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Ann. For. Sci.
Volume 66, Number 5, July-August 2009
Article Number 505
Number of page(s) 8
Published online 09 July 2009

© INRA, EDP Sciences, 2009


Trees are commonly well adapted to local conditions, having evolved ecophysiological characteristics (Chabot and Hicks, 1982; Kikuzawa, 1989; Reich et al., 1992), especially in mountain areas where selection pressure is very important. The main geophysical drivers along altitudinal gradients from an ecological point of view are temperature, air pressure, precipitation and radiation (Körner, 2008). Indeed, morphological, phenological and physiological changes allow trees to maintain a relatively high level of growth-related activity despite increasingly constraining environmental conditions towards high elevation (Cordell et al., 1999). The main physiological traits that control the carbon uptake and water loss in plants and generally vary according to elevation are photosynthesis and stomatal conductance.

To our knowledge, about twenty studies have dealt with photosynthetic capacity along altitudinal gradients (Körner, 2003). However, variations in plant performance with altitude are difficult to predict, partly because of the complexity of the geophysical effects of altitude and partly because of bio- logical responses to these changes. Indeed, maximum rates of CO2 assimilation in plants from different elevations, measured at ambient CO2 partial pressure, have been found to be equal (Benecke et al., 1981; Cordell et al., 1999; Körner and Diemer, 1987), lower (Kao and Chang, 2001; Slatyer and Morrow, 1977; Zhang et al., 2005), or higher at high elevation (Premoli and Brewer, 2007).

When comparing along an altitudinal gradient, the distinction between pressure and concentration of gases becomes crucial. Unfortunately, many studies have used CO2 molar fractions instead of CO2 partial pressure to express CO2 availability, neglecting the fact that partial pressure decreases dramatically with elevation while molar fraction remains stable. As is the case for respiration in animals (Zhang et al., 2007), reduced partial pressure has a significant impact on gas exchange by plants; CO2 assimilation closely depends on CO2 partial pressure (PCO2) and not CO2 molar fraction (Farquhar et al., 1980). The decline in PCO2 with elevation has led various authors to contend that the lack of CO2 may be an important factor in the reduction of photosynthesis at high elevations (Decker, 1947; Tranquillini, 1964). However, more recent modelling studies suggested that air pressure effects on photosynthesis are smaller than predicted based on the decline in ambient PCO2 alone (Gale, 1972; Terashima et al., 1995). They concluded (i) that low pressure has only a small effect on the availability of CO2 for plants photosynthesis, and (ii) that when suppression of photosynthesis in alpine plants occurs it can mostly be attributed to limited CO2 diffusion or low temperatures rather than to lowered PCO2 itself.

In order to compare photosynthetic capacity of populations at various elevations, all microclimatic determinants must be kept constant (temperature, humidity, light and CO2 partial pressure). While many experiments have been carried out at constant temperature and saturating light, few studies have yet compared photosynthetic capacity of low- and high-elevation plants at uniform CO2 partial pressure. Rather, for gas exchange measurements, researchers tended to impose a constant molar fraction of CO2 in the cuvette (Rada et al., 1998; Zhang et al., 2005), and therefore compared CO2 assimilation at different CO2 partial pressures. For example, if the molar fraction of CO2 in air is 375 ppm (equal to 375 μmol mol −1) and the temperature 20 °C, then the partial pressure (PCO2) is 38 Pa (380 μbar) at sea level, but only 32 Pa at 600 m and 27 Pa at 3000 m of elevation. Consequently, these studies have measured photosynthetic capacity under local conditions but did not compare populations in the same air pressure conditions across different elevations. Although such results are useful for studying leaf performance in ambient conditions (instantaneous assimilation) and for quantifying the carbon balance, they do not allow assessment of plant adaptation or acclimation (photosynthetic capacity).

