Short-term thermal photosynthetic responses of C4 grasses are independent of the biochemical subtype.

C4 photosynthesis evolved independently many times, resulting in multiple biochemical pathways; however, little is known about how these different pathways respond to temperature. We investigated the photosynthetic responses of eight C4 grasses belonging to three biochemical subtypes (NADP-ME, PEP-CK, and NAD-ME) to four leaf temperatures (18, 25, 32, and 40 °C). We also explored whether the biochemical subtype influences the thermal responses of (i) in vitro PEPC (Vpmax) and Rubisco (Vcmax) maximal activities, (ii) initial slope (IS) and CO2-saturated rate (CSR) derived from the A-Ci curves, and (iii) CO2 leakage out of the bundle sheath estimated from carbon isotope discrimination. We focussed on leakiness and the two carboxylases because they determine the coordination of the CO2-concentrating mechanism and are important for parameterizing the semi-mechanistic C4 photosynthesis model. We found that the thermal responses of Vpmax and Vcmax, IS, CSR, and leakiness varied among the C4 species independently of the biochemical subtype. No correlation was observed between Vpmax and IS or between Vcmax and CSR; while the ratios Vpmax/Vcmax and IS/CSR did not correlate with leakiness among the C4 grasses. Determining mesophyll and bundle sheath conductances in diverse C4 grasses is required to further elucidate how C4 photosynthesis responds to temperature. © Society for Experimental Biology 2017.

Introduction

Understanding how photosynthesis responds to temperature is critical to our ability to predict the responses of natural and cropping ecosystems to climate change. Modelling the photosynthetic responses of C3 plants to temperature is a routine task where we have a growing appreciation of the natural variation in the underlying mechanisms, such as the temperature dependence of mesophyll conductance (gm) and the kinetics of the CO2-fixing enzyme ribulose 1,5-bisphosphate carboxylase/oxygenase (Rubisco) (Farquhar ; Bernacchi ; Walker ; von Caemmerer and Evans, 2015; Sharwood ). Unlike its C3 counterpart, the semi-mechanistic C4 photosynthesis model (Farquhar, 1983; von Caemmerer, 2000) has not been comprehensively tested across a wide range of species and temperatures. Addressing this gap is critical given that C4 plants include some of the world’s most important food, feed, and biofuel crops (e.g. maize, sorghum, and sugarcane), dominate the understory of warm-climate grasslands and savannas (Ehleringer and Monson, 1993; Brown, 1999; Sage ), and account for 20–25% of terrestrial productivity (Lloyd and Farquhar, 1994).

C4 photosynthesis has evolved independently many times, resulting in multiple biochemical pathways named after the primary C4-acid decarboxylase enzyme found in the bundle sheath cells (BSCs), which are NADP-malic enzyme (-ME), NAD-ME, and phosphoenolpyruvate carboxykinase (PEP-CK) (Hatch 1987). Although PEP-CK operates as a secondary decarboxylase in many C4 species (Leegood and Walker, 2003; Furbank, 2011; Sharwood ; Wang ), the primary decarboxylase is generally associated with a suite of anatomical, biochemical, and physiological features (Gutierrez ; Hattersley, 1992; Kanai and Edwards, 1999; Ghannoum ). The grass family includes species from all biochemical subtypes, but little is known about how these different pathways respond to temperature.

C4 photosynthesis is characterized by the operation of a CO2-concentrating mechanism (CCM) comprising a C4 cycle that fixes atmospheric CO2 into a C4 acid in mesophyll cells (MCs) that is then transported to, and decarboxylated in, BSCs where Rubisco and the C3 cycle are localized (Hatch, 1987). The C4 cycle is faster than the C3 cycle, resulting in elevated CO2 in the BSCs and thus minimizing photorespiration and maximizing CO2 assimilation rates at low intercellular CO2 (Ci) (Hatch, 1987; Kanai and Edwards, 1999). Some CO2 leaks out of the BSCs into the surrounding MCs, costing additional ATP that is required for the phosphorylation of phospenolpyruvate (PEP) in the MCs (Hatch, 1987).

Leakiness (ϕ) describes the efficiency of C4 photosynthesis and is defined as the rate of CO2 leakage out of the BSCs as a fraction of the rate of PEP carboxylation or C4 cycle rate (Vp) (Farquhar, 1983). According to the C4 model, CO2 leakage (L) depends on the BSC wall conductance to CO2 (gbs) and the gradient between the CO2 concentration in the BSCs (Cbs) and MCs (Cm), such that L=gbs(Cbs–Cm). In turn, the BSC–MC CO2 gradient depends on the balance between the activity of the C4 (e.g. PEP carboxylase, PEPC) and C3 (e.g. Rubisco) cycles (Henderson ; von Caemmerer, 2000). The C4 photosynthesis model stipulates that the initial slope of the A-Ci curve (IS) depends on the maximal PEPC activity (Vpmax) while the CO2-saturated rate (CSR) depends on maximal Rubisco activity (Vcmax), in addition to other factors (von Caemmerer, 2000). Consequently, the thermal responses of Vpmax and Vcmax are expected to influence the thermal response of both IS and CSR as well as the BSC–MC CO2 gradient, and hence leakiness. Therefore, in this study we asked whether the thermal responses of these key parameters (Vpmax, Vcmax, IS, CSR, and ϕ) depend on the biochemical subtype of the C4 species.

In a recent study, Sharwood ) showed that the declining response of Rubisco’s in vitro CO2/O2 specificity (Sc/o) with increasing temperature was more pronounced for NAD-ME relative to PEP-CK and NADP-ME species. Given that the CSR of C4 leaves depends strongly on Rubisco and its catalytic properties, we predict that, relative to the other two subtypes, Vcmax of NAD-ME species may increase less with temperature, with possible consequences on Vpmax/Vcmax and ϕ. These predictions remain untested, especially in that thermal responses of Vpmax have been less widely studied than Vcmax (Tieszen and Sigurdson, 1973; Pittermann and Sage, 2000; Sage, 2002; Boyd ; Sharwood ).

In an earlier study, high leaf temperature was found to increase O2 uptake in NAD-ME but not NADP-ME species, pointing to increased Mehler reaction and/or Rubisco oxygenation at higher temperature in NAD-ME species (Siebke ). Higher Rubisco oxygenation may be symptomatic of a less favorable CO2/O2 concentration ratio in the BSCs, which is corroborated by the less relaxed Rubisco affinity for CO2 (higher Km(CO2)) in NAD-ME relative to NADP-ME subtypes (Sharwood ). The suberin lamella lining the BSC walls of NADP-ME and PEP-CK grasses may reduce gbs, which could impact Cbs (Hatch, 1987; von Caemmerer and Furbank, 2003). Consequently, we predict that Cbs and hence leakiness may be affected differently by temperature depending on the C4 subtypes. Previous measurements revealed a slight decrease in leakiness in response to increasing temperature between 21 and 35 °C for the C4 monocot Sorghum bicolor (Henderson ). To our knowledge, the thermal response of leakiness has not yet been compared in C4 grasses with different biochemical subtypes.

