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Plant, Cell and Environment (2014) 37, 2456–2458
doi: 10.1111/pce.12401
Commentary
Mesophyll conductance with a twist It has long been known that both stomatal (gs) and mesophyll conductance (gm) often scale with photosynthetic capacity (Evans & Loreto 2000). More recently, direct correlations between gs and gm have been reported, even on short timescales (reviewed in Warren 2008; Flexas et al. 2008), but the factors underlying these relations remain enigmatic. The issue is of broad interest, as gm limits photosynthetic rates. Moreover, maintaining a high gm when stomata close increases water use efficiency, making gm a key parameter contributing to plant performance under drought. In a recent issue of Plant, Cell and Environment, Cano et al. (2014) investigated the response of gm and gs in Eucalyptus species under water stress, and attempted to correct their gm estimates for the possibility that these were affected by increased rates of photorespiration. This correction was based on our earlier work (Tholen et al. 2012), which promoted the view that increased rates of photorespiration, at low CO2 or high O2 levels, may decrease the observed gm. There is an ongoing debate over the magnitude of this effect and its potential impact on the relation between gm and gs (Evans & Von Caemmerer 2013; Cano et al. 2014; Gu & Sun 2014), underlining the need for additional investigations on this topic. Unfortunately, the work by Cano et al. confuses this debate because of a fundamental misunderstanding of the model put forward in our paper. Mesophyll conductance has traditionally been defined (Flexas et al. 2008; Warren 2008) as the net assimilation (A) divided by the CO2 partial pressure difference between intercellular airspaces (pi) and the site of carboxylation (pc):
gm =
A ( pi − pc )
(1)
The classical interpretation of this equation is that the partial pressure difference between pi and pc drives a net flux A across a linear series of resistances such that (assuming the resistance of the intercellular airspaces and that of the cytosol can be neglected):
pi − pc = A (rwp + rch )
(2)
where rwp represents the combined resistance of the cell wall and the plasmalemma, and rch that of the chloroplast envelopes and stroma. By contrast, our work (Tholen et al. 2012) pointed out that A is not the only flux involved; an additional intracellular respiratory (Rd) and photorespiratory (F) flux from the mitochondria joins flux A in the cytosol (see Fig. 1), giving instead of Eqn 2:
pi − pc = A (rwp + rch ) + ( F + Rd ) rch
(3)
Correspondence: D. Tholen. Fax: +43 (0)1 47654 3180; e-mail: [email protected] 2456
Combining Eqns 1 and 3, we get:
(
gm = ⎡rwp + rch 1 + ⎣⎢
)
F + Rd ⎤ A ⎦⎥
−1
(4)
showing that when rch is significant, the apparent gm, which is experimentally determined using Eqn 1, is in fact dependent on the rate of respiration and photorespiration, and therefore becomes variable with respect to the concentrations of CO2 and O2 in the mesophyll. This equation brings mathematical justification to previous experimental results suggesting that gm declines sharply at sub-ambient CO2 concentrations (e.g. Flexas et al. 2007), or conversely increases at sub-ambient O2 concentrations (reviewed in Tholen et al. 2012). However, it cannot explain the commonly observed decrease in gm at high CO2 concentrations (Flexas et al. 2007). It must be stressed that such a ‘peaked’ gm response to CO2 can also easily arise from methodological artefacts (Gu & Sun 2014). The (photo)respiratory effect outlined above could partially explain the observed coordination between gm and gs under water stress. A low pi arising from stomatal closure would result in a relative increase of the photorespiratory flux and thus decrease the apparent gm according to Eqn 4. We recommended that authors studying the relation between stomatal and mesophyll conductance take precautions to account for occurrence of this effect, and to not automatically assume that a correlation