Effect of elevated carbon dioxide on the growth, development, and nutrient composition of C₃ and C₄ functional groups

Abstract

The concentration of CO₂ ([CO₂]) in the atmosphere has been rapidly increasing over recent decades and is projected to reach 1000 ppm (parts per million) by 2100. This rise in [CO₂] has the potential to impact plant growth and development. Different functional groups of plants have been suggested to respond differently to increases in [CO₂]. In this study, we investigated five crop species belonging to two functional groups represented by one plant species, C₃ dicot (cotton), C₃ monocot (wheat), nodule-forming and nitrogen-fixing C₃ dicot (soybean), C₄ monocot (sorghum), and a C₄ dicot (Amaranthus). We hypothesized that the C₄ functional groups would exhibit a saturated response at current [CO₂] levels, while C₃ plants will continuously respond positively to increased [CO₂]. The five plant species were grown in sunlit plant growth chambers under six [CO₂] levels ranging from 320 ppm to 820 ppm in 100 ppm increments from planting till 34 days. C₃ species, mainly cotton and soybean, exhibited significant increases in leaf area (74%), shoot dry weight (87%), and total biomass under elevated [CO₂], while C₄ species showed minimal response. Root weight and root-by-shoot ratio of all the crops except cotton (69% increase in root weight) were unaffected by increases in [CO₂]. The overall micro- and macro-nutrient composition of leaves decreased under elevated [CO₂], with notable exceptions in zinc for Amaranthus and copper for wheat. The results showed that C₃ plants, mainly dicots, are more responsive to increases in [CO₂], likely due to their photosynthetic mechanism, while C₄ plants showed limited or no response. The study highlights the varying responses of different functional groups to increasing [CO₂] and emphasizes potential challenges for the nutrient quality of crops in the future.

Graphical abstract

Keywords

elevated CO₂ / plant functional groups / early season growth / roots / mineral

1 Introduction

The CO₂ concentration ([CO₂]) in the atmosphere has been rising rapidly over the last few decades, with increases of 1.5 ppm (parts per million) per year in the 1990s, 2 ppm per year in 2000s, and 2.4 ppm per year in 2010s (NOAA Research, 2020). Predictions indicate that it is expected to increase more in the upcoming years, possibly hitting the 1000 ppm mark by 2100 (IPCC, 2023). The industrial age and anthropogenic activities have already increased the atmospheric [CO₂] by 45% (Buis, 2019) to current levels of 425 ppm as compared to 1980. Plant growth and developmental responses to an increase in [CO₂] may depend on plant functional groups, such as C₃ or C₄ groups or monocots or dicots (Poorter and Navas, 2003; Rakhmankulova et al., 2023; Wang et al., 2023).

C₃ plants include a majority of land plants that use one of the earliest evolved photosynthetic pathways, known as the C₃ pathway (Sage, 2004). These plants dominate the world food production, with two of the major staple food crops—wheat (Triticum aestivum) and rice (Oryza sativa)—relying on this photosynthetic pathway. C₄ plants, on the other hand, are relatively recent in a geological time scale, first appearing around 20−30 million years ago when the atmospheric [CO₂] decreased (Sage, 2004). C₄ plants use a specialized photosynthetic pathway characterized by biochemical and anatomical modification (Kranz anatomy) that elevates the intracellular [CO₂] at the site of Rubisco carboxylation (Taiz and Zeiger, 2014). This is facilitated by a spatial separation of metabolic processes between two specialized leaf cell types, mesophyll and bundle sheath cells (Gowik and Westhoff, 2011). CO₂ is initially fixed in mesophyll cells by phosphoenolpyruvate (PEP) carboxylase, which is then transported to bundle sheath cells where CO₂ is released by decarboxylating enzymes and refixed by Rubisco (Hatch, 1987; Taiz and Zeiger, 2014; Von Caemmerer, 2021; Salesse-Smith et al., 2025). In contrast, Rubisco operates in mesophyll cells in C₃ plants and, under ambient [CO₂], is prone to photorespiration (Taiz and Zeiger, 2014; Walker et al., 2016). This mechanism helps C₄ plants to perform better under lower [CO₂], whereas the productivity of C₃ plants decreases under similar conditions (Taylor et al., 2014; Walker et al., 2016).

Both C₃ and C₄ plant groups include monocots as well as dicot plants, though the C₄ dicots are less abundant compared to C₄ monocots (Ehleringer et al., 1997). While agriculturally important C₄ crops are mainly monocots, dicot species also exhibit C₄ photosynthesis, with many of them being noxious weeds or old-field invaders (Ehleringer et al., 1997). C₃ and C₄ plants are affected differently by [CO₂] due to their different photosynthetic mechanisms (Poorter, 1993; Rakhmankulova et al., 2023). Because C₄ plants already concentrate CO₂ around Rubisco, their photosynthesis is primarily saturated at current atmospheric CO₂ levels and is generally expected to show a smaller response to elevated [CO₂] compared to C₃ plants (Ainsworth and Long, 2005; Ainsworth and Long, 2021). However, in a meta-analysis done by Wand et al. (1999), the response of C₄ plants was comparable to that of C₃ plants (33% and 25% increase in carbon assimilation in C₃ and C₄ plants, respectively). In another study by Khan et al. (2024), maize (Zea mays L.) showed a positive response to elevated CO₂ at 550 ppm but not at 700 ppm suggesting the saturation of the crop response at higher [CO₂]. Wild species of C₄ plants respond differently from cultivated species. Plant response to elevated [CO₂] also depends on the age and growth stage, which may further contribute to variability. Therefore, it would be incorrect to say that elevated [CO₂] will not have a notable impact on C₄ plants. In addition to photosynthesis, elevated [CO₂] also affects a range of plant physiologic and biochemical traits, such as stomatal conductance, transpiration efficiency, and mineral nutrient composition (McGrath and Lobell, 2013; Houshmandfar et al., 2018; Hu et al., 2022; Gojon et al., 2023). Nutritional quality often declines under elevated [CO₂] raising concerns for human and livestock nutrition.

N₂-fixing plants exhibiting C₃ photosynthesis are also affected by elevated [CO₂]; however, they have been reported to perform better under elevated CO₂ conditions compared to other functional groups (Reich et al., 2001; Lee et al., 2003; Ainsworth and Long, 2005; Cui et al., 2024). Functional groups are defined as plant groups that share functional traits and respond similarly to changes in environmental conditions (Raunkiaer, 1934; Poorter and Navas, 2003). For example, C₃ monocots, which include wheat and barley (Hordeum vulgare), form a functional group characterized by common morphological traits, such as narrow leaves and fibrous root systems, as well as functional traits like the C₃ photosynthetic pathway (Kellogg, 2015). Lee et al. (2003) reported that the N₂-fixing legume (Lupinus perennis) showed an 80% increase in biomass under elevated [CO₂] conditions irrespective of soil N supply. In contrast, the response of non-N₂ fixing forb (Achillea millefolium) depended on N supply, and even at the highest soil N levels, it was significantly lower than that of Lupinus. Serraj et al. (1998) observed that under elevated [CO₂] levels, soybean plants exhibited a delayed decrease in N₂ fixation rates in response to drought conditions. Experimental data strongly support the theoretical expectation that, under existing [CO₂] levels, C₃ grasses are more limited by CO₂ availability than C₄ species. As a result, they are likely to exhibit more significant responses to elevated CO₂ levels (Reich et al., 2018).

