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Keywords:

  • acclimation;
  • adaptation;
  • nitrogen use efficiency;
  • Rubisco;
  • RuBP regeneration;
  • natural selection;
  • starch accumulation;
  • water use efficiency

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
  • • 
    Atmospheric CO2 elevation may act as a selective agent, which consequently may alter plant traits in the future. We investigated the adaptation to high CO2 using transplant experiments with plants originating from natural CO2 springs and from respective control sites.
  • • 
    We tested three hypotheses for adaptation to high-CO2 conditions: a higher photosynthetic nitrogen use efficiency (PNUE); a higher photosynthetic water use efficiency (WUE); and a higher capacity for carbohydrate transport from leaves.
  • • 
    Although elevated growth CO2 enhanced both PNUE and WUE, there was no genotypic improvement in PNUE. However, some spring plants had a higher WUE, as a result of a significant reduction in stomatal conductance, and also a lower starch concentration. Higher natural variation (assessed by the coefficient of variation) within populations in WUE and starch concentration, compared with PNUE, might be responsible for the observed population differentiation.
  • • 
    These results support the concept that atmospheric CO2 elevation can act as a selective agent on some plant traits in natural plant communities. Reduced stomatal conductance and reduced starch accumulation are highlighted for possible adaptation to high CO2.

Abbreviations: CV

coefficient of variation

IPCC

Intergovernmental Panel on Climate Change

OTC

open-top chamber

PNUE

photosynthetic nitrogen use efficiency

RuBP

ribulose-1,5-bisphosphate

WUE

water use efficiency

Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. 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.

Materials and Methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Plant materials and growth conditions

We used one dominant herbaceous species from each of the three natural CO2 springs: Plantago asiatica from Nibu (also known as Nyuu), and Polygonum sachalinense from Ryuzin-numa and Yuno-kawa. These species were selected for two reasons: they are known to adapt to a wide range of environments with genetic differentiation (i.e. cDNA and morphology; Sawada et al., 1994; Inamura et al., 2000); they were dominant species and probably had been subject to intense competition, in which genotypes that grew better at elevated CO2 might have been selected.

All of these sites were located in National Parks and the vegetation in the surrounding area was generally well preserved. Nibu is located at 1000 m above sea level (asl) in Yamagata Prefecture, Japan (38°32′N, 139°59′E), and Ryuzin-numa and Yuno-kawa are located at 570–575 m asl in Aomori Prefecture, Japan (40°41′N, 140°55′E, c. 300 km from Nibu). The distance between Ryuzin-numa and Yuno-kawa is c. 1 km. At these CO2 springs, the surrounding air has been maintained at high CO2 levels for more than 100 yr without toxic gas contaminations (H2S, SO2) (< 0.03 µmol mol−1 even at the highest CO2 concentration spot). The areas in which the mean daily CO2 concentration was above 500 µmol mol−1 were approximately 600, 300 and 400 m2 at Nibu, Ryuzin-numa and Yuno-kawa, respectively. A detailed description of these CO2 springs is available in Onoda et al. (2007).

Plantago asiatica, a small perennial rosette (0.1–0.3 m), grew predominantly along a path at Nibu where above-ground vegetation was mown annually. There were hundreds of mature individuals with large numbers of seedlings (c. 5000 plants m−2 in May 2003). Pollen dispersal has been reported to be very limited (0.1–0.4 m) in a closely related species (Plantago major; Kuiper & Bos, 1992). Seeds are dispersed by gravity or by attachment to animals’ feet via the sticky seed coat. About 20 genets of P. asiatica were collected at the high-CO2 area near the spring (abbreviated as ‘S’) and the control area (abbreviated as ‘C’) (40 m distant from the high-CO2 area) on 20 May 2003. The two areas had a similar light environment (S, 75–100% of full sun; C, 75–100% of full sun) and soil pH (S, 3.9 ± 0.3; C, 4.2 ± 0.2). The mean daytime CO2 concentrations determined by monthly measurements from July to October in 2003 were 750 ± 199 µmol mol−1 (S) and 370 µmol mol−1 (C).

