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WHOLE PLANT AND ECOPHYSIOLOGY

Carbon Isotope Fractionation during Photorespiration and Carboxylation in Senecio^1,[W],[OA]

Physiological Ecology Group, Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom

	ABSTRACT

TOP ABSTRACT RESULTS DISCUSSION CONCLUSION MATERIALS AND METHODS LITERATURE CITED

 
The magnitude of fractionation during photorespiration and the effect on net photosynthetic ¹³C discrimination () were investigated for three Senecio species, S. squalidus, S. cineraria, and S. greyii. We determined the contributions of different processes during photosynthesis to by comparing observations (_obs) with discrimination predicted from gas-exchange measurements (_pred). Photorespiration rates were manipulated by altering the O₂ partial pressure (pO₂) in the air surrounding the leaves. Contributions from ¹³C-depleted photorespiratory CO₂ were largest at high pO₂. The parameters for photorespiratory fractionation (f), net fractionation during carboxylation by Rubisco and phosphoenolpyruvate carboxylase (b), and mesophyll conductance (g_i) were determined simultaneously for all measurements. Instead of using _obs data to obtain g_i and f successively, which requires that b is known, we treated b, f, and g_i as unknowns. We propose this as an alternative approach to analyze measurements under field conditions when b and g_i are not known or cannot be determined in separate experiments. Good agreement between modeled and observed was achieved with f = 11.6 ± 1.5, b = 26.0 ± 0.3, and g_i of 0.27 ± 0.01, 0.25 ± 0.01, and 0.22 ± 0.01 mol m^–2 s^–1 for S. squalidus, S. cineraria, and S. greyii, respectively. We estimate that photorespiratory fractionation decreases by about 1.2 on average under field conditions. In addition, diurnal changes in are likely to reflect variations in photorespiration even at the canopy level. Our results emphasize that the effects of photorespiration must be taken into account when partitioning net CO₂ exchange of ecosystems into gross fluxes of photosynthesis and respiration.

But additional processes also affect net values: leaf boundary layer diffusion, internal (mesophyll) diffusion, photorespiration, and day respiration. Integrating all contributions, net ¹³C discrimination can be calculated (Farquhar et al., 1982; Wingate et al., 2007) as:

(1)

where C_a, C_s, C_i, and C_c are the CO₂ mole fractions in ambient air, at the leaf surface, in the intercellular air space, and at the sites of carboxylation, respectively, * is the compensation point in the absence of dark respiration, and R_d is the rate of day respiration. In addition to stomatal diffusion (a) and carboxylation (b), there are fractionations associated with CO₂ diffusion through the leaf boundary layer (a_b 2.9) and mesophyll (a_m, consisting of CO₂ dissolution [1.1; Vogel, 1980] and liquid phase diffusion [0.7; O'Leary, 1984]) into the chloroplasts, as well as photorespiration (f) and day respiration (e). A full list of symbols and abbreviations is given in Supplemental Table S1.

Several of these processes are still major sources of uncertainty for estimating . For example, there is no consensus on the fractionation factors during photorespiration (f) and day respiration (e), which can amplify diurnal patterns in (Wingate et al., 2007). The net fractionation during carboxylation (b) may be lower than that of Rubisco (b₃ 29) due to contributions from phosphoenolpyruvate carboxylase (PEPc; b₄ –5.7; O'Leary et al., 1991). In addition, the mesophyll conductance (g_i) of leaves needs to be determined to calculate C_c, the CO₂ mole fraction at the sites of carboxylation [A = g_i(C_i – C_c)]. For photorespiration, f values of 7 (Rooney, 1988), 8 (Gillon, 1997), and 10 to 14 (Igamberdiev et al., 2004) have been reported from a limited number of in vivo experiments on intact leaves, with 11 expected from theory (Tcherkez, 2006).

Here, we present new in vivo estimates of the fractionation factor associated with photorespiration (f) and the net fractionation during carboxylation (b), determined from leaf level measurements for three species in the genus Senecio, with contrasting leaf morphology, photosynthetic rates, and stomatal sensitivities. Photorespiration rates were manipulated by varying the O₂ partial pressure (pO₂) during the experiments. The parameters f, b, and g_i were treated as unknowns and determined simultaneously for all measurements. We propose this as an alternative approach to analyze measurements under field conditions when b and g_i are not known or cannot be determined in separate experiments.