In the present study, we focus on the importance of CO2 partial pressure when studying plant adaptation/acclimation at different elevations. We compare maximum assimilation rates of two temperate tree species growing naturally along an altitudinal gradient (100 to 1600 m) in the Pyrénées Mountains. Gas exchange measurements were performed at each elevation and at two different CO2 partial pressure treatments: (i) at ambient CO2 partial pressure (PCO2 − A), as is generally employed and (ii) at constant-low-elevation PCO2 (PCO2 −C) . Therefore, we were able to quantify the effect of decreasing CO2 partial pressure on photosynthetic capacity (Amax) for two common European tree species (Fagus sylvatica L. and Quercus petraea (Matt.) Liebl.). Three main questions are addressed here: (i) how does maximum assimilation rate vary with increasing elevation? (ii) do maximum assimilation rate and partial pressure vary to the same extent with increasing elevation? and (iii) do measurements made at ambient and constant PCO2 lead to similar results when examining plant adaptation or acclimation?


2.1. Altitudinal gradient and microclimate

The altitudinal study was conducted in the Gavarnie’s valley on the west side of the Pyrénées Mountains in France (from 42° 53 ’N, 0° 25’ W to 43° 45 ’N, 0° 14’ W). This region is characterized by an oceanic mountain climate, with a mean annual temperature of 12 °C and precipitation of 1079 mm (1946–2001) at low elevation (Tarbes, 43° 11’ N 0° .00’ W, 360 m ASL, Météo France). We selected two common European tree species (Fagus sylvatica L. and Quercus petraea (Matt.) Liebl.) along a 1500 m altitudinal gradient. For each species, natural established populations were sampled at six elevations: 100 m, 400 m, 600 m, 800 m, 1200 m and 1600 m ASL (± 50 m).

Table I

Altitudinal variations in summer air temperature (Tas), air pressure (Patm), ambient CO2 partial pressure (PCO2 − A at 375 ppm of molar fraction), and molar fraction (xCO2 − C) imposed to obtain PCO2 −C for each species.

For each population, we used a GPS receiver (GPS Pathfinder ProXR, Trimble Navigation, Sunnyvale, USA) to determine the exact elevation of each site (Tab. I). Air temperature was measured using data loggers (HOBO Pro RH/Temp, Onset Computer Corporation, Bourne, USA) located in each population along the altitudinal gradients. Sensors were mounted 1.5 m above the ground on poles located in clearings near the studied populations, and protected by white plastic shelters to prevent exposure to rain and direct sunlight. All sensors were inter-calibrated in the laboratory before installation. Data were recorded hourly from January 1st 2006 to December 3 1st 2007 and mean summer air temperatures (Tas) were calculated as the mean daily temperature between May 1st and August 3 1st 2006 (Tab. I). The altitudinal gradient used here provided mean annual temperature ranges of 6.5 and 5.6 °C for beech and oak, respectively (Tab. I). The average rate of decrease in temperature with increasing elevation (lapse rate) was 0.42 °C per 100 m (Vitasse et al. 2008). Analysis of monthly precipitation data in 2005–2007 indicated no water stress along the altitudinal gradient. Indeed, average values (2005–2007) ranged from 957 to 1376 mm of water per year between low and high elevations. Variations in air pressure (Patm in Pa) according to elevation were estimated according to Jones (1983):

where z is elevation above sea level (m) and Tas is summer air temperature (K). Values of Patm decreased with increasing elevation by about 10.9 hPa 100 m−1, ranging from 997.9 to 836.9 hPa (16.1% lower at the highest elevation sites; Tab. I). These values were used to calculate the CO2 partial pressure based on the molar fraction reported in situ by the gas analyser. According to the ideal gas law, the fractional abundance of gas expressed in dimensionless percentage or ppm reflects equivalently a molar fraction (μmol mol −1), a volumetric fraction (μL L −1) or a fractional pressure (μbar bar −1). Such a measure of CO2 has no physical dependence on elevation, and infrared gas analyzers (IRGAs) generally allow researchers to fix this value within cuvettes. By contrast, partial gas pressure depends directly on other state variables (temperature and density), with strong altitudinal variation in the atmosphere.

2.2. Gas exchange measurements

Measurements were carried out using a portable steady-state, flow-through chamber (PLC6) connected to an IRGA (CIRAS-2, PP Systems, Hitchin, UK) equipped with temperature, humidity, light and CO2 control modules. The IRGA measures CO2 density (ρCO2) as a function of infrared absorption via the Beer-Bouguer-Lambert law, in an optical chamber where data on temperature and pressure allow calculation of the molar fraction (XCO2). Since XCO2 is unaffected during the passage from the cuvette to the optical chamber (i.e., is conserved when humidity is maintained constant as in the cuvette; Kowalski and Serrano-Ortiz, 2007), the system effectively determines the cuvette’s XCO2, whose changes are due exclusively to leaf CO2 exchange. In addition, this analyser (CIRAS-2 PP System) automatically corrects measurements for water vapour and changes in air pressure. Before measurement campaigns, the analyser was calibrated in the laboratory using 400 ppm standard gas. Full CO2 and H2O zero and differential calibration have been performed in the field at every setting change, or after a set of four measurements.

