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Effect of Vapor Pressure Deficit on Gas Exchange in Wild-Type and Abscisic Acid–Insensitive Plants

Lucas A. Cernusak, Gregory R. Goldsmith, Matthias Arend, Rolf T. W. Siegwolf

Published December 2019. DOI: https://doi.org/10.1104/pp.19.00436

Abstract

Stomata control the gas exchange of terrestrial plant leaves, and are therefore essential to plant growth and survival. We investigated gas exchange responses to vapor pressure deficit (VPD) in two gray poplar (Populus × canescens) lines: wild type and abscisic acid–insensitive (abi1) with functionally impaired stomata. Transpiration rate in abi1 increased linearly with VPD, up to about 2 kPa. Above this, sharply declining transpiration was followed by leaf death. In contrast, wild type showed a steady or slightly declining transpiration rate up to VPD of nearly 7 kPa, and fully recovered photosynthetic function afterward. There were marked differences in discrimination against 13CO2 (Δ13C) and C18OO (Δ18O) between abi1 and wild-type plants. The Δ13C indicated that intercellular CO2 concentrations decreased with VPD in wild-type plants, but not in abi1 plants. The Δ18O reflected progressive stomatal closure in wild type in response to increasing VPD; however, in abi1, stomata remained open and oxygen atoms of CO2 continued to exchange with 18O enriched leaf water. Coupled measurements of Δ18O and gas exchange were used to estimate intercellular vapor pressure, ei. In wild-type leaves, there was no evidence of unsaturation of ei, even at VPD above 6 kPa. In abi1 leaves, ei approached 0.6 times saturation vapor pressure before the precipitous decline in transpiration rate. For wild type, a sensitive stomatal response to increasing VPD was pivotal in preventing unsaturation of ei. In abi1, after taking unsaturation into account, stomatal conductance increased with increasing VPD, consistent with a disabled active response of guard cell osmotic pressure.

The role of stomata in terrestrial plants is essential to growth and survival, and to the exchange of energy, water, and CO2 at the land surface (Farquhar and Sharkey, 1982; Lin et al., 2015; Franks et al., 2017). Measurements of how stomata respond to environmental stimuli have enabled implementation of response functions in ecosystem and global models (Berry et al., 2010). These models are now central to efforts to understand and predict the impacts of global climate change on terrestrial carbon and water cycling, as well as associated ecosystem services. Such experimental characterization of stomatal response functions was greatly facilitated by the advent of a method for continuous calculation of stomatal conductance (gs) from measurements of water loss from a leaf, the air humidity surrounding the leaf, and the leaf temperature (Gaastra, 1959). This method assumes that the leaf intercellular vapor pressure (ei) is saturated and that it can therefore be calculated from leaf temperature according to the well-characterized relationship between temperature and saturation vapor pressure (es).

Online measurements of discrimination against 13C and 18O in CO2 can provide valuable information about leaf stomatal responses when combined with simultaneous measurements of total CO2 and water vapor exchange (Farquhar et al., 1993; Cernusak et al., 2013; Barbour, 2017). Discrimination against 13CO2 (Δ13C) is modulated by the ratio of intercellular to ambient CO2 concentrations, ci/ca, and by the ratio of chloroplastic to intercellular CO2 concentrations, cc/ci (Farquhar et al., 1982; Evans et al., 1986). Discrimination against C18OO (Δ18O), on the other hand, is modulated by the extent of leaf water 18O enrichment, as well as by ci/ca and cca/ci, where cca is the CO2 concentration at the site of carbonic anhydrase activity (Gillon and Yakir, 2000; Yakir and Sternberg, 2000; Ogée et al., 2018). Carbonic anhydrase catalyzes the rapid exchange of oxygen atoms between CO2 and water; the CO2 at the site of carbonic anhydrase activity therefore becomes imprinted with the leaf water 18O signal. Both Δ13C and Δ18O share partial dependence on gs through their relationships to ci/ca, and therefore can provide valuable insight into responses of stomata to environmental stimuli.

Cernusak et al. (2018) recently presented a method for calculating ei from simultaneous measurements of Δ18O, transpired water vapor δ18O, and leaf gas exchange. They used this method to investigate unsaturation of ei in mature, field-grown conifer trees in a semiarid ecosystem in the southwestern United States. They showed intercellular relative humidity, ei/es, declining to values as low as 0.8 as air vapor pressure deficit (VPD) increased in a simulated diurnal cycle. These departures from saturation of ei were sufficient to cause substantial biases in calculations of gs and ci. Moreover, such departures from saturation challenge current understanding of the internal hydraulic features of leaves (Buckley and Sack, 2019).

Abscisic acid (ABA) is essential in guard cell development and stomatal function (Franks and Farquhar, 2001; Kuromori et al., 2018). Catabolism of ABA in guard cells leads to adjustment of stomatal apertures through changes in guard cell osmotic pressure, allowing stomata to close in response to environmental stimuli such as increasing VPD. Genetic transformations that result in plants that are insensitive to ABA through disrupted signaling pathways provide a useful tool for probing stomatal function when these plants are compared with their wild-type counterparts. Transformation of gray poplar, Populus × canescens (Aiton) Sm., with the ABA-insensitive1 (abi1) gene from Arabidopsis (Arabidopsis thaliana) resulted in a phenotype in which the stomata showed impaired function, and stomatal conductance was higher than in the wild type. The abi1 plants did not show stomatal closure in response to application of exogenous ABA or exposure to low air humidity, behavior that clearly distinguished them from their wild-type counterparts (Arend et al., 2009).

In this paper, we made use of the impaired stomatal function of abi1 plants of Populus × canescens, contrasting them with wild-type plants, to achieve three objectives: first, to characterize the responses of Δ13C and Δ18O to VPD to gain insight into the crucial role of stomata in modulating these processes; second, to demonstrate the applicability of the Δ18O method for resolving ei in the abi1 plants, in which stomata were expected to play little role in preventing ei from declining below saturation through stomatal closure; and third, to investigate whether wild-type broad-leaf angiosperm plants would show unsaturation of ei at moderate to high VPD, as was previously observed in two semiarid conifer species (Cernusak et al., 2018).

Theory: Oxygen Isotopes

Here we explain our method for resolving ei from coupled measurements of Δ18O and leaf gas exchange. A list of abbreviations and symbols is shown in Table 1. According to well-established gas exchange equations (von Caemmerer and Farquhar, 1981), transpiration rate (E) can be expressed as the product of leaf-to-air vapor pressure difference (ei-ea) and total conductance of stomata plus boundary layer to water vapor (gt):Embedded Image(1)

View this table:
Table 1. Definitions of Symbols Used Repeatedly in the Text

Symbols that appear only alongside their definition in the text are not included here.