	RESULTS

TOP ABSTRACT RESULTS DISCUSSION CONCLUSION MATERIALS AND METHODS LITERATURE CITED

 

Leaf Physiology and Gas-Exchange Characteristics

Patterns in gas-exchange characteristics common to all species (Table I ) included higher maximum rates of photosynthesis, higher stomatal conductance, and lower * (compensation point in the absence of dark respiration, derived from A/C_i curves) at low pO₂ due to reduced rates of oxygenation. Day respiration rates (R_d) were generally low and showed little effect of pO₂. In addition, gas-exchange and leaf variables exhibited systematic differences between the species. S. squalidus had the lowest specific leaf mass, *, and R_d and the highest photosynthetic capacity and stomatal conductance, whereas S. greyii had the highest specific leaf mass, *, and R_d and the lowest photosynthetic capacity.

At all pO₂ levels, S. squalidus and S. cineraria had higher _obs values (calculated using Eq. 5 below) than S. greyii (Fig. 1 ). In a qualitative comparison at similar C_i/C_a ratios, _obs measured under nonphotorespiratory conditions (20 mbar pO₂) was 1 to 2 higher than at typical atmospheric oxygen concentrations (210 mbar pO₂), illustrating the decrease in _obs due to isotopically depleted CO₂ released during photorespiration. Except for S. greyii, this offset increased further at 300 mbar pO₂.

View larger version (11K): [in this window] [in a new window] [as a PowerPoint slide]   Figure 1. Net 13C discrimination, obs, against the ratio of intercellular to ambient CO2 mole fraction (Ci/Ca) for S. squalidus (A), S. cineraria (B), and S. greyii (C) measured at 20, 210, and 300 mbar pO2.

View larger version (25K): [in this window] [in a new window] [as a PowerPoint slide]   Figure 2. Regression parameters for obs and pred calculated from Equation 1 for a range of combinations of b and f (using e = 0). The plot contains the slopes of the regression (red horizontal lines), their intercepts (dark blue vertical lines), and the mean absolute deviation (gray concentric ovals) between obs and pred. The best fit parameters are found at the minimum of the mean absolute deviation "valley" where the 0 intercept and slope of 1 lines cross.

View larger version (18K): [in this window] [in a new window] [as a PowerPoint slide]   Figure 3. The correlation between obs and pred for the best fit parameters (b = 26.0, f = 11.6) using e = 0. The solid line denotes the 1:1 correlation.

	DISCUSSION

TOP ABSTRACT RESULTS DISCUSSION CONCLUSION MATERIALS AND METHODS LITERATURE CITED

 
This article attempts to quantify the contributions from different processes on net ¹³C discrimination during photosynthesis. In particular, leaf level measurements of gas exchange and were used to determine the fractionation factor f for photorespiration in vivo under controlled laboratory conditions. Keeping everything else constant, different rates of photorespiration were achieved in our experiments by varying the oxygen partial pressure in the air surrounding the leaves. At low pO₂, the decreased oxygenase activity (as indicated by smaller *; Table I) was manifested in 1 to 2 higher _obs at similar C_i/C_a compared with ambient or elevated pO₂ conditions (Fig. 1).

The simultaneous effects of different processes on cannot be separated easily, because contains several unknown parameters: the fractionation factors b, f, and e and mesophyll conductance, g_i. This problem is often addressed successively: g_i is derived using a prescribed value of b (usually 29), and the residual is then assumed to reflect the contribution from photorespiration. A commonly used method to derive g_i is based on a regression of _i – _obs versus A/C_a (Evans et al., 1986), where _i is the predicted value assuming C_c = C_i (i.e. no resistance to CO₂ transfer during internal [mesophyll] diffusion to the sites of carboxylation):

(2)

Assuming that Equation 1 reflects _obs (neglecting boundary layer effects for simplicity) and using A = g_i (C_i – C_c), combining Equations 1 and 2 yields:

(3)

However, this approach requires that the value of b is known and that the contributions from respiratory terms do not change in a systematic way (with A). Otherwise, any errors in the estimate of b are propagated into errors in g_i and affect subsequent calculations, such as the solution for f. Alternatively, the difference between the actual value of b and that assumed in Equation 2 (b') can be estimated from the y intercept of (_i – _obs)C_a/C_i against A/C_i (von Caemmerer and Evans, 1991):

(4)

But this requires that the contributions from photorespiration and day respiration can be neglected, which is often not valid, particularly under field conditions or in our experiments specifically designed to produce a wide range of photorespiratory contributions. Instead, we avoided any interference from propagated errors by identifying the best fit for all parameters simultaneously. We based our analysis on the assumption that the three Senecio species may differ in mesophyll conductance but that the same fractionation factors (b, f, and e) could be applied to all of them.