The temperature dependence of key parameters of the C4 photosynthesis model has primarily been determined for a few representative species, such as maize and Setaria (Henderson ; Chen ; Massad ; Boyd ). In addition, parameterization can be done in vivo (derived from gas exchange) or in vitro (derived from enzyme assays), but comparisons between these two parameterization methods remains unexplored for different C4 species and temperatures. Relationships between ϕ and the ratio of in vivo (IS/CSR) or in vitro (Vpmax/Vcmax) activities of C4 and C3 carboxylases have been demonstrated for single species under different growth environments (Ranjith ; Saliendra ; Meinzer and Zhu, 1998; Gong ). However, such relationships have rarely been explored for diverse C4 grasses at different temperatures. Addressing these knowledge gaps is critical to our ability to interpret gas exchange data and relate them to underlying biochemistry, as has been done for C3 plants (von Caemmerer and Farquhar, 1981; Hudson ; Bernacchi ).

Consequently, in this study we measured the photosynthetic thermal responses of eight diverse C4 grasses belonging to the three biochemical subtypes. We aimed at determining whether the C4 biochemical subtype influences the thermal responses of (i) in vitro PEPC (Vpmax) and Rubisco (Vcmax) maximal activities, (ii) initial slope (IS) and CO2-saturated rate (CSR) derived from the A-Ci curves, and (iii) CO2 leakage out of the bundle sheath as estimated from carbon isotope discrimination. Our results showed that the thermal photosynthetic responses varied among the C4 species independently of the biochemical subtype. We also observed that the ratios of IS/CS and Vpmax/Vcmax were uncorrelated with each other or with leakiness when determined for a range of C4 species. Finally, we derived constants for thermal dependency that can be incorporated in the C4 photosynthesis model.

Material and methods

Plant culture

The experiment was conducted in a naturally lit glasshouse chamber (5 m3) with a mean noon photosynthetic photon flux density (PPFD) of 1230 ± 22 µmol quanta m−2 s−2 (±SE) and a 10-h photoperiod (see Supplementary Fig. S1 at JXB online). The air temperature inside the glasshouse compartment was regulated and day/night temperatures averaged 28/22 °C. Relative humidity was monitored and ranged between 60–80% during the day. Grass seeds (Table 1) were obtained from the Australian Plant Genetic Resources Information System, Australia. Seeds were sown in germination trays containing a common germination mixture. Seedlings at 3–4 weeks old were transplanted into the experimental pots (2 l) containing Osmocote® Professional – Seed Raising & Cutting Mix (Scotts; www.scottsaustralia.com.au). Nutrients were supplied through the addition of Osmocote® Plus Trace Element: Total All Purpose (N:P:K=19.4:1.6:5) (Scotts) and periodic watering with soluble Aquasol (N:P:K=23.3:3.95:14) (Yates; www.yates.com.au/). For each species there were eight pots, each of which contained a single plant. Pots were well-watered and regularly rotated within the glasshouse chamber.

Table 1.

List of C4 grasses used in the current study.

C4 Subtype	C4 tribe	Species
NADP-ME	PaniceaeAndropogoneae	Cenchrus ciliaris Sorghum bicolor Zea mays
PEP-CK	PaniceaeChloridoideae	Eriochloa meyeriana Megathyrsus maximus Chloris gayana
NAD-ME	PaniceaeChloridoideae	Panicum coloratum Leptochloa fusca

Leaf gas exchange measurements

Leaf gas exchange measurements were carried out using a portable open photosynthesis system (LI-6400XT, LI-COR, Lincoln, USA). Measurements were conducted between 10.00 h and 14.00 h, 7–8 weeks after transplanting, on the last fully expanded leaf (LFEL) attached on the main stem. Prior to gas exchange measurements, plants were moved to another chamber where air temperature could be changed separately. Measurements were made at leaf temperatures of 18, 25, 34, and 40 °C by using the internal heating system of the photosynthesis unit in conjunction with the glasshouse chamber heating system, whilst maintaining a relatively constant humidity inside the leaf chamber. Prior to measurements, each leaf was allowed to reach a steady state of CO2 uptake at ambient CO2 (Reference=400 μl l−1), PPFD of 1800 μmol m−2 s−1, and relative humidity of 50–70%. A steady-state measurement was taken at each of the four leaf temperatures, and this was followed by measuring the responses of CO2 assimilation rate (A) to step increases of intercellular CO2 (Ci) by raising the LI-6400XT leaf chamber [CO2] in 10 steps (i.e. 50, 100, 150, 200, 250, 325, 400, 650, 1200, and 1500 μl l−1) with 2 and 3 min as the minimum and maximum waiting times during each step change, respectively. For dark respiration, light in the LI-6400XT leaf chamber was switched off for 20 min before measurements were made. There were three or four biological replicates, i.e. plants per species. The initial slope (IS) of each A-Ci curve was estimated by fitting a linear model to the initial 3–4 linear data points such that maximum Ci was about 55 μl l−1 at all leaf temperatures. The maximum CO2-saturated rate of each A-Ci curve at each leaf temperature was considered as the CO2-saturated rate (CSR).

Calculation of photosynthetic carbon isotope discrimination, leakiness, and C4 cycle rate

Bundle-sheath leakiness was determined by measuring real-time 13CO2/12CO2 carbon isotope discrimination using a LI-6400XT attached to a tunable diode laser (TDL, model TGA100, Campbell Scientific, Inc., Logan, Utah, USA) under similar conditions to the steady-state measurements. For estimation of TDL precision, we used the δ13C value of the LI-6400XT reference gas for S. bicolor. The mean SD of repeated measurements for δ13C were 0.24, 0.14, 0.20, and 0.28‰ at 18, 25, 32, and 40 oC, respectively, with an overall SD of 0.21‰. Photosynthetic carbon isotope discrimination (∆) was calculated according to Evans :

where δe, δo, Ce, and Co are the δ13C (δ) and CO2 mol fraction (C) measured with the TDL of the air entering (e) and leaving (o) the leaf chamber. Leakiness (ϕ) was calculated using the model of Farquhar (1983) as modified by Pengelly and Pengelly . The slightly modified equation used here is:

where Δ is the photosynthetic carbon isotope discrimination measured by the TDL. ai is the fractionation factor associated with the dissolution of CO2 and its diffusion through water. Here, we assume that s=ai. The term t, which represents ternary effects of transpiration rate on the carbon isotope discrimination during CO2 assimilation, is defined according to Farquhar and Cernusak (2012) as:

where E is the transpiration rate and gtac is the total conductance to CO2 diffusion including boundary layer and stomatal conductance (von Caemmerer and Farquhar, 1981).

