Estimation of intrinsic water-use efficiency from δ13C signature of C3 leaves: Assumptions and uncertainty

Ma, Wei Ting; Yu, Yong Zhi; Wang, Xuming; Gong, Xiao Ying

doi:10.3389/fpls.2022.1037972

MINI REVIEW article

Front. Plant Sci., 12 January 2023

Sec. Functional Plant Ecology

Volume 13 - 2022 | https://doi.org/10.3389/fpls.2022.1037972

This article is part of the Research Topic Insights in Functional Plant Ecology 2022 View all 10 articles

Estimation of intrinsic water-use efficiency from δ¹³C signature of C₃ leaves: Assumptions and uncertainty

Wei Ting Ma¹

Yong Zhi Yu¹

Xuming Wang^1,2†

Xiao Ying Gong^1,2,3*†

¹Key Laboratory for Subtropical Mountain Ecology (Ministry of Science and Technology and Fujian Province Funded), College of Geographical Sciences, Fujian Normal University, Fuzhou, China
²Key Laboratory for Humid Subtropical Eco-Geographical Processes of the Ministry of Education, Fujian Normal University, Fuzhou, China
³Fujian Provincial Key Laboratory for Plant Eco-physiology, Fuzhou, China

Carbon isotope composition (δ¹³C) has been widely used to estimate the intrinsic water-use efficiency (iWUE) of plants in ecosystems around the world, providing an ultimate record of the functional response of plants to climate change. This approach relies on established relationships between leaf gas exchange and isotopic discrimination, which are reflected in different formulations of ¹³C-based iWUE models. In the current literature, most studies have utilized the simple, linear equation of photosynthetic discrimination to estimate iWUE. However, recent studies demonstrated that using this linear model for quantitative studies of iWUE could be problematic. Despite these advances, there is a scarcity of review papers that have comprehensively reviewed the theoretical basis, assumptions, and uncertainty of ¹³C-based iWUE models. Here, we 1) present the theoretical basis of ¹³C-based iWUE models: the classical model (iWUE_sim), the comprehensive model (iWUE_com), and the model incorporating mesophyll conductance (iWUE_mes); 2) discuss the limitations of the widely used iWUE_sim model; 3) and make suggestions on the application of the iWUE_mes model. Finally, we suggest that a mechanistic understanding of mesophyll conductance associated effects and post-photosynthetic fractionation are the bottlenecks for improving the ¹³C-based estimation of iWUE.

Introduction

During photosynthesis, plant stomata act as a control valve for the diffusion of CO₂ and water vapor, regulating the rates of water and carbon exchange between the biosphere and the atmosphere (de Boer et al., 2011; Adams et al., 2020; Walker et al., 2021). Intrinsic water-use efficiency (iWUE), defined as the ratio of net photosynthetic rate (A_n) to stomatal conductance for water vapor (g_sw), plays a key role in quantifying carbon uptake and water loss at leaf to continental scales (Seibt et al., 2008; Keenan et al., 2013). The response of iWUE is fundamental to climate change research since small changes in iWUE can have profound impacts on global carbon and water cycles. Furthermore, iWUE can provide insights into the mechanisms of plant physiological responses to climate change and support the screening and breeding of climate-resilient crops (Farquhar and Richards, 1984; von Caemmerer et al., 2014; Gresset et al., 2014). Central to these research domains is the quantification of iWUE.

Stable carbon isotope discrimination (Δ) can be used as an integrated measure of iWUE in C₃ plants (Farquhar et al., 1989). Plants discriminate against ¹³C in favour of ¹²C during photosynthetic CO₂ assimilation in C₃ leaves, and the variation in carbon isotope composition (δ¹³C) from source CO₂ to photosynthetic products (e.g., bulk leaf organic carbon or sugars) is termed as Δ, following Farquhar et al. (1982b); Farquhar et al. (1989):

\begin{array}{l} Δ = \frac{δ^{13} C_{a} - δ^{13} C_{p}}{1 + δ^{13} C_{p}} & Equation 1 \end{array}

where atmospheric δ¹³C_a is approximately -7~-8‰ during the 20th century. Δ can also be estimated from δ¹³C of CO₂ entering (δ_in and C_in) and leaving (δ_out and C_out) the cuvette during gas exchange, termed as online ¹²C/¹³C discrimination (Evans et al., 1986):

\begin{array}{l} Δ_{online} = \frac{ξ (δ_{out} - δ_{in})}{1 + δ_{out} - ξ (δ_{out} - δ_{in})} & Equation 2 \end{array}

