- Top of page
- Materials and Methods
- Supporting Information
The atmospheric CO2 concentration has been lower than the current level for the past 650 000 yr. Currently, it is c. 380 µmol mol−1 and is predicted to reach 700 µmol mol−1 by the end of this century [Intergovernmental Panel on Climate Change (IPCC), 2007]. As CO2 is a substrate for photosynthesis, the increase in CO2 concentration generally enhances the photosynthesis and growth rates of plants. Many researchers have conducted elevated CO2 experiments using ‘current plants’ to simulate plant growth in the future environment. The prediction based on these data is valid if ‘future plants’ respond to elevated CO2 in the same manner as current plants. However, it has been repeatedly discussed that atmospheric CO2 concentration is likely to act as a selective agent (e.g. Woodward et al., 1991; Thomas & Jasienski, 1996; Ward et al., 2000; Kohut, 2003; Ward & Kelly, 2004; Lau et al., 2007). The extent to which plant carbon assimilation is enhanced by elevated CO2 is significantly different both within and between species (Wulff & Alexander, 1985; Poorter, 1993; Thomas & Jasienski, 1996; Ward & Strain, 1997; Klus et al., 2001; Körner et al., 2005). Different growth enhancements influence competition and fitness between individuals and, consequently, cause evolutionary shifts in populations (Farnsworth & Bazzaz, 1995; Thomas & Jasienski, 1996). Such evolutionary responses have been found in selection experiments with short-lived organisms, such as Arabidopsis thaliana (e.g. development rate and biomass production; Ward et al., 2000) and Chlamydomonas reinhardtii (e.g. photosynthesis and cell size; Collins & Bell, 2004). However, the evolutionary response of wild plants (especially long-lived plants) is, in general, difficult to evaluate using growth experiments, because of the fundamental discrepancies between the time scales of experiments and the time scales relevant in an evolutionary context (Fordham et al., 1997).
Genetic differentiation in plant communities occurs across natural environmental gradients, such as light, water, temperature, nutrients and heavy metals (Linhart & Grant, 1996). Such differentiation can be found even on a small scale (a few metres), although gene flow between plant communities somewhat counteracts genetic differentiation (Linhart & Grant, 1996; Kelly et al., 2003; Jump & Peñuelas, 2005). By the same token, plant communities around natural CO2 springs provide us with a unique opportunity to explore the micro-evolutionary response of wild plants to elevated CO2 (e.g. Miglietta & Raschi, 1993; Körner & Miglietta, 1994; Raschi et al., 1997; Kohut, 2003). At these sites, plant communities have been exposed to a CO2-enriched atmosphere over many generations (e.g. Miglietta & Raschi, 1993; Onoda et al., 2007); therefore, some genotypes that have a higher fitness at elevated CO2 could have been selected around natural CO2 springs (Cook et al., 1998). Several studies have found genotypic differences in plants from CO2 springs: for example, plants originating from high-CO2 areas show a lower sugar accumulation (Schulte et al., 2002), higher relative growth rate (Fordham et al., 1997), higher shoot/root ratio (Polle et al., 2001) and a large number of small-sized seeds (Andalo et al., 1999). These results suggest that some variation in traits can be selected under CO2 enrichment. However, each of these studies used a single CO2 spring, and therefore it is not clear whether such differences represent general trends for CO2 adaptation. Furthermore, there have been few studies on photosynthetic traits, which have potentially large influences on whole plant growth and fitness. As photosynthesis and growth are limited by resource availability, the efficient use of resources is important for higher growth and survival in the natural environment. This study therefore employs three CO2 springs and focuses on photosynthetic traits, particularly with respect to nitrogen use, water use and starch accumulation.