Here, ei is the intercellular vapor pressure, ea is the atmospheric vapor pressure, P is atmospheric pressure, and Embedded Image is (ei+ea)/2. This final term is a ternary correction and typically accounts for about 3% of the transpiration rate. Stomatal conductance to water vapor (gs) relates to gt and boundary layer conductance to water vapor (gb) as,Embedded Image(2)

The gb is typically predetermined for a given leaf chamber, taking into account wind speed across the leaf surface within the chamber. With E and ea measured and gb predetermined, one can see from Equations 1 and 2 that an estimate of ei is still required to calculate gs. The very useful innovation provided by Gaastra (1959) was to suggest that ei could be calculated from leaf temperature so long as one assumed that the air inside the leaf was saturated with water vapor. Then, a well-characterized relationship between saturation vapor pressure (es) and temperature could be used to calculate ei by assuming it equal to es:Embedded Image(3)

where es is given in kPa and Tl is leaf temperature in °C.

Analogous to the transpiration rate, the photosynthesis rate (A) can be expressed as the product of the total conductance to CO2 (gtc) and the drawdown in CO2 mole fraction between the atmosphere and the intercellular air spaces (ca-ci):Embedded Image(4)

where ca is the CO2 mole fraction in the atmosphere, ci is that in the intercellular air spaces, and Embedded Image is defined as (ca+ci)/2. The final term in Equation 4 is again a ternary correction, which accounts for the influence of transpiration on the diffusion of CO2 into the leaf. Stomatal conductance to CO2 (gsc) can be calculated from the conductance to water vapor as gs/1.6; and the boundary layer conductance to CO2 (gbc) can be calculated as gb/1.37. The gtc can then be calculated as,Embedded Image(5)

and Equation 4 can now be solved for ci:Embedded Image(6)

The influence of the leaf on the δ18O of CO2 passing through a gas exchange cuvette can be quantified by calculating the δ18O of CO2 taken up by photosynthesis, δ18OA (Evans et al., 1986; Farquhar et al., 1993). This can be done by measuring the CO2 mole fraction and its isotopic composition entering and exiting the gas exchange cuvette, as described in the “Materials and Methods.” With this estimate of δ18OA, the δ18O of CO2 in the intercellular air spaces (δ18Oi) can then be estimated (Cernusak et al., 2004; Farquhar and Cernusak, 2012). This calculation is presented here in two steps: the first step (Eq. 7) represents the calculation without the ternary correction (δ18Oio), and the second step (Eq. 8) then applies the ternary correction (Farquhar and Cernusak, 2012):Embedded Image(7)Embedded Image(8)

Here, δ18Oa is the δ18O of CO2 in air surrounding the leaf, Embedded Image is the combined fractionation for C18OO diffusion through the boundary layer and the stomata, Embedded Image is defined as 1+Embedded Image and t18 is a ternary correction factor. The Embedded Image is defined asEmbedded Image(9)

where Embedded Image is the C18OO fractionation during diffusion through the boundary layer (5.8‰), Embedded Image is that during diffusion through stomata (8.8‰), and cs is the CO2 mole fraction at the leaf surface. The ternary correction factor, t18, is defined as,Embedded Image(10)

The δ18O of CO2 at the sites of carbonic anhydrase activity (δ18Oca) can then be estimated analogously to Equation 7; there is no ternary correction required in this case because the diffusion is through liquid (Cernusak et al., 2004; Farquhar and Cernusak, 2012):Embedded Image(11)

where Embedded Image is the C18OO fractionation during diffusion through liquid water, taken as 0.8‰ (Farquhar and Lloyd, 1993), and Embedded Image is defined as 1+Embedded Image.

We assume that the δ18O of the liquid water at the evaporative sites in the leaf (δ18Oe) is representative of the δ18O of water at the sites of carbonic anhydrase activity (Farquhar et al., 1993; Cernusak et al., 2018). The δ18O of water at the evaporative sites can be calculated from measurements (see Eq. 18) of transpired water δ18O (δ18OE) as (Farquhar et al., 2007)Embedded Image(12)

where ε+ is the equilibrium fractionation for the phase change from liquid water to vapor, and εk is the kinetic fractionation for diffusion through the stomata and boundary layer; these were calculated as described in “Materials and Methods.” The δ18Ov is the δ18O of water vapor in the atmosphere surrounding the leaf, which is taken as the measured δ18O of water vapor exiting the leaf gas exchange cuvette.

The δ18O of CO2 equilibrated with evaporative site water (δ18Oce) can be calculated by taking into account a temperature-dependent equilibrium fractionation factor (εw). Calculation of εw is also described in “Materials and Methods.” With εw in hand, the δ18Oce can be calculated asEmbedded Image(13)

The above set of equations allows for estimation of two important parameters. The first is the δ18O of CO2 at the sites of carbonic anhydrase activity, based on measurements of the δ18O of CO2 entering and leaving the gas exchange cuvette; the second is the δ18O of evaporative site water, based on measurements of the δ18O of water vapor entering and leaving the gas exchange cuvette. This second step allows calculation of the δ18O of CO2 that would be in equilibrium with the evaporative site water. By using the assumption that the δ18O of CO2 at the sites of carbonic anhydrase activity should be equal to the δ18O of CO2 in equilibrium with evaporative site water, that is δ18Oca=δ18Oce, we obtain a constraint through which the intercellular vapor pressure, ei, can be estimated. This can be achieved by allowing ei to vary iteratively to solve the set of equations until ei is such that δ18Oca is equal to δ18Oce. In the Supplemental Data, we have provided a Microsoft Excel workbook that demonstrates in more detail how this was achieved.

Theory: Carbon Isotopes

For carbon isotopes, it can be more convenient to refer to discrimination (Δ13C) with respect to atmospheric CO2 (δ13Ca), as Δ13C results mainly from physiological processes. For oxygen isotopes in CO2, discrimination against 18O (Δ18O) is also a useful expression (Farquhar et al., 1993), but differs notably from Δ13C in that Δ18O varies as a function of the difference between δ18O of atmospheric CO2 and δ18O of leaf water (Farquhar et al., 1993), which can be independent of physiology. For carbon isotopes, online measurements of Δ13C can be related to biochemical and diffusional fractionation within the leaf (Farquhar et al., 1982; Farquhar and Cernusak, 2012):Embedded Image(14)

where Embedded Image is the 13C/12C fractionation for CO2 diffusion across the boundary layer (2.8‰), Embedded Image is that for diffusion through the stomata (4.4‰), and Embedded Image is that for dissolution and diffusion from the intercellular air spaces to the sites of carboxylation in the chloroplasts (1.8‰). The term b is the fractionation by Rubisco (taken as 30‰ because we are using the full model for Δ13C), f is fractionation during photorespiration (11‰), and e is fractionation during day respiration (0 to 5‰). The Rd is the rate of day respiration, Vc is the rate of Rubisco carboxylation, and Γ* is the CO2 compensation point in the absence of day respiration. The terms αb, αe, and αf are defined as 1+b, 1+e, and 1+f, respectively. The ternary correction factor, t13, is defined as above in Equation 10, but with Embedded Image replaced by Embedded Image, which is defined as 1+Embedded Image. The Embedded Image is defined as in Equation 9, but with fractionation factors for 13CO2 rather than C18OO.

