Is mesophyll conductance to CO2 in leaves of three Eucalyptus species sensitive to shortterm changes of irradiance under ambient as well as low O2?

Get Complete Project Material File(s) Now! »

Using the complete form of the discrimination model

To take into account fractionation steps and processes neglected in the simple model, a more detailed model was developed by Farquhar et al. (1982). This model for ∆13C accounts for mesophyll conductance (gm) and the influence of decarboxylation processes due to photorespiration as well as respiration. The complete model for ∆13C is computed following Evans et al. (1986) and Farquhar et al. (1982): ERD  FΓ* CA −CS CS −CI CI −CC CC ∆ A  A  (E  A )  B − K B S I CA ! !!!!!!!!!!!!Eq.4! CA CA CA CA.
where ab is the discrimination due to diffusion in the boundary layer, es and ai the discrimination due to dissolution and diffusion in the liquid phase, respectively, e and f the discrimination during “dark respiration” (Rd) and photorespiration, respectively and k the carboxylation efficiency (k=(A+Rd)/(Ci-Γ*)) following (Farquhar et al., 1982). This model predicts a smaller discrimination than the simple formulation due to: (i) the CO2 draw-down between the intercelullar air-space and the site of carboxylation (i.e., the influence of gm) and (ii) the decarboxylation processes. Because some fractionation occurs during Rd and the photorespiration, the respired CO2 has a different isotopic signature than the respiratory substrate. This shift has to be accounted for to fully explain the observed ∆13C. A global representation of the different carbon flows and associated fractionation factors described here is shown in Figure 2. The main problem of using this model is the parameterization, i.e., choosing the real value for each parameter. For most of the parameters, especially b, e and f, we do not know with certainty their absolute value or if they vary among genotypes or with environmental conditions. We provide here the range of values found in the literature. These values were used afterwards to set the sensitivity analysis (see Table 2).
Figure 2: Schematic representation of the different carbon fluxes and discrimination against 13C in a leaf during photosynthesis. In blue are represented the carbon molar fractions (in µmol mol-1) the atmosphere (Ca), the boundary layer (Cs), the intercellular air-space (Ci) and the chloroplast (Cc). In red are represented the different 13C/12C fractionation factors (in ‰) associated to CO2 gaseous diffusion in the boundary layer (ab), in air through the stomata (a), CO2 hydration in HCO3- (es), CO2 diffusion in liquid phase (ai), carboxylation by RubisCO (b3) and by PEPc (b4*), during decarboxylation of glycine in serine (f) and to non-photorespiration decarboxylation (e).

Diffusion of CO2 from the atmosphere to the chloroplast

The fractionation factor for diffusion in the air (a in ‰, see Table 2) is assessed from theoretical assumptions. Discrimination during CO2 diffusion in air occurs because gas diffusion in air is modulated by the ratio of molar masses of 12CO2 and 13CO2 (see O’Leary, 1981 and Farquhar et al. 1982). Because 13CO2 is heavier than 12CO2 (molar masses of 45 and 44, respectively), the subsequent difference of diffusion leads to a discrimination (against 13CO2) of 4.4‰ during diffusion in the air. This estimation was taken as discrimination factor for gas diffusion by Farquhar et al. (1982) in their model. Such a relationship is not likely to vary with temperature, pressure or CO2 mole fraction (O’Leary, 1981). The parameter a in the model is therefore considered constant and independent of environmental conditions and genotypes.
Fractionation associated to dissolution of gaseous CO2 in water (parameter es) was estimated to be 1.1‰ (Evans et al., 1986), based on Vogel (1980). This corroborates an estimation by (Mook et al., 1974) with es=1.06‰ at 25ºC, where δ13C was measured before and after dissolution. This fractionation factor is relatively insensitive to temperature and varies from 1.18‰ to 1.04‰ between 0ºC and 30ºC (Mook et al., 1974).
Once dissolved, CO2 has to diffuse in the liquid phase to the chloroplast stroma, with a fractionation factor ai. Reported estimations of ai are rare, but (Evans et al., 1986) set ai=0.7‰ based on previous estimations from O’Leary (1984). However, the hydrated form (HCO3-) diffuses faster in the liquid phase than the molecular form CO2.
Hydration of aqueous CO2 induces a fractionation of -9‰ at 25 ºC (Mook et al., 1974), leading to an overall hydration fractionation with respect to gaseous CO2 of -7.9‰, the negative sign meaning 13C accumulation in HCO3-. This parameter is not directly visible in Eq. 4, because it is associated with fractionation by phosphoenolpyruvate carboxylase (PEPc) fixation (see below).

