Biochemical metabolic enhancement acting as a dominant driver in intra-leaf CO2 diffusional response to soil nitrogen supplying in Soybean

Qihui Zuo; Siyu Tan; Lina Gao; Xueer Wang; Jian Zhang; Fenwu Liu; Kai Zhu

doi:10.1371/journal.pone.0340250

Abstract

Biochemical metabolism and anatomical structure within leaf tissues have been proposed as the two principal mechanisms underpinning the rapid responsiveness of mesophyll conductance (g_m) to environmental perturbations; nevertheless, empirical evidence distinguishing which of these factors acts as the dominant driver remains scarce. The response of intra-leaf CO₂ diffusion conductance including g_m and stomatal conductance (g_sc) to soil nitrogen (N) change in soybean was systematically quantified in leaf biochemical and structural characteristics. Our data revealed that (i) soil N made a positive effect on intra-leaf CO₂ diffusion and carbon assimilation that g_m and A_n (net photosynthetic rate) exhibited a significant positive response to increasing N supplying from 7.5 to 15.0 g urea m^-2 while g_sc showed no significant N-dependence. (ii) The enhanced intra-leaf CO₂ diffusion capacity induced by N application was principally attributable to the increase in g_m.(iii) The enhancement of biochemical metabolism rather than the modifications in the leaf anatomical structure constituted the predominant mechanism by which N supplementation facilitated CO₂ diffusion and carbon assimilation in soybean. (iv)Furthermore, the improvement in water use efficiency (WUE) appeared to be more closely linked to aquaporin-mediated water relations, as supported by subsequent correlation analyses.These findings will advance our understanding of the key drivers that shape g_m responsiveness to abrupt environmental variations.

Citation: Zuo Q, Tan S, Gao L, Wang X, Zhang J, Liu F, et al. (2026) Biochemical metabolic enhancement acting as a dominant driver in intra-leaf CO₂ diffusional response to soil nitrogen supplying in Soybean. PLoS One 21(1): e0340250. https://doi.org/10.1371/journal.pone.0340250

Editor: Yunzhou Li, Guizhou University, CHINA

Received: July 19, 2025; Accepted: December 18, 2025; Published: January 30, 2026

Copyright: © 2026 Zuo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: This study was supported by the Fundamental Research Program of Shanxi Province (20210302124229) and the Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi (2021L156).

Competing interests: The authors have declared that no competing interests exist.

Introduction

Like drought in soil, atmospheric nitrogen (N) deposition has become another significant ecological factor affecting plant growth and metabolism as global climate change intensifies.Global warming, by altering atmospheric circulation and hydrological processes, will lead to changes in annual precipitation and its seasonal distribution at both global and regional scales. This can further result in more frequent, prolonged, and intensified droughts in some regions [1]. Model simulations indicate that from 1986 to 2050, the spatial extent of nitrogen deposition will continue to expand globally, with a gradually increasing trend in deposition rates [2]. It is projected that by 2030, global nitrogen deposition will reach 105 Tg per year [3]. Excessive N deposition can severely weaken the photosynthetic carbon assimilation process in plants.As an important indicator of photosynthetic carbon assimilation, intra-leaf CO₂ diffusion conductance, including CO₂ stomatal conductance (g_sc) and mesophyll conductance (g_m) can significantly respond to N availability [4].The Loess Plateau region is located in arid and semiarid regions of central and western China and includes Shanxi, Shaanxi, Gansu, and Ningxia, which are important areas of agricultural production in China. With global climate change, the amount of atmospheric N deposition in this region is gradually increasing to 38.9 kg N ha^-1 a^-1 [5], which results in interactive stresses on plant growth and photosynthetic primary productivity, especially g_sc and g_m, in the local arid climate socially.

There are multiple mechanisms through which N regulates photosynthetic carbon assimilation, with leaf structure and biochemical metabolism being regarded as the two predominant factors underlying variations in intra-leaf CO₂ diffusion conductance [4,6,7]. Nitrogen enhances leaf structural and biochemical properties, inducing alterations in g_sc and g_m parameters, Consequently, substantially boosting the rate of photosynthetic CO₂ assimilation in plants [8,9]. Through its effect on mesophyll cell arrangement (enhanced to a certain extent by nitrogen), the surface areas of mesophyll cells and chloroplasts exposed to the intercellular space per unit leaf area (S_m and S_c) are increased [9], Driving the directional repositioning of chloroplasts to alleviate photo-oxidative damage to the photosynthetic apparatus [10]. In addition, nitrogen can also increase the stomatal opening (SS) [11]; improve the activity of aquaporins (AQPs), carbonic anhydrase (CA) and Rubisco (ribulose-1,5-bisphosphate carboxylase); and reduce the content of abscisic acid (ABA), significantly promoting stomatal and mesophyll CO₂ diffusion. However, excessive nitrogen has been found to increase the ABA content and reduce AQPs, CA, and Rubisco activities [6,9,12–14], thereby reducing stomatal opening and CO₂ transmembrane transport to weaken photosynthetic carbon assimilation. Compared with the dominant contribution of AQPs in regulating g_sc and g_m, the role of CA in regulating the intra-leaf CO₂ diffusion capacity is controversial. Few scholars have maintained that CA has little effect on g_m [15,16], but more studies have resolutely supported its positive role in the increase in g_m, suggesting that it accelerates the metabolism of CO₂ into bicarbonate ions and has a significant biochemical effect on CO₂ diffusion [17–21]. Our previous studies revealed the positive effects of AQPs and CA on g_m [14,22,23], but their coordinated regulatory effects with leaf anatomy in regulating intra-leaf CO₂ diffusion and carbon assimilation have not yet been comprehensively elucidated within contemporary botanical research.

In light of these considerations, some anatomical and biochemical parameters, such as the mesophyll cell wall thickness (T_cw), S_m, S_c, AQPs, CA, Rubisco and ABA, were quantified and systematically examined to delineate the interdependent relationships between leaf structural characteristics and biochemical metabolism in regulating CO₂ diffusion and photosynthetic carbon assimilation capacities against the increased atmospheric N deposition. We propose three scientific hypotheses: (i) the enhancement of intra-leaf CO₂ diffusion and carbon assimilation capacity by soil N primarily stems from its augmentation in g_m rather than in g_sc; (ii) the improvement in plant biochemical metabolic capacity constitutes the dominant mechanism through which soil N increases g_m; and (iii) the positive effect of the anatomical structure of leaves on g_m arises through its indirect promotion of enhanced biochemical metabolic capacity in plants. This methodological framework seeks to establish a theoretical foundation for advancing integrated anatomical and molecular biological investigations into plant photosynthetic carbon assimilation mechanisms.

Materials and methods

Materials

The disease-resistant and drought-resistant soybean (Glycine max (Linn.) Merr.) Jindou 23 (Guoshendou 2001011) was selected as the experimental material to conduct a pot experiment at the Experimental Station of the College of Resources and Environment, Shanxi Agricultural University, Taigu (112°28′ east longitude, 37°12′ north latitude), Shanxi Province, at 764 m a.s.l. In April 2022, three plump soybean seeds were sown in the topsoil of 18.9-L pots measuring 25.0 cm in height and 31 cm in diameter, each holding 12 L of soil. The concentrations of nitrogen (N), phosphorus (P) and potassium (K) in the potted soil were 0.90 ± 0.03, 2.72 ± 0.43 and 30.31 ± 1.94 g kg^-1, respectively.

Experimental design

The soybeans were grown under three nitrogen addition levels of 7.5 g urea m^-2 (low N addition, LN), 15.0 g urea m^-2 (medium N addition, MN) and 22.5 g urea m^-2 (high N addition, HN), respectively, and the treatment without N addition (0 g urea m^-2) was used as the control (CK). Urea solutions varying in N concentration were sprayed onto the containers during the flowering period on July 5, 2022.The growth cycle of the test plants was from April to August 2022, totaling 138 days. During the experiment, all the plants were maintained outdoors under natural sunlight conditions and were fully watered to eliminate the impact of water deficit. In addition, a solution of total nutrients was applied to the potted plants twice per month to maintain their optimum growth conditions, and the composition and content of the total nutrient solution are listed in Zhu et al. [14]. A 4.5-m long, 3-m wide and 2.1-m high rain shelter covered with a transparent plastic film (99% light transmittance) was established to eliminate the impacts of atmospheric N deposited during natural precipitation, and all the potted plants were placed under the shelter.

