Testing unified theories for ozone response in C4 species.

There is tremendous interspecific variability in O3  sensitivity among C3  species, but variation among C4  species has been less clearly documented. It is also unclear whether stomatal conductance and leaf structure such as leaf mass per area (LMA) determine the variation in sensitivity to O3 across species. In this study, we investigated leaf morphological, chemical, and photosynthetic responses of 22 genotypes of four C4 bioenergy species (switchgrass, sorghum, maize, and miscanthus) to elevated O3 in side-by-side field experiments using free-air O3 concentration enrichment (FACE). The C4  species varied largely in leaf morphology, physiology, and nutrient composition. Elevated O3 did not alter leaf morphology, nutrient content, stomatal conductance, chlorophyll fluorescence, and respiration in most genotypes but reduced net CO2 assimilation in maize and photosynthetic capacity in sorghum and maize. Species with lower LMA and higher stomatal conductance tended to show greater losses in photosynthetic rate and capacity in elevated O3 compared with species with higher LMA and lower stomatal conductance. Stomatal conductance was the strongest determinant of leaf photosynthetic rate and capacity. The response of both area- and mass-based leaf photosynthetic rate and capacity to elevated O3 were not affected by LMA directly but negatively influenced by LMA indirectly through stomatal conductance. These results demonstrate that there is significant variation in O3  sensitivity among C4  species with maize and sorghum showing greater sensitivity of photosynthesis to O3 than switchgrass and miscanthus. Interspecific variation in O3  sensitivity was determined by direct effects of stomatal conductance and indirect effects of LMA. This is the first study to provide a test of unifying theories explaining variation in O3  sensitivity in C4 bioenergy grasses. These findings advance understanding of O3 tolerance in C4  grasses and could aid in optimal placement of diverse C4 bioenergy feedstock across a polluted landscape.

INTRODUCTION

Tropospheric ozone (O3) is an important greenhouse gas that significantly contributes to global warming, and a damaging air pollutant that is detrimental to human and ecosystem health worldwide (Ainsworth et al., 2012; Gaudel et al., 2018; Lefohn et al., 2018; Monks et al., 2015; Shindell et al., 2009; Wedow et al., 2021a). O3 has long been known to negatively impact leaf photosynthetic carbon assimilation, stomatal conductance, plant growth and development, and therefore O3 reduces crop yields and forest productivity (Ainsworth et al., 2012; Lefohn et al., 2018; Monks et al., 2015; Wittig et al., 2009). A recent study suggested that current O3 concentrations are reducing global yield by 4.4–12.4% for staple food crops including wheat, soybean, maize, and rice, totaling 227 million tons annually, worth hundreds of billions of dollars per year (Mills et al., 2018). Such a significant crop yield loss to O3 can be a significant threat to global food production and security.

O3 damages plants by entering the leaf mainly through stomata, thereafter rapidly reacting with organic molecules in the apoplast to form other reactive oxygen species (ROS). Antioxidants in the mesophyll can scavenge ROS‐formed by O3, but at high enough concentrations, O3‐induced ROS can trigger signaling cascades that lead to programmed cell death (Ainsworth, 2017; Fiscus et al., 2005; Long & Naidu, 2002). Although plant O3 responses are complex, it is clear that some plant species are more sensitive to O3 than others in both woody and herbaceous species (Ainsworth et al., 2012; Bussotti, 2008; Feng et al., 2018; Li et al., 2016, 2018). For instance, angiosperms are significantly more sensitive to O3 than gymnosperms, and soybean was the most O3 sensitive major food crop based on a global analysis of yield (Ainsworth et al., 2012; Mills et al., 2018; Reich, 1987; Wittig et al., 2009). In soybean and wheat, modern germplasm is generally more susceptible to O3 than older germplasm, and Asian cultivars reportedly showed greater sensitivity to O3 than their North American counterparts (Biswas et al., 2008; Emberson et al., 2009; Osborne et al., 2016). Therefore, understanding the underlying mechanisms determining intra‐ and interspecific variation in O3 sensitivity is crucial for breeding of O3‐tolerant plants (Ainsworth, 2017; Mills et al., 2018).

Several mechanisms could potentially explain genotypic and/or species variability in O3 sensitivity. One theory explaining differences in O3 sensitivity across species is that species with lower stomatal conductance are less sensitive (Brosché et al., 2010; Lin et al., 2001; Reich, 1987). Because uptake of O3 occurs mainly via stomata, stomatal conductance can determine O3 uptake and the subsequent degree of leaf damage. Another trait proposed to influence species‐specific variation in sensitivity to O3 is leaf mass per area (LMA) (Bussotti, 2008; Feng et al., 2018; Li et al., 2016). Leaves with a high LMA often have greater leaf volume per area, greater leaf thickness and density, and greater apoplastic leaf fraction, resulting in a lower O3 load per unit mesophyll cell mass, a longer O3 diffusion pathway, and greater antioxidant concentration within leaves (Niinemets, 1999; Poorter et al., 2009). Meta‐analyses of diverse woody or crop species have suggested that both stomatal conductance and LMA were closely linked to O3 sensitivity (Feng et al., 2018; Li et al., 2016). Moreover, Pääkkönen et al. (1997) showed that O3‐induced visible injury correlated with stomatal density and leaf thickness in Betula clones indicating that the within‐species variability in O3 sensitivity relates to stomatal conductance and LMA (Niinemets, 1999). Additionally, variation in leaf antioxidant capacity has been linked to within‐species variability in O3 sensitivity (Li et al., 2016).

Past efforts to test and understand unified theories of O3 response across species have mainly focused on analyses of leaf damage from compilations of independent peer‐reviewed studies or observations in the field at different locations. Within such studies, environmental factors other than O3 may influence the relationship between stomatal conductance, LMA and O3 sensitivity and there are challenges in diagnosing leaf damage specific to O3. O3 causes a range of visible, interveinal leaf injuries, including chlorosis, necrosis, flecking, stippling, bronzing, bleaching and reddening (Brace et al., 1999). These different types of symptoms can also be caused by other factors such as drought, nitrogen availability, leaf senescence, and/or pest/pathogen damage, making a specific O3 injury difficult to diagnose. The effects of O3 on leaf injury and photosynthesis also vary with leaf age and position in the canopy (Burton et al., 2016; Morgan et al., 2004; Yendrek et al., 2017a), so comparisons across studies on leaves with different ages can be confounded. In addition, previous studies have not consistently accounted for a wide variety of environmental factors affecting stomatal conductance and LMA, such as light, water availability and temperature (Poorter et al., 2009). A reliable assessment of O3 sensitivity in relation to stomatal conductance and LMA requires side‐by‐side field comparison of leaf morphological and photosynthetic response to O3 at the same developmental stages.