The combined fractionation factor through the leaf boundary layer and stomata is denoted by a′:

where: Ca, Ci, and Cls are the ambient, intercellular, and leaf surface CO2 partial pressures, respectively; ab (2.9‰) is the fractionation occurring through diffusion in the boundary layer; s (1.8‰) is the fractionation during leakage of CO2 out of the bundle sheath; and a (4.4‰) is the fractionation due to diffusion in air (Evans ).

and

where: b3 is the fractionation by Rubisco (30‰); b4 is the combined fractionation of the conversion of CO2 to HCO3− and PEP carboxylation (–5.74‰ at 25 °C); f is the fraction associated with photorespiration; Г* is the CO2 partial pressure where rate of photorespiratory CO2 release balances the rate of carboxylation; and Cs is the CO2 partial pressure in the BSC. The fractionation factor e associated with respiration was calculated from the difference between δ13C in the CO2 cylinder used during experiments (–5.6‰) and that in the atmosphere under growth conditions (–8‰) (Tazoe ). A and Rd denote the CO2 assimilation rate and daytime respiration, respectively; Rd was assumed equal to the measured dark respiration (Atkin ). We considered mesophyll conductance (gm) to be 1.78 mol m−2 s−1 at 30 oC (Barbour ; Ubierna ). The temperature dependency of gm was accounted for by using the Arrhenius function:

where Tk is the leaf temperature in K; gm25 is the mesophyll conductance at 25 °C; Ea is the activation energy, taken as 40.6 kJ mol−1 (the value for for Zea mays) (Ubierna ); and R is the universal gas constant (0.008314 kJ K−1). In this study, leaf gas exchange was measured at high light and it was assumed that =0 (Pengelly , 2012; Ubierna ; von Caemmerer ).

We used ϕ, A and Rd to calculate the C4 cycle rate (Vp), assuming that Rubisco oxygenation approximated to zero, i.e. Vo≈0 (Pengelly ).

Determination of Rubisco and soluble protein contents

Following gas exchange measurements, replicate leaf discs were cut and rapidly frozen in liquid nitrogen and then stored at –80 °C until analysis. Each leaf disc was extracted in 0.8 ml of ice-cold extraction buffer [50 mM EPPS-NaOH (pH 7.8), 5 mM DTT, 5 mM MgCl2, 1 mM EDTA, 10 μl protease inhibitor cocktail (Sigma), 1% (w/v) polyvinyl polypyrrolidone] using a 2-ml Tenbroeck glass homogenizer kept on ice. The extract was centrifuged at 15 000 rpm for 1 min and the supernatant was used for enzyme activity (see below), Rubisco content, and soluble protein assays. For Rubisco content, subsamples were activated in buffer [50 mM EPPS (pH 8.0), 10 mM MgCl2, 2 mM EDTA, 20 mM NaHCO3], and content was estimated by the irreversible binding of [14C]-CABP to the fully carbamylated enzyme (Sharwood ). Extractable soluble proteins were measured using the Pierce Coomassie Plus (Bradford) protein assay kit (Thermo scientific, Rockford, USA).

In vitro thermal response of Rubisco and PEPC activities

Enzymatic assays were done for Rubisco and PEPC at 18, 25, 34 and 40 °C. To achieve the target temperatures, cuvettes with assay buffer were kept in incubators for 20 min (18 °C), 10 min (25 °C), 10 min (34 °C), and 5 min (40 °C). The maximal in vitro activities of Rubisco (Vcmax) and PEPC (Vpmax) were measured spectrophotometrically as described previously (Jenkins ; Ashton ; Sharwood , 2014, 2016; Pengelly ). Briefly, Vcmax was measured in assay buffer [50 mM EPPS-NaOH (pH 8), 10 mM MgCl2, 0.5 mM EDTA, 1 mM ATP, 5 mM phosphocreatine, 20 mM NaHCO3, 0.2 mM NADH, 50 U creatine phosphokinase, 0.2 mg carbonic anhydrase, 50 U 3-phosphoglycerate kinase, 40 U glyceraldehyde-3-phosphate dehydrogenase, 113 U triose-phosphate isomerase, 39 U glycerol-3-phosphate dehydrogenase] and the reaction was initiated by the addition of 0.22 mM ribulose-1, 5-bisphosphate (RuBP). Vpmax was measured in assay buffer [50 mM EPPS-NaOH (pH 8.0), 0.5 mM EDTA, 10 mM MgCl2, 0.2 mM NADH, 5 mM glucose-6-phosphate, 0.2 mM NADH, 1 mM NaHCO3, 1 U MDH] after the addition of 4 mM PEP. Maximal activities of Rubisco and PEPC were calculated by monitoring the decrease of NADH absorbance at 340 nm using a UV-VIS spectrophotometer (model 8453, Agilent Technologies Australia, Mulgrave, Victoria).

Temperature dependency

The temperature response of A, CSR, IS, Vpmax, and Vcmax were fitted in the R software (R Development Core Team, 2015) using two different equations, as follows. A modified form of the Arrhenius equation was used to fit the temperature dependence, which yields a peak function (Harley ; Crous ), and is given by the following equation:

where, Tk is the measurement temperature (either leaf or assay buffer) in K; Ea is the activation energy (kJ mol−1) and represents the expansion for the initial part of the temperature response curve; k25 is the parameter at 25 °C; Hd is the deactivation energy (kJ mol−1); R is the universal gas constant; and ∆S (kJ mol−1 K−1) is the entropy term, which describes the peak part of the curve. Hd and ∆S together describe the rate of decrease in the function above the optimum. To avoid over-parameterization, the Hd of all parameters was set as constant (200 kJ mol−1) for model fitting, as has been done previously (Medlyn ; Crous ).

The outputs from the modified Arrhenius and the June equations are compared in Supplementary Fig. S2. The modified form of the Arrhenius equation over-estimates the optimum parameter rate, Popt, at the temperature optimum, Topt. Consequently, Topt and Popt were derived by following the June equation:

where T is the measurement temperature (either leaf or assay buffer) of parameter P in °C; Popt is the optimum parameter rate at the optimum temperature, Topt; and Ω is the difference in temperature from Topt at which the parameter falls to e−1 (0.37) of its value at Topt. A smaller value of Ω means a narrower peak. This equation effectively assumes that the reversible processes are symmetrical around the optimum temperature.

Statistical analyses

The statistical design included species, subtypes, and leaf temperature as factors. Due to the limited number of species used, the statistical analyses could not incorporate phylogenetic or evolutionary effects. Gas exchange measurements and enzyme activity measurements were performed on three or four replicates at each temperature. The coefficients derived by fitting equations (10) and (11) for each parameter were used to test for differences between the thermal responses of species and subtypes. The effect of species was compared using a linear model with type-II ANOVA. The effect of subtype was compared using a linear mixed-effect model using the lme4 package (https://rdrr.io/cran/lme4/) in R (R Development CoreTeam, 2015). Significance tests were performed using type-II ANOVA. Coefficient means were ranked using post hoc Tukey tests.