Table II

Comparison of mean values of maximum assimilation rate (Amax) and maximum stomatal conductance (gsmax) between CO2 partial pressure treatments for each elevation and species. Na is the leaf nitrogen content. Values in parenthesis correspond to the standard error and n is the number of replicates per population. Differences between treatments were performed using a paired t-test: ns, non-significant differences between PCO2 treatments.

We sampled adult individuals of comparable height on a North-facing slope for beech and South-facing slope for sessile oak. Five to nineteen mature individuals were randomly selected per population to monitor leaf gas exchange. Measurements were always done in the field between 8:00 and 11:00 solar time on fully expanded leaves during two consecutive weeks in August 2007. Measurements were carried out on two leaves per tree immediately after cutting the branch using a pole tree pruner between 5 and 7 m height in the crown. As defined by Larcher (1969), maximum assimilation rate and stomatal conductance (Amax and gsmax, respectively) were measured under optimum temperature and relative humidity, saturated light and non-saturated CO2 partial pressure. To compare maximum rates of assimilation at light saturation (Amax) between populations, all gas exchange measurements were made at equal temperature (20.0 °C ± 1.5), VPD (1200 Pa ± 250) and saturating light (1500 μmol m−2 s−1 of light in the leaf chamber, determined by a light response curve made on five individual per species). At each elevation, measurements were performed at two CO2 partial pressures (treatments A and C), by imposing different CO2 molar fractions in the chamber: (A) measurements at ambient CO2 partial pressure (PCO2 − A ; Tab. I) were done using a constant CO2 molar fraction (XCO2 = 375 ppm) in the leaf chamber along the gradient; (C) measurements at constant-low-elevation CO2 partial pressure (PCO2 −C = 37.5 Pa) along the altitudinal gradient were done by adjusting CO2 molar fractions (xCO2 − C ; Tab. I) at each elevation. We calculated CO2 partial pressure as: Pi = Xi × Patm × 106 where Pi is the partial pressure of gas i, Xi the molar fraction (in ppm) and Patm the air pressure. Maximum assimilation rates were performed for both treatments (ambient and constant-low-elevation PCO2) on the same leaf and data were recorded when steady state of assimilation was reached (within ten minutes). For each tree, measurements were randomly conducted between treatments. In the laboratory, leaf samples were dried at 70 °C, mineralised with hot sulphuric acid and assayed colorimetrically for concentrations of nitrogen and phosphorus using the Technicon auto-analyser.

2.3. Data analysis

In order to compare the two treatments (ambient and constant-low-elevation PCO2), the relative differences in Amax (DAmax, %) and PCO2 (DPCO2, %) were calculated as follows:

where Amax − C (μmol m−2 s−1) is the maximal rate of assimilation measured at constant-low-elevation PCO2, Amax − A is the maximal rate of assimilation measured at ambient PCO2, PCO2 −C is the constant-low-elevation partial pressure of CO2 (37.5 Pa) and PCO2 − A (Pa) is the ambient partial pressure of CO2 along the elevational gradient.

Within each population (at each elevation), we used a paired t-test to characterize the effects of PCO2 treatments on ecophysiological variables (Amax and gsmax). Then, to determine whether variations in photosynthetic capacity, stomatal conductance and foliar nitrogen content were related to elevation, the data were analysed by linear regression (for each PCO2 treatment and species). In addition, to compare Amax and gsmax between elevations, analysis of variances (ANOVA) with the Tukey test at P < 0.05 was used for each species. All analyses were performed using the SAS software package (SAS 9.1, SAS Institute Inc., Cary, NC).