Discrimination during carboxylation

Since the early 60’s, it has been proposed that CO2 fixation causes the largest discrimination in plants (Park and Epstein, 1960). Fractionation by carboxylation is noted b in the discrimination model. Two main enzymes are involved in the fixation of carbon in C3 plants: RubisCO that fixes CO2 in the chloroplast stroma and PEPc that fixes HCO3- in the cytosol (see Figure 2), with fractionation factor b3 for RubisCO and b4 for PEPc. For b3, a review by O’Leary (1981) reported in vitro estimations around 30‰, but specified that there is a large uncertainty. A recent study reported very close values for purified RubisCO from tobacco, with b3=27.40.9‰ (McNevin et al., 2007). They compared their values with other published estimations and found a range from 27.5‰ to 29‰ (data for spinach and soybean), with respect to dissolved CO2. When expressed with respect to gas phase CO2, this leads to b3= 28.5‰ to 30‰, with upper and lower SDs covering a range from 26‰ to 30.5‰.
Fractionation by PEPc (noted b4* in Farquhar et al., 1989) is much smaller than by RubisCO, with b4* between 2 and 2.5‰ (O’Leary, 1981), considering HCO3-as the main substrate. These estimations were recently confirmed, with b4*=2.60.2‰ (McNevin et al. 2006), by monitoring CO2 isotope concentrations via membrane inlet mass-spectrometer in a cuvette with carboxylating PEPc and the basic form of the Rayleigh equation. Usually, the term b4* is expressed with respect to gas-phase CO2, taking into consideration the fractionation due to hydration of CO2 (-7.9‰), thus b4=-5.7‰ (Farquhar, 1983).

Could variations of b with irradiance or O2 cancel short-term response of gm?

There is an increasing number of studies testing and observing a rapid (within minutes) response of gm to changes of environmental conditions (CO2 and irradiance, in particular, see Flexas et al., 2008 for review). In these studies it has been considered that other fractionation factors used in the gm equation remain stable with time. This is a crucial hypothesis to validate the rapid response of gm, but has not yet been tested. Here we focus on possible variations of b during changes of irradiance to test if b could vary enough to fully account for the observed changes of ∆13C. We based this analysis on irradiance response curves from 200 to 1000 µmol m-2 s-1 PPFD performed on Eucalyptus sieberii with a calibrated TDLAS, under 21% and 1% O2 to vary the influence of photorespiration, with all parameters constant with O2, except Γ*=38.7 and 1.85 µmol mol-1 respectively (Figure 7). Considering that gm was stable with irradiance and equal to the maximum value measured at an irradiance of 1000 µmol m-2 s-1 (Figure 7, gm= 0.37 µmol m-2 s-1 under 21% O2), b should vary from 28‰ at high irradiance to 26‰ at low irradiance. The same pattern was observed under 1% O2, according to a constant gm= 0.49 µmol m-2 s-1, with b should be 27‰ at low irradiance. Under 21% O2, a decrease of b from 28 to 26‰ could be explained by an increase of β (relative amount of carbon fixed by PEPc) from 0.055 to 0.11 (i.e. 5.5% to 11% carbon fixed by PEPc), for b3= 30‰ and b4=-5.7‰ and constants with irradiance. There are however several possible combinations of b and β to explain this variation (see Figure 8). These values of b and β are comprised in a realistic range of variation, according to the literature (Table 2), suggesting that b variations with irradiance are plausible. Such phenomena could occur since RubisCO carbon fixation is directly dependent of irradiance (via electron transport chain) but not that of PEPc. Thus, β could be higher at low compared to high irradiance. However, to the best of our knowledge, such hypothesis was not directly tested yet. This possibility was mentioned by Von Caemmerer and Evans (1991) and Lloyd et al. (1992), but the authors concluded in favour of a constant β. Von Caemmerer and Evans (1991) cited estimation of β at low light being of the same range as in high light and Lloyd et al. (1992) concluded that the variations of b needed was very unlikely because too large (from 20 to 35‰, for Citrus) to fully explain the variations of ∆13C attributed to gm. Nevertheless, there is a real need to estimate β with independent methods. At the moment, only estimations via RubisCO and PEPc activities are used to assess the relative part of carbon fixed by each enzyme, but we don’t know if maximum activities can be systematically related to the effective amount of carbon fixed.