where ξ= C_in/(C_in-C_out). In this way, Δ can be measured nondestructively to probe real-time responses of photosynthesis at high temporal resolution. Changes in photosynthetic parameters (A_n and g_s) are captured in Δ_online and the isotopic signatures are further imprinted on plant tissues during biosynthesis. As such, biomass-based Δ reflects physiological status of plants throughout the growth period of plant tissues (Cernusak et al., 2013; Soh et al., 2019). Different from classical approaches such as gas exchange or growth analysis, biomass-based Δ can be applied retrospectively, providing a useful record of iWUE at large spatial and temporal scales (Frank et al., 2015; Adams et al., 2020; Gong et al., 2022).

Inferring iWUE from isotopic records relies on theoretical models. In the current literature, most studies have utilized the simple, linear equation of photosynthetic discrimination to estimate iWUE. However, it can be problematic to interpret iWUE using this linear model which ignores effects other than diffusion through stomata and carboxylation. For instance, Seibt et al. (2008) suggested that the uncertainty in iWUE-¹³C models was related to the simplification of mesophyll conductance (g_m). g_m represents the conductance to CO₂ diffusion from the intercellular space to the carboxylation site in chloroplasts, a key limiting factor of photosynthesis in addition to stomatal conductance and biochemical capacity (Tholen et al., 2012; Stangl et al., 2019). However, recent advances in δ¹³C-based iWUE estimation have not been systematically reviewed. The main objective of this mini review is to concisely summarize the theoretical basis and uncertainties of δ¹³C-based iWUE models. We (i) present different formulations of Δ and the associated assumptions, (ii) present Δ-based iWUE models derived from those formulations: the classical model (iWUE_sim), the comprehensive model (iWUE_com), the model incorporating g_m (iWUE_mes), (iii) discuss the limitations of the widely used iWUE_sim model; and make suggestions on the application of the iWUE_mes model.

Comprehensive model of photosynthetic ¹³C discrimination and simplifications

A comprehensive description of ¹³C discrimination (Δ_com) during C₃ photosynthesis was given by Farquhar et al. (1982b) and extended to include ternary effects of transpiration on CO₂ assimilation by Farquhar and Cernusak (2012):

\begin{array}{l} Δ_{com} = \frac{1}{1 - t} (a_{a c} \frac{C_{a} - C_{i}}{C_{a}}) + \frac{1 + t}{1 - t} (a_{m} \frac{C_{i} - C_{c}}{C_{a}} + b \frac{C_{c}}{C_{a}} - \frac{α_{b}}{α_{e}} e \frac{R_{d}}{V_{c}} \frac{C_{c}}{C_{a}} - \frac{α_{b}}{α_{f}} f \frac{Г^{*}}{C_{a}}) & Equation 3 \end{array}

and

\begin{array}{l} t = \frac{(1 + a_{a c}) E}{2 g_{a c}} & Equation 4 \end{array}

\begin{array}{l} a_{a c} = \frac{a_{b} (C_{a} - C_{s}) + a_{s} (C_{s} - C_{i})}{C_{a} - C_{i}} & Equation 5 \end{array}

where a_b (2.9‰) and a_s (4.4‰) are fractionations associated with the diffusion of CO₂ through leaf boundary layer and in the air, respectively. a_m (1.8‰) is the fractionation associated with the dissolution and diffusion of CO₂ in mesophyll (see Table S1 for the list of parameters). C_a, C_s, C_i and C_c represent the mole fraction of CO₂ in air, at leaf surface, in the intercellular spaces and chloroplast, respectively (Figure 1). Δ_com can be separated into a series of fractionation components of leaf boundary layer conductance (Δ_g_bc), stomatal conductance (Δ_g_sc), mesophyll conductance (Δ_g_m), Rubisco (ribulose-1,5-bisphosphate carboxylase/oxygenase) carboxylation (Δ_b), day respiration (Δ_e), and photorespiration (Δ_f). Note that t is included to account for the ternary effects of transpiration rate (E) on photosynthetic discrimination (Farquhar and Cernusak, 2012). Usually, the effect of t is small and can be omitted under low or moderate vapor pressure deficit (VPD) (Farquhar and Cernusak, 2012; Evans and Caemmerer, 2013). If Δ_g_bc is also omitted (C_a=C_s and g_ac=g_sc), the Δ_com model is simplified as:

FIGURE 1

Figure 1 Diagram of the CO₂ diffusion pathway in C₃ leaves and different formulations of iWUE (iWUE_com, iWUE_{mes R}, iWUE_mes, and iWUE_sim) derived from the Farquhar et al. model for photosynthetic ¹³C discrimination.

\begin{array}{l} Δ_{mes R} = a_{s} \frac{C_{a} - C_{i}}{C_{a}} + a_{m} \frac{C_{i} - C_{c}}{C_{a}} + b \frac{C_{c}}{C_{a}} - \frac{α_{b}}{α_{e}} e \frac{R_{d}}{V_{c}} \frac{C_{c}}{C_{a}} - \frac{α_{b}}{α_{f}} f \frac{Г^{*}}{C_{a}} & Equation 6 \end{array}

where the subscript “mes R” indicates that the expression takes mesophyll conductance, day respiration and photorespiration into account.

Δ_e, the respiratory contribution to discrimination is mainly determined by respiratory fractionation (e), and R_d/(An+ R_d). Δ_e has rarely been accurately quantified largely due to the difficulty of estimating R_d (Tcherkez et al., 2017; Gong et al., 2018). Moreover, fractionation of day respiration has rarely been reported, and e estimated from respiration in the dark varies between 0 and -6‰ (Ghashghaie et al., 2003; Tcherkez et al., 2010). Under natural conditions, Δ_e is usually small and negligible (Seibt et al., 2008; Ubierna and Farquhar, 2014). Notably, a significant apparent respiratory fractionation may occur when the CO₂ source used for combined gas exchange and isotopic measurements has a δ¹³C differed from that of the ambient air (Gillon and Griffiths, 1997; Gong et al., 2015). Under such conditions, e should be corrected to account for the isotopic disequilibria between photosynthetic and respiratory fluxes (Wingate et al., 2007; Gong et al., 2015). Assuming Δ_e=0, Equation 6 can be simplified as:

\begin{array}{l} Δ_{mes} = a_{s} \frac{C_{a} - C_{i}}{C_{a}} + a_{m} \frac{C_{i} - C_{c}}{C_{a}} + b \frac{C_{c}}{C_{a}} - \frac{α_{b}}{α_{f}} f \frac{Г^{*}}{C_{a}} & Equation 7 \end{array}

C_c is usually unknown since its calculation requires g_m which cannot be directly measured. g_m is assumed to be infinite in early studies (for a review see Flexas et al., 2012); that is, CO₂ mole fraction in the chloroplast is equal to that in the intercellular space. Assuming C_i=C_c and Δ_f=0, Equation 7 is simplified as:

\begin{array}{l} Δ_{sim} = a_{s} + (b' - a_{s}) \frac{C_{i}}{C_{a}} & Equation 8 \end{array}

Comprehensive model of iWUE and simplifications

The comprehensive model of iWUE which includes all fractionation components of Equation 3 was first derived by Ma et al. (2021):

\begin{array}{l} {iWUE}_{com} = c_{a} \frac{a_{a c} (1 - є) + (1 + t) [\frac{Г^{*}}{c_{a}} (\frac{e' R_{d}}{A_{n} + R_{d}} - f') + є (b - \frac{e' R_{d}}{A_{n} + R_{d}})] - (1 - t) Δ}{\frac{(1 + t) (b - \frac{e' R_{d}}{A_{n} + R_{d}}) - a_{a c}}{\frac{1}{k} + \frac{W}{2}} - (1 + t) k \frac{g_{a c}}{g_{m}} (a_{m} - b + \frac{e' R_{d}}{A_{n} + R_{d}})} & Equation 9 \end{array}

where e’=ea_b/a_e, f’=fa_b/a_f and є=(1/k-W/2)/(1/k+W/2). This formulation is particularly useful for assessing the contribution of each fractionation component to iWUE estimates. Ma et al. (2021) performed sensitivity tests using theoretical data of the standard photosynthetic scenarios. Their results indicated that ternary correction and Δ_g_bc had little influence on iWUE_com estimates (error< 2 μmol mol^-1), which is in agreement with Seibt et al. (2008). Neglecting the contribution of t and Δ_g_bc, Equation 9 can be simplified as:

\begin{array}{l} {iWUE}_{mes R} = \frac{c_{a}}{k} \cdot \frac{b - Δ - f' \frac{Γ^{*}}{c_{a}} - e' \frac{R_{d}}{A_{n} + R_{d}} (1 - \frac{Γ^{*}}{c_{a}})}{b - a_{s} + \frac{g_{s c}}{g_{m}} (b - a_{m} + e' \frac{R_{d}}{A_{n} + R_{d}}) - e' \frac{R_{d}}{A_{n} + R_{d}}} & Equation 10 \end{array}