Combining data from all experiments, we determined a photorespiratory fractionation factor f of 11.6 ± 1.5. (Note that a preliminary version of this data set was presented in Table II and Fig. 6 of Ghashghaie et al. [2003], with f reported as 9 and 11.) Our new value is larger than previous in vivo estimates (Table II) on intact leaves of 6.2 ± 0.5, 7.4 ± 0.3 (Rooney, 1988), and 8 (Gillon, 1997; revised from 0.5 and 3.3 [Gillon and Griffiths, 1997]). The experiments of Rooney (1988) were carried out at the CO₂ compensation point (), where photosynthetic CO₂ uptake is balanced by respiratory CO₂ releases. If the isotopic fluxes are at steady state, all diffusional fractionations cancel. An additional assumption was that there is no day respiration (i.e. = *), so that C_a = C_s = C_i = C_c = *, and Equation 1 can be simplified to = b – f. In two experiments, was determined as 22.6 and 21.4 from the isotopic composition of chamber air and leaf material, yielding f = 6.4 and 7.6 for b = 29, with f again depending on the choice of b. If day respiration is included ( > *), then C_a = C_s = C_i = C_c = , and the above equation changes to = b – f */ – e(1 – */). The equation now reflects the relative contributions from photorespiration and day respiration to total respiratory fluxes, even if there is no fractionation during day respiration (e = 0). With a rough estimate of 0.73 for */ (calculated from Farquhar et al. [1980], using V_cmax 50 µmol m^–2 s^–1 and R_d 0.7 µmol m^–2 s^–1, with R_d/R_n 0.3 at 140 µL L^–1 CO₂ [Tcherkez et al., 2008], where R_n [1 µmol m^–2 s^–1] is the nighttime respiration rate), the resulting f for the experiments of Rooney (1988) would be larger: 8.7 and 10.3 for e = 0 and 10.9 and 12.5 for e = –6, very close to our estimate of 11.6 ± 1.5. Our estimate is also similar to recent results of 10 to 14 (Igamberdiev et al., 2004). In these experiments, photorespiration was manipulated through imposed stress (e.g. drought) and photorespiratory mutants, which may have affected other metabolic processes and complicated the identification of f itself.

We obtained a value of 26 for b, the net fractionation during carboxylation, lower than previous estimates of 27 to 32 (von Caemmerer and Evans, 1991). In vitro determinations of Rubisco fractionation (b₃) have yielded values of 27 to 31 (Roeske and O'Leary, 1984; Guy et al., 1993; McNevin et al., 2006), but the net value of b can be lower due to contributions from PEPc carboxylation (b₄). It is also possible that b₃ itself is smaller in some species. For our experiments on the three Senecio species, differences in net b values were not evident in their _obs data. Based on in vitro estimates of enzyme activity, S. greyii had the highest extractable PEPc activity (Table I) and the lowest maximum photosynthetic rate (A_max), reflecting Rubisco activity. As PEPc discrimination has the opposite sign from that of Rubisco, S. greyii, with the highest PEPc:A_max, could have a lower b than S. squalidus (PEPc:A_max smaller by a factor of 4). However, the _obs data of S. greyii and S. squalidus had almost identical slopes (Fig. 1), and _pred versus _obs fits well with a single b value (Fig. 3). Thus, extractable PEPc activity assayed in vitro does not appear to be a reliable indicator of the in vivo PEPc metabolic flux and its influence on b, the net discrimination during carboxylation.