To date, much attention has been placed on understanding the mechanisms of plants response to O3 in C3 species, but less is known about how O3 affects leaf morphological and physiological traits in C4 species. C4 plants are widely distributed in tropical, subtropical, and warm‐temperate regions and are widely recognized as a major source of food, bioenergy, and ethanol production (Brosse et al., 2012; Carpita, & McCann, 2008; Food and Agriculture Organization, 2019; Heaton et al., 2008; https://afdc.energy.gov/data/10339; Schmer et al., 2008). Considering differential features of leaf anatomy and associated physiology and biochemistry (Sage, 2004), C4 species may respond differently to O3 than C3 species. The ROS from O3 degradation can cause direct damage to mesophyll cells and chloroplasts in C3 leaves leading to reduction of photosynthesis (Montes et al., 2022). While in C4 leaves with Kranz anatomy, mesophyll cells can provide protection against ROS damage to bundle sheath cells where Rubisco and much of the photosynthetic carbon reduction cycle occurs (Montes et al., 2022). Compared with C3 crops, such as rice and sunflower, C4 crops including sorghum and corn exhibit a lower steady‐state or modelled maximal stomatal conductance (Hoshika et al., 2018; Lin et al., 2015; Zhen & Bugbee, 2020). This further suggests that C4 crops may have lower stomatal O3 uptake than C3 crops. Nevertheless, previous studies have shown significant impacts of O3 on maize (Zea mays) (Choquette et al., 2019, 2020; Sorgini et al., 2019; Wedow et al., 2021b; Yendrek et al., 2017a, 2017b), switchgrass (Panicum virgatum) (Li et al., 2019) and sugarcane (Saccharum spp.) (Moura et al., 2018), but not on sorghum (Sorghum bicolor L.) (Li et al., 2021) under field conditions, implying the adverse effects of O3 on plant photosynthesis and productivity vary among C4 species and genotypes. Differential responses in C4 species to chronic O3 exposure have not been tested side‐by‐side under field conditions. Identifying genotypic and species variation in leaf morphological and physiological traits and in O3 sensitivity is a crucial first step to breed C4 crops for O3 tolerance.

We assessed the impacts of elevated O3 on leaf morphology and physiology in 22 genotypes of four C4 bioenergy species that cover a broad range of stomatal conductance and LMA (Choquette et al., 2020; Ferguson et al., 2021). To minimize the effects of other environmental factors on plant growth and development, all genotypes were grown in the field using free‐air concentration enrichment (FACE) technology, which allows plants to be grown under natural and fully open‐air conditions, but with long‐term, continuous exposure to elevated O3 (Ainsworth & Long, 2005, 2021; Long et al., 2004; Montes et al., 2022; Morgan et al., 2004). To better understand O3 flux into the leaves, we distinguished O3 load per unit leaf area and mass and therefore, we considered variation in both area‐ and mass‐based leaf traits. Because different species display different visual symptoms of O3 damage, we proposed the reductions of photosynthetic traits to O3 as a proxy to estimate O3 sensitivity. We used a side‐by‐side experimental design to test for (a) the effects of elevated O3 on leaf morphological, structural, chemical and physiological traits, (b) genotypic and species variation in O3 sensitivity, and (c) relationships between O3 sensitivity and LMA and between O3 sensitivity and stomatal conductance in C4 bioenergy grasses.

MATERIALS AND METHODS

Plant materials, field site, and experimental treatments

Twenty‐two genotypes from four emerging bioenergy crops with varying LMA and stomatal conductance were selected for this study. They were three genotypes (Independence, Shawnee, and Summer) of switchgrass (Panicum virgatum), five genotypes (Pl329597, Pl452891, Pl457183A, Pl665123, and TAM17800) of sorghum (Sorghum bicolor), six genotypes (B73 × Hp301, B73 × Mo17, B73 × NC338, Mo17 × Hp301, Mo17 × NC338 and NC338 × Hp301) of maize (Zea mays) and eight genotypes (Illinois, 12UI‐001–003, 12UI‐001–006, 12UI‐003–006, 13UI‐005–002, 13UI‐005–003, 13UI‐009R‐009, 13UI‐013R‐019, 13UI‐014–003) of miscanthus (Miscanthus × giganteus). These genotypes were chosen based on variation in stomatal conductance and LMA (Ferguson et al., 2021) and prior evidence of variation in O3 sensitivity (Choquette et al., 2020). Switchgrass genotypes were grown from seeds, and miscanthus genotypes were propagated from rhizomes in a greenhouse. All plantlets were maintained in pots in a greenhouse under natural light for a month before being transplanted into the field. The day/night temperatures in greenhouse were maintained at 28/25°C and humidity at ~60%. Plants were watered daily and fertilized weekly to maintain optimal growth conditions. Seedlings of switchgrass and miscanthus were transplanted, and seeds of sorghum and maize genotypes were planted in the field at the FACE facility on May 31 (day of the year (DOY) 151), 2019. Experimental rows were 3.96 m long for all species, and row spacing was 0.91 m for switchgrass and miscanthus and 0.76 m for sorghum and maize. Switchgrass and miscanthus were maintained at a density of 0.91 plants m−1 and sorghum and maize at 8 plants m−1. To minimize the influence of transplantation stress on switchgrass and miscanthus genotypes, plants were watered every day until new leaves emerged. Sorghum and maize were irrigated as needed before germination. The soil was fertilized with N (200 kg ha−1) before transplanting and planting, and no herbicides or pesticides were applied.