The photosynthetic apparatus requires a large amount of nitrogen, whose availability is limited in most natural ecosystems (Chapin, 1980). Efficient allocation of proteins in the apparatus is necessary to maximize photosynthetic rates (Evans & Seemann, 1989; Hikosaka & Terashima, 1995). Rubisco, which constitutes 10–40% of leaf nitrogen, limits photosynthesis at ambient CO2, whereas, at double ambient CO2, photosynthesis is often limited by ribulose-1,5-bisphosphate (RuBP) regeneration (Stitt, 1991). In the latter case, Rubisco no longer limits photosynthetic rate, and its amount is in excess (Sage, 1994; Woodrow, 1994). Theoretical studies have suggested that a large increase in the ratio of RuBP regeneration capacity (Jmax) to RuBP carboxylation capacity (Vcmax) (i.e. selective reduction in Rubisco or reallocation of nitrogen from Rubisco to the RuBP regeneration process) will increase carbon assimilation for a given amount of nitrogen in elevated CO2 (Sage, 1994; Medlyn, 1996; Drake et al., 1997; Hikosaka & Hirose, 1998). This prediction is partly supported by evidence that transgenic plants with a reduced Rubisco content achieve higher growth rates than wild types at elevated CO2 (Makino et al., 2000). However, contrary to theoretical predictions, most current plants grown at elevated CO2 do not or only slightly increase the ratio of Jmax to Vcmax (e.g. Medlyn et al., 1999; Long et al., 2004). Therefore, it has been argued that current plants are inefficient in nitrogen use at elevated CO2, and therefore they may have substantial room for improving photosynthetic nitrogen use efficiency (PNUE) (Sage & Coleman, 2001). If plants originating from natural CO2 springs have adapted to elevated CO2, higher PNUE through higher ratios of Jmax/Vcmax would be expected.
As water is lost from leaves via the same pathway as CO2 enters, CO2 assimilation is inevitably accompanied by water loss (Mooney & Gulmon, 1979). Because water availability is not infinite for plants, excessive use of water can lead to the desiccation of soil and hence to plant death (Cowan, 1986). Elevated CO2 allows plants to save water via a reduction in stomatal conductance as a result of an increased entry of CO2 into leaves, which leads to a higher carbon assimilation per unit transpiration (water use efficiency, WUE) (Drake et al., 1997). It is therefore hypothesized that plants originating from natural CO2 springs should show a reduction in stomatal conductance and a higher WUE. A reduction in stomatal conductance has been observed in plants growing at natural CO2 springs in situ (Tognetti et al., 1996; Bettarini et al., 1998; Paoletti et al., 1998; Onoda et al., 2007). Part of this reduction might be attributed to adaptation to elevated CO2.
Increased photosynthetic rates with elevated CO2 enhance carbohydrate production. This often leads to an overaccumulation of carbohydrate in the leaf (Curtis & Wang, 1998; Wand et al., 1999), causing negative effects on photosynthesis through the suppressed expression of genes related to photosynthesis (e.g. Sheen, 1990; Webber et al., 1994; Moore et al., 1998), disruption of chloroplast structures (Cave et al., 1981) and obstacles to CO2 diffusion in chloroplasts (Stitt, 1991; Nakano et al., 2000). The excessive accumulation of carbohydrates in leaves is caused by a lower sink strength compared with source strength (Stitt, 1991) or by lower carbohydrate transport capacity (Grimmer & Komor, 1999). The adaptation to elevated CO2 therefore should involve an increase in sink strength (e.g. higher root/shoot ratio or higher relative growth rate) or higher carbohydrate transport capacity, which consequently reduces carbohydrate accumulation and helps to maintain high photosynthetic rates without the down-regulation of photosynthesis.
In this study, the adaptation of leaf photosynthesis to elevated CO2 was tested by a common garden experiment with herbaceous species originating from three different natural CO2 springs in Japan: Nibu, Ryuzin-numa and Yuno-kawa. Several genotypes were collected from each high-CO2 area (spring population) and nearby control areas (control population), and each genotype was propagated or divided into two ramets, and grown in pots at 370 and 700 µmol CO2 mol−1. We tested the following three possible adaptive scenarios to elevated CO2:
higher PNUE through increase in Jmax/Vcmax;
higher WUE with lower stomatal conductance;
lower carbohydrate accumulation which mitigates the down-regulation of photosynthesis.