Δ_e in the iWUE_{mes R} model could be ignored as it caused an error of less than 2 μmol mol^-1 in typical photosynthetic scenarios (Ma et al., 2021). Excluding the contribution of day respiratory, Equation 10 can be simplified as:

\begin{array}{l} {iWUE}_{mes} = \frac{c_{a}}{k} \cdot \frac{b - Δ - f' \frac{Γ^{*}}{c_{a}}}{b - a_{s} + \frac{g_{s c}}{g_{m}} (b - a_{m})} & Equation 11 \end{array}

The iWUE_mes model provided iWUE estimates that are numerically very similar with iWUE_com (error< 3 μmol mol^-1) (Ma et al., 2021). Neglecting the contribution of g_m and photorespiration, the simplified equation for iWUE is given as:

\begin{array}{l} {iWUE}_{sim} = \frac{C_{a}}{k} (\frac{b' - Δ}{b' - a}) & Equation 12 \end{array}

This linear relationship between iWUE and photosynthetic ¹³C discrimination is the most used to estimate iWUE, however, the limitations of this formulation have been raised (Seibt et al., 2008; Ubierna and Farquhar, 2014; Ma et al., 2021).

Uncertainty in iWUE_sim estimation associated with mesophyll conductance

Experimental evidence shows that g_m exerts a significant limitation on CO₂ diffusion and leads to a significant drawdown from C_i to C_c (Loreto et al., 1992; Flexas et al., 2008; Cano et al., 2014). It is apparent from Equation 11 that, assuming an infinite g_m will lead to overestimation of iWUE, this is supported by experimental observations (Barbour et al., 2010; Stangl et al., 2019; Adams et al., 2020). Experimental results showed that the relationship between Δ and water-use efficiency is at least partly a function of g_m (Warren and Adams, 2006). Therefore, it is important to incorporate g_m in the parameterization of the iWUE model. Ma et al. (2021) showed that iWUE_sim overestimated iWUE by c. 65%. Importantly, the magnitude of overestimation is dependent on Δ, making correction using empirical relations difficult. These results raise concerns regarding the accuracy of iWUE_sim estimations.

The overestimation of the iWUE_sim model has also been observed in recent studies using ¹³C series of environmental archives (Baca Cabrera et al., 2021; Bing et al., 2022). More importantly, iWUE_sim model could provide biased estimations of historical iWUE trend. Gong et al. (2022) analyzed tree ring ¹³C series across the globe using the iWUE_mes model, and reported that iWUE_sim model significantly overestimated iWUE (by c. 100%) and the rate of iWUE gain with time or C_a (by c. 70%) during the 20th century. This finding has been confirmed by studies carried out in distinct ecosystems (Bing et al., 2022; Mathias and Hudiburg, 2022). Failure to consider g_m must lead to an overestimated historical trend as implied by the partial derivative of iWUE_mes (Equation 11) (Gong et al., 2022):

\begin{array}{l} \frac{d iWUE}{d C_{a}} = \frac{b - Δ}{k (\frac{g_{s c}}{g_{m}} (b - a_{m}) + b - a_{s})} & Equation 13 \end{array}

Given that ¹³C series of environmental archives (e.g. tree rings) provide a unique proxy for benchmarking the output of land surface models (Frank et al., 2015; Wang et al., 2017; Lavergne et al., 2022), cautions should be paid when iWUE_sim model is used to predict historical trend of iWUE.

Uncertainty in iWUE_sim estimation associated with b’

The value and physiological meaning of b’ in the equation of Δ_sim or iWUE_sim remain subjects of debate. Initially, Farquhar et al. (1982a) proposed that b’ (27‰) could be derived from early in vitro estimations of Rubisco carboxylation. As it agreed well with the relationship between measured biomass-based Δ and C_i/C_a, it was interpreted as a fitted value. However, when measured Δ from online instantaneous measurements was used to fit Equation 8, the fitted b’ appears to be lower than 27‰ (Caemmerer and Evans, 1991; Ma et al., 2021).