Recent studies have highlighted the flexibility of the decarboxylases; in particular, the expression of PEP-CK activity in NADP-ME subtypes (Wingler ; Furbank, 2011; Bellasio and Griffiths, 2014). Except for a relatively high activity in Z. mays (one-third of total decarboxylase activity), PEP-CK activity for most NADP-ME subtypes including those used in the current study does not exceed 5–25% of the total decarboxylase activity (see Supplementary Fig. S3). In addition, among the three species in the NADP-ME subtype, two are highly domesticated (S. bicolor and Z. mays), and Z. mays and Cenchrus ciliaris had appreciable secondary PEP-CK activity. However, the three NADP-ME species did not separate according to their known PEP-CK activity or domestication for the parameters collected (Supplementary Fig. S3). Consequently, for the purposes of the current study, it was valid to analyse the NADP-ME species as a single group rather than as one made up of multiple subgroups.

Results

Leaf gas exchange at 25 °C

Leaf gas exchange parameters were measured at ambient CO2 and near-saturating light intensity for all the C4 grasses concurrently with stable carbon isotope discrimination. At 25 °C, net CO2 assimilation rate (A), stomatal conductance (gs), the ratio of internal to atmospheric CO2 partial pressure (Ci/Ca), dark respiration (Rd), and photosynthetic carbon isotope discrimination (∆) all varied significantly among the species (P<0.05; Fig. 1, Supplementary Table S1). Only A varied significantly (P<0.05) according to the C4 subtype, with NAD-ME species having lower A relative to NADP-ME and PEP-CK species. Photosynthetic carbon isotope discrimination was lowest in Megathyrsus maximus and Z. mays, and highest in C. ciliaris, Chloris gayana, and Leptochloa fusca.

Fig. 1.

Thermal responses of leaf gas exchange and photosynthetic carbon isotope discrimination in eight C4 grasses. (A–C) CO2 assimilation rate, A, (D–F) stomatal conductance, g, (G–I) ratio of intercellular to ambient CO2, Ci/Ca, and (J–L) photosynthetic carbon isotope discrimination, Δ, as a function of leaf temperature for the C4 subtypes NADP-ME, PEP-CK, and NAD-ME (as indicated). The grasses were grown in a common glasshouse. Data in (A–F) were fitted according to June and the derived constants are shown in Table 2. Leaves were measured at 1800 μmol m–2 s–1 PPFD and 400 μl l–1 CO2. Values are means of 3–4 replicates ±SE.

Table 2.

Summary of thermal responses of photosynthetic parameters for eight C4 grasses.Coefficients are derived by fitting equation (10) (modified Arrhenius) and equation (11) (June et al., 2004). Ea is the activation energy (kJ mol−1), ∆S is an entropy term (kJ mol−1), k25 and Popt are the parameter values at 25 °C and its optimum temperature (Topt), respectively. Ω (°C) is the difference in temperature from Topt at which the parameter falls to e−1 (0.37) of its value at T. Values are means of three replicates ±SE. The ranking (from lowest =a) of species/subtypes within each individual row was derived using a multiple-comparison Tukey’s post hoc test. Values followed by the same letter are not significantly different at the 5% level. P-values show significance levels derived by fitting a linear model for all the C4 species and a linear mixed-effect model for the three C4 subtypes for each parameter: ns, not significant (P>0.05); * P<0.05; ** P<0.01; *** P<0.001.