- Top of page
- Materials and Methods
- Supporting Information
The photosynthetic rate at growth CO2 concentration (Agrowth) increased significantly with elevated CO2 treatment by 20–40% (on average 31%), but the effect of origin on Agrowth was not significant (Fig. 1a–c, Table 1). Growth CO2 concentration significantly reduced nitrogen concentration per unit area (Narea) on average (−11%) (Fig. 1d–f, Table 1). There was a significant interaction of growth CO2 treatment × site × origin. The spring plants from Nibu showed a smaller reduction in Narea with elevated CO2 treatment (−10%) than did control plants (−22%) (Fig. 1d; ANOVA, P = 0.028 for Nibu site).
Figure 1. Box plots of leaf traits of plants originating from three natural CO2 springs (filled boxes; mean spring CO2 was 500–1000 µmol mol−1) and nearby control areas (open boxes; c. 370 µmol mol−1): Plantago asiatica from Nibu, and Polygonum sachalinense from Ryuzin-numa and Yuno-kawa. (a–c) Photosynthetic rate at growth CO2 concentrations (Agrowth) (370 or 700 µmol mol−1); (d–f) leaf nitrogen concentration per unit area (Narea). The central box in each box plot shows the interquartile range and median; whiskers indicate the 10th and 90th percentiles.
Download figure to PowerPoint
Table 1. Statistical analysis of leaf traits shown in Figs 1 and 2
|Origin × site|| 2||4.056||0.37ns||0.013||0.53ns||0.006||0.15ns||0.003||3.71**||59.852||3.63*|
|Error||37||10.933|| ||0.025|| ||0.038|| ||0.001|| ||16.496|| |
|Growth CO2|| 1||372.055||175.00****||0.324||23.21****||0.459||48.79****||0||0.01ns||470.698||25.15****|
|Growth CO2 × origin|| 1||0.039||0.02ns||0.009||0.62ns||0||0.05ns||0||0ns||2.197||0.12ns|
|Growth CO2 × site|| 2||2.097||0.99ns||0.034||2.46*||0.009||0.92ns||0.001||1.78ns||2.031||0.11ns|
|Growth CO2 × site × origin|| 2||3.225||1.52ns||0.057||4.11**||0||0.01ns||0.001||1.75ns||3.643||0.19ns|
|Error||37||2.126|| ||0.014|| ||0.009|| ||0.001|| ||18.714|| |
The maximum rates of RuBP carboxylation (Vcmax) and electron transport (Jmax) were lower in plants grown at elevated CO2 treatment (on average −17% for Vcmax and −11% for Jmax). There was no significant difference in these reductions between spring and control plants (Table 2). However, similar to Narea, the spring plants from Nibu showed a trend of reduced down-regulation of Jmax with elevated CO2 (−7%) compared with their respective control plants (−14%), although this interaction was insignificant (P = 0.11; Table 2). Yuno-kawa plants, however, showed an opposite trend (−16% and −5%). The Jmax/Vcmax ratio, an indicator of protein allocation, was slightly higher in all plants grown at elevated CO2 treatment (on average 8%; Fig. 2a–c). However, the ratio was not different between spring and control plants (Table 1), which did not support the first hypothesis. Higher Agrowth with lower Narea at elevated CO2 treatment greatly increased PNUE (on average 45%; Table 3). However, there was no further increase in PNUE in spring plants when compared with control plants. The spring plants from Yuno-kawa showed lower PNUE than control plants (−13%), which was partly ascribed to their lower stomatal conductance (see below).