b’ was also explained as the net fractionation caused by Rubisco and PEPC (phosphoenolpyruvate carboxylase). Farquhar and Richards (1984) described b’ as a function of relative contribution of Rubisco and PEPC carboxylation:

\begin{array}{l} b' = (1 - β) b + β b_{4} & Equation 14 \end{array}

where b (29-30‰) and b₄ (usually taken as -5.7‰ at 25°C) are fractionation factors of Rubisco and PEPC carboxylation, respectively. β is the proportion of carbon fixation through PEPC carboxylation. PEPC uses $HC O_{3}^{-}$ produced by CO₂ hydration as the substrate for the synthesis of aspartate or malate, which is important for the control of cellular pH (Davies, 1979). Generally, carboxylation by Rubisco contributes a greater fraction of carbon in plants and respiratory substrates. But it is also suggested that the PEPC carboxylation could be important under the conditions of low stomatal conductance or carboxylation in darkness (Ikeda and Yamada, 1981; Gupta et al., 1994; Hibberd and Quick, 2002). Furthermore, several studies have revealed that N source and concentration were potential factors affecting carbon fixation by PEPC, which indicates that b’ could vary with nitrogen metabolism (Raven and Farquhar, 1990; Douthe et al., 2012; Lian et al., 2021). That is, Equation 14 is not particularly useful for iWUE estimation because β is variable and difficult to quantify.

b’ has also been described by Ubierna and Farquhar (2014) as a parameter that included carboxylation, mesophyll conductance, and photorespiration:

\begin{array}{l} b' ≅ b \frac{C_{c}}{C_{i}} + a_{m} (1 - \frac{C_{c}}{C_{i}}) - f \frac{Г^{*}}{C_{a}} & Equation 15 \end{array}

According to Equation 15, b’ is largely dependent on C_c/C_i which is modulated by g_m. It should be noted that the most used b’=27‰ is consistent with the C_c/C_i value of 0.9, higher than the common values of 0.7-0.8 (Caemmerer and Evans, 1991; Warren et al., 2003). So far, Equations 14 and 15 have only been used to discuss the potential origin of variation in b’, but have not been incorporated in the model of iWUE estimation. In short, there is still no consensus concerning the interpretation of b’, and current discussion on b’ (Equations 14, 15) illustrated that it should not be treated as a constant value of 27‰.

Uncertainty in iWUE associated with post-photosynthetic fractionation

Post-photosynthetic fractionation (Δ_post) includes the discrimination processes that follow photosynthetic carbon fixation, altering δ¹³C signals in plant organs and leaves at different development stages (Badeck et al., 2005; Vogado et al., 2020). In general, heterotrophic organs (branches, stems and roots) are ¹³C-enriched compared with autotrophic organs (leaves) (Badeck et al., 2005; Bowling et al., 2008; Cernusak et al., 2009; Lamade et al., 2016), and the immature leaves (heterotrophic phase) are ¹³C-enriched (by c. 2‰) compared to mature leaves (autotrophic phase) in both deciduous and evergreen species (Lamade et al., 2009; Vogado et al., 2020). However, the contribution of Δ_post to δ¹³C of plant tissues and its influence on iWUE estimation are poorly understood.

Several studies has accounted for Δ_post to estimate iWUE (Table S2). Gimeno et al. (2021) found an improvement in correlation between iWUE estimated from gas exchange and that from Δ when g_m and Δ_post were accounted for. In that study, Δ_post was taken as -2.5‰ estimated from the δ¹³C difference between phloem contents and whole-tree photosynthesis. Similarly, δ¹³C of wood and cellulose have been corrected by -3.2‰ and -1.3‰, respectively, to account for the offset from leaf δ¹³C (Thomas et al., 2013; Brownlee et al., 2016). In other studies, iWUE was calculated from tree-ring with a δ¹³C offset of -2‰ to account for Δ_post (Michelot et al., 2011; Frank et al., 2015). Without correcting a Δ_post of about 2.5‰, iWUE estimated from the δ¹³C of tree-ring could be overestimated by 20% (Gessler et al., 2009).