Parameter	Const.	NADP-ME			PEP-CK			NAD-ME		Subtype			P-value
		C. ciliaris	S. bicolor	Z. mays	M.maximus	Ch.gayana	E.meyeriana	P.coloratum	L. fusca	NADP-ME	PEP-CK	NAD-ME	Species	Subtype
CO2 assimilation rate, A(µmol m–2 s-1)	E a	36 ± 1a	42 ± 7a	34 ± 3a	50 ± 7a	36 ± 7a	48 ± 7a	51 ± 4a	54 ± 13a	37 ± 3a	45 ± 4ab	52 ± 5b	ns	*
	∆S	0.63 ± 0a	0.63 ± 0a	0.64 ± 0a	0.64 ± 0a	0.63 ± 0.01a	0.63 ± 0a	0.63 ± 0a	0.64 ± 0.01a	0.63 ± 0a	0.63 ± 0a	0.64 ± 0a	ns	ns
	k 25	26 ± 1b	28 ± 1b	34 ± 1c	28 ± 1b	28 ± 1b	24 ± 1ab	21 ± 1a	25 ± 0ab	29 ± 1a	27 ± 1a	23 ± 1a	***	0.1
	P opt	40 ± 1abc	42 ± 0bc	43 ± 1bc	41 ± 1abc	38 ± 1ab	46 ± 3c	36 ± 1a	41 ± 0abc	42 ± 1a	41 ± 1a	38 ± 1a	**	ns
	T opt	41 ± 3a	39 ± 4a	33 ± 1a	35 ± 1a	37 ± 3a	43 ± 6a	39 ± 2a	38 ± 3a	38 ± 2a	38 ± 2a	38 ± 1a	ns	ns
	Ω	25 ± 3a	24 ± 6a	20 ± 2a	18 ± 2a	23 ± 4a	22 ± 5a	20 ± 2a	19 ± 4a	23 ± 2a	21 ± 2a	20 ± 2a	ns	ns
CO2 saturated rate, CSR (µmol m–2 s–1)	E a	36 ± 1a	58 ± 2b	45 ± 1ab	45 ± 7ab	42 ± 5ab	49 ± 7ab	44 ± 2ab	37 ± 0ab	47 ± 3a	45 ± 3a	41 ± 2a	*	ns
	∆S	0.63 ± 0a	0.64 ± 0b	0.64 ± 0b	0.64 ± 0b	0.63 ± 0ab	0.64 ± 0b	0.64 ± 0b	0.63 ± 0ab	0.64 ± 0a	0.64 ± 0a	0.64 ± 0a	**	ns
	k 25	31 ± 1ab	29 ± 1a	34 ± 0b	28 ± 0a	31 ± 1ab	32 ± 1ab	29 ± 1a	30 ± 1ab	32 ± 1a	30 ± 1a	29 ± 1a	ns	ns
	P opt	51 ± 1c	50 ± 1bc	44 ± 1abc	40 ± 2a	45 ± 1ac	49 ± 2bc	42 ± 1a	43 ± 2ab	48 ± 1a	45 ± 1a	42 ± 1a	***	ns
	T opt	42 ± 3b	36 ± 0ab	32 ± 0a	36 ± 0ab	36 ± 1ab	36 ± 1ab	35 ± 0a	36 ± 1ab	37 ± 2a	36 ± 0a	35 ± 0a	**	ns
	Ω	26 ± 3c	17 ± 0bc	17 ± 0ac	21 ± 2a	20 ± 2ac	19 ± 2bc	18 ± 0a	21 ± 1ab	20 ± 2a	20 ± 1a	19 ± 1a	*	ns
Rubisco activity, Vcmax(umol m–2 s–1)	E a	42 ± 3ab	36 ± 6a	52 ± 6ab	38 ± 1ab	52 ± 4ab	42 ± 5ab	47 ± 3ab	58 ± 4b	43 ± 3a	44 ± 3a	52 ± 3a	*	ns
	∆S	0.63 ± 0a	0.62 ± 0a	0.63 ± 0a	0.63 ± 0a	0.63 ± 0a	0.63 ± 0a	0.63 ± 0a	0.63 ± 0a	0.63 ± 0a	0.63 ± 0a	0.63 ± 0a	ns	ns
	k 25	13 ± 2a	27 ± 3b	27 ± 1b	19 ± 1ab	21 ± 2ab	16 ± 1a	19 ± 1ab	17 ± 1a	23 ± 3a	19 ± 1a	18 ± 1a	***	ns
	P opt	24 ± 4a	47 ± 1b	49 ± 2b	37 ± 3ab	44 ± 3ab	30 ± 3ab	35 ± 6ab	39 ± 7ab	40 ± 4a	37 ± 3a	37 ± 4a	**	ns
	T opt	42 ± 4a	45 ± 2a	39 ± 0a	47 ± 3a	44 ± 4a	46 ± 1a	42 ± 4a	44 ± 4a	42 ± 2a	46 ± 2a	43 ± 3a	ns	ns
	Ω	23 ± 3a	28 ± 2b	20 ± 1b	29 ± 2ab	23 ± 3ab	27 ± 2ab	22 ± 2ab	22 ± 3ab	24 ± 2a	26 ± 1a	22 ± 2a	ns	ns
Initial slope, IS(µmol m–2 s–1 µbar–1)	E a	47 ± 2ab	70 ± 9b	34 ± 13a	27 ± 3a	48 ± 5ab	43 ± 7ab	47 ± 3ab	52 ± 8ab	53 ± 8a	39 ± 4a	49 ± 3a	**	ns
	∆S	0.62 ± 0.01a	0.63 ± 0.01a	0.63 ± 0.01a	0.63 ± 0a	0.64 ± 0a	0.63 ± 0.01a	0.63 ± 0a	0.64 ± 0a	0.63 ± 0a	0.63 ± 0a	0.64 ± 0a	ns	0.06
	k 25	0.35 ± 0.05ac	0.27 ± 0.04a	0.57 ± 0.02d	0.32 ± 0.02ac	0.41 ± 0.04bc	0.3 ± 0.02ab	0.29 ± 0.01ab	0.47 ± 0.01cd	0.38 ± 0.05a	0.35 ± 0.02a	0.36 ± 0.04a	***	ns
	P opt	1.67 ± 0.68b	0.9 ± 0.1ab	0.73 ± 0.01a	0.42 ± 0.03a	0.63 ± 0.03a	0.66 ± 0.11a	0.49 ± 0.04a	0.7 ± 0.08ab	1.03 ± 0.2a	0.58 ± 0.06a	0.57 ± 0.05a	*	ns
	T opt	72 ± 14b	48 ± 5ab	33 ± 2a	38 ± 2a	36 ± 2a	51 ± 8ab	40 ± 2a	34 ± 2a	49 ± 7a	38 ± 2a	42 ± 3a	**	ns
	Ω	39 ± 4b	22 ± 3ab	20 ± 3a	28 ± 4ab	19 ± 2a	31 ± 5ab	22 ± 2ab	17 ± 0a	25 ± 3a	20 ± 2a	26 ± 3a	*	ns
PEPC activity, Vpmax(µmol m–2 s–1)	E a	39 ± 1a	44 ± 3a	61 ± 6bc	39 ± 5a	47 ± 2ab	39 ± 1a	65 ± 3c	51 ± 2ac	48 ± 4a	42 ± 2a	58 ± 4a	***	ns
	∆S	0.62 ± 0a	0.64 ± 0cd	0.64 ± 0d	0.63 ± 0bc	0.63 ± 0bd	0.62 ± 0ab	0.64 ± 0cd	0.64 ± 0 cd	0.63 ± 0a	0.63 ± 0a	0.64 ± 0a	***	ns
	k 25	71 ± 6a	186 ± 6c	156 ± 7bc	44 ± 18a	81 ± 12a	135 ± 11b	42 ± 3a	37 ± 7a	138 ± 17a	87 ± 15a	40 ± 4a	***	0.07
	P opt	197 ± 19bcd	255 ± 23d	234 ± 18cd	70 ± 30a	138 ± 23ac	288 ± 33d	90 ± 10ab	61 ± 14a	229 ± 13a	165 ± 35a	76 ± 10a	***	0.07
	T opt	61 ± 5c	33 ± 1a	34 ± 1a	40 ± 1ab	40 ± 2ab	51 ± 3bc	40 ± 3ab	37 ± 1a	43 ± 5a	43 ± 2a	39 ± 2a	***	ns
	Ω	36 ± 2bcd	17 ± 0d	16 ± 1cd	24 ± 3a	21 ± 1ac	30 ± 2d	18 ± 2ab	19 ± 0a	23 ± 3a	25 ± 2a	19 ± 1a	***	ns

Temperature response of leaf gas exchange

The initial slope (IS) and CO2-saturated rate (CSR) of photosynthetic response to intercellular CO2 partial pressure (from A-Ci curves) were estimated at four temperatures (see Supplementary Fig. S4). At 25 °C, IS, CSR, and IS/CSR varied significantly with species but not with subtypes. Zea mays and L. fusca had the highest IS and IS/CSR, while M. maximus had the lowest CSR relative to the other C4 species (Fig. 2, Supplementary Table S2).

Fig. 2.

Thermal responses of the CO2-saturated rate (CSR) and the initial slope of the A-Ci curve (IS) in eight C4 grasses. (A–C) CO2-saturated rate, CSR, (D–F) initial slope of the CO2 response curve, IS, and (G–I) the IS/CSR ratio as a function of leaf temperature for the C4 subtypes NADP-ME, PEP-CK, and NAD-ME (as indicated). Data in (A–F) were fitted according to June and the derived parameters are shown in Table 2. Leaves were measured at 1800 μmol m–2 s–1 PPFD. Values are means of 3–4 replicates ±SE

Rubisco and PEPC measurements at 25 °C

Maximal activities of PEPC (Vpmax) and Rubisco (Vcmax) were measured on the same leaves used for gas exchange. At 25 °C, Vcmax and Vpmax were highest in the two NADP-ME subtypes S. bicolor and Z. mays. Vpmax and Vpmax/Vcmax were lowest in the two NAD-ME subtypes along with M. maximus (PEP-CK) relative to the other species (Fig. 3, Supplementary Table S2). In line with earlier studies, we obtained an average extraction yield of 80% for Vcmax (maximal CO2 assimilation/Rubisco activity) for wild C4 grasses (Meinzer and Zhu, 1998; Kingston-Smith ; Crafts-Brandner and Salvucci, 2002; Dwyer ).

Fig. 3.

