Leaf-scale quantification of the effect of photosynthetic gas exchange on Δ17O of atmospheric CO2
- 1Institute for Marine and Atmospheric research Utrecht (IMAU), Utrecht University, Utrecht, the Netherlands
- 2Institute of Environmental Biology, Utrecht University, Utrecht, the Netherlands
- 3Department of Meteorology and Air Quality, Wageningen University, Wageningen, the Netherlands
- 4Centre for Isotope Research, University of Groningen, Groningen, the Netherlands
Correspondence: Getachew Agmuas Adnew (firstname.lastname@example.org)
Understanding the processes that affect the triple oxygen isotope composition of atmospheric CO2 during gas exchange can help constrain the interaction and fluxes between the atmosphere and the biosphere. We conducted leaf cuvette experiments under controlled conditions using three plant species. The experiments were conducted at two different light intensities and using CO2 with different Δ17O. We directly quantify the effect of photosynthesis on Δ17O of atmospheric CO2 for the first time. Our results demonstrate the established theory for δ18O is applicable to Δ17O(CO2) at leaf level, and we confirm that the following two key factors determine the effect of photosynthetic gas exchange on the Δ17O of atmospheric CO2. The relative difference between Δ17O of the CO2 entering the leaf and the CO2 in equilibrium with leaf water and the back-diffusion flux of CO2 from the leaf to the atmosphere, which can be quantified by the cm∕ca ratio, where ca is the CO2 mole fraction in the surrounding air and cm is the one at the site of oxygen isotope exchange between CO2 and H2O. At low cm∕ca ratios the discrimination is governed mainly by diffusion into the leaf, and at high cm∕ca ratios it is governed by back-diffusion of CO2 that has equilibrated with the leaf water. Plants with a higher cm∕ca ratio modify the Δ17O of atmospheric CO2 more strongly than plants with a lower cm∕ca ratio. Based on the leaf cuvette experiments, the global value for discrimination against Δ17O of atmospheric CO2 during photosynthetic gas exchange is estimated to be ‰ using cm∕ca values of 0.3 and 0.7 for C4 and C3 plants, respectively. The main uncertainties in this global estimate arise from variation in cm∕ca ratios among plants and growth conditions.
Stable isotope measurements of CO2 provide important information about the magnitude of the CO2 fluxes between atmosphere and biosphere, which are the largest components of the global carbon cycle (Farquhar et al., 1989, 1993; Ciais et al., 1997a, b; Flanagan and Ehleringer, 1998; Yakir and Sternberg, 2000; Gillon and Yakir, 2001; Cuntz et al., 2003a, b). A better understanding of the terrestrial carbon cycle is essential for predicting future climate and atmospheric CO2 mole fractions (Booth et al., 2012). Gross primary productivity (GPP), the total carbon dioxide uptake by vegetation during photosynthesis, can only be determined indirectly and remains poorly constrained (Cuntz, 2011; Welp et al., 2011). For example, Beer et al. (2010) estimated global GPP to be 102–135 PgC yr−1 (85 % confidence interval, CI) using machine learning techniques by extrapolating from a database of eddy covariance measurements of CO2. This estimate has since then been widely used as target for terrestrial vegetation models (Sitch et al., 2015) and replicated based on cross-consistency checks with atmospheric inversions, sun-induced fluorescence (SIF), and global vegetation models (Jung et al., 2020). As an alternative, Welp et al. (2011) estimated global GPP to be 150–175 PgC yr−1 using variations in δ18O of atmospheric CO2 after the 1997/98 El Niño event; see Eq. (1) for definition of the δ value.
The concept behind the latter study was that atmospheric CO2 exchanges oxygen isotopes with leaf and soil water, and this isotope exchange mostly determines the observed variations in δ18O of CO2 (Francey and Tans, 1987; Yakir, 1998). Following the 97/98 El Niño–Southern Oscillation (ENSO) event, the anomalous δ18O signature imposed on tropical leaf and soil waters was transferred to atmospheric CO2, before slowly disappearing as a function of the lifetime of atmospheric CO2. This in turn is governed by the land vegetation uptake of CO2 during photosynthesis, as well as soil invasion of CO2 (Miller et al., 1999; Wingate et al., 2009). For the photosynthesis term, the equilibration of CO2 with water is an uncertain parameter in this calculation, partly because the δ18O of water at the site of isotope exchange in the leaf is not well defined. Importantly, a significant δ18O variation can occur in leaves due to the preferential evaporation of relative to (Gan et al., 2002, 2003; Farquhar and Gan, 2003; Cernusak et al., 2016), which induces a considerable uncertainty in estimating δ18O of CO2. Similar considerations for the transfer of the δ18O signature of precipitation into the soils, and then up through the roots, stems, and leaves makes 18O of CO2 a challenging measurement to interpret (Peylin et al., 1999; Cuntz et al., 2003a, b).
Classical isotope theory posits that oxygen isotope distributions are modified in a mass-dependent way. This means that the 17O∕16O ratio changes by approximately half of the corresponding change in 18O∕16O (Eq. 2), and it applies to the processes involved in gas exchange between atmosphere and plants. However, in 1983 Thiemens and co-workers (Heidenreich and Thiemens, 1983, 1986; Thiemens and Heidenreich, 1983) reported a deviation from mass-dependent isotope fractionation in ozone (O3) formation called mass-independent isotope fractionation (Δ17O, Eq. 3). In the stratosphere, the Δ17O of O3 is transferred to CO2 via isotope exchange of CO2 with O(1D) produced from O3 photolysis (Yung et al., 1991, 1997; Shaheen et al., 2007), which results in a large amount of Δ17O in stratospheric CO2 (Thiemens et al., 1991, 1995; Lyons, 2001; Lämmerzahl et al., 2002; Thiemens, 2006; Kawagucci et al., 2008; Wiegel et al., 2013).