Simultaneous gas exchange and chlorophyll fluorescence measurements

Leaf gas exchange and chlorophyll fluorescence were simultaneously measured in the fully expanded and sun-exposed leaves from 8:00–11:30 each day under a saturated photosynthetic active photon flux density (PPFD) of 1500 µmol m^-2 s^-1 with a red:blue light ratio of 90:10 using an open-flow gas exchange system (Li-6400XT; LI-COR Inc., Lincoln, NE, USA) equipped with an integrated fluorescence leaf chamber (Li-6400–40; LI-COR). The leaf temperature and relative humidity (RH) in the leaf chamber were set to 25°C and 60%, the CO₂ concentration was maintained at 400 µmol CO₂ mol^-1 via a CO₂ mixture, and the flow rate was controlled at 300 μmol s^-1. The gas exchange parameters, steady-state and maximum fluorescence (F_s and F_m′) of leaves, with a light-saturating pulse of 7800 µmol m^-2 s^-1, were recorded via the multiphase flash method [24] after full light adaptation at an intensity of 1500 µmol m^-2 s^-1 for 25 ~ 30 minutes.

The actual photochemical efficiency of photosystem II (Φ_{PS II}) was calculated using the method of Genty et al. [25]:

(1)

The electron transport rate (J_f, μmol e^- m^-2 s^-1) was then calculated as follows:

(2)

where α represents the leaf absorptance and β represents the distribution of absorbed quanta between PS Ⅱ and PS Ⅰ. In this study, αβ was calibrated as the slope of the relationship between the net photosynthetic rate (A_n) and PPFD·Φ_{PS Ⅱ}/4 using the method of Yin et al. [26], which was obtained from the A_n/PPFD curves under a low O₂ concentration (< 1%) that was achieved by injecting pure N₂.

The g_m was estimated by the ‘variable J’ method described in Harley et al. [27]:

(3)

where C_i is the intercellular CO₂ concentration, which is directly obtained from gas exchange measurements, and Г^* and R_d represent the CO₂ compensation points in the absence of respiration and day respiration, respectively.

The R_d and apparent CO₂ photocompensation point (C_i^*) were determined using the Laisk method [28]. Briefly, three A_n/C_i curves were measured by varying the CO₂ concentration from 150 to 40 µmol CO₂ mol^-1 under three low PPFDs (150, 100 and 50 µmol m^-2 s^-1) and then linearly regressed to intersect at a given point. The intersection points were considered to be C_i^* (x-axis) and R_d (y-axis) [29,30]. Г^* was calculated as follows:

(4)

we used a single set of C_i^* (44.09 μmol mol^-1) and R_d (0.90 μmol m^-2 s^-1) values to calculate Г^* values for all growth conditions in this study because they were less affected by environmental changes.

Another important indicator of photosynthetic carbon assimilation, i.e., stomatal conductance to CO₂ (g_sc, mol CO₂ m^-2 s^-1), is the ratio of stomatal conductance to water (g_sw, mol H₂O m^-2 s^-1) and 1.6, where 1.6 is the ratio of the diffusivities of CO₂ and water in air [29].

Determinations of leaf water use efficiency

At the leaf level, the instantaneous and intrinsic water use efficiencies (WUE_ins and WUE_int, respectively) were determined as described in Ouyang et al.[31]:

(5)

(6)

where E is the transpiration rate (mmol H₂O m^-2 s^-1).

Light and electron microscopy

Three leaf discs (4.0 mm × 1.5 mm) per treatment taken from gas exchange-measured leaves were immediately fixed in FAA (alcohol: formaldehyde: glacial acetic acid = 90: 5: 5) and 2.5% glutaric aldehyde in 0.1 M phosphate buffer (pH = 7.6) at 4 °C and were further processed according to the methods described in Zhu et al. [14].

ImageJ software was used to measure the thicknesses of the leaf (T_leaf, μm) and mesophyll tissue (T_m, μm). The surface areas of mesophyll cells (S_m, μm² μm^-2) and chloroplasts (S_c, μm² μm^-2) exposed to the intercellular airspace per unit leaf area were calculated according to the methods of Evans et al. [32] and Syvertsen et al. [33].

(7)

(8)

where i = m, c. L_i is the total lengths of mesophyll cells (L_m, μm) and chloroplasts (L_c, μm) exposed to the intercellular airspace measured with ImageJ software. W (μm) was the cross-sectional width. F is the curvature correction factor calculated with the methods of Evans et al. [32]and Thain [34]. In this study, the F values for the different treatments were determined to be 1.25 (CK), 1.30 (LN), 1.23 (MN) and 1.27 (HN).

Gas- and liquid-phase conductances (g_ias and g_liq, respectively, m s^-1) were calculated according to the description in Niinemets and Reichstein [35]:

(9)

(10)

where D_a (m² s^-1) is the diffusion coefficient for CO₂ in the gas phase (1.68 × 10⁻⁵ at 30°C) [36]. ΔL_ias (μm) was taken as half of T_m [35]. ϛ is the diffusion path tortuosity (m m^-1), which was equal to 1.57 [33,35]. f_ias (%) is the fraction of mesophyll volume occupied by the intercellular airspace that was calculated according to Syvertsen et al. [33]. g_cw, g_pl, g_ct, g_en and g_st are the partial conductance values for the cell wall, plasmalemma, cytosol, chloroplast envelope and chloroplast stroma (m s^-1), respectively. The value of 0.0035 m s^-1 was taken as the value for both g_pl and g_en [37], and g_cw, g_ct and g_st were calculated using the method in Niinemets and Reichstein [35] as follows:

(11)

where ΔLi (m) represents the diffusion distance within the relevant diffusion component, pi (m³·m ⁻ ³) denotes its effective porosity, and Dw corresponds to the aqueous-phase diffusion coefficient for CO₂ (2.03 × 10 ⁻ ⁹ m²·s ⁻ ¹ at 30°C). In this analysis, ΔL_i was set to 1.2 × 10⁻⁷ (for ΔL_cw), 2.1 × 10⁻⁷ (for ΔL_ct) and 1.6 × 10⁻⁶ (for ΔL_st) according to these values for Phaseolus vulgaris L. [35]. The dimensionless coefficient r_f accounts for the decrease in diffusion conductance in the cell wall, cytosol and chloroplast stroma. r_f,i values for the cytosol (r_f,ct) and chloroplast stroma (r_f,st) were estimated to be 0.294, and r_f,cw = 1 for the cell wall [36]. The cell wall porosity (p_cw) varied with the T_cw, according to Tosens et al. [37] (p_cw = −0.3733 × T_cw + 0.3378), and p_i was set to 1.0 for the cytosol (p_ct) and stroma (p_st) (Nobel, 1991). Conductance in units of m s ⁻ ¹ can be converted to molar units via the formula: g (mol m ⁻ ² s ⁻ ¹) = g (m s ⁻ ¹) × 44.6 × [273.16/ (273.16 + T_leaf)] × (P/ 101.325), with T_leaf defined as leaf temperature (°C) and P (Pa) as air pressure.

The stomatal pore length (PL, μm) and width (PW, μm) (i.e., the major and minor axes of an ellipse) were analyzed with ImageJ software to determine the stomatal opening status at the stoma center (SS, μm²) [11].:

(12)

Measurements of related biochemical parameters

The biochemical parameters related to CO₂ diffusion, such as AQPs, the CA and Rubisco contents and activities and the ABA content, were measured via enzyme-linked immunosorbent assay (ELISA) in three fresh leaves per sample in each treatment according to Maeda et al. [38], as described in detail in Zhu et al. [14].

Statistical analysis

To ensure data validity, normality and homogeneity of variance were verified using SPSS 17.0 (SPSS Inc., Chicago, IL, USA) prior to further statistical procedures. Correlations between CO₂ diffusion conductances (g_m, g_sc and g_m/g_sc) and WUE (WUEins and WUEint), and between gliq and CA activity, were then executed. Mean values across different treatments were compared using the LSD multiple comparison test at P < 0.05.Principal Component Analysis (PCA) was performed using standardized anatomical and biochemical traits to identify the major dimensions of variation under nitrogen treatments. Additionally, partial correlation analysis was conducted to examine the direct relationships between biochemical and physiological parameters (e.g., CA activity vs. WUE_int or g_m/g_sc) while controlling for the effects of nitrogen level and aquaporin activity.