The likely mechanisms underlying Δ_post include fractionation associated with respiration, transport and mixing of assimilates (Tcherkez et al., 2003; Brüggemann et al., 2011; Bögelein et al., 2019). Respiratory fractionation ranges from -6 to 0‰ in various species (Duranceau et al., 1999; Ghashghaie et al., 2001; Tcherkez et al., 2003). Also, there are some variations in the apparent fractionation during transport processes (e.g., day-night differences in δ¹³C of leaf-export organic matter and different leaf-to-phloem δ¹³C signatures along vertical canopy gradients) and very few direct measurements of isotopic differences between components at molecule/atom scale (Gessler et al., 2008; Mauve et al., 2009; Gilbert et al., 2011; Gilbert et al., 2012; Bögelein et al., 2019). In addition, post-photosynthetic fractionation is complicated by ontogenic effects (e.g., size, height, and age of individuals) that can confound the relationship between iWUE and environmental factors (Vadeboncoeur et al., 2020). That is, the influence of Δ_post could accumulate over time and lead to age-dependent patterns (Cernusak et al., 2009). Therefore, using a constant, empirical value of Δ_post could be unreliable. A mechanistic description of Δ_post should be very useful to improve the iWUE estimates, which requires further study on the fractionations associated with respiration, transport and allocation of assimilates.

iWUE_mes, a useful, simplified model for estimating iWUE

iWUE_mes takes the influence of mesophyll conductance and photorespiratory fractionation into account. We propose to use the iWUE_mes model (Equation 11) since it considers the components that have a significant influence on the iWUE estimation. In particular, it includes g_m effect which is known to affect iWUE prediction.

Parameterizing the iWUE_mes model requires g_sc/g_m rather than g_m (Ma et al., 2021). Some studies use a constant g_m in the equation to estimate iWUE (Keeling et al., 2017), which makes more sense than disregarding g_m. However, the assumption of constant g_m is not supported by experimental evidence. The positive relationships between g_sc and g_m have been reported in many studies (Flexas et al., 2013; Gong et al., 2018), and this relationship is rather conserved across levels of CO₂, irradiance, and drought stress and functionally distinct species (Flexas et al., 2008; Ma et al., 2021; Gong et al., 2022). Incorporating the g_sc/g_m ratio improves the predictive accuracy of the iWUE model, as demonstrated in gas exchange experiments (Ma et al., 2021). Without knowing g_m, it is preferable to use the average g_sc/g_m of 0.79 ( ± 0.07) derived from a global synthesis to parameterize the iWUE_mes model rather than using the iWUE_sim model.

We acknowledge that using a constant g_sc/g_m is not always adequate. As more g_m data become available, interspecific differences in g_sc/g_m can be identified and should be accounted for in the estimated iWUE. Theoretically, species-specific g_sc/g_m is more appropriate to be used in the iWUE_mes estimation. It is also noteworthy that short-term responses of g_m are still not well defined, implying that neglecting short-term variation in g_sc/g_m might lead to errors in estimating iWUE at nonsteady-states, thus should be addressed in further work. Moreover, the iWUE_mes model does not account for the post-photosynthetic fractionation, due to a lack of knowledge on post-photosynthetic fractionation. Therefore, we recommend for biomass-based analyses to distinguish the age of organs to minimize the influence of post-photosynthetic fractionation.

Conclusion remarks

The comprehensive model of photosynthetic ¹³C discrimination of Farquhar and Cernusak (2012) is a synthesis of current understanding, and provides the theoretical basis for estimating iWUE from the ¹³C composition of plant materials. The classical iWUE_sim model has been shown to strongly overestimate iWUE and its historical trends due to the neglect of g_m associated effect, limiting its use in quantitative studies. iWUE_mes is suggested as a useful, simplified model for quantitative estimation of iWUE, which has been included in a standardized, open-source tool (R package) for calculation of iWUE from stable isotope signatures (Mathias and Hudiburg, 2022). Nonetheless, the formulation of iWUE_mes could still be further improved. For example, a fixed, empirical g_sc/g_m value could be replaced by species-specific values or mechanistic relationships derived from experimental results. ¹³C discrimination of plant material, combining with appropriate iWUE models, is also an ultimate tool for screening genetic resources to enhance the iWUE of crops under climate change scenarios. One of the primary questions is how g_sc and g_m of plants will respond to changes in temperature, water availability, and carbon dioxide concentration. Furthermore, the response of post-photosynthetic fractionation to climate change factors remains unknown. We conclude that mechanistic descriptions of g_m associated effect and post-photosynthetic fractionation are the bottlenecks for improving the ¹³C-based estimation of iWUE.

Author contributions

XG conceptualized the topic of this review, WM and YY wrote the first draft, and all authors contributed to the writing and revision of the manuscript. All authors contributed to the article and approved the submitted version.

Funding

This work was supported by the National Natural Science Foundation of China (NSFC 31870377, 32120103005, 32201277).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpls.2022.1037972/full#supplementary-material

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