Several studies have been conducted on CO₂ enrichment using various techniques, including greenhouses, growth chambers, open-top chambers, and free-air CO₂ enrichment (FACE). However, there are limitations to using these techniques like the use of artificial lighting that doesn’t represent sunlit conditions (Reddy et al., 2001), and fluctuating [CO₂] levels in most of the FACE systems (Ainsworth and Long, 2005). Some studies have compared different functional groups for their response to elevated [CO₂]_, including meta-analyses (Reich et al., 2001; Ainsworth and Long, 2005); however, meta-analyses do not provide accurate comparisons as the studies used for meta-analysis differ in the length of the experiments, techniques used for CO₂ enrichment, number of replications or species used per functional group. Most comparative studies have incorporated only two [CO₂] levels (ambient and elevated; Barbehenn et al., 2004; Reich et al., 2018). Comparing one elevated [CO₂] level with the ambient [CO₂] may not show the responses that would be evident in the near future, especially if the difference in [CO₂] between the two levels is big.

A comparative study among different functional groups across C₃ and C₄ plants, including monocots, dicots, and nodulating, N₂-fixing species, using the sunlit growth chambers with multiple levels of [CO₂]_, has not been done. Quantitative information on various growth and developmental responses of different functional groups will help predict plants’ precise responses to [CO₂] under well-defined environmental conditions. For this study, we included five different functional groups, each represented by a single plant species: C₃ dicots (cotton, Gossypium hirsutum), C₃ monocots (wheat), nodule-forming and nitrogen-fixing C₃ dicots (soybean, Glycine max), C₄ monocots (sorghum, Sorghum bicolor), and C₄ dicots (Amaranthus). These species were chosen based on their contrasting functional types (C₃ vs. C₄, monocot vs. dicot, nitrogen-fixing vs. non-fixing) and global agricultural significance, which allows for a comparative understanding under elevated [CO₂] conditions. We hypothesized that the C₄ functional groups would exhibit a saturated response at current atmospheric [CO₂] levels, and C₃ plants would continuously respond positively with increased [CO₂]. The objective of this study was to quantify C₃ and C₄ species’ response to a wide range of atmospheric [CO₂] under optimum temperature, water, and nutrient conditions during the early season.

2 Materials and methods

2.1 Experimental facility

The study utilized the Soil-Plant-Atmosphere-Research (SPAR) facility at the Environmental Plant Physiology Laboratory, Department of Plant and Soil Sciences, Mississippi State University, MS, USA. The SPAR is a unique facility with precise control of environments while growing plants under natural sunlight, unlike other growth chambers. It features a metal bin to store soil media and a Plexiglas chamber to support the plant canopy. The Plexiglas chambers permit 97% of the solar radiation (Zhao et al., 2003). The SPAR is controlled through an automated control system, and irrigation and nutrients are supplied via Hoagland’s nutrient solution (Hewitt, 1953) via a semi-automated drip irrigation system. The specifications of the SPAR facility are described by Reddy et al. (2001).

2.2 Experimental details

A pot culture experiment was conducted using five different plant species, representing monocots or dicots with C₃ or C₄ photosynthetic systems, in 2020 (Table 1). Thirty polyvinylchloride pots (10 cm× 46 cm) filled with fine sand and topsoil mix (3:1 ratio by volume; 87% sand, 2% clay, and 11% silt) were placed in each SPAR unit in 10 rows × 3 columns. The bottom of the pots contained a 1 cm diameter hole and were filled with 250 g of gravel for easy drainage. The pots were arranged in a split-plot design with [CO₂] as the main plot and species as sub-plots. Each SPAR unit contained six replications of each species arranged in a completely randomized design. Four seeds were sown per pot and thinned to one plant after emergence. The SPAR facility was maintained at 30°C/22°C day/night temperature and 70% relative humidity throughout the experiment. The plants were watered with Hoagland’s nutrient solution daily using an automated, computer-controlled drip irrigation system. The irrigation amount was adjusted according to the daily evapotranspiration (Reddy et al., 2001). The [CO₂] treatments were imposed immediately after sowing. Six levels of [CO₂] from 320 ppm to 820 ppm at 100 ppm increments were maintained in each SPAR facility, accommodating five species. The [CO₂] levels in each SPAR unit are continuously monitored and adjusted every 10 s throughout the day, as described by Reddy et al. (2001) (Fig. 1). During daylight hours, [CO₂] levels are maintained within 10 ppm of the target set points by adjusting the controls. A mass-balance approach, utilizing the output from dedicated CO₂ analysers for each unit (Model LI 6200, LI-COR Inc., Lincoln, Nebraska, USA), is employed to operate the solenoid valves as required. To regulate [CO₂] in each chamber, pure CO₂ is injected via a system comprising a pressure regulator, solenoid, and needle valves, and a flowmeter. These flowmeters are calibrated with a gas displacement meter at the start and end of each experiment (Reddy et al., 2001). The plants were exposed to different [CO₂] environments up to 34 days after planting (DAP). Variable-density shade cloths were placed around the edges of the canopy and adjusted regularly to stimulate canopy spectral properties and eliminate the need for border plants.

2.3 Trait measurement

2.3.1 Plant growth

The plant growth and biomass measurements were taken during the final day (34 DAP) of the experiment. The plant height (cm) was measured as the distance between the base of the culm and the collar region of the grasses. For non-grass species, the plant height was measured from the base of the mainstem to the tip of the terminal whorl of developing leaves. Leaf numbers were counted to the collar region on the main stem/culm in sorghum and wheat, while fully opened uppermost mainstem leaves in soybean, cotton, and Amaranthus. Leaf area was determined using an LI-3100 leaf area meter (LI-COR Inc., Lincoln, Nebraska, USA). Cotton and soybean produced squares and flowers, respectively, during the experiment. Therefore, days from emergence to the appearance of the first square, 3 mm in length, were recorded in cotton (Reddy et al., 1997). Similarly, days from emergence to the first flower, defined as the R1 stage, were recorded in soybeans (Fehr and Caviness, 1977). Since wheat is the only crop with meaningful numbers of tillers produced during the experimental period, tiller numbers and tillers with a minimum of one leaf collar per axis were counted in this crop.