Polygonum sachalinense is a relatively tall stature (0.5–1.5 m in our study site) perennial herb, and grew predominantly in a semi-open place (relative light intensity, 30–50% of full sun) at Ryuzin-numa. This species is a clonal plant, and a genet produces many ramets. Some ramets have flowers in summer, which attract small insects (e.g. beetles, hoverflies and bees), and seeds are normally dispersed by wind (most seeds appear to drop within a few metres). In the high-CO2 area, there were > 500 shoots in which > 20 genets were included (each genet was recognized by differences in the phenology in 2002). Eight pieces of rhizomes that had more than two buds were collected from different genets in the high-CO2 area and nearby control areas (50–100 m distant from the high-CO2 area) on 6 May 2003. The two areas had a similar light environment (S, 30–50% of full sun; C, 30–60% of full sun) and soil pH (S, 3.6 ± 0.1; C, 3.1 ± 0.3). The mean daytime CO2 concentrations evaluated by monthly measurements from June to October in 2002 were 670 ± 123 µmol mol−1 (S) and 375 µmol mol−1 (C).

Polyponum sachalinense also grew predominantly at Yuno-kawa and was located under an oak–beech forest. There were > 20 genets and 400 shoots in the high-CO2 area. Eight pieces of rhizomes with more than two buds were collected from different genets in the high-CO2 area and nearby control areas (500 m distant from the high-CO2 area) on 6 May 2003. The light environment was 2–20% of full sun for both areas, and the soil pH values were 4.1 ± 0.4 (S) and 4.1 ± 0.4 (C). The mean daytime CO2 concentrations from monthly measurements from June to October in 2003 were 526 ± 58 µmol mol−1 (S) and 370 µmol mol−1 (C).

Plants originating from the CO2 springs (spring plants) and control areas (control plants) were grown in the Experimental Garden of Tohoku University (38°15′N, 140°50′E). Each genet of P. asiatica was grown separately for 1 yr to produce several ramets. Two ramets from each genet were planted separately in two 1.5-l pots filled with washed river sand, and assigned to one of the two CO2 treatments [ambient (c. 370 µmol mol−1) and elevated (targeted at 700 µmol mol−1) CO2 concentrations] with four open-top chambers (OTCs; 2 × 2 × 2 m3; two chambers for each CO2 treatment) on 12 May 2004. The CO2 concentration in the chamber was 360–400 µmol mol−1 for the ambient treatment, and was regulated to c. 700 µmol mol−1 for the elevated CO2 treatment (for details, including the OTC structure, see Nagashima et al., 2003). During the experiment, each pot received sufficient water every day and 90 ml of nutrient solution (7 mM [N]; Hyponex NPK = 6 : 10 : 5; M. Scott & Sons Co., Marysville, OH, USA) every week, and the positions of the pots were randomized within each CO2 treatment every week.

Each rhizome piece of P. sachalinense was split into two similar-sized pieces, both of which had one bud, and was grown in peat moss in 1.5-l pots for 0.5 month. On 23 May 2003, these plants were transplanted to 4-l pots filled with washed river sand, and one of each pair was assigned to elevated CO2 treatment and the other to ambient CO2 treatment. These plants were grown in the same manner as for P. asiatica.

Gas exchange measurements

The CO2 dependence of the net CO2 assimilation rate was determined on attached, fully expanded young leaves with an open gas-exchange system (LI-6400, Li-Cor, Lincoln, NE, USA) on 16–18 August 2003 for P. sachalinense (c. 85 d after transfer to OTC) and on 8–10 July 2004 for P. asiatica (c. 60 d after transfer to OTC). During the measurements, the leaf temperature in the chamber was kept at 25°C, the vapour pressure deficit at < 1 kPa and the photon flux density at 1500 µmol m−2 s−1 with an artificial light source (LI-6400-02B, Li-Cor). The measurements were performed on seven to eight pairs of genotypes (one ramet of each genet grown in ambient CO2 treatment and another grown in elevated CO2 treatment) for each origin (control and spring) and for each site (Nibu, Ryuzin-numa and Yuno-kawa). The total number of samples was therefore 7–8 replications × 2 growth CO2 × 2 origins × 3 sites.