The FACE facility near Champaign, Illinois (40°02’N, 88°14’W; www.igb.illinois.edu/soyface/) is situated on an experimental farm using maize/soybean annual rotation and the soil is classified as a Drummer (Ainsworth et al., 2004). The FACE facility has a randomized block design (n = 4) with eight 20 m diameter octagonal rings, four with ambient O3 (30–50 nl L−1), and four with elevated O3 (~100 nl L−1). All rings were separated from each other by at least 100 m to minimize contamination from the treatment rings. Each block consisted of one ambient and one elevated O3 ring. The core area of each ring was divided into two sub‐plots, the northern plot with sorghum and maize and the southern plot with switchgrass and miscanthus to avoid shade stress by the fast growing annual crops. All genotypes were randomly assigned and planted within each sub‐plot in each of the four pairs of blocks. Elevated O3 rings were fumigated starting on June 10 (DOY 161) in 2019 using FACE technology described in detail by Choquette et al. (2020), Li et al. (2021), Morgan et al. (2004) and Yendrek et al. (2017b). In brief, O3 was produced from pure oxygen by an O3 generator (CFS‐32G; Ozonia), mixed with air and delivered to the elevated rings and then released on the upwind side of the pipes. O3 concentration was measured at the center of the ring using a chemiluminescence O3 sensor (Model 49i, Thermo Scientific, Massachusetts, USA) and the target O3 set point was 100 nl L−1. Within each ring, wind velocity and direction were continually recorded to adjust air enriched O3 flow rate and release position to maintain the set O3 concentration. Elevated O3 rings were fumigated during daylight hours from 10:00–18:00 throughout the growing season unless leaves were wet and/or wind velocity was lower than 0.5 m s−1. Meteorological measurements including air temperature, solar radiation, relative humidity and precipitation were recorded by an onsite weather station. The O3 treatment was stopped on September 15 (DOY 258) in 2019. The 1 min average O3 concentration was 87.6 ± 0.62 nL L−1 within the elevated rings throughout the season, with target concentration within 10% for 66.3% of the time and within 20% for 74.7% of the time.

Photosynthesis measurements

In situ midday measurements of gas exchange and chlorophyll fluorescence were performed three times: July 24–25 (DOY 205–206, hereafter referred to as time point A), August 8–9 (DOY 220–221, hereafter referred to as time point B) and August 23–24 (DOY 235–236, hereafter referred to as time point C). The measurements were conducted on 2–4 plants per genotype per ring between 11:00 and 14:00 on sunny days using portable photosynthesis systems with leaf chamber fluorometers (LI‐6800, LICOR Biosciences, Lincoln, NE, USA). For all genotypes, the third or fourth fully expanded leaf was selected and labelled for the time point A measurement. The same leaf was used for the following time points measurement, but a younger leaf was measured if the tagged leaf had senesced. The Li‐6800 leaf chamber block conditions were set to ambient conditions prior to the measurements for three time points: block temperature was 31–32°C, light intensity at the leaf surface was 1700–1800 µmol m−2 s−1, reference CO2 concentration was 420 µmol mol−1 and relative humidity was 60–65% (Li et al., 2021). After 3–5 min of leaf enclosure and net photosynthesis stabilization, photosynthetic traits included net CO2 assimilation rates per unit leaf area (A A), stomatal conductance to water vapor per unit leaf area (g s,A), the intercellular CO2 concentration (C i), and chlorophyll fluorescence (quantum yield of PSII (Φ PSII), electron transport rate (ETR), PSII maximum efficiency (F v’/F m’), and coefficient of photochemical quenching [qP]) were obtained. Instantaneous water use efficiency (iWUE) was determined as A A divided by g s,A. Mass‐based midday photosynthetic rate (A M) and stomatal conductance (g s,M) were calculated as A A and g s,A, respectively, divided by leaf dry mass per area (LMA).

Photosynthetic CO2 response curves (A A/C i curves) were measured on August 9–23 (DOY 221–235) following the second time point of midday gas exchange measurement. The two leaves per genotype per ring that were used for time point B leaf gas exchange measurements were measured. Leaves were excised in the field before dawn, recut immediately under water, and returned to the laboratory with the cut ends immersed in water. Prior to measurements, leaves were acclimated at saturating irradiance under ambient CO2 concentration for at least 40 min to achieve steady‐state gas exchange. This approach has previously been shown to avoid short‐term decreases in water potential, decreased chloroplast inorganic phosphate concentration, and decreased F v’/F m’ while providing a similar estimation of photosynthetic capacity to those measured in the field (Ainsworth et al., 2004; Leakey et al., 2006; Yendrek et al., 2017a). After the leaves were enclosed in the leaf chamber, the block conditions were maintained at temperature of 28°C, light intensity of 1800 µmol m−2 s−1, and relative humidity of 65% (Li et al., 2021). Measurements were initiated at reference CO2 concentration within the block of 400 µmol mol−1, and once photosynthesis reached steady state, CO2 concentrations were varied as follows: 400, 300, 200, 100, 50, 400, 600, 800, 1000, 1200, and 1500 µmol mol−1. The A A/C i curve was used to solve for the maximum carboxylation capacity of phosphoenolpyruvate carboxylase (PEPc) per unit area (V pmax,A) based on the initial slope using equations from von Caemmerer (2000). Under low CO2 partial pressures, CO2 assimilation rate is linearly related to maximum PEPc activity and bundle sheath flux is low and can be ignored (von Caemmerer, 2021). CO2 saturated photosynthetic capacity per unit area (V max,A) was estimated by the horizontal asymptote of a four‐parameter non‐rectangular hyperbolic function. All curves were fit using a customized curve fit function in SigmaPlot (Systat, San Jose, CA). The maximum carboxylation capacity of phosphoenolpyruvate per unit of dry mass (V pmax,M) and CO2‐saturated photosynthetic capacity per unit of dry mass (V max,M) were determined from V pmax,A and V max,A, respectively, divided by LMA.

After each A A/Ci curve measurement finished, the leaf was immediately removed from the leaf chamber and placed under dark for at least 50 min at room temperature and ambient CO2 concentration. The leaf was then enclosed in the Li‐6800 leaf chamber with the block condition settings of temperature at 30°C, light intensity at 0 µmol m−2 s−1, reference CO2 concentration at 420 µmol mol−1 and relative humidity at 65%. Leaf dark respiration per unit area (R d,A) was measured after stabilization of readings, typically 3–10 min after leaf enclosure. Leaf dark respiration per unit of dry mass (R d,M) was calculated by dividing R d,A by LMA. Following R d,A measurements, the leaf was further illuminated with a saturating irradiance of 7000 µmol quanta m−2 s−1 to determine the minimum (F 0) and maximum (F m) dark‐adapted fluorescence yield. The spatially averaged maximum dark‐adapted quantum yield of photosystem II, F v/F m was calculated as F v/F m = ((F m‐F 0)/F m).