Online measurements of Δ13C can be used to estimate the mesophyll conductance to the sites of carboxylation, gm, if terms other than cc in Equation 14 are measured or are assumed to be known (Evans et al., 1986; Pons et al., 2009). The gm is typically estimated by first calculating the predicted Δ13C when cc=ci, termed Δ13Ci, to denote the case of infinite gm (Evans et al., 1986; Farquhar and Cernusak, 2012):Embedded Image(15)

The gm can then be estimated from the difference between Δ13Ci and the observed Δ13C (Δ13Cobs):Embedded Image(16)

We note that when gm is estimated in this way, ei is typically assumed to be saturated, with gas exchange parameters calculated according to the standard methodology (Gaastra, 1959; von Caemmerer and Farquhar, 1981; Cernusak et al., 2018).

RESULTS

Figure 1 shows example negative impressions of stomata in the wild type and abi1 leaves, and Supplemental Figure S1 shows images of the actual leaf surfaces. For Supplemental Figure S1, the images were captured on a laser scanning microscope, which required that the leaves be detached from the plants. The wild-type image thus shows that the stomata closed in response to leaf detachment, whereas the abi1 image shows that the stomata remained open following leaf detachment.

Figure 1.
Figure 1.

Negative imprints of abaxial leaf surfaces. These are shown for wild-type (A) and abi1 (B) Populus × canescens leaves, in which abi1 leaves had functionally impaired stomata. The imprints were made in situ with Aquasil Ultra XLV Fast Set (DENTSPLY International), and images were captured with VK-X200 3D laser scanning confocal microscope (Keyence).

In total, we measured VPD responses for six wild-type and six abi1 leaves. For wild-type plants, each leaf was from a different individual plant. For abi1 plants, the six leaves came from four individual plants (see Supplemental Dataset S1). Photosynthesis declined linearly with increasing VPD in both wild-type and abi1 plants (F1,84 = 189.9, P < 0.0001), as shown in Figure 2A. The slope of the decline was steeper in abi1 than in wild-type plants (F1,84 = 31.1, P < 0.0001), with a slope of −1.4 µmol CO2 m−2 s−1 kPa−1 in wild type and −3.2 µmol CO2 m−2 s−1 kPa−1 in abi1 plants. The intercept of the relationship between A and VPD did not differ between wild-type and abi1 plants (F1,84 = 1.6, P = 0.21), indicating that photosynthesis rates at the lowest VPDs were similar between wild-type and abi1 plants.

Figure 2.
Figure 2.

Gas exchange responses to air vapor pressure deficit in abi1 and wild-type plants of Populus × canescens. We show photosynthesis (A); transpiration (B); stomatal conductance, gs (C); and the ratio of intercellular to ambient CO2 concentrations, ci/ca (D). The gs and ci/ca have been here calculated assuming saturation of intercellular vapor pressure, following the standard method of gas exchange calculations. Further analyses showed evidence of unsaturation for abi1, but for not wild-type plants. Unsaturation causes biases in calculations of gs and ci/ca. Six wild-type leaves were measured, each from a different individual plant, and six abi1 leaves were measured, representing four individual plants.

The slope of the response of transpiration to VPD differed significantly between wild-type and abi1 plants (F1,84 = 235.4, P < 0.0001), as shown in Figure 2B. The wild-type plants had a slightly negative response of E to VPD, with a slope of −0.1 mmol H2O m−2 s−1 kPa−1. In contrast, E in abi1 plants showed a strongly positive response to VPD with a slope of 3.2 mmol H2O m−2 s−1 kPa−1. The positive linear response in abi1 plants continued up to VPD of about 2 kPa. At VPD of between 2 and 3 kPa, the change in E reached an asymptote, and with any further increase in VPD, the abi1 plants could not sustain a steady transpiration rate. Instead, E declined precipitously and photosynthesis rates decreased to less than 0.5 µmol CO2 m−2 s−1. In contrast, wild-type plants were able to sustain steady transpiration rates at VPDs of between 6 and 7 kPa, while also maintaining photosynthesis rates in the range of 1 to 2 µmol CO2 m−2 s−1 (Fig. 2).

Upon removal from the cuvette, leaves of the abi1 plants were visibly dried (see Supplemental Fig. S2 for an example); leaf death could subsequently be observed within hours (see Supplemental Fig. S3 for an example). In contrast, wild-type leaves maintained a healthy appearance after removal from the cuvette. Photosynthesis measured the following day in wild-type leaves showed a full recovery, with no significant difference from observations on the day of VPD response measurements (t3 = 0.5, P = 0.66).

Responses of gs and ci/ca to VPD are shown in Figure 2, C and D, respectively; it is important to note that data in these figures have been calculated assuming ei equal to es (Eq. 3), following the standard method of gas exchange calculations. According to these data, wild-type plants showed curvilinear decreases of both gs and ci/ca in response to increasing VPD. In contrast, gs of abi1 plants showed an apparent linear decrease in response to increasing VPD, and an apparent lack of response of ci/ca to increasing VPD.

Observed Δ13C differed between abi1 and wild-type plants (Fig. 3A). The intercept of the relationship between Δ13Cobs and VPD was significantly higher in abi1 than in wild-type plants (F1,77 = 30.9, P < 0.0001), with a value of 24.8‰ in the former and 19.2‰ in the latter. According to the mixed model analysis of covariance, the slope of the relationship between Δ13Cobs and VPD did not differ between abi1 and wild-type plants (F1,77 = 0.6, P = 0.43). However, the ranges of VPDs covered by the two treatments were very different, such that the power of this analysis to detect different slopes would be weak. When analyzed separately, the abi1 plants showed no significant response of Δ13C to VPD (F1,31 = 2.7, P = 0.11), whereas the wild-type plants showed a significant negative response (F1,46 = 7 6.8, P < 0.0001). The slope of the relationship between Δ13Cobs and VPD for wild-type plants was −1.0‰ kPa−1. The observed Δ18O also showed a significantly different pattern between abi1 and wild-type plants (Fig. 3B), with the positive slope of the response of Δ18Oobs to VPD being much steeper in abi1 than in wild-type plants (F1,77 = 220.1, P < 0.0001). The slope of this response was 2.5‰ kPa−1 in wild-type plants, whereas it was 65.7‰ kPa−1 in abi1 plants.