Photosynthesis plotted against intercellular CO2 concentration (A/Ci curve) was analysed to estimate the in vivo maximum rate of RuBP carboxylation (Vcmax) and the in vivo maximum rate of electron transport driving RuBP regeneration (Jmax). Vcmax was calculated by fitting the following equation (Farquhar et al., 1980) to the initial slope of the A/Ci curves (Ci < 300 µmol mol−1) using the least-squares method with Kaleida Graph™ (Synergy Software, Reading, PA, USA):

  • image(Eqn 1)

(Ac, photosynthetic rate limited by Rubisco activity; Ci, intercellular CO2 concentration; Γ*, CO2 compensation point in the absence of day respiration (Rd); Kc and Ko, Michaelis–Menten constants of Rubisco activity for CO2 and O2, respectively.) Γ*, Kc and Ko are assumed to be 42.8 µmol mol−1, 405 µmol mol−1 and 278 mmol mol−1, respectively, according to Bernacchi et al. (2001). Rd was assumed to be 0.01 of Vcmax (von Caemmerer, 2000). Jmax was calculated by fitting the following equation (Farquhar et al., 1980) to a near-plateau of A/Ci curves (Ci  > 600 µmol mol−1):

  • image(Eqn 2)

(Aj, photosynthetic rate limited by RuBP regeneration.)

Biochemical measurements

All leaves used for photosynthesis measurements were sampled at around noon, and seven leaf discs of 1 cm in diameter were punched out from each leaf. Three leaf discs per leaf were weighed after drying in an oven at 75°C for more than 3 d, and their total nitrogen content was determined with an NC analyser (NC-80, Shimadzu, Kyoto, Japan). The other leaf discs were frozen in liquid nitrogen and stored at −80°C.

The starch content was determined according to Rufty & Huber (1983). Two leaf discs from each leaf were homogenized in liquid nitrogen and suspended in 1.5 ml of 80% ethanol. The suspension was heated at 80°C for 30 min and centrifuged at 10 000 g for 10 min, and the supernatant was removed. This extraction procedure was repeated three times. The pellet was dried in an oven for 1 d, and then suspended in 1.0 ml of 0.2 M KOH and heated at 90°C for 30 min. After cooling, 0.2 ml of 1.0 M acetic acid and 1.0 ml of amyloglucosidase (35 units ml−1 in sodium acetate buffer, pH 4.5; Rhizopus mould; Sigma, St Louis, MO, USA) were added, and incubated at 55°C for 30 min. The suspension was centrifuged at 10 000 g for 10 min and the supernatant was used for the determination of glucose using the glucose B test (Wako, Osaka, Japan).

Calculations and statistics

The WUE value was calculated as the photosynthetic rate divided by the transpiration rate, which was measured at growth CO2 concentration (370 or 700 µmol mol−1). Similarly, PNUE was calculated as the photosynthetic rate at growth CO2 concentration (Agrowth) divided by the leaf nitrogen concentration per unit area (Narea). For statistical analysis, a mixed-model ANOVA (within and between subject factors) was used. As each genotype was grown at two different CO2 concentrations (ambient and elevated CO2), the response to these two CO2 concentrations can be regarded as repeated measures. Therefore, growth CO2 was treated as a within-subject factor, and origins (spring and control populations) and sites (Nibu, Ryuzin-numa and Yuno-kawa) were treated as between-subject factors. The effects of origin and site were tested by two-way ANOVA, which allowed us to use a single ANOVA for all data without losing statistical power. For practical reasons, the effect of site in our analysis also includes the effect of species, as different species were used for Nibu and the other sites. Traits were log-transformed before analysis if equality of the covariance matrices was rejected (P < 0.05) with Box's test. The coefficient of variation (CV) was calculated as the standard deviation divided by the mean of each trait × 100 (%) as an index of the natural variation of the trait. CV can also be influenced by measurement errors or heterogeneity of traits within a plant, but we assume that the main source of variation was provided by genotypic differences in the community. CV was calculated for each site, origin and growth CO2 (3 sites × 2 origins × 2 growth CO2). Standardized effect size (η2, sum of squares of an effect as a proportion of the total sum of squares) was calculated for each explanatory factor. All statistical analyses were performed using SPSS 15 (SPSS Inc, Chicago, IL, USA).