Leaf morphology, carbon and nitrogen content

Following photosynthesis measurements at each time point, leaf chlorophyll concentration was determined on the same leaf using a portable chlorophyll meter (SPAD 502; Minolta corporation, Ltd., Osaka, Japan). For each leaf, 6–8 measurements across the lamina were averaged. A strong correlation between SPAD readings and total (a + b) chlorophyll concentration per area are observed in both C3 and C4 species (Marenco et al., 2009; Uddling et al., 2007; Yamamoto et al., 2002), suggesting that SPAD measurements can be an accurate method to estimate chlorophyll content. Using the same leaf, we additionally determined leaf area, length and average width with a portable leaf area meter (LI‐3000C, LICOR Biosciences, Lincoln, NE, USA). To determine leaf dry mass per area (LMA), leaf disks were collected from the portion of the leaf that was enclosed in the LI‐6800 chamber and placed in an oven for at least 72 h at 65°C. LMA was calculated as leaf dry mass divided by leaf area. The oven‐dried leaf disks were ground, and mass‐based C and N concentrations (C M and N M) were determined from ~3 mg of fine powder sample using a Costech 4010 elemental analyzer (Costech Analytical Technologies, Inc., Valencia, CA, USA). Leaf N content per unit area (N A) was obtained by multiplying N M by LMA. Leaf C:N ratio was calculated as C:N = C M / N M.

Statistics

The effects of elevated O3 concentration on leaf traits of individual genotype and species were initially tested at each time point by analysis of variance (one‐way ANOVA) followed by Tukey's test. Because different species contain different numbers of genotypes, a nested ANOVA was used in the model with genotype nested within species to determine significant differences between genotype and species and its interaction with O3 treatment.

To evaluate the relationships among LMA, nitrogen content, photosynthesis, stomatal conductance and leaf biochemical potentials, we performed Pearson's correlation tests. In addition, linear and nonlinear regression analyses were applied to explore the relationships among photosynthesis, LMA and stomatal conductance under ambient and elevated O3 and among changes in photosynthesis in elevated O3, LMA and stomatal conductance. The difference in slope and intercept of the relationship among photosynthesis, LMA and stomatal conductance between ambient and elevated O3 were tested with standardized major axis estimation (SMA) using the R package “SMATR 3” (Warton et al., 2012).

To determine whether LMA or stomatal conductance had a stronger link to leaf O3 sensitivity in 22 genotypes, we performed structural equation models (SEMs) using the R package “piecewiseSEM” (Lefcheck, 2016). This approach allows the assessment of causal relationships between variables through path analysis (Lefcheck, 2016), which suits exploring the underlying mechanism of interspecific O3 sensitivity in our study. Given that LMA and stomatal conductance could play both explanatory and response roles for interspecific O3 sensitivity, we started piecewise structural equation modelling with a saturated model and removed the nonsignificant paths in the model in a stepwise fashion. Fisher's C statistic was used as the goodness‐of‐fit, and the final model was considered to have an adequate overall fit to the observed data when the model had a nonsignificant C value (p > 0.05) (Shipley, 2009). We also fit separate models for each time point and each species. The SEM analysis was performed using the mean trait values of each genotype.

Both ANOVA and correlation analyses were performed with SPSS 16.0 (SPSS, Chicago, Illinois, USA). All statistical analyses using R packages were performed on the R platform (version 4.0.3). All statistical tests were considered to be significant at p < 0.05.

RESULTS

Photosynthetic capacity of C4 grasses and their response to elevated O3

Photosynthetic rates and stomatal conductance varied significantly across C4 grass species and genotypes (Table 1; Figure 1; Figures S1 and S2). Sorghum and maize tended to show higher photosynthesis and conductance than switchgrass and miscanthus, although the differences were less pronounced later in the growing season (Figure 1; Figures S1 and S2). In situ rates of photosynthesis measured on an area (A A) and mass basis (A M) were significantly reduced by elevated O3 concentration in maize, but less so in other C4 grasses (Figure 1; Figures S1 and S2; Table S1). Photosynthetic biochemical capacities, V pmax,A and V max,A estimated from A A/C i curves, were also significantly reduced in maize hybrids grown at elevated O3 concentration (Figure S3). V pmax, but not V max, was significantly lower in sorghum grown at elevated O3 concentration (Figure S3). The reductions in leaf biochemical capacity in elevated O3 limited photosynthetic carbon fixation and there was a significant linear correlation between the percent changes in net assimilation rate on both an area‐ and a mass‐basis with percent change in V pmax or V max (Figure 2; Figure S4). Growth at elevated O3 concentration did not significantly alter the intercellular CO2 concentration (C i), the instantaneous water use efficiency or respiration of C4 grasses (Table 1).

TABLE 1

F and P values of the ANOVA of effects of O3, species and O3 × Species and the nested ANOVA of effects of genotype (nested within species) and O3 × genotype (species) on leaf morphological and photosynthetic traits measured in 22 genotypes of four species grown at ambient and elevated O3 on three time points at the FACE