Once Δ17O has been created in stratospheric CO2, the only process that modify its signal is isotope exchange with leaf water, soil water and ocean water at the Earth's surface, after CO2 has reentered the troposphere (Boering, 2004; Thiemens et al., 2014; Liang and Mahata, 2015; Hofmann et al., 2017). Isotope exchange with leaf water is more efficient relative to ocean water due to the presence of the enzyme carbonic anhydrase (CA), which effectively catalyzes the conversion of CO2 and H2O to and H+ and vice versa (Francey and Tans, 1987; Friedli et al., 1987; Badger and Price, 1994; Gillon and Yakir, 2001). The isotope exchange in the atmosphere is negligible due to lower liquid water content, lower residence time, and the absence of carbonic anhydrase (Mills and Urey, 1940; Miller et al., 1971; Johnson, 1982; Silverman, 1982; Francey and Tans, 1987).
Δ17O of CO2 has been suggested as an additional independent tracer for constraining global GPP (Hoag et al., 2005; Thiemens et al., 2013; Hofmann et al., 2017; Liang et al., 2017b; Koren et al., 2019) because the processes involved in plant–atmosphere gas exchange are all mass dependent. Therefore, Δ17O at the CO2−H2O exchange site in the leaf will vary much less than δ18O. Nevertheless, mass-dependent isotope fractionation processes with slightly different three-isotope fractionation slopes are involved, which have been precisely established in the past years. Figure 1 shows how the different processes affect Δ17O of the H2O and CO2 reservoirs involved. The triple isotope slope of oxygen in meteoric waters is taken as reference slope, λRef=0.528 (Meijer and Li, 1998; Barkan and Luz, 2007; Landais et al., 2008; Luz and Barkan, 2010; Uemura et al., 2010), and we assume that soil water is similar to meteoric water. Due to transpiration and diffusion in the leaf, Δ17O of leaf water gets modified following a humidity-dependent three-isotope slope (Landais et al., 2006). Exchange of oxygen isotopes between leaf water and CO2 follows (Barkan and Luz, 2012), which determines the Δ17O of CO2 inside the leaf at the CO2−H2O exchange site. Finally, the Δ17O of the CO2 is modified when CO2 diffuses into and out of the leaf with λdiff=0.509 (Young et al., 2002).
In the first box model study of Hoag et al. (2005), the small deviations in Δ17O of CO2 due to differences in three-isotope slopes were neglected and exchange with water was assumed to reset Δ17O to 0. Hofmann et al. (2017) included the different isotope effects shown in Fig. 1 in their box model. Koren et al. (2019) incorporated all the physicochemical processes affecting Δ17O of CO2 in a 3D atmospheric model and investigated the spatiotemporal variability of Δ17O and its use as tracer for GPP. Using these and other similar models, numerous measurements of Δ17O in atmospheric CO2 from different locations have been performed and used to estimate GPP (Liang et al., 2006; Barkan and Luz, 2012; Thiemens et al., 2014; Liang and Mahata, 2015; Laskar et al., 2016; Hofmann et al., 2017). The three-isotope slopes of the processes involved in the gas exchange (Fig. 1) have been precisely determined in idealized experiments. In the advanced models mentioned above it is assumed that when all the pieces are put together they result in a realistic overall modification of Δ17O of CO2 in the atmosphere surrounding the leaf. However, this has not been confirmed by measurements previously.
In this study we report the effect of photosynthesis on Δ17O of CO2 in the surrounding air at the leaf scale. We measured Δ17O of CO2 entering and leaving a leaf cuvette to calculate the isotopic fractionation associated with photosynthesis for three species that are representative for three different biomes. The fast-growing annual herbaceous C3 species Helianthus annuus (sunflower) has a high photosynthetic capacity (An) and high stomatal conductance (gs) and is representative for temperate and tropical crops (Fredeen et al., 1991). The slower-growing perennial evergreen C3 species Hedera hibernica (ivy) is representative of forests and other woody vegetation and stress-subjected habitats (Pons et al., 2009). The fast-growing, agronomically important crop Zea mays (maize) is an herbaceous annual C4 species with a high An and a low gs, typical for savanna type vegetation (van der Weijde et al., 2013). The mole fraction of CO2 at the CO2−H2O exchange site (cm) is an important parameter to determine the effect of photosynthesis on Δ17O of CO2. In C3 plants, the CO2−H2O exchange can occur anywhere between the plasma membrane and the chloroplast since the catalyzing enzyme CA has been found in the chloroplast, cytosol, mitochondria, and plasma membrane (Fabre et al., 2007; DiMario et al., 2016). For C4 plants, CA is mainly found in the cytosol, and the CO2−H2O exchange occurs there (Badger and Price, 1994). In our experiments, sunflower and ivy are used to cover the wide cm∕ca ratio range among C3 plants and maize represents the cm∕ca ratio for the C4 plants. Using our results from the leaf-scale experiments, we estimated the effect of terrestrial vegetation on Δ17O of CO2 in the global atmosphere.
2.1 Notation and definition of δ values
Isotopic composition is expressed as the deviation of the heavy-to-light isotope ratio in a sample relative to a reference ratio and is denoted as δ, expressed in per mill (‰). In the case of oxygen isotopes, the isotope ratios are and and the reference material is Vienna Standard Mean Ocean Water (VSMOW):
For most processes, isotope fractionation depends on mass, and therefore the fractionation against 17O is approximately half of the fractionation against 18O (Eq. 3).
The mass-dependent isotope fractionation factor λ ranges from 0.5 to 0.5305 for different molecules and processes (Matsuhisa et al., 1978; Thiemens, 1999; Young et al., 2002; Cao and Liu, 2011). Δ17O is used to quantify the degree of deviation from Eq. (2) (see Eq. 3). Note that Δ17O changes not only by mass-independent isotope fractionation processes but also by mass-dependent isotope fractionation processes with a different λ value from the one used in the definition of Δ17O (Barkan and Luz, 2005, 2011; Landais et al., 2006, 2008; Luz and Barkan, 2010; Pack and Herwartz, 2014).