between these parameters was the result of regulatory mechanisms (Tholen et al. 2012). One possible methodology to factor out the (photo)respiratory effect was recently employed by Théroux-Rancourt et al. (2014). In this work, a constant pi was maintained as stomata closed throughout the experiment. Alternatively, the equations given in Tholen et al. (2012) could be used to predict the effect of photorespiration on gm. For example, if the curvature of the relation between the observed (measured) gm and gs is more pronounced than the theoretical curvature calculated assuming a maximal photorespiration effect (e.g. fig. 4 in Tholen et al. 2012), this would be an indication that additional factors are responsible for the relation between gm and gs. This could be a result of a biological control mechanism affecting rch and/or rwp directly, but methodological artefacts may also generate such correlations (Pons et al. 2009; Gu & Sun 2014). We believe that this second approach was the intent of Cano et al. However, in the context of Eqn 4, mesophyll resistance (rm, the reciprocal of gm) is no longer defined as the sum of rwp and rch (i.e. 1/gm ≠ rwp + rch) as Eqns 1 and 2 suggest. We therefore proposed a different notation (rdiff) to represent rwp + rch (Tholen et al. 2012). Unfortunately, © 2014 John Wiley & Sons Ltd
Mesophyll conductance with a twist
A φ(F + Rd)
pa A + φ (F + Rd)
rs pi rwp A + φ (F + Rd) F + Rd
φ(F + Rd) py
Mitochondrion
A + φ (F + Rd) (1 – φ) (F + Rd) rch (1 – φ) (F + Rd)
A + φ (F + Rd) pc
Chloroplast
Vc
Figure 1. Representation of the diffusion network in the leaf and mesophyll and its relation to recycling of (photo)respiratory CO2. Fluxes of CO2 originating from the mitochondria are indicated in red; fluxes of atmospheric CO2 are indicated in blue. A is the net assimilation rate; Vc the gross carboxylation rate; F is the photorespiration rate; and Rd is the respiration rate. pa, pi, py and pc indicate the CO2 partial pressures of the atmosphere, intercellular spaces, cytosol and at the site of carboxylation. ϕ is a simple partitioning factor describing the amount of the photorespiratory flux that diffuses outwards to the atmosphere [ϕ(F + Rd)] and the part that diffuses towards the sink inside the chloroplasts [(1 – ϕ)(F + Rd)]. The outward flux experiences a resistance from the cell wall and plasmalemma (rwp, in blue) and from the stomata (rs, brown); the inward flux crosses the chloroplast envelopes and stroma (rch, in green), but also experiences a ‘carboxylation resistance’ (pc/Vc) arising from the slow turnover rate of Rubisco’s catalytic sites. Regardless of the partitioning between these two fluxes, A is always the difference between Vc and the (photo)respiratory flux (F + Rd), that is, A = Vc – (F + Rd).
several recent works that apply some version of Eqn 4 still retained the previous formulation equating rm to rwp + rch (Evans & Von Caemmerer 2013; Von Caemmerer 2013; Cano et al. 2014). We think this practice should be avoided as it can easily lead to confusion and eventual misinterpretation of results. An example of such a misinterpretation is that one might not recognize that the photorespiration effect described above is inherently included in gm estimates. Indeed, Cano et al. (2014) have applied a photorespiratory effect on top of measured gm values (see their eqns A21 and A22), and proceeded to calculate new estimates of pc and gm (Cc* and gm* in their notation) that purported to include the effect of a
2457