READ  Mitotic and meiotic spindle dynamics comparison in fission yeast

Importance of non-photorespiratory decarboxylation: e and Rd

Fractionation during respiration other than from photorespiration (Rd), so-called “day respiration”, has only a small influence on the estimation of gm, as highlighted by the sensitivity analysis. Using the standard parameterization (Table 3) and changing Rd from 0 to 2 µmol m-2 s-1 affected gm by only 1% (see Figure 6). Even with extreme values of b, f or Γ*, Rd has a small influence. An exception was when Rd and e varied together. With e=-15‰, increasing Rd decreased gm by 0.1 mol m-2 s-1 (20%) and when e=+15‰, enhanced Rd increased gm by 0.15 mol m-2 s-1 (35%). This close relationship is obviously induced by the e*Rd factor in the equation. The e parameter has a larger effect on gm estimation than Rd. Variation between extreme values (e=-15 and +15‰) changed gm by almost 0.1 mol m-2 s-1 (i.e 30% variation). This effect is larger when f=15‰ or b=26‰ is used (60% or 100% increase compared to the standard parameterization, respectively). It has been reported that δ13C of respired CO2 could change with leaf temperature and by maintaining the leaf under prolonged darkness (Tcherkez et al., 2003). These variations are mainly caused by a change of respiratory substrate, with decarboxylation of sucrose resulting in enriched respired CO2 and that of lipids or proteins resulting in depleted respired CO2. Such changes could impact ∆13C recorded during photosynthesis, and should be included in the discrimination model via the e parameter. This is the same rationale as (Wingate et al., 2007) who considered that if the δ13C of source CO2 during the experiment is different from that during growth, then the respired CO2 would be affected because of a mix between freshly synthesised and older carbon pool. We tested the possibility that such changes in isotopic signature of respired CO2 during an experiment could give rise to artefactual short-term variations gm. We estimated that e would have to change from ~3‰ to 25-30‰ under 21% O2, and from ~3‰ to 15‰ under 1% O2 with decreasing irradiance to negate the computed variation of gm. Values of e for 21% O2 are clearly out of the range found in the literature for darkened leaves. Under 1% O2, the values of e are within the range found in the literature (for darkened leaves), except if we consider estimations based on sucrose as respiratory substrate (then e=2-5‰). If we now compare to recent estimations of e during the light period (e<1‰, Tcherkez et al., 2011; Tcherkez et al., 2010), these variations of e are even more unlikely. However, such rapid variations would need large change of the respiratory substrate during the experiment but this phenomenon remains very unlikely due to the constant temperature used in our experiment, and the fact that carbohydrate starvation probably did not occur. This clearly shows that potential changes of e cannot lead to the short-term response of gm to irradiance. We then considered that using values of e close to 0 for estimating mesophyll conductance is probably adapted. It is the same story for Rd. To fully explain the change in gm, Rd would have to increase up to 20 µmol m-2 s-1 under 21% O2 which is not possible. Under 1% O2, Rd would have to increase to 2.2 and 4.5 µmol m-2 s-1 at 600 and 200 µmol m-2 s-1, respectively. These values are far higher than values reported in the literature. Moreover, there is no study observing increasing Rd in such proportions, with decreasing irradiance (between 1000 and 200 µmol m-2 s-1). We conclude that Rd can’t explain short-term variations of gm under either 21% or 1% O2.