Results

Effects of N addition on g_m and g_sc

Different effects of the intensity of soil N addition on intra-leaf CO₂ diffusion were clearly manifested through corresponding variations in g_m and g_sc (Fig 1A and B). With the increase in N addition intensity, g_m showed a fluctuating trend of first increased significantly from 0.09 mol CO₂ m^-2 s^-1 (0 g urea m^-2 N addition, CK) to 0.19 mol CO₂ m^-2 s^-1 (15.0 g urea m^-2 N addition, MN) and then decreased to 0.11 mol CO₂ m^-2 s^-1 (22.5 g urea m^-2 N addition, HN) (P < 0.05), but g_sc did not change overall, except for a significant increase from 0.11 to 0.23 mol CO₂ m^-2 s^-1 under HN (P < 0.05). Thus, the different effects of soil N addition on intra-leaf CO₂ diffusion in soybean were clearly due mainly to its regulation of g_m.

Download:

Fig 1. Changes in g_m, g_sc, A_n and V_cmax during soil N addition.

The error bars represent the standard error of all measurements (n = 3). Different letters indicate significant differences among the groups (P < 0.05). g_sc, stomatal conductance; g_m, mesophyll conductance; A_n, net photosynthetic rate; V_cmax, maximum carboxylation rate. CK, control; LN, low N addition; MN, medium N addition; HN, high N addition. The same applies below.

https://doi.org/10.1371/journal.pone.0340250.g001

Response of CO₂ assimilation capacity

Although soil N addition had a significant positive effect on g_m, it did not have a statistically significant effect on the net photosynthetic or maximum carboxylation rates of CO₂ (A_n and V_cmax) (P < 0.05; Fig 1C and D). Nevertheless, both A_n and V_cmax in N-addition plants were still greater than those in non-N-addition plants, with the mean values in N-addition plants being 14.5 and 97.5 μmol CO₂ m^-2 s^-1, respectively.

Effects of N addition on leaf water use capacity

Soil N addition had a significant effect on leaf water use capacity, with WUE_ins being greater in N-addition plants than in the CK (Fig 2A), whereas WUE_int decreased with increasing N addition from 7.5 to 22.5 g urea m^-2 (Fig 2B). The different effects of N addition on WUE_ins and WUE_int should be attributable primarily to the physiological regulation of g_sc (Fig 1B), as evidenced by the fundamental relationships of WUE_ins = A_n/E and WUE_ins = A_n/g_sw (g_sw = 1.6g_sc), where g_sw denoted E.

Download:

Fig 2. Changes in WUE_ins, WUE_int, E and g_sw during soil N addition.

WUE_ins, instantaneous water use efficiency; WUE_int, intrinsic water use efficiency.

https://doi.org/10.1371/journal.pone.0340250.g002

Relationships between CO₂ diffusion conductance and water use efficiency

The correlations between water use efficiency (WUE_ins and WUE_int) and CO₂ diffusion conductance (g_m, g_sc and g_m/g_sc) and CO₂ assimilation parameters (A_n and V_cmax) were quantified in Fig 3. WUE_int showed a highly significant negative correlation with g_sc (P < 0.01) and a positive correlation with g_m/g_sc (P < 0.05), whereas the correlations between WUE_ins and g_sc and g_m/g_sc were not significant. Water use efficiency did not significantly differ with respect to g_m or A_n and V_cmax. Hence, the pronounced influence of WUE_int on the intraleaf CO₂ diffusion capacity was principally attributable to its regulatory control over g_sc and g_m/g_sc.

Download:

Fig 3. Relationships between g_m, g_sc or g_m/g_sc and WUE_ins and WUE_int and CO₂ assimilation rates (A_n and V_cmax) during soil N addition.

https://doi.org/10.1371/journal.pone.0340250.g003

Changes in leaf anatomical characteristics

Leaf anatomical traits.

N addition improved leaf morphological structure by improving the arrangement of palisade and spongy tissues (Fig 4I). Compared with the control group, mesophyll cells presented a more turgid morphology and more orderly arrangement with enlarged intercellular spaces following soil N addition. These structural modifications became increasingly pronounced with increasing N addition.

Download:

Fig 4. Light micrographs of transverse sections of control and N-addition-treated leaves.

All the leaf cross-sections were observed at 400 × magnification. Scale bar = 50 μm. (a) CK, control; (b) LN, low N addition; (c) MN, medium N addition; (d) HN, high N addition. The same applies below.

https://doi.org/10.1371/journal.pone.0340250.g004

Quantitative anatomical analysis revealed different responses to N addition in terms of leaf, mesophyll cell and cell wall thicknesses (i.e., T_leaf, T_m, and T_cw) (Table 1). Specifically, both T_leaf and T_m were positively correlated with N addition, whereas T_cw was inversely related. Collectively, S_m, V_m and V_c exhibited proportional increases with N supplying, contrasting with S_c which displayed a progressive reduction under elevated N additions. The SS was increased by soil N nutrient and it furtherly increased with N supplying, especially a significant increase under HN condition (P < 0.05). Overall, T_cw, S_m and S_c exhibited the most pronounced alterations under soil nitrogen addition rates of 7.5 and 15.0 g urea m^-2, demonstrating a strongest structural responsiveness at these specific application intensities.

Download:

Table 1. Values of leaf anatomical traits under different soil N addition treatments. All the data are the means ± SEs (n = 3). Different lowercase letters (a, b, c) indicate significant differences at P < 0.05. T_leaf, total leaf thickness; T_m, mesophyll tissue thickness; T_cw, cell wall thickness; SS, stomatal opening status; S_m, surface area of mesophyll cells exposed to intercellular space per unit leaf area; S_c, chloroplast surface facing the intercellular space per unit leaf area; V_m, volume of mesophyll cells per unit leaf area; V_c, chloroplast volume per unit leaf area; g_ias, gas-phase conductance to CO₂; g_liq, liquid-phase conductance to CO₂.

https://doi.org/10.1371/journal.pone.0340250.t001

Gas- and liquid-phase conductances

The CO₂ gas-phase diffusional capacity from substomatal cavities to the outer surface of cell walls was weakened by soil N supplementation, with g_ias values decreasing from 8.95 to 4.89 mol CO₂ m^-2 s^-1 with N addition (Table 1). In contrast to g_ias, g_liq was increased by N addition overall, with no significant difference (P < 0.05), especially under the addition level of 15.0 g urea m^-2, indicating that the CO₂ liquid-phase diffusional capacity from the outer surface of cell walls to chloroplasts was greatly strengthened by 15.0 g of urea m^-2 N addition (Fig 5, 6).

Download:

Fig 5. Transmission electron microscope images of the control and N-addition-treated leaves.

Scale bar = 10 μm. C, chloroplast; CW, mesophyll cell wall; SG, starch granule; IAS, intercellular airspace.

https://doi.org/10.1371/journal.pone.0340250.g005

Download:

Fig 6. Scanning electron microscopy (SEM) images of stoma from the control group and N-addition-treated leaves.

Scale bar = 10 μm.

https://doi.org/10.1371/journal.pone.0340250.g006

Changes in leaf biochemical parameters

Leaf biochemical parameters showed a dependence on N addition levels in soybean (Table 2). The contents of AQPs and CA and the activities of CA and Rubisco were significantly increased by soil N addition (Table 2). A significant statistical difference was found in CA content and the activities of CA and Rubisco (P < 0.05, Table 2). Differed from AQPs, CA and Rubisco, the content of ABA decreased overall, where it was significantly decreased by the HN level (P < 0.05).