The choice of λ is in principle arbitrary, and in this study we use λ=0.528, which was established for meteoric waters (Meijer and Li, 1998; Landais et al., 2008; Brand et al., 2010; Luz and Barkan, 2010; Barkan and Luz, 2012; Sharp et al., 2018). Equation (3) can be linearized to (Miller, 2002), but this approximation causes an error that increases with δ18O (Miller, 2002; Bao et al., 2016).
2.2 Discrimination against Δ17O of CO2
The overall isotope fractionation associated with the photosynthesis of CO2 is commonly quantified using the term discrimination, as described in Farquhar and Richards (1984), Farquhar et al. (1989), and Farquhar and Lloyd (1993). We use the symbol ΔA for discrimination due to assimilation in this paper since the commonly used Δ is already used for the definition of Δ17O (see Eq. 3). ΔA quantifies the enrichment or depletion of carbon and oxygen isotopes of CO2 in the surrounding atmosphere relative to the CO2 that is assimilated (Farquhar and Richards, 1984). It can be calculated from the isotopic composition of the CO2 entering and leaving the leaf cuvette (Evans et al., 1986; Gillon and Yakir, 2000a; Barbour et al., 2016) as follows:
where the indices e, a and A refer to CO2 entering and leaving the cuvette and being assimilated, respectively. , where ce and ca are the mole fractions of CO2 entering and leaving the cuvette. For quantifying the effect of photosynthesis on Δ17O in our experiments, the ΔAΔ17O is calculated from and using the three-isotope slope λRL=0.528, similar to Eq. (3). In previous studies slightly different formulations have been used to define the effect of photosynthesis on Δ17O, and a comparison of the different definitions is provided in the Supplement (Eqs. S37–S40).
It is important to note that when the logarithmic definition of Δ17O or ΔAΔ17O is used, values are not additive (Kaiser et al., 2004). In linear calculations, the error gets larger when the relative difference in δ18O between the two CO2 gases increases regardless of the Δ17O of the individual CO2 gases (Fig. S1 in the Supplement). Therefore, ΔAΔ17O values have to be calculated from the individual and values and not by linear combinations of the Δ17O of air entering and leaving a plant chamber.
3.1 Plant material and growth conditions
Sunflower (Helianthus annuus L. cv “sunny”) was grown from seeds in 0.6 L pots with potting soil (Primasta, the Netherlands) for about 4 weeks. All leaves appearing above the first leaf pair were removed to avoid shading. Established juvenile ivy (Hedera hibernica L.) plants were pruned and planted in 6 L pots for 6 weeks. Ivy leaves that had developed and matured were used for the experiments. Maize (Z. mays L. cv “saccharate”) was grown from seed in 1.6 L pots for at least 7 weeks. For maize, the fourth or higher leaf number was used for the experiments when it was mature. A section of the leaf at about one-third from the tip was inserted into the leaf cuvette. They were placed on a sub-irrigation system that provided water during the growth period in a controlled-environment growth chamber, with an air temperature of 20 ∘C, relative humidity of 70 %, and CO2 mole fraction of about 400 ppm. The photosynthetic photon flux density (PPFD) was about 300 during a daily photoperiod of 16 h measured with a PPFD meter (Li-Cor LI-250A, Li-Cor Inc, NE, USA).
3.2 Gas exchange experiments
Gas exchange experiments were performed in an open system where a controlled flow of air enters and leaves the leaf cuvette, similar to the setup used by Pons and Welschen (2002). A schematic for the gas exchange experimental setup is shown in Fig. 2. The leaf cuvette had dimensions of cm3 () and the top part of the cuvette was transparent. The temperature of the leaf was measured with a K type thermocouple. The leaf chamber temperature was controlled by a temperature-controlled water bath kept at 20 ∘C (Tamson TLC 3, The Netherlands). A halogen lamp (Pradovit 253, Ernst Leitz Wetzlar GmbH, Germany) in a slide projector was used as a light source. Infrared was excluded by reflection from a cold mirror. The light intensity was varied with spectrally neutral filters (Pradovit 253, Ernst Leitz Wetzlar GmbH, Germany).
The CO2 mole fraction of the incoming and outgoing air was measured with an infrared gas analyzer (IRGA, model LI-6262, Li-Cor Inc., NE, USA). The isotopic composition and mole fraction of the incoming and outgoing water vapor were measured with a triple water vapor isotope analyzer (WVIA, model 911-0034, Los Gatos Research, USA). Compressed air (ambient outside air without drying) was passed through soda lime to scrub the CO2. The CO2-free air could be humidified depending on the experiment conditions (see Fig. 2). The humidity of the inlet air was monitored continuously with a dew point meter (HYGRO-M1, General Eastern, Watertown, MA, USA). Pure CO2 (either normal CO2 or isotopically enriched CO2) was mixed with the incoming air to produce a CO2 mole fraction of 500 ppm. The isotopically enriched CO2 was prepared by photochemical isotope exchange between CO2 and O2 under UV irradiation (Adnew et al., 2019).
An attached leaf or part of it was inserted into the cuvette, the composition of the inlet air was measured, and both IRGA and WVIA were switched to measure the outlet air. Based on the CO2 mole fraction of the outgoing air the flow rate of the incoming air to the cuvette was adjusted to establish a drawdown of 100 ppm CO2 due to photosynthesis in the plant chamber. The water vapor content entering the cuvette was adjusted depending on the transpiration rate relative to CO2 uptake to avoid condensation (Fig. 2). The outgoing air was measured continuously until a steady state was reached for CO2 and H2O mole fractions and δD and δ18O of the water vapor. After a steady state was established, the air was directed to the sampling flask while the IRGA and WVIA were switched back to measure the inlet air. The air passed through a Mg(ClO4)2 dryer before entering the sampling flask.
