Modeling Light Response of Electron Transport Rate and Its Allocation for Ribulose Biphosphate Carboxylation and Oxygenation

Abstract

Accurately describing the light response curve of electron transport rate (J–I curve) and allocation of electron flow for ribulose biphosphate (RuBP) carboxylation (J_C–I curve) and that for oxygenation (J_O–I curve) is fundamental for modeling of light relations of electron flow at the whole-plant and ecosystem scales. The non-rectangular hyperbolic model (hereafter, NH model) has been widely used to characterize light response of net photosynthesis rate (A_n; A_n–I curve) and J–I curve. However, NH model has been reported to overestimate the maximum A_n (A_nmax) and the maximum J (J_max), largely due to its asymptotic function. Meanwhile, few efforts have been delivered for describing J_C–I and J_O–I curves. The long-standing challenge on describing A_n–I and J–I curves have been resolved by a recently developed A_n–I and J–I models (hereafter, Ye model), which adopt a nonasymptotic function. To test whether Ye model can resolve the challenge of NH model in reproducing J–I, J_C–I and J_O–I curves over light-limited, light-saturated, and photoinhibitory I levels, we compared the performances of Ye model and NH model against measurements on two C₃ crops (Triticum aestivum L. and Glycine max L.) grown in field. The results showed that NH model significantly overestimated the A_nmax and J_max for both species, which can be accurately obtained by Ye model. Furthermore, NH model significantly overestimated the maximum electron flow for carboxylation (J_C-max) but not the maximum electron flow for oxygenation (J_O-max) for both species, disclosing the reason underlying the long-standing problem of NH model—overestimation of J_max and A_nmax.

Introduction

Light intensity (I) is one of the most important environmental drivers affecting electron flow and its allocation for carboxylation versus oxygenation of ribulose biphosphate (RuBP). At I levels before reaching saturation intensity, the non-rectangular hyperbolic model (hereafter, NH model) is a sub-model which is widely used to characterize the light-response curve of electron transport rate (J–I curve) and to estimate the maximum J (J_max) in C₃ photosynthesis model (e.g., Farquhar et al., 1980; Farquhar and Wong, 1984; von Caemmerer, 2000; Farquhar et al., 2001; Long and Bernacchi, 2003; von Caemmerer et al., 2009; Bernacchi et al., 2013; Bellasio et al., 2015; Busch and Sage, 2017; Walker et al., 2017; Cai et al., 2018) and in C₄ photosynthesis model (Berry and Farquhar, 1978; von Caemmerer and Furbank, 1999; von Caemmerer, 2013). At light saturation, J_max is estimated by the C₃ photosynthesis model (Farquhar et al., 1980; von Caemmerer, 2013; Farquhar and Busch, 2017). Accurate estimation of J_max is important for understanding photosynthesis of C₃ and C₄ species. J_max is a key quantity to represent plant photosynthetic status under different environmental conditions when the net photosynthesis rate (A_n) is limited by the regeneration of RuBP, associated with the partitioning of electron flow through photosystem II (PSII) for RuBP carboxylation (J_C) versus that for RuBP oxygenation (J_O) (Farquhar et al., 1980; Long and Bernacchi, 2003).

By simulating light-response curves of photosynthesis (A_n–I curve), NH model has been widely used to obtain key photosynthetic characteristics (e.g., the maximum net photosynthetic rate, A_nmax; light compensation point when A_n = 0, I_c; dark respiration rate, R_d) for various species under different environmental conditions (e.g., Ögren & Evans, 1993; Thornley, 1998; Ye, 2007; Aspinwall et al., 2011; dos Santos et al., 2013; Mayoral et al., 2015; Sun et al., 2015; Park et al., 2016; Quiroz et al., 2017; Yao et al., 2017; Xu et al., 2019; Yang et al., 2020; Ye et al., 2020). Significant difference between observed A_nmax values and that estimated by NH model for various species has been widely reported (e.g., Chen et al., 2011; dos Santos et al., 2013; Lobo et al., 2014; Ogawa, 2015; Sun et al., 2015; Quiroz et al., 2017; Poirier-Pocovi et al., 2018; Ye et al., 2020). This long-standing challenge has been resolved by an A_n–I model, which adopts a nonasymptotic function and can accurately reproduce A_n–I curve over light-limited, light-saturated and photoinhibitory I levels (Ye et al., 2013) (hereafter, Ye model).