Because many parameter combinations gave a 1:1 slope and an intercept of 0 for _pred versus _obs, the mean absolute deviation was an important criterion in determining the best fit parameters. For example, assuming b = 29, a 1:1 fit could be achieved for f = 5 and g_i = 0.14, 0.13, and 0.11 mol m^–2 s^–1 (for S. squalidus, S. cineraria, and S. greyii, respectively), but the mean absolute deviation of 1.8 was more than twice that of the best fit parameters (0.7). Nevertheless, a range of parameter combinations gave almost equally good agreement between _pred and _obs. Specifically, all g_i values had a range of ±0.01 mol m^–2 s^–1 with similar regression parameters as the best fit parameters reported above. In most cases, the two herbaceous species, S. squalidus and S. cineraria, had higher g_i than the woody species with the thickest leaves, S. greyii, as expected (Warren and Adams, 2006). Within the 0.01 range, the value obtained for b was not sensitive to changes in g_i, but the resulting value of f changed by up to 1.5 depending on the g_i used. To take this uncertainty into account, we report the value of f for our study as 11.6 ± 1.5. Our analysis method is particularly useful for field measurements, in which experimental conditions cannot be as carefully controlled as in the laboratory. On the other hand, we propose that the contributions from different processes to net can be identified best by combining _obs data with independent measurements of b and g_i (through _obs at low O₂ and fluorescence) in controlled laboratory studies.

Our results were not sensitive to the value chosen for e, the fractionation during day respiration. Repeating our analysis for e values of +6 and –6 (Duranceau et al., 1999; Ghashghaie et al., 2003) did not have an effect on the resulting b value and changed the resulting f by less than 0.5. The value of e for use in Equation 1 has not been established yet. Respiratory CO₂ signals reflect the partitioning between starch and sugars (Nogués et al., 2004; Tcherkez and Farquhar, 2005). Additional minor complications can arise from variations in g_i (for review, see Flexas et al., 2008) or changes in the substrate used for day respiration, for example, due to mitochondrial respiration mobilizing older carbon pools (Ghashghaie et al., 2001, 2003; Tcherkez et al., 2003, 2005; Gessler et al., 2008), particularly at low assimilation rates (Wingate et al., 2007).

Neglecting photorespiratory fractionation would lead to an overestimation by 1.2 in the mean assimilation weighted for leaves at temperatures of 21.4°C (Helliker and Richter, 2008), but the deviation can be larger in arid and tropical ecosystems or during periods of higher temperatures in any ecosystem. Diurnal changes in are likely to reflect variations in photorespiration even at the canopy level. For example, photorespiratory contributions can have a large increase between the typically lower morning temperatures (0.9 at 15°C) and higher midday temperatures (2 at 35°C). Thus, reliable f values are required to derive accurate estimates of at the canopy scale and reduce the uncertainty associated with isotopic partitioning of net CO₂ fluxes. At the same time, the amount of structural carbon laid down at times of enhanced photorespiration (drought, high temperature, or salinity; for review, see Wingler et al., 2000) should be minimal. However, relative rates of photorespiration would have been generally higher during periods of low atmospheric CO₂, such as the last glacial maximum or even in the preindustrial atmosphere compared with today's atmosphere. For example, the contribution of photorespiration to net would increase to 1.6 at 280 µmol mol^–1 and to 2.5 at 180 µmol mol^–1 atmospheric CO₂ mole fraction, suggesting small but detectable effects of changing photorespiratory contributions on ¹³C_plant (Seibt et al., 2008).

	CONCLUSION

TOP ABSTRACT RESULTS DISCUSSION CONCLUSION MATERIALS AND METHODS LITERATURE CITED

 
We have demonstrated the effects of fractionation during photorespiration on net at the leaf level. Photorespiratory fractionation was observed as a decrease in _obs at high pO₂, resulting from the release of isotopically lighter CO₂ during the Gly decarboxylase reaction. From concurrent measurements of _obs and gas exchange, we determined the in vivo value of f, the photorespiratory fractionation factor, as 11.6, higher than previous estimates (Rooney, 1988; Gillon, 1997) but similar to theoretical predictions (Tcherkez, 2006). Mesophyll conductance (g_i) and fractionation factors (b and f) were determined simultaneously to avoid propagating errors in b or g_i estimates into subsequent calculations. Our results confirm that photorespiration is an important component of the net photosynthetic discrimination of C3 plants. Photorespiratory effects on should be taken into account to partition net ecosystem exchange into gross CO₂ fluxes at the canopy scale.