Trait	O3	Species	Genotype (species)	O3 × species	O3 × genotype (species)
Leaf morphology and nutrient content
SPAD	5.30, 0.022	89. 9, <0.001	27.9, <0.001	1.55, 0.20	1.43, 0.096
Leaf area (cm2)	6.50, 0.011	2848, <0.001	849.0, <0.001	2.65, 0.048	1.88, 0.010
Leaf length (cm)	2.03, 0.16	327.0, <0.001	77.4, <0.001	0.55, 0.65	1.05, 0.40
Leaf width (cm)	5.95, 0.015	5524, <0.001	1822, <0.001	2.35, 0.072	2.18, 0.002
LMA (g m−2)	0.52, 0.47	148.4, <0.001	29.2, <0.001	0.57, 0.63	0.45, 0.99
N A (g m−2)	0.12, 0.73	35.8, <0.001	9.77, <0.001	0.41, 0.75	0.45, 0.99
N M (%)	0.69, 0.41	199.3, <0.001	35.3, <0.001	1.37, 0.25	0.50, 0.98
C:N	1.24, 0.27	193.5, <0.001	39.2, <0.001	1.09, 0.35	0.92, 0.58
Leaf midday photosynthesis
A A (µmol m−2 s−1)	9.85, 0.002	70.0, <0.001	30.5, <0.001	1.68, 0.17	1.71, 0.024
g s,A (mol m−2 s−1)	4.30, 0.039	50.7, <0.001	15.6, <0.001	0.43, 0.73	0.73, 0.81
A M (nmol g−1 s−1)	5.32, 0.022	119.9, <0.001	23.8, <0.001	0.57, 0.64	0.68, 0.86
g s,M (mmol g−1 s−1)	3.57, 0.059	93.3, <0.001	17.4, <0.001	0.25, 0.86	0.49, 0.98
C i (µmol mol−1)	0.45, 0.50	37.0, <0.001	10.9, <0.001	0.75, 0.53	0.56, 0.95
iWUE (µmol mol−1)	0.11, 0.75	8.10, <0.001	5.45, <0.001	0.083, 0.97	0.51, 0.97
Leaf midday chlorophyll fluorescence
Φ PSII	4.06, 0.045	92.0, <0.001	33.9, <0.001	1.53, 0.21	1.21, 0.23
ETR (µmol m−2 s−1)	3.86, 0.050	93.3, <0.001	34.0, <0.001	1.56, 0.20	1.17, 0.27
F v’/F m’	5.03, 0.025	43.5, <0.001	10.7, <0.001	1.28, 0.28	1.24, 0.21
qP	1.14, 0.29	70.9, <0.001	39.0, <0.001	0.74, 0.53	0.86, 0.65
Leaf photosynthetic capacity
V pmax,A (µmol m−2 s−1)	15.3, <0.001	17.4, <0.001	10.7, <0.001	3.38, 0,020	2.48, 0.001
V max,A (µmol m−2 s−1)	6.38, 0.013	13.6, <0.001	9.51, <0.001	1.79, 0.15	1.24, 0.22
V pmax,M (µmol g−1 s−1)	11.1, 0.001	38.5, <0.001	14.4, <0.001	2.89, 0.037	2.00, 0.009
V max,M (µmol g−1 s−1)	2.61, 0.11	46.7, <0.001	14.6, <0.001	0.85, 0.47	0.60, 0.92
Leaf respiration and maximum dark‐adapted quantum yield of photosystem II
R d,A (µmol m−2 s−1)	<0.001, 0.98	14.4, <0.001	2.64, <0.001	0.20, 0.90	0.53, 0.96
R d,A (µmol g−1 s−1)	0.065, 0.80	20.7, <0.001	3.61, <0.001	0.12, 0.95	0.45, 0.99
F v/F m	3.22, 0.075	12.5, <0.001	4.73, <0.001	1.16, 0.33	1.28, 0.20

Significant effects (p < 0.05) are shown in boldface.

Abbreviations: LMA, leaf dry mass per unit area; N A, nitrogen content per unit area; N M, nitrogen content per unit dry mass; C:N, leaf carbon‐to‐nitrogen ratio; A A, net CO2 assimilation rates per unit leaf area; g s,A, stomatal conductance to water vapor per unit area; A M, net CO2 assimilation rates per unit dry mass; g s,M, stomatal conductance to water vapor per unit dry mass; C i, intercellular CO2 concentration; iWUE, instantaneous water use efficiency; Φ PSII, quantum yield of PSII; ETR, electron transport rate; F v’/F m’, PSII maximum efficiency; qP, coefficient of photochemical quenching; V pmax,A, the maximum carboxylation capacity of phosphoenolpyruvate per unit area; V max,A, CO2 saturated photosynthetic capacity per unit area; V pmax,M, the maximum carboxylation capacity of phosphoenolpyruvate per unit dry mass; V max,M, CO2 saturated photosynthetic capacity per unit dry mass; R d,A, leaf dark respiration per unit area; R d,M, leaf dark respiration per unit dry mass; F v/F m, maximum dark‐adapted quantum yield of photosystem II.

FIGURE 1

Box plots by species cluster for area‐ (a, b) and mass‐ (c, d) based leaf midday net CO2 assimilation rate (a, c) and stomatal conductance (b, d), and scatter plots for A A (e), g s,A (f), A M (g) and g s,M (h) from 22 genotypes measured at ambient and elevated O3 on the time point A. All trait values in (a), (b), (c) and (d) were derived from four replicates of each genotype in each species. Error bars in (e), (f), (g) and (h) show standard errors (n = 4). The box length indicates the interquartile range, the bottom and top parts of the boxes correspond to the 25th and 75th quartiles, and the horizontal line within the boxes is the median. Whiskers extend to 1.5 times the inter‐quartile range, and the dots represent values outside the range of the whisker limits. In all cases, asterisk indicates significant differences between ambient and elevated O3: *p < 0.05; **p < 0.01; ***p < 0.001

FIGURE 2

The relationships (a) between percent change in net CO2 assimilation rate per unit leaf area (A A) and percent change in the maximum carboxylation capacity of phosphoenolpyruvate carboxylase per unit leaf area (V pmax,A), (b) between percent change in A A and percent change in CO2‐saturated photosynthetic rate per unit leaf area (V max,A) and (c) between percent change in V pmax,A and percent change in V max,A at elevated O3 (~100 nL L−1) in 22 genotypes of four C4 grass species (Miscanthus × giganteus, Panicum virgatum, Sorghum bicolor, and Zea mays) grown in a replicated field trial using free‐air O3 concentration enrichment at Champaign, IL and measured on August 8–9, 2019 for A A and on August 9–23, 2019 for V pmax,A and V max,A. Data were fitted by linear regression in the form of y = ax + b

Genotypic and species variation in chlorophyll fluorescence was observed for Φ PSII, ETR, F v’/F m’, and qP (Table 1, S1). Across all species, there was a significant effect of O3 on Φ PSII, ETR and qP at time point B and on F v’/F m’ at time point C (Table S1), leading to a significant O3 effect on chlorophyll fluorescence across the growing season (Table 1). There was no significant interaction between O3 and species and between O3 and genotype (species) on leaf chlorophyll fluorescence at each time point or across all time points (Table 1; Table S1). Significant differences (p < 0.001) among the studied species were observed for R d,A, R d,M, and F v/F m (Table 1). However, elevated O3 did not alter R d,A, R d,M and F v/F m across species or genotypes (Table 1).