significant rch. Such an approach is not logical within the framework of Eqns 3 and 4: because the measured gm already incorporates an effect of photorespiration, it is not necessary to correct for this afterwards. Cano et al. observed that their corrected gm* values often led to unlikely estimates of Cc* that were ‘lower than Γ * [i.e. the CO2 photocompensation point], or even negative’ and their calculated relations between gm* and gs seem to contrast to predictions in our work (cf. fig. 9 Cano et al. 2014 and fig. 4 Tholen et al. 2012). However, the parameters Cc* and gm* are the result of imposing a photorespiratory effect on estimates that already included such an effect. The conclusion that Eucalyptus species have a low chloroplast resistance was based on the occurrence of such unrealistic values, and therefore needs to be re-evaluated. Throughout their paper, Cano et al. referred to rch as the ‘chloroplast resistance to the refixation of CO2’. This description is not adequate. The biochemical model of photosynthesis (Von Caemmerer 2013) makes no assumptions as to the fate of the flux out of the mitochondria. Because the Rubisco turnover rate is slow, some (photo)respiratory CO2 escapes to the atmosphere, but a significant portion may be refixed (see Fig. 1). The combined effect of refixation and leakage out of the leaf is to modulate the amount of atmospheric CO2 that is pulled in and fixed by Rubisco. However, the proportion of refixation does not change the model definition of the gross carboxylation demand of the enzyme (Vc) nor the net CO2 assimilation rate (A) at the leaf level. Assuming a significant rch as part of this model increases the already present resistance to refixation, but does not alter the rate equations for photosynthesis or photorespiration. To determine the magnitude of the photorespiratory effect on gm, reliable estimates of rch are required. Given the aforementioned methodological issues regarding the evaluation of the response of gm to low CO2, Tholen et al. (2012) chose instead to validate Eqn 4 by examining the O2 sensitivity of gm. However, Evans & Von Caemmerer (2013) pointed out that the approach used by Tholen et al. (2012) relied strongly on the estimate of the carbon isotope fractionation factor associated with photorespiration. Unfortunately, this factor is itself estimated by assuming that gm does not vary with oxygen, making estimates of both this fractionation factor and rch in Tholen et al. (2012) and Evans & Von Caemmerer (2013) completely dependent on a priori model assumptions. Our original model assumed complete mixing of CO2 in the cytosol. In response, Cernusak et al. (2013) remarked that if mitochondria are located predominantly close to, but behind the chloroplast, most of the (photo)respired CO2 may enter the chloroplast from the back, making the effect of photorespiration on the gradient between pi and pc (Eqn 3) small or insignificant (so Eqn 3 could be simplified to Eqn 2). The effect of the arrangement of organelles within the cells was underrepresented in our original paper and we are working towards an improved description of such effects. Our preliminary model indicates that photorespiration remains a non-negligible factor determining the magnitude of gm.
© 2014 John Wiley & Sons Ltd, Plant, Cell and Environment, 37, 2456–2458
2458
D. Tholen et al.
Danny Tholen1, Gilbert Éthier2 & Bernard Genty3 Institute of Botany, University of Natural Resources and Life Sciences, Vienna A-1180, Austria 2Centre de Recherche en Horticulture, Université Laval, Québec G1V 0A6, Canada 3Commissariat à l’Energie Atomique et aux Energies Alternatives, Centre National de la Recherche Scientifique, UMR 7265 Biologie Végétale et Microbiologie Environnementale, Aix Marseille Université, CEA Cadarache, Saint-Paul-lez-Durance 13108, France 1
REFERENCES Cano F.J., Lο´ pez R. & Warren C.R. (2014) Implications of the mesophyll conductance to CO2 for photosynthesis and water-use efficiency during longterm water stress and recovery in two contrasting Eucalyptus species. Plant, Cell & Environment 37, 2470–2490. Cernusak L.A., Ubierna N., Winter K., Holtum J.A.M., Marshall J.D. & Farquhar G.D. (2013) Environmental and physiological determinants of carbon isotope discrimination in terrestrial plants. The New Phytologist 200, 950–965. Evans J.R. & Loreto F. (2000) Acquisition and diffusion of CO2 in higher plant leaves. In Photosynthesis: Physiology and Metabolism (eds R.C. Leegood, T.D. Sharkey & S. von Caemmerer), pp. 321–351. Kluwer Academic Publishers, Dordrecht, the Netherlands.