Figure 3.
Figure 3.

Online stable isotope discrimination. This is shown as discrimination against 13CO2 (A) and C18OO (B) for abi1 and wild-type Populus × canescens plants in response to increasing air vapor pressure deficit. The abi1 plants had impaired stomatal function, which strongly influenced the discrimination responses for both isotopes. Six wild-type leaves were measured, each from a different individual plant, and six abi1 leaves were measured, representing four individual plants.

The response of the δ18O of transpired water to increasing VPD also differed between abi1 and wild-type plants (Fig. 4). In abi1 plants, δ18OE increased moderately with increasing VPD (F1,31 = 11.4, P = 0.002), with a slope of 0.9‰ kPa−1 and an intercept of −9.9‰. The wild-type plants showed a more complex pattern: δ18OE initially decreased with increasing VPD up to a breakpoint at about 2.5 kPa; δ18OE then increased with further increase in VPD. At the highest values of VPD, δ18OE of wild-type plants returned to values similar to those of abi1 plants.

Figure 4.
Figure 4.

The oxygen isotope composition (δ18O) of transpired water vapor. This is shown for abi1 and wild-type Populus × canescens plants exposed to a range of air vapor pressure deficits. Six wild-type leaves were measured, each from a different individual plant, and six abi1 leaves were measured, representing four individual plants.

If ei is assumed saturated, the equations above can be solved for gm in the case of Δ13C and for gmc, the mesophyll conductance to the sites of carbonic anhydrase, in the case of Δ18O. Results of these calculations are shown in Supplemental Figure S4. For gm, there was no significant effect of VPD (F1,73 = 2.2, P = 0.14), and no significant difference between abi1 and wild-type plants (F1,74 = 0.1, P = 0.73). For gmc, there was a significant effect of VPD (F1,76 = 28.2, P < 0.0001), and the slope of the relationship with VPD was more negative for abi1 than for wild-type plants (F1,76 = 10.9, P < 0.01). Mean values (± 1SD) of gm and gmc for wild-type plants were 0.17 (± 0.15) and 0.15 (± 0.08) mol m−2 s−1 bar−1; those for abi1 plants were 0.14 (± 0.09) and 0.16 (± 0.05) mol m−2 s−1 bar−1.

If, on the other hand, ei is not assumed saturated, the theory section above provides a means of solving for ei from Δ18O measurements if one assumes values for gmc. We performed these calculations by choosing a value of gmc that resulted in ei/es=1 for measurements at the lowest VPD levels for each leaf. This value of gmc was then applied to the subsequent measurements for that leaf. Results of these calculations are shown in Figure 5, and also in Supplemental Dataset S1. Here, the wild-type plants showed no evidence of ei/es declining below unity as VPD increased. The abi1 plants, on the other hand, showed a coherent pattern of linear decline of ei/es with increasing VPD (F1,31 = 323.4, P < 0.0001), with a slope of −0.23 kPa−1. The calculated ei/es was linearly correlated with the air relative humidity, ea/es, but offset above it (Fig. 6). This suggests that in the absence of stomatal closure, the intercellular relative humidity varies as a function of the ambient air relative humidity.

Figure 5.
Figure 5.

Intercellular relative humidity (ei/es) for abi1 and wild-type plants of Populus × canescens. The ei/es was estimated from measurements of oxygen isotope discrimination in CO2 and transpired water vapor. It is plotted against the vapor pressure deficit of air inside the leaf gas exchange cuvette. The inset shows the response of abi1 plants with the axis for vapor pressure deficit restricted to the range to which these plants were exposed. Six wild-type leaves were measured, each from a different individual plant, and six abi1 leaves were measured, representing four individual plants.

Figure 6.
Figure 6.

Relative humidity in the intercellular air spaces of abi1 plants plotted against the relative humidity of air outside the leaf, but the latter calculated for leaf temperature rather than air temperature. The intercellular relative humidity was estimated from measurements of oxygen isotope discrimination during photosynthesis and in transpired water vapor. Six leaves were measured, representing four Figure 8, A and B, individual plants.

Given that we observed no evidence of unsaturation of ei in the wild-type plants, we show in Figure 7 the relationship between gs calculated assuming ei/es=1 and the leaf-to-air vapor pressure difference (LAVPD; Fig. 7A), as well as that between gs and the air relative humidity (Fig. 7B). The gs was inversely related to LAVPD, and linearly related to air relative humidity.

Figure 7.
Figure 7.

Stomatal response in wild-type Populus × cancescens. Stomatal conductance is plotted against leaf-to-air vapor pressure difference (A) and air relative humidity (B). The wild-type plants did not show evidence of unsaturation of intercellular vapor pressure; thus, measurements of stomatal conductance in wild-type plants can be considered free of bias associated with unsaturation. Six leaves were measured, each from a different plant.

In contrast to wild-type plants, the abi1 plants showed strong evidence of unsaturation, and we therefore show in Figure 8, A and B, the recalculated values for gs and ci/ca in response to VPD in which unsaturation has been taken into account. Accounting for unsaturation, the gs of the abi1 plants increased in response to increasing VPD with a slope of 1.08 mol m−2 s−1 kPa−1 (F1,29 = 59.0, P < 0.0001), and ci/ca also showed an increase in response to VPD, albeit with a very small slope of 0.02 kPa−1 (F1,29 = 84.9, P < 0.0001). Two rows of data were excluded from these analyses because they resulted in gs estimates of 12.6 and −11.0 mol m−2 s−1, respectively.

Figure 8.
Figure 8.

The response of stomatal conductance (gs) and the ratio of intercellular to ambient CO2 mole fractions (ci/ca) in abi1 plants of Populus × cancescens to increasing vapor pressure deficit. The gs is shown in (A) and ci/ca in (B). The red symbols differ from the gray symbols in the important aspect that unsaturation of the intercellular vapor pressure (ei) has been taken into account in calculations for the red symbols. The gray symbols show the same data as is plotted in Figure 2, C and D, where gs and ci/ca were calculated with ei assumed to be saturated, as is standard practice. Six leaves were measured, representing four individual plants.

