambient air and the blank branchchamber and of ambient air and the branch chamber with abranch enclosed.

Table S1 Equations, R² and P values for the concentration depen-dences of the cavity ring-down spectrometer at six different oxy-gen and deuterium isotopic signatures as shown in Fig. S1

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Oxygen isotope signatures of transpired water vapor: the role of isotopic non-steady-state transpiration under natural conditions