Thermal responses of photosynthetic enzyme activities in eight C4 grasses. (A–C) Rubisco activity, (D–F) PEPC activity, and (G–I) the PEPC/Rubisco activity ratio as a function of temperature for the C4 subtypes NADP-ME, PEP-CK, and NAD-ME (as indicated). For each extract, the temperature responses of both enzymes were measured at 18, 25, 34, and 40 °C. Data in (A–F) are fitted according to June and the derived parameters are shown in Table 2. Values are means of 3–4 replicates ±SE.

Leaf Rubisco content varied among the species (3.8–7.8 µmol sites m–2), constituting about 6% of the soluble protein fraction (Supplementary Table S3). Among all the species, Rubisco and soluble protein contents were highest in Z. mays and Panicum coloratum and lowest in C. ciliaris, Eriochloa meyeriana, and L. fusca. Rubisco activation measured at 25 °C tended to be higher in NADP-ME (69%) compared to PEP-CK (53%) and NAD-ME (54%) subtypes.

Thermal responses of photosynthetic parameters

The short-term thermal responses of A, IS, CSR, Vpmax, and Vcmax were well characterized by the modified Arrhenius and June equations (equations 10 and 11, Supplementary Figs S2 and S5–S8). No subtype effect was observed for the activation energy (Ea), entropy factor (∆S), parameter at 25 °C (k25), the optimum parameter (Popt) at the optimum temperature (Topt), or the width of curvature around Topt (Ω) derived for IS, CSR, Vpmax, and Vcmax (Table 2).

For CO2 assimilation rate, the range of variation observed for Topt (33–43 °C), Ea (34–54 kJ mol−1), and Ω (18–24 °C) was not significantly different among all the species (Fig. 1A–C, Table 2). Ea was significantly lower (P<0.05) in NADP-ME subtypes (37 kJ mol−1) relative to NAD-ME (52 kJ mol−1). Conversely, k25 tended to higher (P=0.1) in NADP-ME subtypes relative to NAD-ME. For CSR, C. ciliaris had the highest Popt, Topt, and Ω, while P. coloratum and M. maximus had the lowest Popt, and Z. mays and P. coloratum had the lowest Topt. For IS, C. ciliaris had the highest Topt, Popt, and Ω, while Ea was highest in S. bicolor and lowest in Z. mays and M. maximus relative to the other species (Fig. 2, Table 2). Overall, the ratio IS/CSR was not affected by leaf temperature, except in S. bicolor where IS/CSR increased with temperature (Fig. 2, Supplementary Table S2).

For the temperature response of in vitro Vcmax, no parameter varied significantly according to the biochemical subtype, while Ea, k25, and Popt varied among all the species (Table 2). Rubisco Ea was highest in L. fusca (58 kJ mol−1) and lowest in S. bicolor (36 kJ mol−1), while Rubisco k25 and Popt were highest in S. bicolor and Z. mays and lowest in C. ciliaris (Fig. 3A–C, Table 2).

All parameters describing the thermal response of in vitro Vpmax varied significantly among all the species. In addition, Popt and k25 tended to be lowest (P<0.07) in NAD-ME, intermediate in PEP-CK, and highest in NADP-ME subtypes (Fig. 3D–F, Table 2). Overall, the ratio IS/CSR was unaffected by leaf temperature (Fig. 3, Supplementary Table S2).

Photosynthetic carbon isotope discrimination and bundle sheath leakiness

Photosynthetic carbon isotope discrimination (∆) was unchanged between 25 and 40 °C and increased significantly at 18 °C for most of the species, except in S. bicolor and E. meyeriana where it decreased at 18 °C (Fig. 1J–LSupplementary Table S1). Overall, the NAD-ME subtypes showed higher Δ compared to NADP-ME and PEP-CK. Leakiness (ϕ) was higher at the two lowest temperatures (18 and 25 °C) relative to the two highest temperatures (34 and 40 °C), with ϕ at 40 °C being similar among all the species (Fig. 4A–C, Supplementary Table S1). Sorghum bicolor, M. maximus, and E. meyeriana had lower ϕ relative to the other species at both 18 and 34 °C. Generally, most leakiness values ranged between 35% at 18 °C and 10% at 40 °C (Supplementary Fig. S11). The estimated C4 cycle rate (Vp) increased between 18 and 35 °C and was similar between 35 and 40 °C for all the species (Fig. 4D–F, Supplementary Table S1).

Fig. 4.

Thermal responses of bundle sheath leakiness and the C4 cycle rate in eight C4 grasses. (A–C) Estimated leakiness (ϕ) and (D–F) C4 cycle rate (Vp) as a function of leaf temperature for the C4 subtypes NADP-ME, PEP-CK, and NAD-ME (as indicated). The grasses were grown in a common glasshouse. Leaves were measured at 1800 μmol m–2 s–1 PPFD and 400 μl l–1 CO2. Values are means of 3–4 replicates ±SE.

Relationships among photosynthetic parameters

In vivo estimates of CO2 assimilation rate (A), stomatal conductance (gs), CO2-saturated rate (CSR), initial slope (IS), and leakiness (ϕ), and in vitro measurements of Vcmax and Vpmax were used to assess how in vivo and in vitro photosynthetic parameters correlated with short-term changes in temperature.

Weak relationships were observed between IS and Vpmax (r2=0.21, Fig. 5A) and between CSR and Vcmax (r=0.48, Fig. 5B), and a strong relationship was observed between A and gs (r=0.78, Supplementary Fig. S10). Leakiness (ϕ) was neither correlated to Vpmax/Vcmax nor to IS/CSR (Fig. 6A, B). The ratios of IS/CSR and Vpmax/Vcmax were also not correlated (Fig. 6C).

Fig. 5.

Relationships between measured in vitro and in vivo estimates of photosynthetic carboxylases. (A) The initial slope of the CO2 response curve, IS, versus PEPC activity, and (B) CO2 saturated rate, CSR, versus Rubisco activity, measured at 18, 25, 34, and 40 °C (as indicated) in the C4 subtypes NADP-ME (circles), PEP-CK (squares), and NAD-ME (triangles). The solid lines represent regressions of all data points.

Fig. 6.

Relationships between leakiness and the activity ratio of in vitro or in vivo C4 and C3 cycle carboxylases. (A) Leakiness (ϕ) versus the ratio of the initial slope of the CO2 response curve (IS) and the CO2-saturated rate (CSR), (B) ϕ versus the ratio of PEPC and Rubisco activities, and (C) the IS/CSR ratio versus the ratio of PEPC and Rubisco activities, measured at 18, 25, 34, and 40 °C (as indicated) in the C4 subtypes NADP-ME (circles), PEP-CK (squares), and NAD-ME (triangles). The solid lines represent linear regressions of all data points.

To shed further light on what controls IS in diverse C4 grasses, we used the simplified expression linking Vpmax with IS derived by Pfeffer and Peisker (1998):

where Kp is the Michaelis–Menten constant for CO2. A weak fit was observed between measured Vpmax values and model predictions when published Kp values from Z. mays were used (Supplementary Fig. S12A, dotted and dashed lines). When equation (12) was solved to simultaneously predict gm and Kp using measured Vpmax and IS values for Z. mays at all four temperatures together with published temperature dependencies of gm and Kp (Bauwe, 1986; Boyd ; Ubierna ), the observed fit between the measured and modelled data was much improved (Supplementary Fig. S12A, continuous line, and S12B). Fitted values for Z. mays at 25 °C for gm and Kp were then found to be 1.1 mol m−2 s−1 and 115 µbar, respectively (Fig. S12A).