DISCUSSION

We compared gas exchange and isotope discrimination in abi1 plants of Populus × canescens with impaired ABA signaling to observations in wild-type plants. Transpiration rate increased approximately linearly as VPD increased in abi1 plants. In sharp contrast, stomata of the wild-type plants had a very sensitive response to VPD, such that transpiration rate under steady gas exchange conditions remained little changed or slightly decreased as VPD increased to very high levels (i.e. > 6 kPa). According to our calculations, using concurrent measurements of Δ18O, the abi1 plants showed a strong signal of unsaturation with increasing VPD, whereas the wild-type plants showed no such signal. When unsaturation was accounted for in calculations of gs in the abi1 plants, a surprising response to VPD was revealed: gs increased rather than decreased with rising VPD. Although counterintuitive, this response is consistent with theoretical predictions based on the mechanical advantage of epidermal cells over guard cells in a dehydrating leaf, if active regulation of guard cell osmotic pressure has been disabled (Buckley, 2005; Franks and Farquhar, 2007).

One of our primary motivations for investigating gas exchange in the abi1 plants was to gain insight into the dynamics of intercellular vapor pressure, ei. The fundamental gas exchange processes A and E provide one level of such insight, with further support provided by Δ13C and Δ18O. The responses of A and E are consistent with drying of the air in the intercellular air spaces in the abi1 leaves as VPD increased. The observation that the abi1 plants could not sustain transpiration much above VPD of 2 kPa, combined with the observation that these leaves were then visibly dried and soon to be dead upon removal from the cuvette, strongly supports this notion. The sharp negative response of A to increasing VPD in abi1 plants (Fig. 2A) further suggests progressive impairment of the photosynthetic apparatus as ei declined with increasing VPD. Calculation of ci by the conventional method (Fig. 2D) confirmed that the reduction in A in abi1 plants was in no way caused by declining ci associated with stomatal closure, as was likely the case in the wild-type plants. Calculation of ci by the conventional method sets a lower limit on ci for cases where ei may be unsaturated, because the impact of ei being less than saturation on the calculated value of ci is always to increase it. In fact, when unsaturation was accounted for in the calculation of ci, it showed a slightly increasing trend with rising VPD (Fig. 8B), rather than a decreasing trend, which would indicate a diffusional limitation on photosynthesis.

Measurements of Δ13C and Δ18O provided additional support for these inferences. The abi1 plants showed no significant response of Δ13C to VPD, whereas the wild-type plants showed a significant negative response with a slope of −1.0‰ kPa−1. This provides further evidence that the decrease of A with increasing VPD in abi1 plants was not caused by declining CO2 concentration in the chloroplasts associated with stomatal closure and/or markedly declining mesophyll conductance. The lack of response of Δ13C to VPD, and by inference lack of chloroplastic CO2 concentration response, in abi1 plants suggests that the negative response of A to VPD was rather caused by biochemical inhibition of the photosynthetic apparatus driven by drying of the leaf. For example, it has been shown that leaf water deficit can slow the production of ATP by the light reactions of photosynthesis and inhibit regeneration of ribulose 1,5-bisphosphate by the Calvin cycle, thereby slowing CO2 assimilation (Tezara et al., 1999; Lawlor and Cornic, 2002; Lawlor and Tezara, 2009). On the other hand, the negative response of Δ13C to VPD in wild-type plants provides strong evidence that the decrease in A with increasing VPD was caused by declining chloroplastic CO2 concentrations in these plants. The response of Δ18O to VPD in the abi1 versus wild-type plants also provides cogent support for these conclusions. The Δ18O response of abi1 plants clearly showed that stomata remained open and CO2 continued to diffuse into leaves and exchange oxygen atoms with enriched leaf water as VPD increased, providing further support that diffusion resistance of stomata was not responsible for declining A with increasing VPD in abi1 plants.

Buckley et al. (2017) recently conducted a modeling analysis to test, among other things, whether ei is likely to become unsaturated during photosynthesis in broad-leaved angiosperms. They concluded that ei/es, the intercellular relative humidity, would probably not drop below 0.98 averaged across the intercellular air spaces, even under conditions of high light and low xylem water potential. Our results for wild-type plants of Populus × canescens support this prediction. We observed no evidence for appreciable unsaturation of ei in these plants. However, our results for abi1 plants of Populus × canescens strongly contradict one aspect of the predictions of the Buckley et al. (2017) analysis. In their series of simulations, they ran a scenario in which gs was fixed at 0.4 mol m−2 s−1 at an air temperature of 40°C and air relative humidity of zero. This would correspond to a VPD of 7.4 kPa. Under these conditions, their simulated leaf had a steady transpiration rate of 21 mmol H2O m−2 s−1 and average ei/es of 0.98, with this not being lower than 0.95 even at the driest location in the intercellular air spaces. Our measurements with abi1 plants of Populus × canescens with impaired, open stomata indicated that this scenario of ei being maintained near saturation under these conditions clearly did not apply for these plants. We found that inability to close stomata resulted in impaired CO2 assimilation, visible drying, and subsequent death of leaves exposed to much lower VPDs of only 2 to 3 kPa. We suggest that this could only have been associated with ei/es dropping very far below 0.98. The difference between our observations and the modeled prediction in that particular scenario suggests that there is a consequence of increasing VPD for a leaf with impaired stomatal function that was not manifested in the model. This could be a sharp decline in the hydraulic conductance of veins and/or cell walls as leaf water content and leaf water potential decline (Egorov and Karpushkin, 1990; Scoffoni et al., 2017a, 2017b; Muries et al., 2019; Trueba et al., 2019).

We then used a new method, based on measurements of δ18O of CO2 and water vapor, to make quantitative estimates of ei in the abi1 leaves as they were exposed to progressively increasing VPD. These estimates indicated a linear decline in ei/es with increasing VPD (Fig. 5), which also mirrored the decline in relative humidity of the air surrounding the leaf (Fig. 6). Making these quantitative estimates of ei required assigning values for gmc, the mesophyll conductance to CO2 to the sites of carbonic anhydrase activity. We accomplished this by finding values that corresponded to ei/es similar to unity for the lowest VPD measurements (see Supplemental Dataset S1 for full dataset and analysis). We then held these gmc values fixed throughout the course of the VPD response for that particular leaf. For the abi1 plants, if gmc did in fact decline as VPD increased, this would equate to a shallower slope of the response of ei/es to VPD than that shown in Figure 5. Interestingly, for the wild-type plants, fixing gmc at a single value for each leaf resulted in ei/es increasing above unity at the highest VPDs (Fig. 5). This suggests that gmc probably did decline in the wild-type plants at the highest values of VPD, namely VPD above about 5.5 kPa. This can be seen clearly in Supplemental Figure S4B, where gmc was calculated assuming ei/es=1. Recently, Holloway-Phillips et al. (2019) developed a two-source δ18O technique that allows simultaneous estimation of gmc and ei, and confirmed decreases in both in response to VPD in Vicia faba.