Table 2. Effects of CO2 concentration on leaf traits of plants originating from three natural CO2 springs (mean spring CO2 was 500–1000 µmol mol−1) and nearby control areas (c. 370 µmol mol−1)
|(µmol m−2 s−1)||(µmol m−2 s−1)||(%)||(%)||(g m−2)|
|Nibu||LC||Control||0.83 ± 0.06||74.3 ± 9.9||136.7 ± 14.6||2.32 ± 0.58||47.4 ± 1.0||57.7 ± 13.6|
|Spring||0.83 ± 0.05||71.0 ± 11.1||129.6 ± 17.1||2.40 ± 0.64||46.6 ± 1.7||53.0 ± 9.1|
|HC||Control||0.86 ± 0.05||58.8 ± 9.2||114.3 ± 11.1||1.49 ± 0.22||45.9 ± 1.6||69.0 ± 11.7|
|Spring||0.84 ± 0.06||61.7 ± 9.4||120.2 ± 11.2||1.90 ± 0.37||46.7 ± 1.4||59.9 ± 10.4|
|Ryuzin-numa||LC||Control||0.79 ± 0.03||48.8 ± 11.5||90.9 ± 21.9||2.17 ± 0.25||48.1 ± 2.1||46.5 ± 9.2|
|Spring||0.81 ± 0.05||47.1 ± 8.1||86.8 ± 17.3||2.16 ± 0.26||48.4 ± 1.0||46.9 ± 7.9|
|HC||Control||0.80 ± 0.05||39.5 ± 7.4||80.8 ± 14.8||1.77 ± 0.21||49.1 ± 1.1||56.6 ± 5.4|
|Spring||0.81 ± 0.05||38.5 ± 7.4||77.3 ± 11.4||1.59 ± 0.28||48.7 ± 0.6||54.9 ± 6.1|
|Yuno-kawa||LC||Control||0.83 ± 0.06||48.0 ± 8.7||91.2 ± 14.6||2.24 ± 0.26||49.2 ± 1.6||43.4 ± 7.1|
|Spring||0.75 ± 0.06||48.4 ± 7.2||93.0 ± 13.8||1.99 ± 0.28||49.2 ± 1.1||53.3 ± 4.4|
|HC||Control||0.85 ± 0.05||43.5 ± 11.2||86.8 ± 14.0||1.74 ± 0.24||48.8 ± 2.6||54.1 ± 7.2|
|Spring||0.81 ± 0.03||38.4 ± 7.2||78.3 ± 11.4||1.67 ± 0.53||48.6 ± 2.0||56.7 ± 14.3|
|Mixed-model ANOVA|| ||Ci/Ca||Vcmax||Jmax||Nmass||Cmass||LMA|
|Origin × site|| 2||0.009||2.80*||8.932||0.06ns||23.24||0.07ns||0.015||1.43ns||0.019||0.01ns||212.817||1.66ns|
|Error||37||0.003|| ||137.935|| ||321.38|| ||0.011|| ||3.289|| ||128.198|| |
|Growth CO2|| 1||0.010||6.20**||1985.278||63.92****||3027.12||27.30****||0.238||41.00****||0.519||0.34ns||1236.18||16.74****|
|Growth CO2 × origin|| 1||0||0ns||0.893||0.03ns||6.65||0.06ns||0.008||1.44ns||0.321||0.21ns||215.311||2.92*|
|Growth CO2 × site|| 2||0.002||1.15ns||52.485||1.69ns||97.44||0.88ns||0.011||1.86ns||3.919||2.57*||51.116||0.69ns|
|Growth CO2 × site × origin|| 2||0.002||1.16ns||63.153||2.03ns||256.89||2.32ns||0.009||1.63ns||2.899||1.9ns||50.313||0.68ns|
|Error||37||0.002|| ||31.061|| ||110.89|| ||0.006|| ||1.525|| ||73.84|| |
|Plants were grown at ambient CO2 (LC, 370 µmol mol−1) and elevated CO2 (HC, 700 µmol mol−1). Mean ± 1SD (n = 7–8). Mixed-model ANOVA was used. Growth CO2 concentration is a within-subject factor and fixed between-subject factors are site and origin (two-way ANOVA). Mean square (MS), F value and significance are presented. Significance levels: *, P < 0.1; **, P < 0.05; ***, P < 0.01; ****, P < 0.001; ns, not significant.|
|Ci/Ca, ratio of intercellular and ambient partial pressures of CO2; Cmass, leaf carbon on a mass basis; Jmax, maximum electron transport rate driving ribulose-1,5-bisphosphate (RuBP) regeneration; LMA, leaf mass per unit area; Nmass, leaf nitrogen on a mass basis; Vcmax, maximum rate of RuBP carboxylation.|
Figure 2. Box plots of leaf traits of plants originating from three CO2 springs (filled boxes; mean spring CO2 was 500–1000 µmol mol−1) and nearby control areas (open boxes; 370 µmol mol−1): Plantago asiatica from Nibu, and Polygonum sachalinense from Ryuzin-numa and Yuno-kawa. (a–c) Ratio of the maximum electron transport rate driving ribulose-1,5-bisphosphate (RuBP) regeneration (Jmax) to the maximum rate of RuBP carboxylation (Vcmax); (d–f) stomatal conductance (gs) for water vapour at growth CO2 concentrations; (g–i) leaf starch concentration. The central box in each box plot shows the interquartile range and median; whiskers indicate the 10th and 90th percentiles.