After sampling, the leaf area inside the cuvette was measured with a LI-3100C area meter (Li-Cor Inc., USA). Immediately afterward, the leaf was placed in a leak-tight 9 mL glass vial and kept in a freezer at −20 ∘C until leaf water extraction.
3.3 Calibration of the water vapor isotope analyzer (WVIA) and leaf water analysis
The WVIA was calibrated using five water standards provided by IAEA (Wassenaar et al., 2018) for both δ18O and δD (Fig. S2). We did not calibrate the WVIA for δ17O, so the δ17O data are not used in the quantitative evaluation. The isotopic composition of the water standards ranged from −50.93 ‰ to 3.64 ‰ and −396.98 ‰ to 25.44 ‰ for δ18O and δD, respectively. The detailed characterization and calibration of the WVIA is provided in the Supplement (Figs. S2 to S4).
Leaf water was extracted by cryogenic vacuum distillation for 4 h at 60 ∘C following a well-established procedure as shown in Fig. S5 (Wang and Yakir, 2000; Landais et al., 2006; West et al., 2006). Details are provided in the Supplement. The δ17O and δ18O of leaf water were determined at the Laboratoire des Sciences du Climat et de l'Environnement laboratory using a fluorination technique as described in Barkan and Luz (2005) and Landais et al. (2006, 2008).
3.4 Carbon dioxide extraction and isotope analysis
CO2 was extracted from the air samples in a system made from electropolished stainless steel (Fig. S6). Our system used four commercial traps (MassTech, Bremen, Germany). The first two traps were operated at dry ice temperature (−78 ∘C) to remove moisture and some organics. The other two traps were operated at liquid nitrogen temperature (−196 ∘C) to trap CO2. The flow rate during extraction was 55 mL min−1 controlled by a mass flow controller (Brooks Instruments, the Netherlands). The reproducibility of the extraction system was 0.030 ‰ for δ18O and 0.007 ‰ for δ13C determined on 14 extractions (1σ standard deviation, Table S1 in the Supplement).
The Δ17O of CO2 was determined using the CO2−O2 exchange method (Mahata et al., 2013; Barkan et al., 2015; Adnew et al., 2019). The CO2−O2 exchange system used at Utrecht University is described in Adnew et al. (2019). In short, equal amounts of CO2 and O2 were mixed in a quartz reactor containing a platinum sponge catalyst and heated at 750 ∘C for 2 h. After isotope equilibration, the CO2 was trapped at liquid nitrogen temperature, while the O2 was collected with 1 pellet of a 5Å molecular sieve (1.6 mm, Sigma Aldrich, USA) at liquid nitrogen temperature. The isotopic composition of the isotopically equilibrated O2 was measured with a DeltaPlusXL isotope ratio mass spectrometer in dual-inlet mode with reference to a pure O2 calibration gas that has been assigned values of δ17O=9.254 ‰ and δ18O=18.542 ‰ by Eugeni Barkan at the Hebrew University of Jerusalem. The reproducibility of the Δ17O measurement was better than 0.01 ‰ (Table S1).
3.5 Leaf cuvette model
We used a simple leaf cuvette model to evaluate the dependence of ΔAΔ17O on key parameters. In this model, the leaf is partitioned into three different compartments: the intercellular air space, the mesophyll cell, and the chloroplast. In the leaf cuvette model, we used a 100 ppm down-draw of CO2, similar to the leaf exchange experiments, i.e., the CO2 mole fraction decreases from 500 ppm in the entering air (ce) to 400 ppm in the outgoing air (co), which is identical to the air surrounding the leaf (ca) as a result of thorough mixing in the cuvette. The assimilation rate is set to 20.0 . The leaf area and flow rate of air are set to 30 cm2 and 0.7 L min−1, respectively. The isotope composition of leaf water at the site where the H2O−CO2 exchange occurs is δ17O=5.39 ‰ and δ18O=10.648 ‰, which is the mean of the measured δ17O and δ18O values of bulk leaf water in our experiments. The leaf water temperature is set to 22 ∘C (similar to the experiment). In the model, the δ18O of the CO2 entering the cuvette is set to 30.47 ‰ for all the simulations, as in the normal CO2 experiments, but the assigned Δ17O values range from −0.5 ‰ to 0.5 ‰, which encompasses both the stratospheric intrusion and combustion components. The corresponding δ17O of the CO2 entering the cuvette is calculated from the assigned δ18O value (30.47 ‰) and Δ17O values (−0.5 ‰ to 0.5 ‰). For the calculations with this model, we assumed an infinite boundary layer conductance. The leaf cuvette model is illustrated in the Supplement (Fig. S7), and the detailed code and description is available at https://git.wur.nl/leaf_model (last access: 23 March 2020, Koren et al., 2020).
4.1 Gas exchange parameters
Table 1 summarizes the isotopic composition and mole fraction of the CO2 used in this study for sunflower, ivy and maize. The Δ17O of CO2 used in this study varies from −0.215 ‰ to 0.44 ‰, while the δ18O value is close to 30 ‰ for all the experiments. For all the experiments, the mole fraction of CO2 entering the leaf (ca) is 400 ppm, whereas the mole fraction of the CO2 in the intercellular air space (ci), at the CO2−H2O exchange site (cm), and in the chloroplast (cc) varies depending on the assimilation rate and metabolism type of the plants. Estimating the mesophyll conductance is described in the companion paper. A detailed description for estimating cm and cc is provided in the Supplement. A list of variables and parameters used in this study are summarized in Table 2.