Evans J.R. & Von Caemmerer S. (2013) Temperature response of carbon isotope discrimination and mesophyll conductance in tobacco. Plant, Cell & Environment 36, 745–756. Flexas J., Diaz-Espejo A., Galmés J., Kaldenhoff R., Medrano H.O. & Ribas-Carbó M. (2007) Rapid variations of mesophyll conductance in response to changes in CO2 concentration around leaves. Plant, Cell & Environment 30, 1284–1298. Flexas J., Ribas-Carbó M., Diaz-Espejo A., Galmés J. & Medrano H.O. (2008) Mesophyll conductance to CO2: current knowledge and future prospects. Plant, Cell & Environment 31, 602–621. Gu L. & Sun Y. (2014) Artefactual responses of mesophyll conductance to CO2 and irradiance estimated with the variable J and online isotope discrimination methods. Plant, Cell & Environment 37, 1231–1249. Pons T.L., Flexas J., von Caemmerer S., Evans J.R., Genty B., Ribas-Carbo M. & Brugnoli E. (2009) Estimating mesophyll conductance to CO2: methodology, potential errors, and recommendations. Journal of Experimental Botany 60, 2217–2234. Théroux-Rancourt G., Éthier G. & Pepin S. (2014) Threshold response of mesophyll CO2 conductance to leaf hydraulics in highly transpiring hybrid poplar clones exposed to soil drying. Journal of Experimental Botany 65, 741–753. Tholen D., Ethier G., Genty B., Pepin S. & Zhu X.-G. (2012) Variable mesophyll conductance revisited: theoretical background and experimental implications. Plant, Cell & Environment 35, 2087–2103. Von Caemmerer S. (2013) Steady-state models of photosynthesis. Plant, Cell & Environment 36, 1617–1630. Warren C.R. (2008) Stand aside stomata, another actor deserves centre stage: the forgotten role of the internal conductance to CO2 transfer. Journal of Experimental Botany 59, 1475–1487.
Received 28 June 2014; accepted for publication 28 June 2014
© 2014 John Wiley & Sons Ltd, Plant, Cell and Environment, 37, 2456–2458
Plant, Cell and Environment (2014) 37, 2456–2458
doi: 10.1111/pce.12401
Commentary
Mesophyll conductance with a twist It has long been known that both stomatal (gs) and mesophyll conductance (gm) often scale with photosynthetic capacity (Evans & Loreto 2000). More recently, direct correlations between gs and gm have been reported, even on short timescales (reviewed in Warren 2008; Flexas et al. 2008), but the factors underlying these relations remain enigmatic. The issue is of broad interest, as gm limits photosynthetic rates. Moreover, maintaining a high gm when stomata close increases water use efficiency, making gm a key parameter contributing to plant performance under drought. In a recent issue of Plant, Cell and Environment, Cano et al. (2014) investigated the response of gm and gs in Eucalyptus species under water stress, and attempted to correct their gm estimates for the possibility that these were affected by increased rates of photorespiration. This correction was based on our earlier work (Tholen et al. 2012), which promoted the view that increased rates of photorespiration, at low CO2 or high O2 levels, may decrease the observed gm. There is an ongoing debate over the magnitude of this effect and its potential impact on the relation between gm and gs (Evans & Von Caemmerer 2013; Cano et al. 2014; Gu & Sun 2014), underlining the need for additional investigations on this topic. Unfortunately, the work by Cano et al. confuses this debate because of a fundamental misunderstanding of the model put forward in our paper. Mesophyll conductance has traditionally been defined (Flexas et al. 2008; Warren 2008) as the net assimilation (A) divided by the CO2 partial pressure difference between intercellular airspaces (pi) and the site of carboxylation (pc):
gm =
A ( pi − pc )
(1)
The classical interpretation of this equation is that the partial pressure difference between pi and pc drives a net flux A across a linear series of resistances such that (assuming the resistance of the intercellular airspaces and that of the cytosol can be neglected):
pi − pc = A (rwp + rch )
(2)
where rwp represents the combined resistance of the cell wall and the plasmalemma, and rch that of the chloroplast envelopes and stroma. By contrast, our work (Tholen et al. 2012) pointed out that A is not the only flux involved; an additional intracellular respiratory (Rd) and photorespiratory (F) flux from the mitochondria joins flux A in the cytosol (see Fig. 1), giving instead of Eqn 2:
pi − pc = A (rwp + rch ) + ( F + Rd ) rch
(3)
Correspondence: D. Tholen. Fax: +43 (0)1 47654 3180; e-mail: [email protected] 2456
Combining Eqns 1 and 3, we get:
(
gm = ⎡rwp + rch 1 + ⎣⎢
)
F + Rd ⎤ A ⎦⎥
−1
(4)
showing that when rch is significant, the apparent gm, which is experimentally determined using Eqn 1, is in fact dependent on the rate of respiration and photorespiration, and therefore becomes variable with respect to the concentrations of CO2 and O2 in the mesophyll. This equation brings mathematical justification to previous experimental results suggesting that gm declines sharply at sub-ambient CO2 concentrations (e.g. Flexas et al. 2007), or conversely increases at sub-ambient O2 concentrations (reviewed in Tholen et al. 2012). However, it cannot explain the commonly observed decrease in gm at high CO2 concentrations (Flexas et al. 2007). It must be stressed that such a ‘peaked’ gm response to CO2 can also easily arise from methodological artefacts (Gu & Sun 2014). The (photo)respiratory effect outlined above could partially explain the observed coordination between gm and gs under water stress. A low pi arising from stomatal closure would result in a relative increase of the photorespiratory flux and thus decrease the apparent gm according to Eqn 4. We recommended that authors studying the relation between stomatal and mesophyll conductance take precautions to account for occurrence of this effect, and to not automatically assume that a correlation between these parameters was the result of regulatory mechanisms (Tholen et al. 2012). One possible methodology to factor out the (photo)respiratory effect was recently employed by Théroux-Rancourt et al. (2014). In this work, a constant pi was maintained as stomata closed throughout the experiment. Alternatively, the equations given in Tholen et al. (2012) could be used to predict the effect of photorespiration on gm. For example, if the curvature of the relation between the observed (measured) gm and gs is more pronounced than the theoretical curvature calculated assuming a maximal photorespiration effect (e.g. fig. 4 in Tholen et al. 2012), this would be an indication that additional factors are responsible for the relation between gm and gs. This could be a result of a biological control mechanism affecting rch and/or rwp directly, but methodological artefacts may also generate such correlations (Pons et al. 2009; Gu & Sun 2014). We believe that this second approach was the intent of Cano et al. However, in the context of Eqn 4, mesophyll resistance (rm, the reciprocal of gm) is no longer defined as the sum of rwp and rch (i.e. 1/gm ≠ rwp + rch) as Eqns 1 and 2 suggest. We therefore proposed a different notation (rdiff) to represent rwp + rch (Tholen et al. 2012). Unfortunately, © 2014 John Wiley & Sons Ltd
Mesophyll conductance with a twist
A φ(F + Rd)
pa A + φ (F + Rd)
rs pi rwp A + φ (F + Rd) F + Rd
φ(F + Rd) py
Mitochondrion
A + φ (F + Rd) (1 – φ) (F + Rd) rch (1 – φ) (F + Rd)
A + φ (F + Rd) pc
Chloroplast
Vc
Figure 1. Representation of the diffusion network in the leaf and mesophyll and its relation to recycling of (photo)respiratory CO2. Fluxes of CO2 originating from the mitochondria are indicated in red; fluxes of atmospheric CO2 are indicated in blue. A is the net assimilation rate; Vc the gross carboxylation rate; F is the photorespiration rate; and Rd is the respiration rate. pa, pi, py and pc indicate the CO2 partial pressures of the atmosphere, intercellular spaces, cytosol and at the site of carboxylation. ϕ is a simple partitioning factor describing the amount of the photorespiratory flux that diffuses outwards to the atmosphere [ϕ(F + Rd)] and the part that diffuses towards the sink inside the chloroplasts [(1 – ϕ)(F + Rd)]. The outward flux experiences a resistance from the cell wall and plasmalemma (rwp, in blue) and from the stomata (rs, brown); the inward flux crosses the chloroplast envelopes and stroma (rch, in green), but also experiences a ‘carboxylation resistance’ (pc/Vc) arising from the slow turnover rate of Rubisco’s catalytic sites. Regardless of the partitioning between these two fluxes, A is always the difference between Vc and the (photo)respiratory flux (F + Rd), that is, A = Vc – (F + Rd).