2.3.2 Biomass

The harvested plants were then separated into their respective components: leaves, stems, and roots. Each component was oven-dried at 75°C for five days, and its dry weight was recorded. The combined dry weights of leaves and stems were considered as shoot dry weight, while the sum of shoot dry weight and root dry weight constituted the total dry weight of the plant. All the dry weights were expressed in grams per plant. The root-to-shoot ratio was computed by dividing the root dry weight by the shoot dry weight.

2.3.3 Mineral analysis

Five grams of oven-dried leaf samples were used to analyze the leaf macro- and micro-mineral components of the species. The dried leaves were ground using a laboratory mill, and the mineral content was analyzed through standard protocols at the soil testing laboratory of Mississippi State University, Mississippi State, MS, USA. The leaf nitrogen (N) concentration was measured using one gram of leaf tissue with an organic elemental analyzer (Vario MAX cube, Ronkonkoma, NY, USA) through the dry combustion method (McGeehan and Naylor, 1988). The analysis was performed using an ICP spectrophotometer (Spectro Analytical Instruments, Wilmington, MA, USA) for all other micronutrients. This involved ashing 0.5 g of ground leaf tissue in a muffle furnace at 500°C, followed by diluting the ash in hydrochloric acid (HCl) to determine the nutrient concentrations (Donohue and Aho, 1992).

2.4 Data analysis

Data were analyzed using a mixed-effects model with [CO₂] as the fixed main plot factor, and species as the sub-plot factor in R Studio, utilizing the ‘doebioresearch’ package (Popat and Banakara, 2022). To explain plant-specific responses to [CO₂] levels, multiple comparison tests were conducted using a t-test, with significance set at 0.05. The effect of [CO₂] levels within each species was assessed through one-way analysis of variance. Graphical representations of the results and their functional relationships were generated using Sigmaplot 13.0 (Systat Software Inc., San Jose, CA, USA).

2.5 Regression analysis

Linear and quadratic regression analyses (Eqs. (1) and (2)) were employed to correlate various growth and biomass parameters with [CO₂] levels for each species. The regression correlation coefficient (r²) was then monitored to evaluate the model’s fitness:

(1)\mathit{Y}\mathit{=}\mathit{a}\mathit{+}\mathit{b}\mathit{x},

(2){\mathit{Y}\mathit{=}\mathit{a}\mathit{+}\mathit{b}\mathit{x}\mathit{+}\mathit{c}\mathit{x}}^{\mathit{2}},

where Y is the dependent variable (parameters), x is the independent variable ([CO₂]), and a, b, and c are the regression coefficients for the linear and quadratic functions.

2.6 Species response to [CO₂]

The species’ response to [CO₂] on growth, biomass, macronutrient, micronutrient, and root-to-shoot ratio was calculated through the CO₂ response index described by Wijewardana et al. (2016). The average values of parameters were employed to calculate the indices. The individual stress response index (ISRI) was calculated for each species by dividing each value of a parameter recorded under six [CO₂] treatments (P_i) by the maximum value recorded across the treatments (P_m) (Eq. (3)):

(3)ISRI=\frac{P_i}{P_m}.

The sum of the ISRI values for plant height, leaf area, and leaf number for each [CO₂] treatment was calculated and presented as growth, while the sum of the ISRI values for shoot dry weight, root dry weight, and total dry weight was presented as biomass. A bubble graph was plotted for each species using the ggbiplot2 package available in R Studio (Wickham, 2016).

3 Results

The SPAR facility was able to maintain the set [CO₂] of six treatments, obtaining an average value of 374, 431, 525, 620, 721, and 813 ppm across the experimental period (Fig. 1). The slight variation at 320 ppm was due to the lack of CO₂ buffering system under below ambient [CO₂] levels in the SPAR units. The seedling growth, biomass accumulation, and mineral composition of the studied plant functional groups differed (p < 0.05 and p < 0.001) under various [CO₂] environments (Table 2) except magnesium (Mg) content.

3.1 [CO₂] effects on plant growth and biomass

The overall plant growth in cotton, soybean, and wheat increased when grown under elevated [CO₂] (Fig. 2). The increase in plant height of cotton was not significant under higher levels of [CO₂] above 420 ppm (Fig. 3; Supplementary Table S1). However, the maximum plant height of cotton was recorded under 720 ppm, which is 16% higher than the current [CO₂] level of 420 ppm. The plant height of soybean responded positively to an increase in atmospheric [CO₂], reaching up to 40 cm within 34 days after planting under 820 ppm, and the response followed a quadratic function with [CO₂] with the lowest plant height under 320 ppm [CO₂] (Fig. 3; Supplementary Table S2). At the same time, wheat had 22% more plant height when grown under 820 ppm compared to the current [CO₂] of 420 ppm. Wheat also followed a quadratic function, attaining the highest plant height at 620 ppm [CO₂] (10.1 cm) and the least at 420 ppm (7.9 cm). The two C₄ species, Amaranthus and sorghum, attained their maximum plant height at 420 ppm (51.2 cm and 32.6 cm, respectively). However, an increase in atmospheric [CO₂] beyond this level led to a reduction in plant height up to 620 ppm (48 cm and 32 cm, respectively), while further increases were observed at 720 ppm. The plant height of Amaranthus and sorghum followed a weak linear relationship with atmospheric [CO₂] with r² values of 0.31 and 0.19, respectively (Supplementary Table S2).

Soybean produced 13% and 17% more leaves under 720 ppm and 820 ppm atmospheric [CO₂] levels compared to 420 ppm. In contrast, cotton plants only produced more leaves at 720 ppm (7.67 leaves plant⁻¹) compared to 320 ppm and 520 ppm (6.83 leaves plant⁻¹) [CO₂] levels (Fig. 4(a); Supplementary Table S1). Wheat did not respond significantly to the growing atmospheric [CO₂] with respect to the number of leaves. The lowest number of leaves in Amaranthus and sorghum was recorded at 320 ppm (10.5 leaves plant⁻¹) and 420 ppm (6.2 leaves plant⁻¹), respectively. Conversely, a higher number of leaves was observed at 820 ppm (13.2 leaves plant⁻¹) and 520 ppm (7 leaves plant⁻¹), respectively. The number of leaves in C₃ and C₄ species followed a linear relationship with [CO₂] (Supplementary Table S2).

The leaf area of cotton increased with an increase in [CO₂], reaching 30% more area under 720 ppm compared to 420 ppm (Fig. 4(b); Supplementary Table S1). Similarly, the leaf area of other C₃ species, soybean, and wheat, increased when exposed to higher [CO₂] levels, attaining 51% more leaf area under 720 ppm and 45% more leaf area under 620 ppm, respectively, compared to 420 ppm. Notably, wheat produced the maximum number of tillers per plant under 620 ppm [CO₂] (16.6 tillers plant⁻¹) and the least under 320 ppm (11.6 tillers plant⁻¹) (Supplementary Table S3). The leaf area of Amaranthus and sorghum was not significantly affected by atmospheric [CO₂] levels. The leaf area of C₃ species exhibited a strong quadratic relationship with [CO₂] (Supplementary Table S2).