	MATERIALS AND METHODS

TOP ABSTRACT RESULTS DISCUSSION CONCLUSION MATERIALS AND METHODS LITERATURE CITED

 

Plant Material

Three species of the genus Senecio were studied: (1) S. squalidus (Oxford ragwort), a fast-growing, short-lived annual herb; (2) S. cineraria, a slower growing, annual/biennial herb with thick hairy leaves; and (3) S. greyii, a slow-growing shrub with thick hairy leaves. S. squalidus was grown from seeds collected from specimens grown in the Botanic Gardens at the University of Cambridge and soaked overnight. Postgermination, plants were transplanted into 8-cm pots containing John Innes No. 2 compost and grown in an air-conditioned, naturally lit greenhouse for 3 weeks prior to experiments. S. cineraria and S. greyii plants were purchased at 2 weeks and 6 months age, respectively (from Ansells Nurseries). They were transplanted into 8-cm and 30-cm pots containing John Innes No. 2 compost and grown in the same greenhouse as the S. squalidus specimens for 2 months prior to experimentation.

Gas-Exchange Measurements

Gas-exchange measurements were made on the youngest fully expanded leaves using an infrared gas analyzer (CIRAS-1; PP Systems) with a 10-cm² Parkinson leaf chamber illuminated by a Walz fiber-optic lighting unit (Fiber Illuminator FL-440 and Special Fibreoptics 400-F; Walz). Compressed air (¹³C = –10.9) containing O₂ at partial pressures of 30, 210, and 300 mbar (BOC Special Gases) and CO₂ at 370 µbar were used to supply air to the chamber, bubbled through a saturated solution of NaCl at 25°C to achieve relative humidity of approximately 80%. Light response curves were performed to estimate the maximum photosynthetic rate (A_max). CO₂ response (A/C_i) curves were carried out on four plants at each pO₂ and light levels of 100, 300, and 1,000 µmol m^–2 s^–1 to obtain the compensation point in the absence of dark respiration (*) and day respiration (R_d; Brooks and Farquhar, 1985).

Measurements of ¹³C Discrimination

Attached leaves were placed in the leaf chamber and acclimated to the chamber conditions for 20 min. Flow rates were maintained at 250 mL min^–1 to obtain large CO₂ depletions across the chamber. A range of C_i/C_a values was achieved by measuring each leaf at high and low light (900 and 250 µmol m^–2 s^–1). Four plants were sampled for each species, and measurements at all three pO₂ levels were performed on the same leaf. The CO₂ in the air exiting the chamber was trapped cryogenically (for detailed description, see Broadmeadow et al., 1992). Briefly, air from downstream of the cuvette (analysis gas) was passed at positive pressure to a glass collection line at a rate of 150 mL min^–1 via a needle valve. The CO₂ was trapped by passing the air through a cold trap submerged in liquid N₂ at a pressure of less than 0.6 kPa. The line was then isolated and evacuated to 10^–3 kPa, after which the CO₂ was liberated from the cold trap in acetone at –80°C to retain water vapor. The CO₂ was then drawn into a removable vial, which was sealed with a butane gas torch. Gas-exchange parameters were recorded on the infrared gas analyzer before and after CO₂ collection, with the mean of both readings used in the analyses. Reference gas was collected at the start of each experimentation day and after every fourth sample collection. The samples of analysis and reference gas were purified via two further cryodistillations (Borland et al., 1993) and analyzed on a VG-903 dual-inlet triple collector mass spectrometer (modified by Provac Services).

The ¹³C/¹²C ratios of the samples were determined against those of reference CO₂ (¹³C = –42.5; BDH) and reported with respect to the PeeDee Belemnite standard. Defining net photosynthetic discrimination as – 1, where and are the isotope ratios of atmospheric CO₂ and the product (e.g. photoassimilates), the observed ¹³C discrimination in a leaf cuvette during photosynthesis (_obs) was determined following Evans et al. (1986) from:

(5)

where = C_e/(C_e – C_o), and C_e and C_o, ¹³C_e and ¹³C_o refer to the mole fractions and isotope ratios of CO₂ in air entering and exiting the leaf cuvette, respectively.

Determination of PEPc Activity

Frozen leaf tissue (200 mg) was extracted at 4°C in 2 mL of buffer containing 200 mM Tris base (pH 8), 2 mM EDTA, 2% polyethylene glycol 20,000, 1 mM dithiothrietol, 1 mM benzamidine, 10 mM malate, and 350 mM NaHCO₃. Samples were centrifuged at 12,000g for 3 min, and the supernatant was desalted on a Sephadex G-25 column. PEPc activity was measured as the oxidation of NADH in the presence of PEP, malate dehydrogenase, and total leaf protein (Chu et al., 1990). Briefly, NADH consumption was measured over 6 min at 340 nm using a UV-300 spectrophotometer (Spectronic Unicam), with the reaction initiated by the addition of 100 µL of extract to 850 µL of assay cocktail (65 mM Tris base [pH 7.8], 0.2 mM NADH, 10 mM NaHCO₃, and 5 mM MgCl₂) with 2 mM PEP. Total soluble protein content of extracts was obtained by mixing 10 µL of protein extract with 90 µL of water and 4 mL of Bradford reagent (Bradford, 1976). The sample was precipitated for 15 min and the A₅₉₅ was measured. Protein content was calibrated across a range of 0 to 100 mg using a 1-mg stock of bovine serum albumin in water.