4.2 Discrimination against 18O of CO2
Figure 3a shows discrimination against 18O associated with photosynthesis () for sunflower, ivy, and maize as a function of the cm∕ca ratio. varies with cm∕ca, as found in previous studies (Gillon and Yakir, 2000a; Barbour et al., 2016) . For sunflower, we observe values between 29 ‰ and 64 ‰ for cm∕ca between 0.54 and 0.86. Ivy shows relatively little variation in around a mean of 22 ‰ for cm∕ca between 0.48 and 0.58. For maize, is lower than for the C3 plants measured in this study, with values between 10 ‰ and 20 ‰ for cm∕ca between 0.15 and 0.37.
For sunflower, changing the irradiance from 300 (low light, hereafter LL) to 1200 (high light, hereafter HL) leads to a clear decrease in (average 22 ‰). For maize, the change is only 4.4 ‰ on average. For ivy, changing the light intensity does not significantly change the observed . The solid lines in Fig. 3a show the results of leaf cuvette model calculations, where the dependence of on cm∕ca is explored for a set of calculations with otherwise fixed parameters. The model agrees well with the experimental results, except for ivy, where the model overestimates the discrimination.
4.3 Discrimination against Δ17O of CO2
The discrimination of photosynthesis against Δ17O of CO2 (ΔAΔ17O) is shown in Fig. 3b. ΔAΔ17O is negative for all experiments, it depends strongly on the cm∕ca ratio, and |ΔAΔ17O| increases with cm∕ca ratio. For instance, for Δ17O of CO2 entering the cuvette of −0.215 ‰, ΔAΔ17O is −0.25 ‰ for maize with cm∕ca ratio of 0.3, −0.3 ‰ for ivy with cm∕ca ratio of 0.5 ‰, and −0.5 ‰ for sunflower with cm∕ca ratio of 0.7 (Fig. 3b). For sunflower and ivy, ΔAΔ17O is also strongly dependent on the Δ17O of CO2 supplied to the cuvette, whereas no significant dependence is found for maize. For an increase in Δ17O of CO2 entering the cuvette from −0.215 ‰ to 0.435 ‰, ΔAΔ17O increases from −0.3 ‰ to −0.9 ‰ at cm∕ca ratio of 0.5 for ivy. For sunflower, an increases Δ17O of CO2 entering the cuvette from −0.215 ‰ to 0.31 ‰ increases ΔAΔ17O from −0.8 ‰ to −1.7 ‰ at cm∕ca ratio of 0.8. The leaf cuvette model results illustrate the shape of the dependence on the cm∕ca ratio and agree well with the experiments. For the leaf cuvette model, the Δ17O value of the water is assigned a constant value of −0.122 ‰ (average Δ17O value for the bulk leaf water).
Figure 4b shows the same values of ΔAΔ17O as a function of the difference between Δ17O of CO2 entering the leaf and the calculated Δ17O of leaf water at the evaporation site where CO2−H2O exchange takes place (Δ17Oa−Δ17Owes) for different cm∕ca ratios. The leaf cuvette model results (solid lines in Fig. 4b) suggest a linear dependence between ΔAΔ17O and (Δ17Oa−Δ17Owes). The experimental results agree with the hypothesis that ΔAΔ17O is linearly dependent on Δ17Oa−Δ17Owes at a certain cm∕ca ratio. Figure 4a shows the corresponding relation where ΔAΔ17O is divided by Δ17Oa−Δ17Om. All the values follow the same relationship as a function of the cm∕ca ratio, which can be approximated quite well by an exponential function (Eq. 5). This function quantifies the dependence of ΔAΔ17O on cm∕ca and thus the effect of the diffusion of isotopically exchanged CO2 back to the atmosphere, which increases with increasing cm∕ca ratio.
Figure 5a and c show results from the leaf cuvette model that illustrates in more detail how Δ17Oe and Δ17Owes affect Δ17Oa and ΔAΔ17O and their dependence on cm∕ca. At lower cm∕ca, only a very small fraction of CO2 that has undergone isotopic equilibration in the mesophyll diffuses back to the atmosphere, and therefore Δ17Oa stays close to the incoming Δ17Oe, modified by the fractionation during CO2 diffusion through the stomata (Fig. 5a). Figure 5c confirms that at low cm∕ca, ΔAΔ17O approaches the fractionation constant expected for diffusion, −0.170 ‰. This diffusional fractionation is independent of the isotopic composition of the CO2 entering the leaf, and therefore at low cm∕ca, the ΔAΔ17O curves for the different values of the anomaly of the CO2 entering the leaf converge. For a high cm∕ca ratio, the back-diffusion flux of CO2 that has equilibrated with water becomes the dominant factor, and, in this case, the isotopic composition of the outgoing CO2 converges towards this isotope value, independent of the isotopic composition of the incoming CO2 (Fig. 5a). This can lead to a very wide range of values for the discrimination against Δ17O because now the effect on Δ17O of the ambient CO2 depends strongly on the difference in isotopic composition between incoming CO2 and CO2 in isotopic equilibrium with the leaf water.
In the model calculations shown in Fig. 5b and d, the isotopic composition of the water was changed from ‰ to 0.300 ‰, whereas all other parameters were kept the same. The value of Δ17Oe for which Δ17Oa does not depend on cm∕ca is shifted accordingly, again being similar to Δ17Om. At low converges to the same value as in Fig. 5c, confirming the role of diffusion into the stomata as discussed above.