The shoot dry weight of cotton increased with elevation in [CO₂] levels in the growing environment, resulting in a gain of 21% dry weight under 820 ppm compared to 420 ppm (Fig. 5(a); Supplementary Table S1). Similarly, the shoot dry weight of soybean increased from 9.6 g·plant⁻¹ under 420 ppm to 13.6 g·plant⁻¹ under 820 ppm. Meanwhile, the shoot weight of wheat did not significantly respond to different atmospheric [CO₂] during the early seedling stage. The maximum shoot dry weight of Amaranthus and sorghum was recorded in plants grown under current [CO₂] of 420 ppm (13 and 17.7 g·plant⁻¹) and further increases in [CO₂] had no significant impact. However, there was a numerical decrease in the shoot biomass of either crop. The shoot dry weight of C₃ species followed a strong linear relationship, while the C₄ species had a weak linear relationship with [CO₂] (Supplementary Table S2)

The root dry weight of cotton increased (p < 0.001) when grown under elevated [CO₂], resulting in 144% more accumulation of root dry matter under 820 ppm compared to 420 ppm (Fig. 5(b); Supplementary Table S1). In contrast, the root dry weights of other species of the C₃ or C₄ functional groups were not potentially influenced by [CO₂] levels in the atmosphere. The lowest root dry weight of soybean was recorded at 620 ppm (1.5 g·plant⁻¹), while the highest was recorded at 520 ppm (2.4 g·plant⁻¹). The root dry weight of wheat significantly increased under [CO₂] above the current level of 420 ppm, reaching 300% more dry weight under 520 ppm. A further increase in [CO₂] did not contribute to a gain in root dry weight. Amaranthus did not respond significantly to an increase in atmospheric [CO₂] levels in terms of root dry weight. Meanwhile, sorghum reduced its root dry weight by 40% when exposed to [CO₂] above 520 ppm compared to 420 ppm, and it followed a linear relationship with a negative slope (Supplementary Table S2).

The total plant dry weight of cotton increased with an increase in [CO₂], attaining 26% more biomass at 720 ppm compared to the current [CO₂] (Fig. 6(a); Supplementary Table S1). Similarly, soybeans responded positively to increasing [CO₂], gaining 44% more biomass at 720 ppm [CO₂] than at 420 ppm. Notably, a further increase in [CO₂] above 720 ppm did not result in any gain in biomass accumulation for cotton and soybean. On the other hand, the response of C₃ monocot species to growing [CO₂] levels was not significant. A similar response was recorded for Amaranthus. The highest biomass accumulation in sorghum was recorded at a current [CO₂] of 420 ppm (23.9 g·plant⁻¹). The C₄ species exhibited a weak linear relationship with [CO₂], whereas the C₃ species showed a strong quadratic relationship (Supplementary Table S2).

The maximum root-to-shoot ratio of cotton was observed at 320 ppm (0.15), which was further reduced with increasing [CO₂] (Fig. 6(b); Supplementary Table S1). Meanwhile, the root-to-shoot ratio of soybeans was not affected by increasing [CO₂]. On the other hand, the root-to-shoot ratio of wheat significantly increased when the plant grew above current levels of [CO₂]_, reaching a 300% higher root-to-shoot ratio under 520 ppm than 420 ppm. On the other hand, the root-to-shoot ratio in C₄ species remained unchanged due to the atmospheric [CO₂] levels. All the species followed a less linear relationship with atmospheric [CO₂] (Supplementary Table S2).

3.2 [CO₂] effects on leaf mineral composition

The macronutrient content of Amaranthus varied significantly with [CO₂] (p < 0.01) (Table 3). The leaf N content decreased by 3% at 720 ppm and 2% at 820 ppm compared to 420 ppm. Phosphorus (P) content was highest at 520 ppm and 620 ppm (0.54%) and lowest at 720 ppm (0.46%), with statistically comparable amounts at 420 ppm and 820 ppm. Sulfur (S) content was highest at 320 ppm and 520 ppm (0.23%), whereas 720 ppm, 420 ppm, and 620 ppm (0.19%) had the lowest amounts. The cotton plants exposed to 620 ppm and 720 ppm of [CO₂] had reduced concentrations of leaf N (7% and 11%), Ca (14% and 17%), and S (28%) compared to 520 ppm. At the same time, the leaf P and K content in cotton decreased under [CO₂] above 320 ppm. In sorghum, the leaf N content was highest at 720 ppm and 820 ppm (3.62%), and lowest at 420 ppm and 620 ppm (3.42%), while Ca was lowest under the current atmospheric [CO₂] (0.37%), and highest at 720 ppm (0.41%). K and P were lowest at 320 ppm (3.68%) and 420 ppm (0.39%), respectively, and highest at 720 ppm (4.54% K and 0.52% P). Soybean showed a 31% reduction in P and a 22% reduction in S at 820 ppm compared to 320 ppm. Ca and N contents decreased by 10% and 16%, respectively, at 720 ppm compared to 420 ppm. Wheat P decreased when grown under elevated [CO₂] beyond 420 ppm, reaching 0.76% at 820 ppm, while K remained unchanged. The N and S content decreased by 4% and 9%, respectively, at 520 ppm compared to 420 ppm.

Among the micronutrients (Table 4), Amaranthus Zn content increased by 85% under 820 ppm compared to 420 ppm, while Mn and B values fluctuated under varying [CO₂]. Cotton exhibited inconsistent changes in Cu and Mn. Fe content was highest at 320 ppm (138.6 ppm) and declined with an increase in [CO₂]. Sorghum Fe and B contents were highest under 320 ppm (101.38 ppm and 26.66 ppm, respectively) and then decreased with an increase in [CO₂]. In soybean, Mn, Fe, and B contents declined with an increase in [CO₂], by 23%, 39%, and 22%, respectively, under 820 ppm compared to 320 ppm. Zn content exhibited an inconsistent response to increases in [CO₂]. Similarly, Cu content of wheat also showed fluctuating values under different [CO₂] levels. The other micronutrients, such as Mn, Fe, and B, decreased by 37%, 16%, and 17% under 820 ppm compared to 420 ppm.

3.3 CO₂ response index

The species responded differently to the atmospheric [CO₂] concentration during the early seedling stage (Fig. 7). The overall CO₂ response index of plant growth and biomass of cotton (Fig. 7(b)), soybean (Fig. 7(d)), and wheat (Fig. 7(e)) increased with an increase in atmospheric [CO₂]. In contrast, the highest root-to-shoot ratio response index was observed under 520 ppm, except for cotton. The micro- and macronutrient index of leaves exhibited a decreasing trend under elevated [CO₂] conditions in C₃ species. On the other hand, the maximum growth and biomass response index of C₄ species was observed under the current [CO₂]. The macronutrient response index of Amaranthus (Fig. 7(a)) and sorghum (Fig. 7(c)) was not affected by the atmospheric [CO₂], while these nutrient indices decreased with an increase in [CO₂] levels in C₃ species. A similar trend was observed for the micronutrient indices in C₃ species.