Download:

Table 2. Values of the key biochemical traits in the different soil N addition treatments. All data are mean ± SE (n = 3). Different lowercase letters (a, b, c) indicate significant differences at P < 0.05. AQPs, aquaporins; CA, carbonic anhydrase; Rubisco, ribulose-1,5-bishosphate carboxylase; ABA, abscisic acid.

https://doi.org/10.1371/journal.pone.0340250.t002

Discussion

Nitrogen (N) addition positively affected plant physiological functions [9,39,40], but its positive effects were dependent on the N addition intensity [23,41,42]. In the present study, the net photosynthetic rate (A_n) of soybean leaf presented an N response coherent with g_m rather than g_sc, with A_n and g_m increasing with N supplying from 7.5 to 15.0 g urea m^-2 and then decreasing from 15.0 to 22.5 g urea m^-2 (Fig 1A and C). The g_sc did not exhibit any difference with N addition, except for a transient increase at the HN level (Fig 1B). T_cw, S_m and S_c had been further highlighted as the most important structural components determining g_m[11,19,36].We systematically investigated the mechanisms by which soil N enhanced CO₂ diffusion from these dual perspectives. Although increased S_m under N addition (Table 1) exerted a positive effect on CO₂ liquid-phase diffusion capacity, the observed reductions in S_c following N application diminished the contact area between CO₂ and chloroplast carboxylation sites and made a negative effect on g_m increase. In addition, the decreased T_cw (Table 1) would decrease cellulose and pectin content within cell walls and consequently reduce cell walls’ elasticity or rigidity and set a limitation for maximum g_m [43, 44], thereby increasing resistance to CO₂ diffusion through both cell walls and chloroplast membranes, as T_cw was suggested to be related to the bulk modulus of elasticity (ɛ), which represented the elasticity or rigidity of leaf tissues [45]. These results indicate that N-driven enhancements in photosynthetic carbon assimilation occurred primarily through mesophyll-level processes rather than stomatal adjustments. Although N addition induced anatomical alterations—increasing S_m but reducing S_c and T_cw, which theoretically should constrain g_m—both g_m and carbon assimilation parameters (i.e., A_n and V_cmax) increased in response to N addition (Fig 1). This contrast suggests that the positive effects of N supplementation were predominantly mediated by mechanisms beyond structural modifications, specifically through the enhancement of biochemical metabolism.

In contrast to the adverse effects induced by leaf anatomical modifications, N addition significantly increased both CA and Rubisco contents and activity (P < 0.05; Table 2). This would markedly improve the solubility of CO₂ in the cell matrix [7,19] and accelerate the conversion of gaseous CO₂ to HCO₃⁻ [17,21] and carboxylation efficiency, thereby leading to an increase in g_liq (Table 1), which was supported by the positive correlation between CA activity and g_liq (Fig 7). The PCA loadings plot (Fig 8) quantitatively illustrates the contribution of each measured variable to the principal components. Biochemical activity parameters, specifically CA activity and Rubisco activity, exhibited the strongest loadings on PC1, which alone explained 71.5% of the total variance. Their vectors were longest and aligned almost exclusively with the positive direction of PC1, identifying them as the dominant drivers of the physiological response to nitrogen supply. In contrast, anatomical parameters (e.g., T_CW, SS) and aquaporin activity (AQP activity) showed weaker associations with PC1, indicating their secondary role in this process.

Download:

Fig 7. Correlation between CA activity and g_liq in soybean.

Regression coefficients and significance are shown when P < 0.05. CA, carbonic anhydrase; g_liq, liquid-phase CO₂ diffusion conductance.

https://doi.org/10.1371/journal.pone.0340250.g007

Download:

Fig 8. The PCA loadings plot between biochemical and anatomical parmeters.

AQPs, aquaporins; CA, carbonic anhydrase; Rubisco, ribulose-1,5-bisphosphate carboxylase; T_cw,cellwall thickness; S_c, stomatal conductance; SS, stomatal opening; V_m, volume of mesophyll cells per unit leaf area; V_c, chloroplast volume per unit leaf area; g_ias, gas-phase conductance to CO₂; g_liq, liquid-phase conductance to CO₂.

https://doi.org/10.1371/journal.pone.0340250.g008

We have revealed the negative correlations between ABA and g_sc and g_m in our early study of Zhu et al. [14]. The decrease in leaf ABA content with N addition (Table 2) potentially alleviated its inhibitory effects on stomatal opening and AQPs expression [46,47]. Furthermore, the reduction in ABA might also reflect a shift in hormonal balance, favouring growth-promoting hormones such as cytokinin (CTK) under HN conditions, and this hypothesis requires further validation through hormone profiling. Consequently, the enhancement of biochemical metabolism rather than the modifications in the leaf anatomical structure constituted the predominant mechanism by which N supplementation facilitated CO₂ diffusion and carbon assimilation in soybean, which was also suggested by the statistical results, in which the leaf anatomical parameters did not significantly differ among the treatments (P > 0.05; Table 1), whereas the biochemical parameters, except ABA, significantly varied with N supply (P < 0.05; Table 2).

Notably, the dominant mechanism of biochemical metabolism was reinforced by improved leaf water-use efficiency (WUE), as we have suggested a significant correlation between WUE and g_sc/g_m, i.e., in Zhu et al. [14]. A positive correlation and a significant negative correlation were also found between WUE_int and gₘ/g_sc (P < 0.05, Fig 3C) and between WUE_int and g_sc (P < 0.01, Fig 3B). This further substantiated the regulatory role of WUE in the intra-leaf CO₂ diffusion capacity, with the underlying mechanism likely originating from its influence on Rubisco activity [44,48,49]. Rubisco activity significantly increased (Table 2), which greatly increased the CO₂ carboxylation capacity by increasing V_cmax (Fig 1D) and WUE_int (the ratio of A_n to g_sc, Fig 2B). The increased WUE_int would inevitably lead to increased g_m and carbon assimilation, as increased g_m increased WUE_int [4,50]. These findings suggested that plants under N addition preferentially optimize mesophyll CO₂ utilization over stomatal CO₂ uptake to balance carbon assimilation with water conservation. To quantitatively evaluate the relationships between biochemical enhancement and water relation parameters, we performed partial correlation analyses. The results revealed that aquaporin (AQPs) activity showed a strong direct correlation with the stomatal-to-mesophyll conductance ratio (g_m/g_sc; r = 0.866, P < 0.001), indicating a primary role of water relations in coordinating diffusive conductances. Meanwhile, carbonic anhydrase (CA) activity did not exhibit a significant direct effect on intrinsic water use efficiency (WUE_int) or g_m/g_sc after controlling for nitrogen level and AQPs activity (P > 0.05), and we would further explore their mechanisms in future studies (Table 3). The lack of correlation between WUE_int and g_m suggested that g_m was influenced by multiple interacting factors, including anatomical adaptations and biochemical adjustments, rather than a single dominant pathway.

Download:

Table 3. Relationships between CA activity, AQPs activity, and plant water status indicators, controlling for specific variables.

https://doi.org/10.1371/journal.pone.0340250.t003

Additionally, the observed g_m dynamics in this study aligned with previous studies showing that optimal N increased the intra-leaf CO₂ diffusion efficiency by improving biochemical and structural traits, whereas excessive N disrupted these mechanisms through metabolic imbalances [11,13]. Furthermore, excessive N induced leaf thickening and starch accumulation (Fig 7), likely due to disrupted carbon-N partitioning. These structural changes reduced the intercellular airspace and limit the gas-phase CO₂ diffusion process, as gias decreased from 8.95 to 4.89 mol CO₂ m^-2 s^-1 under HN (Table 1). These findings underscore the delicate trade-off whereby moderate N enhanced photosynthetic capacity through biochemical activation, whereas supra-optimal N imposed physical barriers and metabolic toxicity.

Conclusion

Soil nitrogen (N) had a positive effect on intra-leaf CO₂ diffusion and carbon assimilation in soybean, with g_m and A_n (net photosynthetic rate) significantly increasing with N supplying from 7.5 to 15.0 g urea m^-2, whereas g_sc showed no significant N dependence. A high N addition of 22.5 g urea m^-2 had a negative effect on g_m and A_n. The enhanced intra-leaf CO₂ diffusion capacity induced by N application was principally attributable to its augmentative effect on g_m. The improved leaf structure and enhanced biochemical metabolism constituted the primary mechanisms through which increased soil N elevated intra-leaf CO₂ diffusion and carbon assimilation, with biochemical metabolic enhancement acting as the dominant driver. In addition, the improvement in water use efficiency, with WUE_ins significantly increasing while WUE_int initially increases but then decreases, might have a great positive effect on g_m from the perspective of water dynamics.