We observed differences in the δ18O of transpired water, δ18OE, between the abi1 and wild-type plants in response to increasing VPD (Fig. 4). In isotopic steady state, the δ18OE would be equal to the δ18O of water entering the leaf from the xylem (Harwood et al., 1998). The δ18O of irrigation water in our experiment was −11.6‰. Thus, at low VPD, the wild-type plants had δ18OE similar to δ18O of irrigation water, whereas the abi1 plants appeared to consistently have δ18OE higher than δ18O of irrigation water. For VPD less than 1 kPa, the average δ18OE for wild-type plants was −11.0‰ and that for abi1 plants was −9.3‰. For wild-type plants, the decrease of δ18OE with increasing VPD up to the break-point VPD of about 2.5 kPa would be consistent with increasing leaf water 18O enrichment in response to decreasing ea/ei. To increase the 18O enrichment of leaf water, the leaf must lose 18O-depleted water through transpiration. The leaf water 18O enrichment may not have completely attained steady state, although gas exchange had (Simonin et al., 2013). The subsequent increase in δ18OE at VPD higher than 2.5 kPa may have been caused by a decrease in leaf water content, as this would involve loss of 18O-enriched water through transpiration compared to the source water entering the leaf. By this logic, the leaf water content of the abi1 plants would have started to decrease from the lowest VPD values to explain the progressive increase in δ18OE with increasing VPD. Contemporaneous measurements of leaf water content and δ18OE will be required to test this interpretation in future experiments.

Our result demonstrating that ei of wild-type plants of Populus × canescens remained saturated at VPD up to nearly 7 kPa contrasts with recent results for two semiarid conifer species (Cernusak et al., 2018). In that study, application of the Δ18O method to mature, field-grown individuals of Pinus edulis and Juniperus monosperma indicated decreasing ei/es with increasing VPD with slopes of −0.05 kPa−1 and −0.02 kPa−1, respectively. These can be compared with the slope observed in this study for abi1 plants of −0.23 kPa−1. In P. edulis, ei/es declined to near 0.8 and in J. monosperma to near 0.9 before gas exchange declined to levels at which reliable measurements of isotopic discrimination could no longer be made. Further experimentation is required to determine whether the contrasting results in the two studies, whereby wild-type plants did not show unsaturation in response to increasing VPD in the current study, are likely to represent a generalizable difference between conifers and broad-leaved angiosperms.

Representation of gs in land surface models typically follows either a Ball-Berry approach (Ball et al., 1987) or a more recently derived approach suggested by Medlyn et al. (Medlyn et al., 2011). The Ball-Berry approach models gs as a function of A, ca, and the relative humidity of the air, whereas the Medlyn approach models gs as a function of A, ca, and the inverse square root of the LAVPD (Franks et al., 2017). For the wild-type plants, relationships between gs and LAVPD and air relative humidity are shown in Figure 7, A and B, and both clearly represent coherent patterns of gs. We fitted the data for wild-type plants to both models and found that they performed similarly well. The Ball-Berry model had an R2 of 0.94 and the Medlyn et al. model had an R2 of 0.93. The critical slope parameter, g1, for the Ball-Berry model was estimated to be 13.0 (dimensionless), with the intercept g0 estimated to be 0.02 mol H2O m−2 s−1. For the Medlyn et al. (2011) model, g1 was estimated to be 5.2 kPa0.5 if fitted with the g0 intercept. If fitted without the g0 intercept in the model, g1 for the Medlyn et al. (2011) approach was estimated to be 4.5 kPa0.5. This final method was previously used in a global comparison of g1 values among plant functional types (Lin et al., 2015), where deciduous angiosperm trees had an average g1 of 4.6 kPa0.5. Thus, our estimate of g1 for wild-type Populus × canescens very closely matches the global average for this plant functional type.

Because the abi1 plants showed progressive unsaturation with increasing VPD, it is necessary to include this in the calculation of gs in order to discern its true response. This is shown in Figure 8A, which differs fundamentally from Figure 2C, where saturation of ei was assumed. Figure 2C would incorrectly indicate that gs decreased in response to VPD in the abi1 plants (shown as white symbols in Fig. 8A), similar to the wild-type response. Accounting for unsaturation revealed the opposite: that gs increased in response to VPD. Although counterintuitive, this is indeed the response predicted for angiosperm leaves in the absence of a metabolic system actively controlling guard cell osmotic pressure (Buckley et al., 2003; Buckley, 2005; Franks and Farquhar, 2007; Franks, 2013). This is because epidermal cells have a mechanical advantage over guard cells, such that if turgor pressure of both cell types declines uniformly, a passive widening of the stomatal pore ensues. The hydro-active response of guard cell osmotic pressure in the abi1 plants was presumably disabled through the disruption of the ABA signaling pathway. As foreshadowed by Pantin and Blatt (2018), appreciable unsaturation of ei could mask the true response of gs to VPD in ABA insensitive lines and could make it appear as if stomata are responding similarly to wild type when they are not. Our results raise the possibility that previous assessments of the response of gs to VPD in ABA-insensitive or ABA-deficient plants may have been misconstrued because of unsaturation of ei (Assmann et al., 2000; McAdam et al., 2015; Merilo et al., 2015, 2018; McAdam et al., 2016). However, this would only apply to gas exchange responses, not to responses of stomatal apertures determined through microscopy (Takahashi et al., 2015).

CONCLUSION

We took advantage of an ABA-insensitive line of Populus × canescens with impaired stomatal function to explore the role of stomata in controlling discrimination against 13CO2 and C18OO during leaf gas exchange. There were marked effects in discrimination for both isotopologues related to the smaller drawdown in CO2 concentration from ambient air to the intercellular air spaces in the abi1 plants compared to wild-type plants. The experimental system also provided a window into the dynamic functioning of stomata in the wild-type plants to prevent unsaturation of ei as evaporative demand was increasingly ratcheted up in the leaf gas exchange chamber. The abi1 plants with impaired stomatal function showed clear evidence of unsaturation of ei, whereas wild-type plants showed no such evidence, even at rather extreme VPDs. In addition, the abi1 plants provided at least qualitative validation of our technique for estimating ei from concurrent measurements of leaf gas exchange and Δ18O. Comparison of wild-type with abi1 plants highlighted the pivotal role that the wild-type stomatal response plays in preventing unsaturation of ei in response to increasing VPD.