4 Discussion

Amid the increased prediction on atmospheric [CO₂] and the rising CO₂ emission sources, the associated consequences on global agriculture, specifically in terms of plant growth, nutrient quality, and food security, remain insufficiently studied and understood. This is the first attempt to study the response of multiple plant functional groups to past, present, and future [CO₂] under constant water, temperature, and nutrient concentrations.

Plant growth and productivity are associated with the amount of light intercepted by the canopy and are determined by plant height and leaf area (Ewert, 2004). Under elevated [CO₂], C₃ species exhibit a positive growth response, producing taller plants due to enhanced photosynthesis. We did not measure photosynthesis in the present study, however, the established literature on the effect of elevated [CO₂] conditions on plants shows a positive response in photosynthesis, mainly in C₃ plants (Wang and Wang, 2021; Gojon et al., 2023; Opoku et al., 2024). The increase in photosynthesis is attributed to the increase in ribulose-1,5-bisphosphate (RuBP) carboxylase/oxygenase (Rubisco) activity under elevated [CO₂], which drives the accumulation of non-structural carbohydrates leading to increased starch reserves and auxin biosynthesis (Thompson et al., 2017). This results in apical growth, ultimately leading to increased plant growth. However, the C₄ monocot and dicot species did not exhibit a positive response to elevated [CO₂]. As widely discussed, the structural and functional specialty of the C₄ photosynthetic system contributes to the lower response of these species to elevated [CO₂]. C₄ plants are suggested to already have very high levels of [CO₂] in their bundle sheath cells (2100 µmol·L⁻¹; 10 times more than the [CO₂] in mesophyll cells of C₃ plants) at the present atmospheric [CO₂] (Jenkins et al., 1989; Reddy et al., 2010). The study also revealed that elevated [CO₂] increased internodal length in cotton and wheat, as observed by increasing plant height without increasing the number of nodes. In addition, significant increases in the leaf area were observed in cotton, soybean, and wheat under an elevated [CO₂] environment, likely due to enhanced cell production or expansion under these conditions (Gray and Brady, 2016). This expansion in leaf area increases the surface area for potential light interception, leading to greater carbon assimilation. Consequently, the C₃ crops, cotton and soybean, produced more shoot and total dry weights at higher [CO₂] levels. These results are congruent with the theory that C₃ plants will benefit more under higher [CO₂] levels than C₄ plants. However, C₄ plants may outperform C₃ plants under elevated [CO₂] when additional factors such as high temperature and adequate water availability are present (Opoku et al., 2024; Tian et al., 2024). In our study, by maintaining an optimal temperature and a sufficient water supply, we isolated the effect of elevated CO₂, which aligns with previous studies. Consistent with previous studies, C₃ plants have been shown to respond to higher [CO₂] levels with increased photosynthesis rates (Reddy et al., 1998; Kimball et al., 2002; Aranjuelo et al., 2009; Atwell et al., 2009; Yoon et al., 2009). It is interesting to note that despite the boost in plant growth under elevated [CO₂], no significant changes were observed in key phenological traits, such as days to flowering in soybean and days to squaring in cotton (Supplementary Table S3).

Root growth and development are crucial to plant health, particularly in terms of water and nutrient acquisition during early seedling development (Wang et al., 2016). In the present study, the root weight of all crops except cotton (69% increase from 320 to 820 ppm [CO₂]) was not significantly affected by increased [CO₂] levels. Although past studies often reported increases in root weight under elevated [CO₂], some studies have documented no response of elevated [CO₂] on root weight, or there was a negative response (Bernacchi et al., 2000; Obrist and Arnone III, 2003; Ferguson and Nowak, 2011; Agathokleous et al., 2016). The observed lack of significant changes in root biomass for these functional groups can be attributed to an increased allocation of plant energy to above-ground parts due to intense photosynthetic activity under elevated [CO₂]. This was further reflected in the root-to-shoot ratio, which remained unaffected in all crops except cotton, where it decreased under higher [CO₂] conditions. It is suggested that increases in root-to-shoot ratio are typically observed when the water and nutrients are limited (Bazzaz, 1990; Stulen and den Hertog, 1993; Rogers et al., 1995; Madhu and Hatfield, 2013; Lopez et al., 2023; Seidel et al., 2024). This can be a possible explanation for the results observed in the current study, as the plants were well-watered and received nutrients through Hoagland’s solution with each irrigation. Therefore, the plants did not allocate biomass to the roots, as water and nutrients were not limiting. Similar findings have been reported in other studies. For instance, Bernacchi et al. (2000) reported that the root-to-shoot ratio of three C₃ plant species (Abutilon theophrasti, Chenopodium album, and Polygonum pensylvanicum) and a C₄ plant (Amaranthus retroflexus) reduced or remained unchanged under elevated [CO₂]. Agathokleous et al. (2016) also found no significant differences in total root production and biomass allocation toward roots in birch (Betula sp.) and oak (Quercus sp.) saplings under ambient (375‒395 µmol·mol⁻¹) and elevated (500 µmol·mol⁻¹) [CO₂] conditions. Additionally, studies on species such as Larrea tridentate (Obrist and Arnone III, 2003), tall grasses (Mo et al., 1992), four of the six native chalk grassland herbs (Ferris and Taylor, 1993), and winter wheat (Chaudhuri et al., 1990) reported similar outcomes. Similarly, McGuire et al. (1995) and Wullschleger et al. (1995) also did not observe significant effects of elevated [CO₂] on biomass allocation between roots and shoots.

Besides the effect of [CO₂] on biomass accumulation, elevated [CO₂] significantly influences the concentration of micro- and macro-nutrients in plants. Apparently, the response is not uniform across plants, and it is influenced by the plant’s functional group, organ, and [CO₂] (Seibert et al., 2022; Gojon et al., 2023). The study on five different functional groups revealed that the concentration of the majority of the nutrients reduced under elevated [CO₂] environments. Only Zn in Amaranthus and Cu in wheat increased with an increase in [CO₂]. The reduction in plant mineral content under elevated [CO₂] has been primarily attributed to the dilution effect which suggests that increased carbohydrate production and biomass accumulation under elevated [CO₂] surpass the uptake and assimilation of mineral nutrients, resulting in lower nutrient concentrations per unit dry weight (Loladze, 2014; Mndela et al., 2022). Additionally, restricted transpiration due to reduced stomatal conductance limits the mass flow of nutrient from the soil to the root surface, primarily affecting the uptake of nutrients such as Ca and Mg, which are primarily transported via the transpiration stream (McDonald et al., 2002; Sharmin et al., 2021). Moreover, root system architecture and activity may also be negatively impacted by elevated [CO₂]. Reduced root growth under elevated [CO₂] reduces the active root surface area available for nutrient uptake. Furthermore, plants also interact with their soil environment through root exudates, which play a crucial role in regulating nutrient availability. Elevated [CO₂] can stimulate the release of root exudates, leading to rhizosphere acidification and the selective uptake of specific nutrients, potentially affecting the solubility and availability of nutrients such as phosphorus and micronutrients (Nichols et al., 2002; Jin et al., 2015; Jin et al., 2022). These root-soil interactions can cause selective increases or decreases in the uptake of specific nutrients, adding another layer of complexity to the nutrient dynamics under future CO₂ scenarios.