Supporting information

S1 File. Raw data of photosynthetic fluorescence parameters and leaf anatomical structures under nitrogen treatments.

https://doi.org/10.1371/journal.pone.0340250.s001

(XLSX)

References

1. Knapp AK, Beier C, Briske DD, Classen AT, Luo Y, Reichstein M, et al. Consequences of more extreme precipitation regimes for terrestrial ecosystems. BioScience. 2008;58(9):811–21.
- View Article
- Google Scholar
2. Galloway JN, Dentener FJ, Capone DG, Boyer EW, Howarth RW, Seitzinger SP, et al. Nitrogen cycles: past, present, and future. Biogeochemistry. 2004;70(2):153–226.
- View Article
- Google Scholar
3. Zheng X, Fu C, Xu X, Yan X, Huang Y, Han S, et al. The asian nitrogen cycle case study. Ambio. 2002;31(2):79–87. pmid:12078013
- View Article
- PubMed/NCBI
- Google Scholar
4. Flexas J, Ribas-Carbó M, Diaz-Espejo A, Galmés J, Medrano H. Mesophyll conductance to CO2: current knowledge and future prospects. Plant Cell Environ. 2008;31(5):602–21. pmid:17996013
- View Article
- PubMed/NCBI
- Google Scholar
5. Liu P, Liu XJ, Liu EK, Han YL, Li LJ, Bai GJ. Temporal variation of atmospheric wet/dry reactive nitrogen deposition in Taiyuan rainfed farming area of Shanxi Province. Chin J Eco Agric. 2017;25(5):625–33.
- View Article
- Google Scholar
6. Maurel C, Verdoucq L, Luu D-T, Santoni V. Plant aquaporins: membrane channels with multiple integrated functions. Annu Rev Plant Biol. 2008;59:595–624. pmid:18444909
- View Article
- PubMed/NCBI
- Google Scholar
7. Terashima I, Hanba YT, Tholen D, Niinemets Ü. Leaf functional anatomy in relation to photosynthesis. Plant Physiol. 2011;155(1):108–16. pmid:21075960
- View Article
- PubMed/NCBI
- Google Scholar
8. Yamori W, Nagai T, Makino A. The rate-limiting step for CO(2) assimilation at different temperatures is influenced by the leaf nitrogen content in several C(3) crop species. Plant Cell Environ. 2011;34(5):764–77. pmid:21241332
- View Article
- PubMed/NCBI
- Google Scholar
9. Xiong D, Liu X, Liu L, Douthe C, Li Y, Peng S, et al. Rapid responses of mesophyll conductance to changes of CO2 concentration, temperature and irradiance are affected by N supplements in rice. Plant Cell Environ. 2015;38(12):2541–50. pmid:25923314
- View Article
- PubMed/NCBI
- Google Scholar
10. Tholen D, Boom C, Noguchi K, Ueda S, Katase T, Terashima I. The chloroplast avoidance response decreases internal conductance to CO2 diffusion in Arabidopsis thaliana leaves. Plant Cell Environ. 2008;31(11):1688–700. pmid:18721264
- View Article
- PubMed/NCBI
- Google Scholar
11. Xiong D, Flexas J, Yu T, Peng S, Huang J. Leaf anatomy mediates coordination of leaf hydraulic conductance and mesophyll conductance to CO2 in Oryza. New Phytol. 2017;213(2):572–83. pmid:27653809
- View Article
- PubMed/NCBI
- Google Scholar
12. Franks PJ. Stomatal control and hydraulic conductance, with special reference to tall trees. Tree Physiol. 2004;24(8):865–78. pmid:15172837
- View Article
- PubMed/NCBI
- Google Scholar
13. Sperling O, Karunakaran R, Erel R, Yasuor H, Klipcan L, Yermiyahu U. Excessive nitrogen impairs hydraulics, limits photosynthesis, and alters the metabolic composition of almond trees. Plant Physiol Biochem. 2019;143:265–74. pmid:31525604
- View Article
- PubMed/NCBI
- Google Scholar
14. Zhu K, Zuo Q, Liu F, Qin J, Wang A, Zhang J, et al. Divergences in leaf CO2 diffusion conductance and water use efficiency of soybean coping with water stress and its interaction with N addition. Environ Experimental Botany. 2024;217:105572.
- View Article
- Google Scholar
15. Price GD, von Caemmerer S, Evans JR, Yu J-W, Lloyd J, Oja V, et al. Specific reduction of chloroplast carbonic anhydrase activity by antisense RNA in transgenic tobacco plants has a minor effect on photosynthetic CO2 assimilation. Planta. 1994;193(3):331–40.
- View Article
- Google Scholar
16. Williams TG, Flanagan LB, Coleman JR. Photosynthetic gas exchange and discrimination against 13CO2 and C18O16O in tobacco plants modified by an antisense construct to have low chloroplastic carbonic anhydrase. Plant Physiol. 1996;112(1):319–26. pmid:12226395
- View Article
- PubMed/NCBI
- Google Scholar
17. Gillon JS, Yakir D. Internal conductance to CO(2) diffusion and C(18)OO discrimination in C(3) leaves. Plant Physiol. 2000;123(1):201–14. pmid:10806237
- View Article
- PubMed/NCBI
- Google Scholar
18. Badger M. The roles of carbonic anhydrases in photosynthetic CO(2) concentrating mechanisms. Photosynth Res. 2003;77(2–3):83–94. pmid:16228367
- View Article
- PubMed/NCBI
- Google Scholar
19. Evans JR, Kaldenhoff R, Genty B, Terashima I. Resistances along the CO2 diffusion pathway inside leaves. J Exp Bot. 2009;60(8):2235–48. pmid:19395390
- View Article
- PubMed/NCBI
- Google Scholar
20. Tholen D, Zhu X-G. The mechanistic basis of internal conductance: a theoretical analysis of mesophyll cell photosynthesis and CO2 diffusion. Plant Physiol. 2011;156(1):90–105. pmid:21441385
- View Article
- PubMed/NCBI
- Google Scholar
21. Perez-Martin A, Michelazzo C, Torres-Ruiz JM, Flexas J, Fernández JE, Sebastiani L, et al. Regulation of photosynthesis and stomatal and mesophyll conductance under water stress and recovery in olive trees: correlation with gene expression of carbonic anhydrase and aquaporins. J Exp Bot. 2014;65(12):3143–56. pmid:24799563
- View Article
- PubMed/NCBI
- Google Scholar
22. Zhu K, Yuan F, Wang A, Yang H, Guan D, Jin C, et al. Effects of soil rewatering on mesophyll and stomatal conductance and the associated mechanisms involving leaf anatomy and some physiological activities in Manchurian ash and Mongolian oak in the changbai mountains. Plant Physiol Biochem. 2019;144:22–34. pmid:31550610
- View Article
- PubMed/NCBI
- Google Scholar
23. Zhu K, Wang A, Wu J, Yuan F, Guan D, Jin C, et al. Effects of nitrogen additions on mesophyll and stomatal conductance in Manchurian ash and Mongolian oak. Sci Rep. 2020;10(1):10038. pmid:32572068
- View Article
- PubMed/NCBI
- Google Scholar
24. Loriaux SD, Avenson TJ, Welles JM, McDermitt DK, Eckles RD, Riensche B, et al. Closing in on maximum yield of chlorophyll fluorescence using a single multiphase flash of sub-saturating intensity. Plant Cell Environ. 2013;36(10):1755–70. pmid:23586649
- View Article
- PubMed/NCBI
- Google Scholar
25. Genty B, Briantais J-M, Baker NR. The relationship between the quantum yield of photosynthetic electron transport and quenching of chlorophyll fluorescence. Biochimica et Biophysica Acta (BBA) - General Subjects. 1989;990(1):87–92.
- View Article
- Google Scholar
26. Yin X, Struik PC, Romero P, Harbinson J, Evers JB, Vander PP, et al. Using combined measurements of gas exchange and chlorophyll fluorescence to estimate parameters of a biochemical C photosynthesis model: a critical appraisal and a new integrated approach applied to leaves in a wheat (Triticum aestivum) canopy. Plant Cell Environ. 2009;32(5):448–64. pmid:19183300
- View Article
- PubMed/NCBI
- Google Scholar
27. Harley PC, Loreto F, Di Marco G, Sharkey TD. Theoretical considerations when estimating the Mesophyll conductance to CO(2) Flux by analysis of the response of photosynthesis to CO(2). Plant Physiol. 1992;98(4):1429–36. pmid:16668811
- View Article
- PubMed/NCBI
- Google Scholar
28. Laisk AK. Kinetics of photosynthesis and photorespiration of C3 plants. Moskosw; Nauka. 1977;198(1):243–51.
29. von Caemmerer S, Farquhar GD. Some relationships between the biochemistry of photosynthesis and the gas exchange of leaves. Planta. 1981;153(4):376–87. pmid:24276943
- View Article
- PubMed/NCBI
- Google Scholar
30. Sun J, Guan D, Wu J, Jing Y, Yuan F, Wang A, et al. Day and night respiration of three tree species in a temperate forest of northeastern China. iForest. 2015;8(1):25–32.
- View Article
- Google Scholar
31. Ouyang W, Struik PC, Yin X, Yang J. Stomatal conductance, mesophyll conductance, and transpiration efficiency in relation to leaf anatomy in rice and wheat genotypes under drought. J Exp Bot. 2017;68(18):5191–205. pmid:28992130
- View Article
- PubMed/NCBI
- Google Scholar
32. Evans J, Caemmerer S, Setchell B, Hudson G. The relationship between CO2 transfer conductance and leaf anatomy in transgenic tobacco with a reduced content of rubisco. Functional Plant Biol. 1994;21(4):475.
- View Article
- Google Scholar
33. Syvertsen JP, Lloyd J, Mcconchie C, Kriedemann PE, Farquhar GD. On the relationship between leaf anatomy and CO2 diffusion through the mesophyll of hypostomatous leaves. Plant Cell & Environment. 1995;18(2):149–57.
- View Article
- Google Scholar
34. THAIN JF. Curvature correction factors in the measurement of cell surface areas in plant tissues1. J Exp Bot. 1983;34(1):87–94.
- View Article
- Google Scholar
35. Niinemets Ü, Reichstein M. Controls on the emission of plant volatiles through stomata: A sensitivity analysis. J Geophys Res. 2003;108(D7).
- View Article
- Google Scholar
36. Tomás M, Flexas J, Copolovici L, Galmés J, Hallik L, Medrano H, et al. Importance of leaf anatomy in determining mesophyll diffusion conductance to CO2 across species: quantitative limitations and scaling up by models. J Exp Bot. 2013;64(8):2269–81. pmid:23564954
- View Article
- PubMed/NCBI
- Google Scholar
37. Tosens T, Niinemets Ü, Westoby M, Wright IJ. Anatomical basis of variation in mesophyll resistance in eastern Australian sclerophylls: news of a long and winding path. J Exp Bot. 2012;63(14):5105–19. pmid:22888123
- View Article
- PubMed/NCBI
- Google Scholar
38. Maeda Y, Smith BL, Agre P, Knepper MA. Quantification of Aquaporin-CHIP water channel protein in microdissected renal tubules by fluorescence-based ELISA. J Clin Invest. 1995;95(1):422–8. pmid:7529263
- View Article
- PubMed/NCBI
- Google Scholar
39. Zhang H, McDowell NG, Adams HD, Wang A, Wu J, Jin C, et al. Divergences in hydraulic conductance and anatomical traits of stems and leaves in three temperate tree species coping with drought, N addition and their interactions. Tree Physiol. 2020;40(2):230–44. pmid:31860728
- View Article
- PubMed/NCBI
- Google Scholar
40. Zhang H, Li X, Guan D, Wang A, Yuan F, Wu J. Nitrogen nutrition addition mitigated drought stress by improving carbon exchange and reserves among two temperate trees. Agricultural and Forest Meteorology. 2021;311:108693.
- View Article
- Google Scholar
41. Wang D, Xu Z, Zhao J, Wang Y, Yu Z. Excessive nitrogen application decreases grain yield and increases nitrogen loss in a wheat–soil system. Acta Agriculturae Scandinavica, Section B - Soil & Plant Science. 2011;61(8):681–92.
- View Article
- Google Scholar
42. Kong L, Xie Y, Hu L, Si J, Wang Z. Excessive nitrogen application dampens antioxidant capacity and grain filling in wheat as revealed by metabolic and physiological analyses. Sci Rep. 2017;7:43363. pmid:28233811
- View Article
- PubMed/NCBI
- Google Scholar
43. Peguero-Pina JJ, Sancho-Knapik D, Gil-Pelegrín E. Ancient cell structural traits and photosynthesis in today’s environment. J Experimental Botany. 2017;68(7):1389–92.
- View Article
- Google Scholar
44. Nadal M, Flexas J, Gulías J. Possible link between photosynthesis and leaf modulus of elasticity among vascular plants: a new player in leaf traits relationships?. Ecol Lett. 2018;21(9):1372–9. pmid:30027556
- View Article
- PubMed/NCBI
- Google Scholar
45. Bartlett MK, Scoffoni C, Sack L. The determinants of leaf turgor loss point and prediction of drought tolerance of species and biomes: a global meta-analysis. Ecol Lett. 2012;15(5):393–405. pmid:22435987
- View Article
- PubMed/NCBI
- Google Scholar
46. Shatil-Cohen A, Attia Z, Moshelion M. Bundle-sheath cell regulation of xylem-mesophyll water transport via aquaporins under drought stress: a target of xylem-borne ABA?. Plant J. 2011;67(1):72–80. pmid:21401747
- View Article
- PubMed/NCBI
- Google Scholar
47. Kapilan R, Vaziri M, Zwiazek JJ. Regulation of aquaporins in plants under stress. Biol Res. 2018;51(1):4. pmid:29338771
- View Article
- PubMed/NCBI
- Google Scholar
48. Li S, Liu J, Liu H, Qiu R, Gao Y, Duan A. Role of hydraulic signal and ABA in decrease of leaf stomatal and Mesophyll conductance in soil drought-stressed tomato. Front Plant Sci. 2021;12:653186. pmid:33995449
- View Article
- PubMed/NCBI
- Google Scholar
49. Zhou Z, Struik PC, Gu J, van der Putten PEL, Wang Z, Yin X, et al. Enhancing leaf photosynthesis from altered chlorophyll content requires optimal partitioning of nitrogen. Crop Environ. 2023;2(1):24–36.
- View Article
- Google Scholar
50. Barbour MM, Kaiser BN. The response of mesophyll conductance to nitrogen and water availability differs between wheat genotypes. Plant Sci. 2016;251:119–27. pmid:27593470
- View Article
- PubMed/NCBI
- Google Scholar