MATERIALS AND METHODS

Plant Material

Transgenic gray poplar (Populus × canescens) plants were transformed with the Arabidopsis (Arabidopsis thaliana) mutant abi1 gene, resulting in insensitivity to ABA. Full details of the genetic transformation can be found in Arend et al. (2009). The wild-type and abi1 plants were micropropagated, and then transplanted into 3.5 L pots with commercial potting mix and slow release fertilizer. We grew the plants in high relative humidity under natural light in a glasshouse. They were watered frequently, such that trays beneath the pots always retained some liquid water. Approximately 1 week before gas exchange measurements, the plants were transferred to a growth chamber with air temperature of 25°C, average relative humidity of 80%, and photoperiod of 16 h, with average photosynthetically active radiation of 250 µmol m−2 s−1. The abi1 plants were fitted with clear plastic sleeves to further increase the relative humidity around their canopies.

Gas Exchange System and Isotopic Analyzers

Leaf gas exchange measurements were made with a portable photosynthesis system (GFS-3000, Heinz Walz GmbH) positioned inside the growth chamber. The cuvette was large enough to accommodate an entire leaf and was temperature controlled (3010-GWK1 Gas-Exchange Chamber, Heinz Walz GmbH). While in the chamber, the leaf was illuminated by a light-emitting diode panel (RGBW-L084, Heinz Walz). The system included a by-pass drying loop, through which cuvette air could be circulated to remove excess water vapor resulting from transpiration. Two Nafion driers were placed in series in the drying loop (PD-200T-24MSS, Perma-Pure). The Nafion driers were flushed with CO2-free air with a dew point of less than −25°C. Air returning to the chamber typically had a dewpoint near −20°C. The water vapor concentration of the air stream before and after the Nafion driers was measured with dew point mirrors (Dewpoint mirror unit TS-2M/TS-2, Heinz Walz), and air flow through the drying loop was controlled by a Bypass-Humidity Control System (Heinz Walz). All metal surfaces in the dew point mirror housings and in the leaf chamber were nickel-plated to minimize adhesion of water vapor and thereby improve system performance, both in terms of gas exchange and isotopic measurements. Boundary layer conductance inside the cuvette was determined using the wet filter paper method (Parkinson, 1985).

The gas exchange system was coupled to laser spectrometers for measurements of both the isotopic compositions of CO2 (QCLAS-ISO, Aerodyne Research) and water (L2120-i, Picarro). A valve and gas mixing interface was constructed to allow sampling of air streams entering and exiting the leaf chamber, as well as to allow introduction of calibration gases to the isotope analyzers. For isotopic measurements of CO2, air passed through an additional Nafion drier before introduction to the CO2 laser spectrometer. Additional details and description of the CO2 laser spectrometer can be found elsewhere (Nelson et al., 2008; Tuzson et al., 2008; Sturm et al., 2012). For measurements of δ18O of water, air was drawn directly into the laser spectrometer, with further details as described previously (Crosson, 2008; Gupta et al., 2009; Holloway-Phillips et al., 2016).

To calibrate the portable photosynthesis system, we set the zero values daily for the measured CO2 and water vapor concentrations using dry, CO2 free air, and we set the span weekly using air of known CO2 concentration and a dew point generator (Li-610, Li-Cor) for defined water vapor pressures.

We calibrated the CO2 laser spectrometer daily for both concentration dependence and for span and offset with respect to known calibration standards. For concentration dependence, air from a tank with 5000 ppm CO2 was diluted with CO2 free air to produce a range of stable concentrations before being introduced into the analyzer. Calibration typically covered the range from 100 to 900 ppm CO2. A polynomial function was then fitted to the measured isotope ratios, such that they could be normalized to the singular, known isotope ratio for the tank. To account for the span and offset of measured isotope ratios compared with known values, two gases of differing isotopic composition and concentration of CO2 were introduced into the analyzer sequentially. A linear function was then fitted for normalizing measured isotope ratios to true values following the correction for concentration dependence. Further details on the calibration procedure can be found in Sturm et al. (2012). The span and offset calibration gases had the following values, determined by dual inlet isotope ratio mass spectrometry: 333 ppm CO2, δ13C of −39.5‰, and δ18O of 12.2‰; and 750 ppm CO2, δ13C of −12.9‰, and δ18O of 23.5‰. A third gas of known CO2 concentration and isotopic composition was introduced into the analyzer daily to provide an estimate of the long-term precision of the instrument over the course of the experiment. Day-to-day precision based on these measurements (± 1 SD) was 0.40‰ for δ13C and 0.45‰ for δ18O.

We used a similar approach for the water vapor isotope analyzer of calibrating for concentration dependence and span and offset. Air with water vapor concentrations ranging from 10 to 37 mmol mol−1 was introduced to the analyzer from the dew point generator. We then fit a linear regression to these data, and used it to normalize isotope ratios of water vapor measured at different concentrations. We determined the span and offset correction using waters of differing oxygen isotope composition, as determined by CO2 equilibration and subsequent analysis by dual inlet isotope ratio mass spectrometry. The span and offset calibration waters had δ18O of −10.3‰ and −27.2‰. They were introduced into the analyzer by bubbling dry air through otherwise sealed vessels containing the waters. The water in the vessels was changed every few days to prevent drift in δ18O associated with distillation. The long-term instrument precision (± 1 SD) over the course of the experiment was 0.28‰ for δ18O of water vapor.

Measurement Protocol

An entire leaf was placed in the gas exchange cuvette following calibration and operational checks with an empty cuvette. The cuvette temperature was set to 25°C and vapor pressure of the air entering the cuvette and the flow through the bypass drying loop were adjusted so that the chamber air had a VPD of approximately 0.5 kPa. The CO2 concentration in the chamber was kept constant at 400 µmol mol−1 and the light intensity (photosynthetically active radiation) was set to 1200 µmol m−2 s−1. The leaf was allowed to adjust to the chamber conditions until a steady gas exchange rate was achieved, usually 30 to 40 min. When we were satisfied that gas exchange was steady, the sample line was introduced to the isotope analyzers and air exiting the leaf chamber was measured for CO2 and water vapor stable isotope ratios for ∼10 min. During this time, gas exchange data on the portable photosynthesis system was recorded at 1-s intervals for 30 s. The valve configuration was then changed so that the precuvette air stream was introduced to the isotope analyzers for ∼10 min. At the conclusion of that time, the vapor pressure of air entering the chamber and the flow through the bypass drying loop were again adjusted so that the VPD of air inside the chamber was increased by about 0.5 kPa for wild-type plants, and by about 0.25 kPa for abi1 plants, and the process was repeated. For abi1 plants, this continued until photosynthesis diminished to below 1 µmol CO2 m−2 s−1, and transpiration could no longer be sustained at a steady rate; for wild-type plants it typically continued until VPD was higher than 6 kPa. To achieve these higher VPDs for wild-type plants, it was necessary to increase the temperature of the cuvette by 3°C increments with each VPD step until a maximum of 39°C.