Discussion

This study analysed the thermal photosynthetic responses of eight diverse C4 grasses, deriving constants for thermal dependency that can be incorporated in the C4 photosynthesis model (von Caemmerer, 2000). The main aim of the study was to determine whether the C4 biochemical subtype influenced the thermal responses of in vitro (Vpmax and Vcmax) and in vivo (IS, CSR, and ϕ) photosynthetic parameters that influence the efficiency of the C4 CO2-concentrating mechanism (CCM). The study also explored whether the ratios of IS/CSR and Vpmax/Vcmax were correlated with each other or with leakiness across a range of C4 species. The answers to these questions were largely negative, as discussed below.

Thermal photosynthetic responses varied among the C4 grasses independently of the biochemical subtype

This study revealed large interspecific variations for most parameters derived from the photosynthetic temperature responses; however, these variations were largely independent of the C4 subtype, disagreeing with our prediction (Table 2). There was one exception to this generalization, with the activation energy (Ea) of CO2 assimilation being lowest in the NADP-ME subtype. In addition, Vpmax at 25 °C (k25) and at Topt (Popt) were marginally (P=0.07) lowest in NAD-ME and highest in NADP-ME subtypes. The latter observation is consistent with our previous reports of NAD-ME subtypes generally having lower Vpmax and Vpmax/Vcmax (Pinto ).

The Ea for in vitro Vcmax (36–58 kJ mol−1) and Vpmax (39–65 kJ mol−1) and their corresponding in vivo CSR (36–58 kJ mol−1) and IS (27–70 kJ mol−1) varied by 2-fold among the species examined here. Although these values are in line with published estimates for C3 (Vcmax) and C4 (Vcmax and Vpmax) species, they tended to lie at the lower end of the spectrum reported for most of the C4 grasses used in our study (Ishii ; Bernacchi ; Medlyn ; Sage, 2002; Galmés , 2015; Massad ; Walker ; Perdomo ; Sharwood ). For example, higher E was reported for Vcmax (78 kJ mol−1) and Vpmax (95 kJ mol−1) activities in the NADP-ME grass Setaria viridis (Boyd ), while relatively higher values of Ea were reported for the in vivo Vpmax of the C4 species Z. mays and Andropogon gerardii (60–77.9 kJ mol−1) (Wu and Wedding, 1987; Chen ). Interestingly, Ea was higher for Vcmax than Vpmax in C. ciliaris, Ch. gayana, E. meyeriana, and L. fusca, while the opposite was observed in S. bicolor, Z. mays, M. maximus, and P. coloratum. Similarly, lower Ea for Vcmax than Vpmax was reported in S. viridis (in vitro) (Boyd ), and the opposite trend was reported in A. gerardii (in vivo) (Chen ).

We predicted that thermal photosynthetic responses including leakiness may depend on the biochemical subtypes, based on known differences in Rubisco catalytic properties, PSII activity in the BSCs, suberization of the BSC walls, and possibly other anatomical and biochemical traits. In this study, similar thermal responses for leakiness were observed between the C4 subtypes, and ϕ at 40 °C was similar for all the species. Comparable results were obtained in an earlier study using a smaller set of C4 grasses measured at a common temperature (Cousins ). These results suggest that CCM efficiency is similar among the C4 subtypes despite their biochemical and anatomical differences. This was evident despite the potential for increased oxygenation in NAD-ME and PEP-CK species with increases in temperature (Siebke ) as a result of significant PSII activity in the BSCs of these two subtypes (Edwards ; Ghannoum ). It has also been suggested that the absence of suberin in the BSC walls of NAD-ME subtypes is counterbalanced by the greater cytosolic barrier that exists for CO2 diffusion through the centripetal arrangement of BSC chloroplasts surrounded by mitochondria towards the vascular bundle side (von Caemmerer and Furbank, 2003). However, little is known about the thermal dependence of the CO2 diffusion path from the BSCs to MCs in the different C4 subtypes.

In the current study, leakiness tended to be higher at the two lowest (18 and 25 °C) relative to the two highest (34 and 40 °C) temperatures for four out of the eight C4 grasses (see Supplementary Fig. S11). Similar results were previously reported for a C4 monocot and a C4 dicot species (Henderson ). To gain further insights about the factors leading to higher leakiness at lower temperatures, we calculated the C4 cycle rate (Vp). For all the species, the calculated Vp increased with temperature, which indicates that increased leakiness at lower temperatures in some of the species is not related to increased pumping of CO2 into the BSCs, but is probably due to increased Rubisco limitation. In agreement with this, Sage (2002) showed that C4 plants are limited by Vcmax at low temperature. Taken together, these findings indicate a greater Rubisco limitation at low temperature, which may lead to a greater proportion of CO2 leakage out of the BSCs in some C4 species (Kubien ; Kubien and Sage, 2004), in a manner not explained by the biochemical subtype.

Maximal in vitro activities of PEPC and Rubisco, the initial slope and maximal rate of the A-Ci curves, and leakiness are not correlated across a range of C4 grasses and leaf temperatures

Major progress has been made in our understanding of C3 photosynthesis following the development of a fully mechanistic model (Farquhar ) that was subsequently validated by combining leaf gas exchange measurements with estimates of Rubisco activity and mesophyll conductance (gm) in wild-type (von Caemmerer and Farquhar, 1981; von Caemmerer ; Bernacchi ; von Caemmerer and Evans, 2015) and genetically altered plants (Hudson ). For C4 photosynthesis, model validation has been undertaken mostly under standard conditions using a genetically altered C4 dicot, Flaveria bidentis (von Caemmerer ; Kubien ; Pengelly ), or under a range of conditions using a limited number of model C4 grass species, such as S. bicolor (Henderson ), Z. mays (Yin ) and S. viridis (Boyd ). This study presented an ideal opportunity to undertake model validation using in vitro enzyme assays and leaf gas exchange measurements for a range of C4 species.