[ref1] 1. Knapp AK, Beier C, Briske DD, Classen AT, Luo Y, Reichstein M, et al. Consequences of more extreme precipitation regimes for terrestrial ecosystems. BioScience. 2008;58(9):811–21.
View Article
Google Scholar

[2] View Article

[3] Google Scholar

[ref2] 2. Galloway JN, Dentener FJ, Capone DG, Boyer EW, Howarth RW, Seitzinger SP, et al. Nitrogen cycles: past, present, and future. Biogeochemistry. 2004;70(2):153–226.
View Article
Google Scholar

[5] View Article

[6] Google Scholar

[ref3] 3. Zheng X, Fu C, Xu X, Yan X, Huang Y, Han S, et al. The asian nitrogen cycle case study. Ambio. 2002;31(2):79–87. pmid:12078013
View Article
PubMed/NCBI
Google Scholar

[8] View Article

[9] PubMed/NCBI

[10] Google Scholar

[ref4] 4. Flexas J, Ribas-Carbó M, Diaz-Espejo A, Galmés J, Medrano H. Mesophyll conductance to CO2: current knowledge and future prospects. Plant Cell Environ. 2008;31(5):602–21. pmid:17996013
View Article
PubMed/NCBI
Google Scholar

[12] View Article

[13] PubMed/NCBI

[14] Google Scholar

[ref5] 5. Liu P, Liu XJ, Liu EK, Han YL, Li LJ, Bai GJ. Temporal variation of atmospheric wet/dry reactive nitrogen deposition in Taiyuan rainfed farming area of Shanxi Province. Chin J Eco Agric. 2017;25(5):625–33.
View Article
Google Scholar

[16] View Article

[17] Google Scholar

[ref6] 6. Maurel C, Verdoucq L, Luu D-T, Santoni V. Plant aquaporins: membrane channels with multiple integrated functions. Annu Rev Plant Biol. 2008;59:595–624. pmid:18444909
View Article
PubMed/NCBI
Google Scholar

[19] View Article

[20] PubMed/NCBI

[21] Google Scholar

[ref7] 7. Terashima I, Hanba YT, Tholen D, Niinemets Ü. Leaf functional anatomy in relation to photosynthesis. Plant Physiol. 2011;155(1):108–16. pmid:21075960
View Article
PubMed/NCBI
Google Scholar