Supplemental Data

The following materials are available in the online version of this article.

Supplemental Table S1. List of abbreviations and symbols used in the text.

	ACKNOWLEDGMENTS

 
We thank Barney Davies for his help with the PEPc protocol. We are grateful to Glynn Jones for technical assistance with isotope ratio mass spectroscopy. We thank Guillaume Tcherkez, Jaleh Ghashghaie, and Graham Farquhar for valuable discussions and the anonymous reviewers for their helpful comments on this and an earlier version of the manuscript.

Received September 20, 2008; accepted October 12, 2008; published October 15, 2008.

	FOOTNOTES

 
¹ This work was supported by the European Research Training Network (Network for Ecophysiology in Closing Terrestrial Carbon Budget; contract no. HPRN–CT–1999–00059), by a Marie Curie Fellowship of the European Commission to U.S. (contract no. MOIF–CT–2004–2704), and by the Department of Plant Sciences, University of Cambridge.

² Present address: Teagasc, Johnstown Castle Environmental Research Centre, Wexford, Ireland.

³ Present address: RPS Group, Willowmere House, Compass Point Business Park, Stocks Bridge Way, St. Ives PE27 6JL, United Kingdom.

⁴ Present address: UMR Bioemco, 78850 Thiverval-Grignon, Université Pierre et Marie Curie, Paris 6, France.

The author responsible for the 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: Ulli Seibt (useibt{at}dge.stanford.edu).

^[W] The online version of this article contains Web-only data.

^[OA] Open Access articles can be viewed online without a subscription.

www.plantphysiol.org/cgi/doi/10.1104/pp.108.130153

^* Corresponding author; e-mail useibt{at}dge.stanford.edu.

	LITERATURE CITED

TOP ABSTRACT RESULTS DISCUSSION CONCLUSION MATERIALS AND METHODS LITERATURE CITED

 
Abell LM, O'Leary MH (1988) Isotope effect studies of the pyridoxal 5'-phosphate dependent histidine decarboxylase from Morganella morganni. Biochemistry 27: 5927–5933

Bathellier C, Badeck FW, Couzi P, Harscoët S, Mauve C, Ghashghaie J (2008) Divergence in ¹³C of dark respired CO₂ and bulk organic matter occurs during the transition between heterotrophy and autotrophy in Phaseolus vulgaris plants. New Phytol 177: 406–418[Medline]

Borland AM, Griffiths H, Broadmeadow MSJ, Fordham MC, Maxwell C (1993) Short-term changes in carbon-isotope discrimination in the C₃-CAM intermediate Clusia minor L. growing in Trinidad. Oecologia 95: 444–453[CrossRef][Web of Science]

Bowling DR, Tans PP, Monson RK (2001) Partitioning net ecosystem carbon exchange with isotopic fluxes of CO₂. Glob Change Biol 7: 127–145

Bradford MM (1976) A rapid and sensitive method for the quantification of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72: 248–254[CrossRef][Web of Science][Medline]

Broadmeadow MSJ, Griffiths H, Maxwell C, Borland AM (1992) The carbon isotope ratio of plant organic material reflects temporal and spatial variations in CO₂ partial pressure and ¹³C within tropical forest formations in Trinidad. Oecologia 89: 435–441[CrossRef]

Brooks A, Farquhar GD (1985) Effect of temperature on the CO₂/O₂ specificity of ribulose-1,5-bisphosphate carboxylase/oxygenase and the rate of respiration in the light. Planta 165: 397–406

Cernusak LA, Winter K, Aranda J, Turner BL (2008) Conifers, angiosperm trees, and lianas: growth, whole-plant water and nitrogen use efficiency, and stable isotope composition (¹³C and ¹⁸O) of seedlings grown in a tropical environment. Plant Physiol 148: 642–659[Abstract/Free Full Text]