Figure 6 shows how δ18O and Δ17O vary in key compartments of the leaf cuvette system that determine the oxygen isotope effects associated with photosynthesis, based on the previously established three-isotope slopes of the various processes (Fig. 1). The irrigation water has a Δ17O value of 0.017 ‰. The measured bulk leaf water is 6 ‰ to 16 ‰ enriched in 18O and its Δ17O value is lower by −0.075 ‰ to −0.200 ‰ (mean value −0.121 ‰) than the irrigation water, calculated using a three-isotope slope of θtrans=0.516 % at 80 % humidity (Landais et al., 2006). Δ17O of leaf water at the evaporation site, calculated from the transpired water, has slightly lower Δ17O, with values between −0.119 ‰ and −0.237 (average −0.184 ‰). Note that the bulk leaf water was not measured for all the experiments. For the experiments where the bulk leaf water is measured, Δ17O of leaf water at the evaporation site ranges from −0.160 ‰ to −0.231 ‰ with an average value of ‰. The calculated isotopic composition of water at the exchange site was thus similar but slightly lower in Δ17O than the values measured for bulk leaf water. CO2 exchanges with the water in the leaf with a well-established fractionation constant (see Eq. S17) and a three-isotope slope of (Barkan and Luz, 2012), leading to the lower Δ17O values of the equilibrated CO2. In our experiments, the Δ17O value of CO2 in equilibrium with leaf water is lower than the Δ17O value of CO2 entering the leaf. The Δ17O of the CO2 in the intercellular air space is a mixture between two end-members, the Δ17O of the CO2 entering the leaf and Δ17O of the CO2 in equilibrium with leaf water. This explains why the observed values of ΔAΔ17O are negative for the experiments performed in this study.
5.1 Discrimination against δ18O of CO2
The higher values for sunflower compared to maize and ivy (Fig. 3a) are mainly due to a higher back-diffusion flux (). The back-diffusion flux is higher for the C3 plants sunflower and ivy than for the C4 plant maize, a consequence of the lower stomatal conductance and higher assimilation rate of C4 plants (Gillon and Yakir, 2000a; Barbour et al., 2016). In C4 plants most of the CO2 entering the stomata is carboxylated by phosphoenolpyruvate carboxylase (PEPC), resulting in a lower CO2 mixing ratio in the mesophyll, which results in a lower back-diffusion flux. The increase in assimilation rate with higher light intensity decreases the cm∕ca ratio and thus leads to a lower back-diffusion flux, which explains the decreases in for maize and most clearly for sunflower. A similar trend of increase in with an increase in cm∕ca ratio has been reported in previous studies (Gillon and Yakir, 2000b, a; Osborn et al., 2017). For ivy, and do not decrease with an increase in irradiance because the change in assimilation rate with irradiance is small. Thus, cm will not decrease strongly and the effect on the back diffusion is smaller than the variability in of different leaves of the same plant.
In our experiments, photosynthesis causes an enrichment in the δ18O of atmospheric CO2 for both C3 and C4 plants, i.e., positive value of . In principle, can also be negative if the δ18Om is depleted relative to the ambient CO2. This is in contrast to , which will always be positive since it is determined by the fractionation due to the PEPC and RuBisCO enzyme activity (Figs. S8 and S9). In general, in our experiments the values are about 5 times larger than δ18Oa−δ18Oe, the δ18O difference between CO2 entering and leaving the cuvette (Figs. S10 to S12). This is easy to understand from the definition of ΔA. Taking as an example, , and in our experiments .
5.2 Discrimination against the Δ17O of CO2
The leaf cuvette model includes the isotope fractionations of all the individual processes that have been quantified in dedicated experiments previously (Fig. 1). The good agreement of the model results with the measurements (Fig. 3a) demonstrates that when all these processes are combined in the quantitative description of a gas exchange experiment, they actually result in a correct quantification of the isotope effects associated with photosynthesis. This has already been demonstrated before for but has now been confirmed for ΔAΔ17O.
Unlike ivy and sunflower, maize does not show a significant change in ΔAΔ17O when CO2 gases with different Δ17O are supplied to the plant. The C4 plant maize has a small back-diffusion flux due to its high assimilation rate and low stomatal conductance, leading to a low cm∕ca ratio. At low cm∕ca ratios, ΔAΔ17O is expected to be close to the weighted fractionation due to diffusion through boundary layer and stomata. In general, the effect of diffusion on Δ17O of atmospheric CO2 can be expressed as follows:
where Δ17Oa is the Δ17O of the CO2 surrounding the leaf; Δ17Omodified is the Δ17O of the CO2 modified due to diffusional fractionation; and , λRL, and αdiffusion are the oxygen three-isotope relationships during diffusion from the CO2−H2O exchange site to the atmosphere, the reference slope used, and the fractionation against 18O for CO2 during diffusion through the stomata. Using the values λRL=0.528, (Young et al., 2002), and αdiffusion=0.9912 (Farquhar and Lloyd, 1993), the effect of diffusional fractionation on the Δ17O of atmospheric CO2 is −0.168 ‰ regardless of the anomaly of the CO2 entering the leaf, and the model results confirm this at low cm∕ca ratios (Fig. 5c and d, inset).
At a high cm∕ca ratio, Δ17Oa is dominated by the back-diffusion flux of CO2 that has equilibrated with water. As a consequence, Δ17Oa converges to a common value that is independent of the anomaly of the CO2 entering the cuvette and is determined by the isotopic composition of leaf water. Figure 5 confirms that the end-member is equal to the Δ17O of CO2 in equilibrium with leaf water, Δ17Om. In fact, when Δ17Oa=Δ17Om, Δ17Oa does not change with cm∕ca, indicating that in this case the Δ17O of the CO2 diffusing back from the leaf is the same as the Δ17O(CO2) entering the leaf.
is the overall discrimination occurring during the diffusion of 12C18O16O from the ambient air surrounding the leaf to the CO2−H2O exchange site (see Table 2 for the list of variables). In our study ranges from 5 ‰ to 7.2 ‰, lower than the literature estimate of 7.4 ‰ (Farquhar et al., 1993). depends on the ratio of stomatal conductance, which is associated with a strong fractionation of 8.8 ‰, to mesophyll conductance with an associated fractionation of only 0.8 ‰. Therefore, the higher the ratio (gs∕gm18) the lower the (Table S2). The difference in of 2.4 ‰ between the literature value of 7.4 ‰ and the lowest estimate in this study will introduce an error of only 0.046 ‰ in the Δ17O value (see Eq. 6). The uncertainty has lower influence on the ΔAΔ17O of C3 plants compared to C4 plants since the diffusional fractionation is less important at the higher cm∕ca ratio where C3 plants operate.