Recently, Buckley and Diaz-Espejo (2015) proposed that NH model would overestimate J_max due to its asymptotic function. A robust model which can accurately reproduce the observed J–I curve, and obtain J_max, is urgently needed (Buckley and Diaz-Espejo, 2015). Furthermore, the light response of J partitioning for RuBP carboxylation and oxygenation (J_C–I and J_O–I curves), and the key quantities to describe the curves (e.g., the maximum J_C, J_C-max, and the maximum J_O, J_O-max, as well as their corresponding saturation light intensities) are rarely studied. Meanwhile, for the first time, we compared the performances of the two models in reproducing J_C–I and J_O–I curves.

This study aimed to fill these important gaps using an observation-modeling intercomparison approach. We firstly measured leaf gas exchange and chlorophyll fluorescence over a wide range of I levels for two C₃ species [winter wheat (Triticum aestivum L.) and soybean (Glycine max L.)]. We then incorporated Ye model to reproduce A_n–I, J–I, J_C–I, and J_O–I curves and return key quantities defining the curves, and evaluated its performance against NH model and observations.

Materials and Methods

Plant Material and Measurements of Leaf Gas Exchange and Chlorophyll Fluorescence

The experiment was conducted in the Yucheng Comprehensive Experiment Station of the Chinese Academy of Science. The detailed descriptions about soil and meteorological conditions in this experiment station were referred to Ye et al. (2019; 2020). Winter wheat was planted on October 4^th, 2011 and the measurements were conducted on April 23^th, 2012. Soybean was sown in on May 6^th, 2013, and the measurements were performed on 27^th July, 2013. Using the Li-6400-40 portable photosynthesis system (Li-Cor, Lincoln, NE, USA), measurements on leaf gas exchange and chlorophyll fluorescence were simultaneously performed on mature fully-expanded sun-exposed leaves in sunny days. J was calculated as J = Φ_PSII × I × 0.5 × 0.84, where Φ_PSII is the effective quantum yield of PSII (Genty et al., 1989; Krall and Edward, 1992).

For soybean, A_n–I curves and J–I curves were generated from applying different light intensities in a descending order of 2000, 1800, 1600, 1400, 1200, 1000, 800, 600, 400, 200, 150, 100, 80, 50, and 0 μmol m^-2 s^-1. For winter wheat, the light intensity gradient started from 1800 μmol m^-2 s^-1 as the maximum, in alignment with environmental light availability from October to April. At each I step, CO₂ assimilation was monitored until a steady state was reached before logging a reading. Ambient CO₂ concentration in the cuvette (C_a) was kept constant at 380 μmol mol^-1. Leaf temperature in the cuvette was kept at about 30°C for winter wheat and 36°C for soybean, respectively. The observation-modeling intercomparison was conducted within each species.

A_n–I and J–I Analytical Models

NH model describes J–I curve as follows (Farquhar and Wong, 1984; von Caemmerer, 2000; von Caemmerer, 2013):

where α_e is the initial slope of J–I curve, θ is the curve convexity, I is the light intensity, and J_max is the maximum electron transport rate.

NH model describes A_n–I curve as follows (Ögren and Evans, 1993; Thornley, 1998; von Caemmerer, 2000):

where α is the initial slope of A_n–I curve, A_nmax is the maximum net photosynthetic rate, and R_d is the dark respiration rate when I = 0 μmol m^-2 s^-1. NH model cannot return the corresponding saturation light intensities for J_max or A_nmax due to its asymptotic function.

The model developed by Ye et al. (2013, 2019; hereafter, Ye model) describes J–I curve as follows:

where α_e is the initial slope of J–I curve, and β_e and γ_e are the photoinhibition coefficient and light-saturation coefficient of J–I curve, respectively.

The saturation irradiance corresponding to the J_max (I_e-sat) can be calculated as follows:

Using Ye model, J_max can be calculated as follows:

Ye model describes A_n–I curve as follows (Ye, 2007; Ye et al., 2013):

where α is the initial slope of A_n–I curve, β and γ are the photoinhibition coefficient and light-saturation coefficient of A_n–I curve, respectively.