Overall, values of Amax ranged from 8.8 to 12.7 and from 9.1 to 14.2 μmol m−2 s−1 for beech and oak, respectively (Tab. II). Oak exhibited higher values of Amax than beech independent of elevation; mean values for the whole experiment were about 11.5 and 9.6 μmol m−2 s−1 for oak and beech, respectively. Values of maximum stomatal conductance (gsmax) were less variable for beech (115 to 184 mmol m−2 s−1) than for oak (88 to 366 mmol m−2 s−1) (Tab. II).

At ambient CO2 partial pressure, Amax values did not vary with elevation for either species (Tab. III), whereas Amax values measured at constant-low-elevation PCO2 significantly increased with increasing elevation for both species. Indeed, for both species, Amax values at the highest elevation were about 4 μmol m−2 s−1 higher than those at the lowest elevation (Tab. II). The increase in Amax with elevation was gradual for beech and more variable for oak (values at 1200 m were lower than those at 800 m). Whatever the treatment, we observed a slight but non-significant increase in gsmax for beech whereas no altitudinal trend was found for oak (Tab. III). However, values of gsmax were significantly higher at high elevation sites (1600 m) compared to lower elevations (ANOVA, P < 0.0001) for both species. Leaf nitrogen content significantly increased with increasing elevation for beech but this trend was not significant for oak, despite the higher values observed at high elevations (Tabs. II and III).

Table III

Statistical coefficients of linear regression for Amax, gsmax and Na versus elevation for each partial pressure treatments and for both species.

We found no difference in Amax values between PCO2 treatments at low elevation whereas significant differences were observed at high elevations (paired t -test, Tab. II). Values of ΔAmax were significantly different of 0 only above 600 m and 800 m for oak and beech, respectively. These differences became more marked with increasing elevation (Fig. 1), reaching high values at the highest elevation, about 2.3 and 3.2 μmol m−2 s−1 for oak and beech, respectively. Table II shows that there was no difference between gsmax values measured at ambient versus constant PCO2 for either species, except for the oak population at 1600 m where gsmax values at ambient PCO2 were higher than those at constant-low-elevation PCO2 . The CO2 partial pressure has no effect on stomatal conductance; therefore the observed differences result from non stomatal effects.

thumbnail Figure 1

Differences in maximum assimilation rates (ΔAmax μmol m−2 s−1) between CO2 partial pressure treatments (ΔAmax = Amax − CAmax − A) in relation to elevation (m) for both species. Amax − C : maximal rate of assimilation measured at constant- low-elevation PCO2 (37.5 Pa); Amax − A : maximal rate of assimilation measured at ambient PCO2 . Values correspond of the mean of 5 to 19 individuals per site ± standard errors

Relative differences in Amax (DAmax) reached 25% for both species (Fig. 2). However, for oak, DAmax was lower at 1600 m than 1200 m, due to the very high Amax values measured at the highest elevation. Meanwhile, the highest relative differences in PCO2 (DPCO2) were less than 16% at the highest elevation. Figure 2 shows the steeper increase in CO2 assimilation rate with elevation than that of CO2 partial pressure, since a given increase in DPCO2 resulted in a larger increase in DAmax .

thumbnail Figure 2

Relative differences in Amax (DAmax) versus relative differences in PCO2 (DPCO2) in percentage (%). Dashed line represents the 1:1 relationship.


This study shows that the maximum assimilation rate (Amax) increases significantly with increasing elevation, about 2.8 and 2.6 μmol m−2 s−1 per 1000 m of elevation for beech and oak, respectively when measurements were done at constant-low-elevation PCO2 . By contrast, at ambient PCO2 no significant trend was found in Amax according to elevation. Along the altitudinal transect, we found that values of Amax measured at ambient PCO2 were significantly lower than those measured at constant-low-elevation PCO2 above 600 m of elevation: these between-treatment differences increase as elevation increases. We found that gas exchange measurements realised along altitudinal gradient at ambient or constant PCO2 lead to different results in terms of photosynthetic capacity and therefore to different conclusions regarding plant adaptation or acclimation.