Chu C, Dai Z, Ku SBM, Edwards G (1990) Induction of Crassulacean acid metabolism in the facultative halophyte Mesembryanthemum crystallinum by abscisic acid. Plant Physiol 93: 1253–1260[Abstract/Free Full Text]

Craig H (1953) The geochemistry of the stable carbon isotopes. Geochim Cosmochim Acta 3: 53–92[CrossRef][Web of Science]

Duranceau M, Ghashghaie J, Badeck F, Deleens E, Cornic G (1999) ¹³C of CO₂ respired in the dark in relation to ¹³C of leaf carbohydrates in Phaseolus vulgaris L under progressive drought. Plant Cell Environ 22: 515–523[Medline]

Evans JR, Sharkey TD, Berry JA, Farquhar GD (1986) Carbon isotope discrimination measured concurrently with gas exchange to investigate CO₂ diffusion in leaves of higher plants. J Plant Physiol 13: 281–292

Farquhar GD, O'Leary MH, Berry JA (1982) On the relationship between carbon isotope discrimination and the intercellular carbon dioxide concentration in leaves. J Plant Physiol 9: 121–137

Farquhar GD, von Caemmerer S, Berry JA (1980) A biochemical model of photosynthetic CO₂ assimilation in leaves of C₃ species. Planta 149: 78–90[CrossRef][Web of Science]

Flexas J, Ribas-Carbó M, Diaz-Espejo A, Galmés J, Medrano H (2008) Mesophyll conductance to CO₂: current knowledge and future prospects. Plant Cell Environ 31: 602–621[CrossRef]

Gessler A, Tcherkez G, Peuke AD, Ghashghaie J, Farquhar GD (2008) Experimental evidence for diel variations of the carbon isotope composition in leaf, stem and phloem sap organic matter in Ricinus communis. Plant Cell Environ 31: 941–953

Ghashghaie J, Badeck FW, Lanigan GJ, Nogues S, Tcherkez G, Deleens E, Cornic G, Griffiths H (2003) Carbon isotope fractionation during dark respiration and photorespiration in C₃ plants. Phytochem Rev 2: 145–161[CrossRef]

Ghashghaie J, Duranceau M, Badeck FW, Cornic G, Adeline MT, Deleens E (2001) ¹³C of CO₂ respired in the dark in relation to delta ¹³C of leaf metabolites: comparison between Nicotiana sylvestris and Helianthus annuus under drought. Plant Cell Environ 24: 505–515[CrossRef]

Gillon JS (1997) Carbon isotope discrimination: interactions between respiration, leaf conductance and photosynthetic capacity. PhD thesis. University of Newcastle upon Tyne, Newcastle, UK

Gillon JS, Griffiths H (1997) The influence of (photo)respiration on carbon isotope discrimination in plants. Plant Cell Environ 20: 1217–1230[CrossRef]

Guy RD, Fogel ML, Berry JA (1993) Photosynthetic fractionation of the stable isotopes of oxygen and carbon. Plant Physiol 101: 37–47[Abstract]

Helliker BR, Richter SL (2008) Subtropical to boreal convergence of tree-leaf temperatures. Nature 454: 511–514[Medline]

Hobbie EA, Colpaert JV (2004) Nitrogen availability and mycorrhizal colonization influence water use efficiency and carbon isotope patterns in Pinus sylvestris. New Phytol 164: 515–525[CrossRef][Web of Science]

Igamberdiev AU, Ivlev AA, Bykova NV, Threlkeld CN, Lea PJ, Gardestrom P (2001) Decarboxylation of glycine contributes to carbon isotope fractionation in photosynthetic organisms. Photosynth Res 67: 177–184[CrossRef][Medline]

Igamberdiev AU, Mikkelsen TN, Ambus P, Bauwe H, Lea PJ, Gardeström P (2004) Photorespiration contributes to stomatal regulation and carbon isotope fractionation: a study with barley, potato and Arabidopsis plants deficient in glycine decarboxylase. Photosynth Res 81: 139–152[CrossRef][Web of Science]

Ivlev AA (2001) Carbon isotope effects (C13/C12) in biological systems. Separ Sci Tech 36: 1819–1914

Ivlev AA, Bykova NV, Igamberdiev AU (1996) Fractionation of carbon (C13/C12) isotopes in glycine decarboxylase reaction. FEBS Lett 386: 174–176[Medline]