The saturation irradiance corresponding to A_nmax (I_sat) can be calculated as follows:

Using Ye model, A_nmax can be calculated as follows:

J_C and J_O Estimation and J_C–I and J_O–I Analytical Models

Combining measurements of gas exchange and chlorophyll fluorescence was a reliable and easy-to-use technique widely used to determine J_O and J_C (e.g., Peterson, 1990; Comic and Briantais, 1991). In C₃ plants, carbon assimilation and photorespiration are two closely linked processes catalyzed by the key photosynthetic enzyme—RuBP carboxylase/oxygenase. Photorespiration is considered as an alternative sink for light-induced photosynthetic electron, and as a process helping consume extra photosynthetic electrons under high irradiance or other stressors limiting CO₂ availability at Rubisco (Stuhlfauth et al., 1990; Valentini et al., 1995; Long and Bernacchi, 2003). When the other alternative electron sinks are ignored or kept constant, the electron flow is mainly allocated for RuBP carboxylation and RuBP oxygenation (e.g. Farquhar et al., 1980; von Caemmerer, 2000; Farquhar et al., 2001; Long and Bernacchi, 2003; von Caemmerer et al., 2009; Bernacchi et al., 2013; von Caemmerer, 2013), and J_C and J_O can be respectively calculated as follows (Valentini et al., 1995):

where R_day is the day respiration rate, and following Fila et al. (2006), R_day = 0.5 R_d. In this study, J_C and J_O values calculated from Eqs. 9 and 10 were viewed as experimental observations—to be compared with modelled values derived from NH model and Ye model, respectively.

Using the same J–I modeling framework by Ye model, the light response of J_C (J_C–I) can be described as follows:

where α_C is the initial slope of J_C–I curve, and β_C and γ_C are two coefficient of J_C–I curve. The maximum J_C (J_C-max) and the saturation irradiance corresponding to the J_C-max (I_C-sat) can be calculated as follows:

Using the same J–I modeling framework by Ye model, the light response of J_O (J_O–I) can be described as follows:

where α_O is the initial slope of J_O–I curve, and β_O and γ_O are two coefficient of J_O–I curve. The maximum J_O (J_O-max) and the saturation irradiance corresponding to the J_O-max (I_O-sat) can be calculated as follows:

Meanwhile, NH model can describe the J_C–I and J_O–I curves as follows:

where α_C is the initial slope of J_C–I curve, θ is the curve convexity, and J_C-max is the maximum J_C, and

where α_O is the initial slope of J_O–I curve, θ is the curve convexity, and J_O-max is the maximum J_O. NH model—Eqs. 17 and 18—cannot return the corresponding saturation light intensities for J_C-max or J_O-max due to its asymptotic function.

Statistical Analysis

Statistical tests were performed using the statistical package SPSS 18.5 statistical software (SPSS, Chicago, IL). One-Way ANOVA was used to examine differences between parameter values estimated by NH model, Ye model and observed values of each parameter (A_nmax, I_sat, J_max, I_e-sat, J_C-max, I_C-sat, J_O-max, I_O-sat, etc.). Goodness of fit of the mathematical model to experimental observations was assessed using the coefficient of determination (R² = 1 – SSE/SST, where SSE is the error sum of squares, and SST is the total sum of squares).

Results

Light Response of A_n and J

Soybean and winter wheat exhibited an immediate and rapid initial increase of A_n (α) and J (α_e) with the increasing I (Figure 1 and Table 1). The increase of A_n and J continued until I reached the cultivar-specific maximum values (A_nmax and J_max) at their corresponding saturation light intensities (I_sat and I_e-sat) (Figure 1 and Table 1). Both NH model (Eqs. 1 and 2) and Ye model (Eqs. 3 and 6) showed high level of goodness of fit (R²) to experimental observations of two species (Figure 1 and Table 1). However, compared with observations, NH model significantly overestimated A_nmax and J_max (P < 0.05) for both soybean and winter wheat (Table 1). In contrast, A_nmax and J_max values returned by Ye model were in very close agreement with the observations for both species (Table 1).

Figure 1

Light Response of J_C and J_O

Both species exhibited an immediate and rapid initial increase of J_C (α_C) with the increasing I (Figure 1 and Table 1). The increase of J_C continued until I reached the cultivar-specific maximum values (J_C-max) at the corresponding saturation light intensity (I_C-sat) (Figure 1 and Table 1). Both Ye model (Eq. 11) and NH model (Eq. 17) showed high level of goodness of fit (R²) to experimental observations of both species (Figure 1 and Table 1). However, compared with observations, NH model significantly overestimated J_C-max (P < 0.05) for both soybean and winter wheat (Table 1). In contrast, J_C-max values returned by Ye model were in very close agreement with the observations for both species (Table 1).

Compared to the light-response rapidness of J_C, J_O exhibited a much slower initial increase (α_O) with the increasing I (Figure 1 and Table 1). No species showed significant difference between the observed value of J_O-max and that estimated by Ye model (Eq. 14) or NH model (Eq. 18) (Table 1). Both models showed high level of goodness of fit (R²) to experimental observations of both species (Figure 1 and Table 1).