The response of leaf morphology and nutrient content to elevated O3

Leaf SPAD, morphology, LMA and nitrogen content (N A, N M, and C:N ratio) varied across species and time points (Table 1; Table S1). Sorghum and maize had greater leaf area, with longer and wider leaves than switchgrass and miscanthus (Figures S5 and S6). Leaf SPAD was lower in elevated O3 in miscanthus genotypes at time point A and C and in one maize genotype at time point C (Figure S5a–c), resulting in the overall impact of O3 on SPAD across all species (Table 1; Table S1). However, no significant O3 × species or O3 × genotype (species) interaction was observed (Table 1; Table S1). Leaf gross morphology including area, length, and width was altered in elevated O3 in some genotypes of sorghum, maize and miscanthus (Figures S5 and S6), leading to significant O3 effect among species (Table 1; Table S1). Because growth in elevated O3 did not affect LMA and N M in most of the genotypes at most time points (Figure S7), there was no significant effect of O3 or interaction between O3 and species and between O3 and genotype on LMA, N A, N M and C:N ratios across species (Table 1; Table S1).

Changes in photosynthesis in response to O3 in relation to leaf mass per area and stomatal conductance

Pooling all species together, we tested correlations among leaf traits including LMA, nitrogen content, midday gas exchange and leaf biochemical potentials measured at ambient and elevated O3 concentrations to test the general hypothesis that O3 sensitivity is correlated with stomatal conductance and LMA (Table S2). Both A A and A M were negatively associated with LMA but positively correlated with stomatal conductance (p < 0.001, Figure 3; Table S2). Elevated O3 decreased the intercept of the relationship between LMA and A A (p < 0.01, Figure 3a) and between LMA and A M (p < 0.01, Figure 3d) but increased the intercept of the relationship between g s,M and A A (p < 0.01, Figure 3c). Elevated O3 did not change the slope of any of the correlations (Figure 3). O3‐induced reductions in A A, ΔA A, was positively linked to LMA (Figure 4a) and negatively scaled with stomatal conductance (Figure 4b,c). However, the relationships between g s,A and ΔA A (r 2 = 0.14, p = 0.0023) and between g s,M and ΔA A (r 2 = 0.078, p = 0.023) were more pronounced compared with correlation between LMA and ΔA A (r 2 = 0.063, p = 0.042) (Figure 4). In addition, the relationships of ΔA A with stomatal conductance were stronger when stomatal conductance expressed per unit leaf area (Figure 4b,c). No significant correlations were observed between O3‐induced reductions in A M and LMA, g s,A and g s,M (Figure S8). Strong positive correlation between ΔA A and LMA and negative correlation between ΔA A and g s,A were found at time point A across all species (Table S3). Leaf biochemical potentials in area and mass basis both scaled negatively with LMA and positively associated with g s,A and g s,M (Figures S9 and S10; Table S2). Both the slope and intercept of the correlations between LMA and V pmax,A, and LMA and V pmax,M were significantly altered by elevated O3 (Figure S9a,d). Elevated O3 significantly increased the intercept of relationship between V pmax,A and g s,A and between V pmax,A and g s,M (Figure S9b,c) but decreased the slope of correlation between V pmax,M and g s,A and between V pmax,M and g s,M (Figure S9e,f). No statistical differences in slope and intercept were found between ambient and elevated O3 in the relationships among V max,A, V max,M, LMA, and stomatal conductance (Figure S10). O3‐induced reduction in V pmax,A and V pmax,M were positively associated with LMA but negatively correlated with g s,A and g s,M (Figure 5a–c; Figure S11a–c). However, these correlations were stronger for area‐based (V pmax,A) than mass‐based (V pmax,M) relationships, and the relationship between LMA and O3‐induced reduction in V pmax,A (p = 0.014) was weaker than the relationship between stomatal conductance and O3‐induced reduction in V pmax,A (p = 0.0011 and p = 0.0005) (Figure 5a–c; Figure S11a–c). O3‐induced reduction in V max,A was not correlated with LMA, but scaled negatively with g s,A and g s,M (Figure 5d–f). O3‐induced reduction in V max,M was not correlated with LMA, g s,A and g s,M (Figure S11d–f).

FIGURE 3

Leaf midday net CO2 assimilation rate per unit area (A A; a, b, c) and mass (A M; d, e, f) as a function of leaf mass per area (LMA; a, d), and stomatal conductance per area (g s,A; b, e) and per mass (g s,M; c, f). All trait values were derived from four replicates of each genotype in each species measured at three time points. Data were fitted by linear regressions in the form of y = ax + b for (a), (e), and (f), and nonlinear regressions in the form of y = ax/(1+bx) for (b) and (c) and y = aexp(‐bx) + c for (d) according to the greatest coefficient of determination value (r 2). To test the differences in slope and intercept of nonlinear regressions between ambient and elevated O3, g s,A, g s,M and LMA were log‐transformed (insets in b, c and d). In all cases, ns, not significant; **p < 0.01; ***p < 0.001

FIGURE 4

The percent change of net CO2 assimilation rate per unit lead area (A A) at elevated O3 in relation to leaf mass per area (LMA; a), and stomatal conductance per area (g s,A; b) and per mass (g s,M; c) across 22 genotypes in four species. All trait values were derived from each genotype in each species at three time points measurement. Data were fitted by linear regression in the form of y = ax + b

FIGURE 5

The percent change of the maximum carboxylation capacity of phosphoenolpyruvate carboxylase (PEPC) per unit area (V pmax,A; a‐c) and CO2‐saturated photosynthetic rate (V max,A; d‐f) at elevated O3 in relation to leaf mass per area (LMA; a, d), and stomatal conductance per area (g s,A; b, e) and per mass (g s,M; c, f) across 22 genotypes in four species measured at time point B. Data were fitted by nonlinear regression in the form of y = a(1‐exp(‐bx)) + c

SEMs provided further evidence that leaf midday photosynthetic rate and biochemical capacities were directly related to stomatal conductance rather than to LMA. There were no significant direct effects of elevated O3 on LMA, g s,A, and g s,M in all species (Figure 6; Figure S12). Elevated O3 exerted a negative direct effect (p < 0.05) on V pmax,A (Figure 6b; Figure S12b), whereas V pmax,M, V max,A, and V max,M were not influenced (Figure 6c; Figure S12c). Stomatal conductance was the strongest determinant of leaf midday photosynthetic rate and biochemical potentials (Figure 6; Figure S12). LMA generally showed a weak negative effect on leaf midday photosynthetic rates and biochemical potentials directly, or strong indirect effect through stomatal conductance (Figure 6; Figure S12). In all cases, stomatal conductance on both an area and mass basis had a stronger direct effect on area‐based photosynthetic traits (A A, V pmax,A and V max,A) than that on mass‐based photosynthetic traits (A M, V pmax,M and V max,M) (Figure 6; Figure S12).