In the literature, most studies that have examined photosynthetic capacity (Amax) over altitudinal gradients have kept temperature, humidity and light level constant in order to compare populations, but either (i) did not mention how they managed the CO2 variable (Cordell et al., 1998; Rundel et al., 2003), or (ii) used constant CO2 molar fraction (ppm or μmol mol −1 or μbar bar −1) instead of constant partial pressure (Gonzalez-Real and Baille, 2000; Yin et al., 2004). These studies found results similar to those of Treatment A in our study: no significant variations of Amax along the gradient (Cordell et al., 1999; Körner and Diemer, 1987; Kumar et al., 2006). However, a few studies have showed either slight increases in Amax with increasing elevation (Friend et al., 1989; Premoli and Brewer 2007) or a decrease (Kao and Chang, 2001; Zhang et al., 2005). Only a few studies have used CO2 partial pressure when comparing population adaptation for photosynthesis at different elevations (Friend et al., 1989), but they carried out measurements at ambient PCO2 . To our knowledge, only one study estimated photosynthetic capacity of low- and high-elevation plants applying constant cuvette CO2 partial pressure (Körner and Diemer, 1987). They also found an increase in Amax over a gradient of 2000 m of elevation; values were 20% higher for high elevation versus low elevation plants, using a constant CO2 partial pressure of 25.1 Pa. In other words, they found that photosynthesis varied to the same extent as the variation in PCO2 : a 22.5% shift in Amax for 20.8% variations in PCO2 along their gradient. In our study, we found an even higher shift in Amax (25%) compared to that of PCO2 (16%) for both species.

For beech, the higher values of leaf nitrogen content observed for high-elevation populations partially explained their greater photosynthetic capacity. For oak, we only found a slight but non-significant increase in leaf nitrogen content with increasing elevation. Altitudinal increase in leaf nitrogen content has already been observed for other species (Cordell et al., 1998; Premoli and Brewer, 2007). Photosynthetic capacity tends to be positively related to higher values of foliar nitrogen and phosphorus due to increased levels of Rubisco and other N-containing constituents of the photosynthetic apparatus (Delzon et al., 2005; Field and Mooney, 1986; Marron et al., 2008). Moreover, only for beech, our results also suggest that at least part of the increase in maximum assimilation rate at high elevation may be attributed to a slight increase in stomatal conductance, implying an increase in CO2 diffusion into the leaf. Stomatal density of beech was greater in high elevation populations (data not shown), as were gs and Amax . The relationship between stomatal conductance (or stomatal density) and elevation is not as clear cut, with various authors reporting increases (Körner and Cochrane, 1986; Körner et al., 1986; Premoli and Brewer, 2007), decreases (Körner et al., 1989) or no clear trend with elevation (Cordell et al., 1998), depending of species.

The increase in photosynthetic capacity with increasing elevation suggested that trees accomplish a relatively high level of photosynthesis to compensate for extreme environmental conditions and short growing seasons at high elevation. This ability to cope with varying environment is likely be achieved by genetic adaptation or by acclimation. In order to discern adaptation and acclimation in the future, we have set up a lowland common garden with the same populations for both species. For other species, previous studies have showed that in a common environment, photosynthetic capacity of plants from high elevation remained higher than those of lowland plants (Hovenden and Brodribb, 2000; Oleksyn et al., 1998). Premoli and Brewer (2007) showed that assimilation rates were 40% higher for high-elevation plants in the field (measurements done at ambient PCO2), and 18% higher in the common garden, than those for low-elevation plants. Therefore, photosynthetic capacity seems to be under strong selective pressures typically observed at high elevation. Genetic adaptation to high elevation conditions could be a result of maintaining of higher leaf nitrogen, chlorophyll content (Oleksyn et al., 1998), stomatal density (Kouwenberg et al., 2007) and carboxylation efficiency (Körner and Diemer, 1987), and would allow trees to adapt to their local conditions.

The low partial pressure of CO2 prevailing at high elevations has been hypothesized to be responsible for the reduced photosynthesis (Decker, 1947; Tranquillini, 1964). However, this is in contradiction to some theoretical studies (Gale, 1972; Terashima et al., 1995). Indeed, Gale (1972) demonstrated using a simple diffusion model that low pressure has a small effect on photosynthesis for plants with efficient CO2 -uptake mechanisms. The effect of a reduction in PCO2 could indeed be counterbalanced by an increase in the diffusion coefficient with decreasing air pressure (Terashima et al., 1995). Nevertheless, this compensating effect is only observed in plants with low values of mesophyll resistance (Gale, 1972), which correspond to C4 and not to C3 type plants as in our study. In addition, Terashima et al. (1995) only found no effect of partial pressure on photosynthesis at low temperature; this effect reached 23% at higher leaf temperatures (35 °C) for an elevation of 3000 m. Whereas this last study suggested that changes in the photosynthetic capacity of alpine plants can be attributed mostly to low temperature, we suggest that low CO2 partial pressure at high elevation could also play a role in plant adaptation. Indeed, the decrease in CO2 partial pressure is expected to increase stomatal density and stomatal conductance (Kouwenberg et al., 2007; Woodward and Bazzaz, 1988) and therefore maximum assimilation rate.