Download figure to PowerPoint
Table 3. Effects of CO2 concentration on leaf-level resource use efficiencies of plants originating from three natural CO2 springs (mean growth CO2 was 500–1000 µmol mol−1) and nearby control areas (c. 370 µmol mol−1)
|Site||Growth CO2||Origin||WUE (mmol mol−1)||PNUE (µmol g−1 s−1)|
|Nibu||LC||Control||3.36 ± 0.71||14.3 ± 3.0|
|Spring||3.30 ± 0.82||14.4 ± 2.4|
|HC||Control||4.77 ± 1.32||21.9 ± 2.8|
|Spring||5.31 ± 1.53||20.9 ± 2.9|
|Ryuzin-numa||LC||Control||4.97 ± 0.67||11.8 ± 1.7|
|Spring||4.26 ± 0.85||11.7 ± 2.4|
|HC||Control||7.62 ± 1.63||15.5 ± 2.2|
|Spring||7.51 ± 1.86||17.2 ± 2.6|
|Yuno-kawa||LC||Control||4.19 ± 1.53||12.5 ± 1.5|
|Spring||5.89 ± 1.37||10.4 ± 1.6|
|HC||Control||6.64 ± 2.38||17.8 ± 2.8|
|Spring||8.46 ± 1.42||16.2 ± 2.2|
|Mixed-model ANOVA Source||d.f.||WUE||PNUE|
|Origin × site|| 2||7.935||2.73*||11.186||1.23ns|
|Error||37||2.908|| ||9.076|| |
|Growth CO2|| 1||121.811||113.43****||729.401||248.19****|
|Growth CO2 × origin|| 1||0.778||0.72ns||1.232||0.42ns|
|Growth CO2 × site|| 2||2.882||2.68*||10.426||3.55**|
|Growth CO2 × site × origin|| 2||0.269||0.25ns||3.84||1.31ns|
|Error||37||1.074|| ||2.939|| |
Stomatal conductance tended to be lower in plants grown in elevated CO2 (average reduction of −23%; Fig. 2d–f, Table 1), although the difference was not significant. There was a significant interaction between site and origin (Table 1). In particular, spring plants from Yuno-kawa showed markedly lower stomatal conductance (−40%) than control plants. The lower stomatal conductance was also accompanied by lower Ci/Ca (Table 2). The lower stomatal conductance with higher photosynthetic rate (Fig. 1a–c) resulted in significantly higher WUE with elevated CO2 treatment (on average 55%; Table 3). The effect of origin was not significant, but there was a marginally significant interaction between site and origin, in which the spring plants from Yuno-kawa showed higher WUE (+32%) than control plants. The latter is partly in agreement with our second hypothesis that spring plants have a higher WUE.
Starch concentration per unit mass was sharply and significantly increased by elevated CO2 treatment (21–90%; on average 57%; Fig. 2g–i). The increases were more pronounced when starch was expressed per unit area (on average 85% increase; data not shown) because of the higher leaf mass per unit area (LMA) at elevated CO2 treatment. The effect of origin was not significant, but there was a significant interaction between site and origin (Table 1). The spring plants from Nibu showed, on overage, 15% lower starch concentration per unit mass (and 22% lower per unit area) than control plants. The third hypothesis, that spring plants would have lower starch accumulation, was supported in this case (Fig. 2g), but was not supported by plants from Ryuzin-numa.
The CVs of the measured traits ranged widely, depending on the trait, from c. 3% in carbon concentration to c. 40% in starch concentration (Fig. 3, Table S1). CV is considered to reflect genotypic variation within a population. If high CO2 acts as a very strong selective agent, causing a bottleneck effect, it could be expected that CV of the selected trait would be smaller in spring than control populations because of reduced genetic variation. However, no such trends were observed (Fig. 3a), suggesting that high CO2 acted as a mild selective agent. The presence of gene flow between spring and control populations may also increase genetic variability and, consequently, counteract the possible reduction in genetic variability.