Discussion

Assessed with an observation-modeling intercomparison approach, the results in this study highlight the robustness of Ye model in accurately reproducing A_n–I, J–I, J_C–I, and J_O–I curves and returning key quantities defining the curves, in particular: A_nmax, J_max, J_C-max, and J_O-max. On the contrary, the NH model significantly overestimates A_nmax, J_max, and J_C-max (Table 1). For the first time, our study discloses the previously widely reported overestimation of J_max (and A_nmax) by the NH model is linked to its overestimation of J_C-max but not J_O-max.

The overestimation of A_nmax by NH model found in this study is consistent with the previous reports (e.g., Calama et al., 2013; dos Santos et al., 2013; Lobo et al., 2014; Ježilová et al., 2015; Mayoral et al., 2015; Ogawa, 2015; Park et al., 2016; Quiroz et al., 2017; Poirier-Pocovi et al., 2018; Ye et al., 2020). The accurate returning of A_nmax by Ye model found in this study is consistent with previous studies using Ye model for various species under different environmental conditions (e.g., Wargent et al., 2011; Zu et al., 2011; Xu et al., 2012a; Xu et al., 2012b; Lobo et al., 2014; Xu et al., 2014; Song et al., 2015; Chen et al., 2016; Ye et al., 2019; Yang et al., 2020; Ye et al., 2020). The robustness of Ye model has also been validated for microalgae observations, including four freshwater and three marine microalgae species (Yang et al., 2020). The Ye model reproduced the A_n–I response well for all microalgae species, and produced I_sat closer to the measured values than those by three widely used models for microalgae (Yang et al., 2020). Meanwhile, the overestimation of J_max by NH model found in this study supports Buckley and Diaz-Espejo (2015) in highlighting the demerit of the asymptotic function (i.e. NH model).

One key novelty of the present study is its evaluation of both asymptotic and nonasymptotic functions in describing the light response of electron flow allocation for carboxylation and oxygenation respectively (i.e. J_C–I and J_O–I curves). To the best of our knowledge, this is the first study which has experimentally evidenced the robustness of a nonasymptotic function (Eqs. 3, 11, 14) in accurately (1) reproducing J–I, J_C–I, and J_O–I curves and (2) returning J_max, J_C-max, and J_O-max values, as well as their corresponding the saturation light intensities. These novel findings are of significance for our understanding of light responses of plant carbon assimilation and photorespiration—both are catalyzed by RuBP carboxylase/oxygenase.

The findings, and the approach of bridging experiment and modeling, in the present study remain to be tested for (1) species of different plant function types and/or climatic origin, which could exhibit different response patterns (Ye et al., 2020) and (2) plant response to interaction of multiple environmental factors (e.g., temperature, rainfall pattern, soil type) involving fluctuating light. The explicit and consistent modeling framework and parameter definitions on light responses (i.e. A_n–I, J–I, J_C–I, and J_O–I)—combined with the simplicity and robustness—allows for future transparent scaling-up of leaf-level findings to whole-plant and ecosystem scales.

Conclusions

Ye model can accurately estimate A_nmax, J_max, and J_C-max which the NH model would overestimate. Adopting an explicit and transparent analytical framework and consistent definitions on A_n–I, J–I, J_C–I, and J_O–I curves, this study highlights the advantage of Ye model over NH model in terms of (1) its extremely well reproduction of J–I, J_C–I, and J_O–I trends over a wide I range from light-limited to light-inhibitory light intensities, (2) accurately returning the wealth of key quantities defining J–I, J_C–I, and J_O–I curves, particularly J_max, J_C-max, J_O-max, and their corresponding the saturation light intensities (besides A_nmax and I_sat of A_n–I curve), and (3) being transparent in disclosing that the previously widely reported but poorly explained problem of NH model—overestimation of J_max (and the maximum plant carboxylation capacity)—is linked to its overestimation of J_C-max but not J_O-max. Besides, NH model cannot obtain their saturation light intensities corresponding to J_max, A_nmax, J_C-max, and J_O-max due to its asymptotic function. This study is of significance for both experimentalists and modelers working on better representation of photosynthetic processes under dynamic irradiance conditions.

Funding

This research was supported by the Natural Science Foundation of China (Grant No. 31960054 and 31560069) and the Key Science and Technology Innovation Team Project of Wenzhou City (Grant No. C20150008).

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