5.3 Global average value of ΔAΔ17O and Δ17O isoflux
We can use the established relationship between ΔAΔ17O and Δ17Oa−Δ17Owes for a certain cm∕ca ratio to provide a bottom-up estimate for the global effect of photosynthesis on Δ17O in atmospheric CO2, based on data obtained in real gas exchange experiments. For this, we use results from a recent modeling study, which provides global average values for CO2 and leaf water ( ‰, ‰; Koren et al., 2019; Figs. S13 and 14). The Δ17O(CO2) values agree well with the limited amount of available measurements (Table 3).
To extrapolate ΔAΔ17O determined in the leaf-scale experiments to the global scale, global average cm∕ca ratios of 0.7 and 0.3 are used for C3 and C4 plants, respectively, similar to previous studies (Hoag et al., 2005; Liang et al., 2017b). From the SIBCASA model results we obtained an annual variability of ci∕ca values with a standard deviation of 0.12 and 0.17 for C4 and C3 plants, respectively (Fig. S15) (Schaefer et al., 2008; Koren et al., 2019). We use this variability as the upper limit of the error estimate for cm∕ca, as shown in the light orange and light pink shaded areas in Fig. 4b. This error is converted to an error in ΔAΔ17O using the relation with cm∕ca. Based on the linear dependency of ΔAΔ17O and Δ17Oa−Δ17Owes, we estimate the ΔAΔ17O for tropospheric CO2 based on the Δ17O of leaf water and cm∕ca ratio. In Fig. 4b, the vertical dashed black line indicates Δ17Oa−Δ17Owes obtained from the 3D global model (Koren et al., 2019). The results of the global estimate and parameters used for the extrapolation of a leaf-scale study to the global scale are summarized in Table 3.
The δ17O value of atmospheric CO2 (21.53 ‰) is calculated from the global δ18O and Δ17O values (41.5 ‰ and −0.168 ‰, respectively) (Koren et al., 2019). The δ17O and δ18O values of global mean leaf water are calculated from the soil water. A global mean δ18O value of soil water is −8.4 ‰ assuming soil water to be similar to precipitation (Bowen and Revenaugh, 2003; Koren et al., 2019). The δ17O value of soil water is −4.4 ‰, calculated using Eq. (7) (Luz and Barkan, 2010).
δ17O and δ18O of leaf water are calculated from δ17O and δ18O of soil water with fractionation factors of 1.0043 and 1.0084, respectively (Hofmann et al., 2017; Koren et al., 2019). The fractionation factor for δ17O is calculated using with λtrans=0.516, assuming relative humidity to be 75 % (Landais et al., 2006). The δ17O and δ18O values of global mean leaf water are then −0.136 ‰ and −0.131 ‰, respectively. Thus, the difference between global atmospheric CO2 and leaf water is ‰ and ‰. This yields ‰, and this value is indicated as a dashed black line in Fig. 4. The gray shaded area indicates the propagated error using the standard deviation of the relevant parameters in 180×360 grid boxes for 12 months of leaf water and 45×60 grid boxes for 24 months for CO2 (Koren et al., 2019). In Fig. 4b, the intersection between the vertical dashed black line and the discrimination lines for the representative cm∕ca ratios of C3 and C4 plants corresponds to the ΔAΔ17O value of C3 and C4 plants. For C4 plants () this yields ‰ (dashed gray line in Fig. 4b), and for C3 plants it yields () ‰ (dashed black line in Fig. 4b).
Three main factors contribute to the uncertainty of the extrapolated ΔAΔ17O value. The first is the measurement error, which contributes 0.25 ‰ (standard error for individual experiments). The second factor is the uncertainty in the difference between Δ17O of atmospheric CO2 and leaf water, and we use results from the global model to estimate an error. For Δ17O of atmospheric CO2, statistics for all 45×60 grid boxes for 24 months (2012–2013) show a range of −0.218 ‰ to −0.151 ‰, with a mean of −0.168 ‰ and a standard deviation of 0.013 ‰ (Fig. S13). For Δ17O of the leaf water statistics for all 180×360 grid boxes for 12 months show a range of −0.236 ‰ and −0.027 ‰ (Fig. S14). The mean is −0.067 ‰ with a standard deviation of 0.041 ‰. From the combined errors we estimate the error in (Δ17Oa−Δ17Owes) to be 0.043 ‰. The third uncertainty in the extrapolation of Δ17O comes from the uncertainty in the cm∕ca ratio. For C3 and C4 plants, these errors are indicated by the light orange and light blue shadings in Fig. 4b.
Taking these uncertainties into account leads to a mean value of ‰ for C4 plants and ‰ for C3 plants. The leaf-scale discrimination against Δ17O is then extrapolated to global vegetation using these representative values of ΔAΔ17O and the relative fractions of photosynthesis by C4 and C3 plants, respectively, as follows:
where and are the photosynthesis-weighted global coverage of C4 and C3 vegetation. and quantify the discrimination against Δ17O by C4 and C3 plants, which are calculated using estimated values of cm∕ca from a model. Using assimilation-weighted fractions of 23 % for C4 and 77 % for C3 vegetation (Still et al., 2003), the global mean value of ΔAΔ17O obtained from Eq. (8) is ‰.