Calculations

The transpiration rate, E, was calculated from measurements of water vapor mole fractions and flow rates as (von Caemmerer and Farquhar, 1981)Embedded Image(17)

where uin and ub are the flow rates of air entering the cuvette and the bypass drying loop, respectively; win, wa, and wb are the water vapor mole fractions of air entering the cuvette, leaving the cuvette, and leaving the bypass drying loop, respectively; and s is the leaf area inside the cuvette. We calculated the δ18O of transpired water, δ18OE, asEmbedded Image(18)

where δ18Ov is the δ18O of water vapor in air exiting the cuvette, δ18Oin(v) is that of water vapor in air entering the cuvette, and δ18Ob(v) is that of water vapor in air entering the cuvette from the bypass drying loop. This calculation differs from that applied previously (Simonin et al., 2013; Dubbert et al., 2014; Barbour et al., 2016), in that it includes the removal of water vapor from the chamber by the Bypass-Humidity Control System. This system was operated in the compensation mode in which air was cycled through the bypass drying loop such that win and wa were approximately equal. In this loop the water vapor was removed with a Nafion device (see above). We tested for fractionation of the δ18O of water vapor caused by passage through the bypass drying loop by using the dew point generator to feed water vapor into an empty cuvette to mimic a transpiring leaf (Wang et al., 2012) while cycling air through the bypass drying loop at different rates. The δ18O of water vapor exiting the cuvette varied by less than 0.3‰ irrespective of whether the drying loop was off, cycling at an intermediate rate (1200 µmol s-1), or cycling at its maximum rate (5200 µmol s-1). Thus, we solved Equation 18 by assuming δ18Ob(v)=δ18Ov. The dew point of air leaving the bypass drying loop was typically about −20°C, further indicating minimal potential for the return of fractionated water vapor back to the cuvette from the bypass drying loop.

The rate of CO2 assimilation, A, was calculated from measurements of the CO2 mole fractions entering (cin) and leaving (ca) the cuvette (von Caemmerer and Farquhar, 1981):Embedded Image(19)

Discrimination against 13C or 18O during CO2 assimilation (ΔA) was calculated following Evans et al. (1986):Embedded Image(20)Embedded Image(21)Embedded Image(22)

where cin and ca are CO2 mole fractions entering and leaving the gas exchange cuvette, here expressed with respect to dry air, δin is δ13C or δ18O of CO2 entering the cuvette, δa is δ13C or δ18O of CO2 leaving the cuvette, and δA is δ13C or δ18O of assimilated CO2.

To parameterize the Craig-Gordon equation (Craig and Gordon, 1965) for predicting the δ18O of evaporative site water within leaves, we calculated the equilibrium fractionation factor, ε+, as (Bottinga and Craig, 1969),Embedded Image(23)

where Tl(K) is leaf temperature expressed in Kelvins. We calculated the kinetic fractionation factor, εk, as (Farquhar et al., 1989)Embedded Image(24)

For calculating the δ18O of CO2 in equilibrium with evaporative site water, we calculated the fractionation factor εw as (Brenninkmeijer et al., 1983)Embedded Image(25)

where Tl is leaf temperature in degrees celsius.

To account for the influence of respiration on Δ13C and estimates of gm, we assumed day respiration rates, Rd, of 0.62 and 0.83 at 25°C for wild-type and abi1 plants, respectively. These estimates were based on measurements of dark respiration in leaves of three plants from each treatment. We assumed the temperature response of Rd was as described previously (Sharkey et al., 2007). To account for a change in δ13C of source CO2 caused by placing the leaf in the gas exchange cuvette, we replaced e in Equations 15 and 16 with eRd+e* (Wingate et al., 2007), where eRd is fractionation during day respiration and e* can be defined as δ13Ca-Δ13Cobs-δ13Csubstrate (Cernusak et al., 2013) with δ13Ca being δ13C of CO2 exiting the cuvette during measurements, Δ13Cobs the observed discrimination, and δ13Csubstrate the δ13C of likely respiratory substrates. We assumed δ13Csubstrate to be −28‰ for wild-type plants and −31‰ for abi1 plants based on measurements of δ13C in leaf dry matter.

Statistical Analysis

We analyzed responses of gas exchange and isotopic discrimination to VPD using linear mixed models, with treatment (wild type or abi1), VPD and their interaction as independent fixed effects and leaf number as a random effect. The covariance structure for random effects and errors was variance components. In analyses of gas exchange parameters, we excluded points for which photosynthesis was less than 0.5 µmol CO2 m−2 s−1, to avoid cases where gas exchange was too low to be measured accurately. For analyses of isotopic discrimination, we excluded points for which photosynthesis was less than 1.5 µmol CO2 m−2 s−1, to avoid cases where Embedded Image was very large (> 20) and confidence in isotopic discrimination estimates was therefore low. Statistical analyses were carried out in Systat 12 (Systat Software Inc.).

Supplemental Data

The following supplemental materials are available.

ACKNOWLEDGMENTS

We thank Arthur Gessler for the use of the Picarro laser spectrometer, Nina Buchmann for permission to use the growth chamber, Stan Schymanski for assistance with the laser scanning microscope, Meisha Holloway-Phillips for helpful advice on the data analysis, and three anonymous reviewers for helpful comments on the article.

Footnotes

  • www.plantphysiol.org/cgi/doi/10.1104/pp.19.00436

  • The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Lucas A. Cernusak (lucas.cernusak{at}jcu.edu.au).

  • L.A.C. conceived the project and wrote the article with contributions of all authors; L.A.C., G.R.G., and R.T.W.S. performed the experiments; L.A.C. and G.R.G. designed the experiments and analyzed the data; M.A. prepared the transgenic plants for the experiments; M.A. and R.T.W.S. conceived the original research plans.

  • ↵1 This work was supported by the Swiss National Science Fund (grant no. 31003A_153428 to R.T.W.S.); the Australian Research Council (grant no. DP150100588 to L.A.C.); and the European Community’s Seventh Framework Program (FP7/2007-2013 to G.R.G.) under grant agreement number 290605 (COFUND: PSI-FELLOW).

  • ↵3 Present address: Schmid College of Science and Technology, Chapman University, Orange, California 92866.

  • ↵4 Senior author.

  • ↵[OPEN] Articles can be viewed without a subscription.

  • Received April 11, 2019.
  • Accepted September 8, 2019.
  • Published September 27, 2019.

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Effect of Vapor Pressure Deficit on Gas Exchange in Wild-Type and Abscisic Acid–Insensitive Plants
Lucas A. Cernusak, Gregory R. Goldsmith, Matthias Arend, Rolf T. W. Siegwolf
Plant Physiology Dec 2019, 181 (4) 1573-1586; DOI: 10.1104/pp.19.00436
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