FIGURE 6

Piecewise structural equation models showing direct and indirect effects of O3, leaf mass per area, and stomatal conductance (g s,A) on area‐based (a) net CO2 assimilation (A A), (b) the maximum carboxylation capacity of phosphoenolpyruvate carboxylase (PEPC) (V pmax,A), and (c) CO2‐saturated photosynthetic rate (V max,A). Solid red and black arrows represent significant negative and positive effects (p < 0.05), respectively, and the dashed arrows indicate nonsignificant effects (p > 0.05). Arrow thickness is proportional to the standardized path coefficients, which correspond to the values labelled next to the arrows with asterisks indicating their significance symbolized by: *p < 0.05; **p < 0.01; ***p < 0.001

DISCUSSION

In this study, we investigated the leaf morphological and photosynthetic response of 22 genotypes of four C4 bioenergy species (switchgrass, sorghum, maize, and miscanthus) to elevated O3 using the unique capabilities of FACE technology, which provided elevated concentrations of O3 (100 nl L−1) in open‐air plots at the field scale. We tested whether unifying theories (stomatal conductance and LMA) determine the variation in sensitivity to O3 across C4 species. We demonstrated inter‐ and intraspecific variability in leaf morphological and functional traits and significant variation in O3 response among four species. We also disentangled how leaf functional traits such as LMA and stomatal conductance influence interspecific variation in O3 sensitivity among the studied species. This study provides a comprehensive analysis of O3 response in C4 bioenergy species and tests proposed unifying theories of species variability in O3 sensitivity.

C4 grasses are tolerant to elevated O3

In this study of four C4 grass species, we found that elevated O3 did not alter leaf morphology, LMA, or N content in most of the genotypes, in contrast to trees and C3 crops, which show significant changes with elevated O3 (Feng et al., 2008; Oikawa & Ainsworth, 2016; Wittig et al., 2009). Previous study of maize responses to elevated O3 found that N content was reduced in aging leaves, consistent with accelerated senescence, but O3 did not impact N content of recently mature leaves (Choquette et al., 2020). O3 is also known to negatively impact leaf photosynthetic capacity and stomatal conductance in C3 species (e.g., Ainsworth, 2017; Ainsworth et al., 2012). While elevated O3 reduced A A, V pmax,A, and V max,A in maize, other C4 grasses were less sensitive to elevated O3. A A was not significantly reduced by elevated O3 in any other species, even though V pmax,A was significantly lower in sorghum. g s,A was also not significantly altered by elevated O3 in any species, which is consistent with previous studies of maize, switchgrass and sorghum (Choquette et al., 2019, 2020; Li et al., 2019, 2021). Additionally, elevated O3 did not alter iWUE or respiration in any of the 22 genotypes (Table 1; Table S1). These observations from this side‐by‐side study agree well with previous studies reporting O3‐induced leaf damage in diverse maize lines, but no foliar injury in switchgrass and sorghum (Li et al., 2019, 2021; Sorgini et al., 2019).

What factors influence O3 sensitivity among species?

In the present study, the leaf functional traits were found to be tightly correlated with each other (Table S2). The negative relationship between LMA and photosynthesis for C4 species was in agreement with previously reported the generality of trait relationships in C3 species (Wright et al., 2004). Leaves with greater LMA generally are thicker with greater leaf volume per area (Niinemets, 1999; Poorter et al., 2009). Concerning O3 uptake, thicker leaves and greater leaf volume per area have the potential to increase O3 diffusion pathways but reduce O3 load per unit mesophyll cell mass within leaves (Niinemets, 1999; Poorter et al., 2009). So far, the correlation between LMA and O3 sensitivity had been studied in 57 tree species in the field or within open‐top chambers (OTCs) (Feng et al., 2018; Li et al., 2016). These studies did not account for effects of environmental factors such as canopy position and leaf age on LMA, which may alter the relationship between LMA and O3 sensitivity. Moreover, OTC experiments may amplify downregulation of plant response to O3 due to limited pot size, higher temperature and humidity, and greater exposure of O3 concentration within chambers (Ainsworth & Long, 2005; Long et al., 2004). In the present study, elevated O3 did not alter LMA in all genotypes across three time points under FACE conditions (Figure S7). Both area‐ and mass‐based leaf midday net CO2 assimilation and biochemical potential tended to be slightly lower in elevated O3 in genotypes with lower LMA (Figure 3; Figures S9 and S10), resulting in a greater reduction in photosynthetic traits but not in CO2 saturated photosynthetic capacity (Figures 4 and 5; Figures S8 and S11). This suggests that LMA alone may partially explain why O3 sensitivity varies among species.

High stomatal conductance is often associated with greater O3 uptake and more severe O3 damage in plant species (Li et al., 2017). Our study provided strong evidence that elevated O3 decreased leaf midday photosynthesis and photosynthetic capacity in genotypes with high stomatal conductance (Figure 3; Figues S9–S10) Thus, O3‐induced reductions in leaf midday photosynthesis and biochemical potentials scaled negatively with stomatal conductance (Figures 4 and 5). The correlations of O3‐induced reduction in leaf photosynthesis with stomatal conductance were stronger than that with LMA (Figures 4 and 5), suggesting that O3 sensitivity is more strongly linked to stomatal conductance. Interestingly, these relationships were stronger with leaf midday photosynthesis and biochemical potentials on an area basis (Figures 4 and 5; Figures S8 and S11). This further suggests that there was limited capacity for leaves with greater LMA to redistribute O3 load from leaf area to leaf mass, known as a “dilution effect” (Feng et al., 2018; Li et al., 2016). Analyses of SEMs further confirmed that the interspecific variation in O3 sensitivity was determined by direct effects of stomatal conductance and indirect effects of LMA (Figure 6; Figure S12).