McNevin DB, Badger MR, Kane HJ, Farquhar GD (2006) Measurement of (carbon) kinetic isotope effect by Rayleigh fractionation using membrane inlet mass spectrometry for CO₂-consuming reactions. Funct Plant Biol 33: 1115–1128[CrossRef]

Nogués S, Tcherkez G, Cornic G, Ghashghaie J (2004) Respiratory carbon metabolism following illumination in intact French bean leaves using ¹³C/¹²C isotope labeling. Plant Physiol 136: 3245–3254[Abstract/Free Full Text]

Ogée J, Peylin P, Ciais P, Bariac T, Brunet Y, Berbigier P, Roche C, Richard P, Bardoux G, Bonnefond JM (2003) Partitioning net ecosystem carbon exchange into net assimilation and respiration using ¹³CO₂ measurements: a cost-effective sampling strategy. Global Biogeochem Cycles 17: 39-1–39-18

O'Leary MH (1984) Measurement of the isotopic fractionation associated with diffusion of carbon dioxide in aqueous solution. J Phys Chem 88: 823–825[CrossRef][Web of Science]

O'Leary MH, Madhavan S, Paneth P (1991) Physical and chemical basis of carbon isotope fractionation in plants. Plant Cell Environ 15: 1099–1104

Roeske CA, O'Leary MH (1984) Carbon isotope effects on the enzyme-catalyzed carboxylation of ribulose biphosphate. Biochemistry 23: 6275–6284

Rooney MA (1988) Short-term carbon isotope fractionation by plants. PhD thesis. University of Wisconsin, Madison, WI

Seibt U, Rajabi A, Griffiths H, Berry JA (2008) Carbon isotopes and water use efficiency: sense and sensitivity. Oecologia 155: 441–454[CrossRef][Web of Science][Medline]

Tcherkez G (2006) How large is the carbon isotope fractionation of the photorespiratory enzyme glycine decarboxylase? Funct Plant Biol 33: 911–920

Tcherkez G, Bligny R, Gout E, Mahé A, Hodges M, Cornic G (2008) Respiratory metabolism of illuminated leaves depends on CO₂ and O₂ conditions. Proc Natl Acad Sci USA 105: 797–802[Abstract/Free Full Text]

Tcherkez G, Cornic G, Bligny R, Gout E, Ghashghaie J (2005) In vivo respiratory metabolism of illuminated leaves. Plant Physiol 138: 1596–1606[Abstract/Free Full Text]

Tcherkez G, Farquhar GD (2005) Carbon isotope effect predictions for enzymes involved in the primary carbon metabolism of plant leaves. Funct Plant Biol 32: 277–291[CrossRef]

Tcherkez G, Nogués S, Bleton J, Cornic G, Badeck FW, Ghashghaie J (2003) Metabolic origin of carbon isotope composition of leaf dark-respired CO₂ in Phaseolus vulgaris L. Plant Physiol 131: 237–244[Abstract/Free Full Text]

Vogel JC (1980) Fractionation of the carbon isotopes during photosynthesis. Sitzungsber Heidelb Akad Wiss 3: 111–135

von Caemmerer S, Evans JR (1991) Determination of the average partial pressure of CO₂ in chloroplasts from leaves of several C3 plants. J Plant Physiol 18: 287–305

Walker JL, Oliver DJ (1986) Glycine decarboxylase multienzyme complex: purification and partial characterization from pea leaf mitochondria. J Biol Chem 261: 2214–2221[Abstract/Free Full Text]

Warren CR, Adams MA (2006) Internal conductance does not scale with photosynthetic capacity: implications for carbon isotope discrimination and the economics of water and nitrogen use in photosynthesis. Plant Cell Environ 29: 192–201[CrossRef][Medline]

Wingate L, Seibt U, Moncrieff JB, Jarvis PG, Lloyd JJ (2007) Variations in ¹³C discrimination during CO₂ exchange by Picea sitchensis branches in the field. Plant Cell Environ 30: 600–616[Medline]

Wingler A, Lea PJ, Quick WP, Leegood RC (2000) Photorespiration, metabolic pathways and their role in stress protection. Philos Trans R Soc Lond B Biol Sci. 355: 1517–1529[Abstract/Free Full Text]

Zobitz JM, Burns SP, Ogée J, Reichstein M, Bowling DR (2007) Partitioning net ecosystem exchange of CO₂: a comparison of a Bayesian/isotope approach to environmental regression methods. J Geophys Res 112: G03013

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