In our study, we were not able to take the decrease in partial pressure of oxygen (O2) into account with a decrease in air pressure. Rubisco catalyzes both the carboxylation of RuBP and its oxygenation. The ratio of carboxylation to the oxygenation reaction (initiating photorespiration) strongly depends on the relative concentrations of CO2 and O2, and on leaf temperature (Lambers et al., 1998). Because of competition between CO2 and O2 for Rubisco, the decreased partial pressure of O2 at high elevations combined with the constant CO2 partial pressure treatment likely reduces photorespiration, and could partly explain the large increase in Amax observed with elevation here (Cornic, 1980; Sun, 1999; Ramonell, 2001).

Our study demonstrates the importance of using constant CO2 partial pressure to assess plant adaptation/acclimation at different elevations; i.e. to accurately quantify photosynthetic capacity. Measurements done at ambient and constant PCO2 lead to different results, with different patterns according to elevation. Had we conducted experiments only at ambient CO2 partial pressure, we might have concluded that high-elevation populations did not evolve to be more efficient, and therefore that adaptation/acclimation does not occur along altitudinal gradient. In this case (ambient CO2 partial pressure), a finding that photosynthetic capacity stays constant with increasing elevation suggests the conclusion that high elevation populations did adapt to constraining environmental conditions. However, it is worth knowing that a decrease in photosynthetic capacity at ambient PCO2 did not allow conclusions to be drawn regarding plant adaptation as the effect of decreasing CO2 partial pressure cannot be removed. Therefore, to assess plant adaptation or acclimation to elevation, we recommend carrying out gas exchange measurements at constant partial pressure.


We wish to thank staff of the Experimental Unit of Pierroton for field assistance, Catherine Lambrot for leaf nutrient content analysis, Jean-Marc Louvet for his enthusiasm and information about the Pyrénées forests, and Christian Körner for insightful comments on early drafts of the manuscript. This research was supported by a grant from the Aquitaine and Midi-pyrénées Régions and a bilateral collaboration funded in coordination between the French government PHC PICASSO programme 19187UC, and an Acción Integrada HF2008-0057 from the Spanish Research Ministry. Caroline Bresson was supported by an ONF-Region Aquitaine Doctoral Fellowship.


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All Tables

Table I

Altitudinal variations in summer air temperature (Tas), air pressure (Patm), ambient CO2 partial pressure (PCO2 − A at 375 ppm of molar fraction), and molar fraction (xCO2 − C) imposed to obtain PCO2 −C for each species.

Table II

Comparison of mean values of maximum assimilation rate (Amax) and maximum stomatal conductance (gsmax) between CO2 partial pressure treatments for each elevation and species. Na is the leaf nitrogen content. Values in parenthesis correspond to the standard error and n is the number of replicates per population. Differences between treatments were performed using a paired t-test: ns, non-significant differences between PCO2 treatments.

Table III

Statistical coefficients of linear regression for Amax, gsmax and Na versus elevation for each partial pressure treatments and for both species.

All Figures

thumbnail Figure 1

Differences in maximum assimilation rates (ΔAmax μmol m−2 s−1) between CO2 partial pressure treatments (ΔAmax = Amax − CAmax − A) in relation to elevation (m) for both species. Amax − C : maximal rate of assimilation measured at constant- low-elevation PCO2 (37.5 Pa); Amax − A : maximal rate of assimilation measured at ambient PCO2 . Values correspond of the mean of 5 to 19 individuals per site ± standard errors

In the text
thumbnail Figure 2

Relative differences in Amax (DAmax) versus relative differences in PCO2 (DPCO2) in percentage (%). Dashed line represents the 1:1 relationship.

In the text