The CO₂ response index was employed to obtain the species-specific responses to elevated [CO₂] in terms of growth, biomass, macro- and micronutrients, and root-to-shoot ratio. The species responded differently to increases in atmospheric [CO₂], particularly between C₃ and C₄ plants. Amaranthus and sorghum (C₄ plants) exhibited inconsistent trends in response to elevated [CO₂], whereas cotton and soybean showed increases in growth and biomass. There was also a positive increase in wheat biomass. These results support our hypothesis that C₃ plants will continue to respond positively to an increase in [CO₂].

5 Conclusions

The [CO₂] in the atmosphere has been rapidly rising, which may affect plant growth and development. This study quantified C₃ and C₄ species’ responses to a wide range of atmospheric [CO₂] under optimum temperature, water, and nutrient conditions during the early season. We observed significant increases in total dry weight due to increased leaf area in C₃ plant species, mainly cotton and soybean. In contrast, the C₄ plants (Sorghum and Amaranthus) did not respond significantly to increase atmospheric [CO₂]. Root dry weight and root-to-shoot ratio were not significantly affected under increased [CO₂] in any of the crops except cotton, which can be attributed to the ample supply of water and nutrients. The CO₂ response index showed a positive response only by C₃ plants to higher [CO₂]. In contrast, C₄ plants did not exhibit any response, indicating the presence of a CO₂-concentrating mechanism in the leaves of these plants. The quantitative information of various functional groups of plants in response to a wide range of [CO₂] enables us to predict precise responses to changing [CO₂] levels in the coming decades. Additionally, the study revealed a decline in the concentration of macro- and micro-nutrients, indicating that higher [CO₂] levels may require an increase in the quantity of food intake to meet the same nutritional needs of animals, insects and humans. The results from this study assist in further understanding plant response to elevated [CO₂] and emphasize the need for further research with the consideration of additional environmental variables and more than one representative species for different functional groups.

References

[1] Agathokleous E, Watanabe M, Nakaji T, Wang X, Satoh F, Koike T (2016). Impact of elevated CO₂ on root traits of a sapling community of three birches and an oak: a free-air-CO₂ enrichment (FACE) in northern Japan.Trees (Berl), 30(2): 353–362

[2] Ainsworth E A, Long S P (2005). What have we learned from 15 years of free-air CO₂ enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO₂.New Phytol, 165(2): 351–372

[3] Ainsworth E A, Long S P (2021). 30 years of free-air carbon dioxide enrichment (FACE): what have we learned about future crop productivity and its potential for adaptation.Glob Change Biol, 27(1): 27–49

[4] Aranjuelo I, Irigoyen J J, Nogués S, Sánchez-Díaz M (2009). Elevated CO₂ and water-availability effect on gas exchange and nodule development in N₂-fixing alfalfa plants.Environ Exp Bot, 65(1): 18–26

[5] Atwell B J, Henery M L, Ball M C (2009). Does soil nitrogen influence growth, water transport and survival of snow gum (Eucalyptus pauciflora Sieber ex Sprengel. ) under CO₂ enrichment.Plant Cell Environ, 32(5): 553–566

[6] Barbehenn R V, Chen Z, Karowe D N, Spickard A (2004). C₃ grasses have higher nutritional quality than C₄ grasses under ambient and elevated atmospheric CO₂.Glob Change Biol, 10(9): 1565–1575

[7] Bazzaz F A (1990). The response of natural ecosystems to the rising global CO₂ levels.Annu Rev Ecol Syst, 21(1): 167–196

[8] Bernacchi C J, Coleman J S, Bazzaz F A, McConnaughay K D M (2000). Biomass allocation in old-field annual species grown in elevated CO₂ environments: no evidence for optimal partitioning.Glob Change Biol, 6(7): 855–863

[9] Buis A (2019). Sizing up humanity’s impacts on Earth’s changing atmosphere: a five-part series. The atmosphere: Getting a handle on carbon dioxide. Climate change: Vital signs of the planet. NASA’s Jet Propulsion Laboratory

[10] Chaudhuri U N, Kirkham M B, Kanemasu E T (1990). Root growth of winter wheat under elevated carbon dioxide and drought.Crop Sci, 30(4): 853–857

[11] Cui B, Liu J, Zhang M, Wan H, Wei G, Wei Z, Liu F (2024). CO₂ elevation modulates the growth and physiological responses of soybean (Glycine max L. Merr. ) to progressive soil drying.Plant Growth Regul, 103(1): 139–150

[12] Donohue S J, Aho D W (1992). Determination of P, K, Ca, Mg, Mn, Fe, Al, B, Cu, and Zn in plant tissue by inductively coupled plasma (ICP) emission spectroscopy. In: Plank C O, ed. Plant Analysis Reference Procedures for the Southern Region of the United States. Southern Cooperative Series Bulletin 368. Georgia Agricultural Experimental Station: Athens, GA, USA, pp. 37–40

[13] Ehleringer J R, Cerling T E, Helliker B R (1997). C₄ photosynthesis, atmospheric CO₂, and climate.Oecologia, 112(3): 285–299

[14] Ewert F (2004). Modeling plant responses to elevated CO₂: how vital is leaf area index.Ann Bot (Lond), 93(6): 619–627

[15] Fehr W R, Caviness C E (1977). Stages of soybean development. Spec. Rep. 80, Iowa Agric. Home Econ. Exp. Stn., Iowa State Univ., Ames, IA

[16] Ferguson S D, Nowak R S (2011). Transitory effects of elevated atmospheric CO₂ on fine root dynamics in an arid ecosystem do not increase long-term soil carbon input from fine root litter.New Phytol, 190(4): 953–967

[17] Ferris R, Taylor G (1993). Contrasting effects of elevated CO₂ on the root and shoot growth of four native herbs commonly found in chalk grassland.New Phytol, 125(4): 855–866

[18] Gojon A, Cassan O, Bach L, Lejay L, Martin A (2023). The decline of plant mineral nutrition under rising CO₂: physiological and molecular aspects of a bad deal.Trends Plant Sci, 28(2): 185–198

[19] Gowik U, Westhoff P (2011). The path from C₃ to C₄ photosynthesis.Plant Physiol, 155(1): 56–63