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. 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).

image

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.

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Table 1.  Statistical analysis of leaf traits shown in Figs 1 and 2
Sourced.f.AgrowthNareaJmax/Vcmaxgs1Starch
MSFMSFMSFMSFMSF
  • Mixed-model ANOVA was used. Growth CO2 is a within-subject factor, and site and origin are between-subject factors (two-way ANOVA). Mean square (MS), F value and levels of significance are presented. Significance levels: *, P < 0.1; **, P < 0.05; ***, P < 0.01; ****, P < 0.001; ns, not significant.

  • 1

    Log-transformed before analysis to satisfy equality of covariance matrices (Box's test).

  • Agrowth, photosynthetic rate at growth CO2 concentration; gs, stomatal conductance; Jmax, maximum electron transport rate driving ribulose-1,5-bisphosphate (RuBP) regeneration; Narea, leaf nitrogen concentration per unit area; Vcmax, maximum rate of RuBP carboxylation.

Between-subject effects
Origin 17.8040.71ns0.0010.06ns00.001ns0.0021.81ns0.8570.05ns
Site 2457.20341.82****0.38715.49****0.0481.25ns0.0033.32**266.18916.14****
Origin × site 24.0560.37ns0.0130.53ns0.0060.15ns0.0033.71**59.8523.63*
Error3710.933 0.025 0.038 0.001 16.496 
Within-subject effects
Growth CO2 1372.055175.00****0.32423.21****0.45948.79****00.01ns470.69825.15****
Growth CO2 × origin 10.0390.02ns0.0090.62ns00.05ns00ns2.1970.12ns
Growth CO2 × site 22.0970.99ns0.0342.46*0.0090.92ns0.0011.78ns2.0310.11ns
Growth CO2 × site × origin 23.2251.52ns0.0574.11**00.01ns0.0011.75ns3.6430.19ns
Error372.126 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)
SiteGrowth CO2OriginCi/CaVcmaxJmaxNmassCmassLMA
(µmol m−2 s−1)(µmol m−2 s−1)(%)(%)(g m−2)
NibuLCControl0.83 ± 0.0674.3 ± 9.9136.7 ± 14.62.32 ± 0.5847.4 ± 1.057.7 ± 13.6
Spring0.83 ± 0.0571.0 ± 11.1129.6 ± 17.12.40 ± 0.6446.6 ± 1.753.0 ± 9.1
HCControl0.86 ± 0.0558.8 ± 9.2114.3 ± 11.11.49 ± 0.2245.9 ± 1.669.0 ± 11.7
Spring0.84 ± 0.0661.7 ± 9.4120.2 ± 11.21.90 ± 0.3746.7 ± 1.459.9 ± 10.4
Ryuzin-numaLCControl0.79 ± 0.0348.8 ± 11.590.9 ± 21.92.17 ± 0.2548.1 ± 2.146.5 ± 9.2
Spring0.81 ± 0.0547.1 ± 8.186.8 ± 17.32.16 ± 0.2648.4 ± 1.046.9 ± 7.9
HCControl0.80 ± 0.0539.5 ± 7.480.8 ± 14.81.77 ± 0.2149.1 ± 1.156.6 ± 5.4
Spring0.81 ± 0.0538.5 ± 7.477.3 ± 11.41.59 ± 0.2848.7 ± 0.654.9 ± 6.1
Yuno-kawaLCControl0.83 ± 0.0648.0 ± 8.791.2 ± 14.62.24 ± 0.2649.2 ± 1.643.4 ± 7.1
Spring0.75 ± 0.0648.4 ± 7.293.0 ± 13.81.99 ± 0.2849.2 ± 1.153.3 ± 4.4
HCControl0.85 ± 0.0543.5 ± 11.286.8 ± 14.01.74 ± 0.2448.8 ± 2.654.1 ± 7.2
Spring0.81 ± 0.0338.4 ± 7.278.3 ± 11.41.67 ± 0.5348.6 ± 2.056.7 ± 14.3
Mixed-model ANOVA Ci/CaVcmaxJmaxNmassCmassLMA
d.f.MSFMSFMSFMSFMSFMSF
Between-subject effects
Origin 10.0062.06ns37.5970.27ns145.370.45ns00.03ns0.1020.03ns37.3080.29ns
Site 20.0124.04**5139.87937.26****15997.2849.78****0.0020.16ns44.95413.67****829.2086.47***
Origin × site 20.0092.80*8.9320.06ns23.240.07ns0.0151.43ns0.0190.01ns212.8171.66ns
Error370.003 137.935 321.38 0.011 3.289 128.198 
Within-subject effects
Growth CO2 10.0106.20**1985.27863.92****3027.1227.30****0.23841.00****0.5190.34ns1236.1816.74****
Growth CO2 × origin 100ns0.8930.03ns6.650.06ns0.0081.44ns0.3210.21ns215.3112.92*
Growth CO2 × site 20.0021.15ns52.4851.69ns97.440.88ns0.0111.86ns3.9192.57*51.1160.69ns
Growth CO2 × site × origin 20.0021.16ns63.1532.03ns256.892.32ns0.0091.63ns2.8991.9ns50.3130.68ns
Error370.002 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.
image