Figure 3. (a) Coefficient of variation (CV) for measured traits. CV was calculated for each growth CO2 treatment (370 and 700 µmol mol−1) and the mean is shown for each site and origin. (b) Relationship between effect sizes (proportion of the total sum of squares which can be explained by origin or origin × site) and mean CV across measured traits. (See text for details of the calculation.) The numbers correspond to the traits in (a). There is a positive correlation between CV and effect size of origin × site (y = 0.0038x + 0.0069, R2 = 0.539, P = 0.0018).
Download figure to PowerPoint
To investigate a possible reason why some traits were changed and others were not, CVs were compared between measured traits. Traits that were different between some spring and control populations (e.g. stomatal conductance, WUE and starch) had generally high CVs; however, Jmax/Vcmax had a small CV (Fig. 3a). Although there was no correlation between CV and effect size of origin (sum of squares of the origin effect as a proportion of the total sum of squares), there was a positive trend between CV and effect size of origin × site, suggesting that traits with larger natural variation might be more susceptible to long-term elevated CO2, depending on species or site environments (Fig. 3b).
- Top of page
- Materials and Methods
- Supporting Information
Our study is the first work to use multiple CO2 springs and to investigate plant adaptation to high CO2 concentration. Although significant interactions between site and origin were found in several traits, no consistent change across the three CO2 springs was found (Tables 1–3). General trends of plant adaptation to high CO2 therefore could not be found in this study. However, significant site × origin interactions suggest that high CO2 acted as a selective agent in a different manner, depending on the species and other environmental conditions. A recent molecular study also found relatively large genetic differentiation across the CO2 gradient in these plants (I. Nakamura et al., unpublished). Several previous studies, that used a single CO2 spring, also found significant differences in plant traits between spring and control plants (Fordham et al., 1997; Polle et al., 2001; Schulte et al., 2002). Together with these studies, we support the concept that high CO2 will act as a selective agent, but that the effects of selection will vary across sites and species.
The spring plants, especially those from Yuno-kawa, showed a lower stomatal conductance than did control plants (Fig. 2f). The lower stomatal conductance reduced water loss and resulted in a higher WUE (Table 3). Theory predicts that a decrease in stomatal conductance under high CO2 should be adaptive, because plants can save water while keeping photosynthesis at relatively high levels (Cowan, 1986). Field studies at natural CO2 springs have found that the water saving at elevated CO2 extends the photosynthetically active time in the dry period (Jones et al., 1995; Hättenschwiler et al., 1997) and mitigates the midday depression of stomatal conductance (Tognetti et al., 1999). These advantages may be particularly important for P. sachalinense as it has a relatively large leaf area, which is sensitive to drought. Furthermore, the decrease in transpiration rates may affect the hydraulic balance at the whole plant level. Nakamura et al. found that P. asiatica from the Nibu CO2 spring invested relatively less biomass in roots and more in leaves compared with P. asiatica from the control area (I. Nakamura et al., unpublished), which may contribute to increased fitness in the high-CO2 environment.
It is well known that plants decrease stomatal conductance under short-term elevation of CO2 concentration (up to several years) (−20% at 550 µmol mol−1; Long et al., 2004). Our results suggest that further decreases in stomatal conductance would be favoured under long-term elevated CO2. Our previous study also found that Yuno-kawa spring plants showed very low stomatal conductance compared with control plants in their original locations (−41% with 530 µmol mol−1[CO2]; Onoda et al., 2007), suggesting that the in situ difference was caused by the combined effects of acclimation and adaptation. As lower stomatal conductance would lead to lower transpiration from ecosystems and, consequently, an increase in soil moisture (Field et al., 1995), a further change in stomatal conductance as a result of adaptation may affect the ecosystem function.