[20] Gray S B, Brady S M (2016). Plant developmental responses to climate change.Dev Biol, 419(1): 64–77

[21] Hatch M D (1987). C₄ photosynthesis: a unique elend of modified biochemistry, anatomy and ultrastructure.Biochimica et Biophysica Acta, 895(2): 81–106

[22] Hewitt E J (1953). Sand and water culture methods used in the study of plant nutrition.Soil Science Society of America Journal, 17(3): 301

[23] Houshmandfar A, Fitzgerald G J, O’Leary G, Tausz-Posch S, Fletcher A, Tausz M (2018). The relationship between transpiration and nutrient uptake in wheat changes under elevated atmospheric CO₂.Physiol Plant, 163(4): 516–529

[24] Hu S, Chen W, Tong K, Wang Y, Jing L, Wang Y, Yang L (2022). Response of rice growth and leaf physiology to elevated CO₂ concentrations: a meta-analysis of 20-year FACE studies.Sci Total Environ, 807: 151017

[25] IPCC (2023). Summary for Policymakers. In: Climate Change 2023: Synthesis report. Contribution of working groups I, II and III to the sixth assessment report of the Intergovernmental Panel on Climate Change [Core Writing Team, H. Lee and J. Romero (eds.)]. IPCC, Geneva, Switzerland, 1–34

[26] Jenkins C L, Furbank R T, Hatch M D (1989). Mechanism of C₄ photosynthesis: a model describing the inorganic carbon pool in bundle sheath cells.Plant Physiol, 91(4): 1372–1381

[27] Jin J, Krohn C, Franks A E, Wang X, Wood J L, Petrovski S, McCaskill M, Batinovic S, Xie Z, Tang C (2022). Elevated atmospheric CO₂ alters the microbial community composition and metabolic potential to mineralize organic phosphorus in the rhizosphere of wheat.Microbiome, 10(1): 12

[28] Jin J, Tang C, Sale P (2015). The impact of elevated carbon dioxide on the phosphorus nutrition of plants: a review.Ann Bot (Lond), 116(6): 987–999

[29] Kellogg E A (2015). Flowering plants. Monocots: Poaceae (Vol. 13). Springer

[30] Khan I, Vanaja M, Sathish P, Faizan M, Soysal S, Rajput V, Djalovic I, Trivan G, Alam P (2024). Response of maize (Zea mays L. ) on yield, physiology and stomatal behaviour under two different elevated CO₂ concentrations. Do these anatomical changes affect the physiology of the C₄ crop plant under high CO₂ conditions.Plant Soil Environ, 70(10): 601–616

[31] Kimball B A, Kobayashi K, Bindi M (2002). Responses of agricultural crops to free-air CO₂ enrichment.Adv Agron, 77: 293–368

[32] Lee T D, Tjoelker M G, Reich P B, Russelle M P (2003). Contrasting growth response of an N₂-fixing and non-fixing forb to elevated CO₂: dependence on soil N supply.Plant Soil, 255(2): 475–486

[33] Loladze I (2014). Hidden shift of the ionome of plants exposed to elevated CO₂ depletes minerals at the base of human nutrition.eLife, 3: e02245

[34] Lopez G, Ahmadi S H, Amelung W, Athmann M, Ewert F, Gaiser T, Gocke M I, Kautz T, Postma J, Rachmilevitch S, Schaaf G, Schnepf A, Stoschus A, Watt M, Yu P, Seidel S J (2023). Nutrient deficiency effects on root architecture and root-to-shoot ratio in arable crops.Front Plant Sci, 13: 1067498

[35] Madhu M, Hatfield J L (2013). Dynamics of plant root growth under increased atmospheric carbon dioxide.Agron J, 105(3): 657–669

[36] McDonald E P, Erickson J E, Kruger E L (2002). Can decreased transpiration limit plant nitrogen acquisition in elevated CO₂.Funct Plant Biol, 29(9): 1115–1120

[37] McGeehan S L, Naylor D V (1988). Automated instrumental analysis of carbon and nitrogen in plant and soil samples.Commun Soil Sci Plant Anal, 19(4): 493–505

[38] McGrath J M, Lobell D B (2013). Reduction of transpiration and altered nutrient allocation contribute to nutrient decline of crops grown in elevated CO₂ concentrations.Plant Cell Environ, 36(3): 697–705

[39] McGuire A D, Melillo J M, Joyce L A (1995). The role of nitrogen in the response of forest net primary production to elevated atmospheric carbon dioxide.Annu Rev Ecol Syst, 26(1): 473–503

[40] Mndela M, Tjelele J T, Madakadze I C, Mangwane M, Samuels I M, Muller F, Pule H T (2022). A global meta-analysis of woody plant responses to elevated CO₂: implications on biomass, growth, leaf N content, photosynthesis and water relations.Ecol Process, 11(1): 52

[41] Mo G, Nie D, Kirkham M B, He H, Ballou L K, Caldwell F W, Kanemasu E T (1992). Root and shoot weight in a tallgrass prairie under elevated carbon dioxide.Environ Exp Bot, 32(3): 193–201

[42] Nichols M A, Woolley D J, Christie C B (2002). Effect of oxygen and carbon dioxide concentration in the root zone on the growth of vegetables. In: International Symposium on Design and Environmental Control of Tropical and Subtropical Greenhouses 578, 119–122

[43] NOAA Research (2020). Rise of carbon dioxide unabated. National Oceanic and Atmosphere Administration. Accessed Nov 21, 2024

[44] Obrist D, Arnone III J A (2003). Increasing CO₂ accelerates root growth and enhances water acquisition during early stages of development in Larrea tridentata.New Phytol, 159(1): 175–184

[45] Opoku E, Sahu P P, Findurová H, Holub P, Urban O, Klem K (2024). Differential physiological and production responses of C₃ and C₄ crops to climate factor interactions.Front Plant Sci, 15: 1345462

[46] Poorter H (1993). Interspecific variation in the growth response of plants to an elevated ambient CO2 concentration. In: Rozema J, Lambers H, Geijn S C, Cambridge M L, eds. CO2 and Biosphere. Springer, 77–98

[47] Poorter H, Navas M L (2003). Plant growth and competition at elevated CO₂: on winners, losers and functional groups.New Phytol, 157(2): 175–198

[48] Popat R, Banakara K (2022). Package ‘Doebioresearch.’” 2022. https://cran.r-project.org/web/packages/doebioresearch/doebioresearch.pdf.