Importance of photorespiration: f and Γ*

The fractionation during photorespiration, noted f, is the second most influential parameter in the estimation of gm, according to the sensitivity analysis (Figure 4). Enhanced f increases the value of gm, with gm lowered by 20% when f=0‰ and increased by 30% when f=15‰ (Figure 7). In terms of absolute values this represents a change of gm by 0.3 mol m-2 s-1 with f varying from 0 to 15‰ for b=30‰, but for b=26‰ gm changed by ≈0.5 mol m-2 s-1 (higher sensitivity of gm to f with low b). Comparatively, Γ* has only a small effect on the estimation of gm, with variations remaining 0.05 mol m-2 s-1 when Γ* varies between 35 and 50 µmol mol-1. There is a larger effect with f=15‰, with gm varied by 0.1 µmol mol-1.
Changers in f are unlikely to explain gm variations with irradiance, with respect to the large range of values needed (Figure 6). f should switch from 11‰ under high irradiance up to 26‰ under low irradiance (21% O2), which is double recent estimates (Lanigan et al., 2008; Tcherkez, 2006). Moreover, it has been never suggested that f could vary with irradiance. We found a very large value, with f=150‰ at 1% O2, clearly a computation consequence, regarding of the low Γ* (1.85 µmol mol-1) associated with f. To account for variation in gm at low irradiance, Γ* would have to increase to 60 µmol mol-1 (compared to 38.7) at 21% O2 and 25 µmol mol-1 (compared to 1.85) at 1% O2 . This represents very large increases compared to the value under high irradiance, and since Γ* reflects RubisCO affinity for CO2/O2, it is not likely to vary with O2. This evidence that neither variations of Γ* or f could explain gm variations with irradiance.

Table of contents :

CHAPTER I Relationship between 13C discrimination and leaf gas exchange: Analysis of the model, influence of the parameters and implications for estimating mesophyll conductance to CO2.
INTRODUCTION
Diversity of the Wi-Δ13C relationships found in the literature
Using the complete form of the discrimination model
On the importance of the b parameter
Importance of non-photorespiratory decarboxylation: e and Rd
Importance of photorespiration: f and Γ*
Concluding remarks
CHAPTER II Mesophyll conductance to CO2, assessed from on-line TDL-AS records of 13CO2 discrimination, displays small but significant short term responses to CO2 and irradiance in Eucalypt seedlings.
ABSTRACT
INTRODUCTION
MATERIAL & METHODS
RESULTS
DISCUSSION
Importance of the respiratory and photorespiratory terms in the estimation of mesophyll
conductance
Response of gm to CO2 mole fraction.
Response of gm to irradiance
CONCLUSION
CHAPTER III Is mesophyll conductance to CO2 in leaves of three Eucalyptus species sensitive to shortterm changes of irradiance under ambient as well as low O2?
ABSTRACT
INTRODUCTION
MATERIAL AND METHODS
RESULTS
DISCUSSION
Rapid response of mesophyll conductance to irradiance under 21 and 1% O2
Sensitivity of gm estimates to changes of model parameter values
Are the observed variations of gm with O2 realistic?
CONCLUSION
CHAPTER IV
Mesophyll conductance of poplar leaves varies rapidly with changes in CO2 and
irradiance: an assessment from on line 13CO2 discrimination records with TDL-AS.
ABSTRACT
INTRODUCTION
MATERIAL & METHODS
RESULTS
DISCUSSION
Rapid variations of gm with PPFD and CO2
Impact of a stable gm on net CO2 assimilation rate under PPFD variations
CONCLUSION
CONCLUSIONS
and PERSPECTIVES
ANNEX I
REFERENCES

GET THE COMPLETE PROJECT

Related Posts