several recent works that apply some version of Eqn 4 still retained the previous formulation equating rm to rwp + rch (Evans & Von Caemmerer 2013; Von Caemmerer 2013; Cano et al. 2014). We think this practice should be avoided as it can easily lead to confusion and eventual misinterpretation of results. An example of such a misinterpretation is that one might not recognize that the photorespiration effect described above is inherently included in gm estimates. Indeed, Cano et al. (2014) have applied a photorespiratory effect on top of measured gm values (see their eqns A21 and A22), and proceeded to calculate new estimates of pc and gm (Cc* and gm* in their notation) that purported to include the effect of a
2457
significant rch. Such an approach is not logical within the framework of Eqns 3 and 4: because the measured gm already incorporates an effect of photorespiration, it is not necessary to correct for this afterwards. Cano et al. observed that their corrected gm* values often led to unlikely estimates of Cc* that were ‘lower than Γ * [i.e. the CO2 photocompensation point], or even negative’ and their calculated relations between gm* and gs seem to contrast to predictions in our work (cf. fig. 9 Cano et al. 2014 and fig. 4 Tholen et al. 2012). However, the parameters Cc* and gm* are the result of imposing a photorespiratory effect on estimates that already included such an effect. The conclusion that Eucalyptus species have a low chloroplast resistance was based on the occurrence of such unrealistic values, and therefore needs to be re-evaluated. Throughout their paper, Cano et al. referred to rch as the ‘chloroplast resistance to the refixation of CO2’. This description is not adequate. The biochemical model of photosynthesis (Von Caemmerer 2013) makes no assumptions as to the fate of the flux out of the mitochondria. Because the Rubisco turnover rate is slow, some (photo)respiratory CO2 escapes to the atmosphere, but a significant portion may be refixed (see Fig. 1). The combined effect of refixation and leakage out of the leaf is to modulate the amount of atmospheric CO2 that is pulled in and fixed by Rubisco. However, the proportion of refixation does not change the model definition of the gross carboxylation demand of the enzyme (Vc) nor the net CO2 assimilation rate (A) at the leaf level. Assuming a significant rch as part of this model increases the already present resistance to refixation, but does not alter the rate equations for photosynthesis or photorespiration. To determine the magnitude of the photorespiratory effect on gm, reliable estimates of rch are required. Given the aforementioned methodological issues regarding the evaluation of the response of gm to low CO2, Tholen et al. (2012) chose instead to validate Eqn 4 by examining the O2 sensitivity of gm. However, Evans & Von Caemmerer (2013) pointed out that the approach used by Tholen et al. (2012) relied strongly on the estimate of the carbon isotope fractionation factor associated with photorespiration. Unfortunately, this factor is itself estimated by assuming that gm does not vary with oxygen, making estimates of both this fractionation factor and rch in Tholen et al. (2012) and Evans & Von Caemmerer (2013) completely dependent on a priori model assumptions. Our original model assumed complete mixing of CO2 in the cytosol. In response, Cernusak et al. (2013) remarked that if mitochondria are located predominantly close to, but behind the chloroplast, most of the (photo)respired CO2 may enter the chloroplast from the back, making the effect of photorespiration on the gradient between pi and pc (Eqn 3) small or insignificant (so Eqn 3 could be simplified to Eqn 2). The effect of the arrangement of organelles within the cells was underrepresented in our original paper and we are working towards an improved description of such effects. Our preliminary model indicates that photorespiration remains a non-negligible factor determining the magnitude of gm.