Spring plants from Nibu showed a smaller reduction in Narea (and, similarly, in Jmax) with high growth CO2 concentration than did control plants (Fig. 1d, Table 1). This suggests that the spring plants maintained a high photosynthetic capacity at elevated CO2 concentration without serious down-regulation, and thus utilized CO2 more efficiently than did control plants. This was associated with lower carbohydrate accumulation (Fig. 1). The spring plants showed reduced starch accumulation for a given Agrowth (Fig. S1a,b, see Supporting Information), suggesting that lower starch accumulation was probably caused by higher carbohydrate transport. A reduction in carbohydrate accumulation was also found in Quercus ilex from Italian CO2 springs (Schulte et al., 2002). These results suggest that CO2 adaptation may include an alteration in sink–source balance or an increase in carbohydrate transport capacity.
The Jmax/Vcmax ratio reflects the protein allocation between Rubisco and the RuBP regeneration process (Onoda et al., 2005; Hikosaka, 2005). An increase in this ratio by 5–10% (Fig. 1) suggests that the plants seem to respond positively to high CO2 with slightly more efficient allocation of nitrogen. However, this change may not be sufficiently large to track the CO2 elevation (from 370 to 700 µmol mol−1), because it increased the co-limiting Ci, where nitrogen was optimally allocated between Rubisco and RuBP regeneration processes (Medlyn, 1996; Hikosaka & Hirose, 1998), by 60–120 µmol mol−1 only. Therefore, a further increase in the Jmax/Vcmax ratio should be expected with adaptation to high CO2. However, we did not find any difference in the Jmax/Vcmax ratio between spring and control plants (Table 1), suggesting that the photosynthesis machinery is quite conservative against long-term elevated CO2.
Why were some traits changed, but others were not, in spring plants? As evolution is the interaction of natural selection and genetic variability, one explanation could be that genetic variation in some traits was limited. For example, in the case of Jmax/Vcmax, CV was only 7.7% on average (Fig. 3a), whereas the theoretical study suggests that Jmax/Vcmax should increase by 20–30% following adaptation to high CO2 (from 350 to 700 µmol m−2 s−1; Hikosaka & Hirose, 1998), suggesting that the genetic variability in this trait constrains the adaptive response to high CO2 concentration. Considering the fact that atmospheric CO2 concentration has been more or less constant over the past 650 000 yr (IPCC, 2007), the Jmax/Vcmax ratio might have been strongly selected for the past stable CO2 concentration. If so, the optimization in the past may constrain the optimization in the near future (i.e. ~100 yr). By contrast, stomatal conductance and starch concentration showed relatively large CVs. A large CV implies that: (1) such traits may have been neutral or contributed little to fitness at the current or past CO2 concentration; or (2) such traits may have been selected for various environmental heterogeneities (light, soil nutrients, etc). Regardless of the cause, if such large variations interact with fitness at high CO2 concentration, traits with more variation are more likely to be affected by selective pressure of elevated CO2 (Tonsor & Scheiner, 2007).
The evolutionary response to CO2 has not received as much attention as the short-term response to CO2, but the increasing number of studies on CO2 springs (e.g. Fordham et al., 1997; Polle et al., 2001; Schulte et al., 2002) and selection experiments (Ward et al., 2000; Collins & Bell, 2004) suggest that high CO2 will act as a selective agent. As the atmospheric CO2 concentration is more or less homogeneous over the world, all terrestrial plants have been exposed to increasing CO2 concentration, and thus have been subject to selection pressure of elevated CO2. This could be an important issue in plant evolution, when compared with global warming in which plants may escape (migrate or be translocated) from warming towards high latitude or altitude without evolution (Hoegh-Guldberg et al., 2008). Evolutionary responses to high CO2 may therefore have important effects on ecosystem function and species’ interactions all over the world.
High CO2 concentration directly and greatly increased PNUE and WUE (Table 2), suggesting that plants will show higher growth rates at a given resource availability and, consequently, that plants will be subject to more intense competition. However, a further improvement in PNUE with a selective reduction in Rubisco relative to the RuBP regeneration process (e.g. Sage & Coleman, 2001) was not observed, probably because of the limited genetic variation in the photosynthetic machinery. However, a significant reduction in stomatal conductance, which contributed to higher WUE, and a trend of reduced down-regulation of photosynthesis with a lower starch accumulation were found in some spring plants. These results suggest that there is substantial room for plant evolution in high-CO2 environments, and such evolution could have important implications for species’ interactions and ecosystem functioning in the future.