A weak correlation was observed between CSR and Vcmax, while none was found between IS and Vpmax (Fig. 5), or between Ea of Vcmax (or Vpmax) and Ea of CSR (or IS) across the various C4 grasses. This discrepancy is not surprising and reflects the multitude of factors controlling the A-Ci curves besides the maximal in vitro activity of Rubisco and PEPC. Other than Rubisco activity and level of activation, CSR is also dependent on RuBP and PEP regeneration, and both limitations are generally indistinguishable at high light (von Caemmerer, 2000). The IS is determined by the maximal PEPC activity (Vpmax), its Michaelis–Menten constant for CO2 (Kp), and the mesophyll CO2 partial pressure (Cm), which depends on mesophyll conductance (gm) (von Caemmerer, 2000). The parameters gm and Kp were not measured in this study, but using published values at 25 °C together with their temperature dependencies for Z. mays (Bauwe, 1986; Boyd ; Ubierna ) to model the relationship between IS and Vpmax, a weak fit was observed between measured and predicted Vpmax values (Supplementary Fig. S12A, dotted and dashed lines). In contrast, when model predictions were made using simultaneously solved gm and Kp values using measured Vpmax and IS for Z. mays at all four temperatures, the observed fit between measured and modelled Vpmax was much improved (Supplementary Fig. S12A, continuous line, and S12B). This exercise indicated that gm and Kp as well as their temperature responses may vary with growth environment and species (or genotype), as has recently been shown for Rubisco kinetics among these C4 grasses (Sharwood ). The variation in gm and its temperature response in C3 species is well established (von Caemmerer and Evans, 2015), and discrepancies for gm in C4Z. mays have been reported (Barbour ; Ubierna ).

In C3 species, IS (Rubisco-limited photosynthesis) is largely insensitive to temperature because both the Km and Vcmax of Rubisco have a Q10 of 2 (Berry and Raison, 1981; Sage and Sharkey, 1987). In contrast, we observed a strong temperature response of IS (PEPC-limited) for the C4 species examined, indicating that the Ea for Vpmax is greater than the Ea of Kp (Table 2, Fig. 2D–F). A similar trend has been shown in a recent study (Boyd ). In addition, variation among C4 species for the Ea of IS suggests that the ratio between Ea for Vpmax and Kp also differs. This has been partly supported by our data in the case of the Ea for Vpmax (Table 2, Fig. 3D–F). These findings indicate that there is a significant diversity for PEPC kinetics among C4 species, and warrants further investigation.

The improved relationship between measured and modelled Vpmax relative to that observed between IS and measured Vpmax (Supplementary Fig. S12A versus S12B) demonstrates that the C4 photosynthesis model, when well parameterized, can accurately predict CO2 assimilation rates at limiting Ci in C4 leaves. Given the rapidly improving methodologies for measuring the exchange of 13C and 18O stable isotopes that allow us to estimate both gm and Kp (von Caemmerer ; Boyd ; Barbour ; Ubierna ), the C4 photosynthesis model will form a valuable tool for interpreting leaf gas exchange data for any C4 species under a wide range of environmental conditions, similarly to what has been widely achieved for C3 plants. Further parameterization and validation of the C4 photosynthesis model for diverse C4 species remains a focus of our current research.

Bundle sheath leakiness (ϕ) depends on gbs and the (Cbs–Cm) gradient, which in turn depends on the balance between the activities of PEPC and Rubisco (Henderson ; von Caemmerer, 2000). In accordance with model predictions, earlier studies reported a relationship between leakiness and in vitro Vpmax/Vcmax (Ranjith ; Saliendra ; Meinzer and Zhu, 1998) and in vivo IS/CSR (Gong ). These studies used a single species (sugarcane or Cleistogenes squarrosa) exposed to soil or atmospheric water deficit, and estimated ϕ from the C-isotope composition of leaf dry matter rather than photosynthetic C-isotope discrimination as done here. In the current study, leakiness was neither correlated to in vitro Vpmax/Vcmax nor to IS/CSR when all species and leaf temperatures were considered (Fig. 6). There were three exceptions at the species level: leakiness was positively correlated with Vpmax/Vcmax (but not with IS/CSR) in Ch. gayana, L. fusca, and Z. mays (see Supplementary Figs S13 and S14). Hence, we argue that, in response to short-term changes in leaf temperature, CCM efficiency was balanced by biochemical factors, such as enzyme activity, as well as by physical factors, such as gbs (von Caemmerer, 2000). A contribution by gm is unlikely because very little influence of gm on the carbon isotope discrimination (∆) has been predicted (von Caemmerer ).

Conclusions

Modelling thermal photosynthetic responses at the leaf level is critical for predicting canopy-scale gas exchange in response to diurnal and seasonal changes in leaf temperature (Harley and Baldocchi, 1995). Thermal sensitivities of parameters used by the C4 photosynthesis model are needed to accurately predict CO2 exchange in response to temperature. The findings from the current study demonstrated that, like C3 photosynthesis (Bernacchi ; Walker ), in vivo and in vitro thermal responses of key photosynthetic parameters (e.g. PEPC and Rubisco activities) differ across C4 species. Hence, relying on the thermal responses of selected species to model C4 photosynthesis cannot accurately describe ecosystem responses.

The current study also demonstrated that variations in the thermal responses of leakiness (ϕ) among the C4 grasses is not aligned with the C4 subtypes. This indicates that various biochemical and anatomical trade-offs operate to maintain similar CCM efficiencies in the various C4 biochemical pathways. In addition, no correlations were observed among leakiness, Vpmax/Vcmax, and IS/CSR across a range of C4 grasses and leaf temperatures. Hence, more work is needed to characterize the thermal responses of gm and gbs in diverse C4 species by combining stable isotope and chlorophyll fluorescence studies (Yin ).

Supplementary data

Supplementary data are available at JXB online.

Table S1. Summary of leaf gas exchange parameters for eight C4 grasses.

Table S2. Summary of A-Ci-derived parameters and enzyme activities for eight C4 grasses.

Table S3. Rubisco and protein content of leaves.

Fig. S1. Light environment in the glasshouse during plant growth.

Fig. S2. Comparison of the June and modified Arrhenius models for temperature response.

Fig. S3. Principle component analysis plots for species of the NADP-ME subtype, and all three C4 subtypes.

Fig. S4. Photosynthetic CO2 response curves (A-Ci) measured at four-leaf temperatures in eight C4 grasses.

Fig. S5. Thermal responses of the CO2 assimilation rate (A), CO2-saturated rate (CSR), and initial slope of the A-Ci curve (IS) in eight C4 grasses fitted using the June model.

Fig. S6. Thermal responses of photosynthetic enzyme activities in eight C4 grasses fitted using the June model.

Fig. S7. Thermal responses of the CO2 assimilation rate (A), CO2-saturated rate (CSR), and initial slope of the A-Ci curve (IS) in eight C4 grasses fitted using the modified Arrhenius model.

Fig. S8. Thermal responses of photosynthetic enzyme activities in eight C4 grasses fitted using the modified Arrhenius model.

Fig. S9. Photosynthetic carbon isotope discrimination, Δ, as a function of Ci/Ca measured during the gas exchange for eight C4 grasses.

Fig. S10. Relationship between CO2 assimilation rates and stomatal conductance in eight C4 grasses.

Fig. S11. Thermal response of leakiness in eight C4 grasses.

Fig. S12. Relationship between measured and modelled PEPC activity at various leaf temperatures in Z. mays.

Fig.S13. Relationship between leakiness and ratio of PEPC to Rubisco activity in eight C4 grasses.

Fig. S14. Relationship between leakiness and ratio of initial slope of A-Ci (IS) to CO2-saturated rates in eight C4 grasses.

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