Isoflux is the product of isotope composition and gross mass flux of the molecule. In the case of assimilation, the net flux is multiplied with the discrimination associated with assimilation (Ciais et al., 1997a). FLA and FAL are total CO2 fluxes from leaf to the atmosphere and from atmosphere to leaf, respectively. The global-scale Δ17OA isoflux is calculated by multiplying the discrimination with the assimilation flux as follows:
where is the terrestrial assimilation rate. The factor 0.88 accounts for the fraction of CO2 released due to autotrophic respiration (Ciais et al., 1997a). The ΔAΔ17O isoflux due to photosynthesis is calculated using a GPP value of 120 PgC yr−1 (Beer et al., 2010) and , resulting in an isoflux of ‰ PgC yr−1 globally. This is the first global estimate of ΔAΔ17O based on direct measurements of the discrimination during assimilation. Our value is in good agreement with previous model estimates. Hofmann et al. (2017) estimated an isoflux ranging from −42 ‰ PgC yr−1 to −92 ‰ PgC yr−1 (converted to a reference line with λ=0.528) using an average cm∕ca ratio of 0.7 for both C4 and C3 plants and Δ17O of −0.147 ‰ for atmospheric CO2. A model-estimated value from Hoag et al. (2005) is −47 ‰ PgC yr−1 (converted to our reference slope of λ=0.528), derived with a more simple model and using Δ17O of −0.146 ‰ with cm∕ca ratio of 0.33 and 0.66 for C4 and C3 plants, respectively.
The main uncertainty in the extrapolation of ΔAΔ17O from the leaf experiments to the global scale is the uncertainty in the cm∕ca ratio. The error from the uncertainty in cm∕ca ratio increases when the relative difference in Δ17O between CO2 and leaf water increases (Fig. 5b). It is difficult to determine a single representative cm value for different plants because this value would need to be properly weighted with temperature, irradiance, CO2 mole fraction, and other environmental factors (Flexas et al., 2008, 2012; Shrestha et al., 2019). Recent developments in laser spectroscopy techniques (McManus et al., 2005; Nelson et al., 2008; Tuzson et al., 2008; Kammer et al., 2011) might enable more and easier measurements of cm∕ca both in the laboratory and under field conditions. This could lead to a better understanding of variations in the cm∕ca ratio among plant species temporally, spatially, and environmentally.
In order to directly quantify the effect of photosynthetic gas exchange on the Δ17O of atmospheric CO2, gas exchange experiments were carried out in leaf cuvettes using two C3 plants (sunflower and ivy) and one C4 plant (maize) with isotopically normal and slightly anomalous (17O-enriched) CO2. Results for 18O agree with results reported in the literature previously. Our results for Δ17O confirm that the formalism developed by Farquhar and others for δ18O is also applicable to the evaluation of Δ17O. In particular, our experiments confirm that two parameters determine the effect of photosynthesis on CO2: (1) the Δ17O difference between the incoming CO2 and CO2 in equilibrium with leaf water and (2) the cm∕ca ratio, which determines the degree of back-flux of isotopically exchanged CO2 from the mesophyll to the atmosphere. At low cm∕ca ratios, ΔAΔ17O is mainly influenced by the diffusional fractionation. Under our experimental conditions, the isotopic effect increased with cm∕ca, e.g., ΔAΔ17O was −0.3 ‰ and −0.65 ‰ for maize and sunflower with cm∕ca ratios of 0.3 and 0.7, respectively. However, experiments with mass independently fractionated CO2 demonstrate that the results depend strongly on the Δ17O difference between the incoming CO2 and CO2 in equilibrium with leaf water. This is supported by calculations with a leaf cuvette model.
δ18O is largely affected by kinetic and equilibrium processes between CO2 and leaf water, and also leaf water isotopic inhomogeneity and dynamics. The Δ17O variation is much smaller compared to δ18O and is better defined since conventional biogeochemical processes that modify δ17O and δ18O follow a well-defined three-isotope fractionation slope. Results from the leaf exchange experiments were upscaled to the global atmosphere using modeled values for Δ17O of leaf water and CO2, which results in ‰ and a value for the Δ17O isoflux of ‰ PgC yr−1. This is the first study that provides such an estimate based on direct leaf chamber measurements, and the results agree with previous Δ17O calculations. The largest contribution to the uncertainty originates from uncertainty in the cm∕ca ratio and the largest contributions to the isoflux come from C3 plants, which have both a higher share of the total assimilation and higher discrimination. ΔAΔ17O is less sensitive to cm∕ca ratios at lower values of cm∕ca, for instance for C4 plants such as maize.
Δ17O of tropospheric CO2 is controlled by photosynthetic gas exchange, respiration, soil invasion, and stratospheric influx. The stratospheric flux is well established and the effect of photosynthetic gas exchange can now be quantified more precisely. To untangle the contribution of each component to the Δ17O atmospheric CO2, we recommend measuring the effects of foliage respiration and soil invasion both in the laboratory and at the ecosystem scale.
The data used in this study are included in the paper either with figures or tables. The python code for the cuvette model is available at https://git.wur.nl/leaf_model (last access: 23 March 2020, Koren et al., 2020).
The supplement related to this article is available online at: https://doi.org/10.5194/bg-17-3903-2020-supplement.
GAA and TR designed the main idea of the study. GAA and TP designed the leaf cuvette setup. TP monitors plant growth. GAA and TR designed the CO2 extraction and CO2−O2 exchange system. GAA conducted all the measurements. GK provided the leaf cuvette model. WP enabled the work within the ASICA project. All authors discussed the results at different steps of the project. GAA and TR prepared the manuscript with contributions from all the co-authors.
The authors declare that they have no conflict of interest.
The authors thank Leonard I. Wassenaar and Stefan Terzer-Wassmuth from the International Atomic and Energy Agency, Vienna, for supplying water standards. The authors thank Eugeni Barkan and Rolf Vieten from the Hebrew University of Jerusalem for calibration of our O2 and CO2 working gases. We are grateful to Amaelle Landais from Laboratoire des Sciences Du Climat et de l'Environnement Université Paris-Saclay for measuring the Δ17O of leaf water samples for our study. The authors thank Amzad Laskar for the useful discussion during the design of the experiment. This work is funded by the EU ERC project ASICA.
This research has been supported by the European Research Council (ASICA (grant no. 649087)).
This paper was edited by Aninda Mazumdar and reviewed by two anonymous referees.
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