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.

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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)
SiteGrowth CO2OriginWUE (mmol mol−1)PNUE (µmol g−1 s−1)
NibuLCControl3.36 ± 0.7114.3 ± 3.0
Spring3.30 ± 0.8214.4 ± 2.4
HCControl4.77 ± 1.3221.9 ± 2.8
Spring5.31 ± 1.5320.9 ± 2.9
Ryuzin-numaLCControl4.97 ± 0.6711.8 ± 1.7
Spring4.26 ± 0.8511.7 ± 2.4
HCControl7.62 ± 1.6315.5 ± 2.2
Spring7.51 ± 1.8617.2 ± 2.6
Yuno-kawaLCControl4.19 ± 1.5312.5 ± 1.5
Spring5.89 ± 1.3710.4 ± 1.6
HCControl6.64 ± 2.3817.8 ± 2.8
Spring8.46 ± 1.4216.2 ± 2.2
Mixed-model ANOVA Sourced.f.WUEPNUE
MSFMSF
  1. 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 levels of significance are presented. Significance levels: *, P < 0.1; **, P < 0.05; ***, P < 0.01; ****, P < 0.001; ns, not significant.

  2. PNUE, photosynthetic nitrogen use efficiency; WUE, water use efficiency.

Between-subject effects
Origin 15.4141.86ns5.6430.62ns
Site 240.23713.84****133.77914.74****
Origin × site 27.9352.73*11.1861.23ns
Error372.908 9.076 
Within-subject effects
Growth CO2 1121.811113.43****729.401248.19****
Growth CO2 × origin 10.7780.72ns1.2320.42ns
Growth CO2 × site 22.8822.68*10.4263.55**
Growth CO2 × site × origin 20.2690.25ns3.841.31ns
Error371.074 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.

image

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).

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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).

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. 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.

Conclusion

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.

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

The landowners of the CO2 springs (Hakkoda-Onsen Co., Tashiro Bokuya-Chikusan Kumiai and Yudonosan shrine) kindly gave us permission to collect plants growing in their lands for this study. We thank Ken-ichi Sato, Toshihiko Kinugasa, Yuko Yasumura, Kay-May Miyagi, Ito Nakamura and Noriyuki Osada for their help with fieldwork and growing plants, and Masakado Kawata, Shin-ichi Morinaga, Niels Anten, Belinda Medlyn, David Ackerly and anonymous reviewers for critical and constructive comments on the draft manuscript. This study was partly supported by a Grant-in-Aid from the Japan Society for the Promotion of Science for Young Research Fellows (Y.O.), and from the Japan Ministry of Education, Culture, Sports, Science and Technology for K.H. and T.H.

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  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
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Supporting Information

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Fig. S1 Relationships between maximum electron transport rate driving ribulose-1,5-bisphosphate (RuBP) regeneration (Jmax) and leaf starch concentration (a) and between leaf starch concentration and photosynthetic rate at growth CO2 concentrations (b) of Plantago asiatica originating from a CO2 spring and nearby control area.

Table S1 Mean, standard deviation and coefficient of variation of all leaf traits in this study (n = 7–8)

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