[23] View Article

[24] PubMed/NCBI

[25] Google Scholar

[ref8] 8. Yamori W, Nagai T, Makino A. The rate-limiting step for CO(2) assimilation at different temperatures is influenced by the leaf nitrogen content in several C(3) crop species. Plant Cell Environ. 2011;34(5):764–77. pmid:21241332
View Article
PubMed/NCBI
Google Scholar

[27] View Article

[28] PubMed/NCBI

[29] Google Scholar

[ref9] 9. Xiong D, Liu X, Liu L, Douthe C, Li Y, Peng S, et al. Rapid responses of mesophyll conductance to changes of CO2 concentration, temperature and irradiance are affected by N supplements in rice. Plant Cell Environ. 2015;38(12):2541–50. pmid:25923314
View Article
PubMed/NCBI
Google Scholar

[31] View Article

[32] PubMed/NCBI

[33] Google Scholar

[ref10] 10. Tholen D, Boom C, Noguchi K, Ueda S, Katase T, Terashima I. The chloroplast avoidance response decreases internal conductance to CO2 diffusion in Arabidopsis thaliana leaves. Plant Cell Environ. 2008;31(11):1688–700. pmid:18721264
View Article
PubMed/NCBI
Google Scholar

[35] View Article

[36] PubMed/NCBI

[37] Google Scholar

[ref11] 11. Xiong D, Flexas J, Yu T, Peng S, Huang J. Leaf anatomy mediates coordination of leaf hydraulic conductance and mesophyll conductance to CO2 in Oryza. New Phytol. 2017;213(2):572–83. pmid:27653809
View Article
PubMed/NCBI
Google Scholar

[39] View Article

[40] PubMed/NCBI

[41] Google Scholar

[ref12] 12. Franks PJ. Stomatal control and hydraulic conductance, with special reference to tall trees. Tree Physiol. 2004;24(8):865–78. pmid:15172837
View Article
PubMed/NCBI
Google Scholar

[43] View Article

[44] PubMed/NCBI

[45] Google Scholar

[ref13] 13. Sperling O, Karunakaran R, Erel R, Yasuor H, Klipcan L, Yermiyahu U. Excessive nitrogen impairs hydraulics, limits photosynthesis, and alters the metabolic composition of almond trees. Plant Physiol Biochem. 2019;143:265–74. pmid:31525604
View Article
PubMed/NCBI
Google Scholar

[47] View Article

[48] PubMed/NCBI

[49] Google Scholar

[ref14] 14. Zhu K, Zuo Q, Liu F, Qin J, Wang A, Zhang J, et al. Divergences in leaf CO2 diffusion conductance and water use efficiency of soybean coping with water stress and its interaction with N addition. Environ Experimental Botany. 2024;217:105572.
View Article
Google Scholar

[51] View Article

[52] Google Scholar

[ref15] 15. Price GD, von Caemmerer S, Evans JR, Yu J-W, Lloyd J, Oja V, et al. Specific reduction of chloroplast carbonic anhydrase activity by antisense RNA in transgenic tobacco plants has a minor effect on photosynthetic CO2 assimilation. Planta. 1994;193(3):331–40.
View Article
Google Scholar

[54] View Article

[55] Google Scholar

[ref16] 16. Williams TG, Flanagan LB, Coleman JR. Photosynthetic gas exchange and discrimination against 13CO2 and C18O16O in tobacco plants modified by an antisense construct to have low chloroplastic carbonic anhydrase. Plant Physiol. 1996;112(1):319–26. pmid:12226395
View Article
PubMed/NCBI
Google Scholar

[57] View Article

[58] PubMed/NCBI

[59] Google Scholar

[ref17] 17. Gillon JS, Yakir D. Internal conductance to CO(2) diffusion and C(18)OO discrimination in C(3) leaves. Plant Physiol. 2000;123(1):201–14. pmid:10806237
View Article
PubMed/NCBI
Google Scholar

[61] View Article

[62] PubMed/NCBI

[63] Google Scholar

[ref18] 18. Badger M. The roles of carbonic anhydrases in photosynthetic CO(2) concentrating mechanisms. Photosynth Res. 2003;77(2–3):83–94. pmid:16228367
View Article
PubMed/NCBI
Google Scholar

[65] View Article

[66] PubMed/NCBI

[67] Google Scholar

[ref19] 19. Evans JR, Kaldenhoff R, Genty B, Terashima I. Resistances along the CO2 diffusion pathway inside leaves. J Exp Bot. 2009;60(8):2235–48. pmid:19395390
View Article
PubMed/NCBI
Google Scholar

[69] View Article

[70] PubMed/NCBI

[71] Google Scholar

[ref20] 20. Tholen D, Zhu X-G. The mechanistic basis of internal conductance: a theoretical analysis of mesophyll cell photosynthesis and CO2 diffusion. Plant Physiol. 2011;156(1):90–105. pmid:21441385
View Article
PubMed/NCBI
Google Scholar

[73] View Article

[74] PubMed/NCBI

[75] Google Scholar

[ref21] 21. Perez-Martin A, Michelazzo C, Torres-Ruiz JM, Flexas J, Fernández JE, Sebastiani L, et al. Regulation of photosynthesis and stomatal and mesophyll conductance under water stress and recovery in olive trees: correlation with gene expression of carbonic anhydrase and aquaporins. J Exp Bot. 2014;65(12):3143–56. pmid:24799563
View Article
PubMed/NCBI
Google Scholar

[77] View Article

[78] PubMed/NCBI

[79] Google Scholar

[ref22] 22. Zhu K, Yuan F, Wang A, Yang H, Guan D, Jin C, et al. Effects of soil rewatering on mesophyll and stomatal conductance and the associated mechanisms involving leaf anatomy and some physiological activities in Manchurian ash and Mongolian oak in the changbai mountains. Plant Physiol Biochem. 2019;144:22–34. pmid:31550610
View Article
PubMed/NCBI
Google Scholar

[81] View Article

[82] PubMed/NCBI

[83] Google Scholar

[ref23] 23. Zhu K, Wang A, Wu J, Yuan F, Guan D, Jin C, et al. Effects of nitrogen additions on mesophyll and stomatal conductance in Manchurian ash and Mongolian oak. Sci Rep. 2020;10(1):10038. pmid:32572068
View Article
PubMed/NCBI
Google Scholar

[85] View Article

[86] PubMed/NCBI

[87] Google Scholar

[ref24] 24. Loriaux SD, Avenson TJ, Welles JM, McDermitt DK, Eckles RD, Riensche B, et al. Closing in on maximum yield of chlorophyll fluorescence using a single multiphase flash of sub-saturating intensity. Plant Cell Environ. 2013;36(10):1755–70. pmid:23586649
View Article
PubMed/NCBI
Google Scholar

[89] View Article

[90] PubMed/NCBI

[91] Google Scholar

[ref25] 25. Genty B, Briantais J-M, Baker NR. The relationship between the quantum yield of photosynthetic electron transport and quenching of chlorophyll fluorescence. Biochimica et Biophysica Acta (BBA) - General Subjects. 1989;990(1):87–92.
View Article
Google Scholar

[93] View Article

[94] Google Scholar

[ref26] 26. Yin X, Struik PC, Romero P, Harbinson J, Evers JB, Vander PP, et al. Using combined measurements of gas exchange and chlorophyll fluorescence to estimate parameters of a biochemical C photosynthesis model: a critical appraisal and a new integrated approach applied to leaves in a wheat (Triticum aestivum) canopy. Plant Cell Environ. 2009;32(5):448–64. pmid:19183300
View Article
PubMed/NCBI
Google Scholar

[96] View Article

[97] PubMed/NCBI

[98] Google Scholar

[ref27] 27. Harley PC, Loreto F, Di Marco G, Sharkey TD. Theoretical considerations when estimating the Mesophyll conductance to CO(2) Flux by analysis of the response of photosynthesis to CO(2). Plant Physiol. 1992;98(4):1429–36. pmid:16668811
View Article
PubMed/NCBI
Google Scholar

[100] View Article

[101] PubMed/NCBI

[102] Google Scholar

[ref28] 28. Laisk AK. Kinetics of photosynthesis and photorespiration of C3 plants. Moskosw; Nauka. 1977;198(1):243–51.