Apart from stomata and LMA, other factors that differ among species and genotypes could have impacted the response of C4 grasses to O3. O3 can also enter the plant through leaf cuticles by means of a diffusion process (Clifton et al., 2020; Kerstiens & Lendazian, 1989) and damage cuticles and their protective waxes (Shepherd & Griffiths, 2006). However, cuticular O3 uptake is estimated to be five orders of magnitude lower than stomatal O3 uptake under natural conditions (Kerstiens & Lendazian, 1989). It should be noted that plant canopy architecture and developmental status can also contribute to the differential O3 sensitivity among C4 species. For example, canopy structure can be significantly changed by abundant tillers and leaves in switchgrass and miscanthus (Heaton et al., 2008), and great plant height in sorghum (Rooney et al., 2007), thereby altering O3 distribution within and on the top of canopy (Krzyzanowski, 2004; Morgan et al., 2004). In addition, late‐flowering energy hybrids of switchgrass, sorghum, and miscanthus exhibit a long duration of vegetative growth (Clifton‐Brown et al., 2001; Poudel et al., 2020; Rooney et al., 2007) in contrast to maize hybrid lines, which stop vegetative growth and start anthesis 60–70 days after emergence (Bollero et al., 1996; Yendrek et al., 2017a). Thus, O3 tolerance could be attributed to the continuous development of vegetative tissues.

Additionally, untested mechanisms could potentially explain variability in O3 sensitivity within or among C4 species. For example, various O3 and ROS scavenging compounds emitted from leaves or secreted from glandular trichomes may explain why O3 sensitivity varies among plant species (Jud et al., 2016; Li et al., 2018; Loreto et al., 2004; Loreto & Velikova, 2001; Vickers et al., 2009a, 2009b; Wedow et al., 2021a). However, studies have reported very low overall reactive compound emissions in switchgrass (P. virgatum, Eller et al., 2011), sorghum (S. sudanense, Karl et al., 2005), and maize (Z. mays cv. Prosil, Mozaffar et al., 2018; Z. mays cv. Zoey, Wiβ et al., 2017) and no VOC fluxes were detected above M. × giganteus canopy (Copeland et al., 2012), suggesting that such low amounts of VOC emissions could not enhance O3 tolerance in the studied species. In addition, antioxidants in the apoplast, including ascorbate, glutathione, and phenolic compounds, directly scavenge ROS (Ainsworth, 2017; Grace & Logan, 2000; Wedow et al., 2021a). However, previous studies have failed to demonstrate a clear pattern of correlation between O3 sensitivity and antioxidant compound levels among diverse species (Betzelberger et al., 2010; Choquette et al., 2020; Li et al., 2016; Wedow et al., 2021b). Furthermore, variation in plant responses to O3 may also be partly explained by genetic background (Choquette et al., 2019; Sorgini et al., 2019). The 22 genotypes measured in this study merely scratch the surface of genetic variation available within these species, so further research may reveal even greater differences in O3 sensitivity.

Implications for bioenergy feedstock

Many C4 crops, including switchgrass, sorghum, maize, and miscanthus, have been recognized as emerging and promising bioenergy feedstock and major sources of bioenergy and ethanol production (Brosse et al., 2012; Carpita, & McCann, 2008; Food and Agriculture Organization, 2019; Heaton et al., 2008; https://afdc.energy.gov/data/10339; Rooney et al., 2007; Schmer et al., 2008). Although C4 species are widespread in tropical and temperate latitudes and typically have superior efficiencies of carbon fixation, water and nitrogen use, their ability to produce a high and stable biomass yield under a changing climate is required. Current background O3 concentration reduces US maize yields by roughly 10% annually, which portends a significant decrease in ethanol production from the corn crop (https://afdc.energy.gov/data/10339; McGrath et al., 2015). In our study, maize exhibited greater O3 sensitivity than other three bioenergy feedstock, consistent with previous studies on C4 species using FACE technology under field conditions (Choquette et al., 2019, 2020; Li et al., 2019, 2021; Moura et al., 2018; Yendrek et al., 2017a, 2017b). This suggests that improving O3 tolerance in maize genotypes is crucial to maintain maize biomass yield stability for ethanol production. Notably, O3 tolerant feedstock, including sorghum, switchgrass, and miscanthus, can also provide abundant and sustainable energy and have the potential to replace maize to produce ethanol (Brosse et al., 2012; Carpita, & McCann, 2008; Schmer et al., 2008). In addition, bioenergy feedstock could be better placed on a landscape that varies in O3 pollution according their O3 sensitivity.

CONCLUSIONS

To the best of our knowledge, this is the first side‐by‐side interspecific comparison of leaf morphological and functional trait responses to elevated O3 among C4 bioenergy grasses in the field. In this study, we observed a wide range of leaf functional traits across the species and within each species. Elevated O3 concentration did not alter leaf morphology, nutrient content, stomatal conductance, chlorophyll fluorescence, and respiration in most genotypes of these C4 grasses. There was significant variation in O3 sensitivity among C4 grass species with maize and sorghum more sensitive to O3 than switchgrass and miscanthus. Genotypes with high stomatal conductance were more sensitive to O3 compared with genotypes with lower stomatal conductance and interspecific variation in O3 sensitivity was determined by direct effects of stomatal conductance and indirect effects of LMA. These findings provide valuable information to facilitate initial development of a unifying theory for variation in O3 sensitivity in C4 bioenergy grasses, which is critical for future efforts to breed for O3 resistance in crop and bioenergy feedstock.

CONFLICT OF INTEREST

The authors declare no conflicts of interest.

AUTHOR CONTRIBUTIONS

E.A.A. and S. L. designed the study; S.L., C.A.M., and N.G.M. performed the measurements; S.L. performed the statistical analysis; S.L., D.L., E.J.S., and E.A.A. contributed to the interpretation of results; S.L. wrote the first version of the manuscript, which was reviewed and revised by all the authors.

Supplementary Material

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