© 2014 John Wiley & Sons Ltd, Plant, Cell and Environment, 37, 2456–2458
2458
D. Tholen et al.
Danny Tholen1, Gilbert Éthier2 & Bernard Genty3 Institute of Botany, University of Natural Resources and Life Sciences, Vienna A-1180, Austria 2Centre de Recherche en Horticulture, Université Laval, Québec G1V 0A6, Canada 3Commissariat à l’Energie Atomique et aux Energies Alternatives, Centre National de la Recherche Scientifique, UMR 7265 Biologie Végétale et Microbiologie Environnementale, Aix Marseille Université, CEA Cadarache, Saint-Paul-lez-Durance 13108, France 1
REFERENCES Cano F.J., Lο´ pez R. & Warren C.R. (2014) Implications of the mesophyll conductance to CO2 for photosynthesis and water-use efficiency during longterm water stress and recovery in two contrasting Eucalyptus species. Plant, Cell & Environment 37, 2470–2490. Cernusak L.A., Ubierna N., Winter K., Holtum J.A.M., Marshall J.D. & Farquhar G.D. (2013) Environmental and physiological determinants of carbon isotope discrimination in terrestrial plants. The New Phytologist 200, 950–965. Evans J.R. & Loreto F. (2000) Acquisition and diffusion of CO2 in higher plant leaves. In Photosynthesis: Physiology and Metabolism (eds R.C. Leegood, T.D. Sharkey & S. von Caemmerer), pp. 321–351. Kluwer Academic Publishers, Dordrecht, the Netherlands.
Evans J.R. & Von Caemmerer S. (2013) Temperature response of carbon isotope discrimination and mesophyll conductance in tobacco. Plant, Cell & Environment 36, 745–756. Flexas J., Diaz-Espejo A., Galmés J., Kaldenhoff R., Medrano H.O. & Ribas-Carbó M. (2007) Rapid variations of mesophyll conductance in response to changes in CO2 concentration around leaves. Plant, Cell & Environment 30, 1284–1298. Flexas J., Ribas-Carbó M., Diaz-Espejo A., Galmés J. & Medrano H.O. (2008) Mesophyll conductance to CO2: current knowledge and future prospects. Plant, Cell & Environment 31, 602–621. Gu L. & Sun Y. (2014) Artefactual responses of mesophyll conductance to CO2 and irradiance estimated with the variable J and online isotope discrimination methods. Plant, Cell & Environment 37, 1231–1249. Pons T.L., Flexas J., von Caemmerer S., Evans J.R., Genty B., Ribas-Carbo M. & Brugnoli E. (2009) Estimating mesophyll conductance to CO2: methodology, potential errors, and recommendations. Journal of Experimental Botany 60, 2217–2234. Théroux-Rancourt G., Éthier G. & Pepin S. (2014) Threshold response of mesophyll CO2 conductance to leaf hydraulics in highly transpiring hybrid poplar clones exposed to soil drying. Journal of Experimental Botany 65, 741–753. Tholen D., Ethier G., Genty B., Pepin S. & Zhu X.-G. (2012) Variable mesophyll conductance revisited: theoretical background and experimental implications. Plant, Cell & Environment 35, 2087–2103. Von Caemmerer S. (2013) Steady-state models of photosynthesis. Plant, Cell & Environment 36, 1617–1630. Warren C.R. (2008) Stand aside stomata, another actor deserves centre stage: the forgotten role of the internal conductance to CO2 transfer. Journal of Experimental Botany 59, 1475–1487.
Received 28 June 2014; accepted for publication 28 June 2014
© 2014 John Wiley & Sons Ltd, Plant, Cell and Environment, 37, 2456–2458