[ref29] 29. von Caemmerer S, Farquhar GD. Some relationships between the biochemistry of photosynthesis and the gas exchange of leaves. Planta. 1981;153(4):376–87. pmid:24276943
View Article
PubMed/NCBI
Google Scholar

[105] View Article

[106] PubMed/NCBI

[107] Google Scholar

[ref30] 30. Sun J, Guan D, Wu J, Jing Y, Yuan F, Wang A, et al. Day and night respiration of three tree species in a temperate forest of northeastern China. iForest. 2015;8(1):25–32.
View Article
Google Scholar

[109] View Article

[110] Google Scholar

[ref31] 31. Ouyang W, Struik PC, Yin X, Yang J. Stomatal conductance, mesophyll conductance, and transpiration efficiency in relation to leaf anatomy in rice and wheat genotypes under drought. J Exp Bot. 2017;68(18):5191–205. pmid:28992130
View Article
PubMed/NCBI
Google Scholar

[112] View Article

[113] PubMed/NCBI

[114] Google Scholar

[ref32] 32. Evans J, Caemmerer S, Setchell B, Hudson G. The relationship between CO2 transfer conductance and leaf anatomy in transgenic tobacco with a reduced content of rubisco. Functional Plant Biol. 1994;21(4):475.
View Article
Google Scholar

[116] View Article

[117] Google Scholar

[ref33] 33. Syvertsen JP, Lloyd J, Mcconchie C, Kriedemann PE, Farquhar GD. On the relationship between leaf anatomy and CO2 diffusion through the mesophyll of hypostomatous leaves. Plant Cell & Environment. 1995;18(2):149–57.
View Article
Google Scholar

[119] View Article

[120] Google Scholar

[ref34] 34. THAIN JF. Curvature correction factors in the measurement of cell surface areas in plant tissues1. J Exp Bot. 1983;34(1):87–94.
View Article
Google Scholar

[122] View Article

[123] Google Scholar

[ref35] 35. Niinemets Ü, Reichstein M. Controls on the emission of plant volatiles through stomata: A sensitivity analysis. J Geophys Res. 2003;108(D7).
View Article
Google Scholar

[125] View Article

[126] Google Scholar

[ref36] 36. Tomás M, Flexas J, Copolovici L, Galmés J, Hallik L, Medrano H, et al. Importance of leaf anatomy in determining mesophyll diffusion conductance to CO2 across species: quantitative limitations and scaling up by models. J Exp Bot. 2013;64(8):2269–81. pmid:23564954
View Article
PubMed/NCBI
Google Scholar

[128] View Article

[129] PubMed/NCBI

[130] Google Scholar

[ref37] 37. Tosens T, Niinemets Ü, Westoby M, Wright IJ. Anatomical basis of variation in mesophyll resistance in eastern Australian sclerophylls: news of a long and winding path. J Exp Bot. 2012;63(14):5105–19. pmid:22888123
View Article
PubMed/NCBI
Google Scholar

[132] View Article

[133] PubMed/NCBI

[134] Google Scholar

[ref38] 38. Maeda Y, Smith BL, Agre P, Knepper MA. Quantification of Aquaporin-CHIP water channel protein in microdissected renal tubules by fluorescence-based ELISA. J Clin Invest. 1995;95(1):422–8. pmid:7529263
View Article
PubMed/NCBI
Google Scholar

[136] View Article

[137] PubMed/NCBI

[138] Google Scholar

[ref39] 39. Zhang H, McDowell NG, Adams HD, Wang A, Wu J, Jin C, et al. Divergences in hydraulic conductance and anatomical traits of stems and leaves in three temperate tree species coping with drought, N addition and their interactions. Tree Physiol. 2020;40(2):230–44. pmid:31860728
View Article
PubMed/NCBI
Google Scholar

[140] View Article

[141] PubMed/NCBI

[142] Google Scholar

[ref40] 40. Zhang H, Li X, Guan D, Wang A, Yuan F, Wu J. Nitrogen nutrition addition mitigated drought stress by improving carbon exchange and reserves among two temperate trees. Agricultural and Forest Meteorology. 2021;311:108693.
View Article
Google Scholar

[144] View Article

[145] Google Scholar

[ref41] 41. Wang D, Xu Z, Zhao J, Wang Y, Yu Z. Excessive nitrogen application decreases grain yield and increases nitrogen loss in a wheat–soil system. Acta Agriculturae Scandinavica, Section B - Soil & Plant Science. 2011;61(8):681–92.
View Article
Google Scholar

[147] View Article

[148] Google Scholar

[ref42] 42. Kong L, Xie Y, Hu L, Si J, Wang Z. Excessive nitrogen application dampens antioxidant capacity and grain filling in wheat as revealed by metabolic and physiological analyses. Sci Rep. 2017;7:43363. pmid:28233811
View Article
PubMed/NCBI
Google Scholar

[150] View Article

[151] PubMed/NCBI

[152] Google Scholar

[ref43] 43. Peguero-Pina JJ, Sancho-Knapik D, Gil-Pelegrín E. Ancient cell structural traits and photosynthesis in today’s environment. J Experimental Botany. 2017;68(7):1389–92.
View Article
Google Scholar

[154] View Article

[155] Google Scholar

[ref44] 44. Nadal M, Flexas J, Gulías J. Possible link between photosynthesis and leaf modulus of elasticity among vascular plants: a new player in leaf traits relationships?. Ecol Lett. 2018;21(9):1372–9. pmid:30027556
View Article
PubMed/NCBI
Google Scholar

[157] View Article

[158] PubMed/NCBI

[159] Google Scholar

[ref45] 45. Bartlett MK, Scoffoni C, Sack L. The determinants of leaf turgor loss point and prediction of drought tolerance of species and biomes: a global meta-analysis. Ecol Lett. 2012;15(5):393–405. pmid:22435987
View Article
PubMed/NCBI
Google Scholar

[161] View Article

[162] PubMed/NCBI

[163] Google Scholar

[ref46] 46. Shatil-Cohen A, Attia Z, Moshelion M. Bundle-sheath cell regulation of xylem-mesophyll water transport via aquaporins under drought stress: a target of xylem-borne ABA?. Plant J. 2011;67(1):72–80. pmid:21401747
View Article
PubMed/NCBI
Google Scholar

[165] View Article

[166] PubMed/NCBI

[167] Google Scholar

[ref47] 47. Kapilan R, Vaziri M, Zwiazek JJ. Regulation of aquaporins in plants under stress. Biol Res. 2018;51(1):4. pmid:29338771
View Article
PubMed/NCBI
Google Scholar

[169] View Article

[170] PubMed/NCBI

[171] Google Scholar

[ref48] 48. Li S, Liu J, Liu H, Qiu R, Gao Y, Duan A. Role of hydraulic signal and ABA in decrease of leaf stomatal and Mesophyll conductance in soil drought-stressed tomato. Front Plant Sci. 2021;12:653186. pmid:33995449
View Article
PubMed/NCBI
Google Scholar

[173] View Article

[174] PubMed/NCBI

[175] Google Scholar

[ref49] 49. Zhou Z, Struik PC, Gu J, van der Putten PEL, Wang Z, Yin X, et al. Enhancing leaf photosynthesis from altered chlorophyll content requires optimal partitioning of nitrogen. Crop Environ. 2023;2(1):24–36.
View Article
Google Scholar

[177] View Article

[178] Google Scholar

[ref50] 50. Barbour MM, Kaiser BN. The response of mesophyll conductance to nitrogen and water availability differs between wheat genotypes. Plant Sci. 2016;251:119–27. pmid:27593470
View Article
PubMed/NCBI
Google Scholar

[180] View Article

[181] PubMed/NCBI

[182] Google Scholar

Figures

Abstract

Introduction

Materials and methods

Materials

Experimental design

Simultaneous gas exchange and chlorophyll fluorescence measurements

Determinations of leaf water use efficiency

Light and electron microscopy

Measurements of related biochemical parameters

Statistical analysis

Results

Effects of N addition on gm and gsc

Response of CO2 assimilation capacity

Effects of N addition on leaf water use capacity

Relationships between CO2 diffusion conductance and water use efficiency

Changes in leaf anatomical characteristics

Leaf anatomical traits.

Gas- and liquid-phase conductances

Changes in leaf biochemical parameters

Discussion

Conclusion

Supporting information

S1 File. Raw data of photosynthetic fluorescence parameters and leaf anatomical structures under nitrogen treatments.

References

Effects of N addition on g_m and g_sc

Response of CO₂ assimilation capacity

Relationships between CO₂ diffusion conductance and water use efficiency