[49] Rakhmankulova Z F, Shuyskaya E V, Prokofieva M Y, Saidova L T, Voronin P Y (2023). Effect of elevated CO₂ and temperature on plants with different type of photosynthesis: Quinoa (C₃) and Amaranth (C₄).Russ J Plant Physiol, 70(6): 117

[50] Raunkiaer C (1934). The Life Forms of Plants and Statistical Plant Geography. London: Clarendron Press doi:10.2307/1786954

[51] Reddy A R, Rasineni G K, Raghavendra A S (2010). The impact of global elevated CO₂ concentration on photosynthesis and plant productivity. CurrSci, 99: 46–57 Available at: https://www.jstor.org/stable/24108349

[52] Reddy A R, Reddy K R, Hodges H F (1998). Interactive effects of elevated carbon dioxide and growth temperature on photosynthesis in cotton leaves.Plant Growth Regul, 26(1): 33–40

[53] Reddy K R, Hodges H F, Read J J, McKinion J M, Baker J T, Tarpley L, Reddy V R (2001). Soil-Plant-Atmosphere-Research (SPAR) facility: a tool for plant research and modeling. Biotronics, 30: 27–50. Available at: http://133.5.207.201/index.html

[54] Reddy K R, Hodges H F, McKinion J M (1997). Crop modeling and applications: a cotton example.Adv Agron, 59: 225–290

[55] Reich P B, Hobbie S E, Lee T D, Pastore M A (2018). Unexpected reversal of C₃ versus C₄ grass response to elevated CO₂ during a 20-year field experiment.Science, 360(6386): 317–320

[56] Reich P B, Tilman D, Craine J, Ellsworth D, Tjoelker M G, Knops J, Wedin D, Naeem S, Bahauddin D, Goth J, Bengtson W, Lee T D (2001). Do species and functional groups differ in acquisition and use of C, N and water under varying atmospheric CO₂ and N availability regimes? A field test with 16 grassland species.New Phytol, 150(2): 435–448

[57] Rogers H H, Prior S A, Runion G B, Mitchell R J (1995). Root to shoot ratio of crops as influenced by CO₂.Plant Soil, 187(2): 229–248

[58] Sage R F (2004). The evolution of C₄ photosynthesis.New Phytol, 161(2): 341–370

[59] Salesse-Smith C E, Adar N, Kannan B, Nguyen T, Wei W, Guo M, Ge Z, Altpeter F, Clemente T E, Long S P (2025). Adapting C₄ photosynthesis to atmospheric change and increasing productivity by elevating Rubisco content in sorghum and sugarcane.Proc Natl Acad Sci USA, 122(8): e2419943122

[60] Seibert R, Andresen L C, Jarosch K A, Moser G, Kammann C I, Yuan N, Luterbacher J, Laughlin R J, Watson C J, Erbs M, Müller C (2022). Plant functional types differ in their long-term nutrient response to eCO₂ in an extensive grassland.Ecosystems (N Y), 25(5): 1084–1095

[61] Seidel S J, Ahmadi S H, Weihermüller L, Couëdel A, Lopez G, Behrend D, Kamali B, Gaiser T, Hernández-Ochoa I M (2024). The overlooked effects of environmental impacts on root: shoot ratio in experiments and soil-crop models.Sci Total Environ, 955: 176738

[62] Serraj R A C H I D, Sinclair T R, Allen L H (1998). Soybean nodulation and N₂ fixation response to drought under carbon dioxide enrichment.Plant Cell Environ, 21(5): 491–500

[63] Sharmin S, Lipka U, Polle A, Eckert C (2021). The influence of transpiration on foliar accumulation of salt and nutrients under salinity in poplar (Populus × canescens).PLoS One, 16(6): e0253228

[64] Stulen I, den Hertog J (1993). Root growth and functioning under atmospheric CO₂ enrichment.Vegetatio, 104(1): 99–115

[65] Taiz L, Zeiger E, Moller I M, Murphy A (2014). Plant physiology and Development. Sunderland, MA: Sinauer Associates

[66] Taylor S H, Ripley B S, Martin T, De-Wet L A, Woodward F I, Osborne C P (2014). Physiological advantages of C₄ grasses in the field: a comparative experiment demonstrating the importance of drought.Glob Change Biol, 20(6): 1992–2003

[67] Thompson M, Gamage D, Hirotsu N, Martin A, Seneweera S (2017). Effects of elevated carbon dioxide on photosynthesis and carbon partitioning: a perspective on root sugar sensing and hormonal crosstalk.Front Physiol, 8: 578

[68] Tian W, Su C, Zhang N, Zhao Y, Tang L (2024). Simulation of the physiological and photosynthetic characteristics of C₃ and C₄ plants under elevated temperature and CO₂ concentration.Ecol Modell, 495: 110805

[69] Von Caemmerer S (2021). Updating the steady-state model of C₄ photosynthesis.J Exp Bot, 72(17): 6003–6017

[70] Walker B J, VanLoocke A, Bernacchi C J, Ort D R (2016). The costs of photorespiration to food production now and in the future.Annu Rev Plant Biol, 67(1): 107–129

[71] Wand S J E, Midgley G F, Jones M H, Curtis P S (1999). Responses of wild C₄ and C₃ grass (Poaceae) species to elevated atmospheric CO₂ concentration: a meta-analytic test of current theories and perceptions.Glob Change Biol, 5(6): 723–741

[72] Wang Y, Liu S, Shi H (2023). Comparison of climate change impacts on the growth of C₃ and C₄ crops in China.Ecol Inform, 74: 101968

[73] Wang Y, Thorup-Kristensen K, Jensen L S, Magid J (2016). Vigorous root growth is a better indicator of early nutrient uptake than root hair traits in spring wheat grown under low fertility.Front Plant Sci, 7: 865

[74] Wang Z, Wang C (2021). Responses of tree leaf gas exchange to elevated CO₂ combined with changes in temperature and water availability: a global synthesis.Global Ecology and Biogeography, 30(12): 2500–2512

[75] Wickham H (2016). Ggplot2: Elegant Graphics for Data Analysis. Springer

[76] Wijewardana C, Henry W B, Hock M W, Reddy K R (2016). Growth and physiological trait variation among corn hybrids for cold tolerance.Can J Plant Sci, 96(4): 639–656

[77] Wullschleger S D, Post W M, King A W (1995). On the potential for a CO2 fertilization effect in forest trees: estimates of the biotic growth factor based on 58 controlled-exposure studies. In: Woodwell G M, Mackenzie F T, eds. Biotic Feedbacks in the Global Climatic System: Will the Warming Feed the Warming? New York, NY, Online edn. Oxford Academic, 85–107

[78] Yoon S T, Hoogenboom G, Flitcroft I, Bannayan M (2009). Growth and development of cotton (Gossypium hirsutum L. ) in response to CO₂ enrichment under two different temperature regimes.Environ Exp Bot, 67(1): 178–187

[79] Zhao D, Reddy K R, Kakani V G, Read J J, Sullivan J H (2003). Growth and physiological responses of cotton (Gossypium hirsutum L. ) to elevated carbon dioxide and ultraviolet-B radiation under controlled environmental conditions.Plant Cell Environ, 26(5): 771–782

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